High-throughput simulations of dimer and trimer assembly of membrane proteins. the DAFT approach - Wassenaar, Tsjerk A.; Pluhackova, Kristyna; Moussatova, Anastassiia; Sengupta, Durba; Marrink, Siewert-Jan; Tieleman, D. Peter; Boeckmann, Rainer A. (Journal of Chemical Theory and Computation, 2015)
Interactions between membrane proteins are of great biological significance and are consequently an important target for pharmacological intervention. Unfortunately, it is still difficult to obtain detailed views on such interactions, both experimentally, where the environment hampers atomic resolution investigation, and computationally, where the time and length scales are problematic. Coarse grain simulations have alleviated the later issue, but the slow movement through the bilayer, coupled to the long life times of nonoptimal dimers, still stands in the way of characterizing binding distributions. In this work, we present DAFT, a Docking Assay For Transmembrane components, developed to identify preferred binding orientations. The method builds on a program developed recently for generating custom membranes, called insane (INSert membrANE). The key feature of DAFT is the setup of starting structures, for which optimal periodic boundary conditions are devised. The purpose of DAFT is to perform a large number of simulations with different components, starting from unbiased noninteracting initial states, such that the simulations evolve collectively, in a manner reflecting the underlying energy landscape of interaction. The implementation and characteristic features of DAFT are explained, and the efficacy and relaxation properties of the method are explored for oligomerization of glycophorin A dimers, polyleucine dimers and trimers, MS1 trimers, and rhodopsin dimers. The results suggest that, for simple helices, such as GpA and polyleucine, in POPC/DOPC membranes series of 500 simulations of 500 ns each allow characterization of the helix dimer orientations and allow comparing associating and nonassociating components. However, the results also demonstrate that short simulations may suffer significantly from nonconvergence of the ensemble and that using too few simulations may obscure or distort features of the interaction distribution. For trimers, simulation times exceeding several microseconds appear needed, due to the increased complexity. Similarly, characterization of larger proteins, such as rhodopsin, takes longer time scales due to the slower diffusion and the increased complexity of binding interfaces. DAFT and its auxiliary programs have been made available from http://cgmartini.nl/, together with a working example.

Landscapes of membrane protein interactions from high-throughput MD simulations using the daft approach - Wassenaar, Tsjerk A.; Pluhackova, Kristyna; Moussatova, Anastassiia; Sengupta, Durba; Marrink, Siewert-Jan; Tieleman, D. Peter; Boeckmann, Rainer A. (Biophysical Journal, 2015)
59th Annual Meeting of the Biophysical-Society, Baltimore, MD, FEB 07-11, 2015

Thermodynamic and kinetic characterization of transmembrane helix association - Pawar, Aiswarya B.; Deshpande, Sneha A.; Gopal, Srinivasa M.; Wassenaar, Tsjerk A.; Athale, Chaitanya A.; Sengupta, Durba (Physical Chemistry Chemical Physics, 2015)
The transient dimerization of transmembrane proteins is an important event in several cellular processes and computational methods are being increasingly used to quantify their underlying energetics. Here, we probe the thermodynamics and kinetics of a simple transmembrane dimer to understand membrane protein association. A multi-step framework has been developed in which the dimerization profiles are calculated from coarse-grain molecular dynamics simulations, followed by meso-scale simulations using parameters calculated from the coarse-grain model. The calculated value of Delta G(assoc) is approx. -20 kJ mol(-1) and is consistent between three methods. Interestingly, the meso-scale stochastic model reveals low dimer percentages at physiologically-relevant concentrations, despite a favorable Delta G(assoc). We identify generic driving forces arising from the protein backbone and lipid bilayer and complementary factors, such as protein density, that govern self-interactions in membranes. Our results provide an important contribution in understanding membrane protein organization and linking molecular, nano-scale computational studies to meso-scale experimental data.

Lipid-dependent conformational landscape of the ErbB2 growth factor receptor dimers - Gopal, Srinivasa M.; Pawar, Aiswarya B.; Wassenaar, Tsjerk A.; Sengupta, Durba (Chemistry and Physics of Lipids, 2020)
Altered lipid metabolism has been linked to cancer development and progression. Several roles have been attributed to the increased saturation and length of lipid acyl tails observed in tumors, but its effect on signaling receptors is still emerging. In this work, we have analyzed the lipid dependence of the ErbB2 growth factor receptor dimerization that plays an important role in the pathogenesis of breast cancer. We have performed coarse-grain ensemble molecular dynamics simulations to comprehensively sample the ErbB2 monomer-dimer association. Our results indicate a dynamic dimer state with a complex conformational landscape that is modulated with increasing lipid tail length. We resolve the native N-terminal ``active'' and C-terminal ``inactive'' conformations in all membrane compositions. However, the relative population of the N-terminal and C-terminal conformers is dependent on length of the saturated lipid tails. In short-tail membranes, additional non-specific dimers are observed which are reduced or absent in long-tailed bilayers. Our results indicate that the relative population as well as the structure of the dimer state is modulated by membrane composition. We have correlated these differences to local perturbations of the membrane around the receptor. Our work is an important step in characterizing ErbB dimers in healthy and diseased states and emphasize the importance of sampling lipid dynamics in understanding receptor association.
Keywords: ErbB2 dimer; Lipid effects; Martini coarse-grained simulations; Membrane protein structure; Transmembrane association