1. In silico discovery of inhibitors using structure-based approaches Jasmita Gill Structural and Computational Biology Group, ICGEB, New Delhi Nov 2005

2. Target protein 3D structure Find an inhibitor Molecular modeling In silico screening Computational Techniques Computational approach

3. In silico screening Structure based virtual screening docking methods to fit putative ligands into 3D structure of target receptor

4. Structure-based inhibitor discovery 3D structure of target protein Public drug-like in silico libraries In silico screening Short listed hits provided for testing in biological assays Binding site (s) identification Post-scoring and analysis of results Literature, Visual analysis FlexX Cscore, Visual analysis, Unity Vendors Protein Data Bank

5. Sybyl ® – Molecular modelling suite Tools and Techniques Analysis of molecular surfaces of proteins Preparation of target protein and ligand(s) for screening Screening utility -- FlexX Post-scoring -- Cscore Data Mining -- Unity Public in silico chemical compound libraries used

6. FlexX – an overview Input Output Energetically best ranked ligand placements in target site (s) Each placement has variable conformations Target protein with pre-defined active site (s) and Ligands with designated base fragment (s) Thomas Lengauer et. al, J Mol. Bio. 1996

7. -Multiple conformations determined by torsion angles of acyclic single bonds in the ligands - Low energy conformation of the complex is the goal Considerations in FlexX Receptor target protein rigid Ligand Conformational Flexibility

8. Modeling protein-ligand interactions Interaction geometries proteinligand Interactions types H-acceptorH-donor Metal acceptorMetal Aromatic-ring- atom, Methyl, amide Aromatic-ring- center Main scoring criteria Free energy of binding of protein-ligand Consensus scoring ‘Cscore’

9. Public drug-like in silico libraries A database of structures of small molecule compounds Most libraries are free to download Lead-like properties Available for purchase NameNo. of Compounds NCI Diversity set NCI Open Collection 1990 ~200,000 Maybridge~95,000 Specs~202,000 Peakdale~20,000

10. In silico Screening  Preparation of the target protein structure Templates for charged, neutral, non-polar residues Charges Hydrogens  Preparation of ligand structure Charges Hydrogens Filtering was done based on Lipinski’s rule of 5 Mw < 500 daltons (relaxed, <=900) H-bond acceptors < 10 H-bond donors < 5 ClogP (solubility indicator) < 5  Definition of binding site (s) : whole protein in case of Pfg27

11. Final output of screening: Ranking based on free energy of binding of protein-ligand complex Visual Mathematical Binding sites to which compounds docked Conformations H-bonding interactions Hydrophobic interactions Van Der Waals attractions Cscore Screening results Analysis

12. Application to Pfg27

13. Binding sites of interest on Pfg27 Two RNA binding sites per dimer Four SH3 binding sites per dimer A dimer interface From literature Revealed a deep cavity on a unique surface Visual/computational analysis

14. RNA binding site SH3 binding site (N) Dimer interface RNA binding site SH3 binding site Deep cavity

15. Colour coding Basic Acidic Non-polar Polar

16. Deep cavity Depth Surface Deepest cavity in Pfg27

17. Cavities in the dimer interface Cavities

18. SH3 binding site Cavity Cavities in the SH3 binding site (N)

19. Cavities in the RNA binding site Multiple cavities of different depths

20. NCI-diversity set: 1820 compounds 30% in the RNA binding site 30% in the dimer interface 20% in deep cavity 10% in SH3 binding site (N) 10% on other sites Docking patterns on Pfg27 Visual analysis of top 200

21. Best binding energies observed: from -44.363 KJ/mol to –24.056 KJ/mol Chemical composition Most hits had an electronegative character: N, O -, SO 3 -, Cl -, F -, Br - CLogP: –3.59 to 1 (-4 to 4 range is acceptable for solubility) Cscore 3 to 5 (a good score is 4-5) Score of 3 – 37 compounds Score of 4 – 43 compounds Score of 5 – 48 compounds Analysis of top 200 compounds

22. Dockings in the RNA binding site Most compounds interact with Arg70, Arg74, Arg78, Arg80 and Val71

23. Dockings in the deep cavity Most compounds interact with Ser107, Lys112 and Ile122

24. Dockings at the dimer interface Most compounds interact with Asp40, Arg36, Glu134, Arg131, Phe43, Leu126, Trp127

25. Dockings in SH3 binding sites Most hits interact with Arg34