CAVER Analyst 2.0




CAVER Analyst is a software tool for calculation, analysis and real-time visualization of access tunnels in static and dynamic protein structures. It provides an intuitive graphic user interface for setting up the calculation and interactive exploration of identified tunnels and their characteristics. It integrates the CAVER 3.01 algorithms. The software can easily be applied for the analysis of single static structures, as well as for direct comparison of transport pathways in a set of homologous structures and for the study of their molecular dynamics.

CAVER Analyst

CAVER Analyst provides users with all standard visualization styles and tools for exploration and manipulation with molecules.

Tunnel computation

Computation of pathways is based on powerful CAVER 3.01 algorithm. The calculation can be set and performed directly using the CAVER Analyst interface. The most important calculation settings are available through the Tunnel Computation window, while the advanced parameters can be set in the Tunnel Advanced Settings window or loaded from the configuration file.

The position of the starting point can be loaded from the CSA database, derived from the center of a selected cavity, from a selection or it can be set manually. CAVER Analyst also enables to load results computed by the standalone CAVER 3.01 application. This option is recommended mainly for processing of large trajectories.

CAVER Analyst

Tunnel visualization

Users can utilize various methods for the visualization of tunnels. Tunnel location and curvature can be displayed using a simple center-line. Approximate tunnel geometry is visualized by a set of intersecting spheres. The most precise method, the detailed surface, presents the tunnel geometry more accurately, including the asymmetrical parts.

Pathways identified throughout the entire trajectory can be visualized all in one snapshot as their centerlines, providing their overview and assignment to individual clusters.

CAVER Analyst

Tunnel statistics

This part contains the summary statistics as well as the detailed characteristics of detected tunnels. It shows the statistics of tunnel clusters, such as frequency, priority, average bottleneck radius, length, curvature, etc. Individual tunnels can also be explored on the level of their profiles, where users can observe changes in the tunnel radius and the surrounding residues along its length.

The Tunnel Statistics panel is interactively connected with the visualization window. It enables to immediately explore selected tunnels and residues.

CAVER Analyst

Residues lining a given pathway and bottleneck

The Tunnel Statistics panel intuitively shows the residues lining the given tunnel along the tunnel length. The lining residues are highlighted with green color. Blue color indicates residues forming the tunnel bottleneck.

CAVER Analyst

Pathway profiles and heat plots

Tunnel characteristics can also be plotted using 2D graphs and heat plots. Users can combine profiles of tunnels from various structures or snapshots.

CAVER Analyst

CAVER Analyst

Computation and visualization of cavities

CAVER Analyst integrates the algorithm for calculation and visualization of molecular surfaces and cavities. It utilizes the additively weighted Voronoi diagram and allows users the real-time exploration of detected cavities. Users can also use a cavity for the detection of starting point position for tunnel computation.

CAVER Analyst

The detailed description of all CAVER Analyst features is available in the user guide, which is an integrated part of the CAVER Analyst application (see menu Help -> User Guide).

Other features

Molecular Visualization Methods

Traditional as well as novel approaches to molecular visualization enable the user to explore their molecules from very different points of view. Supported methods involve:

  • Van der Waals method
  • Lines (or Wireframe) method
  • Sticks method
  • Balls and sticks
  • Cartoon (or Ribbon)
  • Alpha trace
  • Surface
  • Dots
  • Points

There are other advanced features still enhance the overall appearance and precision of displayed molecules, such as:

  • Visualization of multiple bonds
  • Visualization of unbonded atoms
  • Displaying fog enhancing depth perception

Selections

Significant parts of molecules (atoms, residues, chains) which are in user's scope of interest can be selected and handled separately. Treatment of such selections involves e.g. changing their visualization method or coloring.

Structure Sequence

Loaded structures can be alternatively explored via the list of their chains and residues which is denoted as structure sequence. This sequence bears the information about the constitution of molecule in form of one-letter abbreviations of residue names. These residues are subsequently ordered according to their position in the molecular chain. Clicking on a specific residue in this sequence causes its selection in the displaying window and involving it into the currently active selection. Moreover, by operating with structure sequence, users can select/deselect not only residues but alse the whole molecule at once or pick only its parts, such as chains or atoms.

Molecular Dynamics

CAVER Analyst enables to load the molecular dynamics as a sequence of PDB snapshots. Such loaded sequence can be replayed as a movie and subsequently explored using standard features for replaying animation, such as changing frame rate, skipping some frames, jumping to desired frame or playing the animation in a loop.

Clip Planes

In comparison with depicting important object by grouping them into selections, molecules contain also parts which are of less importance in some specific cases. In these situations it is valuable to crop such parts and concentrate only on the important ones. In such case CAVER Analyst offers a set of clip planes with configurable position and orientation which filter the uninteresting information in molecules and can be handled in many different ways. Moreover, users can set objects, such as tunnels or selections, which should not be cut away.

Coloring and advanced displaying methods

In order to enhance the visual appearance of molecules, various techniques were involved into CAVER Analyst. Molecules can be colored according to their atoms, residues, chains, secondary structures or various chemical properties, such as hydrophobicity. Color transitions are interpolated or can remain split. Of course, various visualization methods support corresponding types of coloring.

One of the most desired and remarkable features is the perception of depth in molecules. Best results can be obtained by using stereoscopic view but not all computers are currently equipped with such device. Thus CAVER Viewer implements a trade-off between precise 3D and 2D visualization by introducing technique known as ambient occlusion. It enables to perceive the difference in depth inside molecule on traditional displays.

Structure Alignment

Two structures with similar sequences can be aligned so their overlapping parts can be revealed. This can lead to classification of molecules with similar characteristics and behavior.

Hydrogen Computation

For many structures in the PDB database the information about their hydrogen atoms is incomplete or is completely missing. But sometimes hydrogens can play important role in analysis. Thus CAVER Analyst enables to compute hydrogen positions for given molecule or even remove the existing hydrogens and recompute their position.

Workspace management

Users can save their current workspace including loaded structures, their current settings, computed tunnels and many other features, such as clip planes. Such workspace can be subsequently reloaded on the same computer or transferred to another one. This enables users to share their current environment and thus share their ideas and experience very quickly.

Structure Properties

List of the detailed information about the structure and its parts.

CAVER 3.0

CAVER is a software tool widely used for the identification and characterization of transport pathways in static macromolecular structures. CAVER 3.0 implements new algorithms for the calculation and clustering of pathways. A trajectory from a molecular dynamics simulation serves as the typical input, while detailed characteristics and summary statistics of the time evolution of individual pathways are provided in the outputs.

CAVER 3.0 paves the way for the study of important biochemical phenomena in the area of molecular transport, molecular recognition and enzymatic catalysis.

CAVER 3.0 is written in the Java programming language and runs on all operating systems with installed Java Runtime Environment 6.0 or higher. The algorithm of CAVER 3.0 consists of three separable steps:

  1. identification of pathways in each provided structure, e.g., each snapshot of a MD simulation;
  2. clustering of pathways identified in all snapshots; and
  3. calculation and generation of output data.

CAVER 3.0

Due to the separation of the identification and clustering steps, it is possible to run the calculation of pathways in different snapshots in parallel. Moreover, the results of each step can be saved and processed in the subsequent steps with varying parameters, thus accelerating the search for optimal parameters for the studied system.

CAVER 3.0

CAVER 3.0

For detailed information about CAVER 3.0 usage see the user guide.

CAVER 3.0 PyMOL Plugin

CAVER PyMOL plugin v3.0 enables calculation and visualization of tunnels in PyMOL. For the calculation of tunnels, the plugin utilizes CAVER 3.0 software package.

CAVER 3.0

CAVER plugin is written in the Python programming language and runs on all operating systems. We recommend you to use Python 2.7 or higher.

CAVER 3.0

For detailed information about the usage of CAVER PyMOL plugin v3.0 see user guide.

CaverDock

CaverDock is a novel method and the software tool CaverDock for the prediction of the protein-ligand binding or unbinding and the evaluation of the potential energy along the ligand trajectory.This method is based on the molecular docking algorithm from AutoDock Vina. CaverDock iteratively docks the ligand along the tunnel and evaluates the potential energy using a hybrid force-field. It utilizes a combination of a chemical force-field to compute the potential energy of the protein-ligand complex and a constraint force-field which restricts the space of possible ligand positions. Thus, the position of the ligand within the tunnel can be constrained to the defined area. Since there are many possible paths through the tunnel, the paths are searched using a heuristic algorithm with backtracking. The workflow of the method is described in Figure 1. CaverDock uses parallel architecture to maximize the performance of ligand transition computation.

CaverDock

Figure 1. CaverDock workflow. (A) Tunnel geometry obtained from the CAVER is (B) discretized to a set of discs. (C) Initially the lower-bound discontinuous trajectory is calculated. The ligand may flip through narrowed parts of tunnel. (D) Next the upper-bound continuous trajectory is calculated. Here the movement is continuous and the ligand must be in favorable orientation in order to pass through the narrow regions. (E) This is done using the forward movements and backtracking to find the optimal trajectory.

CaverDock calculation is easy to setup, and can be used for comparisons of: 1) different ligands in the same protein, 2) ligands passing through different tunnels of the protein or 3) corresponding tunnels from different protein variants. The main benefit of CaverDock is, that it can sample the binding energy throughout the whole protein tunnel and identify unfavourable binding interactions, which can then be optimized by site-directed mutagenesis. Such places would be missed by traditional docking techniques. (Figure 2). The calculation time of one CaverDock simulation takes from several minutes to hours depending on the complexity of given case (length and geometry of the tunnel, size of the ligand). In comparison MD simulations of the ligand unbinding may take several days of computation time. Therefore, this method is suitable for large scale studies with many proteins and a high number of ligands. CaverDock binaries and Apptainer packages are available at our webpage together with detailed documentation. The method was implemented in the user-friendly webserver Caver Web. Furthermore, a new python API was developed to simplify the tasks required in projects using CaverDock. The usefulness and applicability of the method were shown in published case studies with various enzymes, tunnel geometries and ligands, and in screening analyses.

CaverDock

Figure 2. Example extracted conformations from the binding trajectory of temozolomide through a tunnel of cytochrome P450. CaverDock is able to find parts of the tunnel with low binding energy (green) or unfavourable energies (red).



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