ReaxFF-Guided Optimization of VIRIP-Based HIV-1 Entry Inhibitors.

Peptides hold great promise for safe and effective treatment of viral infections. However, their use is often constrained by limited efficacy and high production costs, especially for long or complex peptide chains. Here, we used ReaxFF molecular dynamics (MD) simulations to optimize the size and activity of VIRIP (Virus Inhibitory Peptide), a naturally occurring 20-residue fragment of α1-antitrypsin that binds the HIV-1 GP41 fusion peptide (FP), thereby blocking viral fusion and entry into host cells. Specifically, we used the NMR structure of the complex between an optimized VIRIP derivative (VIR-165) and the HIV-1 gp41 FP for ReaxFF-guided in silico analysis, evaluating the contribution of each amino acid in the interaction of the inhibitor with its viral target. This approach allowed us to reduce the size of the HIV-1 FP inhibitor from 20 to 10 amino acids (2.28-1.11 kDa). HIV-1 infection assays showed that the size-optimized VIRIP derivative (soVIRIP) retains its broad-spectrum anti-HIV-1 capability and is nontoxic in the vertebrate zebrafish model. Compared to the original VIRIP, soVIRIP displayed more than 100-fold higher antiviral activity (IC₅₀ of ∼120 nM). Thus, it is more potent than a dimeric 20-residue VIRIP derivative (VIR-576) that was proven safe and effective in a phase I/II clinical trial. Our results show that ReaxFF-based MD simulations represent a suitable approach for the optimization of therapeutic peptides.