UniBind: a novel artificial intelligence-based prediction model for SARS-CoV-2 infectivity and variant evolution
Qihong Yan, Jincun Zhao
Abstract
In a recent study published in Nature Medicine , Wang et al. developed an excellent framework called UniBind based on artificial intelligence (AI), which enables accurately predicting infectivity of SARS-CoV-2 variants and evolutionary trends of future viral variants. 1 This computational method holds the possibility to not only serve as a valuable early-warning tool for monitoring potential pathogenic SARS-CoV-2 variants but also facilitate fundamental research on protein-protein interactions (PPIs).
Topics & Concepts
InfectivitySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakCoronavirus disease 2019 (COVID-19)Sars virusComputational biologyVirologyBiologyMedicineVirusPathologyOutbreakInfectious disease (medical specialty)DiseaseSARS-CoV-2 and COVID-19 ResearchCOVID-19 diagnosis using AICOVID-19 epidemiological studies