CAVER Analyst 1.0: graphic tool for interactive visualization and analysis of tunnels and channels in protein structures

ABSTRACT Summary: The transport of ligands, ions or solvent molecules into proteins with buried binding sites or through the membrane is enabled by protein tunnels and channels. CAVER Analyst is a software tool for calculation, analysis and real-time visualization of access tunnels and channels in static and dynamic protein structures. It provides an intuitive graphic user interface for setting up the calculation and interactive exploration of identified tunnels/channels and their characteristics. Availability and Implementation: CAVER Analyst is a multi-platform software written in JAVA. Binaries and documentation are freely available for non-commercial use at http://www.caver.cz

CaverDock: Software tool for fast screening of un/binding of ligands in protein engineering

Protein tunnels, channels and gates are important for enzymatic catalysis and also represent attractive targets for rational protein design and drug design [1]. Drug molecules blocking the access of natural substrate or release of products are very efficient modulators of biological activity. Here we demonstrate the application of newly in-house developed software tool CaverDock [2,3] for the analysis of the transport of ligands through tunnels in biomolecular targets. Caverdock is a new addition to the Caver Suite [4-6]. We performed virtual screening of large databases of drugs against two pharmacologically relevant targets. We have used FDA-approved drugs for both targets. Oncological drugs (133 molecules), taken from the NIH website, and anti-inflammatory (56 molecules), taken from the Drugbank website, as the libraries of ligands for the two molecular targets: (i) cytochrome P450 17A1 and (ii) leukotriene A4 hydrolase/aminopeptidase. Moreover, we will also show the unbinding of the 2,3-dichloropropan-1-ol product from a buried active site of an haloalkane dehalogenase and its variant. With this study we identified hot-spots that may be used for directed evolution or site-directed mutagenesis to create new variants for faster 2,3-dichloropropan-1-ol release [7]. Finally, we will show the difference on ligand transportation when a protein is in an open and closed conformations [8]. We will show how CaverDock tackles the problem of protein flexibility. 1. Marques, S.M., et al., 2017: Enzyme Tunnels and Gates as Relevant Targets in Drug Design. Medicinal Research Reviews 37: 1095-1139. 2. Vavra, O., et al., 2019: CaverDock 1.0: A New Tool for Analysis of Ligand Binding and Unbinding Based on Molecular Docking. Bioinformatics (under review). 3. Filipovic, J., et al, 2019: A Novel Method for Analysis of Ligand Binding and Unbinding Based on Molecular Docking. Transactions on Computational Biology and Bioinformatics (under review) 4. Chovancova, E., et al., 2012: CAVER 3.0: A Tool for Analysis of Transport Pathways in Dynamic Protein Structures. PLOS Computational Biology 8: e1002708. 5. Jurcik, A., et al., 2018: CAVER Analyst 2.0: Analysis and Visualization of Channels and Tunnels in Protein Structures and Molecular Dynamics Trajectories. Bioinformatics 34: 3586-3588. 6. Stourac, J., et al., 2019: Caver Web 1.0: Identification of Tunnels and Channels in Proteins and Analysis of Ligand Transport. Nucleic Acids Research (under review). 7. Marques, S.M., et al., 2019: Computational Study of Protein-Ligand Unbinding for Enzyme Engineering. Frontiers in Chemistry 6: 650. 8. Kokkonen, P., et al., 2018: Molecular Gating of an Engineered Enzyme Captured in Real Time. Journal of the American Chemical Society 140: 17999–18008

Caver Web 1.0: identification of tunnels and channels in proteins and analysis of ligand transport

Caver Web 1.0 is a web server for comprehensive analysis of protein tunnels and channels, and study of the ligands’ transport through these transport pathways. Caver Web is the first interactive tool allowing both the analyses within a single graphical user interface. The server is built on top of the abundantly used tunnel detection tool Caver 3.02 and CaverDock 1.0 enabling the study of the ligand transport. The program is easy-to-use as the only required inputs are a protein structure for a tunnel identification and a list of ligands for the transport analysis. The automated guidance procedures assist the users to set up the calculation in a way to obtain biologically relevant results. The identified tunnels, their properties, energy profiles and trajectories for ligands’ passages can be calculated and visualized. The tool is very fast (2–20 min per job) and is applicable even for virtual screening purposes. Its simple setup and comprehensive graphical user interface make the tool accessible for a broad scientific community. The server is freely available at https://loschmidt.chemi.muni.cz/caverweb.Caver Web 1.0 je webový server pro komplexní analýzu tunelů a kanálů v proteinech a pro studium transportu ligandu přes tyto transportní cesty. Caver Web je první interaktivní nástroj umožňující obě analýzy v jednom grafickém uživatelském rozhraní. Server je vybudován nad hojně užívaným nástrojem pro detekci tunelů Caver 3.02 a nad CaverDock 1.0 umožňujícím studium transportu ligandů. Program se snadno ovládá, jelikož vyžaduje pouze strukturu proteinu pro identifikaci tunelů a seznam ligandů pro analýzu transportu. Procedury pro automatické nastavení výpočtů asistují uživatelům tak, aby získali biologicky relevantní výsledky. Identifikované tunely, jejich vlastnosti, energetické profily a trajektorie průchodů ligandů mohou být spočítány a vizualizovány. Nástroj je velmi rychlý (2-20 minut na úlohu) a je použitelný dokonce pro virtuální screening. Jeho snadné nastavení a ucelené grafické rozhraní dělá nástroj přístupným pro širokou vědeckou komunitu. Server je volně k dispozici na https://loschmidt.chemi.muni.cz/caverweb

Engineering enzyme access tunnels

Enzymes are efficient and specific catalysts for many essential reactions in biotechnological and pharmaceutical industries. Many times, the natural enzymes do not display the catalytic efficiency, stability or specificity required for these industrial processes. The current enzyme engineering methods offer solutions to this problem, but they mainly target the buried active site where the chemical reaction takes place. Despite being many times ignored, the tunnels and channels connecting the environment with the active site are equally important for the catalytic properties of enzymes. Changes in the enzymatic tunnels and channels affect enzyme activity, specificity, promiscuity, enantioselectivity and stability. This review provides an overview of the emerging field of enzyme access tunnel engineering with case studies describing design of all the aforementioned properties. The software tools for the analysis of geometry and function of the enzymatic tunnels and channels and for the rational design of tunnel modifications will also be discussed. The combination of new software tools and enzyme engineering strategies will provide enzymes with access tunnels and channels specifically tailored for individual industrial processes

Interactive Visualization of Molecular Dynamics Simulation Data

Molecular Dynamics Simulations (MD) plays an essential role in the field of computational biology. The simulations produce extensive high-dimensional, spatio-temporal data describ-ing the motion of atoms and molecules. A central challenge in the field is the extraction and visualization of useful behavioral patterns from these simulations. Throughout this thesis, I collaborated with a computational biologist who works on Molecular Dynamics (MD) Simu-lation data. For the sake of exploration, I was provided with a large and complex membrane simulation. I contributed solutions to his data challenges by developing a set of novel visual-ization tools to help him get a better understanding of his simulation data. I employed both scientific and information visualization, and applied concepts of abstraction and dimensions projection in the proposed solutions. The first solution enables the user to interactively fil-ter and highlight dynamic and complex trajectory constituted by motions of molecules. The molecular dynamic trajectories are identified based on path length, edge length, curvature, and normalized curvature, and their combinations. The tool exploits new interactive visual-ization techniques and provides a combination of 2D-3D path rendering in a dual dimension representation to highlight differences arising from the 2D projection on a plane. The sec-ond solution introduces a novel abstract interaction space for Protein-Lipid interaction. The proposed solution addresses the challenge of visualizing complex, time-dependent interactions between protein and lipid molecules. It also proposes a fast GPU-based implementation that maps lipid-constituents involved in the interaction onto the abstract protein interaction space. I also introduced two abstract level-of-detail (LoD) representations with six levels of detail for lipid molecules and protein interaction. Finally, I proposed a novel framework consisting of four linked views: A time-dependent 3D view, a novel hybrid view, a clustering timeline, and a details-on-demand window. The framework exploits abstraction and projection to enable the user to study the molecular interaction and the behavior of the protein-protein interaction and clusters. I introduced a selection of visual designs to convey the behavior of protein-lipid interaction and protein-protein interaction through a unified coordinate system. Abstraction is used to present proteins in hybrid 2D space, and a projected tiled space is used to present both Protein-Lipid Interaction (PLI) and Protein-Protein Interaction (PPI) at the particle level in a heat-map style visual design. Glyphs are used to represent PPI at the molecular level. I coupled visually separable visual designs in a unified coordinate space. The result lets the user study both PLI and PPI separately, or together in a unified visual analysis framework

sMolBoxes: Dataflow Model for Molecular Dynamics Exploration

We present sMolBoxes, a dataflow representation for the exploration and analysis of long molecular dynamics (MD) simulations. When MD simulations reach millions of snapshots, a frame-by-frame observation is not feasible anymore. Thus, biochemists rely to a large extent only on quantitative analysis of geometric and physico-chemical properties. However, the usage of abstract methods to study inherently spatial data hinders the exploration and poses a considerable workload. sMolBoxes link quantitative analysis of a user-defined set of properties with interactive 3D visualizations. They enable visual explanations of molecular behaviors, which lead to an efficient discovery of biochemically significant parts of the MD simulation. sMolBoxes follow a node-based model for flexible definition, combination, and immediate evaluation of properties to be investigated. Progressive analytics enable fluid switching between multiple properties, which facilitates hypothesis generation. Each sMolBox provides quick insight to an observed property or function, available in more detail in the bigBox View. The case study illustrates that even with relatively few sMolBoxes, it is possible to express complex analyses tasks, and their use in exploratory analysis is perceived as more efficient than traditional scripting-based methods.Comment: 10 pages, 9 figures, IEEE VIS, TVC