Combining Transition Path Sampling with Data-Driven Collective Variables through a Reactivity-Biased Shooting Algorithm-Reference-Cited by-同舟云学术

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Combining Transition Path Sampling with Data-Driven Collective Variables through a Reactivity-Biased Shooting Algorithm

Published:2024-05-27 Issue:11 Volume:20 Page:4523-4532
ISSN:1549-9618
Container-title:Journal of Chemical Theory and Computation
language:en
Short-container-title:J. Chem. Theory Comput.

Author:

Zhang Jintu¹²,Zhang Odin¹,Bonati Luigi²^ORCID,Hou TingJun¹³^ORCID

Affiliation:

1. Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China

2. Atomistic Simulations, Italian Institute of Technology, Genova 16152, Italy

3. State Key Lab of CAD&CG, Zhejiang University, Hangzhou, Zhejiang 310058, China

Funder

Bundesministerium f?r Bildung und Forschung

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.4c00423

Reference47 articles.

1. Long-timescale molecular dynamics simulations of protein structure and function

2. Assessing the accuracy of physical models used in protein-folding simulations: quantitative evidence from long molecular dynamics simulations

3. Unified Approach for Molecular Dynamics and Density-Functional Theory

4. Enhanced sampling techniques in molecular dynamics simulations of biological systems

5. Enhanced sampling in molecular dynamics

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