Repositioning of Tak-475 In Mevalonate Kinase Disease: Translating Theory Into Practice.

Curr Med Chem. 2018;25(24):2783-2796

Authors: Marcuzzi A, Loganes C, Celeghini C, Kleiner G

Abstract
BACKGROUND: Mevalonate Kinase Deficiency (MKD, OMIM #610377) is a rare autosomal recessive metabolic and inflammatory disease. In MKD, defective function of the enzyme mevalonate kinase, due to a mutation in the MVK gene, leads to the shortage of mevalonate- derived intermediates, which results in unbalanced prenylation of proteins and altered metabolism of sterols. These defects lead to a complex multisystem inflammatory and metabolic syndrome.
OBJECTIVE: Although biologic therapies aimed at blocking the inflammatory cytokine interleukin- 1 can significantly reduce inflammation, they cannot completely control the clinical symptoms that affect the nervous system. For this reason, MKD can still be considered an orphan drug disease. The availability of MKD models reproducing the MKD-systematic inflammation, is crucial to improve the knowledge on its pathogenesis, which is still unknown. New therapies are also required in order to improve pateints' conditions and their quality of life.
METHODS: MKD-cellular models can be obtained by biochemical inhibition of mevalonatederived isoprenoids. Of note, these cells present an exaggerated response to inflammatory stimuli that can be reduced by treatment with zaragozic acid, an inhibitor of squalene synthase, thus increasing the availability of isoprenoids intermediates upstream the enzymatic block.
RESULTS: A similar action might be obtained by lapaquistat acetate (TAK-475, Takeda), a drug that underwent extensive clinical trials as a cholesterol lowering agent 10 years ago, with a good safety profile.
CONCLUSIONS: Here we describe the preclinical evidence supporting the possible repositioning of TAK-475 from its originally intended use to the treatment of MKD and discuss its potential to modulate the mevalonate pathway in inflammatory diseases.

PMID: 28901277 [PubMed - indexed for MEDLINE]

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

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2018/07/19

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

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

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2018/07/19

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

In Vitro and In Vivo Activity of Amiodarone Against Ebola Virus.

J Infect Dis. 2018 Jul 16;:

Authors: Dyall J, Johnson JC, Hart BJ, Postnikova E, Cong Y, Zhou H, Gerhardt DM, Michelotti J, Honko AN, Kern S, DeWald LE, O'Loughlin KG, Green CE, Mirsalis JC, Bennett RS, Olinger GG, Jahrling PB, Hensley LE

Abstract
At the onset of the 2013-2016 epidemic of Ebola virus disease (EVD), no vaccine or antiviral medication was approved for treatment. Therefore, considerable efforts were directed towards the concept of drug repurposing or repositioning. Amiodarone, an approved multi-ion channel blocker for the treatment of cardiac arrhythmia, was reported to inhibit filovirus entry in vitro. Compassionate use of amiodarone in EVD patients indicated a possible survival benefit. In support of further clinical testing, we confirmed anti-Ebola virus activity of amiodarone in different cell types. Despite promising in vitro results, amiodarone failed to protect guinea pigs from a lethal dose of Ebola virus.

PMID: 30016444 [PubMed - as supplied by publisher]

Cell-line dependent antiviral activity of sofosbuvir against Zika virus.

Antiviral Res. 2017 Oct;146:161-163

Authors: Mumtaz N, Jimmerson LC, Bushman LR, Kiser JJ, Aron G, Reusken CBEM, Koopmans MPG, van Kampen JJA

Abstract
The recent epidemic of Zika virus (ZIKV) in the Americas and its association with fetal and neurological complications has shown the need to develop a treatment. Repurposing of drugs that are already FDA approved or in clinical development may shorten drug development timelines in case of emerging viral diseases like ZIKV. Initial studies have shown conflicting results when testing sofosbuvir developed for treatment of infections with another Flaviviridae virus, hepatitis C virus. We hypothesized that the conflicting results could be explained by differences in intracellular processing of the compound. We assessed the antiviral activity of sofosbuvir and mericitabine against ZIKV using Vero, A549, and Huh7 cells and measured the level of the active sofosbuvir metabolite by mass spectrometry. Mericitabine did not show activity, while sofosbuvir inhibited ZIKV with an IC50 of ∼4 μM, but only in Huh7 cells. This correlated with differences in intracellular concentration of the active triphosphate metabolite of sofosbuvir, GS-461203 or 007-TP, which was 11-342 times higher in Huh7 cells compared to Vero and A549 cells. These results show that a careful selection of cell system for repurposing trials of prodrugs is needed for evaluation of antiviral activity. Furthermore, the intracellular levels of 007-TP in tissues and cell types that support ZIKV replication in vivo should be determined to further investigate the potential of sofosbuvir as anti-ZIKV compound.

PMID: 28912011 [PubMed - indexed for MEDLINE]

Repurposing metformin for the prevention of cancer and cancer recurrence.

Diabetologia. 2017 Sep;60(9):1639-1647

Authors: Heckman-Stoddard BM, DeCensi A, Sahasrabuddhe VV, Ford LG

Abstract
Multiple epidemiological studies have documented an association between metformin, used for treatment of type 2 diabetes, and reduced cancer incidence and mortality. Cell line models may not accurately reflect the effects of metformin in the clinical setting. Moreover, findings from animal model studies have been inconsistent, whilst those from more recent epidemiological studies have tempered the overall effect size. The purpose of this review is to examine metformin's chemopreventive potential by outlining relevant mechanisms of action, the most recent epidemiologic evidence, and recently completed and ongoing clinical trials. Although repurposing drugs with excellent safety profiles is an appealing strategy for cancer prevention and treatment in the adjuvant setting, there is no substitute for well-executed, large randomised clinical trials to define efficacy and determine the populations that are most likely to benefit from an intervention. Thus, enthusiasm remains for understanding the role of metformin in cancer through ongoing clinical research.

PMID: 28776080 [PubMed - indexed for MEDLINE]

Drug repositioning for schizophrenia and depression/anxiety disorders: A machine learning approach leveraging expression data.

IEEE J Biomed Health Inform. 2018 Jul 16;:

Authors: Zhao K, So HC

Abstract
Development of new medications is a lengthy and costly process, and drug repositioning might help to shorten the development cycle. We present a machine learning (ML) workflow to drug discovery or repositioning by predicting indication for a particular disease based on drug expression profiles, with a focus on applications in psychiatry. Drugs that are not originally indicated for the disease but with high predicted probabilities serve as candidates for repurposing. This approach is widely applicable to any chemicals or drugs with expression profiles measured, even if drug targets are unknown. It is also highly flexible as virtually any supervised learning algorithms can be used. We employed the ML approach to identify repositioning opportunities for schizophrenia as well as depression and anxiety disorders. We applied various state-of-the-art ML approaches, including deep neural networks (DNN), support vector machines (SVM), elastic net regression, random forest and gradient boosted trees. The predictive performance of the five approaches in cross-validation did not differ substantially, with SVM slightly outperforming the others. However, other methods also reveal literature-supported repositioning candidates of different mechanisms of actions. As a further validation, we showed that the repositioning hits are enriched for psychiatric medications considered in clinical trials. We also examined the correlation between predicted probabilities of treatment potential and the number of related research articles, and found significant correlations for all methods, especially DNN. Finally, we propose that ML may provide a new avenue to exploring drug mechanisms via examining the variable importance of gene features.

PMID: 30010603 [PubMed - as supplied by publisher]

Drug Repurposing in the Development of Anticancer Agents.

Curr Med Chem. 2018 Jul 13;:

Authors: Olgen S, Kotra L

Abstract
BACKGROUND: Research into repositioning known drugs to treat cancer other than the originally intended disease continues to grow and develop, encouraged in part, by several recent success stories. Many of the studies in this article are geared towards repurposing generic drugs because additional clinical trials are relatively easy to perform and the drug safety profiles have previously been established.
OBJECTIVE: This review provides an overview of anti-cancer drug development strategies which is one of the important areas of drug re-structuring.
METHODS: Repurposed drugs for cancer treatments are classified by their pharmacological effects. The successes and failures of important repurposed drugs as anti-cancer agents are evaluated in this review.
RESULTS AND CONCLUSION: Drugs could have many off-target effects, and can be intelligently repurposed if the off-target effects can be employed for therapeutic purposes. In cancer, due to the heterogeneity of the disease, often targets are quite diverse, hence a number of already known drugs that interfere with these targets could be deployed or repurposed with appropriate research and development.

PMID: 30009698 [PubMed - as supplied by publisher]

Metformin in Idiopathic Pulmonary Fibrosis "Seeking the Holy-Grail through Drug-Repositioning".

Respiration. 2018 Jul 13;:1-3

Authors: Tzouvelekis A, Tzilas V, Dassiou M, Bouros D

PMID: 30007987 [PubMed - as supplied by publisher]

Pluripotent Stem Cell Platforms for Drug Discovery.

Trends Mol Med. 2018 Jul 10;:

Authors: Chen KG, Mallon BS, Park K, Robey PG, McKay RDG, Gottesman MM, Zheng W

Abstract
Use of human pluripotent stem cells (hPSCs) and their differentiated derivatives have led to recent proof-of-principle drug discoveries, defining a pathway to the implementation of hPSC-based drug discovery (hPDD). Current hPDD strategies, however, have inevitable conceptual biases and technological limitations, including the dimensionality of cell-culture methods, cell maturity and functionality, experimental variability, and data reproducibility. In this review, we dissect representative hPDD systems via analysis of hPSC-based 2D-monolayers, 3D culture, and organoids. We discuss mechanisms of drug discovery and drug repurposing, and roles of membrane drug transporters in tissue maturation and hPDD using the example of drugs that target various mutations of CFTR, the cystic fibrosis transmembrane conductance regulator gene, in patients with cystic fibrosis.

PMID: 30006147 [PubMed - as supplied by publisher]

Network-based approach to prediction and population-based validation of in silico drug repurposing.

Nat Commun. 2018 Jul 12;9(1):2691

Authors: Cheng F, Desai RJ, Handy DE, Wang R, Schneeweiss S, Barabási AL, Loscalzo J

Abstract
Here we identify hundreds of new drug-disease associations for over 900 FDA-approved drugs by quantifying the network proximity of disease genes and drug targets in the human (protein-protein) interactome. We select four network-predicted associations to test their causal relationship using large healthcare databases with over 220 million patients and state-of-the-art pharmacoepidemiologic analyses. Using propensity score matching, two of four network-based predictions are validated in patient-level data: carbamazepine is associated with an increased risk of coronary artery disease (CAD) [hazard ratio (HR) 1.56, 95% confidence interval (CI) 1.12-2.18], and hydroxychloroquine is associated with a decreased risk of CAD (HR 0.76, 95% CI 0.59-0.97). In vitro experiments show that hydroxychloroquine attenuates pro-inflammatory cytokine-mediated activation in human aortic endothelial cells, supporting mechanistically its potential beneficial effect in CAD. In summary, we demonstrate that a unique integration of protein-protein interaction network proximity and large-scale patient-level longitudinal data complemented by mechanistic in vitro studies can facilitate drug repurposing.

PMID: 30002366 [PubMed - in process]

Drug repurposing using deep embeddings of gene expression profiles.

Mol Pharm. 2018 Jul 12;:

Authors: Donner Y, Kazmierczak S, Fortney K

Abstract
Computational drug repositioning requires assessment of the functional similarities among compounds. Here, we report a new method for measuring compound functional similarity based on gene expression data. This approach takes advantage of deep neural networks to learn an embedding that substantially denoises expression data, making replicates of the same compound more similar. Our method uses unlabeled data in the sense that it only requires compounds to be labeled by identity rather than detailed pharmacological information, which is often unavailable and costly to obtain. Similarity in the learned embedding space accurately predicted pharmacological similarities despite the lack of any such labels during training, and achieved substantially improved performance in comparison with previous similarity measures applied directly to gene expression measurements. Our method could identify drugs with shared therapeutic and biological targets even when the compounds were structurally dissimilar, thereby revealing previously unreported functional relationships between compounds. Thus, our approach provides an improved engine for drug repurposing based on expression data.

PMID: 30001141 [PubMed - as supplied by publisher]

Sequence Analysis of Drug Target Genes with Suicidal Behavior in Bipolar Disorder Patients.

Mol Neuropsychiatry. 2018 Jun;4(1):1-6

Authors: Zai CC, Tiwari AK, Zai GC, de Luca V, Shaikh SA, King N, Strauss J, Kennedy JL, Vincent JB

Abstract
Background: A number of genes have been implicated in recent genome-wide association studies of suicide attempt in bipolar disorder. More focused investigation of genes coding for protein targets of existing drugs may lead to drug repurposing for the treatment and/or prevention of suicide.
Methods: We analyzed 2,457 DNA variants across 197 genes of interest to GlaxoSmithKline across the pipeline in our sample of European patients suffering from bipolar disorder (N = 219). We analyzed these variants for a possible association with the suicide severity score (ranging from suicidal ideation/plan to serious suicide attempt) from the Schedule for Clinical Assessment in Neuropsychiatry. We conducted tests of individual variants and gene-based tests.
Results: We found a number of DNA variants in the transforming growth factor beta receptor 1 gene (TGFBR1) to be suggestively associated with suicide severity scores (p < 0.005). The gene-based tests also pointed to TGFBR1 to be associated with suicide severity (p = 0.0001). However, these findings were not replicated in an independent bipolar disorder sample.
Conclusions: We report no significant association between DNA sequences of drug target genes and suicidal behavior. Additional larger sequencing studies could further interrogate associations between variants in drug target genes and suicidal behavior.

PMID: 29998113 [PubMed]

Computational drug repositioning with random walk on a heterogeneous network.

IEEE/ACM Trans Comput Biol Bioinform. 2018 May 02;:

Authors: Luo H, Wang J, Li M, Luo J, Ni P, Zhao K, Wu F, Pan Y

Abstract
Drug repositioning is an efficient and promising strategy to identify new indications for existing drugs, which can improve the productivity of traditional drug discovery and development. Rapid advances in high-throughput technologies have generated various types of biomedical data over the past decades, which lay the foundations for furthering the development of computational drug repositioning approaches. Although many researches have tried to improve the repositioning accuracy by integrating information from multiple sources and different levels, it is still appealing to further investigate how to efficiently exploit valuable data for drug repositioning. In this study, we propose an efficient approach, RWHNDR (Random Walk on a Heterogeneous Network for Drug Repositioning), to prioritize candidate drugs for diseases. First, an integrated heterogeneous network is constructed by combining multiple sources including drugs, drug targets, diseases and disease genes data. Then, a random walk model is developed to capture the global information of the heterogeneous network. RWHNDR takes advantage of drug targets and disease genes data more comprehensively for drug repositioning. The experiment results show that our approach achieves well improved performance, compared with other state-of-the-art approaches which prioritized candidate drugs based on multi-source data.

PMID: 29994051 [PubMed - as supplied by publisher]

Constructing Disease Similarity Networks Based on Disease Module Theory.

IEEE/ACM Trans Comput Biol Bioinform. 2018 Mar 21;:

Authors: Ni P, Wang J, Zhong P, Li Y, Wu F, Pan Y

Abstract
Quantifying the associations between diseases is now playing an important role in modern biology and medicine, as discovering associations between diseases could help us gain deeper insights into pathogenic mechanisms of complex diseases, thus could lead to improvements in disease diagnosis, drug repositioning and drug development. Due to the growing body of high-throughput biological data, a number of methods have been developed for computing similarity between diseases during the past decade. However, these methods rarely consider the interconnections of genes related to each disease in protein-protein interaction network (PPIN). Recently, the disease module theory has been proposed, which states that disease-related genes or proteins tend to interact with each other in the same neighborhood of a PPIN. In this study, we propose a new method called ModuleSim to measure associations between diseases by using disease-gene association data and PPIN data based on disease module theory. The experimental results show that by considering the interactions between disease modules and each module's modularity, the disease similarity calculated by ModuleSim has a significant correlation with disease classification of Disease Ontology (DO). Furthermore, ModuleSim outperforms other four popular methods which are all using disease-gene association data and PPIN data. In addition, MoudleSim also is capable of finding potential associations between diseases.

PMID: 29993782 [PubMed - as supplied by publisher]

DrPOCS: Drug repositioning based on projection onto convex sets.

IEEE/ACM Trans Comput Biol Bioinform. 2018 Apr 26;:

Authors: Wang YY, Cui C, Qi L, Yan H, Zhao X

Abstract
Drug repositioning, i.e. identifying new indications for known drugs, has attracted a lot of attentions recently and is becoming an effective strategy in drug development. In literature, several computational approaches have been proposed to identify potential indications of old drugs based on various types of data sources. In this paper, by formulating the drug-disease associations as a low-rank matrix, we propose a novel method, namely DrPOCS, to identify candidate indications of old drugs based on projection onto convex sets (POCS). With the integration of drug structure and disease phenotype information, DrPOCS predicts potential associations between drugs and diseases with matrix completion. Benchmarking results demonstrate that our proposed approach outperforms popular existing approaches with high accuracy. In addition, a number of novel predicted indications are validated with various types of evidences, indicating the predictive power of our proposed approach.

PMID: 29993698 [PubMed - as supplied by publisher]

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

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2018/07/11

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

Recent Drug-Repurposing-Driven Advances in the Discovery of Novel Antibiotics.

Curr Med Chem. 2018 Jul 05;:

Authors: Konreddy AK, Rani GU, Lee K, Choi Y

Abstract
Drug repurposing is a safe and successful pathway to speed up the novel drug discovery and development processes compared with de novo drug discovery approaches. Drug repurposing uses FDA-approved drugs and drugs that failed in clinical trials, which have detailed information of potential toxicity, formulation, and pharmacology. Technical advancements in the informatics, genomics, and biological sciences account for the major success of drug repurposing in identifying secondary indications of existing drugs. Drug repurposing is playing a vital role in filling the gap in the discovery of potential antibiotics. Bacterial infections emerged as an ever increasing global public health threat by dint of multidrug resistance to existing drugs. This raises the urgent need of development of new antibiotics that can effectively fight multidrug-resistant bacterial infections (MDRBIs). The present review describes the key role of drug repurposing in the development of antibiotics during 2016-2017 and of the details of recently FDA-approved antibiotics, pipeline antibiotics, and antibacterial properties of various FDA-approved drugs of anti-cancer, anti-fungal, anti-hyperlipidemia, anti-inflammatory, anti-malarial, anti-parasitic, anti-viral, genetic disorder, immune modulator, etc. Further, in view of combination therapies with the existing antibiotics, their potential for new implications for MDRBIs is discussed. The current review may provide essential data for the development of quick, safe, effective, and novel antibiotics for current needs and suggest acuity into its effective implications for inhibiting MDRBIs by repurposing existing drugs.

PMID: 29984648 [PubMed - as supplied by publisher]

Repurposing potential of 1st generation H1-specific antihistamines as anti-filovirus therapeutics.

Antiviral Res. 2018 Jul 04;:

Authors: Schafer A, Cheng H, Xiong R, Soloveva V, Retterer C, Mo F, Bavari S, Thatcher G, Rong L

Abstract
Ebola and Marburg are filoviruses and biosafety level 4 pathogens responsible for causing severe hemorrhagic fevers in humans with mortality rates up to 90%. The most recent outbreak in West Africa resulted in approximately 11,310 deaths in 28,616 reported cases. Currently there are no FDA-approved vaccines or therapeutics to treat infections of these deadly viruses. Recently we screened an FDA-approved drug library and identified numerous G protein-coupled receptor (GPCR) antagonists including antihistamines possessing anti-filovirus properties. Antihistamines are attractive targets for drug repurposing because of their low cost and ease of access due to wide use. In this report we identify common over the counter antihistamines, such as diphenhydramine (Benadryl) and chlorcyclizine (Ahist) as potential candidates for repurposing as anti-filovirus agents. Furthermore, we demonstrate that this potential is wide-spread through the 1st generation of H1-specific antihistamines but is not present in newer drugs or drugs targeting H2, H3 and H4 receptors. We showed that the filovirus entry inhibition is not dependent on the classical antagonism of cell surface histamine or muscarinic acetylcholine receptors but occurs in the endosome, like the cathepsin inhibitor CA-074. Finally, using extensive docking studies we showed the potential for these drugs to bind directly to the EBOV-GP at the same site as toremifene. These findings suggest that the 1st generation antihistamines are excellent candidates for repurposing as anti-filovirus therapeutics and can be further optimized for removal of unwanted histamine or muscarinic receptor interactions without loss of anti-filovirus efficacy.

PMID: 29981374 [PubMed - as supplied by publisher]

Captopril mitigates splenomegaly and myelofibrosis in the Gata1low murine model of myelofibrosis.

J Cell Mol Med. 2018 Jul 04;:

Authors: Corey SJ, Jha J, McCart EA, Rittase WB, George J, Mattapallil JJ, Mehta H, Ognoon M, Bylicky MA, Summers TA, Day RM

Abstract
Allogeneic stem cell transplantation is currently the only curative therapy for primary myelofibrosis (MF), while the JAK2 inhibitor, ruxolitinib. Has been approved only for palliation. Other therapies are desperately needed to reverse life-threatening MF. However, the cell(s) and cytokine(s) that promote MF remain unclear. Several reports have demonstrated that captopril, an inhibitor of angiotensin-converting enzyme that blocks the production of angiotensin II (Ang II), mitigates fibrosis in heart, lung, skin and kidney. Here, we show that captopril can mitigate the development of MF in the Gata1low mouse model of primary MF. Gata1low mice were treated with 79 mg/kg/d captopril in the drinking water from 10 to 12 months of age. At 13 months of age, bone marrows were examined for fibrosis, megakaryocytosis and collagen expression; spleens were examined for megakaryocytosis, splenomegaly and collagen expression. Treatment of Gata1low mice with captopril in the drinking water was associated with normalization of the bone marrow cellularity; reduced reticulin fibres, splenomegaly and megakaryocytosis; and decreased collagen expression. Our findings suggest that treating with the ACE inhibitors captopril has a significant benefit in overcoming pathological changes associated with MF.

PMID: 29971909 [PubMed - as supplied by publisher]