A Network Pharmacology Approach to Estimate Potential Targets of the Active Ingredients of Epimedium for Alleviating Mild Cognitive Impairment and Treating Alzheimer's Disease

Elucidating the therapeutic mechanism of betanin in Alzheimer's Disease treatment through network pharmacology and bioinformatics analysis

Betanin, a natural compound with anti-inflammatory and antioxidant properties, has shown promise in mitigating Alzheimer's disease (AD) by reducing amyloid plaque production. Employing network pharmacology, this study aimed to elucidate betanin's therapeutic mechanism in AD treatment. Through integrated analyses utilizing SwissTargetPrediction, STITCH, BindingDB, Therapeutic Target Database (TTD), and OMIM databases, potential protein targets of betanin in AD were predicted. Gene ontology analysis facilitated the identification of 49 putative AD targets. Subsequent gene enrichment and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis revealed associations between these targets and AD. Network pharmacology techniques and molecular docking aided in prioritizing essential genes, with APP, CASP7, ITPR1, CASP8, CASP3, ITPR3, and NF-KB1 emerging as top candidates. The results provide novel insights into betanin's therapeutic efficacy, shedding light on its potential clinical application in AD treatment. By targeting key genes implicated in AD pathology, betanin demonstrates promise as a valuable addition to existing therapeutic strategies. This holistic approach emphasizes the relevance of network pharmacology and bioinformatics analysis in understanding natural chemical disease therapy processes.

Deciphering the multi-functional role of Indian propolis for the management of Alzheimer's disease by integrating LC-MS/MS, network pharmacology, molecular docking, and in-vitro studies

The conventional one-drug-one-disease theory has lost its sheen in multigenic diseases such as Alzheimer's disease (AD). Propolis, a honeybee-derived product has ethnopharmacological evidence of antioxidant, anti-inflammatory, antimicrobial and neuroprotective properties. However, the chemical composition is complex and highly variable geographically. So, to leverage the potential of propolis as an effective treatment modality, it is essential to understand the role of each phytochemical in the AD pathophysiology. Therefore, the present study was aimed at investigating the anti-Alzheimer effect of bioactive in Indian propolis (IP) by combining LC-MS/MS fingerprinting, with network-based analysis and experimental validation. First, phytoconstituents in IP extract were identified using an in-house LC-MS/MS method. The drug likeness and toxicity were assessed, followed by identification of AD targets. The constituent-target-gene network was then constructed along with protein-protein interactions, gene pathway, ontology, and enrichment analysis. LC-MS/MS analysis identified 16 known metabolites with druggable properties except for luteolin-5-methyl ether. The network pharmacology-based analysis revealed that the hit propolis constituents were majorly flavonoids, whereas the main AD-associated targets were MAOB, ESR1, BACE1, AChE, CDK5, GSK3β, and PTGS2. A total of 18 gene pathways were identified to be associated, with the pathways related to AD among the topmost enriched. Molecular docking analysis against top AD targets resulted in suitable binding interactions at the active site of target proteins. Further, the protective role of IP in AD was confirmed with cell-line studies on PC-12, in situ AChE inhibition, and antioxidant assays.

Exploring the molecular mechanism of Xuebifang in the treatment of diabetic peripheral neuropathy based on bioinformatics and network pharmacology

Background

Xuebifang (XBF), a potent Chinese herbal formula, has been employed in managing diabetic peripheral neuropathy (DPN). Nevertheless, the precise mechanism of its action remains enigmatic.

Purpose

The primary objective of this investigation is to employ a bioinformatics-driven approach combined with network pharmacology to comprehensively explore the therapeutic mechanism of XBF in the context of DPN.

Study design and Methods

The active chemicals and their respective targets of XBF were sourced from the TCMSP and BATMAN databases. Differentially expressed genes (DEGs) related to DPN were obtained from the GEO database. The targets associated with DPN were compiled from the OMIM, GeneCards, and DrugBank databases. The analysis of GO, KEGG pathway enrichment, as well as immuno-infiltration analysis, was conducted using the R language. The investigation focused on the distribution of therapeutic targets of XBF within human organs or cells. Subsequently, molecular docking was employed to evaluate the interactions between potential targets and active compounds of XBF concerning the treatment of DPN.

Results

The study successfully identified a total of 122 active compounds and 272 targets associated with XBF. 5 core targets of XBF for DPN were discovered by building PPI network. According to GO and KEGG pathway enrichment analysis, the mechanisms of XBF for DPN could be related to inflammation, immune regulation, and pivotal signalling pathways such as the TNF, TLR, CLR, and NOD-like receptor signalling pathways. These findings were further supported by immune infiltration analysis and localization of immune organs and cells. Moreover, the molecular docking simulations demonstrated a strong binding affinity between the active chemicals and the carefully selected targets.

Conclusion

In summary, this study proposes a novel treatment model for XBF in DPN, and it also offers a new perspective for exploring the principles of traditional Chinese medicine (TCM) in the clinical management of DPN.

Role of Network Pharmacology in Prediction of Mechanism of Neuroprotective Compounds

Network pharmacology is an emerging pioneering approach in the drug discovery process, which is used to predict the therapeutic mechanism of compounds using various bioinformatic tools and databases. Emerging studies have indicated the use of network pharmacological approaches in various research fields, particularly in the identification of possible mechanisms of herbal compounds/ayurvedic formulations in the management of various diseases. These techniques could also play an important role in the prediction of the possible mechanisms of neuroprotective compounds. The first part of the chapter includes an introduction on neuroprotective compounds based on literature. Further, network pharmacological approaches are briefly discussed. The use of network pharmacology in the prediction of the neuroprotective mechanism of compounds is discussed in detail with suitable examples. Finally, the chapter concludes with the current challenges and future prospectives.

The interaction of obesity with susceptible gene polymorphisms in the relationship with mild cognitive impairment

Mild cognitive impairment (MCI) in the elderly is threatening the mental health of the elderly, and the interaction of some factors is worth exploring. This study aims to explore the interactions of obesity and gene polymorphisms in the relationship with MCI. A total of 2555 community resident dwellings include 444 participants who met MCI criteria recruited from the Ningxia province of China. Fourteen MCI-susceptible single nucleotide polymorphisms were detected using a high-throughput mass spectrometer. The interaction was examined by performing the multifactor dimensionality reduction model and unconditional logistic regression model. Logistic regression showed that obesity (OR = 1.42, 95%CI: 1.04-1.94), rs2075650G allele carrying (OR = 17.95, 95%CI: 1.32-244.95), rs11556505T allele carrying (OR = 0.06, 95%CI: 0.01-0.87) were statistically associated with MCI. Multifactor dimensionality reduction analysis showed a strong antagonistic effect between obesity and rs4402960 (Interaction dendrogram between obesity and rs4402960 is red) and a weak synergy effect on rs7901695 (Interaction dendrogram between obesity and rs7901695 is green). The hierarchical analysis showed obesity is a risk factor for MCI in the non-rs4402960T allele carrier group (OR = 1.55, 95%CI: 1.02-2.35). This study found that obesity is an independent risk factor for MCI, and the interactions with MCI-susceptible gene polymorphisms suggest a possible precision preventive intervention program should be developed to reduce the risk of MCI among individuals with obesity in the community.

Cornerstone Cellular Pathways for Metabolic Disorders and Diabetes Mellitus: Non-Coding RNAs, Wnt Signaling, and AMPK

Metabolic disorders and diabetes (DM) impact more than five hundred million individuals throughout the world and are insidious in onset, chronic in nature, and yield significant disability and death. Current therapies that address nutritional status, weight management, and pharmacological options may delay disability but cannot alter disease course or functional organ loss, such as dementia and degeneration of systemic bodily functions. Underlying these challenges are the onset of aging disorders associated with increased lifespan, telomere dysfunction, and oxidative stress generation that lead to multi-system dysfunction. These significant hurdles point to the urgent need to address underlying disease mechanisms with innovative applications. New treatment strategies involve non-coding RNA pathways with microRNAs (miRNAs) and circular ribonucleic acids (circRNAs), Wnt signaling, and Wnt1 inducible signaling pathway protein 1 (WISP1) that are dependent upon programmed cell death pathways, cellular metabolic pathways with AMP-activated protein kinase (AMPK) and nicotinamide, and growth factor applications. Non-coding RNAs, Wnt signaling, and AMPK are cornerstone mechanisms for overseeing complex metabolic pathways that offer innovative treatment avenues for metabolic disease and DM but will necessitate continued appreciation of the ability of each of these cellular mechanisms to independently and in unison influence clinical outcome.

A network-based pharmacological investigation to identify the mechanistic regulatory pathway of andrographolide against colorectal cancer

Traditional cancer treatments have posed numerous obstacles, including toxicity, multiple drug resistance, and financial cost. On the contrary, bioactive phytochemicals used in complementary alternative medicine have recently increased attention due to their potential to modulate a wide range of molecular mechanisms with a less toxic effect. Therefore, we investigated the potential regulatory mechanisms of andrographolide to treat colorectal cancer (CRC) using a network pharmacology approach. Target genes of andrographolide were retrieved from public databases (PharmMapper, Swiss target prediction, Targetnet, STITCH, and SuperPred), while targets related to CRC were retrieved from disease databases (Genecards and DisGeNet) and expression datasets (GSE32323 and GSE8671) were retrieved from gene expression omnibus (GEO). Protein-protein interaction networks (PPI) were generated using STRING and Cytoscape, and hub genes were identified by topology analysis and MCODE. Annotation of target proteins was performed using Gene Ontology (GO) database DAVID and signaling pathway enrichment analysis using the Kyoto Encyclopedia and Genome Database (KEGG). Survival and molecular docking analysis for the hub genes revealed three genes (PDGFRA, PTGS2, and MMP9) were involved in the overall survival of CRC patients, and the top three genes with the lowest binding energy include PDGFRA, MET, and MAPK1. MET gene upregulation and PDGFRA and PTGS2 gene downregulation are associated with the survival of CRC patients, as revealed by box plots and correlation analysis. In conclusion, this study has provided the first scientific evidence to support the use of andrographolide to inhibit cellular proliferation, migration, and growth, and induce apoptosis by targeting the hub genes (PDGFRA, PTGS2, MMP9, MAPK1, and MET) involved in CRC migration and invasion.

Identification of Bioactive Compounds and Potential Mechanisms of Kuntai Capsule in the Treatment of Polycystic Ovary Syndrome by Integrating Network Pharmacology and Bioinformatics

Objective

This study elucidates the potential therapeutic targets and molecular mechanisms of KTC in the treatment of PCOS.

Materials and Methods

Using the Traditional Chinese Medicine System Pharmacology Database and Analysis Platform (TCMSP), the active ingredients and potential targets of KTC were obtained. The Gene Expression Omnibus (GEO) database was used to find differentially expressed genes (DEGs) related to PCOS. Search the CTD, DisGeNet, genecards, NCBI, OMIM, and PharmGKB databases for therapeutic targets related to PCOS. The intersection of potential targets, DEGs, and therapeutic targets was submitted to perform bioinformatics analysis by R language. Finally, the analyses' core targets and their corresponding active ingredients were molecularly docked.

Results

88 potential therapeutic targets of KTC for PCOS were discovered by intersecting the potential targets, DEGs, and therapeutic targets. According to bioinformatics analysis, the mechanisms of KTC treatment for PCOS could be linked to IL-17 signaling route, p53 signaling pathway, HIF-1 signaling pathway, etc. The minimal binding energies of the 5 core targets and their corresponding ingredients were all less than -6.5. Further research found that quercetin may replace KTC in the treatment of PCOS. Discussion and Conclusions. We explored the active ingredients and molecular mechanisms of KTC in the treatment of PCOS and found that quercetin may be the core ingredient of KTC in the treatment of PCOS.

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.

Network Pharmacology-Based Study of the Underlying Mechanisms of Huangqi Sijunzi Decoction for Alzheimer's Disease

Background

Huangqi Sijunzi decoction (HQSJZD) is a commonly used conventional Chinese herbal medicine prescription for invigorating Qi, tonifying Yang, and removing dampness. Modern pharmacology and clinical applications of HQSJZD have shown that it has a certain curative effect on Alzheimer's disease (AD).

Methods

The active components and targets of HQSJZD were searched in the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The genes corresponding to the targets were retrieved using UniProt and GeneCard database. The herb-compound-target network and protein-protein interaction (PPI) network were constructed by Cytoscape. The core targets of HQSJZD were analysed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The main active compounds of HQSJZD were docked with acetylcholinesterase (AChE). In vitro experiments were conducted to detect the inhibitory and neuroprotective effects of AChE.

Results

Compound-target network mainly contained 132 compounds and 255 corresponding targets. The main compounds contained quercetin, kaempferol, formononetin, isorhamnetin, hederagenin, and calycosin. Key targets contained AChE, PTGS2, PPARG, IL-1B, GSK3B, etc. There were 1708 GO items in GO enrichment analysis and 310 signalling pathways in KEGG, mainly including the cAMP signalling pathway, the vascular endothelial growth factor (VEGF) signalling pathway, serotonergic synapses, the calcium signalling pathway, type II diabetes mellitus, arginine and proline metabolism, and the longevity regulating pathway. Molecular docking showed that hederagenin and formononetin were the top 2 compounds of HQSJZD, which had a high affinity with AChE. And formononetin has a good neuroprotective effect, which can improve the oxidative damage of nerve cells.

Conclusion

HQSJZD was found to have the potential to treat AD by targeting multiple AD-related targets. Formononetin and hederagenin in HQSJZD may regulate multiple signalling pathways through AChE, which might play a therapeutic role in AD.