Enteroviruses (EVs) represent many important pathogens of humans. Unfortunately, no antiviral compounds currently exist to treat infections with these viruses. We screened the Prestwick Chemical Library, a library of approved drugs, for inhibitors of coxsackievirus B3, identified pirlindole as a potent novel inhibitor, and confirmed the inhibitory action of dibucaine, zuclopenthixol, fluoxetine, and formoterol. Upon testing of viruses of several EV species, we found that dibucaine and pirlindole inhibited EV-B and EV-D and that dibucaine also inhibited EV-A, but none of them inhibited EV-C or rhinoviruses (RVs). In contrast, formoterol inhibited all enteroviruses and rhinoviruses tested. All compounds acted through the inhibition of genome replication. Mutations in the coding sequence of the coxsackievirus B3 (CV-B3) 2C protein conferred resistance to dibucaine, pirlindole, and zuclopenthixol but not formoterol, suggesting that 2C is the target for this set of compounds. Importantly, dibucaine bound to CV-B3 protein 2C in vitro, whereas binding to a 2C protein carrying the resistance mutations was reduced, providing an explanation for how resistance is acquired.

Autophagy-related (ATG) proteins regulate autophagy, but recent work indicates that some also have autophagy-independent roles. Here, Mauthe et al. perform an unbiased siRNA screen to examine the effects of ATG protein depletion on viral replication and demonstrate autophagy-independent functions for ATG13 and FIP200 in the picornaviral life cycle.

High-content screening (HCS) can generate large multidimensional datasets and when aligned with the appropriate data mining tools, it can yield valuable insights into the mechanism of action of bioactive molecules. However, easy-to-use data mining tools are not widely available, with the result that these datasets are frequently underutilized. Here, we present HC StratoMineR, a web-based tool for high-content data analysis. It is a decision-supportive platform that guides even non-expert users through a high-content data analysis workflow. HC StratoMineR is built by using My Structured Query Language for storage and querying, PHP: Hypertext Preprocessor as the main programming language, and jQuery for additional user interface functionality. R is used for statistical calculations, logic and data visualizations. Furthermore, C++ and graphical processor unit power is diffusely embedded in R by using the rcpp and rpud libraries for operations that are computationally highly intensive. We show that we can use HC StratoMineR for the analysis of multivariate data from a high-content siRNA knock-down screen and a small-molecule screen. It can be used to rapidly filter out undesirable data; to select relevant data; and to perform quality control, data reduction, data exploration, morphological hit picking, and data clustering. Our results demonstrate that HC StratoMineR can be used to functionally categorize HCS hits and, thus, provide valuable information for hit prioritization.