Drude Polarizable Force Field Parametrization of Carboxylate and N-Acetyl Amine Carbohydrate Derivatives

Increasing the Accuracy and Robustness of the CHARMM General Force Field with an Expanded Training Set

Small molecule empirical force fields (FFs), including the CHARMM General Force Field (CGenFF), are designed to have wide coverage of organic molecules and to rapidly assign parameters to molecules not explicitly included in the FF. Assignment of parameters to new molecules in CGenFF is based on a trained bond-angle-dihedral charge increment linear interpolation scheme for the partial atomic charges along with bonded parameters assigned based on analogy using a rules-based penalty score scheme associated with atom types and chemical connectivity. Accordingly, the accuracy of CGenFF is related to the extent of the training set of available parameters. In the present study that training set is extended by 1390 molecules selected to represent connectivities new to CGenFF training compounds. Quantum mechanical (QM) data for optimized geometries, bond, valence angle, and dihedral angle potential energy scans, interactions with water, molecular dipole moments, and electrostatic potentials were used as target data. The resultant bonded parameters and partial atomic charges were used to train a new version of the CGenFF program, v5.0, which was used to generate parameters for a validation set of molecules, including drug-like molecules approved by the FDA, which were then benchmarked against both experimental and QM data. CGenFF v5.0 shows overall improvements with respect to QM intramolecular geometries, vibrations, dihedral potential energy scans, dipole moments and interactions with water. Tests of pure solvent properties of 216 molecules show small improvements versus the previous release of CGenFF v2.5.1 reflecting the high quality of the Lennard-Jones parameters that were explicitly optimized during the initial optimization of both the CGenFF and the CHARMM36 force field. CGenFF v5.0 represents an improvement that is anticipated to more accurately model intramolecular geometries and strain energies as well as noncovalent interactions of drug-like and other organic molecules.

Structural and Electronic Properties of Poly(ethylene terephthalate) (PET) from Polarizable Molecular Dynamics Simulations

The environmental and economic challenges posed by the widespread use and disposal of plastics, particularly poly(ethylene terephthalate) (PET), require innovative solutions to mitigate their impact. Such mitigation begins with understanding physical properties of the polymer that could enable new recycling technologies. Although molecular simulations have provided valuable insights into PET interactions with various PET hydrolases, current nonpolarizable force fields neglect the electronic polarization effects inherent to PET interactions. Here, we present parameters for PET polymer and its derivatives that are compatible with the Drude polarizable force field. Our parameter fitting protocol accurately reproduces electrostatic properties from quantum mechanical calculations. We then studied electronic properties of PET amorphous slabs and PET crystal units, revealing a crucial electronic polarization response of PET residues at the interface with water or vacuum, yielding insights into the modulation of electrostatic properties by solvent molecules. Finally, we showcase the interaction between a carbohydrate-binding protein and the PET crystal unit, revealing the role of electronic polarization in enhancing binding affinity. This study represents the first extension of the Drude polarizable force field to a synthetic polymer, offering a robust tool for exploring PET material properties and advancing the design of efficient (bio)technologies for addressing plastic pollution.

sAMP-VGG16: Force-field assisted image-based deep neural network prediction model for short antimicrobial peptides

During the last three decades, antimicrobial peptides (AMPs) have emerged as a promising therapeutic alternative to antibiotics. The approaches for designing AMPs span from experimental trial-and-error methods to synthetic hybrid peptide libraries. To overcome the exceedingly expensive and time-consuming process of designing effective AMPs, many computational and machine-learning tools for AMP prediction have been recently developed. In general, to encode the peptide sequences, featurization relies on approaches based on (a) amino acid (AA) composition, (b) physicochemical properties, (c) sequence similarity, and (d) structural properties. In this work, we present an image-based deep neural network model to predict AMPs, where we are using feature encoding based on Drude polarizable force-field atom types, which can capture the peptide properties more efficiently compared to conventional feature vectors. The proposed prediction model identifies short AMPs (≤30 AA) with promising accuracy and efficiency and can be used as a next-generation screening method for predicting new AMPs. The source code is publicly available at the Figshare server sAMP-VGG16.

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.

CHARMM at 45: Enhancements in Accessibility, Functionality, and Speed

Since its inception nearly a half century ago, CHARMM has been playing a central role in computational biochemistry and biophysics. Commensurate with the developments in experimental research and advances in computer hardware, the range of methods and applicability of CHARMM have also grown. This review summarizes major developments that occurred after 2009 when the last review of CHARMM was published. They include the following: new faster simulation engines, accessible user interfaces for convenient workflows, and a vast array of simulation and analysis methods that encompass quantum mechanical, atomistic, and coarse-grained levels, as well as extensive coverage of force fields. In addition to providing the current snapshot of the CHARMM development, this review may serve as a starting point for exploring relevant theories and computational methods for tackling contemporary and emerging problems in biomolecular systems. CHARMM is freely available for academic and nonprofit research at https://academiccharmm.org/program.

Integration of Artificial Intelligence and Quantum Transport toward Stereoselective Identification of Carbohydrate Isomers

Detection of stereoisomers of carbohydrates with molecular resolution, a challenging goal analysts desire to achieve, is key to the full development of glycosciences. Despite the promise that analytical techniques made, including widely used nuclear magnetic resonance and mass spectrometry, high throughput de novo carbohydrate sequencing remains an unsolved issue. Notably, while next-generation sequencing technologies are readily available for DNA and proteins, they are conspicuously absent for carbohydrates due to the immense stereochemical and structural complexity inherent in these molecules. In this work, we report a novel computational technique that employs quantum tunneling coupled with artificial intelligence to detect complex carbohydrate anomers and stereoisomers with excellent sensitivity. The quantum tunneling footprints of carbohydrate isomers show high distinguishability with an in-depth analysis of underlying chemistry. Our findings open up a new route for carbohydrate sensing, which can be seamlessly integrated with next-generation sequencing technology for real-time analysis.

Developing and Benchmarking Sulfate and Sulfamate Force Field Parameters via Ab Initio Molecular Dynamics Simulations To Accurately Model Glycosaminoglycan Electrostatic Interactions

Glycosaminoglycans (GAGs) are negatively charged polysaccharides found on cell surfaces, where they regulate transport pathways of foreign molecules toward the cell. The structural and functional diversity of GAGs is largely attributed to varied sulfation patterns along the polymer chains, which makes understanding their molecular recognition mechanisms crucial. Molecular dynamics (MD) simulations, thanks to their unmatched microscopic resolution, have the potential to be a reference tool for exploring the patterns responsible for biologically relevant interactions. However, the capability of molecular dynamics force fields used in biosimulations to accurately capture sulfation-specific interactions is not well established, partly due to the intrinsic properties of GAGs that pose challenges for most experimental techniques. In this work, we evaluate the performance of molecular dynamics force fields for sulfated GAGs by studying ion pairing of Ca2+ to sulfated moieties─N-methylsulfamate and methylsulfate─that resemble N- and O-sulfation found in GAGs, respectively. We tested available nonpolarizable (CHARMM36 and GLYCAM06) and explicitly polarizable (Drude and AMOEBA) force fields, and derived new implicitly polarizable models through charge scaling (prosECCo75 and GLYCAM-ECC75) that are consistent with our developed "charge-scaling" framework. The calcium-sulfamate/sulfate interaction free energy profiles obtained with the tested force fields were compared against reference ab initio molecular dynamics (AIMD) simulations, which serve as a robust alternative to experiments. AIMD simulations indicate that the preferential Ca2+ binding mode to sulfated GAG groups is solvent-shared pairing. Only our scaled-charge models agree satisfactorily with the AIMD data, while all other force fields exhibit poorer agreement, sometimes even qualitatively. Surprisingly, even explicitly polarizable force fields display a notable disagreement with the AIMD data, likely attributed to difficulties in their optimization and possible inherent limitations in depicting high-charge-density ion interactions accurately. Finally, the underperforming force fields lead to unrealistic aggregation of sulfated saccharides, which qualitatively disagrees with our understanding of the soft glycocalyx environment. Our results highlight the importance of accurately treating electronic polarization in MD simulations of sulfated GAGs and caution against over-reliance on currently available models without thorough validation and optimization.

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.

Drude Polarizable Lipid Force Field with Explicit Treatment of Long-Range Dispersion: Parametrization and Validation for Saturated and Monounsaturated Zwitterionic Lipids

Accurate empirical force fields of lipid molecules are a critical component of molecular dynamics simulation studies aimed at investigating properties of monolayers, bilayers, micelles, vesicles, and liposomes, as well as heterogeneous systems, such as protein-membrane complexes, bacterial cell walls, and more. While the majority of lipid force field-based simulations have been performed using pairwise-additive nonpolarizable models, advances have been made in the development of the polarizable force field based on the classical Drude oscillator model. In the present study, we undertake further optimization of the Drude lipid force field, termed Drude2023, including improved treatment of the phosphate and glycerol linker region of PC and PE headgroups, additional optimization of the alkene group in monounsaturated lipids, and inclusion of long-range Lennard-Jones interactions using the particle-mesh Ewald method. Initial optimization targeted quantum mechanical (QM) data on small model compounds representative of the linker region. Subsequent optimization targeted QM data on larger model compounds, experimental data, and dihedral potentials of mean force from the CHARMM36 additive lipid force field using a parameter reweighting protocol. The use of both experimental and QM target data during the reweighting protocol is shown to produce physically reasonable parameters that reproduce a collection of experimental observables. Target data for optimization included surface area/lipid for DPPC, DSPC, DMPC, and DLPC bilayers and nuclear magnetic resonance (NMR) order parameters for DPPC bilayers. Validation data include prediction of membrane thickness, scattering form factors, electrostatic potential profiles, compressibility moduli, surface area per lipid, water permeability, NMR T1 relaxation times, diffusion constants, and monolayer surface tensions for a variety of saturated and unsaturated lipid mono- and bilayers. Overall, the agreement with experimental data is quite good, though the results are less satisfactory for the NMR T1 relaxation times for carbons near the ester groups. Notable improvements compared to the additive C36 force field were obtained for membrane dipole potentials, lipid diffusion coefficients, and water permeability with the exception of monounsaturated lipid bilayers. It is anticipated that the optimized polarizable Drude2023 force field will help generate more accurate molecular simulations of pure bilayers and heterogeneous systems containing membranes, advancing our understanding of the role of electronic polarization in these systems.

Impact of Polarization on the Ring Puckering Dynamics of Hexose Monosaccharides

Analysis of crystal structures of hexose monosaccharides α-d-mannose (α-MAN), β-d-mannose (β-MAN), α-d-glucose (α-GLC), β-d-glucose (β-GLC), α-d-galactose (α-GAL), β-d-galactose (β-GAL), α-d-altrose (α-ALT), β-d-altrose (β-ALT), α-d-idose (α-IDO), and β-d-idose (β-IDO) reveals that the monosaccharide ring adopts multiple ring conformations. These ring conformations can be broadly classified as chair, half-chair, envelope, boat, and skew-boat conformations. The ability of the monosaccharide ring to adopt multiple conformations has been closely tied with their bioactivity. However, it has been difficult to capture the dynamic information of these conformations from experimental studies. Even from simulations, capturing these different conformations is challenging because of the energy barriers involved in the transitions between the stable ⁴C₁ and ¹C₄ chair forms. In this study, we analyze the influence of the polarizable force field on the ring dynamics of five major types of unsubstituted aldohexoses─glucose, mannose, galactose, altrose, and idose─and their anomers. We simulate microsecond trajectories to capture the influence of the CHARMM36 additive and polarizable carbohydrate force fields on the ring dynamics. The microsecond trajectories allow us to comment on the issues associated with equilibrium molecular dynamics simulations. Further, we use the extended system adaptive biasing force (eABF) method to compare the conformational sampling efficiencies of the additive and polarizable force fields. Our studies reveal that inclusion of polarization enhances the sampling of ring conformations and lowers the energy barriers between the ⁴C₁ and ¹C₄ conformations. Overall, the CHARMM36 additive force field is observed to be rigid and favor the ⁴C₁ conformations. Although the inclusion of polarizability results in enhancing ring flexibility, we observe sampling that does not agree with experimental results, warranting a revision of the polarizable Drude parameters.

Atomic-Resolution Experimental Structural Biology and Molecular Dynamics Simulations of Hyaluronan and Its Complexes

This review summarizes the atomic-resolution structural biology of hyaluronan and its complexes available in the Protein Data Bank, as well as published studies of atomic-resolution explicit-solvent molecular dynamics simulations on these and other hyaluronan and hyaluronan-containing systems. Advances in accurate molecular mechanics force fields, simulation methods and software, and computer hardware have supported a recent flourish in such simulations, such that the simulation publications now outnumber the structural biology publications by an order of magnitude. In addition to supplementing the experimental structural biology with computed dynamic and thermodynamic information, the molecular dynamics studies provide a wealth of atomic-resolution information on hyaluronan-containing systems for which there is no atomic-resolution structural biology either available or possible. Examples of these summarized in this review include hyaluronan pairing with other hyaluronan molecules and glycosaminoglycans, with ions, with proteins and peptides, with lipids, and with drugs and drug-like molecules. Despite limitations imposed by present-day computing resources on system size and simulation timescale, atomic-resolution explicit-solvent molecular dynamics simulations have been able to contribute significant insight into hyaluronan's flexibility and capacity for intra- and intermolecular non-covalent interactions.

Extension of the CHARMM Classical Drude Polarizable Force Field to N- and O-Linked Glycopeptides and Glycoproteins

Molecular dynamic simulations are an effective tool to study complex molecular systems and are contingent upon the availability of an accurate and reliable molecular mechanics force field. The Drude polarizable force field, which allows for the explicit treatment of electronic polarization in a computationally efficient fashion, has been shown to reproduce experimental properties that were difficult or impossible to reproduce with the CHARMM additive force field, including peptide folding cooperativity, RNA hairpin structures, and DNA base flipping. Glycoproteins are essential components of glycoconjugate vaccines, antibodies, and many pharmaceutically important molecules, and an accurate polarizable force field that includes compatibility between the protein and carbohydrate aspect of the force field is essential to study these types of systems. In this work, we present an extension of the Drude polarizable force field to glycoproteins, including both N- and O-linked species. Parameter optimization focused on the dihedral terms using a reweighting protocol targeting NMR solution J-coupling data for model glycopeptides. Validation of the model include eight model glycopeptides and four glycoproteins with multiple N- and O-linked glycosylations. The new glycoprotein carbohydrate force field can be used in conjunction with the remainder of Drude polarizable force field through a variety of MD simulation programs including GROMACS, OPENMM, NAMD, and CHARMM and may be accessed through the Drude Prepper module in the CHARMM-GUI.

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.

Carbohydrate Force Fields: The Role of Small Partial Atomic Charges in Preventing Conformational Collapse

Although the quality of current additive all-atom force fields for carbohydrates has been demonstrated in many applications, occasional significant differences reported for the hydrodynamic behavior of specific polysaccharides modeled with different force fields is a cause for concern. In particular, irreversible conformational collapse has been noted for some polysaccharide simulations with the GLYCAM06j force field. Here, we investigate the cause of this phenomenon through comparative simulations of a range of saccharides with both the GLYCAM06j and the CHARMM36 carbohydrate force fields. We find that conformational collapse in GLYCAM06j occurs for saccharide chains containing the deoxy sugar α-l-rhamnose after relatively long simulation intervals. Further, we explore the mechanism of conformational collapse and show that this phenomenon arises because of the anomalous low energy in GLYCAM06j (as compared to quantum mechanical calculations) of a specific orientation of α-l-Rha to α-l-Rha glycosidic linkages, which are subsequently sustained by intramolecular interactions in the saccharide chain. We identify the lack of partial charges on aliphatic hydrogens in GLYCAM as the source of this anomaly, demonstrating that addition of small partial atomic charges on the aliphatic protons in rhamnose removes the conformational collapse phenomenon. This work reveals the large cumulative impact that small partial charges may have on the dynamic behavior of polysaccharides and indicates that future reparameterization of the GLYCAM06j force field should investigate the addition of partial charges on all aliphatic hydrogens.

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.

Protein-Ligand Binding Molecular Details Revealed by Terahertz Optical Kerr Spectroscopy: A Simulation Study

Picosecond fast motions and their involvement in the biochemical processes such as protein-ligand binding has engaged significant attention. Terahertz optical Kerr spectroscopy (OKE) has the superior potential to probe these fast motions directly. Application of OKE in protein-ligand binding study is, however, limited by the difficulty of quantitative atomistic interpretation, and the calculation of Kerr spectrum for entire solvated protein complex was considered not yet feasible, due to the lack of one consistent polarizable model for both configuration sampling and polarizability calculation. Here, we analyzed the biochemical relevance of OKE to the lysozyme-triacetylchitotriose binding based on the first OKE simulation using one consistent Drude polarizable model. An analytical multipole and induced dipole scheme was employed to calculate the off-diagonal Drude polarizability more efficiently and accurately. Further theoretical analysis revealed how the subtle twisting and stiffening of aromatic protein residues' spatial arrangement as well as the confinement of small water clusters between ligand and protein cavity due to the ligand binding can be examined using Kerr spectroscopy. Comparison between the signals of bound complex and that of uncorrelated protein/ligand demonstrated that binding action alone has reflection in the OKE spectrum. Our study indicated OKE as a powerful terahertz probe for protein-ligand binding chemistry and dynamics.

Understanding the avidin-biotin binding based on polarized protein-specific charge

In this study, charge updating schemes based on the local polarized protein-specific charge (LPPC) were introduced to vary the atomic charges of the biotin molecule and the residues in close contact during the simulation of the avidin-biotin complexes. The need of the charge variation of the ligand in response to changes in its surroundings was thoroughly studied. The results show that the calculated binding energy difference between biotin (BTN1) and 2'-iminobiotin (BTN2) and avidin is in excellent agreement with the experimental value, thus verifying the feasibility of updating the atomic charges of ligands during the simulation.

Combining Experimental Isotherms, Minimalistic Simulations, and a Model to Understand and Predict Chemical Adsorption onto Montmorillonite Clays

An attractive approach to minimize human and animal exposures to toxic environmental contaminants is the use of safe and effective sorbent materials to sequester them. Montmorillonite clays have been shown to tightly bind diverse toxic chemicals. Due to their promise as sorbents to mitigate chemical exposures, it is important to understand their function and rapidly screen and predict optimal clay-chemical combinations for further testing. We derived adsorption free-energy values for a structurally and physicochemically diverse set of toxic chemicals using experimental adsorption isotherms performed in the current and previous studies. We studied the diverse set of chemicals using minimalistic MD simulations and showed that their interaction energies with calcium montmorillonite clays calculated using simulation snapshots in combination with their net charge and their corresponding solvent's dielectric constant can be used as inputs to a minimalistic model to predict adsorption free energies in agreement with experiments. Additionally, experiments and computations were used to reveal structural and physicochemical properties associated with chemicals that can be adsorbed to calcium montmorillonite clay. These properties include positively charged groups, phosphine groups, halide-rich moieties, hydrogen bond donor/acceptors, and large, rigid structures. The combined experimental and computational approaches used in this study highlight the importance and potential applicability of analogous methods to study and design novel advanced sorbent systems in the future, broadening their applicability for environmental contaminants.

Ion Pairing and Dielectric Decrement in Glycosaminoglycan Brushes

Cell-surface polysaccharides are essential to many aspects of physiology, serving as a highly conserved evolutionary feature of life and as an important part of the innate immune system in mammals. Here, as simplified biophysical models of these sugar coatings, we present results of molecular dynamics simulations of hyaluronic acid and heparin brushes that show important effects of ion pairing, water dielectric decrease, and coion exclusion. As in prior studies of macromolecular crowding under physiologically relevant salt concentrations, our results show equilibria with electroneutrality attained through screening and pairing of brush anionic charges by monovalent cations at the atomistic detail. Most surprising is the reversal of the Donnan potential obtained from both nonpolarizable and Drude polarizable force fields, in contrast to what would be expected based on electrostatic Boltzmann partitioning alone. Water dielectric decrement within the brush domain is also associated with Born hydration-driven cation exclusion from the brush. We observe that the primary partition energy attracting cations to attain brush electroneutrality is the ion pairing or salt-bridge energy. Potassium and sodium pairings to glycosaminoglycan carboxylates and sulfates show similar abundance of contact-pairing and solvent-separated pairing. We conclude that in these crowded macromolecular brushes, ion-pairing, Born-hydration, and electrostatic potential energies all contribute to attain electroneutrality and should therefore contribute in mean-field models to accurately represent brush electrostatics.

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.

Ring Puckering Landscapes of Glycosaminoglycan-Related Monosaccharides from Molecular Dynamics Simulations

The conformational flexibility of the glycosaminoglycans (GAGs) is known to be key in their binding and biological function, for example in regulating coagulation and cell growth. In this work, we employ enhanced sampling molecular dynamics simulations to probe the ring conformations of GAG-related monosaccharides, including a range of acetylated and sulfated GAG residues. We first perform unbiased MD simulations of glucose anomers and the epimers glucuronate and iduronate. These calculations indicate that in some cases, an excess of 15 μs is required for adequate sampling of ring pucker due to the high energy barriers between states. However, by applying our recently developed msesMD simulation method (multidimensional swarm-enhanced sampling molecular dynamics), we were able to quantitatively and rapidly reproduce these ring pucker landscapes. From msesMD simulations, the puckering free energy profiles were then compared for 15 further monosaccharides related to GAGs; this includes to our knowledge the first simulation study of sulfation effects on β-GalNAc ring puckering. For the force field employed, we find that in general the calculated pucker free energy profiles for sulfated sugars were similar to the corresponding unsulfated profiles. This accords with recent experimental studies suggesting that variation in ring pucker of sulfated GAG residues is primarily dictated by interactions with surrounding residues rather than by intrinsic conformational preference. As an exception to this, however, we predict that 4-O-sulfation of β-GalNAc leads to reduced ring rigidity, with a significant lowering in energy of the ¹C₄ ring conformation; this observation may have implications for understanding the structural basis of the biological function of β-GalNAc-containing glycosaminoglycans such as dermatan sulfate.