Recent advances in the development of DprE1 inhibitors using AI/CADD approaches

Kepeng Chen; Ruolan Xu; Xueping Hu; Dan Li; Tingjun Hou; Yu Kang

doi:10.1016/j.drudis.2024.103987

Recent advances in the development of DprE1 inhibitors using AI/CADD approaches

Drug Discov Today. 2024 Apr 25;29(6):103987. doi: 10.1016/j.drudis.2024.103987. Online ahead of print.

Authors

Kepeng Chen¹, Ruolan Xu¹, Xueping Hu², Dan Li¹, Tingjun Hou³, Yu Kang⁴

Affiliations

¹ College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China.
² Institute of Molecular Sciences and Engineering, Institute of Frontier and Interdisciplinary Science, Shandong University, Qingdao, Shandong 266237, China.
³ College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China. Electronic address: tingjunhou@zju.edu.cn.
⁴ College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China. Electronic address: yukang@zju.edu.cn.

PMID: 38670256
DOI: 10.1016/j.drudis.2024.103987

Abstract

Tuberculosis (TB) is a global lethal disease caused by Mycobacterium tuberculosis (Mtb). The flavoenzyme decaprenylphosphoryl-β-d-ribose 2'-oxidase (DprE1) plays a crucial part in the biosynthesis of lipoarabinomannan and arabinogalactan for the cell wall of Mtb and represents a promising target for anti-TB drug development. Therefore, there is an urgent need to discover DprE1 inhibitors with novel scaffolds, improved bioactivity and high drug-likeness. Recent studies have shown that artificial intelligence/computer-aided drug design (AI/CADD) techniques are powerful tools in the discovery of novel DprE1 inhibitors. This review provides an overview of the discovery of DprE1 inhibitors and their underlying mechanism of action and highlights recent advances in the discovery and optimization of DprE1 inhibitors using AI/CADD approaches.

Keywords: DprE1 inhibitors; artificial intelligence drug design; computer-aided drug design; tuberculosis.

Publication types

Review