Identification of key candidate genes and molecular pathways in white fat browning: an anti-obesity drug discovery based on computational biology

Abstract

Background: Obesity-with its increased risk of obesity-associated metabolic diseases-has become one of the greatest public health epidemics of the twenty-first century in affluent countries. To date, there are no ideal drugs for treating obesity. Studies have shown that activation of brown adipose tissue (BAT) can promote energy consumption and inhibit obesity, which makes browning of white adipose tissue (WAT) a potential therapeutic target for obesity. Our objective was to identify genes and molecular pathways associated with WAT and the activation of BAT to WAT browning, by using publicly available data and computational tools; this knowledge might help in targeting relevant signaling pathways for treating obesity and other related metabolic diseases.

Results: In this study, we used text mining to find out genes related to brown fat and white fat browning. Combined with biological process and pathway analysis in GeneCodis and protein-protein interaction analysis by using STRING and Cytoscape, a list of high priority target genes was developed. The Human Protein Atlas was used to analyze protein expression. Candidate drugs were derived on the basis of the drug-gene interaction analysis of the final genes. Our study identified 18 genes representing 6 different pathways, targetable by a total of 33 drugs as possible drug treatments. The final list included 18 peroxisome proliferator-activated receptor gamma (PPAR-γ) agonists, 4 beta 3 adrenoceptor (β3-AR) agonists, 1 insulin sensitizer, 3 insulins, 6 lipase clearing factor stimulants and other drugs.

Conclusions: Drug discovery using in silico text mining, pathway, and protein-protein interaction analysis tools may be a method of exploring drugs targeting the activation of brown fat or white fat browning, which provides a basis for the development of novel targeted therapies as potential treatments for obesity and related metabolic diseases.

Keywords: Brown fat; Browning of white fat; Drug therapy; In silico; Obesity; PPAR-γ; Text mining; β3-AR.

Fig. 1

Overall data mining process. Text mining was used to identify genes associated with brown fat and white fat browning by using pubmed2ensemble. Combining with biological process and pathway analysis in GeneCodis and protein-protein interaction analysis by using STRING and Cytoscape, a list of high priority target genes was picked out. The Human Protein Atlas was used to analyze protein expression. The final drug list was obtained based on the gene-drug interaction analysis by using Pharmaprojects

Fig. 2

Summary of data mining results. a Text mining: Text mining was performed by using the terms “brown-fat-like development”, “brown fat”, and “brown adipose tissue”, respectively. One hundred seventy-eight genes were found by using pubmed2ensembl and total of 121 genes were common to all the three lists. b Gene set enrichment: Biological process and pathway analysis were performed in GeneCodis to enrich 70 and 28 genes, respectively. Next, nine significant genes were derived by protein-protein interaction analysis using STRING and Cytoscape. Together with the 12 genes from the most enriched biological process, “brown fat cell differentiation”, 18 significant genes were selected for the final analysis. c Protein expression analysis: Protein expression analysis was performed using The Human Protein Atlas. d Drug-gene interactions: 33 drugs were selected targeting white fat browning, which may serve as potential treatments of obesity and related metabolic diseases

Fig. 3

The protein-protein high (confidence score 0.900) interaction network of the 28 targeted genes using STRING. Network nodes represent proteins and different colored edges represent protein-protein interactions

Fig. 4

The protein-protein interaction network of the 27 targeted genes by using Cytoscape. Network nodes represent proteins and edges represent protein-protein interactions

Fig. 5

The protein expression analysis by using the Human Protein Atlas. a PPARG was positively expressed in adipose tissue. b ADRB3 was positively expressed in adipose tissue. c CEBPB was positively expressed in adipose tissue

Fig. 6

Key genes and signaling pathways involved in the brown fat activation and white fat browning. In response to cold, norepinephrine (NE) is released by the sympathetic nervous system and binds to the β3-adrenergic receptor (β3-AR) on the membrane of brown and beige adipocytes, which results in the activation of adenylyl cyclase to produce cyclic adenosine monophosphate (cAMP) that activates protein kinase A (PKA). PKA phosphorylates and activates cAMP response element-binding protein (CREB) resulting in enhanced transcription of uncoupling protein-1 (UCP1) and PPAR-γ co-activator (PGC-1α). Activated PGC1-α also stimulates the expression of fibronectin type III domain-containing protein 5 (FNDC5) which encodes a type I membrane protein that is cleaved to form a newly identified hormone, irisin. Irisin works on white adipocyte to stimulate UCP1 expression. Another factor, positive regulatory domain containing 16 (PRDM16), forms a transcriptional complex with CCAAT enhancer-binding protein (C/EBP)-β and induces the expression of PPAR-γ and PGC1-α. In addition, the activation of PKA enhances the phosphorylation of hormone-sensitive lipase (HSL) and promotes the decomposition of triacylglycerol (TG) in lipid droplets into glycerol and fatty acids (FA) that enter the mitochondria for β-oxidation. Activated BAT replenishes these stores via the uptake of TG-derived FA, generated by lipoprotein lipase (LPL)-mediated hydrolysis of TG