Integrating Network Pharmacology and Molecular Docking Approaches to Decipher the Multi-Target Pharmacological Mechanism of Abrus precatorius L. Acting on Diabetes

Novel drug discovery: Advancing Alzheimer's therapy through machine learning and network pharmacology

Alzheimer's disease (AD), marked by tau tangles and amyloid-beta plaques, leads to cognitive decline. Despite extensive research, its complex etiology remains elusive, necessitating new treatments. This study utilized machine learning (ML) to analyze compounds with neuroprotective potential. This approach exposed the disease's complexity and identified important proteins, namely MTOR and BCL2, as central to the pathogenic network of AD. MTOR regulates neuronal autophagy and survival, whereas BCL2 regulates apoptosis, both of which are disrupted in AD. The identified compounds, including Armepavine, Oprea1_264702,1-cyclopropyl-7-fluoro-8-methoxy-4-oxoquinoline-3-carboxylic acid,(2S)-4'-Hydroxy-5,7,3'-trimethoxyflavan,Oprea1_130514,Sativanone,5-hydroxy-7,8-dimethoxyflavanone,7,4'-Dihydroxy-8,3'-dimethoxyflavanone,N,1-dicyclopropyl-6,Difluoro-Methoxy-Gatifloxacin,6,8-difluoro-1-(2-fluoroethyl),1-ethyl-6-fluoro-7-(4-methylpiperidin-1-yl),Avicenol C, demonstrated potential modulatory effects on these proteins. The potential for synergistic effects of these drugs in treating AD has been revealed via network pharmacology. By targeting numerous proteins at once, these chemicals may provide a more comprehensive therapeutic approach, addressing many aspects of AD's complex pathophysiology. A Molecular docking, dynamic simulation, and Principle Component Analysis have confirmed these drugs' efficacy by establishing substantial binding affinities and interactions with important proteins such as MTOR and BCL2. This evidence implies that various compounds may interact within the AD pathological framework, providing a sophisticated and multifaceted therapy strategy. In conclusion, our study establishes a solid foundation for the use of these drugs in AD therapy. Thus current study highlights the possibility of multi-targeted, synergistic therapeutic approaches in addressing the complex pathophysiology of AD by integrating machine learning, network pharmacology, and molecular docking simulations. This holistic technique not only advances drug development but also opens up new avenues for developing more effective treatments for this difficult and widespread disease.

Network pharmacology-based screening of active constituents of Avicennia marina and their clinical biochemistry related mechanism against breast cancer

Breast cancer is the second major cause of cancer death in women globally. Avicennia marina is a medicinal plant that belongs to the family Acanthaceae and is known as grey or white mangrove. It has antioxidant, antiviral, anticancer, anti-inflammatory, and antibacterial activity in the treatment of various diseases including cancer. The goal of the study is to use a network pharmacology method to identify the potential phenomena of bioactive compounds of A. marina in the treatment of breast cancer and explore clinical biochemistry related aspects. A total of 74 active compounds of A. marina were retrieved from various databases as well as a literature review and collectively 429 targets of these compounds were identified by STITCH and Swiss Target Prediction databases. Breast cancer related 15606 potential targets were retrieved from the GeneCards database. A Venn diagram was drawn to find common key targets. To check the biological functions, the GO enrichment and KEGG pathways analysis of 171 key targets were performed through the DAVID database. To understand the interactions among key targets, Protein-protein interaction (PPI) studies were completed using the STRING database, and the Protein-Protein Interaction (PPI) network, as well as the compound-target-pathway network, was constructed using Cytoscape 3.9.0. Finally, molecular docking analysis of 5 hub genes named tumor protein 53 (TP53), catenin beta 1 (CTNNB1), interleukin 6 (IL6), tumor necrosis factor (TNF), and RAC-alpha serine/threonine protein kinases 1 (AKT1) with the active constituent of A. marina against breast cancer were performed. Additionally, a molecular docking study demonstrates that active drugs have a higher affinity for the target that may be used to decrease breast cancer. The molecular dynamic simulation analysis predicted the very stable behavior of docked complexes with no global structure deviations seen. The MMGBSA further supported strong intermolecular interactions with net energy values as; AKT1_Betulinic_acid (-20.97 kcal/mol), AKT1_Stigmasterol (-44.56 kcal/mol), TNF_Betulinic_acid (-28.68 kcal/mol) and TNF_Stigmastero (-29.47 kcal/mol).Communicated by Ramaswamy H. Sarma.

Hypoglycemic Activity of Rice Resistant-Starch Metabolites: A Mechanistic Network Pharmacology and In Vitro Approach

Rice (Oryza sativa L.) is one of the primary sources of energy and nutrients needed by the body, and rice resistant starch (RRS) has been found to have hypoglycemic effects. However, its biological activity and specific mechanisms still need to be further elucidated. In the present study, 52 RRS differential metabolites were obtained from mouse liver, rat serum, canine feces, and human urine, and 246 potential targets were identified through a literature review and database analysis. A total of 151 common targets were identified by intersecting them with the targets of type 2 diabetes mellitus (T2DM). After network pharmacology analysis, 11 core metabolites were identified, including linolenic acid, chenodeoxycholic acid, ursodeoxycholic acid, deoxycholic acid, lithocholic acid, lithocholylglycine, glycoursodeoxycholic acid, phenylalanine, norepinephrine, cholic acid, and L-glutamic acid, and 16 core targets were identified, including MAPK3, MAPK1, EGFR, ESR1, PRKCA, FYN, LCK, DLG4, ITGB1, IL6, PTPN11, RARA, NR3C1, PTPN6, PPARA, and ITGAV. The core pathways included the neuroactive ligand-receptor interaction, cancer, and arachidonic acid metabolism pathways. The molecular docking results showed that bile acids such as glycoursodeoxycholic acid, chenodeoxycholic acid, ursodeoxycholic acid, lithocholic acid, deoxycholic acid, and cholic acid exhibited strong docking effects with EGFR, ITGAV, ITGB1, MAPK3, NR3C1, α-glucosidase, and α-amylase. In vitro hypoglycemic experiments further suggested that bile acids showed significant inhibitory effects on α-glucosidase and α-amylase, with CDCA and UDCA having the most prominent inhibitory effect. In summary, this study reveals a possible hypoglycemic pathway of RRS metabolites and provides new research perspectives to further explore the therapeutic mechanism of bile acids in T2DM.

From desert flora to cancer therapy: systematic exploration of multi-pathway mechanisms using network pharmacology and molecular modeling approaches

Ovarian cancer, often labeled a "silent killer," remains one of the most compelling and challenging areas of cancer research. In 2019 alone, a staggering 222,240 new cases of ovarian cancer were reported, with nearly 14,170 lives tragically lost to this relentless disease. The absence of effective diagnostic methods, increased resistance to chemotherapy, and the heterogeneous nature of ovarian cancer collectively contribute to the unfavorable prognosis observed in the majority of cases. Thus, there is a pressing need to explore therapeutic interventions that offer superior efficacy and safety, thereby enhancing the survival prospects for ovarian cancer patients. Recognizing this potential, our research synergizes bioinformatics with a network pharmacology approach to investigate the underlying molecular interactions of Saudi Arabian flora (Onopordum heteracanthum, Acacia ehrenbergiana, Osteospermum vaillantii, Cyperus rotundus, Carissa carandas, Carissa spinarum, and Camellia sinensis) in ovarian cancer treatment. At first, phytoconstituents of indigenous flora and their associated gene targets, particularly those pertinent to ovarian cancer, were obtained from open-access databases. Later, the shared targets of plants and diseases were compared to identify common targets. A protein-protein interaction (PPI) network of predicted targets was then constructed for the identification of key genes having the highest degree of connectivity among networks. Following that, a compound-target protein-pathway network was constructed, which uncovered that, namely, hispidulin, stigmasterol, ascorbic acid, octopamine, cyperene, kaempferol, pungenin, citric acid, d-tartaric acid, beta-sitosterol, (-)-epicatechin gallate, and (+)-catechin demonstrably influence cell proliferation and growth by impacting the AKT1 and VEGFA proteins. Molecular docking, complemented by a 20-ns molecular dynamic (MD) simulation, was used, and the binding affinity of the compound was further validated. Molecular docking, complemented by a 20-ns MD simulation, confirmed the binding affinity of these compounds. Specifically, for AKT1, ascorbic acid showed a docking score of -11.1227 kcal/mol, interacting with residues Ser A:240, Leu A:239, Arg A:243, Arg C:2, and Glu A:341. For VEGFA, hispidulin exhibited a docking score of -17.3714 kcal/mol, interacting with Asn A:158, Val A:190, Gln B:160, Ser A:179, and Ser B:176. To sum up, both a theoretical and empirical framework were established by this study, directing more comprehensive research and laying out a roadmap for the potential utilization of active compounds in the formulation of anti-cancer treatments.

Identification of active compounds in Vernonia anthelmintica (L.) willd by targeted metabolome MRM and kaempferol promotes HaCaT cell proliferation and reduces oxidative stress

Introduction: Vernonia anthelmintica (L.) Willd. is a traditional treatment for vitiligo in Xinjiang. However, its therapeutic mechanism remains unclear owing to its complex composition and limited research on its chemical profile. Methods: We employed a targeted metabolome approach, combining selective reaction monitoring/multiple response monitoring (SRM/MRM) with high-performance liquid chromatography and MRM mass spectrometry to quantitatively analyze the flavonoid constituents of Vernonia anthelmintica. We also used network pharmacology and molecular docking to identify potential vitiligo-linked compounds and targets of V. anthelmintica seeds. Additionally, we assessed HaCaT cell proliferation by AAPH-induced, alongside changes in SOD activity and MDA content, following treatment with V. anthelmintica components. Finally, flow cytometry was used to detect apoptosis and ROS levels. Results and Discussion: We identified 36 flavonoid compounds in V. anthelmintica seeds, with 14 compounds exhibiting druggability. AKT1, VEGFA, ESR1, PTGS2, and IL2 have been identified as key therapeutic target genes, with PI3K/AKT signaling being an important pathway. Notably, kaempferol, one of the identified compounds, exhibited high expression in network pharmacology analysis. Kaempferol exhibited a strong binding affinity to important targets. Further, kaempferol enhanced HaCaT cell viability, inhibited apoptosis, reduced MDA levels, suppressed ROS activity, and upregulated SOD activity, increase the expression of cellular antioxidant genes, including HO-1, GCLC, GCLM, Nrf2, NQO1 and Keap1, providing significant protection against oxidative stress damage in vitro. Here, we present the first comprehensive study integrating SRM/MRM approaches and network analysis to identify active flavonoid compounds within V. anthelmintica (L.) Willd. Moreover, we revealed that its active ingredient, kaempferol, offers protection against AAPH-induced damage in keratinocytes, highlighting its potential as a clinical resource.

Multitarget Mechanisms of Monocarbonyl Curcuminoid Analogues against HL-60 Cancer Cells: In Vitro and Network Pharmacology-Based Approach

This study addressed the cytotoxic potential of four compounds: monocarbonyl curcuminoid, ethyl (2E)-2-benzylidene-3-oxobutanoate 1, 1,2-dimethoxy-12-methyl-13H- [1,3] benzodioxolo[5,6-c] phenanthridine 2, 3,5-dibenzyloxybenzyl bromide 3, and (E)-4-(4-chlorobenzylidene)-1-(4-nitrophenyl)hexan-3-one 4. In vitro cytotoxic assays were carried out in HL-60 and BJ cells using the MTT assay along with analysis of apoptosis with the annexin V detection kit. Additional network pharmacology and docking analyses were carried out. In the in vitro assays, compounds 2 and 4 displayed significant antiproliferative effects in HL-60 cells, exhibiting IC50 values of 5.02 and 9.50 μM, respectively. Compound 1 showed no activity, and compound 3 displayed toxicity in BJ cells. In addition, both compounds 2 and 4 induced apoptosis in HL-60 cells. Network pharmacology and docking analyses indicated that compounds 2 and 4 had synergistic effects targeting the CASP3 and PARP1 proteins. Notably, these proteins play pivotal roles in cancer-related pathways. Thus, by modulating these proteins, monocarbonyl curcuminoid has the potential to influence various cancer-related pathways. In summary, our novel findings provide valuable insights into the potential of these compounds to serve as novel anticancer therapeutic agents, warranting further mechanistic studies and clinical exploration.

Network pharmacology and molecular dynamic simulation integrated strategy for the screening of active components and mechanisms of phytochemicals from Datura innoxia on Alzheimer and cognitive decline

Alzheimer's disease (AD) ranks as the most prevalent neurodegenerative disorder with dementia and it accounts for more than 70% of all cases. Despite extensive reporting on the experimental investigation of Datura innoxia (DI) and its phytochemical components in the treatment of AD, the urgent need for elucidation of the principle of multi-mechanism and multi-level treatment of AD remains. In this research, molecular docking and network pharmacology were used to evaluate active compounds and molecular targets of DI for the treatment of AD. The phytochemical compounds of DI were obtained from the Indian Medicinal Plants, Phytochemistry, and Therapeutics (IMPPAT) as well as the Traditional Chinese Medicine System Pharmacology (TCMSP) databases. The screening includes the 28 most abundant components of DI and the Swiss Target Prediction database was used to predict targets of these compounds. The GeneCards database was used to collect AD-related genes. Both DI and AD targets were imported into a Venn diagram, and the 28 overlapped genes were identified as potential DI anti-AD targets. The results showed that Dinoxin B, Meteloidine, Scopoline, and Tropic acid had no effect on AD-related genes. Furthermore, the GO enrichment analysis indicates that DI influences molecular functions and biological processes such as learning or memory and modulation of chemical synaptic transmission as well as the membrane raft and membrane microdomain. The KEGG pathway analysis revealed that the key pathways implicated in DI's anti-AD actions include serotonergic synapse, IL-17 signaling pathway, and AGE-RAGE signaling pathway in diabetic complications. Based on the STRING and Cytoscape network-analysis platforms, the top ten anti-AD core targets include APP, CASP3, IL6, BACE1, IL1B, ACE, PSEN1, GAPDH, GSK3B and ACHE. The molecular docking and molecular dynamic simulation of the top two molecules against the top three target proteins confirmed the strong binding affinity and stability at the docked site. Overall, our findings pave the path for further research into the development and optimization of potential anti-AD agents from DI.Communicated by Ramaswamy H. Sarma.

Network pharmacology integrated with molecular docking reveals the anticancer mechanism of Jasminum sambac Linn. essential oil against human breast cancer and experimental validation by in vitro and in vivo studies

Jasminum sambac L. (J. sambac) belongs to the family Oleaceae and it is an ornamental subtropical evergreen shrub used in traditional treatments of certain ailments and diseases. This study aimed at devising an integrated strategy attempts to evaluate the bioactive components in the J. sambac essential oil (JEO) against human breast cancer. JEO extracted by distillation process and analyzed by GC-MS was subjected to screening of therapeutic components in their allegiance to the drug-likeness index. The utility and efficacy of its molecular mechanism relating to anticancer potential were probed with network pharmacology analysis. Gene ontology, pathway enrichment, and compound-target-pathway network by Cytoscape helped to harp on hub targets and pathways involved in curative action. Drawing from the network data, molecular docking analysis of selected compounds on breast cancer targets was approached. The anti-proliferative study was carried out in MCF-7 and MDA-MB-231 to evaluate the cytotoxicity of JEO. Finally, in vivo anticancer activity was verified using rat models. The results showed MDA-MB-231 cell growth was highly inhibited than the MCF-7 cell line. Alongside this in vitro trial, in situ effectiveness of JEO was evaluated using female Sprague-Dawley rat animal models. In vivo experiments and histopathological analysis showed convincing results in DMBA tumor-induced rats. The larger aim of this study is to identify the potential ingredients of the JEO in cancer apoptosis by integrating network pharmacology and experimental validation achieved to certain extent confers credence to the concept of hiring J. sambac as floral therapy in dealing with the disastrous disease.

Deciphering Multi-target Pharmacological Mechanism of Cucurbita pepo Seeds against Kidney Stones: Network Pharmacology and Molecular Docking Approach

BACKGROUND

Urolithiasis is a prevalent condition with significant morbidity and economic implications. The economic burden associated with urolithiasis primarily stems from medical expenses. Previous literature suggests that herbal plants, including Cucurbita pepo, have lithotriptic capabilities. C. pepo is an annual, herbaceous, widely grown, and monoecious vegetative plant known for its antioxidants, fibers, and fatty acids. Recent studies on C. pepo seeds have shown therapeutic potential in reducing bladder stones and urodynamic illnesses, like kidney stones. However, the precise molecular and pharmacological mechanisms are unclear.

OBJECTIVE

In this research, we employed network pharmacology and molecular docking to examine the active compounds and biological mechanisms of Cucurbita pepo against kidney stones.

METHODS

Active constituents were obtained from previous studies and the IMPPAT database, with their targets predicted using Swiss target prediction. Kidney stone-associated genes were collected from DisGeNET and GeneCards. The active constituent-target-pathway network was constructed using Cytoscape, and the target protein-protein interaction network was generated using the STRING database. Gene enrichment analysis of C. pepo core targets was conducted using DAVID. Molecular docking was performed to identify potential kidney stone-fighting agents.

RESULTS

The findings revealed that Cucurbita pepo contains 18 active components and has 192 potential gene targets, including AR, EGFR, ESR1, AKT1, MAPK3, SRC, and MTOR. Network analysis demonstrated that C. pepo seeds may prevent kidney stones by influencing disease-related signaling pathways. Molecular docking indicated that key kidney stone targets (mTOR, EGFR, AR, and ESR1) effectively bind with active constituents of C. pepo.

CONCLUSION

These findings provide insight into the anti-kidney stone effects of Cucurbita pepo at a molecular level. In conclusion, this study contributes to understanding the potential of Cucurbita pepo in combating kidney stones and lays the foundation for further research.

Network pharmacology based virtual screening of Flavonoids from Dodonea angustifolia and the molecular mechanism against inflammation

Inflammation is a nonspecific immune response against injury caused by a harmful agent that strives to restore tissue function and homeostasis. Dodonaea angustifolia L.f. (Sapindaceae) is a medium-sized shrub used to treat a variety of diseases in traditional medicine. In the current study, integrated network-pharmacology and molecular docking approaches were used to identify the active constituents, their possible targets, signaling pathways, and anti-inflammatory effects of flavonoids from D.angustifolia. D. angustifolia active ingredients were acquired from the Indian Medicinal Plants, Phytochemistry and Therapeutics (IMPPAT), and Traditional Chinese Medicine System Pharmacology (TCMSP) databases. The screening included the ten most prevalent D. angustifolia components, and the SwissTargetPrediction database was utilized to anticipate the targets of these compounds. Anti-inflammatory genes were found using the GeneCards database. The 175 overlapping genes were discovered as prospective D. angustifolia anti-inflammatory targets. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that the overlapped targets were closely related to the major pathogenic processes linked to inflammation, such as response to organonitrogen compound, protein kinase activity, phosphotransferase activity, pI3k-Akt signaling pathway, metabolic pathways, and chemical carcinogenesis. Compound-target-pathway, and protein-protein interaction networks revealed 6-Methoxykaempferol and 5-Hydroxy-7,8 dimethoxyflavone as key compounds, and AKT1, VEGFA, and EGFR as key targets. Furthermore, molecular docking followed by molecular dynamic (MD) simulation of D. angustifolia active ingredients with core proteins fully complemented the binding affinity of these compounds and indicated stable complexes at the docked site. These findings reveal D. angustifolia 's multi-target, multi-compound, and multi-pathway strategies against inflammation. Our study paved the way for further research into the mechanism for developing D. angustifolia -based natural products as alternative therapies for inflammation.

Targeting Melanoma with a phytochemical pool: Tailing Makisterone C

BACKGROUND AND OBJECTIVE

According to World Health Organization, melanoma claims the lives of about 48000 people worldwide each year. The purpose of this study was to identify potential phytochemical pool from Diplazium esculentum against proteins that contribute to melanoma development.

METHODS

The research was carried to locate potentially bioactive molecules and conduct a theoretical analysis of active ingredients from DE to impact melanoma. Network pharmacology, pharmacokinetics, protein network interaction, gene enrichment, survival, and infiltration analysis were conducted. Furthermore, molecular docking and molecular dynamics simulation was carried out for makisterone C-MAPK1, MAPK3, and AKT1 complexes.

RESULTS

The potential phytochemical pool were identified (stigmast-5-en-3-ol, esculentic acid, rutin, and makisterone C) and based on network pharmacology and molecular docking studies, makisterone-C was proposed to be the most promising ingredient. Furthermore, the investigation revealed 14 genes as critical "hubs" involved in combating melanoma that are manipulated by the above-mentioned 4 active ingredients and modulate multiple signaling in melanoma development.

CONCLUSION

This study insights into the potential anti-melanoma effects of phytochemical pool from Diplazium esculentum using network pharmacology analysis, molecular docking, and simulation tailing makisterone C as a lead moiety and suggests the need for makisterone C further evaluation in intervening melanoma progression.

From seeds to survival rates: investigating Linum usitatissimum's potential against ovarian cancer through network pharmacology

Ovarian cancer is a malignant tumor that primarily forms in the ovaries. It often goes undetected until it has spread to the pelvis and abdomen, making it more challenging to treat and often fatal. Historically, natural products and their structural analogues have played a pivotal role in pharmacotherapy, especially for cancer. Numerous studies have demonstrated the therapeutic potential of Linum usitatissimum against ovarian cancer, but the specific molecular mechanisms remain elusive. This study combines data mining, network pharmacology, and molecular docking analysis to pioneer an innovative approach for ovarian cancer treatment by identifying potent phytochemicals. Findings of current study revealed that Apigenin, Vitamin E, Palmitic acid, Riboflavin, Isolariciresinol, 5-Dehydro-avenasterol, Cholesterol, Pantothenic acid, Nicotinic acid, Campesterol, Beta-Sitosterol, Stigmasterol, Daucosterol, and Vitexin suppress tumor growth by influencing AKT1, JUN, EGFR, and VEGFA. Kaplan-Meier survival analysis spotlighted AKT1, JUN, EGFR, and VEGFA as potential diagnostic and prognostic biomarkers for ovarian cancer. However, it is imperative to conduct in vivo and in vitro examinations to ascertain the pharmacokinetics and biosafety profiles, bolstering the candidacy of L. usitatissimum in ovarian cancer therapeutics.

Exploring therapeutic targets and drug candidates for obesity: a combined network pharmacology, bioinformatics approach

The remarkably high prevalence of obesity in Saudi Arabia reflects a global epidemic demanding urgent attention due to its associated health risks. The integration of traditional medicine, a vital cultural aspect, involves the use of medicinal plants to address various diseases, including obesity. This research merges network pharmacology (NP) and bioinformatics to innovate obesity treatment by identifying effective phytochemicals from native plants in the Taif valley. Focusing on six indigenous plants-Senna alexandrina, Capsicum annuum, Zingiber officinale, Curcuma longa, Trigonella foenum-graecum, and Foeniculum vulgare-we conducted preliminary screenings for potential bioactive compounds. We systematically compiled compound data from public databases and reviewed literature, revealing active compounds like apigenin, kaempferol, moupinamide, cyclocurcumin, chrysoeriol, isorhamnetin, rheinanthrone, cyclocurcumin, and riboflavin.Constructing a compound-target genes-obesity network unveiled their significant impact on metabolic regulation and fat accumulation, interacting notably with key proteins AKT1 and PTGS2. Molecular docking and 100 ns Molecular Dynamic (MD) simulations demonstrated robust binding affinity and stability at the docking site. Employing adipocytes as a cellular model, we gauged their viability and response to obesity-related stressors post-treatment with these native plant compounds.In conclusion, Saudi Arabia's indigenous plants hold promise as natural solutions for obesity treatment. This research opens new avenues in the battle against this pervasive health crisis by incorporating the potential of native botanicals.Communicated by Ramaswamy H. Sarma.

Unveiling the multi-target compounds of Rhazya stricta: Discovery and inhibition of novel target genes for the treatment of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a prevalent kidney malignancy with a pressing need for innovative therapeutic strategies. In this context, emerging research has focused on exploring the medicinal potential of plants such as Rhazya stricta. Nevertheless, the complex molecular mechanisms underlying its potential therapeutic efficacy remain largely elusive. Our study employed an integrative approach comprising data mining,network pharmacology,tissue cell type analysis, and molecular modelling approaches to identify potent phytochemicals from R. stricta, with potential relevance for ccRCC treatments. Initially, we collected data on R. stricta's phytochemical from public databases. Subsequently, we integrated this information with differentially expressed genes (DEGs) in ccRCC, which were derived from microarray datasets(GSE16441,GSE66270, and GSE76351). We identified potential intersections between R. stricta and ccRCC targets, which enabled us to construct a compound-genes-pathway network using Cytoscape software. This helped illuminate R. stricta's multi-target pharmacological effects on ccRCC. Moreover, tissue cell type analysis added another layer of insight into the cellular specificity of potential therapeutic targets in the kidney. Through further Kaplan-Meier survival analysis, we pinpointed MMP9,ACE,ERBB2, and HSP90AA1 as prospective diagnostic and prognostic biomarkers for ccRCC. Notably, our study underscores the potential of R. stricta derived compounds-namely quebrachamine,corynan-17-ol, stemmadenine,strictanol,rhazinilam, and rhazimolare-to impede ccRCC progression by modulating the activity of MMP9,ACE,ERBB2, and HSP90AA1 genes. Further, molecular docking and dynamic simulations confirmed the plausible binding affinities of these compounds. Despite these promising findings, we recognize the need for comprehensive in vivo and in vitro studies to further investigate the pharmacokinetics and biosafety profiles of these compounds.

Exploring the multi-gene regulatory molecular mechanism of Saudi Arabian flora against epilepsy based on data mining, network pharmacology and docking analysis

Epilepsy is a chronic neurological disorder marked by recurrent seizures, significantly affecting the population in Saudi Arabia across all age demographics. The global prevalence of active epilepsy is around 6.38/1,000 persons and in the Arabian region, the median prevalence of active epilepsy is 4.4/1,000 persons. However, over 75% of individuals are untreated. Consequently, the development of therapeutic strategies with increased efficacy and safety profiles is essential to improve the survival rate among epilepsy patients. The current study integrates network pharmacology along with Bioinformatics approaches to explore the potential molecular mechanisms of local flora of Saudi Arabia including Solanum incanum, Abrus precatorius, Withania somnifera, and Azadirachta indica in epilepsy treatment. In the preliminary phase, data related to the bioactive components of the local plants and the associated target genes of both these plants and epilepsy were gathered from scientific literature and open-source databases. This data was then analyzed to identify common targets between the plants and ovarian cancer. Based on these common targets, a protein-protein interaction (PPI) network was constructed utilizing the STRING database, which was subsequently incorporated into the Cytoscape software for identification of hub genes based on their degree of connectivity. Lastly, an interplay network depicting the associations between the compounds and the overlapping genes was formulated via Cytoscape, to study the potential network pharmacology implications of these active compounds in relation to ovarian cancer. Following that, a compound-target protein-pathway network was constructed which uncovered that namely abrectorin, genistin, (+)-catechin, precatorine, (+)-ascorbic acid, licoflavanone, skrofulein, stigmasterone, 5,7-Dihydroxy-4'-methoxy-8,3'-di-C-prenylflavanone could potentially be used as antagonists for the therapeutic management of epilepsy by targeting TNF and TP53 proteins. Furthermore, the implementation of molecular docking reinforces the binding affinity of the compound, indicating a robust stability of the forecasted compounds at the docked site. This research lays both a theoretical and experimental groundwork for more profound investigations and establishes a practical method for the strategic employment of active compounds in the development of anti-epileptic therapeutics.

Hypericum perforatum L. and the Underlying Molecular Mechanisms for Its Choleretic, Cholagogue, and Regenerative Properties

Any defects in bile formation, secretion, or flow may give rise to cholestasis, liver fibrosis, cirrhosis, and hepatocellular carcinoma. As the pathogenesis of hepatic disorders is multifactorial, targeting parallel pathways potentially increases the outcome of therapy. Hypericum perforatum has been famed for its anti-depressive effects. However, according to traditional Persian medicine, it helps with jaundice and acts as a choleretic medication. Here, we will discuss the underlying molecular mechanisms of Hypericum for its use in hepatobiliary disorders. Differentially expressed genes retrieved from microarray data analysis upon treatment with safe doses of Hypericum extract and intersection with the genes involved in cholestasis are identified. Target genes are located mainly at the endomembrane system with integrin-binding ability. Activation of α5β1 integrins, as osmo-sensors in the liver, activates a non-receptor tyrosine kinase, c-SRC, which leads to the insertion of bile acid transporters into the canalicular membrane to trigger choleresis. Hypericum upregulates CDK6 that controls cell proliferation, compensating for the bile acid damage to hepatocytes. It induces ICAM1 to stimulate liver regeneration and regulates nischarin, a hepatoprotective receptor. The extract targets the expression of conserved oligomeric Golgi (COG) and facilitates the movement of bile acids toward the canalicular membrane via Golgi-derived vesicles. In addition, Hypericum induces SCP2, an intracellular cholesterol transporter, to maintain cholesterol homeostasis. We have also provided a comprehensive view of the target genes affected by Hypericum's main metabolites, such as hypericin, hyperforin, quercitrin, isoquercitrin, quercetin, kaempferol, rutin, and p-coumaric acid to enlighten a new scope in the management of chronic liver disorders. Altogether, standard trials using Hypericum as a neo-adjuvant or second-line therapy in ursodeoxycholic-acid-non-responder patients define the future trajectories of cholestasis treatment with this product.

Comprehensive exploration of JQ1 and GSK2801 targets in breast cancer using network pharmacology and molecular modeling approaches

JQ1 and GSK2801 are bromo domain inhibitors (BDI) known to exhibit enhanced anti-cancer activity when combined with other agents. However, the underlying molecular mechanisms behind such enhanced activity remain unclear. We used network-pharmacology approaches to understand the shared molecular mechanisms behind the enhanced activity of JQ1 and GSK2801 when used together to treat breast cancer (BC). The gene targets of JQ1 and GSK2801 were intersected with known BC-targets and their putative targets against BC were derived. The key genes were explored through gene-ontology-enrichment, Protein-Protein-Interaction (PPI) networking, survival analysis, and molecular modeling simulations. The genes, CTSB, MAPK14, MET, PSEN2 and STAT3, were found to be common targets for both drugs. In total, 49 biological processes, five molecular functions and 61 metabolic pathways were similarly enriched for JQ1 and GSK2801 BC targets among which several terms are related to cancer: IL-17, TNF and JAK-STAT signaling pathways. Survival analyses revealed that all five putative synergistic targets are significantly associated with survival in BC (log-rank p < 0.05). Molecular modeling studies showed stable binding of JQ1 and GSK2801 against their targets. In conclusion, this study explored and illuminated the possible molecular mechanisms behind the enhanced activity of JQ1 and GSK2801 against BC and suggests synergistic action through their similar BC-targets and gene-ontologies.

Bioinformatics and network pharmacology-based study to elucidate the multi-target pharmacological mechanism of the indigenous plants of Medina valley in treating HCV-related hepatocellular carcinoma

The incidence of Hepatocellular Carcinoma (HCC) in Saudi Arabia is not surprising given the relatively high prevalence of hepatitis C virus (HCV) infection. Hepatitis C is also common in Saudi Arabia with a prevalence rate of 1% to 3% of the population, which further increases the risk of HCC. The incidence of HCC has been increasing in recent years, with HCV-related HCC accounting for a significant proportion of cases. Traditional medicine has long been a part of Saudi Arabian culture, and many medicinal plants have been used for centuries to treat various ailments, including cancer. Following that, this study combines network pharmacology with bioinformatics approaches to potentially revolutionize HCV-related HCC treatment by identifying effective phytochemicals of indigenous plants of Medina valley. Eight indigenous plants including Rumex vesicarius, Withania somnifera, Rhazya stricta, Heliotropium arbainense, Asphodelus fistulosus, Pulicaria incise, Commicarpus grandiflorus, and Senna alexandrina, were selected for the initial screening of potential drug-like compounds. At first, the information related to active compounds of eight indigenous plants was retrieved from public databases and through literature review which was later combined with differentially expressed genes (DEGs) obtained through microarray datasets. Later, a compound-target genes-disease network was constructed which uncovered that kaempferol, rhazimol, beta-sitosterol, 12-Hydroxy-3-keto-bisnor-4-cholenic acid, 5-O-caffeoylquinic acid, 24-Methyldesmosterol, stigmasterone, fucosterol, and withanolide_J decisively contributed to the cell growth and proliferation by affecting ALB and PTGS2 proteins. Moreover, the molecular docking and Molecular Dynamic (MD) simulation of 20 ns well complemented the binding affinity of the compound and revealed strong stability of predicted compounds at the docked site. But the findings were not validated in actual patients, so further investigation is needed to confirm the potential use of selected medicinal plants towards HCV-related HC.

Integration of molecular docking, molecular dynamics and network pharmacology to explore the multi-target pharmacology of fenugreek against diabetes

Fenugreek is an ancient herb that has been used for centuries to treat diabetes. However, how the fenugreek-derived chemical compounds work in treating diabetes remains unclarified. Herein, we integrate molecular docking and network pharmacology to elucidate the active constituents and potential mechanisms of fenugreek against diabetes. First, 19 active compounds from fenugreek and 71 key diabetes-related targets were identified through network pharmacology analysis. Then, molecular docking and simulations results suggest diosgenin, luteolin and quercetin against diabetes via regulation of the genes ESR1, CAV1, VEGFA, TP53, CAT, AKT1, IL6 and IL1. These compounds and genes may be key factors of fenugreek in treating diabetes. Cells results demonstrate that fenugreek has good biological safety and can effectively improve the glucose consumption of IR-HepG2 cells. Pathway enrichment analysis revealed that the anti-diabetic effect of fenugreek was regulated by the AGE-RAGE and NF-κB signalling pathways. It is mainly associated with anti-oxidative stress, anti-inflammatory response and β-cell protection. Our study identified the active constituents and potential signalling pathways involved in the anti-diabetic effect of fenugreek. These findings provide a theoretical basis for understanding the mechanism of the anti-diabetic effect of fenugreek. Finally, this study may help for developing anti-diabetic dietary supplements or drugs based on fenugreek.

The Controversial Roles of Areca Nut: Medicine or Toxin?

Areca nut (AN) is used for traditional herbal medicine and social activities in several countries. It was used as early as about A.D. 25-220 as a remedy. Traditionally, AN was applied for several medicinal functions. However, it was also reported to have toxicological effects. In this review article, we updated recent trends of research in addition to acquire new knowledge about AN. First, the history of AN usage from ancient years was described. Then, the chemical components of AN and their biological functions was compared; arecoline is an especially important compound in AN. AN extract has different effects caused by different components. Thus, the dual effects of AN with pharmacological and toxicological effects were summarized. Finally, we described perspectives, trends and challenges of AN. It will provide the insight of removing or modifying the toxic compounds of AN extractions for enhancing their pharmacological activity to treat several diseases in future applications.

Network pharmacology and molecular docking combined with widely targeted metabolomics to elucidate the potential compounds and targets of Euphorbia helioscopia seeds for the treatment of pulmonary fibrosis

BACKGROUND

The whole herb of Euphorbia helioscopia has been traditionally used for treating pulmonary tuberculosis, malaria, warts, lung cancer and bacillary dysentery for a long time in China. However, E. helioscopia seeds are often discarded and its medicinal value is often ignored, resulting in a waste of resources.

METHOD

In this work, widely targeted metabolomics based on UPLC-ESI-QTRAP-MS/MS methods and metware database (MWDB) were firstly used to identify the chemical compositions of EHS. Besides, network pharmacology, molecular docking and molecular dynamics simulation were performed for elucidating the potential compounds and targets of E. helioscopia seeds for the treatment of pulmonary fibrosis via common database (like TCMSP, Genecards, DAVID, STRING) and common software (like Sybyl, Cytoscape, Pymol and Schrödinger).

RESULT

The results of widely targeted metabolomics showed 231 compounds including 12 categories were identified. The highest content compositions are lipids (33.89%) followed by amino acids and derivatives (21.78%), nucleotides and derivatives (15.73%), as well as the content of functional ingredients like phenolic acids (7.33%), alkaloids (7.03%) and flavonoids (4.51%) are relatively high. Besides, the results of network pharmacology and molecular docking showed that EHS presented anti-pulmonary fibrosis medicinal value through multi-ingredients, multi-targets and multi-pathways approach. Key ingredients including 9-Hydroxy-12-oxo-15(Z)-octadecenoic acid, Nordihydrocapsiate, 1-O-Salicyl-d-glucose, 9-(Arabinosyl)hypoxanthine, Xanthosine and Galangin-7-O-glucoside. Key targets including SRC, HSP90AA1, AKT1, EGFR, JUN, EP300 and VEGFA, and key signaling pathways mainly related to AGE-RAGE, EGFR tyrosine kinase inhibitor resistance, VEGF and HIF-1 signaling pathway. Molecular dynamics simulation showed that HSP90AA1 and 9-Hydroxy-12-oxo-15(Z)-octadecenoic complex (with the highest docking score) have a stable combination effect.

CONCLUSION

In conclusion, this study revealed the chemical compositions of EHS and its anti-pulmonary fibrosis medicinal effect for the first time, it will provide scientific insight for the development of EHS as medicinal resource.

Investigation of the Potential Mechanism of Alpinia officinarum Hance in Improving Type 2 Diabetes Mellitus Based on Network Pharmacology and Molecular Docking

Objective

We used network pharmacology, molecular docking, and cellular analysis to explore the pharmacodynamic components and action mechanism of Alpinia officinarum Hance (A. officinarum) in improving type 2 diabetes mellitus (T2DM).

Methods

The protein-protein interaction (PPI) network, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to predict the potential targets and mechanism of A. officinarum toward improving T2DM. The first 9 core targets and potential active compounds were docked using Discovery Studio 2019. Finally, IR-HepG2 cells and qPCR were applied to determine the mRNA expression of the top 6 core targets of the PPI network.

Results

A total of 29 active ingredients and 607 targets of A. officinarum were obtained. T2DM-related targets overlapped with 176 targets. The core targets of the PPI network were identified as AKT serine/threonine kinase 1 (AKT1), an activator of transcription 3 (STAT3), tumor necrosis factor (TNF), tumor protein p53 (TP53), SRC proto-oncogene, nonreceptor tyrosine kinase (SRC), epidermal growth factor receptor (EGFR), albumin (ALB), mitogen-activated protein kinase 1 (MAPK1), and peroxisome proliferator-activated receptor gamma (PPARG). A. officinarum performs an antidiabetic role via the AGE-RAGE signaling pathway, the HIF-1 signaling pathway, the PI3K-AKT signaling pathway, and others, according to GO and KEGG enrichment analyses. Molecular docking revealed that the binding ability of diarylheptanoid active components in A. officinarum to core target protein was higher than that of flavonoids. The cell experiments confirmed that the A. officinarum extracts improved the glucose uptake of IR-HepG2 cells and AKT expression while inhibiting the STAT3, TNF, TP53, SRC, and EGFR mRNA expression.

Conclusion

A. officinarum Hance improves T2DM by acting on numerous components, multiple targets, and several pathways. Our results lay the groundwork for the subsequent research and broaden the clinical application of A. officinarum Hance.

Revealing the Underlying Mechanism of Acacia Nilotica against Asthma from a Systematic Perspective: A Network Pharmacology and Molecular Docking Study

Acacia Nilotica (AN) has long been used as a folk cure for asthma, but little is known about how AN could possibly modulate this disease. Thus, an in-silico molecular mechanism for AN's anti-asthmatic action was elucidated utilizing network pharmacology and molecular docking techniques. DPED, PubChem, Binding DB, DisGeNET, DAVID, and STRING were a few databases used to collect network data. MOE 2015.10 software was used for molecular docking. Out of 51 searched compounds of AN, eighteen compounds interacted with human target genes, a total of 189 compounds-related genes, and 2096 asthma-related genes were found in public databases, with 80 overlapping genes between them. AKT1, EGFR, VEGFA, and HSP90AB were the hub genes, whereas quercetin and apigenin were the most active components. p13AKT and MAPK signaling pathways were found to be the primary target of AN. Outcomes of network pharmacology and molecular docking predicted that AN might exert its anti-asthmatic effect probably by altering the p13AKT and MAPK signaling pathway.

Integrated network pharmacology and molecular modeling approach for the discovery of novel potential MAPK3 inhibitors from whole green jackfruit flour targeting obesity-linked diabetes mellitus

The current study investigates the effectiveness of phytocompounds from the whole green jackfruit flour methanol extract (JME) against obesity-linked diabetes mellitus using integrated network pharmacology and molecular modeling approach. Through network pharmacology, druglikeness and pharmacokinetics, molecular docking simulations, GO analysis, molecular dynamics simulations, and binding free energy analyses, it aims to look into the mechanism of the JME phytocompounds in the amelioration of obesity-linked diabetes mellitus. There are 15 predicted genes corresponding to the 11 oral bioactive compounds of JME. The most important of these 15 genes was MAPK3. According to the network analysis, the insulin signaling pathway has been predicted to have the strongest affinity to MAPK3 protein, which was chosen as the target. With regard to the molecular docking simulation, the greatest notable binding affinity for MAPK3 was discovered to be caffeic acid (-8.0 kJ/mol), deoxysappanone B 7,3'-dimethyl ether acetate (DBDEA) (-8.2 kJ/mol), and syringic acid (-8.5 kJ/mol). All the compounds were found to be stable inside the inhibitor binding pocket of the enzyme during molecular dynamics simulation. During binding free energy calculation, all the compounds chiefly used Van der Waal's free energy to bind with the target protein (caffeic acid: 102.296 kJ/mol, DBDEA: -104.268 kJ/mol, syringic acid: -100.171 kJ/mol). Based on these findings, it may be inferred that the reported JME phytocompounds could be used for in vitro and in vivo research, with the goal of targeting MAPK3 inhibition for the treatment of obesity-linked diabetes mellitus.

Therapeutic effects of Crataegus monogyna inhibitors against breast cancer

Breast cancer is a silent killer disorder among women and a serious economic burden in healthcare management. Every 19 s, a woman is diagnosed with breast cancer, and every 74 s, a woman worldwide passes away from the disease. Despite the increase in progressive research, advanced treatment approaches, and preventive measures, breast cancer rates continue to increase. This study provides a combination of data mining, network pharmacology, and docking analysis that surely could revolutionize cancer treatment by exploiting prestigious phytochemicals. Crataegus monogyna is a small, rounded deciduous tree with glossy, deeply lobed leaves and flat sprays of cream flowers, followed by dark red berries in autumn. Various studies demonstrated that C. monogyna is therapeutically effective against breast cancer. However, the particular molecular mechanism is still unknown. This study is credited for locating bioactive substances, metabolic pathways, and target genes for breast cancer treatment. According to the current investigation, which examined compound-target genes-pathway networks, it was found that the bioactive compounds of C. monogyna may operate as a viable solution against breast cancer by altering the target genes implicated in the disease pathogenesis. The expression level of target genes was analyzed using GSE36295 microarray data. Docking analysis and molecular dynamic simulation studies further strengthened the current findings by validating the effective activity of the bioactive compounds against putative target genes. In summary, we propose that six key compounds, luteolin, apigenin, quercetin, kaempferol, ursolic acid, and oleanolic acid, contributed to the development of breast cancer by affecting the MMP9 and PPARG proteins. Integration of network pharmacology and bioinformatics revealed C. monogyna's multitarget pharmacological mechanisms against breast cancer. This study provides convincing evidence that C. monogyna might partially alleviate breast cancer and ultimately lays a foundation for further experimental research on the anti-breast cancer activity of C. monogyna.

Molecular mechanism of Ginkgo biloba in treating type 2 diabetes mellitus combined with non-alcoholic fatty liver disease based on network pharmacology, molecular docking, and experimental evaluations

Ginkgo biloba has gained increasing attention owing to its remarkable effects against cardiovascular disease. However, the role of G. biloba in hepatic lipid metabolism disorders in type 2 diabetes mellitus (T2DM) combined with non-alcoholic fatty liver disease (NAFLD) and its underlying mechanisms have not been elucidated. Here, the effective ingredients and mechanisms of action of G. biloba in T2DM combined with NAFLD were investigated via an integrated strategy of network pharmacology and molecular docking. Thirty-four core targets for the alleviation of T2DM combined with NAFLD were identified and retrieved from multiple open-source databases, after validating the ameliorative effect of G. biloba on lipid accumulation in vitro. The targets IL6, IL1B, VEGFA, PTGS2, and CCL2, among others, with high network association values, were screened using Cytoscape. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis showed that 34 compounds derived from G. biloba may exert therapeutic effects via response to molecule of bacterial origin, cellular response to lipid, and response to the hormone. In addition, the AGE-RAGE and IL-17 signaling pathways were predicted to be most significantly affected. Meanwhile, the outcomes of the molecular docking experiment showed that the most effective ingredients in G. biloba showed a strong binding affinity to the potential target active sites. Findings from further in vitro experiments confirmed that G. biloba treatment decreased the level of IL6, IL1B, and VEGFA protein. In conclusion, our findings provided novel insights into the mechanisms underlying the therapeutic effect of G. biloba in T2DM combined with NAFLD. PRACTICAL APPLICATIONS: As a medicinal food plant, G. biloba has been shown to exert benefits in cardiovascular diseases. However, the pharmacological material basis and complex mechanism of action in G. biloba in T2DM combined with NAFLD remain unknown. Here, the mechanism by which G. biloba could ameliorate T2DM combined with NAFLD was investigated, and the potential target and molecular mechanism were explored, through a comprehensive strategy combining network pharmacology and molecular docking. Our findings indicate that G. biloba exerts synergistic effects in treating T2DM combined with NAFLD through multi-ingredients, multi-targets, and multi-pathways; the findings also elucidate the nutritional and therapeutic potential of G. biloba in preventing and treating T2DM combined with NAFLD and provides robust evidence for its clinical application.

Integrated Pangenome Analysis and Pharmacophore Modeling Revealed Potential Novel Inhibitors against Enterobacter xiangfangensis

Enterobacter xiangfangensis is a novel, multidrug-resistant pathogen belonging to the Enterobacter genus and has the ability to acquire resistance to multiple antibiotic classes. However, there is currently no registered E. xiangfangensis drug on the market that has been shown to be effective. Hence, there is an urgent need to identify novel therapeutic targets and effective treatments for E. xiangfangensis. In the current study, a bacterial pan genome analysis and subtractive proteomics approach was employed to the core proteomes of six strains of E. xiangfangensis using several bioinformatic tools, software, and servers. However, 2611 nonredundant proteins were predicted from the 21,720 core proteins of core proteome. Out of 2611 nonredundant proteins, 372 were obtained from Geptop2.0 as essential proteins. After the subtractive proteomics and subcellular localization analysis, only 133 proteins were found in cytoplasm. All cytoplasmic proteins were examined using BLASTp against the virulence factor database, which classifies 20 therapeutic targets as virulent. Out of these 20, 3 cytoplasmic proteins: ferric iron uptake transcriptional regulator (FUR), UDP-2,3diacylglucosamine diphosphatase (UDP), and lipid-A-disaccharide synthase (lpxB) were chosen as potential drug targets. These drug targets are important for bacterial survival, virulence, and growth and could be used as therapeutic targets. More than 2500 plant chemicals were used to molecularly dock these proteins. Furthermore, the lowest-binding energetic docked compounds were found. The top five hit compounds, Adenine, Mollugin, Xanthohumol C, Sakuranetin, and Toosendanin demonstrated optimum binding against all three target proteins. Furthermore, molecular dynamics simulations and MM/GBSA analyses validated the stability of ligand-protein complexes and revealed that these compounds could serve as potential E. xiangfangensis replication inhibitors. Consequently, this study marks a significant step forward in the creation of new and powerful drugs against E. xiangfangensis. Future studies should validate these targets experimentally to prove their function in E. xiangfangensis survival and virulence.

Network Pharmacology and Bioinformatics Approach Reveals the Multi-Target Pharmacological Mechanism of Fumaria indica in the Treatment of Liver Cancer

Liver cancer (LC), a frequently occurring cancer, has become the fourth leading cause of cancer mortality. The small number of reported data and diverse spectra of pathophysiological mechanisms of liver cancer make it a challenging task and a serious economic burden in health care management. Fumaria indica is a herbaceous annual plant used in various regions of Asia to treat a variety of ailments, including liver cancer. Several in vitro investigations have revealed the effectiveness of F. indica in the treatment of liver cancer; however, the exact molecular mechanism is still unrevealed. In this study, the network pharmacology technique was utilized to characterize the mechanism of F. indica on liver cancer. Furthermore, we analyzed the active ingredient-target-pathway network and uncovered that Fumaridine, Lastourvilline, N-feruloyl tyramine, and Cryptopine conclusively contributed to the development of liver cancer by affecting the MTOR, MAPK3, PIK3R1, and EGFR gene. Afterward, molecular docking was used to verify the effective activity of the active ingredients against the prospective targets. The results of molecular docking predicted that several key targets of liver cancer (along with MTOR, EGFR, MAPK3, and PIK3R1) bind stably with the corresponding active ingredient of F. indica. We concluded through network pharmacology methods that multiple biological processes and signaling pathways involved in F. indica exerted a preventing effect in the treatment of liver cancer. The molecular docking results also provide us with sound direction for further experiments. In the framework of this study, network pharmacology integrated with docking analysis revealed that F. indica exerted a promising preventive effect on liver cancer by acting on liver cancer-associated signaling pathways. This enables us to understand the biological mechanism of the anti liver cancer activity of F. indica.

Network Pharmacology Approach for Medicinal Plants: Review and Assessment

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.