Luoshu-Markov Geometric Framework: Fiedler Eigenvalue (lambda₂) for Protein Druggability, Allosteric Site Discovery, and Vina Discrepancy Correction (n=123) — v2 Clean

v2 update: All Unicode symbols corrected (lambda₂, C-alpha, Angstrom, summation). Full content identical to v1. We introduce the Markov-Fiedler spectral complement to the Lo-Shu druggability framework. For n=123 DUD-E proteins (87 druggable, 36 undruggable), the Fiedler eigenvalue lambda₂ of the residue-contact graph Laplacian significantly distinguishes druggable from undruggable proteins (drug=0. 0570 vs undrug=0. 0896, Mann-Whitney p=0. 0028). Combined model CHC + Lo-Shu + LTE + lambda₂ + pocketflex achieves 5-fold CV AUC=0. 8393. Lo-Shu Markov allosteric score recovers 5 validated allosteric proteins (cMyc-Max, CaM, HIF-1alpha, XIAP, PTPB) in top-10 from C-alpha geometry alone. CDK2 Vina discrepancy analysis explains BMS387032 gap (+3. 13 kcal/mol) via entropic N/C-lobe boundary binding.