Since there is no precise therapy for treating vascular calcification by directly targeting the vascular wall, we aim to unveil novel drug targets through mining the molecular effect of a high phosphate environment on vascular cells through computational methods. Here, we hypothesize that manipulation of the vascular pathogenic network by small molecule therapeutics predicted from prior knowledge might offer great promise. With this, we intend to understand the publicly available transcriptomic data of vascular smooth muscle cells and endothelial cells exposed to the high phosphate induced vascular calcification milieu and to re-examine the above published experiments for reasons different from those examined in the previous studies through multilevel systems biological understanding. Hence, in this study the differentially expressed genes were subjected to both upstream and downstream network analysis through multiple standalone software and web servers. To provide an insight into causal signaling, we simultaneously predicted upstream regulatory layers through transcription factor and kinome enrichment analysis. Moreover the possible systems pharmacological choices were presented in three ways as (1) drug induced expression modulation, (2) drugs that interact with upstream and downstream regulatory targets, (3) possible natural product therapeutics from target-compound relationship. Furthermore for validating the current study we have specifically evaluated the preventive effect of two predicted natural compounds in a bovine aortic calcification model. The overall observation predicts a few novel mechanisms that might be involved in vascular dysfunction and calcification in both cell types. Also, the systems pharmacological investigation provides clues for the possible therapeutic options along with validation. In conclusion, the current study indicates that reanalysis of transcriptomic data propels us to reposition the approved drugs and use natural compounds as novel therapeutic agents for vascular calcification.

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http://dx.doi.org/10.1039/c6mb00557hDOI Listing

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