Estimating the Binding of Sars-CoV-2 Peptides to HLA Class I in Human Subpopulations Using Artificial Neural Networks.

Journal: Cell systems
Published Date: Oct 21, 2020

Abstract

Epidemiological studies show that SARS-CoV-2 infection leads to severe symptoms only in a fraction of patients, but the determinants of individual susceptibility to the virus are still unknown. The major histocompatibility complex (MHC) class I exposes viral peptides in all nucleated cells and is involved in the susceptibility to many human diseases. Here, we use artificial neural networks to analyze the binding of SARS-CoV-2 peptides with polymorphic human MHC class I molecules. In this way, we identify two sets of haplotypes present in specific human populations: the first displays weak binding with SARS-CoV-2 peptides, while the second shows strong binding and T cell propensity. Our work offers a useful support to identify the individual susceptibility to COVID-19 and illustrates a mechanism underlying variations in the immune response to SARS-CoV-2. A record of this paper's transparent peer review process is included in the Supplemental Information.

Authors

  • Caterina A M La Porta
    Center for Complexity and Biosystems, University of Milan, via Celoria 16, 20133 Milano, Italy; Department of Environmental Science and Policy, University of Milan, via Celoria 26, 20133 Milano, Italy. Electronic address: caterina.laporta@unimi.it.
  • Stefano Zapperi
    Center for Complexity and Biosystems, University of Milan, via Celoria 16, 20133 Milano, Italy; Department of Physics, University of Milan, via Celoria 16, 20133 Milano, Italy; CNR - Consiglio Nazionale delle Ricerche, ICMATE, Via R. Cozzi 53, 20125 Milano, Italy.

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