A Network Pharmacology Approach to Uncover the Mechanisms of Shen-Qi-Di-Huang Decoction against Diabetic Nephropathy

Hindawi Evidence-Based Complementary and Alternative Medicine Volume 2018, Article ID 7043402, 14 pages https://doi.org/10.1155/2018/7043402 Research Article A Network Pharmacology Approach to Uncover the Mechanisms of Shen-Qi-Di-Huang Decoction against Diabetic Nephropathy Sha Di ,1 Lin Han ,1 Qing Wang,1 Xinkui Liu,2 Yingying Yang Fan Li ,2 Linhua Zhao ,1 and Xiaolin Tong 1,3 ,1 1 Department of Endocrinology, Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100054, China Department of Clinical Chinese Pharmacy, School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100102, China 3 Shenzhen Hospital of Guangzhou University of Chinese Medicine, Shenzhen 518034, China 2 Correspondence should be addressed to Linhua Zhao; and Xiaolin Tong; Received 4 April 2018; Revised 15 September 2018; Accepted 11 October 2018; Published 1 November 2018 Academic Editor: Kuttulebbai N. S. Sirajudeen Copyright © 2018 Sha Di et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Shen-Qi-Di-Huang decoction (SQDHD), a well-known herbal formula from China, has been widely used in the treatment of diabetic nephropathy (DN). However, the pharmacological mechanisms of SQDHD have not been entirely elucidated. At first, we conducted a comprehensive literature search to identify the active constituents of SQDHD, determined their corresponding targets, and obtained known DN targets from several databases. A protein-protein interaction network was then built to explore the complex relations between SQDHD targets and those known to treat DN. Following the topological feature screening of each node in the network, 400 major targets of SQDHD were obtained. The pathway enrichment analysis results acquired from DAVID showed that the significant bioprocesses and pathways include oxidative stress, response to glucose, regulation of blood pressure, regulation of cell proliferation, cytokine-mediated signaling pathway, and the apoptotic signaling pathway. More interestingly, five key targets of SQDHD, named AKT1, AR, CTNNB1, EGFR, and ESR1, were significant in the regulation of the above bioprocesses and pathways. This study partially verified and predicted the pharmacological and molecular mechanisms of SQDHD on DN from a holistic perspective. This has laid the foundation for further experimental research and has expanded the rational application of SQDHD in clinical practice. 1. Introduction Diabetic nephropathy (DN), a complex and multifaceted condition, is one of the main microvascular complications of diabetes mellitus, especially type 2 diabetes mellitus (T2DM) [1]. T2DM is an important cause of kidney failure, which presents the risk of development of hypertension. In 2010, 6.4% of the world’s population was diagnosed with diabetes mellitus, and this value is expected to increase to 7.7% in 2030, in other words, from 285 million to 439 million adults [2]. DN is distinguished by the elevated albumin excretion rate and/or the transient increased glomerular filtration rate (GFR) [3]. The earliest sign of DN is microalbuminuria (>30 mg/day), which develops into macroalbuminuria (>300 mg/day) and decreased GFR, eventually leading to end-stagerenal disease (ESRD) [4, 5]. The pathogenesis of DN has been associated with oxidative stress and inflammation caused by chronic high blood glucose [6–8], glucose metabolic disorder [9], hemodynamics, and hemorheology anomalies [10]. The current standard therapy includes intensive treatment and control of hyperglycemia and blood pressure. A blockade of the renin-angiotensin system (RAS) is also associated [11]; however, RAS combination therapy cannot prevent the progression of DN and is linked to an elevated rate of severe adverse events. Novel agents have shown controversial results or side effects [12] which makes it important to develop more efficient treatment to cure DN and reduce side effects. Traditional Chinese Medicine (TCM) is widely propagated and used in more than 100 countries across the world owing to its satisfactory clinical efficacy [13]. SQDHD was documented in Shen Shi Zun Sheng Shu, which was written by Shen Jinao in 1773 during the Qing Dynasty. SQDHD 2 Evidence-Based Complementary and Alternative Medicine SQDHD Compound-Compound Target Network diabetic nephropathy Herb-Compound Target-DN Target Network Compound Target-DN-Other Human Proteins’ PPI Network GO enrichment analysis GO enrichment analysis KEGG enrichment analysis KEGG enrichment analysis Figure 1: Workflow for SQDHD against diabetic nephropathy. contains eight Chinese herbs, including Codonopsis Radix (Dang Shen [DS]), Hedysarum Multijugum Maxim. (Huang Qi [HQ]), dried Radix Rehmannia (Sheng Di Huang [SDH]), Rhizoma Dioscoreae (Shan Yao [SY]), Cornus Officinalis Sieb. Et Zucc. (Shan Zhu Yu [SZY]), Cortex Moutan (Mu Dan Pi [MDP]), Alisma Orientale (Sam.) Juz. (Ze Xie [ZX]), and Poria Cocos(Schw.) Wolf. (Fu Ling [FL]). Liuwei dihuang pill (LDP), including Cornus Officinalis Sieb. Et Zucc., Cortex Moutan, Rhizoma Dioscoreae, Poria Cocos(Schw.) Wolf., Alisma Orientale (Sam.) Juz., and Radix Rehmanniae Praeparata, inhibited erythrocyte aldose reductase activity and lowered urinary albumin excretion rate and beta2-MG in the blood and urine in the treated group compared to those in the control group [14]. LDP can decrease multiple pathways including TGF-𝛽/SMADS, MAPK, and NF-𝜅B signaling to prevent the progress of renal fibrosis and defend glomerular mesangial cells [15]. Astragaloside IV (ASI), active component in Hedysarum Multijugum Maxim., could inhibit high glucose-induced cell apoptosis and decrease TGF-𝛽1 and the activity of p38 in the MAPK pathway [16]. Dried Rehmanniae Radix reduced glucose, urea nitrogen, 5-hydroxymethylfurfural, and thiobarbituric acid- (TBA-) reactive substance levels in DN rats [17]. Moutan Cortex could significantly decrease blood glucose, serum creatinine, and urine protein in DN rats and reduce transforming growth factor beta 2 (TGF-𝛽2) in renal tissue [18]. Therefore, SQDHD might exhibit substantial effect on DN. As SQDHD includes many chemical compounds and adjusts a variety of targets, the pharmacological mechanisms require a complete clarification, which has been a challenge. Network pharmacology, put forward by Hopkins in 2007, is used to elucidate the drugs effect on multiple targets [19]. Network pharmacology can build networks to reflect and clarify the interactive relationship between multiple components, multiple targets, multiple pathways, and complex diseases. It is also capable of interpreting the mechanisms of functional drugs based on the network built on public databases or available data through earlier researches. Network pharmacology can reconstruct a “drug target disease” network prediction model [20, 2 (...truncated)