Anti-HIV Potential of Origanum vulgare Compounds Targeting Viral Reverse Transcriptase with High Binding and Stability Validated by Machine Learning
Abstract
Human immunodeficiency virus (HIV) is one of the viruses that has co-evolved within human populations for a considerable time. With the evolution of new drug-resistant HIV strains, the necessity to discover novel drugs has become an issue of great concern, especially those that have increased binding affinities and inhibitory activity towards RT enzymes. This study used an in silico approach to identify potential HIV-RT inhibitory candidates from Origanum vulgare (oregano). An initial in silico screening of approximately 820 compounds was conducted, and based on molecular docking-derived binding energy scores, four compounds (IMPHY000687, IMPHY007084, IMPHY004619, and IMPHY012021), with docking scores of -9.42, -9.32, -9.24, and -9.23 kcal/mol, respectively, were selected as the top-ranked phytocompounds and were subsequently validated using multiple computational approaches. These compounds were geometrically optimized using quantum-chemical calculations, and detailed interaction analyses were performed using a redocking procedure. Reproducibility of the dynamic behavior was evaluated by carrying out independent replica molecular dynamics simulations for 300 ns each for all complexes. The ligand-dependent conformational dynamics were identified using RMSD and RMSF analyses, along with variations in positional changes during simulation times. PCA and FEL analyses helped in identifying the conformations sampled by the system under study. In addition, QM/MM calculations…
Read the paper
Related studies
- Chaos and quantum thermalization
- The Dalton quantum chemistry program system
- Cord Blood Leptin and Adiponectin as Predictors of Adiposity in Children at 3 Years of Age: A Prospective Cohort Study
- Quantitative metabolomics by H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes
- Stable adiabatic quantum batteries
- A novel self-lipid antigen targets human T cells against CD1c(+) leukemias
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.