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Simulation and Machine Learning Methods for Ion-Channel Structure Determination, Mechanistic Studies and Drug Design.
Zhu, Zhengdan; Deng, Zhenfeng; Wang, Qinrui; Wang, Yuhang; Zhang, Duo; Xu, Ruihan; Guo, Lvjun; Wen, Han.
Afiliação
  • Zhu Z; Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
  • Deng Z; Beijing Institute of Big Data Research, Beijing, China.
  • Wang Q; DP Technology, Beijing, China.
  • Wang Y; School of Pharmaceutical Sciences, Peking University, Beijing, China.
  • Zhang D; DP Technology, Beijing, China.
  • Xu R; DP Technology, Beijing, China.
  • Guo L; Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
  • Wen H; DP Technology, Beijing, China.
Front Pharmacol ; 13: 939555, 2022.
Article em En | MEDLINE | ID: mdl-35837274
Ion channels are expressed in almost all living cells, controlling the in-and-out communications, making them ideal drug targets, especially for central nervous system diseases. However, owing to their dynamic nature and the presence of a membrane environment, ion channels remain difficult targets for the past decades. Recent advancement in cryo-electron microscopy and computational methods has shed light on this issue. An explosion in high-resolution ion channel structures paved way for structure-based rational drug design and the state-of-the-art simulation and machine learning techniques dramatically improved the efficiency and effectiveness of computer-aided drug design. Here we present an overview of how simulation and machine learning-based methods fundamentally changed the ion channel-related drug design at different levels, as well as the emerging trends in the field.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Pharmacol Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Pharmacol Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China