Network analyses in systems pharmacology

Integrated network pharmacology reveals the mechanism of action of Xianlinggubao prescription for inflammation in osteoarthritis

BACKGROUND

Osteoarthritis (OA), a leading cause of disability worldwide, is characterized by complex interactions between cartilage degradation and synovial inflammation. While NSAIDs are the primary treatment, their prolonged use exacerbates gastrointestinal risks and does not alter disease progression. Xianlinggubao (XLGB), an approved Chinese herbal remedy for osteoporosis, has demonstrated promising anti-osteoarthritic effects in preliminary studies. However, its multi-component mechanisms targeting OA-related inflammation require further clarification. This study integrates network pharmacology with experimental validation to investigate XLGB's anti-inflammatory mechanisms in OA.

METHODS

Bioactive compounds of XLGB and their respective targets were sourced from the TCMSP, ETCM, SymMap, and ChEMBL databases. Targets linked to OA-related inflammation were identified through differential expression analysis and by querying OMIM, GeneCards, and PubMed Gene databases. Network pharmacology and bioinformatics approaches were employed to construct compound-target and protein-protein interaction (PPI) networks, enabling the identification of pivotal therapeutic targets. Functional enrichment of these targets was performed using the ClusterProfiler package in R. The binding affinity of compounds to anti-inflammatory OA targets was assessed through molecular docking, dynamics simulations, RT-PCR, and immunofluorescence assays.

RESULTS

Fifty-five bioactive compounds corresponding to 475 XLGB targets and 125 genes involved in OA-related inflammation were identified. PPI network analysis revealed that XLGB may alleviate OA inflammation by modulating key genes, including COX-2, IL-1β, TNF, IL-6, and MMP-9. Molecular simulations indicated strong binding affinities between bioactive compounds in XLGB and these critical targets. Functional enrichment analysis suggested that XLGB's anti-inflammatory action in OA may involve regulation of pathways such as IL-17, TNF, and NF-κB. In vitro experiments further confirmed that XLGB mitigates OA inflammation by modulating these genes, proteins, and signaling pathways.

CONCLUSIONS

Through network pharmacology, this study elucidated the mechanisms of XLGB in OA inflammation, highlighting its modulation of IL-6, IL-1β, TNF-α, PTGS2, MMP-9, and the NF-κB pathway. These findings provide strong support for the clinical application of XLGB in managing OA-related inflammation.

Trends and Pitfalls in the Progress of Network Pharmacology Research on Natural Products

Herbs, used as food and a source of medicine for centuries, have been extensively studied over time for their chemical and pharmacological properties, with two main aims [...].

Network Pharmacology Integrated Experimental Validation Uncover Quercetin as the Key Ingredient of Hedyotis diffusa Anti-BRCA

Hedyotis diffusa, a famous Traditional Chinese Medicine (TCM), has been extensively used clinically for thousands of years. Although the therapeutic effect of Hedyotis diffusa on tumors has attracted wide attention, components, and mechanisms against breast cancer (BRCA) have not been fully understood. The study aims to explore the active components and molecular mechanisms of Hedyotis diffusa against BRCA using network pharmacology combined with experimental validation. The results of network pharmacology indicated that quercetin was the most core component of Hedyotis diffusa. BIRC5, CDK1, FOS, and HSP90AA1 were considered candidate key targets of Hedyotis diffusa against BRCA. KEGG enrichment analysis revealed that multiple cancer-related pathways are enriched, including pathways in cancer, estrogen signaling pathway, and PI3K-AKT signaling pathway, and the like. The results of in vitro experiments showed that quercetin inhibited the proliferation of both MCF-7 cells and MDA-MB-231 cells in a dose-dependent manner. Furthermore, the experimental data demonstrated quercetin may decrease the expression level of BIRC5, CDK1, and HSP90AA1 in MCF-7 cells. Overall, results of the study indicated that quercetin may play a vital role in the anti-BRCA effect of Hedyotis diffusa, and quercetin can affect the expression of BIRC5, CDK1, and HSP90AA1 in MCF-7 cells. This study may provide new evidence for the use of Hedyotis diffusa in the treatment of BRCA.

Exploring common mechanisms of adverse drug reactions and disease phenotypes through network-based analysis

The need for a deeper understanding of adverse drug reaction (ADR) mechanisms is vital for improving drug safety and repurposing. This study introduces Drug Adverse Reaction Mechanism Explainer (DREAMER), a network-based framework that uses a comprehensive knowledge graph to uncover molecular mechanisms underlying ADRs and disease phenotypes. By examining shared phenotypes of drugs and diseases and their effects on protein-protein interaction networks, DREAMER identifies proteins linked to ADR mechanisms. Applied to 649 ADRs, DREAMER identified molecular mechanisms for 67 ADRs, including ventricular arrhythmia and metabolic acidosis, and emphasized pathways like GABAergic signaling and coagulation proteins in personality disorders and intracranial hemorrhage. We further demonstrate the application of DREAMER in drug repurposing and propose sotalol, ranolazine, and diltiazem as candidate drugs to be repurposed for cardiac arrest. In summary, DREAMER effectively detects molecular mechanisms underlying phenotypes, emphasizing the importance of network-based analyses with integrative data for enhancing drug safety and accelerating the discovery of novel therapeutic strategies.

Artificial Intelligence Models and Tools for the Assessment of Drug-Herb Interactions

Artificial intelligence (AI) has emerged as a powerful tool in medical sciences that is revolutionizing various fields of drug research. AI algorithms can analyze large-scale biological data and identify molecular targets and pathways advancing pharmacological knowledge. An especially promising area is the assessment of drug interactions. The AI analysis of large datasets, such as drugs' chemical structure, pharmacological properties, molecular pathways, and known interaction patterns, can provide mechanistic insights and identify potential associations by integrating all this complex information and returning potential risks associated with these interactions. In this context, an area where AI may prove valuable is in the assessment of the underlying mechanisms of drug interactions with natural products (i.e., herbs) that are used as dietary supplements. These products pose a challenging problem since they are complex mixtures of constituents with diverse and limited information regarding their pharmacological properties, especially their pharmacokinetic data. As the use of herbal products and supplements continues to grow, it becomes increasingly important to understand the potential interactions between them and conventional drugs and the associated adverse drug reactions. This review will discuss AI approaches and how they can be exploited in providing valuable mechanistic insights regarding the prediction of interactions between drugs and herbs, and their potential exploitation in experimental validation or clinical utilization.

Adaptogens in Long-Lasting Brain Fatigue: An Insight from Systems Biology and Network Pharmacology

Long-lasting brain fatigue is a consequence of stroke or traumatic brain injury associated with emotional, psychological, and physical overload, distress in hypertension, atherosclerosis, viral infection, and aging-related chronic low-grade inflammatory disorders. The pathogenesis of brain fatigue is linked to disrupted neurotransmission, the glutamate-glutamine cycle imbalance, glucose metabolism, and ATP energy supply, which are associated with multiple molecular targets and signaling pathways in neuroendocrine-immune and blood circulation systems. Regeneration of damaged brain tissue is a long-lasting multistage process, including spontaneously regulating hypothalamus-pituitary (HPA) axis-controlled anabolic-catabolic homeostasis to recover harmonized sympathoadrenal system (SAS)-mediated function, brain energy supply, and deregulated gene expression in rehabilitation. The driving mechanism of spontaneous recovery and regeneration of brain tissue is a cross-talk of mediators of neuronal, microglia, immunocompetent, and endothelial cells collectively involved in neurogenesis and angiogenesis, which plant adaptogens can target. Adaptogens are small molecules of plant origin that increase the adaptability of cells and organisms to stress by interaction with the HPA axis and SAS of the stress system (neuroendocrine-immune and cardiovascular complex), targeting multiple mediators of adaptive GPCR signaling pathways. Two major groups of adaptogens comprise (i) phenolic phenethyl and phenylpropanoid derivatives and (ii) tetracyclic and pentacyclic glycosides, whose chemical structure can be distinguished as related correspondingly to (i) monoamine neurotransmitters of SAS (epinephrine, norepinephrine, and dopamine) and (ii) steroid hormones (cortisol, testosterone, and estradiol). In this narrative review, we discuss (i) the multitarget mechanism of integrated pharmacological activity of botanical adaptogens in stress overload, ischemic stroke, and long-lasting brain fatigue; (ii) the time-dependent dual response of physiological regulatory systems to adaptogens to support homeostasis in chronic stress and overload; and (iii) the dual dose-dependent reversal (hormetic) effect of botanical adaptogens. This narrative review shows that the adaptogenic concept cannot be reduced and rectified to the various effects of adaptogens on selected molecular targets or specific modes of action without estimating their interactions within the networks of mediators of the neuroendocrine-immune complex that, in turn, regulates other pharmacological systems (cardiovascular, gastrointestinal, reproductive systems) due to numerous intra- and extracellular communications and feedback regulations. These interactions result in polyvalent action and the pleiotropic pharmacological activity of adaptogens, which is essential for characterizing adaptogens as distinct types of botanicals. They trigger the defense adaptive stress response that leads to the extension of the limits of resilience to overload, inducing brain fatigue and mental disorders. For the first time, this review justifies the neurogenesis potential of adaptogens, particularly the botanical hybrid preparation (BHP) of Arctic Root and Ashwagandha, providing a rationale for potential use in individuals experiencing long-lasting brain fatigue. The review provided insight into future research on the network pharmacology of adaptogens in preventing and rehabilitating long-lasting brain fatigue following stroke, trauma, and viral infections.

Targeting Ferroptosis in Rare Neurological Disorders Including Pediatric Conditions: Innovations and Therapeutic Challenges

Ferroptosis, characterized by iron dependency and lipid peroxidation, has emerged as a key mechanism underlying neurodegeneration in rare neurological disorders. These conditions, often marked by significant therapeutic gaps and high unmet medical needs, present unique challenges for intervention development. This review examines the involvement of ferroptosis in rare neurological disease pathogenesis, focusing on its role in oxidative damage and neuronal dysfunction. We explore recent pharmacological advancements, including iron chelators, lipid peroxidation blockers, and antioxidant-based strategies, designed to target ferroptosis. While these approaches show promise, challenges such as disease heterogeneity, limited diagnostic tools, and small patient cohorts hinder progress. Furthermore, we discuss the translational and regulatory barriers to implementing ferroptosis-based therapies in clinical practice. By addressing these obstacles and fostering innovative solutions, this review underscores the potential of ferroptosis-targeting strategies to revolutionize treatment paradigms for rare neurological disorders.

Integrating pharmacogenomics and cheminformatics with diverse disease phenotypes for cell type-guided drug discovery

BACKGROUND

Large-scale pharmacogenomic resources, such as the Connectivity Map (CMap), have greatly assisted computational drug discovery. However, despite their widespread use, CMap-based methods have thus far been agnostic to the biological activity of drugs as well as to the genomic effects of drugs in multiple disease contexts. Here, we present a network-based statistical approach, Pathopticon, that uses CMap to build cell type-specific gene-drug perturbation networks and integrates these networks with cheminformatic data and diverse disease phenotypes to prioritize drugs in a cell type-dependent manner.

METHODS

We build cell type-specific gene-drug perturbation networks from CMap data using a statistical procedure we call Quantile-based Instance Z-score Consensus (QUIZ-C). Using these networks and a large-scale disease-gene network consisting of 569 disease signatures from the Enrichr database, we calculate Pathophenotypic Congruity Scores (PACOS) between input gene signatures and drug perturbation signatures and combine these scores with cheminformatic data from ChEMBL to prioritize drugs. We benchmark our approach by calculating area under the receiver operating characteristic curves (AUROC) for 73 gene sets from the Molecular Signatures Database (MSigDB) using target gene expression profiles from the Comparative Toxicogenomics Database (CTD). We validate the drugs predicted in our proofs-of-concept using real-time polymerase chain reaction (qPCR) experiments.

RESULTS

Cell type-specific gene-drug perturbation networks built using QUIZ-C are topologically distinct, reflecting the biological uniqueness of the cell lines in CMap, and are enriched in known drug targets. Pathopticon demonstrates a better prediction performance than solely cheminformatic measures as well as state-of-the-art network and deep learning-based methods. Top predictions made by Pathopticon have high chemical structural diversity, suggesting their potential for building compound libraries. In proof-of-concept applications on vascular diseases, we demonstrate that Pathopticon helps guide in vitro experiments by identifying pathways that are potentially regulated by the predicted therapeutic candidates.

CONCLUSIONS

Our network-based analytical framework integrating pharmacogenomics and cheminformatics (available at https://github.com/r-duh/Pathopticon ) provides a feasible blueprint for a cell type-specific drug discovery and repositioning platform with broad implications for the efficiency and success of drug development.

Network Pharmacology Analysis and In Vitro Validation of the Active Ingredients and Potential Mechanisms of Gynostemma Pentaphyllum Against Esophageal Cancer

BACKGROUND

Esophageal cancer (EC) is one of the deadliest malignancies worldwide. Gynostemma pentaphyllum Thunb. Makino (GpM) has been used in traditional Chinese medicine as a treatment for tumors and hyperlipidemia. Nevertheless, the active components and underlying mechanisms of anti-EC effects of GpM remain elusive.

OBJECTIVE

This study aims to determine the major active ingredients of GpM in the treatment of EC and to explore their molecular mechanisms by using network pharmacology, molecular docking, and in vitro experiments.

METHODS

Firstly, active ingredients and potential targets of GpM, as well as targets of EC, were screened in relevant databases to construct a compound-target network and a protein-protein interaction (PPI) network that narrowed down the pool of ingredients and targets. This was followed by gene ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Next, molecular docking, ADME and toxicity risk prediction, cell viability assays, in vitro scratch assays, Transwell cell invasion assays, and Western blotting analysis were subsequently applied to validate the results of the network analysis.

RESULTS

The screening produced a total of 21 active ingredients and 167 ingredient-related targets for GpM, along with 2653 targets for EC. The PPI network analysis highlighted three targets of interest, namely AKT1, TP53, and VEGFA, and the compound-target network identified three possible active ingredients: quercetin, rhamnazin, and isofucosterol. GO and EKGG indicated that the mechanism of action might be related to the PI3K/AKT signaling pathway as well as the regulation of cell motility and cell migration. Molecular docking and pharmacokinetic analyses suggest that quercetin and isoprostanoid sterols may have therapeutic value and safety for EC. The in vitro experiments confirmed that GpM can inhibit EC cell proliferation, migration, and invasion and suppress PI3K and AKT phosphorylation.

CONCLUSION

Our findings indicate that GpM exerts its anti-tumor effect on EC by inhibiting EC cell migration and invasion via downregulation of the PI3K/AKT signaling pathway. Hence, we have reason to believe that GpM could be a promising candidate for the treatment of EC.

The Potential Compounds in Lansium parasiticum Leaf Extract for Breast Cancer Therapy: Metabolite Profiling, Pharmacological Network Analysis and In Silico Validation

OBJECTIVE

This study aims to identify the compounds found in Lansium parasiticum leaf extract (LPLE) and explain its activity in the context of breast cancer prevention and therapy using a pharmacological network approach and its validation in silico to understand the molecular mechanisms involved.

METHODS

Identification of compounds in LPLE is done using Liquid Chromatography Tandem Mass Spectrophotometry (LC-MS/MS). We also identified absorption and bioavailability profiles using ADMET software. Predictions about the molecular mechanisms of the anti-cancer compounds of LPLE were made through a network pharmacological approach involving devices such as Cytoscape 3.9.1, GeneCards, Disgenet, STRING 2.0.0, the Kyoto Encyclopedia of Genes and Genomes (KEGG) path, and SRplot. Interactions between potential compounds with TP53 receptors were analyzed using site-specific molecular docking, using PyRx Autodock Vina 9.0 and Biovia Discovery Studio.

RESULT

A total of 24 active compounds were successfully identified through LC-MS/MS. The results of the pharmacological network analysis of these compounds showed that there are four substances that have potential against the potential target gene of breast cancer, namely dihydrotestosterone with 8 target genes, Oxoberberine with 8 targets, Pregnenolone with 1 target gene, and Quercetine with 16 targets. The results of in silico validation revealed that the four compounds showed strong affinity to TP53, even higher than their original ligaments.

CONCLUSION

The study successfully identified the active compounds in Lansium parasiticum leaf extract (LPLE) that have potential in the prevention and treatment of breast cancer.

The Mechanism by Which Cyperus rotundus Ameliorates Osteoarthritis: A Work Based on Network Pharmacology

Background

Cyperus rotundus (CR) is widely used in traditional Chinese medicine to prevent and treat a variety of diseases. However, its functions and mechanism of action in osteoarthritis (OA) has not been elucidated. Here, a comprehensive strategy combining network pharmacology, molecular docking, molecular dynamics simulation and in vitro experiments was used to address this issue.

Methods

The bioactive ingredients of CR were screened in TCMSP database, and the potential targets of these ingredients were obtained through Swiss Target Prediction database. Genes in OA pathogenesis were collected through GeneCards, OMIM and DisGeNET databases. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed using DAVID database. STRING database and Cytoscape 3.10 software were used to construct "component-target-pathway" network, and predict the core targets affected by CR. The binding affinity between bioactive components and the core targets was evaluated by molecular docking and molecular dynamics simulation. The therapeutic activity of kaempferol on chondrocytes in inflammatory conditions was verified by in vitro experiments.

Results

Fifteen CR bioactive ingredients were obtained, targeting 192 OA-related genes. A series of biological processes, cell components, molecular functions and pathways were predicted to be modulated by CR components. The core targets of CR in OA treatment were AKT serine/threonine kinase 1 (AKT1), interleukin 1 beta (IL1B), SRC proto-oncogene, non-receptor tyrosine kinase (SRC), BCL2 apoptosis regulator (BCL2), signal transducer and activator of transcription 3 (STAT3), epidermal growth factor receptor (EGFR), hypoxia-inducible factor 1 subunit alpha (HIF1A), matrix metallopeptidase 9 (MMP9), estrogen receptor 1 (ESR1) and PPARG orthologs from vertebrates (PPARG), and the main bioactive ingredients of CR showed good binding affinity with these targets. In addition, kaempferol, one of the CR bioactive components, weakens the effects of IL-1β on the viability, apoptosis and inflammation of chondrocytes.

Conclusion

Theoretically, CR has great potential to ameliorate the symptoms and progression of OA, via multiple components, multiple targets, and multiple downstream pathways.

pyGROMODS: a Python package for the generation of input files for molecular dynamic simulation with GROMACS

The pyGROMODS, an easy-to-use cross-platform python-based package, with a graphical user interface, for the generation of molecular dynamic (MD) input files and running MD simulation (MDS) of proteins, peptides, and protein-ligand complex using GROMACS, is here presented. Four routes, with underlining Python scripts, are implemented in pyGROMODS for the generation of MD input files. They are 'RLmulti' for processing multi-ligand protein complex, 'RLmany' for processing multiple ligands against a single protein target, 'RLsingle' for processing multiple pairs of proteins and ligands, and 'PPmore' for processing peptides or proteins without ligands or non-standard residues. In addition, using the package, the generated input files or appropriate input files from other sources can be uploaded to run MDS with GROMACS. The pyGROMODS is implemented with a unique ability to search the host machine systems for the installation of the required software, update and/or install required Python packages, allow the user to pre-define working directory, and generate unique workflow organization with well-defined folders and files in a well-organized manner. The pyGROMODS, which is released under the MIT License, is freely available for download via the GitHub (https://github.com/Dankem/pyGROMODS) and Zenodo (https://doi.org/10.5281/zenodo.7912747) repositories. The precompiled executables can also be downloaded from Zenodo (https://doi.org/10.5281/zenodo.8087090), and a video tutorial can be downloaded from https://youtu.be/I4OKc6uVx1M.Communicated by Ramaswamy H. Sarma.

Unveiling the therapeutic potential of airpotato yam rhizome against colorectal cancer: a network pharmacology approach

Objective

The objective of this investigation was to elucidate the key active compounds and molecular mechanisms underlying the therapeutic potential of airpotato yam rhizome (AYR) in colorectal cancer (CRC) treatment.

Methods

By utilizing network pharmacology and molecular docking, key targets and signaling pathways of AYR against CRC were predicted and subsequently validated in cellular and mouse xenograft models.

Results

This study initially predicted that quercetin was the primary compound in AYR that might have potential efficacy against CRC and that EGFR and AKT1 could be the main targets of AYR, with the EGF/EGFR-induced PI3K/AKT signaling pathway potentially playing a crucial role in the anti-CRC effects of AYR. Molecular docking analysis further indicated a strong binding affinity between quercetin and EGFR, primarily through hydrogen bonds. Additionally, the AYR-derived drug-containing serum was found to inhibit the PI3K/AKT signaling pathway, as demonstrated by decreased levels of p-PI3K, p-AKT, and BCL2, which ultimately led to enhanced apoptosis of HCT116 and HT29 cells. The potential antitumor effects of AYR were investigated in nude mouse xenograft models of human HCT116 and HT29 cells, in which AYR was found to induce tumor cell apoptosis and inhibit tumor formation.

Conclusion

AYR may promote CRC cell apoptosis by suppressing the PI3K/AKT signaling pathway, which provides a basis for further research on the safe and effective use of AYR for the treatment of CRC.

Network pharmacology and molecular docking-based investigation of monocyte locomotion inhibitory factor attenuates traumatic brain injury by regulating aquaporin 4 expression

Traumatic brain injury (TBI) is a significant cause of disability and mortality worldwide, and effective treatment options are currently limited. Monocyte locomotion inhibitor factor (MLIF), a small molecular pentapeptide, has demonstrated a protective effect against cerebral ischemia. This study aimed to investigate the protective effects of MLIF on TBI and explore its underlying mechanism of action. In animal experiments, we observed that administration of MLIF after TBI reduced brain water content and improved brain edema, suggesting a certain degree of protection against TBI. By utilizing network pharmacology methodologies, we employed target screening techniques to identify the potential targets of MLIF in the context of TBI. As a result, we successfully enriched ten signaling pathways that are closely associated with TBI. Furthermore, using molecular docking techniques, we identified AQP4 as one of the top ten central genes discovered in this study. Eventually, our study demonstrated that MLIF exhibits anti-apoptotic properties and suppresses the expression of AQP4 protein, thus playing a protective role in traumatic brain injury. This conclusion was supported by TUNEL staining and the evaluation of Bcl-2, Bax, and AQP4 protein levels. These discoveries enhance our comprehension of the mechanisms by which MLIF exerts its protective effects and highlight its potential as a promising therapeutic intervention for TBI treatment.

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.

Network pharmacology and in silico approaches to uncover multitargeted mechanism of action of Zingiber zerumbet rhizomes for the treatment of idiopathic pulmonary fibrosis

Background

Idiopathic pulmonary fibrosis (IPF) is a disease with high mortality, and there are only two specific drugs available for therapeutic management with limitations. The study aims to identify comprehensive therapeutic mechanisms of Zingiber zerumbet rhizomes (ZZR) to treat IPF by using network pharmacology followed battery of in silico studies.

Methods

The protein-protein interaction network was developed using Cytoscape to obtain core disease targets involved in IPF and their interactive molecules of ZZR. Based on the pharmacophore properties of phytomolecules from ZZR, the drug targets in IPF were explored. Protein-protein interaction network was built in Cytoscape to screen potential targets and components of ZZR. Molecular docking and dynamics were conducted as an empirical study to investigate the mechanism explored through network pharmacology in relation to the hub targets.

Results

The network analysis conferred kaempferol derivatives that had demonstrated a promising therapeutic effect on the perturbed, robust network hubs of TGF-β1, EGFR, TNF-α, MMP2 & MMP9 reported to alter the biological process of mesenchymal transition, myofibroblast proliferation, and cellular matrix deposition in pulmonary fibrosis. The phytomolecules of ZZR act on two major significant pathways, namely the TGF-β-signaling pathway and the FOXO-signaling pathway, to inhibit IPF. Confirmational molecular docking and dynamics simulation studies possessed good stability and interactions of the protein-ligand complexes by RMSD, RMSF, rGyr, SASA, and principal component analysis (PCA). Validated molecular docking and dynamics simulations provided new insight into exploring the mechanism and multi-target effect of ZZR to treat pulmonary fibrosis by restoring the alveolar phenotype through cellular networking.

Conclusions

Network pharmacology and in silico studies confirm the multitargeted activity of ZZR in the treatment of IPF. Further in vitro and in vivo studies are to be conducted to validate these findings.

DTNPD: A comprehensive database of drugs and targets for neurological and psychiatric disorders

In response to the shortcomings in data quality and coverage for neurological and psychiatric disorders (NPDs) in existing comprehensive databases, this paper introduces the DTNPD database, specifically designed for NPDs. DTNPD contains detailed information on 30 NPDs types, 1847 drugs, 514 drug targets, 64 drug combinations, and 61 potential target combinations, forming a network with 2389 drug-target associations. The database is user-friendly, offering open access and downloadable data, which is crucial for network pharmacology studies. The key strength of DTNPD lies in its robust networks of drug and target combinations, as well as drug-target networks, facilitating research and development in the field of NPDs. The development of the DTNPD database marks a significant milestone in understanding and treating NPDs. For accessing the DTNPD database, the primary URL is http://dtnpd.cnsdrug.com, complemented by a mirror site available at http://dtnpd.lyhbio.com.

Application of artificial intelligence and machine learning in drug repurposing

The purpose of drug repurposing is to leverage previously approved drugs for a particular disease indication and apply them to another disease. It can be seen as a faster and more cost-effective approach to drug discovery and a powerful tool for achieving precision medicine. In addition, drug repurposing can be used to identify therapeutic candidates for rare diseases and phenotypic conditions with limited information on disease biology. Machine learning and artificial intelligence (AI) methodologies have enabled the construction of effective, data-driven repurposing pipelines by integrating and analyzing large-scale biomedical data. Recent technological advances, especially in heterogeneous network mining and natural language processing, have opened up exciting new opportunities and analytical strategies for drug repurposing. In this review, we first introduce the challenges in repurposing approaches and highlight some success stories, including those during the COVID-19 pandemic. Next, we review some existing computational frameworks in the literature, organized on the basis of the type of biomedical input data analyzed and the computational algorithms involved. In conclusion, we outline some exciting new directions that drug repurposing research may take, as pioneered by the generative AI revolution.

Study on the mechanism of action of Saposhnikovia divaricata and its key phytochemical on rheumatoid arthritis based on network pharmacology and bioinformatics

ETHNOPHARMACOLOGICAL RELEVANCE

Saposhnikovia divaricata (Turcz.) Schischk (SD; called "fangfeng" in China) has been widely used in the clinical treatment of rheumatoid arthritis (RA) and has shown well therapeutic effects, but the specific mechanisms of action of its bioactive phytochemicals remain unclear.

AIM OF THE STUDY

This study aimed to investigate the molecular biological mechanism of SD in treating RA through a pharmacology-based strategy. The SD-specific core ingredient Prangenidin was screened for further in-depth study.

MATERIALS AND METHODS

The bioactive phytochemicals of SD and potential targets for the treatment of RA were screened by network pharmacology, and phytochemicals-related parameters such as pharmacology, and toxicology were evaluated. The protein interaction network was established to screen the core targets, and the correlation between the core targets and RA was further validated by bioinformatics strategy. Finally, molecular docking of core components and corresponding targets was performed. The in vitro experiments were performed to elucidate the regulation of Prangenidin on MH7A cells and on the PI3K/AKT pathway, and the in vivo therapeutic effect of Prangenidin was validated in collagen-induced arthritis (CIA) mice.

RESULTS

A total of 18 bioactive phytochemicals and 66 potential target genes intersecting with the screened RA disease target genes were identified from SD. Finally, core ingredients such as wogonin, beta-sitosterol, 5-O-Methylvisamminol, and prangenidin and core targets such as PTGS2, RELA, and AKT1 were obtained. The underlying mechanism of SD in treating RA might be achieved by regulating pathways such as PI3K/AKT, IL-17 pathway, apoptosis, and multiple biological processes to exert anti-inflammatory and immunomodulatory effects. Molecular docking confirmed that all core ingredients and key targets had great docking activity. Prangenidin inhibited viability, migration, and invasion, and induced apoptosis in MH7A cells. Prangenidin also reduced the production of IL-1β, IL-6, IL-8, MMP-1, and MMP-3. Molecular analysis showed that Prangenidin exerts its regulatory effect on MH7A cells by inhibiting PI3K/AKT pathway. Treatment with Prangenidin ameliorated synovial inflammation in the joints of mice with CIA.

CONCLUSION

Our findings provide insights into the therapeutic effects of SD on RA, successfully predicting the effective ingredients and potential targets, which could suggest a novel theoretical basis for further exploration of its molecular mechanisms. It also revealed that Prangenidin inhibited viability, migration, invasion, cytokine, and MMPs expression, and induced apoptosis in RA FLSs via the PI3K/AKT pathway.

Decoding the conformational binding of drug mixtures on ovalbumin: An integrated multimodal network

This research addresses the crucial necessity for a deeper understanding of the binding interactions between surfactants and proteins, with a specific focus on ovalbumin. Considering ovalbumin's role in diverse biochemical processes, it remains a subject of significant interest for drug discovery and design. To fill existing knowledge gaps, we investigated the binding interaction between dicloxacillin and cetyltrimethylammonium bromide (CTAB) on ovalbumin, employing a comprehensive approach that combines computational modeling with experimental validations. Using the ezPocket tool, the computational phase predicted ten relevant binding sites on ovalbumin's surface. The isobologram combination index (CI) heatmap strongly suggested a complex interplay of antagonistic and synergistic effects. Besides, a conformational drug-drug interaction network was proposed to explore the stability of the surfactant mixture within specific binding sites of ovalbumin, revealing a dynamic landscape of suggested antagonist effects. Experimental validations through UV-vis, Fluorescence, and circular dichroism (CD) spectroscopy further corroborated the computational findings, confirming the formation of stable complexes. Finally, this study not only advances our comprehension of ovalbumin's interactions with surfactants but also offers a multidimensional perspective and an advanced methodological framework for efficient therapeutic strategies, opening new avenues for future applications in drug development and applied biochemistry.

Systems pharmacology and multi-scale mechanism of Enicostema axillare bioactives in treating Alzheimer disease

As a progressive neurological disease with increased morbidity and mortality, Alzheimer Disease (AD) is characterized by neuron damage that controls memory and mental functions. Enicostema axillare (EA), an herb with a history of combativeness and effectiveness in treating Rheumatoid Arthritis, Cancer, and Diabetes, is used in Indian folk medicine from a holistic point of view. Though the herb is used for many illnesses, the molecular mechanism of its bioactive on AD has not been deciphered by intricate research. A unique pharmacology approach based on ADME drug screening and targeting, pathway enrichment (GO and KEGG), and network pharmacology, was established to explore the molecular mechanisms of E. axillare (EA) bioactive compounds for the treatment of AD. In brief, we bring to light the three active compounds of EA and seven potential molecular targets of AD, which are mainly implicated in four signaling pathways, i.e., MAPK, Apoptosis, neurodegeneration, and the TNF pathway. Moreover, the network analysis of the active compounds, molecular targets, and their pathways reveals the pharmacological nature of the compounds. Further, molecular docking studies were carried out to explore the interactions between the EA bioactive compounds and the targets and examine the binding affinity. The outcome of the work reflects the potential therapeutic effects of the compounds for treating AD through the modulation of the key proteins, which further corroborates the reliability of our network pharmacology analysis. This study not only helps in understanding the molecular mechanism of the drugs but also helps in finding and sorting new drugs for the treatment of AD, and other complex diseases through modern medicine.

A network pharmacology integrated serum pharmacochemistry strategy for uncovering efficacy of YXC on hepatocellular carcinoma

ETHNOPHARMACOLOGICAL RELEVANCE

The YangzhengXiaoji capsule (YXC) has a wide range of applications as effective traditional Chinese medicine (TCM) preparation for hepatocellular carcinoma (HCC) in China. However, the potential bioactive components and the mechanisms are yet unclear.

AIM OF THE STUDY

The treatment mechanism of YXC on HCC using a network pharmacology integrated serum pharmacochemistry strategy to investigate associated targets and pathways.

MATERIALS AND METHODS

We utilised HPLC-Q-TOF-MS/MS technology to identify components of the serum samples from both the model group and the YXC (H) group serum, which were collected from nude mice with orthotopic liver tumours. Following this, we conducted compound-target prediction and identified the overlap between the target genes in the YXC group and the oncogenes associated with HCC. The anticancer mechanisms of YXC were investigated by creating a compound-target-pathway network using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) analysis. The anticancer efficacy was evaluated in vitro and in vivo. Also, potential predictive targets and pathways associated with YXC in HCC treatment were assessed by western blotting.

RESULTS

The YXC (H) serum had 47 bioactive compounds compared to other models, and identified 173 specific target genes. Using the compound-target-disease network, 141 possible target genes were identified. The KEGG pathway analysis revealed vital enrichment of pathways associated with HCC, including regulating Oncology related pathways of inflammation, immunity, apoptosis, and necrosis biological processes. YXC significantly inhibited HCC cell growth in vitro and in vivo. After YXC treatment, western blotting detected alterations in the p53/Bcl-2/Bax/Caspase-3 and PI3K/Akt pathways.

CONCLUSIONS

YXC can inhibit HCC development and advancement by a variety of components, targets and pathways, especially apoptosis-induction.

Unraveling the mechanisms of Fenugreek seed for managing different gynecological disorders: steroidal saponins and isoflavones revealed as key bioactive metabolites

This study employed network pharmacology-based analysis and reverse molecular docking to investigate the molecular targets and pathways associated with gynecological disorders, particularly those related to steroidal hormones and their receptors, and the potential therapeutic effects of fenugreek (Trigonella foenum-graecum L.) constituents. The STITCH 5.0 database was utilized to identify potential molecular targets, and a compound-target network was constructed. The main targets associated with gynecological disorders included estrogen receptor beta (ESR2), estrogen-related receptor gamma (GPER1), oxytocin receptor (OXTR), progesterone receptor (PGR), prolactin receptor (PRLR), and several enzymes involved in sex hormone biosynthesis. Additionally, network topological analysis revealed that specific compounds, such as quercetin, luteolin, genistein, and vitexin, had significant interactions with the identified targets. Reverse molecular docking analysis confirmed the interactions between the identified compounds and target proteins where quercetin, luteolin, genistein, 4'-methylgenistein, trigoneoside IIB, diosgenin, and vitexin possessed the highest combined docking scores, indicating their multi-target nature. The results highlighted the potential of steroidal saponins, isoflavones, and flavones as active constituents of fenugreek with implications for lactation, reproductive processes, and estrogenic activity. The chemical profiling of saponin-enriched and flavonoid-enriched fractions using UPLC/MS/MS further supported the presence of these bioactive compounds. In an animal model study, the steroidal saponins-enriched fraction of fenugreek seed exhibited a significant increase in the body weight of lactating female rats and serum prolactin levels while the flavonoids-enriched fraction showed an increase in serum estradiol levels and improved the histological structure of ovaries.

Integrated Network Pharmacology Approach to Evaluate Bioactive Phytochemicals of Acalypha indica and Their Mechanistic Actions to Suppress Target Genes of Tuberculosis

Mycobacterium tuberculosis is responsible for tuberculosis (TB) all over the world. Despite tremendous advancements in biomedical research, new treatment approaches, and preventive measures, TB incidence rates continue to ascend. The herbaceous plant Acalypha indica, also known as Indian Nettle, belongs to the Euphorbiaceae family and is known as one of the most important sources of medicines and pharmaceuticals for the medical therapy for a range of ailments. However, the precise molecular mechanism of its therapeutic action is still unknown. In this study, an integrated network pharmacology approach was employed to explore the potential mechanism of A. indica phytochemicals against TB. The active chemical components of A. indica were collected from two independent databases and published sources, whereas SwissTargetPrediction was used to identify the target genes of these phytochemicals. GeneCards and DisGeNET databases were employed to retrieve tuberculosis-related genes and variants. Following the evaluation of overlapped genes, gene enrichment analysis and PPI network analysis were performed using the DAVID and STRING databases, respectively. Later, to identify the potential target(s) for the disease, molecular docking was performed. A. indica revealed 9 active components with 259 potential therapeutic targets; TB attributed 694 intersecting genes from the two data sets; and both TB and A. indica overlapped 44 potential targets. The in-depth analysis based on the degree revealed that AKT1 and EGFR formed the foundation of the PPI network. Moreover, docking analysis followed by molecular dynamics simulations revealed that phytosterol and stigmasterol have higher binding affinities to AKT1 and EGFR to suppress tuberculosis. This study provides a convincing proof that A. indica can be exploited to target TB after experimental endorsement; further, it lays the framework for more experimental research on A. indica's anti-TB activity.

Rebaudioside B Attenuates Lung Ischemia-reperfusion Injury Associated Apoptosis and Inflammation

OBJECTIVE

At present, no proven effective treatment is available for Lung Ischemiareperfusion Injury (LIRI). Natural compounds offer promising prospects for developing new drugs to address various diseases. This study sought to explore the potential of Rebaudioside B (Reb B) as a treatment compound for LIRI, both in vivo and in vitro.

METHODS

This study involved utilizing the human pulmonary alveolar cell line A549, consisting of epithelial type II cells, subjected to Oxygen-glucose Deprivation/recovery (OGD/R) for highthroughput in vitro cell viability screening. The aim was to identify the most promising candidate compounds. Additionally, an in vivo rat model of lung ischemia-reperfusion was employed to evaluate the potential protective effects of Reb B.

RESULTS

Through high-throughput screening, Reb B emerged as the most promising natural compound among those tested. In the A549 OGD/R models, Reb B exhibited a capacity to enhance cell viability by mitigating apoptosis. In the in vivo LIRI model, pre-treatment with Reb B notably decreased apoptotic cells, perivascular edema, and neutrophil infiltration within lung tissues. Furthermore, Reb B demonstrated its ability to attenuate lung inflammation associated with LIRI primarily by elevating IL-10 levels while reducing levels of IL-6, IL-8, and TNF-α.

CONCLUSION

The comprehensive outcomes strongly suggest Reb B's potential as a protective agent against LIRI. This effect is attributed to its inhibition of the mitochondrial apoptotic pathway and its ability to mitigate the inflammatory response.

Integrating network pharmacology and experimental verification to investigate the pharmacological mechanisms of Buzhong Yiqi decoction in the treatment of non-small cell lung cancer

Among all types of cancers, non-small cell lung cancer (NSCLC) exhibits the highest mortality rate with a five-year survival rate below 17% for patients. The Buzhong Yiqi decoction (BZYQD), traditional Chinese medicine (TCM) formula, has been reported to exhibit clinical efficacy in the treatment of NSCLC. Nevertheless, the underlying molecular mechanism remains elusive. This study aimed to assess the mechanistic actions exerted by BZYQD against NSCLC using network pharmacological analysis and experimental validation. The public databases were searched for active compounds in BZYQD, their potential targets, and NSCLC-related targets. The protein-protein interaction (PPI) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to predict the core targets and signaling pathways of BZYQD against NSCLC. After screening, this study validated the results of predictions through in vitro experiments and public databases. We found 192 common targets between BZYQD and NSCLC. KEGG analysis showed that the anti-NSCLC effects of BZYQD were mediated through the PI3K-AKT signaling pathway. The results of in vitro experiment indicated that BZYQD could inhibit cell viability and proliferation of A549 and H1299 cells apart from inducing cell apoptosis. In addition, western blot results substantiated that BZYQD could treat NSCLC by inhibiting the activation of the PI3K-AKT signaling pathway. The current study investigated the pharmacological mechanism of BZYQD against NSCLC via network pharmacology and in vitro analyses. Overall, the results revealed that BZYQD could be a promising therapeutic agent for the treatment of NSCLC in the future. Still, more experimental investigations are needed to confirm the applicability of BZYQD for clinical trials.

The Role of Emodin in the Treatment of Bladder Cancer Based on Network Pharmacology and Experimental Verification

BACKGROUND AND PURPOSE

Emodin, a compound derived from rhubarb and various traditional Chinese medicines, exhibits a range of pharmacological actions, including antiinflammatory, antiviral, and anticancer properties. Nevertheless, its pharmacological impact on bladder cancer (BLCA) and the underlying mechanism are still unclear. This research aimed to analyze the pharmacological mechanisms of Emodin against BLCA using network pharmacology analysis and experimental verification.

METHODS

Initially, network pharmacology was employed to identify core targets and associated pathways affected by Emodin in bladder cancer. Subsequently, the expression of key targets in normal bladder tissues and BLCA tissues was assessed by searching the GEPIA and HPA databases. The binding energy between Emodin and key targets was predicted using molecular docking. Furthermore, in vitro experiments were carried out to confirm the predictions made with network pharmacology.

RESULTS

Our analysis identified 148 common genes targeted by Emodin and BLCA, with the top ten target genes including TP53, HSP90AA1, EGFR, MYC, CASP3, CDK1, PTPN11, EGF, ESR1, and TNF. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses indicated a significant correlation between Emodin and the PI3KAKT pathway in the context of BLCA. Molecular docking investigations revealed a strong affinity between Emodin and critical target proteins. In vitro experiments demonstrated that Emodin inhibits T24 proliferation, migration, and invasion while inducing cell apoptosis. The findings also indicated that Emodin reduces both PI3K and AKT protein and mRNA expression, suggesting that Emodin may mitigate BLCA by modulating the PI3K-AKT signaling pathway.

CONCLUSION

This study integrates network pharmacology with in vitro experimentation to elucidate the potential mechanisms underlying the action of Emodin against BLCA. The results of this research enhance our understanding of the pharmacological mechanisms by which Emodin may be employed in treating BLCA.

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.

Carbazole derivatives as promising competitive and allosteric inhibitors of human serotonin transporter: computational pharmacology

The human serotonin transporters (hSERTs) are neurotransmitter sodium symporters of the aminergic G protein-coupled receptors, regulating the synaptic serotonin and neuropharmacological processes related to neuropsychiatric disorders, notably, depression. Selective serotonin reuptake inhibitors (SSRIs) such as fluoxetine and (S)-citalopram are competitive inhibitors of hSERTs and are commonly the first-line medications for major depressive disorder (MDD). However, treatment-resistance and unpleasant aftereffects constitute their clinical drawbacks. Interestingly, vilazodone emerged with polypharmacological (competitive and allosteric) inhibitions on hSERTs, amenable to improved efficacy. However, its application usually warrants adjuvant/combination therapy, another subject of critical adverse events. Thus, the discovery of alternatives with polypharmacological potentials (one-drug-multiple-target) and improved safety remains essential. In this study, carbazole analogues from chemical libraries were explored using docking and molecular dynamics (MD) simulation. Selectively, two IBScreen ligands, STOCK3S-30866 and STOCK1N-37454 predictively bound to the active pockets and expanded boundaries (extracellular vestibules) of the hSERTs more potently than vilazodone and (S)-citalopram. For instance, the two ligands showed docking scores of -9.52 and -9.59 kcal/mol and MM-GBSA scores of -92.96 and -65.66 kcal/mol respectively compared to vilazodone's respective scores of -7.828 and -59.27 against the central active site of the hSERT (PDB 7LWD). Similarly, the two ligands also docked to the allosteric pocket (PDB 5I73) with scores of -8.15 and -8.40 kcal/mol and MM-GBSA of -96.14 and -68.46 kcal/mol whereas (S)-citalopram has -6.90 and -69.39 kcal/mol respectively. The ligands also conferred conformational stability on the receptors during 100 ns MD simulations and displayed interesting ADMET profiles, representing promising hSERT modulators for MDD upon experimental validation.Communicated by Ramaswamy H. Sarma.

Introducing Matrix Metalloproteinases as Crucial Targets for Intra-articular Laser Therapy in Patients with Synovial Fluid of Knee Osteoarthritis

Background

Many elder people have knee osteoarthritis (OA). The patients are faced with pain and disability in movement. Given the challenging lifestyle of the patients, finding an efficient therapy approach is necessary. Since low-level laser therapy applies to the treatment of many diseases, it seems it can be a suitable option for the treatment of knee OA. The present study aimed to evaluate the molecular mechanism of laser therapy on knee OA via a protein expression change study.

Methods

The present study examines the gene expression profile of patients with OA in the knee using bioinformatics. The protein expression change profile of synovial fluid of knee OA patients is extracted from the literature and is analyzed based on the rate of expression and interactions between the differentially expressed proteins (DEPs). The results are compared with the DEPs of similar tissue of the treated knee OA patients (from published documents) after laser therapy.

Results

Apolipoprotein B (APOB) and matrix metallopeptidase 2 (MMP2) were determined as the hub bottlenecks of the protein-protein interaction (PPI) network of synovial fluid of knee OA patients. MMP2, complement 5, transthyretin, and apolipoprotein A-1 from laser-treated patients were related to the PPI network of knee OA patients. The reduction of Interleukin-6 activity was highlighted as a critical event as a function of laser on the human body.

Conclusion

In conclusion, it was noted that the main phenomenon associated with laser therapy-induced improvement in the condition of knee OA patients is the downregulation of MMP2.

Exploring the mechanism of ellagic acid against gastric cancer based on bioinformatics analysis and network pharmacology

Ellagic acid (EA) is a natural polyphenolic compound. Recent studies have shown that EA has potential anticancer properties against gastric cancer (GC). This study aims to reveal the potential targets and mechanisms of EA against GC. This study adopted methods of bioinformatics analysis and network pharmacology, including the weighted gene co-expression network analysis (WGCNA), construction of protein-protein interaction (PPI) network, receiver operating characteristic (ROC) and Kaplan-Meier (KM) survival curve analysis, Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, molecular docking and molecular dynamics simulations (MDS). A total of 540 EA targets were obtained. Through WGCNA, we obtained a total of 2914 GC clinical module genes, combined with the disease database for screening, a total of 606 GC-related targets and 79 intersection targets of EA and GC were obtained by constructing Venn diagram. PPI network was constructed to identify 14 core candidate targets; TP53, JUN, CASP3, HSP90AA1, VEGFA, HRAS, CDH1, MAPK3, CDKN1A, SRC, CYCS, BCL2L1 and CDK4 were identified as the key targets of EA regulation of GC by ROC and KM curve analysis. The enrichment analysis of GO and KEGG pathways of key targets was performed, and they were mainly enriched in p53 signalling pathway, PI3K-Akt signalling pathway. The results of molecular docking and MDS showed that EA could effectively bind to 13 key targets to form stable protein-ligand complexes. This study revealed the key targets and molecular mechanisms of EA against GC and provided a theoretical basis for further study of the pharmacological mechanism of EA against GC.

The Potential of Eleutherine bulbosa in Inducing Apoptosis and Inhibiting Cell Cycle in Breast Cancer: A Network Pharmacology Approach and In Vitro Experiments

OBJECTIVE

The objective of this study was to evaluate the potential and mechanisms of phytochemicals in Eleutherine bulbosa (EBE) in inducing apoptosis and inhibiting the cell cycle in breast cancer through a network pharmacology approach and in vitro validation.

METHODS

This research employed a literature review approach to identify active anti-cancer compounds and utilized a network pharmacology approach to predict the mechanisms of action of EBE compounds in breast cancer. In addition, in vitro experiments were conducted using MTT method to evaluate the effects of EBE on the cytotoxicity of T47D cells, and the flow cytometry method was employed to determine the impact of EBE on apoptosis and the cell cycle.

RESULTS

The network pharmacology analysis revealed that EBE had an impact on 42 genes involved in breast cancer, including 23 important target genes implicated in the pathophysiology of breast cancer. Pathway analysis using the KEGG database showed a close association between EBE and crucial signaling pathways in breast cancer, including P53 signaling pathway, MAPK signaling pathway, PI3K-Akt signaling pathway, apoptosis and cell cycle. In vitro experiments demonstrated that EBE exhibited moderate anti-cancer activity. Furthermore, EBE demonstrated significant potential in inducing apoptosis in breast cancer cells, with a percentage of apoptotic cells reaching 93.6%. Additionally, EBE was observed to disrupt the cell cycle, leading to a significant increase in the sub G1 and S phases, and a significant decrease in the G2-M and G1 phases.

CONCLUSION

EBE has the potential to be an anti-cancer agent through various mechanisms, including apoptosis induction and cell cycle inhibition in breast cancer cells. These findings provide new insights into the potential of EBE as an alternative treatment for breast cancer.

The potential effect and mechanism of Saikosaponin A against gastric cancer

BACKGROUND

Saikosaponin A (SSA) shows a series of pharmacological activities, such as anti-inflammatory, antioxidant and antitumor. However, there is a lack of comprehensive research or sufficient evidence regarding the efficacy of SSA in treating gastric cancer (GC), and the specific mechanisms by which it inhibits GC growth and progression are still not fully understood.

METHODS

MTT and clonogenic assays were employed to detect the effect of SSA on the proliferation of GC cells. Bioinformatics predicted the SSA targets in the treatment of GC. The core genes and the underlying mechanism of SSA in anti-GC were obtained by analyzing the intersecting targets; molecular docking and Western blot were used to check the reliability of core genes. Flow cytometry was used to analyze apoptosis and cell cycle in GC cells treated with varying concentrations of SSA. Western blot was employed to detect the expression levels of related proteins.

RESULTS

SSA significantly blocked GC cells in the S phase of the cell cycle and induced apoptosis to suppress the proliferation of GC cells. Network pharmacology revealed that the underlying mechanisms through which SSA acts against GC involve the modulation of several signaling pathways, including the PI3K-Akt, MAPK, RAS, and T-cell signaling pathways. Molecular docking showed pivotal target genes with a high affinity to SSA, including STAT3, MYC, TNF, STAT5B, Caspase-3 and SRC. Furthermore, western blot results revealed that SSA significantly increased the protein levels of Bax and Cleaved Caspase-3, whereas decreased the expression levels of p-JAK, p-STAT3, MYC, Bcl-2, p-PI3K, p-AKT and p-mTOR, confirming that the reliability of hub targets and SSA could promote GC cell apoptosis by suppressing PI3K/AKT/mTOR pathway.

CONCLUSIONS

The results suggest that SSA has the ability to trigger apoptosis in GC cells by blocking the PI3K/AKT/mTOR pathway. These findings highlight the potential of SSA as a promising natural therapeutic agent for the treatment of GC.

Network pharmacology and molecular docking to explore Polygoni Cuspidati Rhizoma et Radix treatment for acute lung injury

BACKGROUND

Polygoni Cuspidati Rhizoma et Radix (PCRR), a well-known traditional Chinese medicine (TCM), inhibits inflammation associated with various human diseases. However, the anti-inflammatory effects of PCRR in acute lung injury (ALI) and the underlying mechanisms of action remain unclear.

AIM

To determine the ingredients related to PCRR for treatment of ALI using multiple databases to obtain potential targets for fishing.

METHODS

Recognized and candidate active compounds for PCRR were obtained from Traditional Chinese Medicine Systems Pharmacology, STITCH, and PubMed databases. Target ALI databases were built using the Therapeutic Target, DrugBank, DisGeNET, Online Mendelian Inheritance in Man, and Genetic Association databases. Network pharmacology includes network construction, target prediction, topological feature analysis, and enrichment analysis. Bioinformatics resources from the Database for Annotation, Visualization and Integrated Discovery were utilized for gene ontology biological process and Kyoto Encyclopedia of Genes and Genomes network pathway enrichment analysis, and molecular docking techniques were adopted to verify the combination of major active ingredients and core targets.

RESULTS

Thirteen bioactive compounds corresponding to the 433 PCRR targets were identified. In addition, 128 genes were closely associated with ALI, 60 of which overlapped with PCRR targets and were considered therapeutically relevant. Functional enrichment analysis suggested that PCRR exerted its pharmacological effects in ALI by modulating multiple pathways, including the cell cycle, cell apoptosis, drug metabolism, inflammation, and immune modulation. Molecular docking results revealed a strong associative relationship between the active ingredient and core target.

CONCLUSION

PCRR alleviates ALI symptoms via molecular mechanisms predicted by network pharmacology. This study proposes a strategy to elucidate the mechanisms of TCM at the network pharmacology level.

Identification of potent target and its mechanism of action of Tripterygium wilfordii Hook F in the treatment of lupus nephritis

AIM

The Chinese anti-rheumatic herbal remedy Tripterygium wilfordii Hook F (TWHF) has been widely shown to be effective in treating lupus nephritis (LN), but the therapeutic targets and mechanisms of action are still unclear. In this study, we aimed to combine mRNA expression profile analysis and network pharmacology analysis to screen the pathogenic genes and pathways involved in LN and to explore the potential targets of TWHF in the treatment of LN.

METHODS

The mRNA expression profiles of LN patients were used to screen differentially expressed genes (DEGs) and to predict associated pathogenic pathways and networks via the Ingenuity Pathway Analysis database. Through molecular docking, we predicted the mechanism by which TWHF interacts with candidate targets.

RESULTS

A total of 351 DEGs were screened from the glomeruli of LN patients and were mainly concentrated in the role of pattern recognition receptors in the recognition of bacteria and viruses and interferon signaling pathways. A total of 130 DEGs were screened from the tubulointerstitium of LN patients, which were concentrated in the interferon signaling pathway. TWHF might be effective in treating LN by hydrogen bonding to regulate the functions of 24 DEGs (including HMOX1, ALB, and CASP1), which are mainly concentrated in the B-cell signaling pathway.

CONCLUSION

The mRNA expression profile of renal tissue from LN patients revealed a large number of DEGs. TWHF has been shown to interact with the DEGs (including HMOX1, ALB and CASP1) through hydrogen bonding to treat LN.

A network pharmacology-based investigation of brugine reveals its multi-target molecular mechanism against Breast Cancer

Breast cancer represents the leading cause of mortality among women worldwide. Since the complexity of breast cancer as a disease resides in its heterogeneity as it consists of several subtypes such as hormone receptor-positive subtypes: Luminal A, Luminal B, Her2- overexpressed, basal-like and hormone receptor-negative subtype: TNBC. Among all the subtypes, triple negative breast cancer (TNBC) is the most lethal and complex subtype. Moreover, the available treatment options like surgery, radiation therapy, and chemotherapy are not sufficient because of the associated side effects and drug resistance development. Therefore, discovery of new effective natural compounds with anti-tumor activity is required. In this pursuit, marine organisms provide a plentiful supply of such chemicals compounds. A marine compound Brugine found in the bark and stem of mangrove species Bruguiera sexangula is a potential anti-cancer compound. It has shown its cytotoxic activity against sarcoma 180 and lewis lung cancer. The molecular processes, however, are currently unknown. So, in order to research the molecular pathways this compound utilizes, we sought to apply a network pharmacology approach. The network pharmacology strategy we used in this investigation to identify and evaluate possible molecular pathways involved in the treatment of breast cancer with brugine was supported by simulation and molecular docking experiments. The study was conducted using various databases such as the cancer genome atlas (TCGA) for the genetic profile study of breast cancer, Swiss ADME for studying the pharmacodynamic study of brugine, Gene cards for collection of information of genes, STRING was used to study the interaction among proteins, AutoDock vina was to study the binding efficacy of brugine with the best fit protein. The results showed that the compound and breast cancer target network shared 90 common targets. According to the functional enrichment analysis brugine exhibited its effects in breast cancer via modulating certain pathways such as cAMP signaling pathway, JAK/STAT pathway, HIF-1 signaling pathway PI3K-Akt pathway, calcium signaling pathway, and Necroptosis. Molecular docking investigations demonstrated that the investigated marine compound has a high affinity for the key target, protein kinase A (PKA). A stable protein-ligand combination was created by the best hit molecule, according to molecular dynamics modeling. The purpose of this research was to examine the importance of brugine as a potentially effective treatment for breast cancer and to obtain knowledge of the molecular mechanism used by this substance in breast cancer.

β, β-Dimethylacrylshikonin potentiates paclitaxel activity, suppresses immune evasion and triple negative breast cancer progression via STAT3Y705 phosphorylation inhibition based on network pharmacology and transcriptomics analysis

BACKGOUND

Triple negative breast cancer (TNBC) is an extremely aggressive and rapidly progressing cancer, wherein existing therapies provide little benefit to patients. β, β-Dimethylacrylshikonin (DMAS), an active naphthoquinone derived from comfrey root, has potent anticancer activity. However, the antitumor function of DMAS against TNBC remains to be proved.

PURPOSE

Explore effects of DMAS on TNBC and clarify the mechanism.

STUDY DESIGN

Network pharmacology, transcriptomics and various cell functional experiments were applied to TNBC cells to explore the effects of DMAS on TNBC. The conclusions were further validated in xenograft animal models.

METHODS

MTT, EdU, transwell, scratch tests, flow cytometry, immunofluorescence, and immunoblot were utilized to assess the activity of DMAS on three TNBC cell lines. The anti-TNBC mechanism of DMAS was clarified by overexpression and knockdown of STAT3 in BT-549 cells. In vivo efficacy of DMAS was analysed using a xenograft mouse model.

RESULTS

In vitro analysis revealed that DMAS inhibited the G2/M phase transition and suppressed TNBC proliferation. Additionally, DMAS triggered mitochondrial-dependent apoptosis and reduced cell migration by antagonizing epithelial-mesenchymal transition. Mechanistically, DMAS exerted its antitumour effects by inhibiting STAT3Y705 phosphorylation. STAT3 overexpression abolished the inhibitory effect of DMAS. Further studies showed that treatment with DMAS inhibited TNBC growth in a xenograft model. Notably, DMAS potentiated the sensitivity of TNBC to paclitaxel and inhibited immune evasion by downregulating the immune checkpoint PD-L1.

CONCLUSIONS

For the first time, our study revealed that DMAS potentiates paclitaxel activity, suppresses immune evasion and TNBC progression by inhibiting STAT3 pathway. It has the potential as a promising agent for TNBC.

Network pharmacology-based prediction and experimental verification of the involvement of the PI3K/Akt pathway in the anti-thyroid cancer activity of crocin

Crocin, a unique water-soluble carotenoid extracted from saffron, is known to exert anticancer activity against various cancer types, including thyroid cancer (TC). However, the detailed mechanism underlying the anticancer effect of crocin in TC needs further exploration. Targets of crocin and targets associated with TC were acquired from public databases. Gene Ontology (GO) and KEGG pathway enrichment analyses were performed using DAVID. Cell viability and proliferation were assessed using MMT and EdU incorporation assays, respectively. Apoptosis was assessed using TUNEL and caspase-3 activity assays. The effect of crocin on phosphatidylinositol-3-kinase (PI3K)/protein kinase B (Akt) was explored by western blot analysis. A total of 20 overlapping targets were identified as candidate targets of crocin against TC. GO analysis showed that these overlapping genes were significantly enriched in the positive regulation of cell proliferation. KEGG results showed that the PI3K/Akt pathway was involved in the effect of crocin against TC. Crocin treatment inhibited cell proliferation and promoted apoptosis in TC cells. Moreover, we found that crocin inhibited the PI3K/Akt pathway in TC cells. 740Y-P treatment reversed the effects of crocin on TC cells. In conclusion, crocin suppressed proliferation and elicited apoptosis in TC cells via inactivation of the PI3K/Akt pathway.

Repurposing Drugs for the Treatment of COVID-19 and Its Cardiovascular Manifestations

COVID-19 is an infectious disease caused by SARS-CoV-2 leading to the ongoing global pandemic. Infected patients developed a range of respiratory symptoms, including respiratory failure, as well as other extrapulmonary complications. Multiple comorbidities, including hypertension, diabetes, cardiovascular diseases, and chronic kidney diseases, are associated with the severity and increased mortality of COVID-19. SARS-CoV-2 infection also causes a range of cardiovascular complications, including myocarditis, myocardial injury, heart failure, arrhythmias, acute coronary syndrome, and venous thromboembolism. Although a variety of methods have been developed and many clinical trials have been launched for drug repositioning for COVID-19, treatments that consider cardiovascular manifestations and cardiovascular disease comorbidities specifically are limited. In this review, we summarize recent advances in drug repositioning for COVID-19, including experimental drug repositioning, high-throughput drug screening, omics data-based, and network medicine-based computational drug repositioning, with particular attention on those drug treatments that consider cardiovascular manifestations of COVID-19. We discuss prospective opportunities and potential methods for repurposing drugs to treat cardiovascular complications of COVID-19.

Network pharmacology reveals that Berberine may function against Alzheimer's disease via the AKT signaling pathway

Objective

To investigate the mechanism underlying the effects of berberine (BBR) in the treatment of Alzheimer's disease (AD).

Methods

3 × Tg AD mice were treated with BBR for 3 months, then the open field test (OFT), the novel object recognition test (NOR) and the Morris water maze (MWM) test were performed to assess behavioral performance. Hematoxylin-eosin (HE) staining, Nissl staining were used to examine histopathological changes. The pharmacological and molecular properties of BBR were obtained from the TCMSP database. BBR-associated AD targets were identified using the PharmMapper (PM), the comparative toxicogenomics database (CTD), DisGeNet and the human gene database (GeneCards). Core networks and BBR targets for the treatment of AD were identified using PPI network and functional enrichment analyses. AutoDock software was used to model the interaction between BBR and potential targets. Finally, RT-qPCR, western blotting were used to validate the expression of core targets.

Results

Behavioral experiments, HE staining and Nissl staining have shown that BBR can improve memory task performance and neuronal damage in the hippocampus of AD mice. 117 BBR-associated targets for the treatment of AD were identified, and 43 genes were used for downstream functional enrichment analysis in combination with the results of protein-protein interaction (PPI) network analysis. 2,230 biological processes (BP) terms, 67 cell components (CC) terms, 243 molecular function (MF) terms and 118 KEGG terms were identified. ALB, EGFR, CASP3 and five targets in the PI3K-AKT signaling pathway including AKT1, HSP90AA1, SRC, HRAS, IGF1 were selected by PPI network analysis, validated by molecular docking analysis and RT-q PCR as core targets for further analysis. Akt1 mRNA expression levels were significantly decreased in AD mice and significantly increased after BBR treatment (p < 0.05). Besides, AKT and ERK phosphorylation decreased in the model group, and BBR significantly increased their phosphorylation levels.

Conclusion

AKT1, HSP90AA1, SRC, HRAS, IGF1 and ALB, EGFR, CASP3 were core targets of BBR in the treatment of AD. BBR may exert a neuroprotective effect by modulating the ERK and AKT signaling pathways.

Integrating network pharmacology approaches for the investigation of multi-target pharmacological mechanism of 6-shogaol against cervical cancer

Traditional treatment of cancer has been plagued by a number of obstacles, such as multiple drug resistance, toxicity and financial constraints. In contrast, phytochemicals that modulate a variety of molecular mechanisms are garnering increasing interest in complementary and alternative medicine. Therefore, an approach based on network pharmacology was used in the present study to explore possible regulatory mechanisms of 6-shogaol as a potential treatment for cervical cancer (CC). A number of public databases were screened to collect information on the target genes of 6-shogaol (SuperPred, Targetnet, Swiss target prediction and PharmMapper), while targets pertaining to CC were taken from disease databases (DisGeNet and Genecards) and gene expression omnibus (GEO) provided expression datasets. With STRING and Cytoscape, protein-protein interactions (PPI) were generated and topology analysis along with CytoNCA were used to identify the Hub genes. The Gene Ontology (GO) database Enrichr was used to annotate the target proteins, while, using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, signaling pathway enrichment analysis was conducted. Molecular docking and survival analysis for the Hub genes revealed four genes (HSP90AA1, HRAS, ESR1 and EGFR) with lowest binding energy and majority of the Hub genes (EGFR, SRC, CASP-3, HSP90AA1, MTOR, MAPK-1, MDM2 and ESR1) were linked with the overall survival of CC patients. In conclusion, the present study provides the scientific evidence which strongly supports the use of 6-shogoal as an inhibitor of cellular proliferation, growth, migration as well as inducer of apoptosis via targeting the hub genes involved in the growth of CC.Communicated by Ramaswamy H. Sarma.

Combined Multiomics and In Silico Approach Uncovers PRKAR1A as a Putative Therapeutic Target in Multi-Organ Dysfunction Syndrome

Despite all epidemiological, clinical, and experimental research efforts, therapeutic concepts in sepsis and sepsis-induced multi-organ dysfunction syndrome (MODS) remain limited and unsatisfactory. Currently, gene expression data sets are widely utilized to discover new biomarkers and therapeutic targets in diseases. In the present study, we analyzed MODS expression profiles (comprising 13 sepsis and 8 control samples) retrieved from NCBI-GEO and found 359 differentially expressed genes (DEGs), among which 170 were downregulated and 189 were upregulated. Next, we employed the weighted gene co-expression network analysis (WGCNA) to establish a MODS-associated gene co-expression network (weighted) and identified representative module genes having an elevated correlation with age. Based on the results, a turquoise module was picked as our hub module. Further, we constructed the PPI network comprising 35 hub module DEGs. The DEGs involved in the highest-confidence PPI network were utilized for collecting pathway and gene ontology (GO) terms using various libraries. Nucleotide di- and triphosphate biosynthesis and interconversion was the most significant pathway. Also, 3 DEGs within our PPI network were involved in the top 5 significantly enriched ontology terms, with hypercortisolism being the most significant term. PRKAR1A was the overlapping gene between top 5 significant pathways and GO terms, respectively. PRKAR1A was considered as a therapeutic target in MODS, and 2992 ligands were screened for binding with PRKAR1A. Among these ligands, 3 molecules based on CDOCKER score (molecular dynamics simulated-based score, which allows us to rank the binding poses according to their quality and to identify the best pose for each system) and crucial interaction with human PRKAR1A coding protein and protein kinase-cyclic nucleotide binding domains (PKA RI alpha CNB-B domain) via active site binding residues, viz. Val283, Val302, Gln304, Val315, Ile327, Ala336, Ala337, Val339, Tyr373, and Asn374, were considered as lead molecules.

Uncovering the effects and molecular mechanism of Astragalus membranaceus (Fisch.) Bunge and its bioactive ingredients formononetin and calycosin against colon cancer: An integrated approach based on network pharmacology analysis coupled with experimental validation and molecular docking

Colon cancer is a highly malignant cancer with poor prognosis. Astragalus membranaceus (Fisch.) Bunge (Huang Qi in Chinese, HQ), a well-known Chinese herbal medicine and a popular food additive, possesses various biological functions and has been frequently used for clinical treatment of colon cancer. However, the underlying mechanism is not fully understood. Isoflavonoids, including formononetin (FMNT) and calycosin (CS), are the main bioactive ingredients isolated from HQ. Thus, this study aimed to explore the inhibitory effects and mechanism of HQ, FMNT and CS against colon cancer by using network pharmacology coupled with experimental validation and molecular docking. The network pharmacology analysis revealed that FMNT and CS exerted their anticarcinogenic actions against colon cancer by regulating multiple signaling molecules and pathways, including MAPK and PI3K-Akt signaling pathways. The experimental validation data showed that HQ, FMNT and CS significantly suppressed the viability and proliferation, and promoted the apoptosis in colon cancer Caco2 and HT-29 cells. HQ, FMNT and CS also markedly inhibited the migration of Caco2 and HT-29 cells, accompanied by a marked increase in E-cadherin expression, and a notable decrease in N-cadherin and Vimentin expression. In addition, HQ, FMNT and CS strikingly decreased the expression of ERK1/2 phosphorylation (p-ERK1/2) without marked change in total ERK1/2 expression. They also slightly downregulated the p-Akt expression without significant alteration in total Akt expression. Pearson correlation analysis showed a significant positive correlation between the inactivation of ERK1/2 signaling pathway and the HQ, FMNT and CS-induced suppression of colon cancer. The molecular docking results indicated that FMNT and CS had a strong binding affinity for the key molecules of ERK1/2 signaling pathway. Conclusively, HQ, FMNT and CS exerted good therapeutic effects against colon cancer by mainly inhibiting the ERK1/2 signaling pathway, suggesting that HQ, FMNT and CS could be useful supplements that may enhance chemotherapeutic outcomes and benefit colon cancer patients.

Network pharmacology and bioinformatics approach reveals the therapeutic mechanism of action of curcumin in Alzheimer disease

Curcumin is a natural anti-inflammatory and antioxidant substance which plays a major role in reducing the amyloid plaques formation, which is the major cause of Alzheimer's disease (AD). Consequently, a methodical approach was used to select the potential protein targets of curcumin in AD through network pharmacology. In this study, through integrative methods, AD targets of curcumin through SwissTargetPrediction database, STITCH database, BindingDB, PharmMapper, Therapeutic Target Database (TTD), Online Mendelian Inheritance in Man (OMIM) database were predicted followed by gene enrichment analysis, network construction, network topology, and docking studies. Gene ontology analysis facilitated identification of a list of possible AD targets of curcumin (74 targets genes). The correlation of the obtained targets with AD was analysed by using gene ontology (GO) pathway enrichment analyses and Kyoto Encyclopaedia of Genes and Genomes (KEGG). We have incorporated the applied network pharmacological approach to identify key genes. Furthermore, we have performed molecular docking for analysing the mechanism of curcumin. In order to validate the temporospatial expression of key genes in human central nervous system (CNS), we searched the Human Brain Transcriptome (HBT) dataset. We identified top five key genes namely, PPARγ, MAPK1, STAT3, KDR and APP. Further validated the expression profiling of these key genes in publicly available brain data expression profile databases. In context to a valuable addition in the treatment of AD, this study is concluded with novel insights into the therapeutic mechanisms of curcumin, will ease the treatment of AD with the clinical application of curcumin.

Zhijing powder manages blood pressure by regulating PI3K/AKT signal pathway in hypertensive rats

Background

Zhijing Powder (ZJP) is a traditional Chinese medicine containing two kinds of Chinese medicine. Those studies analyze the molecular mechanism of ZJP in treating hypertension through network pharmacology, combined with animal experiments.

Methods

First, the effective ingredients and potential targets of the drug were obtained through drug databases, while the targets of disease obtained through disease target databases. The potential targets, cellular bioanalysis and signaling pathways were found in some platforms by analyzing collected targets. Further experiments were conducted to verify the effect and mechanism of drugs on cold and high salt in an induced-hypertension rat model.

Results

There are 17 effective components of centipedes and 10 of scorpions, with 464 drug targets obtained after screening. A total of 1263 hypertension targets were obtained after screening and integration, resulting in a protein-protein interaction network (PPI) with 145 points and 1310 edges. Gene ontology (GO) analysis shows that blood circulation regulation and activation of G protein-coupled receptors are mainly biological processes. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis shows that neuroactive ligand-receptor interaction, calcium signaling pathways, PI3K-AKT signaling pathways are the most abundant gene-enriched pathway. Animal experiments indicated that ZJP can reduce blood pressure (BP), affect expression of the PI3K-AKT signaling pathway, and improve oxidative stress in the body.

Conclusion

ZJP ameliorates oxidative stress and reduces BP in hypertensive rats caused by cold stimuli and high salt, revealing its effect on the expression of the PI3K/AKT signaling pathway in the rat aorta.

Ginsenoside Rd protects transgenic Caenorhabditis elegans from β-amyloid toxicity by activating oxidative resistant

Alzheimer's disease (AD) is a serious public health issue but few drugs are currently available for the disease, and these only target the symptoms. It is well established that oxidative stress plays a crucial role in AD, and there is compelling evidence linking oxidative stress to β-amyloid (Aβ). An exciting source of potential new AD therapeutic medication possibilities is medicinal plants. Ginsenoside Rd (GS-Rd) is one of the main bioactive substances in ginseng extracts. In our study, we used a network pharmacology analysis to identify overlapping GS-Rd (therapeutic) and AD (disease)-relevant protein targets, gene ontology (GO) and bio-process annotation, and the KEGG pathway analysis data predicted that GS-Rd impacts multiple targets and pathways, such as the MAPK signal pathway and the JAT-STAT3 signaling pathway. We then assessed the role of GS-Rd in C. elegans and found that GS-Rd prolongs lifespan, improves resistance to heat stress, delays physical paralysis and increases oxidative stress responses. Overall, these results suggest that GS-Rd protects against the toxicity of Aβ. The RNA-seq analysis revealed that GS-Rd achieves its effects by regulating gene expressions like daf-16 and skn-1, as well as by participating in many AD-related pathways like the MAPK signaling pathway. In addition, in CL4176 worms, GS-Rd decreased reactive oxygen species (ROS) levels and increased SOD activity. Additional research with transgenic worms showed that GS-Rd aided in the movement of DAF-16 from the cytoplasm to the nucleus. Taken together, the results indicate that GS-Rd significantly reduces Aβ aggregation by targeting the MAPK signal pathway, induces nuclear translocation of DAF-16 to activate downstream signaling pathways and increases resistance to oxidative stress in C. elegans to protect against Aβ-induced toxicity.

The module triad: a novel network biology approach to utilize patients' multi-omics data for target discovery in ulcerative colitis

Tumor necrosis factor-[Formula: see text] inhibitors (TNFi) have been a standard treatment in ulcerative colitis (UC) for nearly 20 years. However, insufficient response rate to TNFi therapies along with concerns around their immunogenicity and inconvenience of drug delivery through injections calls for development of UC drugs targeting alternative proteins. Here, we propose a multi-omic network biology method for prioritization of protein targets for UC treatment. Our method identifies network modules on the Human Interactome-a network of protein-protein interactions in human cells-consisting of genes contributing to the predisposition to UC (Genotype module), genes whose expression needs to be modulated to achieve low disease activity (Response module), and proteins whose perturbation alters expression of the Response module genes to a healthy state (Treatment module). Targets are prioritized based on their topological relevance to the Genotype module and functional similarity to the Treatment module. We demonstrate utility of our method in UC and other complex diseases by efficiently recovering the protein targets associated with compounds in clinical trials and on the market . The proposed method may help to reduce cost and time of drug development by offering a computational screening tool for identification of novel and repurposing therapeutic opportunities in UC and other complex diseases.

A new framework for host-pathogen interaction research

COVID-19 often manifests with different outcomes in different patients, highlighting the complexity of the host-pathogen interactions involved in manifestations of the disease at the molecular and cellular levels. In this paper, we propose a set of postulates and a framework for systematically understanding complex molecular host-pathogen interaction networks. Specifically, we first propose four host-pathogen interaction (HPI) postulates as the basis for understanding molecular and cellular host-pathogen interactions and their relations to disease outcomes. These four postulates cover the evolutionary dispositions involved in HPIs, the dynamic nature of HPI outcomes, roles that HPI components may occupy leading to such outcomes, and HPI checkpoints that are critical for specific disease outcomes. Based on these postulates, an HPI Postulate and Ontology (HPIPO) framework is proposed to apply interoperable ontologies to systematically model and represent various granular details and knowledge within the scope of the HPI postulates, in a way that will support AI-ready data standardization, sharing, integration, and analysis. As a demonstration, the HPI postulates and the HPIPO framework were applied to study COVID-19 with the Coronavirus Infectious Disease Ontology (CIDO), leading to a novel approach to rational design of drug/vaccine cocktails aimed at interrupting processes occurring at critical host-coronavirus interaction checkpoints. Furthermore, the host-coronavirus protein-protein interactions (PPIs) relevant to COVID-19 were predicted and evaluated based on prior knowledge of curated PPIs and domain-domain interactions, and how such studies can be further explored with the HPI postulates and the HPIPO framework is discussed.

PCW-A1001, AI-assisted de novo design approach to design a selective inhibitor for FLT-3(D835Y) in acute myeloid leukemia

Treating acute myeloid leukemia (AML) by targeting FMS-like tyrosine kinase 3 (FLT-3) is considered an effective treatment strategy. By using AI-assisted hit optimization, we discovered a novel and highly selective compound with desired drug-like properties with which to target the FLT-3 (D835Y) mutant. In the current study, we applied an AI-assisted de novo design approach to identify a novel inhibitor of FLT-3 (D835Y). A recurrent neural network containing long short-term memory cells (LSTM) was implemented to generate potential candidates related to our in-house hit compound (PCW-1001). Approximately 10,416 hits were generated from 20 epochs, and the generated hits were further filtered using various toxicity and synthetic feasibility filters. Based on the docking and free energy ranking, the top compound was selected for synthesis and screening. Of these three compounds, PCW-A1001 proved to be highly selective for the FLT-3 (D835Y) mutant, with an IC50 of 764 nM, whereas the IC50 of FLT-3 WT was 2.54 μM.

Integrating network pharmacology and experimental validation to clarify the anti-hyperuricemia mechanism of cortex phellodendri in mice

Hyperuricemia (HUA), a common metabolic disease, is treated as the second-largest metabolic disease after diabetes in China. Cortex Phellodendri (CP) is one of the most frequently used herbal medicines for treating gout or HUA. However, the mechanism underlying the anti-HUA effect of CP is still unrevealed. Hence, this study aimed to explore the pharmacological mechanism of CP against HUA using network pharmacology coupled with in vivo experimental validation. Active compounds and potential targets of CP, as well as the potential targets related to HUA, were retrieved from multiple open-source databases. The drug-disease overlapping targets were obtained by Venn diagram analysis and used to construct the herb-component-target (HCT), protein-protein-interaction (PPI), and component-target-pathway (CTP) networks. The functional enrichment analysis was also performed for further study. Furthermore, a HUA mouse model was induced by a combination of intraperitoneal injection of potassium oxonate (PO, 300 mg/kg) and intragastric administration of hypoxanthine (HX, 300 mg/kg) daily for 10 days. Different dosages of CP (200, 400, and 800 mg/kg) were orally given to mice 1 h after modeling. The results showed that 12 bioactive compounds and 122 drug-disease overlapping targets were obtained by matching 415 CP-related targets and 679 HUA-related targets, and berberine was one of the most important compounds with the highest degree value. The core targets of CP for treating HUA were TP53, MAPK8, MAPK3, IL-6, c-Jun, AKT1, xanthine oxidase (XOD), and ATP-binding cassette subfamily G member 2 (ABCG2). The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment results showed that the anti-HUA effect of CP mainly involved the pathways of inflammation and apoptosis, such as PI3K/Akt, TNF, MAPK, TLR, AMPK, NF-κB, and NLRP3 signaling pathways. In vivo animal experiment further confirmed the hypouricemic effect of CP in a HUA mouse model, as evidenced by significantly restored kidney histological deteriorations, and considerably decreased levels of serum uric acid (sUA), creatinine (Cre), blood urea nitrogen (BUN), and hepatic UA. Furthermore, the hypouricemic action of CP in vivo might be attributed to its suppression of XOD activity in the liver, rather than ABCG2 in the kidney. Real-time qPCR (RT-qPCR) and Western blot analysis also confirmed the key roles of the hub genes in CP against HUA. In conclusion, CP exhibited therapeutic effect against HUA via multi-compounds, multi-targets, and multi-pathways. It possessed anti-HUA and nephroprotective effects via suppressing XOD activity, and reversed the progression of renal injury by exerting anti-inflammatory and anti-apoptotic effects.