Coarse-grained simulation of transmembrane peptides in the gel phase

We use Dissipative Particle Dynamics simulations, combined with parallel tempering and umbrella sampling, to investigate the potential of mean force between model transmembrane peptides in the various phases of a lipid bilayer, including the low-temperature gel phase. The observed oscillations in the effective interaction between peptides are consistent with the different structures of the surrounding lipid phases

Toy amphiphiles on the computer: What can we learn from generic models?

Generic coarse-grained models are designed such that they are (i) simple and (ii) computationally efficient. They do not aim at representing particular materials, but classes of materials, hence they can offer insight into universal properties of these classes. Here we review generic models for amphiphilic molecules and discuss applications in studies of self-assembling nanostructures and the local structure of bilayer membranes, i.e. their phases and their interactions with nanosized inclusions. Special attention is given to the comparison of simulations with elastic continuum models, which are, in some sense, generic models on a higher coarse-graining level. In many cases, it is possible to bridge quantitatively between generic particle models and continuum models, hence multiscale modeling works on principle. On the other side, generic simulations can help to interpret experiments by providing information that is not accessible otherwise.Comment: Invited feature article, to appear in Macromolecular Rapid Communication

Room for improvement in the initial martini 3 parameterization of peptide interactions

Funding Information: We thank T. Cordeiro for bringing to our attention the coiled coil system that motivated part of this study. J.K.S. acknowledges an internship sponsored by Fundação Luso-Americana para o Desenvolvimento through its Study in Portugal Network. M.N.M. thanks Fundação para a Ciência e a Tecnologia, Portugal for fellowship CEECIND/04124/2017 , and for funding project MOSTMICRO-ITQB with references UIDB/04612/2020 and UIDP/04612/2020 . Publisher Copyright: © 2023 The AuthorsThe Martini 3 coarse-grain force field has greatly improved upon its predecessor, having already been successfully employed in several applications. Here, we gauge the accuracy of Martini 2 and 3 protein interactions in two types of systems: coiled coil peptide dimers in water and transmembrane peptides. Coiled coil dimers form incorrectly under Martini 2 and not at all under Martini 3. With transmembrane peptides, Martini 3 represents better the membrane thickness–peptide tilt relationship, but shorter peptides do not remain transmembranar. We discuss related observations, and describe mitigation strategies involving either scaling interactions or restraining the system.publishersversionpublishe

Excessive aggregation of membrane proteins in the Martini model

The coarse-grained Martini model is employed extensively to study membrane protein oligomerization. While this approach is exceptionally promising given its computational efficiency, it is alarming that a significant fraction of these studies demonstrate unrealistic protein clusters, whose formation is essentially an irreversible process. This suggests that the protein-protein interactions are exaggerated in the Martini model. If this held true, then it would limit the applicability of Martini to study multi-protein complexes, as the rapidly clustering proteins would not be able to properly sample the correct dimerization conformations. In this work we first demonstrate the excessive protein aggregation by comparing the dimerization free energies of helical transmembrane peptides obtained with the Martini model to those determined from FRET experiments. Second, we show that the predictions provided by the Martini model for the structures of transmembrane domain dimers are in poor agreement with the corresponding structures resolved using NMR. Next, we demonstrate that the first issue can be overcome by slightly scaling down the Martini protein-protein interactions in a manner, which does not interfere with the other Martini interaction parameters. By preventing excessive, irreversible, and non-selective aggregation of membrane proteins, this approach renders the consideration of lateral dynamics and protein-lipid interactions in crowded membranes by the Martini model more realistic. However, this adjusted model does not lead to an improvement in the predicted dimer structures. This implicates that the poor agreement between the Martini model and NMR structures cannot be cured by simply uniformly reducing the interactions between all protein beads. Instead, a careful amino-acid specific adjustment of the protein-protein interactions is likely required.Peer reviewe

Membrane models for molecular simulations of peripheral membrane proteins

Peripheral membrane proteins (PMPs) bind temporarily to the surface of biological membranes. They also exist in a soluble form and their tertiary structure is often known. Yet, their membrane-bound form and their interfacial-binding site with membrane lipids remain difficult to observe directly. Their binding and unbinding mechanism, the conformational changes of the PMPs and their influence on the membrane structure are notoriously challenging to study experimentally. Molecular dynamics simulations are particularly useful to fill some knowledge-gaps and provide hypothesis that can be experimentally challenged to further our understanding of PMP-membrane recognition. Because of the time-scales of PMP-membrane binding events and the computational costs associated with molecular dynamics simulations, membrane models at different levels of resolution are used and often combined in multiscale simulation strategies. We here review membrane models belonging to three classes: atomistic, coarse-grained and implicit. Differences between models are rooted in the underlying theories and the reference data they are parameterized against. The choice of membrane model should therefore not only be guided by its computational efficiency. The range of applications of each model is discussed and illustrated using examples from the literature.publishedVersio