Targeting Protein-protein Interactions Research Articles

Network Pharmacological Study on the Mechanism of Cynanchum paniculatum (Xuchangqing) in the Treatment of Bungarus multicinctus Bites.

Background Bungarus multicinctus is one of the top ten venomous snakes in China. Its venom is mainly neurotoxin-based. Novel antivenom drugs need to be further researched and developed. Objective This study aimed to explore the molecular mechanism of Cynanchum paniculatum in treating Bungarus multicinctus bites based on network pharmacology. Material and methods. The potential active ingredients of Cynanchum paniculatum were screened and their SDF structures were obtained using the PubChem database and imported into the SwissTargetPrediction database, and targets were obtained for the antitoxin effects of Cynanchum paniculatum in the treatment of Bungarus multicinctus bites. The Cynanchum paniculatum-active compound-potential target network and protein-protein interaction network were constructed by using Cytoscape software, and then biological function analysis and KEGG pathway enrichment analysis were performed using the DAVID. Results Seven potential active components (cynapanoside C, cynatratoside B, tomentolide A, sitosterol, sarcostin, tomentogenin, and paeonol) and 286 drug targets were obtained, including 30 key targets for the treatment of bungarotoxin toxicity. The active components mainly acted on PIK3CA, MAPK1, MAP2K1, JAK2, FYN, ACHE, CHRNA7, CHRNA4, and CHRNB2, and they antagonized the inhibitory effect of bungarotoxin on the nervous system through cholinergic synapses and the neurotrophin signaling pathway. Conclusions Cynanchum paniculatum exerts a therapeutic effect on Bungarus multicinctus bites through multiple active components, multiple targets, and multiple pathways. The findings provide a theoretical basis for the extraction of active components of Cynanchum paniculatum and for related antivenom experiments.

Abstract 3943: Discovery of a novel menin-MLL inhibitor for potential treatment of MLLr leukemias and NPM1c AML

Abstract Rearrangement of the mixed lineage leukemia (MLL) gene occurs in up to 10% of acute leukemias and is particularly prevalent in infant acute leukemias (~80% of infant ALL cases). MLL-rearranged (MLLr) leukemia is one of the high-risk types of leukemia with aggressive nature, resistance to therapy, and high frequency of early relapse, and currently there are no targeted therapies for its treatment. So, there is huge unmet medical needs for MLLr leukemias. The protein protein interaction (PPI) between menin and MLLr is critical to the pathogenesis of MLLr-driven leukemias by deregulation of the HOXA and MEIS1 genes. It has been demonstrated by both preclinical and clinical studies that blockage of this PPI with menin inhibitors has potential therapeutic effects on MLLr associated acute leukemias. NPM1 mutation (NMP1c) is a frequently mutated gene found in AML, and NMP1 mutated AML depends on menin-MLL interaction for leukemogenesis. Given the fact that wild type MLL and MLLr have similar leukemogenesis-driven target genes like HOXA and MEIS1, as well as the same binding pocket on menin, it was therefore conceived that menin inhibitor could be useful to the treatment of NPM-mutated AML, which was again supported by both preclinical and clinical data. Herein, we would like to report the discovery of our proprietary menin inhibitor. Taking advantage of a couple of key interactions with menin protein, our compounds has relatively low molecular weight for a challenging PPI target, however, demonstrated comparable to or even better potency than those menin inhibitors in clinical trials. Besides in vitro pharmacology data, the DMPK, PK/PD and in vivo efficacy in animal model will be discussed too. Citation Format: Taishan Hu, Zhilin Deng, Honghai Li, Xiaochu Ma, Quanrong Shen, Lei Zhang, Peihua Sun, Ye Hua, Byran Huang. Discovery of a novel menin-MLL inhibitor for potential treatment of MLLr leukemias and NPM1c AML [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3943.

Protein complex structure prediction powered by multiple sequence alignments of interologs from multiple taxonomic ranks and AlphaFold2.

AlphaFold2 can predict protein complex structures as long as a multiple sequence alignment (MSA) of the interologs of the target protein-protein interaction (PPI) can be provided. In this study, a simplified phylogeny-based approach was applied to generate the MSA of interologs, which was then used as the input to AlphaFold2 for protein complex structure prediction. In this extensively benchmarked protocol on nonredundant PPI dataset, including 107 bacterial PPIs and 442 eukaryotic PPIs, we show complex structures of 79.5% of the bacterial PPIs and 49.8% of the eukaryotic PPIs can be successfully predicted, which yielded significantly better performance than the application of MSA of interologs prepared by two existing approaches. Considering PPIs may not be conserved in species with long evolutionary distances, we further restricted interologs in the MSA to different taxonomic ranks of the species of the target PPI in protein complex structure prediction. We found that the success rates can be increased to 87.9% for the bacterial PPIs and 56.3% for the eukaryotic PPIs if interologs in the MSA are restricted to a specific taxonomic rank of the species of each target PPI. Finally, we show that the optimal taxonomic ranks for protein complex structure prediction can be selected with the application of the predicted template modeling (TM) scores of the output models.

Biomedical Analytics of Four Chinese Medicinals in Treatment of Insomnia Based on Network Pharmacology.

Aim Our aim is to recommend the appropriate Chinese medicinals in clinical treatment of insomnia, which are suānzăorén (Semen Ziziphi Spinosae), chuānxiōng (Rhizoma Chuanxiong), fúlíng (Poria), and báisháo (Radix Paeoniae Alba). Method Based on network pharmacology, the active molecules and mechanism of these four Chinese medicinals treating insomnia were sought and analyzed. The components of the four Chinese medicinals with potential activity were collected and screened. Moreover, the recollected human disease-related targets were correlated through Cytoscape 3.8.2, and the network diagram of drug component disease targets was drawn. Based on the human protein-protein interaction database, the above network diagram was imported to establish the protein-protein interaction (PPI) and composite target pathway (C-T-P) networks. After selecting important information, the pathway analysis was carried out to show the biological process, core target, and core pathway of insomnia treatment. Result In this study, 44 active components and 81 drug-disease common targets were obtained; 307 key targets were found in the PPI network; a core cluster composed of 14 nodes and 50 functional associations was found. Conclusion In summary, the four Chinese medicinals' effective components and main mechanism of in the treatment of insomnia may be related to their participation in the regulation of endocrine. Compared with the existing network pharmacological analysis results of SuānZăoRénTāng (Sour Jujube Decoction), which is commonly used in insomnia, they have similar effects on the immune system and HPA axis, while the focus of the four Chinese medicinals is mainly on endocrine regulation, and SuānZăoRénTāng (Sour Jujube Decoction) is mainly on anti-inflammatory effect.

Structure-based assessment and druggability classification of protein–protein interaction sites

The featureless interface formed by protein–protein interactions (PPIs) is notorious for being considered a difficult and poorly druggable target. However, recent advances have shown PPIs to be druggable, with the discovery of potent inhibitors and stabilizers, some of which are currently being clinically tested and approved for medical use. In this study, we assess the druggability of 12 commonly targeted PPIs using the computational tool, SiteMap. After evaluating 320 crystal structures, we find that the PPI binding sites have a wide range of druggability scores. This can be attributed to the unique structural and physiochemical features that influence their ligand binding and concomitantly, their druggability predictions. We then use these features to propose a specific classification system suitable for assessing PPI targets based on their druggability scores and measured binding-affinity. Interestingly, this system was able to distinguish between different PPIs and correctly categorize them into four classes (i.e. very druggable, druggable, moderately druggable, and difficult). We also studied the effects of protein flexibility on the computed druggability scores and found that protein conformational changes accompanying ligand binding in ligand-bound structures result in higher protein druggability scores due to more favorable structural features. Finally, the drug-likeness of many published PPI inhibitors was studied where it was found that the vast majority of the 221 ligands considered here, including orally tested/marketed drugs, violate the currently acceptable limits of compound size and hydrophobicity parameters. This outcome, combined with the lack of correlation observed between druggability and drug-likeness, reinforces the need to redefine drug-likeness for PPI drugs. This work proposes a PPI-specific classification scheme that will assist researchers in assessing the druggability and identifying inhibitors of the PPI interface.

A New Method for Undruggable Targets: Amino Acids as Fragments of Inhibitors

Over the last decade, protein‐protein interactions (PPIs) have emerged as promising targets in the precise treatment of serious diseases. Many essential cellular pathways that are implicated in human diseases are controlled by intracellular PPIs. Such PPIs could be potential drug targets, and thus the ability of molecules to inhibit specific PPIs has remarkable therapeutic value. Unfortunately, PPI interfaces are generally large and present great difficulty for small molecule inhibitor design. Alternate strategies are being developed towards drug design and discovery for this type of target. For example, the synthesis of unnatural amino acids allows production of extremely large libraries of highly modified peptides, which may be screened against a PPI target. Peptide hits are a potential source of lead compounds in the search for new pharmaceutical agents and are promising for PPI inhibition. It is in this context that selection of the right unnatural amino acid becomes crucial.For this reason, developing new strategies to solve this problem is a key factor to find more efficient and specific inhibitors to PPI’s.In this study, we introduce a simple, Nuclear Magnetic Resonance (NMR) based methodology that screens natural and unnatural amino acids as “fragments” for development of new peptide‐based inhibitors for specific PPI’s. We validate this new method against MDM2, a well‐characterized and important negative regulator of the p53 tumor suppressor with known small peptides that inhibit its interaction with p53. A central tryptophan is the largest contributor to binding in this interface, and the corresponding MDM2 binding pocket is where we focused our efforts. Using this methodology, we screened non‐natural tryptophan derivatives, and several displayed a better binding affinity compared with the natural counterpart. Our simplified method allows priority ranking of amino acids according to their affinity to the protein. The highest‐ranking amino acids will be incorporated into peptides synthetically to confirm that improved free amino acid affinity translates to enhanced peptide binding and inhibition. In addition, this serves as a convenient and robust method to ‘pre‐screen’ amino acids for incorporation into in vitro peptide selection via mRNA display.

A network-based pharmacological study on the mechanism of action of muscone in breast cancer.

BackgroundThe purpose of this study was to investigate the mechanism of action of muscone on breast cancer using network pharmacology and molecular docking techniques.MethodsTargets of muscone acid action were collected using the PubChem and SwissTargetPrediction databases. Relevant target sets of breast cancer were collected using the GeneCards database, and the intersection of the drug-disease targets was used as the potential target of muscone action in breast cancer. The STRING database was used to construct a target protein-protein interaction (PPI) network, and the data were imported into Cytoscape 3.7.1 for topological network analysis to obtain the core target genes of muscone in breast cancer. Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the DAVID database. The correlation of core gene expression with breast cancer survival was analyzed using the online Kaplan-Meier plotter tool. Molecular docking of core target genes to muscone was performed using AutoDock Vina.ResultsA total of 18 common targets of muscone and breast cancer were obtained through target intersection. The PPI map and topology analysis revealed that androgen receptor (AR), progesterone receptor (PGR), matrix metalloproteinase 9 (MMP9), prostaglandin-endoperoxide synthase 2 (PTGS2), heat shock protein 90 alpha family class A member 1 (HSP90AA1), mitogen-activated protein kinase 14 (MAPK14), and cytochrome P450 family 19 subfamily A member 1 (CYP19A1) might be the key targets of muscone acting on breast cancer. The GO enrichment analysis identified 60 terms, while the KEGG pathway enrichment analysis identified 7 signaling pathways, including steroid hormone biosynthesis, ovarian steroidogenesis, cancer pathways, and the tumor necrosis factor (TNF) signaling pathway. The results of survival stage analysis showed that the binding activity between muskone and key targets was better than other targets. The molecular docking results showed that muscone had the highest docking affinity for the key target CYP19A1 gene at −7.0 kJ/moL.ConclusionsMuscone might exert anti–breast cancer effects through cancer pathways, ovarian steroidogenesis, and TNF signaling pathways and has the potential to be developed as a clinical agent.

Licoflavone A Suppresses Gastric Cancer Growth and Metastasis by Blocking the VEGFR-2 Signaling Pathway.

Objectives Licoflavone A (LA) is a natural flavonoid compound derived from the root of Glycyrrhiza. This study investigated the antitumor effect and underlying molecular mechanisms of LA against gastric cancer (GC) in vitro and in vivo. Materials and Methods A CCK8 assay was used to measure the antiproliferative activity of LA in human GC SGC-7901, MKN-45, MGC-803 cells, and human GES-1 cells. Target prediction and protein-protein interaction (PPI) analysis were used to identify the potential molecular targets of LA. The binding pattern of LA to VEGFR-2 was analyzed by molecular docking and molecular dynamic (MD). The affinity of LA for VEGFR-2 was determined by microscale thermophoresis (MST). The protein tyrosine kinase activity of VEGFR-2 in the presence of LA was determined by an enzyme activity test. The effect of LA on the proliferation of VEGF-stimulated MKN-45 cells was measured with CCK8 assays, clone formation assays, and 3D microsphere models. Hoechst 33342 staining, FCM, MMP, and WB assays were used to investigate the ability of LA to block cell cycle and promote apoptosis of VEGF-stimulated MKN-45 cells. Transwell matrix assays were used to measure migration and invasion, and WB assays were used to measure EMT. Results LA inhibited the proliferation of SGC-7901, MKN-45, and MGC-803 cells and VEGF-stimulated MKN-45 cells. VEGFR-2 was identified as the target of LA. LA could also block cell cycle, induce apoptosis, and inhibit migration, invasion, and EMT of VEGF-stimulated MKN-45 cells. Functional analyses further revealed that the cytotoxic effect of LA on VEGF-stimulated MKN-45 cells potentially involved the PI3K/AKT and MEK/ERK signaling pathways. Conclusions This study demonstrates that LA has anti-GC potency in vitro and in vivo. LA affects the proliferation, cycle, apoptosis, migration, invasion, and EMT by targeting VEGFR-2 and blocks the PI3K/AKT and MEK/ERK signaling pathways in VEGF-stimulated MKN-45 cells.

Anti-inflammatory mechanism of rhein in treating asthma based on network pharmacology.

To predict the anti-inflammatory targets and related pathways of rhein in the treatment of asthma by using network pharmacology, and to further explore its potential mechanism in asthma. The corresponding targets of rhein were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the rhein-target network was constructed with Cytoscape 3.7.1 software. The Genbank and Drugbank databases were used to collect and screen asthma targets, and the rhein-target-disease interaction network was constructed. A target protein-protein interaction (PPI) network was constructed using the STRING database to screen key targets. Finally, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was used to identify biological processes and signaling pathways. The anti-asthmatic effects of rhein were tested in vitro, and the expression levels of proteins in the mitogen-activated protein kinase/nuclear factor kappa-B (MAPK/ NF-κB) signaling pathway were assessed by western blot analysis. Altogether, 83 targets of rhein were screened in the relevant databases, 989 targets of asthma were obtained in the National Center for Biotechnology Information (NCBI) GENE Database. PPI network analysis and KEGG pathway enrichment analysis predicted that rhein could regulate the epidermal active growth factor receptor (EGFR), mitogen-activated protein kinase 14 (MAPK14), tumour necrosis factor receptor superfamily member 1A (TNFRSF1A), receptor tyrosine-protein kinase erbB-2 (ERBB2), and other signaling pathways. Furthermore, we selected the MAPK signaling pathway to determine the anti-inflammatory effects of rhein. Consistently, further experiments demonstrated that rhein was shown to inhibit HBE cells inflammation. The anti-inflammatory mechanism of rhein in the treatment of asthma may be related to EGFR, MAPK14, TNFRSF1A and ERBB2 as well as their signaling pathways. To prevent the exacerbation of asthma, instead of targeting a single pathway or a single target, all these targets and their signaling pathways should be controlled holistically. Rhein may alleviate the inflammation of asthma by inhibiting the MAPK/NF-κB pathway.

Methods for the Discovery and Identification of Small Molecules Targeting Oxidative Stress-Related Protein-Protein Interactions: An Update.

The oxidative stress response pathway is one of the hotspots of current pharmaceutical research. Many proteins involved in these pathways work through protein–protein interactions (PPIs). Hence, targeting PPI to develop drugs for an oxidative stress response is a promising strategy. In recent years, small molecules targeting protein–protein interactions (PPIs), which provide efficient methods for drug discovery, are being investigated by an increasing number of studies. However, unlike the enzyme–ligand binding mode, PPIs usually exhibit large and dynamic binding interfaces, which raise additional challenges for the discovery and optimization of small molecules and for the biochemical techniques used to screen compounds and study structure–activity relationships (SARs). Currently, multiple types of PPIs have been clustered into different classes, which make it difficult to design stationary methods for small molecules. Deficient experimental methods are plaguing medicinal chemists and are becoming a major challenge in the discovery of PPI inhibitors. In this review, we present current methods that are specifically used in the discovery and identification of small molecules that target oxidative stress-related PPIs, including proximity-based, affinity-based, competition-based, structure-guided, and function-based methods. Our aim is to introduce feasible methods and their characteristics that are implemented in the discovery of small molecules for different types of PPIs. For each of these methods, we highlight successful examples of PPI inhibitors associated with oxidative stress to illustrate the strategies and provide insights for further design.

Molecular Assessment of Scutellaria barbata D. Don in the Treatment of Nasopharyngeal Carcinoma Based on Network Pharmacology and Experimental Verification.

Objective To predict the molecular mechanisms behind the benefits of Scutellaria barbata D. Don (S. barbata) in nasopharyngeal carcinoma (NPC) by network pharmacology and experimental verification. Methods The active ingredients and targets of S. barbata were searched in the traditional Chinese medicine system pharmacology database and analysis platform, and the disease targets of NPC were obtained by searching the GeneCards database. A common target protein-protein interaction network was constructed by STRING, and then, an active ingredients-NPC-target interaction network map was constructed by Cytoscape 3.7.2 software. The functional enrichment analyses of Gene Ontology and KEGG pathway data were carried out by R software programming. Finally, cell proliferation was assessed by CCK8, apoptosis was detected by Annexin V-FITC/PI double fluorescence staining, and protein expression was analyzed by Western blotting. Results In this study, 29 active ingredients were found in S. barbata. Among these, the main targets for NPC were baicalein, wogonin, luteolin, and quercetin. The main molecular targets of S. barbata on NPC were EGFR, MYC, CASP3, CCND1, and ESR1. The main biological processes involved the binding of DNA-binding transcription factors, RNA polymerase II-specific DNA-binding transcription factors, ubiquitin-like protein ligases, and ubiquitin-protein ligases. S. barbata mainly affects NPC through the PI3K-Akt, p53, and MAPK signaling pathways. The experimental results showed that baicalein and wogonin could inhibit proliferation and induce apoptosis of NPC cells and downregulate the expression of PI3K, AKT, and p53, the key proteins of the PI3K/AKT and p53 signaling pathway in CNE2 cells. Conclusion Baicalein and wogonin, the main active ingredients of S. barbata, inhibited the proliferation and induced apoptosis of NPC cells through the PI3K/AKT and p53 signaling pathways.

Network pharmacology and molecular docking analysis reveals the mechanism of asiaticoside on COVID-19.

BackgroundAsiaticoside (AS) is a saponin extracted from the traditional Chinese herbal medicine Centella Asiatica, which has the effects of reducing inflammatory infiltration and anti-oxidation in pneumonia and combating pulmonary fibrosis. We hypothesize that AS might have therapeutic potential for the treatment of the coronavirus disease 2019 (COVID-19). With the help of network pharmacology and molecular docking techniques, this study discussed the underlying molecular mechanism of AS in the treatment of COVID-19.MethodsThe molecular structure of AS was obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) system. The targets of AS were achieved using PharmMapper, SwissTargetPrediction, and the Comparative Toxicogenomics Database (CTD). The targets corresponding to COVID-19 were obtained using GeneCards, Online Mendelian Inheritance in Man (OMIM), and CTD database. Then, a target protein-protein interaction (PPI) network was formed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. A network of AS, COVID-19, and their co-targets was built using Cytoscape. Afterwards, the co-targets were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Moreover, the predictions of crucial targets were further investigated by performing molecular docking with AS.ResultsA total of 45 core targets of AS were found to be engaged in the pathogenesis of COVID-19. The KEGG enrichment analysis indicated that AS might be protective against COVID-19 through inflammation- and immune-related signaling pathways, including interleukin-17 (IL-17) signaling, T helper 17 (Th17) cell differentiation pathway, Coronavirus disease-COVID-19, MAPK, the PI3K-Akt signaling pathway, and so on. The results of molecular docking showed that AS had a high affinity with those core targets.ConclusionsThe beneficial effect of AS on COVID-19 might be through regulating multiple immune or inflammation-related targets and signaling pathways.

Mechanisms and Molecular Targets of BuShenHuoXue Formula for Osteoarthritis.

The aim was to identify latent mechanism of BuShenHuoXue (BSHX) formula for the management of osteoarthritis (OA) through the network pharmacology approach and experimental validation. We obtained OA-related targets through the Gene Expression Omnibus database and bioactive ingredients with corresponding targets in the formula via the Traditional Chinese Medicine Systems Pharmacology database. Subsequently, networks of the protein–protein interaction and compound-disease target were created and enrichment analysis was implemented. Furthermore, in vitro, IL-1β was applied to rat chondrocytes to mediate apoptosis through inflammation and the Alcian blue and type II collagen staining was used to observe cell morphology. The TUNEL and DAPI staining was performed to observe chondrocyte apoptosis, and the apoptosis rates were gauged via flow cytometry. In addition, we utilized Western blot and PCR to detect the protein and mRNA expression, respectively. A total of 104 potential chemicals and 42 intersecting targets were screened out. Quercetin and luteolin from BSHX formula were principal ingredients. The experiment validated quercetin might suppress chondrocyte apoptosis mediated by IL-1β and reduce SELE, MMP2, and COL1 expression. Via the AGE-RAGE signaling pathway in diabetic complications, quercetin could aim at SELE, MMP2, and COL1 and exert antagonistic effects against OA.

PEPscan: A Broad Spectrum Approach for the Characterization of Protein-Binder Interactions?

In a previous study, we have shown that PEPscan can provide a cheap and rapid means to identify candidate interfering peptides (IPs), i.e., peptides able to disrupt a target protein-protein interaction. PEPscan was shown to be effective in identifying a limited number of candidate IPs specific to the target interaction. Here, we investigate the results of 14 new PEPscan experiments for protein complexes of known 3D structures. We show that for almost all complexes, PEPscan is able to identify candidate IPs that are located at the protein-protein interface. The information it provides about the binding site seems, however, too ambiguous to be exploited in a simple manner to assist the modeling of protein complexes. Moreover, these candidates are associated with false positives. For these, we suggest they could correspond to non-specific binders, which leaves room for further optimization of the PEPscan protocol. Another unexpected advance comes from the observation of the applicability of PEPscan for polysaccharides and labeled peptides, suggesting that PEPscan could become a large spectrum approach to investigate protein-binder interactions, the binder not necessarily being a protein.

Systematic Understanding of Mechanism of Danggui Shaoyao San against Ischemic Stroke Using a Network Pharmacology Approach.

Purpose Danggui Shaoyao San (DSS) was developed to treat the ischemic stroke (IS) in patients and animal models. The purpose of this study was to explore its active compounds and demonstrate its mechanism against IS through network pharmacology, molecular docking, and animal experiment. Methods All the components of DSS were retrieved from the pharmacology database of TCM system. The genes corresponding to the targets were retrieved using OMIM, CTD database, and TTD database. The herb-compound-target network was constructed by Cytoscape software. The target protein-protein interaction network was built using the STRING database. The core targets of DSS were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Then, we achieved molecular docking between the hub proteins and the key active compounds. Finally, animal experiments were performed to verify the core targets. Triphenyltetrazolium chloride (TTC) staining was used to calculate the infarct size in mice. The protein expression was determined using the Western blot. Results Compound-target network mainly contained 51 compounds and 315 corresponding targets. Key targets contained MAPK1, SRC, PIK3R1, HRAS, AKT1, RHOA, RAC1, HSP90AA1, and RXRA FN1. There were 417 GO items in GO enrichment analysis (p < 0.05) and 119 signaling pathways (p < 0.05) in KEGG, mainly including negative regulation of apoptosis, steroid hormone-mediated signaling pathway, neutrophil activation, cellular response to oxidative stress, and VEGF signaling pathway. MAPK1, SRC, and PIK3R1 docked with small molecule compounds. According to the Western blot, the expression of p-MAPK 1, p-AKT, and p-SRC was regulated by DSS. Conclusions This study showed that DSS can treat IS through multiple targets and routes and provided new insights to explore the mechanisms of DSS against IS.

A network pharmacology-based strategy for predicting the protective mechanism of Ginkgo biloba on damaged retinal ganglion cells.

Hallmarks of the pathophysiology of glaucoma are oxidative stress and apoptotic death of retinal ganglion cells (RGCs). Ginkgo biloba extract (EGb) with multi-target, multi-pathway functions has been reported to exert positive pharmacological effects on oxidative stress and damaged RGCs. However, the ingredients and anti-apoptotic targets of EGb in the treatment of open-angle glaucoma (OAG) have not been fully elucidated. Therefore, in-depth analysis is necessary for further research. Ginkgo biloba-related and anti-apoptotic targets were identified and then combined to obtain the intersection, representing the potential anti-apoptotic targets of Ginkgo biloba. In addition, compound-anti-apoptotic target and OAG-target protein-protein interaction network were merged to obtain five core genes and compound-OAG-anti-apoptotic target protein-protein interaction network. Consequently, the active compounds and anti-apoptotic targets of Ginkgo biloba in the treatment of OAG were identified, namely luteolin, β-sitosterol, kaempferol, stigmasterol, quercetin, and p53, Bax, Bcl-2, Caspase-3 and Caspase-9, respectively. For the anti-apoptotic targets of Ginkgo biloba in the treatment of OAG, Gene Ontology (GO) and pathway analysis were executed to confirm the gene functions of Ginkgo biloba in antagonizing apoptosis of RGCs. The pathway enrichment was mainly involved in transcriptional activation of p53 responsive genes, activation of caspases and apoptotic processes. Finally, we confirmed the results of the network analysis by H2O2 treated RGC-5 cells in vitro. The results demonstrated that EGb protection can effectively diminish H2O2-induced apoptosis by inhibiting p53 acetylation, reducing the ratio of Bax/Bcl-2 and suppressing the expression of specific cleavage of Caspase-9 and Caspase-3.

Matrix Stiffness-Induced Transcriptome Alterations and Regulatory Mechanisms Revealed by RNA-Seq in Endothelial Cells

Changes in vascular stiffness are associated with the development and progression of many diseases, especially in cardiovascular disease. However, the effect of vascular stiffness on the endothelial cells (ECs) is not fully understood. Therefore, this study aims to determine the gene expression changes of ECs cultured on the matrices with different stiffness (1 kPa and 40 kPa, respectively) by RNA-seq, thereby broadening the knowledge between mechanics and biology. We obtained 1775 differentially expressed genes (DEGs) by RNA-seq, with 450 up-regulated and 1325 down-regulated DEGs in ECs cultured on soft matrix (1 kPa) compared to those cultured on stiff matrix (40 kPa). After that, we performed a series of functional enrichment analyses based on DEGs and found that DEGs were enriched in many signaling pathways like adhesion junction. Furthermore, transcription factor (TF) target gene prediction analysis and protein-protein interaction (PPI) analysis were also conducted. We found that mechanotransduction signaling related TFs such as BRD4 are involved in. And in the PPI analysis, some genes encoding extracellular matrix proteins such as fibronectin 1 (FN1) were identified as the hub genes. In order to confirm the RNA-seq results, we performed real-time qPCR analysis on the genes of interest, including FN1, collagen α2 (IV) chain, matrix metalloproteinase-14 and integrin α5, and found that the expression levels of all these genes were down-regulated on soft matrix, suggesting that soft matrix caused by pathological conditions may directly attenuate vascular barrier function. This study offers the insights about the effects of physical stimulation on cells, paving a way for vascular tissue engineering, regenerative medicine, disease modeling and therapies.

Exploring the Mechanism of Panax notoginseng Saponins against Alzheimer's Disease by Network Pharmacology and Experimental Validation.

Background Panax notoginseng saponins (PNS) have been used for neurodegenerative disorders such as cerebral ischemia and Alzheimer's disease (AD). Although increasing evidences show the neuron protective effects of PNS, the vital compounds and their functional targets remain elusive. To explore the potential functional ingredients of PNS for the AD treatment and their molecular mechanisms, an in vitro neuron injured model induced by Aβ was investigated, and the potential mechanism was predicted by network pharmacology approach and validated by molecular biology methods. Methods Network pharmacology approach was used to reveal the relationship between ingredient-target disease and function-pathway of PNS on the treatment of AD. The active ingredients of PNS were collected from TCMSP, PubChem database, and literature mining in PubMed database. DrugBank and GeneCards database were used to predict potential targets for AD. The STRING database was performed to reveal enrichment of these target proteins, protein-protein interactions, and related pathways. Networks were visualized by utilizing Cytoscape software. The enrichment analysis was performed by the DAVID database. Finally, neuroprotective effect and predictive mechanism of PNS were investigated in an in vitro AD model established by Aβ25–35-treated PC12 cells. Results An ingredient-target disease and function-pathway network demonstrated that 38 active ingredients were derived from PNS modulated 364 common targets shared by PNS and AD. GO and KEGG analysis, further clustering analysis, showed that mTOR signaling targets were associated with the neuroprotective effects of PNS. In Aβ-treated PC12 cells, PNS treatment improved neuroprotective effect, including mTOR inhibition and autophagy activation. Conclusions Collectively, the protective effects of PNS on AD-neuron injury are related to the inhibition of mTOR and autophagy activation.

Computational Prediction of Biomarkers, Pathways, and New Target Drugs in the Pathogenesis of Immune-Based Diseases Regarding Kidney Transplantation Rejection.

BackgroundThe diagnosis of graft rejection in kidney transplantation (KT) patients is made by evaluating the histological characteristics of biopsy samples. The evolution of omics sciences and bioinformatics techniques has contributed to the advancement in searching and predicting biomarkers, pathways, and new target drugs that allow a more precise and less invasive diagnosis. The aim was to search for differentially expressed genes (DEGs) in patients with/without antibody-mediated rejection (AMR) and find essential cells involved in AMR, new target drugs, protein-protein interactions (PPI), and know their functional and biological analysis.Material and MethodsFour GEO databases of kidney biopsies of kidney transplantation with/without AMR were analyzed. The infiltrating leukocyte populations in the graft, new target drugs, protein-protein interactions (PPI), functional and biological analysis were studied by different bioinformatics tools.ResultsOur results show DEGs and the infiltrating leukocyte populations in the graft. There is an increase in the expression of genes related to different stages of the activation of the immune system, antigenic presentation such as antibody-mediated cytotoxicity, or leukocyte migration during AMR. The importance of the IRF/STAT1 pathways of response to IFN in controlling the expression of genes related to humoral rejection. The genes of this biological pathway were postulated as potential therapeutic targets and biomarkers of AMR. These biological processes correlated showed the infiltration of NK cells and monocytes towards the allograft. Besides the increase in dendritic cell maturation, it plays a central role in mediating the damage suffered by the graft during AMR. Computational approaches to the search for new therapeutic uses of approved target drugs also showed that imatinib might theoretically be helpful in KT for the prevention and/or treatment of AMR.ConclusionOur results suggest the importance of the IRF/STAT1 pathways in humoral kidney rejection. NK cells and monocytes in graft damage have an essential role during rejection, and imatinib improves KT outcomes. Our results will have to be validated for the potential use of overexpressed genes as rejection biomarkers that can be used as diagnostic and prognostic markers and as therapeutic targets to avoid graft rejection in patients undergoing kidney transplantation.

Elucidating the Mechanism of Action of Salvia miltiorrhiza for the Treatment of Acute Pancreatitis Based on Network Pharmacology and Molecular Docking Technology.

Using network pharmacology and molecular docking, this study investigated the molecular mechanisms by which the active components in Salvia miltiorrhiza can alleviate acute pancreatitis. Initially, the active components of Salvia miltiorrhiza and the targets collected from the GeneCards database were screened based on the platform of systematic pharmacology analysis of traditional Chinese medicine. Subsequently, the active components were intersected with the disease targets. Also, interactions among the targets were computed using the STRING database. Biological function and pathway enrichment were analyzed using the Cluster Profiler package in the R software. Protein-protein interaction and component target pathway network were constructed using the Cytoscape software. Ultimately, the key targets and their corresponding components in the network were verified using the AutoDock Vina software. The results showed Salvia miltiorrhiza had 111 targets for acute pancreatitis. The biological process (BP) analysis showed that the active components of Salvia miltiorrhiza induced a drug response, positive regulation of transcription by RNA polymerase II promoter, signal transduction, positive regulation of cell proliferation, and negative regulation of apoptosis. Furthermore, the KEGG enrichment analysis screened 118 (P < 0.05) signaling pathways, such as the pathways related to cancer, neuroactive ligand-receptor interaction, PI3K-Akt signaling pathway, and cAMP signaling pathway, to name a few. Finally, molecular docking showed that the active components of Salvia miltiorrhiza had a good binding affinity with their corresponding target proteins. Through network pharmacology, this study predicted the potential pharmacodynamic material basis and the mechanisms by which Salvia miltiorrhiza can treat acute pancreatitis. Moreover, this study provided a scientific basis for mining the pharmacodynamic components of Salvia miltiorrhiza and expanding the scope of its clinical use.