Predicting the Evolution of SARS-CoV-2: New Software Developed Also by Politecnico di Milano
An innovative software based on the phenomenon of convergent evolution makes it possible to predict in advance the evolution of SARS-CoV-2 and to support the selection of the most suitable variants for updating vaccines and monoclonal antibodies. It is called ConvMut, and it was developed by a group of researchers from the Pisan University Hospital (Aoup), Politecnico di Milano, and the INMI “Lazzaro Spallanzani” IRCCS in Rome.
ConvMut is now available on the international platform of the GISAID Data Science Initiative, where it leverages more than 17 million viral sequences shared by laboratories worldwide to analyze the virus’s convergent mutations in real time.
The software originates from an idea by Daniele Focosi, hematologist and virologist at Aoup, developed together with the teams led by Fabrizio Maggi (INMI Spallanzani) and Anna Bernasconi, tenure-track researcher in the Department of Electronics, Information and Bioengineering at Politecnico di Milano.
Although the pandemic now represents a challenge primarily for immunocompromised patients, SARS-CoV-2 continues to evolve rapidly, making timely vaccine updates difficult. ConvMut makes it possible to predict months in advance which mutations of the Spike protein are likely to become dominant, offering policymakers and pharmaceutical companies a valuable tool to improve the precision of future vaccine strategies.
The software, described in the bioRxiv preprint, automatically compiles convergent evolution charts, which until now had to be manually curated. It groups lineages by sets of mutations they share - almost always acquired incrementally - and provides near real-time information on the number of deposited sequences.
Anna Bernasconi, tenure-track researcher in the Department of Electronics, Information and Bioengineering