Automatic Identification of Analogue Series from Large Compound Data Sets: Methods and Applications
| Autor: | Martin Vogt, José J. Naveja |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
compound-core relationships
Theoretical computer science Computer science Pharmaceutical Science Review Analytical Chemistry molecular scaffold QD241-441 matched molecular pairs medicinal chemistry Drug Discovery Physical and Theoretical Chemistry Structure (mathematical logic) Series (mathematics) Drug discovery Organic Chemistry Substitution (logic) structure-activity relationships cheminformatics Identification (information) core structure Chemistry (miscellaneous) Cheminformatics Key (cryptography) matched molecular series Molecular Medicine Single-core analogue series |
| Zdroj: | Molecules Molecules, Vol 26, Iss 5291, p 5291 (2021) |
| ISSN: | 1420-3049 |
| Popis: | Analogue series play a key role in drug discovery. They arise naturally in lead optimization efforts where analogues are explored based on one or a few core structures. However, it is much harder to accurately identify and extract pairs or series of analogue molecules in large compound databases with no predefined core structures. This methodological review outlines the most common and recent methodological developments to automatically identify analogue series in large libraries. Initial approaches focused on using predefined rules to extract scaffold structures, such as the popular Bemis–Murcko scaffold. Later on, the matched molecular pair concept led to efficient algorithms to identify similar compounds sharing a common core structure by exploring many putative scaffolds for each compound. Further developments of these ideas yielded, on the one hand, approaches for hierarchical scaffold decomposition and, on the other hand, algorithms for the extraction of analogue series based on single-site modifications (so-called matched molecular series) by exploring potential scaffold structures based on systematic molecule fragmentation. Eventually, further development of these approaches resulted in methods for extracting analogue series defined by a single core structure with several substitution sites that allow convenient representations, such as R-group tables. These methods enable the efficient analysis of large data sets with hundreds of thousands or even millions of compounds and have spawned many related methodological developments. |
| Databáze: | OpenAIRE |
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