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Article

Prediction of mutation-induced protein stability changes based on the geometric representations learned by a self-supervised method.

BMC bioinformatics - 28 Aug 2024

Li Shan Shan, Liu Zhao Ming, Li Jiao, Ma Yi Bo, Dong Ze Yuan, Hou Jun Wei, Shen Fu Jie, Wang Wei Bu, Li Qi Ming, Su Ji Guo

Abstract excerpt

BACKGROUND: Thermostability is a fundamental property of proteins to maintain their biological functions. Predicting protein stability changes upon mutation is important for our understanding protein structure-function relationship, and is also of great interest in protein engineering and pharmaceutical design. RESULTS: Here we present mutDDG-SSM, a deep learning-based framework that uses the geometric...

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Computational Biology
Databases, Protein
Deep Learning
Myoglobin
Protein Stability

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Supervised Machine Learning

Tumor Suppressor Protein p53

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PMID: 39198740
DOI: 10.1186/s12859-024-05876-6
PMCID: PMC11360314

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