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VarMod: modelling the functional effects of non-synonymous variants
Unravelling the genotype–phenotype relationship in humans remains a challenging task in genomics studies. Recent advances in sequencing technologies mean there are now thousands of sequenced human genomes, revealing millions of single nucleotide variants (SNVs). For non-synonymous SNVs present in pr...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4086131/ https://www.ncbi.nlm.nih.gov/pubmed/24906884 http://dx.doi.org/10.1093/nar/gku483 |
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author | Pappalardo, Morena Wass, Mark N. |
author_facet | Pappalardo, Morena Wass, Mark N. |
author_sort | Pappalardo, Morena |
collection | PubMed |
description | Unravelling the genotype–phenotype relationship in humans remains a challenging task in genomics studies. Recent advances in sequencing technologies mean there are now thousands of sequenced human genomes, revealing millions of single nucleotide variants (SNVs). For non-synonymous SNVs present in proteins the difficulties of the problem lie in first identifying those nsSNVs that result in a functional change in the protein among the many non-functional variants and in turn linking this functional change to phenotype. Here we present VarMod (Variant Modeller) a method that utilises both protein sequence and structural features to predict nsSNVs that alter protein function. VarMod develops recent observations that functional nsSNVs are enriched at protein–protein interfaces and protein–ligand binding sites and uses these characteristics to make predictions. In benchmarking on a set of nearly 3000 nsSNVs VarMod performance is comparable to an existing state of the art method. The VarMod web server provides extensive resources to investigate the sequence and structural features associated with the predictions including visualisation of protein models and complexes via an interactive JSmol molecular viewer. VarMod is available for use at http://www.wasslab.org/varmod. |
format | Online Article Text |
id | pubmed-4086131 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-40861312014-12-01 VarMod: modelling the functional effects of non-synonymous variants Pappalardo, Morena Wass, Mark N. Nucleic Acids Res Article Unravelling the genotype–phenotype relationship in humans remains a challenging task in genomics studies. Recent advances in sequencing technologies mean there are now thousands of sequenced human genomes, revealing millions of single nucleotide variants (SNVs). For non-synonymous SNVs present in proteins the difficulties of the problem lie in first identifying those nsSNVs that result in a functional change in the protein among the many non-functional variants and in turn linking this functional change to phenotype. Here we present VarMod (Variant Modeller) a method that utilises both protein sequence and structural features to predict nsSNVs that alter protein function. VarMod develops recent observations that functional nsSNVs are enriched at protein–protein interfaces and protein–ligand binding sites and uses these characteristics to make predictions. In benchmarking on a set of nearly 3000 nsSNVs VarMod performance is comparable to an existing state of the art method. The VarMod web server provides extensive resources to investigate the sequence and structural features associated with the predictions including visualisation of protein models and complexes via an interactive JSmol molecular viewer. VarMod is available for use at http://www.wasslab.org/varmod. Oxford University Press 2014-07-01 2014-06-06 /pmc/articles/PMC4086131/ /pubmed/24906884 http://dx.doi.org/10.1093/nar/gku483 Text en © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Article Pappalardo, Morena Wass, Mark N. VarMod: modelling the functional effects of non-synonymous variants |
title | VarMod: modelling the functional effects of non-synonymous variants |
title_full | VarMod: modelling the functional effects of non-synonymous variants |
title_fullStr | VarMod: modelling the functional effects of non-synonymous variants |
title_full_unstemmed | VarMod: modelling the functional effects of non-synonymous variants |
title_short | VarMod: modelling the functional effects of non-synonymous variants |
title_sort | varmod: modelling the functional effects of non-synonymous variants |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4086131/ https://www.ncbi.nlm.nih.gov/pubmed/24906884 http://dx.doi.org/10.1093/nar/gku483 |
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