Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 2 de 2
Filtrar
Mais filtros











Base de dados
Intervalo de ano de publicação
1.
Int J Mol Sci ; 25(17)2024 Aug 25.
Artigo em Inglês | MEDLINE | ID: mdl-39273161

RESUMO

The Target-Based Virtual Screening approach is widely employed in drug development, with docking or molecular dynamics techniques commonly utilized for this purpose. This systematic review (SR) aimed to identify in silico therapeutic targets for treating Diabetes mellitus (DM) and answer the question: What therapeutic targets have been used in in silico analyses for the treatment of DM? The SR was developed following the guidelines of the Preferred Reporting Items Checklist for Systematic Review and Meta-Analysis, in accordance with the protocol registered in PROSPERO (CRD42022353808). Studies that met the PECo strategy (Problem, Exposure, Context) were included using the following databases: Medline (PubMed), Web of Science, Scopus, Embase, ScienceDirect, and Virtual Health Library. A total of 20 articles were included, which not only identified therapeutic targets in silico but also conducted in vivo analyses to validate the obtained results. The therapeutic targets most frequently indicated in in silico studies were GLUT4, DPP-IV, and PPARγ. In conclusion, a diversity of targets for the treatment of DM was verified through both in silico and in vivo reassessment. This contributes to the discovery of potential new allies for the treatment of DM.


Assuntos
Simulação por Computador , Diabetes Mellitus , Suplementos Nutricionais , Hipoglicemiantes , Humanos , Diabetes Mellitus/tratamento farmacológico , Hipoglicemiantes/uso terapêutico , Hipoglicemiantes/farmacologia , Transportador de Glucose Tipo 4/metabolismo , Animais , Desenvolvimento de Medicamentos/métodos , PPAR gama/metabolismo , Simulação de Acoplamento Molecular , Terapia de Alvo Molecular/métodos
2.
Int J Mol Sci ; 25(9)2024 Apr 25.
Artigo em Inglês | MEDLINE | ID: mdl-38731918

RESUMO

In the age of information technology and the additional computational search tools and software available, this systematic review aimed to identify potential therapeutic targets for obesity, evaluated in silico and subsequently validated in vivo. The systematic review was initially guided by the research question "What therapeutic targets have been used in in silico analysis for the treatment of obesity?" and structured based on the acronym PECo (P, problem; E, exposure; Co, context). The systematic review protocol was formulated and registered in PROSPERO (CRD42022353808) in accordance with the Preferred Reporting Items Checklist for Systematic Review and Meta-Analysis Protocols (PRISMA-P), and the PRISMA was followed for the systematic review. The studies were selected according to the eligibility criteria, aligned with PECo, in the following databases: PubMed, ScienceDirect, Scopus, Web of Science, BVS, and EMBASE. The search strategy yielded 1142 articles, from which, based on the evaluation criteria, 12 were included in the systematic review. Only seven these articles allowed the identification of both in silico and in vivo reassessed therapeutic targets. Among these targets, five were exclusively experimental, one was exclusively theoretical, and one of the targets presented an experimental portion and a portion obtained by modeling. The predominant methodology used was molecular docking and the most studied target was Human Pancreatic Lipase (HPL) (n = 4). The lack of methodological details resulted in more than 50% of the papers being categorized with an "unclear risk of bias" across eight out of the eleven evaluated criteria. From the current systematic review, it seems evident that integrating in silico methodologies into studies of potential drug targets for the exploration of new therapeutic agents provides an important tool, given the ongoing challenges in controlling obesity.


Assuntos
Simulação por Computador , Obesidade , Humanos , Obesidade/tratamento farmacológico , Obesidade/metabolismo , Animais , Simulação de Acoplamento Molecular , Fármacos Antiobesidade/farmacologia , Fármacos Antiobesidade/uso terapêutico , Lipase/metabolismo , Lipase/antagonistas & inibidores , Terapia de Alvo Molecular/métodos
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA