Analysis and prediction of protein folding energy changes upon mutation by element specific persistent homology
Zixuan Cang, Guo-Wei Wei

TL;DR
This paper introduces a topology-based method using element specific persistent homology for predicting protein mutation impacts, outperforming existing geometric methods especially for membrane proteins.
Contribution
The work presents a novel topology-based mutation predictor (T-MP) that simplifies protein representation and retains biological information, improving prediction accuracy over current methods.
Findings
Achieved a Pearson correlation of 0.82 with RMSE 0.92 kcal/mol on globular proteins.
Outperformed existing methods with 84% higher Pearson correlation on membrane proteins.
Demonstrated superior performance in predicting mutation impacts using topological features.
Abstract
Motivation: Site directed mutagenesis is widely used to understand the structure and function of biomolecules. Computational prediction of protein mutation impacts offers a fast, economical and potentially accurate alternative to laboratory mutagenesis. Most existing methods rely on geometric descriptions, this work introduces a topology based approach to provide an entirely new representation of protein mutation impacts that could not be obtained from conventional techniques. Results: Topology based mutation predictor (T-MP) is introduced to dramatically reduce the geometric complexity and number of degrees of freedom of proteins, while element specific persistent homology is proposed to retain essential biological information. The present approach is found to outperform other existing methods in globular protein mutation impact predictions. A Pearson correlation coefficient of 0.82…
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Taxonomy
TopicsProtein Structure and Dynamics · RNA and protein synthesis mechanisms · Genomics and Chromatin Dynamics
Analysis and prediction of protein folding energy changes upon mutation by element specific persistent homology
Zixuan Cang1, and Guo-Wei Wei1,2,3 iii Address correspondences to Guo-Wei Wei. E-mail:[email protected]
1 Department of Mathematics
Michigan State University, MI 48824, USA
2 Department of Biochemistry and Molecular Biology
Michigan State University, MI 48824, USA
3 Department of Electrical and Computer Engineering
Michigan State University, MI 48824, USA
