in silico small molecule discovery Sales Target gene Discover hit Hit to lead Optimise lead Clinical Target gene identified with a viable assay High throughput screen in silico

Case 1 – receptor structure known Novel in silico hits ~ 100 Computer Database of Molecules 100,000 + dock molecules into receptor Secondary assay ? hits IC 50 < 10 µM

How successful is this method? From Shoichet’s group on target – protein tyrosine phosphate 1B None of the in silico hits found by HTS But unpredictable - other systems yielding < 1% MethodCompounds tested Hits with IC 50 < 10µ MHit rate High throughput screening (HTS) 400, % In silico docking365 from docking 185%

How does one get the receptor structure? X-ray structure available already at RCSB databank Set up a structure determination Predict structure

CloningRecombinant protein Expression Protein purification – mg quantities Protein crystalsElectron density map X-ray diffraction patternProtein structure Crystallization X-ray crystallography pipeline

Prediction protein structure by homology Query sequence Matched fold Match sequence against library of known folds

Phyre- Phyre and predecessor 3DPSSM > 1,000 citations

Case 2: Ligand activity data available Novel in silico hits database Observed activity Structure- activity rules Screen

INDDEx TM – A logic-based method Muggleton & Sternberg developed a logic-based strategy Method now incorporated into INDDEx within an Imperial spin-out Equinox Pharma INDDEx designed to exploit availability of active and inactive data on a at least c. 5 but ideally more ligands

Logic-rules lead to new chemotypes C D 7Å7Å A BB C Fragment B is bonded to fragment C Fragment C is bonded to fragment D A B C D 7Å7Å INDDEx can learn complex rule from simpler facts  Fragment A is 7Å from fragment B which is bonded to fragment C which is bonded to fragment D Fragment A is 7Å from fragment B

Rules can be understood by chemists Standard programs: Activity = 0.45 LogP Lumo V A B C D 7Å7Å ILP rule: In an active molecule: Fragment A is 7Å from fragment B which is bonded to fragment C which is bonded to fragment D  

Chemistrt a Blind trial of hit discovery on GPCR-1 Data from literature 250 novel in silico hits Order Observed activity - From Literature 157 Compounds 30 Verified in vitro hits NEW CHEMOTYPES Test Cerep in silico at Equinox Equinox outsourced wet chemistry and biology INDDEx

GPCR-1: training set Distribution of 686 training molecules collected from public domain Actives Inactives

GPCR Target 1 hits for optimatisation 4.7M molecules in Zinc database 400,000 drug like molecules 500 in silico hits 250 hits & new chemotypes 157 tested for inhibition 76 actives 39 for IC50 30 confirmed 30 chemotypes 30

GPCR-1: results of primary screening Number of in silico hits: 157 (10µM concentration) Number of actives: 76 Number of inactives: 81 Primary screen success rate = 48% True hits False hits

GPCR-1 results: IC 50 Number of hits sent for IC50: 39 Number with IC 50 < 12 µM = 30

GPCR-1: new chemotypes Distribution of hits based on their diversity (Tanimoto coefficients) New chemotype

Chemistrt a INDDEx Equinox hit discovery on GPCR-2 - Data from BioPrint (Cerep) 250 novel in silico hits Order Observed activity - From BioPrint 94 Compounds 28 Verified in vitro hits Test Cerep in silico at Equinox Equinox outsources wet chemistry and biology

Confirmed hit rate of in silico predictions on secondary screen c. 35% Target 1Target 2 In silco hits Primary screen hits (>30% binding at 10µM) No. compounds tested for IC IC50 results (<12µM) Estimated secondary hits if all primary hits tested 4042 Estimated hit rate = estimated secondary hits In silico hits 38/157 = 24 % 42 /94 = 45 %

Comparative hit rates Company / approachTarget Hit Rate Technology INDDExGPCR 1 & 2 + unknown target 35 % Ligand-based Structure-basedMultiple targets Average < 2% Docking into 3D structure High throughputMultiple targets Average 0.001% Experimental screening

Concluding remarks If protein structure available can initiative an in silico screening approach to find hits. –Success rate generally <.2% –X-ray structure determination requires mgs of material –Prediction of structure if sequence identity > 50% If structure- activity data available then in silico methods can yield far better hit rates c. 35% in silco methods complement high throughput and can find different hits

In silico small molecule discovery Michael Sternberg, Ata Amini, Paul Freemont & Michael Sternberg Imperial Collge Lond – & –