target based drug: Topics by Science.gov

Sample records for target based drug

Complementary Approaches to Existing Target Based Drug Discovery for Identifying Novel Drug Targets.

PubMed

Vasaikar, Suhas; Bhatia, Pooja; Bhatia, Partap G; Chu Yaiw, Koon

2016-11-21

In the past decade, it was observed that the relationship between the emerging New Molecular Entities and the quantum of R&D investment has not been favorable. There might be numerous reasons but few studies stress the introduction of target based drug discovery approach as one of the factors. Although a number of drugs have been developed with an emphasis on a single protein target, yet identification of valid target is complex. The approach focuses on an in vitro single target, which overlooks the complexity of cell and makes process of validation drug targets uncertain. Thus, it is imperative to search for alternatives rather than looking at success stories of target-based drug discovery. It would be beneficial if the drugs were developed to target multiple components. New approaches like reverse engineering and translational research need to take into account both system and target-based approach. This review evaluates the strengths and limitations of known drug discovery approaches and proposes alternative approaches for increasing efficiency against treatment.
Deep-Learning-Based Drug-Target Interaction Prediction.

PubMed

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

2017-04-07

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

PubMed Central

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

2012-01-01

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

PubMed

Li, Yan; Kang, Congbao

2017-08-23

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

PubMed Central

2013-01-01

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

PubMed

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

2016-01-01

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

PubMed

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

2016-08-01

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

PubMed

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

2016-01-01

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

PubMed

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

2013-01-01

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

PubMed Central

2013-01-01

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

PubMed Central

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

2013-01-01

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

PubMed Central

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

2016-01-01

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

PubMed

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

2016-06-15

Identifying drug-target interactions is an important task in drug discovery. To reduce heavy time and financial cost in experimental way, many computational approaches have been proposed. Although these approaches have used many different principles, their performance is far from satisfactory, especially in predicting drug-target interactions of new candidate drugs or targets. Approaches based on machine learning for this problem can be divided into two types: feature-based and similarity-based methods. Learning to rank is the most powerful technique in the feature-based methods. Similarity-based methods are well accepted, due to their idea of connecting the chemical and genomic spaces, represented by drug and target similarities, respectively. We propose a new method, DrugE-Rank, to improve the prediction performance by nicely combining the advantages of the two different types of methods. That is, DrugE-Rank uses LTR, for which multiple well-known similarity-based methods can be used as components of ensemble learning. The performance of DrugE-Rank is thoroughly examined by three main experiments using data from DrugBank: (i) cross-validation on FDA (US Food and Drug Administration) approved drugs before March 2014; (ii) independent test on FDA approved drugs after March 2014; and (iii) independent test on FDA experimental drugs. Experimental results show that DrugE-Rank outperforms competing methods significantly, especially achieving more than 30% improvement in Area under Prediction Recall curve for FDA approved new drugs and FDA experimental drugs. http://datamining-iip.fudan.edu.cn/service/DrugE-Rank zhusf@fudan.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.
Nanobiotechnology-based drug delivery in brain targeting.

PubMed

Dinda, Subas C; Pattnaik, Gurudutta

2013-01-01

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

PubMed

Müller, Joachim; Hemphill, Andrew

2016-08-01

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

PubMed Central

Müller, Joachim; Hemphill, Andrew

2016-01-01

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

PubMed

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

2015-07-15

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

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

Chen, S.; Wong, S.; Zhao, X.

An efficient mechanism-based tumor-targeting drug delivery system, based on tumor-specific vitamin-receptor mediated endocytosis, has been developed. The tumor-targeting drug delivery system is a conjugate of a tumor-targeting molecule (biotin: vitamin H or vitamin B-7), a mechanism-based self-immolative linker and a second-generation taxoid (SB-T-1214) as the cytotoxic agent. This conjugate (1) is designed to be (i) specific to the vitamin receptors overexpressed on tumor cell surface and (ii) internalized efficiently through receptor-mediated endocytosis, followed by smooth drug release via glutathione-triggered self-immolation of the linker. In order to monitor and validate the sequence of events hypothesized, i.e., receptor-mediated endocytosis of the conjugate,more » drug release, and drug-binding to the target protein (microtubules), three fluorescent/fluorogenic molecular probes (2, 3, and 4) were designed and synthesized. The actual occurrence of these processes was unambiguously confirmed by means of confocal fluorescence microscopy (CFM) and flow cytometry using L1210FR leukemia cells, overexpressing biotin receptors. The molecular probe 4, bearing the taxoid linked to fluorescein, was also used to examine the cell specificity (i.e., efficacy of receptor-based cell targeting) for three cell lines, L1210FR (biotin receptors overexpressed), L1210 (biotin receptors not overexpressed), and WI38 (normal human lung fibroblast, biotin receptor negative). As anticipated, the molecular probe 4 exhibited high specificity only to L1210FR. To confirm the direct correlation between the cell-specific drug delivery and anticancer activity of the probe 4, its cytotoxicity against these three cell lines was also examined. The results clearly showed a good correlation between the two methods. In the same manner, excellent cell-specific cytotoxicity of the conjugate 1 (without fluorescein attachment to the taxoid) against the same three cell lines was confirmed. This
Mechanism-Based Enhanced Delivery of Drug-Loaded Targeted Nanoparticles for Breast Cancer Therapy

DTIC Science & Technology

2014-02-01

Based Enhanced Delivery of Drug-Loaded Targeted Nanoparticles for Breast Cancer Therapy” 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-11-1-0167 5c... Nanotechnologies in Living Systems”, Moscow Region, Russia, September, 2011. 3. “Ionic nanogels for drug delivery in cancer ”. NanoDDS’12; Atlantic City, New...AD Award Number: W81XWH-11-1-0167 TITLE: Mechanism-Based Enhanced Delivery of Drug-Loaded Targeted Nanoparticles for Breast
Predicting Drug-Target Interactions Based on Small Positive Samples.

PubMed

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

2018-01-01

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

Mechanism-Based Enhanced Delivery of Drug-Loaded Targeted Nanoparticles for Breast Cancer Therapy

DTIC Science & Technology

2014-02-01

Enhanced Delivery of Drug-Loaded Targeted Nanoparticles for Breast Cancer Therapy” 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-11-1-0166 5c... Nanotechnologies in Living Systems”, Moscow Region, Russia, September, 2011. 3. “Ionic nanogels for drug delivery in cancer ”. NanoDDS’12; Atlantic City, New...AD Award Number: W81XWH-11-1-0166 TITLE: Mechanism-Based Enhanced Delivery of Drug-Loaded Targeted Nanoparticles for Breast
Drug Target Protein-Protein Interaction Networks: A Systematic Perspective

PubMed Central

2017-01-01

The identification and validation of drug targets are crucial in biomedical research and many studies have been conducted on analyzing drug target features for getting a better understanding on principles of their mechanisms. But most of them are based on either strong biological hypotheses or the chemical and physical properties of those targets separately. In this paper, we investigated three main ways to understand the functional biomolecules based on the topological features of drug targets. There are no significant differences between targets and common proteins in the protein-protein interactions network, indicating the drug targets are neither hub proteins which are dominant nor the bridge proteins. According to some special topological structures of the drug targets, there are significant differences between known targets and other proteins. Furthermore, the drug targets mainly belong to three typical communities based on their modularity. These topological features are helpful to understand how the drug targets work in the PPI network. Particularly, it is an alternative way to predict potential targets or extract nontargets to test a new drug target efficiently and economically. By this way, a drug target's homologue set containing 102 potential target proteins is predicted in the paper. PMID:28691014
Drug target ontology to classify and integrate drug discovery data.

PubMed

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

2017-11-09

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

PubMed

Tonge, Peter J

2018-01-17

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

PubMed

Price, Amanda J; Howard, Steven; Cons, Benjamin D

2017-11-08

Fragment-based drug discovery (FBDD) is a technique for identifying low molecular weight chemical starting points for drug discovery. Since its inception 20 years ago, FBDD has grown in popularity to the point where it is now an established technique in industry and academia. The approach involves the biophysical screening of proteins against collections of low molecular weight compounds (fragments). Although fragments bind to proteins with relatively low affinity, they form efficient, high quality binding interactions with the protein architecture as they have to overcome a significant entropy barrier to bind. Of the biophysical methods available for fragment screening, X-ray protein crystallography is one of the most sensitive and least prone to false positives. It also provides detailed structural information of the protein-fragment complex at the atomic level. Fragment-based screening using X-ray crystallography is therefore an efficient method for identifying binding hotspots on proteins, which can then be exploited by chemists and biologists for the discovery of new drugs. The use of FBDD is illustrated here with a recently published case study of a drug discovery programme targeting the challenging protein-protein interaction Kelch-like ECH-associated protein 1:nuclear factor erythroid 2-related factor 2. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.
Polysaccharides based nanomaterials for targeted anti-cancer drug delivery.

PubMed

Dheer, Divya; Arora, Divya; Jaglan, Sundeep; Rawal, Ravindra K; Shankar, Ravi

2017-01-01

Polysaccharides, an important class of biological polymers, are effectively bioactive, nontoxic, hydrophilic, biodegradable and offer a wide diversity in structure and properties. These can be easily modified chemically and biochemically to enhance the bioadhesion with biological tissues, better stability and can improve bioavailability of drugs. Most of the chemotherapeutic drugs have a narrow therapeutic index, slow drug delivery systems and poor water solubility that usually proves toxic to human bodies. The inherent biocompatibility of these biopolymers have shown enhancement of solubility of some chemotherapeutic drugs which also leads to the preparation of nanomaterials for the delivery of antibiotics, anticancer, proteins, peptides and nucleic acids using several routes of administration. Recently, synthesis and research on polysaccharides based nanomaterials have gained enormous attention as one of the most applicable resources in nanomedicine area. This review article will provide a specific emphasis on polysaccharides as natural biomaterials for targeted anticancer drug delivery system.
DrugE-Rank: improving drug–target interaction prediction of new candidate drugs or targets by ensemble learning to rank

PubMed Central

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

2016-01-01

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

PubMed

Ashfaq, Usman Ali; Riaz, Muhammad; Yasmeen, Erum; Yousaf, Muhammad Zubair

2017-01-01

Cancer is one of the major causes of death worldwide. The silent activation of cellular factors responsible for deviation from normal regulatory pathways leads to the development of cancer. Nano-biotechnology is a novel drug-delivery system with high potential of efficacy and accuracy to target lethal cancers. Various biocompatible nanoparticle (NP)-based drug-delivery systems such as liposomes, dendrimers, micelles, silica, quantum dots, and magnetic, gold, and carbon nanotubes have already been reported for successful targeted cancer treatment. NPs are functionalized with different biological molecules, peptides, antibody, and protein ligands for targeted drug delivery. These systems include a hydrophilic central core, a target-oriented biocompatible outer layer, and a middle hydrophobic core where the drug destined to reach target site resides. Most of the NPs have the ability to maintain their structural shape and are constructed according to the cancer microenvironment. The self-assembling and colloidal properties of NPs have caused them to become the best vehicles for targeted drug delivery. The tumor microenvironment (TME) plays a major role in cancer progression, detection, and treatment. Due to its continuous complex behavior, the TME can hinder delivery systems, thus halting cancer treatment. Nonetheless, a successful biophysiological interaction between the NPs and the TME results in targeted release of drugs. Currently, a number of drugs and NP-based delivery systems against cancer are in clinical and preclinical trials and a few have been approved by Food and Drug Administration (FDA); for example: taxol, doxil, cerubidine, and adrucil. This review summarizes topical advances about the drugs being used for cancer treatment, their targeted delivery systems based on NPs, and the role of TME in this connection.
Identifying Drug-Target Interactions with Decision Templates.

PubMed

Yan, Xiao-Ying; Zhang, Shao-Wu

2018-01-01

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

PubMed

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

2015-05-11

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

NASA Astrophysics Data System (ADS)

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

2015-05-01

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

PubMed Central

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

2015-01-01

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

PubMed

Penrod, Nadia M; Moore, Jason H

2014-02-05

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

PubMed Central

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

PubMed

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

2017-07-01

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

PubMed Central

Chen, Lu; Morrow, John K.; Tran, Hoang T.; Phatak, Sharangdhar S.; Du-Cuny, Lei; Zhang, Shuxing

2013-01-01

As an important aspect of computer-aided drug design, structure-based drug design brought a new horizon to pharmaceutical development. This in silico method permeates all aspects of drug discovery today, including lead identification, lead optimization, ADMET prediction and drug repurposing. Structure-based drug design has resulted in fruitful successes drug discovery targeting protein-ligand and protein-protein interactions. Meanwhile, challenges, noted by low accuracy and combinatoric issues, may also cause failures. In this review, state-of-the-art techniques for protein modeling (e.g. structure prediction, modeling protein flexibility, etc.), hit identification/optimization (e.g. molecular docking, focused library design, fragment-based design, molecular dynamic, etc.), and polypharmacology design will be discussed. We will explore how structure-based techniques can facilitate the drug discovery process and interplay with other experimental approaches. PMID:22316152
Drug-targeting methodologies with applications: A review

PubMed Central

Kleinstreuer, Clement; Feng, Yu; Childress, Emily

2014-01-01

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

PubMed

Iqbal, Hafiz M N; Rodriguez, Angel M V; Khandia, Rekha; Munjal, Ashok; Dhama, Kuldeep

2017-01-01

In the recent past, a wider spectrum of nanotechnologybased drugs or drug-loaded devices and systems has been engineered and investigated with high interests. The key objective is to help for an enhanced/better quality of patient life in a secure way by avoiding/limiting drug abuse, or severe adverse effects of some in practice traditional therapies. Various methodological approaches including in vitro, in vivo, and ex vivo techniques have been exploited, so far. Among them, nanoparticles-based therapeutic agents are of supreme interests for an enhanced and efficient delivery in the current biomedical sector of the modern world. The development of new types of novel, effective and highly reliable therapeutic drug delivery system (DDS) for multipurpose applications is essential and a core demand to tackle many human health related diseases. In this context, nanotechnology-based several advanced DDS have been engineered with novel characteristics for biomedical, pharmaceutical and cosmeceutical applications that include but not limited to the enhanced/improved bioactivity, bioavailability, drug efficacy, targeted delivery, and therapeutically safer with an extra advantage of overcoming demerits of traditional drug formulations/designs. This review work is focused on recent trends/advances in nanotechnology-based drugs and formulations designed for targeted therapeutic delivery. Moreover, information is also reviewed and given from recent patents and summarized or illustrated diagrammatically to depict a better understanding. Recent patents covering various nanotechnology-based approaches for several applications have also been reviewed. The drug-loaded nanoparticles are among versatile candidates with multifunctional characteristics for potential applications in biomedical, and tissue engineering sector. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
A targeted drug delivery system based on dopamine functionalized nano graphene oxide

NASA Astrophysics Data System (ADS)

Masoudipour, Elham; Kashanian, Soheila; Maleki, Nasim

2017-01-01

The cellular targeting property of a biocompatible drug delivery system can widely increase the therapeutic effect against various diseases. Here, we report a dopamine conjugated nano graphene oxide (DA-nGO) carrier for cellular delivery of the anticancer drug, Methotrexate (MTX) into DA receptor positive human breast adenocarcinoma cell line. The material was characterized using scanning electron microscopy, atomic force microscopy, Fourier transform infrared spectroscopy and UV-vis spectroscopy. Furthermore, the antineoplastic action of MTX loaded DA-nGO against DA receptor positive and negative cell lines were explored. The results presented in this article demonstrated that the application of DA functionalized GO as a targeting drug carrier can improve the drug delivery efficacy for DA receptor positive cancer cell lines and promise future designing of carrier conjugates based on it.
Exploring drug-target interaction networks of illicit drugs.

PubMed

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

2013-01-01

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

Exploring drug-target interaction networks of illicit drugs

PubMed Central

2013-01-01

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

PubMed

Hellerstein, Marc K

2008-01-01

Contemporary drug discovery and development (DDD) is dominated by a molecular target-based paradigm. Molecular targets that are potentially important in disease are physically characterized; chemical entities that interact with these targets are identified by ex vivo high-throughput screening assays, and optimized lead compounds enter testing as drugs. Contrary to highly publicized claims, the ascendance of this approach has in fact resulted in the lowest rate of new drug approvals in a generation. The primary explanation for low rates of new drugs is attrition, or the failure of candidates identified by molecular target-based methods to advance successfully through the DDD process. In this essay, I advance the thesis that this failure was predictable, based on modern principles of metabolic control that have emerged and been applied most forcefully in the field of metabolic engineering. These principles, such as the robustness of flux distributions, address connectivity relationships in complex metabolic networks and make it unlikely a priori that modulating most molecular targets will have predictable, beneficial functional outcomes. These same principles also suggest, however, that unexpected therapeutic actions will be common for agents that have any effect (i.e., that complexity can be exploited therapeutically). A potential operational solution (pathway-based DDD), based on observability rather than predictability, is described, focusing on emergent properties of key metabolic pathways in vivo. Recent examples of pathway-based DDD are described. In summary, the molecular target-based DDD paradigm is built on a naïve and misleading model of biologic control and is not heuristically adequate for advancing the mission of modern therapeutics. New approaches that take account of and are built on principles described by metabolic engineers are needed for the next generation of DDD.
Targeted drug delivery nanosystems based on copolymer poly(lactide)-tocopheryl polyethylene glycol succinate for cancer treatment

NASA Astrophysics Data System (ADS)

Thu Ha, Phuong; Nguyen, Hoai Nam; Doan Do, Hai; Thong Phan, Quoc; Nguyet Tran Thi, Minh; Phuc Nguyen, Xuan; Nhung Hoang Thi, My; Huong Le, Mai; Nguyen, Linh Toan; Quang Bui, Thuc; Hieu Phan, Van

2016-03-01

Along with the development of nanotechnology, drug delivery nanosystems (DDNSs) have attracted a great deal of concern among scientists over the world, especially in cancer treatment. DDNSs not only improve water solubility of anticancer drugs but also increase therapeutic efficacy and minimize the side effects of treatment methods through targeting mechanisms including passive and active targeting. Passive targeting is based on the nano-size of drug delivery systems while active targeting is based on the specific bindings between targeting ligands attached on the drug delivery systems and the unique receptors on the cancer cell surface. In this article we present some of our results in the synthesis and testing of DDNSs prepared from copolymer poly(lactide)-tocopheryl polyethylene glycol succinate (PLA-TPGS), which carry anticancer drugs including curcumin, paclitaxel and doxorubicin. In order to increase the targeting effect to cancer cells, active targeting ligand folate was attached to the DDNSs. The results showed copolymer PLA-TPGS to be an excellent carrier for loading hydrophobic drugs (curcumin and paclitaxel). The fabricated DDNSs had a very small size (50-100 nm) and enhanced the cellular uptake and cytotoxicity of drugs. Most notably, folate-decorated paclitaxel-loaded copolymer PLA-TPGS nanoparticles (Fol/PTX/PLA-TPGS NPs) were tested on tumor-bearing nude mice. During the treatment time, Fol/PTX/PLA-TPGS NPs always exhibited the best tumor growth inhibition compared to free paclitaxel and paclitaxel-loaded copolymer PLA-TPGS nanoparticles. All results evidenced the promising potential of copolymer PLA-TPGS in fabricating targeted DDNSs for cancer treatment.
Nanomedicines based drug delivery systems for anti-cancer targeting and treatment.

PubMed

Jain, Vikas; Jain, Shikha; Mahajan, S C

2015-01-01

Cancer is defined as an uncontrolled growth of abnormal cells. Current treatment strategies for cancer include combination of radiation, chemotherapy and surgery. The long-term use of conventional drug delivery systems for cancer chemotherapy leads to fatal damage of normal proliferate cells and this is particularly used for the management of solid tumors, where utmost tumor cells are not invaded quickly. A targeted drug delivery system (TDDS) is a system, which releases the drug at a preselected biosite in a controlled manner. Nanotechnology based delivery systems are making a significant impact on cancer treatment and the polymers play key role in the development of nanopraticlulate carriers for cancer therapy. Some important technological advantages of nanotherapeutic drug delivery systems (NDDS) include prolonged half-life, improved bio-distribution, increased circulation time of the drug, controlled and sustained release of the drug, versatility of route of administration, increased intercellular concentration of drug and many more. This review covers the current research on polymer based anticancer agents, the rationale for development of these polymer therapeutical systems and discusses the benefits and challenges of cancer nanomedicines including polymer-drug conjugates, micelles, dendrimers, immunoconjugates, liposomes, nanoparticles.
DrugBank: a knowledgebase for drugs, drug actions and drug targets

PubMed Central

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

2008-01-01

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

PubMed

Chatterjee, Paulami; Roy, Debjani; Rathi, Nitin

2018-01-01

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

PubMed

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

NASA Astrophysics Data System (ADS)

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.
Nanostructured porous Si-based nanoparticles for targeted drug delivery

PubMed Central

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

2012-01-01

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

PubMed

Peska, Ladislav; Buza, Krisztian; Koller, Júlia

2017-12-01

In silico prediction of drug-target interactions (DTI) could provide valuable information and speed-up the process of drug repositioning - finding novel usage for existing drugs. In our work, we focus on machine learning algorithms supporting drug-centric repositioning approach, which aims to find novel usage for existing or abandoned drugs. We aim at proposing a per-drug ranking-based method, which reflects the needs of drug-centric repositioning research better than conventional drug-target prediction approaches. We propose Bayesian Ranking Prediction of Drug-Target Interactions (BRDTI). The method is based on Bayesian Personalized Ranking matrix factorization (BPR) which has been shown to be an excellent approach for various preference learning tasks, however, it has not been used for DTI prediction previously. In order to successfully deal with DTI challenges, we extended BPR by proposing: (i) the incorporation of target bias, (ii) a technique to handle new drugs and (iii) content alignment to take structural similarities of drugs and targets into account. Evaluation on five benchmark datasets shows that BRDTI outperforms several state-of-the-art approaches in terms of per-drug nDCG and AUC. BRDTI results w.r.t. nDCG are 0.929, 0.953, 0.948, 0.897 and 0.690 for G-Protein Coupled Receptors (GPCR), Ion Channels (IC), Nuclear Receptors (NR), Enzymes (E) and Kinase (K) datasets respectively. Additionally, BRDTI significantly outperformed other methods (BLM-NII, WNN-GIP, NetLapRLS and CMF) w.r.t. nDCG in 17 out of 20 cases. Furthermore, BRDTI was also shown to be able to predict novel drug-target interactions not contained in the original datasets. The average recall at top-10 predicted targets for each drug was 0.762, 0.560, 1.000 and 0.404 for GPCR, IC, NR, and E datasets respectively. Based on the evaluation, we can conclude that BRDTI is an appropriate choice for researchers looking for an in silico DTI prediction technique to be used in drug
Feasibility of CRISPR-Cas9-Based In Vitro Drug Target Identification for Personalized Prostate Cancer Medicine

DTIC Science & Technology

2017-09-01

AWARD NUMBER: W81XWH-16-1-0502 TITLE: Feasibility of CRISPR -Cas9-Based In Vitro Drug Target Identification for Personalized Prostate Cancer Medicine...CONTRACT NUMBER Feasibility of CRISPR -Cas9-Based In Vitro Drug Target Identification for Personalized Prostate Cancer Medicine 5b. GRANT NUMBER...Approved for Public Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT This study tests the feasibility of using CRISPR -Cas9 to
Biodegradable polymers for targeted delivery of anti-cancer drugs.

PubMed

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

2016-06-01

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

PubMed

Barneh, Farnaz; Jafari, Mohieddin; Mirzaie, Mehdi

2016-11-01

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

PubMed

Gholipourmalekabadi, Mazaher; Mobaraki, Mohammadmahdi; Ghaffari, Maryam; Zarebkohan, Amir; Omrani, Vahid Fallah; Urbanska, Aleksandra M; Seifalian, Alexander

2017-01-01

Drug delivery systems are effective and attractive methods which allow therapeutic substances to be introduced into the body more effectively and safe by having tunable delivery rate and release target site. Gold nanoparticles (AuNPs) have a myriad of favorable physical, chemical, optical, thermal and biological properties that make them highly suitable candidates as non-toxic carriers for drug and gene delivery. The surface modifications of AuNPs profoundly improve their circulation, minimize aggregation rates, enhance attachment to therapeutic molecules and target agents due to their nano range size which further increases their ability to cross cell membranes and reduce overall cytotoxicity. This comprehensive article reviews the applications of the AuNPs in drug delivery systems along with their corresponding surface modifications. The highlighting results obtained from the preclinical trial are promising and next five years have huge possibility move to the clinical setting. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
UniDrug-target: a computational tool to identify unique drug targets in pathogenic bacteria.

PubMed

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

2012-01-01

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

PubMed Central

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

2014-01-01

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

PubMed Central

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
Discovery of novel drugs for promising targets.

PubMed

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

2013-09-01

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

PubMed

Alaimo, Salvatore; Giugno, Rosalba; Pulvirenti, Alfredo

2016-01-01

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

PubMed Central

Yacoby, Iftach; Bar, Hagit; Benhar, Itai

2007-01-01

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

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

PubMed

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

2017-07-19

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

NASA Astrophysics Data System (ADS)

Gitter, K.; Odenbach, S.

2011-12-01

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

PubMed

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

2015-10-06

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

PubMed

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

2016-01-01

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

PubMed Central

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

2017-01-01

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

PubMed

Wang, Yuhao; Zeng, Jianyang

2013-07-01

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

PubMed

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

2012-01-01

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

PubMed

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

2008-01-01

The molecular basis of drug action is often not well understood. This is partly because the very abundant and diverse information generated in the past decades on drugs is hidden in millions of medical articles or textbooks. Therefore, we developed a one-stop data warehouse, SuperTarget that integrates drug-related information about medical indication areas, adverse drug effects, drug metabolization, pathways and Gene Ontology terms of the target proteins. An easy-to-use query interface enables the user to pose complex queries, for example to find drugs that target a certain pathway, interacting drugs that are metabolized by the same cytochrome P450 or drugs that target the same protein but are metabolized by different enzymes. Furthermore, we provide tools for 2D drug screening and sequence comparison of the targets. The database contains more than 2500 target proteins, which are annotated with about 7300 relations to 1500 drugs; the vast majority of entries have pointers to the respective literature source. A subset of these drugs has been annotated with additional binding information and indirect interactions and is available as a separate resource called Matador. SuperTarget and Matador are available at http://insilico.charite.de/supertarget and http://matador.embl.de.
Drug2Gene: an exhaustive resource to explore effectively the drug-target relation network.

PubMed

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

2014-03-11

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

NASA Astrophysics Data System (ADS)

Saraf, Poonam S.

in comparison to free drug in Detroit 551 cells. In A2058 melanoma xenograft mice model, the Paclitaxel-RGD micelles exhibited a significant inhibition of tumor growth in comparison to control treatment for both alternate day and twice weekly treatments. The studies showed the feasibility of using the non covalent peptide based self-assemblies as vehicles for targeted delivery in cancer.
Discovery of Anthelmintic Drug Targets and Drugs Using Chokepoints in Nematode Metabolic Pathways

PubMed Central

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

2013-01-01

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

PubMed Central

Bar, Hagit; Yacoby, Iftach; Benhar, Itai

2008-01-01

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

PubMed

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

2015-11-23

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

PubMed

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.
Development In Drug Targeting And Delivery In Cervical Cancer.

PubMed

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

2017-10-09

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

PubMed Central

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

2013-01-01

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

PubMed

Lin, Tai-Chi; Hung, Kuo-Hsuan; Peng, Chi-Hsien; Liu, Jorn-Hon; Woung, Lin-Chung; Tsai, Ching-Yao; Chen, Shih-Jen; Chen, Yan-Ting; Hsu, Chih-Chien

2015-11-01

Nanoparticles combined with cells, drugs, and specially designed genes provide improved therapeutic efficacy in studies and clinical setting, demonstrating a new era of treatment strategy, especially in retinal diseases. Nanotechnology-based drugs can provide an essential platform for sustaining, releasing and a specific targeting design to treat retinal diseases. Poly-lactic-co-glycolic acid is the most widely used biocompatible and biodegradable polymer approved by the Food and Drug Administration. Many studies have attempted to develop special devices for delivering small-molecule drugs, proteins, and other macromolecules consistently and slowly. In this article, we first review current progress in the treatment of age-related macular degeneration. Then, we discuss the function of vascular endothelial growth factor (VEGF) and the pharmacological effects of anti-VEGF-A antibodies and soluble or modified VEGF receptors. Lastly, we summarize the combination of antiangiogenic therapy and nanomedicines, and review current potential targeting therapy in age-related macular degeneration. Copyright © 2015. Published by Elsevier Taiwan.
The drug target genes show higher evolutionary conservation than non-target genes.

PubMed

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

2016-01-26

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

PubMed Central

Ma, Haisu; Zhao, Hongyu

2013-01-01

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

Properties of Protein Drug Target Classes

PubMed Central

Bull, Simon C.; Doig, Andrew J.

2015-01-01

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

PubMed

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

2017-03-01

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

PubMed

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

2018-01-01

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

PubMed

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

PubMed

Vilar, Santiago; Hripcsak, George

2016-01-01

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

PubMed

Tan, Hepan; Ge, Xiaoxia; Xie, Lei

2013-08-01

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

PubMed Central

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

2015-01-01

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

NASA Astrophysics Data System (ADS)

Sharma, Om Prakash; Kumar, Muthuvel Suresh

2016-01-01

Lymphatic filariasis (Lf) is one of the oldest and most debilitating tropical diseases. Millions of people are suffering from this prevalent disease. It is estimated to infect over 120 million people in at least 80 nations of the world through the tropical and subtropical regions. More than one billion people are in danger of getting affected with this life-threatening disease. Several studies were suggested its emerging limitations and resistance towards the available drugs and therapeutic targets for Lf. Therefore, better medicine and drug targets are in demand. We took an initiative to identify the essential proteins of Wolbachia endosymbiont of Brugia malayi, which are indispensable for their survival and non-homologous to human host proteins. In this current study, we have used proteome subtractive approach to screen the possible therapeutic targets for wBm. In addition, numerous literatures were mined in the hunt for potential drug targets, drugs, epitopes, crystal structures, and expressed sequence tag (EST) sequences for filarial causing nematodes. Data obtained from our study were presented in a user friendly database named FiloBase. We hope that information stored in this database may be used for further research and drug development process against filariasis. URL: http://filobase.bicpu.edu.in.
Targeted cancer drug delivery with aptamer-functionalized polymeric nanoparticles.

PubMed

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

2018-06-21

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

PubMed

Maity, Amit Ranjan; Stepensky, David

2016-01-04

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

PubMed

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

2017-06-23

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

PubMed Central

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

2017-01-01

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

PubMed Central

2015-01-01

Background Computer-aided drug design has a long history of being applied to discover new molecules to treat various cancers, but it has always been focused on single targets. The development of systems biology has let scientists reveal more hidden mechanisms of cancers, but attempts to apply systems biology to cancer therapies remain at preliminary stages. Our lab has successfully developed various systems biology models for several cancers. Based on these achievements, we present the first attempt to combine multiple-target therapy with systems biology. Methods In our previous study, we identified 28 significant proteins--i.e., common core network markers--of four types of cancers as house-keeping proteins of these cancers. In this study, we ranked these proteins by summing their carcinogenesis relevance values (CRVs) across the four cancers, and then performed docking and pharmacophore modeling to do virtual screening on the NCI database for anti-cancer drugs. We also performed pathway analysis on these proteins using Panther and MetaCore to reveal more mechanisms of these cancer house-keeping proteins. Results We designed several approaches to discover targets for multiple-target cocktail therapies. In the first one, we identified the top 20 drugs for each of the 28 cancer house-keeping proteins, and analyzed the docking pose to further understand the interaction mechanisms of these drugs. After screening for duplicates, we found that 13 of these drugs could target 11 proteins simultaneously. In the second approach, we chose the top 5 proteins with the highest summed CRVs and used them as the drug targets. We built a pharmacophore and applied it to do virtual screening against the Life-Chemical library for anti-cancer drugs. Based on these results, wet-lab bio-scientists could freely investigate combinations of these drugs for multiple-target therapy for cancers, in contrast to the traditional single target therapy. Conclusions Combination of systems biology
New Equilibrium Models of Drug-Receptor Interactions Derived from Target-Mediated Drug Disposition.

PubMed

Peletier, Lambertus A; Gabrielsson, Johan

2018-05-14

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

NASA Astrophysics Data System (ADS)

Wang, Xiao-Gang; Dong, Zhi-Yue; Cheng, Hong; Wan, Shuang-Shuang; Chen, Wei-Hai; Zou, Mei-Zhen; Huo, Jia-Wei; Deng, He-Xiang; Zhang, Xian-Zheng

2015-09-01

Drug delivery systems (DDSs) with biocompatibility and precise drug delivery are eagerly needed to overcome the paradox in chemotherapy that high drug doses are required to compensate for the poor biodistribution of drugs with frequent dose-related side effects. In this work, we reported a metal-organic framework (MOF) based tumor targeting DDS developed by a one-pot, and organic solvent-free ``green'' post-synthetic surface modification procedure, starting from the nanoscale MOF MIL-101. Owing to the multifunctional surface coating, premature drug release from this DDS was prevented. Due to the pH responsive benzoic imine bond and the redox responsive disulfide bond at the modified surface, this DDS exhibited tumor acid environment enhanced cellular uptake and intracellular reducing environment triggered drug release. In vitro and in vivo results showed that DOX loaded into this DDS exhibited effective cancer cell inhibition with much reduced side effects.Drug delivery systems (DDSs) with biocompatibility and precise drug delivery are eagerly needed to overcome the paradox in chemotherapy that high drug doses are required to compensate for the poor biodistribution of drugs with frequent dose-related side effects. In this work, we reported a metal-organic framework (MOF) based tumor targeting DDS developed by a one-pot, and organic solvent-free ``green'' post-synthetic surface modification procedure, starting from the nanoscale MOF MIL-101. Owing to the multifunctional surface coating, premature drug release from this DDS was prevented. Due to the pH responsive benzoic imine bond and the redox responsive disulfide bond at the modified surface, this DDS exhibited tumor acid environment enhanced cellular uptake and intracellular reducing environment triggered drug release. In vitro and in vivo results showed that DOX loaded into this DDS exhibited effective cancer cell inhibition with much reduced side effects. Electronic supplementary information (ESI) available
Drug–Target Kinetics in Drug Discovery

PubMed Central

2017-01-01

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

PubMed

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

2014-06-01

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

PubMed

Cohen, Seth M

2017-08-15

Metal-dependent enzymes (i.e., metalloenzymes) make up a large fraction of all enzymes and are critically important in a wide range of biological processes, including DNA modification, protein homeostasis, antibiotic resistance, and many others. Consequently, metalloenzymes represent a vast and largely untapped space for drug development. The discovery of effective therapeutics that target metalloenzymes lies squarely at the interface of bioinorganic and medicinal chemistry and requires expertise, methods, and strategies from both fields to mount an effective campaign. In this Account, our research program that brings together the principles and methods of bioinorganic and medicinal chemistry are described, in an effort to bridge the gap between these fields and address an important class of medicinal targets. Fragment-based drug discovery (FBDD) is an important drug discovery approach that is particularly well suited for metalloenzyme inhibitor development. FBDD uses relatively small but diverse chemical structures that allow for the assembly of privileged molecular collections that focus on a specific feature of the target enzyme. For metalloenzyme inhibition, the specific feature is rather obvious, namely, a metal-dependent active site. Surprisingly, prior to our work, the exploration of diverse molecular fragments for binding the metal active sites of metalloenzymes was largely unexplored. By assembling a modest library of metal-binding pharmacophores (MBPs), we have been able to find lead hits for many metalloenzymes and, from these hits, develop inhibitors that act via novel mechanisms of action. A specific case study on the use of this strategy to identify a first-in-class inhibitor of zinc-dependent Rpn11 (a component of the proteasome) is highlighted. The application of FBDD for the development of metalloenzyme inhibitors has raised several other compelling questions, such as how the metalloenzyme active site influences the coordination chemistry of bound
Synthesis and Biological Evaluation of Novel Folic Acid Receptor-Targeted, β-Cyclodextrin-Based Drug Complexes for Cancer Treatment

PubMed Central

Yin, Juan-Juan; Sharma, Sonali; Shumyak, Stepan P.; Wang, Zhi-Xin; Zhou, Zhi-Wei; Zhang, Yangde; Guo, Peixuan; Li, Chen-Zhong; Kanwar, Jagat R.; Yang, Tianxin; Mohapatra, Shyam S.; Liu, Wanqing; Duan, Wei; Wang, Jian-Cheng; Li, Qi; Zhang, Xueji; Tan, Jun; Jia, Lee; Liang, Jun; Wei, Ming Q.; Li, Xiaotian; Zhou, Shu-Feng

2013-01-01

Drug targeting is an active area of research and nano-scaled drug delivery systems hold tremendous potential for the treatment of neoplasms. In this study, a novel cyclodextrin (CD)-based nanoparticle drug delivery system has been assembled and characterized for the therapy of folate receptor-positive [FR(+)] cancer. Water-soluble folic acid (FA)-conjugated CD carriers (FACDs) were successfully synthesized and their structures were confirmed by 1D/2D nuclear magnetic resonance (NMR), matrix-assisted laser desorption ionization time-of-flight mass spectrometer (MALDI-TOF-MS), high performance liquid chromatography (HPLC), Fourier transform infrared spectroscopy (FTIR), and circular dichroism. Drug complexes of adamatane (Ada) and cytotoxic doxorubicin (Dox) with FACD were readily obtained by mixed solvent precipitation. The average size of FACD-Ada-Dox was 1.5–2.5 nm. The host-guest association constant K a was 1,639 M−1 as determined by induced circular dichroism and the hydrophilicity of the FACDs was greatly enhanced compared to unmodified CD. Cellular uptake and FR binding competitive experiments demonstrated an efficient and preferentially targeted delivery of Dox into FR-positive tumor cells and a sustained drug release profile was seen in vitro. The delivery of Dox into FR(+) cancer cells via endocytosis was observed by confocal microscopy and drug uptake of the targeted nanoparticles was 8-fold greater than that of non-targeted drug complexes. Our docking results suggest that FA, FACD and FACD-Ada-Dox could bind human hedgehog interacting protein that contains a FR domain. Mouse cardiomyocytes as well as fibroblast treated with FACD-Ada-Dox had significantly lower levels of reactive oxygen species, with increased content of glutathione and glutathione peroxidase activity, indicating a reduced potential for Dox-induced cardiotoxicity. These results indicate that the targeted drug complex possesses high drug association and sustained drug release
Target specific delivery of anticancer drug in silk fibroin based 3D distribution model of bone-breast cancer cells.

PubMed

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

2015-02-04

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

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

PubMed

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

2017-03-01

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

PubMed

Prudhviraj, G; Vaidya, Yogyata; Singh, Sachin Kumar; Yadav, Ankit Kumar; Kaur, Puneet; Gulati, Monica; Gowthamarajan, K

2015-11-01

Significant clinical success of colon targeted dosage forms has been limited by their inappropriate release profile at the target site. Their failure to release the drug completely in the colon may be attributed to changes in the colonic milieu because of pathological state, drug effect and psychological stress accompanying the diseased state or, a combination of these. Alteration in normal colonic pH and bacterial picture leads to incomplete release of drug from the designed delivery system. We report the effectiveness of a targeted delivery system wherein the constant replenishment of the colonic microbiota is achieved by concomitant administration of probiotics along with the polysaccharide based drug delivery system. Guar gum coated spheroids of sulfasalazine were prepared. In the dissolution studies, these spheroids showed markedly higher release in the simulated colonic fluid. In vivo experiments conducted in rats clearly demonstrated the therapeutic advantage of co-administration of probiotics with guar gum coated spheroids. Our results suggest that concomitant use of probiotics along with the polysaccharide based delivery systems can be a simple strategy to achieve satisfactory colon targeting of drugs. Copyright © 2015 Elsevier B.V. All rights reserved.
RFDT: A Rotation Forest-based Predictor for Predicting Drug-Target Interactions Using Drug Structure and Protein Sequence Information.

PubMed

Wang, Lei; You, Zhu-Hong; Chen, Xing; Yan, Xin; Liu, Gang; Zhang, Wei

2018-01-01

Identification of interaction between drugs and target proteins plays an important role in discovering new drug candidates. However, through the experimental method to identify the drug-target interactions remain to be extremely time-consuming, expensive and challenging even nowadays. Therefore, it is urgent to develop new computational methods to predict potential drugtarget interactions (DTI). In this article, a novel computational model is developed for predicting potential drug-target interactions under the theory that each drug-target interaction pair can be represented by the structural properties from drugs and evolutionary information derived from proteins. Specifically, the protein sequences are encoded as Position-Specific Scoring Matrix (PSSM) descriptor which contains information of biological evolutionary and the drug molecules are encoded as fingerprint feature vector which represents the existence of certain functional groups or fragments. Four benchmark datasets involving enzymes, ion channels, GPCRs and nuclear receptors, are independently used for establishing predictive models with Rotation Forest (RF) model. The proposed method achieved the prediction accuracy of 91.3%, 89.1%, 84.1% and 71.1% for four datasets respectively. In order to make our method more persuasive, we compared our classifier with the state-of-theart Support Vector Machine (SVM) classifier. We also compared the proposed method with other excellent methods. Experimental results demonstrate that the proposed method is effective in the prediction of DTI, and can provide assistance for new drug research and development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Editorial: Current status and perspective on drug targets in tubercle bacilli and drug design of antituberculous agents based on structure-activity relationship.

PubMed

Tomioka, Haruaki

2014-01-01

Worldwide, tuberculosis (TB) remains the most frequent and important infectious disease causing morbidity and death. However, the development of new drugs for the treatment and prophylaxis of TB, particularly those truly active against dormant and persistent types of tubercle bacilli, has been slow, although some promising drugs, such as diarylquinoline TMC207, nitroimidazopyran PA-824, nitroimidazo-oxazole Delamanid (OPC-67683), oxazolidinone PNU-100480, ethylene diamine SQ-109, and pyrrole derivative LL3858, are currently under phase 1 to 3 clinical trials. Therefore, novel types of antituberculous drug, which act on unique drug targets in Mycobacterium tuberculosis (MTB) pathogens, particularly drug targets related to the establishment of mycobacterial dormancy in the host's macrophages, are urgently needed. In this context, it should be noted that current anti-TB drugs mostly target the metabolic reactions and proteins which are essential for the growth of MTB in extracellular milieus. It may also be promising to develop another type of drug that exerts an inhibitory action against bacterial virulence factors which cross-talk and interfere with signaling pathways of MTB-infected immunocompetent host cells, such as lymphocytes, macrophages, and NK cells, thereby changing the intracellular milieus that are favorable to intramacrophage survival and the growth of infected bacilli. This special issue contains ten review articles, dealing with recent approaches to identify and establish novel drug targets in MTB for the development of new and unique antitubercular drugs, including those related to mycobacterial dormancy and crosstalk with cellular signaling pathways. In addition, this special issue contains some review papers with special reference to the drug design based on quantitative structure-activity relationship (QSAR) analysis, especially three-dimensional (3D)-QSAR. New, critical information on the entire genome of MTB and mycobacterial virulence genes is
A network-based drug repositioning infrastructure for precision cancer medicine through targeting significantly mutated genes in the human cancer genomes.

PubMed

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

2016-07-01

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

PubMed

Malhi, Sarandeep; Gu, Xiaochen

2015-07-01

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

PubMed Central

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

2010-01-01

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

PubMed Central

2016-01-01

We present here a specific targeting nanocarrier system by functionalization of liposomes with one new type of breast cancer targeting peptide (H6, YLFFVFER) by a micromixer with high efficiency. Antitumor drugs could be successfully delivered into human epidermal growth factor receptor 2 (HER2) positive breast cancer cells with high efficiency in both in vivo and ex vivo models. PMID:27096054
Micromixer Based Preparation of Functionalized Liposomes and Targeting Drug Delivery.

PubMed

Jia, Xiangqian; Wang, Weizhi; Han, Qiuju; Wang, Zihua; Jia, Yunhong; Hu, Zhiyuan

2016-04-14

We present here a specific targeting nanocarrier system by functionalization of liposomes with one new type of breast cancer targeting peptide (H6, YLFFVFER) by a micromixer with high efficiency. Antitumor drugs could be successfully delivered into human epidermal growth factor receptor 2 (HER2) positive breast cancer cells with high efficiency in both in vivo and ex vivo models.
Assessment of deoxyhypusine hydroxylase as a putative, novel drug target.

PubMed

Kerscher, B; Nzukou, E; Kaiser, A

2010-02-01

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

PubMed

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

2012-08-01

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

PubMed Central

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

2014-01-01

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

PubMed

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

2018-01-04

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

PubMed Central

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

2018-01-01

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

PubMed

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

2016-05-28

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

PubMed

Mitchell, Michael J; King, Michael R

2015-03-01

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

PubMed

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

2017-02-25

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

PubMed

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

2015-11-10

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

PubMed

Hori, Hitoshi; Uto, Yoshihiro; Nakata, Eiji

2010-09-01

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

Targeting efflux pumps to overcome antifungal drug resistance

PubMed Central

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

2016-01-01

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

PubMed

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

2016-01-01

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

PubMed Central

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

2009-01-01

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

PubMed

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

2017-01-20

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

PubMed

Kumari, Preeti; Ghosh, Balaram; Biswas, Swati

2016-01-01

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

PubMed Central

Mitchell, Michael J

2017-01-01

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

PubMed Central

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

2010-01-01

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

PubMed

Kumar, Akhil; Tiwari, Ashish; Sharma, Ashok

2018-03-15

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

Cancer.gov

A new study details how a suite of web-based tools provides the research community with greatly improved capacity to compare data derived from large collections of genomic information against thousands of drugs. By comparing drugs and genetic targets, re
System-level multi-target drug discovery from natural products with applications to cardiovascular diseases.

PubMed

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

2014-08-01

The term systems pharmacology describes a field of study that uses computational and experimental approaches to broaden the view of drug actions rooted in molecular interactions and advance the process of drug discovery. The aim of this work is to stick out the role that the systems pharmacology plays across the multi-target drug discovery from natural products for cardiovascular diseases (CVDs). Firstly, based on network pharmacology methods, we reconstructed the drug-target and target-target networks to determine the putative protein target set of multi-target drugs for CVDs treatment. Secondly, we reintegrated a compound dataset of natural products and then obtained a multi-target compounds subset by virtual-screening process. Thirdly, a drug-likeness evaluation was applied to find the ADME-favorable compounds in this subset. Finally, we conducted in vitro experiments to evaluate the reliability of the selected chemicals and targets. We found that four of the five randomly selected natural molecules can effectively act on the target set for CVDs, indicating the reasonability of our systems-based method. This strategy may serve as a new model for multi-target drug discovery of complex diseases.
GRP78 enabled micelle-based glioma targeted drug delivery.

PubMed

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

2017-06-10

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

PubMed Central

Li, Xiuyun; Hou, Yinglong; Yue, Longtao; Liu, Shuyuan; Du, Juan

2015-01-01

Fungal infections, especially infections caused by Candida albicans, remain a challenging problem in clinical settings. Despite the development of more-effective antifungal drugs, their application is limited for various reasons. Thus, alternative treatments with drugs aimed at novel targets in C. albicans are needed. Knowledge of growth and virulence in fungal cells is essential not only to understand their pathogenic mechanisms but also to identify potential antifungal targets. This article reviews the current knowledge of the mechanisms of growth and virulence in C. albicans and examines potential targets for the development of new antifungal drugs. PMID:26195510
Advancing cancer drug discovery towards more agile development of targeted combination therapies.

PubMed

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

2012-01-01

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

PubMed

Liu, Juan; Wei, Tuo; Zhao, Jing; Huang, Yuanyu; Deng, Hua; Kumar, Anil; Wang, Chenxuan; Liang, Zicai; Ma, Xiaowei; Liang, Xing-Jie

2016-06-01

By its unique advantages over traditional medicine, nanomedicine has offered new strategies for cancer treatment. In particular, the development of drug delivery strategies has focused on nanoscale particles to improve bioavailability. However, many of these nanoparticles are unable to overcome tumor resistance to chemotherapeutic agents. Recently, new opportunities for drug delivery have been provided by oligonucleotides that can self-assemble into three-dimensional nanostructures. In this work, we have designed and developed functional DNA nanostructures to deliver the chemotherapy drug doxorubicin (Dox) to resistant cancer cells. These nanostructures have two components. The first component is a DNA aptamer, which forms a dimeric G-quadruplex nanostructure to target cancer cells by binding with nucleolin. The second component is double-stranded DNA (dsDNA), which is rich in -GC- base pairs that can be applied for Dox delivery. We demonstrated that Dox was able to efficiently intercalate into dsDNA and this intercalation did not affect the aptamer's three-dimensional structure. In addition, the Aptamer-dsDNA (ApS) nanoparticle showed good stability and protected the dsDNA from degradation in bovine serum. More importantly, the ApS&Dox nanoparticle efficiently reversed the resistance of human breast cancer cells to Dox. The mechanism circumventing doxorubicin resistance by ApS&Dox nanoparticles may be predominantly by cell cycle arrest in S phase, effectively increased cell uptake and decreased cell efflux of doxorubicin. Furthermore, the ApS&Dox nanoparticles could effectively inhibit tumor growth, while less cardiotoxicity was observed. Overall, this functional DNA nanostructure provides new insights into the design of nanocarriers to overcome multidrug resistance through targeted drug delivery. Copyright © 2016 Elsevier Ltd. All rights reserved.
A graphene oxide based smart drug delivery system for tumor mitochondria-targeting photodynamic therapy

NASA Astrophysics Data System (ADS)

Wei, Yanchun; Zhou, Feifan; Zhang, Da; Chen, Qun; Xing, Da

2016-02-01

Subcellular organelles play critical roles in cell survival. In this work, a novel photodynamic therapy (PDT) drug delivery and phototoxicity on/off nano-system based on graphene oxide (NGO) as the carrier is developed to implement subcellular targeting and attacking. To construct the nanodrug (PPa-NGO-mAb), NGO is modified with the integrin αvβ3 monoclonal antibody (mAb) for tumor targeting. Pyropheophorbide-a (PPa) conjugated with polyethylene-glycol is used to cover the surface of the NGO to induce phototoxicity. Polyethylene-glycol phospholipid is loaded to enhance water solubility. The results show that the phototoxicity of PPa on NGO can be switched on and off in organic and aqueous environments, respectively. The PPa-NGO-mAb assembly is able to effectively target the αvβ3-positive tumor cells with surface ligand and receptor recognition; once endocytosized by the cells, they are observed escaping from lysosomes and subsequently transferring to the mitochondria. In the mitochondria, the `on' state PPa-NGO-mAb performs its effective phototoxicity to kill cells. The biological and physical dual selections and on/off control of PPa-NGO-mAb significantly enhance mitochondria-mediated apoptosis of PDT. This smart system offers a potential alternative to drug delivery systems for cancer therapy.Subcellular organelles play critical roles in cell survival. In this work, a novel photodynamic therapy (PDT) drug delivery and phototoxicity on/off nano-system based on graphene oxide (NGO) as the carrier is developed to implement subcellular targeting and attacking. To construct the nanodrug (PPa-NGO-mAb), NGO is modified with the integrin αvβ3 monoclonal antibody (mAb) for tumor targeting. Pyropheophorbide-a (PPa) conjugated with polyethylene-glycol is used to cover the surface of the NGO to induce phototoxicity. Polyethylene-glycol phospholipid is loaded to enhance water solubility. The results show that the phototoxicity of PPa on NGO can be switched on and off in
Drug-target interaction prediction using ensemble learning and dimensionality reduction.

PubMed

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

2017-10-01

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

PubMed

Obradovic, Marko; Mrhar, Ales; Kos, Mitja

2009-12-01

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

PubMed Central

Penrod, Nadia M.; Cowper-Sal_lari, Richard; Moore, Jason H.

2011-01-01

The collection and analysis of genomic data has the potential to reveal novel druggable targets by providing insight into the genetic basis of disease. However, the number of drugs, targeting new molecular entities, approved by the US Food and Drug Administration (FDA) has not increased in the years since the collection of genomic data has become commonplace. The paucity of translatable results can be partly attributed to conventional analysis methods that test one gene at a time in an effort to identify disease-associated factors as candidate drug targets. By disengaging genetic factors from their position within the genetic regulatory system, much of the information stored within the genomic data set is lost. Here we discuss how genomic data is used to identify disease-associated genes or genomic regions, how disease-associated regions are validated as functional targets, and the role network analysis can play in bridging the gap between data generation and effective drug target identification. PMID:21862141
A side-effect free method for identifying cancer drug targets.

PubMed

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

2018-04-27

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

PubMed Central

Cudic, Mare

2015-01-01

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

Receptor-Mediated Drug Delivery Systems Targeting to Glioma

PubMed Central

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

2015-01-01

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

PubMed Central

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

2015-01-01

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

PubMed

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

2016-01-01

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

PubMed Central

Kebebe, Dereje; Liu, Yuanyuan; Wu, Yumei; Vilakhamxay, Maikhone; Liu, Zhidong; Li, Jiawei

2018-01-01

Cancer has become one of the leading causes of mortality globally. The major challenges of conventional cancer therapy are the failure of most chemotherapeutic agents to accumulate selectively in tumor cells and their severe systemic side effects. In the past three decades, a number of drug delivery approaches have been discovered to overwhelm the obstacles. Among these, nanocarriers have gained much attention for their excellent and efficient drug delivery systems to improve specific tissue/organ/cell targeting. In order to enhance targeting efficiency further and reduce limitations of nanocarriers, nanoparticle surfaces are functionalized with different ligands. Several kinds of ligand-modified nanomedicines have been reported. Cell-penetrating peptides (CPPs) are promising ligands, attracting the attention of researchers due to their efficiency to transport bioactive molecules intracellularly. However, their lack of specificity and in vivo degradation led to the development of newer types of CPP. Currently, activable CPP and tumor-targeting peptide (TTP)-modified nanocarriers have shown dramatically superior cellular specific uptake, cytotoxicity, and tumor growth inhibition. In this review, we discuss recent advances in tumor-targeting strategies using CPPs and their limitations in tumor delivery systems. Special emphasis is given to activable CPPs and TTPs. Finally, we address the application of CPPs and/or TTPs in the delivery of plant-derived chemotherapeutic agents. PMID:29563797
Repurposing anticancer drugs for targeting necroptosis.

PubMed

Fulda, Simone

2018-04-25

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

PubMed Central

Jao, Dave; Xue, Ye; Medina, Jethro; Hu, Xiao

2017-01-01

There is a pressing need for long-term, controlled drug release for sustained treatment of chronic or persistent medical conditions and diseases. Guided drug delivery is difficult because therapeutic compounds need to survive numerous transport barriers and binding targets throughout the body. Nanoscale protein-based polymers are increasingly used for drug and vaccine delivery to cross these biological barriers and through blood circulation to their molecular site of action. Protein-based polymers compared to synthetic polymers have the advantages of good biocompatibility, biodegradability, environmental sustainability, cost effectiveness and availability. This review addresses the sources of protein-based polymers, compares the similarity and differences, and highlights characteristic properties and functionality of these protein materials for sustained and controlled drug release. Targeted drug delivery using highly functional multicomponent protein composites to guide active drugs to the site of interest will also be discussed. A systematical elucidation of drug-delivery efficiency in the case of molecular weight, particle size, shape, morphology, and porosity of materials will then be demonstrated to achieve increased drug absorption. Finally, several important biomedical applications of protein-based materials with drug-delivery function—including bone healing, antibiotic release, wound healing, and corneal regeneration, as well as diabetes, neuroinflammation and cancer treatments—are summarized at the end of this review. PMID:28772877
Protein-Based Drug-Delivery Materials.

PubMed

Jao, Dave; Xue, Ye; Medina, Jethro; Hu, Xiao

2017-05-09

There is a pressing need for long-term, controlled drug release for sustained treatment of chronic or persistent medical conditions and diseases. Guided drug delivery is difficult because therapeutic compounds need to survive numerous transport barriers and binding targets throughout the body. Nanoscale protein-based polymers are increasingly used for drug and vaccine delivery to cross these biological barriers and through blood circulation to their molecular site of action. Protein-based polymers compared to synthetic polymers have the advantages of good biocompatibility, biodegradability, environmental sustainability, cost effectiveness and availability. This review addresses the sources of protein-based polymers, compares the similarity and differences, and highlights characteristic properties and functionality of these protein materials for sustained and controlled drug release. Targeted drug delivery using highly functional multicomponent protein composites to guide active drugs to the site of interest will also be discussed. A systematical elucidation of drug-delivery efficiency in the case of molecular weight, particle size, shape, morphology, and porosity of materials will then be demonstrated to achieve increased drug absorption. Finally, several important biomedical applications of protein-based materials with drug-delivery function-including bone healing, antibiotic release, wound healing, and corneal regeneration, as well as diabetes, neuroinflammation and cancer treatments-are summarized at the end of this review.
Active Targeted Drug Delivery for Microbes Using Nano-Carriers

PubMed Central

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

2015-01-01

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

PubMed

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

2015-11-28

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

PubMed

Kaur, Divneet; Mathew, Shalu; Nair, Chinchu G S; Begum, Azitha; Jainanarayan, Ashwin K; Sharma, Mukta; Brahmachari, Samir K

2017-12-21

The problem of drug resistance and bacterial persistence in tuberculosis is a cause of global alarm. Although, the UN's Sustainable Development Goals for 2030 has targeted a Tb free world, the treatment gap exists and only a few new drug candidates are in the pipeline. In spite of large information from medicinal chemistry to 'omics' data, there has been a little effort from pharmaceutical companies to generate pipelines for the development of novel drug candidates against the multi drug resistant Mycobacterium tuberculosis. In the present study, we describe an integrated methodology; utilizing systems level information to optimize ligand selection to lower the failure rates at the pre-clinical and clinical levels. In the present study, metabolic targets (Rv2763c, Rv3247c, Rv1094, Rv3607c, Rv3048c, Rv2965c, Rv2361c, Rv0865, Rv0321, Rv0098, Rv0390, Rv3588c, Rv2244, Rv2465c and Rv2607) in M. tuberculosis, identified using our previous Systems Biology and data-intensive genome level analysis, have been used to design potential lead molecules, which are likely to be non-toxic. Various in silico drug discovery tools have been utilized to generate small molecular leads for each of the 15 targets with available crystal structures. The present study resulted in identification of 20 novel lead molecules including 4 FDA approved drugs (droxidropa, tetroxoprim, domperidone and nemonapride) which can be further taken for drug repurposing. This comprehensive integrated methodology, with both experimental and in silico approaches, has the potential to not only tackle the MDR form of Mtb but also the most important persister population of the bacterium, with a potential to reduce the failures in the Tb drug discovery. We propose an integrated approach of systems and structural biology for identifying targets that address the high attrition rate issue in lead identification and drug development We expect that this system level analysis will be applicable for identification of drug
Identification of potential drug targets based on a computational biology algorithm for venous thromboembolism.

PubMed

Xie, Ruiqiang; Li, Lei; Chen, Lina; Li, Wan; Chen, Binbin; Jiang, Jing; Huang, Hao; Li, Yiran; He, Yuehan; Lv, Junjie; He, Weiming

2017-02-01

Venous thromboembolism (VTE) is a common, fatal and frequently recurrent disease. Changes in the activity of different coagulation factors serve as a pathophysiological basis for the recurrent risk of VTE. Systems biology approaches provide a better understanding of the pathological mechanisms responsible for recurrent VTE. In this study, a novel computational method was presented to identify the recurrent risk modules (RRMs) based on the integration of expression profiles and human signaling network, which hold promise for achieving new and deeper insights into the mechanisms responsible for VTE. The results revealed that the RRMs had good classification performance to discriminate patients with recurrent VTE. The functional annotation analysis demonstrated that the RRMs played a crucial role in the pathogenesis of VTE. Furthermore, a variety of approved drug targets in the RRM M5 were related to VTE. Thus, the M5 may be applied to select potential drug targets for combination therapy and the extended treatment of VTE.
Predicting Drug-Target Interactions for New Drug Compounds Using a Weighted Nearest Neighbor Profile.

PubMed

van Laarhoven, Twan; Marchiori, Elena

2013-01-01

In silico discovery of interactions between drug compounds and target proteins is of core importance for improving the efficiency of the laborious and costly experimental determination of drug-target interaction. Drug-target interaction data are available for many classes of pharmaceutically useful target proteins including enzymes, ion channels, GPCRs and nuclear receptors. However, current drug-target interaction databases contain a small number of drug-target pairs which are experimentally validated interactions. In particular, for some drug compounds (or targets) there is no available interaction. This motivates the need for developing methods that predict interacting pairs with high accuracy also for these 'new' drug compounds (or targets). We show that a simple weighted nearest neighbor procedure is highly effective for this task. We integrate this procedure into a recent machine learning method for drug-target interaction we developed in previous work. Results of experiments indicate that the resulting method predicts true interactions with high accuracy also for new drug compounds and achieves results comparable or better than those of recent state-of-the-art algorithms. Software is publicly available at http://cs.ru.nl/~tvanlaarhoven/drugtarget2013/.
Genomes2Drugs: Identifies Target Proteins and Lead Drugs from Proteome Data

PubMed Central

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

2009-01-01

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

PubMed

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

2015-03-01

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

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

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

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

DOE PAGES

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

2014-12-19

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

PubMed

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

2018-02-21

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

PubMed Central

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

2013-01-01

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

PubMed

Durán, Claudio; Daminelli, Simone; Thomas, Josephine M; Haupt, V Joachim; Schroeder, Michael; Cannistraci, Carlo Vittorio

2017-04-26

The bipartite network representation of the drug-target interactions (DTIs) in a biosystem enhances understanding of the drugs' multifaceted action modes, suggests therapeutic switching for approved drugs and unveils possible side effects. As experimental testing of DTIs is costly and time-consuming, computational predictors are of great aid. Here, for the first time, state-of-the-art DTI supervised predictors custom-made in network biology were compared-using standard and innovative validation frameworks-with unsupervised pure topological-based models designed for general-purpose link prediction in bipartite networks. Surprisingly, our results show that the bipartite topology alone, if adequately exploited by means of the recently proposed local-community-paradigm (LCP) theory-initially detected in brain-network topological self-organization and afterwards generalized to any complex network-is able to suggest highly reliable predictions, with comparable performance with the state-of-the-art-supervised methods that exploit additional (non-topological, for instance biochemical) DTI knowledge. Furthermore, a detailed analysis of the novel predictions revealed that each class of methods prioritizes distinct true interactions; hence, combining methodologies based on diverse principles represents a promising strategy to improve drug-target discovery. To conclude, this study promotes the power of bio-inspired computing, demonstrating that simple unsupervised rules inspired by principles of topological self-organization and adaptiveness arising during learning in living intelligent systems (like the brain) can efficiently equal perform complicated algorithms based on advanced, supervised and knowledge-based engineering. © The Author 2017. Published by Oxford University Press.
Designing multi-targeted agents: An emerging anticancer drug discovery paradigm.

PubMed

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

2017-08-18

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

Drugs and Targets in Fibrosis

PubMed Central

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

2017-01-01

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

PubMed

Upadhyaya, Laxmi; Singh, Jay; Agarwal, Vishnu; Tewari, Ravi Prakash

2014-07-28

Over the last decade carboxymethyl chitosan (CMCS) has emerged as a promising biopolymer for the development of new drug delivery systems and improved scaffolds along with other tissue engineering devices for regenerative medicine that is currently one of the most rapidly growing fields in the life sciences. CMCS is amphiprotic ether, derived from chitosan, exhibiting enhanced aqueous solubility, excellent biocompatibility, controllable biodegradability, osteogenesis ability and numerous other outstanding physicochemical and biological properties. More strikingly, it can load hydrophobic drugs and displays strong bioactivity which highlight its suitability and extensive usage for preparing different drug delivery and tissue engineering formulations respectively. This review provides a comprehensive introduction to various types of CMCS based formulations for delivery of therapeutic agents and tissue regeneration and further describes their preparation procedures and applications in different tissues/organs. Detailed information of CMCS based nano/micro systems for targeted delivery of drugs with emphasis on cancer specific and organ specific drug delivery have been described. Further, we have discussed various CMCS based tissue engineering biomaterials along with their preparation procedures and applications in different tissues/organs. The article then, gives a brief account of therapy combining drug delivery and tissue engineering. Finally, identification of major challenges and opportunities for current and ongoing application of CMCS based systems in the field are summarised. Copyright © 2014 Elsevier B.V. All rights reserved.
Mesoporous silica nanoparticle-based intelligent drug delivery system for bienzyme-responsive tumour targeting and controlled release.

PubMed

Zhang, Yang; Xu, Juan

2018-01-01

This paper proposes a novel type of multifunctional envelope-type mesoporous silica nanoparticle (MSN) to achieve cancer cell targeting and drug-controlled release. In this system, MSNs were first modified by active targeting moiety hyaluronic acid (HA) for breast cancer cell targeting and hyaluronidases (Hyal)-induced intracellular drug release. Then gelatin, a proteinaceous biopolymer, was grafted onto the MSNs to form a capping layer via glutaraldehyde-mediated cross-linking. To shield against unspecific uptake of cells and prolong circulation time, the nanoparticles were further decorated with poly(ethylene glycol) polymers (PEG) to obtain MSN@HA-gelatin-PEG (MHGP). Doxorubicin (DOX), as a model drug, was loaded into PEMSN to assess the breast cancer cell targeting and drug release behaviours. In vitro study revealed that PEG chains protect the targeting ligand and shield against normal cells. After reaching the breast cancer cells, MMP-2 overpressed by cells hydrolyses gelatin layer to deshield PEG and switch on the function of HA. As a result, DOX-loaded MHGP was selectively trapped by cancer cells through HA receptor-mediated endocytosis and subsequently release DOX due to Hyal-catalysed degradation of HA. This system presents successful bienzyme-responsive targeting drug delivery in an optimal fashion and provides potential applications for targeted cancer therapy.
Genetically Validated Drug Targets in Leishmania: Current Knowledge and Future Prospects.

PubMed

Jones, Nathaniel G; Catta-Preta, Carolina M C; Lima, Ana Paula C A; Mottram, Jeremy C

2018-04-13

There has been a very limited number of high-throughput screening campaigns carried out with Leishmania drug targets. In part, this is due to the small number of suitable target genes that have been shown by genetic or chemical methods to be essential for the parasite. In this perspective, we discuss the state of genetic target validation in the field of Leishmania research and review the 200 Leishmania genes and 36 Trypanosoma cruzi genes for which gene deletion attempts have been made since the first published case in 1990. We define a quality score for the different genetic deletion techniques that can be used to identify potential drug targets. We also discuss how the advances in genome-scale gene disruption techniques have been used to assist target-based and phenotypic-based drug development in other parasitic protozoa and why Leishmania has lacked a similar approach so far. The prospects for this scale of work are considered in the context of the application of CRISPR/Cas9 gene editing as a useful tool in Leishmania.
Target-Independent Prediction of Drug Synergies Using Only Drug Lipophilicity

PubMed Central

2015-01-01

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

PubMed Central

2015-01-01

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

PubMed

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

2015-01-01

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

PubMed Central

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

2012-01-01

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

PubMed

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

2017-05-31

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

PubMed Central

Jiang, Jinjian; Wang, Nian; Zhang, Jun

2017-01-01

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

PubMed

Maeda, Hiroshi; Fang, Jun; Ulbrich, Karel; Etrych, Tomáš; Nakamura, Hideaki

2016-05-01

The enhanced permeability and retention (EPR) effect, a tumor-targeting principle of nanomedicine, serves as a standard for tumor-targeted anticancer drug design. There are 3 key issues in ideal EPR-based antitumor drug design: i) stability in blood circulation; ii) tumor-selective accumulation (EPR effect) and efficient release of the active anticancer moiety in tumor tissues; and iii) the active uptake of the active drug into tumor cells. Using these principles, we developed N-(2- hydroxypropyl)methacrylamide (HPMA) copolymer-conjugated pirarubicin (P-THP), which uses hydrazone bond linkage; it was shown to exhibit prolonged circulation time, thereby resulting in good tumor-selective accumulation. More importantly, the hydrazone bond ensured selective and rapid release of the active drug, pirarubicin (THP), in acidic tumor environments. Further, compared to other anthracycline anticancer drugs (eg, doxorubicin), THP demonstrated more rapid intracellular uptake. Consequently, P-THP showed remarkable antitumor effect with minimal side effects. In a clinical pilot study of a stage IV prostate cancer patient with multiple metastases in the lung and bone, P-THP (50-75 mg administered once every 2-3 weeks) was shown to clear the metastatic nodules in the lung almost completely after 3 treatments where 50-70 mg THP equivalent each was administerd per 70 kg body wt, and bone metastasis disappeared after 6 months. There was no recurrence after 2 years. The patient also retained an excellent quality of life during the treatment without any apparent side effects. Thus, we propose the clinical development of P-THP as an EPR-based tumor-targeted anticancer drug.
Computational selection of antibody-drug conjugate targets for breast cancer

PubMed Central

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

2016-01-01

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

PubMed

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

PubMed

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

2017-08-10

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

NASA Astrophysics Data System (ADS)

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

2002-03-01

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

PubMed

Wasko, Michael J; Pellegrene, Kendy A; Madura, Jeffry D; Surratt, Christopher K

2015-01-01

Hundreds of millions of U.S. dollars are invested in the research and development of a single drug. Lead compound development is an area ripe for new design strategies. Therapeutic lead candidates have been traditionally found using high-throughput in vitro pharmacological screening, a costly method for assaying thousands of compounds. This approach has recently been augmented by virtual screening (VS), which employs computer models of the target protein to narrow the search for possible leads. A variant of VS is fragment-based drug design (FBDD), an emerging in silico lead discovery method that introduces low-molecular weight fragments, rather than intact compounds, into the binding pocket of the receptor model. These fragments serve as starting points for "growing" the lead candidate. Current efforts in virtual FBDD within central nervous system (CNS) targets are reviewed, as is a recent rule-based optimization strategy in which new molecules are generated within a 3D receptor-binding pocket using the fragment as a scaffold. This process not only places special emphasis on creating synthesizable molecules but also exposes computational questions worth addressing. Fragment-based methods provide a viable, relatively low-cost alternative for therapeutic lead discovery and optimization that can be applied to CNS targets to augment current design strategies.
A Role for Fragment-Based Drug Design in Developing Novel Lead Compounds for Central Nervous System Targets

PubMed Central

Wasko, Michael J.; Pellegrene, Kendy A.; Madura, Jeffry D.; Surratt, Christopher K.

2015-01-01

Hundreds of millions of U.S. dollars are invested in the research and development of a single drug. Lead compound development is an area ripe for new design strategies. Therapeutic lead candidates have been traditionally found using high-throughput in vitro pharmacological screening, a costly method for assaying thousands of compounds. This approach has recently been augmented by virtual screening (VS), which employs computer models of the target protein to narrow the search for possible leads. A variant of VS is fragment-based drug design (FBDD), an emerging in silico lead discovery method that introduces low-molecular weight fragments, rather than intact compounds, into the binding pocket of the receptor model. These fragments serve as starting points for “growing” the lead candidate. Current efforts in virtual FBDD within central nervous system (CNS) targets are reviewed, as is a recent rule-based optimization strategy in which new molecules are generated within a 3D receptor-binding pocket using the fragment as a scaffold. This process not only places special emphasis on creating synthesizable molecules but also exposes computational questions worth addressing. Fragment-based methods provide a viable, relatively low-cost alternative for therapeutic lead discovery and optimization that can be applied to CNS targets to augment current design strategies. PMID:26441817
Development of a macrophage-targeting and phagocytosis-inducing bio-nanocapsule-based nanocarrier for drug delivery.

PubMed

Li, Hao; Tatematsu, Kenji; Somiya, Masaharu; Iijima, Masumi; Kuroda, Shun'ichi

2018-06-01

Macrophage hyperfunction or dysfunction is tightly associated with various diseases, such as osteoporosis, inflammatory disorder, and cancers. However, nearly all conventional drug delivery system (DDS) nanocarriers utilize endocytosis for entering target cells; thus, the development of macrophage-targeting and phagocytosis-inducing DDS nanocarriers for treating these diseases is required. In this study, we developed a hepatitis B virus (HBV) envelope L particle (i.e., bio-nanocapsule (BNC)) outwardly displaying a tandem form of protein G-derived IgG Fc-binding domain and protein L-derived IgG Fab-binding domain (GL-BNC). When conjugated with the macrophage-targeting ligand, mouse IgG2a (mIgG2a), the GL-BNC itself, and the liposome-fused GL-BNC (i.e., GL-virosome) spontaneously initiated aggregation by bridging between the Fc-binding domain and Fab-binding domain with mIgG2a. The aggregates were efficiently taken up by macrophages, whereas this was inhibited by latrunculin B, a phagocytosis-specific inhibitor. The mIgG2a-GL-virosome containing doxorubicin exhibited higher cytotoxicity toward macrophages than conventional liposomes and other BNC-based virosomes. Thus, GL-BNCs and GL-virosomes may constitute promising macrophage-targeting and phagocytosis-inducing DDS nanocarriers. We have developed a novel macrophage-targeting and phagocytosis-inducing bio-nanocapsule (BNC)-based nanocarrier named GL-BNC, which comprises a hepatitis B virus envelope L particle outwardly displaying protein G-derived IgG Fc- and protein L-derived IgG Fab-binding domains in tandem. The GL-BNC alone or liposome-fused form (GL-virosomes) could spontaneously aggregate when conjugated with macrophage-targeting IgGs, inducing phagocytosis by the interaction between IgG Fc of aggregates and FcγR on phagocytes. Thereby these aggregates were efficiently taken up by macrophages. GL-virosomes containing doxorubicin exhibited higher cytotoxicity towards macrophages than ZZ-virosomes and
A Strategy Based on Protein-Protein Interface Motifs May Help in Identifying Drug Off-Targets

PubMed Central

Engin, H. Billur; Keskin, Ozlem; Nussinov, Ruth; Gursoy, Attila

2014-01-01

Networks are increasingly used to study the impact of drugs at the systems level. From the algorithmic standpoint, a drug can ‘attack’ nodes or edges of a protein-protein interaction network. In this work, we propose a new network strategy, “The Interface Attack”, based on protein-protein interfaces. Similar interface architectures can occur between unrelated proteins. Consequently, in principle, a drug that binds to one has a certain probability of binding others. The interface attack strategy simultaneously removes from the network all interactions that consist of similar interface motifs. This strategy is inspired by network pharmacology and allows inferring potential off-targets. We introduce a network model which we call “Protein Interface and Interaction Network (P2IN)”, which is the integration of protein-protein interface structures and protein interaction networks. This interface-based network organization clarifies which protein pairs have structurally similar interfaces, and which proteins may compete to bind the same surface region. We built the P2IN of p53 signaling network and performed network robustness analysis. We show that (1) ‘hitting’ frequent interfaces (a set of edges distributed around the network) might be as destructive as eleminating high degree proteins (hub nodes); (2) frequent interfaces are not always topologically critical elements in the network; and (3) interface attack may reveal functional changes in the system better than attack of single proteins. In the off-target detection case study, we found that drugs blocking the interface between CDK6 and CDKN2D may also affect the interaction between CDK4 and CDKN2D. PMID:22817115

Drug-therapy networks and the prediction of novel drug targets

PubMed Central

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

2008-01-01

A recent study in BMC Pharmacology presents a network of drugs and the therapies in which they are used. Network approaches open new ways of predicting novel drug targets and overcoming the cellular robustness that can prevent drugs from working. PMID:18710588
Progress and Challenges in Developing Aptamer-Functionalized Targeted Drug Delivery Systems

PubMed Central

Jiang, Feng; Liu, Biao; Lu, Jun; Li, Fangfei; Li, Defang; Liang, Chao; Dang, Lei; Liu, Jin; He, Bing; Atik Badshah, Shaikh; Lu, Cheng; He, Xiaojuan; Guo, Baosheng; Zhang, Xiao-Bing; Tan, Weihong; Lu, Aiping; Zhang, Ge

2015-01-01

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. PMID:26473828
Progress and Challenges in Developing Aptamer-Functionalized Targeted Drug Delivery Systems.

PubMed

Jiang, Feng; Liu, Biao; Lu, Jun; Li, Fangfei; Li, Defang; Liang, Chao; Dang, Lei; Liu, Jin; He, Bing; Badshah, Shaikh Atik; Lu, Cheng; He, Xiaojuan; Guo, Baosheng; Zhang, Xiao-Bing; Tan, Weihong; Lu, Aiping; Zhang, Ge

2015-10-09

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.
Targeting Antibacterial Agents by Using Drug-Carrying Filamentous Bacteriophages

PubMed Central

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

2006-01-01

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

PubMed

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

2017-01-01

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

PubMed Central

Kesharwani, Prashant; Iyer, Arun K.

2015-01-01

Advances in the application of nanotechnology in medicine have given rise to multifunctional smart nanocarriers that can be engineered with tunable physicochemical characteristics to deliver one or more therapeutic agent(s) safely and selectively to cancer cells, including intracellular organelle-specific targeting. Dendrimers having properties resembling biomolecules, with well-defined 3D nanopolymeric architectures, are emerging as a highly attractive class of drug and gene delivery vector. The presence of numerous peripheral functional groups on hyperbranched dendrimers affords efficient conjugation of targeting ligands and biomarkers that can recognize and bind to receptors overexpressed on cancer cells for tumor-cell-specific delivery. The present review compiles the recent advances in dendrimer-mediated drug and gene delivery to tumors by passive and active targeting principles with illustrative examples. PMID:25555748
Peptide drugs to target G protein-coupled receptors.

PubMed

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

2010-09-01

Major indications for use of peptide-based therapeutics include endocrine functions (especially diabetes mellitus and obesity), infectious diseases, and cancer. Whereas some peptide pharmaceuticals are drugs, acting as agonists or antagonists to directly treat cancer, others (including peptide diagnostics and tumour-targeting pharmaceuticals) use peptides to 'shuttle' a chemotherapeutic agent or a tracer to the tumour and allow sensitive imaging or targeted therapy. Significant progress has been made in the last few years to overcome disadvantages in peptide design such as short half-life, fast proteolytic cleavage, and low oral bioavailability. These advances include peptide PEGylation, lipidisation or multimerisation; the introduction of peptidomimetic elements into the sequences; and innovative uptake strategies such as liposomal, capsule or subcutaneous formulations. This review focuses on peptides targeting G protein-coupled receptors that are promising drug candidates or that have recently entered the pharmaceutical market. Copyright 2010 Elsevier Ltd. All rights reserved.
Computational modeling-based discovery of novel classes of anti-inflammatory drugs that target lanthionine synthetase C-like protein 2.

PubMed

Lu, Pinyi; Hontecillas, Raquel; Horne, William T; Carbo, Adria; Viladomiu, Monica; Pedragosa, Mireia; Bevan, David R; Lewis, Stephanie N; Bassaganya-Riera, Josep

2012-01-01

Lanthionine synthetase component C-like protein 2 (LANCL2) is a member of the eukaryotic lanthionine synthetase component C-Like protein family involved in signal transduction and insulin sensitization. Recently, LANCL2 is a target for the binding and signaling of abscisic acid (ABA), a plant hormone with anti-diabetic and anti-inflammatory effects. The goal of this study was to determine the role of LANCL2 as a potential therapeutic target for developing novel drugs and nutraceuticals against inflammatory diseases. Previously, we performed homology modeling to construct a three-dimensional structure of LANCL2 using the crystal structure of lanthionine synthetase component C-like protein 1 (LANCL1) as a template. Using this model, structure-based virtual screening was performed using compounds from NCI (National Cancer Institute) Diversity Set II, ChemBridge, ZINC natural products, and FDA-approved drugs databases. Several potential ligands were identified using molecular docking. In order to validate the anti-inflammatory efficacy of the top ranked compound (NSC61610) in the NCI Diversity Set II, a series of in vitro and pre-clinical efficacy studies were performed using a mouse model of dextran sodium sulfate (DSS)-induced colitis. Our findings showed that the lead compound, NSC61610, activated peroxisome proliferator-activated receptor gamma in a LANCL2- and adenylate cyclase/cAMP dependent manner in vitro and ameliorated experimental colitis by down-modulating colonic inflammatory gene expression and favoring regulatory T cell responses. LANCL2 is a novel therapeutic target for inflammatory diseases. High-throughput, structure-based virtual screening is an effective computational-based drug design method for discovering anti-inflammatory LANCL2-based drug candidates.
Computational Modeling-Based Discovery of Novel Classes of Anti-Inflammatory Drugs That Target Lanthionine Synthetase C-Like Protein 2

PubMed Central

Lu, Pinyi; Hontecillas, Raquel; Horne, William T.; Carbo, Adria; Viladomiu, Monica; Pedragosa, Mireia; Bevan, David R.; Lewis, Stephanie N.; Bassaganya-Riera, Josep

2012-01-01

Background Lanthionine synthetase component C-like protein 2 (LANCL2) is a member of the eukaryotic lanthionine synthetase component C-Like protein family involved in signal transduction and insulin sensitization. Recently, LANCL2 is a target for the binding and signaling of abscisic acid (ABA), a plant hormone with anti-diabetic and anti-inflammatory effects. Methodology/Principal Findings The goal of this study was to determine the role of LANCL2 as a potential therapeutic target for developing novel drugs and nutraceuticals against inflammatory diseases. Previously, we performed homology modeling to construct a three-dimensional structure of LANCL2 using the crystal structure of lanthionine synthetase component C-like protein 1 (LANCL1) as a template. Using this model, structure-based virtual screening was performed using compounds from NCI (National Cancer Institute) Diversity Set II, ChemBridge, ZINC natural products, and FDA-approved drugs databases. Several potential ligands were identified using molecular docking. In order to validate the anti-inflammatory efficacy of the top ranked compound (NSC61610) in the NCI Diversity Set II, a series of in vitro and pre-clinical efficacy studies were performed using a mouse model of dextran sodium sulfate (DSS)-induced colitis. Our findings showed that the lead compound, NSC61610, activated peroxisome proliferator-activated receptor gamma in a LANCL2- and adenylate cyclase/cAMP dependent manner in vitro and ameliorated experimental colitis by down-modulating colonic inflammatory gene expression and favoring regulatory T cell responses. Conclusions/Significance LANCL2 is a novel therapeutic target for inflammatory diseases. High-throughput, structure-based virtual screening is an effective computational-based drug design method for discovering anti-inflammatory LANCL2-based drug candidates. PMID:22509338
Dendritic polymer-based nanodevices for targeted drug delivery applications

NASA Astrophysics Data System (ADS)

Kannan, R. M.; Kolhe, Parag; Gurdag, Sezen; Khandare, Jayant; Lieh-Lai, Mary

2004-03-01

Dendrimers and hyperbranched polymers are unimolecular micellar nanostructures, characterized by globular shape ( ˜ 20 nm) and large density of functional groups at periphery. The tailorable end groups make them ideal for conjugation with drugs, ligands, and imagining agents, making them an attractive molecular nanodevices for drug delivery. Compared to linear polymers and nanoparticles, these nanodevices enter cells rapidly, carrying drugs and delivering them inside cells. Performance of nanodevices prepared for asthma and cancer drug delivery will be discussed. Our conjugation procedure produced very high drug payloads. Dendritic polymer-drug conjugates were very effective in transporting methotrexate (a chemotherapy drug) into both sensitive (CCRF-CEM cell line) and resistant cell line (CEM-MTX). The conjugate nanodevice was 3 times more effective than free drug in the sensitive line, and 9 times more effective in the resistant cell line (based on IC50). The physics of cell entry and drug release from these nanodevices are being investigated. The conjugates appear to enter cells through endocytosis, with the rate of entry dependent on end-group, molecular weight, the pH of the medium, and the cancerous nature of the cells.
Formulation of Biologically-Inspired Silk-Based Drug Carriers for Pulmonary Delivery Targeted for Lung Cancer

PubMed Central

Kim, Sally Yunsun; Naskar, Deboki; Kundu, Subhas C.; Bishop, David P.; Doble, Philip A.; Boddy, Alan V.; Chan, Hak-Kim; Wall, Ivan B.; Chrzanowski, Wojciech

2015-01-01

The benefits of using silk fibroin, a major protein in silk, are widely established in many biomedical applications including tissue regeneration, bioactive coating and in vitro tissue models. The properties of silk such as biocompatibility and controlled degradation are utilized in this study to formulate for the first time as carriers for pulmonary drug delivery. Silk fibroin particles are spray dried or spray-freeze-dried to enable the delivery to the airways via dry powder inhalers. The addition of excipients such as mannitol is optimized for both the stabilization of protein during the spray-freezing process as well as for efficient dispersion using an in vitro aerosolisation impactor. Cisplatin is incorporated into the silk-based formulations with or without cross-linking, which show different release profiles. The particles show high aerosolisation performance through the measurement of in vitro lung deposition, which is at the level of commercially available dry powder inhalers. The silk-based particles are shown to be cytocompatible with A549 human lung epithelial cell line. The cytotoxicity of cisplatin is demonstrated to be enhanced when delivered using the cross-linked silk-based particles. These novel inhalable silk-based drug carriers have the potential to be used as anti-cancer drug delivery systems targeted for the lungs. PMID:26234773
Multifunctional polymer-capped mesoporous silica nanoparticles for pH-responsive targeted drug delivery.

PubMed

Niedermayer, Stefan; Weiss, Veronika; Herrmann, Annika; Schmidt, Alexandra; Datz, Stefan; Müller, Katharina; Wagner, Ernst; Bein, Thomas; Bräuchle, Christoph

2015-05-07

A highly stable modular platform, based on the sequential covalent attachment of different functionalities to the surface of core-shell mesoporous silica nanoparticles (MSNs) for targeted drug delivery is presented. A reversible pH-responsive cap system based on covalently attached poly(2-vinylpyridine) (PVP) was developed as drug release mechanism. Our platform offers (i) tuneable interactions and release kinetics with the cargo drug in the mesopores based on chemically orthogonal core-shell design, (ii) an extremely robust and reversible closure and release mechanism based on endosomal acidification of the covalently attached PVP polymer block, (iii) high colloidal stability due to a covalently coupled PEG shell, and (iv) the ability to covalently attach a wide variety of dyes, targeting ligands and other functionalities at the outer periphery of the PEG shell. The functionality of the system was demonstrated in several cell studies, showing pH-triggered release in the endosome, light-triggered endosomal escape with an on-board photosensitizer, and efficient folic acid-based cell targeting.
Bio-nanocapsules displaying various immunoglobulins as an active targeting-based drug delivery system.

PubMed

Tatematsu, Kenji; Iijima, Masumi; Yoshimoto, Nobuo; Nakai, Tadashi; Okajima, Toshihide; Kuroda, Shun'ichi

2016-04-15

The bio-nanocapsule (BNC) is an approximately 30-nm particle comprising the hepatitis B virus (HBV) envelope L protein and a lipid bilayer. The L protein harbors the HBV-derived infection machinery; therefore, BNC can encapsulate payloads such as drugs, nucleic acids, and proteins and deliver them into human hepatocytes specifically in vitro and in vivo. To diversify the possible functions of BNC, we generated ZZ-BNC by replacing the domain indispensable for the human hepatotrophic property of BNC (N-terminal region of L protein) with the tandem form of the IgG Fc-binding Z domain of Staphylococcus aureus protein A. Thus, the ZZ-BNC is an active targeting-based drug delivery system (DDS) nanocarrier that depends on the specificity of the IgGs displayed. However, the Z domain limits the animal species and subtypes of IgGs that can be displayed on ZZ-BNC. In this study, we introduced into BNC an Ig κ light chain-binding B1 domain of Finegoldia magna protein L (protein-L B1 domain) and an Ig Fc-binding C2 domain of Streptococcus species protein G (protein-G C2 domain) to produce LG-BNC. The LL-BNC was constructed in a similar way using a tandem form of the protein-L B1 domain. Both LG-BNC and LL-BNC could display rat IgGs, mouse IgG1, human IgG3, and human IgM, all of which not binding to ZZ-BNC, and accumulate in target cells in an antibody specificity-dependent manner. Thus, these BNCs could display a broad spectrum of Igs, significantly improving the prospects for BNCs as active targeting-based DDS nanocarriers. We previously reported that ZZ-BNC, bio-nanocapsule deploying the IgG-binding Z domain of protein A, could display cell-specific antibody in an oriented immobilization manner, and act as an active targeting-based DDS nanocarrier. Since the Z domain can only bind to limited types of Igs, we generated BNCs deploying other Ig-binding domains: LL-BNC harboring the tandem form of Ig-binding domain of protein L, and LG-BNC harboring the Ig binding domains of
Emerging principles in protease-based drug discovery

PubMed Central

Drag, Marcin; Salvesen, Guy S.

2010-01-01

Proteases have an important role in many signalling pathways, and represent potential drug targets for diseases ranging from cardiovascular disorders to cancer, as well as for combating many parasites and viruses. Although inhibitors of well-established protease targets such as angiotensin-converting enzyme and HIV protease have shown substantial therapeutic success, developing drugs for new protease targets has proved challenging in recent years. This in part could be due to issues such as the difficulty of achieving selectivity when targeting protease active sites. This Perspective discusses the general principles in protease-based drug discovery, highlighting the lessons learned and the emerging strategies, such as targeting allosteric sites, which could help harness the therapeutic potential of new protease targets. PMID:20811381
Understanding drug targets: no such thing as bad news.

PubMed

Roberts, Ruth A

2018-05-24

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

PubMed

Li, Nannan; Zhao, Qian; Shu, Chang; Ma, Xiaona; Li, Ruixin; Shen, Hongjun; Zhong, Wenying

2015-01-30

Oxidized single-wall carbon nanohorns (oxSWNHs) have shown great potential in drug delivery. The purpose of this study was to design an effective targeted drug delivery system (DDS) based on oxSWNHs, which could carry high dose of drug to tumor sites and improve the therapeutic efficacy with less adverse effects. OxSWNHs incorporated the anticancer drug vincristine (VCR) via physical adsorption, then wrapped DSPE-PEG-IGF-IR monoclonal antibody (mAb) through an amide liker to obtain the drug delivery system, VCR@oxSWNHs-PEG-mAb. The in vitro release behavior study indicated that the DDS had good sustained release and the cumulative release of VCR was 80% at 144h. Compared with free VCR, the tumor targeting drug delivery efficiently enhanced the cytotoxicity in cultured MCF-7 cells in vitro, and afforded higher antitumor efficacy without obvious toxic effects to normal organs in tumor mice in vivo. In addition, the targeted DDS could reduce the toxicity of VCR to the living mice. This study demonstrated that VCR@oxSWNHs-PEG-mAb might be promising for high treatment efficacy with minimal side effects in future cancer therapy. Copyright © 2014 Elsevier B.V. All rights reserved.
Delivery of drugs to intracellular organelles using drug delivery systems: Analysis of research trends and targeting efficiencies.

PubMed

Maity, Amit Ranjan; Stepensky, David

2015-12-30

Targeting of drug delivery systems (DDSs) to specific intracellular organelles (i.e., subcellular targeting) has been investigated in numerous publications, but targeting efficiency of these systems is seldom reported. We searched scientific publications in the subcellular DDS targeting field and analyzed targeting efficiency and major formulation parameters that affect it. We identified 77 scientific publications that matched the search criteria. In the majority of these studies nanoparticle-based DDSs were applied, while liposomes, quantum dots and conjugates were used less frequently. The nucleus was the most common intracellular target, followed by mitochondrion, endoplasmic reticulum and Golgi apparatus. In 65% of the publications, DDSs surface was decorated with specific targeting residues, but the efficiency of this surface decoration was not analyzed in predominant majority of the studies. Moreover, only 23% of the analyzed publications contained quantitative data on DDSs subcellular targeting efficiency, while the majority of publications reported qualitative results only. From the analysis of publications in the subcellular targeting field, it appears that insufficient efforts are devoted to quantitative analysis of the major formulation parameters and of the DDSs' intracellular fate. Based on these findings, we provide recommendations for future studies in the field of organelle-specific drug delivery and targeting. Copyright © 2015 Elsevier B.V. All rights reserved.
Quantitative and Systems Pharmacology. 1. In Silico Prediction of Drug-Target Interactions of Natural Products Enables New Targeted Cancer Therapy.

PubMed

Fang, Jiansong; Wu, Zengrui; Cai, Chuipu; Wang, Qi; Tang, Yun; Cheng, Feixiong

2017-11-27

Natural products with diverse chemical scaffolds have been recognized as an invaluable source of compounds in drug discovery and development. However, systematic identification of drug targets for natural products at the human proteome level via various experimental assays is highly expensive and time-consuming. In this study, we proposed a systems pharmacology infrastructure to predict new drug targets and anticancer indications of natural products. Specifically, we reconstructed a global drug-target network with 7,314 interactions connecting 751 targets and 2,388 natural products and built predictive network models via a balanced substructure-drug-target network-based inference approach. A high area under receiver operating characteristic curve of 0.96 was yielded for predicting new targets of natural products during cross-validation. The newly predicted targets of natural products (e.g., resveratrol, genistein, and kaempferol) with high scores were validated by various literature studies. We further built the statistical network models for identification of new anticancer indications of natural products through integration of both experimentally validated and computationally predicted drug-target interactions of natural products with known cancer proteins. We showed that the significantly predicted anticancer indications of multiple natural products (e.g., naringenin, disulfiram, and metformin) with new mechanism-of-action were validated by various published experimental evidence. In summary, this study offers powerful computational systems pharmacology approaches and tools for the development of novel targeted cancer therapies by exploiting the polypharmacology of natural products.
Breast Cancer-Targeted Nuclear Drug Delivery Overcoming Drug Resistance for Breast Cancer Chemotherapy

DTIC Science & Technology

2011-09-01

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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

PubMed Central

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

2011-01-01

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

PubMed

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

2011-01-01

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

PubMed

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

2018-06-18

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

PubMed

Edgar, Jun Yan Chan; Wang, Hui

2017-01-01

Conventional drug delivery systems contain numerous limitations such as limited targeting, low therapeutic indices, poor water solubility, and the induction of drug resistances. In order to overcome the drawbacks of conventional pathway of drug delivery, nanoparticle delivery systems are therefore designed and used as the drug carriers. Nanoparticle based drug delivery systems have been rapidly growing and are being applied to various sections of biomedicine. Drug nanocarriers based on dendrimers, liposomes, self-assembling peptides, watersoluble polymers, and block copolymer micelles are the most extensively studied types of drug delivery systems and some of them are being used in clinical therapy. In particular for cancer therapy, antineoplastic drugs are taking advantage of nanoparticulate drug carriers to improve the cure efficacy. Nanoparticle based drug carriers are capable of improving the therapeutic effectiveness of the drugs by using active targeting for the site-specific delivery, passive targeting mechanisms such as enhanced permeability and retention (EPR), de novo synthesis and uptake of low density liposome in cancer cells or by being water-soluble to improve the suboptimal pharmacokinetics in limited water-soluble delivery methods. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Targeting bacterial central metabolism for drug development.

PubMed

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

2014-11-20

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

PubMed Central

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

2012-01-01

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

PubMed

Zhang, Wen; Chen, Yanlin; Li, Dingfang

2017-11-25

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

PubMed

Cao, Ran; Li, Wei; Sun, Han-Zi; Zhou, Yu; Huang, Niu

2013-07-01

Today, the understanding of the sequence and structure of biologically relevant targets is growing rapidly and researchers from many disciplines, physics and computational science in particular, are making significant contributions to modern biology and drug discovery. However, it remains challenging to rationally design small molecular ligands with desired biological characteristics based on the structural information of the drug targets, which demands more accurate calculation of ligand binding free-energy. With the rapid advances in computer power and extensive efforts in algorithm development, physics-based computational chemistry approaches have played more important roles in structure-based drug design. Here we reviewed the newly developed computational chemistry methods in structure-based drug design as well as the elegant applications, including binding-site druggability assessment, large scale virtual screening of chemical database, and lead compound optimization. Importantly, here we address the current bottlenecks and propose practical solutions.
Advances in nanotechnology-based carrier systems for targeted delivery of bioactive drug molecules with special emphasis on immunotherapy in drug resistant tuberculosis - a critical review.

PubMed

Singh, Jagdeep; Garg, Tarun; Rath, Goutam; Goyal, Amit K

2016-06-01

From the early sixteenth and seventeenth centuries to the present day of life, tuberculosis (TB) still is a global health threat with some new emergence of resistance. This type of emergence poses a vital challenge to control TB cases across the world. Mortality and morbidity rates are high due to this new face of TB. The newer nanotechnology-based drug-delivery approaches involving micro-metric and nano-metric carriers are much needed at this stage. These delivery systems would provide more advantages over conventional systems of treatment by producing enhanced therapeutic efficacy, uniform distribution of drug molecule to the target site, sustained and controlled release of drug molecules and lesser side effects. The main aim to develop these novel drug-delivery systems is to improve the patient compliance and reduce therapy time. This article reviews and elaborates the new concepts and drug-delivery approaches for the treatment of TB involving solid-lipid particulate drug-delivery systems (solid-lipid micro- and nanoparticles, nanostructured lipid carriers), vesicular drug-delivery systems (liposomes, niosomes and liposphere), emulsion-based drug-delivery systems (micro and nanoemulsion) and some other novel drug-delivery systems for the effective treatment of tuberculosis and role of immunomodulators as an adjuvant therapy for management of MDR-TB and XDR-TB.
Advances in nanotechnology-based carrier systems for targeted delivery of bioactive drug molecules with special emphasis on immunotherapy in drug resistant tuberculosis - a critical review.

PubMed

Singh, Jagdeep; Garg, Tarun; Rath, Goutam; Goyal, Amit K

2015-08-11

From the early sixteenth and seventeenth centuries to the present day of life, tuberculosis (TB) still is a global health threat with some new emergence of resistance. This type of emergence poses a vital challenge to control TB cases across the world. Mortality and morbidity rates are high due to this new face of TB. The newer nanotechnology-based drug-delivery approaches involving micro-metric and nano-metric carriers are much needed at this stage. These delivery systems would provide more advantages over conventional systems of treatment by producing enhanced therapeutic efficacy, uniform distribution of drug molecule to the target site, sustained and controlled release of drug molecules and lesser side effects. The main aim to develop these novel drug-delivery systems is to improve the patient compliance and reduce therapy time. This article reviews and elaborates the new concepts and drug-delivery approaches for the treatment of TB involving solid-lipid particulate drug-delivery systems (solid-lipid micro- and nanoparticles, nanostructured lipid carriers), vesicular drug-delivery systems (liposomes, niosomes and liposphere), emulsion-based drug-delivery systems (micro and nanoemulsion) and some other novel drug-delivery systems for the effective treatment of tuberculosis and role of immunomodulators as an adjuvant therapy for management of MDR-TB and XDR-TB.
Targeted drug delivery for cancer therapy: the other side of antibodies

PubMed Central

2012-01-01

Therapeutic monoclonal antibody (TMA) based therapies for cancer have advanced significantly over the past two decades both in their molecular sophistication and clinical efficacy. Initial development efforts focused mainly on humanizing the antibody protein to overcome problems of immunogenicity and on expanding of the target antigen repertoire. In parallel to naked TMAs, antibody-drug conjugates (ADCs) have been developed for targeted delivery of potent anti-cancer drugs with the aim of bypassing the morbidity common to conventional chemotherapy. This paper first presents a review of TMAs and ADCs approved for clinical use by the FDA and those in development, focusing on hematological malignancies. Despite advances in these areas, both TMAs and ADCs still carry limitations and we highlight the more important ones including cancer cell specificity, conjugation chemistry, tumor penetration, product heterogeneity and manufacturing issues. In view of the recognized importance of targeted drug delivery strategies for cancer therapy, we discuss the advantages of alternative drug carriers and where these should be applied, focusing on peptide-drug conjugates (PDCs), particularly those discovered through combinatorial peptide libraries. By defining the advantages and disadvantages of naked TMAs, ADCs and PDCs it should be possible to develop a more rational approach to the application of targeted drug delivery strategies in different situations and ultimately, to a broader basket of more effective therapies for cancer patients. PMID:23140144
Toxins and derivatives in molecular pharmaceutics: Drug delivery and targeted therapy.

PubMed

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.
HSA-based multi-target combination therapy: regulating drugs' release from HSA and overcoming single drug resistance in a breast cancer model.

PubMed

Gou, Yi; Zhang, Zhenlei; Li, Dongyang; Zhao, Lei; Cai, Meiling; Sun, Zhewen; Li, Yongping; Zhang, Yao; Khan, Hamid; Sun, Hongbing; Wang, Tao; Liang, Hong; Yang, Feng

2018-11-01

Multi-drug delivery systems, which may be promising solution to overcome obstacles, have limited the clinical success of multi-drug combination therapies to treat cancer. To this end, we used three different anticancer agents, Cu(BpT)Br, NAMI-A, and doxorubicin (DOX), to build human serum albumin (HSA)-based multi-drug delivery systems in a breast cancer model to investigate the therapeutic efficacy of overcoming single drug (DOX) resistance to cancer cells in vivo, and to regulate the drugs' release from HSA. The HSA complex structure revealed that NAMI-A and Cu(BpT)Br bind to the IB and IIA sub-domain of HSA by N-donor residue replacing a leaving group and coordinating to their metal centers, respectively. The MALDI-TOF mass spectra demonstrated that one DOX molecule is conjugated with lysine of HSA by a pH-sensitive linker. Furthermore, the release behavior of three agents form HSA can be regulated at different pH levels. Importantly, in vivo results revealed that the HSA-NAMI-A-Cu(BpT)Br-DOX complex not only increases the targeting ability compared with a combination of the three agents (the NAMI-A/Cu(BpT)Br/DOX mixture), but it also overcomes DOX resistance to drug-resistant breast cancer cell lines.
A Computational Approach to Finding Novel Targets for Existing Drugs

PubMed Central

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

2011-01-01

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

PubMed

Cui, Wei; Li, Junbai; Decher, Gero

2016-02-10

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

Cancer.gov

An experimental drug called metarrestin appears to selectively target tumors that have spread to other parts of the body. As this Cancer Currents blog post reports, the drug shrank metastatic tumors and extended survival in in mouse models of pancreatic cancer.
Discovery of peptide drug carrier candidates for targeted multi-drug delivery into prostate cancer cells.

PubMed

Bashari, O; Redko, B; Cohen, A; Luboshits, G; Gellerman, G; Firer, M A

2017-11-01

Metastatic castration-resistant prostate cancer (mCRPC) remains essentially incurable. Targeted Drug Delivery (TDD) systems may overcome the limitations of current mCRPC therapies. We describe the use of strict criteria to isolate novel prostate cancer cell targeting peptides that specifically deliver drugs into target cells. Phage from a libraries displaying 7mer peptides were exposed to PC-3 cells and only internalized phage were recovered. The ability of these phage to internalize into other prostate cancer cells (LNCaP, DU-145) was validated. The displayed peptides of selected phage clones were synthesized and their specificity for target cells was validated in vitro and in vivo. One peptide (P12) which specifically targeted PC-3 tumors in vivo was incorporated into mono-drug (Chlorambucil, Combretastatin or Camptothecin) and dual-drug (Chlorambucil/Combretastatin or Chlorambucil/Camptothecin) PDCs and the cytotoxic efficacy of these conjugates for target cells was tested. Conjugation of P12 into dual-drug PDCs allowed discovery of new drug combinations with synergistic effects. The use of strict selection criteria can lead to discovery of novel peptides for use as drug carriers for TDD. PDCs represent an effective alternative to current modes of free drug chemotherapy for prostate cancer. Copyright © 2017. Published by Elsevier B.V.
Functional differentiation of cytotoxic cancer drugs and targeted cancer therapeutics.

PubMed

Winkler, Gian C; Barle, Ester Lovsin; Galati, Giuseppe; Kluwe, William M

2014-10-01

There is no nationally or internationally binding definition of the term "cytotoxic drug" although this term is used in a variety of regulations for pharmaceutical development and manufacturing of drugs as well as in regulations for protecting medical personnel from occupational exposure in pharmacy, hospital, and other healthcare settings. The term "cytotoxic drug" is frequently used as a synonym for any and all oncology or antineoplastic drugs. Pharmaceutical companies generate and receive requests for assessments of the potential hazards of drugs regularly - including cytotoxicity. This publication is intended to provide functional definitions that help to differentiate between generically-cytotoxic cancer drugs of significant risk to normal human tissues, and targeted cancer therapeutics that pose much lesser risks. Together with specific assessments, it provides comprehensible guidance on how to assess the relevant properties of cancer drugs, and how targeted therapeutics discriminate between cancer and normal cells. The position of several regulatory agencies in the long-term is clearly to regulate all drugs regardless of classification, according to scientific risk based data. Despite ongoing discussions on how to replace the term "cytotoxic drugs" in current regulations, it is expected that its use will continue for the near future. Copyright © 2014 Elsevier Inc. All rights reserved.
Antibody-drug conjugates: Promising and efficient tools for targeted cancer therapy.

PubMed

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

PubMed

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

2013-03-01

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

Calcium silicate-based drug delivery systems.

PubMed

Zhu, Ying-Jie; Guo, Xiao-Xuan; Sham, Tsun-Kong

2017-02-01

Compared with other inorganic materials such as silica, metal oxides, noble metals and carbon, calcium silicate-based materials, especially nanostructured calcium silicate materials, have high biocompatibility, bioactivity and biodegradability, high specific surface area, nanoporous/hollow structure, high drug-loading capacity, pH-responsive drug release behavior and desirable drug release properties, and thus they are promising for the application in drug delivery. Calcium silicate-based drug delivery systems have a long drug-release time, which can significantly prolong the therapeutic effect of drugs. Another advantage of calcium silicate-based drug delivery systems is their pH-responsive drug release property, which can act as an ideal platform for targeted drug delivery. Areas covered: In recent years, studies have been carried out on calcium silicate-based drug delivery systems, and important results and insights have been documented. This article is not intended to offer a comprehensive review on the research on calcium silicate-based drug delivery systems, but presents some examples reported in the literature, and includes new insights obtained by tracking the interactions between drug molecules and calcium silicate carriers on the molecular level using the synchrotron-based X-ray spectroscopy. Expert opinion: Finally, our opinions on calcium silicate-based drug delivery systems are provided, and several research directions for the future studies are proposed.
Advances in silica based nanoparticles for targeted cancer therapy.

PubMed

Yang, Yannan; Yu, Chengzhong

2016-02-01

Targeted delivery of anticancer drug specifically to tumor site without damaging normal tissues has been the dream of all scientists fighting against cancer for decades. Recent breakthrough on nanotechnology based medicines has provided a possible tool to solve this puzzle. Among diverse nanomaterials that are under development and extensive study, silica based nanoparticles with vast advantages have attracted great attention. In this review, we concentrate on the recent progress using silica based nanoparticles, particularly mesoporous silica nanoparticles (MSNs), for targeted drug delivery applications. First, we discuss the passive targeting capability of silica based nanoparticles in relation to their physiochemical properties. Then, we focus on the recent advances of active targeting strategies involving tumor cell targeting, vascular targeting, nuclear targeting and multistage targeting, followed by an introduction to magnetic field directed targeting approach. We conclude with our personal perspectives on the remaining challenges and the possible future directions. Chemotherapy has been one of the mainstays of cancer treatment. The advances in nanotechnology has allowed the development of novel carrier systems for the delivery of anticancer drugs. Mesoporous silica has shown great promise in this respect. In this review article, the authors provided a comprehensive overview of the use of this nanoparticle in both passive, as well as active targeting in the field of oncology. The advantages of this particle were further discussed. Copyright © 2015 Elsevier Inc. All rights reserved.
A metabolic network approach for the identification and prioritization of antimicrobial drug targets

PubMed Central

Chavali, Arvind K.; D’Auria, Kevin M.; Hewlett, Erik L.; Pearson, Richard D.; Papin, Jason A.

2012-01-01

For many infectious diseases, novel treatment options are needed to address problems with cost, toxicity and resistance to current drugs. Systems biology tools can be used to gain valuable insight into pathogenic processes and aid in expediting drug discovery. In the past decade, constraint-based modeling of genome-scale metabolic networks has become widely used. Focusing on pathogen metabolic networks, we review in silico strategies to identify effective drug targets, and we highlight recent successes as well as limitations associated with such computational analyses. We further discuss how accounting for the host environment and even targeting the host may offer new therapeutic options. These systems-level approaches are beginning to provide novel avenues for drug targeting against infectious agents. PMID:22300758
Placenta-specific1 (PLAC1) is a potential target for antibody-drug conjugate-based prostate cancer immunotherapy.

PubMed

Nejadmoghaddam, Mohammad-Reza; Zarnani, Amir-Hassan; Ghahremanzadeh, Ramin; Ghods, Roya; Mahmoudian, Jafar; Yousefi, Maryam; Nazari, Mahboobeh; Ghahremani, Mohammad Hossein; Abolhasani, Maryam; Anissian, Ali; Mahmoudi, Morteza; Dinarvand, Rassoul

2017-10-17

Our recent findings strongly support the idea of PLAC1 being as a potential immunotherapeutic target in prostate cancer (PCa). Here, we have generated and evaluated an anti-placenta-specific1 (PLAC1)-based antibody drug conjugate (ADC) for targeted immunotherapy of PCa. Prostate cancer cells express considerable levels of PLAC1. The Anti-PLAC1 clone, 2H12C12, showed high reactivity with recombinant PLAC1 and selectivity recognized PLAC1 in prostate cancer cells but not in LS180 cells, the negative control. PLAC1 binding induced rapid internalization of the antibody within a few minutes which reached to about 50% after 15 min and almost completed within an hour. After SN38 conjugation to antibody, a drug-antibody ratio (DAR) of about 5.5 was achieved without apparent negative effect on antibody affinity to cell surface antigen. The ADC retained intrinsic antibody activity and showed enhanced and selective cytotoxicity with an IC50 of 62 nM which was about 15-fold lower compared to free drug. Anti-PLAC1-ADC induced apoptosis in human primary prostate cancer cells and prostate cell lines. No apparent cytotoxic effect was observed in in vivo animal safety experiments. Our newly developed anti-PLAC1-based ADCs might pave the way for a reliable, efficient, and novel immunotherapeutic modality for patients with PCa.
Bacterial exopolysaccharide based magnetic nanoparticles: a versatile nanotool for cancer cell imaging, targeted drug delivery and synergistic effect of drug and hyperthermia mediated cancer therapy.

PubMed

Sivakumar, Balasubramanian; Aswathy, Ravindran Girija; Sreejith, Raveendran; Nagaoka, Yutaka; Iwai, Seiki; Suzuki, Masashi; Fukuda, Takahiro; Hasumura, Takashi; Yoshida, Yasuhiko; Maekawa, Toru; Sakthikumar, Dasappan Nair

2014-06-01

Microbial exopolysaccharides (EPSs) are highly heterogeneous polymers produced by fungi and bacteria that have garnered considerable attention and have remarkable potential in various fields, including biomedical research. The necessity of biocompatible materials to coat and stabilize nanoparticles is highly recommended for successful application of the same in biomedical regime. In our study we have coated magnetic nanoparticles (MNPs) with two bacterial EPS-mauran (MR) and gellan gum (GG). The biocompatibility of EPS coated MNPs was enhanced and we have made it multifunctional by attaching targeting moiety, folate and with encapsulation of a potent anticancerous drug, 5FU. We have conjugated an imaging moiety along with nanocomposite to study the effective uptake of nanoparticles. It was also observed that the dye labeled folate targeted nanoparticles could effectively enter into cancer cells and the fate of nanoparticles was tracked with Lysotracker. The biocompatibility of EPS coated MNPs and synergistic effect of magnetic hyperthermia and drug for enhanced antiproliferation of cancer cells was also evaluated. More than 80% of cancer cells was killed within a period of 60 min when magnetic hyperthermia (MHT) was applied along with drug loaded EPS coated MNPs, thus signifying the combined effect of drug loaded MNPs and MHT. Our results suggests that MR and GG coated MNPs exhibited excellent biocompatibility with low cell cytotoxicity, high therapeutic potential, and superparamagnetic behavior that can be employed as prospective candidates for bacterial EPS based targeted drug delivery, cancer cell imaging and for MHT for killing cancer cells within short period of time.
DrugPath: a database for academic investigators to match oncology molecular targets with drugs in development.

PubMed

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

2014-05-01

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

PubMed

Murray, Christopher W; Verdonk, Marcel L; Rees, David C

2012-05-01

Fragment-based drug discovery (FBDD) has become established in both industry and academia as an alternative approach to high-throughput screening for the generation of chemical leads for drug targets. In FBDD, specialised detection methods are used to identify small chemical compounds (fragments) that bind to the drug target, and structural biology is usually employed to establish their binding mode and to facilitate their optimisation. In this article, we present three recent and successful case histories in FBDD. We then re-examine the key concepts and challenges of FBDD with particular emphasis on recent literature and our own experience from a substantial number of FBDD applications. Our opinion is that careful application of FBDD is living up to its promise of delivering high quality leads with good physical properties and that in future many drug molecules will be derived from fragment-based approaches. Copyright © 2012 Elsevier Ltd. All rights reserved.
Drug targets for resistant malaria: Historic to future perspectives.

PubMed

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

2018-05-11

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

PubMed

Hu, Hai-Yu; Lim, Ngee-Han; Ding-Pfennigdorff, Danping; Saas, Joachim; Wendt, K Ulrich; Ritzeler, Olaf; Nagase, Hideaki; Plettenburg, Oliver; Schultz, Carsten; Nazare, Marc

2015-03-18

Targeted drug-delivery methods are crucial for effective treatment of degenerative joint diseases such as osteoarthritis (OA). Toward this goal, we developed a small multivalent structure as a model drug for the attenuation of cartilage degradation. The DOTAM (1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid amide)-based model structure is equipped with the cathepsin D protease inhibitor pepstatin A, a fluorophore, and peptide moieties targeting collagen II. In vivo injection of these soluble probes into the knee joints of mice resulted in 7-day-long local retention, while the drug carrier equipped with a scrambled peptide sequence was washed away within 6-8 h. The model drug conjugate successfully reduced the cathepsin D protease activity as measured by release of GAG peptide. Therefore, these conjugates represent a promising first drug conjugate for the targeted treatment of degenerative joint diseases.
Enhanced cellular transport and drug targeting using dendritic nanostructures

NASA Astrophysics Data System (ADS)

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

2003-03-01

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

PubMed

Lötsch, Jörn; Ultsch, Alfred

2016-12-01

The public accessibility of "big data" about the molecular targets of drugs and the biological functions of genes allows novel data science-based approaches to pharmacology that link drugs directly with their effects on pathophysiologic processes. This provides a phenotypic path to drug discovery and repurposing. This paper compares the performance of a functional genomics-based criterion to the traditional drug target-based classification. Knowledge discovery in the DrugBank and Gene Ontology databases allowed the construction of a "drug target versus biological process" matrix as a combination of "drug versus genes" and "genes versus biological processes" matrices. As a canonical example, such matrices were constructed for classical analgesic drugs. These matrices were projected onto a toroid grid of 50 × 82 artificial neurons using a self-organizing map (SOM). The distance, respectively, cluster structure of the high-dimensional feature space of the matrices was visualized on top of this SOM using a U-matrix. The cluster structure emerging on the U-matrix provided a correct classification of the analgesics into two main classes of opioid and non-opioid analgesics. The classification was flawless with both the functional genomics and the traditional target-based criterion. The functional genomics approach inherently included the drugs' modulatory effects on biological processes. The main pharmacological actions known from pharmacological science were captures, e.g., actions on lipid signaling for non-opioid analgesics that comprised many NSAIDs and actions on neuronal signal transmission for opioid analgesics. Using machine-learned techniques for computational drug classification in a comparative assessment, a functional genomics-based criterion was found to be similarly suitable for drug classification as the traditional target-based criterion. This supports a utility of functional genomics-based approaches to computational system pharmacology for drug
Magnetic nanoparticle-based drug delivery for cancer therapy.

PubMed

Tietze, Rainer; Zaloga, Jan; Unterweger, Harald; Lyer, Stefan; Friedrich, Ralf P; Janko, Christina; Pöttler, Marina; Dürr, Stephan; Alexiou, Christoph

2015-12-18

Nanoparticles have belonged to various fields of biomedical research for quite some time. A promising site-directed application in the field of nanomedicine is drug targeting using magnetic nanoparticles which are directed at the target tissue by means of an external magnetic field. Materials most commonly used for magnetic drug delivery contain metal or metal oxide nanoparticles, such as superparamagnetic iron oxide nanoparticles (SPIONs). SPIONs consist of an iron oxide core, often coated with organic materials such as fatty acids, polysaccharides or polymers to improve colloidal stability and to prevent separation into particles and carrier medium [1]. In general, magnetite and maghemite particles are those most commonly used in medicine and are, as a rule, well-tolerated. The magnetic properties of SPIONs allow the remote control of their accumulation by means of an external magnetic field. Conjugation of SPIONs with drugs, in combination with an external magnetic field to target the nanoparticles (so-called "magnetic drug targeting", MDT), has additionally emerged as a promising strategy of drug delivery. Magnetic nanoparticle-based drug delivery is a sophisticated overall concept and a multitude of magnetic delivery vehicles have been developed. Targeting mechanism-exploiting, tumor-specific attributes are becoming more and more sophisticated. The same is true for controlled-release strategies for the diseased site. As it is nearly impossible to record every magnetic nanoparticle system developed so far, this review summarizes interesting approaches which have recently emerged in the field of targeted drug delivery for cancer therapy based on magnetic nanoparticles. Copyright © 2015 Elsevier Inc. All rights reserved.
Measurement of drug-target engagement in live cells by two-photon fluorescence anisotropy imaging.

PubMed

Vinegoni, Claudio; Fumene Feruglio, Paolo; Brand, Christian; Lee, Sungon; Nibbs, Antoinette E; Stapleton, Shawn; Shah, Sunil; Gryczynski, Ignacy; Reiner, Thomas; Mazitschek, Ralph; Weissleder, Ralph

2017-07-01

The ability to directly image and quantify drug-target engagement and drug distribution with subcellular resolution in live cells and whole organisms is a prerequisite to establishing accurate models of the kinetics and dynamics of drug action. Such methods would thus have far-reaching applications in drug development and molecular pharmacology. We recently presented one such technique based on fluorescence anisotropy, a spectroscopic method based on polarization light analysis and capable of measuring the binding interaction between molecules. Our technique allows the direct characterization of target engagement of fluorescently labeled drugs, using fluorophores with a fluorescence lifetime larger than the rotational correlation of the bound complex. Here we describe an optimized protocol for simultaneous dual-channel two-photon fluorescence anisotropy microscopy acquisition to perform drug-target measurements. We also provide the necessary software to implement stream processing to visualize images and to calculate quantitative parameters. The assembly and characterization part of the protocol can be implemented in 1 d. Sample preparation, characterization and imaging of drug binding can be completed in 2 d. Although currently adapted to an Olympus FV1000MPE microscope, the protocol can be extended to other commercial or custom-built microscopes.
Drug Target Interference in Immunogenicity Assays: Recommendations and Mitigation Strategies.

PubMed

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

2017-11-01

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

PubMed

Odenbach, Stefan

2015-10-01

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

PubMed

Mehraei, Mani; Bashirov, Rza; Tüzmen, Şükrü

2016-10-01

Recent molecular studies provide important clues into treatment of [Formula: see text]-thalassemia, sickle-cell anaemia and other [Formula: see text]-globin disorders revealing that increased production of fetal hemoglobin, that is normally suppressed in adulthood, can ameliorate the severity of these diseases. In this paper, we present a novel approach for drug prediction for [Formula: see text]-globin disorders. Our approach is centered upon quantitative modeling of interactions in human fetal-to-adult hemoglobin switch network using hybrid functional Petri nets. In accordance with the reverse pharmacology approach, we pose a hypothesis regarding modulation of specific protein targets that induce [Formula: see text]-globin and consequently fetal hemoglobin. Comparison of simulation results for the proposed strategy with the ones obtained for already existing drugs shows that our strategy is the optimal as it leads to highest level of [Formula: see text]-globin induction and thereby has potential beneficial therapeutic effects on [Formula: see text]-globin disorders. Simulation results enable verification of model coherence demonstrating that it is consistent with qPCR data available for known strategies and/or drugs.
Targeted delivery of drugs for liver fibrosis.

PubMed

Li, Feng; Wang, Ji-yao

2009-05-01

Liver fibrosis and its end stage disease cirrhosis are a major cause of mortality and morbidity around the world. There is no effective pharmaceutical intervention for liver fibrosis at present. Many drugs that show potent antifibrotic activities in vitro often show only minor effects in vivo because of insufficient concentrations of drugs accumulating around the target cell and their adverse effects as a result of affecting other non-target cells. Hepatic stellate cells (HSC) play a critical role in the fibrogenesis of liver, so they are the target cells of antifibrotic therapy. Several kinds of targeted delivery system that could target the receptors expressed on HSC have been designed, and have shown an attractive targeted potential in vivo. After being carried by these delivery systems, many agents showed a powerful antifibrotic effect in animal models of liver fibrosis. These targeted delivery systems provide a new pathway for the therapy of liver fibrosis. The characteristics of theses targeted carriers are reviewed in this paper.
Structure-based drug discovery for combating influenza virus by targeting the PA-PB1 interaction.

PubMed

Watanabe, Ken; Ishikawa, Takeshi; Otaki, Hiroki; Mizuta, Satoshi; Hamada, Tsuyoshi; Nakagaki, Takehiro; Ishibashi, Daisuke; Urata, Shuzo; Yasuda, Jiro; Tanaka, Yoshimasa; Nishida, Noriyuki

2017-08-25

Influenza virus infections are serious public health concerns throughout the world. The development of compounds with novel mechanisms of action is urgently required due to the emergence of viruses with resistance to the currently-approved anti-influenza viral drugs. We performed in silico screening using a structure-based drug discovery algorithm called Nagasaki University Docking Engine (NUDE), which is optimised for a GPU-based supercomputer (DEstination for Gpu Intensive MAchine; DEGIMA), by targeting influenza viral PA protein. The compounds selected by NUDE were tested for anti-influenza virus activity using a cell-based assay. The most potent compound, designated as PA-49, is a medium-sized quinolinone derivative bearing a tetrazole moiety, and it inhibited the replication of influenza virus A/WSN/33 at a half maximal inhibitory concentration of 0.47 μM. PA-49 has the ability to bind PA and its anti-influenza activity was promising against various influenza strains, including a clinical isolate of A(H1N1)pdm09 and type B viruses. The docking simulation suggested that PA-49 interrupts the PA-PB1 interface where important amino acids are mostly conserved in the virus strains tested, suggesting the strain independent utility. Because our NUDE/DEGIMA system is rapid and efficient, it may help effective drug discovery against the influenza virus and other emerging viruses.
Real-Time Two-Dimensional Magnetic Particle Imaging for Electromagnetic Navigation in Targeted Drug Delivery.

PubMed

Le, Tuan-Anh; Zhang, Xingming; Hoshiar, Ali Kafash; Yoon, Jungwon

2017-09-07

Magnetic nanoparticles (MNPs) are effective drug carriers. By using electromagnetic actuated systems, MNPs can be controlled noninvasively in a vascular network for targeted drug delivery (TDD). Although drugs can reach their target location through capturing schemes of MNPs by permanent magnets, drugs delivered to non-target regions can affect healthy tissues and cause undesirable side effects. Real-time monitoring of MNPs can improve the targeting efficiency of TDD systems. In this paper, a two-dimensional (2D) real-time monitoring scheme has been developed for an MNP guidance system. Resovist particles 45 to 65 nm in diameter (5 nm core) can be monitored in real-time (update rate = 2 Hz) in 2D. The proposed 2D monitoring system allows dynamic tracking of MNPs during TDD and renders magnetic particle imaging-based navigation more feasible.
Neutrophil targeted nano-drug delivery system for chronic obstructive lung diseases.

PubMed

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.

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

PubMed

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.
The Tuberculosis Drug Discovery and Development Pipeline and Emerging Drug Targets

PubMed Central

Mdluli, Khisimuzi; Kaneko, Takushi; Upton, Anna

2015-01-01

The recent accelerated approval for use in extensively drug-resistant and multidrug-resistant-tuberculosis (MDR-TB) of two first-in-class TB drugs, bedaquiline and delamanid, has reinvigorated the TB drug discovery and development field. However, although several promising clinical development programs are ongoing to evaluate new TB drugs and regimens, the number of novel series represented is few. The global early-development pipeline is also woefully thin. To have a chance of achieving the goal of better, shorter, safer TB drug regimens with utility against drug-sensitive and drug-resistant disease, a robust and diverse global TB drug discovery pipeline is key, including innovative approaches that make use of recently acquired knowledge on the biology of TB. Fortunately, drug discovery for TB has resurged in recent years, generating compounds with varying potential for progression into developable leads. In parallel, advances have been made in understanding TB pathogenesis. It is now possible to apply the lessons learned from recent TB hit generation efforts and newly validated TB drug targets to generate the next wave of TB drug leads. Use of currently underexploited sources of chemical matter and lead-optimization strategies may also improve the efficiency of future TB drug discovery. Novel TB drug regimens with shorter treatment durations must target all subpopulations of Mycobacterium tuberculosis existing in an infection, including those responsible for the protracted TB treatment duration. This review summarizes the current TB drug development pipeline and proposes strategies for generating improved hits and leads in the discovery phase that could help achieve this goal. PMID:25635061
gene2drug: a computational tool for pathway-based rational drug repositioning.

PubMed

Napolitano, Francesco; Carrella, Diego; Mandriani, Barbara; Pisonero-Vaquero, Sandra; Sirci, Francesco; Medina, Diego L; Brunetti-Pierri, Nicola; di Bernardo, Diego

2018-05-01

Drug repositioning has been proposed as an effective shortcut to drug discovery. The availability of large collections of transcriptional responses to drugs enables computational approaches to drug repositioning directly based on measured molecular effects. We introduce a novel computational methodology for rational drug repositioning, which exploits the transcriptional responses following treatment with small molecule. Specifically, given a therapeutic target gene, a prioritization of potential effective drugs is obtained by assessing their impact on the transcription of genes in the pathway(s) including the target. We performed in silico validation and comparison with a state-of-art technique based on similar principles. We next performed experimental validation in two different real-case drug repositioning scenarios: (i) upregulation of the glutamate-pyruvate transaminase (GPT), which has been shown to induce reduction of oxalate levels in a mouse model of primary hyperoxaluria, and (ii) activation of the transcription factor TFEB, a master regulator of lysosomal biogenesis and autophagy, whose modulation may be beneficial in neurodegenerative disorders. A web tool for Gene2drug is freely available at http://gene2drug.tigem.it. An R package is under development and can be obtained from https://github.com/franapoli/gep2pep. dibernardo@tigem.it. Supplementary data are available at Bioinformatics online.
Mechanistic models enable the rational use of in vitro drug-target binding kinetics for better drug effects in patients.

PubMed

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

2016-01-01

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

PubMed

Wellington, Samantha; Hung, Deborah T

2018-05-11

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

PubMed Central

Leung, Elaine L.; Cao, Zhi-Wei; Jiang, Zhi-Hong; Zhou, Hua

2013-01-01

Network-based intervention has been a trend of curing systemic diseases, but it relies on regimen optimization and valid multi-target actions of the drugs. The complex multi-component nature of medicinal herbs may serve as valuable resources for network-based multi-target drug discovery due to its potential treatment effects by synergy. Recently, robustness of multiple systems biology platforms shows powerful to uncover molecular mechanisms and connections between the drugs and their targeting dynamic network. However, optimization methods of drug combination are insufficient, owning to lacking of tighter integration across multiple ‘-omics’ databases. The newly developed algorithm- or network-based computational models can tightly integrate ‘-omics’ databases and optimize combinational regimens of drug development, which encourage using medicinal herbs to develop into new wave of network-based multi-target drugs. However, challenges on further integration across the databases of medicinal herbs with multiple system biology platforms for multi-target drug optimization remain to the uncertain reliability of individual data sets, width and depth and degree of standardization of herbal medicine. Standardization of the methodology and terminology of multiple system biology and herbal database would facilitate the integration. Enhance public accessible databases and the number of research using system biology platform on herbal medicine would be helpful. Further integration across various ‘-omics’ platforms and computational tools would accelerate development of network-based drug discovery and network medicine. PMID:22877768
Natural material-decorated mesoporous silica nanoparticle container for multifunctional membrane-controlled targeted drug delivery

PubMed Central

Hu, Yan; Ke, Lei; Chen, Hao; Zhuo, Ma; Yang, Xinzhou; Zhao, Dan; Zeng, Suying; Xiao, Xincai

2017-01-01

To avoid the side effects caused by nonspecific targeting, premature release, weak selectivity, and poor therapeutic efficacy of current nanoparticle-based systems used for drug delivery, we fabricated natural material-decorated nanoparticles as a multifunctional, membrane-controlled targeted drug delivery system. The nanocomposite material coated with a membrane was biocompatible and integrated both specific tumor targeting and responsiveness to stimulation, which improved transmission efficacy and controlled drug release. Mesoporous silica nanoparticles (MSNs), which are known for their biocompatibility and high drug-loading capacity, were selected as a model drug container and carrier. The membrane was established by the polyelectrolyte composite method from chitosan (CS) which was sensitive to the acidic tumor microenvironment, folic acid-modified CS which recognizes the folate receptor expressed on the tumor cell surface, and a CD44 receptor-targeted polysaccharide hyaluronic acid. We characterized the structure of the nanocomposite as well as the drug release behavior under the control of the pH-sensitive membrane switch and evaluated the antitumor efficacy of the system in vitro. Our results provide a basis for the design and fabrication of novel membrane-controlled nanoparticles with improved tumor-targeting therapy. PMID:29200852
Drug discovery in tuberculosis. New drug targets and antimycobacterial agents.

PubMed

Campaniço, André; Moreira, Rui; Lopes, Francisca

2018-04-25

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

PubMed

Baruah, Uday Krishna; Gowthamarajan, Kuppusamy; Vanka, Ravisankar; Karri, Veera Venkata Satyanarayana Reddy; Selvaraj, Kousalya; Jojo, Gifty M

2017-08-01

We reside in an era of technological innovation and advancement despite which infectious diseases like malaria remain to be one of the greatest threats to the humans. Mortality rate caused by malaria disease is a huge concern in the twenty-first century. Multiple drug resistance and nonspecific drug targeting of the most widely used drugs are the main reasons/drawbacks behind the failure in malarial therapy. Dose-related toxicity because of high doses is also a major concern. Therefore, to overcome these problems nano-based drug delivery systems are being developed to facilitate site-specific or target-based drug delivery and hence minimizing the development of resistance progress and dose-dependent toxicity issues. In this review, we discuss about the shortcomings in treating malaria and how nano-based drug delivery systems can help in curtailing the infectious disease malaria.
Real-Time Two-Dimensional Magnetic Particle Imaging for Electromagnetic Navigation in Targeted Drug Delivery

PubMed Central

Le, Tuan-Anh; Zhang, Xingming; Hoshiar, Ali Kafash; Yoon, Jungwon

2017-01-01

Magnetic nanoparticles (MNPs) are effective drug carriers. By using electromagnetic actuated systems, MNPs can be controlled noninvasively in a vascular network for targeted drug delivery (TDD). Although drugs can reach their target location through capturing schemes of MNPs by permanent magnets, drugs delivered to non-target regions can affect healthy tissues and cause undesirable side effects. Real-time monitoring of MNPs can improve the targeting efficiency of TDD systems. In this paper, a two-dimensional (2D) real-time monitoring scheme has been developed for an MNP guidance system. Resovist particles 45 to 65 nm in diameter (5 nm core) can be monitored in real-time (update rate = 2 Hz) in 2D. The proposed 2D monitoring system allows dynamic tracking of MNPs during TDD and renders magnetic particle imaging-based navigation more feasible. PMID:28880220
KCa 3.1-a microglial target ready for drug repurposing?

PubMed

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

2016-10-01

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

PubMed Central

Folger, Ori; Jerby, Livnat; Frezza, Christian; Gottlieb, Eyal; Ruppin, Eytan; Shlomi, Tomer

2011-01-01

The interest in studying metabolic alterations in cancer and their potential role as novel targets for therapy has been rejuvenated in recent years. Here, we report the development of the first genome-scale network model of cancer metabolism, validated by correctly identifying genes essential for cellular proliferation in cancer cell lines. The model predicts 52 cytostatic drug targets, of which 40% are targeted by known, approved or experimental anticancer drugs, and the rest are new. It further predicts combinations of synthetic lethal drug targets, whose synergy is validated using available drug efficacy and gene expression measurements across the NCI-60 cancer cell line collection. Finally, potential selective treatments for specific cancers that depend on cancer type-specific downregulation of gene expression and somatic mutations are compiled. PMID:21694718
Trends in GPCR drug discovery: new agents, targets and indications.

PubMed

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

2017-12-01

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

Cancer.gov

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

PubMed

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

2014-07-01

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

PubMed

Keum, Jongsoo; Nam, Hojung

2017-01-01

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

PubMed

Li, Mengjiao; Li, Haoran; Liu, Fei; Bi, Rui; Tu, Xiaoyu; Chen, Lihua; Ye, Shuang; Cheng, Xi

2017-02-10

It has long been appreciated that different subtypes (serous, clear cell, endometrioid and mucinous) of epithelial ovarian carcinoma (EOC) have distinct pathogenetic pathways. However, clinical management, especially chemotherapeutic regimens, for EOC patients is not subtype specific. Ovarian clear cell carcinoma (CCC) is a rare histological subtype of EOC, which exhibits high rates of recurrence and low chemosensitivity. We assessed potential therapeutic targets for ovarian CCC patients through analyzing the variation of drug-based molecular biomarkers expression between ovarian CCC and high-grade serous carcinoma (HGSC). Seven candidate drug-based molecular biomarkers, human epidermal growth factor receptor (EGFR), human epidermal growth factor receptor-2 (HER2), phosphatase and tensin homolog deleted on chromosome ten (PTEN), aurora kinase A (AURKA), breast cancer susceptibility gene 1 (BRCA1), breast cancer susceptibility gene 2 (BRCA2) and programmed death-ligand 1 (PD-L1) were measured in 96 ovarian CCC and 113 HGSC by immunohistochemistry in paraffin embedded tissues. The relationship between these biomarkers and clinicopathological factors were explored. The expression level of four of the seven drug-based molecular biomarkers was markedly different between HGSC and CCC. High expression levels of HER2 and PD-L1 were more commonly observed in CCC patients (12.6% vs 2.7%, 21.1% vs 11.6%, P = 0.006, 0.064, respectively), while loss of BRCA1 and BRCA2 expression were more frequently occurred in HGSC patients (72.6% vs 54.3%, 89.4% vs 79.8%, P = 0.007, 0.054, respectively). Survival analysis showed that five of seven biomarkers had prognostic values but varied between subtypes. Furthermore, EGFR expressed frequently in CCC patients with endometriosis than in HGSC patients (44.4% vs 8.3%, P = 0.049). AURKA and PD-L1 correlated with the resistance to platinum-based chemotherapy in CCC patients (P = 0.043, 0.028, respectively) while no similar
Targeted Vascular Drug Delivery in Cerebral Cancer.

PubMed

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

2016-01-01

This review presents the present-day literature on the anatomy and physiological mechanisms of the blood-brain barrier and the problematic of cerebral drug delivery in relation to malignant brain tumors. First step in treatment of malignant brain tumors is resection, but there is a high risk of single remnant infiltrative tumor cells in the outer zone of the brain tumor. These infiltrative single-cells will be supplied by capillaries with an intact BBB as opposed to the partly leaky BBB found in the tumor tissue before resection. Even though BBB penetrance of a chemotherapeutic agent is considered irrelevant though the limited success rate for chemotherapeutic treatability of GBM tumors indicate otherwise. Therefore drug delivery strategies to cerebral cancer after resection should be tailored to being able to both penetrate the intact BBB and target the cancer cells. In this review the intact bloodbrain barrier and cerebral cancer with main focus on glioblastoma multiforme (GBM) is introduced. The GBM induced formation of a blood-tumor barrier and the consequences hereof is described and discussed with emphasis on the impact these changes of the BBB has on drug delivery to GBM. The most commonly used drug carriers for drug delivery to GBM is described and the current drug delivery strategies for glioblastoma multiforme including possible routes through the BBB and epitopes, which can be targeted on the GBM cells is outlined. Overall, this review aims to address targeted drug delivery in GBM treatment when taking the differing permeability of the BBB into consideration.
Studies in Multifunctional Drug Development: Preparation and Evaluation of 11beta-Substituted Estradiol-Drug Conjugates, Cell Membrane Targeting Imaging Agents, and Target Multifunctional Nanoparticles

NASA Astrophysics Data System (ADS)

Dao, KinhLuan Lenny D.

with an azido-tetraethylene glycol moiety that could be coupled to a complementary doxorubicin benzoyl hydrazone, functionalized with a propargyl tetraethylene glycol moiety. Huisgen [3+2] cycloaddition chemistry gave the final hybrid which was evaluated for receptor binding to demonstrate ER-affinity and for cytotoxicity in ER(+)-MCF-7 and ER(-)-MDA-MB-231 breast cancer cell lines. The anti-estrogen-doxorubicin hybrid demonstrated enhanced (>70-fold) selectivity for ER(+)-cells versus ER(-)-cells and enhanced efficacy compared to doxorubicin alone. The reversal of these effects by co-administration of estradiol demonstrated that the presence of the anti-estrogenic component was critical for selectivity and cytotoxicity in ER(+)-MCF-7 human breast cancer cells. The results suggest that this approach the basis for developing selective therapeutic agents for ER(+)-cancer cells with reduced effects on non-target tissues.1,2 The second study describes our use of 11beta-AE for targeting ER membrane targeting in hormone-dependent breast cancer, and of a urea-based prostate specific membrane antigen (PSMA) inhibitor for targeting PSMA membrane receptors in androgen-independent of prostate cancer. These derivatives were used to prepare a series of molecular imaging probes. We have successfully established our model compound, 11beta-AE radiolabeled with 18F-fluoro-OEG-azide, for in vivo imaging.3 The third study describes a strategy based on the design and synthesis of a multifunctional gold nanoparticulate (mfAuNPs) drug delivery system that can be used for prostate cancer therapy. We have utilized a convergent modular assembly approach to prepare individual components such as a) prostate specific membrane antigen (PSMA) ligands for targeting; b) pH-sensitive doxorubicin; and c) Re/99Tc chelating complex for radioimaging. The components can be assembled with a terminal lipoic acid or thiolated ethylene glycol oligomer for attachment to the Au surface. Initial in vitro studies
Fe₃O₄ Nanoparticles in Targeted Drug/Gene Delivery Systems.

PubMed

Shen, Lazhen; Li, Bei; Qiao, Yongsheng

2018-02-23

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

Computation-based virtual screening for designing novel antimalarial drugs by targeting falcipain-III: a structure-based drug designing approach.

PubMed

Kesharwani, Rajesh Kumar; Singh, Durg Vijay; Misra, Krishna

2013-01-01

Cysteine proteases (falcipains), a papain-family of enzymes of Plasmodium falciparum, are responsible for haemoglobin degradation and thus necessary for its survival during asexual life cycle phase inside the human red blood cells while remaining non-functional for the human body. Therefore, these can act as potential targets for designing antimalarial drugs. The P. falciparum cysteine proteases, falcipain-II and falcipain- III are the enzymes which initiate the haemoglobin degradation, therefore, have been selected as targets. In the present study, we have designed new leupeptin analogues and subjected to virtual screening using Glide at the active site cavity of falcipain-II and falcipain-III to select the best docked analogues on the basis of Glide score and also compare with the result of AutoDock. The proposed analogues can be synthesized and tested in vivo as future potent antimalarial drugs. Protein falcipain-II and falcipain-III together with bounds inhibitors epoxysuccinate E64 (E64) and leupeptin respectively were retrieved from protein data bank (PDB) and latter leupeptin was used as lead molecule to design new analogues by using Ligbuilder software and refined the molecules on the basis of Lipinski rule of five and fitness score parameters. All the designed leupeptin analogues were screened via docking simulation at the active site cavity of falcipain-II and falcipain-III by using Glide software and AutoDock. The 104 new leupeptin-based antimalarial ligands were designed using structure-based drug designing approach with the help of Ligbuilder and subjected for virtual screening via docking simulation method against falcipain-II and falcipain-III receptor proteins. The Glide docking results suggest that the ligands namely result_037 shows good binding and other two, result_044 and result_042 show nearly similar binding than naturally occurring PDB bound ligand E64 against falcipain-II and in case of falcipain-III, 15 designed leupeptin analogues having
Catechol polymers for pH-responsive, targeted drug delivery to cancer cells.

PubMed

Su, Jing; Chen, Feng; Cryns, Vincent L; Messersmith, Phillip B

2011-08-10

A novel cell-targeting, pH-sensitive polymeric carrier was employed in this study for delivery of the anticancer drug bortezomib (BTZ) to cancer cells. Our strategy is based on facile conjugation of BTZ to catechol-containing polymeric carriers that are designed to be taken up selectively by cancer cells through cell surface receptor-mediated mechanisms. The polymer used as a building block in this study was poly(ethylene glycol), which was chosen for its ability to reduce nonspecific interactions with proteins and cells. The catechol moiety was exploited for its ability to bind and release borate-containing therapeutics such as BTZ in a pH-dependent manner. In acidic environments, such as in cancer tissue or the subcellular endosome, BTZ dissociates from the polymer-bound catechol groups to liberate the free drug, which inhibits proteasome function. A cancer-cell-targeting ligand, biotin, was presented on the polymer carriers to facilitate targeted entry of drug-loaded polymer carriers into cancer cells. Our study demonstrated that the cancer-targeting drug-polymer conjugates dramatically enhanced cellular uptake, proteasome inhibition, and cytotoxicity toward breast carcinoma cells in comparison with nontargeting drug-polymer conjugates. The pH-sensitive catechol-boronate binding mechanism provides a chemoselective approach for controlling the release of BTZ in targeted cancer cells, establishing a concept that may be applied in the future toward other boronic acid-containing therapeutics to treat a broad range of diseases. © 2011 American Chemical Society
Hierarchical pulmonary target nanoparticles via inhaled administration for anticancer drug delivery.

PubMed

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

2017-11-01

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

PubMed Central

Sampath, Aruna; Padmanabhan, R.

2009-01-01

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

PubMed

Schoonen, Lise; van Hest, Jan C M

2014-07-07

Traditional drug delivery strategies involve drugs which are not targeted towards the desired tissue. This can lead to undesired side effects, as normal cells are affected by the drugs as well. Therefore, new systems are now being developed which combine targeting functionalities with encapsulation of drug cargo. Protein nanocages are highly promising drug delivery platforms due to their perfectly defined structures, biocompatibility, biodegradability and low toxicity. A variety of protein nanocages have been modified and functionalized for these types of applications. In this review, we aim to give an overview of different types of modifications of protein-based nanocontainers for drug delivery applications.
Open-source chemogenomic data-driven algorithms for predicting drug-target interactions.

PubMed

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

2018-02-06

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

PubMed Central

2011-01-01

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

PubMed Central

Azam, Mohammad; Raz, Tal; Nardi, Valentina; Opitz, Sarah L.

2003-01-01

The discovery of oncogenes and signal transduction pathways important for mitogenesis has triggered the development of target-specific small molecule anti-cancer compounds. As exemplified by imatinib (Gleevec), a specific inhibitor of the Chronic Myeloid Leukemia (CML)-associated Bcr-Abl kinase, these agents promise impressive activity in clinical trials, with low levels of clinical toxicity. However, such therapy is susceptible to the emergence of drug resistance due to amino acid substitutions in the target protein. Defining the spectrum of such mutations is important for patient monitoring and the design of next-generation inhibitors. Using imatinib and BCR/ABL as a paradigm for a drug-target pair, we recently reported a retroviral vector-based screening strategy to identify the spectrum of resistance-conferring mutations. Here we provide a detailed methodology for the screen, which can be generally applied to any drug-target pair. PMID:14615817
Chemical signatures and new drug targets for gametocytocidal drug development

NASA Astrophysics Data System (ADS)

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

2014-01-01

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

PubMed

Cheng, Feixiong; Murray, James L; Zhao, Junfei; Sheng, Jinsong; Zhao, Zhongming; Rubin, Donald H

2016-09-01

Viruses require host cellular factors for successful replication. A comprehensive systems-level investigation of the virus-host interactome is critical for understanding the roles of host factors with the end goal of discovering new druggable antiviral targets. Gene-trap insertional mutagenesis is a high-throughput forward genetics approach to randomly disrupt (trap) host genes and discover host genes that are essential for viral replication, but not for host cell survival. In this study, we used libraries of randomly mutagenized cells to discover cellular genes that are essential for the replication of 10 distinct cytotoxic mammalian viruses, 1 gram-negative bacterium, and 5 toxins. We herein reported 712 candidate cellular genes, characterizing distinct topological network and evolutionary signatures, and occupying central hubs in the human interactome. Cell cycle phase-specific network analysis showed that host cell cycle programs played critical roles during viral replication (e.g. MYC and TAF4 regulating G0/1 phase). Moreover, the viral perturbation of host cellular networks reflected disease etiology in that host genes (e.g. CTCF, RHOA, and CDKN1B) identified were frequently essential and significantly associated with Mendelian and orphan diseases, or somatic mutations in cancer. Computational drug repositioning framework via incorporating drug-gene signatures from the Connectivity Map into the virus-host interactome identified 110 putative druggable antiviral targets and prioritized several existing drugs (e.g. ajmaline) that may be potential for antiviral indication (e.g. anti-Ebola). In summary, this work provides a powerful methodology with a tight integration of gene-trap insertional mutagenesis testing and systems biology to identify new antiviral targets and drugs for the development of broadly acting and targeted clinical antiviral therapeutics.
Amphiphilic multiarm star block copolymer-based multifunctional unimolecular micelles for cancer targeted drug delivery and MR imaging.

PubMed

Li, Xiaojie; Qian, Yinfeng; Liu, Tao; Hu, Xianglong; Zhang, Guoying; You, Yezi; Liu, Shiyong

2011-09-01

We report on the fabrication of multifunctional polymeric unimolecular micelles as an integrated platform for cancer targeted drug delivery and magnetic resonance imaging (MRI) contrast enhancement under in vitro and in vivo conditions. Starting from a fractionated fourth-generation hyperbranched polyester (Boltorn H40), the ring-opening polymerization of ɛ-caprolactone (CL) from the periphery of H40 and subsequent terminal group esterification with 2-bromoisobutyryl bromide afforded star copolymer-based atom transfer radical polymerization (ATRP) macroinitiator, H40-PCL-Br. Well-defined multiarm star block copolymers, H40-PCL-b-P(OEGMA-co-AzPMA), were then synthesized by the ATRP of oligo(ethylene glycol) monomethyl ether methacrylate (OEGMA) and 3-azidopropyl methacrylate (AzPMA). This was followed by the click reaction of H40-PCL-b-P(OEGMA-co-AzPMA) with alkynyl-functionalized cancer cell-targeting moieties, alkynyl-folate, and T(1)-type MRI contrast agents, alkynyl-DOTA-Gd (DOTA is 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetrakisacetic acid), affording H40-PCL-b-P(OEGMA-Gd-FA). In aqueous solution, the amphiphilic multiarm star block copolymer exists as structurally stable unimolecular micelles possessing a hyperbranched polyester core, a hydrophobic PCL inner layer, and a hydrophilic P(OEGMA-Gd-FA) outer corona. H40-PCL-b-P(OEGMA-Gd-FA) unimolecular micelles are capable of encapsulating paclitaxel, a well-known hydrophobic anticancer drug, with a loading content of 6.67 w/w% and exhibiting controlled release of up to 80% loaded drug over a time period of ∼120 h. In vitro MRI experiments demonstrated considerably enhanced T(1) relaxivity (18.14 s(-1) mM(-1)) for unimolecular micelles compared to 3.12 s(-1) mM(-1) for that of the small molecule counterpart, alkynyl-DOTA-Gd. Further experiments of in vivo MR imaging in rats revealed good accumulation of unimolecular micelles within rat liver and kidney, prominent positive contrast enhancement, and relatively
Target-similarity search using Plasmodium falciparum proteome identifies approved drugs with anti-malarial activity and their possible targets

PubMed Central

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

2017-01-01

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

PubMed Central

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

2018-01-01

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

PubMed Central

Butts, Arielle; DeJarnette, Christian; Peters, Tracy L.; Parker, Josie E.; Kerns, Morgan E.; Eberle, Karen E.; Kelly, Steve L.

2017-01-01

ABSTRACT Traditional approaches to drug discovery are frustratingly inefficient and have several key limitations that severely constrain our capacity to rapidly identify and develop novel experimental therapeutics. To address this, we have devised a second-generation target-based whole-cell screening assay based on the principles of competitive fitness, which can rapidly identify target-specific and physiologically active compounds. Briefly, strains expressing high, intermediate, and low levels of a preselected target protein are constructed, tagged with spectrally distinct fluorescent proteins (FPs), and pooled. The pooled strains are then grown in the presence of various small molecules, and the relative growth of each strain within the mixed culture is compared by measuring the intensity of the corresponding FP tags. Chemical-induced population shifts indicate that the bioactivity of a small molecule is dependent upon the target protein’s abundance and thus establish a specific functional interaction. Here, we describe the molecular tools required to apply this technique in the prevalent human fungal pathogen Candida albicans and validate the approach using two well-characterized drug targets—lanosterol demethylase and dihydrofolate reductase. However, our approach, which we have termed target abundance-based fitness screening (TAFiS), should be applicable to a wide array of molecular targets and in essentially any genetically tractable microbe. IMPORTANCE Conventional drug screening typically employs either target-based or cell-based approaches. The first group relies on biochemical assays to detect modulators of a purified target. However, hits frequently lack drug-like characteristics such as membrane permeability and target specificity. Cell-based screens identify compounds that induce a desired phenotype, but the target is unknown, which severely restricts further development and optimization. To address these issues, we have developed a second
Preparation and Immunoaffinity Depletion of Fresh Frozen Tissue Homogenates for Mass Spectrometry-Based Proteomics in the Context of Drug Target/Biomarker Discovery.

PubMed

Prieto, DaRue A; Chan, King C; Johann, Donald J; Ye, Xiaoying; Whitely, Gordon; Blonder, Josip

2017-01-01

The discovery of novel drug targets and biomarkers via mass spectrometry (MS)-based proteomic analysis of clinical specimens has proven to be challenging. The wide dynamic range of protein concentration in clinical specimens and the high background/noise originating from highly abundant proteins in tissue homogenates and serum/plasma encompass two major analytical obstacles. Immunoaffinity depletion of highly abundant blood-derived proteins from serum/plasma is a well-established approach adopted by numerous researchers; however, the utilization of this technique for immunodepletion of tissue homogenates obtained from fresh frozen clinical specimens is lacking. We first developed immunoaffinity depletion of highly abundant blood-derived proteins from tissue homogenates, using renal cell carcinoma as a model disease, and followed this study by applying it to different tissue types. Tissue homogenate immunoaffinity depletion of highly abundant proteins may be equally important as is the recognized need for depletion of serum/plasma, enabling more sensitive MS-based discovery of novel drug targets, and/or clinical biomarkers from complex clinical samples. Provided is a detailed protocol designed to guide the researcher through the preparation and immunoaffinity depletion of fresh frozen tissue homogenates for two-dimensional liquid chromatography, tandem mass spectrometry (2D-LC-MS/MS)-based molecular profiling of tissue specimens in the context of drug target and/or biomarker discovery.
Folic acid-targeted disulfide-based cross-linking micelle for enhanced drug encapsulation stability and site-specific drug delivery against tumors

PubMed Central

Zhang, Yumin; Zhou, Junhui; Yang, Cuihong; Wang, Weiwei; Chu, Liping; Huang, Fan; Liu, Qiang; Deng, Liandong; Kong, Deling; Liu, Jianfeng; Liu, Jinjian

2016-01-01

Although the shortcomings of small molecular antitumor drugs were efficiently improved by being entrapped into nanosized vehicles, premature drug release and insufficient tumor targeting demand innovative approaches that boost the stability and tumor responsiveness of drug-loaded nanocarriers. Here, we show the use of the core cross-linking method to generate a micelle with enhanced drug encapsulation ability and sensitivity of drug release in tumor. This kind of micelle could increase curcumin (Cur) delivery to HeLa cells in vitro and improve tumor accumulation in vivo. We designed and synthesized the core cross-linked micelle (CCM) with polyethylene glycol and folic acid-polyethylene glycol as the hydrophilic units, pyridyldisulfide as the cross-linkable and hydrophobic unit, and disulfide bond as the cross-linker. CCM showed spherical shape with a diameter of 91.2 nm by the characterization of dynamic light scattering and transmission electron microscope. Attributed to the core cross-linking, drug-loaded CCM displayed higher Nile Red or Cur-encapsulated stability and better sensitivity to glutathione than noncross-linked micelle (NCM). Cellular uptake and in vitro antitumor studies proved the enhanced endocytosis and better cytotoxicity of CCM-Cur against HeLa cells, which had a high level of glutathione. Meanwhile, the folate receptor-mediated drug delivery (FA-CCM-Cur) further enhanced the endocytosis and cytotoxicity. Ex vivo imaging studies showed that CCM-Cur and FA-CCM-Cur possessed higher tumor accumulation until 24 hours after injection. Concretely, FA-CCM-Cur exhibited the highest tumor accumulation with 1.7-fold of noncross-linked micelle Cur and 2.8-fold of free Cur. By combining cross-linking of the core with active tumor targeting of FA, we demonstrated a new and effective way to design nanocarriers for enhanced drug encapsulation, smart tumor responsiveness, and elevated tumor accumulation. PMID:27051287
A New Era for Cancer Target Therapies: Applying Systems Biology and Computer-Aided Drug Design to Cancer Therapies.

PubMed

Wong, Yung-Hao; Chiu, Chia-Chiun; Lin, Chih-Lung; Chen, Ting-Shou; Jheng, Bo-Ren; Lee, Yu-Ching; Chen, Jeremy; Chen, Bor-Sen

In recent years, many systems biology approaches have been used with various cancers. The materials described here can be used to build bases to discover novel cancer therapy targets in connection with computer-aided drug design (CADD). A deeper understanding of the mechanisms of cancer will provide more choices and correct strategies in the development of multiple target drug therapies, which is quite different from the traditional cancer single target therapy. Targeted therapy is one of the most powerful strategies against cancer and can also be applied to other diseases. Due to the large amount of progress in computer hardware and the theories of computational chemistry and physics, CADD has been the main strategy for developing novel drugs for cancer therapy. In contrast to traditional single target therapies, in this review we will emphasize the future direction of the field, i.e., multiple target therapies. Structure-based and ligand-based drug designs are the two main topics of CADD. The former needs both 3D protein structures and ligand structures, while the latter only needs ligand structures. Ordinarily it is estimated to take more than 14 years and 800 million dollars to develop a new drug. Many new CADD software programs and techniques have been developed in recent decades. We conclude with an example where we combined and applied systems biology and CADD to the core networks of four cancers and successfully developed a novel cocktail for drug therapy that treats multiple targets.
Identification of Attractive Drug Targets in Neglected-Disease Pathogens Using an In Silico Approach

PubMed Central

Crowther, Gregory J.; Shanmugam, Dhanasekaran; Carmona, Santiago J.; Doyle, Maria A.; Hertz-Fowler, Christiane; Berriman, Matthew; Nwaka, Solomon; Ralph, Stuart A.; Roos, David S.; Van Voorhis, Wesley C.; Agüero, Fernán

2010-01-01

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

PubMed

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

2016-12-22

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

NASA Astrophysics Data System (ADS)

Toepak, E. P.; Tambunan, U. S. F.

2017-02-01

Dengue is a major health problem in the tropical and sub-tropical regions. The development of antiviral that targeting dengue’s host enzyme can be more effective and efficient treatment than the viral enzyme. Host enzyme processing α-glucosidase I has an important role in the maturation process of dengue virus envelope glycoprotein. The inhibition of processing α-glucosidase I can become a promising target for dengue fever treatment. The antiviral approach using in silico fragment-based drug design can generate drug candidates with high binding affinity. In this research, 198.621 compounds were obtained from ZINC15 Biogenic Database. These compounds were screened to find the favorable fragments according to Rules of Three and pharmacological properties. The screening fragments were docked into the active site of processing α-glucosidase I. The potential fragment candidates from the molecular docking simulation were linked with castanospermine (CAST) to generate ligands with a better binding affinity. The Analysis of ligand - enzyme interaction showed ligands with code LRS 22, 28, and 47 have the better binding free energy than the standard ligand. Ligand LRS 28 (N-2-4-methyl-5-((1S,3S,6S,7R,8R,8aR)-1,6,7,8-tetrahydroxyoctahydroindolizin-3-yl) pentyl) indolin-1-yl) propionamide) itself among the other ligands has the lowest binding free energy. Pharmacological properties prediction also showed the ligands LRS 22, 28, and 47 can be promising as the dengue fever drug candidates.

Targeted and Controlled Anticancer Drug Delivery and Release with Magnetoelectric Nanoparticles

NASA Astrophysics Data System (ADS)

Rodzinski, Alexandra

A major challenge of cancer treatment is successful discrimination of cancer cells from healthy cells. Nanotechnology offers multiple venues for efficient cancer targeting. Magnetoelectric nanoparticles (MENs) are a novel, multifaceted, physics-based cancer treatment platform that enables high specificity cancer targeting and externally controlled loaded drug release. The unique magnetoelectric coupling of MENs allows them to convert externally applied magnetic fields into intrinsic electric signals, which allows MENs to both be drawn magnetically towards the cancer site and to electrically interface with cancer cells. Once internalized, the MEN payload release can be externally triggered with a magnetic field. MENs uniquely allow for discrete manipulation of the drug delivery and drug release mechanisms to allow an unprecedented level of control in cancer targeting. In this study, we demonstrate the physics behind the MEN drug delivery platform, test the MEN drug delivery platform for the first time in a humanized mouse model of cancer, and characterize the biodistribution and clearance of MENs. We found that MENs were able to fully cure the model cancer, which in this case was human ovarian carcinoma treated with paclitaxel. When compared to conventional magnetic nanoparticles and FDA approved organic PLGA nanoparticles, MENs are the highest performing treatment, even in the absence of peripheral active targeting molecules. We also mapped the movement through peripheral organs and established clearance trends of the MENs. The MENs cancer treatment platform has immense potential for future medicine, as it is generalizable, personalizable, and readily traceable in the context of treating essentially any type of cancer.
PharmMapper server: a web server for potential drug target identification using pharmacophore mapping approach

PubMed Central

Liu, Xiaofeng; Ouyang, Sisheng; Yu, Biao; Liu, Yabo; Huang, Kai; Gong, Jiayu; Zheng, Siyuan; Li, Zhihua; Li, Honglin; Jiang, Hualiang

2010-01-01

In silico drug target identification, which includes many distinct algorithms for finding disease genes and proteins, is the first step in the drug discovery pipeline. When the 3D structures of the targets are available, the problem of target identification is usually converted to finding the best interaction mode between the potential target candidates and small molecule probes. Pharmacophore, which is the spatial arrangement of features essential for a molecule to interact with a specific target receptor, is an alternative method for achieving this goal apart from molecular docking method. PharmMapper server is a freely accessed web server designed to identify potential target candidates for the given small molecules (drugs, natural products or other newly discovered compounds with unidentified binding targets) using pharmacophore mapping approach. PharmMapper hosts a large, in-house repertoire of pharmacophore database (namely PharmTargetDB) annotated from all the targets information in TargetBank, BindingDB, DrugBank and potential drug target database, including over 7000 receptor-based pharmacophore models (covering over 1500 drug targets information). PharmMapper automatically finds the best mapping poses of the query molecule against all the pharmacophore models in PharmTargetDB and lists the top N best-fitted hits with appropriate target annotations, as well as respective molecule’s aligned poses are presented. Benefited from the highly efficient and robust triangle hashing mapping method, PharmMapper bears high throughput ability and only costs 1 h averagely to screen the whole PharmTargetDB. The protocol was successful in finding the proper targets among the top 300 pharmacophore candidates in the retrospective benchmarking test of tamoxifen. PharmMapper is available at http://59.78.96.61/pharmmapper. PMID:20430828
Chlorotoxin-conjugated graphene oxide for targeted delivery of an anticancer drug

PubMed Central

Wang, Hao; Gu, Wei; Xiao, Ning; Ye, Ling; Xu, Qunyuan

2014-01-01

Current chemotherapy for glioma is rarely satisfactory due to low therapeutic efficiency and systemic side effects. We have developed a glioma-targeted drug delivery system based on graphene oxide. Targeted peptide chlorotoxin-conjugated graphene oxide (CTX-GO) sheets were successfully synthesized and characterized. Doxorubicin was loaded onto CTX-GO (CTX-GO/DOX) with high efficiency (570 mg doxorubicin per gram CTX-GO) via noncovalent interactions. Doxorubicin release was pH-dependent and showed sustained-release properties. Cytotoxicity experiments demonstrated that CTX-GO/DOX mediated the highest rate of death of glioma cells compared with free doxorubicin or graphene oxide loaded with doxorubicin only. Further, conjugation with chlorotoxin enhanced accumulation of doxorubicin within glioma cells. These findings indicate that CTX-GO is a promising platform for drug delivery and provide a rationale for developing a glioma-specific drug delivery system. PMID:24672236
Untethered magnetic millirobot for targeted drug delivery.

PubMed

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

2015-01-01

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

PubMed Central

van Montfort, Rob L.M.; Workman, Paul

2017-01-01

Knowledge of the three-dimensional structure of therapeutically relevant targets has informed drug discovery since the first protein structures were determined using X-ray crystallography in the 1950s and 1960s. In this editorial we provide a brief overview of the powerful impact of structure-based drug design (SBDD), which has its roots in computational and structural biology, with major contributions from both academia and industry. We describe advances in the application of SBDD for integral membrane protein targets that have traditionally proved very challenging. We emphasize the major progress made in fragment-based approaches for which success has been exemplified by over 30 clinical drug candidates and importantly three FDA-approved drugs in oncology. We summarize the articles in this issue that provide an excellent snapshot of the current state of the field of SBDD and fragment-based drug design and which offer key insights into exciting new developments, such as the X-ray free-electron laser technology, cryo-electron microscopy, open science approaches and targeted protein degradation. We stress the value of SBDD in the design of high-quality chemical tools that are used to interrogate biology and disease pathology, and to inform target validation. We emphasize the need to maintain the scientific rigour that has been traditionally associated with structural biology and extend this to other methods used in drug discovery. This is particularly important because the quality and robustness of any form of contributory data determines its usefulness in accelerating drug design, and therefore ultimately in providing patient benefit. PMID:29118091
Nanothermite-Based Microsystem for Drug Delivery and Cell Transfection

DTIC Science & Technology

2008-12-01

micropyrotechnic-based system in which a nanothermite energy source is coupled to a biological target for gene transfer and drug delivery ... delivery of particulate vaccines and drugs to human skin with a practical, hand-held shock tube-based system . Shock Waves, 12, 23-30. Kodama, T., M...1 NANOTHERMITE-BASED MICROSYSTEM FOR DRUG DELIVERY AND CELL TRANSFECTION S. Apperson, R. Thiruvengadathan, A. Bezmelnitsyn, K. Gangopadhyay, S
Target-mediated drug disposition model for drugs with two binding sites that bind to a target with one binding site.

PubMed

Gibiansky, Leonid; Gibiansky, Ekaterina

2017-10-01

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

NASA Astrophysics Data System (ADS)

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

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

ERIC Educational Resources Information Center

Caulkins, Jonathan P.; Pacula, Rosalie Liccardo; Paddock, Susan; Chiesa, James

School-based drug prevention programs target not only the use of illicit drugs such as marijuana but also licit substances such as alcohol and tobacco. These programs thus have the potential of benefiting society not only by reducing the violence and criminal justice costs associated with abuse of alcohol and cigarettes. This opportunity for…
Systems biology-embedded target validation: improving efficacy in drug discovery.

PubMed

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.
Targeted Drug Delivery with Polymers and Magnetic Nanoparticles: Covalent and Noncovalent Approaches, Release Control, and Clinical Studies.

PubMed

Ulbrich, Karel; Holá, Kateřina; Šubr, Vladimir; Bakandritsos, Aristides; Tuček, Jiří; Zbořil, Radek

2016-05-11

Targeted delivery combined with controlled drug release has a pivotal role in the future of personalized medicine. This review covers the principles, advantages, and drawbacks of passive and active targeting based on various polymer and magnetic iron oxide nanoparticle carriers with drug attached by both covalent and noncovalent pathways. Attention is devoted to the tailored conjugation of targeting ligands (e.g., enzymes, antibodies, peptides) to drug carrier systems. Similarly, the approaches toward controlled drug release are discussed. Various polymer-drug conjugates based, for example, on polyethylene glycol (PEG), N-(2-hydroxypropyl)methacrylamide (HPMA), polymeric micelles, and nanoparticle carriers are explored with respect to absorption, distribution, metabolism, and excretion (ADME scheme) of administrated drug. Design and structure of superparamagnetic iron oxide nanoparticles (SPION) and condensed magnetic clusters are classified according to the mechanism of noncovalent drug loading involving hydrophobic and electrostatic interactions, coordination chemistry, and encapsulation in porous materials. Principles of covalent conjugation of drugs with SPIONs including thermo- and pH-degradable bonds, amide linkage, redox-cleavable bonds, and enzymatically-cleavable bonds are also thoroughly described. Finally, results of clinical trials obtained with polymeric and magnetic carriers are analyzed highlighting the potential advantages and future directions in targeted anticancer therapy.
Drug Target Validation Methods in Malaria - Protein Interference Assay (PIA) as a Tool for Highly Specific Drug Target Validation.

PubMed

Meissner, Kamila A; Lunev, Sergey; Wang, Yuan-Ze; Linzke, Marleen; de Assis Batista, Fernando; Wrenger, Carsten; Groves, Matthew R

2017-01-01

The validation of drug targets in malaria and other human diseases remains a highly difficult and laborious process. In the vast majority of cases, highly specific small molecule tools to inhibit a proteins function in vivo are simply not available. Additionally, the use of genetic tools in the analysis of malarial pathways is challenging. These issues result in difficulties in specifically modulating a hypothetical drug target's function in vivo. The current "toolbox" of various methods and techniques to identify a protein's function in vivo remains very limited and there is a pressing need for expansion. New approaches are urgently required to support target validation in the drug discovery process. Oligomerisation is the natural assembly of multiple copies of a single protein into one object and this self-assembly is present in more than half of all protein structures. Thus, oligomerisation plays a central role in the generation of functional biomolecules. A key feature of oligomerisation is that the oligomeric interfaces between the individual parts of the final assembly are highly specific. However, these interfaces have not yet been systematically explored or exploited to dissect biochemical pathways in vivo. This mini review will describe the current state of the antimalarial toolset as well as the potentially druggable malarial pathways. A specific focus is drawn to the initial efforts to exploit oligomerisation surfaces in drug target validation. As alternative to the conventional methods, Protein Interference Assay (PIA) can be used for specific distortion of the target protein function and pathway assessment in vivo. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Pericyte-targeting drug delivery and tissue engineering.

PubMed

Kang, Eunah; Shin, Jong Wook

2016-01-01

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

PubMed Central

Barve, Ashutosh; Jin, Wei; Cheng, Kun

2014-01-01

Chemotherapy is one of the most widely used approaches in combating advanced prostate cancer, but its therapeutic efficacy is usually insufficient due to lack of specificity and associated toxicity. Lack of targeted delivery to prostate cancer cells is also the primary obstacles in achieving feasible therapeutic effect of other promising agents including peptide, protein, and nucleic acid. Consequently, there remains a critical need for strategies to increase the selectivity of anti-prostate cancer agents. This review will focus on various prostate cancer-specific antigens and enzymes that could be exploited for prostate cancer targeted drug delivery. Among various targeting strategies, active targeting is the most advanced approach to specifically deliver drugs to their designated cancer cells. In this approach, drug carriers are modified with targeting ligands that can specifically bind to prostate cancer-specific antigens. Moreover, there are several specific enzymes in the tumor microenvironment of prostate cancer that can be exploited for stimulus-responsive drug delivery systems. These systems can specifically release the active drug in the tumor microenvironment of prostate cancer, leading to enhanced tumor penetration efficiency. PMID:24878184
CYP51 is an essential drug target for the treatment of primary amoebic meningoencephalitis (PAM)

PubMed Central

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

2017-01-01

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

NASA Astrophysics Data System (ADS)

Zuccotto, Fabio; Martin, Andrew C. R.; Laskowski, Roman A.; Thornton, Janet M.; Gilbert, Ian H.

1998-05-01

Dihydrofolate reductase has successfully been used as a drug target in the area of anti-cancer, anti-bacterial and anti-malarial chemotherapy. Little has been done to evaluate it as a drug target for treatment of the trypanosomiases and leishmaniasis. A crystal structure of Leishmania major dihydrofolate reductase has been published. In this paper, we describe the modelling of Trypanosoma cruzi and Trypanosoma brucei dihydrofolate reductases based on this crystal structure. These structures and models have been used in the comparison of protozoan, bacterial and human enzymes in order to highlight the different features that can be used in the design of selective anti-protozoan agents. Comparison has been made between residues present in the active site, the accessibility of these residues, charge distribution in the active site, and the shape and size of the active sites. Whilst there is a high degree of similarity between protozoan, human and bacterial dihydrofolate reductase active sites, there are differences that provide potential for selective drug design. In particular, we have identified a set of residues which may be important for selective drug design and identified a larger binding pocket in the protozoan than the human and bacterial enzymes.
Development of poly(lactic-co-glycolic) acid nanoparticles-embedded hyaluronic acid-ceramide-based nanostructure for tumor-targeted drug delivery.

PubMed

Park, Ju-Hwan; Lee, Jae-Young; Termsarasab, Ubonvan; Yoon, In-Soo; Ko, Seung-Hak; Shim, Jae-Seong; Cho, Hyun-Jong; Kim, Dae-Duk

2014-10-01

A hyaluronic acid-ceramide (HACE) nanostructure embedded with docetaxel (DCT)-loaded poly(d,l-lactide-co-glycolide) (PLGA) nanoparticles (NPs) was fabricated for tumor-targeted drug delivery. NPs with a narrow size distribution and negative zeta potential were prepared by embedding DCT-loaded PLGA NPs into a HACE nanostructure (DCT/PLGA/HACE). DCT-loaded PLGA and DCT/PLGA/HACE NPs were characterized by solid-state techniques, including Fourier-transform infrared (FT-IR) spectroscopy, differential scanning calorimetry (DSC), and powder X-ray diffraction (PXRD). A sustained drug release pattern from the NPs developed was observed and negligible cytotoxicity was seen in NIH3T3 cells (normal fibroblast, CD44 receptor negative) and MDA-MB-231 cells (breast cancer cells, CD44 receptor positive). PLGA/HACE NPs containing coumarin 6, used as a fluorescent dye, exhibited improved cellular uptake efficiency, based on the HA-CD44 receptor interaction, compared to plain PLGA NPs. Cyanine 5.5 (Cy5.5)-labeled PLGA/HACE NPs were injected intravenously into a MDA-MB-231 tumor xenograft mouse model and demonstrated enhanced tumor targetability, compared with Cy5.5-PLGA NPs, according to a near-infrared fluorescence (NIRF) imaging study. Considering these experimental results, the DCT/PLGA/HACE NPs developed may be useful as a tumor-targeted drug delivery system. Copyright © 2014 Elsevier B.V. All rights reserved.
Target identification of small molecules based on chemical biology approaches.

PubMed

Futamura, Yushi; Muroi, Makoto; Osada, Hiroyuki

2013-05-01

Recently, a phenotypic approach-screens that assess the effects of compounds on cells, tissues, or whole organisms-has been reconsidered and reintroduced as a complementary strategy of a target-based approach for drug discovery. Although the finding of novel bioactive compounds from large chemical libraries has become routine, the identification of their molecular targets is still a time-consuming and difficult process, making this step rate-limiting in drug development. In the last decade, we and other researchers have amassed a large amount of phenotypic data through progress in omics research and advances in instrumentation. Accordingly, the profiling methodologies using these datasets expertly have emerged to identify and validate specific molecular targets of drug candidates, attaining some progress in current drug discovery (e.g., eribulin). In the case of a compound that shows an unprecedented phenotype likely by inhibiting a first-in-class target, however, such phenotypic profiling is invalid. Under the circumstances, a photo-crosslinking affinity approach should be beneficial. In this review, we describe and summarize recent progress in both affinity-based (direct) and phenotypic profiling (indirect) approaches for chemical biology target identification.
2-Aryl-5-carboxytetrazole as a New Photoaffinity Label for Drug Target Identification

PubMed Central

2016-01-01

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

PubMed

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

2016-11-09

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

Label-free integrative pharmacology on-target of drugs at the β2-adrenergic receptor

NASA Astrophysics Data System (ADS)

Ferrie, Ann M.; Sun, Haiyan; Fang, Ye

2011-07-01

We describe a label-free integrative pharmacology on-target (iPOT) method to assess the pharmacology of drugs at the β2-adrenergic receptor. This method combines dynamic mass redistribution (DMR) assays using an array of probe molecule-hijacked cells with similarity analysis. The whole cell DMR assays track cell system-based, ligand-directed, and kinetics-dependent biased activities of the drugs, and translates their on-target pharmacology into numerical descriptors which are subject to similarity analysis. We demonstrate that the approach establishes an effective link between the label-free pharmacology and in vivo therapeutic indications of drugs.
Targeting cysteine proteases in trypanosomatid disease drug discovery.

PubMed

Ferreira, Leonardo G; Andricopulo, Adriano D

2017-12-01

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

NASA Astrophysics Data System (ADS)

Duncan, Gregg A.; Bevan, Michael A.

2015-09-01

Ligand-functionalized nanoparticles capable of selectively binding to diseased versus healthy cell populations are attractive for improved efficacy of nanoparticle-based drug and gene therapies. However, nanoparticles functionalized with high affinity targeting ligands may lead to undesired off-target binding to healthy cells. In this work, Monte Carlo simulations were used to quantitatively determine net surface interactions, binding valency, and selectivity between targeted nanoparticles and cell surfaces. Dissociation constant, KD, and target membrane protein density, ρR, are explored over a range representative of healthy and cancerous cell surfaces. Our findings show highly selective binding to diseased cell surfaces can be achieved with multiple, weaker affinity targeting ligands that can be further optimized by varying the targeting ligand density, ρL. Using the approach developed in this work, nanomedicines can be optimally designed for exclusively targeting diseased cells and tissues.Ligand-functionalized nanoparticles capable of selectively binding to diseased versus healthy cell populations are attractive for improved efficacy of nanoparticle-based drug and gene therapies. However, nanoparticles functionalized with high affinity targeting ligands may lead to undesired off-target binding to healthy cells. In this work, Monte Carlo simulations were used to quantitatively determine net surface interactions, binding valency, and selectivity between targeted nanoparticles and cell surfaces. Dissociation constant, KD, and target membrane protein density, ρR, are explored over a range representative of healthy and cancerous cell surfaces. Our findings show highly selective binding to diseased cell surfaces can be achieved with multiple, weaker affinity targeting ligands that can be further optimized by varying the targeting ligand density, ρL. Using the approach developed in this work, nanomedicines can be optimally designed for exclusively targeting
Molecular Targets for Antiepileptic Drug Development

PubMed Central

Meldrum, Brian S.; Rogawski, Michael A.

2007-01-01

Summary This review considers how recent advances in the physiology of ion channels and other potential molecular targets, in conjunction with new information on the genetics of idiopathic epilepsies, can be applied to the search for improved antiepileptic drugs (AEDs). Marketed AEDs predominantly target voltage-gated cation channels (the α subunits of voltage-gated Na+ channels and also T-type voltage-gated Ca2+ channels) or influence GABA-mediated inhibition. Recently, α2–δ voltage-gated Ca2+ channel subunits and the SV2A synaptic vesicle protein have been recognized as likely targets. Genetic studies of familial idiopathic epilepsies have identified numerous genes associated with diverse epilepsy syndromes, including genes encoding Na+ channels and GABAA receptors, which are known AED targets. A strategy based on genes associated with epilepsy in animal models and humans suggests other potential AED targets, including various voltage-gated Ca2+ channel subunits and auxiliary proteins, A- or M-type voltage-gated K+ channels, and ionotropic glutamate receptors. Recent progress in ion channel research brought about by molecular cloning of the channel subunit proteins and studies in epilepsy models suggest additional targets, including G-protein-coupled receptors, such as GABAB and metabotropic glutamate receptors; hyperpolarization-activated cyclic nucleotide-gated cation (HCN) channel subunits, responsible for hyperpolarization-activated current Ih; connexins, which make up gap junctions; and neurotransmitter transporters, particularly plasma membrane and vesicular transporters for GABA and glutamate. New information from the structural characterization of ion channels, along with better understanding of ion channel function, may allow for more selective targeting. For example, Na+ channels underlying persistent Na+ currents or GABAA receptor isoforms responsible for tonic (extrasynaptic) currents represent attractive targets. The growing understanding of the
Using in Vitro Evolution and Whole Genome Analysis To Discover Next Generation Targets for Antimalarial Drug Discovery

PubMed Central

2018-01-01

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

PubMed

Stephen, Preyesh; Lin, Sheng-Xiang

2018-01-01

Since the first major outbreak of Zika virus (ZIKV) in 2007, ZIKV is spreading explosively through South and Central America, and recent reports in highly populated developing countries alarm the possibility of a more catastrophic outbreak. ZIKV infection in pregnant women leads to embryonic microcephaly and Guillain-Barré syndrome in adults. At present, there is limited understanding of the infectious mechanism, and no approved therapy has been reported. Despite the withdrawal of public health emergency, the WHO still considers the ZIKV as a highly significant and long-term public health challenge that the situation has to be addressed rapidly. Non-structural protein 5 is essential for capping and replication of viral RNA and comprises a methyltransferase and RNA-dependent RNA polymerase (RdRp) domain. We used molecular modeling to obtain the structure of ZIKV RdRp, and by molecular docking and phylogeny analysis, we here demonstrate the potential sites for drug screening. Two metal binding sites and an NS3-interacting region in ZIKV RdRp are demonstrated as potential drug screening sites. The docked structures reveal a remarkable degree of conservation at the substrate binding site and the potential drug screening sites. A phylogeny-based approach is provided for an emergency preparedness, where similar class of ligands could target phylogenetically related proteins. © 2017 John Wiley & Sons A/S.
The application of antitumor drug-targeting models on liver cancer.

PubMed

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

2016-06-01

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

PubMed Central

Bhatia, Sangeeta N.; Sailor, Michael J.

2010-01-01

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

PubMed

Masood, Farha

2016-03-01

A targeted delivery system based on the polymeric nanoparticles as a drug carrier represents a marvelous avenue for cancer therapy. The pivotal characteristics of this system include biodegradability, biocompatibility, non-toxicity, prolonged circulation and a wide payload spectrum of a therapeutic agent. Other outstanding features are their distinctive size and shape properties for tissue penetration via an active and passive targeting, specific cellular/subcellular trafficking pathways and facile control of cargo release by sophisticated material engineering. In this review, the current implications of encapsulation of anticancer agents within polyhydroxyalkanoates, poly-(lactic-co-glycolic acid) and cyclodextrin based nanoparticles to precisely target the tumor site, i.e., cell, tissue and organ are highlighted. Furthermore, the promising perspectives in this emerging field are discussed. Copyright © 2015 Elsevier B.V. All rights reserved.
LHRH-Targeted Drug Delivery Systems for Cancer Therapy.

PubMed

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

2017-01-01

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

PubMed Central

Harrold, JM; Ramanathan, M; Mager, DE

2015-01-01

Identification of novel targets is a critical first step in the drug discovery and development process. Most diseases such as cancer, metabolic disorders, and neurological disorders are complex, and their pathogenesis involves multiple genetic and environmental factors. Finding a viable drug target–drug combination with high potential for yielding clinical success within the efficacy–toxicity spectrum is extremely challenging. Many examples are now available in which network-based approaches show potential for the identification of novel targets and for the repositioning of established targets. The objective of this article is to highlight network approaches for identifying novel targets with greater chances of gaining approved drugs with maximal efficacy and minimal side effects. Further enhancement of these approaches may emerge from effectively integrating computational systems biology with pharmacodynamic systems analysis. Coupling genomics, proteomics, and metabolomics databases with systems pharmacology modeling may aid in the development of disease-specific networks that can be further used to build confidence in target identification. PMID:24025802
P2X Receptors as Drug Targets

PubMed Central

Jarvis, Michael F.

2013-01-01

The study of P2X receptors has long been handicapped by a poverty of small-molecule tools that serve as selective agonists and antagonists. There has been progress, particularly in the past 10 years, as cell-based high-throughput screening methods were applied, together with large chemical libraries. This has delivered some drug-like molecules in several chemical classes that selectively target P2X1, P2X3, or P2X7 receptors. Some of these are, or have been, in clinical trials for rheumatoid arthritis, pain, and cough. Current preclinical research programs are studying P2X receptor involvement in pain, inflammation, osteoporosis, multiple sclerosis, spinal cord injury, and bladder dysfunction. The determination of the atomic structure of P2X receptors in closed and open (ATP-bound) states by X-ray crystallography is now allowing new approaches by molecular modeling. This is supported by a large body of previous work using mutagenesis and functional expression, and is now being supplemented by molecular dynamic simulations and in silico ligand docking. These approaches should lead to P2X receptors soon taking their place alongside other ion channel proteins as therapeutically important drug targets. PMID:23253448
Drug-repositioning opportunities for cancer therapy: novel molecular targets for known compounds.

PubMed

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

2016-01-01

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

PubMed Central

Brecher, Matthew; Zhang, Jing; Li, Hongmin

2014-01-01

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

PubMed

Brecher, Matthew; Zhang, Jing; Li, Hongmin

2013-12-01

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

PubMed

Lee, Yoon Hyeok; Choi, Hojae; Park, Seongyong; Lee, Boah; Yi, Gwan-Su

2017-05-31

Recently, the metabolite-likeness of the drug space has emerged and has opened a new possibility for exploring human metabolite-like candidates in drug discovery. However, the applicability of metabolite-likeness in drug discovery has been largely unexplored. Moreover, there are no reports on its applications for the repositioning of drugs to possible enzyme modulators, although enzyme-drug relations could be directly inferred from the similarity relationships between enzyme's metabolites and drugs. We constructed a drug-metabolite structural similarity matrix, which contains 1,861 FDA-approved drugs and 1,110 human intermediary metabolites scored with the Tanimoto similarity. To verify the metabolite-likeness measure for drug repositioning, we analyzed 17 known antimetabolite drugs that resemble the innate metabolites of their eleven target enzymes as the gold standard positives. Highly scored drugs were selected as possible modulators of enzymes for their corresponding metabolites. Then, we assessed the performance of metabolite-likeness with a receiver operating characteristic analysis and compared it with other drug-target prediction methods. We set the similarity threshold for drug repositioning candidates of new enzyme modulators based on maximization of the Youden's index. We also carried out literature surveys for supporting the drug repositioning results based on the metabolite-likeness. In this paper, we applied metabolite-likeness to repurpose FDA-approved drugs to disease-associated enzyme modulators that resemble human innate metabolites. All antimetabolite drugs were mapped with their known 11 target enzymes with statistically significant similarity values to the corresponding metabolites. The comparison with other drug-target prediction methods showed the higher performance of metabolite-likeness for predicting enzyme modulators. After that, the drugs scored higher than similarity score of 0.654 were selected as possible modulators of enzymes for
Advanced targeted therapies in cancer: Drug nanocarriers, the future of chemotherapy.

PubMed

Pérez-Herrero, Edgar; Fernández-Medarde, Alberto

2015-06-01

Cancer is the second worldwide cause of death, exceeded only by cardiovascular diseases. It is characterized by uncontrolled cell proliferation and an absence of cell death that, except for hematological cancers, generates an abnormal cell mass or tumor. This primary tumor grows thanks to new vascularization and, in time, acquires metastatic potential and spreads to other body sites, which causes metastasis and finally death. Cancer is caused by damage or mutations in the genetic material of the cells due to environmental or inherited factors. While surgery and radiotherapy are the primary treatment used for local and non-metastatic cancers, anti-cancer drugs (chemotherapy, hormone and biological therapies) are the choice currently used in metastatic cancers. Chemotherapy is based on the inhibition of the division of rapidly growing cells, which is a characteristic of the cancerous cells, but unfortunately, it also affects normal cells with fast proliferation rates, such as the hair follicles, bone marrow and gastrointestinal tract cells, generating the characteristic side effects of chemotherapy. The indiscriminate destruction of normal cells, the toxicity of conventional chemotherapeutic drugs, as well as the development of multidrug resistance, support the need to find new effective targeted treatments based on the changes in the molecular biology of the tumor cells. These novel targeted therapies, of increasing interest as evidenced by FDA-approved targeted cancer drugs in recent years, block biologic transduction pathways and/or specific cancer proteins to induce the death of cancer cells by means of apoptosis and stimulation of the immune system, or specifically deliver chemotherapeutic agents to cancer cells, minimizing the undesirable side effects. Although targeted therapies can be achieved directly by altering specific cell signaling by means of monoclonal antibodies or small molecules inhibitors, this review focuses on indirect targeted approaches that
Discovery of novel drug targets and their functions using phenotypic screening of natural products.

PubMed

Chang, Junghwa; Kwon, Ho Jeong

2016-03-01

Natural products are valuable resources that provide a variety of bioactive compounds and natural pharmacophores in modern drug discovery. Discovery of biologically active natural products and unraveling their target proteins to understand their mode of action have always been critical hurdles for their development into clinical drugs. For effective discovery and development of bioactive natural products into novel therapeutic drugs, comprehensive screening and identification of target proteins are indispensable. In this review, a systematic approach to understanding the mode of action of natural products isolated using phenotypic screening involving chemical proteomics-based target identification is introduced. This review highlights three natural products recently discovered via phenotypic screening, namely glucopiericidin A, ecumicin, and terpestacin, as representative case studies to revisit the pivotal role of natural products as powerful tools in discovering the novel functions and druggability of targets in biological systems and pathological diseases of interest.
Application of liposomes in drug development — focus on gastroenterological targets

PubMed Central

Zhang, Jian-Xin; Wang, Kun; Mao, Zheng-Fa; Fan, Xin; Jiang, De-Li; Chen, Min; Cui, Lei; Sun, Kang; Dang, Sheng-Chun

2013-01-01

Over the past decade, liposomes became a focal point in developing drug delivery systems. New liposomes, with novel lipid molecules or conjugates, and new formulations opened possibilities for safely and efficiently treating many diseases including cancers. New types of liposomes can prolong circulation time or specifically deliver drugs to therapeutic targets. This article concentrates on current developments in liposome based drug delivery systems for treating diseases of the gastrointestinal tract. We will review different types and uses of liposomes in the development of therapeutics for gastrointestinal diseases including inflammatory bowel diseases and colorectal cancer. PMID:23630417
Targeting the extracellular matrix of ovarian cancer using functionalized, drug loaded lyophilisomes.

PubMed

van der Steen, Sophieke C H A; Raavé, René; Langerak, Sjoerd; van Houdt, Laurens; van Duijnhoven, Sander M J; van Lith, Sanne A M; Massuger, Leon F A G; Daamen, Willeke F; Leenders, William P; van Kuppevelt, Toin H

2017-04-01

Epithelial ovarian cancer is characterized by a high mortality rate and is in need for novel therapeutic avenues to improve patient outcome. The tumor's extracellular matrix ("stroma") offers new possibilities for targeted drug-delivery. Recently we identified highly sulfated chondroitin sulfate (CS-E) as a component abundantly present in the ovarian cancer extracellular matrix, and as a novel target for anti-cancer therapy. Here, we report on the functionalization of drug-loaded lyophilisomes (albumin-based biocapsules) to specifically target the stroma of ovarian carcinomas with the potential to eliminate cancer cells. To achieve specific targeting, we conjugated single chain antibodies reactive with CS-E to lyophilisomes using a two-step approach comprising sortase-mediated ligation and bioorthogonal click chemistry. Antibody-functionalized lyophilisomes specifically targeted the ovarian cancer stroma through CS-E. In a CS-E rich micro-environment in vitro lyophilisomes induced cell death by extracellular release of doxorubicin which localized to the nucleus. Immunohistochemistry identified CS-E rich stroma in a variety of solid tumors other than ovarian cancer, including breast, lung and colon cancer indicating the potential versatility of matrix therapy and the use of highly sulfated chondroitin sulfates in cancer stroma as a micro-environmental hook for targeted drug delivery. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Retrieval of Enterobacteriaceae drug targets using singular value decomposition.

PubMed

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

2015-04-15

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

PubMed

Finan, Chris; Gaulton, Anna; Kruger, Felix A; Lumbers, R Thomas; Shah, Tina; Engmann, Jorgen; Galver, Luana; Kelley, Ryan; Karlsson, Anneli; Santos, Rita; Overington, John P; Hingorani, Aroon D; Casas, Juan P

2017-03-29

Target identification (determining the correct drug targets for a disease) and target validation (demonstrating an effect of target perturbation on disease biomarkers and disease end points) are important steps in drug development. Clinically relevant associations of variants in genes encoding drug targets model the effect of modifying the same targets pharmacologically. To delineate drug development (including repurposing) opportunities arising from this paradigm, we connected complex disease- and biomarker-associated loci from genome-wide association studies to an updated set of genes encoding druggable human proteins, to agents with bioactivity against these targets, and, where there were licensed drugs, to clinical indications. We used this set of genes to inform the design of a new genotyping array, which will enable association studies of druggable genes for drug target selection and validation in human disease. Copyright © 2017, American Association for the Advancement of Science.
Polymeric micelles with stimuli-triggering systems for advanced cancer drug targeting.

PubMed

Nakayama, Masamichi; Akimoto, Jun; Okano, Teruo

2014-08-01

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

PubMed

Lee, Min Hee; Sharma, Amit; Chang, Min Jung; Lee, Jinju; Son, Subin; Sessler, Jonathan L; Kang, Chulhun; Kim, Jong Seung

2018-01-02

Theranostic systems are receiving ever-increasing attention due to their potential therapeutic utility, imaging enhancement capability, and promise for advancing the field of personalized medicine, particularly as it relates to the diagnosis, staging, and treatment of cancer. In this Tutorial Review, we provide an introduction to the concepts of theranostic drug delivery effected via use of conjugates that are able to target cancer cells selectively, provide cytotoxic chemotherapeutics, and produce readily monitored imaging signals in vitro and in vivo. The underlying design concepts, requiring the synthesis of conjugates composed of imaging reporters, masked chemotherapeutic drugs, cleavable linkers, and cancer targeting ligands, are discussed. Particular emphasis is placed on highlighting the potential benefits of fluorogenic reaction-based targeted systems that are activated for both imaging and therapy by cellular entities, e.g., thiols, reactive oxygen species and enzymes, which are present at relatively elevated levels in tumour environments, physiological characteristics of cancer, e.g., hypoxia and acidic pH. Also discussed are systems activated by an external stimulus, such as light. The work summarized in this Tutorial Review will help define the role fluorogenic reaction-based, cancer-targeting theranostics may have in advancing drug discovery efforts, as well as improving our understanding of cellular uptake and drug release mechanisms.
Computational and Pharmacological Target of Neurovascular Unit for Drug Design and Delivery

PubMed Central

2015-01-01

The blood-brain barrier (BBB) is a dynamic and highly selective permeable interface between central nervous system (CNS) and periphery that regulates the brain homeostasis. Increasing evidences of neurological disorders and restricted drug delivery process in brain make BBB as special target for further study. At present, neurovascular unit (NVU) is a great interest and highlighted topic of pharmaceutical companies for CNS drug design and delivery approaches. Some recent advancement of pharmacology and computational biology makes it convenient to develop drugs within limited time and affordable cost. In this review, we briefly introduce current understanding of the NVU, including molecular and cellular composition, physiology, and regulatory function. We also discuss the recent technology and interaction of pharmacogenomics and bioinformatics for drug design and step towards personalized medicine. Additionally, we develop gene network due to understand NVU associated transporter proteins interactions that might be effective for understanding aetiology of neurological disorders and new target base protective therapies development and delivery. PMID:26579539
Study of the efficacy of antimalarial drugs delivered inside targeted immunoliposomal nanovectors

NASA Astrophysics Data System (ADS)

Urbán, Patricia; Estelrich, Joan; Adeva, Alberto; Cortés, Alfred; Fernàndez-Busquets, Xavier

2011-12-01

Paul Ehrlich's dream of a 'magic bullet' that would specifically destroy invading microbes is now a major aspect of clinical medicine. However, a century later, the implementation of this medical holy grail continues being a challenge in three main fronts: identifying the right molecular or cellular targets for a particular disease, having a drug that is effective against it, and finding a strategy for the efficient delivery of sufficient amounts of the drug in an active state exclusively to the selected targets. In a previous work, we engineered an immunoliposomal nanovector for the targeted delivery of its contents exclusively to Plasmodium falciparum-infected red blood cells [pRBCs]. In preliminary assays, the antimalarial drug chloroquine showed improved efficacy when delivered inside immunoliposomes targeted with the pRBC-specific monoclonal antibody BM1234. Because difficulties in determining the exact concentration of the drug due to its low amounts prevented an accurate estimation of the nanovector performance, here, we have developed an HPLC-based method for the precise determination of the concentrations in the liposomal preparations of chloroquine and of a second antimalarial drug, fosmidomycin. The results obtained indicate that immunoliposome encapsulation of chloroquine and fosmidomycin improves by tenfold the efficacy of antimalarial drugs. The targeting antibody used binds preferentially to pRBCs containing late maturation stages of the parasite. In accordance with this observation, the best performing immunoliposomes are those added to Plasmodium cultures having a larger number of late form-containing pRBCs. An average of five antibody molecules per liposome significantly improves in cell cultures the performance of immunoliposomes over non-functionalized liposomes as drug delivery vessels. Increasing the number of antibodies on the liposome surface correspondingly increases performance, with a reduction of 50% parasitemia achieved with
Adverse drug reaction prediction using scores produced by large-scale drug-protein target docking on high-performance computing machines.

PubMed

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

2014-01-01

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

PubMed

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

2016-05-01

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

PubMed

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.
Breakable mesoporous silica nanoparticles for targeted drug delivery

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

PubMed

Huang, Yu-An; You, Zhu-Hong; Chen, Xing

2018-01-01

Drug-Target Interactions (DTI) play a crucial role in discovering new drug candidates and finding new proteins to target for drug development. Although the number of detected DTI obtained by high-throughput techniques has been increasing, the number of known DTI is still limited. On the other hand, the experimental methods for detecting the interactions among drugs and proteins are costly and inefficient. Therefore, computational approaches for predicting DTI are drawing increasing attention in recent years. In this paper, we report a novel computational model for predicting the DTI using extremely randomized trees model and protein amino acids information. More specifically, the protein sequence is represented as a Pseudo Substitution Matrix Representation (Pseudo-SMR) descriptor in which the influence of biological evolutionary information is retained. For the representation of drug molecules, a novel fingerprint feature vector is utilized to describe its substructure information. Then the DTI pair is characterized by concatenating the two vector spaces of protein sequence and drug substructure. Finally, the proposed method is explored for predicting the DTI on four benchmark datasets: Enzyme, Ion Channel, GPCRs and Nuclear Receptor. The experimental results demonstrate that this method achieves promising prediction accuracies of 89.85%, 87.87%, 82.99% and 81.67%, respectively. For further evaluation, we compared the performance of Extremely Randomized Trees model with that of the state-of-the-art Support Vector Machine classifier. And we also compared the proposed model with existing computational models, and confirmed 15 potential drug-target interactions by looking for existing databases. The experiment results show that the proposed method is feasible and promising for predicting drug-target interactions for new drug candidate screening based on sizeable features. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Multiple polysaccharide-drug complex-loaded liposomes: A unique strategy in drug loading and cancer targeting.

PubMed

Ruttala, Hima Bindu; Ramasamy, Thiruganesh; Gupta, Biki; Choi, Han-Gon; Yong, Chul Soon; Kim, Jong Oh

2017-10-01

In the present study, a unique strategy was developed to develop nanocarriers containing multiple therapeutics with controlled release characteristics. In this study, we demonstrated the synthesis of dextran sulfate-doxorubicin (DS-DOX) and alginate-cisplatin (AL-CIS) polymer-drug complexes to produce a transferrin ligand-conjugated liposome. The targeted nanoparticles (TL-DDAC) were nano-sized and spherical. The targeted liposome exhibited a specific receptor-mediated endocytic uptake in cancer cells. The enhanced cellular uptake of TL-DDAC resulted in a significantly better anticancer effect in resistant and sensitive breast cancer cells compared to that of the free drugs. Specifically, DOX and CIS at a molar ratio of 1:1 exhibited better therapeutic performance compared to that of other combinations. The combination of an anthracycline-based topoisomerase II inhibitor (DOX) and a platinum compound (CIS) resulted in significantly higher cell apoptosis (early and late) in both types of cancer cells. In conclusion, treatment with DS-DOX and AL-CIS based combination liposomes modified with transferrin (TL-DDAC) was an effective cancer treatment strategy. Further investigation in clinically relevant animal models is warranted to prove the therapeutic efficacy of this unique strategy. Copyright © 2017 Elsevier Ltd. All rights reserved.
Activity-based proteome profiling of potential cellular targets of Orlistat--an FDA-approved drug with anti-tumor activities.

PubMed

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

2010-01-20

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

PubMed

Gagliardi, Mariacristina

2017-03-01

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

DTIC Science & Technology

2012-01-01

target representatives. Target profiles were then generated for a given query molecule by computing maximal shape/ chemistry overlap between the query...molecule and the drug sets assigned to each protein target. The overlap was computed using the program ROCS (Rapid Overlay of Chemical Structures ). We...approaches in off-target prediction has been reviewed.9,10 Many structure -based target fishing (SBTF) approaches, such as INVDOCK11 and Target Fishing Dock
Targeting the latest hallmark of cancer: another attempt at 'magic bullet' drugs targeting cancers' metabolic phenotype.

PubMed

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

2012-10-01

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

PubMed

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

2006-01-01

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

PubMed

Torchilin, V P

2004-10-01

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

PubMed

Lu, Nan; Tian, Ying; Tian, Wei; Huang, Peng; Liu, Ying; Tang, Yuxia; Wang, Chunyan; Wang, Shouju; Su, Yunyan; Zhang, Yunlei; Pan, Jing; Teng, Zhaogang; Lu, Guangming

2016-02-10

The integration of diagnosis and therapy into one nanoplatform, known as theranostics, has attracted increasing attention in the biomedical areas. Herein, we first present a cancer cell targeting imaging and drug delivery system based on engineered thioether-bridged periodic mesoporous organosilica nanoparticles (PMOs). The PMOs are stably and selectively conjugated with near-infrared fluorescence (NIRF) dye Cyanine 5.5 (Cy5.5) and anti-Her2 affibody on the outer surfaces to endow them with excellent NIRF imaging and cancer targeting properties. Also, taking the advantage of the thioether-group-incorporated mesopores, the release of chemotherapy drug doxorubicin (DOX) loaded in the PMOs is responsive to the tumor-related molecule glutathione (GSH). The drug release percentage reaches 84.8% in 10 mM of GSH solution within 24 h, which is more than 2-fold higher than that without GSH. In addition, the drug release also exhibits pH-responsive, which reaches 53.6% at pH 5 and 31.7% at pH 7.4 within 24 h. Confocal laser scanning microscopy and flow cytometry analysis demonstrate that the PMOs-based theranostic platforms can efficiently target to and enter Her2 positive tumor cells. Thus, the smart imaging and drug delivery nanoplatforms induce high tumor cell growth inhibition. Meanwhile, the Cy5.5 conjugated PMOs perform great NIRF imaging ability, which could monitor the intracellular distribution, delivery and release of the chemotherapy drug. In addition, cell viability and histological assessments show the engineered PMOs have good biocompatibility, further encouraging the following biomedical applications. Over all, the systemically engineered PMOs can serve as a novel cancer cell targeting imaging and drug delivery platform with NIRF imaging, GSH and pH dual-responsive drug release, and high tumor cell targeting ability.
A smart multifunctional drug delivery nanoplatform for targeting cancer cells

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

Carbon Nanotubes: An Emerging Drug Carrier for Targeting Cancer Cells

PubMed Central

Bhattacharya, Shiv Sankar; Mishra, Arun Kumar; Verma, Navneet; Verma, Anurag; Pandit, Jayanta Kumar

2014-01-01

During recent years carbon nanotubes (CNTs) have been attracted by many researchers as a drug delivery carrier. CNTs are the third allotropic form of carbon-fullerenes which were rolled into cylindrical tubes. To be integrated into the biological systems, CNTs can be chemically modified or functionalised with therapeutically active molecules by forming stable covalent bonds or supramolecular assemblies based on noncovalent interactions. Owing to their high carrying capacity, biocompatibility, and specificity to cells, various cancer cells have been explored with CNTs for evaluation of pharmacokinetic parameters, cell viability, cytotoxicty, and drug delivery in tumor cells. This review attempts to highlight all aspects of CNTs which render them as an effective anticancer drug carrier and imaging agent. Also the potential application of CNT in targeting metastatic cancer cells by entrapping biomolecules and anticancer drugs has been covered in this review. PMID:24872894
Bacterial Transcription as a Target for Antibacterial Drug Development

PubMed Central

Ma, Cong; Yang, Xiao

2016-01-01

SUMMARY Transcription, the first step of gene expression, is carried out by the enzyme RNA polymerase (RNAP) and is regulated through interaction with a series of protein transcription factors. RNAP and its associated transcription factors are highly conserved across the bacterial domain and represent excellent targets for broad-spectrum antibacterial agent discovery. Despite the numerous antibiotics on the market, there are only two series currently approved that target transcription. The determination of the three-dimensional structures of RNAP and transcription complexes at high resolution over the last 15 years has led to renewed interest in targeting this essential process for antibiotic development by utilizing rational structure-based approaches. In this review, we describe the inhibition of the bacterial transcription process with respect to structural studies of RNAP, highlight recent progress toward the discovery of novel transcription inhibitors, and suggest additional potential antibacterial targets for rational drug design. PMID:26764017
Reservoir-Based Drug Delivery Systems Utilizing Microtechnology

PubMed Central

Stevenson, Cynthia L.; Santini, John T.; Langer, Robert

2012-01-01

This review covers reservoir-based drug delivery systems that incorporate microtechnology, with an emphasis on oral, dermal, and implantable systems. Key features of each technology are highlighted such as working principles, fabrication methods, dimensional constraints, and performance criteria. Reservoir-based systems include a subset of microfabricated drug delivery systems and provide unique advantages. Reservoirs, whether external to the body or implanted, provide a well-controlled environment for a drug formulation, allowing increased drug stability and prolonged delivery times. Reservoir systems have the flexibility to accommodate various delivery schemes, including zero order, pulsatile, and on demand dosing, as opposed to a standard sustained release profile. Furthermore, the development of reservoir-based systems for targeted delivery for difficult to treat applications (e.g., ocular) has resulted in potential platforms for patient therapy. PMID:22465783
‘One-pot’ synthesis of multifunctional GSH-CdTe quantum dots for targeted drug delivery

NASA Astrophysics Data System (ADS)

Chen, Xiaoqin; Tang, Yajun; Cai, Bing; Fan, Hongsong

2014-06-01

A novel quantum dots-based multifunctional nanovehicle (DOX-QD-PEG-FA) was designed for targeted drug delivery, fluorescent imaging, tracking, and cancer therapy, in which the GSH-CdTe quantum dots play a key role in imaging and drug delivery. To exert curative effects, the antineoplastic drug doxorubicin hydrochloride (DOX) was loaded on the GSH-CdTe quantum dots through a condensation reaction. Meanwhile, a polyethylene glycol (PEG) shell was introduced to wrap the DOX-QD, thus stabilizing the structure and preventing clearance and drug release during systemic circulation. To actively target cancer cells and prevent the nanovehicles from being absorbed by normal cells, the nanoparticles were further decorated with folic acid (FA), allowing them to target HeLa cells that express the FA receptor. The multifunctional DOX-QD-PEG-FA conjugates were simply prepared using the ‘one pot’ method. In vitro study demonstrated that this simple, multifunctional nanovehicle can deliver DOX to the targeted cancer cells and localize the nanoparticles. After reaching the tumor cells, the FA on the DOX-QD-PEG surface allowed folate receptor recognition and increased the drug concentration to realize a higher curative effect. This novel, multifunctional DOX-QD-PEG-FA system shows great potential for tumor imaging, targeting, and therapy.
Large-Scale Off-Target Identification Using Fast and Accurate Dual Regularized One-Class Collaborative Filtering and Its Application to Drug Repurposing.

PubMed

Lim, Hansaim; Poleksic, Aleksandar; Yao, Yuan; Tong, Hanghang; He, Di; Zhuang, Luke; Meng, Patrick; Xie, Lei

2016-10-01

Target-based screening is one of the major approaches in drug discovery. Besides the intended target, unexpected drug off-target interactions often occur, and many of them have not been recognized and characterized. The off-target interactions can be responsible for either therapeutic or side effects. Thus, identifying the genome-wide off-targets of lead compounds or existing drugs will be critical for designing effective and safe drugs, and providing new opportunities for drug repurposing. Although many computational methods have been developed to predict drug-target interactions, they are either less accurate than the one that we are proposing here or computationally too intensive, thereby limiting their capability for large-scale off-target identification. In addition, the performances of most machine learning based algorithms have been mainly evaluated to predict off-target interactions in the same gene family for hundreds of chemicals. It is not clear how these algorithms perform in terms of detecting off-targets across gene families on a proteome scale. Here, we are presenting a fast and accurate off-target prediction method, REMAP, which is based on a dual regularized one-class collaborative filtering algorithm, to explore continuous chemical space, protein space, and their interactome on a large scale. When tested in a reliable, extensive, and cross-gene family benchmark, REMAP outperforms the state-of-the-art methods. Furthermore, REMAP is highly scalable. It can screen a dataset of 200 thousands chemicals against 20 thousands proteins within 2 hours. Using the reconstructed genome-wide target profile as the fingerprint of a chemical compound, we predicted that seven FDA-approved drugs can be repurposed as novel anti-cancer therapies. The anti-cancer activity of six of them is supported by experimental evidences. Thus, REMAP is a valuable addition to the existing in silico toolbox for drug target identification, drug repurposing, phenotypic screening, and
Large-Scale Off-Target Identification Using Fast and Accurate Dual Regularized One-Class Collaborative Filtering and Its Application to Drug Repurposing

PubMed Central

Poleksic, Aleksandar; Yao, Yuan; Tong, Hanghang; Meng, Patrick; Xie, Lei

2016-01-01

Target-based screening is one of the major approaches in drug discovery. Besides the intended target, unexpected drug off-target interactions often occur, and many of them have not been recognized and characterized. The off-target interactions can be responsible for either therapeutic or side effects. Thus, identifying the genome-wide off-targets of lead compounds or existing drugs will be critical for designing effective and safe drugs, and providing new opportunities for drug repurposing. Although many computational methods have been developed to predict drug-target interactions, they are either less accurate than the one that we are proposing here or computationally too intensive, thereby limiting their capability for large-scale off-target identification. In addition, the performances of most machine learning based algorithms have been mainly evaluated to predict off-target interactions in the same gene family for hundreds of chemicals. It is not clear how these algorithms perform in terms of detecting off-targets across gene families on a proteome scale. Here, we are presenting a fast and accurate off-target prediction method, REMAP, which is based on a dual regularized one-class collaborative filtering algorithm, to explore continuous chemical space, protein space, and their interactome on a large scale. When tested in a reliable, extensive, and cross-gene family benchmark, REMAP outperforms the state-of-the-art methods. Furthermore, REMAP is highly scalable. It can screen a dataset of 200 thousands chemicals against 20 thousands proteins within 2 hours. Using the reconstructed genome-wide target profile as the fingerprint of a chemical compound, we predicted that seven FDA-approved drugs can be repurposed as novel anti-cancer therapies. The anti-cancer activity of six of them is supported by experimental evidences. Thus, REMAP is a valuable addition to the existing in silico toolbox for drug target identification, drug repurposing, phenotypic screening, and
Application of chemical biology in target identification and drug discovery.

PubMed

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

2015-09-01

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

PubMed

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

2009-05-01

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

PubMed Central

Yucel, Tuna; Lovett, Michael L.; Kaplan, David L.

2014-01-01

Silk presents a rare combination of desirable properties for sustained drug delivery, including aqueous-based purification and processing options without chemical cross-linkers, compatibility with common sterilization methods, controllable and surface-mediated biodegradation into non-inflammatory by-products, biocompatibility, utility in drug stabilization, and robust mechanical properties. A versatile silk-based toolkit is currently available for sustained drug delivery formulations of small molecule through macromolecular drugs, with a promise to mitigate several drawbacks associated with other degradable sustained delivery technologies in the market. Silk-based formulations utilize silk’s well-defined nano- through microscale structural hierarchy, stimuli-responsive self-assembly pathways and crystal polymorphism, as well as sequence and genetic modification options towards targeted pharmaceutical outcomes. Furthermore, by manipulating the interactions between silk and drug molecules, near-zero order sustained release may be achieved through diffusion- and degradation-based release mechanisms. Because of these desirable properties, there has been increasing industrial interest in silk-based drug delivery systems currently at various stages of the developmental pipeline from pre-clinical to FDA-approved products. Here, we discuss the unique aspects of silk technology as a sustained drug delivery platform and highlight the current state of the art in silk-based drug delivery. We also offer a potential early development pathway for silk-based sustained delivery products. PMID:24910193
A comparison of machine learning techniques for detection of drug target articles.

PubMed

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

2010-12-01

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

PubMed

Vauquelin, Georges

2016-08-01

Optimal drug therapy often requires continuing high levels of target occupancy. Besides the traditional pharmacokinetic contribution, target binding kinetics is increasingly considered to play an important role as well. While most attention has been focused on the dissociation rate of the complex, recent reports expressed doubt about the unreserved translatability of this pharmacodynamic property into clinical efficacy. 'Micro'-pharmacokinetic mechanisms like drug rebinding and partitioning into the cell membrane may constitute a potential fix. Simulations were based on solving differential equations. Based on a selected range of association and dissociation rate constants, kon and koff , and rebinding potencies of the drugs as variables, their effects on the temporal in vivo occupancy profile of their targets, after one or multiple repetitive dosings, have here been simulated. Most strikingly, the simulations show that, when rebinding is also taken into account, increasing kon may produce closely the same outcome as decreasing koff when dosing is performed in accordance with the therapeutically most relevant constant [Lmax ]/KD ratio paradigm. Also, under certain conditions, rebinding may produce closely the same outcome as invoking slow diffusion of the drug between the plasma compartment and a target-containing 'effect' compartment. Although the present simulations should only be regarded as a 'proof of principle', these findings may help pharmacologists and medicinal chemists to devise ex vivo and in vitro binding kinetic assays that are more relevant and translatable to in vivo settings. © 2016 The British Pharmacological Society.
Synthetic lipoprotein as nano-material vehicle in the targeted drug delivery.

PubMed

Zhang, Xueqin; Huang, Gangliang

2017-12-01

High-density lipoprotein (HDL) and low-density lipoprotein (LDL), as human endogenous lipoprotein particles, have low toxicity, high selectivity, and good safety. They can avoid the recognition and clearance of human reticuloendothelial system. These synthetic lipoproteins (sLPs) have been attracted extensive attention as the nanovectors for tumor-targeted drug and gene delivery. Herein, recent advances in the field of anticancer based on these two lipid proteins and recombinant lipoproteins (rLPs) as target delivery vectors were analyzed and discussed.
Folate-conjugated boron nitride nanospheres for targeted delivery of anticancer drugs.

PubMed

Feng, Shini; Zhang, Huijie; Yan, Ting; Huang, Dandi; Zhi, Chunyi; Nakanishi, Hideki; Gao, Xiao-Dong

With its unique physical and chemical properties and structural similarity to carbon, boron nitride (BN) has attracted considerable attention and found many applications. Biomedical applications of BN have recently started to emerge, raising great hopes in drug and gene delivery. Here, we developed a targeted anticancer drug delivery system based on folate-conjugated BN nanospheres (BNNS) with receptor-mediated targeting. Folic acid (FA) was successfully grafted onto BNNS via esterification reaction. In vitro cytotoxicity assay showed that BNNS-FA complexes were non-toxic to HeLa cells up to a concentration of 100 μg/mL. Then, doxorubicin hydrochloride (DOX), a commonly used anticancer drug, was loaded onto BNNS-FA complexes. BNNS-FA/DOX complexes were stable at pH 7.4 but effectively released DOX at pH 5.0, which exhibited a pH sensitive and sustained release pattern. BNNS-FA/DOX complexes could be recognized and specifically internalized by HeLa cells via FA receptor-mediated endocytosis. BNNS-FA/DOX complexes exhibited greater cytotoxicity to HeLa cells than free DOX and BNNS/DOX complexes due to the increased cellular uptake of DOX mediated by the FA receptor. Therefore, BNNS-FA complexes had strong potential for targeted cancer therapy.
Folate-conjugated boron nitride nanospheres for targeted delivery of anticancer drugs

PubMed Central

Feng, Shini; Zhang, Huijie; Yan, Ting; Huang, Dandi; Zhi, Chunyi; Nakanishi, Hideki; Gao, Xiao-Dong

2016-01-01

With its unique physical and chemical properties and structural similarity to carbon, boron nitride (BN) has attracted considerable attention and found many applications. Biomedical applications of BN have recently started to emerge, raising great hopes in drug and gene delivery. Here, we developed a targeted anticancer drug delivery system based on folate-conjugated BN nanospheres (BNNS) with receptor-mediated targeting. Folic acid (FA) was successfully grafted onto BNNS via esterification reaction. In vitro cytotoxicity assay showed that BNNS-FA complexes were non-toxic to HeLa cells up to a concentration of 100 μg/mL. Then, doxorubicin hydrochloride (DOX), a commonly used anticancer drug, was loaded onto BNNS-FA complexes. BNNS-FA/DOX complexes were stable at pH 7.4 but effectively released DOX at pH 5.0, which exhibited a pH sensitive and sustained release pattern. BNNS-FA/DOX complexes could be recognized and specifically internalized by HeLa cells via FA receptor-mediated endocytosis. BNNS-FA/DOX complexes exhibited greater cytotoxicity to HeLa cells than free DOX and BNNS/DOX complexes due to the increased cellular uptake of DOX mediated by the FA receptor. Therefore, BNNS-FA complexes had strong potential for targeted cancer therapy. PMID:27695318
Current Drug Targets in Obesity Pharmacotherapy - A Review.

PubMed

Bhat, Sangeeta P; Sharma, Arun

2017-01-01

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

PubMed

Farghali, Hassan; Kameníková, Ludmila

2017-01-01

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

PubMed Central

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

2017-01-01

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

PubMed Central

Charbe, Nitin B.; McCarron, Paul A.; Lane, Majella E.; Tambuwala, Murtaza M.

2017-01-01

Orally administered solid dosage forms currently dominate over all other dosage forms and routes of administrations. However, human gastrointestinal tract (GIT) poses a number of obstacles to delivery of the drugs to the site of interest and absorption in the GIT. Pharmaceutical scientists worldwide have been interested in colon drug delivery for several decades, not only for the delivery of the drugs for the treatment of colonic diseases such as ulcerative colitis and colon cancer but also for delivery of therapeutic proteins and peptides for systemic absorption. Despite extensive research in the area of colon targeted drug delivery, we have not been able to come up with an effective way of delivering drugs to the colon. The current tablets designed for colon drug release depend on either pH-dependent or time-delayed release formulations. During ulcerative colitis the gastric transit time and colon pH-levels is constantly changing depending on whether the patient is having a relapse or under remission. Hence, the current drug delivery system to the colon is based on one-size-fits-all. Fails to effectively deliver the drugs locally to the colon for colonic diseases and delivery of therapeutic proteins and peptides for systemic absorption from the colon. Hence, to overcome the current issues associated with colon drug delivery, we need to provide the patients with personalized tablets which are specifically designed to match the individual's gastric transit time depending on the disease state. Three-dimensional (3D) printing (3DP) technology is getting cheaper by the day and bespoke manufacturing of 3D-printed tablets could provide the solutions in the form of personalized colon drug delivery system. This review provides a bird's eye view of applications and current advances in pharmaceutical 3DP with emphasis on the development of colon targeted drug delivery systems. PMID:28929046
Application of three-dimensional printing for colon targeted drug delivery systems.

PubMed

Charbe, Nitin B; McCarron, Paul A; Lane, Majella E; Tambuwala, Murtaza M

2017-01-01

Orally administered solid dosage forms currently dominate over all other dosage forms and routes of administrations. However, human gastrointestinal tract (GIT) poses a number of obstacles to delivery of the drugs to the site of interest and absorption in the GIT. Pharmaceutical scientists worldwide have been interested in colon drug delivery for several decades, not only for the delivery of the drugs for the treatment of colonic diseases such as ulcerative colitis and colon cancer but also for delivery of therapeutic proteins and peptides for systemic absorption. Despite extensive research in the area of colon targeted drug delivery, we have not been able to come up with an effective way of delivering drugs to the colon. The current tablets designed for colon drug release depend on either pH-dependent or time-delayed release formulations. During ulcerative colitis the gastric transit time and colon pH-levels is constantly changing depending on whether the patient is having a relapse or under remission. Hence, the current drug delivery system to the colon is based on one-size-fits-all. Fails to effectively deliver the drugs locally to the colon for colonic diseases and delivery of therapeutic proteins and peptides for systemic absorption from the colon. Hence, to overcome the current issues associated with colon drug delivery, we need to provide the patients with personalized tablets which are specifically designed to match the individual's gastric transit time depending on the disease state. Three-dimensional (3D) printing (3DP) technology is getting cheaper by the day and bespoke manufacturing of 3D-printed tablets could provide the solutions in the form of personalized colon drug delivery system. This review provides a bird's eye view of applications and current advances in pharmaceutical 3DP with emphasis on the development of colon targeted drug delivery systems.
Mathematical description of drug-target interactions: application to biologics that bind to targets with two binding sites.

PubMed

Gibiansky, Leonid; Gibiansky, Ekaterina

2018-02-01

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

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

PubMed Central

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

2012-01-01

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

PubMed

Liu, Xian; Xu, Yuan; Li, Shanshan; Wang, Yulan; Peng, Jianlong; Luo, Cheng; Luo, Xiaomin; Zheng, Mingyue; Chen, Kaixian; Jiang, Hualiang

2014-01-01

Ligand-based in silico target fishing can be used to identify the potential interacting target of bioactive ligands, which is useful for understanding the polypharmacology and safety profile of existing drugs. The underlying principle of the approach is that known bioactive ligands can be used as reference to predict the targets for a new compound. We tested a pipeline enabling large-scale target fishing and drug repositioning, based on simple fingerprint similarity rankings with data fusion. A large library containing 533 drug relevant targets with 179,807 active ligands was compiled, where each target was defined by its ligand set. For a given query molecule, its target profile is generated by similarity searching against the ligand sets assigned to each target, for which individual searches utilizing multiple reference structures are then fused into a single ranking list representing the potential target interaction profile of the query compound. The proposed approach was validated by 10-fold cross validation and two external tests using data from DrugBank and Therapeutic Target Database (TTD). The use of the approach was further demonstrated with some examples concerning the drug repositioning and drug side-effects prediction. The promising results suggest that the proposed method is useful for not only finding promiscuous drugs for their new usages, but also predicting some important toxic liabilities. With the rapid increasing volume and diversity of data concerning drug related targets and their ligands, the simple ligand-based target fishing approach would play an important role in assisting future drug design and discovery.
Systems biology approaches and tools for analysis of interactomes and multi-target drugs.

PubMed

Schrattenholz, André; Groebe, Karlfried; Soskic, Vukic

2010-01-01

Systems biology is essentially a proteomic and epigenetic exercise because the relatively condensed information of genomes unfolds on the level of proteins. The flexibility of cellular architectures is not only mediated by a dazzling number of proteinaceous species but moreover by the kinetics of their molecular changes: The time scales of posttranslational modifications range from milliseconds to years. The genetic framework of an organism only provides the blue print of protein embodiments which are constantly shaped by external input. Indeed, posttranslational modifications of proteins represent the scope and velocity of these inputs and fulfil the requirements of integration of external spatiotemporal signal transduction inside an organism. The optimization of biochemical networks for this type of information processing and storage results in chemically extremely fine tuned molecular entities. The huge dynamic range of concentrations, the chemical diversity and the necessity of synchronisation of complex protein expression patterns pose the major challenge of systemic analysis of biological models. One further message is that many of the key reactions in living systems are essentially based on interactions of moderate affinities and moderate selectivities. This principle is responsible for the enormous flexibility and redundancy of cellular circuitries. In complex disorders such as cancer or neurodegenerative diseases, which initially appear to be rooted in relatively subtle dysfunctions of multimodal physiologic pathways, drug discovery programs based on the concept of high affinity/high specificity compounds ("one-target, one-disease"), which has been dominating the pharmaceutical industry for a long time, increasingly turn out to be unsuccessful. Despite improvements in rational drug design and high throughput screening methods, the number of novel, single-target drugs fell much behind expectations during the past decade, and the treatment of "complex
In silico Analysis of Toxins of Staphylococcus aureus for Validating Putative Drug Targets.

PubMed

Mohana, Ramadevi; Venugopal, Subhashree

2017-01-01

Toxins are one among the numerous virulence factors produced by the bacteria. These are powerful poisonous substances enabling the bacteria to encounter the defense mechanism of human body. The pathogenic system of Staphylococcus aureus is evolved with various exotoxins that cause detrimental effects on human immune system. Four toxins namely enterotoxin A, exfoliative toxin A, TSST-1 and γ-hemolysin were downloaded from Uniprot database and were analyzed to understand the nature of the toxins and for drug target validation. The results inferred that the toxins were found to interact with many protein partners and no homologous sequences for human proteome were found, and based on similarity search in Drugbank, the targets were identified as novel drug targets. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Hyaluronic Acid-Modified Multifunctional Q-Graphene for Targeted Killing of Drug-Resistant Lung Cancer Cells.

PubMed

Luo, Yanan; Cai, Xiaoli; Li, He; Lin, Yuehe; Du, Dan

2016-02-17

Considering the urgent need to explore multifunctional drug delivery system for overcoming multidrug resistance, we prepared a new nanocarbon material Q-Graphene as a nanocarrier for killing drug-resistant lung cancer cells. Attributing to the introduction of hyaluronic acid and rhodamine B isothiocyanate (RBITC), the Q-Graphene-based drug delivery system was endowed with dual function of targeted drug delivery and fluorescence imaging. Additionally, doxorubicin (DOX) as a model drug was loaded on the surface of Q-Graphene via π-π stacking. Interestingly, the fluorescence of DOX was quenched by Q-Graphene due to its strong electron-accepting capability, and a significant recovery of fluorescence was observed, while DOX was released from Q-Graphene. Because of the RBITC labeling and the effect of fluorescence quenching/restoring of Q-Graphene, the uptake of nanoparticles and intracellular DOX release can be tracked. Overall, a highly promising multifunctional nanoplatform was developed for tracking and monitoring targeted drug delivery for efficiently killing drug-resistant cancer cells.
Aminoacyl-tRNA synthetases as drug targets in eukaryotic parasites☆

PubMed Central

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

2013-01-01

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

PubMed

Lundstrom, Kenneth

2018-06-01

Drugs and vaccines based on mRNA and RNA viruses show great potential and direct translation in the cytoplasm eliminates chromosomal integration. Limitations are associated with delivery and stability issues related to RNA degradation. Clinical trials on RNA-based drugs have been conducted in various disease areas. Likewise, RNA-based vaccines for viral infections and various cancers have been subjected to preclinical and clinical studies. RNA delivery and stability improvements include RNA structure modifications, targeting dendritic cells and employing self-amplifying RNA. Single-stranded RNA viruses possess self-amplifying RNA, which can provide extreme RNA replication in the cytoplasm to support RNA-based drug and vaccine development. Although oligonucleotide-based approaches have demonstrated potential, the focus here is on mRNA- and RNA virus-based methods.
GPCR homomers and heteromers: a better choice as targets for drug development than GPCR monomers?

PubMed

Casadó, Vicent; Cortés, Antoni; Mallol, Josefa; Pérez-Capote, Kamil; Ferré, Sergi; Lluis, Carmen; Franco, Rafael; Canela, Enric I

2009-11-01

G protein-coupled receptors (GPCR) are targeted by many therapeutic drugs marketed to fight against a variety of diseases. Selection of novel lead compounds are based on pharmacological parameters obtained assuming that GPCR are monomers. However, many GPCR are expressed as dimers/oligomers. Therefore, drug development may consider GPCR as homo- and hetero-oligomers. A two-state dimer receptor model is now available to understand GPCR operation and to interpret data obtained from drugs interacting with dimers, and even from mixtures of monomers and dimers. Heteromers are distinct entities and therefore a given drug is expected to have different affinities and different efficacies depending on the heteromer. All these concepts would lead to broaden the therapeutic potential of drugs targeting GPCRs, including receptor heteromer-selective drugs with a lower incidence of side effects, or to identify novel pharmacological profiles using cell models expressing receptor heteromers.
Lung Surfactant Microbubbles Increase Lipophilic Drug Payload for Ultrasound-Targeted Delivery

PubMed Central

Sirsi, Shashank R.; Fung, Chinpong; Garg, Sumit; Tianning, Mary Y.; Mountford, Paul A.; Borden, Mark A.

2013-01-01

The cavitation response of circulating microbubbles to targeted ultrasound can be used for noninvasive, site-specific delivery of shell-loaded materials. One challenge for microbubble-mediated delivery of lipophilic compounds is the limitation of drug loading into the microbubble shell, which is commonly a single phospholipid monolayer. In this study, we investigated the use of natural lung surfactant extract (Survanta®, Abbott Nutrition) as a microbubble shell material in order to improve drug payload and delivery. Pulmonary surfactant extracts such as Survanta contain hydrophobic surfactant proteins (SP-B and SP-C) that facilitate lipid folding and retention on lipid monolayers. Here, we show that Survanta-based microbubbles exhibit wrinkles in bright-field microscopy and increased lipid retention on the microbubble surface in the form of surface-associated aggregates observed with fluorescence microscopy. The payload of a model lipophilic drug (DiO), measured by flow cytometry, increased by over 2-fold compared to lipid-coated microbubbles lacking SP-B and SP-C. Lung surfactant microbubbles were highly echogenic to contrast enhanced ultrasound imaging at low acoustic intensities. At higher ultrasound intensity, excess lipid was observed to be acoustically cleaved for localized release. To demonstrate targeting, a biotinylated lipopolymer was incorporated into the shell, and the microbubbles were subjected to a sequence of radiation force and fragmentation pulses as they passed through an avidinated hollow fiber. Lung surfactant microbubbles showed a 3-fold increase in targeted deposition of the model fluorescent drug compared to lipid-only microbubbles. Our results demonstrate that lung surfactant microbubbles maintain the acoustic responsiveness of lipid-coated microbubbles with the added benefit of increased lipophilic drug payload. PMID:23781287
Lung surfactant microbubbles increase lipophilic drug payload for ultrasound-targeted delivery.

PubMed

Sirsi, Shashank R; Fung, Chinpong; Garg, Sumit; Tianning, Mary Y; Mountford, Paul A; Borden, Mark A

2013-01-01

The cavitation response of circulating microbubbles to targeted ultrasound can be used for noninvasive, site-specific delivery of shell-loaded materials. One challenge for microbubble-mediated delivery of lipophilic compounds is the limitation of drug loading into the microbubble shell, which is commonly a single phospholipid monolayer. In this study, we investigated the use of natural lung surfactant extract (Survanta(®), Abbott Nutrition) as a microbubble shell material in order to improve drug payload and delivery. Pulmonary surfactant extracts such as Survanta contain hydrophobic surfactant proteins (SP-B and SP-C) that facilitate lipid folding and retention on lipid monolayers. Here, we show that Survanta-based microbubbles exhibit wrinkles in bright-field microscopy and increased lipid retention on the microbubble surface in the form of surface-associated aggregates observed with fluorescence microscopy. The payload of a model lipophilic drug (DiO), measured by flow cytometry, increased by over 2-fold compared to lipid-coated microbubbles lacking SP-B and SP-C. Lung surfactant microbubbles were highly echogenic to contrast enhanced ultrasound imaging at low acoustic intensities. At higher ultrasound intensity, excess lipid was observed to be acoustically cleaved for localized release. To demonstrate targeting, a biotinylated lipopolymer was incorporated into the shell, and the microbubbles were subjected to a sequence of radiation force and fragmentation pulses as they passed through an avidinated hollow fiber. Lung surfactant microbubbles showed a 3-fold increase in targeted deposition of the model fluorescent drug compared to lipid-only microbubbles. Our results demonstrate that lung surfactant microbubbles maintain the acoustic responsiveness of lipid-coated microbubbles with the added benefit of increased lipophilic drug payload.
Food and Drug Administration Perspective on Negative Symptoms in Schizophrenia as a Target for a Drug Treatment Claim

PubMed Central

Laughren, Thomas; Levin, Robert

2006-01-01

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

PubMed

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

2018-01-01

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

PubMed

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

2017-07-05

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

PubMed Central

Deng, Kerong; Hou, Zhiyao; Li, Xuejiao; Li, Chunxia; Zhang, Yuanxin; Deng, Xiaoran; Cheng, Ziyong; Lin, Jun

2015-01-01

Multifunctional nanocarriers for targeted bioimaging and drug delivery have attracted much attention in early diagnosis and therapy of cancer. In this work, we develop a novel aptamer-guided nanocarrier based on the mesoporous metal-organic framework (MOF) shell and up-conversion luminescent NaYF4:Yb3+/Er3+ nanoparticles (UCNPs) core for the first time to achieve these goals. These UCNPs, chosen as optical labels in biological assays and medical imaging, could emit strong green emission under 980 nm laser. The MOF structure based on iron (III) carboxylate materials [MIL-100 (Fe)] possesses high porosity and non-toxicity, which is of great value as nanocarriers for drug storage/delivery. As a unique nanoplatform, the hybrid inorganic-organic drug delivery vehicles show great promising for simultaneous targeted labeling and therapy of cancer cells. PMID:25597762
A dual-targeting strategy for enhanced drug delivery and synergistic therapy based on thermosensitive nanoparticles.

PubMed

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.
Fragment-based approaches to TB drugs.

PubMed

Marchetti, Chiara; Chan, Daniel S H; Coyne, Anthony G; Abell, Chris

2018-02-01

Tuberculosis is an infectious disease associated with significant mortality and morbidity worldwide, particularly in developing countries. The rise of antibiotic resistance in Mycobacterium tuberculosis (Mtb) urgently demands the development of new drug leads to tackle resistant strains. Fragment-based methods have recently emerged at the forefront of pharmaceutical development as a means to generate more effective lead structures, via the identification of fragment molecules that form weak but high quality interactions with the target biomolecule and subsequent fragment optimization. This review highlights a number of novel inhibitors of Mtb targets that have been developed through fragment-based approaches in recent years.
The relationship between target-class and the physicochemical properties of antibacterial drugs

PubMed Central

Mugumbate, Grace; Overington, John P.

2015-01-01

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

PubMed

Mittal, Rahul; Patel, Amit P; Jhaveri, Vasanti M; Kay, Sae-In S; Debs, Luca H; Parrish, James M; Pan, Debbie R; Nguyen, Desiree; Mittal, Jeenu; Jayant, Rahul Dev

2018-03-01

The emergent field of nanoparticles has presented a wealth of opportunities for improving the treatment of human diseases. Recent advances have allowed for promising developments in drug delivery, diagnostics, and therapeutics. Modified delivery systems allow improved drug delivery over traditional pH, microbe, or receptor dependent models, while antibody association allows for more advanced imaging modalities. Nanoparticles have potential clinical application in the field of gastroenterology as they offer several advantages compared to the conventional treatment systems including target drug delivery, enhanced treatment efficacy, and reduced side effects. Areas covered: The aim of this review article is to summarize the recent advancements in developing nanoparticle technologies to treat gastrointestinal diseases. We have covered the application of nanoparticles in various gastrointestinal disorders including inflammatory bowel disease and colorectal cancer. We also have discussed how the gut microbiota affects the nanoparticle based drug delivery in the gastrointestinal tract. Expert opinion: Nanoparticles based drug delivery offers a great platform for targeted drug delivery for gastrointestinal disorders. However, it is influenced by the presence of microbiota, drug interaction with nanoparticles, and cytotoxicity of nanoparticles. With the advancements in nanoparticle technology, it may be possible to overcome these barriers leading to efficient drug delivery for gastrointestinal disorders based on nanoparticle platform.
Targeting of herbal bioactives through folate receptors: a novel concept to enhance intracellular drug delivery in cancer therapy.

PubMed

Gupta, Anshita; Kaur, Chanchal Deep; Saraf, Shailendra; Saraf, Swarnlata

2017-06-01

Targeted drug delivery through folate receptor (FR) has emerged as a most biocompatible, target oriented, and non-immunogenic cargoes for the delivery of anticancer drugs. FRs are highly overexpressed in many tumor cells (like ovarian, lung, breast, kidney, brain, endometrial, and colon cancer), and targeting them through conjugates bearing specific ligand with encapsulated nanodrug moiety is undoubtedly, a promising approach toward tumor targeting. Folate, being an endogenous ligand, can be exploited well to affect various cellular events occurring during the progress of tumor, in a more natural and definite way. Thus, the aim of the review lies in summarizing the advancements taken place in the drug delivery system of different therapeutics through FRs and to refine its role as an endogenous ligand, in targeting of synthetic as well as natural bioactives. The review also provides an update on the patents received on the folate-based drug delivery system.
The application of carbon nanotubes in target drug delivery systems for cancer therapies

NASA Astrophysics Data System (ADS)

Zhang, Wuxu; Zhang, Zhenzhong; Zhang, Yingge

2011-10-01

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

From crystal to compound: structure-based antimalarial drug discovery.

PubMed

Drinkwater, Nyssa; McGowan, Sheena

2014-08-01

Despite a century of control and eradication campaigns, malaria remains one of the world's most devastating diseases. Our once-powerful therapeutic weapons are losing the war against the Plasmodium parasite, whose ability to rapidly develop and spread drug resistance hamper past and present malaria-control efforts. Finding new and effective treatments for malaria is now a top global health priority, fuelling an increase in funding and promoting open-source collaborations between researchers and pharmaceutical consortia around the world. The result of this is rapid advances in drug discovery approaches and technologies, with three major methods for antimalarial drug development emerging: (i) chemistry-based, (ii) target-based, and (iii) cell-based. Common to all three of these approaches is the unique ability of structural biology to inform and accelerate drug development. Where possible, SBDD (structure-based drug discovery) is a foundation for antimalarial drug development programmes, and has been invaluable to the development of a number of current pre-clinical and clinical candidates. However, as we expand our understanding of the malarial life cycle and mechanisms of resistance development, SBDD as a field must continue to evolve in order to develop compounds that adhere to the ideal characteristics for novel antimalarial therapeutics and to avoid high attrition rates pre- and post-clinic. In the present review, we aim to examine the contribution that SBDD has made to current antimalarial drug development efforts, covering hit discovery to lead optimization and prevention of parasite resistance. Finally, the potential for structural biology, particularly high-throughput structural genomics programmes, to identify future targets for drug discovery are discussed.
Contact-facilitated drug delivery with Sn2 lipase labile prodrugs optimize targeted lipid nanoparticle drug delivery.

PubMed

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

2016-01-01

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

PubMed Central

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

2016-01-01

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

NASA Astrophysics Data System (ADS)

Huang, Ya-Shu; Lu, Yu-Jen; Chen, Jyh-Ping

2017-04-01

A magnetic targeted functionalized graphene oxide (GO) complex is constituted as a nanocarrier for targeted delivery and pH-responsive controlled release of chemotherapy drugs to cancer cells. Magnetic graphene oxide (mGO) was prepared by chemical co-precipitation of Fe3O4 magnetic nanoparticles on GO nano-platelets. The mGO was successively modified by chitosan and mPEG-NHS through covalent bindings to synthesize mGOC-PEG. The polyethylene glycol (PEG) moiety is expected to prolong the circulation time of mGO by reducing the reticuloendothelial system clearance. Irinotecan (CPT-11) or doxorubicin (DOX) was loaded to mGOC-PEG through π-π stacking interactions for magnetic targeted delivery of the cancer chemotherapy drug. The best values of loading efficiency and loading content of CPT-11 were 54% and 2.7% respectively; whereas for DOX, they were 65% and 393% The pH-dependent drug release profile was further experimented at different pHs, in which 60% of DOX was released at pH 5.4 and 10% was released at pH 7.4. In contrast, 90% CPT-11 was released at pH 5.4 and 70% at pH 7.4. Based on the drug loading and release characteristics, mGOC-PEG/DOX was further chosen for in vitro cytotoxicity tests against U87 human glioblastoma cell line. The IC50 value of mGOC-PEG/DOX was found to be similar to that of free DOX but was reduced dramatically when subject to magnetic targeting. It is concluded that with the high drug loading and pH-dependent drug release properties, mGOC-PEG will be a promising drug carrier for targeted delivery of chemotherapy drugs in cancer therapy.
Discovery: an interactive resource for the rational selection and comparison of putative drug target proteins in malaria

PubMed Central

Joubert, Fourie; Harrison, Claudia M; Koegelenberg, Riaan J; Odendaal, Christiaan J; de Beer, Tjaart AP

2009-01-01

Background Up to half a billion human clinical cases of malaria are reported each year, resulting in about 2.7 million deaths, most of which occur in sub-Saharan Africa. Due to the over-and misuse of anti-malarials, widespread resistance to all the known drugs is increasing at an alarming rate. Rational methods to select new drug target proteins and lead compounds are urgently needed. The Discovery system provides data mining functionality on extensive annotations of five malaria species together with the human and mosquito hosts, enabling the selection of new targets based on multiple protein and ligand properties. Methods A web-based system was developed where researchers are able to mine information on malaria proteins and predicted ligands, as well as perform comparisons to the human and mosquito host characteristics. Protein features used include: domains, motifs, EC numbers, GO terms, orthologs, protein-protein interactions, protein-ligand interactions and host-pathogen interactions among others. Searching by chemical structure is also available. Results An in silico system for the selection of putative drug targets and lead compounds is presented, together with an example study on the bifunctional DHFR-TS from Plasmodium falciparum. Conclusion The Discovery system allows for the identification of putative drug targets and lead compounds in Plasmodium species based on the filtering of protein and chemical properties. PMID:19642978
Liposomes and nanotechnology in drug development: focus on ocular targets

PubMed Central

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

2013-01-01

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

NASA Astrophysics Data System (ADS)

Doan Trang Nguyen, Ngoc; Thi Le, Ly

2012-03-01

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

PubMed

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

2014-06-01

Aspergillus fumigatus (Af) is a ubiquitous and opportunistic pathogen capable of causing acute, invasive pulmonary disease in susceptible hosts. Despite current therapeutic options, mortality associated with invasive Af infections remains unacceptably high, increasing 357% since 1980. Therefore, there is an urgent need for the development of novel therapeutic strategies, including more efficacious drugs acting on new targets. Thus, as noted in a recent review, "the identification of essential genes in fungi represents a crucial step in the development of new antifungal drugs". Expanding the target space by rapidly identifying new essential genes has thus been described as "the most important task of genomics-based target validation". In previous research, we were the first to show that essential gene annotation can be reliably transferred between distantly related four Prokaryotic species. In this study, we extend our machine learning approach to the much more complex Eukaryotic fungal species. A compendium of essential genes is predicted in Af by transferring known essential gene annotations from another filamentous fungus Neurospora crassa. This approach predicts essential genes by integrating diverse types of intrinsic and context-dependent genomic features encoded in microbial genomes. The predicted essential datasets contained 1674 genes. We validated our results by comparing our predictions with known essential genes in Af, comparing our predictions with those predicted by homology mapping, and conducting conditional expressed alleles. We applied several layers of filters and selected a set of potential drug targets from the predicted essential genes. Finally, we have conducted wet lab knockout experiments to verify our predictions, which further validates the accuracy and wide applicability of the machine learning approach. The approach presented here significantly extended our ability to predict essential genes beyond orthologs and made it possible to
Fe3O4 Nanoparticles in Targeted Drug/Gene Delivery Systems

PubMed Central

Shen, Lazhen; Li, Bei; Qiao, Yongsheng

2018-01-01

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

PubMed

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

2011-12-01

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

PubMed Central

Xu, Ting; Liu, Chi; Chen, Can; Song, Xiangrong; Zheng, Yu

2013-01-01

The triblock 18β-glycyrrhetinic acid-poly(ethylene glycol)-18β-glycyrrhetinic acid conjugates (GA-PEG-GA) based self-assembled micelles were synthesized and characterized by FTIR, NMR, transmission electron microscopy, and particle size analysis. The GA-PEG-GA conjugates having the critical micelle concentration of 6 × 10−5 M were used to form nanosized micelles, with mean diameters of 159.21 ± 2.2 nm, and then paclitaxel (PTX) was incorporated into GA-PEG-GA micelles by self-assembly method. The physicochemical properties of the PTX loaded GA-PEG-GA micelles were evaluated including in vitro cellular uptake, cytotoxicity, drug release profile, and in vivo tissue distribution. The results demonstrate that the GA-PEG-GA micelles had low cytotoxicity and good ability of selectively delivering drug to hepatic cells in vitro and in vivo by the targeting moiety glycyrrhetinic acid. In conclusion, the GA-PEG-GA conjugates have potential medical applications for targeted delivery of poor soluble drug delivery. PMID:24376388
Inhaled Micro/Nanoparticulate Anticancer Drug Formulations: An Emerging Targeted Drug Delivery Strategy for Lung Cancers.

PubMed

Islam, Nazrul; Richard, Derek

2018-05-24

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

PubMed

Bajpayee, Ambika G; Grodzinsky, Alan J

2017-03-01

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

PubMed

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

2012-06-01

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

PubMed Central

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

2014-01-01

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

PubMed

Jiang, Tao; Yu, Xiaohua; Carbone, Erica J; Nelson, Clarke; Kan, Ho Man; Lo, Kevin W-H

2014-11-20

Delivering drugs specifically to bone tissue is very challenging due to the architecture and structure of bone tissue. Poly(lactic-co-glycolic acid) (PLGA)-based nanoparticles (NPs) hold great promise for the delivery of therapeutics to bone tissue. The goal of the present research was to formulate a PLGA-based NP drug delivery system for bone tissue exclusively. Since poly-aspartic acids (poly-Asp) peptide sequence has been shown to bind to hydroxyapatite (HA), and has been suggested as a molecular tool for bone-targeting applications, we fabricated PLGA-based NPs linked with poly-Asp peptide sequence. Nanoparticles made of methoxy - poly(ethylene glycol) (PEG)-PLGA and maleimide-PEG-PLGA were prepared using a water-in-oil-in-water double emulsion and solvent evaporation method. Fluorescein isothiocyanate (FITC)-tagged poly-Asp peptide was conjugated to the surface of the nanoparticles via the alkylation reaction between the sulfhydryl groups at the N-terminal of the peptide and the CC double bond of maleimide at one end of the polymer chain to form thioether bonds. The conjugation of FITC-tagged poly-Asp peptide to PLGA NPs was confirmed by NMR analysis and fluorescent microscopy. The developed nanoparticle system is highly aqueous dispersible with an average particle size of ∼80 nm. In vitro binding analyses demonstrated that FITC-poly-Asp NPs were able to bind to HA gel as well as to mineralized matrices produced by human mesenchymal stem cells and mouse bone marrow stromal cells. Using a confocal microscopy technique, an ex vivo binding study of mouse major organ ground sections revealed that the FITC-poly-Asp NPs were able to bind specifically to the bone tissue. In addition, proliferation studies indicated that our FITC-poly-Asp NPs did not induce cytotoxicity to human osteoblast-like MG63 cell lines. Altogether, these promising results indicated that this nanoscale targeting system was able to bind to bone tissue specifically and might have a great
Anticancer drug delivery with transferrin targeted polymeric chitosan vesicles.

PubMed

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

2004-01-01

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

PubMed

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

2017-03-28

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

PubMed

Samimi, Hilda; Fallah, Parviz; Naderi Sohi, Alireza; Tavakoli, Rezvan; Naderi, Mahmood; Soleimani, Masoud; Larijani, Bagher; Haghpanah, Vahid

2017-03-01

Personalized medicine is a set of diagnostic, prognostic and therapeutic approaches in which medical interventions are carried out based on individual patient characteristics. As life expectancy increases in developed and developing countries, the incidence of diseases such as cancer goes up among people in the community. Cancer is a disease that the response to treatment varies from one person to another and also it is costly for individuals, families, and society. Among thyroid cancers, anaplastic thyroid carcinoma (ATC) is the most aggressive, lethal and unresponsive form of the disease. Unfortunately, current drugs are not targetable, and therefore they have restricted role in ATC treatment. Consequently, mortality of this cancer, despite advances in the field of diagnosis and treatment, is one of the most important challenges in medicine. Cellular, molecular and genetic evidences play an important role in finding more effective diagnostic and therapeutic approaches. Review of these evidences confirms the application of personalized medicine in cancer treatment including ATC. A growing body of evidence has elucidated that cellular and molecular mechanisms of cancer would pave the way for defining new biomarkers for targeted therapy, taking into account individual differences. It should be noted that this approach requires further progress in the fields of basic sciences, pharmacogenetics and drug design. An overview of the most important aspects in individualized anaplastic thyroid cancer treatment will be discussed in this review.

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

PubMed

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

2015-08-01

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

PubMed

Vilar, Santiago; Uriarte, Eugenio; Santana, Lourdes; Lorberbaum, Tal; Hripcsak, George; Friedman, Carol; Tatonetti, Nicholas P

2014-09-01

Drug-drug interactions (DDIs) are a major cause of adverse drug effects and a public health concern, as they increase hospital care expenses and reduce patients' quality of life. DDI detection is, therefore, an important objective in patient safety, one whose pursuit affects drug development and pharmacovigilance. In this article, we describe a protocol applicable on a large scale to predict novel DDIs based on similarity of drug interaction candidates to drugs involved in established DDIs. The method integrates a reference standard database of known DDIs with drug similarity information extracted from different sources, such as 2D and 3D molecular structure, interaction profile, target and side-effect similarities. The method is interpretable in that it generates drug interaction candidates that are traceable to pharmacological or clinical effects. We describe a protocol with applications in patient safety and preclinical toxicity screening. The time frame to implement this protocol is 5-7 h, with additional time potentially necessary, depending on the complexity of the reference standard DDI database and the similarity measures implemented.
Anticancer drug development from traditional cytotoxic to targeted therapies: evidence of shorter drug research and development time, and shorter drug lag in Japan.

PubMed

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

2012-10-01

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

PubMed

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

2018-03-07

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

PubMed

Wu, Dandan; Wang, Lei; Li, Wei; Xu, Xiaowen; Jiang, Wei

2017-11-25

DNA as a novel biomaterial can be used to fabricate different kinds of DNA nanostructures based on its principle of GC/AT complementary base pairing. Studies have shown that DNA nanostructure is a nice drug carrier to overcome big obstacles existing in cancer therapy such as systemic toxicity and unsatisfied drug efficacy. Thus, different types of DNA nanostructure-based drug delivery nanosystems have been designed in cancer therapy. To improve treating efficacy, they are also developed into more functional drug delivery nanosystems. In recent years, some important progresses have been made. The objective of this review is to make a retrospect and summary about these different kinds of DNA nanostructure-based drug delivery nanosystems and their latest progresses: (1) active targeting; (2) mutidrug co-delivery; (3) construction of stimuli-responsive/intelligent nanosystems. Copyright © 2017 Elsevier B.V. All rights reserved.
A sight on protein-based nanoparticles as drug/gene delivery systems.

PubMed

Salatin, Sara; Jelvehgari, Mitra; Maleki-Dizaj, Solmaz; Adibkia, Khosro

2015-01-01

Polymeric nanomaterials have extensively been applied for the preparation of targeted and controlled release drug/gene delivery systems. However, problems involved in the formulation of synthetic polymers such as using of the toxic solvents and surfactants have limited their desirable applications. In this regard, natural biomolecules including proteins and polysaccharide are suitable alternatives due to their safety. According to literature, protein-based nanoparticles possess many advantages for drug and gene delivery such as biocompatibility, biodegradability and ability to functionalize with targeting ligands. This review provides a general sight on the application of biodegradable protein-based nanoparticles in drug/gene delivery based on their origins. Their unique physicochemical properties that help them to be formulated as pharmaceutical carriers are also discussed.
EphB1 as a Novel Drug Target to Combat Pain and Addiction

DTIC Science & Technology

2017-09-01

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

PubMed

Kang, Xiang; Xiao, Hai-Hua; Song, Hai-Qin; Jing, Xia-Bin; Yan, Le-San; Qi, Ruo-Gu

2015-12-01

Platinum-based anticancer agents are widely used as first-line drugs in cancer chemotherapy for various solid tumors. However, great side effects and occurrence of resistance remain as the major drawbacks for almost all the platinum drugs developed. To conquer these problems, new strategies should be adopted for platinum drug based chemotherapy. Modern nanotechnology has been widely employed in the delivery of various therapeutics and diagnostic. It provides the possibility of targeted delivery of a certain anticancer drug to the tumor site, which could minimize toxicity and optimize the drug efficacy. Here, in this review, we focused on the recent progress in polymer based drug delivery systems for platinum-based combination therapy.
Data mart construction based on semantic annotation of scientific articles: A case study for the prioritization of drug targets.

PubMed

Teixeira, Marlon Amaro Coelho; Belloze, Kele Teixeira; Cavalcanti, Maria Cláudia; Silva-Junior, Floriano P

2018-04-01

Semantic text annotation enables the association of semantic information (ontology concepts) to text expressions (terms), which are readable by software agents. In the scientific scenario, this is particularly useful because it reveals a lot of scientific discoveries that are hidden within academic articles. The Biomedical area has more than 300 ontologies, most of them composed of over 500 concepts. These ontologies can be used to annotate scientific papers and thus, facilitate data extraction. However, in the context of a scientific research, a simple keyword-based query using the interface of a digital scientific texts library can return more than a thousand hits. The analysis of such a large set of texts, annotated with such numerous and large ontologies, is not an easy task. Therefore, the main objective of this work is to provide a method that could facilitate this task. This work describes a method called Text and Ontology ETL (TOETL), to build an analytical view over such texts. First, a corpus of selected papers is semantically annotated using distinct ontologies. Then, the annotation data is extracted, organized and aggregated into the dimensional schema of a data mart. Besides the TOETL method, this work illustrates its application through the development of the TaP DM (Target Prioritization data mart). This data mart has focus on the research of gene essentiality, a key concept to be considered when searching for genes showing potential as anti-infective drug targets. This work reveals that the proposed approach is a relevant tool to support decision making in the prioritization of new drug targets, being more efficient than the keyword-based traditional tools. Copyright © 2018 Elsevier B.V. All rights reserved.
Sperm-Hybrid Micromotor for Targeted Drug Delivery.

PubMed

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

2018-01-23

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

PubMed

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

2016-08-01

Targeted drug delivery systems deliver drugs precisely to a specific targeted site inside the body, and can also release the drugs with controlled kinetics to prolong the efficacy of single dose administration. The advantageous properties of hydrogels make them attractive for use in the area of drug delivery. Calcium alginate is a pH sensitive hydrogel stable in acidic media and soluble in basic media. This enables the hydrogel to absorb and release aqueous solutions at certain ranges of pH values. By absorbing an aqueous solution containing a drug, an active drug release can be triggered at a specified range of pH value. In this paper, we combined calcium alginate with cobalt nickel (CoNi) in a cylindrical hybrid micro robot by electrodeposition. The designed microrobot can be wirelessly actuated with an external magnetic manipulation system and, hence, targeted to a specific location in the human body. At this specific location, characterized by its pH range, the absorbed drug will be released. Here, the fabrication steps of the specified microrobot are characterized, namely the production of a template on a silicon chip and the subsequent template-assisted electrodeposition of CoNi and alginate. Additionally, the dynamics of drug release of calcium alginate is studied.
Reactivity-based drug discovery using vitamin B(6)-derived pharmacophores.

PubMed

Wondrak, Georg T

2008-05-01

Endogenous reactive intermediates including photoexcited states of tissue chromophores, reactive oxygen species (ROS), reactive carbonyl species (RCS), transition metal ions, and Schiff bases have been implicated in the initiation and progression of diverse human pathologies including tumorigenesis, atherosclerosis, diabetes, and neurodegenerative disease. In contrast to structure-based approaches that target macromolecules by selective ligands, reactivity-based drug discovery uses chemical reagents as therapeutics that target reactive chemical species involved in human pathology. Reactivity-based design of prototype agents that effectively antagonize, modulate, and potentially even reverse the chemistry underlying tissue damage from oxidative and carbonyl stress therefore holds great promise in delivering significant therapeutic benefit. Apart from its established role as an essential cofactor for numerous enzymes, a large body of evidence suggests that B(6)-vitamers contain reactive pharmacophores that mediate therapeutically useful non-vitamin drug actions as potent antioxidants, metal chelators, carbonyl scavengers, Schiff base forming agents, and photosensitizers. Based on the fascinating chemical versatility of B(6)-derived pharmacophores, B(6)-vitamers are therefore promising lead compounds for reactivity-based drug design.
Oncogenic targets, magnitude of benefit, and market pricing of antineoplastic drugs.

PubMed

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

2011-06-20

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

PubMed Central

Hecker, Nikolai; Ahmed, Jessica; von Eichborn, Joachim; Dunkel, Mathias; Macha, Karel; Eckert, Andreas; Gilson, Michael K.; Bourne, Philip E.; Preissner, Robert

2012-01-01

There are at least two good reasons for the on-going interest in drug–target interactions: first, drug-effects can only be fully understood by considering a complex network of interactions to multiple targets (so-called off-target effects) including metabolic and signaling pathways; second, it is crucial to consider drug-target-pathway relations for the identification of novel targets for drug development. To address this on-going need, we have developed a web-based data warehouse named SuperTarget, which integrates drug-related information associated with medical indications, adverse drug effects, drug metabolism, pathways and Gene Ontology (GO) terms for target proteins. At present, the updated database contains >6000 target proteins, which are annotated with >330 000 relations to 196 000 compounds (including approved drugs); the vast majority of interactions include binding affinities and pointers to the respective literature sources. The user interface provides tools for drug screening and target similarity inclusion. A query interface enables the user to pose complex queries, for example, to find drugs that target a certain pathway, interacting drugs that are metabolized by the same cytochrome P450 or drugs that target proteins within a certain affinity range. SuperTarget is available at http://bioinformatics.charite.de/supertarget. PMID:22067455
In silico fragment-based drug design.

PubMed

Konteatis, Zenon D

2010-11-01

In silico fragment-based drug design (FBDD) is a relatively new approach inspired by the success of the biophysical fragment-based drug discovery field. Here, we review the progress made by this approach in the last decade and showcase how it complements and expands the capabilities of biophysical FBDD and structure-based drug design to generate diverse, efficient drug candidates. Advancements in several areas of research that have enabled the development of in silico FBDD and some applications in drug discovery projects are reviewed. The reader is introduced to various computational methods that are used for in silico FBDD, the fragment library composition for this technique, special applications used to identify binding sites on the surface of proteins and how to assess the druggability of these sites. In addition, the reader will gain insight into the proper application of this approach from examples of successful programs. In silico FBDD captures a much larger chemical space than high-throughput screening and biophysical FBDD increasing the probability of developing more diverse, patentable and efficient molecules that can become oral drugs. The application of in silico FBDD holds great promise for historically challenging targets such as protein-protein interactions. Future advances in force fields, scoring functions and automated methods for determining synthetic accessibility will all aid in delivering more successes with in silico FBDD.
Target therapy: new drugs or new combinations of drugs in malignant pleural mesothelioma.

PubMed

Zucali, Paolo A

2018-01-01

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

PubMed

Fornaro, Michele; Kardash, Lubna; Novello, Stefano; Fusco, Andrea; Anastasia, Annalisa; De Berardis, Domenico; Perna, Giampaolo; Carta, Mauro Giovanni

2018-03-01

Bipolar disorder (BD) is a considerable burden to the affected individual. The need for novel drug targets and improved drug design (DD) in BD is therefore clear. Areas covered: The following article provides a brief, narrative, clinician-oriented overview of the most promising novel pharmacological targets for BD along with a concise overview regarding the general DD process and the unmet needs relevant to BD. Expert opinion: A number of novel potential drug targets have been investigated. With the notable exception of the kynurenine pathway, available evidence is too scarce to highlight a definitive roadmap for forthcoming DD in BD. BD itself may present with different facets, as it is a polymorphic clinical spectrum. Therefore, promoting clinical-case stratification should be based on precision medicine, rather than on novel biological targets. Furthermore, the full release of raw study data to the scientific community and the development of uniform clinical trial standards (including more realistic outcomes) should be promoted to facilitate the DD process in BD.
Rule of five in 2015 and beyond: Target and ligand structural limitations, ligand chemistry structure and drug discovery project decisions.

PubMed

Lipinski, Christopher A

2016-06-01

The rule of five (Ro5), based on physicochemical profiles of phase II drugs, is consistent with structural limitations in protein targets and the drug target ligands. Three of four parameters in Ro5 are fundamental to the structure of both target and drug binding sites. The chemical structure of the drug ligand depends on the ligand chemistry and design philosophy. Two extremes of chemical structure and design philosophy exist; ligands constructed in the medicinal chemistry synthesis laboratory without input from natural selection and natural product (NP) metabolites biosynthesized based on evolutionary selection. Exceptions to Ro5 are found mostly among NPs. Chemistry chameleon-like behavior of some NPs due to intra-molecular hydrogen bonding as exemplified by cyclosporine A is a strong contributor to NP Ro5 outliers. The fragment derived, drug Navitoclax is an example of the extensive expertise, resources, time and key decisions required for the rare discovery of a non-NP Ro5 outlier. Copyright © 2016 Elsevier B.V. All rights reserved.
A Rapid Python-Based Methodology for Target-Focused Combinatorial Library Design.

PubMed

Li, Shiliang; Song, Yuwei; Liu, Xiaofeng; Li, Honglin

2016-01-01

The chemical space is so vast that only a small portion of it has been examined. As a complementary approach to systematically probe the chemical space, virtual combinatorial library design has extended enormous impacts on generating novel and diverse structures for drug discovery. Despite the favorable contributions, high attrition rates in drug development that mainly resulted from lack of efficacy and side effects make it increasingly challenging to discover good chemical starting points. In most cases, focused libraries, which are restricted to particular regions of the chemical space, are deftly exploited to maximize hit rate and improve efficiency at the beginning of the drug discovery and drug development pipeline. This paper presented a valid methodology for fast target-focused combinatorial library design in both reaction-based and production-based ways with the library creating rates of approximately 70,000 molecules per second. Simple, quick and convenient operating procedures are the specific features of the method. SHAFTS, a hybrid 3D similarity calculation software, was embedded to help refine the size of the libraries and improve hit rates. Two target-focused (p38-focused and COX2-focused) libraries were constructed efficiently in this study. This rapid library enumeration method is portable and applicable to any other targets for good chemical starting points identification collaborated with either structure-based or ligand-based virtual screening.
Drugs That Target Dynamic Microtubules: A New Molecular Perspective

PubMed Central

Stanton, Richard A.; Gernert, Kim M.; Nettles, James H.; Aneja, Ritu

2011-01-01

Microtubules have long been considered an ideal target for anticancer drugs because of the essential role they play in mitosis, forming the dynamic spindle apparatus. As such, there is a wide variety of compounds currently in clinical use and in development that act as antimitotic agents by altering microtubule dynamics. Although these diverse molecules are known to affect microtubule dynamics upon binding to one of the three established drug domains (taxane, vinca alkaloid, or colchicine site), the exact mechanism by which each drug works is still an area of intense speculation and research. In this study, we review the effects of microtubule-binding chemotherapeutic agents from a new perspective, considering how their mode of binding induces conformational changes and alters biological function relative to the molecular vectors of microtubule assembly or disassembly. These “biological vectors” can thus be used as a spatiotemporal context to describe molecular mechanisms by which microtubule-targeting drugs work. PMID:21381049

INTEGRATING GENETIC AND STRUCTURAL DATA ON HUMAN PROTEIN KINOME IN NETWORK-BASED MODELING OF KINASE SENSITIVITIES AND RESISTANCE TO TARGETED AND PERSONALIZED ANTICANCER DRUGS.

PubMed

Verkhivker, Gennady M

2016-01-01

The human protein kinome presents one of the largest protein families that orchestrate functional processes in complex cellular networks, and when perturbed, can cause various cancers. The abundance and diversity of genetic, structural, and biochemical data underlies the complexity of mechanisms by which targeted and personalized drugs can combat mutational profiles in protein kinases. Coupled with the evolution of system biology approaches, genomic and proteomic technologies are rapidly identifying and charactering novel resistance mechanisms with the goal to inform rationale design of personalized kinase drugs. Integration of experimental and computational approaches can help to bring these data into a unified conceptual framework and develop robust models for predicting the clinical drug resistance. In the current study, we employ a battery of synergistic computational approaches that integrate genetic, evolutionary, biochemical, and structural data to characterize the effect of cancer mutations in protein kinases. We provide a detailed structural classification and analysis of genetic signatures associated with oncogenic mutations. By integrating genetic and structural data, we employ network modeling to dissect mechanisms of kinase drug sensitivities to oncogenic EGFR mutations. Using biophysical simulations and analysis of protein structure networks, we show that conformational-specific drug binding of Lapatinib may elicit resistant mutations in the EGFR kinase that are linked with the ligand-mediated changes in the residue interaction networks and global network properties of key residues that are responsible for structural stability of specific functional states. A strong network dependency on high centrality residues in the conformation-specific Lapatinib-EGFR complex may explain vulnerability of drug binding to a broad spectrum of mutations and the emergence of drug resistance. Our study offers a systems-based perspective on drug design by unravelling
tLyP-1-conjugated mesoporous silica nanoparticles for tumor targeting and penetrating hydrophobic drug delivery

NASA Astrophysics Data System (ADS)

Xu, Baiyao; Ju, Yang; Song, Guanbin; Cui, Yanbin

2013-12-01

Mesoporous silica nanoparticles (MSNs) are among the most appealing candidates for targeted drug delivery, a process for which it is essential that nanoparticles be internalized into targeted cells with high speed and efficiency. Therefore, it is necessary to conjugate a targeting ligand to the surface of a nanocarrier in order to trigger rapid receptor-mediated endocytosis and effective cellular uptake, which occurs following recognition and selective binding to a target cell's membrane receptor. Here, a tumor targeting and penetrating drug delivery system (DDS) based on MSNs ( 100 nm in size) is described. The MSNs were functionalized by engrafting with the tumor-homing and penetrating peptide tLyP-1. The fabricated MSN-tLyP-1 loaded with camptothecin (CPT) showed a robust targeting and penetrating efficiency to HeLa cells and MCF-7 cells and induced the death of these cells. Moreover, the adverse side effect of CPT on human mesenchymal stem cells (hMSCs) was minimized, because the nanoparticles were selectively targeted to the tumor cells, and little hydrophobic CPT was released into the culture medium or blood. The results indicate that the MSN-tLyP-1 DDS has great potential for the delivery of hydrophobic anticancer drugs to target tumors.
Combinatorial Approaches for the Identification of Brain Drug Delivery Targets

PubMed Central

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
Formulation development and in-vitro/in-vivo correlation for a novel Sterculia gum-based oral colon-targeted drug delivery system of azathioprine.

PubMed

Nath, Bipul; Nath, Lila Kanta

2013-11-01

The present study was aimed at designing a microflora triggered colon-targeted drug delivery system (MCDDS) based on swellable polysaccharide, Sterculia gum in combination with biodegradable polymers with a view to target azathioprine (AZA) in the colon for the treatment of IBD with reduced systemic toxicity. The microflora degradation study of gum was investigated in rat cecal medium. The polysaccharide tablet was coated to different film thicknesses with blends of chitosan/Eudragit RLPO and over coated with Eudragit L00 to provide acid and intestinal resistance. Swelling and drug release studies were carried out in simulated gastric fluid (SGF) (pH 1.2), simulated intestinal fluid (SIF) (pH 6.8) and simulated colonic fluid (SCF) (pH 7.4 under anaerobic environment), respectively. Drug release study in SCF revealed that swelling force of the gum could concurrently drive the drug out of the polysaccharide core due to the rupture of the chitosan/Eudragit coating in microflora-activated environment. Chitosan in the mixed film coat was found to be degraded by enzymatic action of the microflora in the colon. Release kinetic data revealed that, the optimized MCDDS was fitted well into first order model and apparent lag time was found to be 6 h, followed by Higuchi spherical matrix release. The degradation of chitosan was the rate-limiting factor for drug release in the colon. In-vivo study in rabbit shows delayed T(max), prolonged absorption time, decreased C(max) and absorption rate constant (Ka) indicating reduced systemic toxicity of the drug as compared to other dosage forms.
Cytocompatible chitosan-graft-mPEG-based 5-fluorouracil-loaded polymeric nanoparticles for tumor-targeted drug delivery.

PubMed

Antoniraj, M Gover; Ayyavu, Mahesh; Henry, Linda Jeeva Kumari; Nageshwar Rao, Goutham; Natesan, Subramanian; Sundar, D Sathish; Kandasamy, Ruckmani

2018-03-01

Biodegradable materials like chitosan (CH) and methoxy polyethylene glycol (mPEG) are widely being used as drug delivery carriers for various therapeutic applications. In this study, copolymer (CH-g-mPEG) of CH and carboxylic acid terminated mPEG was synthesized by carbodiimide-mediated acid amine reaction. The resultant hydrophilic copolymer was characterized by Fourier transform infrared spectroscopy and 1 H NMR studies, revealing its relevant functional bands and proton peaks, respectively. Blank polymeric nanoparticles (B-PNPs) and 5-fluorouracil loaded polymeric nanoparticles (5-FU-PNPs) were formulated by ionic gelation method. Furthermore, folic acid functionalized FA-PNPs and FA-5-FU-PNPs were prepared for folate receptor-targeted drug delivery. FA-5-FU-PNPs were characterized by particle size, zeta potential, and in vitro drug release studies, resulting in 197.7 nm, +29.9 mv, and sustained drug release of 88% in 24 h, respectively. Cytotoxicity studies were performed for FA-PNPs and FA-5-FU-PNPs in MCF-7 cell line, which exhibited a cell viability of 80 and 41%, respectively. In vitro internalization studies were carried out for 5-FU-PNPs and FA-5-FU-PNPs which demonstrated increased cellular uptake of FA-5-FU-PNPs by receptor-mediated transport. Significant (p < .01) reduction (1.5-fold) of reactive oxygen species (ROS) accumulation was observed in lipopolysaccharides-stimulated RAW264.7 macrophages, revealing its potent antioxidant property. From the obtained results, it is concluded that folic acid functionalization of 5-FU-PNPs is an ideal approach for sustained and targeted drug delivery, thereby influencing better therapeutic effect.
Redox activation of metal-based prodrugs as a strategy for drug delivery

PubMed Central

Graf, Nora

2012-01-01

This review provides an overview of metal-based anticancer drugs and drug candidates. In particular, we focus on metal complexes that can be activated in the reducing environment of cancer cells, thus serving as prodrugs. There are many reports of Pt and Ru complexes as redox-activatable drug candidates, but other d-block elements with variable oxidation states have a similar potential to serve as prodrugs in this manner. In this context are compounds based on Fe, Co, or Cu chemistry, which are also covered. A trend in the field of medicinal inorganic chemistry has been toward molecularly targeted, metal-based drugs obtained by functionalizing complexes with biologically active ligands. Another recent activity is the use of nanomaterials for drug delivery, exploiting passive targeting of tumors with nanosized constructs made from Au, Fe, carbon, or organic polymers. Although complexes of all of the above mentioned metals will be described, this review focuses primarily on Pt compounds, including constructs containing nanomaterials. PMID:22289471
A drug-delivery strategy for overcoming drug resistance in breast cancer through targeting of oncofetal fibronectin.

PubMed

Saw, Phei Er; Park, Jinho; Jon, Sangyong; Farokhzad, Omid C

2017-02-01

A major problem with cancer chemotherapy begins when cells acquire resistance. Drug-resistant cancer cells typically upregulate multi-drug resistance proteins such as P-glycoprotein (P-gp). However, the lack of overexpressed surface biomarkers has limited the targeted therapy of drug-resistant cancers. Here we report a drug-delivery carrier decorated with a targeting ligand for a surface marker protein extra-domain B(EDB) specific to drug-resistant breast cancer cells as a new therapeutic option for the aggressive cancers. We constructed EDB-specific aptide (APT EDB )-conjugated liposome to simultaneously deliver siRNA(siMDR1) and Dox to drug-resistant breast cancer cells. APT EDB -LS(Dox,siMDR1) led to enhanced delivery of payloads into MCF7/ADR cells and showed significantly higher accumulation and retention in the tumors. While either APT EDB -LS(Dox) or APT EDB -LS(siMDR1) did not lead to appreciable tumor retardation in MCF7/ADR orthotropic model, APT EDB -LS(Dox,siMDR1) treatment resulted in significant reduction of the drug-resistant breast tumor. Taken together, this study provides a new strategy of drug delivery for drug-resistant cancer therapy. Copyright © 2016 Elsevier Inc. All rights reserved.
Identification of a Drug Targeting an Intrinsically Disordered Protein Involved in Pancreatic Adenocarcinoma

NASA Astrophysics Data System (ADS)

Neira, José L.; Bintz, Jennifer; Arruebo, María; Rizzuti, Bruno; Bonacci, Thomas; Vega, Sonia; Lanas, Angel; Velázquez-Campoy, Adrián; Iovanna, Juan L.; Abián, Olga

2017-01-01

Intrinsically disordered proteins (IDPs) are prevalent in eukaryotes, performing signaling and regulatory functions. Often associated with human diseases, they constitute drug-development targets. NUPR1 is a multifunctional IDP, over-expressed and involved in pancreatic ductal adenocarcinoma (PDAC) development. By screening 1120 FDA-approved compounds, fifteen candidates were selected, and their interactions with NUPR1 were characterized by experimental and simulation techniques. The protein remained disordered upon binding to all fifteen candidates. These compounds were tested in PDAC-derived cell-based assays, and all induced cell-growth arrest and senescence, reduced cell migration, and decreased chemoresistance, mimicking NUPR1-deficiency. The most effective compound completely arrested tumor development in vivo on xenografted PDAC-derived cells in mice. Besides reporting the discovery of a compound targeting an intact IDP and specifically active against PDAC, our study proves the possibility to target the ‘fuzzy’ interface of a protein that remains disordered upon binding to its natural biological partners or to selected drugs.
Identification of a Drug Targeting an Intrinsically Disordered Protein Involved in Pancreatic Adenocarcinoma

PubMed Central

Neira, José L.; Bintz, Jennifer; Arruebo, María; Rizzuti, Bruno; Bonacci, Thomas; Vega, Sonia; Lanas, Angel; Velázquez-Campoy, Adrián; Iovanna, Juan L.; Abián, Olga

2017-01-01

Intrinsically disordered proteins (IDPs) are prevalent in eukaryotes, performing signaling and regulatory functions. Often associated with human diseases, they constitute drug-development targets. NUPR1 is a multifunctional IDP, over-expressed and involved in pancreatic ductal adenocarcinoma (PDAC) development. By screening 1120 FDA-approved compounds, fifteen candidates were selected, and their interactions with NUPR1 were characterized by experimental and simulation techniques. The protein remained disordered upon binding to all fifteen candidates. These compounds were tested in PDAC-derived cell-based assays, and all induced cell-growth arrest and senescence, reduced cell migration, and decreased chemoresistance, mimicking NUPR1-deficiency. The most effective compound completely arrested tumor development in vivo on xenografted PDAC-derived cells in mice. Besides reporting the discovery of a compound targeting an intact IDP and specifically active against PDAC, our study proves the possibility to target the ‘fuzzy’ interface of a protein that remains disordered upon binding to its natural biological partners or to selected drugs. PMID:28054562
Environmentally friendly, one-pot synthesis of folic acid-decorated graphene oxide-based drug delivery system

NASA Astrophysics Data System (ADS)

Lin, Quankui; Huang, Xiaojie; Tang, Junmei; Han, Yuemei; Chen, Hao

2013-12-01

A targeted drug delivery system based on graphene oxide (GO) was produced via one-pot synthesis method, taking advantages of the self-polymerization of the dopamine (DA). The polymerization of dopamine resulted in polydopamine capped GO nanocomposite. Meanwhile, the anti-tumor drug doxorubicin (DOX) can be loaded in the nanocomposite and the tumor cell targeting molecule folic acid (FA) can also been immobilized on the nanocomposite surface simultaneously. The size of the obtained FA-decorated GO-based drug delivery system (DA/GO(DOX)-FA) is about 600 nm. It renders a sustained drug release manner. The cell culture results reveal that the FA-decorated GO-based drug delivery system (DA/GO(DOX)-FA) via one-pot method shows property of targeted killing of cancer cells in vitro. This one-pot method just needs the pH adjusting to induce the self-polymerization of DA, but excludes the fussy chemical grafting process and the organic solvents, which make it an environmentally friendly method to synthesize FA-decorated GO-based drug delivery system.
An RNAi-mediated screen identifies novel targets for next-generation antiepileptic drugs based on increased expression of the homeostatic regulator pumilio.

PubMed

Lin, Wei-Hsiang; He, Miaomiao; Fan, Yuen Ngan; Baines, Richard A

2018-05-02

Despite availability of a diverse range of anti-epileptic drugs (AEDs), only about two-thirds of epilepsy patients respond well to drug treatment. Thus, novel targets are required to catalyse the design of next-generation AEDs. Manipulation of neuron firing-rate homoeostasis, through enhancing Pumilio (Pum) activity, has been shown to be potently anticonvulsant in Drosophila. In this study, we performed a genome-wide RNAi screen in S2R + cells, using a luciferase-based dPum activity reporter and identified 1166 genes involved in dPum regulation. Of these genes, we focused on 699 genes that, on knock-down, potentiate dPum activity/expression. Of this subgroup, 101 genes are activity-dependent based on comparison with genes previously identified as activity-dependent by RNA-sequencing. Functional cluster analysis shows these genes are enriched in pathways involved in DNA damage, regulation of cell cycle and proteasomal protein catabolism. To test for anticonvulsant activity, we utilised an RNA-interference approach in vivo. RNAi-mediated knockdown showed that 57/101 genes (61%) are sufficient to significantly reduce seizure duration in the characterized seizure mutant, para bss . We further show that chemical inhibitors of protein products of some of the genes targeted are similarly anticonvulsant. Finally, to establish whether the anticonvulsant activity of identified compounds results from increased dpum transcription, we performed a luciferase-based assay to monitor dpum promoter activity. Third instar larvae exposed to sodium fluoride, gemcitabine, metformin, bestatin, WP1066 or valproic acid all showed increased dpum promoter activity. Thus, this study validates Pum as a favourable target for AED design and, moreover, identifies a number of lead compounds capable of increasing the expression of this homeostatic regulator.
Effects of target binding kinetics on in vivo drug efficacy: koff, kon and rebinding

PubMed Central

2016-01-01

Abstract Background and Purpose Optimal drug therapy often requires continuing high levels of target occupancy. Besides the traditional pharmacokinetic contribution, target binding kinetics is increasingly considered to play an important role as well. While most attention has been focused on the dissociation rate of the complex, recent reports expressed doubt about the unreserved translatability of this pharmacodynamic property into clinical efficacy. ‘Micro’‐pharmacokinetic mechanisms like drug rebinding and partitioning into the cell membrane may constitute a potential fix. Experimental Approach Simulations were based on solving differential equations. Key Results Based on a selected range of association and dissociation rate constants, kon and koff, and rebinding potencies of the drugs as variables, their effects on the temporal in vivo occupancy profile of their targets, after one or multiple repetitive dosings, have here been simulated. Conclusions and Implications Most strikingly, the simulations show that, when rebinding is also taken into account, increasing kon may produce closely the same outcome as decreasing koff when dosing is performed in accordance with the therapeutically most relevant constant [Lmax]/K D ratio paradigm. Also, under certain conditions, rebinding may produce closely the same outcome as invoking slow diffusion of the drug between the plasma compartment and a target‐containing ‘effect’ compartment. Although the present simulations should only be regarded as a ‘proof of principle’, these findings may help pharmacologists and medicinal chemists to devise ex vivo and in vitro binding kinetic assays that are more relevant and translatable to in vivo settings. PMID:27129075
Targeting ALK: Precision Medicine Takes On Drug Resistance

PubMed Central

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

2017-01-01

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

PubMed

Iangcharoen, Pantiwa; Punfa, Wanisa; Yodkeeree, Supachai; Kasinrerk, Watchara; Ampasavate, Chadarat; Anuchapreeda, Songyot; Limtrakul, Pornngarm

2011-10-01

Targeting therapeutics to specific sites can enhance the efficacy of drugs, reduce required doses as well as unwanted side effects. In this work, using the advantages of the specific affinity of an immobilized antibody to membrane P-gp in two different nanoparticle formulations were thus developed for targeted drug delivery to multi-drug resistant cervical carcinoma (KB-V1) cells. Further, this was compared to the human drug sensitive cervical carcinoma cell line (KB-3-1) cells. The two nanoparticle preparations were: NP1, anti-P-gp conjugated with poly (DL-lactic-coglycolic acid) (PLGA) nanoparticle and polyethylene glycol (PEG); NP2, anti-P-gp conjugated to a modified poloxamer on PLGA nanoparticles. The cellular uptake capacity of nanoparticles was confirmed by fluorescent microscopy. Comparing with each counterpart core particles, there was a higher fluorescence intensity of the targeted nanoparticles in KBV1 cells compared to KB-3-1 cells suggesting that the targeted nanoparticles were internalized into KB-V1 cells to a greater extent than KB-3-1 cell. The results had confirmed the specificity and the potential of the developed targeted delivery system for overcoming multi-drug resistance induced by overexpression of P-gp on the cell membrane.
Internalized compartments encapsulated nanogels for targeted drug delivery

NASA Astrophysics Data System (ADS)

Yu, Jicheng; Zhang, Yuqi; Sun, Wujin; Wang, Chao; Ranson, Davis; Ye, Yanqi; Weng, Yuyan; Gu, Zhen

2016-04-01

Drug delivery systems inspired by natural particulates hold great promise for targeted cancer therapy. An endosome formed by internalization of plasma membrane has a massive amount of membrane proteins and receptors on the surface, which is able to specifically target the homotypic cells. Herein, we describe a simple method to fabricate an internalized compartments encapsulated nanogel with endosome membrane components (EM-NG) from source cancer cells. Following intracellular uptake of methacrylated hyaluronic acid (m-HA) adsorbed SiO2/Fe3O4 nanoparticles encapsulating a crosslinker and a photoinitiator, EM-NG was readily prepared through in situ crosslinking initiated under UV irradiation after internalization. The resulting nanogels loaded with doxorubicin (DOX) displayed enhanced internalization efficiency to the source cells through a specific homotypic affinity in vitro. However, when treated with the non-source cells, the EM-NGs exhibited insignificant difference in therapeutic efficiency compared to a bare HA nanogel with DOX. This study illustrates the potential of utilizing an internalized compartments encapsulated formulation for targeted cancer therapy, and offers guidelines for developing a natural particulate-inspired drug delivery system.Drug delivery systems inspired by natural particulates hold great promise for targeted cancer therapy. An endosome formed by internalization of plasma membrane has a massive amount of membrane proteins and receptors on the surface, which is able to specifically target the homotypic cells. Herein, we describe a simple method to fabricate an internalized compartments encapsulated nanogel with endosome membrane components (EM-NG) from source cancer cells. Following intracellular uptake of methacrylated hyaluronic acid (m-HA) adsorbed SiO2/Fe3O4 nanoparticles encapsulating a crosslinker and a photoinitiator, EM-NG was readily prepared through in situ crosslinking initiated under UV irradiation after internalization. The
PLGA/polymeric liposome for targeted drug and gene co-delivery.

PubMed

Wang, Hanjie; Zhao, Peiqi; Su, Wenya; Wang, Sheng; Liao, Zhenyu; Niu, Ruifang; Chang, Jin

2010-11-01

Chemotherapy is one of the most effective approaches to treat cancers in the clinic, but the problems, such as multidrug resistance (MDR), low bioavailability and toxicity, severely constrain the further application of chemotherapy. Our group recently reported that cationic PLGA/folate coated PEGlated polymeric liposome core-shell nanoparticles (PLGA/FPL NPs). It was self-assembled from a hydrophobic PLGA core and a hydrophilic folate coated PEGlated lipid shell for targeting co-delivery of drug and gene. Hydrophobic drugs can be incorporated into the core and the cationic shell of the drug-loaded nanoparticles can be used to bind DNA. The drug-loaded PLGA/FPL NPs/DNA complexes offer advantages to overcome these problems mentioned above, such as co-delivery of drugs and DNA to improving the chemosensitivity of cancer cells at a gene level, and targeting delivery of drug to the cancer tissue that enhance the bioavailability and reduce the toxicity. The experiment showed that nanoparticles have core-shell structure with nanosize, sustained drug release profile and good DNA-binding ability. Importantly, the core-shell nanoparticles achieve the possibility of co-delivering drugs and genes to the same cells with high gene transfection and drug delivery efficiency. Our data suggest that the PLGA/FPL NPs may be a useful drug and gene co-delivery system. Copyright © 2010 Elsevier Ltd. All rights reserved.
Self-assembling toxin-based nanoparticles as self-delivered antitumoral drugs.

PubMed

Sánchez-García, Laura; Serna, Naroa; Álamo, Patricia; Sala, Rita; Céspedes, María Virtudes; Roldan, Mònica; Sánchez-Chardi, Alejandro; Unzueta, Ugutz; Casanova, Isolda; Mangues, Ramón; Vázquez, Esther; Villaverde, Antonio

2018-03-28

Loading capacity and drug leakage from vehicles during circulation in blood is a major concern when developing nanoparticle-based cell-targeted cytotoxics. To circumvent this potential issue it would be convenient the engineering of drugs as self-delivered nanoscale entities, devoid of any heterologous carriers. In this context, we have here engineered potent protein toxins, namely segments of the diphtheria toxin and the Pseudomonas aeruginosa exotoxin as self-assembling, self-delivered therapeutic materials targeted to CXCR4 + cancer stem cells. The systemic administration of both nanostructured drugs in a colorectal cancer xenograft mouse model promotes efficient and specific local destruction of target tumor tissues and a significant reduction of the tumor volume. This observation strongly supports the concept of intrinsically functional protein nanoparticles, which having a dual role as drug and carrier, are designed to be administered without the assistance of heterologous vehicles. Copyright © 2018 Elsevier B.V. All rights reserved.
Amphiphilic Cyclodextrin Derivatives for Targeted Drug Delivery to Tumors.

PubMed

Erdogar, Nazlı; Varan, Gamze; Bilensoy, Erem

2017-01-01

Villiers has extensively studied cyclodextrins, a family of macrocyclic oligosaccharides linked by α-1,4 glycosidic bonds, in different fields since their discovery in 1891. The unique structure enabling inclusion complexation for natural cyclodextrins and cyclodextrin derivatives make them attractive for novel drug delivery systems. Cyclodextrins can be modified with long aliphatic chains to render an amphiphilic property and these different amphiphilic cyclodextrins are able to form nanoparticles without surfactants. In the literature, several different amphiphilic cyclodextrins are reported and applied to drug delivery and targeting especially to tumors. Specificly, folateconjugated amphiphilic cyclodextrin derivatives are used for active tumor targeting of poorly water soluble drugs and improve the efficacy and safety of therapeutic agents. On the other hand, effect of positive surface charge has also been under research in the recent years. Polycationic amphiphilic cyclodextrins have shown promise towards forming small complexes with negatively charged molecules such as drugs or plasmid DNA. Polycationic amphiphilic cyclodextrins enhance interaction with cell membrane due to their net positive surface charge. The scope of this review is to describe potential uses and pharmaceutical applications of tumor-targeted amphiphilic cyclodextrins, with focus on folate-conjugated cyclodextrin derivatives and polycationic cyclodextrin derivatives both studied by our group at Hacettepe University. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Pharmacological and Physical Vessel Modulation Strategies to Improve EPR-mediated Drug Targeting to Tumors

PubMed Central

Ojha, Tarun; Pathak, Vertika; Shi, Yang; Hennink, Wim; Moonen, Chrit; Storm, Gert; Kiessling, Fabian; Lammers, Twan

2018-01-01

The performance of nanomedicine formulations depends on the Enhanced Permeability and Retention (EPR) effect. Prototypic nanomedicine-based drug delivery systems, such as liposomes, polymers and micelles, aim to exploit the EPR effect to accumulate at pathological sites, to thereby improve the balance between drug efficacy and toxicity. Thus far, however, tumor-targeted nanomedicines have not yet managed to achieve convincing therapeutic results, at least not in large cohorts of patients. This is likely mostly due to high inter- and intra-patient heterogeneity in EPR. Besides developing (imaging) biomarkers to monitor and predict EPR, another strategy to address this heterogeneity is the establishment of vessel modulation strategies to homogenize and improve EPR. Over the years, several pharmacological and physical co-treatments have been evaluated to improve EPR-mediated tumor targeting. These include pharmacological strategies, such as vessel permeabilization, normalization, disruption and promotion, as well as physical EPR enhancement via hyperthermia, radiotherapy, sonoporation and phototherapy. In the present manuscript, we summarize exemplary studies showing that pharmacological and physical vessel modulation strategies can be used to improve tumor-targeted drug delivery, and we discuss how these advanced combination regimens can be optimally employed to enhance the (pre-) clinical performance of tumor-targeted nanomedicines. PMID:28697952
Pharmacological and physical vessel modulation strategies to improve EPR-mediated drug targeting to tumors.

PubMed

Ojha, Tarun; Pathak, Vertika; Shi, Yang; Hennink, Wim E; Moonen, Chrit T W; Storm, Gert; Kiessling, Fabian; Lammers, Twan

2017-09-15

The performance of nanomedicine formulations depends on the Enhanced Permeability and Retention (EPR) effect. Prototypic nanomedicine-based drug delivery systems, such as liposomes, polymers and micelles, aim to exploit the EPR effect to accumulate at pathological sites, to thereby improve the balance between drug efficacy and toxicity. Thus far, however, tumor-targeted nanomedicines have not yet managed to achieve convincing therapeutic results, at least not in large cohorts of patients. This is likely mostly due to high inter- and intra-patient heterogeneity in EPR. Besides developing (imaging) biomarkers to monitor and predict EPR, another strategy to address this heterogeneity is the establishment of vessel modulation strategies to homogenize and improve EPR. Over the years, several pharmacological and physical co-treatments have been evaluated to improve EPR-mediated tumor targeting. These include pharmacological strategies, such as vessel permeabilization, normalization, disruption and promotion, as well as physical EPR enhancement via hyperthermia, radiotherapy, sonoporation and phototherapy. In the present manuscript, we summarize exemplary studies showing that pharmacological and physical vessel modulation strategies can be used to improve tumor-targeted drug delivery, and we discuss how these advanced combination regimens can be optimally employed to enhance the (pre-) clinical performance of tumor-targeted nanomedicines. Copyright © 2017 Elsevier B.V. All rights reserved.

Neuropilin-1-targeted gold nanoparticles enhance therapeutic efficacy of platinum(IV) drug for prostate cancer treatment.

PubMed

Kumar, Anil; Huo, Shuaidong; Zhang, Xu; Liu, Juan; Tan, Aaron; Li, Shengliang; Jin, Shubin; Xue, Xiangdong; Zhao, YuanYuan; Ji, Tianjiao; Han, Lu; Liu, Hong; Zhang, XiaoNing; Zhang, Jinchao; Zou, Guozhang; Wang, Tianyou; Tang, Suoqin; Liang, Xing-Jie

2014-05-27

Platinum-based anticancer drugs such as cisplatin, oxaliplatin, and carboplatin are some of the most potent chemotherapeutic agents but have limited applications due to severe dose-limiting side effects and a tendency for cancer cells to rapidly develop resistance. The therapeutic index can be improved through use of nanocarrier systems to target cancer cells efficiently. We developed a unique strategy to deliver a platinum(IV) drug to prostate cancer cells by constructing glutathione-stabilized (Au@GSH) gold nanoparticles. Glutathione (GSH) has well-known antioxidant properties, which lead to cancer regression. Here, we exploit the advantages of both the antioxidant properties and high surface-area-to-volume ratio of Au@GSH NPs to demonstrate their potential for delivery of a platinum(IV) drug by targeting the neuropilin-1 receptor (Nrp-1). A lethal dose of a platinum(IV) drug functionalized with the Nrp-1-targeting peptide (CRGDK) was delivered specifically to prostate cancer cells in vitro. Targeted peptide ensures specific binding to the Nrp-1 receptor, leading to enhanced cellular uptake level and cell toxicity. The nanocarriers were themselves nontoxic, but exhibited high cytotoxicity and increased efficacy when functionalized with the targeting peptide and drug. The uptake of drug-loaded nanocarriers is dependent on the interaction with Nrp-1 in cell lines expressing high (PC-3) and low (DU-145) levels of Nrp-1, as confirmed through inductively coupled plasma mass spectrometry and confocal microscopy. The nanocarriers have effective anticancer activity, through upregulation of nuclear factor kappa-B (NF-κB) protein (p50 and p65) expression and activation of NF-κB-DNA-binding activity. Our preliminary investigations with platinum(IV)-functionalized gold nanoparticles along with a targeting peptide hold significant promise for future cancer treatment.
Circulating Magnetic Microbubbles for Localized Real-Time Control of Drug Delivery by Ultrasonography-Guided Magnetic Targeting and Ultrasound

PubMed Central

Chertok, Beata; Langer, Robert

2018-01-01

Image-guided and target-selective modulation of drug delivery by external physical triggers at the site of pathology has the potential to enable tailored control of drug targeting. Magnetic microbubbles that are responsive to magnetic and acoustic modulation and visible to ultrasonography have been proposed as a means to realize this drug targeting strategy. To comply with this strategy in vivo, magnetic microbubbles must circulate systemically and evade deposition in pulmonary capillaries, while also preserving magnetic and acoustic activities in circulation over time. Unfortunately, challenges in fabricating magnetic microbubbles with such characteristics have limited progress in this field. In this report, we develop magnetic microbubbles (MagMB) that display strong magnetic and acoustic activities, while also preserving the ability to circulate systemically and evade pulmonary entrapment. Methods: We systematically evaluated the characteristics of MagMB including their pharmacokinetics, biodistribution, visibility to ultrasonography and amenability to magneto-acoustic modulation in tumor-bearing mice. We further assessed the applicability of MagMB for ultrasonography-guided control of drug targeting. Results: Following intravenous injection, MagMB exhibited a 17- to 90-fold lower pulmonary entrapment compared to previously reported magnetic microbubbles and mimicked circulation persistence of the clinically utilized Definity microbubbles (>10 min). In addition, MagMB could be accumulated in tumor vasculature by magnetic targeting, monitored by ultrasonography and collapsed by focused ultrasound on demand to activate drug deposition at the target. Furthermore, drug delivery to target tumors could be enhanced by adjusting the magneto-acoustic modulation based on ultrasonographic monitoring of MagMB in real-time. Conclusions: Circulating MagMB in conjunction with ultrasonography-guided magneto-acoustic modulation may provide a strategy for tailored minimally
Drug resistance to targeted therapies: déjà vu all over again.

PubMed

Groenendijk, Floris H; Bernards, René

2014-09-12

A major limitation of targeted anticancer therapies is intrinsic or acquired resistance. This review emphasizes similarities in the mechanisms of resistance to endocrine therapies in breast cancer and those seen with the new generation of targeted cancer therapeutics. Resistance to single-agent cancer therapeutics is frequently the result of reactivation of the signaling pathway, indicating that a major limitation of targeted agents lies in their inability to fully block the cancer-relevant signaling pathway. The development of mechanism-based combinations of targeted therapies together with non-invasive molecular disease monitoring is a logical way forward to delay and ultimately overcome drug resistance development. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.
Assembling of stimuli-responsive tumor targeting polypyrrole nanotubes drug carrier system for controlled release.

PubMed

Chen, Jian; Li, Xiufang; Li, Jiawen; Li, Jianbing; Huang, Ling; Ren, Tao; Yang, Xiao; Zhong, Shian

2018-08-01

A stimuli-responsive polypyrrole (PPy) nanotubes drug carrier system has been designed to deliver anticancer drugs to tumor cells in a targeted and controlled manner. The PPy nanotubes drug carrier was fabricated by a template method. The nanotubes surface was functionalized with cleavable acylhydrazone and disulfide bonds by attaching thiolated β-cyclodextrin (β-CD). The solubilizing poly(ethylene glycol) polymer (PEG), attached with an adamantane (Ad) entity at one end and a folate (FA) entity at the other end, was introduced onto the nanotubes surface via β-cyclodextrin-adamantane interaction. The synthesized FA-PEG-Ad-β-CD-PPy showed excellent biocompatibility and low cytotoxicity for two cell lines. Doxorubicin (Dox) loaded FA-PEG-Ad-β-CD-PPy nanotubes showed a triggered in vitro drug release behavior in the presence of acidic media and reducing agents. The folate-mediated endocytosis and intracellular release of Dox-loaded nanoparticles were confirmed by fluorescence microscopy and cell viability evaluations. In the in vitro study, Dox loaded within the nanoparticles showed enhanced selectivity for cancerous cells and reduced cytotoxicity for normal cells compared to free Dox. The PPy based targeted drug vehicle shows excellent promise for drug delivery. Copyright © 2018 Elsevier B.V. All rights reserved.
A smart multifunctional nanocomposite for intracellular targeted drug delivery and self-release

NASA Astrophysics Data System (ADS)

Wang, Chan; Lv, Piping; Wei, Wei; Tao, Shengyang; Hu, Tao; Yang, Jingbang; Meng, Changgong

2011-10-01

A multifunctional 'all-in-one' nanocomposite is fabricated using a colloid, template and surface-modification method. This material encompasses magnetic induced target delivery, cell uptake promotion and controlled drug release in one system. The nanocomposite is characterized by scanning electron microscopy, transmission electron microscopy, x-ray diffraction, N2 adsorption and vibrating sample magnetometry. The prepared material has a diameter of 350-400 nm, a high surface area of 420.29 m2 g - 1, a pore size of 1.91 nm and a saturation magnetization of 32 emu g - 1. Doxorubicin (DOX) is loaded in mesopores and acid-sensitive blockers are introduced onto the orifices of the mesopores by a Schiff base linker to implement pH-dependent self-release. Folate was also introduced to improve DOX targeted delivery and endocytosis. The linkers remained intact to block pores with ferrocene valves and inhibit the diffusion of DOX at neutral pH. However, in lysosomes of cancer cells, which have a weak acidic pH, hydrolysis of the Schiff base group removes the nanovalves and allows the trapped DOX to be released. These processes are demonstrated by UV-visible absorption spectra, confocal fluorescence microscopy images and methyl thiazolyl tetrazolium assays in vitro, which suggest that the smart nanocomposite successfully integrates targeted drug delivery with internal stimulus induced self-release and is a potentially useful material for nanobiomedicine.
Improved prediction of drug-target interactions using regularized least squares integrating with kernel fusion technique.

PubMed

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

2016-02-25

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

PubMed

Wilson, A Nolan; Guiseppi-Elie, Anthony

2014-01-30

A drug delivery platform comprising a biocompatible, bioresponsive hydrogel and possessing a covalently tethered peptide-drug conjugate was engineered to achieve stasis, via a closed control loop, of the external biochemical activity of the actuating protease. The delivery platform contains a peptide-drug conjugate covalently tethered to the hydrogel matrix, which in the presence of the appropriate protease, was cleaved and the drug released into the bathing environment. This platform was developed and investigated in silico using a finite element modeling (FEM) approach. Firstly, the primary governing phenomena guiding drug release profiles were investigated, and it was confirmed that under transport-limited conditions, the diffusion of the enzyme within the hydrogel and the coupled enzyme kinetics accurately model the system and are in agreement with published results. Secondly, the FEM model was used to investigate the release of a competitive protease inhibitor, MAG283, via cleavage of Acetyl-Pro-Leu-Gly|Leu-MAG-283 by MMP9 in order to achieve targeted homeostasis of MMP-9 activity, such as in the pathophysiology of chronic wounds, via closed-loop feedback control. The key engineering parameters for the delivery device are the radii of the hydrogel microspheres and the concentration of the peptide-inhibitor conjugate. Homeostatic drug delivery, where the focus turns away from the drug release rate and turns toward achieving targeted control of biochemical activity within a biochemical pathway, is an emerging approach in drug delivery methodologies for which the potential has not yet been fully realized. Copyright © 2013 Elsevier B.V. All rights reserved.
FDA approved drugs complexed to their targets: evaluating pose prediction accuracy of docking protocols.

PubMed

Bohari, Mohammed H; Sastry, G Narahari

2012-09-01

Efficient drug discovery programs can be designed by utilizing existing pools of knowledge from the already approved drugs. This can be achieved in one way by repositioning of drugs approved for some indications to newer indications. Complex of drug to its target gives fundamental insight into molecular recognition and a clear understanding of putative binding site. Five popular docking protocols, Glide, Gold, FlexX, Cdocker and LigandFit have been evaluated on a dataset of 199 FDA approved drug-target complexes for their accuracy in predicting the experimental pose. Performance for all the protocols is assessed at default settings, with root mean square deviation (RMSD) between the experimental ligand pose and the docked pose of less than 2.0 Å as the success criteria in predicting the pose. Glide (38.7 %) is found to be the most accurate in top ranked pose and Cdocker (58.8 %) in top RMSD pose. Ligand flexibility is a major bottleneck in failure of docking protocols to correctly predict the pose. Resolution of the crystal structure shows an inverse relationship with the performance of docking protocol. All the protocols perform optimally when a balanced type of hydrophilic and hydrophobic interaction or dominant hydrophilic interaction exists. Overall in 16 different target classes, hydrophobic interactions dominate in the binding site and maximum success is achieved for all the docking protocols in nuclear hormone receptor class while performance for the rest of the classes varied based on individual protocol.
Computational modeling and in-vitro/in-silico correlation of phospholipid-based prodrugs for targeted drug delivery in inflammatory bowel disease

NASA Astrophysics Data System (ADS)

Dahan, Arik; Markovic, Milica; Keinan, Shahar; Kurnikov, Igor; Aponick, Aaron; Zimmermann, Ellen M.; Ben-Shabat, Shimon

2017-11-01

Targeting drugs to the inflamed intestinal tissue(s) represents a major advancement in the treatment of inflammatory bowel disease (IBD). In this work we present a powerful in-silico modeling approach to guide the molecular design of novel prodrugs targeting the enzyme PLA2, which is overexpressed in the inflamed tissues of IBD patients. The prodrug consists of the drug moiety bound to the sn-2 position of phospholipid (PL) through a carbonic linker, aiming to allow PLA2 to release the free drug. The linker length dictates the affinity of the PL-drug conjugate to PLA2, and the optimal linker will enable maximal PLA2-mediated activation. Thermodynamic integration and Weighted Histogram Analysis Method (WHAM)/Umbrella Sampling method were used to compute the changes in PLA2 transition state binding free energy of the prodrug molecule (ΔΔGtr) associated with decreasing/increasing linker length. The simulations revealed that 6-carbons linker is the optimal one, whereas shorter or longer linkers resulted in decreased PLA2-mediated activation. These in-silico results were shown to be in excellent correlation with experimental in-vitro data. Overall, this modern computational approach enables optimization of the molecular design of novel prodrugs, which may allow targeting the free drug specifically to the diseased intestinal tissue of IBD patients.
A Framework of Knowledge Integration and Discovery for Supporting Pharmacogenomics Target Predication of Adverse Drug Events: A Case Study of Drug-Induced Long QT Syndrome.

PubMed

Jiang, Guoqian; Wang, Chen; Zhu, Qian; Chute, Christopher G

2013-01-01

Knowledge-driven text mining is becoming an important research area for identifying pharmacogenomics target genes. However, few of such studies have been focused on the pharmacogenomics targets of adverse drug events (ADEs). The objective of the present study is to build a framework of knowledge integration and discovery that aims to support pharmacogenomics target predication of ADEs. We integrate a semantically annotated literature corpus Semantic MEDLINE with a semantically coded ADE knowledgebase known as ADEpedia using a semantic web based framework. We developed a knowledge discovery approach combining a network analysis of a protein-protein interaction (PPI) network and a gene functional classification approach. We performed a case study of drug-induced long QT syndrome for demonstrating the usefulness of the framework in predicting potential pharmacogenomics targets of ADEs.
Multifunctional Nanocarriers for diagnostics, drug delivery and targeted treatment across blood-brain barrier: perspectives on tracking and neuroimaging.

PubMed

Bhaskar, Sonu; Tian, Furong; Stoeger, Tobias; Kreyling, Wolfgang; de la Fuente, Jesús M; Grazú, Valeria; Borm, Paul; Estrada, Giovani; Ntziachristos, Vasilis; Razansky, Daniel

2010-03-03

Nanotechnology has brought a variety of new possibilities into biological discovery and clinical practice. In particular, nano-scaled carriers have revolutionalized drug delivery, allowing for therapeutic agents to be selectively targeted on an organ, tissue and cell specific level, also minimizing exposure of healthy tissue to drugs. In this review we discuss and analyze three issues, which are considered to be at the core of nano-scaled drug delivery systems, namely functionalization of nanocarriers, delivery to target organs and in vivo imaging. The latest developments on highly specific conjugation strategies that are used to attach biomolecules to the surface of nanoparticles (NP) are first reviewed. Besides drug carrying capabilities, the functionalization of nanocarriers also facilitate their transport to primary target organs. We highlight the leading advantage of nanocarriers, i.e. their ability to cross the blood-brain barrier (BBB), a tightly packed layer of endothelial cells surrounding the brain that prevents high-molecular weight molecules from entering the brain. The BBB has several transport molecules such as growth factors, insulin and transferrin that can potentially increase the efficiency and kinetics of brain-targeting nanocarriers. Potential treatments for common neurological disorders, such as stroke, tumours and Alzheimer's, are therefore a much sought-after application of nanomedicine. Likewise any other drug delivery system, a number of parameters need to be registered once functionalized NPs are administered, for instance their efficiency in organ-selective targeting, bioaccumulation and excretion. Finally, direct in vivo imaging of nanomaterials is an exciting recent field that can provide real-time tracking of those nanocarriers. We review a range of systems suitable for in vivo imaging and monitoring of drug delivery, with an emphasis on most recently introduced molecular imaging modalities based on optical and hybrid contrast, such as
A Bioinformatic Pipeline for Monitoring of the Mutational Stability of Viral Drug Targets with Deep-Sequencing Technology.

PubMed

Kravatsky, Yuri; Chechetkin, Vladimir; Fedoseeva, Daria; Gorbacheva, Maria; Kravatskaya, Galina; Kretova, Olga; Tchurikov, Nickolai

2017-11-23

The efficient development of antiviral drugs, including efficient antiviral small interfering RNAs (siRNAs), requires continuous monitoring of the strict correspondence between a drug and the related highly variable viral DNA/RNA target(s). Deep sequencing is able to provide an assessment of both the general target conservation and the frequency of particular mutations in the different target sites. The aim of this study was to develop a reliable bioinformatic pipeline for the analysis of millions of short, deep sequencing reads corresponding to selected highly variable viral sequences that are drug target(s). The suggested bioinformatic pipeline combines the available programs and the ad hoc scripts based on an original algorithm of the search for the conserved targets in the deep sequencing data. We also present the statistical criteria for the threshold of reliable mutation detection and for the assessment of variations between corresponding data sets. These criteria are robust against the possible sequencing errors in the reads. As an example, the bioinformatic pipeline is applied to the study of the conservation of RNA interference (RNAi) targets in human immunodeficiency virus 1 (HIV-1) subtype A. The developed pipeline is freely available to download at the website http://virmut.eimb.ru/. Brief comments and comparisons between VirMut and other pipelines are also presented.
DDR: efficient computational method to predict drug-target interactions using graph mining and machine learning approaches.

PubMed

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

2018-04-01

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

PubMed

Sierra, Carlos; Acosta, Camilo; Chen, Cherry; Wu, Shih-Ying; Karakatsani, Maria E; Bernal, Manuel; Konofagou, Elisa E

2017-04-01

Focused ultrasound in conjunction with lipid microbubbles has fully demonstrated its ability to induce non-invasive, transient, and reversible blood-brain barrier opening. This study was aimed at testing the feasibility of our lipid-coated microbubbles as a vector for targeted drug delivery in the treatment of central nervous system diseases. These microbubbles were labeled with the fluorophore 5-dodecanoylaminfluorescein. Focused ultrasound targeted mouse brains in vivo in the presence of these microbubbles for trans-blood-brain barrier delivery of 5-dodecanoylaminfluorescein. This new approach, compared to previously studies of our group, where fluorescently labeled dextrans and microbubbles were co-administered, represents an appreciable improvement in safety outcome and targeted drug delivery. This novel technique allows the delivery of 5-dodecanoylaminfluorescein at the region of interest unlike the alternative of systemic exposure. 5-dodecanoylaminfluorescein delivery was assessed by ex vivo fluorescence imaging and by in vivo transcranial passive cavitation detection. Stable and inertial cavitation doses were quantified. The cavitation dose thresholds for estimating, a priori, successful targeted drug delivery were, for the first time, identified with inertial cavitation were concluded to be necessary for successful delivery. The findings presented herein indicate the feasibility and safety of the proposed microbubble-based targeted drug delivery and that, if successful, can be predicted by cavitation detection in vivo.
Prioritizing and modelling of putative drug target proteins of Candida albicans by systems biology approach.

PubMed

Ismail, Tariq; Fatima, Nighat; Muhammad, Syed Aun; Zaidi, Syed Saoud; Rehman, Nisar; Hussain, Izhar; Tariq, Najam Us Sahr; Amirzada, Imran; Mannan, Abdul

2018-01-01

Candida albicans (Candida albicans) is one of the major sources of nosocomial infections in humans which may prove fatal in 30% of cases. The hospital acquired infection is very difficult to treat affectively due to the presence of drug resistant pathogenic strains, therefore there is a need to find alternative drug targets to cure this infection. In silico and computational level frame work was used to prioritize and establish antifungal drug targets of Candida albicans. The identification of putative drug targets was based on acquiring 5090 completely annotated genes of Candida albicans from available databases which were categorized into essential and non-essential genes. The result indicated that 9% of proteins were essential and could become potential candidates for intervention which might result in pathogen eradication. We studied cluster of orthologs and the subtractive genomic analysis of these essential proteins against human genome was made as a reference to minimize the side effects. It was seen that 14% of Candida albicans proteins were evolutionary related to the human proteins while 86% are non-human homologs. In the next step of compatible drug target selections, the non-human homologs were sequentially compared to the human microbiome data to minimize the potential effects against gut flora which accumulated to 38% of the essential genome. The sub-cellular localization of these candidate proteins in fungal cellular systems indicated that 80% of them are cytoplasmic, 10% are mitochondrial and the remaining 10% are associated with the cell wall. The role of these non-human and non-gut flora putative target proteins in Candida albicans biological pathways was studied. Due to their integrated and critical role in Candida albicans replication cycle, four proteins were selected for molecular modeling. For drug designing and development, four high quality and reliable protein models with more than 70% sequence identity were constructed. These proteins are
RecA: a universal drug target in pathogenic bacteria.

PubMed

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.
Physics considerations in targeted anticancer drug delivery by magnetoelectric nanoparticles

NASA Astrophysics Data System (ADS)

Stimphil, Emmanuel; Nagesetti, Abhignyan; Guduru, Rakesh; Stewart, Tiffanie; Rodzinski, Alexandra; Liang, Ping; Khizroev, Sakhrat

2017-06-01

In regard to cancer therapy, magnetoelectric nanoparticles (MENs) have proven to be in a class of its own when compared to any other nanoparticle type. Like conventional magnetic nanoparticles, they can be used for externally controlled drug delivery via application of a magnetic field gradient and image-guided delivery. However, unlike conventional nanoparticles, due to the presence of a non-zero magnetoelectric effect, MENs provide a unique mix of important properties to address key challenges in modern cancer therapy: (i) a targeting mechanism driven by a physical force rather than antibody matching, (ii) a high-specificity delivery to enhance the cellular uptake of therapeutic drugs across the cancer cell membranes only, while sparing normal cells, (iii) an externally controlled mechanism to release drugs on demand, and (iv) a capability for image guided precision medicine. These properties separate MEN-based targeted delivery from traditional biotechnology approaches and lay a foundation for the complementary approach of technobiology. The biotechnology approach stems from the underlying biology and exploits bioinformatics to find the right therapy. In contrast, the technobiology approach is geared towards using the physics of molecular-level interactions between cells and nanoparticles to treat cancer at the most fundamental level and thus can be extended to all the cancers. This paper gives an overview of the current state of the art and presents an ab initio model to describe the underlying mechanisms of cancer treatment with MENs from the perspective of basic physics.
Nanoparticle-based drug delivery to the vagina: a review

PubMed Central

Ensign, Laura M.; Cone, Richard; Hanes, Justin

2014-01-01

Vaginal drug administration can improve prophylaxis and treatment of many conditions affecting the female reproductive tract, including sexually transmitted diseases, fungal and bacterial infections, and cancer. However, achieving sustained local drug concentrations in the vagina can be challenging, due to the high permeability of the vaginal epithelium and expulsion of conventional soluble drug dosage forms. Nanoparticle-based drug delivery platforms have received considerable attention for vaginal drug delivery, as nanoparticles can provide sustained release, cellular targeting, and even intrinsic antimicrobial or adjuvant properties that can improve the potency and/or efficacy of prophylactic and therapeutic modalities. Here, we review the use of polymeric nanoparticles, liposomes, dendrimers, and inorganic nanoparticles for vaginal drug delivery. Although most of the work toward nanoparticle-based drug delivery in the vagina has been focused on HIV prevention, strategies for treatment and prevention of other sexually transmitted infections, treatment for reproductive tract cancer, and treatment of fungal and bacterial infections are also highlighted. PMID:24830303
Implications of protein- and Peptide-based nanoparticles as potential vehicles for anticancer drugs.

PubMed

Elzoghby, Ahmed O; Elgohary, Mayada M; Kamel, Nayra M

2015-01-01

Protein-based nanocarriers have gained considerable attention as colloidal carrier systems for the delivery of anticancer drugs. Protein nanocarriers possess various advantages including their low cytotoxicity, abundant renewable sources, high drug-binding capacity, and significant uptake into the targeted tumor cells. Moreover, the unique protein structure offers the possibility of site-specific drug conjugation and tumor targeting using various ligands modifying the surface of protein nanocarriers. In this chapter, we highlight the most important applications of protein nanoparticles (NPs) for the delivery of anticancer drugs. We examine the various techniques that have been utilized for the preparation of anticancer drug-loaded protein NPs. Finally, the current chapter also reviews the major outcomes of the in vitro and in vivo investigations of surface-modified tumor-targeted protein NPs. © 2015 Elsevier Inc. All rights reserved.
Cancer in silico drug discovery: a systems biology tool for identifying candidate drugs to target specific molecular tumor subtypes.

PubMed

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.

Conatumumab (AMG 655) coated nanoparticles for targeted pro-apoptotic drug delivery.

PubMed

Fay, Francois; McLaughlin, Kirsty M; Small, Donna M; Fennell, Dean A; Johnston, Patrick G; Longley, Daniel B; Scott, Christopher J

2011-11-01

Colloidal nanoparticle drug delivery systems have attracted much interest for their ability to enable effective formulation and delivery of therapeutic agents. The selective delivery of these nanoparticles to the disease site can be enhanced by coating the surface of the nanoparticles with targeting moieties, such as antibodies. In this current work, we demonstrate that antibodies on the surface of the particles can also elicit key biological effects. Specifically, we demonstrate the induction of apoptosis in colorectal HCT116 cancer cells using PLGA nanoparticles coated with Conatumumab (AMG 655) death receptor 5-specific antibodies (DR5-NP). We show that DR5-NP preferentially target DR5-expressing cells and present a sufficient density of antibody paratopes to induce apoptosis via DR5, unlike free AMG 655 or non-targeted control nanoparticles. We also demonstrate that DR5-targeted nanoparticles encapsulating the cytotoxic drug camptothecin are effectively targeted to the tumour cells, thereby producing enhanced cytotoxic effects through simultaneous drug delivery and apoptosis induction. These results demonstrate that antibodies on nanoparticulate surfaces can be exploited for dual modes of action to enhance the therapeutic utility of the modality. Copyright © 2011 Elsevier Ltd. All rights reserved.
Benchmark data sets for structure-based computational target prediction.

PubMed

Schomburg, Karen T; Rarey, Matthias

2014-08-25

Structure-based computational target prediction methods identify potential targets for a bioactive compound. Methods based on protein-ligand docking so far face many challenges, where the greatest probably is the ranking of true targets in a large data set of protein structures. Currently, no standard data sets for evaluation exist, rendering comparison and demonstration of improvements of methods cumbersome. Therefore, we propose two data sets and evaluation strategies for a meaningful evaluation of new target prediction methods, i.e., a small data set consisting of three target classes for detailed proof-of-concept and selectivity studies and a large data set consisting of 7992 protein structures and 72 drug-like ligands allowing statistical evaluation with performance metrics on a drug-like chemical space. Both data sets are built from openly available resources, and any information needed to perform the described experiments is reported. We describe the composition of the data sets, the setup of screening experiments, and the evaluation strategy. Performance metrics capable to measure the early recognition of enrichments like AUC, BEDROC, and NSLR are proposed. We apply a sequence-based target prediction method to the large data set to analyze its content of nontrivial evaluation cases. The proposed data sets are used for method evaluation of our new inverse screening method iRAISE. The small data set reveals the method's capability and limitations to selectively distinguish between rather similar protein structures. The large data set simulates real target identification scenarios. iRAISE achieves in 55% excellent or good enrichment a median AUC of 0.67 and RMSDs below 2.0 Å for 74% and was able to predict the first true target in 59 out of 72 cases in the top 2% of the protein data set of about 8000 structures.
pH-sensitive Au–BSA–DOX–FA nanocomposites for combined CT imaging and targeted drug delivery

PubMed Central

Huang, He; Yang, Da-Peng; Liu, Minghuan; Wang, Xiangsheng; Zhang, Zhiyong; Zhou, Guangdong; Liu, Wei; Cao, Yilin; Zhang, Wen Jie; Wang, Xiansong

2017-01-01

Albumin-based nanoparticles (NPs) as a drug delivery system have attracted much attention owing to their nontoxicity, non-immunogenicity, great stability and ability to bind to many therapeutic drugs. Herein, bovine serum albumin (BSA) was utilized as a template to prepare Au–BSA core/shell NPs. The outer layer BSA was subsequently conjugated with cis-aconityl doxorubicin (DOX) and folic acid (FA) to create Au–BSA–DOX–FA nanocomposites. A list of characterizations was undertaken to identify the successful conjugation of drug molecules and targeted agents. In vitro cytotoxicity using a cell counting kit-8 (CCK-8) assay indicated that Au–BSA NPs did not display obvious cytotoxicity to MGC-803 and GES-1 cells in the concentration range of 0–100 μg/mL, which can therefore be used as a safe drug delivery carrier. Furthermore, compared with free DOX, Au–BSA–DOX–FA nanocomposites exhibited a pH-sensitive drug release ability and superior antitumor activity in a drug concentration-dependent manner. In vivo computed tomography (CT) imaging experiments showed that Au–BSA–DOX–FA nanocomposites could be used as an efficient and durable CT contrast agent for targeted CT imaging of the folate receptor (FR) overexpressed in cancer tissues. In vivo antitumor experiments demonstrated that Au–BSA–DOX–FA nanocomposites have selective antitumor activity effects on FR-overexpressing tumors and no adverse effects on normal tissues and organs. In conclusion, the Au–BSA–DOX–FA nanocomposite exhibits selective targeting activity, X-ray attenuation activity and pH-sensitive drug release activity. Therefore, it can enhance CT imaging and improve the targeting therapeutic efficacy of FR-overexpressing gastric cancers. Our findings suggest that Au–BSA–DOX–FA nanocomposite is a novel drug delivery carrier and a promising candidate for cancer theranostic applications. PMID:28435261
Design of dendrimer-based drug delivery nanodevices with enhanced therapeutic efficacies

NASA Astrophysics Data System (ADS)

Kannan, Rangaramanujam

2007-03-01

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. They have significant potential compared to liposomes and nanoparticles, because of the reduced macrophage update, increased cellular transport, and the ability to modulate the local environment through functional groups. We are developing nanodevices based on dendritic systems for drug delivery, that contain a high drug payload, ligands, and imaging agents, resulting in `smart' drug delivery devices that can target, deliver, and signal. In collaboration with the Children's Hospital of Michigan, Karmanos Cancer Institute, and College of Pharmacy, we are testing the in vitro and in vivo response of these nanodevices, by adapting the chemistry for specific clinical applications such as asthma and cancer. These materials are characterized by UV/Vis spectroscopy, flow cytometry, fluorescence/confocal microscopy, and appropriate animal models. Our results suggest that: (1) We can prepare drug-dendrimer conjugates with drug payloads of greater than 50%, for a variety of drugs; (2) The dendritic polymers are capable of transporting and delivering drugs into cells faster than free drugs, with superior therapeutic efficiency. This can be modulated by the surface functionality of the dendrimer; (3) For chemotherapy drugs, the conjugates are a factor of 6-20 times more effective even in drug-resistant cell lines; (4) For corticosteroidal drugs, the dendritic polymers provide higher drug residence times in the lung, allowing for passive targeting. The ability of the drug-dendrimer-ligand conjugates to target specific asthma and cancer cells is currently being explored using in vitro and in vivo animal models.
Potential biological targets for bioassay development in drug discovery of Sturge-Weber syndrome.

PubMed

Mohammadipanah, Fatemeh; Salimi, Fatemeh

2018-02-01

Sturge-Weber Syndrome (SWS) is a neurocutaneous disease with clinical manifestations including ocular (glaucoma), cutaneous (port-wine birthmark), neurologic (seizures), and vascular problems. Molecular mechanisms of SWS pathogenesis are initiated by the somatic mutation in GNAQ. Therefore, no definite treatments exist for SWS and treatment options only mitigate the intensity of its clinical manifestations. Biological assay design for drug discovery against this syndrome demands comprehensive knowledge on mechanisms which are involved in its pathogenesis. By analysis of the interrelated molecular targets of SWS, some in vitro bioassay systems can be allotted for drug screening against its progression. Development of such platforms of bioassay can bring along the implementation of high-throughput screening of natural or synthetic compounds in drug discovery programs. Regarding the fact that study of molecular targets and their integration in biological assay design can facilitate the process of effective drug discovery; some potential biological targets and their respective biological assay for SWS drug discovery are propounded in this review. For this purpose, some biological targets for SWS drug discovery such as acetylcholinesterase, alkaline phosphatase, GABAergic receptors, Hypoxia-Inducible Factor (HIF)-1α and 2α are suggested. © 2017 John Wiley & Sons A/S.
Current Multistage Drug Delivery Systems Based on the Tumor Microenvironment

PubMed Central

Chen, Binlong; Dai, Wenbing; He, Bing; Zhang, Hua; Wang, Xueqing; Wang, Yiguang; Zhang, Qiang

2017-01-01

The development of traditional tumor-targeted drug delivery systems based on EPR effect and receptor-mediated endocytosis is very challenging probably because of the biological complexity of tumors as well as the limitations in the design of the functional nano-sized delivery systems. Recently, multistage drug delivery systems (Ms-DDS) triggered by various specific tumor microenvironment stimuli have emerged for tumor therapy and imaging. In response to the differences in the physiological blood circulation, tumor microenvironment, and intracellular environment, Ms-DDS can change their physicochemical properties (such as size, hydrophobicity, or zeta potential) to achieve deeper tumor penetration, enhanced cellular uptake, timely drug release, as well as effective endosomal escape. Based on these mechanisms, Ms-DDS could deliver maximum quantity of drugs to the therapeutic targets including tumor tissues, cells, and subcellular organelles and eventually exhibit the highest therapeutic efficacy. In this review, we expatiate on various responsive modes triggered by the tumor microenvironment stimuli, introduce recent advances in multistage nanoparticle systems, especially the multi-stimuli responsive delivery systems, and discuss their functions, effects, and prospects. PMID:28255348
Current Multistage Drug Delivery Systems Based on the Tumor Microenvironment.

PubMed

Chen, Binlong; Dai, Wenbing; He, Bing; Zhang, Hua; Wang, Xueqing; Wang, Yiguang; Zhang, Qiang

2017-01-01

The development of traditional tumor-targeted drug delivery systems based on EPR effect and receptor-mediated endocytosis is very challenging probably because of the biological complexity of tumors as well as the limitations in the design of the functional nano-sized delivery systems. Recently, multistage drug delivery systems (Ms-DDS) triggered by various specific tumor microenvironment stimuli have emerged for tumor therapy and imaging. In response to the differences in the physiological blood circulation, tumor microenvironment, and intracellular environment, Ms-DDS can change their physicochemical properties (such as size, hydrophobicity, or zeta potential) to achieve deeper tumor penetration, enhanced cellular uptake, timely drug release, as well as effective endosomal escape. Based on these mechanisms, Ms-DDS could deliver maximum quantity of drugs to the therapeutic targets including tumor tissues, cells, and subcellular organelles and eventually exhibit the highest therapeutic efficacy. In this review, we expatiate on various responsive modes triggered by the tumor microenvironment stimuli, introduce recent advances in multistage nanoparticle systems, especially the multi-stimuli responsive delivery systems, and discuss their functions, effects, and prospects.
The rise of fragment-based drug discovery.

PubMed

Murray, Christopher W; Rees, David C

2009-06-01

The search for new drugs is plagued by high attrition rates at all stages in research and development. Chemists have an opportunity to tackle this problem because attrition can be traced back, in part, to the quality of the chemical leads. Fragment-based drug discovery (FBDD) is a new approach, increasingly used in the pharmaceutical industry, for reducing attrition and providing leads for previously intractable biological targets. FBDD identifies low-molecular-weight ligands (∼150 Da) that bind to biologically important macromolecules. The three-dimensional experimental binding mode of these fragments is determined using X-ray crystallography or NMR spectroscopy, and is used to facilitate their optimization into potent molecules with drug-like properties. Compared with high-throughput-screening, the fragment approach requires fewer compounds to be screened, and, despite the lower initial potency of the screening hits, offers more efficient and fruitful optimization campaigns. Here, we review the rise of FBDD, including its application to discovering clinical candidates against targets for which other chemistry approaches have struggled.
Trypanosome RNA polymerases and transcription factors: sensible trypanocidal drug targets?

PubMed

Vanhamme, Luc

2008-11-01

Trypanosomes and Leishmaniae are the agents of several important parasitic diseases threatening hundreds of million human beings worldwide. As they diverged early in evolution, they display original molecular characteristics. These peculiarities are each defining putative specific targets for anti-parasitic drugs. Transcription displays its lot of unique characteristics in trypanosomes and will be taken as an example to uncover these targets. Unique features of transcription in trypanosomes include constitutive and poly-cistronic transcription by RNA polymerase II as well as transcription of protein-coding genes by RNA polymerase I. It is becoming clear that these unique mechanisms are performed by dedicated molecular players. The first of them have been recently characterized. They are reviewed and their suitability as drug targets is commented.
Thiamin (Vitamin B1) Biosynthesis and Regulation: A Rich Source of Antimicrobial Drug Targets?

PubMed Central

Du, Qinglin; Wang, Honghai; Xie, Jianping

2011-01-01

Drug resistance of pathogens has necessitated the identification of novel targets for antibiotics. Thiamin (vitamin B1) is an essential cofactor for all organisms in its active form thiamin diphosphate (ThDP). Therefore, its metabolic pathways might be one largely untapped source of antibiotics targets. This review describes bacterial thiamin biosynthetic, salvage, and transport pathways. Essential thiamin synthetic enzymes such as Dxs and ThiE are proposed as promising drug targets. The regulation mechanism of thiamin biosynthesis by ThDP riboswitch is also discussed. As drug targets of existing antimicrobial compound pyrithiamin, the ThDP riboswitch might serves as alternative targets for more antibiotics. PMID:21234302
Drug discovery strategies to outer membrane targets in Gram-negative pathogens.

PubMed

Brown, Dean G

2016-12-15

This review will cover selected recent examples of drug discovery strategies which target the outer membrane (OM) of Gram-negative bacteria either by disruption of outer membrane function or by inhibition of essential gene products necessary for outer membrane assembly. Significant advances in pathway elucidation, structural biology and molecular inhibitor designs have created new opportunities for drug discovery within this target-class space. Copyright Â© 2016 Elsevier Ltd. All rights reserved.
Brain-inspired cheminformatics of drug-target brain interactome, synthesis, and assay of TVP1022 derivatives.

PubMed

Romero-Durán, Francisco J; Alonso, Nerea; Yañez, Matilde; Caamaño, Olga; García-Mera, Xerardo; González-Díaz, Humberto

2016-04-01

The use of Cheminformatics tools is gaining importance in the field of translational research from Medicinal Chemistry to Neuropharmacology. In particular, we need it for the analysis of chemical information on large datasets of bioactive compounds. These compounds form large multi-target complex networks (drug-target interactome network) resulting in a very challenging data analysis problem. Artificial Neural Network (ANN) algorithms may help us predict the interactions of drugs and targets in CNS interactome. In this work, we trained different ANN models able to predict a large number of drug-target interactions. These models predict a dataset of thousands of interactions of central nervous system (CNS) drugs characterized by > 30 different experimental measures in >400 different experimental protocols for >150 molecular and cellular targets present in 11 different organisms (including human). The model was able to classify cases of non-interacting vs. interacting drug-target pairs with satisfactory performance. A second aim focus on two main directions: the synthesis and assay of new derivatives of TVP1022 (S-analogues of rasagiline) and the comparison with other rasagiline derivatives recently reported. Finally, we used the best of our models to predict drug-target interactions for the best new synthesized compound against a large number of CNS protein targets. Copyright © 2015 Elsevier Ltd. All rights reserved.
Quantitative PET Imaging in Drug Development: Estimation of Target Occupancy.

PubMed

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.
Dual-pH Sensitive Charge-reversal Nanocomplex for Tumor-targeted Drug Delivery with Enhanced Anticancer Activity.

PubMed

Zhou, Qing; Hou, Yilin; Zhang, Li; Wang, Jianlin; Qiao, Youbei; Guo, Songyan; Fan, Li; Yang, Tiehong; Zhu, Lin; Wu, Hong

2017-01-01

Poly(β-L-malic acid) (PMLA), a natural aliphatic polyester, has been proven to be a promising carrier for anti-cancer drugs. In spite of excellent bio-compatibility, the application of PMLA as the drug carrier for cancer therapy is limited by its low cellular uptake efficiency. The strong negative charge of PMLA impedes its uptake by cancer cells because of the electrostatic repulsion. In this study, a dual pH-sensitive charge-reversal PMLA-based nanocomplex (PMLA-PEI-DOX-TAT@PEG-DMMA) was developed for effective tumor-targeted drug delivery, enhanced cellular uptake, and intracellular drug release. The prepared nanocomplex showed a negative surface charge at the physiological pH, which could protect the nanocomplex from the attack of plasma proteins and recognition by the reticuloendothelial system, so as to prolong its circulation time. While at the tumor extracellular pH 6.8, the DMMA was hydrolyzed, leading to the charge reversal and exposure of the TAT on the polymeric micelles, thus enhancing the cellular internalization. Then, the polymeric micelles underwent dissociation and drug release in response to the acidic pH in the lyso/endosomal compartments of the tumor cell. Both in vitro and in vivo efficacy studies indicated that the nanocomplex significantly inhibited the tumor growth while the treatment showed negligible systemic toxicity, suggesting that the developed dual pH-sensitive PMLA-based nanocomplex would be a promising drug delivery system for tumor-targeted drug delivery with enhanced anticancer activity.
Dual-pH Sensitive Charge-reversal Nanocomplex for Tumor-targeted Drug Delivery with Enhanced Anticancer Activity

PubMed Central

Zhou, Qing; Hou, Yilin; Zhang, Li; Wang, Jianlin; Qiao, Youbei; Guo, Songyan; Fan, Li; Yang, Tiehong; Zhu, Lin; Wu, Hong

2017-01-01

Poly(β-L-malic acid) (PMLA), a natural aliphatic polyester, has been proven to be a promising carrier for anti-cancer drugs. In spite of excellent bio-compatibility, the application of PMLA as the drug carrier for cancer therapy is limited by its low cellular uptake efficiency. The strong negative charge of PMLA impedes its uptake by cancer cells because of the electrostatic repulsion. In this study, a dual pH-sensitive charge-reversal PMLA-based nanocomplex (PMLA-PEI-DOX-TAT@PEG-DMMA) was developed for effective tumor-targeted drug delivery, enhanced cellular uptake, and intracellular drug release. The prepared nanocomplex showed a negative surface charge at the physiological pH, which could protect the nanocomplex from the attack of plasma proteins and recognition by the reticuloendothelial system, so as to prolong its circulation time. While at the tumor extracellular pH 6.8, the DMMA was hydrolyzed, leading to the charge reversal and exposure of the TAT on the polymeric micelles, thus enhancing the cellular internalization. Then, the polymeric micelles underwent dissociation and drug release in response to the acidic pH in the lyso/endosomal compartments of the tumor cell. Both in vitro and in vivo efficacy studies indicated that the nanocomplex significantly inhibited the tumor growth while the treatment showed negligible systemic toxicity, suggesting that the developed dual pH-sensitive PMLA-based nanocomplex would be a promising drug delivery system for tumor-targeted drug delivery with enhanced anticancer activity. PMID:28638469
Non-Covalent Functionalization of Carbon Nanovectors with an Antibody Enables Targeted Drug Delivery

PubMed Central

Berlin, Jacob M.; Pham, Tam T.; Sano, Daisuke; Mohamedali, Khalid A.; Marcano, Daniela C.; Myers, Jeffrey N.; Tour, James M.

2011-01-01

Current chemotherapeutics are characterized by efficient tumor cell-killing and severe side effects mostly derived from off target toxicity. Hence targeted delivery of these drugs to tumor cells is actively sought. We previously demonstrated that poly(ethylene glycol)-functionalized carbon nanovectors are able to sequester paclitaxel, a widely used hydrophobic cancer drug, by simple physisorption and deliver the drug for killing of cancer cells. The cell-killing when these drug-loaded carbon nanoparticles were used was equivalent to when a commercial formulation of paclitaxel was used. Here we show that by further mixing the drug-loaded nanoparticles with Cetuximab, a monoclonal antibody that recognizes the epidermal growth factor receptor (EGFR), paclitaxel is preferentially targeted to EGFR+ tumor cells in vitro. This supports progressing to in vivo studies. Moreover, the construct is unusual in that all three components are assembled through non-covalent interactions. Such non-covalent assembly could enable high-throughput screening of drug/antibody combinations. PMID:21736358
Hot-spot analysis for drug discovery targeting protein-protein interactions.

PubMed

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.
Structural Basis for Induction of Peripheral Neuropathy by Microtubule-Targeting Cancer Drugs.

PubMed

Smith, Jennifer A; Slusher, Barbara S; Wozniak, Krystyna M; Farah, Mohamed H; Smiyun, Gregoriy; Wilson, Leslie; Feinstein, Stuart; Jordan, Mary Ann

2016-09-01

Peripheral neuropathy is a serious, dose-limiting side effect of cancer treatment with microtubule-targeting drugs. Symptoms present in a "stocking-glove" distribution, with longest nerves affected most acutely, suggesting a length-dependent component to the toxicity. Axonal transport of ATP-producing mitochondria along neuronal microtubules from cell body to synapse is crucial to neuronal function. We compared the effects of the drugs paclitaxel and ixabepilone that bind along the lengths of microtubules and the drugs eribulin and vincristine that bind at microtubule ends, on mitochondrial trafficking in cultured human neuronal SK-N-SH cells and on axonal transport in mouse sciatic nerves. Antiproliferative concentrations of paclitaxel and ixabepilone significantly inhibited the anterograde transport velocity of mitochondria in neuronal cells, whereas eribulin and vincristine inhibited transport only at significantly higher concentrations. Confirming these observations, anterogradely transported amyloid precursor protein accumulated in ligated sciatic nerves of control and eribulin-treated mice, but not in paclitaxel-treated mice, indicating that paclitaxel inhibited anterograde axonal transport, whereas eribulin did not. Electron microscopy of sciatic nerves of paclitaxel-treated mice showed reduced organelle accumulation proximal to the ligation consistent with inhibition of anterograde (kinesin based) transport by paclitaxel. In contrast, none of the drugs significantly affected retrograde (dynein based) transport in neuronal cells or mouse nerves. Collectively, these results suggest that paclitaxel and ixabepilone, which bind along the lengths and stabilize microtubules, inhibit kinesin-based axonal transport, but not dynein-based transport, whereas the microtubule-destabilizing drugs, eribulin and vincristine, which bind preferentially to microtubule ends, have significantly less effect on all microtubule-based axonal transport. Cancer Res; 76(17); 5115-23. �
Physico-chemical strategies to enhance stability and drug retention of polymeric micelles for tumor-targeted drug delivery

PubMed Central

Shi, Yang; Lammers, Twan; Storm, Gert; Hennink, Wim 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 PM have resulted in tremendous numbers of PM-forming amphiphilic polymers, and approximately a dozen micellar nanomedicines have entered the clinic. The first generation of PM can be considered solubilizers of hydrophobic drugs, with short circulation times resulting from poor micelle stability and unstable drug entrapment. To more optimally exploit the potential of PM for targeted drug delivery, several physical (e.g. π-π stacking, stereocomplexation, hydrogen bonding, host-guest complexation and coordination interaction) and chemical (e.g. free radical polymerization, click chemistry, disulfide and hydrazone bonding) strategies have been developed to improve micelle stability and drug retention. In this review, we describe the most promising physico-chemical approaches to enhance micelle stability and drug retention, and we summarize how these strategies have resulted in systems with promising therapeutic efficacy in animal models, paving the way for clinical translation. PMID:27413999
Targeting monoamine oxidases with multipotent ligands: an emerging strategy in the search of new drugs against neurodegenerative diseases.

PubMed

Pisani, L; Catto, M; Leonetti, F; Nicolotti, O; Stefanachi, A; Campagna, F; Carotti, A

2011-01-01

The socioeconomic burden of multi-factorial pathologies, such as neurodegenerative diseases (NDs), is enormous worldwide. Unfortunately, no proven disease-modifying therapy is available yet and in most cases (e.g., Alzheimer's and Parkinson's disease) the approved drugs exert only palliative and symptomatic effects. Nowadays, an emerging strategy for the discovery of disease-modifying drugs is based on the multi-target directed ligand (MTDL) design, an innovative shift from the traditional approach one-drug-one-target to the more ambitious one-drug-more-targets goal. Herein, we review the discovery strategy, the mechanism of action and the biopharmacological evaluation of multipotent ligands exhibiting monoamine oxidase (MAO) inhibition as the core activity with a potential for the treatment of NDs. In particular, MAO inhibitors exhibiting additional acetylcholinesterase (AChE) or nitric oxide synthase (NOS) inhibition, or ion chelation/antioxidant-radical scavenging/anti-inflammatory/A2A receptor antagonist/APP processing modulating activities have been thoroughly examined.

Hydrodynamic interactions for complex-shaped nanocarriers in targeted drug delivery

NASA Astrophysics Data System (ADS)

Wang, Yaohong; Eckmann, David; Radhakrishnan, Ravi; Ayyaswamy, Portonovo

2014-11-01

Nanocarrier motion in a blood vessel involves hydrodynamic and Brownian interactions, which collectively dictate the efficacy in targeted drug delivery. The shape of nanocarriers plays a crucial role in drug delivery. In order to quantify the flow and association properties of elliptical nanoparticles, we have developed an arbitrary Lagrangian-Eulerian framework with capabilities to simulate the hydrodynamic motion of nanoparticles of arbitrary shapes. We introduce the quaternions for rotational motion, and two collision models, namely, (a) an impulse-based model for wall-particle collision, and (b) the short-range repulsive Gay-Berne potential for particle-particle collision. We also study the red blood cell and nanocarrier (such as ellipsoid) interactions. We compare our results with those obtained for a hard sphere model for both RBCs and nanocarriers. Supported by NIH through grant U01-EB016027.
Design, Synthesis, and Biological Evaluations of Asymmetric Bow-Tie PAMAM Dendrimer-Based Conjugates for Tumor-Targeted Drug Delivery.

PubMed

Wang, Tao; Zhang, Yaozhong; Wei, Longfei; Teng, Yuhan G; Honda, Tadashi; Ojima, Iwao

2018-04-30

A unique asymmetric bow-tie poly(amidoamine) (PAMAM) dendrimer (ABTD) scaffold was designed and developed as a well-defined macromolecular carrier for tumor-targeted drug delivery. The ABTD scaffold in this study consists of a G3-half-dendron (G3-HD) unit and a G1-half-dendron (G1-HD) unit, bearing thiol moiety in each unit and a bis(maleimide) linker unit, which undergo sequential thiol-maleimide coupling to assemble the scaffold. This assembly methodology is applicable to all other combinations of different generations of PAMAM dendrimers. In the prototype ABTD in this study, 16 biotin moieties were tethered to the G3-HD unit and 4 payloads (new-generation taxoid) to the G1-HD via a self-immolative linker to form an ABTD-tumor-targeting conjugate (ABTD-TTC-1). Two other ABTD-TTCs were synthesized, wherein the G1-HD unit was tethered to a fluorescence-labeled taxoid or to a fluorescent probe. These three ABTD-TTCs were constructed by using a common key ABTD 6 bearing a terminal acetylene group in the G1-HD unit, which was fully characterized as a single molecule by high-resolution mass spectrometry and NMR despite its high molecular weight ( M w : 12 876). Then, the click reaction was employed to couple ABTD 6 with a small-molecule payload or fluorescence probe unit bearing a terminal azide moiety. ABTD-TTC-3, as a surrogate of ABTD-TTC-2, showed substantially enhanced internalization into two cancer cell lines via receptor-mediated endocytosis, attributed to multibinding effect. ABTD-TTC-1 exhibited a remarkable selectivity to cancer cells (1400-7500 times) compared to human normal cells, which demonstrates the salient feature and bright prospect of the ABTD-based tumor-targeted drug-delivery system.
Specific Cell Targeting Therapy Bypasses Drug Resistance Mechanisms in African Trypanosomiasis

PubMed Central

Unciti-Broceta, Juan D.; Arias, José L.; Maceira, José; Soriano, Miguel; Ortiz-González, Matilde; Hernández-Quero, José; Muñóz-Torres, Manuel; de Koning, Harry P.; Magez, Stefan; Garcia-Salcedo, José A.

2015-01-01

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. PMID:26110623
Advances of blood cell-based drug delivery systems.

PubMed

Sun, Yanan; Su, Jing; Liu, Geyi; Chen, Jianjun; Zhang, Xiumei; Zhang, Ran; Jiang, Minhan; Qiu, Mingfeng

2017-01-01

Blood cells, including erythrocytes, leukocytes and platelets are used as drug carriers in a wide range of applications. They have many unique advantages such as long life-span in circulation (especially erythrocytes), target release capacities (especially platelets), and natural adhesive properties (leukocytes and platelets). These properties make blood cell based delivery systems, as well as their membrane-derived carriers, far superior to other drug delivery systems. Despite the advantages, the further development of blood cell-based delivery systems was hindered by limitations in the source, storage, and mass production. To overcome these problems, synthetic biomaterials that mimic blood cell and nanocrystallization of blood cells have been developed and may represent the future direction for blood cell membrane-based delivery systems. In this paper, we review recent progress of the rising blood cell-based drug delivery systems, and also discuss their challenges and future tendency of development. Copyright © 2016. Published by Elsevier B.V.
The prefrontal cortex: a target for antipsychotic drugs.

PubMed

Artigas, F

2010-01-01

At therapeutic doses, classical antipsychotic drugs occupy a large proportion of subcortical dopamine D2 receptors, whereas atypical antipsychotics preferentially occupy cortical 5-HT(2) receptors. However, the exact cellular and network basis of their therapeutic action is not fully understood. To review the mechanism of action of antipsychotic drugs with a particular emphasis on their action in the prefrontal cortex (PFC). The PFC controls a large number of higher brain functions altered in schizophrenia. Histological studies indicate the presence of a large proportion of PFC neurons expressing monoaminergic receptors sensitive to the action of atypical- and to a lesser extentclassical antipsychotic drugs. Functional studies also indicate that both drug families act at PFC level. Atypical antipsychotic drugs likely exert their therapeutic activity by a preferential action on PFC neurons, thus modulating the PFC output to basal ganglia circuits. Classical antipsychotics also interact with these PFC targets in addition to blocking massively striatal D2 receptors.
Network Analysis of Drug-target Interactions: A Study on FDA-approved New Molecular Entities Between 2000 to 2015.

PubMed

Lin, Hui-Heng; Zhang, Le-Le; Yan, Ru; Lu, Jin-Jian; Hu, Yuanjia

2017-09-25

The U.S. Food and Drug Administration (FDA) approves new drugs every year. Drug targets are some of the most important interactive molecules for drugs, as they have a significant impact on the therapeutic effects of drugs. In this work, we thoroughly analyzed the data of small molecule drugs approved by the U.S. FDA between 2000 and 2015. Specifically, we focused on seven classes of new molecular entity (NME) classified by the anatomic therapeutic chemical (ATC) classification system. They were NMEs and their corresponding targets for the cardiovascular system, respiratory system, nerve system, general anti-infective systemic, genito-urinary system and sex hormones, alimentary tract and metabolisms, and antineoplastic and immunomodulating agents. To study the drug-target interaction on the systems level, we employed network topological analysis and multipartite network projections. As a result, the drug-target relations of different kinds of drugs were comprehensively characterized and global pictures of drug-target, drug-drug, and target-target interactions were visualized and analyzed from the perspective of network models.
Antibody Drug Conjugates: Application of Quantitative Pharmacology in Modality Design and Target Selection.

PubMed

Sadekar, S; Figueroa, I; Tabrizi, M

2015-07-01

Antibody drug conjugates (ADCs) are a multi-component modality comprising of an antibody targeting a cell-specific antigen, a potent drug/payload, and a linker that can be processed within cellular compartments to release payload upon internalization. Numerous ADCs are being evaluated in both research and clinical settings within the academic and pharmaceutical industry due to their ability to selectively deliver potent payloads. Hence, there is a clear need to incorporate quantitative approaches during early stages of drug development for effective modality design and target selection. In this review, we describe a quantitative approach and framework for evaluation of the interplay between drug- and systems-dependent properties (i.e., target expression, density, localization, turnover, and affinity) in order to deliver a sufficient amount of a potent payload into the relevant target cells. As discussed, theoretical approaches with particular considerations given to various key properties for the target and modality suggest that delivery of the payload into particular effect cells to be more sensitive to antigen concentrations for targets with slow turnover rates as compared to those with faster internalization rates. Further assessments also suggest that increasing doses beyond the threshold of the target capacity (a function of target internalization and expression) may not impact the maximum amount of payload delivered to the intended effect cells. This article will explore the important application of quantitative sciences in selection of the target and design of ADC modalities.
A Phenotypic Based Target Screening Approach Delivers New Antitubercular CTP Synthetase Inhibitors.

PubMed

Esposito, Marta; Szadocka, Sára; Degiacomi, Giulia; Orena, Beatrice S; Mori, Giorgia; Piano, Valentina; Boldrin, Francesca; Zemanová, Júlia; Huszár, Stanislav; Barros, David; Ekins, Sean; Lelièvre, Joel; Manganelli, Riccardo; Mattevi, Andrea; Pasca, Maria Rosalia; Riccardi, Giovanna; Ballell, Lluis; Mikušová, Katarína; Chiarelli, Laurent R

2017-06-09

Despite its great potential, the target-based approach has been mostly unsuccessful in tuberculosis drug discovery, while whole cell phenotypic screening has delivered several active compounds. However, for many of these hits, the cellular target has not yet been identified, thus preventing further target-based optimization of the compounds. In this context, the newly validated drug target CTP synthetase PyrG was exploited to assess a target-based approach of already known, but untargeted, antimycobacterial compounds. To this purpose the publically available GlaxoSmithKline antimycobacterial compound set was assayed, uncovering a series of 4-(pyridin-2-yl)thiazole derivatives which efficiently inhibit the Mycobacterium tuberculosis PyrG enzyme activity, one of them showing low activity against the human CTP synthetase. The three best compounds were ATP binding site competitive inhibitors, with K i values ranging from 3 to 20 μM, but did not show any activity against a small panel of different prokaryotic and eukaryotic kinases, thus demonstrating specificity for the CTP synthetases. Metabolic labeling experiments demonstrated that the compounds directly interfere not only with CTP biosynthesis, but also with other CTP dependent biochemical pathways, such as lipid biosynthesis. Moreover, using a M. tuberculosis pyrG conditional knock-down strain, it was shown that the activity of two compounds is dependent on the intracellular concentration of the CTP synthetase. All these results strongly suggest a role of PyrG as a target of these compounds, thus strengthening the value of this kind of approach for the identification of new scaffolds for drug development.
A systematic approach to prioritize drug targets using machine learning, a molecular descriptor-based classification model, and high-throughput screening of plant derived molecules: a case study in oral cancer.

PubMed

Randhawa, Vinay; Kumar Singh, Anil; Acharya, Vishal

2015-12-01

Systems-biology inspired identification of drug targets and machine learning-based screening of small molecules which modulate their activity have the potential to revolutionize modern drug discovery by complementing conventional methods. To utilize the effectiveness of such pipelines, we first analyzed the dysregulated gene pairs between control and tumor samples and then implemented an ensemble-based feature selection approach to prioritize targets in oral squamous cell carcinoma (OSCC) for therapeutic exploration. Based on the structural information of known inhibitors of CXCR4-one of the best targets identified in this study-a feature selection was implemented for the identification of optimal structural features (molecular descriptor) based on which a classification model was generated. Furthermore, the CXCR4-centered descriptor-based classification model was finally utilized to screen a repository of plant derived small-molecules to obtain potential inhibitors. The application of our methodology may assist effective selection of the best targets which may have previously been overlooked, that in turn will lead to the development of new oral cancer medications. The small molecules identified in this study can be ideal candidates for trials as potential novel anti-oral cancer agents. Importantly, distinct steps of this whole study may provide reference for the analysis of other complex human diseases.
Process evaluation and in vitro selectivity analysis of aptamer-drug polymeric formulation for targeted pharmaceutical delivery.

PubMed

Tan, Kei X; Lau, Sie Yon; Danquah, Michael K

2018-05-01

Targeted drug delivery is a promising strategy to promote effective delivery of conventional and emerging pharmaceuticals. The emergence of aptamers as superior targeting ligands to direct active drug molecules specifically to desired malignant cells has created new opportunities to enhance disease therapies. The application of biodegradable polymers as delivery carriers to develop aptamer-navigated drug delivery system is a promising approach to effectively deliver desired drug dosages to target cells. This study reports the development of a layer-by-layer aptamer-mediated drug delivery system (DPAP) via a w/o/w double emulsion technique homogenized by ultrasonication or magnetic stirring. Experimental results showed no significant differences in the biophysical characteristics of DPAP nanoparticles generated using the two homogenization techniques. The DPAP formulation demonstrated a strong targeting performance and selectivity towards its target receptor molecules in the presence of non-targets. The DPAP formulation demonstrated a controlled and sustained drug release profile under the conditions of pH 7 and temperature 37 °C. Also, the drug release rate of DPAP formulation was successfully accelerated under an endosomal acidic condition of ∼pH 5.5, indicating the potential to enhance drug delivery within the endosomal micro-environment. The findings from this work are useful to understanding polymer-aptamer-drug relationship and their impact on developing effective targeted delivery systems. Copyright © 2018 Elsevier Masson SAS. All rights reserved.
Lipid microbubbles as a vehicle for targeted drug delivery using focused ultrasound-induced blood–brain barrier opening

PubMed Central

Sierra, Carlos; Acosta, Camilo; Chen, Cherry; Wu, Shih-Ying; Karakatsani, Maria E; Bernal, Manuel

2016-01-01

Focused ultrasound in conjunction with lipid microbubbles has fully demonstrated its ability to induce non-invasive, transient, and reversible blood–brain barrier opening. This study was aimed at testing the feasibility of our lipid-coated microbubbles as a vector for targeted drug delivery in the treatment of central nervous system diseases. These microbubbles were labeled with the fluorophore 5-dodecanoylaminfluorescein. Focused ultrasound targeted mouse brains in vivo in the presence of these microbubbles for trans-blood–brain barrier delivery of 5-dodecanoylaminfluorescein. This new approach, compared to previously studies of our group, where fluorescently labeled dextrans and microbubbles were co-administered, represents an appreciable improvement in safety outcome and targeted drug delivery. This novel technique allows the delivery of 5-dodecanoylaminfluorescein at the region of interest unlike the alternative of systemic exposure. 5-dodecanoylaminfluorescein delivery was assessed by ex vivo fluorescence imaging and by in vivo transcranial passive cavitation detection. Stable and inertial cavitation doses were quantified. The cavitation dose thresholds for estimating, a priori, successful targeted drug delivery were, for the first time, identified with inertial cavitation were concluded to be necessary for successful delivery. The findings presented herein indicate the feasibility and safety of the proposed microbubble-based targeted drug delivery and that, if successful, can be predicted by cavitation detection in vivo. PMID:27278929
Potential biological targets for bioassay development in drug discovery of Sturge-Weber syndrome.

PubMed

Mohammadipanah, Fatemeh; Salimi, Fatemeh

2017-04-29

Sturge-Weber Syndrome (SWS) is among the neurocutaneous diseases, which has several clinical manifestations of ocular (glaucoma), cutaneous (port-wine stain), neurological (seizures) and vascular problems. Molecular mechanisms of SWS pathogenesis are initiated by the somatic mutation in GNAQ. Therefore, no definite treatments exist for the SWS and treatment options only mitigate the intensity of its clinical manifestations. Biological assay design for drug discovery against this syndrome demands comprehensive knowledge on mechanisms which are involved in its pathogenesis. By analysis of the interrelated molecular targets of SWS, some in vitro bioassay systems can be allotted for drug screening against this syndrome. Development of such platforms of bioassay can bring along the implementation of high throughput screening of natural or synthetic compounds in drug discovery programs. Regarding the fact that study of biological targets and their integration in biological assay design can facilitate the process of effective drug discovery; some potential biological targets and their respective biological assay for SWS drug discovery are propounded in this review. For this purpose, some biological targets for SWS drug discovery such as acetylcholine esterase, alkaline phosphatase, gamma-aminobutyricacidergic, Hypoxia-Inducible Factor (HIF) -1α and 2α are suggested. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
Applications of CRISPR genome editing technology in drug target identification and validation.

PubMed

Lu, Quinn; Livi, George P; Modha, Sundip; Yusa, Kosuke; Macarrón, Ricardo; Dow, David J

2017-06-01

The analysis of pharmaceutical industry data indicates that the major reason for drug candidates failing in late stage clinical development is lack of efficacy, with a high proportion of these due to erroneous hypotheses about target to disease linkage. More than ever, there is a requirement to better understand potential new drug targets and their role in disease biology in order to reduce attrition in drug development. Genome editing technology enables precise modification of individual protein coding genes, as well as noncoding regulatory sequences, enabling the elucidation of functional effects in human disease relevant cellular systems. Areas covered: This article outlines applications of CRISPR genome editing technology in target identification and target validation studies. Expert opinion: Applications of CRISPR technology in target validation studies are in evidence and gaining momentum. Whilst technical challenges remain, we are on the cusp of CRISPR being applied in complex cell systems such as iPS derived differentiated cells and stem cell derived organoids. In the meantime, our experience to date suggests that precise genome editing of putative targets in primary cell systems is possible, offering more human disease relevant systems than conventional cell lines.
Innovative Methodology in the Discovery of Novel Drug Targets in the Free-Living Amoebae

PubMed

Baig, Abdul Mannan

2018-04-25

Despite advances in drug discovery and modifications in the chemotherapeutic regimens, human infections caused by free-living amoebae (FLA) have high mortality rates (~95%). The FLA that cause fatal human cerebral infections include Naegleria fowleri, Balamuthia mandrillaris and Acanthamoeba spp. Novel drug-target discovery remains the only viable option to tackle these central nervous system (CNS) infection in order to lower the mortality rates caused by the FLA. Of these FLA, N. fowleri causes primary amoebic meningoencephalitis (PAM), while the A. castellanii and B. Mandrillaris are known to cause granulomatous amoebic encephalitis (GAE). The infections caused by the FLA have been treated with drugs like Rifampin, Fluconazole, Amphotericin-B and Miltefosine. Miltefosine is an anti-leishmanial agent and an experimental anti-cancer drug. With only rare incidences of success, these drugs have remained unsuccessful to lower the mortality rates of the cerebral infection caused by FLA. Recently, with the help of bioinformatic computational tools and the discovered genomic data of the FLA, discovery of newer drug targets has become possible. These cellular targets are proteins that are either unique to the FLA or shared between the humans and these unicellular eukaryotes. The latter group of proteins has shown to be targets of some FDA approved drugs prescribed in non-infectious diseases. This review out-lines the bioinformatic methodologies that can be used in the discovery of such novel drug-targets, their chronicle by in-vitro assays done in the past and the translational value of such target discoveries in human diseases caused by FLA. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Neuronal and Cardiovascular Potassium Channels as Therapeutic Drug Targets

PubMed Central

Humphries, Edward S. A.

2015-01-01

Potassium (K+) channels, with their diversity, often tissue-defined distribution, and critical role in controlling cellular excitability, have long held promise of being important drug targets for the treatment of dysrhythmias in the heart and abnormal neuronal activity within the brain. With the exception of drugs that target one particular class, ATP-sensitive K+ (KATP) channels, very few selective K+ channel activators or inhibitors are currently licensed for clinical use in cardiovascular and neurological disease. Here we review what a range of human genetic disorders have told us about the role of specific K+ channel subunits, explore the potential of activators and inhibitors of specific channel populations as a therapeutic strategy, and discuss possible reasons for the difficulty in designing clinically relevant K+ channel modulators. PMID:26303307
Insights into Integrated Lead Generation and Target Identification in Malaria and Tuberculosis Drug Discovery

PubMed Central

2017-01-01

Conspectus 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
Computational 3D structures of drug-targeting proteins in the 2009-H1N1 influenza A virus

NASA Astrophysics Data System (ADS)

Du, Qi-Shi; Wang, Shu-Qing; Huang, Ri-Bo; Chou, Kuo-Chen

2010-01-01

The neuraminidase (NA) and M2 proton channel of influenza virus are the drug-targeting proteins, based on which several drugs were developed. However these once powerful drugs encountered drug-resistant problem to the H5N1 and H1N1 flu. To address this problem, the computational 3D structures of NA and M2 proteins of 2009-H1N1 influenza virus were built using the molecular modeling technique and computational chemistry method. Based on the models the structure features of NA and M2 proteins were analyzed, the docking structures of drug-protein complexes were computed, and the residue mutations were annotated. The results may help to solve the drug-resistant problem and stimulate designing more effective drugs against 2009-H1N1 influenza pandemic.
A novel algorithm for finding optimal driver nodes to target control complex networks and its applications for drug targets identification.

PubMed

Guo, Wei-Feng; Zhang, Shao-Wu; Shi, Qian-Qian; Zhang, Cheng-Ming; Zeng, Tao; Chen, Luonan

2018-01-19

The advances in target control of complex networks not only can offer new insights into the general control dynamics of complex systems, but also be useful for the practical application in systems biology, such as discovering new therapeutic targets for disease intervention. In many cases, e.g. drug target identification in biological networks, we usually require a target control on a subset of nodes (i.e., disease-associated genes) with minimum cost, and we further expect that more driver nodes consistent with a certain well-selected network nodes (i.e., prior-known drug-target genes). Therefore, motivated by this fact, we pose and address a new and practical problem called as target control problem with objectives-guided optimization (TCO): how could we control the interested variables (or targets) of a system with the optional driver nodes by minimizing the total quantity of drivers and meantime maximizing the quantity of constrained nodes among those drivers. Here, we design an efficient algorithm (TCOA) to find the optional driver nodes for controlling targets in complex networks. We apply our TCOA to several real-world networks, and the results support that our TCOA can identify more precise driver nodes than the existing control-fucus approaches. Furthermore, we have applied TCOA to two bimolecular expert-curate networks. Source code for our TCOA is freely available from http://sysbio.sibcb.ac.cn/cb/chenlab/software.htm or https://github.com/WilfongGuo/guoweifeng . In the previous theoretical research for the full control, there exists an observation and conclusion that the driver nodes tend to be low-degree nodes. However, for target control the biological networks, we find interestingly that the driver nodes tend to be high-degree nodes, which is more consistent with the biological experimental observations. Furthermore, our results supply the novel insights into how we can efficiently target control a complex system, and especially many evidences on the
Surface engineering of macrophages with nanoparticles to generate a cell-nanoparticle hybrid vehicle for hypoxia-targeted drug delivery.

PubMed

Holden, Christopher A; Yuan, Quan; Yeudall, W Andrew; Lebman, Deborah A; Yang, Hu

2010-02-02

Tumors frequently contain hypoxic regions that result from a shortage of oxygen due to poorly organized tumor vasculature. Cancer cells in these areas are resistant to radiation- and chemotherapy, limiting the treatment efficacy. Macrophages have inherent hypoxia-targeting ability and hold great advantages for targeted delivery of anticancer therapeutics to cancer cells in hypoxic areas. However, most anticancer drugs cannot be directly loaded into macrophages because of their toxicity. In this work, we designed a novel drug delivery vehicle by hybridizing macrophages with nanoparticles through cell surface modification. Nanoparticles immobilized on the cell surface provide numerous new sites for anticancer drug loading, hence potentially minimizing the toxic effect of anticancer drugs on the viability and hypoxia-targeting ability of the macrophage vehicles. In particular, quantum dots and 5-(aminoacetamido) fluorescein-labeled polyamidoamine dendrimer G4.5, both of which were coated with amine-derivatized polyethylene glycol, were immobilized to the sodium periodate-treated surface of RAW264.7 macrophages through a transient Schiff base linkage. Further, a reducing agent, sodium cyanoborohydride, was applied to reduce Schiff bases to stable secondary amine linkages. The distribution of nanoparticles on the cell surface was confirmed by fluorescence imaging, and it was found to be dependent on the stability of the linkages coupling nanoparticles to the cell surface.
Melanin targeting for intracellular drug delivery: Quantification of bound and free drug in retinal pigment epithelial cells.

PubMed

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.

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