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Systemic evolutionary chemical space exploration for drug discovery.

Authors :
Lu, Chong
Liu, Shien
Shi, Weihua
Yu, Jun
Zhou, Zhou
Zhang, Xiaoxiao
Lu, Xiaoli
Cai, Faji
Xia, Ning
Wang, Yikai
Source :
Journal of Cheminformatics; 4/1/2022, Vol. 14 Issue 1, p1-17, 17p
Publication Year :
2022

Abstract

Chemical space exploration is a major task of the hit-finding process during the pursuit of novel chemical entities. Compared with other screening technologies, computational de novo design has become a popular approach to overcome the limitation of current chemical libraries. Here, we reported a de novo design platform named systemic evolutionary chemical space explorer (SECSE). The platform was conceptually inspired by fragment-based drug design, that miniaturized a "lego-building" process within the pocket of a certain target. The key to virtual hits generation was then turned into a computational search problem. To enhance search and optimization, human intelligence and deep learning were integrated. Application of SECSE against phosphoglycerate dehydrogenase (PHGDH), proved its potential in finding novel and diverse small molecules that are attractive starting points for further validation. This platform is open-sourced and the code is available at http://github.com/KeenThera/SECSE. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17582946
Volume :
14
Issue :
1
Database :
Complementary Index
Journal :
Journal of Cheminformatics
Publication Type :
Academic Journal
Accession number :
156100207
Full Text :
https://doi.org/10.1186/s13321-022-00598-4