Identifying New Antiepileptic Drugs Through Genomics-Based Drug Repurposing.

Hum Mol Genet. 2017 Jan 04;:

Authors: Mirza N, Sills GJ, Pirmohamed M, Marson AG

Abstract
Currently available antiepileptic drugs (AEDs) fail to control seizures in 30% of patients. Genomics-based drug repurposing (GBR) offers the potential of savings in the time and cost of developing new AEDs. In the current study, we used published data and software to identify the transcriptomic signature of chornic temporal lobe epilepsy and the drugs that reverse it. After filtering out compounds based on exclusion criteria, such as toxicity, 36 drugs were retained. 11 of the 36 drugs identified (>30%) have published evidence of antiepileptic efficacy (for example, curcumin) or antiepileptogenic affect (for example, atorvastatin) in recognised rodent models or patients. By objectively annotating all ∼20,000 compounds in the LINCS database as either having published evidence of antiepileptic efficacy or lacking such evidence, we demonstrated that our set of repurposable drugs is ∼6-fold more enriched with drugs having published evidence of antiepileptic efficacy in animal models than expected by chance (p-value <0.006). Further, we showed that another of our GBR-identified drugs, the commonly-used well-tolerated antihyperglycemic sitagliptin, produces a dose-dependent reduction in seizures in a mouse model of pharmacoresistant epilepsy. In conclusion, GBR successfully identifies compounds with antiepileptic efficacy in animal models and, hence, it is an appealing methodology for the discovery of potential AEDs.

PMID: 28053048 [PubMed - as supplied by publisher]

Novel Therapeutics Identification for Fibrosis in Renal Allograft Using Integrative Informatics Approach.

Sci Rep. 2017 Jan 04;7:39487

Authors: Li L, Greene I, Readhead B, Menon MC, Kidd BA, Uzilov AV, Wei C, Philippe N, Schroppel B, He JC, Chen R, Dudley JT, Murphy B

Abstract
Chronic allograft damage, defined by interstitial fibrosis and tubular atrophy (IF/TA), is a leading cause of allograft failure. Few effective therapeutic options are available to prevent the progression of IF/TA. We applied a meta-analysis approach on IF/TA molecular datasets in Gene Expression Omnibus to identify a robust 85-gene signature, which was used for computational drug repurposing analysis. Among the top ranked compounds predicted to be therapeutic for IF/TA were azathioprine, a drug to prevent acute rejection in renal transplantation, and kaempferol and esculetin, two drugs not previously described to have efficacy for IF/TA. We experimentally validated the anti-fibrosis effects of kaempferol and esculetin using renal tubular cells in vitro and in vivo in a mouse Unilateral Ureteric Obstruction (UUO) model. Kaempferol significantly attenuated TGF-β1-mediated profibrotic pathways in vitro and in vivo, while esculetin significantly inhibited Wnt/β-catenin pathway in vitro and in vivo. Histology confirmed significantly abrogated fibrosis by kaempferol and esculetin in vivo. We developed an integrative computational framework to identify kaempferol and esculetin as putatively novel therapies for IF/TA and provided experimental evidence for their therapeutic activities in vitro and in vivo using preclinical models. The findings suggest that both drugs might serve as therapeutic options for IF/TA.

PMID: 28051114 [PubMed - in process]

Correction: Large-Scale Off-Target Identification Using Fast and Accurate Dual Regularized One-Class Collaborative Filtering and Its Application to Drug Repurposing.

PLoS Comput Biol. 2017 Jan;13(1):e1005312

Authors: PLOS Computational Biology Staff

Abstract
[This corrects the article DOI: 10.1371/journal.pcbi.1005135.].

PMID: 28045897 [PubMed - in process]

Toward Repurposing Metformin as a Precision Anti-Cancer Therapy Using Structural Systems Pharmacology.

Sci Rep. 2016 Feb 04;6:20441

Authors: Hart T, Dider S, Han W, Xu H, Zhao Z, Xie L

Abstract
Metformin, a drug prescribed to treat type-2 diabetes, exhibits anti-cancer effects in a portion of patients, but the direct molecular and genetic interactions leading to this pleiotropic effect have not yet been fully explored. To repurpose metformin as a precision anti-cancer therapy, we have developed a novel structural systems pharmacology approach to elucidate metformin's molecular basis and genetic biomarkers of action. We integrated structural proteome-scale drug target identification with network biology analysis by combining structural genomic, functional genomic, and interactomic data. Through searching the human structural proteome, we identified twenty putative metformin binding targets and their interaction models. We experimentally verified the interactions between metformin and our top-ranked kinase targets. Notably, kinases, particularly SGK1 and EGFR were identified as key molecular targets of metformin. Subsequently, we linked these putative binding targets to genes that do not directly bind to metformin but whose expressions are altered by metformin through protein-protein interactions, and identified network biomarkers of phenotypic response of metformin. The molecular targets and the key nodes in genetic networks are largely consistent with the existing experimental evidence. Their interactions can be affected by the observed cancer mutations. This study will shed new light into repurposing metformin for safe, effective, personalized therapies.

PMID: 26841718 [PubMed - indexed for MEDLINE]

Neuroblastoma, a Paradigm for Big Data Science in Pediatric Oncology.

Int J Mol Sci. 2016 Dec 27;18(1):

Authors: Salazar BM, Balczewski EA, Ung CY, Zhu S

Abstract
Pediatric cancers rarely exhibit recurrent mutational events when compared to most adult cancers. This poses a challenge in understanding how cancers initiate, progress, and metastasize in early childhood. Also, due to limited detected driver mutations, it is difficult to benchmark key genes for drug development. In this review, we use neuroblastoma, a pediatric solid tumor of neural crest origin, as a paradigm for exploring "big data" applications in pediatric oncology. Computational strategies derived from big data science-network- and machine learning-based modeling and drug repositioning-hold the promise of shedding new light on the molecular mechanisms driving neuroblastoma pathogenesis and identifying potential therapeutics to combat this devastating disease. These strategies integrate robust data input, from genomic and transcriptomic studies, clinical data, and in vivo and in vitro experimental models specific to neuroblastoma and other types of cancers that closely mimic its biological characteristics. We discuss contexts in which "big data" and computational approaches, especially network-based modeling, may advance neuroblastoma research, describe currently available data and resources, and propose future models of strategic data collection and analyses for neuroblastoma and other related diseases.

PMID: 28035989 [PubMed - in process]

Using Drugs as Molecular Probes: A Computational Chemical Biology Approach in Neurodegenerative Diseases.

J Alzheimers Dis. 2016 Dec 30;:

Authors: Emon MA, Kodamullil AT, Karki R, Younesi E, Hofmann-Apitius M

Abstract
Neurodegenerative diseases including Alzheimer's disease are complex to tackle because of the complexity of the brain, both in structure and function. Such complexity is reflected by the involvement of various brain regions and multiple pathways in the etiology of neurodegenerative diseases that render single drug target approaches ineffective. Particularly in the area of neurodegeneration, attention has been drawn to repurposing existing drugs with proven efficacy and safety profiles. However, there is a lack of systematic analysis of the brain chemical space to predict the feasibility of repurposing strategies. Using a mechanism-based, drug-target interaction modeling approach, we have identified promising drug candidates for repositioning. Mechanistic cause-and-effect models consolidate relevant prior knowledge on drugs, targets, and pathways from the scientific literature and integrate insights derived from experimental data. We demonstrate the power of this approach by predicting two repositioning candidates for Alzheimer's disease and one for amyotrophic lateral sclerosis.

PMID: 28035920 [PubMed - as supplied by publisher]

Drug-Mediated Regulation of Glycosaminoglycan Biosynthesis.

Med Res Rev. 2016 Dec 28;:

Authors: Ghiselli G

Abstract
Glycosaminoglycans (GAGs) are a heterogeneous family of unbranched polysaccharides that exist in either a free state or attached to proteins and are found on the cell surface as well as in the extracellular matrix. GAGs play essential roles in cellular and tissue homeostasis, and their metabolism is altered in response to several pathological conditions. Despite strong experimental evidence supporting the function of GAGs in various diseases, little is known about the regulation of GAG biosynthesis via pharmacological intervention. In recent studies, the effects of several experimental drugs on GAG biosynthesis in animal models of disease were examined and key enzymes involved in GAG biosynthesis were found to be druggable. In addition to experimental small-molecule drugs that alter GAG biosynthesis, a number of clinically approved drugs modulate GAG metabolism, contributing to the therapeutic benefits associated with the use of these drugs. In this review article, we propose a classification scheme for drugs affecting GAG biosynthesis. Our goal is to present a rational approach to investigate the pharmacological regulation of these important biological molecules.

PMID: 28029167 [PubMed - as supplied by publisher]

Drug repurposing in anticancer reagent development.

Comb Chem High Throughput Screen. 2016 Dec 26;

Authors: Chen PC, Liu X, Lin Y

Abstract
The development process for cancer drugs is risky, lengthy and costly. Exploration of the anticancer potential of listed non-cancer drugs has become a popular research field in the pharmaceutical industry. The efficacy of various drugs are tested in multiple cancer types and the mechanisms underlying their effect were investigated. In this review, we have summarized the drug relocation instances for different cancer types in recent years and discussed the future direction of drug repurposing.

PMID: 28025934 [PubMed - as supplied by publisher]

HEDD: the human epigenetic drug database.

Database (Oxford). 2016;2016:

Authors: Qi Y, Wang D, Wang D, Jin T, Yang L, Wu H, Li Y, Zhao J, Du F, Song M, Wang R

Abstract
Epigenetic drugs are chemical compounds that target disordered post-translational modification of histone proteins and DNA through enzymes, and the recognition of these changes by adaptor proteins. Epigenetic drug-related experimental data such as gene expression probed by high-throughput sequencing, co-crystal structure probed by X-RAY diffraction and binding constants probed by bio-assay have become widely available. The mining and integration of multiple kinds of data can be beneficial to drug discovery and drug repurposing. HEMD and other epigenetic databases store comprehensively epigenetic data where users can acquire segmental information of epigenetic drugs. However, some data types such as high-throughput datasets are not provide by these databases and they do not support flexible queries for epigenetic drug-related experimental data. Therefore, in reference to HEMD and other epigenetic databases, we developed a relatively comprehensive database for human epigenetic drugs. The human epigenetic drug database (HEDD) focuses on the storage and integration of epigenetic drug datasets obtained from laboratory experiments and manually curated information. The latest release of HEDD incorporates five kinds of datasets: (i) drug, (ii) target, (iii) disease, (vi) high-throughput and (v) complex. In order to facilitate data extraction, flexible search options were built in HEDD, which allowed an unlimited condition query for specific kinds of datasets using drug names, diseases and experiment types.Database URL: http://hedds.org/.

PMID: 28025347 [PubMed - in process]

Drug Repositioning for Alzheimer's Disease Based on Systematic 'omics' Data Mining.

PLoS One. 2016;11(12):e0168812

Authors: Zhang M, Schmitt-Ulms G, Sato C, Xi Z, Zhang Y, Zhou Y, St George-Hyslop P, Rogaeva E

Abstract
Traditional drug development for Alzheimer's disease (AD) is costly, time consuming and burdened by a very low success rate. An alternative strategy is drug repositioning, redirecting existing drugs for another disease. The large amount of biological data accumulated to date warrants a comprehensive investigation to better understand AD pathogenesis and facilitate the process of anti-AD drug repositioning. Hence, we generated a list of anti-AD protein targets by analyzing the most recent publically available 'omics' data, including genomics, epigenomics, proteomics and metabolomics data. The information related to AD pathogenesis was obtained from the OMIM and PubMed databases. Drug-target data was extracted from the DrugBank and Therapeutic Target Database. We generated a list of 524 AD-related proteins, 18 of which are targets for 75 existing drugs-novel candidates for repurposing as anti-AD treatments. We developed a ranking algorithm to prioritize the anti-AD targets, which revealed CD33 and MIF as the strongest candidates with seven existing drugs. We also found 7 drugs inhibiting a known anti-AD target (acetylcholinesterase) that may be repurposed for treating the cognitive symptoms of AD. The CAD protein and 8 proteins implicated by two 'omics' approaches (ABCA7, APOE, BIN1, PICALM, CELF1, INPP5D, SPON1, and SOD3) might also be promising targets for anti-AD drug development. Our systematic 'omics' mining suggested drugs with novel anti-AD indications, including drugs modulating the immune system or reducing neuroinflammation that are particularly promising for AD intervention. Furthermore, the list of 524 AD-related proteins could be useful not only as potential anti-AD targets but also considered for AD biomarker development.

PMID: 28005991 [PubMed - in process]

Next generation metronomic chemotherapy-report from the Fifth Biennial International Metronomic and Anti-angiogenic Therapy Meeting, 6-8 May 2016, Mumbai.

Ecancermedicalscience. 2016;10:689

Authors: Pantziarka P, Hutchinson L, André N, Benzekry S, Bertolini F, Bhattacharjee A, Chiplunkar S, Duda DG, Gota V, Gupta S, Joshi A, Kannan S, Kerbel R, Kieran M, Palazzo A, Parikh A, Pasquier E, Patil V, Prabhash K, Shaked Y, Sholler GS, Sterba J, Waxman DJ, Banavali S

Abstract
The 5(th) Biennial Metronomic and Anti-angiogenic Therapy Meeting was held on 6(th) - 8(th) May in the Indian city of Mumbai. The meeting brought together a wide range of clinicians and researchers interested in metronomic chemotherapy, anti-angiogenics, drug repurposing and combinations thereof. Clinical experiences, including many from India, were reported and discussed in three symposia covering breast cancer, head and neck cancers and paediatrics. On the pre-clinical side research into putative mechanisms of action, and the interactions between low dose metronomic chemotherapy and angiogenesis and immune responses, were discussed in a number of presentations. Drug repurposing was discussed both in terms of clinical results, particularly with respect to angiosarcoma and high-risk neuroblastoma, and in pre-clinical settings, particularly the potential for peri-operative interventions. However, it was clear that there remain a number of key areas of challenge, particularly in terms of definitions, perceptions in the wider oncological community, mechanisms of action and predictive biomarkers. While the potential for metronomics and drug repurposing in low and middle income countries remains a key theme, it is clear that there is also considerable potential for clinically relevant improvements in patient outcomes even in high income economies.

PMID: 27994645 [PubMed]

Repurposing toremifene for the treatment of oral bacterial infections.

Antimicrob Agents Chemother. 2016 Dec 19;:

Authors: Gerits E, Defraine V, Vandamme K, De Cremer K, De Brucker K, Thevissen K, Cammue BP, Beullens S, Fauvart M, Verstraeten N, Michiels J

Abstract
The spread of antibiotic resistance and the challenges associated with antiseptics such as chlorhexidine have necessitated the search for new antibacterial agents against oral bacterial pathogens. As a result of failing traditional approaches, drug repurposing has emerged as a novel paradigm to find new antibacterial agents. In this study, we examined the effect of the FDA-approved anticancer agent toremifene against oral bacteria Porphyromonas gingivalis and Streptococcus mutans. We found that the drug was able to inhibit growth of both pathogens as well as prevent biofilm formation at concentrations ranging from 12.5 to 25 μM. Moreover, toremifene was shown to eradicate preformed biofilms at concentrations ranging from 25 to 50 μM. In addition, we found that toremifene prevents P. gingivalis and S. mutans biofilm formation on titanium surfaces. A time-kill study indicated that toremifene acts bactericidal against S. mutans Macromolecular synthesis assays revealed that treatment with toremifene does not cause preferential inhibition of DNA, RNA, or protein synthesis pathways, indicating membrane-damaging activity. Biophysical studies using fluorescent probes and fluorescence microscopy further confirmed the membrane-damaging mode of action. Taken together, our results suggest that the anti-cancer agent toremifene is a suitable candidate for further investigation for the development of new treatment strategies for oral bacterial infections.

PMID: 27993858 [PubMed - as supplied by publisher]

Predict Drug Permeability to Blood-Brain-Barrier from Clinical Phenotypes: Drug Side Effects and Drug Indications.

Bioinformatics. 2016 Dec 19;:

Authors: Gao Z, Chen Y, Cai X, Xu R

Abstract
MOTIVATION: Blood-Brain-Barrier (BBB) is a rigorous permeability barrier for maintaining homeostasis of Central Nervous System (CNS). Determination of compound's permeability to BBB is prerequisite in CNS drug discovery. Existing computational methods usually predict drug BBB permeability from chemical structure and they generally apply to small compounds passing BBB through passive diffusion. As abundant information on drug side effects and indications has been recorded over time through extensive clinical usage, we aim to explore BBB permeability prediction from a new angle and introduce a novel approach to predict BBB permeability from drug clinical phenotypes (drug side effects and drug indications). This method can apply to both small compounds and macro-molecules penetrating BBB through various mechanisms besides passive diffusion.
RESULTS: We composed a training dataset of 213 drugs with known brain and blood steady-state concentrations ratio and extracted their side effects and indications as features. Next, we trained SVM models with polynomial kernel and obtained accuracy of 76.0%, AUC 0.739, and F1 score (macro weighted) 0.760 with Monte Carlo cross validation. The independent test accuracy was 68.3%, AUC 0.692, F1 score 0.676. When both chemical features and clinical phenotypes were available, combining the two types of features achieved significantly better performance than chemical feature based approach (accuracy 85.5% vs 72.9%, AUC 0.854 vs 0.733, F1 score 0.854 vs 0.725; p < e(-90)). We also conducted de novo prediction and identified 110 drugs in SIDER database having the potential to penetrate BBB, which could serve as start point for CNS drug repositioning research.
AVAILABILITY: https://github.com/bioinformatics-gao/CASE-BBB-prediction-Data CONTACT: rxx@case.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID: 27993785 [PubMed - as supplied by publisher]

Orphan receptor ligand discovery by pickpocketing pharmacological neighbors.

Nat Chem Biol. 2016 Dec 19;:

Authors: Ngo T, Ilatovskiy AV, Stewart AG, Coleman JL, McRobb FM, Riek RP, Graham RM, Abagyan R, Kufareva I, Smith NJ

Abstract
Understanding the pharmacological similarity of G protein-coupled receptors (GPCRs) is paramount for predicting ligand off-target effects, drug repurposing, and ligand discovery for orphan receptors. Phylogenetic relationships do not always correctly capture pharmacological similarity. Previous family-wide attempts to define pharmacological relationships were based on three-dimensional structures and/or known receptor-ligand pairings, both unavailable for orphan GPCRs. Here, we present GPCR-CoINPocket, a novel contact-informed neighboring pocket metric of GPCR binding-site similarity that is informed by patterns of ligand-residue interactions observed in crystallographically characterized GPCRs. GPCR-CoINPocket is applicable to receptors with unknown structure or ligands and accurately captures known pharmacological relationships between GPCRs, even those undetected by phylogeny. When applied to orphan receptor GPR37L1, GPCR-CoINPocket identified its pharmacological neighbors, and transfer of their pharmacology aided in discovery of the first surrogate ligands for this orphan with a 30% success rate. Although primarily designed for GPCRs, the method is easily transferable to other protein families.

PMID: 27992882 [PubMed - as supplied by publisher]

Ribavirin suppresses bacterial virulence by targeting LysR-type transcriptional regulators.

Sci Rep. 2016 Dec 19;6:39454

Authors: Mandal RS, Ta A, Sinha R, Theeya N, Ghosh A, Tasneem M, Bhunia A, Koley H, Das S

Abstract
Targeting bacterial virulence mechanisms without compromising bacterial growth is a promising strategy to prevent drug resistance. LysR-type transcriptional regulators (LTTRs) possess structural conservation across bacterial species and regulate virulence in numerous pathogens, making them attractive targets for antimicrobial agents. We targeted AphB, a Vibrio cholerae LTTR, which regulates the expression of genes encoding cholera toxin and toxin-co-regulated pilus for inhibitor designing. Since AphB ligand is unknown, we followed a molecular fragment-based approach for ligand designing using FDA-approved drugs and subsequent screen to identify molecules that exhibited high-affinity binding to AphB ligand-binding pocket. Among the identified compounds, ribavirin, an anti-viral drug, antagonized AphB functions. Ribavirin perturbed Vibrio cholerae pathogenesis in animal models. The inhibitory effects of the drug was limited to the bacteria expressing wild type AphB, but not its constitutively active mutant (AphBN100E), which represents the ligand-bound state, suggesting that ribavirin binds to the active site of AphB to exert its inhibitory role and there exists no AphB-independent mechanism of its action. Similarly, ribavirin suppressed the functions of Salmonella Typhi LTTR Hrg, indicating its broad spectrum efficacy. Moreover, ribavirin did not affect the bacterial viability in culture. This study cites an example of drug repurposing for anti-infective therapy.

PMID: 27991578 [PubMed - in process]

Drug Repurposing Patent Applications April-June 2016.

Assay Drug Dev Technol. 2016 Dec;14(10):573-576

Authors: Mucke HA

PMID: 27982706 [PubMed - in process]

Drug Repurposing Patent Applications July-September 2016.

Assay Drug Dev Technol. 2016 Dec;14(10):577-582

Authors: Mucke HA

PMID: 27982705 [PubMed - in process]

Revisiting Repurposing.

Assay Drug Dev Technol. 2016 Dec;14(10):554-556

Authors: Sharlow ER

Abstract
Drug repurposing can be a cost-effective strategy to identify new small molecule-based therapies. Thus, drug repurposing significantly influences the discovery of therapeutics, particularly for rare and neglected diseases, which are often constrained by limited research and development funds. The push for translational science and access to drug discovery-associated resources such as high throughput screening instrumentation, assay development expertise, and Food and Drug Administration-approved drug libraries have intensified interest in drug repurposing. However, successful drug repurposing is highly challenging and subject to particular limitations. Despite these challenges, drug repurposing is a critical component to any comprehensive drug discovery strategy and has the capacity to benefit a wide variety of therapeutically underserved diseases.

PMID: 27982703 [PubMed - in process]

The potential role of trimethoprim-sulfamethoxazole in the treatment of drug-resistant tuberculosis.

Future Microbiol. 2016;11(4):539-47

Authors: Palomino JC, Martin A

Abstract
Tuberculosis (TB) remains a serious public health threat worsened by emerging drug resistance. Mycobacterium tuberculosis has become resistant not only to front-line drugs but also to second-line antimicrobials directed at drug-resistant TB. Renewed efforts are devoted for the development of new antibiotics active against TB. Also, repurposing of other antibiotics is being explored to shorten the time to develop new drugs against M. tuberculosis. As a result, trimethoprim-sulfamethoxazole (SXT) has emerged as a potential new option to treat drug-resistant TB. SXT has been found to be surprisingly active against drug-resistant M. tuberculosis, not only in vitro but also in vivo. The potential role of SXT for the treatment of multidrug resistant/extensively drug resistant TB might be explored in further clinical evaluations.

PMID: 27070731 [PubMed - indexed for MEDLINE]

Rebamipide, an Amino Acid Analog of 2(1H)-Quinolinone, Inhibits the Formation of Human Osteoclasts.

Biomed Res Int. 2016;2016:6824719

Authors: Nanke Y, Kobashigawa T, Yago T, Kawamoto M, Yamanaka H, Kotake S

Abstract
Objectives. Drug repositioning or drug reprofiling (DR) has recently been growing in importance. DR has a significant advantage over traditional drug development because the repositioned drug has already passed toxicity tests; its safety is known, and the risk of adverse toxicology is reduced. In the current study, we investigated the role of rebamipide, a mucosa-protecting agent, with recently reported anti-inflammatory function, in human osteoclastogenesis. Methods. Peripheral blood mononuclear cells (PBMCs) were cultured in the presence of M-CSF and sRANKL. Osteoclast formation was evaluated by immunohistological staining for CD51/61 (vitronectin receptors). Osteoclast formation, in the presence or absence of rebamipide (0, 1, and 3 mM), was observed by time-lapse photography and actin ring formation. The number of absorption sites and area of absorption were calculated using Osteologic™ plates. Pit formation was studied by 3D-SEM. Results. Rebamipide inhibited human osteoclast formation at 3 mM, a pharmacological concentration, and inhibited resorbing activity dose-dependently. Rebamipide induced the degradation of actin rings in mature osteoclasts. This mechanism may involve inhibiting the osteoclast fusion pathway through reducing the expression of DC-specific transmembrane protein (DC-STAMP). Conclusions. The present study suggests that rebamipide would be useful as a novel agent for osteoporosis and rheumatoid arthritis.

PMID: 27965978 [PubMed - in process]