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Alan E. Mark

Bio: Alan E. Mark is an academic researcher from University of Queensland. The author has contributed to research in topics: Molecular dynamics & Lipid bilayer. The author has an hindex of 75, co-authored 238 publications receiving 39609 citations. Previous affiliations of Alan E. Mark include National Autonomous University of Mexico & ETH Zurich.


Papers
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Journal ArticleDOI
TL;DR: The software suite GROMACS (Groningen MAchine for Chemical Simulation) that was developed at the University of Groningen, The Netherlands, in the early 1990s is described, which is a very fast program for molecular dynamics simulation.
Abstract: This article describes the software suite GROMACS (Groningen MAchine for Chemical Simulation) that was developed at the University of Groningen, The Netherlands, in the early 1990s. The software, written in ANSI C, originates from a parallel hardware project, and is well suited for parallelization on processor clusters. By careful optimization of neighbor searching and of inner loop performance, GROMACS is a very fast program for molecular dynamics simulation. It does not have a force field of its own, but is compatible with GROMOS, OPLS, AMBER, and ENCAD force fields. In addition, it can handle polarizable shell models and flexible constraints. The program is versatile, as force routines can be added by the user, tabulated functions can be specified, and analyses can be easily customized. Nonequilibrium dynamics and free energy determinations are incorporated. Interfaces with popular quantum-chemical packages (MOPAC, GAMES-UK, GAUSSIAN) are provided to perform mixed MM/QM simulations. The package includes about 100 utility and analysis programs. GROMACS is in the public domain and distributed (with source code and documentation) under the GNU General Public License. It is maintained by a group of developers from the Universities of Groningen, Uppsala, and Stockholm, and the Max Planck Institute for Polymer Research in Mainz. Its Web site is http://www.gromacs.org.

13,116 citations

Journal ArticleDOI
TL;DR: The newest parameter sets, 53A5 and 53A6, were optimized by first fitting to reproduce the thermodynamic properties of pure liquids of a range of small polar molecules and the solvation free enthalpies of amino acid analogs in cyclohexane.
Abstract: Successive parameterizations of the GROMOS force field have been used successfully to simulate biomolecular systems over a long period of time. The continuing expansion of computational power with time makes it possible to compute ever more properties for an increasing variety of molecular systems with greater precision. This has led to recurrent parameterizations of the GROMOS force field all aimed at achieving better agreement with experimental data. Here we report the results of the latest, extensive reparameterization of the GROMOS force field. In contrast to the parameterization of other biomolecular force fields, this parameterization of the GROMOS force field is based primarily on reproducing the free enthalpies of hydration and apolar solvation for a range of compounds. This approach was chosen because the relative free enthalpy of solvation between polar and apolar environments is a key property in many biomolecular processes of interest, such as protein folding, biomolecular association, membrane formation, and transport over membranes. The newest parameter sets, 53A5 and 53A6, were optimized by first fitting to reproduce the thermodynamic properties of pure liquids of a range of small polar molecules and the solvation free enthalpies of amino acid analogs in cyclohexane (53A5). The partial charges were then adjusted to reproduce the hydration free enthalpies in water (53A6). Both parameter sets are fully documented, and the differences between these and previous parameter sets are discussed.

3,383 citations

Journal ArticleDOI
TL;DR: In this article, a coarse-grained (CG) model for lipid and surfactant systems is presented, where only a small number of coarse grained atom types interact using a few discrete levels of interaction.
Abstract: This paper describes the parametrization of a new coarse grained (CG) model for lipid and surfactant systems. Reduction of the number of degrees of freedom together with the use of short range potentials makes it computationally very efficient. Compared to atomistic models a gain of 3-4 orders of magnitude can be achieved. Micrometer length scales or millisecond time scales are therefore within reach. To encourage applications, the model is kept very simple. Only a small number of coarse grained atom types are defined, which interact using a few discrete levels of interaction. Despite the computational speed and the simplistic nature of the model, it proves to be both versatile in its applications and accurate in its predictions. We show that densities of liquid alkanes from decane up to eicosane can be reproduced to within 5%, and the mutual solubilities of alkanes in water and water in alkanes can be reproduced within 0.5 kT of the experimental values. The CG model for dipalmitoylphosphatidylcholine (DPPC) is shown to aggregate spontaneously into a bilayer. Structural properties such as the area per headgroup and the phosphate-phosphate distance match the experimentally measured quantities closely. The same is true for elastic properties such as the bending modulus and the area compressibility, and dynamic properties such as the lipid lateral diffusion coefficient and the water permeation rate. The distribution of the individual lipid components along the bilayer normal is very similar to distributions obtained from atomistic simulations. Phospholipids with different headgroup (ethanolamine) or different tail lengths (lauroyl, stearoyl) or unsaturated tails (oleoyl) can also be modeled with the CG force field. The experimental area per headgroup can be reproduced for most lipids within 0.02 nm(2). Finally, the CG model is applied to nonbilayer phases. Dodecylphosphocholine (DPC) aggregates into small micelles that are structurally very similar to ones modeled atomistically, and DOPE forms an inverted hexagonal phase with structural parameters in agreement with experimental data.

2,062 citations

Journal ArticleDOI
TL;DR: The helical propensity modification is tested using the benchmark proteins hen egg-white lysozyme, fox1 RNA binding domain, chorismate mutase and the GCN4-p1 peptide and good agreement with a range of primary experimental data is obtained.
Abstract: New parameter sets of the GROMOS biomolecular force field, 54A7 and 54B7, are introduced. These parameter sets summarise some previously published force field modifications: The 53A6 helical propensities are corrected through new φ/ψ torsional angle terms and a modification of the N-H, C=O repulsion, a new atom type for a charged -CH(3) in the choline moiety is added, the Na(+) and Cl(-) ions are modified to reproduce the free energy of hydration, and additional improper torsional angle types for free energy calculations involving a chirality change are introduced. The new helical propensity modification is tested using the benchmark proteins hen egg-white lysozyme, fox1 RNA binding domain, chorismate mutase and the GCN4-p1 peptide. The stability of the proteins is improved in comparison with the 53A6 force field, and good agreement with a range of primary experimental data is obtained.

1,782 citations

Journal ArticleDOI
TL;DR: Despite the small differences in sequence between the two peptides studied, the simulations correctly predict a left-handed 31-helical fold for the beta-heptapeptide and a right-handed helical Fold for thebeta-hexapeptides.
Abstract: Accurate reproduction of the mechanism of peptide folding in solution and conformational preferences as a function of amino acid sequence is possible with atomic level dynamics simulations. For example, the simulations correctly predict a left-handed 31-helical fold for the β-heptapeptide 1 (the molecular model is shown in the picture) and a right-handed helical fold for the β-hexapeptide 2, as was confirmed by NMR spectroscopy.

1,689 citations


Cited by
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01 May 1993
TL;DR: 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.
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.

29,323 citations

28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Journal ArticleDOI
TL;DR: NAMD as discussed by the authors is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems that scales to hundreds of processors on high-end parallel platforms, as well as tens of processors in low-cost commodity clusters, and also runs on individual desktop and laptop computers.
Abstract: NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD scales to hundreds of processors on high-end parallel platforms, as well as tens of processors on low-cost commodity clusters, and also runs on individual desktop and laptop computers. NAMD works with AMBER and CHARMM potential functions, parameters, and file formats. This article, directed to novices as well as experts, first introduces concepts and methods used in the NAMD program, describing the classical molecular dynamics force field, equations of motion, and integration methods along with the efficient electrostatics evaluation algorithms employed and temperature and pressure controls used. Features for steering the simulation across barriers and for calculating both alchemical and conformational free energy differences are presented. The motivations for and a roadmap to the internal design of NAMD, implemented in C++ and based on Charm++ parallel objects, are outlined. The factors affecting the serial and parallel performance of a simulation are discussed. Finally, typical NAMD use is illustrated with representative applications to a small, a medium, and a large biomolecular system, highlighting particular features of NAMD, for example, the Tcl scripting language. The article also provides a list of the key features of NAMD and discusses the benefits of combining NAMD with the molecular graphics/sequence analysis software VMD and the grid computing/collaboratory software BioCoRE. NAMD is distributed free of charge with source code at www.ks.uiuc.edu.

14,558 citations

Journal ArticleDOI
TL;DR: A new implementation of the molecular simulation toolkit GROMACS is presented which now both achieves extremely high performance on single processors from algorithmic optimizations and hand-coded routines and simultaneously scales very well on parallel machines.
Abstract: Molecular simulation is an extremely useful, but computationally very expensive tool for studies of chemical and biomolecular systems Here, we present a new implementation of our molecular simulation toolkit GROMACS which now both achieves extremely high performance on single processors from algorithmic optimizations and hand-coded routines and simultaneously scales very well on parallel machines The code encompasses a minimal-communication domain decomposition algorithm, full dynamic load balancing, a state-of-the-art parallel constraint solver, and efficient virtual site algorithms that allow removal of hydrogen atom degrees of freedom to enable integration time steps up to 5 fs for atomistic simulations also in parallel To improve the scaling properties of the common particle mesh Ewald electrostatics algorithms, we have in addition used a Multiple-Program, Multiple-Data approach, with separate node domains responsible for direct and reciprocal space interactions Not only does this combination of a

14,032 citations