Abstract

Author(s): RU Kadam, N Roy
Centre of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research, Sector 67, S. A. S.Nagar, Punjab - 160 062, India

Correspondence Address:
N Roy Centre of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research, Sector 67, S. A. S.Nagar, Punjab - 160 062 India E-mail: nilanjanroy@niper.ac.in

The low success rate of converting lead compounds into drugs owing to unfavorable pharmacokinetic parameters has evoked a renewed interest in understanding more clearly what makes a compound drug-like. This article reviews a number of computational techniques for identifying drug-like molecules, ranging from simple counting schemes to sophisticated machine learning techniques such as neural networks, along with their application and challenges.

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