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Showing 1101 to 1104 of 5186 entries
Published in 2021
Nicardipine Inhibits Breast Cancer Migration via Nrf2/HO-1 Axis and Matrix Metalloproteinase-9 Regulation.
Abstract: Background: Metastasis represents an advanced stage of cancers, and matrix metalloproteinases are critical regulators. Calcium signal is crucial for appropriate cell behaviors. The efficacy and effects of calcium channel blockers in treating cancers are individually differ from each other. Here, we attempt to investigate the effects of nicardipine, a FDA-approved calcium channel blocker, in advanced breast cancers. Methods: We analyzed the influence of nicardipine on the colony-forming ability of triple negative breast cancer cell lines. Using cell culture inserts, cell migration was also examined. The expression of regulatory proteins was evaluated by real-time PCR, Western blot, and ELISA. Results: We have confirmed that nicardipine inhibits the breast cancer cells migration and colony formation. In addition, we also revealed that nicardipine increases the Nrf2 and HO-1 expression. The inhibition of HO-1 abrogates nicardipine-reduced matrix metalloproteinase-9 expression. Moreover, the end products of HO-1, namely, CO, Fe2+, and biliverdin (will converted to bilirubin), also decreases the expression of matrix metalloproteinase-9. Conclusion: These findings suggest that nicardipine-mediated matrix metalloproteinase-9 reduction is regulated by Nrf2/HO-1 axis and its catalytic end products. Therefore, nicardipine may be a potential candidate for repurposing against advanced breast cancers.
Published in 2021
Redox-Dependent Effects in the Physiopathological Role of Bile Acids.
Abstract: Bile acids (BA) are recognized by their role in nutrient absorption. However, there is growing evidence that BA also have endocrine and metabolic functions. Besides, the steroidal-derived structure gives BA a toxic potential over the biological membrane. Thus, cholestatic disorders, characterized by elevated BA on the liver and serum, are a significant cause of liver transplant and extrahepatic complications, such as skeletal muscle, central nervous system (CNS), heart, and placenta. Further, the BA have an essential role in cellular damage, mediating processes such as membrane disruption, mitochondrial dysfunction, and the generation of reactive oxygen species (ROS) and oxidative stress. The purpose of this review is to describe the BA and their role on hepatic and extrahepatic complications in cholestatic diseases, focusing on the association between BA and the generation of oxidative stress that mediates tissue damage.
Published in 2021
Models and Processes to Extract Drug-like Molecules From Natural Language Text.
Abstract: Researchers worldwide are seeking to repurpose existing drugs or discover new drugs to counter the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A promising source of candidates for such studies is molecules that have been reported in the scientific literature to be drug-like in the context of viral research. However, this literature is too large for human review and features unusual vocabularies for which existing named entity recognition (NER) models are ineffective. We report here on a project that leverages both human and artificial intelligence to detect references to such molecules in free text. We present 1) a iterative model-in-the-loop method that makes judicious use of scarce human expertise in generating training data for a NER model, and 2) the application and evaluation of this method to the problem of identifying drug-like molecules in the COVID-19 Open Research Dataset Challenge (CORD-19) corpus of 198,875 papers. We show that by repeatedly presenting human labelers only with samples for which an evolving NER model is uncertain, our human-machine hybrid pipeline requires only modest amounts of non-expert human labeling time (tens of hours to label 1778 samples) to generate an NER model with an F-1 score of 80.5%-on par with that of non-expert humans-and when applied to CORD'19, identifies 10,912 putative drug-like molecules. This enriched the computational screening team's targets by 3,591 molecules, of which 18 ranked in the top 0.1% of all 6.6 million molecules screened for docking against the 3CLPro protein.
Published in 2021
Exploring the Potential Mechanism of Shennao Fuyuan Tang for Ischemic Stroke Based on Network Pharmacology and Molecular Docking.
Abstract: Methods: Screen the biologically active components and potential targets of SNFYT through Traditional Chinese Medicine Systems Pharmacology (TCMSP), Traditional Chinese Medicines Integrated Database (TCMID), and related literature. In addition, DrugBank, OMIM, DisGeNET, and the Therapeutic Target Database were searched to explore the therapeutic targets of IS. The cross-targets of SNFYT potential targets and IS treatment targets were taken as candidate gene targets, and GO and KEGG enrichment analyses were performed on the candidate targets. On this basis, the SNFYT-component-target network and protein-protein interaction (PPI) network were constructed using Cytoscape 3.7.2. Finally, AutoDock was used to verify the molecular docking of core components and core targets. Results: We screened out 95 potentially active components and 143 candidate targets. SNFYT-component-target network, PPI network, and Cytoscape analysis identified four core active ingredients and 14 core targets. GO enrichment analyzed 2333 biological processes, 79 cell components, and 149 molecular functions. There are 170 KEGG-related signal pathways (P < 0.05), including the IL-17 signal pathway, TNF signal pathway, and HIF-1 signal pathway. The molecular docking results of the core components and the core targets showed good binding power. Conclusions: SNFYT may achieve the effect of treating ischemic stroke through its anti-inflammatory effect through a signal pathway with core targets as the core.
Published in 2021
Cross-Disorder Genomics Data Analysis Elucidates a Shared Genetic Basis Between Major Depression and Osteoarthritis Pain.
Abstract: Osteoarthritis (OA) and major depression (MD) are two debilitating disorders that frequently co-occur and affect millions of the elderly each year. Despite the greater symptom severity, poorer clinical outcomes, and increased mortality of the comorbid conditions, we have a limited understanding of their etiologic relationships. In this study, we conducted the first cross-disorder investigations of OA and MD, using genome-wide association data representing over 247K cases and 475K controls. Along with significant positive genome-wide genetic correlations (r g = 0.299 +/- 0.026, p = 9.10 x 10(-31)), Mendelian randomization (MR) analysis identified a bidirectional causal effect between OA and MD (betaOA --> MD = 0.09, SE = 0.02, z-score p-value < 1.02 x 10(-5); betaMD --> OA = 0.19, SE = 0.026, p < 2.67 x 10(-13)), indicating genetic variants affecting OA risk are, in part, shared with those influencing MD risk. Cross-disorder meta-analysis of OA and MD identified 56 genomic risk loci (P meta = 5 x 10(-8)), which show heightened expression of the associated genes in the brain and pituitary. Gene-set enrichment analysis highlighted "mechanosensory behavior" genes (GO:0007638; P gene_set = 2.45 x 10(-8)) as potential biological mechanisms that simultaneously increase susceptibility to these mental and physical health conditions. Taken together, these findings show that OA and MD share common genetic risk mechanisms, one of which centers on the neural response to the sensation of mechanical stimulus. Further investigation is warranted to elaborate the etiologic mechanisms of the pleiotropic risk genes, as well as to develop early intervention and integrative clinical care of these serious conditions that disproportionally affect the aging population.
Published in 2021
Screening Potential Drugs for COVID-19 Based on Bound Nuclear Norm Regularization.
Abstract: The novel coronavirus pneumonia COVID-19 infected by SARS-CoV-2 has attracted worldwide attention. It is urgent to find effective therapeutic strategies for stopping COVID-19. In this study, a Bounded Nuclear Norm Regularization (BNNR) method is developed to predict anti-SARS-CoV-2 drug candidates. First, three virus-drug association datasets are compiled. Second, a heterogeneous virus-drug network is constructed. Third, complete genomic sequences and Gaussian association profiles are integrated to compute virus similarities; chemical structures and Gaussian association profiles are integrated to calculate drug similarities. Fourth, a BNNR model based on kernel similarity (VDA-GBNNR) is proposed to predict possible anti-SARS-CoV-2 drugs. VDA-GBNNR is compared with four existing advanced methods under fivefold cross-validation. The results show that VDA-GBNNR computes better AUCs of 0.8965, 0.8562, and 0.8803 on the three datasets, respectively. There are 6 anti-SARS-CoV-2 drugs overlapping in any two datasets, that is, remdesivir, favipiravir, ribavirin, mycophenolic acid, niclosamide, and mizoribine. Molecular dockings are conducted for the 6 small molecules and the junction of SARS-CoV-2 spike protein and human angiotensin-converting enzyme 2. In particular, niclosamide and mizoribine show higher binding energy of -8.06 and -7.06 kcal/mol with the junction, respectively. G496 and K353 may be potential key residues between anti-SARS-CoV-2 drugs and the interface junction. We hope that the predicted results can contribute to the treatment of COVID-19.
Published in 2021
Computational drug repurposing strategy predicted peptide-based drugs that can potentially inhibit the interaction of SARS-CoV-2 spike protein with its target (humanACE2).
Abstract: Drug repurposing for COVID-19 has several potential benefits including shorter development time, reduced costs and regulatory support for faster time to market for treatment that can alleviate the current pandemic. The current study used molecular docking, molecular dynamics and protein-protein interaction simulations to predict drugs from the Drug Bank that can bind to the SARS-CoV-2 spike protein interacting surface on the human angiotensin-converting enzyme 2 (hACE2) receptor. The study predicted a number of peptide-based drugs, including Sar9 Met (O2)11-Substance P and BV2, that might bind sufficiently to the hACE2 receptor to modulate the protein-protein interaction required for infection by the SARS-CoV-2 virus. Such drugs could be validated in vitro or in vivo as potential inhibitors of the interaction of SARS-CoV-2 spike protein with the human angiotensin-converting enzyme 2 (hACE2) in the airway. Exploration of the proposed and current pharmacological indications of the peptide drugs predicted as potential inhibitors of the interaction between the spike protein and hACE2 receptor revealed that some of the predicted peptide drugs have been investigated for the treatment of acute respiratory distress syndrome (ARDS), viral infection, inflammation and angioedema, and to stimulate the immune system, and potentiate antiviral agents against influenza virus. Furthermore, these predicted drug hits may be used as a basis to design new peptide or peptidomimetic drugs with better affinity and specificity for the hACE2 receptor that may prevent interaction between SARS-CoV-2 spike protein and hACE2 that is prerequisite to the infection by the SARS-CoV-2 virus.
Published in 2021
Uncovering the Anti-Lung-Cancer Mechanisms of the Herbal Drug FDY2004 by Network Pharmacology.
Abstract: With growing evidence on the therapeutic efficacy and safety of herbal drugs, there has been a substantial increase in their application in the lung cancer treatment. Meanwhile, their action mechanisms at the system level have not been comprehensively uncovered. To this end, we employed a network pharmacology methodology to elucidate the systematic action mechanisms of FDY2004, an anticancer herbal drug composed of Moutan Radicis Cortex, Persicae Semen, and Rhei Radix et Rhizoma, in lung cancer treatment. By evaluating the pharmacokinetic properties of the chemical compounds present in FDY2004 using herbal medicine-associated databases, we identified its 29 active chemical components interacting with 141 lung cancer-associated therapeutic targets in humans. The functional enrichment analysis of the lung cancer-related targets of FDY2004 revealed the enriched Gene Ontology terms, involving the regulation of cell proliferation and growth, cell survival and death, and oxidative stress responses. Moreover, we identified key FDY2004-targeted oncogenic and tumor-suppressive pathways associated with lung cancer, including the phosphatidylinositol 3-kinase-Akt, mitogen-activated protein kinase, tumor necrosis factor, Ras, focal adhesion, and hypoxia-inducible factor-1 signaling pathways. Overall, our study provides novel evidence and basis for research on the comprehensive anticancer mechanisms of herbal medicines in lung cancer treatment.
Published in 2021
Drug repositioning of Clopidogrel or Triamterene to inhibit influenza virus replication in vitro.
Abstract: Influenza viruses cause respiratory tract infections and substantial health concerns. Infection may result in mild to severe respiratory disease associated with morbidity and some mortality. Several anti-influenza drugs are available, but these agents target viral components and are susceptible to drug resistance. There is a need for new antiviral drug strategies that include repurposing of clinically approved drugs. Drugs that target cellular machinery necessary for influenza virus replication can provide a means for inhibiting influenza virus replication. We used RNA interference screening to identify key host cell genes required for influenza replication, and then FDA-approved drugs that could be repurposed for targeting host genes. We examined the effects of Clopidogrel and Triamterene to inhibit A/WSN/33 (EC50 5.84 uM and 31.48 uM, respectively), A/CA/04/09 (EC50 6.432 uM and 3.32 uM, respectively), and B/Yamagata/16/1988 (EC50 0.28 uM and 0.11 uM, respectively) replication. Clopidogrel and Triamterene provide a druggable approach to influenza treatment across multiple strains and subtypes.
Published in 2021
Severe fever with thrombocytopenia syndrome virus (SFTSV)-host interactome screen identifies viral nucleoprotein-associated host factors as potential antiviral targets.
Abstract: Severe fever with thrombocytopenia syndrome virus (SFTSV) is an emerging tick-borne virus that causes severe infection in humans characterized by an acute febrile illness with thrombocytopenia and hemorrhagic complications, and a mortality rate of up to 30%. Understanding on virus-host protein interactions may facilitate the identification of druggable antiviral targets. Herein, we utilized liquid chromatography-tandem mass spectrometry to characterize the SFTSV interactome in human embryonic kidney-derived permanent culture (HEK-293T) cells. We identified 445 host proteins that co-precipitated with the viral glycoprotein N, glycoprotein C, nucleoprotein, or nonstructural protein. A network of SFTSV-host protein interactions based on reduced viral fitness affected upon host factor down-regulation was then generated. Screening of the DrugBank database revealed numerous drug compounds that inhibited the prioritized host factors in this SFTSV interactome. Among these drug compounds, the clinically approved artenimol (an antimalarial) and omacetaxine mepesuccinate (a cephalotaxine) were found to exhibit anti-SFTSV activity in vitro. The higher selectivity of artenimol (71.83) than omacetaxine mepesuccinate (8.00) highlights artenimol's potential for further antiviral development. Mechanistic evaluation showed that artenimol interfered with the interaction between the SFTSV nucleoprotein and the host glucose-6-phosphate isomerase (GPI), and that omacetaxine mepesuccinate interfered with the interaction between the viral nucleoprotein with the host ribosomal protein L3 (RPL3). In summary, the novel interactomic data in this study revealed the virus-host protein interactions in SFTSV infection and facilitated the discovery of potential anti-SFTSV treatments.
Showing 1101 to 1104 of 5186 entries