QSAR-ML- and Metadynamics-Guided Design of Symmetrical Bis-Indanones to Overcome Mutational Anchor Loss in...

Background/Objectives: Symmetrical dual-site acetylcholinesterase (AChE) inhibitors offer a compelling strategy to mitigate mutational drug resistance, yet static modeling fails to capture induced-fit dynamics under mutational stress. Methods: Here, a 100,000-compound virtual library was filtered using a machine learning-based QSAR classification pipeline. A strict, empirically calibrated Jaccard applicability domain filter (AD = 0.823) eliminated topological anomalies, yielding a robust cross-validation accuracy (ROC-AUC: 0.80 ± 0.05; independent test MCC: 0.61). Multi-parameter ADMET and shape screening prioritized unique chemotypes to probe the 20 Å enzyme gorge. All-atom explicit-solvent molecular dynamics simulations were coupled with 150 ns enhanced-sampling Metadynamics along two orthogonal collective variables (gorge depth and ligand orientation) to map out the free energy surfaces under mutational stress. Results: Symmetrical probes suffered catastrophic unbinding upon anchor loss. Conversely, the symmetrical core of Lead Compound 1631 demonstrated extraordinary structural resilience. In silico site-directed mutagenesis (W86A and W286A) triggered a thermodynamic locking effect; the W86A mutant forced the complex into a deeper energetic well (ΔG_min = 9.23 ± 1.98 kJ/mol) than the wild-type state (5.26 ± 1.69 kJ/mol). MM/GBSA decomposition confirmed an active electrostatic-solvation compensation mechanism along a "solvation see-saw" diagonal (ΔΔG_total = +1.59 kcal/mol). Finally, Dynamic Cross-Correlation Matrix analysis quantified a mechanical inversion of the CAS-PAS axis into an anti-correlated clamping mode (-0.04) that locked the ligand bridge in place. Conclusions: These results demonstrate that symmetrical dual-site targeting, combined with dynamic thermodynamic locking, provides a resilient framework to overcome mutational resistance in AChE inhibitors.