9 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2020/11/13

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

6 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2020/11/12

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

14 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2020/11/11

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

13 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2020/11/11

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Genomic Medicine: Lessons Learned From Monogenic and Complex Bone Disorders.

Front Endocrinol (Lausanne). 2020;11:556610

Authors: Trajanoska K, Rivadeneira F

Abstract
Current genetic studies of monogenic and complex bone diseases have broadened our understanding of disease pathophysiology, highlighting the need for medical interventions and treatments tailored to the characteristics of patients. As genomic research progresses, novel insights into the molecular mechanisms are starting to provide support to clinical decision-making; now offering ample opportunities for disease screening, diagnosis, prognosis and treatment. Drug targets holding mechanisms with genetic support are more likely to be successful. Therefore, implementing genetic information to the drug development process and a molecular redefinition of skeletal disease can help overcoming current shortcomings in pharmaceutical research, including failed attempts and appalling costs. This review summarizes the achievements of genetic studies in the bone field and their application to clinical care, illustrating the imminent advent of the genomic medicine era.

PMID: 33162933 [PubMed - in process]

Computational drug re-purposing targeting the spike glycoprotein of SARS-CoV-2 as an effective strategy to neutralize COVID-19.

Eur J Pharmacol. 2020 Nov 05;:173720

Authors: Toor HG, Banerjee DI, Lipsa Rath S, Darji SA

Abstract
COVID-19 has intensified into a global pandemic with over a million deaths worldwide. Experimental research analyses have been implemented and executed with the sole rationale to counteract SARS-CoV-2, which has initiated potent therapeutic strategy development in coherence with computational biology validation focusing on the characterized viral drug targets signified by proteomic and genomic data. Spike glycoprotein is one of such potential drug target that promotes viral attachment to the host cellular membrane by binding to its receptor ACE-2 via its Receptor-Binding Domain (RBD). Multiple Sequence alignment and relative phylogenetic analysis revealed significant sequential disparities of SARS-CoV-2 as compared to previously encountered SARS-CoV and MERS-CoV strains. We implemented a drug re-purposing approach wherein the inhibitory efficacy of a cluster of thirty known drug candidates comprising of antivirals, antibiotics and phytochemicals (selection contingent on their present developmental status in underway clinical trials) was elucidated by subjecting them to molecular docking analyses against the spike protein RBD model (developed using homology modelling and validated using SAVES server 5.0) and the composite trimeric structures of spike glycoprotein of SARS-CoV-2. Our results indicated that Camostat, Favipiravir, Tenofovir, Raltegravir and Stavudine showed significant interactions with spike RBD of SARS-CoV-2. Proficient bioavailability coupled with no predicted in silico toxicity rendered them as prospective alternatives for designing and development of novel combinatorial therapy formulations for improving existing treatment regimes to combat COVID-19.

PMID: 33160938 [PubMed - as supplied by publisher]

A network medicine approach to investigation and population-based validation of disease manifestations and drug repurposing for COVID-19.

PLoS Biol. 2020 Nov 06;18(11):e3000970

Authors: Zhou Y, Hou Y, Shen J, Mehra R, Kallianpur A, Culver DA, Gack MU, Farha S, Zein J, Comhair S, Fiocchi C, Stappenbeck T, Chan T, Eng C, Jung JU, Jehi L, Erzurum S, Cheng F

Abstract
The global coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to unprecedented social and economic consequences. The risk of morbidity and mortality due to COVID-19 increases dramatically in the presence of coexisting medical conditions, while the underlying mechanisms remain unclear. Furthermore, there are no approved therapies for COVID-19. This study aims to identify SARS-CoV-2 pathogenesis, disease manifestations, and COVID-19 therapies using network medicine methodologies along with clinical and multi-omics observations. We incorporate SARS-CoV-2 virus-host protein-protein interactions, transcriptomics, and proteomics into the human interactome. Network proximity measurement revealed underlying pathogenesis for broad COVID-19-associated disease manifestations. Analyses of single-cell RNA sequencing data show that co-expression of ACE2 and TMPRSS2 is elevated in absorptive enterocytes from the inflamed ileal tissues of Crohn disease patients compared to uninflamed tissues, revealing shared pathobiology between COVID-19 and inflammatory bowel disease. Integrative analyses of metabolomics and transcriptomics (bulk and single-cell) data from asthma patients indicate that COVID-19 shares an intermediate inflammatory molecular profile with asthma (including IRAK3 and ADRB2). To prioritize potential treatments, we combined network-based prediction and a propensity score (PS) matching observational study of 26,779 individuals from a COVID-19 registry. We identified that melatonin usage (odds ratio [OR] = 0.72, 95% CI 0.56-0.91) is significantly associated with a 28% reduced likelihood of a positive laboratory test result for SARS-CoV-2 confirmed by reverse transcription-polymerase chain reaction assay. Using a PS matching user active comparator design, we determined that melatonin usage was associated with a reduced likelihood of SARS-CoV-2 positive test result compared to use of angiotensin II receptor blockers (OR = 0.70, 95% CI 0.54-0.92) or angiotensin-converting enzyme inhibitors (OR = 0.69, 95% CI 0.52-0.90). Importantly, melatonin usage (OR = 0.48, 95% CI 0.31-0.75) is associated with a 52% reduced likelihood of a positive laboratory test result for SARS-CoV-2 in African Americans after adjusting for age, sex, race, smoking history, and various disease comorbidities using PS matching. In summary, this study presents an integrative network medicine platform for predicting disease manifestations associated with COVID-19 and identifying melatonin for potential prevention and treatment of COVID-19.

PMID: 33156843 [PubMed - as supplied by publisher]

Identification and characterization of novel RdRp and Nsp15 inhibitors for SARS-COV2 using computational approach.

J Biomol Struct Dyn. 2020 Nov 06;:1-18

Authors: Barage S, Karthic A, Bavi R, Desai N, Kumar R, Kumar V, Lee KW

Abstract
The World Health Organization has declared COVID-19 as a global health emergency. COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and highlights an urgent need for therapeutics. Here, we have employed a series of computer-aided drug repurposing campaign to discover inhibitors of RNA dependent RNA polymerase (RdRp) and Nsp15/EndoU. Subsequently, MD simulation has been performed to observe dynamic behavior of identified leads at the active site of RdRp and Nsp15. We successfully identified novel lead molecule such as Alectinib for RdRp while Naldemedine and Ergotamine for NSP15. These lead molecules were accommodated in the active site of the enzyme and stabilized by the networks of the hydrogen bond, pi type and hydrophobic interaction with key residues of either target. Interestingly, identified compounds show molecular mimicry in terms of molecular interactions with key residues of RdRp and Nsp15 essential for catalysis and substrate interaction. Previously, Alectinib, Naldemedine and Ergotamine were used as drug in different diseases might be repurposed against selected protein targets of COVID19. Finally, we propose that the identified inhibitors represent a novel lead molecule to design a more effective inhibitor to stop the progress of pathogen. Communicated by Ramaswamy H. Sarma.

PMID: 33155531 [PubMed - as supplied by publisher]

Repurposing Antimalarials to Tackle the COVID-19 Pandemic.

Trends Parasitol. 2020 Oct 19;:

Authors: Krishna S, Augustin Y, Wang J, Xu C, Staines HM, Platteeuw H, Kamarulzaman A, Sall A, Kremsner P

Abstract
Artemisinin-based combination therapies (ACTs) have demonstrated in vitro inhibition of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Artemisinins have also shown anti-inflammatory effects, including inhibition of interleukin-6 (IL-6) that plays a key role in the development of severe coronavirus disease 2019 (COVID-19). There is now sufficient evidence for the effectiveness of ACTs, and in particular artesunate/pyronaridine, to support clinical studies for COVID-19 infections.

PMID: 33153922 [PubMed - as supplied by publisher]

7 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2020/11/06

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

A review on drug repurposing applicable to COVID-19.

Brief Bioinform. 2020 Nov 05;:

Authors: Dotolo S, Marabotti A, Facchiano A, Tagliaferri R

Abstract
Drug repurposing involves the identification of new applications for existing drugs at a lower cost and in a shorter time. There are different computational drug-repurposing strategies and some of these approaches have been applied to the coronavirus disease 2019 (COVID-19) pandemic. Computational drug-repositioning approaches applied to COVID-19 can be broadly categorized into (i) network-based models, (ii) structure-based approaches and (iii) artificial intelligence (AI) approaches. Network-based approaches are divided into two categories: network-based clustering approaches and network-based propagation approaches. Both of them allowed to annotate some important patterns, to identify proteins that are functionally associated with COVID-19 and to discover novel drug-disease or drug-target relationships useful for new therapies. Structure-based approaches allowed to identify small chemical compounds able to bind macromolecular targets to evaluate how a chemical compound can interact with the biological counterpart, trying to find new applications for existing drugs. AI-based networks appear, at the moment, less relevant since they need more data for their application.

PMID: 33147623 [PubMed - as supplied by publisher]

Computational drug repositioning based on multi-similarities bilinear matrix factorization.

Brief Bioinform. 2020 Nov 05;:

Authors: Yang M, Wu G, Zhao Q, Li Y, Wang J

Abstract
With the development of high-throughput technology and the accumulation of biomedical data, the prior information of biological entity can be calculated from different aspects. Specifically, drug-drug similarities can be measured from target profiles, drug-drug interaction and side effects. Similarly, different methods and data sources to calculate disease ontology can result in multiple measures of pairwise disease similarities. Therefore, in computational drug repositioning, developing a dynamic method to optimize the fusion process of multiple similarities is a crucial and challenging task. In this study, we propose a multi-similarities bilinear matrix factorization (MSBMF) method to predict promising drug-associated indications for existing and novel drugs. Instead of fusing multiple similarities into a single similarity matrix, we concatenate these similarity matrices of drug and disease, respectively. Applying matrix factorization methods, we decompose the drug-disease association matrix into a drug-feature matrix and a disease-feature matrix. At the same time, using these feature matrices as basis, we extract effective latent features representing the drug and disease similarity matrices to infer missing drug-disease associations. Moreover, these two factored matrices are constrained by non-negative factorization to ensure that the completed drug-disease association matrix is biologically interpretable. In addition, we numerically solve the MSBMF model by an efficient alternating direction method of multipliers algorithm. The computational experiment results show that MSBMF obtains higher prediction accuracy than the state-of-the-art drug repositioning methods in cross-validation experiments. Case studies also demonstrate the effectiveness of our proposed method in practical applications. Availability: The data and code of MSBMF are freely available at https://github.com/BioinformaticsCSU/MSBMF. Corresponding author: Jianxin Wang, School of Computer Science and Engineering, Central South University, Changsha, Hunan 410083, P. R. China. E-mail: jxwang@mail.csu.edu.cn Supplementary Data: Supplementary data are available online at https://academic.oup.com/bib.

PMID: 33147616 [PubMed - as supplied by publisher]

Repurposing of Streptomyces antibiotics as adenosine deaminase inhibitors by pharmacophore modeling, docking, molecular dynamics, and in vitro studies.

J Recept Signal Transduct Res. 2020 Feb;40(1):77-88

Authors: Arun KG, Sharanya CS, Abhithaj J, Sadasivan C

Abstract
Adenosine deaminase (ADA) is an enzyme present in purine metabolic pathway. Its inhibitors are considered to be potent drug lead compounds against inflammatory and malignant diseases. This study aimed to test ADA inhibitory activity of some Streptomyces secondary metabolites by using computational and in vitro methods. The in silico screening of the inhibitory properties has been carried out using pharmacophore modeling, docking, and molecular dynamics studies. The in vitro validation of the selected antibiotics has been carried out by enzyme kinetics and fluorescent spectroscopic studies. The results indicated that novobiocin, an aminocoumarin antibiotic from Streptomyces niveus, has significant inhibition on ADA activity. Hence, the antibiotic can be used as a lead compound for the development of potential ADA inhibitors.

PMID: 31971048 [PubMed - indexed for MEDLINE]

10 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2020/11/04

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

9 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2020/11/04

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

8 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2020/11/03

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Tutankhamun's Antimalarial Drug for Covid-19.

Drug Res (Stuttg). 2020 Oct 30;:

Authors: Sommer AP, Försterling HD, Sommer KE

Abstract
Drug repositioning is a strategy that identifies new uses of approved drugs to treat conditions different from their original purpose. Current efforts to treat Covid-19 are based on this strategy. The first drugs used in patients infected with SARS-CoV-2 were antimalarial drugs. It is their mechanism of action, i. e., rise in endosomal pH, which recommends them against the new coronavirus. Disregarding their side effects, the study of their antiviral activity provides valuable hints for the choice and design of drugs against SARS-CoV-2. One prominent drug candidate is thymoquinone, an antimalarial substance contained in Nigella sativa - most likely one of the first antimalarial drugs in human history. Since the outbreak of the pandemic, the number of articles relating thymoquinone to Covid-19 continuously increases. Here, we use it as an exemplary model drug, compare its antiviral mechanism with that of conventional antimalarial drugs and establish an irreducible parametric scheme for the identification of drugs with a potential in Covid-19.Translation into the laboratory is simple. Starting with the discovery of Nigella sativa seeds in the tomb of Pharaoh Tutankhamun, we establish a physicochemical model for the interaction of thymoquinone with both coronavirus and cells. Exploiting the predictive capability of the model, we provide a generalizable scheme for the systematic choice and design of drugs for Covid-19. An unexpected offshoot of our research is that Tutankhamun could not have died of malaria, a finding contrary to the mainstream theory.

PMID: 33128226 [PubMed - as supplied by publisher]

Beta-Adrenergic Blockers as a Potential Treatment for COVID-19 Patients.

Bioessays. 2020 11;42(11):e2000094

Authors: Vasanthakumar N

Abstract
More than 15 million people have been affected by coronavirus disease 2019 (COVID-19) and it has caused 640 016 deaths as of July 26, 2020. Currently, no effective treatment option is available for COVID-19 patients. Though many drugs have been proposed, none of them has shown particular efficacy in clinical trials. In this article, the relationship between the Adrenergic system and the renin-angiotensin-aldosterone system (RAAS) is focused in COVID-19 and a vicious circle consisting of the Adrenergic system-RAAS-Angiotensin converting enzyme 2 (ACE2)-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (which is referred to as the "ARAS loop") is proposed. Hyperactivation of the ARAS loop may be the underlying pathophysiological mechanism in COVID-19, and beta-adrenergic blockers are proposed as a potential treatment option. Beta-adrenergic blockers may decrease the SARS-CoV-2 cellular entry by decreasing ACE2 receptors expression and cluster of differentiation 147 (CD147) in various cells in the body. Beta-adrenergic blockers may decrease the morbidity and mortality in COVID-19 patients by preventing or reducing acute respiratory distress syndrome (ARDS) and other complications. Retrospective and prospective clinical trials should be conducted to check the validity of the hypothesis. Also see the video abstract here https://youtu.be/uLoy7do5ROo.

PMID: 32815593 [PubMed - indexed for MEDLINE]

Targeted repositioning identifies drugs that increase fibroblast growth factor 20 production and protect against 6-hydroxydopamine-induced nigral cell loss in rats.

Sci Rep. 2019 06 06;9(1):8336

Authors: Fletcher EJR, Jamieson AD, Williams G, Doherty P, Duty S

Abstract
Endogenous fibroblast growth factor 20 (FGF20) supports maintenance of dopaminergic neurones within the nigrostriatal pathway. Moreover, direct intracerebral infusion of FGF20 protects against nigrostriatal tract loss in the 6-hydroxydopamine lesion rat model of Parkinson's disease. Increasing endogenous FGF20 production might provide a less-invasive, more translational way of providing such protection. Accordingly, we adopted a targeted repositioning approach to screen for candidate FDA-approved drugs with potential to enhance endogenous FGF20 production in brain. In silico interrogation of the Broad Institute's Connectivity Map database (CMap), revealed 50 candidate drugs predicted to increase FGF20 transcription, 16 of which had profiles favourable for use in Parkinson's disease. Of these, 11 drugs were found to significantly elevate FGF20 protein production in MCF-7 cells, between two- and four-fold. Four drugs were selected for examination in vivo. Following oral dosing in rats for 7 days, salbutamol and triflusal, but not dimethadione or trazodone, significantly elevated FGF20 levels in the nigrostriatal tract. Preliminary examination in the unilateral 6-hydroxydopamine-lesioned rat revealed a modest but significant protection against nigral cell loss with both drugs. Our data demonstrate the power of targeted repositioning as a method to identify existing drugs that may combat disease progression in Parkinson's by boosting FGF20 levels.

PMID: 31171821 [PubMed - indexed for MEDLINE]

6 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2020/10/31

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.