Improved parameters for IDPs

The group of Lindorff-Larsen performed a systematic study on the behavior of intrinsically disordered proteins (IDPs) with Martini 3. Comparing to SAXS data, they show that Martini 3 generally underestimates the global dimensions of the IDPs, which can be fixed by slightly increasing protein-water interactions. Although not an ideal solution, for the time being this seems like a pragmatic approach when modeling IDPs (as well as multi-domain proteins that are connected via flexible linkers) with Martini 3. For details, read the paper ! Thomasen et al, JCTC, 2022.

Sticky Martini

No worries, Martini 3 is not too sticky, but 'Sticky Martini' here refers to a novel way of letting Martini beads stick together on purpose, to mimic chemical reactions. See the work of Carvalho et al., just published in Npj Computational Materials.

Membrane permeability



A nice collaborative effort between our group and the membrane enzymology group of Bert Poolman, unraveling the key factors that govern membrane permeation of weak acids, has now been published in Nature Communications.


polyply-image3.jpgGenerating input files and realistic starting coordinates for complex multi-component simulations is often a major bottleneck, especially for high throughput protocols. To eliminate this bottleneck, we present the polyply software suite that provides 1) a multi-scale graph matching algorithm designed to generate parameters quickly and for arbitrarily complex polymeric topologies, and 2) a generic multi-scale random walk protocol capable of setting up complex systems efficiently and independent of the target force-field or model resolution.

We demonstrate the power of polyply by setting up a number of complex systems, including a liquid-liquid phase separated polymer system inside a lipid vesicle. For details, see Grünewald et al., Nature Commun. 2022.

Massive MuMMI Martinis

A huge consortium effort from the Livermore Lab on RAS dynamics, featuring a staggering 120,000 independent Martini simulations, has now been published: Ingolfsson et al., PNAS, 2022.

Impressive work based on the MuMMI (Multiscale Machine-learned Modeling Infrastructure) workflow.


Small molecules

adts202100391-gra-0001-m.jpgA good start of the new year: Our paper on how to parameterise small molecules with Martini 3 is now published !

You can read about best practices on chosing bead types, handling constraints, and selecting virtual sites for planar compounds, as well as find a large table with best bead types for a wide selection of chemical fragments and numerous validated topologies for small compounds.

Alessandri et al., Adv. Theory & Simul. 2100391.