Stage M1S2 (2018-2019)

The performance of structure-based computing methods used in drug discovery is generally assessed by benchmarking, i.e., running the program through a series of well-defined tests to detect defect prediction. Many test sets have been proposed. For exemple the Astex dataset, which contains 85 3D-structures of ligand-protein complexes, has been widely used to compare docking tools. [1] We have also contributed to this field by systematically analysing the Protein Databank to extract ligandable protein site in complex with a drug-like ligand [2] or a fragment [3].
The project consists in the design and the test of several benchmarking datasets to evaluate the following tasks: ligand pose prediction (docking, pharmacophore), detection of intermolecular interactions, and detection, description, and comparison of cavities.
The candidate must show a strong interest in protein structure analysis. A well-structured and well-organised way of working is required to conduct the project. Basic programming skills in Linux environment are desirable.

[1] Diverse, High-Quality Test Set for the Validation of Protein−Ligand Docking Performance (2007) Michael J. Hartshorn, Marcel L. Verdonk*, Gianni Chessari, Suzanne C. Brewerton, Wijnand T. M. Mooij, Paul N. Mortenson, and Christopher W. Murray. J. Med. Chem. 50:726–741.
[2] sc-PDB: a 3D-database of ligandable binding sites--10 years on. (2015)Desaphy J, Bret G, Rognan D, Kellenberger E. Nucleic Acids Res. 43(Database issue):D399-404.
[3] Structural Insights on Fragment Binding Mode Conservation. (2018) Drwal MN, Bret G, Perez C, Jacquemard C, Desaphy J, Kellenberger E. J Med Chem. 61:5963-5973.