Luoshu Trigram Transition Energy as a Geometric Prior for Drug Binding Pocket Prediction

We propose a novel geometric prior for predicting drug binding pockets in proteins based on the Luoshu (River Map) and Bagua (Eight Trigrams) cosmological framework. Each residue backbone dihedral angles (phi, psi) are mapped to one of eight trigram states via a three-bit classification rule. The Luoshu Transition Energy (LTE) quantifies conformational switching abruptness along the protein chain, computed as a multi-scale weighted sum (w=1,3,5,7) with golden-ratio weighting. Applied to seven structurally rigid proteins with known binding sites, the method achieves meta-analytic AUC=0.668 (p<1e-6, Mann-Whitney U test), with 5/7 proteins individually reaching AUC>0.65 (p<0.05). Adding 3D spatial aggregation raises all seven to AUC≥0.58. LTE requires no MD simulation, 3D docking, or evolutionary sequence data.