Molecular Docking Validation Research Articles

Predictive Analysis of Yi-Gai-San's Multifaceted Mechanisms for Tremor-dominant Parkinson's Disease via Network Pharmacology and Molecular Docking Validation.

Based on comprehensive network-pharmacology and molecular docking analysis, this study was intended to unveil the multiple mechanisms of Yi- Gai-San (YGS) in treating the tremor-dominant subtype of Parkinson's disease (PD-DT). The compounds of YGS were meticulously analyzed, selected, and standardized with references to their pharmacological attributes. Its components included Gouteng (Uncaria rhynchophylla), Chaihu (Radix Bupleuri), Chuanxiong (Chuanxiong Rhizoma), Danggui (Angelicae sinensis radix), Fuling (Wolfiporia extensa), Baizhu (Atractylodis macrocephalae rhizoma), and Gancao (Licorice, Glycyrrhizae radix). We identified 75 active compounds within YGS. From these, we predicted 110 gene targets, which exhibited a direct association with PD-DT. PPI network results highlighted core target proteins, including TP53, SLC6A3, GAPDH, MAOB, AKT, BAX, IL6, BCL2, PKA, and CASP3. These proteins potentially alleviate PD-DT by targeting inflammation, modulating neuronal cell apoptosis, and regulating the dopamine system. Furthermore, GO and KEGG enrichment analyses emphasized that YGS might influence various mechanisms, such as the apoptotic process, mitochondrial autophagy, Age-Rage signaling, and dopaminergic and serotonergic synapses. The core proteins from the PPI analysis were selected for the docking experiment. The docking results demonstrated that the most stable ligand-receptor conformations were kaempferol with CASP3 (-9.5 kcal/mol), stigmasterol with SLC6A3 (-10.5 kcal/mol), shinpterocarpin with BCL2L1 (-9.6 kcal/mol), hirsutine with MAOB (-9.7 kcal/mol), hederagenin with PRKACA (-9.8 kcal/mol), and yatein with GAPDH (-9.8 kcal/mol). These results provide us with research objectives for future endeavors in extracting single compounds for drug manufacturing or in-depth studies on drug mechanisms. From these computational findings, we suggested that YGS might mitigate PD-DT via "multi-compounds, multi-targets, and multi-pathways."

Kaempferol protects against dexamethasone-induced muscle atrophy in mice by increasing PI3K/AKT/mTOR and NRF2/HO-1/KEAP1 signaling pathways: network pharmacology, molecular docking, and experimental validation studies

Kaempferol protects against dexamethasone-induced muscle atrophy in mice by increasing PI3K/AKT/mTOR and NRF2/HO-1/KEAP1 signaling pathways: network pharmacology, molecular docking, and experimental validation studies

Integration of network pharmacology and transcriptomics to explore the mechanism of isoliquiritigenin in treating heart failure induced by myocardial infarction

BackgroundThe inflammatory response and myocardial remodeling play critical roles in the progression of heart failure (HF) following myocardial infarction (MI). Isoliquiritigenin (ISL) possesses anti-inflammatory properties and has been investigated in cardiovascular diseases such as atherosclerosis. However, the effects and mechanism of ISL on MI-induced HF remain unclear. This research aimed to explore the effects and mechanism of ISL in the treatment of HF on the basis of network pharmacology, transcriptomics, and experimental verification. Methods and resultsWe established an MI-induced HF mouse model in which ISL was administered via gavage for 28 days. Ultrasonic cardiogram data were collected from the mice, and pathological staining was conducted. Then, network pharmacology and molecular docking were performed. Transcriptomic analysis was also conducted on mouse myocardial tissue. Ultimately, we integrated transcriptomic data and network pharmacology to reveal the underlying mechanism, with the results verified through in vivo experiments. Our experiments indicated that ISL improved cardiac function, preserved myocardial structure, inhibited collagen fiber accumulation, reduced inflammatory factor secretion, and mitigated myocardial cell apoptosis in mice with MI-induced HF. A combination of transcriptomics and network pharmacology analysis revealed that core targets of ISL related to HF were significantly enriched in the Tumor Necrosis Factor (TNF) signaling pathway. Molecular docking validation demonstrated that ISL shows strong binding to these core targets. Additionally, in vivo experiments verified that ISL protects against HF post-MI by inhibiting the TNF signaling pathway. ConclusionWe clarified the anti-inflammatory and antimyocardial remodeling mechanisms of ISL in the treatment of HF post-MI, which involves the TNF signaling pathway.

Exploring the potential mechanisms of polysaccharides against gastric ulcer: Network pharmacology analysis and molecular docking validation

AbstractGastric ulcer is a common peptic ulcer that affects human health and life quality seriously. As anti‐gastric ulcer drugs usually cause side‐effects, polysaccharides may be the potential alternatives because of better effectiveness and less toxicity. Although the anti‐gastric ulcer activities of polysaccharides have been widely reported, the mechanisms have not yet been well‐disclosed. In this study, network pharmacology analysis was performed to explore the potential mechanisms of polysaccharides against gastric ulcer, and the results were validated by molecular docking. Results indicated that β‐glucan, arabinogalactan, xylan, and arabinan were the key structures, and ABL1, AKT1, androgen receptor, epidermal growth factor receptor, v‐Ha‐ras Harvey rat sarcoma viral oncogene homolog, HSP90AA1, mitogen‐activated protein kinase 8 (MAPK8), MAPK14, NOS2, PIK3R1, RAC1, ras homolog gene family member A, and proto‐oncogene tyrosine‐protein kinase Src were the core targets for polysaccharides in treating gastric ulcer. Polysaccharides have influences on 1958 GO items and 199 KEGG pathways, and their anti‐gastric ulcer activities are related to MAPK, Ras, PI3K‐Akt, vascular endothelial growth factor, prolactin, FoxO and Rap1 signaling pathways, etc. Molecular docking validation showed that the results of network pharmacology analysis were credible, and interactions between polysaccharide structures and core targets were observed. This study contributes to understanding the mechanisms of polysaccharides in treating gastric ulcer and provides references for future activity screening and mechanism research in anti‐gastric ulcer.

Integrating network pharmacology, molecular docking, and experimental validation to reveal the mechanism of Radix Rehmanniae in psoriasis.

Radix Rehmanniae (RR) plays an important role in treating psoriasis. However, the active compounds of RR and potential mechanisms are unclear. The current study was designed to investigate the potential active ingredients, targets, and mechanisms of RR in treating psoriasis through network pharmacology, molecular docking, and vitro experiments. Initially, the TCMSP database and literature retrieval were used to access the active ingredients of RR. The psoriasis target proteins were obtained from Therapeutic Target Database, OMIM, GeneCards, and DrugBank databases. The target proteins were then converted into target genes using Uniprot. Secondly, overlapping genes were obtained through Venn online tool. Then, protein-protein interactions network diagram is finished by STRING database. Next, Cytoscape software was used to acquire the top 10 hub proteins; gene ontology and Kyoto encyclopedia of genes and genomes enrichment analysis were then used to predict possible mechanisms. Afterwards, molecular docking validation of the active ingredients with the main targets was performed by AutoDock software. Finally, lipopolysaccharides induced RAW264.7, to assess the effects and molecular mechanisms by MTT, RT-qPCR, and Western blot assays. Overall, there are 20 effective compounds and 33 targets involved in biological processes including apoptosis, intracellular signaling, vasodilation, and mitogen-activated protein kinase (MAPK) signaling cascade. The docking results showed strong binding capacity between the active ingredients and targets. We verified aucubin as the key active ingredient, tumor necrosis factor α, and IL6 as the core targets, and focused on the p38MAPK protein pathway. Cellular experiments showed that aucubin down-regulated the phosphorylated p38MAP protein and reduced the expression of tumor necrosis factor α mRNA, IL6 mRNA, and IL1βmRNA. In summary, RR is featured with multicomponent, multi-target, and multi-pathway in treating psoriasis; the preliminary mechanism may be associated with the down-regulation of p38MAPK phosphorylation and curbing the expression of inflammatory factor by aucubin. This paper provides the scientific basis for Traditional Chinese medicine treating psoriasis.

Novel, Speedy, and Eco-Friendly Carboxymethyl Cellulose-Nitrogen Doped Carbon Dots Biosensors with DFT Calculations, Molecular Docking, and Experimental Validation

Novel, Speedy, and Eco-Friendly Carboxymethyl Cellulose-Nitrogen Doped Carbon Dots Biosensors with DFT Calculations, Molecular Docking, and Experimental Validation

Ouabain Ameliorates Alzheimer’s Disease-Associated Neuropathology and Cognitive Impairment in FAD4T Mice

Background: Alzheimer’s disease (AD) is a common clinical neurodegenerative disorder, primarily characterized by progressive cognitive decline and behavioral abnormalities. The hallmark pathological changes of AD include widespread neuronal degeneration, plaques formed by the deposition of amyloid β-protein (Aβ), and neurofibrillary tangles (NFTs). With the acceleration of global aging, the incidence of AD is rising year by year, making it a major global public health concern. Due to the complex pathology of AD, finding effective interventions has become a key focus of research. Ouabain (OUA), a cardiac glycoside, is well-known for its efficacy in treating heart disease. Recent studies have also indicated its potential in AD therapy, although its exact mechanism of action remains unclear. Methods: This study integrates bioinformatics, multi-omics technologies, and in vivo and in vitro experiments to investigate the effects of OUA on the pathophysiological changes of AD and its underlying molecular mechanisms. Results: This study analyzed the expression of the triggering receptor expressed on myeloid cells 2 (TREM2) across different stages of AD using bioinformatics. Serum samples from patients were used to validate soluble TREM2 (sTREM2) levels. Using an Aβ1-42-induced microglial cell model, we confirmed that OUA enhances the PI3K/AKT signaling pathway activation by upregulating TREM2, which reduces neuroinflammation and promotes the transition of microglia from an M1 proinflammatory state to an M2 anti-inflammatory state. To evaluate the in vivo effects of OUA, we assessed the learning and memory capacity of FAD4T transgenic mice using the Morris water maze and contextual fear conditioning tests. We used real-time quantitative PCR, immunohistochemistry, and Western blotting to measure the expression of inflammation-associated cytokines and to assess microglia polarization. OUA enhances cognitive function in FAD4T mice and has been confirmed to modulate microglial M1/M2 phenotypes both in vitro and in vivo. Furthermore, through bioinformatics analysis, molecular docking, and experimental validation, TREM2 was identified as a potential target for OUA. It regulates PI3K/Akt signaling pathway activation, playing a crucial role in OUA-mediated M2 microglial polarization and its anti-inflammatory effects in models involving Aβ1-42-stimulated BV-2 cells and FAD4T mice. Conclusions: These findings indicate that OUA exerts anti-neuroinflammatory effects by regulating microglial polarization, reducing the production of inflammatory mediators, and activating the PI3K/Akt signaling pathway. Given its natural origin and dual effects on microglial polarization and neuroinflammation, OUA emerges as a promising therapeutic candidate for neuroinflammatory diseases such as AD.

Anti-inflammatory effects of resveratrol in treating interstitial cystitis/bladder pain syndrome: a multi-faceted approach integrating network pharmacology, molecular docking, and experimental validation.

This study aims to investigate the anti-inflammatory effects of Resveratrol (RES) in the treatment of Interstitial Cystitis/Bladder Pain Syndrome (IC/BPS) by integrating network pharmacology, molecular docking, and experimental validation. Potential targets of RES were identified using DrugBank and SwissTargetPrediction, while IC/BPS-related targets were obtained from DisGeNET and Genecards. Molecular docking was performed using UCSF Chimera and SwissDock to validate the binding affinity of RES to key targets. Experimental validation involved treating TNF-α induced urothelial cells with RES, followed by assessments using RT-qPCR, ELISA, and Western blotting. A total of 86 drug targets and 211 disease targets were analyzed, leading to the identification of 8 key therapeutic targets for RES in IC/BPS treatment. Molecular docking revealed a strong affinity of RES for ESR2, with notable interactions also observed with SHBG, PTGS2, PPARG, KIT, PI3KCA, and AKT1. In vitro experiments confirmed that RES significantly alleviated the inflammatory response in TNF-α-induced urothelial cells, normalizing the expression levels of ESR2, SHBG, PPARG, and AKT1. RES can modulate critical pathways involving ESR2, SHBG, PPARG, and AKT1, highlighting its potential as a therapeutic agent for IC/BPS. This study provides a theoretical foundation for the clinical application of RES in treating IC/BPS.

Exploring the mechanisms of Cornus officinalis in the treatment of non-alcoholic steatohepatitis using network pharmacology, molecular docking and molecular dynamics simulations

Non-alcoholic steatohepatitis (NASH) is a predominant metabolic liver disease, typically characterized by hepatic steatosis, oxidative stress, and inflammation. The traditional Chinese medicine Cornus officinalis possesses anti-inflammatory and hepatoprotective pharmacological properties and has shown ameliorative effects on NASH. however, its mechanism of action remains unclear. This study aims to elucidate the mechanisms by which C. officinalis ameliorates NASH. The active components of C. officinalis were analyzed using the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), and the corresponding targets were predicted. Subsequently, the DisGeNET, GeneCards, and GEO databases were employed to identify NASH-related targets. Venn diagrams were used to intersect the C. officinalis targets with the NASH targets. Protein–protein interaction (PPI) networks were constructed using the STRING database, and PPI network analysis was performed using Cytoscape. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted using the Database for Annotation, Visualization, and Integrated Discovery (DAVID), followed by molecular docking validation. Cornus officinalis was found to contain 20 major active ingredients corresponding to 672 potential targets, 61 of which overlapped with NASH targets. PPI network, GO, and KEGG pathway analyses identified four targets with the highest correlation, and molecular docking results indicated that the active ingredients of C. officinalis exhibited strong binding affinities to NASH targets. The treatment of NASH with C. officinalis is characterized by multiple active ingredients and multiple targets, underscoring the major advantage of traditional Chinese medicine in treating NASH.

Integrated network pharmacology, metabolomics and molecular docking analysis to reveal the mechanisms of quercetin in the treatment of hyperlipidemia

Hyperlipidemia (HLP) is a significant contributor to cardiovascular diseases. Quercetin (QUE), a naturally occurring flavonoid with diverse bioactivities, has garnered attention due to its potential therapeutic effects. However, the precise mechanisms underlying the effects of QUE on HLP remain unclear. In this study, an ultra-high-performance liquid chromatography-quadrupole/electrostatic field Orbitrap high-resolution mass spectrometry (UPLC-Q-Exactive-MS) metabolomics strategy was employed to obtain metabolite profiles, and potential biomarkers were identified following data analysis. Network pharmacology and Drug Affinity Responsive Target Stability (DARTS) assays were utilized to explore the potential targets of QUE for HLP treatment. The results of metabolomics and network pharmacology were then integrated to identify the key targets and metabolic pathways involved in the therapeutic action of the QUE against HLP. Molecular docking and experimental validation were performed to confirm these key targets. A comprehensive database search identified 138 QUE-HLP-related targets. A protein-protein interaction (PPI) network was constructed using STRING, and the shared targets were filtered with Cytoscape. Among these, AKT1, TNF, VEGFA, mTOR, SREBP1, and SCD emerged as potential therapeutic targets. These findings were validated using in vitro cell experiments. Additionally, the mechanism of action of QUE against HLP was evaluated by integrating network pharmacology with metabolomics, identifying two metabolomic pathways crucial to HLP treatment. DARTS experiments confirmed the stable binding of QUE to FASN, p-mTOR, SREBP1, and p-AKT. In HepG2 cells treated with palmitic acid (PA), QUE significantly reduced the mRNA expression of ACLY, ACACA, FASN, and SCD (p < 0.05). Western blot analysis revealed that PA significantly increased protein expression of p-mTOR, SREBP1, FASN, and p-AKT (p < 0.05). In summary, our study provides novel insights into the protective mechanisms of QUE against HLP and offers valuable information regarding its potential benefits in clinical treatment.

Exploring the protective effect and molecular mechanism of betulin in Alzheimer's disease based on network pharmacology, molecular docking and experimental validation.

Alzheimer's disease (AD) is a neurodegenerative disorder that impairs learning and memory, with high rates of mortality. Birch bark has been traditionally used in the treatment of various skin ailments. Betulin (BT) is a key compound of birch bark that exhibits diverse pharmacological benefits and therapeutic potential in AD. However, the therapeutic effects and molecular mechanisms of BT in AD remain unclear. The present study aimed to predict the potential therapeutic targets of BT in the treatment of AD, and to determine the specific underlying molecular mechanisms through network pharmacology analysis and experimental validation. PharmMapper was used to predict the target genes of BT, and four disease databases were searched to screen for AD targets. The intersection targets were identified using the jveen website. Drug‑disease target protein‑protein interaction networks and hub genes were obtained and visualized using the Search Tool for the Retrieval of Interacting Genes/Proteins database and Cytoscape. The Database for Annotation, Visualization and Integrated Discovery was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and AutoDock was used for molecular docking analysis of BT and hub genes. Subsequently, the network‑predicted mechanisms of BT in AD were verified in vitro. A total of 495 BT and 1,386 AD targets were identified, and 120 were identified as potential targets of BT in the treatment of AD. The results of the molecular docking analysis revealed a strong binding affinity between BT and the hub genes. In addition, enrichment analyses of GO and KEGG pathways indicated that the neuroprotective effects of BT mainly involved the 'PI3K‑Akt signaling pathway'. The results of in vitro experiments demonstrated that pretreatment with BT for 2 h may ameliorate formaldehyde (FA)‑induced cytotoxicity and morphological changes in HT22 cells, and decrease FA‑induced Tau hyperphosphorylation and reactive oxygen species levels. Furthermore, the PI3K/AKT signaling pathway was activated and the expression levels of downstream proteins, namely GSK3β, Bcl‑2 and Bax, were modified following pre‑treatment with BT. Overall, the results of network pharmacology and in vitro analyses revealed that BT may reduce FA‑induced AD‑like pathology by modulating the PI3K/AKT signaling pathway, highlighting it as a potential multi‑target drug for the treatment of AD.

Screening the effective components of Lysionotus pauciflorus Maxim. on the treatment of LPS induced acute lung injury mice by integrated UHPLC-Q-TOF-MS/MS and network pharmacology

Ethnopharmacological relevanceAcute lung injury (ALI) is an inflammatory reaction produced through various injury-causing factors acting on the lungs in a direct or indirect way, with a high morbidity and mortality rate. A review of clinical experience has revealed that Lysionotus pauciflorus Maxim (LP) has a significant therapeutic effect on ALI. However, the comprehensive effective components of LP are uncertain, and the mechanisms, especially the potential therapeutic target for anti-ALI, are still unknown. Aims of the studyIn vitro and in vivo validation of the pharmacodynamics of LP in the treatment of ALI and exploration of its potential mechanism of action based on network pharmacology, molecular docking and experimental validation. Materials and methodsUltra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) was employed to identify the ingredients of LP extracts. The potential bioactive ingredients, key targets and signalling pathways were identified by network pharmacology, based on the results of the mass spectrometry analysis. Subsequently, molecular docking was performed on the screened core components and key targets to calculate their molecular binding energies and binding potentials, and to explore the mutual binding modes of small-molecule ligands and large-molecule proteins. Finally, lipopolysaccharide (LPS)-induced RAW264.7 cell model and ALI mice model were used to validate the therapeutic effects and potential mechanism of LP extract towards ALI. ResultsFrom the mass spectrometry results of LP extracts, a total of 89 chemical components were identified, including 46 phenylethanol glycosides, 26 flavonoids, 9 organic acids and their derivatives and 8 other compounds. And furthermore 39 core active components were screened by network pharmacology. The top 10 core components (4 phenylethanol glycosides, 6 flavonoids) have been screened in the composition -target-disease network, and 37 core targets related to LP efficacy were obtained by fitting PPI network analysis. 10 signalling pathways and their targets associated with LP treatment of ALI were obtained by GO/KEGG analysis, indicating that LP could regulate TLR4 and NF-κB signalling pathways through 4 key targets, namely NFKB1, RELA, TLR4 and TNF. The results of the molecular docking procedure indicated a strong affinity, with the binding energies between each component and the target site being less than −6 kcal/mol. The binding modes included Hydrogen Bonds, Pi-Pi interaction, Hydrophobic Interactions, Salt Bridges, Pi-cation interactions. These observations were subsequently validated in vitro and in vivo experiments. The outcomes of in vitro and in vivo experiments demonstrated that LP was effective in reducing the infiltration of inflammatory bacteria in lung tissues and attenuated the expression of pro-inflammatory cytokines in LPS-stimulated mice bronchoalveolar lavage fluid (BALF) and RAW264.7 cells. Furthermore, LP inhibited the expression and phosphorylation of TLR4 protein and NF-κB protein, thus playing a role in the prevention of ALI. ConclusionsIn this study, mass spectrometry analysis was combined with biomolecular networks to initially elucidate the potential of LP to treat ALI by modulating the TLR4/NF-κB pathway. This offers a definitive experimental basis for the development of new LP drugs.

Network pharmacology and experimental study of Angelica sinensis and Astragalus membranaceus capsules in treating heart failure

ObjectiveThis study explores the mechanism of AAC in intervening heart failure (HF) using network pharmacology, molecular docking, and in vitro experimental validation. MethodsThe “active component-target” network and the “drug-disease target” protein interaction network were constructed using Cytoscape 3.9.0 and STRING Database. GO and KEGG enrichment analysis was performed using DAVID database. Then, the molecular docking of major compounds and target proteins was carried out using Autodock 1.5.7, and visualized with PyMOL 2.4.0 software. Finally, in vitro experimental validation was performed to explore the potential targets of AAC in treating HF. ResultsThe study revealed significant targets implicated in a variety of GO bioprocess programs and KEGG signaling networks. The primary chemicals to have strong binding ability with target proteins in molecular docking, with quercetin having the best binding energy with MAPK at −6.72 Kcal/Mol.Validation of cellular experiments showed that AAC might reduce the apoptosis that doxorubicin causes in AC16 cells by controlling the levels of PIK3CA, AKT1, and MAPK1. ConclusionThis study preliminarily reveals that AAC can treat HF through multiple components and multiple targets by using network pharmacology, molecular docking, and experimental validation.

PocketDTA: an advanced multimodal architecture for enhanced prediction of drug-target affinity from 3D structural data of target binding pockets.

Accurately predicting the drug-target binding affinity (DTA) is crucial to drug discovery and repurposing. Although deep learning has been widely used in this field, it still faces challenges with insufficient generalization performance, inadequate use of 3D information, and poor interpretability. To alleviate these problems, we developed the PocketDTA model. This model enhances the generalization performance by pre-trained models ESM-2 and GraphMVP. It ingeniously handles the first 3 (top-3) target binding pockets and drug 3D information through customized GVP-GNN Layers and GraphMVP-Decoder. In addition, it uses a bilinear attention network to enhance interpretability. Comparative analysis with state-of-the-art (SOTA) methods on the optimized Davis and KIBA datasets reveals that the PocketDTA model exhibits significant performance advantages. Further, ablation studies confirm the effectiveness of the model components, whereas cold-start experiments illustrate its robust generalization capabilities. In particular, the PocketDTA model has shown significant advantages in identifying key drug functional groups and amino acid residues via molecular docking and literature validation, highlighting its strong potential for interpretability. Code and data are available at: https://github.com/zhaolongNCU/PocketDTA.

Determination of Potential Lead Compound from Magnolia officinalis for Alzheimer’s Disease through Pharmacokinetic Prediction, Molecular Docking, Dynamic Simulation, and Experimental Validation

Amyloid β protein (Aβ) deposition has been implicated as the molecular driver of Alzheimer’s disease (AD) progression. The modulation of the formation of abnormal aggregates and their post-translational modification is strongly suggested as the most effective approach to anti-AD. Beta-site APP-cleaving enzyme 1 (BACE1) acts upstream in amyloidogenic processing to generate Aβ, which rapidly aggregates alone or in combination with acetylcholinesterase (AChE) to form fibrils. Accumulated Aβ promotes BACE1 activation via glycogen synthase kinase-3β (GSK-3β) and is post-translationally modified by glutaminyl cyclase (QC), resulting in increased neurotoxicity. A novel multi-target inhibitor as a potential AD agent was identified using an in silico approach and experimental validation. Magnolia officinalis, which showed the best anti-AD activity in our preliminary study, was subjected to analysis, and 82 compounds were studied. Among 23 compounds with drug-likeness, blood–brain barrier penetration, and safety, honokiol emerged as a lead structure for the inhibition of BACE1, AChE, QC, and GSK-3β in docking and molecular dynamics (MD) simulations. Furthermore, honokiol was found to be an excellent multi-target inhibitor of these enzymes with an IC50 of 6–90 μM, even when compared to other natural single-target inhibitors. Taken together, the present study is the first to demonstrate that honokiol acts as a multiple enzyme inhibitor with an excellent pharmacokinetic and safety profile which may provide inhibitory effects in broad-range areas including the overproduction, aggregation, and post-translational modification of Aβ. It also provides insight into novel structural features for the design and discovery of multi-target inhibitors for anti-AD.

Exploring the Mechanism of Action of the "Scutellaria Barbata D.Don-Prunella Vulgaris L." Herb Pair in the Treatment of Lung Cancer Using Network Pharmacology and Molecular Docking Techniques

Objective: To explore the mechanism of action of the herbal pair "Scutellaria barbata D.Don-Prunella vulgaris L." in the treatment of lung cancer through network pharmacology and molecular docking techniques. Methods: Active ingredients and their targets of Scutellaria barbata D.Don and Prunella vulgaris L. were collected and screened from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Disease-related targets were obtained and screened from the Genecards and OMIM databases. The intersection Venn diagram of the targets of "Scutellaria barbata D.Don-Prunella vulgaris L." and lung cancer disease targets was obtained using R 4.4.1 software and packages such as "ggvenn". A drug-active ingredient-target-disease association network was constructed in Cytoscape 3.10.0, and core active ingredients were screened using the Analyze Network function. A PPI network for drug-disease common targets was constructed using the String database website, and the TSV format of protein interaction relationship files was imported into Cytoscape 3.10.0 software,install and run CytoHubba to calculate and obtain the core targets in the network. GO function and KEGG pathway enrichment analyses were performed on drug-disease common targets using R 4.4.1 software. Finally, molecular docking validation was performed on core ingredients and core targets using AutoDock, and the three best binding molecular docking patterns were displayed using PyMol software. Results: A total of 33 active drug components and 108 drug-disease common targets were obtained. Among them, there are 5 core active components: quercetin, luteolin, wogonin, kaempferol, and baicalein; core targets include TP53, AKT1, JUN, HSP90AA1, etc. GO analysis yielded 2, 010 related entries. KEGG analysis identified 147 signaling pathways. Molecular docking showed that the core active components have strong affinity with the core targets. Conclusion: The drug pair of Scutellaria barbata D.Don and Prunella vulgaris L. may exert anti-tumor effects by acting on targets such as TP53, AKT1, JUN, HSP90AA1, and through signaling pathways like PI3K-AKT, inhibiting tumor cell proliferation, promoting tumor cell apoptosis, suppressing its proliferation, differentiation, and metastasis, thereby achieving therapeutic effects on lung cancer.

Exploring the Mechanism of Action of Lycium barbarum in Treating Allergic Rhinitis Using Network Pharmacology and Molecular Docking

Objective: Approximately 10%-40% of the global population is affected by allergic rhinitis, and Lycium barbarum has a long history of dual use as a herbal medicine and also as a food. This study utilized network pharmacology and molecular docking to explore the mechanism of action of Lycium barbarum in treating allergic rhinitis. Methods: We screened active ingredients and potential action targets of Lycium barbarum using the TCMSP database. Relevant targets for allergic rhinitis diseases were accessed through the GeneCards and OMIM databases. GO function enrichment and KEGG pathway enrichment analyses of key targets were conducted using the DAVID database. Molecular docking validation was performed using Autodock Vina software to confirm the affinity between the core protein targets and the key active ingredients. Results: Network pharmacological analysis identified 35 major active ingredients of Lycium barbarum, 87 drug targets, and 2200 disease targets. GO functional analysis and KEGG pathway enrichment analysis revealed that the mechanism of action of Lycium barbarum in treating allergic rhinitis involves multiple pathways, including the HIF-1 signaling pathway, IL-17 signaling pathway, and TNF signaling pathway. Molecular docking results demonstrated good binding activity between the main active ingredients and the core protein target. Conclusion: Lycium barbarum exhibits multi-component, multi-target, and multi-pathway actions in treating allergic rhinitis by regulating relevant pathways and targets.

Mechanisms of Cinnamomi Cortex against Diabetes Mellitus Explored by Network Pharmacology combined with Molecular Docking and Experimental Validation.

Cinnamomi cortex (CC), a traditional Chinese herbal medicine, exhibits antidiabetic properties, yet the underlying mechanisms are not fully understood. Our study combined network pharmacology, molecular docking, and experimental validation to elucidate the antidiabetic mechanisms of CC. Active components of CC and their potential antidiabetic targets were identified through TCMSP, DisGeNET, and GeneCards. The PPI networks were constructed with STRING and analyzed with Cytoscape, while GO and KEGG analyses utilized the DAVID database. Molecular docking with core targets was performed using Autodock Vina. The efficacy of CC in diabetes mellitus was evaluated through H&E staining, qPCR, and Western blot in the T2DM mouse. Eleven active components and sixty-six potential antidiabetic targets of CC were identified. The enrichment analysis revealed 288 GO terms and 37 pathways. The molecular docking showed high affinity for PPAR-γ and IL-6 receptors. In vivo studies further confirmed CC's ability to modulate PPAR-γ and IL-6, contributing to its antidiabetic effects. CC manages diabetes by regulating the PPAR-γ pathway and suppressing associated inflammation, providing a multi-pathway therapeutic approach.

The improvement of modified Si-Miao granule on hepatic insulin resistance and glycogen synthesis in type 2 diabetes mellitus involves the inhibition of TNF-α/JNK1/IRS-2 pathway: network pharmacology, molecular docking, and experimental validation

BackgroundModified Si-Miao granule (mSMG), a traditional Chinese medicine, is beneficial for T2DM and insulin resistance (IR), but the underlying mechanism remains unknown.MethodsUsing network pharmacology, we screened the compounds of mSMG and identified its targets and pathway on hepatic IR in T2DM. Using molecular docking, we identified the affinity between the compounds and hub target TNF-α. Then these were verified in KK-Ay mice and HepG2 cells.Results50 compounds and 170 targets of mSMG against IR in T2DM were screened, and 9 hub targets such as TNF and MAPK8 were identified. 170 targets were mainly enriched in insulin resistance and TNF pathway, so we speculated that mSMG might act on TNF-α, JNK1 and then regulate insulin signaling to mitigate IR. Experimental validation proved that mSMG ameliorated hyperglycemia, IR, and TNF-α, enhanced glucose consumption and glycogen synthesis, relieved the phosphorylation of JNK1 and IRS-2 (Ser388), and elevated the phosphorylation of Akt (Ser473) and GSK-3β (Ser9) and GLUT2 expression in KK-Ay mice. Molecular docking further showed berberine from mSMG had excellent binding capacity with TNF-α. Then, in vitro validation experiments, we found that 20% mSMG-MS or 50 μM berberine had little effect in IR-HepG2 cell viability, but significantly increased glucose consumption and glycogen synthesis and regulated TNF-α/JNK1/IRS-2 pathway.ConclusionNetwork pharmacology and molecular docking help us predict potential mechanism of mSMG and further guide experimental validation. mSMG and its representative compound berberine improve hepatic IR and glycogen synthesis, and its mechanism may be related to the inhibition of TNF-α/JNK1/IRS-2 pathway.

Mechanism of emodin in treating hepatitis B virus-associated hepatocellular carcinoma: network pharmacology and cell experiments.

Hepatocellular carcinoma (HCC) is a pressing global issue, with Hepatitis B virus (HBV) infection remaining the primary. Emodin, an anthraquinone compound extracted from the natural plant's. This study investigates the moleculartargets and possible mechanisms of emodin in treating HBV-related HCC based on network pharmacology and molecular docking and validates the screened molecular targets through in vitro experiments. Potential targets related to emodin were obtained through PubChem, CTD, PharmMapper, SuperPred, and TargetNet databases. Potential disease targets for HBV and HCC were identified using the DisGeNET, GeneCards, OMIM, and TTD databases. A Venn diagram was used to determine overlapping genes between the drug and the diseases. Enrichment analysis of these genes was performed using GO and KEGG via bioinformatics websites. The overlapping genes were imported into STRING to construct a protein-protein interaction network. Cytoscape 3.9.1 software was used for visualizing and analyzing the core targets. Molecular docking analysis of the drug and core targets was performed using Schrodinger. The regulatory effects of emodin on these core targets were validate through in vitro experiments. A total of 43 overlapping genes were identified. GO analysis recognized 926 entries, and KEGG analysis identified 135 entries. The main pathways involved in the KEGG analysis included cancer, human cytomegalovirus infection and prostate cancer. The binding energies of emodin with HSP90AA1, PTGS2, GSTP1, SOD2, MAPK3, and PCNA were all less than -5 kcal/mol. Compared to normal liver tissue, the mRNA levels of XRCC1, MAPK3, and PCNA were significantly elevated in liver cancer tissue. The expression levels of XRCC1, HIF1A, MAPK3, and PCNA genes were closely related to HCC progression. High expressions of HSP90AA1, TGFB1, HIF1A, MAPK3, and PCNA were all closely associated with poor prognosis in HCC. In vitro experiments demonstrated that emodin significantly downregulated the expression of HSP90AA1, MAPK3, XRCC1, PCNA, and SOD2, while significantly upregulating the expression of PTGS2 and GSTP1. This study, based on network pharmacology and molecular docking validation, suggests that emodin may exert therapeutic effects on HBV-related HCC by downregulating the expression of XRCC1, MAPK3, PCNA, HSP90AA1, and SOD2, and upregulating the expression of PTGS2 and GSTP1.