Luoshu Trigram Transition Energy as a Geometric Prior for Drug Binding Pocket Prediction
Abstract
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 (p0.65 (p
Fields of Study & Subjects
Protein Structure and Dynamics
Computational Drug Discovery Methods
Machine Learning in Bioinformatics
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 7 May 2026
- Language
- EN
- Document type
- Preprint