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[ NetPro ] [ CliPro ] [ Receptome ] [ XTractor ]
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NetPro™
Is a comprehensive fully hand-curated knowledgebase of Protein-Protein, Protein-Small molecules DNA and RNA interactions, consisting of more than 200,000 interactions captured from approximately 1,400 published journals covering more than 31,000 references.
NetPro™ has received several accolades for the quality and quantity of data it contains. NetPro™ has become an important resource for target identification, validation and pathway research and has subscribers from all over the globe including 3 of the top 5 pharmas.
Some of the areas where data has been restructured to enhance search ability and analysis in the latest version are:
- Attributes of molecules in an interaction are now maintained as controlled vocabulary to facilitate ease of search.
- Experimental details like interaction location and experimental methods are more precisely classified now as 'Interaction specific' or as 'Supporting evidence'. Also to add here, any information on location / method that shows negative results pertaining to the interaction has also been annotated. This would benefit the user in better judgment of the outcome.
- Disease related information with respect to the molecule and the interaction itself has been enriched. Information on enhancement or decline of an interaction in a disease condition is also annotated, which is unique to NetPro™.
- Deciphering the final outcome of an interaction at the physiological level is made more streamlined with the introduction of fields like 'Interaction Process' which shows the resultant biological process that an interaction leads to; and 'Interaction product' where in, the details of the product generated in a biological system as a result of an interaction is available.
- Regulators are now tagged to identifiers to ease search ability.
Some recent developments:
- Regulation not only by molecules but also factors is now highlighted in NetPro™. Factors could vary from biological processes to environmental factors to pathological conditions, which are classified under various categories and maintained in a control vocabulary developed in-house.
- Apart from regulators influencing an interaction, bimolecular interactions in NetPro™ are now furnished with stimulant information where the stimulants are also tagged to identifiers to facilitate search option. This would not only help in pathway building but also to fill missing links in canonical and non-canonical pathways.
- For the first time ever, a bimolecular interaction database would provide qualitative difference in the potency of an interaction with respect to various conditions or factors. The data provides detailed information about the influencing factor which would be of great value to the user.
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Knowledgebase of Clinically Significant Proteins - CliPro™
Predicting possible Biomarkers for drug discovery.
CliPro™ is a comprehensive, easy to access knowledgebase of proteins in various biological fluids that reflects alterations between normal versus diseased conditions, manually mined from literature.
Currently includes a good repertoire of clinically significant proteins with their concentration values under various pathological states, with an emphasis on functional and diagnostic utility.
CliPro™ would serve as an effective platform to identify novel protein-disease associations and validate potential biomarker-disease associations.
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Receptome
A Database of Functional Ligand-Receptor Complexes
Human genome project has now afforded researchers the opportunity to identify novel receptor genes expressed in human tissues. The success in identification of as many new receptors provides a great opportunity for novel drug development today. However, unavailability of the right tools to identify ligands for these receptors has limited their utility for traditional drug discovery approaches that focus on ligand-based assay methods to discover and pharmacologically characterize drug candidates.
Receptome is a solution to this, a one-stop comprehensive knowledgebase that makes optimal use of this plethora of data and centralizes it as a searchable tool to investigate the characteristics of functional ligand-receptor pairs and their potential use and applications
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