MolVa: Workshop on Molecular Graphics and Visual Analysis of Molecular Data 2019

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Browsing MolVa: Workshop on Molecular Graphics and Visual Analysis of Molecular Data 2019 by Subject "Applied computing"

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    A Massively Parallel CUDA Algorithm to Compute and Visualize the Solvent Excluded Surface for Dynamic Molecular Data
    (The Eurographics Association, 2019) Schäfer, Marco; Krone, Michael; Byska, Jan and Krone, Michael and Sommer, Björn
    The interactive visualization of molecular surfaces can help users to understand the dynamic behavior of proteins in molecular dynamics simulations. These simulations play an important role in biochemical and pharmaceutical research, e.g. in drug design. The efficient calculation of molecular surfaces in a fast and memory-saving way is a challenging task. For example, to gain a detailed understanding of complex diseases like Alzheimer, conformational changes and spatial interactions between molecules have to be investigated. Molecular surfaces, such as Solvent Excluded Surfaces (SES), are instrumental for identifying structures such as tunnels or cavities that critically influence transport processes and docking events, which might induce enzymatic reactions. Therefore, we developed a highly parallelized algorithm that exploits the massive computing power of modern graphics hardware. Our analytical algorithm is suitable for the real-time computation of dynamic SES based on many time steps, as it runs interactively on a single consumer GPU for more than 20 k atoms.
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    PBmapclust: Mapping and Clustering the Protein Conformational Space Using a Structural Alphabet
    (The Eurographics Association, 2019) Vetrivel, Iyanar; Hoffmann, Lionel; Guegan, Sean; Offmann, Bernard; Laurent, Adele D.; Byska, Jan and Krone, Michael and Sommer, Björn
    Analyzing the data from molecular dynamics simulation of biological macromolecules like proteins is challenging. We propose a simple tool called PBmapclust that is based on a well established structural alphabet called Protein blocks (PB). PBs help in tracing the trajectory of the protein backbone by categorizing it into 16 distinct structural states. PBmapclust provides a time vs. amino acid residue plot that is color coded to match each of the PBs. Color changes correspond to structural changes, giving a visual overview of the simulation. Further, PBmapclust enables the user to "map" the conformational space sampled by the protein during the MD simulation by clustering the conformations. The ability to generate sub-maps for specific residues and specific time intervals allows the user to focus on residues of interest like for active sites or disordered regions. We have included an illustrative case study to demonstrate the utility of the tool. It describes the effect of the disordered domain of a HSP90 co-chaperone on the conformation of its active site residues. The scripts required to perform PBmapclust are made freely available under the GNU general public license.
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    QuickSES: A Library for Fast Computation of Solvent Excluded Surfaces
    (The Eurographics Association, 2019) Martinez, Xavier; Krone, Michael; Baaden, Marc; Byska, Jan and Krone, Michael and Sommer, Björn
    Recently, several fast methods to compute Solvent Excluded Surfaces (SES) on GPUs have been presented. While these published methods reportedly yield interesting and useful results, up to now no public, freely accessible implementation of a fast and opensource SES mesh computation method that runs on GPUs is available. Most molecular viewers, therefore, still use legacy CPU methods that run only on a single core, without GPU acceleration. In this paper, we present an in-depth explanation and a fully open-source CUDA implementation of the fast, grid-based computation method proposed by Hermosilla et al. [HKG*17]. Our library called QuickSES runs on GPUs and is distributed with a permissive license. It comes with a standalone program that reads Protein Data Bank (PDB) files and outputs a complete SES mesh as a Wavefront OBJ file. Alternatively it can directly be integrated in classical molecular viewers as shared library. We demonstrate the low memory consumption to enable execution on lower-end GPUs, and compare the runtime speed-up to available state-of-the-art tools.