An Efficient Path Classification Algorithm Based on Variational Autoencoder to Identify Metastable Path Channels for Complex Conformational Changes
Author:
Affiliation:
1. Department of Chemistry, Theoretical Chemistry Institute, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
2. Biophysics Graduate Program, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
Funder
Wisconsin Alumni Research Foundation
Office of the Vice Chancellor for Research and Graduate Education, University of Wisconsin-Madison
National Institute of General Medical Sciences
Publisher
American Chemical Society (ACS)
Subject
Physical and Theoretical Chemistry,Computer Science Applications
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.3c00318
Reference107 articles.
1. Dynamics of an Intrinsically Disordered Protein Reveal Metastable Conformations That Potentially Seed Aggregation
2. Molecular Simulation of ab Initio Protein Folding for a Millisecond Folder NTL9(1−39)
3. Accessing a Hidden Conformation of the Maltose Binding Protein Using Accelerated Molecular Dynamics
4. Predicting the structural basis of targeted protein degradation by integrating molecular dynamics simulations with structural mass spectrometry
5. Toward Atomistic Modeling of Irreversible Covalent Inhibitor Binding Kinetics
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