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S2RSLDB: a comprehensive manually curated, internet-accessible database of the sigma-2 receptor selective ligands.

Authors :
Nastasi, Giovanni
Miceli, Carla
Pittalà, Valeria
Modica, Maria
Prezzavento, Orazio
Romeo, Giuseppe
Rescifina, Antonio
Marrazzo, Agostino
Amata, Emanuele
Source :
Journal of Cheminformatics. 1/21/2017, Vol. 9 Issue 1, p1-9. 9p.
Publication Year :
2017

Abstract

Background: Sigma (σ) receptors are accepted as a particular receptor class consisting of two subtypes: sigma-1 (σ) and sigma-2 (σ). The two receptor subtypes have specific drug actions, pharmacological profiles and molecular characteristics. The σ receptor is overexpressed in several tumor cell lines, and its ligands are currently under investigation for their role in tumor diagnosis and treatment. The σ receptor structure has not been disclosed, and researchers rely on σ receptor radioligand binding assay to understand the receptor's pharmacological behavior and design new lead compounds. Description: Here we present the sigma-2 Receptor Selective Ligands Database (S2RSLDB) a manually curated database of the σ receptor selective ligands containing more than 650 compounds. The database is built with chemical structure information, radioligand binding affinity data, computed physicochemical properties, and experimental radioligand binding procedures. The S2RSLDB is freely available online without account login and having a powerful search engine the user may build complex queries, sort tabulated results, generate color coded 2D and 3D graphs and download the data for additional screening. Conclusion: The collection here reported is extremely useful for the development of new ligands endowed of σ receptor affinity, selectivity, and appropriate physicochemical properties. The database will be updated yearly and in the near future, an online submission form will be available to help with keeping the database widely spread in the research community and continually updated. The database is available at . Graphical abstract: [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17582946
Volume :
9
Issue :
1
Database :
Academic Search Index
Journal :
Journal of Cheminformatics
Publication Type :
Academic Journal
Accession number :
120843106
Full Text :
https://doi.org/10.1186/s13321-017-0191-5