Activity

Webinar: Perspective on the Martini Force Field

Activity: Talk or presentationProfessional

Siewert Marrink - Speaker

BioExcel Center of Excellence for Computational Biomolecular Research

Molecular dynamics simulations is a widely used computational tool to describe the collective motions of a system of interacting particles. Traditionally, every atom in the system is represented explicitly. Although such an all-atom approach provides high accuracy, it is computationally very expensive and therefore limited to small system sizes (e.g., a single protein) and short time scales (nanoseconds). To alleviate this problem, coarse-grained (CG) models have gained a lot of popularity in the field of molecular simulations lately. By uniting small groups of atoms into effective interaction sites (“beads”), the simulation costs are strongly reduced and the temporal evolution of much larger systems can be followed over much longer time scales.

In our group, we developed the Martini force field, one of the most popular CG models currently available (1). The Martini force field is a generic model that can be used to simulate a wide range of molecules, from lipids, proteins, and nucleotides to synthetic polymers, nanoparticles, and drug like compounds. In this webinar I will explain in detail how the Martini model has been parameterized, and discuss the assumptions and limitations of the model. I will further illustrate the power of the model by providing a few in-depth examples of large-scale simulations. These include applications in the field of biomolecular processes, such as the exchange of electron carriers in photosystems embedded in the thylakoid membrane (2), and the lateral organization of lipids and proteins in complex plasma membrane models (3), as well as applications in the field of polymer chemistry, such as the rational design of bulk heterojunction morphologies for improved photovoltaics (4).

(1) SJ Marrink, DP Tieleman. Chem. Soc. Rev. 42, 6801 (2013); (2) FJ van Eerden et al. Nature Commun. 8, 15214 (2017); (3) HI Ingólfsson et al. JACS 136, 14554 (2014); (4) R Alessandri et al. JACS 139, 3697 (2017)
18-Apr-2018

External organisation

NameBioExcel Center of Excellence for Computational Biomolecular Research

ID: 57159763