Introduction
description
Transcript of Introduction
Design of high-content and focused libraries to improveDesign of high-content and focused libraries to improvethe development of new active compounds the development of new active compounds
in the framework of the rational drug discoveryin the framework of the rational drug discoveryNicolas Foata, Esther Kellenberger, Mireille Krier, Pascal Muller, Claire Schalon, Jean-Sébastien Surgand, Guillaume Bret and Didier Rognan
CNRS UMR 7175 – LC1 Bioinformatics of the drugF-67400 ILLKIRCH-GRAFFENSTADEN, FRANCE
[email protected]: +33 (0)3-90-24-42-24
Introduction
Abbréviations: #HBA, number of H-bond acceptors; #HBD, number of H-bond donors; aa, aminoacid ; MW, molecular weight; PDB, Protein Data Bank; PSA, polar surface area ; TM, transmembran.
Websites: scPDB http://bioinfo-pharma.u-strasbg.fr/scPDB ; hGPCR-lig http://bioinfo-pharma.u-strasbg.fr/hGPCR-lig
Références:
[1] Kellenberger, E., Muller, P., Schalon, C., Bret, G., Foata, N. and Rognan, D. (2006). sc-PDB: an Annotated Database of Druggable Binding Sites from the Protein Data Bank J. chem. Inf. Model. 46, 717-727.
[2] Surgand, J.-S.; Rodrigo, J.; Kellenberger, E. and Rognan, D. (2006). A chemogenomic analysis of the transmembrane binding cavity of the human G-protein-coupled receptors. PROTEINS: Struct., Funct., and Bioinf., 62(2): 509-538
[3] Paul, N.; Kellenberger, E.; Bret, G.; Muller, P. and Rognan, D. (2004). Recovering the true targets of selective ligands by virtual screening of the Protein Data Bank.Proteins 54, 671-680.
Bioinfo
Filtration of the entries
Nowadays, new communication and information technologies give access to an important quantity of specific data.
However, in chemoinformatics, such data are often too generic, focused on a single application field and not suited to a
precise problem. Consequently, we generated and conceived several databases allowing the crossing of miscellaneous
information. The first one called “Bioinfo”, is a library of 1.8 million commercially available drug-like compounds that can
be use in the framework of the in silico screening.
Databases
hGPCR - lig
Conclusion
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1. Goal - Objective
4. Applications
2. Data presentation
3. Use
1. Goal - Objective
2. Data presentation
Library setting up of commercially available drug-like compounds. Bank of 3-D human G-Protein Coupled Receptor models and their known ligands.
3. Use
sc - PDB1. Goal - Objective
2. Data presentation
3. Use
4. Applications
+ / -
Suppliers
Compilation – Cleaning (PipeLine Pilot)
Filtration (Evaluator)
Ionisation (OpenEye)
4. Applications
Calculation
The second one named "screening-Protein Data Bank" (sc-PDB) is a collection of 6415 druggable binding sites from
proteins whose x-ray structure has been deposited in the Protein Data Bank (PDB). The last one, “human G-Protein
Coupled Receptors & ligands” (hGPCR-lig), is a collection of human GPCR (369) and their ligands (17908), also
classified according to the diversity of receptor binding sites and their ligands, respectively.
1 .. 23
Receptors Ligands
369 human GPCRs
Classification based on 30 main
aminoacids of TM cavities
17908 ligandsin 2-D
Scaffold-based classification
based
Collection of druggable protein binding sites.
All data
Filtering andanalysis
Ligand, active site, protein files
2-D catalogues
MW, logP, PSA, #HBA, #HBD …
More 160 rules : - Drug likeness (Lipinski rule of 5) - Rotatable bond number - Reactive and fluorescent groups …
3-D conversion or/and database
- To quantify identity and similarity of hGPCR transmembrane domains.- To quantify the structural similarity between of hGPCR active sites. - To assist library design by selection of user-defined scaffolds with annotated biological properties.
- Quantify the similarity of active sites ... - Screening and reverse screening, docking
Ste
ps
[2]
[1]
- to increase the fields of investigations of ligands or scaffolds by decreasing skews. - and to improve and accelerate the search of new « hits », and « leads » at lower costs.
Design of high-content libraries with miscellaneous structures such as classifications, proteins, ligands makes it possible: - to highlight some hidden relations and correlations, - to build models more adapted to find new active compounds,
Selection of drug-like compounds by topological, pharmacophoric properties.
6, 415 active sites
1, 706 non redondantproteins
2, 721 non redondantligands