Computational Screening of Repurposed Drugs Targeting Sars-Cov-2 Main Protease By Molecular Docking

Background: COVID-19 (Coronavirus disease 2019) is caused by the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), which poses significant global health and economic crisis that urges effective treatment. Methods: A total of 11 molecules (baricitinib, danoprevir, dexamethasone, hydroxychloroquine, ivermectin, lopinavir, methylprednisolone, remdesivir, ritonavir and saridegib, ascorbic acid, and cepharanthine) were selected for molecular docking studies using AutoDock VINA to study their antiviral activities via targeting SARS-CoV’s main protease (Mpro), a cysteine protease that mediates the maturation cleavage of polyproteins during virus replication. Results: Three drugs showed stronger binding affinity toward Mpro than N3 (active Mpro inhibitor as control): danoprevir (–7.7 kcal/mol), remdesivir (–8.1 kcal/mol), and saridegib (–7.8 kcal/mol). Two primary conventional hydrogen bonds were identified in the danoprevir-Mpro complex at GlyA:143 and GlnA:189, whereas the residue GluA:166 formed a carbon–hydrogen bond. Seven main conventional hydrogen bonds were identified in the remdesivir at AsnA:142, SerA:144, CysA:145, HisA:163, GluA:166, and GlnA:189, whereas two carbon–hydrogen bonds were formed by the residues HisA:41 and MetA:165. Cepharanthine showed a better binding affinity toward Mpro (–7.9 kcal/mol) than ascorbic acid (–5.4 kcal/mol). Four carbon–hydrogen bonds were formed in the cepharanthine-Mpro complex at HisA:164, ProA;168, GlnA;189, and ThrA:190. Conclusion: The findings of this study propose that these drugs are potentially inhibiting the SAR-CoV-2 virus by targeting the Mpro protein

Predicting Diabetes Mellitus With Machine Learning Techniques

Diabetes mellitus is a chronic disease characterized by hyperglycemia. It may cause many complications. According to the growing morbidity in recent years, in 2040, the world’s diabetic patients will reach 642 million, which means that one of the ten adults in the future is suffering from diabetes. There is no doubt that this alarming figure needs great attention. With the rapid development of machine learning, machine learning has been applied to many aspects of medical health. In this study, we used decision tree, random forest and neural network to predict diabetes mellitus. The dataset is the hospital physical examination data in Luzhou, China. It contains 14 attributes. In this study, five-fold cross validation was used to examine the models. In order to verity the universal applicability of the methods, we chose some methods that have the better performance to conduct independent test experiments. We randomly selected 68994 healthy people and diabetic patients’ data, respectively as training set. Due to the data unbalance, we randomly extracted 5 times data. And the result is the average of these five experiments. In this study, we used principal component analysis (PCA) and minimum redundancy maximum relevance (mRMR) to reduce the dimensionality. The results showed that prediction with random forest could reach the highest accuracy (ACC = 0.8084) when all the attributes were used

Phyllanthus

Phyllanthus is a traditional medicinal plant that has been found to have antihepatitis, antibacterial, and anticancer properties. The present studies were to investigate the in vitro molecular mechanisms of anticancer effects of Phyllanthus (P. amarus, P. niruri, P. urinaria, and P. watsonii) plant extracts in human prostate adenocarcinoma. The cancer ten-pathway reporter array was performed and revealed that the expression of six pathway reporters were significantly decreased (Wnt, NFκB, Myc/Max, hypoxia, MAPK/ERK, and MAPK/JNK) in PC-3 cells after treatment with Phyllanthus extracts. Western blot was conducted and identified several signalling molecules that were affected in the signalling pathways including pan-Ras, c-Raf, RSK, Elk1, c-Jun, JNK1/2, p38 MAPK, c-myc, DSH, β-catenin, Akt, HIF-1α, GSK3β, NFκB p50 and p52, Bcl-2, Bax, and VEGF, in treated PC-3 cells. A proteomics-based approach, 2D gel electrophoresis, was performed, and mass spectrometry (MS/MS) results revealed that there were 72 differentially expressed proteins identified in treated PC-3 cells and were involved in tumour cell adhesion, apoptosis, glycogenesis and glycolysis, metastasis, angiogenesis, and protein synthesis and energy metabolism. Overall, these findings suggest that Phyllanthus can interfere with multiple signalling cascades involved in tumorigenesis and be used as a potential therapeutic candidate for treatment of cancer

Pluripotent human embryonic stem cell derived neural lineages for in vitro modelling of enterovirus 71 infection and therapy

The incidence of neurological complications and fatalities associated with Hand, Foot & Mouth disease has increased over recent years, due to emergence of newly-evolved strains of Enterovirus 71 (EV71). In the search for new antiviral therapeutics against EV71, accurate and sensitive in vitro cellular models for preliminary studies of EV71 pathogenesis is an essential prerequisite, before progressing to expensive and time-consuming live animal studies and clinical trials. This study thus investigated whether neural lineages derived from pluripotent human embryonic stem cells (hESC) can fulfil this purpose. EV71 infection of hESC-derived neural stem cells (NSC) and mature neurons (MN) was carried out in vitro, in comparison with RD and SH-SY5Y cell lines. Results: Upon assessment of post-infection survivability and EV71 production by the various types, it was observed that NSC were significantly more susceptible to EV71 infection compared to MN, RD (rhabdomyosarcoma) and SHSY5Y cells, which was consistent with previous studies on mice. The SP81 peptide had significantly greater inhibitory effect on EV71 production by NSC and MN compared to the cancer-derived RD and SH-SY5Y cell lines. Hence, this study demonstrates that hESC-derived neural lineages can be utilized as in vitro models for studying EV71 pathogenesis and for screening of antiviral therapeutics

DA-CHENG-QI DECOCTION, A TRADITIONAL CHINESE HERBAL FORMULA, FOR INTESTINAL OBSTRUCTION: SYSTEMATIC REVIEW AND META-ANALYSIS

Background: This study was aimed at determining the effects and safety of Da-Cheng-Qi decoction (DCQD) or DCQD combined with conservative therapy in patients with intestinal obstruction. Materials and Methods: PubMed, EMBASE, Cochrane Controlled Trials Register, and several other databases were searched. Randomised controlled trials (RCTs) of DCQD or DCQD plus conservative therapy in patients with intestinal obstruction were eligible. Therapeutic effect was estimated by the improvement of clinical manifestations and diagnostic imaging; dichotomous/ordinal data assessment of overall response to therapy, adverse effects; or continuous variable were identified, including time to first bowel movement, time to first flatus, length of hospital stay. Results: Sixty eligible RCTs including 6,095 patients were identified. Response rate: (1) DCQD versus conservative therapy (6 RCTs, 361 patients, RR of respond =1.13; 95% CI 0.97 to 1.31). (2) DCQD plus conservative therapy versus conservative therapy (48 RCTs, 4,916 patients, RR of respond =1.25 which favoured DCQD plus conservative therapy; 95% CI 1.20 to 1.30). Treatment effect remained similar when RCTs at high risk of bias were excluded. Time to first flatus postoperatively: (1) DCQD versus conservative therapy (2 RCTs, 240 patients, SMD=-3.65; 95% CI -8.17 to 0.87). (2) DCQD plus conservative therapy versus conservative therapy (11 RCTs, 1,040 patients, SMD=-2.09 which favoured DCQD plus conservative therapy; 95% CI -3.04 to -1.15). Conclusion: DCQD combined with conservative therapy may increase the success rate of conservative therapy for intestinal obstruction significantly and can shorten the duration of postoperative ileus in patients undergoing abdominal surgery compared with conservative therapy alone

Dynamic Sensing of Localized Corrosion at the Metal/Solution Interface

A Mach-Zehnder interferometer is employed to detect localized corrosion at the metal/solution interface in the potentiodynamic sweep of the iron electrode in solutions. During the electrochemical reactions, local variations of the electrolyte's refractive index, which correlate with the concentration of dissolved species, change the optical path length (OPL) of the object beam when the beam passes through the electrolyte. The distribution of the OPL difference was obtained to present the concentration change of the metal ions visually, which enable direct evidence of corrosion processes. The OPL difference distribution shows localized and general corrosion during the anodic dissolution of the iron electrode in solutions with and without chloride ions, respectively. This method provides an approach for dynamic detection of localized corrosion at the metal/solution interface

Helicobacter pylori CagA Protein Negatively Regulates Autophagy and Promotes Inflammatory Response via c-Met-PI3K/Akt-mTOR Signaling Pathway

Cytotoxin-associated-gene A (CagA) of Helicobacter pylori (H. pylori) is a virulence factor that plays critical roles in H. pylori-induced gastric inflammation. In the present study, gastric biopsies were used for genotyping cagA and vacA genes, determining the autophagic activity, and the severity of gastric inflammation response. It was revealed that autophagy in gastric mucosal tissues infected with cagA+H. pylori strains was lower than the levels produced by cagA−H. pylori strains, accompanied with accumulation of SQSTM1 and decreased LAMP1 expression. In vitro, deletion mutant of cagA gene resulted in increased autophagic activity, and decreased expression of SQSTM1 and cytokines, whereas over-expression of CagA down-regulated the starvation-induced autophagy, and induced more production of the cytokines. Moreover, the production of the cytokines was increased by inhibition of autophagy, but decreased by enhancement of autophagy. Deletion of CagA decreased the ability to activate Akt kinase at Ser-473 site and increased autophagy. c-Met siRNA significantly affected CagA-mediated autophagy, and decreased the level of p-Akt, p-mTOR, and p-S6. Both c-Met siRNA and MK-2206 could reverse inflammatory response. H. pylori CagA protein negatively regulates autophagy and promotes the inflammation in H. pylori infection, which is regulated by c-Met-PI3K/Akt-mTOR signaling pathway activation