Basic Tutorial: Automated Cryptic Pocket Detection with Probe Occupancy Analysis

Quick floe search term: CPD A1-C2

This tutorial demonstrates use of the Automated Cryptic Pocket Detection with Probe Occupancy Analysis Floe on beta-lactamase. This floe performs mixed-solvent simulations with 150 mM of xenon probes and performs probe occupancy analysis to identify potential cryptic pockets as sites with high xenon occupancy.

In the previous versions of the cryptic pocket detection package, this floe was provided as a set of multiple floes (A1-C2) that were run sequentially. You can still run the modular advanced floes sequentially instead of this single floe, starting from the Solvate and Equilibrate Target Protein Floe to the Probe Occupancy Analysis Floe. The instructions for doing this are provided in the Advanced Tutorials.

In this section, we will show you how to use the SPRUCE-prepared beta-lactamase protein for the Automated Cryptic Pocket Detection with Probe Occupancy Analysis Floe. For an example of how to prepare the apo 1JWP protein structure design unit, see the Preparing Input tutorial. Alternatively, you can download the prepared design unit for the 1JWP protein structure of beta-lactamase: Beta-Lactamase 1JWP protein structure DU


Running the Automated Cryptic Pocket Detection with Probe Occupancy Analysis Floe instead of the modular advanced floes (A1-C2) incurs an overhead cost. The amount of overhead cost depends on the system size and number of iterations run in weighted ensemble MD.


This floe typically takes more than a day to finish and costs ~$544.

Search and Run the Floe in Orion

Locate the Floe in Orion

Start by using the left hand vertical navigation tabs on your Orion home page to go to Floe page.

On the Floe page, click on the Floes tab, where you will find the list of the available floes and packages.

Click on a small caret next to Packages (under Filter Floes By section on the left) to expand the list of packages and click on the OpenEye Cryptic Pocket Detection Floes package. This will ensure that the floes listed in the middle of the page are from the Cryptic Pocket Detection package.

From this list, click on the Automated Cryptic Pocket Detection with Probe Occupancy Analysis Floe, and then click on the blue LAUNCH FLOE button in the bottom right corner of the page to launch the job submission form.

Provide Input Files and Parameters to Run the Floe

  • Output path:

    On the page that opens, select the place where your output data should be directed by specifying the Output Path.

  • Input Data:

    Choose the Target Protein to be the SPRUCE prepared dataset for beta-lactamase.

  • Output Data:

    You can customize the output dataset and collection names under the Output Data options.

  • Protein Solvation And Equilibration Advanced Settings:

    Advanced parameters for solvation and equilibration of target protein can be set under this option. Clicking on this tab will display these parameters. Additional details on these parameters can be found on Solvate and Equilibrate Target Protein. These parameters do not allow changing the mixed-solvent condition which is set to 150 mM xenon. For more control over the solvent composition, we recommend running the modular advanced floes.

  • Normal Modes Calculation Advanced Settings:

    Advanced parameters for normal mode calculation can be set under this option. Clicking this tab will display a list of parameters that can be adjusted if required. Additional details on these parameters can be found on Calculate Normal Modes Floe.

  • Weighted Ensemble MD Advanced Settings:

    Clicking on this tab will display advanced parameters for weighted ensemble MD simulations. You can change the total number of iterations and other weighted ensemble parameters here. Additional details on these parameters can be found on the Run a Weighted Ensemble MD Simulation Floe.

  • Weighted Ensemble MD Analysis Advanced Settings:

    Advanced settings for performing weighted ensemble trajectory analysis are provided under this section. See the Perform Weighted Ensemble MD Analysis Floe for additional details on these parameters.

  • Cryptic Pocket Analysis Advanced Settings:

    Functionally important residues, for example, active site residues or a known disease mutation, can be provided as input for the Important Residues. These residues will be displayed along with cryptic pocket residues in the cryptic pocket analysis floe report. See the Probe Occupancy Analysis Floe for additional details.


Job Submission Form

After providing the input design unit and optionally adjusting input parameters, click on the green Start Job button at the bottom right corner of the page.

Visualize Cryptic Pocket Analysis Report and Pocket Receptors

Cryptic Pockets Floe Report (Probe Occupancy Analysis)

  • Access the floe report:

    When the job is complete, the output floe report, Cryptic Pockets Floe Report (Probe Occupancy Analysis), should be inspected for visualization of cryptic pockets. You can get to this floe report by clicking on the job that you want to inspect. Under Reports, click on the floe report Cryptic Pockets Floe Report (Probe Occupancy Analysis). This will redirect you to a report containing an interactive network plot of pockets detected as high-occupancy probe binding sites.

  • Visualize the interactive network plot:

    Each node in the interactive network plot represents a pocket, and the edge connecting two pockets corresponds to the inverse of center of mass distance between two pockets. Node size corresponds to probe-occupancy free energy. The range of node colors corresponds to the number of pocket residues. By clicking on a node, a visualization of a representative protein configuration appears with the pocket-forming residues highlighted by a blue surface. If Important Residues input is provided by the user, those residues will get highlighted by a pink surface along with pocket-forming residues. You can visualize the residue side-chains by clicking on the Show Residues button given at the left-bottom corner of the page. Alternatively, clicking on an individual residue atom will show the label for that atom. Hovering over an edge in the network plot will display edge metadata.

  • Download ranked pockets data:

    You can also download the metadata for the ranked pockets by clicking on the RankedPockets.json link given at the Download figure data: RankedPockets.json. This file lists ranked pockets, their residue composition and probe occupancy free energy.


Interactive Network Plot of Cryptic Pockets

Pocket Receptors (Probe Occupancy Analysis) Dataset

  • Access the pocket receptors dataset:

    After the job is complete, you can get to the dataset PocketReceptors(ProbeOccupancyAnalysis) by clicking on the job. Click on the Floe tab on the blue navigation side bar and then click on the Jobs tab at the top of the page. Click on the job that you want to inspect. Click on VIEW IN PROJECT DATA button next to Results. This will redirect you to the Data navigation side bar tab and show only the outputs associated with the job. Click on the icon of a blue circle with a + symbol that is next to the dataset name (default name: Pocket Receptors (Probe Occupancy Analysis)). It will change to a green circle with a white checkmark and will allow you to view the dataset in the Analyze page and the 3D Modeling page.

  • Visualize pocket receptors dataset in the Analyze page:

    Click on the blue navigation side bar Analyze tab. Make sure that your Active Dataset is set to PocketReceptors(ProbeOccupancyAnalysis) dataset that you are interested in. On the scatter plot on the Analyze page, you can choose the Receptor Volume for the y-axis and Pocket Rank for the x-axis. Also click on the Layouts button in the top-right corner and select the Analyze with 3D option to visualize a design unit with pocket receptor. This will show a visual representation of the protein structures of the representative conformations with a receptor corresponding to a selected pocket and receptor volume.

    • The Pocket Rank column in the SPREADSHEET shows the pocket rank determined by the free energy of probe-occupancy for a pocket. The pocket rank 0 has the lowest free energy.

    • The Receptor Volume column in the SPREADSHEET shows the receptor volume for a pocket in a representative conformation selected from the cluster center conformations generated during cryptic pocket analysis. Two representative conformations are selected for each pocket (high occupancy probe-binding site). One of the conformations has the highest receptor volume within the range 100 to 1500 Å3. Another conformation is the one which has receptor volume value close to the volume of the high-occupancy probe binding site.

    • The Reference Receptor Volume column in the SPREADSHEET shows the receptor volume for a pocket in the equilibrated structure used to start the weighted ensemble MD simulation. Comparison of this value with the receptor volume value provides gives an indication of the pocket opening/closing during simulation.


Pocket Receptors (Probe Occupancy Analysis)

  • Sort and Select Pocket Receptors:

    Clicking on the Pocket Rank column given in the SPREADSHEET sorts the representative conformations by the pocket rank in these conformations, in either ascending or descending order.

    After sorting the structures by rank in the SPREADSHEET, click on a row with the Pocket Rank and Receptor Volume value of choice. This will display the protein structure in the Viewer panel corresponding to the selected row.

    Click on the small caret next to the corresponding design unit listed under All Data to display all components present in this design unit.

    Click on Receptor, IC, and OC to visualize the receptor. The receptor will appear in blue-colored mesh. After visualizing different design units and their receptors, you can select an appropriate design unit for Gigadocking or Sitehopper Analysis.

Failure Report

Your job might fail and generate a Failure Report. Open the Failure Report to see the instructions. The analysis can fail for multiple reasons:

  • The cryptic pocket detection method you chose failed to detect a pocket. It is possible that one or all of our cryptic pocket detection methods fail to detect the pockets. All three methods use different approaches and define “cryptic pockets” in a different manner. For example, Probe Occupancy Analysis will fail if no sites with high probe occupancy were identified.

  • No significant conformational changes associated with cryptic pocket formation were observed during the simulation. This could happen because of insufficient sampling or when the normal modes used as progress coordinates could not efficiently sample pocket formation. You may consider extending your weighted ensemble MD simulation using the Continue a Weighted Ensemble MD Simulation Floe and re-run the cryptic pocket analysis with the extended protein sampling. Alternatively, you can perform another weighted ensemble MD simulation using a different set of normal modes as progress coordinates with high variance in the region of interest in the target protein.

  • It is also possible that your target protein is highly inflexible, and therefore it doesn’t show conformational changes that can potentially reveal a cryptic pocket.