In an effort to better understand the immunological underpinnings of COVID-19, we performed a PPi network analysis, a scRNA-seq data analysis, and artificial neural networks to reveal potential therapeutic targets for drug repurposing. Gordon et al. identified 332 human proteins physically associated with 26 of the 29 SARS-CoV-2 proteins, using affinity-purification mass spectrometry . Consequently, we performed a PPi network between immune system proteins and human proteins physically associated to SARS-CoV-2. The protein with the highest degree centrality was UBA52, followed by GNB1, APP, FPR2, NCBP1, NCBP2, KNG1, PIK3CA, PIK3R1, and MAPK1 (Supplementary Figure and Supplementary Table ). UBA52 encodes a fusion protein that regulates ubiquitination of ribosome, and UBA52-deficient cells display decreased cell cycle arrest and protein synthesis 110 . On the other hand, human proteins physically associated with SARS-CoV-2 proteins and with the highest degree centrality in our network were GNB1, RPL36, PABPC1, GNG5, UPF1, SRP54, SRP19, SRP72, EIF4H, and EXOSC8 (Figure ). GNB1 encodes a protein that acts as a modulator in transmembrane signaling systems, including the GTPase activity .