Drugs targeting SARS-CoV-2 could have saved millions of lives during the COVID-19 pandemic, and it is now crucial to develop inhibitors of coronavirus replication in preparation for future outbreaks. We explored two virtual screening strategies to find inhibitors of the SARS-CoV-2 main protease in ultralarge chemical libraries. First, structure-based docking was used to screen a diverse library of 235 million virtual compounds against the active site. One hundred top-ranked compounds were tested in binding and enzymatic assays. Second, a fragment discovered by crystallographic screening was optimized guided by docking of millions of elaborated molecules and experimental testing of 93 compounds. Three inhibitors were identified in the first library screen, and five of the selected fragment elaborations showed inhibitory effects. Crystal structures of target–inhibitor complexes confirmed docking predictions and guided hit-to-lead optimization, resulting in a noncovalent main protease inhibitor with nanomolar affinity, a promising in vitro pharmacokinetic profile, and broad-spectrum antiviral effect in infected cells.

Proteolysis targeting chimeras (PROTACs) induce intracellular degradation of target proteins. Their bifunctional structure puts degraders in a chemical space where ADME properties often complicate drug discovery. Herein we provide the first structural insight into PROTAC cell permeability obtained by NMR studies of a VHL-based PROTAC (1), which is cell permeable despite having a high molecular weight and polarity and a large number of rotatable bonds. We found that 1 populates elongated and polar conformations in solutions that mimic extra- and intracellular compartments. Conformations were folded and had a smaller polar surface area in chloroform, mimicking a cell membrane interior. Formation of intramolecular and nonclassical hydrogen bonds, π–π interactions, and shielding of amide groups from solvent all facilitate cell permeability by minimization of size and polarity. We conclude that molecular chameleonicity appears to be of major importance for 1 to enter into target cells.

Macrocycles constitute superior ligands for targets that have flat binding sites but often require long synthetic routes, emphasizing the need for property prediction prior to synthesis. We have investigated the scope and limitations of machine learning classification models and of regression models for predicting the cell permeability of a set of de novo-designed, drug-like macrocycles. 2D-Based classification models, which are fast to calculate, discriminated between macrocycles that had low-medium and high permeability and may be used as virtual filters in early drug discovery projects. Importantly, stereo-and regioisomer were correctly classified. QSPR studies of two small sets of comparator drugs suggested that use of 3D descriptors, calculated from biologically relevant conformations, would allow development of more precise regression models for late phase drug projects. However, a 3D permeability model could only be developed for a rigid series of macrocycles. Comparison of NMR based conformational analysis with in silico conformational sampling indicated that this shortcoming originates from the inability of the molecular mechanics force field to identify the relevant conformations for flexible macrocycles. We speculate that a Kier flexibility index of 10 constitutes a current upper limit for reasonably accurate 3D prediction of macrocycle cell permeability.

Proteolysis-targeting chimeras (PROTACs) must be cell permeable to reach their target proteins. This is challenging as the bivalent structure of PROTACs puts them in chemical space at, or beyond, the outer limits of oral druggable space. We used NMR spectroscopy and molecular dynamics (MD) simulations independently to gain insights into the origin of the differences in cell permeability displayed by three flexible cereblon PROTACs having closely related structures. Both methods revealed that the propensity of the PROTACs to adopt folded conformations with a low solvent-accessible 3D polar surface area in an apolar environment is correlated to high cell permeability. The chemical nature and the flexibility of the linker were essential for the PROTACs to populate folded conformations stabilized by intramolecular hydrogen bonds, π–π interactions, and van der Waals interactions. We conclude that MD simulations may be used for the prospective ranking of cell permeability in the design of cereblon PROTACs.

The replica exchange molecular dynamics (REMD) simulation is demonstrated to readily predict the conformations of the macrocyclic drug lorlatinib, as validated by solution NMR studies. In aqueous solution, lorlatinib adopts a conformer identical to its target bound structure. This conformer is stabilized by an extensive hydrogen bond network to the solvents. In chloroform, lorlatinib populates two conformers with the second one being less polar, which may contribute to lorlatinib’s ability to cross cell membranes.