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Interested in improving your binding mode predictions? Surflex-Dock is a unique method for molecular docking, offering automatic pipelines for ensemble docking, applicable to both small molecules and large peptidic macrocycles alike.
Watch Drs Ajay Jain and Ann Cleves, experts in structure-based design, to explore the key features of Surflex-Dock, including scoring function, search methodology, and integration with molecular similarity approaches.
You’ll learn:
Surflex-Dock is a unique method for molecular docking, offering automatic pipelines for ensemble docking from PDB codes through clustering of final predicted ligand poses and ranking the resulting pose families with the benefit of prior knowledge.
We will describe the key differentiating features of the Surflex-Dock approach including its novel scoring function, search methodology, and integration with similarity approaches.
Local protein pocket similarity is used for alignment and clustering of protein binding pockets, and the eSim ligand similarity method is used for exploiting knowledge of experimentally determined ligand poses. Benchmarking results will be presented for two challenging scenarios:
The Surflex-Dock pipeline has been implemented in a PyMol GUI, which will be demonstrated with PDB codes and a SMILES-format ligand as input. The automated processes of complex preparation, alignment, selection, and preparation for docking will be shown, along with examples of docking that include the use of prior known ligand binding modes.
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