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Learning from prepandemic data to forecast viral escape
ISSN: 0028-0836 ;ISSN: 1476-4687 ;EISSN: 1476-4687 ;DOI: 10.1038/s41586-023-06617-0
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Title:
Learning from prepandemic data to forecast viral escape
Author:
Thadani, Nicole
;
Gurev, Sarah
;
Notin, Pascal
;
Youssef, Noor
;
Rollins, Nathan
;
Ritter, Daniel
;
Sander, Chris
;
Gal, Yarin
;
Marks, Debora
Subjects:
Multidisciplinary
Description:
Summary
Effective pandemic preparedness relies on anticipating viral mutations that are able to evade host immune responses in order to facilitate vaccine and therapeutic design. However, current strategies for viral evolution prediction are not available early in a pandemic – experimental approaches require host polyclonal antibodies to test against and existing computational methods draw heavily from current strain prevalence to make reliable predictions of variants of concern. To address this, we developed EVEscape, a generalizable, modular framework that combines fitness predictions from a deep learning model of historical sequences with biophysical structural information. EVEscape quantifies the viral escape potential of mutations at scale and has the advantage of being applicable before surveillance sequencing, experimental scans, or 3D structures of antibody complexes are available. We demonstrate that EVEscape, trained on sequences available prior to 2020, is as accurate as high-throughput experimental scans at anticipating pandemic variation for SARS-CoV-2 and is generalizable to other viruses including Influenza, HIV, and understudied viruses with pandemic potential such as Lassa and Nipah. We provide continually updated escape scores for all current strains of SARS-CoV-2 and predict likely additional mutations to forecast emerging strains as a tool for ongoing vaccine development (
evescape.org
).
Publisher:
Springer Science and Business Media LLC
Creation Date:
2023-10
Language:
English
Identifier:
ISSN: 0028-0836
ISSN: 1476-4687
EISSN: 1476-4687
DOI: 10.1038/s41586-023-06617-0
Source:
Harvard University Library DASH
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