Abstract: INTRODUCTION: Eosinophilic Esophagitis (EoE) is a chronic condition characterized by eosinophilic inflammation of the esophagus which leads to esophageal dysfunction with common symptoms including vomiting, feeding difficulty, dysphagia, abdominal pain. Current main treatment options of EoE include dietary elimination and swallowed steroids. Diet elimination approach could lead to identifying the trigger food(s), but it often requires repeated upper endoscopy with general anesthesia and potentially could negatively affect nutrition intake and growth of the child and individuals' quality of life. Although the swallowed steroid treatment of effective, the EoE will universally recur after discontinuation of the treatment. Digestive Tea formula (DTF) has been used by the Traditional Chinese Medicine (TCM) practice to improve GI symptoms in EoE patients, including abdominal pain, GE reflux, and abnormal bowel movement. Previously, a flavonoid small molecule compound 7, 4 dihydroxy flavone (DHF) from Glycyrrhiza uralensis in DTF inhibited eotaxin, Th2 cytokine and IgE production in vitro and in vivo. METHOD: This study comprehensively evaluates the potential therapeutic and immunological mechanisms underlying DHF improvement of symptoms related to EoE using computational modeling, including target mining, gene ontology enrichment, pathway analyses, protein-protein interaction analyses, in silico molecular docking and dynamic simulation followed by ex-vivo target validation by qRT-PCR using cultured human esophagus biopsy specimen with or without DHF from patients with EoE. RESULTS: Computational analyses defined 29 common targets of DHF on EoE, among which TNF-alpha, IL-6, IL1beta, MAPK1, MAPK3 and AKT1 were most important. Docking analysis and dynamic simulation revealed that DHF directly binds TNF-alpha with a free binding energy of -7.7 kcal/mol with greater stability and flexibility. Subsequently, in the human esophagus biopsy culture system, significant reduction in levels of TNF-alpha, IL-6, IL-8 and IL1-beta was found in the supernatant of biopsy sample cultured with DHF. Furthermore, the gene expression profile showed significant reduction in levels of TNF-alpha, IL1-beta, IL-6, CCND and MAPK1 in the esophagus biopsy sample cultured with DHF. DISCUSSION: Taken together, the current study provides us an insight into the molecular mechanisms underlying multi-targeted benefits of DHF in the treatment of EoE and paves the way for facilitating more effective EoE therapies.

Abstract: INTRODUCTION: Heat-clearing and detoxifying Chinese medicines have been documented to have anti-Alzheimer's disease (AD) activities according to the accumulated clinical experience and pharmacological research results in recent decades. In this study, Fibraurea recisa Pierre (FRP), the classic type of Heat-clearing and detoxifying Chinese medicine, was selected as the object of research. METHODS: 12 components with anti-AD activities were identified in FRP by a variety of methods, including silica gel column chromatography, multiple databases, and literature searches. Then, network pharmacology and molecular docking were adopted to systematically study the potential anti-AD mechanism of these compounds. Consequently, it was found that these 12 compounds could act on 235 anti-AD targets, of which AKT and other targets were the core targets. Meanwhile, among these 235 targets, 71 targets were identified to be significantly correlated with the pathology of amyloid beta (Abeta) and Tau. RESULTS AND DISCUSSION: In view of the analysis results of the network of active ingredients and targets, it was observed that palmatine, berberine, and other alkaloids in FRP were the key active ingredients for the treatment of AD. Further, Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis revealed that the neuroactive ligand-receptor interaction pathway and PI3K-Akt signaling pathway were the most significant signaling pathways for FRP to play an anti-AD role. Findings in our study suggest that multiple primary active ingredients in FRP can play a multitarget anti-AD effect by regulating key physiological processes such as neurotransmitter transmission and anti-inflammation. Besides, key ingredients such as palmatine and berberine in FRP are expected to be excellent leading compounds of multitarget anti-AD drugs.

Abstract: Aim: Vitamin D plays a vital role in Rheumatoid arthritis (RA). However, the mechanism of vitamin D and rheumatism is still unclear. Therefore, a strategy based on network pharmacology and molecular docking was used to explore the mechanism of vitamin D and RA. Methods: The targets of RA were obtained from the GeneCards database and Therapeutic Targets Database, and the targets of vitamin D were obtained from the Drugbank database and STITCH database. Next, overlapping genes were identified by Venny, and further Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and molecular docking analyses were performed. Results: A total of 1,139 targets of RA and 201 targets of vitamin D were obtained. A total of 76 overlapping genes were identified by Venny. The enrichment analysis showed that cell proliferation, immune response, and apoptotic process were the critical biological processes of vitamin D in treating RA. Antifolate resistance, osteoclast differentiation, and the nuclear factor-kappa B (NF-kappaB) signalling pathway are fundamental mechanisms of vitamin D in treating RA. According to further molecular docking, ALB, TNF, CASP3, and TP53 may be important punctuation points or diagnostic markers for future RA treatment. Conclusion: By analysing overlapping genes of diseases and drugs, this study confirmed that ALB, TNF, CASP3, and TP53 may be essential markers or diagnostic markers for future RA treatment.

Abstract: OBJECTIVES: Lotus root (Nelumbo nucifera Gaertn) is a common medicinal-food dual-use vegetable. In this study, the effects of lotus root extract on acute alcoholism were investigated. METHODS: The Walle-Hoch method was used to determine the ADH activity of lotus root extracts in vitro. Lotus root methanol extract were identified by UPLC-QTOF-MS/MS based metabolomics analysis. Then 109 active ingredients with achievable oral doses and drug-like properties were explored using the TCMSP platform. SwissTargetPrediction Database to predict lotus root treatment targets for acute alcoholismSTRING database (https://www.string-db.org/) was used to construct protein-protein interaction network graphs. Gene ontology (GO) functional, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of genes common to lotus root and alcoholism by Metascap database. Molecular docking simulations were performed using AutoDock 1.5.6 software. Animal experiments verified the relieving effect of lotus root extract on acute alcoholism after intervention. RESULTS: Results indicated the methanol extract of lotus root showed the highest activation rate of ethanol dehydrogenase in vitro (18.87%). The 433 compounds of lotus root methanol extract were identified by UPLC-QTOF-MS/MS based metabolomics analysis. Bioinformatics analysis indicate that there were 224 intersectioning targets between lotus root extract and acute alcoholism. KEGG enrichment analysised shows that lotus root extract may play a role in treating acute alcoholism by intervening with the neuroactive ligand-receptor interaction pathway. The protein-protein interaction network (PPI) analysis found that HSP90AA1, MAPK1 and STAT3 played a key role in lotus root extract-modulated PPI networks. Molecular docking showed that (7R, 8S)-dihydrodihydrodipine cypressol had the best binding ability with MAPK1. Experiments in mice indicate that lotus root extract improved the activity of liver alcohol dehydrogenase (ADH), acetaldehyde dehydrogenase (ALDH), catalase (CAT), superoxide dismutase (SOD) and glutathione peroxidase (GSH-PX), increase glutathione (GSH) and reduce malondialdehyde (MDA) levels, decrease glutamate transaminase (AST), alanine transaminase (ALT) and alkaline phosphatase (AKP) in the serum of mice with acute alcoholism, and accelerate the metabolic rate of alcohol after drinking. This study reveals the mechanism of lotus root to alleviate acute alcoholism, which provides a basis for further research on functional foods using lotus root and offers new possibilities for the treatment of acute alcoholism. CONCLUSIONS: The results of the current study showed that the methanolic extract of lotus root had the highest activation rate of ethanol dehydrogenase. Network pharmacology results suggest that lotus root extract may play a role in the treatment of alcoholism by regulating signaling pathways, such as neuroactive ligand-receptor interactions, as well as biological processes, such as regulation of secretion, regulation of ion transport, response to lipopolysaccharides, and response to alcohol. Animal experiments confirmed the therapeutic effect of lotus root on acute alcoholism mechanistically through activation of alcohol catabolic enzyme, reduction of oxidative stress and protection of liver function.

Abstract: Prediction of drug-target interactions (DTIs) plays an important role in drug development. However, traditional laboratory methods to determine DTIs require a lot of time and capital costs. In recent years, many studies have shown that using machine learning methods to predict DTIs can speed up the drug development process and reduce capital costs. An excellent DTI prediction method should have both high prediction accuracy and low computational cost. In this study, we noticed that the previous research based on deep forests used XGBoost as the estimator in the cascade, we applied LightGBM instead of XGBoost to the cascade forest as the estimator, then the estimator group was determined experimentally as three LightGBMs and three ExtraTrees, this new model is called LGBMDF. We conducted 5-fold cross-validation on LGBMDF and other state-of-the-art methods using the same dataset, and compared their Sn, Sp, MCC, AUC and AUPR. Finally, we found that our method has better performance and faster calculation speed.

Abstract: Most patients with pharmacoresistant mesial temporal lobe epilepsy (MTLE) have hippocampal sclerosis on the postoperative histopathological examination. Although most patients with MTLE do not refer to a family history of the disease, familial forms of MTLE have been reported. We studied surgical specimens from patients with MTLE who had epilepsy surgery for medically intractable seizures. We assessed and compared gene expression profiles of the tissue lesion found in patients with familial MTLE (n = 3) and sporadic MTLE (n = 5). In addition, we used data from control hippocampi obtained from a public database (n = 7). We obtained expression profiles using the Human Genome U133 Plus 2.0 (Affymetrix) microarray platform. Overall, the molecular profile identified in familial MTLE differed from that in sporadic MTLE. In the tissue of patients with familial MTLE, we found an over-representation of the biological pathways related to protein response, mRNA processing, and synaptic plasticity and function. In sporadic MTLE, the gene expression profile suggests that the inflammatory response is highly activated. In addition, we found enrichment of gene sets involved in inflammatory cytokines and mediators and chemokine receptor pathways in both groups. However, in sporadic MTLE, we also found enrichment of epidermal growth factor signaling, prostaglandin synthesis and regulation, and microglia pathogen phagocytosis pathways. Furthermore, based on the gene expression signatures, we identified different potential compounds to treat patients with familial and sporadic MTLE. To our knowledge, this is the first study assessing the mRNA profile in surgical tissue obtained from patients with familial MTLE and comparing it with sporadic MTLE. Our results clearly show that, despite phenotypic similarities, both forms of MTLE present distinct molecular signatures, thus suggesting different underlying molecular mechanisms that may require distinct therapeutic approaches.

Abstract: Klebsiella pneumoniae is a gram-negative bacterium that is known for causing infection innosocomial settings. As reported by the World Health Organization, carbapenem-resistantEnterobacteriaceae, a category that includes K. pneumoniae, are classified as an urgentthreat, and the greatest concern is that these bacterial pathogens may acquire genetictraits that make them resistant towards antibiotics. The last class of antibiotics, carbapenems, are not able to combat these bacterial pathogens, allowing them to clonally expandantibiotic-resistant strains. Most antibiotics target essential pathways of bacterial cells;however, these targets are no longer susceptible to antibiotics. Hence, in our study, we focused on a hypothetical protein in K. pneumoniae that contains a DNA methylation proteindomain, suggesting a new potential site as a drug target. DNA methylation regulates theattenuation of bacterial virulence. We integrated computational-aided drug design by using a bioinformatics approach to perform subtractive genomics, virtual screening, and fingerprint similarity search. We identified a new potential drug, koenimbine, which could bea novel antibiotic.

Abstract: Biomedical knowledge is represented in structured databases and published in biomedical literature, and different computational approaches have been developed to exploit each type of information in predictive models. However, the information in structured databases and literature is often complementary. We developed a machine learning method that combines information from literature and databases to predict drug targets and indications. To effectively utilize information in published literature, we integrate knowledge graphs and published literature using named entity recognition and normalization before applying a machine learning model that utilizes the combination of graph and literature. We then use supervised machine learning to show the effects of combining features from biomedical knowledge and published literature on the prediction of drug targets and drug indications. We demonstrate that our approach using datasets for drug-target interactions and drug indications is scalable to large graphs and can be used to improve the ranking of targets and indications by exploiting features from either structure or unstructured information alone.

Abstract: Traditional Chinese medicine (TCM) plays an important role in the treatment of complex diseases, especially cardiovascular diseases. However, it is hard to identify their modes of action on account of their multiple components. The present study aims to evaluate the effects of Dan-Shen-Yin (DSY) granules on hypoxia-induced pulmonary hypertension (HPH), and then to decipher the molecular mechanisms of DSY. Systematic pharmacology was employed to identify the targets of DSY on HPH. Furthermore, core genes were identified by constructing a protein-protein interaction (PPI) network and analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes (KEGG) analysis. Related genes and pathways were verified using a hypoxia-induced mouse model and hypoxia-treated pulmonary artery cells. Based on network pharmacology, 147 potential targets of DSY on HPH were found, constructing a PPI network, and 13 hub genes were predicted. The results showed that the effect of DSY may be closely associated with AKT serine/threonine kinase 1 (AKT1), signal transducer and activator of transcription 3 (STAT3), and HIF-1 signaling pathways, as well as biological processes such as cell proliferation. Consistent with network pharmacology analysis, experiments in vivo demonstrated that DSY could prevent the development of HPH in a hypoxia-induced mouse model and alleviate pulmonary vascular remodeling. In addition, inhibition of STAT3/HIF-1alpha/VEGF and FAK/AKT signaling pathways might serve as mechanisms. Taken together, the network pharmacology analysis suggested that DSY exhibited therapeutic effects through multiple targets in the treatment of HPH. The inferences were initially confirmed by subsequent in vivo and in vitro studies. This study provides a novel perspective for studying the relevance of TCM and disease processes and illustrates the advantage of this approach and the multitargeted anti-HPH effect of DSY.

Abstract: A sensitive and efficient analytical process for detecting lamotrigine in acidic solution based in ultra-high-performance liquid chromatography-diode array detector (UPLC-DAD) was developed; the stationary phase used was a C8, 150 x 4.6 mm, 2.6 microm. The mobile phase consisted of acetonitrile/acidified water (0.01% H3PO4 and 0.005% triethylamine, pH 2.4) (25 : 75 v/v). Limits of detection and quantification were 0.02 microg/mL and 0.05 microg/mL, respectively. The working interval for the evaluation of the method ranged from 0.05 to 12 microg/mL, and the linear fit of the experimental data has a value of r2>/=0.98. Before quantifying lamotrigine in plasma of patients with bipolar disorder, lamotrigine was released from plasma proteins with a 0.2 M sodium hydroxide solution, and then proteins were removed by precipitation with acetonitrile. Afterward, the lamotrigine base was dissolved in ethyl acetate. This extract was reconstituted in potassium phosphate solution (pH 2.4) to obtain more than 98% of lamotrigine protonated in N2, which was detected and quantified as indicated above. The absolute percentage of lamotrigine recovery is >/=80% for all tested concentration levels. The accuracy and precision of the method have %CV values <4% for the lamotrigine levels of 3, 6, and 9 microg/mL. The correlation coefficient for the used concentration range is 0.99. The analytical method is precise and sensitive to measure lamotrigine levels expected in plasma of BD patients and these levels were in the therapeutic dose range.