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Molecular similarity and diversity approaches in chemoinformatics
Author(s) -
Khanna Varun,
Ranganathan Shoba
Publication year - 2011
Publication title -
drug development research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.582
H-Index - 60
eISSN - 1098-2299
pISSN - 0272-4391
DOI - 10.1002/ddr.20404
Subject(s) - cheminformatics , context (archaeology) , in silico , computer science , selection (genetic algorithm) , similarity (geometry) , virtual screening , computational biology , biochemical engineering , drug discovery , data science , machine learning , artificial intelligence , bioinformatics , engineering , biology , paleontology , biochemistry , image (mathematics) , gene
Combinatorial synthesis and high‐throughput screening (HTS) are playing increasingly important roles in chemoinformatics. This review gives an overview of the strategies available for library design and compound selection. Although the traditional approach of diversity‐oriented library design continues to be an important criterion in lead generation, nevertheless, pharmacokinetic properties are also widely recognized in compound selection for generating lead libraries. We summarize all the current molecular similarity and diversity methods employed in chemoinformatics to design lead libraries for in silico drug discovery. We have also included a section on popular molecular descriptors and similarity/diversity coefficients. Recent developments, include multi‐optimization design algorithms to select suitable molecules, such as Pareto‐optimization, representing a compromise between several competing objectives, have also been discussed in the context of virtual screening and library design. Drug Dev Res 72: 74–84, 2011. © 2010 Wiley‐Liss, Inc.