Guwahati: In a breakthrough that could significantly speed up the search for treatments against the deadly Nipah virus, Grade XII student Vihaan Agrawal has developed a sophisticated multi-stage computational pipeline to identify promising drug candidates with greater accuracy and efficiency. The Nipah virus remains a recurring public health emergency in India, but traditional drug discovery methods are slow, expensive, and prone to failure due to the need for physical testing of thousands of compounds. Addressing this challenge, Vihaan designed an advanced computational system that goes beyond conventional virtual screening methods.
Unlike typical models that treat viral proteins as rigid structures, Vihaan’s pipeline considers the virus protein as a flexible and dynamic target, allowing for more realistic and accurate predictions. To ensure scientific reliability, he rigorously tested the system using “decoys”—fake drug candidates—to confirm that the model could statistically differentiate genuine therapeutic hits from random noise. The outcome is a prioritised and validated list of small-molecule compounds that are ready for in vitro laboratory trials. This enables national research bodies such as the Indian Council of Medical Research (ICMR) to bypass early-stage guesswork and focus directly on the most promising candidates.
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Highlighting the project’s significance, Ashi Gupta, former Boston-based researcher at Sanofi, remarked that the work stands out for its methodological rigor and delivers drug candidates that genuinely merit serious experimental evaluation. Vihaan’s innovation underscores the growing role of young minds and computational science in tackling critical public health challenges.
