Residue-Frustration-Based Prediction of Protein–Protein Interactions Using Machine Learning-Reference-Cited by-同舟云学术

Residue-Frustration-Based Prediction of Protein–Protein Interactions Using Machine Learning

Published:2022-02-16 Issue:8 Volume:126 Page:1719-1727
ISSN:1520-6106
Container-title:The Journal of Physical Chemistry B
language:en
Short-container-title:J. Phys. Chem. B

Author:

Zhou Xiaozhou¹,Song Haoyu¹,Li Jingyuan¹^ORCID

Affiliation:

1. Zhejiang Province Key Laboratory of Quantum Technology and Device, Institute of Quantitative Biology, Department of Physics, Zhejiang University, Hangzhou 310027, Zhejiang, China

Funder

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

Materials Chemistry,Surfaces, Coatings and Films,Physical and Theoretical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpcb.1c10525

Reference46 articles.

1. Transient protein-protein interactions

2. The ClusPro web server for protein–protein docking

3. HDOCK: a web server for protein–protein and protein–DNA/RNA docking based on a hybrid strategy

4. LightDock: a new multi-scale approach to protein–protein docking

5. SwarmDock: a server for flexible protein–protein docking

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