After two decades of continued development of the Martini coarse-grained force field (CG FF), further refinment of the already rather accurate Martini lipid models has become a demanding task that could benefit from integrative data-driven methods. Automatic approaches are increasingly used in the development of accurate molecular models, but they typically make use of specifically designed interaction potentials that transfer poorly to molecular systems or conditions different than those used for model calibration. As a proof of concept, here, we employ SwarmCG, an automatic multiobjective optimization approach facilitating the development of lipid force fields, to refine specifically the bonded interaction parameters in building blocks of lipid models within the framework of the general Martini CG FF. As targets of the optimization procedure, we employ both experimental observables (top-down references: area per lipid and bilayer thickness) and all-atom molecular dynamics simulations (bottom-up reference), which respectively inform on the supra-molecular structure of the lipid bilayer systems and on their submolecular dynamics. In our training sets, we simulate at different temperatures in the liquid and gel phases up to 11 homogeneous lamellar bilayers composed of phosphatidylcholine lipids spanning various tail lengths and degrees of (un)saturation. We explore different CG representations of the molecules and evaluate improvements a posteriori using additional simulation temperatures and a portion of the phase diagram of a DOPC/DPPC mixture. Successfully optimizing up to ∼80 model parameters within still limited computational budgets, we show that this protocol allows the obtainment of improved transferable Martini lipid models. In particular, the results of this study demonstrate how a fine-tuning of the representation and parameters of the models may improve their accuracy and how automatic approaches, such as SwarmCG, may be very useful to this end.

In this study, we use surface-sensitive vibrational sum-frequency generation (VSFG) spectroscopy to investigate the interaction between model lipid monolayers and Aβ(1–42) in its monomeric and aggregated states. Combining VSFG with atomic force microscopy (AFM) and thioflavin T (ThT) fluorescence measurements, we found that only small aggregates with probably a β-hairpin-like structure adsorbed to the zwitterionic lipid monolayer (DOPC). In contrast, larger aggregates with an extended β-sheet structure adsorbed to a negatively charged lipid monolayer (DOPG). The adsorption of small, initially formed aggregates strongly destabilized both monolayers, but only the DOPC monolayer was completely disrupted. We showed that the intensity of the amide-II′ band in achiral (SSP) and chiral (SPP) polarization combinations increased in time when Aβ(1–42) aggregates accumulated at the DOPG monolayer. Nevertheless, almost no adsorption of preformed mature fibrils to DOPG monolayers was detected. By performing spectral VSFG calculations, we revealed a clear correlation between the amide-II′ signal and the degree of amyloid aggregates (e.g., oligomers or (proto)­fibrils) of various Aβ(1–42) structures. The calculations showed that only structures with a significant amyloid β-sheet content have a strong amide-II′ intensity, in line with previous Raman studies. The combination of the presented results substantiates the amide-II(′) band as a legitimate amyloid marker.

The human dopamine transporter (hDAT) is one in three members of the monoamine transporter family (MAT). hDAT is essential for regulating the dopamine concentration in the synaptic cleft through dopamine reuptake into the presynaptic neuron; thereby controlling hDAT dopamine signaling. Dysfunction of the transporter is linked to several psychiatric disorders. hDAT and the other MATs have been shown to form oligomers in the plasma membrane, but only limited data exists on which dimeric and higher order oligomeric states are accessible and energetically favorable. In this work, we present several probable dimer conformations using computational coarse-grained self-assembly simulations and assess the relative stability of the different dimer conformations using umbrella sampling replica exchange molecular dynamics. Overall, the dimer conformations primarily involve TM9 and/or TM11 and/or TM12 at the interface. Furthermore, we show that a palmitoyl group (palm) attached to hDAT on TM12 modifies the free energy of separation for interfaces involving TM12, suggesting that S-palmitoylation may change the relative abundance of dimers involving TM12 in a biological context. Finally, a comparison of the identified interfaces of hDAT and palmitoylated hDAT to the human serotonin transporter interfaces and the leucine transporter interface, suggests similar dimer conformations across these protein family.

Independent force field validation is an essential practice to keep track of developments and for performing meaningful Molecular Dynamics simulations. In this work, atomistic force fields for intrinsically disordered proteins (IDP) are tested by simulating the archetypical IDP α-synuclein in solution for 2.5 μs. Four combinations of protein and water force fields were tested: ff19SB/OPC, ff19SB/TIP4P-D, ff03CMAP/ TIP4P-D, and a99SB-disp/TIP4P-disp, with four independent repeat simulations for each combination. We compare our simulations to the results of a 73 μs simulation using the a99SB-disp/TIP4P-disp combination, provided by D. E. Shaw Research.From the trajectories, we predict a range of experimental observations of α-synuclein and compare them to literature data. This includes protein radius of gyration and hydration, intramolecular distances, NMR chemical shifts, and 3 J-couplings. Both ff19SB/TIP4P-D and a99SB-disp/TIP4P-disp produce extended conformational ensembles of α-synuclein that agree well with experimental radius of gyration and intramolecular distances while a99SB-disp/TIP4P-disp reproduces a balanced α-synuclein secondary structure content. It was found that ff19SB/OPC and ff03CMAP/TIP4P-D produce overly compact conformational ensembles and show discrepancies in the secondary structure content compared to the experimental data.

After two decades of continued development of the Martini coarse-grained force field (CG FF), further refining the already rather accurate Martini lipid models has become a demanding task that could benefit from integrative data-driven methods. Automatic approaches are increasingly used in the development of accurate molecular models, but they typically make use of specifically-designed interaction potentials that transfer poorly to molecular systems or conditions different than those used for model calibration. As a proof of concept here we employ SwarmCG, an automatic multi-objective optimization approach facilitating the development of lipid force fields, to refine specifically the bonded interaction parameters in building blocks of lipid models within the framework of the general Martini CG FF. As targets of the optimization procedure, we employ both experimental observables (top-down references: area per lipid & bilayer thickness) and all-atom molecular dynamics simulations (bottom-up reference), respectively informing on the supra-molecular structure of the lipid bilayer systems and on their sub-molecular dynamics. In our training sets we simulate at different temperatures in the liquid and gel phases up to 11 homogeneous lamellar bilayers, composed of phosphatidylcholine lipids spanning various tail lengths and degrees of (un)saturation. We explore different CG representations of the molecules and evaluate improvements a posteriori using additional simulation temperatures and a portion of the phase diagram of a DOPC/DPPC mixture. Successfully optimizing up to ~80 model parameters within still limited computational budgets, we show that this protocol allows to obtain improved transferable Martini lipid models. In particular, the results of this study demonstrate how a fine tuning of the representation and parameters of the models may improve their accuracy, and how automatic approaches such as SwarmCG may be very useful to this end.

The aberrant folding of proteins into amyloid aggregates is associated with over 50 diseases. The amyloid aggregation of α-synuclein (αS), related to Parkinson’s disease, can be catalyzed by lipid-membrane surfaces. Despite the importance of lipid surfaces and several decades of structural studies, the 3D-structure of lipid-membrane bound αS is still not known in detail. In particular, there is little information about the self-assembly and orientation of αS when interacting with lipid surfaces under physiologically relevant conditions. Here, we report interface-specific vibrational sum-frequency generation (VSFG) experiments revealing how monomeric αS binds, folds and orients at anionic lipid membranes. Since VSFG is inherently surface specific, the experiments can be performed at high αS–lipid ratios, far beyond previous structural studies. To interpret the experimental VSFG data, we present an analysis method in which out-of-equilibrium molecular-dynamics simulations are used to generate a large amount of conformations, after which their spectral match is evaluated with excitonic amide-I calculations. Hereby, the previously-determined flat-lying helical structures are corroboratively derived at low αS concentrations, while at higher, physiological concentrations, a transition to interface-protruding αS structures occurs. Such an upright conformation promotes more extensive lateral interactions between monomers and may explain how, at high protein–lipid ratios, lipid membranes can catalyze the formation of αS amyloids.

After two decades of continued development of the Martini coarse-grain force field, further refining Martini lipid models has become a demanding task that could benefit from integrative data-driven methods. Here we employ SwarmCG, an automatic multi-objective optimization approach facilitating the development of lipid force fields, to calibrate exclusively the bonded parameters of lipid models in the context of the finely tuned non-bonded interaction matrix available in Martini 3.0.0. We explore two different CG representations of the molecules and evaluate their ability to further enhance the thermodynamic properties of lipid models in Martini simulations. As training set, we simulate at different temperatures in the liquid and gel phases up to 11 homogeneous lamellar bilayers, composed of phosphatidylcholine lipids spanning various tail lengths and degrees of unsaturation. We evaluate improvements a posteriori using additional simulation temperatures and a portion of the phase diagram of a DOPC/DPPC mixture, thereby gaining insights on the ability of putative refined CG representations to further enhance lipid models in Martini.

No abstract