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WIREs Comput Mol Sci
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In silico applications of bioisosterism in contemporary medicinal chemistry practice

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Abstract Bioisosterism is a key concept in medicinal chemistry, as it allows medicinal chemists to interchange structural fragments without significant perturbation in biological activity. Not surprisingly, given the vast amount of bioactivity data and chemoinformatics resources now available, there has been a significant surge in the number of computational approaches available to mine and identify bioisosteric replacements for fragments of bioactive compounds. Such methods have certainly provided medicinal chemists with a diverse arsenal of in‐house, commercial, and academic tools and interfaces to aid in the optimization across a number of end points such as bioactivity; selectivity; and absorption, distribution, metabolism, excretion, and toxicity properties for effective and efficient drug design. These in silico bioisosteric replacement mining approaches can generally be divided into two categories, namely ligand based and structure based. The approaches of the former category use information that is derived from ligands, whereas the latter category requires knowledge of the biological target, as well as specific knowledge of the interactions between ligand and target in the binding pocket. Ligand‐based methodologies are also typically divided into similarity‐based and database mining (or knowledge‐based) approaches. In general, the former provide an assessment of putative bioisosteric fragments and substructures, in terms of molecular topology and descriptors, whereas the latter extract structural transformations from large chemical repositories and associate them with the induced change in biological or any other property of interest. Following systematic retrospective studies, a large number of nonclassical bioisosteric equivalents have been reported in the literature. This article is categorized under: Computer and Information Science > Chemoinformatics

The top four suggested ring systems for methylene dioxyphenyl provided by GlaxoSmithKline's Drug Rings Database. (Reproduced with permission from Ref 29. Copyright 2003, American Chemical Society.)

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Example of reducing a molecular graph into three nodes bases on its pharmacophoric features.

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Iterative increment of the bond distance radius starting from atom at bond radius 0.

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An example of a dictionary‐based fingerprint.

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Two examples of nonclassical, context‐sensitive bioisosteric transformations found in the ChEMBL database. (Reproduced with permission from Ref 65. Copyright 2011, Future Science Ltd.)

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Two examples of context‐sensitive bioisosteric replacements for lipophilicity (48 pairs, above) and P‐gp efflux (160 pairs, below) found by data mining in the Pfizer archive. (Reproduced with permission from Ref 58. Copyright 2011, Elsevier.)

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Regions to identify patterns of pairwise transformations. (Reproduced with permission from Ref 58. Copyright 2011, Elsevier.)

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Example of a matched molecular pair where the corresponding transformation is H≫CF3.

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