A comprehensive evaluation of connectivity methods for L1000 data.

Brief Bioinform. 2019 Nov 27;:

Authors: Lin K, Li L, Dai Y, Wang H, Teng S, Bao X, Lu ZJ, Wang D

Abstract
The methodologies for evaluating similarities between gene expression profiles of different perturbagens are the key to understanding mechanisms of actions (MoAs) of unknown compounds and finding new indications for existing drugs. L1000-based next-generation Connectivity Map (CMap) data is more than a thousand-fold scale-up of the CMap pilot dataset. Although several systematic evaluations have been performed individually to assess the accuracy of the methodologies for the CMap pilot study, the performance of these methodologies needs to be re-evaluated for the L1000 data. Here, using the drug-drug similarities from the Drug Repurposing Hub database as a benchmark standard, we evaluated six popular published methods for the prediction performance of drug-drug relationships based on the partial area under the receiver operating characteristic (ROC) curve at false positive rates of 0.001, 0.005 and 0.01 (AUC0.001, AUC0.005 and AUC0.01). The similarity evaluating algorithm called ZhangScore was generally superior to other methods and exhibited the highest accuracy at the gene signature sizes ranging from 10 to 200. Further, we tested these methods with an experimentally derived gene signature related to estrogen in breast cancer cells, and the results confirmed that ZhangScore was more accurate than other methods. Moreover, based on scoring results of ZhangScore for the gene signature of TOP2A knockdown, in addition to well-known TOP2A inhibitors, we identified a number of potential inhibitors and at least two of them were the subject of previous investigation. Our studies provide potential guidelines for researchers to choose the suitable connectivity method. The six connectivity methods used in this report have been implemented in R package (https://github.com/Jasonlinchina/RCSM).

PMID: 31774912 [PubMed - as supplied by publisher]

The In Silico Fischer Lock-and-Key Model: The Combined Use of Molecular Descriptors and Docking Poses for the Repurposing of Old Drugs.

Methods Mol Biol. 2020;2089:29-39

Authors: Tutone M, Almerico AM

Abstract
Not always lead compound and/or derivatives are suitable for the specific biological target for which they are designed but, in some cases, discarded compounds proved to be good binders for other biological targets; therefore, drug repurposing constitute a valid alternative to avoid waste of human and financial resources. Our virtual lock-and-key methods, VLKA and Conf-VLKA, furnish a strong support to predict the efficacy of a designed drug a priori its biological evaluation, or the correct biological target for a set of the selected compounds, allowing thus the repurposing of known and unknown, active and inactive compounds.

PMID: 31773645 [PubMed - in process]

Repurposing rosiglitazone, a PPAR-γ agonist and oral antidiabetic, as an inhaled formulation, for the treatment of PAH.

J Control Release. 2018 06 28;280:113-123

Authors: Rashid J, Alobaida A, Al-Hilal TA, Hammouda S, McMurtry IF, Nozik-Grayck E, Stenmark KR, Ahsan F

Abstract
Peroxisome-proliferator-activated-receptor-gamma (PPAR-γ) is implicated, in some capacity, in the pathogenesis of pulmonary arterial hypertension (PAH). Rosiglitazone, an oral antidiabetic and PPAR-γ agonist, has the potential to dilate pulmonary arteries and to attenuate arterial remodeling in PAH. Here, we sought to test the hypothesis that rosiglitazone can be repurposed as inhaled formulation for the treatment of PAH. We have tested this conjecture by preparing and optimizing poly(lactic-co-glycolic) acid (PLGA) based particles of rosiglitazone, assessing the drug particles for pulmonary absorption, investigating the efficacy of the plain versus particulate drug formulation in improving the respiratory hemodynamics in PAH animals, and finally studying the effect of the drug in regulating the molecular markers associated with PAH pathogenesis. The optimized particles were slightly porous and spherical, and released 87.9% ± 6.7% of the drug in 24 h. The elimination half-life of the drug formulated in PLGA particles was 2.5-fold greater than that of the plain drug administered via the same route at the same dose. The optimized formulation, given via the pulmonary route, produced pulmonary selective vasodilation in PAH animals, but oral rosiglitazone had no effect in pulmonary hemodynamics. Rosiglitazone ameliorates the pathogenesis of PAH by balancing the molecular regulators involved in the vasoconstriction and vasodilation of human pulmonary arterial smooth muscle cells. All in all, data generated using intact animal and cellular models point to the conclusion that PLGA particles of an antidiabetic drug can be used for the treatment of a different disease, PAH.

PMID: 29723610 [PubMed - indexed for MEDLINE]

Systematically Prioritizing Candidates in Genome-Based Drug Repurposing.

Assay Drug Dev Technol. 2019 Nov 26;:

Authors: Challa AP, Lavieri RR, Lewis JT, Zaleski NM, Shirey-Rice JK, Harris PA, Aronoff DM, Pulley JM

Abstract
Drug repurposing is the application of approved drugs to treat diseases separate and distinct from their original indications. Herein, we define the scope of all practical precision drug repurposing using DrugBank, a publicly available database of pharmacological agents, and BioVU, a large, de-identified DNA repository linked to longitudinal electronic health records at Vanderbilt University Medical Center. We present a method of repurposing candidate prioritization through integration of pharmacodynamic and marketing variables from DrugBank with quality control thresholds for genomic data derived from the DNA samples within BioVU. Through the synergy of delineated "target-action pairs," along with target genomics, we identify ∼230 "pairs" that represent all practical opportunities for genomic drug repurposing. From this analysis, we present a pipeline of 14 repurposing candidates across 7 disease areas that link to our repurposability platform and present high potential for randomized controlled trial startup in upcoming months.

PMID: 31769998 [PubMed - as supplied by publisher]

Accurate repositioning of an implant interim restoration into the definitive impression to obtain an exact reproduction of tissue contours in the soft tissue cast.

J Prosthet Dent. 2019 Feb;121(2):361-362

Authors: Londono J, Blasi A, Silas J, Abreu A

PMID: 30093129 [PubMed - indexed for MEDLINE]

Repurposing Drugs by In Silico Methods to Target BCR Kinase Domain in Chronic Myeloid Leukemia.

Asian Pac J Cancer Prev. 2019 Nov 01;20(11):3399-3406

Authors: Natarajan A, Thangarajan R, Kesavan S

Abstract
BACKGROUND: Targeted therapy in the form of highly selective tyrosine kinase inhibitors (TKIs) has transformed the treatment of chronic myeloid leukemia (CML). However, mutations in the kinase domain contribute to drug resistance against TKIs which compromises the treatment response. Our aim is to explore regions outside the BCR-ABL oncoprotein to identify potential therapeutic targets to curb drug resistance by targeting growth factor receptor-bound protein-2 (Grb-2) which binds to BCR-ABL at the phosphorylated tyrosine (Y177) thereby activating the Ras and PI3K/AKT signaling pathway.
METHODS: We have used in silico methods to repurpose drugs for identifying their potential to inhibit the binding of Grb-2 with Y177 by occupying the active binding site of the BCR domain.
RESULTS: Differentially expressed genes from GEO dataset were found to be associated with hematopoietic cell lineage, NK cell-mediated cytotoxicity, NF-κB and chemokine signaling, cytokine-cytokine receptor interaction, histidine metabolism and transcriptional misregulation in cancer. The fold recognition method of SPARKS-X tool was used to model the BCR domain (Z-score = 8.21). Connectivity Map generated a drug list based on the gene expression profile, which were docked with BCR. Schrodinger XP glide docking identified Diphosphopyridine nucleotide, Hesperidin, Butirosin, Ovoflavin, and Nor-dihydroguaiaretic acid to show strong interaction in close proximity to the active binding pocket containing Y177 of the target protein and was further validated using iGEMDOCK and Parallelized Open Babel and AutoDock suite Pipeline (POAP).
CONCLUSION: Our study not only extends our current knowledge about repurposing drugs for newer indications but also provides a route towards combinatorial therapy with standard drugs used for CML treatment. However, the efficacy of these repurposed drugs needs to be further investigated using in vitro and in vivo studies.<br />.

PMID: 31759365 [PubMed - in process]

High content phenotypic screening identifies serotonin receptor modulators with selective activity upon breast cancer cell cycle and cytokine signaling pathways.

Bioorg Med Chem. 2019 Nov 09;:115209

Authors: Warchal SJ, Dawson JC, Shepherd E, Munro AF, Hughes RE, Makda A, Carragher NO

Abstract
Heterogeneity in disease mechanisms between genetically distinct patients contributes to high attrition rates in late stage clinical drug development. New personalized medicine strategies aim to identify predictive biomarkers which stratify patients most likely to respond to a particular therapy. However, for complex multifactorial diseases not characterized by a single genetic driver, empirical approaches to identifying predictive biomarkers and the most promising therapies for personalized medicine are required. In vitro pharmacogenomics seeks to correlate in vitro drug sensitivity testing across panels of genetically distinct cell models with genomic, gene expression or proteomic data to identify predictive biomarkers of drug response. However, the vast majority of in vitro pharmacogenomic studies performed to date are limited to dose-response screening upon a single viability assay endpoint. In this article we describe the application of multiparametric high content phenotypic screening and the theta comparative cell scoring method to quantify and rank compound hits, screened at a single concentration, which induce a broad variety of divergent phenotypic responses between distinct breast cancer cell lines. High content screening followed by transcriptomic pathway analysis identified serotonin receptor modulators which display selective activity upon breast cancer cell cycle and cytokine signaling pathways correlating with inhibition of cell growth and survival. These methods describe a new evidence-led approach to rapidly identify compounds which display distinct response between different cell types. The results presented also warrant further investigation of the selective activity of serotonin receptor modulators upon breast cancer cell growth and survival as a potential drug repurposing opportunity.

PMID: 31757681 [PubMed - as supplied by publisher]

Role of dimethyl fumarate in the treatment of glioblastoma multiforme: A review article.

Iran J Neurol. 2019 Jul 06;18(3):127-133

Authors: Ahmadi-Beni R, Najafi A, Savar SM, Mohebbi N, Khoshnevisan A

Abstract
Glioblastoma multiforme (GBM), the most frequent malignant and aggressive primary brain tumor, is characterized by genetically unstable heterogeneous cells, diffused growth pattern, microvascular proliferation, and resistance to chemotherapy. Extensive investigations are being carried out to identify the molecular origin of resistance to chemo- and radio-therapy in GBM and find novel targets for therapy to improve overall survival rate. Dimethyl fumarate (DMF) has been shown to be a safe drug with limited short and long-term side effects, and fumaric acid esters (FAEs), including DMF, present both anti-oxidative and anti-inflammatory activity in different cell types and tissues. DMF has also anti-tumoral and neuroprotective effects and so it could be repurposed in the treatment of this invasive tumor in the future. Here, we have reviewed DMF pharmacokinetics and different mechanisms by which DMF could have therapeutic effects on GBM.

PMID: 31749934 [PubMed]

Mapping actionable pathways and mutations in brain tumours using targeted RNA next generation sequencing.

Acta Neuropathol Commun. 2019 Nov 20;7(1):185

Authors: Lenting K, van den Heuvel CNAM, van Ewijk A, ElMelik D, de Boer R, Tindall E, Wei G, Kusters B, Te Dorsthorst M, Ter Laan M, Huynen MA, Leenders WP

Abstract
Many biology-based precision drugs are available that neutralize aberrant molecular pathways in cancer. Molecular heterogeneity and the lack of reliable companion diagnostic biomarkers for many drugs makes targeted treatment of cancer inaccurate for many individuals. Identifying actionable hyperactive biological pathways in individual cancers may improve this situation.To achieve this we applied a novel targeted RNA next generation sequencing (t/RNA-NGS) technique to surgically obtained glioma tissues. The test combines mutation detection with analysis of biological pathway activities that are involved in tumour behavior in many cancer types (e.g. tyrosine kinase signaling, angiogenesis signaling, immune response, metabolism), via quantitative measurement of transcript levels and splice variants of hundreds of genes. We here present proof of concept that the technique, which uses molecular inversion probes, generates a histology-independent molecular diagnosis and identifies classifiers that are strongly associated with conventional histopathology diagnoses and even with patient prognosis. The test not only confirmed known glioma-associated molecular aberrations but also identified aberrant expression levels of actionable genes and mutations that have so far been considered not to be associated with glioma, opening up the possibility of drug repurposing for individual patients. Its cost-effectiveness makes t/RNA-NGS to an attractive instrument to aid oncologists in therapy decision making.

PMID: 31747973 [PubMed - in process]

Predicting drug-disease associations via sigmoid kernel-based convolutional neural networks.

J Transl Med. 2019 Nov 20;17(1):382

Authors: Jiang HJ, You ZH, Huang YA

Abstract
BACKGROUND: In the process of drug development, computational drug repositioning is effective and resource-saving with regards to its important functions on identifying new drug-disease associations. Recent years have witnessed a great progression in the field of data mining with the advent of deep learning. An increasing number of deep learning-based techniques have been proposed to develop computational tools in bioinformatics.
METHODS: Along this promising direction, we here propose a drug repositioning computational method combining the techniques of Sigmoid Kernel and Convolutional Neural Network (SKCNN) which is able to learn new features effectively representing drug-disease associations via its hidden layers. Specifically, we first construct similarity metric of drugs using drug sigmoid similarity and drug structural similarity, and that of disease using disease sigmoid similarity and disease semantic similarity. Based on the combined similarities of drugs and diseases, we then use SKCNN to learn hidden representations for each drug-disease pair whose labels are finally predicted by a classifier based on random forest.
RESULTS: A series of experiments were implemented for performance evaluation and their results show that the proposed SKCNN improves the prediction accuracy compared with other state-of-the-art approaches. Case studies of two selected disease are also conducted through which we prove the superior performance of our method in terms of the actual discovery of potential drug indications.
CONCLUSION: The aim of this study was to establish an effective predictive model for finding new drug-disease associations. These experimental results show that SKCNN can effectively predict the association between drugs and diseases.

PMID: 31747915 [PubMed - in process]

Leveraging the Medicines for Malaria Venture malaria and pathogen boxes to discover chemical inhibitors of East Coast fever.

Int J Parasitol Drugs Drug Resist. 2019 04;9:80-86

Authors: Nyagwange J, Awino E, Tijhaar E, Svitek N, Pelle R, Nene V

Abstract
Chemotherapy of East Coast fever, a lymphoproliferative cancer-like disease of cattle causing significant economic losses in Africa, is largely dependent on the use of buparvaquone, a drug that was developed in the late 1980's. The disease is caused by the tick-borne protozoan pathogen Theileria parva. Buparvaquone can be used prophylactically and it is also active against tropical theileriosis, caused by the related parasite Theileria annulata. Recently, drug resistance was reported in T. annulata, and could occur in T. parva. Using a 3H-thymidine incorporation assay we screened 796 open source compounds from the Medicines for Malaria Venture (MMV) to discover novel chemicals with potential inhibitory activity to T. parva. We identified nine malaria box compounds and eight pathogen box compounds that inhibited the proliferation of F100TpM, a T. parva infected lymphocyte cell line. However, only two compounds, MMV008212 and MMV688372 represent promising leads with IC50 values of 0.78 and 0.61 μM, respectively, and CC50 values > 5 μM. The remaining compounds exhibited a high degree of toxicity (CC50 values < 1.09 μM) on the proliferation of bovine peripheral blood mononuclear cells stimulated with concanavalin A. We also tested the anti-cancer drug, dasatinib, used in the chemotherapy of some leukemias. Dasatinib was as active and safe as buparvaquone in vitro, with an IC50 of 5 and 4.2 nM, respectively, and CC50 > 10 μM. Our preliminary data suggest that it may be possible to repurpose compounds from the cancer field as well as MMV as novel anti-T. parva molecules.

PMID: 30771616 [PubMed - indexed for MEDLINE]

New life for an old drug: In vitro and in vivo effects of the anthelmintic drug niclosamide against Toxoplasma gondii RH strain.

Int J Parasitol Drugs Drug Resist. 2019 04;9:27-34

Authors: Zhang JL, Si HF, Shang XF, Zhang XK, Li B, Zhou XZ, Zhang JY

Abstract
Toxoplasma gondii is the causative agent of toxoplasmosis and causes serious public health problems. However, the current treatment drugs have many limitations, such as serious side effects. Niclosamide is a salicylanilide drug commonly used to treat worm infections. Herein, the effectiveness of niclosamide for the treatment of T. gondii infection was demonstrated. This study was to evaluate the in vitro and in vivo activities of niclosamide against T. gondii and to explore its mechanism of action. The in vitro cytotoxicity of niclosamide on human foreskin fibroblast cells was evaluated by MTT test. Niclosamide displayed low host toxicity and its 50% inhibitory concentration was 8.3 μg/mL. The in vitro anti-proliferation and anti-invasion effects of niclosamide on T. gondii were determined by quantitative PCR and Giemsa staining. Niclosamide also inhibited T. gondii tachyzoite proliferation, with a 50% effective concentration of 45.3 ng/mL, and reduced the invasion of cells by tachyzoites (17.8% for the parasite control versus 1.9% for the niclosamide group treated with 100 ng/mL). A model was established by infecting BALB/c mice with the virulent RH strain of T. gondii and used to determine the in vivo effects of niclosamide on acute infection. The mice infected with tachyzoites and treated with 160, 200 or 240 mg/kg·bw niclosamide for 7 days exhibited 20%, 40% and 50% survival, respectively. In addition, niclosamide reduced the parasite burden in the blood and tissues of acutely infected mice, and niclosamide induced decreases in the mitochondrial membrane potential (ΔΨm) and adenosine triphosphate (ATP) levels in extracellular tachyzoites, as assessed by laser confocal microscopy and a multilabel reader. These findings indicated that the mechanism of action of niclosamide might be associated with T. gondii mitochondria oxidative phosphorylation. In conclusion, our results support the efficacy of niclosamide as a potential compound for the treatment of T. gondii infection.

PMID: 30599391 [PubMed - indexed for MEDLINE]

A Bayesian machine learning approach for drug target identification using diverse data types.

Nat Commun. 2019 Nov 19;10(1):5221

Authors: Madhukar NS, Khade PK, Huang L, Gayvert K, Galletti G, Stogniew M, Allen JE, Giannakakou P, Elemento O

Abstract
Drug target identification is a crucial step in development, yet is also among the most complex. To address this, we develop BANDIT, a Bayesian machine-learning approach that integrates multiple data types to predict drug binding targets. Integrating public data, BANDIT benchmarked a ~90% accuracy on 2000+ small molecules. Applied to 14,000+ compounds without known targets, BANDIT generated ~4,000 previously unknown molecule-target predictions. From this set we validate 14 novel microtubule inhibitors, including 3 with activity on resistant cancer cells. We applied BANDIT to ONC201-an anti-cancer compound in clinical development whose target had remained elusive. We identified and validated DRD2 as ONC201's target, and this information is now being used for precise clinical trial design. Finally, BANDIT identifies connections between different drug classes, elucidating previously unexplained clinical observations and suggesting new drug repositioning opportunities. Overall, BANDIT represents an efficient and accurate platform to accelerate drug discovery and direct clinical application.

PMID: 31745082 [PubMed - in process]

The Drug Rediscovery protocol facilitates the expanded use of existing anticancer drugs.

Nature. 2019 10;574(7776):127-131

Authors: van der Velden DL, Hoes LR, van der Wijngaart H, van Berge Henegouwen JM, van Werkhoven E, Roepman P, Schilsky RL, de Leng WWJ, Huitema ADR, Nuijen B, Nederlof PM, van Herpen CML, de Groot DJA, Devriese LA, Hoeben A, de Jonge MJA, Chalabi M, Smit EF, de Langen AJ, Mehra N, Labots M, Kapiteijn E, Sleijfer S, Cuppen E, Verheul HMW, Gelderblom H, Voest EE

Abstract
The large-scale genetic profiling of tumours can identify potentially actionable molecular variants for which approved anticancer drugs are available1-3. However, when patients with such variants are treated with drugs outside of their approved label, successes and failures of targeted therapy are not systematically collected or shared. We therefore initiated the Drug Rediscovery protocol, an adaptive, precision-oncology trial that aims to identify signals of activity in cohorts of patients, with defined tumour types and molecular variants, who are being treated with anticancer drugs outside of their approved label. To be eligible for the trial, patients have to have exhausted or declined standard therapies, and have malignancies with potentially actionable variants for which no approved anticancer drugs are available. Here we show an overall rate of clinical benefit-defined as complete or partial response, or as stable disease beyond 16 weeks-of 34% in 215 treated patients, comprising 136 patients who received targeted therapies and 79 patients who received immunotherapy. The overall median duration of clinical benefit was 9 months (95% confidence interval of 8-11 months), including 26 patients who were experiencing ongoing clinical benefit at data cut-off. The potential of the Drug Rediscovery protocol is illustrated by the identification of a successful cohort of patients with microsatellite instable tumours who received nivolumab (clinical benefit rate of 63%), and a cohort of patients with colorectal cancer with relatively low mutational load who experienced only limited clinical benefit from immunotherapy. The Drug Rediscovery protocol facilitates the defined use of approved drugs beyond their labels in rare subgroups of cancer, identifies early signals of activity in these subgroups, accelerates the clinical translation of new insights into the use of anticancer drugs outside of their approved label, and creates a publicly available repository of knowledge for future decision-making.

PMID: 31570881 [PubMed - indexed for MEDLINE]

A network-based approach to identify deregulated pathways and drug effects in metabolic syndrome.

Nat Commun. 2019 Nov 18;10(1):5215

Authors: Misselbeck K, Parolo S, Lorenzini F, Savoca V, Leonardelli L, Bora P, Morine MJ, Mione MC, Domenici E, Priami C

Abstract
Metabolic syndrome is a pathological condition characterized by obesity, hyperglycemia, hypertension, elevated levels of triglycerides and low levels of high-density lipoprotein cholesterol that increase cardiovascular disease risk and type 2 diabetes. Although numerous predisposing genetic risk factors have been identified, the biological mechanisms underlying this complex phenotype are not fully elucidated. Here we introduce a systems biology approach based on network analysis to investigate deregulated biological processes and subsequently identify drug repurposing candidates. A proximity score describing the interaction between drugs and pathways is defined by combining topological and functional similarities. The results of this computational framework highlight a prominent role of the immune system in metabolic syndrome and suggest a potential use of the BTK inhibitor ibrutinib as a novel pharmacological treatment. An experimental validation using a high fat diet-induced obesity model in zebrafish larvae shows the effectiveness of ibrutinib in lowering the inflammatory load due to macrophage accumulation.

PMID: 31740673 [PubMed - in process]

Discovery of disease- and drug-specific pathways through community structures of a literature network.

Bioinformatics. 2019 Nov 18;:

Authors: Pham M, Wilson S, Govindarajan H, Lin CH, Lichtarge O

Abstract
MOTIVATION: In light of the massive growth of the scientific literature, text mining is increasingly used to extract biological pathways. Though multiple tools explore individual connections between genes, diseases, and drugs, few extensively synthesize pathways for specific diseases and drugs.
RESULTS: Through community detection of a literature network, we extracted 3,444 functional gene groups that represented biological pathways for specific diseases and drugs. The network linked Medical Subject Headings (MeSH) terms of genes, diseases, and drugs that co-occurred in publications. The resulting communities detected highly associated genes, diseases, and drugs. These significantly matched current knowledge of biological pathways and predicted future ones in time-stamped experiments. Likewise, disease- and drug-specific communities also recapitulated known pathways for those given diseases and drugs. Moreover, diseases sharing communities had high comorbidity with each other and drugs sharing communities had many common side effects, consistent with related mechanisms. Indeed, the communities robustly recovered mutual targets for drugs (AUROC = 0.75) and shared pathogenic genes for diseases (AUROC = 0.82). These data show that literature communities inform not just known biological processes but also suggest novel disease- and drug-specific mechanisms that may guide disease gene discovery and drug repurposing.
AVAILABILITY: Application tools are available at http://meteor.lichtargelab.org.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID: 31738408 [PubMed - as supplied by publisher]

Sertraline Delivered in Phosphatidylserine Liposomes Is Effective in an Experimental Model of Visceral Leishmaniasis.

Front Cell Infect Microbiol. 2019;9:353

Authors: Romanelli MM, da Costa-Silva TA, Cunha-Junior E, Dias Ferreira D, Guerra JM, Galisteo AJ, Pinto EG, Barbosa LRS, Torres-Santos EC, Tempone AG

Abstract
Liposomes containing phosphatidylserine (PS) has been used for the delivery of drugs into the intramacrophage milieu. Leishmania (L.) infantum parasites live inside macrophages and cause a fatal and neglected viscerotropic disease, with a toxic treatment. Sertraline was studied as a free formulation (SERT) and also entrapped into phosphatidylserine liposomes (LP-SERT) against intracellular amastigotes and in a murine model of visceral leishmaniasis. LP-SERT showed a potent activity against intracellular amastigotes with an EC50 value of 2.5 μM. The in vivo efficacy of SERT demonstrated a therapeutic failure. However, when entrapped into negatively charged liposomes (-58 mV) of 125 nm, it significantly reduced the parasite burden in the mice liver by 89% at 1 mg/kg, reducing the serum levels of the cytokine IL-6 and upregulating the levels of the chemokine MCP-1. Histopathological studies demonstrated the presence of an inflammatory infiltrate with the development of granulomas in the liver, suggesting the resolution of the infection in the treated group. Delivery studies showed fluorescent-labeled LP-SERT in the liver and spleen of mice even after 48 h of administration. This study demonstrates the efficacy of PS liposomes containing sertraline in experimental VL. Considering the urgent need for VL treatments, the repurposing approach of SERT could be a promising alternative.

PMID: 31737574 [PubMed - in process]

Design and optimization strategies for the development of new drugs that treat chronic kidney disease.

Expert Opin Drug Discov. 2019 Nov 18;:1-15

Authors: Ramos AM, Fernández-Fernández B, Pérez-Gómez MV, Carriazo Julio SM, Sanchez-Niño MD, Sanz A, Ruiz-Ortega M, Ortiz A

Abstract
Introduction: Chronic kidney disease (CKD) is characterized by increased risks of progression to end-stage kidney disease requiring dialysis and cardiovascular mortality, predicted to be among the five top causes of death by 2040. Only the design and optimization of novel strategies to develop new drugs to treat CKD will contain this trend. Current therapy for CKD includes nonspecific therapy targeting proteinuria and/or hypertension and cause-specific therapies for diabetic kidney disease, autosomal dominant polycystic kidney disease, glomerulonephritides, Fabry nephropathy, hemolytic uremic syndrome and others.Areas covered: Herein, the authors review the literature on new drugs under development for CKD as well as novel design and development strategies.Expert opinion: New therapies for CKD have become a healthcare priority. Emerging therapies undergoing clinical trials are testing expanded renin-angiotensin system blockade with double angiotensin receptor/endothelin receptor blockers, SGLT2 inhibition, and targeting inflammation, the immune response, fibrosis and the Nrf2 transcription factor. Emerging therapeutic targets include cell senescence, complement activation, Klotho expression preservation and microbiota. Novel approaches include novel model systems that can be personalized (e.g. organoids), unbiased systems biology-based identification of new therapeutic targets, drug databases that speed up drug identification and repurposing, nanomedicines that improve drug delivery and RNA targeting to expand the number of targetable proteins.

PMID: 31736379 [PubMed - as supplied by publisher]

Current state and future perspective of drug repurposing in malignant glioma.

Semin Cancer Biol. 2019 Nov 14;:

Authors: Siegelin MD, Schneider E, Westhoff MA, Wirtz CR, Karpel-Massler G

Abstract
Malignant gliomas are still extremely difficult to treat because complete surgical resection is biologically not feasible due to the invasive nature of the disease and the proximity of tumors to functionally sensitive areas. Moreover, adjuvant therapies are facing a strong therapeutic resistance since the central nervous system is a highly protected environment and the tumor cells display a vast intra-tumoral genetic and epigenetic variation. As a consequence, new therapeutics are urgently needed but the process of developing novel compounds that finally reach clinical application is highly time-consuming and expensive. Drug repurposing is an approach to facilitate and accelerate the discovery of new cancer treatments. In malignant glioma, like in other cancers, pre-existing physiological pathways that regulate cell growth, cell death or cell migration are dysregulated causing malignant transformation. A wide variety of drugs are clinically used to treat non-cancerous diseases interfering with these malignancy-associated pathways. Repurposed drugs have key advantages: They already have approval for clinical use by national regulatory authorities. Moreover, they are for the most part inexpensive and their side effect and safety profiles are well characterized. In this work, we provide an overview on current repurposing strategies for the treatment of malignant glioma.

PMID: 31734137 [PubMed - as supplied by publisher]

Orabase-formulated Gentian Violet Effectively Improved Oral Potentially Malignant Disorder in vitro and in vivo.

Biochem Pharmacol. 2019 Nov 13;:113713

Authors: Wang YY, Xiao LY, Wu PC, Chen YK, Lo S, Hu SCS, Chen YH, Chiu CCC, Yuan SSF

Abstract
Oral cancer is a prevalent cancer in male worldwide. Oral potentially malignant disorders (OMPDs) are the oral mucosa lesions that have high malignant transformation rate to oral cancer. The mainstay for OMPDs treatment includes carbon dioxide (CO2) laser and surgery, which may lead to the side effects of scarring and impaired function of oral cavity in the patients and reduced their willingness to receive curative therapy. Therefore, developing a non-invasive and function-preserving therapy is clinically important. Since development of a novel chemotherapeutic drug requires a lot of time and cost, we applied the high-throughput screening (HTS) approach to identify new bioactivities for FDA-approved drugs, known as drug repurposing. Through this drug repurposing approach, we discovered that gentian violet (GV), which is well known for its antibacterial, antifungal, antihelminthic, antitrypanosomal and antiviral activities, was able to induce significant cell death in DOK oral precancerous cells through ROS production. Moreover, decreased phosphorylation of p53(Ser15) and NFκB(Ser536) was required for GV-induced cell death. In vivo, 3% GV orabase effectively suppressed the progression of DMBA-induced oral precancerous lesions. In conclusion, this new formulation of GV through drug repurposing has the potential to be further developed as a therapeutic drug for OPMD clinically.

PMID: 31733192 [PubMed - as supplied by publisher]