Researchers in China unveiled DrugCLIP, an AI framework that the team says can screen millions of candidate compounds against thousands of protein targets in just hours—described as orders-of-magnitude faster than standard virtual screening. The model couples large-scale compound-protein mapping with high-throughput scoring to prioritize chemical matter for experimental follow-up. The developers position DrugCLIP as a discovery-acceleration tool rather than a finished lead generator: rapid in silico triage should cut early costs and compress timelines, but wet-lab validation remains essential. The paper highlights how AI architectures tailored to chemical–protein relationships can reshape virtual screening throughput.