Identification of drug targets by chemogenomic and metabolomic profiling in yeast

KAUST Repository

Wu, Manhong

2012-12-01

OBJECTIVE: To advance our understanding of disease biology, the characterization of the molecular target for clinically proven or new drugs is very important. Because of its simplicity and the availability of strains with individual deletions in all of its genes, chemogenomic profiling in yeast has been used to identify drug targets. As measurement of drug-induced changes in cellular metabolites can yield considerable information about the effects of a drug, we investigated whether combining chemogenomic and metabolomic profiling in yeast could improve the characterization of drug targets. BASIC METHODS: We used chemogenomic and metabolomic profiling in yeast to characterize the target for five drugs acting on two biologically important pathways. A novel computational method that uses a curated metabolic network was also developed, and it was used to identify the genes that are likely to be responsible for the metabolomic differences found. RESULTS AND CONCLUSION: The combination of metabolomic and chemogenomic profiling, along with data analyses carried out using a novel computational method, could robustly identify the enzymes targeted by five drugs. Moreover, this novel computational method has the potential to identify genes that are causative of metabolomic differences or drug targets. © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins.

Properties of Protein Drug Target Classes

Science.gov (United States)

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

Putative drug and vaccine target protein identification using comparative genomic analysis of KEGG annotated metabolic pathways of Mycoplasma hyopneumoniae.

Science.gov (United States)

Damte, Dereje; Suh, Joo-Won; Lee, Seung-Jin; Yohannes, Sileshi Belew; Hossain, Md Akil; Park, Seung-Chun

2013-07-01

In the present study, a computational comparative and subtractive genomic/proteomic analysis aimed at the identification of putative therapeutic target and vaccine candidate proteins from Kyoto Encyclopedia of Genes and Genomes (KEGG) annotated metabolic pathways of Mycoplasma hyopneumoniae was performed for drug design and vaccine production pipelines against M.hyopneumoniae. The employed comparative genomic and metabolic pathway analysis with a predefined computational systemic workflow extracted a total of 41 annotated metabolic pathways from KEGG among which five were unique to M. hyopneumoniae. A total of 234 proteins were identified to be involved in these metabolic pathways. Although 125 non homologous and predicted essential proteins were found from the total that could serve as potential drug targets and vaccine candidates, additional prioritizing parameters characterize 21 proteins as vaccine candidate while druggability of each of the identified proteins evaluated by the DrugBank database prioritized 42 proteins suitable for drug targets. Copyright © 2013 Elsevier Inc. All rights reserved.

Identifying Drug-Target Interactions with Decision Templates.

Science.gov (United States)

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

Platforms for the identification of GPCR targets, and of orthosteric and allosteric modulators.

Science.gov (United States)

Franco, Rafael; Canela, Enric I; Casado, Vicent; Ferre, Sergi

2010-04-01

The review provides a summary of old and new approaches for GPCR target identification and for the screening of molecules acting on GPCR targets. The new findings in the field are presented as well as an opinion about how these developments may help GPCR drug discovery. Importance in the field: GPCRs have been the most useful family of proteins in terms of targets for drug discovery. The expectations for GPCR target identification and discovery of new drugs acting on 'old' or 'new' GPCR targets are very high. Given the fact that the pace at which new 'GPCR drugs' appear in the market is decreasing and since the new developments in the field are not being translated into drug discovery there is a need to review the field from a critical perspective. To overcome the limitation of the old approaches used in GPCR target identification and drugs discovery new approaches are required. In particular successful approaches in GPCR drug discovery should take into account that the real GPCR targets for a given disease are not GPCR monomers but GPCR heteromers. The reader will gain an overview of the strategies currently used and their pros and cons. The reader will also understand that new strategies may help in accelerating the access of GPCR into the market, and also notice that successful strategies should take advantage of the new findings in the field of GPCRs.

High-throughput identification of off-targets for the mechanistic study of severe adverse drug reactions induced by analgesics

Energy Technology Data Exchange (ETDEWEB)

Pan, Jian-Bo [Department of Chemical Biology, College of Chemistry and Chemical Engineering, The Key Laboratory for Chemical Biology of Fujian Province, Xiamen University, Xiamen, Fujian 361005 (China); Ji, Nan; Pan, Wen; Hong, Ru [State Key Laboratory of Stress Cell Biology, School of Life Sciences, Xiamen University, Xiamen, Fujian 361102 (China); Wang, Hao [Department of Chemical Biology, College of Chemistry and Chemical Engineering, The Key Laboratory for Chemical Biology of Fujian Province, Xiamen University, Xiamen, Fujian 361005 (China); Ji, Zhi-Liang, E-mail: appo@xmu.edu.cn [State Key Laboratory of Stress Cell Biology, School of Life Sciences, Xiamen University, Xiamen, Fujian 361102 (China); Department of Chemical Biology, College of Chemistry and Chemical Engineering, The Key Laboratory for Chemical Biology of Fujian Province, Xiamen University, Xiamen, Fujian 361005 (China)

2014-01-01

Drugs may induce adverse drug reactions (ADRs) when they unexpectedly bind to proteins other than their therapeutic targets. Identification of these undesired protein binding partners, called off-targets, can facilitate toxicity assessment in the early stages of drug development. In this study, a computational framework was introduced for the exploration of idiosyncratic mechanisms underlying analgesic-induced severe adverse drug reactions (SADRs). The putative analgesic-target interactions were predicted by performing reverse docking of analgesics or their active metabolites against human/mammal protein structures in a high-throughput manner. Subsequently, bioinformatics analyses were undertaken to identify ADR-associated proteins (ADRAPs) and pathways. Using the pathways and ADRAPs that this analysis identified, the mechanisms of SADRs such as cardiac disorders were explored. For instance, 53 putative ADRAPs and 24 pathways were linked with cardiac disorders, of which 10 ADRAPs were confirmed by previous experiments. Moreover, it was inferred that pathways such as base excision repair, glycolysis/glyconeogenesis, ErbB signaling, calcium signaling, and phosphatidyl inositol signaling likely play pivotal roles in drug-induced cardiac disorders. In conclusion, our framework offers an opportunity to globally understand SADRs at the molecular level, which has been difficult to realize through experiments. It also provides some valuable clues for drug repurposing. - Highlights: • A novel computational framework was developed for mechanistic study of SADRs. • Off-targets of drugs were identified in large scale and in a high-throughput manner. • SADRs like cardiac disorders were systematically explored in molecular networks. • A number of ADR-associated proteins were identified.

High-throughput identification of off-targets for the mechanistic study of severe adverse drug reactions induced by analgesics

International Nuclear Information System (INIS)

Pan, Jian-Bo; Ji, Nan; Pan, Wen; Hong, Ru; Wang, Hao; Ji, Zhi-Liang

2014-01-01

Drugs may induce adverse drug reactions (ADRs) when they unexpectedly bind to proteins other than their therapeutic targets. Identification of these undesired protein binding partners, called off-targets, can facilitate toxicity assessment in the early stages of drug development. In this study, a computational framework was introduced for the exploration of idiosyncratic mechanisms underlying analgesic-induced severe adverse drug reactions (SADRs). The putative analgesic-target interactions were predicted by performing reverse docking of analgesics or their active metabolites against human/mammal protein structures in a high-throughput manner. Subsequently, bioinformatics analyses were undertaken to identify ADR-associated proteins (ADRAPs) and pathways. Using the pathways and ADRAPs that this analysis identified, the mechanisms of SADRs such as cardiac disorders were explored. For instance, 53 putative ADRAPs and 24 pathways were linked with cardiac disorders, of which 10 ADRAPs were confirmed by previous experiments. Moreover, it was inferred that pathways such as base excision repair, glycolysis/glyconeogenesis, ErbB signaling, calcium signaling, and phosphatidyl inositol signaling likely play pivotal roles in drug-induced cardiac disorders. In conclusion, our framework offers an opportunity to globally understand SADRs at the molecular level, which has been difficult to realize through experiments. It also provides some valuable clues for drug repurposing. - Highlights: • A novel computational framework was developed for mechanistic study of SADRs. • Off-targets of drugs were identified in large scale and in a high-throughput manner. • SADRs like cardiac disorders were systematically explored in molecular networks. • A number of ADR-associated proteins were identified

Combinatorial Approaches for the Identification of Brain Drug Delivery Targets

Science.gov (United States)

Stutz, Charles C.; Zhang, Xiaobin; Shusta, Eric V.

2018-01-01

The blood-brain barrier (BBB) represents a large obstacle for the treatment of central nervous system diseases. Targeting endogenous nutrient transporters that transcytose the BBB is one promising approach to selectively and noninvasively deliver a drug payload to the brain. The main limitations of the currently employed transcytosing receptors are their ubiquitous expression in the peripheral vasculature and the inherent low levels of transcytosis mediated by such systems. In this review, approaches designed to increase the repertoire of transcytosing receptors which can be targeted for the purpose of drug delivery are discussed. In particular, combinatorial protein libraries can be screened on BBB cells in vitro or in vivo to isolate targeting peptides or antibodies that can trigger transcytosis. Once these targeting reagents are discovered, the cognate BBB transcytosis system can be identified using techniques such as expression cloning or immunoprecipitation coupled with mass spectrometry. Continued technological advances in BBB genomics and proteomics, membrane protein manipulation, and in vitro BBB technology promise to further advance the capability to identify and optimize peptides and antibodies capable of mediating drug transport across the BBB. PMID:23789958

Neighborhood Regularized Logistic Matrix Factorization for Drug-Target Interaction Prediction.

Science.gov (United States)

Liu, Yong; Wu, Min; Miao, Chunyan; Zhao, Peilin; Li, Xiao-Li

2016-02-01

In pharmaceutical sciences, a crucial step of the drug discovery process is the identification of drug-target interactions. However, only a small portion of the drug-target interactions have been experimentally validated, as the experimental validation is laborious and costly. To improve the drug discovery efficiency, there is a great need for the development of accurate computational approaches that can predict potential drug-target interactions to direct the experimental verification. In this paper, we propose a novel drug-target interaction prediction algorithm, namely neighborhood regularized logistic matrix factorization (NRLMF). Specifically, the proposed NRLMF method focuses on modeling the probability that a drug would interact with a target by logistic matrix factorization, where the properties of drugs and targets are represented by drug-specific and target-specific latent vectors, respectively. Moreover, NRLMF assigns higher importance levels to positive observations (i.e., the observed interacting drug-target pairs) than negative observations (i.e., the unknown pairs). Because the positive observations are already experimentally verified, they are usually more trustworthy. Furthermore, the local structure of the drug-target interaction data has also been exploited via neighborhood regularization to achieve better prediction accuracy. We conducted extensive experiments over four benchmark datasets, and NRLMF demonstrated its effectiveness compared with five state-of-the-art approaches.

Nanomedicine: Drug Delivery Systems and Nanoparticle Targeting

International Nuclear Information System (INIS)

Youn, Hye Won; Kang, Keon Wook; Chung, Jun Key; Lee, Dong Soo

2008-01-01

Applications of nanotechnology in the medical field have provided the fundamentals of tremendous improvement in precise diagnosis and customized therapy. Recent advances in nanomedicine have led to establish a new concept of theragnosis, which utilizes nanomedicines as a therapeutic and diagnostic tool at the same time. The development of high affinity nanoparticles with large surface area and functional groups multiplies diagnostic and therapeutic capacities. Considering the specific conditions related to the disease of individual patient, customized therapy requires the identification of disease target at the cellular and molecular level for reducing side effects and enhancing therapeutic efficiency. Well-designed nanoparticles can minimize unnecessary exposure of cytotoxic drugs and maximize targeted localization of administrated drugs. This review will focus on major pharmaceutical nanomaterials and nanoparticles as key components of designing and surface engineering for targeted theragnostic drug development

Targeted and non-targeted drug screening in whole blood by UHPLC-TOF-MS with data-independent acquisition

DEFF Research Database (Denmark)

Mollerup, Christian Brinch; Dalsgaard, Petur Weihe; Mardal, Marie

2017-01-01

of peaks to inspect by three orders of magnitude, down to four peaks per DUID sample. The screening allowed for tentative identification of metabolites and drugs not included in the initial screening, and three drugs and thirteen metabolites were tentatively identified in the authentic DUID samples......High-resolution mass spectrometry (HRMS) is widely used for the drug screening of biological samples in clinical and forensic laboratories. With the continuous addition of new psychoactive substances (NPS), keeping such methods updated is challenging. HRMS allows for combined targeted and non......-targeted screening; first, peaks are identified by software algorithms, and identifications are based on reference standard data. Remaining unknown peaks are attempted identified with in silico and literature data. However, several thousand peaks remain where most are unidentifiable or uninteresting in drug...

Solution NMR Spectroscopy in Target-Based Drug Discovery.

Science.gov (United States)

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.

Detection and identification of 700 drugs by multi-target screening with a 3200 Q TRAP LC-MS/MS system and library searching.

Science.gov (United States)

Dresen, S; Ferreirós, N; Gnann, H; Zimmermann, R; Weinmann, W

2010-04-01

The multi-target screening method described in this work allows the simultaneous detection and identification of 700 drugs and metabolites in biological fluids using a hybrid triple-quadrupole linear ion trap mass spectrometer in a single analytical run. After standardization of the method, the retention times of 700 compounds were determined and transitions for each compound were selected by a "scheduled" survey MRM scan, followed by an information-dependent acquisition using the sensitive enhanced product ion scan of a Q TRAP hybrid instrument. The identification of the compounds in the samples analyzed was accomplished by searching the tandem mass spectrometry (MS/MS) spectra against the library we developed, which contains electrospray ionization-MS/MS spectra of over 1,250 compounds. The multi-target screening method together with the library was included in a software program for routine screening and quantitation to achieve automated acquisition and library searching. With the help of this software application, the time for evaluation and interpretation of the results could be drastically reduced. This new multi-target screening method has been successfully applied for the analysis of postmortem and traffic offense samples as well as proficiency testing, and complements screening with immunoassays, gas chromatography-mass spectrometry, and liquid chromatography-diode-array detection. Other possible applications are analysis in clinical toxicology (for intoxication cases), in psychiatry (antidepressants and other psychoactive drugs), and in forensic toxicology (drugs and driving, workplace drug testing, oral fluid analysis, drug-facilitated sexual assault).

Genomes2Drugs: identifies target proteins and lead drugs from proteome data.

LENUS (Irish Health Repository)

Toomey, David

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.

Genomes2Drugs: identifies target proteins and lead drugs from proteome data.

Directory of Open Access Journals (Sweden)

David Toomey

Full Text Available 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.

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

Science.gov (United States)

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.

Prediction of Human Drug Targets and Their Interactions Using Machine Learning Methods: Current and Future Perspectives.

Science.gov (United States)

Nath, Abhigyan; Kumari, Priyanka; Chaube, Radha

2018-01-01

Identification of drug targets and drug target interactions are important steps in the drug-discovery pipeline. Successful computational prediction methods can reduce the cost and time demanded by the experimental methods. Knowledge of putative drug targets and their interactions can be very useful for drug repurposing. Supervised machine learning methods have been very useful in drug target prediction and in prediction of drug target interactions. Here, we describe the details for developing prediction models using supervised learning techniques for human drug target prediction and their interactions.

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

Science.gov (United States)

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.

Gaussian interaction profile kernels for predicting drug-target interaction.

Science.gov (United States)

van Laarhoven, Twan; Nabuurs, Sander B; Marchiori, Elena

2011-11-01

The in silico prediction of potential interactions between drugs and target proteins is of core importance for the identification of new drugs or novel targets for existing drugs. However, only a tiny portion of all drug-target pairs in current datasets are experimentally validated interactions. This motivates the need for developing computational methods that predict true interaction pairs with high accuracy. We show that a simple machine learning method that uses the drug-target network as the only source of information is capable of predicting true interaction pairs with high accuracy. Specifically, we introduce interaction profiles of drugs (and of targets) in a network, which are binary vectors specifying the presence or absence of interaction with every target (drug) in that network. We define a kernel on these profiles, called the Gaussian Interaction Profile (GIP) kernel, and use a simple classifier, (kernel) Regularized Least Squares (RLS), for prediction drug-target interactions. We test comparatively the effectiveness of RLS with the GIP kernel on four drug-target interaction networks used in previous studies. The proposed algorithm achieves area under the precision-recall curve (AUPR) up to 92.7, significantly improving over results of state-of-the-art methods. Moreover, we show that using also kernels based on chemical and genomic information further increases accuracy, with a neat improvement on small datasets. These results substantiate the relevance of the network topology (in the form of interaction profiles) as source of information for predicting drug-target interactions. Software and Supplementary Material are available at http://cs.ru.nl/~tvanlaarhoven/drugtarget2011/. tvanlaarhoven@cs.ru.nl; elenam@cs.ru.nl. Supplementary data are available at Bioinformatics online.

Large-scale prediction of drug-target interactions using protein sequences and drug topological structures

Energy Technology Data Exchange (ETDEWEB)

Cao Dongsheng [Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083 (China); Liu Shao [Xiangya Hospital, Central South University, Changsha 410008 (China); Xu Qingsong [School of Mathematical Sciences and Computing Technology, Central South University, Changsha 410083 (China); Lu Hongmei; Huang Jianhua [Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083 (China); Hu Qiannan [Key Laboratory of Combinatorial Biosynthesis and Drug Discovery (Wuhan University), Ministry of Education, and Wuhan University School of Pharmaceutical Sciences, Wuhan 430071 (China); Liang Yizeng, E-mail: yizeng_liang@263.net [Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083 (China)

2012-11-08

Highlights: Black-Right-Pointing-Pointer Drug-target interactions are predicted using an extended SAR methodology. Black-Right-Pointing-Pointer A drug-target interaction is regarded as an event triggered by many factors. Black-Right-Pointing-Pointer Molecular fingerprint and CTD descriptors are used to represent drugs and proteins. Black-Right-Pointing-Pointer Our approach shows compatibility between the new scheme and current SAR methodology. - Abstract: The identification of interactions between drugs and target proteins plays a key role in the process of genomic drug discovery. It is both consuming and costly to determine drug-target interactions by experiments alone. Therefore, there is an urgent need to develop new in silico prediction approaches capable of identifying these potential drug-target interactions in a timely manner. In this article, we aim at extending current structure-activity relationship (SAR) methodology to fulfill such requirements. In some sense, a drug-target interaction can be regarded as an event or property triggered by many influence factors from drugs and target proteins. Thus, each interaction pair can be represented theoretically by using these factors which are based on the structural and physicochemical properties simultaneously from drugs and proteins. To realize this, drug molecules are encoded with MACCS substructure fingerings representing existence of certain functional groups or fragments; and proteins are encoded with some biochemical and physicochemical properties. Four classes of drug-target interaction networks in humans involving enzymes, ion channels, G-protein-coupled receptors (GPCRs) and nuclear receptors, are independently used for establishing predictive models with support vector machines (SVMs). The SVM models gave prediction accuracy of 90.31%, 88.91%, 84.68% and 83.74% for four datasets, respectively. In conclusion, the results demonstrate the ability of our proposed method to predict the drug-target

Drug-Target Kinetics in Drug Discovery.

Science.gov (United States)

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.

Genome-wide identification of structural variants in genes encoding drug targets

DEFF Research Database (Denmark)

Rasmussen, Henrik Berg; Dahmcke, Christina Mackeprang

2012-01-01

The objective of the present study was to identify structural variants of drug target-encoding genes on a genome-wide scale. We also aimed at identifying drugs that are potentially amenable for individualization of treatments based on knowledge about structural variation in the genes encoding...

Comparative genomics study for the identification of drug and vaccine targets in Staphylococcus aureus: MurA ligase enzyme as a proposed candidate.

Science.gov (United States)

Ghosh, Soma; Prava, Jyoti; Samal, Himanshu Bhusan; Suar, Mrutyunjay; Mahapatra, Rajani Kanta

2014-06-01

Now-a-days increasing emergence of antibiotic-resistant pathogenic microorganisms is one of the biggest challenges for management of disease. In the present study comparative genomics, metabolic pathways analysis and additional parameters were defined for the identification of 94 non-homologous essential proteins in Staphylococcus aureus genome. Further study prioritized 19 proteins as vaccine candidates where as druggability study reports 34 proteins suitable as drug targets. Enzymes from peptidoglycan biosynthesis, folate biosynthesis were identified as candidates for drug development. Furthermore, bacterial secretory proteins and few hypothetical proteins identified in our analysis fulfill the criteria of vaccine candidates. As a case study, we built a homology model of one of the potential drug target, MurA ligase, using MODELLER (9v12) software. The model has been further selected for in silico docking study with inhibitors from the DrugBank database. Results from this study could facilitate selection of proteins for entry into drug design and vaccine production pipelines. Copyright © 2014 Elsevier B.V. All rights reserved.

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

Science.gov (United States)

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.

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

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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.

Drug Elucidation: Invertebrate Genetics Sheds New Light on the Molecular Targets of CNS Drugs

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Donard S. Dwyer

2014-07-01

Full Text Available Many important drugs approved to treat common human diseases were discovered by serendipity, without a firm understanding of their modes of action. As a result, the side effects and interactions of these medications are often unpredictable, and there is limited guidance for improving the design of next-generation drugs. Here, we review the innovative use of simple model organisms, especially Caenorhabditis elegans, to gain fresh insights into the complex biological effects of approved CNS medications. Whereas drug discovery involves the identification of new drug targets and lead compounds/biologics, and drug development spans preclinical testing to FDA approval, drug elucidation refers to the process of understanding the mechanisms of action of marketed drugs by studying their novel effects in model organisms. Drug elucidation studies have revealed new pathways affected by antipsychotic drugs, e.g., the insulin signaling pathway, a trace amine receptor and a nicotinic acetylcholine receptor. Similarly, novel targets of antidepressant drugs and lithium have been identified in C. elegans, including lipid-binding/transport proteins and the SGK-1 signaling pathway, respectively. Elucidation of the mode of action of anesthetic agents has shown that anesthesia can involve mitochondrial targets, leak currents and gap junctions. The general approach reviewed in this article has advanced our knowledge about important drugs for CNS disorders and can guide future drug discovery efforts.

Virtual target screening to rapidly identify potential protein targets of natural products in drug discovery

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Yuri Pevzner

2014-05-01

Full Text Available Inherent biological viability and diversity of natural products make them a potentially rich source for new therapeutics. However, identification of bioactive compounds with desired therapeutic effects and identification of their protein targets is a laborious, expensive process. Extracts from organism samples may show desired activity in phenotypic assays but specific bioactive compounds must be isolated through further separation methods and protein targets must be identified by more specific phenotypic and in vitro experimental assays. Still, questions remain as to whether all relevant protein targets for a compound have been identified. The desire is to understand breadth of purposing for the compound to maximize its use and intellectual property, and to avoid further development of compounds with insurmountable adverse effects. Previously we developed a Virtual Target Screening system that computationally screens one or more compounds against a collection of virtual protein structures. By scoring each compound-protein interaction, we can compare against averaged scores of synthetic drug-like compounds to determine if a particular protein would be a potential target of a compound of interest. Here we provide examples of natural products screened through our system as we assess advantages and shortcomings of our current system in regards to natural product drug discovery.

Virtual target screening to rapidly identify potential protein targets of natural products in drug discovery

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Yuri Pevzner

2015-08-01

Full Text Available Inherent biological viability and diversity of natural products make them a potentially rich source for new therapeutics. However, identification of bioactive compounds with desired therapeutic effects and identification of their protein targets is a laborious, expensive process. Extracts from organism samples may show desired activity in phenotypic assays but specific bioactive compounds must be isolated through further separation methods and protein targets must be identified by more specific phenotypic and in vitro experimental assays. Still, questions remain as to whether all relevant protein targets for a compound have been identified. The desire is to understand breadth of purposing for the compound to maximize its use and intellectual property, and to avoid further development of compounds with insurmountable adverse effects. Previously we developed a Virtual Target Screening system that computationally screens one or more compounds against a collection of virtual protein structures. By scoring each compound-protein interaction, we can compare against averaged scores of synthetic drug-like compounds to determine if a particular protein would be a potential target of a compound of interest. Here we provide examples of natural products screened through our system as we assess advantages and shortcomings of our current system in regards to natural product drug discovery.

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

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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 targeting to tumors: principles, pitfalls and (pre-) clinical progress.

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Lammers, Twan; Kiessling, Fabian; Hennink, Wim E; Storm, Gert

2012-07-20

Many different systems and strategies have been evaluated for drug targeting to tumors over the years. Routinely used systems include liposomes, polymers, micelles, nanoparticles and antibodies, and examples of strategies are passive drug targeting, active drug targeting to cancer cells, active drug targeting to endothelial cells and triggered drug delivery. Significant progress has been made in this area of research both at the preclinical and at the clinical level, and a number of (primarily passively tumor-targeted) nanomedicine formulations have been approved for clinical use. Significant progress has also been made with regard to better understanding the (patho-) physiological principles of drug targeting to tumors. This has led to the identification of several important pitfalls in tumor-targeted drug delivery, including I) overinterpretation of the EPR effect; II) poor tumor and tissue penetration of nanomedicines; III) misunderstanding of the potential usefulness of active drug targeting; IV) irrational formulation design, based on materials which are too complex and not broadly applicable; V) insufficient incorporation of nanomedicine formulations in clinically relevant combination regimens; VI) negligence of the notion that the highest medical need relates to metastasis, and not to solid tumor treatment; VII) insufficient integration of non-invasive imaging techniques and theranostics, which could be used to personalize nanomedicine-based therapeutic interventions; and VIII) lack of (efficacy analyses in) proper animal models, which are physiologically more relevant and more predictive for the clinical situation. These insights strongly suggest that besides making ever more nanomedicine formulations, future efforts should also address some of the conceptual drawbacks of drug targeting to tumors, and that strategies should be developed to overcome these shortcomings. Copyright © 2011 Elsevier B.V. All rights reserved.

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

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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.

Retrieval of Enterobacteriaceae drug targets using singular value decomposition.

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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.

Drug target mining and analysis of the Chinese tree shrew for pharmacological testing.

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Feng Zhao

Full Text Available 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.

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

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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.

Organelle targeting: third level of drug targeting

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Sakhrani NM

2013-07-01

Full Text Available Niraj M Sakhrani, Harish PadhDepartment of Cell and Molecular Biology, BV Patel Pharmaceutical Education and Research Development (PERD Centre, Gujarat, IndiaAbstract: Drug discovery and drug delivery are two main aspects for treatment of a variety of disorders. However, the real bottleneck associated with systemic drug administration is the lack of target-specific affinity toward a pathological site, resulting in systemic toxicity and innumerable other side effects as well as higher dosage requirement for efficacy. An attractive strategy to increase the therapeutic index of a drug is to specifically deliver the therapeutic molecule in its active form, not only into target tissue, nor even to target cells, but more importantly, into the targeted organelle, ie, to its intracellular therapeutic active site. This would ensure improved efficacy and minimize toxicity. Cancer chemotherapy today faces the major challenge of delivering chemotherapeutic drugs exclusively to tumor cells, while sparing normal proliferating cells. Nanoparticles play a crucial role by acting as a vehicle for delivery of drugs to target sites inside tumor cells. In this review, we spotlight active and passive targeting, followed by discussion of the importance of targeting to specific cell organelles and the potential role of cell-penetrating peptides. Finally, the discussion will address the strategies for drug/DNA targeting to lysosomes, mitochondria, nuclei and Golgi/endoplasmic reticulum.Keywords: intracellular drug delivery, cancer chemotherapy, therapeutic index, cell penetrating peptides

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

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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

Identification of cytotoxic drugs that selectively target tumor cells with MYC overexpression.

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Anna Frenzel

Full Text Available Expression of MYC is deregulated in a wide range of human cancers, and is often associated with aggressive disease and poorly differentiated tumor cells. Identification of compounds with selectivity for cells overexpressing MYC would hence be beneficial for the treatment of these tumors. For this purpose we used cell lines with conditional MYCN or c-MYC expression, to screen a library of 80 conventional cytotoxic compounds for their ability to reduce tumor cell viability and/or growth in a MYC dependent way. We found that 25% of the studied compounds induced apoptosis and/or inhibited proliferation in a MYC-specific manner. The activities of the majority of these were enhanced both by c-MYC or MYCN over-expression. Interestingly, these compounds were acting on distinct cellular targets, including microtubules (paclitaxel, podophyllotoxin, vinblastine and topoisomerases (10-hydroxycamptothecin, camptothecin, daunorubicin, doxorubicin, etoposide as well as DNA, RNA and protein synthesis and turnover (anisomycin, aphidicholin, gliotoxin, MG132, methotrexate, mitomycin C. Our data indicate that MYC overexpression sensitizes cells to disruption of specific pathways and that in most cases c-MYC and MYCN overexpression have similar effects on the responses to cytotoxic compounds. Treatment of the cells with topoisomerase I inhibitors led to down-regulation of MYC protein levels, while doxorubicin and the small molecule MYRA-A was found to disrupt MYC-Max interaction. We conclude that the MYC pathway is only targeted by a subset of conventional cytotoxic drugs currently used in the clinic. Elucidating the mechanisms underlying their specificity towards MYC may be of importance for optimizing treatment of tumors with MYC deregulation. Our data also underscores that MYC is an attractive target for novel therapies and that cellular screenings of chemical libraries can be a powerful tool for identifying compounds with a desired biological activity.

The Proteomics Big Challenge for Biomarkers and New Drug-Targets Discovery

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Savino, Rocco; Paduano, Sergio; Preianò, Mariaimmacolata; Terracciano, Rosa

2012-01-01

In the modern process of drug discovery, clinical, functional and chemical proteomics can converge and integrate synergies. Functional proteomics explores and elucidates the components of pathways and their interactions which, when deregulated, lead to a disease condition. This knowledge allows the design of strategies to target multiple pathways with combinations of pathway-specific drugs, which might increase chances of success and reduce the occurrence of drug resistance. Chemical proteomics, by analyzing the drug interactome, strongly contributes to accelerate the process of new druggable targets discovery. In the research area of clinical proteomics, proteome and peptidome mass spectrometry-profiling of human bodily fluid (plasma, serum, urine and so on), as well as of tissue and of cells, represents a promising tool for novel biomarker and eventually new druggable targets discovery. In the present review we provide a survey of current strategies of functional, chemical and clinical proteomics. Major issues will be presented for proteomic technologies used for the discovery of biomarkers for early disease diagnosis and identification of new drug targets. PMID:23203042

Functional expression of parasite drug targets and their human orthologs in yeast.

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Elizabeth Bilsland

2011-10-01

Full Text Available The exacting nutritional requirements and complicated life cycles of parasites mean that they are not always amenable to high-throughput drug screening using automated procedures. Therefore, we have engineered the yeast Saccharomyces cerevisiae to act as a surrogate for expressing anti-parasitic targets from a range of biomedically important pathogens, to facilitate the rapid identification of new therapeutic agents.Using pyrimethamine/dihydrofolate reductase (DHFR as a model parasite drug/drug target system, we explore the potential of engineered yeast strains (expressing DHFR enzymes from Plasmodium falciparum, P. vivax, Homo sapiens, Schistosoma mansoni, Leishmania major, Trypanosoma brucei and T. cruzi to exhibit appropriate differential sensitivity to pyrimethamine. Here, we demonstrate that yeast strains (lacking the major drug efflux pump, Pdr5p expressing yeast ((ScDFR1, human ((HsDHFR, Schistosoma ((SmDHFR, and Trypanosoma ((TbDHFR and (TcDHFR DHFRs are insensitive to pyrimethamine treatment, whereas yeast strains producing Plasmodium ((PfDHFR and (PvDHFR DHFRs are hypersensitive. Reassuringly, yeast strains expressing field-verified, drug-resistant mutants of P. falciparum DHFR ((Pfdhfr(51I,59R,108N are completely insensitive to pyrimethamine, further validating our approach to drug screening. We further show the versatility of the approach by replacing yeast essential genes with other potential drug targets, namely phosphoglycerate kinases (PGKs and N-myristoyl transferases (NMTs.We have generated a number of yeast strains that can be successfully harnessed for the rapid and selective identification of urgently needed anti-parasitic agents.

Identification of drug targets by chemogenomic and metabolomic profiling in yeast

KAUST Repository

Wu, Manhong; Zheng, Ming; Zhang, Weiruo; Suresh, Sundari; Schlecht, Ulrich; Fitch, William L.; Aronova, Sofia; Baumann, Stephan; Davis, Ronald; St.Onge, Robert; Dill, David L.; Peltz, Gary

2012-01-01

OBJECTIVE: To advance our understanding of disease biology, the characterization of the molecular target for clinically proven or new drugs is very important. Because of its simplicity and the availability of strains with individual deletions in all

Crowd sourcing a new paradigm for interactome driven drug target identification in Mycobacterium tuberculosis.

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Rohit Vashisht

Full Text Available 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.

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

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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

Identification of the Schistosoma mansoni Molecular Target for the Antimalarial Drug Artemether

KAUST Repository

Lepore, Rosalba

2011-11-28

Plasmodium falciparum and Schistosoma mansonii are the parasites responsible for most of the malaria and schistosomiasis cases in the world. Notwithstanding their many differences, the two agents have striking similarities in that they both are blood feeders and are targets of an overlapping set of drugs, including the well-known artemether molecule. Here we explore the possibility of using the known information about the mode of action of artemether in Plasmodium to identify the molecular target of the drug in Schistosoma and provide evidence that artemether binds to SmSERCA, a putative Ca2+-ATPase of Schistosoma. We also predict the putative binding mode of the molecule for both its Plasmodium and Schistosoma targets. Our analysis of the mode of binding of artemether to Ca2+-ATPases also provides an explanation for the apparent paradox that, although the molecule has no side effect in humans, it has been shown to possess antitumoral activity. © 2011 American Chemical Society.

Identification of polycystic ovary syndrome potential drug targets based on pathobiological similarity in the protein-protein interaction network

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Li, Wan; Wei, Wenqing; Li, Yiran; Xie, Ruiqiang; Guo, Shanshan; Wang, Yahui; Jiang, Jing; Chen, Binbin; Lv, Junjie; Zhang, Nana; Chen, Lina; He, Weiming

2016-01-01

Polycystic ovary syndrome (PCOS) is one of the most common endocrinological disorders in reproductive aged women. PCOS and Type 2 Diabetes (T2D) are closely linked in multiple levels and possess high pathobiological similarity. Here, we put forward a new computational approach based on the pathobiological similarity to identify PCOS potential drug target modules (PPDT-Modules) and PCOS potential drug targets in the protein-protein interaction network (PPIN). From the systems level and biological background, 1 PPDT-Module and 22 PCOS potential drug targets were identified, 21 of which were verified by literatures to be associated with the pathogenesis of PCOS. 42 drugs targeting to 13 PCOS potential drug targets were investigated experimentally or clinically for PCOS. Evaluated by independent datasets, the whole PPDT-Module and 22 PCOS potential drug targets could not only reveal the drug response, but also distinguish the statuses between normal and disease. Our identified PPDT-Module and PCOS potential drug targets would shed light on the treatment of PCOS. And our approach would provide valuable insights to research on the pathogenesis and drug response of other diseases. PMID:27191267

Identification of attractive drug targets in neglected-disease pathogens using an in silico approach.

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Gregory J Crowther

Full Text Available BACKGROUND: The increased sequencing of pathogen genomes and the subsequent availability of genome-scale functional datasets are expected to guide the experimental work necessary for target-based drug discovery. However, a major bottleneck in this has been the difficulty of capturing and integrating relevant information in an easily accessible format for identifying and prioritizing potential targets. The open-access resource TDRtargets.org facilitates drug target prioritization for major tropical disease pathogens such as the mycobacteria Mycobacterium leprae and Mycobacterium tuberculosis; the kinetoplastid protozoans Leishmania major, Trypanosoma brucei, and Trypanosoma cruzi; the apicomplexan protozoans Plasmodium falciparum, Plasmodium vivax, and Toxoplasma gondii; and the helminths Brugia malayi and Schistosoma mansoni. METHODOLOGY/PRINCIPAL FINDINGS: Here we present strategies to prioritize pathogen proteins based on whether their properties meet criteria considered desirable in a drug target. These criteria are based upon both sequence-derived information (e.g., molecular mass and functional data on expression, essentiality, phenotypes, metabolic pathways, assayability, and druggability. This approach also highlights the fact that data for many relevant criteria are lacking in less-studied pathogens (e.g., helminths, and we demonstrate how this can be partially overcome by mapping data from homologous genes in well-studied organisms. We also show how individual users can easily upload external datasets and integrate them with existing data in TDRtargets.org to generate highly customized ranked lists of potential targets. CONCLUSIONS/SIGNIFICANCE: Using the datasets and the tools available in TDRtargets.org, we have generated illustrative lists of potential drug targets in seven tropical disease pathogens. While these lists are broadly consistent with the research community's current interest in certain specific proteins, and suggest

OPTICAL correlation identification technology applied in underwater laser imaging target identification

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Yao, Guang-tao; Zhang, Xiao-hui; Ge, Wei-long

2012-01-01

The underwater laser imaging detection is an effective method of detecting short distance target underwater as an important complement of sonar detection. With the development of underwater laser imaging technology and underwater vehicle technology, the underwater automatic target identification has gotten more and more attention, and is a research difficulty in the area of underwater optical imaging information processing. Today, underwater automatic target identification based on optical imaging is usually realized with the method of digital circuit software programming. The algorithm realization and control of this method is very flexible. However, the optical imaging information is 2D image even 3D image, the amount of imaging processing information is abundant, so the electronic hardware with pure digital algorithm will need long identification time and is hard to meet the demands of real-time identification. If adopt computer parallel processing, the identification speed can be improved, but it will increase complexity, size and power consumption. This paper attempts to apply optical correlation identification technology to realize underwater automatic target identification. The optics correlation identification technology utilizes the Fourier transform characteristic of Fourier lens which can accomplish Fourier transform of image information in the level of nanosecond, and optical space interconnection calculation has the features of parallel, high speed, large capacity and high resolution, combines the flexibility of calculation and control of digital circuit method to realize optoelectronic hybrid identification mode. We reduce theoretical formulation of correlation identification and analyze the principle of optical correlation identification, and write MATLAB simulation program. We adopt single frame image obtained in underwater range gating laser imaging to identify, and through identifying and locating the different positions of target, we can improve

Visualization of network target crosstalk optimizes drug synergism in myocardial ischemia.

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Xiaojing Wan

Full Text Available Numerous drugs and compounds have been validated as protecting against myocardial ischemia (MI, a leading cause of heart failure; however, synergistic possibilities among them have not been systematically explored. Thus, there appears to be significant room for optimization in the field of drug combination therapy for MI. Here, we propose an easy approach for the identification and optimization of MI-related synergistic drug combinations via visualization of the crosstalk between networks of drug targets corresponding to different drugs (each drug has a unique network of targets. As an example, in the present study, 28 target crosstalk networks (TCNs of random pairwise combinations of 8 MI-related drugs (curcumin, capsaicin, celecoxib, raloxifene, silibinin, sulforaphane, tacrolimus, and tamoxifen were established to illustrate the proposed method. The TCNs revealed a high likelihood of synergy between curcumin and the other drugs, which was confirmed by in vitro experiments. Further drug combination optimization showed a synergistic protective effect of curcumin, celecoxib, and sililinin in combination against H₂O₂-induced ischemic injury of cardiomyocytes at a relatively low concentration of 500 nM. This result is in agreement with the earlier finding of a denser and modular functional crosstalk between their networks of targets in the regulation of cell apoptosis. Our study offers a simple approach to rapidly search for and optimize potent synergistic drug combinations, which can be used for identifying better MI therapeutic strategies. Some new light was also shed on the characteristic features of drug synergy, suggesting that it is possible to apply this method to other complex human diseases.

Visualization of network target crosstalk optimizes drug synergism in myocardial ischemia.

Science.gov (United States)

Wan, Xiaojing; Meng, Jia; Dai, Yingnan; Zhang, Yina; Yan, Shuang

2014-01-01

Numerous drugs and compounds have been validated as protecting against myocardial ischemia (MI), a leading cause of heart failure; however, synergistic possibilities among them have not been systematically explored. Thus, there appears to be significant room for optimization in the field of drug combination therapy for MI. Here, we propose an easy approach for the identification and optimization of MI-related synergistic drug combinations via visualization of the crosstalk between networks of drug targets corresponding to different drugs (each drug has a unique network of targets). As an example, in the present study, 28 target crosstalk networks (TCNs) of random pairwise combinations of 8 MI-related drugs (curcumin, capsaicin, celecoxib, raloxifene, silibinin, sulforaphane, tacrolimus, and tamoxifen) were established to illustrate the proposed method. The TCNs revealed a high likelihood of synergy between curcumin and the other drugs, which was confirmed by in vitro experiments. Further drug combination optimization showed a synergistic protective effect of curcumin, celecoxib, and sililinin in combination against H₂O₂-induced ischemic injury of cardiomyocytes at a relatively low concentration of 500 nM. This result is in agreement with the earlier finding of a denser and modular functional crosstalk between their networks of targets in the regulation of cell apoptosis. Our study offers a simple approach to rapidly search for and optimize potent synergistic drug combinations, which can be used for identifying better MI therapeutic strategies. Some new light was also shed on the characteristic features of drug synergy, suggesting that it is possible to apply this method to other complex human diseases.

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

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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

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

Directory of Open Access Journals (Sweden)

Montiago X LaBute

Full Text Available 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

Drug-induced regulation of target expression

DEFF Research Database (Denmark)

Iskar, Murat; Campillos, Monica; Kuhn, Michael

2010-01-01

Drug perturbations of human cells lead to complex responses upon target binding. One of the known mechanisms is a (positive or negative) feedback loop that adjusts the expression level of the respective target protein. To quantify this mechanism systems-wide in an unbiased way, drug......-induced differential expression of drug target mRNA was examined in three cell lines using the Connectivity Map. To overcome various biases in this valuable resource, we have developed a computational normalization and scoring procedure that is applicable to gene expression recording upon heterogeneous drug treatments....... In 1290 drug-target relations, corresponding to 466 drugs acting on 167 drug targets studied, 8% of the targets are subject to regulation at the mRNA level. We confirmed systematically that in particular G-protein coupled receptors, when serving as known targets, are regulated upon drug treatment. We...

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

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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.

Identification of a Non-Gatekeeper Hot Spot for Drug-Resistant Mutations in mTOR Kinase.

Science.gov (United States)

Wu, Tzung-Ju; Wang, Xiaowen; Zhang, Yanjie; Meng, Linghua; Kerrigan, John E; Burley, Stephen K; Zheng, X F Steven

2015-04-21

Protein kinases are therapeutic targets for human cancer. However, "gatekeeper" mutations in tyrosine kinases cause acquired clinical resistance, limiting long-term treatment benefits. mTOR is a key cancer driver and drug target. Numerous small-molecule mTOR kinase inhibitors have been developed, with some already in human clinical trials. Given our clinical experience with targeted therapeutics, acquired drug resistance in mTOR is thought likely, but not yet documented. Herein, we describe identification of a hot spot (L2185) for drug-resistant mutations, which is distinct from the gatekeeper site, and a chemical scaffold refractory to drug-resistant mutations. We also provide new insights into mTOR kinase structure and function. The hot spot mutations are potentially useful as surrogate biomarkers for acquired drug resistance in ongoing clinical trials and future treatments and for the design of the next generation of mTOR-targeted drugs. Our study provides a foundation for further research into mTOR kinase function and targeting. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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.

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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.

Post-acquisition data mining techniques for LC-MS/MS-acquired data in drug metabolite identification.

Science.gov (United States)

Dhurjad, Pooja Sukhdev; Marothu, Vamsi Krishna; Rathod, Rajeshwari

2017-08-01

Metabolite identification is a crucial part of the drug discovery process. LC-MS/MS-based metabolite identification has gained widespread use, but the data acquired by the LC-MS/MS instrument is complex, and thus the interpretation of data becomes troublesome. Fortunately, advancements in data mining techniques have simplified the process of data interpretation with improved mass accuracy and provide a potentially selective, sensitive, accurate and comprehensive way for metabolite identification. In this review, we have discussed the targeted (extracted ion chromatogram, mass defect filter, product ion filter, neutral loss filter and isotope pattern filter) and untargeted (control sample comparison, background subtraction and metabolomic approaches) post-acquisition data mining techniques, which facilitate the drug metabolite identification. We have also discussed the importance of integrated data mining strategy.

Drug-Target Interactions: Prediction Methods and Applications.

Science.gov (United States)

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.

Application of RNAi to Genomic Drug Target Validation in Schistosomes.

Directory of Open Access Journals (Sweden)

Alessandra Guidi

2015-05-01

Full Text Available Concerns over the possibility of resistance developing to praziquantel (PZQ, has stimulated efforts to develop new drugs for schistosomiasis. In addition to the development of improved whole organism screens, the success of RNA interference (RNAi in schistosomes offers great promise for the identification of potential drug targets to initiate drug discovery. In this study we set out to contribute to RNAi based validation of putative drug targets. Initially a list of 24 target candidates was compiled based on the identification of putative essential genes in schistosomes orthologous of C. elegans essential genes. Knockdown of Calmodulin (Smp_026560.2 (Sm-Calm, that topped this list, produced a phenotype characterised by waves of contraction in adult worms but no phenotype in schistosomula. Knockdown of the atypical Protein Kinase C (Smp_096310 (Sm-aPKC resulted in loss of viability in both schistosomula and adults and led us to focus our attention on other kinase genes that were identified in the above list and through whole organism screening of known kinase inhibitor sets followed by chemogenomic evaluation. RNAi knockdown of these kinase genes failed to affect adult worm viability but, like Sm-aPKC, knockdown of Polo-like kinase 1, Sm-PLK1 (Smp_009600 and p38-MAPK, Sm-MAPK p38 (Smp_133020 resulted in an increased mortality of schistosomula after 2-3 weeks, an effect more marked in the presence of human red blood cells (hRBC. For Sm-PLK-1 the same effects were seen with the specific inhibitor, BI2536, which also affected viable egg production in adult worms. For Sm-PLK-1 and Sm-aPKC the in vitro effects were reflected in lower recoveries in vivo. We conclude that the use of RNAi combined with culture with hRBC is a reliable method for evaluating genes important for larval development. However, in view of the slow manifestation of the effects of Sm-aPKC knockdown in adults and the lack of effects of Sm-PLK-1 and Sm-MAPK p38 on adult viability

Hot-spot analysis for drug discovery targeting protein-protein interactions.

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Rosell, Mireia; Fernández-Recio, Juan

2018-04-01

Protein-protein interactions are important for biological processes and pathological situations, and are attractive targets for drug discovery. However, rational drug design targeting protein-protein interactions is still highly challenging. Hot-spot residues are seen as the best option to target such interactions, but their identification requires detailed structural and energetic characterization, which is only available for a tiny fraction of protein interactions. Areas covered: In this review, the authors cover a variety of computational methods that have been reported for the energetic analysis of protein-protein interfaces in search of hot-spots, and the structural modeling of protein-protein complexes by docking. This can help to rationalize the discovery of small-molecule inhibitors of protein-protein interfaces of therapeutic interest. Computational analysis and docking can help to locate the interface, molecular dynamics can be used to find suitable cavities, and hot-spot predictions can focus the search for inhibitors of protein-protein interactions. Expert opinion: A major difficulty for applying rational drug design methods to protein-protein interactions is that in the majority of cases the complex structure is not available. Fortunately, computational docking can complement experimental data. An interesting aspect to explore in the future is the integration of these strategies for targeting PPIs with large-scale mutational analysis.

Drug-targeting methodologies with applications: A review

Science.gov (United States)

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

Identification of putative drug targets in Vancomycin-resistant Staphylococcus aureus (VRSA) using computer aided protein data analysis.

Science.gov (United States)

Hasan, Md Anayet; Khan, Md Arif; Sharmin, Tahmina; Hasan Mazumder, Md Habibul; Chowdhury, Afrin Sultana

2016-01-01

Vancomycin-resistant Staphylococcus aureus (VRSA) is a Gram-positive, facultative aerobic bacterium which is evolved from the extensive exposure of Vancomycin to Methicillin resistant S. aureus (MRSA) that had become the most common cause of hospital and community-acquired infections. Due to the emergence of different antibiotic resistance strains, there is an exigency to develop novel drug targets to address the provocation of multidrug-resistant bacteria. In this study, in-silico genome subtraction methodology was used to design potential and pathogen specific drug targets against VRSA. Our study divulged 1987 proteins from the proteome of 34,549 proteins, which have no homologues in human genome after sequential analysis through CD-HIT and BLASTp. The high stringency analysis of the remaining proteins against database of essential genes (DEG) resulted in 169 proteins which are essential for S. aureus. Metabolic pathway analysis of human host and pathogen by KAAS at the KEGG server sorted out 19 proteins involved in unique metabolic pathways. 26 human non-homologous membrane-bound essential proteins including 4 which were also involved in unique metabolic pathway were deduced through PSORTb, CELLO v.2.5, ngLOC. Functional classification of uncharacterized proteins through SVMprot derived 7 human non-homologous membrane-bound hypothetical essential proteins. Study of potential drug target against Drug Bank revealed pbpA-penicillin-binding protein 1 and hypothetical protein MQW_01796 as the best drug target candidate. 2D structure was predicted by PRED-TMBB, 3D structure and functional analysis was also performed. Protein-protein interaction network of potential drug target proteins was analyzed by using STRING. The identified drug targets are expected to have great potential for designing novel drugs against VRSA infections and further screening of the compounds against these new targets may result in the discovery of novel therapeutic compounds that can be

Understanding the magnitude of emergent contaminant releases through target screening and metabolite identification using high resolution mass spectrometry: Illicit drugs in raw sewage influents.

Science.gov (United States)

Heuett, Nubia V; Batchu, Sudha Rani; Gardinali, Piero R

2015-01-23

A QExactive Orbitrap was used for the identification of phase I and II transformation products (TPs) of illicit drugs in raw sewage influents. Two operating modes (targeted MS(2) and Data-dependent screening) were used for data acquisition. Even though, data-dependent scan is a faster route towards the potential identification of metabolites, it suffered from its limitation to provide enough data points across the chromatographic peak during the MS(2) cycle in contrast to targeted MS(2). Therefore, the later technique was implemented as the method of choice in this study for the positive confirmation and quantitation of TPs (n=54). The vast majority of the identified TPs were products of phase I transformation reactions, with the latter being more prevalent in the nature. Estimated mole fractions showed that for a large number of the analytes, TPs must also be monitored in order to fully understand their environmental fate and calculate potential consumption. Copyright © 2014 Elsevier B.V. All rights reserved.

Polymeric micelles for drug targeting.

Science.gov (United States)

Mahmud, Abdullah; Xiong, Xiao-Bing; Aliabadi, Hamidreza Montazeri; Lavasanifar, Afsaneh

2007-11-01

Polymeric micelles are nano-delivery systems formed through self-assembly of amphiphilic block copolymers in an aqueous environment. The nanoscopic dimension, stealth properties induced by the hydrophilic polymeric brush on the micellar surface, capacity for stabilized encapsulation of hydrophobic drugs offered by the hydrophobic and rigid micellar core, and finally a possibility for the chemical manipulation of the core/shell structure have made polymeric micelles one of the most promising carriers for drug targeting. To date, three generations of polymeric micellar delivery systems, i.e. polymeric micelles for passive, active and multifunctional drug targeting, have arisen from research efforts, with each subsequent generation displaying greater specificity for the diseased tissue and/or targeting efficiency. The present manuscript aims to review the research efforts made for the development of each generation and provide an assessment on the overall success of polymeric micellar delivery system in drug targeting. The emphasis is placed on the design and development of ligand modified, stimuli responsive and multifunctional polymeric micelles for drug targeting.

The influence of drug distribution and drug-target binding on target occupancy : The rate-limiting step approximation

NARCIS (Netherlands)

Witte, de W.E.A.; Vauquelin, G.; Graaf, van der P.H.; Lange, de E.C.M.

2017-01-01

The influence of drug-target binding kinetics on target occupancy can be influenced by drug distribution and diffusion around the target, often referred to as "rebinding" or "diffusion-limited binding". This gives rise to a decreased decline of the drug-target complex concentration as a result of a

Expression proteomics study to determine metallodrug targets and optimal drug combinations.

Science.gov (United States)

Lee, Ronald F S; Chernobrovkin, Alexey; Rutishauser, Dorothea; Allardyce, Claire S; Hacker, David; Johnsson, Kai; Zubarev, Roman A; Dyson, Paul J

2017-05-08

The emerging technique termed functional identification of target by expression proteomics (FITExP) has been shown to identify the key protein targets of anti-cancer drugs. Here, we use this approach to elucidate the proteins involved in the mechanism of action of two ruthenium(II)-based anti-cancer compounds, RAPTA-T and RAPTA-EA in breast cancer cells, revealing significant differences in the proteins upregulated. RAPTA-T causes upregulation of multiple proteins suggesting a broad mechanism of action involving suppression of both metastasis and tumorigenicity. RAPTA-EA bearing a GST inhibiting ethacrynic acid moiety, causes upregulation of mainly oxidative stress related proteins. The approach used in this work could be applied to the prediction of effective drug combinations to test in cancer chemotherapy clinical trials.

Identification of novel small-molecule Ulex europaeus I mimetics for targeted drug delivery.

Science.gov (United States)

Hamashin, Christa; Spindler, Lisa; Russell, Shannon; Schink, Amy; Lambkin, Imelda; O'Mahony, Daniel; Houghten, Richard; Pinilla, Clemencia

2003-11-17

Lectin mimetics have been identified that may have potential application towards targeted drug delivery. Synthetic multivalent polygalloyl constructs effectively competed with Ulex europaeus agglutinin I (UEA1) for binding to intestinal Caco-2 cell membranes.

Pharmacogenomics of GPCR Drug Targets

DEFF Research Database (Denmark)

Hauser, Alexander Sebastian; Chavali, Sreenivas; Masuho, Ikuo

2018-01-01

Natural genetic variation in the human genome is a cause of individual differences in responses to medications and is an underappreciated burden on public health. Although 108 G-protein-coupled receptors (GPCRs) are the targets of 475 (∼34%) Food and Drug Administration (FDA)-approved drugs...... and account for a global sales volume of over 180 billion US dollars annually, the prevalence of genetic variation among GPCRs targeted by drugs is unknown. By analyzing data from 68,496 individuals, we find that GPCRs targeted by drugs show genetic variation within functional regions such as drug......- and effector-binding sites in the human population. We experimentally show that certain variants of μ-opioid and Cholecystokinin-A receptors could lead to altered or adverse drug response. By analyzing UK National Health Service drug prescription and sales data, we suggest that characterizing GPCR variants...

Utilizing Chemical Genomics to Identify Cytochrome b as a Novel Drug Target for Chagas Disease.

Directory of Open Access Journals (Sweden)

Shilpi Khare

2015-07-01

Full Text Available Unbiased phenotypic screens enable identification of small molecules that inhibit pathogen growth by unanticipated mechanisms. These small molecules can be used as starting points for drug discovery programs that target such mechanisms. A major challenge of the approach is the identification of the cellular targets. Here we report GNF7686, a small molecule inhibitor of Trypanosoma cruzi, the causative agent of Chagas disease, and identification of cytochrome b as its target. Following discovery of GNF7686 in a parasite growth inhibition high throughput screen, we were able to evolve a GNF7686-resistant culture of T. cruzi epimastigotes. Clones from this culture bore a mutation coding for a substitution of leucine by phenylalanine at amino acid position 197 in cytochrome b. Cytochrome b is a component of complex III (cytochrome bc1 in the mitochondrial electron transport chain and catalyzes the transfer of electrons from ubiquinol to cytochrome c by a mechanism that utilizes two distinct catalytic sites, QN and QP. The L197F mutation is located in the QN site and confers resistance to GNF7686 in both parasite cell growth and biochemical cytochrome b assays. Additionally, the mutant cytochrome b confers resistance to antimycin A, another QN site inhibitor, but not to strobilurin or myxothiazol, which target the QP site. GNF7686 represents a promising starting point for Chagas disease drug discovery as it potently inhibits growth of intracellular T. cruzi amastigotes with a half maximal effective concentration (EC50 of 0.15 µM, and is highly specific for T. cruzi cytochrome b. No effect on the mammalian respiratory chain or mammalian cell proliferation was observed with up to 25 µM of GNF7686. Our approach, which combines T. cruzi chemical genetics with biochemical target validation, can be broadly applied to the discovery of additional novel drug targets and drug leads for Chagas disease.

Deep-Learning-Based Drug-Target Interaction Prediction.

Science.gov (United States)

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.

Targeted drugs in radiation therapy

International Nuclear Information System (INIS)

Favaudon, V.; Hennequin, C.; Hennequin, C.

2004-01-01

New drugs aiming at the development of targeted therapies have been assayed in combination with ionizing radiation over the past few years. The rationale of this concept comes from the fact that the cytotoxic potential of targeted drugs is limited, thus requiring concomitant association with a cytotoxic agent for the eradication of tumor cells. Conversely a low level of cumulative toxicity is expected from targeted drugs. Most targeted drugs act through inhibition of post-translational modifications of proteins, such as dimerization of growth factor receptors, prenylation reactions, or phosphorylation of tyrosine or serine-threonine residues. Many systems involving the proteasome, neo-angiogenesis promoters, TGF-β, cyclooxygenase or the transcription factor NF-κB, are currently under investigation in hopes they will allow a control of cell proliferation, apoptosis, cell cycle progression, tumor angiogenesis and inflammation. A few drugs have demonstrated an antitumor potential in particular phenotypes. In most instances, however, radiation-drug interactions proved to be strictly additive in terms of cell growth inhibition or induced cell death. Strong potentiation of the response to radiotherapy is expected to require interaction with DNA repair mechanisms. (authors)

Insights into Integrated Lead Generation and Target Identification in Malaria and Tuberculosis Drug Discovery.

Science.gov (United States)

Okombo, John; Chibale, Kelly

2017-07-18

New, safe and effective drugs are urgently needed to treat and control malaria and tuberculosis, which affect millions of people annually. However, financial return on investment in the poor settings where these diseases are mostly prevalent is very minimal to support market-driven drug discovery and development. Moreover, the imminent loss of therapeutic lifespan of existing therapies due to evolution and spread of drug resistance further compounds the urgency to identify novel effective drugs. However, the advent of new public-private partnerships focused on tropical diseases and the recent release of large data sets by pharmaceutical companies on antimalarial and antituberculosis compounds derived from phenotypic whole cell high throughput screening have spurred renewed interest and opened new frontiers in malaria and tuberculosis drug discovery. This Account recaps the existing challenges facing antimalarial and antituberculosis drug discovery, including limitations associated with experimental animal models as well as biological complexities intrinsic to the causative pathogens. We enlist various highlights from a body of work within our research group aimed at identifying and characterizing new chemical leads, and navigating these challenges to contribute toward the global drug discovery and development pipeline in malaria and tuberculosis. We describe a catalogue of in-house efforts toward deriving safe and efficacious preclinical drug development candidates via cell-based medicinal chemistry optimization of phenotypic whole-cell medium and high throughput screening hits sourced from various small molecule chemical libraries. We also provide an appraisal of target-based screening, as invoked in our laboratory for mechanistic evaluation of the hits generated, with particular focus on the enzymes within the de novo pyrimidine biosynthetic and hemoglobin degradation pathways, the latter constituting a heme detoxification process and an associated cysteine

Identification of antimycotic drugs transformation products upon UV exposure

Energy Technology Data Exchange (ETDEWEB)

Casado, Jorge; Rodríguez, Isaac, E-mail: isaac.rodriguez@usc.es; Ramil, María; Cela, Rafael

2015-05-30

Highlights: • Evaluation of antimycotic drugs UV stabilities in model supports. • Simultaneous detection of precursor drugs and transformation products. • Transformation products identification from their scan, accurate MS/MS spectra. • Directed search of identified transformation products in sand and soil samples. • Preliminary toxicity estimations. - Abstract: The reactivity of three imidazolic, environmental persistent antimycotic drugs (clotrimazole, CTZ; ketoconazole, KTZ; and miconazole, MCZ) upon exposure to ultraviolet (UV) radiation is discussed. First, precursor compounds were immobilized in a silicone support which was further exposed to UV light at two different wavelengths: 254 and 365 nm. After solvent desorption, degradation kinetics of the precursor pharmaceuticals, identification of the arising transformation products (TPs) and evaluation of their time-course were investigated by liquid chromatography (LC) with quadrupole time-of-flight (QTOF) mass spectrometry (MS) detection. The three antimycotics displayed similar stabilities when exposed to 254 nm light; however, CTZ was significantly more stable than MCZ and KTZ when irradiated with the 365 nm lamp. TPs identified in silicone supports resulted from de-chlorination, cleavage, intra-molecular cyclization and hydroxylation reactions. Many of these species were also detected when exposing other solid matrices, such as sand and agricultural soil, previously spiked with target compounds, to UV light. The 50% estimated lethal concentration, calculated using the 48-h Daphnia magna test, for the two main TPs of CTZ and MCZ, at both wavelengths, were lower than those corresponding to the precursor drugs.

Identification of antimycotic drugs transformation products upon UV exposure

International Nuclear Information System (INIS)

Casado, Jorge; Rodríguez, Isaac; Ramil, María; Cela, Rafael

2015-01-01

Highlights: • Evaluation of antimycotic drugs UV stabilities in model supports. • Simultaneous detection of precursor drugs and transformation products. • Transformation products identification from their scan, accurate MS/MS spectra. • Directed search of identified transformation products in sand and soil samples. • Preliminary toxicity estimations. - Abstract: The reactivity of three imidazolic, environmental persistent antimycotic drugs (clotrimazole, CTZ; ketoconazole, KTZ; and miconazole, MCZ) upon exposure to ultraviolet (UV) radiation is discussed. First, precursor compounds were immobilized in a silicone support which was further exposed to UV light at two different wavelengths: 254 and 365 nm. After solvent desorption, degradation kinetics of the precursor pharmaceuticals, identification of the arising transformation products (TPs) and evaluation of their time-course were investigated by liquid chromatography (LC) with quadrupole time-of-flight (QTOF) mass spectrometry (MS) detection. The three antimycotics displayed similar stabilities when exposed to 254 nm light; however, CTZ was significantly more stable than MCZ and KTZ when irradiated with the 365 nm lamp. TPs identified in silicone supports resulted from de-chlorination, cleavage, intra-molecular cyclization and hydroxylation reactions. Many of these species were also detected when exposing other solid matrices, such as sand and agricultural soil, previously spiked with target compounds, to UV light. The 50% estimated lethal concentration, calculated using the 48-h Daphnia magna test, for the two main TPs of CTZ and MCZ, at both wavelengths, were lower than those corresponding to the precursor drugs

Drug target ontology to classify and integrate drug discovery data.

Science.gov (United States)

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

Pharmacologic Management of Duchenne Muscular Dystrophy: Target Identification and Preclinical Trials

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Kornegay, Joe N.; Spurney, Christopher F.; Nghiem, Peter P.; Brinkmeyer-Langford, Candice L.; Hoffman, Eric P.; Nagaraju, Kanneboyina

2014-01-01

Duchenne muscular dystrophy (DMD) is an X-linked human disorder in which absence of the protein dystrophin causes degeneration of skeletal and cardiac muscle. For the sake of treatment development, over and above definitive genetic and cell-based therapies, there is considerable interest in drugs that target downstream disease mechanisms. Drug candidates have typically been chosen based on the nature of pathologic lesions and presumed underlying mechanisms and then tested in animal models. Mammalian dystrophinopathies have been characterized in mice (mdx mouse) and dogs (golden retriever muscular dystrophy [GRMD]). Despite promising results in the mdx mouse, some therapies have not shown efficacy in DMD. Although the GRMD model offers a higher hurdle for translation, dogs have primarily been used to test genetic and cellular therapies where there is greater risk. Failed translation of animal studies to DMD raises questions about the propriety of methods and models used to identify drug targets and test efficacy of pharmacologic intervention. The mdx mouse and GRMD dog are genetically homologous to DMD but not necessarily analogous. Subcellular species differences are undoubtedly magnified at the whole-body level in clinical trials. This problem is compounded by disparate cultures in clinical trials and preclinical studies, pointing to a need for greater rigor and transparency in animal experiments. Molecular assays such as mRNA arrays and genome-wide association studies allow identification of genetic drug targets more closely tied to disease pathogenesis. Genes in which polymorphisms have been directly linked to DMD disease progression, as with osteopontin, are particularly attractive targets. PMID:24936034

Paralog-divergent Features May Help Reduce Off-target Effects of Drugs: Hints from Glucagon Subfamily Analysis

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Zhining Sa

2017-08-01

Full Text Available Side effects from targeted drugs remain a serious concern. One reason is the nonselective binding of a drug to unintended proteins such as its paralogs, which are highly homologous in sequences and have similar structures and drug-binding pockets. To identify targetable differences between paralogs, we analyzed two types (type-I and type-II of functional divergence between two paralogs in the known target protein receptor family G-protein coupled receptors (GPCRs at the amino acid level. Paralogous protein receptors in glucagon-like subfamily, glucagon receptor (GCGR and glucagon-like peptide-1 receptor (GLP-1R, exhibit divergence in ligands and are clinically validated drug targets for type 2 diabetes. Our data showed that type-II amino acids were significantly enriched in the binding sites of antagonist MK-0893 to GCGR, which had a radical shift in physicochemical properties between GCGR and GLP-1R. We also examined the role of type-I amino acids between GCGR and GLP-1R. The divergent features between GCGR and GLP-1R paralogs may be helpful in their discrimination, thus enabling the identification of binding sites to reduce undesirable side effects and increase the target specificity of drugs.

Brain tumor-targeted drug delivery strategies

Directory of Open Access Journals (Sweden)

Xiaoli Wei

2014-06-01

Full Text Available Despite the application of aggressive surgery, radiotherapy and chemotherapy in clinics, brain tumors are still a difficult health challenge due to their fast development and poor prognosis. Brain tumor-targeted drug delivery systems, which increase drug accumulation in the tumor region and reduce toxicity in normal brain and peripheral tissue, are a promising new approach to brain tumor treatments. Since brain tumors exhibit many distinctive characteristics relative to tumors growing in peripheral tissues, potential targets based on continuously changing vascular characteristics and the microenvironment can be utilized to facilitate effective brain tumor-targeted drug delivery. In this review, we briefly describe the physiological characteristics of brain tumors, including blood–brain/brain tumor barriers, the tumor microenvironment, and tumor stem cells. We also review targeted delivery strategies and introduce a systematic targeted drug delivery strategy to overcome the challenges.

The AEROPATH project targeting Pseudomonas aeruginosa: crystallographic studies for assessment of potential targets in early-stage drug discovery

International Nuclear Information System (INIS)

Moynie, Lucille; Schnell, Robert; McMahon, Stephen A.; Sandalova, Tatyana; Boulkerou, Wassila Abdelli; Schmidberger, Jason W.; Alphey, Magnus; Cukier, Cyprian; Duthie, Fraser; Kopec, Jolanta; Liu, Huanting; Jacewicz, Agata; Hunter, William N.; Naismith, James H.; Schneider, Gunter

2012-01-01

A focused strategy has been directed towards the structural characterization of selected proteins from the bacterial pathogen P. aeruginosa. The objective is to exploit the resulting structural data, in combination with ligand-binding studies, and to assess the potential of these proteins for early-stage antimicrobial drug discovery. Bacterial infections are increasingly difficult to treat owing to the spread of antibiotic resistance. A major concern is Gram-negative bacteria, for which the discovery of new antimicrobial drugs has been particularly scarce. In an effort to accelerate early steps in drug discovery, the EU-funded AEROPATH project aims to identify novel targets in the opportunistic pathogen Pseudomonas aeruginosa by applying a multidisciplinary approach encompassing target validation, structural characterization, assay development and hit identification from small-molecule libraries. Here, the strategies used for target selection are described and progress in protein production and structure analysis is reported. Of the 102 selected targets, 84 could be produced in soluble form and the de novo structures of 39 proteins have been determined. The crystal structures of eight of these targets, ranging from hypothetical unknown proteins to metabolic enzymes from different functional classes (PA1645, PA1648, PA2169, PA3770, PA4098, PA4485, PA4992 and PA5259), are reported here. The structural information is expected to provide a firm basis for the improvement of hit compounds identified from fragment-based and high-throughput screening campaigns

Identification of control targets in Boolean molecular network models via computational algebra.

Science.gov (United States)

Murrugarra, David; Veliz-Cuba, Alan; Aguilar, Boris; Laubenbacher, Reinhard

2016-09-23

Many problems in biomedicine and other areas of the life sciences can be characterized as control problems, with the goal of finding strategies to change a disease or otherwise undesirable state of a biological system into another, more desirable, state through an intervention, such as a drug or other therapeutic treatment. The identification of such strategies is typically based on a mathematical model of the process to be altered through targeted control inputs. This paper focuses on processes at the molecular level that determine the state of an individual cell, involving signaling or gene regulation. The mathematical model type considered is that of Boolean networks. The potential control targets can be represented by a set of nodes and edges that can be manipulated to produce a desired effect on the system. This paper presents a method for the identification of potential intervention targets in Boolean molecular network models using algebraic techniques. The approach exploits an algebraic representation of Boolean networks to encode the control candidates in the network wiring diagram as the solutions of a system of polynomials equations, and then uses computational algebra techniques to find such controllers. The control methods in this paper are validated through the identification of combinatorial interventions in the signaling pathways of previously reported control targets in two well studied systems, a p53-mdm2 network and a blood T cell lymphocyte granular leukemia survival signaling network. Supplementary data is available online and our code in Macaulay2 and Matlab are available via http://www.ms.uky.edu/~dmu228/ControlAlg . This paper presents a novel method for the identification of intervention targets in Boolean network models. The results in this paper show that the proposed methods are useful and efficient for moderately large networks.

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

Energy Technology Data Exchange (ETDEWEB)

Hao, Ming; Wang, Yanli, E-mail: ywang@ncbi.nlm.nih.gov; Bryant, Stephen H., E-mail: bryant@ncbi.nlm.nih.gov

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. - Graphical abstract: Flowchart of the proposed RLS-KF algorithm for drug-target interaction predictions. - Highlights: • A nonlinear kernel fusion algorithm is proposed to perform drug-target interaction predictions. • Performance can further be improved by using the recalculated kernel. • Top predictions can be validated by experimental data.

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

International Nuclear Information System (INIS)

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

2016-01-01

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. - Graphical abstract: Flowchart of the proposed RLS-KF algorithm for drug-target interaction predictions. - Highlights: • A nonlinear kernel fusion algorithm is proposed to perform drug-target interaction predictions. • Performance can further be improved by using the recalculated kernel. • Top predictions can be validated by experimental data.

Influence networks based on coexpression improve drug target discovery for the development of novel cancer therapeutics

Science.gov (United States)

2014-01-01

Background The demand for novel molecularly targeted drugs will continue to rise as we move forward toward the goal of personalizing cancer treatment to the molecular signature of individual tumors. However, the identification of targets and combinations of targets that can be safely and effectively modulated is one of the greatest challenges facing the drug discovery process. A promising approach is to use biological networks to prioritize targets based on their relative positions to one another, a property that affects their ability to maintain network integrity and propagate information-flow. Here, we introduce influence networks and demonstrate how they can be used to generate influence scores as a network-based metric to rank genes as potential drug targets. Results We use this approach to prioritize genes as drug target candidates in a set of ER + breast tumor samples collected during the course of neoadjuvant treatment with the aromatase inhibitor letrozole. We show that influential genes, those with high influence scores, tend to be essential and include a higher proportion of essential genes than those prioritized based on their position (i.e. hubs or bottlenecks) within the same network. Additionally, we show that influential genes represent novel biologically relevant drug targets for the treatment of ER + breast cancers. Moreover, we demonstrate that gene influence differs between untreated tumors and residual tumors that have adapted to drug treatment. In this way, influence scores capture the context-dependent functions of genes and present the opportunity to design combination treatment strategies that take advantage of the tumor adaptation process. Conclusions Influence networks efficiently find essential genes as promising drug targets and combinations of targets to inform the development of molecularly targeted drugs and their use. PMID:24495353

Integrative Bioinformatics Approaches for Identification of Drug Targets in Hypertension.

Science.gov (United States)

Hemerich, Daiane; van Setten, Jessica; Tragante, Vinicius; Asselbergs, Folkert W

2018-01-01

High blood pressure or hypertension is an established risk factor for a myriad of cardiovascular diseases. Genome-wide association studies have successfully found over nine hundred loci that contribute to blood pressure. However, the mechanisms through which these loci contribute to disease are still relatively undetermined as less than 10% of hypertension-associated variants are located in coding regions. Phenotypic cell-type specificity analyses and expression quantitative trait loci show predominant vascular and cardiac tissue involvement for blood pressure-associated variants. Maps of chromosomal conformation and expression quantitative trait loci (eQTL) in critical tissues identified 2,424 genes interacting with blood pressure-associated loci, of which 517 are druggable. Integrating genome, regulome and transcriptome information in relevant cell-types could help to functionally annotate blood pressure associated loci and identify drug targets.

Utilizing random Forest QSAR models with optimized parameters for target identification and its application to target-fishing server.

Science.gov (United States)

Lee, Kyoungyeul; Lee, Minho; Kim, Dongsup

2017-12-28

The identification of target molecules is important for understanding the mechanism of "target deconvolution" in phenotypic screening and "polypharmacology" of drugs. Because conventional methods of identifying targets require time and cost, in-silico target identification has been considered an alternative solution. One of the well-known in-silico methods of identifying targets involves structure activity relationships (SARs). SARs have advantages such as low computational cost and high feasibility; however, the data dependency in the SAR approach causes imbalance of active data and ambiguity of inactive data throughout targets. We developed a ligand-based virtual screening model comprising 1121 target SAR models built using a random forest algorithm. The performance of each target model was tested by employing the ROC curve and the mean score using an internal five-fold cross validation. Moreover, recall rates for top-k targets were calculated to assess the performance of target ranking. A benchmark model using an optimized sampling method and parameters was examined via external validation set. The result shows recall rates of 67.6% and 73.9% for top-11 (1% of the total targets) and top-33, respectively. We provide a website for users to search the top-k targets for query ligands available publicly at http://rfqsar.kaist.ac.kr . The target models that we built can be used for both predicting the activity of ligands toward each target and ranking candidate targets for a query ligand using a unified scoring scheme. The scores are additionally fitted to the probability so that users can estimate how likely a ligand-target interaction is active. The user interface of our web site is user friendly and intuitive, offering useful information and cross references.

Chemotext: A Publicly Available Web Server for Mining Drug-Target-Disease Relationships in PubMed.

Science.gov (United States)

Capuzzi, Stephen J; Thornton, Thomas E; Liu, Kammy; Baker, Nancy; Lam, Wai In; O'Banion, Colin P; Muratov, Eugene N; Pozefsky, Diane; Tropsha, Alexander

2018-02-26

Elucidation of the mechanistic relationships between drugs, their targets, and diseases is at the core of modern drug discovery research. Thousands of studies relevant to the drug-target-disease (DTD) triangle have been published and annotated in the Medline/PubMed database. Mining this database affords rapid identification of all published studies that confirm connections between vertices of this triangle or enable new inferences of such connections. To this end, we describe the development of Chemotext, a publicly available Web server that mines the entire compendium of published literature in PubMed annotated by Medline Subject Heading (MeSH) terms. The goal of Chemotext is to identify all known DTD relationships and infer missing links between vertices of the DTD triangle. As a proof-of-concept, we show that Chemotext could be instrumental in generating new drug repurposing hypotheses or annotating clinical outcomes pathways for known drugs. The Chemotext Web server is freely available at http://chemotext.mml.unc.edu .

Chemogenomics profiling of drug targets of peptidoglycan biosynthesis pathway in Leptospira interrogans by virtual screening approaches.

Science.gov (United States)

Bhattacharjee, Biplab; Simon, Rose Mary; Gangadharaiah, Chaithra; Karunakar, Prashantha

2013-06-28

Leptospirosis is a worldwide zoonosis of global concern caused by Leptospira interrogans. The availability of ligand libraries has facilitated the search for novel drug targets using chemogenomics approaches, compared with the traditional method of drug discovery, which is time consuming and yields few leads with little intracellular information for guiding target selection. Recent subtractive genomics studies have revealed the putative drug targets in peptidoglycan biosynthesis pathways in Leptospira interrogans. Aligand library for the murD ligase enzyme in the peptidoglycan pathway has also been identified. Our approach in this research involves screening of the pre-existing ligand library of murD with related protein family members in the putative drug target assembly in the peptidoglycan biosynthesis pathway. A chemogenomics approach has been implemented here, which involves screening of known ligands of a protein family having analogous domain architecture for identification of leads for existing druggable protein family members. By means of this approach, one murC and one murF inhibitor were identified, providing a platform for developing an antileptospirosis drug targeting the peptidoglycan biosynthesis pathway. Given that the peptidoglycan biosynthesis pathway is exclusive to bacteria, the in silico identified mur ligase inhibitors are expected to be broad-spectrum Gram-negative inhibitors if synthesized and tested in in vitro and in vivo assays.

Large-scale prediction of drug–target interactions using protein sequences and drug topological structures

International Nuclear Information System (INIS)

Cao Dongsheng; Liu Shao; Xu Qingsong; Lu Hongmei; Huang Jianhua; Hu Qiannan; Liang Yizeng

2012-01-01

Highlights: ► Drug–target interactions are predicted using an extended SAR methodology. ► A drug–target interaction is regarded as an event triggered by many factors. ► Molecular fingerprint and CTD descriptors are used to represent drugs and proteins. ► Our approach shows compatibility between the new scheme and current SAR methodology. - Abstract: The identification of interactions between drugs and target proteins plays a key role in the process of genomic drug discovery. It is both consuming and costly to determine drug–target interactions by experiments alone. Therefore, there is an urgent need to develop new in silico prediction approaches capable of identifying these potential drug–target interactions in a timely manner. In this article, we aim at extending current structure–activity relationship (SAR) methodology to fulfill such requirements. In some sense, a drug–target interaction can be regarded as an event or property triggered by many influence factors from drugs and target proteins. Thus, each interaction pair can be represented theoretically by using these factors which are based on the structural and physicochemical properties simultaneously from drugs and proteins. To realize this, drug molecules are encoded with MACCS substructure fingerings representing existence of certain functional groups or fragments; and proteins are encoded with some biochemical and physicochemical properties. Four classes of drug–target interaction networks in humans involving enzymes, ion channels, G-protein-coupled receptors (GPCRs) and nuclear receptors, are independently used for establishing predictive models with support vector machines (SVMs). The SVM models gave prediction accuracy of 90.31%, 88.91%, 84.68% and 83.74% for four datasets, respectively. In conclusion, the results demonstrate the ability of our proposed method to predict the drug–target interactions, and show a general compatibility between the new scheme and current SAR

Host pharmacokinetics and drug accumulation of anthelmintics within target helminth parasites of ruminants.

Science.gov (United States)

Lifschitz, A; Lanusse, C; Alvarez, L

2017-07-01

pharmacokinetic behaviour and identification of different factors affecting drug activity is important for achieving optimal parasite control and avoiding selection for drug resistance. The search for novel alternatives to deliver enhanced drug concentrations within target helminth parasites may contribute to avoiding misuse, and prolong the lifespan of existing and novel anthelmintic compounds in the veterinary pharmaceutical market.

Targeted Drug-Carrying Bacteriophages as Antibacterial Nanomedicines▿

Science.gov (United States)

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

Nanorobot architecture for medical target identification

International Nuclear Information System (INIS)

Cavalcanti, Adriano; Shirinzadeh, Bijan; Freita, Robert A Jr; Hogg, Tad

2008-01-01

This work has an innovative approach for the development of nanorobots with sensors for medicine. The nanorobots operate in a virtual environment comparing random, thermal and chemical control techniques. The nanorobot architecture model has nanobioelectronics as the basis for manufacturing integrated system devices with embedded nanobiosensors and actuators, which facilitates its application for medical target identification and drug delivery. The nanorobot interaction with the described workspace shows how time actuation is improved based on sensor capabilities. Therefore, our work addresses the control and the architecture design for developing practical molecular machines. Advances in nanotechnology are enabling manufacturing nanosensors and actuators through nanobioelectronics and biologically inspired devices. Analysis of integrated system modeling is one important aspect for supporting nanotechnology in the fast development towards one of the most challenging new fields of science: molecular machines. The use of 3D simulation can provide interactive tools for addressing nanorobot choices on sensing, hardware architecture design, manufacturing approaches, and control methodology investigation

Nanorobot architecture for medical target identification

Energy Technology Data Exchange (ETDEWEB)

Cavalcanti, Adriano [CAN Center for Automation in Nanobiotech, Melbourne VIC 3168 (Australia); Shirinzadeh, Bijan [Robotics and Mechatronics Research Laboratory, Department of Mechanical Engineering, Monash University, Clayton, Melbourne VIC 3800 (Australia); Freita, Robert A Jr [Institute for Molecular Manufacturing, Pilot Hill, CA 95664 (United States); Hogg, Tad [Hewlett-Packard Laboratories, Palo Alto, CA 94304 (United States)

2008-01-09

This work has an innovative approach for the development of nanorobots with sensors for medicine. The nanorobots operate in a virtual environment comparing random, thermal and chemical control techniques. The nanorobot architecture model has nanobioelectronics as the basis for manufacturing integrated system devices with embedded nanobiosensors and actuators, which facilitates its application for medical target identification and drug delivery. The nanorobot interaction with the described workspace shows how time actuation is improved based on sensor capabilities. Therefore, our work addresses the control and the architecture design for developing practical molecular machines. Advances in nanotechnology are enabling manufacturing nanosensors and actuators through nanobioelectronics and biologically inspired devices. Analysis of integrated system modeling is one important aspect for supporting nanotechnology in the fast development towards one of the most challenging new fields of science: molecular machines. The use of 3D simulation can provide interactive tools for addressing nanorobot choices on sensing, hardware architecture design, manufacturing approaches, and control methodology investigation.

Identification of polycystic ovary syndrome potential drug targets based on pathobiological similarity in the protein-protein interaction network

OpenAIRE

Huang, Hao; He, Yuehan; Li, Wan; Wei, Wenqing; Li, Yiran; Xie, Ruiqiang; Guo, Shanshan; Wang, Yahui; Jiang, Jing; Chen, Binbin; Lv, Junjie; Zhang, Nana; Chen, Lina; He, Weiming

2016-01-01

Polycystic ovary syndrome (PCOS) is one of the most common endocrinological disorders in reproductive aged women. PCOS and Type 2 Diabetes (T2D) are closely linked in multiple levels and possess high pathobiological similarity. Here, we put forward a new computational approach based on the pathobiological similarity to identify PCOS potential drug target modules (PPDT-Modules) and PCOS potential drug targets in the protein-protein interaction network (PPIN). From the systems level and biologi...

A genome-wide RNAi screen identifies novel targets of neratinib resistance leading to identification of potential drug resistant genetic markers.

Science.gov (United States)

Seyhan, Attila A; Varadarajan, Usha; Choe, Sung; Liu, Wei; Ryan, Terence E

2012-04-01

Neratinib (HKI-272) is a small molecule tyrosine kinase inhibitor of the ErbB receptor family currently in Phase III clinical trials. Despite its efficacy, the mechanism of potential cellular resistance to neratinib and genes involved with it remains unknown. We have used a pool-based lentiviral genome-wide functional RNAi screen combined with a lethal dose of neratinib to discover chemoresistant interactions with neratinib. Our screen has identified a collection of genes whose inhibition by RNAi led to neratinib resistance including genes involved in oncogenesis (e.g. RAB33A, RAB6A and BCL2L14), transcription factors (e.g. FOXP4, TFEC, ZNF), cellular ion transport (e.g. CLIC3, TRAPPC2P1, P2RX2), protein ubiquitination (e.g. UBL5), cell cycle (e.g. CCNF), and genes known to interact with breast cancer-associated genes (e.g. CCNF, FOXP4, TFEC, several ZNF factors, GNA13, IGFBP1, PMEPA1, SOX5, RAB33A, RAB6A, FXR1, DDO, TFEC, OLFM2). The identification of novel mediators of cellular resistance to neratinib could lead to the identification of new or neoadjuvant drug targets. Their use as patient or treatment selection biomarkers could make the application of anti-ErbB therapeutics more clinically effective.

Drugs and drug delivery systems targeting amyloid-β in Alzheimer's disease

Directory of Open Access Journals (Sweden)

Morgan Robinson

2015-07-01

Full Text Available Alzheimer's disease (AD is a devastating neurodegenerative disorder with no cure and limited treatment solutions that are unable to target any of the suspected causes. Increasing evidence suggests that one of the causes of neurodegeneration is the overproduction of amyloid beta (Aβ and the inability of Aβ peptides to be cleared from the brain, resulting in self-aggregation to form toxic oligomers, fibrils and plaques. One of the potential treatment options is to target Aβ and prevent self-aggregation to allow for a natural clearing of the brain. In this paper, we review the drugs and drug delivery systems that target Aβ in relation to Alzheimer's disease. Many attempts have been made to use anti-Aβ targeting molecules capable of targeting Aβ (with much success in vitro and in vivo animal models, but the major obstacle to this technique is the challenge posed by the blood brain barrier (BBB. This highly selective barrier protects the brain from toxic molecules and pathogens and prevents the delivery of most drugs. Therefore novel Aβ aggregation inhibitor drugs will require well thought-out drug delivery systems to deliver sufficient concentrations to the brain.

The Research Progress of Targeted Drug Delivery Systems

Science.gov (United States)

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.

Killing cancer cells by targeted drug-carrying phage nanomedicines

Directory of Open Access Journals (Sweden)

Yacoby Iftach

2008-04-01

Full Text Available Abstract 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.

Killing cancer cells by targeted drug-carrying phage nanomedicines

Science.gov (United States)

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

Exploring the Trypanosoma brucei Hsp83 potential as a target for structure guided drug design.

Directory of Open Access Journals (Sweden)

Juan Carlos Pizarro

Full Text Available Human African trypanosomiasis is a neglected parasitic disease that is fatal if untreated. The current drugs available to eliminate the causative agent Trypanosoma brucei have multiple liabilities, including toxicity, increasing problems due to treatment failure and limited efficacy. There are two approaches to discover novel antimicrobial drugs--whole-cell screening and target-based discovery. In the latter case, there is a need to identify and validate novel drug targets in Trypanosoma parasites. The heat shock proteins (Hsp, while best known as cancer targets with a number of drug candidates in clinical development, are a family of emerging targets for infectious diseases. In this paper, we report the exploration of T. brucei Hsp83--a homolog of human Hsp90--as a drug target using multiple biophysical and biochemical techniques. Our approach included the characterization of the chemical sensitivity of the parasitic chaperone against a library of known Hsp90 inhibitors by means of differential scanning fluorimetry (DSF. Several compounds identified by this screening procedure were further studied using isothermal titration calorimetry (ITC and X-ray crystallography, as well as tested in parasite growth inhibitions assays. These experiments led us to the identification of a benzamide derivative compound capable of interacting with TbHsp83 more strongly than with its human homologs and structural rationalization of this selectivity. The results highlight the opportunities created by subtle structural differences to develop new series of compounds to selectively target the Trypanosoma brucei chaperone and effectively kill the sleeping sickness parasite.

Drug repurposing to target Ebola virus replication and virulence using structural systems pharmacology.

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Zhao, Zheng; Martin, Che; Fan, Raymond; Bourne, Philip E; Xie, Lei

2016-02-18

The recent outbreak of Ebola has been cited as the largest in history. Despite this global health crisis, few drugs are available to efficiently treat Ebola infections. Drug repurposing provides a potentially efficient solution to accelerating the development of therapeutic approaches in response to Ebola outbreak. To identify such candidates, we use an integrated structural systems pharmacology pipeline which combines proteome-scale ligand binding site comparison, protein-ligand docking, and Molecular Dynamics (MD) simulation. One thousand seven hundred and sixty-six FDA-approved drugs and 259 experimental drugs were screened to identify those with the potential to inhibit the replication and virulence of Ebola, and to determine the binding modes with their respective targets. Initial screening has identified a number of promising hits. Notably, Indinavir; an HIV protease inhibitor, may be effective in reducing the virulence of Ebola. Additionally, an antifungal (Sinefungin) and several anti-viral drugs (e.g. Maraviroc, Abacavir, Telbivudine, and Cidofovir) may inhibit Ebola RNA-directed RNA polymerase through targeting the MTase domain. Identification of safe drug candidates is a crucial first step toward the determination of timely and effective therapeutic approaches to address and mitigate the impact of the Ebola global crisis and future outbreaks of pathogenic diseases. Further in vitro and in vivo testing to evaluate the anti-Ebola activity of these drugs is warranted.

The target landscape of clinical kinase drugs.

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Klaeger, Susan; Heinzlmeir, Stephanie; Wilhelm, Mathias; Polzer, Harald; Vick, Binje; Koenig, Paul-Albert; Reinecke, Maria; Ruprecht, Benjamin; Petzoldt, Svenja; Meng, Chen; Zecha, Jana; Reiter, Katrin; Qiao, Huichao; Helm, Dominic; Koch, Heiner; Schoof, Melanie; Canevari, Giulia; Casale, Elena; Depaolini, Stefania Re; Feuchtinger, Annette; Wu, Zhixiang; Schmidt, Tobias; Rueckert, Lars; Becker, Wilhelm; Huenges, Jan; Garz, Anne-Kathrin; Gohlke, Bjoern-Oliver; Zolg, Daniel Paul; Kayser, Gian; Vooder, Tonu; Preissner, Robert; Hahne, Hannes; Tõnisson, Neeme; Kramer, Karl; Götze, Katharina; Bassermann, Florian; Schlegl, Judith; Ehrlich, Hans-Christian; Aiche, Stephan; Walch, Axel; Greif, Philipp A; Schneider, Sabine; Felder, Eduard Rudolf; Ruland, Juergen; Médard, Guillaume; Jeremias, Irmela; Spiekermann, Karsten; Kuster, Bernhard

2017-12-01

Kinase inhibitors are important cancer therapeutics. Polypharmacology is commonly observed, requiring thorough target deconvolution to understand drug mechanism of action. Using chemical proteomics, we analyzed the target spectrum of 243 clinically evaluated kinase drugs. The data revealed previously unknown targets for established drugs, offered a perspective on the "druggable" kinome, highlighted (non)kinase off-targets, and suggested potential therapeutic applications. Integration of phosphoproteomic data refined drug-affected pathways, identified response markers, and strengthened rationale for combination treatments. We exemplify translational value by discovering SIK2 (salt-inducible kinase 2) inhibitors that modulate cytokine production in primary cells, by identifying drugs against the lung cancer survival marker MELK (maternal embryonic leucine zipper kinase), and by repurposing cabozantinib to treat FLT3-ITD-positive acute myeloid leukemia. This resource, available via the ProteomicsDB database, should facilitate basic, clinical, and drug discovery research and aid clinical decision-making. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Systematic identification of combinatorial drivers and targets in cancer cell lines.

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Adel Tabchy

Full Text Available There is an urgent need to elicit and validate highly efficacious targets for combinatorial intervention from large scale ongoing molecular characterization efforts of tumors. We established an in silico bioinformatic platform in concert with a high throughput screening platform evaluating 37 novel targeted agents in 669 extensively characterized cancer cell lines reflecting the genomic and tissue-type diversity of human cancers, to systematically identify combinatorial biomarkers of response and co-actionable targets in cancer. Genomic biomarkers discovered in a 141 cell line training set were validated in an independent 359 cell line test set. We identified co-occurring and mutually exclusive genomic events that represent potential drivers and combinatorial targets in cancer. We demonstrate multiple cooperating genomic events that predict sensitivity to drug intervention independent of tumor lineage. The coupling of scalable in silico and biologic high throughput cancer cell line platforms for the identification of co-events in cancer delivers rational combinatorial targets for synthetic lethal approaches with a high potential to pre-empt the emergence of resistance.

Systematic identification of combinatorial drivers and targets in cancer cell lines.

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Tabchy, Adel; Eltonsy, Nevine; Housman, David E; Mills, Gordon B

2013-01-01

There is an urgent need to elicit and validate highly efficacious targets for combinatorial intervention from large scale ongoing molecular characterization efforts of tumors. We established an in silico bioinformatic platform in concert with a high throughput screening platform evaluating 37 novel targeted agents in 669 extensively characterized cancer cell lines reflecting the genomic and tissue-type diversity of human cancers, to systematically identify combinatorial biomarkers of response and co-actionable targets in cancer. Genomic biomarkers discovered in a 141 cell line training set were validated in an independent 359 cell line test set. We identified co-occurring and mutually exclusive genomic events that represent potential drivers and combinatorial targets in cancer. We demonstrate multiple cooperating genomic events that predict sensitivity to drug intervention independent of tumor lineage. The coupling of scalable in silico and biologic high throughput cancer cell line platforms for the identification of co-events in cancer delivers rational combinatorial targets for synthetic lethal approaches with a high potential to pre-empt the emergence of resistance.

Design of a tripartite network for the prediction of drug targets

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Kunimoto, Ryo; Bajorath, Jürgen

2018-02-01

Drug-target networks have aided in many target prediction studies aiming at drug repurposing or the analysis of side effects. Conventional drug-target networks are bipartite. They contain two different types of nodes representing drugs and targets, respectively, and edges indicating pairwise drug-target interactions. In this work, we introduce a tripartite network consisting of drugs, other bioactive compounds, and targets from different sources. On the basis of analog relationships captured in the network and so-called neighbor targets of drugs, new drug targets can be inferred. The tripartite network was found to have a stable structure and simulated network growth was accompanied by a steady increase in assortativity, reflecting increasing correlation between degrees of connected nodes leading to even network connectivity. Local drug environments in the tripartite network typically contained neighbor targets and revealed interesting drug-compound-target relationships for further analysis. Candidate targets were prioritized. The tripartite network design extends standard drug-target networks and provides additional opportunities for drug target prediction.

TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models

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Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

2016-05-01

Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com.

TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models.

Science.gov (United States)

Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

2016-05-01

Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com .

P-glycoprotein targeted nanoscale drug carriers

KAUST Repository

Li, Wengang

2013-02-01

Multi-drug resistance (MDR) is a trend whereby tumor cells exposed to one cytotoxic agent develop cross-resistance to a range of structurally and functionally unrelated compounds. P -glycoprotein (P -gp) efflux pump is one of the mostly studied drug carrying processes that shuttle the drugs out of tumor cells. Thus, P -gp inhibitors have attracted a lot of attention as they can stop cancer drugs from being pumped out of target cells with the consumption of ATP. Using quantitive structure activity relationship (QSAR), we have successfully synthesized a series of novel P -gp inhibitors. The obtained dihydropyrroloquinoxalines series were fully characterized and then tested against bacterial and tumor assays with over-expressed P -gps. All compounds were bioactive especially compound 1c that had enhanced antibacterial activity. Furthermore, these compounds were utilized as targeting vectors to direct drug delivery vehicles such as silica nanoparticles (SNPs) to cancerous Hela cells with over expressed P -gps. Cell uptake studies showed a successful accumulation of these decorated SNPs in tumor cells compared to undecorated SNPs. The results obtained show that dihydropyrroloquinoxalines constitute a promising drug candidate for targeting cancers with MDR. Copyright © 2013 American Scientific Publishers All rights reserved.

Target-mediated drug disposition with drug-drug interaction, Part I: single drug case in alternative formulations.

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Koch, Gilbert; Jusko, William J; Schropp, Johannes

2017-02-01

Target-mediated drug disposition (TMDD) describes drug binding with high affinity to a target such as a receptor. In application TMDD models are often over-parameterized and quasi-equilibrium (QE) or quasi-steady state (QSS) approximations are essential to reduce the number of parameters. However, implementation of such approximations becomes difficult for TMDD models with drug-drug interaction (DDI) mechanisms. Hence, alternative but equivalent formulations are necessary for QE or QSS approximations. To introduce and develop such formulations, the single drug case is reanalyzed. This work opens the route for straightforward implementation of QE or QSS approximations of DDI TMDD models. The manuscript is the first part to introduce DDI TMDD models with QE or QSS approximations.

Application of Combination High-Throughput Phenotypic Screening and Target Identification Methods for the Discovery of Natural Product-Based Combination Drugs.

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Isgut, Monica; Rao, Mukkavilli; Yang, Chunhua; Subrahmanyam, Vangala; Rida, Padmashree C G; Aneja, Ritu

2018-03-01

Modern drug discovery efforts have had mediocre success rates with increasing developmental costs, and this has encouraged pharmaceutical scientists to seek innovative approaches. Recently with the rise of the fields of systems biology and metabolomics, network pharmacology (NP) has begun to emerge as a new paradigm in drug discovery, with a focus on multiple targets and drug combinations for treating disease. Studies on the benefits of drug combinations lay the groundwork for a renewed focus on natural products in drug discovery. Natural products consist of a multitude of constituents that can act on a variety of targets in the body to induce pharmacodynamic responses that may together culminate in an additive or synergistic therapeutic effect. Although natural products cannot be patented, they can be used as starting points in the discovery of potent combination therapeutics. The optimal mix of bioactive ingredients in natural products can be determined via phenotypic screening. The targets and molecular mechanisms of action of these active ingredients can then be determined using chemical proteomics, and by implementing a reverse pharmacokinetics approach. This review article provides evidence supporting the potential benefits of natural product-based combination drugs, and summarizes drug discovery methods that can be applied to this class of drugs. © 2017 Wiley Periodicals, Inc.

Anti-malarial Drug Design by Targeting Apicoplasts: New Perspectives

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Avinaba Mukherjee

2016-03-01

Full Text Available Objectives: Malaria has been a major global health problem in recent times with increasing mortality. Current treatment methods include parasiticidal drugs and vaccinations. However, resistance among malarial parasites to the existing drugs has emerged as a significant area of concern in anti-malarial drug design. Researchers are now desperately looking for new targets to develop anti-malarials drug which is more target specific. Malarial parasites harbor a plastid-like organelle known as the ‘apicoplast’, which is thought to provide an exciting new outlook for the development of drugs to be used against the parasite. This review elaborates on the current state of development of novel compounds targeted againstemerging malaria parasites. Methods: The apicoplast, originates by an endosymbiotic process, contains a range of metabolic pathways and housekeeping processes that differ from the host body and thereby presents ideal strategies for anti-malarial drug therapy. Drugs are designed by targeting the unique mechanism of the apicoplasts genetic machinery. Several anabolic and catabolic processes, like fatty acid, isopenetyl diphosphate and heme synthess in this organelle, have also been targeted by drugs. Results: Apicoplasts offer exciting opportunities for the development of malarial treatment specific drugs have been found to act by disrupting this organelle’s function, which wouldimpede the survival of the parasite. Conclusion: Recent advanced drugs, their modes of action, and their advantages in the treatment of malaria by using apicoplasts as a target are discussed in this review which thought to be very useful in desigining anti-malarial drugs. Targetting the genetic machinery of apicoplast shows a great advantange regarding anti-malarial drug design. Critical knowledge of these new drugs would give a healthier understanding for deciphering the mechanism of action of anti-malarial drugs when targeting apicoplasts to overcome drug

The drug-minded protein interaction database (DrumPID) for efficient target analysis and drug development.

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Kunz, Meik; Liang, Chunguang; Nilla, Santosh; Cecil, Alexander; Dandekar, Thomas

2016-01-01

The drug-minded protein interaction database (DrumPID) has been designed to provide fast, tailored information on drugs and their protein networks including indications, protein targets and side-targets. Starting queries include compound, target and protein interactions and organism-specific protein families. Furthermore, drug name, chemical structures and their SMILES notation, affected proteins (potential drug targets), organisms as well as diseases can be queried including various combinations and refinement of searches. Drugs and protein interactions are analyzed in detail with reference to protein structures and catalytic domains, related compound structures as well as potential targets in other organisms. DrumPID considers drug functionality, compound similarity, target structure, interactome analysis and organismic range for a compound, useful for drug development, predicting drug side-effects and structure-activity relationships.Database URL:http://drumpid.bioapps.biozentrum.uni-wuerzburg.de. © The Author(s) 2016. Published by Oxford University Press.

Drug-target interaction prediction: A Bayesian ranking approach.

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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

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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

Tumor targeting using liposomal antineoplastic drugs

Directory of Open Access Journals (Sweden)

Jörg Huwyler

2008-03-01

Full Text Available Jörg Huwyler1, Jürgen Drewe2, Stephan Krähenbühl21University of Applied Sciences Northwestern Switzerland, Institute of Pharma Technology, Muttenz, Switzerland; 2Department of Research and Division of Clinical Pharmacology, University Hospital Basel, Basel, SwitzerlandAbstract: During the last years, liposomes (microparticulate phospholipid vesicles have beenused with growing success as pharmaceutical carriers for antineoplastic drugs. Fields of application include lipid-based formulations to enhance the solubility of poorly soluble antitumordrugs, the use of pegylated liposomes for passive targeting of solid tumors as well as vector-conjugated liposomal carriers for active targeting of tumor tissue. Such formulation and drug targeting strategies enhance the effectiveness of anticancer chemotherapy and reduce at the same time the risk of toxic side-effects. The present article reviews the principles of different liposomal technologies and discusses current trends in this field of research.Keywords: tumor targeting, antineoplastic drugs, liposomes, pegylation, steric stabilization, immunoliposomes

2013 Philip S. Portoghese Medicinal Chemistry Lectureship: Drug Discovery Targeting Allosteric Sites†

Science.gov (United States)

2015-01-01

The identification of sites on receptors topographically distinct from the orthosteric sites, so-called allosteric sites, has heralded novel approaches and modes of pharmacology for target modulation. Over the past 20 years, our understanding of allosteric modulation has grown significantly, and numerous advantages, as well as caveats (e.g., flat structure–activity relationships, species differences, “molecular switches”), have been identified. For multiple receptors and proteins, numerous examples have been described where unprecedented levels of selectivity are achieved along with improved physiochemical properties. While not a panacea, these novel approaches represent exciting opportunities for tool compound development to probe the pharmacology and therapeutic potential of discrete molecular targets, as well as new medicines. In this Perspective, in commemoration of the 2013 Philip S. Portoghese Medicinal Chemistry Lectureship (LindsleyC. W.Adventures in allosteric drug discovery. Presented at the 246th National Meeting of the American Chemical Society, Indianapolis, IN, September 10, 2013; The 2013 Portoghese Lectureship), several vignettes of drug discovery campaigns targeting novel allosteric mechanisms will be recounted, along with lessons learned and guidelines that have emerged for successful lead optimization. PMID:25180768

Metabolic network analysis-based identification of antimicrobial drug targets in category A bioterrorism agents.

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Yong-Yeol Ahn

Full Text Available The 2001 anthrax mail attacks in the United States demonstrated the potential threat of bioterrorism, hence driving the need to develop sophisticated treatment and diagnostic protocols to counter biological warfare. Here, by performing flux balance analyses on the fully-annotated metabolic networks of multiple, whole genome-sequenced bacterial strains, we have identified a large number of metabolic enzymes as potential drug targets for each of the three Category A-designated bioterrorism agents including Bacillus anthracis, Francisella tularensis and Yersinia pestis. Nine metabolic enzymes- belonging to the coenzyme A, folate, phosphatidyl-ethanolamine and nucleic acid pathways common to all strains across the three distinct genera were identified as targets. Antimicrobial agents against some of these enzymes are available. Thus, a combination of cross species-specific antibiotics and common antimicrobials against shared targets may represent a useful combinatorial therapeutic approach against all Category A bioterrorism agents.

Pharmacogenomics of GPCR Drug Targets

DEFF Research Database (Denmark)

Hauser, Alexander Sebastian; Chavali, Sreenivas; Masuho, Ikuo

2018-01-01

Natural genetic variation in the human genome is a cause of individual differences in responses to medications and is an underappreciated burden on public health. Although 108 G-protein-coupled receptors (GPCRs) are the targets of 475 (∼34%) Food and Drug Administration (FDA)-approved drugs and a...

Biodegradable polymers for targeted delivery of anti-cancer drugs.

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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.

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

Science.gov (United States)

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.

Molecularly targeted drugs for metastatic colorectal cancer

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Cheng YD

2013-11-01

Full Text Available Ying-dong Cheng, Hua Yang, Guo-qing Chen, Zhi-cao Zhang Department of General Surgery, Xinqiao Hospital, Third Military Medical University, Chongqing, People's Republic of China Abstract: The survival rate of patients with metastatic colorectal cancer (mCRC has significantly improved with applications of molecularly targeted drugs, such as bevacizumab, and led to a substantial improvement in the overall survival rate. These drugs are capable of specifically targeting the inherent abnormal pathways in cancer cells, which are potentially less toxic than traditional nonselective chemotherapeutics. In this review, the recent clinical information about molecularly targeted therapy for mCRC is summarized, with specific focus on several of the US Food and Drug Administration-approved molecularly targeted drugs for the treatment of mCRC in the clinic. Progression-free and overall survival in patients with mCRC was improved greatly by the addition of bevacizumab and/or cetuximab to standard chemotherapy, in either first- or second-line treatment. Aflibercept has been used in combination with folinic acid (leucovorin–fluorouracil–irinotecan (FOLFIRI chemotherapy in mCRC patients and among patients with mCRC with wild-type KRAS, the outcomes were significantly improved by panitumumab in combination with folinic acid (leucovorin–fluorouracil–oxaliplatin (FOLFOX or FOLFIRI. Because of the new preliminary studies, it has been recommended that regorafenib be used with FOLFOX or FOLFIRI as first- or second-line treatment of mCRC chemotherapy. In summary, an era of new opportunities has been opened for treatment of mCRC and/or other malignancies, resulting from the discovery of new selective targeting drugs. Keywords: metastatic colorectal cancer (mCRC, antiangiogenic drug, bevacizumab, aflibercept, regorafenib, cetuximab, panitumumab, clinical trial, molecularly targeted therapy

Targeted Delivery of Protein Drugs by Nanocarriers

Directory of Open Access Journals (Sweden)

Antonella Battisti

2010-03-01

Full Text Available Recent advances in biotechnology demonstrate that peptides and proteins are the basis of a new generation of drugs. However, the transportation of protein drugs in the body is limited by their high molecular weight, which prevents the crossing of tissue barriers, and by their short lifetime due to immuno response and enzymatic degradation. Moreover, the ability to selectively deliver drugs to target organs, tissues or cells is a major challenge in the treatment of several human diseases, including cancer. Indeed, targeted delivery can be much more efficient than systemic application, while improving bioavailability and limiting undesirable side effects. This review describes how the use of targeted nanocarriers such as nanoparticles and liposomes can improve the pharmacokinetic properties of protein drugs, thus increasing their safety and maximizing the therapeutic effect.

Emerging technologies, recent developments, and novel applications for drug metabolite identification.

Science.gov (United States)

Lu, Wenjie; Xu, Youzhi; Zhao, Yinglan; Cen, Xiaobo

2014-01-01

Drug metabolite identification and metabolic characteristics analysis play a crucial role in new drug research and development, because they can lead to varied efficacy, severe adverse reactions, and even toxicity. Classical methodologies for metabolite identification have mainly been based on mass spectrometry (MS) coupled with gas chromatography (GC) or liquid chromatography (LC), and some other techniques are used as complementary approaches, such as nuclear magnetic resonance (NMR). Over the past decade, more and more newly emerging techniques or technologies have been applied to metabolite identification, and are making the procedure easier and more robust, such as LC-NMR-MS, ion mobility MS, ambient ionization techniques, and imaging MS. A novel application of drug metabolite identification based on "omics" known as pharmacometabonomics is discussed, which is an interdisciplinary field that combines pre-dose metabolite profiling and chemometrics methods for data analysis and modeling, aiming to predict the responses of individuals to drugs.

Recent advances in targeted drug therapy for hepatocellular carcinoma

Directory of Open Access Journals (Sweden)

FAN Yongqiang

2018-02-01

Full Text Available More and more clinical trials have proved the efficacy of targeted drugs in the treatment of hepatocellular carcinoma (HCC. With the development of science and technology, more and more targeted drugs have appeared. In recent years, targeted drugs such as regorafenib and ramucirumab have shown great potential in related clinical trials. In addition, there are ongoing clinical trials for second-line candidate drugs, such as c-Met inhibitors tivantinib and cabozantinib and a VEGFR-2 inhibitor ramucirumab. This article summarizes the advances in targeted drug therapy for HCC and related trial data, which provides a reference for further clinical trials and treatment.

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

Science.gov (United States)

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.

3D high-content screening for the identification of compounds that target cells in dormant tumor spheroid regions

Energy Technology Data Exchange (ETDEWEB)

Wenzel, Carsten; Riefke, Björn; Gründemann, Stephan; Krebs, Alice; Christian, Sven; Prinz, Florian; Osterland, Marc; Golfier, Sven; Räse, Sebastian [Bayer Pharma AG, Global Drug Discovery, Muellerstrasse 178, 13353 Berlin (Germany); Ansari, Nariman [Physical Biology Group, Buchmann Institute for Molecular Life Sciences (BMLS), Goethe University Frankfurt (Germany); Esner, Milan; Bickle, Marc [Max Planck Institute of Molecular Cell Biology and Genetics, High-Throughput Technology Development Studio (TDS), Dresden (Germany); Pampaloni, Francesco; Mattheyer, Christian; Stelzer, Ernst H. [Physical Biology Group, Buchmann Institute for Molecular Life Sciences (BMLS), Goethe University Frankfurt (Germany); Parczyk, Karsten; Prechtl, Stefan [Bayer Pharma AG, Global Drug Discovery, Muellerstrasse 178, 13353 Berlin (Germany); Steigemann, Patrick, E-mail: Patrick.Steigemann@bayer.com [Bayer Pharma AG, Global Drug Discovery, Muellerstrasse 178, 13353 Berlin (Germany)

2014-04-15

Cancer cells in poorly vascularized tumor regions need to adapt to an unfavorable metabolic microenvironment. As distance from supplying blood vessels increases, oxygen and nutrient concentrations decrease and cancer cells react by stopping cell cycle progression and becoming dormant. As cytostatic drugs mainly target proliferating cells, cancer cell dormancy is considered as a major resistance mechanism to this class of anti-cancer drugs. Therefore, substances that target cancer cells in poorly vascularized tumor regions have the potential to enhance cytostatic-based chemotherapy of solid tumors. With three-dimensional growth conditions, multicellular tumor spheroids (MCTS) reproduce several parameters of the tumor microenvironment, including oxygen and nutrient gradients as well as the development of dormant tumor regions. We here report the setup of a 3D cell culture compatible high-content screening system and the identification of nine substances from two commercially available drug libraries that specifically target cells in inner MCTS core regions, while cells in outer MCTS regions or in 2D cell culture remain unaffected. We elucidated the mode of action of the identified compounds as inhibitors of the respiratory chain and show that induction of cell death in inner MCTS core regions critically depends on extracellular glucose concentrations. Finally, combinational treatment with cytostatics showed increased induction of cell death in MCTS. The data presented here shows for the first time a high-content based screening setup on 3D tumor spheroids for the identification of substances that specifically induce cell death in inner tumor spheroid core regions. This validates the approach to use 3D cell culture screening systems to identify substances that would not be detectable by 2D based screening in otherwise similar culture conditions. - Highlights: • Establishment of a novel method for 3D cell culture based high-content screening. • First reported high

3D high-content screening for the identification of compounds that target cells in dormant tumor spheroid regions

International Nuclear Information System (INIS)

Wenzel, Carsten; Riefke, Björn; Gründemann, Stephan; Krebs, Alice; Christian, Sven; Prinz, Florian; Osterland, Marc; Golfier, Sven; Räse, Sebastian; Ansari, Nariman; Esner, Milan; Bickle, Marc; Pampaloni, Francesco; Mattheyer, Christian; Stelzer, Ernst H.; Parczyk, Karsten; Prechtl, Stefan; Steigemann, Patrick

2014-01-01

Cancer cells in poorly vascularized tumor regions need to adapt to an unfavorable metabolic microenvironment. As distance from supplying blood vessels increases, oxygen and nutrient concentrations decrease and cancer cells react by stopping cell cycle progression and becoming dormant. As cytostatic drugs mainly target proliferating cells, cancer cell dormancy is considered as a major resistance mechanism to this class of anti-cancer drugs. Therefore, substances that target cancer cells in poorly vascularized tumor regions have the potential to enhance cytostatic-based chemotherapy of solid tumors. With three-dimensional growth conditions, multicellular tumor spheroids (MCTS) reproduce several parameters of the tumor microenvironment, including oxygen and nutrient gradients as well as the development of dormant tumor regions. We here report the setup of a 3D cell culture compatible high-content screening system and the identification of nine substances from two commercially available drug libraries that specifically target cells in inner MCTS core regions, while cells in outer MCTS regions or in 2D cell culture remain unaffected. We elucidated the mode of action of the identified compounds as inhibitors of the respiratory chain and show that induction of cell death in inner MCTS core regions critically depends on extracellular glucose concentrations. Finally, combinational treatment with cytostatics showed increased induction of cell death in MCTS. The data presented here shows for the first time a high-content based screening setup on 3D tumor spheroids for the identification of substances that specifically induce cell death in inner tumor spheroid core regions. This validates the approach to use 3D cell culture screening systems to identify substances that would not be detectable by 2D based screening in otherwise similar culture conditions. - Highlights: • Establishment of a novel method for 3D cell culture based high-content screening. • First reported high

A General Strategy for Targeting Drugs to Bone.

Science.gov (United States)

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.

Carrier-free, functionalized pure drug nanorods as a novel cancer-targeted drug delivery platform

International Nuclear Information System (INIS)

Li Yanan; An Feifei; Zhang Xiaohong; Yang Yinlong; Liu Zhuang; Zhang Xiujuan

2013-01-01

A one-dimensional drug delivery system (1D DDS) is highly attractive since it has distinct advantages such as enhanced drug efficiency and better pharmacokinetics. However, drugs in 1D DDSs are all encapsulated in inert carriers, and problems such as low drug loading content and possible undesirable side effects caused by the carriers remain a serious challenge. In this paper, a novel, carrier-free, pure drug nanorod-based, tumor-targeted 1D DDS has been developed. Drugs are first prepared as nanorods and then surface functionalized to achieve excellent water dispersity and stability. The resulting drug nanorods show enhanced internalization rates mainly through energy-dependent endocytosis, with the shape-mediated nanorod (NR) diffusion process as a secondary pathway. The multiple endocytotic mechanisms lead to significantly improved drug efficiency of functionalized NRs with nearly ten times higher cytotoxicity than those of free molecules and unfunctionalized NRs. A targeted drug delivery system can be readily achieved through surface functionalization with targeting group linked amphipathic surfactant, which exhibits significantly enhanced drug efficacy and discriminates between cell lines with high selectivity. These results clearly show that this tumor-targeting DDS demonstrates high potential toward specific cancer cell lines. (paper)

Predicting drug-target interactions using restricted Boltzmann machines.

Science.gov (United States)

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

Camouflage, detection and identification of moving targets.

Science.gov (United States)

Hall, Joanna R; Cuthill, Innes C; Baddeley, Roland; Shohet, Adam J; Scott-Samuel, Nicholas E

2013-05-07

Nearly all research on camouflage has investigated its effectiveness for concealing stationary objects. However, animals have to move, and patterns that only work when the subject is static will heavily constrain behaviour. We investigated the effects of different camouflages on the three stages of predation-detection, identification and capture-in a computer-based task with humans. An initial experiment tested seven camouflage strategies on static stimuli. In line with previous literature, background-matching and disruptive patterns were found to be most successful. Experiment 2 showed that if stimuli move, an isolated moving object on a stationary background cannot avoid detection or capture regardless of the type of camouflage. Experiment 3 used an identification task and showed that while camouflage is unable to slow detection or capture, camouflaged targets are harder to identify than uncamouflaged targets when similar background objects are present. The specific details of the camouflage patterns have little impact on this effect. If one has to move, camouflage cannot impede detection; but if one is surrounded by similar targets (e.g. other animals in a herd, or moving background distractors), then camouflage can slow identification. Despite previous assumptions, motion does not entirely 'break' camouflage.

The periplasmic protein TolB as a potential drug target in Pseudomonas aeruginosa.

Directory of Open Access Journals (Sweden)

Alessandra Lo Sciuto

Full Text Available The Gram-negative bacterium Pseudomonas aeruginosa is one of the most dreaded pathogens in the hospital setting, and represents a prototype of multi-drug resistant "superbug" for which effective therapeutic options are very limited. The identification and characterization of new cellular functions that are essential for P. aeruginosa viability and/or virulence could drive the development of anti-Pseudomonas compounds with novel mechanisms of action. In this study we investigated whether TolB, the periplasmic component of the Tol-Pal trans-envelope protein complex of Gram-negative bacteria, represents a potential drug target in P. aeruginosa. By combining conditional mutagenesis with the analysis of specific pathogenicity-related phenotypes, we demonstrated that TolB is essential for P. aeruginosa growth, both in laboratory and clinical strains, and that TolB-depleted P. aeruginosa cells are strongly defective in cell-envelope integrity, resistance to human serum and several antibiotics, as well as in the ability to cause infection and persist in an insect model of P. aeruginosa infection. The essentiality of TolB for P. aeruginosa growth, resistance and pathogenicity highlights the potential of TolB as a novel molecular target for anti-P. aeruginosa drug discovery.

Tyrosine aminotransferase from Leishmania infantum: A new drug target candidate

Directory of Open Access Journals (Sweden)

Miguel Angel Moreno

2014-12-01

Full Text Available Leishmania infantum is the etiological agent of zoonotic visceral leishmaniasis in the Mediterranean basin. The disease is fatal without treatment, which has been based on antimonial pentavalents for more than 60 years. Due to resistances, relapses and toxicity to current treatment, the development of new drugs is required. The structure of the L. infantum tyrosine aminotransferase (LiTAT has been recently solved showing important differences with the mammalian orthologue. The characterization of LiTAT is reported herein. This enzyme is cytoplasmic and is over-expressed in the more infective stages and nitric oxide resistant parasites. Unlike the mammalian TAT, LiTAT is able to use ketomethiobutyrate as co-substrate. The pharmacophore model of LiTAT with this specific co-substrate is described herein. This may allow the identification of new inhibitors present in the databases. All the data obtained support that LiTAT is a good target candidate for the development of new anti-leishmanial drugs.

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

Science.gov (United States)

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.

Polymeric micelles as a drug carrier for tumor targeting

Directory of Open Access Journals (Sweden)

Neha M Dand

2013-01-01

Full Text Available Polymeric micelle can be targeted to tumor site by passive and active mechanism. Some inherent properties of polymeric micelle such as size in nanorange, stability in plasma, longevity in vivo, and pathological characteristics of tumor make polymeric micelles to be targeted at the tumor site by passive mechanism called enhanced permeability and retention effect. Polymeric micelle formed from the amphiphilic block copolymer is suitable for encapsulation of poorly water soluble, hydrophobic anticancer drugs. Other characteristics of polymeric micelles such as separated functionality at the outer shell are useful for targeting the anticancer drug to tumor by active mechanisms. Polymeric micelles can be conjugated with many ligands such as antibodies fragments, epidermal growth factors, α2 -glycoprotein, transferrine, and folate to target micelles to cancer cells. Application of heat and ultrasound are the alternative methods to enhance drug accumulation in tumoral cells. Targeting using micelles can also be done to tumor angiogenesis which is the potentially promising target for anticancer drugs. This review summarizes about recently available information regarding targeting the anticancer drug to the tumor site using polymeric micelles.

Proteins with complex architecture as potential targets for drug design: a case study of Mycobacterium tuberculosis.

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Bálint Mészáros

2011-07-01

Full Text Available Lengthy co-evolution of Homo sapiens and Mycobacterium tuberculosis, the main causative agent of tuberculosis, resulted in a dramatically successful pathogen species that presents considerable challenge for modern medicine. The continuous and ever increasing appearance of multi-drug resistant mycobacteria necessitates the identification of novel drug targets and drugs with new mechanisms of action. However, further insights are needed to establish automated protocols for target selection based on the available complete genome sequences. In the present study, we perform complete proteome level comparisons between M. tuberculosis, mycobacteria, other prokaryotes and available eukaryotes based on protein domains, local sequence similarities and protein disorder. We show that the enrichment of certain domains in the genome can indicate an important function specific to M. tuberculosis. We identified two families, termed pkn and PE/PPE that stand out in this respect. The common property of these two protein families is a complex domain organization that combines species-specific regions, commonly occurring domains and disordered segments. Besides highlighting promising novel drug target candidates in M. tuberculosis, the presented analysis can also be viewed as a general protocol to identify proteins involved in species-specific functions in a given organism. We conclude that target selection protocols should be extended to include proteins with complex domain architectures instead of focusing on sequentially unique and essential proteins only.

Di/tri-peptide transporters as drug delivery targets

DEFF Research Database (Denmark)

Nielsen, C U; Brodin, Birger

2003-01-01

-dependent, and the transporters thus belong to the Proton-dependent Oligopeptide Transporter (POT)-family. The transporters are not drug targets per se, however due to their uniquely broad substrate specificity; they have proved to be relevant drug targets at the level of drug transport. Drug molecules such as oral active beta....../tri-peptide transporters from vesicular storages 3) changes in gene transcription/mRNA stability. The aim of the present review is to discuss physiological, patho-physiological and drug-induced regulation of di/tri-peptide transporter mediated transport....

[Thalidomide teratogenicity and its direct target identification].

Science.gov (United States)

Ito, Takumi; Ando, Hideki; Handa, Hiroshi

2015-01-01

Half a century ago, thalidomide was developed as a sedative drug and was wildly used over 40 countries. However the drug has serious birth defects such as amelia and phocomelia. Now thalidomide is regarded as a clinically effective drug and used for the treatment of multiple myeloma under strict controls. The direct target of thalidomide had been a long-standing question. We identified cereblon as a primary direct target protein for thalidomide teratogenicity using new affinity bead technology in 2010. In this review, we introduce an overview of thalidomide teratogenicity, a story about how we identified cereblon, and recent advances in cereblon studies.

A computational approach to finding novel targets for existing drugs.

Directory of Open Access Journals (Sweden)

Yvonne Y Li

2011-09-01

Full Text Available 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.

Self-Assembled Smart Nanocarriers for Targeted Drug Delivery.

Science.gov (United States)

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.

A review on target drug delivery: magnetic microspheres

OpenAIRE

Amit Chandna; Deepa Batra; Satinder Kakar; Ramandeep Singh

2013-01-01

Novel drug delivery system aims to deliver the drug at a rate directed by the needs of the body during the period of treatment, and target the active entity to the site of action. A number of novel drug delivery systems have emerged encompassing various routes of administration, to achieve controlled and targeted drug delivery, magnetic micro carriers being one of them. Magnetic microsphere is newer approach in pharmaceutical field. Magnetic microspheres as an alternative to traditional ra...

MODELING OF TARGETED DRUG DELIVERY PART II. MULTIPLE DRUG ADMINISTRATION

Directory of Open Access Journals (Sweden)

A. V. Zaborovskiy

2017-01-01

Full Text Available In oncology practice, despite significant advances in early cancer detection, surgery, radiotherapy, laser therapy, targeted therapy, etc., chemotherapy is unlikely to lose its relevance in the near future. In this context, the development of new antitumor agents is one of the most important problems of cancer research. In spite of the importance of searching for new compounds with antitumor activity, the possibilities of the “old” agents have not been fully exhausted. Targeted delivery of antitumor agents can give them a “second life”. When developing new targeted drugs and their further introduction into clinical practice, the change in their pharmacodynamics and pharmacokinetics plays a special role. The paper describes a pharmacokinetic model of the targeted drug delivery. The conditions under which it is meaningful to search for a delivery vehicle for the active substance were described. Primary screening of antitumor agents was undertaken to modify them for the targeted delivery based on underlying assumptions of the model.

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Anna Cichonska

2017-08-01

-based modeling approach offers practical benefits for probing novel insights into the mode of action of investigational compounds, and for the identification of new target selectivities for drug repurposing applications.

Network Understanding of Herb Medicine via Rapid Identification of Ingredient-Target Interactions

Science.gov (United States)

Zhang, Hai-Ping; Pan, Jian-Bo; Zhang, Chi; Ji, Nan; Wang, Hao; Ji, Zhi-Liang

2014-01-01

Today, herb medicines have become the major source for discovery of novel agents in countermining diseases. However, many of them are largely under-explored in pharmacology due to the limitation of current experimental approaches. Therefore, we proposed a computational framework in this study for network understanding of herb pharmacology via rapid identification of putative ingredient-target interactions in human structural proteome level. A marketing anti-cancer herb medicine in China, Yadanzi (Brucea javanica), was chosen for mechanistic study. Total 7,119 ingredient-target interactions were identified for thirteen Yadanzi active ingredients. Among them, about 29.5% were estimated to have better binding affinity than their corresponding marketing drug-target interactions. Further Bioinformatics analyses suggest that simultaneous manipulation of multiple proteins in the MAPK signaling pathway and the phosphorylation process of anti-apoptosis may largely answer for Yadanzi against non-small cell lung cancers. In summary, our strategy provides an efficient however economic solution for systematic understanding of herbs' power.

Drug targeting to tumors: principles, pitfalls and (pre-) clinical progress

NARCIS (Netherlands)

Lammers, Twan Gerardus Gertudis Maria; Kiessling, F.; Hennink, W.E.; Storm, Gerrit

2012-01-01

Abstract Many different systems and strategies have been evaluated for drug targeting to tumors over the years. Routinely used systems include liposomes, polymers, micelles, nanoparticles and antibodies, and examples of strategies are passive drug targeting, active drug targeting to cancer cells,

Structure and organization of drug-target networks: insights from genomic approaches for drug discovery.

Science.gov (United States)

Janga, Sarath Chandra; Tzakos, Andreas

2009-12-01

Recent years have seen an explosion in the amount of "omics" data and the integration of several disciplines, which has influenced all areas of life sciences including that of drug discovery. Several lines of evidence now suggest that the traditional notion of "one drug-one protein" for one disease does not hold any more and that treatment for most complex diseases can best be attempted using polypharmacological approaches. In this review, we formalize the definition of a drug-target network by decomposing it into drug, target and disease spaces and provide an overview of our understanding in recent years about its structure and organizational principles. We discuss advances made in developing promiscuous drugs following the paradigm of polypharmacology and reveal their advantages over traditional drugs for targeting diseases such as cancer. We suggest that drug-target networks can be decomposed to be studied at a variety of levels and argue that such network-based approaches have important implications in understanding disease phenotypes and in accelerating drug discovery. We also discuss the potential and scope network pharmacology promises in harnessing the vast amount of data from high-throughput approaches for therapeutic advantage.

Drug research methodology. Volume 2, The identification of drugs of interest in highway safety

Science.gov (United States)

1980-03-01

This report presents findings of a workshop on the identification of drugs that should be the focus of near-term highway safety research. Drugs of interest are those that have a potential to increase the likelihood of traffic crashes and their attend...

Identification of Counterfeit Drugs by Community Pharmacists in ...

African Journals Online (AJOL)

Purpose: The problem of fake and counterfeit drugs is real and constitutes a major threat to the health and safety of the Nigerian population. A descriptive study was carried out to assess the methods of identification of counterfeit drugs by community pharmacists in Lagos State. Methods: The research instrument was a ...

Enhanced cellular transport and drug targeting using dendritic nanostructures

Science.gov (United States)

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.

Detection and identification of human targets in radar data

Science.gov (United States)

Gürbüz, Sevgi Z.; Melvin, William L.; Williams, Douglas B.

2007-04-01

Radar offers unique advantages over other sensors, such as visual or seismic sensors, for human target detection. Many situations, especially military applications, prevent the placement of video cameras or implantment seismic sensors in the area being observed, because of security or other threats. However, radar can operate far away from potential targets, and functions during daytime as well as nighttime, in virtually all weather conditions. In this paper, we examine the problem of human target detection and identification using single-channel, airborne, synthetic aperture radar (SAR). Human targets are differentiated from other detected slow-moving targets by analyzing the spectrogram of each potential target. Human spectrograms are unique, and can be used not just to identify targets as human, but also to determine features about the human target being observed, such as size, gender, action, and speed. A 12-point human model, together with kinematic equations of motion for each body part, is used to calculate the expected target return and spectrogram. A MATLAB simulation environment is developed including ground clutter, human and non-human targets for the testing of spectrogram-based detection and identification algorithms. Simulations show that spectrograms have some ability to detect and identify human targets in low noise. An example gender discrimination system correctly detected 83.97% of males and 91.11% of females. The problems and limitations of spectrogram-based methods in high clutter environments are discussed. The SNR loss inherent to spectrogram-based methods is quantified. An alternate detection and identification method that will be used as a basis for future work is proposed.

Identification and quantification of drug-albumin adducts in serum samples from a drug exposure study in mice

NARCIS (Netherlands)

Switzar, L.; Kwast, L.M.; Lingeman, H.; Giera, M.; Pieters, R.H.H.; Niessen, W.M.A.

2013-01-01

The formation of drug-protein adducts following the bioactivation of drugs to reactive metabolites has been linked to adverse drug reactions (ADRs) and is a major complication in drug discovery and development. Identification and quantification of drug-protein adducts in vivo may lead to a better

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

Science.gov (United States)

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.

Systematic identification of proteins that elicit drug side effects

DEFF Research Database (Denmark)

Kuhn, Michael; Al Banchaabouchi, Mumna; Campillos, Monica

2013-01-01

Side effect similarities of drugs have recently been employed to predict new drug targets, and networks of side effects and targets have been used to better understand the mechanism of action of drugs. Here, we report a large-scale analysis to systematically predict and characterize proteins...... that cause drug side effects. We integrated phenotypic data obtained during clinical trials with known drug-target relations to identify overrepresented protein-side effect combinations. Using independent data, we confirm that most of these overrepresentations point to proteins which, when perturbed, cause......) is responsible for hyperesthesia in mice, which, in turn, can be prevented by a drug that selectively inhibits HTR7. Taken together, we show that a large fraction of complex drug side effects are mediated by individual proteins and create a reference for such relations....

Fluid mechanics aspects of magnetic drug targeting.

Science.gov (United States)

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.

Drug-Target Interaction Prediction with Graph Regularized Matrix Factorization.

Science.gov (United States)

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

2017-01-01

Experimental determination of drug-target interactions is expensive and time-consuming. Therefore, there is a continuous demand for more accurate predictions of interactions using computational techniques. Algorithms have been devised to infer novel interactions on a global scale where the input to these algorithms is a drug-target network (i.e., a bipartite graph where edges connect pairs of drugs and targets that are known to interact). However, these algorithms had difficulty predicting interactions involving new drugs or targets for which there are no known interactions (i.e., "orphan" nodes in the network). Since data usually lie on or near to low-dimensional non-linear manifolds, we propose two matrix factorization methods that use graph regularization in order to learn such manifolds. In addition, considering that many of the non-occurring edges in the network are actually unknown or missing cases, we developed a preprocessing step to enhance predictions in the "new drug" and "new target" cases by adding edges with intermediate interaction likelihood scores. In our cross validation experiments, our methods achieved better results than three other state-of-the-art methods in most cases. Finally, we simulated some "new drug" and "new target" cases and found that GRMF predicted the left-out interactions reasonably well.

Landscape of Targeted Anti-Cancer Drug Synergies in Melanoma Identifies a Novel BRAF-VEGFR/PDGFR Combination Treatment.

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Adam A Friedman

Full Text Available A newer generation of anti-cancer drugs targeting underlying somatic genetic driver events have resulted in high single-agent or single-pathway response rates in selected patients, but few patients achieve complete responses and a sizeable fraction of patients relapse within a year. Thus, there is a pressing need for identification of combinations of targeted agents which induce more complete responses and prevent disease progression. We describe the results of a combination screen of an unprecedented scale in mammalian cells performed using a collection of targeted, clinically tractable agents across a large panel of melanoma cell lines. We find that even the most synergistic drug pairs are effective only in a discrete number of cell lines, underlying a strong context dependency for synergy, with strong, widespread synergies often corresponding to non-specific or off-target drug effects such as multidrug resistance protein 1 (MDR1 transporter inhibition. We identified drugs sensitizing cell lines that are BRAFV600E mutant but intrinsically resistant to BRAF inhibitor PLX4720, including the vascular endothelial growth factor receptor/kinase insert domain receptor (VEGFR/KDR and platelet derived growth factor receptor (PDGFR family inhibitor cediranib. The combination of cediranib and PLX4720 induced apoptosis in vitro and tumor regression in animal models. This synergistic interaction is likely due to engagement of multiple receptor tyrosine kinases (RTKs, demonstrating the potential of drug- rather than gene-specific combination discovery approaches. Patients with elevated biopsy KDR expression showed decreased progression free survival in trials of mitogen-activated protein kinase (MAPK kinase pathway inhibitors. Thus, high-throughput unbiased screening of targeted drug combinations, with appropriate library selection and mechanistic follow-up, can yield clinically-actionable drug combinations.

Ex vivo investigation of magnetically targeted drug delivery system

International Nuclear Information System (INIS)

Yoshida, Y.; Fukui, S.; Fujimoto, S.; Mishima, F.; Takeda, S.; Izumi, Y.; Ohtani, S.; Fujitani, Y.; Nishijima, S.

2007-01-01

In conventional systemic drug delivery the drug is administered by intravenous injection; it then travels to the heart from where it is pumped to all regions of the body. When the drug is aimed at a small target region, this method is extremely inefficient and leads to require much larger doses than those being necessary. In order to overcome this problem a number of targeted drug delivery methods are developed. One of these, magnetically targeted drug delivery system (MT-DDS) will be a promising way, which involves binding a drug to small biocompatible magnetic particles, injecting these into the blood stream and using a high gradient magnetic field to pull them out of suspension in the target region. In the present paper, we describe an ex vivo experimental work. It is also reported that navigation and accumulation test of the magnetic particles in the Y-shaped glass tube was performed in order to examine the threshold of the magnetic force for accumulation. It is found that accumulation of the magnetic particles was succeeded in the blood vessel when a permanent magnet was placed at the vicinity of the blood vessel. This result indicates the feasibility of the magnetically drug targeting in the blood vessel

Advances in Antisense Oligonucleotide Development for Target Identification, Validation, and as Novel Therapeutics

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Moizza Mansoor

2008-01-01

Full Text Available Antisense oligonucleotides (As-ODNs are single stranded, synthetically prepared strands of deoxynucleotide sequences, usually 18–21 nucleotides in length, complementary to the mRNA sequence of the target gene. As-ODNs are able to selectively bind cognate mRNA sequences by sequence-specific hybridization. This results in cleavage or disablement of the mRNA and, thus, inhibits the expression of the target gene. The specificity of the As approach is based on the probability that, in the human genome, any sequence longer than a minimal number of nucleotides (nt, 13 for RNA and 17 for DNA, normally occurs only once. The potential applications of As-ODNs are numerous because mRNA is ubiquitous and is more accessible to manipulation than DNA. With the publication of the human genome sequence, it has become theoretically possible to inhibit mRNA of almost any gene by As-ODNs, in order to get a better understanding of gene function, investigate its role in disease pathology and to study novel therapeutic targets for the diseases caused by dysregulated gene expression. The conceptual simplicity, the availability of gene sequence information from the human genome, the inexpensive availability of synthetic oligonucleotides and the possibility of rational drug design makes As-ODNs powerful tools for target identification, validation and therapeutic intervention. In this review we discuss the latest developments in antisense oligonucleotide design, delivery, pharmacokinetics and potential side effects, as well as its uses in target identification and validation, and finally focus on the current developments of antisense oligonucleotides in therapeutic intervention in various diseases.

Targeted Drug-Carrying Bacteriophages as Antibacterial Nanomedicines▿

OpenAIRE

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, w...

Some Remarks on Prediction of Drug-Target Interaction with Network Models.

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Zhang, Shao-Wu; Yan, Xiao-Ying

2017-01-01

System-level understanding of the relationships between drugs and targets is very important for enhancing drug research, especially for drug function repositioning. The experimental methods used to determine drug-target interactions are usually time-consuming, tedious and expensive, and sometimes lack reproducibility. Thus, it is highly desired to develop computational methods for efficiently and effectively analyzing and detecting new drug-target interaction pairs. With the explosive growth of different types of omics data, such as genome, pharmacology, phenotypic, and other kinds of molecular networks, numerous computational approaches have been developed to predict Drug-Target Interactions (DTI). In this review, we make a survey on the recent advances in predicting drug-target interaction with network-based models from the following aspects: i) Available public data sources and benchmark datasets; ii) Drug/target similarity metrics; iii) Network construction; iv) Common network algorithms; v) Performance comparison of existing network-based DTI predictors. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Folate mediated self-assembled phytosterol-alginate nanoparticles for targeted intracellular anticancer drug delivery.

Science.gov (United States)

Wang, Jianting; Wang, Ming; Zheng, Mingming; Guo, Qiong; Wang, Yafan; Wang, Heqing; Xie, Xiangrong; Huang, Fenghong; Gong, Renmin

2015-05-01

Self-assembled core/shell nanoparticles (NPs) were synthesized from water-soluble alginate substituted by hydrophobic phytosterols. Folate, a cancer-cell-specific ligand, was conjugated to the phytosterol-alginate (PA) NPs for targeting folate-receptor-overexpressing cancer cells. The physicochemical properties of folate-phytosterol-alginate (FPA) NPs were characterized by nuclear magnetic resonance, transmission electron microscopy, dynamic light scattering, electrophoretic light scattering, and fluorescence spectroscopy. Doxorubicin (DOX), an anticancer drug, was entrapped inside prepared NPs by dialysis method. The identification of prepared FPA NPs to folate-receptor-overexpressing cancer cells (KB cells) was confirmed by cytotoxicity and folate competition assays. Compared to the pure DOX and DOX/PA NPs, the DOX/FPA NPs had lower IC50 value to KB cells because of folate-receptor-mediated endocytosis process and the cytotoxicity of DOX/FPA NPs to KB cells could be competitively inhibited by free folate. The cellular uptake and internalization of pure DOX and DOX/FPA NPs was confirmed by confocal laser scanning microscopy image and the higher intracellular uptake of drug for DOX/FPA NPs over pure DOX was observed. The FPA NPs had the potential as a promising carrier to target drugs to cancer cells overexpressing folate receptors and avoid cytotoxicity to normal tissues. Copyright © 2015 Elsevier B.V. All rights reserved.

Recent Advances in Target Characterization and Identification by Photoaffinity Probes

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Sang J. Chung

2013-08-01

Full Text Available Target identification of biologically active molecules such as natural products, synthetic small molecules, peptides, and oligonucleotides mainly relies on affinity chromatography, activity-based probes, or photoaffinity labeling (PAL. Amongst them, activity-based probes and PAL have offered great advantages in target identification technology due to their ability to form covalent bonds with the corresponding targets. Activity-based probe technology mainly relies on the chemical reactivity of the target proteins, thereby limiting the majority of the biological targets to enzymes or proteins which display reactive residues at the probe-binding site. In general, the probes should bear a reactive moiety such as an epoxide, a Michael acceptor, or a reactive alkyl halide in their structures. On the other hand, photoaffinity probes (PAPs are composed of a target-specific ligand and a photoactivatable functional group. When bound to the corresponding target proteins and activated with wavelength-specific light, PAPs generate highly reactive chemical species that covalently cross-link proximal amino acid residues. This process is better known as PAL and is widely employed to identify cellular targets of biologically active molecules. This review highlights recent advances in target identification by PAL, with a focus on the structure and chemistry of the photoaffinity probes developed in the recent decade, coupled to the target proteins identified using these probes.

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

Energy Technology Data Exchange (ETDEWEB)

Yadavalli, Tejabhiram, E-mail: tejabhiram@gmail.com [Nanotechnology Research Centre, SRM University, Chennai 603203 (India); Ramasamy, Shivaraman [Nanotechnology Research Centre, SRM University, Chennai 603203 (India); School of Physics, The University of Western Australia, 35 Stirling Hwy, Crawley, WA 6009 (Australia); Chandrasekaran, Gopalakrishnan; Michael, Isaac; Therese, Helen Annal [Nanotechnology Research Centre, SRM University, Chennai 603203 (India); Chennakesavulu, Ramasamy [Department of Pharmacy practice, SRM College of Pharmacy, Chennai 603203 (India)

2015-04-15

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. - Highlights: • The use of gadolinium doped nickel ferrite with the suggested doping level. • The use of PNIPMA–chitosan polymer with folic acid and fluorescein as a drug carrier complex. • Magnetic hyperthermia studies of gadolinium doped nickel ferrites are being reported for the first time. • Proton relaxivity studies which indicate the MRI contrasting properties on the reported system are new. • Use of curcumin, a hydrophobic Indian spice as a cancer killing agent inside the reported magnetic polymer complex.

Pericyte-targeting drug delivery and tissue engineering

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Kang E

2016-05-01

Full Text Available Eunah Kang,1 Jong Wook Shin2 1School of Chemical Engineering and Material Science, 2Division of Allergic and Pulmonary Medicine, Department of Internal Medicine, College of Medicine, Chung-Ang University, Dongjak-Gu, Seoul, South Korea Abstract: 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. Keywords: pericytes, pericyte-targeting drug delivery, tissue engineering, platelet-derived growth factor, angiogenesis, vascular remodeling

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

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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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

The collagen receptor uPARAP/Endo180 as a novel target for antibody-drug conjugate mediated treatment of mesenchymal and leukemic cancers

DEFF Research Database (Denmark)

Nielsen, Christoffer Fagernæs; van Putten, Sander Maarten; Lund, Ida Katrine

2017-01-01

A key task in developing the field of personalized cancer therapy is the identification of novel molecular targets that enable treatment of cancers not susceptible to other means of specific therapy. The collagen receptor uPARAP/Endo180 is overexpressed by malignant cells in several non-epithelia......A key task in developing the field of personalized cancer therapy is the identification of novel molecular targets that enable treatment of cancers not susceptible to other means of specific therapy. The collagen receptor uPARAP/Endo180 is overexpressed by malignant cells in several non...... into the endosomal-lysosomal system, thus opening a potential route of entry into receptor-positive cells. This combination of specific expression and endocytic function appears well suited for targeting of uPARAP/Endo180-positive cancers by antibody-drug conjugate (ADC) mediated drug delivery. Therefore, we...... model with human uPARAP/Endo180-positive leukemic cells, obtaining a complete cure of all tested mice following intravenous ADC treatment with no sign of adverse effects. Our study identifies uPARAP/Endo180 as a promising target for novel therapy against several highly malignant cancer types....

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

Science.gov (United States)

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.

Maximum flow approach to prioritize potential drug targets of Mycobacterium tuberculosis H37Rv from protein-protein interaction network.

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Melak, Tilahun; Gakkhar, Sunita

2015-12-01

In spite of the implementations of several strategies, tuberculosis (TB) is overwhelmingly a serious global public health problem causing millions of infections and deaths every year. This is mainly due to the emergence of drug-resistance varieties of TB. The current treatment strategies for the drug-resistance TB are of longer duration, more expensive and have side effects. This highlights the importance of identification and prioritization of targets for new drugs. This study has been carried out to prioritize potential drug targets of Mycobacterium tuberculosis H37Rv based on their flow to resistance genes. The weighted proteome interaction network of the pathogen was constructed using a dataset from STRING database. Only a subset of the dataset with interactions that have a combined score value ≥770 was considered. Maximum flow approach has been used to prioritize potential drug targets. The potential drug targets were obtained through comparative genome and network centrality analysis. The curated set of resistance genes was retrieved from literatures. Detail literature review and additional assessment of the method were also carried out for validation. A list of 537 proteins which are essential to the pathogen and non-homologous with human was obtained from the comparative genome analysis. Through network centrality measures, 131 of them were found within the close neighborhood of the centre of gravity of the proteome network. These proteins were further prioritized based on their maximum flow value to resistance genes and they are proposed as reliable drug targets of the pathogen. Proteins which interact with the host were also identified in order to understand the infection mechanism. Potential drug targets of Mycobacterium tuberculosis H37Rv were successfully prioritized based on their flow to resistance genes of existing drugs which is believed to increase the druggability of the targets since inhibition of a protein that has a maximum flow to

Increasing the Structural Coverage of Tuberculosis Drug Targets

Science.gov (United States)

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 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

In vivo characteristics of targeted drug-carrying filamentous bacteriophage nanomedicines

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Vaks Lilach

2011-12-01

Full Text Available Abstract 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.

Aptamer-Mediated Polymeric Vehicles for Enhanced Cell-Targeted Drug Delivery.

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Tan, Kei X; Danquah, Michael K; Sidhu, Amandeep; Yon, Lau Sie; Ongkudon, Clarence M

2018-02-08

The search for smart delivery systems for enhanced pre-clinical and clinical pharmaceutical delivery and cell targeting continues to be a major biomedical research endeavor owing to differences in the physicochemical characteristics and physiological effects of drug molecules, and this affects the delivery mechanisms to elicit maximum therapeutic effects. Targeted drug delivery is a smart evolution essential to address major challenges associated with conventional drug delivery systems. These challenges mostly result in poor pharmacokinetics due to the inability of the active pharmaceutical ingredients to specifically act on malignant cells thus, causing poor therapeutic index and toxicity to surrounding normal cells. Aptamers are oligonucleotides with engineered affinities to bind specifically to their cognate targets. Aptamers have gained significant interests as effective targeting elements for enhanced therapeutic delivery as they can be generated to specifically bind to wide range of targets including proteins, peptides, ions, cells and tissues. Notwithstanding, effective delivery of aptamers as therapeutic vehicles is challenged by cell membrane electrostatic repulsion, endonuclease degradation, low pH cleavage, and binding conformation stability. The application of molecularly engineered biodegradable and biocompatible polymeric particles with tunable features such as surface area and chemistry, particulate size distribution and toxicity creates opportunities to develop smart aptamer-mediated delivery systems for controlled drug release. This article discusses opportunities for particulate aptamer-drug formulations to advance current drug delivery modalities by navigating active ingredients through cellular and biomolecular traffic to target sites for sustained and controlled release at effective therapeutic dosages while minimizing systemic cytotoxic effects. A proposal for a novel drug-polymer-aptamer-polymer (DPAP) design of aptamer-drug formulation with

C-mii: a tool for plant miRNA and target identification.

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Numnark, Somrak; Mhuantong, Wuttichai; Ingsriswang, Supawadee; Wichadakul, Duangdao

2012-01-01

MicroRNAs (miRNAs) have been known to play an important role in several biological processes in both animals and plants. Although several tools for miRNA and target identification are available, the number of tools tailored towards plants is limited, and those that are available have specific functionality, lack graphical user interfaces, and restrict the number of input sequences. Large-scale computational identifications of miRNAs and/or targets of several plants have been also reported. Their methods, however, are only described as flow diagrams, which require programming skills and the understanding of input and output of the connected programs to reproduce. To overcome these limitations and programming complexities, we proposed C-mii as a ready-made software package for both plant miRNA and target identification. C-mii was designed and implemented based on established computational steps and criteria derived from previous literature with the following distinguishing features. First, software is easy to install with all-in-one programs and packaged databases. Second, it comes with graphical user interfaces (GUIs) for ease of use. Users can identify plant miRNAs and targets via step-by-step execution, explore the detailed results from each step, filter the results according to proposed constraints in plant miRNA and target biogenesis, and export sequences and structures of interest. Third, it supplies bird's eye views of the identification results with infographics and grouping information. Fourth, in terms of functionality, it extends the standard computational steps of miRNA target identification with miRNA-target folding and GO annotation. Fifth, it provides helper functions for the update of pre-installed databases and automatic recovery. Finally, it supports multi-project and multi-thread management. C-mii constitutes the first complete software package with graphical user interfaces enabling computational identification of both plant miRNA genes and mi

Drug-target interaction prediction from PSSM based evolutionary information.

Science.gov (United States)

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.

Taking aim at a moving target: designing drugs to inhibit drug-resistant HIV-1 reverse transcriptases.

Science.gov (United States)

Sarafianos, Stefan G; Das, Kalyan; Hughes, Stephen H; Arnold, Eddy

2004-12-01

HIV undergoes rapid genetic variation; this variation is caused primarily by the enormous number of viruses produced daily in an infected individual. Because of this variation, HIV presents a moving target for drug and vaccine development. The variation within individuals has led to the generation of diverse HIV-1 subtypes, which further complicates the development of effective drugs and vaccines. In general, it is more difficult to hit a moving target than a stationary target. Two broad strategies for hitting a moving target (in this case, HIV replication) are to understand the movement and to aim at the portions that move the least. In the case of anti-HIV drug development, the first option can be addressed by understanding the mechanism(s) of drug resistance and developing drugs that effectively inhibit mutant viruses. The second can be addressed by designing drugs that interact with portions of the viral machinery that are evolutionarily conserved, such as enzyme active sites.

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

Science.gov (United States)

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

Cancer in silico drug discovery: a systems biology tool for identifying candidate drugs to target specific molecular tumor subtypes.

Science.gov (United States)

San Lucas, F Anthony; Fowler, Jerry; Chang, Kyle; Kopetz, Scott; Vilar, Eduardo; Scheet, Paul

2014-12-01

Large-scale cancer datasets such as The Cancer Genome Atlas (TCGA) allow researchers to profile tumors based on a wide range of clinical and molecular characteristics. Subsequently, TCGA-derived gene expression profiles can be analyzed with the Connectivity Map (CMap) to find candidate drugs to target tumors with specific clinical phenotypes or molecular characteristics. This represents a powerful computational approach for candidate drug identification, but due to the complexity of TCGA and technology differences between CMap and TCGA experiments, such analyses are challenging to conduct and reproduce. We present Cancer in silico Drug Discovery (CiDD; scheet.org/software), a computational drug discovery platform that addresses these challenges. CiDD integrates data from TCGA, CMap, and Cancer Cell Line Encyclopedia (CCLE) to perform computational drug discovery experiments, generating hypotheses for the following three general problems: (i) determining whether specific clinical phenotypes or molecular characteristics are associated with unique gene expression signatures; (ii) finding candidate drugs to repress these expression signatures; and (iii) identifying cell lines that resemble the tumors being studied for subsequent in vitro experiments. The primary input to CiDD is a clinical or molecular characteristic. The output is a biologically annotated list of candidate drugs and a list of cell lines for in vitro experimentation. We applied CiDD to identify candidate drugs to treat colorectal cancers harboring mutations in BRAF. CiDD identified EGFR and proteasome inhibitors, while proposing five cell lines for in vitro testing. CiDD facilitates phenotype-driven, systematic drug discovery based on clinical and molecular data from TCGA. ©2014 American Association for Cancer Research.

Increasing the structural coverage of tuberculosis drug targets.

Science.gov (United States)

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 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.

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

DEFF Research Database (Denmark)

Hauser, Alexander Sebastian; Gloriam, David E.; Attwood, Misty M.

2017-01-01

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...... 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......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...

Technological advances and proteomic applications in drug discovery and target deconvolution: identification of the pleiotropic effects of statins.

Science.gov (United States)

Banfi, Cristina; Baetta, Roberta; Gianazza, Erica; Tremoli, Elena

2017-06-01

Proteomic-based techniques provide a powerful tool for identifying the full spectrum of protein targets of a drug, elucidating its mechanism(s) of action, and identifying biomarkers of its efficacy and safety. Herein, we outline the technological advancements in the field, and illustrate the contribution of proteomics to the definition of the pharmacological profile of statins, which represent the cornerstone of the prevention and treatment of cardiovascular diseases (CVDs). Statins act by inhibiting 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase, thus reducing cholesterol biosynthesis and consequently enhancing the clearance of low-density lipoproteins from the blood; however, HMG-CoA reductase inhibition can result in a multitude of additional effects beyond lipid lowering, known as 'pleiotropic effects'. The case of statins highlights the unique contribution of proteomics to the target profiling of a drug molecule. Copyright © 2017 Elsevier Ltd. All rights reserved.

New Molecules and Old Drugs as Emerging Approaches to Selectively Target Human Glioblastoma Cancer Stem Cells

Directory of Open Access Journals (Sweden)

Roberto Würth

2014-01-01

Full Text Available Despite relevant progress obtained by multimodal treatment, glioblastoma (GBM, the most aggressive primary brain tumor, is still incurable. The most encouraging advancement of GBM drug research derives from the identification of cancer stem cells (CSCs, since these cells appear to represent the determinants of resistance to current standard therapies. The goal of most ongoing studies is to identify drugs able to affect CSCs biology, either inducing selective toxicity or differentiating this tumor cell population into nontumorigenic cells. Moreover, the therapeutic approach for GBM could be improved interfering with chemo- or radioresistance mechanisms, microenvironment signals, and the neoangiogenic process. During the last years, molecular targeted compounds such as sorafenib and old drugs, like metformin, displayed interesting efficacy in preclinical studies towards several tumors, including GBM, preferentially affecting CSC viability. In this review, the latest experimental results, controversies, and prospective application concerning these promising anticancer drugs will be discussed.

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

Science.gov (United States)

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.

Membrane Transporters: Structure, Function and Targets for Drug Design

Science.gov (United States)

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 network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information.

Science.gov (United States)

Luo, Yunan; Zhao, Xinbin; Zhou, Jingtian; Yang, Jinglin; Zhang, Yanqing; Kuang, Wenhua; Peng, Jian; Chen, Ligong; Zeng, Jianyang

2017-09-18

The emergence of large-scale genomic, chemical and pharmacological data provides new opportunities for drug discovery and repositioning. In this work, we develop a computational pipeline, called DTINet, to predict novel drug-target interactions from a constructed heterogeneous network, which integrates diverse drug-related information. DTINet focuses on learning a low-dimensional vector representation of features, which accurately explains the topological properties of individual nodes in the heterogeneous network, and then makes prediction based on these representations via a vector space projection scheme. DTINet achieves substantial performance improvement over other state-of-the-art methods for drug-target interaction prediction. Moreover, we experimentally validate the novel interactions between three drugs and the cyclooxygenase proteins predicted by DTINet, and demonstrate the new potential applications of these identified cyclooxygenase inhibitors in preventing inflammatory diseases. These results indicate that DTINet can provide a practically useful tool for integrating heterogeneous information to predict new drug-target interactions and repurpose existing drugs.Network-based data integration for drug-target prediction is a promising avenue for drug repositioning, but performance is wanting. Here, the authors introduce DTINet, whose performance is enhanced in the face of noisy, incomplete and high-dimensional biological data by learning low-dimensional vector representations.

Systems biology-embedded target validation: improving efficacy in drug discovery.

Science.gov (United States)

Vandamme, Drieke; Minke, Benedikt A; Fitzmaurice, William; Kholodenko, Boris N; Kolch, Walter

2014-01-01

The pharmaceutical industry is faced with a range of challenges with the ever-escalating costs of drug development and a drying out of drug pipelines. By harnessing advances in -omics technologies and moving away from the standard, reductionist model of drug discovery, there is significant potential to reduce costs and improve efficacy. Embedding systems biology approaches in drug discovery, which seek to investigate underlying molecular mechanisms of potential drug targets in a network context, will reduce attrition rates by earlier target validation and the introduction of novel targets into the currently stagnant market. Systems biology approaches also have the potential to assist in the design of multidrug treatments and repositioning of existing drugs, while stratifying patients to give a greater personalization of medical treatment. © 2013 Wiley Periodicals, Inc.

Novel Methods for Drug-Target Interaction Prediction using Graph Mining

KAUST Repository

Ba Alawi, Wail

2016-08-31

The problem of developing drugs that can be used to cure diseases is important and requires a careful approach. Since pursuing the wrong candidate drug for a particular disease could be very costly in terms of time and money, there is a strong interest in minimizing such risks. Drug repositioning has become a hot topic of research, as it helps reduce these risks significantly at the early stages of drug development by reusing an approved drug for the treatment of a different disease. Still, finding new usage for a drug is non-trivial, as it is necessary to find out strong supporting evidence that the proposed new uses of drugs are plausible. Many computational approaches were developed to narrow the list of possible candidate drug-target interactions (DTIs) before any experiments are done. However, many of these approaches suffer from unacceptable levels of false positives. We developed two novel methods based on graph mining networks of drugs and targets. The first method (DASPfind) finds all non-cyclic paths that connect a drug and a target, and using a function that we define, calculates a score from all the paths. This score describes our confidence that DTI is correct. We show that DASPfind significantly outperforms other state-of-the-art methods in predicting the top ranked target for each drug. We demonstrate the utility of DASPfind by predicting 15 novel DTIs over a set of ion channel proteins, and confirming 12 out of these 15 DTIs through experimental evidence reported in literature and online drug databases. The second method (DASPfind+) modifies DASPfind in order to increase the confidence and reliability of the resultant predictions. Based on the structure of the drug-target interaction (DTI) networks, we introduced an optimization scheme that incrementally alters the network structure locally for each drug to achieve more robust top 1 ranked predictions. Moreover, we explored effects of several similarity measures between the targets on the prediction

Model-based global sensitivity analysis as applied to identification of anti-cancer drug targets and biomarkers of drug resistance in the ErbB2/3 network

Science.gov (United States)

Lebedeva, Galina; Sorokin, Anatoly; Faratian, Dana; Mullen, Peter; Goltsov, Alexey; Langdon, Simon P.; Harrison, David J.; Goryanin, Igor

2012-01-01

High levels of variability in cancer-related cellular signalling networks and a lack of parameter identifiability in large-scale network models hamper translation of the results of modelling studies into the process of anti-cancer drug development. Recently global sensitivity analysis (GSA) has been recognised as a useful technique, capable of addressing the uncertainty of the model parameters and generating valid predictions on parametric sensitivities. Here we propose a novel implementation of model-based GSA specially designed to explore how multi-parametric network perturbations affect signal propagation through cancer-related networks. We use area-under-the-curve for time course of changes in phosphorylation of proteins as a characteristic for sensitivity analysis and rank network parameters with regard to their impact on the level of key cancer-related outputs, separating strong inhibitory from stimulatory effects. This allows interpretation of the results in terms which can incorporate the effects of potential anti-cancer drugs on targets and the associated biological markers of cancer. To illustrate the method we applied it to an ErbB signalling network model and explored the sensitivity profile of its key model readout, phosphorylated Akt, in the absence and presence of the ErbB2 inhibitor pertuzumab. The method successfully identified the parameters associated with elevation or suppression of Akt phosphorylation in the ErbB2/3 network. From analysis and comparison of the sensitivity profiles of pAkt in the absence and presence of targeted drugs we derived predictions of drug targets, cancer-related biomarkers and generated hypotheses for combinatorial therapy. Several key predictions have been confirmed in experiments using human ovarian carcinoma cell lines. We also compared GSA-derived predictions with the results of local sensitivity analysis and discuss the applicability of both methods. We propose that the developed GSA procedure can serve as a

Nanoparticles for intracellular-targeted drug delivery

International Nuclear Information System (INIS)

Paulo, Cristiana S O; Pires das Neves, Ricardo; Ferreira, Lino S

2011-01-01

Nanoparticles (NPs) are very promising for the intracellular delivery of anticancer and immunomodulatory drugs, stem cell differentiation biomolecules and cell activity modulators. Although initial studies in the area of intracellular drug delivery have been performed in the delivery of DNA, there is an increasing interest in the use of other molecules to modulate cell activity. Herein, we review the latest advances in the intracellular-targeted delivery of short interference RNA, proteins and small molecules using NPs. In most cases, the drugs act at different cellular organelles and therefore the drug-containing NPs should be directed to precise locations within the cell. This will lead to the desired magnitude and duration of the drug effects. The spatial control in the intracellular delivery might open new avenues to modulate cell activity while avoiding side-effects.

Preparation of magnetic nanoparticles and their application to magnetic targeting drug delivery

International Nuclear Information System (INIS)

Li Guiping; Wang Yongxian

2006-01-01

Magnetic nanoparticles barrier is a novel kind of drug delivery system for magnetic targeting drugs, which can effectively deliver the drug to a tumor target site and increase therapeutic benefit, with the side effects minimized. This article summarizes the most outstanding papers on the of magnetic nanoparticles used as the targeting drug's delivery systems. (authors)

Targeting cysteine proteases in trypanosomatid disease drug discovery.

Science.gov (United States)

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.

ProSelection: A Novel Algorithm to Select Proper Protein Structure Subsets for in Silico Target Identification and Drug Discovery Research.

Science.gov (United States)

Wang, Nanyi; Wang, Lirong; Xie, Xiang-Qun

2017-11-27

Molecular docking is widely applied to computer-aided drug design and has become relatively mature in the recent decades. Application of docking in modeling varies from single lead compound optimization to large-scale virtual screening. The performance of molecular docking is highly dependent on the protein structures selected. It is especially challenging for large-scale target prediction research when multiple structures are available for a single target. Therefore, we have established ProSelection, a docking preferred-protein selection algorithm, in order to generate the proper structure subset(s). By the ProSelection algorithm, protein structures of "weak selectors" are filtered out whereas structures of "strong selectors" are kept. Specifically, the structure which has a good statistical performance of distinguishing active ligands from inactive ligands is defined as a strong selector. In this study, 249 protein structures of 14 autophagy-related targets are investigated. Surflex-dock was used as the docking engine to distinguish active and inactive compounds against these protein structures. Both t test and Mann-Whitney U test were used to distinguish the strong from the weak selectors based on the normality of the docking score distribution. The suggested docking score threshold for active ligands (SDA) was generated for each strong selector structure according to the receiver operating characteristic (ROC) curve. The performance of ProSelection was further validated by predicting the potential off-targets of 43 U.S. Federal Drug Administration approved small molecule antineoplastic drugs. Overall, ProSelection will accelerate the computational work in protein structure selection and could be a useful tool for molecular docking, target prediction, and protein-chemical database establishment research.

Identification of Thioredoxin Target Disulfides Using Isotope-Coded Affinity Tags

DEFF Research Database (Denmark)

Hägglund, Per; Bunkenborg, Jakob; Maeda, Kenji

2014-01-01

Thioredoxins (Trx) are small redox proteins that reduce disulfide bonds in various target proteins and maintain cellular thiol redox control. Here, a thiol-specific labeling and affinity enrichment approach for identification and relative quantification of Trx target disulfides in complex protein...... reduction is determined by LC-MS/MS-based quantification of tryptic peptides labeled with "light" (12C) and "heavy" (13C) ICAT reagents. The methodology can be adapted to monitor the effect of different reductants or oxidants on the redox status of thiol/disulfide proteomes in biological systems....... extracts is described. The procedure utilizes the isotope-coded affinity tag (ICAT) reagents containing a thiol reactive iodoacetamide group and a biotin affinity tag to target peptides containing reduced cysteine residues. The identification of substrates for Trx and the extent of target disulfide...

A new disaster victim identification management strategy targeting "near identification-threshold" cases: Experiences from the Boxing Day tsunami.

Science.gov (United States)

Wright, Kirsty; Mundorff, Amy; Chaseling, Janet; Forrest, Alexander; Maguire, Christopher; Crane, Denis I

2015-05-01

The international disaster victim identification (DVI) response to the Boxing Day tsunami, led by the Royal Thai Police in Phuket, Thailand, was one of the largest and most complex in DVI history. Referred to as the Thai Tsunami Victim Identification operation, the group comprised a multi-national, multi-agency, and multi-disciplinary team. The traditional DVI approach proved successful in identifying a large number of victims quickly. However, the team struggled to identify certain victims due to incomplete or poor quality ante-mortem and post-mortem data. In response to these challenges, a new 'near-threshold' DVI management strategy was implemented to target presumptive identifications and improve operational efficiency. The strategy was implemented by the DNA Team, therefore DNA kinship matches that just failed to reach the reporting threshold of 99.9% were prioritized, however the same approach could be taken by targeting, for example, cases with partial fingerprint matches. The presumptive DNA identifications were progressively filtered through the Investigation, Dental and Fingerprint Teams to add additional information necessary to either strengthen or conclusively exclude the identification. Over a five-month period 111 victims from ten countries were identified using this targeted approach. The new identifications comprised 87 adults, 24 children and included 97 Thai locals. New data from the Fingerprint Team established nearly 60% of the total near-threshold identifications and the combined DNA/Physical method was responsible for over 30%. Implementing the new strategy, targeting near-threshold cases, had positive management implications. The process initiated additional ante-mortem information collections, and established a much-needed, distinct "end-point" for unresolved cases. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Targeted electrohydrodynamic printing for micro-reservoir drug delivery systems

International Nuclear Information System (INIS)

Hwang, Tae Heon; Kim, Jin Bum; Yang, Da Som; Ryu, WonHyoung; Park, Yong-il

2013-01-01

Microfluidic drug delivery systems consisting of a drug reservoir and microfluidic channels have shown the possibility of simple and robust modulation of drug release rate. However, the difficulty of loading a small quantity of drug into drug reservoirs at a micro-scale limited further development of such systems. Electrohydrodynamic (EHD) printing was employed to fill micro-reservoirs with controlled amount of drugs in the range of a few hundreds of picograms to tens of micrograms with spatial resolution of as small as 20 µm. Unlike most EHD systems, this system was configured in combination with an inverted microscope that allows in situ targeting of drug loading at micrometer scale accuracy. Methylene blue and rhodamine B were used as model drugs in distilled water, isopropanol and a polymer solution of a biodegradable polymer and dimethyl sulfoxide (DMSO). Also tetracycline-HCl/DI water was used as actual drug ink. The optimal parameters of EHD printing to load an extremely small quantity of drug into microscale drug reservoirs were investigated by changing pumping rates, the strength of an electric field and drug concentration. This targeted EHD technique was used to load drugs into the microreservoirs of PDMS microfluidic drug delivery devices and their drug release performance was demonstrated in vitro. (paper)

Site Identification by Ligand Competitive Saturation (SILCS) simulations for fragment-based drug design.

Science.gov (United States)

Faller, Christina E; Raman, E Prabhu; MacKerell, Alexander D; Guvench, Olgun

2015-01-01

Fragment-based drug design (FBDD) involves screening low molecular weight molecules ("fragments") that correspond to functional groups found in larger drug-like molecules to determine their binding to target proteins or nucleic acids. Based on the principle of thermodynamic additivity, two fragments that bind nonoverlapping nearby sites on the target can be combined to yield a new molecule whose binding free energy is the sum of those of the fragments. Experimental FBDD approaches, like NMR and X-ray crystallography, have proven very useful but can be expensive in terms of time, materials, and labor. Accordingly, a variety of computational FBDD approaches have been developed that provide different levels of detail and accuracy.The Site Identification by Ligand Competitive Saturation (SILCS) method of computational FBDD uses all-atom explicit-solvent molecular dynamics (MD) simulations to identify fragment binding. The target is "soaked" in an aqueous solution with multiple fragments having different identities. The resulting computational competition assay reveals what small molecule types are most likely to bind which regions of the target. From SILCS simulations, 3D probability maps of fragment binding called "FragMaps" can be produced. Based on the probabilities relative to bulk, SILCS FragMaps can be used to determine "Grid Free Energies (GFEs)," which provide per-atom contributions to fragment binding affinities. For essentially no additional computational overhead relative to the production of the FragMaps, GFEs can be used to compute Ligand Grid Free Energies (LGFEs) for arbitrarily complex molecules, and these LGFEs can be used to rank-order the molecules in accordance with binding affinities.

Identification of anti-HBV activities in Paeonia suffruticosa Andr. using GRP78 as a drug target on Herbochip®.

Science.gov (United States)

Lam, Iao-Fai; Huang, Min; Chang, Margaret Dah-Tysr; Yao, Pei-Wun; Chou, Yu-Ting; Ng, Sim-Kun; Tsai, Ying-Lin; Lin, Yu-Chang; Zhang, Yun-Feng; Yang, Xiao-Yuan; Lai, Yiu-Kay

2017-01-01

Herbochip ® technology is a high throughput drug screening platform in a reverse screening manner, in which potential chemical leads in herbal extracts are immobilized and drug target proteins can be used as probes for screening process [BMC Complementary and Alternative Medicine (2015) 15:146]. While herbal medicines represent an ideal reservoir for drug screenings, here a molecular chaperone GRP78 is demonstrated to serve as a potential target for antiviral drug discovery. We cloned and expressed a truncated but fully functional form of human GRP78 (hGRP78 1-508 ) and used it as a probe for anti-HBV drug screening on herbochips. In vitro cytotoxicity and in vitro anti-HBV activity of the herbal extracts were evaluated by MTT and ELISA assays, respectively. Finally, anti-HBV activity was confirmed by in vivo assay using DHBV DNA levels in DHBV-infected ducklings as a model. Primary screenings using GRP78 on 40 herbochips revealed 11 positives. Four of the positives, namely Dioscorea bulbifera , Lasiosphaera fenzlii , Paeonia suffruticosa and Polygonum cuspidatum were subjected to subsequent assays. None of the above extracts was cytotoxic to AML12 cells, but P. cuspidatum extract (PCE) was found to be cytotoxic to HepG2 2.2.15 cells. Both PCE and P. suffruticosa extract (PSE) suppressed secretion of HBsAg and HBeAg in HepG2 2.2.15 cells. The anti-HBV activity of PSE was further confirmed in vivo. We have demonstrated that GRP78 is a valid probe for anti-HBV drug screening on herbochips. We have also shown that PSE, while being non-cytotoxic, possesses in vitro and in vivo anti-HBV activities. Taken together, our data suggest that PSE may be a potential anti-HBV agent for therapeutic use.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

A novel antibody-drug conjugate targeting SAIL for the treatment of hematologic malignancies.

Science.gov (United States)

Kim, S Y; Theunissen, J-W; Balibalos, J; Liao-Chan, S; Babcock, M C; Wong, T; Cairns, B; Gonzalez, D; van der Horst, E H; Perez, M; Levashova, Z; Chinn, L; D'Alessio, J A; Flory, M; Bermudez, A; Jackson, D Y; Ha, E; Monteon, J; Bruhns, M F; Chen, G; Migone, T-S

2015-05-29

Although several new therapeutic approaches have improved outcomes in the treatment of hematologic malignancies, unmet need persists in acute myeloid leukemia (AML), multiple myeloma (MM) and non-Hodgkin's lymphoma. Here we describe the proteomic identification of a novel cancer target, SAIL (Surface Antigen In Leukemia), whose expression is observed in AML, MM, chronic lymphocytic leukemia (CLL), diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL). While SAIL is widely expressed in CLL, AML, MM, DLBCL and FL patient samples, expression in cancer cell lines is mostly limited to cells of AML origin. We evaluated the antitumor activity of anti-SAIL monoclonal antibodies, 7-1C and 67-7A, conjugated to monomethyl auristatin F. Following internalization, anti-SAIL antibody-drug conjugates (ADCs) exhibited subnanomolar IC50 values against AML cell lines in vitro. In pharmacology studies employing AML cell line xenografts, anti-SAIL ADCs resulted in significant tumor growth inhibition. The restricted expression profile of this target in normal tissues, the high prevalence in different types of hematologic cancers and the observed preclinical activity support the clinical development of SAIL-targeted ADCs.

Screening Technologies for Target Identification in Pancreatic Cancer

Energy Technology Data Exchange (ETDEWEB)

Michl, Patrick, E-mail: michlp@med.uni-marburg.de; Ripka, Stefanie; Gress, Thomas; Buchholz, Malte [Department of Gastroenterology and Endocrinology, University Hospital, Philipps-University Marburg, Baldinger Strasse, D-35043 Marburg (Germany)

2010-12-29

Pancreatic cancer exhibits an extraordinarily high level of resistance to almost any kind of systemic therapy evaluated in clinical trials so far. Therefore, the identification of novel therapeutic targets is urgently required. High-throughput screens have emerged as an important tool to identify putative targets for diagnosis and therapy in an unbiased manner. More than a decade ago, microarray technology was introduced to identify differentially expressed genes in pancreatic cancer as compared to normal pancreas, chronic pancreatitis and other cancer types located in close proximity to the pancreas. In addition, proteomic screens have facilitated the identification of differentially secreted proteins in body fluids of pancreatic cancer patients, serving as possible biomarkers. Recently, RNA interference-based loss-of-function screens have been used to identify functionally relevant genes, whose knock-down has impact on pancreatic cancer cell viability, thereby representing potential new targets for therapeutic intervention. This review summarizes recent results of transcriptional, proteomic and functional screens in pancreatic cancer and discusses potentials and limitations of the respective technologies as well as their impact on future therapeutic developments.

Screening Technologies for Target Identification in Pancreatic Cancer

International Nuclear Information System (INIS)

Michl, Patrick; Ripka, Stefanie; Gress, Thomas; Buchholz, Malte

2010-01-01

Pancreatic cancer exhibits an extraordinarily high level of resistance to almost any kind of systemic therapy evaluated in clinical trials so far. Therefore, the identification of novel therapeutic targets is urgently required. High-throughput screens have emerged as an important tool to identify putative targets for diagnosis and therapy in an unbiased manner. More than a decade ago, microarray technology was introduced to identify differentially expressed genes in pancreatic cancer as compared to normal pancreas, chronic pancreatitis and other cancer types located in close proximity to the pancreas. In addition, proteomic screens have facilitated the identification of differentially secreted proteins in body fluids of pancreatic cancer patients, serving as possible biomarkers. Recently, RNA interference-based loss-of-function screens have been used to identify functionally relevant genes, whose knock-down has impact on pancreatic cancer cell viability, thereby representing potential new targets for therapeutic intervention. This review summarizes recent results of transcriptional, proteomic and functional screens in pancreatic cancer and discusses potentials and limitations of the respective technologies as well as their impact on future therapeutic developments

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Nanostructured materials for selective recognition and targeted drug delivery

International Nuclear Information System (INIS)

Kotrotsiou, O; Kotti, K; Dini, E; Kammona, O; Kiparissides, C

2005-01-01

Selective recognition requires the introduction of a molecular memory into a polymer matrix in order to make it capable of rebinding an analyte with a very high specificity. In addition, targeted drug delivery requires drug-loaded vesicles which preferentially localize to the sites of injury and avoid uptake into uninvolved tissues. The rapid evolution of nanotechnology is aiming to fulfill the goal of selective recognition and optimal drug delivery through the development of molecularly imprinted polymeric (MIP) nanoparticles, tailor-made for a diverse range of analytes (e.g., pharmaceuticals, pesticides, amino acids, etc.) and of nanostructured targeted drug carriers (e.g., liposomes and micelles) with increased circulation lifetimes. In the present study, PLGA microparticles containing multilamellar vesicles (MLVs), and MIP nanoparticles were synthesized to be employed as drug carriers and synthetic receptors respectively

Functionalized mesoporous silicon for targeted-drug-delivery.

Science.gov (United States)

Tabasi, Ozra; Falamaki, Cavus; Khalaj, Zahra

2012-10-01

The present work concerns a preliminary step in the production of anticancer drug loaded porous silicon (PSi) for targeted-drug-delivery applications. A successful procedure for the covalent attachment of folic acid, polyethylene glycol (PEG) and doxorubicin to hydrophilic mesoporous silicon layers is presented. A systematic approach has been followed to obtain the optimal composition of the N,N'-dicyclohexylcarbodiimide (DCC)/N-hydroxysuccimide (NHS) in dimethylsulfoxide (DMSO) solution for the surface activation process of the undecylenic acid (UD) grafted molecules to take place with minimal undesired byproduct formation. The effect of reactant concentration and kind of solvent (aqueous or DMSO) on the attachment of folic acid to the activated PSi layer has been investigated. The covalent attachment of the doxorubicin molecules to the PSi layer functionalized with folic acid and PEG is discussed. The drug release kinetics as a function of pH has been studied. The functionalized PSi particles show a high cytotoxicity compared to the equivalent amount of free drug. Cell toxicity tests show clearly that the incorporation of folate molecules increases substantially the toxicity of the loaded PSi particles. Accordingly this new functionalized PSi may be considered a proper candidate for targeted drug delivery. Copyright © 2012 Elsevier B.V. All rights reserved.

Nanoscale drug delivery for targeted chemotherapy.

Science.gov (United States)

Xin, Yong; Huang, Qian; Tang, Jian-Qin; Hou, Xiao-Yang; Zhang, Pei; Zhang, Long Zhen; Jiang, Guan

2016-08-28

Despite significant improvements in diagnostic methods and innovations in therapies for specific cancers, effective treatments for neoplastic diseases still represent major challenges. Nanotechnology as an emerging technology has been widely used in many fields and also provides a new opportunity for the targeted delivery of cancer drugs. Nanoscale delivery of chemotherapy drugs to the tumor site is highly desirable. Recent studies have shown that nanoscale drug delivery systems not only have the ability to destroy cancer cells but may also be carriers for chemotherapy drugs. Some studies have demonstrated that delivery of chemotherapy via nanoscale carriers has greater therapeutic benefit than either treatment modality alone. In this review, novel approaches to nanoscale delivery of chemotherapy are described and recent progress in this field is discussed. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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

NARCIS (Netherlands)

Witte, W.E.; Wong, Y.C.; Nederpelt, I.; Heitman, L.H.; Danhof, M.; Graaf, van der P.H.; Gilissen, R.A.; de, Lange E.C.

2016-01-01

INTRODUCTION 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

Mining predicted essential genes of Brugia malayi for nematode drug targets.

Directory of Open Access Journals (Sweden)

Sanjay Kumar

Full Text Available We report results from the first genome-wide application of a rational drug target selection methodology to a metazoan pathogen genome, the completed draft sequence of Brugia malayi, a parasitic nematode responsible for human lymphatic filariasis. More than 1.5 billion people worldwide are at risk of contracting lymphatic filariasis and onchocerciasis, a related filarial disease. Drug treatments for filariasis have not changed significantly in over 20 years, and with the risk of resistance rising, there is an urgent need for the development of new anti-filarial drug therapies. The recent publication of the draft genomic sequence for B. malayi enables a genome-wide search for new drug targets. However, there is no functional genomics data in B. malayi to guide the selection of potential drug targets. To circumvent this problem, we have utilized the free-living model nematode Caenorhabditis elegans as a surrogate for B. malayi. Sequence comparisons between the two genomes allow us to map C. elegans orthologs to B. malayi genes. Using these orthology mappings and by incorporating the extensive genomic and functional genomic data, including genome-wide RNAi screens, that already exist for C. elegans, we identify potentially essential genes in B. malayi. Further incorporation of human host genome sequence data and a custom algorithm for prioritization enables us to collect and rank nearly 600 drug target candidates. Previously identified potential drug targets cluster near the top of our prioritized list, lending credibility to our methodology. Over-represented Gene Ontology terms, predicted InterPro domains, and RNAi phenotypes of C. elegans orthologs associated with the potential target pool are identified. By virtue of the selection procedure, the potential B. malayi drug targets highlight components of key processes in nematode biology such as central metabolism, molting and regulation of gene expression.

A review on target drug delivery: magnetic microspheres

Directory of Open Access Journals (Sweden)

Amit Chandna

2013-01-01

Magnetic microsphere is newer approach in pharmaceutical field. Magnetic microspheres as an alternative to traditional radiation methods which use highly penetrating radiation that is absorbed throughout the body. Its use is limited by toxicity and side effects. The aim of the specific targeting is to enhance the efficiency of drug delivery & at the same time to reduce the toxicity & side effects. This kind of delivery system is very much important which localises the drug to the disease site. In this larger amount of freely circulating drug can be replaced by smaller amount of magnetically targeted drug. Magnetic carriers receive magnetic responses to a magnetic field from incorporated materials that are used for magnetic microspheres are chitosan, dextran etc. magnetic microspheres can be prepared from a variety of carrier material. One of the most utilized is serum albumin from human or other appropriate species. Drug release from albumin microspheres can be sustained or controlled by various stabilization procedures generally involving heat or chemical cross-linking of the protein carrier matrix.

Targeting molecular networks for drug research

Directory of Open Access Journals (Sweden)

José Pedro Pinto

2014-06-01

Full Text Available The study of molecular networks has recently moved into the limelight of biomedical research. While it has certainly provided us with plenty of new insights into cellular mechanisms, the challenge now is how to modify or even restructure these networks. This is especially true for human diseases, which can be regarded as manifestations of distorted states of molecular networks. Of the possible interventions for altering networks, the use of drugs is presently the most feasible. In this mini-review, we present and discuss some exemplary approaches of how analysis of molecular interaction networks can contribute to pharmacology (e.g., by identifying new drug targets or prediction of drug side effects, as well as listing pointers to relevant resources and software to guide future research. We also outline recent progress in the use of drugs for in vitro reprogramming of cells, which constitutes an example par excellence for altering molecular interaction networks with drugs.

Emerging migraine treatments and drug targets

DEFF Research Database (Denmark)

Olesen, Jes; Ashina, Messoud

2011-01-01

Migraine has a 1-year prevalence of 10% and high socioeconomic costs. Despite recent drug developments, there is a huge unmet need for better pharmacotherapy. In this review we discuss promising anti-migraine strategies such as calcitonin gene-related peptide (CGRP) receptor antagonists and 5....... Tonabersat, a cortical spreading depression inhibitor, has shown efficacy in the prophylaxis of migraine with aura. Several new drug targets such as nitric oxide synthase, the 5-HT(1D) receptor, the prostanoid receptors EP(2) and EP(4), and the pituitary adenylate cyclase receptor PAC1 await development....... The greatest need is for new prophylactic drugs, and it seems likely that such compounds will be developed in the coming decade....

Identifying problematic drugs based on the characteristics of their targets.

Science.gov (United States)

Lopes, Tiago J S; Shoemaker, Jason E; Matsuoka, Yukiko; Kawaoka, Yoshihiro; Kitano, Hiroaki

2015-01-01

Identifying promising compounds during the early stages of drug development is a major challenge for both academia and the pharmaceutical industry. The difficulties are even more pronounced when we consider multi-target pharmacology, where the compounds often target more than one protein, or multiple compounds are used together. Here, we address this problem by using machine learning and network analysis to process sequence and interaction data from human proteins to identify promising compounds. We used this strategy to identify properties that make certain proteins more likely to cause harmful effects when targeted; such proteins usually have domains commonly found throughout the human proteome. Additionally, since currently marketed drugs hit multiple targets simultaneously, we combined the information from individual proteins to devise a score that quantifies the likelihood of a compound being harmful to humans. This approach enabled us to distinguish between approved and problematic drugs with an accuracy of 60-70%. Moreover, our approach can be applied as soon as candidate drugs are available, as demonstrated with predictions for more than 5000 experimental drugs. These resources are available at http://sourceforge.net/projects/psin/.

Identifying problematic drugs based on the characteristics of their targets

Directory of Open Access Journals (Sweden)

Tiago Jose eDa Silva Lopes

2015-09-01

Full Text Available Identifying promising compounds during the early stages of drug development is a major challenge for both academia and the pharmaceutical industry. The difficulties are even more pronounced when we consider multi-target pharmacology, where the compounds often target more than one protein, or multiple compounds are used together. Here, we address this problem by using machine learning and network analysis to process sequence and interaction data from human proteins to identify promising compounds. We used this strategy to identify properties that make certain proteins more likely to cause harmful effects when targeted; such proteins usually have domains commonly found throughout the human proteome. Additionally, since currently marketed drugs hit multiple targets simultaneously, we combined the information from individual proteins to devise a score that quantifies the likelihood of a compound being harmful to humans. This approach enabled us to distinguish between approved and problematic drugs with an accuracy of 60%¬–70%. Moreover, our approach can be applied as soon as candidate drugs are available, as demonstrated with predictions for more than 5000 experimental drugs. These resources are available at http://sourceforge.net/projects/psin/.

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

Science.gov (United States)

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.

Computational prediction of drug-drug interactions based on drugs functional similarities.

Science.gov (United States)

Ferdousi, Reza; Safdari, Reza; Omidi, Yadollah

2017-06-01

Therapeutic activities of drugs are often influenced by co-administration of drugs that may cause inevitable drug-drug interactions (DDIs) and inadvertent side effects. Prediction and identification of DDIs are extremely vital for the patient safety and success of treatment modalities. A number of computational methods have been employed for the prediction of DDIs based on drugs structures and/or functions. Here, we report on a computational method for DDIs prediction based on functional similarity of drugs. The model was set based on key biological elements including carriers, transporters, enzymes and targets (CTET). The model was applied for 2189 approved drugs. For each drug, all the associated CTETs were collected, and the corresponding binary vectors were constructed to determine the DDIs. Various similarity measures were conducted to detect DDIs. Of the examined similarity methods, the inner product-based similarity measures (IPSMs) were found to provide improved prediction values. Altogether, 2,394,766 potential drug pairs interactions were studied. The model was able to predict over 250,000 unknown potential DDIs. Upon our findings, we propose the current method as a robust, yet simple and fast, universal in silico approach for identification of DDIs. We envision that this proposed method can be used as a practical technique for the detection of possible DDIs based on the functional similarities of drugs. Copyright © 2017. Published by Elsevier Inc.

One For All? Hitting multiple Alzheimer’s Disease targets with one drug

Directory of Open Access Journals (Sweden)

Rebecca Ellen Hughes

2016-04-01

Full Text Available Alzheimer’s disease is a complex and multifactorial disease for which the mechanism is still not fully understood. As new insights into disease progression are discovered, new drugs must be designed to target those aspects of the disease that cause neuronal damage rather than just the symptoms currently addressed by single target drugs. It is becoming possible to target several aspects of the disease pathology at once using multi-target drugs. Intended as a introduction for non-experts, this review describes the key multi-target drug design approaches, namely structure-based, in silico, and data-mining, to evaluate what is preventing compounds progressing through the clinic to the market. Repurposing current drugs using their off-target effects reduces the cost of development, time to launch and also the uncertainty associated with safety and pharmacokinetics. The most promising drugs currently being investigated for repurposing to Alzheimer’s Disease are rasagiline, originally developed for the treatment of Parkinson’s Disease, and liraglutide, an antidiabetic. Rational drug design can combine pharmacophores of multiple drugs, systematically change functional groups, and rank them by virtual screening. Hits confirmed experimentally are rationally modified to generate an effective multi-potent lead compound. Examples from this approach are ASS234 with properties similar to rasagiline, and donecopride, a hybrid of an acetylcholinesterase inhibitor and a 5-HT4 receptor agonist with pro-cognitive effects. Exploiting these interdisciplinary approaches, public-private collaborative lead factories promise faster delivery of new drugs to the clinic.

A review on proniosomal drug delivery system for targeted drug action

OpenAIRE

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

2013-01-01

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 po...

Concise Review: Cell Surface N-Linked Glycoproteins as Potential Stem Cell Markers and Drug Targets.

Science.gov (United States)

Boheler, Kenneth R; Gundry, Rebekah L

2017-01-01

Stem cells and their derivatives hold great promise to advance regenerative medicine. Critical to the progression of this field is the identification and utilization of antibody-accessible cell-surface proteins for immunophenotyping and cell sorting-techniques essential for assessment and isolation of defined cell populations with known functional and therapeutic properties. Beyond their utility for cell identification and selection, cell-surface proteins are also major targets for pharmacological intervention. Although comprehensive cell-surface protein maps are highly valuable, they have been difficult to define until recently. In this review, we discuss the application of a contemporary targeted chemoproteomic-based technique for defining the cell-surface proteomes of stem and progenitor cells. In applying this approach to pluripotent stem cells (PSCs), these studies have improved the biological understanding of these cells, led to the enhanced use and development of antibodies suitable for immunophenotyping and sorting, and contributed to the repurposing of existing drugs without the need for high-throughput screening. The utility of this latter approach was first demonstrated with human PSCs (hPSCs) through the identification of small molecules that are selectively toxic to hPSCs and have the potential for eliminating confounding and tumorigenic cells in hPSC-derived progeny destined for research and transplantation. Overall, the cutting-edge technologies reviewed here will accelerate the development of novel cell-surface protein targets for immunophenotyping, new reagents to improve the isolation of therapeutically qualified cells, and pharmacological studies to advance the treatment of intractable diseases amenable to cell-replacement therapies. Stem Cells Translational Medicine 2017;6:131-138. © 2016 The Authors Stem Cells Translational Medicine published by Wiley Periodicals, Inc. on behalf of AlphaMed Press.

Microarray-Based Identification of Transcription Factor Target Genes

NARCIS (Netherlands)

Gorte, M.; Horstman, A.; Page, R.B.; Heidstra, R.; Stromberg, A.; Boutilier, K.A.

2011-01-01

Microarray analysis is widely used to identify transcriptional changes associated with genetic perturbation or signaling events. Here we describe its application in the identification of plant transcription factor target genes with emphasis on the design of suitable DNA constructs for controlling TF

A dual-targeting strategy for enhanced drug delivery and synergistic therapy based on thermosensitive nanoparticles.

Science.gov (United States)

Wang, Mingxin; You, Chaoqun; Gao, Zhiguo; Wu, Hongshuai; Sun, Baiwang; Zhu, Xiaoli; Chen, Renjie

2018-08-01

The functionalized nanoparticles have been widely studied and reported as carriers of drug transport recently. Furthermore, many groups have focused more on developing novel and efficient treatment methods, such as photodynamic therapy and photothermal therapy, since both therapies have shown inspiring potential in the application of antitumor. The mentioned treatments exhibited the superiority of cooperative manner and showed the ability to compensate for the adverse effects caused by conventional monotherapy in proposed strategies. In view of the above descriptions, we formulated a thermosensitive drug delivery system, which achieved the enhanced delivery of cisplatin and two photosensitizers (ICG and Ce6) by dual-targeting traction. Drawing on the thin film hydration method, cisplatin and photosensitizers were encapsulated inside nanoparticles. Meanwhile, the targeting peptide cRGD and targeting molecule folate can be modified on the surface of nanoparticles to realize the active identification of tumor cells. The measurements of dynamic light scattering showed that the prepared nanoparticles had an ideal dispersibility and uniform particle size of 102.6 nm. On the basis of the results observed from confocal laser scanning microscope, the modified nanoparticles were more efficient endocytosed by MCF-7 cells as a contrast to SGC-7901 cells. Photothermal conversion-triggered drug release and photo-therapies produced a significant apoptosis rate of 85.9% on MCF-7 cells. The distinguished results made it believed that the formulated delivery system had conducted great efforts and innovations for the realization of concise collaboration and provided a promising strategy for the treatment of breast cancer.

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

Science.gov (United States)

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.

Science.gov (United States)

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

[Targeting high-risk drugs to optimize clinical pharmacists' intervention].

Science.gov (United States)

Mouterde, Anne-Laure; Bourdelin, Magali; Maison, Ophélie; Coursier, Sandra; Bontemps, Hervé

2016-12-01

By the Order of 6 April 2011, the pharmacist must validate all the prescriptions containing "high-risk drugs" or those of "patients at risk". To optimize this clinical pharmacy activity, we identified high-risk drugs. A list of high-risk drugs has been established using literature, pharmacists' interventions (PI) performed in our hospital and a survey sent to hospital pharmacists. In a prospective study (analysis of 100 prescriptions for each high-risk drug selected), we have identified the most relevant to target. We obtained a statistically significant PI rate (P<0.05) for digoxin, oral anticoagulants direct, oral methotrexate and colchicine. This method of targeted pharmaceutical validation based on high-risk drugs is relevant to detect patients with high risk of medicine-related illness. Copyright © 2016 Société française de pharmacologie et de thérapeutique. Published by Elsevier Masson SAS. All rights reserved.

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

Science.gov (United States)

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.

An efficient targeted drug delivery through apotransferrin loaded nanoparticles.

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Athuluri Divakar Sai Krishna

Full Text Available BACKGROUND: Cancerous state is a highly stimulated environment of metabolically active cells. The cells under these conditions over express selective receptors for assimilation of factors essential for growth and transformation. Such receptors would serve as potential targets for the specific ligand mediated transport of pharmaceutically active molecules. The present study demonstrates the specificity and efficacy of protein nanoparticle of apotransferrin for targeted delivery of doxorubicin. METHODOLOGY/PRINCIPAL FINDINGS: Apotransferrin nanoparticles were developed by sol-oil chemistry. A comparative analysis of efficiency of drug delivery in conjugated and non-conjugated forms of doxorubicin to apotransferrin nanoparticle is presented. The spherical shaped apotransferrin nanoparticles (nano have diameters of 25-50 etam, which increase to 60-80 etam upon direct loading of drug (direct-nano, and showed further increase in dimension (75-95 etam in conjugated nanoparticles (conj-nano. The competitive experiments with the transferrin receptor specific antibody showed the entry of both conj-nano and direct-nano into the cells through transferrin receptor mediated endocytosis. Results of various studies conducted clearly establish the superiority of the direct-nano over conj-nano viz. (a localization studies showed complete release of drug very early, even as early as 30 min after treatment, with the drug localizing in the target organelle (nucleus (b pharmacokinetic studies showed enhanced drug concentrations, in circulation with sustainable half-life (c the studies also demonstrated efficient drug delivery, and an enhanced inhibition of proliferation in cancer cells. Tissue distribution analysis showed intravenous administration of direct nano lead to higher drug localization in liver, and blood as compared to relatively lesser localization in heart, kidney and spleen. Experiments using rat cancer model confirmed the efficacy of the formulation in

Protein and Peptide in Drug Targeting and its Therapeutic Approach

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Raj K. Keservani

2015-09-01

Full Text Available Aim: The main aim of this review article is to provide information like advantages of protein and peptides via different routes of drug administration, targeted to a particular site and its implication in drug delivery system. Methods: To that aim, from the web sites of PubMed, HCAplus, Thomson, and Registry were used as the main sources to perform the search for the most significant research articles published on the subject. The information was then carefully analyzed, highlighting the most important results in the development of protein and peptide drug targeting as well as its therapeutic activity. Results: In recent years many researchers use protein and peptide as a target site of drug by a different delivery system. Proteins and peptides are used as specific and effective therapeutic agents, due to instability and side effects their use is complicated. Protein kinases are important regulators of most, if not all, biological processes. Abnormal activity of proteins and peptides has been implicated in many human diseases, such as diabetes, cancer and neurodegenerative disorders. Conclusions: It is concluded that the protein and peptide were used in drug targeting to specific site and also used in different diseased states like cancer, diabetes, immunomodulating, neurodegenerative effects and antimicrobial activity.

Orexin Receptor Targets for Anti-Relapse Medication Development in Drug Addiction

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Ronald E. See

2011-06-01

Full Text Available Drug addiction is a chronic illness characterized by high rates of relapse. Relapse to drug use can be triggered by re-exposure to drug-associated cues, stressful events, or the drug itself after a period of abstinence. Pharmacological intervention to reduce the impact of relapse-instigating factors offers a promising target for addiction treatment. Growing evidence has implicated an important role of the orexin/hypocretin system in drug reward and drug-seeking, including animal models of relapse. Here, we review the evidence for the role of orexins in modulating reward and drug-seeking in animal models of addiction and the potential for orexin receptors as specific targets for anti-relapse medication approaches.

Progress and perspectives on targeting nanoparticles for brain drug delivery

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Huile Gao

2016-07-01

Full Text Available Due to the ability of the blood–brain barrier (BBB to prevent the entry of drugs into the brain, it is a challenge to treat central nervous system disorders pharmacologically. The development of nanotechnology provides potential to overcome this problem. In this review, the barriers to brain-targeted drug delivery are reviewed, including the BBB, blood–brain tumor barrier (BBTB, and nose-to-brain barrier. Delivery strategies are focused on overcoming the BBB, directly targeting diseased cells in the brain, and dual-targeted delivery. The major concerns and perspectives on constructing brain-targeted delivery systems are discussed.

Progress and perspectives on targeting nanoparticles for brain drug delivery

Institute of Scientific and Technical Information of China (English)

Huile Gao

2016-01-01

Due to the ability of the blood–brain barrier(BBB) to prevent the entry of drugs into the brain, it is a challenge to treat central nervous system disorders pharmacologically. The development of nanotechnology provides potential to overcome this problem. In this review, the barriers to brain-targeted drug delivery are reviewed, including the BBB, blood–brain tumor barrier(BBTB), and nose-to-brain barrier. Delivery strategies are focused on overcoming the BBB, directly targeting diseased cells in the brain, and dual-targeted delivery. The major concerns and perspectives on constructing brain-targeted delivery systems are discussed.

Increasing the Structural Coverage of Tuberculosis Drug Targets

OpenAIRE

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

2014-01-01

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 s...

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

Energy Technology Data Exchange (ETDEWEB)

Chakkarapani, Prabu [Department of Pharmaceutical Technology & Centre for Excellence in Nanobio Translational Research, Anna University, Bharathidasan Institute of Technology Campus, Tiruchirappalli 620024, Tamil Nadu (India); Subbiah, Latha, E-mail: lathasuba2010@gmail.com [Department of Pharmaceutical Technology & Centre for Excellence in Nanobio Translational Research, Anna University, Bharathidasan Institute of Technology Campus, Tiruchirappalli 620024, Tamil Nadu (India); Palanisamy, Selvamani; Bibiana, Arputha [Department of Pharmaceutical Technology & Centre for Excellence in Nanobio Translational Research, Anna University, Bharathidasan Institute of Technology Campus, Tiruchirappalli 620024, Tamil Nadu (India); Ahrentorp, Fredrik; Jonasson, Christian; Johansson, Christer [Acreo Swedish ICT AB, Arvid Hedvalls backe 4, SE-411 33 Göteborg (Sweden)

2015-04-15

We report on the development and evaluation of methotrexate magnetic microcapsules (MMC) for targeted rheumatoid arthritis therapy. Methotrexate was loaded into CaCO{sub 3}-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. CaCO{sub 3}-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. - Highlights: • Development of methotrexate magnetic microcapsules (MMC) by layer-by-layer method. • Characterization of physicochemical, pharmaceutical and magnetic properties of MMC. • Multiple layers of alternative polyelectrolytes prolongs methotrexate release time. • MMC is capable for targeted and sustained release rheumatoid arthritis therapy.

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

Science.gov (United States)

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.

An integrative in-silico approach for therapeutic target identification in the human pathogen Corynebacterium diphtheriae.

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Syed Babar Jamal

Full Text Available Corynebacterium diphtheriae (Cd is a Gram-positive human pathogen responsible for diphtheria infection and once regarded for high mortalities worldwide. The fatality gradually decreased with improved living standards and further alleviated when many immunization programs were introduced. However, numerous drug-resistant strains emerged recently that consequently decreased the efficacy of current therapeutics and vaccines, thereby obliging the scientific community to start investigating new therapeutic targets in pathogenic microorganisms. In this study, our contributions include the prediction of modelome of 13 C. diphtheriae strains, using the MHOLline workflow. A set of 463 conserved proteins were identified by combining the results of pangenomics based core-genome and core-modelome analyses. Further, using subtractive proteomics and modelomics approaches for target identification, a set of 23 proteins was selected as essential for the bacteria. Considering human as a host, eight of these proteins (glpX, nusB, rpsH, hisE, smpB, bioB, DIP1084, and DIP0983 were considered as essential and non-host homologs, and have been subjected to virtual screening using four different compound libraries (extracted from the ZINC database, plant-derived natural compounds and Di-terpenoid Iso-steviol derivatives. The proposed ligand molecules showed favorable interactions, lowered energy values and high complementarity with the predicted targets. Our proposed approach expedites the selection of C. diphtheriae putative proteins for broad-spectrum development of novel drugs and vaccines, owing to the fact that some of these targets have already been identified and validated in other organisms.

A novel antibody–drug conjugate targeting SAIL for the treatment of hematologic malignancies

International Nuclear Information System (INIS)

Kim, S Y; Theunissen, J-W; Balibalos, J; Liao-Chan, S; Babcock, M C

2015-01-01

Although several new therapeutic approaches have improved outcomes in the treatment of hematologic malignancies, unmet need persists in acute myeloid leukemia (AML), multiple myeloma (MM) and non-Hodgkin's lymphoma. Here we describe the proteomic identification of a novel cancer target, SAIL (Surface Antigen In Leukemia), whose expression is observed in AML, MM, chronic lymphocytic leukemia (CLL), diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL). While SAIL is widely expressed in CLL, AML, MM, DLBCL and FL patient samples, expression in cancer cell lines is mostly limited to cells of AML origin. We evaluated the antitumor activity of anti-SAIL monoclonal antibodies, 7-1C and 67-7A, conjugated to monomethyl auristatin F. Following internalization, anti-SAIL antibody–drug conjugates (ADCs) exhibited subnanomolar IC 50 values against AML cell lines in vitro. In pharmacology studies employing AML cell line xenografts, anti-SAIL ADCs resulted in significant tumor growth inhibition. The restricted expression profile of this target in normal tissues, the high prevalence in different types of hematologic cancers and the observed preclinical activity support the clinical development of SAIL-targeted ADCs

A novel antibody–drug conjugate targeting SAIL for the treatment of hematologic malignancies

Science.gov (United States)

Kim, S Y; Theunissen, J-W; Balibalos, J; Liao-Chan, S; Babcock, M C; Wong, T; Cairns, B; Gonzalez, D; van der Horst, E H; Perez, M; Levashova, Z; Chinn, L; D‘Alessio, J A; Flory, M; Bermudez, A; Jackson, D Y; Ha, E; Monteon, J; Bruhns, M F; Chen, G; Migone, T-S

2015-01-01

Although several new therapeutic approaches have improved outcomes in the treatment of hematologic malignancies, unmet need persists in acute myeloid leukemia (AML), multiple myeloma (MM) and non-Hodgkin's lymphoma. Here we describe the proteomic identification of a novel cancer target, SAIL (Surface Antigen In Leukemia), whose expression is observed in AML, MM, chronic lymphocytic leukemia (CLL), diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL). While SAIL is widely expressed in CLL, AML, MM, DLBCL and FL patient samples, expression in cancer cell lines is mostly limited to cells of AML origin. We evaluated the antitumor activity of anti-SAIL monoclonal antibodies, 7-1C and 67-7A, conjugated to monomethyl auristatin F. Following internalization, anti-SAIL antibody–drug conjugates (ADCs) exhibited subnanomolar IC50 values against AML cell lines in vitro. In pharmacology studies employing AML cell line xenografts, anti-SAIL ADCs resulted in significant tumor growth inhibition. The restricted expression profile of this target in normal tissues, the high prevalence in different types of hematologic cancers and the observed preclinical activity support the clinical development of SAIL-targeted ADCs. PMID:26024286

Rational polypharmacology: systematically identifying and engaging multiple drug targets to promote axon growth

Science.gov (United States)

Al-Ali, Hassan; Lee, Do-Hun; Danzi, Matt C.; Nassif, Houssam; Gautam, Prson; Wennerberg, Krister; Zuercher, Bill; Drewry, David H.; Lee, Jae K.; Lemmon, Vance P.; Bixby, John L.

2016-01-01

Mammalian Central Nervous System (CNS) neurons regrow their axons poorly following injury, resulting in irreversible functional losses. Identifying therapeutics that encourage CNS axon repair has been difficult, in part because multiple etiologies underlie this regenerative failure. This suggests a particular need for drugs that engage multiple molecular targets. Although multi-target drugs are generally more effective than highly selective alternatives, we lack systematic methods for discovering such drugs. Target-based screening is an efficient technique for identifying potent modulators of individual targets. In contrast, phenotypic screening can identify drugs with multiple targets; however, these targets remain unknown. To address this gap, we combined the two drug discovery approaches using machine learning and information theory. We screened compounds in a phenotypic assay with primary CNS neurons and also in a panel of kinase enzyme assays. We used learning algorithms to relate the compounds’ kinase inhibition profiles to their influence on neurite outgrowth. This allowed us to identify kinases that may serve as targets for promoting neurite outgrowth, as well as others whose targeting should be avoided. We found that compounds that inhibit multiple targets (polypharmacology) promote robust neurite outgrowth in vitro. One compound with exemplary polypharmacology, was found to promote axon growth in a rodent spinal cord injury model. A more general applicability of our approach is suggested by its ability to deconvolve known targets for a breast cancer cell line, as well as targets recently shown to mediate drug resistance. PMID:26056718

Drug design with Cdc7 kinase: a potential novel cancer therapy target

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Masaaki Sawa

2008-11-01

Full Text Available Masaaki Sawa1, Hisao Masai21Carna Biosciences, Inc., Kobe, Japan; 2Genome Dynamics Project, Tokyo Metropolitan Institute of Medical Science, Tokyo, JapanAbstract: Identification of novel molecular targets is critical in development of new and efficient cancer therapies. Kinases are one of the most common drug targets with a potential for cancer therapy. Cell cycle progression is regulated by a number of kinases, some of which are being developed to treat cancer. Cdc7 is a serine-threonine kinase originally discovered in budding yeast, which has been shown to be necessary to initiate the S phase. Inhibition of Cdc7 in cancer cells retards the progression of the S phase, accumulates DNA damage, and induces p53-independent cell death, but the same treatment in normal cells does not significantly affect viability. Low-molecular-weight compounds that inhibit Cdc7 kinase with an IC50 of less than 10 nM have been identified, and shown to be effective in the inhibition of tumor growth in animal models. Thus Cdc7 kinase can be recognized as a novel molecular target for cancer therapy.Keywords: Cdc7 kinase, cell cycle, replication fork, genome stability, DNA damages, ATP-binding pocket, kinase inhibitor

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

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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.

Targeted proteins for diabetes drug design

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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.

Targeted proteins for diabetes drug design

International Nuclear Information System (INIS)

Trang Nguyen, Ngoc Doan; Le, Ly Thi

2012-01-01

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. (review)

Mathematical modeling for novel cancer drug discovery and development.

Science.gov (United States)

Zhang, Ping; Brusic, Vladimir

2014-10-01

Mathematical modeling enables: the in silico classification of cancers, the prediction of disease outcomes, optimization of therapy, identification of promising drug targets and prediction of resistance to anticancer drugs. In silico pre-screened drug targets can be validated by a small number of carefully selected experiments. This review discusses the basics of mathematical modeling in cancer drug discovery and development. The topics include in silico discovery of novel molecular drug targets, optimization of immunotherapies, personalized medicine and guiding preclinical and clinical trials. Breast cancer has been used to demonstrate the applications of mathematical modeling in cancer diagnostics, the identification of high-risk population, cancer screening strategies, prediction of tumor growth and guiding cancer treatment. Mathematical models are the key components of the toolkit used in the fight against cancer. The combinatorial complexity of new drugs discovery is enormous, making systematic drug discovery, by experimentation, alone difficult if not impossible. The biggest challenges include seamless integration of growing data, information and knowledge, and making them available for a multiplicity of analyses. Mathematical models are essential for bringing cancer drug discovery into the era of Omics, Big Data and personalized medicine.

Oridonin Targets Multiple Drug-Resistant Tumor Cells as Determined by in Silico and in Vitro Analyses

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Onat Kadioglu

2018-04-01

Full Text Available Drug resistance is one of the main reasons of chemotherapy failure. Therefore, overcoming drug resistance is an invaluable approach to identify novel anticancer drugs that have the potential to bypass or overcome resistance to established drugs and to substantially increase life span of cancer patients for effective chemotherapy. Oridonin is a cytotoxic diterpenoid isolated from Rabdosia rubescens with in vivo anticancer activity. In the present study, we evaluated the cytotoxicity of oridonin toward a panel of drug-resistant cancer cells overexpressing ABCB1, ABCG2, or ΔEGFR or with a knockout deletion of TP53. Interestingly, oridonin revealed lower degree of resistance than the control drug, doxorubicin. Molecular docking analyses pointed out that oridonin can interact with Akt/EGFR pathway proteins with comparable binding energies and similar docking poses as the known inhibitors. Molecular dynamics results validated the stable conformation of oridonin docking pose on Akt kinase domain. Western blot experiments clearly revealed dose-dependent downregulation of Akt and STAT3. Pharmacogenomics analyses pointed to a mRNA signature that predicted sensitivity and resistance to oridonin. In conclusion, oridonin bypasses major drug resistance mechanisms and targets Akt pathway and might be effective toward drug refractory tumors. The identification of oridonin-specific gene expressions may be useful for the development of personalized treatment approaches.

TiPs: a database of therapeutic targets in pathogens and associated tools.

KAUST Repository

Lepore, Rosalba

2013-05-21

MOTIVATION: The need for new drugs and new targets is particularly compelling in an era that is witnessing an alarming increase of drug resistance in human pathogens. The identification of new targets of known drugs is a promising approach, which has proven successful in several cases. Here, we describe a database that includes information on 5153 putative drug-target pairs for 150 human pathogens derived from available drug-target crystallographic complexes. AVAILABILITY AND IMPLEMENTATION: The TiPs database is freely available at http://biocomputing.it/tips. CONTACT: anna.tramontano@uniroma1.it or allegra.via@uniroma1.it.

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

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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.

Science.gov (United States)

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.

Automatic identification and normalization of dosage forms in drug monographs

Science.gov (United States)

2012-01-01

Background Each day, millions of health consumers seek drug-related information on the Web. Despite some efforts in linking related resources, drug information is largely scattered in a wide variety of websites of different quality and credibility. Methods As a step toward providing users with integrated access to multiple trustworthy drug resources, we aim to develop a method capable of identifying drug's dosage form information in addition to drug name recognition. We developed rules and patterns for identifying dosage forms from different sections of full-text drug monographs, and subsequently normalized them to standardized RxNorm dosage forms. Results Our method represents a significant improvement compared with a baseline lookup approach, achieving overall macro-averaged Precision of 80%, Recall of 98%, and F-Measure of 85%. Conclusions We successfully developed an automatic approach for drug dosage form identification, which is critical for building links between different drug-related resources. PMID:22336431

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

Science.gov (United States)

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.

Snapshot spectral and polarimetric imaging; target identification with multispectral video

Science.gov (United States)

Bartlett, Brent D.; Rodriguez, Mikel D.

2013-05-01

As the number of pixels continue to grow in consumer and scientific imaging devices, it has become feasible to collect the incident light field. In this paper, an imaging device developed around light field imaging is used to collect multispectral and polarimetric imagery in a snapshot fashion. The sensor is described and a video data set is shown highlighting the advantage of snapshot spectral imaging. Several novel computer vision approaches are applied to the video cubes to perform scene characterization and target identification. It is shown how the addition of spectral and polarimetric data to the video stream allows for multi-target identification and tracking not possible with traditional RGB video collection.

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

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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.

GEPSI: A Gene Expression Profile Similarity-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula.

Science.gov (United States)

Zhang, Baixia; He, Shuaibing; Lv, Chenyang; Zhang, Yanling; Wang, Yun

2018-01-01

The identification of bioactive components in traditional Chinese medicine (TCM) is an important part of the TCM material foundation research. Recently, molecular docking technology has been extensively used for the identification of TCM bioactive components. However, target proteins that are used in molecular docking may not be the actual TCM target. For this reason, the bioactive components would likely be omitted or incorrect. To address this problem, this study proposed the GEPSI method that identified the target proteins of TCM based on the similarity of gene expression profiles. The similarity of the gene expression profiles affected by TCM and small molecular drugs was calculated. The pharmacological action of TCM may be similar to that of small molecule drugs that have a high similarity score. Indeed, the target proteins of the small molecule drugs could be considered TCM targets. Thus, we identified the bioactive components of a TCM by molecular docking and verified the reliability of this method by a literature investigation. Using the target proteins that TCM actually affected as targets, the identification of the bioactive components was more accurate. This study provides a fast and effective method for the identification of TCM bioactive components.

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

Science.gov (United States)

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.

Hazard identification and risk assessment for biologics targeting the immune system.

Science.gov (United States)

Weir, Andrea B

2008-01-01

Biologic pharmaceuticals include a variety of products, such as monoclonal antibodies, fusion proteins and cytokines. Products in those classes include immunomodulatory biologics, which are intended to enhance or diminish the activity of the immune system. Immunomodulatory biologics have been approved by the U.S. FDA for a variety of indications, including cancer and inflammatory conditions. Prior to gaining approval for marketing, sponsoring companies for all types of products must demonstrate a product's safety in toxicology studies conducted in animals and show safety and efficacy in clinical trials conducted in patients. The overall goal of toxicology studies, which applies to immunomodulatory and other product types, is to identify the hazards that products pose to humans. Because biologics are generally highly selective for specific targets (receptors/epitopes), conducting toxicology studies in animal models with the target is essential. Such animals are referred to as pharmacologically relevant. Endpoints routinely included in toxicology studies, such as hematology, organ weight and histopathology, can be used to assess the effect of a product on the structure of the immune system. Additionally, specialized endpoints, such as immunophenotyping and immune function tests, can be used to define effects of immunomodulatory products on the immune system. Following hazard identification, risks posed to patients are assessed and managed. Risks can be managed through clinical trial design and risk communication, a practice that applies to immunomodulatory and other product types. Examples of risk management in clinical trial design include establishing a safe starting dose, defining the appropriate patient population and establishing appropriate patient monitoring. Risk communication starts during clinical trials and continues after product approval. A combination of hazard identification, risk assessment and risk management allows for drug development to proceed

21 CFR 886.1880 - Fusion and stereoscopic target.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Fusion and stereoscopic target. 886.1880 Section... (CONTINUED) MEDICAL DEVICES OPHTHALMIC DEVICES Diagnostic Devices § 886.1880 Fusion and stereoscopic target. (a) Identification. A fusion and stereoscopic target is a device intended for use as a viewing object...

Target mediated drug disposition with drug-drug interaction, Part II: competitive and uncompetitive cases.

Science.gov (United States)

Koch, Gilbert; Jusko, William J; Schropp, Johannes

2017-02-01

We present competitive and uncompetitive drug-drug interaction (DDI) with target mediated drug disposition (TMDD) equations and investigate their pharmacokinetic DDI properties. For application of TMDD models, quasi-equilibrium (QE) or quasi-steady state (QSS) approximations are necessary to reduce the number of parameters. To realize those approximations of DDI TMDD models, we derive an ordinary differential equation (ODE) representation formulated in free concentration and free receptor variables. This ODE formulation can be straightforward implemented in typical PKPD software without solving any non-linear equation system arising from the QE or QSS approximation of the rapid binding assumptions. This manuscript is the second in a series to introduce and investigate DDI TMDD models and to apply the QE or QSS approximation.

Sperm-Hybrid Micromotor for Targeted Drug Delivery.

Science.gov (United States)

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.

Targeted drug delivery using temperature-sensitive liposomes

International Nuclear Information System (INIS)

Magin, R.L.; Niesman, M.R.

1984-01-01

Liposomes are receiving considerable attention as vehicles for selective drug delivery. One method of targeting liposomal contents involves the combination of local hyperthermia with temperature-sensitive liposomes. Such liposomes have been used to increase the uptake of methotrexate and cis-platinum into locally heated mouse tumors. However, additional information is needed on the mechanism of liposome drug release and the physiologic deposition of liposomes in vivo before clinical trails are begun. Current research is directed at studying the encapsulation and release of water soluble drugs from temperature-sensitive liposomes. The influence of liposome size, structure, and composition on the rapid release in plasma of cytosine arabinoside, cis-platinum, and the radiation sensitizer SR-2508 are described. These results demonstrate potential applications for temperature-sensitive liposomes in selective drug delivery

Peptide drugs to target G protein-coupled receptors.

Science.gov (United States)

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.

ORAL COLON TARGETED DRUG DELIVERY SYSTEM: A REVIEW ON CURRENT AND NOVEL PERSPECTIVES

OpenAIRE

Asija Rajesh; Chaudhari Bharat; Asija Sangeeta

2012-01-01

Small intestine is mostly the site for drug absorption but in some cases the drug needs to be targeted to colon due to some factors like local colonic disease, degradation related conditions, delayed release of drugs, systemic delivery of protein and peptide drugs etc. Colon targeted drug delivery is important and relatively new concept for the absorption of drugs because it offers almost neutral pH and long residence time, thereby increasing the drug absorption. Colon has proved to be a site...

Identification of gene targets against dormant phase Mycobacterium tuberculosis infections

Directory of Open Access Journals (Sweden)

Murphy Dennis J

2007-07-01

Full Text Available Abstract Background Mycobacterium tuberculosis, the causative agent of tuberculosis (TB, infects approximately 2 billion people worldwide and is the leading cause of mortality due to infectious disease. Current TB therapy involves a regimen of four antibiotics taken over a six month period. Patient compliance, cost of drugs and increasing incidence of drug resistant M. tuberculosis strains have added urgency to the development of novel TB therapies. Eradication of TB is affected by the ability of the bacterium to survive up to decades in a dormant state primarily in hypoxic granulomas in the lung and to cause recurrent infections. Methods The availability of M. tuberculosis genome-wide DNA microarrays has lead to the publication of several gene expression studies under simulated dormancy conditions. However, no single model best replicates the conditions of human pathogenicity. In order to identify novel TB drug targets, we performed a meta-analysis of multiple published datasets from gene expression DNA microarray experiments that modeled infection leading to and including the dormant state, along with data from genome-wide insertional mutagenesis that examined gene essentiality. Results Based on the analysis of these data sets following normalization, several genome wide trends were identified and used to guide the selection of targets for therapeutic development. The trends included the significant up-regulation of genes controlled by devR, down-regulation of protein and ATP synthesis, and the adaptation of two-carbon metabolism to the hypoxic and nutrient limited environment of the granuloma. Promising targets for drug discovery were several regulatory elements (devR/devS, relA, mprAB, enzymes involved in redox balance and respiration, sulfur transport and fixation, pantothenate, isoprene, and NAD biosynthesis. The advantages and liabilities of each target are discussed in the context of enzymology, bacterial pathways, target tractability

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

Science.gov (United States)

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 targets are clinically the most beneficial, but their monthly market prices are not significantly different from those of other anticancer agents.

Virus-encoded chemokine receptors--putative novel antiviral drug targets

DEFF Research Database (Denmark)

Rosenkilde, Mette M

2005-01-01

Large DNA viruses, in particular herpes- and poxviruses, have evolved proteins that serve as mimics or decoys for endogenous proteins in the host. The chemokines and their receptors serve key functions in both innate and adaptive immunity through control of leukocyte trafficking, and have...... receptors belong to the superfamily of G-protein coupled 7TM receptors that per se are excellent drug targets. At present, non-peptide antagonists have been developed against many chemokine receptors. The potentials of the virus-encoded chemokine receptors as drug targets--ie. as novel antiviral strategies...

Drug target ontology to classify and integrate drug discovery data

DEFF Research Database (Denmark)

Lin, Yu; Mehta, Saurabh; Küçük-McGinty, Hande

2017-01-01

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. CONCLUSIONS: DTO was built based on the need for a formal semantic model for druggable targets including various related information such as protein, gene, protein...

CRISPR Approaches to Small Molecule Target Identification. | Office of Cancer Genomics

Science.gov (United States)

A long-standing challenge in drug development is the identification of the mechanisms of action of small molecules with therapeutic potential. A number of methods have been developed to address this challenge, each with inherent strengths and limitations. We here provide a brief review of these methods with a focus on chemical-genetic methods that are based on systematically profiling the effects of genetic perturbations on drug sensitivity.

Identification and management of prescription drug abuse in pregnancy.

Science.gov (United States)

Worley, Julie

2014-01-01

Prescription drug abuse is a growing problem in the United States and many other countries. Estimates of prescription drug abuse rates during pregnancy range from 5% to 20%. The primary prescription drugs designated as controlled drugs with abuse potential in pregnancy are opiates prescribed for pain, benzodiazepines prescribed for anxiety, and stimulants prescribed for attention-deficit/hyperactivity disorder. Prescription drugs are obtained for abuse through diversion methods, such as purchasing them from others or by doctor shopping. The use of prescription drugs puts both the mother and the fetus at high risk during pregnancy. Identification of women who are abusing prescription drugs is important so that treatment can be ensured. It is crucial for healthcare professionals to use a multidisciplinary approach and be supportive and maintain a good rapport with pregnant women who abuse prescription drugs. Management includes inpatient hospitalization for detoxification and withdrawal symptoms, and in the case of opiate abuse, opiate maintenance is recommended for pregnant women for the duration of their pregnancy to reduce relapse rates and improve maternal and fetal outcomes. Other recommendations include referral for support groups and supportive housing.

Off-target effects of psychoactive drugs revealed by genome-wide assays in yeast.

Directory of Open Access Journals (Sweden)

Elke Ericson

2008-08-01

Full Text Available To better understand off-target effects of widely prescribed psychoactive drugs, we performed a comprehensive series of chemogenomic screens using the budding yeast Saccharomyces cerevisiae as a model system. Because the known human targets of these drugs do not exist in yeast, we could employ the yeast gene deletion collections and parallel fitness profiling to explore potential off-target effects in a genome-wide manner. Among 214 tested, documented psychoactive drugs, we identified 81 compounds that inhibited wild-type yeast growth and were thus selected for genome-wide fitness profiling. Many of these drugs had a propensity to affect multiple cellular functions. The sensitivity profiles of half of the analyzed drugs were enriched for core cellular processes such as secretion, protein folding, RNA processing, and chromatin structure. Interestingly, fluoxetine (Prozac interfered with establishment of cell polarity, cyproheptadine (Periactin targeted essential genes with chromatin-remodeling roles, while paroxetine (Paxil interfered with essential RNA metabolism genes, suggesting potential secondary drug targets. We also found that the more recently developed atypical antipsychotic clozapine (Clozaril had no fewer off-target effects in yeast than the typical antipsychotics haloperidol (Haldol and pimozide (Orap. Our results suggest that model organism pharmacogenetic studies provide a rational foundation for understanding the off-target effects of clinically important psychoactive agents and suggest a rational means both for devising compound derivatives with fewer side effects and for tailoring drug treatment to individual patient genotypes.

Vaccines targeting drugs of abuse: is the glass half-empty or half-full?

Science.gov (United States)

Janda, Kim D; Treweek, Jennifer B

2011-12-16

The advent of vaccines targeting drugs of abuse heralded a fundamentally different approach to treating substance-related disorders. In contrast to traditional pharmacotherapies for drug abuse, vaccines act by sequestering circulating drugs and terminating the drug-induced 'high' without inducing unwanted neuromodulatory effects. Drug-targeting vaccines have entered clinical evaluation, and although these vaccines show promise from a biomedical viewpoint, the ethical and socioeconomic implications of vaccinating patients against drugs of abuse merit discussion within the scientific community.

The Nicotinic Acetylcholine Receptor as a Target for Antidepressant Drug Development

Directory of Open Access Journals (Sweden)

Noah S. Philip

2012-01-01

Full Text Available An important new area of antidepressant drug development involves targeting the nicotinic acetylcholine receptor (nAChR. This receptor, which is distributed widely in regions of the brain associated with depression, is also implicated in other important processes that are relevant to depression, such as stress and inflammation. The two classes of drugs that target nAChRs can be broadly divided into mecamylamine- and cytisine-based compounds. These drugs probably exert their effects via antagonism at α4β2 nAChRs, and strong preclinical data support the antidepressant efficacy of both classes when used in conjunction with other primary antidepressants (e.g., monoamine reuptake inhibitors. Although clinical data remain limited, preliminary results in this area constitute a compelling argument for further evaluation of the nAChR as a target for future antidepressant drug development.

Elucidating antimalarial drug targets/mode-of-action by application of system biology technologies

CSIR Research Space (South Africa)

Becker, J

2008-11-01

Full Text Available targets/mode-of-action by application of systems biology technologies J BECKER, L MTWISHA, B CRAMPTON AND D MANCAMA CSIR Biosciences, PO Box 395, Pretoria, 0001, South Africa Email: JBecker@csir.co.za – www.csir.co.za INTRODUCTION Malaria is one... The objective of this study was to use systems biology tools to unravel the drug target/mode-of-action (MoA) of an antimalarial drug (cyclohexylamine) with a known drug target/MoA, by analysing differential expression profiles of drug treated vs untreated...

Multifunctional Polymer Nanoparticles for Dual Drug Release and Cancer Cell Targeting

Directory of Open Access Journals (Sweden)

Yu-Han Wen

2017-06-01

Full Text Available Multifunctional polymer nanoparticles have been developed for cancer treatment because they could be easily designed to target cancer cells and to enhance therapeutic efficacy according to cancer hallmarks. In this study, we synthesized a pH-sensitive polymer, poly(methacrylic acid-co-histidine/doxorubicin/biotin (HBD in which doxorubicin (DOX was conjugated by a hydrazone bond to encapsulate an immunotherapy drug, imiquimod (IMQ, to form dual cancer-targeting and dual drug-loaded nanoparticles. At low pH, polymeric nanoparticles could disrupt and simultaneously release DOX and IMQ. Our experimental results show that the nanoparticles exhibited pH-dependent drug release behavior and had an ability to target cancer cells via biotin and protonated histidine.

Progress and Challenges in Developing Aptamer-Functionalized Targeted Drug Delivery Systems

Directory of Open Access Journals (Sweden)

Feng Jiang

2015-10-01

Full Text Available Aptamers, which can be screened via systematic evolution of ligands by exponential enrichment (SELEX, are superior ligands for molecular recognition due to their high selectivity and affinity. The interest in the use of aptamers as ligands for targeted drug delivery has been increasing due to their unique advantages. Based on their different compositions and preparation methods, aptamer-functionalized targeted drug delivery systems can be divided into two main categories: aptamer-small molecule conjugated systems and aptamer-nanomaterial conjugated systems. In this review, we not only summarize recent progress in aptamer selection and the application of aptamers in these targeted drug delivery systems but also discuss the advantages, challenges and new perspectives associated with these delivery systems.

Liposomal Tumor Targeting in Drug Delivery Utilizing MMP-2- and MMP-9-Binding Ligands

Directory of Open Access Journals (Sweden)

Oula Penate Medina

2011-01-01

Full Text Available Nanotechnology offers an alternative to conventional treatment options by enabling different drug delivery and controlled-release delivery strategies. Liposomes being especially biodegradable and in most cases essentially nontoxic offer a versatile platform for several different delivery approaches that can potentially enhance the delivery and targeting of therapies to tumors. Liposomes penetrate tumors spontaneously as a result of fenestrated blood vessels within tumors, leading to known enhanced permeability and subsequent drug retention effects. In addition, liposomes can be used to carry radioactive moieties, such as radiotracers, which can be bound at multiple locations within liposomes, making them attractive carriers for molecular imaging applications. Phage display is a technique that can deliver various high-affinity and selectivity peptides to different targets. In this study, gelatinase-binding peptides, found by phage display, were attached to liposomes by covalent peptide-PEG-PE anchor creating a targeted drug delivery vehicle. Gelatinases as extracellular targets for tumor targeting offer a viable alternative for tumor targeting. Our findings show that targeted drug delivery is more efficient than non-targeted drug delivery.

On-orbit real-time robust cooperative target identification in complex background

Directory of Open Access Journals (Sweden)

Wen Zhuoman

2015-10-01

Full Text Available Cooperative target identification is the prerequisite for the relative position and orientation measurement between the space robot arm and the to-be-arrested object. We propose an on-orbit real-time robust algorithm for cooperative target identification in complex background using the features of circle and lines. It first extracts only the interested edges in the target image using an adaptive threshold and refines them to about single-pixel-width with improved non-maximum suppression. Adapting a novel tracking approach, edge segments changing smoothly in tangential directions are obtained. With a small amount of calculation, large numbers of invalid edges are removed. From the few remained edges, valid circular arcs are extracted and reassembled to obtain circles according to a reliable criterion. Finally, the target is identified if there are certain numbers of straight lines whose relative positions with the circle match the known target pattern. Experiments demonstrate that the proposed algorithm accurately identifies the cooperative target within the range of 0.3–1.5 m under complex background at the speed of 8 frames per second, regardless of lighting condition and target attitude. The proposed algorithm is very suitable for real-time visual measurement of space robot arm because of its robustness and small memory requirement.

Adverse Drug Reaction Identification and Extraction in Social Media: A Scoping Review.

Science.gov (United States)

Lardon, Jérémy; Abdellaoui, Redhouane; Bellet, Florelle; Asfari, Hadyl; Souvignet, Julien; Texier, Nathalie; Jaulent, Marie-Christine; Beyens, Marie-Noëlle; Burgun, Anita; Bousquet, Cédric

2015-07-10

The underreporting of adverse drug reactions (ADRs) through traditional reporting channels is a limitation in the efficiency of the current pharmacovigilance system. Patients' experiences with drugs that they report on social media represent a new source of data that may have some value in postmarketing safety surveillance. A scoping review was undertaken to explore the breadth of evidence about the use of social media as a new source of knowledge for pharmacovigilance. Daubt et al's recommendations for scoping reviews were followed. The research questions were as follows: How can social media be used as a data source for postmarketing drug surveillance? What are the available methods for extracting data? What are the different ways to use these data? We queried PubMed, Embase, and Google Scholar to extract relevant articles that were published before June 2014 and with no lower date limit. Two pairs of reviewers independently screened the selected studies and proposed two themes of review: manual ADR identification (theme 1) and automated ADR extraction from social media (theme 2). Descriptive characteristics were collected from the publications to create a database for themes 1 and 2. Of the 1032 citations from PubMed and Embase, 11 were relevant to the research question. An additional 13 citations were added after further research on the Internet and in reference lists. Themes 1 and 2 explored 11 and 13 articles, respectively. Ways of approaching the use of social media as a pharmacovigilance data source were identified. This scoping review noted multiple methods for identifying target data, extracting them, and evaluating the quality of medical information from social media. It also showed some remaining gaps in the field. Studies related to the identification theme usually failed to accurately assess the completeness, quality, and reliability of the data that were analyzed from social media. Regarding extraction, no study proposed a generic approach to easily

Peptide and low molecular weight proteins based kidney targeted drug delivery systems.

Science.gov (United States)

Xu, Pengfei; Zhang, Hailiang; Dang, Ruili; Jiang, Pei

2018-05-30

Renal disease is a worldwide public health problem, and unfortunately, the therapeutic index of regular drugs is limited. Thus, it is a great need to develop effective treatment strategies. Among the reported strategies, kidney-targeted drug delivery system is a promising method to increase renal efficacy and reduce extra-renal toxicity. In recent years, working as vehicles for targeted drug delivery, low molecular weight proteins (LMWP) and peptide have received immense attention due to their many advantages, such as selective accumulation in kidney, high drug loading capability, control over routes of biodegradation, convenience in modification at the amino terminus, and good biocompatibility. In this review, we describe the current LMWP and peptide carriers for kidney targeted drug delivery systems. In addition, we discuss different linking strategies between carriers and drugs. Furthermore, we briefly outline the current status and attempt to give an outlook on the further study. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Antibody-drug conjugates: Promising and efficient tools for targeted cancer therapy.

Science.gov (United States)

Nasiri, Hadi; Valedkarimi, Zahra; Aghebati-Maleki, Leili; Majidi, Jafar

2018-09-01

Over the recent decades, the use of antibody-drug conjugates (ADCs) has led to a paradigm shift in cancer chemotherapy. Antibody-based treatment of various human tumors has presented dramatic efficacy and is now one of the most promising strategies used for targeted therapy of patients with a variety of malignancies, including hematological cancers and solid tumors. Monoclonal antibodies (mAbs) are able to selectively deliver cytotoxic drugs to tumor cells, which express specific antigens on their surface, and has been suggested as a novel category of agents for use in the development of anticancer targeted therapies. In contrast to conventional treatments that cause damage to healthy tissues, ADCs use mAbs to specifically attach to antigens on the surface of target cells and deliver their cytotoxic payloads. The therapeutic success of future ADCs depends on closely choosing the target antigen, increasing the potency of the cytotoxic cargo, improving the properties of the linker, and reducing drug resistance. If appropriate solutions are presented to address these issues, ADCs will play a more important role in the development of targeted therapeutics against cancer in the next years. We review the design of ADCs, and focus on how ADCs can be exploited to overcome multiple drug resistance (MDR). © 2018 Wiley Periodicals, Inc.

Meningococcal disease and future drug targets

DEFF Research Database (Denmark)

Gammelgaard, L K; Colding, H; Hartzen, S H

2011-01-01

recent data and current knowledge on molecular mechanisms of meningococcal disease and explains how host immune responses ultimately may aggravate neuropathology and the clinical prognosis. Within this context, particular importance is paid to the endotoxic components that provide potential drug targets...... for novel neuroprotective adjuvants, which are needed in order to improve the clinical management of meningoencephalitis and patient prognosis....

Inhibition of Glutamine Synthetase: A Potential Drug Target in Mycobacterium tuberculosis

Directory of Open Access Journals (Sweden)

Sherry L. Mowbray

2014-08-01

Full Text Available Tuberculosis is an infectious disease caused by Mycobacterium tuberculosis. Globally, tuberculosis is second only to AIDS in mortality and the disease is responsible for over 1.3 million deaths each year. The impractically long treatment schedules (generally 6–9 months and unpleasant side effects of the current drugs often lead to poor patient compliance, which in turn has resulted in the emergence of multi-, extensively- and totally-drug resistant strains. The development of new classes of anti-tuberculosis drugs and new drug targets is of global importance, since attacking the bacterium using multiple strategies provides the best means to prevent resistance. This review presents an overview of the various strategies and compounds utilized to inhibit glutamine synthetase, a promising target for the development of drugs for TB therapy.

Identification of the epigenetic reader CBX2 as a potential drug target in advanced prostate cancer.

Science.gov (United States)

Clermont, Pier-Luc; Crea, Francesco; Chiang, Yan Ting; Lin, Dong; Zhang, Amy; Wang, James Z L; Parolia, Abhijit; Wu, Rebecca; Xue, Hui; Wang, Yuwei; Ding, Jiarui; Thu, Kelsie L; Lam, Wan L; Shah, Sohrab P; Collins, Colin C; Wang, Yuzhuo; Helgason, Cheryl D

2016-01-01

While localized prostate cancer (PCa) can be effectively cured, metastatic disease inevitably progresses to a lethal state called castration-resistant prostate cancer (CRPC). Emerging evidence suggests that aberrant epigenetic repression by the polycomb group (PcG) complexes fuels PCa progression, providing novel therapeutic opportunities. In the search for potential epigenetic drivers of CRPC, we analyzed the molecular profile of PcG members in patient-derived xenografts and clinical samples. Overall, our results identify the PcG protein and methyl-lysine reader CBX2 as a potential therapeutic target in advanced PCa. We report that CBX2 was recurrently up-regulated in metastatic CRPC and that elevated CBX2 expression was correlated with poor clinical outcome in PCa cohorts. Furthermore, CBX2 depletion abrogated cell viability and induced caspase 3-mediated apoptosis in metastatic PCa cell lines. Mechanistically explaining this phenotype, microarray analysis in CBX2-depleted cells revealed that CBX2 controls the expression of many key regulators of cell proliferation and metastasis. Taken together, this study provides the first evidence that CBX2 inhibition induces cancer cell death, positioning CBX2 as an attractive drug target in lethal CRPC.

Targeted therapy in lung and breast cancer: a big deal

OpenAIRE

Caffarra, Cristina

2015-01-01

Great strides have been done in treating cancer. For decades, the hallmark of medical treatment for cancer has been intravenous cytotoxic chemotherapy which targets all dividing cells. In the last ten years the identification of different driver oncogenic mutations has allowed the development of targeted drugs. Targeted cancer therapies are based on the use of drugs that block the growth and spread of cancer by interfering with specific molecules involved in tumor growth and progression. The ...

EphB1 as a Novel Drug Target to Combat Pain and Addiction

Science.gov (United States)

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...neuronal and has functions in vascular endothelial cells. 6. We have also carried out computational analysis of potantial docking/binding of chemical

A smart polymeric platform for multistage nucleus-targeted anticancer drug delivery.

Science.gov (United States)

Zhong, Jiaju; Li, Lian; Zhu, Xi; Guan, Shan; Yang, Qingqing; Zhou, Zhou; Zhang, Zhirong; Huang, Yuan

2015-10-01

Tumor cell nucleus-targeted delivery of antitumor agents is of great interest in cancer therapy, since the nucleus is one of the most frequent targets of drug action. Here we report a smart polymeric conjugate platform, which utilizes stimulus-responsive strategies to achieve multistage nuclear drug delivery upon systemic administration. The conjugates composed of a backbone based on N-(2-hydroxypropyl) methacrylamide (HPMA) copolymer and detachable nucleus transport sub-units that sensitive to lysosomal enzyme. The sub-units possess a biforked structure with one end conjugated with the model drug, H1 peptide, and the other end conjugated with a novel pH-responsive targeting peptide (R8NLS) that combining the strength of cell penetrating peptide and nuclear localization sequence. The conjugates exhibited prolonged circulation time and excellent tumor homing ability. And the activation of R8NLS in acidic tumor microenvironment facilitated tissue penetration and cellular internalization. Once internalized into the cell, the sub-units were unleashed for nuclear transport through nuclear pore complex. The unique features resulted in 50-fold increase of nuclear drug accumulation relative to the original polymer-drug conjugates in vitro, and excellent in vivo nuclear drug delivery efficiency. Our report provides a strategy in systemic nuclear drug delivery by combining the microenvironment-responsive structure and detachable sub-units. Copyright © 2015 Elsevier Ltd. All rights reserved.

High-Speed Target Identification System Based on the Plume’s Spectral Distribution

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Wenjie Lang

2015-01-01

Full Text Available In order to recognize the target of high speed quickly and accurately, an identification system was designed based on analysis of the distribution characteristics of the plume spectrum. In the system, the target was aligned with visible light tracking module, and the spectral analysis of the target’s plume radiation was achieved by interference module. The distinguishing factor recognition algorithm was designed on basis of ratio of multifeature band peaks and valley mean values. Effective recognition of the high speed moving target could be achieved after partition of the active region and the influence of target motion on spectral acquisition was analyzed. In the experiment the small rocket combustion was used as the target. The spectral detection experiment was conducted at different speeds 2.0 km away from the detection system. Experimental results showed that spectral distribution had significant spectral offset in the same sampling period for the target with different speeds, but the spectral distribution was basically consistent. Through calculation of the inclusion relationship between distinguishing factor and distinction interval of the peak value and the valley value at the corresponding wave-bands, effective identification of target could be achieved.

Toxins and derivatives in molecular pharmaceutics: Drug delivery and targeted therapy.

Science.gov (United States)

Zhan, Changyou; Li, Chong; Wei, Xiaoli; Lu, Wuyuan; Lu, Weiyue

2015-08-01

Protein and peptide toxins offer an invaluable source for the development of actively targeted drug delivery systems. They avidly bind to a variety of cognate receptors, some of which are expressed or even up-regulated in diseased tissues and biological barriers. Protein and peptide toxins or their derivatives can act as ligands to facilitate tissue- or organ-specific accumulation of therapeutics. Some toxins have evolved from a relatively small number of structural frameworks that are particularly suitable for addressing the crucial issues of potency and stability, making them an instrumental source of leads and templates for targeted therapy. The focus of this review is on protein and peptide toxins for the development of targeted drug delivery systems and molecular therapies. We summarize disease- and biological barrier-related toxin receptors, as well as targeted drug delivery strategies inspired by those receptors. The design of new therapeutics based on protein and peptide toxins is also discussed. Copyright © 2015 Elsevier B.V. All rights reserved.

Study on the knowledge base system for the identification of typical target

International Nuclear Information System (INIS)

Qin Kai; Zhao Yingjun

2008-01-01

Based on the research on target knowledge base, target database, texture analysis, shape analysis, this paper proposed a new knowledge based method for typical target identification from remote sensing image. By extracting the texture characters and shape characters, joining with spatial analysis in GIS, reasoning according to the prior knowledge in the knowledge base, this method can identify and ex- tract typical target from remote sensing images. (authors)

New approaches to targeted drug delivery to tumour cells

International Nuclear Information System (INIS)

Severin, E S

2015-01-01

Basic approaches to the design of targeted drugs for the treatment of human malignant tumours have been considered. The stages of the development of these approaches have been described in detail and theoretically substantiated, and basic experimental results have been reported. Considerable attention is paid to the general characteristic of nanopharmacological drugs and to the description of mechanisms of cellular interactions with nanodrugs. The potentialities and limitations of application of nanodrugs for cancer therapy and treatment of other diseases have been considered. The use of nanodrugs conjugated with vector molecules seems to be the most promising trend of targeted therapy of malignant tumours. The bibliography includes 122 references

Targeted drug delivery to magnetic implants for therapeutic applications

International Nuclear Information System (INIS)

Yellen, Benjamin B.; Forbes, Zachary G.; Halverson, Derek S.; Fridman, Gregory; Barbee, Kenneth A.; Chorny, Michael; Levy, Robert; Friedman, Gary

2005-01-01

A new method for locally targeted drug delivery is proposed that employs magnetic implants placed directly in the cardiovascular system to attract injected magnetic carriers. Theoretical simulations and experimental results support the assumption that using magnetic implants in combination with externally applied magnetic field will optimize the delivery of magnetic drug to selected sites within a subject

RecA: a universal drug target in pathogenic bacteria.

Science.gov (United States)

Pavlopoulou, Athanasia

2018-01-01

The spread of bacterial infectious diseases due to the development of resistance to antibiotic drugs in pathogenic bacteria is an emerging global concern. Therefore, the efficacious management and prevention of bacterial infections are major public health challenges. RecA is a pleiotropic recombinase protein that has been demonstrated to be implicated strongly in the bacterial drug resistance, survival and pathogenicity. In this minireview, RecA's role in the development of antibiotic resistance and its potential as an antimicrobial drug target are discussed.

Identification of drug metabolites in human plasma or serum integrating metabolite prediction, LC-HRMS and untargeted data processing

NARCIS (Netherlands)

Jacobs, P.L.; Ridder, L.; Ruijken, M.; Rosing, H.; Jager, N.G.L.; Beijnen, J.H.; Bas, R.R.; Dongen, W.D. van

2013-01-01

Background: Comprehensive identification of human drug metabolites in first-in-man studies is crucial to avoid delays in later stages of drug development. We developed an efficient workflow for systematic identification of human metabolites in plasma or serum that combines metabolite prediction,

Targeting Biological Sensing with Commercial SERS Substrates

Science.gov (United States)

2012-09-01

substrate substrate. Sl x 4 mm waf urement to re ossible contam substrates, fiv resented as an e being used f tigated, and nam eived in an ac cations...targeted nanotechnology-based inhalation co-delivery of anticancer drugs and siRNA," Journal of Drug Targeting, 900-914 (2011). [35] Jong , H.J., Na...J.H., Jin, B.S., Lee, W.K., Lee, W.H., Jung, H.J., Kim , S.C., Lim, S.H., Yu, Y.G., "Identification of Dinitrotoluene Selective Peptides by Phage

Target identification using Zernike moments and neural networks

Science.gov (United States)

Azimi-Sadjadi, Mahmood R.; Jamshidi, Arta A.; Nevis, Andrew J.

2001-10-01

The development of an underwater target identification algorithm capable of identifying various types of underwater targets, such as mines, under different environmental conditions pose many technical problems. Some of the contributing factors are: targets have diverse sizes, shapes and reflectivity properties. Target emplacement environment is variable; targets may be proud or partially buried. Environmental properties vary significantly from one location to another. Bottom features such as sand, rocks, corals, and vegetation can conceal a target whether it is partially buried or proud. Competing clutter with responses that closely resemble those of the targets may lead to false positives. All the problems mentioned above contribute to overly difficult and challenging conditions that could lead to unreliable algorithm performance with existing methods. In this paper, we developed and tested a shape-dependent feature extraction scheme that provides features invariant to rotation, size scaling and translation; properties that are extremely useful for any target classification problem. The developed schemes were tested on an electro-optical imagery data set collected under different environmental conditions with variable background, range and target types. The electro-optic data set was collected using a Laser Line Scan (LLS) sensor by the Coastal Systems Station (CSS), located in Panama City, Florida. The performance of the developed scheme and its robustness to distortion, rotation, scaling and translation was also studied.

Rapid identification of drug-type strains in Cannabis sativa using loop-mediated isothermal amplification assay.

Science.gov (United States)

Kitamura, Masashi; Aragane, Masako; Nakamura, Kou; Watanabe, Kazuhito; Sasaki, Yohei

2017-01-01

In Cannabis sativa L., tetrahydrocannabinol (THC) is the primary psychoactive compound and exists as the carboxylated form, tetrahydrocannabinolic acid (THCA). C. sativa is divided into two strains based on THCA content-THCA-rich (drug-type) strains and THCA-poor (fiber-type) strains. Both strains are prohibited by law in many countries including Japan, whereas the drug-type strains are regulated in Canada and some European countries. As the two strains cannot be discriminated by morphological analysis, a simple method for identifying the drug-type strains is required for quality control in legal cultivation and forensic investigation. We have developed a novel loop-mediated isothermal amplification (LAMP) assay for identifying the drug-type strains of C. sativa. We designed two selective LAMP primer sets for on-site or laboratory use, which target the drug-type THCA synthase gene. The LAMP assay was accomplished within approximately 40 min. The assay showed high specificity for the drug-type strains and its sensitivity was the same as or higher than that of conventional polymerase chain reaction. We also showed the effectiveness of melting curve analysis that was conducted after the LAMP assay. The melting temperature values of the drug-type strains corresponded to those of the cloned drug-type THCA synthase gene, and were clearly different from those of the cloned fiber-type THCA synthase gene. Moreover, the LAMP assay with simple sample preparation could be accomplished within 1 h from sample treatment to identification without the need for special devices or techniques. Our rapid, sensitive, specific, and simple assay is expected to be applicable to laboratory and on-site detection.

Structural genomics of infectious disease drug targets: the SSGCID

International Nuclear Information System (INIS)

Stacy, Robin; Begley, Darren W.; Phan, Isabelle; Staker, Bart L.; Van Voorhis, Wesley C.; Varani, Gabriele; Buchko, Garry W.; Stewart, Lance J.; Myler, Peter J.

2011-01-01

An introduction and overview of the focus, goals and overall mission of the Seattle Structural Genomics Center for Infectious Disease (SSGCID) is given. The Seattle Structural Genomics Center for Infectious Disease (SSGCID) is a consortium of researchers at Seattle BioMed, Emerald BioStructures, the University of Washington and Pacific Northwest National Laboratory that was established to apply structural genomics approaches to drug targets from infectious disease organisms. The SSGCID is currently funded over a five-year period by the National Institute of Allergy and Infectious Diseases (NIAID) to determine the three-dimensional structures of 400 proteins from a variety of Category A, B and C pathogens. Target selection engages the infectious disease research and drug-therapy communities to identify drug targets, essential enzymes, virulence factors and vaccine candidates of biomedical relevance to combat infectious diseases. The protein-expression systems, purified proteins, ligand screens and three-dimensional structures produced by SSGCID constitute a valuable resource for drug-discovery research, all of which is made freely available to the greater scientific community. This issue of Acta Crystallographica Section F, entirely devoted to the work of the SSGCID, covers the details of the high-throughput pipeline and presents a series of structures from a broad array of pathogenic organisms. Here, a background is provided on the structural genomics of infectious disease, the essential components of the SSGCID pipeline are discussed and a survey of progress to date is presented

Self-assembled peptide-based nanostructures: Smart nanomaterials toward targeted drug delivery.

Science.gov (United States)

Habibi, Neda; Kamaly, Nazila; Memic, Adnan; Shafiee, Hadi

2016-02-01

Self-assembly of peptides can yield an array of well-defined nanostructures that are highly attractive nanomaterials for many biomedical applications such as drug delivery. Some of the advantages of self-assembled peptide nanostructures over other delivery platforms include their chemical diversity, biocompatibility, high loading capacity for both hydrophobic and hydrophilic drugs, and their ability to target molecular recognition sites. Furthermore, these self-assembled nanostructures could be designed with novel peptide motifs, making them stimuli-responsive and achieving triggered drug delivery at disease sites. The goal of this work is to present a comprehensive review of the most recent studies on self-assembled peptides with a focus on their "smart" activity for formation of targeted and responsive drug-delivery carriers.

Deep mining heterogeneous networks of biomedical linked data to predict novel drug-target associations.

Science.gov (United States)

Zong, Nansu; Kim, Hyeoneui; Ngo, Victoria; Harismendy, Olivier

2017-08-01

A heterogeneous network topology possessing abundant interactions between biomedical entities has yet to be utilized in similarity-based methods for predicting drug-target associations based on the array of varying features of drugs and their targets. Deep learning reveals features of vertices of a large network that can be adapted in accommodating the similarity-based solutions to provide a flexible method of drug-target prediction. We propose a similarity-based drug-target prediction method that enhances existing association discovery methods by using a topology-based similarity measure. DeepWalk, a deep learning method, is adopted in this study to calculate the similarities within Linked Tripartite Network (LTN), a heterogeneous network generated from biomedical linked datasets. This proposed method shows promising results for drug-target association prediction: 98.96% AUC ROC score with a 10-fold cross-validation and 99.25% AUC ROC score with a Monte Carlo cross-validation with LTN. By utilizing DeepWalk, we demonstrate that: (i) this method outperforms other existing topology-based similarity computation methods, (ii) the performance is better for tripartite than with bipartite networks and (iii) the measure of similarity using network topology outperforms the ones derived from chemical structure (drugs) or genomic sequence (targets). Our proposed methodology proves to be capable of providing a promising solution for drug-target prediction based on topological similarity with a heterogeneous network, and may be readily re-purposed and adapted in the existing of similarity-based methodologies. The proposed method has been developed in JAVA and it is available, along with the data at the following URL: https://github.com/zongnansu1982/drug-target-prediction . nazong@ucsd.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

EphB1 as a Novel Drug Target to Combat Pain and Addiction

Science.gov (United States)

2015-09-01

EphB1  as  a  Novel  Drug  Target  to  Combat  Pain  and   Addiction   Principal  Investigator  Name:   Mark...Principal  Investigator   Phone  and  Email:   Phone :  214-­‐645-­‐5916   Email:  Mark.Henkemeyer@UTSouthwestern.edu   Report  Date...31 Aug 2015 4. TITLE AND SUBTITLE EphB1 as a Novel Drug Target to Combat Pain and Addiction 5a. CONTRACT NUMBER EphB1 as a Novel Drug Target to

Novel Methods for Drug-Target Interaction Prediction using Graph Mining

KAUST Repository

Ba Alawi, Wail

2016-01-01

-target interactions (DTIs) before any experiments are done. However, many of these approaches suffer from unacceptable levels of false positives. We developed two novel methods based on graph mining networks of drugs and targets. The first method (DASPfind) finds all

Cancer therapy with drug loaded magnetic nanoparticles-magnetic drug targeting

International Nuclear Information System (INIS)

Alexiou, Christoph; Tietze, Rainer; Schreiber, Eveline; Jurgons, Roland; Richter, Heike; Trahms, Lutz; Rahn, Helene; Odenbach, Stefan; Lyer, Stefan

2011-01-01

The aim of magnetic drug targeting (MDT) in cancer therapy is to concentrate chemotherapeutics to a tumor region while simultaneously the overall dose is reduced. This can be achieved with coated superparamagnetic nanoparticles bound to a chemotherapeutic agent. These particles are applied intra arterially close to the tumor region and focused to the tumor by a strong external magnetic field. The interaction of the particles with the field gradient leads to an accumulation in the region of interest (i.e. tumor). The particle enrichment and thereby the drug-load in the tumor during MDT has been proven by several analytical and imaging methods. Moreover, in pilot studies we investigated in an experimental in vivo tumor model the effectiveness of this approach. Complete tumor regressions without any negative side effects could be observed. - Research Highlights: →Iron oxide nanoparticles can be enriched in tumors by external magnetic fields. → Histology evidences the intravasation of particles enter the intracellular space. → Non-invasive imaging techniques can display the spatial arrangement of particles. → HPLC-analysis show outstanding drug enrichment in tumors after MDT.

Cancer therapy with drug loaded magnetic nanoparticles-magnetic drug targeting

Energy Technology Data Exchange (ETDEWEB)

Alexiou, Christoph, E-mail: c.alexiou@web.d [Department of Oto-rhino-laryngology, Head and Neck Surgery, University Hospital Erlangen, Section for Experimental Oncology and Nanomedicine at the Else Kroener-Fresenius-Stiftung-Professorship (Germany); Tietze, Rainer; Schreiber, Eveline [Department of Oto-rhino-laryngology, Head and Neck Surgery, University Hospital Erlangen, Section for Experimental Oncology and Nanomedicine at the Else Kroener-Fresenius-Stiftung-Professorship (Germany); Jurgons, Roland [Franz Penzoldt Center, University Hospital Erlangen (Germany); Richter, Heike; Trahms, Lutz [PTB Berlin (Germany); Rahn, Helene; Odenbach, Stefan [TU Dresden, Chair of Magnetofluiddynamics, 01062 Dresden (Germany); Lyer, Stefan [Department of Oto-rhino-laryngology, Head and Neck Surgery, University Hospital Erlangen, Section for Experimental Oncology and Nanomedicine at the Else Kroener-Fresenius-Stiftung-Professorship (Germany)

2011-05-15

The aim of magnetic drug targeting (MDT) in cancer therapy is to concentrate chemotherapeutics to a tumor region while simultaneously the overall dose is reduced. This can be achieved with coated superparamagnetic nanoparticles bound to a chemotherapeutic agent. These particles are applied intra arterially close to the tumor region and focused to the tumor by a strong external magnetic field. The interaction of the particles with the field gradient leads to an accumulation in the region of interest (i.e. tumor). The particle enrichment and thereby the drug-load in the tumor during MDT has been proven by several analytical and imaging methods. Moreover, in pilot studies we investigated in an experimental in vivo tumor model the effectiveness of this approach. Complete tumor regressions without any negative side effects could be observed. - Research Highlights: Iron oxide nanoparticles can be enriched in tumors by external magnetic fields. Histology evidences the intravasation of particles enter the intracellular space. Non-invasive imaging techniques can display the spatial arrangement of particles. HPLC-analysis show outstanding drug enrichment in tumors after MDT.

Identification and characterization of carprofen as a multi-target FAAH/COX inhibitor

Science.gov (United States)

Favia, Angelo D.; Habrant, Damien; Scarpelli, Rita; Migliore, Marco; Albani, Clara; Bertozzi, Sine Mandrup; Dionisi, Mauro; Tarozzo, Glauco; Piomelli, Daniele; Cavalli, Andrea; De Vivo, Marco

2013-01-01

Pain and inflammation are major therapeutic areas for drug discovery. Current drugs for these pathologies have limited efficacy, however, and often cause a number of unwanted side effects. In the present study, we identify the non-steroid anti-inflammatory drug, carprofen, as a multi-target-directed ligand that simultaneously inhibits cyclooxygenase-1 (COX-1), COX-2 and fatty acid amide hydrolase (FAAH). Additionally, we synthesized and tested several racemic derivatives of carprofen, sharing this multi-target activity. This may result in improved analgesic efficacy and reduced side effects (Naidu, et al (2009) J Pharmacol Exp Ther 329, 48-56; Fowler, C.J. et al. (2012) J Enzym Inhib Med Chem Jan 6; Sasso, et al (2012) Pharmacol Res 65, 553). The new compounds are among the most potent multi-target FAAH/COXs inhibitors reported so far in the literature, and thus may represent promising starting points for the discovery of new analgesic and anti-inflammatory drugs. PMID:23043222

Neutrophil targeted nano-drug delivery system for chronic obstructive lung diseases.

Science.gov (United States)

Vij, Neeraj; Min, Taehong; Bodas, Manish; Gorde, Aakruti; Roy, Indrajit

2016-11-01

The success of drug delivery to target airway cell(s) remains a significant challenge due to the limited ability of nanoparticle (NP) systems to circumvent protective airway-defense mechanisms. The size, density, surface and physical-chemical properties of nanoparticles are the key features that determine their ability to navigate across the airway-barrier. We evaluated here the efficacy of a PEGylated immuno-conjugated PLGA-nanoparticle (PINP) to overcome this challenge and selectively deliver drug to specific inflammatory cells (neutrophils). We first characterized the size, shape, surface-properties and neutrophil targeting using dynamic laser scattering, transmission electron microscopy and flow cytometry. Next, we assessed the efficacy of neutrophil-targeted PINPs in transporting through the airway followed by specific binding and release of drug to neutrophils. Finally, our results demonstrate the efficacy of PINP mediated non-steroidal anti-inflammatory drug-(ibuprofen) delivery to neutrophils in murine models of obstructive lung diseases, based on its ability to control neutrophilic-inflammation and resulting lung disease. Copyright © 2016 Elsevier Inc. All rights reserved.

FUNCTIONAL GENOMICS IDENTIFIES TIS21-DEPENDENT MECHANISMS AND PUTATIVE CANCER DRUG TARGETS UNDERLYING MEDULLOBLASTOMA SHH-TYPE DEVELOPMENT

Directory of Open Access Journals (Sweden)

Giulia Gentile

2016-11-01

Full Text Available We have recently generated a novel medulloblastoma (MB mouse model with activation of the Shh pathway and lacking the MB suppressor Tis21 (Patched1+-Tis21KO.ts main phenotype is a defect of migration of the cerebellar granule precursor cells (GCPs. By genomic analysis of GCPs in vivo, we identified as drug target and major responsible of this defect the down-regulation of the promigratory chemokine Cxcl3. Consequently, the GCPs remain longer in the cerebellum proliferative area, and the MB frequency is enhanced. Here, we further analyzed the genes deregulated in a Tis21-dependent manner (Patched1+-is21 wild-type versus Ptch1+-Tis21 knockout, among which are a number of down-regulated tumor inhibitors and up-regulated tumor facilitators, focusing on pathways potentially involved in the tumorigenesis and on putative new drug targets.The data analysis using bioinformatic tools revealed: i a link between the Shh signaling and the Tis21-dependent impairment of the GCPs migration, through a Shh-dependent deregulation of the clathrin-mediated chemotaxis operating in the primary cilium through the Cxcl3-Cxcr2 axis; ii a possible lineage shift of Shh-type GCPs toward retinal precursor phenotype the neural cell type involved in group 3 MB; iii the identification of a subset of putative drug targets for MB, involved, among the others, in the regulation of Hippo signaling and centrosome assembly. Finally, our findings define also the role of Tis21 in the regulation of gene expression, through epigenetic and RNA processing mechanisms, influencing the fate of the GCPs.

Target Detection, Identification, and Marksmanship Under Various Types of Physiological Strain

National Research Council Canada - National Science Library

Tikuisis, Peter

2006-01-01

.... Using a small arms trainer (SAT), target detection, identification, and engagement were tested under a variety of conditions including heat and cold exposure, fatiguing exercise, and sleep deprivation, with caffeine intervention...

Quantitative PET Imaging in Drug Development: Estimation of Target Occupancy.

Science.gov (United States)

Naganawa, Mika; Gallezot, Jean-Dominique; Rossano, Samantha; Carson, Richard E

2017-12-11

Positron emission tomography, an imaging tool using radiolabeled tracers in humans and preclinical species, has been widely used in recent years in drug development, particularly in the central nervous system. One important goal of PET in drug development is assessing the occupancy of various molecular targets (e.g., receptors, transporters, enzymes) by exogenous drugs. The current linear mathematical approaches used to determine occupancy using PET imaging experiments are presented. These algorithms use results from multiple regions with different target content in two scans, a baseline (pre-drug) scan and a post-drug scan. New mathematical estimation approaches to determine target occupancy, using maximum likelihood, are presented. A major challenge in these methods is the proper definition of the covariance matrix of the regional binding measures, accounting for different variance of the individual regional measures and their nonzero covariance, factors that have been ignored by conventional methods. The novel methods are compared to standard methods using simulation and real human occupancy data. The simulation data showed the expected reduction in variance and bias using the proper maximum likelihood methods, when the assumptions of the estimation method matched those in simulation. Between-method differences for data from human occupancy studies were less obvious, in part due to small dataset sizes. These maximum likelihood methods form the basis for development of improved PET covariance models, in order to minimize bias and variance in PET occupancy studies.

Ultrasound-sensitive nanoparticle aggregates for targeted drug delivery.

Science.gov (United States)

Papa, Anne-Laure; Korin, Netanel; Kanapathipillai, Mathumai; Mammoto, Akiko; Mammoto, Tadanori; Jiang, Amanda; Mannix, Robert; Uzun, Oktay; Johnson, Christopher; Bhatta, Deen; Cuneo, Garry; Ingber, Donald E

2017-09-01

Here we describe injectable, ultrasound (US)-responsive, nanoparticle aggregates (NPAs) that disintegrate into slow-release, nanoscale, drug delivery systems, which can be targeted to selective sites by applying low-energy US locally. We show that, unlike microbubble based drug carriers which may suffer from stability problems, the properties of mechanical activated NPAs, composed of polymer nanoparticles, can be tuned by properly adjusting the polymer molecular weight, the size of the nanoparticle precursors as well as the percentage of excipient utilized to hold the NPA together. We then apply this concept to practice by fabricating NPAs composed of nanoparticles loaded with Doxorubicin (Dox) and tested their ability to treat tumors via ultrasound activation. Mouse studies demonstrated significantly increased efficiency of tumor targeting of the US-activated NPAs compared to PLGA nanoparticle controls (with or without US applied) or intact NPAs. Importantly, when the Dox-loaded NPAs were injected and exposed to US energy locally, this increased ability to concentrate nanoparticles at the tumor site resulted in a significantly greater reduction in tumor volume compared to tumors treated with a 20-fold higher dose of the free drug. Copyright © 2017 Elsevier Ltd. All rights reserved.

NSAIDs: Old Drugs Reveal New Anticancer Targets

Directory of Open Access Journals (Sweden)

Gary A. Piazza

2010-05-01

Full Text Available There is compelling evidence that nonsteroidal anti-inflammatory drugs (NSAIDs and cyclooxygenase-2 selective inhibitors have antineoplastic activity, but toxicity from cyclooxygenase (COX inhibition and the suppression of physiologically important prostaglandins limits their use for cancer chemoprevention. Previous studies as reviewed here suggest that the mechanism for their anticancer properties does not require COX inhibition, but instead involves an off-target effect. In support of this possibility, recent molecular modeling studies have shown that the NSAID sulindac can be chemically modified to selectively design out its COX-1 and COX-2 inhibitory activity. Unexpectedly, certain derivatives that were synthesized based on in silico modeling displayed increased potency to inhibit tumor cell growth. Other experiments have shown that sulindac can inhibit phosphodiesterase to increase intracellular cyclic GMP levels and that this activity is closely associated with its ability to selectively induce apoptosis of tumor cells. Together, these studies suggest that COX-independent mechanisms can be targeted to develop safer and more efficacious drugs for cancer chemoprevention.

Mitochondrial electron transport is the cellular target of the oncology drug elesclomol.

Directory of Open Access Journals (Sweden)

Ronald K Blackman

Full Text Available Elesclomol is a first-in-class investigational drug currently undergoing clinical evaluation as a novel cancer therapeutic. The potent antitumor activity of the compound results from the elevation of reactive oxygen species (ROS and oxidative stress to levels incompatible with cellular survival. However, the molecular target(s and mechanism by which elesclomol generates ROS and subsequent cell death were previously undefined. The cellular cytotoxicity of elesclomol in the yeast S. cerevisiae appears to occur by a mechanism similar, if not identical, to that in cancer cells. Accordingly, here we used a powerful and validated technology only available in yeast that provides critical insights into the mechanism of action, targets and processes that are disrupted by drug treatment. Using this approach we show that elesclomol does not work through a specific cellular protein target. Instead, it targets a biologically coherent set of processes occurring in the mitochondrion. Specifically, the results indicate that elesclomol, driven by its redox chemistry, interacts with the electron transport chain (ETC to generate high levels of ROS within the organelle and consequently cell death. Additional experiments in melanoma cells involving drug treatments or cells lacking ETC function confirm that the drug works similarly in human cancer cells. This deeper understanding of elesclomol's mode of action has important implications for the therapeutic application of the drug, including providing a rationale for biomarker-based stratification of patients likely to respond in the clinical setting.

Effect of Various Environmental Stressors on Target Detection, Identification, and Marksmanship

National Research Council Canada - National Science Library

Tikuisis, Peter; Keefe, Allan A

2007-01-01

.... Using a small arms trainer (SAT), the detection, identification, and engagement of targets were tested under a variety of environmentally stressful conditions including heat and cold exposure, noise, fatiguing exercise, and sleep...

Specific Cell Targeting Therapy Bypasses Drug Resistance Mechanisms in African Trypanosomiasis.

Directory of Open Access Journals (Sweden)

Juan D Unciti-Broceta

2015-06-01

Full Text Available African trypanosomiasis is a deadly neglected disease caused by the extracellular parasite Trypanosoma brucei. Current therapies are characterized by high drug toxicity and increasing drug resistance mainly associated with loss-of-function mutations in the transporters involved in drug import. The introduction of new antiparasitic drugs into therapeutic use is a slow and expensive process. In contrast, specific targeting of existing drugs could represent a more rapid and cost-effective approach for neglected disease treatment, impacting through reduced systemic toxicity and circumventing resistance acquired through impaired compound uptake. We have generated nanoparticles of chitosan loaded with the trypanocidal drug pentamidine and coated by a single domain nanobody that specifically targets the surface of African trypanosomes. Once loaded into this nanocarrier, pentamidine enters trypanosomes through endocytosis instead of via classical cell surface transporters. The curative dose of pentamidine-loaded nanobody-chitosan nanoparticles was 100-fold lower than pentamidine alone in a murine model of acute African trypanosomiasis. Crucially, this new formulation displayed undiminished in vitro and in vivo activity against a trypanosome cell line resistant to pentamidine as a result of mutations in the surface transporter aquaglyceroporin 2. We conclude that this new drug delivery system increases drug efficacy and has the ability to overcome resistance to some anti-protozoal drugs.

Magnetically responsive microparticles for targeted drug and radionuclide delivery

International Nuclear Information System (INIS)

Kaminski, M. D.; Ghebremeskel, A. N.; Nunez, L.; Kasza, K. E.; Chang, F.; Chien, T.-H.; Fisher, P. F.; Eastman, J. A.; Rosengart, A. J.; McDonald, L.; Xie, Y.; Johns, L.; Pytel, P.; Hafeli, U. O.

2004-01-01

We are currently investigating the use of magnetic particles--polymeric-based spheres containing dispersed magnetic nanocrystalline phases--for the precise delivery of drugs via the human vasculature. According to this review, meticulously prepared magnetic drug targeting holds promise as a safe and effective method of delivering drugs to specific organ, tissue or cellular targets. We have critically examined the wide range of approaches in the design and implementation of magnetic-particle-based drug delivery systems to date, including magnetic particle preparation, drug encapsulation, biostability, biocompatibility, toxicity, magnetic field designs, and clinical trials. However, we strongly believe that there are several limitations with past developments that need to be addressed to enable significant strides in the field. First, particle size has to be carefully chosen. Micrometer-sized magnetic particles are better attracted over a distance than nanometer sized magnetic particles by a constant magnetic field gradient, and particle sizes up to 1 (micro)m show a much better accumulation with no apparent side effects in small animal models, since the smallest blood vessels have an inner diameter of 5-7 (micro)m. Nanometer-sized particles <70 nm will accumulate in organ fenestrations despite an effective surface stabilizer. To be suitable for future human applications, our experimental approach synthesizes the magnetic drug carrier according to specific predefined outcome metrics: monodisperse population in a size range of 100 nm to 1.0 (micro)m, non-toxic, with appropriate magnetic properties, and demonstrating successful in vitro and in vivo tests. Another important variable offering possible improvement is surface polarity, which is expected to prolong particle half-life in circulation and modify biodistribution and stability of drugs in the body. The molecules in the blood that are responsible for enhancing the uptake of particles by the reticuloendothelial

Predicting Drug-Target Interactions Based on Small Positive Samples.

Science.gov (United States)

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

The heme biosynthetic pathway of the obligate Wolbachia endosymbiont of Brugia malayi as a potential anti-filarial drug target.

Directory of Open Access Journals (Sweden)

Bo Wu

2009-07-01

Full Text Available Filarial parasites (e.g., Brugia malayi, Onchocerca volvulus, and Wuchereria bancrofti are causative agents of lymphatic filariasis and onchocerciasis, which are among the most disabling of neglected tropical diseases. There is an urgent need to develop macro-filaricidal drugs, as current anti-filarial chemotherapy (e.g., diethylcarbamazine [DEC], ivermectin and albendazole can interrupt transmission predominantly by killing microfilariae (mf larvae, but is less effective on adult worms, which can live for decades in the human host. All medically relevant human filarial parasites appear to contain an obligate endosymbiotic bacterium, Wolbachia. This alpha-proteobacterial mutualist has been recognized as a potential target for filarial nematode life cycle intervention, as antibiotic treatments of filarial worms harboring Wolbachia result in the loss of worm fertility and viability upon antibiotic treatments both in vitro and in vivo. Human trials have confirmed this approach, although the length of treatments, high doses required and medical counter-indications for young children and pregnant women warrant the identification of additional anti-Wolbachia drugs.Genome sequence analysis indicated that enzymes involved in heme biosynthesis might constitute a potential anti-Wolbachia target set. We tested different heme biosynthetic pathway inhibitors in ex vivo B. malayi viability assays and report a specific effect of N-methyl mesoporphyrin (NMMP, which targets ferrochelatase (FC, the last step. Our phylogenetic analysis indicates evolutionarily significant divergence between Wolbachia heme genes and their human homologues. We therefore undertook the cloning, overexpression and analysis of several enzymes of this pathway alongside their human homologues, and prepared proteins for drug targeting. In vitro enzyme assays revealed a approximately 600-fold difference in drug sensitivities to succinyl acetone (SA between Wolbachia and human 5

Advances in research of targeting delivery and controlled release of drug-loaded nanoparticles

International Nuclear Information System (INIS)

Tan Zhonghua

2003-01-01

Biochemistry drug, at present, is still the main tool that human struggle to defeat the diseases. So, developing safe and efficacious technique of drug targeting delivery and controlled release is key to enhance curative effect, decrease drug dosage, and lessen its side effect. Drug-loaded nanoparticles, which is formed by conjugate between nanotechnology and modern pharmaceutics, is a new fashioned pharmic delivery carrier. Because of advantages in pharmic targeting transport and controlled or slow release and improving bioavailability, it has been one of developing trend of modern pharmaceutical dosage forms

Doxorubicin loaded PVA coated iron oxide nanoparticles for targeted drug delivery

International Nuclear Information System (INIS)

Kayal, S.; Ramanujan, R.V.

2010-01-01

Magnetic drug targeting is a drug delivery system that can be used in locoregional cancer treatment. Coated magnetic particles, called carriers, are very useful for delivering chemotherapeutic drugs. Magnetic carriers were synthesized by coprecipitation of iron oxide followed by coating with polyvinyl alcohol (PVA). Characterization was carried out using X-ray diffraction, TEM, TGA, FTIR and VSM techniques. The magnetic core of the carriers was magnetite (Fe 3 O 4 ), with average size of 10 nm. The room temperature VSM measurements showed that magnetic particles were superparamagnetic. The amount of PVA bound to the iron oxide nanoparticles were estimated by thermogravimetric analysis (TGA) and the attachment of PVA to the iron oxide nanoparticles was confirmed by FTIR analysis. Doxorubicin (DOX) drug loading and release profiles of PVA coated iron oxide nanoparticles showed that up to 45% of adsorbed drug was released in 80 h, the drug release followed the Fickian diffusion-controlled process. The binding of DOX to the PVA was confirmed by FTIR analysis. The present findings show that DOX loaded PVA coated iron oxide nanoparticles are promising for magnetically targeted drug delivery.

Retention of ferrofluid aggregates at the target site during magnetic drug targeting

Energy Technology Data Exchange (ETDEWEB)

Asfer, Mohammed, E-mail: asfer786@gmail.com [School of Engineering and Technology, BML Munjal University, Haryana (India); Saroj, Sunil Kumar [Department of Mechanical Engineering, IIT Kanpur, Kanpur (India); Panigrahi, Pradipta Kumar, E-mail: panig@iitk.ac.in [Department of Mechanical Engineering, IIT Kanpur, Kanpur (India)

2017-08-15

Highlights: • The present in vitro work reports the retention dynamics of ferrofluid aggregates at the target site against a bulk flow of DI water inside a micro capillary during magnetic drug targeting. • The recirculation zone at the downstream of the aggregate is found to be a function of aggregate height, Reynolds number and the degree of surface roughness of the outer boundary of the aggregate. • The reported results of the present work can be used as a guideline for the better design of MDT technique for in vivo applications. - Abstract: The present study reports the retention dynamics of a ferrofluid aggregate localized at the target site inside a glass capillary (500 × 500 µm{sup 2} square cross section) against a bulk flow of DI water (Re = 0.16 and 0.016) during the process of magnetic drug targeting (MDT). The dispersion dynamics of iron oxide nanoparticles (IONPs) into bulk flow for different initial size of aggregate at the target site is reported using the brightfield visualization technique. The flow field around the aggregate during the retention is evaluated using the µPIV technique. IONPs at the outer boundary experience a higher shear force as compared to the magnetic force, resulting in dispersion of IONPs into the bulk flow downstream to the aggregate. The blockage effect and the roughness of the outer boundary of the aggregate resulting from chain like clustering of IONPs contribute to the flow recirculation at the downstream region of the aggregate. The entrapment of seeding particles inside the chain like clusters of IONPs at the outer boundary of the aggregate reduces the degree of roughness resulting in a streamlined aggregate at the target site at later time. The effect of blockage, structure of the aggregate, and disturbed flow such as recirculation around the aggregate are the primary factors, which must be investigated for the effectiveness of the MDT process for in vivo applications.

Individualization of anticancer therapy; molecular targets of novel drugs in oncology

Directory of Open Access Journals (Sweden)

Katarzyna Regulska

2012-11-01

Full Text Available Deregulation of cellular signal transduction, caused by gene mutations, has been recognized as a basic factor of cancer initiation, promotion and progression. Thus, the ability to control the activity of overstimulated signal molecules by the use of appropriate inhibitors became the idea of targeted cancer therapy, which has provided an effective tool to normalize the molecular disorders in malignant cells and to treat certain types of cancer. The molecularly targeted drugs are divided into two major pharmaceutical classes: monoclonal antibodies and small-molecule kinase inhibitors. This review presents a summary of their characteristics, analyzing their chemical structures, specified molecular targets, mechanisms of action and indications for use. Also the molecules subjected to preclinical trials or phase I, II and III clinical trials evaluating their efficiency and safety are presented. Moreover, the article discusses further perspectives for development of targeted therapies focusing on three major directions: systematic searching and discovery of new targets that are oncogenic drivers, improving the pharmacological properties of currently known drugs, and developing strategies to overcome drug resistance. Finally, the role of proper pharmacodiagnostics as a key to rational anticancer therapy has been emphasized since the verification of reliable predictive biomarkers is a basis of individualized medicine in oncology. 

Melanin targeting for intracellular drug delivery: Quantification of bound and free drug in retinal pigment epithelial cells.

Science.gov (United States)

Rimpelä, Anna-Kaisa; Hagström, Marja; Kidron, Heidi; Urtti, Arto

2018-05-31

Melanin binding affects drug distribution and retention in pigmented ocular tissues, thereby affecting drug response, duration of activity and toxicity. Therefore, it is a promising possibility for drug targeting and controlled release in the pigmented cells and tissues. Intracellular unbound drug concentrations determine pharmacological and toxicological actions, but analyses of unbound vs. total drug concentrations in pigmented cells are lacking. We studied intracellular binding and cellular drug uptake in pigmented retinal pigment epithelial cells and in non-pigmented ARPE-19 cells with five model drugs (chloroquine, propranolol, timolol, diclofenac, methotrexate). The unbound drug fractions in pigmented cells were 0.00016-0.73 and in non-pigmented cells 0.017-1.0. Cellular uptake (i.e. distribution ratio Kp), ranged from 1.3 to 6300 in pigmented cells and from 1.0 to 25 in non-pigmented cells. Values for intracellular bioavailability, F ic , were similar in both cells types (although larger variation in pigmented cells). In vitro melanin binding parameters were used to predict intracellular unbound drug fraction and cell uptake. Comparison of predictions with experimental data indicates that other factors (e.g. ion-trapping, lipophilicity-related binding to other cell components) also play a role. Melanin binding is a major factor that leads to cellular uptake and unbound drug fractions of a range of 3-4 orders of magnitude indicating that large reservoirs of melanin bound drug can be generated in the cells. Understanding melanin binding has important implications on retinal drug targeting, efficacy and toxicity. Copyright © 2017. Published by Elsevier B.V.

Immunoliposomes for the targeted delivery of antitumor drugs

NARCIS (Netherlands)

Mastrobattista, E; Koning, GA; Storm, G

1999-01-01

This review presents an overview of the field of immunoliposome-mediated targeting of anticancer agents. First, problems that are encountered when immunoliposomes are used for systemic anticancer drug delivery and potential solutions are discussed. Second, an update is given of the in vivo results

Current and future drug targets in weight management

NARCIS (Netherlands)

Witkamp, R.F.

2011-01-01

Obesity will continue to be one of the leading causes of chronic disease unless the ongoing rise in the prevalence of this condition is reversed. Accumulating morbidity figures and a shortage of effective drugs have generated substantial research activity with several molecular targets being

Emerging migraine treatments and drug targets

DEFF Research Database (Denmark)

Olesen, Jes; Ashina, Messoud

2011-01-01

Migraine has a 1-year prevalence of 10% and high socioeconomic costs. Despite recent drug developments, there is a huge unmet need for better pharmacotherapy. In this review we discuss promising anti-migraine strategies such as calcitonin gene-related peptide (CGRP) receptor antagonists and 5......-hydroxytrypamine (5-HT)(1F) receptor agonists, which are in late-stage development. Nitric oxide antagonists are also in development. New forms of administration of sumatriptan might improve efficacy and reduce side effects. Botulinum toxin A has recently been approved for the prophylaxis of chronic migraine....... Tonabersat, a cortical spreading depression inhibitor, has shown efficacy in the prophylaxis of migraine with aura. Several new drug targets such as nitric oxide synthase, the 5-HT(1D) receptor, the prostanoid receptors EP(2) and EP(4), and the pituitary adenylate cyclase receptor PAC1 await development...

Pluronic F127 nanomicelles engineered with nuclear localized functionality for targeted drug delivery

International Nuclear Information System (INIS)

Li, Yong-Yong; Li, Lan; Dong, Hai-Qing; Cai, Xiao-Jun; Ren, Tian-Bin

2013-01-01

PKKKRKV (Pro-Lys-Lys-Lys-Arg-Lys-Val, PV7), a seven amino acid peptide, has emerged as one of the primary nuclear localization signals that can be targeted into cell nucleus via the nuclear import machinery. Taking advantage of chemical diversity and biological activities of this short peptide sequence, in this study, Pluronic F127 nanomicelles engineered with nuclear localized functionality were successfully developed for intracellular drug delivery. These nanomicelles with the size ∼ 100 nm were self-assembled from F127 polymer that was flanked with two PV7 sequences at its both terminal ends. Hydrophobic anticancer drug doxorubicin (DOX) with inherent fluorescence was chosen as the model drug, which was found to be efficiently encapsulated into nanomicelles with the encapsulation efficiency at 72.68%. In comparison with the non-functionalized namomicelles, the microscopic observation reveals that PV7 functionalized nanomicelles display a higher cellular uptake, especially into the nucleus of HepG2 cells, due to the nuclear localization signal effects. Both cytotoxicity and apoptosis studies show that the DOX-loaded nanomicelles were more potent than drug nanomicelles without nuclear targeting functionality. It was thus concluded that PV7 functionalized nanomicelles could be a potentially alternative vehicle for nuclear targeting drug delivery. - Highlights: ► A new nuclear targeted drug delivery system based on micelles is developed. ► This micellar system features a core-shell structure with the size peaked at 100 nm. ► PV7, a short peptide sequence, is adopted as a nuclear targeting ligand. ► PV7 functionalized drug loaded micelles are more potent in killing tumor cells

[Advances of tumor targeting peptides drug delivery system with pH-sensitive activities].

Science.gov (United States)

Ma, Yin-yun; Li, Li; Huang, Hai-feng; Gou, San-hu; Ni, Jing-man

2016-05-01

The pH-sensitive peptides drug delivery systems, which target to acidic extracellular environment of tumor tissue, have many advantages in drug delivery. They exhibit a high specificity to tumor and low cytotoxicity, which significantly increase the efficacy of traditional anti-cancer drugs. In recent years the systems have received a great attention. The pH-sensitive peptides drug delivery systems can be divided into five types according to the difference in pH-responsive mechanism,type of peptides and carrier materials. This paper summarizes the recent progresses in the field with a focus on the five types of pH-sensitive peptides in drug delivery systems. This may provide a guideline to design and application of tumor targeting drugs.

Physico-Chemical Strategies to Enhance Stability and Drug Retention of Polymeric Micelles for Tumor-Targeted Drug Delivery

NARCIS (Netherlands)

Shi, Y.; Lammers, Twan Gerardus Gertudis Maria; Storm, Gerrit; Hennink, W.E.

2017-01-01

Polymeric micelles (PM) have been extensively used for tumor-targeted delivery of hydrophobic anti-cancer drugs. The lipophilic core of PM is naturally suitable for loading hydrophobic drugs and the hydrophilic shell endows them with colloidal stability and stealth properties. Decades of research on

Dendrimers in drug delivery and targeting: Drug-dendrimer interactions and toxicity issues

Directory of Open Access Journals (Sweden)

Kanika Madaan

2014-01-01

Full Text Available Dendrimers are the emerging polymeric architectures that are known for their defined structures, versatility in drug delivery and high functionality whose properties resemble with biomolecules. These nanostructured macromolecules have shown their potential abilities in entrapping and/or conjugating the high molecular weight hydrophilic/hydrophobic entities by host-guest interactions and covalent bonding (prodrug approach respectively. Moreover, high ratio of surface groups to molecular volume has made them a promising synthetic vector for gene delivery. Owing to these properties dendrimers have fascinated the researchers in the development of new drug carriers and they have been implicated in many therapeutic and biomedical applications. Despite of their extensive applications, their use in biological systems is limited due to toxicity issues associated with them. Considering this, the present review has focused on the different strategies of their synthesis, drug delivery and targeting, gene delivery and other biomedical applications, interactions involved in formation of drug-dendrimer complex along with characterization techniques employed for their evaluation, toxicity problems and associated approaches to alleviate their inherent toxicity.

Dendrimers in drug delivery and targeting: Drug-dendrimer interactions and toxicity issues

Science.gov (United States)

Madaan, Kanika; Kumar, Sandeep; Poonia, Neelam; Lather, Viney; Pandita, Deepti

2014-01-01

Dendrimers are the emerging polymeric architectures that are known for their defined structures, versatility in drug delivery and high functionality whose properties resemble with biomolecules. These nanostructured macromolecules have shown their potential abilities in entrapping and/or conjugating the high molecular weight hydrophilic/hydrophobic entities by host-guest interactions and covalent bonding (prodrug approach) respectively. Moreover, high ratio of surface groups to molecular volume has made them a promising synthetic vector for gene delivery. Owing to these properties dendrimers have fascinated the researchers in the development of new drug carriers and they have been implicated in many therapeutic and biomedical applications. Despite of their extensive applications, their use in biological systems is limited due to toxicity issues associated with them. Considering this, the present review has focused on the different strategies of their synthesis, drug delivery and targeting, gene delivery and other biomedical applications, interactions involved in formation of drug-dendrimer complex along with characterization techniques employed for their evaluation, toxicity problems and associated approaches to alleviate their inherent toxicity. PMID:25035633

Peptide- and saccharide-conjugated dendrimers for targeted drug delivery: a concise review

Science.gov (United States)

Liu, Jie; Gray, Warren D.; Davis, Michael E.; Luo, Ying

2012-01-01

Dendrimers comprise a category of branched materials with diverse functions that can be constructed with defined architectural and chemical structures. When decorated with bioactive ligands made of peptides and saccharides through peripheral chemical groups, dendrimer conjugates are turned into nanomaterials possessing attractive binding properties with the cognate receptors. At the cellular level, bioactive dendrimer conjugates can interact with cells with avidity and selectivity, and this function has particularly stimulated interests in investigating the targeting potential of dendrimer materials for the design of drug delivery systems. In addition, bioactive dendrimer conjugates have so far been studied for their versatile capabilities to enhance stability, solubility and absorption of various types of therapeutics. This review presents a brief discussion on three aspects of the recent studies to use peptide- and saccharide-conjugated dendrimers for drug delivery: (i) synthesis methods, (ii) cell- and tissue-targeting properties and (iii) applications of conjugated dendrimers in drug delivery nanodevices. With more studies to elucidate the structure–function relationship of ligand–dendrimer conjugates in transporting drugs, the conjugated dendrimers hold promise to facilitate targeted delivery and improve drug efficacy for discovery and development of modern pharmaceutics. PMID:23741608

Leveraging structure determination with fragment screening for infectious disease drug targets: MECP synthase from Burkholderia pseudomallei

Energy Technology Data Exchange (ETDEWEB)

Begley, Darren W.; Hartley, Robert C.; Davies, Douglas R.; Edwards, Thomas E.; Leonard, Jess T.; Abendroth, Jan; Burris, Courtney A.; Bhandari, Janhavi; Myler, Peter J.; Staker, Bart L.; Stewart, Lance J. (UWASH); (Emerald)

2011-09-28

As part of the Seattle Structural Genomics Center for Infectious Disease, we seek to enhance structural genomics with ligand-bound structure data which can serve as a blueprint for structure-based drug design. We have adapted fragment-based screening methods to our structural genomics pipeline to generate multiple ligand-bound structures of high priority drug targets from pathogenic organisms. In this study, we report fragment screening methods and structure determination results for 2C-methyl-D-erythritol-2,4-cyclo-diphosphate (MECP) synthase from Burkholderia pseudomallei, the gram-negative bacterium which causes melioidosis. Screening by nuclear magnetic resonance spectroscopy as well as crystal soaking followed by X-ray diffraction led to the identification of several small molecules which bind this enzyme in a critical metabolic pathway. A series of complex structures obtained with screening hits reveal distinct binding pockets and a range of small molecules which form complexes with the target. Additional soaks with these compounds further demonstrate a subset of fragments to only bind the protein when present in specific combinations. This ensemble of fragment-bound complexes illuminates several characteristics of MECP synthase, including a previously unknown binding surface external to the catalytic active site. These ligand-bound structures now serve to guide medicinal chemists and structural biologists in rational design of novel inhibitors for this enzyme.

Real-Time Two-Dimensional Magnetic Particle Imaging for Electromagnetic Navigation in Targeted Drug Delivery