shRNAs can trigger effective silencing of gene expression in mammalian cells, thereby providing powerful tools for genetic studies, as well as potential therapeutic strategies. Specific shRNAs can interfere with the replication of pathogenic viruses and are currently being tested as antiviral therapies in clinical trials. However, this effort is hindered by our inability to systematically and accurately identify potent shRNAs for viral genomes. Here we apply a recently developed highly parallel sensor assay to identify potent shRNAs for HIV, hepatitis C virus (HCV), and influenza. We observe known and previously unknown sequence features that dictate shRNAs efficiency. Validation using HIV and HCV cell culture models demonstrates very high potency of the top-scoring shRNAs. Comparing our data with the secondary structure of HIV shows that shRNA efficacy is strongly affected by the secondary structure at the target RNA site. Artificially introducing secondary structure to the target site markedly reduces shRNA silencing. In addition, we observe that HCV has distinct sequence features that bias HCV-targeting shRNAs toward lower efficacy. Our results facilitate further development of shRNA based antiviral therapies and improve our understanding and ability to predict efficient shRNAs.