Abstract
Huang-Lian-Jie-Du Decoction (HLJDD) is a "Fangji" made up of well-designed Chinese herb array and widely used to treat ischemic stroke. Here we aimed to investigate pharmacological mechanism by introducing an inter-module analysis to identify an overarching view of target profile and action mode of HLJDD. Stroke-related genes were obtained from OMIM (Online Mendelian Inheritance in Man). And the potential target proteins of HLJDD were identified according to TCMsp (Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform). The two sets of molecules related to stroke and HLJDD were respectively imported into STRING database to construct the stroke network and HLJDD network, which were dissected into modules through MCODE, respectively. We analyzed the inter-module connectivity by quantify "coupling score" (CS) between HLJDD-modules (H-modules) and stroke-modules (S-module) to explore the pharmacological acting pattern of HLJDD on stroke. A total of 267 stroke-related proteins and 15 S-modules, 335 HLJDD putative targeting proteins, and 13 H-modules were identified, respectively. HLJDD directly targeted 28 proteins in stroke network, majority (16, 57.14%) of which were in S-modules 1 and 4. According to the modular map based on inter-module CS analysis, H-modules 1, 2, and 8 densely connected with S-modules 1, 3, and 4 to constitute a module-to-module bridgeness, and the enriched pathways of this bridgeness with top significance were TNF signaling pathway, HIF signaling pathway, and PI3K-Akt signaling pathway. Furthermore, through this bridgeness, H-modules 2 and 4 cooperatively work together to regulate mitochondrial apoptosis against the ischemia injury. Finally, the core protein in H-module 4 account for mitochondrial apoptosis was validated by an in vivo experiment. This study has developed an integrative approach by inter-modular analysis for elucidating the "shotgun-like" pharmacological mechanism of HLJDD for stroke.
Highlights
Stroke is a complex disease featured by various genetic variations and dysfunction (Matthew et al, 2012)
Based on the proteins that correspond to imported stroke genes and protein-to-protein interactions from STRING, proteins association network related to stroke was constructed, in which proteins were represented as vertex, and interaction confidence more than 0.4 was set as the edge connecting corresponding proteins
The official symbols, domains, and annotations of the 267 proteins are shown in Supplementary Table 1.And 256 in 267 proteins were involved in the stroke-related network, and the other 11 proteins were distributed individually; 1,502 edges were included in the network
Summary
Stroke is a complex disease featured by various genetic variations and dysfunction (Matthew et al, 2012). The subsequent mess brought by gene interactions and pathway crosstalk makes it difficult to obtain a “magic bullet” acting on “single gene, single target” to achieve therapeutic efficacy (Roth et al, 2004; Frantz, 2005; Hopkins, 2009; Wang et al, 2018) These observations, coupled with the increasing failure rate of drug discovery based on reductionism (Khanna, 2012) have led to calls for a new science of “network medicine” to find a multi-target therapy modulating multiple genes and their interactions (Chandra and Padiadpu, 2013; Wang and Wang, 2013; Harvey et al, 2015; Greene and Loscalzo, 2017). As amount and sheer diversity of high throughput data generated are enormous in the post-genomic age, it is pertinent to explore underlying pathogenesis and pharmacological mechanism by taking a more overarching view of Fangji multi-target therapies on stroke (Hasan et al, 2012; Gu and Chen, 2014; Huang et al, 2014; Li et al, 2017)
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