Systemic Evolutionary Chemical Space Exploration for Drug Discovery

Overview

Journal J Cheminform

Publisher Biomed Central

Specialty Chemistry

Date 2022 Apr 2

PMID 35365231

Authors

Chong Lu

Shien Liu

Weihua Shi

Jun Yu

Zhou Zhou

Xiaoxiao Zhang

Xiaoli Lu

Faji Cai

Ning Xia

Yikai Wang

Affiliations

Soon will be listed here.

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.

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