Structural, spectroscopic, molecular docking, ADME, molecular dynamics studies of Val-Trp dipeptide
Abstract
Hypertension is a significant risk factor for various diseases, especially heart, brain, and kidney diseases. It is known that many peptides have the property of lowering blood pressure and determine as ACE inhibitors. The purpose of this study is to obtain information about the molecular structure of Val-Trp (L-valyl-L-tryptophan), which is one of the antihypertensive peptides, by molecular mechanical, quantum mechanical, and spectroscopic methods (FT-IR and Raman). Also, it is aimed to investigate the interactions of Val-Trp dipeptide with receptors related to hypertension and to determine the pharmacokinetic profile due to the potential of the peptide to be a drug candidate. The peptide structure was optimized by DFT/B3LYP/6-311++G(d,p) basis set, then vibrational wavenumbers, molecular electrostatic potential (MEP), HOMO-LUMO (highest occupied molecular orbital- lowest unoccupied molecular orbital), NBO (natural bond orbital) analyzes were performed. The assignment of fundamental theoretical vibration wavenumbers was carried out with potential energy distribution analysis (PED). After the structural analyzes of the peptide were performed, the interactions of the peptide with Angiotensin-converting enzyme (ACE), Angiotensin II Receptor Type 1 (AT1R) and Renin were investigated by molecular docking study. Then, the molecular dynamic (MD) simulation of the peptide-ACE complex with the best binding affinity in the molecular docking studies was carried out for 50 ns. ADME…
Read the paper
Related studies
- Chaos and quantum thermalization
- The Dalton quantum chemistry program system
- Quantum dots: synthesis, bioapplications, and toxicity
- Cord Blood Leptin and Adiponectin as Predictors of Adiposity in Children at 3 Years of Age: A Prospective Cohort Study
- A Guide to In Silico Drug Design
- Quantitative metabolomics by H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.