In CACHE #2, 23 computational teams were challenged to prospectively predict ligands for the RNA binding site of SARS-CoV-2 Nsp13, a binding pocket with no known drug-like ligand. Testing the predicted compounds experimentally yielded a low hit rate of 0.7 %, indicating that a breakthrough in computational hit finding where bioactive molecules are reliably designed in silico remains to be seen. Strikingly, the highest scoring prediction in CACHE #2 was a compound manually designed by citizen scientists using the Fold-it online interface and further prioritized by physics and ML-based computational tools (WF1414), emphasizing the value of human intervention in the design process. Computational hit finding strategies and tools recurrently successful across the first two CACHE challenges define emerging trends that may inform the community when constructing hit-finding computational pipelines. To the best of our knowledge, the thirteen compounds confirmed experimentally are the first with a measurable binding affinity expected to engage the RNA binding site of Nsp13. Considering the exceptionally high conservation of this site and its central role in the essential replication-transcription complex , molecules discovered in CACHE #2 provide valuable chemical starting points for future medicinal chemistry exploration.