Analysis of Molecular Mechanism of Erxian Decoction in Treating Osteoporosis Based on Formula Optimization Model

Abstract

Osteoporosis (OP) is a highly prevalent orthopedic condition in postmenopausal women and the elderly. Currently, OP treatments mainly include bisphosphonates, receptor activator of nuclear factor kappa-B ligand (RANKL) antibody therapy, selective estrogen receptor modulators, teriparatide (PTH1-34), and menopausal hormone therapy. However, increasing evidence has indicated these treatments may exert serious side effects. In recent years, Traditional Chinese Medicine (TCM) has become popular for treating orthopedic disorders. Erxian Decoction (EXD) is widely used for the clinical treatment of OP, but its underlying molecular mechanisms are unclear thanks to its multiple components and multiple target features. In this research, we designed a network pharmacology method, which used a novel node importance calculation model to identify critical response networks (CRNs) and effective proteins. Based on these proteins, a target coverage contribution (TCC) model was designed to infer a core active component group (CACG). This approach decoded the mechanisms underpinning EXD’s role in OP therapy. Our data indicated that the drug response network mediated by the CACG effectively retained information of the component-target (C-T) network of pathogenic genes. Functional pathway enrichment analysis showed that EXD exerted therapeutic effects toward OP by targeting PI3K-Akt signaling (hsa04151), calcium signaling (hsa04020), apoptosis (hsa04210), estrogen signaling (hsa04915), and osteoclast differentiation (hsa04380) via JNK, AKT, and ERK. Our method furnishes a feasible methodological strategy for formula optimization and mechanism analysis and also supplies a reference scheme for the secondary development of the TCM formula.

Computational Network Pharmacology–Based Strategy to Capture Key Functional Components and Decode the Mechanism of Chai-Hu-Shu-Gan-San in Treating Depression

“…Whether botanical drugs or ingredients in the formula are necessary, especially when treating a specific disease, still needs analysis and verification. Through compound optimization, these botanical drugs and components with a better intervention effect can be screened out, while those botanical drugs and components with the antagonistic effect and even side effects are removed, making the compound simpler and more effective ( Wang et al, 2020a ; Wang et al, 2020b ; Gao et al, 2020 ; Yang et al, 2021 ).…”

Detecting Critical Functional Ingredients Group and Mechanism of Xuebijing Injection in Treating Sepsis

“…The level of TNF-α was reported to be increased significantly in LPS-stimulated BMDMs (Liu et al, 2020). Comparatively, TNF-α could be reduced by baicalin (MOL002776) in the blood of sepsis mice (Chen et al, 2016) A Chinese formula, RDN, had been proved to ameliorate LPSinduced acute lung injury by downregulating TNF-α (Yang et al, 2021). 3) IL-1β: This is also a typical pro-inflammatory factor, which could promote T cells to further produce a large number of inflammatory mediators, which could reduce the body's immune function and destroy the barrier function of various tissues and organs, leading to the spread of systemic inflammatory response (Kamisoglu et al, 2015).…”

“…3) IL-1β: This is also a typical pro-inflammatory factor, which could promote T cells to further produce a large number of inflammatory mediators, which could reduce the body's immune function and destroy the barrier function of various tissues and organs, leading to the spread of systemic inflammatory response (Kamisoglu et al, 2015). Comparatively, it was proved to be downregulated by RDN and to ameliorate LPS-induced acute lung injury (Yang et al, 2021). It was indicated to be decreased by CX (Lv et al, 2012) and reported to be reduced by baicalin (MOL002776) in the sera of bacterial infected mice, significantly, thereby improving mouse survival in bacterial sepsis , and to have been reduced by caffeic acid [MOL000223 (CX, DS, and HH)] in LPS-stimulated macrophages (Chen et al, 2019).…”

“…In our study, NFKB1 was the target of many ingredients in the CFIG, including MOL000389, COM10, MOL007022, MOL000874, MOL000223, COM17, MOL007116, COM16, MOL007050, and MOL001942. TNF-α, a pro-inflammatory cytokine, could be promoted to transcript through the NF-κB and MAPK signaling pathway, thereby activating the cytokine storm (Hotchkiss et al, 2016;Yang et al, 2021). It was the target of MOL001494, MOL002883, and COM12.…”

“…For example, Shenfu injection has been proved to attenuate apoptosis and inflammation induced by lipopolysaccharide (LPS) via downregulating the ERK and MEK signaling pathways (Chen et al, 2020); refined Qingkailing injection has been proved to inhibit inflammatory response against ischemic stroke by activating the AKT/PI3K signaling pathway, decreasing chemokines Ccl2, Cxcl2, Cxcl3, and proinflammatory factors tumor necrosis factor (TNF), IL-6, and IL-1b, and by increasing anti-inflammatory cytokine IL-10 (Ma et al, 2020). Re-Du-Ning injection (RDN) has been proved to ameliorate LPS-induced acute lung injury by downregulating some pro-inflammatory cytokines, such as IL-1β, IL-6, and TNF-α, and by suppressing the MAPK pathway (Yang et al, 2021).…”