In silico structure-based designers of therapeutic targets for diabetes mellitus or obesity: a protocol for systematic review

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dc.contributor.authorMorais, Ana Heloneida de Araújo
dc.contributor.authorGomes, Ana Francisca Teixeira
dc.contributor.authorMedeiros, Wendjilla Fortunato de
dc.contributor.authorOliveira, Gerciane Silva de
dc.contributor.authorMedeiros, Isaiane
dc.contributor.authorMaia, Juliana Kelly da Silva
dc.contributor.authorBezerra, Ingrid Wilza Leal
dc.contributor.authorPiuvezam, Grasiela
dc.contributor.authorIDhttps://orcid.org/0000-0002-6460-911Xpt_BR
dc.date.accessioned2023-07-27T19:24:17Z
dc.date.available2023-07-27T19:24:17Z
dc.date.issued2022
dc.description.resumoObesity is a significant risk factor for several chronic non-communicable diseases, being closely related to Diabetes Mellitus. Computer modeling techniques favor the understanding of interaction mechanisms between specific targets and substances of interest, optimizing drug development. In this article, the protocol of two protocols of systematic reviews are described for identifying therapeutic targets and models for treating obesity or diabetes mellitus investi gated in silico. The protocol is by the guidelines from the Preferred Reporting Items for System atic Reviews and Meta-Analyzes Protocols (PRISMA-P) and was published in the International Prospective Register of Systematic Reviews database (PROSPERO: CRD42022353808). Search strategies will be developed based on the combination of descriptors and executed in the following databases: PubMed; ScienceDirect; Scopus; Web of Science; Virtual Health Library; EMBASE. Only original in silico studies with molecular dynamics, molecular docking, or both will be inserted. Two trained researchers will independently select the articles, extract the data, and assess the risk of bias. The quality will be assessed through an adapted version of the Strengthening the Reporting of Empirical Simulation Studies (STRESS) and the risk of bias using a checklist obtained from separate literature sources. The implementation of this protocol will result in the elaboration of two systematic reviews identifying the therapeutic tar gets for treating obesity (review 1) or diabetes mellitus (review 2) used in computer simulation studies and their models. The systematization of knowledge about these treatment targets and their in silico structures is fundamental, primarily because computer simulation contributes to more accurate planning of future either in vitro or in vivo studies. Therefore, the reviews devel oped from this protocol will guide decision-making regarding the choice of targets/models in future research focused on therapeutics of obesity or Diabetes Mellitus contributing to mitigate of factors such as costs, time, and necessity of in vitro and/or in vivo assayspt_BR
dc.identifier.citationGOMES, Ana Francisca Teixeira et al. In silico structure-based designers of therapeutic targets for diabetes mellitus or obesity: a protocol for systematic review. Plos one, v. 17, n. 12, p. e0279039, 2022.pt_BR
dc.identifier.doihttps://doi.org/10.1371/journal.pone.0279039
dc.identifier.urihttps://repositorio.ufrn.br/handle/123456789/54236
dc.languageenpt_BR
dc.publisherPlos Onept_BR
dc.subjectDiabetes mellituspt_BR
dc.subjectobesitypt_BR
dc.subjecttherapeutic targetspt_BR
dc.subjectsilico structurespt_BR
dc.subjectsystematic reviewspt_BR
dc.titleIn silico structure-based designers of therapeutic targets for diabetes mellitus or obesity: a protocol for systematic reviewpt_BR
dc.typearticlept_BR

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