Simulation and Machine Learning Methods for Ion-Channel Structure Determination, Mechanistic Studies and Drug Design
Zhengdan Zhu, Zhenfeng Deng, Qinrui Wang, Yuhang Wang, Duo Zhang, Ruihan Xu, Lvjun Guo, Han Wen
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.