Refined Coordinate Structures and Pocket Analyses for Monogenic Pathologies and Cardiovascular Targets

Dataset Title: Refined Coordinate Structures and Pocket Analyses for Monogenic Pathologies and Cardiovascular Targets Overview: Focuses on large-scale structural targets in muscular dystrophy, tissue elasticity, and monogenic diseases (e.g., CFTR, DMD, KCNH2, KCNQ1, MYH7, MYO7A, COL1A1, FBN1, ALB, ATP7B, FAH, LDLR). Refined models highlight structural pocket volumes to develop molecular chaperones. 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