Refined Coordinate Structures and Pocket Analyses for Endocrine Receptors and Viral Surface Antigens

Dataset Title: Refined Coordinate Structures and Pocket Analyses for Endocrine Receptors and Viral Surface Antigens Overview: Focuses on GPCR endocrine networks and viral spike/glycoprotein complexes (e.g., SARS-CoV-2_S, HIV-1_Env, Influenza_HA, GCGR, GHR). The models expose open epitope loops and GPCR ligand cavities to screen for entry inhibitors and receptor antagonists. Computational Methodology: Target structures are optimized using the NRC CASP-17 Pure Math Folding Engine. This pipeline applies C-alpha harmonic guide potential constraints ($k_{guide} = 0.5$) for comparative modeling (or $k_{guide} = 0.0$ for ab-initio modeling), followed by sidechain relaxation and pocket expansion simulations to identify allosteric and active cavities. All coordinates are audited using the Trageser Tensor Theorem (TTT-7) lattice-parity verification to eliminate steric clashes (minimum inter-atomic distance > 1.10 Å) and loop hallucinations. License: Distributed under Creative Commons Attribution 4.0 International (CC BY 4.0) to enable open, commercial, and academic therapeutic drug design. Principal Investigator: James Paul Trageser Affiliation: Nexus Resonance Codex ORCID: 0009-0006-6678-2908 X (Twitter): @jtrag Repository: https://GitHub.com/Nexus-Resonance-Codex/Drug-Discovery