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MTR3D: identifying regions within protein tertiary structures under purifying selection.
Silk, Michael; Pires, Douglas E V; Rodrigues, Carlos H M; D'Souza, Elston N; Olshansky, Moshe; Thorne, Natalie; Ascher, David B.
Afiliación
  • Silk M; Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Australia.
  • Pires DEV; Structural Biology and Bioinformatics, Department of Biochemistry and Molecular Biology, University of Melbourne, Melbourne, Melbourne, Australia.
  • Rodrigues CHM; Systems and Computational Biology, Bio21 Institute, University of Melbourne, Melbourne, Australia.
  • D'Souza EN; Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Australia.
  • Olshansky M; Structural Biology and Bioinformatics, Department of Biochemistry and Molecular Biology, University of Melbourne, Melbourne, Melbourne, Australia.
  • Thorne N; Systems and Computational Biology, Bio21 Institute, University of Melbourne, Melbourne, Australia.
  • Ascher DB; School of Computing and Information Systems, University of Melbourne, Melbourne, Australia.
Nucleic Acids Res ; 49(W1): W438-W445, 2021 07 02.
Article en En | MEDLINE | ID: mdl-34050760
ABSTRACT
The identification of disease-causal variants is non-trivial. By mapping population variation from over 448,000 exome and genome sequences to over 81,000 experimental structures and homology models of the human proteome, we have calculated both regional intolerance to missense variation (Missense Tolerance Ratio, MTR), using a sliding window of 21-41 codons, and introduce a new 3D spatial intolerance to missense variation score (3D Missense Tolerance Ratio, MTR3D), using spheres of 5-8 Å. We show that the MTR3D is less biased by regions with limited data and more accurately identifies regions under purifying selection than estimates relying on the sequence alone. Intolerant regions were highly enriched for both ClinVar pathogenic and COSMIC somatic missense variants (Mann-Whitney U test P < 2.2 × 10-16). Further, we combine sequence- and spatial-based scores to generate a consensus score, MTRX, which distinguishes pathogenic from benign variants more accurately than either score separately (AUC = 0.85). The MTR3D server enables easy visualisation of population variation, MTR, MTR3D and MTRX scores across the entire gene and protein structure for >17,000 human genes and >42,000 alternative alternate transcripts, including both Ensembl and RefSeq transcripts. MTR3D is freely available by user-friendly web-interface and API at http//biosig.unimelb.edu.au/mtr3d/.
Asunto(s)

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Programas Informáticos / Estructura Terciaria de Proteína / Mutación Missense Tipo de estudio: Prognostic_studies Idioma: En Revista: Nucleic Acids Res Año: 2021 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Programas Informáticos / Estructura Terciaria de Proteína / Mutación Missense Tipo de estudio: Prognostic_studies Idioma: En Revista: Nucleic Acids Res Año: 2021 Tipo del documento: Article