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Computational Biology of BRCA2 in Male Breast Cancer, through Prediction of Probable nsSNPs, and Hit Identification
[Image: see text] Male breast cancer (MBC) is a relatively rare disease, but emerging data recommend the development of novel therapeutics considering its alarming threats. Compared to female breast cancer (FBC), MBC is reportedly associated with inferior outcomes (poor survival) owing to their late...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9434626/ https://www.ncbi.nlm.nih.gov/pubmed/36061650 http://dx.doi.org/10.1021/acsomega.2c03851 |
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author | Shinde, Sangita Dattatray Satpute, Dinesh Parshuram Behera, Santosh Kumar Kumar, Dinesh |
author_facet | Shinde, Sangita Dattatray Satpute, Dinesh Parshuram Behera, Santosh Kumar Kumar, Dinesh |
author_sort | Shinde, Sangita Dattatray |
collection | PubMed |
description | [Image: see text] Male breast cancer (MBC) is a relatively rare disease, but emerging data recommend the development of novel therapeutics considering its alarming threats. Compared to female breast cancer (FBC), MBC is reportedly associated with inferior outcomes (poor survival) owing to their late diagnosis and lack of adequate treatment. Treatment typically correlates with FBC, involving surgical removal of the breast tissue along with chemo/hormonal/radiation therapy, the tamoxifen being a standard adjuvant. Considering the distinct immunophenotypic (implying different pathogenesis and progression) differences from FBC, the identification of diagnostics, prognostics, and therapeutics for MBC is highly desirable. In this context, we have analyzed the most deleterious nsSNPs of BRCA2, a human tumor suppressor gene constituting the potential biomarker for tumors including MBC, to predict the structural changes associated with the mutants hampering the normal protein–protein and protein–ligand interactions, resulting in MBC progression. Among 27 nsSNPs confined to 21 rsIDs pertaining to MBC, the 19 nsSNPs constituting 14 rsIDs have been predicted as highly deleterious. We believe that these nsSNPs could serve as potential biomarkers for diagnostic and prognostic purposes and could be the pivotal target for MBC drug discovery. Subsequently, the study highlights the exploration of the key nsSNPs (of BRCA2 associated with the MBC) and its applications toward the identification of therapeutic hit TIP006136 following the homology modeling, virtual screening of 5284 phytochemicals retrieved from the TIPdb (a database of phytochemicals from indigenous plants in Taiwan) database, molecular docking (against native and mutant BRCA2), dynamic simulations (against native and mutant BRCA2), density functional theory (DFT), and molecular electrostatic potential. To the best of our knowledge, this is the first report to use diverse computational modules to investigate the important nsSNPs of BRCA2 related to MBC, implying that TIP006136 could be a potential hit and must be studied further (in vitro and in vivo) to establish its anticancer property and efficacy against MBC. |
format | Online Article Text |
id | pubmed-9434626 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-94346262022-09-02 Computational Biology of BRCA2 in Male Breast Cancer, through Prediction of Probable nsSNPs, and Hit Identification Shinde, Sangita Dattatray Satpute, Dinesh Parshuram Behera, Santosh Kumar Kumar, Dinesh ACS Omega [Image: see text] Male breast cancer (MBC) is a relatively rare disease, but emerging data recommend the development of novel therapeutics considering its alarming threats. Compared to female breast cancer (FBC), MBC is reportedly associated with inferior outcomes (poor survival) owing to their late diagnosis and lack of adequate treatment. Treatment typically correlates with FBC, involving surgical removal of the breast tissue along with chemo/hormonal/radiation therapy, the tamoxifen being a standard adjuvant. Considering the distinct immunophenotypic (implying different pathogenesis and progression) differences from FBC, the identification of diagnostics, prognostics, and therapeutics for MBC is highly desirable. In this context, we have analyzed the most deleterious nsSNPs of BRCA2, a human tumor suppressor gene constituting the potential biomarker for tumors including MBC, to predict the structural changes associated with the mutants hampering the normal protein–protein and protein–ligand interactions, resulting in MBC progression. Among 27 nsSNPs confined to 21 rsIDs pertaining to MBC, the 19 nsSNPs constituting 14 rsIDs have been predicted as highly deleterious. We believe that these nsSNPs could serve as potential biomarkers for diagnostic and prognostic purposes and could be the pivotal target for MBC drug discovery. Subsequently, the study highlights the exploration of the key nsSNPs (of BRCA2 associated with the MBC) and its applications toward the identification of therapeutic hit TIP006136 following the homology modeling, virtual screening of 5284 phytochemicals retrieved from the TIPdb (a database of phytochemicals from indigenous plants in Taiwan) database, molecular docking (against native and mutant BRCA2), dynamic simulations (against native and mutant BRCA2), density functional theory (DFT), and molecular electrostatic potential. To the best of our knowledge, this is the first report to use diverse computational modules to investigate the important nsSNPs of BRCA2 related to MBC, implying that TIP006136 could be a potential hit and must be studied further (in vitro and in vivo) to establish its anticancer property and efficacy against MBC. American Chemical Society 2022-08-17 /pmc/articles/PMC9434626/ /pubmed/36061650 http://dx.doi.org/10.1021/acsomega.2c03851 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Shinde, Sangita Dattatray Satpute, Dinesh Parshuram Behera, Santosh Kumar Kumar, Dinesh Computational Biology of BRCA2 in Male Breast Cancer, through Prediction of Probable nsSNPs, and Hit Identification |
title | Computational Biology
of BRCA2 in Male Breast Cancer,
through Prediction of Probable nsSNPs, and Hit Identification |
title_full | Computational Biology
of BRCA2 in Male Breast Cancer,
through Prediction of Probable nsSNPs, and Hit Identification |
title_fullStr | Computational Biology
of BRCA2 in Male Breast Cancer,
through Prediction of Probable nsSNPs, and Hit Identification |
title_full_unstemmed | Computational Biology
of BRCA2 in Male Breast Cancer,
through Prediction of Probable nsSNPs, and Hit Identification |
title_short | Computational Biology
of BRCA2 in Male Breast Cancer,
through Prediction of Probable nsSNPs, and Hit Identification |
title_sort | computational biology
of brca2 in male breast cancer,
through prediction of probable nssnps, and hit identification |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9434626/ https://www.ncbi.nlm.nih.gov/pubmed/36061650 http://dx.doi.org/10.1021/acsomega.2c03851 |
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