CMS College Researchers Develop a Ground Breaking Computational Framework to Predict Future Pandemics
Researchers at CMS College Kottayam have developed an innovative computational framework that could help identify dangerous viruses before they trigger future pandemics. The study, recently published in the prestigious journal Nature Scientific Reports, introduces a new system called SPHAK (Sequence-based Prediction of Host Spillover by Analysis of k-mers), designed to predict whether viruses may jump from animals or plants to new hosts.
The research gains particular importance at a time when the world continues to witness emerging viral threats such as COVID-19, Nipah, Mpox, Influenza variants, and the recent Hantavirus outbreak aboard the MV Hondius cruise ship. These incidents highlight the growing danger of “host spillover,” where viruses cross from their natural hosts into humans or other species.
Unlike traditional approaches that rely mainly on full viral genomes, SPHAK focuses on viral proteins, which act as molecular “keys” enabling viruses to infect host cells. By analysing short amino-acid patterns known as k-mers, the framework can detect subtle evolutionary changes that indicate a virus may be adapting to a new host species. The system then generates a Spillover Prediction (SP) score to estimate the likelihood of cross-species transmission.
In a significant global first, the CMS College team also extended the computational approach to plant viruses, aiming to prevent future “plant pandemics” that threaten food security. The framework demonstrated strong performance in identifying high-risk plant viruses, potentially enabling faster intervention to protect crops such as rice and legumes.
The multidisciplinary research was led by Dr. Vibin Ipe Thomas, Assistant Professor of Chemistry and Dean of Academics at CMS College Kottayam, along with Prisho Mariam Paul, Assistant Professor of Biotechnology, and student researchers Vinny N. G., Ananya Prakash, S. Kavya, and C. Rajalakshmi.
By developing a fast, scalable, and cost-effective early warning system capable of working even with incomplete viral samples, the CMS College research team has contributed an important technological advancement toward strengthening global health surveillance and food security preparedness.
