A Web-Based Computational Tool for Combinatorial Library Design

that Simultaneously Optimises Multiple Properties

Weifan Zheng, Sunny T. Hung,

Joel T. Saunders, Stephen R. Johnson, George L. Seibel

A short paper:http://www-smi.stanford.edu/projects/helix/psb-online/

Outline

• Library Design - Problem Definition• Criteria in Early Computational Techniques• Important Developability Parameters• Multifactorial Nature of Library Design • PICCOLO

– Optimisation Protocol

– Individual Penalty Terms and Their Definition

– Snapshots of the Intranet-Based System

• Conclusions

Library Design - Problem Definition

10 x 10 => 5 x 5

R1

R2

5x5 full combination

?

Criteria Used in Early Computational Design Techniques

• Diverse Design: – diversity analysis and void-filling

• Targeted Design:– similarity to leads– docking to a binding site– predicted activity using QSAR/QualSAR

models– Pphore models

Failure of Compounds in Development

• Poor biopharmaceutical properties, 39%

• Lack of efficacy, 29%

• Toxicity, 21%

• Market reasons, 6%

- Venkatesh & Lipper, J. Pharm. Sci. 89, 145-154 (2000)

“an efficacious but non-absorbed agent is no better than a well absorbed but in-efficacious one”

- Curatolo W. Pharm Sci Tech Today 1, 387 (1998)

Developability Should Be Considered in Library Design

To avoid serious ADME liabilities as early as possible in the drug discovery process

• Empirical rules– Lipinski rules of 5 (MW, clogP, #HD, #HA)

• Drug-likeness– Ajay & Murcko (JMC, 1998, 41, 3314-3324) – Sadowski & Kubinyi (JMC, 1998 , 41, 3325-3329)

Some Fundamental Properties Contributing to Pharmacokinetics (PK)

• Aqueous solubility

• Membrane passive permeability

• Cytochrome P450 activities

• Plasma protein binding

• Efflux pumping and active transport

• ...

Factors That Are Optimised Similarity to leads Reagent diversity/coverage Product novelty with respect to the corporate

compound inventory Lipinski parameters Liabilities against P450 enzymes Aqueous solubility; [Permeability] Molecular flexibility; MS redundancy; reagent price

Penalty Scores

Iteration

Initial Library

Better Library

Optimal Library

Lipinski PropertiesP450 Activity

Diversity

PICCOLO: reagent PICking by COmbinatorial Library

Optimisation

R1 R2

R1

R2

R1

R2

R1

R2

The Size of the Solution Space is Huge

50 Amines + 50 carboxylic acids

• Total number of compounds

50 x 50 = 2500

• Total number of solutions for an 8 x 12 library

50!/(8!42!) * 50!/(12!38!) = 6.52 x 1019

Randomly Pick5x5

EnumerateCalc penalty scores for

the trial solution &save scores

Metropoliscriteria?

Reject trialsolution

ReagentPool

Swap aFraction ofReagents

N

Y

Stochastic Optimisation to Sample the Solution Space

Save the trialsolution

Perturbation Scheme

• Which R-group to perturb – bias toward the R-groups that need more

sampling

• Which new reagent to pick– uniform sampling by cycling through the

selected R-group list

• Which old reagent to kick out– randomly chosen

Total Penalty Score is the Weighted Sum of Individual Penalty Terms

)()( SEwSE ii

Similarity to Leads

• Esim(S) = Daylight Tanimoto “distances” between all the compounds in a given library and the lead, averaged over the size of the library

• In case of multiple leads, the Tanimoto distance between a compound and the leads is defined as the nearest neighbour distance

Reagent Diversity: S-Optimal Criterion

• Esdiv (S) = Reverse S optimal scores for all R-groups averaged over the number of R-groups

Sopt

d

N1

y,D - y

D

y D

D: a set of design points (i.e., the selected reagents)

d(x, A): minimum TD between point x and set of points A

Product Novelty with Respect to Corporate Collection

• All S.B. compounds were mapped onto a 6D cell space (PCA, or formed by selected features to distinguish biological activities)

• Epn (S) = the smoothed average number of S.B. compounds in the neighbouring cells

Developability Penalty Scores

• Lipinski Parameters– MW < = 500– ClogP: -1 to 5– NHD <= 5– NHA <= 10

• P450s - non-inhibitory predicted by the P450 classifiers

• Solubility - should be higher than a limit

Each penalty term is the percentageof library compounds that violatethe limits for each term

P450 Classifiers and Solubility Predictor

• P450s: 2d6, 3a4, 1a2, 2c9– dataset(2d6): Active: ~3500; Inactive: ~4000

– method: 3 layer ANN

– FP: 20%; FN: 10%; Ambiguous - 12 - 18%

• Solubility– N = ~550

– 3 layer ANN

– rms error ~1.0 log unit

Logon page

Experiment list

New Experiment Page

Spreadsheet Page

Structure Show

MW/ClogP

MW/ClogP

Conclusions

• PICCOLO is an in-house library design system that can simultaneously optimise all the factors we care about

• Important developability parameters are taken into account

• Expandable to include other criteria

• A Web based system being used by SB chemists worldwide

Acknowledgements

Colleagues in Cheminformatics DepartmentKen KoppleJie Liang (now at Univ. Illinois at Chicago)

Medicinal Chemists Todd Graybill, Jian Jin , Ronggang Liu, Tom Ku, Dennis Yamashita, Scott Thompson, Jia-Ning Xiang