In-silico identification of phytochemical compounds from various medicinal plants as potent HIV-1 non-nucleoside reverse transcriptase inhibitors utilizing molecular docking and molecular dynamics simulations.

ABSTRACT: HIV is a global public health challenge. The Reverse Transcriptase (RT) enzyme facilitates an important step in HIV replication. Inhibition of this enzyme provides a critical target for HIV treatment. The aim of this study is to employ computational techniques to screen bioactive compounds from different medicinal plants toward identifying potent HIV-1 RT inhibitors better activity than the current ones. We conducted a literature review of HIV-1 RT inhibitors, and eighty-four (84) compounds, while target receptor (1REV) was retrieved from Protein Data Bank. The molecular docking and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) evaluations were performed using the Maestro Schrodinger software user interface. The drug-likeness and pharmacokinetic profile evaluation were carrie

SUBMITTER: Danladi S 

PROVIDER: S-EPMC12619908 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature