Lack of evidence of molecular biology has marginalized the clinical success of alternative and complementary medicine (CAM). In turn, most life scientists have not been able to help develop therapeutic potential in these therapies. In this study, we measured descriptive classification theory in one of the branches of CAM, namely Iranian traditional medicine (ITM). Using proteomics tools and network analysis, the proteins were expressed and their relationships were with each other. Mitochondrial lysates isolated from PBMCs from two different temperaments namely hot and humid (HW) and cold (CD) were studied. 82% of the marked proteins are more or less shown separately. Temperaments Also, our results showed different protein and different protein cross-networks (PPINs) that are shown in these two temperaments using centralization and module analysis. After gene ontology and pathway enrichment analysis, we found enriched biological terms in each group according to known physiological evidence in ITM. Finally, we argued that network biology, which naturally considers system-level life with a variety of different data, paves the way for explicit mapping of CAM activities.