Hydration free energies in the FreeSolv database calculated with polarized iterative Hirshfeld charges

Computer simulations of biomolecular systems often use force fields, which are combinations of simple empirical atom-based functions to describe the molecular interactions. Even though polarizable force fields give a more detailed description of intermolecular interactions, nonpolarizable force fields, developed several decades ago, are often still preferred because of their reduced computation cost. Electrostatic interactions play a major role in biomolecular systems and are therein described by atomic point charges. In this work, we address the performance of different atomic charges to reproduce experimental hydration free energies in the FreeSolv database in combination with the GAFF force field. Atomic charges were calculated by two atoms-in-molecules approaches, Hirshfeld-I and Minimal Basis Iterative Stockholder (MBIS). To account for polarization effects, the charges were derived from the solute’s electron density computed with an implicit solvent model, and the energy required to polarize the solute was added to the free energy cycle. The calculated hydration free energies were analyzed with an error model, revealing systematic errors associated with specific functional groups or chemical elements. The best agreement with the experimental data is observed for the AM1-BCC and the MBIS atomic charge methods. The latter includes the solvent polarization and presents a root-mean-square error of 2.0 kcal mol–1 for the 613 organic molecules studied. The largest deviation was observed for phosphorus-containing molecules and the molecules with amide, ester and amine functional groups

Systematic Quantum Mechanical Region Determination in QM/MM Simulation

Hybrid quantum mechanical-molecular mechanical (QM/MM) simulations are widely used in enzyme simulation. Over ten convergence studies of QM/MM methods have revealed over the past several years that key energetic and structural properties approach asymptotic limits with only very large (ca. 500-1000 atom) QM regions. This slow convergence has been observed to be due in part to significant charge transfer between the core active site and surrounding protein environment, which cannot be addressed by improvement of MM force fields or the embedding method employed within QM/MM. Given this slow convergence, it becomes essential to identify strategies for the most atom-economical determination of optimal QM regions and to gain insight into the crucial interactions captured only in large QM regions. Here, we extend and develop two methods for quantitative determination of QM regions. First, in the charge shift analysis (CSA) method, we probe the reorganization of electron density when core active site residues are removed completely, as determined by large-QM region QM/MM calculations. Second, we introduce the highly-parallelizable Fukui shift analysis (FSA), which identifies how core/substrate frontier states are altered by the presence of an additional QM residue on smaller initial QM regions. We demonstrate that the FSA and CSA approaches are complementary and consistent on three test case enzymes: catechol O-methyltransferase, cytochrome P450cam, and hen eggwhite lysozyme. We also introduce validation strategies and test sensitivities of the two methods to geometric structure, basis set size, and electronic structure methodology. Both methods represent promising approaches for the systematic, unbiased determination of quantum mechanical effects in enzymes and large systems that necessitate multi-scale modeling.Comment: 44 pages, 13 figures, submitte

Radical Stabilization Energies for Enzyme Engineering: Tackling the Substrate Scope of the Radical Enzyme QueE

© 2019 American Chemical Society. Experimental assessment of catalytic reaction mechanisms and profiles of radical enzymes can be severely challenging due to the reactive nature of the intermediates and sensitivity of cofactors such as iron-sulfur clusters. Here, we present an enzyme-directed computational methodology for the assessment of thermodynamic reaction profiles and screening for radical stabilization energies (RSEs) for the assessment of catalytic turnovers in radical enzymes. We have applied this new screening method to the radical S-adenosylmethione enzyme 7-carboxy-7-deazaguanine synthase (QueE), following a detailed molecular dynamics (MD) analysis that clarifies the role of both specific enzyme residues and bound Mg2+, Ca2+, or Na+. The MD simulations provided the basis for a statistical approach to sample different conformational outcomes. RSE calculation at the M06-2X/6-31+G∗ level of theory provided the most computationally cost-effective assessment of enzyme-based energies, facilitated by an initial triage using semiempirical methods. The impact of intermolecular interactions on RSE was clearly established, and application to the assessment of potential alternative substrates (focusing on radical clock type rearrangements) proposes a selection of carbon-substituted analogues that would react to afford cyclopropylcarbinyl radical intermediates as candidates for catalytic turnover by QueE

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 the 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) Mg[supercript 2+]-dependent catechol O-methyltransferase (COMT), ii) radical enzyme choline trimethylamine lyase (CutC), and iii) DNA methyltransferase (DNMT1), which has structural Zn[superscript 2+] 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.NEC CorporationNational Institute of Environmental Health Sciences (Grant P30-ES002109)Burroughs Wellcome Fund (Career Award at the Scientific Interface)United States. Department of Energy (Computational Science Graduate Fellowship

Activation of Glycyl Radical Enzymes─Multiscale Modeling Insights into Catalysis and Radical Control in a Pyruvate Formate-Lyase-Activating Enzyme

Pyruvate formate-lyase (PFL) is a glycyl radical enzyme (GRE) playing a pivotal role in the metabolism of strict and facultative anaerobes. Its activation is carried out by a PFL-activating enzyme, a member of the radical S-adenosylmethionine (rSAM) superfamily of metalloenzymes, which introduces a glycyl radical into the Gly radical domain of PFL. The activation mechanism is still not fully understood and is structurally based on a complex with a short model peptide of PFL. Here, we present extensive molecular dynamics simulations in combination with quantum mechanics/molecular mechanics (QM/MM)-based kinetic and thermodynamic reaction evaluations of a more complete activation model comprising the 49 amino acid long C-terminus region of PFL. We reveal the benefits and pitfalls of the current activation model, providing evidence that the bound peptide conformation does not resemble the bound protein-protein complex conformation with PFL, with implications for the activation process. Substitution of the central glycine with (S)- and (R)-alanine showed excellent binding of (R)-alanine over unstable binding of (S)-alanine. Radical stabilization calculations indicate that a higher radical stability of the glycyl radical might not be the sole origin of the evolutionary development of GREs. QM/MM-derived radical formation kinetics further demonstrate feasible activation barriers for both peptide and C-terminus activation, demonstrating why the crystalized model peptide system is an excellent inhibitory system for natural activation. This new evidence supports the theory that GREs converged on glycyl radical formation due to the better conformational accessibility of the glycine radical loop, rather than the highest radical stability of the formed peptide radicals

Extending the Scope of the Density Overlap Region Indicator

In this thesis, original applications of the Density Overlap Region Indicator (DORI), a density dependent bonding descriptor capable of simultaneously capturing covalent and noncovalent interactions, are discussed. The use of scalar fields, such as DORI, were generally restricted to visualizing bonding situations in static gas phase molecules. Here, DORI is pushed out of its comfort zone and used to probe systems prone to electronic and geometric fluctuations, or those constrained by their condensed phase environments. The applications to challenging chemical systems highlighted within demonstrate the capabilities of DORI as a formidable tool that can be beneficial in many facets of chemistry. Molecules in the excited state are difficult to analyze using popular bonding descriptors, primarily because the required information (orbitals) are not given by standard computational methodologies. DORI, which relies exclusively on the electron density and its derivatives, overcomes previous limitations and permits the characterization of excitation processes (charge transfer, excimer, Rydberg, ...) through visual and numerical signatures. Using DORI, the evolution of covalent and non-covalent excited state interactions where used to rationalize photoemission in BODIPY-derivatives. Certain BODIPY substituents formnon-covalent intramolecular interactions in the excited state, which are crucial for stabilizing the Sx - S0 intersection and prompting nonradiative decay. This application demonstrates that DORI is ideally suited for characterizing excited state phenomena. Dynamical fluctuations represent another domain beyond the standard usage of bonding descriptors. Highly fluxionalmolecules, such as molecular machines or proteins, have complex multi-dimensional conformational spaces that are generally explored using a handful of geometrical collective variables (bond lengths, angles, etc.), or dimensionality reduction algorithms. DORIâs covalent and non-covalent patterns are exploited as alternative sets of descriptors, which are simpler than geometrical parameters because electronic and geometrical fluctuations can be captured by a single-dimensional variable. DORI is also synergistically used alongside dimensionality reduction algorithms to reveal enhanced descriptions of the conformational spaces of a molecular rotor and a photoswitch. Thus, cost effective bonding descriptors are well adapted and beneficial in analyzing electronic and geometrical fluctuations requiring extended mapping of conformational spaces. Finally, DORI allows for simultaneous visualization of covalent and non-covalent interactions, and is thus particularly suited to investigate their interplay, notably present in dense environments of high-pressure crystals and in protein-ligand cavities. Using actual experimental electron densities of an organic crystal, DORI exposes pressure-induced disruptions of intramolecular delocalization and identifies the directional non-covalent interactions that cause these perturbations. Similarly, the scalar field pinpoints the specific non-covalent proteinligand interactions which modify the covalent regions of the ligand and facilitate the reactive process. Overall, the examples presented in this thesis demonstrate the versatility of DORI in translating complex chemical behavior into intuitive representations, greatly extending the range of applications that benefit from visual bonding descriptors