Doxycycline counteracts neuroinflammation restoring memory in Alzheimer's disease mouse models.

Neurobiol Aging. 2018 10;70:128-139

Authors: Balducci C, Santamaria G, La Vitola P, Brandi E, Grandi F, Viscomi AR, Beeg M, Gobbi M, Salmona M, Ottonello S, Forloni G

Abstract
β-Amyloid oligomers (AβOs) and neuroinflammation are 2 main culprits to counteract in Alzheimer's disease (AD). Doxycycline (DOXY) is a second generation antibiotic of the tetracycline class that are promising drugs tested in many clinical trials for a number of different pathologies. DOXY is endowed with antiamyloidogenic properties and better crosses the blood-brain barrier, but its efficacy has never been tested in AD mice. We herein show that 15- to 16-month-old APP/PS1dE9 (APP/PS1) AD mice receiving DOXY under different treatment regimens recovered their memory without plaque reduction. An acute DOXY treatment was, also, sufficient to improve APP/PS1 mouse memory, suggesting an action against soluble AβOs. This was confirmed in an AβO-induced mouse model, where the AβO-mediated memory impairment was abolished by a DOXY pretreatment. Although AβOs induce memory impairment through glial activation, assessing the anti-inflammatory action of DOXY, we found that in both the AβO-treated and APP/PS1 mice, the memory recovery was associated with a lower neuroinflammation. Our data promote DOXY as a hopeful repositioned drug counteracting crucial neuropathological AD targets.

PMID: 30007162 [PubMed - indexed for MEDLINE]

Asymmetric Golgi Repositioning: A Prerequisite for Appropriate Dendrite Formation in Adult-Born Neurons.

J Neurosci. 2018 05 23;38(21):4843-4845

Authors: Sundaram SM, Garg P

PMID: 29793931 [PubMed - indexed for MEDLINE]

Drug Repurposing of Haloperidol: Discovery of New Benzocyclane Derivatives as Potent Antifungal Agents against Cryptococcosis and Candidiasis.

ACS Infect Dis. 2019 Sep 24;:

Authors: Ji C, Liu N, Tu J, Li Z, Han G, Li J, Sheng C

Abstract
Despite the high morbidity and mortality of invasive fungal infections (IFIs), effective and safe antifungal agents are rather limited. Starting from antifungal lead compound haloperidol that was identified by drug repurposing, a series of novel benzocyclane derivatives were designed, synthesized and assayed. Several compounds showed improved antifungal potency and broader antifungal spectrum. Particularly, compound B10 showed good inhibitory activities against a variety of fungal pathogens, and was proven to be inhibitors of several virulence factors important for drug resistance. In the in vivo cryptococcosis and candidiasis models, compound B10 could effectively reduce the brain fungal burden of Cryptococcus neoformans, and synergize with fluconazole to treat resistant Candida albicans infections. Preliminary antifungal mechanism studies revealed that compound B10 regained cell membrane damage and down-regulated the overexpression of ERG11 and MDR1 genes when used in combination with fluconazole. Taken together, haloperidol derivative B10 represent a promising lead compound for the development of new generation of antifungal agents.

PMID: 31550886 [PubMed - as supplied by publisher]

A drug repurposing screening reveals a novel epigenetic activity of hydroxychloroquine.

Eur J Med Chem. 2019 Sep 17;183:111715

Authors: Catalano R, Rocca R, Juli G, Costa G, Maruca A, Artese A, Caracciolo D, Tagliaferri P, Alcaro S, Tassone P, Amodio N

Abstract
Multiple myeloma (MM) is an incurable hematological malignancy driven by several genetic and epigenetic alterations. The hyperactivation of the Polycomb repressive complex 2 (PRC2), a multi-subunit oncogenic histone methyltransferase, has been implicated in the pathogenesis of this malignancy. Upon protein-protein interaction (PPI) between the catalytic subunit EZH2 and EED, PRC2 primarily methylates lysine 27 of histone H3 (H3K27me3), thus modulating the chromatin structure and inducing transcriptional repression. Herein, we highlight a new mechanism of action that can contribute to explain the anti-tumor activity of hydroxychloroquine (HCQ), an anti-malaric agent also known as autophagy inhibitor. By structural studies, we demonstrate that HCQ inhibits the allosteric binding of PRC2 to EED within the H3K27me3-binding pocket, thus antagonizing the PRC2 catalytic activity. In silico results are compatible with the significant reduction of the H3K27me3 levels in MM cells exerted by HCQ. Overall, these findings disclose a novel epigenetic activity of HCQ with potential implications for its clinical repositioning.

PMID: 31550663 [PubMed - as supplied by publisher]

Drug Repurposing for Breast Cancer Therapy: Old Weapon for New Battle.

Semin Cancer Biol. 2019 Sep 21;:

Authors: Aggarwal S, Verma SS, Aggarwal S, Gupta SC

Abstract
Despite tremendous resources being invested in prevention and treatment, breast cancer remains a leading cause of cancer deaths in women globally. The available treatment modalities are very costly and produces severe side effects. Drug repurposing that relate to new uses for old drugs has emerged as a novel approach for drug development. Repositioning of old, clinically approved, off patent non-cancer drugs with known targets, into newer indication is like using old weapons for new battle. The advances in genomics, proteomics and information computational biology has facilitated the process of drug repurposing. Repositioning approach not only fastens the process of drug development but also offers more effective, cheaper, safer drugs with lesser/known side effects. During the last decade, drugs such as alkylating agents, anthracyclins, antimetabolite, CDK4/6 inhibitor, aromatase inhibitor, mTOR inhibitor and mitotic inhibitors has been repositioned for breast cancer treatment. The repositioned drugs have been successfully used for the treatment of most aggressive triple negative breast cancer. The literature review suggest that serendipity plays a major role in the drug development. This article describes the comprehensive overview of the current scenario of drug repurposing for the breast cancer treatment. The strategies as well as several examples of repurposed drugs are provided. The challenges associated with drug repurposing are discussed.

PMID: 31550502 [PubMed - as supplied by publisher]

Drug Repurposing as an Antitumor Agent: Disulfiram-Mediated Carbonic Anhydrase 12 and Anion Exchanger 2 Modulation to Inhibit Cancer Cell Migration.

Molecules. 2019 Sep 19;24(18):

Authors: Hwang S, Shin DM, Hong JH

Abstract
Disulfiram has been used in the treatment of alcoholism and exhibits an anti-tumor effect. However, the intracellular mechanism of anti-tumor activity of Disulfiram remains unclear. In this study, we focused on the modulatory role of Disulfiram via oncogenic factor carbonic anhydrase CA12 and its associated transporter anion exchanger AE2 in lung cancer cell line A549. The surface expression of CA12 and AE2 were decreased by Disulfiram treatment with a time-dependent manner. Disulfiram treatment did not alter the expression of Na+-bicarbonate cotransporters, nor did it affect autophagy regulation. The chloride bicarbonate exchanger activity of A549 cells was reduced by Disulfiram treatment in a time-dependent manner without change in the resting pH level. The expression and activity of AE2 and the expression of CA12 were also reduced by Disulfiram treatment in the breast cancer cell line. An invasion assay and cell migration assay revealed that Disulfiram attenuated the invasion and migration of A549 cells. In conclusion, the attenuation of AE2 and its supportive enzyme CA12, and the inhibitory effect on cell migration by Disulfiram treatment in cancer cells provided the molecular evidence supporting the potential of Disulfiram as an anticancer agent.

PMID: 31546841 [PubMed - in process]

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 2019/09/24

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.

Lovastatin inhibits Toll-like receptor 4 signaling in microglia by targeting its co-receptor myeloid differentiation protein 2 and attenuates neuropathic pain.

Brain Behav Immun. 2019 Sep 19;:

Authors: Peng Y, Zhang X, Zhang T, Grace PM, Li H, Wang Y, Li H, Chen H, Watkins LR, Hutchinson MR, Yin H, Wang X

Abstract
There is growing interest in drug repositioning to find new therapeutic indications for drugs already approved for use in people. Lovastatin is an FDA approved drug that has been used clinically for over a decade as a lipid-lowering medication. While lovastatin is classically considered to act as a hydroxymethylglutaryl (HMG)-CoA reductase inhibitor, the present series of studies reveal a novel lovastatin effect, that being as a Toll-like receptor 4 (TLR4) antagonist. Lovastatin selectively inhibits lipopolysaccharide (LPS)-induced TLR4-NF-κB activation without affecting signaling by other homologous TLRs. In vitro biophysical binding and cellular thermal shift assay (CETSA) show that lovastatin is recognized by TLR4's coreceptor myeloid differentiation protein 2 (MD-2). This finding is supported by molecular dynamics simulations that lovastatin targets the LPS binding pocket of MD-2 and lovastatin binding stabilizes the MD-2 conformation. In vitro studies of BV-2 microglial cells revealed that lovastatin inhibits multiple effects of LPS, including activation of NFkB; mRNA expression of tumor necrosis factor-a, interleukin-6 and cyclo-oxygenase 2; production of nitric oxide and reactive oxygen species; as well as phagocytic activity. Furthermore, intrathecal delivery of lovastatin over lumbosacral spinal cord of rats attenuated both neuropathic pain from sciatic nerve injury and expression of the microglial activation marker CD11 in lumbar spinal cord dorsal horn. Given the well-established role of microglia and proinflammatory signaling in neuropathic pain, these data are supportive that lovastatin, as a TLR4 antagonist, may be productively repurposed for treating chronic pain.

PMID: 31542403 [PubMed - as supplied by publisher]

Drug repositioning via matrix completion with multi-view side information.

IET Syst Biol. 2019 Oct;13(5):267-275

Authors: Hao Y, Cai M, Li L

Abstract
In the process of drug discovery and disease treatment, drug repositioning is broadly studied to identify biological targets for existing drugs. Many methods have been proposed for drug-target interaction prediction by taking into account different kinds of data sources. However, most of the existing methods only use one side information for drugs or targets to predict new targets for drugs. Some recent works have improved the prediction accuracy by jointly considering multiple representations of drugs and targets. In this work, the authors propose a drug-target prediction approach by matrix completion with multi-view side information (MCM) of drugs and proteins from both structural view and chemical view. Different from existing studies for drug-target prediction, they predict drug-target interaction by directly completing the interaction matrix between them. The experimental results show that the MCM method could obtain significantly higher accuracies than the comparison methods. They finally report new drug-target interactions for 26 FDA-approved drugs, and biologically discuss these targets using existing references.

PMID: 31538961 [PubMed - in process]

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

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2019/09/20

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

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

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2019/09/20

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

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

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2019/09/19

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.

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

"drug repositioning" OR "drug repurposing"

These pubmed results were generated on 2019/09/19

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.

Pharmacological approaches to tackle NCLs.

Biochim Biophys Acta Mol Basis Dis. 2019 Sep 12;:165553

Authors: Valerjans K, Maija D, Luis MD

Abstract
Neuronal ceroid lipofuscinoses, also collectively known as Batten disease, are a group of rare monogenic disorders caused by mutations in at least 13 different genes. They are characterized by the accumulation of lysosomal storage material and progressive neurological deterioration with dementia, epilepsy, retinopathy, motor disturbances, and early death [1]. Although the identification of disease-causing genes provides an important step for understanding the molecular mechanisms underlying neuronal ceroid lipofuscinoses, compared to other diseases, obstacles to the development of therapies for these rare diseases include less extensive physiopathology knowledge, limited number of patients to test treatments, and poor commercial interest from the industry. Current therapeutic strategies include enzyme replacement therapies, gene therapies targeting the brain and the eye, cell therapies, and pharmacological drugs that could modulate defective molecular pathways. In this review, we will focus in the emerging therapies based in the identification of small-molecules. Recent advances in high- throughput and high-content screening (HTS and HCS) using relevant cell-based assays and applying automation and imaging analysis algorithms, will allow the screening of a large number of compounds in lesser time. These approaches are particularly useful for drug repurposing for Batten disease, that takes the advantage to search for compounds that have already been tested in humans, thereby reducing significantly the resources needed for translation to clinics.

PMID: 31521819 [PubMed - as supplied by publisher]

Chemogenomic Analysis of the Druggable Kinome and Its Application to Repositioning and Lead Identification Studies.

Cell Chem Biol. 2019 Sep 10;:

Authors: Ravikumar B, Timonen S, Alam Z, Parri E, Wennerberg K, Aittokallio T

Abstract
Owing to the intrinsic polypharmacological nature of most small-molecule kinase inhibitors, there is a need for computational models that enable systematic exploration of the chemogenomic landscape underlying druggable kinome toward more efficient kinome-profiling strategies. We implemented VirtualKinomeProfiler, an efficient computational platform that captures distinct representations of chemical similarity space of the druggable kinome for various drug discovery endeavors. By using the computational platform, we profiled approximately 37 million compound-kinase pairs and made predictions for 151,708 compounds in terms of their repositioning and lead molecule potential, against 248 kinases simultaneously. Experimental testing with biochemical assays validated 51 of the predicted interactions, identifying 19 small-molecule inhibitors of EGFR, HCK, FLT1, and MSK1 protein kinases. The prediction model led to a 1.5-fold increase in precision and 2.8-fold decrease in false-discovery rate, when compared with traditional single-dose biochemical screening, which demonstrates its potential to drastically expedite the kinome-specific drug discovery process.

PMID: 31521622 [PubMed - as supplied by publisher]

Learning Drug Function from Chemical Structure with Convolutional Neural Networks and Random Forests.

J Chem Inf Model. 2019 Sep 13;:

Authors: Meyer JG, Liu S, Miller IJ, Coon JJ, Gitter A

Abstract
Empirical testing of chemicals for drug efficacy costs many billions of dollars every year. The ability to predict the action of molecules in silico would greatly increase the speed and decrease the cost of prioritizing drug leads. Here, we asked whether drug function, defined as MeSH 'Therapeutic Use' classes, can be predicted from only chemical structure. We evaluated two chemical structure-derived drug classification methods, chemical images with convolutional neural networks and molecular fingerprints with random forests, both of which outperformed previous predictions that used drug-induced transcriptomic changes as chemical representations. This suggests that a chemical's structure contains at least as much information about its therapeutic use as the transcriptional cellular response to that chemical. Further, because training data based on chemical structure is not limited to a small set of molecules for which transcriptomic measurements are available, our strategy can leverage more training data to significantly improve predictive accuracy to 83-88%. Finally, we explore use of these models for prediction of side effects and drug repurposing opportunities, and demonstrate the effectiveness of this modeling strategy for multi-label classification.

PMID: 31518132 [PubMed - as supplied by publisher]

Multi-target drugs active against leishmaniasis: A paradigm of drug repurposing.

Eur J Med Chem. 2019 Aug 29;183:111660

Authors: Braga SS

Abstract
This mini-review focuses on leishmanicidal drugs that were sourced from small molecules previously approved for other diseases. The mechanisms of action of these molecules are herein explored, to probe the origins of their inter-species growth inhibitory activities. It is shown how the transversal action of the azoles - fluconazole, posaconazole and itraconazole - in both fungi and Leishmania is due to the occurrence of the same target, lanosterol 14-α-demethylase, in these two groups of species. In turn, the drugs miltefosine and amphotericin B are presented as truly multi-target agents, acting on small molecules, proteins, genes and even organelles. Steps towards future leishmanicidal drug candidates based on the multi-target strategy and on drug repurposing are also briefly presented.

PMID: 31514064 [PubMed - as supplied by publisher]

Internalization of Particulate Delivery Systems by Activated Microglia Influenced the Therapeutic Efficacy of Simvastatin Repurposing for Neuroinflammation.

Int J Pharm. 2019 Sep 09;:118690

Authors: Manickavasagam D, Oyewumi MO

Abstract
We recently evaluated the suitability of polymersome delivery systems in simvastatin repurposing for treating neuroinflammation. The goal of the current study is to elucidate the therapeutic impact of particulate internalization by activated microglia on the resultant anti-inflammatory properties. Thus, we investigated the endocytic mechanism(s) involved in uptake and transport of simvastatin-loaded polymersomes by BV2 microglia cells coupled with delineation of the intracellular pathway(s) involved in regulating anti-inflammatory effects. Our data indicated that internalization of polymersome delivery systems by activated microglial BV2 cells was important in the suppression of nitric oxide (NO), TNF-α and IL-6 production. Further, we observed that the lipid raft/caveolae pathway had the most influential effect on polymersome internalization by microglia cells while clathrin-mediated endocytosis did not play a major role. Enhancement of anti-inflammatory effects of simvastatin could be attributed to inhibition of ERK1/2, JNK and AKT signaling pathways and internalization of polymersome delivery systems in activated microglia. Taken together, our data provided insights into how the intracellular trafficking of delivery systems by microglial could be a useful tool in modulating the desired anti-inflammatory effects of drugs.

PMID: 31513872 [PubMed - as supplied by publisher]

Predicting drug-induced transcriptome responses of a wide range of human cell lines by a novel tensor-train decomposition algorithm.

Bioinformatics. 2019 Jul 15;35(14):i191-i199

Authors: Iwata M, Yuan L, Zhao Q, Tabei Y, Berenger F, Sawada R, Akiyoshi S, Hamano M, Yamanishi Y

Abstract
MOTIVATION: Genome-wide identification of the transcriptomic responses of human cell lines to drug treatments is a challenging issue in medical and pharmaceutical research. However, drug-induced gene expression profiles are largely unknown and unobserved for all combinations of drugs and human cell lines, which is a serious obstacle in practical applications.
RESULTS: Here, we developed a novel computational method to predict unknown parts of drug-induced gene expression profiles for various human cell lines and predict new drug therapeutic indications for a wide range of diseases. We proposed a tensor-train weighted optimization (TT-WOPT) algorithm to predict the potential values for unknown parts in tensor-structured gene expression data. Our results revealed that the proposed TT-WOPT algorithm can accurately reconstruct drug-induced gene expression data for a range of human cell lines in the Library of Integrated Network-based Cellular Signatures. The results also revealed that in comparison with the use of original gene expression profiles, the use of imputed gene expression profiles improved the accuracy of drug repositioning. We also performed a comprehensive prediction of drug indications for diseases with gene expression profiles, which suggested many potential drug indications that were not predicted by previous approaches.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID: 31510663 [PubMed - in process]

Drug repositioning based on bounded nuclear norm regularization.

Bioinformatics. 2019 Jul 15;35(14):i455-i463

Authors: Yang M, Luo H, Li Y, Wang J

Abstract
MOTIVATION: Computational drug repositioning is a cost-effective strategy to identify novel indications for existing drugs. Drug repositioning is often modeled as a recommendation system problem. Taking advantage of the known drug-disease associations, the objective of the recommendation system is to identify new treatments by filling out the unknown entries in the drug-disease association matrix, which is known as matrix completion. Underpinned by the fact that common molecular pathways contribute to many different diseases, the recommendation system assumes that the underlying latent factors determining drug-disease associations are highly correlated. In other words, the drug-disease matrix to be completed is low-rank. Accordingly, matrix completion algorithms efficiently constructing low-rank drug-disease matrix approximations consistent with known associations can be of immense help in discovering the novel drug-disease associations.
RESULTS: In this article, we propose to use a bounded nuclear norm regularization (BNNR) method to complete the drug-disease matrix under the low-rank assumption. Instead of strictly fitting the known elements, BNNR is designed to tolerate the noisy drug-drug and disease-disease similarities by incorporating a regularization term to balance the approximation error and the rank properties. Moreover, additional constraints are incorporated into BNNR to ensure that all predicted matrix entry values are within the specific interval. BNNR is carried out on an adjacency matrix of a heterogeneous drug-disease network, which integrates the drug-drug, drug-disease and disease-disease networks. It not only makes full use of available drugs, diseases and their association information, but also is capable of dealing with cold start naturally. Our computational results show that BNNR yields higher drug-disease association prediction accuracy than the current state-of-the-art methods. The most significant gain is in prediction precision measured as the fraction of the positive predictions that are truly positive, which is particularly useful in drug design practice. Cases studies also confirm the accuracy and reliability of BNNR.
AVAILABILITY AND IMPLEMENTATION: The code of BNNR is freely available at https://github.com/BioinformaticsCSU/BNNR.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID: 31510658 [PubMed - in process]