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Briefings in Bioinformatics
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Briefings in Bioinformatics
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Apollo
Article . 2021
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Article . 2021
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UCL Discovery
Article . 2021
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DBLP
Article . 2024
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COSMIC Cancer Gene Census 3D database: understanding the impacts of mutations on cancer targets

Authors: Ali F. Alsulami; Pedro H. M. Torres; Ismail Moghul; Sheikh Mohammed Arif; Amanda K. Chaplin; Sundeep Chaitanya Vedithi; Tom L. Blundell;

COSMIC Cancer Gene Census 3D database: understanding the impacts of mutations on cancer targets

Abstract

AbstractMutations 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.

Country
United Kingdom
Keywords

Data Analysis, Models, Molecular, modelling cancer genes census, Computational Biology, Oncogenes, Workflow, Cancer Gene Census 3D, mutational analyses of cancer drug targets, Structure-Activity Relationship, User-Computer Interface, Neoplasms, Databases, Genetic, Mutation, Biomarkers, Tumor, Problem Solving Protocol, Humans, hallmark mutations, Software

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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Top 10%
Average
Top 10%
Green
gold