Drug Discovery for Neglected Diseases: Molecular Target-Based and Phenotypic Approaches

PubMed Central

2013-01-01

Drug discovery for neglected tropical diseases is carried out using both target-based and phenotypic approaches. In this paper, target-based approaches are discussed, with a particular focus on human African trypanosomiasis. Target-based drug discovery can be successful, but careful selection of targets is required. There are still very few fully validated drug targets in neglected diseases, and there is a high attrition rate in target-based drug discovery for these diseases. Phenotypic screening is a powerful method in both neglected and non-neglected diseases and has been very successfully used. Identification of molecular targets from phenotypic approaches can be a way to identify potential new drug targets. PMID:24015767

Proteomic validation of protease drug targets: pharmacoproteomics of matrix metalloproteinase inhibitor drugs using isotope-coded affinity tag labelling and tandem mass spectrometry.

PubMed

Butler, G S; Overall, C M

2007-01-01

We illustrate the use of quantitative proteomics, namely isotope-coded affinity tag labelling and tandem mass spectrometry, to assess the targets and effects of the blockade of matrix metalloproteinases by an inhibitor drug in a breast cancer cell culture system. Treatment of MT1-MMP-transfected MDA-MB-231 cells with AG3340 (Prinomastat) directly affected the processing a multitude of matrix metalloproteinase substrates, and indirectly altered the expression of an array of other proteins with diverse functions. Therefore, broad spectrum blockade of MMPs has wide-ranging biological consequences. In this human breast cancer cell line, secreted substrates accumulated uncleaved in the conditioned medium and plasma membrane protein substrates were retained on the cell surface, due to reduced processing and shedding of these proteins (cell surface receptors, growth factors and bioactive molecules) to the medium in the presence of the matrix metalloproteinase inhibitor. Hence, proteomic investigation of drug-perturbed cellular proteomes can identify new protease substrates and at the same time provides valuable information for target validation, drug efficacy and potential side effects prior to commitment to clinical trials.

Validation of N-myristoyltransferase as an antimalarial drug target using an integrated chemical biology approach

NASA Astrophysics Data System (ADS)

Wright, Megan H.; Clough, Barbara; Rackham, Mark D.; Rangachari, Kaveri; Brannigan, James A.; Grainger, Munira; Moss, David K.; Bottrill, Andrew R.; Heal, William P.; Broncel, Malgorzata; Serwa, Remigiusz A.; Brady, Declan; Mann, David J.; Leatherbarrow, Robin J.; Tewari, Rita; Wilkinson, Anthony J.; Holder, Anthony A.; Tate, Edward W.

2014-02-01

Malaria is an infectious disease caused by parasites of the genus Plasmodium, which leads to approximately one million deaths per annum worldwide. Chemical validation of new antimalarial targets is urgently required in view of rising resistance to current drugs. One such putative target is the enzyme N-myristoyltransferase, which catalyses the attachment of the fatty acid myristate to protein substrates (N-myristoylation). Here, we report an integrated chemical biology approach to explore protein myristoylation in the major human parasite P. falciparum, combining chemical proteomic tools for identification of the myristoylated and glycosylphosphatidylinositol-anchored proteome with selective small-molecule N-myristoyltransferase inhibitors. We demonstrate that N-myristoyltransferase is an essential and chemically tractable target in malaria parasites both in vitro and in vivo, and show that selective inhibition of N-myristoylation leads to catastrophic and irreversible failure to assemble the inner membrane complex, a critical subcellular organelle in the parasite life cycle. Our studies provide the basis for the development of new antimalarials targeting N-myristoyltransferase.

Targeting bacterial central metabolism for drug development.

PubMed

Murima, Paul; McKinney, John D; Pethe, Kevin

2014-11-20

Current antibiotics, derived mainly from natural sources, inhibit a narrow spectrum of cellular processes, namely DNA replication, protein synthesis, and cell wall biosynthesis. With the worldwide explosion of drug resistance, there is renewed interest in the investigation of alternate essential cellular processes, including bacterial central metabolic pathways, as a drug target space for the next generation of antibiotics. However, the validation of targets in central metabolism is more complex, as essentiality of such targets can be conditional and/or contextual. Bearing in mind our enhanced understanding of prokaryotic central metabolism, a key question arises: can central metabolism be bacteria's Achilles' heel and a therapeutic target for the development of new classes of antibiotics? In this review, we draw lessons from oncology and attempt to address some of the open questions related to feasibility of targeting bacterial central metabolism as a strategy for developing new antibacterial drugs. Copyright © 2014 Elsevier Ltd. All rights reserved.

Genome-Scale Screening of Drug-Target Associations Relevant to Ki Using a Chemogenomics Approach

PubMed Central

Cao, Dong-Sheng; Liang, Yi-Zeng; Deng, Zhe; Hu, Qian-Nan; He, Min; Xu, Qing-Song; Zhou, Guang-Hua; Zhang, Liu-Xia; Deng, Zi-xin; Liu, Shao

2013-01-01

The identification of interactions between drugs and target proteins plays a key role in genomic drug discovery. In the present study, the quantitative binding affinities of drug-target pairs are differentiated as a measurement to define whether a drug interacts with a protein or not, and then a chemogenomics framework using an unbiased set of general integrated features and random forest (RF) is employed to construct a predictive model which can accurately classify drug-target pairs. The predictability of the model is further investigated and validated by several independent validation sets. The built model is used to predict drug-target associations, some of which were confirmed by comparing experimental data from public biological resources. A drug-target interaction network with high confidence drug-target pairs was also reconstructed. This network provides further insight for the action of drugs and targets. Finally, a web-based server called PreDPI-Ki was developed to predict drug-target interactions for drug discovery. In addition to providing a high-confidence list of drug-target associations for subsequent experimental investigation guidance, these results also contribute to the understanding of drug-target interactions. We can also see that quantitative information of drug-target associations could greatly promote the development of more accurate models. The PreDPI-Ki server is freely available via: http://sdd.whu.edu.cn/dpiki. PMID:23577055

Genomes2Drugs: Identifies Target Proteins and Lead Drugs from Proteome Data

PubMed Central

Toomey, David; Hoppe, Heinrich C.; Brennan, Marian P.; Nolan, Kevin B.; Chubb, Anthony J.

2009-01-01

Background Genome sequencing and bioinformatics have provided the full hypothetical proteome of many pathogenic organisms. Advances in microarray and mass spectrometry have also yielded large output datasets of possible target proteins/genes. However, the challenge remains to identify new targets for drug discovery from this wealth of information. Further analysis includes bioinformatics and/or molecular biology tools to validate the findings. This is time consuming and expensive, and could fail to yield novel drugs if protein purification and crystallography is impossible. To pre-empt this, a researcher may want to rapidly filter the output datasets for proteins that show good homology to proteins that have already been structurally characterised or proteins that are already targets for known drugs. Critically, those researchers developing novel antibiotics need to select out the proteins that show close homology to any human proteins, as future inhibitors are likely to cross-react with the host protein, causing off-target toxicity effects later in clinical trials. Methodology/Principal Findings To solve many of these issues, we have developed a free online resource called Genomes2Drugs which ranks sequences to identify proteins that are (i) homologous to previously crystallized proteins or (ii) targets of known drugs, but are (iii) not homologous to human proteins. When tested using the Plasmodium falciparum malarial genome the program correctly enriched the ranked list of proteins with known drug target proteins. Conclusions/Significance Genomes2Drugs rapidly identifies proteins that are likely to succeed in drug discovery pipelines. This free online resource helps in the identification of potential drug targets. Importantly, the program further highlights proteins that are likely to be inhibited by FDA-approved drugs. These drugs can then be rapidly moved into Phase IV clinical studies under ‘change-of-application’ patents. PMID:19593435

Drug-Target Kinetics in Drug Discovery.

PubMed

Tonge, Peter J

2018-01-17

The development of therapies for the treatment of neurological cancer faces a number of major challenges including the synthesis of small molecule agents that can penetrate the blood-brain barrier (BBB). Given the likelihood that in many cases drug exposure will be lower in the CNS than in systemic circulation, it follows that strategies should be employed that can sustain target engagement at low drug concentration. Time dependent target occupancy is a function of both the drug and target concentration as well as the thermodynamic and kinetic parameters that describe the binding reaction coordinate, and sustained target occupancy can be achieved through structural modifications that increase target (re)binding and/or that decrease the rate of drug dissociation. The discovery and deployment of compounds with optimized kinetic effects requires information on the structure-kinetic relationships that modulate the kinetics of binding, and the molecular factors that control the translation of drug-target kinetics to time-dependent drug activity in the disease state. This Review first introduces the potential benefits of drug-target kinetics, such as the ability to delineate both thermodynamic and kinetic selectivity, and then describes factors, such as target vulnerability, that impact the utility of kinetic selectivity. The Review concludes with a description of a mechanistic PK/PD model that integrates drug-target kinetics into predictions of drug activity.

Discovery of novel drugs for promising targets.

PubMed

Martell, Robert E; Brooks, David G; Wang, Yan; Wilcoxen, Keith

2013-09-01

Once a promising drug target is identified, the steps to actually discover and optimize a drug are diverse and challenging. The goal of this study was to provide a road map to navigate drug discovery. Review general steps for drug discovery and provide illustrating references. A number of approaches are available to enhance and accelerate target identification and validation. Consideration of a variety of potential mechanisms of action of potential drugs can guide discovery efforts. The hit to lead stage may involve techniques such as high-throughput screening, fragment-based screening, and structure-based design, with informatics playing an ever-increasing role. Biologically relevant screening models are discussed, including cell lines, 3-dimensional culture, and in vivo screening. The process of enabling human studies for an investigational drug is also discussed. Drug discovery is a complex process that has significantly evolved in recent years. © 2013 Elsevier HS Journals, Inc. All rights reserved.

Target-similarity search using Plasmodium falciparum proteome identifies approved drugs with anti-malarial activity and their possible targets

PubMed Central

Akala, Hoseah M.; Macharia, Rosaline W.; Juma, Dennis W.; Cheruiyot, Agnes C.; Andagalu, Ben; Brown, Mathew L.; El-Shemy, Hany A.; Nyanjom, Steven G.

2017-01-01

Malaria causes about half a million deaths annually, with Plasmodium falciparum being responsible for 90% of all the cases. Recent reports on artemisinin resistance in Southeast Asia warrant urgent discovery of novel drugs for the treatment of malaria. However, most bioactive compounds fail to progress to treatments due to safety concerns. Drug repositioning offers an alternative strategy where drugs that have already been approved as safe for other diseases could be used to treat malaria. This study screened approved drugs for antimalarial activity using an in silico chemogenomics approach prior to in vitro verification. All the P. falciparum proteins sequences available in NCBI RefSeq were mined and used to perform a similarity search against DrugBank, TTD and STITCH databases to identify similar putative drug targets. Druggability indices of the potential P. falciparum drug targets were obtained from TDR targets database. Functional amino acid residues of the drug targets were determined using ConSurf server which was used to fine tune the similarity search. This study predicted 133 approved drugs that could target 34 P. falciparum proteins. A literature search done at PubMed and Google Scholar showed 105 out of the 133 drugs to have been previously tested against malaria, with most showing activity. For further validation, drug susceptibility assays using SYBR Green I method were done on a representative group of 10 predicted drugs, eight of which did show activity against P. falciparum 3D7 clone. Seven had IC50 values ranging from 1 μM to 50 μM. This study also suggests drug-target association and hence possible mechanisms of action of drugs that did show antiplasmodial activity. The study results validate the use of proteome-wide target similarity approach in identifying approved drugs with activity against P. falciparum and could be adapted for other pathogens. PMID:29088219

Drug target ontology to classify and integrate drug discovery data.

PubMed

Lin, Yu; Mehta, Saurabh; Küçük-McGinty, Hande; Turner, John Paul; Vidovic, Dusica; Forlin, Michele; Koleti, Amar; Nguyen, Dac-Trung; Jensen, Lars Juhl; Guha, Rajarshi; Mathias, Stephen L; Ursu, Oleg; Stathias, Vasileios; Duan, Jianbin; Nabizadeh, Nooshin; Chung, Caty; Mader, Christopher; Visser, Ubbo; Yang, Jeremy J; Bologa, Cristian G; Oprea, Tudor I; Schürer, Stephan C

2017-11-09

One of the most successful approaches to develop new small molecule therapeutics has been to start from a validated druggable protein target. However, only a small subset of potentially druggable targets has attracted significant research and development resources. The Illuminating the Druggable Genome (IDG) project develops resources to catalyze the development of likely targetable, yet currently understudied prospective drug targets. A central component of the IDG program is a comprehensive knowledge resource of the druggable genome. As part of that effort, we have developed a framework to integrate, navigate, and analyze drug discovery data based on formalized and standardized classifications and annotations of druggable protein targets, the Drug Target Ontology (DTO). DTO was constructed by extensive curation and consolidation of various resources. DTO classifies the four major drug target protein families, GPCRs, kinases, ion channels and nuclear receptors, based on phylogenecity, function, target development level, disease association, tissue expression, chemical ligand and substrate characteristics, and target-family specific characteristics. The formal ontology was built using a new software tool to auto-generate most axioms from a database while supporting manual knowledge acquisition. A modular, hierarchical implementation facilitate ontology development and maintenance and makes use of various external ontologies, thus integrating the DTO into the ecosystem of biomedical ontologies. As a formal OWL-DL ontology, DTO contains asserted and inferred axioms. Modeling data from the Library of Integrated Network-based Cellular Signatures (LINCS) program illustrates the potential of DTO for contextual data integration and nuanced definition of important drug target characteristics. DTO has been implemented in the IDG user interface Portal, Pharos and the TIN-X explorer of protein target disease relationships. DTO was built based on the need for a formal semantic

Predicting Drug-Target Interactions With Multi-Information Fusion.

PubMed

Peng, Lihong; Liao, Bo; Zhu, Wen; Li, Zejun; Li, Keqin

2017-03-01

Identifying potential associations between drugs and targets is a critical prerequisite for modern drug discovery and repurposing. However, predicting these associations is difficult because of the limitations of existing computational methods. Most models only consider chemical structures and protein sequences, and other models are oversimplified. Moreover, datasets used for analysis contain only true-positive interactions, and experimentally validated negative samples are unavailable. To overcome these limitations, we developed a semi-supervised based learning framework called NormMulInf through collaborative filtering theory by using labeled and unlabeled interaction information. The proposed method initially determines similarity measures, such as similarities among samples and local correlations among the labels of the samples, by integrating biological information. The similarity information is then integrated into a robust principal component analysis model, which is solved using augmented Lagrange multipliers. Experimental results on four classes of drug-target interaction networks suggest that the proposed approach can accurately classify and predict drug-target interactions. Part of the predicted interactions are reported in public databases. The proposed method can also predict possible targets for new drugs and can be used to determine whether atropine may interact with alpha1B- and beta1- adrenergic receptors. Furthermore, the developed technique identifies potential drugs for new targets and can be used to assess whether olanzapine and propiomazine may target 5HT2B. Finally, the proposed method can potentially address limitations on studies of multitarget drugs and multidrug targets.

DrugE-Rank: improving drug–target interaction prediction of new candidate drugs or targets by ensemble learning to rank

PubMed Central

Yuan, Qingjun; Gao, Junning; Wu, Dongliang; Zhang, Shihua; Mamitsuka, Hiroshi; Zhu, Shanfeng

2016-01-01

Motivation: Identifying drug–target interactions is an important task in drug discovery. To reduce heavy time and financial cost in experimental way, many computational approaches have been proposed. Although these approaches have used many different principles, their performance is far from satisfactory, especially in predicting drug–target interactions of new candidate drugs or targets. Methods: Approaches based on machine learning for this problem can be divided into two types: feature-based and similarity-based methods. Learning to rank is the most powerful technique in the feature-based methods. Similarity-based methods are well accepted, due to their idea of connecting the chemical and genomic spaces, represented by drug and target similarities, respectively. We propose a new method, DrugE-Rank, to improve the prediction performance by nicely combining the advantages of the two different types of methods. That is, DrugE-Rank uses LTR, for which multiple well-known similarity-based methods can be used as components of ensemble learning. Results: The performance of DrugE-Rank is thoroughly examined by three main experiments using data from DrugBank: (i) cross-validation on FDA (US Food and Drug Administration) approved drugs before March 2014; (ii) independent test on FDA approved drugs after March 2014; and (iii) independent test on FDA experimental drugs. Experimental results show that DrugE-Rank outperforms competing methods significantly, especially achieving more than 30% improvement in Area under Prediction Recall curve for FDA approved new drugs and FDA experimental drugs. Availability: http://datamining-iip.fudan.edu.cn/service/DrugE-Rank Contact: zhusf@fudan.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307615

Drug-Target Interaction Prediction through Label Propagation with Linear Neighborhood Information.

PubMed

Zhang, Wen; Chen, Yanlin; Li, Dingfang

2017-11-25

Interactions between drugs and target proteins provide important information for the drug discovery. Currently, experiments identified only a small number of drug-target interactions. Therefore, the development of computational methods for drug-target interaction prediction is an urgent task of theoretical interest and practical significance. In this paper, we propose a label propagation method with linear neighborhood information (LPLNI) for predicting unobserved drug-target interactions. Firstly, we calculate drug-drug linear neighborhood similarity in the feature spaces, by considering how to reconstruct data points from neighbors. Then, we take similarities as the manifold of drugs, and assume the manifold unchanged in the interaction space. At last, we predict unobserved interactions between known drugs and targets by using drug-drug linear neighborhood similarity and known drug-target interactions. The experiments show that LPLNI can utilize only known drug-target interactions to make high-accuracy predictions on four benchmark datasets. Furthermore, we consider incorporating chemical structures into LPLNI models. Experimental results demonstrate that the model with integrated information (LPLNI-II) can produce improved performances, better than other state-of-the-art methods. The known drug-target interactions are an important information source for computational predictions. The usefulness of the proposed method is demonstrated by cross validation and the case study.

A Computational Approach to Finding Novel Targets for Existing Drugs

PubMed Central

Li, Yvonne Y.; An, Jianghong; Jones, Steven J. M.

2011-01-01

Repositioning existing drugs for new therapeutic uses is an efficient approach to drug discovery. We have developed a computational drug repositioning pipeline to perform large-scale molecular docking of small molecule drugs against protein drug targets, in order to map the drug-target interaction space and find novel interactions. Our method emphasizes removing false positive interaction predictions using criteria from known interaction docking, consensus scoring, and specificity. In all, our database contains 252 human protein drug targets that we classify as reliable-for-docking as well as 4621 approved and experimental small molecule drugs from DrugBank. These were cross-docked, then filtered through stringent scoring criteria to select top drug-target interactions. In particular, we used MAPK14 and the kinase inhibitor BIM-8 as examples where our stringent thresholds enriched the predicted drug-target interactions with known interactions up to 20 times compared to standard score thresholds. We validated nilotinib as a potent MAPK14 inhibitor in vitro (IC50 40 nM), suggesting a potential use for this drug in treating inflammatory diseases. The published literature indicated experimental evidence for 31 of the top predicted interactions, highlighting the promising nature of our approach. Novel interactions discovered may lead to the drug being repositioned as a therapeutic treatment for its off-target's associated disease, added insight into the drug's mechanism of action, and added insight into the drug's side effects. PMID:21909252

Exploring drug-target interaction networks of illicit drugs.

PubMed

Atreya, Ravi V; Sun, Jingchun; Zhao, Zhongming

2013-01-01

Drug addiction is a complex and chronic mental disease, which places a large burden on the American healthcare system due to its negative effects on patients and their families. Recently, network pharmacology is emerging as a promising approach to drug discovery by integrating network biology and polypharmacology, allowing for a deeper understanding of molecular mechanisms of drug actions at the systems level. This study seeks to apply this approach for investigation of illicit drugs and their targets in order to elucidate their interaction patterns and potential secondary drugs that can aid future research and clinical care. In this study, we extracted 188 illicit substances and their related information from the DrugBank database. The data process revealed 86 illicit drugs targeting a total of 73 unique human genes, which forms an illicit drug-target network. Compared to the full drug-target network from DrugBank, illicit drugs and their target genes tend to cluster together and form four subnetworks, corresponding to four major medication categories: depressants, stimulants, analgesics, and steroids. External analysis of Anatomical Therapeutic Chemical (ATC) second sublevel classifications confirmed that the illicit drugs have neurological functions or act via mechanisms of stimulants, opioids, and steroids. To further explore other drugs potentially having associations with illicit drugs, we constructed an illicit-extended drug-target network by adding the drugs that have the same target(s) as illicit drugs to the illicit drug-target network. After analyzing the degree and betweenness of the network, we identified hubs and bridge nodes, which might play important roles in the development and treatment of drug addiction. Among them, 49 non-illicit drugs might have potential to be used to treat addiction or have addictive effects, including some results that are supported by previous studies. This study presents the first systematic review of the network

Exploring drug-target interaction networks of illicit drugs

PubMed Central

2013-01-01

Background Drug addiction is a complex and chronic mental disease, which places a large burden on the American healthcare system due to its negative effects on patients and their families. Recently, network pharmacology is emerging as a promising approach to drug discovery by integrating network biology and polypharmacology, allowing for a deeper understanding of molecular mechanisms of drug actions at the systems level. This study seeks to apply this approach for investigation of illicit drugs and their targets in order to elucidate their interaction patterns and potential secondary drugs that can aid future research and clinical care. Results In this study, we extracted 188 illicit substances and their related information from the DrugBank database. The data process revealed 86 illicit drugs targeting a total of 73 unique human genes, which forms an illicit drug-target network. Compared to the full drug-target network from DrugBank, illicit drugs and their target genes tend to cluster together and form four subnetworks, corresponding to four major medication categories: depressants, stimulants, analgesics, and steroids. External analysis of Anatomical Therapeutic Chemical (ATC) second sublevel classifications confirmed that the illicit drugs have neurological functions or act via mechanisms of stimulants, opioids, and steroids. To further explore other drugs potentially having associations with illicit drugs, we constructed an illicit-extended drug-target network by adding the drugs that have the same target(s) as illicit drugs to the illicit drug-target network. After analyzing the degree and betweenness of the network, we identified hubs and bridge nodes, which might play important roles in the development and treatment of drug addiction. Among them, 49 non-illicit drugs might have potential to be used to treat addiction or have addictive effects, including some results that are supported by previous studies. Conclusions This study presents the first systematic

Advancing cancer drug discovery towards more agile development of targeted combination therapies.

PubMed

Carragher, Neil O; Unciti-Broceta, Asier; Cameron, David A

2012-01-01

Current drug-discovery strategies are typically 'target-centric' and are based upon high-throughput screening of large chemical libraries against nominated targets and a selection of lead compounds with optimized 'on-target' potency and selectivity profiles. However, high attrition of targeted agents in clinical development suggest that combinations of targeted agents will be most effective in treating solid tumors if the biological networks that permit cancer cells to subvert monotherapies are identified and retargeted. Conventional drug-discovery and development strategies are suboptimal for the rational design and development of novel drug combinations. In this article, we highlight a series of emerging technologies supporting a less reductionist, more agile, drug-discovery and development approach for the rational design, validation, prioritization and clinical development of novel drug combinations.

Predicting drug-target interactions using restricted Boltzmann machines.

PubMed

Wang, Yuhao; Zeng, Jianyang

2013-07-01

In silico prediction of drug-target interactions plays an important role toward identifying and developing new uses of existing or abandoned drugs. Network-based approaches have recently become a popular tool for discovering new drug-target interactions (DTIs). Unfortunately, most of these network-based approaches can only predict binary interactions between drugs and targets, and information about different types of interactions has not been well exploited for DTI prediction in previous studies. On the other hand, incorporating additional information about drug-target relationships or drug modes of action can improve prediction of DTIs. Furthermore, the predicted types of DTIs can broaden our understanding about the molecular basis of drug action. We propose a first machine learning approach to integrate multiple types of DTIs and predict unknown drug-target relationships or drug modes of action. We cast the new DTI prediction problem into a two-layer graphical model, called restricted Boltzmann machine, and apply a practical learning algorithm to train our model and make predictions. Tests on two public databases show that our restricted Boltzmann machine model can effectively capture the latent features of a DTI network and achieve excellent performance on predicting different types of DTIs, with the area under precision-recall curve up to 89.6. In addition, we demonstrate that integrating multiple types of DTIs can significantly outperform other predictions either by simply mixing multiple types of interactions without distinction or using only a single interaction type. Further tests show that our approach can infer a high fraction of novel DTIs that has been validated by known experiments in the literature or other databases. These results indicate that our approach can have highly practical relevance to DTI prediction and drug repositioning, and hence advance the drug discovery process. Software and datasets are available on request. Supplementary data are

DrugBank: a knowledgebase for drugs, drug actions and drug targets

PubMed Central

Wishart, David S.; Knox, Craig; Guo, An Chi; Cheng, Dean; Shrivastava, Savita; Tzur, Dan; Gautam, Bijaya; Hassanali, Murtaza

2008-01-01

DrugBank is a richly annotated resource that combines detailed drug data with comprehensive drug target and drug action information. Since its first release in 2006, DrugBank has been widely used to facilitate in silico drug target discovery, drug design, drug docking or screening, drug metabolism prediction, drug interaction prediction and general pharmaceutical education. The latest version of DrugBank (release 2.0) has been expanded significantly over the previous release. With ∼4900 drug entries, it now contains 60% more FDA-approved small molecule and biotech drugs including 10% more ‘experimental’ drugs. Significantly, more protein target data has also been added to the database, with the latest version of DrugBank containing three times as many non-redundant protein or drug target sequences as before (1565 versus 524). Each DrugCard entry now contains more than 100 data fields with half of the information being devoted to drug/chemical data and the other half devoted to pharmacological, pharmacogenomic and molecular biological data. A number of new data fields, including food–drug interactions, drug–drug interactions and experimental ADME data have been added in response to numerous user requests. DrugBank has also significantly improved the power and simplicity of its structure query and text query searches. DrugBank is available at http://www.drugbank.ca PMID:18048412

Targeting cysteine proteases in trypanosomatid disease drug discovery.

PubMed

Ferreira, Leonardo G; Andricopulo, Adriano D

2017-12-01

Chagas disease and human African trypanosomiasis are endemic conditions in Latin America and Africa, respectively, for which no effective and safe therapy is available. Efforts in drug discovery have focused on several enzymes from these protozoans, among which cysteine proteases have been validated as molecular targets for pharmacological intervention. These enzymes are expressed during the entire life cycle of trypanosomatid parasites and are essential to many biological processes, including infectivity to the human host. As a result of advances in the knowledge of the structural aspects of cysteine proteases and their role in disease physiopathology, inhibition of these enzymes by small molecules has been demonstrated to be a worthwhile approach to trypanosomatid drug research. This review provides an update on drug discovery strategies targeting the cysteine peptidases cruzain from Trypanosoma cruzi and rhodesain and cathepsin B from Trypanosoma brucei. Given that current chemotherapy for Chagas disease and human African trypanosomiasis has several drawbacks, cysteine proteases will continue to be actively pursued as valuable molecular targets in trypanosomatid disease drug discovery efforts. Copyright © 2017. Published by Elsevier Inc.

Focus on flaviviruses: current and future drug targets.

PubMed

Geiss, Brian J; Stahla, Hillary; Hannah, Amanda M; Gari, Amanda M; Keenan, Susan M

2009-05-01

Infection by mosquito-borne flaviviruses (family Flaviviridae) is increasing in prevalence worldwide. The vast global, social and economic impact due to the morbidity and mortality associated with the diseases caused by these viruses necessitates therapeutic intervention. There is currently no effective clinical treatment for any flaviviral infection. Therefore, there is a great need for the identification of novel inhibitors to target the virus life cycle. In this article, we discuss structural and nonstructural viral proteins that are the focus of current target validation and drug discovery efforts. Both inhibition of essential enzymatic activities and disruption of necessary protein–protein interactions are considered. In addition, we address promising new targets for future research. As our molecular and biochemical understanding of the flavivirus life cycle increases, the number of targets for antiviral therapeutic discovery grows and the possibility for novel drug discovery continues to strengthen.

The Tuberculosis Drug Discovery and Development Pipeline and Emerging Drug Targets

PubMed Central

Mdluli, Khisimuzi; Kaneko, Takushi; Upton, Anna

2015-01-01

The recent accelerated approval for use in extensively drug-resistant and multidrug-resistant-tuberculosis (MDR-TB) of two first-in-class TB drugs, bedaquiline and delamanid, has reinvigorated the TB drug discovery and development field. However, although several promising clinical development programs are ongoing to evaluate new TB drugs and regimens, the number of novel series represented is few. The global early-development pipeline is also woefully thin. To have a chance of achieving the goal of better, shorter, safer TB drug regimens with utility against drug-sensitive and drug-resistant disease, a robust and diverse global TB drug discovery pipeline is key, including innovative approaches that make use of recently acquired knowledge on the biology of TB. Fortunately, drug discovery for TB has resurged in recent years, generating compounds with varying potential for progression into developable leads. In parallel, advances have been made in understanding TB pathogenesis. It is now possible to apply the lessons learned from recent TB hit generation efforts and newly validated TB drug targets to generate the next wave of TB drug leads. Use of currently underexploited sources of chemical matter and lead-optimization strategies may also improve the efficiency of future TB drug discovery. Novel TB drug regimens with shorter treatment durations must target all subpopulations of Mycobacterium tuberculosis existing in an infection, including those responsible for the protracted TB treatment duration. This review summarizes the current TB drug development pipeline and proposes strategies for generating improved hits and leads in the discovery phase that could help achieve this goal. PMID:25635061

Targeting ALK: Precision Medicine Takes On Drug Resistance

PubMed Central

Lin, Jessica J.; Riely, Gregory J.; Shaw, Alice T.

2017-01-01

Anaplastic lymphoma kinase (ALK) is a validated molecular target in several ALK-rearranged malignancies, including non-small-cell lung cancer (NSCLC). However, the clinical benefit of targeting ALK using tyrosine kinase inhibitors (TKIs) is almost universally limited by the emergence of drug resistance. Diverse mechanisms of resistance to ALK TKIs have now been discovered, and these basic mechanisms are informing the development of novel therapeutic strategies to overcome resistance in the clinic. In this Review, we summarize the current successes and challenges of targeting ALK. PMID:28122866

Application of chemical biology in target identification and drug discovery.

PubMed

Zhu, Yue; Xiao, Ting; Lei, Saifei; Zhou, Fulai; Wang, Ming-Wei

2015-09-01

Drug discovery and development is vital to the well-being of mankind and sustainability of the pharmaceutical industry. Using chemical biology approaches to discover drug leads has become a widely accepted path partially because of the completion of the Human Genome Project. Chemical biology mainly solves biological problems through searching previously unknown targets for pharmacologically active small molecules or finding ligands for well-defined drug targets. It is a powerful tool to study how these small molecules interact with their respective targets, as well as their roles in signal transduction, molecular recognition and cell functions. There have been an increasing number of new therapeutic targets being identified and subsequently validated as a result of advances in functional genomics, which in turn led to the discovery of numerous active small molecules via a variety of high-throughput screening initiatives. In this review, we highlight some applications of chemical biology in the context of drug discovery.

Drug discovery in tuberculosis. New drug targets and antimycobacterial agents.

PubMed

Campaniço, André; Moreira, Rui; Lopes, Francisca

2018-04-25

Tuberculosis (TB) remains a major health problem worldwide. The infectious agent, Mycobacterium tuberculosis, has a unique ability to survive within the host, alternating between active and latent disease states, and escaping the immune system defences. The extended duration of anti-TB regimens and the increasing prevalence of multidrug- (MDR) and extensively drug-resistant (XDR) M. tuberculosis strains have created an urgent need for new antibiotics active against drug-resistant organisms and that can shorten standard therapy. However, despite success in identifying active compounds through phenotypic screens, the conversion of hits into novel chemical series and ultimately into clinical candidates is hampered by the poor efficacy in eliminating M. tuberculosis within different host compartments, including macrophages, as well as a lack of knowledge about the specific target(s) inhibited and/or upregulated. The current status of anti-TB lead generation has much improved over the last decade, as exemplified by the recent approval of bedaquiline and delamanid to treat MDR-TB and XDR-TB. This review provides a critical analysis on the strategies used to progress hit compounds into viable lead candidates, and how emerging targets may play a role in TB drug discovery in the near future. Four new relevant targets are addressed: the enoyl-acyl carrier protein reductase, InhA; the transmembrane transport protein large, MmpL3; the decaprenylphospho-beta-d-ribofuranose 2-oxidase, DprE1; and the ubiquinol-cytochrome C reductase, QcrB. Validated hit compounds for each target are presented and explored, and the medicinal chemistry strategies to expand SAR around novel chemotypes analyzed. In addition, very recent emerging targets are also discussed. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Grants4Targets - an innovative approach to translate ideas from basic research into novel drugs.

PubMed

Lessl, Monika; Schoepe, Stefanie; Sommer, Anette; Schneider, Martin; Asadullah, Khusru

2011-04-01

Collaborations between industry and academia are steadily gaining importance. To combine expertises Bayer Healthcare has set up a novel open innovation approach called Grants4Targets. Ideas on novel drug targets can easily be submitted to http://www.grants4targets.com. After a review process, grants are provided to perform focused experiments to further validate the proposed targets. In addition to financial support specific know-how on target validation and drug discovery is provided. Experienced scientists are nominated as project partners and, depending on the project, tools or specific models are provided. Around 280 applications have been received and 41 projects granted. According to our experience, this type of bridging fund combined with joint efforts provides a valuable tool to foster drug discovery collaborations. Copyright © 2010 Elsevier Ltd. All rights reserved.

UniDrug-target: a computational tool to identify unique drug targets in pathogenic bacteria.

PubMed

Chanumolu, Sree Krishna; Rout, Chittaranjan; Chauhan, Rajinder S

2012-01-01

Targeting conserved proteins of bacteria through antibacterial medications has resulted in both the development of resistant strains and changes to human health by destroying beneficial microbes which eventually become breeding grounds for the evolution of resistances. Despite the availability of more than 800 genomes sequences, 430 pathways, 4743 enzymes, 9257 metabolic reactions and protein (three-dimensional) 3D structures in bacteria, no pathogen-specific computational drug target identification tool has been developed. A web server, UniDrug-Target, which combines bacterial biological information and computational methods to stringently identify pathogen-specific proteins as drug targets, has been designed. Besides predicting pathogen-specific proteins essentiality, chokepoint property, etc., three new algorithms were developed and implemented by using protein sequences, domains, structures, and metabolic reactions for construction of partial metabolic networks (PMNs), determination of conservation in critical residues, and variation analysis of residues forming similar cavities in proteins sequences. First, PMNs are constructed to determine the extent of disturbances in metabolite production by targeting a protein as drug target. Conservation of pathogen-specific protein's critical residues involved in cavity formation and biological function determined at domain-level with low-matching sequences. Last, variation analysis of residues forming similar cavities in proteins sequences from pathogenic versus non-pathogenic bacteria and humans is performed. The server is capable of predicting drug targets for any sequenced pathogenic bacteria having fasta sequences and annotated information. The utility of UniDrug-Target server was demonstrated for Mycobacterium tuberculosis (H37Rv). The UniDrug-Target identified 265 mycobacteria pathogen-specific proteins, including 17 essential proteins which can be potential drug targets. UniDrug-Target is expected to accelerate

Assessment of deoxyhypusine hydroxylase as a putative, novel drug target.

PubMed

Kerscher, B; Nzukou, E; Kaiser, A

2010-02-01

Antimalarial drug resistance has nowadays reached each drug class on the market for longer than 10 years. The focus on validated, classical targets has severe drawbacks. If resistance is arising or already present in the field, a target-based High-Throughput-Screening (HTS) with the respective target involves the risk of identifying compounds to which field populations are also resistant. Thus, it appears that a rewarding albeit demanding challenge for target-based drug discovery is to identify novel drug targets. In the search for new targets for antimalarials, we have investigated the biosynthesis of hypusine, present in eukaryotic initiation factor 5A (eIF5A). Deoxyhypusine hydroxylase (DOHH), which has recently been cloned and expressed from P. falciparum, completes the modification of eIF5A through hydroxylation. Here, we assess the present druggable data on Plasmodium DOHH and its human counterpart. Plasmodium DOHH arose from a cyanobacterial phycobilin lyase by loss of function. It has a low FASTA score of 27 to its human counterpart. The HEAT-like repeats present in the parasite DOHH differ in number and amino acid identity from its human ortholog and might be of considerable interest for inhibitor design.

Computational-experimental approach to drug-target interaction mapping: A case study on kinase inhibitors

PubMed Central

Ravikumar, Balaguru; Parri, Elina; Timonen, Sanna; Airola, Antti; Wennerberg, Krister

2017-01-01

Due to relatively high costs and labor required for experimental profiling of the full target space of chemical compounds, various machine learning models have been proposed as cost-effective means to advance this process in terms of predicting the most potent compound-target interactions for subsequent verification. However, most of the model predictions lack direct experimental validation in the laboratory, making their practical benefits for drug discovery or repurposing applications largely unknown. Here, we therefore introduce and carefully test a systematic computational-experimental framework for the prediction and pre-clinical verification of drug-target interactions using a well-established kernel-based regression algorithm as the prediction model. To evaluate its performance, we first predicted unmeasured binding affinities in a large-scale kinase inhibitor profiling study, and then experimentally tested 100 compound-kinase pairs. The relatively high correlation of 0.77 (p < 0.0001) between the predicted and measured bioactivities supports the potential of the model for filling the experimental gaps in existing compound-target interaction maps. Further, we subjected the model to a more challenging task of predicting target interactions for such a new candidate drug compound that lacks prior binding profile information. As a specific case study, we used tivozanib, an investigational VEGF receptor inhibitor with currently unknown off-target profile. Among 7 kinases with high predicted affinity, we experimentally validated 4 new off-targets of tivozanib, namely the Src-family kinases FRK and FYN A, the non-receptor tyrosine kinase ABL1, and the serine/threonine kinase SLK. Our sub-sequent experimental validation protocol effectively avoids any possible information leakage between the training and validation data, and therefore enables rigorous model validation for practical applications. These results demonstrate that the kernel-based modeling approach

Drug Target Mining and Analysis of the Chinese Tree Shrew for Pharmacological Testing

PubMed Central

Liu, Jie; Lee, Wen-hui; Zhang, Yun

2014-01-01

The discovery of new drugs requires the development of improved animal models for drug testing. The Chinese tree shrew is considered to be a realistic candidate model. To assess the potential of the Chinese tree shrew for pharmacological testing, we performed drug target prediction and analysis on genomic and transcriptomic scales. Using our pipeline, 3,482 proteins were predicted to be drug targets. Of these predicted targets, 446 and 1,049 proteins with the highest rank and total scores, respectively, included homologs of targets for cancer chemotherapy, depression, age-related decline and cardiovascular disease. Based on comparative analyses, more than half of drug target proteins identified from the tree shrew genome were shown to be higher similarity to human targets than in the mouse. Target validation also demonstrated that the constitutive expression of the proteinase-activated receptors of tree shrew platelets is similar to that of human platelets but differs from that of mouse platelets. We developed an effective pipeline and search strategy for drug target prediction and the evaluation of model-based target identification for drug testing. This work provides useful information for future studies of the Chinese tree shrew as a source of novel targets for drug discovery research. PMID:25105297

A comparison of machine learning techniques for detection of drug target articles.

PubMed

Danger, Roxana; Segura-Bedmar, Isabel; Martínez, Paloma; Rosso, Paolo

2010-12-01

Important progress in treating diseases has been possible thanks to the identification of drug targets. Drug targets are the molecular structures whose abnormal activity, associated to a disease, can be modified by drugs, improving the health of patients. Pharmaceutical industry needs to give priority to their identification and validation in order to reduce the long and costly drug development times. In the last two decades, our knowledge about drugs, their mechanisms of action and drug targets has rapidly increased. Nevertheless, most of this knowledge is hidden in millions of medical articles and textbooks. Extracting knowledge from this large amount of unstructured information is a laborious job, even for human experts. Drug target articles identification, a crucial first step toward the automatic extraction of information from texts, constitutes the aim of this paper. A comparison of several machine learning techniques has been performed in order to obtain a satisfactory classifier for detecting drug target articles using semantic information from biomedical resources such as the Unified Medical Language System. The best result has been achieved by a Fuzzy Lattice Reasoning classifier, which reaches 98% of ROC area measure. Copyright © 2010 Elsevier Inc. All rights reserved.

The Human Kinome Targeted by FDA Approved Multi-Target Drugs and Combination Products: A Comparative Study from the Drug-Target Interaction Network Perspective.

PubMed

Li, Ying Hong; Wang, Pan Pan; Li, Xiao Xu; Yu, Chun Yan; Yang, Hong; Zhou, Jin; Xue, Wei Wei; Tan, Jun; Zhu, Feng

2016-01-01

The human kinome is one of the most productive classes of drug target, and there is emerging necessity for treating complex diseases by means of polypharmacology (multi-target drugs and combination products). However, the advantages of the multi-target drugs and the combination products are still under debate. A comparative analysis between FDA approved multi-target drugs and combination products, targeting the human kinome, was conducted by mapping targets onto the phylogenetic tree of the human kinome. The approach of network medicine illustrating the drug-target interactions was applied to identify popular targets of multi-target drugs and combination products. As identified, the multi-target drugs tended to inhibit target pairs in the human kinome, especially the receptor tyrosine kinase family, while the combination products were able to against targets of distant homology relationship. This finding asked for choosing the combination products as a better solution for designing drugs aiming at targets of distant homology relationship. Moreover, sub-networks of drug-target interactions in specific disease were generated, and mechanisms shared by multi-target drugs and combination products were identified. In conclusion, this study performed an analysis between approved multi-target drugs and combination products against the human kinome, which could assist the discovery of next generation polypharmacology.

Predicting Drug Combination Index and Simulating the Network-Regulation Dynamics by Mathematical Modeling of Drug-Targeted EGFR-ERK Signaling Pathway

NASA Astrophysics Data System (ADS)

Huang, Lu; Jiang, Yuyang; Chen, Yuzong

2017-01-01

Synergistic drug combinations enable enhanced therapeutics. Their discovery typically involves the measurement and assessment of drug combination index (CI), which can be facilitated by the development and applications of in-silico CI predictive tools. In this work, we developed and tested the ability of a mathematical model of drug-targeted EGFR-ERK pathway in predicting CIs and in analyzing multiple synergistic drug combinations against observations. Our mathematical model was validated against the literature reported signaling, drug response dynamics, and EGFR-MEK drug combination effect. The predicted CIs and combination therapeutic effects of the EGFR-BRaf, BRaf-MEK, FTI-MEK, and FTI-BRaf inhibitor combinations showed consistent synergism. Our results suggest that existing pathway models may be potentially extended for developing drug-targeted pathway models to predict drug combination CI values, isobolograms, and drug-response surfaces as well as to analyze the dynamics of individual and combinations of drugs. With our model, the efficacy of potential drug combinations can be predicted. Our method complements the developed in-silico methods (e.g. the chemogenomic profile and the statistically-inferenced network models) by predicting drug combination effects from the perspectives of pathway dynamics using experimental or validated molecular kinetic constants, thereby facilitating the collective prediction of drug combination effects in diverse ranges of disease systems.

Target-Independent Prediction of Drug Synergies Using Only Drug Lipophilicity

PubMed Central

2015-01-01

Physicochemical properties of compounds have been instrumental in selecting lead compounds with increased drug-likeness. However, the relationship between physicochemical properties of constituent drugs and the tendency to exhibit drug interaction has not been systematically studied. We assembled physicochemical descriptors for a set of antifungal compounds (“drugs”) previously examined for interaction. Analyzing the relationship between molecular weight, lipophilicity, H-bond donor, and H-bond acceptor values for drugs and their propensity to show pairwise antifungal drug synergy, we found that combinations of two lipophilic drugs had a greater tendency to show drug synergy. We developed a more refined decision tree model that successfully predicted drug synergy in stringent cross-validation tests based on only lipophilicity of drugs. Our predictions achieved a precision of 63% and allowed successful prediction for 58% of synergistic drug pairs, suggesting that this phenomenon can extend our understanding for a substantial fraction of synergistic drug interactions. We also generated and analyzed a large-scale synergistic human toxicity network, in which we observed that combinations of lipophilic compounds show a tendency for increased toxicity. Thus, lipophilicity, a simple and easily determined molecular descriptor, is a powerful predictor of drug synergy. It is well established that lipophilic compounds (i) are promiscuous, having many targets in the cell, and (ii) often penetrate into the cell via the cellular membrane by passive diffusion. We discuss the positive relationship between drug lipophilicity and drug synergy in the context of potential drug synergy mechanisms. PMID:25026390

Multi-target drugs: the trend of drug research and development.

PubMed

Lu, Jin-Jian; Pan, Wei; Hu, Yuan-Jia; Wang, Yi-Tao

2012-01-01

Summarizing the status of drugs in the market and examining the trend of drug research and development is important in drug discovery. In this study, we compared the drug targets and the market sales of the new molecular entities approved by the U.S. Food and Drug Administration from January 2000 to December 2009. Two networks, namely, the target-target and drug-drug networks, have been set up using the network analysis tools. The multi-target drugs have much more potential, as shown by the network visualization and the market trends. We discussed the possible reasons and proposed the rational strategies for drug research and development in the future.

SuperTarget and Matador: resources for exploring drug-target relationships.

PubMed

Günther, Stefan; Kuhn, Michael; Dunkel, Mathias; Campillos, Monica; Senger, Christian; Petsalaki, Evangelia; Ahmed, Jessica; Urdiales, Eduardo Garcia; Gewiess, Andreas; Jensen, Lars Juhl; Schneider, Reinhard; Skoblo, Roman; Russell, Robert B; Bourne, Philip E; Bork, Peer; Preissner, Robert

2008-01-01

The molecular basis of drug action is often not well understood. This is partly because the very abundant and diverse information generated in the past decades on drugs is hidden in millions of medical articles or textbooks. Therefore, we developed a one-stop data warehouse, SuperTarget that integrates drug-related information about medical indication areas, adverse drug effects, drug metabolization, pathways and Gene Ontology terms of the target proteins. An easy-to-use query interface enables the user to pose complex queries, for example to find drugs that target a certain pathway, interacting drugs that are metabolized by the same cytochrome P450 or drugs that target the same protein but are metabolized by different enzymes. Furthermore, we provide tools for 2D drug screening and sequence comparison of the targets. The database contains more than 2500 target proteins, which are annotated with about 7300 relations to 1500 drugs; the vast majority of entries have pointers to the respective literature source. A subset of these drugs has been annotated with additional binding information and indirect interactions and is available as a separate resource called Matador. SuperTarget and Matador are available at http://insilico.charite.de/supertarget and http://matador.embl.de.

Drug targeting of oncogenic pathways in melanoma.

PubMed

Fecher, Leslie A; Amaravadi, Ravi K; Schuchter, Lynn M; Flaherty, Keith T

2009-06-01

Melanoma continues to be one of the most aggressive and morbid malignancies once metastatic. Overall survival for advanced unresectable melanoma has not changed over the past several decades. However, the presence of some long-term survivors of metastatic melanoma highlights the heterogeneity of this disease and the potential for improved outcomes. Current research is uncovering the molecular and genetic scaffolding of normal and aberrant cell function. The known oncogenic pathways in melanoma and the attempts to develop therapy for them are discussed. The targeting of certain cellular processes, downstream of the common genetic alterations, for which the issues of target and drug validation are somewhat distinct, are also highlighted.

Predicting drug-target interaction for new drugs using enhanced similarity measures and super-target clustering.

PubMed

Shi, Jian-Yu; Yiu, Siu-Ming; Li, Yiming; Leung, Henry C M; Chin, Francis Y L

2015-07-15

Predicting drug-target interaction using computational approaches is an important step in drug discovery and repositioning. To predict whether there will be an interaction between a drug and a target, most existing methods identify similar drugs and targets in the database. The prediction is then made based on the known interactions of these drugs and targets. This idea is promising. However, there are two shortcomings that have not yet been addressed appropriately. Firstly, most of the methods only use 2D chemical structures and protein sequences to measure the similarity of drugs and targets respectively. However, this information may not fully capture the characteristics determining whether a drug will interact with a target. Secondly, there are very few known interactions, i.e. many interactions are "missing" in the database. Existing approaches are biased towards known interactions and have no good solutions to handle possibly missing interactions which affect the accuracy of the prediction. In this paper, we enhance the similarity measures to include non-structural (and non-sequence-based) information and introduce the concept of a "super-target" to handle the problem of possibly missing interactions. Based on evaluations on real data, we show that our similarity measure is better than the existing measures and our approach is able to achieve higher accuracy than the two best existing algorithms, WNN-GIP and KBMF2K. Our approach is available at http://web.hku.hk/∼liym1018/projects/drug/drug.html or http://www.bmlnwpu.org/us/tools/PredictingDTI_S2/METHODS.html. Copyright © 2015 Elsevier Inc. All rights reserved.

The drug target genes show higher evolutionary conservation than non-target genes.

PubMed

Lv, Wenhua; Xu, Yongdeng; Guo, Yiying; Yu, Ziqi; Feng, Guanglong; Liu, Panpan; Luan, Meiwei; Zhu, Hongjie; Liu, Guiyou; Zhang, Mingming; Lv, Hongchao; Duan, Lian; Shang, Zhenwei; Li, Jin; Jiang, Yongshuai; Zhang, Ruijie

2016-01-26

Although evidence indicates that drug target genes share some common evolutionary features, there have been few studies analyzing evolutionary features of drug targets from an overall level. Therefore, we conducted an analysis which aimed to investigate the evolutionary characteristics of drug target genes. We compared the evolutionary conservation between human drug target genes and non-target genes by combining both the evolutionary features and network topological properties in human protein-protein interaction network. The evolution rate, conservation score and the percentage of orthologous genes of 21 species were included in our study. Meanwhile, four topological features including the average shortest path length, betweenness centrality, clustering coefficient and degree were considered for comparison analysis. Then we got four results as following: compared with non-drug target genes, 1) drug target genes had lower evolutionary rates; 2) drug target genes had higher conservation scores; 3) drug target genes had higher percentages of orthologous genes and 4) drug target genes had a tighter network structure including higher degrees, betweenness centrality, clustering coefficients and lower average shortest path lengths. These results demonstrate that drug target genes are more evolutionarily conserved than non-drug target genes. We hope that our study will provide valuable information for other researchers who are interested in evolutionary conservation of drug targets.

Predicting drug-target interactions by dual-network integrated logistic matrix factorization

NASA Astrophysics Data System (ADS)

Hao, Ming; Bryant, Stephen H.; Wang, Yanli

2017-01-01

In this work, we propose a dual-network integrated logistic matrix factorization (DNILMF) algorithm to predict potential drug-target interactions (DTI). The prediction procedure consists of four steps: (1) inferring new drug/target profiles and constructing profile kernel matrix; (2) diffusing drug profile kernel matrix with drug structure kernel matrix; (3) diffusing target profile kernel matrix with target sequence kernel matrix; and (4) building DNILMF model and smoothing new drug/target predictions based on their neighbors. We compare our algorithm with the state-of-the-art method based on the benchmark dataset. Results indicate that the DNILMF algorithm outperforms the previously reported approaches in terms of AUPR (area under precision-recall curve) and AUC (area under curve of receiver operating characteristic) based on the 5 trials of 10-fold cross-validation. We conclude that the performance improvement depends on not only the proposed objective function, but also the used nonlinear diffusion technique which is important but under studied in the DTI prediction field. In addition, we also compile a new DTI dataset for increasing the diversity of currently available benchmark datasets. The top prediction results for the new dataset are confirmed by experimental studies or supported by other computational research.

Properties of Protein Drug Target Classes

PubMed Central

Bull, Simon C.; Doig, Andrew J.

2015-01-01

Accurate identification of drug targets is a crucial part of any drug development program. We mined the human proteome to discover properties of proteins that may be important in determining their suitability for pharmaceutical modulation. Data was gathered concerning each protein’s sequence, post-translational modifications, secondary structure, germline variants, expression profile and drug target status. The data was then analysed to determine features for which the target and non-target proteins had significantly different values. This analysis was repeated for subsets of the proteome consisting of all G-protein coupled receptors, ion channels, kinases and proteases, as well as proteins that are implicated in cancer. Machine learning was used to quantify the proteins in each dataset in terms of their potential to serve as a drug target. This was accomplished by first inducing a random forest that could distinguish between its targets and non-targets, and then using the random forest to quantify the drug target likeness of the non-targets. The properties that can best differentiate targets from non-targets were primarily those that are directly related to a protein’s sequence (e.g. secondary structure). Germline variants, expression levels and interactions between proteins had minimal discriminative power. Overall, the best indicators of drug target likeness were found to be the proteins’ hydrophobicities, in vivo half-lives, propensity for being membrane bound and the fraction of non-polar amino acids in their sequences. In terms of predicting potential targets, datasets of proteases, ion channels and cancer proteins were able to induce random forests that were highly capable of distinguishing between targets and non-targets. The non-target proteins predicted to be targets by these random forests comprise the set of the most suitable potential future drug targets, and should therefore be prioritised when building a drug development programme. PMID

Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases.

PubMed

Williams, Kevin; Bilsland, Elizabeth; Sparkes, Andrew; Aubrey, Wayne; Young, Michael; Soldatova, Larisa N; De Grave, Kurt; Ramon, Jan; de Clare, Michaela; Sirawaraporn, Worachart; Oliver, Stephen G; King, Ross D

2015-03-06

There is an urgent need to make drug discovery cheaper and faster. This will enable the development of treatments for diseases currently neglected for economic reasons, such as tropical and orphan diseases, and generally increase the supply of new drugs. Here, we report the Robot Scientist 'Eve' designed to make drug discovery more economical. A Robot Scientist is a laboratory automation system that uses artificial intelligence (AI) techniques to discover scientific knowledge through cycles of experimentation. Eve integrates and automates library-screening, hit-confirmation, and lead generation through cycles of quantitative structure activity relationship learning and testing. Using econometric modelling we demonstrate that the use of AI to select compounds economically outperforms standard drug screening. For further efficiency Eve uses a standardized form of assay to compute Boolean functions of compound properties. These assays can be quickly and cheaply engineered using synthetic biology, enabling more targets to be assayed for a given budget. Eve has repositioned several drugs against specific targets in parasites that cause tropical diseases. One validated discovery is that the anti-cancer compound TNP-470 is a potent inhibitor of dihydrofolate reductase from the malaria-causing parasite Plasmodium vivax.

Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases

PubMed Central

Williams, Kevin; Bilsland, Elizabeth; Sparkes, Andrew; Aubrey, Wayne; Young, Michael; Soldatova, Larisa N.; De Grave, Kurt; Ramon, Jan; de Clare, Michaela; Sirawaraporn, Worachart; Oliver, Stephen G.; King, Ross D.

2015-01-01

There is an urgent need to make drug discovery cheaper and faster. This will enable the development of treatments for diseases currently neglected for economic reasons, such as tropical and orphan diseases, and generally increase the supply of new drugs. Here, we report the Robot Scientist ‘Eve’ designed to make drug discovery more economical. A Robot Scientist is a laboratory automation system that uses artificial intelligence (AI) techniques to discover scientific knowledge through cycles of experimentation. Eve integrates and automates library-screening, hit-confirmation, and lead generation through cycles of quantitative structure activity relationship learning and testing. Using econometric modelling we demonstrate that the use of AI to select compounds economically outperforms standard drug screening. For further efficiency Eve uses a standardized form of assay to compute Boolean functions of compound properties. These assays can be quickly and cheaply engineered using synthetic biology, enabling more targets to be assayed for a given budget. Eve has repositioned several drugs against specific targets in parasites that cause tropical diseases. One validated discovery is that the anti-cancer compound TNP-470 is a potent inhibitor of dihydrofolate reductase from the malaria-causing parasite Plasmodium vivax. PMID:25652463

Drug-Target Interactions: Prediction Methods and Applications.

PubMed

Anusuya, Shanmugam; Kesherwani, Manish; Priya, K Vishnu; Vimala, Antonydhason; Shanmugam, Gnanendra; Velmurugan, Devadasan; Gromiha, M Michael

2018-01-01

Identifying the interactions between drugs and target proteins is a key step in drug discovery. This not only aids to understand the disease mechanism, but also helps to identify unexpected therapeutic activity or adverse side effects of drugs. Hence, drug-target interaction prediction becomes an essential tool in the field of drug repurposing. The availability of heterogeneous biological data on known drug-target interactions enabled many researchers to develop various computational methods to decipher unknown drug-target interactions. This review provides an overview on these computational methods for predicting drug-target interactions along with available webservers and databases for drug-target interactions. Further, the applicability of drug-target interactions in various diseases for identifying lead compounds has been outlined. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Fruitful research: drug target discovery for neurodegenerative diseases in Drosophila.

PubMed

Konsolaki, Mary

2013-12-01

Although vertebrate model systems have obvious advantages in the study of human disease, invertebrate organisms have contributed enormously to this field as well. The conservation of genome structure and physiology among organisms poses unexpected peculiarities, and the redundancy in certain gene families or the presence of polymorphisms that can slightly alter gene expression can, in certain instances, bring invertebrate systems, such as Drosophila, closer to humans than mice and vice versa. This necessitates the analysis of disease pathways in multiple model organisms. The author highlights findings from Drosophila models of neurodegenerative diseases that have occurred in the past few years. She also highlights and discusses various molecular, genetic and genomic tools used in flies, as well as methods for generating disease models. Finally, the author describes Drosophila models of Alzheimer's, Parkinson's tri-nucleotide repeat diseases, and Fragile X syndrome and summarizes insights in disease mechanisms that have been discovered directly in fly models. Full genome genetic screens in Drosophila can lead to the rapid identification of drug target candidates that can be subsequently validated in a vertebrate system. In addition, the Drosophila models of neurodegeneration may often show disease phenotypes that are absent in equivalent mouse models. The author believes that the extensive contribution of Drosophila to both new disease drug target discovery, in addition to target validation, makes them indispensible to drug discovery and development.

Drug-targeting methodologies with applications: A review

PubMed Central

Kleinstreuer, Clement; Feng, Yu; Childress, Emily

2014-01-01

Targeted drug delivery to solid tumors is a very active research area, focusing mainly on improved drug formulation and associated best delivery methods/devices. Drug-targeting has the potential to greatly improve drug-delivery efficacy, reduce side effects, and lower the treatment costs. However, the vast majority of drug-targeting studies assume that the drug-particles are already at the target site or at least in its direct vicinity. In this review, drug-delivery methodologies, drug types and drug-delivery devices are discussed with examples in two major application areas: (1) inhaled drug-aerosol delivery into human lung-airways; and (2) intravascular drug-delivery for solid tumor targeting. The major problem addressed is how to deliver efficiently the drug-particles from the entry/infusion point to the target site. So far, most experimental results are based on animal studies. Concerning pulmonary drug delivery, the focus is on the pros and cons of three inhaler types, i.e., pressurized metered dose inhaler, dry powder inhaler and nebulizer, in addition to drug-aerosol formulations. Computational fluid-particle dynamics techniques and the underlying methodology for a smart inhaler system are discussed as well. Concerning intravascular drug-delivery for solid tumor targeting, passive and active targeting are reviewed as well as direct drug-targeting, using optimal delivery of radioactive microspheres to liver tumors as an example. The review concludes with suggestions for future work, considereing both pulmonary drug targeting and direct drug delivery to solid tumors in the vascular system. PMID:25516850

Predicting essential genes for identifying potential drug targets in Aspergillus fumigatus.

PubMed

Lu, Yao; Deng, Jingyuan; Rhodes, Judith C; Lu, Hui; Lu, Long Jason

2014-06-01

Aspergillus fumigatus (Af) is a ubiquitous and opportunistic pathogen capable of causing acute, invasive pulmonary disease in susceptible hosts. Despite current therapeutic options, mortality associated with invasive Af infections remains unacceptably high, increasing 357% since 1980. Therefore, there is an urgent need for the development of novel therapeutic strategies, including more efficacious drugs acting on new targets. Thus, as noted in a recent review, "the identification of essential genes in fungi represents a crucial step in the development of new antifungal drugs". Expanding the target space by rapidly identifying new essential genes has thus been described as "the most important task of genomics-based target validation". In previous research, we were the first to show that essential gene annotation can be reliably transferred between distantly related four Prokaryotic species. In this study, we extend our machine learning approach to the much more complex Eukaryotic fungal species. A compendium of essential genes is predicted in Af by transferring known essential gene annotations from another filamentous fungus Neurospora crassa. This approach predicts essential genes by integrating diverse types of intrinsic and context-dependent genomic features encoded in microbial genomes. The predicted essential datasets contained 1674 genes. We validated our results by comparing our predictions with known essential genes in Af, comparing our predictions with those predicted by homology mapping, and conducting conditional expressed alleles. We applied several layers of filters and selected a set of potential drug targets from the predicted essential genes. Finally, we have conducted wet lab knockout experiments to verify our predictions, which further validates the accuracy and wide applicability of the machine learning approach. The approach presented here significantly extended our ability to predict essential genes beyond orthologs and made it possible to

Development of Bone Targeting Drugs.

PubMed

Stapleton, Molly; Sawamoto, Kazuki; Alméciga-Díaz, Carlos J; Mackenzie, William G; Mason, Robert W; Orii, Tadao; Tomatsu, Shunji

2017-06-23

The skeletal system, comprising bones, ligaments, cartilage and their connective tissues, is critical for the structure and support of the body. Diseases that affect the skeletal system can be difficult to treat, mainly because of the avascular cartilage region. Targeting drugs to the site of action can not only increase efficacy but also reduce toxicity. Bone-targeting drugs are designed with either of two general targeting moieties, aimed at the entire skeletal system or a specific cell type. Most bone-targeting drugs utilize an affinity to hydroxyapatite, a major component of the bone matrix that includes a high concentration of positively-charged Ca 2+ . The strategies for designing such targeting moieties can involve synthetic and/or biological components including negatively-charged amino acid peptides or bisphosphonates. Efficient delivery of bone-specific drugs provides significant impact in the treatment of skeletal related disorders including infectious diseases (osteoarthritis, osteomyelitis, etc.), osteoporosis, and metabolic skeletal dysplasia. Despite recent advances, however, both delivering the drug to its target without losing activity and avoiding adverse local effects remain a challenge. In this review, we investigate the current development of bone-targeting moieties, their efficacy and limitations, and discuss future directions for the development of these specific targeted treatments.

Development of Bone Targeting Drugs

PubMed Central

Stapleton, Molly; Sawamoto, Kazuki; Alméciga-Díaz, Carlos J.; Mackenzie, William G.; Mason, Robert W.; Orii, Tadao; Tomatsu, Shunji

2017-01-01

The skeletal system, comprising bones, ligaments, cartilage and their connective tissues, is critical for the structure and support of the body. Diseases that affect the skeletal system can be difficult to treat, mainly because of the avascular cartilage region. Targeting drugs to the site of action can not only increase efficacy but also reduce toxicity. Bone-targeting drugs are designed with either of two general targeting moieties, aimed at the entire skeletal system or a specific cell type. Most bone-targeting drugs utilize an affinity to hydroxyapatite, a major component of the bone matrix that includes a high concentration of positively-charged Ca2+. The strategies for designing such targeting moieties can involve synthetic and/or biological components including negatively-charged amino acid peptides or bisphosphonates. Efficient delivery of bone-specific drugs provides significant impact in the treatment of skeletal related disorders including infectious diseases (osteoarthritis, osteomyelitis, etc.), osteoporosis, and metabolic skeletal dysplasia. Despite recent advances, however, both delivering the drug to its target without losing activity and avoiding adverse local effects remain a challenge. In this review, we investigate the current development of bone-targeting moieties, their efficacy and limitations, and discuss future directions for the development of these specific targeted treatments. PMID:28644392

Using in Vitro Evolution and Whole Genome Analysis To Discover Next Generation Targets for Antimalarial Drug Discovery

PubMed Central

2018-01-01

Although many new anti-infectives have been discovered and developed solely using phenotypic cellular screening and assay optimization, most researchers recognize that structure-guided drug design is more practical and less costly. In addition, a greater chemical space can be interrogated with structure-guided drug design. The practicality of structure-guided drug design has launched a search for the targets of compounds discovered in phenotypic screens. One method that has been used extensively in malaria parasites for target discovery and chemical validation is in vitro evolution and whole genome analysis (IVIEWGA). Here, small molecules from phenotypic screens with demonstrated antiparasitic activity are used in genome-based target discovery methods. In this Review, we discuss the newest, most promising druggable targets discovered or further validated by evolution-based methods, as well as some exceptions. PMID:29451780

Drug-target interaction prediction using ensemble learning and dimensionality reduction.

PubMed

Ezzat, Ali; Wu, Min; Li, Xiao-Li; Kwoh, Chee-Keong

2017-10-01

Experimental prediction of drug-target interactions is expensive, time-consuming and tedious. Fortunately, computational methods help narrow down the search space for interaction candidates to be further examined via wet-lab techniques. Nowadays, the number of attributes/features for drugs and targets, as well as the amount of their interactions, are increasing, making these computational methods inefficient or occasionally prohibitive. This motivates us to derive a reduced feature set for prediction. In addition, since ensemble learning techniques are widely used to improve the classification performance, it is also worthwhile to design an ensemble learning framework to enhance the performance for drug-target interaction prediction. In this paper, we propose a framework for drug-target interaction prediction leveraging both feature dimensionality reduction and ensemble learning. First, we conducted feature subspacing to inject diversity into the classifier ensemble. Second, we applied three different dimensionality reduction methods to the subspaced features. Third, we trained homogeneous base learners with the reduced features and then aggregated their scores to derive the final predictions. For base learners, we selected two classifiers, namely Decision Tree and Kernel Ridge Regression, resulting in two variants of ensemble models, EnsemDT and EnsemKRR, respectively. In our experiments, we utilized AUC (Area under ROC Curve) as an evaluation metric. We compared our proposed methods with various state-of-the-art methods under 5-fold cross validation. Experimental results showed EnsemKRR achieving the highest AUC (94.3%) for predicting drug-target interactions. In addition, dimensionality reduction helped improve the performance of EnsemDT. In conclusion, our proposed methods produced significant improvements for drug-target interaction prediction. Copyright © 2017 Elsevier Inc. All rights reserved.

Identification of inhibitors for putative malaria drug targets amongst novel antimalarial compounds

PubMed Central

Crowther, Gregory J.; Napuli, Alberto J.; Gilligan, James H.; Gagaring, Kerstin; Borboa, Rachel; Francek, Carolyn; Chen, Zhong; Dagostino, Eleanor F.; Stockmyer, Justin B.; Wang, Yu; Rodenbough, Philip P.; Castaneda, Lisa J.; Leibly, David J.; Bhandari, Janhavi; Gelb, Michael H.; Brinker, Achim; Engels, Ingo; Taylor, Jennifer; Chatterjee, Arnab K.; Fantauzzi, Pascal; Glynne, Richard J.; Van Voorhis, Wesley C.; Kuhen, Kelli L.

2011-01-01

The efficacy of most marketed antimalarial drugs has been compromised by evolution of parasite resistance, underscoring an urgent need to find new drugs with new mechanisms of action. We have taken a high-throughput approach toward identifying novel antimalarial chemical inhibitors of prioritized drug targets for P. falciparum, excluding targets which are inhibited by currently used drugs. A screen of commercially available libraries identified 5,655 low molecular weight compounds that inhibit growth of P. falciparum cultures with EC50 values below 1.25 μM. These compounds were then tested in 384- or 1536-well biochemical assays for activity against nine Plasmodium enzymes: adenylosuccinate synthetase (AdSS), choline kinase (CK), deoxyuridine triphosphate nucleotidohydrolase (dUTPase), glutamate dehydrogenase (GDH), guanylate kinase (GK), N-myristoyltransferase (NMT), orotidine 5′-monophosphate decarboxylase (OMPDC), farnesyl pyrophosphate synthase (FPPS) and S-adenosylhomocysteine hydrolase (SAHH). These enzymes were selected using TDRtargets.org, and are believed to have excellent potential as drug targets based on criteria such as their likely essentiality, druggability, and amenability to high-throughput biochemical screening. Six of these targets were inhibited by one or more of the antimalarial scaffolds and may have potential use in drug development, further target validation studies and exploration of P. falciparum biochemistry and biology. PMID:20813141

Identification of inhibitors for putative malaria drug targets among novel antimalarial compounds.

PubMed

Crowther, Gregory J; Napuli, Alberto J; Gilligan, James H; Gagaring, Kerstin; Borboa, Rachel; Francek, Carolyn; Chen, Zhong; Dagostino, Eleanor F; Stockmyer, Justin B; Wang, Yu; Rodenbough, Philip P; Castaneda, Lisa J; Leibly, David J; Bhandari, Janhavi; Gelb, Michael H; Brinker, Achim; Engels, Ingo H; Taylor, Jennifer; Chatterjee, Arnab K; Fantauzzi, Pascal; Glynne, Richard J; Van Voorhis, Wesley C; Kuhen, Kelli L

2011-01-01

The efficacy of most marketed antimalarial drugs has been compromised by evolution of parasite resistance, underscoring an urgent need to find new drugs with new mechanisms of action. We have taken a high-throughput approach toward identifying novel antimalarial chemical inhibitors of prioritized drug targets for Plasmodium falciparum, excluding targets which are inhibited by currently used drugs. A screen of commercially available libraries identified 5655 low molecular weight compounds that inhibit growth of P. falciparum cultures with EC(50) values below 1.25μM. These compounds were then tested in 384- or 1536-well biochemical assays for activity against nine Plasmodium enzymes: adenylosuccinate synthetase (AdSS), choline kinase (CK), deoxyuridine triphosphate nucleotidohydrolase (dUTPase), glutamate dehydrogenase (GDH), guanylate kinase (GK), N-myristoyltransferase (NMT), orotidine 5'-monophosphate decarboxylase (OMPDC), farnesyl pyrophosphate synthase (FPPS) and S-adenosylhomocysteine hydrolase (SAHH). These enzymes were selected using TDRtargets.org, and are believed to have excellent potential as drug targets based on criteria such as their likely essentiality, druggability, and amenability to high-throughput biochemical screening. Six of these targets were inhibited by one or more of the antimalarial scaffolds and may have potential use in drug development, further target validation studies and exploration of P. falciparum biochemistry and biology. Copyright © 2010 Elsevier B.V. All rights reserved.

Adverse drug reaction prediction using scores produced by large-scale drug-protein target docking on high-performance computing machines.

PubMed

LaBute, Montiago X; Zhang, Xiaohua; Lenderman, Jason; Bennion, Brian J; Wong, Sergio E; Lightstone, Felice C

2014-01-01

Late-stage or post-market identification of adverse drug reactions (ADRs) is a significant public health issue and a source of major economic liability for drug development. Thus, reliable in silico screening of drug candidates for possible ADRs would be advantageous. In this work, we introduce a computational approach that predicts ADRs by combining the results of molecular docking and leverages known ADR information from DrugBank and SIDER. We employed a recently parallelized version of AutoDock Vina (VinaLC) to dock 906 small molecule drugs to a virtual panel of 409 DrugBank protein targets. L1-regularized logistic regression models were trained on the resulting docking scores of a 560 compound subset from the initial 906 compounds to predict 85 side effects, grouped into 10 ADR phenotype groups. Only 21% (87 out of 409) of the drug-protein binding features involve known targets of the drug subset, providing a significant probe of off-target effects. As a control, associations of this drug subset with the 555 annotated targets of these compounds, as reported in DrugBank, were used as features to train a separate group of models. The Vina off-target models and the DrugBank on-target models yielded comparable median area-under-the-receiver-operating-characteristic-curves (AUCs) during 10-fold cross-validation (0.60-0.69 and 0.61-0.74, respectively). Evidence was found in the PubMed literature to support several putative ADR-protein associations identified by our analysis. Among them, several associations between neoplasm-related ADRs and known tumor suppressor and tumor invasiveness marker proteins were found. A dual role for interstitial collagenase in both neoplasms and aneurysm formation was also identified. These associations all involve off-target proteins and could not have been found using available drug/on-target interaction data. This study illustrates a path forward to comprehensive ADR virtual screening that can potentially scale with increasing number

Drug target identification in protozoan parasites.

PubMed

Müller, Joachim; Hemphill, Andrew

2016-08-01

Despite the fact that diseases caused by protozoan parasites represent serious challenges for public health, animal production and welfare, only a limited panel of drugs has been marketed for clinical applications. Herein, the authors investigate two strategies, namely whole organism screening and target-based drug design. The present pharmacopoeia has resulted from whole organism screening, and the mode of action and targets of selected drugs are discussed. However, the more recent extensive genome sequencing efforts and the development of dry and wet lab genomics and proteomics that allow high-throughput screening of interactions between micromolecules and recombinant proteins has resulted in target-based drug design as the predominant focus in anti-parasitic drug development. Selected examples of target-based drug design studies are presented, and calcium-dependent protein kinases, important drug targets in apicomplexan parasites, are discussed in more detail. Despite the enormous efforts in target-based drug development, this approach has not yet generated market-ready antiprotozoal drugs. However, whole-organism screening approaches, comprising of both in vitro and in vivo investigations, should not be disregarded. The repurposing of already approved and marketed drugs could be a suitable strategy to avoid fastidious approval procedures, especially in the case of neglected or veterinary parasitoses.

Drug target identification in protozoan parasites

PubMed Central

Müller, Joachim; Hemphill, Andrew

2016-01-01

Introduction Despite the fact that diseases caused by protozoan parasites represent serious challenges for public health, animal production and welfare, only a limited panel of drugs has been marketed for clinical applications. Areas covered Herein, the authors investigate two strategies, namely whole organism screening and target-based drug design. The present pharmacopoeia has resulted from whole organism screening, and the mode of action and targets of selected drugs are discussed. However, the more recent extensive genome sequencing efforts and the development of dry and wet lab genomics and proteomics that allow high-throughput screening of interactions between micromolecules and recombinant proteins has resulted in target-based drug design as the predominant focus in anti-parasitic drug development. Selected examples of target-based drug design studies are presented, and calcium-dependent protein kinases, important drug targets in apicomplexan parasites, are discussed in more detail. Expert opinion Despite the enormous efforts in target-based drug development, this approach has not yet generated market-ready antiprotozoal drugs. However, whole-organism screening approaches, comprising of both in vitro and in vivo investigations, should not be disregarded. The repurposing of already approved and marketed drugs could be a suitable strategy to avoid fastidious approval procedures, especially in the case of neglected or veterinary parasitoses. PMID:27238605

Deep-Learning-Based Drug-Target Interaction Prediction.

PubMed

Wen, Ming; Zhang, Zhimin; Niu, Shaoyu; Sha, Haozhi; Yang, Ruihan; Yun, Yonghuan; Lu, Hongmei

2017-04-07

Identifying interactions between known drugs and targets is a major challenge in drug repositioning. In silico prediction of drug-target interaction (DTI) can speed up the expensive and time-consuming experimental work by providing the most potent DTIs. In silico prediction of DTI can also provide insights about the potential drug-drug interaction and promote the exploration of drug side effects. Traditionally, the performance of DTI prediction depends heavily on the descriptors used to represent the drugs and the target proteins. In this paper, to accurately predict new DTIs between approved drugs and targets without separating the targets into different classes, we developed a deep-learning-based algorithmic framework named DeepDTIs. It first abstracts representations from raw input descriptors using unsupervised pretraining and then applies known label pairs of interaction to build a classification model. Compared with other methods, it is found that DeepDTIs reaches or outperforms other state-of-the-art methods. The DeepDTIs can be further used to predict whether a new drug targets to some existing targets or whether a new target interacts with some existing drugs.

Drug–Target Kinetics in Drug Discovery

PubMed Central

2017-01-01

The development of therapies for the treatment of neurological cancer faces a number of major challenges including the synthesis of small molecule agents that can penetrate the blood-brain barrier (BBB). Given the likelihood that in many cases drug exposure will be lower in the CNS than in systemic circulation, it follows that strategies should be employed that can sustain target engagement at low drug concentration. Time dependent target occupancy is a function of both the drug and target concentration as well as the thermodynamic and kinetic parameters that describe the binding reaction coordinate, and sustained target occupancy can be achieved through structural modifications that increase target (re)binding and/or that decrease the rate of drug dissociation. The discovery and deployment of compounds with optimized kinetic effects requires information on the structure–kinetic relationships that modulate the kinetics of binding, and the molecular factors that control the translation of drug–target kinetics to time-dependent drug activity in the disease state. This Review first introduces the potential benefits of drug-target kinetics, such as the ability to delineate both thermodynamic and kinetic selectivity, and then describes factors, such as target vulnerability, that impact the utility of kinetic selectivity. The Review concludes with a description of a mechanistic PK/PD model that integrates drug–target kinetics into predictions of drug activity. PMID:28640596

New Structural Templates for Clinically Validated and Novel Targets in Antimicrobial Drug Research and Development.

PubMed

Klahn, Philipp; Brönstrup, Mark

The development of bacterial resistance against current antibiotic drugs necessitates a continuous renewal of the arsenal of efficacious drugs. This imperative has not been met by the output of antibiotic research and development of the past decades for various reasons, including the declining efforts of large pharma companies in this area. Moreover, the majority of novel antibiotics are chemical derivatives of existing structures that represent mostly step innovations, implying that the available chemical space may be exhausted. This review negates this impression by showcasing recent achievements in lead finding and optimization of antibiotics that have novel or unexplored chemical structures. Not surprisingly, many of the novel structural templates like teixobactins, lysocin, griselimycin, or the albicidin/cystobactamid pair were discovered from natural sources. Additional compounds were obtained from the screening of synthetic libraries and chemical synthesis, including the gyrase-inhibiting NTBI's and spiropyrimidinetrione, the tarocin and targocil inhibitors of wall teichoic acid synthesis, or the boronates and diazabicyclo[3.2.1]octane as novel β-lactamase inhibitors. A motif that is common to most clinically validated antibiotics is that they address hotspots in complex biosynthetic machineries, whose functioning is essential for the bacterial cell. Therefore, an introduction to the biological targets-cell wall synthesis, topoisomerases, the DNA sliding clamp, and membrane-bound electron transport-is given for each of the leads presented here.

Identifying Drug-Target Interactions with Decision Templates.

PubMed

Yan, Xiao-Ying; Zhang, Shao-Wu

2018-01-01

During the development process of new drugs, identification of the drug-target interactions wins primary concerns. However, the chemical or biological experiments bear the limitation in coverage as well as the huge cost of both time and money. Based on drug similarity and target similarity, chemogenomic methods can be able to predict potential drug-target interactions (DTIs) on a large scale and have no luxurious need about target structures or ligand entries. In order to reflect the cases that the drugs having variant structures interact with common targets and the targets having dissimilar sequences interact with same drugs. In addition, though several other similarity metrics have been developed to predict DTIs, the combination of multiple similarity metrics (especially heterogeneous similarities) is too naïve to sufficiently explore the multiple similarities. In this paper, based on Gene Ontology and pathway annotation, we introduce two novel target similarity metrics to address above issues. More importantly, we propose a more effective strategy via decision template to integrate multiple classifiers designed with multiple similarity metrics. In the scenarios that predict existing targets for new drugs and predict approved drugs for new protein targets, the results on the DTI benchmark datasets show that our target similarity metrics are able to enhance the predictive accuracies in two scenarios. And the elaborate fusion strategy of multiple classifiers has better predictive power than the naïve combination of multiple similarity metrics. Compared with other two state-of-the-art approaches on the four popular benchmark datasets of binary drug-target interactions, our method achieves the best results in terms of AUC and AUPR for predicting available targets for new drugs (S2), and predicting approved drugs for new protein targets (S3).These results demonstrate that our method can effectively predict the drug-target interactions. The software package can

Is there a rational approach for increasing drug specificity? Considerations on CNS target choice and validation.

PubMed

Resende, Rodrigo R; Ulrich, Henning; Faria, Marcella

2007-01-01

The description of mental illness states brings into light a referential paradox on the absence of grounds for normality. Furthermore, the semiology itself poses a problem throughout the intricate consensual relations between psychiatrists. New molecules with activity on the CNS are ever more specific as to molecular cognitive capabilities, reaching limits of individual genetic variability. Cultural mechanisms of neuronal adaptation also contribute significantly to representations and its correlation with feelings. Neuropeptides increase excitability in various different brain regions, with networks underlying optimal behaviour patterns. Therefore, the sole specification of target molecules yet does not lead directly to specific results, as insights from a systematic approach should conceal. Current validation methods generate insufficient data for discriminating successful treatable candidates. Instead of regarding the heuristics of empirically classified disease models, a new tendency to compromise scientia rationale with technical capabilities should be regarded. Some of the drugs that have obtained patents recently will be discussed in the framework of their rational and actual specificity. The molecular basis underlining function will be contrasted with an alternative approach, namely: how functional organization constrains molecular action. The categories comprising neurogenarative pathologies at one hand and the mood disorders at the other hand will be analysed separately as the procedures guiding drug design in each case seem to be different.

The enemy within: Targeting host-parasite interaction for antileishmanial drug discovery.

PubMed

Lamotte, Suzanne; Späth, Gerald F; Rachidi, Najma; Prina, Eric

2017-06-01

The state of antileishmanial chemotherapy is strongly compromised by the emergence of drug-resistant Leishmania. The evolution of drug-resistant phenotypes has been linked to the parasites' intrinsic genome instability, with frequent gene and chromosome amplifications causing fitness gains that are directly selected by environmental factors, including the presence of antileishmanial drugs. Thus, even though the unique eukaryotic biology of Leishmania and its dependence on parasite-specific virulence factors provide valid opportunities for chemotherapeutical intervention, all strategies that target the parasite in a direct fashion are likely prone to select for resistance. Here, we review the current state of antileishmanial chemotherapy and discuss the limitations of ongoing drug discovery efforts. We finally propose new strategies that target Leishmania viability indirectly via mechanisms of host-parasite interaction, including parasite-released ectokinases and host epigenetic regulation, which modulate host cell signaling and transcriptional regulation, respectively, to establish permissive conditions for intracellular Leishmania survival.

CYP51 is an essential drug target for the treatment of primary amoebic meningoencephalitis (PAM)

PubMed Central

Debnath, Anjan; Calvet, Claudia M.; Aksenov, Alexander; Abagyan, Ruben; Nes, W. David; McKerrow, James H.

2017-01-01

Primary Amoebic Meningoencephalitis (PAM) is caused by Naegleria fowleri, a free-living amoeba that occasionally infects humans. While considered “rare” (but likely underreported) the high mortality rate and lack of established success in treatment makes PAM a particularly devastating infection. In the absence of economic inducements to invest in development of anti-PAM drugs by the pharmaceutical industry, anti-PAM drug discovery largely relies on drug ‘repurposing’—a cost effective strategy to apply known drugs for treatment of rare or neglected diseases. Similar to fungi, N. fowleri has an essential requirement for ergosterol, a building block of plasma and cell membranes. Disruption of sterol biosynthesis by small-molecule inhibitors is a validated interventional strategy against fungal pathogens of medical and agricultural importance. The N. fowleri genome encodes the sterol 14-demethylase (CYP51) target sharing ~35% sequence identity to fungal orthologues. The similarity of targets raises the possibility of repurposing anti-mycotic drugs and optimization of their usage for the treatment of PAM. In this work, we (i) systematically assessed the impact of anti-fungal azole drugs, known as conazoles, on sterol biosynthesis and viability of cultured N. fowleri trophozotes, (ii) identified the endogenous CYP51 substrate by mass spectrometry analysis of N. fowleri lipids, and (iii) analyzed the interactions between the recombinant CYP51 target and conazoles by UV-vis spectroscopy and x-ray crystallography. Collectively, the target-based and parasite-based data obtained in these studies validated CYP51 as a potentially ‘druggable’ target in N. fowleri, and conazole drugs as the candidates for assessment in the animal model of PAM. PMID:29284029

An integrated structure- and system-based framework to identify new targets of metabolites and known drugs

PubMed Central

Naveed, Hammad; Hameed, Umar S.; Harrus, Deborah; Bourguet, William; Arold, Stefan T.; Gao, Xin

2015-01-01

Motivation: The inherent promiscuity of small molecules towards protein targets impedes our understanding of healthy versus diseased metabolism. This promiscuity also poses a challenge for the pharmaceutical industry as identifying all protein targets is important to assess (side) effects and repositioning opportunities for a drug. Results: Here, we present a novel integrated structure- and system-based approach of drug-target prediction (iDTP) to enable the large-scale discovery of new targets for small molecules, such as pharmaceutical drugs, co-factors and metabolites (collectively called ‘drugs’). For a given drug, our method uses sequence order–independent structure alignment, hierarchical clustering and probabilistic sequence similarity to construct a probabilistic pocket ensemble (PPE) that captures promiscuous structural features of different binding sites on known targets. A drug’s PPE is combined with an approximation of its delivery profile to reduce false positives. In our cross-validation study, we use iDTP to predict the known targets of 11 drugs, with 63% sensitivity and 81% specificity. We then predicted novel targets for these drugs—two that are of high pharmacological interest, the peroxisome proliferator-activated receptor gamma and the oncogene B-cell lymphoma 2, were successfully validated through in vitro binding experiments. Our method is broadly applicable for the prediction of protein-small molecule interactions with several novel applications to biological research and drug development. Availability and implementation: The program, datasets and results are freely available to academic users at http://sfb.kaust.edu.sa/Pages/Software.aspx. Contact: xin.gao@kaust.edu.sa and stefan.arold@kaust.edu.sa Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26286808

The enemy within: Targeting host–parasite interaction for antileishmanial drug discovery

PubMed Central

Späth, Gerald F.; Rachidi, Najma; Prina, Eric

2017-01-01

The state of antileishmanial chemotherapy is strongly compromised by the emergence of drug-resistant Leishmania. The evolution of drug-resistant phenotypes has been linked to the parasites’ intrinsic genome instability, with frequent gene and chromosome amplifications causing fitness gains that are directly selected by environmental factors, including the presence of antileishmanial drugs. Thus, even though the unique eukaryotic biology of Leishmania and its dependence on parasite-specific virulence factors provide valid opportunities for chemotherapeutical intervention, all strategies that target the parasite in a direct fashion are likely prone to select for resistance. Here, we review the current state of antileishmanial chemotherapy and discuss the limitations of ongoing drug discovery efforts. We finally propose new strategies that target Leishmania viability indirectly via mechanisms of host–parasite interaction, including parasite-released ectokinases and host epigenetic regulation, which modulate host cell signaling and transcriptional regulation, respectively, to establish permissive conditions for intracellular Leishmania survival. PMID:28594938

SELF-BLM: Prediction of drug-target interactions via self-training SVM.

PubMed

Keum, Jongsoo; Nam, Hojung

2017-01-01

Predicting drug-target interactions is important for the development of novel drugs and the repositioning of drugs. To predict such interactions, there are a number of methods based on drug and target protein similarity. Although these methods, such as the bipartite local model (BLM), show promise, they often categorize unknown interactions as negative interaction. Therefore, these methods are not ideal for finding potential drug-target interactions that have not yet been validated as positive interactions. Thus, here we propose a method that integrates machine learning techniques, such as self-training support vector machine (SVM) and BLM, to develop a self-training bipartite local model (SELF-BLM) that facilitates the identification of potential interactions. The method first categorizes unlabeled interactions and negative interactions among unknown interactions using a clustering method. Then, using the BLM method and self-training SVM, the unlabeled interactions are self-trained and final local classification models are constructed. When applied to four classes of proteins that include enzymes, G-protein coupled receptors (GPCRs), ion channels, and nuclear receptors, SELF-BLM showed the best performance for predicting not only known interactions but also potential interactions in three protein classes compare to other related studies. The implemented software and supporting data are available at https://github.com/GIST-CSBL/SELF-BLM.

Predicting new molecular targets for known drugs

PubMed Central

Keiser, Michael J.; Setola, Vincent; Irwin, John J.; Laggner, Christian; Abbas, Atheir; Hufeisen, Sandra J.; Jensen, Niels H.; Kuijer, Michael B.; Matos, Roberto C.; Tran, Thuy B.; Whaley, Ryan; Glennon, Richard A.; Hert, Jérôme; Thomas, Kelan L.H.; Edwards, Douglas D.; Shoichet, Brian K.; Roth, Bryan L.

2009-01-01

Whereas drugs are intended to be selective, at least some bind to several physiologic targets, explaining both side effects and efficacy. As many drug-target combinations exist, it would be useful to explore possible interactions computationally. Here, we compared 3,665 FDA-approved and investigational drugs against hundreds of targets, defining each target by its ligands. Chemical similarities between drugs and ligand sets predicted thousands of unanticipated associations. Thirty were tested experimentally, including the antagonism of the β1 receptor by the transporter inhibitor Prozac, the inhibition of the 5-HT transporter by the ion channel drug Vadilex, and antagonism of the histamine H4 receptor by the enzyme inhibitor Rescriptor. Overall, 23 new drug-target associations were confirmed, five of which were potent (< 100 nM). The physiological relevance of one such, the drug DMT on serotonergic receptors, was confirmed in a knock-out mouse. The chemical similarity approach is systematic and comprehensive, and may suggest side-effects and new indications for many drugs. PMID:19881490

Improved prediction of drug-target interactions using regularized least squares integrating with kernel fusion technique.

PubMed

Hao, Ming; Wang, Yanli; Bryant, Stephen H

2016-02-25

Identification of drug-target interactions (DTI) is a central task in drug discovery processes. In this work, a simple but effective regularized least squares integrating with nonlinear kernel fusion (RLS-KF) algorithm is proposed to perform DTI predictions. Using benchmark DTI datasets, our proposed algorithm achieves the state-of-the-art results with area under precision-recall curve (AUPR) of 0.915, 0.925, 0.853 and 0.909 for enzymes, ion channels (IC), G protein-coupled receptors (GPCR) and nuclear receptors (NR) based on 10 fold cross-validation. The performance can further be improved by using a recalculated kernel matrix, especially for the small set of nuclear receptors with AUPR of 0.945. Importantly, most of the top ranked interaction predictions can be validated by experimental data reported in the literature, bioassay results in the PubChem BioAssay database, as well as other previous studies. Our analysis suggests that the proposed RLS-KF is helpful for studying DTI, drug repositioning as well as polypharmacology, and may help to accelerate drug discovery by identifying novel drug targets. Published by Elsevier B.V.

Drug resistance mechanisms and novel drug targets for tuberculosis therapy.

PubMed

Islam, Md Mahmudul; Hameed, H M Adnan; Mugweru, Julius; Chhotaray, Chiranjibi; Wang, Changwei; Tan, Yaoju; Liu, Jianxiong; Li, Xinjie; Tan, Shouyong; Ojima, Iwao; Yew, Wing Wai; Nuermberger, Eric; Lamichhane, Gyanu; Zhang, Tianyu

2017-01-20

Drug-resistant tuberculosis (TB) poses a significant challenge to the successful treatment and control of TB worldwide. Resistance to anti-TB drugs has existed since the beginning of the chemotherapy era. New insights into the resistant mechanisms of anti-TB drugs have been provided. Better understanding of drug resistance mechanisms helps in the development of new tools for the rapid diagnosis of drug-resistant TB. There is also a pressing need in the development of new drugs with novel targets to improve the current treatment of TB and to prevent the emergence of drug resistance in Mycobacterium tuberculosis. This review summarizes the anti-TB drug resistance mechanisms, furnishes some possible novel drug targets in the development of new agents for TB therapy and discusses the usefulness using known targets to develop new anti-TB drugs. Whole genome sequencing is currently an advanced technology to uncover drug resistance mechanisms in M. tuberculosis. However, further research is required to unravel the significance of some newly discovered gene mutations in their contribution to drug resistance. Copyright © 2016 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Ltd. All rights reserved.

Nanocarriers for cancer-targeted drug delivery.

PubMed

Kumari, Preeti; Ghosh, Balaram; Biswas, Swati

2016-01-01

Nanoparticles as drug delivery system have received much attention in recent years, especially for cancer treatment. In addition to improving the pharmacokinetics of the loaded poorly soluble hydrophobic drugs by solubilizing them in the hydrophobic compartments, nanoparticles allowed cancer specific drug delivery by inherent passive targeting phenomena and adopted active targeting strategies. For this reason, nanoparticles-drug formulations are capable of enhancing the safety, pharmacokinetic profiles and bioavailability of the administered drugs leading to improved therapeutic efficacy compared to conventional therapy. The focus of this review is to provide an overview of various nanoparticle formulations in both research and clinical applications with a focus on various chemotherapeutic drug delivery systems for the treatment of cancer. The use of various nanoparticles, including liposomes, polymeric nanoparticles, dendrimers, magnetic and other inorganic nanoparticles for targeted drug delivery in cancer is detailed.

Predicting Drug-Target Interaction Networks Based on Functional Groups and Biological Features

PubMed Central

Shi, Xiao-He; Hu, Le-Le; Kong, Xiangyin; Cai, Yu-Dong; Chou, Kuo-Chen

2010-01-01

Background Study of drug-target interaction networks is an important topic for drug development. It is both time-consuming and costly to determine compound-protein interactions or potential drug-target interactions by experiments alone. As a complement, the in silico prediction methods can provide us with very useful information in a timely manner. Methods/Principal Findings To realize this, drug compounds are encoded with functional groups and proteins encoded by biological features including biochemical and physicochemical properties. The optimal feature selection procedures are adopted by means of the mRMR (Maximum Relevance Minimum Redundancy) method. Instead of classifying the proteins as a whole family, target proteins are divided into four groups: enzymes, ion channels, G-protein- coupled receptors and nuclear receptors. Thus, four independent predictors are established using the Nearest Neighbor algorithm as their operation engine, with each to predict the interactions between drugs and one of the four protein groups. As a result, the overall success rates by the jackknife cross-validation tests achieved with the four predictors are 85.48%, 80.78%, 78.49%, and 85.66%, respectively. Conclusion/Significance Our results indicate that the network prediction system thus established is quite promising and encouraging. PMID:20300175

Target assessment for antiparasitic drug discovery

PubMed Central

Frearson, Julie A.; Wyatt, Paul G.; Gilbert, Ian H.; Fairlamb, Alan H.

2010-01-01

Drug discovery is a high-risk, expensive and lengthy process taking at least 12 years and costing upwards of US$500 million per drug to reach the clinic. For neglected diseases, the drug discovery process is driven by medical need and guided by pre-defined target product profiles. Assessment and prioritisation of the most promising targets for entry into screening programmes is crucial for maximising chances of success. Here we describe criteria used in our drug discovery unit for target assessment and introduce the ‘traffic light’ system as a prioritisation and management tool. We hope this brief review will stimulate basic scientists to acquire additional information necessary for drug discovery. PMID:17962072

Targets of drugs are generally, and targets of drugs having side effects are specifically good spreaders of human interactome perturbations.

PubMed

Perez-Lopez, Áron R; Szalay, Kristóf Z; Türei, Dénes; Módos, Dezső; Lenti, Katalin; Korcsmáros, Tamás; Csermely, Peter

2015-05-11

Network-based methods are playing an increasingly important role in drug design. Our main question in this paper was whether the efficiency of drug target proteins to spread perturbations in the human interactome is larger if the binding drugs have side effects, as compared to those which have no reported side effects. Our results showed that in general, drug targets were better spreaders of perturbations than non-target proteins, and in particular, targets of drugs with side effects were also better spreaders of perturbations than targets of drugs having no reported side effects in human protein-protein interaction networks. Colorectal cancer-related proteins were good spreaders and had a high centrality, while type 2 diabetes-related proteins showed an average spreading efficiency and had an average centrality in the human interactome. Moreover, the interactome-distance between drug targets and disease-related proteins was higher in diabetes than in colorectal cancer. Our results may help a better understanding of the network position and dynamics of drug targets and disease-related proteins, and may contribute to develop additional, network-based tests to increase the potential safety of drug candidates.

Targets of drugs are generally, and targets of drugs having side effects are specifically good spreaders of human interactome perturbations

NASA Astrophysics Data System (ADS)

Perez-Lopez, Áron R.; Szalay, Kristóf Z.; Türei, Dénes; Módos, Dezső; Lenti, Katalin; Korcsmáros, Tamás; Csermely, Peter

2015-05-01

Network-based methods are playing an increasingly important role in drug design. Our main question in this paper was whether the efficiency of drug target proteins to spread perturbations in the human interactome is larger if the binding drugs have side effects, as compared to those which have no reported side effects. Our results showed that in general, drug targets were better spreaders of perturbations than non-target proteins, and in particular, targets of drugs with side effects were also better spreaders of perturbations than targets of drugs having no reported side effects in human protein-protein interaction networks. Colorectal cancer-related proteins were good spreaders and had a high centrality, while type 2 diabetes-related proteins showed an average spreading efficiency and had an average centrality in the human interactome. Moreover, the interactome-distance between drug targets and disease-related proteins was higher in diabetes than in colorectal cancer. Our results may help a better understanding of the network position and dynamics of drug targets and disease-related proteins, and may contribute to develop additional, network-based tests to increase the potential safety of drug candidates.

Targets of drugs are generally, and targets of drugs having side effects are specifically good spreaders of human interactome perturbations

PubMed Central

Perez-Lopez, Áron R.; Szalay, Kristóf Z.; Türei, Dénes; Módos, Dezső; Lenti, Katalin; Korcsmáros, Tamás; Csermely, Peter

2015-01-01

Network-based methods are playing an increasingly important role in drug design. Our main question in this paper was whether the efficiency of drug target proteins to spread perturbations in the human interactome is larger if the binding drugs have side effects, as compared to those which have no reported side effects. Our results showed that in general, drug targets were better spreaders of perturbations than non-target proteins, and in particular, targets of drugs with side effects were also better spreaders of perturbations than targets of drugs having no reported side effects in human protein-protein interaction networks. Colorectal cancer-related proteins were good spreaders and had a high centrality, while type 2 diabetes-related proteins showed an average spreading efficiency and had an average centrality in the human interactome. Moreover, the interactome-distance between drug targets and disease-related proteins was higher in diabetes than in colorectal cancer. Our results may help a better understanding of the network position and dynamics of drug targets and disease-related proteins, and may contribute to develop additional, network-based tests to increase the potential safety of drug candidates. PMID:25960144

Heterocyclic Drug-polymer Conjugates for Cancer Targeted Drug Delivery.

PubMed

Kaur, Harmeet; Desai, Sapna D; Kumar, Virender; Rathi, Pooja; Singh, Jasbir

2016-01-01

New polymer therapeutics like polymer-drug conjugates (PDCs) are developing day by day. Heterocyclic drugs with excellent cytotoxic properties are available, but lack of their specificity makes them available to the normal cells also, which is the main cause of their toxicity. Drugs in the form of PDCs make delivery possible to the specific sites. Most of the PDCs are designed with the aim to either target and/or to get activated in specific cancer microenvironments. Therefore, the most exploited targets for cancer drug delivery are; cancer cell enzymes, heat shock protein 90 (HSP90), multi-drug resistance (MDR) proteins, angiogenesis, apoptosis and cell membrane receptors (e.g., folates, transferrin, etc.). In this review, we will summarize PDCs of heterocyclic drugs, like doxorubicin (DOX), daunorubicin, paclitaxel (PTX), docetaxel (DTX), cisplatin, camptothecin (CPT), geldanamycin (GDM), etc., and some of their analogs for efficient delivery of drugs to cancer cells.

2-Aryl-5-carboxytetrazole as a New Photoaffinity Label for Drug Target Identification

PubMed Central

2016-01-01

Photoaffinity labels are powerful tools for dissecting ligand–protein interactions, and they have a broad utility in medicinal chemistry and drug discovery. Traditional photoaffinity labels work through nonspecific C–H/X–H bond insertion reactions with the protein of interest by the highly reactive photogenerated intermediate. Herein, we report a new photoaffinity label, 2-aryl-5-carboxytetrazole (ACT), that interacts with the target protein via a unique mechanism in which the photogenerated carboxynitrile imine reacts with a proximal nucleophile near the target active site. In two distinct case studies, we demonstrate that the attachment of ACT to a ligand does not significantly alter the binding affinity and specificity of the parent drug. Compared with diazirine and benzophenone, two commonly used photoaffinity labels, in two case studies ACT showed higher photo-cross-linking yields toward their protein targets in vitro based on mass spectrometry analysis. In the in situ target identification studies, ACT successfully captured the desired targets with an efficiency comparable to the diazirine. We expect that further development of this class of photoaffinity labels will lead to a broad range of applications across target identification, and validation and elucidation of the binding site in drug discovery. PMID:27740749

2-Aryl-5-carboxytetrazole as a New Photoaffinity Label for Drug Target Identification.

PubMed

Herner, András; Marjanovic, Jasmina; Lewandowski, Tracey M; Marin, Violeta; Patterson, Melanie; Miesbauer, Laura; Ready, Damien; Williams, Jon; Vasudevan, Anil; Lin, Qing

2016-11-09

Photoaffinity labels are powerful tools for dissecting ligand-protein interactions, and they have a broad utility in medicinal chemistry and drug discovery. Traditional photoaffinity labels work through nonspecific C-H/X-H bond insertion reactions with the protein of interest by the highly reactive photogenerated intermediate. Herein, we report a new photoaffinity label, 2-aryl-5-carboxytetrazole (ACT), that interacts with the target protein via a unique mechanism in which the photogenerated carboxynitrile imine reacts with a proximal nucleophile near the target active site. In two distinct case studies, we demonstrate that the attachment of ACT to a ligand does not significantly alter the binding affinity and specificity of the parent drug. Compared with diazirine and benzophenone, two commonly used photoaffinity labels, in two case studies ACT showed higher photo-cross-linking yields toward their protein targets in vitro based on mass spectrometry analysis. In the in situ target identification studies, ACT successfully captured the desired targets with an efficiency comparable to the diazirine. We expect that further development of this class of photoaffinity labels will lead to a broad range of applications across target identification, and validation and elucidation of the binding site in drug discovery.

Optimization of vascular-targeting drugs in a computational model of tumor growth

NASA Astrophysics Data System (ADS)

Gevertz, Jana

2012-04-01

A biophysical tool is introduced that seeks to provide a theoretical basis for helping drug design teams assess the most promising drug targets and design optimal treatment strategies. The tool is grounded in a previously validated computational model of the feedback that occurs between a growing tumor and the evolving vasculature. In this paper, the model is particularly used to explore the therapeutic effectiveness of two drugs that target the tumor vasculature: angiogenesis inhibitors (AIs) and vascular disrupting agents (VDAs). Using sensitivity analyses, the impact of VDA dosing parameters is explored, as is the effects of administering a VDA with an AI. Further, a stochastic optimization scheme is utilized to identify an optimal dosing schedule for treatment with an AI and a chemotherapeutic. The treatment regimen identified can successfully halt simulated tumor growth, even after the cessation of therapy.

Open-source chemogenomic data-driven algorithms for predicting drug-target interactions.

PubMed

Hao, Ming; Bryant, Stephen H; Wang, Yanli

2018-02-06

While novel technologies such as high-throughput screening have advanced together with significant investment by pharmaceutical companies during the past decades, the success rate for drug development has not yet been improved prompting researchers looking for new strategies of drug discovery. Drug repositioning is a potential approach to solve this dilemma. However, experimental identification and validation of potential drug targets encoded by the human genome is both costly and time-consuming. Therefore, effective computational approaches have been proposed to facilitate drug repositioning, which have proved to be successful in drug discovery. Doubtlessly, the availability of open-accessible data from basic chemical biology research and the success of human genome sequencing are crucial to develop effective in silico drug repositioning methods allowing the identification of potential targets for existing drugs. In this work, we review several chemogenomic data-driven computational algorithms with source codes publicly accessible for predicting drug-target interactions (DTIs). We organize these algorithms by model properties and model evolutionary relationships. We re-implemented five representative algorithms in R programming language, and compared these algorithms by means of mean percentile ranking, a new recall-based evaluation metric in the DTI prediction research field. We anticipate that this review will be objective and helpful to researchers who would like to further improve existing algorithms or need to choose appropriate algorithms to infer potential DTIs in the projects. The source codes for DTI predictions are available at: https://github.com/minghao2016/chemogenomicAlg4DTIpred. Published by Oxford University Press 2018. This work is written by US Government employees and is in the public domain in the US.

Detecting drug-target binding in cells using fluorescence-activated cell sorting coupled with mass spectrometry analysis.

PubMed

Wilson, Kris; Webster, Scott P; Iredale, John P; Zheng, Xiaozhong; Homer, Natalie Z; Pham, Nhan T; Auer, Manfred; Mole, Damian J

2017-12-15

The assessment of drug-target engagement for determining the efficacy of a compound inside cells remains challenging, particularly for difficult target proteins. Existing techniques are more suited to soluble protein targets. Difficult target proteins include those with challenging in vitro solubility, stability or purification properties that preclude target isolation. Here, we report a novel technique that measures intracellular compound-target complex formation, as well as cellular permeability, specificity and cytotoxicity-the toxicity-affinity-permeability-selectivity (TAPS) technique. The TAPS assay is exemplified here using human kynurenine 3-monooxygenase (KMO), a challenging intracellular membrane protein target of significant current interest. TAPS confirmed target binding of known KMO inhibitors inside cells. We conclude that the TAPS assay can be used to facilitate intracellular hit validation on most, if not all intracellular drug targets.

Detecting drug-target binding in cells using fluorescence-activated cell sorting coupled with mass spectrometry analysis

NASA Astrophysics Data System (ADS)

Wilson, Kris; Webster, Scott P.; Iredale, John P.; Zheng, Xiaozhong; Homer, Natalie Z.; Pham, Nhan T.; Auer, Manfred; Mole, Damian J.

2018-01-01

The assessment of drug-target engagement for determining the efficacy of a compound inside cells remains challenging, particularly for difficult target proteins. Existing techniques are more suited to soluble protein targets. Difficult target proteins include those with challenging in vitro solubility, stability or purification properties that preclude target isolation. Here, we report a novel technique that measures intracellular compound-target complex formation, as well as cellular permeability, specificity and cytotoxicity-the toxicity-affinity-permeability-selectivity (TAPS) technique. The TAPS assay is exemplified here using human kynurenine 3-monooxygenase (KMO), a challenging intracellular membrane protein target of significant current interest. TAPS confirmed target binding of known KMO inhibitors inside cells. We conclude that the TAPS assay can be used to facilitate intracellular hit validation on most, if not all intracellular drug targets.

Inferring protein domains associated with drug side effects based on drug-target interaction network.

PubMed

Iwata, Hiroaki; Mizutani, Sayaka; Tabei, Yasuo; Kotera, Masaaki; Goto, Susumu; Yamanishi, Yoshihiro

2013-01-01

Most phenotypic effects of drugs are involved in the interactions between drugs and their target proteins, however, our knowledge about the molecular mechanism of the drug-target interactions is very limited. One of challenging issues in recent pharmaceutical science is to identify the underlying molecular features which govern drug-target interactions. In this paper, we make a systematic analysis of the correlation between drug side effects and protein domains, which we call "pharmacogenomic features," based on the drug-target interaction network. We detect drug side effects and protein domains that appear jointly in known drug-target interactions, which is made possible by using classifiers with sparse models. It is shown that the inferred pharmacogenomic features can be used for predicting potential drug-target interactions. We also discuss advantages and limitations of the pharmacogenomic features, compared with the chemogenomic features that are the associations between drug chemical substructures and protein domains. The inferred side effect-domain association network is expected to be useful for estimating common drug side effects for different protein families and characteristic drug side effects for specific protein domains.

Target validation: linking target and chemical properties to desired product profile.

PubMed

Wyatt, Paul G; Gilbert, Ian H; Read, Kevin D; Fairlamb, Alan H

2011-01-01

The discovery of drugs is a lengthy, high-risk and expensive business taking at least 12 years and is estimated to cost upwards of US$800 million for each drug to be successfully approved for clinical use. Much of this cost is driven by the late phase clinical trials and therefore the ability to terminate early those projects destined to fail is paramount to prevent unwanted costs and wasted effort. Although neglected diseases drug discovery is driven more by unmet medical need rather than financial considerations, the need to minimise wasted money and resources is even more vital in this under-funded area. To ensure any drug discovery project is addressing the requirements of the patients and health care providers and delivering a benefit over existing therapies, the ideal attributes of a novel drug needs to be pre-defined by a set of criteria called a target product profile. Using a target product profile the drug discovery process, clinical study design, and compound characteristics can be defined all the way back through to the suitability or druggability of the intended biochemical target. Assessment and prioritisation of the most promising targets for entry into screening programmes is crucial for maximising chances of success.

Drug Target Discovery Methods In Targeting Neurotropic Parasitic Amoebae.

PubMed

Baig, Abdul Mannan; Waliani, Nuzair; Karim, Saiqa

2018-02-21

Neurotropic parasitic amoebal infections have imposed an enormous challenge to chemotherapy in patients who fall victims to the infections caused by them. Conventional antibiotics that are given to treat these infections have a low patient compliance because of the serious adverse effects that are associated with their use. Additionally, the growing incidence of the development of drug resistance by the neurotropic parasites like Naegleria fowleri, Balamuthia mandrillaris, and Acanthamoeba spp has made the drug therapy more challenging. Recent studies have reported some cellular targets in the neurotropic parasitic Acanthamoeba that are used as receptors by human neurotransmitters like acetylcholine. This Viewpoint attempts to highlight the novel methodologies that use drug assays and structural modeling to uncover cellular targets of diverse groups of drugs and the safety issues of the drugs proposed for their use in brain infections caused by the neurotropic parasitic amoebae.

Targeted Drug-Carrying Bacteriophages as Antibacterial Nanomedicines▿

PubMed Central

Yacoby, Iftach; Bar, Hagit; Benhar, Itai

2007-01-01

While the resistance of bacteria to traditional antibiotics is a major public health concern, the use of extremely potent antibacterial agents is limited by their lack of selectivity. As in cancer therapy, antibacterial targeted therapy could provide an opportunity to reintroduce toxic substances to the antibacterial arsenal. A desirable targeted antibacterial agent should combine binding specificity, a large drug payload per binding event, and a programmed drug release mechanism. Recently, we presented a novel application of filamentous bacteriophages as targeted drug carriers that could partially inhibit the growth of Staphylococcus aureus bacteria. This partial success was due to limitations of drug-loading capacity that resulted from the hydrophobicity of the drug. Here we present a novel drug conjugation chemistry which is based on connecting hydrophobic drugs to the phage via aminoglycoside antibiotics that serve as solubility-enhancing branched linkers. This new formulation allowed a significantly larger drug-carrying capacity of the phages, resulting in a drastic improvement in their performance as targeted drug-carrying nanoparticles. As an example for a potential systemic use for potent agents that are limited for topical use, we present antibody-targeted phage nanoparticles that carry a large payload of the hemolytic antibiotic chloramphenicol connected through the aminoglycoside neomycin. We demonstrate complete growth inhibition toward the pathogens Staphylococcus aureus, Streptococcus pyogenes, and Escherichia coli with an improvement in potency by a factor of ∼20,000 compared to the free drug. PMID:17404004

Inferring protein domains associated with drug side effects based on drug-target interaction network

PubMed Central

2013-01-01

Background Most phenotypic effects of drugs are involved in the interactions between drugs and their target proteins, however, our knowledge about the molecular mechanism of the drug-target interactions is very limited. One of challenging issues in recent pharmaceutical science is to identify the underlying molecular features which govern drug-target interactions. Results In this paper, we make a systematic analysis of the correlation between drug side effects and protein domains, which we call "pharmacogenomic features," based on the drug-target interaction network. We detect drug side effects and protein domains that appear jointly in known drug-target interactions, which is made possible by using classifiers with sparse models. It is shown that the inferred pharmacogenomic features can be used for predicting potential drug-target interactions. We also discuss advantages and limitations of the pharmacogenomic features, compared with the chemogenomic features that are the associations between drug chemical substructures and protein domains. Conclusion The inferred side effect-domain association network is expected to be useful for estimating common drug side effects for different protein families and characteristic drug side effects for specific protein domains. PMID:24565527

Drugs and Targets in Fibrosis

PubMed Central

Li, Xiaoyi; Zhu, Lixin; Wang, Beibei; Yuan, Meifei; Zhu, Ruixin

2017-01-01

Fibrosis contributes to the development of many diseases and many target molecules are involved in fibrosis. Currently, the majority of fibrosis treatment strategies are limited to specific diseases or organs. However, accumulating evidence demonstrates great similarities among fibroproliferative diseases, and more and more drugs are proved to be effective anti-fibrotic therapies across different diseases and organs. Here we comprehensively review the current knowledge on the pathological mechanisms of fibrosis, and divide factors mediating fibrosis progression into extracellular and intracellular groups. Furthermore, we systematically summarize both single and multiple component drugs that target fibrosis. Future directions of fibrosis drug discovery are also proposed. PMID:29218009

Discovery of Anthelmintic Drug Targets and Drugs Using Chokepoints in Nematode Metabolic Pathways

PubMed Central

Taylor, Christina M.; Wang, Qi; Rosa, Bruce A.; Huang, Stanley Ching-Cheng; Powell, Kerrie; Schedl, Tim; Pearce, Edward J.; Abubucker, Sahar; Mitreva, Makedonka

2013-01-01

Parasitic roundworm infections plague more than 2 billion people (1/3 of humanity) and cause drastic losses in crops and livestock. New anthelmintic drugs are urgently needed as new drug resistance and environmental concerns arise. A “chokepoint reaction” is defined as a reaction that either consumes a unique substrate or produces a unique product. A chokepoint analysis provides a systematic method of identifying novel potential drug targets. Chokepoint enzymes were identified in the genomes of 10 nematode species, and the intersection and union of all chokepoint enzymes were found. By studying and experimentally testing available compounds known to target proteins orthologous to nematode chokepoint proteins in public databases, this study uncovers features of chokepoints that make them successful drug targets. Chemogenomic screening was performed on drug-like compounds from public drug databases to find existing compounds that target homologs of nematode chokepoints. The compounds were prioritized based on chemical properties frequently found in successful drugs and were experimentally tested using Caenorhabditis elegans. Several drugs that are already known anthelmintic drugs and novel candidate targets were identified. Seven of the compounds were tested in Caenorhabditis elegans and three yielded a detrimental phenotype. One of these three drug-like compounds, Perhexiline, also yielded a deleterious effect in Haemonchus contortus and Onchocerca lienalis, two nematodes with divergent forms of parasitism. Perhexiline, known to affect the fatty acid oxidation pathway in mammals, caused a reduction in oxygen consumption rates in C. elegans and genome-wide gene expression profiles provided an additional confirmation of its mode of action. Computational modeling of Perhexiline and its target provided structural insights regarding its binding mode and specificity. Our lists of prioritized drug targets and drug-like compounds have potential to expedite the discovery

The identification of new protein kinase inhibitors as targets in modern drug discovery.

PubMed

Akritopoulou-Zanze, Irini

2006-07-01

In recent years there has been great interest in developing protein kinase inhibitors as therapeutic agents for a variety of diseases. This article provides an overview on the history, development and validity of kinases as drug targets, as well as a description of kinase research, including its limitations, challenges and successes.

The Research Progress of Targeted Drug Delivery Systems

NASA Astrophysics Data System (ADS)

Zhan, Jiayin; Ting, Xizi Liang; Zhu, Junjie

2017-06-01

Targeted drug delivery system (DDS) means to selectively transport drugs to targeted tissues, organs, and cells through a variety of drugs carrier. It is usually designed to improve the pharmacological and therapeutic properties of conventional drugs and to overcome problems such as limited solubility, drug aggregation, poor bio distribution and lack of selectivity, controlling drug release carrier and to reduce normal tissue damage. With the characteristics of nontoxic and biodegradable, it can increase the retention of drug in lesion site and the permeability, improve the concentration of the drug in lesion site. at present, there are some kinds of DDS using at test phase, such as slow controlled release drug delivery system, targeted drug delivery systems, transdermal drug delivery system, adhesion dosing system and so on. This paper makes a review for DDS.

A method for predicting target drug efficiency in cancer based on the analysis of signaling pathway activation.

PubMed

Artemov, Artem; Aliper, Alexander; Korzinkin, Michael; Lezhnina, Ksenia; Jellen, Leslie; Zhukov, Nikolay; Roumiantsev, Sergey; Gaifullin, Nurshat; Zhavoronkov, Alex; Borisov, Nicolas; Buzdin, Anton

2015-10-06

A new generation of anticancer therapeutics called target drugs has quickly developed in the 21st century. These drugs are tailored to inhibit cancer cell growth, proliferation, and viability by specific interactions with one or a few target proteins. However, despite formally known molecular targets for every "target" drug, patient response to treatment remains largely individual and unpredictable. Choosing the most effective personalized treatment remains a major challenge in oncology and is still largely trial and error. Here we present a novel approach for predicting target drug efficacy based on the gene expression signature of the individual tumor sample(s). The enclosed bioinformatic algorithm detects activation of intracellular regulatory pathways in the tumor in comparison to the corresponding normal tissues. According to the nature of the molecular targets of a drug, it predicts whether the drug can prevent cancer growth and survival in each individual case by blocking the abnormally activated tumor-promoting pathways or by reinforcing internal tumor suppressor cascades. To validate the method, we compared the distribution of predicted drug efficacy scores for five drugs (Sorafenib, Bevacizumab, Cetuximab, Sorafenib, Imatinib, Sunitinib) and seven cancer types (Clear Cell Renal Cell Carcinoma, Colon cancer, Lung adenocarcinoma, non-Hodgkin Lymphoma, Thyroid cancer and Sarcoma) with the available clinical trials data for the respective cancer types and drugs. The percent of responders to a drug treatment correlated significantly (Pearson's correlation 0.77 p = 0.023) with the percent of tumors showing high drug scores calculated with the current algorithm.

Validation of the proteasome as a therapeutic target in Plasmodium using an epoxyketone inhibitor with parasite-specific toxicity

PubMed Central

Li, Hao; Ponder, Elizabeth L.; Verdoes, Martijn; Asbjornsdottir, Kristijana H.; Deu, Edgar; Edgington, Laura E.; Lee, Jeong Tae; Kirk, Christopher J.; Demo, Susan D.; Williamson, Kim C.; Bogyo, Matthew

2012-01-01

Summary The Plasmodium proteasome has been suggested to be a potential anti-malarial drug target, however toxicity of inhibitors has prevented validation of this enzyme in vivo. We report here a screen of a library of 670 analogs of the recently FDA approved inhibitor, carfilzomib, to identify compounds that selectively kill parasites. We identified one compound, PR3, that has significant parasite killing activity in vitro but dramatically reduced toxicity in host cells. We found that this parasite-specific toxicity is not due to selective targeting of the Plasmodium proteasome over the host proteasome, but instead is due to a lack of activity against one of the human proteasome subunits. Subsequently, we used PR3 to significantly reduce parasite load in P. berghei infected mice without host toxicity, thus validating the proteasome as a viable anti-malarial drug target. PMID:23142757

Killing cancer cells by targeted drug-carrying phage nanomedicines

PubMed Central

Bar, Hagit; Yacoby, Iftach; Benhar, Itai

2008-01-01

Background Systemic administration of chemotherapeutic agents, in addition to its anti-tumor benefits, results in indiscriminate drug distribution and severe toxicity. This shortcoming may be overcome by targeted drug-carrying platforms that ferry the drug to the tumor site while limiting exposure to non-target tissues and organs. Results We present a new form of targeted anti-cancer therapy in the form of targeted drug-carrying phage nanoparticles. Our approach is based on genetically-modified and chemically manipulated filamentous bacteriophages. The genetic manipulation endows the phages with the ability to display a host-specificity-conferring ligand. The phages are loaded with a large payload of a cytotoxic drug by chemical conjugation. In the presented examples we used anti ErbB2 and anti ERGR antibodies as targeting moieties, the drug hygromycin conjugated to the phages by a covalent amide bond, or the drug doxorubicin conjugated to genetically-engineered cathepsin-B sites on the phage coat. We show that targeting of phage nanomedicines via specific antibodies to receptors on cancer cell membranes results in endocytosis, intracellular degradation, and drug release, resulting in growth inhibition of the target cells in vitro with a potentiation factor of >1000 over the corresponding free drugs. Conclusion The results of the proof-of concept study presented here reveal important features regarding the potential of filamentous phages to serve as drug-delivery platform, on the affect of drug solubility or hydrophobicity on the target specificity of the platform and on the effect of drug release mechanism on the potency of the platform. These results define targeted drug-carrying filamentous phage nanoparticles as a unique type of antibody-drug conjugates. PMID:18387177

Assessment of Dengue virus helicase and methyltransferase as targets for fragment-based drug discovery.

PubMed

Coutard, Bruno; Decroly, Etienne; Li, Changqing; Sharff, Andrew; Lescar, Julien; Bricogne, Gérard; Barral, Karine

2014-06-01

Seasonal and pandemic flaviviruses continue to be leading global health concerns. With the view to help drug discovery against Dengue virus (DENV), a fragment-based experimental approach was applied to identify small molecule ligands targeting two main components of the flavivirus replication complex: the NS3 helicase (Hel) and the NS5 mRNA methyltransferase (MTase) domains. A library of 500 drug-like fragments was first screened by thermal-shift assay (TSA) leading to the identification of 36 and 32 fragment hits binding Hel and MTase from DENV, respectively. In a second stage, we set up a fragment-based X-ray crystallographic screening (FBS-X) in order to provide both validated fragment hits and structural binding information. No fragment hit was confirmed for DENV Hel. In contrast, a total of seven fragments were identified as DENV MTase binders and structures of MTase-fragment hit complexes were solved at resolution at least 2.0Å or better. All fragment hits identified contain either a five- or six-membered aromatic ring or both, and three novel binding sites were located on the MTase. To further characterize the fragment hits identified by TSA and FBS-X, we performed enzymatic assays to assess their inhibition effect on the N7- and 2'-O-MTase enzymatic activities: five of these fragment hits inhibit at least one of the two activities with IC50 ranging from 180μM to 9mM. This work validates the FBS-X strategy for identifying new anti-flaviviral hits targeting MTase, while Hel might not be an amenable target for fragment-based drug discovery (FBDD). This approach proved to be a fast and efficient screening method for FBDD target validation and discovery of starting hits for the development of higher affinity molecules that bind to novel allosteric sites. Copyright © 2014 Elsevier B.V. All rights reserved.

Identifying mechanism-of-action targets for drugs and probes

PubMed Central

Gregori-Puigjané, Elisabet; Setola, Vincent; Hert, Jérôme; Crews, Brenda A.; Irwin, John J.; Lounkine, Eugen; Marnett, Lawrence; Roth, Bryan L.; Shoichet, Brian K.

2012-01-01

Notwithstanding their key roles in therapy and as biological probes, 7% of approved drugs are purported to have no known primary target, and up to 18% lack a well-defined mechanism of action. Using a chemoinformatics approach, we sought to “de-orphanize” drugs that lack primary targets. Surprisingly, targets could be easily predicted for many: Whereas these targets were not known to us nor to the common databases, most could be confirmed by literature search, leaving only 13 Food and Drug Administration—approved drugs with unknown targets; the number of drugs without molecular targets likely is far fewer than reported. The number of worldwide drugs without reasonable molecular targets similarly dropped, from 352 (25%) to 44 (4%). Nevertheless, there remained at least seven drugs for which reasonable mechanism-of-action targets were unknown but could be predicted, including the antitussives clemastine, cloperastine, and nepinalone; the antiemetic benzquinamide; the muscle relaxant cyclobenzaprine; the analgesic nefopam; and the immunomodulator lobenzarit. For each, predicted targets were confirmed experimentally, with affinities within their physiological concentration ranges. Turning this question on its head, we next asked which drugs were specific enough to act as chemical probes. Over 100 drugs met the standard criteria for probes, and 40 did so by more stringent criteria. A chemical information approach to drug-target association can guide therapeutic development and reveal applications to probe biology, a focus of much current interest. PMID:22711801

Prediction of Drug-Target Interactions and Drug Repositioning via Network-Based Inference

PubMed Central

Jiang, Jing; Lu, Weiqiang; Li, Weihua; Liu, Guixia; Zhou, Weixing; Huang, Jin; Tang, Yun

2012-01-01

Drug-target interaction (DTI) is the basis of drug discovery and design. It is time consuming and costly to determine DTI experimentally. Hence, it is necessary to develop computational methods for the prediction of potential DTI. Based on complex network theory, three supervised inference methods were developed here to predict DTI and used for drug repositioning, namely drug-based similarity inference (DBSI), target-based similarity inference (TBSI) and network-based inference (NBI). Among them, NBI performed best on four benchmark data sets. Then a drug-target network was created with NBI based on 12,483 FDA-approved and experimental drug-target binary links, and some new DTIs were further predicted. In vitro assays confirmed that five old drugs, namely montelukast, diclofenac, simvastatin, ketoconazole, and itraconazole, showed polypharmacological features on estrogen receptors or dipeptidyl peptidase-IV with half maximal inhibitory or effective concentration ranged from 0.2 to 10 µM. Moreover, simvastatin and ketoconazole showed potent antiproliferative activities on human MDA-MB-231 breast cancer cell line in MTT assays. The results indicated that these methods could be powerful tools in prediction of DTIs and drug repositioning. PMID:22589709

In silico re-identification of properties of drug target proteins.

PubMed

Kim, Baeksoo; Jo, Jihoon; Han, Jonghyun; Park, Chungoo; Lee, Hyunju

2017-05-31

Computational approaches in the identification of drug targets are expected to reduce time and effort in drug development. Advances in genomics and proteomics provide the opportunity to uncover properties of druggable genomes. Although several studies have been conducted for distinguishing drug targets from non-drug targets, they mainly focus on the sequences and functional roles of proteins. Many other properties of proteins have not been fully investigated. Using the DrugBank (version 3.0) database containing nearly 6,816 drug entries including 760 FDA-approved drugs and 1822 of their targets and human UniProt/Swiss-Prot databases, we defined 1578 non-redundant drug target and 17,575 non-drug target proteins. To select these non-redundant protein datasets, we built four datasets (A, B, C, and D) by considering clustering of paralogous proteins. We first reassessed the widely used properties of drug target proteins. We confirmed and extended that drug target proteins (1) are likely to have more hydrophobic, less polar, less PEST sequences, and more signal peptide sequences higher and (2) are more involved in enzyme catalysis, oxidation and reduction in cellular respiration, and operational genes. In this study, we proposed new properties (essentiality, expression pattern, PTMs, and solvent accessibility) for effectively identifying drug target proteins. We found that (1) drug targetability and protein essentiality are decoupled, (2) druggability of proteins has high expression level and tissue specificity, and (3) functional post-translational modification residues are enriched in drug target proteins. In addition, to predict the drug targetability of proteins, we exploited two machine learning methods (Support Vector Machine and Random Forest). When we predicted drug targets by combining previously known protein properties and proposed new properties, an F-score of 0.8307 was obtained. When the newly proposed properties are integrated, the prediction performance

DrugECs: An Ensemble System with Feature Subspaces for Accurate Drug-Target Interaction Prediction

PubMed Central

Jiang, Jinjian; Wang, Nian; Zhang, Jun

2017-01-01

Background Drug-target interaction is key in drug discovery, especially in the design of new lead compound. However, the work to find a new lead compound for a specific target is complicated and hard, and it always leads to many mistakes. Therefore computational techniques are commonly adopted in drug design, which can save time and costs to a significant extent. Results To address the issue, a new prediction system is proposed in this work to identify drug-target interaction. First, drug-target pairs are encoded with a fragment technique and the software “PaDEL-Descriptor.” The fragment technique is for encoding target proteins, which divides each protein sequence into several fragments in order and encodes each fragment with several physiochemical properties of amino acids. The software “PaDEL-Descriptor” creates encoding vectors for drug molecules. Second, the dataset of drug-target pairs is resampled and several overlapped subsets are obtained, which are then input into kNN (k-Nearest Neighbor) classifier to build an ensemble system. Conclusion Experimental results on the drug-target dataset showed that our method performs better and runs faster than the state-of-the-art predictors. PMID:28744468

Updates on drug-target network; facilitating polypharmacology and data integration by growth of DrugBank database.

PubMed

Barneh, Farnaz; Jafari, Mohieddin; Mirzaie, Mehdi

2016-11-01

Network pharmacology elucidates the relationship between drugs and targets. As the identified targets for each drug increases, the corresponding drug-target network (DTN) evolves from solely reflection of the pharmaceutical industry trend to a portrait of polypharmacology. The aim of this study was to evaluate the potentials of DrugBank database in advancing systems pharmacology. We constructed and analyzed DTN from drugs and targets associations in the DrugBank 4.0 database. Our results showed that in bipartite DTN, increased ratio of identified targets for drugs augmented density and connectivity of drugs and targets and decreased modular structure. To clear up the details in the network structure, the DTNs were projected into two networks namely, drug similarity network (DSN) and target similarity network (TSN). In DSN, various classes of Food and Drug Administration-approved drugs with distinct therapeutic categories were linked together based on shared targets. Projected TSN also showed complexity because of promiscuity of the drugs. By including investigational drugs that are currently being tested in clinical trials, the networks manifested more connectivity and pictured the upcoming pharmacological space in the future years. Diverse biological processes and protein-protein interactions were manipulated by new drugs, which can extend possible target combinations. We conclude that network-based organization of DrugBank 4.0 data not only reveals the potential for repurposing of existing drugs, also allows generating novel predictions about drugs off-targets, drug-drug interactions and their side effects. Our results also encourage further effort for high-throughput identification of targets to build networks that can be integrated into disease networks. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Plasmodial sugar transporters as anti-malarial drug targets and comparisons with other protozoa.

PubMed

Slavic, Ksenija; Krishna, Sanjeev; Derbyshire, Elvira T; Staines, Henry M

2011-06-15

Glucose is the primary source of energy and a key substrate for most cells. Inhibition of cellular glucose uptake (the first step in its utilization) has, therefore, received attention as a potential therapeutic strategy to treat various unrelated diseases including malaria and cancers. For malaria, blood forms of parasites rely almost entirely on glycolysis for energy production and, without energy stores, they are dependent on the constant uptake of glucose. Plasmodium falciparum is the most dangerous human malarial parasite and its hexose transporter has been identified as being the major glucose transporter. In this review, recent progress regarding the validation and development of the P. falciparum hexose transporter as a drug target is described, highlighting the importance of robust target validation through both chemical and genetic methods. Therapeutic targeting potential of hexose transporters of other protozoan pathogens is also reviewed and discussed.

Targeted Cellular Drug Delivery using Tailored Dendritic Nanostructures

NASA Astrophysics Data System (ADS)

Kannan, Rangaramanujam; Kolhe, Parag; Kannan, Sujatha; Lieh-Lai, Mary

2002-03-01

Dendrimers and hyperbranched polymers possess highly branched architectures, with a large number of controllable, tailorble, ‘peripheral’ functionalities. Since the surface chemistry of these materials can be modified with relative ease, these materials have tremendous potential in targeted drug and gene delivery. The large number of end groups can also be tailored to create special affinity to targeted cells, and can also encapsulate drugs and deliver them in a controlled manner. We are developing tailor-modified dendritic systems for drug delivery. Synthesis, in-vitro drug loading, in-vitro drug delivery, and the targeting efficiency to the cell are being studied systematically using a wide variety of experimental tools. Polyamidoamine and Polyol dendrimers, with different generations and end-groups are studied, with drugs such as Ibuprofen and Methotrexate. Our results indicate that a large number of drug molecules can be encapsulated/attached to the dendrimers, depending on the end groups. The drug-encapsulated dendrimer is able to enter the cells rapidly and deliver the drug. Targeting strategies being explored

Glycyrrhetinic acid-functionalized mesoporous silica nanoparticles as hepatocellular carcinoma-targeted drug carrier.

PubMed

Lv, Yongjiu; Li, Jingjing; Chen, Huali; Bai, Yan; Zhang, Liangke

2017-01-01

In this study, a glycyrrhetinic acid-functionalized mesoporous silica nanoparticle (MSN-GA) was prepared for active tumor targeting. MSN-GA exhibited satisfactory loading capacity for insoluble drugs, uniform size distribution, and specific tumor cell targeting. Glycyrrhetinic acid, a hepatocellular carcinoma-targeting group, was covalently decorated on the surface of MSN via an amido bond. The successful synthesis of MSN-GA was validated by the results of Fourier transform infrared spectroscopy, transmission electron microscopy (TEM), and zeta potential measurement. TEM images revealed the spherical morphology and uniform size distribution of the naked MSN and MSN-GA. Curcumin (CUR), an insoluble model drug, was loaded into MSN-GA (denoted as MSN-GA-CUR) with a high-loading capacity (8.78%±1.24%). The results of the in vitro cellular experiment demonstrated that MSN-GA-CUR significantly enhanced cytotoxicity and cellular uptake toward hepatocellular carcinoma (HepG2) cells via a specific GA receptor-mediated endocytosis mechanism. The results of this study provide a promising nanoplatform for the targeting of hepatocellular carcinoma.

Glycyrrhetinic acid-functionalized mesoporous silica nanoparticles as hepatocellular carcinoma-targeted drug carrier

PubMed Central

Lv, Yongjiu; Li, Jingjing; Chen, Huali; Bai, Yan; Zhang, Liangke

2017-01-01

In this study, a glycyrrhetinic acid-functionalized mesoporous silica nanoparticle (MSN-GA) was prepared for active tumor targeting. MSN-GA exhibited satisfactory loading capacity for insoluble drugs, uniform size distribution, and specific tumor cell targeting. Glycyrrhetinic acid, a hepatocellular carcinoma-targeting group, was covalently decorated on the surface of MSN via an amido bond. The successful synthesis of MSN-GA was validated by the results of Fourier transform infrared spectroscopy, transmission electron microscopy (TEM), and zeta potential measurement. TEM images revealed the spherical morphology and uniform size distribution of the naked MSN and MSN-GA. Curcumin (CUR), an insoluble model drug, was loaded into MSN-GA (denoted as MSN-GA-CUR) with a high-loading capacity (8.78%±1.24%). The results of the in vitro cellular experiment demonstrated that MSN-GA-CUR significantly enhanced cytotoxicity and cellular uptake toward hepatocellular carcinoma (HepG2) cells via a specific GA receptor-mediated endocytosis mechanism. The results of this study provide a promising nanoplatform for the targeting of hepatocellular carcinoma. PMID:28652738

Crowd Sourcing a New Paradigm for Interactome Driven Drug Target Identification in Mycobacterium tuberculosis

PubMed Central

Rohira, Harsha; Bhat, Ashwini G.; Passi, Anurag; Mukherjee, Keya; Choudhary, Kumari Sonal; Kumar, Vikas; Arora, Anshula; Munusamy, Prabhakaran; Subramanian, Ahalyaa; Venkatachalam, Aparna; S, Gayathri; Raj, Sweety; Chitra, Vijaya; Verma, Kaveri; Zaheer, Salman; J, Balaganesh; Gurusamy, Malarvizhi; Razeeth, Mohammed; Raja, Ilamathi; Thandapani, Madhumohan; Mevada, Vishal; Soni, Raviraj; Rana, Shruti; Ramanna, Girish Muthagadhalli; Raghavan, Swetha; Subramanya, Sunil N.; Kholia, Trupti; Patel, Rajesh; Bhavnani, Varsha; Chiranjeevi, Lakavath; Sengupta, Soumi; Singh, Pankaj Kumar; Atray, Naresh; Gandhi, Swati; Avasthi, Tiruvayipati Suma; Nisthar, Shefin; Anurag, Meenakshi; Sharma, Pratibha; Hasija, Yasha; Dash, Debasis; Sharma, Arun; Scaria, Vinod; Thomas, Zakir; Chandra, Nagasuma; Brahmachari, Samir K.; Bhardwaj, Anshu

2012-01-01

A decade since the availability of Mycobacterium tuberculosis (Mtb) genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative ‘Connect to Decode’ (C2D) to generate the first and largest manually curated interactome of Mtb termed ‘interactome pathway’ (IPW), encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach. PMID:22808064

Drug-therapy networks and the prediction of novel drug targets

PubMed Central

Spiro, Zoltan; Kovacs, Istvan A; Csermely, Peter

2008-01-01

A recent study in BMC Pharmacology presents a network of drugs and the therapies in which they are used. Network approaches open new ways of predicting novel drug targets and overcoming the cellular robustness that can prevent drugs from working. PMID:18710588

Nanogel Carrier Design for Targeted Drug Delivery

PubMed Central

Eckmann, D. M.; Composto, R. J.; Tsourkas, A.; Muzykantov, V. R.

2014-01-01

Polymer-based nanogel formulations offer features attractive for drug delivery, including ease of synthesis, controllable swelling and viscoelasticity as well as drug loading and release characteristics, passive and active targeting, and the ability to formulate nanogel carriers that can respond to biological stimuli. These unique features and low toxicity make the nanogels a favorable option for vascular drug targeting. In this review, we address key chemical and biological aspects of nanogel drug carrier design. In particular, we highlight published studies of nanogel design, descriptions of nanogel functional characteristics and their behavior in biological models. These studies form a compendium of information that supports the scientific and clinical rationale for development of this carrier for targeted therapeutic interventions. PMID:25485112

Exoproteome and Secretome Derived Broad Spectrum Novel Drug and Vaccine Candidates in Vibrio cholerae Targeted by Piper betel Derived Compounds

PubMed Central

Barh, Debmalya; Barve, Neha; Gupta, Krishnakant; Chandra, Sudha; Jain, Neha; Tiwari, Sandeep; Leon-Sicairos, Nidia; Canizalez-Roman, Adrian; Rodrigues dos Santos, Anderson; Hassan, Syed Shah; Almeida, Síntia; Thiago Jucá Ramos, Rommel; Augusto Carvalho de Abreu, Vinicius; Ribeiro Carneiro, Adriana; de Castro Soares, Siomar; Luiz de Paula Castro, Thiago; Miyoshi, Anderson; Silva, Artur; Kumar, Anil; Narayan Misra, Amarendra; Blum, Kenneth; Braverman, Eric R.; Azevedo, Vasco

2013-01-01

Vibrio cholerae is the causal organism of the cholera epidemic, which is mostly prevalent in developing and underdeveloped countries. However, incidences of cholera in developed countries are also alarming. Because of the emergence of new drug-resistant strains, even though several generic drugs and vaccines have been developed over time, Vibrio infections remain a global health problem that appeals for the development of novel drugs and vaccines against the pathogen. Here, applying comparative proteomic and reverse vaccinology approaches to the exoproteome and secretome of the pathogen, we have identified three candidate targets (ompU, uppP and yajC) for most of the pathogenic Vibrio strains. Two targets (uppP and yajC) are novel to Vibrio, and two targets (uppP and ompU) can be used to develop both drugs and vaccines (dual targets) against broad spectrum Vibrio serotypes. Using our novel computational approach, we have identified three peptide vaccine candidates that have high potential to induce both B- and T-cell-mediated immune responses from our identified two dual targets. These two targets were modeled and subjected to virtual screening against natural compounds derived from Piper betel. Seven compounds were identified first time from Piper betel to be highly effective to render the function of these targets to identify them as emerging potential drugs against Vibrio. Our preliminary validation suggests that these identified peptide vaccines and betel compounds are highly effective against Vibrio cholerae. Currently we are exhaustively validating these targets, candidate peptide vaccines, and betel derived lead compounds against a number of Vibrio species. PMID:23382822

Limited Efficiency of Drug Delivery to Specific Intracellular Organelles Using Subcellularly "Targeted" Drug Delivery Systems.

PubMed

Maity, Amit Ranjan; Stepensky, David

2016-01-04

Many drugs have been designed to act on intracellular targets and to affect intracellular processes inside target cells. For the desired effects to be exerted, these drugs should permeate target cells and reach specific intracellular organelles. This subcellular drug targeting approach has been proposed for enhancement of accumulation of these drugs in target organelles and improved efficiency. This approach is based on drug encapsulation in drug delivery systems (DDSs) and/or their decoration with specific targeting moieties that are intended to enhance the drug/DDS accumulation in the intracellular organelle of interest. During recent years, there has been a constant increase in interest in DDSs targeted to specific intracellular organelles, and many different approaches have been proposed for attaining efficient drug delivery to specific organelles of interest. However, it appears that in many studies insufficient efforts have been devoted to quantitative analysis of the major formulation parameters of the DDSs disposition (efficiency of DDS endocytosis and endosomal escape, intracellular trafficking, and efficiency of DDS delivery to the target organelle) and of the resulting pharmacological effects. Thus, in many cases, claims regarding efficient delivery of drug/DDS to a specific organelle and efficient subcellular targeting appear to be exaggerated. On the basis of the available experimental data, it appears that drugs/DDS decoration with specific targeting residues can affect their intracellular fate and result in preferential drug accumulation within an organelle of interest. However, it is not clear whether these approaches will be efficient in in vivo settings and be translated into preclinical and clinical applications. Studies that quantitatively assess the mechanisms, barriers, and efficiencies of subcellular drug delivery and of the associated toxic effects are required to determine the therapeutic potential of subcellular DDS targeting.

Numerical simulations of targeted delivery of magnetic drug aerosols in the human upper and central respiratory system: a validation study.

PubMed

Kenjereš, Saša; Tjin, Jimmy Leroy

2017-12-01

In the present study, we investigate the concept of the targeted delivery of pharmaceutical drug aerosols in an anatomically realistic geometry of the human upper and central respiratory system. The geometry considered extends from the mouth inlet to the eighth generation of the bronchial bifurcations and is identical to the phantom model used in the experimental studies of Banko et al. (2015 Exp. Fluids 56 , 1-12 (doi:10.1007/s00348-015-1966-y)). In our computer simulations, we combine the transitional Reynolds-averaged Navier-Stokes (RANS) and the wall-resolved large eddy simulation (LES) methods for the air phase with the Lagrangian approach for the particulate (aerosol) phase. We validated simulations against recently obtained magnetic resonance velocimetry measurements of Banko et al. (2015 Exp. Fluids 56 , 1-12. (doi:10.1007/s00348-015-1966-y)) that provide a full three-dimensional mean velocity field for steady inspiratory conditions. Both approaches produced good agreement with experiments, and the transitional RANS approach is selected for the multiphase simulations of aerosols transport, because of significantly lower computational costs. The local and total deposition efficiency are calculated for different classes of pharmaceutical particles (in the 0.1 μm≤ d p ≤10 μm range) without and with a paramagnetic core (the shell-core particles). For the latter, an external magnetic field is imposed. The source of the imposed magnetic field was placed in the proximity of the first bronchial bifurcation. We demonstrated that both total and local depositions of aerosols at targeted locations can be significantly increased by an applied magnetization force. This finding confirms the possible potential for further advancement of the magnetic drug targeting technique for more efficient treatments for respiratory diseases.

Drug-target interaction prediction: A Bayesian ranking approach.

PubMed

Peska, Ladislav; Buza, Krisztian; Koller, Júlia

2017-12-01

In silico prediction of drug-target interactions (DTI) could provide valuable information and speed-up the process of drug repositioning - finding novel usage for existing drugs. In our work, we focus on machine learning algorithms supporting drug-centric repositioning approach, which aims to find novel usage for existing or abandoned drugs. We aim at proposing a per-drug ranking-based method, which reflects the needs of drug-centric repositioning research better than conventional drug-target prediction approaches. We propose Bayesian Ranking Prediction of Drug-Target Interactions (BRDTI). The method is based on Bayesian Personalized Ranking matrix factorization (BPR) which has been shown to be an excellent approach for various preference learning tasks, however, it has not been used for DTI prediction previously. In order to successfully deal with DTI challenges, we extended BPR by proposing: (i) the incorporation of target bias, (ii) a technique to handle new drugs and (iii) content alignment to take structural similarities of drugs and targets into account. Evaluation on five benchmark datasets shows that BRDTI outperforms several state-of-the-art approaches in terms of per-drug nDCG and AUC. BRDTI results w.r.t. nDCG are 0.929, 0.953, 0.948, 0.897 and 0.690 for G-Protein Coupled Receptors (GPCR), Ion Channels (IC), Nuclear Receptors (NR), Enzymes (E) and Kinase (K) datasets respectively. Additionally, BRDTI significantly outperformed other methods (BLM-NII, WNN-GIP, NetLapRLS and CMF) w.r.t. nDCG in 17 out of 20 cases. Furthermore, BRDTI was also shown to be able to predict novel drug-target interactions not contained in the original datasets. The average recall at top-10 predicted targets for each drug was 0.762, 0.560, 1.000 and 0.404 for GPCR, IC, NR, and E datasets respectively. Based on the evaluation, we can conclude that BRDTI is an appropriate choice for researchers looking for an in silico DTI prediction technique to be used in drug

Targeting Antibacterial Agents by Using Drug-Carrying Filamentous Bacteriophages

PubMed Central

Yacoby, Iftach; Shamis, Marina; Bar, Hagit; Shabat, Doron; Benhar, Itai

2006-01-01

Bacteriophages have been used for more than a century for (unconventional) therapy of bacterial infections, for half a century as tools in genetic research, for 2 decades as tools for discovery of specific target-binding proteins, and for nearly a decade as tools for vaccination or as gene delivery vehicles. Here we present a novel application of filamentous bacteriophages (phages) as targeted drug carriers for the eradication of (pathogenic) bacteria. The phages are genetically modified to display a targeting moiety on their surface and are used to deliver a large payload of a cytotoxic drug to the target bacteria. The drug is linked to the phages by means of chemical conjugation through a labile linker subject to controlled release. In the conjugated state, the drug is in fact a prodrug devoid of cytotoxic activity and is activated following its dissociation from the phage at the target site in a temporally and spatially controlled manner. Our model target was Staphylococcus aureus, and the model drug was the antibiotic chloramphenicol. We demonstrated the potential of using filamentous phages as universal drug carriers for targetable cells involved in disease. Our approach replaces the selectivity of the drug itself with target selectivity borne by the targeting moiety, which may allow the reintroduction of nonspecific drugs that have thus far been excluded from antibacterial use (because of toxicity or low selectivity). Reintroduction of such drugs into the arsenal of useful tools may help to combat emerging bacterial antibiotic resistance. PMID:16723570

Promising Targets in Anti-cancer Drug Development: Recent Updates.

PubMed

Kumar, Bhupinder; Singh, Sandeep; Skvortsova, Ira; Kumar, Vinod

2017-01-01

Cancer is a multifactorial disease and its genesis and progression are extremely complex. The biggest problem in the anticancer drug development is acquiring of multidrug resistance and relapse. Classical chemotherapeutics directly target the DNA of the cell, while the contemporary anticancer drugs involve molecular-targeted therapy such as targeting the proteins possessing abnormal expression inside the cancer cells. Conventional strategies for the complete eradication of the cancer cells proved ineffective. Targeted chemotherapy was successful in certain malignancies however, the effectiveness has often been limited by drug resistance and side effects on normal tissues and cells. Since last few years, many promising drug targets have been identified for the effective treatment of cancer. The current review article describes some of these promising anticancer targets that include kinases, tubulin, cancer stem cells, monoclonal antibodies and vascular targeting agents. In addition, promising drug candidates under various phases of clinical trials are also described. Multi-acting drugs that simultaneously target different cancer cell signaling pathways may facilitate the process of effective anti-cancer drug development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A compact targeted drug delivery mechanism for a next generation wireless capsule endoscope.

PubMed

Woods, Stephen P; Constandinou, Timothy G

2016-01-01

This paper reports a novel medication release and delivery mechanism as part of a next generation wireless capsule endoscope (WCE) for targeted drug delivery. This subsystem occupies a volume of only 17.9mm 3 for the purpose of delivering a 1 ml payload to a target site of interest in the small intestinal tract. An in-depth analysis of the method employed to release and deliver the medication is described and a series of experiments is presented which validates the drug delivery system. The results show that a variable pitch conical compression spring manufactured from stainless steel can deliver 0.59 N when it is fully compressed and that this would be sufficient force to deliver the onboard medication.

A standalone perfusion platform for drug testing and target validation in micro-vessel networks

PubMed Central

Zhang, Boyang; Peticone, Carlotta; Murthy, Shashi K.; Radisic, Milica

2013-01-01

Studying the effects of pharmacological agents on human endothelium includes the routine use of cell monolayers cultivated in multi-well plates. This configuration fails to recapitulate the complex architecture of vascular networks in vivo and does not capture the relationship between shear stress (i.e. flow) experienced by the cells and dose of the applied pharmacological agents. Microfluidic platforms have been applied extensively to create vascular systems in vitro; however, they rely on bulky external hardware to operate, which hinders the wide application of microfluidic chips by non-microfluidic experts. Here, we have developed a standalone perfusion platform where multiple devices were perfused at a time with a single miniaturized peristaltic pump. Using the platform, multiple micro-vessel networks, that contained three levels of branching structures, were created by culturing endothelial cells within circular micro-channel networks mimicking the geometrical configuration of natural blood vessels. To demonstrate the feasibility of our platform for drug testing and validation assays, a drug induced nitric oxide assay was performed on the engineered micro-vessel network using a panel of vaso-active drugs (acetylcholine, phenylephrine, atorvastatin, and sildenafil), showing both flow and drug dose dependent responses. The interactive effects between flow and drug dose for sildenafil could not be captured by a simple straight rectangular channel coated with endothelial cells, but it was captured in a more physiological branching circular network. A monocyte adhesion assay was also demonstrated with and without stimulation by an inflammatory cytokine, tumor necrosis factor-α. PMID:24404058

Plasmodial sugar transporters as anti-malarial drug targets and comparisons with other protozoa

PubMed Central

2011-01-01

Glucose is the primary source of energy and a key substrate for most cells. Inhibition of cellular glucose uptake (the first step in its utilization) has, therefore, received attention as a potential therapeutic strategy to treat various unrelated diseases including malaria and cancers. For malaria, blood forms of parasites rely almost entirely on glycolysis for energy production and, without energy stores, they are dependent on the constant uptake of glucose. Plasmodium falciparum is the most dangerous human malarial parasite and its hexose transporter has been identified as being the major glucose transporter. In this review, recent progress regarding the validation and development of the P. falciparum hexose transporter as a drug target is described, highlighting the importance of robust target validation through both chemical and genetic methods. Therapeutic targeting potential of hexose transporters of other protozoan pathogens is also reviewed and discussed. PMID:21676209

Predicting Drug-Target Interactions Based on Small Positive Samples.

PubMed

Hu, Pengwei; Chan, Keith C C; Hu, Yanxing

2018-01-01

A basic task in drug discovery is to find new medication in the form of candidate compounds that act on a target protein. In other words, a drug has to interact with a target and such drug-target interaction (DTI) is not expected to be random. Significant and interesting patterns are expected to be hidden in them. If these patterns can be discovered, new drugs are expected to be more easily discoverable. Currently, a number of computational methods have been proposed to predict DTIs based on their similarity. However, such as approach does not allow biochemical features to be directly considered. As a result, some methods have been proposed to try to discover patterns in physicochemical interactions. Since the number of potential negative DTIs are very high both in absolute terms and in comparison to that of the known ones, these methods are rather computationally expensive and they can only rely on subsets, rather than the full set, of negative DTIs for training and validation. As there is always a relatively high chance for negative DTIs to be falsely identified and as only partial subset of such DTIs is considered, existing approaches can be further improved to better predict DTIs. In this paper, we present a novel approach, called ODT (one class drug target interaction prediction), for such purpose. One main task of ODT is to discover association patterns between interacting drugs and proteins from the chemical structure of the former and the protein sequence network of the latter. ODT does so in two phases. First, the DTI-network is transformed to a representation by structural properties. Second, it applies a oneclass classification algorithm to build a prediction model based only on known positive interactions. We compared the best AUROC scores of the ODT with several state-of-art approaches on Gold standard data. The prediction accuracy of the ODT is superior in comparison with all the other methods at GPCRs dataset and Ion channels dataset. Performance

Biodegradable polymers for targeted delivery of anti-cancer drugs.

PubMed

Doppalapudi, Sindhu; Jain, Anjali; Domb, Abraham J; Khan, Wahid

2016-06-01

Biodegradable polymers have been used for more than three decades in cancer treatment and have received increased interest in recent years. A range of biodegradable polymeric drug delivery systems designed for localized and systemic administration of therapeutic agents as well as tumor-targeting macromolecules has entered into the clinical phase of development, indicating the significance of biodegradable polymers in cancer therapy. This review elaborates upon applications of biodegradable polymers in the delivery and targeting of anti-cancer agents. Design of various drug delivery systems based on biodegradable polymers has been described. Moreover, the indication of polymers in the targeted delivery of chemotherapeutic drugs via passive, active targeting, and localized drug delivery are also covered. Biodegradable polymer-based drug delivery systems have the potential to deliver the payload to the target and can enhance drug availability at desired sites. Systemic toxicity and serious side effects observed with conventional cancer therapeutics can be significantly reduced with targeted polymeric systems. Still, there are many challenges that need to be met with respect to the degradation kinetics of the system, diffusion of drug payload within solid tumors, targeting tumoral tissue and tumor heterogeneity.

Dual responsive PNIPAM-chitosan targeted magnetic nanopolymers for targeted drug delivery

NASA Astrophysics Data System (ADS)

Yadavalli, Tejabhiram; Ramasamy, Shivaraman; Chandrasekaran, Gopalakrishnan; Michael, Isaac; Therese, Helen Annal; Chennakesavulu, Ramasamy

2015-04-01

A dual stimuli sensitive magnetic hyperthermia based drug delivery system has been developed for targeted cancer treatment. Thermosensitive amine terminated poly-N-isopropylacrylamide complexed with pH sensitive chitosan nanoparticles was prepared as the drug carrier. Folic acid and fluorescein were tagged to the nanopolymer complex via N-hydroxysuccinimide and ethyl-3-(3-dimethylaminopropyl)carbodiimide reaction to form a fluorescent and cancer targeting magnetic carrier system. The formation of the polymer complex was confirmed using infrared spectroscopy. Gadolinium doped nickel ferrite nanoparticles prepared by a hydrothermal method were encapsulated in the polymer complex to form a magnetic drug carrier system. The proton relaxation studies on the magnetic carrier system revealed a 200% increase in the T1 proton relaxation rate. These magnetic carriers were loaded with curcumin using solvent evaporation method with a drug loading efficiency of 86%. Drug loaded nanoparticles were tested for their targeting and anticancer properties on four cancer cell lines with the help of MTT assay. The results indicated apoptosis of cancer cell lines within 3 h of incubation.

GRP78 enabled micelle-based glioma targeted drug delivery.

PubMed

Ran, Danni; Mao, Jiani; Shen, Qing; Xie, Cao; Zhan, Changyou; Wang, Ruifeng; Lu, Weiyue

2017-06-10

GRP78, a specific cancer cell-surface marker, is implicated in cancer cells proliferation, apoptosis resistance, metastasis and drug resistance. l-VAP (SNTRVAP) is a tumor homing peptide exhibiting high binding affinity in vitro to GRP78 protein overexpressed on glioma, glioma stem cells, vasculogenic mimicry and neovasculature. Even though short peptides are often non-immunogenic and demonstrate high affinity to tumor cells, their targeting efficacy is always undermined by rapid blood clearance and enzymatic degradation. In the present study, two d peptides RI-VAP (retro inverso isomer of l-VAP) and d-VAP (retro isomer of l-VAP) were developed by structure-guided peptide design and retro-inverso isomerization technique for glioma targeting. RI-VAP and d-VAP were predicted to bind their receptor GRP78 protein with similar binding affinity, which was experimentally confirmed. The results of in vivo imaging demonstrated that RI-VAP and d-VAP had remarkably advantage over l-VAP for tumor accumulation. In addition, RI-VAP and d-VAP modified paclitaxel-loaded polymeric micelle had better anti-tumor efficacy in comparison to taxol, paclitaxel-loaded plain micelles and l-VAP modified micelles. Overall, the VAP modified micelles suggested in the present study could effectively achieve glioma-targeted drug delivery, validating the potential of the stable VAP peptides in improving the therapeutic efficacy of paclitaxel for glioma. Copyright © 2017 Elsevier B.V. All rights reserved.

New Equilibrium Models of Drug-Receptor Interactions Derived from Target-Mediated Drug Disposition.

PubMed

Peletier, Lambertus A; Gabrielsson, Johan

2018-05-14

In vivo analyses of pharmacological data are traditionally based on a closed system approach not incorporating turnover of target and ligand-target kinetics, but mainly focussing on ligand-target binding properties. This study incorporates information about target and ligand-target kinetics parallel to binding. In a previous paper, steady-state relationships between target- and ligand-target complex versus ligand exposure were derived and a new expression of in vivo potency was derived for a circulating target. This communication is extending the equilibrium relationships and in vivo potency expression for (i) two separate targets competing for one ligand, (ii) two different ligands competing for a single target and (iii) a single ligand-target interaction located in tissue. The derived expressions of the in vivo potencies will be useful both in drug-related discovery projects and mechanistic studies. The equilibrium states of two targets and one ligand may have implications in safety assessment, whilst the equilibrium states of two competing ligands for one target may cast light on when pharmacodynamic drug-drug interactions are important. The proposed equilibrium expressions for a peripherally located target may also be useful for small molecule interactions with extravascularly located targets. Including target turnover, ligand-target complex kinetics and binding properties in expressions of potency and efficacy will improve our understanding of within and between-individual (and across species) variability. The new expressions of potencies highlight the fact that the level of drug-induced target suppression is very much governed by target turnover properties rather than by the target expression level as such.

Understanding drug targets: no such thing as bad news.

PubMed

Roberts, Ruth A

2018-05-24

How can small-to-medium pharma and biotech companies enhance the chances of running a successful drug project and maximise the return on a limited number of assets? Having a full appreciation of the safety risks associated with proposed drug targets is a crucial element in understanding the unwanted side-effects that might stop a project in its tracks. Having this information is necessary to complement knowledge about the probable efficacy of a future drug. However, the lack of data-rich insight into drug-target safety is one of the major causes of drug-project failure today. Conducting comprehensive target-safety reviews early in the drug discovery process enables project teams to make the right decisions about which drug targets to take forward. Copyright © 2018 Elsevier Ltd. All rights reserved.

Treponema pallidum Putative Novel Drug Target Identification and Validation: Rethinking Syphilis Therapeutics with Plant-Derived Terpenoids

PubMed Central

Tiwari, Sameeksha; Singh, Priyanka; Singh, Swati; Awasthi, Manika; Pandey, Veda P.

2015-01-01

Abstract Syphilis, a slow progressive and the third most common sexually transmitted disease found worldwide, is caused by a spirochete gram negative bacteria Treponema pallidum. Emergence of antibiotic resistant T. pallidum has led to a search for novel drugs and their targets. Subtractive genomics analyses of pathogen T. pallidum and host Homo sapiens resulted in identification of 126 proteins essential for survival and viability of the pathogen. Metabolic pathway analyses of these essential proteins led to discovery of nineteen proteins distributed among six metabolic pathways unique to T. pallidum. One hundred plant-derived terpenoids, as potential therapeutic molecules against T. pallidum, were screened for their drug likeness and ADMET (absorption, distribution, metabolism, and toxicity) properties. Subsequently the resulting nine terpenoids were docked with five unique T. pallidum targets through molecular modeling approaches. Out of five targets analyzed, D-alanine:D-alanine ligase was found to be the most promising target, while terpenoid salvicine was the most potent inhibitor. A comparison of the inhibitory potential of the best docked readily available natural compound, namely pomiferin (flavonoid) with that of the best docked terpenoid salvicine, revealed that salvicine was a more potent inhibitor than that of pomiferin. To the best of our knowledge, this is the first report of a terpenoid as a potential therapeutic molecule against T. pallidum with D-alanine:D-alanine ligase as a novel target. Further studies are warranted to evaluate and explore the potential clinical ramifications of these findings in relation to syphilis that has public health importance worldwide. PMID:25683888

Natural products used as a chemical library for protein-protein interaction targeted drug discovery.

PubMed

Jin, Xuemei; Lee, Kyungro; Kim, Nam Hee; Kim, Hyun Sil; Yook, Jong In; Choi, Jiwon; No, Kyoung Tai

2018-01-01

Protein-protein interactions (PPIs), which are essential for cellular processes, have been recognized as attractive therapeutic targets. Therefore, the construction of a PPI-focused chemical library is an inevitable necessity for future drug discovery. Natural products have been used as traditional medicines to treat human diseases for millennia; in addition, their molecular scaffolds have been used in diverse approved drugs and drug candidates. The recent discovery of the ability of natural products to inhibit PPIs led us to use natural products as a chemical library for PPI-targeted drug discovery. In this study, we collected natural products (NPDB) from non-commercial and in-house databases to analyze their similarities to small-molecule PPI inhibitors (iPPIs) and FDA-approved drugs by using eight molecular descriptors. Then, we evaluated the distribution of NPDB and iPPIs in the chemical space, represented by the molecular fingerprint and molecular scaffolds, to identify the promising scaffolds, which could interfere with PPIs. To investigate the ability of natural products to inhibit PPI targets, molecular docking was used. Then, we predicted a set of high-potency natural products by using the iPPI-likeness score based on a docking score-weighted model. These selected natural products showed high binding affinities to the PPI target, namely XIAP, which were validated in an in vitro experiment. In addition, the natural products with novel scaffolds might provide a promising starting point for further medicinal chemistry developments. Overall, our study shows the potency of natural products in targeting PPIs, which might help in the design of a PPI-focused chemical library for future drug discovery. Copyright © 2017 Elsevier Inc. All rights reserved.

Identification and validation nucleolin as a target of curcumol in nasopharyngeal carcinoma cells.

PubMed

Wang, Juan; Wu, Jiacai; Li, Xumei; Liu, Haowei; Qin, Jianli; Bai, Zhun; Chi, Bixia; Chen, Xu

2018-06-30

Identification of the specific protein target(s) of a drug is a critical step in unraveling its mechanisms of action (MOA) in many natural products. Curcumol, isolated from well known Chinese medicinal plant Curcuma zedoary, has been shown to possess multiple biological activities. It can inhibit nasopharyngeal carcinoma (NPC) proliferation and induce apoptosis, but its target protein(s) in NPC cells remains unclear. In this study, we employed a mass spectrometry-based chemical proteomics approach reveal the possible protein targets of curcumol in NPC cells. Cellular thermal shift assay (CETSA), molecular docking and cell-based assay was used to validate the binding interactions. Chemical proteomics capturing uncovered that NCL is a target of curcumol in NPC cells, Molecular docking showed that curcumol bound to NCL with an -7.8 kcal/mol binding free energy. Cell function analysis found that curcumol's treatment leads to a degradation of NCL in NPC cells, and it showed slight effects on NP69 cells. In conclusion, our results providing evidences that NCL is a target protein of curcumol. We revealed that the anti-cancer effects of curcumol in NPC cells are mediated, at least in part, by NCL inhibition. Many natural products showed high bioactivity, while their mechanisms of action (MOA) are very poor or completely missed. Understanding the MOA of natural drugs can thoroughly exploit their therapeutic potential and minimize their adverse side effects. Identification of the specific protein target(s) of a drug is a critical step in unraveling its MOA. Compound-centric chemical proteomics is a classic chemical proteomics approach which integrates chemical synthesis with cell biology and mass spectrometry (MS) to identify protein targets of natural products determine the drug mechanism of action, describe its toxicity, and figure out the possible cause of off-target. It is an affinity-based chemical proteomics method to identify small molecule-protein interactions

Breast Cancer-Targeted Nuclear Drug Delivery Overcoming Drug Resistance for Breast Cancer Chemotherapy

DTIC Science & Technology

2011-09-01

breast-cancer-targeted nuclear drug delivery carriers , but we found that the ability of the PEI to disrupt the endosome/lysosome membrane was not...AD_________________ Award Number: W81XWH-09-1-0502 TITLE: Breast Cancer-Targeted Nuclear Drug ...Delivery Overcoming Drug Resistance for Breast Cancer Chemotherapy PRINCIPAL INVESTIGATOR: Youqing Shen, Ph.D

Targeted delivery of anti-tuberculosis drugs to macrophages: targeting mannose receptors

NASA Astrophysics Data System (ADS)

Filatova, L. Yu; Klyachko, N. L.; Kudryashova, E. V.

2018-04-01

The development of systems for targeted delivery of anti-tuberculosis drugs is a challenge of modern biotechnology. Currently, these drugs are encapsulated in a variety of carriers such as liposomes, polymers, emulsions and so on. Despite successful in vitro testing of these systems, virtually no success was achieved in vivo, because of low accessibility of the foci of infection located in alveolar macrophage cells. A promising strategy for increasing the efficiency of therapeutic action of anti-tuberculosis drugs is to encapsulate the agents into mannosylated carriers targeting the mannose receptors of alveolar macrophages. The review addresses the methods for modification of drug substance carriers, such as liposomes and biodegradable polymers, with mannose residues. The use of mannosylated carriers to deliver anti-tuberculosis agents increases the drug circulation time in the blood stream and increases the drug concentration in alveolar macrophage cells. The bibliography includes 113 references.

A General Strategy for Targeting Drugs to Bone.

PubMed

Jahnke, Wolfgang; Bold, Guido; Marzinzik, Andreas L; Ofner, Silvio; Pellé, Xavier; Cotesta, Simona; Bourgier, Emmanuelle; Lehmann, Sylvie; Henry, Chrystelle; Hemmig, René; Stauffer, Frédéric; Hartwieg, J Constanze D; Green, Jonathan R; Rondeau, Jean-Michel

2015-11-23

Targeting drugs to their desired site of action can increase their safety and efficacy. Bisphosphonates are prototypical examples of drugs targeted to bone. However, bisphosphonate bone affinity is often considered too strong and cannot be significantly modulated without losing activity on the enzymatic target, farnesyl pyrophosphate synthase (FPPS). Furthermore, bisphosphonate bone affinity comes at the expense of very low and variable oral bioavailability. FPPS inhibitors were developed with a monophosphonate as a bone-affinity tag that confers moderate affinity to bone, which can furthermore be tuned to the desired level, and the relationship between structure and bone affinity was evaluated by using an NMR-based bone-binding assay. The concept of targeting drugs to bone with moderate affinity, while retaining oral bioavailability, has broad application to a variety of other bone-targeted drugs. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Importance of target-mediated drug disposition for small molecules.

PubMed

Smith, Dennis A; van Waterschoot, Robert A B; Parrott, Neil J; Olivares-Morales, Andrés; Lavé, Thierry; Rowland, Malcolm

2018-06-18

Target concentration is typically not considered in drug discovery. However, if targets are expressed at relatively high concentrations and compounds have high affinity, such that most of the drug is bound to its target, in vitro screens can give unreliable information on compound affinity. In vivo, a similar situation will generate pharmacokinetic (PK) profiles that deviate greatly from those normally expected, owing to target binding affecting drug distribution and clearance. Such target-mediated drug disposition (TMDD) effects on small molecules have received little attention and might only become apparent during clinical trials, with the potential for data misinterpretation. TMDD also confounds human microdosing approaches by providing therapeutically unrepresentative PK profiles. Being aware of these phenomena will improve the likelihood of successful drug discovery and development. Copyright © 2018. Published by Elsevier Ltd.

Non-clinical studies required for new drug development - Part I: early in silico and in vitro studies, new target discovery and validation, proof of principles and robustness of animal studies.

PubMed

Andrade, E L; Bento, A F; Cavalli, J; Oliveira, S K; Freitas, C S; Marcon, R; Schwanke, R C; Siqueira, J M; Calixto, J B

2016-10-24

This review presents a historical overview of drug discovery and the non-clinical stages of the drug development process, from initial target identification and validation, through in silico assays and high throughput screening (HTS), identification of leader molecules and their optimization, the selection of a candidate substance for clinical development, and the use of animal models during the early studies of proof-of-concept (or principle). This report also discusses the relevance of validated and predictive animal models selection, as well as the correct use of animal tests concerning the experimental design, execution and interpretation, which affect the reproducibility, quality and reliability of non-clinical studies necessary to translate to and support clinical studies. Collectively, improving these aspects will certainly contribute to the robustness of both scientific publications and the translation of new substances to clinical development.

Drug2Gene: an exhaustive resource to explore effectively the drug-target relation network.

PubMed

Roider, Helge G; Pavlova, Nadia; Kirov, Ivaylo; Slavov, Stoyan; Slavov, Todor; Uzunov, Zlatyo; Weiss, Bertram

2014-03-11

Information about drug-target relations is at the heart of drug discovery. There are now dozens of databases providing drug-target interaction data with varying scope, and focus. Therefore, and due to the large chemical space, the overlap of the different data sets is surprisingly small. As searching through these sources manually is cumbersome, time-consuming and error-prone, integrating all the data is highly desirable. Despite a few attempts, integration has been hampered by the diversity of descriptions of compounds, and by the fact that the reported activity values, coming from different data sets, are not always directly comparable due to usage of different metrics or data formats. We have built Drug2Gene, a knowledge base, which combines the compound/drug-gene/protein information from 19 publicly available databases. A key feature is our rigorous unification and standardization process which makes the data truly comparable on a large scale, allowing for the first time effective data mining in such a large knowledge corpus. As of version 3.2, Drug2Gene contains 4,372,290 unified relations between compounds and their targets most of which include reported bioactivity data. We extend this set with putative (i.e. homology-inferred) relations where sufficient sequence homology between proteins suggests they may bind to similar compounds. Drug2Gene provides powerful search functionalities, very flexible export procedures, and a user-friendly web interface. Drug2Gene v3.2 has become a mature and comprehensive knowledge base providing unified, standardized drug-target related information gathered from publicly available data sources. It can be used to integrate proprietary data sets with publicly available data sets. Its main goal is to be a 'one-stop shop' to identify tool compounds targeting a given gene product or for finding all known targets of a drug. Drug2Gene with its integrated data set of public compound-target relations is freely accessible without

Aging Biology and Novel Targets for Drug Discovery

PubMed Central

McLachlan, Andrew J.; Quinn, Ronald J.; Simpson, Stephen J.; de Cabo, Rafael

2012-01-01

Despite remarkable technological advances in genetics and drug screening, the discovery of new pharmacotherapies has slowed and new approaches to drug development are needed. Research into the biology of aging is generating many novel targets for drug development that may delay all age-related diseases and be used long term by the entire population. Drugs that successfully delay the aging process will clearly become “blockbusters.” To date, the most promising leads have come from studies of the cellular pathways mediating the longevity effects of caloric restriction (CR), particularly target of rapamycin and the sirtuins. Similar research into pathways governing other hormetic responses that influence aging is likely to yield even more targets. As aging becomes a more attractive target for drug development, there will be increasing demand to develop biomarkers of aging as surrogate outcomes for the testing of the effects of new agents on the aging process. PMID:21693687

Chloride channels as drug targets

PubMed Central

Verkman, Alan S.; Galietta, Luis J. V.

2013-01-01

Chloride channels represent a relatively under-explored target class for drug discovery as elucidation of their identity and physiological roles has lagged behind that of many other drug targets. Chloride channels are involved in a wide range of biological functions, including epithelial fluid secretion, cell-volume regulation, neuroexcitation, smooth-muscle contraction and acidification of intracellular organelles. Mutations in several chloride channels cause human diseases, including cystic fibrosis, macular degeneration, myotonia, kidney stones, renal salt wasting and hyperekplexia. Chloride-channel modulators have potential applications in the treatment of some of these disorders, as well as in secretory diarrhoeas, polycystic kidney disease, osteoporosis and hypertension. Modulators of GABAA (γ-aminobutyric acid A) receptor chloride channels are in clinical use and several small-molecule chloride-channel modulators are in preclinical development and clinical trials. Here, we discuss the broad opportunities that remain in chloride-channel-based drug discovery. PMID:19153558

Towards a Drug Development Path that Targets Metastatic Progression in Osteosarcoma

PubMed Central

Khanna, Chand; Fan, Timothy M.; Gorlick, Richard; Helman, Lee J; Kleinerman, Eugenie S.; Adamson, Peter C.; Houghton, Peter J.; Tap, William D.; Welch, Danny R.; Steeg, Patricia S.; Merlino, Glenn; Sorensen, Poul HB; Kirsch, David G.; Janeway, Katherine A.; Weigel, Brenda; Randall, R. Lor; Meltzer, Paul; Withrow, Stephen J; Paoloni, Melissa; Kaplan, Rosandra N.; Teicher, Beverly A.; Seibel, Nita L.; Üren, Aykut; Patel, Shreyaskumar R.; Trent, Jeffrey; Savage, Sharon A.; Mirabello, Lisa; Reinke, Denise; Barkauskas, Donald A.; Krailo, Mark; Smith, Malcolm A.; Bernstein, Mark

2014-01-01

Despite successful primary tumor treatment, the development of pulmonary metastasis continues to be the most common cause of mortality in osteosarcoma patients. A conventional drug development path requiring drugs to induce regression of established lesions has not led to improvements for osteosarcoma patients in over 30 years. Based on our growing understanding of metastasis biology, it is now reasonable and essential that we focus on developing therapeutics that target metastatic progression. To advance this agenda a meeting of key opinion leaders and experts in the metastasis and osteosarcoma communities was convened in Bethesda Maryland. The goal of this meeting was to provide a “Perspective” that would establish a preclinical translational path that could support the early evaluation of potential therapeutic agents that uniquely target the metastatic phenotype. Although focused on osteosarcoma the need for this perspective is shared among many cancer types. The consensus achieved from the meeting included the following: That the biology of metastatic progression is associated with metastasis-specific targets/processes that may not influence grossly detectable lesions; targeting of metastasis-specific processes is feasible; rigorous preclinical data is needed to support translation of metastasis-specific agents into human trials where regression of measurable disease is not an expected outcome; preclinical data should include an understanding of mechanism of action, validation of pharmacodynamic markers of effective exposure and response, the use of several murine models of effectiveness, and where feasible the inclusion of the dog with naturally occurring osteosarcoma to define the activity of new drugs in the micro-metastatic disease setting. PMID:24803583

Self-Assembled Smart Nanocarriers for Targeted Drug Delivery.

PubMed

Cui, Wei; Li, Junbai; Decher, Gero

2016-02-10

Nanostructured drug-carrier systems promise numerous benefits for drug delivery. They can be engineered to precisely control drug-release rates or to target specific sites within the body with a specific amount of therapeutic agent. However, to achieve the best therapeutic effects, the systems should be designed for carrying the optimum amount of a drug to the desired target where it should be released at the optimum rate for a specified time. Despite numerous attempts, fulfilling all of these requirements in a synergistic way remains a huge challenge. The trend in drug delivery is consequently directed toward integrated multifunctional carrier systems, providing selective recognition in combination with sustained or triggered release. Capsules as vesicular systems enable drugs to be confined for controlled release. Furthermore, carriers modified with recognition groups can enhance the capability of encapsulated drug efficacy. Here, recent advances are reviewed regarding designing and preparing assembled capsules with targeting ligands or size controllable for selective recognition in drug delivery. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Solution NMR Spectroscopy in Target-Based Drug Discovery.

PubMed

Li, Yan; Kang, Congbao

2017-08-23

Solution NMR spectroscopy is a powerful tool to study protein structures and dynamics under physiological conditions. This technique is particularly useful in target-based drug discovery projects as it provides protein-ligand binding information in solution. Accumulated studies have shown that NMR will play more and more important roles in multiple steps of the drug discovery process. In a fragment-based drug discovery process, ligand-observed and protein-observed NMR spectroscopy can be applied to screen fragments with low binding affinities. The screened fragments can be further optimized into drug-like molecules. In combination with other biophysical techniques, NMR will guide structure-based drug discovery. In this review, we describe the possible roles of NMR spectroscopy in drug discovery. We also illustrate the challenges encountered in the drug discovery process. We include several examples demonstrating the roles of NMR in target-based drug discoveries such as hit identification, ranking ligand binding affinities, and mapping the ligand binding site. We also speculate the possible roles of NMR in target engagement based on recent processes in in-cell NMR spectroscopy.

Experimental Drug Metarrestin Targets Metastatic Tumors

Cancer.gov

An experimental drug called metarrestin appears to selectively target tumors that have spread to other parts of the body. As this Cancer Currents blog post reports, the drug shrank metastatic tumors and extended survival in in mouse models of pancreatic cancer.

CRISPR-Cas9-based target validation for p53-reactivating model compounds

PubMed Central

Wanzel, Michael; Vischedyk, Jonas B; Gittler, Miriam P; Gremke, Niklas; Seiz, Julia R; Hefter, Mirjam; Noack, Magdalena; Savai, Rajkumar; Mernberger, Marco; Charles, Joël P; Schneikert, Jean; Bretz, Anne Catherine; Nist, Andrea; Stiewe, Thorsten

2015-01-01

Inactivation of the p53 tumor suppressor by Mdm2 is one of the most frequent events in cancer, so compounds targeting the p53-Mdm2 interaction are promising for cancer therapy. Mechanisms conferring resistance to p53-reactivating compounds are largely unknown. Here we show using CRISPR-Cas9–based target validation in lung and colorectal cancer that the activity of nutlin, which blocks the p53-binding pocket of Mdm2, strictly depends on functional p53. In contrast, sensitivity to the drug RITA, which binds the Mdm2-interacting N terminus of p53, correlates with induction of DNA damage. Cells with primary or acquired RITA resistance display cross-resistance to DNA crosslinking compounds such as cisplatin and show increased DNA cross-link repair. Inhibition of FancD2 by RNA interference or pharmacological mTOR inhibitors restores RITA sensitivity. The therapeutic response to p53-reactivating compounds is therefore limited by compound-specific resistance mechanisms that can be resolved by CRISPR-Cas9-based target validation and should be considered when allocating patients to p53-reactivating treatments. PMID:26595461

A review on proniosomal drug delivery system for targeted drug action.

PubMed

Radha, G V; Rani, T Sudha; Sarvani, B

2013-03-01

Proniosomes are dry formulation of water soluble carrier particles that are coated with surfactant. They are rehydrated to form niosomal dispersion immediately before use on agitation in hot aqueous media within minutes. Proniosomes are physically stable during the storage and transport. Drug encapsulated in the vesicular structure of proniosomes prolong the existence of drug in the systematic circulation and enhances the penetration into target tissue and reduce toxicity. From a technical point of view, niosomes are promising drug carriers as they possess greater chemical stability and lack of many disadvantages associated with liposomes, such as high- cost and variable purity problems of phospholipids. The present review emphasizes on overall methods of preparation characterization and applicability of proniosomes in targeted drug action.

Multifunctional particles for melanoma-targeted drug delivery.

PubMed

Wadajkar, Aniket S; Bhavsar, Zarna; Ko, Cheng-Yu; Koppolu, Bhanuprasanth; Cui, Weina; Tang, Liping; Nguyen, Kytai T

2012-08-01

New magnetic-based core-shell particles (MBCSPs) were developed to target skin cancer cells while delivering chemotherapeutic drugs in a controlled fashion. MBCSPs consist of a thermo-responsive shell of poly(N-isopropylacrylamide-acrylamide-allylamine) and a core of poly(lactic-co-glycolic acid) (PLGA) embedded with magnetite nanoparticles. To target melanoma cancer cells, MBCSPs were conjugated with Gly-Arg-Gly-Asp-Ser (GRGDS) peptides that specifically bind to the α(5)β(3) receptors of melanoma cells. MBCSPs consist of unique multifunctional and controlled drug delivery characteristics. Specially, they can provide dual drug release mechanisms (a sustained release of drugs through degradation of PLGA core and a controlled release in response to changes in temperature via thermo-responsive polymer shell), and dual targeting mechanisms (magnetic localization and receptor-mediated targeting). Results from in vitro studies indicate that GRGDS-conjugated MBCSPs have an average diameter of 296 nm and exhibit no cytotoxicity towards human dermal fibroblasts up to 500 μg ml(-1). Further, a sustained release of curcumin from the core and a temperature-dependent release of doxorubicin from the shell of MBCSPs were observed. The particles also produced a dark contrast signal in magnetic resonance imaging. Finally, the particles were accumulated at the tumor site in a B16F10 melanoma orthotopic mouse model, especially in the presence of a magnet. Results indicate great potential of MBCSPs as a platform technology to target, treat and monitor melanoma for targeted drug delivery to reduce side effects of chemotherapeutic reagents. Copyright © 2012 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

DrugPath: a database for academic investigators to match oncology molecular targets with drugs in development.

PubMed

Shah, Eric D; Fisch, Brandon M A; Arceci, Robert J; Buckley, Jonathan D; Reaman, Gregory H; Sorensen, Poul H; Triche, Timothy J; Reynolds, C Patrick

2014-05-01

Academic laboratories are developing increasingly large amounts of data that describe the genomic landscape and gene expression patterns of various types of cancers. Such data can potentially identify novel oncology molecular targets in cancer types that may not be the primary focus of a drug sponsor's initial research for an investigational new drug. Obtaining preclinical data that point toward the potential for a given molecularly targeted agent, or a novel combination of agents requires knowledge of drugs currently in development in both the academic and commercial sectors. We have developed the DrugPath database ( http://www.drugpath.org ) as a comprehensive, free-of-charge resource for academic investigators to identify agents being developed in academics or industry that may act against molecular targets of interest. DrugPath data on molecular targets overlay the Michigan Molecular Interactions ( http://mimi.ncibi.org ) gene-gene interaction map to facilitate identification of related agents in the same pathway. The database catalogs 2,081 drug development programs representing 751 drug sponsors and 722 molecular and genetic targets. DrugPath should assist investigators in identifying and obtaining drugs acting on specific molecular targets for biological and preclinical therapeutic studies.

Drug targets for resistant malaria: Historic to future perspectives.

PubMed

Kumar, Sahil; Bhardwaj, T R; Prasad, D N; Singh, Rajesh K

2018-05-11

New antimalarial targets are the prime need for the discovery of potent drug candidates. In order to fulfill this objective, antimalarial drug researches are focusing on promising targets in order to develop new drug candidates. Basic metabolism and biochemical process in the malaria parasite, i.e. Plasmodium falciparum can play an indispensable role in the identification of these targets. But, the emergence of resistance to antimalarial drugs is an escalating comprehensive problem with the progress of antimalarial drug development. The development of resistance has highlighted the need for the search of novel antimalarial molecules. The pharmaceutical industries are committed to new drug development due to the global recognition of this life threatening resistance to the currently available antimalarial therapy. The recent developments in the understanding of parasite biology are exhilarating this resistance issue which is further being ignited by malaria genome project. With this background of information, this review was aimed to highlights and provides useful information on various present and promising treatment approaches for resistant malaria, new progresses, pursued by some innovative targets that have been explored till date. This review also discusses modern and futuristic multiple approaches to antimalarial drug discovery and development with pictorial presentations highlighting the various targets, that could be exploited for generating promising new drugs in the future for drug resistant malaria. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Enhanced cellular transport and drug targeting using dendritic nanostructures

NASA Astrophysics Data System (ADS)

Kannan, R. M.; Kolhe, Parag; Kannan, Sujatha; Lieh-Lai, Mary

2003-03-01

Dendrimers and hyperbranched polymers possess highly branched architectures, with a large number of controllable, tailorable, peripheral' functionalities. Since the surface chemistry of these materials can be modified with relative ease, these materials have tremendous potential in targeted drug delivery. The large density of end groups can also be tailored to create enhanced affinity to targeted cells, and can also encapsulate drugs and deliver them in a controlled manner. We are developing tailor-modified dendritic systems for drug delivery. Synthesis, drug/ligand conjugation, in vitro cellular and in vivo drug delivery, and the targeting efficiency to the cell are being studied systematically using a wide variety of experimental tools. Results on PAMAM dendrimers and polyol hyperbranched polymers suggest that: (1) These materials complex/encapsulate a large number of drug molecules and release them at tailorable rates; (2) The drug-dendrimer complex is transported very rapidly through a A549 lung epithelial cancel cell line, compared to free drug, perhaps by endocytosis. The ability of the drug-dendrimer-ligand complexes to target specific asthma and cancer cells is currently being explored using in vitro and in vivo animal models.

Data-Driven prioritisation of antibody-drug conjugate targets in head and neck squamous cell carcinoma.

PubMed

Hanemaaijer, Saskia H; van Gijn, Stephanie E; Oosting, Sjoukje F; Plaat, Boudewijn E C; Moek, Kirsten L; Schuuring, Ed M; van der Laan, Bernard F A M; Roodenburg, Jan L N; van Vugt, Marcel A T M; van der Vegt, Bert; Fehrmann, Rudolf S N

2018-05-01

For patients with recurrent or metastatic head and neck squamous cell carcinoma (HNSCC) palliative treatment options that improve overall survival are limited. The prognosis in this group remains poor and there is an unmet need for new therapeutic options. An emerging class of therapeutics, targeting tumor-specific antigens, are antibodies bound to a cytotoxic agent, known as antibody-drug conjugates (ADCs). The aim of this study was to prioritize ADC targets in HNSCC. With a systematic search, we identified 55 different ADC targets currently targeted by registered ADCs and ADCs under clinical evaluation. For these 55 ADC targets, protein overexpression was predicted in a dataset containing 344 HNSCC mRNA expression profiles by using a method called functional genomic mRNA profiling. The ADC target with the highest predicted overexpression was validated by performing immunohistochemistry (IHC) on an independent tissue microarray containing 414 HNSCC tumors. The predicted top 5 overexpressed ADC targets in HNSCC were: glycoprotein nmb (GPNMB), SLIT and NTRK-like family member 6, epidermal growth factor receptor, CD74 and CD44. IHC validation showed combined cytoplasmic and membranous GPNMB protein expression in 92.0% of the cases. Strong expression was seen in 65.9% of the cases. In addition, 86.5% and 67.7% of cases showed ≥5% and >25% GPNMB positive tumor cells, respectively. This study provides a data-driven prioritization of ADCs targets that will facilitate clinicians and drug developers in deciding which ADC should be taken for further clinical evaluation in HNSCC. This might help to improve disease outcome of HNSCC patients. Copyright © 2018 Elsevier Ltd. All rights reserved.

Liposome-based glioma targeted drug delivery enabled by stable peptide ligands.

PubMed

Wei, Xiaoli; Gao, Jie; Zhan, Changyou; Xie, Cao; Chai, Zhilan; Ran, Danni; Ying, Man; Zheng, Ping; Lu, Weiyue

2015-11-28

The treatment of glioma is one of the most challenging tasks in clinic. As an intracranial tumor, glioma exhibits many distinctive characteristics from other tumors. In particular, various barriers including enzymatic barriers in the blood and brain capillary endothelial cells, blood-brain barrier (BBB) and blood-brain tumor barrier (BBTB) rigorously prevent drug and drug delivery systems from reaching the tumor site. To tackle this dilemma, we developed a liposomal formulation to circumvent multiple-barriers by modifying the liposome surface with proteolytically stable peptides, (D)CDX and c(RGDyK). (D)CDX is a D-peptide ligand of nicotine acetylcholine receptors (nAChRs) on the BBB, and c(RGDyK) is a ligand of integrin highly expressed on the BBTB and glioma cells. Lysosomal compartments of brain capillary endothelial cells are implicated in the transcytosis of those liposomes. However, both peptide ligands displayed exceptional stability in lysosomal homogenate, ensuring that intact ligands could exert subsequent exocytosis from brain capillary endothelial cells and glioma targeting. In the cellular uptake studies, dually labeled liposomes could target both brain capillary endothelial cells and tumor cells, effectively traversing the BBB and BBTB monolayers, overcoming enzymatic barrier and targeting three-dimensional tumor spheroids. Its targeting ability to intracranial glioma was further verified in vivo by ex vivo imaging and histological studies. As a result, doxorubicin liposomes modified with both (D)CDX and c(RGDyK) presented better anti-glioma effect with prolonged median survival of nude mice bearing glioma than did unmodified liposomes and liposomes modified with individual peptide ligand. In conclusion, the liposome suggested in the present study could effectively overcome multi-barriers and accomplish glioma targeted drug delivery, validating its potential value in improving the therapeutic efficacy of doxorubicin for glioma. Copyright © 2015

Drug Target Interference in Immunogenicity Assays: Recommendations and Mitigation Strategies.

PubMed

Zhong, Zhandong Don; Clements-Egan, Adrienne; Gorovits, Boris; Maia, Mauricio; Sumner, Giane; Theobald, Valerie; Wu, Yuling; Rajadhyaksha, Manoj

2017-11-01

Sensitive and specific methodology is required for the detection and characterization of anti-drug antibodies (ADAs). High-quality ADA data enables the evaluation of potential impact of ADAs on the drug pharmacokinetic profile, patient safety, and efficacious response to the drug. Immunogenicity assessments are typically initiated at early stages in preclinical studies and continue throughout the drug development program. One of the potential bioanalytical challenges encountered with ADA testing is the need to identify and mitigate the interference mediated by the presence of soluble drug target. A drug target, when present at sufficiently high circulating concentrations, can potentially interfere with the performance of ADA and neutralizing antibody (NAb) assays, leading to either false-positive or, in some cases, false-negative ADA and NAb assay results. This publication describes various mechanisms of assay interference by soluble drug target, as well as strategies to recognize and mitigate such target interference. Pertinent examples are presented to illustrate the impact of target interference on ADA and NAb assays as well as several mitigation strategies, including the use of anti-target antibodies, soluble versions of the receptors, target-binding proteins, lectins, and solid-phase removal of targets. Furthermore, recommendations for detection and mitigation of such interference in different formats of ADA and NAb assays are provided.

Drug Targeting and Biomarkers in Head and Neck Cancers: Insights from Systems Biology Analyses.

PubMed

Islam, Tania; Rahman, Rezanur; Gov, Esra; Turanli, Beste; Gulfidan, Gizem; Haque, Anwarul; Arga, Kazım Yalçın; Haque Mollah, Nurul

2018-06-01

The head and neck squamous cell carcinoma (HNSCC) is one of the most common cancers in the world, but robust biomarkers and diagnostics are still not available. This study provides in-depth insights from systems biology analyses to identify molecular biomarker signatures to inform systematic drug targeting in HNSCC. Gene expression profiles from tumors and normal tissues of 22 patients with histological confirmation of nonmetastatic HNSCC were subjected to integrative analyses with genome-scale biomolecular networks (i.e., protein-protein interaction and transcriptional and post-transcriptional regulatory networks). We aimed to discover molecular signatures at RNA and protein levels, which could serve as potential drug targets for therapeutic innovation in the future. Eleven proteins, 5 transcription factors, and 20 microRNAs (miRNAs) came into prominence as potential drug targets. The differential expression profiles of these reporter biomolecules were cross-validated by independent RNA-Seq and miRNA-Seq datasets, and risk discrimination performance of the reporter biomolecules, BLNK, CCL2, E4F1, FOSL1, ISG15, MMP9, MYCN, MYH11, miR-1252, miR-29b, miR-29c, miR-3610, miR-431, and miR-523, was also evaluated. Using the transcriptome guided drug repositioning tool, geneXpharma, several candidate drugs were repurposed, including antineoplastic agents (e.g., gemcitabine and irinotecan), antidiabetics (e.g., rosiglitazone), dermatological agents (e.g., clocortolone and acitretin), and antipsychotics (e.g., risperidone), and binding affinities of the drugs to their potential targets were assessed using molecular docking analyses. The molecular signatures and repurposed drugs presented in this study warrant further attention for experimental studies since they offer significant potential as biomarkers and candidate therapeutics for precision medicine approaches to clinical management of HNSCC.

Drug Target Prediction and Repositioning Using an Integrated Network-Based Approach

PubMed Central

Emig, Dorothea; Ivliev, Alexander; Pustovalova, Olga; Lancashire, Lee; Bureeva, Svetlana; Nikolsky, Yuri; Bessarabova, Marina

2013-01-01

The discovery of novel drug targets is a significant challenge in drug development. Although the human genome comprises approximately 30,000 genes, proteins encoded by fewer than 400 are used as drug targets in the treatment of diseases. Therefore, novel drug targets are extremely valuable as the source for first in class drugs. On the other hand, many of the currently known drug targets are functionally pleiotropic and involved in multiple pathologies. Several of them are exploited for treating multiple diseases, which highlights the need for methods to reliably reposition drug targets to new indications. Network-based methods have been successfully applied to prioritize novel disease-associated genes. In recent years, several such algorithms have been developed, some focusing on local network properties only, and others taking the complete network topology into account. Common to all approaches is the understanding that novel disease-associated candidates are in close overall proximity to known disease genes. However, the relevance of these methods to the prediction of novel drug targets has not yet been assessed. Here, we present a network-based approach for the prediction of drug targets for a given disease. The method allows both repositioning drug targets known for other diseases to the given disease and the prediction of unexploited drug targets which are not used for treatment of any disease. Our approach takes as input a disease gene expression signature and a high-quality interaction network and outputs a prioritized list of drug targets. We demonstrate the high performance of our method and highlight the usefulness of the predictions in three case studies. We present novel drug targets for scleroderma and different types of cancer with their underlying biological processes. Furthermore, we demonstrate the ability of our method to identify non-suspected repositioning candidates using diabetes type 1 as an example. PMID:23593264

Fluid mechanics aspects of magnetic drug targeting.

PubMed

Odenbach, Stefan

2015-10-01

Experiments and numerical simulations using a flow phantom for magnetic drug targeting have been undertaken. The flow phantom is a half y-branched tube configuration where the main tube represents an artery from which a tumour-supplying artery, which is simulated by the side branch of the flow phantom, branches off. In the experiments a quantification of the amount of magnetic particles targeted towards the branch by a magnetic field applied via a permanent magnet is achieved by impedance measurement using sensor coils. Measuring the targeting efficiency, i.e. the relative amount of particles targeted to the side branch, for different field configurations one obtains targeting maps which combine the targeting efficiency with the magnetic force densities in characteristic points in the flow phantom. It could be shown that targeting efficiency depends strongly on the magnetic field configuration. A corresponding numerical model has been set up, which allows the simulation of targeting efficiency for variable field configuration. With this simulation good agreement of targeting efficiency with experimental data has been found. Thus, the basis has been laid for future calculations of optimal field configurations in clinical applications of magnetic drug targeting. Moreover, the numerical model allows the variation of additional parameters of the drug targeting process and thus an estimation of the influence, e.g. of the fluid properties on the targeting efficiency. Corresponding calculations have shown that the non-Newtonian behaviour of the fluid will significantly influence the targeting process, an aspect which has to be taken into account, especially recalling the fact that the viscosity of magnetic suspensions depends strongly on the magnetic field strength and the mechanical load.

Leukocytes as carriers for targeted cancer drug delivery.

PubMed

Mitchell, Michael J; King, Michael R

2015-03-01

Metastasis contributes to over 90% of cancer-related deaths. Numerous nanoparticle platforms have been developed to target and treat cancer, yet efficient delivery of these systems to the appropriate site remains challenging. Leukocytes, which share similarities to tumor cells in terms of their transport and migration through the body, are well suited to serve as carriers of drug delivery systems to target cancer sites. This review focuses on the use and functionalization of leukocytes for therapeutic targeting of metastatic cancer. Tumor cell and leukocyte extravasation, margination in the bloodstream, and migration into soft tissue are discussed, along with the potential to exploit these functional similarities to effectively deliver drugs. Current nanoparticle-based drug formulations for the treatment of cancer are reviewed, along with methods to functionalize delivery vehicles to leukocytes, either on the surface and/or within the cell. Recent progress in this area, both in vitro and in vivo, is also discussed, with a particular emphasis on targeting cancer cells in the bloodstream as a means to interrupt the metastatic process. Leukocytes interact with cancer cells both in the bloodstream and at the site of solid tumors. These interactions can be utilized to effectively deliver drugs to targeted areas, which can reduce both the amount of drug required and various nonspecific cytotoxic effects within the body. If drug delivery vehicle functionalization does not interfere with leukocyte function, this approach may be utilized to neutralize tumor cells in the bloodstream to prevent the formation of new metastases, and also to deliver drugs to metastatic sites within tissues.

Targeted delivery of drugs for liver fibrosis.

PubMed

Li, Feng; Wang, Ji-yao

2009-05-01

Liver fibrosis and its end stage disease cirrhosis are a major cause of mortality and morbidity around the world. There is no effective pharmaceutical intervention for liver fibrosis at present. Many drugs that show potent antifibrotic activities in vitro often show only minor effects in vivo because of insufficient concentrations of drugs accumulating around the target cell and their adverse effects as a result of affecting other non-target cells. Hepatic stellate cells (HSC) play a critical role in the fibrogenesis of liver, so they are the target cells of antifibrotic therapy. Several kinds of targeted delivery system that could target the receptors expressed on HSC have been designed, and have shown an attractive targeted potential in vivo. After being carried by these delivery systems, many agents showed a powerful antifibrotic effect in animal models of liver fibrosis. These targeted delivery systems provide a new pathway for the therapy of liver fibrosis. The characteristics of theses targeted carriers are reviewed in this paper.

Common pitfalls in preclinical cancer target validation.

PubMed

Kaelin, William G

2017-07-01

An alarming number of papers from laboratories nominating new cancer drug targets contain findings that cannot be reproduced by others or are simply not robust enough to justify drug discovery efforts. This problem probably has many causes, including an underappreciation of the danger of being misled by off-target effects when using pharmacological or genetic perturbants in complex biological assays. This danger is particularly acute when, as is often the case in cancer pharmacology, the biological phenotype being measured is a 'down' readout (such as decreased proliferation, decreased viability or decreased tumour growth) that could simply reflect a nonspecific loss of cellular fitness. These problems are compounded by multiple hypothesis testing, such as when candidate targets emerge from high-throughput screens that interrogate multiple targets in parallel, and by a publication and promotion system that preferentially rewards positive findings. In this Perspective, I outline some of the common pitfalls in preclinical cancer target identification and some potential approaches to mitigate them.

Mechanistic models enable the rational use of in vitro drug-target binding kinetics for better drug effects in patients.

PubMed

de Witte, Wilhelmus E A; Wong, Yin Cheong; Nederpelt, Indira; Heitman, Laura H; Danhof, Meindert; van der Graaf, Piet H; Gilissen, Ron A H J; de Lange, Elizabeth C M

2016-01-01

Drug-target binding kinetics are major determinants of the time course of drug action for several drugs, as clearly described for the irreversible binders omeprazole and aspirin. This supports the increasing interest to incorporate newly developed high-throughput assays for drug-target binding kinetics in drug discovery. A meaningful application of in vitro drug-target binding kinetics in drug discovery requires insight into the relation between in vivo drug effect and in vitro measured drug-target binding kinetics. In this review, the authors discuss both the relation between in vitro and in vivo measured binding kinetics and the relation between in vivo binding kinetics, target occupancy and effect profiles. More scientific evidence is required for the rational selection and development of drug-candidates on the basis of in vitro estimates of drug-target binding kinetics. To elucidate the value of in vitro binding kinetics measurements, it is necessary to obtain information on system-specific properties which influence the kinetics of target occupancy and drug effect. Mathematical integration of this information enables the identification of drug-specific properties which lead to optimal target occupancy and drug effect in patients.

The Expanding Diversity of Mycobacterium tuberculosis Drug Targets.

PubMed

Wellington, Samantha; Hung, Deborah T

2018-05-11

After decades of relative inactivity, a large increase in efforts to discover antitubercular therapeutics has brought insights into the biology of Mycobacterium tuberculosis (Mtb) and promising new drugs such as bedaquiline, which inhibits ATP synthase, and the nitroimidazoles delamanid and pretomanid, which inhibit both mycolic acid synthesis and energy production. Despite these advances, the drug discovery pipeline remains underpopulated. The field desperately needs compounds with novel mechanisms of action capable of inhibiting multi- and extensively drug -resistant Mtb (M/XDR-TB) and, potentially, nonreplicating Mtb with the hope of shortening the duration of required therapy. New knowledge about Mtb, along with new methods and technologies, has driven exploration into novel target areas, such as energy production and central metabolism, that diverge from the classical targets in macromolecular synthesis. Here, we review new small molecule drug candidates that act on these novel targets to highlight the methods and perspectives advancing the field. These new targets bring with them the aspiration of shortening treatment duration as well as a pipeline of effective regimens against XDR-TB, positioning Mtb drug discovery to become a model for anti-infective discovery.

Analysis of A Drug Target-based Classification System using Molecular Descriptors.

PubMed

Lu, Jing; Zhang, Pin; Bi, Yi; Luo, Xiaomin

2016-01-01

Drug-target interaction is an important topic in drug discovery and drug repositioning. KEGG database offers a drug annotation and classification using a target-based classification system. In this study, we gave an investigation on five target-based classes: (I) G protein-coupled receptors; (II) Nuclear receptors; (III) Ion channels; (IV) Enzymes; (V) Pathogens, using molecular descriptors to represent each drug compound. Two popular feature selection methods, maximum relevance minimum redundancy and incremental feature selection, were adopted to extract the important descriptors. Meanwhile, an optimal prediction model based on nearest neighbor algorithm was constructed, which got the best result in identifying drug target-based classes. Finally, some key descriptors were discussed to uncover their important roles in the identification of drug-target classes.

Glycyrrhetinic Acid-Mediated Polymeric Drug Delivery Targeting the Acidic Microenvironment of Hepatocellular Carcinoma.

PubMed

Zhang, Jinming; Zhang, Min; Ji, Juan; Fang, Xiefan; Pan, Xin; Wang, Yitao; Wu, Chuanbin; Chen, Meiwan

2015-10-01

The major hurdle of current drug carrier against hepatocellular carcinoma (HCC) is the lack of specific and selective drug delivery to HCC. In this study, a novel glycyrrhetinic acid (GA) and poly(L-Histidine) (PHIS) mediated polymeric drug delivery system was developed to target HCC that have GA binding receptors and release its encapsulated anticancer drug in the acidic microenvironment of HCC. Firstly, GA and PHIS were conjugated to form poly (ethylene glycol)-poly(lactic-co-glycolic acid) (GA-PEG-PHIS-PLGA, GA-PPP) micelles by grafting reaction between active terminal groups. Secondly, andrographolide (AGP) was encapsulated to GA-PPP to make AGP/GA-PPP using the solvent evaporation method. The pH-responsive property of AGP/GA-PPP micelles was validated by monitoring its stability and drug release behavior in different pH conditions. Furthermore, selective hepatocellular uptake of GA-PPP micelles in vitro, liver specific drug accumulation in vivo, as well as the enhanced antitumor effects of AGP/GA-PPP micelles confirmed the HCC targeting property of our novel drug delivery system. Average size of AGP/GA-PPP micelles increased significantly and the encapsulated AGP released faster in vitro at pH 5.0, while micelles keeping stable in pH 7.4. AGP/GA-PPP micelles were uptaken more efficiently by human Hep3B liver cells than that by human MDA-MB-231 breast cancer cells. GA-PPP micelles accumulated specifically in the liver and possessed long retention time in vivo. AGP/GA-PPP micelles significantly inhibited tumor growth and provided better therapeutic outcomes compared to free AGP and AGP/PEG-PLGA(AGP/PP) micelles without GA and PHIS decoration. This novel GA-PPP polymeric carrier is promising for targeted treatment of HCC.

Targeting Tumor Associated Phosphatidylserine with New Zinc Dipicolylamine-Based Drug Conjugates.

PubMed

Liu, Yu-Wei; Shia, Kak-Shan; Wu, Chien-Huang; Liu, Kuan-Liang; Yeh, Yu-Cheng; Lo, Chen-Fu; Chen, Chiung-Tong; Chen, Yun-Yu; Yeh, Teng-Kuang; Chen, Wei-Han; Jan, Jiing-Jyh; Huang, Yu-Chen; Huang, Chen-Lung; Fang, Ming-Yu; Gray, Brian D; Pak, Koon Y; Hsu, Tsu-An; Huang, Kuan-Hsun; Tsou, Lun K

2017-07-19

A series of zinc(II) dipicolylamine (ZnDPA)-based drug conjugates have been synthesized to probe the potential of phosphatidylserine (PS) as a new antigen for small molecule drug conjugate (SMDC) development. Using in vitro cytotoxicity and plasma stability studies, PS-binding assay, in vivo pharmacokinetic studies, and maximum tolerated dose profiles, we provided a roadmap and the key parameters required for the development of the ZnDPA based drug conjugate. In particular, conjugate 24 induced tumor regression in the COLO 205 xenograft model and exhibited a more potent antitumor effect with a 70% reduction of cytotoxic payload compared to that of the marketed irinotecan when dosed at the same regimen. In addition to the validation of PS as an effective pharmacodelivery target for SMDC, our work also provided the foundation that, if applicable, a variety of therapeutic agents could be conjugated in the same manner to treat other PS-associated diseases.

Leukocytes as carriers for targeted cancer drug delivery

PubMed Central

Mitchell, Michael J

2017-01-01

Introduction Metastasis contributes to over 90% of cancer-related deaths. Numerous nanoparticle platforms have been developed to target and treat cancer, yet efficient delivery of these systems to the appropriate site remains challenging. Leukocytes, which share similarities to tumor cells in terms of their transport and migration through the body, are well suited to serve as carriers of drug delivery systems to target cancer sites. Areas covered This review focuses on the use and functionalization of leukocytes for therapeutic targeting of metastatic cancer. Tumor cell and leukocyte extravasation, margination in the bloodstream, and migration into soft tissue are discussed, along with the potential to exploit these functional similarities to effectively deliver drugs. Current nanoparticle-based drug formulations for the treatment of cancer are reviewed, along with methods to functionalize delivery vehicles to leukocytes, either on the surface and/or within the cell. Recent progress in this area, both in vitro and in vivo, is also discussed, with a particular emphasis on targeting cancer cells in the bloodstream as a means to interrupt the metastatic process. Expert opinion Leukocytes interact with cancer cells both in the bloodstream and at the site of solid tumors. These interactions can be utilized to effectively deliver drugs to targeted areas, which can reduce both the amount of drug required and various nonspecific cytotoxic effects within the body. If drug delivery vehicle functionalization does not interfere with leukocyte function, this approach may be utilized to neutralize tumor cells in the bloodstream to prevent the formation of new metastases, and also to deliver drugs to metastatic sites within tissues. PMID:25270379

Leveraging 3D chemical similarity, target and phenotypic data in the identification of drug-protein and drug-adverse effect associations.

PubMed

Vilar, Santiago; Hripcsak, George

2016-01-01

Drug-target identification is crucial to discover novel applications for existing drugs and provide more insights about mechanisms of biological actions, such as adverse drug effects (ADEs). Computational methods along with the integration of current big data sources provide a useful framework for drug-target and drug-adverse effect discovery. In this article, we propose a method based on the integration of 3D chemical similarity, target and adverse effect data to generate a drug-target-adverse effect predictor along with a simple leveraging system to improve identification of drug-targets and drug-adverse effects. In the first step, we generated a system for multiple drug-target identification based on the application of 3D drug similarity into a large target dataset extracted from the ChEMBL. Next, we developed a target-adverse effect predictor combining targets from ChEMBL with phenotypic information provided by SIDER data source. Both modules were linked to generate a final predictor that establishes hypothesis about new drug-target-adverse effect candidates. Additionally, we showed that leveraging drug-target candidates with phenotypic data is very useful to improve the identification of drug-targets. The integration of phenotypic data into drug-target candidates yielded up to twofold precision improvement. In the opposite direction, leveraging drug-phenotype candidates with target data also yielded a significant enhancement in the performance. The modeling described in the current study is simple and efficient and has applications at large scale in drug repurposing and drug safety through the identification of mechanism of action of biological effects.

Low MITF/AXL ratio predicts early resistance to multiple targeted drugs in melanoma.

PubMed

Müller, Judith; Krijgsman, Oscar; Tsoi, Jennifer; Robert, Lidia; Hugo, Willy; Song, Chunying; Kong, Xiangju; Possik, Patricia A; Cornelissen-Steijger, Paulien D M; Geukes Foppen, Marnix H; Kemper, Kristel; Goding, Colin R; McDermott, Ultan; Blank, Christian; Haanen, John; Graeber, Thomas G; Ribas, Antoni; Lo, Roger S; Peeper, Daniel S

2014-12-15

Increased expression of the Microphthalmia-associated transcription factor (MITF) contributes to melanoma progression and resistance to BRAF pathway inhibition. Here we show that the lack of MITF is associated with more severe resistance to a range of inhibitors, while its presence is required for robust drug responses. Both in primary and acquired resistance, MITF levels inversely correlate with the expression of several activated receptor tyrosine kinases, most frequently AXL. The MITF-low/AXL-high/drug-resistance phenotype is common among mutant BRAF and NRAS melanoma cell lines. The dichotomous behaviour of MITF in drug response is corroborated in vemurafenib-resistant biopsies, including MITF-high and -low clones in a relapsed patient. Furthermore, drug cocktails containing AXL inhibitor enhance melanoma cell elimination by BRAF or ERK inhibition. Our results demonstrate that a low MITF/AXL ratio predicts early resistance to multiple targeted drugs, and warrant clinical validation of AXL inhibitors to combat resistance of BRAF and NRAS mutant MITF-low melanomas.

Target-Pathogen: a structural bioinformatic approach to prioritize drug targets in pathogens.

PubMed

Sosa, Ezequiel J; Burguener, Germán; Lanzarotti, Esteban; Defelipe, Lucas; Radusky, Leandro; Pardo, Agustín M; Marti, Marcelo; Turjanski, Adrián G; Fernández Do Porto, Darío

2018-01-04

Available genomic data for pathogens has created new opportunities for drug discovery and development to fight them, including new resistant and multiresistant strains. In particular structural data must be integrated with both, gene information and experimental results. In this sense, there is a lack of an online resource that allows genome wide-based data consolidation from diverse sources together with thorough bioinformatic analysis that allows easy filtering and scoring for fast target selection for drug discovery. Here, we present Target-Pathogen database (http://target.sbg.qb.fcen.uba.ar/patho), designed and developed as an online resource that allows the integration and weighting of protein information such as: function, metabolic role, off-targeting, structural properties including druggability, essentiality and omic experiments, to facilitate the identification and prioritization of candidate drug targets in pathogens. We include in the database 10 genomes of some of the most relevant microorganisms for human health (Mycobacterium tuberculosis, Mycobacterium leprae, Klebsiella pneumoniae, Plasmodium vivax, Toxoplasma gondii, Leishmania major, Wolbachia bancrofti, Trypanosoma brucei, Shigella dysenteriae and Schistosoma Smanosoni) and show its applicability. New genomes can be uploaded upon request. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Target-Pathogen: a structural bioinformatic approach to prioritize drug targets in pathogens

PubMed Central

Sosa, Ezequiel J; Burguener, Germán; Lanzarotti, Esteban; Radusky, Leandro; Pardo, Agustín M; Marti, Marcelo

2018-01-01

Abstract Available genomic data for pathogens has created new opportunities for drug discovery and development to fight them, including new resistant and multiresistant strains. In particular structural data must be integrated with both, gene information and experimental results. In this sense, there is a lack of an online resource that allows genome wide-based data consolidation from diverse sources together with thorough bioinformatic analysis that allows easy filtering and scoring for fast target selection for drug discovery. Here, we present Target-Pathogen database (http://target.sbg.qb.fcen.uba.ar/patho), designed and developed as an online resource that allows the integration and weighting of protein information such as: function, metabolic role, off-targeting, structural properties including druggability, essentiality and omic experiments, to facilitate the identification and prioritization of candidate drug targets in pathogens. We include in the database 10 genomes of some of the most relevant microorganisms for human health (Mycobacterium tuberculosis, Mycobacterium leprae, Klebsiella pneumoniae, Plasmodium vivax, Toxoplasma gondii, Leishmania major, Wolbachia bancrofti, Trypanosoma brucei, Shigella dysenteriae and Schistosoma Smanosoni) and show its applicability. New genomes can be uploaded upon request. PMID:29106651

Drug target inference through pathway analysis of genomics data

PubMed Central

Ma, Haisu; Zhao, Hongyu

2013-01-01

Statistical modeling coupled with bioinformatics is commonly used for drug discovery. Although there exist many approaches for single target based drug design and target inference, recent years have seen a paradigm shift to system-level pharmacological research. Pathway analysis of genomics data represents one promising direction for computational inference of drug targets. This article aims at providing a comprehensive review on the evolving issues is this field, covering methodological developments, their pros and cons, as well as future research directions. PMID:23369829

KCa 3.1-a microglial target ready for drug repurposing?

PubMed

Dale, Elena; Staal, Roland G W; Eder, Claudia; Möller, Thomas

2016-10-01

Over the past decade, glial cells have attracted attention for harboring unexploited targets for drug discovery. Several glial targets have attracted de novo drug discovery programs, as highlighted in this GLIA Special Issue. Drug repurposing, which has the objective of utilizing existing drugs as well as abandoned, failed, or not yet pursued clinical development candidates for new indications, might provide a faster opportunity to bring drugs for glial targets to patients with unmet needs. Here, we review the potential of the intermediate-conductance calcium-activated potassium channels KCa 3.1 as the target for such a repurposing effort. We discuss the data on KCa 3.1 expression on microglia in vitro and in vivo and review the relevant literature on the two KCa 3.1 inhibitors TRAM-34 and Senicapoc. Finally, we provide an outlook of what it might take to harness the potential of KCa 3.1 as a bona fide microglial drug target. GLIA 2016;64:1733-1741. © 2016 Wiley Periodicals, Inc.

A small molecule nanodrug consisting of amphiphilic targeting ligand-chemotherapy drug conjugate for targeted cancer therapy.

PubMed

Mou, Quanbing; Ma, Yuan; Zhu, Xinyuan; Yan, Deyue

2016-05-28

Targeted drug delivery is a broadly applicable approach for cancer therapy. However, the nanocarrier-based targeted delivery system suffers from batch-to-batch variation, quality concerns and carrier-related toxicity issues. Thus, to develop a carrier-free targeted delivery system with nanoscale characteristics is very attractive. Here, a novel targeting small molecule nanodrug self-delivery system consisting of targeting ligand and chemotherapy drug was constructed, which combined the advantages of small molecules and nano-assemblies together and showed excellent targeting ability and long blood circulation time with well-defined structure, high drug loading ratio and on-demand drug release behavior. As a proof-of-concept, lactose (Lac) and doxorubicin (DOX) were chosen as the targeting ligand and chemotherapy drug, respectively. Lac and DOX were conjugated through a pH-responsive hydrazone group. For its intrinsic amphiphilic property, Lac-DOX conjugate could self-assemble into nanoparticles in water. Both in vitro and in vivo assays indicated that Lac-DOX nanoparticles exhibited enhanced anticancer activity and weak side effects. This novel active targeting nanodrug delivery system shows great potential in cancer therapy. Copyright © 2016 Elsevier B.V. All rights reserved.

Design and characterization of ebolavirus GP prehairpin intermediate mimics as drug targets

PubMed Central

Clinton, Tracy R; Weinstock, Matthew T; Jacobsen, Michael T; Szabo-Fresnais, Nicolas; Pandya, Maya J; Whitby, Frank G; Herbert, Andrew S; Prugar, Laura I; McKinnon, Rena; Hill, Christopher P; Welch, Brett D; Dye, John M; Eckert, Debra M; Kay, Michael S

2015-01-01

Ebolaviruses are highly lethal filoviruses that cause hemorrhagic fever in humans and nonhuman primates. With no approved treatments or preventatives, the development of an anti-ebolavirus therapy to protect against natural infections and potential weaponization is an urgent global health need. Here, we describe the design, biophysical characterization, and validation of peptide mimics of the ebolavirus N-trimer, a highly conserved region of the GP2 fusion protein, to be used as targets to develop broad-spectrum inhibitors of ebolavirus entry. The N-trimer region of GP2 is 90% identical across all ebolavirus species and forms a critical part of the prehairpin intermediate that is exposed during viral entry. Specifically, we fused designed coiled coils to the N-trimer to present it as a soluble trimeric coiled coil as it appears during membrane fusion. Circular dichroism, sedimentation equilibrium, and X-ray crystallography analyses reveal the helical, trimeric structure of the designed N-trimer mimic targets. Surface plasmon resonance studies validate that the N-trimer mimic binds its native ligand, the C-peptide region of GP2. The longest N-trimer mimic also inhibits virus entry, thereby confirming binding of the C-peptide region during viral entry and the presence of a vulnerable prehairpin intermediate. Using phage display as a model system, we validate the suitability of the N-trimer mimics as drug screening targets. Finally, we describe the foundational work to use the N-trimer mimics as targets in mirror-image phage display, which will be used to identify d-peptide inhibitors of ebolavirus entry. PMID:25287718

Design and characterization of ebolavirus GP prehairpin intermediate mimics as drug targets.

PubMed

Clinton, Tracy R; Weinstock, Matthew T; Jacobsen, Michael T; Szabo-Fresnais, Nicolas; Pandya, Maya J; Whitby, Frank G; Herbert, Andrew S; Prugar, Laura I; McKinnon, Rena; Hill, Christopher P; Welch, Brett D; Dye, John M; Eckert, Debra M; Kay, Michael S

2015-04-01

Ebolaviruses are highly lethal filoviruses that cause hemorrhagic fever in humans and nonhuman primates. With no approved treatments or preventatives, the development of an anti-ebolavirus therapy to protect against natural infections and potential weaponization is an urgent global health need. Here, we describe the design, biophysical characterization, and validation of peptide mimics of the ebolavirus N-trimer, a highly conserved region of the GP2 fusion protein, to be used as targets to develop broad-spectrum inhibitors of ebolavirus entry. The N-trimer region of GP2 is 90% identical across all ebolavirus species and forms a critical part of the prehairpin intermediate that is exposed during viral entry. Specifically, we fused designed coiled coils to the N-trimer to present it as a soluble trimeric coiled coil as it appears during membrane fusion. Circular dichroism, sedimentation equilibrium, and X-ray crystallography analyses reveal the helical, trimeric structure of the designed N-trimer mimic targets. Surface plasmon resonance studies validate that the N-trimer mimic binds its native ligand, the C-peptide region of GP2. The longest N-trimer mimic also inhibits virus entry, thereby confirming binding of the C-peptide region during viral entry and the presence of a vulnerable prehairpin intermediate. Using phage display as a model system, we validate the suitability of the N-trimer mimics as drug screening targets. Finally, we describe the foundational work to use the N-trimer mimics as targets in mirror-image phage display, which will be used to identify D-peptide inhibitors of ebolavirus entry. © 2014 The Protein Society.

Trends in GPCR drug discovery: new agents, targets and indications.

PubMed

Hauser, Alexander S; Attwood, Misty M; Rask-Andersen, Mathias; Schiöth, Helgi B; Gloriam, David E

2017-12-01

G protein-coupled receptors (GPCRs) are the most intensively studied drug targets, mostly due to their substantial involvement in human pathophysiology and their pharmacological tractability. Here, we report an up-to-date analysis of all GPCR drugs and agents in clinical trials, which reveals current trends across molecule types, drug targets and therapeutic indications, including showing that 475 drugs (~34% of all drugs approved by the US Food and Drug Administration (FDA)) act at 108 unique GPCRs. Approximately 321 agents are currently in clinical trials, of which ~20% target 66 potentially novel GPCR targets without an approved drug, and the number of biological drugs, allosteric modulators and biased agonists has increased. The major disease indications for GPCR modulators show a shift towards diabetes, obesity and Alzheimer disease, although several central nervous system disorders are also highly represented. The 224 (56%) non-olfactory GPCRs that have not yet been explored in clinical trials have broad untapped therapeutic potential, particularly in genetic and immune system disorders. Finally, we provide an interactive online resource to analyse and infer trends in GPCR drug discovery.

NCI-MATCH Trial Links Targeted Drugs to Mutations

Cancer.gov

Investigators for the nationwide trial, NCI-MATCH: Molecular Analysis for Therapy Choice, announced that the trial will seek to determine whether targeted therapies for people whose tumors have specific gene mutations will be effective regardless of their cancer type. NCI-MATCH will incorporate more than 20 different study drugs or drug combinations, each targeting a specific gene mutation, in order to match each patient in the trial with a therapy that targets a molecular abnormality in their tumor.

A combined pre-clinical meta-analysis and randomized confirmatory trial approach to improve data validity for therapeutic target validation.

PubMed

Kleikers, Pamela W M; Hooijmans, Carlijn; Göb, Eva; Langhauser, Friederike; Rewell, Sarah S J; Radermacher, Kim; Ritskes-Hoitinga, Merel; Howells, David W; Kleinschnitz, Christoph; Schmidt, Harald H H W

2015-08-27

Biomedical research suffers from a dramatically poor translational success. For example, in ischemic stroke, a condition with a high medical need, over a thousand experimental drug targets were unsuccessful. Here, we adopt methods from clinical research for a late-stage pre-clinical meta-analysis (MA) and randomized confirmatory trial (pRCT) approach. A profound body of literature suggests NOX2 to be a major therapeutic target in stroke. Systematic review and MA of all available NOX2(-/y) studies revealed a positive publication bias and lack of statistical power to detect a relevant reduction in infarct size. A fully powered multi-center pRCT rejects NOX2 as a target to improve neurofunctional outcomes or achieve a translationally relevant infarct size reduction. Thus stringent statistical thresholds, reporting negative data and a MA-pRCT approach can ensure biomedical data validity and overcome risks of bias.

Drug-target residence time--a case for G protein-coupled receptors.

PubMed

Guo, Dong; Hillger, Julia M; IJzerman, Adriaan P; Heitman, Laura H

2014-07-01

A vast number of marketed drugs act on G protein-coupled receptors (GPCRs), the most successful category of drug targets to date. These drugs usually possess high target affinity and selectivity, and such combined features have been the driving force in the early phases of drug discovery. However, attrition has also been high. Many investigational new drugs eventually fail in clinical trials due to a demonstrated lack of efficacy. A retrospective assessment of successfully launched drugs revealed that their beneficial effects in patients may be attributed to their long drug-target residence times (RTs). Likewise, for some other GPCR drugs short RT could be beneficial to reduce the potential for on-target side effects. Hence, the compounds' kinetics behavior might in fact be the guiding principle to obtain a desired and durable effect in vivo. We therefore propose that drug-target RT should be taken into account as an additional parameter in the lead selection and optimization process. This should ultimately lead to an increased number of candidate drugs moving to the preclinical development phase and on to the market. This review contains examples of the kinetics behavior of GPCR ligands with improved in vivo efficacy and summarizes methods for assessing drug-target RT. © 2014 Wiley Periodicals, Inc.

Structural systems pharmacology: a new frontier in discovering novel drug targets.

PubMed

Tan, Hepan; Ge, Xiaoxia; Xie, Lei

2013-08-01

The modern target-based drug discovery process, characterized by the one-drug-one-gene paradigm, has been of limited success. In contrast, phenotype-based screening produces thousands of active compounds but gives no hint as to what their molecular targets are or which ones merit further research. This presents a question: What is a suitable target for an efficient and safe drug? In this paper, we argue that target selection should take into account the proteome-wide energetic and kinetic landscape of drug-target interactions, as well as their cellular and organismal consequences. We propose a new paradigm of structural systems pharmacology to deconvolute the molecular targets of successful drugs as well as to identify druggable targets and their drug-like binders. Here we face two major challenges in structural systems pharmacology: How do we characterize and analyze the structural and energetic origins of drug-target interactions on a proteome scale? How do we correlate the dynamic molecular interactions to their in vivo activity? We will review recent advances in developing new computational tools for biophysics, bioinformatics, chemoinformatics, and systems biology related to the identification of genome-wide target profiles. We believe that the integration of these tools will realize structural systems pharmacology, enabling us to both efficiently develop effective therapeutics for complex diseases and combat drug resistance.

Market uptake of biologic and small-molecule--targeted oncology drugs in Europe.

PubMed

Obradovic, Marko; Mrhar, Ales; Kos, Mitja

2009-12-01

The aim of this study was to investigate the market uptake of biologic and small-molecule-targeted oncology drugs in Europe. Targeted oncology drugs that were used in one of the selected European countries before the end of 2007 were eligible for inclusion in the analysis. The following European countries were included: Austria, Croatia, France, Germany, Hungary, Italy, Slovenia, and the United Kingdom. Monetary market uptake of targeted oncology drugs was assessed by using sales data (in euros) obtained from 2 large data- bases for the period 1997-2007. Market uptake was assessed in terms of expenditures for specific drugs in euros per capita and in market shares. The monetary market uptake of targeted oncology drugs had an exponential growth from 1997 to 2007 in all comparison countries and reached 40% of the total oncology drug market in 2007. Although the various European countries allocate substantially different amounts of resources per capita for oncology drugs, the share of expenditures attributed to targeted oncology drugs did not differ substantially among the countries. Biologic molecules were used in clinical practice before the small-molecule-targeted oncology drugs. Targeted oncology drugs that were introduced first to clinical practice in most of the comparison countries (ie, rituximab, trastuzumab, imatinib mesylate) maintained the leading positions on the market throughout the period of the analysis. In 2007, approximately 25% of all expenditures for oncology drugs were attributed to biologic oncology drugs, and approximately 15% were spent on small-molecule-targeted oncology drugs. Expenditures on targeted oncology drugs have been increasing exponentially in Europe throughout the past decade and have reached a 40% share of the oncology drug market. As of 2007, the market share of biologic oncology drugs was higher than the market share of small-molecule-targeted oncology drugs. Copyright 2009 Excerpta Medica Inc. All rights reserved.

Prediction of Drug-Target Interaction Networks from the Integration of Protein Sequences and Drug Chemical Structures.

PubMed

Meng, Fan-Rong; You, Zhu-Hong; Chen, Xing; Zhou, Yong; An, Ji-Yong

2017-07-05

Knowledge of drug-target interaction (DTI) plays an important role in discovering new drug candidates. Unfortunately, there are unavoidable shortcomings; including the time-consuming and expensive nature of the experimental method to predict DTI. Therefore, it motivates us to develop an effective computational method to predict DTI based on protein sequence. In the paper, we proposed a novel computational approach based on protein sequence, namely PDTPS (Predicting Drug Targets with Protein Sequence) to predict DTI. The PDTPS method combines Bi-gram probabilities (BIGP), Position Specific Scoring Matrix (PSSM), and Principal Component Analysis (PCA) with Relevance Vector Machine (RVM). In order to evaluate the prediction capacity of the PDTPS, the experiment was carried out on enzyme, ion channel, GPCR, and nuclear receptor datasets by using five-fold cross-validation tests. The proposed PDTPS method achieved average accuracy of 97.73%, 93.12%, 86.78%, and 87.78% on enzyme, ion channel, GPCR and nuclear receptor datasets, respectively. The experimental results showed that our method has good prediction performance. Furthermore, in order to further evaluate the prediction performance of the proposed PDTPS method, we compared it with the state-of-the-art support vector machine (SVM) classifier on enzyme and ion channel datasets, and other exiting methods on four datasets. The promising comparison results further demonstrate that the efficiency and robust of the proposed PDTPS method. This makes it a useful tool and suitable for predicting DTI, as well as other bioinformatics tasks.

Targeted Vascular Drug Delivery in Cerebral Cancer.

PubMed

Humle, Nanna; Johnsen, Kasper Bendix; Arendt, Gitte Abildgaard; Nielsen, Rikke Paludan; Moos, Torben; Thomsen, Louiza Bohn

2016-01-01

This review presents the present-day literature on the anatomy and physiological mechanisms of the blood-brain barrier and the problematic of cerebral drug delivery in relation to malignant brain tumors. First step in treatment of malignant brain tumors is resection, but there is a high risk of single remnant infiltrative tumor cells in the outer zone of the brain tumor. These infiltrative single-cells will be supplied by capillaries with an intact BBB as opposed to the partly leaky BBB found in the tumor tissue before resection. Even though BBB penetrance of a chemotherapeutic agent is considered irrelevant though the limited success rate for chemotherapeutic treatability of GBM tumors indicate otherwise. Therefore drug delivery strategies to cerebral cancer after resection should be tailored to being able to both penetrate the intact BBB and target the cancer cells. In this review the intact bloodbrain barrier and cerebral cancer with main focus on glioblastoma multiforme (GBM) is introduced. The GBM induced formation of a blood-tumor barrier and the consequences hereof is described and discussed with emphasis on the impact these changes of the BBB has on drug delivery to GBM. The most commonly used drug carriers for drug delivery to GBM is described and the current drug delivery strategies for glioblastoma multiforme including possible routes through the BBB and epitopes, which can be targeted on the GBM cells is outlined. Overall, this review aims to address targeted drug delivery in GBM treatment when taking the differing permeability of the BBB into consideration.

Recommendation Techniques for Drug-Target Interaction Prediction and Drug Repositioning.

PubMed

Alaimo, Salvatore; Giugno, Rosalba; Pulvirenti, Alfredo

2016-01-01

The usage of computational methods in drug discovery is a common practice. More recently, by exploiting the wealth of biological knowledge bases, a novel approach called drug repositioning has raised. Several computational methods are available, and these try to make a high-level integration of all the knowledge in order to discover unknown mechanisms. In this chapter, we review drug-target interaction prediction methods based on a recommendation system. We also give some extensions which go beyond the bipartite network case.

Development In Drug Targeting And Delivery In Cervical Cancer.

PubMed

Aggarwal, Urvashi; Goyal, Amit Kumar; Rath, Goutam

2017-10-09

Cervical cancer is the second most common cancer in women. Standard treatment options available for cervical cancer including chemotherapy, surgery and radiation therapy associated with their own side effects and toxicities. Tumor-targeted delivery of anticancer drugs is perhaps one of the most appropriate strategies to achieve optimal outcomes from treatment and improve quality of life. Recently nanocarriers based drug delivery systems owing to their unique properties have been extensively investigated for anticancer drug delivery. In addition to that addressing the anatomical significance of cervical cancer, various local drug delivery strategies for the cancer treatment are introduced like: gels, nanoparticles, polymeric films, rods and wafers, lipid based nanocarrier. Localized drug delivery systems allows passive drug targeting results in high drug concentration at the target site. Further they can be tailor made to achieve both sustained and controlled release behavior, substantially improving therapeutic outcomes and minimizing side effects. This review summarizes the meaningful advances in drug delivery strategies to treat cervical cancer. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Fe₃O₄ Nanoparticles in Targeted Drug/Gene Delivery Systems.

PubMed

Shen, Lazhen; Li, Bei; Qiao, Yongsheng

2018-02-23

Fe₃O₄ nanoparticles (NPs), the most traditional magnetic nanoparticles, have received a great deal of attention in the biomedical field, especially for targeted drug/gene delivery systems, due to their outstanding magnetism, biocompatibility, lower toxicity, biodegradability, and other features. Naked Fe₃O₄ NPs are easy to aggregate and oxidize, and thus are often made with various coatings to realize superior properties for targeted drug/gene delivery. In this review, we first list the three commonly utilized synthesis methods of Fe₃O₄ NPs, and their advantages and disadvantages. In the second part, we describe coating materials that exhibit noticeable features that allow functionalization of Fe₃O₄ NPs and summarize their methods of drug targeting/gene delivery. Then our efforts will be devoted to the research status and progress of several different functionalized Fe₃O₄ NP delivery systems loaded with chemotherapeutic agents, and we present targeted gene transitive carriers in detail. In the following section, we illuminate the most effective treatment systems of the combined drug and gene therapy. Finally, we propose opportunities and challenges of the clinical transformation of Fe₃O₄ NPs targeting drug/gene delivery systems.

Validity of Integrity Tests for Predicting Drug and Alcohol Abuse

DTIC Science & Technology

1993-08-31

Wiinkler and Sheridan (1989) found that employees who entered employee assistance programs for treating drug addiction were more likely be absent...August 31, 1993 Final 4. TITLE AND SUBTITLE S. FUNDING NUMBERS Validity of Integrity Tests for Predicting Drug and Alcohol Abuse C No. N00014-92-J...words) This research used psychometric meta-analysis (Hunter & Schmidt, 1990b) to examine the validity of integrity tests for predicting drug and

Graphene quantum dots for cancer targeted drug delivery.

PubMed

Iannazzo, Daniela; Pistone, Alessandro; Salamò, Marina; Galvagno, Signorino; Romeo, Roberto; Giofré, Salvatore V; Branca, Caterina; Visalli, Giuseppa; Di Pietro, Angela

2017-02-25

A biocompatible and cell traceable drug delivery system Graphene Quantum Dots (GQD) based, for the targeted delivery of the DNA intercalating drug doxorubicin (DOX) to cancer cells, is here reported. Highly dispersible and water soluble GQD, synthesized by acidic oxidation and exfoliation of multi-walled carbon nanotubes (MWCNT), were covalently linked to the tumor targeting module biotin (BTN), able to efficiently recognize biotin receptors over-expressed on cancer cells and loaded with DOX. Biological test performed on A549 cells reported a very low toxicity of the synthesized carrier (GQD and GQD-BTN). In GQD-BTN-DOX treated cancer cells, the cytotoxicity was strongly dependent from cell uptake which was greater and delayed after treatment with GQD-BTN-DOX system with respect to what observed for cells treated with the same system lacking of the targeting module BTN (GQD-DOX) or with the free drug alone. A delayed nuclear internalization of the drug is reported, due to the drug detachment from the nanosystem, triggered by the acidic environment of cancer cells. Copyright © 2017 Elsevier B.V. All rights reserved.

Increasing the Structural Coverage of Tuberculosis Drug Targets

PubMed Central

Baugh, Loren; Phan, Isabelle; Begley, Darren W.; Clifton, Matthew C.; Armour, Brianna; Dranow, David M.; Taylor, Brandy M.; Muruthi, Marvin M.; Abendroth, Jan; Fairman, James W.; Fox, David; Dieterich, Shellie H.; Staker, Bart L.; Gardberg, Anna S.; Choi, Ryan; Hewitt, Stephen N.; Napuli, Alberto J.; Myers, Janette; Barrett, Lynn K.; Zhang, Yang; Ferrell, Micah; Mundt, Elizabeth; Thompkins, Katie; Tran, Ngoc; Lyons-Abbott, Sally; Abramov, Ariel; Sekar, Aarthi; Serbzhinskiy, Dmitri; Lorimer, Don; Buchko, Garry W.; Stacy, Robin; Stewart, Lance J.; Edwards, Thomas E.; Van Voorhis, Wesley C.; Myler, Peter J.

2015-01-01

High-resolution three-dimensional structures of essential Mycobacterium tuberculosis (Mtb) proteins provide templates for TB drug design, but are available for only a small fraction of the Mtb proteome. Here we evaluate an intra-genus “homolog-rescue” strategy to increase the structural information available for TB drug discovery by using mycobacterial homologs with conserved active sites. Of 179 potential TB drug targets selected for x-ray structure determination, only 16 yielded a crystal structure. By adding 1675 homologs from nine other mycobacterial species to the pipeline, structures representing an additional 52 otherwise intractable targets were solved. To determine whether these homolog structures would be useful surrogates in TB drug design, we compared the active sites of 106 pairs of Mtb and non-TB mycobacterial (NTM) enzyme homologs with experimentally determined structures, using three metrics of active site similarity, including superposition of continuous pharmacophoric property distributions. Pair-wise structural comparisons revealed that 19/22 pairs with >55% overall sequence identity had active site Cα RMSD <1Å, >85% side chain identity, and ≥80% PSAPF (similarity based on pharmacophoric properties) indicating highly conserved active site shape and chemistry. Applying these results to the 52 NTM structures described above, 41 shared >55% sequence identity with the Mtb target, thus increasing the effective structural coverage of the 179 Mtb targets over three-fold (from 9% to 32%). The utility of these structures in TB drug design can be tested by designing inhibitors using the homolog structure and assaying the cognate Mtb enzyme; a promising test case, Mtb cytidylate kinase, is described. The homolog-rescue strategy evaluated here for TB is also generalizable to drug targets for other diseases. PMID:25613812

Modulation of Epigenetic Targets for Anticancer Therapy: Clinicopathological Relevance, Structural Data and Drug Discovery Perspectives

PubMed Central

Andreol, Federico; Barbosa, Arménio Jorge Moura; Daniele Parenti, Marco; Rio, Alberto Del

2013-01-01

Research on cancer epigenetics has flourished in the last decade. Nevertheless growing evidence point on the importance to understand the mechanisms by which epigenetic changes regulate the genesis and progression of cancer growth. Several epigenetic targets have been discovered and are currently under validation for new anticancer therapies. Drug discovery approaches aiming to target these epigenetic enzymes with small-molecules inhibitors have produced the first pre-clinical and clinical outcomes and many other compounds are now entering the pipeline as new candidate epidrugs. The most studied targets can be ascribed to histone deacetylases and DNA methyltransferases, although several other classes of enzymes are able to operate post-translational modifications to histone tails are also likely to represent new frontiers for therapeutic interventions. By acknowledging that the field of cancer epigenetics is evolving with an impressive rate of new findings, with this review we aim to provide a current overview of pre-clinical applications of small-molecules for cancer pathologies, combining them with the current knowledge of epigenetic targets in terms of available structural data and drug design perspectives. PMID:23016851

Hierarchical pulmonary target nanoparticles via inhaled administration for anticancer drug delivery.

PubMed

Chen, Rui; Xu, Liu; Fan, Qin; Li, Man; Wang, Jingjing; Wu, Li; Li, Weidong; Duan, Jinao; Chen, Zhipeng

2017-11-01

Inhalation administration, compared with intravenous administration, significantly enhances chemotherapeutic drug exposure to the lung tissue and may increase the therapeutic effect for pulmonary anticancer. However, further identification of cancer cells after lung deposition of inhaled drugs is necessary to avoid side effects on normal lung tissue and to maximize drug efficacy. Moreover, as the action site of the major drug was intracellular organelles, drug target to the specific organelle is the final key for accurate drug delivery. Here, we designed a novel multifunctional nanoparticles (MNPs) for pulmonary antitumor and the material was well-designed for hierarchical target involved lung tissue target, cancer cell target, and mitochondrial target. The biodistribution in vivo determined by UHPLC-MS/MS method was employed to verify the drug concentration overwhelmingly increasing in lung tissue through inhaled administration compared with intravenous administration. Cellular uptake assay using A549 cells proved the efficient receptor-mediated cell endocytosis. Confocal laser scanning microscopy observation showed the location of MNPs in cells was mitochondria. All results confirmed the intelligent material can progressively play hierarchical target functions, which could induce more cell apoptosis related to mitochondrial damage. It provides a smart and efficient nanocarrier platform for hierarchical targeting of pulmonary anticancer drug. So far, this kind of material for pulmonary mitochondrial-target has not been seen in other reports.

Drug effects on drug targets: inhibition of enzymes by neuroleptics, antimycotics, antibiotics and other drugs on human pathogenic amoebas and their anti-proliferative effects.

PubMed

Ondarza, Raúl N

2007-11-01

This paper reviews the inhibition of various enzymes by neuroleptics, anti-mycotics, antibiotics and other drugs on three species of human pathogenic amoebas, mainly Entamoeba histolytica, Acanthamoeba polyphaga and Naegleria fowleri, and their antiproliferative effects. A recent patent registered by Philip relates to the combination of an antibacterial formulation and antifungal agent for producing a therapeutically effective quantity of an antimicrobial that is suitable for suppressing or treating fungal growth. The rationale behind this patent focused on essential and valid targets with a description of the main pathogenic characteristics of these amoebas. The study of new targets, such as trypanothione and trypanothione reductase, and the drug effects of selected agents were arranged into six main groups: A) Inhibition of disulfide reducing enzymes by neuroleptics, antimycotics and antibiotics; B) Comparative evaluation of the efficacies of several drugs with antiproliferative activities; C) Inhibition of the enzymes for the synthesis of trypanothione, such as ornithine decarboxylase, spermidine synthase and trypanothione synthetase; D) Inhibition of the glycolytic enzyme PPi-dependent phosphofructokinase (PFK) from Entamoeba and Naegleria by pyrophosphate analogues, different from the host enzyme; E) Inhibition of enzymes secreted by these parasites to invade the human host, for example cysteine proteinases; and F) Inhibition of encystment pathways and cyst-wall assembly proteins.

Molecular targets for flavivirus drug discovery

PubMed Central

Sampath, Aruna; Padmanabhan, R.

2009-01-01

Flaviviruses are a major cause of infectious disease in humans. Dengue virus causes an estimated 50 million cases of febrile illness each year, including an increasing number of cases of hemorrhagic fever. West Nile virus, which recently spread from the Mediterranean basin to the Western Hemisphere, now causes thousands of sporadic cases of encephalitis annually. Despite the existence of licensed vaccines, yellow fever, Japanese encephalitis and tick-borne encephalitis also claim many thousands of victims each year across their vast endemic areas. Antiviral therapy could potentially reduce morbidity and mortality from flavivirus infections, but no effective drugs are currently available. This article introduces a collection of papers in Antiviral Research on molecular targets for flavivirus antiviral drug design and murine models of dengue virus disease that aims to encourage drug development efforts. After reviewing the flavivirus replication cycle, we discuss the envelope glycoprotein, NS3 protease, NS3 helicase, NS5 methyltransferase and NS5 RNA-dependent RNA polymerase as potential drug targets, with special attention being given to the viral protease. The other viral proteins are the subject of individual articles in the journal. Together, these papers highlight current status of drug discovery efforts for flavivirus diseases and suggest promising areas for further research. PMID:18796313

10 CFR 26.139 - Reporting initial validity and drug test results.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 10 Energy 1 2014-01-01 2014-01-01 false Reporting initial validity and drug test results. 26.139... § 26.139 Reporting initial validity and drug test results. (a) The licensee testing facility shall... permitted under § 26.75(h), positive test results from initial drug tests at the licensee testing facility...

10 CFR 26.139 - Reporting initial validity and drug test results.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 10 Energy 1 2012-01-01 2012-01-01 false Reporting initial validity and drug test results. 26.139... § 26.139 Reporting initial validity and drug test results. (a) The licensee testing facility shall... permitted under § 26.75(h), positive test results from initial drug tests at the licensee testing facility...

Validated MicroRNA Target Databases: An Evaluation.

PubMed

Lee, Yun Ji Diana; Kim, Veronica; Muth, Dillon C; Witwer, Kenneth W

2015-11-01

Preclinical Research Positive findings from preclinical and clinical studies involving depletion or supplementation of microRNA (miRNA) engender optimism about miRNA-based therapeutics. However, off-target effects must be considered. Predicting these effects is complicated. Each miRNA may target many gene transcripts, and the rules governing imperfectly complementary miRNA: target interactions are incompletely understood. Several databases provide lists of the relatively small number of experimentally confirmed miRNA: target pairs. Although incomplete, this information might allow assessment of at least some of the off-target effects. We evaluated the performance of four databases of experimentally validated miRNA: target interactions (miRWalk 2.0, miRTarBase, miRecords, and TarBase 7.0) using a list of 50 alphabetically consecutive genes. We examined the provided citations to determine the degree to which each interaction was experimentally supported. To assess stability, we tested at the beginning and end of a five-month period. Results varied widely by database. Two of the databases changed significantly over the course of 5 months. Most reported evidence for miRNA: target interactions were indirect or otherwise weak, and relatively few interactions were supported by more than one publication. Some returned results appear to arise from simplistic text searches that offer no insight into the relationship of the search terms, may not even include the reported gene or miRNA, and may thus, be invalid. We conclude that validation databases provide important information, but not all information in all extant databases is up-to-date or accurate. Nevertheless, the more comprehensive validation databases may provide useful starting points for investigation of off-target effects of proposed small RNA therapies. © 2015 Wiley Periodicals, Inc.

Polysaccharide-based micro/nanocarriers for oral colon-targeted drug delivery.

PubMed

Zhang, Lin; Sang, Yuan; Feng, Jing; Li, Zhaoming; Zhao, Aili

2016-08-01

Oral colon-targeted drug delivery has attracted many researchers because of its distinct advantages of increasing the bioavailability of the drug at the target site and reducing the side effects. Polysaccharides that are precisely activated by the physiological environment of the colon hold greater promise for colon targeting. Considerable research efforts have been directed towards developing polysaccharide-based micro/nanocarriers. Types of polysaccharides for colon targeting and in vitro/in vivo assessments of polysaccharide-based carriers for oral colon-targeted drug delivery are summarised. Polysaccharide-based microspheres have gained increased importance not just for the delivery of the drugs for the treatment of local diseases associated with the colon (colon cancer, inflammatory bowel disease (IBD), amoebiasis and irritable bowel syndrome (IBS)), but also for it's potential for the delivery of anti-rheumatoid arthritis and anti-chronic stable angina drugs. Besides, Polysaccharide-based micro/nanocarriers such as microbeads, microcapsules, microparticles, nanoparticles, nanogels and nanospheres are also introduced in this review.

In vivo characteristics of targeted drug-carrying filamentous bacteriophage nanomedicines

PubMed Central

2011-01-01

Background Targeted drug-carrying phage nanomedicines are a new class of nanomedicines that combines biological and chemical components into a modular nanometric drug delivery system. The core of the system is a filamentous phage particle that is produced in the bacterial host Escherichia coli. Target specificity is provided by a targeting moiety, usually an antibody that is displayed on the tip of the phage particle. A large drug payload is chemically conjugated to the protein coat of the phage via a chemically or genetically engineered linker that provides for controlled release of the drug after the particle homed to the target cell. Recently we have shown that targeted drug-carrying phage nanomedicines can be used to eradicate pathogenic bacteria and cultured tumor cells with great potentiation over the activity of the free untargeted drug. We have also shown that poorly water soluble drugs can be efficiently conjugated to the phage coat by applying hydrophilic aminoglycosides as branched solubility-enhancing linkers. Results With an intention to move to animal experimentation of efficacy, we tested anti-bacterial drug-carrying phage nanomedicines for toxicity and immunogenicity and blood pharmacokinetics upon injection into mice. Here we show that anti-bacterial drug-carrying phage nanomedicines that carry the antibiotic chloramphenicol conjugated via an aminoglycoside linker are non-toxic to mice and are greatly reduced in immunogenicity in comparison to native phage particles or particles to which the drug is conjugated directly and are cleared from the blood more slowly in comparison to native phage particles. Conclusion Our results suggest that aminoglycosides may serve as branched solubility enhancing linkers for drug conjugation that also provide for a better safety profile of the targeted nanomedicine. PMID:22185583

Chemical signatures and new drug targets for gametocytocidal drug development

NASA Astrophysics Data System (ADS)

Sun, Wei; Tanaka, Takeshi Q.; Magle, Crystal T.; Huang, Wenwei; Southall, Noel; Huang, Ruili; Dehdashti, Seameen J.; McKew, John C.; Williamson, Kim C.; Zheng, Wei

2014-01-01

Control of parasite transmission is critical for the eradication of malaria. However, most antimalarial drugs are not active against P. falciparum gametocytes, responsible for the spread of malaria. Consequently, patients can remain infectious for weeks after the clearance of asexual parasites and clinical symptoms. Here we report the identification of 27 potent gametocytocidal compounds (IC50 < 1 μM) from screening 5,215 known drugs and compounds. All these compounds were active against three strains of gametocytes with different drug sensitivities and geographical origins, 3D7, HB3 and Dd2. Cheminformatic analysis revealed chemical signatures for P. falciparum sexual and asexual stages indicative of druggability and suggesting potential targets. Torin 2, a top lead compound (IC50 = 8 nM against gametocytes in vitro), completely blocked oocyst formation in a mouse model of transmission. These results provide critical new leads and potential targets to expand the repertoire of malaria transmission-blocking reagents.

Targeted cancer drug delivery with aptamer-functionalized polymeric nanoparticles.

PubMed

Zununi Vahed, Sepideh; Fathi, Nazanin; Samiei, Mohammad; Maleki Dizaj, Solmaz; Sharifi, Simin

2018-06-21

Based on exceptional advantages of aptamers, increasing attention has been presented in the utilize of them as targeted ligands for cancer drug delivery. Recently, the progress of aptamer- targeted nanoparticles has presented new therapeutic systems for several types of cancer with decreased toxicity and improved efficacy. We highlight some of the promising formulations of aptamer-conjugated polymeric nanoparticles for specific targeted drug delivery to cancer cells. This review paper focuses on the current progresses in the use of the novel strategies to aptamer-targeted drug delivery for chemotherapy. An extensive literature review was performed using internet database, mainly PubMed based on MeSH keywords. The searches included full-text publications written in English without any limitation in date. The abstracts, reviews, books as well as studies without obvious relating of aptamers as targeted ligands for cancer drug delivery were excluded from the study. The reviewed literature revealed that aptamers with ability to modify and conjugate to various molecules can be used as targeted cancer therapy agents. However, development of aptamers unique to each individual's tumor to the development of personalized medicine seems to be needed.

The target invites a foe: antibody-drug conjugates in gynecologic oncology.

PubMed

Campos, Maira P; Konecny, Gottfried E

2018-02-01

Antibody-drug conjugates (ADCs) represent a promising new class of cancer therapeutics. Currently more than 60 ADCs are in clinical development, however, only very few trials focus on gynecologic malignancies. In this review, we summarize the most recent advances in ADC drug development with an emphasis on how this progress relates to patients diagnosed with gynecologic malignancies and breast cancer. The cytotoxic payloads of the majority of the ADCs that are currently in clinical trials for gynecologic malignancies or breast cancer are auristatins (MMAE, MMAF), maytansinoids (DM1, DM4), calicheamicin, pyrrolobenzodiazepines and SN-38. Both cleavable and noncleavable linkers are currently being investigated in clinical trials. A number of novel target antigens are currently being validated in ongoing clinical trials including folate receptor alpha, mesothelin, CA-125, NaPi2b, NOTCH3, protein tyrosine kinase-like 7, ephrin-A4, TROP2, CEACAM5, and LAMP1. For most ADCs currently in clinical development, dose-limiting toxicities appear to be unrelated to the targeted antigen but more tightly associated with the payload. Rational drug design involving optimization of the antibody, the linker and the conjugation chemistry is aimed at improving the therapeutic index of new ADCs. Antibody-drug conjugates can increase the efficacy and decrease the toxicity of their payloads in comparison with traditional cyctotoxic agents. A better and quicker translation of recent scientific advances in the field of ADCs into rational clinical trials for patients diagnosed with ovarian, endometrial or cervical cancer could create real improvements in tumor response, survival and quality of life for our patients.

Targeted drug delivery using genetically engineered diatom biosilica.

PubMed

Delalat, Bahman; Sheppard, Vonda C; Rasi Ghaemi, Soraya; Rao, Shasha; Prestidge, Clive A; McPhee, Gordon; Rogers, Mary-Louise; Donoghue, Jacqueline F; Pillay, Vinochani; Johns, Terrance G; Kröger, Nils; Voelcker, Nicolas H

2015-11-10

The ability to selectively kill cancerous cell populations while leaving healthy cells unaffected is a key goal in anticancer therapeutics. The use of nanoporous silica-based materials as drug-delivery vehicles has recently proven successful, yet production of these materials requires costly and toxic chemicals. Here we use diatom microalgae-derived nanoporous biosilica to deliver chemotherapeutic drugs to cancer cells. The diatom Thalassiosira pseudonana is genetically engineered to display an IgG-binding domain of protein G on the biosilica surface, enabling attachment of cell-targeting antibodies. Neuroblastoma and B-lymphoma cells are selectively targeted and killed by biosilica displaying specific antibodies sorbed with drug-loaded nanoparticles. Treatment with the same biosilica leads to tumour growth regression in a subcutaneous mouse xenograft model of neuroblastoma. These data indicate that genetically engineered biosilica frustules may be used as versatile 'backpacks' for the targeted delivery of poorly water-soluble anticancer drugs to tumour sites.

Drug-induced amplification of nanoparticle targeting to tumors

PubMed Central

Lin, Kevin Y.; Kwon, Ester J.; Lo, Justin H.; Bhatia, Sangeeta N.

2018-01-01

Summary Nanomedicines have the potential to significantly impact cancer therapy by improving drug efficacy and decreasing off-target effects, yet our ability to efficiently home nanoparticles to disease sites remains limited. One frequently overlooked constraint of current active targeting schemes is the relative dearth of targetable antigens within tumors, which restricts the amount of cargo that can be delivered in a tumor-specific manner. To address this limitation, we exploit tumor-specific responses to drugs to construct a cooperative targeting system where a small molecule therapeutic modulates the disease microenvironment to amplify nanoparticle recruitment in vivo. We first administer a vascular disrupting agent, ombrabulin, which selectively affects tumors and leads to locally elevated presentation of the stress-related protein, p32. This increase in p32 levels provides more binding sites for circulating p32-targeted nanoparticles, enhancing their delivery of diagnostic or therapeutic cargos to tumors. We show that this cooperative targeting system recruits over five times higher doses of nanoparticles to tumors and decreases tumor burden when compared with non-cooperative controls. These results suggest that using nanomedicine in conjunction with drugs that enhance the presentation of target antigens in the tumor environment may be an effective strategy for improving the diagnosis and treatment of cancer. PMID:29731806

Systems-level modeling of mycobacterial metabolism for the identification of new (multi-)drug targets.

PubMed

Rienksma, Rienk A; Suarez-Diez, Maria; Spina, Lucie; Schaap, Peter J; Martins dos Santos, Vitor A P

2014-12-01

Systems-level metabolic network reconstructions and the derived constraint-based (CB) mathematical models are efficient tools to explore bacterial metabolism. Approximately one-fourth of the Mycobacterium tuberculosis (Mtb) genome contains genes that encode proteins directly involved in its metabolism. These represent potential drug targets that can be systematically probed with CB models through the prediction of genes essential (or the combination thereof) for the pathogen to grow. However, gene essentiality depends on the growth conditions and, so far, no in vitro model precisely mimics the host at the different stages of mycobacterial infection, limiting model predictions. These limitations can be circumvented by combining expression data from in vivo samples with a validated CB model, creating an accurate description of pathogen metabolism in the host. To this end, we present here a thoroughly curated and extended genome-scale CB metabolic model of Mtb quantitatively validated using 13C measurements. We describe some of the efforts made in integrating CB models and high-throughput data to generate condition specific models, and we will discuss challenges ahead. This knowledge and the framework herein presented will enable to identify potential new drug targets, and will foster the development of optimal therapeutic strategies. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Target specific delivery of anticancer drug in silk fibroin based 3D distribution model of bone-breast cancer cells.

PubMed

Subia, Bano; Dey, Tuli; Sharma, Shaily; Kundu, Subhas C

2015-02-04

To avoid the indiscriminating action of anticancer drugs, the cancer cell specific targeting of drug molecule becomes a preferred choice for the treatment. The successful screening of the drug molecules in 2D culture system requires further validation. The failure of target specific drug in animal model raises the issue of creating a platform in between the in vitro (2D) and in vivo animal testing. The metastatic breast cancer cells migrate and settle at different sites such as bone tissue. This work evaluates the in vitro 3D model of the breast cancer and bone cells to understand the cellular interactions in the presence of a targeted anticancer drug delivery system. The silk fibroin based cytocompatible 3D scaffold is used as in vitro 3D distribution model. Human breast adenocarcinoma and osteoblast like cells are cocultured to evaluate the efficiency of doxorubicin loaded folic acid conjugated silk fibroin nanoparticle as drug delivery system. Decreasing population of the cancer cells, which lower the levels of vascular endothelial growth factors, glucose consumption, and lactate production are observed in the drug treated coculture constructs. The drug treated constructs do not show any major impact on bone mineralization. The diminished expression of osteogenic markers such as osteocalcein and alkaline phosphatase are recorded. The result indicates that this type of silk based 3D in vitro coculture model may be utilized as a bridge between the traditional 2D and animal model system to evaluate the new drug molecule (s) or to reassay the known drug molecules or to develop target specific drug in cancer research.

Drug-target interaction prediction from PSSM based evolutionary information.

PubMed

Mousavian, Zaynab; Khakabimamaghani, Sahand; Kavousi, Kaveh; Masoudi-Nejad, Ali

2016-01-01

The labor-intensive and expensive experimental process of drug-target interaction prediction has motivated many researchers to focus on in silico prediction, which leads to the helpful information in supporting the experimental interaction data. Therefore, they have proposed several computational approaches for discovering new drug-target interactions. Several learning-based methods have been increasingly developed which can be categorized into two main groups: similarity-based and feature-based. In this paper, we firstly use the bi-gram features extracted from the Position Specific Scoring Matrix (PSSM) of proteins in predicting drug-target interactions. Our results demonstrate the high-confidence prediction ability of the Bigram-PSSM model in terms of several performance indicators specifically for enzymes and ion channels. Moreover, we investigate the impact of negative selection strategy on the performance of the prediction, which is not widely taken into account in the other relevant studies. This is important, as the number of non-interacting drug-target pairs are usually extremely large in comparison with the number of interacting ones in existing drug-target interaction data. An interesting observation is that different levels of performance reduction have been attained for four datasets when we change the sampling method from the random sampling to the balanced sampling. Copyright © 2015 Elsevier Inc. All rights reserved.

Drug-target interaction prediction via class imbalance-aware ensemble learning.

PubMed

Ezzat, Ali; Wu, Min; Li, Xiao-Li; Kwoh, Chee-Keong

2016-12-22

Multiple computational methods for predicting drug-target interactions have been developed to facilitate the drug discovery process. These methods use available data on known drug-target interactions to train classifiers with the purpose of predicting new undiscovered interactions. However, a key challenge regarding this data that has not yet been addressed by these methods, namely class imbalance, is potentially degrading the prediction performance. Class imbalance can be divided into two sub-problems. Firstly, the number of known interacting drug-target pairs is much smaller than that of non-interacting drug-target pairs. This imbalance ratio between interacting and non-interacting drug-target pairs is referred to as the between-class imbalance. Between-class imbalance degrades prediction performance due to the bias in prediction results towards the majority class (i.e. the non-interacting pairs), leading to more prediction errors in the minority class (i.e. the interacting pairs). Secondly, there are multiple types of drug-target interactions in the data with some types having relatively fewer members (or are less represented) than others. This variation in representation of the different interaction types leads to another kind of imbalance referred to as the within-class imbalance. In within-class imbalance, prediction results are biased towards the better represented interaction types, leading to more prediction errors in the less represented interaction types. We propose an ensemble learning method that incorporates techniques to address the issues of between-class imbalance and within-class imbalance. Experiments show that the proposed method improves results over 4 state-of-the-art methods. In addition, we simulated cases for new drugs and targets to see how our method would perform in predicting their interactions. New drugs and targets are those for which no prior interactions are known. Our method displayed satisfactory prediction performance and was

A side-effect free method for identifying cancer drug targets.

PubMed

Ashraf, Md Izhar; Ong, Seng-Kai; Mujawar, Shama; Pawar, Shrikant; More, Pallavi; Paul, Somnath; Lahiri, Chandrajit

2018-04-27

Identifying effective drug targets, with little or no side effects, remains an ever challenging task. A potential pitfall of failing to uncover the correct drug targets, due to side effect of pleiotropic genes, might lead the potential drugs to be illicit and withdrawn. Simplifying disease complexity, for the investigation of the mechanistic aspects and identification of effective drug targets, have been done through several approaches of protein interactome analysis. Of these, centrality measures have always gained importance in identifying candidate drug targets. Here, we put forward an integrated method of analysing a complex network of cancer and depict the importance of k-core, functional connectivity and centrality (KFC) for identifying effective drug targets. Essentially, we have extracted the proteins involved in the pathways leading to cancer from the pathway databases which enlist real experimental datasets. The interactions between these proteins were mapped to build an interactome. Integrative analyses of the interactome enabled us to unearth plausible reasons for drugs being rendered withdrawn, thereby giving future scope to pharmaceutical industries to potentially avoid them (e.g. ESR1, HDAC2, F2, PLG, PPARA, RXRA, etc). Based upon our KFC criteria, we have shortlisted ten proteins (GRB2, FYN, PIK3R1, CBL, JAK2, LCK, LYN, SYK, JAK1 and SOCS3) as effective candidates for drug development.

Increasing the structural coverage of tuberculosis drug targets.

PubMed

Baugh, Loren; Phan, Isabelle; Begley, Darren W; Clifton, Matthew C; Armour, Brianna; Dranow, David M; Taylor, Brandy M; Muruthi, Marvin M; Abendroth, Jan; Fairman, James W; Fox, David; Dieterich, Shellie H; Staker, Bart L; Gardberg, Anna S; Choi, Ryan; Hewitt, Stephen N; Napuli, Alberto J; Myers, Janette; Barrett, Lynn K; Zhang, Yang; Ferrell, Micah; Mundt, Elizabeth; Thompkins, Katie; Tran, Ngoc; Lyons-Abbott, Sally; Abramov, Ariel; Sekar, Aarthi; Serbzhinskiy, Dmitri; Lorimer, Don; Buchko, Garry W; Stacy, Robin; Stewart, Lance J; Edwards, Thomas E; Van Voorhis, Wesley C; Myler, Peter J

2015-03-01

High-resolution three-dimensional structures of essential Mycobacterium tuberculosis (Mtb) proteins provide templates for TB drug design, but are available for only a small fraction of the Mtb proteome. Here we evaluate an intra-genus "homolog-rescue" strategy to increase the structural information available for TB drug discovery by using mycobacterial homologs with conserved active sites. Of 179 potential TB drug targets selected for x-ray structure determination, only 16 yielded a crystal structure. By adding 1675 homologs from nine other mycobacterial species to the pipeline, structures representing an additional 52 otherwise intractable targets were solved. To determine whether these homolog structures would be useful surrogates in TB drug design, we compared the active sites of 106 pairs of Mtb and non-TB mycobacterial (NTM) enzyme homologs with experimentally determined structures, using three metrics of active site similarity, including superposition of continuous pharmacophoric property distributions. Pair-wise structural comparisons revealed that 19/22 pairs with >55% overall sequence identity had active site Cα RMSD <1 Å, >85% side chain identity, and ≥80% PSAPF (similarity based on pharmacophoric properties) indicating highly conserved active site shape and chemistry. Applying these results to the 52 NTM structures described above, 41 shared >55% sequence identity with the Mtb target, thus increasing the effective structural coverage of the 179 Mtb targets over three-fold (from 9% to 32%). The utility of these structures in TB drug design can be tested by designing inhibitors using the homolog structure and assaying the cognate Mtb enzyme; a promising test case, Mtb cytidylate kinase, is described. The homolog-rescue strategy evaluated here for TB is also generalizable to drug targets for other diseases. Copyright © 2014 Elsevier Ltd. All rights reserved.

Increasing the structural coverage of tuberculosis drug targets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baugh, Loren; Phan, Isabelle; Begley, Darren W.

High-resolution three-dimensional structures of essential Mycobacterium tuberculosis (Mtb) proteins provide templates for TB drug design, but are available for only a small fraction of the Mtb proteome. Here we evaluate an intra-genus “homolog-rescue” strategy to increase the structural information available for TB drug discovery by using mycobacterial homologs with conserved active sites. We found that of 179 potential TB drug targets selected for x-ray structure determination, only 16 yielded a crystal structure. By adding 1675 homologs from nine other mycobacterial species to the pipeline, structures representing an additional 52 otherwise intractable targets were solved. To determine whether these homolog structuresmore » would be useful surrogates in TB drug design, we compared the active sites of 106 pairs of Mtb and non-TB mycobacterial (NTM) enzyme homologs with experimentally determined structures, using three metrics of active site similarity, including superposition of continuous pharmacophoric property distributions. Pair-wise structural comparisons revealed that 19/22 pairs with >55% overall sequence identity had active site Cα RMSD <1 Å, >85% side chain identity, and ≥80% PS APF (similarity based on pharmacophoric properties) indicating highly conserved active site shape and chemistry. Applying these results to the 52 NTM structures described above, 41 shared >55% sequence identity with the Mtb target, thus increasing the effective structural coverage of the 179 Mtb targets over three-fold (from 9% to 32%). The utility of these structures in TB drug design can be tested by designing inhibitors using the homolog structure and assaying the cognate Mtb enzyme; a promising test case, Mtb cytidylate kinase, is described. The homolog-rescue strategy evaluated here for TB is also generalizable to drug targets for other diseases.« less

Increasing the structural coverage of tuberculosis drug targets

DOE PAGES

Baugh, Loren; Phan, Isabelle; Begley, Darren W.; ...

2014-12-19

High-resolution three-dimensional structures of essential Mycobacterium tuberculosis (Mtb) proteins provide templates for TB drug design, but are available for only a small fraction of the Mtb proteome. Here we evaluate an intra-genus “homolog-rescue” strategy to increase the structural information available for TB drug discovery by using mycobacterial homologs with conserved active sites. We found that of 179 potential TB drug targets selected for x-ray structure determination, only 16 yielded a crystal structure. By adding 1675 homologs from nine other mycobacterial species to the pipeline, structures representing an additional 52 otherwise intractable targets were solved. To determine whether these homolog structuresmore » would be useful surrogates in TB drug design, we compared the active sites of 106 pairs of Mtb and non-TB mycobacterial (NTM) enzyme homologs with experimentally determined structures, using three metrics of active site similarity, including superposition of continuous pharmacophoric property distributions. Pair-wise structural comparisons revealed that 19/22 pairs with >55% overall sequence identity had active site Cα RMSD <1 Å, >85% side chain identity, and ≥80% PS APF (similarity based on pharmacophoric properties) indicating highly conserved active site shape and chemistry. Applying these results to the 52 NTM structures described above, 41 shared >55% sequence identity with the Mtb target, thus increasing the effective structural coverage of the 179 Mtb targets over three-fold (from 9% to 32%). The utility of these structures in TB drug design can be tested by designing inhibitors using the homolog structure and assaying the cognate Mtb enzyme; a promising test case, Mtb cytidylate kinase, is described. The homolog-rescue strategy evaluated here for TB is also generalizable to drug targets for other diseases.« less

Untethered magnetic millirobot for targeted drug delivery.

PubMed

Iacovacci, Veronica; Lucarini, Gioia; Ricotti, Leonardo; Dario, Paolo; Dupont, Pierre E; Menciassi, Arianna

2015-01-01

This paper reports the design and development of a novel millimeter-sized robotic system for targeted therapy. The proposed medical robot is conceived to perform therapy in relatively small diameter body canals (spine, urinary system, ovary, etc.), and to release several kinds of therapeutics, depending on the pathology to be treated. The robot is a nearly-buoyant bi-component system consisting of a carrier, in which the therapeutic agent is embedded, and a piston. The piston, by exploiting magnetic effects, docks with the carrier and compresses a drug-loaded hydrogel, thus activating the release mechanism. External magnetic fields are exploited to propel the robot towards the target region, while intermagnetic forces are exploited to trigger drug release. After designing and fabricating the robot, the system has been tested in vitro with an anticancer drug (doxorubicin) embedded in the carrier. The efficiency of the drug release mechanism has been demonstrated by both quantifying the amount of drug released and by assessing the efficacy of this therapeutic procedure on human bladder cancer cells.

Target-mediated drug disposition model for drugs with two binding sites that bind to a target with one binding site.

PubMed

Gibiansky, Leonid; Gibiansky, Ekaterina

2017-10-01

The paper extended the TMDD model to drugs with two identical binding sites (2-1 TMDD). The quasi-steady-state (2-1 QSS), quasi-equilibrium (2-1 QE), irreversible binding (2-1 IB), and Michaelis-Menten (2-1 MM) approximations of the model were derived. Using simulations, the 2-1 QSS approximation was compared with the full 2-1 TMDD model. As expected and similarly to the standard TMDD for monoclonal antibodies (mAb), 2-1 QSS predictions were nearly identical to 2-1 TMDD predictions, except for times of fast changes following initiation of dosing, when equilibrium has not yet been reached. To illustrate properties of new equations and approximations, several variations of population PK data for mAbs with soluble (slow elimination of the complex) or membrane-bound (fast elimination of the complex) targets were simulated from a full 2-1 TMDD model and fitted to 2-1 TMDD models, to its approximations, and to the standard (1-1) QSS model. For a mAb with a soluble target, it was demonstrated that the 2-1 QSS model provided nearly identical description of the observed (simulated) free drug and total target concentrations, although there was some minor bias in predictions of unobserved free target concentrations. The standard QSS approximation also provided a good description of the observed data, but was not able to distinguish between free drug concentrations (with no target attached and both binding site free) and partially bound drug concentrations (with one of the binding sites occupied by the target). For a mAb with a membrane-bound target, the 2-1 MM approximation adequately described the data. The 2-1 QSS approximation converged 10 times faster than the full 2-1 TMDD, and its run time was comparable with the standard QSS model.

Screening the receptorome to discover the molecular targets for plant-derived psychoactive compounds: a novel approach for CNS drug discovery.

PubMed

Roth, Bryan L; Lopez, Estela; Beischel, Scott; Westkaemper, Richard B; Evans, Jon M

2004-05-01

Because psychoactive plants exert profound effects on human perception, emotion, and cognition, discovering the molecular mechanisms responsible for psychoactive plant actions will likely yield insights into the molecular underpinnings of human consciousness. Additionally, it is likely that elucidation of the molecular targets responsible for psychoactive drug actions will yield validated targets for CNS drug discovery. This review article focuses on an unbiased, discovery-based approach aimed at uncovering the molecular targets responsible for psychoactive drug actions wherein the main active ingredients of psychoactive plants are screened at the "receptorome" (that portion of the proteome encoding receptors). An overview of the receptorome is given and various in silico, public-domain resources are described. Newly developed tools for the in silico mining of data derived from the National Institute of Mental Health Psychoactive Drug Screening Program's (NIMH-PDSP) K(i) Database (K(i) DB) are described in detail. Additionally, three case studies aimed at discovering the molecular targets responsible for Hypericum perforatum, Salvia divinorum, and Ephedra sinica actions are presented. Finally, recommendations are made for future studies.

Membrane Transporters: Structure, Function and Targets for Drug Design

NASA Astrophysics Data System (ADS)

Ravna, Aina W.; Sager, Georg; Dahl, Svein G.; Sylte, Ingebrigt

Current therapeutic drugs act on four main types of molecular targets: enzymes, receptors, ion channels and transporters, among which a major part (60-70%) are membrane proteins. This review discusses the molecular structures and potential impact of membrane transporter proteins on new drug discovery. The three-dimensional (3D) molecular structure of a protein contains information about the active site and possible ligand binding, and about evolutionary relationships within the protein family. Transporters have a recognition site for a particular substrate, which may be used as a target for drugs inhibiting the transporter or acting as a false substrate. Three groups of transporters have particular interest as drug targets: the major facilitator superfamily, which includes almost 4000 different proteins transporting sugars, polyols, drugs, neurotransmitters, metabolites, amino acids, peptides, organic and inorganic anions and many other substrates; the ATP-binding cassette superfamily, which plays an important role in multidrug resistance in cancer chemotherapy; and the neurotransmitter:sodium symporter family, which includes the molecular targets for some of the most widely used psychotropic drugs. Recent technical advances have increased the number of known 3D structures of membrane transporters, and demonstrated that they form a divergent group of proteins with large conformational flexibility which facilitates transport of the substrate.

A high content, high throughput cellular thermal stability assay for measuring drug-target engagement in living cells.

PubMed

Massey, Andrew J

2018-01-01

Determining and understanding drug target engagement is critical for drug discovery. This can be challenging within living cells as selective readouts are often unavailable. Here we describe a novel method for measuring target engagement in living cells based on the principle of altered protein thermal stabilization / destabilization in response to ligand binding. This assay (HCIF-CETSA) utilizes high content, high throughput single cell immunofluorescent detection to determine target protein levels following heating of adherent cells in a 96 well plate format. We have used target engagement of Chk1 by potent small molecule inhibitors to validate the assay. Target engagement measured by this method was subsequently compared to target engagement measured by two alternative methods (autophosphorylation and CETSA). The HCIF-CETSA method appeared robust and a good correlation in target engagement measured by this method and CETSA for the selective Chk1 inhibitor V158411 was observed. However, these EC50 values were 23- and 12-fold greater than the autophosphorylation IC50. The described method is therefore a valuable advance in the CETSA method allowing the high throughput determination of target engagement in adherent cells.

Herceptin conjugated PLGA-PHis-PEG pH sensitive nanoparticles for targeted and controlled drug delivery.

PubMed

Zhou, Zilan; Badkas, Apurva; Stevenson, Max; Lee, Joo-Youp; Leung, Yuet-Kin

2015-06-20

A dual functional nano-scaled drug carrier, comprising of a targeting ligand and pH sensitivity, has been made in order to increase the specificity and efficacy of the drug delivery system. The nanoparticles are made of a tri-block copolymer, poly(d,l lactide-co-glycolide) (PLGA)-b-poly(l-histidine) (PHis)-b-polyethylene glycol (PEG), via nano-precipitation. To provide the nanoparticle feature of endolysosomal escape and pH sensitivity, poly(l-histidine) was chosen as a proton sponge polymer. Herceptin, which specifically binds to HER2 antigen, was conjugated to the nanoparticles through click chemistry. The nanoparticles were characterized via dynamic light scattering (DLS) and transmission electron microscopy (TEM). Both methods showed the sizes of about 100nm with a uniform size distribution. The pH sensitivity was assessed by drug releases and size changes at different pH conditions. As pH decreased from 7.4 to 5.2, the drug release rate accelerated and the size significantly increased. During in vitro tests against human breast cancer cell lines, MCF-7 and SK-BR-3 showed significantly increased uptake for Herceptin-conjugated nanoparticles, as compared to non-targeted nanoparticles. Herceptin-conjugated pH-sensitive nanoparticles showed the highest therapeutic effect, and thus validated the efficacy of a combined approach of pH sensitivity and active targeting. Copyright © 2015 Elsevier B.V. All rights reserved.

Pericyte-targeting drug delivery and tissue engineering.

PubMed

Kang, Eunah; Shin, Jong Wook

2016-01-01

Pericytes are contractile mural cells that wrap around the endothelial cells of capillaries and venules. Depending on the triggers by cellular signals, pericytes have specific functionality in tumor microenvironments, properties of potent stem cells, and plasticity in cellular pathology. These features of pericytes can be activated for the promotion or reduction of angiogenesis. Frontier studies have exploited pericyte-targeting drug delivery, using pericyte-specific peptides, small molecules, and DNA in tumor therapy. Moreover, the communication between pericytes and endothelial cells has been applied to the induction of vessel neoformation in tissue engineering. Pericytes may prove to be a novel target for tumor therapy and tissue engineering. The present paper specifically reviews pericyte-specific drug delivery and tissue engineering, allowing insight into the emerging research targeting pericytes.

Targeting efflux pumps to overcome antifungal drug resistance

PubMed Central

Holmes, Ann R; Cardno, Tony S; Strouse, J Jacob; Ivnitski-Steele, Irena; Keniya, Mikhail V; Lackovic, Kurt; Monk, Brian C; Sklar, Larry A; Cannon, Richard D

2016-01-01

Resistance to antifungal drugs is an increasingly significant clinical problem. The most common antifungal resistance encountered is efflux pump-mediated resistance of Candida species to azole drugs. One approach to overcome this resistance is to inhibit the pumps and chemosensitize resistant strains to azole drugs. Drug discovery targeting fungal efflux pumps could thus result in the development of azole-enhancing combination therapy. Heterologous expression of fungal efflux pumps in Saccharomyces cerevisiae provides a versatile system for screening for pump inhibitors. Fungal efflux pumps transport a range of xenobiotics including fluorescent compounds. This enables the use of fluorescence-based detection, as well as growth inhibition assays, in screens to discover compounds targeting efflux-mediated antifungal drug resistance. A variety of medium- and high-throughput screens have been used to identify a number of chemical entities that inhibit fungal efflux pumps. PMID:27463566

Prostate Cancer Relevant Antigens and Enzymes for Targeted Drug Delivery

PubMed Central

Barve, Ashutosh; Jin, Wei; Cheng, Kun

2014-01-01

Chemotherapy is one of the most widely used approaches in combating advanced prostate cancer, but its therapeutic efficacy is usually insufficient due to lack of specificity and associated toxicity. Lack of targeted delivery to prostate cancer cells is also the primary obstacles in achieving feasible therapeutic effect of other promising agents including peptide, protein, and nucleic acid. Consequently, there remains a critical need for strategies to increase the selectivity of anti-prostate cancer agents. This review will focus on various prostate cancer-specific antigens and enzymes that could be exploited for prostate cancer targeted drug delivery. Among various targeting strategies, active targeting is the most advanced approach to specifically deliver drugs to their designated cancer cells. In this approach, drug carriers are modified with targeting ligands that can specifically bind to prostate cancer-specific antigens. Moreover, there are several specific enzymes in the tumor microenvironment of prostate cancer that can be exploited for stimulus-responsive drug delivery systems. These systems can specifically release the active drug in the tumor microenvironment of prostate cancer, leading to enhanced tumor penetration efficiency. PMID:24878184

A network-based drug repositioning infrastructure for precision cancer medicine through targeting significantly mutated genes in the human cancer genomes.

PubMed

Cheng, Feixiong; Zhao, Junfei; Fooksa, Michaela; Zhao, Zhongming

2016-07-01

Development of computational approaches and tools to effectively integrate multidomain data is urgently needed for the development of newly targeted cancer therapeutics. We proposed an integrative network-based infrastructure to identify new druggable targets and anticancer indications for existing drugs through targeting significantly mutated genes (SMGs) discovered in the human cancer genomes. The underlying assumption is that a drug would have a high potential for anticancer indication if its up-/down-regulated genes from the Connectivity Map tended to be SMGs or their neighbors in the human protein interaction network. We assembled and curated 693 SMGs in 29 cancer types and found 121 proteins currently targeted by known anticancer or noncancer (repurposed) drugs. We found that the approved or experimental cancer drugs could potentially target these SMGs in 33.3% of the mutated cancer samples, and this number increased to 68.0% by drug repositioning through surveying exome-sequencing data in approximately 5000 normal-tumor pairs from The Cancer Genome Atlas. Furthermore, we identified 284 potential new indications connecting 28 cancer types and 48 existing drugs (adjusted P < .05), with a 66.7% success rate validated by literature data. Several existing drugs (e.g., niclosamide, valproic acid, captopril, and resveratrol) were predicted to have potential indications for multiple cancer types. Finally, we used integrative analysis to showcase a potential mechanism-of-action for resveratrol in breast and lung cancer treatment whereby it targets several SMGs (ARNTL, ASPM, CTTN, EIF4G1, FOXP1, and STIP1). In summary, we demonstrated that our integrative network-based infrastructure is a promising strategy to identify potential druggable targets and uncover new indications for existing drugs to speed up molecularly targeted cancer therapeutics. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All

Human genetics as a model for target validation: finding new therapies for diabetes.

PubMed

Thomsen, Soren K; Gloyn, Anna L

2017-06-01

Type 2 diabetes is a global epidemic with major effects on healthcare expenditure and quality of life. Currently available treatments are inadequate for the prevention of comorbidities, yet progress towards new therapies remains slow. A major barrier is the insufficiency of traditional preclinical models for predicting drug efficacy and safety. Human genetics offers a complementary model to assess causal mechanisms for target validation. Genetic perturbations are 'experiments of nature' that provide a uniquely relevant window into the long-term effects of modulating specific targets. Here, we show that genetic discoveries over the past decades have accurately predicted (now known) therapeutic mechanisms for type 2 diabetes. These findings highlight the potential for use of human genetic variation for prospective target validation, and establish a framework for future applications. Studies into rare, monogenic forms of diabetes have also provided proof-of-principle for precision medicine, and the applicability of this paradigm to complex disease is discussed. Finally, we highlight some of the limitations that are relevant to the use of genome-wide association studies (GWAS) in the search for new therapies for diabetes. A key outstanding challenge is the translation of GWAS signals into disease biology and we outline possible solutions for tackling this experimental bottleneck.

Nanobiotechnology-based drug delivery in brain targeting.

PubMed

Dinda, Subas C; Pattnaik, Gurudutta

2013-01-01

Blood brain barrier (BBB) found to act as rate limiting factor in drug delivery to brain in combating the central nervous system (CNS) disorders. Such limiting physiological factors include the reticuloendothelial system and protein opsonization, which present across BBB, play major role in reducing the passage of drug. Several approaches employed to improve the drug delivery across the BBB. Nanoparticles (NP) are the solid colloidal particle ranges from 1 to 1000 nm in size utilized as career for drug delivery. At present NPs are found to play a significant advantage over the other methods of available drug delivery systems to deliver the drug across the BBB. Nanoparticles may be because of its size and functionalization characteristics able to penetrate and facilitate the drug delivery through the barrier. There are number of mechanisms and strategies found to be involved in this process, which are based on the type of nanomaterials used and its combination with therapeutic agents, such materials include liposomes, polymeric nanoparticles and non-viral vectors of nano-sizes for CNS gene therapy, etc. Nanotechnology is expected to reduce the need for invasive procedures for delivery of therapeutics to the CNS. Some devices such as implanted catheters and reservoirs however will still be needed to overcome the problems in effective drug delivery to the CNS. Nanomaterials are found to improve the safety and efficacy level of drug delivery devices in brain targeting. Nanoegineered devices are found to be delivering the drugs at cellular levels through nono-fluidic channels. Different drug delivery systems such as liposomes, microspheres, nanoparticles, nonogels and nonobiocapsules have been used to improve the bioavailability of the drug in the brain, but microchips and biodegradable polymeric nanoparticulate careers are found to be more effective therapeutically in treating brain tumor. The physiological approaches also utilized to improve the transcytosis capacity

EGFR, HER2 and VEGF pathways: validated targets for cancer treatment.

PubMed

Press, Michael F; Lenz, Heinz-Josef

2007-01-01

Targeted therapies are rationally designed to interfere with specific molecular events that are important in tumour growth, progression or survival. Several targeted therapies with anti-tumour activity in human cancer cell lines and xenograft models have now been shown to produce objective responses, delay disease progression and, in some cases, improve survival of patients with advanced malignancies. These targeted therapies include cetuximab, an anti-epidermal growth factor receptor (EGFR) monoclonal antibody; gefitinib and erlotinib, EGFR-specific tyrosine kinase inhibitors; trastuzumab, an anti-human EGFR type 2 (HER2)-related monoclonal antibody; lapatinib, a dual inhibitor of both EGFR- and HER2-associated tyrosine kinases; and bevacizumab, an anti-vascular endothelial growth factor (VEGF) monoclonal antibody. On the basis of preclinical and clinical evidence, EGFR, HER2 and VEGF represent validated targets for cancer therapy and remain the subject of intensive investigation. Both EGFR and HER2 are targets found on cancer cells, whereas VEGF is a target that acts in the tumour microenvironment. Clinical studies are focusing on how to best incorporate targeted therapy into current treatment regimens and other studies are exploring whether different strategies for inhibiting these targets will offer greater benefit. It is clear that optimal use of targeted therapy will depend on understanding how these drugs work mechanistically, and recognising that their activities may differ across patient populations, tumour types and disease stages, as well as when and how they are used in cancer treatment. The results achieved with targeted therapies to date are promising, although they illustrate the need for additional preclinical and clinical study.

Activity-based proteome profiling of potential cellular targets of Orlistat--an FDA-approved drug with anti-tumor activities.

PubMed

Yang, Peng-Yu; Liu, Kai; Ngai, Mun Hong; Lear, Martin J; Wenk, Markus R; Yao, Shao Q

2010-01-20

Orlistat, or tetrahydrolipstatin (THL), is an FDA-approved antiobesity drug with potential antitumor activities. Cellular off-targets and potential side effects of Orlistat in cancer therapies, however, have not been extensively explored thus far. In this study, we report the total of synthesis of THL-like protein-reactive probes, in which extremely conservative modifications (i.e., an alkyne handle) were introduced in the parental THL structure to maintain the native biological properties of Orlistat, while providing the necessary functionality for target identification via the bio-orthogonal click chemistry. With these natural productlike, cell-permeable probes, we were able to demonstrate, for the first time, this chemical proteomic approach is suitable for the identification of previously unknown cellular targets of Orlistat. In addition to the expected fatty acid synthase (FAS), we identified a total of eight new targets, some of which were further validated by experiments including Western blotting, recombinant protein expression, and site-directed mutagenesis. Our findings have important implications in the consideration of Orlistat as a potential anticancer drug at its early stages of development for cancer therapy. Our strategy should be broadly useful for off-target identification against quite a number of existing drugs and/or candidates, which are also covalent modifiers of their biological targets.

Healthcare Databases for Drug Safety Research: Data Validity Assessment Remains Crucial.

PubMed

Rawson, Nigel S B; D'Arcy, Carl

2018-04-30

Administrative healthcare utilization databases are frequently used either individually or as a component of aggregated data for evaluating drug safety issues without taking into account their known deficiencies. All too often insufficient evidence is provided about their validity for the purposes for which they are used. The assessment of data validity is a key constituent that should be included in drug safety research studies and should take a broad multifaceted approach that encompasses both diagnostic and drug exposure data. Drug safety researchers need to continue advancing their knowledge of the data resources they use and to ensure that they and the users of their research understand the limitations of the data that are the foundation on which their research is built. Fundamental issues regarding data validity should be addressed in each use of administrative data for drug safety research.

The application of antitumor drug-targeting models on liver cancer.

PubMed

Yan, Yan; Chen, Ningbo; Wang, Yunbing; Wang, Ke

2016-06-01

Hepatocarcinoma animal models, such as the induced tumor model, transplanted tumor model, gene animal model, are significant experimental tools for the evaluation of targeting drug delivery system as well as the pre-clinical studies of liver cancer. The application of antitumor drug-targeting models not only furnishes similar biological characteristics to human liver cancer but also offers guarantee of pharmacokinetic indicators of the liver-targeting preparations. In this article, we have reviewed some kinds of antitumor drug-targeting models of hepatoma and speculated that the research on this field would be capable of attaining a deeper level and expecting a superior achievement in the future.

Targeting of drugs and nanoparticles to tumors

PubMed Central

Bhatia, Sangeeta N.; Sailor, Michael J.

2010-01-01

The various types of cells that comprise the tumor mass all carry molecular markers that are not expressed or are expressed at much lower levels in normal cells. These differentially expressed molecules can be used as docking sites to concentrate drug conjugates and nanoparticles at tumors. Specific markers in tumor vessels are particularly well suited for targeting because molecules at the surface of blood vessels are readily accessible to circulating compounds. The increased concentration of a drug in the site of disease made possible by targeted delivery can be used to increase efficacy, reduce side effects, or achieve some of both. We review the recent advances in this delivery approach with a focus on the use of molecular markers of tumor vasculature as the primary target and nanoparticles as the delivery vehicle. PMID:20231381

LHRH-Targeted Drug Delivery Systems for Cancer Therapy.

PubMed

Li, Xiaoning; Taratula, Oleh; Taratula, Olena; Schumann, Canan; Minko, Tamara

2017-01-01

Targeted delivery of therapeutic and diagnostic agents to cancer sites has significant potential to improve the therapeutic outcome of treatment while minimizing severe side effects. It is widely accepted that decoration of the drug delivery systems with targeting ligands that bind specifically to the receptors on the cancer cells is a promising strategy that may substantially enhance accumulation of anticancer agents in the tumors. Due to the transformed cellular nature, cancer cells exhibit a variety of overexpressed cell surface receptors for peptides, hormones, and essential nutrients, providing a significant number of target candidates for selective drug delivery. Among others, luteinizing hormonereleasing hormone (LHRH) receptors are overexpressed in the majority of cancers, while their expression in healthy tissues, apart from pituitary cells, is limited. The recent studies indicate that LHRH peptides can be employed to efficiently guide anticancer and imaging agents directly to cancerous cells, thereby increasing the amount of these substances in tumor tissue and preventing normal cells from unnecessary exposure. This manuscript provides an overview of the targeted drug delivery platforms that take advantage of the LHRH receptors overexpression by cancer cells.

Epigenetic Drug Repositioning for Alzheimer's Disease Based on Epigenetic Targets in Human Interactome.

PubMed

Chatterjee, Paulami; Roy, Debjani; Rathi, Nitin

2018-01-01

Epigenetics has emerged as an important field in drug discovery. Alzheimer's disease (AD), the leading neurodegenerative disorder throughout the world, is shown to have an epigenetic basis. Currently, there are very few effective epigenetic drugs available for AD. In this work, for the first time we have proposed 14 AD repositioning epigenetic drugs and identified their targets from extensive human interactome. Interacting partners of the AD epigenetic proteins were identified from the extensive human interactome to construct Epigenetic Protein-Protein Interaction Network (EP-PPIN). Epigenetic Drug-Target Network (EP-DTN) was constructed with the drugs associated with the proteins of EP-PPIN. Regulation of non-coding RNAs associated with the target proteins of these drugs was also studied. AD related target proteins, epigenetic targets, enriched pathways, and functional categories of the proposed repositioning drugs were also studied. The proposed 14 AD epigenetic repositioning drugs have overlapping targets and miRs with known AD epigenetic targets and miRs. Furthermore, several shared functional categories and enriched pathways were obtained for these drugs with FDA approved epigenetic drugs and known AD drugs. The findings of our work might provide insight into future AD epigenetic-therapeutics.

Neuroinflammatory targets and treatments for epilepsy validated in experimental models.

PubMed

Aronica, Eleonora; Bauer, Sebastian; Bozzi, Yuri; Caleo, Matteo; Dingledine, Raymond; Gorter, Jan A; Henshall, David C; Kaufer, Daniela; Koh, Sookyong; Löscher, Wolfgang; Louboutin, Jean-Pierre; Mishto, Michele; Norwood, Braxton A; Palma, Eleonora; Poulter, Michael O; Terrone, Gaetano; Vezzani, Annamaria; Kaminski, Rafal M

2017-07-01

A large body of evidence that has accumulated over the past decade strongly supports the role of inflammation in the pathophysiology of human epilepsy. Specific inflammatory molecules and pathways have been identified that influence various pathologic outcomes in different experimental models of epilepsy. Most importantly, the same inflammatory pathways have also been found in surgically resected brain tissue from patients with treatment-resistant epilepsy. New antiseizure therapies may be derived from these novel potential targets. An essential and crucial question is whether targeting these molecules and pathways may result in anti-ictogenesis, antiepileptogenesis, and/or disease-modification effects. Therefore, preclinical testing in models mimicking relevant aspects of epileptogenesis is needed to guide integrated experimental and clinical trial designs. We discuss the most recent preclinical proof-of-concept studies validating a number of therapeutic approaches against inflammatory mechanisms in animal models that could represent novel avenues for drug development in epilepsy. Finally, we suggest future directions to accelerate preclinical to clinical translation of these recent discoveries. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Repurposing anticancer drugs for targeting necroptosis.

PubMed

Fulda, Simone

2018-04-25

Necroptosis represents a form of programmed cell death that can be engaged by various upstream signals, for example by ligation of death receptors, by viral sensors or by pattern recognition receptors. It depends on several key signaling proteins, including the kinases Receptor-Interacting Protein (RIP)1 and RIP3 and the pseudokinase mixed-lineage kinase domain-like protein (MLKL). Necroptosis has been implicated in a number of physiological and pathophysiological conditions and is disturbed in many human diseases. Thus, targeted interference with necroptosis signaling may offer new opportunities for the treatment of human diseases. Besides structure-based drug design, in recent years drug repositioning has emerged as a promising alternative to develop drug-like compounds. There is accumulating evidence showing that multi-targeting kinase inhibitors, for example Dabrafenib, Vemurafenib, Sorafenib, Pazopanib and Ponatinib, used for the treatment of cancer also display anti-necroptotic activity. This review summarizes recent evidence indicating that some anticancer kinase inhibitors also negatively affect necroptosis signaling. This implies that some cancer therapeutics may be repurposed for other pathologies, e.g. ischemic or inflammatory diseases.

Drug-repositioning opportunities for cancer therapy: novel molecular targets for known compounds.

PubMed

Würth, Roberto; Thellung, Stefano; Bajetto, Adriana; Mazzanti, Michele; Florio, Tullio; Barbieri, Federica

2016-01-01

Drug repositioning is gaining increasing attention in drug discovery because it represents a smart way to exploit new molecular targets of a known drug or target promiscuity among diverse diseases, for medical uses different from the one originally considered. In this review, we focus on known non-oncological drugs with new therapeutic applications in oncology, explaining the rationale behind this approach and providing practical evidence. Moving from incompleteness of the knowledge of drug-target interactions, particularly for older molecules, we highlight opportunities for repurposing compounds as cancer therapeutics, underling the biologically and clinically relevant affinities for new targets. Ideal candidates for repositioning can contribute to the therapeutically unmet need for more-efficient anticancer agents, including drugs that selectively target cancer stem cells. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Flavivirus Protease As a Target for Drug Discovery

PubMed Central

Brecher, Matthew; Zhang, Jing; Li, Hongmin

2014-01-01

Many flaviviruses are significant human pathogens causing considerable disease burdens, including encephalitis and hemorrhagic fever, in the regions in which they are endemic. A paucity of treatments for flaviviral infections has driven interest in drug development targeting proteins essential to flavivirus replication, such as the viral protease. During viral replication, the flavivirus genome is translated as a single polyprotein precursor, which must be cleaved into individual proteins by a complex of the viral protease, NS3, and its cofactor, NS2B. Because this cleavage is an obligate step of the viral life-cycle, the flavivirus protease is an attractive target for antiviral drug development. In this review, we will survey recent drug development studies targeting the NS3 active site, as well as studies targeting an NS2B/NS3 interaction site determined from flavivirus protease crystal structures. PMID:24242363

The flavivirus protease as a target for drug discovery.

PubMed

Brecher, Matthew; Zhang, Jing; Li, Hongmin

2013-12-01

Many flaviviruses are significant human pathogens causing considerable disease burdens, including encephalitis and hemorrhagic fever, in the regions in which they are endemic. A paucity of treatments for flaviviral infections has driven interest in drug development targeting proteins essential to flavivirus replication, such as the viral protease. During viral replication, the flavivirus genome is translated as a single polyprotein precursor, which must be cleaved into individual proteins by a complex of the viral protease, NS3, and its cofactor, NS2B. Because this cleavage is an obligate step of the viral life-cycle, the flavivirus protease is an attractive target for antiviral drug development. In this review, we will survey recent drug development studies targeting the NS3 active site, as well as studies targeting an NS2B/NS3 interaction site determined from flavivirus protease crystal structures.

Integrating Transcriptomics with Metabolic Modeling Predicts Biomarkers and Drug Targets for Alzheimer's Disease

PubMed Central

Stempler, Shiri; Yizhak, Keren; Ruppin, Eytan

2014-01-01

Accumulating evidence links numerous abnormalities in cerebral metabolism with the progression of Alzheimer's disease (AD), beginning in its early stages. Here, we integrate transcriptomic data from AD patients with a genome-scale computational human metabolic model to characterize the altered metabolism in AD, and employ state-of-the-art metabolic modelling methods to predict metabolic biomarkers and drug targets in AD. The metabolic descriptions derived are first tested and validated on a large scale versus existing AD proteomics and metabolomics data. Our analysis shows a significant decrease in the activity of several key metabolic pathways, including the carnitine shuttle, folate metabolism and mitochondrial transport. We predict several metabolic biomarkers of AD progression in the blood and the CSF, including succinate and prostaglandin D2. Vitamin D and steroid metabolism pathways are enriched with predicted drug targets that could mitigate the metabolic alterations observed. Taken together, this study provides the first network wide view of the metabolic alterations associated with AD progression. Most importantly, it offers a cohort of new metabolic leads for the diagnosis of AD and its treatment. PMID:25127241

Retrieval of Enterobacteriaceae drug targets using singular value decomposition.

PubMed

Silvério-Machado, Rita; Couto, Bráulio R G M; Dos Santos, Marcos A

2015-04-15

The identification of potential drug target proteins in bacteria is important in pharmaceutical research for the development of new antibiotics to combat bacterial agents that cause diseases. A new model that combines the singular value decomposition (SVD) technique with biological filters composed of a set of protein properties associated with bacterial drug targets and similarity to protein-coding essential genes of Escherichia coli (strain K12) has been created to predict potential antibiotic drug targets in the Enterobacteriaceae family. This model identified 99 potential drug target proteins in the studied family, which exhibit eight different functions and are protein-coding essential genes or similar to protein-coding essential genes of E.coli (strain K12), indicating that the disruption of the activities of these proteins is critical for cells. Proteins from bacteria with described drug resistance were found among the retrieved candidates. These candidates have no similarity to the human proteome, therefore exhibiting the advantage of causing no adverse effects or at least no known adverse effects on humans. rita_silverio@hotmail.com. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Polymeric micelles with stimuli-triggering systems for advanced cancer drug targeting.

PubMed

Nakayama, Masamichi; Akimoto, Jun; Okano, Teruo

2014-08-01

Since the 1990s, nanoscale drug carriers have played a pivotal role in cancer chemotherapy, acting through passive drug delivery mechanisms and subsequent pharmaceutical action at tumor tissues with reduction of adverse effects. Polymeric micelles, as supramolecular assemblies of amphiphilic polymers, have been considerably developed as promising drug carrier candidates, and a number of clinical studies of anticancer drug-loaded polymeric micelle carriers for cancer chemotherapy applications are now in progress. However, these systems still face several issues; at present, the simultaneous control of target-selective delivery and release of incorporated drugs remains difficult. To resolve these points, the introduction of stimuli-responsive mechanisms to drug carrier systems is believed to be a promising approach to provide better solutions for future tumor drug targeting strategies. As possible trigger signals, biological acidic pH, light, heating/cooling and ultrasound actively play significant roles in signal-triggering drug release and carrier interaction with target cells. This review article summarizes several molecular designs for stimuli-responsive polymeric micelles in response to variation of pH, light and temperature and discusses their potentials as next-generation tumor drug targeting systems.

Experimental and theoretical studies of implant assisted magnetic drug targeting

NASA Astrophysics Data System (ADS)

Aviles, Misael O.

One way to achieve drug targeting in the body is to incorporate magnetic nanoparticles into drug carriers and then retain them at the site using an externally applied magnetic field. This process is referred to as magnetic drug targeting (MDT). However, the main limitation of MDT is that an externally applied magnetic field alone may not be able to retain a sufficient number of magnetic drug carrier particles (MDCPs) to justify its use. Such a limitation might not exist when high gradient magnetic separation (HGMS) principles are applied to assist MDT by means of ferromagnetic implants. It was hypothesized that an Implant Assisted -- MDT (IA-MDT) system would increase the retention of the MDCPs at a target site where an implant had been previously located, since the magnetic forces are produced internally. With this in mind, the overall objective of this work was to demonstrate the feasibility of an IA-MDT system through mathematical modeling and in vitro experimentation. The mathematical models were developed and used to demonstrate the behavior and limitations of IA-MDT, and the in vitro experiments were designed and used to validate the models and to further elucidate the important parameters that affect the performance of the system. IA-MDT was studied with three plausible implants, ferromagnetic stents, seed particles, and wires. All implants were studied theoretically and experimentally using flow through systems with polymer particles containing magnetite nanoparticles as MDCPs. In the stent studies, a wire coil or mesh was simply placed in a flow field and the capture of the MDCPs was studied. In the other cases, a porous polymer matrix was used as a surrogate capillary tissue scaffold to study the capture of the MDCPs using wires or particle seeds as the implant, with the seeds either fixed within the polymer matrix or captured prior to capturing the MDCPs. An in vitro heart tissue perfusion model was also used to study the use of stents. In general, all

A comparative study of disease genes and drug targets in the human protein interactome

PubMed Central

2015-01-01

Background Disease genes cause or contribute genetically to the development of the most complex diseases. Drugs are the major approaches to treat the complex disease through interacting with their targets. Thus, drug targets are critical for treatment efficacy. However, the interrelationship between the disease genes and drug targets is not clear. Results In this study, we comprehensively compared the network properties of disease genes and drug targets for five major disease categories (cancer, cardiovascular disease, immune system disease, metabolic disease, and nervous system disease). We first collected disease genes from genome-wide association studies (GWAS) for five disease categories and collected their corresponding drugs based on drugs' Anatomical Therapeutic Chemical (ATC) classification. Then, we obtained the drug targets for these five different disease categories. We found that, though the intersections between disease genes and drug targets were small, disease genes were significantly enriched in targets compared to their enrichment in human protein-coding genes. We further compared network properties of the proteins encoded by disease genes and drug targets in human protein-protein interaction networks (interactome). The results showed that the drug targets tended to have higher degree, higher betweenness, and lower clustering coefficient in cancer Furthermore, we observed a clear fraction increase of disease proteins or drug targets in the near neighborhood compared with the randomized genes. Conclusions The study presents the first comprehensive comparison of the disease genes and drug targets in the context of interactome. The results provide some foundational network characteristics for further designing computational strategies to predict novel drug targets and drug repurposing. PMID:25861037

A comparative study of disease genes and drug targets in the human protein interactome.

PubMed

Sun, Jingchun; Zhu, Kevin; Zheng, W; Xu, Hua

2015-01-01

Disease genes cause or contribute genetically to the development of the most complex diseases. Drugs are the major approaches to treat the complex disease through interacting with their targets. Thus, drug targets are critical for treatment efficacy. However, the interrelationship between the disease genes and drug targets is not clear. In this study, we comprehensively compared the network properties of disease genes and drug targets for five major disease categories (cancer, cardiovascular disease, immune system disease, metabolic disease, and nervous system disease). We first collected disease genes from genome-wide association studies (GWAS) for five disease categories and collected their corresponding drugs based on drugs' Anatomical Therapeutic Chemical (ATC) classification. Then, we obtained the drug targets for these five different disease categories. We found that, though the intersections between disease genes and drug targets were small, disease genes were significantly enriched in targets compared to their enrichment in human protein-coding genes. We further compared network properties of the proteins encoded by disease genes and drug targets in human protein-protein interaction networks (interactome). The results showed that the drug targets tended to have higher degree, higher betweenness, and lower clustering coefficient in cancer Furthermore, we observed a clear fraction increase of disease proteins or drug targets in the near neighborhood compared with the randomized genes. The study presents the first comprehensive comparison of the disease genes and drug targets in the context of interactome. The results provide some foundational network characteristics for further designing computational strategies to predict novel drug targets and drug repurposing.

10 CFR 26.139 - Reporting initial validity and drug test results.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 10 Energy 1 2011-01-01 2011-01-01 false Reporting initial validity and drug test results. 26.139 Section 26.139 Energy NUCLEAR REGULATORY COMMISSION FITNESS FOR DUTY PROGRAMS Licensee Testing Facilities § 26.139 Reporting initial validity and drug test results. (a) The licensee testing facility shall...

10 CFR 26.139 - Reporting initial validity and drug test results.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 10 Energy 1 2010-01-01 2010-01-01 false Reporting initial validity and drug test results. 26.139 Section 26.139 Energy NUCLEAR REGULATORY COMMISSION FITNESS FOR DUTY PROGRAMS Licensee Testing Facilities § 26.139 Reporting initial validity and drug test results. (a) The licensee testing facility shall...

10 CFR 26.139 - Reporting initial validity and drug test results.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 10 Energy 1 2013-01-01 2013-01-01 false Reporting initial validity and drug test results. 26.139 Section 26.139 Energy NUCLEAR REGULATORY COMMISSION FITNESS FOR DUTY PROGRAMS Licensee Testing Facilities § 26.139 Reporting initial validity and drug test results. (a) The licensee testing facility shall...

Characterization of parasite-specific indels and their proposed relevance for selective anthelminthic drug targeting

PubMed Central

Wang, Qi; Heizer, Esley; Rosa, Bruce A.; Wildman, Scott A.; Janetka, James W.; Mitreva, Makedonka

2016-01-01

Insertions and deletions (indels) are important sequence variants that are considered as phylogenetic markers that reflect evolutionary adaptations in different species. In an effort to systematically study indels specific to the phylum Nematoda and their structural impact on the proteins bearing them, we examined over 340,000 polypeptides from 21 nematode species spanning the phylum, compared them to non-nematodes and identified indels unique to nematode proteins in more than 3,000 protein families. Examination of the amino acid composition revealed uneven usage of amino acids for insertions and deletions. The amino acid composition and cost, along with the secondary structure constitution of the indels, were analyzed in the context of their biological pathway associations. Species-specific indels could enable indel-based targeting for drug design in pathogens/parasites. Therefore, we screened the spatial locations of the indels in the parasite’s protein 3D structures, determined the location of the indel and identified potential unique drug targeting sites. These indels could be confirmed by RNA-Seq data. Examples are presented that illustrate the close proximity of the indel to established small-molecule binding pockets that can potentially facilitate selective targeting to the parasites and bypassing their host, thus reducing or eliminating the toxicity of the potential drugs. The study presents an approach for understanding the adaptation of pathogens/parasites at a molecular level, and outlines a strategy to identify such nematode-selective targets that remain essential to the organism. With further experimental characterization and validation, it opens a possible channel for the development of novel treatments with high target specificity, addressing both host toxicity and resistance concerns. PMID:26829384

Characterization of parasite-specific indels and their proposed relevance for selective anthelminthic drug targeting.

PubMed

Wang, Qi; Heizer, Esley; Rosa, Bruce A; Wildman, Scott A; Janetka, James W; Mitreva, Makedonka

2016-04-01

Insertions and deletions (indels) are important sequence variants that are considered as phylogenetic markers that reflect evolutionary adaptations in different species. In an effort to systematically study indels specific to the phylum Nematoda and their structural impact on the proteins bearing them, we examined over 340,000 polypeptides from 21 nematode species spanning the phylum, compared them to non-nematodes and identified indels unique to nematode proteins in more than 3000 protein families. Examination of the amino acid composition revealed uneven usage of amino acids for insertions and deletions. The amino acid composition and cost, along with the secondary structure constitution of the indels, were analyzed in the context of their biological pathway associations. Species-specific indels could enable indel-based targeting for drug design in pathogens/parasites. Therefore, we screened the spatial locations of the indels in the parasite's protein 3D structures, determined the location of the indel and identified potential unique drug targeting sites. These indels could be confirmed by RNA-Seq data. Examples are presented illustrating the close proximity of some indels to established small-molecule binding pockets that can potentially facilitate selective targeting to the parasites and bypassing their host, thus reducing or eliminating the toxicity of the potential drugs. This study presents an approach for understanding the adaptation of pathogens/parasites at a molecular level, and outlines a strategy to identify such nematode-selective targets that remain essential to the organism. With further experimental characterization and validation, it opens a possible channel for the development of novel treatments with high target specificity, addressing both host toxicity and resistance concerns. Copyright © 2016 Elsevier B.V. All rights reserved.

Advances in Bone-targeted Drug Delivery Systems for Neoadjuvant Chemotherapy for Osteosarcoma.

PubMed

Li, Cheng-Jun; Liu, Xiao-Zhou; Zhang, Lei; Chen, Long-Bang; Shi, Xin; Wu, Su-Jia; Zhao, Jian-Ning

2016-05-01

Targeted therapy for osteosarcoma includes organ, cell and molecular biological targeting; of these, organ targeting is the most mature. Bone-targeted drug delivery systems are used to concentrate chemotherapeutic drugs in bone tissues, thus potentially resolving the problem of reaching the desired foci and minimizing the toxicity and adverse effects of neoadjuvant chemotherapy. Some progress has been made in bone-targeted drug delivery systems for treatment of osteosarcoma; however, most are still at an experimental stage and there is a long transitional period to clinical application. Therefore, determining how to combine new, polymolecular and multi-pathway targets is an important research aspect of designing new bone-targeted drug delivery systems in future studies. The purpose of this article was to review the status of research on targeted therapy for osteosarcoma and to summarize the progress made thus far in developing bone-targeted drug delivery systems for neoadjuvant chemotherapy for osteosarcoma with the aim of providing new ideas for highly effective therapeutic protocols with low toxicity for patients with osteosarcoma. © 2016 Chinese Orthopaedic Association and John Wiley & Sons Australia, Ltd.

Breakable mesoporous silica nanoparticles for targeted drug delivery

NASA Astrophysics Data System (ADS)

Maggini, Laura; Cabrera, Ingrid; Ruiz-Carretero, Amparo; Prasetyanto, Eko A.; Robinet, Eric; de Cola, Luisa

2016-03-01

``Pop goes the particle''. Here we report on the preparation of redox responsive mesoporous organo-silica nanoparticles containing disulfide (S-S) bridges (ss-NPs) that, even upon the exohedral grafting of targeting ligands, retained their ability to undergo structural degradation, and increase their local release activity when exposed to a reducing agent. This degradation could be observed also inside glioma C6 cancer cells. Moreover, when anticancer drug-loaded pristine and derivatized ss-NPs were fed to glioma C6 cells, the responsive hybrids were more effective in their cytotoxic action compared to non-breakable particles. The possibility of tailoring the surface functionalization of this hybrid, yet preserving its self-destructive behavior and enhanced drug delivery properties, paves the way for the development of effective biodegradable materials for in vivo targeted drug delivery.``Pop goes the particle''. Here we report on the preparation of redox responsive mesoporous organo-silica nanoparticles containing disulfide (S-S) bridges (ss-NPs) that, even upon the exohedral grafting of targeting ligands, retained their ability to undergo structural degradation, and increase their local release activity when exposed to a reducing agent. This degradation could be observed also inside glioma C6 cancer cells. Moreover, when anticancer drug-loaded pristine and derivatized ss-NPs were fed to glioma C6 cells, the responsive hybrids were more effective in their cytotoxic action compared to non-breakable particles. The possibility of tailoring the surface functionalization of this hybrid, yet preserving its self-destructive behavior and enhanced drug delivery properties, paves the way for the development of effective biodegradable materials for in vivo targeted drug delivery. Electronic supplementary information (ESI) available: Full experimental procedures, additional SEM and TEM images of particles, complete UV-Vis and PL-monitored characterization of the breakdown of

Extracellular proteases as targets for drug development

PubMed Central

Cudic, Mare

2015-01-01

Proteases constitute one of the primary targets in drug discovery. In the present review, we focus on extracellular proteases (ECPs) because of their differential expression in many pathophysiological processes, including cancer, cardiovascular conditions, and inflammatory, pulmonary, and periodontal diseases. Many new ECP inhibitors are currently under clinical investigation and a significant increase in new therapies based on protease inhibition can be expected in the coming years. In addition to directly blocking the activity of a targeted protease, one can take advantage of differential expression in disease states to selectively deliver therapeutic or imaging agents. Recent studies in targeted drug development for the metalloproteases (matrix metalloproteinases, adamalysins, pappalysins, neprilysin, angiotensin-converting enzyme, metallocarboxypeptidases, and glutamate carboxypeptidase II), serine proteases (elastase, coagulation factors, tissue/urokinase plasminogen activator system, kallikreins, tryptase, dipeptidyl peptidase IV), cysteine proteases (cathepsin B), and renin system are discussed herein. PMID:19689354

Receptor-Mediated Drug Delivery Systems Targeting to Glioma

PubMed Central

Wang, Shanshan; Meng, Ying; Li, Chengyi; Qian, Min; Huang, Rongqin

2015-01-01

Glioma has been considered to be the most frequent primary tumor within the central nervous system (CNS). The complexity of glioma, especially the existence of the blood-brain barrier (BBB), makes the survival and prognosis of glioma remain poor even after a standard treatment based on surgery, radiotherapy, and chemotherapy. This provides a rationale for the development of some novel therapeutic strategies. Among them, receptor-mediated drug delivery is a specific pattern taking advantage of differential expression of receptors between tumors and normal tissues. The strategy can actively transport drugs, such as small molecular drugs, gene medicines, and therapeutic proteins to glioma while minimizing adverse reactions. This review will summarize recent progress on receptor-mediated drug delivery systems targeting to glioma, and conclude the challenges and prospects of receptor-mediated glioma-targeted therapy for future applications. PMID:28344260

Biomimetic and bioinspired nanoparticles for targeted drug delivery.

PubMed

Gagliardi, Mariacristina

2017-03-01

In drug targeting, the urgent need for more effective and less iatrogenic therapies is pushing toward a complete revision of carrier setup. After the era of 'articles used as homing systems', novel prototypes are now emerging. Newly conceived carriers are endowed with better biocompatibility, biodistribution and targeting properties. The biomimetic approach bestows such improved functional properties. Exploiting biological molecules, organisms and cells, or taking inspiration from them, drug vector performances are now rapidly progressing toward the perfect carrier. Following this direction, researchers have refined carrier properties, achieving significant results. The present review summarizes recent advances in biomimetic and bioinspired drug vectors, derived from biologicals or obtained by processing synthetic materials with a biomimetic approach.

Alzheimer's disease master regulators analysis: search for potential molecular targets and drug repositioning candidates.

PubMed

Vargas, D M; De Bastiani, M A; Zimmer, E R; Klamt, F

2018-06-23

tools as exploratory strategies in neurodegenerative diseases research, and also provides new perspectives on molecular targets and drug therapies for future investigation and validation in AD.

Designing multi-targeted agents: An emerging anticancer drug discovery paradigm.

PubMed

Fu, Rong-Geng; Sun, Yuan; Sheng, Wen-Bing; Liao, Duan-Fang

2017-08-18

The dominant paradigm in drug discovery is to design ligands with maximum selectivity to act on individual drug targets. With the target-based approach, many new chemical entities have been discovered, developed, and further approved as drugs. However, there are a large number of complex diseases such as cancer that cannot be effectively treated or cured only with one medicine to modulate the biological function of a single target. As simultaneous intervention of two (or multiple) cancer progression relevant targets has shown improved therapeutic efficacy, the innovation of multi-targeted drugs has become a promising and prevailing research topic and numerous multi-targeted anticancer agents are currently at various developmental stages. However, most multi-pharmacophore scaffolds are usually discovered by serendipity or screening, while rational design by combining existing pharmacophore scaffolds remains an enormous challenge. In this review, four types of multi-pharmacophore modes are discussed, and the examples from literature will be used to introduce attractive lead compounds with the capability of simultaneously interfering with different enzyme or signaling pathway of cancer progression, which will reveal the trends and insights to help the design of the next generation multi-targeted anticancer agents. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Targeting the latest hallmark of cancer: another attempt at 'magic bullet' drugs targeting cancers' metabolic phenotype.

PubMed

Cuperlovic-Culf, M; Culf, A S; Touaibia, M; Lefort, N

2012-10-01

The metabolism of tumors is remarkably different from the metabolism of corresponding normal cells and tissues. Metabolic alterations are initiated by oncogenes and are required for malignant transformation, allowing cancer cells to resist some cell death signals while producing energy and fulfilling their biosynthetic needs with limiting resources. The distinct metabolic phenotype of cancers provides an interesting avenue for treatment, potentially with minimal side effects. As many cancers show similar metabolic characteristics, drugs targeting the cancer metabolic phenotype are, perhaps optimistically, expected to be 'magic bullet' treatments. Over the last few years there have been a number of potential drugs developed to specifically target cancer metabolism. Several of these drugs are currently in clinical and preclinical trials. This review outlines examples of drugs developed for different targets of significance to cancer metabolism, with a focus on small molecule leads, chemical biology and clinical results for these drugs.

Quantitative targeting maps based on experimental investigations for a branched tube model in magnetic drug targeting

NASA Astrophysics Data System (ADS)

Gitter, K.; Odenbach, S.

2011-12-01

Magnetic drug targeting (MDT), because of its high targeting efficiency, is a promising approach for tumour treatment. Unwanted side effects are considerably reduced, since the nanoparticles are concentrated within the target region due to the influence of a magnetic field. Nevertheless, understanding the transport phenomena of nanoparticles in an artery system is still challenging. This work presents experimental results for a branched tube model. Quantitative results describe, for example, the net amount of nanoparticles that are targeted towards the chosen region due to the influence of a magnetic field. As a result of measurements, novel drug targeting maps, combining, e.g. the magnetic volume force, the position of the magnet and the net amount of targeted nanoparticles, are presented. The targeting maps are valuable for evaluation and comparison of setups and are also helpful for the design and the optimisation of a magnet system with an appropriate strength and distribution of the field gradient. The maps indicate the danger of accretion within the tube and also show the promising result of magnetic drug targeting that up to 97% of the nanoparticles were successfully targeted.

Pros and cons of the liposome platform in cancer drug targeting.

PubMed

Gabizon, Alberto A; Shmeeda, Hilary; Zalipsky, Samuel

2006-01-01

Coating of liposomes with polyethylene-glycol (PEG) by incorporation in the liposome bilayer of PEG-derivatized lipids results in inhibition of liposome uptake by the reticulo-endothelial system and significant prolongation of liposome residence time in the blood stream. Parallel developments in drug loading technology have improved the efficiency and stability of drug entrapment in liposomes, particularly with regard to cationic amphiphiles such as anthracyclines. An example of this new generation of liposomes is a formulation of pegylated liposomal doxorubicin known as Doxil or Caelyx, whose clinical pharmacokinetic profile is characterized by slow plasma clearance and small volume of distribution. A hallmark of these long-circulating liposomal drug carriers is their enhanced accumulation in tumors. The mechanism underlying this passive targeting effect is the phenomenon known as enhanced permeability and retention (EPR) which has been described in a broad variety of experimental tumor types. Further to the passive targeting effect, the liposome drug delivery platform offers the possibility of grafting tumor-specific ligands on the liposome membrane for active targeting to tumor cells, and potentially intracellular drug delivery. The pros and cons of the liposome platform in cancer targeting are discussed vis-à-vis nontargeted drugs, using as an example a liposome drug delivery system targeted to the folate receptor.

Targeted polymeric micelles for delivery of poorly soluble drugs.

PubMed

Torchilin, V P

2004-10-01

Polymeric micelles (micelles formed by amphiphilic block copolymers) demonstrate a series of attractive properties as drug carriers, such as high stability both in vitro and in vivo and good biocompatibility, and can be successfully used for the solubilization of various poorly soluble pharmaceuticals. These micelles can also be used as targeted drug delivery systems. The targeting can be achieved via the enhanced permeability and retention effect (into the areas with the compromised vasculature), by making micelles of stimuli-responsive amphiphilic block copolymers, or by attaching specific targeting ligand molecules to the micelle surface. Immunomicelles prepared by coupling monoclonal antibody molecules to p-nitrophenylcarbonyl groups on the water-exposed termini of the micelle corona-forming blocks demonstrate high binding specificity and targetability. Immunomicelles prepared with cancer-specific monoclonal antibody 2C5 specifically bind to different cancer cells in vitro and demonstrate increased therapeutic activity in vivo. This new family of pharmaceutical carriers can be used for the solubilization and targeted delivery of poorly soluble drugs to various pathological sites in the body.

Targeted nanomedicine for cancer therapeutics: Towards precision medicine overcoming drug resistance.

PubMed

Bar-Zeev, Maya; Livney, Yoav D; Assaraf, Yehuda G

2017-03-01

Intrinsic anticancer drug resistance appearing prior to chemotherapy as well as acquired resistance due to drug treatment, remain the dominant impediments towards curative cancer therapy. Hence, novel targeted strategies to overcome cancer drug resistance constitute a key aim of cancer research. In this respect, targeted nanomedicine offers innovative therapeutic strategies to overcome the various limitations of conventional chemotherapy, enabling enhanced selectivity, early and more precise cancer diagnosis, individualized treatment as well as overcoming of drug resistance, including multidrug resistance (MDR). Delivery systems based on nanoparticles (NPs) include diverse platforms enabling a plethora of rationally designed therapeutic nanomedicines. Here we review NPs designed to enhance antitumor drug uptake and selective intracellular accumulation using strategies including passive and active targeting, stimuli-responsive drug activation or target-activated release, triggered solely in the cancer cell or in specific organelles, cutting edge theranostic multifunctional NPs delivering drug combinations for synergistic therapy, while facilitating diagnostics, and personalization of therapeutic regimens. In the current paper we review the recent findings of the past four years and discuss the advantages and limitations of the various novel NPs-based drug delivery systems. Special emphasis is put on in vivo study-based evidences supporting significant therapeutic impact in chemoresistant cancers. A future perspective is proposed for further research and development of complex targeted, multi-stage responsive nanomedical drug delivery systems for personalized cancer diagnosis and efficacious therapy. Copyright © 2017 Elsevier Ltd. All rights reserved.

A smart multifunctional drug delivery nanoplatform for targeting cancer cells

NASA Astrophysics Data System (ADS)

Hoop, M.; Mushtaq, F.; Hurter, C.; Chen, X.-Z.; Nelson, B. J.; Pané, S.

2016-06-01

Wirelessly guided magnetic nanomachines are promising vectors for targeted drug delivery, which have the potential to minimize the interaction between anticancer agents and healthy tissues. In this work, we propose a smart multifunctional drug delivery nanomachine for targeted drug delivery that incorporates a stimuli-responsive building block. The nanomachine consists of a magnetic nickel (Ni) nanotube that contains a pH-responsive chitosan hydrogel in its inner cavity. The chitosan inside the nanotube serves as a matrix that can selectively release drugs in acidic environments, such as the extracellular space of most tumors. Approximately a 2.5 times higher drug release from Ni nanotubes at pH = 6 is achieved compared to that at pH = 7.4. The outside of the Ni tube is coated with gold. A fluorescein isothiocyanate (FITC) labeled thiol-ssDNA, a biological marker, was conjugated on its surface by thiol-gold click chemistry, which enables traceability. The Ni nanotube allows the propulsion of the device by means of external magnetic fields. As the proposed nanoarchitecture integrates different functional building blocks, our drug delivery nanoplatform can be employed for carrying molecular drug conjugates and for performing targeted combinatorial therapies, which can provide an alternative and supplementary solution to current drug delivery technologies.Wirelessly guided magnetic nanomachines are promising vectors for targeted drug delivery, which have the potential to minimize the interaction between anticancer agents and healthy tissues. In this work, we propose a smart multifunctional drug delivery nanomachine for targeted drug delivery that incorporates a stimuli-responsive building block. The nanomachine consists of a magnetic nickel (Ni) nanotube that contains a pH-responsive chitosan hydrogel in its inner cavity. The chitosan inside the nanotube serves as a matrix that can selectively release drugs in acidic environments, such as the extracellular space of

Computational selection of antibody-drug conjugate targets for breast cancer

PubMed Central

Fauteux, François; Hill, Jennifer J.; Jaramillo, Maria L.; Pan, Youlian; Phan, Sieu; Famili, Fazel; O'Connor-McCourt, Maureen

2016-01-01

The selection of therapeutic targets is a critical aspect of antibody-drug conjugate research and development. In this study, we applied computational methods to select candidate targets overexpressed in three major breast cancer subtypes as compared with a range of vital organs and tissues. Microarray data corresponding to over 8,000 tissue samples were collected from the public domain. Breast cancer samples were classified into molecular subtypes using an iterative ensemble approach combining six classification algorithms and three feature selection techniques, including a novel kernel density-based method. This feature selection method was used in conjunction with differential expression and subcellular localization information to assemble a primary list of targets. A total of 50 cell membrane targets were identified, including one target for which an antibody-drug conjugate is in clinical use, and six targets for which antibody-drug conjugates are in clinical trials for the treatment of breast cancer and other solid tumors. In addition, 50 extracellular proteins were identified as potential targets for non-internalizing strategies and alternative modalities. Candidate targets linked with the epithelial-to-mesenchymal transition were identified by analyzing differential gene expression in epithelial and mesenchymal tumor-derived cell lines. Overall, these results show that mining human gene expression data has the power to select and prioritize breast cancer antibody-drug conjugate targets, and the potential to lead to new and more effective cancer therapeutics. PMID:26700623

DDR: efficient computational method to predict drug-target interactions using graph mining and machine learning approaches.

PubMed

Olayan, Rawan S; Ashoor, Haitham; Bajic, Vladimir B

2018-04-01

Finding computationally drug-target interactions (DTIs) is a convenient strategy to identify new DTIs at low cost with reasonable accuracy. However, the current DTI prediction methods suffer the high false positive prediction rate. We developed DDR, a novel method that improves the DTI prediction accuracy. DDR is based on the use of a heterogeneous graph that contains known DTIs with multiple similarities between drugs and multiple similarities between target proteins. DDR applies non-linear similarity fusion method to combine different similarities. Before fusion, DDR performs a pre-processing step where a subset of similarities is selected in a heuristic process to obtain an optimized combination of similarities. Then, DDR applies a random forest model using different graph-based features extracted from the DTI heterogeneous graph. Using 5-repeats of 10-fold cross-validation, three testing setups, and the weighted average of area under the precision-recall curve (AUPR) scores, we show that DDR significantly reduces the AUPR score error relative to the next best start-of-the-art method for predicting DTIs by 34% when the drugs are new, by 23% when targets are new and by 34% when the drugs and the targets are known but not all DTIs between them are not known. Using independent sources of evidence, we verify as correct 22 out of the top 25 DDR novel predictions. This suggests that DDR can be used as an efficient method to identify correct DTIs. The data and code are provided at https://bitbucket.org/RSO24/ddr/. vladimir.bajic@kaust.edu.sa. Supplementary data are available at Bioinformatics online.

Targeting RAS Membrane Association: Back to the Future for Anti-RAS Drug Discovery?

PubMed Central

Cox, Adrienne D.; Der, Channing J.; Philips, Mark R.

2015-01-01

RAS proteins require membrane association for their biological activity, making this association a logical target for anti-RAS therapeutics. Lipid modification of RAS proteins by a farnesyl isoprenoid is an obligate step in that association, and is an enzymatic process. Accordingly, farnesyltransferase inhibitors (FTIs) were developed as potential anti-RAS drugs. The lack of efficacy of FTIs as anti-cancer drugs was widely seen as indicating that blocking RAS membrane association was a flawed approach to cancer treatment. However, a deeper understanding of RAS modification and trafficking has revealed that this was an erroneous conclusion. In the presence of FTIs, KRAS and NRAS, which are the RAS isoforms most frequently mutated in cancer, become substrates for alternative modification, can still associate with membranes, and can still function. Thus, FTIs failed not because blocking RAS membrane association is an ineffective approach, but because FTIs failed to accomplish that task. Recent findings regarding RAS isoform trafficking and the regulation of RAS subcellular localization have rekindled interest in efforts to target these processes. In particular, improved understanding of the palmitoylation/depalmitoylation cycle that regulates RAS interaction with the plasma membrane, endomembranes and cytosol, and of the potential importance of RAS chaperones, have led to new approaches. Efforts to validate and target other enzymatically regulated post-translational modifications are also ongoing. In this review, we revisit lessons learned, describe the current state of the art, and highlight challenging but promising directions to achieve the goal of disrupting RAS membrane association and subcellular localization for anti-RAS drug development. PMID:25878363

Active Targeted Drug Delivery for Microbes Using Nano-Carriers

PubMed Central

Lin, Yung-Sheng; Lee, Ming-Yuan; Yang, Chih-Hui; Huang, Keng-Shiang

2015-01-01

Although vaccines and antibiotics could kill or inhibit microbes, many infectious diseases remain difficult to treat because of acquired resistance and adverse side effects. Nano-carriers-based technology has made significant progress for a long time and is introducing a new paradigm in drug delivery. However, it still has some challenges like lack of specificity toward targeting the infectious site. Nano-carriers utilized targeting ligands on their surface called ‘active target’ provide the promising way to solve the problems like accelerating drug delivery to infectious areas and preventing toxicity or side-effects. In this mini review, we demonstrate the recent studies using the active targeted strategy to kill or inhibit microbes. The four common nano-carriers (e.g. liposomes, nanoparticles, dendrimers and carbon nanotubes) delivering encapsulated drugs are introduced. PMID:25877093

[Preventable drug-related morbidity: determining valid indicators for primary care in Portugal].

PubMed

Guerreiro, Mara Pereira; Cantrill, Judith A; Martins, Ana Paula

2007-01-01

Preventable drug-related morbidity (PDRM) indicators are operational measures of therapeutic risk management. These clinical indicators, which cover a wide range of drugs, combine process and outcome in the same instrument. They were developed in the US and have been validated for primary care settings in the US, UK and Canada. This study is part of a research programme; it aimed to determine a valid set of PDRM indicators for adult patients in primary care in Portugal. Face validity of 61 US and UK-derived indicators translated to Portuguese was preliminarily determined by means of a postal questionnaire using a purposive sample of four Portuguese pharmacists with different backgrounds. Preliminary content validity of indicators approved in the previous stage was determined by cross-checking each definition of PDRM with standard drug information sources in Portugal. Face and content validity of indicators yielded by preliminary work were then established by a 37 expert panel (20 community pharmacists and 17 general practitioners) using a two-round Delphi survey. Data were analysed using SPSS release 11.5. Nineteen indicators were ruled out in preliminary validation. Changes were made in the content of eight of the remaining 42 indicators; these were related to differences in the drugs being marketed and patterns of drug monitoring between countries. Thirty-five indicators were consensus approved as PDRM for adult patients in Portuguese primary care by the Delphi panel.

Medicinal electronomics bricolage design of hypoxia-targeting antineoplastic drugs and invention of boron tracedrugs as innovative future-architectural drugs.

PubMed

Hori, Hitoshi; Uto, Yoshihiro; Nakata, Eiji

2010-09-01

We describe herein for the first time our medicinal electronomics bricolage design of hypoxia-targeting antineoplastic drugs and boron tracedrugs as newly emerging drug classes. A new area of antineoplastic drugs and treatments has recently focused on neoplastic cells of the tumor environment/microenvironment involving accessory cells. This tumor hypoxic environment is now considered as a major factor that influences not only the response to antineoplastic therapies but also the potential for malignant progression and metastasis. We review our medicinal electronomics bricolage design of hypoxia-targeting drugs, antiangiogenic hypoxic cell radiosensitizers, sugar-hybrid hypoxic cell radiosensitizers, and hypoxia-targeting 10B delivery agents, in which we design drug candidates based on their electronic structures obtained by molecular orbital calculations, not based solely on pharmacophore development. These drugs include an antiangiogenic hypoxic cell radiosensitizer TX-2036, a sugar-hybrid hypoxic cell radiosensitizer TX-2244, new hypoxia-targeting indoleamine 2,3-dioxygenase (IDO) inhibitors, and a hypoxia-targeting BNCT agent, BSH (sodium borocaptate-10B)-hypoxic cytotoxin tirapazamine (TPZ) hybrid drug TX-2100. We then discuss the concept of boron tracedrugs as a new drug class having broad potential in many areas.

Genomic approach to therapeutic target validation identifies a glucose-lowering GLP1R variant protective for coronary heart disease

PubMed Central

Scott, Robert A.; Freitag, Daniel F.; Li, Li; Chu, Audrey Y.; Surendran, Praveen; Young, Robin; Grarup, Niels; Stancáková, Alena; Chen, Yuning; V.Varga, Tibor; Yaghootkar, Hanieh; Luan, Jian'an; Zhao, Jing Hua; Willems, Sara M.; Wessel, Jennifer; Wang, Shuai; Maruthur, Nisa; Michailidou, Kyriaki; Pirie, Ailith; van der Lee, Sven J.; Gillson, Christopher; Olama, Ali Amin Al; Amouyel, Philippe; Arriola, Larraitz; Arveiler, Dominique; Aviles-Olmos, Iciar; Balkau, Beverley; Barricarte, Aurelio; Barroso, Inês; Garcia, Sara Benlloch; Bis, Joshua C.; Blankenberg, Stefan; Boehnke, Michael; Boeing, Heiner; Boerwinkle, Eric; Borecki, Ingrid B.; Bork-Jensen, Jette; Bowden, Sarah; Caldas, Carlos; Caslake, Muriel; Cupples, L. Adrienne; Cruchaga, Carlos; Czajkowski, Jacek; den Hoed, Marcel; Dunn, Janet A.; Earl, Helena M.; Ehret, Georg B.; Ferrannini, Ele; Ferrieres, Jean; Foltynie, Thomas; Ford, Ian; Forouhi, Nita G.; Gianfagna, Francesco; Gonzalez, Carlos; Grioni, Sara; Hiller, Louise; Jansson, Jan-Håkan; Jørgensen, Marit E.; Jukema, J. Wouter; Kaaks, Rudolf; Kee, Frank; Kerrison, Nicola D.; Key, Timothy J.; Kontto, Jukka; Kote-Jarai, Zsofia; Kraja, Aldi T.; Kuulasmaa, Kari; Kuusisto, Johanna; Linneberg, Allan; Liu, Chunyu; Marenne, Gaëlle; Mohlke, Karen L.; Morris, Andrew P.; Muir, Kenneth; Müller-Nurasyid, Martina; Munroe, Patricia B.; Navarro, Carmen; Nielsen, Sune F.; Nilsson, Peter M.; Nordestgaard, Børge G.; Packard, Chris J.; Palli, Domenico; Panico, Salvatore; Peloso, Gina M.; Perola, Markus; Peters, Annette; Poole, Christopher J.; Quirós, J. Ramón; Rolandsson, Olov; Sacerdote, Carlotta; Salomaa, Veikko; Sánchez, María-José; Sattar, Naveed; Sharp, Stephen J.; Sims, Rebecca; Slimani, Nadia; Smith, Jennifer A.; Thompson, Deborah J.; Trompet, Stella; Tumino, Rosario; van der A, Daphne L.; van der Schouw, Yvonne T.; Virtamo, Jarmo; Walker, Mark; Walter, Klaudia; Abraham, Jean E.; Amundadottir, Laufey T.; Aponte, Jennifer L.; Butterworth, Adam S.; Dupuis, Josée; Easton, Douglas F.; Eeles, Rosalind A.; Erdmann, Jeanette; Franks, Paul W.; Frayling, Timothy M.; Hansen, Torben; Howson, Joanna M. M.; Jørgensen, Torben; Kooner, Jaspal; Laakso, Markku; Langenberg, Claudia; McCarthy, Mark I.; Pankow, James S.; Pedersen, Oluf; Riboli, Elio; Rotter, Jerome I.; Saleheen, Danish; Samani, Nilesh J.; Schunkert, Heribert; Vollenweider, Peter; O'Rahilly, Stephen; Deloukas, Panos; Danesh, John; Goodarzi, Mark O.; Kathiresan, Sekar; Meigs, James B.; Ehm, Margaret G.; Wareham, Nicholas J.; Waterworth, Dawn M.

2016-01-01

Regulatory authorities have indicated that new drugs to treat type 2 diabetes (T2D) should not be associated with an unacceptable increase in cardiovascular risk. Human genetics may be able to inform development of antidiabetic therapies by predicting cardiovascular and other health endpoints. We therefore investigated the association of variants in 6 genes that encode drug targets for obesity or T2D with a range of metabolic traits in up to 11,806 individuals by targeted exome sequencing, and follow-up in 39,979 individuals by targeted genotyping, with additional in silico follow up in consortia. We used these data to first compare associations of variants in genes encoding drug targets with the effects of pharmacological manipulation of those targets in clinical trials. We then tested the association those variants with disease outcomes, including coronary heart disease, to predict cardiovascular safety of these agents. A low-frequency missense variant (Ala316Thr;rs10305492) in the gene encoding glucagon-like peptide-1 receptor (GLP1R), the target of GLP1R agonists, was associated with lower fasting glucose and lower T2D risk, consistent with GLP1R agonist therapies. The minor allele was also associated with protection against heart disease, thus providing evidence that GLP1R agonists are not likely to be associated with an unacceptable increase in cardiovascular risk. Our results provide an encouraging signal that these agents may be associated with benefit, a question currently being addressed in randomised controlled trials. Genetic variants associated with metabolic traits and multiple disease outcomes can be used to validate therapeutic targets at an early stage in the drug development process. PMID:27252175

Predicting Pharmacodynamic Drug-Drug Interactions through Signaling Propagation Interference on Protein-Protein Interaction Networks.

PubMed

Park, Kyunghyun; Kim, Docyong; Ha, Suhyun; Lee, Doheon

2015-01-01

As pharmacodynamic drug-drug interactions (PD DDIs) could lead to severe adverse effects in patients, it is important to identify potential PD DDIs in drug development. The signaling starting from drug targets is propagated through protein-protein interaction (PPI) networks. PD DDIs could occur by close interference on the same targets or within the same pathways as well as distant interference through cross-talking pathways. However, most of the previous approaches have considered only close interference by measuring distances between drug targets or comparing target neighbors. We have applied a random walk with restart algorithm to simulate signaling propagation from drug targets in order to capture the possibility of their distant interference. Cross validation with DrugBank and Kyoto Encyclopedia of Genes and Genomes DRUG shows that the proposed method outperforms the previous methods significantly. We also provide a web service with which PD DDIs for drug pairs can be analyzed at http://biosoft.kaist.ac.kr/targetrw.

The processivity factor complex of feline herpes virus-1 is a new drug target.

PubMed

Zhukovskaya, Natalia L; Guan, Hancheng; Saw, Yih Ling; Nuth, Manunya; Ricciardi, Robert P

2015-03-01

Feline herpes virus-1 (FHV-1) is ubiquitous in the cat population and is a major cause of blindness for which antiviral drugs, including acyclovir, are not completely effective. Recurrent infections, due to reactivation of latent FHV-1 residing in the trigeminal ganglia, can lead to epithelial keratitis and stromal keratitis and eventually loss of sight. This has prompted the medical need for an antiviral drug that will specifically inhibit FHV-1 infection. A new antiviral target is the DNA polymerase and its associated processivity factor, which forms a complex that is essential for extended DNA strand synthesis. In this study we have cloned and expressed the FHV-1 DNA polymerase (f-UL30) and processivity factor (f-UL42) and demonstrated that both proteins are required to completely synthesize the 7249 nucleotide full-length DNA from the M13 primed-DNA template in vitro. Significantly, a known inhibitor of human herpes simplex virus-1 (HSV-1) processivity complex was shown to inhibit FHV-1 processive DNA synthesis in vitro and block infection of cells. This validates using f-UL42/f-UL30 as a new antiviral drug target to treat feline ocular herpes infection. Copyright © 2015 Elsevier B.V. All rights reserved.

Current Drug Targets in Obesity Pharmacotherapy - A Review.

PubMed

Bhat, Sangeeta P; Sharma, Arun

2017-01-01

Obesity, an impending global pandemic, is not being effectively controlled by current measures such as lifestyle modifications, bariatric surgery or available medications. Its toll on health and economy compels us to look for more effective measures. Fortunately, the advances in biology and molecular technology have been in our favour for delineating new pathways in the pathophysiology of obesity and have led to subsequent development of new drug targets. Development of antiobesity drugs has often been riddled with problems in the past. Some of the recently approved drugs for pharmacotherapy of obesity have been lorcaserin, phentermine/topiramate and naltrexone/ bupropion combinations. Several promising new targets are currently being evaluated, such as amylin analogues (pramlintide, davalintide), leptin analogues (metreleptin), GLP-1 analogues (exenatide, liraglutide, TTP-054), MC4R agonists (RM-493), oxyntomodulin analogues, neuropeptide Y antagonists (velneperit), cannabinoid type-1 receptor blockers (AM-6545), MetAP2 inhibitors (beloranib), lipase inhibitors (cetilistat) and anti-obesity vaccines (ghrelin, somatostatin, Ad36). Many of these groups of drugs act as "satiety signals" while others act by antagonizing orexigenic signals, increasing fat utilisation and decreasing absorption of fats. Since these targets act through various pathways, the possibility of combined use of two or more classes of these drugs unlocks numerous therapeutic avenues. Hence, the dream of personalized management of obesity might be growing closer to reality. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

[Targeted drug delivery system: potential application to resveratrol].

PubMed

Farghali, Hassan; Kameníková, Ludmila

2017-01-01

Drug delivery system (DDS) is intended to increasing effectiveness of drugs through targeted distribution and to reducing of unwanted effects. In this mini-review, the basic principles of nanotechnology that were developed for DDS were reported including sections on the present research in key areas that are important for future investigations. Attention is paid on resveratrol as a model phytochemical with interesting pharmacologic profile which was demonstrated in great numbers of studies and for its wide use as supplemental therapy. Due to complicated pharmacokinetic profile of resveratrol that is characterized by very low bioavailability in spite of high oral absorption, the effects of resveratrol is being studied in new nanotechnology preparations of pharmaceutical formulation. Herein we report on results of present in vitro and in vivo investigations with resveratrol in new types of drug formulations using different nanoparticles as liposomes, solid lipid particles, cyclodextrins and micelles.Key words: targeted drug delivery nanotechnology resveratrol.

Mathematical description of drug-target interactions: application to biologics that bind to targets with two binding sites.

PubMed

Gibiansky, Leonid; Gibiansky, Ekaterina

2018-02-01

The emerging discipline of mathematical pharmacology occupies the space between advanced pharmacometrics and systems biology. A characteristic feature of the approach is application of advance mathematical methods to study the behavior of biological systems as described by mathematical (most often differential) equations. One of the early application of mathematical pharmacology (that was not called this name at the time) was formulation and investigation of the target-mediated drug disposition (TMDD) model and its approximations. The model was shown to be remarkably successful, not only in describing the observed data for drug-target interactions, but also in advancing the qualitative and quantitative understanding of those interactions and their role in pharmacokinetic and pharmacodynamic properties of biologics. The TMDD model in its original formulation describes the interaction of the drug that has one binding site with the target that also has only one binding site. Following the framework developed earlier for drugs with one-to-one binding, this work aims to describe a rigorous approach for working with similar systems and to apply it to drugs that bind to targets with two binding sites. The quasi-steady-state, quasi-equilibrium, irreversible binding, and Michaelis-Menten approximations of the model are also derived. These equations can be used, in particular, to predict concentrations of the partially bound target (RC). This could be clinically important if RC remains active and has slow internalization rate. In this case, introduction of the drug aimed to suppress target activity may lead to the opposite effect due to RC accumulation.

Changing paradigm from one target one ligand towards multi target directed ligand design for key drug targets of Alzheimer disease: An important role of Insilco methods in multi target directed ligands design.

PubMed

Kumar, Akhil; Tiwari, Ashish; Sharma, Ashok

2018-03-15

Alzheimer disease (AD) is now considered as a multifactorial neurodegenerative disorder and rapidly increasing to an alarming situation and causing higher death rate. One target one ligand hypothesis is not able to provide complete solution of AD due to multifactorial nature of disease and one target one drug seems to fail to provide better treatment against AD. Moreover, current available treatments are limited and most of the upcoming treatments under clinical trials are based on modulating single target. So the current AD drug discovery research shifting towards new approach for better solution that simultaneously modulate more than one targets in the neurodegenerative cascade. This can be achieved by network pharmacology, multi-modal therapies, multifaceted, and/or the more recently proposed term "multi-targeted designed drugs. Drug discovery project is tedious, costly and long term project. Moreover, multi target AD drug discovery added extra challenges such as good binding affinity of ligands for multiple targets, optimal ADME/T properties, no/less off target side effect and crossing of the blood brain barrier. These hurdles may be addressed by insilico methods for efficient solution in less time and cost as computational methods successfully applied to single target drug discovery project. Here we are summarizing some of the most prominent and computationally explored single target against AD and further we discussed successful example of dual or multiple inhibitors for same targets. Moreover we focused on ligand and structure based computational approach to design MTDL against AD. However is not an easy task to balance dual activity in a single molecule but computational approach such as virtual screening docking, QSAR, simulation and free energy are useful in future MTDLs drug discovery alone or in combination with fragment based method. However, rational and logical implementations of computational drug designing methods are capable of assisting AD drug

In Silico Identification of Proteins Associated with Drug-induced Liver Injury Based on the Prediction of Drug-target Interactions.

PubMed

Ivanov, Sergey; Semin, Maxim; Lagunin, Alexey; Filimonov, Dmitry; Poroikov, Vladimir

2017-07-01

Drug-induced liver injury (DILI) is the leading cause of acute liver failure as well as one of the major reasons for drug withdrawal from clinical trials and the market. Elucidation of molecular interactions associated with DILI may help to detect potentially hazardous pharmacological agents at the early stages of drug development. The purpose of our study is to investigate which interactions with specific human protein targets may cause DILI. Prediction of interactions with 1534 human proteins was performed for the dataset with information about 699 drugs, which were divided into three categories of DILI: severe (178 drugs), moderate (310 drugs) and without DILI (211 drugs). Based on the comparison of drug-target interactions predicted for different drugs' categories and interpretation of those results using clustering, Gene Ontology, pathway and gene expression analysis, we identified 61 protein targets associated with DILI. Most of the revealed proteins were linked with hepatocytes' death caused by disruption of vital cellular processes, as well as the emergence of inflammation in the liver. It was found that interaction of a drug with the identified targets is the essential molecular mechanism of the severe DILI for the most of the considered pharmaceuticals. Thus, pharmaceutical agents interacting with many of the identified targets may be considered as candidates for filtering out at the early stages of drug research. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Nanocarrier-mediated drugs targeting cancer stem cells: an emerging delivery approach.

PubMed

Malhi, Sarandeep; Gu, Xiaochen

2015-07-01

Cancer stem cells (CSCs) play an important role in the development of drug resistance, metastasis and recurrence. Current conventional therapies do not commonly target CSCs. Nanocarrier-based delivery systems targeting cancer cells have entered a new era of treatment, where specific targeting to CSCs may offer superior outcomes to efficient cancer therapies. This review discusses the involvement of CSCs in tumor progression and relevant mechanisms associated with CSCs resistance to conventional chemo- and radio-therapies. It highlights CSCs-targeted strategies that are either under evaluation or could be explored in the near future, with a focus on various nanocarrier-based delivery systems of drugs and nucleic acids to CSCs. Novel nanocarriers targeting CSCs are presented in a cancer-specific way to provide a current perspective on anti-CSCs therapeutics. The field of CSCs-targeted therapeutics is still emerging with a few small molecules and macromolecules currently proving efficacy in clinical trials. However considering the complexities of CSCs and existing delivery difficulties in conventional anticancer therapies, CSC-specific delivery systems would face tremendous technical and clinical challenges. Nanocarrier-based approaches have demonstrated significant potential in specific drug delivery and targeting; their success in CSCs-targeted drug delivery would not only significantly enhance anticancer treatment but also address current difficulties associated with cancer resistance, metastasis and recurrence.

Mononuclear phagocytes as a target, not a barrier, for drug delivery.

PubMed

Yong, Seok-Beom; Song, Yoonsung; Kim, Hyung Jin; Ain, Qurrat Ul; Kim, Yong-Hee

2017-08-10

Mononuclear phagocytes have been generally recognized as a barrier to drug delivery. Recently, a new understanding of mononuclear phagocytes (MPS) ontogeny has surfaced and their functions in disease have been unveiled, demonstrating the need for re-evaluation of perspectives on mononuclear phagocytes in drug delivery. In this review, we described mononuclear phagocyte biology and focus on their accumulation mechanisms in disease sites with explanations of monocyte heterogeneity. In the 'MPS as a barrier' section, we summarized recent studies on mechanisms to avoid phagocytosis based on two different biological principles: protein adsorption and self-recognition. In the 'MPS as a target' section, more detailed descriptions were given on mononuclear phagocyte-targeted drug delivery systems and their applications to various diseases. Collectively, we emphasize in this review that mononuclear phagocytes are potent targets for future drug delivery systems. Mononuclear phagocyte-targeted delivery systems should be created with an understanding of mononuclear phagocyte ontogeny and pathology. Each specific subset of phagocytes should be targeted differently by location and function for improved disease-drug delivery while avoiding RES clearance such as Kupffer cells and splenic macrophages. Copyright © 2017 Elsevier B.V. All rights reserved.

Aminoacyl-tRNA synthetases as drug targets in eukaryotic parasites☆

PubMed Central

Pham, James S.; Dawson, Karen L.; Jackson, Katherine E.; Lim, Erin E.; Pasaje, Charisse Flerida A.; Turner, Kelsey E.C.; Ralph, Stuart A.

2013-01-01

Aminoacyl-tRNA synthetases are central enzymes in protein translation, providing the charged tRNAs needed for appropriate construction of peptide chains. These enzymes have long been pursued as drug targets in bacteria and fungi, but the past decade has seen considerable research on aminoacyl-tRNA synthetases in eukaryotic parasites. Existing inhibitors of bacterial tRNA synthetases have been adapted for parasite use, novel inhibitors have been developed against parasite enzymes, and tRNA synthetases have been identified as the targets for compounds in use or development as antiparasitic drugs. Crystal structures have now been solved for many parasite tRNA synthetases, and opportunities for selective inhibition are becoming apparent. For different biological reasons, tRNA synthetases appear to be promising drug targets against parasites as diverse as Plasmodium (causative agent of malaria), Brugia (causative agent of lymphatic filariasis), and Trypanosoma (causative agents of Chagas disease and human African trypanosomiasis). Here we review recent developments in drug discovery and target characterisation for parasite aminoacyl-tRNA synthetases. PMID:24596663

Identification and Validation of Small-Gatekeeper Kinases as Drug Targets in Giardia lamblia

PubMed Central

Hennessey, Kelly M.; Smith, Tess R.; Xu, Jennifer W.; Alas, Germain C. M.; Ojo, Kayode K.; Merritt, Ethan A.

2016-01-01

Giardiasis is widely acknowledged to be a neglected disease in need of new therapeutics to address toxicity and resistance issues associated with the limited available treatment options. We examined seven protein kinases in the Giardia lamblia genome that are predicted to share an unusual structural feature in their active site. This feature, an expanded active site pocket resulting from an atypically small gatekeeper residue, confers sensitivity to “bumped” kinase inhibitors (BKIs), a class of compounds that has previously shown good pharmacological properties and minimal toxicity. An initial phenotypic screen for biological activity using a subset of an in-house BKI library found that 5 of the 36 compounds tested reduced trophozoite growth by at least 50% at a concentration of 5 μM. The cellular localization and the relative expression levels of the seven protein kinases of interest were determined after endogenously tagging the kinases. Essentiality of these kinases for parasite growth and infectivity were evaluated genetically using morpholino knockdown of protein expression to establish those that could be attractive targets for drug design. Two of the kinases were critical for trophozoite growth and attachment. Therefore, recombinant enzymes were expressed, purified and screened against a BKI library of >400 compounds in thermal stability assays in order to identify high affinity compounds. Compounds with substantial thermal stabilization effects on recombinant protein were shown to have good inhibition of cell growth in wild-type G. lamblia and metronidazole-resistant strains of G. lamblia. Our data suggest that BKIs are a promising starting point for the development of new anti-giardiasis therapeutics that do not overlap in mechanism with current drugs. PMID:27806042

System-level multi-target drug discovery from natural products with applications to cardiovascular diseases.

PubMed

Zheng, Chunli; Wang, Jinan; Liu, Jianling; Pei, Mengjie; Huang, Chao; Wang, Yonghua

2014-08-01

The term systems pharmacology describes a field of study that uses computational and experimental approaches to broaden the view of drug actions rooted in molecular interactions and advance the process of drug discovery. The aim of this work is to stick out the role that the systems pharmacology plays across the multi-target drug discovery from natural products for cardiovascular diseases (CVDs). Firstly, based on network pharmacology methods, we reconstructed the drug-target and target-target networks to determine the putative protein target set of multi-target drugs for CVDs treatment. Secondly, we reintegrated a compound dataset of natural products and then obtained a multi-target compounds subset by virtual-screening process. Thirdly, a drug-likeness evaluation was applied to find the ADME-favorable compounds in this subset. Finally, we conducted in vitro experiments to evaluate the reliability of the selected chemicals and targets. We found that four of the five randomly selected natural molecules can effectively act on the target set for CVDs, indicating the reasonability of our systems-based method. This strategy may serve as a new model for multi-target drug discovery of complex diseases.

Food and Drug Administration Perspective on Negative Symptoms in Schizophrenia as a Target for a Drug Treatment Claim

PubMed Central

Laughren, Thomas; Levin, Robert

2006-01-01

Negative symptoms of schizophrenia are not adequately addressed by available treatments for schizophrenia. Thus, it is reasonable to consider them as a target for a drug claim. This article describes the thought process that the Food and Drug Administration (FDA) will undertake in considering negative symptoms of schizophrenia as a novel and distinct drug target. Beyond this basic question, this article identifies a number of design issues that the FDA needs to consider regarding how best to conduct studies to support claims for this target. These design issues include (1) what population to study, (2) what phase of illness to target, (3) whether to focus on the negative symptom domain overall or on some specific aspect of negative symptoms, (4) the role of functional measures in negative symptom trials, and (5) optimal designs for targeting drugs for add-on therapy or broad-spectrum agents. PMID:16079389

Identification and characterization of potential druggable targets among hypothetical proteins of extensively drug resistant Mycobacterium tuberculosis (XDR KZN 605) through subtractive genomics approach.

PubMed

Uddin, Reaz; Siddiqui, Quratulain Nehal; Azam, Syed Sikander; Saima, Bibi; Wadood, Abdul

2018-03-01

Among the resistant isolates of tuberculosis (TB), the multidrug resistance tuberculosis (MDR-TB) and extensively drug resistant tuberculosis (XDR-TB) are the areas of growing concern for which the front-line antibiotics are no more effective. As a result, the search of new therapeutic targets against TB is an imperative need of time. On the other hand, the target identification is an a priori step in drug discovery based research. Furthermore, the availability of the complete proteomic data of extensively drug resistant Mycobacterium tuberculosis (XDR-MTB) made it possible to carry out in silico analysis for the discovery of new drug targets. In the current study, we aimed to prioritize the potential drug targets among the hypothetical proteins of XDR-TB via subtractive genomics approach. In the subtractive genomics, we stepwise reduced the complete proteome of XDR-MTB to only two hypothetical proteins and evidently proposed them as new therapeutic targets. The 3D structure of one of the two target proteins was predicted via homology modeling and later on, validated by various analysis tools. Our study suggested that the domains identified and the motif hits found in the sequences of the shortlisted drug targets are crucial for the survival of the XDR-MTB. To the best of our knowledge, the current study is the first attempt in which the complete proteomic data of XDR-MTB was subjected to the computational subtractive genomics approach and therefore, would provide an opportunity to identify the unique therapeutic targets against deadly XDR-MTB. Copyright © 2017 Elsevier B.V. All rights reserved.

Is Bacterial Fatty Acid Synthesis a Valid Target for Antibacterial Drug Discovery?

PubMed Central

Parsons, Joshua B.; Rock, Charles O.

2011-01-01

The emergence of resistance against most current drugs emphasizes the need to develop new approaches to control bacterial pathogens, particularly Staphylococcus aureus. Bacterial fatty acid synthesis is one such target that is being actively pursued by several research groups to develop anti-Staphylococcal agents. Recently, the wisdom of this approach has been challenged based on the ability of a Gram-positive bacterium to incorporate extracellular fatty acids and thus circumvent the inhibition of de novo fatty acid synthesis. The generality of this conclusion has been challenged, and there is enough diversity in the enzymes and regulation of fatty acid synthesis in bacteria to conclude that there isn’t a single organism that can be considered typical and representative of bacteria as a whole. We are left without a clear resolution to this ongoing debate and await new basic research to define the pathways for fatty acid uptake and that determine the biochemical and genetic mechanisms for the regulation of fatty acid synthesis in Gram-positive bacteria. These crucial experiments will determine whether diversity in the control of this important pathway accounts for the apparently different responses of Gram-positive bacteria to the inhibition of de novo fatty acid synthesis in presence of extracellular fatty acid supplements. PMID:21862391

Smart linkers in polymer-drug conjugates for tumor-targeted delivery.

PubMed

Chang, Minglu; Zhang, Fang; Wei, Ting; Zuo, Tiantian; Guan, Yuanyuan; Lin, Guimei; Shao, Wei

2016-01-01

To achieve effective chemotherapy, many types of drug delivery systems have been developed for the specific environments in tumor tissues. Polymer-drug conjugates are increasingly used in tumor therapy due to several significant advantages over traditional delivery systems. In the fabrication of polymer-drug conjugates, a smart linker is an important component that joins two fragments or molecules together and can be cleared by a specific stimulus, which results in targeted drug delivery and controlled release. By regulating the conjugation between the drug and the nanocarriers, stimulus-sensitive systems based on smart linkers can offer high payloads, certified stability, controlled release and targeted delivery. In this review, we summarize the current state of smart linkers (e.g. disulfide, hydrazone, peptide, azo) used recently in various polymer-drug conjugate-based delivery systems with a primary focus on their sophisticated design principles and drug delivery mechanisms as well as in vivo processes.

The relationship between target-class and the physicochemical properties of antibacterial drugs

PubMed Central

Mugumbate, Grace; Overington, John P.

2015-01-01

The discovery of novel mechanism of action (MOA) antibacterials has been associated with the concept that antibacterial drugs occupy a differentiated region of physicochemical space compared to human-targeted drugs. With, in broad terms, antibacterials having higher molecular weight, lower log P and higher polar surface area (PSA). By analysing the physicochemical properties of about 1700 approved drugs listed in the ChEMBL database, we show, that antibacterials for whose targets are riboproteins (i.e., composed of a complex of RNA and protein) fall outside the conventional human ‘drug-like’ chemical space; whereas antibacterials that modulate bacterial protein targets, generally comply with the ‘rule-of-five’ guidelines for classical oral human drugs. Our analysis suggests a strong target-class association for antibacterials—either protein-targeted or riboprotein-targeted. There is much discussion in the literature on the failure of screening approaches to deliver novel antibacterial lead series, and linkage of this poor success rate for antibacterials with the chemical space properties of screening collections. Our analysis suggests that consideration of target-class may be an underappreciated factor in antibacterial lead discovery, and that in fact bacterial protein-targets may well have similar binding site characteristics to human protein targets, and questions the assumption that larger, more polar compounds are a key part of successful future antibacterial discovery. PMID:25975639

Prediction of intracellular exposure bridges the gap between target- and cell-based drug discovery

PubMed Central

Gordon, Laurie J.; Wayne, Gareth J.; Almqvist, Helena; Axelsson, Hanna; Seashore-Ludlow, Brinton; Treyer, Andrea; Lundbäck, Thomas; West, Andy; Hann, Michael M.; Artursson, Per

2017-01-01

Inadequate target exposure is a major cause of high attrition in drug discovery. Here, we show that a label-free method for quantifying the intracellular bioavailability (Fic) of drug molecules predicts drug access to intracellular targets and hence, pharmacological effect. We determined Fic in multiple cellular assays and cell types representing different targets from a number of therapeutic areas, including cancer, inflammation, and dementia. Both cytosolic targets and targets localized in subcellular compartments were investigated. Fic gives insights on membrane-permeable compounds in terms of cellular potency and intracellular target engagement, compared with biochemical potency measurements alone. Knowledge of the amount of drug that is locally available to bind intracellular targets provides a powerful tool for compound selection in early drug discovery. PMID:28701380

The application of carbon nanotubes in target drug delivery systems for cancer therapies

NASA Astrophysics Data System (ADS)

Zhang, Wuxu; Zhang, Zhenzhong; Zhang, Yingge

2011-10-01

Among all cancer treatment options, chemotherapy continues to play a major role in killing free cancer cells and removing undetectable tumor micro-focuses. Although chemotherapies are successful in some cases, systemic toxicity may develop at the same time due to lack of selectivity of the drugs for cancer tissues and cells, which often leads to the failure of chemotherapies. Obviously, the therapeutic effects will be revolutionarily improved if human can deliver the anticancer drugs with high selectivity to cancer cells or cancer tissues. This selective delivery of the drugs has been called target treatment. To realize target treatment, the first step of the strategies is to build up effective target drug delivery systems. Generally speaking, such a system is often made up of the carriers and drugs, of which the carriers play the roles of target delivery. An ideal carrier for target drug delivery systems should have three pre-requisites for their functions: (1) they themselves have target effects; (2) they have sufficiently strong adsorptive effects for anticancer drugs to ensure they can transport the drugs to the effect-relevant sites; and (3) they can release the drugs from them in the effect-relevant sites, and only in this way can the treatment effects develop. The transporting capabilities of carbon nanotubes combined with appropriate surface modifications and their unique physicochemical properties show great promise to meet the three pre-requisites. Here, we review the progress in the study on the application of carbon nanotubes as target carriers in drug delivery systems for cancer therapies.

Nanostructured porous Si-based nanoparticles for targeted drug delivery

PubMed Central

Shahbazi, Mohammad-Ali; Herranz, Barbara; Santos, Hélder A.

2012-01-01

One of the backbones in nanomedicine is to deliver drugs specifically to unhealthy cells. Drug nanocarriers can cross physiological barriers and access different tissues, which after proper surface biofunctionalization can enhance cell specificity for cancer therapy. Recent developments have highlighted the potential of mesoporous silica (PSiO2) and silicon (PSi) nanoparticles for targeted drug delivery. In this review, we outline and discuss the most recent advances on the applications and developments of cancer therapies by means of PSiO2 and PSi nanomaterials. Bio-engineering and fine tuning of anti-cancer drug vehicles, high flexibility and potential for sophisticated release mechanisms make these nanostructures promising candidates for “smart” cancer therapies. As a result of their physicochemical properties they can be controllably loaded with large amounts of drugs and coupled to homing molecules to facilitate active targeting. The main emphasis of this review will be on the in vitro and in vivo studies. PMID:23507894

How many genomics targets can a portfolio afford?

PubMed

Betz, Ulrich A K

2005-08-01

The pharmaceutical industry can look back at a history of successful innovations. Although genomics technologies have provided drug discovery pipelines with a plethora of new potential drug targets, solid target validation is crucial to avoiding high attrition rates. Biomarkers for patient stratification and approaches for personalized medicine will further help to reduce the risk associated with new targets. To achieve an overall risk balance, portfolios have to be supplemented with precedented targets, me-too approaches and line extensions of existing drugs. However, capitalizing on genomics investments and working on unprecedented targets is essential for a continuous stream of innovative drugs.

Contact-facilitated drug delivery with Sn2 lipase labile prodrugs optimize targeted lipid nanoparticle drug delivery.

PubMed

Pan, Dipanjan; Pham, Christine T N; Weilbaecher, Katherine N; Tomasson, Michael H; Wickline, Samuel A; Lanza, Gregory M

2016-01-01

Sn2 lipase labile phospholipid prodrugs in conjunction with contact-facilitated drug delivery offer an important advancement in Nanomedicine. Many drugs incorporated into nanosystems, targeted or not, are substantially lost during circulation to the target. However, favorably altering the pharmacokinetics and volume of distribution of systemic drug delivery can offer greater efficacy with lower toxicity, leading to new prolonged-release nanoexcipients. However, the concept of achieving Paul Erhlich's inspired vision of a 'magic bullet' to treat disease has been largely unrealized due to unstable nanomedicines, nanosystems achieving low drug delivery to target cells, poor intracellular bioavailability of endocytosed nanoparticle payloads, and the substantial biological barriers of extravascular particle penetration into pathological sites. As shown here, Sn2 phospholipid prodrugs in conjunction with contact-facilitated drug delivery prevent premature drug diffusional loss during circulation and increase target cell bioavailability. The Sn2 phospholipid prodrug approach applies equally well for vascular constrained lipid-encapsulated particles and micelles the size of proteins that penetrate through naturally fenestrated endothelium in the bone marrow or thin-walled venules of an inflamed microcirculation. At one time Nanomedicine was considered a 'Grail Quest' by its loyal opposition and even many in the field adsorbing the pains of a long-learning curve about human biology and particles. However, Nanomedicine with innovations like Sn2 phospholipid prodrugs has finally made 'made the turn' toward meaningful translational success. © 2015 The Authors. WIREs Nanomedicine and Nanobiotechnology published by Wiley Periodicals, Inc.

Contact-facilitated drug delivery with Sn2 lipase labile prodrugs optimize targeted lipid nanoparticle drug delivery

PubMed Central

Pan, Dipanjan; Pham, Christine TN; Weilbaecher, Katherine N; Tomasson, Michael H; Wickline, Samuel A; Lanza, Gregory M

2016-01-01

Sn2 lipase labile phospholipid prodrugs in conjunction with contact-facilitated drug delivery offer an important advancement in Nanomedicine. Many drugs incorporated into nanosystems, targeted or not, are substantially lost during circulation to the target. However, favorably altering the pharmacokinetics and volume of distribution of systemic drug delivery can offer greater efficacy with lower toxicity, leading to new prolonged-release nanoexcipients. However, the concept of achieving Paul Erhlich's inspired vision of a ‘magic bullet’ to treat disease has been largely unrealized due to unstable nanomedicines, nanosystems achieving low drug delivery to target cells, poor intracellular bioavailability of endocytosed nanoparticle payloads, and the substantial biological barriers of extravascular particle penetration into pathological sites. As shown here, Sn2 phospholipid prodrugs in conjunction with contact-facilitated drug delivery prevent premature drug diffusional loss during circulation and increase target cell bioavailability. The Sn2 phospholipid prodrug approach applies equally well for vascular constrained lipid-encapsulated particles and micelles the size of proteins that penetrate through naturally fenestrated endothelium in the bone marrow or thin-walled venules of an inflamed microcirculation. At one time Nanomedicine was considered a ‘Grail Quest’ by its loyal opposition and even many in the field adsorbing the pains of a long-learning curve about human biology and particles. However, Nanomedicine with innovations like Sn2 phospholipid prodrugs has finally made ‘made the turn’ toward meaningful translational success. PMID:26296541

Liposomes and nanotechnology in drug development: focus on ocular targets

PubMed Central

Honda, Miki; Asai, Tomohiro; Oku, Naoto; Araki, Yoshihiko; Tanaka, Minoru; Ebihara, Nobuyuki

2013-01-01

Poor drug delivery to lesions in patients’ eyes is a major obstacle to the treatment of ocular diseases. The accessibility of these areas to drugs is highly restricted by the presence of barriers, including the corneal barrier, aqueous barrier, and the inner and outer blood–retinal barriers. In particular, the posterior segment is difficult to reach for drugs because of its structural peculiarities. This review discusses various barriers to drug delivery and provides comprehensive information for designing nanoparticle-mediated drug delivery systems for the treatment of ocular diseases. Nanoparticles can be designed to improve penetration, controlled release, and drug targeting. As highlighted in this review, the therapeutic efficacy of drugs in ocular diseases has been reported to be enhanced by the use of nanoparticles such as liposomes, micro/nanospheres, microemulsions, and dendrimers. Our recent data show that intravitreal injection of targeted liposomes encapsulating an angiogenesis inhibitor caused significantly greater suppression of choroidal neovascularization than did the injection of free drug. Recent progress in ocular drug delivery systems research has provided new insights into drug development, and the use of nanoparticles for drug delivery is thus a promising approach for advanced therapy of ocular diseases. PMID:23439842

Challenges in validating candidate therapeutic targets in cancer

PubMed Central

Sawyers, Charles L; Hunter, Tony

2018-01-01

More than 30 published articles have suggested that a protein kinase called MELK is an attractive therapeutic target in human cancer, but three recent reports describe compelling evidence that it is not. These reports highlight the caveats associated with some of the research tools that are commonly used to validate candidate therapeutic targets in cancer research. PMID:29417929

Targeted proteins for diabetes drug design

NASA Astrophysics Data System (ADS)

Doan Trang Nguyen, Ngoc; Thi Le, Ly

2012-03-01

Type 2 diabetes mellitus is a common metabolism disorder characterized by high glucose in the bloodstream, especially in the case of insulin resistance and relative insulin deficiency. Nowadays, it is very common in middle-aged people and involves such dangerous symptoms as increasing risk of stroke, obesity and heart failure. In Vietnam, besides the common treatment of insulin injection, some herbal medication is used but no unified optimum remedy for the disease yet exists and there is no production of antidiabetic drugs in the domestic market yet. In the development of nanomedicine at the present time, drug design is considered as an innovative tool for researchers to study the mechanisms of diseases at the molecular level. The aim of this article is to review some common protein targets involved in type 2 diabetes, offering a new idea for designing new drug candidates to produce antidiabetic drugs against type 2 diabetes for Vietnamese people.

Development and Validation of the Appearance and Performance Enhancing Drug Use Schedule

PubMed Central

Langenbucher, James W.; Lai, Justine Karmin; Loeb, Katharine L.; Hollander, Eric

2011-01-01

Appearance-and-performance enhancing drug (APED) use is a form of drug use that includes use of a wide range of substances such as anabolic-androgenic steroids (AASs) and associated behaviors including intense exercise and dietary control. To date, there are no reliable or valid measures of the core features of APED use. The present study describes the development and psychometric evaluation of the Appearance and Performance Enhancing Drug Use Schedule (APEDUS) which is a semi-structured interview designed to assess the spectrum of drug use and related features of APED use. Eighty-five current APED using men and women (having used an illicit APED in the past year and planning to use an illicit APED in the future) completed the APEDUS and measures of convergent and divergent validity. Inter-rater agreement, scale reliability, one-week test-retest reliability, convergent and divergent validity, and construct validity were evaluated for each of the APEDUS scales. The APEDUS is a modular interview with 10 sections designed to assess the core drug and non-drug phenomena associated with APED use. All scales and individual items demonstrated high inter-rater agreement and reliability. Individual scales significantly correlated with convergent measures (DSM-IV diagnoses, aggression, impulsivity, eating disorder pathology) and were uncorrelated with a measure of social desirability. APEDUS subscale scores were also accurate measures of AAS dependence. The APEDUS is a reliable and valid measure of APED phenomena and an accurate measure of the core pathology associated with APED use. Issues with assessing APED use are considered and future research considered. PMID:21640487

Rhamnogalacturonan-I Based Microcapsules for Targeted Drug Release

PubMed Central

Kusic, Anja; De Gobba, Cristian; Larsen, Flemming H.; Sassene, Philip; Zhou, Qi; van de Weert, Marco; Mullertz, Anette; Jørgensen, Bodil; Ulvskov, Peter

2016-01-01

Drug targeting to the colon via the oral administration route for local treatment of e.g. inflammatory bowel disease and colonic cancer has several advantages such as needle-free administration and low infection risk. A new source for delivery is plant-polysaccharide based delivery platforms such as Rhamnogalacturonan-I (RG-I). In the gastro-intestinal tract the RG-I is only degraded by the action of the colonic microflora. For assessment of potential drug delivery properties, RG-I based microcapsules (~1 μm in diameter) were prepared by an interfacial poly-addition reaction. The cross-linked capsules were loaded with a fluorescent dye (model drug). The capsules showed negligible and very little in vitro release when subjected to media simulating gastric and intestinal fluids, respectively. However, upon exposure to a cocktail of commercial RG-I cleaving enzymes, ~ 9 times higher release was observed, demonstrating that the capsules can be opened by enzymatic degradation. The combined results suggest a potential platform for targeted drug delivery in the terminal gastro-intestinal tract. PMID:27992455

Fe3O4 Nanoparticles in Targeted Drug/Gene Delivery Systems

PubMed Central

Shen, Lazhen; Li, Bei; Qiao, Yongsheng

2018-01-01

Fe3O4 nanoparticles (NPs), the most traditional magnetic nanoparticles, have received a great deal of attention in the biomedical field, especially for targeted drug/gene delivery systems, due to their outstanding magnetism, biocompatibility, lower toxicity, biodegradability, and other features. Naked Fe3O4 NPs are easy to aggregate and oxidize, and thus are often made with various coatings to realize superior properties for targeted drug/gene delivery. In this review, we first list the three commonly utilized synthesis methods of Fe3O4 NPs, and their advantages and disadvantages. In the second part, we describe coating materials that exhibit noticeable features that allow functionalization of Fe3O4 NPs and summarize their methods of drug targeting/gene delivery. Then our efforts will be devoted to the research status and progress of several different functionalized Fe3O4 NP delivery systems loaded with chemotherapeutic agents, and we present targeted gene transitive carriers in detail. In the following section, we illuminate the most effective treatment systems of the combined drug and gene therapy. Finally, we propose opportunities and challenges of the clinical transformation of Fe3O4 NPs targeting drug/gene delivery systems. PMID:29473914

Encapsulation of methotrexate loaded magnetic microcapsules for magnetic drug targeting and controlled drug release

NASA Astrophysics Data System (ADS)

Chakkarapani, Prabu; Subbiah, Latha; Palanisamy, Selvamani; Bibiana, Arputha; Ahrentorp, Fredrik; Jonasson, Christian; Johansson, Christer

2015-04-01

We report on the development and evaluation of methotrexate magnetic microcapsules (MMC) for targeted rheumatoid arthritis therapy. Methotrexate was loaded into CaCO3-PSS (poly (sodium 4-styrenesulfonate)) doped microparticles that were coated successively with poly (allylamine hydrochloride) and poly (sodium 4-styrenesulfonate) by layer-by-layer technique. Ferrofluid was incorporated between the polyelectrolyte layers. CaCO3-PSS core was etched by incubation with EDTA yielding spherical MMC. The MMC were evaluated for various physicochemical, pharmaceutical parameters and magnetic properties. Surface morphology, crystallinity, particle size, zeta potential, encapsulation efficiency, loading capacity, drug release pattern, release kinetics and AC susceptibility studies revealed spherical particles of ~3 μm size were obtained with a net zeta potential of +24.5 mV, 56% encapsulation and 18.6% drug loading capacity, 96% of cumulative drug release obeyed Hixson-Crowell model release kinetics. Drug excipient interaction, surface area, thermal and storage stability studies for the prepared MMC was also evaluated. The developed MMC offer a promising mode of targeted and sustained release drug delivery for rheumatoid arthritis therapy.

Emerging drugs which target the renin-angiotensin-aldosterone system.

PubMed

Steckelings, Ulrike Muscha; Paulis, Ludovit; Unger, Thomas; Bader, Michael

2011-12-01

The renin-angiotensin-aldosterone system (RAAS) is already the most important target for drugs in the cardiovascular system. However, still new developments are underway to interfere with the system on different levels. The novel strategies to interfere with RAAS aim to reduce the synthesis of the two major RAAS effector hormones, angiotensin (Ang) II and aldosterone, or interfere with their receptors, AT1 and mineralocorticoid receptor, respectively. Moreover, novel targets have been identified in RAAS, such as the (pro)renin receptor, and molecules, which counteract the classical actions of Ang II and are therefore beneficial in cardiovascular diseases. These include the AT2 receptor and the ACE2/Ang-(1-7)/Mas axis. The search for drugs activating these tissue-protective arms of RAAS is therefore the most innovative field in RAAS pharmacology. Most of the novel pharmacological strategies to inhibit the classical RAAS need to prove their superiority above the existing treatment in clinical trials and then have to compete against these now quite cheap drugs in a competitive market. The newly discovered targets have functions beyond the cardiovascular system opening up novel therapeutic areas for drugs interfering with RAAS components.

Inhaled Micro/Nanoparticulate Anticancer Drug Formulations: An Emerging Targeted Drug Delivery Strategy for Lung Cancers.

PubMed

Islam, Nazrul; Richard, Derek

2018-05-24

Local delivery of drug to the target organ via inhalation offers enormous benefits in the management of many diseases. Lung cancer is the most common of all cancers and it is the leading cause of death worldwide. Currently available treatment systems (intravenous or oral drug delivery) are not efficient in accumulating the delivered drug into the target tumor cells and are usually associated with various systemic and dose-related adverse effects. The pulmonary drug delivery technology would enable preferential accumulation of drug within the cancer cell and thus be superior to intravenous and oral delivery in reducing cancer cell proliferation and minimising the systemic adverse effects. Site-specific drug delivery via inhalation for the treatment of lung cancer is both feasible and efficient. The inhaled drug delivery system is non-invasive, produces high bioavailability at low dose and avoids first pass metabolism of the delivered drug. Various anticancer drugs including chemotherapeutics, proteins and genes have been investigated for inhalation in lung cancers with significant outcomes. Pulmonary delivery of drugs from dry powder inhaler (DPI) formulation is stable and has high patient compliance. Herein, we report the potential of pulmonary drug delivery from dry powder inhaler (DPI) formulations inhibiting lung cancer cell proliferation at very low dose with reduced unwanted adverse effects. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

NIH tools facilitate matching cancer drugs with gene targets

Cancer.gov

A new study details how a suite of web-based tools provides the research community with greatly improved capacity to compare data derived from large collections of genomic information against thousands of drugs. By comparing drugs and genetic targets, re

Cartilage-targeting drug delivery: can electrostatic interactions help?

PubMed

Bajpayee, Ambika G; Grodzinsky, Alan J

2017-03-01

Current intra-articular drug delivery methods do not guarantee sufficient drug penetration into cartilage tissue to reach cell and matrix targets at the concentrations necessary to elicit the desired biological response. Here, we provide our perspective on the utilization of charge-charge (electrostatic) interactions to enhance drug penetration and transport into cartilage, and to enable sustained binding of drugs within the tissue's highly negatively charged extracellular matrix. By coupling drugs to positively charged nanocarriers that have optimal size and charge, cartilage can be converted from a drug barrier into a drug reservoir for sustained intra-tissue delivery. Alternatively, a wide variety of drugs themselves can be made cartilage-penetrating by functionalizing them with specialized positively charged protein domains. Finally, we emphasize that appropriate animal models, with cartilage thickness similar to that of humans, must be used for the study of drug transport and retention in cartilage.

Sodium dependent multivitamin transporter (SMVT): a potential target for drug delivery.

PubMed

Vadlapudi, Aswani Dutt; Vadlapatla, Ramya Krishna; Mitra, Ashim K

2012-06-01

Sodium dependent multivitamin transporter (SMVT; product of the SLC5A6 gene) is an important transmembrane protein responsible for translocation of vitamins and other essential cofactors such as biotin, pantothenic acid and lipoic acid. Hydropathy plot (Kyte-Dolittle algorithm) revealed that human SMVT protein consists of 635 amino acids and 12 transmembrane domains with both amino and carboxyl termini oriented towards the cytoplasm. SMVT is expressed in various tissues such as placenta, intestine, brain, liver, lung, kidney, cornea, retina and heart. This transporter displays broad substrate specificity and excellent capacity for utilization in drug delivery. Drug absorption is often limited by the presence of physiological (epithelial tight junctions), biochemical (efflux transporters and enzymatic degradation) and chemical (size, lipophilicity, molecular weight, charge etc.) barriers. These barriers may cause many potential therapeutics to be dropped from the preliminary screening portfolio and subsequent entry into the market. Transporter targeted delivery has become a powerful approach to deliver drugs to target tissues because of the ability of the transporter to translocate the drug to intracellular organelles at a higher rate. This review highlights studies employing SMVT transporter as a target for drug delivery to improve bioavailability and investigate the feasibility of developing SMVT targeted drug delivery systems.

Anticancer drug delivery with transferrin targeted polymeric chitosan vesicles.

PubMed

Dufes, Christine; Muller, Jean-Marc; Couet, William; Olivier, Jean-Christophe; Uchegbu, Ijeoma F; Schätzlein, Andreas G

2004-01-01

The study reports the initial biological evaluation of targeted polymeric glycol chitosan vesicles as carrier systems for doxorubicin (Dox). Transferrin (Tf) was covalently bound to the Dox-loaded palmitoylated glycol chitosan (GCP) vesicles using dimethylsuberimidate (DMSI). For comparison, glucose targeted niosomes were prepared using N-palmitoyl glucosamine. Biological properties were studied using confocal microscopy, flow cytometry, and cytotoxicity assays as well as a mouse xenograft model. Tf vesicles were taken up rapidly with a plateau after 1-2 h and Dox reached the nucleus after 60-90 min. Uptake was not increased with the use of glucose ligands, but higher uptake and increased cytotoxicity were observed for Tf targeted as compared to GCP Dox alone. In the drug-resistant A2780AD cells and in A431 cells, the relative increase in activity was significantly higher for the Tf-GCP vesicles than would have been expected from the uptake studies. All vesicle formulations had a superior in vivo safety profile compared to the free drug. The in vitro advantage of targeted Tf vesicles did not translate into a therapeutic advantage in vivo. All vesicles reduced tumor size on day 2 but were overall less active than the free drug.

Recent developments in anticancer drug delivery using cell penetrating and tumor targeting peptides.

PubMed

Dissanayake, Shama; Denny, William A; Gamage, Swarna; Sarojini, Vijayalekshmi

2017-03-28

Efficient intracellular trafficking and targeted delivery to the site of action are essential to overcome the current drawbacks of cancer therapeutics. Cell Penetrating Peptides (CPPs) offer the possibility of efficient intracellular trafficking, and, therefore the development of drug delivery systems using CPPs as cargo carriers is an attractive strategy to address the current drawbacks of cancer therapeutics. Additionally, the possibility of incorporating Tumor Targeting Peptides (TTPs) into the delivery system provides the necessary drug targeting effect. Therefore the conjugation of CPPs and/or TTPs with therapeutics provides a potentially efficient method of improving intracellular drug delivery mechanisms. Peptides used as cargo carriers in DDS have been shown to enhance the cellular uptake of drugs and thereby provide an efficient therapeutic benefit over the drug on its own. After providing a brief overview of various drug targeting approaches, this review focusses on peptides as carriers and targeting moieties in drug-peptide covalent conjugates and summarizes the most recent literature examples where CPPs on their own or CPPs together with TTPs have been conjugated to anticancer drugs such as Doxorubicin, Methotrexate, Paclitaxel, Chlorambucil etc. A short section on CPPs used in multicomponent drug delivery systems is also included. Copyright © 2017 Elsevier B.V. All rights reserved.

Colon-targeted oral drug delivery systems: design trends and approaches.

PubMed

Amidon, Seth; Brown, Jack E; Dave, Vivek S

2015-08-01

Colon-specific drug delivery systems (CDDS) are desirable for the treatment of a range of local diseases such as ulcerative colitis, Crohn's disease, irritable bowel syndrome, chronic pancreatitis, and colonic cancer. In addition, the colon can be a potential site for the systemic absorption of several drugs to treat non-colonic conditions. Drugs such as proteins and peptides that are known to degrade in the extreme gastric pH, if delivered to the colon intact, can be systemically absorbed by colonic mucosa. In order to achieve effective therapeutic outcomes, it is imperative that the designed delivery system specifically targets the drugs into the colon. Several formulation approaches have been explored in the development colon-targeted drug delivery systems. These approaches involve the use of formulation components that interact with one or more aspects of gastrointestinal (GI) physiology, such as the difference in the pH along the GI tract, the presence of colonic microflora, and enzymes, to achieve colon targeting. This article highlights the factors influencing colon-specific drug delivery and colonic bioavailability, and the limitations associated with CDDS. Further, the review provides a systematic discussion of various conventional, as well as relatively newer formulation approaches/technologies currently being utilized for the development of CDDS.

Aptamers as tools for target prioritization and lead identification.

PubMed

Burgstaller, Petra; Girod, Anne; Blind, Michael

2002-12-15

The increasing number of potential drug target candidates has driven the development of novel technologies designed to identify functionally important targets and enhance the subsequent lead discovery process. Highly specific synthetic nucleic acid ligands--also known as aptamers--offer a new exciting route in the drug discovery process by linking target validation directly with HTS. Recently, aptamers have proven to be valuable tools for modulating the function of endogenous cellular proteins in their natural environment. A set of technologies has been developed to use these sophisticated ligands for the validation of potential drug targets in disease models. Moreover, aptamers that are specific antagonists of protein function can act as substitute interaction partners in HTS assays to facilitate the identification of small-molecule lead compounds.

Anticancer drug development from traditional cytotoxic to targeted therapies: evidence of shorter drug research and development time, and shorter drug lag in Japan.

PubMed

Kawabata-Shoda, E; Masuda, S; Kimura, H

2012-10-01

Concern about the drug lag, the delay in marketing approval between one country and another, for anticancer drugs has increased in Japan. Although a number of studies have investigated the drug lag, none has investigated it in relation to the transition of anticancer therapy from traditional cytotoxic drugs to molecularly targeted agents. Our aim was to investigate current trend in oncology drug lag between the US and Japan and identify oncology drugs approved in only one of the two countries. Publicly and commercially available data sources were used to identify drugs approved in the US and Japan as of 31 December 2010 and the data used to calculate the drug lag for individual drugs. Fifty-one drugs were approved in both the US and Japan, whereas 34 and 19 drugs were approved only in the US or Japan, respectively. Of the 19 drugs approved only in Japan, 12 had not been subject to development for a cancer indication in the US, and all were approved before 1996 in Japan. Of the 34 drugs approved only in the US, 20 had not been subject to development in Japan, and none was in the top 25 by annual US anticancer drug-class sales. For drugs approved in both countries, the mean approval lag of the molecularly targeted drugs (MTDs) was significantly shorter than that of the non-molecularly targeted drugs (non-MTDs) (3·3 vs. 5·4 years). Further, mean R&D time of the MTDs was significantly shorter than that of non-MTDs (10·0 vs. 13·7 years). The price of MTDs had increased on average by 6·6% annually in the US, whereas it had decreased on average by 4·3% biyearly in Japan. The emergence of new molecularly targeted agents has contributed to reducing the approval lag, most likely due to improvements in R&D strategy. © 2012 Blackwell Publishing Ltd.

Biodegradable Drug-Loaded Hydroxyapatite Nanotherapeutic Agent for Targeted Drug Release in Tumors.

PubMed

Sun, Wen; Fan, Jiangli; Wang, Suzhen; Kang, Yao; Du, Jianjun; Peng, Xiaojun

2018-03-07

Tumor-targeted drug delivery systems have been increasingly used to improve the therapeutic efficiency of anticancer drugs and reduce their toxic side effects in vivo. Focused on this point, doxorubicin (DOX)-loaded hydroxyapatite (HAP) nanorods consisting of folic acid (FA) modification (DOX@HAP-FA) were developed for efficient antitumor treatment. The DOX-loaded nanorods were synthesized through in situ coprecipitation and hydrothermal method with a DOX template, demonstrating a new procedure for drug loading in HAP materials. DOX could be efficiently released from DOX@HAP-FA within 24 h in weakly acidic buffer solution (pH = 6.0) because of the degradation of HAP nanorods. With endocytosis under the mediation of folate receptors, the nanorods exhibited enhanced cellular uptake and further degraded, and consequently, the proliferation of targeted cells was inhibited. More importantly, in a tumor-bearing mouse model, DOX@HAP-FA treatment demonstrated excellent tumor growth inhibition. In addition, no apparent side effects were observed during the treatment. These results suggested that DOX@HAP-FA may be a promising nanotherapeutic agent for effective cancer treatment in vivo.

HMGB1 as a drug target in staphylococcal pneumonia.

PubMed

Fink, Mitchell P

2014-03-31

High mobility group box (HMGB)1 is a small DNA-binding protein. In the nucleus, HMGB1 plays a role in gene expression and DNA replication. When it is released or secreted into the extracellular milieu, HMGB1 functions as a pro-inflammatory cytokine-like mediator. Recently reported data support the view that treatment with a neutralizing anti-HMGB1 antibody ameliorated pulmonary damage in a murine model of pneumonia caused by a pathogenic strain of Staphylococcus aureus. These findings suggest that HMGB1 may be an important drug target as scientists, clinical investigators and pharmaceutical companies seek to develop better agents for the treatment of staphylococcal pneumonia. Unfortunately, however, encouraging results from murine models of human disease often fail to translate into positive findings in clinical trials. Thus, before moving from pre-clinical into clinical studies, it may be prudent to validate and extend the recent experimental findings by carrying out additional studies, using a large animal model of pneumonia.

EphB1 as a Novel Drug Target to Combat Pain and Addiction

DTIC Science & Technology

2017-09-01

AWARD NUMBER: W81XWH-14-1-0220 TITLE: EphB1 as a Novel Drug Target to Combat Pain and Addiction PRINCIPAL INVESTIGATOR: Mark Henkemeyer...as a Novel Drug Target to Combat Pain and Ad 5a. CONTRACT NUMBER EphB1 as a Novel Drug Target to Combat Pain and Addiction 5b. GRANT NUMBER W81XWH...identify small molecular weight drug -like compounds from a >200,000 complex library that antagonize EphB1 protein-protein interactions. While we

Computational repositioning of ethno medicine elucidated gB-gH-gL complex as novel anti herpes drug target

PubMed Central

2013-01-01

Background Herpes viruses are important human pathogens that can cause mild to severe lifelong infections with high morbidity. They remain latent in the host cells and can cause recurrent infections that might prove fatal. These viruses are known to infect the host cells by causing the fusion of viral and host cell membrane proteins. Fusion is achieved with the help of conserved fusion machinery components, glycoproteins gB, heterodimer gH-gL complex along with other non-conserved components. Whereas, another important glycoprotein gD without which viral entry to the cell is not possible, acts as a co-activator for the gB-gH-gL complex formation. Thus, this complex formation interface is the most promising drug target for the development of novel anti-herpes drug candidates. In the present study, we propose a model for binding of gH-gL to gB glycoprotein leading from pre to post conformational changes during gB-gH-gL complex formation and reported the key residues involved in this binding activity along with possible binding site locations. To validate the drug targetability of our proposed binding site, we have repositioned some of the most promising in vitro, in vivo validated anti-herpes molecules onto the proposed binding site of gH-gL complex in a computational approach. Methods Hex 6.3 standalone software was used for protein-protein docking studies. Arguslab 4.0.1 and Accelrys® Discovery Studio 3.1 Visualizer softwares were used for semi-flexible docking studies and visualizing the interactions respectively. Protein receptors and ethno compounds were retrieved from Protein Data Bank (PDB) and Pubchem databases respectively. Lipinski’s Filter, Osiris Property Explorer and Lazar online servers were used to check the pharmaceutical fidelity of the drug candidates. Results Through protein-protein docking studies, it was identified that the amino acid residues VAL342, GLU347, SER349, TYR355, SER388, ASN395, HIS398 and ALA387 of gH-gL complex play an active

Sperm-Hybrid Micromotor for Targeted Drug Delivery.

PubMed

Xu, Haifeng; Medina-Sánchez, Mariana; Magdanz, Veronika; Schwarz, Lukas; Hebenstreit, Franziska; Schmidt, Oliver G

2018-01-23

A sperm-driven micromotor is presented as a targeted drug delivery system, which is appealing to potentially treat diseases in the female reproductive tract. This system is demonstrated to be an efficient drug delivery vehicle by first loading a motile sperm cell with an anticancer drug (doxorubicin hydrochloride), guiding it magnetically, to an in vitro cultured tumor spheroid, and finally freeing the sperm cell to deliver the drug locally. The sperm release mechanism is designed to liberate the sperm when the biohybrid micromotor hits the tumor walls, allowing it to swim into the tumor and deliver the drug through the sperm-cancer cell membrane fusion. In our experiments, the sperm cells exhibited a high drug encapsulation capability and drug carrying stability, conveniently minimizing  toxic side effects and unwanted drug accumulation in healthy tissues. Overall, sperm cells are excellent candidates to operate in physiological environments, as they neither express pathogenic proteins nor proliferate to form undesirable colonies, unlike other cells or microorganisms. This sperm-hybrid micromotor is a biocompatible platform with potential application in gynecological healthcare, treating or detecting cancer or other diseases in the female reproductive system.

Validation of CoaBC as a Bactericidal Target in the Coenzyme A Pathway of Mycobacterium tuberculosis.

PubMed

Evans, Joanna C; Trujillo, Carolina; Wang, Zhe; Eoh, Hyungjin; Ehrt, Sabine; Schnappinger, Dirk; Boshoff, Helena I M; Rhee, Kyu Y; Barry, Clifton E; Mizrahi, Valerie

2016-12-09

Mycobacterium tuberculosis relies on its own ability to biosynthesize coenzyme A to meet the needs of the myriad enzymatic reactions that depend on this cofactor for activity. As such, the essential pantothenate and coenzyme A biosynthesis pathways have attracted attention as targets for tuberculosis drug development. To identify the optimal step for coenzyme A pathway disruption in M. tuberculosis, we constructed and characterized a panel of conditional knockdown mutants in coenzyme A pathway genes. Here, we report that silencing of coaBC was bactericidal in vitro, whereas silencing of panB, panC, or coaE was bacteriostatic over the same time course. Silencing of coaBC was likewise bactericidal in vivo, whether initiated at infection or during either the acute or chronic stages of infection, confirming that CoaBC is required for M. tuberculosis to grow and persist in mice and arguing against significant CoaBC bypass via transport and assimilation of host-derived pantetheine in this animal model. These results provide convincing genetic validation of CoaBC as a new bactericidal drug target.

Peptide drugs to target G protein-coupled receptors.

PubMed

Bellmann-Sickert, Kathrin; Beck-Sickinger, Annette G

2010-09-01

Major indications for use of peptide-based therapeutics include endocrine functions (especially diabetes mellitus and obesity), infectious diseases, and cancer. Whereas some peptide pharmaceuticals are drugs, acting as agonists or antagonists to directly treat cancer, others (including peptide diagnostics and tumour-targeting pharmaceuticals) use peptides to 'shuttle' a chemotherapeutic agent or a tracer to the tumour and allow sensitive imaging or targeted therapy. Significant progress has been made in the last few years to overcome disadvantages in peptide design such as short half-life, fast proteolytic cleavage, and low oral bioavailability. These advances include peptide PEGylation, lipidisation or multimerisation; the introduction of peptidomimetic elements into the sequences; and innovative uptake strategies such as liposomal, capsule or subcutaneous formulations. This review focuses on peptides targeting G protein-coupled receptors that are promising drug candidates or that have recently entered the pharmaceutical market. Copyright 2010 Elsevier Ltd. All rights reserved.

Electrosynthesis of magnetoresponsive microrobot for targeted drug delivery using calcium alginate.

PubMed

Chengzhi Hu; Riederer, Katharina; Klemmer, Michael; Pane, Salvador; Nelson, Bradley J

2016-08-01

Targeted drug delivery systems deliver drugs precisely to a specific targeted site inside the body, and can also release the drugs with controlled kinetics to prolong the efficacy of single dose administration. The advantageous properties of hydrogels make them attractive for use in the area of drug delivery. Calcium alginate is a pH sensitive hydrogel stable in acidic media and soluble in basic media. This enables the hydrogel to absorb and release aqueous solutions at certain ranges of pH values. By absorbing an aqueous solution containing a drug, an active drug release can be triggered at a specified range of pH value. In this paper, we combined calcium alginate with cobalt nickel (CoNi) in a cylindrical hybrid micro robot by electrodeposition. The designed microrobot can be wirelessly actuated with an external magnetic manipulation system and, hence, targeted to a specific location in the human body. At this specific location, characterized by its pH range, the absorbed drug will be released. Here, the fabrication steps of the specified microrobot are characterized, namely the production of a template on a silicon chip and the subsequent template-assisted electrodeposition of CoNi and alginate. Additionally, the dynamics of drug release of calcium alginate is studied.

Targeting the ubiquitin-proteasome system for cancer treatment: discovering novel inhibitors from nature and drug repurposing.

PubMed

Soave, Claire L; Guerin, Tracey; Liu, Jinbao; Dou, Q Ping

2017-12-01

In the past 15 years, the proteasome has been validated as an anti-cancer drug target and 20S proteasome inhibitors (such as bortezomib and carfilzomib) have been approved by the FDA for the treatment of multiple myeloma and some other liquid tumors. However, there are shortcomings of clinical proteasome inhibitors, including severe toxicity, drug resistance, and no effect in solid tumors. At the same time, extensive research has been conducted in the areas of natural compounds and old drug repositioning towards the goal of discovering effective, economical, low toxicity proteasome-inhibitory anti-cancer drugs. A variety of dietary polyphenols, medicinal molecules, metallic complexes, and metal-binding compounds have been found to be able to selectively inhibit tumor cellular proteasomes and induce apoptotic cell death in vitro and in vivo, supporting the clinical success of specific 20S proteasome inhibitors bortezomib and carfilzomib. Therefore, the discovery of natural proteasome inhibitors and researching old drugs with proteasome-inhibitory properties may provide an alternative strategy for improving the current status of cancer treatment and even prevention.

Oncogenic targets, magnitude of benefit, and market pricing of antineoplastic drugs.

PubMed

Amir, Eitan; Seruga, Bostjan; Martinez-Lopez, Joaquin; Kwong, Ryan; Pandiella, Atanasio; Tannock, Ian F; Ocaña, Alberto

2011-06-20

The relationship between market pricing of new anticancer drugs and the magnitude of clinical benefit caused by them has not been reported. Randomized clinical trials (RCTs) that evaluated approved new agents for solid tumors by the U.S. Food and Drug administration since the year 2000 were assessed. Hazard ratios (HRs) and 95% CIs were extracted for time-to-event end points described for each RCT. HRs were pooled for three groups: agents directed against a specific molecular target, for which the target population is selected by a biomarker (group A); less specific biologic targeted agents (group B); and chemotherapeutic agents (group C). Monthly market prices of these different drugs were compared. For overall survival (OS), the pooled HR was 0.69 (95% CI, 0.59 to 0.81) for group A (six drugs, six trials); it was 0.78 (95% CI, 0.74 to 0.83) for group B (seven drugs, 14 trials); and it was 0.84 (95% CI, 0.79 to 0.90) for group C (eight drugs, 12 trials). For progression-free survival (PFS), the pooled HR was 0.42 (95% CI, 0.36 to 0.49) for group A (six drugs, seven trials); it was 0.57 (95% CI, 0.51 to 0.64) for group B (seven drugs, 14 trials); and it was 0.75 (95% CI, 0.66 to 0.85) for group C (six drugs, 10 trials). Tests for heterogeneity between subgroups were highly significant for PFS (P < .001) and OS (P = .02). The median monthly prices for standard doses of drugs were $5375 for group A, $5644 for group B, and $6584 for group C (P = .87). New agents with specific molecular targets are clinically the most beneficial, but their monthly market prices are not significantly different from those of other anticancer agents.

Adaptable setups for magnetic drug targeting in human muscular arteries: Design and implementation

NASA Astrophysics Data System (ADS)

Hajiaghajani, Amirhossein; Hashemi, Soheil; Abdolali, Ali

2017-09-01

Magnetic drug targeting has been used to steer magnetic therapeutic agents and has received much attention for capillaries and human brain arteries. In this paper, we focus on noninvasive targeting of nanoparticles in muscular arteries, in where the vessel diameter and blood flow are much challengingly higher than brain capillaries. We aim to design a low intensity magnetic field which avoids potential side effects on blood cells while steers particles with high targeting rate. The setup design procedure is considerably flexible to be used in a wide variety of large vessels. Using particle tracing, a new method is proposed to connect the geometry of the vessel under the action of targeting to the required magnetic force. Specifications of the coil which is placed outside the body are derived based on this required force. Mutual effects of coil dimensions on the produced magnetic force are elaborated and summarized in a design flowchart to be used for arbitrary muscular vessel sizes. The performance of the optimized coil is validated by in vitro experiments and it is shown that particles are steered with the average efficiency of 80.2% for various conditions.

Target therapy: new drugs or new combinations of drugs in malignant pleural mesothelioma.

PubMed

Zucali, Paolo A

2018-01-01

Malignant pleural mesothelioma (MPM) is a disease with a poor prognosis due to its aggressive nature. The management of patients with MPM is controversial. Considering that the contribution of surgery and radiation therapy in the management of this disease is not yet established, systemic treatments are predominantly considered during the course of MPM. Unfortunately, the currently therapeutic armamentarium is scarce and its outcomes still appear modest. New treatment strategies are needed. In preclinical setting, cell cycle regulation, apoptosis, growth factor pathways, and angiogenesis pathways involved in the development of MPM have been identified. However, in clinical setting, several drugs targeting these pathways resulted without a significant activity. A deeper knowledge of the biology and pathogenesis of this disease is required to develop more effective tools for diagnosis, therapy and prevention. This paper reviews therapeutic advances in MPM, with a particular focus on new drugs and new association of drugs of target therapy.

RFDT: A Rotation Forest-based Predictor for Predicting Drug-Target Interactions Using Drug Structure and Protein Sequence Information.