Predicting associations among drugs, targets and diseases by tensor decomposition for drug repositioning.

BMC Bioinformatics. 2019 Dec 16;20(Suppl 26):628

Authors: Wang R, Li S, Cheng L, Wong MH, Leung KS

Abstract
BACKGROUND: Development of new drugs is a time-consuming and costly process, and the cost is still increasing in recent years. However, the number of drugs approved by FDA every year per dollar spent on development is declining. Drug repositioning, which aims to find new use of existing drugs, attracts attention of pharmaceutical researchers due to its high efficiency. A variety of computational methods for drug repositioning have been proposed based on machine learning approaches, network-based approaches, matrix decomposition approaches, etc. RESULTS: We propose a novel computational method for drug repositioning. We construct and decompose three-dimensional tensors, which consist of the associations among drugs, targets and diseases, to derive latent factors reflecting the functional patterns of the three kinds of entities. The proposed method outperforms several baseline methods in recovering missing associations. Most of the top predictions are validated by literature search and computational docking. Latent factors are used to cluster the drugs, targets and diseases into functional groups. Topological Data Analysis (TDA) is applied to investigate the properties of the clusters. We find that the latent factors are able to capture the functional patterns and underlying molecular mechanisms of drugs, targets and diseases. In addition, we focus on repurposing drugs for cancer and discover not only new therapeutic use but also adverse effects of the drugs. In the in-depth study of associations among the clusters of drugs, targets and cancer subtypes, we find there exist strong associations between particular clusters.
CONCLUSIONS: The proposed method is able to recover missing associations, discover new predictions and uncover functional clusters of drugs, targets and diseases. The clustering of drugs, targets and diseases, as well as the associations among the clusters, provides a new guiding framework for drug repositioning.

PMID: 31839008 [PubMed - in process]

Therapies for rare diseases: therapeutic modalities, progress and challenges ahead.

Nat Rev Drug Discov. 2019 Dec 13;:

Authors: Tambuyzer E, Vandendriessche B, Austin CP, Brooks PJ, Larsson K, Miller Needleman KI, Valentine J, Davies K, Groft SC, Preti R, Oprea TI, Prunotto M

Abstract
Most rare diseases still lack approved treatments despite major advances in research providing the tools to understand their molecular basis, as well as legislation providing regulatory and economic incentives to catalyse the development of specific therapies. Addressing this translational gap is a multifaceted challenge, for which a key aspect is the selection of the optimal therapeutic modality for translating advances in rare disease knowledge into potential medicines, known as orphan drugs. With this in mind, we discuss here the technological basis and rare disease applicability of the main therapeutic modalities, including small molecules, monoclonal antibodies, protein replacement therapies, oligonucleotides and gene and cell therapies, as well as drug repurposing. For each modality, we consider its strengths and limitations as a platform for rare disease therapy development and describe clinical progress so far in developing drugs based on it. We also discuss selected overarching topics in the development of therapies for rare diseases, such as approval statistics, engagement of patients in the process, regulatory pathways and digital tools.

PMID: 31836861 [PubMed - as supplied by publisher]

Drug repurposing to improve treatment of rheumatic autoimmune inflammatory diseases.

Nat Rev Rheumatol. 2019 Dec 12;:

Authors: Kingsmore KM, Grammer AC, Lipsky PE

Abstract
The past century has been characterized by intensive efforts, within both academia and the pharmaceutical industry, to introduce new treatments to individuals with rheumatic autoimmune inflammatory diseases (RAIDs), often by 'borrowing' treatments already employed in one RAID or previously used in an entirely different disease, a concept known as drug repurposing. However, despite sharing some clinical manifestations and immune dysregulation, disease pathogenesis and phenotype vary greatly among RAIDs, and limited understanding of their aetiology has made repurposing drugs for RAIDs challenging. Nevertheless, the past century has been characterized by different 'waves' of repurposing. Early drug repurposing occurred in academia and was based on serendipitous observations or perceived disease similarity, often driven by the availability and popularity of drug classes. Since the 1990s, most biologic therapies have been developed for one or several RAIDs and then tested among the others, with varying levels of success. The past two decades have seen data-driven repurposing characterized by signature-based approaches that rely on molecular biology and genomics. Additionally, many data-driven strategies employ computational modelling and machine learning to integrate multiple sources of data. Together, these repurposing periods have led to advances in the treatment for many RAIDs.

PMID: 31831878 [PubMed - as supplied by publisher]

Comparison Study of Computational Prediction Tools for Drug-Target Binding Affinities.

Front Chem. 2019;7:782

Authors: Thafar M, Raies AB, Albaradei S, Essack M, Bajic VB

Abstract
The drug development is generally arduous, costly, and success rates are low. Thus, the identification of drug-target interactions (DTIs) has become a crucial step in early stages of drug discovery. Consequently, developing computational approaches capable of identifying potential DTIs with minimum error rate are increasingly being pursued. These computational approaches aim to narrow down the search space for novel DTIs and shed light on drug functioning context. Most methods developed to date use binary classification to predict if the interaction between a drug and its target exists or not. However, it is more informative but also more challenging to predict the strength of the binding between a drug and its target. If that strength is not sufficiently strong, such DTI may not be useful. Therefore, the methods developed to predict drug-target binding affinities (DTBA) are of great value. In this study, we provide a comprehensive overview of the existing methods that predict DTBA. We focus on the methods developed using artificial intelligence (AI), machine learning (ML), and deep learning (DL) approaches, as well as related benchmark datasets and databases. Furthermore, guidance and recommendations are provided that cover the gaps and directions of the upcoming work in this research area. To the best of our knowledge, this is the first comprehensive comparison analysis of tools focused on DTBA with reference to AI/ML/DL.

PMID: 31824921 [PubMed]

Ifenprodil and Flavopiridol Identified by Genomewide RNA Interference Screening as Effective Drugs To Ameliorate Murine Acute Lung Injury after Influenza A H5N1 Virus Infection.

mSystems. 2019 Dec 10;4(6):

Authors: Zhang C, Zhang Y, Qin Y, Zhang Q, Liu Q, Shang D, Lu H, Li X, Zhou C, Huang F, Jin N, Jiang C

Abstract
Due to the limitations of effective treatments, avian influenza A H5N1 virus is the most lethal influenza virus strain that causes severe acute lung injury (ALI). To develop effective drugs ameliorating H5N1-induced ALI, we explore an RNA interference (RNAi) screening method to monitor changes in cell death induced by H5N1 infection. We performed RNAi screening on 19,424 genes in A549 lung epithelial cells and examined cell death induced by H5N1 infection. These screens identified 1,137 host genes for which knockdown altered cell viability by over 20%. DrugBank searches of these 1,137 host genes identified 146 validated druggable target genes with 372 drug candidates. We obtained 104 commercially available drugs with 65 validated target genes and examined their improvement of cell viability following H5N1 infection. We identified 28 drugs that could significantly recover cell viability following H5N1 infection and tested 10 in an H5N1-induced-ALI mouse model. The neurological drug ifenprodil and the anticancer drug flavopiridol markedly decreased leukocyte infiltration and lung injury scores in infected mouse lungs, significantly ameliorated edema in infected mouse lung tissues, and significantly improved the survival of H5N1-infected mice. Ifenprodil is an antagonist of the N-methyl-d-aspartate (NMDA) receptor, which is linked to inflammation and lung injury. Flavopiridol is an inhibitor of cyclin-dependent kinase 4 (CDK4), which is linked to leukocyte migration and lung injury. These results suggest that ifenprodil and flavopiridol represent novel remedies against potential H5N1 epidemics in addition to their proven indications. Furthermore, our strategy for identifying repurposable drugs could be a general approach for other diseases.IMPORTANCE Drug repurposing is a quick and economical strategy for developing new therapies with approved drugs. H5N1 is a highly pathogenic avian influenza virus subtype that can cause severe acute lung injury (ALI) and a high mortality rate due to limited treatments. The use of RNA interference (RNAi) is a reliable approach to identify essential genes in diseases. In most genomewide RNAi screenings, virus replication is the readout of interference. Since H5N1 virus infection could induce significant cell death and the percentage of cell death is associated with virus lethality, we designed a genomewide RNAi screening method to identify repurposable drugs against H5N1 virus with cell death as the readout. We discovered that the neurological drug ifenprodil and the anticancer drug flavopiridol could effectively ameliorate murine ALI after influenza A H5N1 virus infection, suggesting that they might be novel remedies for H5N1 virus-induced ALI in addition to the traditional indications.

PMID: 31822599 [PubMed]

In silico repositioning of etidronate as a potential inhibitor of the Trypanosoma cruzi enolase.

J Mol Graph Model. 2019 Dec 03;95:107506

Authors: Valera-Vera EA, Sayé M, Reigada C, Miranda MR, Pereira CA

Abstract
Enolase is a glycolytic enzyme that catalyzes the interconversion between 2-phosphoglycerate and phosphoenolpyruvate. In trypanosomatids, enolase was proposed as a key enzyme after in silico and in vivo analysis and it was validated as a protein essential for the survival of the parasite. Therefore, enolase constitutes an interesting enzyme target for the identification of drugs against Chagas disease. In this work, a combined virtual screening strategy was implemented, employing similarity virtual screening, molecular docking, and molecular dynamics. First, two known enolase inhibitors and the enzyme substrates were used as queries for the similarity screening on the Sweetlead database using five different algorithms. Compounds retrieved in the top 10 of at least three search algorithms were selected for further analysis, resulting in six compounds of medical use (etidronate, pamidronate, fosfomycin, acetohydroxamate, triclofos, and aminohydroxybutyrate). Molecular docking simulations and pose re-scoring predicted that binding with acetohydroxamate and triclofos would be weak, while fosfomycin and aminohydroxybutyrate predicted binding is experimentally implausible. Docking poses obtained for etidronate, pamidronate, and PEP were used for molecular dynamics calculations to describe their mode of binding. From the obtained results, we propose etidronate as a potential TcENO inhibitor and describe molecular motifs to be taken into account in the repurposing or design of drugs targeting this enzyme active site.

PMID: 31821935 [PubMed - as supplied by publisher]

Benzethonium chloride suppresses lung cancer tumorigenesis through inducing p38-mediated cyclin D1 degradation.

Am J Cancer Res. 2019;9(11):2397-2412

Authors: Huang XH, Wang Y, Hong P, Yang J, Zheng CC, Yin XF, Song WB, Xu WW, Li B, He QY

Abstract
Lung cancer is the leading cause of cancer-related deaths worldwide, but effective therapeutics is limited. This study aims to identify novel anticancer strategy from a Food and Drug Administration (FDA)-approved drug library consisting of 528 compounds. Benzethonium Chloride (BZN), a FDA-approved drug for anti-infective, was found to markedly induce apoptosis and inhibit proliferation and colony formation ability of lung cancer cells in dose- and time-dependent manners. BZN also enhanced the sensitivity of lung cancer cells to gefitinib, the first-line treatment strategy for selected lung cancer patients. Furthermore, BZN significantly delayed the growth of tumor xenografts in nude mice by increasing apoptosis and decreasing Ki-67 proliferation index, without obvious toxic effects to the vital organs of animals. Mechanistically, quantitative proteomics coupled with bioinformatics analyses and a series of functional assays demonstrated that BZN induced cell cycle arrest at G1 phase, and this was associated with an increase in p38-mediated phosphorylation at threonine 286 (T286) and accelerated degradation of cyclin D1. Our findings provide the first evidence that BZN could be a promising therapeutic agent in lung cancer treatment.

PMID: 31815042 [PubMed]

Landscape of cancer diagnostic biomarkers from specifically expressed genes.

Brief Bioinform. 2019 Dec 08;:

Authors: Lv Y, Lin SY, Hu FF, Ye Z, Zhang Q, Wang Y, Guo AY

Abstract
Although there has been great progress in cancer treatment, cancer remains a serious health threat to humans because of the lack of biomarkers for diagnosis, especially for early-stage diagnosis. In this study, we comprehensively surveyed the specifically expressed genes (SEGs) using the SEGtool based on the big data of gene expression from the The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) projects. In 15 solid tumors, we identified 233 cancer-specific SEGs (cSEGs), which were specifically expressed in only one cancer and showed great potential to be diagnostic biomarkers. Among them, three cSEGs (OGDH, MUDENG and ACO2) had a sample frequency >80% in kidney cancer, suggesting their high sensitivity. Furthermore, we identified 254 cSEGs as early-stage diagnostic biomarkers across 17 cancers. A two-gene combination strategy was applied to improve the sensitivity of diagnostic biomarkers, and hundreds of two-gene combinations were identified with high frequency. We also observed that 13 SEGs were targets of various drugs and nearly half of these drugs may be repurposed to treat cancers with SEGs as their targets. Several SEGs were regulated by specific transcription factors in the corresponding cancer, and 39 cSEGs were prognosis-related genes in 7 cancers. This work provides a survey of cancer biomarkers for diagnosis and early diagnosis and new insights to drug repurposing. These biomarkers may have great potential in cancer research and application.

PMID: 31814027 [PubMed - as supplied by publisher]

Deep learning of pharmacogenomics resources: moving towards precision oncology.

Brief Bioinform. 2019 Dec 08;:

Authors: Chiu YC, Chen HH, Gorthi A, Mostavi M, Zheng S, Huang Y, Chen Y

Abstract
The recent accumulation of cancer genomic data provides an opportunity to understand how a tumor's genomic characteristics can affect its responses to drugs. This field, called pharmacogenomics, is a key area in the development of precision oncology. Deep learning (DL) methodology has emerged as a powerful technique to characterize and learn from rapidly accumulating pharmacogenomics data. We introduce the fundamentals and typical model architectures of DL. We review the use of DL in classification of cancers and cancer subtypes (diagnosis and treatment stratification of patients), prediction of drug response and drug synergy for individual tumors (treatment prioritization for a patient), drug repositioning and discovery and the study of mechanism/mode of action of treatments. For each topic, we summarize current genomics and pharmacogenomics data resources such as pan-cancer genomics data for cancer cell lines (CCLs) and tumors, and systematic pharmacologic screens of CCLs. By revisiting the published literature, including our in-house analyses, we demonstrate the unprecedented capability of DL enabled by rapid accumulation of data resources to decipher complex drug response patterns, thus potentially improving cancer medicine. Overall, this review provides an in-depth summary of state-of-the-art DL methods and up-to-date pharmacogenomics resources and future opportunities and challenges to realize the goal of precision oncology.

PMID: 31813953 [PubMed - as supplied by publisher]

Long acting GLP-1 analog liraglutide ameliorates skeletal muscle atrophy in rodents.

Metabolism. 2019 Dec 05;:154044

Authors: Gurjar AA, Kushwaha S, Chattopadhyay S, Das N, Pal S, China SP, Kumar H, Trivedi AK, Guha R, Chattopadhyay N, Sanyal S

Abstract
BACKGROUND: Skeletal muscle atrophy is characterized by muscle wasting with partial or complete functional loss. Skeletal muscle atrophy severely affects the quality of life and currently, there is no available therapy except for spinal muscular atrophy.
OBJECTIVE: Drug repositioning is a promising strategy that reduces cost and time due to prior availability of safety and toxicity details. Here we investigated myogenic and anti-atrophy effects of glucagon-like peptide-1 (GLP-1) analog liraglutide.
METHODS: We used several in vitro atrophy models in C2C12 cells and in vivo models in Sprague Dawley rats to study Liraglutide's efficacy. QPCR and western blotting were used to assess cAMP-dependent signaling pathways specifically activated by liraglutide. Therapeutic efficacy of liraglutide was investigated by histological analysis of transverse muscle sections followed by morphometry. Myogenic capacity was investigated by immunostaining for myogenic factors.
RESULTS: Liraglutide induced myogenesis in C2C12 myoblasts through GLP-1 receptor via a cAMP-dependent complex network of signaling events involving protein kinase A, phosphoinositide 3-kinase/protein kinase B, p38 mitogen-activated protein kinase and extracellular signal-regulated kinase. Liraglutide imparted protection against freeze injury, denervation, and dexamethasone -induced skeletal muscle atrophy and improved muscular function in all these models. In a therapeutic mode, liraglutide restored myofibrillar architecture in ovariectomy-induced atrophy. Anti-atrophy actions of liraglutide involved suppression of atrogene expression and enhancement in expression of myogenic factors.
CONCLUSION: Liraglutide imparted protection and restored myofybrillar architecture in diverse models of muscle atrophy. Given its potent anti-atrophy, and recently reported osteoanabolic effects, we propose liraglutide's clinical evaluation in skeletal muscle atrophy and musculoskeletal disorders associated with diverse pathologies.

PMID: 31812628 [PubMed - as supplied by publisher]

The first wide-scale drug repurposing screen using the Prestwick Chemical Library (1200 bioactive molecules) against Neisseria gonorrhoeae identifies high in vitro activity of auranofin and many additional drugs.

APMIS. 2019 Dec 07;:

Authors: Foerster S, Gustafsson TN, Rita Brochado A, Desilvestro V, Typas A, Unemo M

Abstract
Treatment options for gonorrhoea are scarce. Drug repurposing of bioactive molecules approved for other conditions might therefore be of value. We developed a method for wide-scale, systematic drug repurposing screen to identify molecules with activity against Neisseria gonorrhoeae and screened the Prestwick Chemical Library (1200 FDA-approved drugs). As a proof-of-concept, we further examined one promising and interesting screening hit (auranofin; antirheumatic agent). Three WHO gonococcal reference strains (WHO F, O, P) were used for the Library screening. The strains were grown in presence of a fixed concentration of the library drugs in 384-well plates for 12 hours and the remaining bacterial respiration, to reflect growth, was then quantitatively measured using optical density (OD) 450 nm and a resazurin assay. The activity of auranofin was further examined using in vitro susceptibility testing (minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC)) against genetically diverse antimicrobial-resistant N. gonorrhoeae strains and time-kill assays. Sixty-eight molecules significantly inhibited bacterial growth of WHO F, O and, P. Auranofin showed potent in vitro bactericidal activity (in MIC-, MBC-, and time-kill assays) against four WHO reference strains. No cross resistance between auranofin and any antimicrobial currently or previously used for gonorrhoea treatment was found when examining 51 selected antimicrobial-resistant gonococcal strains. In conclusion, this is the first wide-scale systematic screening effort for repurposing drugs for future treatment of gonorrhoea. Additional studies examining mechanism(s) of action, resistance development, in vivo anti-gonococcal activity, and pharmacokinetics/pharmacodynamics for gonococcal infections of auranofin and several other significant screening hits would be valuable.

PMID: 31811739 [PubMed - as supplied by publisher]

Repurposing of Iloperidone: Antihypertensive and Ocular Hypotensive Activity in Animals.

Eur J Pharm Sci. 2019 Dec 03;:105173

Authors: Joshi SV, Patel EP, Vyas BA, Lodha SR, Kalyankar GG

Abstract
PURPOSE: Iloperidone, second generation antipsychotic drug, reported in clinical trial to produce orthostatic hypotension as side effect. It was claimed to be antagonistic at alpha adrenergic receptor in central nervous system. We evaluated effect of Iloperidone on peripheral alpha 1 adrenoreceptor by in silico and in vitro methods while in vivo hypotensive, antihypertensive and ocular hypotensive activity was evaluated in animals.
METHODS: Pharmacological activity prediction of Iloperidone was done using PASSOnline and SwissTargetPrediction softwares and molecular docking with Alpha 1A adrenoreceptor using AutoDock Vina. Hypotensive activity in normotensive and antihypertensive activity against DOCA-salt induced hypertension in rats were evaluated at doses 0.03 mg/Kg and 0.1 mg/Kg, i.p of Iloperidone. Blood pressure was measured by invasive blood pressure measurement technique using PowerLab 4/30 and intraocular pressure was measured using digital tonometer.
RESULTS: Iloperidone (0.1 mg/Kg) showed significant decrease in blood pressure (38.96±1.1%) in normotensive rats, while in DOCA salt induced hypertensive rats, systolic blood pressure was found to be decreased by 29.04 ± 1.45 % and 31.43 ± 1.21 % in 0.03 mg/Kg and 0.1 mg/Kg treated rats respectively. Iloperidone prevented rise in systolic BP with adrenaline. Intraocular pressure was found to be decreased by 36.66 ± 3.15 % in rabbits after 1 hour of instillation of 0.1% Iloperidone.
CONCLUSION: Iloperidone exerted hypotensive and/or anti-hypertensive activity in rats and ocular hypotensive activity in rabbits.

PMID: 31809906 [PubMed - as supplied by publisher]

The pathogenesis of systemic lupus erythematosus: Harnessing big data to understand the molecular basis of lupus.

J Autoimmun. 2019 Dec 02;:102359

Authors: Catalina MD, Owen KA, Labonte AC, Grammer AC, Lipsky PE

Abstract
Systemic lupus erythematosus (SLE) is a chronic, systemic autoimmune disease that causes damage to multiple organ systems. Despite decades of research and available murine models that capture some aspects of the human disease, new treatments for SLE lag behind other autoimmune diseases such as Rheumatoid Arthritis and Crohn's disease. Big data genomic assays have transformed our understanding of SLE by providing important insights into the molecular heterogeneity of this multigenic disease. Gene wide association studies have demonstrated more than 100 risk loci, supporting a model of multiple genetic hits increasing SLE risk in a non-linear fashion, and providing evidence of ancestral diversity in susceptibility loci. Epigenetic studies to determine the role of methylation, acetylation and non-coding RNAs have provided new understanding of the modulation of gene expression in SLE patients and identified new drug targets and biomarkers for SLE. Gene expression profiling has led to a greater understanding of the role of myeloid cells in the pathogenesis of SLE, confirmed roles for T and B cells in SLE, promoted clinical trials based on the prominent interferon signature found in SLE patients, and identified candidate biomarkers and cellular signatures to further drug development and drug repurposing. Gene expression studies are advancing our understanding of the underlying molecular heterogeneity in SLE and providing hope that patient stratification will expedite new therapies based on personal molecular signatures. Although big data analyses present unique interpretation challenges, both computationally and biologically, advances in machine learning applications may facilitate the ability to predict changes in SLE disease activity and optimize therapeutic strategies.

PMID: 31806421 [PubMed - as supplied by publisher]

Combinatorial screening of a panel of FDA-approved drugs identifies several candidates with anti-Ebola activities.

Biochem Biophys Res Commun. 2019 Dec 02;:

Authors: Du X, Zuo X, Meng F, Wu F, Zhao X, Li C, Cheng G, Qin FX

Abstract
Ebola virus (EBOV), pathogen of Ebola hemorrhagic fever (EHF), is an enveloped filamental RNA virus. Recently, the EHF crisis occurred in the Democratic Republic of the Congo again highlights the urgency for its clinical treatments. However, no Food and Drug Administration (FDA)-approved therapeutics are currently available. Drug repurposing screening is a time- and cost-effective approach for identifying anti-EBOV therapeutics. Here, by combinatorial screening using pseudovirion and minigenome replicon systems we have identified several FDA-approved drugs with significant anti-EBOV activities. These potential candidates include azithromycin, clomiphene, chloroquine, digitoxin, epigallocatechin-gallate, fluvastatin, tetrandrine and tamoxifen. Mechanistic studies revealed that fluvastatin inhibited EBOV pseudovirion entry by blocking the pathway of mevalonate biosynthesis, while the inhibitory effect of azithromycin on EBOV maybe due to its intrinsic cationic amphiphilic structure altering the homeostasis of later endosomal vesicle similar as tamoxifen. Moreover, based on structure and pathway analyses, the anti-EBOV activity has been extended to other family members of statins, such as simvastatin, and multiple other cardiac glycoside drugs, some of which exhibited even stronger activities. More importantly, in searching for drug interaction, we found various synergy between several anti-EBOV drug combinations, showing substantial and powerful synergistic against EBOV infection. In conclusion, our work illustrates a successful and productive approach to identify new mechanisms and targets for treating EBOV infection by combinatorial screening of FDA-approved drugs.

PMID: 31806372 [PubMed - as supplied by publisher]

Teaching an Old Molecule New Tricks: Drug Repositioning for Duchenne Muscular Dystrophy.

Int J Mol Sci. 2019 Nov 30;20(23):

Authors: Vitiello L, Tibaudo L, Pegoraro E, Bello L, Canton M

Abstract
: Duchenne muscular dystrophy (DMD) is one of the most severe forms of inherited muscular dystrophies. The disease is caused by the lack of dystrophin, a structurally essential protein; hence, a definitive cure would necessarily have to pass through some form of gene and/or cell therapy. Cell- and genetic-based therapeutics for DMD have been explored since the 1990s and recently, two of the latter have been approved for clinical use, but their efficacy is still very low. In parallel, there have been great ongoing efforts aimed at targeting the downstream pathogenic effects of dystrophin deficiency using classical pharmacological approaches, with synthetic or biological molecules. However, as it is always the case with rare diseases, R&D costs for new drugs can represent a major hurdle for researchers and patients alike. This problem can be greatly alleviated by experimenting the use of molecules that had originally been developed for different conditions, a process known as drug repurposing or drug repositioning. In this review, we will describe the state of the art of such an approach for DMD, both in the context of clinical trials and pre-clinical studies.

PMID: 31801292 [PubMed - in process]

Systematic Approach for Drug Repositioning of Anti-Epileptic Drugs.

Diagnostics (Basel). 2019 Nov 30;9(4):

Authors: Ko Y, Lee C, Lee Y, Lee JS

Abstract
Epilepsy is a central neurological disorder affecting individuals of all ages and causing unpredictable seizures. In spite of the improved efficacy of new antiepileptic drugs and novel therapy, there are still approximately 20%~30% of patients, who have either intractable or uncontrolled seizures. The epilepsy drug-target network (EDT) is constructed and successfully demonstrates the characteristics and efficacy of popularly used AEDs through the identification of causative genes for 60 epilepsy patients. We discovered that the causative genes of most intractable patients were not the targets of existing AEDs, as well as being very far from the etiological mechanisms of existing AEDs in the functional networks. We show that the existence of new drugs that target the causative genes of intractable epilepsy patients, which will be potential candidates for refractory epilepsy patients. Our systematic approach demonstrates a new possibility for drug repositioning through the combination of the drug-target and functional networks.

PMID: 31801232 [PubMed]

Discovery of Small Molecules for the Reversal of T Cell Exhaustion.

Cell Rep. 2019 Dec 03;29(10):3293-3302.e3

Authors: Marro BS, Zak J, Zavareh RB, Teijaro JR, Lairson LL, Oldstone MBA

Abstract
Inhibitory receptors (IRs) function as critical regulators of immune responses by tempering T cell activity. In humans, several persisting viruses as well as cancers exploit IR signaling by upregulating IR ligands, resulting in suppression of T cell function (i.e., exhaustion). This allows escape from immune surveillance and continuation of disease. Here, we report the design, implementation, and results of a phenotypic high-throughput screen for molecules that modulate CD8+ T cell activity. We identify 19 compounds from the ReFRAME drug-repurposing collection that restore cytokine production and enhance the proliferation of exhausted T cells. Analysis of our top hit, ingenol mebutate, a protein kinase C (PKC) inducing diterpene ester, reveals a role for this molecule in overriding the suppressive signaling cascade mediated by IR signaling on T cells. Collectively, these results demonstrate a disease-relevant methodology for identifying modulators of T cell function and reveal new targets for immunotherapy.

PMID: 31801090 [PubMed - in process]

A Literature-Based Knowledge Graph Embedding Method for Identifying Drug Repurposing Opportunities in Rare Diseases.

Pac Symp Biocomput. 2020;25:463-474

Authors: Sosa DN, Derry A, Guo M, Wei E, Brinton C, Altman RB

Abstract
Millions of Americans are affected by rare diseases, many of which have poor survival rates. However, the small market size of individual rare diseases, combined with the time and capital requirements of pharmaceutical R&D, have hindered the development of new drugs for these cases. A promising alternative is drug repurposing, whereby existing FDA-approved drugs might be used to treat diseases different from their original indications. In order to generate drug repurposing hypotheses in a systematic and comprehensive fashion, it is essential to integrate information from across the literature of pharmacology, genetics, and pathology. To this end, we leverage a newly developed knowledge graph, the Global Network of Biomedical Relationships (GNBR). GNBR is a large, heterogeneous knowledge graph comprising drug, disease, and gene (or protein) entities linked by a small set of semantic themes derived from the abstracts of biomedical literature. We apply a knowledge graph embedding method that explicitly models the uncertainty associated with literature-derived relationships and uses link prediction to generate drug repurposing hypotheses. This approach achieves high performance on a gold-standard test set of known drug indications (AUROC = 0.89) and is capable of generating novel repurposing hypotheses, which we independently validate using external literature sources and protein interaction networks. Finally, we demonstrate the ability of our model to produce explanations of its predictions.

PMID: 31797619 [PubMed - in process]

Drug Repurposing of Bromodomain Inhibitors as Potential Novel Therapeutic Leads for Lymphatic Filariasis Guided by Multispecies Transcriptomics.

mSystems. 2019 Dec 03;4(6):

Authors: Chung M, Teigen LE, Libro S, Bromley RE, Olley D, Kumar N, Sadzewicz L, Tallon LJ, Mahurkar A, Foster JM, Michalski ML, Dunning Hotopp JC

Abstract
To better understand the transcriptomic interplay of organisms associated with lymphatic filariasis, we conducted multispecies transcriptome sequencing (RNA-Seq) on the filarial nematode Brugia malayi, its Wolbachia endosymbiont wBm, and its laboratory vector Aedes aegypti across the entire B. malayi life cycle. In wBm, transcription of the noncoding 6S RNA suggests that it may be a regulator of bacterial cell growth, as its transcript levels correlate with bacterial replication rates. For A. aegypti, the transcriptional response reflects the stress that B. malayi infection exerts on the mosquito with indicators of increased energy demand. In B. malayi, expression modules associated with adult female samples consistently contained an overrepresentation of genes involved in chromatin remodeling, such as the bromodomain-containing proteins. All bromodomain-containing proteins encoded by B. malayi were observed to be upregulated in the adult female, embryo, and microfilaria life stages, including 2 members of the bromodomain and extraterminal (BET) protein family. The BET inhibitor JQ1(+), originally developed as a cancer therapeutic, caused lethality of adult worms in vitro, suggesting that it may be a potential therapeutic that can be repurposed for treating lymphatic filariasis.IMPORTANCE The current treatment regimen for lymphatic filariasis is mostly microfilaricidal. In an effort to identify new drug candidates for lymphatic filariasis, we conducted a three-way transcriptomics/systems biology study of one of the causative agents of lymphatic filariasis, Brugia malayi, its Wolbachia endosymbiont wBm, and its vector host Aedes aegypti at 16 distinct B. malayi life stages. B. malayi upregulates the expression of bromodomain-containing proteins in the adult female, embryo, and microfilaria stages. In vitro, we find that the existing cancer therapeutic JQ1(+), which is a bromodomain and extraterminal protein inhibitor, has adulticidal activity in B. malayi.

PMID: 31796568 [PubMed]

Induced pluripotent stem cell-based Drug Repurposing for Amyotrophic lateral sclerosis Medicine (iDReAM) study: protocol for a phase I dose escalation study of bosutinib for amyotrophic lateral sclerosis patients.

BMJ Open. 2019 Dec 02;9(12):e033131

Authors: Imamura K, Izumi Y, Banno H, Uozumi R, Morita S, Egawa N, Ayaki T, Nagai M, Nishiyama K, Watanabe Y, Hanajima R, Oki R, Fujita K, Takahashi N, Ikeda T, Shimizu A, Morinaga A, Hirohashi T, Fujii Y, Takahashi R, Inoue H

Abstract
INTRODUCTION: Amyotrophic lateral sclerosis (ALS) is a progressive and severe neurodegenerative disease caused by motor neuron death. There have as yet been no fundamental curative medicines, and the development of a medicine for ALS is urgently required. Induced pluripotent stem cell (iPSC)-based drug repurposing identified an Src/c-Abl inhibitor, bosutinib, as a candidate molecular targeted therapy for ALS. The objectives of this study are to evaluate the safety and tolerability of bosutinib for the treatment of patients with ALS and to explore the efficacy of bosutinib on ALS. This study is the first clinical trial of administered bosutinib for patients with ALS.
METHODS AND ANALYSIS: An open-label, multicentre phase I dose escalation study has been designed. The study consists of a 12-week observation period, a 1-week transitional period, a 12-week study treatment period and a 4-week follow-up period. After completion of the transitional period, subjects whose total ALS Functional Rating Scale-Revised (ALSFRS-R) score decreased by 1-3 points during the 12-week observation period receive bosutinib for 12 weeks. Three to six patients with ALS are enrolled in each of the four bosutinib dose levels (100, 200, 300 or 400 mg/day) to evaluate the safety and tolerability under a 3+3 dose escalation study design. Dose escalation and maximum tolerated dose are determined by the safety assessment committee comprising oncologists/haematologists and neurologists based on the incidence of dose-limiting toxicity in the first 4 weeks of the treatment at each dose level. A recommended phase II dose is determined by the safety assessment committee on completion of the 12-week study treatment in all subjects at all dose levels. The efficacy of bosutinib is also evaluated exploratorily using ALS clinical scores and biomarkers.
ETHICS AND DISSEMINATION: This study received full ethical approval from the institutional review board of each participating site. The findings of the study will be disseminated in peer-reviewed journals and at scientific conferences.
TRIAL REGISTRATION NUMBER: UMIN000036295; Pre-results, JMA-IIA00419; Pre-results.

PMID: 31796494 [PubMed - in process]