Understanding and predicting the cell permeability and solubility of macrocycles
Abstract
During the last 10+ years my group has investigated the relationship between the conformations adopted by compounds that are larger than traditional small molecule drugs and their solubility and permeability across cell membranes, i.e. two of the three properties that are crucial for orally administered drugs. Our focus has been on macrocycles, which can modulate targets out of reach for traditional drugs, and PROTACs which operate by a novel mode of action, i.e. by inducing degradation of the target. By combining computational studies (e.g. Monte Carlo conformational sampling and MD simulations) with experimental studies based on NMR spectroscopy we have generated mechanistic models for how macrocycles and PROTACs can display both high solubility and cell permeability, properties that are often mutually exclusive. We have also used machine learning to develop models that can predict cell permeability rapidly and with high throughput before embarking on time-consuming and costly synthesis. Our work has been reported in more than 40 publications, with the most influential ones being (number of citations in parenthesis): Chem. & Biol., 2014, 21, 1115 (804); J. Med. Chem., 2014, 57, 278 (623); J. Med. Chem., 2016, 59, 2312 (350); Nature Chem. Biol., 2016, 12, 1065 (203); J. Med. Chem., 2018, 61, 4189 (216); Chem. Eur. J., 2020, 26, 5231 (120); ACS Med. Chem. Lett., 2020, 12, 107 (147); J. Med. Chem., 2022, 65, 13029 (88); J. Chem. Inf. Model., 2022, 63, 138 (20); J. Med. Chem., 2023, 66, 5377 (160); Nat. Rev. Chem., 2024, 8, 45 (42); Nat. Chem. Biol., 2024, 20, 1242 (2). As revealed by the high citations rates for our articles and invitations for lectures at conferences this project has attracted large interest in the international scientific community. As a result, we are one of the co-applicants that obtained a prestigious Horizon-MSCA grant providing funding for the project “Macrocycles for Drug Discovery” (MC4DD) in which three PhD students have been employed at Uppsala University during the spring. Our aim is to expand both our mechanistic understanding of macrocycle solubility and cell permeability, and to make our first-generation predictive machine learning models much more accurate. Both aims will have a large impact on our ability to design cell permeable and orally bioavailable macrocyclic drugs. Two of the three PhD students will require a substantial access to HPC resources. In particular these resources will be used for Monte Carlo conformational searches and Molecular Dynamics simulations in explicit solvents and across artificial membranes. Energy minimizations will be done both by molecular mechanics and by quantum mechanics at the DFT level. This project is continuation of our previous projects SNIC 2019/3-295, SNIC 2021/22-244, SNIC 2022/22-287, SNIC 2022/6-287, NAISS 2023/22-253, NAISS 2023/5-88, NAISS 2024/22-527, NAISS 2024/22-628, submitted by me or the previous coworkers in my group Vasanthanathan Poongavanam and Saw Simeon. Continued access to computational resources is essential for us to succeed in the EU funded MC4DD project.
