Institute of Microbial Technology (सूक्ष्मजीव प्रौद्योगिकी संस्थान)
A Council of Scientific & Industrial Research (वैज्ञानिक औद्योगिक अनुसंधान परिषद)
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  About ONRLDB  
  Over the years orphans and adopted orphans have emerged as the most attractive drug targets mainly 1) because of their implication in considerably large number of human diseases, such as cancer, obesity, diabetes, infectious diseases, etc. 2) the lipophilic nature of their ligands with abilities to cross over the cellular membranes 3) and crucial link they provide between signaling pathways and transcriptional regulation. The advancement in cell-culture based methods for testing large number of compounds has lead to the identification of overwhelming number of newer synthetic ligands for orphan and adopted orphan receptors. In Orphan Nuclear Receptor Ligand Binding Database (ONRLBD), we collected and combined all information about endogenous, heterogenous and synthetic ligands available for orphan and adopted orphans in scientific literature. We have incorporated structure based similarity search as well as substructure search to effectively navigate various small molecules targeting different nuclear receptors. In addition, we have also provided Chemmine tool (http://chemmine.ucr.edu/) so that a user can perform various physiochemical property based clustering analysis such as hierarchal binning and multidimensional clustering. Users can upload .sdf files or paste smiles to perform clustering analysis. Also for case of navigation, a tree based visual description of various nuclear receptor along with their number of ligands that target them have been provided. ONRLBD currently consists of approximately 12000 small molecules which are manually curated for ligands with proper experimental support however, we didn’t include information regarding those small molecules which are proved as ligands just by bioassays or by docking studies. We have provided ligand structure with all QSAR properties and aligning all quantitative binding measurements strictly from published experimental data only. Our database user interface is advanced, user friendly and provides interactive sessions between ligand vs target protein and will help user to identify cross reacting ligands and the best scaffold for a particular nuclear receptor.

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