|日時||2012年10月25日（木) 15:00 - 16:30|
|場所||化学研究所 総合研究実験棟2階 CB207(化研へのアクセス)|
|講師||Didier ROGNAN氏(フランス国立科学研究センター 研究ディレクター)|
Fingerprinting protein cavities and protein-ligand complexes for drug design
The combinatorial explosion of bioactivity and structural data on
protein-ligand complexes of pharmaceutical interest enable the generation of
large matrices to better understand reasons for either fine
selectivity or polypharmacology.
We herewith present various 1-D fingerprints featuring either
druggable cavity attributes or protein-ligand complexes in various drug design scenarios:
-predict the structural druggability of any given pocket
-predict possible off-targets from binding site similarity calculations
-screen a ligand against 3600 targets to get a polypharmacology profile
-post-process docking poses by interaction fingerprint similarity
-compare interaction patterns across the Protein Data Bank to enable scaffold hopping
Receptor-Ligand Pharmacophores: A novel structure-based screening weapon
for ligand profiling and discovery of protein-protein interface inhibitors
We herewith present PharmaDB, a collection of 68,000 pharmacophores derived from 8,000 high resolution protein-ligand complexes from the sc-PDB dataset. A maximum of 10 pharmacophores (3-6 features) per complex are automatically derived from the simple inspection of receptor-ligand atomic coordinates, and further ranked by expected decreasing selectivity using a genetic function approximation.
In a first application, receptor-ligand pharmacophore search was compared to ligand-centric (2-D and 3-D similarity searches) and docking methods in profiling a set of 157 diverse ligands against a panel of 2,556 unique targets of known X-ray structure. As expected, ligand-based methods outperformed, in most of the cases, structure-based approaches in ranking the true targets among the top 1% scoring entries. However, we could identify ligands for which only a single method was successful. Receptor-ligand-based pharmacophore search is notably a very fast and reliable alternative to docking in which constraints are explicitly defined, and which generates high-quality poses.
In a second scenario, the method was applied (in parallel to docking) to screen a collection of 3 million commercially-available compounds for finding the very first inhibitors of two independent protein-protein interfaces (PPI). Strikingly, only protein-protein pharmacophore mapping was able to identify micromolar hits which were later confirmed by binding and functional assays. Although more prospective examples are required to derive general rules, protein-protein pharmacophore search appears a very promising and robust tool to find PPI inhibitors.