Predicting biotransformation potential from molecular structure

Yu Borodina; A Sadym; D Filimonov; V Blinova; A Dmitriev; V Poroikov

doi:10.1021/ci034078l

Predicting biotransformation potential from molecular structure

J Chem Inf Comput Sci. 2003 Sep-Oct;43(5):1636-46. doi: 10.1021/ci034078l.

Authors

Yu Borodina¹, A Sadym, D Filimonov, V Blinova, A Dmitriev, V Poroikov

Affiliation

¹ Laboratory of Structure-Function Based Drug Design, Institute of Biomedical Chemistry of Russian Academy of Medical Sciences, 10 Pogodinskaya Str, Moscow 119121, Russia. borodina@ibmh.msk.su

PMID: 14502498
DOI: 10.1021/ci034078l

Abstract

The program PASS-BioTransfo is presented, which is capable of predicting many classes of biotransformation for chemical compounds. A particular class of biotransformation is defined by the chemical transformation type and may additionally include the name of the enzyme involved in a transformation. An evaluation of the approach is presented, using biotransformations taken from the databases Metabolite (MDL) and Metabolism (Accelrys), respectively. When trained with biotransformations from Metabolite, PASS-BioTransfo predicts 1927 classes of biotransformation; the average accuracy estimated in LOO cross-validation is about 88%. After training with the biotransformations from the Metabolism database, 178 classes of biotransformation are predicted with an average accuracy of about 85%. The results of cross-prediction with several training and evaluation sets are presented and discussed.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Animals
Biotransformation*
Databases, Factual
Humans
Molecular Structure
Pharmaceutical Preparations / chemistry*
Pharmaceutical Preparations / metabolism
Software*
Structure-Activity Relationship

Substances

Pharmaceutical Preparations