Teemu Murtola

Bio: Teemu Murtola is an academic researcher from Stockholm University. The author has contributed to research in topics: Ewald summation & Low-density lipoprotein. The author has an hindex of 5, co-authored 5 publications receiving 8415 citations. Previous affiliations of Teemu Murtola include Aalto University & Royal Institute of Technology.

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

Abstract: 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.

Abstract: 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.

Low density lipoprotein: structure, dynamics, and interactions of apoB-100 with lipids

Abstract: Low-density lipoprotein (LDL) transports cholesterol in the bloodstream and plays an important role in the development of cardiovascular diseases, in particular atherosclerosis. Despite its importance to health, the structure of LDL is not known in detail. This is worrying since the lack of LDL's structural information makes it more difficult to understand its function. In this work, we have combined experimental and theoretical data to construct LDL models comprised of the apoB-100 protein wrapped around a lipid droplet of about 20 nm in size. The models are considered by near-atomistic multi-microsecond simulations to unravel structural as well as dynamical properties of LDL, with particular attention paid to lipids and their interactions with the protein. We find that the distribution and the ordering of the lipids in the LDL particle are rather complex. The previously proposed 2- and 3-layer models turn out to be inadequate to describe the properties of the lipid droplet. At the surface of LDL, apoB-100 is found to interact favorably with cholesterol and its esters. The interactions of apoB-100 with core molecules, in particular cholesteryl esters, are rather frequent and arise from hydrophobic amino acids interacting with the ring of cholesteryl esters, and also in part from the rather loose packing of lipids at the surface of the lipoparticle. The loose packing may foster the function of transfer proteins, which transport lipids between lipoproteins. Finally, the comparison of the several apoB-100 models in our study suggests that the properties of lipids in LDL are rather insensitive to the conformation of apoB-100. Altogether, the findings pave the way for further studies of LDL to better understand the central steps in the emergence of atherosclerosis.

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

CHARMM-GUI Input Generator for NAMD, Gromacs, Amber, Openmm, and CHARMM/OpenMM Simulations using the CHARMM36 Additive Force Field

Abstract: Proper treatment of nonbonded interactions is essential for the accuracy of molecular dynamics (MD) simulations, especially in studies of lipid bilayers. The use of the CHARMM36 force field (C36 FF) in different MD simulation programs can result in disagreements with published simulations performed with CHARMM due to differences in the protocols used to treat the long-range and 1-4 nonbonded interactions. In this study, we systematically test the use of the C36 lipid FF in NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM. A wide range of Lennard-Jones (LJ) cutoff schemes and integrator algorithms were tested to find the optimal simulation protocol to best match bilayer properties of six lipids with varying acyl chain saturation and head groups. MD simulations of a 1,2-dipalmitoyl-sn-phosphatidylcholine (DPPC) bilayer were used to obtain the optimal protocol for each program. MD simulations with all programs were found to reasonably match the DPPC bilayer properties (surface area per lipid, chain order para...