Researchers at Amity University, Noida and Baylor College of Medicine, Houston, have created an AI platform to find clinically important vaccine targets to transform the vaccine discovery process for infectious diseases.
Researchers at Amity University, Noida and Baylor College of Medicine (BCM-Houston, USA) have developed a powerful AI platform that can detect clinically important vaccine targets and epitopes that could lead to vaccine mutations in deadly infectious diseases such as COVID19 and Chagas disease. . The results of the study were published in the UK-based journal Scientific Reports and PubMed, entitled 'Pathogen Vaccine Target Identification and Design of a Vaccine Using Computational Methods' by Dr. Kamal Rawal, Scientist, Associate Professor and Project Director, Amity Inc. Biotechnology, Amity University, Dr. Peter Hotage (Dean, National School of Tropical Medicine, Baylor College of Medicine), Dr. Maria Elena Botazzi (Co-Dean, National School of Tropical Medicine, BCM), and Dr. Ulrich Streich (Associate Professor, BCM) as Senior Co-Writer.
Infectious diseases kill millions of people worldwide each year. Despite this fact, the vaccine is an effective way to control infectious diseases - the rapid emergence of a highly pathogenic, easily transmissible coronavirus has led to a global epidemic. This catastrophe has exposed our shortcomings in creating a safe and effective vaccine in the shortest possible time.
A joint team of Indian and US scientists today announced the successful development of an artificial intelligence-driven platform that could accelerate the development of vaccines, tested on 40 different pathogens, including the deadly SARS-CoV-2 (COVID-19), Mycobacterium tuberculosis. (TB), Vibro Cholera (Cholera) and Plasmodium falciparum (Malaria).
According to Dr. Rawal, "The key innovation is to combine thousands of proteins and genes using artificial intelligence to combine hundreds of parameters to achieve the right goal and to design vaccines using these proteins." As evidence, researchers have tested this platform on vaccine targets that have been experimentally known, including vaccines on the market. The team of researchers has a long-standing interest in the neglected disease of poverty. The team of researchers has a long-standing interest in the neglected disease of poverty, so they chose to analyze the entire genome and proteome (set of all protein sequences in the cell) of an important pathogen known as Trypanosoma cruciate (T. crucii).
To help other biologists and experimenters working in immunology and vaccines, Dr. Rawal has created a cloud-based server that researchers around the world can use to analyze their proteins and genes as potential vaccine targets. In the wake of the Delta variant of COVID19, the team has partnered with various pharmaceutical and biotechnology companies to create customized deployments for commercial-scale applications to create new vaccines against emerging infectious diseases.
To test the AI system, the team shortlisted more than 335 experimentally verified antigens from 40 different pathogens and found that the system accurately predicted most of them with reasonable accuracy levels. These examples also include targets for FDA approved / marketed vaccines which make a strong case for this platform. Before entering the clinical trial, rats were injected into rats with the help of these computer-recommended vaccines, to show that the vaccines designed were non-toxic and sufficiently immunogenic (producing sufficient antibodies). "Right now, it's too early to say how this work will affect patients down the line, but preliminary data suggest the platform will be useful in a variety of ways," Dr. Ulrich Streich added.
According to Dr. Hotz, we first selected 8 important proteins from a set of 19000 proteins and then from these targets we identified the top epitope (part of an antigen molecule that attaches itself to an antibody). "Subsequently, we designed a multi-epitop vaccine against CD, followed by sophisticated analysis using the Bioinformatics tool to determine if the proposed vaccine was able to activate the immune system."
"An ideal vaccine should not be similar to the host protein (human) to avoid targeted cross-effects and subsequent side effects, so special care was taken to filter such data during the study," said Dr. Maria Elena Botaji.
The study was supported by the Kleberg Foundation, USA and the Baylor College of Medicine, USA.