Computational Druggability Assessment of Mitochondrial Targets: Structure-Function Constraints and Binding Site Characterization

Background Precision drug design for mitochondrial disease requires a systematic evaluation of whether each drug target possesses a pharmacologically tractable binding site. Druggability is determined by the intersection of structural accessibility, ligand efficiency evidence, pharmacological precedent, and mitochondrial delivery feasibility. No comprehensive druggability map exists for the curated mitochondrial target landscape defined by the MitoCorex compendium. Methods Computational and literature-based druggability assessment was performed for all 25 targets from the MitoCorex pathway registry. Assessment integrated five dimensions: binding site type and geometry (PDB structures and AlphaFold2 homology models), pocket accessibility (fpocket v4.0, SiteMap v3.5), ligand efficiency evidence (ChEMBL v33), pharmacological precedent (approved drugs, clinical-stage compounds, tool compounds), and mitochondrial delivery feasibility (encoding locus, subcellular compartment, established delivery strategies). Targets were stratified into three druggability tiers using a weighted five-dimension scoring rubric. Results Fifteen targets achieved Tier 1 (high druggability; 60%), nine Tier 2 (moderate; 36%), and one Tier 3 (low; 4%). Five highest-priority targets were identified: DNM1L/DRP1, PINK1, NFE2L2/Keap1, NDUFV1, and SDHA. Three mtDNA-encoded structural subunits (MT-ND1, MT-ND4, MT-ATP6) were designated gene therapy primary. The druggability registry (druggability_registry_v1.yaml) is deposited at GitHub under CC-BY 4.0 and functions as a machine-readable structured input for downstream AI-driven molecule design. Conclusions The MitoCorex target landscape is pharmacologically tractable: 60% Tier 1, 36% Tier 2. The five highest-priority targets combine favorable structural profiles, clinical-stage precedent scaffolds, and no mitochondrial targeting barrier, making them immediate candidates for AI-driven de novo molecule design. The druggability registry provides a FAIR-compliant, machine-readable resource for the mitochondrial disease research community.