Learning Correlations between Internal Coordinates to Improve 3D Cartesian Coordinates for Proteins-Reference-Cited by-同舟云学术

Learning Correlations between Internal Coordinates to Improve 3D Cartesian Coordinates for Proteins

Published:2023-02-07 Issue:14 Volume:19 Page:4689-4700
ISSN:1549-9618
Container-title:Journal of Chemical Theory and Computation
language:en
Short-container-title:J. Chem. Theory Comput.

Author:

Li Jie¹^ORCID,Zhang Oufan¹,Lee Seokyoung¹,Namini Ashley²,Liu Zi Hao²³^ORCID,Teixeira João M. C.²,Forman-Kay Julie D.²³^ORCID,Head-Gordon Teresa¹⁴^ORCID

Affiliation:

1. Pitzer Center for Theoretical Chemistry, Department of Chemistry, University of California, Berkeley, California 94720, United States

2. Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5S 1A8, Canada

3. Department of Biochemistry, University of Toronto, Toronto, Ontario M5G 1X8, Canada

4. Departments of Bioengineering and Chemical and Biomolecular Engineering, University of California, Berkeley, California 94720, United States

Funder

Canada Research Chairs

Natural Sciences and Engineering Research Council of Canada

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.2c01270

Reference45 articles.

1. Geometry optimization in delocalized internal coordinates: An efficient quadratically scaling algorithm for large molecules

2. Internal Coordinates for Molecular Dynamics and Minimization in Structure Determination and Refinement

3. Molecular Dynamics: Survey of Methods for Simulating the Activity of Proteins

4. Protein Data Bank: the single global archive for 3D macromolecular structure data

5. Practical conversion from torsion space to Cartesian space forin silico protein synthesis

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Local vibrational mode theory meets graph theory: Complete and non-redundant local mode sets;Chemical Physics Letters;2024-08

2. A New Perspective on the Homogeneous Coordinate System for Calculating Interatomic Distances and Their Derivatives in Terms of Internal Coordinates;Advanced Theory and Simulations;2024-07-15

3. Machine-learning-based methods to generate conformational ensembles of disordered proteins;Biophysical Journal;2024-01

4. Open-Source Machine Learning in Computational Chemistry;Journal of Chemical Information and Modeling;2023-07-19

5. IDPConformerGenerator: A Flexible Software Suite for Sampling the Conformational Space of Disordered Protein States;The Journal of Physical Chemistry A;2022-08-28