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

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Authors: Yao-Kai Kao
Cited by: 2

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