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Computational Modeling of complete HOXB13 protein for predicting the functional effect of SNPs and the associated role in hereditary prostate cancer
The human HOXB13 gene encodes a 284 amino acid transcription factor belonging to the homeobox gene family containing a homeobox and a HoxA13 N-terminal domain. It is highly linked to hereditary prostate cancer, the majority of which is manifested as a result of a Single Nucleotide Polymorphism (SNP)...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5363706/ https://www.ncbi.nlm.nih.gov/pubmed/28272408 http://dx.doi.org/10.1038/srep43830 |
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author | Chandrasekaran, Gopalakrishnan Hwang, Eu Chang Kang, Taek Won Kwon, Dong Deuk Park, Kwangsung Lee, Je-Jung Lakshmanan, Vinoth-Kumar |
author_facet | Chandrasekaran, Gopalakrishnan Hwang, Eu Chang Kang, Taek Won Kwon, Dong Deuk Park, Kwangsung Lee, Je-Jung Lakshmanan, Vinoth-Kumar |
author_sort | Chandrasekaran, Gopalakrishnan |
collection | PubMed |
description | The human HOXB13 gene encodes a 284 amino acid transcription factor belonging to the homeobox gene family containing a homeobox and a HoxA13 N-terminal domain. It is highly linked to hereditary prostate cancer, the majority of which is manifested as a result of a Single Nucleotide Polymorphism (SNP). In silico analysis of 95 missense SNP’s corresponding to the non-homeobox region of HOXB13 predicted 21 nsSNP’s to be potentially deleterious. Among 123 UTR SNPs analysed by UTRScan, rs543028086, rs550968159, rs563065128 were found to affect the UNR_BS, GY-BOX and MBE UTR signals, respectively. Subsequent analysis by PolymiRTS revealed 23 UTR SNPs altering the miRNA binding site. The complete HOXB13_M26 protein structure was modelled using MODELLER v9.17. Computational analysis of the 21 nsSNP’s mapped into the HOXB13_M26 protein revealed seven nsSNP’s (rs761914407, rs8556, rs138213197, rs772962401, rs778843798, rs770620686 and rs587780165) seriously resulting in a damaging and deleterious effect on the protein. G84E, G135E, and A128V resulted in increased, while, R215C, C66R, Y80C and S122R resulted in decreased protein stability, ultimately predicted to result in the altered binding patterns of HOXB13. While the genotype-phenotype based effects of nsSNP’s were assessed, the exact biological and biochemical mechanism driven by the above predicted SNPs still needs to be extensively evaluated by in vivo and GWAS studies. |
format | Online Article Text |
id | pubmed-5363706 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-53637062017-03-24 Computational Modeling of complete HOXB13 protein for predicting the functional effect of SNPs and the associated role in hereditary prostate cancer Chandrasekaran, Gopalakrishnan Hwang, Eu Chang Kang, Taek Won Kwon, Dong Deuk Park, Kwangsung Lee, Je-Jung Lakshmanan, Vinoth-Kumar Sci Rep Article The human HOXB13 gene encodes a 284 amino acid transcription factor belonging to the homeobox gene family containing a homeobox and a HoxA13 N-terminal domain. It is highly linked to hereditary prostate cancer, the majority of which is manifested as a result of a Single Nucleotide Polymorphism (SNP). In silico analysis of 95 missense SNP’s corresponding to the non-homeobox region of HOXB13 predicted 21 nsSNP’s to be potentially deleterious. Among 123 UTR SNPs analysed by UTRScan, rs543028086, rs550968159, rs563065128 were found to affect the UNR_BS, GY-BOX and MBE UTR signals, respectively. Subsequent analysis by PolymiRTS revealed 23 UTR SNPs altering the miRNA binding site. The complete HOXB13_M26 protein structure was modelled using MODELLER v9.17. Computational analysis of the 21 nsSNP’s mapped into the HOXB13_M26 protein revealed seven nsSNP’s (rs761914407, rs8556, rs138213197, rs772962401, rs778843798, rs770620686 and rs587780165) seriously resulting in a damaging and deleterious effect on the protein. G84E, G135E, and A128V resulted in increased, while, R215C, C66R, Y80C and S122R resulted in decreased protein stability, ultimately predicted to result in the altered binding patterns of HOXB13. While the genotype-phenotype based effects of nsSNP’s were assessed, the exact biological and biochemical mechanism driven by the above predicted SNPs still needs to be extensively evaluated by in vivo and GWAS studies. Nature Publishing Group 2017-03-08 /pmc/articles/PMC5363706/ /pubmed/28272408 http://dx.doi.org/10.1038/srep43830 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Chandrasekaran, Gopalakrishnan Hwang, Eu Chang Kang, Taek Won Kwon, Dong Deuk Park, Kwangsung Lee, Je-Jung Lakshmanan, Vinoth-Kumar Computational Modeling of complete HOXB13 protein for predicting the functional effect of SNPs and the associated role in hereditary prostate cancer |
title | Computational Modeling of complete HOXB13 protein for predicting the functional effect of SNPs and the associated role in hereditary prostate cancer |
title_full | Computational Modeling of complete HOXB13 protein for predicting the functional effect of SNPs and the associated role in hereditary prostate cancer |
title_fullStr | Computational Modeling of complete HOXB13 protein for predicting the functional effect of SNPs and the associated role in hereditary prostate cancer |
title_full_unstemmed | Computational Modeling of complete HOXB13 protein for predicting the functional effect of SNPs and the associated role in hereditary prostate cancer |
title_short | Computational Modeling of complete HOXB13 protein for predicting the functional effect of SNPs and the associated role in hereditary prostate cancer |
title_sort | computational modeling of complete hoxb13 protein for predicting the functional effect of snps and the associated role in hereditary prostate cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5363706/ https://www.ncbi.nlm.nih.gov/pubmed/28272408 http://dx.doi.org/10.1038/srep43830 |
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