Clinical studies have shown that dapagliflozin can reduce cardiovascular outcome in patients with type 2 diabetes mellitus (T2DM), but the exact mechanism is unclear. In this study, we used the molecular docking and network pharmacology methods to explore the potential mechanism of dapagliflozin on T2DM complicated with cardiovascular diseases (CVD). Dapagliflozin's potential targets were predicted via the Swiss Target Prediction platform. The pathogenic targets of T2DM and CVD were screened by the Online Mendelian Inheritance in Man (OMIM) and Gene Cards databases. The common targets of dapagliflozin, T2DM and CVD were used to establish a protein‐protein interaction (PPI) network; the potential protein functional modules in the PPI network were found out by MCODE. Metascape tool was used for Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis. A potential protein functional module with the best score was obtained from the PPI network and 9 targets in the protein functional module all showed good binding properties when docking with dapagliflozin. The results of KEGG pathway enrichment analysis showed that the underlying mechanism mainly involved AGE‐RAGE signalling pathway in diabetic complications, TNF signalling pathway and MAPK signalling pathway. Significantly, the MAPK signalling pathway was considered as the key pathway. In conclusion, we speculated that dapagliflozin played a therapeutic role in T2DM complicated with CVD mainly through MAPK signalling pathway. This study preliminarily reveals the possible mechanism of dapagliflozin in the treatment of T2DM complicated with CVD and provides a theoretical basis for future clinical research.

Aims: To evaluate the effectiveness and potential mechanism of calcium dobesilate (CaD) in diabetic kidney disease (DKD) patients.Methods: We searched for available randomized controlled studies on DKD patients’ treatment with CaD through open databases. Continuous variables were expressed as standardized mean difference (SMD) with a 95% confidence interval (CI). The putative targets and possible pathways of CaD on DKD were analyzed by network pharmacology. Molecular docking was employed to verify the match between CaD and the target genes.Results: In the meta-analysis, 42 trials were included, involving 3,671 DKD patients, of which 1,839 received CaD treatment in addition to conventional treatment, while 1,832 received conventional treatment. Compared with routine therapy, the levels of serum creatinine (Scr) and blood urea nitrogen (BUN) significantly decreased in the CaD treatment (early stage of DKD, Scr: p < 0.00001; BUN: p < 0.0001; clinical stage of DKD, Scr: p < 0.00001; BUN: p < 0.00001; kidney failure stage, Scr: p = 0.001; BUN: p = 0.004). The levels of serum cystatin C (Cys-C), urine levels of molecules reflecting kidney function (urinary albumin excretion rate (UAER) and micro glycoprotein), and inflammatory factors [hypersensitive c-reactive protein (hs-CRP)] were reduced compared with control groups, while glomerular filtration rate (GFR) was increased in patients treated with CaD for 12 weeks. CaD also showed a better effect on improving endothelial function. Network pharmacology results showed that the interaction pathway between CaD and DKD was mainly enriched in MAPK and chemokine signaling pathways. AKT1, CASP3, IGF1, MAPK8, and CCL5 might be the key targets for CaD in treating DKD.Conclusion: Combination with CaD is effective and safe in patients with DKD. Inhibition of MAPK and chemokine signaling pathways might be vital in treating CaD in DKD patients.