A computational in silico approach to predict high-risk coding and non-coding SNPs of human PLCG1 gene.

PLCG1 gene is responsible for many T-cell lymphoma subtypes, including peripheral T-cell lymphoma (PTCL), angioimmunoblastic T-cell lymphoma (AITL), cutaneous T-cell lymphoma (CTCL), adult T-cell leukemia/lymphoma along with other diseases. Missense mutations of this gene have already been found in...

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Autores principales:	Safayat Mahmud Khan, Ar-Rafi Md Faisal, Tasnin Akter Nila, Nabila Nawar Binti, Md Ismail Hosen, Hossain Uddin Shekhar
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/19e98233cc124af6beaa08413a367474
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spelling	oai:doaj.org-article:19e98233cc124af6beaa08413a3674742021-12-02T20:12:45ZA computational in silico approach to predict high-risk coding and non-coding SNPs of human PLCG1 gene.1932-620310.1371/journal.pone.0260054https://doaj.org/article/19e98233cc124af6beaa08413a3674742021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0260054https://doaj.org/toc/1932-6203PLCG1 gene is responsible for many T-cell lymphoma subtypes, including peripheral T-cell lymphoma (PTCL), angioimmunoblastic T-cell lymphoma (AITL), cutaneous T-cell lymphoma (CTCL), adult T-cell leukemia/lymphoma along with other diseases. Missense mutations of this gene have already been found in patients of CTCL and AITL. The non-synonymous single nucleotide polymorphisms (nsSNPs) can alter the protein structure as well as its functions. In this study, probable deleterious and disease-related nsSNPs in PLCG1 were identified using SIFT, PROVEAN, PolyPhen-2, PhD-SNP, Pmut, and SNPS&GO tools. Further, their effect on protein stability was checked along with conservation and solvent accessibility analysis by I-mutant 2.0, MUpro, Consurf, and Netsurf 2.0 server. Some SNPs were finalized for structural analysis with PyMol and BIOVIA discovery studio visualizer. Out of the 16 nsSNPs which were found to be deleterious, ten nsSNPs had an effect on protein stability, and six mutations (L411P, R355C, G493D, R1158H, A401V and L455F) were predicted to be highly conserved. Among the six highly conserved mutations, four nsSNPs (R355C, A401V, L411P and L455F) were part of the catalytic domain. L411P, L455F and G493D made significant structural change in the protein structure. Two mutations-Y210C and R1158H had post-translational modification. In the 5' and 3' untranslated region, three SNPs, rs139043247, rs543804707, and rs62621919 showed possible miRNA target sites and DNA binding sites. This in silico analysis has provided a structured dataset of PLCG1 gene for further in vivo researches. With the limitation of computational study, it can still prove to be an asset for the identification and treatment of multiple diseases associated with the target gene.Safayat Mahmud KhanAr-Rafi Md FaisalTasnin Akter NilaNabila Nawar BintiMd Ismail HosenHossain Uddin ShekharPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 11, p e0260054 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Safayat Mahmud Khan Ar-Rafi Md Faisal Tasnin Akter Nila Nabila Nawar Binti Md Ismail Hosen Hossain Uddin Shekhar A computational in silico approach to predict high-risk coding and non-coding SNPs of human PLCG1 gene.
description	PLCG1 gene is responsible for many T-cell lymphoma subtypes, including peripheral T-cell lymphoma (PTCL), angioimmunoblastic T-cell lymphoma (AITL), cutaneous T-cell lymphoma (CTCL), adult T-cell leukemia/lymphoma along with other diseases. Missense mutations of this gene have already been found in patients of CTCL and AITL. The non-synonymous single nucleotide polymorphisms (nsSNPs) can alter the protein structure as well as its functions. In this study, probable deleterious and disease-related nsSNPs in PLCG1 were identified using SIFT, PROVEAN, PolyPhen-2, PhD-SNP, Pmut, and SNPS&GO tools. Further, their effect on protein stability was checked along with conservation and solvent accessibility analysis by I-mutant 2.0, MUpro, Consurf, and Netsurf 2.0 server. Some SNPs were finalized for structural analysis with PyMol and BIOVIA discovery studio visualizer. Out of the 16 nsSNPs which were found to be deleterious, ten nsSNPs had an effect on protein stability, and six mutations (L411P, R355C, G493D, R1158H, A401V and L455F) were predicted to be highly conserved. Among the six highly conserved mutations, four nsSNPs (R355C, A401V, L411P and L455F) were part of the catalytic domain. L411P, L455F and G493D made significant structural change in the protein structure. Two mutations-Y210C and R1158H had post-translational modification. In the 5' and 3' untranslated region, three SNPs, rs139043247, rs543804707, and rs62621919 showed possible miRNA target sites and DNA binding sites. This in silico analysis has provided a structured dataset of PLCG1 gene for further in vivo researches. With the limitation of computational study, it can still prove to be an asset for the identification and treatment of multiple diseases associated with the target gene.
format	article
author	Safayat Mahmud Khan Ar-Rafi Md Faisal Tasnin Akter Nila Nabila Nawar Binti Md Ismail Hosen Hossain Uddin Shekhar
author_facet	Safayat Mahmud Khan Ar-Rafi Md Faisal Tasnin Akter Nila Nabila Nawar Binti Md Ismail Hosen Hossain Uddin Shekhar
author_sort	Safayat Mahmud Khan
title	A computational in silico approach to predict high-risk coding and non-coding SNPs of human PLCG1 gene.
title_short	A computational in silico approach to predict high-risk coding and non-coding SNPs of human PLCG1 gene.
title_full	A computational in silico approach to predict high-risk coding and non-coding SNPs of human PLCG1 gene.
title_fullStr	A computational in silico approach to predict high-risk coding and non-coding SNPs of human PLCG1 gene.
title_full_unstemmed	A computational in silico approach to predict high-risk coding and non-coding SNPs of human PLCG1 gene.
title_sort	computational in silico approach to predict high-risk coding and non-coding snps of human plcg1 gene.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/19e98233cc124af6beaa08413a367474
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A computational in silico approach to predict high-risk coding and non-coding SNPs of human PLCG1 gene.

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