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H. Jelger Risselada

Bio: H. Jelger Risselada is an academic researcher from University of Göttingen. The author has contributed to research in topics: Membrane & Medicine. The author has an hindex of 17, co-authored 21 publications receiving 6347 citations. Previous affiliations of H. Jelger Risselada include Leiden University & Max Planck Society.

Papers
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Journal ArticleDOI
TL;DR: An improved and extended version of the coarse grained lipid model is presented, coined the MARTINI force field, based on the reproduction of partitioning free energies between polar and apolar phases of a large number of chemical compounds to reproduce the free energies of these chemical building blocks.
Abstract: We present an improved and extended version of our coarse grained lipid model. The new version, coined the MARTINI force field, is parametrized in a systematic way, based on the reproduction of partitioning free energies between polar and apolar phases of a large number of chemical compounds. To reproduce the free energies of these chemical building blocks, the number of possible interaction levels of the coarse-grained sites has increased compared to those of the previous model. Application of the new model to lipid bilayers shows an improved behavior in terms of the stress profile across the bilayer and the tendency to form pores. An extension of the force field now also allows the simulation of planar (ring) compounds, including sterols. Application to a bilayer/cholesterol system at various concentrations shows the typical cholesterol condensation effect similar to that observed in all atom representations.

4,580 citations

Journal ArticleDOI
24 Nov 2011-Nature
TL;DR: The results demonstrate that electrostatic protein–lipid interactions can result in the formation of microdomains independently of cholesterol or lipid phases.
Abstract: Neuronal exocytosis is catalysed by the SNAP receptor protein syntaxin-1A, which is clustered in the plasma membrane at sites where synaptic vesicles undergo exocytosis. However, how syntaxin-1A is sequestered is unknown. Here we show that syntaxin clustering is mediated by electrostatic interactions with the strongly anionic lipid phosphatidylinositol-4,5-bisphosphate (PIP2). Using super-resolution stimulated-emission depletion microscopy on the plasma membranes of PC12 cells, we found that PIP2 is the dominant inner-leaflet lipid in microdomains about 73 nanometres in size. This high accumulation of PIP2 was required for syntaxin-1A sequestering, as destruction of PIP2 by the phosphatase synaptojanin-1 reduced syntaxin-1A clustering. Furthermore, co-reconstitution of PIP2 and the carboxy-terminal part of syntaxin-1A in artificial giant unilamellar vesicles resulted in segregation of PIP2 and syntaxin-1A into distinct domains even when cholesterol was absent. Our results demonstrate that electrostatic protein-lipid interactions can result in the formation of microdomains independently of cholesterol or lipid phases.

545 citations

Journal ArticleDOI
TL;DR: A simulation model is applied to assess the molecular nature of domains formed in ternary mixtures, showing the spontaneous separation of a saturated phosphatidylcholine (PC)/unsaturated PC/cholesterol mixture into a liquid-ordered and aLiquid-disordered phase with structural and dynamic properties closely matching experimental data.
Abstract: Cell membranes contain a large number of different lipid species. Such a multicomponent mixture exhibits a complex phase behavior with regions of structural and compositional heterogeneity. Especially domains formed in ternary mixtures, composed of saturated and unsaturated lipids together with cholesterol, have received a lot of attention as they may resemble raft formation in real cells. Here we apply a simulation model to assess the molecular nature of these domains at the nanoscale, information that has thus far eluded experimental determination. We are able to show the spontaneous separation of a saturated phosphatidylcholine (PC)/unsaturated PC/cholesterol mixture into a liquid-ordered and a liquid-disordered phase with structural and dynamic properties closely matching experimental data. The near-atomic resolution of the simulations reveals remarkable features of both domains and the boundary domain interface. Furthermore, we predict the existence of a small surface tension between the monolayer leaflets that drives registration of the domains. At the level of molecular detail, raft-like lipid mixtures show a surprising face with possible implications for many cell membrane processes.

516 citations

Journal ArticleDOI
TL;DR: This work investigates the molecular mechanism of monolayer collapse using molecular dynamics simulations and finds that transformation into a vesicle reduces the energy of the fold perimeter and is facilitated for softer bilayers, e.g., those with a higher content of unsaturated lipids, or at higher temperatures.
Abstract: Lipid monolayers at an air-water interface can be compressed laterally and reach high surface density. Beyond a certain threshold, they become unstable and collapse. Lipid monolayer collapse plays an important role in the regulation of surface tension at the air-liquid interface in the lungs. Although the structures of lipid aggregates formed upon collapse can be characterized experimentally, the mechanism leading to these structures is not fully understood. We investigate the molecular mechanism of monolayer collapse using molecular dynamics simulations. Upon lateral compression, the collapse begins with buckling of the monolayer, followed by folding of the buckle into a bilayer in the water phase. Folding leads to an increase in the monolayer surface tension, which reaches the equilibrium spreading value. Immediately after their formation, the bilayer folds have a flat semielliptical shape, in agreement with theoretical predictions. The folds undergo further transformation and form either flat circular bilayers or vesicles. The transformation pathway depends on macroscopic parameters of the system: the bending modulus, the line tension at the monolayer-bilayer connection, and the line tension at the bilayer perimeter. These parameters are determined by the system composition and temperature. Coexistence of the monolayer with lipid aggregates is favorable at lower tensions of the monolayer-bilayer connection. Transformation into a vesicle reduces the energy of the fold perimeter and is facilitated for softer bilayers, e.g., those with a higher content of unsaturated lipids, or at higher temperatures.

267 citations

Journal ArticleDOI
TL;DR: The results suggest that PIP2 clusters organized by syntaxin-1 act as molecular beacons for vesicle docking, with the subsequent Ca2+ influx bringing the vesicles membrane close enough for membrane fusion.
Abstract: Synaptic-vesicle exocytosis is mediated by the vesicular Ca(2+) sensor synaptotagmin-1. Synaptotagmin-1 interacts with the SNARE protein syntaxin-1A and acidic phospholipids such as phosphatidylinositol 4,5-bisphosphate (PIP2). However, it is unclear how these interactions contribute to triggering membrane fusion. Using PC12 cells from Rattus norvegicus and artificial supported bilayers, we show that synaptotagmin-1 interacts with the polybasic linker region of syntaxin-1A independent of Ca(2+) through PIP2. This interaction allows both Ca(2+)-binding sites of synaptotagmin-1 to bind to phosphatidylserine in the vesicle membrane upon Ca(2+) triggering. We determined the crystal structure of the C2B domain of synaptotagmin-1 bound to phosphoserine, allowing development of a high-resolution model of synaptotagmin bridging two different membranes. Our results suggest that PIP2 clusters organized by syntaxin-1 act as molecular beacons for vesicle docking, with the subsequent Ca(2+) influx bringing the vesicle membrane close enough for membrane fusion.

248 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

Journal ArticleDOI
TL;DR: GROMACS is one of the most widely used open-source and free software codes in chemistry, used primarily for dynamical simulations of biomolecules, and provides a rich set of calculation types.

12,985 citations

Journal ArticleDOI
TL;DR: A range of new simulation algorithms and features developed during the past 4 years are presented, leading up to the GROMACS 4.5 software package, which provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations.
Abstract: Motivation: Molecular simulation has historically been a low-throughput technique, but faster computers and increasing amounts of genomic and structural data are changing this by enabling large-scale automated simulation of, for instance, many conformers or mutants of biomolecules with or without a range of ligands. At the same time, advances in performance and scaling now make it possible to model complex biomolecular interaction and function in a manner directly testable by experiment. These applications share a need for fast and efficient software that can be deployed on massive scale in clusters, web servers, distributed computing or cloud resources. Results: Here, we present a range of new simulation algorithms and features developed during the past 4 years, leading up to the GROMACS 4.5 software package. The software now automatically handles wide classes of biomolecules, such as proteins, nucleic acids and lipids, and comes with all commonly used force fields for these molecules built-in. GROMACS supports several implicit solvent models, as well as new free-energy algorithms, and the software now uses multithreading for efficient parallelization even on low-end systems, including windows-based workstations. Together with hand-tuned assembly kernels and state-of-the-art parallelization, this provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations. Availability: GROMACS is an open source and free software available from http://www.gromacs.org. Contact: erik.lindahl@scilifelab.se Supplementary information:Supplementary data are available at Bioinformatics online.

6,029 citations

Journal ArticleDOI
TL;DR: A new CG model for proteins as an extension of the MARTINI force field is developed and effectively reproduces peptide-lipid interactions and the partitioning of amino acids and peptides in lipid bilayers.
Abstract: Many biologically interesting phenomena occur on a time scale that is too long to be studied by atomistic simulations. These phenomena include the dynamics of large proteins and self-assembly of biological materials. Coarse-grained (CG) molecular modeling allows computer simulations to be run on length and time scales that are 2–3 orders of magnitude larger compared to atomistic simulations, providing a bridge between the atomistic and the mesoscopic scale. We developed a new CG model for proteins as an extension of the MARTINI force field. Here, we validate the model for its use in peptide-bilayer systems. In order to validate the model, we calculated the potential of mean force for each amino acid as a function of its distance from the center of a dioleoylphosphatidylcholine (DOPC) lipid bilayer. We then compared amino acid association constants, the partitioning of a series of model pentapeptides, the partitioning and orientation of WALP23 in DOPC lipid bilayers and a series of KALP peptides in dimyris...

2,173 citations

Journal ArticleDOI
TL;DR: The latest generations of sophisticated synthetic molecular machine systems in which the controlled motion of subcomponents is used to perform complex tasks are discussed, paving the way to applications and the realization of a new era of “molecular nanotechnology”.
Abstract: The widespread use of molecular machines in biology has long suggested that great rewards could come from bridging the gap between synthetic molecular systems and the machines of the macroscopic world. In the last two decades, it has proved possible to design synthetic molecular systems with architectures where triggered large amplitude positional changes of submolecular components occur. Perhaps the best way to appreciate the technological potential of controlled molecular-level motion is to recognize that nanomotors and molecular-level machines lie at the heart of every significant biological process. Over billions of years of evolution, nature has not repeatedly chosen this solution for performing complex tasks without good reason. When mankind learns how to build artificial structures that can control and exploit molecular level motion and interface their effects directly with other molecular-level substructures and the outside world, it will potentially impact on every aspect of functional molecule and materials design. An improved understanding of physics and biology will surely follow. The first steps on the long path to the invention of artificial molecular machines were arguably taken in 1827 when the Scottish botanist Robert Brown observed the haphazard motion of tiny particles under his microscope.1,2 The explanation for Brownian motion, that it is caused by bombardment of the particles by molecules as a consequence of the kinetic theory of matter, was later provided by Einstein, followed by experimental verification by Perrin.3,4 The random thermal motion of molecules and its implications for the laws of thermodynamics in turn inspired Gedankenexperiments (“thought experiments”) that explored the interplay (and apparent paradoxes) of Brownian motion and the Second Law of Thermodynamics. Richard Feynman’s famous 1959 lecture “There’s plenty of room at the bottom” outlined some of the promise that manmade molecular machines might hold.5,6 However, Feynman’s talk came at a time before chemists had the necessary synthetic and analytical tools to make molecular machines. While interest among synthetic chemists began to grow in the 1970s and 1980s, progress accelerated in the 1990s, particularly with the invention of methods to make mechanically interlocked molecular systems (catenanes and rotaxanes) and control and switch the relative positions of their components.7−24 Here, we review triggered large-amplitude motions in molecular structures and the changes in properties these can produce. We concentrate on conformational and configurational changes in wholly covalently bonded molecules and on catenanes and rotaxanes in which switching is brought about by various stimuli (light, electrochemistry, pH, heat, solvent polarity, cation or anion binding, allosteric effects, temperature, reversible covalent bond formation, etc.). Finally, we discuss the latest generations of sophisticated synthetic molecular machine systems in which the controlled motion of subcomponents is used to perform complex tasks, paving the way to applications and the realization of a new era of “molecular nanotechnology”. 1.1. The Language Used To Describe Molecular Machines Terminology needs to be properly and appropriately defined and these meanings used consistently to effectively convey scientific concepts. Nowhere is the need for accurate scientific language more apparent than in the field of molecular machines. Much of the terminology used to describe molecular-level machines has its origins in observations made by biologists and physicists, and their findings and descriptions have often been misinterpreted and misunderstood by chemists. In 2007 we formalized definitions of some common terms used in the field (e.g., “machine”, “switch”, “motor”, “ratchet”, etc.) so that chemists could use them in a manner consistent with the meanings understood by biologists and physicists who study molecular-level machines.14 The word “machine” implies a mechanical movement that accomplishes a useful task. This Review concentrates on systems where a stimulus triggers the controlled, relatively large amplitude (or directional) motion of one molecular or submolecular component relative to another that can potentially result in a net task being performed. Molecular machines can be further categorized into various classes such as “motors” and “switches” whose behavior differs significantly.14 For example, in a rotaxane-based “switch”, the change in position of a macrocycle on the thread of the rotaxane influences the system only as a function of state. Returning the components of a molecular switch to their original position undoes any work done, and so a switch cannot be used repetitively and progressively to do work. A “motor”, on the other hand, influences a system as a function of trajectory, meaning that when the components of a molecular motor return to their original positions, for example, after a 360° directional rotation, any work that has been done is not undone unless the motor is subsequently rotated by 360° in the reverse direction. This difference in behavior is significant; no “switch-based” molecular machine can be used to progressively perform work in the way that biological motors can, such as those from the kinesin, myosin, and dynein superfamilies, unless the switch is part of a larger ratchet mechanism.14

1,434 citations