A computational workflow for analysis of missense mutations in precision oncology

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00159816%3A_____%2F24%3A00080294" target="_blank" >RIV/00159816:_____/24:00080294 - isvavai.cz</a>

Alternative codes found

RIV/00216224:14310/24:00136618 RIV/00216305:26230/24:PU156205 RIV/65269705:_____/24:00080294

Result on the web

<a href="https://jcheminf.biomedcentral.com/articles/10.1186/s13321-024-00876-3" target="_blank" >https://jcheminf.biomedcentral.com/articles/10.1186/s13321-024-00876-3</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1186/s13321-024-00876-3" target="_blank" >10.1186/s13321-024-00876-3</a>

Result language

angličtina

Original language name

A computational workflow for analysis of missense mutations in precision oncology

Original language description

Every 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&apos;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&apos;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.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10400 - Chemical sciences

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

—

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Journal of Cheminformatics

ISSN

1758-2946

e-ISSN

1758-2946

Volume of the periodical

16

Issue of the periodical within the volume

1

Country of publishing house

GB - UNITED KINGDOM

Number of pages

10

Pages from-to

86

UT code for WoS article

001281138800001

EID of the result in the Scopus database

2-s2.0-85199996054