Predicting the impacts of mutations on protein-ligand binding affinity based on molecular dynamics simulations and machine learning methods

Predicting the impacts of mutations on protein-ligand binding affinity based on molecular dynamics simulations and machine learning methods

Purpose: Mutation-induced variation of protein-ligand binding affinity is the key to many genetic diseases and the emergence of drug resistance, and therefore predicting such mutation impacts is of great importance. In this work, we aim to predict the mutation impacts on protein-ligand binding affin...

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Bibliographic Details
Main Authors: Debby D. Wang, Le Ou-Yang, Haoran Xie, Mengxu Zhu, Hong Yan
Format: Article
Language:English
Published: Elsevier 2020-01-01
Series:Computational and Structural Biotechnology Journal
Subjects:
Missense mutation
Mutation impact
Protein-ligand binding affinity
Molecular dynamics (MD) simulations
Local geometrical features
Time series features
Online Access:http://www.sciencedirect.com/science/article/pii/S2001037019303757

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http://www.sciencedirect.com/science/article/pii/S2001037019303757

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