4.8 Article

AutophagySMDB: a curated database of small molecules that modulate protein targets regulating autophagy

期刊

AUTOPHAGY
卷 15, 期 7, 页码 1280-1295

出版社

TAYLOR & FRANCIS INC
DOI: 10.1080/15548627.2019.1571717

关键词

Autophagy; autophagySMDB; database; drug target; small molecule

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Macroautophagy/autophagy is a complex self-degradative mechanism responsible for clearance of non functional organelles and proteins. A range of factors influences the autophagic process, and disruptions in autophagy-related mechanisms lead to disease states, and further exacerbation of disease. Despite in-depth research into autophagy and its role in pathophysiological processes, the resources available to use it for therapeutic purposes are currently lacking. Herein we report the Autophagy Small Molecule Database (AutophagySMDB; ) of small molecules and their cognate protein targets that modulate autophagy. Presently, AutophagySMDB enlists ~10,000 small molecules which regulate 71 target proteins. All entries are comprised of information such as EC50 (half maximal effective concentration), IC50 (half maximal inhibitory concentration), Kd (dissociation constant) and Ki (inhibition constant), IUPAC name, canonical SMILE, structure, molecular weight, QSAR (quantitative structure activity relationship) properties such as hydrogen donor and acceptor count, aromatic rings and XlogP. AutophagySMDB is an exhaustive, cross-platform, manually curated database, where either the cognate targets for small molecule or small molecules for a target can be searched. This database is provided with different search options including text search, advanced search and structure search. Various computational tools such as tree tool, cataloging tools, and clustering tools have also been implemented for advanced analysis. Data and the tools provided in this database helps to identify common or unique scaffolds for designing novel drugs or to improve the existing ones for autophagy small molecule therapeutics. The approach to multitarget drug discovery by identifying common scaffolds has been illustrated with experimental validation.

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