Investigating the multi-target pharmacological mechanism of danhong injection acting on unstable angina by combined network pharmacology and molecular docking

Abstract

Background: Danhong injection (DHI), which is one of the most well-known Traditional Chinese Medicine (TCM) injections, widely used to treat unstable angina (UA). However, its underlying pharmacological mechanisms need to be further clarified. Methods: In the present study, network pharmacology was adopted. Firstly, the relative compounds were obtained by a wide-scaled literatures-mining and potential targets of these compounds by target fishing were collected. Then, we built the UA target database by DisGeNET, DigSee, TTD, OMIM. Based on data, protein-protein interaction (PPI) analysis, GO and KEGG pathway enrichment analysis were performed and screen the hub targets by topology. Furthermore, evaluation of the binding potential of key targets and compounds through molecular docking. Results: The results showed that 12 ingredients of DHI and 27 putative known therapeutic targets were picked out. By systematic analysis, identified 4 hub targets (TNF, TLR4, NFKB1 and SERPINE1) mainly involved in the complex treating effects associated with coagulation and hemostasis, cell membrane region, platelet alpha granule, NFkappa B signaling pathway and TNF signaling pathway. Conclusion: The results of this study preliminarily explained the potential targets and signaling pathways of DHI in the treatment of UA, which may help to laid a good foundation for experimental research and further clinical application.

Network Pharmacology and Molecular Docking Analysis of Shanhaidan granules in treatment of coronary heart disease angina pectoris

“…In coronary heart disease, TNF-α might increase the expression of monocyte/macrophage tissue factor which could enhance thrombus activity. In atherosclerotic plaques, TNF-α cause plaque instability by enhancing apoptosis and degradation of matrix metalloproteinases (MMP), which aggravated the development of atherosclerosis and angina pectoris [20]. In patients with CHD and heart failure, TNF-α activated the transcription nuclear factor-kappa B which further induce in ammatory and oxidative stress responses [21].…”

“…Caspase-3 acted as the convergence of apoptosis-related signal pathways, and activation of Caspase-3 thereby amplify the apoptotic signalling pathway irreversibly [17]. Several studies showed that TNF-α, IL-6 and caspase-3 were closely related to the occurrence of angina pectoris, which can induce in ammatory factors, apoptosis pathway, oxidative stress, and aggravate the myocardial injury [19,20,22]. In the treatment of CHD-AP, Shanhaidan granule might improve the level of in ammation, apoptosis, and oxidative stress by affecting the expression of IL-6, TNF-α, and caspase-3.…”

Dissecting the mechanism of Yuzhi Zhixue granule on ovulatory dysfunctional uterine bleeding by network pharmacology and molecular docking

“…The therapeutic target database (TTD, https://db.idrblab.org/ttd/ ), is a database that provides information about nucleic acid targets and the therapeutic effects of proteins [ 25 ]. The pharmacogenomics knowledgebase (PharmGKB, https://www.pharmgkb.org/ ) is a database that collects complete genotypic and phenotypic information related to the pharmacogenomics and systematically categorizes this information [ 26 ].…”

Essential Oil Phytocomplex Activity, a Review with a Focus on Multivariate Analysis for a Network Pharmacology-Informed Phytogenomic Approach

“…This field is currently being extensively used in pharmacology. Identifying in silico the most promising compounds or mixtures of compounds for the desired molecular targets on virtual platforms is currently one emerging strategy in the discovery of new drugs to be used for the treatment of multifactorial diseases [62]. Currently, several research teams have developed in silico platforms at a higher level, endowed with software capable of assembling and analyzing billions of known bioactive compounds that can be used to verify their effectiveness against key proteins associated with multifactorial diseases [63].…”