Benchmarking Density Functional Theory Methods for Metalloenzyme Reactions: The Introduction of the MME55 Set

We present a new benchmark set of metalloenzyme model reaction energies and barrier heights that we call MME55. The set contains 10 different enzymes, representing eight transition metals, both open and closed shell systems, and system sizes of up to 116 atoms. We use four DLPNO-CCSD(T)-based approaches to calculate reference values against which we then benchmark the performance of a range of density functional approximations with and without dispersion corrections. Dispersion corrections improve the results across the board, and triple-ζ basis sets provide the best balance of efficiency and accuracy. Jacob's ladder is reproduced for the whole set based on averaged mean absolute (percent) deviations, with the double hybrids SOS0-PBE0-2-D3(BJ) and revDOD-PBEP86-D4 standing out as the most accurate methods for the MME55 set. The range-separated hybrids ωB97M-V and ωB97X-V also perform well here and can be recommended as a reliable compromise between accuracy and efficiency; they have already been shown to be robust across many other types of chemical problems, as well. Despite the popularity of B3LYP in computational enzymology, it is not a strong performer on our benchmark set, and we discourage its use for enzyme energetics.

The Glycine N-Methyltransferase Case Study: Another Challenge for QM-Cluster Models?

The methyl transfer reaction between SAM and glycine catalyzed by glycine N-methyltransferase (GNMT) was examined using QM-cluster models generated by Residue Interaction Network ResidUe Selector (RINRUS). RINRUS is a Python-based tool that can build QM-cluster models with rules-based processing of the active site residue interaction network. This way of enzyme model-building allows quantitative analysis of residue and fragment contributions to kinetic and thermodynamic properties of the enzyme. Many residue fragments are important for the GNMT catalytic reaction, such as Gly137, Asn138, and Arg175, which interact with the glycine substrate, and Trp30, Asp85, and Tyr242, which interact with the SAM cofactor. Our study shows that active site fragments that interact with the glycine substrate and the SAM cofactor must both be included in the QM-cluster models. Even though the proposed mechanism is a simple one-step reaction, GNMT may be a rather challenging case study for QM-cluster models because convergence in energetics requires models with >350 atoms. "Maximal" QM-cluster models built with either qualitative contact count ranking or quantitative interaction energies from functional group symmetry adapted perturbation theory provide acceptable results. Hence, important residue fragments that contribute to the energetics of the methyl-transfer reaction in GNMT are correctly identified in the RIN. Observations from this work suggest new directions to better establish an effective approach for constructing atomic-level enzyme models.

Benchmarking First-Principles Reaction Equilibrium Composition Prediction

The availability of thermochemical properties allows for the prediction of the equilibrium compositions of chemical reactions. The accurate prediction of these can be crucial for the design of new chemical synthesis routes. However, for new processes, these data are generally not completely available. A solution is the use of thermochemistry calculated from first-principles methods such as Density Functional Theory (DFT). Before this can be used reliably, it needs to be systematically benchmarked. Although various studies have examined the accuracy of DFT from an energetic point of view, few studies have considered its accuracy in predicting the temperature-dependent equilibrium composition. In this work, we collected 117 molecules for which experimental thermochemical data were available. From these, we constructed 2648 reactions. These experimentally constructed reactions were then benchmarked against DFT for 6 exchange-correlation functionals and 3 quality of basis sets. We show that, in reactions that do not show temperature dependence in the equilibrium composition below 1000 K, over 90% are predicted correctly. Temperature-dependent equilibrium compositions typically demonstrate correct qualitative behavior. Lastly, we show that the errors are equally caused by errors in the vibrational spectrum and the DFT electronic ground state energy.

The Essential Role of Water Molecules in the Reaction Mechanism of Protein O-Fucosyltransferase 2

Protein O-fucosyltransferase 2 (PoFUT2) is an inverting glycosyltransferase (GT) that fucosylates thrombospondin repeats (TSRs) from group 1 and 2. PoFUT2 recognizes a large and diverse number of TSRs through a dynamic network of water-mediated interactions. By X-ray structural studies of C. elegans PoFUT2 complexed to a TSR of group 2, we demonstrate that this GT recognizes similarly the 3D structure of TSRs from both groups 1 and 2. Its active site is highly exposed to the solvent, suggesting that water molecules might also play an essential role in the fucosylation mechanism. We applied QM/MM methods using human PoFUT2 as a model, and found that HsPoFUT2 follows a classical S_N 2 reaction mechanism in which water molecules contribute to a great extent in facilitating the release of the leaving pyrophosphate unit, causing the H transfer from the acceptor nucleophile (Thr/Ser) to the catalytic base, which is the last event in the reaction. This demonstrates the importance of water molecules not only in recognition of the ligands but also in catalysis.

Targeted Free Energy Perturbation Revisited: Accurate Free Energies from Mapped Reference Potentials

We present an approach that extends the theory of targeted free energy perturbation (TFEP) to calculate free energy differences and free energy surfaces at an accurate quantum mechanical level of theory from a cheaper reference potential. The convergence is accelerated by a mapping function that increases the overlap between the target and the reference distributions. Building on recent work, we show that this map can be learned with a normalizing flow neural network, without requiring simulations with the expensive target potential but only a small number of single-point calculations, and, crucially, avoiding the systematic error that was found previously. We validate the method by numerically evaluating the free energy difference in a system with a double-well potential and by describing the free energy landscape of a simple chemical reaction in the gas phase.

Mechanistic and thermodynamic characterization of oxathiazolones as potent and selective covalent immunoproteasome inhibitors

The ubiquitin–proteasome system is responsible for the degradation of proteins and plays a critical role in key cellular processes. While the constitutive proteasome (cPS) is expressed in all eukaryotic cells, the immunoproteasome (iPS) is primarily induced during disease processes, and its inhibition is beneficial in the treatment of cancer, autoimmune disorders and neurodegenerative diseases. Oxathiazolones were reported to selectively inhibit iPS over cPS, and the inhibitory activity of several oxathiazolones against iPS was experimentally determined. However, the detailed mechanism of the chemical reaction leading to irreversible iPS inhibition and the key selectivity drivers are unknown, and separate characterization of the noncovalent and covalent inhibition steps is not available for several compounds. Here, we investigate the chemical reaction between oxathiazolones and the Thr1 residue of iPS by quantum mechanics/molecular mechanics (QM/MM) simulations to establish a plausible reaction mechanism and to determine the rate-determining step of covalent complex formation. The modelled binding mode and reaction mechanism are in line with the selective inhibition of iPS versus cPS by oxathiazolones. The k_inact value of several ligands was estimated by constructing the potential of mean force of the rate-determining step by QM/MM simulations coupled with umbrella sampling. The equilibrium constant K_i of the noncovalent complex formation was evaluated by classical force field-based thermodynamic integration. The calculated K_i and k_inact values made it possible to analyse the contribution of the noncovalent and covalent steps to the overall inhibitory activity. Compounds with similar intrinsic reactivities exhibit varying selectivities for iPS versus cPS owing to subtle differences in the binding modes that slightly affect K_i, the noncovalent affinity, and importantly alter k_inact, the covalent reactivity of the bound compounds. A detailed understanding of the inhibitory mechanism of oxathiazolones is useful in designing iPS selective inhibitors with improved drug-like properties.

Catalytic mechanism of the colistin resistance protein MCR-1

The mcr-1 gene encodes a membrane-bound Zn2+-metalloenzyme, MCR-1, which catalyses phosphoethanolamine transfer onto bacterial lipid A, making bacteria resistant to colistin, a last-resort antibiotic. Mechanistic understanding of this process remains incomplete. Here, we investigate possible catalytic pathways using DFT and ab initio calculations on cluster models and identify a complete two-step reaction mechanism. The first step, formation of a covalent phosphointermediate via transfer of phosphoethanolamine from a membrane phospholipid donor to the acceptor Thr285, is rate-limiting and proceeds with a single Zn2+ ion. The second step, transfer of the phosphoethanolamine group to lipid A, requires an additional Zn2+. The calculations suggest the involvement of the Zn2+ orbitals directly in the reaction is limited, with the second Zn2+ acting to bind incoming lipid A and direct phosphoethanolamine addition. The new level of mechanistic detail obtained here, which distinguishes these enzymes from other phosphotransferases, will aid in the development of inhibitors specific to MCR-1 and related bacterial phosphoethanolamine transferases.

Theoretical and Mechanistic Validation of Global Kinetic Parameters of the Inactivation of GABA Aminotransferase by OV329 and CPP-115

((S)-3-Amino-(difluoromethylenyl)cyclopent-1-ene-1-carboxylic acid (OV329) is a recently discovered inactivator of γ-aminobutyric acid aminotransferase (GABA-AT), which has 10 times better inactivation efficiency than its predecessor, CPP-115, despite the only structural difference being an endocyclic double bond in OV329. Both compounds are mechanism-based enzyme inactivators (MBEIs), which inactivate GABA-AT by a similar mechanism. Here, a combination of a variety of computational chemistry tools and experimental methods, including quantum mechanical (QM) calculations, molecular dynamic simulations, progress curve analysis, and deuterium kinetic isotope effect (KIE) experiments, are utilized to comprehensively study the mechanism of inactivation of GABA-AT by CPP-115 and OV329 and account for their experimentally obtained global kinetic parameters k_inact and K_I. Our first key finding is that the rate-limiting step of the inactivation mechanism is the deprotonation step, and according to QM calculations and the KIE experiments, k_inact accurately represents the enhancement of the rate-limiting step for the given mechanism. Second, the present study shows that the widely used simple QM models do not accurately represent the geometric criteria that are present in the enzyme for the deprotonation step. In contrast, QM cluster models successfully represent both the ground state destabilization and the transition state stabilization, as revealed by natural bond orbital analysis. Furthermore, the globally derived K_I values for both of the inactivators represent the inhibitor constants for the initial binding complexes (K_d) and indicate the inactivator competition with the substrate according to progress curve analysis and the observed binding isotope effect. The configurational entropy loss accounts for the difference in K_I values between the inactivators. The approach we describe in this work can be employed to determine the validity of globally derived parameters in the process of MBEI optimization for given inactivation mechanisms.

Electronic structure benchmark calculations of CO2 fixing elementary chemical steps in RuBisCO using the projector-based embedding approach

Ribulose 1,5-bisphosphate carboxylase-oxygenase (RuBisCO) is the main enzyme involved in atmospheric carbon dioxide (CO₂ ) fixation in the biosphere. This enzyme catalyzes a set of five chemical steps that take place in the same active-site within magnesium (II) coordination sphere. Here, a set of electronic structure benchmark calculations have been carried out on a reaction path proposed by Gready et al. by means of the projector-based embedding approach. Activation and reaction energies for all main steps catalyzed by RuBisCO have been calculated at the MP2, SCS-MP2, CCSD, and CCSD(T)/aug-cc-pVDZ and cc-pVDZ levels of theory. The treatment of the magnesium cation with post-HF methods is explored to determine the nature of its involvement in the mechanism. With the high-level ab initio values as a reference, we tested the performance of a set of density functional theory (DFT) exchange-correlation (xc) functionals in reproducing the reaction energetics of RuBisCO carboxylase activity on a set of model fragments. Different DFT xc-functionals show large variation in activation and reaction energies. Activation and reaction energies computed at the B3LYP level are close to the reference SCS-MP2 results for carboxylation, hydration and protonation reactions. However, for the carbon-carbon bond dissociation reaction, B3LYP and other functionals give results that differ significantly from the ab initio reference values. The results show the applicability of the projector-based embedding approach to metalloenzymes. This technique removes the uncertainty associated with the selection of different DFT xc-functionals and so can overcome some of inherent limitations of DFT calculations, complementing, and potentially adding to modeling of enzyme reaction mechanisms with DFT methods.