A network flow approach to predict protein targets and flavonoid backbones to treat respiratory syncytial virus infection

Network pharmacology, molecular docking, and untargeted metabolomics reveal molecular mechanisms of multi-targets effects of Qingfei Tongluo Plaster improving respiratory syncytial virus pneumonia

Objective

Qingfei Tongluo Plaster (QFP), an improved Chinese medicine hospital preparation, is an attractive treatment option due to its well clinical efficacy, convenience, economy, and patient compliance in the treatment of respiratory syncytial virus (RSV) pneumonia. The aim of this study was to investigate the efficacy mechanism of QFP on RSV rats from the perspective of alleviating lung inflammation and further explore the changes of serum metabolites and metabolic pathways in RSV rats under the influence of QFP.

Methods

This study used network pharmacological methods and molecular docking combined with molecular biology and metabolomics from multi-dimensional perspectives to screen and verify the therapeutic targets. Open online databases were used to speculate the gene targets of efficient ingredients and diseases. Then, we used the String database to examine the fundamental interaction of common targets of drugs and diseases. An online enrichment analysis was performed to predict the functional pathways. Molecular docking was applied to discover the binding modes between essential ingredients and crucial gene targets. Finally, we demonstrated the anti-inflammatory ability of QFP in the RSV-evoked pneumonia rat model and explained the mechanism in combination with the metabolomics results.

Results

There were 19 critical targets defined as the core targets: tumor necrosis factor (TNF), inducible nitric oxide synthase 2 (NOS2), mitogen-activated protein kinase 14 (MAPK14), g1/S-specific cyclin-D1 (CCND1), signal transducer and activator of transcription 1-alpha/beta (STAT1), proto-oncogene tyrosine-protein kinase Src (SRC), cellular tumor antigen p53 (TP53), interleukin-6 (IL6), hypoxia-inducible factor 1-alpha (HIF1A), RAC-alpha serine/threonine-protein kinase (AKT1), signal transducer and activator of transcription 3 (STAT3), heat shock protein HSP 90-alpha (HSP90AA1), tyrosine-protein kinase JAK2 (JAK2), cyclin-dependent kinase inhibitor 1 (CDKN1A), mitogen-activated protein kinase 3 (MAPK3), epidermal growth factor receptor (EGFR), myc proto-oncogene protein (MYC), protein c-Fos (FOS) and transcription factor p65 (RELA). QFP treated RSV pneumonia mainly through the phosphatidylinositol 3-kinase (PI3K)/RAC AKT pathway, HIF-1 pathway, IL-17 pathway, TNF pathway, and MAPK pathway. Animal experiments proved that QFP could effectively ameliorate RSV-induced pulmonary inflammation. A total of 28 metabolites underwent significant changes in the QFP treatment, and there are four metabolic pathways consistent with the KEGG pathway analyzed by network pharmacology, suggesting that they may be critical processes related to treatment.

Conclusion

These results provide essential perspicacity into the mechanisms of action of QFP as a promising anti-RSV drug.

Molecular weight-dependent antitumor effects of prunes-derived type I arabinogalactan on human and murine triple wild-type melanomas

The regulation of metastasis-related cellular aspects of two structurally similar AGIs from prunes tea infusion, with different molar masses, was studied in vitro against Triple Wild-Type metastatic melanoma (TWM) from murine and human origin. The higher molar mass AGI (AGI-78KDa) induced TWMs cells death and, in murine cell line, it decreased some metastasis-related cellular processes: invasiveness capacity, cell-extracellular matrix interaction, and colonies sizes. The lower molar mass AGI (AGI-12KDa) did not induce cell death but decreased TWMs proliferation rate and, in murine cell line, it decreased cell adhesion and colonies sizes. Both AGIs alter the clonogenic capacity of human cell line. In spite to understand why we saw so many differences between AGIs effects on murine and human cell lines we performed in silico analysis that demonstrated differential gene expression profiles between them. Complementary network topological predictions suggested that AGIs can modulate multiple pathways in a specie-dependent manner, which explain differential results obtained in vitro between cell lines. Our results pointed to therapeutic potential of AGIs from prunes tea against TWMs and showed that molecular weight of AGIs may influence their antitumor effects.

Vincristine promotes differential levels of apoptosis, mitotic catastrophe, and senescence depending on the genetic background of glioblastoma cells

Vincristine (VCR) is a classical chemotherapeutic that has been revisited to treat refractory solid tumors producing encouraging results. VCR binds to tubulin and decreases the rate of microtubule dynamics, thus triggering many cellular responses and behaviors. However, the dynamics of these responses and fates are uncharacterized. This study combined systems biology approaches with acute and long-term in vitro experiments to predict key pathways and mechanisms associated with cell fates during and after VCR treatment. Glioblastoma (GBM) cells were treated with clinically relevant doses of VCR, and interconnected cell fates were explored. A correlation matrix based on experimental cell analysis reported strong negative correlations between cell number, nuclear irregularities, senescence, or apoptosis, depending on the cells' genetic makeup and treatment regimen. P53 would be essential in all analyzed processes according to topological network analysis. Furthermore, despite the high acute sensitivity, both cell lines re-growth in the long term after a single VCR treatment, especially in those populations with high levels of autophagy. These multiple responses may also be triggered in patients' exposed tumors, which should be considered to allow the rational design of VCR protocols, including modulators of the cell fates and pathways mentioned above.

PHILM2Web: A high-throughput database of macromolecular host–pathogen interactions on the Web

During infection, the pathogen’s entry into the host organism, breaching the host immune defense, spread and multiplication are frequently mediated by multiple interactions between the host and pathogen proteins. Systematic studying of host–pathogen interactions (HPIs) is a challenging task for both experimental and computational approaches and is critically dependent on the previously obtained knowledge about these interactions found in the biomedical literature. While several HPI databases exist that manually filter HPI protein–protein interactions from the generic databases and curated experimental interactomic studies, no comprehensive database on HPIs obtained from the biomedical literature is currently available. Here, we introduce a high-throughput literature-mining platform for extracting HPI data that includes the most comprehensive to date collection of HPIs obtained from the PubMed abstracts. Our HPI data portal, PHILM2Web (Pathogen–Host Interactions by Literature Mining on the Web), integrates an automatically generated database of interactions extracted by PHILM, our high-precision HPI literature-mining algorithm. Currently, the database contains 23 581 generic HPIs between 157 host and 403 pathogen organisms from 11 609 abstracts. The interactions were obtained from processing 608 972 PubMed abstracts, each containing mentions of at least one host and one pathogen organisms. In response to the coronavirus disease 2019 (COVID-19) pandemic, we also utilized PHILM to process 25 796 PubMed abstracts obtained by the same query as the COVID-19 Open Research Dataset. This COVID-19 processing batch resulted in 257 HPIs between 19 host and 31 pathogen organisms from 167 abstracts. The access to the entire HPI dataset is available via a searchable PHILM2Web interface; scientists can also download the entire database in bulk for offline processing.

Database URL: http://philm2web.live

Hesperidin identified from Citrus extracts potently inhibits HCV genotype 3a NS3 protease

Background

Hepatitis C virus infection is the main cause of liver ailments across the globe. Several HCV genotypes have been identified in different parts of the world. Effective drugs for combating HCV infections are available but not affordable, particularly to infected individuals from resource-limited countries. Hence, cost-effective drugs need to be developed against important HCV drug targets. As Citrus fruits naturally contain bioactive compounds with antiviral activities, the current study was designed to identify antiviral inhibitors from Citrus fruit extracts against an important drug target, NS3 protease, of HCV genotype 3a which is found predominantly in South Asian countries.

Methods

The full-length NS3 protease alone and the NS3 protease domain in fusion with the cognate NS4A cofactor were expressed in Escherichia coli, and purified by chromatographic techniques. Using the purified protein as a drug target, Citrus extracts were evaluated in a FRET assay, and active ingredients, identified using ESI–MS/MS, were docked to observe the interaction with active site residues of NS3. The best interacting compound was further confirmed through the FRET assay as the inhibitor of NS3 protease.

Results

Fusion of the NS3 protease domain to the NS4A cofactor significantly improved the purification yield, and NS3-NS4A was functionally more active than the full-length NS3 alone. The purified protein (NS3-NS4A) was successfully employed in a validated FRET assay to evaluate 14 Citrus fruit extracts, revealing that the mesocarp extract of Citrus paradisi, and whole fruit extracts of C. sinesis, C. aurantinum, and C. reticulata significantly inhibited the protease activity of HCV NS3 protease (IC₅₀ values of 5.79 ± 1.44 µg/mL, 37.19 ± 5.92 µg/mL, 42.62 ± 6.89 µg/mL, and 57.65 ± 3.81 µg/mL, respectively). Subsequent ESI-MSⁿ analysis identified a flavonoid, hesperidin, abundantly present in all the afore-mentioned Citrus extracts. Importantly, docking studies suggested that hesperidin interacts with active site residues, and acts as a potent inhibitor of NS3 protease, exhibiting an IC₅₀ value of 11.34 ± 3.83 µg/mL.

Conclusions

A FRET assay was developed using NS3-NS4A protease, which was successfully utilized for the evaluation of Citrus fruit extracts. Hesperidin, a compound present in the Citrus extracts, was identified as the main flavonoid, which can serve as a cost-effective potent inhibitor of NS3 protease, and could be developed as a drug for antiviral therapy against HCV genotype 3a.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12906-022-03578-1.

Diclofenac Administration after Physical Training Blunts Adaptations of Peripheral Systems and Leads to Losses in Exercise Performance: In Vivo and In Silico Analyses

Recovery in athletes is hampered by soreness and fatigue. Consequently, nonsteroidal anti-inflammatory drugs are used as an effective strategy to maintain high performance. However, impact of these drugs on adaptations induced by training remains unknown. This study assessed the effects of diclofenac administration (10 mg/kg/day) on rats subjected to an exhaustive test, after six weeks of swimming training. Over the course of 10 days, three repeated swimming bouts were performed, and diclofenac or saline were administered once a day. Trained animals exhibited higher muscle citrate synthase and lower plasma creatinine kinase activities as compared to sedentary animals, wherein diclofenac had no impact. Training increased time to exhaustion, however, diclofenac blunted this effect. It also impaired the increase in plasma and liver interleukin-6 levels. The trained group exhibited augmented catalase, glutathione peroxidase, and glutathione reductase activities, and a higher ratio of reduced-to-oxidized glutathione in the liver. However, diclofenac treatment blunted all these effects. Systems biology analysis revealed a close relationship between diclofenac and liver catalase. These results confirmed that regular exercise induces inflammation and oxidative stress, which are crucial for tissue adaptations. Altogether, diclofenac treatment might be helpful in preventing pain and inflammation, but its use severely affects performance and tissue adaptation.

Screening and identification of bioactive compounds from citrus against non-structural protein 3 protease of hepatitis C virus genotype 3a by fluorescence resonance energy transfer assay and mass spectrometry

BACKGROUND

Hepatitis C virus genotype 3a (HCV G3a) is highly prevalent in Pakistan. Due to the elevated cost of available Food and Drug Administration-approved drugs against HCV, medicinal natural products of potent antiviral activity should be screened for the cost-effective treatment of the disease. Furthermore, from natural products, active compounds against vital HCV proteins like non-structural protein 3 (NS3) protease could be identified to prevent viral proliferation in the host.

AIM

To develop cost-effective HCV genotype 3a NS3 protease inhibitors from citrus fruit extracts.

METHODS

Full-length NS3 without co-factor non-structural protein 4A (NS4A) and codon optimized NS3 protease in fusion with NS4A were expressed in Escherichia coli. The expressed protein was purified by metal ion affinity chromatography and gel filtration. Citrus fruit extracts were screened using fluorescence resonance energy transfer (FRET) assay against the protease and polyphenols were identified as potential inhibitors using electrospray ionization-mass spectrometry (MS)/MS technique. Among different polyphenols, highly potent compounds were screened using molecular modeling approaches and consequently the most active compound was further evaluated against HCV NS4A-NS3 protease domain using FRET assay.

RESULTS

NS4A fused with NS3 protease domain gene was overexpressed and the purified protein yield was high in comparison to the lower yield of the full-length NS3 protein. Furthermore, in enzyme kinetic studies, NS4A fused with NS3 protease proved to be functionally active compared to full-length NS3. So it was concluded that co-factor NS4A fusion is essential for the purification of functionally active protease. FRET assay was developed and validated by the half maximal inhibitory concentration (IC₅₀) values of commercially available inhibitors. Screening of citrus fruit extracts against the native purified fused NS4A-NS3 protease domain showed that the grapefruit mesocarp extract exhibits the highest percentage inhibition 91% of protease activity. Among the compounds identified by LCMS analysis, hesperidin showed strong binding affinity with the protease catalytic triad having S-score value of -10.98.

CONCLUSION

Fused NS4A-NS3 protease is functionally more active, which is effectively inhibited by hesperidin from the grapefruit mesocarp extract with an IC₅₀ value of 23.32 µmol/L.

Cellular Mechanisms Triggered by the Cotreatment of Resveratrol and Doxorubicin in Breast Cancer: A Translational In Vitro-In Silico Model

Doxorubicin (Doxo) is the most effective chemotherapeutic agent for the treatment of breast cancer. However, resistance to Doxo is common. Adjuvant compounds capable of modulating mechanisms involved in Doxo resistance may potentiate the effectiveness of the drug. Resveratrol (Rsv) has been tested as an adjuvant in mammary malignancies. However, the cellular and molecular mechanisms underlying the effects of cotreatment with Doxo and Rsv in breast cancer are poorly understood. Here, we combined in vitro and in silico analysis to characterize these mechanisms. In vitro, we employed a clinically relevant experimental design consisting of acute (24 h) treatment followed by 15 days of analysis. Acute Rsv potentiated the long-lasting effect of Doxo through the induction of apoptosis and senescence. Cells that survived to the cotreatment triggered high levels of autophagy. Autophagy inhibition during its peak of activation but not concomitant with Doxo+Rsv increased the long-term toxicity of the cotreatment. To uncover key proteins potentially associated with in vitro effects, an in silico multistep strategy was implemented. Chemical-protein networks were predicted based on constitutive gene expression of MCF7 cells and interatomic data from breast cancer. Topological analysis, KM survival analysis, and a quantitative model based on the connectivity between apoptosis, senescence, and autophagy were performed. We found seven putative genes predicted to be modulated by Rsv in the context of Doxo treatment: CCND1, CDH1, ESR1, HSP90AA1, MAPK3, PTPN11, and RPS6KB1. Six out of these seven genes have been experimentally proven to be modulated by Rsv in cancer cells, with 4 of the 6 genes in MCF7 cells. In conclusion, acute Rsv potentiated the long-term toxicity of Doxo in breast cancer potentially through the modulation of genes and mechanisms involved in Doxo resistance. Rational autophagy inhibition potentiated the effects of Rsv+Doxo, a strategy that should be further tested in animal models.

Cytogenomic Integrative Network Analysis of the Critical Region Associated with Wolf-Hirschhorn Syndrome

Deletions in the 4p16.3 region are associated with Wolf-Hirschhorn syndrome (WHS), a contiguous gene deletion syndrome involving variable size deletions. In this study, we perform a cytogenomic integrative analysis combining classical cytogenetic methods, fluorescence in situ hybridization (FISH), chromosomal microarray analysis (CMA), and systems biology strategies, to establish the cytogenomic profile involving the 4p16.3 critical region and suggest WHS-related intracellular cell signaling cascades. The cytogenetic and clinical patient profiles were evaluated. We characterized 12 terminal deletions, one interstitial deletion, two ring chromosomes, and one classical translocation 4;8. CMA allowed delineation of the deletions, which ranged from 3.7 to 25.6 Mb with breakpoints from 4p16.3 to 4p15.33. Furthermore, the smallest region of overlapping (SRO) encompassed seven genes in a terminal region of 330 kb in the 4p16.3 region, suggesting a region of susceptibility to convulsions and microcephaly. Therefore, molecular interaction networks and topological analysis were performed to understand these WHS-related symptoms. Our results suggest that specific cell signaling pathways including dopamine receptor, NAD+ nucleosidase activity, and fibroblast growth factor-activated receptor activity are associated with the diverse pathological WHS phenotypes and their symptoms. Additionally, we identified 29 hub-bottlenecks (H-B) nodes with a major role in WHS.

Respiratory Syncytial Virus: Infection, Detection, and New Options for Prevention and Treatment

Respiratory syncytial virus (RSV) infection is a significant cause of hospitalization of children in North America and one of the leading causes of death of infants less than 1 year of age worldwide, second only to malaria. Despite its global impact on human health, there are relatively few therapeutic options available to prevent or treat RSV infection. Paradoxically, there is a very large volume of information that is constantly being refined on RSV replication, the mechanisms of RSV-induced pathology, and community transmission. Compounding the burden of acute RSV infections is the exacerbation of preexisting chronic airway diseases and the chronic sequelae of RSV infection. A mechanistic link is even starting to emerge between asthma and those who suffer severe RSV infection early in childhood. In this article, we discuss developments in the understanding of RSV replication, pathogenesis, diagnostics, and therapeutics. We attempt to reconcile the large body of information on RSV and why after many clinical trials there is still no efficacious RSV vaccine and few therapeutics.

Drug Repurposing by Simulating Flow Through Protein-Protein Interaction Networks

As drug development is extremely expensive, the identification of novel indications for in‐market drugs is financially attractive. Multiple algorithms are used to support such drug repurposing, but highly reliable methods combining simulation of intracellular networks and machine learning are currently not available. We developed an algorithm that simulates drug effects on the flow of information through protein–protein interaction networks, and used support vector machine to identify potentially effective drugs in our model disease, psoriasis. Using this method, we screened about 1,500 marketed and investigational substances, identified 51 drugs that were potentially effective, and selected three of them for experimental confirmation. All drugs inhibited tumor necrosis factor alpha‐induced nuclear factor kappa B activity in vitro, suggesting they might be effective for treating psoriasis in humans. Additionally, these drugs significantly inhibited imiquimod‐induced ear thickening and inflammation in the mouse model of the disease. All results suggest high prediction performance for the algorithm.

Identifying a biomarker network for corticosteroid resistance in asthma from bronchoalveolar lavage samples

Corticosteroid resistance (CR) is a major barrier to the effective treatment of severe asthma. Hence, a better understanding of the molecular mechanisms involved in this condition is a priority. Network analysis is an emerging strategy to explore this complex heterogeneous disorder at system level to identify a small own network for CR in asthma. Gene expression profile of GSE7368 from bronchoalveolar lavage (BAL) of CR in subjects with asthma was downloaded from the gene expression omnibus (GEO) database and compared to BAL of corticosteroid-sensitive (CS) patients. DEGs were identified by the Limma package in R language. In addition, DEGs were mapped to STRING to acquire protein-protein interaction (PPI) pairs. Topological properties of PPI network were calculated by Centiscape, ClusterOne and BINGO. Subsequently, text-mining tools were applied to design one own cell signalling for CR in asthma. Thirty-five PPI networks were obtained; including a major network consisted of 370 nodes, connected by 777 edges. After topological analysis, a minor PPI network composed by 48 nodes was indentified, which is composed by most relevant nodes of major PPI network. In this subnetwork, several receptors (EGFR, EGR1, ESR2, PGR), transcription factors (MYC, JAK), cytokines (IL8, IL6, IL1B), one chemokine (CXCL1), one kinase (SRC) and one cyclooxygenase (PTGS2) were described to be associated with inflammatory environment and steroid resistance in asthma. We suggest a biomarker network composed by 48 nodes that could be potentially explored with diagnostic or therapeutic use.