Unknown

Dataset Information

0

Targeting N-Terminal Human Maltase-Glucoamylase to Unravel Possible Inhibitors Using Molecular Docking, Molecular Dynamics Simulations, and Adaptive Steered Molecular Dynamics Simulations.


ABSTRACT: There are multiple drugs for the treatment of type 2 diabetes, including traditional sulfonylureas biguanides, glinides, thiazolidinediones, α-glucosidase inhibitors, glucagon-like peptide-1 (GLP-1) receptor agonists, dipeptidyl peptidase IV (DPP-4) inhibitors, and sodium-glucose cotransporter 2 (SGLT2) inhibitors. α-Glucosidase inhibitors have been used to control postprandial glucose levels caused by type 2 diabetes since 1990. α-Glucosidases are rather crucial in the human metabolic system and are principally found in families 13 and 31. Maltase-glucoamylase (MGAM) belongs to glycoside hydrolase family 31. The main function of MGAM is to digest terminal starch products left after the enzymatic action of α-amylase; hence, MGAM becomes an efficient drug target for insulin resistance. In order to explore the conformational changes in the active pocket and unbinding pathway for NtMGAM, molecular dynamics (MD) simulations and adaptive steered molecular dynamics (ASMD) simulations were performed for two NtMGAM-inhibitor [de-O-sulfonated kotalanol (DSK) and acarbose] complexes. MD simulations indicated that DSK bound to NtMGAM may influence two domains (inserted loop 1 and inserted loop 2) by interfering with the spiralization of residue 497-499. The flexibility of inserted loop 1 and inserted loop 2 can influence the volume of the active pocket of NtMGAM, which can affect the binding progress for DSK to NtMGAM. ASMD simulations showed that compared to acarbose, DSK escaped from NtMGAM easily with lower energy. Asp542 is an important residue on the bottleneck of the active pocket of NtMGAM and could generate hydrogen bonds with DSK continuously. Our theoretical results may provide some useful clues for designing new α-glucosidase inhibitors to treat type 2 diabetes.

SUBMITTER: Zhang S 

PROVIDER: S-EPMC8435576 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC10058326 | biostudies-literature
| S-EPMC4169427 | biostudies-literature
| S-EPMC9543079 | biostudies-literature
| S-EPMC3742645 | biostudies-literature
| S-EPMC4875297 | biostudies-literature
| S-EPMC8204395 | biostudies-literature
| S-EPMC3192114 | biostudies-literature
| S-EPMC1302184 | biostudies-other
| S-EPMC5015890 | biostudies-literature
| S-EPMC3663486 | biostudies-literature