The coronavirus SARS-CoV-2 main protease, M pro , is conserved among coronaviruses with no human homolog and has therefore attracted significant attention as an enzyme drug target for COVID-19. The number of studies targeting M pro for in silico screening has grown rapidly, and it would be of great interest to know in advance how well docking methods can reproduce the correct ligand binding modes and rank these correctly. Clearly, current attempts at designing drugs targeting M pro with the aid of computational docking would benefit from a priori knowledge of the ability of docking programs to predict correct binding modes and score these correctly. In the current work, we tested the ability of several leading docking programs, namely, Glide, DOCK, AutoDock, AutoDock Vina, FRED, and EnzyDock, to correctly identify and score the binding mode of M pro ligands in 193 crystal structures. None of the codes were able to correctly identify the crystal structure binding mode (lowest energy pose with root-mean-square deviation < 2 Å) in more than 26% of the cases for noncovalently bound ligands (Glide: top performer), whereas for covalently bound ligands the top score was 45% (EnzyDock). These results suggest that one should perform in silico campaigns of M pro with care and that more comprehensive strategies including ligand free energy perturbation might be necessary in conjunction with virtual screening and docking.

Carbocations play key roles in classical organic reactions and have also been implicated in several enzyme families. A hallmark of carbocation chemistry is multitudes of competing reaction pathways, and to be able to distinguish between pathways with quantum chemical calculations, it is necessary to approach chemical accuracy for relative energies between carbocations. Here, we present an extensive study of the performance of selected density functional theory (DFT) methods in describing the thermochemistry and kinetics of carbocations and their corresponding neutral alkenes both in the gas-phase and within a hybrid quantum mechanics-molecular mechanics (QM/MM) framework. The density functionals are benchmarked against accurate ab initio methods such as CBS-QB3 and DLPNO-CCSD(T). Based on the findings in the gas-phase calculations of carbocations and alkenes, the best functionals are chosen and tested further for non-covalent interactions in model systems using QM and QM/MM methods. We compute the interaction energies between a model carbocation/alkane and model π, dipole, and hydrophobic systems using DFT and QM(DFT)/MM and compare with DLPNO-CCSD(T). These latter model systems are representative of side chains of amino acids such as phenylalanine/tyrosine, tryptophan, asparagine/glutamine, serine/threonine, methionine, and other hydrophobic groups. The Lennard−Jones parameters of the QM atoms in QM(DFT)/MM calculations are modified to obtain an optimal fit with the QM energies. Finally, a selected carbocation reaction is studied in the gas phase and in implicit chloroform solvent using QM and in explicit chloroform solvent using QM/MM and umbrella sampling simulations. This study highlights the highest accuracy possible with selected density functionals and QM/MM methods but also some limitations in using QM/MM methods for carbocation systems.

The sizes of available self‐assembled hydrogen‐bond‐based supramolecular capsules and cages are rather limited. The largest systems have volumes of approximately 1400–2300 Å3. Herein, we report a large, hexameric cage based on intermolecular amide–amide dimerization. The unusual structure with openings, reminiscent of covalently linked cages, is held together by 24 hydrogen bonds. With a diameter of 2.3 nm and a cavity volume of ∼2800 Å3, the assembly is larger than any previously known capsule/cage structure relying exclusively on hydrogen bonds. The self‐assembly process in chlorinated, organic solvents was found to be strongly concentration dependent, with the monomeric form prevailing at low concentrations. Additionally, the formation of host–guest complexes with fullerenes (C60 and C70) was observed.

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Terpene synthases are responsible for the biosynthesis of terpenes, the largest family of natural products. Hydropyrene synthase generates hydropyrene and hydropyrenol as its main products along with two byproducts, isoelisabethatriene A and B. Fascinatingly, a single active site mutation (M75L) diverts the product distribution towards isoelisabethatriene A and B. In the current work, we study the competing pathways leading to these products using quantum chemical calculations in the gas-phase. We show that there is a great thermodynamic preference for hydropyrene and hydropyrenol formation, and hence most likely in the synthesis of the isoelisabethatriene products kinetic control is at play.

Terpene synthases are responsible for the biosynthesis of terpenes, the largest family of natural products. Hydropyrene synthase generates hydropyrene and hydropyrenol as its main products along with two byproducts, isoelisabethatrienes A and B. Fascinatingly, a single active site mutation (M75L) diverts the product distribution towards isoelisabethatrienes A and B. In the current work, we study the competing pathways leading to these products using quantum chemical calculations in the gas phase. We show that there is a great thermodynamic preference for hydropyrene and hydropyrenol formation, and hence most likely in the synthesis of the isoelisabethatriene products kinetic control is at play.