We present an improved and extended version of our coarse grained lipid model. The new version, coined the MARTINI force field, is parametrized in a systematic way, based on the reproduction of partitioning free energies between polar and apolar phases of a large number of chemical compounds. To reproduce the free energies of these chemical building blocks, the number of possible interaction levels of the coarse-grained sites has increased compared to those of the previous model. Application of the new model to lipid bilayers shows an improved behavior in terms of the stress profile across the bilayer and the tendency to form pores. An extension of the force field now also allows the simulation of planar (ring) compounds, including sterols. Application to a bilayer/cholesterol system at various concentrations shows the typical cholesterol condensation effect similar to that observed in all atom representations.

This paper describes the parametrization of a new coarse grained (CG) model for lipid and surfactant systems. Reduction of the number of degrees of freedom together with the use of short range potentials makes it computationally very efficient. Compared to atomistic models a gain of 3-4 orders of magnitude can be achieved. Micrometer length scales or millisecond time scales are therefore within reach. To encourage applications, the model is kept very simple. Only a small number of coarse grained atom types are defined, which interact using a few discrete levels of interaction. Despite the computational speed and the simplistic nature of the model, it proves to be both versatile in its applications and accurate in its predictions. We show that densities of liquid alkanes from decane up to eicosane can be reproduced to within 5%, and the mutual solubilities of alkanes in water and water in alkanes can be reproduced within 0.5 kT of the experimental values. The CG model for dipalmitoylphosphatidylcholine (DPPC) is shown to aggregate spontaneously into a bilayer. Structural properties such as the area per headgroup and the phosphate-phosphate distance match the experimentally measured quantities closely. The same is true for elastic properties such as the bending modulus and the area compressibility, and dynamic properties such as the lipid lateral diffusion coefficient and the water permeation rate. The distribution of the individual lipid components along the bilayer normal is very similar to distributions obtained from atomistic simulations. Phospholipids with different headgroup (ethanolamine) or different tail lengths (lauroyl, stearoyl) or unsaturated tails (oleoyl) can also be modeled with the CG force field. The experimental area per headgroup can be reproduced for most lipids within 0.02 nm 2 . Finally, the CG model is applied to nonbilayer phases. Dodecylphosphocholine (DPC) aggregates into small micelles that are structurally very similar to ones modeled atomistically, and DOPE forms an inverted hexagonal phase with structural parameters in agreement with experimental data.

Many biologically interesting phenomena occur on a time scale that is too long to be studied by atomistic simulations. These phenomena include the dynamics of large proteins and self-assembly of biological materials. Coarse-grained (CG) molecular modeling allows computer simulations to be run on length and time scales that are 2-3 orders of magnitude larger compared to atomistic simulations, providing a bridge between the atomistic and the mesoscopic scale. We developed a new CG model for proteins as an extension of the MARTINI force field. Here, we validate the model for its use in peptide-bilayer systems. In order to validate the model, we calculated the potential of mean force for each amino acid as a function of its distance from the center of a dioleoylphosphatidylcholine (DOPC) lipid bilayer. We then compared amino acid association constants, the partitioning of a series of model pentapeptides, the partitioning and orientation of WALP23 in DOPC lipid bilayers and a series of KALP peptides in dimyristoylphosphatidylcholine and dipalmitoylphosphatidylcholine (DPPC) bilayers. A comparison with results obtained from atomistic models shows good agreement in all of the tests performed. We also performed a systematic investigation of the partitioning of five series of polyalanine-leucine peptides (with different lengths and compositions) in DPPC bilayers. As expected, the fraction of peptides partitioned at the interface increased with decreasing peptide length and decreasing leucine content, demonstrating that the CG model is capable of discriminating partitioning behavior arising from subtle differences in the amino acid composition. Finally, we simulated the concentration-dependent formation of transmembrane pores by magainin, an antimicrobial peptide. In line with atomistic simulation studies, disordered toroidal pores are formed. In conclusion, the model is computationally efficient and effectively reproduces peptide-lipid interactions and the partitioning of amino acids and peptides in lipid bilayers.

The Martini coarse-grained force field has been successfully used for simulating a wide range of (bio)molecular systems. Recent progress in our ability to test the model against fully atomistic force fields, however, has revealed some shortcomings. Most notable, phenylalanine and proline were too hydrophobic, and dimers formed by polar residues in apolar solvents did not bind strongly enough. Here, we reparametrize these residues either through reassignment of particle types or by introducing embedded charges. The new parameters are tested with respect to partitioning across a lipid bilayer, membrane binding of Wimley-White peptides, and dimerization free energy in solvents of different polarity. In addition, we improve some of the bonded terms in the Martini protein force field that lead to a more realistic length of α-helices and to improved numerical stability for polyalanine and glycine repeats. The new parameter set is denoted Martini version 2.2.

The Martini model, a coarse-grained force field for biomolecular simulations, has found a broad range of applications since its release a decade ago. Based on a building block principle, the model combines speed and versatility while maintaining chemical specificity. Here we review the current state of the model. We describe recent highlights as well as shortcomings, and our ideas on the further development of the model.

To obtain insight in the process of water permeation through a lipid membrane, we performed molecular dynamics simulations on a phospholipid (DPPC)/water system with atomic detail. Since the actual process of permeation is too slow to be studied directly, we deduced the permeation rate indirectly via computation of the free energy and diffusion rate profiles of a water molecule across the bilayer. We conclude that the permeation of water through a lipid membrane cannot be described adequately by a simple homogeneous solubilitydiffusion model. Both the excess free energy and the diffusion rate strongly depend on the position in the membrane, as a result from the inhomogeneous nature of the membrane. The calculated excess free energy profile has a shallow slope and a maximum height of 26 kJ/mol. The diffusion rate is highest in the middle of the membrane where the lipid density is low. In the interfacial region almost all water molecules are bound by the lipid headgroups, and the diffusion turns out to be 1 order of magnitude smaller. The total transport process is essentially determined by the free energy barrier. The rate-limiting step is the permeation through the dense part of the lipid tails, where the resistance is highest. W e found a permeation rate of 7(f3) X 1 t 2 cm/s at 350 K, comparable to experimental values for DPPC membranes, if corrected for the temperature of the simulation. Taking the inhomogeneity of the membrane into account, we define a new "four-region" model which seems to be more realistic than the "two-phase" solubility4iffusion model.

Coarse-grained (CG) simulations have become an essential tool to study a large variety of biomolecular processes, exploring temporal and spatial scales inaccessible to traditional models of atomistic resolution. One of the major simplifications of CG models is the representation of the solvent, which is either implicit or modeled explicitly as a van der Waals particle. The effect of polarization, and thus a proper screening of interactions depending on the local environment, is absent. Given the important role of water as a ubiquitous solvent in biological systems, its treatment is crucial to the properties derived from simulation studies. Here, we parameterize a polarizable coarse-grained water model to be used in combination with the CG MARTINI force field. Using a three-bead model to represent four water molecules, we show that the orientational polarizability of real water can be effectively accounted for. This has the consequence that the dielectric screening of bulk water is reproduced. At the same time, we parameterized our new water model such that bulk water density and oil/water partitioning data remain at the same level of accuracy as for the standard MARTINI force field. We apply the new model to two cases for which current CG force fields are inadequate. First, we address the transport of ions across a lipid membrane. The computed potential of mean force shows that the ions now naturally feel the change in dielectric medium when moving from the high dielectric aqueous phase toward the low dielectric membrane interior. In the second application we consider the electroporation process of both an oil slab and a lipid bilayer. The electrostatic field drives the formation of water filled pores in both cases, following a similar mechanism as seen with atomistically detailed models.

The coarse-grained Martini force field is widely used in biomolecular simulations. Here, we present the refined model, Martini 3 (http://cgmartini.nl), with an improved interaction balance, new bead types, and expanded ability to include specific interactions representing, e.g. hydrogen bonding and electronic polarizability. The new model allows more accurate predictions of molecular packing and interactions in general, which is exemplified with a vast and diverse set of applications, ranging from oil/water partitioning and miscibility data to complex molecular systems, involving protein-protein and protein-lipid interactions and material science applications as ionic liquids and aedamers.