Compound Danshen Formula (CDF) is a widely used Traditional Chinese Medicine (TCM) which has been extensively applied in clinical treatment of cardiovascular diseases (CVDs). However, the underlying mechanism of clinical administrating CDF on CVDs is not clear. In this study, the pharmacological effect of CDF on CVDs was analyzed at a systemic point of view. A systems-pharmacological model based on chemical, chemogenomics and pharmacological data is developed via network reconstruction approach. By using this model, we performed a high-throughput in silico screen and obtained a group of compounds from CDF which possess desirable pharmacodynamical and pharmacological characteristics. These compounds and the corresponding protein targets are further used to search against biological databases, such as the compound-target associations, compound-pathway connections and disease-target interactions for reconstructing the biologically meaningful networks for a TCM formula. This study not only made a contribution to a better understanding of the mechanisms of CDF, but also proposed a strategy to develop novel TCM candidates at a network pharmacology level.