Identifying Drug-Target interactions is a core component in the development of new therapeutics, the repurposing of existing drugs, and the mechanistic research. To efficiently identify target sites for drugs, we propose the Drug-Target Explorer, a real-time system for extracting drug-target relationships from vast literature. This system employs a multi-stage intelligent retrieval strategy, leveraging dual large language models to simultaneously extract structured target information from original PubMed literature. Each result includes original evidence with links to PubMed source publications. Drug-Target Explorer supports conditional filtering, model comparisons, and one-click export, reducing the technical barriers and time investment required for target discovery.