By integrating this QM-based conformational database of low-toxicity natural products with the QFD docking scheme, we present a comprehensive and versatile solution for drug discovery. Although the primary goal here is to identify new potent, nontoxic inhibitors of IDO1 for the treatment of Alzheimer's disease and cancer, the methodology applies equally well to a broad range of disease targets. This integrated approach systematically identifies compounds with realistic low-energy conformations, leveraging high-level QM and ab initio methods. Furthermore, using the wellestablished Vinardo and dkoes scoring functions, these compounds are likely to exhibit strong protein-ligand binding interactions. Finally, because we have selected the safest few percent of natural products from the COCONUT database, the identified compounds are also expected to have low toxicity. Overall, this robust framework provides a powerful platform for advancing therapeutic discovery across multiple disease areas.