A deep learning approach predicting the activity of COVID-19 therapeutics and vaccines against emerging variants.

Journal: NPJ systems biology and applications
PMID: 39604453

Abstract

Understanding which viral variants evade neutralization is crucial for improving antibody-based treatments, especially with rapidly evolving viruses like SARS-CoV-2. Yet, conventional assays are labor intensive and cannot capture the full spectrum of variants. We present a deep learning approach to predict changes in neutralizing antibody activity of COVID-19 therapeutics and vaccine-elicited sera/plasma against emerging viral variants. Our approach leverages data of 67,885 unique SARS-CoV-2 Spike sequences and 7,069 in vitro assays. The resulting model accurately predicted fold changes in neutralizing activity (R = 0.77) for a test set (N = 980) of data collected up to eight months after the training data. Next, the model was used to predict changes in activity of current therapeutic and vaccine-induced antibodies against emerging SARS-CoV-2 lineages. Consistent with other work, we found significantly reduced activity against newer XBB descendants, notably EG.5, FL.1.5.1, and XBB.1.16; primarily attributed to the F456L spike mutation.

Authors

  • Robert P Matson
    nference, Cambridge, MA, 02139, USA.
  • Isin Y Comba
    nference, Cambridge, MA, 02139, USA.
  • Eli Silvert
    nference, Cambridge, MA.
  • Michiel J M Niesen
    nference, Cambridge, MA, 02139, USA. mniesen@nference.net.
  • Karthik Murugadoss
    nference, Cambridge, MA, 02139, USA.
  • Dhruti Patwardhan
    nference Labs, Bengaluru, Karnataka, 560017, India.
  • Rohit Suratekar
    nference Labs, Bengaluru, Karnataka, 560017, India.
  • Elizabeth-Grace Goel
    nference, Cambridge, MA, 02139, USA.
  • Brittany J Poelaert
    Division of Preclinical Innovation, National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Rockville, MD, USA.
  • Kanny K Wan
    Division of Preclinical Innovation, National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Rockville, MD, USA.
  • Kyle R Brimacombe
    Division of Preclinical Innovation, National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Rockville, MD, USA.
  • A J Venkatakrishnan
    nference, One Main Street, Cambridge, MA 02142, USA.
  • Venky Soundararajan
    nference, One Main Street, Cambridge, MA 02142, USA.

Keywords

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