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Advanced Bioinformatics Tools in the Pharmacokinetic Profiles of Natural and Synthetic Compounds with Anti-Diabetic Activity

期刊

BIOMOLECULES
卷 11, 期 11, 页码 -

出版社

MDPI
DOI: 10.3390/biom11111692

关键词

diabetes mellitus; natural compounds; QSAR; molecular docking; molecular dynamics; blood-brain barrier; in silico

资金

  1. Romanian National Authority for Scientific Research and Innovation, CNCS/CCCDI-UEFISCDI [PN-III-P2-2.1-PED-2019-4771, PN-III-P2-2.1-PED-2019-1264, PN-III-P2-2.1-PED-2019-5283, PN-III-P2-2.1-PED-2019-1471, PN-III-P4-ID-PCE-2020-0620]
  2. Nucleu Programme [16N/08.02.2019]

向作者/读者索取更多资源

Diabetes is a serious health issue with unclear molecular mechanisms and severe side effects associated with current synthetic drug treatments. Natural compounds from plants have shown promising anti-diabetic activity, as well as benefits for lipid-lowering and anti-obesity. Bioinformatics tools are used to study the mechanisms of action of these compounds, particularly focusing on blood-brain barrier permeability in relation to diabetes.
Diabetes represents a major health problem, involving a severe imbalance of blood sugar levels, which can disturb the nerves, eyes, kidneys, and other organs. Diabes management involves several synthetic drugs focused on improving insulin sensitivity, increasing insulin production, and decreasing blood glucose levels, but with unclear molecular mechanisms and severe side effects. Natural chemicals extracted from several plants such as Gymnema sylvestre, Momordica charantia or Ophiopogon planiscapus Niger have aroused great interest for their anti-diabetes activity, but also their hypolipidemic and anti-obesity activity. Here, we focused on the anti-diabetic activity of a few natural and synthetic compounds, in correlation with their pharmacokinetic/pharmacodynamic profiles, especially with their blood-brain barrier (BBB) permeability. We reviewed studies that used bioinformatics methods such as predicted BBB, molecular docking, molecular dynamics and quantitative structure-activity relationship (QSAR) to elucidate the proper action mechanisms of antidiabetic compounds. Currently, it is evident that BBB damage plays a significant role in diabetes disorders, but the molecular mechanisms are not clear. Here, we presented the efficacy of natural (gymnemic acids, quercetin, resveratrol) and synthetic (TAK-242, propofol, or APX3330) compounds in reducing diabetes symptoms and improving BBB dysfunctions. Bioinformatics tools can be helpful in the quest for chemical compounds with effective anti-diabetic activity that can enhance the druggability of molecular targets and provide a deeper understanding of diabetes mechanisms.

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