Doping with Martini

A nice example of how Martini can help you improving your performance, featuring the first Martini 3.0 dope:

Liu, Qiu, Alessandri, et al., Enhancing Molecular n-Type Doping of Donor–Acceptor Copolymers by Tailoring Side Chains. Advanced Materials, 2018, online.

Lipidated aminoacids

Adding a lipid to your protein will be a piece of cake from now on.

Yoav Atsmon-Raz, and D. Peter Tieleman. Parameterization of Palmitoylated Cysteine, Farnesylated Cysteine, Geranylgeranylated Cysteine and Myristoylated Glycine for the Martini Force Field  J. Phys. Chem. B,16 Nov 2017. article

The adapted they used for adding the tails.

Brain plasma membrane

brain plasmamembrane

Lipid organization and dynamics of biologically complex plasma membranes; comparison of on idealized brain to an average membrane mixture.

H.I. Ingólfsson, T.S. Carpenter, H. Bhatia, P.T. Bremer, S.J. Marrink, F.C. Lightstone. Computational Lipidomics of the Neuronal Plasma Membrane. Biophys. J. 113:2271–2280, 2017. open access

For simulation files and parameters, see

Sticky proteins

Current force fields tend to overstabilize protein-protein interactions, and Martini is no exception. A recent paper by the Vattulainen group shows the stickiness is also haunting membrane embedded proteins:

M. Javanainen, H. Martinez-Seara, I. Vattulainen. PLoS ONE 12:e0187936, 2017.

We are working hard to improve the protein-protein interactions in the forthcoming Martini 3.0 force field, featuring a thoroughly recalibrated interaction matrix, with a planned release early 2018.

Membrane fusion

fusion nature

Our former PhD student Jelger Risselada has performed large scale Martini simulations of SNARE-mediated membrane fusion and teamed up with experimentalists to explain how tethering proteins facilitate opening of the fusion pore. The exciting results are published in Nature:

M. D’Agostino, H.J. Risselada, A. Lürick, C. Ungermann, A. Mayer. A tethering complex drives the terminal stage of SNARE-dependent membrane fusion. Nature, doi:10.1038/nature24469

High-throughput drug screening

The group of Tristan Bereau uses truly high-throughput Martini simulations to screen thermodynamic properties of drug-membrane interactions. They establish linear relationships between partitioning coefficients and key features of the potential of mean force, allowing them to predict the structure of the insertion from bulk experimental measurements for more than 400 000 (!!) compounds. Details can be found here:

And ... Tristan is looking for new PhD students and postdocs to work on this topic, so send him an email if you are interested (This email address is being protected from spambots. You need JavaScript enabled to view it.)