A group of bioengineers from the Indian Institute of Technology (IIT) Bombay have invented new intelligent systems, BrainProt and DrugProtAI, that integrate the information of scattered brain diseases to assist researchers in locating markers, analyzing treatments, and finding druggable targets. BrainProt v3.0 is a database that collects different types of biological information, from genes to proteins, and merges them in a single platform to allow getting insights into human brain activity in both the normal and pathological situations. The system is the first to combine the data of multiple diseases from genomics, transcriptomics, proteomics, and biomarker research, as well as multi, database information into a single 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.
