Frontiers in Pharmacology (Jun 2022)

Simulation and Machine Learning Methods for Ion-Channel Structure Determination, Mechanistic Studies and Drug Design

  • Zhengdan Zhu,
  • Zhengdan Zhu,
  • Zhenfeng Deng,
  • Zhenfeng Deng,
  • Qinrui Wang,
  • Yuhang Wang,
  • Duo Zhang,
  • Duo Zhang,
  • Ruihan Xu,
  • Ruihan Xu,
  • Lvjun Guo,
  • Han Wen

DOI
https://doi.org/10.3389/fphar.2022.939555
Journal volume & issue
Vol. 13

Abstract

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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.

Keywords