1. Lecture 10 Cheminformatics of TCM Y.Z. Chen Department of Pharmacy National University of Singapore Tel: 65-6616-6877; Email: phacyz@nus.edu.sg ; Web: http://bidd.nus.edu.sg phacyz@nus.edu.sghttp://bidd.nus.edu.sgphacyz@nus.edu.sghttp://bidd.nus.edu.sgContent TCM ingredients and databasesTCM ingredients and databases Digital representation of TCM ingredientsDigital representation of TCM ingredients Molecular descriptorsMolecular descriptors TCM ingredient classification by molecular descriptorsTCM ingredient classification by molecular descriptors

2. TCM Ingredients Pharmacology & Therapeutics 2000, 86:191-198

3. Medicinal Herb Databases at BIDD Comparison with existing TCM databases: Formula: TCM-ID: 1000 TCHFL: 270 Herb: TCM-ID: 1200 TCSHL: 520 TCMD: 1500 Compound: TCM-ID: 9000 CNPD: 3000 TCMD: 6800 TCM Formula Herb Compound Protein Function Structure TCMD TCHF Library CNPD TCSH Library TCM-ID: Traditional Chinese Medicine - Information Database   Only database providing integrated and comprehensive info about: TCM formula, constituent herbs, herbal ingredients, effect on proteins Molecular structure Function at the formula, herb and compound levels

4. TCM-ID Database at BIDD http://bidd.nus.edu.sg/group/TCMsite/Default.aspx

5. TCM-ID Database at BIDD http://bidd.nus.edu.sg/group/TCMsite/Default.aspx

6. TCM-ID Database at BIDD

8. http://bidd.nus.edu.sg/group/TCMsite/Default.aspx

9. TCM-ID Database at BIDD http://bidd.nus.edu.sg/group/TCMsite/Default.aspx

10. TCM-ID Database at BIDD http://bidd.nus.edu.sg/group/TCMsite/Default.aspx

11. TCM-ID Database at BIDD

15. http://bidd.nus.edu.sg/group/TCMsite/Default.aspx

16. TCM-ID Database at BIDD http://bidd.nus.edu.sg/group/TCMsite/Default.aspx

17. TCM-ID Database at BIDD http://bidd.nus.edu.sg/group/TCMsite/Default.aspx

18. PUBCHEM Database http://pubchem.ncbi.nlm.nih.gov/summary/summary.cgi?cid=90781

19. PUBCHEM Database http://pubchem.ncbi.nlm.nih.gov/summary/summary.cgi?cid=90781

20. Representation of Herbal Ingredients by SMILES Simplified Molecular Input Line Entry System (SMILES) Widely used AND computationally efficient Uses atomic symbols and a set of intuitive rules Uses hydrogen-suppressed molecular graphs (HSMG)

21. SMILES Bonds SINGLE* DOUBLE TRIPLE AROMATIC* * can be omitted -=#:-=#:

22. Butanols 2-Butanol iso-Butanol tert-Butanol

23. SMILES Branches Represented by enclosure in parentheses Can be nested or stacked Examples: CC(O)CC is 2-Butanol OCC(C)C is iso-Butanol OC(C)(C)C is tert-Butanol

24. SMILES Bonds Ethene Chloroethene 1,1-Dichloroethene cis-1,2-Dichloroethene Trichloroethene Perchloroethene C=C ClC=C ClC(Cl)=C ClC=CCl ClC(Cl)=CCl ClC(Cl)=C(Cl)Cl

25. SMILES Atoms Use normal chemical symbols Add punctuation symbols if necessary No super- or subscripts

26. SMILES Symbols String of alphanumeric characters and certain punctuation symbols Terminates at the first space encountered when read left to right The ORGANIC SUBSET: B, C, N, O, P, S, F, Cl, Br, I

27. Other SMILES Atoms Aliphatic or nonaromatic carbon: C Atom in aromatic ring: lowercase letter Designate ring closure with pairs of matching digits, e.g. c1ccccc1 (or C1=CC=CC=C1) is Benzene, whereas C1CCCCC1 is Cyclohexane

28. SMILES Charges Specify attached hydrogens and charges in square brackets Number of attached hydrogens is the symbol H followed by optional digit

29. SMILES Charges [H+] [OH-] [OH3+] [Fe++] [NH4+] proton hydroxyl anion hydronium cation iron(II) cation ammonium cation

30. SMILES Cyclic Structures Break one single or one aromatic bond in each ring Number in any order –Designate ring-breaking atoms by the same digit following the atomic symbol

31. Representation of Herbal Ingredients by Molecular Descriptor Molecular descriptors are numerical values that characterize properties of molecules Examples: –Physicochemical properties (empirical) –Values from algorithms, such as 2D fingerprints Vary in complexity of encoded information and in compute time

32. 32 Molecular Descriptors Constitutional –MW, N atoms, Topological –Connectivity,Weiner index Electrostatic –Polarity, polarizability, partial charges Geometrical Descriptors –Length, width, Molecular volume Quantum Chemical –HOMO and LUMO energies –Vibrational frequencies –Bond orders –Total energy

33. 33 Molecular Descriptors van der Waals volume –The sum of the non-overlaping volume of van der Waals sphere of each atom of the molecule Molecular surface –The area of the surface contours generated by rolling a probing sphere against the surface atoms of the molecule

34. 34 Molecular size vectors –Define ranges for distances and angles Molecular Descriptors

35. Molecular Descriptors for Large Data Sets Descriptors representing properties of complete molecules –Examples: LogP, Molar Refractivity Descriptors calculated from 2D graphs –Examples: Topological Indexes, 2D fingerprints Descriptors requiring 3D representations Example: Pharmacophore descriptors

36. Molecular Descriptors Calculated From 2D Structures Simple counts of features –Lipinski Rule of Five (H bonds, MW, etc.) –Number of ring systems –Number of rotatable bonds Not likely to discriminate sufficiently when used alone Combined with other descriptors for best effect

37. Physicochemical Properties Hydrophobicity –LogP – the logarithm of the partition coefficient between n-octanol and water ClogP (Leo and Hansch) – based on small set of values from a small set of simple molecules –BioByte: http://www.biobyte.com/http://www.biobyte.com/ –Daylight’s MedChem Help page –http://www.daylight.com/dayhtml/databases/medchem/m edchem-help.htmlhttp://www.daylight.com/dayhtml/databases/medchem/m edchem-help.html –Isolating carbon: one not doubly or triply bonded to a heteroatom

38. 38 Molecular Descriptor LogP Octanol-Water Partition Coefficients P = C(octanol) / C(water) log P like  r G = - RT ln K eq Hydrophobic - hydrophilic character P increases then more hydrophobic

39. TCM Ingredient Classification by Molecular Descriptors J. Chem. Inf. Model., Vol. 47, No. 6, 2007

40. TCM Ingredient Classification by Molecular Descriptors Classification of TCM ingredients of specific chemical classes by decision trees method

41. TCM Ingredient Classification by Molecular Descriptors

43. Classification of TCM ingredients of specific chemical classes by decision trees method

44. TCM Ingredient Classification by Molecular Descriptors Distribution of TCM ingredients of specific chemical classes without using decision trees method

45. TCM Ingredient Classification by Molecular Descriptors Distribution of TCM ingredients of specific chemical classes without using decision trees method

46. Acknowledgement Current Group Members: Computer-Aided Drug Design: CY Ung, XH Ma, XH Liu, Pankaj Kumar, F Zhu, X Liu, J Jia Protein Function, Interaction, Network: HL Zhang, CY Ung, XH Ma, F Zhu, WK Teo, Z Shi Databases and Servers: J Jia Medicinal Herb: CY Ung, Pankaj Kumar, Cao Jinyi(undergraduate students) Microarray and biomarkers: J Jia, ZQ Tang Former Members: PhD: ZW Cao (Prof SCBIT, Tongji U), ZL Ji (Assoc Prof Xiamen U), X Chen (Assoc Prof Zhejiang U), CW Yap (Assist Prof NUS), LY Han (Postdoc NIH), CJ Zheng (Postdoc NIH), HH Lin (Postdoc Harvard ), J Cui (Postdoc U Georgia), H Li (Postdoc Einstein College Med) Research Fellow/Assistant: ZR Li (Assoc Prof SiChuan U), Y Xue (Prof SiChuan U), W Liu (Assoc Prof DUT), D Mi (Assoc Prof DUT), CZ Cai (Prof ChongQing U), DG Zhi (Postdoc, Berkeley), MSc: Y.J. Guo (Postdoc NIH), L.Z. Sun (RA, U Tenn.), J. F. Wang (MSU), L.X. Yao (Columbia), S Ong (Washington U), H Zhou (local company), B Xie (local company) BSc: W.K. Yeo (IMCB, Novartis)