Small-molecule ligand docking into comparative models with Rosetta.

Area of Science:

• Computational Biology
• Structural Bioinformatics
• Drug Discovery

Background:

• Structure-based drug design accelerates therapeutic development.
• Experimental structure determination (X-ray crystallography, NMR) is limited for large/flexible proteins.
• Computational methods can predict structures and model ligand interactions in the absence of experimental data.

Purpose of the Study:

• To describe a comprehensive protocol for docking small-molecule ligands into comparative protein models using the Rosetta modeling suite.
• To provide a didactic example and tutorial for hands-on user experience with Rosetta.
• To outline strategies for improving ligand docking and assessing model quality.

Main Methods:

• Detailed protocol for comparative protein modeling, including sequence alignment, threading, and loop building.
• Ligand docking into comparative protein models using the Rosetta suite.
• Discussion of criteria for enhancing ligand docking accuracy and a strategy for model quality assessment.

Main Results:

• A complete protocol for structure-based drug design using Rosetta is presented.
• The protocol covers comparative modeling, ligand docking, and model evaluation.
• A tutorial is provided for practical application of the Rosetta modeling suite.

Conclusions:

• The Rosetta modeling suite offers a viable computational approach for structure-based drug design when experimental data are scarce.
• The presented protocol facilitates the modeling of ligand interactions with protein comparative models.
• This work provides a valuable resource for researchers seeking to utilize computational methods in drug discovery.