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1.
BMC Bioinformatics ; 20(Suppl 13): 383, 2019 Jul 24.
Artigo em Inglês | MEDLINE | ID: mdl-31337333

RESUMO

BACKGROUND: Drug repurposing has been motivated to ameliorate low probability of success in drug discovery. For the recent decade, many in silico attempts have received primary attention as a first step to alleviate the high cost and longevity. Such study has taken benefits of abundance, variety, and easy accessibility of pharmaceutical and biomedical data. Utilizing the research friendly environment, in this study, we propose a network-based machine learning algorithm for drug repurposing. Particularly, we show a framework on how to construct a drug network, and how to strengthen the network by employing multiple/heterogeneous types of data. RESULTS: The proposed method consists of three steps. First, we construct a drug network from drug-target protein information. Then, the drug network is reinforced by utilizing drug-drug interaction knowledge on bioactivity and/or medication from literature databases. Through the enhancement, the number of connected nodes and the number of edges between them become more abundant and informative, which can lead to a higher probability of success of in silico drug repurposing. The enhanced network recommends candidate drugs for repurposing through drug scoring. The scoring process utilizes graph-based semi-supervised learning to determine the priority of recommendations. CONCLUSIONS: The drug network is reinforced in terms of the coverage and connections of drugs: the drug coverage increases from 4738 to 5442, and the drug-drug associations as well from 808,752 to 982,361. Along with the network enhancement, drug recommendation becomes more reliable: AUC of 0.89 was achieved lifted from 0.79. For typical cases, 11 recommended drugs were shown for vascular dementia: amantadine, conotoxin GV, tenocyclidine, cycloeucine, etc.


Assuntos
Reposicionamento de Medicamentos/métodos , Preparações Farmacêuticas/química , Área Sob a Curva , Interações de Medicamentos , Humanos , Preparações Farmacêuticas/metabolismo , Proteínas/química , Proteínas/metabolismo , Curva ROC , Aprendizado de Máquina Supervisionado
2.
Pharm Res ; 36(9): 137, 2019 Jul 22.
Artigo em Inglês | MEDLINE | ID: mdl-31332533

RESUMO

PURPOSE: Pitt Hopkins Syndrome (PTHS) is a rare genetic disorder caused by mutations of a specific gene, transcription factor 4 (TCF4), located on chromosome 18. PTHS results in individuals that have moderate to severe intellectual disability, with most exhibiting psychomotor delay. PTHS also exhibits features of autistic spectrum disorders, which are characterized by the impaired ability to communicate and socialize. PTHS is comorbid with a higher prevalence of epileptic seizures which can be present from birth or which commonly develop in childhood. Attenuated or absent TCF4 expression results in increased translation of peripheral ion channels Kv7.1 and Nav1.8 which triggers an increase in after-hyperpolarization and altered firing properties. METHODS: We now describe a high throughput screen (HTS) of 1280 approved drugs and machine learning models developed from this data. The ion channels were expressed in either CHO (KV7.1) or HEK293 (Nav1.8) cells and the HTS used either 86Rb+ efflux (KV7.1) or a FLIPR assay (Nav1.8). RESULTS: The HTS delivered 55 inhibitors of Kv7.1 (4.2% hit rate) and 93 inhibitors of Nav1.8 (7.2% hit rate) at a screening concentration of 10 µM. These datasets also enabled us to generate and validate Bayesian machine learning models for these ion channels. We also describe a structure activity relationship for several dihydropyridine compounds as inhibitors of Nav1.8. CONCLUSIONS: This work could lead to the potential repurposing of nicardipine or other dihydropyridine calcium channel antagonists as potential treatments for PTHS acting via Nav1.8, as there are currently no approved treatments for this rare disorder.


Assuntos
Di-Hidropiridinas/farmacologia , Reposicionamento de Medicamentos/métodos , Hiperventilação/tratamento farmacológico , Deficiência Intelectual/tratamento farmacológico , Canal de Potássio KCNQ1/antagonistas & inibidores , Canal de Sódio Disparado por Voltagem NAV1.8/metabolismo , Bloqueadores dos Canais de Potássio/farmacologia , Bloqueadores dos Canais de Sódio/farmacologia , Bloqueadores do Canal de Sódio Disparado por Voltagem/farmacologia , Animais , Teorema de Bayes , Células CHO , Cricetulus , Di-Hidropiridinas/química , Facies , Células HEK293 , Humanos , Canal de Potássio KCNQ1/metabolismo , Aprendizado de Máquina , Bloqueadores dos Canais de Potássio/química , Bibliotecas de Moléculas Pequenas/química , Bloqueadores dos Canais de Sódio/química , Relação Estrutura-Atividade , Bloqueadores do Canal de Sódio Disparado por Voltagem/química
3.
Med Sci Monit ; 25: 3247-3255, 2019 May 02.
Artigo em Inglês | MEDLINE | ID: mdl-31048671

RESUMO

BACKGROUND Multiple myeloma (MM) is the second most common hematologic cancer with poor prognosis. Novel therapeutic strategies are needed to decrease the high mortality rate. The aim of this study was to identify prospective agents for MM. MATERIAL AND METHODS A microarray dataset was mined, which contains the transcriptome profiles of 588 MM patients. Univariate Cox analysis was performed to analyze the relationships between genes and clinical outcome. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were determined. Protective and risky genes were uploaded to Connectivity Map (CMAP) database to identify the potentially unknown effects of existing drugs. An example was selected to be docked on the known molecules. RESULTS A total of 1445 genes significantly correlated with the event free survival (EFS) of MM patients were identified and included 676 protective and 769 risky indicators. KEGG pathway analysis revealed that these prognosis-associated genes were enriched in the "cell cycle," "DNA replication," and "P53 signaling pathway". The top t3 most significant potential molecules were vorinostat, trifluoperazine, and thioridazine. CDK1 (cyclin-dependent kinase-1) ranked as the core in the class of prognosis-related genes in MM based on protein-protein interaction (PPI) network analysis. With Sybyl-X 2.0, the majority of the top 10 molecules aforementioned displayed high binding forces with CDK1. Among these molecules, trichostatin A had the greatest ability in combining with CDK1. CONCLUSIONS Genes that mainly accumulate in the cell cycle pathway play an essential role in the prognosis of MM, and these prognosis-related genes also have great value in drug development.


Assuntos
Reposicionamento de Medicamentos/métodos , Mieloma Múltiplo/tratamento farmacológico , Mieloma Múltiplo/genética , Biomarcadores Farmacológicos/análise , Biologia Computacional/métodos , Bases de Dados Genéticas , Perfilação da Expressão Gênica , Ontologia Genética , Redes Reguladoras de Genes , Humanos , Simulação de Acoplamento Molecular , Mieloma Múltiplo/metabolismo , Medicina de Precisão , Prognóstico , Intervalo Livre de Progressão , Modelos de Riscos Proporcionais , Estudos Prospectivos , Mapas de Interação de Proteínas , Transdução de Sinais , Transcriptoma
4.
Mediators Inflamm ; 2019: 6481812, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31049025

RESUMO

Clinically active drugs for the treatment of acute pain have their prescription limited due to the significant side effects they induce. An increase in reactive oxygen species (ROS) has been linked to several conditions, including inflammation and pain processing. Therefore, new or repurposed drugs with the ability of reducing ROS-triggered responses are promising candidates for analgesic drugs. Vinpocetine is a clinically used nootropic drug with antioxidant, anti-inflammatory, and analgesic properties. However, the effects of vinpocetine have not been investigated in a model with a direct relationship between ROS, inflammation, and pain. Based on that, we aimed to investigate the effects of vinpocetine in a model of superoxide anion-induced pain and inflammation using potassium superoxide (KO2) as a superoxide anion donor to trigger inflammation and pain. In the KO2 model, vinpocetine dose-dependently reduced pain-like behaviors (spontaneous pain and hyperalgesia), paw edema, and neutrophil and mononuclear cell recruitment to the paw skin (assessed by H&E staining, fluorescence, and enzymatic assays) and to the peritoneal cavity. Vinpocetine also restored tissue endogenous antioxidant ability and Nrf2 and Ho-1 mRNA expression and reduced superoxide anion production and gp91phox mRNA expression. We also observed the inhibition of IκBα degradation by vinpocetine, which demonstrates a reduction in the activation of NF-κB explaining the diminished production of IL-33, IL-1ß, and TNF-α. Collectively, our data show that vinpocetine alleviates pain and inflammation induced by KO2, which is a mouse model with a direct role of ROS in triggering pain and other inflammatory phenomena. Thus, the results suggest the repurposing of vinpocetine as an anti-inflammatory and analgesic drug.


Assuntos
Analgésicos/uso terapêutico , Anti-Inflamatórios/uso terapêutico , Reposicionamento de Medicamentos/métodos , Inflamação/tratamento farmacológico , Inflamação/metabolismo , Nootrópicos/uso terapêutico , Superóxidos/toxicidade , Alcaloides de Vinca/uso terapêutico , Animais , Citocinas/metabolismo , Modelos Animais de Doenças , Edema/tratamento farmacológico , Edema/metabolismo , Heme Oxigenase-1 , Hiperalgesia/tratamento farmacológico , Hiperalgesia/metabolismo , Masculino , Proteínas de Membrana , Camundongos , Fator 2 Relacionado a NF-E2/genética , Fator 2 Relacionado a NF-E2/metabolismo , NF-kappa B/metabolismo , Estresse Oxidativo/efeitos dos fármacos , Espécies Reativas de Oxigênio/metabolismo
5.
Gene ; 706: 77-83, 2019 Jul 20.
Artigo em Inglês | MEDLINE | ID: mdl-31048070

RESUMO

Therapeutic induction of fetal hemoglobin (HbF) is one of the most promising approaches to ameliorate the severity of hemoglobinopathies like ß-thalassemia and sickle cell anemia. Although several pharmacological agents have been investigated for HbF induction in adults, the majority of these are associated with significant side-effects. While drug repurposing is known to open new doors for the use of approved drugs in unexplored clinical conditions, the primary challenge lies in identifying such candidates. In this study, we aimed to identify repurposing candidates for HbF induction using a novel in silico approach utilizing microRNA-pathway-drug relationships. A computational drug repurposing strategy identified several unique candidates for HbF induction; among which Curcumin, Ginsenoside, Valproate, and Vorinostat were found to be most suitable for future trials. This study identified new drug repurposing candidates for HbF induction and demonstrates an easily adaptable methodology that can be used for other pathophysiological conditions.


Assuntos
Hemoglobina Fetal/biossíntese , Perfilação da Expressão Gênica/métodos , Hemoglobinopatias/genética , Anemia Falciforme/genética , Simulação por Computador , Reposicionamento de Medicamentos/métodos , Hemoglobinopatias/fisiopatologia , Hemoglobinas/biossíntese , Hemoglobinas/metabolismo , Humanos , MicroRNAs/genética , MicroRNAs/uso terapêutico , Transcriptoma/genética , Talassemia beta/genética
6.
Phytomedicine ; 59: 152900, 2019 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-30974310

RESUMO

BACKGROUND: Extracts derived from natural products have been used to produce health supplements or therapeutic agents in oriental medicine. Although these extracts contain various bioactive compounds, their applications are generally limited to a few previously known diseases. To effectively expand their use for the treatment of other conditions, systematic analysis should be conducted for repurposing. PURPOSE: The purpose of the present study was to investigate the new therapeutic efficacies of the Platycodon grandiflorum and ginseng extract using the CMAP-based gene expression analysis. METHODS: In the present study, we analyzed the expression patterns of differentially expressed genes (DEGs) from extracts as the basis for drug repurposing. Cells were treated with extracts or single compounds derived from nine natural products. DEG analysis indicated that the gene expression patterns of cells treated with P. grandiflorum and ginseng extracts were highly similar to those of cells treated with different types of Histone deacetylase (HDAC) inhibitors. To identify the new mechanism of these extracts, we carried out cell viability assay, TUNEL assay, HDAC enzyme activity assay and immunoblot analysis. RESULTS: In vitro experiments at the dose of 50 µg/ml of each extract did not affect cell death rate but significantly inhibited HDAC activity. Each extract was found to inhibit HDAC enzymatic activity and induce the expression of the p21. Furthermore, our results revealed that each extract stimulated cell death and inhibited cell proliferation. CONCLUSION: These findings demonstrate the HDAC-inhibiting activity of P. grandiflorum and ginseng extracts and further validate the effectiveness of DEG similarity-based repurposing of natural products.


Assuntos
Produtos Biológicos/farmacologia , Reposicionamento de Medicamentos/métodos , Inibidores de Histona Desacetilases/farmacologia , Extratos Vegetais/farmacologia , Linhagem Celular Tumoral , Proliferação de Células/efeitos dos fármacos , Sobrevivência Celular/efeitos dos fármacos , Humanos , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patologia , Panax/química , Platycodon/química , Transcriptoma/efeitos dos fármacos
7.
Math Biosci Eng ; 16(3): 1376-1391, 2019 02 20.
Artigo em Inglês | MEDLINE | ID: mdl-30947425

RESUMO

For discovery of new usage of drugs, the function type of their target genes plays an important role, and the hypothesis of "Antagonist-GOF" and "Agonist-LOF" has laid a solid foundation for supporting drug repurposing. In this research, an active gene annotation corpus was used as training data to predict the gain-of-function or loss-of-function or unknown character of each human gene after variation events. Unlike the design of(entity, predicate, entity) triples in a traditional three way tensor, a four way and a five way tensor, GMFD-/GMAFD-tensor, were designed to represent higher order links among or among part of these entities: genes(G), mutations(M), functions(F), diseases( D) and annotation labels(A). A tensor decomposition algorithm, CP decomposition, was applied to the higher order tensor and to unveil the correlation among entities. Meanwhile, a state-of-the-art baseline tensor decomposition algorithm, RESCAL, was carried on the three way tensor as a comparing method. The result showed that CP decomposition on higher order tensor performed better than RESCAL on traditional three way tensor in recovering masked data and making predictions. In addition, The four way tensor was proved to be the best format for our issue. At the end, a case study reproducing two disease-gene-drug links(Myelodysplatic Syndromes-IL2RA-Aldesleukin, Lymphoma- IL2RA-Aldesleukin) presented the feasibility of our prediction model for drug repurposing.


Assuntos
Reposicionamento de Medicamentos/economia , Reposicionamento de Medicamentos/métodos , Variação Genética , Aprendizado de Máquina , Mutação , Algoritmos , Análise Custo-Benefício , Doenças Genéticas Inatas/genética , Humanos , Interleucina-2/análogos & derivados , Interleucina-2/uso terapêutico , Subunidade alfa de Receptor de Interleucina-2/genética , Linfoma/genética , Modelos Genéticos , Anotação de Sequência Molecular , Síndromes Mielodisplásicas/genética , Proteínas Recombinantes/uso terapêutico , Software
8.
Biochim Biophys Acta Rev Cancer ; 1871(2): 434-454, 2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-31034926

RESUMO

The strategy of using existing drugs originally developed for one disease to treat other indications has found success across medical fields. Such drug repurposing promises faster access of drugs to patients while reducing costs in the long and difficult process of drug development. However, the number of existing drugs and diseases, together with the heterogeneity of patients and diseases, notably including cancers, can make repurposing time consuming and inefficient. The key question we address is how to efficiently repurpose an existing drug to treat a given indication. As drug efficacy remains the main bottleneck for overall success, we discuss the need for machine-learning computational methods in combination with specific phenotypic studies along with mechanistic studies, chemical genetics and omics assays to successfully predict disease-drug pairs. Such a pipeline could be particularly important to cancer patients who face heterogeneous, recurrent and metastatic disease and need fast and personalized treatments. Here we focus on drug repurposing for colorectal cancer and describe selected therapeutics already repositioned for its prevention and/or treatment as well as potential candidates. We consider this review as a selective compilation of approaches and methodologies, and argue how, taken together, they could bring drug repurposing to the next level.


Assuntos
Antineoplásicos/farmacologia , Neoplasias Colorretais/tratamento farmacológico , Reposicionamento de Medicamentos/métodos , Aprendizado de Máquina , Animais , Humanos , Oncologia/métodos , Fenótipo
9.
Methods Mol Biol ; 1953: 89-103, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30912017

RESUMO

Pharmacological science is trying to establish the link between chemicals, targets, and disease-related phenotypes. A plethora of chemical proteomics and structural data have been generated, thanks to the target-based approach that has dominated drug discovery at the turn of the century. There is an invaluable source of information for in silico target profiling. Prediction is based on the principle of chemical similarity (similar drugs bind similar targets) or on first principles from the biophysics of molecular interactions. In the first case, compound comparison is made through ligand-based chemical similarity search or through classifier-based machine learning approach. The 3D techniques are based on 3D structural descriptors or energy-based scoring scheme to infer a binding affinity of a compound with its putative target. More recently, a new approach based on compound set metric has been proposed in which a query compound is compared with a whole of compounds associated with a target or a family of targets. This chapter reviews the different techniques of in silico target profiling and their main applications such as inference of unwanted targets, drug repurposing, or compound prioritization after phenotypic-based screening campaigns.


Assuntos
Projeto Auxiliado por Computador , Desenho de Drogas , Descoberta de Drogas/métodos , Software , Animais , Simulação por Computador , Reposicionamento de Medicamentos/métodos , Humanos , Ligantes , Aprendizado de Máquina , Terapia de Alvo Molecular , Relação Estrutura-Atividade
10.
Methods Mol Biol ; 1939: 91-118, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30848458

RESUMO

The surge of public disease and drug-related data availability has facilitated the application of computational methodologies to transform drug discovery. In the current chapter, we outline and detail the various resources and tools one can leverage in order to perform such analyses. We further describe in depth the in silico workflows of two recent studies that have identified possible novel indications of existing drugs. Lastly, we delve into the caveats and considerations of this process to enable other researchers to perform rigorous computational drug discovery experiments of their own.


Assuntos
Big Data , Biologia Computacional/métodos , Descoberta de Drogas/métodos , Software , Ontologias Biológicas , Simulação por Computador , Bases de Dados Factuais , Reposicionamento de Medicamentos/métodos , Registros Eletrônicos de Saúde , Humanos , Farmacogenética/métodos
11.
Oncol Rep ; 41(4): 2241-2253, 2019 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-30816547

RESUMO

Systemic treatment options for soft tissue sarcomas (STSs) have remained unchanged despite the need for novel drug candidates to improve STS outcomes. Drug repurposing involves the application of clinical drugs to different diseases, reducing development time, and cost. It has also become a fast and effective way to identify drug candidates. The present study used a computational method to screen three drug­gene interaction databases for novel drug candidates for the treatment of several common STS histologic subtypes through drug repurposing. STS survival­associated genes were generated by conducting a univariate cox regression analysis using The Cancer Genome Atlas survival data. These genes were then applied to three databases (the Connectivity Map, the Drug Gene Interaction Database and the L1000 Fireworks Display) to identify drug candidates for STS treatment. Additionally, pathway analysis and molecular docking were conducted to evaluate the molecular mechanisms of the candidate drug. Bepridil was identified as a potential candidate for several STS histologic subtype treatments by overlapping the screening results from three drug­gene interaction databases. The pathway analysis with the Kyoto Encyclopedia of Genes and Genomes predicted that Bepridil may target CRK, fibroblast growth factor receptor 4 (FGFR4), laminin subunit ß1 (LAMB1), phosphoinositide­3­kinase regulatory subunit 2 (PIK3R2), WNT5A, cluster of differentiation 47 (CD47), elastase, neutrophil expressed (ELANE), 15­hydroxyprostaglandin dehydrogenase (HPGD) and protein kinase cß (PRKCB) to suppress STS development. Further molecular docking simulation suggested a relatively stable binding selectivity between Bepridil and eight proteins (CRK, FGFR4, LAMB1, PIK3R2, CD47, ELANE, HPGD, and PRKCB). In conclusion, a computational method was used to identify Bepridil as a potential candidate for the treatment of several common STS histologic subtypes. Experimental validation of these in silico results is necessary before clinical translation can occur.


Assuntos
Antineoplásicos/farmacologia , Bepridil/farmacologia , Reposicionamento de Medicamentos/métodos , Redes Reguladoras de Genes/genética , Sarcoma/tratamento farmacológico , Antineoplásicos/química , Antineoplásicos/uso terapêutico , Bepridil/química , Bepridil/uso terapêutico , Biologia Computacional , Bases de Dados Genéticas/estatística & dados numéricos , Perfilação da Expressão Gênica , Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Redes Reguladoras de Genes/efeitos dos fármacos , Humanos , Simulação de Acoplamento Molecular , Ligação Proteica , Sarcoma/genética , Sarcoma/mortalidade , Sarcoma/patologia , Análise de Sobrevida
12.
Methods Mol Biol ; 1939: 199-214, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30848463

RESUMO

Systems pharmacology aims to understand drug actions on a multi-scale from atomic details of drug-target interactions to emergent properties of biological network and rationally design drugs targeting an interacting network instead of a single gene. Multifaceted data-driven studies, including machine learning-based predictions, play a key role in systems pharmacology. In such works, the integration of multiple omics data is the key initial step, followed by optimization and prediction. Here, we describe the overall procedures for drug-target association prediction using REMAP, a large-scale off-target prediction tool. The method introduced here can be applied to other relation inference problems in systems pharmacology.


Assuntos
Descoberta de Drogas/métodos , Software , Biologia de Sistemas/métodos , Bases de Dados Factuais , Reposicionamento de Medicamentos/métodos , Humanos , Aprendizado de Máquina
13.
Carbohydr Polym ; 212: 252-259, 2019 May 15.
Artigo em Inglês | MEDLINE | ID: mdl-30832855

RESUMO

Niclosamide, previously used as an anthelmintic drug is currently being repurposed for its anticancer activity. Niclosamide is a brick like biopharmaceutical classification system (BCS) class II drug with poor aqueous solubility and dissolution consequently leading to low bioavailability. By considering the physicochemical properties and geometry of niclosamide, inclusion complex with cyclodextrin was prepared by freeze drying method and characterized using FT-IR, DSC, PXRD, and 1HNMR. In silico molecular modeling study was performed to study the possible interactions between niclosamide and cyclodextrin. The anticancer activity of niclosamide formulation was evaluated through in vitro cell cytotoxicity study using various cancer cell lines. The potential of niclosamide complex for improvement of the bioavailability was evaluated in male BALB/c mice. In vitro cytotoxicity studies indicated significantly higher cytotoxicity at lower concentrations and the pharmacokinetic studies showed significant improvement in Cmax and Tmax of niclosamide from cyclodextrin complex in comparison to pure niclosamide alone.


Assuntos
Antineoplásicos/síntese química , Ciclodextrinas/síntese química , Composição de Medicamentos/métodos , Reposicionamento de Medicamentos/métodos , Niclosamida/síntese química , Animais , Anticestoides/síntese química , Anticestoides/metabolismo , Antineoplásicos/metabolismo , Ciclodextrinas/metabolismo , Avaliação Pré-Clínica de Medicamentos/métodos , Células HCT116 , Humanos , Masculino , Camundongos , Camundongos Endogâmicos BALB C , Niclosamida/metabolismo
14.
Biomed Pharmacother ; 111: 934-946, 2019 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-30841473

RESUMO

Increasing development costs and higher failure rate in clinical trials has reduced the repertoire of newer drugs in the market for clinical use. The most appropriate approach to end the search for newer drugs is "Repositioning", as it requires less time and money to explore new indication of existing drug or failed drug. In the past, several drugs have been repositioned for different indication but the full potential remains unharnessed. With rise in cancer prevalence and treatment costs, it is imperative to search for newer drugs and the use of repositioning approach may help us. Fluoroquinolones has been used as antibiotics for over four decades now, but recent research highlighted their use as pharmacological compounds with multifaceted implication. Repositioning of fluoroquinolones into anti-cancer molecule seems to be a highly plausible option owing to their profound immunomodulatory, pro-apoptotic, anti-proliferative and anti-metastatic potential. The present review provides a comprehensive account of the recent and past explorations pertaining to the anti-cancer activity of fluoroquinolones and also discusses the various approaches that are being considered to remodel them for the treatment of cancer.


Assuntos
Antibacterianos/farmacologia , Antibacterianos/uso terapêutico , Antineoplásicos/farmacologia , Antineoplásicos/uso terapêutico , Fluoroquinolonas/farmacologia , Fluoroquinolonas/uso terapêutico , Neoplasias/tratamento farmacológico , Animais , Reposicionamento de Medicamentos/métodos , Humanos
15.
J Clin Pharm Ther ; 44(3): 337-348, 2019 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-30738020

RESUMO

WHAT IS KNOWN AND OBJECTIVE: Alzheimer's disease (AD) is the most common cause of dementia among the elderly. The exact cause of the disease is not clearly known, and no existing therapies are able to prevent disease progression. Identification of the possible "impaired brain insulin signalling in AD" enriched the scope for "the repurposing of diabetic drugs in AD management." Among the different classes of diabetic drugs, pioglitazone (PIO), a PPARγ agonist classed as an insulin sensitizer, is of the highest interest for AD management. The drug is reported to have direct action on multiple targets involved in AD, independent of insulin signalling. Even though PIO has appeared to be a potent molecule in preclinical trials, limited success was observed in the clinical stage. The tentative reasons for the limited therapeutic success in the clinical stage are not clear. The main focus of the review is to discuss various factors that might limit the therapeutic success of PIO in clinical trials and possible approaches to overcome those limitations. METHOD: The research articles, review articles, and patents containing information regarding the clinical and preclinical trials of PIO in AD have been reviewed thoroughly using the keywords related to diabetic drugs in AD, PIO for AD management and mechanism of PIO in AD. Literature search was conducted on PubMed, SCOPUS and EMBASE. RESULTS AND DISCUSSION: Previous studies have indicated that the blood-brain barrier (BBB) is the biggest challenge to delivering PIO to the brain. Therefore, to attain a therapeutic concentration in the brain, a higher dose is needed, which is also supported by preclinical investigations in AD; however, in clinical studies, scientists have used the usual diabetic doses. This dose is inadequate to attain a therapeutic concentration in the brain and appears to be the primary reason for the limited success of PIO in clinical trials. The stage of drug intervention and the nature of the study population are also influential factors for the therapeutic response. WHAT IS NEW AND CONCLUSION: The insufficient concentration of the drug reaching the brain appears to be the crucial factor that limits the therapeutic success of PIO in AD management. Since the administration of higher doses cannot be recommended due to safety issues, the current situation demands the use of novel tools to ensure a therapeutic concentration reaches the brain.


Assuntos
Doença de Alzheimer/tratamento farmacológico , Hipoglicemiantes/farmacologia , Hipoglicemiantes/uso terapêutico , Pioglitazona/farmacologia , Pioglitazona/uso terapêutico , Doença de Alzheimer/metabolismo , Animais , Química Farmacêutica/métodos , Reposicionamento de Medicamentos/métodos , Humanos , Insulina/metabolismo
16.
Gene ; 693: 114-126, 2019 Apr 20.
Artigo em Inglês | MEDLINE | ID: mdl-30716439

RESUMO

Arabinosyl tranferases (embA, embB, embC) are the key enzymes responsible for biogenesis of arabinan domain of arabinogalactan (AG) and lipoarabinomannan (LAM), two major heteropolysaccharide constituents of the peculiar mycobacterial cell envelope. EmbC is predominantly responsible for LAM synthesis and has been commonly associated with Ethambutol resistance. We have screened the FDA library against EmbC to reposition a drug better than Ethambutol with higher binding affinity to Embc. High throughput virtual screening followed by extra precision docking using Glide gave two best leads i.e. Terlipressin and Amikacin with docking score of -11.39 kcal/mol and -10.71 kcal/mol, respectively. Binding mechanics of the selected drugs was elucidated through long range molecular dynamics simulations (100 ns) using binding free energy rescoring, essential dynamics and free energy minima based approaches, thus revealing the most stable binding modes of Terlipressin with EmbC. Our study establishes the EmbC binding potential of the repurposed drugs Terlipressin and Amikacin.


Assuntos
Mycobacterium tuberculosis/efeitos dos fármacos , Pentosiltransferases/efeitos dos fármacos , Pentosiltransferases/farmacocinética , Sequência de Aminoácidos , Antituberculosos/farmacocinética , Antituberculosos/farmacologia , Proteínas de Bactérias/metabolismo , Parede Celular/metabolismo , Reposicionamento de Medicamentos/métodos , Galactanos , Lipopolissacarídeos , Simulação de Dinâmica Molecular , Mycobacterium tuberculosis/enzimologia , Mycobacterium tuberculosis/metabolismo
17.
BMJ Case Rep ; 12(1)2019 Jan 14.
Artigo em Inglês | MEDLINE | ID: mdl-30642865

RESUMO

A 61-year-old woman with chronic lymphocytic leukaemia, with Richter's transformation to a diffuse, large, B-cell lymphoma, treated with six cycles of rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone and in complete remission, presented to the hospital after her platelets were found to be 2×10³/µL in outpatient laboratory studies. She initially underwent a platelet transfusion without improvement. This was followed by 4 days of high-dose dexamethasone and intravenous immunoglobulin, which again yielded no meaningful effect. Even a single-dose rituximab failed to achieve a platelet increase after 5 days of monitoring. The patient was then given 2 mg of intravenous vincristine along with a high-dose of dexamethasone and IVIG and demonstrated substantial recovery in platelets to >50×10³/µL within 48 hours. This case study provides an overview of the current management strategies for idiopathic thrombocytopenic purpura that is unresponsive to conventional medical therapy and particularly sheds light on their therapeutic benefits and potential adverse effects.


Assuntos
Protocolos Clínicos/normas , Reposicionamento de Medicamentos/métodos , Linfoma Difuso de Grandes Células B/tratamento farmacológico , Púrpura Trombocitopênica Idiopática/diagnóstico , Vincristina/uso terapêutico , Dexametasona/administração & dosagem , Dexametasona/uso terapêutico , Resistência a Múltiplos Medicamentos , Feminino , Glucocorticoides/uso terapêutico , Humanos , Imunoglobulinas Intravenosas/uso terapêutico , Leucemia Linfocítica Crônica de Células B/complicações , Linfoma Difuso de Grandes Células B/patologia , Pessoa de Meia-Idade , Transfusão de Plaquetas/métodos , Púrpura Trombocitopênica Idiopática/sangue , Púrpura Trombocitopênica Idiopática/terapia , Resultado do Tratamento , Moduladores de Tubulina/uso terapêutico , Vincristina/administração & dosagem
18.
Life Sci ; 220: 8-20, 2019 Mar 01.
Artigo em Inglês | MEDLINE | ID: mdl-30611787

RESUMO

Drug repurposing off late has been emerging as an inspiring alternative approach to conventional, exhaustive and arduous process of drug discovery. It is a process of identifying new therapeutic values for a drug already established for the treatment of a certain condition. Our current study is aimed at repurposing the old anti-helimenthic drug Niclosamide as an anti-fibrotic drug against pulmonary fibrosis (PF). PF is most common lethal interstitial lung disease hallmarked by deposition of extracelluar matrix and scarring of lung. Heterogenous nature, untimely diagnosis and lack of appropriate treatment options make PF an inexorable lung disorder. Prevailing void in PF treatment and drug repositioning strategy of drugs kindled our interest to demonstrate the anti-fibrotic activity of Niclosamide. Our study is aimed at investigating the anti-fibrotic potential of Niclosamide in TGF-ß1 induced in vitro model of PF and 21-day model of Bleomycin induced PF in vivo respectively. Our study results showed that Niclosamide holds the potential to exert anti-fibrotic effect by hampering fibroblast migration, attenuating EMT, inhibiting fibrotic signaling and by regulating WNT/ß-catenin signaling as evident from protein expression studies. Our study findings can give new directions to development of Niclosamide as an anti-fibrotic agent for treatment of pulmonary fibrosis.


Assuntos
Niclosamida/farmacologia , Fibrose Pulmonar/tratamento farmacológico , Animais , Bleomicina , Técnicas de Cultura de Células , Sobrevivência Celular/efeitos dos fármacos , Reposicionamento de Medicamentos/métodos , Células Epiteliais/efeitos dos fármacos , Transição Epitelial-Mesenquimal/efeitos dos fármacos , Fibroblastos/efeitos dos fármacos , Humanos , Pulmão/metabolismo , Masculino , Camundongos , Fator de Crescimento Transformador beta1/metabolismo , Via de Sinalização Wnt/efeitos dos fármacos , beta Catenina/efeitos dos fármacos
19.
Methods Mol Biol ; 1903: 1-21, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30547433

RESUMO

Drug repurposing is a creative and resourceful approach to increase the number of therapies by exploiting available and approved drugs. However, identifying new protein targets for previously approved drugs is challenging. Although new strategies have been developed for drug repurposing, there is broad agreement that there is room for further improvements. In this chapter, we review protein-protein interaction (PPI) interface-targeting strategies for drug repurposing applications. We discuss certain features, such as hot spot residue and hot region prediction and their importance in drug repurposing, and illustrate common methods used in PPI networks to identify drug off-targets. We also collect available online resources for hot spot prediction, binding pocket identification, and interface clustering which are effective resources in polypharmacology. Finally, we provide case studies showing the significance of protein interfaces and hot spots in drug repurposing.


Assuntos
Biologia Computacional , Reposicionamento de Medicamentos , Ligação Proteica/efeitos dos fármacos , Mapeamento de Interação de Proteínas , Biologia Computacional/métodos , Bases de Dados de Proteínas , Descoberta de Drogas , Reposicionamento de Medicamentos/métodos , Ligantes , Modelos Moleculares , Conformação Molecular , Mapeamento de Interação de Proteínas/métodos , Mapas de Interação de Proteínas , Proteínas/química , Relação Estrutura-Atividade
20.
Methods Mol Biol ; 1903: 23-43, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30547434

RESUMO

Drug repurposing has become one of the most widely used methods that can make drug discovery more efficient and less expensive. Additionally, computational methods such as structure-based drug designing can be utilized to make drug discovery more efficient and more accurate. Now imagine what can be achieved by combining drug repurposing and computational methods together in drug discovery, "in silico repurposing." In this chapter, we tried to describe a method that combines structure-based virtual screening and molecular dynamics simulation which can find effective compounds among existing drugs that may affect on a specific molecular target. By using molecular docking as a tool for the screening process and then by calculating ligand binding in an active receptor site using scoring functions and inspecting the proper orientation of pharmacophores in the binding site, the potential compounds will be chosen. After that, in order to test the potential compounds in a realistic environment, molecular dynamics simulation and related analysis have to be carried out for separating the false positives and the true positives from each other and finally identifying true "Hit" compounds. It's good to emphasize that if any of these identified potential compounds turn out to have the efficacy to affect that specific molecular target, it can be taken to the phase 2 clinical trials straightaway.


Assuntos
Reposicionamento de Medicamentos , Simulação de Acoplamento Molecular , Simulação de Dinâmica Molecular , Sítios de Ligação , Biologia Computacional/métodos , Interpretação Estatística de Dados , Descoberta de Drogas , Reposicionamento de Medicamentos/métodos , Ensaios de Triagem em Larga Escala , Ligantes , Ligação Proteica , Relação Quantitativa Estrutura-Atividade
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