Rational Design of Broad-Spectrum Non-Nucleoside Reverse Transcriptase Inhibitors via Pharmacophore-Oriented Generative Artificial Intelligence

Clinical Snapshot

Key Findings

• P Value: Not reported

• Effect Size: 2.8-fold improvement against Y188L mutant compared to rilpivirine (28.8 nM vs 79.4 nM)

• Primary Outcome: A24 demonstrated potent activity against wild-type HIV-1 (EC50 = 2.07-28.8 nM against resistant mutants)

• Nnt Or Sensitivity: Therapeutic index improvement: A24 CC50/EC50 ratio substantially higher than rilpivirine (>4000 vs 500)

• Confidence Interval: Not reported

Clinical Application

Requires clinical trials before implementation; synthetic feasibility reportedly assessed Relevant to Australian HIV treatment guidelines; could address resistance challenges in treatment-experienced patients if clinical development succeeds HIV-positive patients, particularly those with or at risk of NNRTI resistance

Abstract

Guided by the pharmacophore-oriented molecular generation platform PhoreGen, we employed rilpivirine (RPV) as a lead compound to generate 300 structurally diverse analogs that preserve key pharmacophoric features. Subsequent drug-likeness evaluation, molecular docking score, and synthetic feasibility led to the identification of compound No.102 (A19), which displayed potent inhibition activity against WT HIV-1 (EC50 = 3.15 nM) and low cytotoxicity (CC50 > 335 μM). Subsequent structure-activity relationship optimization identified A24, which demonstrated robust activity against clinically relevant drug-resistant HIV-1 mutants (EC50 = 2.07-28.8 nM). Notably, compared to RPV, A24 exhibited significantly reduced cytotoxicity (CC50 = 82.3 μM vs. 3.98 μM) and enhanced potency against the Y188L (EC50 = 28.8 nM vs. 79.4 nM) and F227L + V106A (EC50 = 19.0 nM vs. 81.6 nM) mutants. Pharmacokinetic evaluations revealed that A24 exhibited attenuated CYP enzyme inhibition (IC50 ≥ 1.88 μM), reduced hERG-related toxicity (IC50 = 2.633 μM), and improved metabolic stability (human t1/2 = 39.1 min). Collectively, these favorable properties position A24 as a promising NNRTI for further development.

References

1. 1.Zhang, K., Lin, Y., Dong, L., Niu, Y., Peng, J., Pannecouque, C., De Clercq, E., Tran, P.-T., Li, G., Zhao, T., Li, X., Su, S., Wang, S., & Chen, F.-E. (2026). Rational design of broad-spectrum non-nucleoside reverse transcriptase inhibitors via pharmacophore-oriented generative artificial intelligence. Journal of Medicinal Chemistry. https://doi.org/10.1021/acs.jmedchem.6c00048