{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T06:53:27Z","timestamp":1781679207544,"version":"3.54.5"},"reference-count":93,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T00:00:00Z","timestamp":1781222400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Pharmaceutics"],"abstract":"<jats:p>Background\/Objectives: Traditional protein contact analysis often fails to distinguish between local, sequence-driven motifs and global, tertiary scaffolding, which ensures structural determinism. While deep-learning models do not fully elucidate the \u2018why\u2019, they do reveal the underlying directional rules of the stability landscape. In this study, we analyzed 475 non-redundant Protein Data Bank (PDB) structures categorized into SCOP classes (all-\u03b1, all-\u03b2, \u03b1\/\u03b2, \u03b1+\u03b2) of the hydrolase superfamily. Methods: To isolate the structural anchors of the global fold, we applied a sequence separation filter of \u2223i \u2212 j\u2223 \u2265 6 and a precise spatial cutoff of 3\u20135 \u00c5 between C\u03b1-only to construct asymmetric 20 \u00d7 20 frequency matrices, both raw and normalized, then present the former using a violin diagram. We developed a Pearson Correlation (PC) framework to analyze these matrices, providing high correlation when considered as vectors and giving the directionality (N-to-C vs. C-to-N) in protein folding when considered as matrices. Results: Our results reveal a hierarchical organization of tertiary determinism. Initial visualization of Residue\u2013Residue Contact Frequency Matrices (RRCFMs), Z-score normalization (NRRCFM), and violin plots reveal the Universal Structural Grammar (USG) of interaction. Furthermore, a near-perfect PC (r = 0.99) as determined via inter-class Z-score correlation and inter-class PC demonstrates shared statistical interaction laws. In addition, PC Stage 1 (intra-class) analysis identified high symmetry, with around 80% of contacts exhibiting a very strong to strong positive correlations, while PC Stage 2 (inter-class) analysis demonstrated that around 50% of contacts exhibited very strong to strong positive correlations. Finally, we identified universal druggable pockets for drug discovery. Conclusions: This powerful mathematical framework provides a robust analytical tool for structure-based drug design.<\/jats:p>","DOI":"10.3390\/pharmaceutics18060728","type":"journal-article","created":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T05:56:31Z","timestamp":1781675791000},"page":"728","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Universal Structural Grammar in Enzyme Fold for Predicting Drug Target Stability: Deciphering Directional Scaffolding via Multi-Stage Pearson Correlation of Asymmetric Contact Matrices"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7419-8492","authenticated-orcid":false,"given":"Fatin","family":"Jannus","sequence":"first","affiliation":[{"name":"Department of Biochemistry and Molecular Biology I, Faculty of Sciences, University of Granada, Av. Fuentenueva, 18071 Granada, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hilario","family":"Ram\u00edrez-Rodrigo","sequence":"additional","affiliation":[{"name":"Department of Biochemistry and Molecular Biology I, Faculty of Sciences, University of Granada, Av. Fuentenueva, 18071 Granada, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"862","DOI":"10.1007\/s12033-024-01119-4","article-title":"Importance of Inter-Residue Contacts for Understanding Protein Folding and Unfolding Rates, Remote Homology, and Drug Design","volume":"67","author":"Harihar","year":"2025","journal-title":"Mol. 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