A comparative study on the molecular descriptors for predicting drug-likeness of small molecules.
Screening of " drug-like" molecule from the molecular database produced through high throughput techniques and their large repositories requires robust classification. In our work, a set of heuristically chosen nine molecular descriptors including four from Lipinski's rule, were used as classification parameter for screening "drug-like" molecules. The robustness of classification was compared with four fundamental descriptors of Lipinski. Back propagation neural network based classifier was applied on a database of 60000 molecules for classification of, " drug-like" and "non drug-like" molecules. Classification result using nine descriptors showed high classification accuracy of 96.1% in comparison to that using four Lipinski's descriptors which yielded an accuracy of 82.48%. Also a significant decrease of false positives resulted while using nine descriptors causing a sharp 18% increase of specificity of classification. From this study it appeared that Lipinski's descriptors which mainly deal with pharmacokinetic properties of molecules form the basis for identification of "drug-like" molecules that can be substantially improved by adding more descriptors representing pharmaco-dynamics properties of molecules.
Mishra
Hrishikesh
H
Bioinformatics Division, Indian Institute of Information Technology, Allahabad, India. hrishikesh@iiita.ac.in
Singh
Nitya
N
Lahiri
Tapobrata
T
Misra
Krishna
K
Nat Rev Drug Discov. 2003 Apr;2(4):259-66
12669025
J Comput Aided Mol Des. 2000 Mar;14(3):251-64
10756480
J Med Chem. 1984 Dec;27(12):1648-57
6094812
J Chem Inf Model. 2007 Sep-Oct;47(5):1776-86
17718552
J Chem Inf Model. 2005 Jan-Feb;45(1):177-82
15667143
Bioinformatics. 2000 May;16(5):412-24
10871264
Adv Drug Deliv Rev. 2002 Mar 31;54(3):255-71
11922947
J Chem Inf Comput Sci. 2000 Nov-Dec;40(6):1315-24
11128089
J Mol Model. 2004 Jun;10(3):204-11
15067522
J Pharmacol Toxicol Methods. 2000 Jul-Aug;44(1):235-49
11274893
J Med Chem. 1998 Aug 27;41(18):3325-9
9719584