In silico structure-based designers of therapeutic targets for diabetes mellitus or obesity: a protocol for systematic review
Obesity 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 art...
Na minha lista:
| Principais autores: | , , , , , , , |
|---|---|
| Outros Autores: | |
| Formato: | article |
| Idioma: | English |
| Publicado em: |
Plos One
|
| Assuntos: | |
| Endereço do item: | https://repositorio.ufrn.br/handle/123456789/54236 https://doi.org/10.1371/journal.pone.0279039 |
| Tags: |
Adicionar Tag
Sem tags, seja o primeiro a adicionar uma tag!
|
| Resumo: | Obesity 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 assays |
|---|