A Coarse-Grained Model for Molecular Dynamics Simulations of Native Cellulose

High-Throughput Molecular Dynamics Study and Turbidity Analysis on Clustering and Agglomeration of Cellulose Nanocrystals in Suspensions

The dispersion of cellulose nanocrystals (CNCs) in suspensions determines the quality of the CNC-reinforced composites. Before being mixed into the composite matrix, stable suspensions must maintain a well-dispersed state, requiring proper design strategies to prevent agglomeration and precipitation. Considering the volume fraction, aspect ratio, and zeta potential, this paper proposes a coarse-grained model to simulate CNC clustering and an experimental program to observe accelerated precipitation of CNCs. High-throughput molecular dynamics simulations yield a diagram of clustering time plotted against aspect ratio, zeta potential, and volume fraction of CNCs. Turbidity analysis with centrifugation-accelerated tests shows that precipitation occurs only after clustering and agglomeration are completed and that centrifugation rarely accelerates clustering. Clustering of short chains instantly leads to agglomeration, whereas clustering of long chains features delayed agglomeration, which can be triggered by centrifugation. Zeta potential is found to be the most critical factor affecting clustering, agglomeration, and precipitation. The findings provide critical insights into the conditions that favor stable CNC suspensions, which are essential for preparing well-dispersed suspensions and improving the composite material performance.

MARTINI Coarse-Grained Force Field for Thermoplastic Starch Nanocomposites

Thermoplastic starch (TPS) is an excellent film-forming material, and the addition of fillers, such as tetramethylammonium-montmorillonite (TMA-MMT) clay, has significantly expanded its use in packaging applications. We first used an all-atom (AA) simulation to predict several macroscopic (Young's modulus, glass transition temperature, density) and microscopic (conformation along 1-4 and 1-6 glycosidic linkages, composite morphology) properties of TPS melt and TPS-TMA-MMT composite. The interplay of polymer-surface (weakly repulsive), plasticizer-surface (attractive), and polymer-plasticizer (weakly attractive) interactions leads to conformational and dynamics properties distinct from those in systems with either attractive or repulsive polymer-surface interactions. A subset of AA properties was used to parametrize the MARTINI-2 coarse-grained (CG) force field (FF) for the melt and composite systems. The missing bonded parameters of amylose and amylopectin and the bead types for 1-4 and 1-6 linked α-D glucose were determined using two-body excess entropy, density, and bond and angle distributions in the AA TPS melt. This new MARTINI-2 CG model was also compared with the MARTINI-3 model for the TPS melt. However, the requirement of a polarizable water model necessitates the use of MARTINI-2 FF for the composite system. This liquid-liquid partitioning-based FF shows freezing and compaction of polymer chains near the clay surface, further accentuated by lowering of dispersive interactions between pairs of high-covalent-coordination ring units of TPS polymers and the montmorillonite sheet. A rescaling of the effective dispersive component of TPS-MMT cross interactions was used to optimize the MARTINI-2 FF for the composite system with structural (chain size distribution), thermodynamic (chain conformational entropy and density), and dynamic (self-diffusion coefficient) properties obtained from long AA simulations forming the constraints for optimization. The obtained CG FF parameters provided excellent estimates for several other properties of the melt and composite systems not used in parameter estimation, thus establishing the robustness of the developed model.

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.

Friction Properties of Crystalline Cellulose Sliding on Chromium under Water Lubrication Based on Molecular Dynamics Simulations

This work studies the friction and wear behaviors of chromium (hard material) and crystalline cellulose (soft material) under water lubrication considering the loading and sliding velocity on friction force, temperature of contact interfaces, and worn atoms from the atomic view. The change of friction force with sliding velocity is greater than that with loading, and it is easier to obtain a stable friction at high velocity. The average friction force in the stabilization gradually increases with loading and velocity, and the growth rate decreases with loading, while it increases with velocity. The temperature of contact interfaces at the beginning of sliding changes rapidly and gradually becomes stable. The temperature at the stabilization increases distinctly with velocity, while it does not change much with loading. Both the loading and sliding velocity have an important influence on the wear of soft material; it is noticed that the amount of worn atoms increases close to exponentially with velocity and linearly with loading. However, the wear of hard material changes less with increasing loading and sliding velocity.

A study across scales to unveil microstructural regimes in the multivalent metal driven self-assembly of cellulose nanocrystals

Understanding the behaviour of self-assembled systems, from nanoscale building blocks to bulk materials, is a central theme for the rational design of high-performance materials. Herein, we revealed, at different length scales, how the self-assembly of TEMPO-oxidised cellulose nanocrystals (TOCNCs) into rod fractal gels is directed by the complexation of Fe3+ ions on the surface of colloidal particles. Different specificities in Fe3+ binding on the TOCNC surface and conformational changes of the nanocellulose chain were unveiled by paramagnetic NMR spectroscopy. The macroscopic properties of systems presenting different concentrations of TOCNCs and Fe3+ ions were investigated by rheology and microscopy, demonstrating the tunability of the self-assembly of cellulose nanorods driven by Fe3+ complexation. Near-atomistic coarse-grained molecular dynamics simulations were developed to gain microscopic insight into the behaviour of this colloidal system. We found that the formation of different self-assembled architectures is driven by metal-nanocellulose complexation combined with the attenuation of electrostatic repulsion and water structuration around cellulose, leading to different microstructural regimes, from isolated nanorods to disconnected rod fractal clusters and rod fractal gels. These findings lay the foundation to unlock the full potential of cellulose nanocrystals as sustainable building blocks to develop self-assembled materials with defined structural control for a range of advanced applications.

Understanding Nanocellulose-Water Interactions: Turning a Detriment into an Asset

Modern technology has enabled the isolation of nanocellulose from plant-based fibers, and the current trend focuses on utilizing nanocellulose in a broad range of sustainable materials applications. Water is generally seen as a detrimental component when in contact with nanocellulose-based materials, just like it is harmful for traditional cellulosic materials such as paper or cardboard. However, water is an integral component in plants, and many applications of nanocellulose already accept the presence of water or make use of it. This review gives a comprehensive account of nanocellulose-water interactions and their repercussions in all key areas of contemporary research: fundamental physical chemistry, chemical modification of nanocellulose, materials applications, and analytical methods to map the water interactions and the effect of water on a nanocellulose matrix.

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.

Understanding Plant Biomass via Computational Modeling

Plant biomass, especially wood, has been used for structural materials since ancient times. It is also showing great potential for new structural materials and it is the major feedstock for the emerging biorefineries for building a sustainable society. The plant cell wall is a hierarchical matrix of mainly cellulose, hemicellulose, and lignin. Herein, the structure, properties, and reactions of cellulose, lignin, and wood cell walls, studied using density functional theory (DFT) and molecular dynamics (MD), which are the widely used computational modeling approaches, are reviewed. Computational modeling, which has played a crucial role in understanding the structure and properties of plant biomass and its nanomaterials, may serve a leading role on developing new hierarchical materials from biomass in the future.

The Martini Model in Materials Science

The Martini model, a coarse-grained force field initially developed with biomolecular simulations in mind, has found an increasing number of applications in the field of soft materials science. The model's underlying building block principle does not pose restrictions on its application beyond biomolecular systems. Here, the main applications to date of the Martini model in materials science are highlighted, and a perspective for the future developments in this field is given, particularly in light of recent developments such as the new version of the model, Martini 3.

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.

Molecular Dynamics Simulation of Nanocellulose-Stabilized Pickering Emulsions

While the economy is rapidly expanding in most emerging countries, issues coupled with a higher population has created foreseeable tension among food, water, and energy. It is crucial for more sustainable valorization of resources, for instance, nanocellulose, to address the core challenges in environmental sustainability. As the complexity of the system evolved, the timescale of project development has increased exponentially. However, research on the design and operation of integrated nanomaterials, along with energy supply, monitoring, and control infrastructure, has seriously lagged. The development cost of new materials can be significantly reduced by utilizing molecular simulation technology in the design of nanostructured materials. To realize its potential, nanocellulose, an amphiphilic biopolymer with the presence of rich -OH and -CH structural groups, was investigated via molecular dynamics simulation to reveal its full potential as Pickering emulsion stabilizer at the molecular level. This work has successfully quantified the Pickering stabilization mechanism profiles by nanocellulose, and the phenomenon could be visualized in three stages, namely the initial homogenous phase, rapid formation of micelles and coalescence, and lastly the thermodynamic equilibrium of the system. It was also observed that the high bead order was always coupled with a high volume of phase separation activities, through a coarse-grained model within 20,000 time steps. The outcome of this work would be helpful to provide an important perspective for the future design and development of nanocellulose-based emulsion products, which cater for food, cosmeceutical, and pharmaceutical industries.

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.

An overview of biomass conversion: exploring new opportunities

Recycling biomass is indispensable these days not only because fossil energy sources are gradually depleted, but also because pollution of the environment, caused by the increasing use of energy, must be reduced. This article intends to overview the results of plant biomass processing methods that are currently in use. Our aim was also to review published methods that are not currently in use. It is intended to explore the possibilities of new methods and enzymes to be used in biomass recycling. The results of this overview are perplexing in almost every area. Advances have been made in the pre-treatment of biomass and in the diversity and applications of the enzymes utilized. Based on molecular modeling, very little progress has been made in the modification of existing enzymes for altered function and adaptation for the environmental conditions during the processing of biomass. There are hardly any publications in which molecular modeling techniques are used to improve enzyme function and to adapt enzymes to various environmental conditions. Our view is that using modern computational, biochemical, and biotechnological methods would enable the purposeful design of enzymes that are more efficient and suitable for biomass processing.

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.

Discovery and design of soft polymeric bio-inspired materials with multiscale simulations and artificial intelligence

Establishing the “Materials 4.0” paradigm requires intimate knowledge of the virtual space in materials design.

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.

Mechanical Properties of Cellulose Nanocrystal (CNC) Bundles: Coarse-Grained Molecular Dynamic Simulation

Cellulose nanocrystals (CNCs) is a promising biodegradable nanomaterial with outstanding physical, chemical, and mechanical properties for many applications. Although aligned CNCs can self-assemble into bundles, their mechanical performance is reduced by interfacial strength between CNCs and a twisted structure. In this paper, we employ developed coarse-grained (CG) molecular dynamic (MD) simulations to investigate the influence of twist and interface energy on the tensile performance of CNC bundles. CNC bundles of different sizes (number of particles) are tested to also include the effect of size on mechanical performance. The effect of interfacial energy and twist on the mechanical performance shows that elastic modulus, strength, and toughness are more sensitive to twisted angle than interfacial energy. In addition, the effect of size on the bundle and twist on their mechanical performance revealed that both size and twist have a significant effect on the results and can reduce the strength and elastic modulus by 75% as a results of covalent bond dissociation. In addition, a comparison of the broken regions for different values of twist shows that by increasing the twist angle the crack propagates in multiple locations with a twisted shape.

Design of Polyphosphate Inhibitors: A Molecular Dynamics Investigation on Polyethylene Glycol-Linked Cationic Binding Groups

Inorganic polyphosphate (polyP) released by human platelets has recently been shown to activate blood clotting and identified as a potential target for the development of novel antithrombotics. Recent studies have shown that polymers with cationic binding groups (CBGs) inhibit polyP and attenuate thrombosis. However, a good molecular-level understanding of the binding mechanism is lacking for further drug development. While molecular dynamics (MD) simulation can provide molecule-level information, the time scale required to simulate these large biomacromolecules makes classical MD simulation impractical. To overcome this challenge, we employed metadynamics simulations with both all-atom and coarse-grained force fields. The force field parameters for polyethylene glycol (PEG) conjugated CBGs and polyP were developed to carry out coarse-grained MD simulations, which enabled simulations of these large biomacromolecules in a reasonable time scale. We found that the length of the PEG tail does not impact the interaction between the (PEG) _n-CBG and polyP. As expected, increasing the number of the charged tertiary amine groups in the head group strengthens its binding to polyP. Our simulation shows that (PEG) _n-CBG initially form aggregates, mostly with the PEG in the core and the hydrophilic CBG groups pointing toward water; then the aggregates approach the polyP and sandwich the polyP to form a complex. We found that the binding of (PEG) _n-CBG remains intact against various lengths of polyP. Binding thermodynamics for two of the (PEG) _n-CBG/polyP systems simulated were measured by isothermal titration calorimetry to confirm the key finding of the simulations that the length PEG tail does not influence ligand binding to polyP.

Elastic moduli of biological fibers in a coarse-grained model: crystalline cellulose and β-amyloids

We study the mechanical response of cellulose and β-amyloid microfibrils to three types of deformation: tensile, indentational, and shear. The cellulose microfibrils correspond to the allomorphs Iα or Iβ whereas the β-amyloid microfibrils correspond to the polymorphs of either two- or three-fold symmetry. This response can be characterized by three elastic moduli, namely, Y_L, Y_T, and S. We use a structure-based coarse-grained model to analyze the deformations in a unified manner. We find that each of the moduli is almost the same for the two allomorphs of cellulose but Y_L is about 20 times larger than Y_T (140 GPa vs. 7 GPa), indicating the existence of significant anisotropy. For cellulose we note that the anisotropy results from the involvement of covalent bonds in stretching. For β-amyloid, the sense of anisotropy is opposite to that of cellulose. In the three-fold symmetry case, Y_L is about half of Y_T (3 vs. 7) whereas for two-fold symmetry the anisotropy is much larger (1.6 vs. 21 GPa). The S modulus is derived to be 1.2 GPa for three-fold symmetry and one half of it for the other symmetry and 3.0 GPa for cellulose. The values of the moduli reflect deformations in the hydrogen-bond network. Unlike in our theoretical approach, no experiment can measure all three elastic moduli with the same apparatus. However, our theoretical results are consistent with various measured values: typical Y_L for cellulose Iβ ranges from 133 to 155 GPa, Y_T from 2 to 25 GPa, and S from 1.8 to 3.8 GPa. For β-amyloid, the experimental values of S and Y_T are about 0.3 GPa and 3.3 GPa respectively, while the value of Y_L has not been reported.

Hydrogen bonds and twist in cellulose microfibrils

There is increasing experimental and computational evidence that cellulose microfibrils can exist in a stable twisted form. In this study, atomistic molecular dynamics (MD) simulations are performed to investigate the importance of intrachain hydrogen bonds on the twist in cellulose microfibrils. We systematically enforce or block the formation of these intrachain hydrogen bonds by either constraining dihedral angles or manipulating charges. For the majority of simulations a consistent right handed twist is observed. The exceptions are two sets of simulations that block the O2-O6' intrachain hydrogen bond, where no consistent twist is observed in multiple independent simulations suggesting that the O2-O6' hydrogen bond can drive twist. However, in a further simulation where exocyclic group rotation is also blocked, right-handed twist still develops suggesting that intrachain hydrogen bonds are not necessary to drive twist in cellulose microfibrils.

Modeling the Hydrophobicity of Nanoparticles and Their Interaction with Lipids and Proteins

We present a method of modeling nanoparticle (NP) hydrophobicity using coarse-grained molecular dynamics (CG MD) simulations, and apply this to the interaction of lipids with nanoparticles. To model at a coarse-grained level the wettability or hydrophobicity of a given material, we choose the MARTINI coarse-grained force field, and determine through simulation the contact angles of MARTINI water droplets residing on flat regular surfaces composed of various MARTINI bead types (C1, C2, etc.). Each surface is composed of a single bead type in each of three crystallographic symmetries (FCC, BCC, and HCP). While this method lumps together several atoms (for example, one cerium and two oxygens of CeO₂) into a single CG bead, we can still capture the overall hydrophobicity of the actual material by choosing the MARTINI bead type that gives the best fit of the contact angle to that of the actual material, as determined by either experimental or all-atom simulations. For different MARTINI bead types, the macroscopic contact angle is obtained by extrapolating the microscopic contact angles of droplets of eight different sizes (containing N_w = 3224-22978 water molecules) to infinite droplet size. For each droplet, the contact angle was computed from a best fit of a circular curve to the droplet interface extrapolated to the first layer of the surface. We then examine how small nanoparticles of differing wettability interact with MARTINI dipalmitoylphosphotidylcholine (DPPC) lipids and SP-C peptides (a component of lung surfactant). The DPPC shows a transition from tails coating the nanoparticle to a hemimicelle coating the water-wet NP, as the contact angle of a water droplet on the surface is lowered below ∼60°. The results are relevant to developing a taxonomy describing the potential nanotoxicity of nanoparticle interactions with components in the lung.

Coarse-grained modeling of crystal growth and polymorphism of a model pharmaceutical molecule

We describe a systematic coarse-graining method to study crystallization and predict possible polymorphs of small organic molecules. In this method, a coarse-grained (CG) force field is obtained by inverse-Boltzmann iteration from the radial distribution function of atomistic simulations of the known crystal. With the force field obtained by this method, we show that CG simulations of the drug phenytoin predict growth of a crystalline slab from a melt of phenytoin, allowing determination of the fastest-growing surface, as well as giving the correct lattice parameters and crystal morphology. By applying meta-dynamics to the coarse-grained model, a new crystalline form of phenytoin (monoclinic, space group P2₁) was predicted which is different from the experimentally known crystal structure (orthorhombic, space group Pna2₁). Atomistic simulations and quantum calculations then showed the polymorph to be meta-stable at ambient temperature and pressure, and thermodynamically more stable than the conventional orthorhombic crystal at high pressure. The results suggest an efficient route to study crystal growth of small organic molecules that could also be useful for identification of possible polymorphs as well.

Unraveling cellulose microfibrils: a twisted tale

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

Molecular dynamics of the Bacillus subtilis expansin EXLX1: interaction with substrates and structural basis of the lack of activity of mutants

Expansins are disruptive proteins that loosen growing plant cell walls and can enhance the enzymatic hydrolysis of cellulose.

Polysaccharide-Protein Complexes in a Coarse-Grained Model

We construct two variants of coarse-grained models of three hexaoses: one based on the centers of mass of the monomers and the other associated with the C4 atoms. The latter is found to be better defined and more suitable for studying interactions with proteins described within α-C based models. We determine the corresponding effective stiffness constants through all-atom simulations and two statistical methods. One method is the Boltzmann inversion (BI) and the other, named energy-based (EB), involves direct monitoring of energies as a function of the variables that define the stiffness potentials. The two methods are generally consistent in their account of the stiffness. We find that the elastic constants differ between the hexaoses and are noticeably different from those determined for the crystalline cellulose Iβ. The nonbonded couplings through hydrogen bonds between different sugar molecules are modeled by the Lennard-Jones potentials and are found to be stronger than the hydrogen bonds in proteins. We observe that the EB method agrees with other theoretical and experimental determinations of the nonbonded parameters much better than BI. We then consider the hexaose-Man5B catalytic complexes and determine the contact energies between their the C4-α-C atoms. These interactions are found to be stronger than the proteinic hydrogen bonds: about four times as strong for cellohexaose and two times for mannohexaose. The fluctuational dynamics of the coarse-grained complexes are found to be compatible with previous all-atom studies by Bernardi et al.

A coarse-grain force-field for xylan and its interaction with cellulose

We have built a coarse-grain (CG) model describing xylan and its interaction with crystalline cellulose surfaces. Each xylosyl or glucosyl unit was represented by a single grain. Our calculations rely on force-field parameters adapted from the atomistic description of short xylan fragments and their adsorption on cellulose. This CG model was first validated for xylan chains both isolated and in the bulk where a good match was found with its atomistic counterpart as well as with experimental measurements. A similar agreement was also found when short xylan fragments were adsorbed on the (110) surface of crystalline cellulose. The CG model, which was extended to the (100) and (1-10) surfaces, revealed that the adsorbed xylan, which was essentially extended in the atomistic situation, could also adopt coiled structures, especially when laying on the hydrophobic cellulose surfaces.

MARTINI coarse-grained model for crystalline cellulose microfibers

Commercial-scale biofuel production requires a deep understanding of the structure and dynamics of its principal target: cellulose. However, an accurate description and modeling of this carbohydrate structure at the mesoscale remains elusive, particularly because of its overwhelming length scale and configurational complexity. We have derived a set of MARTINI coarse-grained force field parameters for the simulation of crystalline cellulose fibers. The model is adapted to reproduce different physicochemical and mechanical properties of native cellulose Iβ. The model is able not only to handle a transition from cellulose Iβ to another cellulose allomorph, cellulose IIII, but also to capture the physical response to temperature and mechanical bending of longer cellulose nanofibers. By developing the MARTINI model of a solid cellulose crystalline fiber from the building blocks of a soluble cellobiose coarse-grained model, we have provided a systematic way to build MARTINI models for other crystalline biopolymers.

Computational approaches to understanding reaction outcomes of organic processes in ionic liquids

The utility of using a combined experimental and computational approach for understanding ionic liquid media, and their effect on reaction outcome, is highlighted through a number of case studies.

The power of coarse graining in biomolecular simulations

Computational modeling of biological systems is challenging because of the multitude of spatial and temporal scales involved. Replacing atomistic detail with lower resolution, coarse grained (CG), beads has opened the way to simulate large-scale biomolecular processes on time scales inaccessible to all-atom models. We provide an overview of some of the more popular CG models used in biomolecular applications to date, focusing on models that retain chemical specificity. A few state-of-the-art examples of protein folding, membrane protein gating and self-assembly, DNA hybridization, and modeling of carbohydrate fibers are used to illustrate the power and diversity of current CG modeling.

Perspective: Coarse-grained models for biomolecular systems

By focusing on essential features, while averaging over less important details, coarse-grained (CG) models provide significant computational and conceptual advantages with respect to more detailed models. Consequently, despite dramatic advances in computational methodologies and resources, CG models enjoy surging popularity and are becoming increasingly equal partners to atomically detailed models. This perspective surveys the rapidly developing landscape of CG models for biomolecular systems. In particular, this review seeks to provide a balanced, coherent, and unified presentation of several distinct approaches for developing CG models, including top-down, network-based, native-centric, knowledge-based, and bottom-up modeling strategies. The review summarizes their basic philosophies, theoretical foundations, typical applications, and recent developments. Additionally, the review identifies fundamental inter-relationships among the diverse approaches and discusses outstanding challenges in the field. When carefully applied and assessed, current CG models provide highly efficient means for investigating the biological consequences of basic physicochemical principles. Moreover, rigorous bottom-up approaches hold great promise for further improving the accuracy and scope of CG models for biomolecular systems.

An Anisotropic Coarse-Grained Model for Proteins Based On Gay-Berne and Electric Multipole Potentials

Gay–Berne anisotropic potential has been widely used to evaluate the nonbonded interactions between coarse-grained particles being described as elliptical rigid bodies. In this paper, we are presenting a coarse-grained model for twenty kinds of amino acids and proteins, based on the anisotropic Gay–Berne and point electric multipole (EMP) potentials. We demonstrate that the anisotropic coarse-grained model, namely GBEMP model, is able to reproduce many key features observed from experimental protein structures (Dunbrack Library), as well as from atomistic force field simulations (using AMOEBA, AMBER, and CHARMM force fields), while saving the computational cost by a factor of about 10–200 depending on specific cases and atomistic models. More importantly, unlike other coarse-grained approaches, our framework is based on the fundamental intermolecular forces with explicit treatment of electrostatic and repulsion-dispersion forces. As a result, the coarse-grained protein model presented an accurate description of nonbonded interactions (particularly electrostatic component) between hetero/homodimers (such as peptide–peptide, peptide–water). In addition, the encouraging performance of the model was reflected by the excellent correlation between GBEMP and AMOEBA models in the calculations of the dipole moment of peptides. In brief, the GBEMP model given here is general and transferable, suitable for simulating complex biomolecular systems.

3D electron tomography of pretreated biomass informs atomic modeling of cellulose microfibrils

Fundamental insights into the macromolecular architecture of plant cell walls will elucidate new structure-property relationships and facilitate optimization of catalytic processes that produce fuels and chemicals from biomass. Here we introduce computational methodology to extract nanoscale geometry of cellulose microfibrils within thermochemically treated biomass directly from electron tomographic data sets. We quantitatively compare the cell wall nanostructure in corn stover following two leading pretreatment strategies: dilute acid with iron sulfate co-catalyst and ammonia fiber expansion (AFEX). Computational analysis of the tomographic data is used to extract mathematical descriptions for longitudinal axes of cellulose microfibrils from which we calculate their nanoscale curvature. These nanostructural measurements are used to inform the construction of atomistic models that exhibit features of cellulose within real, process-relevant biomass. By computational evaluation of these atomic models, we propose relationships between the crystal structure of cellulose Iβ and the nanoscale geometry of cellulose microfibrils.