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COSMIC Cancer Gene Census 3D database: understanding the impacts of mutations on cancer targets
Mutations in hallmark genes are believed to be the main drivers of cancer progression. These mutations are reported in the Catalogue of Somatic Mutations in Cancer (COSMIC). Structural appreciation of where these mutations appear, in protein–protein interfaces, active sites or deoxyribonucleic acid...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8574963/ https://www.ncbi.nlm.nih.gov/pubmed/34137435 http://dx.doi.org/10.1093/bib/bbab220 |
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author | Alsulami, Ali F Torres, Pedro H M Moghul, Ismail Arif, Sheikh Mohammed Chaplin, Amanda K Vedithi, Sundeep Chaitanya Blundell, Tom L |
author_facet | Alsulami, Ali F Torres, Pedro H M Moghul, Ismail Arif, Sheikh Mohammed Chaplin, Amanda K Vedithi, Sundeep Chaitanya Blundell, Tom L |
author_sort | Alsulami, Ali F |
collection | PubMed |
description | Mutations in hallmark genes are believed to be the main drivers of cancer progression. These mutations are reported in the Catalogue of Somatic Mutations in Cancer (COSMIC). Structural appreciation of where these mutations appear, in protein–protein interfaces, active sites or deoxyribonucleic acid (DNA) interfaces, and predicting the impacts of these mutations using a variety of computational tools are crucial for successful drug discovery and development. Currently, there are 723 genes presented in the COSMIC Cancer Gene Census. Due to the complexity of the gene products, structures of only 87 genes have been solved experimentally with structural coverage between 90% and 100%. Here, we present a comprehensive, user-friendly, web interface (https://cancer-3d.com/) of 714 modelled cancer-related genes, including homo-oligomers, hetero-oligomers, transmembrane proteins and complexes with DNA, ribonucleic acid, ligands and co-factors. Using SDM and mCSM software, we have predicted the impacts of reported mutations on protein stability, protein–protein interfaces affinity and protein–nucleic acid complexes affinity. Furthermore, we also predicted intrinsically disordered regions using DISOPRED3. |
format | Online Article Text |
id | pubmed-8574963 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-85749632021-11-09 COSMIC Cancer Gene Census 3D database: understanding the impacts of mutations on cancer targets Alsulami, Ali F Torres, Pedro H M Moghul, Ismail Arif, Sheikh Mohammed Chaplin, Amanda K Vedithi, Sundeep Chaitanya Blundell, Tom L Brief Bioinform Problem Solving Protocol Mutations in hallmark genes are believed to be the main drivers of cancer progression. These mutations are reported in the Catalogue of Somatic Mutations in Cancer (COSMIC). Structural appreciation of where these mutations appear, in protein–protein interfaces, active sites or deoxyribonucleic acid (DNA) interfaces, and predicting the impacts of these mutations using a variety of computational tools are crucial for successful drug discovery and development. Currently, there are 723 genes presented in the COSMIC Cancer Gene Census. Due to the complexity of the gene products, structures of only 87 genes have been solved experimentally with structural coverage between 90% and 100%. Here, we present a comprehensive, user-friendly, web interface (https://cancer-3d.com/) of 714 modelled cancer-related genes, including homo-oligomers, hetero-oligomers, transmembrane proteins and complexes with DNA, ribonucleic acid, ligands and co-factors. Using SDM and mCSM software, we have predicted the impacts of reported mutations on protein stability, protein–protein interfaces affinity and protein–nucleic acid complexes affinity. Furthermore, we also predicted intrinsically disordered regions using DISOPRED3. Oxford University Press 2021-06-17 /pmc/articles/PMC8574963/ /pubmed/34137435 http://dx.doi.org/10.1093/bib/bbab220 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Problem Solving Protocol Alsulami, Ali F Torres, Pedro H M Moghul, Ismail Arif, Sheikh Mohammed Chaplin, Amanda K Vedithi, Sundeep Chaitanya Blundell, Tom L COSMIC Cancer Gene Census 3D database: understanding the impacts of mutations on cancer targets |
title | COSMIC Cancer Gene Census 3D database: understanding the impacts of mutations on cancer targets |
title_full | COSMIC Cancer Gene Census 3D database: understanding the impacts of mutations on cancer targets |
title_fullStr | COSMIC Cancer Gene Census 3D database: understanding the impacts of mutations on cancer targets |
title_full_unstemmed | COSMIC Cancer Gene Census 3D database: understanding the impacts of mutations on cancer targets |
title_short | COSMIC Cancer Gene Census 3D database: understanding the impacts of mutations on cancer targets |
title_sort | cosmic cancer gene census 3d database: understanding the impacts of mutations on cancer targets |
topic | Problem Solving Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8574963/ https://www.ncbi.nlm.nih.gov/pubmed/34137435 http://dx.doi.org/10.1093/bib/bbab220 |
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