Drug design in the chemical space beyond the ¨rule of 5¨

Discovery of oral drugs that reach intracellular, difficult-to-drug targets is a daunting task.

We have revealed that such drugs are often found in the uncharted chemical space beyond that defined by Lipinski’s Rule of 5 (bRo5) and that their 3D conformations determines their cell permeability and solubility, two key drug properties.

We will develop methods based on quantum mechanics, accelerated MD and/or machine learning for 3D property based design that can be used to prioritize drug candidates in bRo5 space before embarking on long synthetic routes.

Our models will be validated using several unique in-house datasets for which cell permeability, aqueous solubility and solution conformational ensembles have been determined.By in silico mining of natural products we have discovered macrocyclic lead compounds for the highly charged Keap1-Nrf2 protein-protein interaction (PPI) and potent inhibitors of Leishmania parasite infections.

We will now combine structure based design with high-throughput docking and our computational tools to discover neutral, cell permeable and potent inhibitors of Keap1.

Our tools  will also be important in optimization of the pharmacokinetics and potency of the Leishmania inhibitors for in-vivo proof-of-concept studies and target identification.

Overall, this project will provide methods for design of drugs in the bRo5 space that are applied to discover cell permeable inhibitors of a PPI and of the neglected tropical disease Leishmaniasis.