Resurrected Ancestors Reveal Origins of Metamorphism in XCL1.

In a recent study, Dishman et al. resurrected ancestors of the metamorphic chemokine, XCL1, inferred through phylogenetics, and found that metamorphism arose in the XCL1 lineage ~150 million years ago. A zigzagging evolutionary path suggests that the metamorphic properties are adaptive and reveals three design principles that could be used for technological applications.

Revealing elusive conformations of sucrose from hydrogen bond J-coupling in H2O: A combined NMR and quantum mechanics study.

Hydrogen bonding is a crucial feature of biomolecules, but its characterization in glycans dissolved in aqueous solutions is challenging due to rapid hydrogen exchange between hydroxyl groups and H2O. In principle, the scalar (J) coupling constant can reveal the relative orientation of the atoms in the molecule. In contrast to J-coupling through H-bonds reported in proteins and nucleic acids, research on J-coupling through H-bonds in glycans dissolved in water is lacking. Here, we use sucrose as a model system for H-bonding studies; its structure, which consists of glucose (Glc) and fructose (Frc), is well-studied, and it is readily available. We apply the in-phase, antiphase-HSQC-TOCSY and quantify previously unreported through H-bond J-values for Frc-OH1-Glc-OH2 in H2O. While earlier reports of Brown and Levy indicate this H-bond as having only a single direction, our reported findings indicate the potential presence of two involving these same atoms, namely, G2OH âž” F1O and F1OH âž” G2O (where F and G stand for Frc and Glc, respectively). The calculated density functional theory J-values for the G2OH âž” F1O agree with the experimental values. Additionally, we detected four other possible H-bonds in sucrose, which require different phi, psi (ϕ, ψ) torsion angles. The ϕ, ψ values are consistent with previous predictions of du Penhoat et al. and Venable et al. Our results will provide new insights into the molecular structure of sucrose and its interactions with proteins.

The impact of conformational sampling on first-principles calculations of vicinal COCH J-couplings in carbohydrates.

Dihedral angles in organic molecules and biomolecules are vital structural parameters that can be indirectly probed by nuclear magnetic resonance (NMR) measurements of vicinal J-couplings. The empirical relations that map the measured couplings to dihedral angles are typically determined by fitting using static structural models, but this neglects the effects of thermal fluctuations at the finite temperature conditions under which NMR measurements are often taken. In this study, we calculate ensemble-averaged J-couplings for several structurally rigid carbohydrate derivatives using first-principles molecular dynamics simulations to sample the thermally accessible conformations around the minimum energy structure. Our results show that including thermal fluctuation effects significantly shifts the predicted couplings relative to single-point calculations at the energy minima, leading to improved agreement with experiments. This provides evidence that accounting for conformational sampling in first-principles calculations can improve the accuracy of NMR-based structure determination for structurally complex carbohydrates.

Copper(II) Affects the Biochemical Behavior of Proinsulin C-peptide by Forming Ternary Complexes with Serum Albumin.

Peptide hormones are essential signaling molecules with therapeutic importance. Identifying regulatory factors that drive their activity gives important insight into their mode of action and clinical development. In this work, we demonstrate the combined impact of Cu(II) and the serum protein albumin on the activity of C-peptide, a 31-mer peptide derived from the same prohormone as insulin. C-peptide exhibits beneficial effects, particularly in diabetic patients, but its clinical use has been hampered by a lack of mechanistic understanding. We show that Cu(II) mediates the formation of ternary complexes between albumin and C-peptide and that the resulting species depend on the order of addition. These ternary complexes notably alter peptide activity, showing differences from the peptide or Cu(II)/peptide complexes alone in redox protection as well as in cellular internalization of the peptide. In standard clinical immunoassays for measuring C-peptide levels, the complexes inflate the quantitation of the peptide, suggesting that such adducts may affect biomarker quantitation. Altogether, our work points to the potential relevance of Cu(II)-linked C-peptide/albumin complexes in the peptide's mechanism of action and application as a biomarker.

Quantum Chemistry Calculations for Metabolomics.

A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversity present within the metabolome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials ("standards"), which are not available for most molecules. Computational quantum chemistry methods, which can be used to calculate chemical properties that are then measured by analytical platforms, offer an alternative route for building reference libraries, i.e., in silico libraries for "standards-free" identification. In this review, we cover the major roadblocks currently facing metabolomics and discuss applications where quantum chemistry calculations offer a solution. Several successful examples for nuclear magnetic resonance spectroscopy, ion mobility spectrometry, infrared spectroscopy, and mass spectrometry methods are reviewed. Finally, we consider current best practices, sources of error, and provide an outlook for quantum chemistry calculations in metabolomics studies. We expect this review will inspire researchers in the field of small-molecule identification to accelerate adoption of in silico methods for generation of reference libraries and to add quantum chemistry calculations as another tool at their disposal to characterize complex samples.

Accumulation and Pulse Electron Paramagnetic Resonance Spectroscopic Investigation of the 4-Oxidobenzyl Radical Generated in the Radical S-Adenosyl-l-methionine Enzyme HydG.

The radical S-adenosyl-l-methionine (SAM) enzyme HydG cleaves tyrosine to generate CO and CN- ligands of the [FeFe] hydrogenase H-cluster, accompanied by the formation of a 4-oxidobenzyl radical (4-OB•), which is the precursor to the HydG p-cresol byproduct. Native HydG only generates a small amount of 4-OB•, limiting detailed electron paramagnetic resonance (EPR) spectral characterization beyond our initial EPR lineshape study employing various tyrosine isotopologues. Here, we show that the concentration of trapped 4-OB• is significantly increased in reactions using HydG variants, in which the "dangler Fe" to which CO and CN- bind is missing or substituted by a redox-inert Zn2+ ion. This allows for the detailed characterization of 4-OB• using high-field EPR and electron nuclear double resonance spectroscopy to extract its g-values and 1H/13C hyperfine couplings. These results are compared to density functional theory-predicted values of several 4-OB• models with different sizes and protonation states, with a best fit to the deprotonated radical anion configuration of 4-OB•. Overall, our results depict a clearer electronic structure of the transient 4-OB• radical and provide new insights into the radical SAM chemistry of HydG.

O-Acetyl Migration within the Sialic Acid Side Chain: A Mechanistic Study Using the Ab Initio Nanoreactor.

Many disease-causing viruses target sialic acids on the surface of host cells. Some viruses bind preferentially to sialic acids with O-acetyl modification at the hydroxyl group of C7, C8, or C9 on the glycerol-like side chain. Studies of proteins binding to sialosides containing O-acetylated sialic acids are crucial in understanding the related diseases but experimentally difficult due to the lability of the ester group. We recently showed that O-acetyl migration among hydroxyl groups of C7, C8, and C9 in sialic acids occurs in all directions in a pH-dependent manner. In the current study, we elucidate a full mechanistic pathway for the migration of O-acetyl among C7, C8, and C9. We used an ab initio nanoreactor to explore potential reaction pathways and density functional theory, pKa calculations, and umbrella sampling to investigate elementary steps of interest. We found that when a base is present, migration is easy in any direction and involves three key steps: deprotonation of the hydroxyl group, cyclization between the two carbons, and the migration of the O-acetyl group. This dynamic equilibrium may play a defensive role against pathogens that evolve to gain entry to the cell by binding selectively to one acetylation state.

Source of Rate Acceleration for Carbocation Cyclization in Biomimetic Supramolecular Cages.

The results of quantum chemical and molecular dynamics calculations reveal that polyanionic gallium-based cages accelerate cyclization reactions of pentadienyl alcohols as a result of substrate cage interactions, preferential binding of reactive conformations of substrate/H3O+ pairs, and increased substrate basicity. However, the increase in basicity dominates. Experimental structure-activity relationship studies in which the metal vertices and overall charge of the cage are varied confirm the model derived via calculations.

Exploration and validation of force field design protocols through QM-to-MM mapping.

The scale of the parameter optimisation problem in traditional molecular mechanics force field construction means that design of a new force field is a long process, and sub-optimal choices made in the early stages can persist for many generations. We hypothesise that careful use of quantum mechanics to inform molecular mechanics parameter derivation (QM-to-MM mapping) should be used to significantly reduce the number of parameters that require fitting to experiment and increase the pace of force field development. Here, we design and train a collection of 15 new protocols for small, organic molecule force field derivation, and test their accuracy against experimental liquid properties. Our best performing model has only seven fitting parameters, yet achieves mean unsigned errors of just 0.031 g cm-3 and 0.69 kcal mol-1 in liquid densities and heats of vaporisation, compared to experiment. The software required to derive the designed force fields is freely available at https://github.com/qubekit/QUBEKit.

Benchmarking Density Functionals, Basis Sets, and Solvent Models in Predicting Thermodynamic Hydricities of Organic Hydrides.

Many renewable energy technologies, such as hydrogen gas synthesis and carbon dioxide reduction, rely on chemical reactions involving hydride anions (H-). When selecting molecules to be used in such applications, an important quantity to consider is the thermodynamic hydricity, which is the free energy required for a species to donate a hydride anion. Theoretical calculations of thermodynamic hydricity depend on several parameters, mainly the density functional, basis set, and solvent model. In order to assess the effects of the above three parameters, we carry out hydricity calculations with different combinations of density functionals, basis sets, and solvent models for a set of organic molecules with known experimental hydricity values. The data are analyzed by comparing the R2 and root-mean-squared error (RMSE) of linear fits with a fixed slope of 1 and using the Akaike Information Criterion to determine statistical significance of the RMSE rank ordering. Based on these results, we quantified the accuracy of theoretical predictions of hydricity and found that the best compromise between accuracy and computational cost was obtained by using the B3LYP-D3 density functional for the geometry optimization and free-energy corrections, either ωB97X-D3 or M06-2X-D3 for single-point energy corrections, combined with a basis set no larger than def-TZVP and the C-PCM ISWIG solvation model. At this level of theory, the RMSEs of hydricity calculations for organic molecules in acetonitrile and dimethyl sulfoxide were found to be <4 and <10 kcal/mol, respectively, for an experimental data set with a dynamic range of 20-150 kcal/mol.

Multireference configuration interaction study of the predissociation of C2 via its F1Πu state.

Photodissociation is one of the main destruction pathways for dicarbon (C2) in astronomical environments, such as diffuse interstellar clouds, yet the accuracy of modern astrochemical models is limited by a lack of accurate photodissociation cross sections in the vacuum ultraviolet range. C2 features a strong predissociative F1Πu-X1Σg + electronic transition near 130 nm originally measured in 1969; however, no experimental studies of this transition have been carried out since, and theoretical studies of the F1Πu state are limited. In this work, potential energy curves of excited electronic states of C2 are calculated with the aim of describing the predissociative nature of the F1Πu state and providing new ab initio photodissociation cross sections for astrochemical applications. Accurate electronic calculations of 56 singlet, triplet, and quintet states are carried out at the DW-SA-CASSCF/MRCI+Q level of theory with a CAS(8,12) active space and the aug-cc-pV5Z basis set augmented with additional diffuse functions. Photodissociation cross sections arising from the vibronic ground state to the F1Πu state are calculated by a coupled-channel model. The total integrated cross section through the F1Πu v = 0 and v = 1 bands is 1.198 × 10-13 cm2 cm-1, giving rise to a photodissociation rate of 5.02 × 10-10 s-1 under the standard interstellar radiation field, much larger than the rate in the Leiden photodissociation database. In addition, we report a new 21Σu + state that should be detectable via a strong 21Σu +-X1Σg + band around 116 nm.

SARS-CoV-2 and MERS-CoV Spike Protein Binding Studies Support Stable Mimic of Bound 9-O-Acetylated Sialic Acids.

Many disease-causing viruses target sialic acids (Sias), a class of nine-carbon sugars known to coat the surface of many cells, including those in the lungs. Human beta coronaviridae, known for causing respiratory tract diseases, often bind Sias, and some preferentially bind to those with 9-O-Ac-modification. Currently, co-binding of SARS-CoV-2, a beta coronavirus responsible for the COVID-19 pandemic, to human Sias has been reported and its preference towards α2-3-linked Neu5Ac has been shown. Nevertheless, O-acetylated Sias-protein binding studies are difficult to perform, due to the ester lability. We studied the binding free energy differences between Neu5,9Ac2α2-3GalßpNP and its more stable 9-NAc mimic binding to SARS-CoV-2 spike protein using molecular dynamics and alchemical free energy simulations. We identified multiple Sia-binding pockets, including two novel sites, with similar binding affinities to those of MERS-CoV, a known co-binder of sialic acid. In our binding poses, 9-NAc and 9-OAc Sias bind similarly, suggesting an experimentally reasonable mimic to probe viral mechanisms.

Quantum Chemical Study of a Radical Relay Mechanism for the HydG-Catalyzed Synthesis of a Fe(II)(CO)2(CN)cysteine Precursor to the H-Cluster of [FeFe] Hydrogenase.

The [FeFe] hydrogenase catalyzes the redox interconversion of protons and H2 with a Fe-S "H-cluster" employing CO, CN, and azadithiolate ligands to two Fe centers. The biosynthesis of the H-cluster is a highly interesting reaction carried out by a set of Fe-S maturase enzymes called HydE, HydF, and HydG. HydG, a member of the radical S-adenosylmethionine (rSAM) family, converts tyrosine, cysteine, and Fe(II) into an organometallic Fe(II)(CO)2(CN)cysteine "synthon", which serves as the substrate for HydE. Although key aspects of the HydG mechanism have been experimentally determined via isotope-sensitive spectroscopic methods, other important mechanistic questions have eluded experimental determination. Here, we use computational quantum chemistry to refine the mechanism of the HydG catalytic reaction. We utilize quantum mechanics/molecular mechanics simulations to investigate the reactions at the canonical Fe-S cluster, where a radical cleavage of the tyrosine substrate takes place and proceeds through a relay of radical intermediates to form HCN and a COO•- radical anion. We then carry out a broken-symmetry density functional theory study of the reactions at the unusual five-iron auxiliary Fe-S cluster, where two equivalents of CN- and COOH• coordinate to the fifth "dangler iron" in a series of substitution and redox reactions that yield the synthon as the final product for further processing by HydE.

Identification and characterization of metamorphic proteins: Current and future perspectives.

Proteins that can reversibly alternate between distinctly different folds under native conditions are described as being metamorphic. The "metamorphome" is the collection of all metamorphic proteins in the proteome, but it remains unknown the extent to which the proteome is populated by this class of proteins. We propose that uncovering the metamorphome will require a synergy of computational screening of protein sequences to identify potential metamorphic behavior and validation through experimental techniques. This perspective discusses computational and experimental approaches that are currently used to predict and characterize metamorphic proteins as well as the need for developing improved methodologies. Since metamorphic proteins act as molecular switches, understanding their properties and behavior could lead to novel applications of these proteins as sensors in biological or environmental contexts.

The automated optimisation of a coarse-grained force field using free energy data.

Atomistic models provide a detailed representation of molecular systems, but are sometimes inadequate for simulations of large systems over long timescales. Coarse-grained models enable accelerated simulations by reducing the number of degrees of freedom, at the cost of reduced accuracy. New optimisation processes to parameterise these models could improve their quality and range of applicability. We present an automated approach for the optimisation of coarse-grained force fields, by reproducing free energy data derived from atomistic molecular simulations. To illustrate the approach, we implemented hydration free energy gradients as a new target for force field optimisation in ForceBalance and applied it successfully to optimise the un-charged side-chains and the protein backbone in the SIRAH protein coarse-grain force field. The optimised parameters closely reproduced hydration free energies of atomistic models and gave improved agreement with experiment.

Quantum Chemistry Common Driver and Databases (QCDB) and Quantum Chemistry Engine (QCEngine): Automation and interoperability among computational chemistry programs.

Community efforts in the computational molecular sciences (CMS) are evolving toward modular, open, and interoperable interfaces that work with existing community codes to provide more functionality and composability than could be achieved with a single program. The Quantum Chemistry Common Driver and Databases (QCDB) project provides such capability through an application programming interface (API) that facilitates interoperability across multiple quantum chemistry software packages. In tandem with the Molecular Sciences Software Institute and their Quantum Chemistry Archive ecosystem, the unique functionalities of several CMS programs are integrated, including CFOUR, GAMESS, NWChem, OpenMM, Psi4, Qcore, TeraChem, and Turbomole, to provide common computational functions, i.e., energy, gradient, and Hessian computations as well as molecular properties such as atomic charges and vibrational frequency analysis. Both standard users and power users benefit from adopting these APIs as they lower the language barrier of input styles and enable a standard layout of variables and data. These designs allow end-to-end interoperable programming of complex computations and provide best practices options by default.

Sequence-Based Prediction of Metamorphic Behavior in Proteins.

An increasing number of proteins have been demonstrated in recent years to adopt multiple three-dimensional folds with different functions. These metamorphic proteins are characterized by having two or more folds with significant differences in their secondary structure, in which each fold is stabilized by a distinct local environment. So far, ∼90 metamorphic proteins have been identified in the Protein Databank, but we and others hypothesize that a far greater number of metamorphic proteins remain undiscovered. In this work, we introduce a computational model to predict metamorphic behavior in proteins using only knowledge of the sequence. In this model, secondary structure prediction programs are used to calculate diversity indices, which are measures of uncertainty in predicted secondary structure at each position in the sequence; these are then used to assign protein sequences as likely to be metamorphic versus monomorphic (i.e., having just one fold). We constructed a reference data set to train our classification method, which includes a novel compilation of 136 likely monomorphic proteins and a set of 201 metamorphic protein structures taken from the literature. Our model is able to classify proteins as metamorphic versus monomorphic with a Matthews correlation coefficient of ∼0.36 and true positive/true negative rates of ∼65%/80%, suggesting that it is possible to predict metamorphic behavior in proteins using only sequence information.

Linkage between Proximal and Distal Movements of P450cam Induced by Putidaredoxin.

Putidaredoxin (Pdx) is the exclusive reductase and a structural effector for P450cam (CYP101A1). However, the mechanism of how Pdx modulates the conformational states of P450cam remains elusive. Here we report a putative communication pathway for the Pdx-induced conformational change in P450cam using results of double electron-electron resonance (DEER) spectroscopy and molecular dynamics simulations. Use of solution state DEER measurements allows us to observe subtle conformational changes in the internal helices in P450cam among closed, open, and P450cam-Pdx complex states. Molecular dynamics simulations and dynamic network analysis suggest that Pdx binding is coupled to small coordinated movements of several regions of P450cam, including helices C, B', I, G, and F. These changes provide a linkage between the Pdx binding site on the proximal side of the enzyme and helices F/G on the distal side and the site of the largest movement resulting from the Pdx-induced closed-to-open transition. This study provides a detailed rationale for how Pdx exerts its long-recognized effector function at the active site from its binding site on the opposite face of the enzyme.

A combined NMR, MD and DFT conformational analysis of 9-O-acetyl sialic acid-containing GM3 ganglioside glycan and its 9-N-acetyl mimic.

O-Acetylation of carbohydrates such as sialic acids is common in nature, but its role is not clearly understood due to the lability of O-acetyl groups. We demonstrated previously that 9-acetamido-9-deoxy-N-acetylneuraminic acid (Neu5Ac9NAc) is a chemically and biologically stable mimic of the 9-O-acetyl-N-acetylneuraminic acid (Neu5,9Ac2) of the corresponding sialoglycans. Here, a systematic nuclear magnetic resonance (NMR) spectroscopic and molecular dynamics (MD) simulation study was undertaken for Neu5,9Ac2-containing GM3 ganglioside glycan (GM3-glycan) and its Neu5Ac9NAc analog. GM3-glycan with Neu5Ac as the non-O-acetyl form of Neu5,9Ac2 was used as a control. Complete 1H and 13C NMR chemical shift assignments, three-bond 1H-13C trans-glycosidic coupling constants (3JCH), accurate 1H-1H coupling constants (3JHH), nuclear Overhauser effects and hydrogen bonding detection were carried out. Results show that structural modification (O- or N-acetylation) on the C-9 of Neu5Ac in GM3 glycan does not cause significant conformational changes on either its glycosidic dihedral angles or its secondary structure. All structural differences are confined to the Neu5Ac glycerol chain, and minor temperature-dependent changes are seen in the aglycone portion. We also used Density Functional Theory (DFT) quantum mechanical calculations to improve currently used 3JHH Karplus relations. Furthermore, OH chemical shifts were assigned at -10°C and no evidence of an intramolecular hydrogen bond was observed. The results provide additional evidence regarding structural similarities between sialosides containing 9-N-acetylated and 9-O-acetylated Neu5Ac and support the opportunity of using 9-N-acetylated Neu5Ac as a stable mimic to study the biochemical role of 9-O-acetylated Neu5Ac.

Driving torsion scans with wavefront propagation.

The parameterization of torsional/dihedral angle potential energy terms is a crucial part of developing molecular mechanics force fields. Quantum mechanical (QM) methods are often used to provide samples of the potential energy surface (PES) for fitting the empirical parameters in these force field terms. To ensure that the sampled molecular configurations are thermodynamically feasible, constrained QM geometry optimizations are typically carried out, which relax the orthogonal degrees of freedom while fixing the target torsion angle(s) on a grid of values. However, the quality of results and computational cost are affected by various factors on a non-trivial PES, such as dependence on the chosen scan direction and the lack of efficient approaches to integrate results started from multiple initial guesses. In this paper, we propose a systematic and versatile workflow called TorsionDrive to generate energy-minimized structures on a grid of torsion constraints by means of a recursive wavefront propagation algorithm, which resolves the deficiencies of conventional scanning approaches and generates higher quality QM data for force field development. The capabilities of our method are presented for multi-dimensional scans and multiple initial guess structures, and an integration with the MolSSI QCArchive distributed computing ecosystem is described. The method is implemented in an open-source software package that is compatible with many QM software packages and energy minimization codes.