Coarse-grained Force Field Research Articles

Mapping scheme as key element in coarse-graining of methacrylate-based polymers

Atomistic molecular modelling of polymeric hybrid materials becomes more relevant with continually increasing computing power. Currently, the simulations are still limited to medium size atomistic models, although polymer dynamics demand large polymer chain models and time scales. Coarse-graining of atomistic polymer models is aiming at the transfer of structure related properties from fully atomistic models to bead representations having less degrees of freedom but allowing the increase of model size and time scales. Key for a successful bead representation is the mapping scheme. Although there are a lot of meaningful approaches for polymer mapping schemes available (e. g. mapping one repeat unit to one bead), the successful development is not always a trivial task and every approach has advantages and shortcomings. Even for the rather “simple” polystyrene at least seven different and meaningful mapping scheme approaches are known (H. A. Karimi-Varzaneh, N. F. A. van der Vegt, F. Müller-Plathe, P. Carbone, ChemPhysChem2012, 13, 3428.).Here, we show the importance of the mapping scheme for a more sophisticated hybrid material substance and evaluate its quality, i. e. speedup and atomistic model representation by the coarse-grained models. The degree of coarse-graining of different mapping schemes is discussed. The coarse-grained models are evaluated according to their glass transition analysis in comparison to the full atomistic glass transition analysis. It is shown, that the choice of the mapping scheme becomes more crucial with increasing monomer complexity. Finally, the trade-off between efficiency, i. e. time-saving with speed-up during simulation vs. time-loss for coarse-grained force field parameter development, and quality of results, i. e. comparability with fully atomistic models, has to be considered carefully.

SARS-CoV-2 omicron RBD forms a weaker binding affinity to hACE2 compared to Delta RBD in in-silico studies

The COVID-19 pandemic sparked an unprecedented race in biotechnology in a search for effective therapies and a preventive vaccine. The continued appearance of SARS-CoV-2 variants of concern (VoCs) further swept the world. The entry of SARS-CoV-2 into cells is mediated by binding the receptor-binding domain (RBD) of the S protein to the cell-surface receptor, human angiotensin-converting enzyme 2 (hACE2). In this study, using a coarse-grained force field to parameterize the system, we employed steered-molecular dynamics (SMD) simulations to reveal the binding of SARS-CoV-2 Delta/Omicron RBD to hACE2. Our benchmarked results demonstrate a good correlation between computed rupture force and experimental binding free energy for known protein-protein systems. Moreover, our findings show that the Omicron RBD has a weaker binding affinity to hACE2, consistent with the respective experimental results. This indicates that our method can effectively be applied to other emerging SARS-CoV-2 strains. Communicated by Ramaswamy H. Sarma

Automatic Optimization of Lipid Models in the Martini Force Field Using SwarmCG.

After two decades of continued development of the Martini coarse-grained force field (CG FF), further refinment of the already rather accurate Martini lipid models has become a demanding task that could benefit from integrative data-driven methods. Automatic approaches are increasingly used in the development of accurate molecular models, but they typically make use of specifically designed interaction potentials that transfer poorly to molecular systems or conditions different than those used for model calibration. As a proof of concept, here, we employ SwarmCG, an automatic multiobjective optimization approach facilitating the development of lipid force fields, to refine specifically the bonded interaction parameters in building blocks of lipid models within the framework of the general Martini CG FF. As targets of the optimization procedure, we employ both experimental observables (top-down references: area per lipid and bilayer thickness) and all-atom molecular dynamics simulations (bottom-up reference), which respectively inform on the supra-molecular structure of the lipid bilayer systems and on their submolecular dynamics. In our training sets, we simulate at different temperatures in the liquid and gel phases up to 11 homogeneous lamellar bilayers composed of phosphatidylcholine lipids spanning various tail lengths and degrees of (un)saturation. We explore different CG representations of the molecules and evaluate improvements a posteriori using additional simulation temperatures and a portion of the phase diagram of a DOPC/DPPC mixture. Successfully optimizing up to ∼80 model parameters within still limited computational budgets, we show that this protocol allows the obtainment of improved transferable Martini lipid models. In particular, the results of this study demonstrate how a fine-tuning of the representation and parameters of the models may improve their accuracy and how automatic approaches, such as SwarmCG, may be very useful to this end.

In silico induced effect of N-ε-lysine acetylation on microtubule stability and subsequent interaction of microtubule-associated proteins.

Plant systems have been considered valuable models for addressing fundamental questions of microtubule (MT) organization due to their considerable practical utility. Protein acetylation is a very common protein modification, and therate of acetylation can be modulated in cells in different biological states, and these changes can be detected at a molecular level. Here, we focused on K40, K112, and K394 residues as putative acetylation sites, which were shown to exist in both plants and mammals. Such residual effect of acetylation causes critical but unclear effect on MT stability. In turn, it was shown that acetylation indirectly affects the probability of interaction with different MAPs (Microtubule-associated proteins). In a multiscale study using an all-atom force field to reproduce several lattice-forming elements found on the surface the microtubule, we assembled a fragment of a plant microtubule composed of nine tubulins and used it as a model object along with the existing human complex. Triplets of tubulins assembled in a lattice cell were then simulated for both human and plant protein complexes, using a coarse-grained force field. We then analyzed the trajectories and identified some critical deformations of the MAP interaction surface. The initial coordinates were used to investigate the structural scenario in which autophagy-related protein 8 (ATG8) was able to interact with the MT fragment.

Long-Time Dynamics of Selected Molecular-Motor Components Using a Physics-Based Coarse-Grained Approach.

Molecular motors are essential for the movement and transportation of macromolecules in living organisms. Among them, rotatory motors are particularly efficient. In this study, we investigated the long-term dynamics of the designed left-handed alpha/alpha toroid (PDB: 4YY2), the RBM2 flagellum protein ring from Salmonella (PDB: 6SD5), and the V-type Na+-ATPase rotor in Enterococcus hirae (PDB: 2BL2) using microcanonical and canonical molecular dynamics simulations with the coarse-grained UNRES force field, including a lipid-membrane model, on a millisecond laboratory time scale. Our results demonstrate that rotational motion can occur with zero total angular momentum in the microcanonical regime and that thermal motions can be converted into net rotation in the canonical regime, as previously observed in simulations of smaller cyclic molecules. For 6SD5 and 2BL2, net rotation (with a ratcheting pattern) occurring only about the pivot of the respective system was observed in canonical simulations. The extent and direction of the rotation depended on the initial conditions. This result suggests that rotatory molecular motors can convert thermal oscillations into net rotational motion. The energy from ATP hydrolysis is required probably to set the direction and extent of rotation. Our findings highlight the importance of molecular-motor structures in facilitating movement and transportation within living organisms.

Investigating the Impact of the Glycolipid Content on Aurein 1.2 Pores in Prokaryotic Model Bilayers: A Coarse-Grain Molecular Dynamics Simulation Study.

Aurein 1.2 is an antimicrobial peptide (AMP) with known lytic activity against bacterial membranes. Our previous studies revealed a differential action of aurein by both experimental and computational methods. This differential action was over membranes of two related probiotic strains, where the main difference between membranes was the number of glycolipids in the lipid composition. In this work, we aimed to investigate the interaction of aurein 1.2 with model bacterial membranes of varying glycolipid content. To this end, we performed extensive molecular dynamics simulations using the MARTINI coarse-grain force field and differential mixtures of phosphatidylglycerol (PG), phosphatidylethanolamine (PE), and monogalactosylglycerol (MG). We found a correlation between the presence of MG in PG/PE mixtures and the difficulty of aurein to stabilize pore structures, suggesting an AMP-resistance factor encoded in the lipid composition of the membrane. These findings may shed light on a possible mechanism of bacterial resistance to AMPs that is related to the glycolipid content of bacterial membranes.

Design single-stranded DNA aptamer of cluster of differentiation 47 protein by stochastic tunnelling-basin hopping-discrete molecular dynamics method

The formation of the Cluster of Differentiation 47 (CD47, PDB code: 2JJT)/signal regulatory protein α (SIRPα) complex is very important as it protects healthy cells from immune clearance while promoting macrophage phagocytosis for tumour elimination. Although several antibodies have been developed for cancer therapy, new function-blocking aptamers are still under development. This study aims to design the aptamer AptCD47, which can block the formation of the CD47/SIRPα complex. This study employs the MARTINI coarse-grained (CG) force field and the stochastic tunnelling-basin hopping-discrete molecular dynamics (STUN-BH-DMD) method to identify the most stable AptCD47/CD47 complexes. Coarse-grained molecular dynamics (CGMD) simulations were used to obtain root-mean-square deviation (RMSD) and root-mean-square fluctuation (RMSF) analyses. The results demonstrate that the formation of AptCD47/CD47 complexes renders the CD47 structure more stable than the single CD47 molecule in a water environment. The minimum energy pathway (MEP) obtained by the nudged elastic band (NEB) method indicates that the binding processes of 5′-ATTCAATTCC-3′ and 5′-AGTGCAATCT-3′ to CD47 are barrierless, which is much lower than the binding barrier of SIRPα to CD47 of about 14.23 kcal/mol. Therefore, these two AptCD47/CD47 complexes can create a high spatial binding barrier for SIRPα, preventing the formation of a stable CD47/SIRPα complex. The proposed numerical process with the MARTINI CG force field can be used to design CD47 aptamers that efficiently block SIRPα from binding to CD47. Communicated by Ramaswamy H. Sarma

Application of coarse-grained water model in the study of mixed collectors compounding mechanism in low-rank coal flotation

ABSTRACT The investigation of the compounding mechanisms of mixed collectors in low-rank coal flotation has gradually progressed from a macro to a micro level, and the accuracy of research outcomes significantly depends on the development of micro models. While All-Atom Molecular Dynamics (AAMD) simulations have been used for this purpose, the employment of an excessive amount of collector in the system leads to a failure in replicating the actual flotation process, which in turn, limits the practical applicability of research findings. To overcome this drawback, this paper suggests using the MARTINI Coarse-Grained force field (CGFF), developed by the S.J.Marrink group, to construct a simulation system that accurately mimics the amount of collector employed in practical flotation processes. In light of this, to make the MARTINI force field more applicable for research in the low-rank coal field, we employ density functional theory (DFT) and coarse-grained molecular dynamics (CGMD) methods to investigate water cluster interactions, identify magic number clusters, and fit the corresponding CGFF parameters to develop a CG water model suitable for exploring the compounding mechanism of mixed collectors. This research lays the groundwork for future investigations into the aggregation behavior of mixed collectors under actual usage conditions, as well as their synergistic adsorption at the coal/water interface.

RNA Folding Based on 5 Beads Model and Multiscale Simulation.

RNA folding prediction is very meaningful and challenging. The molecular dynamics simulation (MDS) of all atoms (AA) is limited to the folding of small RNA molecules. At present, most of the practical models are coarse grained (CG) model, and the coarse-grained force field (CGFF) parameters usually depend on known RNA structures. However, the limitation of the CGFF is obvious that it is difficult to study the modified RNA. Based on the 3 beads model (AIMS_RNA_B3), we proposed the AIMS_RNA_B5 model with three beads representing a base and two beads representing the main chain (sugar group and phosphate group). We first run the all atom molecular dynamic simulation (AAMDS), and fit the CGFF parameter with the AA trajectory. Then perform the coarse-grained molecular dynamic simulation (CGMDS). AAMDS is the foundation of CGMDS. CGMDS is mainly to carry out the conformation sampling based on the current AAMDS state and improve the folding speed. We simulated the folding of three RNAs, which belong to hairpin, pseudoknot and tRNA respectively. Compared to the AIMS_RNA_B3 model, the AIMS_RNA_B5 model is more reasonable and performs better.

Dynamic viscosity and interfacial tension of CO2 and n-tetracosane system by dynamic light scattering method and molecular simulation

In this work, the viscosity and interfacial tension of the CO2 + n-tetracosane system were obtained experimentally by dynamic light scattering method at the temperature range of 423.15 ∼ 473.15 K and the pressure range of 1 ∼ 5 MPa. A new coarse-grained force field for n-C24H50 was established with intramolecular parameters fitted according to the LOPLS all-atom force field and intermolecular parameters fitted according to the viscosity and interfacial tension of the pure n-C24H50. The viscosity and interfacial tension of CO2 + n-C24H50 were calculated by molecular simulation, and the average relative deviations between the calculated and experimental data are 5.2% and 9.9%, respectively. The minimum mixed-phase pressures of the CO2 + n-C24H50 were calculated to be 26.93 MPa, 27.14 MPa and 27.47 MPa at 423.15 K, 448.15 K and 473.15 K, respectively.

Statistically Optimal Force Aggregation for Coarse-Graining Molecular Dynamics

Machine-learned coarse-grained (CG) models have the potential for simulating large molecular complexes beyond what is possible with atomistic molecular dynamics. However, training accurate CG models remains a challenge. A widely used methodology for learning bottom-up CG force fields maps forces from all-atom molecular dynamics to the CG representation and matches them with a CG force field on average. We show that there is flexibility in how to map all-atom forces to the CG representation and that the most commonly used mapping methods are statistically inefficient and potentially even incorrect in the presence of constraints in the all-atom simulation. We define an optimization statement for force mappings and demonstrate that substantially improved CG force fields can be learned from the same simulation data when using optimized force maps. The method is demonstrated on the miniproteins chignolin and tryptophan cage and published as open-source code.

Optimized OPEP Force Field for Simulation of Crowded Protein Solutions.

Macromolecular crowding has profound effects on the mobility of proteins, with strong implications on the rates of intracellular processes. To describe the dynamics of crowded environments, detailed molecular models are needed, capturing the structures and interactions arising in the crowded system. In this work, we present OPEPv7, which is a coarse-grained force field at amino-acid resolution, suited for rigid-body simulations of the structure and dynamics of crowded solutions formed by globular proteins. Using the OPEP protein model as a starting point, we have refined the intermolecular interactions to match the experimentally observed dynamical slowdown caused by crowding. The resulting force field successfully reproduces the diffusion slowdown in homogeneous and heterogeneous protein solutions at different crowding conditions. Coupled with the lattice Boltzmann technique, it allows the study of dynamical phenomena in protein assemblies and opens the way for the in silico rheology of protein solutions.

An implementation of the Martini coarse-grained force field in OpenMM

We describe a complete implementation of Martini 2 and Martini 3 in the OpenMM molecular dynamics software package. Martini is a widely used coarse-grained force field with applications in biomolecular simulation, materials, and broader areas of chemistry. It is implemented as a force field but makes extensive use of facilities unique to the GROMACS software, including virtual sites and bonded terms that are not commonly used in standard atomistic force fields. OpenMM is a flexible molecular dynamics package widely used for methods development and is competitive in speed on GPUs with other commonly used packages. OpenMM has facilities to easily implement new force field terms, external forces and fields, and other nonstandard features, which we use to implement all force field terms used in Martini 2 and Martini 3. This allows Martini simulations, starting with GROMACS topology files that are processed by custom scripts, with all the added flexibility of OpenMM. We provide a GitHub repository with test cases, compare accuracy and performance between GROMACS and OpenMM, and discuss the limitations of our implementation in terms of direct comparison with GROMACS. We describe a use case that implements the Modeling Employing Limited Data method to apply experimental constraints in a Martini simulation to efficiently determine the structure of a protein complex. We also discuss issues and a potential solution with the Martini 2 topology for cholesterol.

Experiment and Simulation Reveal Residue Details for How Target Binding Tunes Calmodulin's Calcium-Binding Properties.

We aim to elucidate the molecular mechanism of the reciprocal relation of calmodulin's (CaM) target binding and its affinity for calcium ions (Ca2+), which is central to decoding CaM-dependent Ca2+ signaling in a cell. We employed stopped-flow experiments and coarse-grained molecular simulations that learn the coordination chemistry of Ca2+ in CaM from first-principle calculations. The associative memories as part of the coarse-grained force fields built on known protein structures further influence CaM's selection of its polymorphic target peptides in the simulations. We modeled the peptides from the Ca2+/CaM-binding domain of Ca2+/CaM-dependent kinase II (CaMKII), CaMKIIp (293-310) and selected distinctive mutations at the N-terminus. Our stopped-flow experiments have shown that the CaM's affinity for Ca2+ in the bound complex of Ca2+/CaM/CaMKIIp decreased significantly when Ca2+/CaM bound to the mutant peptide (296-AAA-298) compared to that bound to the wild-type peptide (296-RRK-298). The coarse-grained molecular simulations revealed that the 296-AAA-298 mutant peptide destabilized the structures of Ca2+-binding loops at the C-domain of CaM (c-CaM) due to both loss of electrostatic interactions and differences in polymorphic structures. We have leveraged a powerful coarse-grained approach to advance a residue-level understanding of the reciprocal relation in CaM, that could not be possibly achieved by other computational approaches.

Using the SAFT-γ-Mie to Generate Coarse-Grained Force Fields Useable in Molecular Dynamics Simulations: Describing the Micellar Phases of Polyalkylglycols in Aqueous Solutions

In this work, we showcase the potential of the SAFT-γ-Mie equation of state to obtain, in a top-down approach, coarse-grained molecular models capable of describing micellization phenomena. For this purpose, we selected polyethylene oxide (PEO)/polypropylene oxide (PPO) triblock copolymers in aqueous solutions as a case study. The model was fitted to reproduce the thermophysical properties─liquid densities and vapor pressures─of small PEO/PPO oligomers as well as the activity coefficients or liquid–liquid phase diagrams of their binary mixtures with water. At low concentrations, the MD simulations show the formation of spherical micelles of morphology comparable to experiments, with the characteristic star-shaped or flower-shaped morphology depending on the polymer block sequence. The local structure and molecular conformations were analyzed, showing distinctions between the two types of aggregates. At higher concentrations, depending on the co-polymer sequence, the molecules form larger micelles or coalesce into larger aggregates when signs of phase separation are observed, as expected.

Room for improvement in the initial martini 3 parameterization of peptide interactions

The Martini 3 coarse-grain force field has greatly improved upon its predecessor, having already been successfully employed in several applications. Here, we gauge the accuracy of Martini 2 and 3 protein interactions in two types of systems: coiled coil peptide dimers in water and transmembrane peptides. Coiled coil dimers form incorrectly under Martini 2 and not at all under Martini 3. With transmembrane peptides, Martini 3 represents better the membrane thickness–peptide tilt relationship, but shorter peptides do not remain transmembranar. We discuss related observations, and describe mitigation strategies involving either scaling interactions or restraining the system.

Predicting 3D structures and stabilities for complex RNA pseudoknots in ion solutions

RNA pseudoknots are a kind of important tertiary motif, and the structures and stabilities of pseudoknots are generally critical to the biological functions of RNAs with the motifs. In this work, we have carefully refined our previously developed coarse-grained model with salt effect through involving a new coarse-grained force field and a replica-exchange Monte Carlo algorithm, and employed the model to predict structures and stabilities of complex RNA pseudoknots in ion solutions beyond minimal H-type pseudoknots. Compared with available experimental data, the newly refined model can successfully predict 3D structures from sequences for the complex RNA pseudoknots including SARS-CoV-2 programming-1 ribosomal frameshifting element and Zika virus xrRNA, and can reliably predict the thermal stabilities of RNA pseudoknots with various sequences and lengths over broad ranges of monovalent/divalent salts. In addition, for complex pseudoknots including SARS-CoV-2 frameshifting element, our analyses show that their thermally unfolding pathways are mainly dependent on the relative stabilities of unfolded intermediate states, in analogy to those of minimal H-type pseudoknots.

Coarse-Grained Force Field for Polyethylene Oxide and Polyethylene Glycol Aqueous Solutions Based on a Polarizable Water Model

A new, accurate and transferable coarse-grained (CG) force field (FF) for polyethylene oxide (PEO) and polyethylene glycol (PEG) aqueous solutions based on a polarizable CG water (PCGW) model is developed in this work. A PCGW bead, which represents four water molecules, is modeled as two charged dummy particles connected by two constrained bonds to a central neutral particle; a PEO or PEG oligomer is modeled as a chain with repeated middle beads (PEOM) representing diether groups and two terminal beads (PEOT or PEGT) of a different type compared to PEOM. To describe nonbonded van der Waals interactions, a piecewise Morse potential with four tunable parameters is used. The force parameters are automatically and rigorously optimized by a meta-multilinear interpolation parameterization (meta-MIP) algorithm to simultaneously match multiple thermodynamic properties, including the density, heat of vaporization, vapor-liquid interfacial tension, and solvation free energy of the pure PEO or PEG oligomer bulk system as well as the mixing density and hydration free energy of the oligomer/water binary mixture. Additional thermodynamic and structural properties for longer PEO and PEG polymer aqueous solutions, such as the self-diffusion coefficient, radius of gyration, and end-to-end distance, are predicted to test the accuracy and transferability of this new CG FF. Based on the PCGW model, the presented FF optimization algorithm and strategy can be extended to more complex polyelectrolytes and surfactants.

Short Peptide Self-Assembly in the Martini Coarse-Grain Force Field Family.

ConspectusPivotal to the success of any computational experiment is the ability to make reliable predictions about the system under study and the time required to yield these results. Biomolecular interactions is one area of research that sits in every camp of resolution vs the time required, from the quantum mechanical level to in vivo studies. At an approximate midpoint, there is coarse-grained molecular dynamics, for which the Martini force fields have become the most widely used, fast enough to simulate the entire membrane of a mitochondrion though lacking atom-specific precision. While many force fields have been parametrized to account for a specific system under study, the Martini force field has aimed at casting a wider net with more generalized bead types that have demonstrated suitability for broad use and reuse in applications from protein-graphene oxide coassembly to polysaccharides interactions.In this Account, the progressive (Martini versions 1 through 3) and peripheral (Sour Martini, constant pH, Martini Straight, Dry Martini, etc.) developmental trajectory of the Martini force field will be analyzed in terms of self-assembling systems with a focus on short (two to three amino acids) peptide self-assembly in aqueous environments. In particular, this will focus on the effects of the Martini solvent model and compare how changes in bead definitions and mapping have effects on different systems. Considerable effort in the development of Martini has been expended to reduce the "stickiness" of amino acids to better simulate proteins in bilayers. We have included in this Account a short study of dipeptide self-assembly in water, using all mainstream Martini force fields, to examine their ability to reproduce this behavior. The three most recently released versions of Martini and variations in their solvents are used to simulate in triplicate all 400 dipeptides of the 20 gene-encoded amino acids. The ability of the force fields to model the self-assembly of the dipeptides in aqueoues environments is determined by the measurement of the aggregation propensity, and additional descriptors are used to gain further insight into the dipeptide aggregates.

Scaling Protein-Water Interactions in the Martini 3 Coarse-Grained Force Field to Simulate Transmembrane Helix Dimers in Different Lipid Environments.

Martini 3, the latest version of the widely used Martini force field for coarse-grained molecular dynamics simulations, is a promising tool to investigate proteins in phospholipid bilayers. However, simulating other lipid environments, such as detergent micelles, presents challenges due to the absence of validated parameters for their constituent molecules. Here, we propose parameters for the micelle-forming surfactant, dodecylphosphocholine (DPC). These result in micelle assembly with aggregation numbers in agreement with the experimental values. However, we identified a lack of hydrophobic interactions between transmembrane helix protein dimers and the tails of DPC molecules, preventing insertion and stabilization of the protein in the micelles. This problem was also observed for protein insertion by self-assembling 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) or dipalmitoylphosphatidylcholine (DPPC) bilayers. We propose the reduction of the nonbonded interactions between protein and water beads by 10% as a simple and effective solution to this problem that enables protein encapsulation in phospholipid micelles and bilayers without altering protein dimerization or the bilayer structure.