Protein druggability assessment for natural products using in silico simulation: A case study with estrogen receptor and the flavonoid genistein.

Abstract Traditional herbal medicine (THM) comprises a vast number of natural compounds. Most of them are metabolized into different structures after administration, which makes the clarification of THM’s mode of action more complicated. To evaluate the biological activities of those components and metabolites, in silico simulation technology is helpful. We focused on mixed-solvent molecular dynamics (MD) simulation for druggability assessment of natural products. Mixed-solvent MD is an in silico simulation method for the exploration of ligand-binding sites on target proteins, which uses water and an organic molecule mixture. The selection of organic small molecules is an important factor for predicting the characteristics of natural products. In this study, we used the known crystal structure of estrogen receptors with genistein as a test case and explored fragments reflecting the characteristics of natural products. We found that structures with a 4-pyrone structure are more often included in the natural products database compared with the DrugBank database, and we selectively detected the known-binding sites of estrogen receptor α and β. The results indicate that the 4-pyrone structure might be promising for predicting the protein druggability of flavonoids. Additionally, mixed-solvent MD simulation discriminates the selectivity of genistein between estrogen receptor β and α, indicating that the simulation can be evaluated using indices that differ from those of traditional ligand docking. Although this approach is still in its early stages, it has the potential to provide valuable information for understanding the diverse biological activities of natural products.