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Abstract
Indoleamine 2,3-dioxygenase 1 (IDO1) is implicated in Alzheimer’s disease, Parkinson’s disease, and various cancers, underscoring the need for potent and nontoxic inhibitors. In our previous work, we introduced QFVina and QFVinardo, highlighting the integration of high-level quantum mechanical (QM) conformational data with AutoDock Vina’s vina and Vinardo scoring functions. Building on these methods, we now introduce the generalized QuantumFuture’s Docking (QFD) framework and demonstrate its first broad application, featuring a newly curated library of approximately 30,000 natural products, each rigorously screened for very low predicted toxicity. Using ab initio DFT-D4 calculations (rev-SCAN functional, def2-TZVP basis set) to obtain accurate conformational strain energies, QFD was applied to 16 protein targets (eight with and eight without a heme cofactor), revealing several dozen top-scoring ligands that combine strong binding with minimal toxicity. Interestingly, the Vinardo and dkoes scoring functions emphasized different subsets of promising hits, highlighting the advantage of using multiple scoring perspectives. These potential IDO1 inhibitors are prime candidates for further refinement via QM/MM and/or molecular dynamics (MD) simulations to account for ligand and protein flexibility. We encourage experimental validation to accelerate the development of these low-toxicity compounds for therapeutic applications in neurodegenerative diseases and cancer.
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