Teemu Murtola

Coarse-Grained Model for Phospholipid / Cholesterol Bilayer

We construct a coarse-grained (CG) model for dipalmitoylphosphatidylcholine (DPPC)/cholesterol bilayers and apply it to large-scale simulation studies of lipid membranes. Our CG model is a two-dimensional representation of the membrane, where the individual lipid and sterol molecules are described by pointlike particles. The effective intermolecular interactions used in the model are systematically derived from detailed atomic-scale molecular dynamics simulations using the Inverse Monte Carlo technique, which guarantees that the radial distribution properties of the CG model are consistent with those given by the corresponding atomistic system. We find that the coarse-grained model for the DPPC/cholesterol bilayer is substantially more efficient than atomistic models, providing a speedup of approximately eight orders of magnitude. The results are in favor of formation of cholesterol-rich and cholesterol-poor domains at intermediate cholesterol concentrations, in agreement with the experimental phase diagram of the system. We also explore the limits of the coarse-grained model, and discuss the general validity and applicability of the present approach.

Coarse-grained model for phospholipid/cholesterol bilayer employing inverse Monte Carlo with thermodynamic constraints

The authors introduce a coarse-grained (CG) model for a lipid membrane comprised of phospholipids and cholesterol at different molar concentrations, which allows them to study systems that are approximately 100 nm in linear size. The systems are studied in the fluid phase above the main transition temperature. The effective interactions for the CG model are extracted from atomic-scale molecular dynamics simulations using the inverse Monte Carlo (IMC) technique, an approach similar to the one the authors used earlier to construct another CG bilayer model [T. Murtola et al., J. Chem. Phys. 121, 9156 (2004)]. Here, the authors improve their original CG model by employing a more accurate description of the molecular structure for the phospholipid molecules. Further, they include a thermodynamic constraint in the IMC procedure to yield area compressibilities in line with experimental data. The more realistic description of the molecular structure of phospholipids and a more accurate representation of the interaction between cholesterols and phospholipid tails are shown to improve the behavior of the model significantly. In particular, the new model predicts the formation of denser transient regions in a pure phospholipid system, a finding that the authors have verified through large scale atomistic simulations. They also find that the model predicts the formation of cholesterol-rich and cholesterol-poor domains at intermediate cholesterol concentrations, in agreement with the original model and the experimental phase diagram. However, the domains observed here are much more distinct compared to the previous model. Finally, the authors also explore the limitations of the model, discussing its advantages and disadvantages.

Systematic coarse-graining from structure using internal states: Application to phospholipid / cholesterol bilayer

We present a two-dimensional coarse-grained (CG) model for a lipid membrane composed of phospholipids and cholesterol. The effective CG interactions are determined using radial distribution functions (RDFs) from atom-scale molecular dynamics simulations using the inverse Monte Carlo (IMC) technique, based on our earlier work [T. Murtola et al., J. Chem. Phys. 121, 9156 (2004); J. Chem. Phys. 126, 075101 (2007)]. Here, the original model is improved by including an internal discrete degree of freedom for the phospholipid tails to describe chain ordering. We also discuss the problem of RDF inversion in the presence of internal states, in general, and present a modified IMC method for their inclusion. The new model agrees with the original models on large-scale structural features such as density fluctuations in pure dipalmitoylphosphocholine and cholesterol domain formation at intermediate concentrations and also indicates that ordered and disordered domains form at all cholesterol concentrations, even if the global density remains uniform. The inclusion of ordering also improves transferability of the interactions between different concentrations, but does not eliminate transferability problems completely. We also present a general discussion of problems related to RDF inversion.

Lennard-Jones Lattice Summation in Bilayer Simulations Has Critical Effects on Surface Tension and Lipid Properties

The accuracy of electrostatic interactions in molecular dynamics advanced tremendously with the introduction of particle-mesh Ewald (PME) summation almost 20 years ago. Lattice summation electrostatics is now the de facto standard for most types of biomolecular simulations, and in particular, for lipid bilayers, it has been a critical improvement due to the large charges typically present in zwitterionic lipid headgroups. In contrast, Lennard-Jones interactions have continued to be handled with increasingly longer cutoffs, partly because few alternatives have been available despite significant difficulties in tuning cutoffs and parameters to reproduce lipid properties. Here, we present a new Lennard-Jones PME implementation applied to lipid bilayers. We confirm that long-range contributions are well approximated by dispersion corrections in simple systems such as pentadecane (which makes parameters transferable), but for inhomogeneous and anisotropic systems such as lipid bilayers there are large effects on surface tension, resulting in up to 5.5% deviations in area per lipid and order parameters-far larger than many differences for which reparameterization has been attempted. We further propose an approximation for combination rules in reciprocal space that significantly reduces the computational cost of Lennard-Jones PME and makes accurate treatment of all nonbonded interactions competitive with simulations employing long cutoffs. These results could potentially have broad impact on important applications such as membrane proteins and free energy calculations.

Direct-Space Corrections Enable Fast and Accurate Lorentz-Berthelot Combination Rule Lennard-Jones Lattice Summation

Long-range lattice summation techniques such as the particle-mesh Ewald (PME) algorithm for electrostatics have been revolutionary to the precision and accuracy of molecular simulations in general. Despite the performance penalty associated with lattice summation electrostatics, few biomolecular simulations today are performed without it. There are increasingly strong arguments for moving in the same direction for Lennard-Jones (LJ) interactions, and by using geometric approximations of the combination rules in reciprocal space, we have been able to make a very high-performance implementation available in GROMACS. Here, we present a new way to correct for these approximations to achieve exact treatment of Lorentz-Berthelot combination rules within the cutoff, and only a very small approximation error remains outside the cutoff (a part that would be completely ignored without LJ-PME). This not only improves accuracy by almost an order of magnitude but also achieves absolute biomolecular simulation performance that is an order of magnitude faster than any other available lattice summation technique for LJ interactions. The implementation includes both CPU and GPU acceleration, and its combination with improved scaling LJ-PME simulations now provides performance close to the truncated potential methods in GROMACS but with much higher accuracy.

Conformational analysis of lipid molecules by self-organizing maps

The authors have studied the use of the self-organizing map (SOM) in the analysis of lipid conformations produced by atomic-scale molecular dynamics simulations. First, focusing on the methodological aspects, they have systematically studied how the SOM can be employed in the analysis of lipid conformations in a controlled and reliable fashion. For this purpose, they have used a previously reported 50 ns atomistic molecular dynamics simulation of a 1-palmitoyl-2-linoeayl-sn-glycero-3-phosphatidylcholine (PLPC) lipid bilayer and analyzed separately the conformations of the headgroup and the glycerol regions, as well as the diunsaturated fatty acid chain. They have elucidated the effect of training parameters on the quality of the results, as well as the effect of the size of the SOM. It turns out that the main conformational states of each region in the molecule are easily distinguished together with a variety of other typical structural features. As a second topic, the authors applied the SOM to the PLPC data to demonstrate how it can be used in the analysis that goes beyond the standard methods commonly used to study the structure and dynamics of lipid membranes. Overall, the results suggest that the SOM method provides a relatively simple and robust tool for quickly gaining a qualitative understanding of the most important features of the conformations of the system, without a priori knowledge. It seems plausible that the insight given by the SOM could be applied to a variety of biomolecular systems and the design of coarse-grained models for these systems.

Insights into activation and RNA binding of trp RNA-binding attenuation protein (TRAP) through all-atom simulations.

Tryptophan biosynthesis in Bacillus stearothermophilus is regulated by a trp RNA binding attenuation protein (TRAP). It is a ring‐shaped 11‐mer of identical 74 residue subunits. Tryptophan binding pockets are located between adjacent subunits, and tryptophan binding activates TRAP to bind RNA. Here, we report results from all‐atom molecular dynamics simulations of the system, complementing existing extensive experimental studies. We focus on two questions. First, we look at the activation mechanism, of which relatively little is known experimentally. We find that the absence of tryptophan allows larger motions close to the tryptophan binding site, and we see indication of a conformational change in the BC loop. However, complete deactivation seems to occur on much longer time scales than the 40 ns studied here. Second, we study the TRAP–RNA interactions. We look at the relative flexibilities of the different bases in the complex and analyze the hydrogen bonds between the protein and RNA. We also study the role of Lys37, Lys56, and Arg58, which have been experimentally identified as essential for RNA binding. Hydrophobic stacking of Lys37 with the nearby RNA base is confirmed, but we do not see direct hydrogen bonding between RNA and the other two residues, in contrast to the crystal structure. Rather, these residues seem to stabilize the RNA‐binding surface, and their positive charge may also play a role in RNA binding. Simulations also indicate that TRAP is able to attract RNA nonspecifically, and the interactions are quantified in more detail using binding energy calculations. The formation of the final binding complex is a very slow process: within the simulation time scale of 40 ns, only two guanine bases become bound (and no others), indicating that the binding initiates at these positions. In general, our results are in good agreement with experimental studies, and provide atomic‐scale insights into the processes. Proteins 2008.