Can the local electric field be a descriptor of catalytic activity? A case study on chorismate mutase

Exploration of biochemical reactivity with a QM/MM growing string method

In this work, we have implemented the single-ended growing string method using a hybrid internal/Cartesian coordinate scheme within our in-house QM/MM package, QoMMMa, representing the first implementation of the growing string method in the QM/MM framework. The goal of the implementation was to facilitate generation of QM/MM reaction pathways with minimal user input, and also to improve the quality of the pathways generated as compared to the widely used adiabatic mapping approach. We have validated the algorithm against a reaction which has been studied extensively in previous computational investigations - the Claisen rearrangement catalysed by chorismate mutase. The nature of the transition state and the height of the barrier was predicted well using our algorithm, where more than 88% of the pathways generated were deemed to be of production quality. Directly compared to using adiabatic mapping, we found that while our QM/MM single-ended growing string method is slightly less efficient, it readily produces reaction pathways with fewer discontinuites and thus minimises the need for involved remapping of unsatisfactory energy profiles.

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.

A porphyrin-based molecular cage guided by designed local-electric field is highly selective and efficient

The present work outlines a general methodology for designing efficient catalytic machineries that can easily be tweaked to meet the demands of the target reactions. This work utilizes a principle of the designed local electric field (LEF) as the driver for an efficient catalyst. It is demonstrated that by tweaking the LEF, we can catalyze the desired hydroxylation products with enantioselectivity that can be changed at will. Using computation tools, we caged a synthetic analog of heme porphyrin (HM1) and investigated the pharmaceutically relevant conversion of tetralin to tetralol, inside the modified supramolecular cage. The QM/MM calculations demonstrate a resulting catalytic efficiency with virtually absolute R-selectivity for the tetralin hydroxylation. Our calculations show that the LEF of the supramolecular cage and HM1 exert a strong electric field along the Fe-O reaction axis, which is the main driving force for enhanced reactivity. At the same time, the supramolecular cage applies a lateral LEF that regulates the enantioselectivity. We further demonstrate that swapping the charged/polar substitution in the supramolecular cage switches the lateral LEF which changes the enantioselectivity of hydroxylation from R to S.

Multiscale QM/MM modelling of catalytic systems with ChemShell

Hybrid quantum mechanical/molecular mechanical (QM/MM) methods are a powerful computational tool for the investigation of all forms of catalysis, as they allow for an accurate description of reactions occurring at catalytic sites in the context of a complicated electrostatic environment. The scriptable computational chemistry environment ChemShell is a leading software package for QM/MM calculations, providing a flexible, high performance framework for modelling both biomolecular and materials catalysis. We present an overview of recent applications of ChemShell to problems in catalysis and review new functionality introduced into the redeveloped Python-based version of ChemShell to support catalytic modelling. These include a fully guided workflow for biomolecular QM/MM modelling, starting from an experimental structure, a periodic QM/MM embedding scheme to support modelling of metallic materials, and a comprehensive set of tutorials for biomolecular and materials modelling.

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.

Evaluating the active site-substrate interplay between x-ray crystal structure and molecular dynamics in chorismate mutase

Designing realistic quantum mechanical (QM) models of enzymes is dependent on reliably discerning and modeling residues, solvents, and cofactors important in crafting the active site microenvironment. Interatomic van der Waals contacts have previously demonstrated usefulness toward designing QM-models, but their measured values (and subsequent residue importance rankings) are expected to be influenceable by subtle changes in protein structure. Using chorismate mutase as a case study, this work examines the differences in ligand-residue interatomic contacts between an x-ray crystal structure and structures from a molecular dynamics simulation. Select structures are further analyzed using symmetry adapted perturbation theory to compute ab initio ligand-residue interaction energies. The findings of this study show that ligand-residue interatomic contacts measured for an x-ray crystal structure are not predictive of active site contacts from a sampling of molecular dynamics frames. In addition, the variability in interatomic contacts among structures is not correlated with variability in interaction energies. However, the results spotlight using interaction energies to characterize and rank residue importance in future computational enzymology workflows.

The Performance of Different Water Models on the Structure and Function of Cytochrome P450 Enzymes

Modeling approaches and modern simulations to investigate the biomolecular structure and function rely on various methods. Since water molecules play a crucial role in all sorts of chemistry, the accurate modeling of water molecules is vital for such simulations. In cytochrome P450 (CYP450), in particular, water molecules play a key role in forming active oxidant that ultimately performs oxidation and metabolism. In the present study, we have highlighted the behavior of the three most widely used water models─TIP3P, SPC/E, and OPC─for three different CYP450 enzymes─CYP450_BM3, CYP450_OleT, and CYP450_BSβ─during MD simulations and QM/MM calculations. We studied the various properties, such as RMSD, RMSF, H-bond, water occupancy, and hydrogen atom transfer (HAT), using QM/MM calculations and compared them for all three water models. Our study shows that the stabilities of the enzyme complexes are well maintained in all three water models. However, the OPC water model performs well for the polar active sites, that is, in CYP450_OleT and CYP450_BSβ, while the TIP3P water model is superior for the hydrophobic site, such as CYP450_BM3.

Local Electric Fields: From Enzyme Catalysis to Synthetic Catalyst Design

This Mini-Review Article outlines recent advances in the study of local electric field (LEF) governed enzyme catalysis and the application of the LEF principle in synthetic catalyst design. We start by discussing the electrostatics principles that drive enzyme catalysis, and its experimental verifications through vibrational Stark spectroscopy. Subsequently, we describe aspects of LEFs other than catalysis, i.e., induction of mechanistic crossovers, among others. Here, we focus on the early work done using computational tools, along with some recent contributions. Following an in-depth discussion of the role of LEFs in enzyme catalysis, we then highlight some recent works on designed local electric fields (D-LEF) and their applications in organic synthesis. Subsequently, we turn to D-LEFs in synthetic enzymes and supramolecular systems (cf. the work by the Head-Gordon group). We end by discussing some of the software packages that have been developed to analyze local electric fields computationally. Overall, the present Mini-Review Article paints an insightful picture of the current state of the art using LEF in enzyme catalysis and its application for further bioengineering and synthetic organic frameworks in a broad perspective.

Unraveling key interactions and the mechanism of demethylation during hAGT-mediated DNA repair via simulations

Alkylating agents pose the biggest threat to the genomic integrity of cells by damaging DNA bases through regular alkylation. Such damages are repaired by several automated types of machinery inside the cell. O6-alkylguanine-DNA alkyltransferase (AGT) is an enzyme that performs the direct repair of an alkylated guanine base by transferring the alkyl group to a cysteine residue. In the present study, using extensive MD simulations and hybrid QM/MM calculations, we have investigated the key interactions between the DNA lesion and the hAGT enzyme and elucidated the mechanisms of the demethylation of the guanine base. Our simulation shows that the DNA lesion is electrostatically stabilized by the enzyme and the Arg135 of hAGT enzyme provides the main driving force to flip the damaged base into the enzyme. The QM/MM calculations show demethylation of the damaged base as a three-step process in a thermodynamically feasible and irreversible manner. Our calculations show that the final product forms via Tyr114 in a facile way in contrast to the previously proposed Lys-mediated route.