Pivotal 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 time required, from the quantum mechanical level through to in vivo studies. At an approximate mid-point there is coarse-grained molecular dynamics, for which the Martini forcefields have become the most widely used, fast enough to simulate the entire membrane of a mitochondrion though lacking atom-specific precision. While many forcefields have been parameterized to account for a specific system under study, the Martini forcefield 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 co-assembly 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 forcefield will be analyzed in terms of self-assembling systems with a focus on short (2-3 amino acids) peptide self-assembly in aqueous environments. Particularly, 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 taken 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 forcefields, 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 forcefields to model the self-assembly of the dipeptides in aqueoues environments is determined by measurement of the aggregation propensity and additional descriptors are used to gain further insight into the dipeptide aggregates.
|Number of pages||11|
|Journal||Accounts of Chemical Research|
|Early online date||3 Mar 2023|
|Publication status||E-pub ahead of print - 3 Mar 2023|
- Martini coarse grain forcefield family