Catalytic Fields as a Tool to Analyze Enzyme Reaction Mechanism Variants and Reaction Steps

Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development

Understanding enzyme mechanisms is essential for unraveling the complex molecular machinery of life. In this review, we survey the field of computational enzymology, highlighting key principles governing enzyme mechanisms and discussing ongoing challenges and promising advances. Over the years, computer simulations have become indispensable in the study of enzyme mechanisms, with the integration of experimental and computational exploration now established as a holistic approach to gain deep insights into enzymatic catalysis. Numerous studies have demonstrated the power of computer simulations in characterizing reaction pathways, transition states, substrate selectivity, product distribution, and dynamic conformational changes for various enzymes. Nevertheless, significant challenges remain in investigating the mechanisms of complex multistep reactions, large-scale conformational changes, and allosteric regulation. Beyond mechanistic studies, computational enzyme modeling has emerged as an essential tool for computer-aided enzyme design and the rational discovery of covalent drugs for targeted therapies. Overall, enzyme design/engineering and covalent drug development can greatly benefit from our understanding of the detailed mechanisms of enzymes, such as protein dynamics, entropy contributions, and allostery, as revealed by computational studies. Such a convergence of different research approaches is expected to continue, creating synergies in enzyme research. This review, by outlining the ever-expanding field of enzyme research, aims to provide guidance for future research directions and facilitate new developments in this important and evolving field.

Designed Local Electric Fields-Promising Tools for Enzyme Engineering

Designing efficient catalysts is one of the ultimate goals of chemists. In this Perspective, we discuss how local electric fields (LEFs) can be exploited to improve the catalytic performance of supramolecular catalysts, such as enzymes. More specifically, this Perspective starts by laying out the fundamentals of how local electric fields affect chemical reactivity and review the computational tools available to study electric fields in various settings. Subsequently, the advances made so far in optimizing enzymatic electric fields through targeted mutations are discussed critically and concisely. The Perspective ends with an outlook on some anticipated evolutions of the field in the near future. Among others, we offer some pointers on how the recent data science/machine learning revolution, engulfing all science disciplines, could potentially provide robust and principled tools to facilitate rapid inference of electric field effects, as well as the translation between optimal electrostatic environments and corresponding chemical modifications.

Free Energy Profile Decomposition Analysis for QM/MM Simulations of Enzymatic Reactions

In enzyme mechanistic studies and mutant design, it is highly desirable to know the individual residue contributions to the reaction free energy and barrier. In this work, we show that such free energy contributions from each residue can be readily obtained by postprocessing ab initio quantum mechanical molecular mechanical (ai-QM/MM) free energy simulation trajectories. Specifically, through a mean force integration along the minimum free energy pathway, one can obtain the electrostatic, polarization, and van der Waals contributions from each residue to the free energy barrier. Separately, a similar analysis procedure allows us to assess the contribution from different collective variables along the reaction coordinate. The chorismate mutase reaction is used to demonstrate the utilization of these two trajectory analysis tools.

Evaluating the Transition State Stabilization/Destabilization Effects of the Electric Fields from Scaffold Residues by a QM/MM Approach

The protein scaffolds of enzymes not only provide structural support for the catalytic center but also exert preorganized electric fields for electrostatic catalysis. In recent years, uniform oriented external electric fields (OEEFs) have been widely applied to enzymatic reactions to mimic the electrostatic effects of the environment. However, the electric fields exerted by individual residues in proteins may be quite heterogeneous across the active site, with varying directions and strengths at different positions of the active site. Here, we propose a QM/MM-based approach to evaluate the effects of the electric fields exerted by individual residues in the protein scaffold. In particular, the heterogeneity of the residue electric fields and the effect of the native protein environment can be properly accounted for by this QM/MM approach. A case study of the O-O heterolysis reaction in the catalytic cycle of TyrH shows that (1) for scaffold residues that are relatively far from the active site, the heterogeneity of the residue electric field in the active site is not very significant and the electrostatic stabilization/destabilization due to each residue can be well approximated with the interaction energy between a uniform electric field and the QM region dipole; (2) for scaffold residues near the active site, the residue electric fields can be highly heterogeneous along the breaking O-O bond. In such a case, approximating the residue electric fields as uniform fields may misrepresent the overall electrostatic effect of the residue. The present QM/MM approach can be applied to evaluate the residues' electrostatic impact on enzymatic reactions, which also can be useful in computational optimization of electric fields to boost the enzyme catalysis.

A Multiple Proton Transfer Mechanism for the Charging Step of the Aminoacylation Reaction at the Active Site of Aspartyl tRNA Synthetase

Aspartyl-tRNA synthetase catalyzes the attachment of aspartic acid to its cognate tRNA by the aminoacylation reaction during the initiation of the protein biosynthesis process. In the second step of the aminoacylation reaction, known as the charging step, the aspartate moiety is transferred from aspartyl-adenylate to the 3'-OH of A76 of tRNA through a proton transfer process. We have investigated different pathways for the charging step through three separate QM/MM simulations combined with the enhanced sampling method of well-sliced metadynamics and found out the most feasible pathway for the reaction at the active site of the enzyme. In the charging reaction, both the phosphate group and the ammonium group after deprotonation can potentially act as a base for proton transfer in the substrate-assisted mechanism. We have considered three possible mechanisms involving different pathways of proton transfer, and only one of them is determined to be enzymatically feasible. The free energy landscape along reaction coordinates where the phosphate group acts as the general base showed that, in the absence of water, the barrier height is 52.6 kcal/mol. The free energy barrier is reduced to 39.7 kcal/mol when the active site water molecules are also treated quantum mechanically, thus allowing a water mediated proton transfer. The charging reaction involving the ammonium group of the aspartyl adenylate is found to follow a path where first a proton from the ammonium group moves to a water in the vicinity forming a hydronium ion (H₃O⁺) and NH₂ group. The hydronium ion subsequently passes the proton to the Asp233 residue, thus minimizing the chance of back proton transfer from hydronium to the NH₂ group. The neutral NH₂ group subsequently takes the proton from the O3' of A76 with a free energy barrier of 10.7 kcal/mol. In the next step, the deprotonated O3' makes a nucleophilic attack to the carbonyl carbon forming a tetrahedral transition state with a free energy barrier of 24.8 kcal/mol. Thus, the present work shows that the charging step proceeds through a multiple proton transfer mechanism where the amino group formed after deprotonation acts as the base to capture a proton from O3' of A76 rather than the phosphate group. The current study also shows the important role played by Asp233 in the proton transfer process.