Welcome to the AtlasCBS server!
AtlasCBS is a tool that allows you to explore chemico-biological space using Ligand Efficiency Indices (LEIs) as variables. This unique set of variables permits a graphical representation of the content of databases that contain affinity data (SAR databases such as PDBBind, BindingDB) in an atlas-like fashion. The server allows you see the content of the database(s) of choice as pages in a map-like environment with different variables and scales. The content of the databases is displayed in two-dimensional pages where the angular coordinate is related to the chemical composition of the ligand(s) and the radial coordinate is related to affinity of the ligand(s) towards the specific target(s). Details can be found in the specific publications.
The purpose of this server is to help you navigate in Chemico-Biological Space (CBS) so that you can examine the affinity and polarity of the chemical matter available for certain target(s) and possibly compare against what your own laboratory can produce, or what your competitors are designing. This comparison can be extremely useful and can allow you to design strategies to optimize your drug-discovery projects in your academic or private research.
Currently, available databases include BindingDB, PDBBind v2011, ChEMBL 13 and private user uploaded databases. In order to use your own the private databases you have to register here
Some additional references can be found below.
- Abad-Zapatero, C.; Blasi, D.Ligand Efficiency Indices (LEI): More than a Simple Efficiency Yardstick (2011). Molecular Informatics. 30 (2-3), 122-132.
- Christmann-Franck, S.; Cravo, D.; Abad-Zapatero, C.;Time-Trajectories in Efficiency Maps as Effective Guides for Drug Discovery Efforts (2011). Molecular Informatics. 30 (2-3), 137-144.
- Blasi, D.; Arsequell, G.; Valencia, G.; Nieto, J.; Planas, A.; Pinto, M.; Centero, N. B.; Abad-Zapatero, C.; Quintana, J.;Retrospective Mapping of SAR Data for TTR Protein in Chemico-Biological Space Using Ligand Efficiency Indices as a Guide to Drug Discovery Strategies (2011). Molecular Informatics. 30 (2-3), 161-167.