A comprehensive application: Molecular docking and network pharmacology for the prediction of bioactive constituents and elucidation of mechanisms of action in component-based Chinese medicine

Natural products have played a critical role in medicine due to their ability to bind and modulate cellular targets involved in disease. Medicinal plants hold a variety of bioactive scaffolds for the treatment of multiple disorders. The less adverse effects, affordability, and easy accessibility highlight their potential in traditional remedies. Identifying pharmacological targets from active ingredients of medicinal plants has become a hot topic for biomedical research to generate innovative therapies. By developing an unprecedented opportunity for the systematic investigation of traditional medicines, network pharmacology is evolving as a systematic paradigm and becoming a frontier research field of drug discovery and development. The advancement of network pharmacology has opened up new avenues for understanding the complex bioactive components found in various medicinal plants. This study is attributed to a comprehensive summary of network pharmacology based on current research, highlighting various active ingredients, related techniques/tools/databases, and drug discovery and development applications. Moreover, this study would serve as a protocol for discovering novel compounds to explore the full range of biological potential of traditionally used plants. We have attempted to cover this vast topic in the review form. We hope it will serve as a significant pioneer for researchers working with medicinal plants by employing network pharmacology approaches.

https://www.mdpi.com/1424-8247/15/5/572/pdf?version=1651635674

Network Pharmacology Approach for Medicinal Plants: Review and Assessment

Pharmacological inhibition of MELK restricts ferroptosis and the inflammatory response in colitis and colitis-propelled carcinogenesis.

Purpose Network pharmacology is considered to be the next-generation drug development model that uses bioinformatics to predict and identify multiple drug targets and interactions in diseases. Here, network pharmacology was used to investigate the mechanism by which Curculigoside A (CA) acts in rheumatoid arthritis (RA) and osteoporosis.
 Methods
 First, TCMSP and SwissADME were applied to predict the druggability of CA. Then, potential targets were identified from overlapping data in SwissTarget and TargetNet, and targets were analyzed using Genemania and DAVID6.8 to obtain information about the GO and KEGG pathways. Ultimately, the drug-target-pathway network was identified after using Cytoscape 3.0 for visualization. Besides, qPCR was used to validate the predicted five major genes targets (EGFR, MAP2K1, MMP2, FGFR1, and MCL1).
 Results
 The results of TCMSP and SwissADME demonstrated that CA exhibits good druggability; 26 potential protein targets were classified by SwissTarget and TargetNet. The results of Genemania and DAVID6.8 indicated that CA probably caused anti-osteoporosis and anti-RA effects by regulating some biological pathways, especially nitrogen metabolism, estrogen signaling pathway, Rap1 signaling pathway, and PI3K/Akt signaling pathway. Besides, the result of Cytoscape 3.0 showed that the 26 targets participate in osteoporosis and RA-related pathways, metabolism, and other physiological processes. In vitro induced inflammation cell model experiments, the qPCR results showed that CA pretreatment significantly decreased the expression of EGFR, MAP2K1, MMP2, FGFR1, and MCL1 genes.
 Conclusion
 These results suggested that network pharmacology may provide possible mechanism of how CA exerts therapeutic effects in osteoporosis and RA.

/pdf/prediction-of-targets-of-curculigoside-a-in-osteoporosis-and-4myvdx86jr.pdf

Prediction of Targets of Curculigoside A in Osteoporosis and Rheumatoid Arthritis Using Network Pharmacology and Experimental Verification

Endometriosis is a common benign disease in women of reproductive age. It has been defined as a disorder characterized by inflammation, compromised immunity, hormone dependence, and neuroangiogenesis. Unfortunately, the mechanisms of endometriosis have not yet been fully elucidated, and available treatment methods are currently limited. The discovery of new therapeutic drugs and improvements in existing treatment schemes remain the focus of research initiatives. Chinese medicine can improve the symptoms associated with endometriosis. Many Chinese herbal medicines could exert antiendometriosis effects via comprehensive interactions with multiple targets. However, these interactions have not been defined. This study used association rule mining and systems pharmacology to discover a method by which potential antiendometriosis herbs can be investigated. We analyzed various combinations and mechanisms of action of medicinal herbs to establish molecular networks showing interactions with multiple targets. The results showed that endometriosis treatment in Chinese medicine is mainly based on methods of supplementation with blood-activating herbs and strengthening qi. Furthermore, we used network pharmacology to analyze the main herbs that facilitate the decoding of multiscale mechanisms of the herbal compounds. We found that Chinese medicine could affect the development of endometriosis by regulating inflammation, immunity, angiogenesis, and other clusters of processes identified by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The antiendometriosis effect of Chinese medicine occurs mainly through nervous system-associated pathways, such as the serotonergic synapse, the neurotrophin signaling pathway, and dopaminergic synapse, among others, to reduce pain. Chinese medicine could also regulate VEGF signaling, toll-like reporter signaling, NF-κB signaling, MAPK signaling, PI3K-Akt signaling, and the HIF-1 signaling pathway, among others. Synergies often exist in herb pairs and herbal prescriptions. In conclusion, we identified some important targets, target pairs, and regulatory networks, using bioinformatics and data mining. The combination of data mining and network pharmacology may offer an efficient method for drug discovery and development from herbal medicines.

/pdf/modular-characteristics-and-mechanism-of-action-of-herbs-for-1qxpjqiwg0.pdf

Modular Characteristics and Mechanism of Action of Herbs for Endometriosis Treatment in Chinese Medicine: A Data Mining and Network Pharmacology–Based Identification

Objective Withaferin A (WA) is a bioactive compound with a remarkable anti-cancer effect derived from Withania somnifera, commonly known as ashwagandha. However, the anti-cancer mechanisms of WA in glioblastoma multiforme (GBM) are still unclear. Materials and methods Cell viability assays and xenografted nude mice were used to evaluate the effects of WA, along with flow cytometry to detect apoptosis and cell cycle of GBM. RNA-seq analysis, Western blotting, immunofluorescence staining, qRT-PCR and siRNA gene silencing were carried out to determine the signalling pathways affected by WA. Results Withaferin A significantly inhibited the growth of GBM in vitro and in vivo and triggered the intrinsic apoptosis of GBM cells by up-regulating expression of Bim and Bad. WA arrested GBM cells at the G2/M phase of the cell cycle through dephosphorylating Thr161 of CDK1 by activating p53-independent p21 up-regulation. Knockdown of p21 restored cell cycle progression and cell viability by down-regulating the expression of Bad rather than Bim. We demonstrated that endoplasmic reticulum (ER) stress induced by WA through the ATF4-ATF3-CHOP axis, initiated apoptosis and G2/M arrest in GBM cells. Conclusion We revealed a novel pathway that elucidated WA activation of apoptosis and G2/M arrest in GBM cells through the ATF4-ATF3-CHOP axis. This discovery is important for optimization of WA-based regimens for prevention and/or treatment of GBM.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/cpr.12706

Withaferin A triggers G2/M arrest and intrinsic apoptosis in glioblastoma cells via ATF4-ATF3-CHOP axis.

Lung cancer is the fastest growth rate of morbidity and mortality in nearly a decade, and remains difficult to treat. Furthermore, the molecular mechanisms underlying its development are still unclear. In this study, bioinformatics analysis showed that MELK was highly expressed in lung cancer and negatively correlated to the survival of lung adenocarcinoma (LUAD). Immunohistochemistry analysis of LUAD patient tissues revealed there were a high level of MELK expression in LUAD. Knockdown of MELK expression inhibits the migration and invasion of LUAD cells, which may be mediated by Twist1, Slug, MMP7, and N-catenin. Overexpression of MELK promoted the growth of LUAD cells in medium, 3D Matrigel, and nude mice. Inhibition of MELK by OTSSP167 arrested cycle of LUAD cells at G2/M phase via PLK1-CDC25C-CDK1 pathway, and triggered apoptosis-mediated pyroptosis. Together, these data indicate that MELK is critical for metastasis, mitotic progression, and programmed death of LUAD and may be a promising therapeutic target for LUAD.

/pdf/melk-is-an-oncogenic-kinase-essential-for-metastasis-mitotic-3y1vld7bdj.pdf

MELK is an oncogenic kinase essential for metastasis, mitotic progression, and programmed death in lung carcinoma.

Network pharmacology study of traditional Chinese medicines for stroke treatment and effective constituents screening.

Glioblastoma multiforme (GBM) is the most aggressive, common, and lethal subtype of malignant gliomas originating from the central nervous system. Currently, the standard therapy for GBM is surgical resection combined with radiation and temozolomide (TMZ). However, the treatment only improves the 2-year survival rate from 10% to 26%, accompanied by more than 90% recurrence of GBM tumors at the original site. Low survival rate, serious side effects, and poor prognosis force people to find new therapies. Recent years, the combination of clinical drugs improves the survival rate of GBM patients, but new therapeutic drugs with high-efficiency and low-toxicity are still needed to be discovered. The successful use of immunotherapy in tumor brings hope for people to explore new methods in treating GBM. While the inability to cross the blood-brain barrier (BBB), loss of lymphatic tissue drainage, and antigen-presenting cells in the central nervous system are major reasons for the failure of immunotherapy in the treatment of GBM. Glioma stem cells (GSCs) is a subtype of tumorigenic stem cells which has more specific tumorigenic potential indicating targeting GSCs may be expected to improve therapeutic efficacy. In this review, we discuss clinical drugs that have benefited patients with GBM, cancer immunotherapy for GBM, summarize new drug targets of GBM, and review strategies for increasing the passage of drugs through the BBB.

/pdf/a-narrative-review-of-research-progress-on-drug-therapies-1e1h3233u7.pdf

Qin Tang

Papers

Withaferin A triggers G2/M arrest and intrinsic apoptosis in glioblastoma cells via ATF4-ATF3-CHOP axis.

MELK is an oncogenic kinase essential for metastasis, mitotic progression, and programmed death in lung carcinoma.

Network pharmacology study of traditional Chinese medicines for stroke treatment and effective constituents screening.

A narrative review of research progress on drug therapies for glioblastoma multiforme.