Machine learning methods accurately predict host specificity of coronaviruses based on spike sequences alone.

ABSTRACT: Coronaviruses infect many animals, including humans, due to interspecies transmission. Three of the known human coronaviruses: MERS, SARS-CoV-1, and SARS-CoV-2, the pathogen for the COVID-19 pandemic, cause severe disease. Improved methods to predict host specificity of coronaviruses will be valuable for identifying and controlling future outbreaks. The coronavirus S protein plays a key role in host specificity by attaching the virus to receptors on the cell membrane. We analyzed 1238 spike sequences for their host specificity. Spike sequences readily segregate in t-SNE embeddings into clusters of similar hosts and/or virus species. Machine learning with SVM, Logistic Regression, Decision Tree, Random Forest gave high average accuracies, F₁ scores, sensitivities and specificitie

SUBMITTER: Kuzmin K 

PROVIDER: S-EPMC7500881 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature