Literature DB >> 17554854

In silico identification of bioisosteric functional groups.

Peter Ertl1.   

Abstract

Bioisosteric replacement is a standard technique that is used in medicinal chemistry to design analogs of bioactive molecules with similar activity and with additional improved characteristics. However, successful bioisosteric design requires significant prior chemical knowledge, and the identification of a replacement group with an optimal balance of steric, hydrophobic, electronic and hydrogen-bonding properties that all influence ligand-receptor interactions usually requires a demanding procedure of trial and error. In this article, various methods that can help medicinal chemists to identify bioisosteric analogs are reviewed, beginning with classical techniques using experimental group properties. Methods to find bioisosteric pairs based on the analysis of large molecular databases are discussed. Various descriptors to characterize properties of functional groups are described, and methods to identify bioisosteric replacement by conducting property similarity search are presented. Examples of tools that help chemists to navigate within the group functional property space are also provided.

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Year:  2007        PMID: 17554854

Source DB:  PubMed          Journal:  Curr Opin Drug Discov Devel        ISSN: 1367-6733


  4 in total

Review 1.  Amide Bond Bioisosteres: Strategies, Synthesis, and Successes.

Authors:  Shikha Kumari; Angelica V Carmona; Amit K Tiwari; Paul C Trippier
Journal:  J Med Chem       Date:  2020-08-04       Impact factor: 7.446

2.  On drug discovery against infectious diseases and academic medicinal chemistry contributions.

Authors:  Yves L Janin
Journal:  Beilstein J Org Chem       Date:  2022-09-29       Impact factor: 2.544

3.  R-group replacement database for medicinal chemistry.

Authors:  Kosuke Takeuchi; Ryo Kunimoto; Jürgen Bajorath
Journal:  Future Sci OA       Date:  2021-06-30

4.  On the Value of Using 3D Shape and Electrostatic Similarities in Deep Generative Methods.

Authors:  Giovanni Bolcato; Esther Heid; Jonas Boström
Journal:  J Chem Inf Model       Date:  2022-03-10       Impact factor: 4.956

  4 in total

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