Join us 14 November

8am PST | 11am EST | 4pm GMT | 5pm CET

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.

Join 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:

  • How we can automate complex preparation, alignment, selection, and preparation for docking, with a hands-on demonstration of Surflex-Dock in action addressing a variety of docking examples
  • How we can predict the binding modes of future ligands, using a temporal case study where target structures used for docking were determined prior to those of the ligands being docked
  • How Surflex-Dock can use non-macrocyclic complexes to predict the binding modes of macrocyclic ligands

Abstract:

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:

  1. predicting the binding modes of novel ligands whose experimental bound structures were determined long after the ensemble of complexes used for docking; and
  2. predicting the binding modes of macrocyclic ligands using structures limited to non-macrocyclic protein-ligand complexes.

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.