Learning the language of viral evolution and escape

Natural language predicts viral escape Viral mutations that evade neutralizing antibodies, an occurrence known as escape, can occur and may impede the development of vaccines. To predict which lead to Hie et al. used a machine learning technique for natural processing with two components: grammar (or syntax) meaning semantics) (see Perspective by Kim Przytycka). Three different unsupervised models were constructed influenza A hemagglutinin, HIV-1 envelope glycoprotein, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike glycoprotein. Semantic landscapes these viruses predicted produce sequences are syntactically and/or grammatically correct but effectively in semantics thus able immune system. Science , this issue p. 284 ; see also 233