A Network Pharmacology and Molecular Docking Strategy to Explore Potential Targets and Mechanisms Underlying the Effect of Curcumin on Osteonecrosis of the Femoral Head in Systemic Lupus Erythematosus

Abstract

Background. Systemic lupus erythematosus (SLE) is a refractory immune disease, which is often complicated with osteonecrosis of the femoral head (ONFH). Curcumin, the most active ingredient of Curcuma longa with a variety of biological activities, has wide effects on the body system. The study is aimed at exploring the potential therapeutic targets underlying the effect of curcumin on SLE-ONFH by utilizing a network pharmacology approach and molecular docking strategy. Methods. Curcumin and its drug targets were identified using network analysis. First, the Swiss target prediction, GeneCards, and OMIM databases were mined for information relevant to the prediction of curcumin targets and SLE-ONFH-related targets. Second, the curcumin target gene, SLE-ONFH shared gene, and curcumin-SLE-ONFH target gene networks were created in Cytoscape software followed by collecting the candidate targets of each component by R software. Third, the targets and enriched pathways were examined by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Eventually, a gene-pathway network was constructed and visualized by Cytoscape software; key potential central targets were verified and checked by molecular docking and literature review. Results. 201 potential targets of curcumin and 170 related targets involved in SLE-ONFH were subjected to network analysis, and the 36 intersection targets indicated the potential targets of curcumin for the treatment of SLE-ONFH. Additionally, for getting more comprehensive and accurate candidate genes, the 36 potential targets were determined to be analyzed by network topology and 285 candidate genes were obtained finally. The top 20 biological processes, cellular components, and molecular functions were identified, when corrected by a P value ≤ 0.05. 20 related signaling pathways were identified by KEGG analysis, when corrected according to a Bonferroni P value ≤ 0.05. Molecular docking showed that the top three genes (TP53, IL6, VEGFA) have good binding force with curcumin; combined with literature review, some other genes such as TNF, CCND1, CASP3, and MMP9 were also identified. Conclusion. The present study explored the potential targets and signaling pathways of curcumin against SLE-ONFH, which could provide a better understanding of its effects in terms of regulating cell cycle, angiogenesis, immunosuppression, inflammation, and bone destruction.

Exploring Molecular Targets and Mechanisms of Apigenin in the Treatment of Papillary Thyroid Carcinoma Based on Network Pharmacology and Molecular Docking Analysis

“…Previous studies indicated that the affinity between curcumin and TP53 and VEGFA was −6.5 and −5 kcal/mol and the binding affinity between resveratrol and AKT1 was −6.2 kcal/mol. 58,59 Our study revealed that API showed better affinity with VEGFA (−5.27) and AKT1 (−6.83) in in silico studies. The co-crystalized ligand of the chosen macromolecule was re-docked using the same docking parameter as a test (Table 6).…”

Network-pharmacology-based study on the mechanism of fibrates regulating HIF-1A in the treatment of ischemic stroke

“…In this study, targets for feno brate, pirinixic acid, clo brate, beza brate, and gem brozil were obtained through Swiss Target Prediction platform (http://www.swisstargetprediction.ch/) 16 and CTD platform (http://ctdbase.org/) 17 , then the duplicate targets were removed, nally, the nal targets of each drug was obtained. Targets of IS was obtained through Genecard database (https://www.genecards.org/) 18 , OMIM database (https://omim.org/) 19 , DrugBank database (https://www.drugbank.com/) 19 , TTD database (https://db.idrblab.net/ttd/) 20 and DisGeNET database (https://www.disgenet.org/) 21 , the obtained targets were summarized, then duplicated targets were removed to obtain the nal targets of IS. Finally, the common targets of each drug and IS was obtained through the Venny 2.1.0 (https://bioinfogp.cnb.csic.es/tools/venny/) 22 .…”

Mechanistic Study of the Herbal Drug FDY003 for the Treatment of HER2-Positive Breast Cancer via Network Pharmacology Analysis

“…Using Autodock Vina [44], the binding energies between the hub target genes of FDY003 and their interacting bioactive ingredients were determined based on their threedimensional structures. Generally, binding energies lower than -5.0 kcal/mol are indicative that the ingredient and its target exhibit high binding affinity [45][46][47][48].…”