Espinosa_et_al_(2014).pdf (1.48 MB)
Deriving a mutation index of carcinogenicity using protein structure and protein interfaces
journal contribution
posted on 2023-06-08, 20:15 authored by Octavio Espinosa, Konstantinos Mitsopoulos, Jarle Hakas, Frances PearlFrances Pearl, Marketa ZvelebilWith the advent of Next Generation Sequencing the identification of mutations in the genomes of healthy and diseased tissues has become commonplace. While much progress has been made to elucidate the aetiology of disease processes in cancer, the contributions to disease that many individual mutations make remain to be characterised and their downstream consequences on cancer phenotypes remain to be understood. Missense mutations commonly occur in cancers and their consequences remain challenging to predict. However, this knowledge is becoming more vital, for both assessing disease progression and for stratifying drug treatment regimes. Coupled with structural data, comprehensive genomic databases of mutations such as the 1000 Genomes project and COSMIC give an opportunity to investigate general principles of how cancer mutations disrupt proteins and their interactions at the molecular and network level. We describe a comprehensive comparison of cancer and neutral missense mutations; by combining features derived from structural and interface properties we have developed a carcinogenicity predictor, InCa (Index of Carcinogenicity). Upon comparison with other methods, we observe that InCa can predict mutations that might not be detected by other methods. We also discuss general limitations shared by all predictors that attempt to predict driver mutations and discuss how this could impact high-throughput predictions. A web interface to a server implementation is publicly available at http://inca.icr.ac.uk/.
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Publication status
- Published
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- Published version
Journal
PLoS ONEISSN
1932-6203Publisher
Public Library of ScienceExternal DOI
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1Volume
9Article number
e84598Department affiliated with
- Biochemistry Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2015-03-06First Open Access (FOA) Date
2015-03-06First Compliant Deposit (FCD) Date
2015-03-06Usage metrics
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