Coarse-Grained Molecular Models of Water: A Review

Coarse-grained (CG) models have proven to be very effective tools in the study of phenomena or systems that involve large time- and length-scales. By decreasing the degrees of freedom in the system and using softer interactions than seen in atomistic models, larger timesteps can be used and much longer simulation times can be studied. CG simulations are widely used to study systems of biological importance that are beyond the reach of atomistic simulation, necessitating a computationally efficient and accurate CG model for water. In this review, we discuss the methods used for developing CG water models and the relative advantages and disadvantages of the resulting models. In general, CG water models differ with regards to how many waters each CG group or bead represents, whether analytical or tabular potentials have been used to describe the interactions, and how the model incorporates electrostatic interactions. Finally, how the models are parameterized depends on their application, so, while some are fitted to experimental properties such as surface tension and density, others are fitted to radial distribution functions extracted from atomistic simulations.     

Aggregation of Lipid-Anchored Full-Length H-Ras in Lipid Bilayers: Simulations with the MARTINI Force Field

Lipid-anchored Ras oncoproteins assemble into transient, nano-sized substructures on the plasma membrane. These substructures, called nanoclusters, were proposed to be crucial for high-fidelity signal transmission in cells. However, the molecular basis of Ras nanoclustering is poorly understood. In this work, we used coarse-grained (CG) molecular dynamics simulations to investigate the molecular mechanism by which full-length H-ras proteins form nanoclusters in a model membrane. We chose two different conformations of H-ras that were proposed to represent the active and inactive state of the protein, and a domain-forming model bilayer made up of di16:0-PC (DPPC), di18:2-PC (DLiPC) and cholesterol. We found that, irrespective of the initial conformation, Ras molecules assembled into a single large aggregate. However, the two binding modes, which are characterized by the different orientation of the G-domain with respect to the membrane, differ in dynamics and organization during and after aggregation. Some of these differences involve regions of Ras that are important for effector/modulator binding, which may partly explain observed differences in the ability of active and inactive H-ras nanoclusters to recruit effectors. The simulations also revealed some limitations in the CG force field to study protein assembly in solution, which we discuss in the context of proposed potential avenues of improvement.     

Implementation of residue-level coarse-grained models in GENESIS for large-scale molecular dynamics simulations

Residue-level coarse-grained (CG) models have become one of the most popular tools in biomolecular simulations in the trade-off between modeling accuracy and computational efficiency. To investigate large-scale biological phenomena in molecular dynamics (MD) simulations with CG models, unified treatments of proteins and nucleic acids, as well as efficient parallel computations, are indispensable. In the GENESIS MD software, we implement several residue-level CG models, covering structure-based and context-based potentials for both well-folded biomolecules and intrinsically disordered regions. An amino acid residue in protein is represented as a single CG particle centered at the Cα atom position, while a nucleotide in RNA or DNA is modeled with three beads. Then, a single CG particle represents around ten heavy atoms in both proteins and nucleic acids. The input data in CG MD simulations are treated as GROMACS-style input files generated from a newly developed toolbox, GENESIS-CG-tool. To optimize the performance in CG MD simulations, we utilize multiple neighbor lists, each of which is attached to a different nonbonded interaction potential in the cell-linked list method. We found that random number generations for Gaussian distributions in the Langevin thermostat are one of the bottlenecks in CG MD simulations. Therefore, we parallelize the computations with message-passing-interface (MPI) to improve the performance on PC clusters or supercomputers. We simulate Herpes simplex virus (HSV) type 2 B-capsid and chromatin models containing more than 1,000 nucleosomes in GENESIS as examples of large-scale biomolecular simulations with residue-level CG models. This framework extends accessible spatial and temporal scales by multi-scale simulations to study biologically relevant phenomena, such as genome-scale chromatin folding or phase-separated membrane-less condensations.     

A multiscale coarse-grained model of the SARS-CoV-2 virion

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the COVID-19 pandemic. Computer simulations of complete viral particles can provide theoretical insights into large-scale viral processes including assembly, budding, egress, entry, and fusion. Detailed atomistic simulations are constrained to shorter timescales and require billion-atom simulations for these processes. Here, we report the current status and ongoing development of a largely “bottom-up” coarse-grained (CG) model of the SARS-CoV-2 virion. Data from a combination of cryo-electron microscopy (cryo-EM), x-ray crystallography, and computational predictions were used to build molecular models of structural SARS-CoV-2 proteins, which were then assembled into a complete virion model. We describe how CG molecular interactions can be derived from all-atom simulations, how viral behavior difficult to capture in atomistic simulations can be incorporated into the CG models, and how the CG models can be iteratively improved as new data become publicly available. Our initial CG model and the detailed methods presented are intended to serve as a resource for researchers working on COVID-19 who are interested in performing multiscale simulations of the SARS-CoV-2 virion.     

Coarse-Graining Provides Insights on the Essential Nature of Heterogeneity in Actin Filaments

Experiments have shown that actin is structurally polymorphic, but knowledge of the details of molecular level heterogeneity in both the dynamics of a single subunit and the interactions between subunits is still lacking. Here, using atomistic molecular dynamics simulations of the actin filament, we identify domains of atoms that move in a correlated fashion, quantify interactions between these domains using coarse-grained (CG) analysis methods, and perform CG simulations to explore the importance of filament heterogeneity. The persistence length and torsional stiffness calculated from molecular dynamics simulation data agree with experimental values. We additionally observe that distinct actin conformations coexist in actin filaments. The filaments also exhibit random twist angles that are broadly distributed. CG analysis reveals that interactions between equivalent CG pairs vary from one subunit to another. To explore the importance of heterogeneity on filament dynamics, we perform CG simulations using different methods of parameterization to show that only by including heterogeneous interactions can we reproduce the twist angles and related properties. Free energy calculations further suggest that in general the actin filament is best represented as a set of subunits with differing CG sites and interactions, and the incorporating heterogeneity into the CG interactions is more important than including that in the CG sites. Our work therefore presents a systematic method to explore molecular level detail in this large and complex biopolymer.     

Identification of Drosophila neuropeptide receptors by G protein-coupled receptors-beta-arrestin2 interactions

Activation of G protein-coupled receptors (GPCR) leads to the recruitment of beta-arrestins. By tagging the beta-arrestin molecule with a green fluorescent protein, we can visualize the activation of GPCRs in living cells. We have used this approach to de-orphan and study 11 GPCRs for neuropeptide receptors in Drosophila melanogaster. Here we verify the identities of ligands for several recently de-orphaned receptors, including the receptors for the Drosophila neuropeptides proctolin (CG6986), neuropeptide F (CG1147), corazonin (CG10698), dFMRF-amide (CG2114), and allatostatin C (CG7285 and CG13702). We also de-orphan CG6515 and CG7887 by showing these two suspected tachykinin receptor family members respond specifically to a Drosophila tachykinin neuropeptide. Additionally, the translocation assay was used to de-orphan three Drosophila receptors. We show that CG14484, encoding a receptor related to vertebrate bombesin receptors, responds specifically to allatostatin B. Furthermore, the pair of paralogous receptors CG8985 and CG13803 responds specifically to the FMRF-amide-related peptide dromyosuppressin. To corroborate the findings on orphan receptors obtained by the translocation assay, we show that dromyosuppressin also stimulated GTPgammaS binding and inhibited cAMP by CG8985 and CG13803. Together these observations demonstrate the beta-arrestin-green fluorescent protein translocation assay is an important tool in the repertoire of strategies for ligand identification of novel G protein-coupled receptors.     

Interpretation of H-NMR Experiments on the Orientation of the Transmembrane Helix WALP23 by Computer Simulations

Orientation, dynamics, and packing of transmembrane helical peptides are important determinants of membrane protein structure, dynamics, and function. Because it is difficult to investigate these aspects by studying real membrane proteins, model transmembrane helical peptides are widely used. NMR experiments provide information on both orientation and dynamics of peptides, but they require that motional models be interpreted. Different motional models yield different interpretations of quadrupolar splittings (QS) in terms of helix orientation and dynamics. Here, we use coarse-grained (CG) molecular dynamics (MD) simulations to investigate the behavior of a well-known model transmembrane peptide, WALP23, under different hydrophobic matching/mismatching conditions. We compare experimental ²H-NMR QS (directly measured in experiments), as well as helix tilt angle and azimuthal rotation (not directly measured), with CG MD simulation results. For QS, the agreement is significantly better than previously obtained with atomistic simulations, indicating that equilibrium sampling is more important than atomistic details for reproducing experimental QS. Calculations of helix orientation confirm that the interpretation of QS depends on the motional model used. Our simulations suggest that WALP23 can form dimers, which are more stable in an antiparallel arrangement. The origin of the preference for the antiparallel orientation lies not only in electrostatic interactions but also in better surface complementarity. In most cases, a mixture of monomers and antiparallel dimers provides better agreement with NMR data compared to the monomer and the parallel dimer. CG MD simulations allow predictions of helix orientation and dynamics and interpretation of QS data without requiring any assumption about the motional model.     

The interaction of phospholipase A2 with a phospholipid bilayer: coarse-grained molecular dynamics simulations

A number of membrane-active enzymes act in a complex environment formed by the interface between a lipid bilayer and bulk water. Although x-ray diffraction studies yield structures of isolated enzyme molecules, a detailed characterization of their interactions with the interface requires a measure of how deeply such a membrane-associated protein penetrates into a lipid bilayer. Here, we apply coarse-grained (CG) molecular dynamics (MD) simulations to probe the interaction of porcine pancreatic phospholipase A2 (PLA2) with a lipid bilayer containing palmitoyl-oleoyl-phosphatidyl choline and palmitoyl-oleoyl-phosphatidyl glycerol molecules. We also used a configuration from a CG-MD trajectory to initiate two atomistic (AT) MD simulations. The results of the CG and AT simulations are evaluated by comparison with available experimental data. The membrane-binding surface of PLA2 consists of a patch of hydrophobic residues surrounded by polar and basic residues. We show this proposed footprint interacts preferentially with the anionic headgroups of the palmitoyl-oleoyl-phosphatidyl glycerol molecules. Thus, both electrostatic and hydrophobic interactions determine the location of PLA2 relative to the bilayer. From a general perspective, this study demonstrates that CG-MD simulations may be used to reveal the orientation and location of a membrane-surface-bound protein relative to a lipid bilayer, which may subsequently be refined by AT-MD simulations to probe more detailed interactions.     

The thermosetting resin prepared by curing reaction of typical soybean oil and properties of the product network structures: a multiscale simulation study

With our multiscale simulation strategy developed previously, we study the curing reaction of soybean oil and styrene to prepare a thermosetting resin. From atomistic simulation details, we estimate the parameters used in coarse-grained (CG) simulations. Then, with the mesoscopic dissipative particle dynamics simulation, the CG network structure and average cross-linking density of a material can be obtained. Finally, the reverse-mapping scheme of the CG structure to atomistic representation is carried out to analyse the mechanical properties and the glass transition temperature of the system. We find in such a system that the molar ratio of double bonds in the two reactants plays a significant role in determining the physical properties of a product. These results shed light on improved control and design of thermosetting resin material via curing reaction of soybean oil.     

CpG methylation recruits sequence specific transcription factors essential for tissue specific gene expression

CG methylation is an epigenetically inherited chemical modification of DNA found in plants and animals. In mammals it is essential for accurate regulation of gene expression and normal development. Mammalian genomes are depleted for the CG dinucleotide, a result of the chemical deamination of methyl-cytosine in CG resulting in TpG. Most CG dinucleotides are methylated, but ~ 15% are unmethylated. Five percent of CGs cluster into ~ 20,000 regions termed CG islands (CGI) which are generally unmethylated. About half of CGIs are associated with housekeeping genes. In contrast, the gene body, repeats and transposable elements in which CGs are generally methylated. Unraveling the epigenetic machinery operating in normal cells is important for understanding the epigenetic aberrations that are involved in human diseases including cancer. With the advent of high-throughput sequencing technologies, it is possible to identify the CG methylation status of all 30 million unique CGs in the human genome, and monitor differences in distinct cell types during differentiation and development. Here we summarize the present understanding of DNA methylation in normal cells and discuss recent observations that CG methylation can have an effect on tissue specific gene expression. We also discuss how aberrant CG methylation can lead to cancer. This article is part of a Special Issue entitled: Chromatin in time and space.     

Characterisation of the hydrophobic collapse of polystyrene in water using free energy techniques

We characterise the hydrophobic collapse of single polystyrene chains in water using molecular dynamics simulations. Specifically, we calculate the potential of mean force for the collapse of a single polystyrene chain in water using metadynamics, comparing the results between all atomistic with coarse-grained (CG) molecular simulation. We next explore the scaling behaviour of the collapsed globular shape at the minimum energy configuration, characterised by the radius of gyration, as a function of chain length. The exponent is close to one third, consistent with that predicted for a polymer chain in bad solvent. We also explore the scaling behaviour of the solvent accessible surface area (SASA) as a function of chain length, finding a similar exponent for both all atomistic and CG simulations. Furthermore, calculation of the local water density as a function of chain length near the minimum energy configuration suggests that intermediate chain lengths are more likely to form dewetted states, as compared to shorter or longer chain lengths.     

Conformational flexibility of the leucine binding protein examined by protein domain coarse-grained molecular dynamics

Periplasmic binding proteins are the initial receptors for the transport of various substrates over the inner membrane of gram-negative bacteria. The binding proteins are composed of two domains, and the substrate is entrapped between these domains. For several of the binding proteins it has been established that a closed-up conformation exists even without substrate present, suggesting a highly flexible apo-structure which would compete with the ligand-bound protein for the transporter interaction. For the leucine binding protein (LBP), structures of both open and closed conformations are known, but no closed-up structure without substrate has been reported. Here we present molecular dynamics simulations exploring the conformational flexibility of LBP. Coarse grained models based on the MARTINI force field are used to access the microsecond timescale. We show that a standard MARTINI model cannot maintain the structural stability of the protein whereas the ELNEDIN extension to MARTINI enables simulations showing a stable protein structure and nanosecond dynamics comparable to atomistic simulations, but does not allow the simulation of conformational flexibility. A modification to the MARTINI-ELNEDIN setup, referred to as domELNEDIN, is therefore presented. The domELNEDIN setup allows the protein domains to move independently and thus allows for the simulation of conformational changes. Microsecond domELNEDIN simulations starting from either the open or the closed conformations consistently show that also for LBP, the apo-structure is flexible and can exist in a closed form.

Coarse-grained modeling of the actin filament derived from atomistic-scale simulations

A coarse-grained (CG) procedure that incorporates the information obtained from all-atom molecular dynamics (MD) simulations is presented and applied to actin filaments (F-actin). This procedure matches the averaged values and fluctuations of the effective internal coordinates that are used to define a CG model to the values extracted from atomistic MD simulations. The fluctuations of effective internal coordinates in a CG model are computed via normal-mode analysis (NMA), and the computed fluctuations are matched with the atomistic MD results in a self-consistent manner. Each actin monomer (G-actin) is coarse-grained into four sites, and each site corresponds to one of the subdomains of G-actin. The potential energy of a CG G-actin contains three bonds, two angles, and one dihedral angle; effective harmonic bonds are used to describe the intermonomer interactions in a CG F-actin. The persistence length of a CG F-actin was found to be sensitive to the cut-off distance of assigning intermonomer bonds. Effective harmonic bonds for a monomer with its third nearest neighboring monomers are found to be necessary to reproduce the values of persistence length obtained from all-atom MD simulations. Compared to the elastic network model, incorporating the information of internal coordinate fluctuations enhances the accuracy and robustness for a CG model to describe the shapes of low-frequency vibrational modes. Combining the fluctuation-matching CG procedure and NMA, the achievable time- and length scales of modeling actin filaments can be greatly enhanced. In particular, a method is described to compute the force-extension curve using the CG model developed in this work and NMA. It was found that F-actin is easily buckled under compressive deformation, and a writhing mode is developed as a result. In addition to the bending and twisting modes, this novel writhing mode of F-actin could also play important roles in the interactions of F-actin with actin-binding proteins and in the force-generation process via polymerization.     

Multiscale Coarse-Grained Approach to Investigate Self-Association of Antibodies

Self-association of therapeutic monoclonal antibodies (mabs) are thought to modulate the undesirably high viscosity observed in their concentrated solutions. Computational prediction of such a self-association behavior is advantageous early during mab drug candidate selection when material availability is limited. Here, we present a coarse-grained (CG) simulation method that enables microsecond molecular dynamics simulations of full-length antibodies at high concentrations. The proposed approach differs from others in two ways: first, charges are assigned to CG beads in an effort to reproduce molecular multipole moments and charge asymmetry of full-length antibodies instead of only localized charges. This leads to great improvements in the agreement between CG and all-atom electrostatic fields. Second, the distinctive hydrophobic character of each antibody is incorporated through empirical adjustments to the short-range van der Waals terms dictated by cosolvent all-atom molecular dynamics simulations of antibody variable regions. CG simulations performed on a set of 15 different mabs reveal that diffusion coefficients in crowded environments are markedly impacted by intermolecular interactions. Diffusion coefficients computed from the simulations are in correlation with experimentally measured observables, including viscosities at a high concentration. Further, we show that the evaluation of electrostatic and hydrophobic characters of the mabs is useful in predicting the nonuniform effect of salt on the viscosity of mab solutions. This CG modeling approach is particularly applicable as a material-free screening tool for selecting antibody candidates with desirable viscosity properties.     

Peptide Aggregation and Pore Formation in a Lipid Bilayer: A Combined Coarse-Grained and All Atom Molecular Dynamics Study

We present a simulation study where different resolutions, namely coarse-grained (CG) and all-atom (AA) molecular dynamics simulations, are used sequentially to combine the long timescale reachable by CG simulations with the high resolution of AA simulations, to describe the complete processes of peptide aggregation and pore formation by alamethicin peptides in a hydrated lipid bilayer. In the 1-μs CG simulations the peptides spontaneously aggregate in the lipid bilayer and exhibit occasional transitions between the membrane-spanning and the surface-bound configurations. One of the CG systems at t = 1 μs is reverted to an AA representation and subjected to AA simulation for 50 ns, during which water molecules penetrate the lipid bilayer through interactions with the peptide aggregates, and the membrane starts leaking water. During the AA simulation significant deviations from the α-helical structure of the peptides are observed, however, the size and arrangement of the clusters are not affected within the studied time frame. Solid-state NMR experiments designed to match closely the setup used in the molecular dynamics simulations provide strong support for our finding that alamethicin peptides adopt a diverse set of configurations in a lipid bilayer, which is in sharp contrast to the prevailing view of alamethicin oligomers formed by perfectly aligned helical alamethicin peptides in a lipid bilayer.     

Structure-Based Simulations of the Translocation Mechanism of the Hepatitis C Virus NS3 Helicase along Single-Stranded Nucleic Acid

The NS3 helicase of Hepatitis C virus is an ATP-fueled molecular motor that can translocate along single-stranded (ss) nucleic acid, and unwind double-stranded nucleic acids. It makes a promising antiviral target and an important prototype system for helicase research. Despite recent progress, the detailed mechanism of NS3 helicase remains unknown. In this study, we have combined coarse-grained (CG) and atomistic simulations to probe the translocation mechanism of NS3 helicase along ssDNA. At the residue level of detail, our CG simulations have captured functionally important interdomain motions of NS3 helicase and reproduced single-base translocation of NS3 helicase along ssDNA in the 3′–5′ direction, which is in good agreement with experimental data and the inchworm model. By combining the CG simulations with residue-specific perturbations to protein-DNA interactions, we have identified a number of key residues important to the translocation machinery that agree with previous structural and mutational studies. Additionally, our atomistic simulations with targeted molecular dynamics have corroborated the findings of CG simulations and further revealed key protein-DNA hydrogen bonds that break/form during the transitions. This study offers, to our knowledge, the most detailed and realistic simulations of translocation mechanism of NS3 helicase. The simulation protocol established in this study will be useful for designing inhibitors that target the translocation machinery of NS3 helicase, and for simulations of a variety of nucleic-acid-based molecular motors.