PITOMBA: Parameter Interface for Oligosaccharide Molecules Based on Atoms

SIRAH Late Harvest: Coarse-Grained Models for Protein Glycosylation

Glycans constitute one of the most complex families of biological molecules. Despite their crucial role in a plethora of biological processes, they remain largely uncharacterized because of their high complexity. Their intrinsic flexibility and the vast variability associated with the many combination possibilities have hampered their experimental determination. Although theoretical methods have proven to be a valid alternative to the study of glycans, the large size associated with polysaccharides, proteoglycans, and glycolipids poses significant challenges to a fully atomistic description of biologically relevant glycoconjugates. On the other hand, the exquisite dependence on hydrogen bonds to determine glycans' structure makes the development of simplified or coarse-grained (CG) representations extremely challenging. This is particularly the case when glycan representations are expected to be compatible with CG force fields that include several molecular types. We introduce a CG representation able to simulate a wide variety of polysaccharides and common glycosylation motifs in proteins, which is fully compatible with the CG SIRAH force field. Examples of application to N-glycosylated proteins, including antibody recognition and calcium-mediated glycan-protein interactions, highlight the versatility of the enlarged set of CG molecules provided by SIRAH.

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.

A Review of Cellulose Coarse-Grained Models and Their Applications

Cellulose is the most common biopolymer and widely used in our daily life. Due to its unique properties and biodegradability, it has been attracting increased attention in the recent years and various new applications of cellulose and its derivatives are constantly being found. The development of new materials with improved properties, however, is not always an easy task, and theoretical models and computer simulations can often help in this process. In this review, we give an overview of different coarse-grained models of cellulose and their applications to various systems. Various coarse-grained models with different mapping schemes are presented, which can efficiently simulate systems from the single cellulose fibril/crystal to the assembly of many fibrils/crystals. We also discuss relevant applications of these models with a focus on the mechanical properties, self-assembly, chiral nematic phases, conversion between cellulose allomorphs, composite materials and interactions with other molecules.

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.

Extending the Martini Coarse-Grained Force Field to N-Glycans

Glycans play a vital role in a large number of cellular processes. Their complex and flexible nature hampers structure-function studies using experimental techniques. Molecular dynamics (MD) simulations can help in understanding dynamic aspects of glycans if the force field parameters used can reproduce key experimentally observed properties. Here, we present optimized coarse-grained (CG) Martini force field parameters for N-glycans, calibrated against experimentally derived binding affinities for lectins. The CG bonded parameters were obtained from atomistic (ATM) simulations for different glycan topologies including high mannose and complex glycans with various branching patterns. In the CG model, additional elastic networks are shown to improve maintenance of the overall conformational distribution. Solvation free energies and octanol-water partition coefficients were also calculated for various N-glycan disaccharide combinations. When using standard Martini nonbonded parameters, we observed that glycans spontaneously aggregated in the solution and required down-scaling of their interactions for reproduction of ATM model radial distribution functions. We also optimized the nonbonded interactions for glycans interacting with seven lectin candidates and show that a relatively modest scaling down of the glycan-protein interactions can reproduce free energies obtained from experimental studies. These parameters should be of use in studying the role of glycans in various glycoproteins and carbohydrate binding proteins as well as their complexes, while benefiting from the efficiency of CG sampling.

Aggregation of Lipid A Variants: A Hybrid Particle-Field Model

Lipid A is one of the three components of bacterial lipopolysaccharides constituting the outer membrane of Gram-negative bacteria, and is recognized to have an important biological role in the inflammatory response of mammalians. Its biological activity is modulated by the number of acyl-chains that are present in the lipid and by the dielectric medium, i.e., the type of counter-ions, through electrostatic interactions. In this paper, we report on a coarse-grained model of chemical variants of Lipid A based on the hybrid particle-field/molecular dynamics approach (hPF-MD). In particular, we investigate the stability of Lipid A bilayers for two different hexa- and tetra-acylated structures. Comparing particle density profiles along bilayer cross-sections, we find good agreement between the hPF-MD model and reference all-atom simulation for both chemical variants of Lipid A. hPF-MD models of constituted bilayers composed by hexa-acylated Lipid A in water are stable within the simulation time. We further validate our model by verifying that the phase behavior of Lipid A/counterion/water mixtures is correctly reproduced. In particular, hPF-MD simulations predict the correct self-assembly of different lamellar and micellar phases from an initially random distribution of Lipid A molecules with counterions in water. Finally, it is possible to observe the spontaneous formation and stability of Lipid A vesicles by fusion of micellar aggregates.

The Lazy Life of Lipid-Linked Oligosaccharides in All Life Domains

Lipid-linked oligosaccharides (LLOs) play an important role in the N-glycosylation pathway as the donor substrate of oligosaccharyltransferases (OSTs), which are responsible for the en bloc transfer of glycan chains onto a nascent polypeptide. The lipid component of LLO in both eukarya and archaea consists of a dolichol, and an undecaprenol in prokarya, whereas the number of isoprene units may change between species. Given the potential relevance of LLOs and their related enzymes to diverse biotechnological applications, obtaining reliable LLO models from distinct domains of life could support further studies on complex formation and their processing by OSTs, as well as protein engineering on such systems. In this work, molecular modeling techniques, such as quantum mechanics calculations, molecular dynamics simulations, and metadynamics were employed to study eukaryotic (Glc₃-Man₉-GlcNAc₂-PP-Dolichol), bacterial (Glc₁-GalNAc₅-Bac₁-PP-Undecaprenol), and archaeal (Glc₁-Man1-Gal₁-Man1-Glc₁-Gal₁-Glc₁-P-Dolichol) LLOs in membrane bilayers. Microsecond molecular dynamics simulations and metadynamics calculations of LLOs revealed that glycan chains are more prone to interact with the membrane lipid head groups, while the PP linkages are positioned at the lipid phosphate head groups level. The dynamics of isoprenoid chains embedded within the bilayer are described, and membrane dynamics and related properties are also investigated. Overall, there are similarities regarding the structure and dynamics of the eukaryotic, the bacterial, and the archaeal LLOs in bilayers, which can support the comprehension of their association with OSTs. These data may support future studies on the transferring mechanism of the oligosaccharide chain to an acceptor protein.

Coarse-grained molecular dynamics simulations of α-1,3-glucan

In this paper we present a computational study of aggregation in aqueous solutions of α-1,3-glucan captured using a coarse-grained (CG) model that can be extended to other polysaccharides. This CG model captures atomistic geometry (i.e., relative placement of the hydrogen bonding donors and acceptors within the monomer) of the α-1,3-glucan monomer, the directional interactions due to the donor-acceptor hydrogen bonds, and their effect on aggregation of multiple α-1,3-glucan chains without the extensive computational resources needed for simulations with atomistic models. Using this CG model, we conduct molecular dynamics simulations to assess the effect of varying α-1,3-glucan chain length and hydrogen bond interaction strengths on the aggregation of multiple chains at finite concentrations in implicit solvent. We quantify the hydrogen bonding strength needed for multiple chains to aggregate, the distribution of inter- and intra-chain hydrogen bonds within the aggregate and in some cases, the shapes of the aggregate. We also explore the effect of substitution/silencing of some randomly selected or specific hydrogen bonding sites in the chain on the aggregation and aggregate structure. In the unmodified α-1,3-glucan solution, the inter-chain hydrogen bonds cause the chains to aggregate into sheets. Random silencing of hydrogen bonding donor sites only increases the hydrogen bond strength needed for aggregation but retains the same aggregate structure as the unmodified chains. Specific silencing of the hydrogen-bonding site on the C6 carbon leads to the chains aggregating into planar sheets that then fold over to form hollow cylinders at intermediate hydrogen bond strength - 4.7 to 5.3 kcal mol-1. These cylindrical aggregates assemble end-to-end to form larger aggregates at higher hydrogen bond strengths.

Graph-Based Approach to Systematic Molecular Coarse-Graining

A novel methodology is introduced here to generate coarse-grained (CG) representations of molecular models for simulations. The proposed strategy relies on basic graph-theoretic principles and is referred to as graph-based coarse-graining (GBCG). It treats a given system as a molecular graph and derives a corresponding CG representation by using edge contractions to combine nodes in the graph, which correspond to atoms in the molecule, into CG sites. A key element of this methodology is that the nodes are combined according to well-defined protocols that rank-order nodes based on the underlying chemical connectivity. By iteratively performing these operations, successively coarser representations of the original atomic system can be produced to yield a systematic set of CG mappings with hierarchical resolution in an automated fashion. These capabilities are demonstrated in the context of several test systems, including toluene, pentadecane, a polysaccharide dimer, and a rhodopsin protein. In these examples, GBCG yields multiple, intuitive structures that naturally preserve the chemical topology of the system. Importantly, these representations are rendered from algorithmic implementation rather than an arbitrary ansatz, which, until now, has been the conventional approach for defining CG mapping schemes. Overall, the results presented here indicate that GBCG is efficient, robust, and unambiguous in its application, making it a valuable tool for future CG modeling.

Aromatic Rings Commonly Used in Medicinal Chemistry: Force Fields Comparison and Interactions With Water Toward the Design of New Chemical Entities

The identification of lead compounds usually includes a step of chemical diversity generation. Its rationale may be supported by both qualitative (SAR) and quantitative (QSAR) approaches, offering models of the putative ligand-receptor interactions. In both scenarios, our understanding of which interactions functional groups can perform is mostly based on their chemical nature (such as electronegativity, volume, melting point, lipophilicity etc.) instead of their dynamics in aqueous, biological solutions (solvent accessibility, lifetime of hydrogen bonds, solvent structure etc.). As a consequence, it is challenging to predict from 2D structures which functional groups will be able to perform interactions with the target receptor, at which intensity and relative abundance in the biological environment, all of which will contribute to ligand potency and intrinsic activity. With this in mind, the aim of this work is to assess properties of aromatic rings, commonly used for drug design, in aqueous solution through molecular dynamics simulations in order to characterize their chemical features and infer their impact in complexation dynamics. For this, common aromatic and heteroaromatic rings were selected and received new atomic charge set based on the direction and module of the dipole moment from MP2/6-31G^* calculations, while other topological terms were taken from GROMOS53A6 force field. Afterwards, liquid physicochemical properties were simulated for a calibration set composed by nearly 40 molecules and compared to their respective experimental data, in order to validate each topology. Based on the reliance of the employed strategy, we expanded the dataset to more than 100 aromatic rings. Properties in aqueous solution such as solvent accessible surface area, H-bonds availability, H-bonds residence time, and water structure around heteroatoms were calculated for each ring, creating a database of potential interactions, shedding light on features of drugs in biological solutions, on the structural basis for bioisosterism and on the enthalpic/entropic costs for ligand-receptor complexation dynamics.

Nanoscale Engineering of Designer Cellulosomes

Biocatalysts showcase the upper limit obtainable for high-speed molecular processing and transformation. Efforts to engineer functionality in synthetic nanostructured materials are guided by the increasing knowledge of evolving architectures, which enable controlled molecular motion and precise molecular recognition. The cellulosome is a biological nanomachine, which, as a fundamental component of the plant-digestion machinery from bacterial cells, has a key potential role in the successful development of environmentally-friendly processes to produce biofuels and fine chemicals from the breakdown of biomass waste. Here, the progress toward so-called "designer cellulosomes", which provide an elegant alternative to enzyme cocktails for lignocellulose breakdown, is reviewed. Particular attention is paid to rational design via computational modeling coupled with nanoscale characterization and engineering tools. Remaining challenges and potential routes to industrial application are put forward.