Network Representation Learning-Based Drug Mechanism Discovery and Anti-Inflammatory Response Against COVID-19

<div>Recent studies have been demonstrated that host immune imbalance is an important factors leading to acute respiratory distress syndrome (ARDS) in COVID-19 patients. Therefore, discovery of potential drugs and identification of their mechanisms of action for the prevention of immune imbalance in COVID-19 patients are urgently needed. In this study, we proposed a network representation learning-based methodology, termed AIdrug2cov, to discover drug mechanism and anti-inflammatory response for patients with COVID19. In AIdrug2cov, a deep bidirectional Transformer encoder network representation approach is developed to automatically learn lowdimensional vector of heterogeneous network. Using the representation vectors, AIdrug2cov identifies 40 potential targets and 24 high-confidence drugs that bind to tumor necrosis factor(TNF)-α or interleukin(IL)-6 to prevent excessive inflammatory responses in COVID-19 patients. In particular, AIdrug2cov indicated that chloroquine and hydroxychloroquine are able to reduce fatality of COVID-19 patients, and that their mechanisms of action are likely mediated through their inhibition of inflammatory cytokines on top of their antiviral ability, consistent with the findings of clinical studies. In addition, the results in 5 pharmacological application suggested that AIdrug2cov significantly outperforms 5 other state-of-the-art network representation approaches, future demonstrating the availability of AIdrug2cov in drug development field. In summary, AIdrug2cov is practically useful for accelerating COVID-19 therapeutic development. The source code and data can be downloaded from https://github.com/pengsl-lab/AIdrug2cov.git</div>

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Network Representation Learning-Based Drug Mechanism Discovery and Anti-Inflammatory Response Against COVID-19

10.26434/chemrxiv.12531314.v1 ◽

2020 ◽

Author(s):

Wang Xiaoqi ◽

Bin Xin ◽

Zhijian Xu ◽

Kenli LI ◽

Fei Li ◽

...

Keyword(s):

Inflammatory Response ◽

Inflammatory Responses ◽

Representation Learning ◽

Mechanisms Of Action ◽

Network Representation ◽

Drug Mechanism ◽

Tnf Α ◽

Therapeutic Development ◽

Anti Inflammatory ◽

Immune Imbalance

<div>Recent studies have been demonstrated that host immune imbalance is an important factors leading to acute respiratory distress syndrome (ARDS) in COVID-19 patients. Therefore, discovery of potential drugs and identification of their mechanisms of action for the prevention of immune imbalance in COVID-19 patients are urgently needed. In this study, we proposed a network representation learning-based methodology, termed AIdrug2cov, to discover drug mechanism and anti-inflammatory response for patients with COVID19. In AIdrug2cov, a deep bidirectional Transformer encoder network representation approach is developed to automatically learn lowdimensional vector of heterogeneous network. Using the representation vectors, AIdrug2cov identifies 40 potential targets and 24 high-confidence drugs that bind to tumor necrosis factor(TNF)-α or interleukin(IL)-6 to prevent excessive inflammatory responses in COVID-19 patients. In particular, AIdrug2cov indicated that chloroquine and hydroxychloroquine are able to reduce fatality of COVID-19 patients, and that their mechanisms of action are likely mediated through their inhibition of inflammatory cytokines on top of their antiviral ability, consistent with the findings of clinical studies. In addition, the results in 5 pharmacological application suggested that AIdrug2cov significantly outperforms 5 other state-of-the-art network representation approaches, future demonstrating the availability of AIdrug2cov in drug development field. In summary, AIdrug2cov is practically useful for accelerating COVID-19 therapeutic development. The source code and data can be downloaded from https://github.com/pengsl-lab/AIdrug2cov.git</div>

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Network Representation Learning-Based Drug Mechanism Discovery and Anti-Inflammatory Response Against COVID-19

10.26434/chemrxiv.12531314 ◽

2020 ◽

Author(s):

Wang Xiaoqi ◽

Bin Xin ◽

Zhijian Xu ◽

Kenli LI ◽

Fei Li ◽

...

Keyword(s):

Inflammatory Response ◽

Inflammatory Responses ◽

Representation Learning ◽

Mechanisms Of Action ◽

Network Representation ◽

Drug Mechanism ◽

Tnf Α ◽

Therapeutic Development ◽

Anti Inflammatory ◽

Immune Imbalance

<div>Recent studies have been demonstrated that host immune imbalance is an important factors leading to acute respiratory distress syndrome (ARDS) in COVID-19 patients. Therefore, discovery of potential drugs and identification of their mechanisms of action for the prevention of immune imbalance in COVID-19 patients are urgently needed. In this study, we proposed a network representation learning-based methodology, termed AIdrug2cov, to discover drug mechanism and anti-inflammatory response for patients with COVID19. In AIdrug2cov, a deep bidirectional Transformer encoder network representation approach is developed to automatically learn lowdimensional vector of heterogeneous network. Using the representation vectors, AIdrug2cov identifies 40 potential targets and 24 high-confidence drugs that bind to tumor necrosis factor(TNF)-α or interleukin(IL)-6 to prevent excessive inflammatory responses in COVID-19 patients. In particular, AIdrug2cov indicated that chloroquine and hydroxychloroquine are able to reduce fatality of COVID-19 patients, and that their mechanisms of action are likely mediated through their inhibition of inflammatory cytokines on top of their antiviral ability, consistent with the findings of clinical studies. In addition, the results in 5 pharmacological application suggested that AIdrug2cov significantly outperforms 5 other state-of-the-art network representation approaches, future demonstrating the availability of AIdrug2cov in drug development field. In summary, AIdrug2cov is practically useful for accelerating COVID-19 therapeutic development. The source code and data can be downloaded from https://github.com/pengsl-lab/AIdrug2cov.git</div>

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p38/AP-1 Pathway in Lipopolysaccharide-Induced Inflammatory Responses Is Negatively Modulated by Electrical Stimulation

Mediators of Inflammation ◽

10.1155/2013/183042 ◽

2013 ◽

Vol 2013 ◽

pp. 1-11 ◽

Cited By ~ 10

Author(s):

Deok Jeong ◽

Jaehwi Lee ◽

Young-Su Yi ◽

Yanyan Yang ◽

Kyoung Won Kim ◽

...

Keyword(s):

Electrical Stimulation ◽

Inflammatory Response ◽

Inflammatory Responses ◽

Inflammatory Diseases ◽

Physiological Role ◽

Peritoneal Macrophages ◽

Cellular Level ◽

Transcriptional Level ◽

Weak Current ◽

Anti Inflammatory

Electrical stimulation with a weak current has been demonstrated to modulate various cellular and physiological responses, including the differentiation of mesenchymal stem cells and acute or chronic physical pain. Thus, a variety of investigations regarding the physiological role of nano- or microlevel currents at the cellular level are actively proceeding in the field of alternative medicine. In this study, we focused on the anti-inflammatory activity of aluminum-copper patches (ACPs) under macrophage-mediated inflammatory conditions. ACPs generated nanolevel currents ranging from 30 to 55 nA in solution conditions. Interestingly, the nanocurrent-generating aluminum-copper patches (NGACPs) were able to suppress both lipopolysaccharide-(LPS-) and pam3CSK-induced inflammatory responses such as NO and PGE2production in both RAW264.7 cells and peritoneal macrophages at the transcriptional level. Through immunoblotting and immunoprecipitation analyses, we found that p38/AP-1 could be the major inhibitory pathway in the NGACP-mediated anti-inflammatory response. Indeed, inhibition of p38 by SB203580 showed similar inhibitory activity of the production of TNF-αand PGE2and the expression of TNF-αand COX-2 mRNA. These results suggest that ACP-induced nanocurrents alter signal transduction pathways that are involved in the inflammatory response and could therefore be utilized in the treatment of various inflammatory diseases such as arthritis and colitis.

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Exponential Family Graph Embeddings

Proceedings of the AAAI Conference on Artificial Intelligence ◽

10.1609/aaai.v34i04.5737 ◽

2020 ◽

Vol 34 (04) ◽

pp. 3357-3364

Author(s):

Abdulkadir Celikkanat ◽

Fragkiskos D. Malliaros

Keyword(s):

Random Walk ◽

Exponential Family ◽

Representation Learning ◽

Learning Problems ◽

Interaction Patterns ◽

Network Representation ◽

Learning Tasks ◽

Learning Techniques ◽

Real World Datasets ◽

Low Dimensional

Representing networks in a low dimensional latent space is a crucial task with many interesting applications in graph learning problems, such as link prediction and node classification. A widely applied network representation learning paradigm is based on the combination of random walks for sampling context nodes and the traditional Skip-Gram model to capture center-context node relationships. In this paper, we emphasize on exponential family distributions to capture rich interaction patterns between nodes in random walk sequences. We introduce the generic exponential family graph embedding model, that generalizes random walk-based network representation learning techniques to exponential family conditional distributions. We study three particular instances of this model, analyzing their properties and showing their relationship to existing unsupervised learning models. Our experimental evaluation on real-world datasets demonstrates that the proposed techniques outperform well-known baseline methods in two downstream machine learning tasks.

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Obesity Affects β2 Adrenergic Regulation of the Inflammatory Profile and Phenotype of Circulating Monocytes from Exercised Animals

Nutrients ◽

10.3390/nu11112630 ◽

2019 ◽

Vol 11 (11) ◽

pp. 2630 ◽

Cited By ~ 5

Author(s):

Isabel Gálvez ◽

Leticia Martín-Cordero ◽

María Dolores Hinchado ◽

Alberto Álvarez-Barrientos ◽

Eduardo Ortega

Keyword(s):

Inflammatory Response ◽

Adrenergic Receptor ◽

Acute Exercise ◽

Inflammatory Responses ◽

Adrenergic Regulation ◽

Immune Stress ◽

Β2 Adrenergic Receptor ◽

Anti Inflammatory ◽

Inflammatory Profile ◽

Inflammatory Effect

Anomalous immune/inflammatory responses in obesity take place along with alterations in the neuroendocrine responses and dysregulation in the immune/stress feedback mechanisms. Exercise is a potential anti-inflammatory strategy in this context, but the influence of exercise on the β2 adrenergic regulation of the monocyte-mediated inflammatory response in obesity remains completely unknown. The first objective of this study was to analyze the effect of exercise on the inflammatory profile and phenotype of monocytes from obese and lean animals, and the second aim was to determine whether obesity could affect monocytes’ inflammatory response to β2 adrenergic activation in exercised animals. C57BL/6J mice were allocated to different lean or obese groups: sedentary, with acute exercise, or with regular exercise. The inflammatory profile and phenotype of their circulating monocytes were evaluated by flow cytometry in the presence or absence of the selective β2 adrenergic receptor agonist terbutaline. Exercise caused an anti-inflammatory effect in obese individuals and a pro-inflammatory effect in lean individuals. β2 adrenergic receptor stimulation exerted a global pro-inflammatory effect in monocytes from exercised obese animals and an anti-inflammatory effect in monocytes from exercised lean animals. Thus, β2 adrenergic regulation of inflammation in monocytes from exercised animals seems to depend on the inflammatory basal set-point.

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Comparing the effect of intestinal bacteria from rabbit, pig, and chicken on inflammatory response in cultured rabbit crypt and villus

Canadian Journal of Microbiology ◽

10.1139/cjm-2017-0757 ◽

2019 ◽

Vol 65 (1) ◽

pp. 59-67 ◽

Cited By ~ 1

Author(s):

Hong Xiao Cui ◽

Xiu Rong Xu

Keyword(s):

Inflammatory Response ◽

Inflammatory Responses ◽

Intestinal Bacteria ◽

Inflammatory Factors ◽

Rabbit Ileum ◽

Necrosis Factor Alpha ◽

Heat Treated ◽

Tnf Α ◽

Factor Alpha ◽

Anti Inflammatory

Rabbit is susceptible to intestinal infection, which often results in severe inflammatory response. To investigate whether the special community structure of rabbit intestinal bacteria contributes to this susceptibility, we compared the inflammatory responses of isolated rabbit crypt and villus to heat-treated total bacteria in pig, chicken, and rabbit ileal contents. The dominant phylum in pig and chicken ileum was Firmicutes, while Bacteroidetes was dominant in rabbit ileum. The intestinal bacteria from rabbit induced higher expression of toll-like receptor 4 (TLR4) in rabbit crypt and villus (P < 0.05). TLR2 and TLR3 expression was obviously stimulated by chicken and pig intestinal bacteria (P < 0.05) but not by those of rabbit. The ileal bacteria from those three animals all increased the expression of tumor necrosis factor alpha (TNF-α) and interleukin 6 (IL-6) in crypts and villus (P < 0.05). Chicken and pig ileal bacteria also stimulated the expression of anti-inflammatory factors interferon beta (IFN-β) and IL-10 (P < 0.05), while those of rabbit did not (P > 0.05). In conclusion, a higher abundance of Gram-negative bacteria in rabbit ileum did not lead to more expressive pro-inflammatory cytokines in isolated rabbit crypt and villus, but a higher percentage of Lactobacillus in chicken ileum might result in more expressive anti-inflammatory factors.

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Glycyrrhizin inhibits the manifestations of anti-inflammatory responses that appear in association with systemic inflammatory response syndrome (SIRS)-like reactions

Cytokine ◽

10.1016/j.cyto.2006.10.002 ◽

2006 ◽

Vol 35 (5-6) ◽

pp. 295-301 ◽

Cited By ~ 18

Author(s):

Miwa Takei ◽

Makiko Kobayashi ◽

David N. Herndon ◽

Richard B. Pollard ◽

Fujio Suzuki

Keyword(s):

Systemic Inflammatory Response Syndrome ◽

Inflammatory Response ◽

Inflammatory Responses ◽

Systemic Inflammatory Response ◽

Anti Inflammatory

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Modeling Inflammation in Zebrafish for the Development of Anti-inflammatory Drugs

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2020.620984 ◽

2021 ◽

Vol 8 ◽

Author(s):

Yufei Xie ◽

Annemarie H. Meijer ◽

Marcel J. M. Schaaf

Keyword(s):

Immune System ◽

Inflammatory Response ◽

Molecular Mechanisms ◽

Inflammatory Responses ◽

Inflammatory Diseases ◽

Critical Role ◽

Model Systems ◽

Trinitrobenzene Sulfonic Acid ◽

Inflammatory Drugs ◽

Anti Inflammatory

Dysregulation of the inflammatory response in humans can lead to various inflammatory diseases, like asthma and rheumatoid arthritis. The innate branch of the immune system, including macrophage and neutrophil functions, plays a critical role in all inflammatory diseases. This part of the immune system is well-conserved between humans and the zebrafish, which has emerged as a powerful animal model for inflammation, because it offers the possibility to image and study inflammatory responses in vivo at the early life stages. This review focuses on different inflammation models established in zebrafish, and how they are being used for the development of novel anti-inflammatory drugs. The most commonly used model is the tail fin amputation model, in which part of the tail fin of a zebrafish larva is clipped. This model has been used to study fundamental aspects of the inflammatory response, like the role of specific signaling pathways, the migration of leukocytes, and the interaction between different immune cells, and has also been used to screen libraries of natural compounds, approved drugs, and well-characterized pathway inhibitors. In other models the inflammation is induced by chemical treatment, such as lipopolysaccharide (LPS), leukotriene B4 (LTB4), and copper, and some chemical-induced models, such as treatment with trinitrobenzene sulfonic acid (TNBS), specifically model inflammation in the gastro-intestinal tract. Two mutant zebrafish lines, carrying a mutation in the hepatocyte growth factor activator inhibitor 1a gene (hai1a) and the cdp-diacylglycerolinositol 3-phosphatidyltransferase (cdipt) gene, show an inflammatory phenotype, and they provide interesting model systems for studying inflammation. These zebrafish inflammation models are often used to study the anti-inflammatory effects of glucocorticoids, to increase our understanding of the mechanism of action of this class of drugs and to develop novel glucocorticoid drugs. In this review, an overview is provided of the available inflammation models in zebrafish, and how they are used to unravel molecular mechanisms underlying the inflammatory response and to screen for novel anti-inflammatory drugs.

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dl-2-Hydroxyisocaproic Acid Attenuates Inflammatory Responses in a Murine Candida albicans Biofilm Model

Clinical and Vaccine Immunology ◽

10.1128/cvi.00339-14 ◽

2014 ◽

Vol 21 (9) ◽

pp. 1240-1245 ◽

Cited By ~ 14

Author(s):

M. T. Nieminen ◽

M. Hernandez ◽

L. Novak-Frazer ◽

H. Kuula ◽

G. Ramage ◽

...

Keyword(s):

Candida Albicans ◽

Inflammatory Response ◽

Chronic Wounds ◽

Inflammatory Responses ◽

Therapeutic Potential ◽

Histopathological Examination ◽

Mouse Skin ◽

Irreversible Damage ◽

Content Type ◽

Anti Inflammatory

ABSTRACTChronic biofilm infections are often accompanied by a chronic inflammatory response, leading to impaired healing and increased, irreversible damage to host tissues. Biofilm formation is a major virulence factor forCandida albicansand a challenge for treatment. Most current antifungals have proved ineffective in eradicating infections attributed to biofilms. The biofilm structure protectsCandidaspecies against antifungals and provides a way for them to evade host immune systems. This leads to a very distinct inflammatory response compared to that seen in planktonic infections. Previously, we showed the superior efficacy ofdl-2-hydroxyisocaproic acid (HICA) against various bacteria and fungi. However, the immunomodulatory properties of HICA have not been studied. Our aim was to investigate the potential anti-inflammatory response to HICAin vivo. We hypothesized that HICA reduces the levels of immune mediators and attenuates the inflammatory response. In a murine model, a robust biofilm was formed for 5 days in a diffusion chamber implanted underneath mouse skin. The biofilm was treated for 12 h with HICA, while caspofungin and phosphate-buffered saline (PBS) were used as controls. The pathophysiology and immunoexpression in the tissues surrounding the chamber were determined by immunohistochemistry. Histopathological examination showed an attenuated inflammatory response together with reduced expression of matrix metalloproteinase 9 (MMP-9) and myeloperoxidase (MPO) compared to those of chambers containing caspofungin and PBS. Interestingly, the expression of developmental endothelial locus 1 (Del-1), an antagonist of neutrophil extravasation, increased after treatment with HICA. Considering its anti-inflammatory and antimicrobial activity, HICA may have enormous therapeutic potential in the treatment of chronic biofilm infections and inflammation, such as those seen with chronic wounds.

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