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In Silico Evaluation of the Potential Association of the Pathogenic Mutations of Alpha Synuclein Protein with Induction of Synucleinopathies

Alpha synuclein (α-Syn) is a neuronal protein encoded by the SNCA gene and is involved in the development of Parkinson’s disease (PD). The objective of this study was to examine in silico the functional implications of non-synonymous single nucleotide polymorphisms (nsSNPs) in the SNCA gene. We used...

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Autores principales: Elnageeb, Mohamed E., Elfaki, Imadeldin, Adam, Khalid M., Ahmed, Elsadig Mohamed, Elkhalifa, Elkhalifa M., Abuagla, Hytham A., Ahmed, Abubakr Ali Elamin Mohamed, Ali, Elshazali Widaa, Eltieb, Elmoiz Idris, Edris, Ali M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10529770/
https://www.ncbi.nlm.nih.gov/pubmed/37754311
http://dx.doi.org/10.3390/diseases11030115
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author Elnageeb, Mohamed E.
Elfaki, Imadeldin
Adam, Khalid M.
Ahmed, Elsadig Mohamed
Elkhalifa, Elkhalifa M.
Abuagla, Hytham A.
Ahmed, Abubakr Ali Elamin Mohamed
Ali, Elshazali Widaa
Eltieb, Elmoiz Idris
Edris, Ali M.
author_facet Elnageeb, Mohamed E.
Elfaki, Imadeldin
Adam, Khalid M.
Ahmed, Elsadig Mohamed
Elkhalifa, Elkhalifa M.
Abuagla, Hytham A.
Ahmed, Abubakr Ali Elamin Mohamed
Ali, Elshazali Widaa
Eltieb, Elmoiz Idris
Edris, Ali M.
author_sort Elnageeb, Mohamed E.
collection PubMed
description Alpha synuclein (α-Syn) is a neuronal protein encoded by the SNCA gene and is involved in the development of Parkinson’s disease (PD). The objective of this study was to examine in silico the functional implications of non-synonymous single nucleotide polymorphisms (nsSNPs) in the SNCA gene. We used a range of computational algorithms such as sequence conservation, structural analysis, physicochemical properties, and machine learning. The sequence of the SNCA gene was analyzed, resulting in the mapping of 42,272 SNPs that are classified into different functional categories. A total of 177 nsSNPs were identified within the coding region; there were 20 variants that may influence the α-Syn protein structure and function. This identification was made by employing different analytical tools including SIFT, PolyPhen2, Mut-pred, SNAP2, PANTHER, PhD-SNP, SNP&Go, MUpro, Cosurf, I-Mut, and HOPE. Three mutations, V82A, K80E, and E46K, were selected for further examinations due to their spatial positioning within the α-Syn as determined by PyMol. Results indicated that these mutations may affect the stability and function of α-Syn. Then, a molecular dynamics simulation was conducted for the SNCA wildtype and the four mutant variants (p.A18G, p.V82A, p.K80E, and p.E46K). The simulation examined temperature, pressure, density, root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), solvent-accessible surface area (SASA), and radius of gyration (Rg). The data indicate that the mutations p.V82A, p.K80E, and p.E46K reduce the stability and functionality of α-Syn. These findings highlight the importance of understanding the impact of nsSNPs on α-syn structure and function. Our results required verifications in further protein functional and case–control studies. After being verified these findings can be used in genetic testing for the early diagnosis of PD, the evaluation of the risk factors, and therapeutic approaches.
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spelling pubmed-105297702023-09-28 In Silico Evaluation of the Potential Association of the Pathogenic Mutations of Alpha Synuclein Protein with Induction of Synucleinopathies Elnageeb, Mohamed E. Elfaki, Imadeldin Adam, Khalid M. Ahmed, Elsadig Mohamed Elkhalifa, Elkhalifa M. Abuagla, Hytham A. Ahmed, Abubakr Ali Elamin Mohamed Ali, Elshazali Widaa Eltieb, Elmoiz Idris Edris, Ali M. Diseases Article Alpha synuclein (α-Syn) is a neuronal protein encoded by the SNCA gene and is involved in the development of Parkinson’s disease (PD). The objective of this study was to examine in silico the functional implications of non-synonymous single nucleotide polymorphisms (nsSNPs) in the SNCA gene. We used a range of computational algorithms such as sequence conservation, structural analysis, physicochemical properties, and machine learning. The sequence of the SNCA gene was analyzed, resulting in the mapping of 42,272 SNPs that are classified into different functional categories. A total of 177 nsSNPs were identified within the coding region; there were 20 variants that may influence the α-Syn protein structure and function. This identification was made by employing different analytical tools including SIFT, PolyPhen2, Mut-pred, SNAP2, PANTHER, PhD-SNP, SNP&Go, MUpro, Cosurf, I-Mut, and HOPE. Three mutations, V82A, K80E, and E46K, were selected for further examinations due to their spatial positioning within the α-Syn as determined by PyMol. Results indicated that these mutations may affect the stability and function of α-Syn. Then, a molecular dynamics simulation was conducted for the SNCA wildtype and the four mutant variants (p.A18G, p.V82A, p.K80E, and p.E46K). The simulation examined temperature, pressure, density, root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), solvent-accessible surface area (SASA), and radius of gyration (Rg). The data indicate that the mutations p.V82A, p.K80E, and p.E46K reduce the stability and functionality of α-Syn. These findings highlight the importance of understanding the impact of nsSNPs on α-syn structure and function. Our results required verifications in further protein functional and case–control studies. After being verified these findings can be used in genetic testing for the early diagnosis of PD, the evaluation of the risk factors, and therapeutic approaches. MDPI 2023-09-06 /pmc/articles/PMC10529770/ /pubmed/37754311 http://dx.doi.org/10.3390/diseases11030115 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Elnageeb, Mohamed E.
Elfaki, Imadeldin
Adam, Khalid M.
Ahmed, Elsadig Mohamed
Elkhalifa, Elkhalifa M.
Abuagla, Hytham A.
Ahmed, Abubakr Ali Elamin Mohamed
Ali, Elshazali Widaa
Eltieb, Elmoiz Idris
Edris, Ali M.
In Silico Evaluation of the Potential Association of the Pathogenic Mutations of Alpha Synuclein Protein with Induction of Synucleinopathies
title In Silico Evaluation of the Potential Association of the Pathogenic Mutations of Alpha Synuclein Protein with Induction of Synucleinopathies
title_full In Silico Evaluation of the Potential Association of the Pathogenic Mutations of Alpha Synuclein Protein with Induction of Synucleinopathies
title_fullStr In Silico Evaluation of the Potential Association of the Pathogenic Mutations of Alpha Synuclein Protein with Induction of Synucleinopathies
title_full_unstemmed In Silico Evaluation of the Potential Association of the Pathogenic Mutations of Alpha Synuclein Protein with Induction of Synucleinopathies
title_short In Silico Evaluation of the Potential Association of the Pathogenic Mutations of Alpha Synuclein Protein with Induction of Synucleinopathies
title_sort in silico evaluation of the potential association of the pathogenic mutations of alpha synuclein protein with induction of synucleinopathies
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10529770/
https://www.ncbi.nlm.nih.gov/pubmed/37754311
http://dx.doi.org/10.3390/diseases11030115
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