An anisotropic coarse-grained model based on Gay-Berne and electric multipole potentials and its application to simulate a DMPC bilayer in an implicit solvent model

Polarizable atomic multipole-based force field for cholesterol

Cholesterol is one of the essential component of lipid in membrane. We present a polarizable atomic multipole force field (FF) for the molecular dynamic simulation of cholesterol. The FF building process follows the computational framework as the atomic multipole optimized energetics for biomolecular applications (AMOEBA) model. In this framework, the electronics parameters, including atomic monopole moments, dipole moments, and quadrupole moments calculated from ab initio calculations in the gas phase, are applied to represent the charge distribution. Furthermore, the many-body polarization is modeled by following the same pattern of distributed atomic polarizabilities. Then, the bilayers composed of two typical phospholipid molecules, 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC), and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC), in a range of different cholesterol concentrations are built and implemented by molecular dynamics (MD) simulations based on the proposed polarizable FF. The simulation results are statistically analyzed to validate the feasibility of the proposed FF. The structural properties of the bilayers are calculated to compare with the related experimental values. The MD values show the same trend of experimental values changes.Communicated by Ramaswamy H. Sarma.

Developing Hybrid All-Atom and Ultra-Coarse-Grained Models to Investigate Taxol-Binding and Dynein Interactions on Microtubules

Simulating the conformations and functions of biological macromolecules by using all-atom (AA) models is a challenging task due to expensive computational costs. One possible strategy to solve this problem is to develop hybrid all-atom and ultra-coarse-grained (AA/UCG) models of the biological macromolecules. In the AA/UCG scheme, the interest regions are described by AA models, while the other regions are described in the UCG representation. In this study, we develop the hybrid AA/UCG models and apply them to investigate the conformational changes of microtubule-bound tubulins. The simulation results of the hybrid models elucidated the mechanism of why the taxol molecules selectively bound microtubules but not tubulin dimers. In addition, we also explore the interactions of the microtubules and dyneins. Our study shows that the hybrid AA/UCG model has great application potential in studying the function of complex biological systems.

SPICA Force Field for Proteins and Peptides

A coarse-grained (CG) model for peptides and proteins was developed as an extension of the Surface Property fItting Coarse grAined (SPICA) force field (FF). The model was designed to examine membrane proteins that are fully compatible with the lipid membranes of the SPICA FF. A preliminary version of this protein model was created using thermodynamic properties, including the surface tension and density in the SPICA (formerly called SDK) FF. In this study, we improved the CG protein model to facilitate molecular dynamics (MD) simulations with a reproduction of multiple properties from both experiments and all-atom (AA) simulations. An elastic network model was adopted to maintain the secondary structure within a single chain. The side-chain analogues reproduced the transfer free energy profiles across the lipid membrane and demonstrated reasonable association free energy (potential of mean force) in water compared to those from AA MD. A series of peptides/proteins adsorbed onto or penetrated into the membrane simulated by the CG MD correctly predicted the penetration depths and tilt angles of peripheral and transmembrane peptides/proteins as comparable to those in the orientations of proteins in membranes (OPM) database. In addition, the dimerization free energies of several transmembrane helices within a lipid bilayer were comparable to those from experimental estimation. Application studies on a series of membrane protein assemblies, scramblases, and poliovirus capsids demonstrated the good performance of the SPICA FF.

Extension of the CAVS model to the simulation of helical peptides in a membrane environment

Considering the effect of peptide insertion on the dipole potential of the lipid membrane, we extend the CAVS coarse-grained (CG) model to the simulation of helical peptides in a membrane environment. In this approach, the CG scheme for a peptide backbone is similar to the treatment in the united-atom model, while we treated the side chain of an amino acid by grouping 1-3 heavy atoms into a CG unit. The CAVS CG force field for peptides is optimized by reproducing the experimental results for the backbone (φ, ψ) distribution and predicting the PMF profiles of transferring organic molecules in a lipid bilayer membrane obtained from all-atom simulations. The CAVS simulation of a helical peptide in a phosphatidylcholine (PC) lipid bilayer revealed that the insertion of a peptide increases the dipole potential of the PC lipid bilayer, in which the peptide and its neutralized ions make a significant contribution. Finally, we carried out the CAVS simulation for five different helical peptides in the PC lipid bilayer to explore the behavior of peptide tilt, showing excellent agreement with the all-atom simulations. Our work suggests that the peptide tilt should relieve the deformation stress from the lipid bilayer, and the peptide aggregation could reduce the peptide tilt by resisting the deformation stress from the surrounding lipids.

Adsorption of Organic Molecules and Surfactants on Graphene: A Coarse-Grained Study

The research studies on the adsorption of surfactants on graphene help us to know how to use surfactants to exfoliate graphene from graphite or functionalize the graphene surface. Among them, molecular dynamics (MD) simulation has been widely used to investigate the adsorption of organic molecules and surfactants on graphene. In particular, coarse-grained (CG) MD simulation greatly improves the computational efficiency by simplifying the complexity of the studied systems, allowing us to explore the structure and dynamics of complex systems on larger spatial scales and longer time scales. However, an accurate prediction of the adsorption of surfactants on graphene is required by optimizing the interaction between surfactants and graphene, which is often overlooked by some CG models. In this work, we found that an accurate prediction of the adsorption enthalpies of organic molecules on graphene can be achieved by optimizing the interactions between organic molecules and benzene. Meanwhile, we simulated the adsorption of a surfactant on single-layer and double-layer graphene nanosheets, respectively. Our results revealed that increasing the temperature would favor the interactions between hydrophilic groups of surfactants. In addition, we discovered that the surfactant prefers to be adsorbed on the inner surfaces of double-layer graphene compared with the outer surfaces, and this is owing to the dehydration in the middle of double-layer graphene, which is beneficial to the hydrophilic interactions between surfactant molecules inside the double-layer graphene.

Arbitrary Resolution with Two Bead Types Coarse-Grained Strategy and Applications to Protein Recognition

Molecular recognition is a fundamental step in essentially any biological process. However, the kinetic processes during association and dissociation are difficult to be efficiently sampled by direct all-atom molecular dynamics simulations because of the large spatial and temporal scales. Here we propose an arbitrary resolution with two bead types (ART) coarse-grained (CG) strategy that is adept in molecular recognition. ART is a universal user-customized CG strategy that can generate a system-specific CG force field anytime and be applied to any system with an arbitrary CG resolution according to research requirements. ART CG simulations can be very efficiently performed with implicit solvation in prevalent simulation packages and provide interfaces for any enhanced sampling method. We used three applications, HLA-HIV epitope recognition, barnase-barstar association, and trimeric TRAF2 self-assembly, to validate the feasibility of the ART CG strategy, its advantages in protein recognition, and its high performance in simulations. Regular CG simulations can successfully achieve valid protein recognitions without any prior bound structure.

MOLC. A reversible coarse grained approach using anisotropic beads for the modelling of organic functional materials

We describe the development and implementation of a coarse grained (CG) modelling approach where complex organic molecules, and particularly the π-conjugated ones often employed in organic electronics, are modelled in terms of connected sets of attractive-repulsive biaxial Gay-Berne ellipsoidal beads. The CG model is aimed at reproducing realistically large scale morphologies (e.g. up to 100 nm thick films) for the materials involved, while being able to generate, with a back-mapping procedure, atomistic coordinates suitable, with limited effort, to be applied for charge transport calculations. Detailed methodology and an application to the common hole transporter material α-NPD are provided.

Effect of Cholesterol and 6-Ketocholestanol on Membrane Dipole Potential and Sterol Flip-Flop Motion in Bilayer Membranes

A variety of experimental and theoretical approaches have been employed to investigate the sterol flip-flop motion in lipid bilayer membranes. However, the sterol effect on the dipole potential of lipid bilayer membranes is less well studied and the influence of dipole potential on sterol flip-flop motion in lipid bilayer membranes is less well understood. In our previous works, we have demonstrated the performance of our coarse-grained (CG) model in the computation of the dipole potential. In this work, five 30 μs CG simulations of dimyristoylphosphatidylcholine (DMPC) bilayers were carried out at different sterol concentrations (in a range from 10 to 50% mole fraction). Then, a comparison was made between the effects of cholesterol (CHOL) and 6-ketocholestanol (6-KC) on the dipole potential of DMPC lipid bilayers as well as the sterol flip-flop motion. Our CG simulations show that the membrane dipole potential is impacted more significantly by 6-KC than by CHOL. This finding is consistent with recent experimental studies. Meanwhile, our work suggests that the sterol-sterol interactions (in particular, electrostatic interactions) should be critical to the formation of sterol-sterol clusters, which would hinder the sterol flip-flop motion inside the lipid bilayers. This is in support of the recent experimental study on the sterol transportation in lipid bilayer membranes.

Model parameters for simulation of physiological lipids

Coarse grain simulation of proteins in their physiological membrane environment can offer insight across timescales, but requires a comprehensive force field. Parameters are explored for multicomponent bilayers composed of unsaturated lipids DOPC and DOPE, mixed-chain saturation POPC and POPE, and anionic lipids found in bacteria: POPG and cardiolipin. A nonbond representation obtained from multiscale force matching is adapted for these lipids and combined with an improved bonding description of cholesterol. Equilibrating the area per lipid yields robust bilayer simulations and properties for common lipid mixtures with the exception of pure DOPE, which has a known tendency to form nonlamellar phase. The models maintain consistency with an existing lipid-protein interaction model, making the force field of general utility for studying membrane proteins in physiologically representative bilayers.

Coarse-Grained Modeling of Nucleic Acids Using Anisotropic Gay-Berne and Electric Multipole Potentials

In this work, we attempt to apply a coarse-grained (CG) model, which is based on anisotropic Gay-Berne and electric multipole (EMP) potentials, to the modeling of nucleic acids. First, a comparison has been made between the CG and atomistic models (AMBER point-charge model) in the modeling of DNA and RNA hairpin structures. The CG results have demonstrated a good quality in maintaining the nucleic acid hairpin structures, in reproducing the dynamics of backbone atoms of nucleic acids, and in describing the hydrogen-bonding interactions between nucleic acid base pairs. Second, the CG and atomistic AMBER models yield comparable results in modeling double-stranded DNA and RNA molecules. It is encouraging that our CG model is capable of reproducing many elastic features of nucleic acid base pairs in terms of the distributions of the interbase pair step parameters (such as shift, slide, tilt, and twist) and the intrabase pair parameters (such as buckle, propeller, shear, and stretch). Finally, The GBEMP model has shown a promising ability to predict the melting temperatures of DNA duplexes with different lengths.