The shift from 'magic bullets' to 'magic shotguns' has prospered the pharmaceutical industry, where a belief is that a drug that'hits' multiple sensitive nodes belonging to a network of interacting targets offers the potential for higher efficacy and may limit drawbacks arising from the use of a single-target drug or a combination of multiple drugs. More high-quality drug-target interactions, profiled by the 'magic shotguns' design paradigm, have emerged from diverse labs. However, the rapid production at scale and in variety challenges the efficacy of data usage. A creative and systematical approach is in demand to comprehensively analyze and integrate drug- target interactions for better prediction. In the project, taking the diversity into consideration, we carried out a gene family-led, meta-analysis, investigated diverse properties that drug-target pharmacological promiscuity relies on, and examined the consistency or integrity of drug-target data. The novel approach can facilitate the identification of cohesive multi-target combinations and revealed the interconnected properties of determining and rationalizing the promiscuity of profiled drugs. The approach can be further expanded to coordinate other experimental drug-target data and set a stage for the analysis of the mechanism of action of biological therapies.