Objective: To predict the targets of Yimai granules by bioinformatics

according to the adjustment of target genes

to determine its signaling pathways and the molecular mechanism of Yimai granules. Method: Bioinformatics was used to predict the potential regulatory genes of all drugs in Yimai granules.According to the principles of formulating prescription

a Venn diagram was drawn for all target genes of Yimai granules that acted on atherosclerosis(AS)

the overlapping genes were defined as target genes.Before and after administration

the hemogram changes of the AS model mice and the corresponding target gene regulation methods were used to determine the mechanism of Yimai granules to improve AS.The experimental group consisted of 60 ApoE-/- mice

they were randomly divided into 5 groups and fed continuously for 12 weeks.Twelve rats in model group were fed with high fat and high cholesterol diet+normal saline by intragastric administration;twelve rats in the high

medium and low dosage groups of Yimai granules were fed with high fat and cholesterol diet+high

medium and low dose of Yimai granules

respectively;twelve rats in the positive group were fed with high fat and high cholesterol diet+atorvastatin calcium tablets. Result: Yimai granules can reduce levels of triglyceride(TG)

total cholesterol(TC)

low density lipoprotein cholesterol(LDL-C) and high-density lipoprotein cholesterol(HDL-C) in mice

and the effect was positively correlated with the dose of Yimai granules.The lowering of TG

TC

LDL-C and HDL-C in the high-dose group of Yimai granules was weaker than those in the atorvastatin calcium tablets group.The targets of Yimai granules included carboxylesterase 1(CES1)

3-hydroxy-3-methylglutaryl coenzyme A reductase(HMGCR)

peroxisome proliferator-activated receptor(PPAR)D

PPARG

liver X receptor-α(LXR-α) and adenosine triphosphate(ATP)-binding cassette transporter A1(ABCA1). Conclusion: Yimai granules can activate the corresponding signaling pathway by up-regulating the expression of target genes of CES1

HMGCR

PPARD

PPARG

LXR-α and ABCA1

so as to achieve the therapeutic effect on AS.Bioinformatics can be used to predict and verify the action targets of formulas

which can provide a method to explain the mechanism of clinical formulas.