Physics-Based Computational Protein Design: An Update-Reference-Cited by-同舟云学术

Physics-Based Computational Protein Design: An Update

Published:2020-11-10 Issue:51 Volume:124 Page:10637-10648
ISSN:1089-5639
Container-title:The Journal of Physical Chemistry A
language:en
Short-container-title:J. Phys. Chem. A

Author:

Mignon David¹,Druart Karen¹,Michael Eleni²,Opuu Vaitea¹,Polydorides Savvas²,Villa Francesco¹,Gaillard Thomas¹^ORCID,Panel Nicolas¹^ORCID,Archontis Georgios²,Simonson Thomas¹^ORCID

Affiliation:

1. Laboratoire de Biologie Structurale de la Cellule (CNRS UMR7654), Ecole Polytechnique, 91128 Palaiseau, France

2. Department of Physics, University of Cyprus, PO20537, CY1678 Nicosia, Cyprus

Publisher

American Chemical Society (ACS)

Subject

Physical and Theoretical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpca.0c07605

Reference119 articles.

1. De Novo Protein Design: Fully Automated Sequence Selection

2. Design of a Novel Globular Protein Fold with Atomic-Level Accuracy

3. A Large Scale Test of Computational Protein Design: Folding and Stability of Nine Completely Redesigned Globular Proteins

4. Protein design with a comprehensive statistical energy function and boosted by experimental selection for foldability

5. De novo design of a four-fold symmetric TIM-barrel protein with atomic-level accuracy

Cited by 17 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. The Damietta Server: a comprehensive protein design toolkit;Nucleic Acids Research;2024-04-25

2. When Data Are Lacking: Physics-Based Inverse Design of Biopolymers Interacting with Complex, Fluid Phases;Journal of Chemical Theory and Computation;2024-02-27

3. From De Novo Design to Redesign: Harnessing Computational Protein Design for Understanding SARS-CoV-2 Molecular Mechanisms and Developing Therapeutics;The Journal of Physical Chemistry B;2023-10-10

4. Redesigning methionyl‐tRNA synthetase for β‐methionine activity with adaptive landscape flattening and experiments;Protein Science;2023-08-25

5. Machine Learning: A Suitable Method for Biocatalysis;Catalysts;2023-06-01