<p>Network Pharmacology-Based Prediction and Verification of the Active Ingredients and Potential Targets of Zuojinwan for Treating Colorectal Cancer</p>

Abstract

Background: Zuojinwan (ZJW), a famous Chinese medicine formula, has been widely used to treat colorectal cancer (CRC). However, its bioactive compounds, potential targets, and molecular mechanism remain largely elusive. Aim: A network pharmacology-based strategy combined with molecular docking studies and in vitro validation were employed to investigate bioactive compounds, potential targets, and molecular mechanism of ZJW against CRC. Materials and Methods: Bioactive compounds and potential targets of ZJW, as well as related genes of CRC, were acquired from public databases. Important ingredients, potential targets, and signaling pathways were determined through bioinformatics analysis, including protein-protein interaction (PPI), the Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, molecular docking and cell experiments were performed to further verify the findings. Results: A total of 36 bioactive ingredients of ZJW and 163 gene targets of ZJW were identified. The network analysis revealed that quercetin, baicalein, wogonin, beta-sitosterol, and isorhamnetin may be candidate agents. The AKT1, JUN, CDKN1A, BCL2L1, and NCOA1 could become potential drug targets. The KEGG indicated that PI3K-AKT signaling pathway may play an important role in the effect of ZJW against CRC. Molecular docking suggested that quercetin, baicalein, and wogonin combined well with AKT1 and JUN. The in vitro experiment showed that quercetin, the most important ingredient of ZJW, could induce apoptosis of HCT116 cells through PI3K-Akt signaling pathway. This finding was congruent with the prediction obtained through the network pharmacology approach. Conclusion: This study comprehensively illuminated the active ingredients, potential targets, and molecular mechanism of ZJW against CRC. It also provided a promising approach to uncover the scientific basis and therapeutic mechanism of traditional Chinese medicine (TCM) formula treating for disease.

Dissecting the novel mechanism of reduning injection in treating Coronavirus Disease 2019 (COVID-19) based on network pharmacology and experimental verification

“… Adamson and Swenson, 2017 ; Channappanavar and Perlman, 2017 ; Das and Yu, 2012 ; Eijkelenboom and Burgering, 2013 ; Ferner and Aronson, 2020 ; Grimes and Grimes, 2020 ; BHolshue et al, 2020 ; Hou et al, 2016 ; Kanehisa and Sato, 2020 ; Kim and Choi, 2010 ; Lai et al, 2020 ; Tukaj and Węgrzyn, 2016 ; Wan et al, 2020 ; Wu and Yang, 2020 ; Zhang et al, 2020 , Cao et al, 2020 , Huang et al, 2020 , Luo et al, 2019 …”

Integrating Network Pharmacology and Experimental Verification to Explore the Mechanism of Effect of Zuojin Pills in Pancreatic Cancer Treatment

“…Previous studies have shown that ZJP mainly inhibits proliferation, induces cell apoptosis and autophagic cell death, and has certain anticancer effects on colon cancer, breast cancer, liver cancer, lung cancer, colorectal cancer, and other types of cancer. 27 In the current study, a total of 294 types of Chinese herbal medicines were identified, and 41 components were followed up using comprehensive retrieval methods in the Chinese herbal medicine database and the BATMAN-TCM database. In addition, 2969 pancreatic cancer-related genes were identified.…”

“…19 In addition, ZJP significantly inhibited the proliferation of human tumor cell lines by inducing mitochondrial apoptosis and had significant inhibitory effects on HepG2-derived mouse tumors, breast cancer, colorectal cancer, and other cancers. [25][26][27] In recent years, biotechnology has made great progress. Network pharmacology based on large databases has become a powerful tool for studying TCM because it allows investigators to study the mechanism of action of compounds from the molecular level to the pathway level.…”

Network Pharmacology-Based Prediction and Verification of the Mechanism of Shikonin in the Treatment of Colorectal Cancer

“…Furthermore, it provides a basic set of characteristics for data integration, analysis, and visualization for complicated network analysis. The key topological parameters (degree) characterize the most important nodes in the network; higher quantitative values of topological parameters indicate greater importance of the node [12]. GO enrichment analysis GO analysis was performed using the online functional annotation and enrichment tool DAVID (https://david.ncifcrf.gov/).…”