BrainProt v3.0 is a database that combines various types of biological data. Anna Shvets/Pexels
Medicine

IIT Bombay Launches Smart AI Platforms to Help Decode Brain Diseases and Drug Targets

It is the first system to integrate multi-disease data from genomics, transcriptomics, proteomics, and biomarker research and multi-database information into one portal.

Author : MBT Desk

New Delhi, January 2026: A team of bioengineers at the Indian Institute of Technology (IIT) Bombay has developed new smart platforms --BrainProt and DrugProtAI -- that unify data on scattered brain diseases to help researchers find markers, explore treatments, and pinpoint druggable targets.

BrainProt v3.0 is a database that combines various types of biological data -- from genes to proteins -- into a single platform to enable systematic insights into human brain function in both healthy and diseased states.

It is the first system to integrate multi-disease data from genomics, transcriptomics, proteomics, and biomarker research and multi-database information into one portal.

“BrainProt also includes resources to identify and understand protein expression differences between the left and right hemispheres of the human brain across 20 neuroanatomical regions. This is the first resource of its kind,” said Prof. Sanjeeva Srivastava from the Department of Biosciences and Bioengineering, IIT Bombay.

BrainProt includes data on 56 human brain diseases and 52 multi-omics datasets derived from more than 1,800 patient samples. These datasets include transcriptomic data for 11 diseases and proteomic data for six diseases.

For each disease, users can examine genes and proteins frequently associated with the disease, assess how strongly these genes and proteins are already supported by existing medical and scientific databases, and how their activity levels change in patient samples.

DrugProtAI was developed to understand whether a protein can be druggable (has the biological and physical characteristics needed to be a useful drug target) before doing costly experiments.

This is crucial because only about 10 per cent of human proteins currently have an FDA-approved drug, with another 3-4 per cent under investigation.

“Before investing years of work in a protein target, DrugProtAI predicts whether the protein is druggable by looking beyond the protein’s sequence, such as cellular location, structural attributes, and other unique characteristics it has,” said Dr. Ankit Halder, co-author of the study.

The tool generates a “druggability index” -- a probability score indicating how likely a protein is to be druggable. A higher score suggests that the protein shares many properties with proteins that already have approved drugs, while a lower score indicates that drug development would be more challenging.

“By integrating DrugProtAI directly into BrainProt, we created a pipeline where researchers can move from identifying a disease marker to examining its expression patterns to evaluating its druggability and exploring existing compounds or clinical trials, all within an hour,” Halder said.

This news was originally published on NewsGram.

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