Exposon Analysis

Quick floe search term: CPD B1-C2

This floe can be run with the protein sampling output generated from either a water-xenon mixed-solvent simulation or a single-solvent simulation. This method detects pockets by finding sites that show cooperative changes in solvent exposure [Porter2019].

Tip

This floe typically takes 3 hours to run and costs ~$30.

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 Exposon 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:

  Select the destination for your output data by specifying the Output path.

• Input Data:

  You will need to provide a Protein Sampling Data collection generated by the Run a Weighted Ensemble MD Simulation floe as an input.

• Output Data:

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

• Cryptic Pocket Analysis Advanced Settings:

  Functionally important residues e.g. 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 Exposon Analysis for additional details.

• Selection Range For Trajectories:

  End Iteration: If left unspecified, the entire simulation dataset is analyzed. You can select a number lower than the total number of iterations for which your weighted ensemble MD simulation was run.

  Start Iteration: This parameter and End Iteration define the range of iterations to include in cryptic pocket analysis from the weighted ensemble simulations. The default setting includes all iterations starting from 1. By setting a number greater than 1 for Start Iteration, initial iterations can be excluded from the analysis. We do not recommend excluding initial iterations from the analysis.

Job Submission Form

Click on the green Start Job button a the bottom right corner of the page.

Visualize Cryptic Pocket Analysis Report and Pocket Receptors

Cryptic Pockets Floe Report (Exposon Analysis)

• Access the floe report:

  When the job is complete, the output floe report - Cryptic Pockets Floe Report (Exposon 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 (Exposon Analysis). This will redirect you to a report containing an Interactive Network Plot of pockets detected as sites that undergo cooperative changes in solvent exposure.

• Visualize the interactive network plot:

  Each node in the Interactive Network Plot represents a pocket. The edge connecting two pockets corresponds to the inverse of the center-of-mass distance between those pockets. Node size corresponds to average intra-pocket cooperativity in solvent exposure. 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 be highlighted by a pink surface. 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 a node or the middle of an edge in the network plot will display the metadata associated with it.

• Download ranked pockets data:

  You can download the ranked pockets metadata by clicking on the RankedPockets.json link given at the Download figure data: RankedPockets.json. This file lists ranked pockets, their residue composition, and average intra-pocket cooperativity in solvent exposure.

Interactive Network Plot

Pocket Receptors (Exposon Analysis) Dataset

• Access the pocket receptors dataset:

  After the job is complete, you can get to the dataset - Pocket Receptors (Exposon Analysis) 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 the 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 (Exposon 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 the Pocket Receptors (Exposon Analysis) dataset that you are interested in. On the scatter plot on the Analyze page, choose the Receptor Volume for the y-axis and Pocket Rank for the x-axis. Click on the Layouts button in the top-right corner and select the Analyze with 3D option to visualize a design unit with a pocket receptor. This will show the protein structures of the representative conformations with a receptor corresponding to a selected pocket & receptor volume.

  • Pocket Rank column in the SPREADSHEET shows the pocket rank determined by the intra-pocket cooperativity in solvent exposure. The pocket rank 0 has the highest intra-pocket cooperativity.

  • 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. A representative conformation is selected for each pocket (exposon). This conformations has the highest receptor volume within the range 100 to 1500 ų.

  • 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 with the Receptor Volume provides gives an indication of the pocket opening/closing during simulation.

Pocket Receptors (Exposon Analysis)

• Sort and Select Pocket Receptors:

  Clicking on the Pocket Rank column given in the SPREADSHEET sorts the pockets by their rank, 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, Exposon Analysis will fail if no sites with cooperative changes in solvent exposure 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 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.