Biological Recognition:Beyond the Antibody

Paul Ko Ferrigno Chief Scientific Officer

This talk

• Antibodies and the need for new scaffolds

• Historical perspective- scaffolds

• Next generation scaffolds- design considerations

• Affimer performance

Biological Recognition- Antibodies

Antibodies

• Are fantastic diagnostic tools

• Are pretty good reagents for research

• Can be made to be good drugs

Why?

• Optimisation

• Large binding surface area

• Constant region allows generic protocols

But antibodies…

• Can suffer from cross-reactivity

• Can be difficult to express

• Can be difficult to engineer

• Can be difficult to use

• Generating a functional binder for each element of proteome is a huge challenge

What we need to do- Human Protein Atlas

Berglund et al (2008) Proteomics 2008, 8, 2832–2839

Validation score

Validation category

Criteria Number of antibodies

Fraction%

1. High Supportive Two independent antibodies with similar staining pattern consistent with experimental and/or bioinformatics data

687 7

2. Medium Supportive Staining pattern consistent with experimental and/or bioinformatics data

1414 15

3. Low Uncertain Staining pattern partly consistent with experimental and/or bioinformatics data

1853 20

4. Very low Uncertain No literature or bioinformatics data available 861 9

5. Failed Failed Staining pattern not consistent with experimental and/or bioinformatics data

4543 49

Where we are- Catalogue reagents and HPA

TABLE II Validation of 9358 internally generated antibodies

Berglund et al (2008) A Genecentric Human Protein Atlas for Expression Profiles Based on Antibodies. Molecular & Cellular Proteomics, 7, 2019-2027.

5436 external antibodies from 51 different antibody providers were obtained and subsequently validated. Of these, 1410 mono -clonal antibodies and 1316 polyclonal antibodies were approved by a standardized validation using Western blotting and IHC on tissue microarrays as described above. The success rates (…) showed (…) an average success rate of 49%.

If half of all research antibodies tested fail…

Research: huge amount of time wasted in finding the right reagent

Proteomics: limited coverage, limited understanding

Pharma: new target, but no tools= no assays = no drugs

First Gen Scaffolds

Binz, Amstutz & Plückthun, Nature Biotech 23, 1257 - 1268 (2005)

Why do we need more scaffolds?

• Early scaffolds started as academic research projects

• Later ‘fit for purposes’ scaffolds may rely on untested assumptions

• Purpose may dictate scaffold choice-but what happens if the experimental paradigm changes?

• Multiplexing represents unique challenges, but is needed for personalised medicine/CDx

Next Gen Scaffolds

A successful non-Ab scaffold protein should be:

(1) of known structure: informed choice of the site for peptide insertion or replacement

(2) stable: to constrain the folding of a broad range of peptides

(3) flexible: folding not affected by peptide inserts

(4) biologically neutral: lacking interactions with irrelevant proteins

(5) well-expressed in prokaryotic and eukaryotic environments, data obtained in one system informs experiments performed in the other

Woodman et al, J Mol Biol, 2005

Woodman et al, J Mol Biol, 2005

Affimers start from a robust, neutral and versatile scaffold

Small- 98 aa

Lysosomal resident

Protease inhibitor

No cys

Well understood interaction surfaces: very similar to Ab

Capable of 1 fM KD

Affimers are robust to extremes of pH

θ (d

eg c

m2 d

mol

-1)

wavelength (nm)

Peptide presentation and protein yields

100

50

0

200

protein yield (mg l-1)

SQM SQT

Affimers: non-antibody binding proteins derived from Stefin A

Multiple libraries

CIS display: 1012

Phage display: 1010

Y2H: >108

Microarray: >104

Speed of Screening

-5

0

5

10

15

20

25

30

35

40

-200 -140 -80 -20 40 100 160 220 280 340 400 460 520 580 640 700

Time sRe

spon

se

RU

ka (1/Ms) kd (1/s) Rmax (RU) RI (RU) Conc of analyte KA (1/M) KD (M) Req (RU) kobs (1/s) Chi26.76e3 2.15e-5 44.1 -1.28 1000n 3.15e8 3.18e-9 44 6.78e-3 0.0331

0

0.5

1

1.5

2

2.5Direct ELISA of Ψ F6 against Human Recombinant Proc-

alcitonin

No Ψ Ψ F6

Coat Concentration (µg/mL)

Abso

rban

ce O

D 48

0 nm

Binders generated in 7 weeks. LOD ~ 0.16 μg PCL /mL in a non-signal amplified direct ELISA.

Biacore trace

Kd= 3 nM

Baseline ELISA- No signal amplification 1:1:1 binding between Target, Affimer and Secondary

0 0.2 0.4 0.6 0.8 1 1.2 1.40

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

Direct ELISA against TargetX with ΨE3

Gal7 ΨE3 Secondary Control

Target Coating Concentration (μg/mL)

Abs

orba

nce

OD

450

nm

0 0.2 0.4 0.6 0.8 1 1.2 1.40

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Direct ELISA against IL-2 with 2 Ψ's

IL-2 ΨA3 IL-2 ΨF3

Secondary Control

Target Coating Concentration (μg/mL)

Abs

orba

nce

OD

450

nm

0 0.2 0.4 0.6 0.8 1 1.2 1.40

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

Direct ELISA against IL-6 with ΨA7

IL-6 ΨA7 Secondary Control

Target Coating Concentration (μg/mL)

Abs

orba

nce

OD

450

nm

X

0 0.2 0.4 0.6 0.8 1 1.2 1.40

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0.045

0.05Anti-rabbit IgG Affimer D1 is highly specificrIgG

mIgG1

mIgG2a

mIgG2b

mIgG3

rat IgG

donkey IgG

sheep IgG

chicken IgG

goat IgG

mouse IgM

canine IgGAntibody coat concentration (μg/mL)

Ab

so

rba

nc

e (

45

0-6

20

nm

)

Western Blotting

Anti-SAAClone E12 Lysate

Lanes 1, 4 & 7 – Life Tech SeeBlue Plus 2 Marker, 5μlLanes 2, 5 & 8 – HeLa RIPA lysate, 10 μg, reducedLanes 3, 6 & 9 – Recombinant SAA, 0.1 μg, reduced

BinderLanes 1, 2 & 3 – Anti-SAA Ψ, 0.5 μg/mlLanes 4, 5 & 6 – Anti-SAA Ψ, 5 μg/mlLanes 7, 8 & 9 – No binder

DetectionAll Lanes – ab1187 anti-6xHis Rabbit Polyclonal, HRP conjugated, 1/5000

Affimers to Small Molecules

1 2 3 4 5 6 7 80

0.2

0.4

0.6

0.8

1

1.2

Phage ELISA of candidate Posaconazole binders from a screen

Posaconazole+Linker

Posaconazole+Linker & Free Posaconazole

Posaconazole+Linker & Free Voriconazole

No Coat Control

Clone ID

Ab

sorb

ance

O

D 4

80n

mPosaconazole

Voriconazole

Isoform Specificity and Intracellular Use

inactive active

p85 regulates p110 lipid kinase activity via its SH2 domain.

In the presence of a p85 SH2 binding protein the inhibition is released, activating p110

Active p110 inhibits phosphorylation of Akt

Isoform Specificity and Intracellular Use

Binders were generated to the SH2 domains of PI3K subunits.

PI3K p85A N-termPI3K p85B N-termPI3K p55G N-term

consensus

PI3K p85A N-termPI3K p85B N-termPI3K p55G N-term

consensus

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 240

0.2

0.4

0.6

0.8

1

1.2

1.4p85A C p85A N p85B C p85B N p55G C p55G N control

Clone ID

Ab

so

rba

nc

e O

D 4

50

nm

Phage ELISA results of a screen against the PI3K P85A N-terminal SH2 domain

Isoform Specificity and Intracellular Use

Candidate Affimers were expressed in 3T3 cells and shown to increase pAKT.

Inhibition does not correlate with expression level ie some Affimers are more potent

Affimer Arrays for Protein Detection

25,000 features

LLOD currently pg/mL in human serum

Signatures of Drug Action- DMSO 0.5 1 2 4 hours Staurosporine

Up-regulated Down-regulated

Panel A: Cells treated with staurosporine undergo apoptosis.

A

B

Panel C: highlights of some of the 336 other Affimers also gave altered signals- some proteins decreasing (probably represent-ing proteins cleaved in apoptosis) while others are increasing (possibly reflecting the detection of cleaved products)

Panel B: At 4 hours, after treatment with drug or carrier (DMSO) cells were lysed and proteins fluorescently labelled with Cy3 or Cy5. 17k Arrays were challenged with a mixture of these labelled lysates. Affimers binding proteins such as BAD, known to be in-creased in apoptosis, showed increased signals from cells treated with staurosporine. Affimers recognising proteins cleaved in ap-optosis, such as CDK2, showed decreased signals. Affimers bind-ing BCL6, a protein whose levels have not been investigated in apoptosis, suggest this protein is down-regulated.

Sumoylation

Yeast-SUMO-_smt3_ MSESPSANISDADKSAITPTTGDTSQQDVKPSTEHINLKVVGQDNNEVFFKIKKTTEFSKHuman-SUMO1 --------MSDQEAKPSTEDLGD------KKEGEYIKLKVIGQDSSEIHFKVKMTTHLKKHuman-SUMO2 --------MADEKPKEGVKTENN----------DHINLKVAGQDGSVVQFKIKRHTPLSK ::* . . . .: ::*:*** ***.. : **:* * :.* Yeast-SUMO-_smt3_ LMKIYCARQGKSMNSLRFLVDGERIRPDQTPAELDMEDGDQIEAVLEQLGGCTHLCLHuman-SUMO1 LKESYCQRQGVPMNSLRFLFEGQRIADNHTPKELGMEEEDVIEVYQEQTGGHSTV--Human-SUMO2 LMKAYCERQGLSMRQIRFRFDGQPINETDTPAQLEMEDEDTIDVFQQQTGGVY---- * : ** *** .*..:** .:*: * .** :* **: * *:. :* **    

Yeast SUMO binders and Species Specificity

ITC: Ψ-Clone 10

Ψ-Clone 10

Ψ-Clone 15

Ψ-Clone 19

Ψ-Clone 22

Yeas

t SU

MO

Hum

an S

UM

O1

Hum

an S

UM

O2

Ψ-C

lone

10

Ψ-C

lone

15

Ψ-C

lone

19

Ψ-C

lone

22

cont

rol

Yeast SUMOHuman SUMO1Human SUMO2

Abso

rban

ce O

D 4

80nm

0

0.5

1.0

1.5

Binders were generated that were specific to yeast SUMO. Data shown are direct ELISA and western blot results for 4 candidates against yeast SUMO and human SUMO 1 & 2. ITC for one candidate shows a Kd of ~30 nM.

Summary

• Affimers are small, robust and versatile proteins

• The scaffold has been engineered to lack partners in human systems

• Very large libraries can be quickly screened against a broad range of targets

• The resulting binders are high affinity and exquisitely specific

Acknowledgments

Screening/Validation

Christina RäuberLaura Dicker

Davinia FernandezRob Ford

Lindsay McMorran

Protein Expression

Paul ShadboltEmma BransonAmanda Evans

Katarzyna GorczakTony KwokRuth Lunn

Graham Spence

Affimer Arrays

Kit-Yee TanVincent Puard

University of Leeds

Mike McPhersonDarren Tomlinson

Christian TiedeAnna Tang

Presentation by Paul Ko Ferringo

Head of R&D: Matt Johnson

For more info visit Avacta Life Sciences or contact chris.miller@avacta.com