Abstract: Ulcerative colitis (UC) is the major type of inflammatory bowel disease (IBD) characterized by an overactive immune responses and destruction of the colorectal epithelium with intricate pathological factors. In China, Huiyangjiuji decoction (HYJJ) has been widely administered against inflammation, but the underlying mechanical mechanisms are not known. A murine model of colitis was established by orally feeding 4% dextran sodium sulfate for 5 days. Intestinal organoids (IOs) were treated with TNFalpha (Tumor necrosis factor-alpha) as an ex-vivo UC model. A scratch assay combined with a co-culture system that incubated murine epithelial cell line (IEC-6) with macrophages (Mphis) was utilized to assess epithelial recovery under inflammatory conditions. Network pharmacology analysis was performed to elucidate the mechanism of HYJJ decoction. In the present study, we confirmed that HYJJ considerably alleviated of DSS-induced colitis, as evidenced by the improved intestinal injury and fecal albumin, as well as feces blood. Network pharmacology analysis identified the active components in HYJJ formula, and KEGG enrichment analysis indicated that HYJJ-target genes were enriched in pathogen-induced infections, cancer-related as well as inflammatory pathways. Consistently, RNA-sequencing demonstrated that HYJJ treated inhibited cytokine-cytokine interaction, IBD as well as TNF signaling pathways, confirming the anti-inflammatory and anti-neoplastic role of HYJJ decoction. In-vitro experimental evidence confirmed the suppression of pro-interleukins by HYJJ, including IL-2, IL-10 and IL-12. Moreover, the contribution of HYJJ to mucosal healing was corroborated by ex-vivo experiments, in which HYJJ rescued TNFalpha-compromised IOs functions, i.e., elevated mitochondrial stress (MOS) and impaired regeneration capacity. IEC-6 cells co-culture with Mphis from HYJJ-treated experimental colitis mice showed an improved migration capacity as compared to those incubated with Mphis from untreated colitis mice. We conclude that HYJJ re-establishes homeostasis of the gut epithelium during colitis by suppressing inflammation and orchestrating cytokines interaction.

Abstract: Towards the objectives of the UnitedStates Food and Drug Administration (FDA) generic drug science and research program, it is of vital importance in developing product-specific guidances (PSGs) with recommendations that can facilitate and guide generic product development. To generate a PSG, the assessor needs to retrieve supportive information about the drug product of interest, including from the drug labeling, which contain comprehensive information about drug products and instructions to physicians on how to use the products for treatment. Currently, although there are many drug labeling data resources, none of them including those developed by the FDA (e.g., Drugs@FDA) can cover all the FDA-approved drug products. Furthermore, these resources, housed in various locations, are often in forms that are not compatible or interoperable with each other. Therefore, there is a great demand for retrieving useful information from a large number of textual documents from different data resources to support an effective PSG development. To meet the needs, we developed a Natural Language Processing (NLP) pipeline by integrating multiple disparate publicly available data resources to extract drug product information with minimal human intervention. We provided a case study for identifying food effect information to illustrate how a machine learning model is employed to achieve accurate paragraph labeling. We showed that the pre-trained Bidirectional Encoder Representations from Transformers (BERT) model is able to outperform the traditional machine learning techniques, setting a new state-of-the-art for labelling food effect paragraphs from drug labeling and approved drug products datasets.

Abstract: Cervical cancer (CC) is one of the most common gynecological malignant tumors. The 5-year survival rate remains poor for the advanced and metastatic cervical cancer for the lack of effective treatments. Immunotherapy plays an important role in clinical tumor therapy. Neoantigens derived from tumor-specific somatic mutations are prospective targets for immunotherapy. Hence, the identification of new targets is of great significance for the treatment of advanced and metastatic cervical cancer. In this study, we performed whole-exome sequencing in 70 samples, including 25 cervical intraepithelial neoplasia (CINs) with corresponding blood samples and 10 CCs along with paired adjacent tissues to identify genomic variations and to find the potential neoantigens for CC immunotherapy. Using systematic bioinformatics pipeline, we found that C>T transitions were in both CINs and CCs. In contrast, the number of somatic mutations in CCs was significantly higher than those in CINs (t-test, P = 6.60E-04). Meanwhile, mutational signatures analysis revealed that signature 6 was detected in CIN2, CIN3, and CC, but not in CIN1, while signature 2 was only observed in CCs. Furthermore, PIK3CA, ARHGAP5 and ADGRB1 were identified as potential driver genes in this report, of which ADGRB1 was firstly reported in CC. Based on the genomic variation profiling of CINs and CCs, we identified 2586 potential neoantigens in these patients, of which 45 neoantigens were found in three neoantigen-related databases (TSNAdb, IEDB, and CTDatabase). Our current findings lay a solid foundation for the study of the pathogenesis of CC and the development of neoantigen-targeted immunotherapeutic measures.

Abstract: Emerging and re-emerging viral diseases occur with regularity within the human population. The conventional 'one drug, one virus' paradigm for antivirals does not adequately allow for proper preparedness in the face of unknown future epidemics. In addition, drug developers lack the financial incentives to work on antiviral drug discovery, with most pharmaceutical companies choosing to focus on more profitable disease areas. Safe-in-man broad spectrum antiviral agents (BSAAs) can help meet the need for antiviral development by already having passed phase I clinical trials, requiring less time and money to develop, and having the capacity to work against many viruses, allowing for a speedy response when unforeseen epidemics arise. In this chapter, we discuss the benefits of repurposing existing drugs as BSAAs, describe the major steps in safe-in-man BSAA drug development from discovery through clinical trials, and list several database resources that are useful tools for antiviral drug repositioning.

Abstract: Lung alveolar type-II (AT-II) cells produce pulmonary surfactant (PS), consisting of proteins and lipids. The lipids in PS are primarily responsible for reducing the air-fluid surface tension inside the alveoli of the lungs and to prevent atelectasis. The proteins are of two types: hydrophilic and hydrophobic. Hydrophilic surfactants are primarily responsible for opsonisation, thereby protecting the lungs from microbial and environmental contaminants. Hydrophobic surfactants are primarily responsible for respiratory function. Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) enters the lungs through ACE-2 receptors on lungs and replicates in AT-II cells leading to the etiology of Coronavirus disease - 2019 (COVID-19). The SARS-CoV-2 virus damages the AT-II cells and results in decreased production of PS. The clinical symptoms of acute respiratory distress syndrome (ARDS) in COVID-19 patients are like those of neonatal respiratory distress syndrome (NRDS). The PS treatment is first-line treatment option for NRDS and found to be well tolerated in ARDS patients with inconclusive efficacy. Over the past 70 degrees years, a lot of research is underway to produce natural/synthetic PS and developing systems for delivering PS directly to the lungs, in addition to finding the association between PS levels and respiratory illnesses. In the present COVID-19 pandemic situation, the scientific community all over the world is searching for the effective therapeutic options to improve the clinical outcomes. With a strong scientific and evidence-based background on role of PS in lung homeostasis and infection, few clinical trials were initiated to evaluate the functions of PS in COVID-19. Here, we connect the data on PS with reference to pulmonary physiology and infection with its possible therapeutic benefit in COVID-19 patients.

Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for coronavirus disease 2019 (COVID-19). Since its emergence, the COVID-19 pandemic has not only distressed medical services but also caused economic upheavals, marking urgent the need for effective therapeutics. The experience of combating SARS-CoV and MERS-CoV has shown that inhibiting the 3-chymotrypsin-like protease (3CLpro) blocks the replication of the virus. Given the well-studied properties of FDA-approved drugs, identification of SARS-CoV-2 3CLpro inhibitors in an FDA-approved drug library would be of great therapeutic value. Here, we screened a library consisting of 774 FDA-approved drugs for potent SARS-CoV-2 3CLpro inhibitors, using an intramolecularly quenched fluorescence (IQF) peptide substrate. Ethacrynic acid, naproxen, allopurinol, butenafine hydrochloride, raloxifene hydrochloride, tranylcypromine hydrochloride, and saquinavir mesylate have been found to block the proteolytic activity of SARS-CoV-2 3CLpro. The inhibitory activity of these repurposing drugs against SARS-CoV-2 3CLpro highlights their therapeutic potential for treating COVID-19 and other Betacoronavirus infections.

Abstract: Background: Hypertensive vascular remodeling (HVR) is the pathophysiological basis of hypertension, which is also an important cause of vascular disease and target organ damage. Treatment with Fructus Tribuli (FT), a traditional Chinese medicine, has a positive effect on HVR. However, the pharmacological mechanisms of FT are still unclear. Therefore, this study aimed to reveal the potential mechanisms involved in the effects of FT on HVR based on network pharmacology and molecular docking. Materials and Methods: We selected the active compounds and targets of FT according to the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and the Swiss Target Prediction database, and the targets of HVR were collected from the Online Mendelian Inheritance in Man (OMIM), GeneCards, and DrugBank databases. The protein-protein interaction network (PPI) was established using the STRING database. Moreover, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses and network analysis were performed to further explore the potential mechanisms. Finally, molecular docking methods were used to evaluate the affinity between the active compounds and the main target. Results: Seventeen active compounds of FT and 164 potential targets for the treatment of HVR were identified. Component-target and PPI networks were constructed, and 12 main active components and 33 main targets were identified by analyzing the topological parameters. Additionally, GO analysis indicated that the potential targets were enriched in 483 biological processes, 52 cellular components, and 110 molecular functions. KEGG analysis revealed that the potential targets were correlated with 122 pathways, such as the HIF-1 signaling pathway, ErbB signaling pathway, and VEGF signaling pathway. Finally, molecular docking showed that the 12 main active components had a good affinity for the top five main targets. Conclusion: This study demonstrated the multiple compounds, targets, and pathway characteristics of FT in the treatment of HVR. The network pharmacology method provided a novel research approach to analyze potential mechanisms.

Abstract: Aging is a multifactorial process that involves numerous genetic changes, so identifying anti-aging agents is quite challenging. Age-associated genetic factors must be better understood to search appropriately for anti-aging agents. We utilized an aging-related gene expression pattern-trained machine learning system that can implement reversible changes in aging by linking combinatory drugs. In silico gene expression pattern-based drug repositioning strategies, such as connectivity map, have been developed as a method for unique drug discovery. However, these strategies have limitations such as lists that differ for input and drug-inducing genes or constraints to compare experimental cell lines to target diseases. To address this issue and improve the prediction success rate, we modified the original version of expression profiles with a stepwise-filtered method. We utilized a machine learning system called deep-neural network (DNN). Here we report that combinational drug pairs using differential expressed genes (DEG) had a more enhanced anti-aging effect compared with single independent treatments on leukemia cells. This study shows potential drug combinations to retard the effects of aging with higher efficacy using innovative machine learning techniques.

Abstract: SARS-CoV-2 has triggered a major epidemic among people around the world, and it is the newest in the sequence to become prevalent among other infectious diseases. The drug repurposing concept has been utilized effectively for numerous viral infections. Considering the situation and the urgency, the idea of drug repurposing for coronavirus infection (COVID-19) is also being studied. The molecular docking method was used for the screening of 29 antiviral drugs against primary protease proteins (MPP) of SARS-CoV-2, spike ecto-domain, spike receptor binding domain, Nsp9 RNA binding protein, and HR2 domain. Among these drugs, in terms of least binding energy, Indinavir, Sorivudine, Cidofovir, and Darunavir showed minimum docking scores with all the key proteins. For ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) analysis, the ADMET properties of the top 4 drug candidates were retrieved through literature study. This analysis revealed that these drug candidates are well metabolized, distributed, and bioavailable, but have some undesirable effects. Furthermore, some approved structural analogues, such as Telbivudine, Tenofovir, Amprenavir, Fosamprenavir, etc., were predicted as similar drugs which may also be used for treating viral infections. We highly recommend these drug candidates as potential fighters against the deadly SARS-CoV-2 virus, and suggest in vivo trials for experimental validation of our findings.

Abstract: Purpose: Atopic dermatitis (AD) is a common chronic inflammatory skin disorder associated with immune dysregulation and barrier dysfunction. In this study, we investigated immunological biomarkers for AD diagnosis and treatment using CIBERSORT to identify immune cell infiltration characteristics. Patients and Methods: Common differentially expressed genes (DEGs) of lesioned (LS) vs non-lesioned (NL) groups were obtained from public datasets (GSE140684 and GSE99802). We performed functional enrichment analysis and selected hub genes from the protein-protein interaction (PPI) network. The hub genes were then subjected to transcription factor (TF), microRNA (miRNA), long non-coding RNA (lncRNA), drug interaction, and protein subcellular localization analyses. We also performed correlation analysis on differentially expressed immune cells, TFs, and hub genes. Receiver operating characteristic (ROC) curve analysis and binomial least absolute shrinkage and selection operator (LASSO) regression analysis were employed to assess the expression of hub genes in the GSE99802, GSE140684, GSE58558, GSE120721, and GSE36842 datasets. Results: We identified 238 common DEGs and 25 hub genes. Additionally, we predicted TFs, miRNAs, lncRNA, drugs, and protein subcellular localizations. The proportions of activated dendritic cells (DCs) and CD4+ memory T cells were relatively high in the LS skin. Expression levels of the TF FOXC1 were negatively correlated with target genes and the abundance of two immune cell types. The LASSO model showed that GZMB, CXCL1, and CD274 are candidate diagnostic biomarkers. Conclusion: Our study suggests that downregulated expression of FOXC1 expression may enhance the levels of chemokines, chemokine receptors, T cell receptor signaling molecules, activating CD4+ memory T cells and DCs in AD.