In silico prediction of the permeability of phytochemicals across the blood-brain barrier

Introduction The role of phytochemicals like xanthines, and (poly)phenols in neurodegenerative diseases has been highly established and explored. However, the mechanism of these molecules to cross the membranes reaching the blood and the brain has largely been understudied. Methods In this work, we used in silico methods to predict the permeability of more than 800 molecules across the membranes and specifically the blood-brain barrier. Our dataset included phytochemicals, like xanthine, phenolic terpenes, (poly)phenols and metabolites, including phase II conjugates, while some endogenous molecules and commercial drugs were used as positive/negative controls. We used QikProp to generate 42 computed physicochemical properties to predict the blood absorption, distribution to the brain, metabolism, and elimination of these molecules. Results According to Qikprop 555 of 800 molecules were inside the range of 95% of known drugs for all computed properties, while through passive di[usion, 78 molecules may reach the blood and 52 may reach the brain parenchyma. Furthermore, using data from natural molecules present in human CSF samples, we used machine learning to build a model that was capable to predict 171 novel molecules with the potential to reach the brain environment. Conclusion Overall, in this work we predicted the natural molecules with the potential to reach the brain, highlighting those that may do so by passive mechanisms. Our study creates an opportunity to track novel molecules in theblood and the brain and highlighting the most drug-promising natural molecules for brain drug development in the treatment and prevention of brain diseases.