Carbohydrate force fields

The evolution of the Amber additive protein force field: History, current status, and future

Molecular dynamics simulations are pivotal in elucidating the intricate properties of biological molecules. Nonetheless, the reliability of their outcomes hinges on the precision of the molecular force field utilized. In this perspective, we present a comprehensive review of the developmental trajectory of the Amber additive protein force field, delving into researchers' persistent quest for higher precision force fields and the prevailing challenges. We detail the parameterization process of the Amber protein force fields, emphasizing the specific improvements and retained features in each version compared to their predecessors. Furthermore, we discuss the challenges that current force fields encounter in balancing the interactions of protein-protein, protein-water, and water-water in molecular dynamics simulations, as well as potential solutions to overcome these issues.

Refinement of the Drude Polarizable Force Field for Hexose Monosaccharides: Capturing Ring Conformational Dynamics with Enhanced Accuracy

We present a revised version of the Drude polarizable carbohydrate force field (FF), focusing on refining the ring and exocyclic torsional parameters for hexopyranose monosaccharides. This refinement addresses the previously observed discrepancies between calculated and experimental NMR 3J coupling values, particularly in describing ring dynamics and exocyclic rotamer populations within major hexose monosaccharides and their anomers. Specifically, α-MAN, β-MAN, α-GLC, β-GLC, α-GAL, β-GAL, α-ALT, β-ALT, α-IDO, and β-IDO were targeted for optimization. The optimization process involved potential energy scans (PES) of the ring and exocyclic dihedral angles computed using quantum mechanical (QM) methods. The target data for the reoptimization included PES of the inner ring dihedrals (C1-C2-C3-C4, C2-C3-C4-C5, C5-O5-C1-C2, C4-C5-O5-C1, O5-C1-C2-C3, C3-C4-C5-O5) and the exocyclic torsions, other than the pseudo ring dihedrals (O1-C1-O5-C5, O2-C2-C1-O5, and O4-C4-C5-O5) and hydroxyl torsions used in the previous parametrization efforts. These parameters, in conjunction with previously developed Drude parameters for hexopyranose monosaccharides, were validated against experimental observations, including NMR data and conformational energetics, in aqueous environments. The resulting polarizable model is shown to be in good agreement with a range of QM data, experimental NMR data, and conformational energetics of monosaccharides in aqueous solutions. This offers a significant improvement of the Drude carbohydrate force field, wherein the refinement enhances the accuracy of accessing the conformational dynamics of carbohydrates in biomolecular simulations.

The Conformation of Glycosidic Linkages According to Various Force Fields: Monte Carlo Modeling of Polysaccharides Based on Extrapolation of Short-Chain Properties

The conformational features of the glycosidic linkage are the most important variable to consider when studying di-, oligo-, and polysaccharide molecules using molecular dynamics (MD) simulations. The accuracy of the theoretical model describing this degree of freedom influences the quality of the results obtained from MD calculations based on this model. This article focuses on the following two issues related to the conformation of the glycosidic linkage. First, we describe the results of a comparative analysis of the predictions of three carbohydrate-dedicated classical force fields for MD simulations, namely, CHARMM, GLYCAM, and GROMOS, in the context of different parameters of structural and energetic nature related to the conformation of selected types of glycosidic linkages, α(1 → 4), β(1 → 3), and β(1 → 4), connecting glucopyranose units. This analysis revealed several differences, mainly concerning the energy levels of the secondary and tertiary conformers and the linkage flexibility within the dominant exo-syn conformation for α(1 → 4) and β(1 → 3) linkages. Some aspects of the comparative analysis also included the newly developed, carbohydrate-dedicated Martini 3 coarse-grained force field. Second, to overcome the time-scale problem associated with sampling slow degrees of freedom in polysaccharide chains during MD simulations, we developed a coarse-grained (CG) model based on the data from MD simulations and designed for Monte Carlo modeling. This model (CG MC) is based on information from simulations of short saccharide chains, effectively sampled in atomistic MD simulations, and is capable of extrapolating local conformational properties to the case of polysaccharides of arbitrary length. The CG MC model has the potential to estimate the conformations of very long polysaccharide chains, taking into account the influence of secondary and tertiary conformations of glycosidic linkages. With respect to the comparative analysis of force fields, the application of CG MC modeling showed that relatively small differences in the predictions of individual force fields with respect to a single glycosidic linkage accumulate when considering their effect on the structure of longer chains, leading to drastically different predictions with respect to parameters describing the polymer conformation, such as the persistence length.

Create artilysins from a recombinant library to serve as bactericidal and antibiofilm agents targeting Pseudomonas aeruginosa

Pseudomonas aeruginosa is a critical pathogen and novel treatments are urgently needed. The out membrane of P. aeruginosa facilitates biofilm formation and antibiotic resistance, and hinders the exogenous application against Gram-negative bacteria of endolysins. Engineered endolysins are investigated for enhancing antimicrobial activity, exemplified by artilysins. Nevertheless, existing research predominantly relies on laborious and time-consuming approaches of individually artilysin identification. This study proposes a novel strategy for expedited artilysin discovery using a recombinant artilysin library comprising proteins derived from 38 antimicrobial peptides and 8 endolysins. In this library, 19 colonies exhibited growth inhibition against P. aeruginosa exceeding 50 %, and three colonies were designated as dutarlysin-1, dutarlysin-2 and dutarlysin-3. Remarkably, dutarlysin-1, dutarlysin-2 and dutarlysin-3 demonstrated rapid and enhanced antibacterial activity, even minimum inhibitory concentration of them killed approximately 4.93 lg units, 6.75 lg units and 5.36 lg units P. aeruginosa, respectively. Dutarlysins were highly refractory to P. aeruginosa resistance development. Furthermore, 2 μmol/L dutarlysin-1 and dutarlysin-3 effectively eradicated over 76 % of the mature biofilm. These dutarlysins exhibited potential broad-spectrum activity against hospital susceptible Gram-negative bacteria. These results supported the effectiveness of this artilysins discovery strategy and suggested dutarlysin-1 and dutarlysin-3 could be promising antimicrobial agents for combating P. aeruginosa.

Graph theoretical descriptors differentiate d-Mannose isomers in the principal component proposed feature space: A computational approach

The intricate nature of carbohydrates, particularly monosaccharides, stems from the existence of several chiral centers within their tertiary structures. Predicting and characterizing the molecular geometries and electrostatic landscapes of these substances is difficult due to their complex electrical properties. Moreover, these structures can display a substantial degree of conformational flexibility due to the presence of many rotatable bonds. Moreover, identifying and distinguishing between D and L enantiomers of monosaccharides presents a significant analytical obstacle since there is a need for empirically measurable properties that can distinguish them. This work uses Principal Component Analysis (PCA) to explore the chemical information included in 3D descriptors in order to comprehend the conformational space of d-Mannose stereoisomers. The isomers may be discriminated by utilizing 3D matrix-based indices, geometrical descriptors, and RDF descriptors. The isomers can be distinguished by descriptors, such as the Harary-like index from the reciprocal squared geometrical matrix (H_RG), Harary-like index from Coulomb matrix (H_Coulomb), Wiener-like index from Coulomb matrix (Wi_Coulomb), Wiener-like index from geometrical matrix (Wi_G), Graph energy from Coulomb matrix (SpAbs_Coulomb), Spectral absolute deviation from Coulomb matrix (SpAD_Coulomb), and Spectral positive sum from Coulomb matrix (SpPos_Coulomb). Among these descriptors, the first two, H_RG and H_Coulomb, perform the best in differentiation among the 3D-Matrix-Based Descriptors (3D-MBD) class. The results obtained from this study provide a significant chemical insight into the structural characteristics of the compounds inside the graph theoretical framework. These findings are likely to serve as the basis for developing new methods for analytical experiments.

The Legionella collagen-like protein employs a distinct binding mechanism for the recognition of host glycosaminoglycans

Bacterial adhesion is a fundamental process which enables colonisation of niche environments and is key for infection. However, in Legionella pneumophila, the causative agent of Legionnaires' disease, these processes are not well understood. The Legionella collagen-like protein (Lcl) is an extracellular peripheral membrane protein that recognises sulphated glycosaminoglycans on the surface of eukaryotic cells, but also stimulates bacterial aggregation in response to divalent cations. Here we report the crystal structure of the Lcl C-terminal domain (Lcl-CTD) and present a model for intact Lcl. Our data reveal that Lcl-CTD forms an unusual trimer arrangement with a positively charged external surface and negatively charged solvent exposed internal cavity. Through molecular dynamics simulations, we show how the glycosaminoglycan chondroitin-4-sulphate associates with the Lcl-CTD surface via distinct binding modes. Our findings show that Lcl homologs are present across both the Pseudomonadota and Fibrobacterota-Chlorobiota-Bacteroidota phyla and suggest that Lcl may represent a versatile carbohydrate-binding mechanism.

A True Reverse Anomeric Effect Does Exist After All: A Hydrogen Bonding Stereocontrolling Effect in 2-Iminoaldoses

The reverse anomeric effect is usually associated with the equatorial preference of nitrogen substituents at the anomeric center. Once postulated as another anomeric effect with explanations ranging from electrostatic interactions to delocalization effects, it is now firmly considered to be essentially steric in nature. Through an extensive research on aryl imines from 2-amino-2-deoxyaldoses, spanning nearly two decades, we realized that such substances often show an anomalous anomeric behavior that cannot easily be rationalized on the basis of purely steric grounds. The apparent preference, or stabilization, of the β-anomer takes place to an extent that not only neutralizes but also overcomes the normal anomeric effect. Calculations indicate that there is no stereoelectronic effect opposing the anomeric effect, resulting from the repulsion between electron lone pairs on the imine nitrogen and the endocyclic oxygen. Such data and compelling structural evidence unravel why the exoanomeric effect is largely inhibited. We are now confident, as witnessed by 2-iminoaldoses, that elimination of the exo-anomeric effect in the α-anomer is due to the formation of an intramolecular hydrogen bond between the anomeric hydroxyl and the iminic nitrogen, thereby accounting for a true electronic effect. In addition, discrete solvation may help justify the observed preference for the β-anomer.

Outstanding Properties of the Hydration Shell around β-d-Glucose: A Computational Study

Ab initio molecular dynamics (AIMD) simulations have been performed on aqueous solutions of four simple sugars, α-d-glucose, β-d-glucose, α-d-mannose, and α-d-galactose. Hydrogen-bonding (HB) properties, such as the number of donor- and acceptor-type HB-s, and the lengths and strengths of hydrogen bonds between sugar and water molecules, have been determined. Related electronic properties, such as the dipole moments of water molecules and partial charges of the sugar O atoms, have also been calculated. The hydrophilic and hydrophobic shells were characterized by means of spatial distribution functions. β-d-Glucose was found to form the highest number of hydrophilic and the smallest number of hydrophobic connections to neighboring water molecules. The average sugar-water H-bond length was the shortest for β-d-glucose, which suggests that these are the strongest such H-bonds. Furthermore, β-d-glucose appears to stand out in terms of the symmetry properties of both its hydrophilic and hydrophobic hydration shells. In summary, in all aspects considered here, there seems to be a correlation between the distinct characteristics of β-d-glucose reported here and its outstanding solubility in water. Admittedly, our findings represent only some of the important factors that influence the solubility.

Glycans modulate lipid binding in Lili-Mip lipocalin protein: insights from molecular simulations and protein network analyses

The unique viviparous Pacific Beetle cockroaches provide nutrition to their embryo by secreting milk proteins Lili-Mip, a lipid-binding glycoprotein that crystallises in-vivo. The resolved in-vivo crystal structure of variably glycosylated Lili-Mip shows a classical Lipocalin fold with an eight-stranded antiparallel beta-barrel enclosing a fatty acid. The availability of physiologically unaltered glycoprotein structure makes Lili-Mip a very attractive model system to investigate the role of glycans on protein structure, dynamics, and function. Towards that end, we have employed all-atom molecular dynamics simulations on various glycosylated stages of a bound and free Lili-Mip protein and characterised the impact of glycans and the bound lipid on the dynamics of this glycoconjugate. Our work provides important molecular-level mechanistic insights into the role of glycans in the nutrient storage function of the Lili-Mip protein. Our analyses show that the glycans stabilise spatially proximal residues and regulate the low amplitude opening motions of the residues at the entrance of the binding pocket. Glycans also preserve the native orientation and conformational flexibility of the ligand. However, we find that either deglycosylation or glycosylation with high-mannose and paucimannose on the core glycans, which better mimic the natural insect glycosylation state, significantly affects the conformation and dynamics. A simple but effective distance- and correlation-based network analysis of the protein also reveals the key residues regulating the barrel's architecture and ligand binding characteristics in response to glycosylation.

Benchmarking Water Models in Molecular Dynamics of Protein-Glycosaminoglycan Complexes

Glycosaminoglycans (GAGs) made of repeating disaccharide units intricately engage with proteins, playing a crucial role in the spatial organization of the extracellular matrix (ECM) and the transduction of biological signals in cells to modulate a number of biochemical processes. Exploring protein-GAG interactions reveals several challenges for their analysis, namely, the highly charged and periodic nature of GAGs, their multipose binding, and the abundance of the interfacial water molecules in the protein-GAG complexes. Most of the studies on protein-GAG interactions are conducted using the TIP3P water model, and there are no data on the effect of various water models on the results obtained in molecular dynamics (MD) simulations of protein-GAG complexes. Hence, it is essential to perform a systematic analysis of different water models in MD simulations for these systems. In this work, we aim to evaluate the properties of the protein-GAG complexes in MD simulations using different explicit: TIP3P, SPC/E, TIP4P, TIP4PEw, OPC, and TIP5P and implicit: IGB = 1, 2, 5, 7, and 8 water models to find out which of them are best suited to study the dynamics of protein-GAG complexes. The FF14SB and GLYCAM06 force fields were used for the proteins and GAGs, respectively. The interactions of several GAG types, such as heparin, chondroitin sulfate, and hyaluronic acid with basic fibroblast growth factor, cathepsin K, and CD44 receptor, respectively, are investigated. The observed variations in different descriptors used to study the binding in these complexes emphasize the relevance of the choice of water models for the MD simulation of these complexes.

Insights into receptor structure and dynamics at the surface of living cells

Evaluating protein structures in living cells remains a challenge. Here, we investigate Interleukin-4 receptor alpha (IL-4Rα) into which the non-canonical amino acid bicyclo[6.1.0]nonyne-lysine (BCNK) is incorporated by genetic code expansion. Bioorthogonal click labeling is performed with tetrazine-conjugated dyes. To quantify the reaction yield in situ, we develop brightness-calibrated ratiometric imaging, a protocol where fluorescent signals in confocal multi-color images are ascribed to local concentrations. Screening receptor mutants bearing BCNK in the extracellular domain uncovered site-specific variations of both click efficiency and Interleukin-4 binding affinity, indicating subtle well-defined structural perturbations. Molecular dynamics and continuum electrostatics calculations suggest solvent polarization to determine site-specific variations of BCNK reactivity. Strikingly, signatures of differential click efficiency, measured for IL-4Rα in ligand-bound and free form, mirror sub-angstrom deformations of the protein backbone at corresponding locations. Thus, click efficiency by itself represents a remarkably informative readout linked to protein structure and dynamics in the native plasma membrane.

Modeling pyranose ring pucker in carbohydrates using machine learning and semi-empirical quantum chemical methods

Pyranose ring pucker is a key coordinate governing the structure, interactions and reactivity of carbohydrates. We assess the ability of the machine learning potentials, ANI-1ccx and ANI-2x, and the GFN2-xTB semiempirical quantum chemical method, to model ring pucker conformers of five monosaccharides and oxane in the gas phase. Relative to coupled-cluster quantum mechanical calculations, we find that ANI-1ccx most accurately reproduces the ring pucker energy landscape for these molecules, with a correlation coefficient r2 of 0.83. This correlation in relative energies lowers to values of 0.70 for ANI-2x and 0.60 for GFN2-xTB. The ANI-1ccx also provides the most accurate estimate of the energetics of the 4 C1 -to-1 C4 minimum energy pathway for the six molecules. All three models reproduce chair more accurately than non-chair geometries. Analysis of small model molecules suggests that the ANI-1ccx model favors puckers with equatorial hydrogen bonding substituents; that ANI-2x and GFN2-xTB models overstabilize conformers with axially oriented groups; and that the endo-anomeric effect is overestimated by the machine learning models and underestimated via the GFN2-xTB method. While the pucker conformers considered in this study correspond to a gas phase environment, the accuracy and computational efficiency of the ANI-1ccx approach in modeling ring pucker in vacuo provides a promising basis for future evaluation and application to condensed phase environments.

Extending the Martini 3 Coarse-Grained Force Field to Carbohydrates

Carbohydrates play an essential role in a large number of chemical and biochemical processes. High structural diversity and conformational heterogeneity make it problematic to link their measurable properties to molecular features. Molecular dynamics simulations carried out at the level of classical force fields are routinely applied to study the complex processes occurring in carbohydrate-containing systems, while the usefulness of such simulations relies on the accuracy of the underlying theoretical model. In this article, we present the coarse-grained force field dedicated to glucopyranose-based carbohydrates and compatible with the recent version of the Martini force field (v. 3.0). The parameterization was based on optimizing bonded and nonbonded parameters with a reference to the all-atom simulation results and the experimental data. Application of the newly developed coarse-grained carbohydrate model to oligosaccharides curdlan and cellulose displays spontaneous formation of aggregates of experimentally identified features. In contact with other biomolecules, the model is capable of recovering the protective effect of glucose monosaccharides on a lipid bilayer and correctly identifying the binding pockets in carbohydrate-binding proteins. The features of the newly proposed model make it an excellent candidate for further extensions, aimed at modeling more complex, functionalized, and biologically relevant carbohydrates.

Multifaceted Computational Modeling in Glycoscience

Glycoscience assembles all the scientific disciplines involved in studying various molecules and macromolecules containing carbohydrates and complex glycans. Such an ensemble involves one of the most extensive sets of molecules in quantity and occurrence since they occur in all microorganisms and higher organisms. Once the compositions and sequences of these molecules are established, the determination of their three-dimensional structural and dynamical features is a step toward understanding the molecular basis underlying their properties and functions. The range of the relevant computational methods capable of addressing such issues is anchored by the specificity of stereoelectronic effects from quantum chemistry to mesoscale modeling throughout molecular dynamics and mechanics and coarse-grained and docking calculations. The Review leads the reader through the detailed presentations of the applications of computational modeling. The illustrations cover carbohydrate-carbohydrate interactions, glycolipids, and N- and O-linked glycans, emphasizing their role in SARS-CoV-2. The presentation continues with the structure of polysaccharides in solution and solid-state and lipopolysaccharides in membranes. The full range of protein-carbohydrate interactions is presented, as exemplified by carbohydrate-active enzymes, transporters, lectins, antibodies, and glycosaminoglycan binding proteins. A final section features a list of 150 tools and databases to help address the many issues of structural glycobioinformatics.

Molecular simulations of complex carbohydrates and glycoconjugates

Complex carbohydrates (glycans) are the most abundant and versatile biopolymers in nature. The broad diversity of biochemical functions that carbohydrates cover is a direct consequence of the variety of 3D architectures they can adopt, displaying branched or linear arrangements, widely ranging in sizes, and with the highest diversity of building blocks of any other natural biopolymer. Despite this unparalleled complexity, a common denominator can be found in the glycans' inherent flexibility, which hinders experimental characterization, but that can be addressed by high-performance computing (HPC)-based molecular simulations. In this short review, I present and discuss the state-of-the-art of molecular simulations of complex carbohydrates and glycoconjugates, highlighting methodological strengths and weaknesses, important insights through emblematic case studies, and suggesting perspectives for future developments.

How molecular modelling can better broaden the understanding of glycosylations

Glycosylations are among the most ubiquitous post-translational modifications (PTMs) in proteins, and the effects of their perturbations are seen in various diseases such as cancers, diabetes and arthritis to name a few. Yet they remain one of the most enigmatic aspects of protein structure and function. On the other hand, molecular modelling techniques have been rapidly bridging this knowledge gap since the last decade. In this review, we discuss how these techniques have proven to be indispensable for a better understanding of the role of glycosylations in glycoprotein structure and function.

NMR and MD Analysis of the Bonding Interaction of Vancomycin with Muramyl Pentapeptide

The article describes an NMR spectroscopy study of interactions between vancomycin and a muramyl pentapeptide in two complexes: vancomycin and a native muramyl pentapeptide ended with D-alanine (MPP-D-Ala), and vancomycin and a modified muramyl pentapeptide ended with D-serine (MPP-D-Ser). The measurements were made in a 9:1 mixture of H₂O and D₂O. The obtained results confirmed the presence of hydrogen bonds previously described in the literature. At the same time, thanks to the pentapeptide model used, we were able to prove the presence of two more hydrogen bonds formed by the side chain amino group of L-lysine and oxygen atoms from the vancomycin carboxyl and amide groups. This type of interaction has not been described before. The existence of these hydrogen bonds was confirmed by the ¹H NMR and molecular modeling. The formation of these bonds incurs additional through-space interactions, visible in the NOESY spectrum, between the protons of the L-lysine amino group and a vancomycin-facing hydrogen atom in the benzylic position. The presence of such interactions was also confirmed by molecular dynamics trajectory analysis.

CHARMM-GUI Drude prepper for molecular dynamics simulation using the classical Drude polarizable force field

Explicit treatment of electronic polarizability in empirical force fields (FFs) represents an extension over a traditional additive or pairwise FF and provides a more realistic model of the variations in electronic structure in condensed phase, macromolecular simulations. To facilitate utilization of the polarizable FF based on the classical Drude oscillator model, Drude Prepper has been developed in CHARMM-GUI. Drude Prepper ingests additive CHARMM protein structures file (PSF) and pre-equilibrated coordinates in CHARMM, PDB, or NAMD format, from which the molecular components of the system are identified. These include all residues and patches connecting those residues along with water, ions, and other solute molecules. This information is then used to construct the Drude FF-based PSF using molecular generation capabilities in CHARMM, followed by minimization and equilibration. In addition, inputs are generated for molecular dynamics (MD) simulations using CHARMM, GROMACS, NAMD, and OpenMM. Validation of the Drude Prepper protocol and inputs is performed through conversion and MD simulations of various heterogeneous systems that include proteins, nucleic acids, lipids, polysaccharides, and atomic ions using the aforementioned simulation packages. Stable simulations are obtained in all studied systems, including 5 μs simulation of ubiquitin, verifying the integrity of the generated Drude PSFs. In addition, the ability of the Drude FF to model variations in electronic structure is shown through dipole moment analysis in selected systems. The capabilities and availability of Drude Prepper in CHARMM-GUI is anticipated to greatly facilitate the application of the Drude FF to a range of condensed phase, macromolecular systems.

A Computational Perspective on Molecular Recognition by Galectins

This article presents an overview of recent computational studies dedicated to the analysis of binding between galectins and small-molecule ligands. We first present a summary of the most popular simulation techniques adopted for calculating binding poses and binding energies, and then discuss relevant examples reported in the literature for the three main classes of galectins (dimeric, tandem and chimera). We show that simulation of galectin-ligand interactions is a mature field which has proven invaluable for completing and unraveling experimental observations. Future perspectives to further improve the accuracy and cost-effectiveness of existing computational approaches will involve the development of new schemes to account for solvation and entropy effects, which represent the main current limitations to the accuracy of computational results.

Fighting viruses with computers, right now

The synergistic conjunction of various technological revolutions with the accumulated knowledge and workflows is rapidly transforming several scientific fields. Particularly, Virology can now feed from accurate physical models, polished computational tools, and massive computational power to readily integrate high-resolution structures into biological representations of unprecedented detail. That preparedness allows for the first time to get crucial information for vaccine and drug design from in-silico experiments against emerging pathogens of worldwide concern at relevant action windows. The present work reviews some of the main milestones leading to these breakthroughs in Computational Virology, providing an outlook for future developments in capacity building and accessibility to computational resources.

Stochastic Modelling of 13C NMR Spin Relaxation Experiments in Oligosaccharides

A framework for the stochastic description of relaxation processes in flexible macromolecules including dissipative effects has been recently introduced, starting from an atomistic view, describing the joint relaxation of internal coordinates and global degrees of freedom, and depending on parameters recoverable from classic force fields (energetics) and medium modelling at the continuum level (friction tensors). The new approach provides a rational context for the interpretation of magnetic resonance relaxation experiments. In its simplest formulation, the semi-flexible Brownian (SFB) model has been until now shown to reproduce correctly correlation functions and spectral densities related to orientational properties obtained by direct molecular dynamics simulations of peptides. Here, for the first time, we applied directly the SFB approach to the practical evaluation of high-quality ¹³C nuclear magnetic resonance relaxation parameters, T1 and T2, and the heteronuclear NOE of several oligosaccharides, which were previously interpreted on the basis of refined ad hoc modelling. The calculated NMR relaxation parameters were in agreement with the experimental data, showing that this general approach can be applied to diverse classes of molecular systems, with the minimal usage of adjustable parameters.

Comparison of Carbohydrate Force Fields in Molecular Dynamics Simulations of Protein-Carbohydrate Complexes

In this paper, we present the results of molecular dynamics simulations aimed at critical comparison of classical, biomolecular force fields (FFs) in the context of their capabilities to describe the structural and thermodynamic features of carbohydrate-protein interactions. We have considered the three main families of FFs (CHARMM, GROMOS, and GLYCAM/AMBER) by applying them to investigate the seven different carbohydrate-protein complexes. The results indicate that although the qualitative pattern of several structural descriptors (intermolecular hydrogen bonding, ligand dynamic location, etc.) is conserved among the compared FFs, there also exists a number of significant divergences (mainly the patterns of contacts between particular amino acid residues and bound carbohydrate). The carbohydrate-protein unbinding free energies also vary from one FF to another, displaying diversified trends in deviations from the experimental data. The magnitude of those deviations is not negligible and indicates the need for refinement in the currently existing combinations of carbohydrate- and protein-dedicated biomolecular force fields. In spite of the lack of explicit functional terms responsible for the corresponding intermolecular forces, all tested FFs are capable of adequately reproducing the CH-π interactions, crucial for carbohydrate-protein binding.

Rotational Profiler: A Fast, Automated, and Interactive Server to Derive Torsional Dihedral Potentials for Classical Molecular Simulations

Rotational Profiler provides an analytical algorithm to compute sets of classical torsional dihedral parameters by fitting an empirical energy profile to a reference one that can be obtained experimentally or by quantum-mechanical methods. The resulting profiles are compatible with the functional forms in the most widely used biomolecular force fields (e.g., GROMOS, AMBER, OPLS, and CHARMM). The linear least-squares regression method is used to generate sets of parameters that best satisfy the fitting. Rotational Profiler is free to use, analytical, and force field/package independent. The formalism is herein described, and its usage, in an interactive and automated manner, is made available as a Web server at http://rotprof.lncc.br.

Three-Dimensional Structures of Carbohydrates and Where to Find Them

Analysis and systematization of accumulated data on carbohydrate structural diversity is a subject of great interest for structural glycobiology. Despite being a challenging task, development of computational methods for efficient treatment and management of spatial (3D) structural features of carbohydrates breaks new ground in modern glycoscience. This review is dedicated to approaches of chemo- and glyco-informatics towards 3D structural data generation, deposition and processing in regard to carbohydrates and their derivatives. Databases, molecular modeling and experimental data validation services, and structure visualization facilities developed for last five years are reviewed.

Computational tools for drawing, building and displaying carbohydrates: a visual guide

Drawing and visualisation of molecular structures are some of the most common tasks carried out in structural glycobiology, typically using various software. In this perspective article, we outline developments in the computational tools for the sketching, visualisation and modelling of glycans. The article also provides details on the standard representation of glycans, and glycoconjugates, which helps the communication of structure details within the scientific community. We highlight the comparative analysis of the available tools which could help researchers to perform various tasks related to structure representation and model building of glycans. These tools can be useful for glycobiologists or any researcher looking for a ready to use, simple program for the sketching or building of glycans.

Combining scattering analysis and atomistic simulation of wood-water interactions

Molecular-scale interactions between water and cellulose microfibril bundles in plant cell walls are not fully understood, despite their crucial role for many applications of plant biomass. Recent advances in X-ray and neutron scattering analysis allow more accurate interpretation of experimental data from wood cell walls. At the same time, microfibril bundles including hemicelluloses and water can be modelled at atomistic resolution. Computing scattering patterns from atomistic models enables a new, complementary approach to decipher some of the most fundamental questions at this level of the hierarchical cell wall structure. This article introduces studies related to moisture behavior of wood with small/wide-angle X-ray/neutron scattering and atomistic simulations, recent attempts to combine these two approaches, and perspectives and open questions for future research using this powerful combination. Finally, we discuss the opportunities of the combined method in relation to applications of lignocellulosic materials.

ADD Force Field for Sugars and Polyols: Predicting the Additivity of Protein-Osmolyte Interaction

The protein–osmolyte interaction has been shown experimentally to follow an additive construct, where the individual osmolyte–backbone and osmolyte–side-chain interactions contribute to the overall conformational stability of proteins. Here, we computationally reconstruct this additive relation using molecular dynamics simulations, focusing on sugars and polyols, including sucrose and sorbitol, as model osmolytes. A new set of parameters (ADD) is developed for this purpose, using the individual Kirkwood–Buff integrals for sugar–backbone and sugar–side-chain interactions as target experimental data. We show that the ADD parameters can reproduce the additivity of protein–sugar interactions and correctly predict sucrose and sorbitol self-association and their interaction with water. The accurate description of the separate osmolyte–backbone and osmolyte–side-chain contributions also automatically translates into a good prediction of preferential exclusion from the surface of ribonuclease A and α-chymotrypsinogen A. The description of sugar polarity is improved compared to previous force fields, resulting in closer agreement with the experimental data and better compatibility with charged groups, such as the guanidinium moiety. The ADD parameters are developed in combination with the CHARMM36m force field for proteins, but good compatibility is also observed with the AMBER 99SB-ILDN and the OPLS-AA force fields. Overall, exploiting the additivity of protein–osmolyte interactions is a promising approach for the development of new force fields.

Rigorous analysis of free solution glycosaminoglycan dynamics using simple, new tools

Heparin/heparan sulfates (H/HS) are ubiquitous biopolymers that interact with many proteins to induce a range of biological functions. Unfortunately, how these biopolymers recognize their preferred protein targets remain poorly understood. It is suggested that computational simulations offer attractive avenues but a number of challenges, e.g., difficulty of selecting a comprehensive force field, few simple tools to interpret data, among others, remain. This work addresses several such challenges so as to help ease the implementation and analysis of computational experiments. First, this work presents a rigorous comparison of two different recent force fields, CHARMM36 and GLYCAM06, for H/HS studies. Second, it introduces two new straightforward parameters, i.e., end-to-end distance and minimum volume enclosing ellipsoid, to understand the myriad conformational forms of oligosaccharides that evolve over time in water. Third, it presents an application to elucidate the number and nature of inter and intramolecular, nondirect bridging water molecules, which help stabilize unique forms of H/HS. The results show that nonspecialists can use either CHARMM36 or GLYCAM06 force fields because both gave comparable results, albeit with small differences. The comparative study shows that the HS hexasaccharide samples a range of conformations with nearly equivalent energies, which could be the reason for its recognition by different proteins. Finally, analysis of the nondirect water bridges across the dynamics trajectory shows their importance in stabilization of certain conformational forms, which may become important for protein recognition. Overall, the work aids nonspecialists employ computational studies for understanding the solution behavior of H/HS.

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.

Aggregation behaviors of thermo-responsive methylcellulose in water: A molecular dynamics simulation study

The aggregation behaviors of methylcellulose (MC) in aqueous solution were investigated using all-atom molecular dynamic simulations (MD). The interactions between MC chains and water molecules at different temperatures were investigated by a series of MD analyses, such as the solvent accessible surface area, number of hydrogen bonds, radial distribution functions and the interaction energies. Constant temperature simulations and heating simulations of MC aqueous solution were carried out in this work. In the simulations at three constant temperatures (25 °C, 50 °C and 75 °C), the aggregation behaviors of MC chains were affected by the temperature. In the heating simulation (25 °C ∼ 75 °C), temperature increases were accompanied by decreases in interactions between MC and water molecules, and by increases in interactions between MC chains, which led to the aggregation of MC chains. The degree of aggregation of MC chains increased with the rise of temperature.

Hydration and Dispersion Forces in Hydroxypropylcellulose Phase Behavior

Many-body polarization and hydration forces can strongly affect the equilibrium structure and energetics of mixed phases. Accurately reproducing both forces presents a challenge to force field models because it requires balancing hydrogen bonding at short range with many-body orientational order and dispersive attraction at long range. This work reports the first comparison of experimental measurements of the pressure-area isotherm for hydroxypropylcellulose (HPC) against molecular dynamics results with four different force field models-united-atom, all-atom (OPLS and CHARMM), and Drude oscillator models. All force fields exhibit the experimentally determined, exponentially shaped repulsive force at short range. Above a critical temperature of about 40 °C and a lattice spacing of around 14 Å, HPC experiments show a reversible, heat-induced polymer aggregation into an ordered phase driven by loss of water. The nonpolarizable force fields do not display the critical point and instead show biphasic behavior at all temperatures tested. This indicates net attractive forces at intermediate lattice spacings. In contrast, the Drude polarizable force field shows positive osmotic pressure and a single, homogeneous phase over all temperatures and spacings tested. Analysis of structural data from our simulations provides several clues to help interpret these findings. Although all force fields show similar water-water hydrogen bond numbers in the mixed phase, the polarizable model predicts that water-HPC hydrogen bonds are much more favorable than HPC-HPC hydrogen bonds when polymers are dispersed. At high density, water is driven out and replaced by HPC-HPC hydrogen bonds. The polarizable force field shows that both effects have a stronger dependence on polymer density than any of the nonpolarizable models. Our observations support the conclusion that hydration forces are coupled to the polymer coordination number by local, structural waters and that long-range dispersive attraction is overestimated by pairwise additive models.

Structural Aspects of the O-glycosylation Linkage in Glycopeptides via MD Simulations and Comparison with NMR Experiments

A powerful conformational searching and enhanced sampling simulation method, and unbiased molecular dynamics simulations have been used along with NMR spectroscopic observables to provide a detailed structural view of O-glycosylation. For four model systems, the force-field parameters can accurately predict experimental NMR observables (J couplings and NOE's). This enables us to derive conclusions based on the generated ensembles, in which O-glycosylation affects the peptide backbone conformation by forcing it towards to an extended conformation. An exception is described for β-GalNAc-Thr where the α content is increased and stabilized via hydrogen bonding between the sugar and the peptide backbone, which was not observed in the rest of the studied systems. These observations might offer an explanation for the evolutionary preference of α-linked GalNAc glycosylation instead of a β link.

Docking software performance in protein-glycosaminoglycan systems

We present a benchmarking study for protein-glycosaminoglycan systems with eight docking programs: Dock, rDock, ClusPro, PLANTS, HADDOCK, Hex, SwissDock and ATTRACT. We used a non-redundant representative dataset of 28 protein-glycosaminoglycan complexes with experimentally available structures, where a glycosaminoglycan ligand was longer than a trimer. Overall, the ligand binding poses could be correctly predicted in many cases by the tested docking programs, however the ranks of the docking poses are often poorly assigned. Our results suggest that Dock program performs best in terms of the pose placement, has the most suitable scoring function, and its performance did not depend on the ligand size. This suggests that the implementation of the electrostatics as well as the shape complementarity procedure in Dock are the most suitable for docking glycosaminoglycan ligands. We also analyzed how free energy patterns of the benchmarking complexes affect the performance of the evaluated docking software.

Perspective on computational simulations of glycosaminoglycans

Glycosaminoglycans (GAGs) represent a formidable frontier for chemists, biochemists, biologists, medicinal chemists and drug delivery specialists because of massive structural complexity. GAGs are arguably the most complex, natural linear biopolymers with theoretical diversity orders of magnitude higher than proteins and nucleic acids. Yet, this diversity remains generally untapped. Computational approaches offer major routes to understand GAG structure and dynamics so as to enable novel applications of these biopolymers. In fact, computational algorithms, softwares, online tools and techniques have reached a level of sophistication that help understand atomistic details of conformational variation and protein recognition of individual GAG sequences. This review describes current approaches and challenges in computational study of GAGs. It presents a history of major findings since the earliest mention of GAGs (the 1960s), the development of parameters and force fields specific for GAGs, and the application of these tools in understanding GAG structure-function relationship. This review also presents a section on how to perform simulation of GAGs, which is directed toward researchers interested in entering this promising field with potential to impact therapy.

Molecular Dynamics Simulation for Mechanism Elucidation of Food Processing and Safety: State of the Art

Molecular dynamics (MD) simulation is a useful technique to study the interaction between molecules and how they are affected by various processes and processing conditions. This review summarizes the application of MD simulations in food processing and safety, with an emphasis on the effects that emerging nonthermal technologies (for example, high hydrostatic pressure, pulsed electric field) have on the molecular and structural characteristics of foods and biomaterials. The advances and potential projection of MD simulations in the science and engineering aspects of food materials are discussed and focused on research work conducted to study the effects of emerging technologies on food components. It is expected by showing key case studies that it will stir novel developments as a valuable tool to study the effects of emerging food technologies on biomaterials. This review is useful to food researchers and the food industry, as well as researchers and practitioners working on flavor and nutraceutical encapsulations, dietary carbohydrate product developments, modified starches, protein engineering, and other novel food applications.

Proper balance of solvent-solute and solute-solute interactions in the treatment of the diffusion of glucose using the Drude polarizable force field

Motivated by underestimation of the diffusion constant of glucose in aqueous solution at high glucose concentrations we performed additional optimization of the Drude polarizable hexopyranose monosaccharide force field. This indicated aggregation of the glucose at higher concentrations, which is a concern for studies of complex glycan systems such as the HIV Envelope where high effective concentrations of sugars are present. High-level quantum mechanical calculations were undertaken on water monohydrate-glucose interactions, on water cluster-glucose interactions and on glucose-glucose dimers in stacked (parallel) and perpendicular orientations. Optimization of the nonbond and dihedral parameters targeting these data yielded a revised model that showed improved agreement with experimental aqueous diffusion data. However, limitations in the diffusion constants were still present. These were due to the SWM4-NDP inherently overestimating the diffusion constant of water, a problem that was validated by calculation of the aqueous diffusion constants using the SWM6-NDP water model. In addition, results show the water diffusion constant to be significantly overestimated at high glucose concentrations though the glucose diffusion is in satisfactory agreement with experiment. These results indicate the subtle balance of water-sugar, water-water and sugar-sugar interactions that needs to be properly modeled to account for the full range of aqueous behavior of sugars in aqueous solution.

Validation and Comparison of Force Fields for Native Cyclodextrins in Aqueous Solution

Molecular dynamics simulations of native α-, β-, and γ-cyclodextrin in aqueous solution have been conducted with the goal to investigate the performance of the CHARMM36 force field, the AMBER-compatible q4md-CD force field, and five variants of the GROMOS force field. The properties analyzed are structural parameters derived from X-ray diffraction and NMR experiments as well as hydrogen bonds and hydration patterns, including hydration free enthalpies. Recent revisions of the torsional-angle parameters for carbohydrate systems within the GROMOS family of force fields lead to a significant improvement of the agreement between simulated and experimental NMR data. Therefore, we recommend using the variant 53A6_GLYC instead of 53A6 and 56A6_{CARBO_R} or 2016H66 instead of 56A6_CARBO to simulate cyclodextrins in solution. The CHARMM36 and q4md-CD force fields show a similar performance as the three recommended GROMOS parameter sets. A significant difference is the more flexible nature of the cyclodextrins modeled with the CHARMM36 and q4md-CD force fields compared to the three recommended GROMOS parameter sets.

Predicting Accurate Solvation Free Energy in n-Octanol Using 3D-RISM-KH Molecular Theory of Solvation: Making Right Choices

Molecular theory of solvation, a.k.a., three-dimensional reference interaction site model theory of solvation with Kovalenko-Hirata closure relation (3D-RISM-KH), is an accurate and fast theory predicting solvation free energy and structure. Here we report a benchmark study of n-octanol solvation free energy calculations using this theory. The choice of correct force field parameters is quintessential for the success of 3D-RISM theory, and we present a guideline to obtain them for n-octanol solvent. Our best prediction of the solvation free energy on a set of 205 small organic molecules supplemented with the so-called "universal correction" scheme yields relative mean unsigned error of 0.94 kcal/mol against the reported database. The best agreement is obtained with the united atom (UA) type force field parametrization of n-octanol with the van der Waals parameters of hydroxyl hydrogen reported by Kobryn et al. [ Kobryn , A. E. ; Kovalenko , A. J. Chem. Phys. 2008 , 129 , 134701 ].

Modification of 56ACARBO force field for molecular dynamic calculations of chitosan and its derivatives

The GROMOS 56A_CARBO force field for the description of carbohydrates was modified for calculations of chitosan (poly-1,4-(N-acetyl)-β-D-glucopyranosamine-2) with protonated and non-protonated amino groups and its derivatives. Additional parameterization was developed on the basis of quantum chemical calculations. The modified force field (56A_{CARBO_CHT}) allows performing the molecular dynamic calculations of chitosans with different degrees of protonation corresponding to various acidity of medium. Test calculations of the conformational transitions in the chitosan rings and polymeric chains as well as the chitosan nanocrystal dissolution demonstrate good agreement with experimental data. Graphical abstract The GROMOS 56A_{CARBO_CHT} force field allows performing the molecular dynamic calculations of chitosans with different types of amio-group: free, protonated, substituted.