| Literature DB >> 35273901 |
Muhammad Shaiful Alam1,2, Md Sohorab Uddin3, Tahmida Shamsuddin4, Maruf Rubayed2, Tania Sharmin1, Rasheda Akter1, S M Zahid Hosen1,5.
Abstract
Proline specific serine protease enzyme, dipeptidyl peptidase IV (DPP-4) has become a promising target for diabetes, as it stops glucagon-like peptide 1 (GLP-1) from becoming inactive, resulting in higher levels of active GLP-1. This lowers glucose levels by increasing insulin secretion and decreasing glucagon secretion. DPP-4 is also linked to a higher BMI and a 0.7 to 1% reduction in HbA1c. Currently available DPP-4 inhibitor drugs showed less promising anti-diabetic activity as this class associated with many side effects due to non-selectivity and therefore searching on more potent DPP-4 inhibitors are still ongoing. In our present study, we investigate the inhibition of DPP-4 through a series of antibiotic compounds which were previously reported to be used in diabetic foot infections and compared with existing DPP-4 inhibitors. To obtain this objective, three-dimensional crystal structure of DPP-4 was retrieved from the protein data bank (PDB id: 1 × 70). A systematic computational method combining molecular docking, MM-GBSA binding energy calculation, MD simulations, MM-PBSA binding free energy calculations and ADME were used to find best DPP-4 inhibitor. Molecular docking results revealed that clindamycin has a higher affinity towards the catalytic sides of DPP-4 and built solid hydrophobic and polar interactions with the amino acids involved in the binding region of DPP-4, such as S1 subsite, S2 subsite and S2 extensive subsite. MD simulations results showed clindamycin as potent virtual hit and suggested that it binds with DPP-4 in competitive manner, which virtually indicate that besides antibiotic activity clindamycin has anti-diabetic activity. Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-021-00118-6.Entities:
Keywords: Clindamycin; Diabetes; Dipeptidyl peptidase 4; Molecular docking; Molecular dynamics simulation; Sitagliptin
Year: 2022 PMID: 35273901 PMCID: PMC8898203 DOI: 10.1007/s40203-021-00118-6
Source DB: PubMed Journal: In Silico Pharmacol ISSN: 2193-9616