Computational Identification and Evaluation of Perlolyrine as a Promising AT1R Antagonist for Hypertension Therapy

Abstract The angiotensin II type 1 receptor (AT1R) is a key target for antihypertensive drug development. This study uses an integrative computational approach to identify perlolyrine (MOL002140) as a promising AT1R modulator. A comprehensive in silico workflow was used, which included pharmacophore modeling, molecular docking, ADMET profiling, DFT calculations, and molecular dynamics (MD) simulations. Strong binding affinity to AT1R (− 8.2 kcal/mol) was demonstrated by perlolyrine, which also formed stable interactions with important residues like TRP84, TYR87, ASP281, and ARG167. ADMET predictions showed a good safety profile and favorable pharmacokinetic properties. The electronic stability of the compound with a HOMO–LUMO energy gap of 3.95 eV was confirmed by DFT analysis. The AT1R–Perlolyrine complex was found to be stable, compact, and exhibit few conformational fluctuations in long-timescale MD simulations (200 ns). Consistent receptor–ligand dynamics were further shown by principal component analysis (PCA) and angular distribution studies, confirming the compound's potential as a potent AT1R antagonist. All of these results point to perlolyrine as a viable option for additional research and development in the treatment of hypertension.