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.

MDAnalysis (http://mdanalysis.org) is a library for structural and temporal analysis of molecular dynamics (MD) simulation trajectories and individual protein structures. MD simulations of biological molecules have become an important tool to elucidate the relationship between molecular structure and physiological function. Simulations are performed with highly optimized software packages on HPC resources but most codes generate output trajectories in their own formats so that the development of new trajectory analysis algorithms is confined to specific user communities and widespread adoption and further development is delayed. MDAnalysis addresses this problem by abstracting access to the raw simulation data and presenting a uniform object-oriented Python interface to the user. It thus enables users to rapidly write code that is portable and immediately usable in virtually all biomolecular simulation communities. The user interface and modular design work equally well in complex scripted work flows, as foundations for other packages, and for interactive and rapid prototyping work in IPython / Jupyter notebooks, especially together with molecular visualization provided by nglview and time series analysis with pandas. MDAnalysis is written in Python and Cython and uses NumPy arrays for easy interoperability with the wider scientific Python ecosystem. It is widely used and forms the foundation for more specialized biomolecular simulation tools. MDAnalysis is available under the GNU General Public License v2.

Nonionic surfactants are used for the isolation and purification of membrane proteins, as well as for the study of fundamental aspects of protein diffusion in membranes. Here we present a new coarse-grained model of polyethylene glycol (PEG) and of the family of polyoxyethylene alkyl ether (C(i)E(j)) surfactants. The model is compatible with the MARTINI coarse-grained force-field for lipids and proteins. We validate the model by comparing molecular dynamics simulations with experimental data. In particular, we show that the model reproduces the phase behavior of water-surfactant mixtures as a function of water concentration. We also simulate the self-assembly of two ternary mixtures that have been used for the experimental measure of protein diffusion coefficients. The first includes a cosurfactant that affects the curvature of the surfactant bilayers; the second is a mixture of C(i)E(j) surfactants, alkanes and water. In both cases, the results of self-assembly simulations are in agreement with experimental observations and pave the way to the use of the surfactant model in combination with MARTINI peptides and proteins.