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