A computational workflow for analysis of missense mutations in precision oncology

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dc.contributor.authorKhan, Rayyancs
dc.contributor.authorPokorná, Petracs
dc.contributor.authorŠtourač, Jancs
dc.contributor.authorBorko, Simeoncs
dc.contributor.authorArefiev, Ihorcs
dc.contributor.authorPlanas-Iglesias, Joancs
dc.contributor.authorDobiáš, Adamcs
dc.contributor.authorPinto, Gaspar P.cs
dc.contributor.authorSzotkowská, Veronikacs
dc.contributor.authorŠtěrba, Jaroslavcs
dc.contributor.authorSlabý, Ondřejcs
dc.contributor.authorDamborský, Jiřícs
dc.contributor.authorMazurenko, Stanislavcs
dc.contributor.authorBednář, Davidcs
dc.coverage.issue1cs
dc.coverage.volume16cs
dc.date.accessioned2025-06-16T09:56:07Z
dc.date.available2025-06-16T09:56:07Z
dc.date.issued2024-07-24cs
dc.description.abstractEvery year, more than 19 million cancer cases are diagnosed, and this number continues to increase annually. Since standard treatment options have varying success rates for different types of cancer, understanding the biology of an individual's tumour becomes crucial, especially for cases that are difficult to treat. Personalised high-throughput profiling, using next-generation sequencing, allows for a comprehensive examination of biopsy specimens. Furthermore, the widespread use of this technology has generated a wealth of information on cancer-specific gene alterations. However, there exists a significant gap between identified alterations and their proven impact on protein function. Here, we present a bioinformatics pipeline that enables fast analysis of a missense mutation's effect on stability and function in known oncogenic proteins. This pipeline is coupled with a predictor that summarises the outputs of different tools used throughout the pipeline, providing a single probability score, achieving a balanced accuracy above 86%. The pipeline incorporates a virtual screening method to suggest potential FDA/EMA-approved drugs to be considered for treatment. We showcase three case studies to demonstrate the timely utility of this pipeline. To facilitate access and analysis of cancer-related mutations, we have packaged the pipeline as a web server, which is freely available at https://loschmidt.chemi.muni.cz/predictonco/.Scientific contributionThis work presents a novel bioinformatics pipeline that integrates multiple computational tools to predict the effects of missense mutations on proteins of oncological interest. The pipeline uniquely combines fast protein modelling, stability prediction, and evolutionary analysis with virtual drug screening, while offering actionable insights for precision oncology. This comprehensive approach surpasses existing tools by automating the interpretation of mutations and suggesting potential treatments, thereby striving to bridge the gap between sequencing data and clinical application.en
dc.formattextcs
dc.format.extent1-10cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationJournal of Cheminformatics. 2024, vol. 16, issue 1, p. 1-10.en
dc.identifier.doi10.1186/s13321-024-00876-3cs
dc.identifier.issn1758-2946cs
dc.identifier.other197550cs
dc.identifier.urihttps://hdl.handle.net/11012/252539
dc.language.isoencs
dc.publisherBMCcs
dc.relation.ispartofJournal of Cheminformaticscs
dc.relation.urihttps://jcheminf.biomedcentral.com/articles/10.1186/s13321-024-00876-3cs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/1758-2946/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectBioinformaticsen
dc.subjectCanceren
dc.subjectFunctionen
dc.subjectHigh-performance computingen
dc.subjectMachine learningen
dc.subjectMolecular modellingen
dc.subjectOncologyen
dc.subjectPersonalised medicineen
dc.subjectSingle nucleotide polymorphismen
dc.subjectStabilityen
dc.subjectTreatmenten
dc.titleA computational workflow for analysis of missense mutations in precision oncologyen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-197550en
sync.item.dbtypeVAVen
sync.item.insts2025.06.16 11:56:07en
sync.item.modts2025.06.16 11:32:47en
thesis.grantorVysoké učení technické v Brně. Fakulta informačních technologií. Ústav informačních systémůcs
thesis.grantorVysoké učení technické v Brně. . Loschmidtovy laboratořecs
thesis.grantorVysoké učení technické v Brně. . Fakultní nemocnice u sv. Anny v Brněcs
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