Dissecting affinity determinants of benzotriazine-based ligands at sigma-1 receptor: a multilevel molecular dynamics analysis

The sigma-1 receptor (S1R) is a chaperone protein involved in several physiological and pathological processes and represents an attractive target for the development of neuroactive and anticancer agents. Among S1R ligands, 3,3-disubstituted 3,4-dihydro-1,2,4-benzotriazines constitute a pharmacologically relevant but mechanistically underexplored scaffold. In this work, we computationally re-examine a representative set of benzotriazine derivatives previously synthesized and pharmacologically characterized by Fabio Sparatore and coworkers, integrating their published experimental binding affinities with newly generated molecular dynamics simulations to investigate subtle structure–affinity relationships within the series, using haloperidol as a reference S1R antagonist. The analyzed ligands span a broad S1R affinity range while sharing persistent pocket retention and largely conserved anchoring to Glu172, suggesting that affinity differences are not primarily driven by ligand dissociation or loss of the canonical ionic interaction. Instead, residue-resolved contact fingerprints, local flexibility profiles, dynamic cross-correlation analysis, and free-energy landscapes reconstructed from principal component analysis indicated ligand-specific organization of the receptor-bound ensemble. High affinity ligands either preserved a haloperidol-compatible interaction architecture, exemplified by persistent Phe107 and Ala185 contacts, or preferentially sampled a focused alternative ensemble involving Tyr120 and Trp89. In contrast, weaker ligands remained stably retained within the binding pocket but populated more diffuse and less efficiently consolidated receptor-bound ensembles. Collectively, these results demonstrate that S1R affinity in this series is not dictated by static binding motifs alone, but by the joint stabilization of specific local interaction networks and receptor-bound conformational ensembles. This integrated dynamic framework extends the interpretation of S1R structure–affinity relationships beyond static pharmacophore models and provides a computational basis for the rational optimization of future benzotriazine-based ligands.