DockingPie

DockingPie performs consensus and individual protein–ligand docking analyses within the PyMOL environment to predict binding modes for virtual screening and computer-aided drug discovery.

Key Features:

• Integration with PyMOL: Operates as a plugin within the PyMOL molecular graphics environment to run docking analyses inside that computational context.
• Support for Multiple Docking Engines: Interfaces with Smina, AutoDock Vina, ADFR, and RxDock to leverage different docking algorithms and scoring functions.
• Consensus Docking Capabilities: Aggregates results from multiple docking engines to generate consensus predictions of binding modes.
• Protein–ligand Binding Mode Prediction: Performs protein–ligand docking to predict probable ligand binding configurations within target receptors.
• Virtual Screening Support: Enables virtual screening workflows by producing and combining docking results to prioritize candidate small molecules.

Scientific Applications:

• Computer-aided drug discovery: Predicts small-molecule interactions with biological targets to support early-stage drug development.
• Virtual screening and hit identification: Ranks and prioritizes candidate ligands from screening libraries based on predicted binding modes.
• Robustness evaluation of docking predictions: Uses consensus docking to increase confidence and reduce variability across docking algorithms.

Methodology:

Performs protein–ligand docking using multiple engines (Smina, AutoDock Vina, ADFR, RxDock) and integrates their results via consensus docking techniques to identify the most probable ligand binding configurations.