Search Tool For Interactions Of Chemicals Research Articles

Molecular Docking Analysis of Four Drugs (Phenytoin, Amoxicillin, Aceclofenac and Ciprofloxacin) and Their Association With Four Human Leukocyte Antigen (HLA) Alleles.

Background Numerous reports have shown the role of human leukocyte antigen (HLA) alleles in the induction of cutaneous adverse drug reactions by moderating drug metabolism. Wetherefore aimed to investigate the docking patterns of four HLA alleles (HLA-B x 5101, HLA-B x 1501, HLA-A x 02:06 and HLA-B x 57:01) against four commercial drugs. Methodology Four drugs (phenytoin (PHT), amoxicillin (AMX), aceclofenac (ACE) and ciprofloxacin (CIP)) were investigated for their docking behavior against four HLA alleles (HLA-B x 5101, HLA-B x 1501, HLA-A x 02:06, and HLA-B x 57:01) using the SwissDock method. In addition, toxicity (Tox) and the search tool for interactions of chemicals (STITCH) (protein-drug interaction) analyses were also carried out using the predicating the small molecule pharmaco-kinetic (pk) properties using graph-based signature method (pkCSM) and STITCH free online servers, respectively. Results Toxicity analysis showed that two drugs (amoxicillin and ciprofloxacin) exhibit hepatotoxicity. The STITCH analysis of the drug amoxicillin revealed its interaction with two humanproteins. The drug phenytoin exhibited the lowest binding energy (LBE) with all four HLA alleles (HLA-B x 5101, HLA-B x 1501, HLA-A x 02:06, and HLA-B x 57:01). Conclusions The present findings provide new knowledge about the four drugs (phenytoin (PHT), amoxicillin (AMX), aceclofenac (ACE) and ciprofloxacin (CIP)) and their binding affinities with HLA alleles, which may cause cutaneous adverse drug reactions.

Sivelestat (Neutrophil Elastase Inhibitor) as an Anti-inflammatory and Anti-viral Agent: An In Silico Study.

Background Sivelestat is a potent and specific neutrophil elastase inhibitor. It is clinically used in treating lung injury and respiratory distress syndrome. This engaged us to undertake the present study in which sivelestat was studied as an anti-inflammatory and anti-viral agent. Methodology The docking study of sivelestat on matrix metalloproteinase-2 (MMP-2), matrix metalloproteinase-9 (MMP-9), chikungunya virus nonstructural protein-2 (CVnsP2) protease, and influenza A (H1N9) virus neuraminidase was assessed using the Chemistry at Harvard Macromolecular Mechanics (CHARMM) Dock (CDOCK) method. Furthermore, molecular physicochemical; bioactivity; absorption, distribution, metabolism, and excretion (ADME); toxicity; and Search Tool for Interacting Chemicals (STITCH) analyses were performed by using the Molinspiration (Molinspiration Cheminformatics, Slovensky Grob, Slovak Republic), SwissADME SwissADME (Swiss Institute of Bioinformatics, Quartier Sorge - Bâtiment Amphipôle, Switzerland), pkCSM (University of Melbourne, Melbourne, Australia), and STITCH-free online tools. Results The molecular physicochemical assessment of the ligand (sivelestat) showed no (zero) violation and agreed with the thumb rule of five, otherwise known as Lipinski's rule of five. ADME prediction of the ligand (sivelestat) is shown to possess a low gastrointestinal absorption (GIA) property. Similarly, toxicity analysis of the ligand (sivelestat) is predicted to have a hepatotoxicity effect. STITCH analysis reveals that the ligand (sivelestat) has exhibited interactions with the three human proteins. Conclusions The present molecular docking studies showed that the ligand (sivelestat) has successfully docked with all four enzymes of interest. Hence, the current finding has provided a good understanding of sivelestat as an effective suppressor activity against all four enzymes: MMP-2, MMP-9, CVnsP2 protease, and influenza neuraminidase.

Insights into dietary phytochemicals targeting Parkinson's disease key genes and pathways: A network pharmacology approach

Parkinson's disease (PD) is a complex neurological disease associated with the degeneration of dopaminergic neurons. Oxidative stress is a key player in instigating apoptosis in dopaminergic neurons. To improve the survival of neurons many dietary phytochemicals have gathered significant attention recently. Thus, the present study implements a comprehensive network pharmacology approach to unravel the mechanisms of action of dietary phytochemicals that benefit disease management. A literature search was performed to identify ligands (i.e., comprising dietary phytochemicals and Food and Drug Administration pre-approved PD drugs) in the PubMed database. Targets associated with selected ligands were extracted from the search tool for interactions of chemicals (STITCH) database. Then, the construction of a gene-gene interaction (GGI) network, analysis of hub-gene, functional and pathway enrichment, associated transcription factors, miRNAs, ligand-target interaction network, docking were performed using various bioinformatics tools together with molecular dynamics (MD) simulations. The database search resulted in 69 ligands and 144 unique targets. GGI and subsequent topological measures indicate histone acetyltransferase p300 (EP300), mitogen-activated protein kinase 1 (MAPK1) or extracellular signal-regulated kinase (ERK)2, and CREB-binding protein (CREBBP) as hub genes. Neurodegeneration, MAPK signaling, apoptosis, and zinc binding are key pathways and gene ontology terms. hsa-miR-5692a and SCNA gene-associated transcription factors interact with all the 3 hub genes. Ligand-target interaction (LTI) network analysis suggest rasagiline and baicalein as candidate ligands targeting MAPK1. Rasagiline and baicalein form stable complexes with the Y205, K330, and V173 residues of MAPK1. Computational molecular insights suggest that baicalein and rasagiline are promising preclinical candidates for PD management.

Construction of microgravity biological knowledge graph and its applications in anti-osteoporosis drug prediction

Microgravity in the space environment can potentially have various negative effects on the human body, one of which is bone loss. Given the increasing frequency of human space activities, there is an urgent need to identify effective anti-osteoporosis drugs for the microgravity environment. Traditional microgravity experiments conducted in space suffer from limitations such as time-consuming procedures, high costs, and small sample sizes. In recent years, the in-silico drug discovery method has emerged as a promising strategy due to the advancements in bioinformatics and computer technology. In this study, we first collected a total of 184,915 literature articles related to microgravity and bone loss. We employed a combination of dependency path extraction and clustering techniques to extract data from the text. Afterwards, we conducted data cleaning and standardization to integrate data from several sources, including The Global Network of Biomedical Relationships (GNBR), Curated Drug–Drug Interactions Database (DDInter), Search Tool for Interacting Chemicals (STITCH), DrugBank, and Traditional Chinese Medicines Integrated Database (TCMID). Through this integration process, we constructed the Microgravity Biology Knowledge Graph (MBKG) consisting of 134,796 biological entities and 3,395,273 triplets. Subsequently, the TransE model was utilized to perform knowledge graph embedding. By calculating the distances between entities in the model space, the model successfully predicted potential drugs for treating osteoporosis and microgravity-induced bone loss. The results indicate that out of the top 10 ranked western medicines, 7 have been approved for the treatment of osteoporosis. Additionally, among the top 10 ranked traditional Chinese medicines, 5 have scientific literature supporting their effectiveness in treating bone loss. Among the top 20 predicted medicines for microgravity-induced bone loss, 15 have been studied in microgravity or simulated microgravity environments, while the remaining 5 are also applicable for treating osteoporosis. This research highlights the potential application of MBKG in the field of space drug discovery.

Multiple gene-drug prediction tool reveals Rosiglitazone based treatment pathway for non-segmental vitiligo

Vitiligo is a skin disease characterized by selective loss of melanocytes, which seriously affects the appearance and causes great psychological stress to patients. In this study, we performed a comprehensive analysis of two vitiligo microarray datasets from the GEO database using bioinformatics tools to identify 297 up-regulated mRNAs and 186 down-regulated mRNAs, revealing important roles for pathways related to melanin synthesis, tyrosine metabolism, and inflammatory factors, such as “PPAR signaling pathway”, “tyrosine metabolism”, “nonalcoholic fatty liver disease (NAFLD) pathway”, “melanogenesis”, and “IL-17 signaling pathway”. Combining the Search Tool for Interacting Chemicals (STITCH) database 5.0 and the drug-gene interaction database 3.0 (DGIdb), we identified that the PPAR-γ agonist rosiglitazone may promote melanin synthesis via EDNRB. Next, we investigated the mechanism of rosiglitazone and PPAR-γ pathway in promoting melanin production. Consistent with the results of bioinformatics analysis, the expression levels of PPAR-γ, EDNRB, and TYR were significantly reduced in human non-segmental vitiligo skin along with the reduction of MITF, a key gene for epidermal melanogenesis. Meanwhile, rosiglitazone increased melanin synthesis capacity in melanocytes and zebrafish by activating PPAR-γ and upregulating TYR, TYRP-1, and TYRP-2. Conversely, treatment of melanocytes with the PPAR-γ antagonist GW resulted in inhibition of melanin synthesis and expression of melanin-related factors. At the same time, simultaneous treatment of rosiglitazone with GW reversed the inhibitory effect of GW on melanin synthesis. In this study, we identified that rosiglitazone, an important insulin sensitizer, promotes melanin synthesis in melanocytes by increasing PPAR-γ activity and upregulating the expression levels of EDNRB and TYR. These findings may provide new ideas for exploring the pathogenesis and potential therapeutic targets of non-segmental vitiligo.

Targeting ADA and HIV-1 Nef Protein with Protease Inhibitors: a Repurposing Strategy through Molecular Networking and an in silico Approach for Integrated Management of HIV Co-infected with Abdominal Tuberculosis

Background: Background: The co-infection of HIV and abdominal TB poses a worldwide danger to humanity. This is because there are more strains of bacteria that are resistant to many classes of currently available medications. According to current findings, repurposing existing available medications will result in more effective functioning than using newly designed medications. Objective: Based on this fact, we hypothesised that the PI could be repurposed; we used Food and Drug Administration (FDA)-approved PI drugs to treat HIV co-infected patients with abdominal TB, and a computational study has been conducted. Method: This comprises network analysis models to find their protein drug interaction (PDI) through a search tool for interacting chemicals (STICH) module of Cytoscape network analysis model followed by the screening of these drugs for their ADMET prediction and binding affinity with adenosine deaminase (ADA), a protein responsible for abdominal TB, and the HIV-1 Nef protein, responsible for the regulation of immune function (CD4+). Result: The network analysis showed 13 nearest binding drugs of these proteins of interest. The ADMET study result showed the pharmacologically relevant parameters that have a significant effect on the binding affinity, bioavailability, and toxicity of PI. The top three scores achieved by PI against adenosine deaminase enzyme activity (PDB ID: 1A4M) are viz., -23.7919, -23.3529, and -22.6773 for Ritonavir, Tipranavir, and Atazanavir, respectively. The top three scores achieved by PI against HIV-1 Nef protein activity (PDB ID: 6URI) are viz., -28.7321, -28.4987, and -28.3155 for Atazanavir, Tipranavir, and Simeprevir, respectively. The active site of ADA and HIV-1 Nef proteins comprises amino acid residues such as for Tipranavir: Arene-Cation interaction (Phenyl and Pyridine)- Arg B1081, and Lys B1033 (1A4M) and Arene-Cation interaction (Pyridine and Phenyl)- Lys D11 and Arg D33; Sidechain acceptor Thr B40; Sidechain donor- Asp D30; Backbone donor- Ala B37 (6URI). Atazanavir: Arene-Cation interaction (Phenyl)- Lys A254 and Lys B1033; Sidechain acceptor - Arg A251 (1A4M). Conclusion: Thus, from the computational studies carried out, we could obtain hints for optimising the molecular selectivity of the PI to provide help in the design of new compounds via the repurposing strategy of the FDA-approved PI for effective treatment of co-morbidity with HIV and abdominal TB. However, further pharmacokinetics, pharmacodynamics, preclinical, and clinical studies permit the design of the new agents without undesirable interactions.

STITCH, Physicochemical, ADMET, and In Silico Analysis of Selected Mikania Constituents as Anti-Inflammatory Agents

The Mikania genus has been known to possess numerous pharmacological activities. In the present study, we aimed to evaluate the interaction of 26 selected constituents of Mikania species with (i) cyclooxygenase 2 (COX 2), (ii) human neutrophil elastase (HNE), (iii) lipoxygenase (LOX), matrix metalloproteinase ((iv) MMP 2 and (v) MMP 9), and (vi) microsomal prostaglandin E synthase 2 (mPGES 2) inhibitors using an in silico approach. The 26 selected constituents of Mikania species, namely mikamicranolide, kaurenoic acid, stigmasterol, grandifloric acid, kaurenol, spathulenol, caryophyllene oxide, syringaldehyde, dihydrocoumarin, o-coumaric acid, taraxerol, melilotoside, patuletin, methyl-3,5-di-O-caffeoyl quinate, 3,3′,5-trihydroxy-4′,6,7-trimethoxyflavone, psoralen, curcumene, herniarin, 2,6-dimethoxy quinone, bicyclogermacrene, α-bisabolol, γ-elemene, provincialin, dehydrocostus lactone, mikanin-3-O-sulfate, and nepetin, were assessed based on the docking action with COX 2, HNE, LOX, MMP 2, MMP 9, and mPGES 2 using Discovery Studio (in the case of LOX, the Autodock method was utilized). Moreover, STITCH (Search Tool for Interacting Chemicals), physicochemical, drug-likeness, and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) analyses were conducted utilizing the STITCH web server, the Mol-inspiration web server, and Discovery Studio, respectively. In the present study, STITCH analysis revealed only six ligands (dihydrocoumarin, patuletin, kaurenol, psoralen, curcumene, and nepetin) that showed interactions with human proteins. Physicochemical analysis showed that seventeen ligands complied well with Lipinski’s rule. ADMET analysis showed eleven ligands to possess hepatotoxic effects. Significantly, the binding free energy estimation displayed that the ligand methyl-3, 5-di-O-caffeoyl quinate revealed the highest binding energy for all the target enzymes, excluding LOX, suggesting that this may have efficacy as a non-steroidal anti-inflammatory drug (NSAID). The current study presents a better understanding of how Mikania is used as a traditional medicinal plant. Specifically, the 26 ligands of the Mikania plant are potential inhibitor against COX 2, HNE, LOX, MMP 2, MMP 9, and mPGES 2 for treatments for acute and/or chronic inflammatory diseases.

Salidroside ameliorates severe acute pancreatitis-induced cell injury and pyroptosis by inactivating Akt/NF-κB and caspase-3/GSDME pathways

Our previous studies showed that Salidroside (Sal), a glucoside of the phenylpropanoid tyrosol isolated from Rhodiola rosea L, alleviated severe acute pancreatitis (SAP) by inhibiting inflammation. However, the detailed mechanism remains unclear. Recent evidence has indicated a critical role of Sal in ameliorating inflammatory disorders by regulating pyroptosis. The present study aimed to explore the involvement of Sal and pyroptosis in the pathogenesis of SAP and investigate the potential mechanism. The effects of Sal on pyroptosis were first evaluated using SAP rat and cell model. Our results revealed that Sal treatment significantly decreased SAP-induced pancreatic cell damage and pyroptosis in vivo and in vitro, as well as reduced the release of lactate dehydrogenase (LDH), IL-1β and IL-18. Search Tool for Interacting Chemicals (STITCH) online tool identified 4 genes (CASP3, AKT1, HIF1A and IL10) as candidate targets of Sal in both rattus norvegicus and homo sapiens. Western blot and immunohistochemistry staining validated that Sal treatment decreased the phosphorylation levels of Akt and NF-κB p65, as well as cleaved caspase-3 and N-terminal fragments of GSDME (GSDME-N), suggesting that Sal might suppress pyroptosis through inactivating Akt/NF-κB and Caspase-3/GSDME pathways. Furthermore, overexpression of AKT1 or CASP3 could partially reverse the inhibitory effects of Sal on cell injury and pyroptosis, while downregulation of AKT1 or CASP3 promoted the inhibitory effects of Sal. Taken together, our data indicate that Sal suppresses SAP-induced pyroptosis through inactivating Akt/NF-κB and Caspase-3/GSDME pathways.

Identification of the effect and mechanism of Yiyi Fuzi Baijiang powder against colorectal cancer using network pharmacology and experimental validation.

Background: Yiyi Fuzi Baijiang powder (YFBP) is a traditional Chinese medicine used to treat colorectal cancer, although its bioactivity and mechanisms of action have not been studied in depth yet. The study intended to identify the potential targets and signaling pathways affected by YFBP during the treatment of colorectal cancer through pharmacological network analysis and to further analyze its chemical compositions and molecular mechanisms of action. Methods: The Traditional Chinese Medicine Systems Pharmacology (TCMSP), Traditional Chinese Medicine Integrated Database (TCMID), HitPredict (HIT), and Search Tool for Interactions of Chemicals (STITCH) databases were used to screen the bioactive components and promising targets of YFBP. Targets related to colorectal cancer were retrieved from the GeneCards and Gene Ontology databases. Cytoscape software was used to construct the "herb-active ingredient-target" network. The STRING database was used to construct and analyze protein-protein interactions (PPIs). Afterward, the R packages clusterProfiler and Cytoscape Hub plug-in were used to perform Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of target genes. The results of the network pharmacological analysis were also experimentally validated. Results: In total, 33 active components and 128 target genes were screened. Among them, 46 target genes were considered potential therapeutic targets that crossed the CRC target genes. The network pharmacology analysis showed that the active components of YFBP were correlated positively with CRC inflammatory target genes such as TLR4, TNF, and IL-6. The inflammation-related signaling pathways affected by the active components included the TNF-α, interleukin-17, and toll-like receptor signaling pathways. The active ingredients of YFBP, such as luteolin, β-sitosterol, myristic acid, and vanillin, may exert anti-tumor effects by downregulating SMOX expression via anti-inflammatory signaling and regulation of the TLR4/NF-κB signaling pathway. Conclusion: In the present study, the potential active components, potential targets, and key biological pathways involved in the YFBP treatment of CRC were determined, providing a theoretical foundation for further anti-tumor research.

Integrative In Silico Investigation Reveals the Host-Virus Interactions in Repurposed Drugs Against SARS-CoV-2.

The ongoing COVID-19 outbreak have posed a significant threat to public health worldwide. Recently Toll-like receptor (TLR) has been proposed to be the drug target of SARS-CoV-2 treatment, the specificity and efficacy of such treatments remain unknown. In the present study we performed the investigation of repurposed drugs via a framework comprising of Search Tool for Interacting Chemicals (STITCH), Kyoto Encyclopedia of Genes and Genomes (KEGG), molecular docking, and virus-host-drug interactome mapping. Chloroquine (CQ) and hydroxychloroquine (HCQ) were utilized as probes to explore the interaction network that is linked to SARS-CoV-2. 47 drug targets were shown to be overlapped with SARS-CoV-2 network and were enriched in TLR signaling pathway. Molecular docking analysis and molecular dynamics simulation determined the direct binding affinity of TLR9 to CQ and HCQ. Furthermore, we established SARS-CoV-2-human-drug protein interaction map and identified the axis of TLR9-ERC1-Nsp13 and TLR9-RIPK1-Nsp12. Therefore, the elucidation of the interactions of SARS-CoV-2 with TLR9 axis will not only provide pivotal insights into SARS-CoV-2 infection and pathogenesis but also improve the treatment against COVID-19.

Docking-based virtual screening, ADMET, and network pharmacology prediction of anthocyanidins against human alpha-amylase and alpha-glucosidase enzymes as potential antidiabetic agents

Diabetes mellitus (DM) characterized by high blood sugar concentration is a major global public health problem and untreated DM results in blindness, kidney failure, heart attack, stroke, and lower extremity amputation. In this structure-based drug design (SBDD) study, the potential inhibitory effects of twelve anthocyanidins (aglycon unit of anthocyanins) components on human pancreatic α-amylase and intestinal α-glucosidase enzymes were investigated using the molecular docking method and a novel approach developed by our research group was used to rank the global binding potentials of ligands to a series of different enzymes simultaneously. In addition, drug-likeness, absorption-distribution-metabolism-excretion-toxicity (ADMET) predictions, and intracellular target-component interaction network analyses of twelve anthocyanidin components were performed using the search tool for interactions of chemicals (STITCH). Petunidin, peonidin, and aurantinidin were determined as 'hit' phytochemicals according to the docking binding energy and relative binding capacity index (RBCI) analyses, whereas, based on the RBCI index, petunidin was found to be the most effective ligand in terms of binding capacity to both enzymes that play an important role in DM. The more accessible and large-volume active site of α-amylase compared to α-glucosidase caused petunidin to bind with higher affinity against α-amylase. Promisingly, petunidin did not violate any of the criteria for drug-likeness consisting of a combination of the Lipinski's rule of 5, Ghose and Veber filters, showed no cytochrome (CYP) P450 or hERG I-II inhibitory activity in the ADMET analysis, however, it was found to have a low gastrointestinal absorption profile. In intracellular target-component network analysis using the STITCH online platform, it was determined that petunidin did not show negative functional interactions with any enzyme in the human protein network. Considering these results, it is recommended that petunidin be advanced to further in vitro and in vivo assays as a potential α-amylase and α-glucosidase inhibitory agent in the treatment of DM. However, the intestinal absorption profile of petunidin must be enhanced by molecular optimization without compromising its pharmacological activity.

Potential therapy of Sambiloto plant (Andrographis paniculata) using multi-compounds analysis

Introduction: Sambiloto plant (Andrographis paniculata) is often used as herbal medicine plant in Indonesia. Previous evidence indicates the use of a whole plant or single-compound approach. Analysis of multi-compounds is needed to determine the therapeutic potential for standardizing herbal medicine to provide a reliable effect. Methods: An exploratory study searching for the active content of A. paniculata was carried out in the Knapsack program. The chemical structure is analyzed computationally using Prediction of Activity Spectra for Substances (PASS) software. The analysis of the mechanism of action of drug molecules was analyzed using the Search Tool for Interacting Chemicals (STITCH) software. Results: The active content of A. paniculata is 46 types, with 5 of them having 6 effects based on chemical bonds and targeting 12 receptor proteins. Five active contents of A. paniculata include andrographidin A, caffeic acid, chlorogenic acid, wogonin 5-glucoside, and cinnamic acid. Analysis of the mechanism of action of A. paniculata based on 12 target proteins from active ingredients using a multi-compound approach shows 6 unique biological processes. Based on the chemical bonds, 5 active contents of A. paniculata have six effects, including anaphylatoxin receptor antagonist, a beta-adrenergic receptor kinase inhibitor, GABA C receptor agonist, G-protein-coupled receptor kinase inhibitor, Aryl hydrocarbon receptor agonist, and Nicotinic alpha6beta3beta4alpha5 receptor antagonist. Conclusion: There is a therapeutic potential of A. paniculata with multi-compounds analysis. A molecular docking analysis is needed to predict the affinity between the ligand (active ingredient) and the target protein.

Pongol Methyl Ether Inhibits Akt and Suppresses Cancer Stem Cell Phenotypes in Lung Cancer Cells

Cancer stem cells (CSCs) are an important therapeutic target. The therapeutic agents targeting CSCs should lead to improved clinical outcomes. Here we have demonstrated the CSC-suppressing activity of pongol methyl ether (PME), a pure compound from Millettia erythrocalyx. Methods: CSC-suppressing effects were evaluated by spheroid formation assay and detection of CSC markers. The related CSC cell signals were evaluated by Western blot, immunofluorescence and molecular docking analysis. Proteins affected by PME treatment were subjected to bioinformatic analysis. Protein–protein interaction (PPI) networks were constructed by the Search Tool for Interactions of Chemicals (STITCH). The Kyoto Encyclopedia of Genes and Genomes (KEGG) mapper were used to confirm the underlying pathways. Results: PME (5–25 µM) significantly suppressed the ability of lung cancer cells to form colonies, grow in an anchorage-independent manner and generate tumour spheroids. PME at 25 µM significantly decreased the CSC markers (CD133 and ALDH1A1) and pluripotent transcription factors (Oct4 and Nanog). Akt, the key upstream signal of CSC control, was significantly decreased by the PME treatment. The molecular docking indicated that PME was bound to Akt-1 with a binding affinity of −9.2 kcal/mol greater than the Akt-1 inhibitor (reference compound; CQW). The STITCH network identified a total of 15 proteins interacted in PPI networks, and Akt-1 was identified as a central protein. The KEGG mapper indicated that the selected CSC markers were mostly involved in the ‘signalling pathways regulating pluripotency of stem cells’ pathway map and Akt, Oct4 and Nanog were the regulatory proteins in the dominant pathway. In addition, PME (10–25 µM) can suppress spheroid formation and reduce CSC-specific marker expression in patient-derived primary lung cancer cells. Conclusions: Our study revealed a novel pharmacological effect and the underlying mechanism of PME that can attenuate CSC phenotypes in lung cancer cells and may be developed for lung cancer therapy.

Polydatin Ameliorates Osteoporosis via Suppression of the Mitogen-Activated Protein Kinase Signaling Pathway.

Purpose: Polydatin (POL) is a natural active compound found in Polygonum multiflorum with reported anti-oxidant and antiviral effects. With the aging population there has been a stark increase in the prevalence of osteoporosis (OP), rendering it an imposing public health issue. The potential effect of POL as a therapy for OP remains unclear. Therefore, we sought to investigate the therapeutic effect of POL in OP and to elucidate the underlying signaling mechanisms in its regulatory process.Methods: The POL-targeted genes interaction network was constructed using the Search Tool for Interacting Chemicals (STITCH) database, and the shared Kyoto Encyclopedia of Genes and Genomes (KEGG). Pathways involved in OP and POL-targeted genes were identified. Quantitative real-time PCR (qRT-PCR) and enzyme-linked immunosorbent assay (ELISA) were performed to evaluate the osteogenic genes and the phosphorylation level in pre-osteoblastic cells. In addition, ALP and alizarin red staining was used to test the effect of POL on extracellular matrix mineralization.Results: Twenty-seven KEGG pathways shared between POL-related genes and OP were identified. MAPK signaling was identified as a potential key mechanism. In vitro results highlighted a definitive anti-OP effect of POL. The phosphorylation levels of MAPK signaling, including p38α, ERK1/2, and JNK, were significantly decreased in this regulatory process.Conclusion: Our results suggest that POL has a promising therapeutic effect in OP. MAPK signaling may be the underlying mechanism in this effect, providing a novel sight in discovering new drugs for OP.

Effects of Atorvastatin on T-Cell Activation and Apoptosis in Systemic Lupus Erythematosus and Novel Simulated Interactions With C-Reactive Protein and Interleukin 6.

ObjectiveWe study activation of T helper 17 (Th17) and regulatory T (Treg) cells and induction of apoptosis in cells from patients with systemic lupus erythematosus (SLE) compared with controls and effects of atorvastatin and its simulated interactions with other compounds.MethodsMononuclear cells from 10 patients with SLE and 10 controls were cultured in conditions that induce Th17 and/or Treg cell polarization and/or apoptosis and were studied by FACScan. Gene expression was determined by quantitative real‐time reverse transcription–polymerase chain reaction. Cytokines in plasma were determined by enzyme‐linked immunosorbent assay. The Search Tool for Interactions of Chemicals (STITCH) was used to retrieve information regarding the binding properties of atorvastatin.ResultsAmong patients with SLE, the proportion of Th17 (CD4+IL17+) cells was higher compared with controls after activation, with Th17 or Treg polarizing cytokines, phorbol myristate acetate, and ionomycin. In contrast, Treg cells (CD4+CD25+CD127dim/−) frequencies were lower. CD95 stimulation induced relatively more apoptosis in Treg cells and less in Th17 cells, as compared with controls. Addition of atorvastatin normalized Th17/Treg cell balance and apoptosis induction. Accordingly, the ratio of RORC/FoxP3 decreased in patients with SLE. Interleukin 17 and interleukin 6 (IL‐6) levels were increased in patients with SLE. Atorvastatin interacted strongly with C‐reactive protein (CRP) and also significantly with IL‐6.ConclusionThere is a higher proportion of Th17 cells and a lower proportion of Treg cells in patients with SLE after activation. Th17 cells were more resistant than Treg cells to CD95‐induced apoptosis in SLE. Atorvastatin normalized these effects. Our findings reveal a novel mechanism behind the imbalance of Th17/Treg cells with implications for treatment in SLE. We determine for the first time simulated interaction between atorvastatin, CRP, and IL‐6, implying a novel role of atorvastatin.

Curculigoside promotes osteogenic differentiation of ADSCs to prevent ovariectomized-induced osteoporosis

BackgroundCurculigoside is a natural phenolic glycoside compound produced by Curculigo orchioides Gaertn. This study aimed to explore the effects of curculigoside in promoting the osteogenic differentiation of adipose-derived stem cells (ADSCs) as well as the underlying mechanism.MethodsADSCs were treated with curculigoside at different concentrations (0 μmol/L, 1 μmol/L, 2.5 μmol/L, 5 μmol/L, 10 μmol/L, and 20 μmol/L), and cell viability was assessed by CCK-8 assay. Then, the alkaline phosphatase (ALP) activity was determined, and alizarin red S (ARS) staining was performed to measure the extracellular mineralization of curculigoside. Information about protein-chemical interactions is provided by the search tool for interactions of chemicals (STITCH) database. Then, LY294002 was administered to explore the mechanism by which curculigoside promotes the osteogenic differentiation of ADSCs. Western blot assays were performed to assess changes in the expression of osteogenic-related markers and the phosphorylation of PI3K and AKT. Finally, we established an ovariectomized (OVX)-induced osteoporosis mouse model and administered curculigoside to explore the effects of curculigoside in preventing bone loss in vivo.ResultsThe CCK-8 assay indicated that curculigoside did not induce cytotoxicity at a concentration of 5 μmol/L after 48 h. The ALP and ARS results revealed that the induced group had higher ALP activity and calcium deposition than the control group. Moreover, the curculigoside group exhibited increased biomineralization, ALP activity, and ARS staining compared to the induced and control groups, and these effects were partially inhibited by LY294002. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated that the target genes of curculigoside were mainly involved in the PI3K-Akt signaling pathway. PCR and western blot analysis showed that the expression of RUNX2, ALP, and Osterix was upregulated in curculigoside-treated ADSCs, but this effect was partially reversed by the PI3K inhibitor LY294002. Moreover, the curculigoside-treated group exhibited significantly increased phosphorylation of AKT to P-AKT compared with the osteogenic induction group. After treatment with curculigoside, the mice had a higher bone volume than the OVX mice, suggesting partial protection from cancellous bone loss. In addition, when LY294002 was added, the protective effects of curculigoside could be neutralized.ConclusionsCurculigoside could induce the osteogenic differentiation of ADSCs and prevent bone loss in an OVX model through the PI3K/Akt signaling pathway.

MedFused: A framework to discover the relationships between drug chemical functional group impacts and side effects

It is a well-known fact that there are often side effects to the long-term use of certain medications. These side effects can vary from mild dizziness to, at its most serious, death. The main factors that cause these side effects are the chemical composition, the mode of treatment, and the dose. The dynamics that govern the reaction of a drug heavily depend on its structural composition. The structural composition of a drug is defined by the structural arrangement of the corresponding basic chemical functional groups. Hence, it is essential to investigate the effect of chemical functional groups on the side effects to synthesize drugs with minimal side effects. To support this process, we developed a framework named MedFused (Medical Functional Group Side Effects Database), which is composed of drugs (International Union of Pure and Applied Chemistry: IUPAC nomenclature), functional groups, and the side effects along with other valuable information such as STITCH (search tool for interactions of chemicals) compound ID, and the Unified Medical Language System (UMLS) concept ID. We develop a web framework that functions on the MedFused system database on top of the Django web framework. Our web server supports functionalities such as exploring the database and descriptive graph tools, which provide additional exploration capabilities to the framework. These descriptive tools include histograms, pie charts, and association charts, which further explore the system. Above these basic tools, MedFused includes functionality to discover the drug's “chemical functional group” impact on “side effects”. The method conducts an association rule analysis on the relationships by considering the MedFused database as a collection of transactions. A specific transaction has a list of the functional groups of a drug and one side effect. Hence, a drug that has more than one side effect forms multiple transactions. Next, we generate a binary feature matrix based on the transactions and introduce a pruning mechanism to consider only the potential functional groups and side effects based on their support (frequencies), subjected to a predefined threshold (which can be changed accordingly). As the current version of the MedFused database has a limited number of side effects (hence low support), we restricted the analysis to identify the functional groups which have the most potential of causing a particular side effect, based on a confidence value of 1. Our framework can be further extended with more functions and tools as it supports the model view controller (MVC) architecture, which is inherited from the Django Python web framework.

Untargeted fecal metabolomics revealed biochemical mechanisms of the blood lipid-lowering effect of koumiss treatment in patients with hyperlipidemia

Our previous study found that consuming koumiss daily could beneficially reduce the levels of blood lipids, but the exact mechanism is not clear. Thus, this work aimed to investigate the biochemical mechanism of lipid-lowering effect using untargeted metabolomics by liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR). The fecal metabolomes of hyperlipidemia patients who consumed koumiss daily were analyzed before and after koumiss treatment. A total of ten significant differential metabolites (ursolic acid, linoleic acid, stearic acid, α-tocotrienol, γ-tocotrienol, alanine, tyrosine, sphingosine, acetate, and butyrate) were detected, and they all showed significant increased relative concentrations at days 30 and 60. Many of these metabolites were involved in lipid metabolism and transport. These results suggested that the ten identified metabolites were likely associated with the observed lipid-lowering effect. Finally, by using the Search Tool for Interactions of Chemicals (STITCH), metabolic networks connecting these metabolites were constructed to elucidate the biochemical mechanism of the hypolipidemic effect.

Systems Pharmacology-Based Identification of Mechanisms of Action of Bolbostemma paniculatum for the Treatment of Hepatocellular Carcinoma.

BackgroundTraditional Chinese medicine has widely used Bolbostemma paniculatum to treat diseases, including cancer, but its underlying mechanisms remain unclear. The present study aimed to elucidate the potential pharmacological mechanisms of “Tu Bei Mu” (TBM), the Chinese name for Bolbostemmatis Rhizoma, the dry tuber of B. paniculatum, for the treatment of hepatocellular carcinoma (HCC).Material/MethodsThe active components and putative therapeutic targets of TBM were explored using SwissTargetPrediction, Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and Search Tool for Interactions of Chemicals (STITCH). The HCC-related target database was built using DrugBank, DisGeNet, Online Mendelian Inheritance in Man (OMIM), and Therapeutic Target Database (TTD). A protein–protein interaction network of the common targets was constructed, based on the matches between TBM potential targets and HCC-related targets, using Cytoscape software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of the cluster networks were used to elucidate the biological functions of TBM.ResultsPharmacological network diagrams of the TBM compound-target network and HCC-related target network were successfully constructed. A total of 22 active components, 191 predicted biological targets of TBM, and 3775 HCC-related targets were identified. Through construction of an HCC-related target database and a protein–protein interaction network of the common targets, TBM was predicted to be effective in treating HCC mainly through the PI3K-Akt, HIF-1, p53, and PPAR signaling pathways.ConclusionsThe PI3K/Akt, HIF1, p53, and PPAR pathways may play vital roles in TBM treatment of HCC. Also, the potential anti-cancer effect of TBM on HCC appears to stem from the synergetic effect of multiple targets and mechanisms.

Study of interaction between Papaya ringspot virus coat protein and infected Carica papaya proteins

ABSTRACT Papaya ringspot virus (PRSV) causes the Papaya ringspot disease. Virus–host interactions appear to play a significant role in the replication, pathogenesis, and infection caused by the PRSV. PRSV coat protein is likely to be involved in the processes of RNA replication, aphid transmission, and cell-to-cell movement, which is closely related to the host cell proteins resulting in a PRSV infection. To identify the host proteins that interact with the CP in vitro, immune precipitation, in-solution trypsin digestion, and LC–MS/MS were performed. Twenty-three identified proteins that interacted with the CP are involved in cellular metabolism, transcription, signal, translation, carbohydrate metabolism, protein metabolism, stress response, photosynthesis, nucleotide metabolism, respiration, and lipid metabolism processes. The search tool for interactions of chemicals (STITCH) results show that SWP (an RNA polymerase II transcription mediator) and MPPBETA (Mitochondrial processing peptidase) are involved in known plant defense mechanisms including transcription factors, cell division, hormones, stress, mitochondrial electron transferase, respiration, and proteasome. Therefore, analyzing virus–host protein interactions at a molecular level is important to build a better understanding of the virus replication mechanism and cellular responses mounted against viruses by the host defense system.