AUTHOR=Zhu Zhengdan , Deng Zhenfeng , Wang Qinrui , Wang Yuhang , Zhang Duo , Xu Ruihan , Guo Lvjun , Wen Han TITLE=Simulation and Machine Learning Methods for Ion-Channel Structure Determination, Mechanistic Studies and Drug Design JOURNAL=Frontiers in Pharmacology VOLUME=13 YEAR=2022 URL=https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2022.939555 DOI=10.3389/fphar.2022.939555 ISSN=1663-9812 ABSTRACT=

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.