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Big Challenges on Joliot-Curie
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Big Challenges on Joliot-Curie - Before it goes in full production, a series of Grand Challenges – large scale simulations from academic and industry research – were carried out on Joliot-Curie supercomputer, from June to September 2018, to check that the system is functioning properly. These Grand Challenges represent a unique opportunity for selected scientists to gain access to the full supercomputer's resources, enabling them to make major advances, or even achieve world firsts that would be impossible to achieve with shared use.
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We present Tinker-HP, a massively MPI parallel package dedicated to classical molecular dynamics (MD) and to multiscale simulations, using advanced polarizable force fields (PFF) encompassing distributed multipoles electrostatics. Tinker-HP is an evolution of the popular Tinker package code that conserves its simplicity of use and its reference double precision implementation for CPUs. Grounded on interdisciplinary efforts with applied mathematics, Tinker-HP allows for long polarizable MD simulations on large systems up to millions of atoms.We detail in the paper the newly developed extension of massively parallel 3D spatial decomposition to point dipole polarizable models as well as their coupling to efficient Krylov iterative and non-iterative polarization solvers. The design of the code allows the use of various computer systems ranging from laboratory workstations to modern petascale supercomputers with thousands of cores. Tinker-HP proposes therefore the first high-performance scalable CPU computing environment for the development of next generation point dipole PFFs and for production simulations. Strategies linking Tinker-HP to Quantum Mechanics (QM) in the framework of multiscale polarizable self-consistent QM/MD simulations are also provided. The possibilities, performances and scalability of the software are demonstrated via benchmarks calculations using the polarizable AMOEBA force field on systems ranging from large water boxes of increasing size and ionic liquids to (very) large biosystems encompassing several proteins as well as the complete satellite tobacco mosaic virus and ribosome structures. For small systems, Tinker-HP appears to be competitive with the Tinker-OpenMM GPU implementation of Tinker. As the system size grows, Tinker-HP remains operational thanks to its access to distributed memory and takes advantage of its new algorithmic enabling for stable long timescale polarizable simulations. Overall, a several thousand-fold acceleration over a single-core computation is observed for the largest systems. The extension of the present CPU implementation of Tinker-HP to other computational platforms is discussed.
Significance
We use Brownian and Stokesian dynamics simulations to explore diffusion processes within an idealized biological cell. Although most studies assume processes occurring in an infinite medium, we focus on the effect that confinement within a cellular membrane may have on intracellular dynamics. One finding is that model proteins near the membrane tend to diffuse along the membrane; this may give additional time for signal transduction across the membrane to occur. We also observe more strongly correlated motions near the membrane than in the cell’s interior, potentially facilitating interactions between proteins there. Finally, we find that deep in the interior of the model cell, the confining effects of the finite size of a cell on the dynamics can be neglected.
The AMOEBA polarizable atomic multipole force field for nucleic acids is presented. Valence and electrostatic parameters were determined from high-level quantum mechanical data, including structures, conformational energy and electrostatic potentials, of nucleotide model compounds. Previously derived parameters for the phosphate group and nucleobases were incorporated. A total of over 35 microseconds of condensed phase molecular dynamics simulations of DNA and RNA molecules in aqueous solution and crystal lattice were performed to validate and refine the force field. The solution and/or crystal structures of DNA B-form duplexes, RNA duplexes and hairpins were captured with an average RMSD from NMR structures below or around 2.0 Å. Structural details, such as base pairing and stacking, sugar puckering, backbone and χ torsion angles, groove geometries and crystal packing interfaces, agreed well with NMR and/or X-ray. The interconversion between A- and B-form DNAs was observed in ethanol-water mixtures at 328K. Crystal lattices of B- and Z-form DNA and A-form RNA were examined with simulations. For the RNA tetra loop, single strand tetramers, and HIV TAR with 29 residues, the simulated conformational states, ³J-coupling, NOE and RDC data were compared with NMR results. Starting from a totally unstacked/unfolding state, the rCAAU tetranucleotide was folded into A-form like structures during ~1μs MD simulations.
Artificial organelles created from a bottom up approach are a new type of engineered materials, which are not designed to be living but, instead, to mimic some specific functions inside cells. By doing so, artificial organelles are expected to become a powerful tool in biomedicine. They can act as nanoreactors to convert a prodrug into a drug inside the cells or as carriers encapsulating therapeutic enzymes to replace malfunctioning organelles in pathological conditions. For the design of artificial organelles, several requirements need to be fulfilled: a compartmentalized structure that can encapsulate the synthetic machinery to perform an enzymatic function, as well as a means to allow for communication between the interior of the artificial organelle and the external environment, so that substrates and products can diffuse in and out the carrier allowing for continuous enzymatic reactions. The most recent and exciting advances in architectures that fulfill the aforementioned requirements are featured in this review. Artificial organelles are classified depending on their constituting materials, being lipid and polymer-based systems the most prominent ones. Finally, special emphasis will be put on the intracellular response of these newly emerging systems.
In order to mimic cell organelles, artificial nanoreactors have been investigated based on polymeric vesicles with reconstituted channel proteins (outer membrane protein F) and coencapsulated enzymes horseradish peroxidase (HRP) along with a crowding agent (Ficoll or polyethylene glycol) inside the cavity. Importantly, the presence of macromolecules has a strong impact on the enzyme kinetics, but no influence on the integrity of vesicles up to certain concentrations. This particular design allows for the first time the determination of HRP kinetics inside nonreactors with crowded milieu. The values of the Michaelis–Menten constant (K m) measured for HRP in a confined space (encapsulated in nanoreactors) in the absence of macromolecules are ≈50% lower than in free conditions, and the presence of a crowding agent results in a further pronounced decrease. These results clearly suggest that activities of enzymes in confined spaces can be tuned by varying the concentrations of crowding compounds. The present investigation represents an advance in nanoreactor design by considering the influence of environmental factors on enzymatic performance, and it demonstrates that both encapsulation and the presence of a crowding environment increase the enzyme-substrate affinity.
Computer simulations based on simplified representations are routinely used to explore the early steps of amyloid aggregation. However, when protein models with implicit solvent are employed, these simulations miss the effect of solvent induced correlations on the aggregation kinetics and lifetimes of metastable states. In this work, we apply the multi-scale Lattice Boltzmann Molecular Dynamics technique (LBMD) to investigate the initial aggregation phases of the amyloid Aβ 16−22 peptide. LBMD includes naturally hydrodynamic interactions (HIs) via a kinetic on-lattice representation of the fluid kinetics. The peptides are represented by the flexible OPEP coarse-grained force field. First, we have tuned the essential parameters that control the coupling between the molecular and fluid evolutions in order to reproduce the experimental diffusivity of elementary species. The method is then deployed to investigate the effect of HIs on the aggregation of 100 and 1000 Aβ 16−22 peptides. We show that HIs clearly impact the aggregation process and the fluctuations of the oligomer sizes by favouring the fusion and exchange dynamics of oligomers between aggregates. HIs also guide the growth of the leading largest cluster. For the 100 Aβ 16−22 peptide system, the simulation of ∼300 ns allowed us to observe the transition from ellipsoidal assemblies to an elongated and slightly twisted aggregate involving almost the totality of the peptides. For the 1000 Aβ 16−22 peptides, a system of unprecedented size at quasi-atomistic resolution, we were able to explore a branched disordered fibril-like structure that has never been described by other computer simulations, but has been observed experimentally.
Within each biological cell, surface-and volume-confined enzymes control a highly complex network of chemical reactions. These reactions are efficient, timely, and spatially defined. Efforts to transfer such appealing features to in vitro systems have led to several successful examples of chemical reactions catalysed by isolated and immobilized enzymes. In most cases, these enzymes are either bound or adsorbed to an insoluble support, physically trapped in a macromolecular network, or encapsulated within compartments. Advanced applications of enzymatic cascade reactions with immobilized enzymes include enzymatic fuel cells and enzymatic nanoreactors, both for in vitro and possible in vivo applications. In this Review, we discuss some of the general principles of enzymatic reactions confined on surfaces, at interfaces, and inside small volumes. We also highlight the similarities and differences between the in vivo and in vitro cases and attempt to critically evaluate some of the necessary future steps to improve our fundamental understanding of these systems.
Combined experimental and computational study of lipid membranes and liposomes, with the aim to attain mechanistic understanding, results in a synergy that makes possible the rational design of liposomal drug delivery system (LDS) based therapies. The LDS is the leading form of nanoscale drug delivery platform, an avenue in drug research, known as “nanomedicine", that holds the promise to transcend the current paradigm of drug development that has led to diminishing returns. Unfortunately this field of research has, so far, been far more successful in generating publications than new drug therapies. This partly results from the trial and error based methodologies used. We discuss experimental techniques capable of obtaining mechanistic insight into LDS structure and behavior. Insight obtained purely experimentally is, however, limited; computational modeling using molecular dynamics simulation can provide insight not otherwise available. We review computational research, that makes use of the multiscale modeling paradigm, simulating the phospholipid membrane with all atom resolution and the entire liposome with coarse grained models. We discuss in greater detail the computational modeling of liposome PEGylation. Overall, we wish to convey the power that lies in the combined use of experimental and computational methodologies; we hope to provide a roadmap for the rational design of LDS based therapies. Computational modeling is able to provide mechanistic insight that explains the context of experimental results and can also take the lead and inspire new directions for experimental research into LDS development. This article is part of a Special Issue entitled: Biosimulations edited by Ilpo Vattulainen and Tomasz Róg.
