Drug Repurposing News

A new algorithm for drug repositioning

September 9th 2019, Posted by: Drug Repurposing Portal

The multi-label learning framework could identify new uses for old drugs or discover new drugs for a known target. The application utilizes supervised learning model of l2-regularized logistic regression to train over a data consisting of drug labels and associated target genes. The prediction results were well supported with available literature, GO enrichment analysis & disease association.

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Drug repurposing with network reinforcement

July 24th 2019, Posted by: Drug Repurposing Portal

The article intends to propose the implementation of network-based machine learning algorithm for drug repurposing technique. It describes the framework construction of a drug network, and the ways of strengthening it by employing multiple/heterogeneous types of data.

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New Drug Repurposing Strategies using the existing Omics Data

July 23rd 2019, Posted by: Drug Repurposing Portal

The Drug Repurposing has definitely increased the chances of success taking advantage of the previously validated tests related to drug safety and allowing the incorporation of omics. The review summarizes drug repurposing strategies and methodologies by exploring the existing omics data under various field; where each omics field has specific strengths and limitations but incorporating it into the drug repurposing has shown to be a success.

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deepDR: A network-based deep learning approach to in silico drug repositioning

May 22nd 2019, Posted by: Drug Repurposing Portal

Researchers from China have developed a deep learning algorithm, termed as deepDR, by integrating 10 heterogenous drug-related networks for in-silico drug repurposing. The algorithm is trained to generate low-dimensional network features common to all heterogenous networks using multimodal deep autoencoder. The deepDR generated features and known clinical drug-disease interactions were encoded and decoded collectively via an autoencoder to infer novel candidates for approved drugs.

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Drug ReposER: a new web-based application to predict alternative target for drug repositioning.

May 20th 2019, Posted by: Drug Repurposing Portal

The possible existence of a similar drug binding site on an alternative target as in the original target is a crucial aspect of drug repurposing. Hence, the assumption that proteins with similar binding sites may also bind to similar drugs. In this regard, the 3D substructure similarity data of other non-target proteins may be used to identify similar drug binding sites. A newly designed Drug ReposER (DRug REPOSitioning Exploration Resource) application utilizes pre-computed amino acid arrangements from protein structures in the Protein Data Bank to identify alternative drug targets having similarity with the 3D drug binding sites. Using this application user may explore alternative targets for known drugs.

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Drug repositioning using gene expression signature in multiple myeloma

May 2nd 2019, Posted by: Drug Repurposing Portal

In a recent study, researchers based in China explored personalized drug repositioning avenues to identify therapeutic agents for Multiple Myeloma (MM). Associations between genes and clinical outcomes were spotted based on transcriptome profiles of 588 MM patients. Vorinostat (used against cutaneous T cell lymphoma), Trifluoperazine and Thioridazine (both antipsychotics) were found to be the top three drugs to exhibit potential effects on the genes involved in the prognosis of MM. Most of the molecules assessed by CMAP database showcased high affinity towards CDK1 (cyclin-dependent kinase-1), the prominent class of prognosis-related genes in MM. Further research would be able to elucidate the potential of these repurposed drugs in the treatment of MM.

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A new method to predict drug-disease associations

March 29th 2019, Posted by: Drug Repurposing Portal

A common assumption while repurposing drugs is that similar drugs might be able to treat similar diseases. Many existing computational methods hence compute drug-disease similarities. To train the models, these methods treat the unlabeled samples as negative ones, which might introduce artificial noise. In a recent study, researchers based in China and the US have proposed a method, EMP-SVD (Ensemble Meta Paths and Singular Value Decomposition) to predict drug-disease associations without the need of similarity information and select more likely negative samples. Experiments with this method have shown that it could mine out many drug-disease associations as revealed by literature analysis of case studies. It can integrate the interaction data of diseases, proteins and drugs to predict the drug-disease associations without the need of similarity information.

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Use of genome-scale metabolic models to repurpose drugs against prostate cancer

March 21st 2019, Posted by: Drug Repurposing Portal

Genome-scale metabolic models (GEMs) are used in cancer research to identify potential drug targets as well as biomarkers. In a recent study, researchers based in the UK, Turkey and Sweden built up a prostate cancer (PRAD)-specific GEM to understand prostate cancer metabolism and explore the repurposing potential of therapeutic agents. In this study, novel gene-drug interactions are predicted through the integration of global gene expression profiles of cell lines with more than a thousand drugs by using the prostate cancer GEM. Based on in-vitro cell viability assay, it was found that Azlocillin, Ifenprodil, Sulfamethoxypyridazine, and Hydroflumethiazide can be repurposed for the treatment of prostate cancer. The effect of Ifenprodil was validated using an in-vitro cell assay and its inhibitory effect on a prostate cancer cell line was shown. Apart from their other uses, this study shows the potential of GEMs in the process of repurposing of drugs.

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Phenotypic high-throughput screen to enable potential repurposing of drugs to combat idiopathic lung fibrosis

February 15th 2019, Posted by: Drug Repurposing Portal

Idiopathic pulmonary fibrosis (IPF) is a type of chronic lung disease characterized by a progressive decline in lung function. About 5 million people are affected globally. Excessive deposition of altered extra cellular matrix (ECM) has been shown to play a crucial role in the pathophysiology of IPF. A group of scientists based in Germany developed a new phenotypic high-throughput drug discovery assay for identifying novel fibrotic ECM deposition inhibitors.Live immunolabeling and an automated confocal imaging, coupled to an automated 3D image analysis, resulted in a confident assessment of the alterations in the ECM's deposition.Screening of 1039 FDA/EMA approved drugs (of different classes) resulted in the identification of potential 22 ECM-deposition-inhibitors for drug repurposing. This study shows a phenotypic screening strategy to identify drugs for use against IPF.

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Na+/K+ATPase inhibitors suppress the formation of metastases

February 5th 2019, Posted by: Drug Repurposing Portal

Researchers at the University and the University Hospital of Basel have now discovered a substance that suppresses the formation of metastases. Circulating tumor cells (CTCs) travel to distant parts of the body via the bloodstream leading to metastases. The researchers used a high-throughput phenotypic screening approach testing 2486 FDA-approved compounds in this study. Of the drugs tested, Na+/K+ATPase inhibitors were found to dissociate CTC clusters into single cells. CTC clusters are vital for metastases as epigenetic changes in these clusters aids metastasis seeding. The dissociation of CTC clusters into individual cells by drugs leads to epigenetic remodeling, thereby preventing the formation of new metastases. Thus, the repurposing of Na+/K+ATPase inhibitors and other drugs to dissociate CTC clusters could be a method to prevent cancer metastasis.

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Computational prediction for drug repositioning using meta-path-based semantic network analysis

January 3rd 2019, Posted by: Drug Repurposing Portal

Scientists based in China have developed a methodology called HeteSim_DrugDisease (HSDD) for the prediction of drug repositioning, as described in a recent publication. The first step in the HSDD methodology involves building the drug-drug similarity network and disease-disease similarity network by integrating the information of drugs and diseases. Next, a drug-disease heterogeneous network is created, which combines the drug similarity network, disease similarity network as well as the known drug-disease association network. Finally, HSDD predicts novel drug-disease associations based on the HeteSim scores of different meta-paths. Experimental results aimed at validating the HSDD methodology have shown that HSDD performs better than the currently available state-of-the-art approaches.

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Pathway-Based Drug Repositioning for Cancers

October 29th 2018, Posted by: Drug Repurposing Portal

The article discusses a novel computational approach for drug repositioning for cancer treatment. Chemically induced gene expression data for 1112 drugs on 66 human cell lines was analyzed and searched for drugs that inactivate pathways involved in the growth of cancer cells (cell cycle) and activate pathways that contribute to the death of cancer cells (e.g., apoptosis and p53 signaling). A large-scale prediction approach was adopted for predicting potential anticancer effects for all the drugs and experimentally validated the prediction results via three in vitro cellular assays that evaluate cell viability, cytotoxicity, and apoptosis induction. Using this strategy, several anticancer drugs were identified. The proposed pathway-based method has great potential to improve drug repositioning research for cancer treatment.

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A novel gene expression-based method for drug repositioning

August 23rd 2018, Posted by: Drug Repurposing Portal

Specific environmental or genetic perturbations result in biological changes without any pervasive gene expression changes. Current computational strategies that utilize gene expression do not consider the robustness to perturbations. A new expression intensity-based similarity metric method is proposed which consistently achieved better performance with respect to the gold-standard clustering of drugs. This framework systematically compared 3,332 chemical and 3,934 genetic perturbations across 10 cell types representing diverse cellular signatures, and thereafter identified thousands of recurrent and cell type-specific connections. This framework can be useful in hypothesis generation, functional testing, and drug repositioning strategies.

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Machine learning-based drug-target interaction prediction as an aid for drug repurposing

August 20th 2018, Posted by: Drug Repurposing Portal

A new study has reviewed latest computational methods to predict drug-target interactions, a crucial step in drug discovery and drug repurposing. Using machine learning-based approaches, the authors introduced data and datasets to summarize critical features extracted from different drugs and targets. Since drug-drug similarity and target-target similarity are important for several machine learning prediction models, the study came up with a method to calculate similarities based on data or features, and thereby provides a guide to the development of significant molecular drug-target fingerprints.

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Pathway-based approach for drug repositioning in breast cancer subtypes

August 15th 2018, Posted by: Drug Repurposing Portal

In this study the authors have integrated several tools to prioritize associated pathways and drugs in breast cancer subtypes. These tools use disease-specific experimental gene expression data in addition to information from biological and pharmacological databases. New associations between pathways and breast cancer subtypes are proposed in this study. These results might provide novel insights to drug repurposing strategies in each breast cancer molecular subtype therapy. This methodology could be further developed to provide personalized treatment schemes to those who do not respond to existing therapeutic options.

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Predicting approved and novel drug-diseases associations using computational drug repurposing methods

August 14th 2018, Posted by: Drug Repurposing Portal

Since conventional drug discovery and development are resource- and time-intensive, new methods are required to hasten the availability of drugs to treat critical diseases. Drug repurposing/repositioning/therapeutic switching is an application of polypharmacology, wherein a single drug can bind to multiple targets, thereby making it a suitable alternative to the traditional process. By combining PPIs, biological pathways, binding site structural similarities, and disease-disease similarity measures, the authors of a new study have proposed an integrative method based on similarity scheme to predict approved and novel drug targets with new disease associations. This approach could thus the pave way for drug repurposing efforts of finding new uses for old drugs.

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A novel network-based drug repositioning approach for discovering potential antidepressants

August 6th 2018, Posted by: Drug Repurposing Portal

In a recently published study, researchers have used a new repositioning approach to predict novel drug-target associations. This method uses network-based integration of drug chemical similarity, therapeutic similarity, and protein-protein interactions. In the next step, drugs that can act on depression-related targets were screened and validation of these potential antidepressants and their molecular targets is done using drugs data documented in DrugBank. Following this method, six potential drugs including the antispasmodic drug Alverine were identified and evaluated their antidepressant functions in mice. This novel drug repositioning method may thus hold immense promise in drug discovery for heterogeneous and complex diseases such as depression.

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Structure-based approaches for repurposing of FDA-approved drugs as BET-BRD4 inhibitors

August 6th 2018, Posted by: Drug Repurposing Portal

Various bromodomain (BRD) inhibitors are under preclinical/clinical investigations as anti-cancer agents. This study aimed to identify of the FDA-approved drugs that can be used as potential human BRD4 inhibitors. For this purpose, various approaches like structural insights into the ligand recognition modes guiding bromodomain selectivity, enrichment analysis and docking-based database screening were used. Interestingly, authors have found several drugs have better binding affinity than JQ1, a well-known BRD4 inhibitor. Further ranking of these drugs identified a selective histamine H1 receptor antagonist azelastine binds with higher binding affinity than JQ1. Thus, these data provide insights for structure-based drug designing/repurposing.

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Machine learning based drug repositioning approach for schizophrenia and depression/anxiety disorders

July 16th 2018, Posted by: Drug Repurposing Portal

A recently published study discussed a machine learning (ML) workflow, including deep neural networks (DNN), support vector machines (SVM), elastic net regression, random forest and gradient boosted trees for a disease-centric drug repurposing. This ML approach identified repositioning opportunities for schizophrenia, depression, and anxiety disorders. It was found to be widely applicable to any chemicals or drugs with measured expression profiles, even if the drug targets were unknown.

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Regression analysis to predict novel drug-disease association

July 13th 2018, Posted by: Drug Repurposing Portal

The current study demonstrated graph regularized transductive regression method (GRTR) to predict novel drug-disease associations. The proposed method uses drug-disease associations that are sparse and performs the scoring and ranking of associations iteratively. This approach is different from most of the existing computational methods that are biased towards known drug-disease associations already verified by biological experiments. Additionally, case studies on several selected drugs evaluated the utility of above described method in discovering potential indications for drugs.

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Deep embeddings of gene expression profiles as a strategy for drug repurposing

July 12th 2018, Posted by: Drug Repurposing Portal

Functional similarities among compounds serve as a pre-requisite for computational drug repositioning. A recent study has found a new method to measure compound functional similarity based on gene expression data. It takes advantage of deep neural networks to learn an embedding that substantially denoises expression data, making replicates of the same compound more similar. This approach could lead to the identification of drugs with shared therapeutic and biological targets, even among structurally divergent compounds, thereby paving the way for drug repurposing endeavors based on expression data.

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Transcription factor centered drug repurposing through Master Regulators Connectivity Map

July 2nd 2018, Posted by: Drug Repurposing Portal

Transcription factors are strong modulators of phenotypic changes due to their inherent characteristic of driving expression of numerous genes. Therefore, they form an important component of drug repurposing activities which is based on studing connection between "disease-gene-drug". However, activity of transcription factors is driven more by post-transcriptional modifications and other other processes rather than expression alone, making their study complicated. This current study proposes use of high-throughput transcriptomic data to infer transcription factors-targets interactions, and assess their activity through co-expression networks. This information can be used further to search for drugs capable of reverting the gene expression profile of pathological phenotypes employing the connectivity maps paradigm.

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Targeting ageing through a gene expression-based drug repurposing approach

June 30th 2018, Posted by: Drug Repurposing Portal

New pharmacological agents are required to lessen the symptoms of ageing. In order to combat ageing in the human brain, the authors of the current study used a systems level drug repurposing methodology to discover new drugs. Using multiple gene expression datasets from the brain tissue of patients of different ages, the authors compared gene expression changes associated with ageing to drug-perturbed expression profiles using the Connectivity Map. 24 drugs were identified through this method, with some of them having the potential to function as anti-ageing drugs by reversing the detrimental changes associated with ageing, while others could possibly mimic cellular defence mechanisms.

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Drug repurposing by analysing common pathways among complex diseases

June 22nd 2018, Posted by: Drug Repurposing Portal

The traditional drug discovery approach of "one target, one disease" is associated with high drug attrition rate due to polygenic nature of most complex diseases, causing immense heterogeneity in drug response across patients. The present study proposes a tool, "PxEA- proximal pathway enrichment analysis" for pinpointing drugs that target common disease pathways. PxEA uses topology information from the network of interactions between disease genes, pathway genes, drug targets and other proteins to rank drugs by their interactome-based proximity to pathways shared across multiple diseases, thereby providing unprecedented drug repurposing opportunities.

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Matrix factorization method to predict drug-disease associations

June 19th 2018, Posted by: Drug Repurposing Portal

The current study proposes the merits of the similarity constrained matrix factorization method for predicting unknown drug-disease associations (SCMFDD). To do this, the method uses known drug-disease associations, drug features and disease semantic information to predict novel drug-disease associations. Further information on this method is available at http://www.bioinfotech.cn/SCMFDD/.

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Cancer Drug Response Profile scan (CDRscan): an application of a deep learning model in drug repurposing

June 11th 2018, Posted by: Drug Repurposing Portal

This study presents a deep learning model for predicting anti-cancer drug responsiveness based on data from a large-scale drug screening assay that encompasses genomic profiles of 787 human cancer cell lines and structural profiles of 244 drugs. CDRscan was used to identify 14 oncology and 23 non-oncology drugs from 1,487 approved drugs for repurposing to new potential cancer indications. CDRscan also holds promise for precision medicine.

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DeCOST: Applying the control theory paradigm for drug repuposing

June 5th 2018, Posted by: Drug Repurposing Portal

An important cornerstone of drug repurposing is to build connectivity among drugs, genes, and diseases acquired from different sources. The present study proposes a framework called DeCoST which builds disease-specific mathematical models based on the quantification of connections between drugs-diseases-genes. The DeCoST framework could for instance classify between FDA-approved drugs and rejected/withdrawn drugs, an approach often used as a foundation to apply DeCoST in recommending potential new treatment startegies.

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Predicting drug-disease associations and their therapeutic function based on the drug-disease association bipartite network

June 4th 2018, Posted by: Drug Repurposing Portal

Researchers report a network topological similarity-based inference method (NTSIM) to predict unobserved drug-disease associations which could be useful for drug repositioning. A novel representation for drugs and diseases based on the bipartite network and linear neighborhood similarity was proposed. Compared with existing drug-disease association prediction methods, NTSIM can produce superior performances in predicting drug-disease associations, and NTSIM-C can accurately classify drug-disease associations.

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Drug repositioning and target prioritization methods based on connecting genetics and gene expression data

May 31st 2018, Posted by: Drug Repurposing Portal

Mining public repositories of GWAS data and drug transcriptome profiles can offer systematic approaches to generate drug repositioning hypotheses based on disease genetics. A recent study highlights the findings that genes genetically associated with certain diseases are more likely to be differentially expressed in the same disease and that in existing drug-disease combinations, genes significantly up- or down-regulated after drug treatment were enriched for genes genetically associated with that disease. Thus, the study offers a potential method to generate and rank novel GWAS-driven drug repositioning predictions.

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Utility of multi-task learning in linking drug-target and pathway activation for effective drug repurposing strategies

May 28th 2018, Posted by: Drug Repurposing Portal

Mechanisms underlying treatment efficacy in cancer are often difficult to decipher. How would activation of a pathway Y confer sensitivity to any drug targeting a protein X? A possible solution is the new approach that utilizes bayesian multitask, multi-relational algorithms for exploring possible interactions between drug targets and signaling pathways' activation and validating the same through GDSC data. Such an analysis of interactions across tissues might be useful for target discovery, repurposing of tissue-specific drug combination strategies, and for patient stratification.

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Findings from GWAS and PheWAS analysis might provide new drug repositioning opportunities

May 18th 2018, Posted by: Drug Repurposing Portal

A recent study from Duke and Vanderbilt universities proposes a framework to infer novel disease-gene associations using GWAS (Genome-Wide Association Studies) and PheWAS (Phenome-Wide Association Studies) data. Clinical relevance of drug indications postulated from GWAS/PheWAS findings is inferred from Medication Indication Resource (MEDI). The study found 16 drug-GWAS pairs with clinical indications out of 151,011 total drug-GWAS pairs, thus providing a potential method for future drug repositioning.

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Repurposing as a rapid approach for finding new agents to treat neglected infectious diseases.

May 4th 2018, Posted by: Drug Repurposing Portal

Drug repurposing, where existing drugs are screened for alternative activities, is becoming an attractive approach in antimicrobial discovery programs, and various compound libraries are now commercially available. As these drugs have already undergone extensive optimisation and passed regulatory hurdles this can fast-track their progress to market for new uses. This study screened the Screen-Well Enzo library of 640 compounds for candidates that phenotypically inhibited the growth of Cryptococcus deuterogattii.

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New drug candidates for treatment of atypical meningiomas: An integrated approach using gene expression signatures for drug repurposing

March 23rd 2018, Posted by: Drug Repurposing Portal

Atypical meningiomas are one of the most common cerebral neoplasms with poor prognosis and extremely high recurrence rate compared to their grade I subtypes. The only available therapeutic routes are surgery and radiotherapy, with limited efficacy. In a recent study published in PLoS One, researchers have identified novel drug candidates such as emetine, verteporfin, phenoxybenzamine and trazodone using a computational drug repurposing approach based on gene expression signatures of atypical meningioma tissues, with subsequent ingenuity pathway analysis (IPA) of drug-generated expression profiles. IPA revealed that these drugs target signal cascades such as ERK/MAPK signaling which potentially drive pathogenesis of meningiomas, and warrant further in vivo experimental validation. Beyond proposing already approved drug candidates in the management of atypical meningioma the study highlights the potential of computational techniques in improving disease management strategies.

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Calcium channel blockers as drug repurposing candidates for gestational diabetes: Mining large scale genomic and electronic health records data to repurpose medications.

March 17th 2018, Posted by: Drug Repurposing Portal

New therapeutic approaches are needed for gestational diabetes mellitus (GDM). In this study they investigated associations between electronic medical record (EMR) phenotypes and genetic variants to uncover drugs currently considered safe in pregnancy that could treat or prevent GDM. The study identified 129 systemically active drugs considered safe in pregnancy targeting the proteins produced from 196 genes. They also tested for associations between GDM and/or type 2 diabetes (DM2) and 306 SNPs in 130 genes represented on the Illumina Infinium Human Exome Bead Chip (DM2 was included due to shared pathophysiological features with GDM). On the other hand, they tested the association between drugs and glucose tolerance during pregnancy as measured by the glucose recorded during a routine 50-g glucose tolerance test (GTT). They found an association between GDM/DM2 and the genes targeted by 11 drug classes. Thus, CCBs were identified as a class of drugs considered safe in pre gnancy could have efficacy in treating or preventing GDM. 5HT-3 antagonists may be associated with worse glucose tolerance.

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Software Helps Find Drugs That Can be Repurposed to Treat Rare Disease

March 16th 2018, Posted by: Drug Repurposing Portal

Researchers at the LSU Computational Systems Biology group have developed a sophisticated and systematic way to identify existing drugs that can be repositioned to treat a rare disease or condition. They have fine-tuned a computer-assisted drug repositioning process that can save time and money in helping these patients receive effective treatment.

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Calcium channel blockers as potential repurposing candidates for gestational diabetes mellitus

February 23rd 2018, Posted by: Drug Repurposing Portal

The incidence of gestational diabetes mellitus (GDM) continues to rise suggesting for development of novel therapeutic strategies. However, the usual target-driven drug discovery is complicated in pregnancy due to associated risk factors. To overcome this drawback, the authors of the present study, proposed a new treatment strategy from the associations between electronic medical record (EMR) phenotypes and GDM genetic variants. Drugs considered safe in pregnancy are sorted from EMR and corresponding target genes associated with GDM and type 2 diabetes are identified. In a parallel analysis, authors have shown that L-type calcium channel blocking antihypertensives (CCBs) were associated with a decrease in glucose during glucose tolerance test. These findings demonstrate the repurposing potential of calcium channel blockers for gestational diabetes mellitus treatment.

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Protein Analysis Enables Treatment of Eye-Disease Symptoms with Existing Drugs

January 9th 2018, Posted by: Drug Repurposing Portal

University School of Medicine has matched existing drugs to errant proteins expressed by patients with a rare eye disease. “Analyzing fluid samples from the eye can totally change how we treat patients,” said Vinit Mahajan, MD, PhD, associate professor of ophthalmology. The team employed proteomics, the large-scale study of proteins, in identifying four on-the-market drugs that successfully quelled symptoms triggered by several of the overabundant proteins.

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KAIST team develops technology to find optimum drug target for cancer

January 4th 2018, Posted by: Drug Repurposing Portal

A technology using systems biology approach for identifying the optimum drug target based on cancer cell type was developed by KAIST research team led by Professor Kwang-Hyun Cho of the Department of Bio and Brain Engineering. Large-scale cancer cell genomic data from The Cancer Cell Line Encyclopedia (CCLE) was used to construct different molecular networks specific to the characteristics of genetic variations that aid in predicting the drug resistance in cancer cells. The team suggest that the new technology can be used in drug repositioning via identifying optimum drug targets.

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gene2drug: a Computational Tool for Pathway-based Rational Drug Repositioning.

December 15th 2017, Posted by: Drug Repurposing Portal

A novel computational methodology for rational drug repositioning, which exploits the transcriptional responses following treatment with small molecule. Specifically, given a therapeutic target gene, a prioritization of potential effective drugs is obtained by assessing their impact on the transcription of genes in the pathway(s) including the target. (Available @ http://gene2drug.tigem.it)

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New Drug Repurposing e-learning from ecancer and ReDO

November 30th 2017, Posted by: Drug Repurposing Portal

ecancer.org and the Repurposing Drugs in Oncology (ReDO) Project are delighted to announce the launch of a new free e-learning module designed to teach clinical researchers and health care professionals about the key issues involved in drug repurposing.

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An in-silico approach to predict and exploit synthetic lethality in cancer metabolism

September 21st 2017, Posted by: Drug Repurposing Portal

Synthetic lethality is a promising concept in cancer research, potentially opening new possibilities for the development of more effective and selective treatments. Here, we present a computational method to predict and exploit synthetic lethality in cancer metabolism. Our approach relies on the concept of genetic minimal cut sets and gene expression data, demonstrating a superior performance to previous approaches predicting metabolic vulnerabilities in cancer. Our genetic minimal cut set computational framework is applied to evaluate the lethality of ribonucleotide reductase catalytic subunit M1 (RRM1) inhibition in multiple myeloma. We present a computational and experimental study of the effect of RRM1 inhibition in four multiple myeloma cell lines. In addition, using publicly available genome-scale loss-of-function screens, a possible mechanism by which the inhibition of RRM1 is effective in cancer is established. Overall, our approach shows promising results and lays the foundation to build a novel family of algorithms to target metabolism in cancer.

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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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On the Integration of In Silico Drug Design Methods for Drug Repurposing

March 23rd 2017, Posted by: Drug Repurposing Portal

Drug repurposing has become an important branch of drug discovery. Several computational approaches that help to uncover new repurposing opportunities and aid the discovery process have been put forward, or adapted from previous applications. A number of successful examples are now available. Overall, future developments will greatly benefit from integration of different methods, approaches and disciplines. Steps forward in this direction are expected to help to clarify, and therefore to rationally predict, new drug-target, target-disease, and ultimately drug-disease associations.

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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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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).

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

"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.

News Methods Funding Collaborations

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.

News Methods Funding Collaborations

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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