Harder, better, faster, stronger: Large-scale QM and QM/MM for predictive modeling in enzymes and proteins.

Computational prediction of enzyme mechanism and protein function requires accurate physics-based models and suitable sampling. We discuss recent advances in large-scale quantum mechanical (QM) modeling of biochemical systems that have reduced the cost of high-accuracy models. Tradeoffs between sampling and accuracy have motivated modeling with molecular mechanics (MM) in a multiscale QM/MM or iterative approach. Limitations to both conventional density-functional theory and classical MM force fields remain for describing noncovalent interactions in comparison to experiment or wavefunction theory. Because predictions of enzyme action (i.e. electrostatics), free energy barriers, and mechanisms are sensitive to the protocol and embedding method in QM/MM, convergence tests and systematic methods for quantifying QM-level interactions are a needed, active area of development.

Quantum-Mechanical/Molecular-Mechanical (QM/MM) Simulations for Understanding Enzyme Dynamics.

Quantum mechanics/molecular mechanics (QM/MM) methods have become widely used for computational modeling of enzyme structure and mechanism. In these approaches, a portion of the enzyme of great interest (e.g., where a chemical reaction is occurring) is treated with QM, whereas the surrounding region is treated with MM. A critical challenge with these methods is the choice of the region to partition into QM and which to treat with MM along with numerous practical choices that must be made at each step of the modeling procedure. Here, we attempt to simplify this process by describing the steps involved in preparing protein structures, choosing the appropriate QM region size and electronic structure methods, preparing all necessary input files, and troubleshooting common errors for QM/MM simulations of enzymes.

Biochemical and crystallographic investigations into isonitrile formation by a nonheme iron-dependent oxidase/decarboxylase.

The isonitrile moiety is found in marine sponges and some microbes, where it plays a role in processes such as virulence and metal acquisition. Until recently only one route was known for isonitrile biosynthesis, a condensation reaction that brings together a nitrogen atom of l-Trp/l-Tyr with a carbon atom from ribulose-5-phosphate. With the discovery of ScoE, a mononuclear Fe(II) α-ketoglutarate-dependent dioxygenase from Streptomyces coeruleorubidus, a second route was identified. ScoE forms isonitrile from a glycine adduct, with both the nitrogen and carbon atoms coming from the same glycyl moiety. This reaction is part of the nonribosomal biosynthetic pathway of isonitrile lipopeptides. Here, we present structural, biochemical, and computational investigations of the mechanism of isonitrile formation by ScoE, an unprecedented reaction in the mononuclear Fe(II) α-ketoglutarate-dependent dioxygenase superfamily. The stoichiometry of this enzymatic reaction is measured, and multiple high-resolution (1.45-1.96 Å resolution) crystal structures of Fe(II)-bound ScoE are presented, providing insight into the binding of substrate, (R)-3-((carboxylmethyl)amino)butanoic acid (CABA), cosubstrate α-ketoglutarate, and an Fe(IV)=O mimic oxovanadium. Comparison to a previously published crystal structure of ScoE suggests that ScoE has an "inducible" α-ketoglutarate binding site, in which two residues arginine-157 and histidine-299 move by approximately 10 Å from the surface of the protein into the active site to create a transient α-ketoglutarate binding pocket. Together, data from structural analyses, site-directed mutagenesis, and computation provide insight into the mode of α-ketoglutarate binding, the mechanism of isonitrile formation, and how the structure of ScoE has been adapted to perform this unusual chemical reaction.

When are two hydrogen bonds better than one? Accurate first-principles models explain the balance of hydrogen bond donors and acceptors found in proteins.

Hydrogen bonds (HBs) play an essential role in the structure and catalytic action of enzymes, but a complete understanding of HBs in proteins challenges the resolution of modern structural (i.e., X-ray diffraction) techniques and mandates computationally demanding electronic structure methods from correlated wavefunction theory for predictive accuracy. Numerous amino acid sidechains contain functional groups (e.g., hydroxyls in Ser/Thr or Tyr and amides in Asn/Gln) that can act as either HB acceptors or donors (HBA/HBD) and even form simultaneous, ambifunctional HB interactions. To understand the relative energetic benefit of each interaction, we characterize the potential energy surfaces of representative model systems with accurate coupled cluster theory calculations. To reveal the relationship of these energetics to the balance of these interactions in proteins, we curate a set of 4000 HBs, of which >500 are ambifunctional HBs, in high-resolution protein structures. We show that our model systems accurately predict the favored HB structural properties. Differences are apparent in HBA/HBD preference for aromatic Tyr versus aliphatic Ser/Thr hydroxyls because Tyr forms significantly stronger O-H⋯O HBs than N-H⋯O HBs in contrast to comparable strengths of the two for Ser/Thr. Despite this residue-specific distinction, all models of residue pairs indicate an energetic benefit for simultaneous HBA and HBD interactions in an ambifunctional HB. Although the stabilization is less than the additive maximum due both to geometric constraints and many-body electronic effects, a wide range of ambifunctional HB geometries are more favorable than any single HB interaction.

Both Configuration and QM Region Size Matter: Zinc Stability in QM/MM Models of DNA Methyltransferase.

Quantum-mechanical/molecular-mechanical (QM/MM) methods are essential to the study of metalloproteins, but the relative importance of sampling and degree of QM treatment in achieving quantitative predictions is poorly understood. We study the relative magnitude of configurational and QM-region sensitivity of energetic and electronic properties in a representative Zn2+ metal binding site of a DNA methyltransferase. To quantify property variations, we analyze snapshots extracted from 250 ns of molecular dynamics simulation. To understand the degree of QM-region sensitivity, we perform analysis using QM regions ranging from a minimal 49-atom region consisting only of the Zn2+ metal and its four coordinating Cys residues up to a 628-atom QM region that includes residues within 12 Å of the metal center. Over the configurations sampled, we observe that illustrative properties (e.g., rigid Zn2+ removal energy) exhibit large fluctuations that are well captured with even minimal QM regions. Nevertheless, for both energetic and electronic properties, we observe a slow approach to asymptotic limits with similarly large changes in absolute values that converge only with larger (ca. 300-atom) QM region sizes. For the smaller QM regions, the electronic description of Zn2+ binding is incomplete: the metal binds too tightly and is too stabilized by the strong electrostatic potential of MM point charges, and the Zn-S bond covalency is overestimated. Overall, this work suggests that efficient sampling with QM/MM in small QM regions is an effective method to explore the influence of enzyme structure on target properties. At the same time, accurate descriptions of electronic and energetic properties require a larger QM region than the minimal metal-coordinating residues in order to converge treatment of both metal-local bonding and the overall electrostatic environment.

Revealing quantum mechanical effects in enzyme catalysis with large-scale electronic structure simulation.

Enzymes have evolved to facilitate challenging reactions at ambient conditions with specificity seldom matched by other catalysts. Computational modeling provides valuable insight into catalytic mechanism, and the large size of enzymes mandates multi-scale, quantum mechanical-molecular mechanical (QM/MM) simulations. Although QM/MM plays an essential role in balancing simulation cost to enable sampling with full QM treatment needed to understand electronic structure in enzyme active sites, the relative importance of these two strategies for understanding enzyme mechanism is not well known. We explore challenges in QM/MM for studying the reactivity and stability of three diverse enzymes: i) Mg2+-dependent catechol O-methyltransferase (COMT), ii) radical enzyme choline trimethylamine lyase (CutC), and iii) DNA methyltransferase (DNMT1), which has structural Zn2+ binding sites. In COMT, strong non-covalent interactions lead to long range coupling of electronic structure properties across the active site, but the more isolated nature of the metallocofactor in DNMT1 leads to faster convergence of some properties. We quantify these effects in COMT by computing covariance matrices of by-residue electronic structure properties during dynamics and along the reaction coordinate. In CutC, we observe spontaneous bond cleavage following initiation events, highlighting the importance of sampling and dynamics. We use electronic structure analysis to quantify the relative importance of CHO and OHO non-covalent interactions in imparting reactivity. These three diverse cases enable us to provide some general recommendations regarding QM/MM simulation of enzymes.