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Estimating the Binding of Sars-CoV-2 Peptides to HLA Class I in Human Subpopulations Using Artificial Neural Networks.
La Porta, Caterina A M; Zapperi, Stefano.
  • La Porta CAM; Center for Complexity and Biosystems, Department of Environmental Science and Policy, University of Milan, via Celoria 26, Milano 20133, Italy; CNR - Consiglio Nazionale delle Ricerche, Istituto di Biofisica, via Celoria 26, Milano 20133, Italy. Electronic address: caterina.laporta@unimi.it.
  • Zapperi S; Center for Complexity and Biosystems, Department of Physics, University of Milan, via Celoria 16, Milano 20133, Italy; CNR - Consiglio Nazionale delle Ricerche, Istituto di Chimica della Materia Condensata e di Tecnologie per l'Energia, via R. Cozzi 53, Milano 20125, Italy.
Cell Syst ; 11(4): 412-417.e2, 2020 10 21.
Article in English | MEDLINE | ID: covidwho-753813
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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Peptides / Polymorphism, Genetic / Viral Proteins / Histocompatibility Antigens Class I / Neural Networks, Computer / Betacoronavirus Type of study: Observational study Limits: Humans Language: English Journal: Cell Syst Year: 2020 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Peptides / Polymorphism, Genetic / Viral Proteins / Histocompatibility Antigens Class I / Neural Networks, Computer / Betacoronavirus Type of study: Observational study Limits: Humans Language: English Journal: Cell Syst Year: 2020 Document Type: Article