characterizing binding affinity of somatropin...

FACULTY OF PHARMACEUTICAL SCIENCES

Department of Pharmaceutical Analysis

Drug Quality and Registration

Academic Year 2012-2013

CHARACTERIZING BINDING AFFINITY OF SOMATROPIN AND DERIVED STRUCTURES

TO HGHAB BY SURFACE ACOUSTIC WAVES AND SIZE EXCLUSION

CHROMATOGRAPHY

Apr. Evelyn Buyst

Master of Industrial Pharmacy

Promotor

Prof. dr. Apr. Bart De Spiegeleer

Mentor

Nathalie Bracke

Board of commissioners

Prof. Erwin Adams

Prof. Roger Kemel

Prof. Ann Van Schepdael

Prof. Sandra Apers

Prof. Ann Van Eeckhaut

Prof. Yvette Michotte

COPYRIGHT

"The author and the promoters give the authorization to consult and to copy parts of this

thesis for personal use only. Any other use is limited by the laws of copyright, especially

concerning the obligation to refer to the source whenever results from this thesis are cited."

April 22, 2013

Appreciations

First of all,

I would like to enounce my appreciations towards Prof. dr. Apr. Bart De Spiegeleer.

He gave me the opportunity to work in the DruQuaR laboratory. He arranged an internship at

the very last moment, offered me a very interesting and defiant topic to work on, and he was

always available for questions and his professional and expansive view on many things.

Secondly, I want to thank tremendously my mentor, Nathalie Bracke,

who was always and at every time available for questions and good advice.

It was really a pleasure to work with her.

Another word of thanks is for all other colleagues in the laboratory for their daily help and

the positive atmosphere they created to work in.

Thanks to all other students for the good company

and pleasant leisure time during this last year.

Last but not least,

I thank my parents and my family for all the opportunities

they gave me, their never ending support and encouraging words.

TABLE OF CONTENTS

1. INTRODUCTION ....................................................................................................... 1

1.1. BIOLOGICAL FUNCTION OF HUMAN GROWTH HORMONE AND ITS ROL

IN CANCER .............................................................................................................. 1

1.1.1. Neuro-endocrine tumors ....................................................................... 1

1.1.2. Growth hormone ................................................................................... 2

1.2. PROTEIN AND PEPTIDE THERAPEUTICS .................................................................. 3

1.2.1. Protein scaffolds .................................................................................... 3

1.2.2. Peptide therapeutics .............................................................................. 4

1.3. BIOSENSORS IN DRUG DEVELOPMENT .................................................................. 5

1.3.1. What are biosensors? ............................................................................. 5

1.3.2. Surface acoustic waves biosensors ......................................................... 6

1.3.3. Sensorgram of surface acoustic wave biosensors .................................... 7

1.3.4. Other tools for the characterization of binding events ........................... 8

1.3.4.1. Surface plasmon resonance............................................................. 8

1.3.4.2. Quarz crystal microbalance ............................................................ 8

1.3.4.3. Isothermal titration calorimetry ..................................................... 9

1.3.5. Comparison of biosensors and other techniques .................................... 9

2. OBJECTIVES ............................................................................................................ 11

3. MATERIALS AND METHODS .................................................................................... 12

3.1. SENSOR CHIP .......................................................................................................... 12

3.1.1. Cleaning sensor chips ............................................................................. 12

3.1.1.1. Pre-cleaning .................................................................................... 12

3.1.1.2. Chemical etching with AMP ............................................................ 12

3.1.2. Coating sensor chip with dextran ........................................................... 12

3.2. LIGAND IMMOBILIZATION ...................................................................................... 13

3.3. SAM5 BINDING EXPERIMENTS ............................................................................... 14

3.3.1. Screening for a regeneration condition .................................................. 14

3.3.2. Analytes (modified) somatropin ............................................................ 14

3.3.2.1. Binding experiment between hGHAb and (modified) somatropin with

regeneration ................................................................................... 14

3.3.3. Somatropin derived peptides ................................................................. 15

3.3.3.1. QC analysis of somatropin derived peptides ................................... 15

3.3.3.2. Binding experiments with somatropin derived peptides ............... 15

3.3.4. Data processing of SAW binding experiments for (modified) somatropin and

peptides ................................................................................................ 16

3.4. SIZE EXCLUSION CHROMATOGRAPHY .................................................................... 18

4. RESULTS AND DISCISSION ....................................................................................... 19

4.1. LIGAND IMMOBILIZATION ...................................................................................... 19

4.2. SOMATROPIN ......................................................................................................... 21

4.2.1. Screening for regeneration conditions ................................................... 21

4.2.2. SAM5 binding experiments .................................................................... 22

4.2.2.1. Binding experiment between hGHAb and somatropin .................. 22

4.2.3. SEC experiments .................................................................................... 24

4.2.3.1. Calibration curve of the SEC column .............................................. 24

4.2.3.2. SEC analysis of hGHAb .................................................................... 25

4.2.3.3. SEC analysis of somatropin ............................................................. 25

4.2.3.4. SEC analysis of mixtures of hGHAb and somatropin ...................... 27

4.3. MODIFIED SOMATROPIN ........................................................................................ 30

4.3.1. 1:1 NOTA-somatropin ............................................................................ 30

4.3.1.1. SAM5 binding experiment with regeneration ................................ 30

4.3.1.2. SEC experiments ............................................................................. 31

4.3.1.2.1. SEC analysis of 1:1 NOTA-somatropin ............................ 31

4.3.1.2.2. SEC analysis of mixtures of hGHAb and

1:1 NOTA-somatropin ..................................................... 32

4.3.2. 1:3 NOTA-somatropin ............................................................................ 33

4.3.2.1. SAM5 binding experiment with regeneration ................................ 33

4.3.2.2. SEC experiments ............................................................................. 34

4.3.2.2.1. SEC analysis of 1:3 NOTA-somatropin ............................ 34


1:3 NOTA-somatropin ..................................................... 35

4.3.3. 1:10 NOTA-somatropin .......................................................................... 36

4.3.3.1. SAM5 binding experiments ............................................................. 36

4.3.3.1.1. Binding experiment with regeneration ........................... 36

4.3.3.1.2. Duplication of binding experiment with regeneration ... 37

4.3.3.2. SEC experiments .............................................................................. 38

4.3.3.2.1. SEC analysis of 1:10 NOTA-somatropin .......................... 38


1:10 NOTA-somatropin ................................................... 39

4.3.4. Comparison of the modified somatropin structures ............................... 41

4.4. SOMATROPIN DERIVED PEPTIDES .......................................................................... 45

4.4.1. Choise of peptides ................................................................................. 45

4.4.2. QC analysis somatropin derived peptides .............................................. 45

4.4.3. SAM5 binding experiments .................................................................... 46

4.4.3.1. Feasability calculations ................................................................... 46

4.4.3.2. Binding experiments ....................................................................... 47

4.4.4. SEC experiments .................................................................................... 50

4.4.4.1. SEC analysis of P0320 ...................................................................... 50

4.4.4.2. SEC analysis of mixtures of hGHAb and P0320 ............................... 52

5. CONCLUSION AND PERSPECTIVES ............................................................................ 53

6. REFERENCES ........................................................................................................... 54

SUMMARY

The global aim of the project was to develop a Surface Acoustic Wave (SAW) biosensor

technology into a functional quality characterization tool. In this work, we have used

somatropin or recombinant human growth hormone (GH) as analyte. The more specific

project goals are (i) the development of a method for selective immobilization of human GH

antibody (hGHAb), (ii) the development of robust operational conditions and (iii) the

quantitative binding characterization (affinity, on- and off-rates) of 1,4,7-triazacyclononane-

1,4,7-triacetic acid (NOTA) modified somatropin (equimolar (1:1) or 3 to 10 times molar

excess of NOTA (1:3 and 1:10) added to somatropin) and multiple somatropin derived

peptides. This quantitative binding was also investigated by SEC.

In the SAW binding experiments, the hGHAb ligand was immobilized via the amine coupling

chemistry. When the ligand has multiple copies of the functional group (-NH2) that mediates

immobilization, proteins are coupled heterogeneously and sometimes at multiple sites. This

random immobilization therefore influences the accessibility and/or activity of the ligand,

and hence, the binding signal upon analyte binding. One of the most important finding was

the overall variability of the binding results (within-measurement variability as well as

between-measurement variability), which indicate a lack of reproducibility. Therefore

attention must be paid to the quality of the operations, of materials and of the chip. The

binding affinity of the multiple modified somatropin forms are at least similar than

unmodified somatropin. The experiments with somatropin derived peptides have to be

interpreted even more carefully, because of the presence of impurities in almost all peptide

samples, which can have a major influence on the affinity. Our pilot data indicate a possible

interaction between two of the peptides and the hGHAb. The observed binding in the SAW

experiments was confirmed with size exclusion chromatography (SEC). Binding was observed

with somatropin and 1:1 NOTA-somatropine, but not for the 1:3 and 1:10 NOTA-derivates.

As a final conclusion, we can state that the SAW biosensor is a very promising instrument to

be involved in different stages of the drug discovery process, but further improvements,

especially in robustness, are absolutely necessary.

SAMENVATTING

Het algemene doel van dit project was een Surface Acoustic Wave (SAW) biosensor

technologie te ontwikkelen als een functioneel instrument voor kwalitatieve karakterisatie.

In dit werk werd gebruikt gemaakt van somatropine of recombinant groeihormoon (GH) als

analiet. De meer specifieke doelen zijn (i) de ontwikkeling van een methode voor selectieve

immobilisatie van humaan GH antilichaam (hGHAb), (ii) de ontwikkeling van robuuste

operationele condities en (iii) de kwantitatieve bindingskarakterisatie (affiniteit, on- en off-

rates) van 1,4,7-triazacyclonaan-1,4,7 triazijnzuur (NOTA) gemodificeerd somatropine

(equimolair (1:1) of 3 tot 10 keer molaire overmaat van NOTA (1:3 en 1:10) toegevoegd aan

somatropine) en meerdere somatropine afgeleide peptiden. Deze kwantitatieve binding

werd ook onderzocht door gebruik te maken van size exclusion chromatografie (SEC).

In de SAW bindingsexperimenten werd de hGHAb ligand geïmmobiliseerd via

aminekoppeling. Wanneer de ligand meerdere functionele groepen (-NH2) heeft die

beschikbaar zijn voor immobilisatie, werden proteïnen heterogeen gekoppeld en soms via

meerdere groepen gekoppeld. Deze random immobilisatie beïnvloedt de beschikbaarheid

en/of de activiteit van de ligand, en bijgevolg ook het bindingssignaal. Een van de

belangrijkste bevindingen is de algemene variabiliteit van de bindingsresultaten (zowel

variabiliteit tussen metingen als binnen metingen), wat wijst op een gebrek aan

reproduceerbaarheid. Daarom moet er aandacht worden besteed aan de kwaliteit van het

experiment, de gebruikte materialen en de chip. De bindingsaffiniteiten van de meerdere

vormen gemodificeerd somatropine zijn gelijkend aan het niet-gemodificeerde somatropine.

De experimenten met de somatropine afgeleide peptiden moeten echter worden

geïnterpreteerd met enige voorzichtigheid, aangezien de aanwezigheid van onzuiverheden

in bijna alle peptide stalen een invloed kunnen hebben op de affiniteit. De data van piloot

experimenten geven een mogelijke interactie van twee van de peptiden met hGHAb aan. De

waargenomen binding in de SAW experimenten werd bevestigd met SEC. Binding werd

waargenomen met somatropine en 1:1 NOTA-somatropine, maar niet met de 1:3 en 1:10

NOTA afgeleide structuren.

Finaal kunnen we besluiten dat de SAW biosensor een veelbelovende techniek is die kan

gebruikt worden in meerdere stadia bij het ontwikkelen van geneesmiddelen, maar verdere

vooruitgang, inzake robuustheid van de techniek, is absoluut nodig.

LIST OF ABBREVIATIONS

5-HIAA 5-hydroxyindoleacetic acid

ACN Acetonitrile

AMP Ammonia-peroxide-mixture

CE Capillary electrophoresis

Cgs Chromogranins

CT Computed tomography

DAD Diode array detector

DMSO Dimethylsulfoxide

DruQuaR Drug Quality and Registration

DSA Digital substraction angiography

DTE Dithioerythritol

EDC 1-ethyl-3-(3-dimethylaminopropyl)-carbodiimide

ELISA Enzyme-linked immunosorbent assay

EMA European Medicines Agency

FDA Food and Drug Administration

GH Growth hormone

GHBp Growth hormone binding protein

GHIH Growth hormone-inhibiting hormone

GHR Growth hormone receptor

GHRH Growth hormone-releasing hormone

GLP Good laboratory practice

GLP-1 Glucagon-like-peptide-1

GMP Good manufacturing practice

HBS HEPES buffered saline

HEPES 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid

hGHAb Human growth hormone antibody

hGHR Human growth hormone receptor

HILIC Hydrophilic interaction liquid chromatography

HPLC High performance liquid chromatography

IDT Interdigital transducer

ITC Isothermal titration calorimetry

IUPAC International Union of Pure and Applied Chemistry

JAK2 Janus kinase 2

KD Binding constant

koff Dissociation constant

kon Association constant

MRI Magnetic resonance imaging

NET Neuro-endocrine tumor

NHS N-Hydroxysuccinimide

NOTA 1, 4, 7-triazacyclononane-1,4,7-triacetic acid

PDA Photodiode array

PDEA 2-(2-pyridinyldithio)ethaneamine

PEG Polyethylene glycol

PET Positron emission tomography

QC Quality control

QCM Quarz cristal microbalance

RP Reversed phase

RU Resonance Unit

SAM Self assembled monolayer

SAW Surface acoustic waves

SDS Sodium dodecyl sulfate

SEC Size exclusion chromatography

SPECT Sigle-photon emission computed tomography

SPR Surface plasmon resonance

SSRS Somatostatin receptor scinctigraphy

TIR Total internal reflection

TSM Thickness shear mode

UPLC Ultra performance liquid chromatography

USA United States of America

1

1. INTRODUCTION

1.1. BIOLOGICAL FUNCTION OF HUMAN GROWTH HORMONE AND ITS ROLE IN CANCER

Cancer is a major health problem worldwide. It is a genetic disease, characterized by an

uncontrolled growth of cells, which sometimes is induced by bacteria and viruses or can be

heritable. However, it is caused most of the times by exposure to exogenous factors such as

carcinogens, radiation or hormones that initiate mutations of the DNA. Particularly,

mutations of oncogenes (including growth factors and their receptors, signal transducer

molecules and transcription factors), tumor suppressor genes and genes responsible for DNA

repair can lead to disturbed cell proliferation [1-2].

In 2008 approximately 12.7 million cancer cases and 7.6 million people died of cancer

worldwide [4]. Statistics in Belgium reported 59 996 new diagnoses of cancer in 2008,

whereof 54% were diagnosed in men (622 per 100 000 individuals) and 46% in females (505

per 100 000 individuals). Leading cancer sites are breast cancer (16%), prostate cancer

(15%), colorectal cancer (14%) and lung cancer (12%). They cover more than 56% of all newly

diagnosed tumors in Belgium [4].

1.1.1. Neuro-endocrine tumors

Neuro-endocrine tumors (NETs) are a rare but life-threatening type of tumors with an

incidence of 0.0053%. They arise from cells in the neuroendocrine system, composed of both

nervous and endocrine cells. These tumors are able to develop at any epithelial site in the

human body, but the main primary sites are the gastrointestinal tractus, with most occurring

places: ileum, appendix, rectum and the bronchopulmonary system [5-6]. The NETs can be

divided into two groups, the poorly differentiated and well differentiated tumors. The poorly

differentiated tumors are in general relative indolent and are characterized by small

resemblance to neuroendocrine cells, a more sheetlike or diffuse architecture, irregular

nuclei and less cytoplasmic granularity. The well-differentiated tumors have an aggressive

nature and show more or less uniform cells. They are responsible for the production of

abundant neurosecretory granules containing overexpressed neuroendocrine markers.

General tumor markers for both types are for example chromogranins (Cgs) and pancreatic

polypeptides. Specific markers produced by well-defined tumors are for example

2

neuropeptide K, supstance P and 5-hydroxyindoleacetic acid (5-HIAA), which is a metabolite

of serotonin. Tumormarkers can also be specific to the primary site as for example endocrine

pancreatic tumors produce for example gastrin, insulin, vasoactive intestinal polypeptide

and glucagon. Also, an expression of somatostatin receptors was observed in multiple NETs

[7-9].

Because clinical symptoms are lacking and the disease is characterized with slow growth and

progression, diagnosis comes most often too late. Diagnosis is based on detection of

biochemical markers, especially Cgs, 5-HIAA and the more specific biomarkers in blood and

urine. Visualisation of the tumors is performed by using computed tomography (CT),

magnetic resonance imaging (MRI), somatostatin receptor scintigraphy (SSRS) and digital

substraction angiography (DSA) [9-11]. The choice of treatment depends on the symptoms and

the stage of the disease. Surgical therapy is only an option for a small group, when

diagnosed in an early stage. Symptomatic treatment, by using somatostatin-analogues

(growth hormone inhibiting analogues) can provide a relief of clinical symptoms. Also

targeted radionuclide therapy becomes more and more important. Still, the available

treatments are limited and the need for new therapies is high [9-14].

1.1.2. Growth hormone

Growth hormone (GH) or somatropin is a heterogeneous peptide hormone consisting of

multiple isoforms. The gene cluster is located on chromosome 17q and includes 2 genes GH1

and GH2. The main product of the GH1 gene is GH expressed by the pituitary. It has a

sequence of 191 amino acids an is a 22 129 Da single chain protein containing two disulfide

bridges. Isoforms arise by differences in mRNA splicing, post-translational modifications and

metabolism [15].

GH is secreted by the pituitary and is controlled by the hypothalamus which produces the

stimulating growth hormone-releasing hormone (GHRH) and the growth hormone-inhibiting

hormone (GHIH) or somatostatin. The release of both hormones is controlled by a feedback

system [17]. One GH molecule binds two extracellular growth hormone receptor molecules

sequential (Figure 1) what results in the activation of Janus kinase 2 (JAK2), a GH receptor

associated tyrosine kinase, and influences the transcription of genes for a variety of proteins,

3

especially concerning cell metabolism, differentiation and proliferation. GH has major

importance in postnatal growth and plays a key role in metabolism, reproductive,

gastrointestinal, cardiovascular and renal systems [18].

Figure 1: Growth hormone receptor complex (PDB: 3HHR [16]

).

Binding site I colors blue and binding site II green.

Up till now, GH has been used several decades as a first-line therapeutic, mainly within

treatment of children with short stature, short stature-related diseases or growth hormone

deficiency. Recently, it is also administered to adults with growth hormone deficiency and

short bowel syndrome. Short-term use of this therapeutic is suggested to be safe; however,

immune responses can occur and a periodic overuse of GH can cause acromegaly. Long-term

effects and/or administering higher concentrations of GH, are correlated with significantly

increased (colorectal) cancer risks and Hodgkin’s disease [19-20]. Within multiple cancer cell

lines, e.g. prostate cancer and breast cancer, an overexpression of GH and its receptor was

observed [21-24]. GH can act as a lymphangiogenic factor, which is associated with lymphatic

vessel activation in pathological conditions, as well as in growth and metastasis [25].

Up till now, experimental evidence for the GH/GHR role in NETs is still lacking. However,

treatment of NETs with somatostatin (GHIH) analogues proved to be successful and inhibited

the function of NETs, what might indicate a potential role of the GH system in NETs [9-14,26].

1.2. PROTEIN AND PEPTIDE THERAPEUTICS

1.2.1. Protein scaffolds

R&D initiatives in targeting protein-protein interfaces are a relative recent venture in the

pharmaceutical sector. Since the commercialization of insulin in 1923 (FDA approved in

4

1939) as a protein therapeutic for the treatment of diabetis, protein therapeutics are

introduced in many categories of medically important applications [27].

Many advantages can be seen compared to small-molecule drugs, for example because of

the high affinity and highly specific interaction capacity, i.e. less adverse reactions are

observed. Because the human body produces many of the proteins that are therapeutically

used, good toleration and fewer occurrence of immune responses are observed. Also, the

clinical development and the regulatory approval by official agencies such as FDA is generally

faster than within conventional drugs. For treatment and diagnose of cancer, mostly

antibody derived structures are available e.g. rituximab and cetuximab. In 2008, more than

300 protein therapeutics were on the market and used for many applications and about 60

peptide drugs are currently available. In the near future, many data from clinical studies

using protein scaffolds are expected [27-30].

1.2.2. Peptide therapeutics

Peptides can be defined as polypeptide chains containing less than 50 amino acids and

having a molecular weight lower than 5 000 Da what can result in a highly developed

secondary structure, without tertiary structure. They have multiple advantages over proteins

including a higher affinity/specificity for targeting, and because of their limited seize, lower

toxicity profiles and a better tissue penetration can be observed. For some cases, a

disadvantage can be their short half-life because of rapid renal clearance and protease

degradation. Structural changes, including unnatural aminoacids and modifications, can be

introduced within peptides to improve the stability and the therapeutic potential.

Modifications with polyethylene glycol (PEG), which functions as a carrier for peptides, can

be used to improve the solubility in aqueous environments and is characterized by a low

immunogenicity. Research on peptide therapeutics has increased the latest years because of

their advantages compared to small molecules and because the technical production and

quality improvements. In 2010, about 60 peptide therapeutics were approved by the FDA as

for example Byetta, containing exenatide, a 39 amino acid peptide, which is an analogue of

the glucagon-like peptide-1 (GLP-1) and is used for the treatment of diabetis [31-33].

5

1.3. BIOSENSORS IN DRUG DEVELOPMENT

1.3.1. What are biosensors?

According the IUPAC, a biosensor is: “a self-contained integrated device which is capable of

providing specific quantitative or semi-quantitative analytical information using a biological

recognition element (biochemical receptor) which is in direct spatial contact with a

transducer element. A biosensor should be clearly distinguished from a bioanalytical system,

which requires additional processing steps such as reagent addition. Furthermore, a

biosensor should be distinguished from a bioprobe which is either disposable after one

measurement, i.e. single use, or unable to continuously monitor the analyte concentration”

[34]. An immunosensor is a specific form of a biosensor, including a recognition element

composed of antibodies. Most of these biosensors are based on the ELISA principle, whereby

the substrate is converted by enzymes into a detectable signal, for example a visible light

sensitive products [35-36]. Electrochemical immunosensors on the other hand have the

advantage they can be automated and have great potential for miniaturization. Because of

the high affinity and specificity for its antigens and the high diversity potential, this is a very

powerful tool [36].

One of the major aims of biosensors in R&D is the characterization of biomolecular

interactions. Specific, detailed, qualitative and quantitative information can be gathered on

the binding affinity and kinetics of an interaction. Also cell-based assays can be performed

with these instruments. A major advantage is that characterization can be performed in real-

time in a near-native state. The analysis has a high reproducibility, a high sensitivity and only

a minimum of sample is used. This explains why biosensors are effective workhorses used in

many stages of drug discovery research, like for example target identification, ligand fishing,

screening drugs that interfere with cell adhesion, hit selection and optimization or early

ADME and/or toxicological screens [37-38].

In addition, biosensors are promising techniques in quality control in GLP/GMP

environments. FDA and EMA directives require a validated binding assay as part of the

product-release portfolio for all therapeutic biological products. Traditional biological assays

for drug response, which use in vitro cell cultures or in vivo animal models, are expensive

6

and not always reliable. Provided that there are sufficient physicochemical data for drug

response (receptor binding does not always correlate with drug potency), binding assays

that use purified receptors or membrane fragments can form an alternative [74-75].

Biosensors have a lot of possible applications in many other fields like for example screening

for (veterinary) drug and/or toxic residues in the food industry [39-40], environmental

detection of pollutants [41], screening for specific targets in body fluids in forensic cases [42],

military screening for biological of chemical warfare agents [43] and describing disease

parameters by for example continuous glucose monitoring [44]. However, these applications

are still to be further developed.

1.3.2. Surface acoustic waves biosensors

Surface Acoustic Wave (SAW) biosensors are devices based on physical properties to detect

and quantify label-free interactions in real time. The popularity of this method has increased

enormously the latest years: between 1996 and 2006, publications using this technique

increased by a factor of 1.5-78 [45-51]. A setting is shown in Figure 2 [51-52].

Figure 2: Principle of a SAW biosensor. (a) A SAW biosensor is composed of a piezoelectric crystal or substrate, a sensitive layer and a guiding layer. A surface acoustic wave is generated by an input IDT, propagates in the z-direction and is detected by the output IDT. (b) Placing of a biosensor, whereby a

sealed flow cell is required [52].

A SAW biosensor is composed of a piezoelectric crystal, two interdigital transducers (IDTs), a

guiding layer and a sensitive layer containing a ligand, which can be modified in function of

7

the investigated analyte. An electric signal is converted by the input IDT into a polarized

transversal wave, which propagates through the substrate and is afterwards converted again

by the output IDT into an electrical signal, which can be detected. The propagation of the

wave is performed within the guiding layer and the wave energy is retained near the surface.

Responsible for this is the lower acoustic wave velocity in the guiding layer, what results in

being guided in only this layer and a minimization of loss into the bulk of the substrate or

into the liquid/gas that passes above the sensor surface. Thereby, the thickness of the

substrate doesn’t have influence on the detection capacities of the SAW sensors [51-54].

Investigation of the binding properties of an analyte to its ligand requires a sensor chip of

good quality. On this sensor chip, the ligand is immobilized and the passing analyte is able to

associate and dissociate with the immobilized ligand. The quality of the sensor chip and

therefore also its sensitivity, is related to the ligand immobilization, which has to be as

homogeneous and representative as possible. A gold sensor chip is mostly used because of

its potential to easily form strong bonds by multiple methods. In addition, gold is an inert

material and has the advantage of being resistant to corrosion due to aqueous buffer

solutions [53, 55-56].

Changes at the gold surface influence the oscillation behaviour of the surface acoustic

waves. A divergent phase is related to mass changes (i.e. acting as microbalance), while a

changed amplitude is related to viscoelastic and conformational changes [52-57]. Other

parameters such as electrical conductivity, liquid viscosity, liquid density pressure and

temperature can have influence on the waves as well [58].

1.3.3. Sensorgram of surface acoustic wave biosensors

A typical sensorgram of a binding process, where the analyte is interacting with an

immobilized ligand, is represented in Figure 3. While the analyte is injected, an exponential

curve can be noticed, which flattens when saturation of the surface is obtained. During the

post-injection phase, when only buffer has contact with the surface, the unbounded analyte

is washed away and bound analyte dissociates, which can be noticed by a descending curve.

When a regeneration step is performed, and the analyte is removed from the immobilized

ligand by specific conditions, the curve is brought back to the baseline [59-61].

8

Figure 3: SAW sensorgram [based on 60]

.

1.3.4. Other tools for the characterization of binding events

1.3.4.1. Surface plasmon resonance

The most frequent used biosensor technique of the latest years is the surface plasmon

resonance biosensor (SPR). This optical biosensor performs a non-destructive analysis that

uses plane-polarized light to investigate the interaction of molecules on the sensor chip. The

chip is constructed out of an inert metal coating and glass, where total internal reflection

(TIR) of polarized light can be observed. The surface plasmons are sensitive to fluctuations of

electron density at the interface of two materials. This means that when analyte and ligand

interact at the interface, the angle of reflected light is modified. The amount of bound

analyte, affinity to its ligand and interaction kinetics can be observed by optical signals [46, 49-

51, 62].

1.3.4.2. Quartz crystal microbalance

The quartz crystal microbalance (QCM) sensor, is based on the properties of piezoelectric

materials. These sensors work with acoustic waves which are generated in the whole

substrate, which are afterwards converted back into an electric signal and is applied for

detection [63-67]. The binding of molecules to the surface results in modified waves passing

the substrate. The mass and viscosity changes of this process are converted on the waves by

a proportional change in resonant frequency and a signal attenuation which can be detected

in real time [68].

9

1.3.4.3. Isothermal titration calorimetry

Isothermal titration calorimetry (ITC) is a technique giving information about binding

constants, reaction stoichiometry and the thermodynamic profile (enthalpy and entropy) of

an interaction [46, 69-73]. The system is composed out of two identical cells with equal

temperature at any time. When an analyte is added to the sample cell, which contains a

ligand solution, an enthalpic change is induced by interaction and a thermodynamic effect,

being an exothermic or endothermic reaction, can be observed. Respectively less or more

heat per time unit has to be produced to retain an equal temperature of the sample cell

compared to the reference cell. Registration of this dispensed heat and plotting against the

time or concentration of analyte, can give the thermodynamic profile of an interaction [46, 69-

73].

1.3.5. Comparison of biosensors and other techniques

SPR is based on the optical properties of molecules for measurements, which makes

detection of more complex solutions often complicated and limited. SAW sensors are

microbalances and are unaffected by the complexity of the solution. For example, fragments

and small molecules are often dissolved in DMSO whose high refractory index typically

adversely affects optical detection methods such as SPR. In addition, SAW based biosensors

are able to registrate changes in viscoelastiscitiy. Both SAW and SPR make use of inert

materials for the sensor chip surface, mostly gold. SAW sensors however are able to use

alternative new materials for sensor surfaces as for example SiO2 and ZnO what possibly

might lead to chromatographic techniques on the chip in the future [45-58].

Both SAW and QCM sensor techniques use acoustic waves to investigate binding

characteristics. The major difference between the two are the used waves. Within SAW

sensors, the waves propagate within the guiding layer versus the whole substrate by QCM

what results in a reduction of energy and sensitivity. Therefor, SAW biosensors are more

suitable to investigate molecular interactions of for example small peptides and proteins,

and QCM is more likely to be used to observe interactions with cells [52, 63-69]. However,

interaction studies on cells are also reported with the SAW biosensor.

10

In ITC, the molecular interactions are studied in their native state, meaning that no

modification like surface immobilization is necessary. However, both cells (reference and

sample cell) have to contain the exact same buffer solution to prevent disturbances in the

results. A high concentration (> µM) of both ligand and receptor are necessary to perform

the analysis, what decreases its potential in industrial applications [69-73]. Because its

thermodynamic information output, it can be seen as a complementary technique to SAW

and SPR.

11

2. OBJECTIVES

The global aim of the project is to develop a SAW biosensor technology into a functional

quality characterization tool. In this work, we have used somatropin or recombinant human

growth hormone (GH) as analyte, as well as 1,4,7-triazacyclononane-1,4,7-triacetic acid

(NOTA) modified somatropin (equimolar (1:1) or 3 to 10 times molar excess of NOTA (1:3

and 1:10) added to somatropin) and multiple somatropin derived peptides. This NOTA group

can allow the incorporation of radiometals for SPECT/PET-diagnostic (67Ga, 68Ga, 111In) or

therapeutic (90Y) purposes for further investigations in the future.

The more specific project goals are

(i) The development of a method for selective immobilization of antibody (hGHAb),

thereby preserve the binding capacity and binding characteristics of the antibody

for the analyte somatropin.

(ii) The development of robust operational conditions, to obtain reproducible

binding studies and minimal variation.

(iii) The quantitative binding characterization (affinity, on- and off-rates) of NOTA-

modified somatropin and multiple somatropin derived peptides. The binding

characteristics will be a benchmark for the functional quality control since the

addition of NOTA under different synthesis procedures can affect the

functionality of somatoprin.

(iv) Confirmation binding experiments with size exclustion chromatography were

performed.

12

3. MATERIALS AND METHODS

3.1. SENSOR CHIP

3.1.1. Cleaning sensor chips

3.1.1.1. Pre-cleaning

The pre-cleaning process of the sensor chip is composed out of three steps. To remove salts

and other polar compounds like carbohydrates, the chip was sonicated during three minutes

in water. The chip was placed in 100% acetone (Fisher Scientific) and exposed to ultrasonic

vibrations to remove nonpolar, lipophilic compounds like lipids, membranes, cell contents

and many proteins. The chip had to be placed immediately in 100% isopropanol (Fluka) to

prevent stains on the gold surface due to drying. Washing and sonication in isopropanol also

removed nonpolar compounds and some sugars. Advantageous is the quick drying property

of isopropanol, especially when N2 or O2 is used.

3.1.1.2. Chemical etching with AMP

Chemical etching is necessary when the chip was already modified. The chip was boiled in a

freshly prepared solution (70°C) of 5:1:1 water, ammonia (32%) (PRS Panreac) and hydrogen

peroxide (30%) (Merck). After three minutes, the chip was dried in a steam of N2 or O2.

3.1.2. Coating sensor chip with dextran

First, an alkanethiol sensor chip was prepared by covering the golden sensor chip (SAW

instruments) in a 2 mM 11-mercapto-1-undecanol (Sigma Aldrich) in 100% ethanol solution

(Sigma Aldrich) overnight in dark at room temperature. During this process, the thiol groups

were coupled to the golden surface and free –OH groups were created on the surface. After

the chip was sonicated three times in ethanol, the free terminating hydroxyl groups of

alkanethiol were activated. For this purpose, the chip was incubated during 4 hours in 0.6 M

epichlorohydrin (Sigma Aldrich) in a 1:1 mixture of diglyme (Sigma Aldrich) and 0.4 M NaOH

(Sigma Aldrich). The extremely reactive epoxides, formed by this reaction, will be able to

react easily with the dextran molecules by covalent bindings. Next, the sensor chip was

washed and sonicated three times in water, two times in ethanol and again three times in

water and dried in streaming N2 or O2. The dextran hydrogel sensor chip was prepared by

13

dripping a dextran (Sigma Aldrich) solution of 0.30 mg/ml in 0.1 M NaOH on the sensor chip

surface and incubation during night by room temperature. The unbounded dextran was

removed the next day by vigorously washing in 50°C water for multiple times and alternated

by sonication. Free carboxyl groups, whereon immobilization of the ligand can take place,

were created by incubating the chip in 1 M bromoacetic acid (Sigma Aldrich) in 2 M NaOH

overnight at room temperature. After this carboxylation, the chip was washed again

vigorously with 50°C water and exposed to ultrasonic vibrations to speed up dissolution. The

chip was dried in a steam of N2 or O2 and stored in a refrigerator at 4°C to prevent bacterial

or fungal growth.

3.2. LIGAND IMMOBILIZATION

A dextran hydrogel sensor chip was placed in the SAM5 instrument (SAW Instruments). The

binding of biomolecules is promoted by the hydrophilic environment, created by the dextran

layer. Positive loaded compounds also have the advantage in binding because of the

electrostatic attraction due to the negative charge of dextran [51-53]. The complete ligand

immobilization procedure was completed within one sequence. A flow rate of 13 µl/min was

maintained during the immobilization procedure with running buffer (HBS containing 20 mM

HEPES (Fluka), 150 mM NaCl (Sigma Aldrich), pH 7.4). The carboxyl groups were activated by

forming reactive succinimide esters by injecting 130 µl 1:1 1-ethyl-3-(3-

dimethylaminopropyl)-carbodiimide (EDC) (Sigma Aldrich) and N-hydroxysuccinimide (NHS)

(Sigma). Next, six injections of 65 µl 50 µg/ml hGHAb (Thermo) in a HBS and acetic acid

(Sigma Aldrich) pH 4.5 solution were injected, each with an equilibration time of ten

minutes. The immobilization procedure was terminated by inactivation of the reactive

succinimide ester groups by injecting 100 µl ethanol amine (Sigma Aldrich), followed by 30

minutes equilibration.

A SAM5 feasability test was performed, whereby the amount of analyte that can be detected

(in pg/mm²) has to be determined, with the assumption that all binding sites of the ligand

are available and active. The calculated amount of bound analyte has to exceed 0.5 pg/mm²

to obtain a detectable signal. The theoretical formula is represented below, where X is the

theoretical amount of bound analyte (in pg/mm²), P is the phase shift (in °) related to the

14

amount of surface bound ligand, Mw2 is the molecular weight of the analyte (in pg/pmol),

Mw1 is the molecular weight of the ligand (in pg/pmol) and S, the conversion factor, is a

sensor sensitivity constant (515 °cm²/µg).

3.3. SAM5 BINDING EXPERIMENTS

3.3.1. Screening for a regeneration condition

A regeneration experiment was performed with 0.1% sodiumdodecylsulphate (SDS). HBS (20

mM HEPES, 150 mM NaCl, pH 7.4) was used as running buffer with a flow rate of 30 µl/min.

180 µl of a 500 nM 1:10 NOTA-somatropin solution was injected first to generate binding to

the immobilized ligand. After 5 minutes while running only buffer flowed over the chip, 30 µl

of 0.1% SDS was injected. This reloading and regeneration step was repeated once more

after 10 minutes while running buffer flowing over the sensor chip to ensure all unbounded

particles were removed.

3.3.2. Analytes (modified) somatropin

3.3.2.1. Binding experiments between hGHAb and (modified) somatropin with regeneration

A dilution series was made from the 10 µM somatropin (Zomacton, Ferring) stock solution

and from the 8 µM stocks of modified somatropin, including 1:1 NOTA-somatropin, 1:3

NOTA-somatropin and 1:10 NOTA-somatropin. HBS (20 mM HEPES, 150 mM NaCl, pH 7.4)

was used as running buffer with a flow rate of 30 µl/min. After a wait of 10 minutes, 180 µl

of the 75 nM somatropin sample was injected, followed by the increasing concentrations of

100 nM, 150 nM, 200 nM, 250 nM, 300 nM, 500 nM, 500 nM (duplication), 600 nM, 750 nM,

900 nM, 1 000 nM and 500 nM. After every injection, only buffer was running 20 minutes for

providing sufficiently dissociation and equilibration of the analyte. 0.1% SDS (Sigma Aldrich)

was injected for one minute to regenerate the coated chip whereon the growth hormone

antibody was bound. An equilibration period of 10 minutes was maintained here as well.

This procedure was finished by an extra injection with 5% glycerol (Merck). The experiment

with 1:10 NOTA-somatropin was performed 2 times.

15

3.3.3. Somatropin derived peptides

3.3.3.1. QC analysis of somatropin derived peptides

Mobile phases A and B consisted of 0.1% (m/V) FA (Fisher scientific) in respectively water or

ACN (Fisher scientific). All somatropin derived peptides P0326, P0320, P0318, P0368, P0355

and P0389 (GC Biochem) (Attachment 1) were solved to a concentration of 1 mg/ml. For the

UPLC-RP, the peptide solvent was 95:5 A:B. The UPLC-HILIC analysis used 5:95 A:B as peptide

solvent. All somatropin derived peptides were analysed by UPLC-RP, and P0355 and P0389

were analysed by UPLC-HILIC. The certificates of both columns (Aquity) were enclosed in

Attachments 2 and 3. The temperatures for the column and the sample were respectively

30°C and 5°C. The flow rate was 0.5 ml/min and 2 µl was injected. Detection was performed

using a PDA 190-400 nm, with quantification at 210 nm. The gradient program of both the

UPLC-RP and UPLC-HILIC experiments was represented in Table 1 and Table 2.

Table 1: Gradient program (RP).

Time (min) Flow rate (ml/min)

Solvent composition

MP A (%) MP B (%)

Initial

0.5

95 5

20.00 20 80

22.00 20 80

23.00 95 5

30.00 95 5

Table 2: Gradient program (HILIC).

Time (min) Flow rate (ml/min)

Solvent composition

MP A (%) MP B (%)

Initial

0.5

10 90

20.00 90 10

22.00 90 10

23.00 10 90

30.00 10 90

3.3.3.2. Binding experiments with somatropin derived peptides

This experiment was performed with all somatropin derived peptides, namely P0318, P0320,

P0326, P0355, P0368 and P0389. The HBS running buffer had a flow rate of 30 µl/min. After

10 minutes only buffer running, 180 µl of a blank was injected, followed by a 180 µl injection

of the 100 nM peptide sample after 10 minutes equilibration period. Next injections

included the ascending concentrations of 200 nM, 300 nM, 400 nM, 500 nM, 600 nM, 700

16

nM, 800 nM, 800 nM (duplication), 900 nM, 1 000 nM, 2 000 nM, 3 000 nM, 4 000 nM, 6 000

nM, 8 000 nM, 10 000 nM and 800 nM. After every injection, buffer was running 10 minutes

for sufficiently dissociation and equilibration of the analyte was provided. No regeneration

procedure was performed between the multiple injections.

3.3.4. Data processing of SAW binding experiments for (modified) somatropin and

peptides

For the protein binding study a one-to-one kinetic model was used, assuming that the two

antigen binding sites of the hGHAb ligand are individual, independent binders for the mobile

analyte somatropin [76-77].

[

[ [ [

kon is the association rate constant (units M-1s-1) and koff the dissociation rate constant (units

s-1). In the biosensor, ligand L is immobilized on the sensor surface. The concentration of

complex [AL] is therefore identical to the concentration of bound analyte A. The

concentration of bound analyte is proportional to the phase P, which is detected by the SAW

biosensor. Free ligand concentration [L] is the difference between total and bound ligand

concentration. When the analyte is injected in a flow over the sensor surface, the analyte

solution is constantly replenished and hence the free concentration of the analyte may be

considered and identical to total analyte concentration C. The reaction between immobilized

ligand and analyte in solution can therefore be assumed to follow pseudo first order kinetics

and since the concentration of complex and free ligand now can be expressed in terms of

analyte phase response P:

( )

( ) ⌊ ⌋

kon

koff

17

Where,

The blanc subtracted association curves (0-300 s) of the sensorgrams were analysed using

the integrated rate equation. For each concentration of (modified) somatropin, an apparent

rate constant was determined (kobs) as well as a phase equilibrium Peq, i.e. the analyte phase

response where an equilibrium between association and dissociation or steady state

condition was reached. These apparent rate constants were plotted against the analyte

concentration C (nM). The intercept is the dissociation rate constant at equilibrium (koff). The

slope is the association constant (kon). The binding constant (KD expressed in nM) is

determined by:

The peptide interaction studies, characterized with extreme fast association, were unable to

be analyzed with a one-to-one binding model. Therefore, a steady state model was applied

where P equals to the blanc substracted phase signal at 200 s, C is equal to the used peptide

concentration and Pmax is the maximal phase signal (Figure 4).

( )

Figure 4: Steady state model.

18

3.4. SIZE EXCLUSION CHROMATOGRAPHY

Gel filtration HPLC was performed on a Alliance 2695 separations module and 2996

photodiode array detector (Waters) with a BioSep-SEC-S 2000 (300 x 7.8 mm) column

(Phenomenex) (Attachment 4) protected with a suitable guard column (Phenomenex) in HBS

(20 mM HEPES, pH 7.5, 150 mM NaCl). The (modified) somatropin concentrations applied to

the column contained 45.1 pM in HBS. The hGHAb concentration was 4.43 pM in HBS. The

mixture of hGHAb and (modified) somatropin contained 4.34 pM and 45.1 pM in HBS,

respectively. The P0320 peptide concentration was 8.81 pM, the hGHAb concentration was

0.67 pM, all in HBS. The peptide and hGHAb concentrations were maintained in the

mixtures. For the SEC/HPLC analysis an injection volume of 10 µl was applied, with a flow

rate of 10 µl/min. The column and sample temperature were maintained at respectively

20°C and 5°C during analysis, and detection was performed at 280 nm.

19

4. RESULTS AND DISCUSSION

4.1. LIGAND IMMOBILIZATION

The hGHAb was immobilized via the amine coupling chemistry (Figure 5). Amine coupling is a

direct covalent immobilisation procedure which can be used for any protein: amines present

on the ligand (e.g. lysine residues) are covalently bond to activated carboxyl-groups on the

dextran surface [86]. This procedure however, has two drawbacks. Firstly, because proteins

usually have multiple copies of the functional group (-NH2) that mediates immobilization,

proteins are coupled heterogeneously or random and sometimes at multiple sites. Secondly,

direct coupling often decreases or completely abrogates binding to analyte.

Figure 6 shows the sensorgram of the immobilization procedure. An injection of NHS/EDC

was performed to activate the carboxyl groups on the alkanethiol sensor chip to reactive

succinimide esters (Figure 5). Successive injections of hGHAb revealed an increased phase

shift. Multiple injections were performed to maximize the amount of immobilized ligand.

Not all active NHS esters react with a ligand and it is therefore crucial to eliminate unreacted

esters by deactivation, else they could attack amino groups in buffer or analyte during the

interaction experiment. The deactivation step with a high concentration of ethanolamine

changes the active ester into an inactive hydroxyethyl amide.

Figure 5: Immobilization procedure of ligands

[56]. Activation of carboxyl terminating groups in

dextran layers on the golden sensor chip by EDS/NHS, followed by amine coupling of ligands.

Table 3 shows the immobilization efficiency of every hGHAb injection, calculated as the

percentage phase shift of each hGHAb injection compared to total surface bound ligand per

channel. The injection efficiency decreased over the different injections (e.g. 38% for

injection 1 to 7% for injection 6 in channel 1). This could indicate that:

(i) the surface becomes saturated with hGHAb. Less reactive succinimide esters

are (sterically) available for binding of primairy amines on the ligand. If we

assume that the immobilization is a covalent irreversible reaction and the

20

ligand solution (L) is constantly replenished, then the immobilization is

dependent on the amount of (sterically) available reactive groups on the

surface (S).

(ii) the reactivity of the succinimide esters decreases overtime.

Table 3: hGHAb immobilization efficiency for each injection (% bound).

Final phase

shift Injection 1 (% bound)

Injection 2 (% bound)





Channel 1 5.41° 38 21 15 11 9 7

Channel 2 3.43° 36 21 15 12 9 7

Channel 3 2.22° 33 21 16 12 10 8

Channel 4 2.09° 33 21 16 13 10 7

Channel 5 3.07° 35 21 15 12 9 7

Mean 3.24° 34.9 21.2 15.4 11.9 9.3 7.2

St. Dev. 1.34° 2.0 0.1 0.5 0.6 0.5 0.4

A decrease in surface bond ligand was observed over the different channels. Channel 1 had

the highest final phase shift of 5.41°, followed by 3.43°, 3.07°, 2.22° and 2.09° for channel 2,

channel 5, channel 3 and channel 4, respectively. The difference in surface bound ligand over

the channels can be caused by a heterogeneous carboxymethylated dextran hydrogel.

Figure 6: Sensorgram of the hGHAb immobilization process. EDC/NHS injection, followed by six injections of hGHAb and an ethanolamine injection.

Using the feasibility calculations, a binding stoichiometry of 2, a Mw of 150 000 Da for

hGHAb and 22 125 Da for somatropin, we calculated the quantity of surface bound hGHAb

and the amount of somatropin (analyte) that can bind to the surface, assuming all binding

sites are active (Table 4). The theoretically calculated ad hoc signal value from analyte

0

2

4

6

8

10

12

0 2000 4000 6000 8000 10000

Ph

ase

sh

ift(

°)

Time (s)

Channel 1

Channel 2

Channel 3

Channel 4

Channel 5

21

somatropin exceeds 0.5 pg/mm2 (area/concentration), which is necessary to obtain a

detectable signal.

Table 4: Quantitative overview of ligand immobilization and ad hoc analyte binding signal.

Channel 1 Channel 2 Channel 3 Channel 4 Channel 5

pg hGHAb per mm2

105.11 66.64 43.13 40.52 59.64

pg somatropin per mm2

31.01 19.66 12.72 11.95 17.59

4.2. SOMATROPIN

4.2.1. Screening for regeneration conditions

The hGHAb bound sensor chip was exposed to an injection of 500 nM 1:10 NOTA-

somatropin, which resulted in a positive phase shift. A regeneration step with 0.1% SDS

should result in a decreasing phase. Repetition of this loading and regeneration experiment

gave similar trends in the results (Figure 7 and Table 5).

Figure 7: Sensorgram screening for regeneration condition with 0.1% SDS.

(A) association, (D) dissociation and (R) regeneration.

Table 5: Phase overview at multiple steps of regeneration procedure.

Phase at t1 (°) Phase at t2 (°) Phase at t3 (°) Phase at t4 (°) Phase at t5 (°)

Channel 1 -0.0123 0.0754 -0.1065 0.0288 -0.1076

Channel 2 -0.0133 0.0512 -0.0911 0.0152 -0.0993

Channel 3 0.0116 0.0670 -0.0424 0.0414 -0.0624

Channel 4 -0.0019 0.0419 -0.0577 0.0162 -0.0762

Channel 5 0.0177 0.0873 -0.1103 0.0239 -0.1371

Ideal regeneration conditions are able to generate a signal which is brought back to the

baseline. By testing 0.1% SDS, a negative phase shift was observed i.e. below baseline. This

could indicate that:

the anionic detergent is too strong and can affect the binding capacity of the hGHAb.

-0.4

-0.2

0

0.2

0.4

0.6

0.8

3000 3500 4000 4500 5000 5500 6000Ph

ase

shif

t (°

)

Time (seconds)

Channel 1

Channel 2

Channel 3

Channel 4

Channel 5t1

t5

t4 t3

t2

A A D D R R

22

non-covalently bound hGHAb (Figure 8) are washed away by this regeneration

procedure.

A. B. C. D.

Figure 8: Schematic overview of random binding between hGHAb and the dextran layer. (A) All antigen binding sites are still available for analyte binding, (B) no analyte can bind on the

antigen binding sites, (C) limited antigen binding sites are available to analyte molecules and

(D) non-covalently bound antibodies with (limited) available antigen binding sites.

4.2.2. SAM5 binding experiments

4.2.2.1. Binding experiment between hGHAb and somatropin

Figure 9 shows the binding of somatropin to the immobilised hGHAb in channel 1. The

association (0-300s) was fitted for all injections and for all channels (Attachment 5). All fitted

curves had an R2 of at least 0.90.

Figure 9: Sensorgram of somatropin binding to the hGHAb in channel 1.

The non-linear regression resulted in a pseudo-first order kinetic constant (kobs) for each

injection. The kon and koff for each channel and the resulting KD are shown in Table 6.

Affinities going from 1 276 nM to 1 900 nM were calculated indicating a high variation

between the channels. Also a large standard error was calculated.

-0.05

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

-200 0 200 400 600 800 1000

Ph

ase

shif

t (°

)

Time (s)

75 nM

100 nM

150 nM

250 nM

300 nM

500 nM

500 nM

550 nM

600 nM

750 nM

900 nM

1000 nM

Blanc

23

The maximal phase signal at 1 000 nM is presented in Table 7. This was obtained by

subtraction of the phase signal at -80 s and 300 s. Assuming that the injection of 1 000 nM

somatropin is capable of saturating all hGHAb binding sites, the percentage of active hGHAb

was calculated by using the amount of analyte somatropin that was theoretically able to

bind in every channel (Table 4). The calculated percentage of active hGHAb is low and can be

due to the random immobilization procedure (amine coupling) (Figure 8), which can make

the somatropin binding sites on hGHAb sterically unavailable and/or influence its

functionality.

Table 6: Schematic overview of the dissociation constant (KD) and kinetic parameters (kon and koff).


kon (M-1s-1)

± SE 8.32E-06

± 3.98E-06 8.22E-06

± 4.19E-06 8.22E-06

± 5.34E-06 7.16E-06

± 4.74E-06 7.31E-06

± 2.19E-06

koff (s-1)

± SE 0.011

± 0.002 0.012

± 0.002 0.013

± 0.003 0.014

± 0.003 0.010

± 0.001

KD (nM) ± SE

1 276 ± 589

1 424 ± 706

1 579 ± 1 084

1 900 ± 1 308

1 519 ± 484

Table 7: Binding capacity of 1 000 nM NOTA-somatropin to surface immobilized hGHAb.


Phase signal analyte binding at 1 000 nM (°)

0.332 0.255 0.195 0.177 0.323

Amount pg/mm2

6.447 4.954 3.792 3.428 6.273

% active hGHAb 21 25 30 29 36

The observed phase shift seems low but can be related to the used immobilization chemistry

which is an ad random procedure, whereby antigen recognition sites of the antibody can

possibly be non-functional. When direct capturing approaches are used, as for example the

streptavidine-biotine capture or antibody based capture (Fc region), the ligand is attached to

the surface in a specific orientation (determined by the location of the binding site for the

capturing molecule) so that attachment to the surface does not introduce heterogeneity in

the ligand population [78-79].

24

4.2.3. SEC experiments

4.2.3.1. Calibration curve of the SEC column

Figure 10 represents the calibration curve of the BioSep-SEC-S 2000 column, which has a

supplier-specified separation range from 244 to 670 000 Da (Attachment 4). This curve was

based on the logarithm of the molecular weight against the retention time of both own

experimental and supplier-originated data (Table 8 and Attachment 4). Multiple models and

corresponding calibration curves are described in literature, with higher order equations

being more precisely [80]. However, a linear calibration curve was chosen above a more

complex polynominal equation because of the limited available calibration points and to

minimize deviations of the model. Still, an observed error of 3-23% between the theoretical

weight and the weight was determined. The premised model had a sufficient sensitivity to

detect small differences in molecular weight.

Table 8: Calibration curve of the SEC column.

Compound Molecular

weight (Da) Retention time

(minutes) Origin

Modelled molecular weight (Da)

Deviation (%)

IgG 150 000 6.46 Supplier info 124 433 17.0

Ovalbumin 44 000 7.65 Supplier info 45 501 3.4

Somatropin 22 125 8.41 Experimental 23 932 8.2

Myoglobin 17 000 8.57 Supplier info 20 904 23.0

Obestatin (mouse/rat)

2 517 11.23 Experimental 2 206 12.4

Contributing to the deviation of the model can be the use of different specific equipment,

wich have their own parameters such as dead volume, tubings, e.g., other values could also

be obtained by using other buffer solutions, for example the supplier used a phosphate

buffer compared to an HBS buffer within all described SEC experiments.

Figure 10: Calibration curve of the SEC column.

y = -0.3672x + 7.4668 R² = 0.9885

0

1

2

3

4

5

6

5 7 9 11 13

log

Mw

(D

a)

Time (minutes)

25

4.2.3.2. SEC analysis of hGHAb

Figure 11 represents the chromatogram of an hGHAb injection (4.34 pM) obtained by SEC.

The characteristics of the multiple injections are presented in Table 9, where an average

retention time of 6.46 minutes was calculated. Using the calibration curve (Figure 10), this

elution time corresponded to a compound with a calculated molecular weight of 124 362 Da.

The theoretical Mw of the hGHAb was not given by the supplier, however, most antibodies

have an Mw of approximately 150 000 Da. Comparing both molecular weights by the

selected model indicates a deviation of 17%.

Figure 11: SEC chromatogram of hGHAb.

Table 9: SEC results of hGHAb.

RT Area

1 6.49 152 258

2 6.44 150 916

3 6.45 148 268

4 6.45 153 000

5 6.47 156 142

Average 6.46 152 117

SD 0.02 2 883

4.2.3.3. SEC analysis of somatropin

Figure 12 represents the injection of a 45.1 pM somatropin sample derived from a Zomacton

dilution within HBS. Multiple peaks were visible: the major peak at RT 8.41 min (Table 10)

corresponds with somatropin and has a calculated molecular weight of 23 914 Da according

to the previous calibration model. The smallest peak, eluting before somatropin at RT 7.73

min corresponds to a compound with a molecular weight of 42 496 Da according to the

model and has an AUC which is 3.5% of the main peak and lower than the limit of 4%

allowed impurities by the Ph. Eur. There is also a second peak at RT 10.39 min,

26

corresponding to a molecular weight of 4 483 Da and which is 4.5 % of the main peak. Out of

the DAD spectra seemed this peak was not originating from peptides and is considered as a

contaminant.

Figure 12: SEC chromatogram of somatropin (Zomacton).

Table 10: SEC results of somatropin (Zomacton).

RT Area Height

Extra peak

1 7.733 19 216 707

2 7.729 13 395 500

Average 7.73 16 306 604

SD 0.0028 4 116 146

Somatropin (Zomacton)

1 8.413 479 800 28 271

2 8.411 456 352 27 676

Average 8.41 468 076 27 974

SD 0.0014 16 580 421

Extra peak

1 10.392 20 842 1 888

2 10.396 21 634 1 633

Average 10.39 21 238 1 761

SD 0.0028 560 180

Table 11 represents the injection of a 45.1 pM somatropin (lyophilized) sample where the

component had undergone the same lyophilisation procedures as the NOTA-modified

somatropin samples (discussed later). The lyophilized somatropin sample had a similar

chromatogram (not represented) and RT of 8.41 minutes as the Zomacton sample described

above and also an extra peak wich corresponds to 3.4% of the main peak and is lower than

the maximal limit for impurities of the Ph. Eur.

27

Table 11: SEC results of somatropin (lyophilized).

RT Area Height

Extra peak

1 7.658 14 658 521

2 7.644 9 598 539

Average 7.65 12 128 530

SD 0.01 3 578 13

Somatropin (lyophilized)

1 8.407 361816 21492

2 8.412 361906 21323

Average 8.41 361861 21408

SD 0.0035 63.64 119.50

4.2.3.4. SEC analysis of mixtures of hGHAb and somatropin

Figure 13 represents the chromatogram of a sample containing hGHAb (4.34 pM) and a 10

fold molar excess of somatropin (45.1 pM) in HBS. Within the chromatogram, an extra peak

was visible, characterized by an average retention time of 5.76 minutes (Table 12), which

corresponds to a calculated molecular weight of 224 765 Da. The hGHAb (RT 6.32 min) and

somatropin (RT 8.41 min) corresponded to a calculated molecular weight of respectively 139

990 Da and 23 914 Da. The SEC system is sufficiently sensitive to separate both compounds.

The importance of SEC in studying binding characteristics between molecules has become

more important, also because it can replace the deficiancies of the CE technique which is

often used as well [81].

Figure 13: SEC chromatogram of hGHAb and somatropin (Zomacton).

Table 12: SEC results of mixture hGHAb and somatropin (Zomacton).

RT Area Height

Extra peak

1 5.745 9 068 876

2 5.765 11 442 1 105

Average 5.76 10 255 991

SD 0.014 1 679 162

28

Table 12 continued: SEC results of mixture hGHAb and somatropin (Zomacton).

hGHAb

1 6.312 139 901 4 748

2 6.324 141 513 4 726

Average 6.32 140 707 4 737

SD 0.0085 1 140 16

Extra peak

1 7.653 17 952 685

2 7.600 17 573 703

Average 7.63 17 763 694

SD 0.038 268 13

Somatropin (Zomacton)

1 8.407 468 355 28 152

2 8.414 469 857 28 248

Average 8.41 469 106 28 200

SD 0.0050 1 062 68

Assuming additive UV properties (at 280 nm), the compounds ‘alone’ and the ‘mixture’ are

reported to give identical peak areas. This is indeed confirmed by Table 13, whereby the loss

in hGHAb peak area is compensated by the extra peak area at 5.74 minutes. Moreover the

hGHAb peak is shifted from 6.41 minutes (alone) to 6.32 minutes (mixture), while the peak

has widened, what indicates no certainity this peak is pure.

Table 13: Area-balance (at 280 nm) of somatropin (Zomacton).

Alone Mixture

hGHAb 152 117 140 707

Somatropin (Zomacton) 468 076 469 106

Extra complex - 10 255

Total area 620 193 620 068

Figure 14 represents an injection of 4.34 pM hGHAb and a 10 fold excess of somatropin

(lyophilized) in HBS. The results of all runs were gathered in Table 16. An additional peak was

observed with an average retention time of 5.78 minutes, corresponding to a calculated

molecular weight of 220 996 Da. The antibody and somatropin peaks had average retention

times of 6.33 and 8.41 minutes which corresponded to a molecular weight of respectively

138 811 Da and 23 914 Da. The variation to the theoretical weight could be explained to an

error of the model (Table 8). Also the already discussed impurity peak was visible here at

7.64 minutes.

29

Figure 14: SEC chromatogram of hGHAb and somatropin (lyophilized).

Table 16: SEC results of hGHAb and somatropin (lyophilized).

RT Area Height

Extra peak

1 5.781 3 542 518

2 5.783 3 971 577

Average 5.78 3 757 548

SD 0.0014 303 42

hGHAb

1 6.330 176 136 5 513

2 6.329 164 870 5 328

Average 6.33 170 503 5 421

SD 0.00071 7 966 131

Extra peak

1 7.681 20 240 723

2 7.602 14 877 616

Average 7.64 17 559 670

SD 0.06 3 792 76

Somatropin (lyophilized)

1 8.412 359 054 21 112

2 8.407 354 596 21 056

Average 8.41 356 825 21 084

SD 0.0035 3152 40

Assuming additive UV properties (at 280 nm), the solutions ‘alone’ and the ‘mixture’ are

reported to give practically identical peak areas, where small differences probably are due to

differences within pipetting or integration. This is indeed confirmed Table 17, whereby the

loss in hGHAb peak area was compensated by the extra peak area at 5.78 minutes. An other

important remark is the shift of the hGHAb peak from 6.41 to 6.33 minutes and the widening

of the peak what assumes the hGHAb peak is not pure.

30

Table 17: Area-balance (at 280 nm) of somatropin (lyophilized).

Alone Mixture

hGHAb 152 117 170 503

Somatropin (lyophilized) 361 861 356 825


Total area 513 978 531 085

However, by considering the results of somatropin (Zomacton and lyophilized), smaller

values were observed for the extra peak of the lyophilized sample. This could be an

indication that the lyophilized somatropin is less reactive then the Zomacton sample, which

could be due to the lyophilisation process or to a decrease in stability of the compound.

4.3. MODIFIED SOMATROPIN

4.3.1. 1:1 NOTA-somatropin

4.3.1.1. SAM5 binding experiment with regeneration

Figure 15 shows the binding of 1:1 NOTA-somatropin to the immobilized hGHAb. The

binding curve showed spiking at the beginning (0 s) and at the end (300 s) of an injection.

Injections were performed with injection parameter ‘burst on’ to quickly change from the

buffer solution to the analyte at the beginning and end of an injection. If the burst is turned

off, the interface between analyte and buffer solution will continuously flow with the regular

flow rate over the sensor chip. This will cause a delay of signal on the last sensor. With the

burst turned on, the flow rate (and the pressure) is increased shortly when the interface

reaches the sensor chip. The spiking has therefore a physical and chemical origin. However,

this spiking was not always observed in experiments with identical injection parameters.

Figure 15: Sensorgram of 1:1 NOTA-somatropin binding to hGHAb in channel 1.

-0.05

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

-200 0 200 400 600 800 1000

Ph

ase

sh

ift

(°)

Time (s)

100 nM

150 nM

200 nM

250 nM

300 nM

500 nM

500 nM

550 nM

600 nM

750 nM

900 nM

1000 nM

500 nM

Blanc

31

The one-to-one binding model was used for the calculation of the kon and koff for each

channel, and the resulting KD (Table 18 and Attachment 6). The maximal phase signal at

1 000 nM somatropin is presented in Table 19. As with somatropin (section 4.2.2.1), the

calculated percentage of active ligand concentration is relative low: 18% to 35% of all

surface bound ligand is active and available for analyte interaction.

Table 18: Schematic overview of the dissociation constant and kinetic parameters.


kon (M-1s-1)

± SE 3.80E-05

± 3.96E-06 2.51E-05

± 2.24E-06 2.13E-05

± 2.01E-06 1.64E-05

± 1.99E-06 1.57E-05 1.52E-06

koff (s-1)

± SE 0.0099

± 0.0022 0.0135

± 0.0012 0.0133

± 0.0011 0.0013

± 0.0011 0.0153

± 0.0008

KD (nM) ± SE

260 ± 138

538 ± 68

623 ± 78

796 ± 116

979 ± 108

Table 19: Binding capacity of 1 000 nM 1:1 NOTA-somatropin to surface immobilized hGHAb.


Phase signal analyte binding at 1000 nM (°)

0.285 0.231 0.173 0.515 0.315

Amount pg/mm2

5.540 4.491 3.359 2.942 6.113

% hGHAb active 18 23 26 25 35

4.3.1.2. SEC experiments

4.3.1.2.1. SEC analysis of 1:1 NOTA-somatropin

Figure 16 represents the injection of 1:1 NOTA-somatropin with a concentration of

approximately 45.1 pM. The results of the two runs were collected in Table 20. This

modification had an average retention time of 8.33 minutes, what corresponds to an

calculated molecular weight of 25 587 Da. The higher molecular weight, compared to

somatropin (23 914 Da) can be related to the coupling of NOTA-chelator groups to free

amines of somatropin (Mw NOTA is 450 Da).

32

Figure 16: SEC chromatogram of hGHAb and 1:1 NOTA-somatropin.

Table 20: SEC results of 1:1 NOTA-somatropin.

RT Area Height

1 8.325 62 650 2912

2 8.338 64 997 2987

Average 8.33 63824 2950

SD 0.0092 1660 53

4.3.1.2.2. SEC analysis of mixtures of hGHAb and 1:1 NOTA-somatropin

Figure 17 represents the chromatogram of an injected sample containing both hGHAb and a

tenfold molar excess of 1:1 NOTA-somatropin (Table 21). An extra peak was observed with

an average retention time of 5.80 minutes, which corresponds to a molecular weight of 217

290 Da according to the calibration model.


Table 21: SEC results of hGHAb and 1:1 NOTA-somatropin.

RT Area Height

Extra peak

1 5.792 12 751 1 390

2 5.815 11 128 1 255

Average 5.80 11 940 1 323

SD 0.016 1 148 95

33

Table 21 continued: SEC results of hGHAb and 1:1 NOTA-somatropin.

hGHAb

1 6.353 143 790 4 884

2 6.390 152 690 4 458

Average 6.37 148 240 4 671

SD 0.026 6 293 301

1:1 NOTA-somatropin

1 8.325 76 072 3 548

2 8.366 79 795 3 517

Average 8.35 77 934 3 533

SD 0.029 2 633 22


reported to give a small difference in peak areas, which probably were due to variation in 1:1

NOTA-somatropin concentration between the samples (Table 22). The similar trend in peak

shift and peak widening was also observed here, indicating the peak might not be pure en

may be partially deriving from other compounds than hGHAb.

Table 22: Area-balance (at 280 nm) of 1:1 NOTA-somatropin.

Alone Mixture

hGHAb 152 117 148 240

1:1 NOTA-somatropin 63 824 77 934


Total area 215 941 238 114


4.3.2.1. SAM5 binding experiment with regeneration

Figure 18 shows the binding of 1:3 NOTA-somatropin to the immobilised hGHAb. The

association was fitted using the one-to-one binding model (Attachment 7). The results are

shown in Table 23. For channel 5, the kon and koff were not significantly different from 0. The

maximal phase signal at 1 000 nM is presented in Table 24. The calculated percentage of

active hGHAb ligand is lower than in previous experiments, what may point to

(i) a loss in ligand activity by the successive interaction and regeneration cycles,

and/or,

(ii) the influence of the NOTA-group on binding.

34

Figure 18: Sensorgram of 1:3 NOTA-somatropin binding to the hGHAb in channel 1.



kon (M-1s-1)

± SE 1.15E-05

± 3.89E-06 1.33E-05

± 2.24E-06 1.64E-05

± 2.01E-06 1.31E-05

± 1.99E-06 1.41E-05

± 1.57E-05

koff (s-1)

± SE 0.00637 ± 0.0021

0.0074 ± 0.0012

0.0031 ± 0.0012

0.0060 ± 0.0012

0.0073 ± 0.0153

KD (nM) ± SE

551 ± 90

560 ± 96

188 ± 60

460 ± 67

517 ± 35

Table 24: Binding capacity of 1 000 nM 1:3 NOTAsomatropin to surface immobilized hGHAb.



0.225 0.180 0.131 0.119 0.258

Amount pg/mm2

4.369 3.491 2.550 2.318 5.018

% hGHAb active 14 18 20 19 29




approximately 45.1 pM. The results of the two runs are collected in Table 25. This

modification had an average retention time of 8.26 minutes, what corresponds to a

molecular weight of 27 147 Da. The higher molecular weight, compared to somatropin, can

be related to the coupling of NOTA-chelator groups to free amines of somatropin (Mw NOTA

is 450 Da). Again, a small impurity peak was observed, here at an average retention time of

7.54 minutes, corresponding to a molecular weight of 49 901 Da and remained 3.8% of the

main peak what was beneath the acceptable limit of the Ph. Eur. The mean peak

-0.05

0.05

0.15

0.25

0.35

-200 0 200 400 600 800 1000

Ph

ase

sh

ift

(°)

Time (s)

50 nM

75 nM

100 nM

150 nM

250 nM

300 nM

500 nM

500 nM

550 nM

600 nM

750 nM

900 nM

1000 nM

Blanc

35

corresponding to 1:3 NOTA-somatropin showed a higher peak area and high compared to

the 1:1 NOTA-somatropin. This will be discussed in the 1:10 NOTA-somatropin section.

Figure 19: SEC chromatogram of 1:3 NOTA-somatropin.


RT Area Height

Extra peak

1 7.507 15 541 695

2 7.582 17 897 724

Average 7.54 16 719 710

SD 0.05 1 666 21

1:3 NOTA-somatropin

1 8.258 436 422 20 562

2 8.271 452 057 20 265

Average 8.26 444 240 20 414

SD 0.0092 11 056 210


Figure 20 represented the chromatogram of an injected sample containing both hGHAb and

a tenfold excess of 1:3 NOTA-somatropin. All results were assembled in Table 26. No extra

peak was here detected at 280 nm, which can be due to an insufficient detection limit.


36


RT Area Height

hGHAb

1 6.328 99 121 3 002

2 6.305 94 264 2 684

Average 6.32 96 693 2 843

SD 0.016 3 434 225

Extra peak

1 7.467 23 003 879

2 7.477 34 045 866

Average 7.47 28 524 873

SD 0.007 7 808 9

1:3 NOTA-somatropin

1 8.252 451 110 20 775

2 8.275 470 131 20 613

Average 8.26 460 621 20 694

SD 0.016 13 450 115


reported to give difference in peak areas (Table 27), which probably were due to variation in

hGHAb and 1:3 NOTA-somatropin concentration between the samples. An extra peak

corresponding to the complex of hGHAb and 1:3 NOTA-somatropin was not observable. This

lacking peak is due to the lacking sensitivity of the system to detect this complex. Also the

antibody peak showed a shift as previously described what could include a part of the

complex. Deconvolution of the peaks could give further information about this.


Alone Mixture

hGHAb 152 117 96 693

1:3 NOTA-somatropin 444 240 460 621

Extra complex - -

Total area 596 357 557 314


4.3.3.1. SAM5 binding experiments

4.3.3.1.1. Binding experiment with regeneration


association (0-300s) was fitted for all injections and for all channels. The statistical analysis of

the non-linear regression is summarised in Attachment 8.

37

Figure 21: Sensorgram of 1:10 NOTA-somatropin binding to hGHAb in channel 1.

The on- and off-rates as well as the calculated affinities (KD) are shown in Table 28. We

observe a decrease in affinity from channel 1 to 5, including an increased standard error. The

maximal phase signal at 1 000 nM is presented in Table 29.

Table 28: Schematic overview of the dissociation constant (KD) and kinetic parameters (kon and koff).


kon (M-1s-1)

± SE 1.58E-05

± 4.45E-06 8.11E-06

± 2.79E-06 1.05E-05

± 4.03E-06 5.01E-06

± 1.69E-06 4.40E-06

± 1.49E-06

koff (s-1)

± SE 0.0114

± 0.0023 0.0147

± 0.0016 0.0112

± 0.0021 0.0129

± 0.0009 0.0103

± 0.0008

KD (nM) ± SE

724 ± 251

1808 ± 651

1062 ± 455

2571 ± 887

2336 ± 812

Table 29: Binding capacity of 1000 nM 1:10 NOTA-somatropin to surface immobilized hGHAb



0.198 0.162 0.133 0.119 0.206

Amount pg/mm2 3.848 3.143 2.586 2.305 4.008

% hGHAb active 12 16 20 19 23

4.3.3.1.2. Duplication of binding experiment with regeneration


statistical analysis of the non-linear regression is summarised in Attachment 9. The binding

characteristics are summarized in Table 30. The calculated affinities deviated from the ones

calculated in previous experiment (Table 28) by a factor 2 to 4. Consequently, serious

considerations have to be made according the robustness of the system The calculated

-0.05

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

-200 0 200 400 600 800 1000

Ph

ase

sh

ift

(°)

Time (s)

100

150

200

250

300

500

500

600

750

1000

500

Blanc

38

active ligand binding sites (Table 31) are similar than in previous experiments with 1:3 and

1:10 NOTA-somatropin.

Figure 22: Sensorgram of 1:10 NOTA-somatropin binding to the hGHAb in channel 1.



kon (M-1s-1)

± SE 1.02E-05

± 1.51E-06 1.18E-05

± 1.23E-06 1.18E-05

± 1.03E-06 1.30E-05

± 9.81E-07 1.76E-05

± 2.81E-06

koff (s-1)

± SE 0.0032

± 0.0008 0.0042

± 0.0006 0.0038

± 0.0055 0.0040

± 0.0005 0.0097

± 0.0015

KD (nM) ± SE

316 ± 95

358 ± 67

322 ± 55

306 ± 47

554 ± 123

Table 31: Binding capacity of 1 000 nM 1:10 NOTA-somatropin to surface immobilized hGHAb.



0.268 0.208 0.148 0.127 0.287

Amount pg/mm2

5.210 4.048 2.875 2.460 5.566

% hGHAb active 17 21 23 21 32




approximately 45.1 pM. The results of the two runs were collected in Table 32. This

modification had an average retention time of 8.15 minutes, what corresponds to a

calculated molecular weight of 29 793 Da. The two extra peaks had an average retention

time of 7.41 minutes and 10.12 minutes, corresponding to the calculated weights of

respectively 55 699 Da and 5 633 Da and were identified as an impurity and a contamination.

-0.2

-0.1

0

0.1

0.2

0.3

-200 0 200 400 600 800 1000

Ph

ase

sh

ift

(°)

Time (S)

100 nM150 nM200 nM250 nM300 nM500 nM500 nM550 nM600 nM750 nM900 nM1000 nM500 nMBlanc

39

Figure 23: SEC chromatogram of 1:10 NOTA-somatropin.


RT Area Height

Extra peak

1 7.365 17 938 731

2 7.446 18 657 817

Average 7.41 18 298 774

Mean 0.06 508 61

1:10 NOTA-somatropin

1 8.143 558 746 25 007

2 8.152 566 399 24 170

Average 8.15 562 573 24 589

SD 0.0064 5 411 592

Extra peak

1 10.091 16 927 961

2 10.150 18 864 1 004

Average 10.12 17 896 983

Mean 0.04 1 370 30


Figure 24 represented the chromatogram of an injected sample containing a mixture of

hGHAb and a tenfold excess of 1:10 NOTA-somatropin. All results were assembled within

Table 33 and in Table 34. No extra peak was here detected at 280 nm, which can be due to

low sensitivity and the peak of the complex can be included in the hGHAb peak because of

the peak shift and difference in shape. Deconvolution can give exclusion about this.


40


RT Area Height

hGHAb

1 6.28 17 6575 4 946

Extra peak

1 7.47 33 298 1 039

1:10 NOTA-somatropin

1 8.15 572 275 23 618

Extra peak

1 10.16 32 273 1 054


Alone Mixture

hGHAb 152 117 176 575

1:10 NOTA-somatropin 562 573 572 275

Extra complex - -

Total area 714 690 748 850

We can conclude that the binding experiments performed with SEC have to be interpreted

carefully because the observed error on the used model between the experimental and

theoretical data from 2 517 to 150 000 Da in this range varied between 3-23%. Also

differences in shape and compactness of a molecule can influence the retention

characteristics. A shorter retention time was observed by higher order NOTA-modifications.

Calculated molecular weights of 25 587 Da, 27 147 Da and 29 793 Da were determined by

respectively 1:1, 1:3 and 1:10 NOTA-somatropin, indicating the higher amounts of NOTA that

were used for modification, the more NOTA was bound on somatropin. This conclusion

could be made considering the separation of NOTA-groups (Mw NOTA is 450 Da) is possible

at the respectively retention times. Previous investigations indicated that within the 1:1

NOTA-somatropin batch about half of the molecules were modified with one NOTA group

and the other half was remained unmodified. Within the 1:3 NOTA-somatropin batch, 13%

had no modifications, 45% contained one NOTA-group, 35% were coupled to two groups and

7% were coupled to tree NOTA-groups. Within the 1:10 NOTA-somatropin batch, all

molecules were modified: 11% contained one NOTA-group and respectively 56% and 33%

were coupled to two and three NOTA-groups. The additional effect of the NOTA-groups on

280 nm, detection was reflected on the 1:3 and 1:10 NOTA-somatropin batches. The amount

of bound NOTA to somatropin was proportional to the difference in peak heights; the more

NOTA that was bound to somatropin, the higher the peak height. 1:1 NOTA-somatropin

showed proportionally a lower additional effect, which was probably due to production

41

variation. The 1:1 NOTA-somatropin modification showed clearly an extra peak. The 1:3 and

1:10 modifications did not qualitatively show an extra peak, but a small RT peak shift and a

broader peak width were observed. The absence of the complex peak could be the result of

a low detection limit or the low affinity of the complex, as SEC is a method to detect high

affinity complexes.

4.3.4. Comparison of the modified somatropin structures

Table 35 gives an overview of the weighed means of the KD values over the different

channels. The calculations are enclosed in Attachment 10.

Table 35: Weighted mean of the KD values of (modified) somatropin.

KD Somatropin

(nM))

KD 1:1 NOTA-somatropin

(nM)

KD 1:3 NOTA-somatropin

(nM)

KD 1:10 NOTA- somatropin

(nM)

KD 1:10 NOTA- somatropin

(nM) (repetition)

Weighted mean 1 512 713 490 1725 365

Out of the duplication experiments with the SAW biosensor, we detected variability between

measurements. For example, two times 1:10 NOTA-modified somatropin was investigated

for its binding to hGHAb, resulting in two different overall calculated affinities (KD1: 1 725

nM, KD2: 365 nM). The experimental conditions were different: lower concentrations were

excluded from the first 1:10 experiment (KD 1 725 nM). However, this experimental

difference may not influence the calculated affinity. In addition, the standard error on the KD

values for each channel were relative high for the 1:10 NOTA-somatropin (KD 1 725 nM) and

somatropin (KD 1 213 nM) experiments.

The 1:1, 1:3 and 1:10 NOTA-somatropin samples seem to have at least similar affinities for

the hGHAb (in the higher nM affinity range). However, the calculated affinity of somatropin

for hGHAb seems to be low (KD in µM range, which is unusual for antibody interactions). This

could indicate that the NOTA-bifunctional chelator has strong affinity for the hGHAb

immobilized chip (either specific or aspecific). Since the high variability, we suggest to

optimize the experimental conditions to improve the reproducibility of measurements.

Figure 25 represents the risk analysis of the variability in affinities (KD values), based on the

Ishikawa diagram. Attention must be payed to the operational quality of the system

42

(equipment). During experiments care must be taken for any airbubble present in tubings or

injector syringes, which can cause aberrant signals and therefore, variability between

experiments. The flow cells are formed by pressing the sensor chip against a set of meandric

channels on the surface of the fluidic cell, so that the chip can easily be exchanged. Since the

fluidic cell is under constant pressure during experiments, it is recommended to replace the

fluidic cell once a year. Maintenance on a regular basis is necessary to remove absorbed

proteins or analytes and micro-organisms from tubings, pumps, fluidic cell and autosampler.

The researcher (personnel) should be trained and qualified to perform experiments with the

SAW biosensor. The presence of a quality system including standard operating procedures

(SOP) is therefore very important.

The quality of the materials is crutial, since they can influence the results obtained with

bioassays [84]. The purity of the analyte and ligand samples should be as high as possible.

When new running buffer is prepared, minimal variation in pH, salt or buffer concentration

can influence the baseline and hence the experimental variability. When buffers are

exchanged, the system should be equilibrated for at least one hour to stabilize the baseline.

The sensor chip was chosen to be classified seperatly (not under materials), since the

different manipulations that can influence the measurement variability. For example, before

modifying the chip with a carboxymethylated dextran hydrogel, the chip has to be of plain

gold. Therefore the cleaning and etching procedure is crucial to obtain a homogeneous

carboxymethylated dextran hydrogel. Environmental conditions like room temperature and

humidity can also influence the variation in affinity.

44

Figure 25: Risk analysis of the KD determination.

45

4.4. SOMATROPIN DERIVED PEPTIDES

4.4.1. Choise of peptides

The DruQuaR laboratory has rationally developed somatropin derived peptides based on the

3D structure of hGH in complex with the soluble part of the hGHR or growth hormone

binding protein (GHBp) (PDB 3HHR [16]). Figure 26 shows the different peptides that were

tested with hGHAb.

A. B.

C. D.

Figure 26: Somatropin derived peptides situated in the growth-hormone receptor complex. One molecule growth hormone binds two receptor molecules sequentially l [82-83], including binding site I

(blue), binding site II (green) and a third binding site between both receptors. The red marked structure represents the orientation of the somatropin derived peptide P0326 (A), P0320 (B), P0318

(C) and P0355 (D). The peptides P0368 and P0389 are similar to P0355, but extended with a few extra amino acids.

4.4.2. QC analysis somatropin derived peptides

Before starting experiments, the peptides were analyzed by UPLC-PDA to control if the

requested 95% purity was provided by the supplier. This quality control is absolutely

necessary, since studies have proved that the quality of peptides supplied by the

manufacturer sometimes can be unacceptable and insufficient for experiments [84]. A

reporting threshhold of 0.1% for impurities in peptides obtained by chemical synthesis was

46

applied (Ph. Eur.) (Attachment 11). The purity of the peptides was determined by using a

C18 reversed phase column. The somatropin derived peptides P0355 and P0389 showed a

too low retention (k’ 1.56 and 0.47 respectively). Therefore, the analysis was repeated with a

HILIC column where sufficient retention was obtained (Table 36).

Table 36: Purity of the somatropin derived peptides by UPLC analysis.

Peptide Purity (C18) (%) Purity (HILIC) (%)

P0326 98.2 -

P0320 44.1 -

P0318 89.7 -

P0368 81.4 -

P0355 - 62.8

P0389 - 91.7

Insufficient quality for most of the peptides was detected. Experiments performed with

these peptides consequently have to be interpreted carefully because by-products and

impurities can have a strong inpact on bioassay results, in this case the binding affinity (KD)

to hGHAb [84].

4.4.3. SAM5 binding experiments

4.4.3.1. Feasability calculations

Because of the presence of airbubbles, another sensor chip (including a new immobilization

procedure) was used to perform the somatropin derived peptide experiments. The total

bound ligand from the hGHAb immobilization and SAM5 feasibility calculations are shown in

Table 37. All peptides exceeded the limit of 0.5 pg/mm2 to obtain a detectable signal.

Table 37: Totatal surface bound hGHAb and maximal analyte signal.

Total

bound ligand (°)

Analyte signal P0320

(pg/mm2)


(pg/mm2)


(pg/mm2)


(pg/mm2)


(pg/mm2)


(pg/mm2)

Channel 1 7.70 4.44 4.31 2.58 1.09 0.32 0.12

Channel 2 8.35 4.82 4.68 2.80 1.18 0.34 0.13

Channel 3 7.19 4.15 4.02 2.41 1.02 0.30 0.11

Channel 4 2.88 1.66 1.61 0.96 0.41 0.12 0.05

Channel 5 3.36 1.94 1.88 1.13 0.48 0.14 0.05

47

4.4.3.2. SAW binding experiments

Figure 27 shows the binding of peptide P0320 to the immobilized hGHAb. No significant

increase in phase shift was detected during the association (0-300s) so this peptide was

considered as a non-binder. Steady state analysis was impossible, as well as for peptides

P0318, P0368 and P0355 (Figures 28, 29 and 30). The binding of these peptides can be

influenced by their quality and the presence of impurities.

Figure 27: Sensorgram of P0320 binding to hGHAb in channel 1.


-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25

-200 0 200 400 600 800

Ph

ase

sh

ift

(°)

Time (s)

100 nM200 nM300 nM400 nM500 nM600 nM700 nM800 nM800 nM900 nM1000 nM2000 nM3000 nM4000 nM6000 nM8000 nM10000 nM800 nM

-0.1

-0.08

-0.06

-0.04

-0.02

0

0.02

0.04

0.06

0.08

0.1

-200 0 200 400 600 800 1000

Ph

ase

shif

t (°

)

Time (seconds)

0 nM100 nM200 nM300 nM400 nM500 nM600 nM700 nM800 nM800 nM900 nM1000 nM2000 nM3000 nM4000 nM6000 nM8000 nM10000 nM800 nM

48



Figure 31 shows the binding of peptide P0326 to the immobilized hGHAb. An increase in

phase signal was observed with increasing P0326 concentrations. The binding is

characterized with fast on- and off- rates; therefore, the KD will be determined by plotting

the phase signal during association (at 200s) against analyte concentration. In Table 38, the

calculated binding affinities for each channel are summarized. R2 values of more than 0.85

were obtained for fitting. The spiking in the sensorgrams can be due to physical or chemical

influences and will be investigated later.

-0.1

-0.05

0

0.05

0.1

0.15

0.2

-200 0 200 400 600 800 1000

Ph

ase

sh

ift

(°)

Time (seconds)


-0.06

-0.04

-0.02

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

-200 0 200 400 600 800 1000

Ph

ase

shif

t (°

)

Time (seconds)


49


Table 38: Calculated affinities of peptide P0326.


KD (nM) 29 077

± 37 719 18 391

± 15 946 20 771

± 19 316 114 574

± 436 612 28 027

± 32 574

Figure 32 shows the binding of peptide P0389 to the immobilized hGHAb. An increasing

phase signal was observed with increasing P0389 concentrations. The binding is

characterized with fast on and off rates; therefore, the KD will be determined by plotting the

phase signal during association (at 200s) against analyte concentration. Table 39 represents

the calculated affinities for each channel. For all channels, R2 of more than 0.75 were

obtained for fitting.


-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2

-200 0 200 400 600 800 1000

Ph

ase

shif

t (°

)

Time (seconds)

0 nM100 nM200 nM300 nM400 nM500 nM600 nM700 nM800 nM800 nM900 nM1000 nM2000 nM3000 nM4000 nM6000 nM8000 nM10000800 nM

-0.08

-0.06

-0.04

-0.02

0

0.02

0.04

0.06

0.08

0.1

-200 0 200 400 600 800 1000Ph

ase

sh

ift

(°)

Time (seconds)


50

Table 39: Calculated affinities of peptide P0389.


KD (nM) 3 909

± 1 751 2 859

± 1 277 3 046

± 1 393 2 711

± 1 217 3 739

± 1 732

Lower affinities for P0326 (higher µM range) were calculated than for P0389 (µM range).

According to the R2 values, the fitting of P0326 was better than the fitting of P0389. The

theoretical molecular weight of P0389 is 1 478 Da and of P0326 is 2 231 Da. Since SAW is a

microbalance technology, higher signals would be expected from the P0326 peptide

interaction. The phase signal of channel 1 of the 10 000 nM P0389 injection at 200s

amounted for 0.086° and for P0326 0.145°. A large variance was observed in the KD values of

P0326. The system seemed to be more robust for the experiment with P0389. However this

data should be interpreted carefully.

Table 40 gives an overview of the weighted KD values of all somatropin derived peptides.

Only 2 somatropin derived peptides gave possible interaction to hGHAb, however this was

an interesting experiment to investigate the capacity of the SAW biosensor to detect

interactions with low molecular weight peptides.

Table 40: Weighted means and SEM of the calculated affinities for P0326 and P0389.

Peptide P0326 P0389

KD (nM) 29 144

± 25 384 3 250 ± 539

4.4.4. SEC experiments

4.4.4.1. SEC analysis of P0320

Only two somatropin derived peptides showed possible binding to the hGHAb. However,

since some ambiguity arised with peptide P0320, a SEC confirmation experiment was

performed. Figure 33 represents a typical chromatogram obtained by injecting 8.75 µM

P0320, showing a second related impurity peak. Table 41 represents the corresponding

results.

51

Figure 33: SEC chromatogram of P0320.

An average retention time of 8.55 minutes was found for the main compound, what

corresponds to 21 244 Da according to the calibration model. The large deviation to the

molecular weight of 3 746 Da from the peptide P0320 could be attributed to errors in the

calibration model, but also on the different hydratation or shape effects which influence the

separation by SEC. The extra peak showed deviation in peak values, which was due to a

variable integration of the peak. However, this impurity was identified as the 44.1% purity as

determined with C18 UPLC analysis. Considering the DAD spectra, this are peptides as well

and can be related products of the P0320.

Table 41: SEC results of P0320.

RT Area Height

P0320

1 8.553 42 480 2 432

2 8.550 39 780 2 500

3 8.553 39 189 2 376

4 8.551 40 699 2 433

Average 8.55 40 537 2 435

SD 0.0015 1 437 51

Extra peak

1 9.640 24 931 713

2 9.587 19 888 615

3 9.547 12 210 344

4 9.490 17 097 535

Average 9.57 18 532 552

Mean 0.06 5 317 156

52

4.4.4.2. SEC analysis of mixtures of hGHAb and P0320

Figure 34 represents a chromatogram of the two injections of the sample consisting of 0.875

µM hGHAb and 8.75 µM P0320. The results of the SEC analyses with samples including both

hGHAb and P0320 were represented in Table 42.

Figure 34: SEC chromatogram of hGHAb and P0320.

Table 42: SEC results of hGHAb and P0320.

RT Area Height

Extra peak

1 6.163 47 189 1 369

2 6.224 55 324 1 490

Average 6.19 51 257 1 430

Mean 0.04 5 752 86

P0320

1 8.552 42 394 2 477

2 8.534 42 398 2 417

Average 8.54 42 396 2 447

SD 0.013 3 42

Extra peak

1 9.588 14 716 485

2 9.736 17 897 547

Average 9.66 16 307 516

Mean 0.10 2 249 44

Comparing both experiments indicated that no statistic significant difference between the

AUC and peak heights of both experiments was observed, what confirms the results of the

SAW experiment. Further investigation of the other peptides is necessary, but interaction

might not be visible due to a lacking sensitivity of SEC to detect interactions on the

micromolar level.

53

5. CONCLUSION AND PERSPECTIVES

The first goal of this project was to develop a selective immobilization procedure for the

ligand hGHAb. The used immobilization procedure is responsible for the ad random ligand

binding and has major influences on the observed phase signal and on the integrity of the

ligand immobilized chip. We have calculated that 15-35 % of the surface bound ligand

remained active, however this amount was sufficient to perform binding experiments.

The second goal was to develop robust operational conditions; however, an overall

relatively large variability in the results was observed. For example the calculated affinity

(KD) between channels for the somatropin experiment varied from 1 276 to 1 900 nM. The

standard error on the KD was high with relative standard errors ranging from 32 to 68%. In

addition to the within-measurement variability (between-channel), the between-

measurement variability was high as well, as demonstrated for the 1:10 NOTA-somatropin

sample (KD1: 1 725 nM and KD2: 365 nM). Therefore, the operational conditions should be

further optimized to improve reproducibility: attention must be paid to the quality of the

operations, of the materials and of the chip.

The third goal contained the quantitative binding characterization of NOTA-modified

somatropin and multiple somatropin derived peptides. Since the overall variability, it is

difficult to make biomedical relevant conclusions about the binding characteristics.

Nevertheless, our data indicates that the binding of the multiple modified forms are at least

similar than unmodified somatropin. The experiments with somatropin derived peptides

have to be interpreted even more carefully, because of the presence of impurities in almost

all peptide samples, which can have a major influence on the KD. Again, our pilot data

indicate a possible interaction between two of the peptides and hGHAb.

For the last goal, the observed binding in the SAW experiments was confirmed with size

exclusion chromatography. Binding of hGHAb was observed with somatropine and 1:1

NOTA-somatropin, but not for 1:3 and 1:10 NOTA derivates.

As a final conclusion, we can state that the SAW biosensor is a very promising instrument to

act as a functional quality characterization tool in the drug discovery process, but further

improvements, especially in robustness, are absolutely necessary.

54

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Attachments

LIST OF ATTACHMENTS

Attachment 1: Certificates of analysis of the somatropin derived peptides.

P0318

P0320

P0326

P0355

P0368

P0389

Attachment 2: Certificate of the Acquity UPLC BEH 300 C18 column.

Attachment 3: Certificates of Acquity UPLC BEH HILIC column.

Attachment 4: Certificate of the Phenomenex BioSep-SEC-S 2000 column.

Attachment 5: Data analysis of somatropin to hGHAb using GraphPad.

Attachment 6: Data analysis of 1:1 NOTA-somatropin to hGHAb using GraphPad.



Attachment 9: Data analysis of duplication 1:10 NOTA-somatropin to hGHAb using

GraphPad.

Attachment 10: Calculation of weighted means of the GraphPad analysed data.

Attachment 11: European Pharmacopoeia 7.0: reporting, identification and

qualification of organic impurities in active substances.

Attachments

Attachment 1: Certificates of analysis of the somatropin derived peptides.

P0318

Attachments

Attachments

P0320

Attachments

Attachments

P0326

Attachments

Attachments

P0355

Attachments

Attachments

P0368

Attachments

Attachments

P0389

Attachments

Attachments

Attachment 2: Certificate of the Acquity UPLC BEH 300 C18 column.

Attachments

Attachment 3: Certificate of the Acquity UPLC BEH HILIC column.

Attachments

Attachment 4: Certificate of the Phenomenex BioSep-SEC-S 2000 column.

Attachments

Attachment 5: Data analysis of somatropin to hGHAb using GraphPad.

Experiment performed on 12/10/2012.

Table A: Data after fitting in GraphPad.

Conc (nM) Kobs channel 1 Kobs channel 2 Kobs channel 3 Kobs channel 4 Kobs channel 5

75 0.009996 0.01181 0.01332 0.0155 0.01145

100 0.008529 0.01002 0.01001 0.01226 0.01043

150 0.01224 0.01317 0.01464 0.01376 0.01223

200 0.01459 0.01536 0.0176 0.01708 0.01387

250 0.01635 0.01801 0.01988 0.01865 0.01508

300 0.01611 0.01723 0.01834 0.01787 0.01495

500 0.009229 0.009475 0.008896 0.009791 0.01144

500 0.008621 0.009028 0.008178 0.00893 0.01083

550 0.0206 0.02127 0.02428 0.02381 0.01779

600 0.0208 0.02159 0.0245 0.02378 0.01799

750 0.02248 0.02383 0.02558 0.02515 0.01868

900 0.01737 0.01831 0.01909 0.01921 0.01726

1000 0.01732 0.01906 0.01941 0.01911 0.01818

500 0.01088 0.01089 0.01049 0.01119 0.0118

Attachments

Table B: Statistical analysis of the non-linear regression on the association curves of somatropin to hGHAb interaction.

Channel 1

75 nM 100 nM 150 nM 200 nM 250 nM 300 nM 500 nM 500 nM 550 nM 600 nM 750 nM 900 nM 1000 nM 500 nM

Dgr. free. (1)

403 403 403 403 403 403 403 403 403 403 403 403 403 403

R2 0.9675 0.9793 0.9876 0.986 0.9863 0.9863 0.9934 0.9932 0.9839 0.9835 0.9838 0.9821 0.9799 0.9525

Abs SS (2) 0.005913 0.00505 0.009485 0.01634 0.02194 0.02572 0.01692 0.01479 0.04889 0.05418 0.06763 0.06785 0.1439 0.05335

Sy.x (3) 0.003831 0.00354 0.004852 0.006368 0.007378 0.007989 0.00648 0.006059 0.01101 0.01159 0.01295 0.01298 0.0189 0.01151

Channel 2


Dgr. free. (1) 403 403 403 403 403 403 403 403 403 403 403 403 403 403

R2 0.9681 0.9748 0.9853 0.9866 0.9862 0.986 0.9927 0.9925 0.9865 0.9867 0.9849 0.9859 0.9838 0.9762

Abs SS (2) 0.005196 0.005175 0.008381 0.01126 0.01563 0.01764 0.01215 0.0106 0.02745 0.02899 0.04169 0.03512 0.07213 0.01828

Sy.x (3) 0.003591 0.003583 0.00456 0.005285 0.006227 0.006615 0.00549 0.00513 0.008254 0.008482 0.01017 0.009335 0.01338 0.006735

Channel 3


Dgr. free. (1) 403 403 403 403 403 403 403 403 403 403 403 403 403 403

R2 0.9488 0.9645 0.983 0.9858 0.9869 0.9876 0.9933 0.9927 0.987 0.9877 0.9876 0.9858 0.9841 0.9812

Abs SS (2) 0.003022 0.002816 0.004533 0.005903 0.007648 0.007888 0.005615 0.00514 0.01411 0.01425 0.01866 0.01894 0.03982 0.00735

Sy.x (3) 0.002738 0.002643 0.003354 0.003827 0.004356 0.004424 0.003733 0.003571 0.005916 0.005946 0.006805 0.006856 0.00994 0.004271

Channel 4


Dgr. free. (1) 403 403 403 403 403 403 403 403 403 403 403 403 403 403

R2 0.9504 0.9651 0.9829 0.9877 0.9897 0.9893 0.9935 0.9938 0.9886 0.9899 0.9882 0.9876 0.9848 0.9863

Abs SS (2) 0.002216 0.002205 0.003467 0.003911 0.004625 0.005293 0.004562 0.003661 0.009899 0.009167 0.01423 0.01339 0.03109 0.004754

Sy.x (3) 0.002345 0.002339 0.002933 0.003115 0.003388 0.003624 0.003365 0.003014 0.004956 0.004769 0.005942 0.005763 0.008784 0.003435

Channel 5


Dgr. free. (1) 402 402 402 402 402 402 402 402 402 402 402 402 402 402

R2 0.9707 0.9787 0.9856 0.9882 0.9891 0.9887 0.9922 0.9925 0.9895 0.9902 0.9902 0.9899 0.9886 0.9901

Abs SS (2) 0.014 0.01303 0.01723 0.01945 0.02261 0.02669 0.02476 0.02123 0.03704 0.03734 0.04565 0.04477 0.08264 0.01864

Sy.x (3) 0.005902 0.005694 0.006547 0.006956 0.0075 0.008148 0.007848 0.007267 0.009599 0.009638 0.01066 0.01055 0.01434 0.006809

(1) Degrees of freedom (2) Absolute sum of squares (3) Standard error or estimate

Attachments

Table C: Outlier method Grubb’s test on data somatropin to hGHAb interaction.

Concentration Channel 1 Channel 2 Channel 3

(in nM) Kobs-y G Kobs-y G Kobs-y G

75 -0.001241934 0.384598548 -0.000517 0.17284615 -0.000282216 0.052123748

100 -0.002916833 0.785494519 -0.002512 0.624406775 -0.00379777 0.701426696

150 0.00037837 0.003229661 0.0002268 0.004641038 0.000421122 0.077778886

200 0.002312572 0.466191247 0.0020057 0.397892677 0.002970014 0.548544898

250 0.003656774 0.787933191 0.0042445 0.904516736 0.004838907 0.893718749

300 0.003000976 0.63096449 0.0030534 0.634988882 0.002887799 0.533360169

500 -0.005543215 1.414133183 -0.006346 1.491945888 -0.008200632 1.514610408

500 -0.006151215 1.559661219 -0.006793 1.593094548 -0.008918632 1.647220954

550 0.005411987 1.208052771 0.0050379 1.084039465 0.00677226 1.250798254

600 0.005196189 1.156400412 0.0049468 1.063423304 0.006581153 1.215501737

750 0.005628796 1.259947083 0.0059535 1.291217516 0.006427829 1.187183813

900 -0.000728598 0.261728889 -0.0008 0.236947118 -0.001295494 0.239270368

1000 -0.001610194 0.472743502 -0.000872 0.253288272 -0.001797709 0.332026725

500 -0.003892215 1.018957545 -0.004931 1.171754939 -0.006606632 1.220207608

Average (Kobs-y) 0.000364876 0.0002473 -2.72599E-18

St Dev 0.004177889 0.0044192 0.005414351

Table C: Outlier method Grubb’s test on data somatropin to hGHAb interaction (continued).

Channel 4 Channel 5

Kobs-y G Kobs-y G

0.001359604 0.282857036 -0.000198199 0.089157442

-0.002059388 0.428442629 -0.001400853 0.630155632

-0.000917374 0.1908538 3.38399E-05 0.015222451

0.002044641 0.425374434 0.001308533 0.588626599

0.003256655 0.677526317 0.002153226 0.968600793

0.002118669 0.440775672 0.001657919 0.745793274

-0.007392273 1.537915263 -0.00331331 1.490449729

-0.008253273 1.717040827 -0.00392331 1.76485036

0.006268742 1.304171756 0.002671383 1.201687158

0.005880756 1.223453833 0.002506076 1.127325882

0.006176799 1.285043761 0.002100154 0.944727392

-0.000837157 0.174165237 -0.000415767 0.187027377

-0.001653128 0.343922828 -0.000226381 0.101834637

-0.005993273 1.246862226 -0.00295331 1.328508373

-9.91271E-19 -2.47818E-18

0.004806684 0.002223027

The critical G value (P=0.05) for a sample size 14 is 2.5073. The outliers as identified by the Grubb’s test and Dixon’s test are shown in blue.

Attachments

y = 0.0000089x + 0.0106142 R² = 0.2925078

0.0000

0.0050

0.0100

0.0150

0.0200

0.0250

0 200 400 600 800 1000 1200

Ko

bs

Concentration analyte (nM)

Channel 1

y = 0.0000086x + 0.0117099 R² = 0.2616435

0.0000

0.0050

0.0100

0.0150

0.0200

0.0250

0 200 400 600 800 1000 1200

Ko

bs


Channel 2

y = 0.0000082x + 0.0129856 R² = 0.1648493

0.0000

0.0050

0.0100

0.0150

0.0200

0.0250

0 200 400 600 800 1000 1200

Ko

bs


Channel 3

y = 0.00000716x + 0.01360342 R² = 0.15959901

0.0000

0.0050

0.0100

0.0150

0.0200

0.0250

0 200 400 600 800 1000 1200

Ko

bs


Channel 4

y = 0.0000073x + 0.0111002 R² = 0.4803981

0.0000

0.0050

0.0100

0.0150

0.0200

0.0250

0 200 400 600 800 1000 1200

Ko

bs


Channel 5

Attachments



Table D: Data after fitting in GraphPad.


75 0.6948 0.01385 0.01374 0.01249 0.01331

100 0.01295 0.01436 0.01406 0.01394 0.01559

150 0.01453 0.0166 0.01605 0.01507 0.01726

200 0.01472 0.01657 0.01546 0.01438 0.01855

250 0.01947 0.02091 0.01975 0.01761 0.02027

300 0.02463 0.02415 0.02259 0.01968 0.0218

500 0.02473 0.02425 0.02236 0.01989 0.02347

500 0.0265 0.02573 0.02346 0.02095 0.02374

550 0.03654 0.03146 0.02937 0.025 0.02567

600 0.03412 0.03042 0.02686 0.02295 0.0255

750 0.04526 0.03442 0.03069 0.02571 0.02751

900 0.04263 0.03475 0.03185 0.02664 0.02819

1000 0.04322 0.03536 0.03193 0.02724 0.02864

500 0.2397 0.04318 0.03517 0.02624 0.02493

Attachments

Table E: Statistical analysis of the non-linear regression on the association curves of 1:1 NOTA-somatropin to hGHAb interaction.

Channel 1


Dgr. free. (1)

403 403 403 403 403 403 403 403 403 403 403 403 403 403

R2 0.6968 0.9612 0.965 0.969 0.9606 0.9562 0.9627 0.9604 0.9579 0.9591 0.959 0.9617 0.9632 0.96

Abs SS (2) 0.07377 0.02902 0.0326 0.06871 0.08559 0.1095 0.1638 0.1611 0.1616 0.1756 0.1882 0.2177 0.2196 0.1056

Sy.x (3) 0.01353 0.008486 0.008994 0.01306 0.01457 0.01649 0.02016 0.01999 0.02002 0.02087 0.02161 0.02324 0.02334 0.01619

Channel 2


Dgr. free. (1) 402 402 402 402 402 402 402 402 402 402 402 402 402 402

R2 0.9634 0.9709 0.9762 0.9795 0.9775 0.9762 0.9799 0.9774 0.9772 0.9778 0.9782 0.9789 0.9804 0.9741

Abs SS (2) 0.0105 0.01788 0.01755 0.03267 0.0351 0.04145 0.05913 0.06176 0.06028 0.0645 0.06843 0.08032 0.07878 0.0485

Sy.x (3) 0.005111 0.006669 0.006608 0.009015 0.009344 0.01015 0.01213 0.0124 0.01225 0.01267 0.01305 0.01414 0.014 0.01098

Channel 3


Dgr. free. (1) 403 403 403 403 403 403 403 403 403 403 403 403 403 403

R2 0.9615 0.9725 0.9768 0.9813 0.9817 0.9796 0.9824 0.9803 0.9794 0.981 0.9803 0.9808 0.9818 0.9768

Abs SS (2) 0.004507 0.007604 0.007393 0.01446 0.01302 0.01644 0.02543 0.02647 0.0269 0.02808 0.03189 0.03927 0.03985 0.02208

Sy.x (3) 0.003344 0.004344 0.004283 0.00599 0.005683 0.006387 0.007944 0.008105 0.00817 0.008347 0.008896 0.009872 0.009944 0.007403

Channel 4


Dgr. free. (1) 403 403 403 403 403 403 403 403 403 403 403 403 403 403

R2 0.9656 0.9762 0.9831 0.9867 0.987 0.9867 0.9882 0.9865 0.9838 0.9863 0.9847 0.9859 0.9872 0.9826

Abs SS (2) 0.00329 0.005051 0.004195 0.007784 0.007192 0.008327 0.01318 0.014 0.01681 0.0159 0.01983 0.02286 0.02233 0.01332

Sy.x (3) 0.002857 0.00354 0.003227 0.004395 0.004224 0.004546 0.00572 0.005894 0.006459 0.006281 0.007014 0.007531 0.007444 0.00575

Channel 5


Dgr. free. (1) 403 403 403 403 403 403 403 403 403 403 403 403 403 403

R2 0.9819 0.9845 0.9875 0.9868 0.9881 0.9882 0.9884 0.9876 0.9872 0.9879 0.9872 0.9875 0.9879 0.9873

Abs SS (2) 0.01662 0.02719 0.02684 0.04687 0.0442 0.04787 0.06815 0.06839 0.0714 0.07314 0.08256 0.09289 0.09289 0.05495

Sy.x (3) 0.006422 0.008214 0.008161 0.01078 0.01047 0.0109 0.013 0.01303 0.01331 0.01347 0.01431 0.01518 0.01518 0.01168


Attachments

Table F: Outlier method Grubb’s test on data 1:1 NOTA-somatropin to hGHAb interaction.



75 0.515717168 11.39368064 -0.002194 0.818485766 -0.0017846 0.499734445

100 -0.16716867 0.267282047 -0.002229 0.825043133 -0.0020092 0.562623964

150 -0.167660346 0.27567791 -0.001078 0.606822303 -0.0011083 0.310363149

200 -0.169542022 0.307809422 -0.002197 0.819037317 -0.0027875 0.780578494

250 -0.166863698 0.262074346 0.0010536 0.202615926 0.00041335 0.115750216

300 -0.163775374 0.209338107 0.0032044 0.205224219 0.00216419 0.606036123

500 -0.171962078 0.349134317 -0.001052 0.601919588 -0.0024225 0.678362383

500 -0.170192078 0.318909786 0.0004278 0.321283002 -0.0013225 0.370329911

550 -0.162223754 0.182842639 0.0050686 0.558709236 0.00349837 0.979646621

600 -0.16671543 0.259542526 0.0029394 0.154978714 -0.0001008 0.028225403

750 -0.161790459 0.175443677 0.0036719 0.293876669 0.00046172 0.12929387

900 -0.170635487 0.32648143 0.0007344 0.263128261 -0.0016458 0.460865674

1000 -0.174188839 0.387158492 -0.000834 0.560513348 -0.0037441 1.048459171

500 0.043007922 3.321694698 0.0178778 2.987574039 0.01038753 2.908815764

Average (Kobs-y) -0.151516178

0.0021221

-1.363E-18

St. Dev. 0.058561703

0.0052737

0.00357105

Table F: Outlier method Grubb’s test on data 1:1 NOTA-somatropin to hGHAb interaction

(continued).

Channel 4 Channel 5

Kobs-y G Kobs-y G

-0.001816144 0.902130522 -0.003195437 2.08053433

-0.00077696 0.385938509 -0.00130677 0.850831692

-0.000468594 0.232764142 -0.000419435 0.273092292

-0.001980228 0.983635867 8.78993E-05 0.057230834

0.000428138 0.212668605 0.001025234 0.667525007

0.001676505 0.832767875 0.001772568 1.154111043

-0.00140003 0.695435017 0.000311906 0.203080396

-0.00034003 0.168902678 0.000581906 0.37887617

0.002888336 1.434719263 0.00172924 1.125900389

1.67025E-05 0.008296614 0.000776575 0.505624145

0.000311801 0.154880682 0.000438578 0.28555597

-0.0012231 0.607548627 -0.001229419 0.800469165

-0.002266367 1.125769406 -0.00234475 1.52665624

0.00494997 2.458791729 0.001771906 1.153679765

1.363E-18

-2.8499E-18

0.002013172

0.001535873

The critical value of G (P= 0.05) for a sample size 14 is 2.5073. The outliers as identified by the Grubb’s test and Dixon’s test are shown in red.

Attachments

y = 0.0000380x + 0.0098868 R² = 0.9023988

0.0000

0.0200

0.0400

0.0600

0 200 400 600 800 1000 1200

Ko

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Channel 1

y = 0.0000251x + 0.0134994 R² = 0.9195805

0.0000

0.0100

0.0200

0.0300

0.0400

0.0500

0 200 400 600 800 1000 1200

Ko

bs


Channel 2

y = 0.0000213x + 0.0132950 R² = 0.9110390

0.0000

0.0100

0.0200

0.0300

0.0400

0 200 400 600 800 1000 1200

Ko

bs


Channel 3

y = 0.00001643x + 0.01307369 R² = 0.85081169

0.0000

0.0100

0.0200

0.0300

0.0400

0 200 400 600 800 1000 1200

Ko

bs


Channel 4

y = 0.0000157x + 0.0153314 R² = 0.8988969

0.0000

0.0100

0.0200

0.0300

0.0400

0 200 400 600 800 1000 1200

Ko

bs


Channel 5

Attachments



Table G: Data after fitting in GraphPad.


75 0.008914 0.01333 0.0003836 0.0082 0.007643

100 0.008832 0.01122 0.003959 0.00612 0.008473

150 0.007325 0.008683 0.006018 0.007252 0.008843

200 0.007258 0.008566 0.006703 0.007514 0.00982

250 0.00864 0.01035 0.008434 0.00909 0.01112

300 0.009204 0.01104 0.009294 0.0101 0.01227

500 0.01223 0.01441 0.01232 0.01302 0.01523

500 0.01244 0.01438 0.01287 0.01373 0.01482

550 0.01265 0.0152 0.01315 0.01453 0.0151

600 0.01344 0.01611 0.01453 0.0159 0.0166

750 0.0132 0.01581 0.01354 0.01438 0.01768

900 0.01499 0.01707 0.01541 0.01572 0.01573

1000 0.02071 0.02333 0.01959 0.01982 0.02042

Attachments

Table H: Statistical analysis of the non-linear regression on the association curves of 1:3 NOTA-somatropin to hGHAb interaction.

Channel 1

75 nM 100 nM 150 nM 200 nM 250 nM 300 nM 500 nM 500 nM 550 nM 600 nM 750 nM 900 nM 1000 nM

Dgr. free. (1)

403 403 403 403 403 403 403 403 403 403 403 403 403

R2 0.8502 0.9387 0.9851 0.9942 0.9935 0.9939 0.9936 0.9938 0.9918 0.9919 0.9877 0.9824 0.9717

Abs SS (2) 0.004987 0.006251 0.008053 0.005404 0.006506 0.006111 0.01322 0.01184 0.01257 0.01553 0.03261 0.05552 0.1033

Sy.x (3) 0.003518 0.003938 0.00447 0.003662 0.004018 0.003894 0.005728 0.00542 0.005586 0.006208 0.008995 0.01174 0.01601

Channel 2


Dgr. free. (1) 403 403 403 403 403 403 403 403 403 403 403 403 403

R2 0.8197 0.9325 0.9854 0.9925 0.9914 0.9919 0.9925 0.9932 0.99 0.9899 0.9876 0.9848 0.9825

Abs SS (2) 0.002701 0.004165 0.005003 0.004383 0.005622 0.005143 0.009389 0.007802 0.009677 0.01235 0.02071 0.02889 0.04028

Sy.x (3) 0.002589 0.003215 0.003523 0.003298 0.003735 0.003572 0.004827 0.0044 0.0049 0.005537 0.007168 0.008467 0.009998

Channel 3


Dgr. free. (1) 402 402 402 402 402 402 402 402 402 402 402 402 402

R2 0.7961 0.9353 0.9878 0.9935 0.9932 0.9933 0.9939 0.9949 0.9909 0.9899 0.9892 0.9869 0.9859

Abs SS (2) 0.001464 0.001673 0.002336 0.002156 0.002391 0.002114 0.003823 0.00291 0.004426 0.006552 0.009505 0.01373 0.01743

Sy.x (3) 0.001908 0.00204 0.002411 0.002316 0.002439 0.002293 0.003084 0.002691 0.003318 0.004037 0.004862 0.005844 0.006585

Channel 4


Dgr. free. (1) 403 403 403 403 403 403 403 403 403 403 403 403 403

R2 0.8374 0.9384 0.9847 0.9922 0.9902 0.9916 0.9923 0.9941 0.9897 0.9869 0.9881 0.9878 0.988

Abs SS (2) 0.001681 0.001644 0.002687 0.002279 0.003058 0.002261 0.004052 0.002717 0.0042 0.00736 0.008708 0.01062 0.01231

Sy.x (3) 0.002042 0.00202 0.002582 0.002378 0.002755 0.002369 0.003171 0.002597 0.003228 0.004273 0.004648 0.005132 0.005527

Channel 5


Dgr. free. (1) 403 403 403 403 403 403 403 403 403 403 403 403 403

R2 0.9326 0.9718 0.986 0.9901 0.9894 0.9908 0.9913 0.9913 0.9907 0.9891 0.9883 0.9895 0.9888

Abs SS (2) 0.007103 0.008721 0.01291 0.01466 0.0188 0.01594 0.02505 0.02367 0.02259 0.03215 0.04523 0.03817 0.05328

Sy.x (3) 0.004198 0.004652 0.005659 0.006032 0.00683 0.006288 0.007885 0.007663 0.007487 0.008932 0.01059 0.009733 0.0115


Attachments

Table I: Outlier method Grubb’s test on data 1:3 NOTA-somatropin to hGHAb interaction.



75 0.001666586 1.667077701 0.00354 3.505167376 -0.0039261 2.260756458

100 0.001278801 1.368512216 0.0010209 2.072663229 -0.0007598 0.437507472

150 -0.000839771 0.262626538 -0.002334 0.164721603 0.00048109 0.277022579

200 -0.001518342 0.785074891 -0.003269 0.367045732 0.00034798 0.200373887

250 -0.000747914 0.191903529 -0.002303 0.182223019 0.00126087 0.726034486

300 -0.000795485 0.228529909 -0.002432 0.109370003 0.00130276 0.750154557

500 -0.000215771 0.217805969 -0.002334 0.164844849 0.00105631 0.608244739

500 -5.77078E-06 0.379489986 -0.002364 0.147784837 0.00160631 0.924946565

550 -0.000407342 0.070310549 -0.002362 0.148858539 0.0010682 0.615090165

600 -0.000228914 0.207686969 -0.00227 0.201112277 0.00163008 0.938637416

750 -0.002303628 1.389685123 -0.005025 1.365187708 -0.0018143 1.044685131

900 -0.002348342 1.42411172 -0.006219 2.044367075 -0.0023986 1.381158185

1000 0.002148515 2.038126021 -0.001595 0.585022159 0.00014519 0.083602851

Average (Kobs-y) -0.000498664

-0.002624

-1.268E-18

stdev 0.00129883

0.0017585

0.00173665

Table I: Outlier method Grubb’s test on data 1:3 NOTA-somatropin to hGHAb interaction

(continued).

Channel 4 Channel 5

Kobs-y G Kobs-y G

0.001190119 0.943289814 -0.001046208 0.852883426

-0.001217675 0.965130752 -0.000526358 0.429094157

-0.000741262 0.58752529 -0.000776657 0.633141213

-0.001134849 0.899483044 -0.000419956 0.342353591

-0.000214436 0.169962561 0.000259745 0.211748037

0.000139976 0.11094553 0.000789447 0.643567619

0.000437628 0.346864331 0.001268251 1.03389558

0.001147628 0.909611323 0.000858251 0.699657988

0.001292041 1.024073121 0.000517952 0.422241704

0.002006453 1.590317715 0.001397653 1.13938606

-0.001480308 1.173294367 0.000616757 0.502788482

-0.00210707 1.670066454 -0.00319414 2.603906423

0.000681756 0.540360635 0.000255262 0.208093339

-7.33921E-19

-2.0016E-19

0.001261668

0.001226672

The critical value of G (P= 0.05) for a sample size 13 is 2.4620. The outliers as identified by the Grubb’s test and Dixon’s test are shown in blue.

Attachments

y = 0.0000122x + 0.0058314 R² = 0.8852277

0.0000

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Channel 1

y = 0.0000133x + 0.0074343 R² = 0.8713845

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Channel 2

y = 0.0000164x + 0.0030826 R² = 0.8914860

0.0000

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Channel 3

y = 0.00001311x + 0.00602650 R² = 0.90905246

0.0000

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Channel 4

y = 0.0000141x + 0.0073052 R² = 0.9764270

0.0000

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Channel 5

Attachments



Table J: Data after fitting in GraphPad.


100 0.005574 0.004009 0.004681 0.005794 0.002198

150 0.01362 0.01476 0.01581 0.01374 0.01017

200 0.01557 0.01619 0.016 0.01541 0.01017

250 0.02244 0.02509 0.031 0.02179 0.01418

300 0.01636 0.01604 0.01476 0.01316 0.011

500 0.01845 0.01738 0.016 0.01377 0.01195

500 0.01946 0.01818 0.01623 0.01464 0.01195

600 0.02219 0.01972 0.01752 0.01603 0.01306

750 0.02485 0.02207 0.02013 0.01865 0.0144

1000 0.02429 0.02081 0.01906 0.01736 0.01427

500 0.1474 0.02332 0.01977 0.01575 0.01243

Attachments

Table K: Statistical analysis of the non-linear regression on the association curves of 1:10 NOTA-somatropin to hGHAb interaction. Channel 1

100 nM 150 nM 200 nM 250 nM 300 nM 500 nM 500 nM 600 nM 750 nM 1000 nM 500 nM

Degr. free. (1)

403 403 403 403 403 403 403 403 403 403 403

R2 0.856000 0.937500 0.924800 0.954600 0.948300 0.963600 0.957100 0.959900 0.969300 0.971000 0.936800

Abs SS (2) 0.002895 0.007656 0.015900 0.018930 0.038990 0.052810 0.064130 0.064000 0.071210 0.088410 0.072130

Sy.x (3) 0.002680 0.004359 0.006282 0.006853 0.009836 0.011450 0.012620 0.012600 0.013290 0.014810 0.013380

Channel 2


Degr. free. (1) 403 403 403 403 403 403 403 403 403 403 403

R2 0.837600 0.94900 0.955700 0.975600 0.973200 0.980200 0.976900 0.980000 0.98480 0.985700 0.966100

Abs SS (2) 0.001413 0.003751 0.005526 0.005639 0.01205 0.01737 0.02085 0.01937 0.02172 0.027630 0.0245700

Sy.x (3) 0.001873 0.003051 0.003703 0.003741 0.005467 0.006566 0.007192 0.006932 0.007341 0.008281 0.007808

Channel 3


Degr. free. (1) 404 404 404 404 404 404 404 404 404 404 404

R2 0.587100 0.926600 0.943800 0.952400 0.973400 0.984200 0.981500 0.982000 0.986900 0.987600 0.974400

Abs SS (2) 0.001878 0.003027 0.004248 0.006060 0.007197 0.008596 0.010280 0.010520 0.011930 0.015690 0.011600

Sy.x (3) 0.002156 0.002737 0.003243 0.003873 0.004221 0.004613 0.005045 0.005102 0.005434 0.006231 0.005359

Channel 4


Degr. free. (1) 404 404 404 404 404 404 404 404 404 404 404

R2 0.649000 0.945100 0.957400 0.965600 0.983000 0.989200 0.984700 0.98910 0.992600 0.991300 0.98100

Abs SS (2) 0.001666 0.001907 0.00278 0.003399 0.003738 0.004665 0.006873 0.00499 0.005399 0.008841 0.00705

Sy.x (3) 0.002031 0.002173 0.002623 0.0029 0.003042 0.003398 0.004124 0.003514 0.003656 0.004678 0.004177

Channel 5


Degr. free. (1) 404 404 404 404 404 404 404 404 404 404 404

R2 0.916400 0.963100 0.973500 0.985800 0.985600 0.990500 0.990300 0.990400 0.993300 0.99300 0.988300

Abs SS (2) 0.001440 0.006707 0.007579 0.00689 0.01165 0.01389 0.01473 0.01521 0.01513 0.02094 0.01519

Sy.x (3) 0.001888 0.004074 0.004331 0.00413 0.00537 0.005864 0.006039 0.006135 0.00612 0.007199 0.006132


Attachments

Table L: Outlier method Grubb’s test on data 1:10 NOTA-somatropin to hGHAb interaction.



100 -0.014738701 0.513986678 -0.009655 4.124500919 -0.0105725 1.791289814

150 -0.007514265 0.334837945 0.0007873 0.819130256 0.00024753 0.041938253

200 -0.006385829 0.306855439 0.0019083 0.464272748 0.00012856 0.021782031

250 -0.000337394 0.156868695 0.0104994 2.255173674 0.0148196 2.51086992

300 -0.007238958 0.328010992 0.0011404 0.70735728 -0.0017294 0.293005462

500 -0.008435215 0.357675316 0.0012445 0.674393035 -0.0017252 0.292304411

500 -0.007425215 0.33262973 0.0020445 0.421157275 -0.0014952 0.253335731

600 -0.006338344 0.305677921 0.0029666 0.129281263 -0.0008232 0.139467748

750 -0.006143037 0.300834776 0.0043897 0.321194543 0.00085994 0.145698831

1000 -0.010810859 0.416585597 0.0015849 0.566658847 -0.0017549 0.297328946

500 0.120514785 2.83997641 0.0071845 1.205882487 0.00204477 0.346443077

Average (Kobs-y) 0.005988567 0.003375 -3.154E-18

St dev 0.040326468 0.0031591 0.00590218

Table L: Outlier method Grubb’s test on data 1:10 NOTA-somatropin to hGHAb interaction

(continued).

Channel 4 Channel 5

Kobs-y G Kobs-y G

-0.007090913 1.997535272 -0.006434581 2.505344563

0.000530287 0.14938384 0.001126491 0.43860637

0.001875488 0.528331597 0.000715563 0.27860891

0.007930689 2.234102981 0.004314635 1.679930198

-0.001024111 0.288495621 0.000723707 0.281779716

-0.001713308 0.48264502 2.9994E-05 0.011678357

-0.000843308 0.237562948 2.9994E-05 0.011678357

-0.000102907 0.028989317 0.000318138 0.123868926

0.001542695 0.434582518 0.000425353 0.165613983

-0.001371302 0.386300725 -0.001759287 0.684989636

0.000266692 0.07512797 0.000509994 0.19856938

-1.97128E-18 -4.73106E-19

0.003549831 0.002568342

The critical G value (P=0.05) for a sample size 11 is 2.3547. The outliers as identified by the Grubb’s test and Dixon’s test are shown in blue.

Attachments

y = 0.0000158x + 0.0114211 R² = 0.6107206

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Channel 1

y = 0.0000081x + 0.0146637 R² = 0.5473450

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Channel 2

y = 0.0000105x + 0.0111626 R² = 0.4597031 0.0000

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Channel 3

y = 0.00000501x + 0.01288435 R² = 0.55687816

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Channel 4

y = 0.00000440x + 0.01026988 R² = 0.52143752

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Channel 5

Attachments

Attachment 9: Data analysis of duplication 1:10 NOTA-somatropin to hGHAb using

GraphPad.


Table M: Data after fitting in GraphPad.


75 4.20E-07 0.001819 0.002199 0.002576 0.005347

100 0.004344 0.005949 0.005177 0.00551 0.009525

150 0.006284 0.007567 0.007159 0.007006 0.01305

200 0.001212 0.005516 0.005115 0.005628 0.01209

250 0.006827 0.008483 0.007852 0.008513 0.01645

300 0.00691 0.008443 0.007673 0.008087 0.01701

500 0.009186 0.01076 0.0104 0.01117 0.01933

500 0.009107 0.01083 0.01055 0.01149 0.01974

550 0.00866 0.01058 0.01047 0.01143 0.02003

600 0.009274 0.01117 0.01054 0.01158 0.02067

750 0.01065 0.01266 0.01212 0.0135 0.02208

900 0.01219 0.0146 0.0141 0.01573 0.02392

1000 0.01324 0.01545 0.01538 0.01619 0.02423

500 0.01507 0.01772 0.0195 0.02092 0.02504

Attachments

Table N: Statistical analysis of the non-linear regression on the association curves of duplication of 1:10 NOTA-somatropin to hGHAb interaction.

Channel 1


Dgr. free. (1)

403 403 403 403 403 403 403 403 403 403 403 403 403 403

R2 0.9828 0.9756 0.9436 0.9738 0.936 0.9424 0.9757 0.9708 0.9587 0.9738 0.9853 0.9917 0.991 0.9875

Abs SS (2) 0.04613 0.02289 0.03624 0.06099 0.07706 0.0925 0.08159 0.08864 0.1021 0.08169 0.0519 0.03757 0.04087 0.02457

Sy.x (3) 0.0107 0.007537 0.009482 0.0123 0.01383 0.01515 0.01423 0.01483 0.01591 0.01424 0.01135 0.009656 0.01007 0.007809

Channel 2


Dgr. free. (1) 402 402 402 402 402 402 402 402 402 402 402 402 402 402

R2 0.9919 0.9853 0.9787 0.9866 0.9801 0.984 0.9917 0.9914 0.9888 0.992 0.9921 0.9917 0.9899 0.9864

Abs SS (2) 0.005732 0.008283 0.0093 0.0136 0.01452 0.01559 0.01657 0.01547 0.01702 0.01533 0.01731 0.02344 0.02939 0.01839

Sy.x (3) 0.003776 0.004539 0.00481 0.005816 0.006009 0.006228 0.006421 0.006204 0.006506 0.006175 0.006562 0.007636 0.008551 0.006764

Channel 3


Dgr. free. (1) 403 403 403 403 403 403 403 403 403 403 403 403 403 403

R2 0.9922 0.9846 0.9805 0.9878 0.9792 0.9868 0.9912 0.9922 0.9912 0.9941 0.9926 0.9906 0.9859 0.9781

Abs SS (2) 0.003093 0.004192 0.0035 0.005907 0.005734 0.005397 0.007577 0.005989 0.005836 0.00511 0.007632 0.013 0.02066 0.01261

Sy.x (3) 0.00277 0.003225 0.002947 0.003828 0.003772 0.00366 0.004336 0.003855 0.003805 0.003561 0.004352 0.00568 0.00716 0.005594

Channel 4


Dgr. free. (1) 403 403 403 403 403 403 403 403 403 403 403 403 403 403

R2 0.9938 0.9885 0.9844 0.9905 0.9868 0.9928 0.9928 0.9937 0.9931 0.9943 0.9931 0.9918 0.9882 0.9838

Abs SS (2) 0.001911 0.002552 0.002203 0.003319 0.002596 0.002165 0.004363 0.003351 0.003314 0.003586 0.005044 0.008248 0.01292 0.00683

Sy.x (3) 0.002178 0.002516 0.002338 0.00287 0.002538 0.002318 0.00329 0.002884 0.002868 0.002983 0.003538 0.004524 0.005662 0.004117

Channel 5


Dgr. free. (1) 403 403 403 403 403 403 403 403 403 403 403 403 403 403

R2 0.9911 0.9892 0.9924 0.9872 0.9892 0.9886 0.9877 0.9887 0.9883 0.9876 0.9873 0.9869 0.9853 0.9867

Abs SS (2) 0.01085 0.01514 0.01059 0.03034 0.02313 0.02958 0.05324 0.04642 0.04308 0.05468 0.06068 0.0754 0.08755 0.04745

Sy.x (3) 0.005188 0.00613 0.005125 0.008677 0.007576 0.008567 0.01149 0.01073 0.01034 0.01165 0.01227 0.01368 0.01474 0.01085


Attachments

Table O: Outlier method Grubb’s test on data duplication of 1:10 NOTA-somatropin to hGHAb interaction.



75 -0.003450776 1.937018337 -0.00371 1.790517098 -0.0030379 1.084798224

100 0.000635017 0.164351418 0.0001152 0.050197119 -0.0003647 0.130213939

150 0.002059442 0.453651448 0.0011236 0.40859954 0.00100778 0.359871016

200 -0.003528132 1.970580098 -0.001537 0.801851477 -0.0016458 0.58769643

250 0.001571293 0.241862509 0.0008205 0.270686014 0.00048165 0.171992987

300 0.001138719 0.054185212 0.0001709 0.024840751 -0.0003069 0.109597875

500 0.00135242 0.146902108 4.967E-05 0.080012276 -1.818E-05 0.006493559

500 0.00127342 0.112627077 0.0001197 0.048165087 0.00013182 0.047070242

550 0.000310846 0.304996631 -0.00074 0.439233421 -0.0005578 0.199168512

600 0.000409271 0.262293655 -0.000759 0.448135483 -0.0010973 0.391843465

750 0.000238548 0.336364025 -0.001098 0.602230429 -0.001346 0.480652282

900 0.000231824 0.339281166 -0.000987 0.551593444 -0.0011947 0.426624298

1000 0.000250675 0.3311025 -0.001356 0.719534319 -0.0011339 0.404889322

500 0.00723642 2.699741139 0.0070097 3.086508252 0.00908182 3.24304366

Average (Kobs-y) 0.001013828

0.0002255

0

St. Dev. 0.002304885

0.002198

0.0028004

Table O: Outlier method Grubb’s test on data duplication of 1:10 NOTA-somatropin to hGHAb

interaction (continued).

Channel 4 Channel 5

Kobs-y G Kobs-y G

-0.002972253 1.011262784 -0.005712859 2.004031402

-0.000374658 0.127471724 -0.001974643 0.692691081

0.00044853 0.152605258 0.000670789 0.23530821

-0.001602282 0.54515165 -0.001168779 0.409999446

0.000609906 0.207511022 0.002311654 0.810912063

-0.000488906 0.166342663 0.001992086 0.698809883

-9.71535E-05 0.033054957 0.000793814 0.27846461

0.000222847 0.075820076 0.001203814 0.422289772

-0.000509965 0.17350779 0.000614247 0.215473461

-0.001032777 0.351386416 0.000374679 0.131434728

-0.001131213 0.38487761 -0.000854025 0.299585942

-0.000919648 0.312896116 -0.001652728 0.57976559

-0.001805272 0.61421585 -0.003101864 1.088112341

0.009652847 3.284231204 0.006503814 2.281493074

-1.73472E-18

1.23909E-18

0.00293915

0.002850683

The critical value of G (P= 0.05) for a sample size 14 is 2.5073. The outliers as identified by the Grubb’s test and Dixon’s test are shown in blue.

Attachments

y = 0.0000116x + 0.0023065 R² = 0.8115255

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Channel 1

y = 0.0000118x + 0.0042091 R² = 0.8930930

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y = 0.0000118x + 0.0038016 R² = 0.9226857

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y = 0.00001304x + 0.00398535 R² = 0.94134953

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Channel 4

y = 0.0000173x + 0.0093675 R² = 0.8472319

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Channel 5

Attachments

Attachment 10: Calculation of the weighted mean of the GraphPad analysis data.

Table P: Calculation of the weighted mean of somatropin.

KD SE RSD weight (X-wm)2 (X-wm)2 * weight

channel 1 1276.37 588.855 46.14 0.69 201609 139109.281

channel 2 1424.19 706.3198 49.59 0.64 90715 58226.61832

channel 3 1579.337 1083.576 68.61 0.46 21328 9895.716343

channel 4 1899.995 1307.653 68.82 0.46 30491 14102.87696

channel 5 1519.302 483.6397 31.83 1.00 42468 42467.58191

Weighed mean 1511.711

som 263802.0746

som weights *(N'-1/N) 2.606689917

weighed SD 318.1225223

Table Q: Calculation of the weighted mean of 1:1 NOTA-somatropin.

KD SE RSD weight (X-wm)

2 (X-wm)

2 * weight

channel 1 259.8733 138.2474 53.20 0.21 2147707 445472.6541

channel 2 538.2794 67.8706 12.61 0.88 1409205 1233223.287

channel 3 623.196 77.5821 12.45 0.89 1214807 1076742.53

channel 4 795.5913 115.9327 14.57 0.76 864505 654625.5996

channel 5 979.4373 108.0732 11.03 1.00 556429 556428.9316


som 3966493.002

som weights *(N'-1/N) 2.98088946


Table R: Calculation of the weighted mean of 1:3 NOTA-somatropin.


channel 1 550.6046 90.4539 16.43 0.41 1380095 572410.037

channel 2 560.2892 96.2198 17.17 0.40 1357434 538582.6449

channel 3 188.3956 59.984 31.84 0.21 2362318 505544.5702

channel 4 459.6262 67.4977 14.69 0.46 1602130 743360.2813

channel 5 516.5545 35.1967 6.81 1.00 1461257 1461256.529


som 3821154.062

som weights *(N'-1/N) 1.9916102


Table S: Calculation of the weighted mean of 1:10 NOTA-somatropin.


channel 1 724.2986 250.785 34.62 1.00 1002162 998757.9745

channel 2 1808.001 650.5978 35.98 0.96 6826 6546.078126

channel 3 1062.321 455.4638 42.87 0.80 439646 353843.4559

channel 4 2571.057 887.1927 34.51 1.00 715171 715170.8723

channel 5 2336.167 811.9365 34.76 0.99 373062 370398.0731


som 2444716.454

som weights *(N'-1/N) 3.802594425


Attachments

Table T: Calculation of the weighted mean of 1:10 NOTA-somatropin.


channel 1 316.1309 95.0929 30.08 0.51 1985980 1006158.216

channel 2 357.8182 67.4201 18.84 0.81 1870222 1512651.306

channel 3 322.2184 54.7485 16.99 0.90 1968860 1765897.049

channel 4 305.6636 46.5818 15.24 1.00 2015592 2015591.649

channel 5 553.7098 123.1743 22.25 0.69 1372809 940469.3216


som 7240767.541

som weights *(N'-1/N) 3.117937645


Anova test of the last three experiments

Anova: Single Factor

SUMMARY Groups Count Sum Average Variance

4 5 2275.4701 455.09402 23778.56882 5 5 3196.3773 639.27546 73637.36785 6 5 1855.5409 371.10818 10803.92004

ANOVA Source of Variation SS df MS F P-value F crit

Between Groups 188150.1904 2 94075.09519 2.607888184 0.114690594 3.885293835

Within Groups 432879.4268 12 36073.28557

Total 621029.6172 14

Attachments

Attachment 11: The reporting threshold limit for reporting, identification and

qualification of organic impurities in peptides obtained by chemical

synthesis.

characterizing binding affinity of somatropin...

Documents