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In Silico profiling of deleterious amino acid substitutions of potential pathological importance in haemophlia A and haemophlia B
BACKGROUND: In this study, instead of current biochemical methods, the effects of deleterious amino acid substitutions in F8 and F9 gene upon protein structure and function were assayed by means of computational methods and information from the databases. Deleterious substitutions of F8 and F9 are r...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2012
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3361463/ https://www.ncbi.nlm.nih.gov/pubmed/22423892 http://dx.doi.org/10.1186/1423-0127-19-30 |
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author | C, George Priya Doss |
author_facet | C, George Priya Doss |
author_sort | C, George Priya Doss |
collection | PubMed |
description | BACKGROUND: In this study, instead of current biochemical methods, the effects of deleterious amino acid substitutions in F8 and F9 gene upon protein structure and function were assayed by means of computational methods and information from the databases. Deleterious substitutions of F8 and F9 are responsible for Haemophilia A and Haemophilia B which is the most common genetic disease of coagulation disorders in blood. Yet, distinguishing deleterious variants of F8 and F9 from the massive amount of nonfunctional variants that occur within a single genome is a significant challenge. METHODS: We performed an in silico analysis of deleterious mutations and their protein structure changes in order to analyze the correlation between mutation and disease. Deleterious nsSNPs were categorized based on empirical based and support vector machine based methods to predict the impact on protein functions. Furthermore, we modeled mutant proteins and compared them with the native protein for analysis of protein structure stability. RESULTS: Out of 510 nsSNPs in F8, 378 nsSNPs (74%) were predicted to be 'intolerant' by SIFT, 371 nsSNPs (73%) were predicted to be 'damaging' by PolyPhen and 445 nsSNPs (87%) as 'less stable' by I-Mutant2.0. In F9, 129 nsSNPs (78%) were predicted to be intolerant by SIFT, 131 nsSNPs (79%) were predicted to be damaging by PolyPhen and 150 nsSNPs (90%) as less stable by I-Mutant2.0. Overall, we found that I-Mutant which emphasizes support vector machine based method outperformed SIFT and PolyPhen in prediction of deleterious nsSNPs in both F8 and F9. CONCLUSIONS: The models built in this work would be appropriate for predicting the deleterious amino acid substitutions and their functions in gene regulation which would be useful for further genotype-phenotype researches as well as the pharmacogenetics studies. These in silico tools, despite being helpful in providing information about the nature of mutations, may also function as a first-pass filter to determine the substitutions worth pursuing for further experimental research in other coagulation disorder causing genes. |
format | Online Article Text |
id | pubmed-3361463 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-33614632012-05-29 In Silico profiling of deleterious amino acid substitutions of potential pathological importance in haemophlia A and haemophlia B C, George Priya Doss J Biomed Sci Research BACKGROUND: In this study, instead of current biochemical methods, the effects of deleterious amino acid substitutions in F8 and F9 gene upon protein structure and function were assayed by means of computational methods and information from the databases. Deleterious substitutions of F8 and F9 are responsible for Haemophilia A and Haemophilia B which is the most common genetic disease of coagulation disorders in blood. Yet, distinguishing deleterious variants of F8 and F9 from the massive amount of nonfunctional variants that occur within a single genome is a significant challenge. METHODS: We performed an in silico analysis of deleterious mutations and their protein structure changes in order to analyze the correlation between mutation and disease. Deleterious nsSNPs were categorized based on empirical based and support vector machine based methods to predict the impact on protein functions. Furthermore, we modeled mutant proteins and compared them with the native protein for analysis of protein structure stability. RESULTS: Out of 510 nsSNPs in F8, 378 nsSNPs (74%) were predicted to be 'intolerant' by SIFT, 371 nsSNPs (73%) were predicted to be 'damaging' by PolyPhen and 445 nsSNPs (87%) as 'less stable' by I-Mutant2.0. In F9, 129 nsSNPs (78%) were predicted to be intolerant by SIFT, 131 nsSNPs (79%) were predicted to be damaging by PolyPhen and 150 nsSNPs (90%) as less stable by I-Mutant2.0. Overall, we found that I-Mutant which emphasizes support vector machine based method outperformed SIFT and PolyPhen in prediction of deleterious nsSNPs in both F8 and F9. CONCLUSIONS: The models built in this work would be appropriate for predicting the deleterious amino acid substitutions and their functions in gene regulation which would be useful for further genotype-phenotype researches as well as the pharmacogenetics studies. These in silico tools, despite being helpful in providing information about the nature of mutations, may also function as a first-pass filter to determine the substitutions worth pursuing for further experimental research in other coagulation disorder causing genes. BioMed Central 2012-03-16 /pmc/articles/PMC3361463/ /pubmed/22423892 http://dx.doi.org/10.1186/1423-0127-19-30 Text en Copyright ©2012 Doss; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research C, George Priya Doss In Silico profiling of deleterious amino acid substitutions of potential pathological importance in haemophlia A and haemophlia B |
title | In Silico profiling of deleterious amino acid substitutions of potential pathological importance in haemophlia A and haemophlia B |
title_full | In Silico profiling of deleterious amino acid substitutions of potential pathological importance in haemophlia A and haemophlia B |
title_fullStr | In Silico profiling of deleterious amino acid substitutions of potential pathological importance in haemophlia A and haemophlia B |
title_full_unstemmed | In Silico profiling of deleterious amino acid substitutions of potential pathological importance in haemophlia A and haemophlia B |
title_short | In Silico profiling of deleterious amino acid substitutions of potential pathological importance in haemophlia A and haemophlia B |
title_sort | in silico profiling of deleterious amino acid substitutions of potential pathological importance in haemophlia a and haemophlia b |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3361463/ https://www.ncbi.nlm.nih.gov/pubmed/22423892 http://dx.doi.org/10.1186/1423-0127-19-30 |
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