Computational prioritization of FSP1 inhibitor candidates targeting the ferroptosis-associated protein interactome

Abstract

Ferroptosis suppressor protein 1 (FSP1) mediates cancer resistance to ferroptosis, but structurally diverse inhibitors remain scarce. We present an integrated computational workflow prioritizing FSP1 inhibitors from 306 million compounds across twelve libraries. A validated structure-based pharmacophore from the FSP1-FSEN1 cocrystal selected 5,118 hits. Ensemble docking across six FSP1 conformations, ligand efficiency filtering, and conservation of the critical PHE360 contact narrowed these to 25 compounds for MM-GBSA calculations. Three compounds, MCULE-3726147426, ZINC000022276027, and PubChem-66668216, exhibited predicted binding free energies exceeding FSEN1 (-70.9 kcal/mol), with improvements of 1.8-7.6 kcal/mol. All three engage PHE360 through π-π stacking while exploiting distinct hydrogen bonding and halogen networks. Molecular dynamics simulations showed compound-specific effects. MCULE-3726147426 reduced PHE360 flexibility by 41.1%. PubChem-66668216 formed a π-cation interaction with LYS355 (−7.49 kcal/mol). ZINC000022276027 displayed a distributed binding network. Network pharmacology predicted targeting of 44 ferroptosis-associated proteins, with enrichment in MAPK signaling (FDR = 2.30 × 10⁻ 11 ) and autophagy pathways (FDR = 2.42 × 10⁻⁶), suggesting potential polypharmacological interactions that warrant experimental investigation. ADMET profiling and DFT calculations identified ZINC000022276027 as possessing the most favorable predicted safety profile (HOMO-LUMO gap = 4.28 eV; low toxicity probabilities). This integrated pipeline delivers three structurally distinct chemotypes with predicted activity that warrant experimental evaluation.

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