Evaluating Unexpectedly Short Non-covalent Distances in X-ray Crystal Structures of Proteins with Electronic Structure Analysis.

We investigate unexpectedly short non-covalent distances (<85% of the sum of van der Waals radii) in X-ray crystal structures of proteins. We curate over 11 000 high-quality protein crystal structures and an ultra-high-resolution (1.2 Šor better) subset containing >900 structures. Although our non-covalent distance criterion excludes standard hydrogen bonds known to be essential in protein stability, we observe over 75 000 close contacts (CCs) in the curated protein structures. Analysis of the frequency of amino acids participating in these interactions demonstrates some expected trends (i.e., enrichment of charged Lys, Arg, Asp, and Glu) but also reveals unexpected enhancement of Tyr in such interactions. Nearly all amino acids are observed to form at least one CC with all other amino acids, and most interactions are preserved in the much smaller ultra-high-resolution subset. We quantum-mechanically characterize the interaction energetics of a subset of >5000 CCs with symmetry-adapted perturbation theory to enable decomposition of interactions. We observe the majority of CCs to be favorable. The shortest favorable non-covalent distances are under 2.2 Šand are very repulsive when characterized with classical force fields. This analysis reveals stabilization by a combination of electrostatic and charge-transfer effects between hydrophobic (i.e., Val, Ile, Leu) amino acids and charged Asp or Glu. We also observe a unique hydrogen-bonding configuration between Tyr and Asn/Gln involving both residues acting simultaneously as hydrogen bond donors and acceptors. This work confirms the importance of first-principles simulation in explaining unexpected geometries in protein crystal structures.

Ab Initio Screening Approach for the Discovery of Lignin Polymer Breaking Pathways.

The directed depolymerization of lignin biopolymers is of utmost relevance for the valorization or commercialization of biomass fuels. We present a computational and theoretical screening approach to identify potential cleavage pathways and resulting fragments that are formed during depolymerization of lignin oligomers containing two to six monomers. We have developed a chemical discovery technique to identify the chemically relevant putative fragments in eight known polymeric linkage types of lignin. Obtaining these structures is a crucial precursor to the development of any further kinetic modeling. We have developed this approach by adapting steered molecular dynamics calculations under constant force and varying the points of applied force in the molecule to diversify the screening approach. Key observations include relationships between abundance and breaking frequency, the relative diversity of potential pathways for a given linkage, and the observation that readily cleaved bonds can destabilize adjacent bonds, causing subsequent automatic cleavage.

Water 16-mers and hexamers: assessment of the three-body and electrostatically embedded many-body approximations of the correlation energy or the nonlocal energy as ways to include cooperative effects.

This work presents a new fragment method, the electrostatically embedded many-body expansion of the nonlocal energy (EE-MB-NE), and shows that it, along with the previously proposed electrostatically embedded many-body expansion of the correlation energy (EE-MB-CE), produces accurate results for large systems at the level of CCSD(T) coupled cluster theory. We primarily study water 16-mers, but we also test the EE-MB-CE method on water hexamers. We analyze the distributions of two-body and three-body terms to show why the many-body expansion of the electrostatically embedded correlation energy converges faster than the many-body expansion of the entire electrostatically embedded interaction potential. The average magnitude of the dimer contributions to the pairwise additive (PA) term of the correlation energy (which neglects cooperative effects) is only one-half of that of the average dimer contribution to the PA term of the expansion of the total energy; this explains why the mean unsigned error (MUE) of the EE-PA-CE approximation is only one-half of that of the EE-PA approximation. Similarly, the average magnitude of the trimer contributions to the three-body (3B) term of the EE-3B-CE approximation is only one-fourth of that of the EE-3B approximation, and the MUE of the EE-3B-CE approximation is one-fourth that of the EE-3B approximation. Finally, we test the efficacy of two- and three-body density functional corrections. One such density functional correction method, the new EE-PA-NE method, with the OLYP or the OHLYP density functional (where the OHLYP functional is the OptX exchange functional combined with the LYP correlation functional multiplied by 0.5), has the best performance-to-price ratio of any method whose computational cost scales as the third power of the number of monomers and is competitive in accuracy in the tests presented here with even the electrostatically embedded three-body approximation.

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.

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.

Protection of tissue physicochemical properties using polyfunctional crosslinkers.

Understanding complex biological systems requires the system-wide characterization of both molecular and cellular features. Existing methods for spatial mapping of biomolecules in intact tissues suffer from information loss caused by degradation and tissue damage. We report a tissue transformation strategy named stabilization under harsh conditions via intramolecular epoxide linkages to prevent degradation (SHIELD), which uses a flexible polyepoxide to form controlled intra- and intermolecular cross-link with biomolecules. SHIELD preserves protein fluorescence and antigenicity, transcripts and tissue architecture under a wide range of harsh conditions. We applied SHIELD to interrogate system-level wiring, synaptic architecture, and molecular features of virally labeled neurons and their targets in mouse at single-cell resolution. We also demonstrated rapid three-dimensional phenotyping of core needle biopsies and human brain cells. SHIELD enables rapid, multiscale, integrated molecular phenotyping of both animal and clinical tissues.

The effect of macromolecular crowding on the electrostatic component of barnase-barstar binding: a computational, implicit solvent-based study.

Macromolecular crowding within the cell can impact both protein folding and binding. Earlier models of cellular crowding focused on the excluded volume, entropic effect of crowding agents, which generally favors compact protein states. Recently, other effects of crowding have been explored, including enthalpically-related crowder-protein interactions and changes in solvation properties. In this work, we explore the effects of macromolecular crowding on the electrostatic desolvation and solvent-screened interaction components of protein-protein binding. Our simple model enables us to focus exclusively on the electrostatic effects of water depletion on protein binding due to crowding, providing us with the ability to systematically analyze and quantify these potentially intuitive effects. We use the barnase-barstar complex as a model system and randomly placed, uncharged spheres within implicit solvent to model crowding in an aqueous environment. On average, we find that the desolvation free energy penalties incurred by partners upon binding are lowered in a crowded environment and solvent-screened interactions are amplified. At a constant crowder density (fraction of total available volume occupied by crowders), this effect generally increases as the radius of model crowders decreases, but the strength and nature of this trend can depend on the water probe radius used to generate the molecular surface in the continuum model. In general, there is huge variation in desolvation penalties as a function of the random crowder positions. Results with explicit model crowders can be qualitatively similar to those using a lowered "effective" solvent dielectric to account for crowding, although the "best" effective dielectric constant will likely depend on multiple system properties. Taken together, this work systematically demonstrates, quantifies, and analyzes qualitative intuition-based insights into the effects of water depletion due to crowding on the electrostatic component of protein binding, and it provides an initial framework for future analyses.

Assessing the Accuracy of Density Functional and Semiempirical Wave Function Methods for Water Nanoparticles: Comparing Binding and Relative Energies of (H2O)16 and (H2O)17 to CCSD(T) Results.

The binding energies and relative conformational energies of five configurations of the water 16-mer are computed using 61 levels of density functional (DF) theory, 12 methods combining DF theory with molecular mechanics damped dispersion (DF-MM), seven semiempirical-wave function (SWF) methods, and five methods combining SWF theory with molecular mechanics damped dispersion (SWF-MM). The accuracies of the computed energies are assessed by comparing them to recent high-level ab initio results; this assessment is more relevant to bulk water than previous tests on small clusters because a 16-mer is large enough to have water molecules that participate in more than three hydrogen bonds. We find that for water 16-mer binding energies the best DF, DF-MM, SWF, and SWF-MM methods (and their mean unsigned errors in kcal/mol) are respectively M06-2X (1.6), ωB97X-D (2.3), SCC-DFTB-γ(h) (35.2), and PM3-D (3.2). We also mention the good performance of CAM-B3LYP (1.8), M05-2X (1.9), and TPSSLYP (3.0). In contrast, for relative energies of various water nanoparticle 16-mer structures, the best methods (and mean unsigned errors in kcal/mol), in the same order of classes of methods, are SOGGA11-X (0.3), ωB97X-D (0.2), PM6 (0.4), and PMOv1 (0.6). We also mention the good performance of LC-ωPBE-D3 (0.3) and ωB97X (0.4). When both relative and binding energies are taken into consideration, the best methods overall (out of the 85 tested) are M05-2X without molecular mechanics and ωB97X-D when molecular mechanics corrections are included; with considerably higher average errors and considerably lower cost, the best SWF or SWF-MM method is PMOv1. We use six of the best methods for binding energies of the water 16-mers to calculate the binding energies of water hexamers and water 17-mers to test whether these methods are also reliable for binding energy calculations on other types of water clusters.