TIP5P-Consistent Treatment of Electrostatics for Biomolecular Simulations

Computerized Molecular Modeling of Carbohydrates

Computerized molecular modeling continues to increase in capability and applicability to carbohydrates. This chapter covers nomenclature and conformational aspects of carbohydrates, perhaps of greater use to computational chemists who do not have a strong background in carbohydrates, and its comments on various methods and studies might be of more use to carbohydrate chemists who are inexperienced with computation. Work on the intrinsic variability of glucose, an overall theme, is described. Other areas of the authors' emphasis, including evaluation of hydrogen bonding by the atoms-in-molecules approach, and validation of modeling methods with crystallographic results are also presented.

Predicting the Structures of Glycans, Glycoproteins, and Their Complexes

Complex carbohydrates are ubiquitous in nature, and together with proteins and nucleic acids they comprise the building blocks of life. But unlike proteins and nucleic acids, carbohydrates form nonlinear polymers, and they are not characterized by robust secondary or tertiary structures but rather by distributions of well-defined conformational states. Their molecular flexibility means that oligosaccharides are often refractory to crystallization, and nuclear magnetic resonance (NMR) spectroscopy augmented by molecular dynamics (MD) simulation is the leading method for their characterization in solution. The biological importance of carbohydrate-protein interactions, in organismal development as well as in disease, places urgency on the creation of innovative experimental and theoretical methods that can predict the specificity of such interactions and quantify their strengths. Additionally, the emerging realization that protein glycosylation impacts protein function and immunogenicity places the ability to define the mechanisms by which glycosylation impacts these features at the forefront of carbohydrate modeling. This review will discuss the relevant theoretical approaches to studying the three-dimensional structures of this fascinating class of molecules and interactions, with reference to the relevant experimental data and techniques that are key for validation of the theoretical predictions.

Unraveling cellulose microfibrils: a twisted tale

Molecular dynamics (MD) simulations of cellulose microfibrils are pertinent to the paper, textile, and biofuels industries for their unique capacity to characterize dynamic behavior and atomic-level interactions with solvent molecules and cellulase enzymes. While high-resolution crystallographic data have established a solid basis for computational analysis of cellulose, previous work has demonstrated a tendency for modeled microfibrils to diverge from the linear experimental structure and adopt a twisted conformation. Here, we investigate the dependence of this twisting behavior on computational approximations and establish the theoretical basis for its occurrence. We examine the role of solvent, the effect of nonbonded force field parameters [partial charges and van der Waals (vdW) contributions], and the use of explicitly modeled oxygen lone pairs in both the solute and solvent. Findings suggest that microfibril twisting is favored by vdW interactions, and counteracted by both intrachain hydrogen bonds and solvent effects at the microfibril surface.

Experimental and theoretical charge-density analysis of 1,4-bis(5-hexyl-2-thienyl)butane-1,4-dione: applications of a virtual-atom model

The experimental and theoretical charge densities of 1,4-bis(5-hexyl-2-thienyl)butane-1,4-dione, a precursor in the synthesis of thiophene-based semiconductors and organic solar cells, are presented. A dummy bond charges spherical atom model is applied besides the multipolar atom model. The results show that the dummy bond charges model is accurate enough to calculate electrostatic-derived properties which are comparable with those obtained by the multipolar atom model. The refinement statistics and the residual electron density values are found to be intermediate between the independent atom and the multipolar formalisms.

Carbohydrate-protein interactions: molecular modeling insights

The article reviews the significant contributions to, and the present status of, applications of computational methods for the characterization and prediction of protein-carbohydrate interactions. After a presentation of the specific features of carbohydrate modeling, along with a brief description of the experimental data and general features of carbohydrate-protein interactions, the survey provides a thorough coverage of the available computational methods and tools. At the quantum-mechanical level, the use of both molecular orbitals and density-functional theory is critically assessed. These are followed by a presentation and critical evaluation of the applications of semiempirical and empirical methods: QM/MM, molecular dynamics, free-energy calculations, metadynamics, molecular robotics, and others. The usefulness of molecular docking in structural glycobiology is evaluated by considering recent docking- validation studies on a range of protein targets. The range of applications of these theoretical methods provides insights into the structural, energetic, and mechanistic facets that occur in the course of the recognition processes. Selected examples are provided to exemplify the usefulness and the present limitations of these computational methods in their ability to assist in elucidation of the structural basis underlying the diverse function and biological roles of carbohydrates in their dialogue with proteins. These test cases cover the field of both carbohydrate biosynthesis and glycosyltransferases, as well as glycoside hydrolases. The phenomenon of (macro)molecular recognition is illustrated for the interactions of carbohydrates with such proteins as lectins, monoclonal antibodies, GAG-binding proteins, porins, and viruses.

Solution Properties of Hemicellulose Polysaccharides with Four Common Carbohydrate Force Fields

Hemicellulose polysaccharides play an important role in the swelling behavior of the primary plant cell wall, and molecular dynamics simulations provide the means of gaining a concise understanding of the interactions of hemicellulose polysaccharides with water. Here, we compare four of the main polysaccharide force fields (CHARMM36 TIP3P, GROMOS56A6(CARBO) SPC, GLYCAM06h TIP3P, and GLYCAM06h TIP5P) for the most abundant hemicellulose backbone components. In particular, we compare aggregation, diffusion coefficients, system density, and investigate the free energy of hydration of saccharides in water. We find that the saccharides show nonphysical aggregation at low concentrations with the GLYCAM06h TIP3P force field, which can be rectified by the use of the TIP5P water model. As a result of the aggregation, GLYCAM06h TIP3P does not lead to reasonable diffusion coefficients whereas the diffusion coefficients, as well as the system density, agrees best with experimental data for the GLYCAM06h TIP5P force field. Overall, GLYCAM06h TIP5P gives good agreement with experimental free energy of hydration data for small saccharides. In addition, the free energy of hydration for short polysaccharides calculated with the GLYCAM06h TIP5P force field is consistent with the radial distribution functions between the polysaccharides and water, the hydration number of the polysaccharides, and the hydrogen bonds formed in the system.

Calculating binding free energies for protein-carbohydrate complexes

A variety of computational techniques may be applied to compute theoretical binding free energies for protein-carbohydrate complexes. Elucidation of the intermolecular interactions, as well as the thermodynamic effects, that contribute to the relative strength of receptor binding can shed light on biomolecular recognition, and the resulting initiation or inhibition of a biological process. Three types of free energy methods are discussed here, including MM-PB/GBSA, thermodynamic integration, and a non-equilibrium alternative utilizing SMD. Throughout this chapter, the well-known concanavalin A lectin is employed as a model system to demonstrate the application of these methods to the special case of carbohydrate binding.

Carbohydrate force fields

Carbohydrates present a special set of challenges to the generation of force fields. First, the tertiary structures of monosaccharides are complex merely by virtue of their exceptionally high number of chiral centers. In addition, their electronic characteristics lead to molecular geometries and electrostatic landscapes that can be challenging to predict and model. The monosaccharide units can also interconnect in many ways, resulting in a large number of possible oligosaccharides and polysaccharides, both linear and branched. These larger structures contain a number of rotatable bonds, meaning they potentially sample an enormous conformational space. This article briefly reviews the history of carbohydrate force fields, examining and comparing their challenges, forms, philosophies, and development strategies. Then it presents a survey of recent uses of these force fields, noting trends, strengths, deficiencies, and possible directions for future expansion.

The use of glycoinformatics in glycochemistry

Glycoinformatics is a small but growing branch of bioinformatics and chemoinformatics. Various resources are now available that can be of use to glycobiologists, but also to chemists who work on the synthesis or analysis of carbohydrates. This article gives an overview of existing glyco-specific databases and tools, with a focus on their application to glycochemistry: Databases can provide information on candidate glycan structures for synthesis, or on glyco-enzymes that can be used to synthesize carbohydrates. Statistical analyses of glycan databases help to plan glycan synthesis experiments. 3D-Structural data of protein-carbohydrate complexes are used in targeted drug design, and tools to support glycan structure analysis aid with quality control. Specific problems of glycoinformatics compared to bioinformatics for genomics or proteomics, especially concerning integration and long-term maintenance of the existing glycan databases, are also discussed.

Directional Dependence of Hydrogen Bonds: a Density-based Energy Decomposition Analysis and Its Implications on Force Field Development

One well-known shortcoming of widely-used biomolecular force fields is the description of the directional dependence of hydrogen bonding (HB). Here we aim to better understand the origin of this difficulty and thus provide some guidance for further force field development. Our theoretical approaches center on a novel density-based energy decomposition analysis (DEDA) method [J. Chem. Phys., 131, 164112 (2009)], in which the frozen density energy is variationally determined through constrained search. This unique and most significant feature of DEDA enables us to find that the frozen density interaction term is the key factor in determining the HB orientation, while the sum of polarization and charge-transfer components shows very little HB directional dependence. This new insight suggests that the difficulty for current non-polarizable force fields to describe the HB directional dependence is not due to the lack of explicit polarization or charge-transfer terms. Using the DEDA results as reference, we further demonstrate that the main failure coming from the atomic point charge model can be overcome largely by introducing extra charge sites or higher order multipole moments. Among all the electrostatic models explored, the smeared charge distributed multipole model (up to quadrupole), which also takes account of charge penetration effects, gives the best agreement with the corresponding DEDA results. Meanwhile, our results indicate that the van der Waals interaction term needs to be further improved to better model directional hydrogen bonding.

Sucrose in aqueous solution revisited, Part 2: adaptively biased molecular dynamics simulations and computational analysis of NMR relaxation

We report 100 ns molecular dynamics simulations, at various temperatures, of sucrose in water (with concentrations of sucrose ranging from 0.02 to 4M), and in a 7:3 water-DMSO mixture. Convergence of the resulting conformational ensembles was checked using adaptive-biased simulations along the glycosidic Φ and ψ torsion angles. NMR relaxation parameters, including longitudinal (R₁) and transverse (R₂) relaxation rates, nuclear Overhauser enhancements (NOE), and generalized order parameter (S²) were computed from the resulting time-correlation functions. The amplitude and time scales of molecular motions change with temperature and concentration in ways that track closely with experimental results, and are consistent with a model in which sucrose conformational fluctuations are limited (with 80-90% of the conformations having ϕ-ψ values within 20° of an average conformation), but with some important differences in conformation between pure water and DMSO-water mixtures.

Computerized molecular modeling of carbohydrates

Computerized molecular modeling continues to increase in capability and applicability to carbohydrates. This chapter covers nomenclature and conformational aspects of carbohydrates, perhaps of greater use to carbohydrate-inexperienced computational chemists. Its comments on various methods and studies might be of more use to computation-inexperienced carbohydrate chemists. New work on intrinsic variability of glucose, an overall theme, is described.

CHARMM additive all-atom force field for glycosidic linkages in carbohydrates involving furanoses

Presented is an extension of the CHARMM additive carbohydrate all-atom force field to enable modeling of polysaccharides containing furanose sugars. The new force field parameters encompass 1 ↔ 2, 1 → 3, 1 → 4, and 1 → 6 pyranose-furanose linkages and 2 → 1 and 2 → 6 furanose-furanose linkages, building on existing hexopyranose and furanose monosaccharide parameters. The model compounds were chosen to be monomers or glycosidic-linked dimers of tetrahydropyran (THP) and tetrahydrofuran (THF) as to contain the key atoms in full carbohydrates. Target data for optimization included two-dimensional quantum mechanical (QM) potential energy scans of the Φ/Ψ glycosidic dihedral angles, with geometry optimization at the MP2/6-31G(d) level followed by MP2/cc-pVTZ single-point energies. All possible chiralities of the model compounds at the linkage carbons were considered, and for each geometry, the THF ring was constrained to the favorable south or north conformations. Target data also included QM vibrational frequencies and pair interaction energies and distances with water molecules. Force field validation included comparison of computed crystal properties, aqueous solution densities, and NMR J-coupling constants to experimental reference values. Simulations of infinite crystals showed good agreement with experimental values for intramolecular geometries as well as for crystal unit cell parameters. Additionally, aqueous solution densities and available NMR data were reproduced to a high degree of accuracy, thus validating the hierarchically optimized parameters in both crystalline and aqueous condensed phases. The newly developed parameters allow for the modeling of linear, branched, and cyclic pyranose/furanose polysaccharides both alone and in heterogeneous systems including proteins, nucleic acids, and/or lipids when combined with existing additive CHARMM biomolecular force fields.

Bioinformatics and molecular modeling in glycobiology

The field of glycobiology is concerned with the study of the structure, properties, and biological functions of the family of biomolecules called carbohydrates. Bioinformatics for glycobiology is a particularly challenging field, because carbohydrates exhibit a high structural diversity and their chains are often branched. Significant improvements in experimental analytical methods over recent years have led to a tremendous increase in the amount of carbohydrate structure data generated. Consequently, the availability of databases and tools to store, retrieve and analyze these data in an efficient way is of fundamental importance to progress in glycobiology. In this review, the various graphical representations and sequence formats of carbohydrates are introduced, and an overview of newly developed databases, the latest developments in sequence alignment and data mining, and tools to support experimental glycan analysis are presented. Finally, the field of structural glycoinformatics and molecular modeling of carbohydrates, glycoproteins, and protein-carbohydrate interaction are reviewed.

Molecular simulations of carbohydrates and protein-carbohydrate interactions: motivation, issues and prospects

The characterization of the 3D structure of oligosaccharides, their conjugates and analogs is particularly challenging for traditional experimental methods. Molecular simulation methods provide a basis for interpreting sparse experimental data and for independently predicting conformational and dynamic properties of glycans. Here, we summarize and analyze the issues associated with modeling carbohydrates, with a detailed discussion of four of the most recently developed carbohydrate force fields, reviewed in terms of applicability to natural glycans, carbohydrate-protein complexes and the emerging area of glycomimetic drugs. In addition, we discuss prospectives and new applications of carbohydrate modeling in drug discovery.

Universal solvation model based on solute electron density and on a continuum model of the solvent defined by the bulk dielectric constant and atomic surface tensions

We present a new continuum solvation model based on the quantum mechanical charge density of a solute molecule interacting with a continuum description of the solvent. The model is called SMD, where the "D" stands for "density" to denote that the full solute electron density is used without defining partial atomic charges. "Continuum" denotes that the solvent is not represented explicitly but rather as a dielectric medium with surface tension at the solute-solvent boundary. SMD is a universal solvation model, where "universal" denotes its applicability to any charged or uncharged solute in any solvent or liquid medium for which a few key descriptors are known (in particular, dielectric constant, refractive index, bulk surface tension, and acidity and basicity parameters). The model separates the observable solvation free energy into two main components. The first component is the bulk electrostatic contribution arising from a self-consistent reaction field treatment that involves the solution of the nonhomogeneous Poisson equation for electrostatics in terms of the integral-equation-formalism polarizable continuum model (IEF-PCM). The cavities for the bulk electrostatic calculation are defined by superpositions of nuclear-centered spheres. The second component is called the cavity-dispersion-solvent-structure term and is the contribution arising from short-range interactions between the solute and solvent molecules in the first solvation shell. This contribution is a sum of terms that are proportional (with geometry-dependent proportionality constants called atomic surface tensions) to the solvent-accessible surface areas of the individual atoms of the solute. The SMD model has been parametrized with a training set of 2821 solvation data including 112 aqueous ionic solvation free energies, 220 solvation free energies for 166 ions in acetonitrile, methanol, and dimethyl sulfoxide, 2346 solvation free energies for 318 neutral solutes in 91 solvents (90 nonaqueous organic solvents and water), and 143 transfer free energies for 93 neutral solutes between water and 15 organic solvents. The elements present in the solutes are H, C, N, O, F, Si, P, S, Cl, and Br. The SMD model employs a single set of parameters (intrinsic atomic Coulomb radii and atomic surface tension coefficients) optimized over six electronic structure methods: M05-2X/MIDI!6D, M05-2X/6-31G, M05-2X/6-31+G, M05-2X/cc-pVTZ, B3LYP/6-31G, and HF/6-31G. Although the SMD model has been parametrized using the IEF-PCM protocol for bulk electrostatics, it may also be employed with other algorithms for solving the nonhomogeneous Poisson equation for continuum solvation calculations in which the solute is represented by its electron density in real space. This includes, for example, the conductor-like screening algorithm. With the 6-31G basis set, the SMD model achieves mean unsigned errors of 0.6-1.0 kcal/mol in the solvation free energies of tested neutrals and mean unsigned errors of 4 kcal/mol on average for ions with either Gaussian03 or GAMESS.