Introduction to Chemoinformatics

1. Introduction to Chemoinformatics Irene Kouskoumvekaki Associate Professor December 12th, 2012 Biological Sequence Analysis course

2. Drug Discovery Process

3. The drug candidate • ... is a (ligand) compound that binds to a biological target (protein, enzyme, receptor, ...) and in this way either initiates a process (agonist) or inhibits it (antagonist/inhibitor) • The structure/conformation of the ligand is complementary to the space defined by the protein’s active site • The binding is caused by favorable interactions between the ligand and the side chains of the amino acidsin the active site. (electrostatic interactions, hydrogen bonds, hydrophobic contacts...)

5. Wet-lab drug discovery process HTS Screening collection Actives 106 cmp. 103 actives

6. Wet-lab drug discovery process HTS Screening collection Actives 106 cmp. 103 actives High rate of false actives!!! High throughput is not enough to get high output…..

7. Wet-lab drug discovery process Chemical structure Purity Mechanism Activity value HTS Follow-up Screening collection Actives 106 cmp. 103 actives

8. Wet-lab drug discovery process HTS Follow-up Screening collection Actives Hits 106 cmp. 103 actives 1-10 hits Analogues synthesis and testing ADMET properties

9. Wet-lab drug discovery process HTS Follow-up Hit-to-lead Screening collection Lead series Actives Hits 106 cmp. 103 actives 1-10 hits 0-3 lead series Analogues synthesis and testing ADMET properties

10. Wet-lab drug discovery process Lead-to-drug HTS Follow-up Hit-to-lead Screening collection Lead series Drug candidate Actives Hits 106 cmp. 103 actives 1-10 hits 0-3 lead series 0-1 Analogues synthesis and testing ADMET properties

12. Failures

13. We need more.. to find less..

14. Drug Discovery Process Chemoinformatics

15. Wet-lab + Dry-lab drug discovery in vitro in silico+ in vitro Diverse set of molecules tested in the lab Computational methods to select subsets (to be tested in the lab) based on prediction of drug-likeness, solubility, binding, pharmacokinetics, toxicity, side effects, ...

16. The Lipinski ‘rule of five’ for drug-likeness prediction • Molecular weight ≤ 500 • # hydrogen bond acceptors (HBA) ≤ 10 • # hydrogen bond donors (HBD) ≤ 5 • Octanol-water partition coefficient (logP) ≤ 5 (MlogP ≤ 4.15) • If two or more of these rules are violated, the compound might • have problems with oral bioavailability. (Lipinski et al., Adv. Drug Delivery Rev., 23, 1997, 3.)

17. Exercise : Prediction of drug-likeness • Go to the following webpage www.molsoft.com/mprop • Draw proguanil and decide if it is a drug-like compound

19. Proguanil antimalarian tablets

20. Gathering and systematic use of chemical information, and application of this information to predict the behavior of unknown compounds in silico. Chemoinformatics data prediction

21. Major Aspects of Chemoinformatics • Databases:Development of databases for storage and retrieval of small molecule structures and their properties. • Machine learning: Training of Decision Trees, Neural Networks, Self Organizing Maps, etc. on molecular data. • Predictions: Molecular properties relevant to drugs, virtual screening of chemical libraries, system chemical biology networks…

23. Representinga chemicalstructure • How much information do you want to include? • atoms present • connections between atoms • bond types • stereochemical configuration • charges • isotopes • 3D-coordinates for atoms C8H9NO3

24. Representinga chemicalstructure • How much information do you want to include? • atoms present • connections between atoms • bond types • stereochemical configuration • charges • isotopes • 3D-coordinates for atoms

25. Representinga chemicalstructure • How much information do you want to include? • atoms present • connections between atoms • bond types (aromatic ring identification) • stereochemical configuration • charges • isotopes • 3D-coordinates for atoms

26. Representinga chemicalstructure • How much information do you want to include? • atoms present • connections between atoms • bond types • stereochemical configuration • charges • isotopes • 3D-coordinates for atoms

27. Representinga chemicalstructure • How much information do you want to include? • atoms present • connections between atoms • bond types • stereochemical configuration • charges • isotopes • 3D-coordinates for atoms

28. Representinga chemicalstructure • How much information do you want to include? • atoms present • connections between atoms • bond types • stereochemical configuration • charges • isotopes • 3D-coordinates for atoms

29. Representinga chemicalstructure • How much information do you want to include? • atoms present • connections between atoms • bond types • stereochemical configuration • charges • isotopes • 3D-coordinates for atoms

30. From chemists to representations

31. Structural representation of molecules Structural representation of molecules Line notations Connection tables

32. SMILES (Simplified Molecular Input Line Entry System) Canonical SMILES: unique for each structure Isomeric SMILES: describe isotopism, configuration around double bonds and tetrahedral centers, chirality

33. InChI(IUPAC International Chemical Identifier)

34. MOLfile format (.sdf)

35. Small molecule databases

36. Try it yourself! • Go to PubChem: pubchem.ncbi.nlm.nih.gov/ • Type proguanil and press Go • Click on the first result on the list

37. Try it yourself! • Scroll down and find the SMILES and InChI

38. Try it yourself! • Click on SDF (top right icon) • Select: 2D SDF: Display

39. Try it yourself! • Go back and click again on SDF • Select: 3D SDF: Display

40. Questions?