Abstract: BACKGROUND: Drug repositioning, meanings finding new uses for existing drugs, which can accelerate the processing of new drugs research and development. Various computational methods have been presented to predict novel drug-disease associations for drug repositioning based on similarity measures among drugs and diseases. However, there are some known associations between drugs and diseases that previous studies not utilized. METHODS: In this work, we develop a deep gated recurrent units model to predict potential drug-disease interactions using comprehensive similarity measures and Gaussian interaction profile kernel. More specifically, the similarity measure is used to exploit discriminative feature for drugs based on their chemical fingerprints. Meanwhile, the Gaussian interactions profile kernel is employed to obtain efficient feature of diseases based on known disease-disease associations. Then, a deep gated recurrent units model is developed to predict potential drug-disease interactions. RESULTS: The performance of the proposed model is evaluated on two benchmark datasets under tenfold cross-validation. And to further verify the predictive ability, case studies for predicting new potential indications of drugs were carried out. CONCLUSION: The experimental results proved the proposed model is a useful tool for predicting new indications for drugs or new treatments for diseases, and can accelerate drug repositioning and related drug research and discovery.

Abstract: We improved a previous pharmacological target adverse-event (TAE) profile model to predict adverse events (AEs) on US Food and Drug Administration (FDA) drug labels at the time of approval. The new model uses more drugs and features for learning as well as a new algorithm. Comparator drugs sharing similar target activities to a drug of interest were evaluated by aggregating AEs from the FDA Adverse Event Reporting System (FAERS), FDA drug labels, and medical literature. An ensemble machine learning model was used to evaluate FAERS case count, disproportionality scores, percent of comparator drug labels with a specific AE, and percent of comparator drugs with the reports of the event in the literature. Overall classifier performance was F1 of 0.71, area under the precision-recall curve of 0.78, and area under the receiver operating characteristic curve of 0.87. TAE analysis continues to show promise as a method to predict adverse events at the time of approval.

Abstract: BACKGROUND: The limited treatment options for children with severe respiratory syncytial virus (RSV) infection highlights the need for a comprehensive understanding of the host cellular response during infection. We aimed to identify host genes that are associated with severe RSV disease and to identify drugs that can be repurposed for the treatment of severe RSV infection. METHODS: We examined clinical data and blood samples from 37 hospitalized children (29 mild and 8 severe) with RSV infection. We tested RNA from blood samples using next-generation sequencing to profile global mRNA expression and identify cellular processes. RESULTS: Retractions, decreased breath sounds, and tachypnea were associated with disease severity. We observed upregulation of genes related to neutrophil, inflammatory response, blood coagulation, and downregulation of genes related to T cell response in children with severe RSV. Using network-based approach, 43 drugs were identified that are predicted to interact with the gene products of these differentially expressed genes. CONCLUSIONS: These results suggest that the changes in the expression pattern in the innate and adaptive immune responses may be associated with RSV clinical severity. Compounds that target these cellular processes can be repositioned as candidate drugs in the treatment of severe RSV. IMPACT: Neutrophil, inflammation, and blood coagulation genes are upregulated in children with severe RSV infection. Expression of T cell response genes are suppressed in cases of severe RSV. Genes identified in this study can contribute in understanding the pathogenesis of RSV disease severity. Drugs that target cellular processes associated with severe RSV can be repositioned as potential therapeutic options.

Abstract: Infectious diseases caused by intestinal protozoan, such as Entamoeba histolytica (E. histolytica) and Giardia lamblia (G. lamblia) are a worldwide public health issue. They affect more than 70 million people every year. They colonize intestines causing primarily diarrhea; nevertheless, these infections can lead to more serious complications. The treatment of choice, metronidazole, is in doubt due to adverse effects and resistance. Therefore, there is a need for new compounds against these parasites. In this work, a structure-based virtual screening of FDA-approved drugs was performed to identify compounds with antiprotozoal activity. The glycolytic enzyme triosephosphate isomerase, present in both E. histolytica and G. lamblia, was used as the drug target. The compounds with the best average docking score on both structures were selected for the in vitro evaluation. Three compounds, chlorhexidine, tolcapone, and imatinib, were capable of inhibit growth on G. lamblia trophozoites (0.05-4.935 mug/mL), while folic acid showed activity against E. histolytica (0.186 mug/mL) and G. lamblia (5.342 mug/mL).

Abstract: Antiprotozoal drug nitazoxanide (NTZ) has shown diverse pharmacological properties and has appeared in several clinical trials. Herein we present the synthesis, characterization, in vitro biological investigation, and in silico study of four hetero aryl amide analogs of NTZ. Among the synthesized molecules, compound 2 and compound 4 exhibited promising antibacterial activity against Escherichia coli (E. coli), superior to that displayed by the parent drug nitazoxanide as revealed from the in vitro antibacterial assay. Compound 2 displayed zone of inhibition of 20 mm, twice as large as the parent drug NTZ (10 mm) in their least concentration (12.5 microg/ml). Compound 1 also showed antibacterial effect similar to that of nitazoxanide. The analogs were also tested for in vitro cytotoxic activity by employing cell counting kit-8 (CCK-8) assay technique in HeLa cell line, and compound 2 was identified as a potential anticancer agent having IC50 value of 172 microg which proves it to be more potent than nitazoxanide (IC50 = 428 microg). Furthermore, the compounds were subjected to molecular docking study against various bacterial and cancer signaling proteins. The in vitro test results corroborated with the in silico docking study as compound 2 and compound 4 had comparatively stronger binding affinity against the proteins and showed a higher docking score than nitazoxanide toward human mitogen-activated protein kinase (MAPK9) and fatty acid biosynthesis enzyme (FabH) of E. coli. Moreover, the docking study demonstrated dihydrofolate reductase (DHFR) and thymidylate synthase (TS) as probable new targets for nitazoxanide and its synthetic analogs. Overall, the study suggests that nitazoxanide and its analogs can be a potential lead compound in the drug development.

Abstract: This study describes two complementary methods that use network-based and sequence similarity tools to identify drug repurposing opportunities predicted to modulate viral proteins. This approach could be rapidly adapted to new and emerging viruses. The first method built and studied a virus-host-physical interaction network; a three-layer multimodal network of drug target proteins, human protein-protein interactions, and viral-host protein-protein interactions. The second method evaluated sequence similarity between viral proteins and other proteins, visualized by constructing a virus-host-similarity interaction network. Methods were validated on the human immunodeficiency virus, hepatitis B, hepatitis C, and human papillomavirus, then deployed on SARS-CoV-2. Comparison of virus-host-physical interaction predictions to known antiviral drugs had AUCs of 0.69, 0.59, 0.78, and 0.67, respectively, reflecting that the scores are predictive of effective drugs. For SARS-CoV-2, 569 candidate drugs were predicted, of which 37 had been included in clinical trials for SARS-CoV-2 (AUC = 0.75, P-value 3.21 x 10(-3)). As further validation, top-ranked candidate antiviral drugs were analyzed for binding to protein targets in silico; binding scores generated by BindScope indicated a 70% success rate.

Abstract: Introduction: Direct-acting antivirals (DAAs) represent a breakthrough in hepatitis C virus (HCV) treatment as they directly inhibit HCV nonstructural (NS) proteins (NS3/4A, NS5A, and NS5B). However, ongoing debates exist regarding their relationship with hepatocellular carcinoma (HCC) whose incidence is widely debated among investigators. This study was conducted to identify host pharmacogenetic factors that may influence HCC incidence upon using HCV DAAs. Materials and methods: Details regarding 16 HCV DAAs were collected from literature and DrugBank database. Digital structures of these drugs were fed into the pharmacogenomics/pharmacovigilance in - silico pipeline (PHARMIP) to predict the genetic factors that may underpin HCC development. Results: We identified 184 unique genes and 40 unique variants that may have key answers for the DAA/HCC paradox. These findings could be used in different methods to aid in the precise application of HCV DAAs and minimize the proposed risk for HCC. All results could be accessed at: https://doi.org/10.17632/8ws8258hn3.2. Discussion: All the identified factors are evidence related to HCC and significantly predicted by PHARMIP as DAA targets. We discuss some examples of the methods of using these results to address the DAA/HCC controversy based on the following three primary levels: 1 - individual DAA drug, 2 - DAA subclass, and 3 - the entire DAA class. Further wet laboratory investigation is required to evaluate these results.

Abstract: The utilization of approved medication is a requisite to combat certain diseases for health; however, the undesirable adverse effects (AEs) due to medication are generally unavoidable. Hypertension is one of such AEs resulting from approved medication in which blood pressure in the arteries gets elevated and is a risk factor for several diseases including heart and kidney failure. HTs are the approved drugs that can cause hypertension as an AE. Here, the goal of the study is to investigate the structural and functional diversities of HTs. In our quest to unravel the structural parameters of the HTs, a systematic analysis of the HTs having a different number and type of ring systems was conducted. The cellular component, molecular function and biological processes adopted by the gene products were analyzed. Moreover, our systematically done analysis suggests that all the target families are active in a common pathway, that is, nerve transmission. A comparison of the selected structural and functional aspect of HTs with anti-hypertensives suggests that HTs follow certain structural and functional features in spite of many possibilities. Our study provides a promising methodology that considers the influence of structural diversity of AE causing agents on a functional perspective for precursory clinical decision making. This could be extended to explore the structural and functional trends that are adopted by agents causing certain diseases or AEs.

Abstract: PURPOSE: The antifungal drugs ketoconazole and itraconazole reduce serum concentrations of 4beta-hydroxycholesterol, which is a validated marker for hepatic cytochrome P450 (CYP) 3A4 activity. We tested the effect of another antifungal triazole agent, fluconazole, on serum concentrations of different sterols and oxysterols within the cholesterol metabolism to see if this inhibitory reaction is a general side effect of azole antifungal agents. METHODS: In a prospective, double-blind, placebo-controlled, two-way crossover design, we studied 17 healthy subjects (nine men, eight women) who received 400 mg fluconazole or placebo daily for 8 days. On day 1 before treatment and on day 8 after the last dose, fasting blood samples were collected. Serum cholesterol precursors and oxysterols were measured by gas chromatography-mass spectrometry-selected ion monitoring and expressed as the ratio to cholesterol (R_sterol). RESULTS: Under fluconazole treatment, serum R_lanosterol and R_24,25-dihydrolanosterol increased significantly without affecting serum cholesterol or metabolic downstream markers of hepatic cholesterol synthesis. Serum R_4beta-, R_24S-, and R_27-hydroxycholesterol increased significantly. CONCLUSION: Fluconazole inhibits the 14alpha-demethylation of lanosterol and 24,25-dihydrolanosterol, regulated by CYP51A1, without reduction of total cholesterol synthesis. The increased serum level of R_4beta-hydroxycholesterol under fluconazole treatment is in contrast to the reductions observed under ketoconazole and itraconazole treatments. The question, whether this increase is caused by induction of CYP3A4 or by inhibition of the catabolism of 4beta-hydroxycholesterol, must be answered by mechanistic in vitro and in vivo studies comparing effects of various azole antifungal agents on hepatic CYP3A4 activity.

Abstract: BACKGROUND: The genetic basis of lacunar stroke is poorly understood, with a single locus on 16q24 identified to date. We sought to identify novel associations and provide mechanistic insights into the disease. METHODS: We did a pooled analysis of data from newly recruited patients with an MRI-confirmed diagnosis of lacunar stroke and existing genome-wide association studies (GWAS). Patients were recruited from hospitals in the UK as part of the UK DNA Lacunar Stroke studies 1 and 2 and from collaborators within the International Stroke Genetics Consortium. Cases and controls were stratified by ancestry and two meta-analyses were done: a European ancestry analysis, and a transethnic analysis that included all ancestry groups. We also did a multi-trait analysis of GWAS, in a joint analysis with a study of cerebral white matter hyperintensities (an aetiologically related radiological trait), to find additional genetic associations. We did a transcriptome-wide association study (TWAS) to detect genes for which expression is associated with lacunar stroke; identified significantly enriched pathways using multi-marker analysis of genomic annotation; and evaluated cardiovascular risk factors causally associated with the disease using mendelian randomisation. FINDINGS: Our meta-analysis comprised studies from Europe, the USA, and Australia, including 7338 cases and 254 798 controls, of which 2987 cases (matched with 29 540 controls) were confirmed using MRI. Five loci (ICA1L-WDR12-CARF-NBEAL1, ULK4, SPI1-SLC39A13-PSMC3-RAPSN, ZCCHC14, ZBTB14-EPB41L3) were found to be associated with lacunar stroke in the European or transethnic meta-analyses. A further seven loci (SLC25A44-PMF1-BGLAP, LOX-ZNF474-LOC100505841, FOXF2-FOXQ1, VTA1-GPR126, SH3PXD2A, HTRA1-ARMS2, COL4A2) were found to be associated in the multi-trait analysis with cerebral white matter hyperintensities (n=42 310). Two of the identified loci contain genes (COL4A2 and HTRA1) that are involved in monogenic lacunar stroke. The TWAS identified associations between the expression of six genes (SCL25A44, ULK4, CARF, FAM117B, ICA1L, NBEAL1) and lacunar stroke. Pathway analyses implicated disruption of the extracellular matrix, phosphatidylinositol 5 phosphate binding, and roundabout binding (false discovery rate <0.05). Mendelian randomisation analyses identified positive associations of elevated blood pressure, history of smoking, and type 2 diabetes with lacunar stroke. INTERPRETATION: Lacunar stroke has a substantial heritable component, with 12 loci now identified that could represent future treatment targets. These loci provide insights into lacunar stroke pathogenesis, highlighting disruption of the vascular extracellular matrix (COL4A2, LOX, SH3PXD2A, GPR126, HTRA1), pericyte differentiation (FOXF2, GPR126), TGF-beta signalling (HTRA1), and myelination (ULK4, GPR126) in disease risk. FUNDING: British Heart Foundation.