Communications of the ACM
Predicting the Future of COVID
Boston College's Babak Momeni said having data on potential COVID-19 mutations "would help with readiness for detecting and preventing, as well as treating, emerging and future variants.”
Credit: maltonschool.org
A new analytical tool developed by a research team led by biologists at Boston College (BC) uses quantum mechanical modeling to predict future mutations of SARS-CoV-2.
BC's Babak Momeni said, "We computationally predict what mutations allow better binding to host receptors and better evasion of antibodies."
The goal is to prepare for future COVID variants of concern.
Said Momeni, "We use a fully quantum mechanical model to theoretically assess how different mutations in the spike [protein of the coronavirus] can contribute to its increased, or decreased, binding strength to human ACE2."
The study also found that factors other than binding may be involved in determining how a variant evolves.
From Boston College
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Abstracts Copyright © 2022 SmithBucklin, Washington, DC, USA
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