Two decades of Martini: Better beads, broader scope

Abstract

The Martini model, a coarse-grained force field for molecular dynamics simulations, has been around for nearly two decades. Originally developed for lipidbased systems by the groups of Marrink and Tieleman, the Martini model has over the years been extended as a community effort to the current level of a general-purpose force field. Apart from the obvious benefit of a reduction in computational cost, the popularity of the model is largely due to the systematic yet intuitive building-block approach that underlies the model, as well as the open nature of the development and its continuous validation. The easy implementation in the widely used Gromacs software suite has also been instrumental. Since its conception in 2002, the Martini model underwent a gradual refinement of the bead interactions and a widening scope of applications. In this review, we look back at this development, culminating with the release of the Martini 3 version in 2021. The power of the model is illustrated with key examples of recent important findings in biological and material sciences enabled with Martini, as well as examples from areas where coarse-grained resolution is essential, namely highthroughput applications, systems with large complexity, and simulations approaching the scale of whole cells.

Room for Improvement in the Initial Martini 3 Parameterization of Peptide Interactions

“…Having ruled out limitations specific to the membrane or WALP models, we are left to conclude that the pattern of Martini 3 protein-membrane affinities is offset in a way that favors 1 Observation of WALP19 TM instability was serendipitous in that it was first observed, at a shorter timescale, under wrong (isotropic) pressure coupling conditions. This prompted us to monitor WALP19 stability -with correct pressure coupling -into the 10 2 µs scale, and indeed the same behavior was seen as for WALP16.…”

“…The past decade has seen an explosion in the adoption of coarse-grain (CG) molecular dynamics (MD) [1]. By employing reduced-dimensionality models one can lower the computational costs of MD simulations by several orders of magnitude, and bring into reach timescales of milliseconds and size scales approaching the micrometer [1].…”

“…The past decade has seen an explosion in the adoption of coarse-grain (CG) molecular dynamics (MD) [1]. By employing reduced-dimensionality models one can lower the computational costs of MD simulations by several orders of magnitude, and bring into reach timescales of milliseconds and size scales approaching the micrometer [1]. The Martini force field has been at the forefront of many important CG MD applications [1] and is arguably the most used such model for biomolecular simulations.…”

“…By employing reduced-dimensionality models one can lower the computational costs of MD simulations by several orders of magnitude, and bring into reach timescales of milliseconds and size scales approaching the micrometer [1]. The Martini force field has been at the forefront of many important CG MD applications [1] and is arguably the most used such model for biomolecular simulations. This is not to say CG models like Martini -where simplification is achieved by representing groups of about 4 non-hydrogen atoms as single particles, or "beads" -are without limitations: besides obvious tradeoffs, such as the inability to represent fine chirality or explicit hydrogen-bonding, Martini often suffered from 'overmapping', a condition in which models with mappings finer that 4-to-1 led to imbalanced hydrophobic/hydrophilic interactions [2].…”

Protein Function Analysis through Machine Learning

“…The elastic network model (ENM) [ 104 ] and the DCM [ 37 , 38 ] are two very different examples of a coarse-grained model. A coarse-grained model commonly used today for MD simulation is the Martini force field [ 105 , 106 ], which replaces certain groups of about 4 atoms in amino acids by single elements called beads and applies physics-based effective potentials. Another choice is to use a forcefield based on the potential of mean force (PMF), such as the United Residue (UNRES) [ 107 , 108 ] model.…”