Drug Repurposing News

Network-based analysis of transcriptional profiles from chemical perturbations experiments

April 11th 2017, Posted by: Drug Repurposing Portal

A pipeline for analyzing transcriptional network inference and comparison for grouping chemicals with similar functions and carcinogenicity / genotoxicity profiles. In the context of drug discovery or drug repositioning, discussed method could help assign new functions to novel or existing drugs, based on the similarity of their associated network with those built for other known compounds. Additionally, the method has broad applicability beyond the uses here described and could be used as an alternative or as a complement to standard approaches of differential gene expression analysis.

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Deep-Learning-Based Drug-Target Interaction Prediction

March 13th 2017, Posted by: Drug Repurposing Portal

Wen and team from Central South University & Chinese Academy of Tropical Agricultural Sciences-China, have found a method to accurately predict new drug-target interactions (DTIs) between approved drugs and targets without separating the targets into different classes. The group has developed a deep-learning-based algorithmic framework named DeepDTIs which can be further used to predict whether a new drug targets to some existing targets or whether a new target interacts with some existing drugs.

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In vitro screening of an FDA-Approved Library against ESKAPE pathogens

March 9th 2017, Posted by: Drug Repurposing Portal

In an effort to repurpose drugs and explore new leads in the field of antimicrobial drug discovery, Younis et al at Purdue University College of Veterinary Medicine performed a whole-cell screening assay of 1,600 Food and Drug Administration (FDA) approved drugs against Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter cloacae (ESKAPE) pathogens. The in vitro screening identified 49 non-antimicrobial drugs that were active against at least one species of ESKAPE pathogen. Although some of these drugs were known to have antibacterial activity, many have never been reported before and Sulfonamide based structures were proposed for further investigation.

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Drug voyager: a computational platform for exploring unintended drug action

February 28th 2017, Posted by: Drug Repurposing Portal

This study addresses how we can computationally represent drug-signaling pathways to understand unintended drug actions and to facilitate drug discovery and screening. This is ?a novel platform to construct a drug-specific pathway in which a molecular-level mechanism of action is formulated based on pharmacologic, pharmacogenomic, transcriptomic, and phenotypic data related to drug response ( http://databio.gachon.ac.kr/tools/ )

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Computational Multitarget Drug Design

February 23rd 2017, Posted by: Drug Repurposing Portal

An overview of recent progress on finding drugs that can hit multiple targets for a complex disease. Such approach takes in to account features of both ligand and its different receptors. On successful application, these drugs have the potential to replace or reduce the requirements of multi-drug therapy.

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A Systematic Framework for Drug Repositioning from Integrated Omics and Drug Phenotype Profiles Using Pathway-Drug Network

February 23rd 2017, Posted by: Drug Repurposing Portal

Drug repositioning offers new clinical indications for old drugs. Recently, many computational approaches have been developed to repurpose marketed drugs in human diseases by mining various of biological data including disease expression profiles, pathways, drug phenotype expression profiles, and chemical structure data. However, despite encouraging results, a comprehensive and efficient computational drug repositioning approach is needed that includes the high-level integration of available resources. In this study, we propose a systematic framework employing experimental genomic knowledge and pharmaceutical knowledge to reposition drugs for a specific disease. Specifically, we first obtain experimental genomic knowledge from disease gene expression profiles and pharmaceutical knowledge from drug phenotype expression profiles and construct a pathway-drug network representing a priori known associations between drugs and pathways. To discover promising candidates for drug repositioning, we initialize node labels for the pathway-drug network using identified disease pathways and known drugs associated with the phenotype of interest and perform network propagation in a semi-supervised manner. To evaluate our method, we conducted some experiments to reposition 1309 drugs based on four different breast cancer datasets and verified the results of promising candidate drugs for breast cancer by a two-step validation procedure. Consequently, our experimental results showed that the proposed framework is quite useful approach to discover promising candidates for breast cancer treatment.

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Human enterovirus 71 protein interaction network prompts antiviral drug repositioning

February 21st 2017, Posted by: Drug Repurposing Portal

Lu et al of Beijing Institute of Radiation Medicine used a combination of experimental and computational approaches to identify interactions between EV71 proteins and host cellular proteins and confirmed the functional relationships of EV71-interacting proteins (EIPs) with virus proliferation and infection by integrating a human protein interaction network and by functional annotation. The team predicted tanespimycin as a candidate and demonstrated its antiviral efficiency in vitro. These findings provide the first systematic identification of EV71-host protein interactions, an analysis of EIP protein characteristics and a demonstration of their value in developing host-oriented antiviral therapies.

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Pharmacophore-based screening and drug repurposing exemplified on glycogen synthase kinase-3 inhibitors

January 21st 2017, Posted by: Drug Repurposing Portal

Study by Crisan et al elaborate a novel pharmacophore model to accurately map selective glycogen synthase kinase-3 (GSK-3) inhibitors, and perform virtual screening and drug repurposing. Pharmacophore modeling was developed using PHASE on a data set of 203 maleimides. Two benchmarking validation data sets with focus on selectivity were assembled using ChEMBL and PubChem GSK-3 confirmatory assays. A drug repurposing experiment linking pharmacophore matching with drug information originating from multiple data sources was performed. A five-point pharmacophore model was built consisting of a hydrogen bond acceptor (A), hydrogen bond donor (D), hydrophobic (H), and two rings (RR). An atom-based 3D quantitative structure-activity relationship (QSAR) model showed good correlative and satisfactory predictive. The pharmacophore and 3D QSAR models can provide assistance to design novel, potential GSK-3 inhibitors with high potency and selectivity pattern, with potential application for the treatment of GSK-3-driven diseases. A class of purine nucleoside antileukemic drugs was identified as potential inhibitor of GSK-3, suggesting the reassessment of the target range of these drugs.

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Link prediction in drug-target interactions network using similarity indices

January 21st 2017, Posted by: Drug Repurposing Portal

In silico drug-target interaction (DTI) prediction plays an integral role in drug repositioning. One popular method of drug repositioning is network-based DTI prediction, which uses complex network theory to predict DTIs from a drug-target network. DTI prediction of this algorithm makes use of only network topology information yield higher precision for high-ranking predictions than Restricted Boltzmann Machines (RBM) when no information regarding DTI types is available.

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Predicting High-Impact Pharmacological Targets by Integrating Transcriptome and Text-Mining Features

December 31st 2016, Posted by: Drug Repurposing Portal

Novel, "outside of the box" approaches are needed for evaluating candidate molecules, especially in oncology. Throughout the years of 2000-2010, the efficiency of drug development fell to barely acceptable levels, and in the second decade of this century, levels have improved only marginally. This dismal condition continues despite unprecedented progress in the development of a variety of high-throughput tools, computational methods, aggregated databases, drug repurposing programs and innovative chemistries. Here we tested a hypothesis that the economic impact of targeting a particular gene product is predictable a priori by employing a combination of transcriptome profiles and quantitative metrics reflecting existing literature.

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Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

December 11th 2016, Posted by: Drug Repurposing Portal

The promise of drug repurposing is that existing drugs may be used for new disease indications in order to curb the high costs and time for approval. The goal of computational methods for drug repurposing is to enable solutions for safer, cheaper and faster drug discovery. Towards this end, we developed a novel method that integrates genetic and clinical phenotype data from large-scale GWAS and PheWAS studies with detailed drug information on the concept of transitive Drug-Gene-Disease triads. We created "RE:fine Drugs," a freely available, interactive dashboard that automates gene, disease and drug-based searches to identify drug repurposing candidates. This web-based tool supports a user-friendly interface that includes an array of advanced search and export options. Results can be prioritized in a variety of ways, including but not limited to, biomedical literature support, strength and statistical significance of GWAS and/or PheWAS associations, disease indications and molecular drug targets. Here we provide a protocol that illustrates the functionalities available in the "RE:fine Drugs" system and explores the different advanced options through a case study.

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An Integrative Drug Repurposing Pipeline: Switching Viral Drugs to Breast Cancer

November 23rd 2016, Posted by: Drug Repurposing Portal

Resistance due to mutation is more common in Breast Cancer and there are no feasible tactics to overcome this bottleneck. A multi-modal computational drug repositioning approach proposed by scientists at VIT University suggest that Ombitasvir, a Hepatitis C NS5B Polymerase inhibitor, could be "repurposed" for the control and prevention of beta-tubulin driven breast cancers.

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A review of validation strategies for computational drug repositioning

November 22nd 2016, Posted by: Drug Repurposing Portal

Repositioning of previously approved drugs is a promising methodology because it reduces the cost and duration of the drug development pipeline and reduces the likelihood of unforeseen adverse events. Computational repositioning is especially appealing because of the ability to rapidly screen candidates in silico and to reduce the number of possible repositioning candidates. What is unclear, however, is how useful such methods are in producing clinically efficacious repositioning hypotheses. Furthermore, there is no agreement in the field over the proper way to perform validation of in silico predictions, and in fact no systematic review of repositioning validation methodologies. To address this unmet need, we review the computational repositioning literature and capture studies in which authors claimed to have validated their work. Our analysis reveals widespread variation in the types of strategies, predictions made and databases used as 'gold standards'. We highlight a key weakness of the most commonly used strategy and propose a path forward for the consistent analytic validation of repositioning techniques.

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Computational Drug Target Screening through Protein Interaction Profiles

November 15th 2016, Posted by: Drug Repurposing Portal

The development of computational methods to discover novel drug-target interactions on a large scale is of great interest. We propose a new method for virtual screening based on protein interaction profile similarity to discover new targets for molecules, including existing drugs. We calculated Target Interaction Profile Fingerprints (TIPFs) based on ChEMBL database to evaluate drug similarity and generated new putative compound-target candidates from the non-intersecting targets in each pair of compounds. A set of drugs was further studied in monoamine oxidase B (MAO-B) and cyclooxygenase-1 (COX-1) enzyme through molecular docking and experimental assays. The drug ethoxzolamide and the natural compound piperlongumine, present in Piper longum L, showed hMAO-B activity with IC50 values of 25 and 65??M respectively. Five candidates, including lapatinib, SB-202190, RO-316233, GW786460X and indirubin-3'-monoxime were tested against human COX-1. Compounds SB-202190 and RO-316233 showed a IC50 in hCOX-1 of 24 and 25??M respectively (similar range as potent inhibitors such as diclofenac and indomethacin in the same experimental conditions). Lapatinib and indirubin-3'-monoxime showed moderate hCOX-1 activity (19.5% and 28% of enzyme inhibition at 25??M respectively). Our modeling constitutes a multi-target predictor for large scale virtual screening with potential in lead discovery, repositioning and drug safety.

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DPDR-CPI, a server that predicts Drug Positioning and Drug Repositioning via Chemical-Protein Interactome

November 2nd 2016, Posted by: Drug Repurposing Portal

The cost of developing a new drug has increased sharply over the past years. To ensure a reasonable return-on-investment, it is useful for drug discovery researchers in both industry and academia to identify all the possible indications for early pipeline molecules. For the first time, we propose the term computational "drug candidate positioning" or "drug positioning", to describe the above process. It is distinct from drug repositioning, which identifies new uses for existing drugs and maximizes their value. Since many therapeutic effects are mediated by unexpected drug-protein interactions, it is reasonable to analyse the chemical-protein interactome (CPI) profiles to predict indications. Here we introduce the server DPDR-CPI, which can make real-time predictions based only on the structure of the small molecule. When a user submits a molecule, the server will dock it across 611 human proteins, generating a CPI profile of features that can be used for predictions. It can suggest the likelihood of relevance of the input molecule towards ~1,000 human diseases with top predictions listed. DPDR-CPI achieved an overall AUROC of 0.78 during 10-fold cross-validations and AUROC of 0.76 for the independent validation.

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A Computational Systems Biology Approach for Identifying Candidate Drugs for Repositioning for Cardiovascular Disease

October 24th 2016, Posted by: Drug Repurposing Portal

Combining disease-associated gene sets,drug-transcriptome-responses datasets and drug-target annotations can potentially be useful as a screening tool for diseases that lack an accepted cellular model for in vitro screening. With this view, a dataset of transcriptome responses of a cell line to a panel of drugs; two sets of genes for the disease; and mappings between drugs and the receptors or pathways that they target, were integrated. The application of this method to data from (1) CMap 2.0; (2) gene sets from two transcriptome profiling studies of atherosclerosis; and (3) a combined dataset of drug/target information recapitulated the known targets related to CVD (e.g., PPARγ ; HMG-CoA reductase, HDACs) and novel targets (e.g., amine oxidase A, σ-opioid receptor). From this study it can be concluded that this method can potentially be useful as a screening tool for diseases that lack an accepted cellular model for in vitro screening.

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Drug repurposing by integrated literature mining and drug-gene-disease triangulation

October 22nd 2016, Posted by: Drug Repurposing Portal

Drug design is expensive, time-consuming and becoming increasingly complicated. Computational approaches for inferring potentially new purposes of existing drugs, referred to as drug repositioning, play an increasingly important part in current pharmaceutical studies. Here, we first summarize recent developments in computational drug repositioning and introduce the utilized data sources. Afterwards, we introduce a new data fusion model based on n-cluster editing as a novel multi-source triangulation strategy, which was further combined with semantic literature mining. Our evaluation suggests that utilizing drug-gene-disease triangulation coupled to sophisticated text analysis is a robust approach for identifying new drug candidates for repurposing.

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Identification of Potential Therapeutics to Conquer Drug Resistance in Salmonella typhimurium: Drug Repurposing Strategy

October 19th 2016, Posted by: Drug Repurposing Portal

The objective of this study was to use computational drug repurposing to identify a novel candidate with an effective mechanism of action to circumvent the drug resistance.

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Drug Repurposing for Glioblastoma based on Molecular Subtypes

September 30th 2016, Posted by: Drug Repurposing Portal

A novel computational drugrepurposing approach was developed to predict glioblastoma (GBM) drugs based on the molecular subtypes. Recently, multi-platform analysis by The Cancer Genome Atlas identified four distinct molecular subtypes for GBM and demonstrated that the subtypes correlate with clinical phenotypes and treatment responses. This approach leverages the genomic signature for each GBM subtype, and integrates the human cancer genomics with mouse phenotype data to identify the opportunity of reusing the FDA-approved agents to treat specific GBM subtypes.

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Advances in computational biology and artificial intelligence used to identify compounds with potential to extend human life

September 27th 2016, Posted by: Drug Repurposing Portal

Insilico Medicine, Inc. and Life Extension today announced the publication of a research paper describing the applications of its human signaling pathway-centric GeroScope platform for scoring human tissue-specific geroprotective properties of compounds implicated in the aging of model organisms. Insilico Medicine, Inc. utilizes advances in genomics, big data analysis and deep learning for in silico drug discovery and drug repurposing for aging and age-related diseases.

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Computational Method Identifies Existing Drugs with Virus-Fighting Potential

September 16th 2016, Posted by: Drug Repurposing Portal

A new, computer-based screening method could reveal the virus-fighting potential of drugs originally developed to treat other conditions, reports a study in PLOS Computational Biology. Every year, viral infections cause millions of deaths worldwide. While traditional drug development can yield powerful new antiviral medications, repurposing existing drugs that are already well understood is an appealing alternative. Feixiong Cheng of Vanderbilt University School of Medicine, Tennessee, and colleagues has developed a new strategy to quickly identify drugs with this potential.

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A Network-Based Data Integration Approach to Support Drug Repurposing and Multi-Target Therapies in Triple Negative Breast Cancer

September 15th 2016, Posted by: Drug Repurposing Portal

Dr Bellazzi and his colleagues used a network-based modelling within a novel bioinformatics pipeline to identify promising multi-target drugs. A list of drug candidates is extracted by applying a recent data fusion approach based on matrix tri-factorization. Available knowledge about selected drugs mechanisms of action is finally exploited to identify the most promising candidates for repurposing drugs for triple negative breast cancer.

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Symptom Science: Repurposing Existing Omics Data

September 9th 2016, Posted by: Drug Repurposing Portal

Omics approaches, including genomics, transcriptomics, proteomics, epigenomics, microbiomics, and metabolomics, generate large data sets. Once they have been used to address initial study aims, these large data sets are extremely valuable to the greater research community for ancillary investigations. Repurposing available omics data sets provides data to address research questions, generate and test hypotheses, replicate findings, and conduct mega-analyses. Many well-characterized, longitudinal, epidemiological studies collected extensive phenotype data related to symptom occurrence and severity. While the main phenotype of interest for many of these studies was often not symptom related, these data were collected to better understand the primary phenotype of interest. A search for symptom data (i.e., cognitive impairment, fatigue, gastrointestinal distress/nausea, sleep, and pain) in the database of genotypes and phenotypes (dbGaP) revealed many studies that collected symptom and omics data. There is thus a real possibility for nurse scientists to be able to look at symptom data over time from thousands of individuals and use omics data to identify key biological underpinnings that account for the development and severity of symptoms without recruiting participants or generating any new data. The purpose of this article is to introduce the reader to resources that provide omics data to the research community for repurposing, provide guidance on using these databases, and encourage the use of these data to move symptom science forward.

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Cancer Drug Development Using Drosophila as an in vivo Tool: From Bedside to Bench and Back

September 1st 2016, Posted by: Drug Repurposing Portal

Several cell signalling pathways in Drosophila have been used for cancer drug development. The efficacy of combination therapy and uptake/bioavailability of drugs have also been studied. Drosophila has been validated using several FDA-approved drugs, suggesting a potential application of this model in drug repurposing. The model is emerging as a powerful tool for high-throughput screening and should significantly reduce the cost and time associated with drug development.

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Pharmacodynamics and Systems Pharmacology Approaches to Repurposing Drugs in the Wake of Global Health Burden.

August 26th 2016, Posted by: Drug Repurposing Portal

There are emergent needs for cost-effective treatment worldwide, for which repurposing to develop a drug with existing marketing approval of disease(s) for new disease(s) is a valid option. Although strategic mining of electronic health records has produced real-world evidences to inform drug repurposing, using omics data (drug and disease), knowledge base of protein interactions, and database of transcription factors have been explored. Structured integration of all the existing data under the framework of drug repurposing will facilitate decision making. The ability to foresee the need to integrate new data types produced by emergent technologies and to enable data connectivity in the context of human biology and targeted diseases, as well as to use the existing crucial quality data of all approved drugs will catapult the number of drugs being successfully repurposed. However, translational pharmacodynamics databases for modeling information across human biology in the context of host factors are lacking and are critically needed for drug repurposing to improve global public health, especially for the efforts to combat neglected tropic diseases as well as emergent infectious diseases such as Zika or Ebola virus.

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Drug repositioning in SLE: crowd-sourcing, literature-mining and Big Data analysis.

August 26th 2016, Posted by: Drug Repurposing Portal

Lupus patients are in need of modern drugs to treat specific manifestations of their disease effectively and safely. In the past half century, only one new treatment has been approved by the US Food and Drug Administration (FDA) for systemic lupus erythematosus (SLE). In 2014-2015, the FDA approved 71 new drugs, only one of which targeted a rheumatic disease and none of which was approved for use in SLE. Repositioning/repurposing drugs approved for other diseases using multiple approaches is one possible means to find new treatment options for lupus patients. "Big Data" analysis approaches this challenge from an unbiased standpoint whereas literature mining and crowd sourcing for candidates assessed by the CoLTs (Combined Lupus Treatment Scoring) system provide a hypothesis-based approach to rank potential therapeutic candidates for possible clinical application. Both approaches mitigate risk since the candidates assessed have largely been extensively tested in clinical trials for other indications. The usefulness of a multi-pronged approach to drug repositioning in lupus is highlighted by orthogonal confirmation of hypothesis-based drug repositioning predictions by "Big Data" analysis of differentially expressed genes from lupus patient samples. The goal is to identify novel therapies that have the potential to affect disease processes specifically. Involvement of SLE patients and the scientists that study this disease in thinking about new drugs that may be effective in lupus though crowd-sourcing sites such as LRxL-STAT (www.linkedin.com/in/lrxlstat) is important in stimulating the momentum needed to test these novel drug targets for efficacy in lupus rapidly in small, proof-of-concept trials conducted by LuCIN, the Lupus Clinical Investigators Network (www.linkedin.com/in/lucinstat).

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Computational Approaches for Innovative Antiepileptic Drug Discovery

August 5th 2016, Posted by: Drug Repurposing Portal

Herein, the author discusses the impact that network pharmacology and the current hypotheses of refractory epilepsy and drug repurposing could have if integrated with anti-epileptic computer-aided discovery. With many complex diseases, the advancement in the understanding of disorder pathophysiology in addition to the contribution of systems biology have rapidly translated into the discovery of novel drug candidates. However, antiepileptic drug developers have fallen a little behind in this regard, with fewer examples of computer-aided antiepileptic drug design and network-based approximations appearing in scientific literature. New generation single-target agents have so far shown limited success in terms of enhanced efficacy; in contrast, multi-target agents could possibly demonstrate improved safety and efficacy.

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A network based approach to drug repositioning identifies plausible candidates for breast cancer and prostate cancer

July 30th 2016, Posted by: Drug Repurposing Portal

Chen and colleagues have used a novel approach to identify potential drugs for repositioning. This method utilized functional linkage network, mutations and alterations in RNA expression and narrowed down on five potential multi-target drug candidates for treating breast and prostate cancer. In vitro studies in MCF7 and SUM149 cancer cell lines supported the superior therapeutic indices of the short-listed candidates over Doxorubicin.

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Semantic Web Ontology and Data Integration: a Case Study in Aiding Psychiatric Drug Repurposing

July 20th 2016, Posted by: Drug Repurposing Portal

Despite ongoing progress towards treating mental illness, there remain significant difficulties in selecting probable candidate drugs from the existing database. In this study an ontology - oriented approach aims to represent the nexus between genes, drugs, phenotypes, symptoms, and diseases from multiple information sources. Along with this approach, author reported a case study in which he attempted to explore the candidate drugs that effective for both bipolar disorder and epilepsy.

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Tumor Deconstruction as a Tool for Advanced Drug Screening and Repositioning

July 15th 2016, Posted by: Drug Repurposing Portal

Embracing of a comprehensive, informative and analytical assessment of the cellular content of residual tumors, it is possible to immensely improve the fidelity and statistical robustness of preclinical drug discovery as suggested in this current study. Iterating this approach after initial POC screening in the drug discovery pipeline would have a great impact in terms of precision of drug evaluation, design of optimal drug combinations and/or drug repositioning.

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Interaction and Localization Diversities of Global and Local hubs in human Protein-Protein Interaction Networks

July 12th 2016, Posted by: Drug Repurposing Portal

Protein-protein interaction networks (PPINs) have been used for deciphering protein function, disease gene prioritization for the sake of drug discovery and drug repurposing. In a PPIN the highly connected nodes are referred to as "hubs" and they are associated with important biological functions. Deletion of some of the inter-modular hubs altered the topology of network. Identification and understanding of different topological aspects of highly interacting proteins in the PPIN would enable us in finding the most appropriate target during target prioritization for drug designing or repositioning with minimal side-effects.

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Comparing Drug Images and Repurposing Drugs with BioGPS and FLAPdock: The Thymidylate Synthase Case

July 12th 2016, Posted by: Drug Repurposing Portal

Repurposing and repositioning drugs has become a frequently pursued and successful strategy in the current era, as new chemical entities are increasingly difficult to find and get approved. Herein Siragusa et al has reported an integrated BioGPS/FLAPdock pipeline for rapid and effective off-target identification and drug repurposing. They used human thymidylate synthase (TS) as a test case and searched the entire RCSB Protein Data Bank (PDB) for similar target pockets. They chose casein kinase II alpha as a control and tested a series of its inhibitors against the TS template. Ellagic acid and apigenin were identified as TS inhibitors, and various flavonoids were selected and synthesized in a second-round selection. The compounds were demonstrated to be active in the low-micromolar range.

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Web-Based Data Tool Designed to Enhance Drug Safety

July 9th 2016, Posted by: Drug Repurposing Portal

Scientists at Cincinnati Children's Hospital Medical Center have developed a database called AERSMine to find, combine and analyze the growing volume of drug information stored in the U.S. Food and Drug Administration's Adverse Reporting System (FAERS). When the authors studied the use of NSAIDs for arthritis, chronic pain, etc., they were able to see differential rates of adverse clinical events depending on if people used propionic acid derivatives (like ibuprofen) or so-called cox-2 inhibitors known as coxibs, and patient groups for whom the risks of NSAID adverse events are much lower than others (for example patients with chronic arthritis). The database has the potential to help reduce negative side effects from prescription drugs and identify opportunities to reposition existing drugs for new uses.

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Web-based Data Tool Designed to Enhance Drug Safety

July 8th 2016, Posted by: Drug Repurposing Portal

Scientists in the Division of Biomedical Informatics and the Clinical and Translational Sciences Program at Cincinnati Children's Hospital Medical Center have developed a new online open-access database and it has the potential to help reduce negative side effects from prescription drugs and identify opportunities to reposition existing drugs for new uses. The database is called AERSMine has the ability to use knowledge frameworks - ontologies -to form the groupings of patients, medications, and outcomes and gain what we believe is an unprecedented power to explore and identify both unexpectedly negative and positive drug effects. Doing this has the potential to uncover new uses for drugs and drug regimen combinations.

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Leveraging 3D Chemical Similarity, Target and Phenotypic Data in the Identification of Drug-Protein and Drug-Adverse Effect Associations

July 1st 2016, Posted by: Drug Repurposing Portal

Target identification for drugs is crucial to discover many novel applications for existing drugs. It would help us in providing more insights about biological action and also adverse drug effects. Using computational methods authors has integrated 3D chemical similarity, target and adverse effect data to generate drug-target-adverse effect predictor. This particular model has wide applications in drug repurposing strategy, which would be helpful in predicting the drug safety.

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Teaching an Old Drug New Tricks to Fight Cytomegalovirus

June 30th 2016, Posted by: Drug Repurposing Portal

Researchers at Johns Hopkins have found that an old drug once mostly used to treat amebiasis -- a disease caused by a parasite -- and induce vomiting in cases of poisoning appears to also halt replication of cytomegalovirus (CMV), a herpesvirus that can cause serious disease in immunocompromised individuals, including those with HIV or organ transplant recipients. A report on the finding, made in test tube and mice studies, is published in the June 23 PLOS Pathogens and could potentially offer a much-needed tool to inhibit CMV, the investigators say.

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Soluble Aspirin May Be Able To Cross Blood Brain Barrier to Attack Glioblastomas

June 29th 2016, Posted by: Drug Repurposing Portal

Research team at the Brain Tumor Research Centre of Excellence at the University of Portsmouth, has demonstrated that a reformulation of aspirin to a truly soluble form allows it to enter the brain so that it can target the tumor cells. Aspirin existing preparations cannot readily enter the brain because the drug is a suspension rather than being completely soluble. Truly soluble form of aspirin when combined with two other compounds, the drug enters the brain and can therefore target the tumor cells. Brain Tumor Research is promoting the development of a programme for the screening of some current drugs to identify potential new therapies which will be effective but safe and bring us closer to developing a cure for brain tumors.

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Shape-Changing Enzyme Suggests how Small Doses of Anti-HIV Drug might treat Alzheimers

June 28th 2016, Posted by: Drug Repurposing Portal

According to National Institute of Standards of Technology (NIST) researchers, an approved anti-HIV drug, Efavirenz latches to the enzyme already responsible for about 80 percent of the cholesterol elimination from the human brain. The NIST team used HDX (hydrogen-deuterium exchange) to compare and contrast CYP46A1 in four different states: alone, with cholesterol only, with Efavirenz only, and with cholesterol and Efavirenz. Analyses of NIST's HDX data and follow on experiments helped to explain why, in studies of mice, tiny doses of Efavirenz ramped up CYP46A1's cholesterol removal capability. Efavirenz is focused as part of strategy to "repurpose" already approved drugs.

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Inflammatory Pathway Network-Based Drug Repositioning and Molecular Phenomics

June 27th 2016, Posted by: Drug Repurposing Portal

In a collaborative effort by the University of Auckland and Peking University, scientists constructed the pathway network of inflammation and adopted network efficiency and network flux to evaluate drug efficacy. By using approved and experimentally validated anti-inflammatory drugs as training sets, a predictive model was built to screen potential anti-inflammatory drugs from approved drugs in DrugBank. It's also an effective approach for drug repositioning and ten potential anti-inflammatory drugs were identified. Moreover, molecular phenomics was proposed to describe the phenotypic correlation and drug mechanism of action. This work provides a novel insight into pathway network-based drug repositioning and promotes molecular phenomics as a tool for drug discovery.

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Drug Repositioning Approaches to Parasitic Diseases: A Medicinal Chemistry Perspective

June 21st 2016, Posted by: Drug Repurposing Portal

Neglected Tropical Diseases (NTDs), mostly caused by parasitic organisms, affecting nearly billion people in developing and underdeveloped countries. The impact caused by these diseases could lead to irreversible injuries and premature deaths. Considering the severity of these diseases, the authors (Leonardo G. Ferreira et al.,) from Brazil has reviewed the applications of drug re-positioning strategy in discovery of novel small molecules for some parasitic diseases.

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Using Social Media Data to Identify Potential Candidates for Drug Repurposing: A Feasibility Study

June 16th 2016, Posted by: Drug Repurposing Portal

Patients today report their experiences with medications on social media and reveal side effects as well as beneficial effects of those medications. Aim was to assess the feasibility of using patient reviews from social media to identify potential candidates for drug repurposing using patient reviews of medications from an online forum, WebMD. Using dictionary-based and machine learning approaches & several publicly available resources, preliminary study shows that social media has the potential to be used in drug repurposing.

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Deep Learning system for Drug Discovery to be Presented at the Machine Intelligence Summit in Berlin

June 14th 2016, Posted by: Drug Repurposing Portal

Following the publication of the first proof of concept of predicting the functional properties of drugs by their transcriptional response signature, scientists at Insilico Medicine developed a multimodal input drug discovery engine capable of predicting therapeutic use, toxicity and adverse effects of thousands of molecules. Several of these advances will be presented at the Re-Work Machine Intelligence Summit Berlin, June 29-30.

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New Tool Brings Personalized Medicine Closer

June 13th 2016, Posted by: Drug Repurposing Portal

Scientists from EPFL and ETHZ have developed a powerful tool for exploring and determining the inherent biological differences between individuals, which overcomes a major hurdle for personalized medicine. Johan Auwerx at EPFL and Ruedi Aebersold at ETH Zurich looked at 40 different mice strains and successfully connected the variation between individuals' genomes to the variation between their proteomes -- their full set of proteins. In this way, they took a giant leap in profiling the biology of a particular individual. The aim here is to be able to customise medical intervention for each patient based on their individual biological makeup.

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In silico Methods for Drug Repurposing and Pharmacology

May 31st 2016, Posted by: Drug Repurposing Portal

One exciting application of computational pharmacology is drug repurposing-finding new uses for existing drugs. Already yielding many promising candidates, this strategy has the potential to improve the efficiency of the drug development process and reach patient populations with previously unmet needs such as those with rare diseases. While current techniques in computational pharmacology and drug repurposing often focus on just a single data modality such as gene expression or drug-target interactions, we argue that methods such as matrix factorization that can integrate data within and across diverse data types have the potential to improve predictive performance and provide a fuller picture of a drug's pharmacological action.

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A Computational Drug Repositioning Approach for Targeting Oncogenic Transcription Factors

May 31st 2016, Posted by: Drug Repurposing Portal

Transcription factors (TFs) are frequently mutated in cancer. TFs are often considered undruggable due to the absence of targetable enzymatic activity. CRAFTT is a computational drug-repositioning approach for targeting TFs. CRAFTT combines ChIP-seq with drug-induced expression profiling to identify small molecules that can specifically perturb TF activity. CRAFTT predicted that dexamethasone would inhibit ERG activity. Furthermore, analysis of electronic medical record data indicates a protective role for dexamethasone against prostate cancer.

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Cogena, a Novel tool for Co-expressed Gene-Set Enrichment Analysis, Applied to Drug Repositioning and Drug mode of action Discovery

May 27th 2016, Posted by: Drug Repurposing Portal

Jia and colleagues used a novel framework, co-expressed gene-set enrichment analysis (cogena) for analysis of gene expression signatures and gene set enrichment. The cogena framework enables simultaneous, pathway driven, disease and drug repositioning analysis. Cogena can be used to analyze coordinated changes within disease transcriptomes and identify drugs acting mechanistically within this framework.

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An Integrated Data Driven Approach to Drug Repositioning Using Gene-Disease Associations

May 23rd 2016, Posted by: Drug Repurposing Portal

Drug development is both increasing in cost whilst decreasing in productivity. There is a general acceptance that the current paradigm of R&D needs to change. One alternative approach is drug repositioning. With target-based approaches utilised heavily in the field of drug discovery, it becomes increasingly necessary to have a systematic method to rank gene-disease associations. Although methods already exist to collect, integrate and score these associations, they are often not a reliable reflection of expert knowledge. Furthermore, the amount of data available in all areas covered by bioinformatics is increasing dramatically year on year. It thus makes sense to move away from more generalised hypothesis driven approaches to research to one that allows data to generate their own hypothesis. We introduce an integrated, data driven approach to drug repositioning. We first apply a Bayesian statistics approach to rank 309,885 gene-disease associations using existing knowledge. Ranked associations are then integrated with other biological data to produce a semantically-rich drug discovery network. Using this network, we show how our approach identifies diseases of the central nervous system (CNS) to be an area of interest. CNS disorders are identified due to the low numbers of such disorders that currently have marketed treatments, in comparison to other therapeutic areas. We then systematically mine our network for semantic subgraphs that allow us to infer drug-disease relations that are not captured in the network. We identify and rank 275,934 drug-disease has_indication associations after filtering those that are more likely to be side effects, whilst commenting on the top ranked associations in more detail. The dataset has been created in Neo4j and is available for download at https://bitbucket.org/ncl-intbio/genediseaserepositioning along with a Java implementation of the searching algorithm.

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DNetDB: The Human Disease Network Database based on Dysfunctional Regulation Mechanism

May 22nd 2016, Posted by: Drug Repurposing Portal

Researchers at Shanghai Center for Bioinformation Technology and Chinese Academy of Sciences, Shanghai, have developed DNetDB, a human disease network database. DNetDB is the first database focusing on disease similarity from the viewpoint of gene regulation mechanism. In total, 1,326 disease relationships among 108 diseases, 5,598 pathways, 7,357 disease-related genes and 342 disease drugs are recorded in DNetDB, among which 3,762 genes and 148 drugs are shared by at least two diseases. It provides an easy-to-use web interface to search and browse the disease relationships and thus helps to systematically investigate etiology and pathogenesis, perform drug repositioning, and design novel therapeutic interventions.

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Deep Learning Applications for Predicting Pharmacological Properties of Drugs and Drug Repurposing using Transcriptomic Data

May 20th 2016, Posted by: Drug Repurposing Portal

Scientists at InSilico Medicine Inc., have demonstrated a deep learning neural net trained on transcriptomic data to recognize pharmacological properties of multiple drugs across different biological systems and conditions. They used the perturbation samples of 678 drugs across A549, MCF-7 and PC-3 cell lines from the LINCS project and linked those to 12 therapeutic use categories derived from MeSH. They have also proposed using deep neural net confusion matrices for drug repositioning. This work is a proof of principle for applying deep learning to drug discovery and development.

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"RE:fine drugs": An Interactive Dashboard to Access Drug Repurposing Opportunities

May 18th 2016, Posted by: Drug Repurposing Portal

Scientists at The Research Institute at Nationwide Children's Hospital Columbus and The Ohio State University, have developed "RE:fine Drugs", a freely available interactive website for integrated search and discovery of drug repurposing candidates from GWAS and PheWAS repurposing datasets constructed using previously reported methods in Nature Biotechnology. The group led by Simon Lin, demonstrate the possibilities to identify and prioritize novelty of candidates for drug repurposing based on the theory of transitive Drug-Gene-Disease triads. It currently contains 60,911 opportunities covering 916 drugs, 567 genes and 1770 diseases.

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Learning Disease Relationships from Clinical Drug Trials

May 17th 2016, Posted by: Drug Repurposing Portal

Scientists at MIT have devised a unique deep learning method from clinical trial metadata, which exploits latent scientific, clinical, and regulatory expert knowledge to draw conclusions about the underlying biology of diseases. The Disease-Disease Network constructed using this method, shows surprising agreement with another the Human Disease Network based on genetic data and on the Medical Subject Headings (MeSH) taxonomy, yet it also contains unique disease similarities. The disease relationships unique to this network may be used to generate hypotheses for future biological and clinical research as well as drug repurposing and design. This provides an example of using experimental data on humans to generate biologically useful information and point to a set of new and promising strategies to link clinical outcomes data back to biological research.

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DrugGenEx-Net: A Novel Computational platform for Systems Pharmacology and Gene Expression-based Drug Repurposing

May 5th 2016, Posted by: Drug Repurposing Portal

DGE-NET is a novel computational method, built by scientists at Georgetown Universty that predicts drug therapeutic and counter-therapeutic indications by uniquely integrating systems pharmacology with gene expression analysis. DGE-NET correctly predicts various drug-disease indications by linking the biological activity of drugs and diseases at multiple tiers of biological action, and is therefore a useful approach to identifying drug candidates for re-purposing. DGE-NET predicted the angiotensin receptor blocker (ARB) irbesartan as potential therapy for IBD. It also predicted the drugs topotecan and mebendazole for repurposing to rheumatoid arthritis. Topotecan is a DNA topoisomerase 1 (Top1) inhibitor used for NSCLC cancer and Mebendazole is an anti-hookworm tubulin inhibitor with anti-cancer potential through mammalian crossover tubulin and kinase inhibition.

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Drug Repositioning based on Comprehensive Similarity Measures and Bi-Random walk Algorithm

May 5th 2016, Posted by: Drug Repurposing Portal

In this article, based on the assumption that similar drugs are normally associated with similar diseases and vice versa, Authors have propose a novel computational method named MBiRW, which utilizes some comprehensive similarity measures and Bi-Random walk (BiRW) algorithm to identify potential novel indications for a given drug.

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QUADrATiC: scalable gene expression connectivity mapping for repurposing FDA-approved therapeutics.

May 4th 2016, Posted by: Drug Repurposing Portal

A new online tool for re-purposing focused studies of FDA approved small molecules. It incorporates gene expression data and its computational architecture facilitates dynamic resource scalability depending on the system in which it is installed. Other advantages include improved visualization.

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Screening Method Uncovers Drugs that may combat deadly Antibiotic-Resistant Bacteria

April 29th 2016, Posted by: Drug Repurposing Portal

Investigators at Beth Israel Deaconess Medical Center (BIDMC) have developed a promising method of identifying new antimicrobials that target antibiotic-resistant bacteria carbapenem resistant Enterobacteriaceae (CRE). To identify new or existing drugs that can destroy multidrug resistant CRE, scientists examined approximately 10,000 compounds including most previously FDA approved drugs, veterinary drugs and inhibitors of various cellular processes not currently used as therapeutics. Through high throughput screening 79 compounds were found to inhibit CRE. Of these, 3 had already been approved for human and veterinary use: azidothymidine, spectinomycin and apramycin. Recent findings suggest they could potentially be repurposed for CRE treatment. Apramycin and spectinomycin are of particular interest because they have minimal side effects, making them potentially ideal new therapeutic options for CRE infection.

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Opportunities for Web-based Drug Repositioning: Searching for Potential Antihypertensive Agents with Hypotension Adverse Events

April 1st 2016, Posted by: Drug Repurposing Portal

The electronic records of the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) were searched systematically, through the openFDA platform to assess the association between hypotension incidence and antihypertensive therapeutic effect. Statistical analysis of FAERS data demonstrated that those drugs frequently co-occurring with hypotension events were more likely to have antihypertensive activity. More important, study showed that a pharmacovigilance system could alternatively be used to identify antihypertensive agents and sustainably create opportunities for drug repositioning.

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A Network-based Drug Repositioning Infrastructure for Precision Cancer Medicine through Targeting Significantly Mutated Genes in the Human Cancer Genomes

March 28th 2016, Posted by: Drug Repurposing Portal

Scientists at Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, proposed an integrative network-based infrastructure to identify new druggable targets and anticancer indications for existing drugs through targeting significantly mutated genes (SMGs) discovered in the human cancer genomes. They used integrative analysis to showcase a potential mechanism-of-action for resveratrol in breast and lung cancer treatment whereby it targets several SMGs (ARNTL, ASPM, CTTN, EIF4G1, FOXP1, and STIP1).

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Exploring polypharmacology in Drug Discovery and Repurposing using the CANDO Platform

March 25th 2016, Posted by: Drug Repurposing Portal

Scientists at Purdue University, developed the Computational Analysis of Novel Drug Opportunities (CANDO) platform based on a hypothesis that drugs function by interacting with multiple protein targets to create a molecular interaction signature that can be exploited for therapeutic repurposing and discovery. They have then used the CANDO platform to analyse and determine the contribution of multitargeting (polypharmacology) to drug repurposing benchmarking accuracy. Their results indicate that a large number of protein structures with diverse fold space and a specific polypharmacological interactome is necessary for accurate drug predictions using their proteomic and evolutionary drug discovery and repurposing platform.

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Drug Repositioning for Cancer Therapy Based on Large-Scale Drug-Induced Transcriptional Signatures

March 8th 2016, Posted by: Drug Repurposing Portal

An in-silico chemical genomics approach has been developed by scientists at Ewha Research Center for Systems Biology, Division of Molecular & Life Sciences, Ewha Womans University, Seoul, Korea, to predict drug repositioning (DR) candidates for three types of cancer: glioblastoma, lung cancer, and breast cancer. It is based on a recent large-scale dataset of ~20,000 drug-induced expression profiles in multiple cancer cell lines, publicly released by the NIH LINCS program (Library of Integrated Network-based Cellular Signatures). They predicted 14 high-scoring DR candidates solely based on expression signatures. Eight of the fourteen drugs showed significant anti-proliferative activity against glioblastoma; i.e., ivermectin, trifluridine, astemizole, amlodipine, maprotiline, apomorphine, mometasone, and nortriptyline. The DR score strongly correlated with that of cell-based experimental results; the top seven DR candidates were positive, corresponding to an approximately 20-fold enrichment compared with conventional HTS. The LINCS dataset also enabled them to interpret the mode of action of the validated DR candidates.

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Prediction of Candidate Drugs for Treating Pancreatic Cancer by Using a Combined Approach

March 3rd 2016, Posted by: Drug Repurposing Portal

They first identified the potentially useful drugs (PUDs) for pancreatic cancer by using C-Map-based gene expression correlation analyses and then applied an algorithm (Met-express) to predict key pancreatic cancer (KPC) enzymes involved in pancreatic cancer metabolism. Using this combined approach, they shortlisted seven candidate drugs for treating pancreatic cancer, three of which are supported by literature evidence, and three were experimentally validated to be inhibitory to pancreatic cancer cell lines.

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Computational Drug Repositioning Based on Side-Effects Mined from Social Media

February 24th 2016, Posted by: Drug Repurposing Portal

Drug repositioning methods attempt to identify novel therapeutic indications for marketed drugs. Drugs with similar side-effects might share a common mechanism of action linking side-effects with disease treatment, or may serve as a treatment by ?rescuing? a disease phenotype on the basis of their side-effects; therefore it may be possible to infer new indications based on the similarity of side-effect profiles. In this they described a novel computational method that uses side-effect data mined from social media to generate a sparse undirected graphical model.

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ksRepo: A Generalized Platform for Computational Drug Repositioning

February 9th 2016, Posted by: Drug Repurposing Portal

Scientists at the Harvard medical centre, dept. of medical bioinformatics have developed ksRepo, a platform which enables investigators to use any data inputs for computational drug repositioning. ksRepo is implemented in a series of four functions in the R statistical environment under a BSD3 license.

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Repurposing Metformin as a Precision Anti-Cancer Therapy Using Structural Systems Pharmacology

February 4th 2016, Posted by: Drug Repurposing Portal

A recent study described a novel structural systems pharmacology approach to elucidate metformin's molecular basis and genetic biomarkers of action. In this method, structural genomic, functional genomics, and interactomic data was integrated to identify putative metformin binding targets and their interaction models. Network biomarkers of phenotypic response of metformin was generated by linking the putative binding targets to genes that do not directly bind to metformin but whose expressions are altered by metformin through protein-protein interactions. Finally, this network was used to correlate drug target interactions with drug response phenotypes under diverse genetic backgrounds. This study sheds new light into repurposing metformin for safe, effective, personalized therapies and suggests that structural systems pharmacology could be a powerful tool for precision medicine.

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Patient-Specific Data Fusion for Cancer Stratifications and Personalized Treatment

January 8th 2016, Posted by: Drug Repurposing Portal

Recently published study described a versatile data integration framework that can effectively integrate somatic mutation data, molecular interactions and drug chemical data to address three key challenges in cancer research: stratification of patients into groups having different clinical outcomes, prediction of driver genes whose mutations trigger the onset and development of cancers, and repurposing of drugs treating particular cancer patient groups. This framework is based on graph-regularized non-negative matrix tri-factorization, a machine learning technique for co-clustering heterogeneous datasets. Using this approach, the authors have identified potential candidate drugs for repurposing that could be used in treatment of the identified patient subgroups of ovarian cancer by targeting their mutated gene products.

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A Multilayer Network Approach for Guiding Drug Repositioning in Neglected Diseases

January 6th 2016, Posted by: Drug Repurposing Portal

A recent study developed a novel integrative network by using the data from extensively studied organisms like human, mouse, E.coli and yeast etc. Several functional relations were modeled among 1.67X105 proteins. These relations comprised of orthology, sharing of protein domains, and shared participation in defined biochemical pathways. Based on the information available in the graph for known compound-target associations, this network model can be used to prioritize and identify potential candidate drug targets in neglected pathogen proteomes and bioactive drug-like molecules to foster drug development against neglected disease. This approach provides a mean to leverage data from other, more studied organisms to guide drug repositioning exercises for neglected diseases that usually lack experimental, high-volume, chemogenomic datasets.

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Drug Repurposing for the Development of Novel Analgesics

December 17th 2015, Posted by: Drug Repurposing Portal

Recent finding suggested a role for several existing drugs, such as minocycline, ceftriaxone, sivelestat, and pioglitazone, as novel analgesics in chronic and neuropathic pain states. In this article, a group of German scientists has discussed these findings as well as their proposed antihyperalgesic mechanisms. The article further outlines the merits of pathway-based repurposing screens, in combination with bioinformatics and novel cellular reprogramming techniques, for the identification of novel analgesics.

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Drug Signature-based Finding of Additional Clinical Use of LC28-0126 for Neutrophilic Bronchial Asthma

December 7th 2015, Posted by: Drug Repurposing Portal

LC28-0126 is an investigational drug for acute myocardial infarction (MI) at undergoing clinical trials. A study using connectivity map conducted at research Institute of National University Hospital, Jeonju, Korea, showed top-ranked connection of LC28-0126 with dyphilline, an FDA-approved drug for bronchial asthma. Trials with LC28-0126 have demonstrated the ability of effectively ameliorating the pathophysiology of neutrophilic bronchial asthma in OVALPS-OVA mice suggesting that LC28-0126 could be repurposed bronchial asthma. In addition, this study demonstrated the potential general utility of computational drug repositioning using clinical profiles of the investigational drug.

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A Computational Method for Drug Repositioning based on Publicly Available Gene Expression Data.

December 7th 2015, Posted by: Drug Repurposing Portal

Many computational methods are available to process publicly available transcriptional data for successful drug repositioning. In the current work, authors have applied data mining on gene expression data. The outcome of this study led them to identify 3 compounds for the possible treatment of cancers.

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PDID: Database of Molecular-level Putative Protein-Drug Interactions in the Structural Human Proteome

October 26th 2015, Posted by: Drug Repurposing Portal

Putative protein drug interactions data help in repurposing Drugs. PDID (Protein-Drug Interaction Database) provides access to putative protein-drug interactions that cover the entire structural human proteome. Many drugs interact with numerous proteins besides their intended therapeutic targets.

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Zebrafish Drug-Repurposing Screen reveals sGC-Dependent and sGC-Independent Pro-Inflammatory Activities of Nitric Oxide

October 7th 2015, Posted by: Drug Repurposing Portal

Wittmann et al from Karlsruhe Institute of Technology (KIT) under the FP7 grant developed a multi-parametric zebrafish screen to repurpose FDA approved drug library for use in anti-inflammatory indications. The study successfully outlined 63 potent compounds that exhibited immuno-modulatory characteristics which were used for other indications earlier.

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Repurposing Registered Drugs as Antagonists for Protease-Activated Receptor 2

October 7th 2015, Posted by: Drug Repurposing Portal

A group of scientists from The University of Queensland, Brisbane, Queensland, Australia have identified new target, Protease-Activated Receptor 2 (PAR2), for old drugs Carvedilol, Loratadine, Nefazodone and Astemizole and identified these drugs are PAR2 antagonists. Virtual screening of a drug database after ligand docking and molecular dynamics simulations using a PAR2 homology model and a putative binding mode of a known PAR2 ligand demonstrated competitive binding and antagonism of PAR2 by these old drugs.

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A Practical Guide for Exploring Opportunities of Repurposing Drugs for CNS Diseases in Systems Biology

October 5th 2015, Posted by: Drug Repurposing Portal

Informatics and Structure Biology section of GlaxoSmithKline at China, has come up with a Multiple Level Network Modeling (MLNM) example to illustrate the great potential of systems biology for CNS diseases. The system focuses on the benefit and practical applications in pathway centric therapy and drug repositioning.

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An Integrated Structure- And System-Based Framework To Identify New Targets Of Metabolites And Known Drugs

August 18th 2015, Posted by: Drug Repurposing Portal

A team of scientists from King Abdullah University of Science and Technology, Thuwal, Saudi Arabia, used a novel integrated structure- and system-based approach of drug-target prediction (iDTP) to identify new targets for known drugs for the purpose of drug repositioning. For a given drug, using sequence order-independent structure alignment, hierarchical clustering, and probabilistic sequence similarity to construct a probabilistic pocket ensemble (PPE), scientists identified the genetic diseases associated with the predicted target proteins for each drug.

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Dsviadrm: An R Package For Estimating Disease Similarity Via Dysfunctional Regulation Mechanism

August 13th 2015, Posted by: Drug Repurposing Portal

An R package 'DSviaDRM' to identify significant Disease similarity (DS) via dysfunctional regulation mechanism (DRM) based on transcriptomic data contains five easy-to-use functions, DCEA, DCpathway, DS, comDCGL and comDCGLplot. This can be applied for identifying disease relationships and showing common differential regulation information shared by similar diseases. Elucidation of human disease similarities will provide new insights into etiology, disease classification and drug repositioning.

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Anti-Aging Researchers Develop New Algorithm That Provides Precision Medicine For Cancer Patients

August 7th 2015, Posted by: Drug Repurposing Portal

The Johns Hopkins Based Bioinformatics firm in-silico Medicine has developed an algorithm that detects activation of intracellular regulatory pathways in the tumor in comparison to the corresponding normal tissues. It then predicts whether the drug can prevent cancer growth and survival in each individual case by blocking the abnormal, tumor promoting pathways. In-silico Medicine is a Baltimore-based company utilizing advances in genomics and big data analysis for in-silico drug discovery and drug repurposing for aging and age-related.

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Integrating Data Into A Heterogeneous Network For Drug Repurposing

August 6th 2015, Posted by: Drug Repurposing Portal

Daniel Himmelstein is a PhD candidate in the Biological & Medical Informatics program at UCSF, created a heterogeneous network for drug repurposing. The network consists of 10 types of nodes (metanodes) and 27 types of edges (metaedges). It contains 49,427 nodes and 5,998,711 edges (2,977,167 of which are unbiased). This repository creates heterogeneous network for repurposing drug. The underlying databases are processed elsewhere but integrated here.

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Chemoinformatics Approach Used To Repurpose HDAC Inhibitors

August 3rd 2015, Posted by: Drug Repurposing Portal

Studies by Zhao et al., shows that with the use of cheminformatics method particularly structure activity relationship and exploiting privileged structures for scaffold refining, from medicinal chemistry perspective is a very good method for lead discovery. This method is applied in the discovery of anti-HCV therapies where hydroxamic acid-based privileged structures with cancer-associated HDAC inhibitory mechanisms have been refined.

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Repurposevs: An Efficient And Powerful In Silico Tool To Predict Drug-Target Associations In Drug Repurposing

August 3rd 2015, Posted by: Drug Repurposing Portal

RepurposeVS is a virtual screening method that incorporates docking, drug-centric and protein-centric 2D/3D fingerprints with a rigorous mathematical normalization procedure to account for the variability in units and provide high-resolution contextual information for drug-target binding. Benchmarking was conducted on a set of 3,671 FDA approved and experimental drugs rather than the Database of Useful Decoys (DUD-E) so as to streamline downstream repurposing experiments.

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Using Gene Expression Signatures To Identify Novel Treatment Strategies In Gulf War Illness

July 21st 2015, Posted by: Drug Repurposing Portal

Gulf War Illness (GWI) is a complex multi-symptom disorder that affects up to one in three veterans of this 1991 conflict and for which no effective treatment has been found. Discovering novel treatment strategies for such a complex chronic illness is extremely expensive, carries a high probability of failure and a lengthy cycle time. Here, in this article drug re-purposing opportunities in GWI were explored by combining systems biology and bioinformatics techniques with pharmacogenomic information to find overlapping elements in gene expression linking GWI to successfully treated diseases. Gene modules were defined based on cellular function and their activation estimated from the differential expression of each module's constituent genes.

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Large-Scale Direct Targeting For Drug Repositioning And Discovery

July 9th 2015, Posted by: Drug Repurposing Portal

A novel algorithm termed weighted ensemble similarity (WES) has been developed by Wang et. al at Bioinformatics Center, Northwest A&F University, Shaanxi, China, to identify drug direct targets based on a large-scale of 98,327 drug-target relationships. WES is able to predict drug direct targets with external and experimental test accuracies of 70% and 71%, respectively. This shows that the WES method provides a potential in-silico model for drug repositioning and discovery.

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Identification Of Binding Site Similarities Through Molecular Interaction Field Based Approach

July 9th 2015, Posted by: Drug Repurposing Portal

A new method for the classification of protein binding site similarity is proposed. Isomorphism Molecular Interaction Fields (IsoMIF) utilizes 6 chemical probes and the detection of sub-graph isomorphisms to identify geometrically and chemically equivalent sections of protein cavity pairs. IsoMIF may be used to detect potential cross-reactivity or polypharmacology targets for Drug Repurposing.

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Targeting The Schizophrenia Genome: A Repositioning Strategy From Gwas To Clinic

July 1st 2015, Posted by: Drug Repurposing Portal

To reposition drugs to new targets, all the genes within loci implicated by the Psychiatric Genomics Consortium Schizophrenia Workgroup GWAS were compared against databases of targets of both approved and registered pharmaceutical compounds. 20 potential schizophrenia susceptibility genes that encode proteins that are the targets of approved drugs were identified for repositioning. An additional 20 genes coding for proteins that are the targets of drugs in registered clinical trials, but without approved indications, were also identified for repurposing.

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Network Analysis Of Hypnotherapy-Induced Regressing Tumors Identifies Novel Synergistic Drug Combinations

June 24th 2015, Posted by: Drug Repurposing Portal

Scientists at The University of Western Australia, led by Lesterhuis et al. have devised an approach by which to visualize the effector response in the tumor as a complex network of interacting gene products and by mapping this network have proposed to effectively predict pharmacological interventions. They claim that their approach provides a powerful platform to repurpose drugs, and define contextually relevant novel therapeutic targets and have used a drug repurposing approach to the response-associated network data. This resulted in the identification of pleiotropic drugs that improved the response rate to the backbone therapy, anti-CTLA4 in a murine mesothelioma model. One of the repurposed drugs that was identified in this manner, meticrane, has not been associated with any anti-tumor or pro-immune effect and could not have been predicted to work in synergy with anti-CTLA4 otherwise.

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Drug Repurposing: Use Of Connectivity Map For Identification Of New Small Molecules For Treating Acute Myeloid Leukemia

June 23rd 2015, Posted by: Drug Repurposing Portal

In acute myeloid leukemia (AML) cells the transcription factor C/EBP? is frequently inactivated. By interrogation of the Connectivity Map database, biological effects of candidate C/EBP?-mimetics was identified and amantadine, an antiviral and anti-Parkinson agent, has been identified as a potential therapeutic agent for treating AML as it induced a monocyte-macrophage-like differentiation of HL60, U937, Kasumi-1 myeloid leukemia cell lines, proving once again that CMAP could serve as a very useful approach in drug repurposing.

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DT-Web: a web-based Application for Drug-Target Interaction and Drug Combination Prediction

June 1st 2015, Posted by: Drug Repurposing Portal

DT-Web a software resource accessible via web uses known sources, such as DrugBank and PathwayCommons, in connection with Drug Target-Hybrid recommendation algorithm. It predicts new targets with the corresponding p-values expressing the reliability of each group of predictions. It is also possible to specify a list of genes tracking down all the drugs that may have an indirect influence on them based on a multi-drug, multi-target, multi-pathway analysis.

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Drug Repositioning for Diabetes Based on 'Omics' Data Mining

May 6th 2015, Posted by: Drug Repurposing Portal

Zhang et al. analyzed data from genome wide association studies, proteomics and metabolomics studies and revealed a total of 992 proteins as potential anti-diabetic targets in human. Drug information for these 992 proteins was retrieved from the Therapeutic Target Database (TTD) and 9 drugs were found to have the potential to treat diabetes. Among the 9 drugs, 4 drugs targeting COX2 were repurposed for treating type-1 diabetes, and 2 drugs targeting ADRA2A had a new indication for treating type 2 diabetes.

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NFFinder: an online Bioinformatics Tool for searching similar Transcriptomics Experiments in the context of Drug Repositioning

May 4th 2015, Posted by: Drug Repurposing Portal

NFFinder uses transcriptomic data to find relationships between drugs, diseases and a phenotype of interest, as well as identifying experts having published on that domain. The application shows in a dashboard a series of graphics and tables designed to help researchers formulate repositioning hypotheses and identify potential biological relationships between drugs and diseases.

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Drug repurposing and emerging adjunctive treatments for schizophrenia

April 12th 2015, Posted by: Drug Repurposing Portal

An overview of repurposed drugs and emerging treatments for schizophrenia is presented, focusing on randomized, controlled trials and meta-analyses.Given the current failure of a number of mechanistically new drugs, repurposed compounds may serve as alternative and/or adjunctive agents for schizophrenic patients and for treatment refractory patients in particular.

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Drug Repurposing: A Systematic Approach to Evaluate Candidate Oral Neuroprotective Interventions for Secondary Progressive Multiple Sclerosis

April 9th 2015, Posted by: Drug Repurposing Portal

Hanna M. Vesterinen and Peter Connick demonstrated a standardised and systematic approach to identify candidates for drug rescue and repurposing trials that can be applied widely to neurodegenerative disorders using progressive MS as an exemplar disease. After review of all clinical and preclinical evidences; ibudilast, riluzole, amiloride, pirfenidone, fluoxetine, oxcarbazepine, and the polyunsaturated fatty-acid class (Linoleic Acid, Lipoic acid; Omega-3 fatty acid, Max EPA oil) were identified as lead candidates for clinical evaluation from this approach .

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Opportunities for drug repositioning from phenome-wide association studies (PheWAS)

April 7th 2015, Posted by: Drug Repurposing Portal

Results from large scale phenome wide association studies (PheWAS) allows, association of a genetic variant with wide range of human disorders and have provided an immense knowledge on disease etiologies. Like GWAS now PheWAS can be used for drug repurposing. PheWAS is similar to GWAS, but PheWAS provides insight for what diseases are associated with a genetic variant.

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Integrative Approaches Key To Understanding Cancer And Developing Therapies

March 29th 2015, Posted by: Drug Repurposing Portal

Moffitt Cancer Center researchers are using integrative approaches to study cancer by combining mathematical and computational modeling with experimental and clinical data.

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Drug Repurposing, Rescue, and Repositioning

March 19th 2015, Posted by: Drug Repurposing Portal

Drug Repurposing, Rescue, and Repositioning Journal Volume 1, Issue 1 released. All Articles are belongs to Drug Repurposing area and open access.

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Cancer Based Pharmacogenomics Network (CPN) Supported With Scientific Evidences: From The View Of Drug Repurposing

February 25th 2015, Posted by: Drug Repurposing Portal

Using various data sources (PharmGKB, GWAS catalog, FDA Biomarkers, SemMedDB), Wang et al developed CPN, a comprehensive pharmacogenomics information that can be used in cancer oriented drug repurposing research.

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A miRNA-Driven Inference Model To Construct Potential Drug-Disease Associations For Drug Repositioning

February 19th 2015, Posted by: Drug Repurposing Portal

Increasing evidence discovered that the inappropriate expression of microRNAs (miRNAs) will lead to many kinds of complex diseases and drugs can regulate the expression level of miRNAs. Therefore human diseases may be treated by targeting some specific miRNAs with drugs, which provides a new perspective for drug repositioning.

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Computer Algorithm Picks Out The Drugs That Work

February 18th 2015, Posted by: Drug Repurposing Portal

Scientists at the Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB) conducted a ?proof-of-principle? with analgesic drugs based on its machine learning algorithm which recorded brain activity in participants who received drugs versus who received a placebo. With 70% accuracy, the team hopes to predict drugs that could possibly be effective from the ones that are less likely to work.

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Systematic Drug Repositioning For A Wide Range Of Diseases With Integrative Analyses Of Phenotypic And Molecular Data

February 2nd 2015, Posted by: Drug Repurposing Portal

Performed a comprehensive prediction of a drug disease association network consisting of 2349 drugs and 858 diseases and described biologically meaningful examples of newly predicted drug indications for several types of cancers and nonhereditary diseases.

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Drugnet: Network Based Drug Disease Prioritization By Integrating Heterogeneous Data

January 13th 2015, Posted by: Drug Repurposing Portal

This is a network based approach that combines drugs, proteins and diseases. An attempt at automating what we do, albeit with a more sophisticated algorithm ProphNet.

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Homopharma: A New Concept For Exploring The Molecular Binding Mechanisms And Drug Repurposing

December 8th 2014, Posted by: Drug Repurposing Portal

Drugs that simultaneously target multiple proteins often improve efficacy, particularly in the treatment of complex diseases such as cancers and central nervous system disorders. Many approaches have been proposed to identify the potential targets of a drug. Recently, we have introduced Space-Related Pharmamotif (SRPmotif) method to recognize the proteins that share similar binding environments. In addition, compounds with similar topology may bind to similar proteins and have similar protein-compound interactions. However, few studies have focused on exploring the relationships between binding environments and protein-compound interactions, which is important for understanding molecular binding mechanisms and helpful to be used in discovering drug repurposing.

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Illuminating The Interactome

November 24th 2014, Posted by: Drug Repurposing Portal

Connecting genotype to phenotype will require a comprehensive view of how the protein products of genes operate and interact. Researchers at the Dana-Farber Cancer Institute s Center for Cancer Systems Biology and their colleagues have produced a new human interactome map, reported today (November 20) in Cell. The map is based on a systematic screen of 13,000 human proteins that uncovered 14,000 pairwise interactions.

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Computational Linguistics And Graph Theory May Expedite Drug Repurposing For Rare Diseases

November 21st 2014, Posted by: Drug Repurposing Portal

A recent study by Gramatica et al. (2014) report an alternative approach, using computational linguistics and graph theory to identify previously unknown links between drugs and diseases.Gramatica et al. analysed three million publication abstracts relating to 300 rare diseases from the PubMed literature database. Analysing the language in the abstracts allowed the researchers to build visual networks linking different types of node, such as disease, protein, biological process, or drug. To show how these networks were built, the researchers used an example from a paper describing the pathogenesis of lymphangioleimyomatosis (LAM).Each sentence was analysed independently, the nodes highlighted, and arranged into a network with each node linked pairwise.By arranging the results of a large number of studies in this case three million into a single network, links between drugs and diseases that were not previously recognized can be identified. Pathways with fewer steps linking a drug and a disease, and where multiple different pathways linked a drug and a disease, were considered to be particularly plausible candidates for drug repurposing.

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Caepidr: A Computational Approach To Efficient Peptide Influenced Drug Repurposing

October 31st 2014, Posted by: Drug Repurposing Portal

A Computational Approach to Efficient Peptide Influenced Drug Repurposing (CAEPIDR) has been developed to explore the conformational ligand binding space of the alpha3beta2 nicotinic acetylcholine receptor (nAChR) isoform and use the results to identify small molecule drugs that target the receptor. CAEPIDR has been integrated with the DockoMatic suite to create DockoMatic 2.1, which can be used to create virtual peptide analog libraries, virtually dock ligands to macromolecular receptors, and identify small molecule drugs for disease treatment. A utility was also created to search the PubChem Compound database for small molecule drugs with a 3-D shape similar to the highest affinity peptides from the virtual screen.

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A Network-Based Classification Model For Deriving Novel Drug-Disease Associations And Assessing Their Molecular Actions

October 30th 2014, Posted by: Drug Repurposing Portal

The growing number and variety of genetic network datasets increases the feasibility of understanding how drugs and diseases are associated at the molecular level. Properly selected features of the network representations of existing drug-disease associations can be used to infer novel indications of existing drugs. To find new drug-disease association, an integrative genetic network was generated using combinations of interactions, including protein-protein interactions and gene regulatory network datasets.

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Anti-Infectious Drug Repurposing Using An Integrated Chemical Genomics And Structural Systems Biology Approach

October 30th 2014, Posted by: Drug Repurposing Portal

Drug repurposing is a new hope for developing anti-infectious therapies. Genome scale based drug-target interaction networks are constructed to identify novel significant targets for the given chemical entity. A new methodology, Ligand Enrichment of Topological Similarity (ligENTS)is used to detect novel drug-target associations. ligENTS integrates graph mining algorithms and Random set theory. ligENTS identified nine top ranked drugs and their respective targets that have potential to treat malaria. ligENTS drugs opens new doors to next generation of chemical genomics algorithms.

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Thioredoxin Reductase Inhibitors-Pipeline Insights, 2014 Market Trend, Share And Research Analysis

October 13th 2014, Posted by: Drug Repurposing Portal

Thioredoxin Reductase Inhibitors-Pipeline Insights, 2014, report provides comprehensive insights about pipeline drugs across this mechanism of action (MOA). Reasons to buy Complete MOA intelligence and complete understanding over therapeutics development for Thioredoxin Reductase Inhibitors Identify the relationship between the drugs and use it for target finding, drug repurposing, and precision medicine. Devise corrective measures for pipeline projects by understanding Thioredoxin Reductase Inhibitors pipeline depth and focus of Indication therapeutics Developing strategic initiatives to support your drug development activities. Optimize your portfolio and keep you in touch with the rapidly changing pharmaceutical markets, and make the best decisions for your business. Develop and design in licensing and out licensing strategies by identifying prospective partners with the most attractive projects to enhance and expand business potential and scope Provides strategically signifi cant competitor information, analysis, and insights to formulate effective R&D development strategies Modify the therapeutic portfolio by identifying discontinued projects and understanding the factors that drove them from pipeline Gaining a Full Picture of the Competitive Landscape for Evidence based Decisions.

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J&J, Sanofi Apply Ibm'S Watson To R&D

September 9th 2014, Posted by: Drug Repurposing Portal

Sanofi is trying to use Watson to fast-track discoveries too, with the French Big Pharma applying the technology to research on new uses for old drugs. Such computer-driven drug repurposing projects are already underway at other organizations using different technology--Dr. Atul Butte's NuMedii is a high-profile example--but Watson may be able to crunch the data faster.

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A Phenome-Guided Drug Repositioning Through A Latent Variable Model

August 8th 2014, Posted by: Drug Repurposing Portal

The phenome represents a distinct set of information in the human population. It has been explored particularly in its relationship with the genome to identify correlations for diseases.For a comprehensive analysis of the phenome, we assumed that all phenotypes (indications and side effects) were inter-connected with a probabilistic distribution and this characteristic may offe r an opportunity to identify new therapeutic indications for a given drug. Correspondingly, we employed Latent Dirichlet Allocation (LDA), which introduces latent variables (topics) to govern the phenome distribution.

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Drug-Target Database Lets Researchers Match Old Drugs To New Uses

May 28th 2014, Posted by: Drug Repurposing Portal

Drug-target database (K-Map database) developed by researchers at UC Denver lets researchers match old drugs to new uses.

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Exploiting Large-Scale Drug-Protein Interaction Information For Computational Drug Repurposing

May 28th 2014, Posted by: Drug Repurposing Portal

Computational method termed "drug-protein interaction-based repurposing" (DPIR) was developed by Scientists at U.S. Army Medical Research that is potentially applicable to diseases with very few approved drugs.

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Visualization Of Network Target Crosstalk Optimizes Drug Synergism In Myocardial Ischemia

April 25th 2014, Posted by: Drug Repurposing Portal

Visualization of Network can be a good approach for the identification and optimization of disease-related synergistic drug combinations via visualization of the crosstalk between networks of drug targets corresponding to different drugs.

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Research By Structural Genomics Consortium And Discoverx Points To New Multi-Targeting Approaches To Cancer Therapy

March 14th 2014, Posted by: Drug Repurposing Portal

New Drug Repurposing approach using 3D drug chemical structure information, drug target interactions, gene semantic similarity information and gene expression profiles was developed by College of Bioinformatics Science and Technology, Harbin Medical University, China.

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Drug Repurposing: Mining Protozoan Proteomes For Targets Of Known Bioactive Compounds

March 7th 2014, Posted by: Drug Repurposing Portal

Potential opportunities for drug repurposing by developing an automated approach to pre-screen the predicted proteomes of any organism against databases of known drug targets using only freely available resources.

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Pathway-Based Drug Repositioning Using Causal Inference

February 28th 2014, Posted by: Drug Repurposing Portal

A new Pathway-based drug repositioning approach using causal inference has been developed by National Center for Biotechnology Information (NCBI), National Institutes of Health, Bethesda, USA.

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Graph Theory Enables Drug Repurposing How A Mathematical Model Can Drive The Discovery Of Hidden Mechanisms Of Action

January 9th 2014, Posted by: Drug Repurposing Portal

Using the mathematically robust graph theory, the authors develop a methodology to efficiently exploit natural-language expressed biomedical knowledge for repurposing existing drugs towards diseases for which they were not initially intended.

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MeSHDD: Literature-Based Drug-Drug Similarity for Drug Repositioning

May 12th 0005, Posted by: Drug Repurposing Portal

Brown and Patel developed a computational method based on literature annotation like Medical Subject Heading (MeSH) terms for drug repositioning. They established that similarities between drugs stemming from literature predicted the number of shared indication across a drug-drug pair and that clustering drugs based on their similarity revealed both known and novel 'drug' indications. As a case study, the approach was used for repositioning hypothesis generation for metformin, a diabetes drug. Furthermore, the authors have developed a free-to-use application to explore the databases of similarity-based drug clusters.

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Large-Scale Off-Target Identification Using Fast and Accurate Dual Regularized One-Class Collaborative Filtering and Its Application to Drug Repurposing

June 11th 0005, Posted by: Drug Repurposing Portal

Although many computational methods have been developed to predict drug-target interactions, they are either less accurate than the one that Authers are proposing here or computationally too intensive, thereby limiting their capability for large-scale off-target identification. In addition, the performances of most machine learning based algorithms have been mainly evaluated to predict off-target interactions in the same gene family for hundreds of chemicals. It is not clear how these algorithms perform in terms of detecting off-targets across gene families on a proteome scale. Here, Authers are presenting a fast and accurate off-target prediction method, REMAP, which is based on a dual regularized one-class collaborative filtering algorithm, to explore continuous chemical space, protein space, and their interactome on a large scale. When tested in a reliable, extensive, and cross-gene family benchmark, REMAP outperforms the state-of-the-art methods. Furthermore, REMAP is highly scalable. It can screen a dataset of 200 thousands chemicals against 20 thousands proteins within 2 hours. Using the reconstructed genome-wide target profile as the fingerprint of a chemical compound, Auther predicted that seven FDA-approved drugs can be repurposed as novel anti-cancer therapies. The anti-cancer activity of six of them is supported by experimental evidences. Thus, REMAP is a valuable addition to the existing in silico toolbox for drug target identification, drug repurposing, phenotypic screening, and side effect prediction.

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A Comprehensive Analysis of Drug Repurposing Workflows Published by Insilico Medicine

June 11th 0010, Posted by: Drug Repurposing Portal

An international group of expert scientists led by Insilico Medicine published a paper describing a comprehensive overview of the current status of in silico repurposing methods by establishing links between current technological trends, data availability and characteristics of the algorithms used in these methods. The paper highlights the possibilities offered by incorporation of deep learning approaches into the modular drug repurposing workflows. The study describes the major advances in the field and the approaches to incorporate various methods into comprehensive pipeline for drug repurposing.

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New Computational Tool May Speed Drug Discovery

September 11th 0007, Posted by: Drug Repurposing Portal

A new computational tool called fABMACS is helping scientists see beyond static images of proteins to more efficiently understand how these molecules function, which could ultimately speed up the drug discovery process ? Research work by Bradley Dickson, Ph.D., a computational biophysicist in the laboratory of Scott Rothbart, Ph.D., at Van Andel Research Institute (VARI)

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Repurposing strategies for tropical disease drug discovery

October 12th 0012, Posted by: Drug Repurposing Portal

Seeing the extent to which the human health is getting effected by Neglected tropical diseases (NTDs), much attention is need than to what is given now. New practical initiatives for launching novel drug discovery programs have emerged that repurpose existing chemical matter as new drugs or new starting points for optimization. The article describes the applications of different repurposing approaches for NTDs, and thus, provide a means by which these approaches are distinct to each other. These include drug repurposing, target repurposing, target class repurposing, and lead repurposing.

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