Deciphering the interactions of SARS-CoV-2 proteins with human ion channels using machine learning-based method

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the worldwide COVID-19 pandemic which began in 2019. It has a high transmission rate and pathogenicity leading to health emergencies and economic crisis. Recent studies pertaining to the understanding of the molecular pathogenesis of SARS-CoV-2 infection exhibited the indispensable role of ion channels in viral infection inside the host. Moreover, machine learning (ML)-based algorithms are providing higher accuracy for host-SARS-CoV-2 protein-protein interactions (PPIs). In this study, predictions of PPIs of SARS-CoV-2 proteins with human ion channels (HICs) were performed using PPI-MetaGO algorithm. The PPIs were predicted with 82.71% accuracy, 84.09% precision, 84.09% sensitivity, 0.89 AUC-ROC, 65.17% Matthews correlation coefficient (MCC) score and 84.09% F1 score. Thereafter, PPI networks of SARSCoV-2 proteins with HICs were generated. Furthermore, biological pathway analysis of HICs interacting with SARS-CoV-2 proteins showed the involvement of six pathways, namely inflammatory mediator regulation of transient receptor potential (TRP) channels, insulin secretion, renin secretion, gap junction, taste transduction and apelin signaling pathway. Our analysis suggests that transient receptor potential cation channel subfamily M member 4 (TRPM4), transient receptor potential cation channel subfamily A member 1 (TRPA1), gap junction protein alpha 1 (GJA1), potassium calcium-activated channel subfamily N member 4 (KCNN4), acid sensing ion channel subunit 1 (ASIC1) and inositol 1,4,5-trisphosphate receptor type 1 (ITPR1) could serve as an initial set to the experimentalists for further validation. Additionally, various US food and drug administration (FDA) approved drugs interacting with the potential HICs were also identified. The study also reinforcesthe drug repurposing approach for the development of host directed antiviral drugs.