Towards the Accurate Thermodynamic Characterization of Enzyme Reaction Mechanisms

Kinetic View of Enzyme Catalysis from Enhanced Sampling QM/MM Simulations

The rate constants of enzyme-catalyzed reactions (kcat) are often approximated from the barrier height of the reactive step. We introduce an enhanced sampling QM/MM approach that directly calculates the kinetics of enzymatic reactions, without introducing the transition-state theory assumptions, and takes into account the dynamical equilibrium between the reactive and non-reactive conformations of the enzyme/substrate complex. Our computed kcat values are in order-of-magnitude agreement with the experimental data for two representative enzymatic reactions.

Impacts of QM region sizes and conformation numbers on modelling enzyme reactions: a case study of polyethylene terephthalate hydrolase

A quantum mechanics/molecular mechanics (QM/MM) approach is a broadly used tool in computational enzymology. Treating the QM region with a high-level DFT method is one of the important branches. Here, taking leaf-branch compost cutinase-catalyzed polyethylene terephthalate depolymerization as an example, the convergence behavior of energy barriers as well as key structural and charge features with respect to the size of the QM region (up to 1000 atoms) is systematically investigated. BP86/6-31G(d)//CHARMM and M06-2X/6-311G(d,p)//CHARMM level of theories were applied for geometry optimizations and single-point energy calculations, respectively. Six independent enzyme conformations for all the four catalytic steps (steps (i)-(iv)) were considered. Most of the twenty-four cases show that at least 500 QM atoms are needed while only two rare cases show that ∼100 QM atoms are sufficient for convergence when only a single conformation was considered. This explains why most previous studies showed that 500 or more QM atoms are required while a few others showed that ∼100 QM atoms are sufficient for DFT/MM calculations. More importantly, average energy barriers and key structural/charge features from six conformations show an accelerated convergence than that in a single conformation. For instance, to reach energy barrier convergence (within 2.0 kcal mol-1) for step (ii), only ∼100 QM atoms are required if six conformations are considered while 500 or more QM atoms are needed with a single conformation. The convergence is accelerated to be more rapid if hundreds and thousands of conformations were considered, which aligns with previous findings that only several dozens of QM atoms are required for convergence with semi-empirical QM/MM MD simulations.

Deciphering the Catalytic Mechanism of Virginiamycin B Lyase with Multiscale Methods and Molecular Dynamics Simulations

Due to the emergence of antibiotic resistance, the need to explore novel antibiotics and/or novel strategies to counter antibiotic resistance is of utmost importance. In this work, we explored the molecular and mechanistic details of the degradation of a streptogramin B antibiotic by virginiamycin B (Vgb) lyase of Staphylococcus aureus using classical molecular dynamics simulations and multiscale quantum mechanics/molecular mechanics methods. Our results were in line with available experimental kinetic information. Although we were able to identify a stepwise mechanism, in the wild-type enzyme, the intermediate is short-lived, showing a small barrier to decay to the product state. The impact of point mutations on the reaction was also assessed, showing not only the importance of active site residues to the reaction catalyzed by Vgb lyase but also of near positive and negative residues surrounding the active site. Using molecular dynamics simulations, we also predicted the most likely protonation state of the 3-hydroxypicolinic moiety of the antibiotic and the impact of mutants on antibiotic binding. All this information will expand our understanding of linearization reactions of cyclic antibiotics, which are crucial for the development of novel strategies that aim to tackle antibiotic resistance.

Unraveling the Reaction Mechanism of Russell's Viper Venom Factor X Activator: A Paradigm for the Reactivity of Zinc Metalloproteinases?

Snake venom metalloproteinases (SVMPs) are important drug targets against snakebite envenoming, the neglected tropical disease with the highest mortality worldwide. Here, we focus on Russell's viper (Daboia russelii), one of the "big four" snakes of the Indian subcontinent that, together, are responsible for ca. 50,000 fatalities annually. The "Russell's viper venom factor X activator" (RVV-X), a highly toxic metalloproteinase, activates the blood coagulation factor X (FX), leading to the prey's abnormal blood clotting and death. Given its tremendous public health impact, the WHO recognized an urgent need to develop efficient, heat-stable, and affordable-for-all small-molecule inhibitors, for which a deep understanding of the mechanisms of action of snake's principal toxins is fundamental. In this study, we determine the catalytic mechanism of RVV-X by using a density functional theory/molecular mechanics (DFT:MM) methodology to calculate its free energy profile. The results showed that the catalytic process takes place via two steps. The first step involves a nucleophilic attack by an in situ generated hydroxide ion on the substrate carbonyl, yielding an activation barrier of 17.7 kcal·mol^-1, while the second step corresponds to protonation of the peptide nitrogen and peptide bond cleavage with an energy barrier of 23.1 kcal·mol^-1. Our study shows a unique role played by Zn²⁺ in catalysis by lowering the pK_a of the Zn²⁺-bound water molecule, enough to permit the swift formation of the hydroxide nucleophile through barrierless deprotonation by the formally much less basic Glu140. Without the Zn²⁺ cofactor, this step would be rate-limiting.

Engineering DszC Mutants from Transition State Macrodipole Considerations and Evolutionary Sequence Analysis

We describe an approach to identify enzyme mutants with increased turnover using the enzyme DszC as a case study. Our approach is based on recalculating the barriers of alanine mutants through single-point energy calculations at the hybrid QM/MM level in the wild-type reactant and transition state geometries. We analyze the difference in the electron density between the reactant and transition state to identify sites/residues where electrostatic interactions stabilize the transition state over the reactants. We also assess the insertion of a unit probe charge to identify positions in which the introduction of charged residues lowers the barrier.

Transmembrane Protease Serine 2 Proteolytic Cleavage of the SARS-CoV-2 Spike Protein: A Mechanistic Quantum Mechanics/Molecular Mechanics Study to Inspire the Design of New Drugs To Fight the COVID-19 Pandemic

Despite the development of vaccines against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, there is an urgent need for efficient drugs to treat infected patients. An attractive drug target is the human transmembrane protease serine 2 (TMPRSS2) because of its vital role in the viral infection mechanism of SARS-CoV-2 by activation of the virus spike protein (S protein). Having in mind that the information derived from quantum mechanics/molecular mechanics (QM/MM) studies could be an important tool in the design of transition-state (TS) analogue inhibitors, we resorted to adiabatic QM/MM calculations to determine the mechanism of the first step (acylation) of proteolytic cleavage of the S protein with atomistic details. Acylation occurred in two stages: (i) proton transfer from Ser441 to His296 concerted with the nucleophilic attack of Ser441 to the substrate's P1-Arg and (ii) proton transfer from His296 to the P1'-Ser residue concerted with the cleavage of the ArgP1-SerP1' peptide bond, with a Gibbs activation energy of 17.1 and 15.8 kcal mol^-1, relative to the reactant. An oxyanion hole composed of two hydrogen bonds stabilized the rate-limiting TS by 8 kcal mol^-1. An analysis of the TMPRSS2 interactions with the high-energy, short-lived tetrahedral intermediate highlighted the limitations of current clinical inhibitors and pointed out specific ways to develop higher-affinity TS analogue inhibitors. The results support the development of more efficient drugs against SARS-CoV-2 using a human target, free from resistance development.