Estimating The Accuracy Of The Martini Model Towards The Investigation Of Peripheral Protein-Membrane Interactions

Peripheral membrane proteins play a major role in numerous biological processes by transiently associating with cellular membranes, often with extreme membrane specificity. Because of the short-lived nature of these interactions, molecular dynamics (MD) simulations have emerged as an appealing tool to characterize at the structural level the molecular details of the protein-membrane interface. Transferable coarse-grained (CG) MD simulations, in particular, offer the possibility to investigate the spontaneous association of peripheral proteins with lipid bilayers of different compositions at limited computational cost, but they are hampered by the lack of a reliable estimation of their accuracy and thus typically require experimental validation. In this article, we investigate the ability of the MARTINI CG force field, specifically the 3 open-beta version, to reproduce known experimental observations regarding the membrane binding behavior of 12 peripheral membrane proteins and peptides. Based on observations of multiple binding and unbinding events in several independent replicas, we found that, despite the presence of false positives and false negatives, this model is mostly able to correctly characterize the membrane binding behavior of peripheral proteins, and to identify key residues found to disrupt membrane binding in mutagenesis experiments. While preliminary, our investigations suggest that transferable chemical-specific CG force fields have enormous potential in the characterization of the membrane binding process by peripheral proteins, and that the identification of negative results could help drive future force field development efforts.