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In silico analysis of missense mutations as a first step in functional studies: examples from two sphingolipidoses

2018-10-31Artigo científico Acesso aberto
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dc.contributor.authorDuarte, Ana Joana
dc.contributor.authorRibeiro, Diogo
dc.contributor.authorMoreira, Luciana
dc.contributor.authorAmaral, Olga
dc.date.accessioned2019-03-20T16:05:40Z
dc.date.available2019-03-20T16:05:40Z
dc.date.issued2018-10-31
dc.descriptionFree PMC Article: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6275066/pt_PT
dc.descriptionNote: Where it reads BBB-BMD/6301, should be PTDC/BIM-MEC/4762/2014. Erro de edição, tendo sido solicitado correção.
dc.description.abstractIn order to delineate a better approach to functional studies, we have selected 23 missense mutations distributed in different domains of two lysosomal enzymes, to be studied by in silico analysis. In silico analysis of mutations relies on computational modeling to predict their effects. Various computational platforms are currently available to check the probable causality of mutations encountered in patients at the protein and at the RNA levels. In this work we used four different platforms freely available online (Protein Variation Effect Analyzer- PROVEAN, PolyPhen-2, Swiss-model Expert Protein Analysis System-ExPASy, and SNAP2) to check amino acid substitutions and their effect at the protein level. The existence of functional studies, regarding the amino acid substitutions, led to the selection of the distinct protein mutants. Functional data were used to compare the results obtained with different bioinformatics tools. With the advent of next-generation sequencing, it is not feasible to carry out functional tests in all the variants detected. In silico analysis seems to be useful for the delineation of which mutants are worth studying through functional studies. Therefore, prediction of the mutation impact at the protein level, applying computational analysis, confers the means to rapidly provide a prognosis value to genotyping results, making it potentially valuable for patient care as well as research purposes. The present work points to the need to carry out functional studies in mutations that might look neutral. Moreover, it should be noted that single nucleotide polymorphisms (SNPs), occurring in coding and non-coding regions, may lead to RNA alterations and should be systematically verified. Functional studies can gain from a preliminary multi-step approach, such as the one proposed here.pt_PT
dc.description.sponsorshipFinancial support was received from the Portuguese Foundation of Science and Technology (FCT), project PTDC/BIM-MEC/4762/2014 (PI-O.A.) Diogo Ribeiro and Luciana Moreira were grant recipients from FCT under the same project. Ana Duarte was a PhD student with grant a FCTSFRH/BD/118009/2016.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationInt J Mol Sci. 2018 Oct 31;19(11). pii: E3409. doi: 10.3390/ijms19113409pt_PT
dc.identifier.doi10.3390/ijms19113409pt_PT
dc.identifier.issn1661-6596
dc.identifier.urihttp://hdl.handle.net/10400.18/6244
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relation.publisherversionhttps://www.mdpi.com/1422-0067/19/11/3409pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectLysosomal Disorderspt_PT
dc.subjectARSApt_PT
dc.subjectCSTBpt_PT
dc.subjectGALCpt_PT
dc.subjectGBA1pt_PT
dc.subjectGLApt_PT
dc.subjectFunctional Studiespt_PT
dc.subjectIn silico Analysispt_PT
dc.subjectLysosomal Alpha-galactosidasept_PT
dc.subjectLysosomal Glucocerebrosidasept_PT
dc.subjectHuman Geneticspt_PT
dc.subjectSphingolipidosespt_PT
dc.subjectGenética Humanapt_PT
dc.subjectDoenças Genéticaspt_PT
dc.titleIn silico analysis of missense mutations as a first step in functional studies: examples from two sphingolipidosespt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.issue11pt_PT
oaire.citation.startPageE3409pt_PT
oaire.citation.titleInternational Journal of Molecular Sciencespt_PT
oaire.citation.volume19pt_PT
person.familyNameAmaral
person.givenNameOlga
person.identifier.ciencia-id6F1F-54A3-BBB9
person.identifier.orcid0000-0002-3478-2122
person.identifier.scopus-author-id7004054964
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication8c7fb04a-80c0-4dd7-b3c5-682f6d25662b
relation.isAuthorOfPublication.latestForDiscovery8c7fb04a-80c0-4dd7-b3c5-682f6d25662b

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