Tunable triazole-based cholera toxin inhibitors: A QSAR-guided design and evaluation approach

Cholera toxin B subunit (CTB) is a validated target for anticholera therapeutics, but current inhibitors often suffer from synthetic complexity and limited tunability. This study aimed to develop a compact, tunable triazole scaffold exhibiting low-micromolar potency combined with high synthetic tractability. We applied a unified, QSAR-driven, multiscale computational-experimental workflow integrating molecular docking, induced fit docking (IFD), molecular dynamics (MD), QM/MM calculations, and descriptor-based QSAR modeling to prioritize a focused library of 44 N-sulfonyl triazole inhibitors. QSAR modeling employed multiple regression techniques on molecular descriptors derived from E-Dragon software and quantum mechanical (QM/QM-MM) parameters. Models including Ordinary Linear Regression, LASSO, Ridge, Elastic Net, Random Forest, Support Vector Machine (SVM), and Gradient Boosting Machine (GBM) were developed. The best predictive performance was achieved by SVM (test R² = 0.79, RMSE = 0.49) and Random Forest (test R² = 0.77, RMSE = 0.52) on E-Dragon descriptors, while multiple linear regression yielded outstanding fits on QM descriptors (test R² up to 0.98, RMSE ∼0.14). Key molecular descriptors influencing activity included hydrogen bond donor count (ndonr), polarizability (AlogP), and topological indices (Jhetv). Guided by these QSAR models, lead candidates were synthesized via regioselective Cu(I)/Ru-catalyzed click chemistry, with experimental CTB-ELISA screening confirming compound 5d as the most potent inhibitor (IC₅₀ = 11.78 ± 1.2 μM). Computational studies consistently supported these findings, demonstrating favorable binding energetics, dynamic adaptability, and optimal electronic complementarity for lead compounds. This integrated strategy not only delivers a potent, synthetically accessible monovalent CTB inhibitor but also provides a rational, data-driven platform for rapid design and optimization for multivalent cholera toxin antagonists with improved efficacy.

1,2,3-Triazole derivatives; Cholera toxin B-subunit; Click chemistry (CuAAC/RuAAC); ELISA binding assay; Molecular docking; Molecular dynamics (MD) simulations; Multivalent inhibitors; QM/MM descriptors; QSAR modeling.