C1. Cryptic Pocket Detection: Cooperative Cosolvent Binding Analysis

Category Paths

Follow one of these paths in the Orion user interface, to find the floe.

  • Product-based/Molecular Dynamics

  • Solution-based/Virtual-screening/Target Preparation

  • Solution-based/Hit to Lead/Target Preparation/Enhanced Sampling

  • Solution-based/Target Identification/Target Preparation/Pocket Detection

  • Solution-based/Hit to Lead/Target Preparation/Cryptic Pocket Detection

  • Role-based/Computational Chemist

  • Task-based/Target Prep & Analysis/Pocket Detection

Description

This floe identifies cryptic pockets as groups of residues that exhibit cooperative changes in their co-solvent binding behavior during Weighted Ensemble MD simulations.

Promoted Parameters

Title in user interface (promoted name)

Inputs from Protein Sampling

Solvated and Equilibrated Design Unit (du_data_in): This is the ‘Solvated and Equilibrated Design Unit’ output dataset from the ‘A1. Protein Sampling (for Cryptic Pockets): Solvate and Equilibrate Target Protein’ floe.

  • Required

  • Type: data_source

Topology File (top_file): PDB file specifying the system topology. This file is generated by

the ‘A1. Protein Sampling (for Cryptic Pockets): Solvate and Equilibrate Target Protein’ Floe.

  • Required

  • Type: file_in

Protein Sampling (Weighted Ensemble MD Simulation) Dataset (westdata_in): This is a ‘Protein Sampling Dataset’ output generated by ‘A3a. Protein Sampling (for Cryptic Pockets): Run a Weighted Ensemble MD Simulation’ or ‘A3b. Protein Sampling (for Cryptic Pockets): Continue a Weighted Ensemble MD Simulation’. The dataset should come from the most recent Protein Sampling job run for a given protein.

  • Required

  • Type: data_source

Inputs from Trajectory Analysis

Cluster Members Dataset (Residue-Cosolvent Distances) (clusters_data_in): This is the ‘Cluster Members’ dataset output from the ‘B2. Trajectory Analysis (for Cryptic Pockets): Cluster Conformations’.The datset contains cluster-labels assigned to each MD frame.

  • Required

  • Type: data_source

Cluster Medoids Dataset (Residue-Cosolvent Distances) (medoids_data_in): This is the ‘Cluster Medoids’ dataset output from the ‘B2. Trajectory Analysis (for Cryptic Pockets): Cluster Conformations’. The dataset contains MD features and atomic coordinates of cluster medoids.

  • Required

  • Type: data_source

Outputs

Ranked Pockets (pockets_data_out): This dataset saves information pertaining to each pocket including pocket residues, COM distance from functionally important site, and other pocket characteristics.

  • Required

  • Type: dataset_out

  • Default: Ranked Pockets - Cooperative Cosolvent Binding Analysis

MSM Weighted Medoids (msm_weights_data_out): Output dataset containing the cluster medoids and equilibrium populations of clusters derived from Markov state estimation.

  • Required

  • Type: dataset_out

  • Default: MSM Weighted Medoids - Cooperative Cosolvent Binding Analysis

Failure Output Dataset (failure_data_out): Failure output dataset to write to.

  • Required

  • Type: dataset_out

  • Default: Failure - Cooperative Cosolvent Binding Analysis

Floe Report Output Collection (floe_report_out):

  • Required

  • Type: string

  • Default: Floe Report - Cooperative Cosolvent Binding Analysis

Cooperative Cosolvent Binding Analysis Inputs

Important Residues (select_string_key_resids): String for selecting functionally important residues e.g. active site residues or a known disease mutation. Distance between center of mass (COM) of selected residues and COM of pocket residues will be computed as a pocket ranking parameter. Residues should be specified in <residue number><chain id> format. For example, active site consisting of residues 11, 12 (chain A) and residues 23 (chain B) should be specified as 11A, 12A, 23B.. Residue numbers and chain IDs should match those given in the pdb file generated by ‘A1. Protein Sampling (for Cryptic Pockets): Solvate and Equilibrate Target Protein’ Floe.

  • Required

  • Type: string

Pocket Ranking Parameter (pocket_ranking_metric): Metric used for ranking the pockets. ‘Key distances’ ranks the pocket by center of mass distance between functionally important residue(s) and pocket residues in ascending order. ‘Intra-pocket cooperativity’ ranks the pockets by average strength of cooperativity between pocket residues.

  • Required

  • Type: string

  • Default: Key distances

  • Choices: [‘Key distances’, ‘Intra-pocket cooperativity’]

Maximum Cosolvent-Residue Binding Distance (threshold): Threshold (in Å) used for binary classification of co-solvent bound state of residues for computing mutual information. If residue-cosolvent minimum distance is less than the threshold, the residue will be classified as co-solvent bound (1). Otherwise, the residue will be classified as unbound (0). Default value is preferred for the cryptic pocket analysis.

  • Type: decimal

  • Default: 5