Consensual classification of drug and nondrug compounds

Int J Comput Biol Drug Des. 2008;1(3):224-34. doi: 10.1504/ijcbdd.2008.021416.

Abstract

A special consensual approach is discussed for separating a molecular group with a proven pharmacological activity from another molecular group without any activity. It is mainly a group decision to produce a consensus of multiple classification results obtained with a single classification algorithm. For this purpose, the constructed model has a preprocessing unit which consists of transformation of input patterns by random matrices and median filtering to generate independent errors for a single type of classifier and postprocessing for consensus. The neural network based consensus classifier operating with MOE descriptors was applied to a set of 641 chemical structures. The confirmed drugs were classified with an accuracy of 86.54% while nondrugs resulted in 82.67% accuracy.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Computational Biology
  • Databases, Factual
  • Drug Design*
  • Neural Networks, Computer
  • Pharmaceutical Preparations / classification*
  • Quantitative Structure-Activity Relationship

Substances

  • Pharmaceutical Preparations