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Showing 2501 to 2504 of 5186 entries
Published on May 27, 2020
Systematic metabolic analysis of potential target, therapeutic drug, diagnostic method and animal model applicability in three neurodegenerative diseases.
Abstract: Considerable evidence suggests that metabolic abnormalities are associated with neurodegenerative diseases. This study aimed to conduct a systematic metabolic analysis of Alzheimer's disease (AD), Parkinson's disease (PD) and Huntington's disease (HD). Human and mouse model microarray datasets were downloaded from the Gene Expression Omnibus database. The metabolic genes and pathways were collected from the Recon 3D human metabolic model. Drug and target information was obtained from the DrugBank database. This study identified ATP1A1, ATP6V1G2, GOT1, HPRT1, MAP2K1, PCMT1 and PLK2 as key metabolic genes that were downregulated in AD, PD and HD. We screened 57 drugs that target these genes, such as digoxin, ouabain and diazoxide. This study constructed multigene diagnostic models for AD, PD and HD by using metabolic gene expression profiles in blood, all models showed high accuracy (AUC > 0.8) both in the experimental and validation sets. Furthermore, analysis of animal models showed that there was almost no consistency among the metabolic changes between mouse models and human diseases. This study systematically revealed the metabolic damage among AD, PD, and HD and uncovered the differences between animal models and human diseases. This information may be helpful for understanding the metabolic mechanisms and drug development for neurodegenerative diseases.
Published on May 22, 2020
An integrated multi-omics approach identifies the landscape of interferon-alpha-mediated responses of human pancreatic beta cells.
Abstract: Interferon-alpha (IFNalpha), a type I interferon, is expressed in the islets of type 1 diabetic individuals, and its expression and signaling are regulated by T1D genetic risk variants and viral infections associated with T1D. We presently characterize human beta cell responses to IFNalpha by combining ATAC-seq, RNA-seq and proteomics assays. The initial response to IFNalpha is characterized by chromatin remodeling, followed by changes in transcriptional and translational regulation. IFNalpha induces changes in alternative splicing (AS) and first exon usage, increasing the diversity of transcripts expressed by the beta cells. This, combined with changes observed on protein modification/degradation, ER stress and MHC class I, may expand antigens presented by beta cells to the immune system. Beta cells also up-regulate the checkpoint proteins PDL1 and HLA-E that may exert a protective role against the autoimmune assault. Data mining of the present multi-omics analysis identifies two compound classes that antagonize IFNalpha effects on human beta cells.
Published on May 22, 2020
In Silico Subtractive Proteomics Approach for Identification of Potential Drug Targets in Staphylococcus saprophyticus.
Abstract: Staphylococcus saprophyticus is a uropathogenic bacteria responsible for acute urinary tract infections (UTIs) mainly in young female patients. Patients suffering from urinary catheterization, pregnant patients, the elderly as well as those with nosocomial UTIs are at greater risk of the colonizing S. saprophyticus infection. The causative factors include benign prostatic hyperplasia, indwelling catheter, neurogenic bladder, pregnancy, and history of frequent UTIs. Recent findings have exhibited that S. saprophyticus is resistant to several antimicrobial agents. Moreover, there is a global concern regarding the increasing level of antimicrobial resistance, which leads to treatment failure and reduced effectiveness of broad-spectrum antimicrobials. Therefore, a novel approach is being utilized to combat resistant microbes since the past few years. Subtractive proteome analysis has been performed with the entire proteome of S. saprophyticus strain American Type Culture Collection (ATCC) 15305 using several bioinformatics servers and software. The proteins that were non-homologous to humans and bacteria were identified for metabolic pathway analysis. Only four cytoplasmic proteins were found possessing the potential of novel drug target candidates. The development of innovative therapeutic agents by targeting the inhibition of any essential proteins may disrupt the metabolic pathways specific to the pathogen, thus causing destruction as well as eradication of the pathogen from a particular host. The identified targets can facilitate in designing novel and potent drugs against S. saprophyticus strain ATCC 15305.
Published on May 21, 2020
TraPS-VarI: Identifying genetic variants altering phosphotyrosine based signalling motifs.
Abstract: Patient stratification and individualized therapeutic strategies rely on the established knowledge of genotype-specific molecular and cellular alterations of biological and therapeutic significance. Whilst almost all approved drugs have been developed based on the Reference Sequence protein database (RefSeq), the latest genome sequencing studies establish the substantial prevalence of non-synonymous genetic mutations in the general population, including stop-insertion and frame shift mutations within the coding regions of membrane proteins. While the availability of individual genotypes are becoming increasingly common, the biological and clinical interpretations of mutations among individual genomes is largely lagging behind. Lately, transmembrane proteins of haematopoietic (myeloid and lymphoid) derived immune cells have attracted much attention as important targets for cancer immunotherapies. As such, the signalling properties of haematological transmembrane receptors rely on the membrane-proximal phosphotyrosine based sequence motifs (TBSMs) such as ITAM (immunoreceptor tyrosine-based activation motif), ITIM (immunoreceptor tyrosine-based inhibition motif) and signal transducer and activator of transcription 3 (STAT3)-recruiting YxxQ motifs. However, mutations that alter the coding regions of transmembrane proteins, resulting in either insertion or deletion of crucial signal modulating TBSMs, remains unknown. To conveniently identify individual cell line-specific or patient-specific membrane protein altering mutations, we present the Transmembrane Protein Sequence Variant Identifier (TraPS-VarI). TraPS-VarI is an annotation tool for accurate mapping of the effect of an individual's mutation in the transmembrane protein sequence, and to identify the prevalence of TBSMs. TraPS-VarI is a biologist and clinician-friendly algorithm with a web interface and an associated database browser (https://www.traps-vari.org/).
Published on May 21, 2020
Potential Inhibitors for Novel Coronavirus Protease Identified by Virtual Screening of 606 Million Compounds.
Abstract: The rapid outbreak of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China followed by its spread around the world poses a serious global concern for public health. To this date, no specific drugs or vaccines are available to treat SARS-CoV-2 despite its close relation to the SARS-CoV virus that caused a similar epidemic in 2003. Thus, there remains an urgent need for the identification and development of specific antiviral therapeutics against SARS-CoV-2. To conquer viral infections, the inhibition of proteases essential for proteolytic processing of viral polyproteins is a conventional therapeutic strategy. In order to find novel inhibitors, we computationally screened a compound library of over 606 million compounds for binding at the recently solved crystal structure of the main protease (M(pro)) of SARS-CoV-2. A screening of such a vast chemical space for SARS-CoV-2 M(pro) inhibitors has not been reported before. After shape screening, two docking protocols were applied followed by the determination of molecular descriptors relevant for pharmacokinetics to narrow down the number of initial hits. Next, molecular dynamics simulations were conducted to validate the stability of docked binding modes and comprehensively quantify ligand binding energies. After evaluation of potential off-target binding, we report a list of 12 purchasable compounds, with binding affinity to the target protease that is predicted to be more favorable than that of the cocrystallized peptidomimetic compound. In order to quickly advise ongoing therapeutic intervention for patients, we evaluated approved antiviral drugs and other protease inhibitors to provide a list of nine compounds for drug repurposing. Furthermore, we identified the natural compounds (-)-taxifolin and rhamnetin as potential inhibitors of M(pro). Rhamnetin is already commercially available in pharmacies.
Published on May 21, 2020
Serotonin re-uptake transporter gene polymorphisms are associated with imatinib-induced diarrhoea in chronic myeloid leukaemia patients.
Abstract: Tyrosine kinase inhibitors (TKIs), the treatment of choice for chronic myeloid leukaemia (CML), can cause lower gastrointestinal (GI) toxicity which is manifested as diarrhoea. The mechanisms are not fully understood. The enteroendocrine signalling compound, serotonin (5-HT), is important for regulating peristaltic motion, fluid secretion and visceral hypersensitivity in the GI tract, and has been implicated in diseases such as irritable bowel syndrome. In this study, we have evaluated whether TKI-induced diarrhoea may be related to variation in the serotonin re-uptake transporter (SERT) gene. CML patients with and without diarrhoea on the SPIRIT2 trial (imatinib, n = 319; and dasatinib, n = 297) were genotyped for the promoter 5-HTTLPR, intron 2 VNTR and rs25531 polymorphisms by PCR-based methods. Diarrhoea was more prevalent in imatinib, than in dasatinib treated patients (P = 0.015), which when stratified by gender was seen to be driven by female patients (P = 0.036). Logistic regression analysis revealed that age, and the dominant HTTLPR with the rs25531 single nucleotide polymorphism (SNP) model, explained the occurrence of diarrhoea in ~10% of imatinib-treated female CML patients. These data suggest SERT polymorphisms influence imatinib-induced diarrhoea but not that of dasatinib.
Published on May 14, 2020
Methods to Enhance the Metabolic Stability of Peptide-Based PET Radiopharmaceuticals.
Abstract: The high affinity and specificity of peptides towards biological targets, in addition to their favorable pharmacological properties, has encouraged the development of many peptide-based pharmaceuticals, including peptide-based positron emission tomography (PET) radiopharmaceuticals. However, the poor in vivo stability of unmodified peptides against proteolysis is a major challenge that must be overcome, as it can result in an impractically short in vivo biological half-life and a subsequently poor bioavailability when used in imaging and therapeutic applications. Consequently, many biologically and pharmacologically interesting peptide-based drugs may never see application. A potential way to overcome this is using peptide analogues designed to mimic the pharmacophore of a native peptide while also containing unnatural modifications that act to maintain or improve the pharmacological properties. This review explores strategies that have been developed to increase the metabolic stability of peptide-based pharmaceuticals. It includes modifications of the C- and/or N-termini, introduction of d- or other unnatural amino acids, backbone modification, PEGylation and alkyl chain incorporation, cyclization and peptide bond substitution, and where those strategies have been, or could be, applied to PET peptide-based radiopharmaceuticals.
Published on May 13, 2020
Interactome of SARS-CoV-2 / nCoV19 modulated host proteins with computationally predicted PPIs.
Abstract: World over, people are looking for solutions to tackle the pandemic coronavirus disease (COVID-19) caused by the virus SARS-CoV-2/nCoV-19. Notable contributions in biomedical field have been characterizing viral genomes, host transcriptomes and proteomes, repurposable drugs and vaccines. In one such study, 332 human proteins targeted by nCoV19 were identified. We expanded this set of host proteins by constructing their protein interactome, including in it not only the known protein-protein interactions (PPIs) but also novel, hitherto unknown PPIs predicted with our High-precision Protein-Protein Interaction Prediction (HiPPIP) model that was shown to be highly accurate. In fact, one of the earliest discoveries made possible by HiPPIP is related to activation of immunity upon viral infection. We found that several interactors of the host proteins are differentially expressed upon viral infection, are related to highly relevant pathways, and that the novel interaction of NUP98 with CHMP5 may activate an antiviral mechanism leading to disruption of viral budding. We are making the interactions available as downloadable files to facilitate future systems biology studies and also on a web-server at http://hagrid.dbmi.pitt.edu/corona that allows not only keyword search but also queries such as "PPIs where one protein is associated with 'virus' and the interactors with 'pulmonary'".
Published on May 13, 2020
The COVID-19 Gene and Drug Set Library.
Abstract: The coronavirus (CoV) severe acute respiratory syndrome (SARS)-CoV-2 (COVID-19) pandemic has received rapid response by the research community to offer suggestions for repurposing of approved drugs as well as to improve our understanding of the COVID-19 viral life cycle molecular mechanisms. In a short period, tens of thousands of research preprints and other publications have emerged including those that report lists of experimentally validated drugs and compounds as potential COVID-19 therapies. In addition, gene sets from interacting COVID-19 virus-host proteins and differentially expressed genes when comparing infected to uninfected cells are being published at a fast rate. To organize this rapidly accumulating knowledge, we developed the COVID-19 Gene and Drug Set Library (https://amp.pharm.mssm.edu/covid19/), a collection of gene and drug sets related to COVID-19 research from multiple sources. The COVID-19 Gene and Drug Set Library is delivered as a web-based interface that enables users to view, download, analyze, visualize, and contribute gene and drug sets related to COVID-19 research. To evaluate the content of the library, we performed several analyses including comparing the results from 6 in-vitro drug screens for COVID-19 repurposing candidates. Surprisingly, we observe little overlap across these initial screens. The most common and unique hit across these screen is mefloquine, a malaria drug that should receive more attention as a potential therapeutic for COVID-19. Overall, the library of gene and drug sets can be used to identify community consensus, make researchers and clinicians aware of the development of new potential therapies, as well as allow the research community to work together towards a cure for COVID-19.
Published on May 13, 2020
SARS-CoV-2 receptor networks in diabetic kidney disease, BK-Virus nephropathy and COVID-19 associated acute kidney injury.
Abstract: COVID-19 morbidity and mortality is significantly increased in patients with diabetes and kidney disease via unknown mechanisms. SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2) for entry into human host cells, and ACE2 levels in target cells may influence SARS-CoV-2 susceptibility. We investigated how pre-existing conditions and drug treatments alter receptor expression in kidney tissue. Using single cell RNA profiling (scRNAseq) to assess ACE2 and associated SARS-CoV-2 proteases in healthy living donors (LD) kidneys, diabetic kidney disease (DKD), and in kidney injury during viral infection, ACE2 expression was primarily associated with proximal tubular epithelial cells (PTEC). ACE2 mRNA expression levels were significantly upregulated in DKD versus LD, however, ACE2 levels were not altered by exposures to renin angiotensin aldosterone system (RAAS) inhibitors. ACE2+ expression signatures were defined by differential expression analysis and characterized by Bayesian integrative analysis of a large compendium of public -omics datasets, resulting in the identification of network modules induced in ACE2 positive PTEC in DKD and BK virus nephropathy. These ACE2 upregulated cell programs were linked to viral entry, immune activation, endomembrane reorganization, and RNA processing and overlapped significantly with the cellular responses induced by SARS-CoV-2 infection. Similar cellular programs were activated in ACE2-positive PTEC isolated in a urine sample from a COVID19 patient with acute kidney injury, suggesting a consistent ACE2-coregulated expression program that may interact with SARS-Cov-2 infection processes. The SARS-CoV-2 receptor associated gene signatures could seed further research into therapeutic strategies for COVID-19. Functional networks of gene expression signatures are available for further exploration to researchers at HumanBase (hb.flatironinstitute.org/covid-kidney).
Showing 2501 to 2504 of 5186 entries