In silico identification of prolyl hydroxylase inhibitor by per‐residue energy decomposition‐based pharmacophore approach

Abstract

Hypoxia is an effective preconditioning stimulus and many cellular responses to hypoxia are mediated through a transcription control complex termed the hypoxia‐inducible factor (HIF). The stability and activation of HIF are governed by HIF prolyl‐4‐hydroxylases 2 (PHD2). Hence, the development of a small molecule inhibitor for prolyl hydroxylase has been suggested as a potentially useful therapeutic strategy for the treatment of oxidative/ischemic stress conditions. Thus, to unveil a novel human PHD2 inhibitor, a custom‐based virtual screening was carried out to identify the potential inhibitors against PHD2 based on; (1) the per‐residue energy decomposition (PRED)‐based pharmacophore model, (2) molecular docking, and (3) MD approaches. The PRED analysis was performed to identify the common interaction pattern of HIF fragment (5L9B) and crystallized ligand (4JZR) to develop a relevant accurate allosteric pharmacophore model. The custom pharmacophore model (AAARR) was developed and further used to screen multiple databases. The docking was performed as a secondary strategy for screening the pharmacophore hits. Furthermore, the docked complexes were screened by molecular dynamics (MD) simulation and molecular mechanics/generalized Born surface area (MM–GBSA) based binding free energy calculations to determine the binding energy of the inhibitors and to identify crucial interaction energy fingerprint. One hit has demonstrated good binding free energy and a better binding affinity for PHD2 compared to the other four selected ligands. Thus, the results obtained from pharmacophore, docking, and MD simulations depicted that linker length and metal binding in the scaffold could be effectively used as a potent inhibitor toward human PHD2 in AD therapeutics.

Metabolite fingerprinting of phytoconstituents from Fritillaria cirrhosa D. Don and molecular docking analysis of bioactive peonidin with microbial drug target proteins

“…Peonidin (2-(4-hydroxy-3-methoxyphenyl) chromenylium-3,5,7-triol) exhibited the best binding conformations with the lowest binding energy values with bacterial (− 8.2 kcal/mol), fungal (− 8.2 kcal/mol) target proteins (Tables 5 and 6 ). Our findings are supported by a previous study that showed that the lower the binding energy score, the better the protein–ligand binding stability was identified 44 . The peonidin formed the most excellent ligand–protein complexes with six tested microbial target proteins compared with other compounds.…”

Mechanistic Insight into Binding of Huperzine A with Human Serum Albumin: Computational and Spectroscopic Approaches

“…Many studies have used the MD simulation approach to investigate ligand binding with proteins [ 7 , 19 , 20 , 21 ]. All-atom MD simulations were carried out for the docked complex of HSA–HpzA and compared with those for the free state of HSA.…”

Bioactive Phytoconstituents as Potent Inhibitors of Tyrosine-Protein Kinase Yes (YES1): Implications in Anticancer Therapeutics

“…The solvent-accessible surface area (SASA) of a protein is the surface area accessible to its adjacent solvent [ 19 ]. The stability and folding behavior of proteins are studied using SASA [ 20 ].…”