High-content image-based screening of a signal transduction pathway inhibitor small-molecule library against highly pathogenic RNA viruses.

High-content image-based screening was developed as an approach to test a small-molecule library of compounds targeting signal transduction pathways for antiviral activity against multiple highly pathogenic RNA viruses. Of the 2843 compounds screened, 120 compounds exhibited ≥60% antiviral activity. Four compounds (E225-0969, E528-0039, G118-0778, and G544-0735), which were most active against Rift Valley fever virus (RVFV) and showed broad-spectrum antiviral activity, were selected for further evaluation for their concentration-response profile and cytotoxicity. These compounds did not show any visible cytotoxicity at the highest concentration of compound tested (200 µM). All four of these compounds were more active than ribavirin against several viruses. One compound, E225-0969, had the lowest effective concentration (EC50 = 1.9-8.92 µM) for all the viruses tested. This compound was 13- and 43-fold more inhibitory against RVFV and Chikungunya virus (CHIKV), respectively, than ribavirin. The highest selectivity index (>106.2) was for E225-0969 against CHIKV. Time-of-addition assays suggested that all four lead compounds targeted early steps in the viral life cycle (entry and/or replication) but not virus egress. Overall, this work demonstrates that high-content image analysis can be used to screen chemical libraries for new antivirals against highly pathogenic viruses.