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LIST-S2: taxonomy based sorting of deleterious missense mutations across species.

ABSTRACT: The separation of deleterious from benign mutations remains a key challenge in the interpretation of genomic data. Computational methods used to sort mutations based on their potential deleteriousness rely largely on conservation measures derived from sequence alignments. Here, we introduce LIST-S2, a successor to our previously developed approach LIST, which aims to exploit local sequence identity and taxonomy distances in quantifying the conservation of human protein sequences. Unlike its predecessor, LIST-S2 is not limited to human sequences but can assess conservation and make predictions for sequences from any organism. Moreover, we provide a web-tool and downloadable software to compute and visualize the deleteriousness of mutations in user-provided sequences. This web-tool contains an HTML interface and a RESTful API to submit and manage sequences as well as a browsable set of precomputed predictions for a large number of UniProtKB protein sequences of common taxa. LIST-S2 is available at: https://list-s2.msl.ubc.ca/.

SUBMITTER: Malhis N

PROVIDER: S-EPMC7319545 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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LIST-S2: taxonomy based sorting of deleterious missense mutations across species.

Malhis Nawar N Jacobson Matthew M Jones Steven J M SJM Gsponer Jörg J

Nucleic acids research 20200701 W1

The separation of deleterious from benign mutations remains a key challenge in the interpretation of genomic data. Computational methods used to sort mutations based on their potential deleteriousness rely largely on conservation measures derived from sequence alignments. Here, we introduce LIST-S2, a successor to our previously developed approach LIST, which aims to exploit local sequence identity and taxonomy distances in quantifying the conservation of human protein sequences. Unlike its pred ...[more]

PMID: 32352516

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Project description:Traditional cancer treatment approaches are often hindered by the presence of toxic side effects and the high rate of relapse observed in treated organs. In contrast, novel immunotherapeutic strategies targeting immune checkpoint inhibitors, particularly PD-1, have demonstrated promising results with minimal adverse effects. However, the emergence of immunotherapeutic-resistant tumors, predominantly caused by intrinsic mutations, poses a significant obstacle to successful treatment outcomes. Consequently, the primary objective of this study was to screen for the most detrimental missense mutations in the PD-1 gene associated with immunotherapeutic resistance. To achieve this aim, a comprehensive screening process utilizing 20 web servers, incorporating both sequence- and structure-based methodologies, was undertaken. Through meticulous analysis and mutual disease association sorting, four specific missense mutations were successfully identified. These mutations, namely, R38C, D61V, R94C, and D117V, emerged as the leading contributors to genetic cancer progression and immunotherapeutic resistance against PD-1 blockers. The findings presented in this study are supported by multiple lines of evidence. A thorough examination of protein topology, structural alignment, docking interactions with PD-L1, and protein flexibility collectively confirmed the pathogenic nature of these sorted mutations. By considering these various aspects, we have gained a comprehensive understanding of the underlying mechanisms driving immunotherapeutic resistance. In conclusion, the comprehensive screening process undertaken in this study has successfully identified R38C, D61V, R94C, and D117V as the primary mutations contributing to genetic cancer progression and immunotherapeutic resistance against PD-1 blockers. The integration of protein topology analysis, structural alignment, docking studies with PD-L1, and assessment of protein flexibility have collectively provided robust evidence to support the pathogenic significance of these mutations.

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Dataset Information

LIST-S2: taxonomy based sorting of deleterious missense mutations across species.

Publications

LIST-S2: taxonomy based sorting of deleterious missense mutations across species.

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