Introducing the Automated Ligand Searcher.

Area of Science:

• Computational chemistry
• Drug discovery
• Biophysics

Background:

• Automated computational drug discovery tools are essential for efficient pharmaceutical research.
• Accurate approximation of ligand-receptor binding free energy is critical for identifying effective drug candidates.
• Existing workflows can be time-consuming and require significant computational resources.

Purpose of the Study:

• To introduce the Automated Ligand Searcher (ALISE), a novel computational tool for drug discovery.
• To present a three-stage workflow within ALISE for approximating ligand-receptor binding free energy.
• To evaluate the performance and usability of ALISE using a case study.

Main Methods:

• ALISE employs a three-stage computational workflow: molecular docking, molecular dynamics, and free energy perturbation.
• The workflow progressively filters out poorly performing ligands.
• Benchmarking was conducted using known active ligands and decoys for the HIV protease.

Main Results:

• ALISE successfully filtered out decoys, distinguishing them from known active ligands.
• The software demonstrated effectiveness in identifying potential drug candidates.
• The case study validated the computational approach for ligand screening.

Conclusions:

• ALISE is a comprehensive, automated, and user-friendly software tool.
• The tool significantly improves and accelerates drug development workflows.
• ALISE represents a valuable advancement in computational drug discovery.