Benchmarking the Ability of Common Docking Programs to Correctly Reproduce and Score Binding Modes in SARS-CoV-2 Protease Mpro.

The coronavirus SARS-CoV-2 main protease, Mpro, 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 Mpro 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 Mpro 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 Mpro 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 Mpro with care and that more comprehensive strategies including ligand free energy perturbation might be necessary in conjunction with virtual screening and docking.

The Impression of a Nonexisting Catalytic Effect: The Role of CotB2 in Guiding the Complex Biosynthesis of Cyclooctat-9-en-7-ol.

Terpene synthases generate terpenes employing diversified carbocation chemistry, including highly specific ring formations, proton and hydride transfers, and methyl as well as methylene migrations, followed by reaction quenching. In this enzyme family, the main catalytic challenge is not rate enhancement, but rather structural and reactive control of intrinsically unstable carbocations in order to guide the resulting product distribution. Here we employ multiscale modeling within classical and quantum dynamics frameworks to investigate the reaction mechanism in the diterpene synthase CotB2, commencing with the substrate geranyl geranyl diphosphate and terminating with the carbocation precursor to the final product cyclooctat-9-en-7-ol. The 11-step in-enzyme carbocation cascade is compared with the same reaction in the absence of the enzyme. Remarkably, the free energy profiles in gas phase and in CotB2 are surprisingly similar. This similarity contrasts the multitude of strong π-cation, dipole-cation, and ion-pair interactions between all intermediates in the reaction cascade and the enzyme, suggesting a remarkable balance of interactions in CotB2. We ascribe this balance to the similar magnitude of the interactions between the carbocations along the reaction coordinate and the enzyme environment. The effect of CotB2 mutations is studied using multiscale mechanistic docking, machine learning, and X-ray crystallography, pointing the way for future terpene synthase design.

Enzymatic control of product distribution in terpene synthases: insights from multiscale simulations.

In this opinion, we review some recent work on terpene biosynthesis using multiscale simulation approaches, with special focus on contributions from our group. Terpene synthases generate terpenes employing rich carbocation chemistry, including highly specific ring formations, proton, hydride, methyl, and methylene migrations, followed by reaction quenching. In these enzymes, the main catalytic challenge is not rate enhancement, but rather control of intrinsically reactive carbocations and the resulting product distribution. Herein, we review multiscale simulations of selected mono-, sesqui-, and diterpene synthases. We point to the many tools adopted by terpene synthases to achieve correct substrate fold, carbocation formation, carbocation reaction environment, and reaction quenching. A better understanding of the toolbox employed by terpene synthases is expected to aid in the search for new enzymatic and biomimetic synthetic routes to natural and unnatural terpenes.

Understanding the role of active site residues in CotB2 catalysis using a cluster model.

Terpene cyclases are responsible for the initial cyclization cascade in the multistep synthesis of a large number of terpenes. CotB2 is a diterpene cyclase from Streptomyces melanosporofaciens, which catalyzes the formation of cycloocta-9-en-7-ol, a precursor to the next-generation anti-inflammatory drug cyclooctatin. In this work, we present evidence for the significant role of the active site's residues in CotB2 on the reaction energetics using quantum mechanical calculations in an active site cluster model. The results revealed the significant effect of the active site residues on the relative electronic energy of the intermediates and transition state structures with respect to gas phase data. A detailed understanding of the role of the enzyme environment on the CotB2 reaction cascade can provide important information towards a biosynthetic strategy for cyclooctatin and the biomanufacturing of related terpene structures.

Current understanding and biotechnological application of the bacterial diterpene synthase CotB2.

CotB2 catalyzes the first committed step in cyclooctatin biosynthesis of the soil bacterium Streptomyces melanosporofaciens. To date, CotB2 represents the best studied bacterial diterpene synthase. Its reaction mechanism has been addressed by isoptope labeling, targeted mutagenesis and theoretical computations in the gas phase, as well as full enzyme molecular dynamic simulations. By X-ray crystallography different snapshots of CotB2 from the open, inactive, to the closed, active conformation have been obtained in great detail, allowing us to draw detailed conclusions regarding the catalytic mechanism at the molecular level. Moreover, numerous alternative geranylgeranyl diphosphate cyclization products obtained by CotB2 mutagenesis have exciting applications for the sustainable production of high value bioactive substances.

EnzyDock: Protein-Ligand Docking of Multiple Reactive States along a Reaction Coordinate in Enzymes.

Enzymes play a pivotal role in all biological systems. These biomachines are the most effective catalysts known, dramatically enhancing the rate of reactions by more than 10 orders of magnitude relative to the uncatalyzed reactions in solution. Predicting the correct, mechanistically appropriate binding modes for substrate and product, as well as all reaction intermediates and transition states, along a reaction pathway is immensely challenging and remains an unsolved problem. In the present work, we developed an effective methodology for identifying probable binding modes of multiple ligand states along a reaction coordinate in an enzyme active site. The program is called EnzyDock and is a CHARMM-based multistate consensus docking program that includes a series of protocols to predict the chemically relevant orientation of substrate, reaction intermediates, transition states, product, and inhibitors. EnzyDock is based on simulated annealing molecular dynamics and Monte Carlo sampling and allows ligand, as well as enzyme side-chain and backbone flexibility. The program can employ many user-defined constraints and restraints and classical force field potentials, as well as a range of hybrid quantum mechanics-molecular mechanics potentials. Herein, we apply EnzyDock to several different kinds of problems. First, we study two terpene synthase reactions, namely bornyl diphosphate synthase and the bacterial diterpene synthase CotB2. Second, we use EnzyDock to predict reaction coordinate states in a pair of Diels-Alder reactions in the enzymes spirotetronate AbyU and LepI. Third, we study a couple of racemases: the cofactor-dependent serine racemase and the cofactor independent proline racemase. Finally, we study several cases of covalent docking involving the Michael addition reaction. For all systems we predict binding modes that are consistent with available experimental observations, as well as with theoretical modeling studies from the literature. EnzyDock provides a platform for generating mechanistic insight into enzyme reactions, useful and reliable starting points for in-depth multiscale modeling projects, and rational design of noncovalent and covalent enzyme inhibitors.