Epilepsy Research – Identification of novel drug-targets, using tools of data science

• Epilepsy, a common neurological disease affecting nearly 50 million people across the world.  Approximately 10 million people in India. 30% of patients are resistant to the known Anti-Epileptic Drugs (AEDs) There is a need to discover new drugs and drug targets for Epilepsy and to reduce the cost and time for drug discovery computational methods are used.
• In this project, machine learning classifier models are built in-house to identify druggable proteins. A comprehensive Epilepsy database consisting of data related to Anti-epileptic drugs and related gene and drug target information is populated. A platform named TREADS  was developed to access in-house developed Machine learning models and Epilepsy Database.

Salient Features

• Search using a Gene Name, Uniprot identifier or the Ensemble Identifier
• Browse – AEDs, AED targets, known Epilepsy-associated genes, epileptic syndromes, and microRNA targets, Epilepsy-associated pathways and protein families.
• Predict potential druggable proteins using machine learning models.
• Epilepsy related PubMed literature is displayed for the proteins of interest.