Computing disease-linked SOD1 mutations: deciphering protein stability and patient-phenotype relations

Abstract Protein stability is a requisite in the field of biotechnology, cell biology and drug design. To understand effects of amino acid substitutions, computational models are preferred to save time and expenses. As a systemically important, highly abundant, stable protein, the knowledge of Cu/Zn...

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Autores principales:	Vijay Kumar, Safikur Rahman, Hani Choudhry, Mazin A. Zamzami, Mohammad Sarwar Jamal, Asimul Islam, Faizan Ahmad, Md. Imtaiyaz Hassan
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/7a7aa2c0cdef490db3fa45664a3ddf86
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spelling	oai:doaj.org-article:7a7aa2c0cdef490db3fa45664a3ddf862021-12-02T16:06:55ZComputing disease-linked SOD1 mutations: deciphering protein stability and patient-phenotype relations10.1038/s41598-017-04950-92045-2322https://doaj.org/article/7a7aa2c0cdef490db3fa45664a3ddf862017-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-04950-9https://doaj.org/toc/2045-2322Abstract Protein stability is a requisite in the field of biotechnology, cell biology and drug design. To understand effects of amino acid substitutions, computational models are preferred to save time and expenses. As a systemically important, highly abundant, stable protein, the knowledge of Cu/Zn Superoxide dismutase1 (SOD1) is important, making it a suitable test case for genotype-phenotype correlation in understanding ALS. Here, we report performance of eight protein stability calculators (PoPMuSiC 3.1, I-Mutant 2.0, I-Mutant 3.0, CUPSAT, FoldX, mCSM, BeatMusic and ENCoM) against 54 experimental stability changes due to mutations of SOD1. Four different high-resolution structures were used to test structure sensitivity that may affect protein calculations. Bland-Altman plot was also used to assess agreement between stability analyses. Overall, PoPMuSiC and FoldX emerge as the best methods in this benchmark. The relative performance of all the eight methods was very much structure independent, and also displayed less structural sensitivity. We also analyzed patient’s data in relation to experimental and computed protein stabilities for mutations of human SOD1. Correlation between disease phenotypes and stability changes suggest that the changes in SOD1 stability correlate with ALS patient survival times. Thus, the results clearly demonstrate the importance of protein stability in SOD1 pathogenicity.Vijay KumarSafikur RahmanHani ChoudhryMazin A. ZamzamiMohammad Sarwar JamalAsimul IslamFaizan AhmadMd. Imtaiyaz HassanNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-13 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Vijay Kumar Safikur Rahman Hani Choudhry Mazin A. Zamzami Mohammad Sarwar Jamal Asimul Islam Faizan Ahmad Md. Imtaiyaz Hassan Computing disease-linked SOD1 mutations: deciphering protein stability and patient-phenotype relations
description	Abstract Protein stability is a requisite in the field of biotechnology, cell biology and drug design. To understand effects of amino acid substitutions, computational models are preferred to save time and expenses. As a systemically important, highly abundant, stable protein, the knowledge of Cu/Zn Superoxide dismutase1 (SOD1) is important, making it a suitable test case for genotype-phenotype correlation in understanding ALS. Here, we report performance of eight protein stability calculators (PoPMuSiC 3.1, I-Mutant 2.0, I-Mutant 3.0, CUPSAT, FoldX, mCSM, BeatMusic and ENCoM) against 54 experimental stability changes due to mutations of SOD1. Four different high-resolution structures were used to test structure sensitivity that may affect protein calculations. Bland-Altman plot was also used to assess agreement between stability analyses. Overall, PoPMuSiC and FoldX emerge as the best methods in this benchmark. The relative performance of all the eight methods was very much structure independent, and also displayed less structural sensitivity. We also analyzed patient’s data in relation to experimental and computed protein stabilities for mutations of human SOD1. Correlation between disease phenotypes and stability changes suggest that the changes in SOD1 stability correlate with ALS patient survival times. Thus, the results clearly demonstrate the importance of protein stability in SOD1 pathogenicity.
format	article
author	Vijay Kumar Safikur Rahman Hani Choudhry Mazin A. Zamzami Mohammad Sarwar Jamal Asimul Islam Faizan Ahmad Md. Imtaiyaz Hassan
author_facet	Vijay Kumar Safikur Rahman Hani Choudhry Mazin A. Zamzami Mohammad Sarwar Jamal Asimul Islam Faizan Ahmad Md. Imtaiyaz Hassan
author_sort	Vijay Kumar
title	Computing disease-linked SOD1 mutations: deciphering protein stability and patient-phenotype relations
title_short	Computing disease-linked SOD1 mutations: deciphering protein stability and patient-phenotype relations
title_full	Computing disease-linked SOD1 mutations: deciphering protein stability and patient-phenotype relations
title_fullStr	Computing disease-linked SOD1 mutations: deciphering protein stability and patient-phenotype relations
title_full_unstemmed	Computing disease-linked SOD1 mutations: deciphering protein stability and patient-phenotype relations
title_sort	computing disease-linked sod1 mutations: deciphering protein stability and patient-phenotype relations
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/7a7aa2c0cdef490db3fa45664a3ddf86
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Computing disease-linked SOD1 mutations: deciphering protein stability and patient-phenotype relations

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