We describe large scale ab initio quantum chemical and mixed quantum mechanics/molecular mechanics (QM/MM) methods for studying enzymatic reactions. First, technical aspects of the methodology are reviewed, including the hybrid density functional theory (DFT) methods that are typically employed for the QM aspect of the calculations, and various approaches to defining the interface between the QM and MM regions in QM/MM approaches. The modeling of the enzymatic catalytic cycle for three examples--methane monooxygenase, cytochrome P450, and triose phosphate isomerase--are discussed in some depth, followed by a brief summary of other systems that have been investigated by ab initio methods over the past several years. Finally, a discussion of the qualitative and quantitative conclusions concerning enzymatic catalysis that are available from modern ab initio approaches is presented, followed by a conclusion briefly summarizing future prospects.

The extent to which accuracy of electric charges plays a role in protein-ligand docking is investigated through development of a docking algorithm, which incorporates quantum mechanical/molecular mechanical (QM/MM) calculations. In this algorithm, fixed charges of ligands obtained from force field parameterization are replaced by QM/MM calculations in the protein environment, treating only the ligands as the quantum region. The algorithm is tested on a set of 40 cocrystallized structures taken from the Protein Data Bank (PDB) and provides strong evidence that use of nonfixed charges is important. An algorithm, dubbed "Survival of the Fittest" (SOF) algorithm, is implemented to incorporate QM/MM charge calculations without any prior knowledge of native structures of the complexes. Using an iterative protocol, this algorithm is able in many cases to converge to a nativelike structure in systems where redocking of the ligand using a standard fixed charge force field exhibits nontrivial errors. The results demonstrate that polarization effects can play a significant role in determining the structures of protein-ligand complexes, and provide a promising start towards the development of more accurate docking methods for lead optimization applications.

Esterases receive special attention because of their wide distribution in biological systems and environments and their importance for physiology and chemical synthesis. The prediction of esterases' substrate promiscuity level from sequence data and the molecular reasons why certain such enzymes are more promiscuous than others remain to be elucidated. This limits the surveillance of the sequence space for esterases potentially leading to new versatile biocatalysts and new insights into their role in cellular function. Here, we performed an extensive analysis of the substrate spectra of 145 phylogenetically and environmentally diverse microbial esterases, when tested with 96 diverse esters. We determined the primary factors shaping their substrate range by analyzing substrate range patterns in combination with structural analysis and protein-ligand simulations. We found a structural parameter that helps rank (classify) the promiscuity level of esterases from sequence data at 94% accuracy. This parameter, the active site effective volume, exemplifies the topology of the catalytic environment by measuring the active site cavity volume corrected by the relative solvent accessible surface area (SASA) of the catalytic triad. Sequences encoding esterases with active site effective volumes (cavity volume/SASA) above a threshold show greater substrate spectra, which can be further extended in combination with phylogenetic data. This measure provides also a valuable tool for interrogating substrates capable of being converted. This measure, found to be transferred to phosphatases of the haloalkanoic acid dehalogenase superfamily and possibly other enzymatic systems, represents a powerful tool for low-cost bioprospecting for esterases with broad substrate ranges, in large scale sequence data sets.

The catalytic pathway of cytochrome P450cam is studied by means of a hybrid quantum mechanics/molecular mechanics method. Our results reveal an active role of the enzyme in the different catalytic steps. The protein initially controls the energy gap between the high- and low-spin states in the substrate binding process, allowing thermodynamic reduction by putidaredoxin reductase and molecular oxygen addition. A second electron reduction activates the delivery of protons to the active site through a selective interaction of Thr252 and the distal oxygen causing the O--O cleavage. Finally, the protein environment catalyzes the substrate hydrogen atom abstraction step with a remarkably low free energy barrier ( approximately 8 kcal/mol). Our results are consistent with the effect of mutations on the enzymatic efficacy and provide a satisfactory explanation for the experimental failure to trap the proposed catalytically competent species, a ferryl Fe(IV) heme.

Summary Substantial improvements in enzyme activity demand multiple mutations at spatially proximal positions in the active site. Such mutations, however, often exhibit unpredictable epistatic (non-additive) effects on activity. Here, we describe FuncLib - an automated method for designing multipoint mutations at enzyme active sites using phylogenetic analysis and Rosetta design calculations. We applied FuncLib to two unrelated enzymes, a phosphotriesterase and an acetyl-CoA synthetase. All designs were active and most showed activity profiles that significantly differed from the wild type and from one another. Several dozen designs with only 3-6 active-site mutations exhibited 10-4,000-fold higher efficiencies with a range of alternative substrates, including the hydrolysis of the toxic organophosphate nerve agents soman and cyclosarin and the synthesis of butyryl-CoA. FuncLib is implemented as a web-server (http://FuncLib.weizmann.ac.il); it circumvents iterative, high-throughput screens and opens the way to design highly efficient and diverse catalytic repertoires.

Combining protein structure prediction algorithms and Metropolis Monte Carlo techniques, we provide a novel method to explore all-atom energy landscapes. The core of the technique is based on a steered localized perturbation followed by side-chain sampling as well as minimization cycles. The algorithm and its application to ligand diffusion are presented here. Ligand exit pathways are successfully modeled for different systems containing ligands of various sizes:  carbon monoxide in myoglobin, camphor in cytochrome P450cam, and palmitic acid in the intestinal fatty-acid-binding protein. These initial applications reveal the potential of this new technique in mapping millisecond-time-scale processes. The computational cost associated with the exploration is significantly less than that of conventional MD simulations.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of COVID-19, is considered a zoonotic pathogen mainly transmitted human to human. Few reports indicate that pets may be exposed to the virus. The present report describes a cat suffering from severe respiratory distress and thrombocytopenia living with a family with several members affected by COVID-19. Clinical signs of the cat prompted humanitarian euthanasia and a detailed postmortem investigation to assess whether a COVID-19−like disease was causing the condition. Necropsy results showed the animal suffered from feline hypertrophic cardiomyopathy and severe pulmonary edema and thrombosis. SARS-CoV-2 RNA was only detected in nasal swab, nasal turbinates, and mesenteric lymph node, but no evidence of histopathological lesions compatible with a viral infection were detected. The cat seroconverted against SARS-CoV-2, further evidencing a productive infection in this animal. We conclude that the animal had a subclinical SARS-CoV-2 infection concomitant to an unrelated cardiomyopathy that led to euthanasia.

We elucidate the hydroxylation of camphor by cytochrome P450 with the use of density functional and mixed quantum mechanics͞ molecular mechanics methods. Our results reveal that the enzyme catalyzes the hydrogen-atom abstraction step with a remarkably low free-energy barrier. This result provides a satisfactory explanation for the experimental failure to trap the proposed catalytically competent high-valent heme Fe(IV) oxo (oxyferryl) species responsible for this hydroxylation chemistry. The primary and previously unappreciated contribution to stabilization of the transition state is the interaction of positively charged residues in the active-site cavity with carboxylate groups on the heme periphery. A similar stabilization found in dioxygen binding to hemerythrin, albeit with reversed polarity, suggests that this mechanism for controlling the relative energetics of redox-active intermediates and transition states in metalloproteins may be widespread in nature.T he family of cytochrome P450 monooxygenases is ubiquitous in human biology, playing a key role in the metabolism of pharmaceutical agents and other ingested exogenous compounds (1). These enzymes insert an oxygen atom from O 2 into a wide variety of substrates, with substrate specificity determined by the nature of the protein active-site cavity. All members of the family are believed to share a common mechanism for such hydroxylation (2). In the catalytic cycle, dioxygen bound to an iron porphyrin undergoes a series of transformations to produce an intermediate capable of hydroxylating a COH bond of the substrate. The currently accepted steps in this cycle are depicted in Fig. 1. We focus here on the bacterial isozyme cytochrome P450cam, for which camphor is the substrate, to exploit the wealth of experimental data measured for this system.Because of its prominent role in biology and medicine, an exceptionally large amount of experimental and theoretical work has been invested in understanding the various steps of the cytochrome P450 reaction cycle (1-16). A complete atomic-level picture of the key steps, particularly the hydroxylation reaction, has yet to be produced, however. Such knowledge is essential in building quantitative models of P450-based contributions to drug metabolism and toxicity. This deficiency is due in part to the difficulties in carrying out incisive experimental and theoretical studies. Experimental investigation of the catalytically competent species in the hydroxylation reaction is hindered by the fact that the presence of substrate is necessary to initiate the reaction cycle. This situation can be contrasted with that in soluble methane monooxygenase (MMO). Formation of the key catalytic intermediate in the reaction cycle of the MMO hydroxylase can be initiated by dioxygen and then trapped in the absence of substrate. Such a result has yet to be duplicated in P450, as is discussed in more detail below. From a theoretical point of view, the P450 core chemistry is larger and more dispersed in the active site than that of MMO, ren...