From sequence analysis of DPP-4 to molecular docking based searching of its inhibitors

Abstract

Literature data suggests that Dipeptidyl peptidase-4 (DPP-4) is a potential target for type 2 Diabetes Mellitus. Therefore, it is of interest to identify new DPP-4 inhibitors using molecular docking analysis. We document compounds such as STOCK1N-98884, STOCK1N-98881, and STOCK1N-98866 with optimal binding features with DPP-4 from the ligand database at https://www.ibscreen.com/ for further consideration.

Screening of potential antidiabetic phytochemicals from Gongronema latifolium leaf against therapeutic targets of type 2 diabetes mellitus: multi-targets drug design

“…Molecular docking is an exciting technique in computeraided drug design that employs a computer algorithm (e.g. Glide) to find the best ligand that fits into the binding pocket of a receptor at the atomic and sub-atomic levels, thereby simulating intermolecular interaction between them [21,22]. Recent studies have shown the antidiabetic properties of Gongronema latifolium in rat model [23][24][25].…”

Dipeptidyl Peptidase 4 Inhibitors in Type 2 Diabetes Mellitus Management: Pharmacophore Virtual Screening, Molecular Docking, Pharmacokinetic Evaluations, and Conceptual DFT Analysis

“…A total of 1,149,497 published papers were assembled in the Web of Science Core Collection (WoSCC) until June 2023 on the topics of "diabetes", 930,263 of which have been published after the year 2000 The scientific community's interest in the management of this disease has grown considerably (about 40%), observing a significant increase in scientific publications from approximately 17,000 in the year 2000 to approximately 70,000 in the year 2022 (Figure 1). So, in the early stage of drug design, in silico requirements have been managed by using various computational approaches, such as pharmacophore modeling [28][29][30][31], quantitative structure-activity relationships (QSAR) [32][33][34][35], molecular docking [36][37][38][39], molecular dynamics simulation [40][41][42], DFT simulation [35,[43][44][45][46], etc. These techniques have generated notable interest by reducing the time required for experimental trials, as well as human and resource costs.…”

“…Investigating the binding interactions of DPP-4 inhibitors at the binding site is essential for gaining insights into their effectiveness and for providing guidance in the exploration of new drug candidates. The crystal structure of DPP-4 displays a homodimeric configuration, with two chains, chain A and chain B, and it consists of four domains (a cytoplasmic domain (1-6), a transmembrane domain (TMD) , a flexible stalk segment (29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39), and the extracellular domain (40-766) with five subsites: S1 (SER630, VAL656, TRP659, TYR662, TYR666, ASN710, VAL711), S2 (ARG125, GLU205, GLU206, PHE357, ARG358, ARG669), S1 (PHE357, TYR547, PRO550, SER630, TYR631, TYR666), S2 (TYR547, TRP629, SER630, HIS740), and S2 extensive (VAL207, SER209, PHE357, ARG358) [52,53]. The mandatory ligand's interactions for DPP-4 inhibition with S1 and S2 subunits were observed both for alogliptin within the 3GB0 binding site, linagliptin within the 2RGU binding site, and sitagliptin within the 1 × 70 binding site.…”