OmeDDG: Improved Protein Mutation Stability Prediction Based on Predicted 3D Structures-Reference-Cited by-同舟云学术

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OmeDDG: Improved Protein Mutation Stability Prediction Based on Predicted 3D Structures

Published:2023-12-22 Issue:1 Volume:128 Page:67-76
ISSN:1520-6106
Container-title:The Journal of Physical Chemistry B
language:en
Short-container-title:J. Phys. Chem. B

Author:

Liu Baoying¹^ORCID,Jiang Yongquan¹²,Yang Yan¹²,Chen Jim X.³

Affiliation:

1. School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu 611756, Sichuan, China

2. Artificial Intelligence Research Institute, Southwest Jiaotong University, Chengdu 611756, Sichuan, China

3. Department of Computer Science, George Mason University, Fairfax, Virginia 22030-4444, United States

Funder

Fundamental Research Funds for the Central Universities

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.3c05601

Reference45 articles.

1. Beyond a pedagogical tool: 30 years of Molecular Biology of the Cell

2. Predicting changes in protein thermodynamic stability upon point mutation with deep 3D convolutional neural networks

3. HGVS Recommendations for the Description of Sequence Variants: 2016 Update

4. Effects of Mutations on the Thermodynamics of a Protein Folding Reaction: Implications for the Mechanism of Formation of the Intermediate and Transition States

5. Mycobacterium tuberculosis whole genome sequencing and protein structure modelling provides insights into anti-tuberculosis drug resistance

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