Comparative analysis of web-based programs for single amino acid substitutions in proteinsopen access
- Authors
- Choudhury, A.; Mohammad, T.; Anjum, F.; Shafie, A.; Singh, I.K.; Abdullaev, B.; Pasupuleti, V.R.; Adnan, M.; Yadav, D.K.; Hassan, Md.I.
- Issue Date
- May-2022
- Publisher
- Public Library of Science
- Citation
- PLoS ONE, v.17, no.5
- Journal Title
- PLoS ONE
- Volume
- 17
- Number
- 5
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/84890
- DOI
- 10.1371/journal.pone.0267084
- ISSN
- 1932-6203
- Abstract
- Single amino-acid substitution in a protein affects its structure and function. These changes are the primary reasons for the advent of many complex diseases. Analyzing single point mutations in a protein is crucial to see their impact and to understand the disease mechanism. This has given many biophysical resources, including databases and web-based tools to explore the effects of mutations on the structure and function of human proteins. For a given mutation, each tool provides a score-based outcomes which indicate deleterious probability. In recent years, developments in existing programs and the introduction of new prediction algorithms have transformed the state-of-the-art protein mutation analysis. In this study, we have performed a systematic study of the most commonly used mutational analysis programs (10 sequence-based and 5 structure-based) to compare their prediction efficiency. We have carried out extensive mutational analyses using these tools for previously known pathogenic single point mutations of five different proteins. These analyses suggested that sequence-based tools, PolyPhen2, PROVEAN, and PMut, and structure-based web tool, mCSM have a better prediction accuracy. This study indicates that the employment of more than one program based on different approaches should significantly improve the prediction power of the available methods. © 2022 Choudhury et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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