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Oxford University Press (OUP), Bioinformatics, 13(24), p. i366-i374

DOI: 10.1093/bioinformatics/btn186

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A maximum common substructure-based algorithm for searching and predicting drug-like compounds

Journal article published in 2008 by Yiqun Cao, Tao Jiang, Thomas Girke
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Motivation: The prediction of biologically active compounds is of great importance for high-throughput screening (HTS) approaches in drug discovery and chemical genomics. Many computational methods in this area focus on measuring the structural similarities between chemical structures. However, traditional similarity measures are often too rigid or consider only global similarities between structures. The maximum common substructure (MCS) approach provides a more promising and flexible alternative for predicting bioactive compounds.