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COSMIC 癌症基因普查 3D 数据库:了解突变对癌症靶点的影响。

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

机构信息

Department of Biochemistry at the University of Cambridge, Cambridge CB2 1GA, UK.

Laboratório de Modelagem e Dinâmica Molecular, Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ, Brasil.

出版信息

Brief Bioinform. 2021 Nov 5;22(6). doi: 10.1093/bib/bbab220.

Abstract

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.

摘要

标志性基因的突变被认为是癌症进展的主要驱动因素。这些突变在《癌症体细胞突变目录》(COSMIC)中有所报道。了解这些突变出现在蛋白质-蛋白质界面、活性位点或脱氧核糖核酸(DNA)界面的位置,并使用各种计算工具预测这些突变的影响,对于成功发现和开发药物至关重要。目前,COSMIC 癌症基因普查中列出了 723 个基因。由于基因产物的复杂性,只有 87 个基因的结构已通过实验得到解决,结构覆盖率在 90%到 100%之间。在这里,我们提供了一个全面、用户友好的网络界面(https://cancer-3d.com/),其中包含 714 个建模的癌症相关基因,包括同源寡聚体、异源寡聚体、跨膜蛋白以及与 DNA、核糖核酸、配体和辅助因子的复合物。我们使用 SDM 和 mCSM 软件预测了报道的突变对蛋白质稳定性、蛋白质-蛋白质界面亲和力和蛋白质-核酸复合物亲和力的影响。此外,我们还使用 DISOPRED3 预测了内在无序区域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b87/8574963/6dfb1abb46e3/bbab220f1.jpg

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