Investigation of 3D structural specificities between neurotransmitters and receptors using the TSR-based computational method

Neurons in the brain communicate through interactions between neurotransmitters and their receptors. Structure-based rational design of opioid drugs remains a major challenge, largely due to a lack of mechanistic insight into opioid-receptor selectivity and receptor activation. To address this gap, we present an enhanced Triangular Spatial Relationship (TSR)-based method to define and quantitatively characterize ligand-induced conformational changes in both receptors and ligands. To accurately model the geometries of neurotransmitters and opioids, we developed a novel algorithm for extracting their three-dimensional structural features. The key contributions of this work are summarized as follows: (i) Synergistic improvements in elucidating structure-function relationships were achieved by simultaneously applying two feature-engineering strategies. (ii) The influence of local receptor environments on the structural variations of glutamate and aspartate was quantitatively analyzed to elucidate conformational changes. (iii) Complementary structural features between fentanyl and its biosensor were identified, providing insights into binding specificity. (iv) Tyrosine residues within neurotransmitter binding sites were shown to be structurally distinct from those located outside these sites. (v) For the first time, the TSR-based method was integrated with Density Functional Theory and Quantum Mechanics/Molecular Mechanics optimization, revealing a clear relationship between structure and energy. (vi) The TSR-based method demonstrated superior performance compared with RMSD, USR, ROSHAMBO, and Phase approaches. In conclusion, this study establishes an advanced computational framework for representing and quantifying neurotransmitter structures. The TSR-based approach provides a powerful tool for dissecting structural specificity in ligand-receptor interactions and lays a solid foundation for deeper mechanistic insight and more effective rational drug design.