Comparison of different force fields for the study of disaccharides

Advancing plant cell wall modelling: Atomistic insights into cellulose, disordered cellulose, and hemicelluloses - A review

The complexity of plant cell walls on different hierarchical levels still impedes the detailed understanding of biosynthetic pathways, interferes with processing in industry and finally limits applicability of cellulose materials. While there exist many challenges to readily accessing these hierarchies at (sub-) angström resolution, the development of advanced computational methods has the potential to unravel important questions in this field. Here, we summarize the contributions of molecular dynamics simulations in advancing the understanding of the physico-chemical properties of natural fibres. We aim to present a comprehensive view of the advancements and insights gained from molecular dynamics simulations in the field of carbohydrate polymers research. The review holds immense value as a vital reference for researchers seeking to undertake atomistic simulations of plant cell wall constituents. Its significance extends beyond the realm of molecular modeling and chemistry, as it offers a pathway to develop a more profound comprehension of plant cell wall chemistry, interactions, and behavior. By delving into these fundamental aspects, the review provides invaluable insights into future perspectives for exploration. Researchers within the molecular modeling and carbohydrates community can greatly benefit from this resource, enabling them to make significant strides in unraveling the intricacies of plant cell wall dynamics.

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.

The Giardia lamblia ribosome structure reveals divergence in several biological pathways and the mode of emetine function

Giardia lamblia is a deeply branching protist and a human pathogen. Its unusual biology presents the opportunity to explore conserved and fundamental molecular mechanisms. We determined the structure of the G. lamblia 80S ribosome bound to tRNA, mRNA, and the antibiotic emetine by cryo-electron microscopy, to an overall resolution of 2.49 Å. The structure reveals rapidly evolving protein and nucleotide regions, differences in the peptide exit tunnel, and likely altered ribosome quality control pathways. Examination of translation initiation factor binding sites suggests these interactions are conserved despite a divergent initiation mechanism. Highlighting the potential of G. lamblia to resolve conserved biological principles; our structure reveals the interactions of the translation inhibitor emetine with the ribosome and mRNA, thus providing insight into the mechanism of action for this widely used antibiotic. Our work defines key questions in G. lamblia and motivates future experiments to explore the diversity of eukaryotic gene regulation.

Computational 3D Modeling-Based Identification of Inhibitors Targeting Cysteine Covalent Bond Catalysts for JAK3 and CYP3A4 Enzymes in the Treatment of Rheumatoid Arthritis

This work aimed to find new inhibitors of the CYP3A4 and JAK3 enzymes, which are significant players in autoimmune diseases such as rheumatoid arthritis. Advanced computer-aided drug design techniques, such as pharmacophore and 3D-QSAR modeling, were used. Two strong 3D-QSAR models were created, and their predictive power was validated by the strong correlation (R2 values > 80%) between the predicted and experimental activity. With an ROC value of 0.9, a pharmacophore model grounded in the DHRRR hypothesis likewise demonstrated strong predictive ability. Eight possible inhibitors were found, and six new inhibitors were designed in silico using these computational models. The pharmacokinetic and safety characteristics of these candidates were thoroughly assessed. The possible interactions between the inhibitors and the target enzymes were made clear via molecular docking. Furthermore, MM/GBSA computations and molecular dynamics simulations offered insightful information about the stability of the binding between inhibitors and CYP3A4 or JAK3. Through the integration of various computational approaches, this study successfully identified potential inhibitor candidates for additional investigation and efficiently screened compounds. The findings contribute to our knowledge of enzyme-inhibitor interactions and may help us create more effective treatments for autoimmune conditions like rheumatoid arthritis.

Conformational energies of reference organic molecules: benchmarking of common efficient computational methods against coupled cluster theory

We selected 145 reference organic molecules that include model fragments used in computer-aided drug design. We calculated 158 conformational energies and barriers using force fields, with wide applicability in commercial and free softwares and extensive application on the calculation of conformational energies of organic molecules, e.g. the UFF and DREIDING force fields, the Allinger's force fields MM3-96, MM3-00, MM4-8, the MM2-91 clones MMX and MM+, the MMFF94 force field, MM4, ab initio Hartree-Fock (HF) theory with different basis sets, the standard density functional theory B3LYP, the second-order post-HF MP2 theory and the Domain-based Local Pair Natural Orbital Coupled Cluster DLPNO-CCSD(T) theory, with the latter used for accurate reference values. The data set of the organic molecules includes hydrocarbons, haloalkanes, conjugated compounds, and oxygen-, nitrogen-, phosphorus- and sulphur-containing compounds. We reviewed in detail the conformational aspects of these model organic molecules providing the current understanding of the steric and electronic factors that determine the stability of low energy conformers and the literature including previous experimental observations and calculated findings. While progress on the computer hardware allows the calculations of thousands of conformations for later use in drug design projects, this study is an update from previous classical studies that used, as reference values, experimental ones using a variety of methods and different environments. The lowest mean error against the DLPNO-CCSD(T) reference was calculated for MP2 (0.35 kcal mol-1), followed by B3LYP (0.69 kcal mol-1) and the HF theories (0.81-1.0 kcal mol-1). As regards the force fields, the lowest errors were observed for the Allinger's force fields MM3-00 (1.28 kcal mol-1), ΜΜ3-96 (1.40 kcal mol-1) and the Halgren's MMFF94 force field (1.30 kcal mol-1) and then for the MM2-91 clones MMX (1.77 kcal mol-1) and MM+ (2.01 kcal mol-1) and MM4 (2.05 kcal mol-1). The DREIDING (3.63 kcal mol-1) and UFF (3.77 kcal mol-1) force fields have the lowest performance. These model organic molecules we used are often present as fragments in drug-like molecules. The values calculated using DLPNO-CCSD(T) make up a valuable data set for further comparisons and for improved force field parameterization.

Computer-Aided Drug Design of Novel Derivatives of 2-Amino-7,9-dihydro-8H-purin-8-one as Potent Pan-Janus JAK3 Inhibitors

Rheumatoid arthritis (RA) remains one of the most prevalent autoimmune diseases worldwide. Janus kinase 3 (JAK3) is an essential enzyme for treating autoimmune diseases, including RA. Molecular modeling techniques play a crucial role in the search for new drugs by reducing time delays. In this study, the 3D-QSAR approach is employed to predict new JAK3 inhibitors. Two robust models, both field-based with R2 = 0.93, R = 0.96, and Q2 = 87, and atom-based with R2 = 0.94, R = 0.97, and Q2 = 86, yielded good results by identifying groups that may readily direct their interaction. A reliable pharmacophore model, DHRRR1, was provided in this work to enable the clear characterization of chemical features, leading to the design of 13 inhibitors with their pIC50 values. The DHRRR1 model yielded a validation result with a ROC value of 0.87. Five promising inhibitors were selected for further study based on an ADMET analysis of their pharmacokinetic properties and covalent docking (CovDock). Compared to the FDA-approved drug tofacitinib, the pharmaceutical features, binding affinity and stability of the inhibitors were analyzed through CovDock, 300 ns molecular dynamics simulations, free energy binding calculations and ADMET predictions. The results show that the inhibitors have strong binding affinity, stability and favorable pharmaceutical properties. The newly predicted molecules, as JAK3 inhibitors for the treatment of RA, are promising candidates for use as drugs.

Polyguluronate simulations shed light onto the therapeutic action of OligoG CF-5/20

Chronic mucoid P. aeruginosa cystic fibrosis (CF) lung infections are associated with the development of a biofilm composed of anionic acetylated exopolysaccharide (EPS) alginate, electrostatically stabilised by extracellular Ca2+ ions. OligoG CF-5/20, a low molecular weight guluronate rich oligomer, is emerging as a novel therapeutic capable of disrupting mature P. aeruginosa biofilms. However, its method of therapeutic action on the mucoid biofilm EPS is not definitively known at a molecular level. This work, utilising molecular dynamics (MD) and Density-Functional Theory (DFT), has revealed that OligoG CF-5/20 interaction with the EPS is facilitated solely through bridging Ca2+ ions, which are not liberated from their native EPS binding sites upon OligoG CF-5/20 dispersal, suggesting that OligoG CF-5/20 does not cause disruptions to mature P. aeruginosa biofilms through breaking EPS-Ca2+-EPS ionic cross-links. Rather it is likely that the therapeutic activity arises from sequestering free Ca2+ ions and preventing further Ca2+ induced EPS aggregation.

Identification of 1H-purine-2,6-dione derivative as a potential SARS-CoV-2 main protease inhibitor: molecular docking, dynamic simulations, and energy calculations

The rapid spread of the coronavirus since its first appearance in 2019 has taken the world by surprise, challenging the global economy, and putting pressure on healthcare systems across the world. The introduction of preventive vaccines only managed to slow the rising death rates worldwide, illuminating the pressing need for developing effective antiviral therapeutics. The traditional route of drug discovery has been known to require years which the world does not currently have. In silico approaches in drug design have shown promising results over the last decade, helping to decrease the required time for drug development. One of the vital non-structural proteins that are essential to viral replication and transcription is the SARS-CoV-2 main protease (Mpro). Herein, using a test set of recently identified COVID-19 inhibitors, a pharmacophore was developed to screen 20 million drug-like compounds obtained from a freely accessible Zinc database. The generated hits were ranked using a structure based virtual screening technique (SBVS), and the top hits were subjected to in-depth molecular docking studies and MM-GBSA calculations over SARS-COV-2 Mpro. Finally, the most promising hit, compound (1), and the potent standard (III) were subjected to 100 ns molecular dynamics (MD) simulations and in silico ADME study. The result of the MD analysis as well as the in silico pharmacokinetic study reveal compound 1 to be a promising SARS-Cov-2 MPro inhibitor suitable for further development.

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.

Combining Computational Chemistry and Crystallography for a Better Understanding of the Structure of Cellulose

The approaches in this article seek to enhance understanding of cellulose at the molecular level, independent of the source and the particular crystalline form of cellulose. Four main areas of structure research are reviewed. Initially, the molecular shape is inferred from the crystal structures of many small molecules that have β-(1→4) linkages. Then, conformational analyses with potential energy calculations of cellobiose are covered, followed by the use of Atoms-In-Molecules theory to learn about interactions in experimental and theoretical structures. The last section covers models of cellulose nanoparticles. Controversies addressed include the stability of twofold screw-axis conformations, the influence of different computational methods, the predictability of crystalline conformations by studies of isolated molecules, and the twisting of model cellulose crystals.

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.

Benchmark assessment of molecular geometries and energies from small molecule force fields

Background: Force fields are used in a wide variety of contexts for classical molecular simulation, including studies on protein-ligand binding, membrane permeation, and thermophysical property prediction. The quality of these studies relies on the quality of the force fields used to represent the systems. Methods: Focusing on small molecules of fewer than 50 heavy atoms, our aim in this work is to compare nine force fields: GAFF, GAFF2, MMFF94, MMFF94S, OPLS3e, SMIRNOFF99Frosst, and the Open Force Field Parsley, versions 1.0, 1.1, and 1.2. On a dataset comprising 22,675 molecular structures of 3,271 molecules, we analyzed force field-optimized geometries and conformer energies compared to reference quantum mechanical (QM) data. Results: We show that while OPLS3e performs best, the latest Open Force Field Parsley release is approaching a comparable level of accuracy in reproducing QM geometries and energetics for this set of molecules. Meanwhile, the performance of established force fields such as MMFF94S and GAFF2 is generally somewhat worse. We also find that the series of recent Open Force Field versions provide significant increases in accuracy. Conclusions: This study provides an extensive test of the performance of different molecular mechanics force fields on a diverse molecule set, and highlights two (OPLS3e and OpenFF 1.2) that perform better than the others tested on the present comparison. Our molecule set and results are available for other researchers to use in testing.

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.

Comparison of Methods for Bulk Automated Simulation of Glycosidic Bond Conformations

Six empirical force fields were tested for applicability to calculations for automated carbohydrate database filling. They were probed on eleven disaccharide molecules containing representative structural features from widespread classes of carbohydrates. The accuracy of each method was queried by predictions of nuclear Overhauser effects (NOEs) from conformational ensembles obtained from 50 to 100 ns molecular dynamics (MD) trajectories and their comparison to the published experimental data. Using various ranking schemes, it was concluded that explicit solvent MM3 MD yielded non-inferior NOE accuracy with newer GLYCAM-06, and ultimately PBE0-D3/def2-TZVP (Triple-Zeta Valence Polarized) Density Functional Theory (DFT) simulations. For seven of eleven molecules, at least one empirical force field with explicit solvent outperformed DFT in NOE prediction. The aggregate of characteristics (accuracy, speed, and compatibility) made MM3 dynamics with explicit solvent at 300 K the most favorable method for bulk generation of disaccharide conformation maps for massive database filling.

Effect of hydroxylysine-O-glycosylation on the structure of type I collagen molecule: A computational study

Collagen undergoes many types of post-translational modifications (PTMs), including intracellular modifications and extracellular modifications. Among these PTMs, glycosylation of hydroxylysine (Hyl) is the most complicated. Experimental studies demonstrated that this PTM ceases once the collagen triple helix is formed and that Hyl-O-glycosylation modulates collagen fibrillogenesis. However, the underlying atomic-level mechanisms of these phenomena remain unclear. In this study, we first adapted the force field parameters for O-linkages between Hyl and carbohydrates and then investigated the influence of Hyl-O-glycosylation on the structure of type I collagen molecule, by performing comprehensive molecular dynamic simulations in explicit solvent of collagen molecule segment with and without the glycosylation of Hyl. Data analysis demonstrated that (i) collagen triple helices remain in a triple-helical structure upon glycosylation of Hyl; (ii) glycosylation of Hyl modulates the peptide backbone conformation and their solvation environment in the vicinity and (iii) the attached sugars are arranged such that their hydrophilic faces are well exposed to the solvent, while their hydrophobic faces point towards the hydrophobic portions of collagen. The adapted force field parameters for O-linkages between Hyl and carbohydrates will aid future computational studies on proteins with Hyl-O-glycosylation. In addition, this work, for the first time, presents the detailed effect of Hyl-O-glycosylation on the structure of human type I collagen at the atomic level, which may provide insights into the design and manufacture of collagenous biomaterials and the development of biomedical therapies for collagen-related diseases.

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.

Thermal Response in Cellulose Iβ Based on Molecular Dynamics

The structural details of cellulose I β were discussed according to molecular dynamics simulations with the GLYCAM-06 force field. The simulation outcomes were in agreement with previous experimental data, including structural parameters and hydrogen bond pattern at 298 K. We found a new conformation of cellulose Iβ existed at the intermediate temperature that is between the low and high temperatures. Partial chain rotations along the backbone direction were found and conformations of hydroxymethyl groups that alternated from tg to either gt or gg were observed when the temperature increased from 298 K to 400 K. In addition, the gg conformation is preferred than gt. For the structure adopted at high temperature of 500 K, major chains were twisted and two chains detached from each plain. In contrast to the observation under intermediate temperature, the population of hydroxymethyl groups in gt exceeded that in gg conformation at high temperature. In addition, three patterns of hydrogen bonding were identified at low, intermediate and high temperatures in the simulations. The provided structural information indicated the transitions occurred around 350 K and 450 K, considered as the transitional temperatures of cellulose Iβ in this work.

Molecular Dynamics with Orientational Tensorial Constraints: A New Approach to Probe the Torsional Angle Distributions of Small Rotationally Flexible Molecules

The potential of residual dipolar couplings (RDCs) in conformational studies of small molecules is now widely recognized, but current theoretical approaches for their interpretation have several limitations and there is still the need for a general method to probe the torsional angle distributions applicable to any rotationally flexible molecule. Molecular dynamics simulations with RDC-based orientational tensorial constraints (MDOC), implemented in the software COSMOS, are presented here as a conceptually new strategy. For the cases of the fluorinated anti-inflammatory drug diflunisal and the disaccharide cellobiose, we demonstrate that MDOC simulations with one-bond RDCs as tensorial constraints unveil torsion distributions and allow the determination of relative configuration in the presence of rotational flexibility. The independence of the initial structure or any a priori assumption as well as the possibility to combine different experimental constraints represent features, which make the COSMOS software a promising tool for the investigation of torsional angle distributions of flexible molecules, regardless of their size and degree of freedom.

Fragmentation Behavior and Gas-Phase Structures of Cationized Glycosphingolipids in Ozone-Induced Dissociation Mass Spectrometry

The role of cationization in the fragmentation behavior of glycoconjugates is amply documented in collisional activation techniques but remains less explored in ozone-induced dissociation mass spectrometry (OzID-MS). OzID-MS has been used to elucidate the location of carbon-carbon double bonds in unsaturated lipids. Previously, we demonstrated the structural analysis of unsaturated glycosphingolipids using OzID-MS by mass-selecting the [M+Na]+ adduct for fragmentation. In this work, we aimed to examine the effect of different adducts, namely [M+Na]+, [M+Li]+, and [M+H]+ on the OzID-MS fragmentation behavior of a representative unsaturated glycosphingolipid, LacCer d18:1/18:1(9Z). Our data show that [M+H]+ primarily undergoes dehydration followed by collision-induced dissociation-like loss of the headgroup, while [M+Li]+ and [M+Na]+ dissociate at the double bonds albeit with slightly different intensities of the resulting fragments. Using molecular mechanics and theoretical calculations at the semiempirical level, we report for the first time the gas-phase structure of cationized glycosphingolipids, which helps rationalize the observed bond cleavage. Our findings highlight that the type of adducts can influence gas-phase ion structure of glycosphingolipids and subsequently affect their fragmentation in OzID-MS. This study contributes to the growing body of knowledge on OzID-MS and gas-phase structures of ionized lipids and the findings have the potential to be extended to other more complex glycoconjugates.

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.

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.

Molecular dynamics approach to understand the denaturing effect of a millimolar concentration of dodine on a λ-repressor and counteraction by trehalose

Here, we use a molecular dynamics approach to calculate the spatial distribution function of the ternary water–dodine–trehalose (1.0 M) system.

Cationic Peptides and Peptidomimetics Bind Glycosaminoglycans as Potential Sema3A Pathway Inhibitors

Semaphorin3A (Sema3A) is a vertebrate-secreted protein that was initially characterized as a repulsive-guidance cue. Semaphorins have crucial roles in several diseases; therefore, the development of Sema3A inhibitors is of therapeutic interest. Sema3A interacts with glycosaminoglycans (GAGs), presumably through its C-terminal basic region. We used different biophysical techniques (i.e., NMR, surface plasmon resonance, isothermal titration calorimetry, fluorescence, and UV-visible spectroscopy) to characterize the binding of two Sema3A C-terminus-derived basic peptides (FS2 and NFS3) to heparin and chondroitin sulfate A. We found that these peptides bind to both GAGs with affinities in the low-micromolar range. On the other hand, a peptoid named SICHI (semaphorin-induced chemorepulsion inhibitor), which is positively charged at physiological pH, was first identified by our group as being able to block Sema3A chemorepulsion and growth-cone collapse in axons at the extracellular level. To elucidate the direct target for the reported SICHI inhibitory effect in the Sema3A signaling pathway, we looked first to the protein-protein interaction between secreted Sema3A and the Nrp1 receptor. However, our results show that SICHI does not bind directly to the Sema3A sema domain or to Nrp1 extracellular domains. We evaluated a new, to our knowledge, hypothesis, according to which SICHI binds to GAGs, thereby perturbing the Sema3A-GAG interaction. By using the above-mentioned techniques, we observed that SICHI binds to GAGs and competes with Sema3A C-terminus-derived basic peptides for binding to GAGs. These data support the ability of SICHI to block the biologically relevant interaction between Sema3A and GAGs, thus revealing SICHI as a new, to our knowledge, class of inhibitors that target the GAG-protein interaction.

The influence of the carbohydrate anomeric linkage on the free radical scavenging activity of enzymatically-synthesized phenolic glycosides

Phenolic glycosides, widely recognized for their nutraceutical properties exist in nature as α- and β-glycosides.

Stereoelectronic effects of the glycosidic linkage on the conformational preference of d-sucrose

d-Sucrose conformational analysis at DFT theory level applying NBO and NCI methodology.

All-Atom Internal Coordinate Mechanics (ICM) Force Field for Hexopyranoses and Glycoproteins

We present an extension of the all-atom internal-coordinate force field, ICMFF, that allows for simulation of heterogeneous systems including hexopyranose saccharides and glycan chains in addition to proteins. A library of standard glycan geometries containing α- and β-anomers of the most common hexapyranoses, i.e., d-galactose, d-glucose, d-mannose, d-xylose, l-fucose, N-acetylglucosamine, N-acetylgalactosamine, sialic, and glucuronic acids, is created based on the analysis of the saccharide structures reported in the Cambridge Structural Database. The new force field parameters include molecular electrostatic potential-derived partial atomic charges and the torsional parameters derived from quantum mechanical data for a collection of minimal molecular fragments and related molecules. The ϕ/ψ torsional parameters for different types of glycosidic linkages are developed using model compounds containing the key atoms in the full carbohydrates, i.e., glycosidic-linked tetrahydropyran-cyclohexane dimers. Target data for parameter optimization include two-dimensional energy surfaces corresponding to the ϕ/ψ glycosidic dihedral angles in the disaccharide analogues, as determined by quantum mechanical MP2/6-31G** single-point energies on HF/6-31G** optimized structures. To achieve better agreement with the observed geometries of glycosidic linkages, the bond angles at the O-linkage atoms are added to the internal variable set and the corresponding bond bending energy term is parametrized using quantum mechanical data. The resulting force field is validated on glycan chains of 1-12 residues from a set of high-resolution X-ray glycoprotein structures based on heavy atom root-mean-square deviations of the lowest-energy glycan conformations generated by the biased probability Monte Carlo (BPMC) molecular mechanics simulations from the native structures. The appropriate BPMC distributions for monosaccharide-monosaccharide and protein-glycan linkages are derived from the extensive analysis of conformational properties of glycoprotein structures reported in the Protein Data Bank. Use of the BPMC search leads to significant improvements in sampling efficiency for glycan simulations. Moreover, good agreement with the X-ray glycoprotein structures is achieved for all glycan chain lengths. Thus, average/median RMSDs are 0.81/0.68 Å for one-residue glycans and 1.32/1.47 Å for three-residue glycans. RMSD from the native structure for the lowest-energy conformation of the 12-residue glycan chain (PDB ID 3og2) is 1.53 Å. Additionally, results obtained for free short oligosaccharides using the new force field are in line with the available experimental data, i.e., the most populated conformations in solution are predicted to be the lowest energy ones. The newly developed parameters allow for the accurate modeling of linear and branched hexopyranose glycosides in heterogeneous systems.

Performance of four different force fields for simulations of dipeptide conformations: GlyGly, GlyGly-, GlyGly · Cl-, GlyGly · Na+ and GlyGly · (H2O)2

Monte-Carlo conformational searches with four kinds of force fields (AMBER94, MM3*, MMFFs, and OPLS-2005) were performed on glycylglycine (GlyGly), deprotonated glycylglycine (GlyGly(-)), glycylglycine chloride anion complex (GlyGly · Cl(-)), glycylglycine sodium cation complex (GlyGly · Na(+)) and glycylglycine dihydrate [GlyGly · (H2O)2]. Combined with Hartree-Fock (HF) and second-order Møller-Plesset (MP2) optimizations, conformations within an energy of 20 kJ mol(-1) were predicted. After MP2 calculations, the geometries and relative energies of the predicted structures were the same regardless of the force field used. Therefore, the performance of different force fields reflects mainly the conformational search process. For GlyGly, there was practically no difference among the four force fields. Due to the complex hydrogen bonding network when involving water, the total number of resulting conformers for GlyGly · (H2O)2 increased drastically. Moreover, the MMFFs force field fared best in finding the global minimum compared to the remaining three force fields. In describing hydrogen bonded and inter-molecular complexes, we recommend application of the MMFFs and AMBER94 force fields. Furthermore, the MMFFs and OPLS-2005 force fields have a good description of electrostatic interactions. This work will contribute to helping the reader make an optimal choice of force field, taking into account the latter's strengths and limitations.

Computationally assisted assignment of kahalalide Y configuration using an NMR-constrained conformational search

Assignment of the absolute configuration of cyclic peptides frequently yields challenges, leaving one or more stereogenic centers unassigned due to small quantities of sample and the limited utility of Marfey's or other methods for assigning amino or hydroxy acids. Here, we report isolation of kahalalide Y (1) from Bryopsis pennata for the first time; in addition, the application of a combination of molecular modeling and NOE distance constraint calculations was utilized to determine the conformation of 1 and the absolute configuration of the final stereogenic center of 1. Using the Schrödinger suite, the structure of 1 was sketched in Maestro and minimized using the OPLS2005 force field in Macromodel. A conformational search was performed separately for structures having an R or S configuration at C-3 of the beta-hydroxy fatty acid subunit that completes the cyclic scaffold of 1, after which multiple minimizations for all generated conformers were carried out. The lowest energy conformers of R and S stereoisomers were then subjected to B3LYP geometry optimizations including solvent effects. The S stereoisomer was shown to be in excellent agreement with the NOE-derived distance constraints and hydrogen-bonding stability studies.

Density functional conformational study of 2-O-sulfated 3,6 anhydro-α-D-galactose and of neo-κ- and ι-carrabiose molecules in gas phase and water

We examined the conformational preferences of the 2-O-sulfated-3,6-α-D-anhydrogalactose (compound I) and two 1,3 linked disaccharides constituting-κ or ι-carrageenans using density functional and ab initio methods in gas phase and aqueous solution. Systematic modifications of two torsion angles leading to 324 and 144 starting geometries for the compound I and each disaccharide were used to generate adiabatic maps using B3LYP/6-31G(d). The lower energy conformers were then fully optimized using B3LYP, B3PW91 and MP2 with several basis sets. Overall, we discuss the impact of full relaxation on the energy and structure of the dominant conformations, present the performance comparison with previous molecular mechanics calculations if available, and determine whether our results are impacted, when polarization and diffuse functions are added to the 6-31G(d) basis set, or when the MP2 level of theory is used.