Proteins and Peptides Studied In Silico and In Vivo for the Treatment of Diabetes Mellitus: A Systematic Review.
Isaiane MedeirosAna Francisca Teixeira GomesEmilly Guedes Oliveira E SilvaIngrid Wilza Leal BezerraJuliana Kelly da Silva MaiaGrasiela PiuvezamAna Heloneida de Araújo MoraisPublished in: Nutrients (2024)
Bioinformatics has expedited the screening of new efficient therapeutic agents for diseases such as diabetes mellitus (DM). The objective of this systematic review (SR) was to understand naturally occurring proteins and peptides studied in silico and subsequently reevaluated in vivo for treating DM, guided by the question: which peptides or proteins have been studied in silico for the treatment of diabetes mellitus? The RS protocol was registered in the International Prospective Register of Systematic Reviews database. Articles meeting the eligibility criteria were selected from the PubMed, ScienceDirect, Scopus, Web of Science, Virtual Health Library (VHL), and EMBASE databases. Five studies that investigated peptides or proteins analyzed in silico and in vivo were selected. Risk of bias assessment was conducted using the adapted Strengthening the Reporting of Empirical Simulation Studies (STRESS) tool. A diverse range of assessed proteins and/or peptides that had a natural origin were investigated in silico and corresponding in vivo reevaluation demonstrated reductions in glycemia and/or insulin, morphological enhancements in pancreatic β cells, and alterations in the gene expression of markers associated with DM. The in silico studies outlined offer crucial insights into therapeutic strategies for DM, along with promising leads for screening novel therapeutic agents in future trials.
Keyphrases
- molecular docking
- systematic review
- glycemic control
- gene expression
- public health
- type diabetes
- amino acid
- meta analyses
- healthcare
- dna methylation
- case control
- induced apoptosis
- mental health
- adipose tissue
- molecular dynamics simulations
- emergency department
- atomic force microscopy
- solid state
- machine learning
- signaling pathway
- climate change
- health information
- stress induced
- human health