Acid-mediated Lipinski's second rule: application to drug design and targeting in cancer.

PubMed

Omran, Ziad; Rauch, Cyril

2014-05-01

With a predicted 382.4 per 100,000 people expected to suffer from some form of malignant neoplasm by 2015, and a current death toll of 1 out of 8 deaths worldwide, improving treatment and/or drug design is an essential focus of cancer research. Multi-drug resistance is the leading cause of chemotherapeutic failure, and delivery of anticancer drugs to the inside of cancerous cells is another major challenge. Fifteen years ago, in a completely different field in which improving drug delivery is the objective, the bioavailability of oral compounds, Christopher Lipinski formulated some rules that are still used by the pharmaceutical industry as rules of thumb to improve drug delivery to their target. Although Lipinski's rules were not formulated to improve delivery of antineoplastic drugs to the inside of cancer cells, it is interesting to note that the problems are similar. On the basis of the strong similarity between the fields, we discuss how they can be connected and how new drug targets can be defined in cancer.

Bioengineering Strategies for Designing Targeted Cancer Therapies

PubMed Central

Wen, Xuejun

2014-01-01

The goals of bioengineering strategies for targeted cancer therapies are (1) to deliver a high dose of an anticancer drug directly to a cancer tumor, (2) to enhance drug uptake by malignant cells, and (3) to minimize drug uptake by nonmalignant cells. Effective cancer-targeting therapies will require both passive- and active targeting strategies and a thorough understanding of physiologic barriers to targeted drug delivery. Designing a targeted therapy includes the selection and optimization of a nanoparticle delivery vehicle for passive accumulation in tumors, a targeting moiety for active receptor-mediated uptake, and stimuli-responsive polymers for control of drug release. The future direction of cancer targeting is a combinatorial approach, in which targeting therapies are designed to use multiple targeting strategies. The combinatorial approach will enable combination therapy for delivery of multiple drugs and dual ligand targeting to improve targeting specificity. Targeted cancer treatments in development and the new combinatorial approaches show promise for improving targeted anticancer drug delivery and improving treatment outcomes. PMID:23768509

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.

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

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.

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.

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.

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

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

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.

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

NASA Astrophysics Data System (ADS)

Hajiaghajani, Amirhossein; Hashemi, Soheil; Abdolali, Ali

2017-09-01

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

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.

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

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.

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

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

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

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

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

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

Targeting the dopamine D3 receptor: an overview of drug design strategies.

PubMed

Cortés, Antoni; Moreno, Estefanía; Rodríguez-Ruiz, Mar; Canela, Enric I; Casadó, Vicent

2016-07-01

Dopamine is a neurotransmitter widely distributed in both the periphery and the central nervous system (CNS). Its physiological effects are mediated by five closely related G protein-coupled receptors (GPCRs) that are divided into two major subclasses: the D1-like (D1, D5) and the D2-like (D2, D3, D4) receptors. D3 receptors (D3Rs) have the highest density in the limbic areas of the brain, which are associated with cognitive and emotional functions. These receptors are therefore attractive targets for therapeutic management. This review summarizes the functional and pharmacological characteristics of D3Rs, including the design and clinical relevance of full agonists, partial agonists and antagonists, as well as the capacity of these receptors to form active homodimers, heterodimers or higher order receptor complexes as pharmacological targets in several neurological and neurodegenerative disorders. The high sequence homology between D3R and the D2-type challenges the development of D3R-selective compounds. The design of new D3R-preferential ligands with improved physicochemical properties should provide a better pharmacokinetic/bioavailability profile and lesser toxicity than is found with existing D3R ligands. It is also essential to optimize D3R affinity and, especially, D3R vs. D2-type binding and functional selectivity ratios. Developing allosteric and bitopic ligands should help to improve the D3R selectivity of these drugs. As most evidence points to the ability of GPCRs to form homomers and heteromers, the most promising therapeutic strategy in the future is likely to involve the application of heteromer-selective drugs. These selective ligands would display different affinities for a given receptor depending on the receptor partners within the heteromer. Therefore, designing novel compounds that specifically target and modulate D1R-D3R heteromers would be an interesting approach for the treatment of levodopa (L-DOPA)-induced dyskinesias.

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-04-01

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

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.

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

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.

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.

Targeted polymeric therapeutic nanoparticles: design, development and clinical translation†

PubMed Central

Kamaly, Nazila; Xiao, Zeyu; Valencia, Pedro M.; Radovic-Moreno, Aleksandar F.; Farokhzad, Omid C.

2013-01-01

Polymeric materials have been used in a range of pharmaceutical and biotechnology products for more than 40 years. These materials have evolved from their earlier use as biodegradable products such as resorbable sutures, orthopaedic implants, macroscale and microscale drug delivery systems such as microparticles and wafers used as controlled drug release depots, to multifunctional nanoparticles (NPs) capable of targeting, and controlled release of therapeutic and diagnostic agents. These newer generations of targeted and controlled release polymeric NPs are now engineered to navigate the complex in vivo environment, and incorporate functionalities for achieving target specificity, control of drug concentration and exposure kinetics at the tissue, cell, and subcellular levels. Indeed this optimization of drug pharmacology as aided by careful design of multifunctional NPs can lead to improved drug safety and efficacy, and may be complimentary to drug enhancements that are traditionally achieved by medicinal chemistry. In this regard, polymeric NPs have the potential to result in a highly differentiated new class of therapeutics, distinct from the original active drugs used in their composition, and distinct from first generation NPs that largely facilitated drug formulation. A greater flexibility in the design of drug molecules themselves may also be facilitated following their incorporation into NPs, as drug properties (solubility, metabolism, plasma binding, biodistribution, target tissue accumulation) will no longer be constrained to the same extent by drug chemical composition, but also become in-part the function of the physicochemical properties of the NP. The combination of optimally designed drugs with optimally engineered polymeric NPs opens up the possibility of improved clinical outcomes that may not be achievable with the administration of drugs in their conventional form. In this critical review, we aim to provide insights into the design and development

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

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.

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.

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

iDrug: a web-accessible and interactive drug discovery and design platform

PubMed Central

2014-01-01

Background The progress in computer-aided drug design (CADD) approaches over the past decades accelerated the early-stage pharmaceutical research. Many powerful standalone tools for CADD have been developed in academia. As programs are developed by various research groups, a consistent user-friendly online graphical working environment, combining computational techniques such as pharmacophore mapping, similarity calculation, scoring, and target identification is needed. Results We presented a versatile, user-friendly, and efficient online tool for computer-aided drug design based on pharmacophore and 3D molecular similarity searching. The web interface enables binding sites detection, virtual screening hits identification, and drug targets prediction in an interactive manner through a seamless interface to all adapted packages (e.g., Cavity, PocketV.2, PharmMapper, SHAFTS). Several commercially available compound databases for hit identification and a well-annotated pharmacophore database for drug targets prediction were integrated in iDrug as well. The web interface provides tools for real-time molecular building/editing, converting, displaying, and analyzing. All the customized configurations of the functional modules can be accessed through featured session files provided, which can be saved to the local disk and uploaded to resume or update the history work. Conclusions iDrug is easy to use, and provides a novel, fast and reliable tool for conducting drug design experiments. By using iDrug, various molecular design processing tasks can be submitted and visualized simply in one browser without installing locally any standalone modeling softwares. iDrug is accessible free of charge at http://lilab.ecust.edu.cn/idrug. PMID:24955134

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.

Design strategies and applications of circulating cell-mediated drug delivery systems.

PubMed

Su, Yixue; Xie, Zhiwei; Kim, Gloria B; Dong, Cheng; Yang, Jian

2015-01-01

Drug delivery systems, particularly nanomaterial-based drug delivery systems, possess a tremendous amount of potential to improve diagnostic and therapeutic effects of drugs. Controlled drug delivery targeted to a specific disease is designed to significantly improve the pharmaceutical effects of drugs and reduce their side effects. Unfortunately, only a few targeted drug delivery systems can achieve high targeting efficiency after intravenous injection, even with the development of numerous surface markers and targeting modalities. Thus, alternative drug and nanomedicine targeting approaches are desired. Circulating cells, such as erythrocytes, leukocytes, and stem cells, present innate disease sensing and homing properties. Hence, using living cells as drug delivery carriers has gained increasing interest in recent years. This review highlights the recent advances in the design of cell-mediated drug delivery systems and targeting mechanisms. The approaches of drug encapsulation/conjugation to cell-carriers, cell-mediated targeting mechanisms, and the methods of controlled drug release are elaborated here. Cell-based "live" targeting and delivery could be used to facilitate a more specific, robust, and smart payload distribution for the next-generation drug delivery systems.

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.

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

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.

Peptide-Drug Conjugate: A Novel Drug Design Approach.

PubMed

Ma, Liang; Wang, Chao; He, Zihao; Cheng, Biao; Zheng, Ling; Huang, Kun

2017-01-01

More than 100 years ago, German physician Paul Ehrlich first proposed the concept of selectively delivering "magic bullets" to tumors through targeting agents. The targeting therapy with antibody-drug conjugates (ADCs) and peptide-drug conjugate (PDCs), which are usually composed of monoclonal antibodies or peptides, toxic payloads and cleavage/ noncleavage linkers, has been extensively studied for decades. The conjugates enable selective delivery of cytotoxic payloads to target cells, which results in improved efficacy, reduced systemic toxicity and improved pharmacokinetics (PK)/pharmacodynamics (PD) compared with traditional chemotherapy. PDC and ADC share similar concept, but with vastly different structures and properties. Humanized antibodies introduce high specificity and prolonged half-life, while small molecule weight peptides exhibit higher drug loading and enhanced tissue penetration capacity, and the flexible linear or cyclic peptides are also modified more easily. In this review, the principles of design, synthesis approaches and the latest advances of PDCs are summarized. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Computer Aided Drug Design: Success and Limitations.

PubMed

Baig, Mohammad Hassan; Ahmad, Khurshid; Roy, Sudeep; Ashraf, Jalaluddin Mohammad; Adil, Mohd; Siddiqui, Mohammad Haris; Khan, Saif; Kamal, Mohammad Amjad; Provazník, Ivo; Choi, Inho

2016-01-01

Over the last few decades, computer-aided drug design has emerged as a powerful technique playing a crucial role in the development of new drug molecules. Structure-based drug design and ligand-based drug design are two methods commonly used in computer-aided drug design. In this article, we discuss the theory behind both methods, as well as their successful applications and limitations. To accomplish this, we reviewed structure based and ligand based virtual screening processes. Molecular dynamics simulation, which has become one of the most influential tool for prediction of the conformation of small molecules and changes in their conformation within the biological target, has also been taken into account. Finally, we discuss the principles and concepts of molecular docking, pharmacophores and other methods used in computer-aided drug design.

[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.

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.

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.

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.

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

TRPV1: A Target for Rational Drug Design

PubMed Central

Carnevale, Vincenzo; Rohacs, Tibor

2016-01-01

Transient Receptor Potential Vanilloid 1 (TRPV1) is a non-selective, Ca2+ permeable cation channel activated by noxious heat, and chemical ligands, such as capsaicin and resiniferatoxin (RTX). Many compounds have been developed that either activate or inhibit TRPV1, but none of them are in routine clinical practice. This review will discuss the rationale for antagonists and agonists of TRPV1 for pain relief and other conditions, and strategies to develop new, better drugs to target this ion channel, using the newly available high-resolution structures. PMID:27563913

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

PubMed

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

2015-07-15

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

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

PubMed

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

2016-01-26

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

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

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

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.

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

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.

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

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

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

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.

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.

Patient centric drug product design in modern drug delivery as an opportunity to increase safety and effectiveness.

PubMed

Stegemann, Sven

2018-06-01

The advances in drug delivery technologies have enabled pharmaceutical scientists to deliver a drug through various administration routes and optimize the drug release and absorption. The wide range of drug delivery systems and dosage forms represent a toolbox of technology for the development of pharmaceutical drug products but might also be a source of medication errors and nonadherence. Patient centric drug product development is being suggested as an important factor to increase therapeutic outcomes. Areas covered: Patients have impaired health and potentially disabilities and they are not medical or pharmaceutical experts but are requested to manage complex therapeutic regimens. As such the application of technology should also serve to reduce complexity, build on patients' intuition and ease of use. Patients form distinct populations based on the targeted disease, disease cluster or age group with specific characteristics or therapeutic contexts. Expert opinion: Establishing a target product and patient profile is essential to guide drug product design development. Including the targeted patient populations in the process is a prerequisite to achieve patient-centric pharmaceutical drug product design. Addressing the needs early on in the product design process, will create more universal design, avoiding the necessity for multiple product presentations to cover the different patient populations.

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

Smarter Drugs: How Protein Crystallography Revolutionizes Drug Design

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

Smith, Clyde

2005-04-26

According to Smith, protein crystallography allows scientists to design drugs in a much more efficient way than the standard methods traditionally used by large drug companies, which can cost close to a billion dollars and take 10 to 15 years. 'A lot of the work can be compressed down,' Smith said. Protein crystallography enables researchers to learn the structure of molecules involved in disease and health. Seeing the loops, folds and placement of atoms in anything from a virus to a healthy cell membrane gives important information about how these things work - and how to encourage, sidestep or stopmore » their functions. Drug design can be much faster when the relationship between structure and function tells you what area of a molecule to target. Smith will use a timeline to illustrate the traditional methods of drug development and the new ways it can be done now. 'It is very exciting work. There have been some failures, but many successes too.' A new drug to combat the flu was developed in a year or so. Smith will tell us how. He will also highlight drugs developed to combat HIV, Tuberculosis, hypertension and Anthrax.« less

Organic carbamates in drug design and medicinal chemistry.

PubMed

Ghosh, Arun K; Brindisi, Margherita

2015-04-09

The carbamate group is a key structural motif in many approved drugs and prodrugs. There is an increasing use of carbamates in medicinal chemistry and many derivatives are specifically designed to make drug-target interactions through their carbamate moiety. In this Perspective, we present properties and stabilities of carbamates, reagents and chemical methodologies for the synthesis of carbamates, and recent applications of carbamates in drug design and medicinal chemistry.

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.

Targeting targeted agents: open issues for clinical trial design.

PubMed

Bria, Emilio; Di Maio, Massimo; Carlini, Paolo; Cuppone, Federica; Giannarelli, Diana; Cognetti, Francesco; Milella, Michele

2009-05-22

Molecularly targeted agents for the treatment of solid tumors had entered the market in the last 5 years, with a great impact upon both the scientific community and the society. Many randomized phase III trials conducted in recent years with new targeted agents, despite previous data coming from preclinical research and from phase II trials were often promising, have produced disappointingly negative results. Some other trials have actually met their primary endpoint, demonstrating a statistically significant result favouring the experimental treatment. Unfortunately, with a few relevant exceptions, this advantage is often small, if not negligible, in absolute terms. The difference between statistical significance and clinical relevance should always be considered when translating clinical trials' results in the practice. The reason why this 'revolution' did not significantly impact on cancer treatment to displace chemotherapy from the patient' bedside is in part due to complicated, and in many cases, unknown, mechanisms of action of such drugs; indeed, the traditional way the clinical investigators were used to test the efficacy of 'older' chemotherapeutics, has become 'out of date' from the methodological perspective. As these drugs should be theoretically tailored upon featured bio-markers expressed by the patients, the clinical trial design should follow new rules based upon stronger hypotheses than those developed so far. Indeed, the early phases of basic and clinical drug development are crucial in the correct process which is able to correctly identify the target (when present). Targeted trial designs can result in easier studies, with less, better selected, and supported by stronger proofs of response evidences, patients, in order to not waste time and resources.

Closing the door on flaviviruses: entry as a target for antiviral drug design.

PubMed

Perera, Rushika; Khaliq, Mansoora; Kuhn, Richard J

2008-10-01

With the emergence and rapid spread of West Nile virus in the United States since 1999, and the 50-100 million infections per year caused by dengue virus globally, the threat of flaviviruses as re-emerging human pathogens has become a reality. To support the efforts that are currently being pursued to develop effective vaccines against these viruses, researchers are also actively pursuing the development of small molecule compounds that target various aspects of the virus life cycle. Recent advances in the structural characterization of the flaviviruses have provided a strong foundation towards these efforts. These studies have provided the pseudo-atomic structures of virions from several members of the genus as well as atomic resolution structures of several viral proteins. Most importantly, these studies have highlighted specific structural rearrangements that occur within the virion that are necessary for the virus to complete its life cycle. These rearrangements occur when the virus must transition from immature, to mature, to fusion-active states and rely heavily on the conformational flexibility of the envelope (E) protein that forms the outer glycoprotein shell of the virus. Analysis of these conformational changes can suggest promising targets for structure-based antiviral design. For instance, by targeting the flexibility of the E protein, it might be possible to inhibit required rearrangements of this protein and trap the virus in a specific state. This would interfere with a productive flaviviral infection. This review presents a structural perspective of the flavivirus life cycle and focuses on the role of the E protein as an opportune target for structure-based antiviral drug design.

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.

Emerging paradigms in anti-infective drug design.

PubMed

Barrett, Michael P; Croft, Simon L

2014-01-01

The need for new drugs to treat microbial infections is pressing. The great progress made in the middle part of the twentieth Century was followed by a period of relative inactivity as the medical needs relating to infectious disease in the wealthier nations receded. Growing realisation that anti-infectives are needed in many parts of the world, to treat neglected diseases as well as to combat the burgeoning risk of resistance to existing drugs, has galvanised a new wave of research into anti-microbial drugs. The transfer of knowledge from the Pharmaceutical industry relating to the importance of understanding how to target drugs successfully within the body, and improved understanding of how pathogens interact with their hosts, is driving a series of new paradigms in anti-infective drug design. Here we provide an overview of those processes as an introduction to a series of articles from experts in this area that emerged from a meeting entitled "Emerging Paradigms in Anti-Infective Drug Design" held in London on the 17th and 18th September 2012. The symposium was organised jointly by British Society for Parasitology (BSP) and the Biological & Medicinal Chemistry sector of the Royal Society of Chemistry (RSC) and held at the London School of Hygiene & Tropical Medicine. The symposium set out to cover all aspects of the identification of new therapeutic modalities for the treatment of neglected and tropical diseases. We aimed to bring together leading scientists from all the disciplines working in this field and cover the pharmacology, medicinal chemistry and drug delivery of potential new medicines. Sessions were held on: "Target diseases and targets for drugs", "Target based medicinal chemistry", "Bioavailability and chemistry", "Targeting intracellular microbes", "Alternative approaches and models", and "New anti-infectives - how do we get there?" This symposium was organised by Simon Croft (LSHTM) and Mike Barrett (University of Glasgow) for the BSP, and David

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.

Design of ligand-targeted nanoparticles for enhanced cancer targeting

NASA Astrophysics Data System (ADS)

Stefanick, Jared F.

Ligand-targeted nanoparticles are increasingly used as drug delivery vehicles for cancer therapy, yet have not consistently produced successful clinical outcomes. Although these inconsistencies may arise from differences in disease models and target receptors, nanoparticle design parameters can significantly influence therapeutic efficacy. By employing a multifaceted synthetic strategy to prepare peptide-targeted nanoparticles with high purity, reproducibility, and precisely controlled stoichiometry of functionalities, this work evaluates the roles of polyethylene glycol (PEG) coating, ethylene glycol (EG) peptide-linker length, peptide hydrophilicity, peptide density, and nanoparticle size on tumor targeting in a systematic manner. These parameters were analyzed in multiple disease models by targeting human epidermal growth factor receptor 2 (HER2) in breast cancer and very late antigen-4 (VLA-4) in multiple myeloma to demonstrate the widespread applicability of this approach. By increasing the hydrophilicity of the targeting peptide sequence and simultaneously optimizing the EG peptide-linker length, the in vitro cellular uptake of targeted liposomes was significantly enhanced. Specifically, including a short oligolysine chain adjacent to the targeting peptide sequence effectively increased cellular uptake ~80-fold using an EG6 peptide-linker compared to ~10-fold using an EG45 linker. In vivo, targeted liposomes prepared in a traditional manner lacking the oligolysine chain demonstrated similar biodistribution and tumor uptake to non-targeted liposomes. However, by including the oligolysine chain, targeted liposomes using an EG45 linker significantly improved tumor uptake ~8-fold over non-targeted liposomes, while the use of an EG6 linker decreased tumor accumulation and uptake, owing to differences in cellular uptake kinetics, clearance mechanisms, and binding site barrier effects. To further improve tumor targeting and enhance the selectivity of targeted

Evolution and intelligent design in drug development.

PubMed

Agafonov, Roman V; Wilson, Christopher; Kern, Dorothee

2015-01-01

Sophisticated protein kinase networks, empowering complexity in higher organisms, are also drivers of devastating diseases such as cancer. Accordingly, these enzymes have become major drug targets of the twenty-first century. However, the holy grail of designing specific kinase inhibitors aimed at specific cancers has not been found. Can new approaches in cancer drug design help win the battle with this multi-faced and quickly evolving enemy? In this perspective we discuss new strategies and ideas that were born out of a recent breakthrough in understanding the molecular basis underlying the clinical success of the cancer drug Gleevec. An "old" method, stopped-flow kinetics, combined with old enzymes, the ancestors dating back up to about billion years, provides an unexpected outlook for future intelligent design of drugs.

Pleiotropic effects of statins: new therapeutic targets in drug design.

PubMed

Bedi, Onkar; Dhawan, Veena; Sharma, P L; Kumar, Puneet

2016-07-01

The HMG Co-enzyme inhibitors and new lipid-modifying agents expand their new therapeutic target options in the field of medical profession. Statins have been described as the most effective class of drugs to reduce serum cholesterol levels. Since the discovery of the first statin nearly 30 years ago, these drugs have become the main therapeutic approach to lower cholesterol levels. The present scientific research demonstrates numerous non-lipid modifiable effects of statins termed as pleiotropic effects of statins, which could be beneficial for the treatment of various devastating disorders. The most important positive effects of statins are anti-inflammatory, anti-proliferative, antioxidant, immunomodulatory, neuroprotective, anti-diabetes, and antithrombotic, improving endothelial dysfunction and attenuating vascular remodeling besides many others which are discussed under the scope of this review. In particular, inhibition of Rho and its downstream target, Rho-associated coiled-coil-containing protein kinase (ROCK), and their agonistic action on peroxisome proliferator-activated receptors (PPARs) can be viewed as the principle mechanisms underlying the pleiotropic effects of statins. With gradually increasing knowledge of new therapeutic targets of statins, their use has also been advocated in chronic inflammatory disorders for example rheumatoid arthritis (RA) and in systemic lupus erythematosus (SLE). In the scope of review, we highlight statins and their pleiotropic effects with reference to their harmful and beneficial effects as a novel approach for their use in the treatment of devastating disorders. Graphical abstract Pleiotropic effect of statins.

Targeted prodrugs in oral drug delivery: the modern molecular biopharmaceutical approach.

PubMed

Dahan, Arik; Khamis, Mustafa; Agbaria, Riad; Karaman, Rafik

2012-08-01

The molecular revolution greatly impacted the field of drug design and delivery in general, and the utilization of the prodrug approach in particular. The increasing understanding of membrane transporters has promoted a novel 'targeted-prodrug' approach utilizing carrier-mediated transport to increase intestinal permeability, as well as specific enzymes to promote activation to the parent drug. This article provides the reader with a concise overview of this modern approach to prodrug design. Targeting the oligopeptide transporter PEPT1 for absorption and the serine hydrolase valacyclovirase for activation will be presented as examples for the successful utilization of this approach. Additionally, the use of computational approaches, such as DFT and ab initio molecular orbital methods, in modern prodrugs design will be discussed. Overall, in the coming years, more and more information will undoubtedly become available regarding intestinal transporters and potential enzymes that may be exploited for the targeted modern prodrug approach. Hence, the concept of prodrug design can no longer be viewed as merely a chemical modification to solve problems associated with parent compounds. Rather, it opens promising opportunities for precise and efficient drug delivery, as well as enhancement of treatment options and therapeutic efficacy.

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.

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.

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.

Design of pH-sensitive methotrexate prodrug-targeted curcumin nanoparticles for efficient dual-drug delivery and combination cancer therapy.

PubMed

Xie, Jiajiang; Fan, Zhongxiong; Li, Yang; Zhang, Yinying; Yu, Fei; Su, Guanghao; Xie, Liya; Hou, Zhenqing

2018-01-01

We designed acid-labile methotrexate (MTX) targeting prodrug self-assembling nanoparticles loaded with curcumin (CUR) drug for simultaneous delivery of multi-chemotherapeutic drugs and combination cancer therapy. A dual-acting MTX, acting as both an anticancer drug and as a tumor-targeting ligand, was coupled to 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[aldehyde(polyethylene glycol)-2000] via Schiff's base reaction. The synthesized prodrug conjugate (DSPE-PEG-Imine-MTX) could be self-assembled into micellar nanoparticles (MTX-Imine-M) in aqueous solution, which encapsulated CUR into their core by hydrophobic interactions (MTX-Imine-M-CUR). The prepared MTX-Imine-M-CUR nanoparticles were composed of an inner hydrophobic DSPE/CUR core and an outside hydrophilic bishydroxyl poly (ethyleneglycol) (PEG) shell with a self-targeting MTX prodrug corona. The imine linker between 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[aldehyde(polyethyleneglycol)-2000] and MTX, as a dynamic covalent bond, was strong enough to remain intact in physiological pH, even though it is rapidly cleaved in acidic pH. The MTX-Imine-M-CUR could codeliver MTX and CUR selectively and efficiently into the cancer cells via folate receptor-mediated endocytosis followed by the rapid intracellular release of CUR and the active form of MTX via the acidity of endosomes/lysosomes. Moreover, the MTX-Imine-M-CUR resulted in significantly higher in vitro and in vivo anticancer activity than pH-insensitive DSPE-PEGAmide-MTX assembling nanoparticles loaded with CUR (MTX-Amide-M-CUR), MTX unconjugated DSPE-PEG assembling micellar nanoparticles loaded with CUR (M-CUR), combination of both free drugs, and individual free drugs. The smart system provided a simple, yet feasible, drug delivery strategy for targeted combination chemotherapy.

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.

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.

Drug target ontology to classify and integrate drug discovery data.

PubMed

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

2017-11-09

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

Predicting 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

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

Computer-aided drug design for AMP-activated protein kinase activators.

PubMed

Wang, Zhanli; Huo, Jianxin; Sun, Lidan; Wang, Yongfu; Jin, Hongwei; Yu, Hui; Zhang, Liangren; Zhou, Lishe

2011-09-01

AMP-activated protein kinase (AMPK) is an important therapeutic target for the potential treatment of metabolic disorders, cardiovascular disease and cancer. Recently, various classes of compounds that activate AMPK by direct or indirect interactions have been reported. The importance of computer-aided drug design approaches in the search for potent activators of AMPK is now established, including structure-based design, ligand-based design, fragment-based design, as well as structural analysis. This review article highlights the computer-aided drug design approaches utilized to discover of activators targeting AMPK. The principles, advantages or limitation of the different methods are also being discussed together with examples of applications taken from the literatures.

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 © 2016 Elsevier Ltd. All rights reserved.

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.

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.

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.

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

Spotting and designing promiscuous ligands for drug discovery.

PubMed

Schneider, P; Röthlisberger, M; Reker, D; Schneider, G

2016-01-21

The promiscuous binding behavior of bioactive compounds forms a mechanistic basis for understanding polypharmacological drug action. We present the development and prospective application of a computational tool for identifying potential promiscuous drug-like ligands. In combination with computational target prediction methods, the approach provides a working concept for rationally designing such molecular structures. We could confirm the multi-target binding of a de novo generated compound in a proof-of-concept study relying on the new method.

Organic Carbamates in Drug Design and Medicinal Chemistry

PubMed Central

2016-01-01

The carbamate group is a key structural motif in many approved drugs and prodrugs. There is an increasing use of carbamates in medicinal chemistry and many derivatives are specifically designed to make drug–target interactions through their carbamate moiety. In this Perspective, we present properties and stabilities of carbamates, reagents and chemical methodologies for the synthesis of carbamates, and recent applications of carbamates in drug design and medicinal chemistry. PMID:25565044

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.

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.

Generative Recurrent Networks for De Novo Drug Design.

PubMed

Gupta, Anvita; Müller, Alex T; Huisman, Berend J H; Fuchs, Jens A; Schneider, Petra; Schneider, Gisbert

2018-01-01

Generative artificial intelligence models present a fresh approach to chemogenomics and de novo drug design, as they provide researchers with the ability to narrow down their search of the chemical space and focus on regions of interest. We present a method for molecular de novo design that utilizes generative recurrent neural networks (RNN) containing long short-term memory (LSTM) cells. This computational model captured the syntax of molecular representation in terms of SMILES strings with close to perfect accuracy. The learned pattern probabilities can be used for de novo SMILES generation. This molecular design concept eliminates the need for virtual compound library enumeration. By employing transfer learning, we fine-tuned the RNN's predictions for specific molecular targets. This approach enables virtual compound design without requiring secondary or external activity prediction, which could introduce error or unwanted bias. The results obtained advocate this generative RNN-LSTM system for high-impact use cases, such as low-data drug discovery, fragment based molecular design, and hit-to-lead optimization for diverse drug targets. © 2017 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

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

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

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

Multi-Step Usage of in Vivo Models During Rational Drug Design and Discovery

PubMed Central

Williams, Charles H.; Hong, Charles C.

2011-01-01

In this article we propose a systematic development method for rational drug design while reviewing paradigms in industry, emerging techniques and technologies in the field. Although the process of drug development today has been accelerated by emergence of computational methodologies, it is a herculean challenge requiring exorbitant resources; and often fails to yield clinically viable results. The current paradigm of target based drug design is often misguided and tends to yield compounds that have poor absorption, distribution, metabolism, and excretion, toxicology (ADMET) properties. Therefore, an in vivo organism based approach allowing for a multidisciplinary inquiry into potent and selective molecules is an excellent place to begin rational drug design. We will review how organisms like the zebrafish and Caenorhabditis elegans can not only be starting points, but can be used at various steps of the drug development process from target identification to pre-clinical trial models. This systems biology based approach paired with the power of computational biology; genetics and developmental biology provide a methodological framework to avoid the pitfalls of traditional target based drug design. PMID:21731440

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.

Advantages of Structure-Based Drug Design Approaches in Neurological Disorders

PubMed Central

Aarthy, Murali; Panwar, Umesh; Selvaraj, Chandrabose; Singh, Sanjeev Kumar

2017-01-01

Objective: The purpose of the review is to portray the theoretical concept on neurological disorders from research data. Background: The freak changes in chemical response of nerve impulse causes neurological disorders. The research evidence of the effort done in the older history suggests that the biological drug targets and their effective feature with responsive drugs could be valuable in promoting the future development of health statistics structure for improved treatment for curing the nervous disorders. Methods: In this review, we summarized the most iterative theoretical concept of structure based drug design approaches in various neurological disorders to unfathomable understanding of reported information for future drug design and development. Results: On the premise of reported information we analyzed the model of theoretical drug designing process for understanding the mechanism and pathology of the neurological diseases which covers the development of potentially effective inhibitors against the biological drug targets. Finally, it also suggests the management and implementation of the current treatment in improving the human health system behaviors. Conclusion: With the survey of reported information we concluded the development strategies of diagnosis and treatment against neurological diseases which leads to supportive progress in the drug discovery. PMID:28042767

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.

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.

Thermodynamic Studies for Drug Design and Screening

PubMed Central

Garbett, Nichola C.; Chaires, Jonathan B.

2012-01-01

Introduction A key part of drug design and development is the optimization of molecular interactions between an engineered drug candidate and its binding target. Thermodynamic characterization provides information about the balance of energetic forces driving binding interactions and is essential for understanding and optimizing molecular interactions. Areas covered This review discusses the information that can be obtained from thermodynamic measurements and how this can be applied to the drug development process. Current approaches for the measurement and optimization of thermodynamic parameters are presented, specifically higher throughput and calorimetric methods. Relevant literature for this review was identified in part by bibliographic searches for the period 2004 – 2011 using the Science Citation Index and PUBMED and the keywords listed below. Expert opinion The most effective drug design and development platform comes from an integrated process utilizing all available information from structural, thermodynamic and biological studies. Continuing evolution in our understanding of the energetic basis of molecular interactions and advances in thermodynamic methods for widespread application are essential to realize the goal of thermodynamically-driven drug design. Comprehensive thermodynamic evaluation is vital early in the drug development process to speed drug development towards an optimal energetic interaction profile while retaining good pharmacological properties. Practical thermodynamic approaches, such as enthalpic optimization, thermodynamic optimization plots and the enthalpic efficiency index, have now matured to provide proven utility in design process. Improved throughput in calorimetric methods remains essential for even greater integration of thermodynamics into drug design. PMID:22458502

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.

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.

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

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.

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

Drug Target Discovery Methods In Targeting Neurotropic Parasitic Amoebae.

PubMed

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

2018-02-21

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

Targeted Drug-Carrying Bacteriophages as Antibacterial Nanomedicines▿

PubMed Central

Yacoby, Iftach; Bar, Hagit; Benhar, Itai

2007-01-01

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

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.

MPD3: a useful medicinal plants database for drug designing.

PubMed

Mumtaz, Arooj; Ashfaq, Usman Ali; Ul Qamar, Muhammad Tahir; Anwar, Farooq; Gulzar, Faisal; Ali, Muhammad Amjad; Saari, Nazamid; Pervez, Muhammad Tariq

2017-06-01

Medicinal plants are the main natural pools for the discovery and development of new drugs. In the modern era of computer-aided drug designing (CADD), there is need of prompt efforts to design and construct useful database management system that allows proper data storage, retrieval and management with user-friendly interface. An inclusive database having information about classification, activity and ready-to-dock library of medicinal plant's phytochemicals is therefore required to assist the researchers in the field of CADD. The present work was designed to merge activities of phytochemicals from medicinal plants, their targets and literature references into a single comprehensive database named as Medicinal Plants Database for Drug Designing (MPD3). The newly designed online and downloadable MPD3 contains information about more than 5000 phytochemicals from around 1000 medicinal plants with 80 different activities, more than 900 literature references and 200 plus targets. The designed database is deemed to be very useful for the researchers who are engaged in medicinal plants research, CADD and drug discovery/development with ease of operation and increased efficiency. The designed MPD3 is a comprehensive database which provides most of the information related to the medicinal plants at a single platform. MPD3 is freely available at: http://bioinform.info .

Nanobiotechnology-based drug delivery in brain targeting.

PubMed

Dinda, Subas C; Pattnaik, Gurudutta

2013-01-01

of specific receptors expressed across the BBB. It is found that the low density lipoproteins related protein (LPR) with engineered peptide compound (EpiC) formed the platform incorporating the Angiopep peptide as a new effective therapeutics. The current challenges are to design and develop the drug delivery careers, which must be able to deliver the drug across the BBB at a safe and effective manner. Nanoparticles are found to be effective careers in delivery of conventional drugs, recombinant proteins, vaccines as well as nucleotides. Nanoparticlulate drug delivery systems are found to be improving in the pharmacokinetic strategies of the drug molecules such as biodistribution, bioavailability and drug release characteristics in a controlled and effective manner with site specific drug delivery targeting to tissue or cell with reduction in toxic manifestation. Therefore, the use of nanotechnology in the field of pharmaceutical biotechnology helps in improving the drug delivery strategy including the kinetics and therapeutic index to solve the delivery problems of some biotech drugs including the recombinant proteins and oligonucleotides. This review is made to provide an insight to the role of nanobiotechnology in drug delivery and drug targeting to brain and its recent advances in the field of drug delivery systems.

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.

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

PubMed Central

2013-01-01

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

Drugs and Targets in Fibrosis

PubMed Central

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

2017-01-01

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

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

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

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

NASA Astrophysics Data System (ADS)

Gevertz, Jana

2012-04-01

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

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

Mechanisms and biomaterials in pH-responsive tumour targeted drug delivery: A review.

PubMed

Kanamala, Manju; Wilson, William R; Yang, Mimi; Palmer, Brian D; Wu, Zimei

2016-04-01

As the mainstay in the treatment of various cancers, chemotherapy plays a vital role, but still faces many challenges, such as poor tumour selectivity and multidrug resistance (MDR). Targeted drug delivery using nanotechnology has provided a new strategy for addressing the limitations of the conventional chemotherapy. In the last decade, the volume of research published in this area has increased tremendously, especially with functional nano drug delivery systems (nanocarriers). Coupling a specific stimuli-triggered drug release mechanism with these delivery systems is one of the most prevalent approaches for improving therapeutic outcomes. Among the various stimuli, pH triggered delivery is regarded as the most general strategy, targeting the acidic extracellular microenvironment and intracellular organelles of solid tumours. In this review, we discuss recent advances in the development of pH-sensitive nanocarriers for tumour-targeted drug delivery. The review focuses on the chemical design of pH-sensitive biomaterials, which are used to fabricate nanocarriers for extracellular and/or intracellular tumour site-specific drug release. The pH-responsive biomaterials bring forth conformational changes in these nanocarriers through various mechanisms such as protonation, charge reversal or cleavage of a chemical bond, facilitating tumour specific cell uptake or drug release. A greater understanding of these mechanisms will help to design more efficient drug delivery systems to address the challenges encountered in conventional chemotherapy. Copyright © 2016 Elsevier Ltd. 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.

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

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

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

PubMed

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

2016-05-01

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

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

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.

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

Computational Tools for Allosteric Drug Discovery: Site Identification and Focus Library Design.

PubMed

Huang, Wenkang; Nussinov, Ruth; Zhang, Jian

2017-01-01

Allostery is an intrinsic phenomenon of biological macromolecules involving regulation and/or signal transduction induced by a ligand binding to an allosteric site distinct from a molecule's active site. Allosteric drugs are currently receiving increased attention in drug discovery because drugs that target allosteric sites can provide important advantages over the corresponding orthosteric drugs including specific subtype selectivity within receptor families. Consequently, targeting allosteric sites, instead of orthosteric sites, can reduce drug-related side effects and toxicity. On the down side, allosteric drug discovery can be more challenging than traditional orthosteric drug discovery due to difficulties associated with determining the locations of allosteric sites and designing drugs based on these sites and the need for the allosteric effects to propagate through the structure, reach the ligand binding site and elicit a conformational change. In this study, we present computational tools ranging from the identification of potential allosteric sites to the design of "allosteric-like" modulator libraries. These tools may be particularly useful for allosteric drug discovery.

Ligand design for riboswitches, an emerging target class for novel antibiotics.

PubMed

Rekand, Illimar Hugo; Brenk, Ruth

2017-09-01

Riboswitches are cis-acting gene regulatory elements and constitute potential targets for new antibiotics. Recent studies in this field have started to explore these targets for drug discovery. New ligands found by fragment screening, design of analogs of the natural ligands or serendipitously by phenotypic screening have shown antibacterial effects in cell assays against a range of bacteria strains and in animal models. In this review, we highlight the most advanced drug design work of riboswitch ligands and discuss the challenges in the field with respect to the development of antibiotics with a new mechanism of action.

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

Multiscale Modeling in the Clinic: Drug Design and Development

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

Clancy, Colleen E.; An, Gary; Cannon, William R.

A wide range of length and time scales are relevant to pharmacology, especially in drug development, drug design and drug delivery. Therefore, multi-scale computational modeling and simulation methods and paradigms that advance the linkage of phenomena occurring at these multiple scales have become increasingly important. Multi-scale approaches present in silico opportunities to advance laboratory research to bedside clinical applications in pharmaceuticals research. This is achievable through the capability of modeling to reveal phenomena occurring across multiple spatial and temporal scales, which are not otherwise readily accessible to experimentation. The resultant models, when validated, are capable of making testable predictions tomore » guide drug design and delivery. In this review we describe the goals, methods, and opportunities of multi-scale modeling in drug design and development. We demonstrate the impact of multiple scales of modeling in this field. We indicate the common mathematical techniques employed for multi-scale modeling approaches used in pharmacology and present several examples illustrating the current state-of-the-art regarding drug development for: Excitable Systems (Heart); Cancer (Metastasis and Differentiation); Cancer (Angiogenesis and Drug Targeting); Metabolic Disorders; and Inflammation and Sepsis. We conclude with a focus on barriers to successful clinical translation of drug development, drug design and drug delivery multi-scale models.« less

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

The Co-Metabolism within the Gut-Brain Metabolic Interaction: Potential Targets for Drug Treatment and Design.

PubMed

Obrenovich, Mark; Flückiger, Rudolf; Sykes, Lorraine; Donskey, Curtis

2016-01-01

We know that within the complex mammalian gut is any number of metabolic biomes. The gut has been sometimes called the "second brain" within the "gut-brain axis". A more informative term would be the gut-brain metabolic interactome, which is coined here to underscore the relationship between the digestive system and cognitive function or dysfunction as the case may be. Co-metabolism between the host and the intestinal microbiota is essential for life's processes. How diet, lifestyle, antibiotics and other factors shape the gut microbiome constitutes a rapidly growing area of research. Conversely, the gut microbiome also affects mammalian systems. Metabolites of the gut-brain axis are potential targets for treatment and drug design since the interaction or biochemical interplay results in net metabolite production or end-products with either positive or negative effects on human health. This review explores the gut-brain metabolic interactome, with particular emphasis on drug design and treatment strategies and how commensal bacteria or their disruption lead to dysbiosis and the effect this has on neurochemistry. Increasing data indicate that the intestinal microbiome can affect neurobiology, from mental and even behavioral health to memory, depression, mood, anxiety, obesity, cravings and even the creation and maintenance of the blood brain barrier.

Drug-target interaction prediction: A Bayesian ranking approach.

PubMed

Peska, Ladislav; Buza, Krisztian; Koller, Júlia

2017-12-01

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

Targeting Antibacterial Agents by Using Drug-Carrying Filamentous Bacteriophages

PubMed Central

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

2006-01-01

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

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

PubMed

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

2017-01-01

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

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

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.

Importance of polar solvation and configurational entropy for design of antiretroviral drugs targeting HIV-1 protease.

PubMed

Kar, Parimal; Lipowsky, Reinhard; Knecht, Volker

2013-05-16

Both KNI-10033 and KNI-10075 are high affinity preclinical HIV-1 protease (PR) inhibitors with affinities in the picomolar range. In this work, the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method has been used to investigate the potency of these two HIV-1 PR inhibitors against the wild-type and mutated proteases assuming that potency correlates with the affinity of the drugs for the target protein. The decomposition of the binding free energy reveals the origin of binding affinities or mutation-induced affinity changes. Our calculations indicate that the mutation I50V causes drug resistance against both inhibitors. On the other hand, we predict that the mutant I84V causes drug resistance against KNI-10075 while KNI-10033 is more potent against the I84V mutant compared to wild-type protease. Drug resistance arises mainly from unfavorable shifts in van der Waals interactions and configurational entropy. The latter indicates that neglecting changes in configurational entropy in the computation of relative binding affinities as often done is not appropriate in general. For the bound complex PR(I50V)-KNI-10075, an increased polar solvation free energy also contributes to the drug resistance. The importance of polar solvation free energies is revealed when interactions governing the binding of KNI-10033 or KNI-10075 to the wild-type protease are compared to the inhibitors darunavir or GRL-06579A. Although the contributions from intermolecular electrostatic and van der Waals interactions as well as the nonpolar component of the solvation free energy are more favorable for PR-KNI-10033 or PR-KNI-10075 compared to PR-DRV or PR-GRL-06579A, both KNI-10033 and KNI-10075 show a similar affinity as darunavir and a lower binding affinity relative to GRL-06579A. This is because of the polar solvation free energy which is less unfavorable for darunavir or GRL-06579A relative to KNI-10033 or KNI-10075. The importance of the polar solvation as revealed here

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.

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.

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.

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

PubMed

Peletier, Lambertus A; Gabrielsson, Johan

2018-05-14

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

Understanding drug targets: no such thing as bad news.

PubMed

Roberts, Ruth A

2018-05-24

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

Computational Fragment-Based Drug Design: Current Trends, Strategies, and Applications.

PubMed

Bian, Yuemin; Xie, Xiang-Qun Sean

2018-04-09

Fragment-based drug design (FBDD) has become an effective methodology for drug development for decades. Successful applications of this strategy brought both opportunities and challenges to the field of Pharmaceutical Science. Recent progress in the computational fragment-based drug design provide an additional approach for future research in a time- and labor-efficient manner. Combining multiple in silico methodologies, computational FBDD possesses flexibilities on fragment library selection, protein model generation, and fragments/compounds docking mode prediction. These characteristics provide computational FBDD superiority in designing novel and potential compounds for a certain target. The purpose of this review is to discuss the latest advances, ranging from commonly used strategies to novel concepts and technologies in computational fragment-based drug design. Particularly, in this review, specifications and advantages are compared between experimental and computational FBDD, and additionally, limitations and future prospective are discussed and emphasized.

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.

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

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.

Design challenges in nanoparticle-based platforms: Implications for targeted drug delivery systems

NASA Astrophysics Data System (ADS)

Mullen, Douglas Gurnett

Characterization and control of heterogeneous distributions of nanoparticle-ligand components are major design challenges for nanoparticle-based platforms. This dissertation begins with an examination of poly(amidoamine) (PAMAM) dendrimer-based targeted delivery platform. A folic acid targeted modular platform was developed to target human epithelial cancer cells. Although active targeting was observed in vitro, active targeting was not found in vivo using a mouse tumor model. A major flaw of this platform design was that it did not provide for characterization or control of the component distribution. Motivated by the problems experienced with the modular design, the actual composition of nanoparticle-ligand distributions were examined using a model dendrimer-ligand system. High Pressure Liquid Chromatography (HPLC) resolved the distribution of components in samples with mean ligand/dendrimer ratios ranging from 0.4 to 13. A peak fitting analysis enabled the quantification of the component distribution. Quantified distributions were found to be significantly more heterogeneous than commonly expected and standard analytical parameters, namely the mean ligand/nanoparticle ratio, failed to adequately represent the component heterogeneity. The distribution of components was also found to be sensitive to particle modifications that preceded the ligand conjugation. With the knowledge gained from this detailed distribution analysis, a new platform design was developed to provide a system with dramatically improved control over the number of components and with improved batch reproducibility. Using semi-preparative HPLC, individual dendrimer-ligand components were isolated. The isolated dendrimer with precise numbers of ligands were characterized by NMR and analytical HPLC. In total, nine different dendrimer-ligand components were obtained with degrees of purity ≥80%. This system has the potential to serve as a platform to which a precise number of functional molecules

Design of Drug Delivery Methods for the Brain and Central Nervous System

NASA Astrophysics Data System (ADS)

Lueshen, Eric

Due to the impermeability of the blood-brain barrier (BBB) to macromolecules delivered systemically, drug delivery to the brain and central nervous system (CNS) is quite difficult and has become an area of intense research. Techniques such as convection-enhanced intraparenchymal delivery and intrathecal magnetic drug targeting offer a means of circumventing the blood-brain barrier for targeted delivery of therapeutics. This dissertation focuses on three aspects of drug delivery: pharmacokinetics, convection-enhanced delivery, and intrathecal magnetic drug targeting. Classical pharmacokinetics mainly uses black-box curve fitting techniques without biochemical or biological basis. This dissertation advances the state-of-the-art of pharmacokinetics and pharmacodynamics by incorporating first principles and biochemical/biotransport mechanisms in the prediction of drug fate in vivo. A whole body physiologically-based pharmacokinetics (PBPK) modeling framework is engineered which creates multiscale mathematical models for entire organisms composed of organs, tissues, and a detailed vasculature network to predict drug bioaccumulation and to rigorously determine kinetic parameters. These models can be specialized to account for species, weight, gender, age, and pathology. Systematic individual therapy design using the proposed mechanistic PBPK modeling framework is also a possibility. Biochemical, anatomical, and physiological scaling laws are also developed to accurately project drug kinetics in humans from small animal experiments. Our promising results demonstrate that the whole-body mechanistic PBPK modeling approach not only elucidates drug mechanisms from a biochemical standpoint, but offers better scaling precision. Better models can substantially accelerate the introduction of drug leads to clinical trials and eventually to the market by offering more understanding of the drug mechanisms, aiding in therapy design, and serving as an accurate dosing tool. Convection

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

PubMed Central

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

2012-01-01

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

A General Strategy for Targeting Drugs to Bone.

PubMed

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

2015-11-23

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

Importance of target-mediated drug disposition for small molecules.

PubMed

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

2018-06-18

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

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

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.

Using computer-aided drug design and medicinal chemistry strategies in the fight against diabetes.

PubMed

Semighini, Evandro P; Resende, Jonathan A; de Andrade, Peterson; Morais, Pedro A B; Carvalho, Ivone; Taft, Carlton A; Silva, Carlos H T P

2011-04-01

The aim of this work is to present a simple, practical and efficient protocol for drug design, in particular Diabetes, which includes selection of the illness, good choice of a target as well as a bioactive ligand and then usage of various computer aided drug design and medicinal chemistry tools to design novel potential drug candidates in different diseases. We have selected the validated target dipeptidyl peptidase IV (DPP-IV), whose inhibition contributes to reduce glucose levels in type 2 diabetes patients. The most active inhibitor with complex X-ray structure reported was initially extracted from the BindingDB database. By using molecular modification strategies widely used in medicinal chemistry, besides current state-of-the-art tools in drug design (including flexible docking, virtual screening, molecular interaction fields, molecular dynamics, ADME and toxicity predictions), we have proposed 4 novel potential DPP-IV inhibitors with drug properties for Diabetes control, which have been supported and validated by all the computational tools used herewith.

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

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

New approach of delivering cytotoxic drugs towards CAIX expressing cells: A concept of dual-target drugs.

PubMed

van Kuijk, Simon J A; Parvathaneni, Nanda Kumar; Niemans, Raymon; van Gisbergen, Marike W; Carta, Fabrizio; Vullo, Daniela; Pastorekova, Silvia; Yaromina, Ala; Supuran, Claudiu T; Dubois, Ludwig J; Winum, Jean-Yves; Lambin, Philippe

2017-02-15

Carbonic anhydrase IX (CAIX) is a hypoxia-regulated and tumor-specific protein that maintains the pH balance of cells. Targeting CAIX might be a valuable approach for specific delivery of cytotoxic drugs, thereby reducing normal tissue side-effects. A series of dual-target compounds were designed and synthesized incorporating a sulfonamide, sulfamide, or sulfamate moiety combined with several different anti-cancer drugs, including the chemotherapeutic agents chlorambucil, tirapazamine, and temozolomide, two Ataxia Telangiectasia and Rad3-related protein inhibitors (ATRi), and the anti-diabetic biguanide agent phenformin. An ATRi derivative (12) was the only compound to show a preferred efficacy in CAIX overexpressing cells versus cells without CAIX expression when combined with radiation. Its efficacy might however not solely depend on binding to CAIX, since all described compounds generally display low activity as carbonic anhydrase inhibitors. The hypothesis that dual-target compounds specifically target CAIX expressing tumor cells was therefore not confirmed. Even though dual-target compounds remain an interesting approach, alternative options should also be investigated as novel treatment strategies. Copyright © 2016 The Authors. Published by Elsevier Masson SAS.. 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

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.

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

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.

Rational drug design paradigms: the odyssey for designing better drugs.

PubMed

Kellici, Tahsin; Ntountaniotis, Dimitrios; Vrontaki, Eleni; Liapakis, George; Moutevelis-Minakakis, Panagiota; Kokotos, George; Hadjikakou, Sotiris; Tzakos, Andreas G; Afantitis, Antreas; Melagraki, Georgia; Bryant, Sharon; Langer, Thierry; Di Marzo, Vincenzo; Mavromoustakos, Thomas

2015-01-01

Due to the time and effort requirements for the development of a new drug, and the high attrition rates associated with this developmental process, there is an intense effort by academic and industrial researchers to find novel ways for more effective drug development schemes. The first step in the discovery process of a new drug is the identification of the lead compound. The modern research tendency is to avoid the synthesis of new molecules based on chemical intuition, which is time and cost consuming, and instead to apply in silico rational drug design. This approach reduces the consumables and human personnel involved in the initial steps of the drug design. In this review real examples from our research activity aiming to discover new leads will be given for various dire warnings diseases. There is no recipe to follow for discovering new leads. The strategy to be followed depends on the knowledge of the studied system and the experience of the researchers. The described examples constitute successful and unsuccessful efforts and reflect the reality which medicinal chemists have to face in drug design and development. The drug stability is also discussed in both organic molecules and metallotherapeutics. This is an important issue in drug discovery as drug metabolism in the body can lead to various toxic and undesired molecules.

Optimized hydrophobic interactions and hydrogen bonding at the target-ligand interface leads the pathways of drug-designing.

PubMed

Patil, Rohan; Das, Suranjana; Stanley, Ashley; Yadav, Lumbani; Sudhakar, Akulapalli; Varma, Ashok K

2010-08-16

Weak intermolecular interactions such as hydrogen bonding and hydrophobic interactions are key players in stabilizing energetically-favored ligands, in an open conformational environment of protein structures. However, it is still poorly understood how the binding parameters associated with these interactions facilitate a drug-lead to recognize a specific target and improve drugs efficacy. To understand this, comprehensive analysis of hydrophobic interactions, hydrogen bonding and binding affinity have been analyzed at the interface of c-Src and c-Abl kinases and 4-amino substituted 1H-pyrazolo [3, 4-d] pyrimidine compounds. In-silico docking studies were performed, using Discovery Studio software modules LigandFit, CDOCKER and ZDOCK, to investigate the role of ligand binding affinity at the hydrophobic pocket of c-Src and c-Abl kinase. Hydrophobic and hydrogen bonding interactions of docked molecules were compared using LigPlot program. Furthermore, 3D-QSAR and MFA calculations were scrutinized to quantify the role of weak interactions in binding affinity and drug efficacy. The in-silico method has enabled us to reveal that a multi-targeted small molecule binds with low affinity to its respective targets. But its binding affinity can be altered by integrating the conformationally favored functional groups at the active site of the ligand-target interface. Docking studies of 4-amino-substituted molecules at the bioactive cascade of the c-Src and c-Abl have concluded that 3D structural folding at the protein-ligand groove is also a hallmark for molecular recognition of multi-targeted compounds and for predicting their biological activity. The results presented here demonstrate that hydrogen bonding and optimized hydrophobic interactions both stabilize the ligands at the target site, and help alter binding affinity and drug efficacy.

Optimized Hydrophobic Interactions and Hydrogen Bonding at the Target-Ligand Interface Leads the Pathways of Drug-Designing

PubMed Central

Stanley, Ashley; Yadav, Lumbani; Sudhakar, Akulapalli; Varma, Ashok K.

2010-01-01

Background Weak intermolecular interactions such as hydrogen bonding and hydrophobic interactions are key players in stabilizing energetically-favored ligands, in an open conformational environment of protein structures. However, it is still poorly understood how the binding parameters associated with these interactions facilitate a drug-lead to recognize a specific target and improve drugs efficacy. To understand this, comprehensive analysis of hydrophobic interactions, hydrogen bonding and binding affinity have been analyzed at the interface of c-Src and c-Abl kinases and 4-amino substituted 1H-pyrazolo [3, 4-d] pyrimidine compounds. Methodology In-silico docking studies were performed, using Discovery Studio software modules LigandFit, CDOCKER and ZDOCK, to investigate the role of ligand binding affinity at the hydrophobic pocket of c-Src and c-Abl kinase. Hydrophobic and hydrogen bonding interactions of docked molecules were compared using LigPlot program. Furthermore, 3D-QSAR and MFA calculations were scrutinized to quantify the role of weak interactions in binding affinity and drug efficacy. Conclusions The in-silico method has enabled us to reveal that a multi-targeted small molecule binds with low affinity to its respective targets. But its binding affinity can be altered by integrating the conformationally favored functional groups at the active site of the ligand-target interface. Docking studies of 4-amino-substituted molecules at the bioactive cascade of the c-Src and c-Abl have concluded that 3D structural folding at the protein-ligand groove is also a hallmark for molecular recognition of multi-targeted compounds and for predicting their biological activity. The results presented here demonstrate that hydrogen bonding and optimized hydrophobic interactions both stabilize the ligands at the target site, and help alter binding affinity and drug efficacy. PMID:20808434

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

Solution NMR Spectroscopy in Target-Based Drug Discovery.

PubMed

Li, Yan; Kang, Congbao

2017-08-23

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

Experimental Drug Metarrestin Targets Metastatic Tumors

Cancer.gov

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

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.

CADD Modeling of Multi-Target Drugs Against Alzheimer's Disease.

PubMed

Ambure, Pravin; Roy, Kunal

2017-01-01

Alzheimer's disease (AD) is a neurodegenerative disorder that is described by multiple factors linked with the progression of the disease. The currently approved drugs in the market are not capable of curing AD; instead, they merely provide symptomatic relief. Development of multi-target directed ligands (MTDLs) is an emerging strategy for improving the quality of the treatment against complex diseases like AD. Polypharmacology is a branch of pharmaceutical sciences that deals with the MTDL development. In this mini-review, we have summarized and discussed different strategies that are reported in the literature to design MTDLs for AD. Further, we have discussed the role of different in silico techniques and online resources in computer-aided drug discovery (CADD), for designing or identifying MTDLs against AD. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Physics and Its Interfaces with Medicinal Chemistry and Drug Design

NASA Astrophysics Data System (ADS)

Santos, Ricardo N.; Andricopulo, Adriano D.

2013-08-01

Medicinal chemistry is a multidisciplinary subject that integrates knowledge from a variety of fields of science, including, but not limited to, chemistry, biology, and physics. The area of drug design involves the cooperative work of scientists with a diverse range of backgrounds and technical skills, trying to tackle complex problems using an integration of approaches and methods. One important contribution to this field comes from physics through studies that attempt to identify and quantify the molecular interactions between small molecules (drugs) and biological targets (receptors), such as the forces that govern the interactions, the thermodynamics of the drug-receptor interactions, and so on. In this context, the interfaces of physics, medicinal chemistry, and drug design are of vital importance for the development of drugs that not only have the right chemistry but also the right intermolecular properties to interact at the macromolecular level, providing useful information about the principles and molecular mechanisms underlying the therapeutic action of drugs. This article highlights some of the most important connections between physics and medicinal chemistry in the design of new drugs.

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.

Design and syntheses of mono and multivalent mannosyl-lipoconjugates for targeted liposomal drug delivery.

PubMed

Štimac, Adela; Cvitaš, Jelena TrmĿiĿ; Frkanec, Leo; Vugrek, Oliver; Frkanec, Ruža

2016-09-10

Multivalent mannosyl-lipoconjugates may be of interest for glycosylation of liposomes and targeted drug delivery because the mannose specifically binds to C-type lectin receptors on the particular cells. In this paper syntheses of two types of novel O-mannosides are presented. Conjugates 1 and 2 with a COOH- and NH2-functionalized spacer and the connection to a lysine and FmocNH-PEG-COOH, are described. The coupling reactions of prepared intermediates 6 and 4 with a PEGylated-DSPE or palmitic acid, respectively, are presented. Compounds 5, mono-, 8, di- and 12, tetravalent mannosyl-lipoconjugates, were synthesized. The synthesized compounds were incorporated into liposomes and liposomal preparations featuring exposed mannose units were characterized. Carbohydrate liposomal quartz crystal microbalance based assay has been established for studying carbohydrate-lectin binding. It was demonstrated that liposomes with incorporated mannosyl-lipoconjugates were effectively recognized by Con A and have great potential to be used for targeted liposomal drug delivery systems. Copyright © 2016 Elsevier B.V. All rights reserved.

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 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

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.

Evolutionary and Comparative Genomics to Drive Rational Drug Design, with Particular Focus on Neuropeptide Seven-Transmembrane Receptors.

PubMed

Furlong, Michael; Seong, Jae Young

2017-01-01

Seven transmembrane receptors (7TMRs), also known as G protein-coupled receptors, are popular targets of drug development, particularly 7TMR systems that are activated by peptide ligands. Although many pharmaceutical drugs have been discovered via conventional bulk analysis techniques the increasing availability of structural and evolutionary data are facilitating change to rational, targeted drug design. This article discusses the appeal of neuropeptide-7TMR systems as drug targets and provides an overview of concepts in the evolution of vertebrate genomes and gene families. Subsequently, methods that use evolutionary concepts and comparative analysis techniques to aid in gene discovery, gene function identification, and novel drug design are provided along with case study examples.

Evolutionary and Comparative Genomics to Drive Rational Drug Design, with Particular Focus on Neuropeptide Seven-Transmembrane Receptors

PubMed Central

Furlong, Michael; Seong, Jae Young

2017-01-01

Seven transmembrane receptors (7TMRs), also known as G protein-coupled receptors, are popular targets of drug development, particularly 7TMR systems that are activated by peptide ligands. Although many pharmaceutical drugs have been discovered via conventional bulk analysis techniques the increasing availability of structural and evolutionary data are facilitating change to rational, targeted drug design. This article discusses the appeal of neuropeptide-7TMR systems as drug targets and provides an overview of concepts in the evolution of vertebrate genomes and gene families. Subsequently, methods that use evolutionary concepts and comparative analysis techniques to aid in gene discovery, gene function identification, and novel drug design are provided along with case study examples. PMID:28035082

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

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.

Advances in oral nano-delivery systems for colon targeted drug delivery in inflammatory bowel disease: selective targeting to diseased versus healthy tissue.

PubMed

Hua, Susan; Marks, Ellen; Schneider, Jennifer J; Keely, Simon

2015-07-01

Colon targeted drug delivery is an active area of research for local diseases affecting the colon, as it improves the efficacy of therapeutics and enables localized treatment, which reduces systemic toxicity. Targeted delivery of therapeutics to the colon is particularly advantageous for the treatment of inflammatory bowel disease (IBD), which includes ulcerative colitis and Crohn's disease. Advances in oral drug delivery design have significantly improved the bioavailability of drugs to the colon; however in order for a drug to have therapeutic efficacy during disease, considerations must be made for the altered physiology of the gastrointestinal (GI) tract that is associated with GI inflammation. Nanotechnology has been used in oral dosage formulation design as strategies to further enhance uptake into diseased tissue within the colon. This review will describe some of the physiological challenges faced by orally administered delivery systems in IBD, the important developments in orally administered nano-delivery systems for colon targeting, and the future advances of this research. Inflammatory Bowel Disease (IBD) poses a significant problem for a large number of patients worldwide. Current medical therapy mostly aims at suppressing the active inflammatory episodes. In this review article, the authors described and discussed the various approaches current nano-delivery systems can offer in overcoming the limitations of conventional drug formulations. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Enhanced cellular transport and drug targeting using dendritic nanostructures

NASA Astrophysics Data System (ADS)

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

2003-03-01

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

Emulsomes Meet S-layer Proteins: An Emerging Targeted Drug Delivery System

PubMed Central

Ucisik, Mehmet H.; Sleytr, Uwe B.; Schuster, Bernhard

2015-01-01

Here, the use of emulsomes as a drug delivery system is reviewed and compared with other similar lipidic nanoformulations. In particular, we look at surface modification of emulsomes using S-layer proteins, which are self-assembling proteins that cover the surface of many prokaryotic organisms. It has been shown that covering emulsomes with a crystalline S-layer lattice can protect cells from oxidative stress and membrane damage. In the future, the capability to recrystallize S-layer fusion proteins on lipidic nanoformulations may allow the presentation of binding functions or homing protein domains to achieve highly specific targeted delivery of drug-loaded emulsomes. Besides the discussion on several designs and advantages of composite emulsomes, the success of emulsomes for the delivery of drugs to fight against viral and fungal infections, dermal therapy, cancer, and autoimmunity is summarized. Further research might lead to smart, biocompatible emulsomes, which are able to protect and reduce the side effects caused by the drug, but at the same time are equipped with specific targeting molecules to find the desired site of action. PMID:25697368

Rational, computer-enabled peptide drug design: principles, methods, applications and future directions.

PubMed

Diller, David J; Swanson, Jon; Bayden, Alexander S; Jarosinski, Mark; Audie, Joseph

2015-01-01

Peptides provide promising templates for developing drugs to occupy a middle space between small molecules and antibodies and for targeting 'undruggable' intracellular protein-protein interactions. Importantly, rational or in cerebro design, especially when coupled with validated in silico tools, can be used to efficiently explore chemical space and identify islands of 'drug-like' peptides to satisfy diverse drug discovery program objectives. Here, we consider the underlying principles of and recent advances in rational, computer-enabled peptide drug design. In particular, we consider the impact of basic physicochemical properties, potency and ADME/Tox opportunities and challenges, and recently developed computational tools for enabling rational peptide drug design. Key principles and practices are spotlighted by recent case studies. We close with a hypothetical future case study.

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

PubMed

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

2017-11-01

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

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

PubMed Central

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

2013-01-01

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

Fluid mechanics aspects of magnetic drug targeting.

PubMed

Odenbach, Stefan

2015-10-01

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

Leukocytes as carriers for targeted cancer drug delivery.

PubMed

Mitchell, Michael J; King, Michael R

2015-03-01

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

Engineered Peptides for Applications in Cancer-Targeted Drug Delivery and Tumor Detection.

PubMed

Soudy, R; Byeon, N; Raghuwanshi, Y; Ahmed, S; Lavasanifar, A; Kaur, K

2017-01-01

Cancer-targeting peptides as ligands for targeted delivery of anticancer drugs or drug carriers have the potential to significantly enhance the selectivity and the therapeutic benefit of current chemotherapeutic agents. Identification of tumor-specific biomarkers like integrins, aminopeptidase N, and epidermal growth factor receptor as well as the popularity of phage display techniques along with synthetic combinatorial methods used for peptide design and structure optimization have fueled the advancement and application of peptide ligands for targeted drug delivery and tumor detection in cancer treatment, detection and guided therapy. Although considerable preclinical data have shown remarkable success in the use of tumor targeting peptides, peptides generally suffer from poor pharmacokinetics, enzymatic instability, and weak receptor affinity, and they need further structural modification before successful translation to clinics is possible. The current review gives an overview of the different engineering strategies that have been developed for peptide structure optimization to confer selectivity and stability. We also provide an update on the methods used for peptide ligand identification, and peptide- receptor interactions. Additionally, some applications for the use of peptides in targeted delivery of chemotherapeutics and diagnostics over the past 5 years are summarized. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

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.

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

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.

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

PubMed

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

2016-01-01

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

The Expanding Diversity of Mycobacterium tuberculosis Drug Targets.

PubMed

Wellington, Samantha; Hung, Deborah T

2018-05-11

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

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

PubMed

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

2016-01-01

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

Leukocytes as carriers for targeted cancer drug delivery

PubMed Central

Mitchell, Michael J

2017-01-01

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

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

PubMed

Vilar, Santiago; Hripcsak, George

2016-01-01

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

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

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.

Preparation, Characterization, and Optimization of Folic Acid-Chitosan-Methotrexate Core-Shell Nanoparticles by Box-Behnken Design for Tumor-Targeted Drug Delivery.

PubMed

Naghibi Beidokhti, Hamid Reza; Ghaffarzadegan, Reza; Mirzakhanlouei, Sasan; Ghazizadeh, Leila; Dorkoosh, Farid Abedin

2017-01-01

The objective of this study was to investigate the combined influence of independent variables in the preparation of folic acid-chitosan-methotrexate nanoparticles (FA-Chi-MTX NPs). These NPs were designed and prepared for targeted drug delivery in tumor. The NPs of each batch were prepared by coaxial electrospray atomization method and evaluated for particle size (PS) and particle size distribution (PSD). The independent variables were selected to be concentration of FA-chitosan, ratio of shell solution flow rate to core solution flow rate, and applied voltage. The process design of experiments (DOE) was obtained with three factors in three levels by Design expert software. Box-Behnken design was used to select 15 batches of experiments randomly. The chemical structure of FA-chitosan was examined by FTIR. The NPs of each batch were collected separately, and morphologies of NPs were investigated by field emission scanning electron microscope (FE-SEM). The captured pictures of all batches were analyzed by ImageJ software. Mean PS and PSD were calculated for each batch. Polynomial equation was produced for each response. The FE-SEM results showed the mean diameter of the core-shell NPs was around 304 nm, and nearly 30% of the produced NPs are in the desirable range. Optimum formulations were selected. The validation of DOE optimization results showed errors around 2.5 and 2.3% for PS and PSD, respectively. Moreover, the feasibility of using prepared NPs to target tumor extracellular pH was shown, as drug release was greater in the pH of endosome (acidic medium). Finally, our results proved that FA-Chi-MTX NPs were active against the human epithelial cervical cancer (HeLa) cells.

[Designer drugs in Finland].

PubMed

Tacke, Ulrich; den Hollander, Bjørnar; Simojoki, Kaarlo; Korpi, Esa R; Pihlainen, Katja; Alho, Hannu

2011-01-01

Designer drugs are synthetic psychotropic drugs which are marketed as "legal drugs". Their emergence, rapid spreading and unpredictable effects have challenged the health and substance abuse care. The slow process of classification of an abusable drug has provided too many possibilities for spreading the designer drugs. Once a certain substance receives an illegal drugs classification, dealers and users usually move to another, slightly different molecule that is still legal. In Finland, the Narcotics Act has been amended to the effect that the addition of a new substance to the illegal drug list does not require an amendment to the law.

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.

The design of drugs for HIV and HCV.

PubMed

De Clercq, Erik

2007-12-01

Since the discovery of the human immunodeficiency virus (HIV) in 1983, dramatic progress has been made in the development of novel antiviral drugs. The HIV epidemic fuelled the development of new antiviral drug classes, which are now combined to provide highly active antiretroviral therapies. The need for the treatment of hepatitis C virus (HCV), which was discovered in 1989, has also provided considerable impetus for the development of new classes of antiviral drugs, and future treatment strategies for chronic HCV might involve combination regimens that are analogous to those currently used for HIV. By considering the drug targets in the different stages of the life cycle of these two viruses, this article presents aspects of the history, medicinal chemistry and mechanisms of action of approved and investigational drugs for HIV and HCV, and highlights general lessons learned from anti-HIV-drug design that could be applied to HCV.

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.

Orally active-targeted drug delivery systems for proteins and peptides.

PubMed

Li, Xiuying; Yu, Miaorong; Fan, Weiwei; Gan, Yong; Hovgaard, Lars; Yang, Mingshi

2014-09-01

In the past decade, extensive efforts have been devoted to designing 'active targeted' drug delivery systems (ATDDS) to improve oral absorption of proteins and peptides. Such ATDDS enhance cellular internalization and permeability of proteins and peptides via molecular recognition processes such as ligand-receptor or antigen-antibody interaction, and thus enhance drug absorption. This review focuses on recent advances with orally ATDDS, including ligand-protein conjugates, recombinant ligand-protein fusion proteins and ligand-modified carriers. In addition to traditional intestinal active transport systems of substrates and their corresponding receptors, transporters and carriers, new targets such as intercellular adhesion molecule-1 and β-integrin are also discussed. ATDDS can improve oral absorption of proteins and peptides. However, currently, no clinical studies on ATDDS for proteins and peptides are underway, perhaps due to the complexity and limited knowledge of transport mechanisms. Therefore, more research is warranted to optimize ATDDS efficiency.

Participatory design for drug-drug interaction alerts.

PubMed

Luna, Daniel; Otero, Carlos; Almerares, Alfredo; Stanziola, Enrique; Risk, Marcelo; González Bernaldo de Quirós, Fernán

2015-01-01

The utilization of decision support systems, in the point of care, to alert drug-drug interactions has been shown to improve quality of care. Still, the use of these systems has not been as expected, it is believed, because of the difficulties in their knowledge databases; errors in the generation of the alerts and the lack of a suitable design. This study expands on the development of alerts using participatory design techniques based on user centered design process. This work was undertaken in three stages (inquiry, participatory design and usability testing) it showed that the use of these techniques improves satisfaction, effectiveness and efficiency in an alert system for drug-drug interactions, a fact that was evident in specific situations such as the decrease of errors to meet the specified task, the time, the workload optimization and users overall satisfaction in the system.

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.

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

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.

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

21 CFR 316.23 - Timing of requests for orphan-drug designation; designation of already approved drugs.

Code of Federal Regulations, 2010 CFR

2010-04-01

...) A sponsor may request orphan-drug designation at any time in the drug development process prior to... 21 Food and Drugs 5 2010-04-01 2010-04-01 false Timing of requests for orphan-drug designation..., DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) DRUGS FOR HUMAN USE ORPHAN DRUGS Designation of an Orphan...

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.

‘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.

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

PubMed

Tan, Hepan; Ge, Xiaoxia; Xie, Lei

2013-08-01

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

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

PubMed

Obradovic, Marko; Mrhar, Ales; Kos, Mitja

2009-12-01

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

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

Targeted Vascular Drug Delivery in Cerebral Cancer.

PubMed

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

2016-01-01

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

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

PubMed

Alaimo, Salvatore; Giugno, Rosalba; Pulvirenti, Alfredo

2016-01-01

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

Development In Drug Targeting And Delivery In Cervical Cancer.

PubMed

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

2017-10-09

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

Targeting CYP51 for drug design by the contributions of molecular modeling.

PubMed

Rabelo, Vitor W; Santos, Taísa F; Terra, Luciana; Santana, Marcos V; Castro, Helena C; Rodrigues, Carlos R; Abreu, Paula A

2017-02-01

CYP51 is an enzyme of sterol biosynthesis pathway present in animals, plants, protozoa and fungi. This enzyme is described as an important drug target that is still of interest. Therefore, in this work, we reviewed the structure and function of CYP51 and explored the molecular modeling approaches for the development of new antifungal and antiprotozoans that target this enzyme. Crystallographic structures of CYP51 of some organisms have already been described in the literature, which enable the construction of homology models of other organisms' enzymes and molecular docking studies of new ligands. The binding mode and interactions of some new series of azoles with antifungal or antiprotozoan activities has been studied and showed important residues of the active site. Molecular modeling is an important tool to be explored for the discovery and optimization of CYP51 inhibitors with better activities, pharmacokinetics, and toxicological profiles. © 2016 Société Française de Pharmacologie et de Thérapeutique.

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.

Miscellaneous Topics in Computer-Aided Drug Design: Synthetic Accessibility and GPU Computing, and Other Topics.

PubMed

Fukunishi, Yoshifumi; Mashimo, Tadaaki; Misoo, Kiyotaka; Wakabayashi, Yoshinori; Miyaki, Toshiaki; Ohta, Seiji; Nakamura, Mayu; Ikeda, Kazuyoshi

2016-01-01

Computer-aided drug design is still a state-of-the-art process in medicinal chemistry, and the main topics in this field have been extensively studied and well reviewed. These topics include compound databases, ligand-binding pocket prediction, protein-compound docking, virtual screening, target/off-target prediction, physical property prediction, molecular simulation and pharmacokinetics/pharmacodynamics (PK/PD) prediction. Message and Conclusion: However, there are also a number of secondary or miscellaneous topics that have been less well covered. For example, methods for synthesizing and predicting the synthetic accessibility (SA) of designed compounds are important in practical drug development, and hardware/software resources for performing the computations in computer-aided drug design are crucial. Cloud computing and general purpose graphics processing unit (GPGPU) computing have been used in virtual screening and molecular dynamics simulations. Not surprisingly, there is a growing demand for computer systems which combine these resources. In the present review, we summarize and discuss these various topics of drug design.

Miscellaneous Topics in Computer-Aided Drug Design: Synthetic Accessibility and GPU Computing, and Other Topics

PubMed Central

Fukunishi, Yoshifumi; Mashimo, Tadaaki; Misoo, Kiyotaka; Wakabayashi, Yoshinori; Miyaki, Toshiaki; Ohta, Seiji; Nakamura, Mayu; Ikeda, Kazuyoshi

2016-01-01

Abstract: Background Computer-aided drug design is still a state-of-the-art process in medicinal chemistry, and the main topics in this field have been extensively studied and well reviewed. These topics include compound databases, ligand-binding pocket prediction, protein-compound docking, virtual screening, target/off-target prediction, physical property prediction, molecular simulation and pharmacokinetics/pharmacodynamics (PK/PD) prediction. Message and Conclusion: However, there are also a number of secondary or miscellaneous topics that have been less well covered. For example, methods for synthesizing and predicting the synthetic accessibility (SA) of designed compounds are important in practical drug development, and hardware/software resources for performing the computations in computer-aided drug design are crucial. Cloud computing and general purpose graphics processing unit (GPGPU) computing have been used in virtual screening and molecular dynamics simulations. Not surprisingly, there is a growing demand for computer systems which combine these resources. In the present review, we summarize and discuss these various topics of drug design. PMID:27075578

Process optimization for the preparation of oligomycin-loaded folate-conjugated chitosan nanoparticles as a tumor-targeted drug delivery system using a two-level factorial design method.

PubMed

Zu, Yuangang; Zhao, Qi; Zhao, Xiuhua; Zu, Shuchong; Meng, Li

2011-01-01

Oligomycin-A (Oli-A), an anticancer drug, was loaded to the folate (FA)-conjugated chitosan as a tumor-targeted drug delivery system for the purpose of overcoming the nonspecific targeting characteristics and the hydrophobicity of the compound. The two-level factorial design (2-LFD) was applied to modeling the preparation process, which was composed of five independent variables, namely FA-conjugated chitosan (FA-CS) concentration, Oli-A concentration, sodium tripolyphosphate (TPP) concentration, the mass ratio of FA-CS to TPP, and crosslinking time. The mean particle size (MPS) and the drug loading rate (DLR) of the resulting Oli-loaded FA-CS nanoparticles (FA-Oli-CSNPs) were used as response variables. The interactive effects of the five independent variables on the response variables were studied. The characteristics of the nanoparticles, such as amount of FA conjugation, drug entrapment rate (DER), DLR, surface morphology, and release kinetics properties in vitro were investigated. The FA-Oli-CSNPs with MPS of 182.6 nm, DER of 17.3%, DLR of 58.5%, and zeta potential (ZP) of 24.6 mV were obtained under optimum conditions. The amount of FA conjugation was 45.9 mg/g chitosan. The FA-Oli-CSNPs showed sustained-release characteristics for 576 hours in vitro. The results indicated that FA-Oli-CSNPs obtained as a targeted drug delivery system could be effective in the therapy of leukemia in the future.

Folate biosynthesis pathway: mechanisms and insights into drug design for infectious diseases.

PubMed

Bertacine Dias, Marcio V; Santos, Jademilson C; Libreros-Zúñiga, Gerardo A; Ribeiro, João A; Chavez-Pacheco, Sair M

2018-04-01

Folate pathway is a key target for the development of new drugs against infectious diseases since the discovery of sulfa drugs and trimethoprim. The knowledge about this pathway has increased in the last years and the catalytic mechanism and structures of all enzymes of the pathway are fairly understood. In addition, differences among enzymes from prokaryotes and eukaryotes could be used for the design of specific inhibitors. In this review, we show a panorama of progress that has been achieved within the folate pathway obtained in the last years. We explored the structure and mechanism of enzymes, several genetic features, strategies, and approaches used in the design of new inhibitors that have been used as targets in pathogen chemotherapy.

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.

Design and Fabrication of Multifunctional Sericin Nanoparticles for Tumor Targeting and pH-Responsive Subcellular Delivery of Cancer Chemotherapy Drugs.

PubMed

Huang, Lei; Tao, Kaixiong; Liu, Jia; Qi, Chao; Xu, Luming; Chang, Panpan; Gao, Jinbo; Shuai, Xiaoming; Wang, Guobin; Wang, Zheng; Wang, Lin

2016-03-01

The severe cytotoxicity of cancer chemotherapy drugs limits their clinical applications. Various protein-based nanoparticles with good biocompatibility have been developed for chemotherapy drug delivery in hope of reducing drugs' side effects. Sericin, a natural protein from silk, has no immunogenicity and possesses diverse bioactivities that have prompted sericin's application studies. However, the potential of sericin as a multifunctional nanoscale vehicle for cancer therapy have not been fully explored. Here we report the successful fabrication and characterization of folate-conjugated sericin nanoparticles with cancer-targeting capability for pH-responsive release of doxorubicin (these nanoparticles are termed "FA-SND"). DOX is covalently linked to sericin through pH-sensitive hydrazone bonds that render a pH-triggered release property. The hydrophobicity of DOX and the hydrophilicity of sericin promote the self-assembly of sericin-DOX (SND) nanoconjugates. Folate (FA) is then covalently grafted to SND nanoconjugates as a binding unit for actively targeting cancer cells that overexpress folate receptors. Our characterization study shows that FA-SND nanoparticles exhibit negative surface charges that would reduce nonspecific clearance by circulation. These nanoparticles possess good cytotoxicity and hemocompatibiliy. Acidic environment (pH 5.0) triggers effective DOX release from FA-SND, 5-fold higher than does a neutral condition (pH 7.4). Further, FA-SND nanoparticles specifically target folate-receptor-rich KB cells, and endocytosed into lysosomes, an acidic organelle. The acidic microenvironment of lysosomes promotes a rapid release of DOX to nuclei, producing cancer specific chemo-cytotoxicity. Thus, FA-mediated cancer targeting and lysosomal-acidity promoting DOX release, two sequentially-occurring cellular events triggered by the designed components of FA-SND, form the basis for FA-SND to achieve its localized and intracellular chemo

Designer drugs: the evolving science of drug discovery.

PubMed

Wanke, L A; DuBose, R F

1998-07-01

Drug discovery and design are fundamental to drug development. Until recently, most drugs were discovered through random screening or developed through molecular modification. New technologies are revolutionizing this phase of drug development. Rational drug design, using powerful computers and computational chemistry and employing X-ray crystallography, nuclear magnetic resonance spectroscopy, and three-dimensional quantitative structure activity relationship analysis, is creating highly specific, biologically active molecules by virtual reality modeling. Sophisticated screening technologies are eliminating all but the most active lead compounds. These new technologies promise more efficacious, safe, and cost-effective medications, while minimizing drug development time and maximizing profits.

Thermal treatment of galactose-branched polyelectrolyte microcapsules to improve drug delivery with reserved targetability.

PubMed

Zhang, Fu; Wu, Qi; Liu, Li-Jun; Chen, Zhi-Chun; Lin, Xian-Fu

2008-06-05

A novel multilayered drug delivery system by LbL assembly of galactosylated polyelectrolyte, which is possible to have the potential in hepatic targeting by the presence of galactose residues at the microcapsule's surface, is designed. Thermal treatment was performed on the capsules and a dramatic thermal shrinkage up to 60% decrease of capsule diameter above 50 degrees C was observed. This thermal behavior was then used to manipulate drug loading capacity and release rate. Heating after drug loading could seal the capsule shell, enhancing the loading capacity and reducing the release rate significantly. Excellent affinity between galactose-binding lectin and heated galactose-containing microcapsules were observed, indicating a stable targeting potential even after high temperature elevating up to 90 degrees C.

Computer-aided drug design at Boehringer Ingelheim

NASA Astrophysics Data System (ADS)

Muegge, Ingo; Bergner, Andreas; Kriegl, Jan M.

2017-03-01

Computer-Aided Drug Design (CADD) is an integral part of the drug discovery endeavor at Boehringer Ingelheim (BI). CADD contributes to the evaluation of new therapeutic concepts, identifies small molecule starting points for drug discovery, and develops strategies for optimizing hit and lead compounds. The CADD scientists at BI benefit from the global use and development of both software platforms and computational services. A number of computational techniques developed in-house have significantly changed the way early drug discovery is carried out at BI. In particular, virtual screening in vast chemical spaces, which can be accessed by combinatorial chemistry, has added a new option for the identification of hits in many projects. Recently, a new framework has been implemented allowing fast, interactive predictions of relevant on and off target endpoints and other optimization parameters. In addition to the introduction of this new framework at BI, CADD has been focusing on the enablement of medicinal chemists to independently perform an increasing amount of molecular modeling and design work. This is made possible through the deployment of MOE as a global modeling platform, allowing computational and medicinal chemists to freely share ideas and modeling results. Furthermore, a central communication layer called the computational chemistry framework provides broad access to predictive models and other computational services.

Ebola virus: A gap in drug design and discovery - experimental and computational perspective.

PubMed

Balmith, Marissa; Faya, Mbuso; Soliman, Mahmoud E S

2017-03-01

The Ebola virus, formally known as the Ebola hemorrhagic fever, is an acute viral syndrome causing sporadic outbreaks that have ravaged West Africa. Due to its extreme virulence and highly transmissible nature, Ebola has been classified as a category A bioweapon organism. Only recently have vaccine or drug regimens for the Ebola virus been developed, including Zmapp and peptides. In addition, existing drugs which have been repurposed toward anti-Ebola virus activity have been re-examined and are seen to be promising candidates toward combating Ebola. Drug development involving computational tools has been widely employed toward target-based drug design. Screening large libraries have greatly stimulated research toward effective anti-Ebola virus drug regimens. Current emphasis has been placed on the investigation of host proteins and druggable viral targets. There is a huge gap in the literature regarding guidelines in the discovery of Ebola virus inhibitors, which may be due to the lack of information on the Ebola drug targets, binding sites, and mechanism of action of the virus. This review focuses on Ebola virus inhibitors, drugs which could be repurposed to combat the Ebola virus, computational methods which study drug-target interactions as well as providing further insight into the mode of action of the Ebola virus. © 2016 John Wiley & Sons A/S.

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

PubMed

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

2016-08-01

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

In vivo characteristics of targeted drug-carrying filamentous bacteriophage nanomedicines

PubMed Central

2011-01-01

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

Chemical signatures and new drug targets for gametocytocidal drug development

NASA Astrophysics Data System (ADS)

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

2014-01-01

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

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

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.

MRP4/ABCC4 as a new therapeutic target: meta-analysis to determine cAMP binding sites as a tool for drug design.

PubMed

Yaneff, Agustín; Sahores, Ana; Gomez, Natalia; Carozzo, Alejandro; Shayo, Carina; Davio, Carlos

2017-12-29

MRP4 transports multiple endogenous and exogenous substances and is critical not only for detoxification but also in the homeostasis of several signaling molecules. Its dysregulation has been reported in numerous pathological disorders, thus MRP4 appears as an attractive therapeutic target. However, the efficacy of MRP4 inhibitors is still controversial. The design of specific pharmacological agents with the ability to selectively modulate the activity of this transporter or modify its affinity to certain substrates represents a challenge in current medicine and chemical biology. The first step in the long process of drug rational design is to identify the therapeutic target and characterize the mechanism by which it affects the given pathology. In order to develop a pharmacological agent with high specific activity, the second step is to systematically study the structure of the target and identify all the possible binding sites. Using available homology models and mutagenesis assays, in this review we recapitulate the up-to-date knowledge about MRP structure and aligned amino acid sequences to identify the candidate MRP4 residues where cyclic nucleotides bind. We have also listed the most relevant MRP inhibitors studied to date, considering drug safety and specificity for MRP4 in particular. This metaanalysis platform may serve as a basis for the future development of inhibitors of MRP4 cAMP specific transport. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

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

Targeted drug delivery using genetically engineered diatom biosilica.

PubMed

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

2015-11-10

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

Drug-induced amplification of nanoparticle targeting to tumors

PubMed Central

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

2018-01-01

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

ROCK1 is a potential combinatorial drug target for BRAF mutant melanoma

PubMed Central

Smit, Marjon A; Maddalo, Gianluca; Greig, Kylie; Raaijmakers, Linsey M; Possik, Patricia A; van Breukelen, Bas; Cappadona, Salvatore; Heck, Albert JR; Altelaar, AF Maarten; Peeper, Daniel S

2014-01-01

Treatment of BRAF mutant melanomas with specific BRAF inhibitors leads to tumor remission. However, most patients eventually relapse due to drug resistance. Therefore, we designed an integrated strategy using (phospho)proteomic and functional genomic platforms to identify drug targets whose inhibition sensitizes melanoma cells to BRAF inhibition. We found many proteins to be induced upon PLX4720 (BRAF inhibitor) treatment that are known to be involved in BRAF inhibitor resistance, including FOXD3 and ErbB3. Several proteins were down-regulated, including Rnd3, a negative regulator of ROCK1 kinase. For our genomic approach, we performed two parallel shRNA screens using a kinome library to identify genes whose inhibition sensitizes to BRAF or ERK inhibitor treatment. By integrating our functional genomic and (phospho)proteomic data, we identified ROCK1 as a potential drug target for BRAF mutant melanoma. ROCK1 silencing increased melanoma cell elimination when combined with BRAF or ERK inhibitor treatment. Translating this to a preclinical setting, a ROCK inhibitor showed augmented melanoma cell death upon BRAF or ERK inhibition in vitro. These data merit exploration of ROCK1 as a target in combination with current BRAF mutant melanoma therapies. PMID:25538140

Drug-target interaction prediction from PSSM based evolutionary information.

PubMed

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

2016-01-01

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

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

PubMed

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

2016-12-22

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

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

PubMed

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

2018-04-27

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

Experimental Design for Multi-drug Combination Studies Using Signaling Networks

PubMed Central

Huang, Hengzhen; Fang, Hong-Bin; Tan, Ming T.

2017-01-01

Summary Combinations of multiple drugs are an important approach to maximize the chance for therapeutic success by inhibiting multiple pathways/targets. Analytic methods for studying drug combinations have received increasing attention because major advances in biomedical research have made available large number of potential agents for testing. The preclinical experiment on multi-drug combinations plays a key role in (especially cancer) drug development because of the complex nature of the disease, the need to reduce development time and costs. Despite recent progresses in statistical methods for assessing drug interaction, there is an acute lack of methods for designing experiments on multi-drug combinations. The number of combinations grows exponentially with the number of drugs and dose-levels and it quickly precludes laboratory testing. Utilizing experimental dose-response data of single drugs and a few combinations along with pathway/network information to obtain an estimate of the functional structure of the dose-response relationship in silico, we propose an optimal design that allows exploration of the dose-effect surface with the smallest possible sample size in this paper. The simulation studies show our proposed methods perform well. PMID:28960231

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.

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.

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.

Tumor Targeting and Drug Delivery by Anthrax Toxin.

PubMed

Bachran, Christopher; Leppla, Stephen H

2016-07-01

Anthrax toxin is a potent tripartite protein toxin from Bacillus anthracis. It is one of the two virulence factors and causes the disease anthrax. The receptor-binding component of the toxin, protective antigen, needs to be cleaved by furin-like proteases to be activated and to deliver the enzymatic moieties lethal factor and edema factor to the cytosol of cells. Alteration of the protease cleavage site allows the activation of the toxin selectively in response to the presence of tumor-associated proteases. This initial idea of re-targeting anthrax toxin to tumor cells was further elaborated in recent years and resulted in the design of many modifications of anthrax toxin, which resulted in successful tumor therapy in animal models. These modifications include the combination of different toxin variants that require activation by two different tumor-associated proteases for increased specificity of toxin activation. The anthrax toxin system has proved to be a versatile system for drug delivery of several enzymatic moieties into cells. This highly efficient delivery system has recently been further modified by introducing ubiquitin as a cytosolic cleavage site into lethal factor fusion proteins. This review article describes the latest developments in this field of tumor targeting and drug delivery.

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.

A green approach to dual-drug nanoformulations with targeting and synergistic effects for cancer therapy.

PubMed

Wu, Shichao; Yang, Xiangrui; Lu, Yue; Fan, Zhongxiong; Li, Yang; Jiang, Yuan; Hou, Zhenqing

2017-11-01

Exploration of efficient dual-drug nanohybrids, particularly those with high drug loading, specific targeting property, and long-termed stability, is of highly importance in cancer therapy. A pH-driven coprecipitation was performed in the aqueous phase to obtain a dual-drug nanoformulation, composed of 10-hydroxycamptothecine (HCPT) nanoneedles integrated with an exterior thin layer of the methotrexate (MTX)-chitosan conjugate. The high stability of nanohybrids in water and the targeting property provided by the MTX ingredient function synergistically to the prolonged and sustained drug release property in tumor tissues and the increased cellular uptake. The cytotoxicity test illustrates that dual-drug nanoneedles possess the remarkable killing ability to HeLa cells with the combination index at 0.33 ± 0.07. After cellular internalization, the release of both drug ingredients results in an excellent anticancer activity in vivo with the minimized adverse side effects. Design of a green approach to the carrier-free, dual-drug nanoformulations enables to develop emerging drug delivery systems for cancer diagnosis and treatment.

Pericyte-targeting drug delivery and tissue engineering.

PubMed

Kang, Eunah; Shin, Jong Wook

2016-01-01

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

Targeting efflux pumps to overcome antifungal drug resistance

PubMed Central

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

2016-01-01

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

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

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.

Design, Synthesis and Bio-evaluation of an EphA2-based Targeted Delivery System

PubMed Central

Barile, Elisa; Wang, Si; Das, Swadesh K.; Noberini, Roberta; Dahl, Russell; Stebbins, John L.; Pasquale, Elena B.; Fisher, Paul B.; Pellecchia, Maurizio

2014-01-01

We recently described a new targeted delivery system based on specific EphA2 receptor targeting peptides conjugated with the chemotherapeutic agent paclitaxel. In this manuscript we investigate the chemical determinants responsible for the stability and degradation of these agents in plasma. Introducing modifications in both the peptide and the linker between the peptide and paclitaxel, resulted in drug conjugates that are both long-lived in rat plasma and that markedly reduced tumor size in a prostate cancer xenograft model compared to paclitaxel alone treatment. These studies identify critical rate-limiting degradation sites on the peptide-drug conjugates, enabling the design of agents with increased stability and efficacy. These results provide support for our central hypothesis that peptide-drug conjugates targeting the EphA2 receptor represent an innovative and potentially effective strategy to selectively deliver cytotoxic drugs to cancer cells. PMID:24677792

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.

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.

Designing an intuitive web application for drug discovery scientists.

PubMed

Karamanis, Nikiforos; Pignatelli, Miguel; Carvalho-Silva, Denise; Rowland, Francis; Cham, Jennifer A; Dunham, Ian

2018-06-01

We discuss how we designed the Open Targets Platform (www.targetvalidation.org), an intuitive application for bench scientists working in early drug discovery. To meet the needs of our users, we applied lean user experience (UX) design methods: we started engaging with users very early and carried out research, design and evaluation activities within an iterative development process. We also emphasize the collaborative nature of applying lean UX design, which we believe is a foundation for success in this and many other scientific projects. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Experiments and synthesis of bone-targeting epirubicin with the water-soluble macromolecular drug delivery systems of oxidized-dextran.

PubMed

Yu, Li; Cai, Lin; Hu, Hao; Zhang, Yi

2014-05-01

Epirubicin (EPI) is a broad spectrum antineoplastic drug, commonly used as a chemotherapy method to treat osteosarcoma. However, its application has been limited by many side-effects. Therefore, targeted drug delivery to bone has been the aim of current anti-bone-tumor drug studies. Due to the exceptional affinity of Bisphosphonates (BP) to bone, 1-amino-ethylene-1, 1-dephosphate acid (AEDP) was chosen as the bone targeting moiety for water-soluble macromolecular drug delivery systems of oxidized-dextran (OXD) to transport EPI to bone in this article. The bone targeting drug of AEDP-OXD-EPI was designed for the treatment of malignant bone tumors. The successful conjugation of AEDP-OXD-EPI was confirmed by analysis of FTIR and (1)H-NMR spectra. To study the bone-seeking potential of AEDP-OXD-EPI, an in vitro hydroxyapatite (HAp) binding assay and an in vivo experiment of bone-targeting capacity were established. The effectiveness of AEDP-OXD-EPI was demonstrated by inducing apoptosis and necrosis of MG-63 tumor cell line. The obtained experimental data indicated that AEDP-OXD-EPI is an ideal bone-targeting anti-tumor drug.

Rational optimization of drug-target residence time: Insights from inhibitor binding to the S. aureus FabI enzyme-product complex

PubMed Central

Chang, Andrew; Schiebel, Johannes; Yu, Weixuan; Bommineni, Gopal R.; Pan, Pan; Baxter, Michael V.; Khanna, Avinash; Sotriffer, Christoph A.; Kisker, Caroline; Tonge, Peter J.

2013-01-01

Drug-target kinetics has recently emerged as an especially important facet of the drug discovery process. In particular, prolonged drug-target residence times may confer enhanced efficacy and selectivity in the open in vivo system. However, the lack of accurate kinetic and structural data for series of congeneric compounds hinders the rational design of inhibitors with decreased off-rates. Therefore, we chose the Staphylococcus aureus enoyl-ACP reductase (saFabI) - an important target for the development of new anti-staphylococcal drugs - as a model system to rationalize and optimize the drug-target residence time on a structural basis. Using our new, efficient and widely applicable mechanistically informed kinetic approach, we obtained a full characterization of saFabI inhibition by a series of 20 diphenyl ethers complemented by a collection of 9 saFabI-inhibitor crystal structures. We identified a strong correlation between the affinities of the investigated saFabI diphenyl ether inhibitors and their corresponding residence times, which can be rationalized on a structural basis. Due to its favorable interactions with the enzyme, the residence time of our most potent compound exceeds 10 hours. In addition, we found that affinity and residence time in this system can be significantly enhanced by modifications predictable by a careful consideration of catalysis. Our study provides a blueprint for investigating and prolonging drug-target kinetics and may aid in the rational design of long-residence-time inhibitors targeting the essential saFabI enzyme. PMID:23697754

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.

Designing Novel Nanoformulations Targeting Glutamate Transporter Excitatory Amino Acid Transporter 2: Implications in Treating Drug Addiction.

PubMed

Rao, Pss; Yallapu, Murali M; Sari, Youssef; Fisher, Paul B; Kumar, Santosh

Chronic drug abuse is associated with elevated extracellular glutamate concentration in the brain reward regions. Deficit of glutamate clearance has been identified as a contributing factor that leads to enhanced glutamate concentration following extended drug abuse. Importantly, normalization of glutamate level through induction of glutamate transporter 1 (GLT1)/ excitatory amino acid transporter 2 (EAAT2) expression has been described in several in vivo studies. GLT1 upregulators including ceftriaxone, a beta-lactam antibiotic, have been effective in attenuating drug-seeking and drug-consumption behavior in rodent models. However, potential obstacles toward clinical translation of GLT1 (EAAT2) upregulators as treatment for drug addiction might include poor gastrointestinal absorption, serious peripheral adverse effects, and/or suboptimal CNS concentrations. Given the growing success of nanotechnology in targeting CNS ailments, nanoformulating known GLT1 (EAAT2) upregulators for selective uptake across the blood brain barrier presents an ideal therapeutic approach for treating drug addiction. In this review, we summarize the results obtained with promising GLT1 (EAAT2) inducing compounds in animal models recapitulating drug addiction. Additionally, the various nanoformulations that can be employed for selectively increasing the CNS bioavailability of GLT1 (EAAT2) upregulators are discussed. Finally, the applicability of GLT1 (EAAT2) induction via central delivery of drug-loaded nanoformulations is described.

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

Design, Characterization, and Optimization of Controlled Drug Delivery System Containing Antibiotic Drug/s

PubMed Central

Shelate, Pragna; Dave, Divyang

2016-01-01

The objective of this work was design, characterization, and optimization of controlled drug delivery system containing antibiotic drug/s. Osmotic drug delivery system was chosen as controlled drug delivery system. The porous osmotic pump tablets were designed using Plackett-Burman and Box-Behnken factorial design to find out the best formulation. For screening of three categories of polymers, six independent variables were chosen for Plackett-Burman design. Osmotic agent sodium chloride and microcrystalline cellulose, pore forming agent sodium lauryl sulphate and sucrose, and coating agent ethyl cellulose and cellulose acetate were chosen as independent variables. Optimization of osmotic tablets was done by Box-Behnken design by selecting three independent variables. Osmotic agent sodium chloride, pore forming agent sodium lauryl sulphate, and coating agent cellulose acetate were chosen as independent variables. The result of Plackett-Burman and Box-Behnken design and ANOVA studies revealed that osmotic agent and pore former had significant effect on the drug release up to 12 hr. The observed independent variables were found to be very close to predicted values of most satisfactory formulation which demonstrates the feasibility of the optimization procedure in successful development of porous osmotic pump tablets containing antibiotic drug/s by using sodium chloride, sodium lauryl sulphate, and cellulose acetate as key excipients. PMID:27610247

Inhibitor designing, virtual screening, and docking studies for methyltransferase: A potential target against dengue virus

PubMed Central

Singh, Jagbir; Kumar, Mahesh; Mansuri, Rani; Sahoo, Ganesh Chandra; Deep, Aakash

2016-01-01

Aim: Aim of this work was to design and identify some S-adenosyl-L-homocysteine (SAH) analogs as inhibitors of S-adenosyl-L-methionine-dependent methyltransferase (MTase) protein using computational approaches. Introduction: According to the current scenario the dengue has been a global burden. The people are being killed by dengue virus in an abundant number. Despite of lot of research being going on dengue worldwide, there is no single drug which can kill its virus. This creates an urge for new drug target identification and designing. MTase has been reported as an effective target against dengue virus as it catalyzes an essential step in methylation and capping of viral RNA for viral replication. Materials and Methods: The crystal structure of MTase in complex with SAH was used for designing new analogs of SAH. SAH analogs designed were analyzed on the basis of docking, ADMET, and toxicity analysis done using Discovery Studio 3.5. Results: Seventeen analogs found noncarcinogenic, nonmutagenic, as well as good ADMET properties and good drug-like profile. Conclusion: These SAH analogs, inhibitors of MTase may act as drugs against dengue virus. Further synthesis and biological testing against dengue virus is under observation. PMID:27413346

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

State-of-the-art in design rules for drug delivery platforms: lessons learned from FDA-approved nanomedicines.

PubMed

Dawidczyk, Charlene M; Kim, Chloe; Park, Jea Ho; Russell, Luisa M; Lee, Kwan Hyi; Pomper, Martin G; Searson, Peter C

2014-08-10

The ability to efficiently deliver a drug to a tumor site is dependent on a wide range of physiologically imposed design constraints. Nanotechnology provides the possibility of creating delivery vehicles where these design constraints can be decoupled, allowing new approaches for reducing the unwanted side effects of systemic delivery, increasing targeting efficiency and efficacy. Here we review the design strategies of the two FDA-approved antibody-drug conjugates (Brentuximab vedotin and Trastuzumab emtansine) and the four FDA-approved nanoparticle-based drug delivery platforms (Doxil, DaunoXome, Marqibo, and Abraxane) in the context of the challenges associated with systemic targeted delivery of a drug to a solid tumor. The lessons learned from these nanomedicines provide an important insight into the key challenges associated with the development of new platforms for systemic delivery of anti-cancer drugs. Copyright © 2014 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.

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.

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.

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.

Drug design and discovery: translational biomedical science varies among countries.

PubMed

Weaver, Ian N; Weaver, Donald F

2013-10-01

Drug design and discovery is an innovation process that translates the outcomes of fundamental biomedical research into therapeutics that are ultimately made available to people with medical disorders in many countries throughout the world. To identify which nations succeed, exceed, or fail at the drug design/discovery endeavor--more specifically, which countries, within the context of their national size and wealth, are "pulling their weight" when it comes to developing medications targeting the myriad of diseases that afflict humankind--we compiled and analyzed a comprehensive survey of all new drugs (small molecular entities and biologics) approved annually throughout the world over the 20-year period from 1991 to 2010. Based upon this analysis, we have devised prediction algorithms to ascertain which countries are successful (or not) in contributing to the worldwide need for effective new therapeutics. © 2013 Wiley Periodicals, Inc.

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

Design and development of a multifunctional nano carrier system for imaging, drug delivery, and cell targeting in cancer research

NASA Astrophysics Data System (ADS)

Cho, Hoon-Sung

There has been an increasing need in the last decade for early diagnosis and treatment of cancer prior to the tumor mass becoming evident as anatomical anomaly. A major challenge in cancer diagnosis is to distinguish cancer cells from the surrounding, normal tissue. For early cancer diagnosis and treatment, a nano carrier system was designed and developed with key components uniquely structured according to biomedical and clinical requirements: targeting, drug storage capabilities, fluorescent emissions near the infrared range for in vivo imaging, and magnetic hyperthermia. For in vivo imaging, quantum dots with emissions near infrared range (˜800 nm) were conjugated onto the surface of carbon nanotubes and nanospheres consisting of a spherical polystyrene matrix (˜100 nm) and high fraction of superparamagnetic Fe3O4 nanoparticles (˜10 nm) embedded. The QDs on these nano carriers exhibited intense visible emissions using fluorescent spectroscopy and successfully facilitated in vivo soft tissue imaging in mice. For drug storage, the chemotherapeutic agent, paclitaxel (PTX) was loaded onto the surfaces of these nano-carriers by using a layer of biodegradable poly(lactic-co-glycolic acid) (PLGA). A cell-based cytotoxicity assay was employed to verify successful loading of pharmacologically active drug, PTX. Cell viability of human, metastatic PC3mm2 prostate cancer cells was assessed in the presence and absence of various nano-carrier populations using the MTT assay. For hyperthermia, Fe3O 4 nanoparticles were conjugated onto the surfaces of carbon nanotubes (CNT) and embedded into the nanospheres. Magnetization measurements showed nearly reversible hysteresis curves from the Fe3O4-conjugated CNTs and the magnetic nanospheres (MNS). Application of an alternating electromagnetic field effectively induced heating the solution of the Fe3O 4-conjugated CNTs and the magnetic nanospheres (MNS) into temperature ranges (up to 55ºC) suitable for therapeutic hyperthermia

Design attributes of long-circulating polymeric drug delivery vehicles.

PubMed

Beck-Broichsitter, Moritz; Nicolas, Julien; Couvreur, Patrick

2015-11-01

Following systemic administration polymeric drug delivery vehicles allow for a controlled and targeted release of the encapsulated medication at the desired site of action. For an elevated and organ specific accumulation of their cargo, nanocarriers need to avoid opsonization, activation of the complement system and uptake by macrophages of the mononuclear phagocyte system. In this respect, camouflaged vehicles revealed a delayed elimination from systemic circulation and an improved target organ deposition. For instance, a steric shielding of the carrier surface by poly(ethylene glycol) substantially decreased interactions with the biological environment. However, recent studies disclosed possible deficits of this approach, where most notably, poly(ethylene glycol)-modified drug delivery vehicles caused significant immune responses. At present, identification of novel potential carrier coating strategies facilitating negligible immune reactions is an emerging field of interest in drug delivery research. Moreover, physical carrier properties including geometry and elasticity seem to be very promising design attributes to surpass numerous biological barriers, in order to improve the efficacy of the delivered medication. Copyright © 2015 Elsevier B.V. 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-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

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