WorldWideScience

Sample records for model protein drug

  1. Elastic-contractile model proteins: Physical chemistry, protein function and drug design and delivery.

    Science.gov (United States)

    Urry, Dan W; Urry, Kelley D; Szaflarski, Witold; Nowicki, Michal

    2010-12-30

    This review presents the structure and physico-chemical properties of ECMPs, elastic-contractile model proteins using sparse design modifications of elastic (GVGVP)(n); it describes the capacity of ECMP to perform the energy conversions that sustain living organisms; it arrives at the hydration thermodynamics of ECMP in terms of the change in Gibbs free energy of hydrophobic association, ΔG(HA), and the apolar-polar repulsive free energy of hydration, ΔG(ap); it applies ΔG(HA), ΔG(ap), and the nature of elasticity to describe the function of basic diverse proteins, namely - the F₁-motor of ATP synthase, Complex III of mitochondria, the KscA potassium-channel, and the molecular chaperonin, GroEL/ES; it applies ΔG(HA) and ΔG(ap) to describe the function of ABC exporter proteins that confer multi-drug resistance (MDR) on micro-organisms and human carcinomas and suggests drug modifications with which to overcome MDR. Using ECMP, means are demonstrated, for quantifying drug hydrophobicity with which to combat MDR and for preparing ECMP drug delivery nanoparticles, ECMPddnp, decorated with synthetic antigen-binding fragments, Fab1 and Fab2, with which to target specific up-regulated receptors, characteristic of human carcinoma cells, for binding and localized drug release. Copyright © 2010 Elsevier B.V. All rights reserved.

  2. Utility of population pharmacokinetic modeling in the assessment of therapeutic protein-drug interactions.

    Science.gov (United States)

    Chow, Andrew T; Earp, Justin C; Gupta, Manish; Hanley, William; Hu, Chuanpu; Wang, Diane D; Zajic, Stefan; Zhu, Min

    2014-05-01

    Assessment of pharmacokinetic (PK) based drug-drug interactions (DDI) is essential for ensuring patient safety and drug efficacy. With the substantial increase in therapeutic proteins (TP) entering the market and drug development, evaluation of TP-drug interaction (TPDI) has become increasingly important. Unlike for small molecule (e.g., chemical-based) drugs, conducting TPDI studies often presents logistical challenges, while the population PK (PPK) modeling may be a viable approach dealing with the issues. A working group was formed with members from the pharmaceutical industry and the FDA to assess the utility of PPK-based TPDI assessment including study designs, data analysis methods, and implementation strategy. This paper summarizes key issues for consideration as well as a proposed strategy with focuses on (1) PPK approach for exploratory assessment; (2) PPK approach for confirmatory assessment; (3) importance of data quality; (4) implementation strategy; and (5) potential regulatory implications. Advantages and limitations of the approach are also discussed.

  3. Predicting Drug Extraction in the Human Gut Wall: Assessing Contributions from Drug Metabolizing Enzymes and Transporter Proteins using Preclinical Models.

    Science.gov (United States)

    Peters, Sheila Annie; Jones, Christopher R; Ungell, Anna-Lena; Hatley, Oliver J D

    2016-06-01

    Intestinal metabolism can limit oral bioavailability of drugs and increase the risk of drug interactions. It is therefore important to be able to predict and quantify it in drug discovery and early development. In recent years, a plethora of models-in vivo, in situ and in vitro-have been discussed in the literature. The primary objective of this review is to summarize the current knowledge in the quantitative prediction of gut-wall metabolism. As well as discussing the successes of current models for intestinal metabolism, the challenges in the establishment of good preclinical models are highlighted, including species differences in the isoforms; regional abundances and activities of drug metabolizing enzymes; the interplay of enzyme-transporter proteins; and lack of knowledge on enzyme abundances and availability of empirical scaling factors. Due to its broad specificity and high abundance in the intestine, CYP3A is the enzyme that is frequently implicated in human gut metabolism and is therefore the major focus of this review. A strategy to assess the impact of gut wall metabolism on oral bioavailability during drug discovery and early development phases is presented. Current gaps in the mechanistic understanding and the prediction of gut metabolism are highlighted, with suggestions on how they can be overcome in the future.

  4. Label-free detection of protein molecules secreted from an organ-on-a-chip model for drug toxicity assays

    Science.gov (United States)

    Morales, Andres W.; Zhang, Yu S.; Aleman, Julio; Alerasool, Parissa; Dokmeci, Mehmet R.; Khademhosseini, Ali; Ye, Jing Yong

    2016-03-01

    Clinical attrition is about 30% from failure of drug candidates due to toxic side effects, increasing the drug development costs significantly and slowing down the drug discovery process. This partly originates from the fact that the animal models do not accurately represent human physiology. Hence there is a clear unmet need for developing drug toxicity assays using human-based models that are complementary to traditional animal models before starting expensive clinical trials. Organ-on-a-chip techniques developed in recent years have generated a variety of human organ models mimicking different human physiological conditions. However, it is extremely challenging to monitor the transient and long-term response of the organ models to drug treatments during drug toxicity tests. First, when an organ-on-a-chip model interacts with drugs, a certain amount of protein molecules may be released into the medium due to certain drug effects, but the amount of the protein molecules is limited, since the organ tissue grown inside microfluidic bioreactors have minimum volume. Second, traditional fluorescence techniques cannot be utilized for real-time monitoring of the concentration of the protein molecules, because the protein molecules are continuously secreted from the tissue and it is practically impossible to achieve fluorescence labeling in the dynamically changing environment. Therefore, direct measurements of the secreted protein molecules with a label-free approach is strongly desired for organs-on-a-chip applications. In this paper, we report the development of a photonic crystal-based biosensor for label-free assays of secreted protein molecules from a liver-on-a-chip model. Ultrahigh detection sensitivity and specificity have been demonstrated.

  5. A physiologically based pharmacokinetic model to predict the pharmacokinetics of highly protein-bound drugs and the impact of errors in plasma protein binding.

    Science.gov (United States)

    Ye, Min; Nagar, Swati; Korzekwa, Ken

    2016-04-01

    Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data were often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding and the blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate the model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for the terminal elimination half-life (t1/2 , 100% of drugs), peak plasma concentration (Cmax , 100%), area under the plasma concentration-time curve (AUC0-t , 95.4%), clearance (CLh , 95.4%), mean residence time (MRT, 95.4%) and steady state volume (Vss , 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. Copyright © 2016 John Wiley & Sons, Ltd.

  6. Supplementary Material for: Mycobacterium tuberculosis whole genome sequencing and protein structure modelling provides insights into anti-tuberculosis drug resistance

    KAUST Repository

    Phelan, Jody

    2016-01-01

    Abstract Background Combating the spread of drug resistant tuberculosis is a global health priority. Whole genome association studies are being applied to identify genetic determinants of resistance to anti-tuberculosis drugs. Protein structure and interaction modelling are used to understand the functional effects of putative mutations and provide insight into the molecular mechanisms leading to resistance. Methods To investigate the potential utility of these approaches, we analysed the genomes of 144 Mycobacterium tuberculosis clinical isolates from The Special Programme for Research and Training in Tropical Diseases (TDR) collection sourced from 20 countries in four continents. A genome-wide approach was applied to 127 isolates to identify polymorphisms associated with minimum inhibitory concentrations for first-line anti-tuberculosis drugs. In addition, the effect of identified candidate mutations on protein stability and interactions was assessed quantitatively with well-established computational methods. Results The analysis revealed that mutations in the genes rpoB (rifampicin), katG (isoniazid), inhA-promoter (isoniazid), rpsL (streptomycin) and embB (ethambutol) were responsible for the majority of resistance observed. A subset of the mutations identified in rpoB and katG were predicted to affect protein stability. Further, a strong direct correlation was observed between the minimum inhibitory concentration values and the distance of the mutated residues in the three-dimensional structures of rpoB and katG to their respective drugs binding sites. Conclusions Using the TDR resource, we demonstrate the usefulness of whole genome association and convergent evolution approaches to detect known and potentially novel mutations associated with drug resistance. Further, protein structural modelling could provide a means of predicting the impact of polymorphisms on drug efficacy in the absence of phenotypic data. These approaches could ultimately lead to novel

  7. Mycobacterium tuberculosis whole genome sequencing and protein structure modelling provides insights into anti-tuberculosis drug resistance

    KAUST Repository

    Phelan, Jody

    2016-03-23

    Background Combating the spread of drug resistant tuberculosis is a global health priority. Whole genome association studies are being applied to identify genetic determinants of resistance to anti-tuberculosis drugs. Protein structure and interaction modelling are used to understand the functional effects of putative mutations and provide insight into the molecular mechanisms leading to resistance. Methods To investigate the potential utility of these approaches, we analysed the genomes of 144 Mycobacterium tuberculosis clinical isolates from The Special Programme for Research and Training in Tropical Diseases (TDR) collection sourced from 20 countries in four continents. A genome-wide approach was applied to 127 isolates to identify polymorphisms associated with minimum inhibitory concentrations for first-line anti-tuberculosis drugs. In addition, the effect of identified candidate mutations on protein stability and interactions was assessed quantitatively with well-established computational methods. Results The analysis revealed that mutations in the genes rpoB (rifampicin), katG (isoniazid), inhA-promoter (isoniazid), rpsL (streptomycin) and embB (ethambutol) were responsible for the majority of resistance observed. A subset of the mutations identified in rpoB and katG were predicted to affect protein stability. Further, a strong direct correlation was observed between the minimum inhibitory concentration values and the distance of the mutated residues in the three-dimensional structures of rpoB and katG to their respective drugs binding sites. Conclusions Using the TDR resource, we demonstrate the usefulness of whole genome association and convergent evolution approaches to detect known and potentially novel mutations associated with drug resistance. Further, protein structural modelling could provide a means of predicting the impact of polymorphisms on drug efficacy in the absence of phenotypic data. These approaches could ultimately lead to novel resistance

  8. Protein-protein interactions as drug targets.

    Science.gov (United States)

    Skwarczynska, Malgorzata; Ottmann, Christian

    2015-01-01

    Modulation of protein-protein interactions (PPIs) is becoming increasingly important in drug discovery and chemical biology. While a few years ago this 'target class' was deemed to be largely undruggable an impressing number of publications and success stories now show that targeting PPIs with small, drug-like molecules indeed is a feasible approach. Here, we summarize the current state of small-molecule inhibition and stabilization of PPIs and review the active molecules from a structural and medicinal chemistry angle, especially focusing on the key examples of iNOS, LFA-1 and 14-3-3.

  9. Ligand efficiency-based support vector regression models for predicting bioactivities of ligands to drug target proteins.

    Science.gov (United States)

    Sugaya, Nobuyoshi

    2014-10-27

    The concept of ligand efficiency (LE) indices is widely accepted throughout the drug design community and is frequently used in a retrospective manner in the process of drug development. For example, LE indices are used to investigate LE optimization processes of already-approved drugs and to re-evaluate hit compounds obtained from structure-based virtual screening methods and/or high-throughput experimental assays. However, LE indices could also be applied in a prospective manner to explore drug candidates. Here, we describe the construction of machine learning-based regression models in which LE indices are adopted as an end point and show that LE-based regression models can outperform regression models based on pIC50 values. In addition to pIC50 values traditionally used in machine learning studies based on chemogenomics data, three representative LE indices (ligand lipophilicity efficiency (LLE), binding efficiency index (BEI), and surface efficiency index (SEI)) were adopted, then used to create four types of training data. We constructed regression models by applying a support vector regression (SVR) method to the training data. In cross-validation tests of the SVR models, the LE-based SVR models showed higher correlations between the observed and predicted values than the pIC50-based models. Application tests to new data displayed that, generally, the predictive performance of SVR models follows the order SEI > BEI > LLE > pIC50. Close examination of the distributions of the activity values (pIC50, LLE, BEI, and SEI) in the training and validation data implied that the performance order of the SVR models may be ascribed to the much higher diversity of the LE-based training and validation data. In the application tests, the LE-based SVR models can offer better predictive performance of compound-protein pairs with a wider range of ligand potencies than the pIC50-based models. This finding strongly suggests that LE-based SVR models are better than pIC50-based

  10. New potential nonsteroidal anti-inflammatory drugs with antileukotrienic effects: influence on model proteins with catalytic activity.

    Science.gov (United States)

    Netopilová, Miloslava; Drsata, Jaroslav; Beránek, Martin; Palicka, Vladimír

    2002-01-01

    Unspecific and side effects caused by interaction with proteins belong to common problems of many structures synthesized as potential medicaments. Possible in vitro interactions with proteins of a group of phenylsulfonyl benzoic acid derivatives (VUFB 19363, 19369, 19370, 19371, and 19760) as new potential anti-inflammatory compounds with anti-leukotrienic activities were studied in the present work. Three purified enzymes were used as model proteins with catalytic activities: Pig heart aspartate aminotransferase (AST, EC 2.6.1.1), alanine aminotransferase (ALT, EC 2.6.1.2), and glutamate decarboxylase (GAD, EC 4.1.1.15) from E. coli. Catalytic activities during incubation of individual compounds (6 x 10(-5) M solution to 5 x 10(-2) M suspension) at 37 degrees C with enzymes served as criteria of stability and function of the proteins. No immediate influence of any compound studied on enzyme activities was found. Aminotransferase activities were not affected even during incubation up to 20 d. In the case of GAD, the compounds VUFB 19369, 19370, 19371, and 19760 had stabilizing influence on GAD activity during incubation at enzyme concentrations of 11.25 and 5.62 mg prot/l. The lack of an immediate effect of compounds and the stability of enzymes during incubation them are favorable and support the prospective of the compounds as potential drugs.

  11. Development and validation of four Leishmania species constitutively expressing GFP protein. A model for drug discovery and disease pathogenesis studies.

    Science.gov (United States)

    Patel, Asha Parbhu; Deacon, Andrew; Getti, Giulia

    2014-04-01

    Green fluorescent protein (GFP)-parasite transfectants have been widely used as a tool for studying disease pathogenesis in several protozoan models and their application in drug screening assays has increased rapidly. In the past decade, the expression of GFP has been established in several Leishmania species, mostly for in vitro studies. The current work reports generation of four transgenic parasites constitutively expressing GFP (Leishmania mexicana, Leishmania aethiopica, Leishmania tropica and Leishmania major) and their validation as a representative model of infection. This is the first report where stable expression of GFP has been achieved in L. aethiopica and L. tropica. Integration of GFP was accomplished through homologous recombination of the expression construct, pRib1.2αNEOαGFP downstream of the 18S rRNA promoter in all species. A homogeneous and high level expression of GFP was detected in both the promastigote and the intracellular amastigote stages. All transgenic species showed the same growth pattern, ability to infect mammalian host cells and sensitivity to reference drugs as their wild type counterparts. All four transgenic Leishmania are confirmed as models for in vitro and possibly in vivo infections and represent an ideal tool for medium throughput testing of compound libraries.

  12. Towards structure-based protein drug design.

    Science.gov (United States)

    Zhang, Changsheng; Lai, Luhua

    2011-10-01

    Structure-based drug design for chemical molecules has been widely used in drug discovery in the last 30 years. Many successful applications have been reported, especially in the field of virtual screening based on molecular docking. Recently, there has been much progress in fragment-based as well as de novo drug discovery. As many protein-protein interactions can be used as key targets for drug design, one of the solutions is to design protein drugs based directly on the protein complexes or the target structure. Compared with protein-ligand interactions, protein-protein interactions are more complicated and present more challenges for design. Over the last decade, both sampling efficiency and scoring accuracy of protein-protein docking have increased significantly. We have developed several strategies for structure-based protein drug design. A grafting strategy for key interaction residues has been developed and successfully applied in designing erythropoietin receptor-binding proteins. Similarly to small-molecule design, we also tested de novo protein-binder design and a virtual screen of protein binders using protein-protein docking calculations. In comparison with the development of structure-based small-molecule drug design, we believe that structure-based protein drug design has come of age.

  13. Impact of hyperlipidemia on plasma protein binding and hepatic drug transporter and metabolic enzyme regulation in a rat model of gestational diabetes.

    Science.gov (United States)

    Anger, Gregory J; Piquette-Miller, Micheline

    2010-07-01

    It is currently unknown whether gestational diabetes mellitus (GDM), a prevalent obstetrical complication, compounds the changes in drug disposition that occur naturally in pregnancy. Hyperlipidemia occurs in GDM. Using a rat model of GDM, we determined whether excess lipids compete with drugs for plasma protein binding. Because lipids activate nuclear receptors that regulate drug transporters and metabolic enzymes, we used proteome analysis to determine whether hyperlipidemia indirectly leads to the dysregulation of these proteins in the liver. GDM was induced on gestational day 6 (GD6) via streptozotocin injection. Controls received either vehicle alone or streptozotocin with subsequent insulin treatment. Liver and plasma were collected on GD20. Glyburide and saquinavir protein binding was determined by ultrafiltration, and an established solvent method was used for plasma delipidation. Proteomics analysis was performed by using isobaric tags for relative and absolute quantitation methodology with membrane-enriched hepatic protein samples. Relative to controls, GDM rat plasma contained more cholesterol and triglycerides. Plasma protein binding of glyburide and saquinavir was decreased in GDM. Delipidation normalized protein binding in GDM plasma. Proteins linked to lipid metabolism were strongly affected in the GDM proteomics data set, with prohyperlipidemic and antihyperlipidemic changes observed, and formed networks that implicated several nuclear receptors. Up-regulation of drug transporters and metabolic enzymes was observed (e.g., multidrug resistance 1/2, CYP2A1, CYP2B9, and CYP2D3). In this study, GDM-induced hyperlipidemia decreased protein binding and was associated with drug transporter and metabolic enzyme up-regulation in the liver. Both of these findings could change drug disposition in affected pregnancies, compounding changes associated with pregnancy itself.

  14. Characterization of particulate drug delivery systems for oral delivery of Peptide and protein drugs

    DEFF Research Database (Denmark)

    Christophersen, Philip Carsten; Fano, Mathias; Saaby, Lasse;

    2015-01-01

    are summarized. Additionally, the paper provides an overview of recent studies on characterization of solid drug carriers for peptide/protein drugs, drug distribution in particles, drug release and stability in simulated GI fluids, as well as the absorption of peptide/protein drugs in cell-based models. The use......Oral drug delivery is a preferred route because of good patient compliance. However, most peptide/ protein drugs are delivered via parenteral routes because of the absorption barriers in the gastrointestinal (GI) tract such as enzymatic degradation by proteases and low permeability acrossthe...... biological membranes. To overcome these barriers, different formulation strategies for oral delivery of biomacromolecules have been proposed, including lipid based formulations and polymer-based particulate drug delivery systems (DDS). The aim of this review is to summarize the existing knowledge about oral...

  15. Protein-Based Drug-Delivery Materials

    Directory of Open Access Journals (Sweden)

    Dave Jao

    2017-05-01

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

  16. Recent advances in (therapeutic protein) drug development

    Science.gov (United States)

    Lagassé, H.A. Daniel; Alexaki, Aikaterini; Simhadri, Vijaya L.; Katagiri, Nobuko H.; Jankowski, Wojciech; Sauna, Zuben E.; Kimchi-Sarfaty, Chava

    2017-01-01

    Therapeutic protein drugs are an important class of medicines serving patients most in need of novel therapies. Recently approved recombinant protein therapeutics have been developed to treat a wide variety of clinical indications, including cancers, autoimmunity/inflammation, exposure to infectious agents, and genetic disorders. The latest advances in protein-engineering technologies have allowed drug developers and manufacturers to fine-tune and exploit desirable functional characteristics of proteins of interest while maintaining (and in some cases enhancing) product safety or efficacy or both. In this review, we highlight the emerging trends and approaches in protein drug development by using examples of therapeutic proteins approved by the U.S. Food and Drug Administration over the previous five years (2011–2016, namely January 1, 2011, through August 31, 2016). PMID:28232867

  17. Drug Target Protein-Protein Interaction Networks: A Systematic Perspective

    Directory of Open Access Journals (Sweden)

    Yanghe Feng

    2017-01-01

    Full Text Available 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.

  18. Drug models of schizophrenia

    Science.gov (United States)

    Steeds, Hannah; Carhart-Harris, Robin L.

    2015-01-01

    Schizophrenia is a complex mental health disorder with positive, negative and cognitive symptom domains. Approximately one third of patients are resistant to currently available medication. New therapeutic targets and a better understanding of the basic biological processes that drive pathogenesis are needed in order to develop therapies that will improve quality of life for these patients. Several drugs that act on neurotransmitter systems in the brain have been suggested to model aspects of schizophrenia in animals and in man. In this paper, we selectively review findings from dopaminergic, glutamatergic, serotonergic, cannabinoid, GABA, cholinergic and kappa opioid pharmacological drug models to evaluate their similarity to schizophrenia. Understanding the interactions between these different neurotransmitter systems and their relationship with symptoms will be an important step towards building a coherent hypothesis for the pathogenesis of schizophrenia. PMID:25653831

  19. Properties of protein drug target classes.

    Directory of Open Access Journals (Sweden)

    Simon C Bull

    Full Text Available 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.

  20. QSAR AND PHARMACOPHORE MODELING BASED DRUG DESIGNING FOR SPLEEN TYROSINE KINASE (SYK PROTEIN FOR HUMAN USING ACCELRYS DISCOVERY STUDIO SOFTWARE IN LINUX SERVER

    Directory of Open Access Journals (Sweden)

    Kuldeep Sahu

    2013-11-01

    Full Text Available From this current research, Syk (spleen tyrosine kinase protein and gene information is analyzed by different genomics, proteomics tools & databases. One crystal ligand 4DFL was collected from protein data bank (pdb. From different literature review 131 syk protein inhibitors were collected. Molecular modeling of these 131 molecules was done through Accelrys discovery studio (ADS. Choose appropriate force-field & minimization (Smart, Stephent Descent, and Conjugate Gradient according to selected molecules. Then collected crystal ligand is purified by protein purification method and used appropriate conformation (BEST, FAST, and CAESAR. Docking methods were analyzed with protein, crystal ligand and similar inhibitors to know the best protein-ligand interaction. Pharmacophore research is done through HIPHOP and HYPOGEN method. Protein with final compound docking method is done after completion of virtual screening method. Pharmacophore research with final molecule was done. Quantitative structure activity relationship (qsar method is analyzed to know the correlation between the above selective structures. From virtual screening method, best and final compound is analyzed. So, final molecule can be a drug molecule for SYK protein abnormality diseases. However, the scope for fine tuning and optimizing this potent class of syK inhibitors could lead to the generation of new therapeutic agents.

  1. Computational modeling-based discovery of novel classes of anti-inflammatory drugs that target lanthionine synthetase C-like protein 2.

    Directory of Open Access Journals (Sweden)

    Pinyi Lu

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

  2. Protective effect of geranylgeranylacetone, an inducer of heat shock protein 70, against drug-induced lung injury/fibrosis in an animal model

    Directory of Open Access Journals (Sweden)

    Hasegawa Yoshinori

    2009-09-01

    Full Text Available Abstract Background To determine whether oral administration of geranylgeranylacetone (GGA, a nontoxic anti-ulcer drug that is an inducer of heat shock protein (HSP 70, protects against drug-induced lung injury/fibrosis in vivo. Methods We used a bleomycin (BLM-induced lung fibrosis model in which mice were treated with oral 600 mg/kg of GGA before and after BLM administration. Inflammation and fibrosis were evaluated by histological scoring, hydroxyproline content in the lung and inflammatory cell count, and quantification by ELISA of macrophage inflammatory protein-2 (MIP-2 in bronchoalveolar lavage fluid. Apoptosis was evaluated by the TUNEL method. The induction of HSP70 in the lung was examined with western blot analysis and its localization was determined by immunohistochemistry. Results We confirmed the presence of inflammation and fibrosis in the BLM-induced lung injury model and induction of HSP70 by oral administration of GGA. GGA prevented apoptosis of cellular constituents of lung tissue, such as epithelial cells, most likely related to the de novo induction of HSP70 in the lungs. GGA-treated mice also showed less fibrosis of the lungs, associated with the findings of suppression of both production of MIP-2 and inflammatory cell accumulation in the injured lung, compared with vehicle-treated mice. Conclusion GGA had a protective effect on drug-induced lung injury/fibrosis. Disease-modifying antirheumatic drugs such as methotrexate, which are indispensable for the treatment of rheumatoid arthritis, often cause interstitial lung diseases, an adverse event that currently cannot be prevented. Clinical use of GGA for drug-induced pulmonary fibrosis might be considered in the future.

  3. Protein Structure Network-based Drug Design.

    Science.gov (United States)

    Liang, Zhongjie; Hu, Guang

    2016-01-01

    Although structure-based drug design (SBDD) has become an indispensable tool in drug discovery for a long time, it continues to pose major challenges to date. With the advancement of "omics" techniques, systems biology has enriched SBDD into a new era, called polypharmacology, in which multi-targets drug or drug combination is designed to fight complex diseases. As a preliminary tool in systems biology, protein structure networks (PSNs) treat a protein as a set of residues linked by edges corresponding to the intramolecular interactions existing in folded structures between the residues. The PSN offers a computationally efficient tool to study the structure and function of proteins, and thus may facilitate structurebased drug design. Herein, we provide an overview of recent advances in PSNs, from predicting functionally important residues, to charactering protein-protein interactions and allosteric communication paths. Furthermore, we discuss potential pharmacological applications of PSN concepts and tools, and highlight the application to two families of drug targets, GPCRs and Hsp90. Although the application of PSNs as a framework for computer-aided drug discovery has been limited to date, we put forward the potential utility value in the near future and propose the PSNs could also serve as a new tool for polypharmacology research.

  4. Protein chemical synthesis in drug discovery.

    Science.gov (United States)

    Liu, Fa; Mayer, John P

    2015-01-01

    The discovery of novel therapeutics to combat human disease has traditionally been among the most important goals of research chemists. After a century of innovation, state-of-the-art chemical protein synthesis is now capable of efficiently assembling proteins of up to several hundred residues in length from individual amino acids. By virtue of its unique ability to incorporate non-native structural elements, chemical protein synthesis has been seminal in the recent development of several novel drug discovery technologies. In this chapter, we review the key advances in peptide and protein chemistry which have enabled our current synthetic capabilities. We also discuss the synthesis of D-proteins and their applications in mirror image phage-display and racemic protein crystallography, the synthesis of enzymes for structure-based drug discovery, and the direct synthesis of homogenous protein pharmaceuticals.

  5. Targeted Delivery of Protein Drugs by Nanocarriers

    Directory of Open Access Journals (Sweden)

    Antonella Battisti

    2010-03-01

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

  6. From Protein Communication to Drug Discovery.

    Science.gov (United States)

    Persico, Marco; Di Dato, Antonio; Orteca, Nausicaa; Fattorusso, Caterina; Novellino, Ettore; Andreoli, Mirko; Ferlini, Cristiano

    2015-01-01

    The majority of functionally important biological processes are regulated by allosteric communication within individual proteins and across protein complexes. The proteins controlling these communication networks respond to changes in the cellular environment by switching between different conformational states. Targeting the interface residues mediating these processes through the rational identification of molecules modulating or mimicking their effects holds great therapeutic potential. Protein-protein interactions (PPIs) have shown to have a high degree of plasticity since they occur through small regions, called hot spots, which are included in binding surfaces or in binding clefts of the proteins and are characterized by a high degree of complementarity. This prompted several researchers to compare the protein structure to human grammar proposing terms like "protein language". The decoding of this language represent a new paradigm not only to clarify the dynamics of many biological processes but also to improve the opportunities in drug discovery. In this review, we try to give an overview on intra-molecular and inter-molecular protein communication mechanisms describing the protein interaction domains (PIDs) and short linear motifs (SLiMs), which delineate the authentic syntactic and semantic units in a protein. Moreover, we illustrate some novel approaches performed on natural compounds and on synthetic derivatives aimed at developing new classes of potential drugs able to interfere with intra-molecular and inter-molecular protein communication.

  7. [Lyophilisation of protein-based drugs].

    Science.gov (United States)

    Murányi, Andrej; Vitková, Mária

    2014-10-01

    Lyophilisation is a well-established method for drying of various substances with a wide range of applications in the pharmaceutical area. During the last decade its relevance increases with a number of therapeutically used proteins. A sensitive protein drug may undergo several changes, like unfolding and loss of activity due to various stresses during the lyophilisation process. Understanding of these processes (freezing, primary drying, secondary drying) is fundamental for manufacturing of a drug product with desired properties, namely its safety and efficacy. In order to reduce costs and increase the quality, new technologies are being rapidly developed and established in industrial lyophilisation (e.g. process analytical technologies, control nucleation techniques).

  8. Modeling complexes of modeled proteins.

    Science.gov (United States)

    Anishchenko, Ivan; Kundrotas, Petras J; Vakser, Ilya A

    2017-03-01

    Structural characterization of proteins is essential for understanding life processes at the molecular level. However, only a fraction of known proteins have experimentally determined structures. This fraction is even smaller for protein-protein complexes. Thus, structural modeling of protein-protein interactions (docking) primarily has to rely on modeled structures of the individual proteins, which typically are less accurate than the experimentally determined ones. Such "double" modeling is the Grand Challenge of structural reconstruction of the interactome. Yet it remains so far largely untested in a systematic way. We present a comprehensive validation of template-based and free docking on a set of 165 complexes, where each protein model has six levels of structural accuracy, from 1 to 6 Å C(α) RMSD. Many template-based docking predictions fall into acceptable quality category, according to the CAPRI criteria, even for highly inaccurate proteins (5-6 Å RMSD), although the number of such models (and, consequently, the docking success rate) drops significantly for models with RMSD > 4 Å. The results show that the existing docking methodologies can be successfully applied to protein models with a broad range of structural accuracy, and the template-based docking is much less sensitive to inaccuracies of protein models than the free docking. Proteins 2017; 85:470-478. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  9. Protein Models Comparator

    CERN Document Server

    Widera, Paweł

    2011-01-01

    The process of comparison of computer generated protein structural models is an important element of protein structure prediction. It has many uses including model quality evaluation, selection of the final models from a large set of candidates or optimisation of parameters of energy functions used in template free modelling and refinement. Although many protein comparison methods are available online on numerous web servers, their ability to handle a large scale model comparison is often very limited. Most of the servers offer only a single pairwise structural comparison, and they usually do not provide a model-specific comparison with a fixed alignment between the models. To bridge the gap between the protein and model structure comparison we have developed the Protein Models Comparator (pm-cmp). To be able to deliver the scalability on demand and handle large comparison experiments the pm-cmp was implemented "in the cloud". Protein Models Comparator is a scalable web application for a fast distributed comp...

  10. Targeted proteins for diabetes drug design

    Science.gov (United States)

    Doan Trang Nguyen, Ngoc; Thi Le, Ly

    2012-03-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-11-08

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

  12. Exploiting protein intrinsic flexibility in drug design.

    Science.gov (United States)

    Lukman, Suryani; Verma, Chandra S; Fuentes, Gloria

    2014-01-01

    Molecular recognition in biological systems relies on the existence of specific attractive interactions between two partner molecules. Structure-based drug design seeks to identify and optimize such interactions between ligands and their protein targets. The approach followed in medicinal chemistry follows a combination of careful analysis of structural data together with experimental and/or theoretical studies on the system. This chapter focuses on the fact that a protein is not fully characterized by a single structure, but by an ensemble of states, some of them represent "hidden conformations" with cryptic binding sites. We highlight case studies where both experimental and computational methods have been used to mutually drive each other in an attempt to improve the success of the drug design approaches.Advances in both experimental techniques and computational methods have greatly improved our physico-chemical understanding of the functional mechanisms in biomolecules and opened a debate about the interplay between molecular structure and biomolecular function. The beautiful static pictures of protein structures may have led to neglecting the intrinsic protein flexibility, however we are entering a new era where more sophisticated methods are used to exploit this ability of macromolecules, and this will definitely lead to the inclusion of the notion in the pharmaceutical field of drug design.

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

    Directory of Open Access Journals (Sweden)

    Kyunghyun Park

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

  14. Protein-Based Nanomedicine Platforms for Drug Delivery

    Energy Technology Data Exchange (ETDEWEB)

    Ma Ham, Aihui; Tang, Zhiwen; Wu, Hong; Wang, Jun; Lin, Yuehe

    2009-08-03

    Drug delivery systems have been developed for many years, however some limitations still hurdle the pace of going to clinical phase, for example, poor biodistribution, drug molecule cytotoxicity, tissue damage, quick clearance from the circulation system, solubility and stability of drug molecules. To overcome the limitations of drug delivery, biomaterials have to be developed and applied to drug delivery to protect the drug molecules and to enhance the drug’s efficacy. Protein-based nanomedicine platforms for drug delivery are platforms comprised of naturally self-assembled protein subunits of the same protein or a combination of proteins making up a complete system. They are ideal for drug delivery platforms due to their biocompatibility and biodegradability coupled with low toxicity. A variety of proteins have been used and characterized for drug delivery systems including the ferritin/apoferritin protein cage, plant derived viral capsids, the small Heat shock protein (sHsp) cage, albumin, soy and whey protein, collagen, and gelatin. There are many different types and shapes that have been prepared to deliver drug molecules using protein-based platforms including the various protein cages, microspheres, nanoparticles, hydrogels, films, minirods and minipellets. There are over 30 therapeutic compounds that have been investigated with protein-based drug delivery platforms for the potential treatment of various cancers, infectious diseases, chronic diseases, autoimmune diseases. In protein-based drug delivery platforms, protein cage is the most newly developed biomaterials for drug delivery and therapeutic applications. Their uniform sizes, multifunctions, and biodegradability push them to the frontier for drug delivery. In this review, the recent strategic development of drug delivery has been discussed with a special emphasis upon the polymer based, especially protein-based nanomedicine platforms for drug delivery. The advantages and disadvantages are also

  15. MODELS OF PROTEIN FOLDING

    Directory of Open Access Journals (Sweden)

    Unnati Ahluwalia

    2012-12-01

    Full Text Available In an attempt to explore the understanding of protein folding mechanism, various models have been proposed in the literature. Advances in recent experimental and computational techniques rationalized our understanding on some of the fundamental features of the protein folding pathways. The goal of this review is to revisit the various models and outline the essential aspects of the folding reaction.

  16. Identifying drug-target proteins based on network features

    Institute of Scientific and Technical Information of China (English)

    ZHU MingZhu; GAO Lei; LI Xia; LIU ZhiCheng

    2009-01-01

    Proteins rarely function in isolation Inside and outside cells, but operate as part of a highly Intercon-nected cellular network called the interaction network. Therefore, the analysis of the properties of drug-target proteins in the biological network is especially helpful for understanding the mechanism of drug action In terms of informatice. At present, no detailed characterization and description of the topological features of drug-target proteins have been available in the human protein-protein interac-tion network. In this work, by mapping the drug-targets in DrugBank onto the interaction network of human proteins, five topological indices of drug-targets were analyzed and compared with those of the whole protein interactome set and the non-drug-target set. The experimental results showed that drug-target proteins have higher connectivity and quicker communication with each other in the PPI network. Based on these features, all proteins In the interaction network were ranked. The results showed that, of the top 100 proteins, 48 are covered by DrugBank; of the remaining 52 proteins, 9 are drug-target proteins covered by the TTD, Matador and other databases, while others have been dem-onstrated to be drug-target proteins in the literature.

  17. Identifying drug-target proteins based on network features

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    Proteins rarely function in isolation inside and outside cells, but operate as part of a highly intercon- nected cellular network called the interaction network. Therefore, the analysis of the properties of drug-target proteins in the biological network is especially helpful for understanding the mechanism of drug action in terms of informatics. At present, no detailed characterization and description of the topological features of drug-target proteins have been available in the human protein-protein interac- tion network. In this work, by mapping the drug-targets in DrugBank onto the interaction network of human proteins, five topological indices of drug-targets were analyzed and compared with those of the whole protein interactome set and the non-drug-target set. The experimental results showed that drug-target proteins have higher connectivity and quicker communication with each other in the PPI network. Based on these features, all proteins in the interaction network were ranked. The results showed that, of the top 100 proteins, 48 are covered by DrugBank; of the remaining 52 proteins, 9 are drug-target proteins covered by the TTD, Matador and other databases, while others have been dem- onstrated to be drug-target proteins in the literature.

  18. Animal models of drug addiction.

    Science.gov (United States)

    García Pardo, María Pilar; Roger Sánchez, Concepción; De la Rubia Ortí, José Enrique; Aguilar Calpe, María Asunción

    2017-01-12

    The development of animal models of drug reward and addiction is an essential factor for progress in understanding the biological basis of this disorder and for the identification of new therapeutic targets. Depending on the component of reward to be studied, one type of animal model or another may be used. There are models of reinforcement based on the primary hedonic effect produced by the consumption of the addictive substance, such as the self-administration (SA) and intracranial self-stimulation (ICSS) paradigms, and there are models based on the component of reward related to associative learning and cognitive ability to make predictions about obtaining reward in the future, such as the conditioned place preference (CPP) paradigm. In recent years these models have incorporated methodological modifications to study extinction, reinstatement and reconsolidation processes, or to model specific aspects of addictive behavior such as motivation to consume drugs, compulsive consumption or drug seeking under punishment situations. There are also models that link different reinforcement components or model voluntary motivation to consume (two-bottle choice, or drinking in the dark tests). In short, innovations in these models allow progress in scientific knowledge regarding the different aspects that lead individuals to consume a drug and develop compulsive consumption, providing a target for future treatments of addiction.

  19. Predict drug-protein interaction in cellular networking.

    Science.gov (United States)

    Xiao, Xuan; Min, Jian-Liang; Wang, Pu; Chou, Kuo-Chen

    2013-01-01

    Involved with many diseases such as cancer, diabetes, neurodegenerative, inflammatory and respiratory disorders, GPCRs (G-protein-coupled receptors) are the most frequent targets for drug development: over 50% of all prescription drugs currently on the market are actually acting by targeting GPCRs directly or indirectly. Found in every living thing and nearly all cells, ion channels play crucial roles for many vital functions in life, such as heartbeat, sensory transduction, and central nervous system response. Their dysfunction may have significant impact to human health, and hence ion channels are deemed as "the next GPCRs". To develop GPCR-targeting or ion-channel-targeting drugs, the first important step is to identify the interactions between potential drug compounds with the two kinds of protein receptors in the cellular networking. In this minireview, we are to introduce two predictors. One is called iGPCR-Drug accessible at http://www.jci-bioinfo.cn/iGPCR-Drug/; the other called iCDI-PseFpt at http://www.jci-bioinfo.cn/iCDI-PseFpt. The former is for identifying the interactions of drug compounds with GPCRs; while the latter for that with ion channels. In both predictors, the drug compound was formulated by the two-dimensional molecular fingerprint, and the protein receptor by the pseudo amino acid composition generated with the grey model theory, while the operation engine was the fuzzy K-nearest neighbor algorithm. For the convenience of most experimental pharmaceutical and medical scientists, a step-bystep guide is provided on how to use each of the two web-servers to get the desired results without the need to follow the complicated mathematics involved originally for their establishment.

  20. Protein Model Database

    Energy Technology Data Exchange (ETDEWEB)

    Fidelis, K; Adzhubej, A; Kryshtafovych, A; Daniluk, P

    2005-02-23

    The phenomenal success of the genome sequencing projects reveals the power of completeness in revolutionizing biological science. Currently it is possible to sequence entire organisms at a time, allowing for a systemic rather than fractional view of their organization and the various genome-encoded functions. There is an international plan to move towards a similar goal in the area of protein structure. This will not be achieved by experiment alone, but rather by a combination of efforts in crystallography, NMR spectroscopy, and computational modeling. Only a small fraction of structures are expected to be identified experimentally, the remainder to be modeled. Presently there is no organized infrastructure to critically evaluate and present these data to the biological community. The goal of the Protein Model Database project is to create such infrastructure, including (1) public database of theoretically derived protein structures; (2) reliable annotation of protein model quality, (3) novel structure analysis tools, and (4) access to the highest quality modeling techniques available.

  1. Protein Innovations Advance Drug Treatments, Skin Care

    Science.gov (United States)

    2012-01-01

    Dan Carter carefully layered the sheets of tracing paper on the light box. On each sheet were renderings of the atomic components of an essential human protein, one whose structure had long been a mystery. With each layer Carter laid down, a never-before-seen image became clearer. Carter joined NASA s Marshall Space Flight Center in 1985 and began exploring processes of protein crystal growth in space. By bouncing intense X-rays off the crystals, researchers can determine the electron densities around the thousands of atoms forming the protein molecules, unveiling their atomic structures. Cultivating crystals of sufficient quality on Earth was problematic; the microgravity conditions of space were far more accommodating. At the time, only a few hundred protein structures had been mapped, and the methods were time consuming and tedious. Carter hoped his work would help reveal the structure of human serum albumin, a major protein in the human circulatory system responsible for ferrying numerous small molecules in the blood. More was at stake than scientific curiosity. Albumin has a high affinity for most of the world s pharmaceuticals, Carter explains, and its interaction with drugs can change their safety and efficacy. When a medication enters the bloodstream a cancer chemotherapy drug, for example a majority of it can bind with albumin, leaving only a small percentage active for treatment. How a drug interacts with albumin can influence considerations like the necessary effective dosage, playing a significant role in the design and application of therapeutic measures. In spite of numerous difficulties, including having no access to microgravity following the 1986 Space Shuttle Challenger disaster, the image Carter had hoped to see was finally clarifying. In 1988, his lab had acquired specialized X-ray and detection equipment a tipping point. Carter and his colleagues began to piece together albumin s portrait, the formation of its electron densities coalescing on

  2. Three-dimensional structure of heat shock protein 90 from Plasmodium falciparum: molecular modelling approach to rational drug design against malaria

    Indian Academy of Sciences (India)

    Ranjit Kumar; Soundara Raghavan Pavithra; Utpal Tatu

    2007-04-01

    We have recently implicated heat shock protein 90 from Plasmodium falciparum (PfHsp90) as a potential drug target against malaria. Using inhibitors specific to the nucleotide binding domain of Hsp90, we have shown potent growth inhibitory effects on development of malarial parasite in human erythrocytes. To gain better understanding of the vital role played by PfHsp90 in parasite growth, we have modeled its three dimensional structure using recently described full length structure of yeast Hsp90. Sequence similarity found between PfHsp90 and yeast Hsp90 allowed us to model the core structure with high confidence. The superimposition of the predicted structure with that of the template yeast Hsp90 structure reveals an RMSD of 3.31 Å. The N-terminal and middle domains showed the least RMSD (1.76 Å) while the more divergent C–terminus showed a greater RMSD (2.84 Å) with respect to the template. The structure shows overall conservation of domains involved in nucleotide binding, ATPase activity, co-chaperone binding as well as inter-subunit interactions. Important co-chaperones known to modulate Hsp90 function in other eukaryotes are conserved in malarial parasite as well. An acidic stretch of amino acids found in the linker region, which is uniquely extended in PfHsp90 could not be modeled in this structure suggesting a flexible conformation. Our results provide a basis to compare the overall structure and functional pathways dependent on PfHsp90 in malarial parasite. Further analysis of differences found between human and parasite Hsp90 may make it possible to design inhibitors targeted specifically against malaria.

  3. High Throughput Screening for Drugs that Modulate Intermediate Filament Proteins

    Science.gov (United States)

    Sun, Jingyuan; Groppi, Vincent E.; Gui, Honglian; Chen, Lu; Xie, Qing; Liu, Li

    2016-01-01

    Intermediate filament (IF) proteins have unique and complex cell and tissue distribution. Importantly, IF gene mutations cause or predispose to more than 80 human tissue-specific diseases (IF-pathies), with the most severe disease phenotypes being due to mutations at conserved residues that result in a disrupted IF network. A critical need for the entire IF-pathy field is the identification of drugs that can ameliorate or cure these diseases, particularly since all current therapies target the IF-pathy complication, such as diabetes or cardiovascular disease, rather than the mutant IF protein or gene. We describe a high throughput approach to identify drugs that can normalize disrupted IF proteins. This approach utilizes transduction of lentivirus that expresses green-fluorescent-protein-tagged keratin 18 (K18) R90C in A549 cells. The readout is drug ‘hits’ that convert the dot-like keratin filament distribution, due to the R90C mutation, to a wildtype-like filamentous array. A similar strategy can be used to screen thousands of compounds and can be utilized for practically any IF protein with a filament-disrupting mutation, and could therefore potentially target many IF-pathies. ‘Hits’ of interest require validation in cell culture then using in vivo experimental models. Approaches to study the mechanism of mutant-IF normalization by potential drugs of interest are also described. The ultimate goal of this drug screening approach is to identify effective and safe compounds that can potentially be tested for clinical efficacy in patients. PMID:26795471

  4. Syntheses and self-assembly of novel asparagine-derived amphiphiles: Applications in the encapsulation of proteins, hydrophobic, and hydrophilic drug models

    Science.gov (United States)

    Mfuh, Adelphe Mbufung

    This thesis focuses mainly on the synthesis, characterization, and self-assembly of a novel series of asparagine-derived amphiphiles and their use in the preparation and stabilization of nano and microcapsules for the encapsulation of proteins, and hydrophilic and hydrophobic drug models. Chapter 1 gives a brief literature overview of lipid molecular assembly, which covers some aspects of morphological analyses, encapsulation of chemical entity and some reported characterization techniques of supramolecular assemblies. It introduces the scope of this dissertation and contains some information on stimulus responsive liposomal systems for controlled release of drug models. Chapter 2 introduces a novel asparagine-derived lipid bearing two fatty chains (C11 and C17) and a tetrahydropyrimidinone head group. It presents information on the synthesis and characterization of this lipid and describes the self-assembly and effects of this lipid in distearoyl phosphatidyl choline bilayer. Chapter 3 presents the synthesis and characterization of a series of ALAn,m (where n and m represent the length of the hydrocarbon chains on the asparagine-derived, heterocyclic head group). It contains data on the effect of chain length, solvent media and head group ionization on the conformational equilibrium about a tertiary amide bond in ALAn,m. The chapter also examines the influence of chain length on ALAn,m on the colloidal stability of DSPC liposomes. Chapter 4 presents the first example of an N,N-acetal linkage in a novel pH responsive nanocarrier system obtained from the cyclocondensation of dodecanal with sodium asparaginate. Data is presented on the spontaneous self-assembly, encapsulation studies and morphological characterization of the nano-systems with the inclusion of cholesterol as additive. Chapter 5 presents the development of a photoresponsive nanocarrier via the self- assembly of an asparagine-derived lipid containing a coumarin unit in the hydrophobic domain. The

  5. Computational modeling of membrane proteins.

    Science.gov (United States)

    Koehler Leman, Julia; Ulmschneider, Martin B; Gray, Jeffrey J

    2015-01-01

    The determination of membrane protein (MP) structures has always trailed that of soluble proteins due to difficulties in their overexpression, reconstitution into membrane mimetics, and subsequent structure determination. The percentage of MP structures in the protein databank (PDB) has been at a constant 1-2% for the last decade. In contrast, over half of all drugs target MPs, only highlighting how little we understand about drug-specific effects in the human body. To reduce this gap, researchers have attempted to predict structural features of MPs even before the first structure was experimentally elucidated. In this review, we present current computational methods to predict MP structure, starting with secondary structure prediction, prediction of trans-membrane spans, and topology. Even though these methods generate reliable predictions, challenges such as predicting kinks or precise beginnings and ends of secondary structure elements are still waiting to be addressed. We describe recent developments in the prediction of 3D structures of both α-helical MPs as well as β-barrels using comparative modeling techniques, de novo methods, and molecular dynamics (MD) simulations. The increase of MP structures has (1) facilitated comparative modeling due to availability of more and better templates, and (2) improved the statistics for knowledge-based scoring functions. Moreover, de novo methods have benefited from the use of correlated mutations as restraints. Finally, we outline current advances that will likely shape the field in the forthcoming decade.

  6. STABLE DRUG DESIGNING BY MINIMIZING DRUG PROTEIN INTERACTION ENERGY USING PSO

    Directory of Open Access Journals (Sweden)

    Anupam Ghosh

    2015-07-01

    Full Text Available Each and every biological function in living organism happens as a result of protein-protein interactions. The diseases are no exception to this. Identifying one or more proteins for a particular disease and then designing a suitable chemical compound (known as drug to destroy these proteins has been an interesting topic of research in bio-informatics. In previous methods, drugs were designed using only seven chemical components and were represented as a fixedlength tree. But in reality, a drug contains many chemical groups collectively known as pharmacophore. Moreover, the chemical length of the drug cannot be determined before designing the drug.

  7. Protein nanoparticle: A unique system as drug delivery vehicles

    African Journals Online (AJOL)

    STORAGESEVER

    2008-12-29

    . ... contributions in the field of protein nanoparticles used as drug delivery systems. .... tic guidance. ..... response of cytoskeletal organization and adhesion ..... Helicobacter Pylori Effect of Mucoadhesive Nanoparticles Bearing.

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

    Science.gov (United States)

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

    2016-11-14

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

  9. Clustering drug-drug interaction networks with energy model layouts: community analysis and drug repurposing

    OpenAIRE

    Lucreţia Udrescu; Laura Sbârcea; Alexandru Topîrceanu; Alexandru Iovanovici; Ludovic Kurunczi; Paul Bogdan; Mihai Udrescu

    2016-01-01

    Analyzing drug-drug interactions may unravel previously unknown drug action patterns, leading to the development of new drug discovery tools. We present a new approach to analyzing drug-drug interaction networks, based on clustering and topological community detection techniques that are specific to complex network science. Our methodology uncovers functional drug categories along with the intricate relationships between them. Using modularity-based and energy-model layout community detection...

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

    LENUS (Irish Health Repository)

    Toomey, David

    2009-01-01

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

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

    Directory of Open Access Journals (Sweden)

    David Toomey

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

  12. Molecular modelling and drug design.

    Science.gov (United States)

    Meyer, E F; Swanson, S M; Williams, J A

    2000-03-01

    Drug design is a creative act of the same magnitude as composing, sculpting, or writing. The results can touch the lives of millions, but the creator is rarely one scientist and the rewards are distributed differently in the arts than in the sciences. The mechanisms of creativity are the same, i.e., incremental (plodding from darkness to dawn) or sudden (the "Eureka" effect) realization, but both are poorly understood. Creativity remains a human characteristic, but it is directly related to the tools available, especially computer software and hardware. While modelling software continues to mature, very little new has evolved in terms of hardware. Here, we discuss the history of molecular modelling and describe two novel modelling tools, a haptic device and a program, SCULPT, to generate solid molecular models at atomic resolution.

  13. Structure-based Drug Screening and Ligand-Based Drug Screening Toward Protein-Compound Network

    Science.gov (United States)

    Fukunishi, Yoshifumi

    2007-12-01

    We developed two new methods to improve the accuracy of molecular interaction data using a protein-compound affinity matrix calculated by a protein-compound docking software. One method is a structure-based in silico drug screening method and another method is a ligand-based in silico drug screening method. These methods were applied to enhance the database enrichment of in silico drug screening and in silico target protein screening.

  14. Homology Modeling a Fast Tool for Drug Discovery: Current Perspectives

    Science.gov (United States)

    Vyas, V. K.; Ukawala, R. D.; Ghate, M.; Chintha, C.

    2012-01-01

    Major goal of structural biology involve formation of protein-ligand complexes; in which the protein molecules act energetically in the course of binding. Therefore, perceptive of protein-ligand interaction will be very important for structure based drug design. Lack of knowledge of 3D structures has hindered efforts to understand the binding specificities of ligands with protein. With increasing in modeling software and the growing number of known protein structures, homology modeling is rapidly becoming the method of choice for obtaining 3D coordinates of proteins. Homology modeling is a representation of the similarity of environmental residues at topologically corresponding positions in the reference proteins. In the absence of experimental data, model building on the basis of a known 3D structure of a homologous protein is at present the only reliable method to obtain the structural information. Knowledge of the 3D structures of proteins provides invaluable insights into the molecular basis of their functions. The recent advances in homology modeling, particularly in detecting and aligning sequences with template structures, distant homologues, modeling of loops and side chains as well as detecting errors in a model contributed to consistent prediction of protein structure, which was not possible even several years ago. This review focused on the features and a role of homology modeling in predicting protein structure and described current developments in this field with victorious applications at the different stages of the drug design and discovery. PMID:23204616

  15. Protein Complex Production from the Drug Discovery Standpoint.

    Science.gov (United States)

    Moarefi, Ismail

    2016-01-01

    Small molecule drug discovery critically depends on the availability of meaningful in vitro assays to guide medicinal chemistry programs that are aimed at optimizing drug potency and selectivity. As it becomes increasingly evident, most disease relevant drug targets do not act as a single protein. In the body, they are instead generally found in complex with protein cofactors that are highly relevant for their correct function and regulation. This review highlights selected examples of the increasing trend to use biologically relevant protein complexes for rational drug discovery to reduce costly late phase attritions due to lack of efficacy or toxicity.

  16. The Development and Characterization of Protein-Based Stationary Phases for Studying Drug-Protein and Protein-Protein Interactions

    OpenAIRE

    Sanghvi, Mitesh; Moaddel, Ruin; Wainer, Irving W.

    2011-01-01

    Protein-based liquid chromatography stationary phases are used in bioaffinity chromatography for studying drug-protein interactions, the determination of binding affinities, competitive and allosteric interactions, as well as for studying protein-protein interactions. This review addresses the development and characterization of protein-based stationary phase, and the application of these phases using frontal and zonal chromatography techniques. The approach will be illustrated using immobili...

  17. Modeling Mercury in Proteins

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Jeremy C [ORNL; Parks, Jerry M [ORNL

    2016-01-01

    Mercury (Hg) is a naturally occurring element that is released into the biosphere both by natural processes and anthropogenic activities. Although its reduced, elemental form Hg(0) is relatively non-toxic, other forms such as Hg2+ and, in particular, its methylated form, methylmercury, are toxic, with deleterious effects on both ecosystems and humans. Microorganisms play important roles in the transformation of mercury in the environment. Inorganic Hg2+ can be methylated by certain bacteria and archaea to form methylmercury. Conversely, bacteria also demethylate methylmercury and reduce Hg2+ to relatively inert Hg(0). Transformations and toxicity occur as a result of mercury interacting with various proteins. Clearly, then, understanding the toxic effects of mercury and its cycling in the environment requires characterization of these interactions. Computational approaches are ideally suited to studies of mercury in proteins because they can provide a detailed picture and circumvent issues associated with toxicity. Here we describe computational methods for investigating and characterizing how mercury binds to proteins, how inter- and intra-protein transfer of mercury is orchestrated in biological systems, and how chemical reactions in proteins transform the metal. We describe quantum chemical analyses of aqueous Hg(II), which reveal critical factors that determine ligand binding propensities. We then provide a perspective on how we used chemical reasoning to discover how microorganisms methylate mercury. We also highlight our combined computational and experimental studies of the proteins and enzymes of the mer operon, a suite of genes that confers mercury resistance in many bacteria. Lastly, we place work on mercury in proteins in the context of what is needed for a comprehensive multi-scale model of environmental mercury cycling.

  18. Membrane-Protein Crystallography and Potentiality for Drug Design

    Science.gov (United States)

    Yamashita, Atsuko

    Structure-based drug design for membrane proteins is far behind that for soluble proteins due to difficulty in crystallographic structure determination, despite the fact that about 60% of FDA-approved drugs target membrane proteins located at the cell surface. Stable homologs for a membrane protein of interest, such as prokaryotic neurotransmitter transporter homolog LeuT, might enable cooperative analyses by crystallography and functional assays, provide useful information for functional mechanisms, and thus serve as important probes for drug design based on mechanisms as well as structures.

  19. Design of cationic microspheres based on aminated gelatin for controlled release of peptide and protein drugs.

    Science.gov (United States)

    Morimoto, Kazuhiro; Chono, Sumio; Kosai, Tadashi; Seki, Toshinobu; Tabata, Yasuhiko

    2008-02-01

    Two different types of cationized microspheres based on a native cationic gelatin (NGMS) and aminated gelatin with ethylendiamine (CGMS) were investigated for the controlled release of three model acidic peptide/protein drugs with different molecular weights (MWs) and isoelectric points (IEPs). Recombinant human (rh)-insulin (MW: 5.8 kDa, IEP: 5.3), bovine milk lactoalbumin, BMLA (MW: 14 kDa, IEP: 4.3), and bovine serum albumin (BSA MW: 67 kDa, IEP: 4.9) were used as model acidic peptide/protein drugs. The in vitro release profiles of these acidic peptide/protein drugs from NGMS and CGMS were compared and different periods of cross-linking were obtained. The slower release of these acidic peptide/protein drugs from CGMS compared with those from NGMS with cross-linking for 48 hr. was caused by the suppression of burst release during the initial phase. The degree of suppression of burst release of the three peptide/protein drugs during the initial phase by CGMS was in the following order: (rh)-insulin > BMLA > BSA. The release of insulin with a lower molecular weight from CGMS was particularly suppressed compared with the other two drugs with higher molecular weights in the initial phase. The control of the release rate of acidic peptide/protein drugs from gelatin microsphere can be achieved by amination of gelatin. Therefore, CGMS is useful for the controlled release of acidic peptide/ protein drugs.

  20. Benchmarking human protein complexes to investigate drug-related systems and evaluate predicted protein complexes.

    Directory of Open Access Journals (Sweden)

    Min Wu

    Full Text Available Protein complexes are key entities to perform cellular functions. Human diseases are also revealed to associate with some specific human protein complexes. In fact, human protein complexes are widely used for protein function annotation, inference of human protein interactome, disease gene prediction, and so on. Therefore, it is highly desired to build an up-to-date catalogue of human complexes to support the research in these applications. Protein complexes from different databases are as expected to be highly redundant. In this paper, we designed a set of concise operations to compile these redundant human complexes and built a comprehensive catalogue called CHPC2012 (Catalogue of Human Protein Complexes. CHPC2012 achieves a higher coverage for proteins and protein complexes than those individual databases. It is also verified to be a set of complexes with high quality as its co-complex protein associations have a high overlap with protein-protein interactions (PPI in various existing PPI databases. We demonstrated two distinct applications of CHPC2012, that is, investigating the relationship between protein complexes and drug-related systems and evaluating the quality of predicted protein complexes. In particular, CHPC2012 provides more insights into drug development. For instance, proteins involved in multiple complexes (the overlapping proteins are potential drug targets; the drug-complex network is utilized to investigate multi-target drugs and drug-drug interactions; and the disease-specific complex-drug networks will provide new clues for drug repositioning. With this up-to-date reference set of human protein complexes, we believe that the CHPC2012 catalogue is able to enhance the studies for protein interactions, protein functions, human diseases, drugs, and related fields of research. CHPC2012 complexes can be downloaded from http://www1.i2r.a-star.edu.sg/xlli/CHPC2012/CHPC2012.htm.

  1. Multiscale modeling of proteins.

    Science.gov (United States)

    Tozzini, Valentina

    2010-02-16

    The activity within a living cell is based on a complex network of interactions among biomolecules, exchanging information and energy through biochemical processes. These events occur on different scales, from the nano- to the macroscale, spanning about 10 orders of magnitude in the space domain and 15 orders of magnitude in the time domain. Consequently, many different modeling techniques, each proper for a particular time or space scale, are commonly used. In addition, a single process often spans more than a single time or space scale. Thus, the necessity arises for combining the modeling techniques in multiscale approaches. In this Account, I first review the different modeling methods for bio-systems, from quantum mechanics to the coarse-grained and continuum-like descriptions, passing through the atomistic force field simulations. Special attention is devoted to their combination in different possible multiscale approaches and to the questions and problems related to their coherent matching in the space and time domains. These aspects are often considered secondary, but in fact, they have primary relevance when the aim is the coherent and complete description of bioprocesses. Subsequently, applications are illustrated by means of two paradigmatic examples: (i) the green fluorescent protein (GFP) family and (ii) the proteins involved in the human immunodeficiency virus (HIV) replication cycle. The GFPs are currently one of the most frequently used markers for monitoring protein trafficking within living cells; nanobiotechnology and cell biology strongly rely on their use in fluorescence microscopy techniques. A detailed knowledge of the actions of the virus-specific enzymes of HIV (specifically HIV protease and integrase) is necessary to study novel therapeutic strategies against this disease. Thus, the insight accumulated over years of intense study is an excellent framework for this Account. The foremost relevance of these two biomolecular systems was

  2. Systematic identification of proteins that elicit drug side effects

    DEFF Research Database (Denmark)

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

    2013-01-01

    Side effect similarities of drugs have recently been employed to predict new drug targets, and networks of side effects and targets have been used to better understand the mechanism of action of drugs. Here, we report a large-scale analysis to systematically predict and characterize proteins...... that cause drug side effects. We integrated phenotypic data obtained during clinical trials with known drug-target relations to identify overrepresented protein-side effect combinations. Using independent data, we confirm that most of these overrepresentations point to proteins which, when perturbed, cause...... side effects. Of 1428 side effects studied, 732 were predicted to be predominantly caused by individual proteins, at least 137 of them backed by existing pharmacological or phenotypic data. We prove this concept in vivo by confirming our prediction that activation of the serotonin 7 receptor (HTR7...

  3. Chromatin proteins and modifications as drug targets

    DEFF Research Database (Denmark)

    Helin, Kristian; Dhanak, Dashyant

    2013-01-01

    A plethora of groundbreaking studies have demonstrated the importance of chromatin-associated proteins and post-translational modifications of histones, proteins and DNA (so-called epigenetic modifications) for transcriptional control and normal development. Disruption of epigenetic control...

  4. Multivariate Analysis of Side Effects of Drug Molecules Based on Knowledge of Protein Bindings and ProteinProtein Interactions.

    Science.gov (United States)

    Hasegawa, Kiyoshi; Funatsu, Kimito

    2014-12-01

    Here, we examined the relationships between 969 side effects associated with 658 drugs and their 1368 human protein targets using our hybrid approaches. Firstly, L-shaped PLS (LPLS) was used to construct a multivariate model of side effects and protein bindings of drug molecules. LPLS is an extension of standard PLS regression, where, in addition to the response matrix Y and the regressor matrix X, an extra data matrix Z is constructed that summarizes the background information of X. X and Y are matrices comprising drugs-target proteins, and drugs-side effects, respectively. The Z matrix is the proteinprotein interaction data. From the loading plot of Y, we could identify two remarkable side effects (urinary incontinence and increased salivation) From the corresponding loading plot of X, the responsible protein targets causing each side effect could be estimated (sodium channels and gamma-aminobutyric acid (GABA) receptors). The loading plot of the Z matrix indicated that the GABA receptors interact with each other and they heavily influence the side effect of increased salivation. Secondly, Bayesian classifier methods were separately applied to the cases of the two side effects. That is, the Bayesian classifier method was used to classify drug molecules as binding or not binding to the responsible protein targets associated with each side effect. Using atom-coloring techniques, it was possible to estimate which fragments on the drug molecule might cause the specific side effects. This information is valuable for drug design to avoid specific side effects.

  5. Novel non-invasive protein and peptide drug delivery approaches.

    Science.gov (United States)

    Wallis, L; Kleynhans, E; Toit, T Du; Gouws, C; Steyn, D; Steenekamp, J; Viljoen, J; Hamman, J

    2014-01-01

    Protein and peptide based therapeutics are typically administered by injection due to their poor uptake when administered via enteral routes of drug administration. Unfortunately, chronic administration of these drugs through multiple injections presents certain patient related problems and it is difficult to mimic the normal physiological release patterns via this mode of drug administration. A need therefore exists to non-invasively deliver these drugs by means of alternative ways such as via the oral, pulmonary, nasal, transdermal and buccal administration routes. Although some attempts of needle free peptide and protein drug delivery have progressed to the clinical stage, relatively limited success has been achieved in terms of commercially available products. Despite the low frequency of clinical breakthroughs with noninvasive protein drug delivery this far, it remains an active research area with renewed interest not only due to its improved therapeutic potential, but also due to the attractive commercial outcomes it offers. It is the aim of this review article to reflect on the main strategies investigated to overcome the barriers against effective systemic protein drug delivery in different routes of drug administration. Approaches based on chemical modifications and pharmaceutical technologies are discussed with reference to examples of drugs and devices that have shown potential, while attempts that have failed are also briefly outlined.

  6. Pharmacokinetics of biotech drugs: peptides, proteins and monoclonal antibodies.

    Science.gov (United States)

    Lin, Jiunn H

    2009-09-01

    With the advances in recombinant DNA biotechnology, molecular biology and immunology, the number of biotech drugs, including peptides, proteins and monoclonal antibodies, available for clinical use has dramatically increased in recent years. Although pharmacokinetic principles are equally applicable to the large molecule drugs and conventional small molecule drugs, the underlying mechanisms for the processes of absorption, distribution, metabolism and excretion (ADME) of large molecule drugs are often very different from that of small molecule drugs. Therefore, a good understanding of the ADME processes of large molecule drugs is essential in support of the development of therapeutic biologics. The purpose of this article is to review the current knowledge of the ADME processes that govern the pharmacokinetics of biotech drugs. The challenges encountered by orally administered peptide and protein drugs, and the nature of lymphatic absorption after subcutaneous administration will be discussed. In addition, molecular mechanisms of biodistribution, metabolism and renal excretion of biotech drugs will also be discussed. Finally, approaches used for prediction of human pharmacokinetics of protein drugs will be briefly discussed.

  7. Protein nanoparticles as drug delivery carriers for cancer therapy.

    Science.gov (United States)

    Lohcharoenkal, Warangkana; Wang, Liying; Chen, Yi Charlie; Rojanasakul, Yon

    2014-01-01

    Nanoparticles have increasingly been used for a variety of applications, most notably for the delivery of therapeutic and diagnostic agents. A large number of nanoparticle drug delivery systems have been developed for cancer treatment and various materials have been explored as drug delivery agents to improve the therapeutic efficacy and safety of anticancer drugs. Natural biomolecules such as proteins are an attractive alternative to synthetic polymers which are commonly used in drug formulations because of their safety. In general, protein nanoparticles offer a number of advantages including biocompatibility and biodegradability. They can be prepared under mild conditions without the use of toxic chemicals or organic solvents. Moreover, due to their defined primary structure, protein-based nanoparticles offer various possibilities for surface modifications including covalent attachment of drugs and targeting ligands. In this paper, we review the most significant advancements in protein nanoparticle technology and their use in drug delivery arena. We then examine the various sources of protein materials that have been used successfully for the construction of protein nanoparticles as well as their methods of preparation. Finally, we discuss the applications of protein nanoparticles in cancer therapy.

  8. Protein Nanoparticles as Drug Delivery Carriers for Cancer Therapy

    Science.gov (United States)

    Lohcharoenkal, Warangkana; Wang, Liying; Chen, Yi Charlie

    2014-01-01

    Nanoparticles have increasingly been used for a variety of applications, most notably for the delivery of therapeutic and diagnostic agents. A large number of nanoparticle drug delivery systems have been developed for cancer treatment and various materials have been explored as drug delivery agents to improve the therapeutic efficacy and safety of anticancer drugs. Natural biomolecules such as proteins are an attractive alternative to synthetic polymers which are commonly used in drug formulations because of their safety. In general, protein nanoparticles offer a number of advantages including biocompatibility and biodegradability. They can be prepared under mild conditions without the use of toxic chemicals or organic solvents. Moreover, due to their defined primary structure, protein-based nanoparticles offer various possibilities for surface modifications including covalent attachment of drugs and targeting ligands. In this paper, we review the most significant advancements in protein nanoparticle technology and their use in drug delivery arena. We then examine the various sources of protein materials that have been used successfully for the construction of protein nanoparticles as well as their methods of preparation. Finally, we discuss the applications of protein nanoparticles in cancer therapy. PMID:24772414

  9. Stereoselective binding of chiral drugs to plasma proteins

    Institute of Scientific and Technical Information of China (English)

    Qi SHEN; Lu WANG; Hui ZHOU; Hui-di JIANG; Lu-shan YU; Su ZENG

    2013-01-01

    Chiral drugs show distinct biochemical and pharmacological behaviors in the human body.The binding of chiral drugs to plasma proteins usually exhibits stereoselectivity,which has a far-reaching influence on their pharmacological activities and pharmacokinetic profiles.In this review,the stereoselective binding of chiral drugs to human serum albumin (HSA),α1-acid glycoprotein (AGP)and lipoprotein,three most important proteins in human plasma,are detailed.Furthermore,the application of AGP variants and recombinant fragments of HSA for studying enantiomer binding properties is also discussed.Apart from the stereoselectivity of enantiomer-protein binding,enantiomer-enantiomer interactions that may induce allosteric effects are also described.Additionally,the techniques and methods used to determine drug-protein binding parameters are briefly reviewed.

  10. Drug efflux proteins in multidrug resistant bacteria

    NARCIS (Netherlands)

    vanVeen, HW; Konings, WN

    1997-01-01

    Bacteria contain an array of transport proteins in their cytoplasmic membrane. Many of these proteins play an important role in conferring resistance to toxic compounds. The multidrug efflux systems encountered in prokaryotic cells are very similar to those observed in eukaryotic cells. Therefore, a

  11. Drug efflux proteins in multidrug resistant bacteria

    NARCIS (Netherlands)

    vanVeen, HW; Konings, WN

    Bacteria contain an array of transport proteins in their cytoplasmic membrane. Many of these proteins play an important role in conferring resistance to toxic compounds. The multidrug efflux systems encountered in prokaryotic cells are very similar to those observed in eukaryotic cells. Therefore, a

  12. Transporter protein and drug resistance of Trypanosoma.

    Science.gov (United States)

    Medina, Noraine P; Mingala, Claro N

    2016-01-01

    Trypanosoma infection is one of the most important infections in livestock and humans. One of the main problems of its therapeutic control and treatment is the resurgence of drug resistance. One of the most studied causes of such resistance is the function of its adenosine transporter gene. A trypanosomal gene TbAT1 from Trypanosoma brucei has been cloned in yeast to demonstrate its function in the transport of adenosine and trypanocidal agents. Drug resistant trypanosomes showed a defective TbAT1 variant; furthermore, deletion of the gene and set point mutations in the transporter gene has been demonstrated from isolates from relapse patients. The molecular understanding of the mechanism of action trypanocidal agents and function of transporter gene can lead to control of drug resistance of Trypanosomes.

  13. S-Glutathionylation and Redox Protein Signaling in Drug Addiction.

    Science.gov (United States)

    Womersley, Jacqueline S; Uys, Joachim D

    2016-01-01

    Drug addiction is a chronic relapsing disorder that comes at a high cost to individuals and society. Therefore understanding the mechanisms by which drugs exert their effects is of prime importance. Drugs of abuse increase the production of reactive oxygen and nitrogen species resulting in oxidative stress. This change in redox homeostasis increases the conjugation of glutathione to protein cysteine residues; a process called S-glutathionylation. Although traditionally regarded as a protective mechanism against irreversible protein oxidation, accumulated evidence suggests a more nuanced role for S-glutathionylation, namely as a mediator in redox-sensitive protein signaling. The reversible modification of protein thiols leading to alteration in function under different physiologic/pathologic conditions provides a mechanism whereby change in redox status can be translated into a functional response. As such, S-glutathionylation represents an understudied means of post-translational protein modification that may be important in the mechanisms underlying drug addiction. This review will discuss the evidence for S-glutathionylation as a redox-sensing mechanism and how this may be involved in the response to drug-induced oxidative stress. The function of S-glutathionylated proteins involved in neurotransmission, dendritic spine structure, and drug-induced behavioral outputs will be reviewed with specific reference to alcohol, cocaine, and heroin. Copyright © 2016. Published by Elsevier Inc.

  14. Recent trends in protein and peptide drug delivery systems

    Directory of Open Access Journals (Sweden)

    Gupta Himanshu

    2009-01-01

    Full Text Available With the discovery of insulin in 1922, identification and commercialization of potential protein and peptide drugs have been increased. Since then, research and development to improve the means of delivering protein therapeutics to patients has begun. The research efforts have followed two basic pathways: One path focused on noninvasive means of delivering proteins to the body and the second path has been primarily aimed at increasing the biological half-life of the therapeutic molecules. The search for approaches that provide formulations that are stable, bioavailable, readily manufacturable, and acceptable to the patient, has led to major advances in the development of nasal and controlled release technology, applicable to every protein or peptide. In several limited cases, sustained delivery of peptides and proteins has employed the use of polymeric carriers. More successes have been achieved by chemical modification using amino acid substitutions, protein pegylation or glycosylation to improve the pharmacodynamic properties of certain macromolecules and various delivery systems have been developed like the prolease technology, nano-particulate and microparticulate delivery systems, and the mucoadhesive delivery of peptides. The needle and syringe remain the primary means of protein delivery. Major hurdles remain in order to overcome the combined natural barriers of drug permeability, drug stability, pharmacokinetics, and pharmacodynamics of protein therapeutics. In our present review we have tried to compile some recent advances in protein and peptide drug delivery systems.

  15. Chromatin proteins and modifications as drug targets

    DEFF Research Database (Denmark)

    Helin, Kristian; Dhanak, Dashyant

    2013-01-01

    A plethora of groundbreaking studies have demonstrated the importance of chromatin-associated proteins and post-translational modifications of histones, proteins and DNA (so-called epigenetic modifications) for transcriptional control and normal development. Disruption of epigenetic control...... is a frequent event in disease, and the first epigenetic-based therapies for cancer treatment have been approved. A generation of new classes of potent and specific inhibitors for several chromatin-associated proteins have shown promise in preclinical trials. Although the biology of epigenetic regulation...

  16. Inferring drug-disease associations based on known protein complexes.

    Science.gov (United States)

    Yu, Liang; Huang, Jianbin; Ma, Zhixin; Zhang, Jing; Zou, Yapeng; Gao, Lin

    2015-01-01

    Inferring drug-disease associations is critical in unveiling disease mechanisms, as well as discovering novel functions of available drugs, or drug repositioning. Previous work is primarily based on drug-gene-disease relationship, which throws away many important information since genes execute their functions through interacting others. To overcome this issue, we propose a novel methodology that discover the drug-disease association based on protein complexes. Firstly, the integrated heterogeneous network consisting of drugs, protein complexes, and disease are constructed, where we assign weights to the drug-disease association by using probability. Then, from the tripartite network, we get the indirect weighted relationships between drugs and diseases. The larger the weight, the higher the reliability of the correlation. We apply our method to mental disorders and hypertension, and validate the result by using comparative toxicogenomics database. Our ranked results can be directly reinforced by existing biomedical literature, suggesting that our proposed method obtains higher specificity and sensitivity. The proposed method offers new insight into drug-disease discovery. Our method is publicly available at http://1.complexdrug.sinaapp.com/Drug_Complex_Disease/Data_Download.html.

  17. Characterization of particulate drug delivery systems for oral delivery of Peptide and protein drugs

    DEFF Research Database (Denmark)

    Christophersen, Philip Carsten; Fano, Mathias; Saaby, Lasse

    2015-01-01

    Oral drug delivery is a preferred route because of good patient compliance. However, most peptide/ protein drugs are delivered via parenteral routes because of the absorption barriers in the gastrointestinal (GI) tract such as enzymatic degradation by proteases and low permeability acrossthe...... biological membranes. To overcome these barriers, different formulation strategies for oral delivery of biomacromolecules have been proposed, including lipid based formulations and polymer-based particulate drug delivery systems (DDS). The aim of this review is to summarize the existing knowledge about oral...... delivery of peptide/protein drugs and to provide an overview of formulationand characterization strategies. For a better understanding of the challenges in oral delivery of peptide/protein drugs, the composition of GI fluids and the digestion processes of different kinds of excipients in the GI tract...

  18. A systematic prediction of drug-target interactions using molecular fingerprints and protein sequences.

    Science.gov (United States)

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

    2016-11-21

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

  19. Quantifying drug-protein binding in vivo.

    Energy Technology Data Exchange (ETDEWEB)

    Buchholz, B; Bench, G; Keating III, G; Palmblad, M; Vogel, J; Grant, P G; Hillegonds, D

    2004-02-17

    Accelerator mass spectrometry (AMS) provides precise quantitation of isotope labeled compounds that are bound to biological macromolecules such as DNA or proteins. The sensitivity is high enough to allow for sub-pharmacological (''micro-'') dosing to determine macromolecular targets without inducing toxicities or altering the system under study, whether it is healthy or diseased. We demonstrated an application of AMS in quantifying the physiologic effects of one dosed chemical compound upon the binding level of another compound in vivo at sub-toxic doses [4].We are using tissues left from this study to develop protocols for quantifying specific binding to isolated and identified proteins. We also developed a new technique to quantify nanogram to milligram amounts of isolated protein at precisions that are comparable to those for quantifying the bound compound by AMS.

  20. Modelling of proteins in membranes

    DEFF Research Database (Denmark)

    Sperotto, Maria Maddalena; May, S.; Baumgaertner, A.

    2006-01-01

    This review describes some recent theories and simulations of mesoscopic and microscopic models of lipid membranes with embedded or attached proteins. We summarize results supporting our understanding of phenomena for which the activities of proteins in membranes are expected to be significantly...... affected by the lipid environment. Theoretical predictions are pointed out, and compared to experimental findings, if available. Among others, the following phenomena are discussed: interactions of interfacially adsorbed peptides, pore-forming amphipathic peptides, adsorption of charged proteins onto...... oppositely charged lipid membranes, lipid-induced tilting of proteins embedded in lipid bilayers, protein-induced bilayer deformations, protein insertion and assembly, and lipid-controlled functioning of membrane proteins....

  1. Hydrogel based drug carriers for controlled release of hydrophobic drugs and proteins

    NARCIS (Netherlands)

    Ke Peng,

    2011-01-01

    The aim of this study is to prepare in situ forming hydrogels based on biocompatible polymers for the controlled release of hydrophobic drug and proteins. In order to load hydrophobic drug to the hydrophilic hydrogel matrix, beta-cyclodextrin and human serum albumin was introduced to the hydrogel ne

  2. Stabilization of protein-protein interactions in drug discovery.

    Science.gov (United States)

    Andrei, Sebastian A; Sijbesma, Eline; Hann, Michael; Davis, Jeremy; O'Mahony, Gavin; Perry, Matthew W D; Karawajczyk, Anna; Eickhoff, Jan; Brunsveld, Luc; Doveston, Richard G; Milroy, Lech-Gustav; Ottmann, Christian

    2017-09-01

    PPIs are involved in every disease and specific modulation of these PPIs with small molecules would significantly improve our prospects of developing therapeutic agents. Both industry and academia have engaged in the identification and use of PPI inhibitors. However in comparison, the opposite strategy of employing small-molecule stabilizers of PPIs is underrepresented in drug discovery. Areas covered: PPI stabilization has not been exploited in a systematic manner. Rather, this concept validated by a number of therapeutically used natural products like rapamycin and paclitaxel has been shown retrospectively to be the basis of the activity of synthetic molecules originating from drug discovery projects among them lenalidomide and tafamidis. Here, the authors cover the growing number of synthetic small-molecule PPI stabilizers to advocate for a stronger consideration of this as a drug discovery approach. Expert opinion: Both the natural products and the growing number of synthetic molecules show that PPI stabilization is a viable strategy for drug discovery. There is certainly a significant challenge to adapt compound libraries, screening techniques and downstream methodologies to identify, characterize and optimize PPI stabilizers, but the examples of molecules reviewed here in our opinion justify these efforts.

  3. Computational 3D structures of drug-targeting proteins in the 2009-H1N1 influenza A virus

    Science.gov (United States)

    Du, Qi-Shi; Wang, Shu-Qing; Huang, Ri-Bo; Chou, Kuo-Chen

    2010-01-01

    The neuraminidase (NA) and M2 proton channel of influenza virus are the drug-targeting proteins, based on which several drugs were developed. However these once powerful drugs encountered drug-resistant problem to the H5N1 and H1N1 flu. To address this problem, the computational 3D structures of NA and M2 proteins of 2009-H1N1 influenza virus were built using the molecular modeling technique and computational chemistry method. Based on the models the structure features of NA and M2 proteins were analyzed, the docking structures of drug-protein complexes were computed, and the residue mutations were annotated. The results may help to solve the drug-resistant problem and stimulate designing more effective drugs against 2009-H1N1 influenza pandemic.

  4. Microencapsulation of protein drugs for drug delivery: strategy, preparation, and applications.

    Science.gov (United States)

    Ma, Guanghui

    2014-11-10

    Bio-degradable poly(lactide) (PLA)/poly(lactide-glycolide) (PLGA) and chitosan microspheres (or microcapsules) have important applications in Drug Delivery Systems (DDS) of protein/peptide drugs. By encapsulating protein/peptide drugs in the microspheres, the serum drug concentration can be maintained at a higher constant value for a prolonged time, or injection formulation can be changed to orally or mucosally administered formulation. PLA/PLGA and chitosan are most often used in injection formulation and oral formulation. However, in the preparation and applications of PLA/PLGA and chitosan microspheres containing protein/peptide drugs, the problems of broad size distribution and poor reproducibility of microspheres, and deactivation of protein during the preparation, storage and release, are still big challenges. In this article, the techniques for control of the diameter of microspheres and microcapsules will be introduced at first, then the strategies about how to maintain the bioactivity of protein drugs during preparation and drug release will be reviewed and developed in our research group. The membrane emulsification techniques including direct membrane emulsification and rapid membrane emulsification processes were developed to prepare uniform-sized microspheres, the diameter of microspheres can be controlled from submicron to 100μm by these two processes, and the reproducibility of products can be guaranteed. Furthermore, compared with conventional stirring method, the big advantages of membrane emulsification process were that the uniform microspheres with much higher encapsulation efficiency can be obtained, and the release behavior can be adjusted by selecting microsphere size. Mild membrane emulsification condition also can prevent the deactivation of proteins, which frequently occurred under high shear force in mechanical stirring, sonification, and homogenization methods. The strategies for maintaining the bioactivity of protein drug were

  5. Review on Medusa:a polymer-based sustained release technology for protein and peptide drugs.

    Science.gov (United States)

    Chan, Y-P; Meyrueix, R; Kravtzoff, R; Nicolas, F; Lundstrom, K

    2007-07-01

    The polymer-based Medusa system (Flamel Technologies) has been designed for slow release of therapeutic proteins and peptides. The Medusa II consists of a poly L-glutamate backbone grafted with hydrophobic alpha-tocopherol molecules, creating a colloidal suspension of nanoparticles (10 - 50 nm) in water. The sustained drug release is based on reversible drug interactions with hydrophobic nanodomains within the nanoparticles. In vivo, it is suggested that the therapeutic protein is displaced by endogenous proteins present in physiological fluids, leading to a slow drug release. The peak concentration is dramatically decreased and the protein release substantially extended. The Medusa technology has been applied to subcutaneous injection for several therapeutic proteins, such as IL-2 and IFN-alpha(2b), in animal models (rats, dogs, monkeys) and clinical trials in renal cancer (IL-2) and hepatitis C (IFN-alpha(2b)) patients.

  6. Construction of a cancer-perturbed protein-protein interaction network for discovery of apoptosis drug targets

    Directory of Open Access Journals (Sweden)

    Chen Bor-Sen

    2008-06-01

    Full Text Available Abstract Background Cancer is caused by genetic abnormalities, such as mutations of oncogenes or tumor suppressor genes, which alter downstream signal transduction pathways and protein-protein interactions. Comparisons of the interactions of proteins in cancerous and normal cells can shed light on the mechanisms of carcinogenesis. Results We constructed initial networks of protein-protein interactions involved in the apoptosis of cancerous and normal cells by use of two human yeast two-hybrid data sets and four online databases. Next, we applied a nonlinear stochastic model, maximum likelihood parameter estimation, and Akaike Information Criteria (AIC to eliminate false-positive protein-protein interactions in our initial protein interaction networks by use of microarray data. Comparisons of the networks of apoptosis in HeLa (human cervical carcinoma cells and in normal primary lung fibroblasts provided insight into the mechanism of apoptosis and allowed identification of potential drug targets. The potential targets include BCL2, caspase-3 and TP53. Our comparison of cancerous and normal cells also allowed derivation of several party hubs and date hubs in the human protein-protein interaction networks involved in caspase activation. Conclusion Our method allows identification of cancer-perturbed protein-protein interactions involved in apoptosis and identification of potential molecular targets for development of anti-cancer drugs.

  7. Coacervate delivery systems for proteins and small molecule drugs.

    Science.gov (United States)

    Johnson, Noah R; Wang, Yadong

    2014-12-01

    Coacervates represent an exciting new class of drug delivery vehicles, developed in the past decade as carriers of small molecule drugs and proteins. This review summarizes several well-described coacervate systems, including: i) elastin-like peptides for delivery of anticancer therapeutics; ii) heparin-based coacervates with synthetic polycations for controlled growth factor delivery; iii) carboxymethyl chitosan aggregates for oral drug delivery; iv) Mussel adhesive protein and hyaluronic acid coacervates. Coacervates present advantages in their simple assembly and easy incorporation into tissue engineering scaffolds or as adjuncts to cell therapies. They are also amenable to functionalization such as for targeting or for enhancing the bioactivity of their cargo. These new drug carriers are anticipated to have broad applications and noteworthy impact in the near future.

  8. Considerations of Protein Subpockets in Fragment-Based Drug Design.

    Science.gov (United States)

    Bartolowits, Matthew; Davisson, V Jo

    2016-01-01

    While the fragment-based drug design approach continues to gain importance, gaps in the tools and methods available in the identification and accurate utilization of protein subpockets have limited the scope. The importance of these features of small molecule-protein recognition is highlighted with several examples. A generalized solution for the identification of subpockets and corresponding chemical fragments remains elusive, but there are numerous advancements in methods that can be used in combination to address subpockets. Finally, additional examples of approaches that consider the relative importance of small-molecule co-dependence of protein conformations are highlighted to emphasize an increased significance of subpockets, especially at protein interfaces.

  9. Targeted Protein Degradation: from Chemical Biology to Drug Discovery.

    Science.gov (United States)

    Cromm, Philipp M; Crews, Craig M

    2017-09-21

    Traditional pharmaceutical drug discovery is almost exclusively focused on directly controlling protein activity to cure diseases. Modulators of protein activity, especially inhibitors, are developed and applied at high concentration to achieve maximal effects. Thereby, reduced bioavailability and off-target effects can hamper compound efficacy. Nucleic acid-based strategies that control protein function by affecting expression have emerged as an alternative. However, metabolic stability and broad bioavailability represent development hurdles that remain to be overcome for these approaches. More recently, utilizing the cell's own protein destruction machinery for selective degradation of essential drivers of human disorders has opened up a new and exciting area of drug discovery. Small-molecule-induced proteolysis of selected substrates offers the potential of reaching beyond the limitations of the current pharmaceutical paradigm to expand the druggable target space. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Malaria heat shock proteins: drug targets that chaperone other drug targets.

    Science.gov (United States)

    Pesce, E-R; Cockburn, I L; Goble, J L; Stephens, L L; Blatch, G L

    2010-06-01

    Ongoing research into the chaperone systems of malaria parasites, and particularly of Plasmodium falciparum, suggests that heat shock proteins (Hsps) could potentially be an excellent class of drug targets. The P. falciparum genome encodes a vast range and large number of chaperones, including 43 Hsp40, six Hsp70, and three Hsp90 proteins (PfHsp40s, PfHsp70s and PfHsp90s), which are involved in a number of fundamental cellular processes including protein folding and assembly, protein translocation, signal transduction and the cellular stress response. Despite the fact that Hsps are relatively conserved across different species, PfHsps do exhibit a considerable number of unique structural and functional features. One PfHsp90 is thought to be sufficiently different to human Hsp90 to allow for selective targeting. PfHsp70s could potentially be used as drug targets in two ways: either by the specific inhibition of Hsp70s by small molecule modulators, as well as disruption of the interactions between Hsp70s and co-chaperones such as the Hsp70/Hsp90 organising protein (Hop) and Hsp40s. Of the many PfHsp40s present on the parasite, there are certain unique or essential members which are considered to have good potential as drug targets. This review critically evaluates the potential of Hsps as malaria drug targets, as well as the use of chaperones as aids in the heterologous expression of other potential malarial drug targets.

  11. MODELING OF TARGETED DRUG DELIVERY PART II. MULTIPLE DRUG ADMINISTRATION

    Directory of Open Access Journals (Sweden)

    A. V. Zaborovskiy

    2017-01-01

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

  12. Comparative Protein Structure Modeling Using MODELLER.

    Science.gov (United States)

    Webb, Benjamin; Sali, Andrej

    2016-06-20

    Comparative protein structure modeling predicts the three-dimensional structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and how to use the ModBase database of such models, and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described. © 2016 by John Wiley & Sons, Inc.

  13. Prediction and evaluation of protein farnesyltransferase inhibition by commercial drugs

    Science.gov (United States)

    DeGraw, Amanda J.; Keiser, Michael J.; Ochocki, Joshua D.; Shoichet, Brian K.; Distefano, Mark D.

    2010-01-01

    The Similarity Ensemble Approach (SEAa) relates proteins based on the set-wise chemical similarity among their ligands. It can be used to rapidly search large compound databases and to build cross-target similarity maps. The emerging maps relate targets in ways that reveal relationships one might not recognize based on sequence or structural similarities alone. SEA has previously revealed cross talk between drugs acting primarily on G-protein coupled receptors (GPCRs). Here we used SEA to look for potential off-target inhibition of the enzyme protein farnesyltransferase (PFTase) by commercially available drugs. The inhibition of PFTase has profound consequences for oncogenesis, as well as a number of other diseases. In the present study, two commercial drugs, Loratadine and Miconazole, were identified as potential ligands for PFTase and subsequently confirmed as such experimentally. These results point towards the applicability of SEA for the prediction of not only GPCR-GPCR drug cross talk, but also GPCR-enzyme and enzyme-enzyme drug cross talk. PMID:20180535

  14. Novel Technology for Protein-Protein Interaction-based Targeted Drug Discovery

    Directory of Open Access Journals (Sweden)

    Jung Me Hwang

    2011-12-01

    Full Text Available We have developed a simple but highly efficient in-cell protein-protein interaction (PPI discovery system based on the translocation properties of protein kinase C- and its C1a domain in live cells. This system allows the visual detection of trimeric and dimeric protein interactions including cytosolic, nuclear, and/or membrane proteins with their cognate ligands. In addition, this system can be used to identify pharmacological small compounds that inhibit specific PPIs. These properties make this PPI system an attractive tool for screening drug candidates and mapping the protein interactome.

  15. CREDO: a protein-ligand interaction database for drug discovery.

    Science.gov (United States)

    Schreyer, Adrian; Blundell, Tom

    2009-02-01

    Harnessing data from the growing number of protein-ligand complexes in the Protein Data Bank is an important task in drug discovery. In order to benefit from the abundance of three-dimensional structures, structural data must be integrated with sequence as well as chemical data and the protein-small molecule interactions characterized structurally at the inter-atomic level. In this study, we present CREDO, a new publicly available database of protein-ligand interactions, which represents contacts as structural interaction fingerprints, implements novel features and is completely scriptable through its application programming interface. Features of CREDO include implementation of molecular shape descriptors with ultrafast shape recognition, fragmentation of ligands in the Protein Data Bank, sequence-to-structure mapping and the identification of approved drugs. Selected analyses of these key features are presented to highlight a range of potential applications of CREDO. The CREDO dataset has been released into the public domain together with the application programming interface under a Creative Commons license at http://www-cryst.bioc.cam.ac.uk/credo. We believe that the free availability and numerous features of CREDO database will be useful not only for commercial but also for academia-driven drug discovery programmes.

  16. Role of protein-protein interactions in cytochrome P450-mediated drug metabolism and toxicity.

    Science.gov (United States)

    Kandel, Sylvie E; Lampe, Jed N

    2014-09-15

    Through their unique oxidative chemistry, cytochrome P450 monooxygenases (CYPs) catalyze the elimination of most drugs and toxins from the human body. Protein-protein interactions play a critical role in this process. Historically, the study of CYP-protein interactions has focused on their electron transfer partners and allosteric mediators, cytochrome P450 reductase and cytochrome b5. However, CYPs can bind other proteins that also affect CYP function. Some examples include the progesterone receptor membrane component 1, damage resistance protein 1, human and bovine serum albumin, and intestinal fatty acid binding protein, in addition to other CYP isoforms. Furthermore, disruption of these interactions can lead to altered paths of metabolism and the production of toxic metabolites. In this review, we summarize the available evidence for CYP protein-protein interactions from the literature and offer a discussion of the potential impact of future studies aimed at characterizing noncanonical protein-protein interactions with CYP enzymes.

  17. Hybrid protein-synthetic polymer nanoparticles for drug delivery.

    Science.gov (United States)

    Koseva, Neli S; Rydz, Joanna; Stoyanova, Ekaterina V; Mitova, Violeta A

    2015-01-01

    Among the most common nanoparticulate systems, the polymeric nanocarriers have a number of key benefits, which give a great choice of delivery platforms. Nevertheless, polymeric nanoparticles possess some limitations that include use of toxic solvents in the production process, polymer degradation, drug leakage outside the diseased tissue, and polymer cytotoxicity. The combination of polymers of biological and synthetic origin is an appealing modern strategy for the production of novel nanocarriers with unprecedented properties. Proteins' interface can play an important role in determining bioactivity and toxicity and gives perspective for future development of the polymer-based nanoparticles. The design of hybrid constructs composed of synthetic polymer and biological molecules such as proteins can be considered as a straightforward tool to integrate a broad spectrum of properties and biofunctions into a single device. This review discusses hybrid protein-synthetic polymer nanoparticles with different structures and levels in complexity and functionality, in view of their applications as drug delivery systems.

  18. Modelling of proteins in membranes

    DEFF Research Database (Denmark)

    Sperotto, Maria Maddalena; May, S.; Baumgaertner, A.

    2006-01-01

    This review describes some recent theories and simulations of mesoscopic and microscopic models of lipid membranes with embedded or attached proteins. We summarize results supporting our understanding of phenomena for which the activities of proteins in membranes are expected to be significantly ...

  19. From laptop to benchtop to bedside: Structure-based Drug Design on Protein Targets

    OpenAIRE

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

    2012-01-01

    As an important aspect of computer-aided drug design, structure-based drug design brought a new horizon to pharmaceutical development. This in silico method permeates all aspects of drug discovery today, including lead identification, lead optimization, ADMET prediction and drug repurposing. Structure-based drug design has resulted in fruitful successes drug discovery targeting protein-ligand and protein-protein interactions. Meanwhile, challenges, noted by low accuracy and combinatoric issue...

  20. Animal models in drug development for MRSA.

    Science.gov (United States)

    Marra, Andrea

    2014-01-01

    One of the foremost challenges of drug discovery in any therapeutic area is that of solidifying the correlation between in vitro activity and clinical efficacy. Between these is the confirmation that affecting a particular target in vivo will lead to a therapeutic benefit. In antibacterial drug discovery, there is a key advantage from the start, since the targets are bacteria-therefore, it is simple to ascertain in vitro whether a drug has the desired effect, i.e., bacterial cell inhibition or killing, and to understand the mechanism by which that occurs. The downstream criteria, whether a compound reaches the infection site and achieves appropriately high levels to affect bacterial viability, can be evaluated in animal models of infection. In this way animal models of infection can be a highly valuable and predictive bridge between in vitro drug discovery and early clinical evaluation.The Gram-positive pathogen Staphylococcus aureus causes a wide variety of infections in humans (Archer, Clin Infect Dis 26:1179-1181, 1998) and has been said to be able to infect every tissue type. Fortunately, over the years a great deal of effort has been expended toward developing infection models in rodents using this organism, with good success. This chapter will describe the advantages, methods, and outcome measurements of the rodent models most used in drug discovery for S. aureus. Mouse models will be the focus of this chapter, as they are the most economical and thus most commonly used, but a rat infection model is included as well.

  1. Part I---Evaluating Effects of Oligomer Formation on Cytochrome P450 2C9 Electron Transfer and Drug Metabolism, Part II---Utilizing Molecular Modeling Techniques to Study the Src-Interacting Proteins Actin Filament Associated Protein of 110 kDa (AFAP-110) and Cortactin

    Science.gov (United States)

    Jett, John Edward, Jr.

    The dissertation has been divided into two parts to accurately reflect the two distinct areas of interest pursued during my matriculation in the School of Pharmacy at West Virginia University. In Part I, I discuss research probing the nature of electron transfer in the Cytochrome P450 family of proteins, a group of proteins well-known for their role in drug metabolism. In Part II, I focus on in silico and in vitro work developed in concert to probe protein structure and protein-protein interactions involved in actin filament reorganization and cellular motility. Part I. Cytochrome P450s (P450s) are an important class of enzymes known to metabolize a variety of endogenous and xenobiotic compounds. P450s are most commonly found in liver and intestinal endothelial cells and are responsible for the metabolism of approximately 75% of pharmaceutical drugs on the market. CYP2C9---one of the six major P450 isoforms---is responsible for ˜20% of drug metabolism. Elucidation of the factors that affect in vitro drug metabolism is crucial to the accurate prediction of in vivo drug metabolism kinetics. Currently, the two major techniques for studying in vitro drug metabolism are solution-based. However, it is known that the results of solution-based studies can vary from in vivo drug metabolism. One reason suggested to account for this variation is the state of P450 oligomer formation in solution compared to the in vivo environment, where P450s are membrane-bound. To understand the details of how oligomer formation affects in vitro drug metabolism, it is imperative that techniques be developed which will allow for the unequivocal control of oligomer formation without altering other experimental parameters. Our long term goal of this research is to develop methods to more accurately predict in vivo drug metabolism from in vitro data. This section of the dissertation will discuss the development of a platform consisting of a doped silicon surface containing a large array of gold

  2. Animal models of alcohol and drug dependence

    Directory of Open Access Journals (Sweden)

    Cleopatra S. Planeta

    2013-01-01

    Full Text Available Drug addiction has serious health and social consequences. In the last 50 years, a wide range of techniques have been developed to model specific aspects of drug-taking behaviors and have greatly contributed to the understanding of the neurobiological basis of drug abuse and addiction. In the last two decades, new models have been proposed in an attempt to capture the more genuine aspects of addiction-like behaviors in laboratory animals. The goal of the present review is to provide an overview of the preclinical procedures used to study drug abuse and dependence and describe recent progress that has been made in studying more specific aspects of addictive behavior in animals.

  3. Genome evolution predicts genetic interactions in protein complexes and reveals cancer drug targets

    NARCIS (Netherlands)

    Lu, X.; Kensche, P.R.; Huynen, M.A.; Notebaart, R.A.

    2013-01-01

    Genetic interactions reveal insights into cellular function and can be used to identify drug targets. Here we construct a new model to predict negative genetic interactions in protein complexes by exploiting the evolutionary history of genes in parallel converging pathways in metabolism. We evaluate

  4. Drugging the Undruggable: Therapeutic Potential of Targeting Protein Tyrosine Phosphatases.

    Science.gov (United States)

    Zhang, Zhong-Yin

    2017-01-17

    Protein tyrosine phosphatases (PTPs) are essential signaling enzymes that, together with protein tyrosine kinases, regulate tyrosine phosphorylation inside the cell. Proper level of tyrosine phosphorylation is important for a diverse array of cellular processes, such as proliferation, metabolism, motility, and survival. Aberrant tyrosine phosphorylation, resulting from alteration of PTP expression, misregulation, and mutation, has been linked to the etiology of many human ailments including cancer, diabetes/obesity, autoimmune disorders, and infectious diseases. However, despite the fact that PTPs have been garnering attention as compelling drug targets, they remain a largely underexploited resource for therapeutic intervention. Indeed, PTPs have been widely dismissed as "undruggable", due to concerns that (1) the highly conserved active site (i.e., pTyr-binding pocket) makes it difficult to achieve inhibitor selectivity among closely related family members, and (2) the positive-charged active site prefers negatively charged molecules, which usually lack cell permeability. To address the issue of selectivity, we advanced a novel paradigm for the acquisition of highly potent and selective PTP inhibitors through generation of bivalent ligands that interact with both PTP active site and adjacent unique peripheral pockets. To overcome the bioavailability issue, we have identified nonhydrolyzable pTyr mimetics that are sufficiently polar to bind the PTP active site, yet still capable of efficiently penetrating cell membranes. We show that these pTyr mimetics interact in the desired inhibitory fashion with the PTP active site and tethering them to appropriate molecular fragments to engage less conserved interactions outside of PTP active site can increase PTP inhibitor potency and selectivity. We demonstrate through three pTyr mimetics fragment-based approaches that it is completely feasible to obtain highly potent and selective PTP inhibitors with robust in vivo

  5. Coarse-grain modelling of protein-protein interactions

    NARCIS (Netherlands)

    Baaden, Marc; Marrink, Siewert J.

    2013-01-01

    Here, we review recent advances towards the modelling of protein-protein interactions (PPI) at the coarse-grained (CG) level, a technique that is now widely used to understand protein affinity, aggregation and self-assembly behaviour. PPI models of soluble proteins and membrane proteins are separate

  6. Mathematical modelling of magnetically targeted drug delivery

    Energy Technology Data Exchange (ETDEWEB)

    Grief, Andrew D. [Theoretical Mechanics, School of Mathematical Sciences, University of Nottingham, University Park, Nottingham NG7 2RD (United Kingdom)]. E-mail: andrew.grief@nottingham.ac.uk; Richardson, Giles [Theoretical Mechanics, School of Mathematical Sciences, University of Nottingham, University Park, Nottingham NG7 2RD (United Kingdom)]. E-mail: giles.richardson@nottingham.ac.uk

    2005-05-15

    A mathematical model for targeted drug delivery using magnetic particles is developed. This includes a diffusive flux of particles arising from interactions between erythrocytes in the microcirculation. The model is used to track particles in a vessel network. Magnetic field design is discussed and we show that it is impossible to specifically target internal regions using an externally applied field.

  7. An invertebrate model for CNS drug discovery

    DEFF Research Database (Denmark)

    Al-Qadi, Sonia; Schiøtt, Morten; Hansen, Steen Honoré

    2015-01-01

    BACKGROUND: ABC efflux transporters at the blood brain barrier (BBB), namely the P-glycoprotein (P-gp), restrain the development of central nervous system (CNS) drugs. Consequently, early screening of CNS drug candidates is pivotal to identify those affected by efflux activity. Therefore, simple,...... barriers. CONCLUSION: Findings suggest a conserved mechanism of brain efflux activity between insects and vertebrates, confirming that this model holds promise for inexpensive and high-throughput screening relative to in vivo models, for CNS drug discovery......., high-throughput and predictive screening models are required. The grasshopper (locust) has been developed as an invertebrate in situ model for BBB permeability assessment, as it has shown similarities to vertebrate models. METHODS: Transcriptome profiling of ABC efflux transporters in the locust brain......BACKGROUND: ABC efflux transporters at the blood brain barrier (BBB), namely the P-glycoprotein (P-gp), restrain the development of central nervous system (CNS) drugs. Consequently, early screening of CNS drug candidates is pivotal to identify those affected by efflux activity. Therefore, simple...

  8. Protein-protein interactions: principles, techniques, and their potential role in new drug development.

    Science.gov (United States)

    Khan, Shagufta H; Ahmad, Faizan; Ahmad, Nihal; Flynn, Daniel C; Kumar, Raj

    2011-06-01

    A vast network of genes is inter-linked through protein-protein interactions and is critical component of almost every biological process under physiological conditions. Any disruption of the biologically essential network leads to pathological conditions resulting into related diseases. Therefore, proper understanding of biological functions warrants a comprehensive knowledge of protein-protein interactions and the molecular mechanisms that govern such processes. The importance of protein-protein interaction process is highlighted by the fact that a number of powerful techniques/methods have been developed to understand how such interactions take place under various physiological and pathological conditions. Many of the key protein-protein interactions are known to participate in disease-associated signaling pathways, and represent novel targets for therapeutic intervention. Thus, controlling protein-protein interactions offers a rich dividend for the discovery of new drug targets. Availability of various tools to study and the knowledge of human genome have put us in a unique position to understand highly complex biological network, and the mechanisms involved therein. In this review article, we have summarized protein-protein interaction networks, techniques/methods of their binding/kinetic parameters, and the role of these interactions in the development of potential tools for drug designing.

  9. Metabotropic glutamate receptors and interacting proteins: evolving drug targets.

    Science.gov (United States)

    Enz, Ralf

    2012-01-01

    The correct targeting, localization, regulation and signaling of metabotropic glutamate receptors (mGluRs) represent major mechanisms underlying the complex function of neuronal networks. These tasks are accomplished by the formation of synaptic signal complexes that integrate functionally related proteins such as neurotransmitter receptors, enzymes and scaffold proteins. By these means, proteins interacting with mGluRs are important regulators of glutamatergic neurotransmission. Most described mGluR interaction partners bind to the intracellular C-termini of the receptors. These domains are extensively spliced and phosphorylated, resulting in a high variability of binding surfaces offered to interacting proteins. Malfunction of mGluRs and associated proteins are linked to neurodegenerative and neuropsychiatric disorders including addiction, depression, epilepsy, schizophrenia, Alzheimer's, Huntington's and Parkinson's disease. MGluR associated signal complexes are dynamic structures that assemble and disassemble in response to the neuronal fate. This, in principle, allows therapeutic intervention, defining mGluRs and interacting proteins as promising drug targets. In the last years, several studies elucidated the geometry of mGluRs in contact with regulatory proteins, providing a solid fundament for the development of new therapeutic strategies. Here, I will give an overview of human disorders directly associated with mGluR malfunction, provide an up-to-date summary of mGluR interacting proteins and highlight recently described structures of mGluR domains in contact with binding partners.

  10. Packaging protein drugs as bacterial inclusion bodies for therapeutic applications

    Directory of Open Access Journals (Sweden)

    Villaverde Antonio

    2012-06-01

    Full Text Available Abstract A growing number of insights on the biology of bacterial inclusion bodies (IBs have revealed intriguing utilities of these protein particles. Since they combine mechanical stability and protein functionality, IBs have been already exploited in biocatalysis and explored for bottom-up topographical modification in tissue engineering. Being fully biocompatible and with tuneable bio-physical properties, IBs are currently emerging as agents for protein delivery into mammalian cells in protein-replacement cell therapies. So far, IBs formed by chaperones (heat shock protein 70, Hsp70, enzymes (catalase and dihydrofolate reductase, grow factors (leukemia inhibitory factor, LIF and structural proteins (the cytoskeleton keratin 14 have been shown to rescue exposed cells from a spectrum of stresses and restore cell functions in absence of cytotoxicity. The natural penetrability of IBs into mammalian cells (reaching both cytoplasm and nucleus empowers them as an unexpected platform for the controlled delivery of essentially any therapeutic polypeptide. Production of protein drugs by biopharma has been traditionally challenged by IB formation. However, a time might have arrived in which recombinant bacteria are to be engineered for the controlled packaging of therapeutic proteins as nanoparticulate materials (nanopills, for their extra- or intra-cellular release in medicine and cosmetics.

  11. Beyond Membrane Protein Structure: Drug Discovery, Dynamics and Difficulties.

    Science.gov (United States)

    Biggin, Philip C; Aldeghi, Matteo; Bodkin, Michael J; Heifetz, Alexander

    2016-01-01

    Most of the previous content of this book has focused on obtaining the structures of membrane proteins. In this chapter we explore how those structures can be further used in two key ways. The first is their use in structure based drug design (SBDD) and the second is how they can be used to extend our understanding of their functional activity via the use of molecular dynamics. Both aspects now heavily rely on computations. This area is vast, and alas, too large to consider in depth in a single book chapter. Thus where appropriate we have referred the reader to recent reviews for deeper assessment of the field. We discuss progress via the use of examples from two main drug target areas; G-protein coupled receptors (GPCRs) and ion channels. We end with a discussion of some of the main challenges in the area.

  12. Modelling and enhanced molecular dynamics to steer structure-based drug discovery.

    Science.gov (United States)

    Kalyaanamoorthy, Subha; Chen, Yi-Ping Phoebe

    2014-05-01

    The ever-increasing gap between the availabilities of the genome sequences and the crystal structures of proteins remains one of the significant challenges to the modern drug discovery efforts. The knowledge of structure-dynamics-functionalities of proteins is important in order to understand several key aspects of structure-based drug discovery, such as drug-protein interactions, drug binding and unbinding mechanisms and protein-protein interactions. This review presents a brief overview on the different state of the art computational approaches that are applied for protein structure modelling and molecular dynamics simulations of biological systems. We give an essence of how different enhanced sampling molecular dynamics approaches, together with regular molecular dynamics methods, assist in steering the structure based drug discovery processes.

  13. Inactivation of indispensable bacterial proteins by early proteins of bacteriophages: implication in antibacterial drug discovery.

    Science.gov (United States)

    Sau, S; Chattoraj, P; Ganguly, T; Chanda, P K; Mandal, N C

    2008-06-01

    Bacteriophages utilize host bacterial cellular machineries for their own reproduction and completion of life cycles. The early proteins that phage synthesize immediately after the entry of their genomes into bacterial cells participate in inhibiting host macromolecular biosynthesis, initiating phage-specific replication and synthesizing late proteins. Inhibition of synthesis of host macromolecules that eventually leads to cell death is generally performed by the physical and/or chemical modification of indispensable host proteins by early proteins. Interestingly, most modified bacterial proteins were shown to take part actively in phage-specific transcription and replication. Research on phages in last nine decades has demonstrated such lethal early proteins that interact with or chemically modify indispensable host proteins. Among the host proteins inhibited by lethal phage proteins, several are not inhibited by any chemical inhibitor available today. Under the context of widespread dissemination of antibiotic-resistant strains of pathogenic bacteria in recent years, the information of lethal phage proteins and cognate host proteins could be extremely invaluable as they may lead to the identification of novel antibacterial compounds. In this review, we summarize the current knowledge about some early phage proteins, their cognate host proteins and their mechanism of action and also describe how the above interacting proteins had been exploited in antibacterial drug discovery.

  14. Prediction of Effective Drug Combinations by Chemical Interaction, Protein Interaction and Target Enrichment of KEGG Pathways

    Directory of Open Access Journals (Sweden)

    Lei Chen

    2013-01-01

    Full Text Available Drug combinatorial therapy could be more effective in treating some complex diseases than single agents due to better efficacy and reduced side effects. Although some drug combinations are being used, their underlying molecular mechanisms are still poorly understood. Therefore, it is of great interest to deduce a novel drug combination by their molecular mechanisms in a robust and rigorous way. This paper attempts to predict effective drug combinations by a combined consideration of: (1 chemical interaction between drugs, (2 protein interactions between drugs’ targets, and (3 target enrichment of KEGG pathways. A benchmark dataset was constructed, consisting of 121 confirmed effective combinations and 605 random combinations. Each drug combination was represented by 465 features derived from the aforementioned three properties. Some feature selection techniques, including Minimum Redundancy Maximum Relevance and Incremental Feature Selection, were adopted to extract the key features. Random forest model was built with its performance evaluated by 5-fold cross-validation. As a result, 55 key features providing the best prediction result were selected. These important features may help to gain insights into the mechanisms of drug combinations, and the proposed prediction model could become a useful tool for screening possible drug combinations.

  15. Homology modeling: an important tool for the drug discovery.

    Science.gov (United States)

    França, Tanos Celmar Costa

    2015-01-01

    In the last decades, homology modeling has become a popular tool to access theoretical three-dimensional (3D) structures of molecular targets. So far several 3D models of proteins have been built by this technique and used in a great diversity of structural biology studies. But are those models consistent enough with experimental structures to make this technique an effective and reliable tool for drug discovery? Here we present, briefly, the fundamentals and current state-of-the-art of the homology modeling techniques used to build 3D structures of molecular targets, which experimental structures are not available in databases, and list some of the more important works, using this technique, available in literature today. In many cases those studies have afforded successful models for the drug design of more selective agonists/antagonists to the molecular targets in focus and guided promising experimental works, proving that, when the appropriate templates are available, useful models can be built using some of the several software available today for this purpose. Limitations of the experimental techniques used to solve 3D structures allied to constant improvements in the homology modeling software will maintain the need for theoretical models, establishing the homology modeling as a fundamental tool for the drug discovery.

  16. Transgenic chickens as bioreactors for protein-based drugs.

    Science.gov (United States)

    Lillico, Simon G; McGrew, Michael J; Sherman, Adrian; Sang, Helen M

    2005-02-01

    The potential of using transgenic animals for the synthesis of therapeutic proteins was suggested over twenty years ago. Considerable progress has been made in developing methods for the production of transgenic animals and specifically in the expression of therapeutic proteins in the mammary glands of cows, sheep and goats. Development of transgenic hens for protein production in eggs has lagged behind these systems. The positive features associated with the use of the chicken in terms of cost, speed of development of a production flock and potentially appropriate glycosylation of target proteins have led to significant advances in transgenic chicken models in the past few years.

  17. Thioxylated cyclosporin A for studying protein-drug interactions.

    Science.gov (United States)

    Lin, Weilin; Erdmann, Frank; Quintero, Andres; Fischer, Gunter; Zhang, Yixin

    2016-12-01

    Single atom substitution of cyclosporin A (CsA) through thioxylation has been used to study the structure-activity relationship of the immunosuppressive complex, involving the CsA receptor protein cyclophilin 18 (Cyp18) and the immunological target protein phosphatase calcineurin (CaN), illustrating the contributions of peptide backbone in protein-drug interaction. Moreover, the subtle difference between thioxylation positions in CsA has led to a remarkable change in the quenching effect on Cyp18 intrinsic fluorescence. Using the thioxylated compound Cs7 as an isosteric derivative of CsA in competition assay, the experiment has led to the determination of koff value in solution. Whereas the conformational heterogeneity of CsA has been found to be associated with its two-phase binding kinetics to Cyp18, the dissociation rate of CsA from complex is independent from the initial ligand structure. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Profiling of drug binding proteins by monolithic affinity chromatography in combination with liquid chromatography-tandem mass spectrometry.

    Science.gov (United States)

    Zhang, Xuepei; Wang, Tongdan; Zhang, Hanzhi; Han, Bing; Wang, Lishun; Kang, Jingwu

    2014-09-12

    A new approach for proteome-wide profiling drug binding proteins by using monolithic capillary affinity chromatography in combination with HPLC-MS/MS is reported. Two immunosuppresive drugs, namely FK506 and cyclosporin A, were utilized as the experimental models for proof-of-concept. The monolithic capillary affinity columns were prepared through a single-step copolymerization of the drug derivatives with glycidyl methacrylate and ethylene dimethacrylate. The capillary chromatography with the affinity monolithic column facilitates the purification of the drug binding proteins from the cell lysate. By combining the capillary affinity column purification and the shot-gun proteomic analysis, totally 33 FK506- and 32 CsA-binding proteins including all the literature reported target proteins of these two drugs were identified. Among them, two proteins, namely voltage-dependent anion-selective channel protein 1 and serine/threonine-protein phosphatase PGAM5 were verified by using the recombinant proteins. The result supports that the monolithic capillary affinity chromatography is likely to become a valuable tool for profiling of binding proteins of small molecular drugs as well as bioactive compounds.

  19. Polysaccharides-based polyelectrolyte nanoparticles as protein drugs delivery system

    Energy Technology Data Exchange (ETDEWEB)

    Shu Shujun; Sun Lei; Zhang Xinge, E-mail: zhangxinge@nankai.edu.cn [Nankai University, Key Laboratory of Functional Polymer Materials Ministry of Education, Institute of Polymer Chemistry (China); Wu Zhongming [Tianjin Medical University, Metabolic Diseases Hospital (China); Wang Zhen; Li Chaoxing, E-mail: lcx@nankai.edu.cn [Nankai University, Key Laboratory of Functional Polymer Materials Ministry of Education, Institute of Polymer Chemistry (China)

    2011-09-15

    Polysaccharides-based nanoparticles were prepared by synthesized quaternized chitosan and dextran sulfate through simple ionic-gelation self-assembled method. Introduction of quaternized groups was intended to increase water solubility of chitosan and make the nanoparticles have broader pH sensitive range which can remain more stable in physiological pH and decrease the loss of protein drugs caused by the gastric cavity. The load of BSA was affected by molecular parameter, i.e., degree of substitution, and average molecular weight of quaternized chitosan, as well as concentration of BSA. Fast release occurred in phosphate buffer solution (pH 7.4) while the release was slow in hydrochloric acid (pH 1.4). The drug release mechanism is Fickian diffusion through release kinetics analysis. Cell uptake demonstrated nanoparicles can internalize into Caco-2 cells, which suggested that nanoparticles had good biocompatibility. No significant conformation change was noted for the released BSA in comparison with native BSA using circular dichroism spectroscopy. This kind of novel composite nanoparticles may be a promising delivery system for oral protein and peptide drugs.

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

    Directory of Open Access Journals (Sweden)

    Montiago X LaBute

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

  1. Triggered drug release from dynamic microspheres via a protein conformational change.

    Science.gov (United States)

    King, William J; Pytel, Nicholas J; Ng, Kelvin; Murphy, William L

    2010-06-11

    In this study we formed and characterized dynamic hydrogel microspheres in which a protein conformational change was used to control microsphere volume changes and the release of an encapsulated drug. In particular, a specific biochemical ligand, trifluoperazine, induced calmodulin's nanometer scale conformation change, which translated to a 48.7% microsphere volume decrease. This specific, ligand-induced volume change triggered the release of a model drug, vascular endothelial growth factor (VEGF), at pre-determined times. After release from the microspheres, 85.6 +/- 10.5% of VEGF was in its native conformation. Taken together, these results suggest that protein conformational change could serve as a useful mechanism to control drug release from dynamic hydrogels.

  2. In Vitro Cytotoxicity and Protein Drug Release Properties of Chitosan/Heparin Microspheres

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Chitosan/heparin microspheres were prepared using the water-in-oil emulsification solvent evaporation technique. The microsphere diameters were controlled by selecting the fabrication process parameters. Scanning electron micrographs showed that the chitosan/heparin microspheres were regular and the surface morphology was smooth. Fourier transform infrared showed that the chitosan amino groups reacted with heparin carboxylic groups to form acylamides in the microspheres. Analysis of the microsphere cytotoxicity showed that they had no cytotoxic effect and behaved very similar to the negative control (polystyrene).To analyze the protein drug release profiles of the microspheres, bovine serum albumin was loaded as a model drug into the microspheres and released in vitro. Marked retardation was observed in the BSA release profiles. The results show that chitosan/heparin microspheres may provide a useful controlled release protein drug system for used in pharmaceutics.

  3. Electrochemistry-mass spectrometry in drug metabolism and protein research.

    Science.gov (United States)

    Permentier, Hjalmar P; Bruins, Andries P; Bischoff, Rainer

    2008-01-01

    The combination of electrochemistry coupled on-line to mass spectrometry (EC-MS) forms a powerful analytical technique with unique applications in the fields of drug metabolism and proteomics. In this review the latest developments are surveyed from both instrumental and application perspectives. The limitations and solutions for coupling an electrochemical system to a mass spectrometer are discussed. The electrochemical mimicking of drug metabolism, specifically by Cytochrome P450, is high-lighted as an application with high biomedical relevance. The EC-MS analysis of proteins also has promising new applications for both proteomics research and biomarker discovery. EC-MS has furthermore advantages for improved analyte detection with mass spectrometry, both for small molecules and large biomolecules. Finally, potential future directions of development of the technique are briefly discussed.

  4. Small-molecule stabilization of protein-protein interactions: an underestimated concept in drug discovery?

    Science.gov (United States)

    Thiel, Philipp; Kaiser, Markus; Ottmann, Christian

    2012-02-27

    The modulation of protein-protein interactions (PPIs) has been recognized as one of the most challenging tasks in drug discovery. While their systematic development has long been considered as intractable, this view has changed over the last years, with the first drug candidates undergoing clinical studies. To date, the vast majority of PPI modulators are interaction inhibitors. However, in many biological contexts a prolonged lifespan of a PPI might be desirable, calling for the complementary approach of PPI stabilization. In fact, nature offers impressive examples of this concept and some PPI-stabilizing natural products have already found application as important drugs. Moreover, directed small-molecule stabilization has recently been demonstrated. Therefore, it is time to take a closer look at the constructive side of modulating PPIs. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Multifunctional Electrospun Nanofibers Incorporated with an Anti-infection Drug and Immobilized with Proteins

    Science.gov (United States)

    Zhou, Shufei

    Electrospinning has been used to fabricate ultrafine fibers with sizes ranging from nano to micrometers. Nanofibers electrospun from biocompatible and biodegradable polymers have been extensively investigated for their potential applications in wound healing and tissue regeneration. These nanofiber materials can be modified to incorporate bioactive molecules, such as antibacterial agents that provide infection control, or functional proteins which promote cell proliferation and tissue reconstruction. Despite the numerous studies on the development and design of nanofibers for biomedical applications, there has been little research on multifunctional nanofibers that are incorporated with both antibacterial drug(s) and bioactive proteins. The objective of the current study is, therefore, to develop nanofibers that are functionalized by several bioactive molecules. In this study, electrospinning was utilized to fabricate nanofibers from biodegradable polymers PLLA (Poly-L-lactide) and the copolymer PLLA-PEG (Polyethylene glycol)-NH2.A water soluble antibiotic drug, Tetracycline Hydrochloride (TCH), was incorporated into the electrospun nanofibers via emulsion electrospinning. The TCH-loaded nanofibers were surface modified to produce functional groups that can be further conjugated with a model protein, Bovine Serum Albumin (BSA).Drug releasing profiles of the medicated nanofibers were monitored and their antimicrobial properties were evaluated. Proteins (BSAs) immobilized on the fiber surface were verified by ATR-FTIR. The number of immobilized BSAs was determined using a UV-Vis spectrophotometer. The results of the study suggested that this multifunctional nanofibrous material could be a promising material for wound dressing or scaffolds for tissue engineering.

  6. Injectable, thermo-reversible and complex coacervate combination gels for protein drug delivery.

    Science.gov (United States)

    Jin, Kwang-Mi; Kim, Yong-Hee

    2008-05-01

    Injectable and thermo-reversible physical combination gels were formed in aqueous solution by preparing complex coacervate with two oppositely charged biomacromolecules that composed of negatively charged chondroitin 6-sulfate and positively charged high molecular weight gelatin type A and co-formulating with a negative, thermo-sensitive polysaccharide, methylcellulose containing a salting-out salt, ammonium sulfate. The combination of complex coacervation and a thermo-reversible gel demonstrated synergistic effects on the complex coacervate formation the release rates of model proteins and in situ gel depot formation. Gels indicated sustained release patterns of the protein over 25 days with minimal initial bursts. Optimized novel in situ gel depot systems containing dual advantages of complex coacervation and temperature responsiveness demonstrated a potential for efficient protein drug delivery in terms of high protein loading, sustained protein release, ease of administration, an aqueous environment without toxic organic solvents, and a simple fabrication method.

  7. Microstructured dextran hydrogels for burst-free sustained release of PEGylated protein drugs.

    Science.gov (United States)

    Bae, Ki Hyun; Lee, Fan; Xu, Keming; Keng, Choong Tat; Tan, Sue Yee; Tan, Yee Joo; Chen, Qingfeng; Kurisawa, Motoichi

    2015-09-01

    Hydrogels have gained significant attention as ideal delivery vehicles for protein drugs. However, the use of hydrogels for protein delivery has been restricted because their porous structures inevitably cause a premature leakage of encapsulated proteins. Here, we report a simple yet effective approach to regulate the protein release kinetics of hydrogels through the creation of microstructures, which serve as a reservoir, releasing their payloads in a controlled manner. Microstructured dextran hydrogels enable burst-free sustained release of PEGylated interferon over 3 months without compromising its bioactivity. These hydrogels substantially extend the circulation half-life of PEGylated interferon, allowing for less frequent dosing in a humanized mouse model of hepatitis C. The present approach opens up possibilities for the development of sustained protein delivery systems for a broad range of pharmaceutical and biomedical applications.

  8. Stabilization of Protein-Protein Interactions in chemical biology and drug discovery.

    Science.gov (United States)

    Bier, David; Thiel, Philipp; Briels, Jeroen; Ottmann, Christian

    2015-10-01

    More than 300,000 Protein-Protein Interactions (PPIs) can be found in human cells. This number is significantly larger than the number of single proteins, which are the classical targets for pharmacological intervention. Hence, specific and potent modulation of PPIs by small, drug-like molecules would tremendously enlarge the "druggable genome" enabling novel ways of drug discovery for essentially every human disease. This strategy is especially promising in diseases with difficult targets like intrinsically disordered proteins or transcription factors, for example neurodegeneration or metabolic diseases. Whereas the potential of PPI modulation has been recognized in terms of the development of inhibitors that disrupt or prevent a binary protein complex, the opposite (or complementary) strategy to stabilize PPIs has not yet been realized in a systematic manner. This fact is rather surprising given the number of impressive natural product examples that confer their activity by stabilizing specific PPIs. In addition, in recent years more and more examples of synthetic molecules are being published that work as PPI stabilizers, despite the fact that in the majority they initially have not been designed as such. Here, we describe examples from both the natural products as well as the synthetic molecules advocating for a stronger consideration of the PPI stabilization approach in chemical biology and drug discovery. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Drug-Protein Interactions for Clinical Research by Nucleic Acid Programmable Protein Arrays-Quartz Crystal Microbalance with Dissipation Factor Monitoring Nanoconductometric Assay

    Directory of Open Access Journals (Sweden)

    Claudio Nicolini

    2014-01-01

    Full Text Available Conductometric monitoring of drug-gene and drug-protein interactions is of fundamental importance in the field of molecular pharmacology. Here, we present our main findings and characterizations of an important antiblastic used in neuro-oncology (Temozolomide, interacting with selected proteins that represent predictive biomarkers of the rate survival of the patients, of the outcome of chemotherapy and resistance to drug itself (namely, BRIP1 and MLH1. We use our previously introduced two genes along with previously described Nucleic Acid Programmable Protein Arrays (NAPPA-based nanoconductometric sensor. We performed a positive control (Temozolomide plus MLH1 protein, a negative control (Temozolomide plus BRIP1 protein and a multi-gene experiment (Temozolomide plus BRIP1&MLH1 being co-expressed, showing that we are able to properly perform pharmacoproteomics tasks, discriminating each protein and drug unique conductance curve as well as their interactions, even in the presence of multi-proteins being immobilized. Moreover, in the last part of our paper, we used a multiple regression model in order to predict the behavior of Temozolomide when exposed to BRIP1&MLH1 co-expressed and we showed that we are able to predict the drug-protein interaction profile with a good regression coefficient.

  10. Modeling drug- and chemical- induced hepatotoxicity with systems biology approaches

    Directory of Open Access Journals (Sweden)

    Sudin eBhattacharya

    2012-12-01

    Full Text Available We provide an overview of computational systems biology approaches as applied to the study of chemical- and drug-induced toxicity. The concept of ‘toxicity pathways’ is described in the context of the 2007 US National Academies of Science report, Toxicity testing in the 21st Century: A Vision and A Strategy. Pathway mapping and modeling based on network biology concepts are a key component of the vision laid out in this report for a more biologically-based analysis of dose-response behavior and the safety of chemicals and drugs. We focus on toxicity of the liver (hepatotoxicity – a complex phenotypic response with contributions from a number of different cell types and biological processes. We describe three case studies of complementary multi-scale computational modeling approaches to understand perturbation of toxicity pathways in the human liver as a result of exposure to environmental contaminants and specific drugs. One approach involves development of a spatial, multicellular virtual tissue model of the liver lobule that combines molecular circuits in individual hepatocytes with cell-cell interactions and blood-mediated transport of toxicants through hepatic sinusoids, to enable quantitative, mechanistic prediction of hepatic dose-response for activation of the AhR toxicity pathway. Simultaneously, methods are being developing to extract quantitative maps of intracellular signaling and transcriptional regulatory networks perturbed by environmental contaminants, using a combination of gene expression and genome-wide protein-DNA interaction data. A predictive physiological model (DILIsymTM to understand drug-induced liver injury (DILI, the most common adverse event leading to termination of clinical development programs and regulatory actions on drugs, is also described. The model initially focuses on reactive metabolite-induced DILI in response to administration of acetaminophen, and spans multiple biological scales.

  11. High-Throughput Screening for Drugs that Modulate Intermediate Filament Proteins.

    Science.gov (United States)

    Sun, Jingyuan; Groppi, Vincent E; Gui, Honglian; Chen, Lu; Xie, Qing; Liu, Li; Omary, M Bishr

    2016-01-01

    Intermediate filament (IF) proteins have unique and complex cell and tissue distribution. Importantly, IF gene mutations cause or predispose to more than 80 human tissue-specific diseases (IF-pathies), with the most severe disease phenotypes being due to mutations at conserved residues that result in a disrupted IF network. A critical need for the entire IF-pathy field is the identification of drugs that can ameliorate or cure these diseases, particularly since all current therapies target the IF-pathy complication, such as diabetes or cardiovascular disease, rather than the mutant IF protein or gene. We describe a high-throughput approach to identify drugs that can normalize disrupted IF proteins. This approach utilizes transduction of lentivirus that expresses green fluorescent protein-tagged keratin 18 (K18) R90C in A549 cells. The readout is drug "hits" that convert the dot-like keratin filament distribution, due to the R90C mutation, to a wild-type-like filamentous array. A similar strategy can be used to screen thousands of compounds and can be utilized for practically any IF protein with a filament-disrupting mutation, and could therefore potentially target many IF-pathies. "Hits" of interest require validation in cell culture then using in vivo experimental models. Approaches to study the mechanism of mutant IF normalization by potential drugs of interest are also described. The ultimate goal of this drug screening approach is to identify effective and safe compounds that can potentially be tested for clinical efficacy in patients.

  12. Bayesian hierarchical modeling of drug stability data.

    Science.gov (United States)

    Chen, Jie; Zhong, Jinglin; Nie, Lei

    2008-06-15

    Stability data are commonly analyzed using linear fixed or random effect model. The linear fixed effect model does not take into account the batch-to-batch variation, whereas the random effect model may suffer from the unreliable shelf-life estimates due to small sample size. Moreover, both methods do not utilize any prior information that might have been available. In this article, we propose a Bayesian hierarchical approach to modeling drug stability data. Under this hierarchical structure, we first use Bayes factor to test the poolability of batches. Given the decision on poolability of batches, we then estimate the shelf-life that applies to all batches. The approach is illustrated with two example data sets and its performance is compared in simulation studies with that of the commonly used frequentist methods. (c) 2008 John Wiley & Sons, Ltd.

  13. Modelling Simple Experimental Platform for In Vitro Study of Drug Elution from Drug Eluting Stents (DES)

    Science.gov (United States)

    Kalachev, L. V.

    2016-06-01

    We present a simple model of experimental setup for in vitro study of drug release from drug eluting stents and drug propagation in artificial tissue samples representing blood vessels. The model is further reduced using the assumption on vastly different characteristic diffusion times in the stent coating and in the artificial tissue. The model is used to derive a relationship between the times at which the measurements have to be taken for two experimental platforms, with corresponding artificial tissue samples made of different materials with different drug diffusion coefficients, to properly compare the drug release characteristics of drug eluting stents.

  14. A Novel Model for Protein Immobilization on Microspheres

    Institute of Scientific and Technical Information of China (English)

    WANG Di-qiang; LIU Bai-ling; LI He; HU Jie

    2004-01-01

    The immobilization of proteins, especially receptor proteins commonly used in high through-put screening of drugs (HTS), have received great attention in recent years. There are many successful isothermal models for describing the adsorption of protein onto solid surface, such as Langmuir model, Bi-Langmuir model, Fowler model, Freundlich model, Freundlich-Langmuir model and Tekmin model etc. In all these models, Langmuir model was the most favorable one model accepted by many researchers, but the experimental results showed that it was not entirely fit to all adsorption behaviors. So new models were required for describing protein adsorption onto microspheres in different conditions.In our research, a novel isothermal model, including Langmuir and other adsorbing behaviors was presented basing on the holding degree of surface active sites and the interaction styles of protein immobilization. In Langmuir model, the adsorbing amount of protein was described as [PS] =Km[P]/1 + K[P], where [PS] was the concentration of adsorbed protein, [P] was the concentration of freeprotein at equilibrium state, and Km and K was constant. According to the interactions of protein and ligands, there were three patterns in the interactions of protein and ligands. On the similar assumption that the interaction of protein and microspheres were three styles, and based on the definition of the holding degree of surface active sites (Y), three adsorption behaviors could be described as Y K[ P ]φ/ K[P]φ+1 or ln K + φ ln[P] =ln(Y/1-Y) in which [P] was the concentration of free protein at equilibrium state, and φ and K was constant. Different scale of φ presented different adsorption behaviors, especially when φ was 1, the adsorption behavior was Langmuir adsorbing model. Figure I indicated the different adsorbing results in different adsorption behaviors (φ>1, φ<1,and φ=1).

  15. A Quantitative Model to Estimate Drug Resistance in Pathogens

    Directory of Open Access Journals (Sweden)

    Frazier N. Baker

    2016-12-01

    Full Text Available Pneumocystis pneumonia (PCP is an opportunistic infection that occurs in humans and other mammals with debilitated immune systems. These infections are caused by fungi in the genus Pneumocystis, which are not susceptible to standard antifungal agents. Despite decades of research and drug development, the primary treatment and prophylaxis for PCP remains a combination of trimethoprim (TMP and sulfamethoxazole (SMX that targets two enzymes in folic acid biosynthesis, dihydrofolate reductase (DHFR and dihydropteroate synthase (DHPS, respectively. There is growing evidence of emerging resistance by Pneumocystis jirovecii (the species that infects humans to TMP-SMX associated with mutations in the targeted enzymes. In the present study, we report the development of an accurate quantitative model to predict changes in the binding affinity of inhibitors (Ki, IC50 to the mutated proteins. The model is based on evolutionary information and amino acid covariance analysis. Predicted changes in binding affinity upon mutations highly correlate with the experimentally measured data. While trained on Pneumocystis jirovecii DHFR/TMP data, the model shows similar or better performance when evaluated on the resistance data for a different inhibitor of PjDFHR, another drug/target pair (PjDHPS/SMX and another organism (Staphylococcus aureus DHFR/TMP. Therefore, we anticipate that the developed prediction model will be useful in the evaluation of possible resistance of the newly sequenced variants of the pathogen and can be extended to other drug targets and organisms.

  16. Modeling HIV-1 drug resistance as episodic directional selection.

    Directory of Open Access Journals (Sweden)

    Ben Murrell

    Full Text Available The evolution of substitutions conferring drug resistance to HIV-1 is both episodic, occurring when patients are on antiretroviral therapy, and strongly directional, with site-specific resistant residues increasing in frequency over time. While methods exist to detect episodic diversifying selection and continuous directional selection, no evolutionary model combining these two properties has been proposed. We present two models of episodic directional selection (MEDS and EDEPS which allow the a priori specification of lineages expected to have undergone directional selection. The models infer the sites and target residues that were likely subject to directional selection, using either codon or protein sequences. Compared to its null model of episodic diversifying selection, MEDS provides a superior fit to most sites known to be involved in drug resistance, and neither one test for episodic diversifying selection nor another for constant directional selection are able to detect as many true positives as MEDS and EDEPS while maintaining acceptable levels of false positives. This suggests that episodic directional selection is a better description of the process driving the evolution of drug resistance.

  17. Role of Nanotechnology in Delivery of Protein and Peptide Drugs.

    Science.gov (United States)

    Patil, Sushilkumar; Vhora, Imran; Amrutiya, Jitendra; Lalani, Rohan; Misra, Ambikanandan

    2015-01-01

    The advent of recombinant DNA technology and computational designing has fueled the emergence of proteins and peptides as a new class of modern therapeutics such as vaccines, antigens, antibodies and hormones. Demand for such therapeutics has increased recently due to their distinct pharmacodynamic characteristics of specificity of action and high potency. However, their potential clinical applications are often hindered by involvement of factors which impact their therapeutic potential negatively. Large size, low permeability, conformational fragility, immunogenicity, metabolic degradation and short half-life results in poor bioavailability and inferior efficacy. These challenges have encouraged researchers to devise strategies for effective delivery of proteins and peptides. Recent advances made in nanotechnology are being sought to overcome aforesaid problems and to offer advantages such as higher drug loading, improved stability, sustained release, amenability for non-parenteral administration and targeting through surface modifications. This review focuses on elaborating the role of nanotechnology based formulations and associated challenges in protein and peptide delivery, their clinical outlook and future perspective.

  18. Protein crystallography and drug discovery: recollections of knowledge exchange between academia and industry

    Directory of Open Access Journals (Sweden)

    Tom L. Blundell

    2017-07-01

    Full Text Available The development of structure-guided drug discovery is a story of knowledge exchange where new ideas originate from all parts of the research ecosystem. Dorothy Crowfoot Hodgkin obtained insulin from Boots Pure Drug Company in the 1930s and insulin crystallization was optimized in the company Novo in the 1950s, allowing the structure to be determined at Oxford University. The structure of renin was developed in academia, on this occasion in London, in response to a need to develop antihypertensives in pharma. The idea of a dimeric aspartic protease came from an international academic team and was discovered in HIV; it eventually led to new HIV antivirals being developed in industry. Structure-guided fragment-based discovery was developed in large pharma and biotechs, but has been exploited in academia for the development of new inhibitors targeting protein–protein interactions and also antimicrobials to combat mycobacterial infections such as tuberculosis. These observations provide a strong argument against the so-called `linear model', where ideas flow only in one direction from academic institutions to industry. Structure-guided drug discovery is a story of applications of protein crystallography and knowledge exhange between academia and industry that has led to new drug approvals for cancer and other common medical conditions by the Food and Drug Administration in the USA, as well as hope for the treatment of rare genetic diseases and infectious diseases that are a particular challenge in the developing world.

  19. Vaccinia complement control protein: Multi-functional protein and a potential wonder drug

    Indian Academy of Sciences (India)

    Purushottam Jha; Girish J Kotwal

    2003-04-01

    Vaccinia virus complement control protein (VCP) was one of the first viral molecules demonstrated to have a role in blocking complement and hence in the evasion of host defense. Structurally it is very similar to the human C4b-BP and the other members of complement control protein. Functionally it is most similar to the CR1 protein. VCP blocks both major pathways of complement activation. The crystal structure of VCP was determined a little over a year ago and it is the only known structure of an intact and complete complement control protein. In addition to binding complement, VCP also binds to heparin. These two binding abilities can take place simultaneously and contribute to its many function and to its potential use in several inflammatory diseases, e.g. Alzheimer’s disease (AD), CNS injury, xenotransplantation, etc. making it a truly fascinating molecule and potential drug.

  20. Microdialysis-liquid chromatographic study on competitive binding of drugs to protein

    Institute of Scientific and Technical Information of China (English)

    汪海林; 邹汉法; 张玉奎

    1997-01-01

    A new method to determine the interaction between drug and protein has been developed by utilizing the technique of microdialysis sampling with the ketoprofen and the human serum albumin (HSA) as the model of drug and protein.Two kinds of binding sites of HSA to ketoprofen have been observed.The binding constants and number of binding sites obtained by the Scatchard equation are 0.799,3.18×106 mol-1 L and 2.15,2.01×105 mol-1 L,respectively The displacement binding of drugs to HSA has also been studied.The strong displacement of competitive binding of ibuprofen with ketoprofen to HSA was observed,which means that the primary binding site of HSA to ketoprofen and that to ibuprofen are the same.However,only a weaker displacement of warfarin for the association of ketoprofen with HSA was observed,which may suggest that the primary binding site of HSA to ketoprofen is different from that to warfarin.Such a displacement effect for competitive binding of drugs to HSA was explained by the displacement model i

  1. A Learning Model for Drug Dependent Behaviors.

    Science.gov (United States)

    Bremkamp, Steven

    1982-01-01

    Presents the complex factors, i.e., social determinants, drug types, personality characteristics, reasons for drug use and misuse, which characterize the drug experience. Defines awareness of these characteristics as a developmental approach to treatment and prevention of addiction. (RC)

  2. Exploiting Large-Scale Drug-Protein Interaction Information for Computational Drug Repurposing

    Science.gov (United States)

    2014-06-20

    advantages and disadvantages of different model training processes, we needed to use diseases with a sig- nificant number of approved drugs. For...to the parasite. The formation of hemozoin is a parasite detoxification pathway. Quinolones with fused bicyclic aromatic rings bind well with heme...bRef. [26]. Liu et al. BMC Bioinformatics 2014, 15:210 Page 11 of 16 http://www.biomedcentral.com/1471-2105/15/210 not have a fused bicyclic

  3. Induction of drug efflux protein expression by venlafaxine but not desvenlafaxine.

    Science.gov (United States)

    Bachmeier, Corbin J; Beaulieu-Abdelahad, David; Ganey, Nowell J; Mullan, Michael J; Levin, Gary M

    2011-05-01

    Venlafaxine and its metabolite desvenlafaxine are serotonin-norepinephrine reuptake inhibitors currently prescribed for the treatment of depression. Previously, it was reported that venlafaxine is an inducer of MDR1, the gene responsible for P-glycoprotein (P-gp). The present study expanded upon these findings by examining the effect of venlafaxine and desvenlafaxine on the expression of both P-gp and the breast cancer resistance protein (BCRP) in human brain endothelial cells (HBMEC), an in vitro model of the blood-brain barrier (BBB). The HBMEC were treated for 1 h with various concentrations (500 nM to 50 µM) of venlafaxine and desvenlafaxine. Western blot analysis revealed treatment with venlafaxine significantly induced the expression of P-gp (2-fold) and BCRP (1.75-fold) in a dose-dependent manner, while treatment with desvenlafaxine had no effect on drug efflux transporter expression. To determine the functional significance of this effect, the permeability of a known drug efflux probe, rhodamine 123, across the BBB model and Caco-2 cells, a model of intestinal absorption, were examined. Treatment with venlafaxine (1-50 µM) for 1 h significantly reduced the apical-to-basolateral permeability of R123 across the BBB model (30%) and Caco-2 cell monolayers (25%), indicative of increased drug efflux transporter expression at the apical membrane. Conversely, desvenlafaxine had no effect on R123 permeability in either cellular model. These studies indicate that venlafaxine, but not desvenlafaxine is an inducer of drug efflux transporter expression, which consequently increases the potential for clinical drug-drug interactions. Therefore, based on these preliminary results, caution should be taken when prescribing venlafaxine with other P-gp substrates. Copyright © 2011 John Wiley & Sons, Ltd.

  4. SynSysNet: integration of experimental data on synaptic protein–protein interactions with drug-target relations

    Science.gov (United States)

    von Eichborn, Joachim; Dunkel, Mathias; Gohlke, Björn O.; Preissner, Sarah C.; Hoffmann, Michael F.; Bauer, Jakob M. J.; Armstrong, J. D.; Schaefer, Martin H.; Andrade-Navarro, Miguel A.; Le Novere, Nicolas; Croning, Michael D. R.; Grant, Seth G. N.; van Nierop, Pim; Smit, August B.; Preissner, Robert

    2013-01-01

    We created SynSysNet, available online at http://bioinformatics.charite.de/synsysnet, to provide a platform that creates a comprehensive 4D network of synaptic interactions. Neuronal synapses are fundamental structures linking nerve cells in the brain and they are responsible for neuronal communication and information processing. These processes are dynamically regulated by a network of proteins. New developments in interaction proteomics and yeast two-hybrid methods allow unbiased detection of interactors. The consolidation of data from different resources and methods is important to understand the relation to human behaviour and disease and to identify new therapeutic approaches. To this end, we established SynSysNet from a set of ∼1000 synapse specific proteins, their structures and small-molecule interactions. For two-thirds of these, 3D structures are provided (from Protein Data Bank and homology modelling). Drug-target interactions for 750 approved drugs and 50 000 compounds, as well as 5000 experimentally validated protein–protein interactions, are included. The resulting interaction network and user-selected parts can be viewed interactively and exported in XGMML. Approximately 200 involved pathways can be explored regarding drug-target interactions. Homology-modelled structures are downloadable in Protein Data Bank format, and drugs are available as MOL-files. Protein–protein interactions and drug-target interactions can be viewed as networks; corresponding PubMed IDs or sources are given. PMID:23143269

  5. Protein target discovery of drug and its reactive intermediate metabolite by using proteomic strategy

    OpenAIRE

    Lianghai Hu; John Paul Fawcett; Jingkai Gu

    2012-01-01

    Identifying protein targets of bioactive compounds is an effective approach to discover unknown protein functions, identify molecular mechanisms of drug action, and obtain information for optimization of lead compounds. At the same time, metabolic activation of a drug can lead to cytotoxicities. Therefore, it is very important to systemically characterize the drug and its reactive intermediate. Mass spectrometry-based proteomic approach has emerged as the most efficient to study protein funct...

  6. Challenges in modelling nanoparticles for drug delivery

    Science.gov (United States)

    Barnard, Amanda S.

    2016-01-01

    Although there have been significant advances in the fields of theoretical condensed matter and computational physics, when confronted with the complexity and diversity of nanoparticles available in conventional laboratories a number of modeling challenges remain. These challenges are generally shared among application domains, but the impacts of the limitations and approximations we make to overcome them (or circumvent them) can be more significant one area than another. In the case of nanoparticles for drug delivery applications some immediate challenges include the incompatibility of length-scales, our ability to model weak interactions and solvation, the complexity of the thermochemical environment surrounding the nanoparticles, and the role of polydispersivity in determining properties and performance. Some of these challenges can be met with existing technologies, others with emerging technologies including the data-driven sciences; some others require new methods to be developed. In this article we will briefly review some simple methods and techniques that can be applied to these (and other) challenges, and demonstrate some results using nanodiamond-based drug delivery platforms as an exemplar.

  7. Mathematical modelling of the release of drug from porous, nonswelling transdermal drug-delivery devices.

    Science.gov (United States)

    Lee, A J; King, J R; Hibberd, S

    1998-06-01

    A general model is presented for the release of drug from porous nonswelling, transdermal drug-delivery devices and it is shown to reduce to previously proposed models in suitable limits. The processes which govern the release of drug are considered to be diffusion of dissolved drug and dissolution of dispersed drug, both in the body of the device and in the device pores, and transfer of drug between the two domains. In the classical limit of large dissolution rates, the problem reduces to one of the moving-boundary type, and solution of this problem in the case where the initial drug loading is much greater than the drug solubility in the device yields expressions for the flux of drug to a perfect sink (modelling in vitro conditions). It is shown that behaviour greatly differing from the classical first-order drug delivery (alpha t 1/2) may be exhibited, depending upon the parameter regime. In some situations the dissolution rates may not be so large and solutions of the general model are derived in the case where the dispersed drug is considered to be undepleted and the diffusivity in the solvent-filled pores is much larger than in the body of the delivery device. Numerical studies are undertaken, and the coupling of delivery device and skin-diffusion models (in order to model the complete transdermal drug-delivery process) is also considered.

  8. Drug-drug interactions related to altered absorption and plasma protein binding: theoretical and regulatory considerations, and an industry perspective.

    Science.gov (United States)

    Hochman, Jerome; Tang, Cuyue; Prueksaritanont, Thomayant

    2015-03-01

    Drug-drug interactions (DDIs) related to altered drug absorption and plasma protein binding have received much less attention from regulatory agencies relative to DDIs mediated via drug metabolizing enzymes and transporters. In this review, a number of theoretical bases and regulatory framework are presented for these DDI aspects. Also presented is an industry perspective on how to approach these issues in support of drug development. Overall, with the exception of highly permeable and highly soluble (BCS 1) drugs, DDIs related to drug-induced changes in gastrointestinal (GI) physiology can be substantial, thus warranting more attentions. For a better understanding of absorption-associated DDI potential in a clinical setting, mechanistic studies should be conducted based on holistic integration of the pharmaceutical profiles (e.g., pH-dependent solubility) and pharmacological properties (e.g., GI physiology and therapeutic margin) of drug candidates. Although majority of DDI events related to altered plasma protein binding are not expected to be of clinical significance, exceptions exist for a subset of compounds with certain pharmacokinetic and pharmacological properties. Knowledge of the identity of binding proteins and the binding extent in various clinical setting (including disease states) can be valuable in aiding clinical DDI data interpretations, and ensuring safe and effective use of new drugs.

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

    Science.gov (United States)

    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

  10. Bioanalysis for plasma protein binding studies in drug discovery and drug development: views and recommendations of the European Bioanalysis Forum.

    Science.gov (United States)

    Buscher, Brigitte; Laakso, Sirpa; Mascher, Hermann; Pusecker, Klaus; Doig, Mira; Dillen, Lieve; Wagner-Redeker, Winfried; Pfeifer, Thomas; Delrat, Pascal; Timmerman, Philip

    2014-03-01

    Plasma protein binding (PPB) is an important parameter for a drug's efficacy and safety that needs to be investigated during each drug-development program. Even though regulatory guidance exists to study the extent of PPB before initiating clinical studies, there are no detailed instructions on how to perform and validate such studies. To explore how PPB studies involving bioanalysis are currently executed in the industry, the European Bioanalysis Forum (EBF) has conducted three surveys among their member companies: PPB studies in drug discovery (Part I); in vitro PPB studies in drug development (Part II); and in vivo PPB studies in drug development. This paper reflects the outcome of the three surveys, which, together with the team discussions, formed the basis of the EBF recommendation. The EBF recommends a tiered approach to the design of PPB studies and the bioanalysis of PPB samples: 'PPB screening' experiments in (early) drug discovery versus qualified/validated procedures in drug development.

  11. Animal models of social contact and drug self-administration.

    Science.gov (United States)

    Strickland, Justin C; Smith, Mark A

    2015-09-01

    Social learning theories of drug abuse propose that individuals imitate drug use behaviors modeled by social peers, and that these behaviors are selectively reinforced and/or punished depending on group norms. Historically, animal models of social influence have focused on distal factors (i.e., those factors outside the drug-taking context) in drug self-administration studies. Recently, several investigators have developed novel models, or significantly modified existing models, to examine the role of proximal factors (i.e., those factors that are immediately present at the time of drug taking) on measures of drug self-administration. Studies using these newer models have revealed several important conclusions regarding the effects of social learning on drug abuse: 1) the presence of a social partner influences drug self-administration, 2) the behavior of a social partner determines whether social contact will increase or decrease drug intake, and 3) social partners can model and imitate specific patterns of drug self-administration. These findings are congruent with those obtained in the human laboratory, providing support for the cross-species generality and validity of these preclinical models. This mini-review describes in detail some of the preclinical animal models used to study social contact and drug self-administration to guide future research on social learning and drug abuse.

  12. Induced circular dichroism as a tool to investigate the binding of drugs to carrier proteins: Classic approaches and new trends.

    Science.gov (United States)

    Tedesco, Daniele; Bertucci, Carlo

    2015-09-10

    Induced circular dichroism (ICD) is a spectroscopic phenomenon that provides versatile and useful methods for characterizing the structural and dynamic properties of the binding of drugs to target proteins. The understanding of biorecognition processes at the molecular level is essential to discover and validate new pharmacological targets, and to design and develop new potent and selective drugs. The present article reviews the main applications of ICD to drug binding studies on serum carrier proteins, going from the classic approaches for the derivation of drug binding parameters and the identification of binding sites, to an overview of the emerging trends for the characterization of binding modes by means of quantum chemical (QC) techniques. The advantages and limits of the ICD methods for the determination of binding parameters are critically reviewed; the capability to investigate the binding interactions of drugs and metabolites to their target proteins is also underlined, as well as the possibility of characterizing the binding sites to obtain a complete picture of the binding mechanism and dynamics. The new applications of ICD methods to identify stereoselective binding modes of drug/protein complexes are then reviewed with relevant examples. The combined application of experimental ICD spectroscopy and QC calculations is shown to identify qualitatively the bound conformations of ligands to target proteins even in the absence of a detailed structure of the binding sites, either obtained from experimental X-ray crystallography and NMR measurements or from computational models of the complex. Copyright © 2015 Elsevier B.V. All rights reserved.

  13. DNA Binding Proteins and Drug Delivery Vehicles: Tales of Elephants and Snakes.

    Science.gov (United States)

    Karpel, Richard L

    2015-01-01

    We compare the DNA-interactive properties of bacteriophage T4 gene 32 protein (gp32) with those of crotamine, a component of the venom of the South American rattlesnake. Gene 32 protein is a classical single-stranded DNA binding protein that has served as a model for this class of proteins. We discuss its biological functions, structure, binding specificities, and how it controls its own expression. In addition, we delineate the roles of the structural domains of gp32 and how they regulate the protein's various activities. Crotamine, a component of the venom of the South American rattlesnake, is probably not a DNA binding protein in nature, but clearly shows significant DNA binding in vitro. Crotamine has been shown to selectively disrupt rapidly dividing cells and this specificity has been demonstrated for crotamine-facilitated delivery of plasmid DNA Thus, crotamine, or a variant of the protein, could have important clinical and/or diagnostic roles. Understanding its DNA binding properties may therefore lead to more effective drug delivery vehicles.

  14. [Development of a novel transdermal delivery system of peptide and protein drugs using microneedle arrays].

    Science.gov (United States)

    Katsumi, Hidemasa; Quan, Ying-Shu; Kamiyama, Fumio; Kusamori, Kosuke; Sakane, Toshiyasu; Yamamoto, Akira

    2014-01-01

    Transdermal delivery of peptide and protein drugs may be limited by the stratum corneum, which is a protective barrier against the entry of microorganisms and water. Many approaches have been utilized to promote peptide and protein drugs delivery across the stratum corneum, including chemical enhancer modification and physical disruption of barrier function. However, it has been difficult to achieve therapeutic levels of peptide and protein drugs via this route without any skin irritation. Recently, attention has been paid to the possibility of using microneedle arrays in delivering peptide and protein drugs into the skin. As a novel and minimally invasive approach, microneedle arrays are capable of creating superficial pathways across the skin for peptide and protein drugs to achieve enhanced transdermal drug delivery. This method combines the efficacy of conventional injection needles with the convenience of transdermal patches, while minimizing the disadvantages of these administration methods. Therefore, microneedle arrays are a very useful alternative method for delivering peptide and protein drugs from the skin into the systemic circulation without any serious damage to skin. In this review, recent challenges in the developments of microneedle arrays for the delivery of peptide and protein drugs are summarized. Then, future developments of microneedle arrays for the delivery of peptide and protein drugs are also discussed in order to improve their therapeutic efficacy and safety.

  15. DrugScorePPI knowledge-based potentials used as scoring and objective function in protein-protein docking.

    Directory of Open Access Journals (Sweden)

    Dennis M Krüger

    Full Text Available The distance-dependent knowledge-based DrugScore(PPI potentials, previously developed for in silico alanine scanning and hot spot prediction on given structures of protein-protein complexes, are evaluated as a scoring and objective function for the structure prediction of protein-protein complexes. When applied for ranking "unbound perturbation" ("unbound docking" decoys generated by Baker and coworkers a 4-fold (1.5-fold enrichment of acceptable docking solutions in the top ranks compared to a random selection is found. When applied as an objective function in FRODOCK for bound protein-protein docking on 97 complexes of the ZDOCK benchmark 3.0, DrugScore(PPI/FRODOCK finds up to 10% (15% more high accuracy solutions in the top 1 (top 10 predictions than the original FRODOCK implementation. When used as an objective function for global unbound protein-protein docking, fair docking success rates are obtained, which improve by ∼ 2-fold to 18% (58% for an at least acceptable solution in the top 10 (top 100 predictions when performing knowledge-driven unbound docking. This suggests that DrugScore(PPI balances well several different types of interactions important for protein-protein recognition. The results are discussed in view of the influence of crystal packing and the type of protein-protein complex docked. Finally, a simple criterion is provided with which to estimate a priori if unbound docking with DrugScore(PPI/FRODOCK will be successful.

  16. Homology Modeling: Generating Structural Models to Understand Protein Function and Mechanism

    Science.gov (United States)

    Ramachandran, Srinivas; Dokholyan, Nikolay V.

    Geneticists and molecular and cell biologists routinely uncover new proteins important in specific biological processes/pathways. However, either the molecular functions or the functional mechanisms of many of these proteins are unclear due to a lack of knowledge of their atomic structures. Yet, determining experimental structures of many proteins presents technical challenges. The current methods for obtaining atomic-resolution structures of biomolecules (X-ray crystallography and NMR spectroscopy) require pure preparations of proteins at concentrations much higher than those at which the proteins exist in a physiological environment. Additionally, NMR has size limitations, with current technology limited to the determination of structures of proteins with masses of up to 15 kDa. Due to these reasons, atomic structures of many medically and biologically important proteins do not exist. However, the structures of these proteins are essential for several purposes, including in silico drug design [1], understanding the effects of disease mutations [2], and designing experiments to probe the functional mechanisms of proteins. Comparative modeling has gained importance as a tool for bridging the gap between sequence and structure space, allowing researchers to build structural models of proteins that are difficult to crystallize or for which structure determination by NMR spectroscopy is not tractable. Comparative modeling, or homology modeling, exploits the fact that two proteins whose sequences are evolutionarily connected display similar structural features [3]. Thus, the known structure of a protein (template) can be used to generate a molecular model of the protein (query) whose experimental structure is notknown.

  17. A Model for Random Student Drug Testing

    Science.gov (United States)

    Nelson, Judith A.; Rose, Nancy L.; Lutz, Danielle

    2011-01-01

    The purpose of this case study was to examine random student drug testing in one school district relevant to: (a) the perceptions of students participating in competitive extracurricular activities regarding drug use and abuse; (b) the attitudes and perceptions of parents, school staff, and community members regarding student drug involvement; (c)…

  18. Protein structure-based design of anti-protozoal drugs

    Directory of Open Access Journals (Sweden)

    Verlinde Christophe L. M. J.

    2002-01-01

    Full Text Available The repertory of drugs to fight protozoal diseases such as malaria, Chagas' disease, leishmaniasis, and African trypanosomiasis is woefully inadequate. Now, genome sequencing and structural genomics projects are quickly elucidating new drug targets, providing incredible opportunities for medicinal chemists. Here, we illustrate the power of structure-based drug design in this process by our efforts to selectively block trypanosomal glycolysis.

  19. Effect of nonsteroidal antiinflammatory drugs on the C-reactive protein level in rheumatoid arthritis

    DEFF Research Database (Denmark)

    Tarp, Simon; Bartels, Else M; Bliddal, Henning;

    2012-01-01

    To evaluate the effects of oral nonsteroidal antiinflammatory drugs (NSAIDs) on C-reactive protein (CRP) levels in rheumatoid arthritis (RA) patients, with a prespecified focus on the different NSAIDs.......To evaluate the effects of oral nonsteroidal antiinflammatory drugs (NSAIDs) on C-reactive protein (CRP) levels in rheumatoid arthritis (RA) patients, with a prespecified focus on the different NSAIDs....

  20. Pharmacogenetics of drug-induced birth defects : the role of polymorphisms of placental transporter proteins

    NARCIS (Netherlands)

    Daud, Aizati N. A.; Bergman, Jorieke E. H.; Bakker, Marian K.; Wang, Hao; de Walle, Hermien E. K.; Plosch, Torsten; Wilffert, Bob

    2014-01-01

    One of the ongoing issues in perinatal medicine is the risk of birth defects associated with maternal drug use. The teratogenic effect of a drug depends, apart from other factors, on the exposition of the fetus to the drug. Transporter proteins are known to be involved in the pharmacokinetics of dru

  1. An Introductory Classroom Exercise on Protein Molecular Model Visualization and Detailed Analysis of Protein-Ligand Binding

    Science.gov (United States)

    Poeylaut-Palena, Andres, A.; de los Angeles Laborde, Maria

    2013-01-01

    A learning module for molecular level analysis of protein structure and ligand/drug interaction through the visualization of X-ray diffraction is presented. Using DeepView as molecular model visualization software, students learn about the general concepts of protein structure. This Biochemistry classroom exercise is designed to be carried out by…

  2. Modelling proteins' hidden conformations to predict antibiotic resistance

    Science.gov (United States)

    Hart, Kathryn M.; Ho, Chris M. W.; Dutta, Supratik; Gross, Michael L.; Bowman, Gregory R.

    2016-10-01

    TEM β-lactamase confers bacteria with resistance to many antibiotics and rapidly evolves activity against new drugs. However, functional changes are not easily explained by differences in crystal structures. We employ Markov state models to identify hidden conformations and explore their role in determining TEM's specificity. We integrate these models with existing drug-design tools to create a new technique, called Boltzmann docking, which better predicts TEM specificity by accounting for conformational heterogeneity. Using our MSMs, we identify hidden states whose populations correlate with activity against cefotaxime. To experimentally detect our predicted hidden states, we use rapid mass spectrometric footprinting and confirm our models' prediction that increased cefotaxime activity correlates with reduced Ω-loop flexibility. Finally, we design novel variants to stabilize the hidden cefotaximase states, and find their populations predict activity against cefotaxime in vitro and in vivo. Therefore, we expect this framework to have numerous applications in drug and protein design.

  3. Particle designs for the stabilization and controlled-delivery of protein drugs by biopolymers: a case study on insulin.

    Science.gov (United States)

    Lim, Hui-Peng; Tey, Beng-Ti; Chan, Eng-Seng

    2014-07-28

    Natural biopolymers have attracted considerable interest for the development of delivery systems for protein drugs owing to their biocompatibility, non-toxicity, renewability and mild processing conditions. This paper offers an overview of the current status and future perspectives of particle designs using biopolymers for the stabilization and controlled-delivery of a model protein drug--insulin. We first describe the design criteria for polymeric encapsulation and subsequently classify the basic principles of particle fabrication as well as the existing particle designs for oral insulin encapsulation. The performances of these existing particle designs in terms of insulin stability and in vitro release behavior in acidic and alkaline media, as well as their in vivo performance are compared and reviewed. This review forms the basis for future works on the optimization of particle design and material formulation for the development of an improved oral delivery system for protein drugs.

  4. Elastin-based protein polymer nanoparticles carrying drug at both corona and core suppress tumor growth in vivo.

    Science.gov (United States)

    Shi, Pu; Aluri, Suhaas; Lin, Yi-An; Shah, Mihir; Edman, Maria; Dhandhukia, Jugal; Cui, Honggang; MacKay, J Andrew

    2013-11-10

    Numerous nanocarriers of small molecules depend on either non-specific physical encapsulation or direct covalent linkage. In contrast, this manuscript explores an alternative encapsulation strategy based on high-specificity avidity between a small molecule drug and its cognate protein target fused to the corona of protein polymer nanoparticles. With the new strategy, the drug associates tightly to the carrier and releases slowly, which may decrease toxicity and promote tumor accumulation via the enhanced permeability and retention effect. To test this hypothesis, the drug Rapamycin (Rapa) was selected for its potent anti-proliferative properties, which give it immunosuppressant and anti-tumor activity. Despite its potency, Rapa has low solubility, low oral bioavailability, and rapid systemic clearance, which make it an excellent candidate for nanoparticulate drug delivery. To explore this approach, genetically engineered diblock copolymers were constructed from elastin-like polypeptides (ELPs) that assemble small (nanoparticles. ELPs are protein polymers of the sequence (Val-Pro-Gly-Xaa-Gly)n, where the identity of Xaa and n determine their assembly properties. Initially, a screening assay for model drug encapsulation in ELP nanoparticles was developed, which showed that Rose Bengal and Rapa have high non-specific encapsulation in the core of ELP nanoparticles with a sequence where Xaa=Ile or Phe. While excellent at entrapping these drugs, their release was relatively fast (2.2h half-life) compared to their intended mean residence time in the human body. Having determined that Rapa can be non-specifically entrapped in the core of ELP nanoparticles, FK506 binding protein 12 (FKBP), which is the cognate protein target of Rapa, was genetically fused to the surface of these nanoparticles (FSI) to enhance their avidity towards Rapa. The fusion of FKBP to these nanoparticles slowed the terminal half-life of drug release to 57.8h. To determine if this class of drug

  5. Solid lipid particles for oral delivery of peptide and protein drugs I - Elucidating the release mechanism of lysozyme during lipolysis

    DEFF Research Database (Denmark)

    Christophersen, Philip Carsten B; Zhang, L.; Yang, M

    2013-01-01

    The mechanism of protein release from solid lipid particles was investigated by a new lipolysis model in a biorelevant medium containing both bile salts and phospholipids. Lysozyme, a model protein, was formulated into solid lipid particles using four different types of lipids, two triglycerides...... with different chain-length of fatty acyl groups i.e. trimyristin (TG14) and tristearin (TG18), and two lipid blends dominated by diglycerides and monoglycerides, respectively. The release of lysozyme from the solid lipid particles and the lipid hydrolysis process were assessed in the lipolysis model, while...... the drug release mechanism from solid lipid particles and can potentially be used in rational selection of lipid excipients for oral delivery of peptide/protein drugs....

  6. Multiscale Modeling in the Clinic: Drug Design and Development

    Energy Technology Data Exchange (ETDEWEB)

    Clancy, Colleen E.; An, Gary; Cannon, William R.; Liu, Yaling; May, Elebeoba E.; Ortoleva, Peter; Popel, Aleksander S.; Sluka, James P.; Su, Jing; Vicini, Paolo; Zhou, Xiaobo; Eckmann, David M.

    2016-02-17

    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 to 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.

  7. Multiscale Modeling in the Clinic: Drug Design and Development.

    Science.gov (United States)

    Clancy, Colleen E; An, Gary; Cannon, William R; Liu, Yaling; May, Elebeoba E; Ortoleva, Peter; Popel, Aleksander S; Sluka, James P; Su, Jing; Vicini, Paolo; Zhou, Xiaobo; Eckmann, David M

    2016-09-01

    A wide range of length and time scales are relevant to pharmacology, especially in drug development, drug design and drug delivery. Therefore, multiscale computational modeling and simulation methods and paradigms that advance the linkage of phenomena occurring at these multiple scales have become increasingly important. Multiscale 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 to guide drug design and delivery. In this review we describe the goals, methods, and opportunities of multiscale modeling in drug design and development. We demonstrate the impact of multiple scales of modeling in this field. We indicate the common mathematical and computational techniques employed for multiscale modeling approaches used in pharmacometric and systems pharmacology models in drug development and present several examples illustrating the current state-of-the-art models for (1) excitable systems and applications in cardiac disease; (2) stem cell driven complex biosystems; (3) nanoparticle delivery, with applications to angiogenesis and cancer therapy; (4) host-pathogen interactions and their use in metabolic disorders, inflammation and sepsis; and (5) computer-aided design of nanomedical systems. We conclude with a focus on barriers to successful clinical translation of drug development, drug design and drug delivery multiscale models.

  8. Protein crystallization for drug design in the last 50 years

    Directory of Open Access Journals (Sweden)

    Stura, Enrico A.

    2015-04-01

    Full Text Available We live in an era where we expect to be able to visit our doctor and obtain a pill to cure any ailment from which we suffer. Yet, this is still not the case. Many of the current cures are still derived from natural sources although new drugs are increasingly the result of intelligent design. In this process, X-ray protein crystallography now plays a major and effective role in the discovery of new treatments. The developments that have made this possible have evolved during the past fifty years. The methods for crystallizing macromolecules and determining their structures by X-ray crystallography have been automated and the speed for X-ray data acquisition is several orders of magnitude faster. Fifty years ago it took several years to solve a single structure. Now, several protein–ligand complexes can be determined in single day. High-throughput crystallography is considered to be a great asset to the drug discovery process, providing a fast way to tailor drug candidates to their targets by analysing their binding mode in detail. Crystallization remains the main challenge.Vivimos en una época en la que esperamos ir al médico y obtener una pastilla para curar cualquier dolencia que padezcamos; por desgracia, esta expectativa no es real. Aunque muchos de los remedios en uso provienen de fuentes naturales, la mayoría de los nuevos medicamentos son el resultado de la investigación científica. En el proceso de diseño y descubrimiento de fármacos, la cristalografía de proteínas juega un papel central. Los conocimientos que han hecho esto posible han venido evolucionando desde hace cincuenta años aproximadamente. Los métodos de cristalización de macromoléculas y la determinación de sus estructuras a través de la cristalografía de rayos X han sido automatizados y miniaturizados y la velocidad de la adquisición de datos de difracción ha aumentado en varios órdenes de magnitud. Si hace cincuenta años la resolución de una sola

  9. Models to predict intestinal absorption of therapeutic peptides and proteins.

    Science.gov (United States)

    Antunes, Filipa; Andrade, Fernanda; Ferreira, Domingos; Nielsen, Hanne Morck; Sarmento, Bruno

    2013-01-01

    Prediction of human intestinal absorption is a major goal in the design, optimization, and selection of drugs intended for oral delivery, in particular proteins, which possess intrinsic poor transport across intestinal epithelium. There are various techniques currently employed to evaluate the extension of protein absorption in the different phases of drug discovery and development. Screening protocols to evaluate protein absorption include a range of preclinical methodologies like in silico, in vitro, in situ, ex vivo and in vivo. It is the careful and critical use of these techniques that can help to identify drug candidates, which most probably will be well absorbed from the human intestinal tract. It is well recognized that the human intestinal permeability cannot be accurately predicted based on a single preclinical method. However, the present social and scientific concerns about the animal well care as well as the pharmaceutical industries need for rapid, cheap and reliable models predicting bioavailability give reasons for using methods providing an appropriate correlation between results of in vivo and in vitro drug absorption. The aim of this review is to describe and compare in silico, in vitro, in situ, ex vivo and in vivo methods used to predict human intestinal absorption, giving a special attention to the intestinal absorption of therapeutic peptides and proteins.

  10. Analysis and Ranking of Protein-Protein Docking Models Using Inter-Residue Contacts and Inter-Molecular Contact Maps

    KAUST Repository

    Oliva, Romina

    2015-07-01

    In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, protein-protein docking becomes the method of choice for predicting the arrangement of the complex. However, reliably scoring protein-protein docking poses is still an unsolved problem. As a consequence, the screening of many docking models is usually required in the analysis step, to possibly single out the correct ones. Here, making use of exemplary cases, we review our recently introduced methods for the analysis of protein complex structures and for the scoring of protein docking poses, based on the use of inter-residue contacts and their visualization in inter-molecular contact maps. We also show that the ensemble of tools we developed can be used in the context of rational drug design targeting protein-protein interactions.

  11. Palbociclib can overcome mutations in cyclin dependent kinase 6 that break hydrogen bonds between the drug and the protein.

    Science.gov (United States)

    Hernandez Maganhi, Stella; Jensen, Patrizia; Caracelli, Ignez; Zukerman Schpector, Julio; Fröhling, Stefan; Friedman, Ran

    2017-04-01

    Inhibition of cyclin dependent kinases (CDKs) 4 and 6 prevent cells from entering the synthesis phase of the cell cycle. CDK4 and 6 are therefore important drug targets in various cancers. The selective CDK4/6 inhibitor palbociclib is approved for the treatment of breast cancer and has shown activity in a cellular model of mixed lineage leukaemia (MLL)-rearranged acute myeloid leukaemia (AML). We studied the interactions of palbociclib and CDK6 using molecular dynamics simulations. Analysis of the simulations suggested several interactions that stabilized the drug in its binding site and that were not observed in the crystal structure of the protein-drug complex. These included a hydrogen bond to His 100 that was hitherto not reported and several hydrophobic contacts. Evolutionary-based bioinformatic analysis was used to suggest two mutants, D163G and H100L that would potentially yield drug resistance, as they lead to loss of important protein-drug interactions without hindering the viability of the protein. One of the mutants involved a change in the glycine of the well-conserved DFG motif of the kinase. Interestingly, CDK6-dependent human AML cells stably expressing either mutant retained sensitivity to palbociclib, indicating that the protein-drug interactions are not affected by these. Furthermore, the cells were proliferative in the absence of palbociclib, indicating that the Asp to Gly mutation in the DFG motif did not interfere with the catalytic activity of the protein. © 2017 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

  12. Binding of small molecules at interface of protein-protein complex - A newer approach to rational drug design.

    Science.gov (United States)

    Gurung, A B; Bhattacharjee, A; Ajmal Ali, M; Al-Hemaid, F; Lee, Joongku

    2017-02-01

    Protein-protein interaction is a vital process which drives many important physiological processes in the cell and has also been implicated in several diseases. Though the protein-protein interaction network is quite complex but understanding its interacting partners using both in silico as well as molecular biology techniques can provide better insights for targeting such interactions. Targeting protein-protein interaction with small molecules is a challenging task because of druggability issues. Nevertheless, several studies on the kinetics as well as thermodynamic properties of protein-protein interactions have immensely contributed toward better understanding of the affinity of these complexes. But, more recent studies on hot spots and interface residues have opened up new avenues in the drug discovery process. This approach has been used in the design of hot spot based modulators targeting protein-protein interaction with the objective of normalizing such interactions.

  13. Predicting Anticancer Drug Responses Using a Dual-Layer Integrated Cell Line-Drug Network Model.

    Directory of Open Access Journals (Sweden)

    Naiqian Zhang

    Full Text Available The ability to predict the response of a cancer patient to a therapeutic agent is a major goal in modern oncology that should ultimately lead to personalized treatment. Existing approaches to predicting drug sensitivity rely primarily on profiling of cancer cell line panels that have been treated with different drugs and selecting genomic or functional genomic features to regress or classify the drug response. Here, we propose a dual-layer integrated cell line-drug network model, which uses both cell line similarity network (CSN data and drug similarity network (DSN data to predict the drug response of a given cell line using a weighted model. Using the Cancer Cell Line Encyclopedia (CCLE and Cancer Genome Project (CGP studies as benchmark datasets, our single-layer model with CSN or DSN and only a single parameter achieved a prediction performance comparable to the previously generated elastic net model. When using the dual-layer model integrating both CSN and DSN, our predicted response reached a 0.6 Pearson correlation coefficient with observed responses for most drugs, which is significantly better than the previous results using the elastic net model. We have also applied the dual-layer cell line-drug integrated network model to fill in the missing drug response values in the CGP dataset. Even though the dual-layer integrated cell line-drug network model does not specifically model mutation information, it correctly predicted that BRAF mutant cell lines would be more sensitive than BRAF wild-type cell lines to three MEK1/2 inhibitors tested.

  14. Pharmacogenetics of drug-induced birth defects: the role of polymorphisms of placental transporter proteins.

    Science.gov (United States)

    Daud, Aizati N A; Bergman, Jorieke E H; Bakker, Marian K; Wang, Hao; de Walle, Hermien E K; Plösch, Torsten; Wilffert, Bob

    2014-05-01

    One of the ongoing issues in perinatal medicine is the risk of birth defects associated with maternal drug use. The teratogenic effect of a drug depends, apart from other factors, on the exposition of the fetus to the drug. Transporter proteins are known to be involved in the pharmacokinetics of drugs and have an effect on drug level and fetal drug exposure. This condition may subsequently alter the risk of teratogenicity, which occurs in a dose-dependent manner. This review focuses on the clinically important polymorphisms of transporter proteins and their effects on the mRNA and protein expression in placental tissue. We also propose a novel approach on how the different genotypes of the polymorphism can be translated into phenotypes to facilitate genetic association studies. The last section looks into the recent studies exploring the association between P-glycoprotein polymorphisms and the risk of fetal birth defects associated with medication use during pregnancy.

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

    Science.gov (United States)

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

    2016-05-01

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

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

    Science.gov (United States)

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

    2016-05-01

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

  17. Structure Based Drug Design for HIM Protease: From Molecular Modeling to Cheminformatics

    Energy Technology Data Exchange (ETDEWEB)

    Volarath, Patra; Weber, Irene T.; Harrison, Robert W. (GSU)

    2008-06-06

    Significant progress over the past decade in virtual representations of molecules and their physicochemical properties has produced new drugs from virtual screening of the structures of single protein molecules by conventional modeling methods. The development of clinical antiviral drugs from structural data for HIV protease has been a major success in structure based drug design. Techniques for virtual screening involve the ranking of the affinity of potential ligands for the target site on a protein. Two main alternatives have been developed: modeling of the target protein with a series of related ligand molecules, and docking molecules from a database to the target protein site. The computational speed and prediction accuracy will depend on the representation of the molecular structure and chemistry, the search or simulation algorithm, and the scoring function to rank the ligands. Moreover, the general challenges in modern computational drug design arise from the profusion of data, including whole genomes of DNA, protein structures, chemical libraries, affinity and pharmacological data. Therefore, software tools are being developed to manage and integrate diverse data, and extract and visualize meaningful relationships. Current areas of research include the development of searchable chemical databases, which requires new algorithms to represent molecules and search for structurally or chemically similar molecules, and the incorporation of machine learning techniques for data mining to improve the accuracy of predictions. Examples will be presented for the virtual screening of drugs that target HIV protease.

  18. Effects of Radiation and Dietary Iron on Expression of Genes and Proteins Involved in Drug Metabolism

    Science.gov (United States)

    Faust, K. M.; Wotring, V. E.

    2014-01-01

    Liver function, especially the rate of metabolic enzyme activities, determines the concentration of circulating drugs and the duration of their efficacy. Most pharmaceuticals are metabolized by the liver, and clinically-used medication doses are given with normal liver function in mind. A drug overdose can result in the case of a liver that is damaged and removing pharmaceuticals from the circulation at a rate slower than normal. Alternatively, if liver function is elevated and removing drugs from the system more quickly than usual, it would be as if too little drug had been given for effective treatment. Because of the importance of the liver in drug metabolism, we want to understand any effects of spaceflight on the enzymes of the liver. Dietary factors and exposure to radiation are aspects of spaceflight that are potential oxidative stressors and both can be modeled in ground experiments. In this experiment, we examined the effects of high dietary iron and low dose gamma radiation (individually and combined) on the gene expression of enzymes involved in drug metabolism, redox homeostasis, and DNA repair. METHODS All procedures were approved by the JSC Animal Care and Use Committee. Male Sprague-Dawley rats were divided into 4 groups (n=8); control, high Fe diet (650 mg iron/kg), radiation (fractionated 3 Gy exposure from a Cs- 137 source) and combined high Fe diet + radiation exposure. Animals were euthanized 24h after the last treatment of radiation; livers were removed immediately and flash -frozen in liquid nitrogen. Expression of genes thought to be involved in redox homeostasis, drug metabolism and DNA damage repair was measured by RT-qPCR. Where possible, protein expression of the same genes was measured by western blotting. All data are expressed as % change in expression normalized to reference gene expression; comparisons were then made of each treatment group to the sham exposed/ normal diet control group. Data was considered significant at pmetabolism

  19. A Molecular Communication System Model for Particulate Drug Delivery Systems.

    Science.gov (United States)

    Chahibi, Youssef; Pierobon, Massimiliano; Song, Sang Ok; Akyildiz, Ian F

    2013-12-01

    The goal of a drug delivery system (DDS) is to convey a drug where the medication is needed, while, at the same time, preventing the drug from affecting other healthy parts of the body. Drugs composed of micro- or nano-sized particles (particulate DDS) that are able to cross barriers which prevent large particles from escaping the bloodstream are used in the most advanced solutions. Molecular communication (MC) is used as an abstraction of the propagation of drug particles in the body. MC is a new paradigm in communication research where the exchange of information is achieved through the propagation of molecules. Here, the transmitter is the drug injection, the receiver is the drug delivery, and the channel is realized by the transport of drug particles, thus enabling the analysis and design of a particulate DDS using communication tools. This is achieved by modeling the MC channel as two separate contributions, namely, the cardiovascular network model and the drug propagation network. The cardiovascular network model allows to analytically compute the blood velocity profile in every location of the cardiovascular system given the flow input by the heart. The drug propagation network model allows the analytical expression of the drug delivery rate at the targeted site given the drug injection rate. Numerical results are also presented to assess the flexibility and accuracy of the developed model. The study of novel optimization techniques for a more effective and less invasive drug delivery will be aided by this model, while paving the way for novel communication techniques for Intrabody communication networks.

  20. TIMP-1 increases expression and phosphorylation of proteins associated with drug resistance in breast cancer cells

    DEFF Research Database (Denmark)

    Hekmat, Omid; Munk, Stephanie; Fogh, Louise

    2013-01-01

    Tissue inhibitor of metalloproteinase 1 (TIMP-1) is a protein with a potential biological role in drug resistance. To elucidate the unknown molecular mechanisms underlying the association between high TIMP-1 levels and increased chemotherapy resistance, we employed SILAC-based quantitative mass...... may explain the resistance phenotype to topoisomerase inhibitors that was observed in cells with high TIMP-1 levels. Pathway analysis showed an enrichment of proteins from functional categories such as apoptosis, cell cycle, DNA repair, transcription factors, drug targets and proteins associated...... with drug resistance or sensitivity and drug transportation. The NetworKIN algorithm predicted the protein kinases CK2a, CDK1, PLK1 and ATM as likely candidates involved in the hyper-phosphorylation of the topoisomerases. Up-regulation of protein and/or phosphorylation levels of topoisomerases in TIMP-1...

  1. LC-MS quantification of protein drugs: validating protein LC-MS methods with predigestion immunocapture.

    Science.gov (United States)

    Duggan, Jeffrey; Ren, Bailuo; Mao, Yan; Chen, Lin-Zhi; Philip, Elsy

    2016-09-01

    A refinement of protein LC-MS bioanalysis is to use predigestion immunoaffinity capture to extract the drug from matrix prior to digestion. Because of their increased sensitivity, such hybrid assays have been successfully validated and applied to a number of clinical studies; however, they can also be subject to potential interferences from antidrug antibodies, circulating ligands or other matrix components specific to patient populations and/or dosed subjects. The purpose of this paper is to describe validation experiments that measure immunocapture efficiency, digestion efficiency, matrix effect and selectivity/specificity that can be used during method optimization and validation to test the resistance of the method to these potential interferences. The designs and benefits of these experiments are discussed in this report using an actual assay case study.

  2. Drugs and Crime: An Empirically Based, Interdisciplinary Model

    Science.gov (United States)

    Quinn, James F.; Sneed, Zach

    2008-01-01

    This article synthesizes neuroscience findings with long-standing criminological models and data into a comprehensive explanation of the relationship between drug use and crime. The innate factors that make some people vulnerable to drug use are conceptually similar to those that predict criminality, supporting a spurious reciprocal model of the…

  3. Drugs and Crime: An Empirically Based, Interdisciplinary Model

    Science.gov (United States)

    Quinn, James F.; Sneed, Zach

    2008-01-01

    This article synthesizes neuroscience findings with long-standing criminological models and data into a comprehensive explanation of the relationship between drug use and crime. The innate factors that make some people vulnerable to drug use are conceptually similar to those that predict criminality, supporting a spurious reciprocal model of the…

  4. Information-driven structural modelling of protein-protein interactions.

    Science.gov (United States)

    Rodrigues, João P G L M; Karaca, Ezgi; Bonvin, Alexandre M J J

    2015-01-01

    Protein-protein docking aims at predicting the three-dimensional structure of a protein complex starting from the free forms of the individual partners. As assessed in the CAPRI community-wide experiment, the most successful docking algorithms combine pure laws of physics with information derived from various experimental or bioinformatics sources. Of these so-called "information-driven" approaches, HADDOCK stands out as one of the most successful representatives. In this chapter, we briefly summarize which experimental information can be used to drive the docking prediction in HADDOCK, and then focus on the docking protocol itself. We discuss and illustrate with a tutorial example a "classical" protein-protein docking prediction, as well as more recent developments for modelling multi-body systems and large conformational changes.

  5. Spread of anti-malarial drug resistance: Mathematical model with implications for ACT drug policies

    Directory of Open Access Journals (Sweden)

    Dondorp Arjen M

    2008-11-01

    Full Text Available Abstract Background Most malaria-endemic countries are implementing a change in anti-malarial drug policy to artemisinin-based combination therapy (ACT. The impact of different drug choices and implementation strategies is uncertain. Data from many epidemiological studies in different levels of malaria endemicity and in areas with the highest prevalence of drug resistance like borders of Thailand are certainly valuable. Formulating an appropriate dynamic data-driven model is a powerful predictive tool for exploring the impact of these strategies quantitatively. Methods A comprehensive model was constructed incorporating important epidemiological and biological factors of human, mosquito, parasite and treatment. The iterative process of developing the model, identifying data needed, and parameterization has been taken to strongly link the model to the empirical evidence. The model provides quantitative measures of outcomes, such as malaria prevalence/incidence and treatment failure, and illustrates the spread of resistance in low and high transmission settings. The model was used to evaluate different anti-malarial policy options focusing on ACT deployment. Results The model predicts robustly that in low transmission settings drug resistance spreads faster than in high transmission settings, and treatment failure is the main force driving the spread of drug resistance. In low transmission settings, ACT slows the spread of drug resistance to a partner drug, especially at high coverage rates. This effect decreases exponentially with increasing delay in deploying the ACT and decreasing rates of coverage. In the high transmission settings, however, drug resistance is driven by the proportion of the human population with a residual drug level, which gives resistant parasites some survival advantage. The spread of drug resistance could be slowed down by controlling presumptive drug use and avoiding the use of combination therapies containing drugs with

  6. Spread of anti-malarial drug resistance: mathematical model with implications for ACT drug policies.

    Science.gov (United States)

    Pongtavornpinyo, Wirichada; Yeung, Shunmay; Hastings, Ian M; Dondorp, Arjen M; Day, Nicholas P J; White, Nicholas J

    2008-11-02

    Most malaria-endemic countries are implementing a change in anti-malarial drug policy to artemisinin-based combination therapy (ACT). The impact of different drug choices and implementation strategies is uncertain. Data from many epidemiological studies in different levels of malaria endemicity and in areas with the highest prevalence of drug resistance like borders of Thailand are certainly valuable. Formulating an appropriate dynamic data-driven model is a powerful predictive tool for exploring the impact of these strategies quantitatively. A comprehensive model was constructed incorporating important epidemiological and biological factors of human, mosquito, parasite and treatment. The iterative process of developing the model, identifying data needed, and parameterization has been taken to strongly link the model to the empirical evidence. The model provides quantitative measures of outcomes, such as malaria prevalence/incidence and treatment failure, and illustrates the spread of resistance in low and high transmission settings. The model was used to evaluate different anti-malarial policy options focusing on ACT deployment. The model predicts robustly that in low transmission settings drug resistance spreads faster than in high transmission settings, and treatment failure is the main force driving the spread of drug resistance. In low transmission settings, ACT slows the spread of drug resistance to a partner drug, especially at high coverage rates. This effect decreases exponentially with increasing delay in deploying the ACT and decreasing rates of coverage. In the high transmission settings, however, drug resistance is driven by the proportion of the human population with a residual drug level, which gives resistant parasites some survival advantage. The spread of drug resistance could be slowed down by controlling presumptive drug use and avoiding the use of combination therapies containing drugs with mismatched half-lives, together with reducing malaria

  7. Systems pharmacology modeling: an approach to improving drug safety.

    Science.gov (United States)

    Bai, Jane P F; Fontana, Robert J; Price, Nathan D; Sangar, Vineet

    2014-01-01

    Advances in systems biology in conjunction with the expansion in knowledge of drug effects and diseases present an unprecedented opportunity to extend traditional pharmacokinetic and pharmacodynamic modeling/analysis to conduct systems pharmacology modeling. Many drugs that cause liver injury and myopathies have been studied extensively. Mitochondrion-centric systems pharmacology modeling is important since drug toxicity across a large number of pharmacological classes converges to mitochondrial injury and death. Approaches to systems pharmacology modeling of drug effects need to consider drug exposure, organelle and cellular phenotypes across all key cell types of human organs, organ-specific clinical biomarkers/phenotypes, gene-drug interaction and immune responses. Systems modeling approaches, that leverage the knowledge base constructed from curating a selected list of drugs across a wide range of pharmacological classes, will provide a critically needed blueprint for making informed decisions to reduce the rate of attrition for drugs in development and increase the number of drugs with an acceptable benefit/risk ratio.

  8. Hydrodynamic modeling of ferrofluid flow in magnetic targeting drug delivery

    Institute of Scientific and Technical Information of China (English)

    LIU Han-dan; XU Wei; WANG Shi-gang; KE Zun-ji

    2008-01-01

    Among the proposed techniques for delivering drugs to specific locations within human body, magnetic drug targeting prevails due to its non-invasive character and its high targeting efficiency. Magnetic targeting drug delivery is a method of carrying drug-loaded magnetic nanoparticles to a target tissue target under the applied magnetic field. This method increases the drug concentration in the target while reducing the adverse side-effects. Although there have been some theoretical analyses for magnetic drug targeting, very few researchers have addressed the hydrodynamic models of magnetic fluids in the blood vessel. A mathematical model is presented to describe the hydrodynamics of ferrofluids as drug carriers flowing in a blood vessel under the applied magnetic field. In this model, magnetic force and asymmetrical force are added, and an angular momentum equation of magnetic nanoparticles in the applied magnetic field is modeled. Engineering approximations are achieved by retaining the physically most significant items in the model due to the mathematical complexity of the motion equations. Numerical simulations are performed to obtain better insight into the theoretical model with computational fluid dynamics. Simulation results demonstrate the important parameters leading to adequate drug delivery to the target site depending on the magnetic field intensity, which coincident with those of animal experiments. Results of the analysis provide important information and suggest strategies for improving delivery in clinical application.

  9. Integrating Multiscale Modeling with Drug Effects for Cancer Treatment.

    Science.gov (United States)

    Li, Xiangfang L; Oduola, Wasiu O; Qian, Lijun; Dougherty, Edward R

    2015-01-01

    In this paper, we review multiscale modeling for cancer treatment with the incorporation of drug effects from an applied system's pharmacology perspective. Both the classical pharmacology and systems biology are inherently quantitative; however, systems biology focuses more on networks and multi factorial controls over biological processes rather than on drugs and targets in isolation, whereas systems pharmacology has a strong focus on studying drugs with regard to the pharmacokinetic (PK) and pharmacodynamic (PD) relations accompanying drug interactions with multiscale physiology as well as the prediction of dosage-exposure responses and economic potentials of drugs. Thus, it requires multiscale methods to address the need for integrating models from the molecular levels to the cellular, tissue, and organism levels. It is a common belief that tumorigenesis and tumor growth can be best understood and tackled by employing and integrating a multifaceted approach that includes in vivo and in vitro experiments, in silico models, multiscale tumor modeling, continuous/discrete modeling, agent-based modeling, and multiscale modeling with PK/PD drug effect inputs. We provide an example application of multiscale modeling employing stochastic hybrid system for a colon cancer cell line HCT-116 with the application of Lapatinib drug. It is observed that the simulation results are similar to those observed from the setup of the wet-lab experiments at the Translational Genomics Research Institute.

  10. COMPUTATIONAL MODELING AND DRUG DESIGNING OF LIPOPROTEIN LIPASE (LPL INVOLVED IN ISCHEMIC STROKE

    Directory of Open Access Journals (Sweden)

    Maryam Torabizadeh

    2012-12-01

    Full Text Available Homology modeling and flexible docking of Lipoprotein Lipase has been studied in silico approach. Blast result was found to have similarity with Lipoprotein Lipase of 83% identity with 1LPA. Active site of LPL protein was identified by CASTP. Large potential drugs were designed for identifying molecules that can likely bind to protein target of interest. The different drug derivatives designed were used for docking with the generated structure, among the 10 derivatives designed, 3rd derivative showed highest docking result. The drug derivatives were docked to the protein by hydrogen bonding interactions and these interactions play an important role in the binding studies. Our investigations may be helpful for further studies.

  11. K-Ras protein as a drug target.

    Science.gov (United States)

    McCormick, Frank

    2016-03-01

    K-Ras proteins are major drivers of human cancers, playing a direct causal role in about one million cancer cases/year. In cancers driven by mutant K-Ras, the protein is locked in the active, GTP-bound state constitutively, through a defect in the off-switch mechanism. As such, the mutant protein resembles the normal K-Ras protein from a structural perspective, making therapeutic attack extremely challenging. K-Ras is a member of a large family of related proteins, which share very similar GDP/GTP-binding domains, making specific therapies more difficult. Furthermore, Ras proteins lack pockets to which small molecules can bind with high affinity, with a few interesting exceptions. However, new insights into the structure and function of K-Ras proteins reveal opportunities for intervention that were not appreciated many years ago, when efforts were launched to develop K-Ras therapies. Furthermore, K-Ras undergoes post-translational modification and interactions with cellular signaling proteins that present additional therapeutic opportunities, such as specific binding to calmodulin and regulation of non-canonical Wnt signaling.

  12. Tumor Growth Model with PK Input for Neuroblastoma Drug Development

    Science.gov (United States)

    2015-09-01

    9/2012 - 4/30/2017 2.40 calendar NCI Anticancer Drug Pharmacology in Very Young Children The proposed studies will use pharmacokinetic... anticancer drugs . DOD W81XWH-14-1-0103 CA130396 (Stewart) 9/1/2014 - 8/31/2016 .60 calendar DOD-DEPARTMENT OF THE ARMY Tumor Growth Model with PK... anticancer drugs . .60 calendar V Foundation Translational (Stewart) 11/1/2012-10/31/2015 THE V FDN FOR CA RES Identification & preclinical testing

  13. The Role of ABC Proteins in Drug Resistant Breast Cancer Cells

    Science.gov (United States)

    2009-03-01

    intracellular compartments is due to a perturbation in the chemical environment and/or the number of drug binding sites [2]. Regardless of the...CQ does in fact directly interact with the protein, and competition studies also suggested a physical interaction with other quinoline drugs (e.g

  14. Predicted essential proteins ofPlasmodium falciparum for potential drug targets

    Institute of Scientific and Technical Information of China (English)

    Qing-Feng He; Li Deng; Qin-Ying Xu; Zheng Shao

    2012-01-01

    ABSTRACT Objective:To identify novel drug targets for treatment ofPlasmodium falciparum.Methods:LocalBLASTP were used to find the proteins non-homologous to human essential proteins as novel drug targets. Functional domains of novel drug targets were identified by InterPro and Pfam,3D structures of potential drug targets were predicated by theSWISS-MODELworkspace. Ligands and ligand-binding sites of the proteins were searched byEf-seek.Results:Three essential proteins were identified that might be considered as potential drug targets.AAN37254.1 belonged to1-deoxy-D-xylulose5-phosphate reductoisomerase,CAD50499.1 belonged to chorismate synthase,CAD51220.1 belonged toFAD binging3 family, but the function of CAD51220.1 was unknown. The3D structures, ligands and ligand-binding sites ofAAN37254.1 andCAD50499.1 were successfully predicated.Conclusions:Two of these potential drug targets are key enzymes in2-C-methyl-d-erythritol4-phosphate pathway and shikimate pathway, which are absent in humans, so these two essential proteins are good potential drug targets. The function and3D structures ofCAD50499.1 is still unknown, it still need further study.

  15. In silico modeling to predict drug-induced phospholipidosis

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Sydney S.; Kim, Jae S.; Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov; Sadrieh, Nakissa

    2013-06-01

    Drug-induced phospholipidosis (DIPL) is a preclinical finding during pharmaceutical drug development that has implications on the course of drug development and regulatory safety review. A principal characteristic of drugs inducing DIPL is known to be a cationic amphiphilic structure. This provides evidence for a structure-based explanation and opportunity to analyze properties and structures of drugs with the histopathologic findings for DIPL. In previous work from the FDA, in silico quantitative structure–activity relationship (QSAR) modeling using machine learning approaches has shown promise with a large dataset of drugs but included unconfirmed data as well. In this study, we report the construction and validation of a battery of complementary in silico QSAR models using the FDA's updated database on phospholipidosis, new algorithms and predictive technologies, and in particular, we address high performance with a high-confidence dataset. The results of our modeling for DIPL include rigorous external validation tests showing 80–81% concordance. Furthermore, the predictive performance characteristics include models with high sensitivity and specificity, in most cases above ≥ 80% leading to desired high negative and positive predictivity. These models are intended to be utilized for regulatory toxicology applied science needs in screening new drugs for DIPL. - Highlights: • New in silico models for predicting drug-induced phospholipidosis (DIPL) are described. • The training set data in the models is derived from the FDA's phospholipidosis database. • We find excellent predictivity values of the models based on external validation. • The models can support drug screening and regulatory decision-making on DIPL.

  16. QSAR Models for the Prediction of Plasma Protein Binding

    Directory of Open Access Journals (Sweden)

    Zeshan Amin

    2013-02-01

    Full Text Available Introduction: The prediction of plasma protein binding (ppb is of paramount importance in the pharmacokinetics characterization of drugs, as it causes significant changes in volume of distribution, clearance and drug half life. This study utilized Quantitative Structure – Activity Relationships (QSAR for the prediction of plasma protein binding. Methods: Protein binding values for 794 compounds were collated from literature. The data was partitioned into a training set of 662 compounds and an external validation set of 132 compounds. Physicochemical and molecular descriptors were calculated for each compound using ACD labs/logD, MOE (Chemical Computing Group and Symyx QSAR software packages. Several data mining tools were employed for the construction of models. These included stepwise regression analysis, Classification and Regression Trees (CART, Boosted trees and Random Forest. Results: Several predictive models were identified; however, one model in particular produced significantly superior prediction accuracy for the external validation set as measured using mean absolute error and correlation coefficient. The selected model was a boosted regression tree model which had the mean absolute error for training set of 13.25 and for validation set of 14.96. Conclusion: Plasma protein binding can be modeled using simple regression trees or multiple linear regressions with reasonable model accuracies. These interpretable models were able to identify the governing molecular factors for a high ppb that included hydrophobicity, van der Waals surface area parameters, and aromaticity. On the other hand, the more complicated ensemble method of boosted regression trees produced the most accurate ppb estimations for the external validation set.

  17. Recent advances in the preparation progress of protein/peptide drug loaded PLA/PLGA microspheres.

    Science.gov (United States)

    Xu, Feng-Hua; Zhang, Qiang

    2007-01-01

    Sustained release drug delivery from microparticles is an excellent alternative for daily protein/peptide drug administration protocol. Poly(lactic acid) (PLA) and poly(lactic-co-glycolic acid) (PLGA) are the most commonly used polymer carriers in the development of protein/peptide microspheres. Basically there are three preparation methods for PLA/PLGA microspheres: the solvent extraction/evaporation based multiple emulsion (W/O/W emulsion) method, the phase separation method and the spray drying method. The stability of the protein/pipetide loaded, encapsulation efficiency, and the burst effect of the microspheres are key problems usually met in the preparation of microspheres. In this review the preparation techniques and progress in the development of protein/pipetide microspheres which aimed to stabilize protein/peptide structural integrity, keep the bioactivity of drugs, increase the encapsulation efficiency and improve the release profile were summarized and evaluated.

  18. Protein export systems of Mycobacterium tuberculosis: novel targets for drug development?

    Science.gov (United States)

    Feltcher, Meghan E; Sullivan, Jonathan Tabb; Braunstein, Miriam

    2010-10-01

    Protein export is essential in all bacteria and many bacterial pathogens depend on specialized protein export systems for virulence. In Mycobacterium tuberculosis, the etiological agent of the disease tuberculosis, the conserved general secretion (Sec) and twin-arginine translocation (Tat) pathways perform the bulk of protein export and are both essential. M. tuberculosis also has specialized export pathways that transport specific subsets of proteins. One such pathway is the accessory SecA2 system, which is important for M. tuberculosis virulence. There are also specialized ESX export systems that function in virulence (ESX-1) or essential physiologic processes (ESX-3). The increasing prevalence of drug-resistant M. tuberculosis strains makes the development of novel drugs for tuberculosis an urgent priority. In this article, we discuss our current understanding of the protein export systems of M. tuberculosis and consider the potential of these pathways to be novel targets for tuberculosis drugs.

  19. A two-dimensional mathematical model of percutaneous drug absorption

    Directory of Open Access Journals (Sweden)

    Kubota K

    2004-06-01

    Full Text Available Abstract Background When a drug is applied on the skin surface, the concentration of the drug accumulated in the skin and the amount of the drug eliminated into the blood vessel depend on the value of a parameter, r. The values of r depend on the amount of diffusion and the normalized skin-capillary clearence. It is defined as the ratio of the steady-state drug concentration at the skin-capillary boundary to that at the skin-surface in one-dimensional models. The present paper studies the effect of the parameter values, when the region of contact of the skin with the drug, is a line segment on the skin surface. Methods Though a simple one-dimensional model is often useful to describe percutaneous drug absorption, it may be better represented by multi-dimensional models. A two-dimensional mathematical model is developed for percutaneous absorption of a drug, which may be used when the diffusion of the drug in the direction parallel to the skin surface must be examined, as well as in the direction into the skin, examined in one-dimensional models. This model consists of a linear second-order parabolic equation with appropriate initial conditions and boundary conditions. These boundary conditions are of Dirichlet type, Neumann type or Robin type. A finite-difference method which maintains second-order accuracy in space along the boundary, is developed to solve the parabolic equation. Extrapolation in time is applied to improve the accuracy in time. Solution of the parabolic equation gives the concentration of the drug in the skin at a given time. Results Simulation of the numerical methods described is carried out with various values of the parameter r. The illustrations are given in the form of figures. Conclusion Based on the values of r, conclusions are drawn about (1 the flow rate of the drug, (2 the flux and the cumulative amount of drug eliminated into the receptor cell, (3 the steady-state value of the flux, (4 the time to reach the steady

  20. Electrochemistry-mass spectrometry in drug metabolism and protein research

    NARCIS (Netherlands)

    Permentier, Hjalmar P.; Bruins, Andries P.; Bischoff, Rainer

    2008-01-01

    The combination of electrochemistry coupled on-line to mass spectrometry (EC-MS) forms a powerful analytical technique with unique applications in the fields of drug metabolism and proteomics. In this review the latest developments are surveyed from both instrumental and application perspectives. Th

  1. Solid state drug-polymer miscibility studies using the model drug ABT-102.

    Science.gov (United States)

    Jog, Rajan; Gokhale, Rajeev; Burgess, Diane J

    2016-07-25

    Amorphous solid dispersions typically suffer storage stability issues due to: their amorphous nature, high drug loading, uneven drug:stabilizer ratio and plasticization effects as a result of hygroscopic excipients. An extensive solid state miscibility study was conducted to aid in understanding the mechanisms involved in drug/stabilizer interactions. ABT-102 (model drug) and nine different polymers with different molecular weights and viscosities were selected to investigate drug/polymer miscibility. Three different polymer:drug ratios (1:3, 1:1 and 3:1, w/w) were analyzed using: DSC, FTIR and PXRD. Three different techniques were used to prepare the amorphous solid dispersions: serial dilution, solvent evaporation and spray drying. Spray drying was the best method to obtain amorphous solid dispersions. However, under certain conditions amorphous formulations could be obtained using solvent evaporation. Melting point depression was used to calculate interaction parameters and free energy of mixing for the various drug polymer mixtures. The spray dried solid dispersions yielded a negative free energy of mixing which indicated strong drug-polymer miscibility compared to the solvent evaporation and serial dilution method. Soluplus was the best stabilizer compared to PVP and HPMC, which is probably a consequence of strong hydrogen bonding between the two CO moieties of soluplus and the drug NH moieities. Copyright © 2016. Published by Elsevier B.V.

  2. Towards a pragmatic human migraine model for drug testing

    DEFF Research Database (Denmark)

    Hansen, Emma Katrine; Olesen, Jes

    2017-01-01

    BACKGROUND: A model for the testing of novel anti-migraine drugs should preferably use healthy volunteers for ease of recruiting. Isosorbide-5-mononitrate (5-ISMN) provokes headache in healthy volunteers with some migraine features such as pulsating pain quality and aggravation by physical activity...... drug testing....

  3. A Mathematical Model for HIV Drug-Resistance

    Science.gov (United States)

    Faedo, Ivan; Raimundo, Silvia Martorano; Venturino, Ezio

    2010-09-01

    In this paper we present a mathematical model of the transmission of HIV infection here the individuals receive antiretroviral drugs but may not respond to treatment. In such case the latter can be changed to a different therapy, and individuals may or may not respond also to this second set of drugs.

  4. Hybrid imbalanced data classifier models for computational discovery of antibiotic drug targets.

    Science.gov (United States)

    Kocyigit, Yucel; Seker, Huseyin

    2014-01-01

    Identification of drug candidates is an important but also difficult process. Given drug resistance bacteria that we face, this process has become more important to identify protein candidates that demonstrate antibacterial activity. The aim of this study is therefore to develop a bioinformatics approach that is more capable of identifying a small but effective set of proteins that are expected to show antibacterial activity, subsequently to be used as antibiotic drug targets. As this is regarded as an imbalanced data classification problem due to smaller number of antibiotic drugs available, a hybrid classification model was developed and applied to the identification of antibiotic drugs. The model was developed by taking into account of various statistical models leading to the development of six different hybrid models. The best model has reached the accuracy of as high as 50% compared to earlier study with the accuracy of less than 1% as far as the proportion of the candidates identified and actual antibiotics in the candidate list is concerned.

  5. Bioactive electrospun fish sarcoplasmic proteins as a drug delivery system

    DEFF Research Database (Denmark)

    Stephansen, Karen; Chronakis, Ioannis S.; Jessen, Flemming

    2014-01-01

    Nano-microfibers were made from cod (Gadus morhua) sarcoplasmic proteins (FSP) (Mwelectrospinning technique. The FSP fibers were studied by scanning electron microscopy, and thefiber morphology was found to be strongly dependent on FSP concentration. Interestingly, the FSP...

  6. Photo-synthesis of protein-based nanoparticles and the application in drug delivery

    Energy Technology Data Exchange (ETDEWEB)

    Xie, Jinbing; Wang, Hongyang; Cao, Yi; Qin, Meng, E-mail: qinmeng@nju.edu.cn; Wang, Wei, E-mail: wangwei@nju.edu.cn

    2015-07-15

    Recently, protein-based nanoparticles as drug delivery systems have attracted great interests due to the excellent behavior of high biocompatibility and biodegradability, and low toxicity. However, the synthesis techniques are generally costly, chemical reagents introduced, and especially present difficulties in producing homogeneous monodispersed nanoparticles. Here, we introduce a novel physical method to synthesize protein nanoparticles which can be accomplished under physiological condition only through ultraviolet (UV) illumination. By accurately adjusting the intensity and illumination time of UV light, disulfide bonds in proteins can be selectively reduced and the subsequent self-assembly process can be well controlled. Importantly, the co-assembly can also be dominated when the proteins mixed with either anti-cancer drugs, siRNA, or active targeting molecules. Both in vitro and in vivo experiments indicate that our synthesized protein–drug nanoparticles (drug-loading content and encapsulation efficiency being ca. 8.2% and 70%, respectively) not only possess the capability of traditional drug delivery systems (DDS), but also have a greater drug delivery efficiency to the tumor sites and a better inhibition of tumor growth (only 35% of volume comparing to the natural growing state), indicating it being a novel drug delivery system in tumor therapy.

  7. Predict potential drug targets from the ion channel proteins based on SVM.

    Science.gov (United States)

    Huang, Chen; Zhang, Ruijie; Chen, Zhiqiang; Jiang, Yongshuai; Shang, Zhenwei; Sun, Peng; Zhang, Xuehong; Li, Xia

    2010-02-21

    The identification of molecular targets is a critical step in the drug discovery and development process. Ion channel proteins represent highly attractive drug targets implicated in a diverse range of disorders, in particular in the cardiovascular and central nervous systems. Due to the limits of experimental technique and low-throughput nature of patch-clamp electrophysiology, they remain a target class waiting to be exploited. In our study, we combined three types of protein features, primary sequence, secondary structure and subcellular localization to predict potential drug targets from ion channel proteins applying classical support vector machine (SVM) method. In addition, our prediction comprised two stages. In stage 1, we predicted ion channel target proteins based on whole-genome target protein characteristics. Firstly, we performed feature selection by Mann-Whitney U test, then made predictions to identify potential ion channel targets by SVM and designed a new evaluating indicator Q to prioritize results. In stage 2, we made a prediction based on known ion channel target protein characteristics. Genetic algorithm was used to select features and SVM was used to predict ion channel targets. Then, we integrated results of two stages, and found that five ion channel proteins appeared in both prediction results including CGMP-gated cation channel beta subunit and Gamma-aminobutyric acid receptor subunit alpha-5, etc., and four of which were relative to some nerve diseases. It suggests that these five proteins are potential targets for drug discovery and our prediction strategies are effective.

  8. The Øie-Tozer model of drug distribution and its suitability for drugs with different pharmacokinetic behavior.

    Science.gov (United States)

    Stepensky, David

    2011-10-01

    Drug distribution is a major pharmacokinetic process that affects the time course of drug concentrations in tissues, biological fluids and the resulting pharmacological activities. Drug distribution may follow different pathways and patterns, and is governed by the drug's physicochemical properties and the body's physiology. The classical Øie-Tozer model is frequently used for predicting volume of drug distribution and for pharmacokinetic calculations. In this review, the suitability of the Øie-Tozer model for drugs that exhibit different distribution patterns is critically analyzed and illustrated. The method used is a pharmacokinetic modeling and simulation approach. It is demonstrated that the major limitation of the Øie-Tozer model stems from its focus on the total drug concentrations and not on the active (unbound) concentrations. Moreover, the Øie-Tozer model may be inappropriate for drugs with nonlinear or complex pharmacokinetic behavior, such as biopharmaceuticals, drug conjugates or for drugs incorporated into drug delivery systems. Distribution mechanisms and alternative distribution models for these drugs are discussed. The Øie-Tozer model can serve for predicting unbound volume of drug distribution for 'classical' small molecular mass drugs with linear pharmacokinetics. However, more detailed mechanism-based distribution models should be used in preclinical and clinical settings for drugs that exhibit more complex pharmacokinetic behavior.

  9. Influence of Matrices on 3D-Cultured Prostate Cancer Cells' Drug Response and Expression of Drug-Action Associated Proteins.

    Science.gov (United States)

    Edmondson, Rasheena; Adcock, Audrey F; Yang, Liju

    2016-01-01

    This study investigated the effects of matrix on the behaviors of 3D-cultured cells of two prostate cancer cell lines, LNCaP and DU145. Two biologically-derived matrices, Matrigel and Cultrex BME, and one synthetic matrix, the Alvetex scaffold, were used to culture the cells. The cell proliferation rate, cellular response to anti-cancer drugs, and expression levels of proteins associated with drug sensitivity/resistance were examined and compared amongst the 3D-cultured cells on the three matrices and 2D-cultured cells. The cellular responses upon treatment with two common anti-cancer drugs, Docetaxel and Rapamycin, were examined. The expressions of epidermal growth factor receptor (EGFR) and β-III tubulin in DU145 cells and p53 in LNCaP cells were examined. The results showed that the proliferation rates of cells cultured on the three matrices varied, especially between the synthetic matrix and the biologically-derived matrices. The drug responses and the expressions of drug sensitivity-associated proteins differed between cells on various matrices as well. Among the 3D cultures on the three matrices, increased expression of β-III tubulin in DU145 cells was correlated with increased resistance to Docetaxel, and decreased expression of EGFR in DU145 cells was correlated with increased sensitivity to Rapamycin. Increased expression of a p53 dimer in 3D-cultured LNCaP cells was correlated with increased resistance to Docetaxel. Collectively, the results showed that the matrix of 3D cell culture models strongly influences cellular behaviors, which highlights the imperative need to achieve standardization of 3D cell culture technology in order to be used in drug screening and cell biology studies.

  10. Application of concave microwells to pancreatic tumor spheroids enabling anticancer drug evaluation in a clinically relevant drug resistance model.

    Directory of Open Access Journals (Sweden)

    Sang-Eun Yeon

    Full Text Available Intrinsic drug resistance of pancreatic ductal adenocarcinoma (PDAC warrants studies using models that are more clinically relevant for identifying novel resistance mechanisms as well as for drug development. Tumor spheroids (TS mimic in vivo tumor conditions associated with multicellular resistance and represent a promising model for efficient drug screening, however, pancreatic cancer cells often fail to form spheroids using conventional methods such as liquid overlay. This study describes the induction of TS of human pancreatic cancer cells (Panc-1, Aspc-1, Capan-2 in concave polydimethylsiloxane (PDMS microwell plates and evaluation of their usefulness as an anticancer efficacy test model. All three cell lines showed TS formation with varying degree of necrosis inside TS. Among these, Panc-1 spheroid with spherical morphology, a rather rough surface, and unique adhesion structures were successfully produced with no notable necrosis in concave microwell plates. Panc-1 TS contained growth factors or enzymes such as TGF-β1, CTGF, and MT1-MMP, and extracellular matrix proteins such as collagen type I, fibronectin, and laminin. Panc-1 cells grown as TS showed changes in stem cell populations and in expression levels of miRNAs that may play roles in chemoresistance. Visualization of drug penetration and detection of viability indicators, such as Ki-67 and MitoSOX, were optimized for TS for quantitative analysis. Water-soluble tetrazolium (MTS and acid phosphatase (APH assays were also successfully optimized. Overall, we demonstrated that concave PDMS microwell plates are a novel platform for preparation of TS of weakly aggregating cells and that Panc-1 spheroids may represent a novel three-dimensional model for anti-pancreatic cancer drug screening.

  11. Application of concave microwells to pancreatic tumor spheroids enabling anticancer drug evaluation in a clinically relevant drug resistance model.

    Science.gov (United States)

    Yeon, Sang-Eun; No, Da Yoon; Lee, Sang-Hoon; Nam, Suk Woo; Oh, Il-Hoan; Lee, Jaehwi; Kuh, Hyo-Jeong

    2013-01-01

    Intrinsic drug resistance of pancreatic ductal adenocarcinoma (PDAC) warrants studies using models that are more clinically relevant for identifying novel resistance mechanisms as well as for drug development. Tumor spheroids (TS) mimic in vivo tumor conditions associated with multicellular resistance and represent a promising model for efficient drug screening, however, pancreatic cancer cells often fail to form spheroids using conventional methods such as liquid overlay. This study describes the induction of TS of human pancreatic cancer cells (Panc-1, Aspc-1, Capan-2) in concave polydimethylsiloxane (PDMS) microwell plates and evaluation of their usefulness as an anticancer efficacy test model. All three cell lines showed TS formation with varying degree of necrosis inside TS. Among these, Panc-1 spheroid with spherical morphology, a rather rough surface, and unique adhesion structures were successfully produced with no notable necrosis in concave microwell plates. Panc-1 TS contained growth factors or enzymes such as TGF-β1, CTGF, and MT1-MMP, and extracellular matrix proteins such as collagen type I, fibronectin, and laminin. Panc-1 cells grown as TS showed changes in stem cell populations and in expression levels of miRNAs that may play roles in chemoresistance. Visualization of drug penetration and detection of viability indicators, such as Ki-67 and MitoSOX, were optimized for TS for quantitative analysis. Water-soluble tetrazolium (MTS) and acid phosphatase (APH) assays were also successfully optimized. Overall, we demonstrated that concave PDMS microwell plates are a novel platform for preparation of TS of weakly aggregating cells and that Panc-1 spheroids may represent a novel three-dimensional model for anti-pancreatic cancer drug screening.

  12. Development and evaluation of mucoadhesive nanoparticles based on thiolated Eudragit for oral delivery of protein drugs

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Yan [Shenyang University, Normal College (China); Yang, Zhijie; Hu, Xi; Zhang, Ling [Shenyang Pharmaceutical University, Department of Pharmaceutics (China); Li, Feng; Li, Meimei [Shenyang University, Normal College (China); Tang, Xing [Shenyang Pharmaceutical University, Department of Pharmaceutics (China); Xiao, Wei, E-mail: wzhzh-nj@tom.com [Jiangsu Kanion Pharmaceutical Co., Ltd (China)

    2015-02-15

    The objective of this study was to develop pH-sensitive Eudragit L100–cysteine/reduced glutathione (Eul–cys/GSH) nanoparticles (NPs), which provided the mucoadhesion and protection for protein drugs against enzymatic degradation. Insulin was chosen as a model biomolecule for testing this system. The Eul–cys conjugate, which was obtained by grafting cysteine onto the carboxy group of Eudragit L100, was analyzed by HNMR and SEM, and the swelling degree (SD), cation binding, and enzymatic inhibition were also determined. The results obtained showed that the Eul–cys conjugate represent a pH-sensitive delivery system which effectively protected the insulin from being degraded by the proteases, and this is related to the mechanism of Ca{sup 2+} binding. Insulin-loaded Eul–cys/GSH NPs were prepared by a diffusion method involving an electrostatic interaction between the network structure of the polymer and the embedded proteins, including insulin and GSH. TEM images indicated that Eul–cys/GSH existed as smooth and spherical NPs in aqueous solution with particle sizes of 260 ± 20 nm. The X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) findings showed the presence of amorphous insulin in thiolated NPs and higher free thiol oxidation than the result obtained by Ellman’s reagent method. In addition, thiolated NPs showed excellent binding efficiency to the mucin in rat intestine, indicating that Eul–cys/GSH NPs have great potential to be applied as safe carriers for the oral administration of protein drugs.

  13. Pharmacological modeling and biostatistical analysis of a new drug

    Directory of Open Access Journals (Sweden)

    Revathi Ananthakrishnan

    2010-04-01

    Full Text Available Revathi Ananthakrishnan1, Philimon Gona21Cambridge, MA, USA; 2Boston University, Mathematics and Statistics Department, 111 Cummington St, Boston, MA-02215, USAAbstract: Clinical research and clinical trials of experimental drugs to treat human diseases have gained greater importance in recent years. Phase I–IV clinical trials offer patients the opportunity to gain access to a new, more efficacious and safer medication to alleviate or cure their disease. There are potential side effects of every new drug; however, such trials and studies are crucial for drug development and testing in humans. The US Food and Drug Administration (FDA regulated process of evaluating a new drug for treating a particular disease in humans is long, rigorous, and includes the stages starting from preclinical research through the entire human clinical trials process. This review synthesizes results from the above stages and describes the entire mechanism of the clinical study of a new drug for human disease. It emphasizes the associated mathematical modeling and statistical analyses, and bridges pharmacological modeling and biostatistics in clinical research and also provides a basic theoretical overview to biomedical experimentalists. The modern trend in clinical research involves a unified approach among several biomedical subspecialties and it is hoped that even more integrated studies of new drugs will continue to be carried out, leading to novel drugs that are highly effective in curing the associated condition.Keywords: PK/PD pharmacological modeling, biostatistical analyses of clinical trials data, clinical trials, phases of clinical trials, types and designs of clinical trials

  14. Rational use of plasma protein and tissue binding data in drug design.

    Science.gov (United States)

    Liu, Xingrong; Wright, Matthew; Hop, Cornelis E C A

    2014-10-23

    It is a commonly accepted assumption that only unbound drug molecules are available to interact with their targets. Therefore, one of the objectives in drug design is to optimize the compound structure to increase in vivo unbound drug concentration. In this review, theoretical analyses and experimental observations are presented to illustrate that low plasma protein binding does not necessarily lead to high in vivo unbound plasma concentration. Similarly, low brain tissue binding does not lead to high in vivo unbound brain tissue concentration. Instead, low intrinsic clearance leads to high in vivo unbound plasma concentration, and low efflux transport activity at the blood-brain barrier leads to high unbound brain concentration. Plasma protein and brain tissue binding are very important parameters in understanding pharmacokinetics, pharmacodynamics, and toxicities of drugs, but these parameters should not be targeted for optimization in drug design.

  15. Teratogenic Potential of Antiepileptic Drugs in the Zebrafish Model

    Directory of Open Access Journals (Sweden)

    Sung Hak Lee

    2013-01-01

    Full Text Available The zebrafish model is an attractive candidate for screening of developmental toxicity during early drug development. Antiepileptic drugs (AEDs arouse concern for the risk of teratogenicity, but the data are limited. In this study, we evaluated the teratogenic potential of seven AEDs (carbamazepine (CBZ, ethosuximide (ETX, valproic acid (VPN, lamotrigine (LMT, lacosamide (LCM, levetiracetam (LVT, and topiramate (TPM in the zebrafish model. Zebrafish embryos were exposed to AEDs from initiation of gastrula (5.25 hours post-fertilization (hpf to termination of hatching (72 hpf which mimic the mammalian teratogenic experimental design. The lethality and teratogenic index (TI of AEDs were determined and the TI values of each drug were compared with the US FDA human pregnancy categories. Zebrafish model was useful screening model for teratogenic potential of antiepilepsy drugs and was in concordance with in vivo mammalian data and human clinical data.

  16. Statistical Agent Based Modelization of the Phenomenon of Drug Abuse

    Science.gov (United States)

    di Clemente, Riccardo; Pietronero, Luciano

    2012-07-01

    We introduce a statistical agent based model to describe the phenomenon of drug abuse and its dynamical evolution at the individual and global level. The agents are heterogeneous with respect to their intrinsic inclination to drugs, to their budget attitude and social environment. The various levels of drug use were inspired by the professional description of the phenomenon and this permits a direct comparison with all available data. We show that certain elements have a great importance to start the use of drugs, for example the rare events in the personal experiences which permit to overcame the barrier of drug use occasionally. The analysis of how the system reacts to perturbations is very important to understand its key elements and it provides strategies for effective policy making. The present model represents the first step of a realistic description of this phenomenon and can be easily generalized in various directions.

  17. Statistical Agent Based Modelization of the Phenomenon of Drug Abuse

    CERN Document Server

    Di Clemente, Riccardo; 10.1038/srep00532

    2012-01-01

    We introduce a statistical agent based model to describe the phenomenon of drug abuse and its dynamical evolution at the individual and global level. The agents are heterogeneous with respect to their intrinsic inclination to drugs, to their budget attitude and social environment. The various levels of drug use were inspired by the professional description of the phenomenon and this permits a direct comparison with all available data. We show that certain elements have a great importance to start the use of drugs, for example the rare events in the personal experiences which permit to overcame the barrier of drug use occasionally. The analysis of how the system reacts to perturbations is very important to understand its key elements and it provides strategies for effective policy making. The present model represents the first step of a realistic description of this phenomenon and can be easily generalized in various directions.

  18. Development of novel protein-Ag nanocomposite for drug delivery and inactivation of bacterial applications.

    Science.gov (United States)

    Vimala, Kanikireddy; Varaprasad, Kokkarachedu; Sadiku, Rotimi; Ramam, Koduri; Kanny, Krishnan

    2014-02-01

    The potential applications, in the biomedical fields, of curcumin loaded silver nanocomposite were studied by using bovine serum albumin (protein) and acrylamide. The design and development of silver nanoparticles with small size and adequate stability are very important, in addition to their applicability, particularly in bio-medicine. In this study, silver nanoparticles were prepared by chemical reduction method, employing sodium borohydride as the reducing agent for silver nanoparticles. The properties of the protein hydrogels formed were characterized via Fourier transform infrared spectroscopy and X-ray diffraction analyses. The size and its distribution, and formation of metal nanoparticles were confirmed by transmission electron microscopy indicating the diameter of the silver nanoparticles in the range of 3-8 nm. The thermal study of curcumin-silver nanocomposite hydrogels was determined by thermo-gravimetric analysis. In order to increase the antibacterial activity of theses inorganic nanomaterials, natural biological curcumin was incorporated into the protein hydrogel. The main emphasis in this investigation is to increase the antibacterial activity of the hydrogels by loading curcumin, for advanced medical application and as a model drug.

  19. Use of a physiologically based pharmacokinetic model to simulate drug-drug interactions between antineoplastic and antiretroviral drugs.

    Science.gov (United States)

    Moltó, José; Rajoli, Rajith; Back, David; Valle, Marta; Miranda, Cristina; Owen, Andrew; Clotet, Bonaventura; Siccardi, Marco

    2017-03-01

    Co-administration of antineoplastics with ART is challenging due to potential drug-drug interactions (DDIs). However, trials specifically assessing such DDIs are lacking. Our objective was to simulate DDIs between the antineoplastics erlotinib and gefitinib with key antiretroviral drugs and to predict dose adjustments using a physiologically based pharmacokinetic (PBPK) model. In vitro data describing chemical properties and pharmacokinetic processes of each drug and their effect on cytochrome P450 isoforms were obtained from the literature. Plasma drug-concentration profiles were simulated in a virtual population of 50 individuals receiving erlotinib or gefitinib alone or with darunavir/ritonavir, efavirenz or etravirine. Simulated pharmacokinetic parameters and the magnitude of DDIs with probe drugs (midazolam, maraviroc) were compared with literature values. Erlotinib and gefitinib pharmacokinetics with and without antiretrovirals were compared and dose-adjustment strategies were evaluated. Simulated parameters of each drug and the magnitude of DDIs with probe drugs were in agreement with reference values. Darunavir/ritonavir increased erlotinib and gefitinib exposure, while efavirenz and etravirine decreased erlotinib and gefitinib concentrations. Based on our predictions, dose-adjustment strategies may consist of once-daily dosing erlotinib at 25 mg and gefitinib at 125 mg with darunavir/ritonavir; or erlotinib at 200 mg and gefitinib at 375 mg with etravirine. The interaction with efavirenz was not overcome even after doubling erlotinib or gefitinib doses. PBPK models predicted the in vivo pharmacokinetics of erlotinib, gefitinib and the antiretrovirals darunavir/ritonavir, efavirenz and etravirine, and the DDIs between them. The simulated dose-adjustments may represent valuable strategies to optimize antineoplastic therapy in HIV-infected patients.

  20. PBPK modeling and simulation in drug research and development

    OpenAIRE

    Xiaomei Zhuang; Chuang Lu

    2016-01-01

    Physiologically based pharmacokinetic (PBPK) modeling and simulation can be used to predict the pharmacokinetic behavior of drugs in humans using preclinical data. It can also explore the effects of various physiologic parameters such as age, ethnicity, or disease status on human pharmacokinetics, as well as guide dose and dose regiment selection and aid drug–drug interaction risk assessment. PBPK modeling has developed rapidly in the last decade within both the field of academia and the phar...

  1. Pharmacokinetic, pharmacodynamic and biodistribution following oral administration of nanocarriers containing peptide and protein drugs.

    Science.gov (United States)

    Griffin, Brendan T; Guo, Jianfeng; Presas, Elena; Donovan, Maria D; Alonso, María J; O'Driscoll, Caitriona M

    2016-11-15

    The influence of nanoparticle (NP) formulations on the pharmacokinetic, pharmacodynamic and biodistribution profiles of peptide- and protein-like drugs following oral administration is critically reviewed. The possible mechanisms of absorption enhancement and the effects of the physicochemical properties of the NP are examined. The potential advantages and challenges of physiologically-based pharmacokinetic (PBPK) modelling to help predict efficacy in man are discussed. The importance of developing and expanding the regulatory framework to help translate the technology into the clinic and accelerate the availability of oral nanoparticulate formulations is emphasized. In conclusion, opportunities for future work to improve the state of the art of oral nanomedicines are identified. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. Drug/protein interactions studied by time-resolved fluorescence spectroscopy

    Science.gov (United States)

    Gustavsson, Thomas; Markovitsi, Dimitra; Vayá, Ignacio; Bonancía, Paula; Jiménez, M. C.; Miranda, Miguel A.

    2014-09-01

    We report here on a recent time-resolved fluorescence study [1] of the interaction between flurbiprofen (FBP), a chiral non-steroidal anti-inflammatory drug, and human serum albumin (HSA), the main transport protein in the human body. We compare the results obtained for the drug-protein complex with those of various covalently linked flurbiprofentryptophan dyads having well-defined geometries. In all cases stereoselective dynamic fluorescence quenching is observed, varying greatly from one system to another. In addition, the fluorescence anisotropy decays also display a clear stereoselectivity. For the drug-protein complexes, this can be interpreted in terms of the protein microenvironment playing a significant role in the conformational relaxation of FBP, which is more restricted in the case of the (R)- enantiomer.

  3. Modeling and Simulation of In Vivo Drug Effects.

    Science.gov (United States)

    Lippert, Jörg; Burghaus, Rolf; Kuepfer, Lars; Ploeger, Bart; Schaller, Stephan; Schmitt, Walter; Willmann, Stefan

    2016-01-01

    The concept of a pharmacokinetics-pharmacodynamics (PK/PD) assessment of drug development candidates is well established in pharmaceutical research and development, and PK/PD modeling is common practice in all pharmaceutical companies. A recent analysis (Morgan et al., Drug Discov Today 17(9-10):419-424, 2012) revealed however that insufficient certainty in the integrity of the causal chain of fundamental pharmacological steps from drug dosing through systemic exposure, target tissue exposure, and engagement of molecular target to pharmacological response is still the major driver of failure in phase II of clinical drug development. Despite the rise of molecular biomarkers, ethical, scientific, and practical constraints very often still prevent a direct assessment of each necessary step ultimately leading to an intended drug effect or an unintended adverse reaction. Yet, incomplete investigation of the causality of drug responses is a major risk for translational assessments and the prediction of drug responses in different species or other populations. Mechanism-based modeling and simulation (M&S) offers a means to investigate complex physiological and pharmacological processes and to complement experimental data for non-accessible steps in the pharmacological causal chain. With the help of two examples, it is illustrated, what level of physiological detail, state-of-the-art models can represent, how predictive these models are and how mechanism-based approaches can be combined with empirical correlation-based concepts.

  4. Drug discovery and development for neglected diseases: the DNDi model

    Directory of Open Access Journals (Sweden)

    Eric Chatelain

    2011-03-01

    Full Text Available Eric Chatelain, Jean-Robert IosetDrugs for Neglected Diseases Initiative (DNDi, Geneva, SwitzerlandAbstract: New models of drug discovery have been developed to overcome the lack of modern and effective drugs for neglected diseases such as human African trypanosomiasis (HAT; sleeping sickness, leishmaniasis, and Chagas disease, which have no financial viability for the pharmaceutical industry. With the purpose of combining the skills and research capacity in academia, pharmaceutical industry, and contract researchers, public–private partnerships or product development partnerships aim to create focused research consortia that address all aspects of drug discovery and development. These consortia not only emulate the projects within pharmaceutical and biotechnology industries, eg, identification and screening of libraries, medicinal chemistry, pharmacology and pharmacodynamics, formulation development, and manufacturing, but also use and strengthen existing capacity in disease-endemic countries, particularly for the conduct of clinical trials. The Drugs for Neglected Diseases initiative (DNDi has adopted a model closely related to that of a virtual biotechnology company for the identification and optimization of drug leads. The application of this model to the development of drug candidates for the kinetoplastid infections of HAT, Chagas disease, and leishmaniasis has already led to the identification of new candidates issued from DNDi’s own discovery pipeline. This demonstrates that the model DNDi has been implementing is working but its DNDi, neglected diseases sustainability remains to be proven.Keywords: R&D, screening, lead optimization, human African trypanosomiasis, leishmaniasis, Chagas disease, product development partnerships

  5. Learning generative models for protein fold families.

    Science.gov (United States)

    Balakrishnan, Sivaraman; Kamisetty, Hetunandan; Carbonell, Jaime G; Lee, Su-In; Langmead, Christopher James

    2011-04-01

    We introduce a new approach to learning statistical models from multiple sequence alignments (MSA) of proteins. Our method, called GREMLIN (Generative REgularized ModeLs of proteINs), learns an undirected probabilistic graphical model of the amino acid composition within the MSA. The resulting model encodes both the position-specific conservation statistics and the correlated mutation statistics between sequential and long-range pairs of residues. Existing techniques for learning graphical models from MSA either make strong, and often inappropriate assumptions about the conditional independencies within the MSA (e.g., Hidden Markov Models), or else use suboptimal algorithms to learn the parameters of the model. In contrast, GREMLIN makes no a priori assumptions about the conditional independencies within the MSA. We formulate and solve a convex optimization problem, thus guaranteeing that we find a globally optimal model at convergence. The resulting model is also generative, allowing for the design of new protein sequences that have the same statistical properties as those in the MSA. We perform a detailed analysis of covariation statistics on the extensively studied WW and PDZ domains and show that our method out-performs an existing algorithm for learning undirected probabilistic graphical models from MSA. We then apply our approach to 71 additional families from the PFAM database and demonstrate that the resulting models significantly out-perform Hidden Markov Models in terms of predictive accuracy.

  6. Site-specific antibody-drug conjugates: the nexus of bioorthogonal chemistry, protein engineering, and drug development.

    Science.gov (United States)

    Agarwal, Paresh; Bertozzi, Carolyn R

    2015-02-18

    Antibody-drug conjugates (ADCs) combine the specificity of antibodies with the potency of small molecules to create targeted drugs. Despite the simplicity of this concept, generation of clinically successful ADCs has been very difficult. Over the past several decades, scientists have learned a great deal about the constraints on antibodies, linkers, and drugs as they relate to successful construction of ADCs. Once these components are in hand, most ADCs are prepared by nonspecific modification of antibody lysine or cysteine residues with drug-linker reagents, which results in heterogeneous product mixtures that cannot be further purified. With advances in the fields of bioorthogonal chemistry and protein engineering, there is growing interest in producing ADCs by site-specific conjugation to the antibody, yielding more homogeneous products that have demonstrated benefits over their heterogeneous counterparts in vivo. Here, we chronicle the development of a multitude of site-specific conjugation strategies for assembly of ADCs and provide a comprehensive account of key advances and their roots in the fields of bioorthogonal chemistry and protein engineering.

  7. Illustrating and homology modeling the proteins of the Zika virus

    Science.gov (United States)

    Ekins, Sean; Liebler, John; Neves, Bruno J.; Lewis, Warren G.; Coffee, Megan; Bienstock, Rachelle; Southan, Christopher; Andrade, Carolina H.

    2016-01-01

    The Zika virus (ZIKV) is a flavivirus of the family Flaviviridae, which is similar to dengue virus, yellow fever and West Nile virus. Recent outbreaks in South America, Latin America, the Caribbean and in particular Brazil have led to concern for the spread of the disease and potential to cause Guillain-Barré syndrome and microcephaly. Although ZIKV has been known of for over 60 years there is very little in the way of knowledge of the virus with few publications and no crystal structures. No antivirals have been tested against it either in vitro or in vivo. ZIKV therefore epitomizes a neglected disease. Several suggested steps have been proposed which could be taken to initiate ZIKV antiviral drug discovery using both high throughput screens as well as structure-based design based on homology models for the key proteins. We now describe preliminary homology models created for NS5, FtsJ, NS4B, NS4A, HELICc, DEXDc, peptidase S7, NS2B, NS2A, NS1, E stem, glycoprotein M, propeptide, capsid and glycoprotein E using SWISS-MODEL. Eleven out of 15 models pass our model quality criteria for their further use. While a ZIKV glycoprotein E homology model was initially described in the immature conformation as a trimer, we now describe the mature dimer conformer which allowed the construction of an illustration of the complete virion. By comparing illustrations of ZIKV based on this new homology model and the dengue virus crystal structure we propose potential differences that could be exploited for antiviral and vaccine design. The prediction of sites for glycosylation on this protein may also be useful in this regard. While we await a cryo-EM structure of ZIKV and eventual crystal structures of the individual proteins, these homology models provide the community with a starting point for structure-based design of drugs and vaccines as well as a for computational virtual screening. PMID:27746901

  8. Illustrating and homology modeling the proteins of the Zika virus.

    Science.gov (United States)

    Ekins, Sean; Liebler, John; Neves, Bruno J; Lewis, Warren G; Coffee, Megan; Bienstock, Rachelle; Southan, Christopher; Andrade, Carolina H

    2016-01-01

    The Zika virus (ZIKV) is a flavivirus of the family Flaviviridae, which is similar to dengue virus, yellow fever and West Nile virus. Recent outbreaks in South America, Latin America, the Caribbean and in particular Brazil have led to concern for the spread of the disease and potential to cause Guillain-Barré syndrome and microcephaly. Although ZIKV has been known of for over 60 years there is very little in the way of knowledge of the virus with few publications and no crystal structures. No antivirals have been tested against it either in vitro or in vivo. ZIKV therefore epitomizes a neglected disease. Several suggested steps have been proposed which could be taken to initiate ZIKV antiviral drug discovery using both high throughput screens as well as structure-based design based on homology models for the key proteins. We now describe preliminary homology models created for NS5, FtsJ, NS4B, NS4A, HELICc, DEXDc, peptidase S7, NS2B, NS2A, NS1, E stem, glycoprotein M, propeptide, capsid and glycoprotein E using SWISS-MODEL. Eleven out of 15 models pass our model quality criteria for their further use. While a ZIKV glycoprotein E homology model was initially described in the immature conformation as a trimer, we now describe the mature dimer conformer which allowed the construction of an illustration of the complete virion. By comparing illustrations of ZIKV based on this new homology model and the dengue virus crystal structure we propose potential differences that could be exploited for antiviral and vaccine design. The prediction of sites for glycosylation on this protein may also be useful in this regard. While we await a cryo-EM structure of ZIKV and eventual crystal structures of the individual proteins, these homology models provide the community with a starting point for structure-based design of drugs and vaccines as well as a for computational virtual screening.

  9. Computational modeling in melanoma for novel drug discovery.

    Science.gov (United States)

    Pennisi, Marzio; Russo, Giulia; Di Salvatore, Valentina; Candido, Saverio; Libra, Massimo; Pappalardo, Francesco

    2016-06-01

    There is a growing body of evidence highlighting the applications of computational modeling in the field of biomedicine. It has recently been applied to the in silico analysis of cancer dynamics. In the era of precision medicine, this analysis may allow the discovery of new molecular targets useful for the design of novel therapies and for overcoming resistance to anticancer drugs. According to its molecular behavior, melanoma represents an interesting tumor model in which computational modeling can be applied. Melanoma is an aggressive tumor of the skin with a poor prognosis for patients with advanced disease as it is resistant to current therapeutic approaches. This review discusses the basics of computational modeling in melanoma drug discovery and development. Discussion includes the in silico discovery of novel molecular drug targets, the optimization of immunotherapies and personalized medicine trials. Mathematical and computational models are gradually being used to help understand biomedical data produced by high-throughput analysis. The use of advanced computer models allowing the simulation of complex biological processes provides hypotheses and supports experimental design. The research in fighting aggressive cancers, such as melanoma, is making great strides. Computational models represent the key component to complement these efforts. Due to the combinatorial complexity of new drug discovery, a systematic approach based only on experimentation is not possible. Computational and mathematical models are necessary for bringing cancer drug discovery into the era of omics, big data and personalized medicine.

  10. From G Protein-coupled Receptor Structure Resolution to Rational Drug Design.

    Science.gov (United States)

    Jazayeri, Ali; Dias, Joao M; Marshall, Fiona H

    2015-08-07

    A number of recent technical solutions have led to significant advances in G protein-coupled receptor (GPCR) structural biology. Apart from a detailed mechanistic view of receptor activation, the new structures have revealed novel ligand binding sites. Together, these insights provide avenues for rational drug design to modulate the activities of these important drug targets. The application of structural data to GPCR drug discovery ushers in an exciting era with the potential to improve existing drugs and discover new ones. In this review, we focus on technical solutions that have accelerated GPCR crystallography as well as some of the salient findings from structures that are relevant to drug discovery. Finally, we outline some of the approaches used in GPCR structure based drug design.

  11. Chemical genetics and drug screening in Drosophila cancer models

    Institute of Scientific and Technical Information of China (English)

    Mara Gladstone; Tin Tin Su

    2011-01-01

    Drug candidates often fail in preclinical and clinical testing because of reasons of efficacy and/or safety.It would be time- and cost-efficient to have screening models that reduce the rate of such false positive candidates that appear promising at first but fail later.In this regard,it would be particularly useful to have a rapid and inexpensive whole animal model that can pre-select hits from high-throughput screens but before testing in costly rodent assays.Drosophila melanogaster has emerged as a potential whole animal model for drug screening.Of particular interest have been drugs that must act in the context of multi-cellularity such as those for neurological disorders and cancer.A recent review provides a comprehensive summary of drug screening in Drosophila,but with an emphasis on neurodegenerative disorders.Here,we review Drosophila screens in the literature aimed at cancer therapeutics.

  12. A novel evolutionary drug scheduling model in cancer chemotherapy.

    Science.gov (United States)

    Liang, Yong; Leung, Kwong-Sak; Mok, Tony Shu Kam

    2006-04-01

    In this paper, we introduce a modified optimal control model of drug scheduling in cancer chemotherapy and a new adaptive elitist-population-based genetic algorithm (AEGA) to solve it. Working closely with an oncologist, we first modify the existing model, because its equation for the cumulative drug toxicity is inconsistent with medical knowledge and clinical experience. To explore multiple efficient drug scheduling policies, we propose a novel variable representation--a cycle-wise representation, and modify the elitist genetic search operators in the AEGA. The simulation results obtained by the modified model match well with the clinical treatment experiences, and can provide multiple efficient solutions for oncologists to consider. Moreover, it has been shown that the evolutionary drug scheduling approach is simple, and capable of solving complex cancer chemotherapy problems by adapting multimodal versions of evolutionary algorithms.

  13. Animal Migraine Models for Drug Development

    DEFF Research Database (Denmark)

    Jansen-Olesen, Inger; Tfelt-Hansen, Peer; Olesen, Jes

    2013-01-01

    responses are likely to be behavioral, allowing multiple experiments in each individual animal. Distinction is made between acute and prophylactic models and how to validate each of them. Modern insight into neurobiological mechanisms of migraine is so good that it is only a question of resources...... for headache has almost come to a standstill partly because of a lack of valid animal models. Here we review previous models with emphasis on optimal characteristics of a future model. In addition to selection of animal species, the method of induction of migraine-like changes and the method of recording...

  14. PDTD: a web-accessible protein database for drug target identification

    Directory of Open Access Journals (Sweden)

    Gao Zhenting

    2008-02-01

    Full Text Available Abstract Background Target identification is important for modern drug discovery. With the advances in the development of molecular docking, potential binding proteins may be discovered by docking a small molecule to a repository of proteins with three-dimensional (3D structures. To complete this task, a reverse docking program and a drug target database with 3D structures are necessary. To this end, we have developed a web server tool, TarFisDock (Target Fishing Docking http://www.dddc.ac.cn/tarfisdock, which has been used widely by others. Recently, we have constructed a protein target database, Potential Drug Target Database (PDTD, and have integrated PDTD with TarFisDock. This combination aims to assist target identification and validation. Description PDTD is a web-accessible protein database for in silico target identification. It currently contains >1100 protein entries with 3D structures presented in the Protein Data Bank. The data are extracted from the literatures and several online databases such as TTD, DrugBank and Thomson Pharma. The database covers diverse information of >830 known or potential drug targets, including protein and active sites structures in both PDB and mol2 formats, related diseases, biological functions as well as associated regulating (signaling pathways. Each target is categorized by both nosology and biochemical function. PDTD supports keyword search function, such as PDB ID, target name, and disease name. Data set generated by PDTD can be viewed with the plug-in of molecular visualization tools and also can be downloaded freely. Remarkably, PDTD is specially designed for target identification. In conjunction with TarFisDock, PDTD can be used to identify binding proteins for small molecules. The results can be downloaded in the form of mol2 file with the binding pose of the probe compound and a list of potential binding targets according to their ranking scores. Conclusion PDTD serves as a comprehensive and

  15. Cannabinoid CB1 receptor-interacting proteins: novel targets for central nervous system drug discovery?

    Science.gov (United States)

    Smith, Tricia H; Sim-Selley, Laura J; Selley, Dana E

    2010-06-01

    The main pharmacological effects of marijuana, as well as synthetic and endogenous cannabinoids, are mediated through G-protein-coupled receptors (GPCRs), including CB(1) and CB(2) receptors. The CB(1) receptor is the major cannabinoid receptor in the central nervous system and has gained increasing interest as a target for drug discovery for treatment of nausea, cachexia, obesity, pain, spasticity, neurodegenerative diseases and mood and substance abuse disorders. Evidence has accumulated to suggest that CB(1) receptors, like other GPCRs, interact with and are regulated by several other proteins beyond the established role of heterotrimeric G-proteins. These proteins, which include the GPCR kinases, beta-arrestins, GPCR-associated sorting proteins, factor associated with neutral sphingomyelinase, other GPCRs (heterodimerization) and the novel cannabinoid receptor-interacting proteins: CRIP(1a/b), are thought to play important roles in the regulation of intracellular trafficking, desensitization, down-regulation, signal transduction and constitutive activity of CB(1) receptors. This review examines CB(1) receptor-interacting proteins, including heterotrimeric G-proteins, but with particular emphasis on non-G-protein entities, that might comprise the CB(1) receptosomal complex. The evidence for direct interaction with CB(1) receptors and potential functional roles of these interacting proteins is discussed, as are future directions and challenges in this field with an emphasis on the possibility of eventually targeting these proteins for drug discovery.

  16. Homology modelling and insilico analysis of neuraminidase protein in H1N1 Influenza A virus

    Directory of Open Access Journals (Sweden)

    Abhilash Manohar

    2011-02-01

    Full Text Available In this work, modelling of Neuraminidase protein of Influenza A virus (A/Himeji/1/2009(H1N1 neuraminidase (NA protein was done using Modeller 9V2. Modelled structure was submitted to protein model database and could be downloaded using accession number PM0075830. The modelled protein structure was subjected to In silco analysis using various bioinformatics tools. Two anti-influenza drugs currently being used to treat infected patients are oseltamivir (Tamiflu and zanamivir (Relenza, both of which target the neuraminidase enzyme of the virus. Reports of the emergence of drug resistance make the development of new anti-influenza molecules a priority. Hence the modelled structure of H1NI Neuraminidase could be very useful for in silico analysis of potential neuraminidase inhibitors.

  17. Drug-loaded electrospun mats of poly(vinyl alcohol) fibres and their release characteristics of four model drugs

    Science.gov (United States)

    Taepaiboon, Pattama; Rungsardthong, Uracha; Supaphol, Pitt

    2006-05-01

    Mats of PVA nanofibres were successfully prepared by the electrospinning process and were developed as carriers of drugs for a transdermal drug delivery system. Four types of non-steroidal anti-inflammatory drug with varying water solubility property, i.e. sodium salicylate (freely soluble in water), diclofenac sodium (sparingly soluble in water), naproxen (NAP), and indomethacin (IND) (both insoluble in water), were selected as model drugs. The morphological appearance of the drug-loaded electrospun PVA mats depended on the nature of the model drugs. The 1H-nuclear magnetic resonance results confirmed that the electrospinning process did not affect the chemical integrity of the drugs. Thermal properties of the drug-loaded electrospun PVA mats were analysed by differential scanning calorimetry and thermogravimetric analysis. The molecular weight of the model drugs played a major role on both the rate and the total amount of drugs released from the as-prepared drug-loaded electrospun PVA mats, with the rate and the total amount of the drugs released decreasing with increasing molecular weight of the drugs. Lastly, the drug-loaded electrospun PVA mats exhibited much better release characteristics of the model drugs than drug-loaded as-cast films.

  18. Heat Shock Protein (HSP) Drug Discovery and Development: Targeting Heat Shock Proteins in Disease

    Science.gov (United States)

    Shrestha, Liza; Bolaender, Alexander; Patel, Hardik J.; Taldone, Tony

    2016-01-01

    Heat shock proteins (HSPs) present as a double edged sword. While they play an important role in maintaining protein homeostasis in a normal cell, cancer cells have evolved to co-opt HSP function to promote their own survival. As a result, HSPs such as HSP90 have attracted a great deal of interest as a potential anticancer target. These efforts have resulted in over 20 distinct compounds entering clinical evaluation for the treatment of cancer. However, despite the potent anticancer activity demonstrated in preclinical models, to date no HSP90 inhibitor has obtained regulatory approval. In this review we discuss the unique challenges faced in targeting HSPs that have likely contributed to their lack of progress in the clinic and suggest ways to overcome these so that the enormous potential of these compounds to benefit patients can finally be realized. We also provide a guideline for the future development of HSP-targeted agents based on the many lessons learned during the last two decades in developing HSP90 inhibitors. PMID:27072696

  19. Computational modeling of drug response with applications to neuroscience.

    Science.gov (United States)

    Herwig, Ralf

    2014-12-01

    The development of novel high-throughput technologies has opened up the opportunity to deeply characterize patient tissues at various molecular levels and has given rise to a paradigm shift in medicine towards personalized therapies. Computational analysis plays a pivotal role in integrating the various genome data and understanding the cellular response to a drug. Based on that data, molecular models can be constructed that incorporate the known downstream effects of drug-targeted receptor molecules and that predict optimal therapy decisions. In this article, we describe the different steps in the conceptual framework of computational modeling. We review resources that hold information on molecular pathways that build the basis for constructing the model interaction maps, highlight network analysis concepts that have been helpful in identifying predictive disease patterns, and introduce the basic concepts of kinetic modeling. Finally, we illustrate this framework with selected studies related to the modeling of important target pathways affected by drugs.

  20. Advanced progress of microencapsulation technologies: in vivo and in vitro models for studying oral and transdermal drug deliveries.

    Science.gov (United States)

    Lam, P L; Gambari, R

    2014-03-28

    This review provides an overall discussion of microencapsulation systems for both oral and transdermal drug deliveries. Clinically, many drugs, especially proteins and peptides, are susceptible to the gastrointestinal tract and the first-pass metabolism after oral administration while some drugs exhibit low skin permeability through transdermal delivery route. Medicated microcapsules as oral and transdermal drug delivery vehicles are believed to offer an extended drug effect at a relatively low dose and provide a better patient compliance. The polymeric microcapsules can be produced by different microencapsulation methods and the drug microencapsulation technology provides the quality preservation for drug stabilization. The release of the entrapped drug is controlled and prolonged for specific usages. Some recent studies have focused on the evaluation of drug containing microcapsules on potential biological and therapeutic applications. For the oral delivery, in vivo animal models were used for evaluating possible treatment effects of drug containing microcapsules. For the transdermal drug delivery, skin delivery models were introduced to investigate the potential skin delivery of medicated microcapsules. Finally, the challenges and limitations of drug microencapsulation in real life are discussed and the commercially available drug formulations using microencapsulation technology for oral and transdermal applications are shown.

  1. Recent advances in protein and Peptide drug delivery: a special emphasis on polymeric nanoparticles.

    Science.gov (United States)

    Patel, Ashaben; Patel, Mitesh; Yang, Xiaoyan; Mitra, Ashim K

    2014-01-01

    Proteins and peptides are widely indicated in many diseased states. Parenteral route is the most commonly em- ployed method of administration for therapeutic proteins and peptides. However, requirement of frequent injections due to short in vivo half-life results in poor patient compliance. Non-invasive drug delivery routes such as nasal, transdermal, pulmonary, and oral offer several advantages over parenteral administration. Intrinsic physicochemical properties and low permeability across biological membrane limit protein delivery via non-invasive routes. One of the strategies to improve protein and peptide absorption is by delivering through nanostructured delivery carriers. Among nanocarriers, polymeric nanoparticles (NPs) have demonstrated significant advantages over other delivery systems. This article summarizes the application of polymeric NPs for protein and peptide drug delivery following oral, nasal, pulmonary, parenteral, transder mal, and ocular administrations.

  2. Understanding Amino Acid Mutations in Hepatitis B Virus Proteins for Rational Design of Vaccines and Drugs.

    Science.gov (United States)

    Shen, Ke; Shen, Li; Wang, Jing; Jiang, Zhi; Shen, Bairong

    2015-01-01

    The hepatitis B virus (HBV) genome encodes four proteins, i.e., DNA polymerase, surface protein, X, and core proteins. HBV undergoes different selective pressures for drug resistance and immune/vaccine escape and mutations are common for the HBV proteins. We here collected all the reported amino acid mutations happened in these four HBV proteins and studied their patterns. The relationship between the mutations and epitopic functions are investigated with bioinformatics tools, based on their sequence information. Some interesting results are observed for the mutation patterns, such as we found the serine and threonine are both for frequently mutated residues and mutant residues, while the tryptophan and methionine have low mutability. The results provide important information for the understanding of the molecular mechanism of virus evolution and therefore will facilitate the future rational design of HBV vaccines or drugs.

  3. Neural network models of protein domain evolution

    OpenAIRE

    Sylvia Nagl

    2000-01-01

    Protein domains are complex adaptive systems, and here a novel procedure is presented that models the evolution of new functional sites within stable domain folds using neural networks. Neural networks, which were originally developed in cognitive science for the modeling of brain functions, can provide a fruitful methodology for the study of complex systems in general. Ethical implications of developing complex systems models of biomolecules are discussed, with particular reference to molecu...

  4. Multivalent drug design and inhibition of cholera toxin by specific and transient protein-ligand interactions.

    Science.gov (United States)

    Liu, Jiyun; Begley, Darren; Mitchell, Daniel D; Verlinde, Christophe L M J; Varani, Gabriele; Fan, Erkang

    2008-05-01

    Multivalent inhibitors of the cholera toxin B pentamer are potential therapeutic drugs for treating cholera and serve as models for demonstrating multivalent ligand effects through a structure-based approach. A crucial yet often overlooked aspect of multivalent drug design is the length, rigidity and chemical composition of the linker used to connect multiple binding moieties. To specifically study the role of chemical linkers in multivalent ligand design, we have synthesized a series of compounds with one and two binding motifs connected by several different linkers. These compounds have affinity for and potency against the cholera toxin B pentamer despite the fact that none can simultaneously bind two toxin receptor sites. Results from saturation transfer difference NMR reveal transient, non-specific interactions between the cholera toxin and linker groups contribute significantly to overall binding affinity of monovalent compounds. However, the same random protein-ligand interactions do not appear to affect binding of bivalent molecules. Moreover, the binding affinities and potencies of these 'non-spanning' bivalent ligands appear to be wholly independent of linker length. Our detailed analysis identifies multiple effects that account for the improved inhibitory potencies of bivalent ligands and suggest approaches to further improve the activity of this class of compounds.

  5. Zebrafish as a potential model organism for drug test against hepatitis C virus.

    Directory of Open Access Journals (Sweden)

    Cun-Bao Ding

    Full Text Available Screening and evaluating anti- hepatitis C virus (HCV drugs in vivo is difficult worldwide, mainly because of the lack of suitable small animal models. We investigate whether zebrafish could be a model organism for HCV replication. To achieve NS5B-dependent replication an HCV sub-replicon was designed and created with two vectors, one with HCV ns5b and fluorescent rfp genes, and the other containing HCV's 5'UTR, core, 3'UTR and fluorescent gfp genes. The vectors containing sub-replicons were co-injected into zebrafish zygotes. The sub-replicon amplified in liver showing a significant expression of HCV core RNA and protein. The sub-replicon amplification caused no abnormality in development and growth of zebrafish larvae, but induced gene expression change similar to that in human hepatocytes. As the amplified core fluorescence in live zebrafish was detectable microscopically, it rendered us an advantage to select those with replicating sub-replicon for drug experiments. Ribavirin and oxymatrine, two known anti-HCV drugs, inhibited sub-replicon amplification in this model showing reduced levels of HCV core RNA and protein. Technically, this method had a good reproducibility and is easy to operate. Thus, zebrafish might be a model organism to host HCV, and this zebrafish/HCV (sub-replicon system could be an animal model for anti-HCV drug screening and evaluation.

  6. Identification and Evaluation of Novel Drug Targets against the Human Fungal Pathogen Aspergillus fumigatus with Elaboration on the Possible Role of RNA-Binding Protein

    Science.gov (United States)

    Malekzadeh, Saeid; Sardari, Soroush; Azerang, Parisa; Khorasanizadeh, Dorsa; Amiri, Solmaz Agha; Azizi, Mohammad; Mohajerani, Nazanin; Khalaj, Vahid

    2017-01-01

    Bakground: Aspergillus fumigatus is an airborne opportunistic fungal pathogen that can cause fatal infections in immunocompromised patients. Although the current anti-fungal therapies are relatively efficient, some issues such as drug toxicity, drug interactions, and the emergence of drug-resistant fungi have promoted the intense research toward finding the novel drug targets. Methods: In search of new antifungal drug targets, we have used a bioinformatics approach to identify novel drug targets. We compared the whole proteome of this organism with yeast Saccharomyces cerevisiae to come up with 153 specific proteins. Further screening of these proteins revealed 50 potential molecular targets in A. fumigatus. Amongst them, RNA-binding protein (RBP) was selected for further examination. The aspergillus fumigatus RBP (AfuRBP), as a peptidylprolyl isomerase, was evaluated by homology modeling and bioinformatics tools. RBP-deficient mutant strains of A. fumigatus were generated and characterized. Furthermore, the susceptibility of these strains to known peptidylprolyl isomerase inhibitors was assessed. Results: AfuRBP-deficient mutants demonstrated a normal growth phenotype. MIC assay results using inhibitors of peptidylprolyl isomerase confirmed a higher sensitivity of these mutants compared to the wild type. Conclusion: Our bioinformatics approach revealed a number of fungal-specific proteins that may be considered as new targets for drug discovery purposes. Peptidylprolyl isomerase, as a possible drug target, was evaluated against two potential inhibitors, and the promising results were investigated mechanistically. Future studies would confirm the impact of such target on the antifungal discovery investigations PMID:28000798

  7. Drug discovery and development for neglected diseases: the DNDi model.

    Science.gov (United States)

    Chatelain, Eric; Ioset, Jean-Robert

    2011-03-16

    New models of drug discovery have been developed to overcome the lack of modern and effective drugs for neglected diseases such as human African trypanosomiasis (HAT; sleeping sickness), leishmaniasis, and Chagas disease, which have no financial viability for the pharmaceutical industry. With the purpose of combining the skills and research capacity in academia, pharmaceutical industry, and contract researchers, public-private partnerships or product development partnerships aim to create focused research consortia that address all aspects of drug discovery and development. These consortia not only emulate the projects within pharmaceutical and biotechnology industries, eg, identification and screening of libraries, medicinal chemistry, pharmacology and pharmacodynamics, formulation development, and manufacturing, but also use and strengthen existing capacity in disease-endemic countries, particularly for the conduct of clinical trials. The Drugs for Neglected Diseases initiative (DNDi) has adopted a model closely related to that of a virtual biotechnology company for the identification and optimization of drug leads. The application of this model to the development of drug candidates for the kinetoplastid infections of HAT, Chagas disease, and leishmaniasis has already led to the identification of new candidates issued from DNDi's own discovery pipeline. This demonstrates that the model DNDi has been implementing is working but its DNDi, neglected diseases sustainability remains to be proven.

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

    Directory of Open Access Journals (Sweden)

    Bálint Mészáros

    2011-07-01

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

  9. Modeling protein synthesis from a physicist's perspective: a toy model

    CERN Document Server

    Basu, A; Basu, Aakash; Chowdhury, Debashish

    2007-01-01

    Proteins are polymers of amino acids. These macromolecules are synthesized by intracellular machines called {\\it ribosome}. Although, traditionally, the experimental investigation of protein synthesis has been an active area of research in molecular cell biology, important quantitative models of this phenomenon have been reported mostly in the research journals devoted to statistical physics and related interdisciplinary topics. From the perspective of a physicist, protein synthesis is a phenomenon of {\\it classical transport of interacting ribosomes on a messenger RNA (mRNA) template} that dictates the sequence of the amino acids on the protein. Here we bring this frontier area of contemporary research into the classroom by appropriate simplification of the models and methods. In particular, we develope a simple toy model and analyze it by some elementary techniques of non-equilibrium statistical mechanics to predict the average rate of protein synthesis and their spatial organization in the steady-state.

  10. Genipin-induced inhibition of uncoupling protein-2 sensitizes drug-resistant cancer cells to cytotoxic agents.

    Directory of Open Access Journals (Sweden)

    Ryan J Mailloux

    Full Text Available Uncoupling protein-2 (UCP2 is known to suppress mitochondrial reactive oxygen species (ROS production and is employed by drug-resistant cancer cells to mitigate oxidative stress. Using the drug-sensitive HL-60 cells and the drug-resistant MX2 subline as model systems, we show that genipin, a UCP2 inhibitor, sensitizes drug-resistant cells to cytotoxic agents. Increased MX2 cell death was observed upon co-treatment with genipin and different doses of menadione, doxorubicin, and epirubicin. DCFH-DA fluorimetry revealed that the increase in MX2 cell death was accompanied by enhanced cellular ROS levels. The drug-induced increase in ROS was linked to genipin-mediated inhibition of mitochondrial proton leak. State 4 and resting cellular respiratory rates were higher in the MX2 cells in comparison to the HL-60 cells, and the increased respiration was readily suppressed by genipin in the MX2 cells. UCP2 accounted for a remarkable 37% of the resting cellular oxygen consumption indicating that the MX2 cells are functionally reliant on this protein. Higher amounts of UCP2 protein were detected in the MX2 versus the HL-60 mitochondria. The observed effects of genipin were absent in the HL-60 cells pointing to the selectivity of this natural product for drug-resistant cells. The specificity of genipin for UCP2 was confirmed using CHO cells stably expressing UCP2 in which genipin induced an ∼22% decrease in state 4 respiration. These effects were absent in empty vector CHO cells expressing no UCP2. Thus, the chemical inhibition of UCP2 with genipin sensitizes multidrug-resistant cancer cells to cytotoxic agents.

  11. Modelling of DNA-protein recognition

    Science.gov (United States)

    Rein, R.; Garduno, R.; Colombano, S.; Nir, S.; Haydock, K.; Macelroy, R. D.

    1980-01-01

    Computer model-building procedures using stereochemical principles together with theoretical energy calculations appear to be, at this stage, the most promising route toward the elucidation of DNA-protein binding schemes and recognition principles. A review of models and bonding principles is conducted and approaches to modeling are considered, taking into account possible di-hydrogen-bonding schemes between a peptide and a base (or a base pair) of a double-stranded nucleic acid in the major groove, aspects of computer graphic modeling, and a search for isogeometric helices. The energetics of recognition complexes is discussed and several models for peptide DNA recognition are presented.

  12. Approaches to Mitigate the Unwanted Immunogenicity of Therapeutic Proteins during Drug Development.

    Science.gov (United States)

    Salazar-Fontana, Laura I; Desai, Dharmesh D; Khan, Tarik A; Pillutla, Renuka C; Prior, Sandra; Ramakrishnan, Radha; Schneider, Jennifer; Joseph, Alexandra

    2017-03-01

    All biotherapeutics have the potential to induce an immune response. This immunological response is complex and, in addition to antibody formation, involves T cell activation and innate immune responses that could contribute to adverse effects. Integrated immunogenicity data analysis is crucial to understanding the possible clinical consequences of anti-drug antibody (ADA) responses. Because patient- and product-related factors can influence the immunogenicity of a therapeutic protein, a risk-based approach is recommended and followed by most drug developers to provide insight over the potential harm of unwanted ADA responses. This paper examines mitigation strategies currently implemented and novel under investigation approaches used by drug developers. The review describes immunomodulatory regimens used in the clinic to mitigate deleterious ADA responses to replacement therapies for deficiency syndromes, such as hemophilia A and B, and high risk classical infantile Pompe patients (e.g., cyclophosphamide, methotrexate, rituximab); novel in silico and in vitro prediction tools used to select candidates based on their immunogenicity potential (e.g., anti-CD52 antibody primary sequence and IFN beta-1a formulation); in vitro generation of tolerogenic antigen-presenting cells (APCs) to reduce ADA responses to factor VIII and IX in murine models of hemophilia; and selection of novel delivery systems to reduce in vivo ADA responses to highly immunogenic biotherapeutics (e.g., asparaginase). We conclude that mitigation strategies should be considered early in development for biotherapeutics based on our knowledge of existing clinical data for biotherapeutics and the immune response involved in the generation of these ADAs.

  13. A sight on protein-based nanoparticles as drug/gene delivery systems.

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2017-07-01

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

  15. Modeling Illicit Drug Use Dynamics and Its Optimal Control Analysis

    Directory of Open Access Journals (Sweden)

    Steady Mushayabasa

    2015-01-01

    Full Text Available The global burden of death and disability attributable to illicit drug use, remains a significant threat to public health for both developed and developing nations. This paper presents a new mathematical modeling framework to investigate the effects of illicit drug use in the community. In our model the transmission process is captured as a social “contact” process between the susceptible individuals and illicit drug users. We conduct both epidemic and endemic analysis, with a focus on the threshold dynamics characterized by the basic reproduction number. Using our model, we present illustrative numerical results with a case study in Cape Town, Gauteng, Mpumalanga and Durban communities of South Africa. In addition, the basic model is extended to incorporate time dependent intervention strategies.

  16. A Cooperative Model to Improve Hospital Equipments and Drugs Management

    Science.gov (United States)

    Baffo, Ilaria; Confessore, Giuseppe; Liotta, Giacomo; Stecca, Giuseppe

    The cost of services provided by public and private healthcare systems is nowadays becoming critical. This work tackles the criticalities of hospital equipments and drugs management by emphasizing its implications on the whole healthcare system efficiency. The work presents a multi-agent based model for decisional cooperation in order to address the problem of integration of departments, wards and personnel for improving equipments, and drugs management. The proposed model faces the challenge of (i) gaining the benefits deriving from successful collaborative models already used in industrial systems and (ii) transferring the most appropriate industrial management practices to healthcare systems.

  17. A model of a transmembrane drug-efflux pump from Gram-negative bacteria.

    Science.gov (United States)

    Fernandez-Recio, Juan; Walas, Fabien; Federici, Luca; Venkatesh Pratap, J; Bavro, Vassiliy N; Miguel, Ricardo Nunez; Mizuguchi, Kenji; Luisi, Ben

    2004-12-03

    In Gram-negative bacteria, drug resistance is due in part to the activity of transmembrane efflux-pumps, which are composed of three types of proteins. A representative pump from Escherichia coli is an assembly of the trimeric outer-membrane protein TolC, which is an allosteric channel, the trimeric inner-membrane proton-antiporter AcrB, and the periplasmic protein, AcrA. The pump displaces drugs vectorially from the bacterium using proton electrochemical force. Crystal structures are available for TolC and AcrB from E. coli, and for the AcrA homologue MexA from Pseudomonas aeruginosa. Based on homology modelling and molecular docking, we show how AcrA, AcrB and TolC might assemble to form a tripartite pump, and how allostery may occur during transport.

  18. Rat gingival model for testing drugs influencing inflammation

    Directory of Open Access Journals (Sweden)

    Shaju P Jacob

    2013-07-01

    Full Text Available Preclinical drug testing is an important areain new drug development where animals are used.An ideal animal model for this is one which is simple,reliable and can be extrapolated to humans. Topicaldrugs for inflammation are conventionally tested onthe skin of animals after induction of inflammation.A gingival model would be simple as inflammation canbe induced naturally by the action of plaque. Rats area popular animal model for testing drugs as well as tostudy various diseases of the periodontium. Periodontaldisease including gingival inflammation develops inrats in relation to indigenous plaque or experimentallyinduced bacterial products. A number of features ofrats ranging from anatomy, histology and response tobacterial insult can be seen mirrored to a great extentin humans. There is a lot similarity in the developmentand resolution of inflammation as well as the gingivalwound healing of rats and humans. This paper tries toexplore the feasibility of using the rat gingival modelfor preclinical testing of drugs acting on or influencinginflammation and concludes by identifying potentialareas of research using this model. The addition of sucha simple and inexpensive model for preclinical testing ofdrugs will be welcomed by the drug developers.

  19. PBPK modeling and simulation in drug research and development

    Directory of Open Access Journals (Sweden)

    Xiaomei Zhuang

    2016-09-01

    Full Text Available Physiologically based pharmacokinetic (PBPK modeling and simulation can be used to predict the pharmacokinetic behavior of drugs in humans using preclinical data. It can also explore the effects of various physiologic parameters such as age, ethnicity, or disease status on human pharmacokinetics, as well as guide dose and dose regiment selection and aid drug–drug interaction risk assessment. PBPK modeling has developed rapidly in the last decade within both the field of academia and the pharmaceutical industry, and has become an integral tool in drug discovery and development. In this mini-review, the concept and methodology of PBPK modeling are briefly introduced. Several case studies were discussed on how PBPK modeling and simulation can be utilized through various stages of drug discovery and development. These case studies are from our own work and the literature for better understanding of the absorption, distribution, metabolism and excretion (ADME of a drug candidate, and the applications to increase efficiency, reduce the need for animal studies, and perhaps to replace clinical trials. The regulatory acceptance and industrial practices around PBPK modeling and simulation is also discussed.

  20. Advances in Engineered Liver Models for Investigating Drug-Induced Liver Injury

    Science.gov (United States)

    Lin, Christine

    2016-01-01

    Drug-induced liver injury (DILI) is a major cause of drug attrition. Testing drugs on human liver models is essential to mitigate the risk of clinical DILI since animal studies do not always suffice due to species-specific differences in liver pathways. While primary human hepatocytes (PHHs) can be cultured on extracellular matrix proteins, a rapid decline in functions leads to low sensitivity (<50%) in DILI prediction. Semiconductor-driven engineering tools now allow precise control over the hepatocyte microenvironment to enhance and stabilize phenotypic functions. The latest platforms coculture PHHs with stromal cells to achieve hepatic stability and enable crosstalk between the various liver cell types towards capturing complex cellular mechanisms in DILI. The recent introduction of induced pluripotent stem cell-derived human hepatocyte-like cells can potentially allow a better understanding of interindividual differences in idiosyncratic DILI. Liver models are also being coupled to other tissue models via microfluidic perfusion to study the intertissue crosstalk upon drug exposure as in a live organism. Here, we review the major advances being made in the engineering of liver models and readouts as they pertain to DILI investigations. We anticipate that engineered human liver models will reduce drug attrition, animal usage, and cases of DILI in humans. PMID:27725933

  1. Effect of venlafaxine and desvenlafaxine on drug efflux protein expression and biodistribution in vivo.

    Science.gov (United States)

    Bachmeier, Corbin; Levin, Gary M; Beaulieu-Abdelahad, David; Reed, Jon; Mullan, Michael

    2013-10-01

    Venlafaxine, and to a lesser extent desvenlafaxine, has previously been shown to induce the expression of the drug efflux transporters P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP) in whole cells and alter the cellular permeability of a known drug efflux probe (rhodamine 123). To validate these in vitro findings, wild-type mice were treated for 4 days with 10 mg/kg venlafaxine or desvenlafaxine, and drug efflux transporter expression was examined in the brain, liver, and intestine. P-gp and BCRP expression was significantly upregulated in the intestine, following a treatment with venlafaxine (2.6- and 6.7-fold, respectively) or desvenlafaxine (2.3- and 4.8-fold, respectively). In addition, venlafaxine increased the BCRP expression in the brain (40%) and liver (60%), whereas desvenlafaxine had no effect on drug efflux transporter levels in these tissues. Using the same treatment paradigm, we observed a minimal impact of either drug on the brain disposition of the known drug efflux probe, topotecan. However, in the periphery, venlafaxine treatment significantly reduced the topotecan oral bioavailability by nearly 40%, whereas the impact of desvenlafaxine on topotecan plasma levels was more modest (23%). These studies demonstrate an effect of venlafaxine on the drug efflux transport activity and the potential for clinical drug-drug interactions. © 2013 Wiley Periodicals, Inc. and the American Pharmacists Association.

  2. Heat Shock Protein translocation induced by membrane fluidization increases tumor-cell sensitivity to chemotherapeutic drugs.

    Science.gov (United States)

    Dempsey, Nina C; Ireland, H Elyse; Smith, Carly M; Hoyle, Christine F; Williams, John H H

    2010-10-28

    Treatment of chronic lymphocytic leukemia (CLL) remains a challenge due to the frequency of drug resistance amongst patients. Improving the delivery of chemotherapeutic agents while reducing the expression of anti-apoptotic Heat Shock Proteins (HSPs) within the cancer cells may facilitate in overcoming this drug resistance. We demonstrate for the first time that sub-lethal doses of chemotherapeutic agents can be combined with membrane fluidizing treatments to produce a significant increase in drug efficacy and apoptosis in vitro. We show that fluidizers result in a transient decrease in intracellular HSPs, resulting in increased tumor-cell sensitivity and a membrane-associated induction of HSP gene expression.

  3. iDrug-Target: predicting the interactions between drug compounds and target proteins in cellular networking via benchmark dataset optimization approach.

    Science.gov (United States)

    Xiao, Xuan; Min, Jian-Liang; Lin, Wei-Zhong; Liu, Zi; Cheng, Xiang; Chou, Kuo-Chen

    2015-01-01

    Information about the interactions of drug compounds with proteins in cellular networking is very important for drug development. Unfortunately, all the existing predictors for identifying drug-protein interactions were trained by a skewed benchmark data-set where the number of non-interactive drug-protein pairs is overwhelmingly larger than that of the interactive ones. Using this kind of highly unbalanced benchmark data-set to train predictors would lead to the outcome that many interactive drug-protein pairs might be mispredicted as non-interactive. Since the minority interactive pairs often contain the most important information for drug design, it is necessary to minimize this kind of misprediction. In this study, we adopted the neighborhood cleaning rule and synthetic minority over-sampling technique to treat the skewed benchmark datasets and balance the positive and negative subsets. The new benchmark datasets thus obtained are called the optimized benchmark datasets, based on which a new predictor called iDrug-Target was developed that contains four sub-predictors: iDrug-GPCR, iDrug-Chl, iDrug-Ezy, and iDrug-NR, specialized for identifying the interactions of drug compounds with GPCRs (G-protein-coupled receptors), ion channels, enzymes, and NR (nuclear receptors), respectively. Rigorous cross-validations on a set of experiment-confirmed datasets have indicated that these new predictors remarkably outperformed the existing ones for the same purpose. To maximize users' convenience, a public accessible Web server for iDrug-Target has been established at http://www.jci-bioinfo.cn/iDrug-Target/ , by which users can easily get their desired results. It has not escaped our notice that the aforementioned strategy can be widely used in many other areas as well.

  4. Relative Binding Free Energy Calculations Applied to Protein Homology Models.

    Science.gov (United States)

    Cappel, Daniel; Hall, Michelle Lynn; Lenselink, Eelke B; Beuming, Thijs; Qi, Jun; Bradner, James; Sherman, Woody

    2016-12-27

    A significant challenge and potential high-value application of computer-aided drug design is the accurate prediction of protein-ligand binding affinities. Free energy perturbation (FEP) using molecular dynamics (MD) sampling is among the most suitable approaches to achieve accurate binding free energy predictions, due to the rigorous statistical framework of the methodology, correct representation of the energetics, and thorough treatment of the important degrees of freedom in the system (including explicit waters). Recent advances in sampling methods and force fields coupled with vast increases in computational resources have made FEP a viable technology to drive hit-to-lead and lead optimization, allowing for more efficient cycles of medicinal chemistry and the possibility to explore much larger chemical spaces. However, previous FEP applications have focused on systems with high-resolution crystal structures of the target as starting points-something that is not always available in drug discovery projects. As such, the ability to apply FEP on homology models would greatly expand the domain of applicability of FEP in drug discovery. In this work we apply a particular implementation of FEP, called FEP+, on congeneric ligand series binding to four diverse targets: a kinase (Tyk2), an epigenetic bromodomain (BRD4), a transmembrane GPCR (A2A), and a protein-protein interaction interface (BCL-2 family protein MCL-1). We apply FEP+ using both crystal structures and homology models as starting points and find that the performance using homology models is generally on a par with the results when using crystal structures. The robustness of the calculations to structural variations in the input models can likely be attributed to the conformational sampling in the molecular dynamics simulations, which allows the modeled receptor to adapt to the "real" conformation for each ligand in the series. This work exemplifies the advantages of using all-atom simulation methods with

  5. Efficient Data Mining Algorithms for Screening Potential Proteins of Drug Target

    Directory of Open Access Journals (Sweden)

    Qi Wang

    2017-01-01

    Full Text Available The past few decades have witnessed the boom in pharmacology as well as the dilemma of drug development. Playing a crucial role in drug design, the screening of potential human proteins of drug targets from open access database with well-measured physical and chemical properties is a task of challenge but significance. In this paper, the screening of potential drug target proteins (DTPs from a fine collected dataset containing 5376 unlabeled proteins and 517 known DTPs was researched. Our objective is to screen potential DTPs from the 5376 proteins. Here we proposed two strategies assisting the construction of dataset of reliable nondrug target proteins (NDTPs and then bagging of decision trees method was employed in the final prediction. Such two-stage algorithms have shown their effectiveness and superior performance on the testing set. Both of the algorithms maintained higher recall ratios of DTPs, respectively, 93.5% and 97.4%. In one turn of experiments, strategy1-based bagging of decision trees algorithm screened about 558 possible DTPs while 1782 potential DTPs were predicted in the second algorithm. Besides, two strategy-based algorithms showed the consensus of the predictions in the results, with approximately 442 potential DTPs in common. These selected DTPs provide reliable choices for further verification based on biomedical experiments.

  6. Lovastatin Corrects Excess Protein Synthesis and Prevents Epileptogenesis in a Mouse Model of Fragile X Syndrome

    OpenAIRE

    Chuang, Shih-Chieh; Chubykin, Alexander A.; Sidorov, Michael; Bianchi, Riccardo; Wong, Robert K.S.; Osterweil, Emily; Bear, Mark; Chubykin, Alexander A.

    2013-01-01

    Many neuropsychiatric symptoms of fragile X syndrome (FXS) are believed to be a consequence of altered regulation of protein synthesis at synapses. We discovered that lovastatin, a drug that is widely prescribed for the treatment of high cholesterol, can correct excess hippocampal protein synthesis in the mouse model of FXS and can prevent one of the robust functional consequences of increased protein synthesis in FXS, epileptogenesis. These data suggest that lovastatin is potentially disease...

  7. Lovastatin corrects excess protein synthesis and prevents epileptogenesis in a mouse model of fragile X syndrome

    OpenAIRE

    Osterweil, Emily K.; Chuang, Shih-Chieh; Chubykin, Alexander A.; Sidorov, Michael; Bianchi, Riccardo; Wong, Robert K. S.; Bear, Mark F.

    2013-01-01

    Many neuropsychiatric symptoms of fragile X syndrome (FXS) are believed to be a consequence of altered regulation of protein synthesis at synapses. We discovered that lovastatin, a drug that is widely prescribed for treatment of high cholesterol, can correct excess hippocampal protein synthesis in themouse model of FXS and can prevent one of the robust functional consequences of increased protein synthesis in FXS, epileptogenesis. These data suggest that lovastatin is potentially disease modi...

  8. Detection of drug-drug interactions by modeling interaction profile fingerprints.

    Directory of Open Access Journals (Sweden)

    Santiago Vilar

    Full Text Available Drug-drug interactions (DDIs constitute an important problem in postmarketing pharmacovigilance and in the development of new drugs. The effectiveness or toxicity of a medication could be affected by the co-administration of other drugs that share pharmacokinetic or pharmacodynamic pathways. For this reason, a great effort is being made to develop new methodologies to detect and assess DDIs. In this article, we present a novel method based on drug interaction profile fingerprints (IPFs with successful application to DDI detection. IPFs were generated based on the DrugBank database, which provided 9,454 well-established DDIs as a primary source of interaction data. The model uses IPFs to measure the similarity of pairs of drugs and generates new putative DDIs from the non-intersecting interactions of a pair. We described as part of our analysis the pharmacological and biological effects associated with the putative interactions; for example, the interaction between haloperidol and dicyclomine can cause increased risk of psychosis and tardive dyskinesia. First, we evaluated the method through hold-out validation and then by using four independent test sets that did not overlap with DrugBank. Precision for the test sets ranged from 0.4-0.5 with more than two fold enrichment factor enhancement. In conclusion, we demonstrated the usefulness of the method in pharmacovigilance as a DDI predictor, and created a dataset of potential DDIs, highlighting the etiology or pharmacological effect of the DDI, and providing an exploratory tool to facilitate decision support in DDI detection and patient safety.

  9. Analysis of drug-protein binding using on-line immunoextraction and high-performance affinity microcolumns: Studies with normal and glycated human serum albumin.

    Science.gov (United States)

    Matsuda, Ryan; Jobe, Donald; Beyersdorf, Jared; Hage, David S

    2015-10-16

    A method combining on-line immunoextraction microcolumns with high-performance affinity chromatography (HPAC) was developed and tested for use in examining drug-protein interactions with normal or modified proteins. Normal human serum albumin (HSA) and glycated HSA were used as model proteins for this work. High-performance immunoextraction microcolumns with sizes of 1.0-2.0 cm × 2.1mm i.d. and containing anti-HSA polyclonal antibodies were developed and tested for their ability to bind normal HSA or glycated HSA. These microcolumns were able to extract up to 82-93% for either type of protein at 0.05-0.10 mL/min and had a binding capacity of 0.34-0.42 nmol HSA for a 1.0 cm × 2.1mm i.d. microcolumn. The immunoextraction microcolumns and their adsorbed proteins were tested for use in various approaches for drug binding studies. Frontal analysis was used with the adsorbed HSA/glycated HSA to measure the overall affinities of these proteins for the drugs warfarin and gliclazide, giving comparable values to those obtained previously using similar protein preparations that had been covalently immobilized within HPAC columns. Zonal elution competition studies with gliclazide were next performed to examine the specific interactions of this drug at Sudlow sites I and II of the adsorbed proteins. These results were also comparable to those noted in prior work with covalently immobilized samples of normal HSA or glycated HSA. These experiments indicated that drug-protein binding studies can be carried out by using on-line immunoextraction microcolumns with HPAC. The same method could be used in the future with clinical samples and other drugs or proteins of interest in pharmaceutical studies or biomedical research.

  10. IAP proteins as targets for drug development in oncology

    Directory of Open Access Journals (Sweden)

    Dubrez L

    2013-09-01

    Full Text Available Laurence Dubrez,1,2 Jean Berthelet,1,2 Valérie Glorian,1,21Institut National de la Santé et de la Recherche Médicale (Inserm, Dijon, France; 2Université de Bourgogne, Dijon, FranceAbstract: The inhibitors of apoptosis (IAPs constitute a family of proteins involved in the regulation of various cellular processes, including cell death, immune and inflammatory responses, cell proliferation, cell differentiation, and cell motility. There is accumulating evidence supporting IAP-targeting in tumors: IAPs regulate various cellular processes that contribute to tumor development, such as cell death, cell proliferation, and cell migration; their expression is increased in a number of human tumor samples, and IAP overexpression has been correlated with tumor growth, and poor prognosis or low response to treatment; and IAP expression can be rapidly induced in response to chemotherapy or radiotherapy because of the presence of an internal ribosome entry site (IRES-dependent mechanism of translation initiation, which could contribute to resistance to antitumor therapy. The development of IAP antagonists is an important challenge and was subject to intense research over the past decade. Six molecules are currently in clinical trials. This review focuses on the role of IAPs in tumors and the development of IAP-targeting molecules for anticancer therapy.Keywords: Smac mimetics, apoptosis, antitumor therapy

  11. Perturbation waves in proteins and protein networks: Applications of percolation and game theories in signaling and drug design

    CERN Document Server

    Antal, Miklos A; Csermely, Peter

    2008-01-01

    The network paradigm is increasingly used to describe the dynamics of complex systems. Here we review the current results and propose future development areas in the assessment of perturbation waves, i.e. propagating structural changes in amino acid networks building individual protein molecules and in protein-protein interaction networks (interactomes). We assess the possibilities and critically review the initial attempts for the application of game theory to the often rather complicated process, when two protein molecules approach each other, mutually adjust their conformations via multiple communication steps and finally, bind to each other. We also summarize available data on the application of percolation theory for the prediction of amino acid network- and interactome-dynamics. Furthermore, we give an overview of the dissection of signals and noise in the cellular context of various perturbations. Finally, we propose possible applications of the reviewed methodologies in drug design.

  12. Dysregulation of protein degradation pathways may mediate the liver injury and phospholipidosis associated with a cationic amphiphilic antibiotic drug

    Energy Technology Data Exchange (ETDEWEB)

    Mosedale, Merrie [Hamner-University of North Carolina Institute for Drug Safety Sciences, The Hamner Institutes for Health Sciences, Research Triangle Park, NC 27709 (United States); Wu, Hong [Drug Safety Research and Development, Pfizer Global Research and Development, Groton, CT06340 (United States); Kurtz, C. Lisa [Hamner-University of North Carolina Institute for Drug Safety Sciences, The Hamner Institutes for Health Sciences, Research Triangle Park, NC 27709 (United States); Schmidt, Stephen P. [Drug Safety Research and Development, Pfizer Global Research and Development, Groton, CT06340 (United States); Adkins, Karissa, E-mail: Karissa.Adkins@pfizer.com [Drug Safety Research and Development, Pfizer Global Research and Development, Groton, CT06340 (United States); Harrill, Alison H. [Hamner-University of North Carolina Institute for Drug Safety Sciences, The Hamner Institutes for Health Sciences, Research Triangle Park, NC 27709 (United States); University of Arkansas for Medical Sciences, Little Rock, AR72205 (United States)

    2014-10-01

    A large number of antibiotics are known to cause drug-induced liver injury in the clinic; however, interpreting clinical risk is not straightforward owing to a lack of predictivity of the toxicity by standard preclinical species and a poor understanding of the mechanisms of toxicity. An example is PF-04287881, a novel ketolide antibiotic that caused elevations in liver function tests in Phase I clinical studies. In this study, a mouse diversity panel (MDP), comprised of 34 genetically diverse, inbred mouse strains, was utilized to model the toxicity observed with PF-04287881 treatment and investigate potential mechanisms that may mediate the liver response. Significant elevations in serum alanine aminotransferase (ALT) levels in PF-04287881-treated animals relative to vehicle-treated controls were observed in the majority (88%) of strains tested following a seven day exposure. The average fold elevation in ALT varied by genetic background and correlated with microscopic findings of hepatocellular hypertrophy, hepatocellular single cell necrosis, and Kupffer cell vacuolation (confirmed as phospholipidosis) in the liver. Global liver mRNA expression was evaluated in a subset of four strains to identify transcript and pathway differences that distinguish susceptible mice from resistant mice in the context of PF-04287881 treatment. The protein ubiquitination pathway was highly enriched among genes associated with PF-04287881-induced hepatocellular necrosis. Expression changes associated with PF-04287881-induced phospholipidosis included genes involved in drug transport, phospholipid metabolism, and lysosomal function. The findings suggest that perturbations in genes involved in protein degradation leading to accumulation of oxidized proteins may mediate the liver injury induced by this drug. - Highlights: • Identified susceptible and resistant mouse strains to liver injury induced by a CAD • Liver injury characterized by single cell necrosis, and phospholipidosis

  13. Testing a fall risk model for injection drug users.

    Science.gov (United States)

    Pieper, Barbara; Templin, Thomas N; Goldberg, Allon

    2012-01-01

    Fall risk is a critical component of clinical assessment and has not been examined for persons who have injected illicit drugs and are aging. The aim of this study was to test and develop the Fall Risk Model for Injection Drug Users by examining the relationships among injection drug use, chronic venous insufficiency, lower extremity impairments (i.e., decreased ankle range of motion, reduced calf muscle endurance, and leg pain), age and other covariates, and the Tinetti balance and gait total score as a measure of fall risk. A cross-sectional comparative design was used with four crossed factors. Standardized instruments were used to assess the variables. Moderated multiple regression with linear and quadratic trends in age was used to examine the nature of the relationship between the Tinetti balance and gait total and age and the potential moderating role of injection drug use. A prespecified series of models was tested. Participants (n = 713) were men (46.9%) and women with a mean age of 46.26 years and primarily African American (61.7%) in methadone treatment centers. The fall risk of a 48-year-old leg injector was comparable with the fall risk of a 69-year-old who had not injected drugs. Variables were added to the model sequentially, resulting in some lost significance of some when they were explained by subsequent variables. Final significant variables in the model were employment status, number of comorbidities, ankle range of motion, leg pain, and calf muscle endurance. Fall risk was associated with route of drug use. Lower extremity impairments accounted for the effects of injection drug use and chronic venous insufficiency on risk for falls. Further understanding of fall risk in injection users is necessary as they age, attempt to work, and participate in activities.

  14. Protein corona change the drug release profile of nanocarriers: the "overlooked" factor at the nanobio interface.

    Science.gov (United States)

    Behzadi, Shahed; Serpooshan, Vahid; Sakhtianchi, Ramin; Müller, Beate; Landfester, Katharina; Crespy, Daniel; Mahmoudi, Morteza

    2014-11-01

    The emergence of nanocarrier systems in drug delivery applications has ushered in rapid development of new classes of therapeutic agents which can provide an essential breakthrough in the fight against refractory diseases. However, successful clinical application of nano-drug delivery devices has been limited mainly due to the lack of control on sustained release of therapeutics from the carriers. A wide range of sophisticated approaches employs the formation of crosslinkable, non-crosslinkable, stimuli-responsive polymer nanocarriers in order to enhance their delivery efficiency. Despite the extensive research conducted on the development of various nanocarriers, the effect of the biological milieu on the drug release profile of these constructs is not yet fully investigated. In particular, the formation of a protein corona on the surface of nanocarriers, when they interact with living organisms in vivo is largely decisive for their biological function. Using a number of synthetized (i.e., superparamagnetic iron oxide nanoparticles and polymeric nanocapsules) and commercialized nanocarriers (i.e., Abraxane®, albumin-bound paclitaxel drug), this study demonstrates that the protein corona can shield the nanocarriers and, consequently, alters the release profile of the drugs from the nanocarriers. More specifically, the protein corona could significantly reduce the burst effect of either protein conjugated nanocarriers or carriers with surface loaded drug (i.e., SPIONs). However, the corona shell only slightly changed the release profile of polymeric nanocapsules. Therefore, the intermediary, buffer effect of the protein shells on the surface of nanoscale carriers plays a crucial role in their successful high-yield applications in vivo.

  15. Erectile Dysfunction Drugs Changed the Protein Expressions and Activities of Drug-Metabolising Enzymes in the Liver of Male Rats

    Directory of Open Access Journals (Sweden)

    Salah A. Sheweita

    2016-01-01

    Full Text Available Erectile dysfunction (ED is a major health problem and is mainly associated with the persistent inability of men to maintain sufficient erection for satisfactory sexual performance. Millions of men are using sildenafil, vardenafil, and/or tadalafil for ED treatment. Cytochrome P450s (CYPs play a central role in the metabolism of a wide range of xenobiotics as well as endogenous compounds. Susceptibility of individuals to the adverse effects of different drugs is mainly dependent on the expression of CYPs proteins. Therefore, changes in activities of phase I drug-metabolising enzymes [arylhydrocarbon hydroxylase (AHH, dimethylnitrosamine N-demethylase (DMN-dI, 7-ethoxycoumarin-O-deethylase (ECOD, and ethoxyresorufin-O-deethylase ((EROD] and the protein expression of different CYPs isozymes (CYP1A2, CYP2E1, CYP2B1/2, CYP3A4, CYP2C23, and CYP2C6 were determined after treatment of male rats with either low or high doses of sildenafil (Viagra, tadalafil (Cialis, and/or vardenafil (Levitra for 3 weeks. The present study showed that low doses of tadalafil and vardenafil increased DMN-dI activity by 32 and 23%, respectively. On the other hand, high doses of tadalafil, vardenafil, and sildenafil decreased such activity by 50, 56, and 52%, respectively. In addition, low doses of tadalafil and vardenafil induced the protein expression of CYP2E1. On the other hand, high doses of either tadalafil or sildenafil were more potent inhibitors to CYP2E1 expression than vardenafil. Moreover, low doses of both vardenafil and sildenafil markedly increased AHH activity by 162 and 247%, respectively, whereas high doses of tadalafil, vardenafil, and sildenafil inhibited such activity by 36, 49, and 57% and inhibited the EROD activity by 39, 49, and 33%, respectively. Low and high doses of tadalafil, vardenafil, and sildenafil inhibited the activity of NADPH-cytochrome c reductase as well as its protein expression. In addition, such drugs inhibited the expression of CYP

  16. Bioresorbable polymer coated drug eluting stent: a model study.

    Science.gov (United States)

    Rossi, Filippo; Casalini, Tommaso; Raffa, Edoardo; Masi, Maurizio; Perale, Giuseppe

    2012-07-01

    In drug eluting stent technologies, an increased demand for better control, higher reliability, and enhanced performances of drug delivery systems emerged in the last years and thus offered the opportunity to introduce model-based approaches aimed to overcome the remarkable limits of trial-and-error methods. In this context a mathematical model was studied, based on detailed conservation equations and taking into account the main physical-chemical mechanisms involved in polymeric coating degradation, drug release, and restenosis inhibition. It allowed highlighting the interdependence between factors affecting each of these phenomena and, in particular, the influence of stent design parameters on drug antirestenotic efficacy. Therefore, the here-proposed model is aimed to simulate the diffusional release, for both in vitro and the in vivo conditions: results were verified against various literature data, confirming the reliability of the parameter estimation procedure. The hierarchical structure of this model also allows easily modifying the set of equations describing restenosis evolution to enhance model reliability and taking advantage of the deep understanding of physiological mechanisms governing the different stages of smooth muscle cell growth and proliferation. In addition, thanks to its simplicity and to the very low system requirements and central processing unit (CPU) time, our model allows obtaining immediate views of system behavior.

  17. Biophysical Approaches Facilitate Computational Drug Discovery for ATP-Binding Cassette Proteins

    Science.gov (United States)

    Molinski, Steven V.; Bozóky, Zoltán; Iram, Surtaj H.

    2017-01-01

    Although membrane proteins represent most therapeutically relevant drug targets, the availability of atomic resolution structures for this class of proteins has been limited. Structural characterization has been hampered by the biophysical nature of these polytopic transporters, receptors, and channels, and recent innovations to in vitro techniques aim to mitigate these challenges. One such class of membrane proteins, the ATP-binding cassette (ABC) superfamily, are broadly expressed throughout the human body, required for normal physiology and disease-causing when mutated, yet lacks sufficient structural representation in the Protein Data Bank. However, recent improvements to biophysical techniques (e.g., cryo-electron microscopy) have allowed for previously “hard-to-study” ABC proteins to be characterized at high resolution, providing insight into molecular mechanisms-of-action as well as revealing novel druggable sites for therapy design. These new advances provide ample opportunity for computational methods (e.g., virtual screening, molecular dynamics simulations, and structure-based drug design) to catalyze the discovery of novel small molecule therapeutics that can be easily translated from computer to bench and subsequently to the patient's bedside. In this review, we explore the utility of recent advances in biophysical methods coupled with well-established in silico techniques towards drug development for diseases caused by dysfunctional ABC proteins. PMID:28409029

  18. Modularity in protein complex and drug interactions reveals new polypharmacological properties.

    Directory of Open Access Journals (Sweden)

    Jose C Nacher

    Full Text Available Recent studies have highlighted the importance of interconnectivity in a large range of molecular and human disease-related systems. Network medicine has emerged as a new paradigm to deal with complex diseases. Connections between protein complexes and key diseases have been suggested for decades. However, it was not until recently that protein complexes were identified and classified in sufficient amounts to carry out a large-scale analysis of the human protein complex system. We here present the first systematic and comprehensive set of relationships between protein complexes and associated drugs and analyzed their topological features. The network structure is characterized by a high modularity, both in the bipartite graph and in its projections, indicating that its topology is highly distinct from a random network and that it contains a rich and heterogeneous internal modular structure. To unravel the relationships between modules of protein complexes, drugs and diseases, we investigated in depth the origins of this modular structure in examples of particular diseases. This analysis unveils new associations between diseases and protein complexes and highlights the potential role of polypharmacological drugs, which target multiple cellular functions to combat complex diseases driven by gain-of-function mutations.

  19. Recent Applications of Mesoscale Modeling to Nanotechnology and Drug Delivery

    Energy Technology Data Exchange (ETDEWEB)

    Maiti, A; Wescott, J; Kung, P; Goldbeck-Wood, G

    2005-02-11

    Mesoscale simulations have traditionally been used to investigate structural morphology of polymer in solution, melts and blends. Recently we have been pushing such modeling methods to important areas of Nanotechnology and Drug delivery that are well out of reach of classical molecular dynamics. This paper summarizes our efforts in three important emerging areas: (1) polymer-nanotube composites; (2) drug diffusivity through cell membranes; and (3) solvent exchange in nanoporous membranes. The first two applications are based on a bead-spring-based approach as encoded in the Dissipative Particle Dynamics (DPD) module. The last application used density-based Mesoscale modeling as implemented in the Mesodyn module.

  20. From drug response profiling to target addiction scoring in cancer cell models

    Directory of Open Access Journals (Sweden)

    Bhagwan Yadav

    2015-10-01

    Full Text Available Deconvoluting the molecular target signals behind observed drug response phenotypes is an important part of phenotype-based drug discovery and repurposing efforts. We demonstrate here how our network-based deconvolution approach, named target addiction score (TAS, provides insights into the functional importance of druggable protein targets in cell-based drug sensitivity testing experiments. Using cancer cell line profiling data sets, we constructed a functional classification across 107 cancer cell models, based on their common and unique target addiction signatures. The pan-cancer addiction correlations could not be explained by the tissue of origin, and only correlated in part with molecular and genomic signatures of the heterogeneous cancer cells. The TAS-based cancer cell classification was also shown to be robust to drug response data resampling, as well as predictive of the transcriptomic patterns in an independent set of cancer cells that shared similar addiction signatures with the 107 cancers. The critical protein targets identified by the integrated approach were also shown to have clinically relevant mutation frequencies in patients with various cancer subtypes, including not only well-established pan-cancer genes, such as PTEN tumor suppressor, but also a number of targets that are less frequently mutated in specific cancer types, including ABL1 oncoprotein in acute myeloid leukemia. An application to leukemia patient primary cell models demonstrated how the target deconvolution approach offers functional insights into patient-specific addiction patterns, such as those indicative of their receptor-type tyrosine-protein kinase FLT3 internal tandem duplication (FLT3-ITD status and co-addiction partners, which may lead to clinically actionable, personalized drug treatment developments. To promote its application to the future drug testing studies, we have made available an open-source implementation of the TAS calculation in the form

  1. Modeling of transdermal drug delivery with a microneedle array

    Science.gov (United States)

    Lv, Y.-G.; Liu, J.; Gao, Y.-H.; Xu, B.

    2006-11-01

    Transdermal drug delivery is generally limited by the extraordinary barrier properties of the stratum corneum, the outer 10-15 µm layer of skin. A conventional needle inserted across this barrier and into deeper tissues could effectively deliver drugs. However, it would lead to infection and cause pain, thereby reducing patient compliance. In order to administer a frequent injection of insulin and other therapeutic agents more efficiently, integrated arrays with very short microneedles were recently proposed as very good candidates for painless injection or extraction. A variety of microneedle designs have thus been made available by employing the fabrication tools of the microelectronics industry and using materials such as silicon, metals, polymers and glass with feature sizes ranging from sub-micron to nanometers. At the same time, experiments were also made to test the capability of the microneedles to inject drugs into tissues. However, due to the difficulty encountered in measurement, a detailed understanding of the spatial and transient drug delivery process still remains unclear up to now. To better grasp the mechanisms involved, quantitative theoretical models were developed in this paper to simultaneously characterize the flow and drug transport, and numerical solutions were performed to predict the kinetics of dispersed drugs injected into the skin from a microneedle array. Calculations indicated that increasing the initial injection velocity and accelerating the blood circulation in skin tissue with high porosity are helpful to enhance the transdermal drug delivery. This study provides the first quantitative simulation of fluid injection through a microneedle array and drug species transport inside the skin. The modeling strategy can also possibly be extended to deal with a wider range of clinical issues such as targeted nanoparticle delivery for therapeutics or molecular imaging.

  2. In vitro haematic proteins adsorption and cytocompatibility study on acrylic copolymer to realise coatings for drug-eluting stents

    Energy Technology Data Exchange (ETDEWEB)

    Gagliardi, Mariacristina, E-mail: mariacristina.gagliardi@iit.it

    2012-12-01

    In the present paper, a preliminary in vitro analysis of biocompatibility of newly-synthesised acrylic copolymers is reported. In particular, with the aim to obtain coatings for drug-eluting stents, blood protein absorption and cytocompatibility were studied. For protein absorption tests, bovine serum albumin and bovine plasma fibrinogen were considered. Cytocompatibility was tested using C2C12 cell line as model, analysing the behaviour of polymeric matrices and of drug-eluting systems, obtained loading polymeric matrices with paclitaxel, an anti-mitotic drug, in order to evaluate the efficacy of a pharmacological treatment locally administered from these materials. Results showed that the amount of albumin absorbed was greater than the amount of fibrinogen (comprised in the range of 70%-85% and 10%-22% respectively) and it is a good behaviour in terms of haemocompatibility. Cell culture tests showed good adhesion properties and a relative poor proliferation. In addition, a strong effect related to drug elution and a correlation with the macromolecular composition were detected. In this preliminary analysis, tested materials showed good characteristics and can be considered possible candidates to obtain coatings for drug-eluting stents. Highlights: Black-Right-Pointing-Pointer Preliminary evaluation of haemo- and cytocompatibility of newly-synthesised acrylic copolymers Black-Right-Pointing-Pointer Materials adsorb higher amounts of albumin and with a faster rate than fibrinogen. Black-Right-Pointing-Pointer Protein adsorption depended on the macromolecular composition and surface properties. Black-Right-Pointing-Pointer Cell viability on pure samples and efficacy of paclitaxel release were verified in C2C12 cultures.

  3. Predicting Drugs Side Effects Based on Chemical-Chemical Interactions and Protein-Chemical Interactions

    Directory of Open Access Journals (Sweden)

    Lei Chen

    2013-01-01

    Full Text Available A drug side effect is an undesirable effect which occurs in addition to the intended therapeutic effect of the drug. The unexpected side effects that many patients suffer from are the major causes of large-scale drug withdrawal. To address the problem, it is highly demanded by pharmaceutical industries to develop computational methods for predicting the side effects of drugs. In this study, a novel computational method was developed to predict the side effects of drug compounds by hybridizing the chemical-chemical and protein-chemical interactions. Compared to most of the previous works, our method can rank the potential side effects for any query drug according to their predicted level of risk. A training dataset and test datasets were constructed from the benchmark dataset that contains 835 drug compounds to evaluate the method. By a jackknife test on the training dataset, the 1st order prediction accuracy was 86.30%, while it was 89.16% on the test dataset. It is expected that the new method may become a useful tool for drug design, and that the findings obtained by hybridizing various interactions in a network system may provide useful insights for conducting in-depth pharmacological research as well, particularly at the level of systems biomedicine.

  4. Pathophysiological changes that affect drug disposition in protein-energy malnourished children

    Directory of Open Access Journals (Sweden)

    Oshikoya Kazeem A

    2009-12-01

    Full Text Available Abstract Protein-energy malnutrition (PEM is a major public health problem affecting a high proportion of infants and older children world-wide and accounts for a high childhood morbidity and mortality in the developing countries. The epidemiology of PEM has been extensively studied globally and management guidelines formulated by the World Health Organization (WHO. A wide spectrum of infections such as measles, malaria, acute respiratory tract infection, intestinal parasitosis, tuberculosis and HIV/AIDS may complicate PEM with two or more infections co-existing. Thus, numerous drugs may be required to treat the patients. In-spite of abundant literature on the epidemiology and management of PEM, focus on metabolism and therapeutic drug monitoring is lacking. A sound knowledge of pathophysiology of PEM and pharmacology of the drugs frequently used for their treatment is required for safe and rational treatment. In this review, we discuss the pathophysiological changes in children with PEM that may affect the disposition of drugs frequently used for their treatment. This review has established abnormal disposition of drugs in children with PEM that may require dosage modification. However, the relevance of these abnormalities to the clinical management of PEM remains inconclusive. At present, there are no good indications for drug dosage modification in PEM; but for drug safety purposes, further studies are required to accurately determine dosages of drugs frequently used for children with PEM.

  5. Multidrug resistance-associated protein 1 decreases the concentrations of antiepileptic drugs in cortical extracellular fluid in amygdale kindling rats

    Institute of Scientific and Technical Information of China (English)

    Ying-hui CHEN; Cui-cui WANG; Xia XIAO; Li WEI; Guoxiong XU

    2013-01-01

    Aim:To investigate whether multidrug resistance-associated protein 1 (MRP1) was responsible for drug resistence in refractory epilepsy in amygdale kindling rats.Methods:Rat amygdale kindling was used as a model of refractory epilepsy.The expression of MRP1 mRNA and protein in the brains was examined using RT-PCR and Western blot.MRP1-positive cells in the cortex and hippocampus were studied with immunohistochemical staining.The rats were intraperitoneally injected with phenytoin (50 mg/kg) or carbamazepine (20 mg/kg),and their concentrations in the cortical extracellular fluid were measured using microdialysis and HPLC.Probenecid,a MRP1 inhibitor (40 mmol/L,50 μL) was administered through an inflow tube into the cortex 30 min before injection of the antiepileptic drugs.Results:The expression of MRP1 mRNA and protein was significantly up-regulated in the cortex and hippocampus in amygdale kindling rats compared with the control group.Furthermore,the number of MRP1-positive cells in the cortex and hippocampus was also significantly increased in amygdale kindling rats.Microdialysis studies showed that the concentrations of phenytoin and carbamazepine in the cortical extracellular fluid were significantly decreased in amygdale kindling rats.Pre-administration of probenecid could restore the concentrations back to their control levels.Conclusion:Up-regulation of MRP1 is responsible for the resistance of brain cells to antiepileptic drugs in the amygdale kindling rats.

  6. Process Modeling of Ferrofluids Flowfor Magnetic Targeting Drug Delivery

    Institute of Scientific and Technical Information of China (English)

    LIU Handan; WANG Shigang; XU Wei

    2009-01-01

    Among the proposed techniques for delivering drugs to specific sites within the human body, magnetic targeting drug delivery surpasses due to its non-invasive character and its high targeting efficiency. Although there have been some analyses theoretically for magnetic drug targeting, very few researchers have addressed the hydrodynamic models of magnetic fluids in the blood vessel of human body. This paper presents a mathematical model to describe the hydrodynamics of ferrofluids as drug carriers flowing in a blood vessel under the applied magnetic field. A 3D flow field of magnetic particles in a blood vessel model is numerically simulated in order to further understand clinical application of magnetic targeting drug delivery. Simulation results show that magnetic nanoparticles can be enriched in a target region depending on the applied magnetic field intensity. Magnetic resonance imaging conftrms the enrichment of ferrofluids in a desired body tissue of Sprague-Dawley rats. The simulation results coincide with those animal experiments. Results of the analysis provide the important information and can suggest strategies for improving delivery in favor of the clinical application.

  7. Hydration dynamics near a model protein surface

    Energy Technology Data Exchange (ETDEWEB)

    Russo, Daniela; Hura, Greg; Head-Gordon, Teresa

    2003-09-01

    The evolution of water dynamics from dilute to very high concentration solutions of a prototypical hydrophobic amino acid with its polar backbone, N-acetyl-leucine-methylamide (NALMA), is studied by quasi-elastic neutron scattering and molecular dynamics simulation for both the completely deuterated and completely hydrogenated leucine monomer. We observe several unexpected features in the dynamics of these biological solutions under ambient conditions. The NALMA dynamics shows evidence of de Gennes narrowing, an indication of coherent long timescale structural relaxation dynamics. The translational water dynamics are analyzed in a first approximation with a jump diffusion model. At the highest solute concentrations, the hydration water dynamics is significantly suppressed and characterized by a long residential time and a slow diffusion coefficient. The analysis of the more dilute concentration solutions takes into account the results of the 2.0M solution as a model of the first hydration shell. Subtracting the first hydration layer based on the 2.0M spectra, the translational diffusion dynamics is still suppressed, although the rotational relaxation time and residential time are converged to bulk-water values. Molecular dynamics analysis shows spatially heterogeneous dynamics at high concentration that becomes homogeneous at more dilute concentrations. We discuss the hydration dynamics results of this model protein system in the context of glassy systems, protein function, and protein-protein interfaces.

  8. Self-Assembling Peptide Amphiphiles for Therapeutic Delivery of Proteins, Drugs, and Stem Cells

    Science.gov (United States)

    Lee, Sungsoo Seth

    Biomaterials are used to help regenerate or replace the structure and function of damaged tissues. In order to elicit desired therapeutic responses in vivo, biomaterials are often functionalized with bioactive agents, such as growth factors, small molecule drugs, or even stem cells. Therefore, the strategies used to incorporate these bioactive agents in the microstructures and nanostructures of biomaterials can strongly influence the their therapeutic efficacy. Using self-assembling peptide amphiphiles (PAs), this work has investigated supramolecular nanostructures with improved interaction with three types of therapeutic agents: bone morphogenetic protein 2 (BMP-2) which promotes osteogenic differentiation and bone growth, anti-inflammatory drug naproxen which is used to treat osteo- and rheumatoid arthritis, and neural stem cells that could differentiate into neurons to treat neurodegenerative diseases. For BMP-2 delivery, two specific systems were investigated with affinity for BMP-2: 1) heparin-binding nanofibers that display the natural ligand of the osteogenic protein, and 2) nanofibers that display a synthetic peptide ligand discovered in our laboratory through phage display to directly bind BMP-2. Both systems promoted enhanced osteoblast differentiation of pluripotent C2C12 cells and augmented bone regeneration in two in vivo models, a rat critical-size femur defect model and spinal arthrodesis model. The thesis also describes the use of PA nanofibers to improve the delivery of the anti-inflammatory drug naproxen. To promote a controlled release, naproxen was chemically conjugated to the nanofiber surface via an ester bond that would only be cleaved by esterases, which are enzymes found naturally in the body. In the absence of esterases, the naproxen remained conjugated to the nanofibers and was non-bioactive. On the other hand, in the presence of esterases, naproxen was slowly released and inhibited cyclooxygenase-2 (COX-2) activity, an enzyme responsible

  9. The skill and style to model the evolution of resistance to pesticides and drugs.

    Science.gov (United States)

    2010-07-01

    Resistance to pesticides and drugs led to the development of theoretical models aimed at identifying the main factors of resistance evolution and predicting the efficiency of resistance management strategies. We investigated the various ways in which the evolution of resistance has been modelled over the last three decades, by reviewing 187 articles published on models of the evolution of resistance to all major classes of pesticides and drugs. We found that (i) the technical properties of the model were most strongly influenced by the class of pesticide or drug and the target organism, (ii) the resistance management strategies studied were quite similar for the different classes of pesticides or drugs, except that the refuge strategy was mostly used in models of the evolution of resistance to insecticidal proteins, (iii) economic criteria were rarely used to evaluate the evolution of resistance and (iv) the influence of mutation, migration and drift on the speed of resistance development has been poorly investigated. We propose guidelines for the future development of theoretical models of the evolution of resistance. For instance, we stress the potential need to give more emphasis to the three evolutionary forces migration, mutation and genetic drift rather than simply selection.

  10. Zebrafish as a Model Organism for the Development of Drugs for Skin Cancer

    Directory of Open Access Journals (Sweden)

    Fatemeh Bootorabi

    2017-07-01

    Full Text Available Skin cancer, which includes melanoma and squamous cell carcinoma, represents the most common type of cutaneous malignancy worldwide, and its incidence is expected to rise in the near future. This condition derives from acquired genetic dysregulation of signaling pathways involved in the proliferation and apoptosis of skin cells. The development of animal models has allowed a better understanding of these pathomechanisms, with the possibility of carrying out toxicological screening and drug development. In particular, the zebrafish (Danio rerio has been established as one of the most important model organisms for cancer research. This model is particularly suitable for live cell imaging and high-throughput drug screening in a large-scale fashion. Thanks to the recent advances in genome editing, such as the clustered regularly-interspaced short palindromic repeats (CRISPR/CRISPR-associated protein 9 (Cas9 methodologies, the mechanisms associated with cancer development and progression, as well as drug resistance can be investigated and comprehended. With these unique tools, the zebrafish represents a powerful platform for skin cancer research in the development of target therapies. Here, we will review the advantages of using the zebrafish model for drug discovery and toxicological and phenotypical screening. We will focus in detail on the most recent progress in the field of zebrafish model generation for the study of melanoma and squamous cell carcinoma (SCC, including cancer cell injection and transgenic animal development. Moreover, we will report the latest compounds and small molecules under investigation in melanoma zebrafish models.

  11. Predicting Protein Secondary Structure with Markov Models

    DEFF Research Database (Denmark)

    Fischer, Paul; Larsen, Simon; Thomsen, Claus

    2004-01-01

    we are considering here, is to predict the secondary structure from the primary one. To this end we train a Markov model on training data and then use it to classify parts of unknown protein sequences as sheets, helices or coils. We show how to exploit the directional information contained......The primary structure of a protein is the sequence of its amino acids. The secondary structure describes structural properties of the molecule such as which parts of it form sheets, helices or coils. Spacial and other properties are described by the higher order structures. The classification task...

  12. Biopartitioning micellar chromatography with sodium dodecyl sulfate as a pseudo α(1)-acid glycoprotein to the prediction of protein-drug binding.

    Science.gov (United States)

    Hadjmohammadi, Mohammadreza; Salary, Mina

    2013-01-01

    A simple and fast method is of urgent need to measure protein-drug binding affinity in order to meet the rapid development of new drugs. Biopartitioning micellar chromatography (BMC), a mode of micellar liquid chromatography (MLC) using micellar mobile phases in adequate experimental conditions, can be useful as an in vitro system in mimicking the drug-protein interactions. In this study, sodium dodecyl sulfate-micellar liquid chromatography (SDS-MLC) was used for the prediction of protein-drug binding based on the similar property of SDS micelles to α(1)-acid glycoprotein (AGP). The relationships between the BMC retention data of a heterogeneous set of 14 basic and neutral drugs and their plasma protein binding parameter were studied and the predictive ability of models was evaluated. Modeling of logk(BMC) of these compounds was established by multiple linear regression (MLR) and second-order polynomial models obtained in two different concentrations (0.07 and 0.09M) of SDS. The developed MLR models were characterized by both the descriptive and predictive ability (R(2)=0.882, R(CV)(2)=0.832 and R(2)=0.840, R(CV)(2)=0.765 for 0.07 and 0.09M SDS, respectively). The p values <0.01 also indicated that the relationships between the protein-drug binding and the logk(BMC) values were statistically significant at the 99% confidence level. The standard error of estimation showed the standard deviation of the regression to be 11.89 and 13.87 for 0.07 and 0.09M, respectively. The application of the developed model to a prediction set demonstrated that the model was also reliable with good predictive accuracy. The external and internal validation results showed that the predicted values were in good agreement with the experimental value.

  13. Emulsomes meet S-layer proteins: an emerging targeted drug delivery system.

    Science.gov (United States)

    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.

  14. Proteomics Analysis of Ovarian Cancer Cell Lines and Tissues Reveals Drug Resistance-associated Proteins

    Science.gov (United States)

    CRUZ*, ISA N.; COLEY*, HELEN M.; KRAMER, HOLGER B.; MADHURI, THUMULURU KAVITAH; SAFUWAN, NUR A.M.; ANGELINO, ANA RITA; YANG, MIN

    2016-01-01

    Background: Carboplatin and paclitaxel form the cornerstone of chemotherapy for epithelial ovarian cancer, however, drug resistance to these agents continues to present challenges. Despite extensive research, the mechanisms underlying this resistance remain unclear. Materials and Methods: A 2D-gel proteomics method was used to analyze protein expression levels of three human ovarian cancer cell lines and five biopsy samples. Representative proteins identified were validated via western immunoblotting. Ingenuity pathway analysis revealed metabolomic pathway changes. Results: A total of 189 proteins were identified with restricted criteria. Combined treatment targeting the proteasome-ubiquitin pathway resulted in re-sensitisation of drug-resistant cells. In addition, examination of five surgical biopsies of ovarian tissues revealed α-enolase (ENOA), elongation factor Tu, mitochondrial (EFTU), glyceraldehyde-3-phosphate dehydrogenase (G3P), stress-70 protein, mitochondrial (GRP75), apolipoprotein A-1 (APOA1), peroxiredoxin (PRDX2) and annexin A (ANXA) as candidate biomarkers of drug-resistant disease. Conclusion: Proteomics combined with pathway analysis provided information for an effective combined treatment approach overcoming drug resistance. Analysis of cell lines and tissues revealed potential prognostic biomarkers for ovarian cancer. *These Authors contributed equally to this study. PMID:28031236

  15. Animal models of drug relapse and craving: From drug priming-induced reinstatement to incubation of craving after voluntary abstinence.

    Science.gov (United States)

    Venniro, Marco; Caprioli, Daniele; Shaham, Yavin

    2016-01-01

    High rates of relapse to drug use during abstinence is a defining feature of drug addiction. In abstinent drug users, drug relapse is often precipitated by acute exposure to the self-administered drug, drug-associated cues, stress, as well as by short-term and protracted withdrawal symptoms. In this review, we discuss different animal models that have been used to study behavioral and neuropharmacological mechanisms of these relapse-related phenomena. In the first part, we discuss relapse models in which abstinence is achieved through extinction training, including the established reinstatement model, as well as the reacquisition and resurgence models. In the second part, we discuss recent animal models in which drug relapse is assessed after either forced abstinence (e.g., the incubation of drug craving model) or voluntary (self-imposed) abstinence achieved either by introducing adverse consequences to ongoing drug self-administration (e.g., punishment) or by an alternative nondrug reward using a discrete choice (drug vs. palatable food) procedure. We conclude by briefly discussing the potential implications of the recent developments of animal models of drug relapse after voluntary abstinence to the development of medications for relapse prevention.

  16. Determination of the total concentration of highly protein-bound drugs in plasma by on-line dialysis and column liquid chromatography : application to non-steroidal anti-inflammatory drugs

    NARCIS (Netherlands)

    Herráez-Hernández, R; van de Merbel, N C; Brinkman, U A

    1995-01-01

    The potential of on-line dialysis as a sample preparation procedure for compounds highly bound to plasma proteins is evaluated, using non-steroidal anti-inflammatory drugs as model compounds and column liquid chromatography as the separation technique. Different strategies to reduce the degree of dr

  17. Protein cages and synthetic polymers: a fruitful symbiosis for drug delivery applications, bionanotechnology and materials science.

    Science.gov (United States)

    Rother, Martin; Nussbaumer, Martin G; Renggli, Kasper; Bruns, Nico

    2016-11-07

    Protein cages are hollow protein nanoparticles, such as viral capsids, virus-like particles, ferritin, heat-shock proteins and chaperonins. They have well-defined capsule-like structures with a monodisperse size. Their protein subunits can be modified by genetic engineering at predetermined positions, allowing for example site-selective introduction of attachment points for functional groups, catalysts or targeting ligands on their outer surface, in their interior and between subunits. Therefore, protein cages have been extensively explored as functional entities in bionanotechnology, as drug-delivery or gene-delivery vehicles, as nanoreactors or as templates for the synthesis of organic and inorganic nanomaterials. The scope of functionalities and applications of protein cages can be significantly broadened if they are combined with synthetic polymers on their surface or within their interior. For example, PEGylation reduces the immunogenicity of protein cage-based delivery systems and active targeting ligands can be attached via polymer chains to favour their accumulation in diseased tissue. Polymers within protein cages offer the possibility of increasing the loading density of drug molecules, nucleic acids, magnetic resonance imaging contrast agents or catalysts. Moreover, the interaction of protein cages and polymers can be used to modulate the size and shape of some viral capsids to generate structures that do not occur with native viruses. Another possibility is to use the interior of polymer cages as a confined reaction space for polymerization reactions such as atom transfer radical polymerization or rhodium-catalysed polymerization of phenylacetylene. The protein nanoreactors facilitate a higher degree of control over polymer synthesis. This review will summarize the hybrid structures that have been synthesized by polymerizing from protein cage-bound initiators, by conjugating polymers to protein cages, by embedding protein cages into bulk polymeric

  18. Modeling mass drug treatment and resistant filaria disease transmission

    Science.gov (United States)

    Fuady, A. M.; Nuraini, N.; Soewono, E.; Tasman, H.; Supriatna, A. K.

    2014-03-01

    It has been indicated that a long term application of combined mass drug treatment may contribute to the development of drug resistance in lymphatic filariasis. This phenomenon is not well understood due to the complexity of filaria life cycle. In this paper we formulate a mathematical model for the spread of mass drug resistant in a filaria endemic region. The model is represented in a 13-dimensional Host-Vector system. The basic reproductive ratio of the system which is obtained from the next generation matrix, and analysis of stability of both the disease free equilibrium and the coexistence equilibria are shown. Numerical simulation for long term dynamics for possible field conditions is also shown.

  19. Chronic Neuroinflammation in Alzheimer’s Disease: New Perspectives on Animal Models and Promising Candidate Drugs

    Directory of Open Access Journals (Sweden)

    Christopher Millington

    2014-01-01

    Full Text Available Chronic neuroinflammation is now considered one of the major factors in the pathogenesis of Alzheimer’s disease (AD. However, the most widely used transgenic AD models (overexpressing mutated forms of amyloid precursor protein, presenilin, and/or tau do not demonstrate the degree of inflammation, neurodegeneration (particularly of the cholinergic system, and cognitive decline that is comparable with the human disease. Hence a more suitable animal model is needed to more closely mimic the resulting cognitive decline and memory loss in humans in order to investigate the effects of neuroinflammation on neurodegeneration. One of these models is the glial fibrillary acidic protein-interleukin 6 (GFAP-IL6 mouse, in which chronic neuroinflammation triggered constitutive expression of the cytokine interleukin-6 (IL-6 in astrocytes. These transgenic mice show substantial and progressive neurodegeneration as well as a decline in motor skills and cognitive function, starting from 6 months of age. This animal model could serve as an excellent tool for drug discovery and validation in vivo. In this review, we have also selected three potential anti-inflammatory drugs, curcumin, apigenin, and tenilsetam, as candidate drugs, which could be tested in this model.

  20. Model-building codes for membrane proteins.

    Energy Technology Data Exchange (ETDEWEB)

    Shirley, David Noyes; Hunt, Thomas W.; Brown, W. Michael; Schoeniger, Joseph S. (Sandia National Laboratories, Livermore, CA); Slepoy, Alexander; Sale, Kenneth L. (Sandia National Laboratories, Livermore, CA); Young, Malin M. (Sandia National Laboratories, Livermore, CA); Faulon, Jean-Loup Michel; Gray, Genetha Anne (Sandia National Laboratories, Livermore, CA)

    2005-01-01

    We have developed a novel approach to modeling the transmembrane spanning helical bundles of integral membrane proteins using only a sparse set of distance constraints, such as those derived from MS3-D, dipolar-EPR and FRET experiments. Algorithms have been written for searching the conformational space of membrane protein folds matching the set of distance constraints, which provides initial structures for local conformational searches. Local conformation search is achieved by optimizing these candidates against a custom penalty function that incorporates both measures derived from statistical analysis of solved membrane protein structures and distance constraints obtained from experiments. This results in refined helical bundles to which the interhelical loops and amino acid side-chains are added. Using a set of only 27 distance constraints extracted from the literature, our methods successfully recover the structure of dark-adapted rhodopsin to within 3.2 {angstrom} of the crystal structure.

  1. Protein Folding: Search for Basic Physical Models

    Directory of Open Access Journals (Sweden)

    Ivan Y. Torshin

    2003-01-01

    Full Text Available How a unique three-dimensional structure is rapidly formed from the linear sequence of a polypeptide is one of the important questions in contemporary science. Apart from biological context of in vivo protein folding (which has been studied only for a few proteins, the roles of the fundamental physical forces in the in vitro folding remain largely unstudied. Despite a degree of success in using descriptions based on statistical and/or thermodynamic approaches, few of the current models explicitly include more basic physical forces (such as electrostatics and Van Der Waals forces. Moreover, the present-day models rarely take into account that the protein folding is, essentially, a rapid process that produces a highly specific architecture. This review considers several physical models that may provide more direct links between sequence and tertiary structure in terms of the physical forces. In particular, elaboration of such simple models is likely to produce extremely effective computational techniques with value for modern genomics.

  2. Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets.

    Science.gov (United States)

    Vinayagam, Arunachalam; Gibson, Travis E; Lee, Ho-Joon; Yilmazel, Bahar; Roesel, Charles; Hu, Yanhui; Kwon, Young; Sharma, Amitabh; Liu, Yang-Yu; Perrimon, Norbert; Barabási, Albert-László

    2016-05-03

    The protein-protein interaction (PPI) network is crucial for cellular information processing and decision-making. With suitable inputs, PPI networks drive the cells to diverse functional outcomes such as cell proliferation or cell death. Here, we characterize the structural controllability of a large directed human PPI network comprising 6,339 proteins and 34,813 interactions. This network allows us to classify proteins as "indispensable," "neutral," or "dispensable," which correlates to increasing, no effect, or decreasing the number of driver nodes in the network upon removal of that protein. We find that 21% of the proteins in the PPI network are indispensable. Interestingly, these indispensable proteins are the primary targets of disease-causing mutations, human viruses, and drugs, suggesting that altering a network's control property is critical for the transition between healthy and disease states. Furthermore, analyzing copy number alterations data from 1,547 cancer patients reveals that 56 genes that are frequently amplified or deleted in nine different cancers are indispensable. Among the 56 genes, 46 of them have not been previously associated with cancer. This suggests that controllability analysis is very useful in identifying novel disease genes and potential drug targets.

  3. In silico ADME/T modelling for rational drug design.

    Science.gov (United States)

    Wang, Yulan; Xing, Jing; Xu, Yuan; Zhou, Nannan; Peng, Jianlong; Xiong, Zhaoping; Liu, Xian; Luo, Xiaomin; Luo, Cheng; Chen, Kaixian; Zheng, Mingyue; Jiang, Hualiang

    2015-11-01

    In recent decades, in silico absorption, distribution, metabolism, excretion (ADME), and toxicity (T) modelling as a tool for rational drug design has received considerable attention from pharmaceutical scientists, and various ADME/T-related prediction models have been reported. The high-throughput and low-cost nature of these models permits a more streamlined drug development process in which the identification of hits or their structural optimization can be guided based on a parallel investigation of bioavailability and safety, along with activity. However, the effectiveness of these tools is highly dependent on their capacity to cope with needs at different stages, e.g. their use in candidate selection has been limited due to their lack of the required predictability. For some events or endpoints involving more complex mechanisms, the current in silico approaches still need further improvement. In this review, we will briefly introduce the development of in silico models for some physicochemical parameters, ADME properties and toxicity evaluation, with an emphasis on the modelling approaches thereof, their application in drug discovery, and the potential merits or deficiencies of these models. Finally, the outlook for future ADME/T modelling based on big data analysis and systems sciences will be discussed.

  4. Toward a pragmatic migraine model for drug testing

    DEFF Research Database (Denmark)

    Hansen, Emma Katrine; Guo, Song; Ashina, Messoud

    2016-01-01

    BACKGROUND: A model for the testing of novel antimigraine drugs should ideally use healthy volunteers for ease of recruiting. Cilostazol provokes headache in healthy volunteers with some migraine features such as pulsating pain quality and aggravation by physical activity. Therefore, this headache...

  5. New Hepatitis C Virus Drug Discovery Strategies and Model Systems

    Science.gov (United States)

    Hussain, Snawar; Barretto, Naina; Uprichard, Susan L

    2013-01-01

    Introduction Hepatitis C virus is a major cause of liver disease worldwide and the leading indication for liver transplantation in the United States. Current treatment options are expensive, not effective in all patients and are associated with serious side effects. While pre-clinical anti-HCV drug screening is still hampered by the lack of readily infectable small animal models, the development of cell culture HCV experimental model systems has driven a promising new wave of HCV antiviral drug discovery. Areas covered This review contains a concise overview of current HCV treatment options and limitations with a subsequent in-depth focus on the available experimental models and novel strategies that have and continue to enable important advances in HCV drug development. Expert opinion With a large cohort of chronically HCV infected patients progressively developing liver disease that puts them at risk for hepatocellular carcinoma and hepatic decompensation, there is an urgent need to develop effective therapeutics that are well-tolerated and effective in all patients and against all HCV genotypes. Significant advances in HCV experimental model development have expedited drug discovery; however, additional progress is needed. Importantly, the current trends and momentum in the field suggests that we will continue to overcome critical experimental challenges to reach this end goal. PMID:22861052

  6. Discovery of cancer drug targets by CRISPR-Cas9 screening of protein domains.

    Science.gov (United States)

    Shi, Junwei; Wang, Eric; Milazzo, Joseph P; Wang, Zihua; Kinney, Justin B; Vakoc, Christopher R

    2015-06-01

    CRISPR-Cas9 genome editing technology holds great promise for discovering therapeutic targets in cancer and other diseases. Current screening strategies target CRISPR-Cas9-induced mutations to the 5' exons of candidate genes, but this approach often produces in-frame variants that retain functionality, which can obscure even strong genetic dependencies. Here we overcome this limitation by targeting CRISPR-Cas9 mutagenesis to exons encoding functional protein domains. This generates a higher proportion of null mutations and substantially increases the potency of negative selection. We also show that the magnitude of negative selection can be used to infer the functional importance of individual protein domains of interest. A screen of 192 chromatin regulatory domains in murine acute myeloid leukemia cells identifies six known drug targets and 19 additional dependencies. A broader application of this approach may allow comprehensive identification of protein domains that sustain cancer cells and are suitable for drug targeting.

  7. Structure-based drug design for G protein-coupled receptors.

    Science.gov (United States)

    Congreve, Miles; Dias, João M; Marshall, Fiona H

    2014-01-01

    Our understanding of the structural biology of G protein-coupled receptors has undergone a transformation over the past 5 years. New protein-ligand complexes are described almost monthly in high profile journals. Appreciation of how small molecules and natural ligands bind to their receptors has the potential to impact enormously how medicinal chemists approach this major class of receptor targets. An outline of the key topics in this field and some recent examples of structure- and fragment-based drug design are described. A table is presented with example views of each G protein-coupled receptor for which there is a published X-ray structure, including interactions with small molecule antagonists, partial and full agonists. The possible implications of these new data for drug design are discussed.

  8. Cell and small animal models for phenotypic drug discovery

    Directory of Open Access Journals (Sweden)

    Szabo M

    2017-06-01

    Full Text Available Mihaly Szabo,1 Sara Svensson Akusjärvi,1 Ankur Saxena,1 Jianping Liu,2 Gayathri Chandrasekar,1 Satish S Kitambi1 1Department of Microbiology Tumor, and Cell Biology, 2Department of Biochemistry and Biophysics, Karolinska Institutet, Solna, Sweden Abstract: The phenotype-based drug discovery (PDD approach is re-emerging as an alternative platform for drug discovery. This review provides an overview of the various model systems and technical advances in imaging and image analyses that strengthen the PDD platform. In PDD screens, compounds of therapeutic value are identified based on the phenotypic perturbations produced irrespective of target(s or mechanism of action. In this article, examples of phenotypic changes that can be detected and quantified with relative ease in a cell-based setup are discussed. In addition, a higher order of PDD screening setup using small animal models is also explored. As PDD screens integrate physiology and multiple signaling mechanisms during the screening process, the identified hits have higher biomedical applicability. Taken together, this review highlights the advantages gained by adopting a PDD approach in drug discovery. Such a PDD platform can complement target-based systems that are currently in practice to accelerate drug discovery. Keywords: phenotype, screening, PDD, discovery, zebrafish, drug

  9. A thermal analogy for modelling drug elution from cardiovascular stents.

    Science.gov (United States)

    Hose, D R; Narracott, A J; Griffiths, B; Mahmood, S; Gunn, J; Sweeney, D; Lawford, P V

    2004-10-01

    Restriction of blood flow by the narrowing or occlusion of arteries is one of the most common presentations of cardiovascular disease. One treatment involves the introduction of a metal scaffold, or stent, designed to prevent recoil and to provide structural stability to the vessel. On the occasions that this treatment is ineffective, failure is usually associated with re-invasion of tissue. This can be prevented by local delivery of drugs which inhibit tissue growth. The drug might be delivered locally in a polymer coating on the stent. This paper develops and explores the use of a thermal analogue of the drug delivery process and the associated three-dimensional convection-diffusion equation to model the spatial and temporal distribution of drug concentration within the vessel wall. This allows the routine use of commercial finite element analysis software to investigate the dynamics of drug distribution, assist in the understanding of the treatment process and develop improved delivery systems. Two applications illustrate how the model might be used to investigate the effects of controllable or measurable parameters on the progression of the process. It is demonstrated that the geometric characteristics of the stent can have significant impact on the homogeneity of the dosing in the vessel wall.

  10. Review: US Spelling Colorectal cancer models for novel drug discovery

    Science.gov (United States)

    Golovko, Daniel; Kedrin, Dmitriy; Yilmaz, Omer H.; Roper, Jatin

    2016-01-01

    Introduction Despite increased screening rates and advances in targeted therapy, colorectal cancer (CRC) remains the third leading cause of cancer-related mortality. CRC models that recapitulate key features of human disease are essential to the development of novel and effective therapeutics. Classic methods of modeling CRC such as human cell lines and xenograft mice, while useful for many applications, carry significant limitations. Recently developed in vitro and in vivo models overcome some of these deficiencies and thus can be utilized to better model CRC for mechanistic and translational research. Areas Covered The authors review established models of in vitro cell culture and describe advances in organoid culture for studying normal and malignant intestine. They also discuss key features of classic xenograft models and describe other approaches for in vivo CRC research, including patient-derived xenograft, carcinogen-induced, orthotopic transplantation, and transgenic mouse models. We also describe mouse models of metastatic CRC. Expert opinion No single model is optimal for drug discovery in CRC. Genetically engineered models overcome many limitations of xenograft models. Three-dimensional organoids can be efficiently derived from both normal and malignant tissue for large-scale in vitro and in vivo (transplantation) studies, and are thus a significant advance in CRC drug discovery. PMID:26295972

  11. Properties and formulation of oral drug delivery systems of protein and peptides

    Directory of Open Access Journals (Sweden)

    Semalty A

    2007-01-01

    Full Text Available Although most protein pharmaceuticals are usually formulated as a solution or suspension and delivered by invasive routes such as subcutaneous injections, major efforts in both academic and industrial laboratories have been directed towards developing effective oral formulations and increasing the oral absorption of intact protein through the use of formulations that protect the macromolecule and/or enhance it′s uptake into the intestinal mucosa. However, in spite of these major attempts, relatively little progress has been made. For the efficient delivery of peptides and proteins by non-parenteral route, in particular via the gastrointestinal tract, novel concepts are needed to overcome significant enzymatic and diffusion barriers. The properties of protein and peptides, which are of major interest in oral delivery, are highlighted in the article. This article reviews the various problems associated and novel approaches for formulation and development of oral protein and peptide drug delivery systems.

  12. Quantitative modeling of selective lysosomal targeting for drug design

    DEFF Research Database (Denmark)

    Trapp, Stefan; Rosania, G.; Horobin, R.W.;

    2008-01-01

    Lysosomes are acidic organelles and are involved in various diseases, the most prominent is malaria. Accumulation of molecules in the cell by diffusion from the external solution into cytosol, lysosome and mitochondrium was calculated with the Fick–Nernst–Planck equation. The cell model considers....... This demonstrates that the cell model can be a useful tool for the design of effective lysosome-targeting drugs with minimal off-target interactions....

  13. Modeling disordered regions in proteins using Rosetta.

    Directory of Open Access Journals (Sweden)

    Ray Yu-Ruei Wang

    Full Text Available Protein structure prediction methods such as Rosetta search for the lowest energy conformation of the polypeptide chain. However, the experimentally observed native state is at a minimum of the free energy, rather than the energy. The neglect of the missing configurational entropy contribution to the free energy can be partially justified by the assumption that the entropies of alternative folded states, while very much less than unfolded states, are not too different from one another, and hence can be to a first approximation neglected when searching for the lowest free energy state. The shortcomings of current structure prediction methods may be due in part to the breakdown of this assumption. Particularly problematic are proteins with significant disordered regions which do not populate single low energy conformations even in the native state. We describe two approaches within the Rosetta structure modeling methodology for treating such regions. The first does not require advance knowledge of the regions likely to be disordered; instead these are identified by minimizing a simple free energy function used previously to model protein folding landscapes and transition states. In this model, residues can be either completely ordered or completely disordered; they are considered disordered if the gain in entropy outweighs the loss of favorable energetic interactions with the rest of the protein chain. The second approach requires identification in advance of the disordered regions either from sequence alone using for example the DISOPRED server or from experimental data such as NMR chemical shifts. During Rosetta structure prediction calculations the disordered regions make only unfavorable repulsive contributions to the total energy. We find that the second approach has greater practical utility and illustrate this with examples from de novo structure prediction, NMR structure calculation, and comparative modeling.

  14. Total Protein Profile and Drug Resistance in Candida albicans Isolated from Clinical Samples

    Directory of Open Access Journals (Sweden)

    Kamal Uddin Zaidi

    2016-01-01

    Full Text Available This study was done to assess the antifungal susceptibility of clinical isolates of Candida albicans and to evaluate its total protein profile based on morphological difference on drug resistance. Hundred and twenty clinical isolates of C. albicans from various clinical specimens were tested for susceptibility against four antifungal agents, namely, fluconazole, itraconazole, amphotericin B, and ketoconazole. A significant increase of drug resistance in clinical isolates of C. albicans was observed. The study showed 50% fluconazole and itraconazole resistance at 32 μg mL−1 with a MIC50 and MIC90 values at 34 and 47 and 36 and 49 μg mL−1, respectively. All isolates were sensitive to amphotericin B and ketoconazole. The SDS-PAGE protein profile showed a prevalent band of ~52.5 kDa, indicating overexpression of gene in 72% strains with fluconazole resistance. Since the opportunistic infections of Candida spp. are increasing along with drug resistance, the total protein profile will help in understanding the evolutionary changes in drug resistance and also to characterize them.

  15. Functional characterisation of Burkholderia pseudomallei biotin protein ligase: A toolkit for anti-melioidosis drug development.

    Science.gov (United States)

    Bond, Thomas E H; Sorenson, Alanna E; Schaeffer, Patrick M

    2017-06-01

    Burkholderia pseudomallei (Bp) is the causative agent of melioidosis. The bacterium is responsible for 20% of community-acquired sepsis cases and 40% of sepsis-related mortalities in northeast Thailand, and is intrinsically resistant to aminoglycosides, macrolides, rifamycins, cephalosporins, and nonureidopenicillins. There is no vaccine and its diagnosis is problematic. Biotin protein ligase (BirA) which is essential for fatty acid synthesis has been proposed as a drug target in bacteria. Very few bacterial BirA have been characterized, and a better understanding of these enzymes is necessary to further assess their value as drug targets. BirA within the Burkholderia genus have not yet been investigated. We present for the first time the cloning, expression, purification and functional characterisation of the putative Bp BirA and orthologous B. thailandensis (Bt) biotin carboxyl carrier protein (BCCP) substrate. A GFP-tagged Bp BirA was produced and applied for the development of a high-throughput (HT) assay based on our differential scanning fluorimetry of GFP-tagged proteins (DSF-GTP) principle as well as an electrophoretic mobility shift assay. Our biochemical data in combination with the new HT DSF-GTP and biotinylation activity assay could facilitate future drug screening efforts against this drug-resistant organism. Copyright © 2017 Elsevier GmbH. All rights reserved.

  16. INVESTIGATION ON EFFECT OF DRUG DOSING REGIMENTS ON DRUG DELIVERY IN SOLID TUMOR VIA LUMPED PARAMETER MODELING AND ANIMAL EXPERIMENTS

    Institute of Scientific and Technical Information of China (English)

    GAO Ci-xiu; XU Shi-xiong; JIANG Yu-ping; TU Jiang-long

    2009-01-01

    This work aims to investigate the effects of dosing regiments on drug delivery in solid tumors and to validate them with experiments on rats.The lumped parameter models of pharmacokinetics and of drug delivery in tumor were developed to simulate time courses of average drug concentration(Ct)of tumor interstitium in two types of dosing regiments(i.e.,single-shot and triple-shot ones).The two regiments were performed via antitumor drug,hydroxycamptothecin(HCPT),on rats,to measure the drug concentration in the tumor.The simulations of the drug concentration in the tumor of the two dosing regiments were conducted and compared with the experimental data on rats.The coefficients in the models were investigated.It is concluded that the triple-shot method is more effective than that of single-shot injection.The present lumped-parameter model is quantitatively competent for drug delivery in solid tumor.

  17. A critical evaluation of Amicon Ultra centrifugal filters for separating proteins, drugs and nanoparticles in biosamples.

    Science.gov (United States)

    Johnsen, Elin; Brandtzaeg, Ole Kristian; Vehus, Tore; Roberg-Larsen, Hanne; Bogoeva, Vanya; Ademi, Ornela; Hildahl, Jon; Lundanes, Elsa; Wilson, Steven Ray

    2016-02-20

    Amicon(®) Ultra centrifugal filters were critically evaluated for various sample preparations, namely (a) proteome fractionation, (b) sample cleanup prior to liquid chromatography mass spectrometry (LC-MS) measurement of small molecules in cell lysate, and (c) separating drug-loaded nanoparticles and released drugs for accurate release profiling in biological samples. (a) Filters of supposedly differing molar mass (MM) selectivity (10, 30, 50 and 100K) were combined to attempt fractionation of samples of various complexity and concentration. However, the products had surprisingly similar MM retentate/filtrate profiles, and the filters were unsuited for proteome fractionation. (b) Centrifugal filtration was the only clean-up procedure in a FDA-guideline validated LC-MS method for determining anti-tuberculosis agents rifampicin and thioridazine in macrophage cell lysate. An additional organic solvent washing step (drug/protein-binding disruption) was required for satisfactory recovery. (c) The centrifugation filters are well suited for separating drugs and nanoparticles in simple aqueous solutions, but significantly less so for biological samples, as common drug-protein binding disruptors can dissolve NPs or be incompatible with LC-MS instrumentation.

  18. Harvesting candidate genes responsible for serious adverse drug reactions from a chemical-protein interactome.

    Directory of Open Access Journals (Sweden)

    Lun Yang

    2009-07-01

    Full Text Available Identifying genetic factors responsible for serious adverse drug reaction (SADR is of critical importance to personalized medicine. However, genome-wide association studies are hampered due to the lack of case-control samples, and the selection of candidate genes is limited by the lack of understanding of the underlying mechanisms of SADRs. We hypothesize that drugs causing the same type of SADR might share a common mechanism by targeting unexpectedly the same SADR-mediating protein. Hence we propose an approach of identifying the common SADR-targets through constructing and mining an in silico chemical-protein interactome (CPI, a matrix of binding strengths among 162 drug molecules known to cause at least one type of SADR and 845 proteins. Drugs sharing the same SADR outcome were also found to possess similarities in their CPI profiles towards this 845 protein set. This methodology identified the candidate gene of sulfonamide-induced toxic epidermal necrolysis (TEN: all nine sulfonamides that cause TEN were found to bind strongly to MHC I (Cw*4, whereas none of the 17 control drugs that do not cause TEN were found to bind to it. Through an insight into the CPI, we found the Y116S substitution of MHC I (B*5703 enhances the unexpected binding of abacavir to its antigen presentation groove, which explains why B*5701, not B*5703, is the risk allele of abacavir-induced hypersensitivity. In conclusion, SADR targets and the patient-specific off-targets could be identified through a systematic investigation of the CPI, generating important hypotheses for prospective experimental validation of the candidate genes.

  19. Protein redox chemistry: post-translational cysteine modifications that regulate signal transduction and drug pharmacology

    Directory of Open Access Journals (Sweden)

    Revati eWani

    2014-10-01

    Full Text Available The perception of reactive oxygen species (ROS has evolved over the past decade from agents of cellular damage to secondary messengers which modify signaling proteins in physiology and the disease state (e.g. cancer. New protein targets of specific oxidation are rapidly being identified. One emerging class of redox modification occurs to the thiol side chain of cysteine residues which can produce multiple chemically-distinct alterations to the protein (e.g. sulfenic/sulfinic/sulfonic acid, disulfides. These post-translational modifications (PTM are shown to affect the protein structure and function. Because redox-sensitive proteins can traffic between subcellular compartments that have different redox environments, cysteine oxidation enables a spatio-temporal control to signaling. Understanding ramifications of these oxidative modifications to the functions of signaling proteins is crucial for understanding cellular regulation as well as for informed-drug discovery process. The effects of EGFR oxidation of Cys797 on inhibitor pharmacology are presented to illustrate the principle. Taken together, cysteine redox PTM can impact both cell biology and drug pharmacology.

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

    Directory of Open Access Journals (Sweden)

    Yuri Pevzner

    2014-05-01

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

  1. Implying Analytic Measures for Unravelling Rheumatoid Arthritis Significant Proteins Through Drug-Target Interaction.

    Science.gov (United States)

    Singh, Sachidanand; Vennila, J Jannet; Snijesh, V P; George, Gincy; Sunny, Chinnu

    2016-06-01

    Rheumatoid arthritis (RA) is a systemic autoimmune and inflammatory disease that mainly alters the synovial joints and ultimately leads to their destruction. The involvement of the immune system and its related cells is a basic trademark of autoimmune-associated diseases. The present work focuses on network analysis and its functional characterization to predict novel targets for RA. The interactive model called as rheumatoid arthritis drug-target-protein (RA-DTP) is built of 1727 nodes and 7954 edges followed the power-law distribution. RA-DTP comprised of 20 islands, 55 modules and 123 submodules. Good interactome coverage of target-protein was detected in island 2 (Q-Score 0.875) which includes 673 molecules with 20 modules and 68 submodules. The biological landscape of these modules was examined based on the participation molecules in specific cellular localization, molecular function and biological pathway with favourable p value. Functional characterization and pathway analysis through KEGG, Biocarta and Reactome also showed their involvement in relation to the immune system and inflammatory processes and biological processes such as cell signalling and communication, glucosamine metabolic process, renin-angiotensin system, BCR signals, galactose metabolism, MAPK signalling, complement and coagulation system and NGF signalling pathways. Traffic values and centrality parameters were applied as the selection criteria for identifying potential targets from the important hubs which resulted into FOS, KNG1, PTGDS, HSP90AA1, REN, POMC, FCER1G, IL6, ICAM1, SGK1, NOS3 and PLA2G4A. This approach provides an insight into experimental validation of these associations of potential targets for clinical value to find their effect on animal studies.

  2. Reinforcement, dopamine and rodent models in drug development for ADHD.

    Science.gov (United States)

    Tripp, Gail; Wickens, Jeff

    2012-07-01

    Attention deficit hyperactivity disorder (ADHD) presents special challenges for drug development. Current treatment with psychostimulants and nonstimulants is effective, but their mechanism of action beyond the cellular level is incompletely understood. We review evidence suggesting that altered reinforcement mechanisms are a fundamental characteristic of ADHD. We show that a deficit in the transfer of dopamine signals from established positive reinforcers to cues that predict such reinforcers may underlie these altered reinforcement mechanisms, and in turn explain key symptoms of ADHD. We argue that the neural substrates controlling the excitation and inhibition of dopamine neurons during the transfer process are a promising target for future drug development. There is a need to develop animal models and behavioral paradigms that can be used to experimentally investigate these mechanisms and their effects on sensitivity to reinforcement. More specific and selective targeting of drug development may be possible through this approach.

  3. Optimal Control of Drug Therapy in a Hepatitis B Model

    Directory of Open Access Journals (Sweden)

    Jonathan E. Forde

    2016-08-01

    Full Text Available Combination antiviral drug therapy improves the survival rates of patients chronically infected with hepatitis B virus by controlling viral replication and enhancing immune responses. Some of these drugs have side effects that make them unsuitable for long-term administration. To address the trade-off between the positive and negative effects of the combination therapy, we investigated an optimal control problem for a delay differential equation model of immune responses to hepatitis virus B infection. Our optimal control problem investigates the interplay between virological and immunomodulatory effects of therapy, the control of viremia and the administration of the minimal dosage over a short period of time. Our numerical results show that the high drug levels that induce immune modulation rather than suppression of virological factors are essential for the clearance of hepatitis B virus.

  4. Modeling energy intake by adding homeostatic feedback and drug intervention.

    Science.gov (United States)

    Gennemark, Peter; Hjorth, Stephan; Gabrielsson, Johan

    2015-02-01

    Energy intake (EI) is a pivotal biomarker used in quantification approaches to metabolic disease processes such as obesity, diabetes, and growth disorders. Eating behavior is however under both short-term and long-term control. This control system manifests itself as tolerance and rebound phenomena in EI, when challenged by drug treatment or diet restriction. The paper describes a model with the capability to capture physiological counter-regulatory feedback actions triggered by energy imbalances. This feedback is general as it handles tolerance to both increases and decreases in EI, and works in both acute and chronic settings. A drug mechanism function inhibits (or stimulates) EI. The deviation of EI relative to a reference level (set-point) serves as input to a non-linear appetite control signal which in turn impacts EI in parallel to the drug intervention. Three examples demonstrate the potential usefulness of the model in both acute and chronic dosing situations. The model shifts the predicted concentration-response relationship rightwardly at lower concentrations, in contrast to models that do not handle functional adaptation. A fourth example further shows that the model may qualitatively explain differences in rate and extent of adaptation in observed EI and its concomitants in both rodents and humans.

  5. Growth Factor Tethering to Protein Nanoparticles via Coiled-Coil Formation for Targeted Drug Delivery.

    Science.gov (United States)

    Assal, Yasmine; Mizuguchi, Yoshinori; Mie, Masayasu; Kobatake, Eiry

    2015-08-19

    Protein-based nanoparticles are attractive carriers for drug delivery because they are biodegradable and can be genetically designed. Moreover, modification of protein-based nanoparticles with cell-specific ligands allows for active targeting abilities. Previously, we developed protein nanoparticles comprising genetically engineered elastin-like polypeptides (ELPs) with fused polyaspartic acid tails (ELP-D). Epidermal growth factor (EGF) was displayed on the surface of the ELP-D nanoparticles via genetic design to allow for active cell-targeting abilities. Herein, we focused on the coiled-coil structural motif as a means for noncovalent tethering of growth factor to ELP-D. Specifically, two peptides known to form a heterodimer via a coiled-coil structural motif were fused to ELP-D and single-chain vascular endothelial growth factor (scVEGF121), to facilitate noncovalent tethering upon formation of the heterodimer coiled-coil structure. Drug-loaded growth factor-tethered ELP-Ds were found to be effective against cancer cells by provoking cell apoptosis. These results demonstrate that tethering growth factor to protein nanoparticles through coiled-coil formation yields a promising biomaterial candidate for targeted drug delivery.

  6. Investigating the effect of an arterial hypertension drug on the structural properties of plasma protein.

    Science.gov (United States)

    Hassan, Natalia; Maldonado-Valderrama, Julia; Gunning, A Patrick; Morris, V J; Ruso, Juan M

    2011-10-15

    Propanolol is a betablocker drug used in the treatment of arterial hypertension related diseases. In order to achieve an optimal performance of this drug it is important to consider the possible interactions of propanolol with plasma proteins. In this work, we have used several experimental techniques to characterise the effect of addition of the betablocker propanolol on the properties of bovine plasma fibrinogen (FB). Differential scanning calorimeter (DSC), circular dichroism (CD), dynamic light scattering (DLS), surface tension techniques and atomic force microscopy (AFM) measurements have been combined to carry out a detailed physicochemical and surface characterization of the mixed system. As a result, DSC measurements show that propranolol can play two opposite roles, either acting as a structure stabilizer at low molar concentrations or as a structure destabilizer at higher concentrations, in different domains of fibrinogen. CD measurements have revealed that the effect of propanolol on the secondary structure of fibrinogen depends on the temperature and the drug concentration and the DLS analysis showed evidence for protein aggregation. Interestingly, surface tension measurements provided further evidence of the conformational change induced by propanolol on the secondary structure of FB by importantly increasing the surface tension of the system. Finally, AFM imaging of the fibrinogen system provided direct visualization of the protein structure in the presence of propanolol. Combination of these techniques has produced complementary information on the behavior of the mixed system, providing new insights into the structural properties of proteins with potential medical interest.

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

    Science.gov (United States)

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

    2016-01-01

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

  8. Pharmacophore model of drugs involved in P-glycoprotein multidrug resistance: explanation of structural variety (hypothesis).

    Science.gov (United States)

    Pajeva, Ilza K; Wiese, Michael

    2002-12-19

    A general pharmacophore model of P-glycoprotein (P-gp) drugs is proposed that is based on a highly diverse data set and relates to the verapamil binding site of the protein. It is derived from structurally different drugs using the program GASP. The pharmacophore model consists of two hydrophobic points, three hydrogen bond (HB) acceptor points, and one HB donor point. Pharmacophore patterns of various drugs are obtained, and different binding modes are presumed for some of them. It is concluded that the binding affinity of the drugs depends on the number of the pharmacophore points simultaneously involved in the interaction with P-gp. On the basis of the obtained results, a hypothesis is proposed to explain the broad structural variety of the P-gp substrates and inhibitors: (i) the verapamil binding site of P-gp has several points that can participate in hydrophobic and HB interactions; (ii) different drugs can interact with different receptor points in different binding modes.

  9. A Model for Predicting the Interindividual Variability of Drug-Drug Interactions.

    Science.gov (United States)

    Tod, M; Bourguignon, L; Bleyzac, N; Goutelle, S

    2017-03-01

    Pharmacokinetic drug-drug interactions are frequently characterized and quantified by an AUC ratio (Rauc). The typical value of the AUC ratio in case of cytochrome-mediated interactions may be predicted by several approaches, based on in vitro or in vivo data. Prediction of the interindividual variability of Rauc would help to anticipate more completely the consequences of a drug-drug interaction. We propose and evaluate a simple approach for predicting the standard deviation (sd) of Ln(Rauc), a metric close to the interindividual coefficient of variation of Rauc. First, a model was derived to link sd(Ln Rauc) with the substrate fraction metabolized by each cytochrome and the potency of the interactors, in case of induction or inhibition. Second, the parameters involved in these equations were estimated by a Bayesian hierarchical model, using the data from 56 interaction studies retrieved from the literature. Third, the model was evaluated by several metrics based on the fold prediction error (PE) of sd(Ln Rauc). The median PE was 0.998 (the ideal value is 1) and the interquartile range was 0.96-1.03. The PE was in the acceptable interval (0.5 to 2) in 52 cases out of 56. Fourth, a surface plot of sd(Ln Rauc) as a function of the characteristics of the substrate and the interactor has been built. The minimal value of sd(Ln Rauc) was about 0.08 (obtained for Rauc = 1) while the maximal value, 0.7, was obtained for interactions involving highly metabolized substrates with strong interactors.

  10. A Two-Layer Mathematical Modelling of Drug Delivery to Biological Tissues

    CERN Document Server

    Chakravarty, Koyel

    2016-01-01

    Local drug delivery has received much recognition in recent years, yet it is still unpredictable how drug efficacy depends on physicochemical properties and delivery kinetics. The purpose of the current study is to provide a useful mathematical model for drug release from a drug delivery device and consecutive drug transport in biological tissue, thereby aiding the development of new therapeutic drug by a systemic approach. In order to study the complete process, a two-layer spatio-temporal model depicting drug transport between the coupled media is presented. Drug release is described by considering solubilisation dynamics of drug particle, diffusion of the solubilised drug through porous matrix and also some other processes like reversible dissociation / recrystallization, drug particle-receptor binding and internalization phenomena. The model has led to a system of partial differential equations describing the important properties of drug kinetics. This model contributes towards the perception of the roles...

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

    Science.gov (United States)

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

    2013-07-01

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

  12. Animal models for testing anti-prion drugs.

    Science.gov (United States)

    Fernández-Borges, Natalia; Elezgarai, Saioa R; Eraña, Hasier; Castilla, Joaquín

    2013-01-01

    Prion diseases belong to a group of fatal infectious diseases with no effective therapies available. Throughout the last 35 years, less than 50 different drugs have been tested in different experimental animal models without hopeful results. An important limitation when searching for new drugs is the existence of appropriate models of the disease. The three different possible origins of prion diseases require the existence of different animal models for testing anti-prion compounds. Wild type, over-expressing transgenic mice and other more sophisticated animal models have been used to evaluate a diversity of compounds which some of them were previously tested in different in vitro experimental models. The complexity of prion diseases will require more pre-screening studies, reliable sporadic (or spontaneous) animal models and accurate chemical modifications of the selected compounds before having an effective therapy against human prion diseases. This review is intended to put on display the more relevant animal models that have been used in the search of new antiprion therapies and describe some possible procedures when handling chemical compounds presumed to have anti-prion activity prior to testing them in animal models.

  13. Animal models in therapeutic drug discovery for oculopharyngeal muscular dystrophy.

    Science.gov (United States)

    Chartier, Aymeric; Simonelig, Martine

    2013-01-01

    Oculopharyngeal muscular dystrophy (OPMD) is a late onset disease which affects specific muscles. No pharmacological treatments are currently available for OPMD. In recent years, genetically tractable models of OPMD – Drosophila and Caenorhabditis elegans – have been generated. Although these models have not yet been used for large-scale primary drug screening, they have been very useful in candidate approaches for the identification of potential therapeutic compounds for OPMD. In this brief review, we summarize the data that validated active molecules for OPMD in animal models including Drosophila, C. elegans and mouse.

  14. Biomembrane models and drug-biomembrane interaction studies: Involvement in drug design and development

    Directory of Open Access Journals (Sweden)

    R Pignatello

    2011-01-01

    Full Text Available Contact with many different biological membranes goes along the destiny of a drug after its systemic administration. From the circulating macrophage cells to the vessel endothelium, to more complex absorption barriers, the interaction of a biomolecule with these membranes largely affects its rate and time of biodistribution in the body and at the target sites. Therefore, investigating the phenomena occurring on the cell membranes, as well as their different interaction with drugs in the physiological or pathological conditions, is important to exploit the molecular basis of many diseases and to identify new potential therapeutic strategies. Of course, the complexity of the structure and functions of biological and cell membranes, has pushed researchers toward the proposition and validation of simpler two- and three-dimensional membrane models, whose utility and drawbacks will be discussed. This review also describes the analytical methods used to look at the interactions among bioactive compounds with biological membrane models, with a particular accent on the calorimetric techniques. These studies can be considered as a powerful tool for medicinal chemistry and pharmaceutical technology, in the steps of designing new drugs and optimizing the activity and safety profile of compounds already used in the therapy.

  15. Tuning HERG out: antitarget QSAR models for drug development.

    Science.gov (United States)

    Braga, Rodolpho C; Alves, Vinicius M; Silva, Meryck F B; Muratov, Eugene; Fourches, Denis; Tropsha, Alexander; Andrade, Carolina H

    2014-01-01

    Several non-cardiovascular drugs have been withdrawn from the market due to their inhibition of hERG K+ channels that can potentially lead to severe heart arrhythmia and death. As hERG safety testing is a mandatory FDArequired procedure, there is a considerable interest for developing predictive computational tools to identify and filter out potential hERG blockers early in the drug discovery process. In this study, we aimed to generate predictive and well-characterized quantitative structure-activity relationship (QSAR) models for hERG blockage using the largest publicly available dataset of 11,958 compounds from the ChEMBL database. The models have been developed and validated according to OECD guidelines using four types of descriptors and four different machine-learning techniques. The classification accuracies discriminating blockers from non-blockers were as high as 0.83-0.93 on external set. Model interpretation revealed several SAR rules, which can guide structural optimization of some hERG blockers into non-blockers. We have also applied the generated models for screening the World Drug Index (WDI) database and identify putative hERG blockers and non-blockers among currently marketed drugs. The developed models can reliably identify blockers and non-blockers, which could be useful for the scientific community. A freely accessible web server has been developed allowing users to identify putative hERG blockers and non-blockers in chemical libraries of their interest (http://labmol.farmacia.ufg.br/predherg).

  16. Secondary Prevention Services for Clients Who Are Low Risk in Drug Court: A Conceptual Model

    Science.gov (United States)

    DeMatteo, David S.; Marlowe, Douglas B.; Festinger, David S.

    2006-01-01

    The drug court model assumes that most drug offenders are addicts, and that drug use fuels other criminal activity. As a result, drug court clients must satisfy an intensive regimen of treatment and supervisory obligations. However, research suggests that roughly one third of drug court clients do not have a clinically significant substance use…

  17. Metallomics for drug development: serum protein binding and analysis of an anticancer tris(8-quinolinolato)gallium(III) drug using inductively coupled plasma mass spectrometry.

    Science.gov (United States)

    Ossipov, Konstantin; Foteeva, Lidia S; Seregina, Irina F; Perevalov, Sergei A; Timerbaev, Andrei R; Bolshov, Mikhail A

    2013-06-27

    The application of an inductively coupled plasma mass spectrometry (ICP-MS) assay for quantifying in vitro binding of a gallium-based anticancer drug, tris(8-quinolinolato)gallium(III), to serum albumin and transferrin and in human serum is described. The distribution of the drug between the protein-rich and protein-free fractions was assessed via ICP-MS measurement of total gallium in ultrafiltrates. Comparative kinetic studies revealed that the drug exhibits a different reactivity toward individual proteins. While the maximum possible binding to albumin (~10%) occurs practically immediately, interaction with transferrin has a step-like character and the equilibrium state (with more than 50% binding) is reached for about 48 h. Drug transformation into the bound form in serum, also very fast, results in almost quantitative binding (~95%). The relative affinity of protein-drug binding was characterized in terms of the association constants ranging from 10(3) to 10(4)M(-1). In order to further promote clinical testing of the gallium drug, the ICP-MS method was applied for direct quantification of gallium in human serum spiked with the drug. The detection limit for gallium was found to be as low as 20 ng L(-1). The repeatability was better than 8% (as RSD) and the achieved recoveries were in the range 99-103%.

  18. Role of antibodies in developing drugs that target G-protein-coupled receptor dimers.

    Science.gov (United States)

    Hipser, Chris; Bushlin, Ittai; Gupta, Achla; Gomes, Ivone; Devi, Lakshmi A

    2010-01-01

    G-protein-coupled receptors are important molecular targets in drug discovery. These receptors play a pivotal role in physiological signaling pathways and are targeted by nearly 50% of currently available drugs. Mounting evidence suggests that G-protein-coupled receptors form dimers, and various studies have shown that dimerization is necessary for receptor maturation, signaling, and trafficking. However, the physiological implications of dimerization in vivo have not been well explored because detection of GPCR dimers in endogenous systems has been a challenging task. One exciting new approach to this challenge is the generation of antibodies against specific G-protein-coupled receptor dimers. Such antibodies could be used as tools for characterization of heteromer-specific function; as reagents for their purification, tissue localization, and regulation in vivo; and as probes for mapping their functional domains. In addition, such antibodies could serve as alternative ligands for G-protein-coupled receptor heteromers. Thus, heteromer-specific antibodies represent novel tools for the exploration and manipulation of G-protein-coupled receptor-dimer pharmacology.

  19. Drug interference in the Bradford and 2,2'-bicinchoninic acid protein assays.

    Science.gov (United States)

    Marshall, T; Williams, K M

    1991-11-01

    The interference of a range of drugs and related substances has been investigated in the Bradford Coomassie brilliant blue (CBB) protein dye-binding assay and the 2,2'-bicinchoninic acid (BCA) protein assays. Chlorpromazine was the only substance to interfere in the CBB assay but the interference was slight. In contrast, the BCA reagent interacted strongly with chlorpromazine, the penicillins, vitamin C, and paracetamol and the mode of interference varied with the test substance. The chlorpromazine produced turbidity and an atypical color. The penicillins show a slow but normal color response while vitamin C and paracetamol gave an immediate and intense response.

  20. Nanoporous membrane based on block copolymer thin film for protein drug delivery

    Science.gov (United States)

    Yang, Seung Yun; Yang, Jeong-A.; Kim, Eung-Sam; Jeon, Gumhye; Oh, Eun Ju; Choi, Kwan Yong; Hahn, Sei Kwang; Kim, Jin Kon

    2010-03-01

    We studied long term and controlled release of protein drugs by using nanoporous membranes with various pore sizes. Nanoporous membrane consists of the separation layer prepared by polystyrene-block-poly(methylmethacrylate) copolymer thin film and conventional microfiltration membrane as a support. We demonstrate a long-term constant in vitro release of bovine serum albumin (BSA)and human growth hormone ) (hGH) without their denaturation up to 2 months. A nearly constant serum concentration of hGH was maintained up to 3 weeks in SD rats. The long-term constant delivery based on this membrane for protein drugs within the therapeutic range can be highly appreciated for the patients with hormone- deficiency.

  1. A bacterial protein enhances the release and efficacy of liposomal cancer drugs.

    Science.gov (United States)

    Cheong, Ian; Huang, Xin; Bettegowda, Chetan; Diaz, Luis A; Kinzler, Kenneth W; Zhou, Shibin; Vogelstein, Bert

    2006-11-24

    Clostridium novyi-NT is an anaerobic bacterium that can infect hypoxic regions within experimental tumors. Because C. novyi-NT lyses red blood cells, we hypothesized that its membrane-disrupting properties could be exploited to enhance the release of liposome-encapsulated drugs within tumors. Here, we show that treatment of mice bearing large, established tumors with C. novyi-NT plus a single dose of liposomal doxorubicin often led to eradication of the tumors. The bacterial factor responsible for the enhanced drug release was identified as a previously unrecognized protein termed liposomase. This protein could potentially be incorporated into diverse experimental approaches for the specific delivery of chemotherapeutic agents to tumors.

  2. Expression of the Prion Protein Family Member Shadoo Causes Drug Hypersensitivity That Is Diminished by the Coexpression of the Wild Type Prion Protein.

    Science.gov (United States)

    Nyeste, Antal; Bencsura, Petra; Vida, István; Hegyi, Zoltán; Homolya, László; Fodor, Elfrieda; Welker, Ervin

    2016-02-26

    The prion protein (PrP) seems to exert both neuroprotective and neurotoxic activities. The toxic activities are associated with the C-terminal globular parts in the absence of the flexible N terminus, specifically the hydrophobic domain (HD) or the central region (CR). The wild type prion protein (PrP-WT), having an intact flexible part, exhibits neuroprotective qualities by virtue of diminishing many of the cytotoxic effects of these mutant prion proteins (PrPΔHD and PrPΔCR) when coexpressed. The prion protein family member Doppel, which possesses a three-dimensional fold similar to the C-terminal part of PrP, is also harmful to neuronal and other cells in various models, a phenotype that can also be eliminated by the coexpression of PrP-WT. In contrast, another prion protein family member, Shadoo (Sho), a natively disordered protein possessing structural features similar to the flexible N-terminal tail of PrP, exhibits PrP-WT-like protective properties. Here, we report that, contrary to expectations, Sho expression in SH-SY5Y or HEK293 cells induces the same toxic phenotype of drug hypersensitivity as PrPΔCR. This effect is exhibited in a dose-dependent manner and is also counteracted by the coexpression of PrP-WT. The opposing effects of Shadoo in different model systems revealed here may be explored to help discern the relationship of the various toxic activities of mutant PrPs with each other and the neurotoxic effects seen in neurodegenerative diseases, such as transmissible spongiform encephalopathy and Alzheimer disease.

  3. Power-Law Modeling of Cancer Cell Fates Driven by Signaling Data to Reveal Drug Effects

    Science.gov (United States)

    Zhang, Fan; Wu, Min; Kwoh, Chee Keong; Zheng, Jie

    2016-01-01

    Extracellular signals are captured and transmitted by signaling proteins inside a cell. An important type of cellular responses to the signals is the cell fate decision, e.g., apoptosis. However, the underlying mechanisms of cell fate regulation are still unclear, thus comprehensive and detailed kinetic models are not yet available. Alternatively, data-driven models are promising to bridge signaling data with the phenotypic measurements of cell fates. The traditional linear model for data-driven modeling of signaling pathways has its limitations because it assumes that the a cell fate is proportional to the activities of signaling proteins, which is unlikely in the complex biological systems. Therefore, we propose a power-law model to relate the activities of all the measured signaling proteins to the probabilities of cell fates. In our experiments, we compared our nonlinear power-law model with the linear model on three cancer datasets with phosphoproteomics and cell fate measurements, which demonstrated that the nonlinear model has superior performance on cell fates prediction. By in silico simulation of virtual protein knock-down, the proposed model is able to reveal drug effects which can complement traditional approaches such as binding affinity analysis. Moreover, our model is able to capture cell line specific information to distinguish one cell line from another in cell fate prediction. Our results show that the power-law data-driven model is able to perform better in cell fate prediction and provide more insights into the signaling pathways for cancer cell fates than the linear model. PMID:27764199

  4. Transport of diclofenac by breast cancer resistance protein (ABCG2) and stimulation of multidrug resistance protein 2 (ABCC2)-mediated drug transport by diclofenac and benzbromarone.

    Science.gov (United States)

    Lagas, Jurjen S; van der Kruijssen, Cornelia M M; van de Wetering, Koen; Beijnen, Jos H; Schinkel, Alfred H

    2009-01-01

    Diclofenac is an important analgesic and anti-inflammatory drug, widely used for treatment of postoperative pain, rheumatoid arthritis, and chronic pain associated with cancer. Consequently, diclofenac is often used in combination regimens and undesirable drug-drug interactions may occur. Because many drug-drug interactions may occur at the level of drug transporting proteins, we studied interactions of diclofenac with apical ATP-binding cassette (ABC) multidrug efflux transporters. Using Madin-Darby canine kidney (MDCK)-II cells transfected with human P-glycoprotein (P-gp; MDR1/ABCB1), multidrug resistance protein 2 (MRP2/ABCC2), and breast cancer resistance protein (BCRP/ABCG2) and murine Bcrp1, we found that diclofenac was efficiently transported by murine Bcrp1 and moderately by human BCRP but not by P-gp or MRP2. Furthermore, in Sf9-BCRP membrane vesicles diclofenac inhibited transport of methotrexate in a concentration-dependent manner. We next used MDCK-II-MRP2 cells to study interactions of diclofenac with MRP2-mediated drug transport. Diclofenac stimulated paclitaxel, docetaxel, and saquinavir transport at only 50 microM. We further found that the uricosuric drug benzbromarone stimulated MRP2 at an even lower concentration, having maximal stimulatory activity at only 2 microM. Diclofenac and benzbromarone stimulated MRP2-mediated transport of amphipathic lipophilic drugs at 10- and 250-fold lower concentrations, respectively, than reported for other MRP2 stimulators. Because these concentrations are readily achieved in patients, adverse drug-drug interactions may occur, for example, during cancer therapy, in which drug concentrations are often critical and stimulation of elimination via MRP2 may result in suboptimal chemotherapeutic drug concentrations. Moreover, stimulation of MRP2 activity in tumors may lead to increased efflux of chemotherapeutic drugs and thereby drug resistance.

  5. Impulsivity in Animal Models for Drug Abuse Disorders

    OpenAIRE

    Jentsch, J. David

    2008-01-01

    Different conceptual frameworks have been generated to explain substance abuse; of relevance to this article, dysfunction of impulse control systems that are required for avoiding or stopping drug-seeking and –taking may play a key role in addiction. This review summarizes work in animal models that explains the pervasive association between impulse control and substance abuse. It further underscores the concept that impulse control may be a critical target for pharmacological intervention in...

  6. Protein encapsulated magnetic carriers for micro/nanoscale drug delivery systems.

    Energy Technology Data Exchange (ETDEWEB)

    Xie, Y.; Kaminski, M. D.; Mertz, C. J.; Finck, M. R.; Guy, S. G.; Chen, H.; Rosengart, A. J.; Chemical Engineering; Univ. of Chicago, Pritzker School of Medicine

    2005-01-01

    Novel methods for drug delivery may be based on nanotechnology using non-invasive magnetic guidance of drug loaded magnetic carriers to the targeted site and thereafter released by external ultrasound energy. The key building block of this system is to successfully synthesize biodegradable, magnetic drug carriers. Magnetic carriers using poly(D,L-lactide-co-glycolide) (PLGA) or poly(lactic acid)-poly(ethylene glycol) (PLA-PEG) as matrix materials were loaded with bovine serum albumin (BSA) by a double-emulsion technique. BSA-loaded magnetic microspheres were characterized for size, morphology, surface charge, and magnetization. The BSA encapsulation efficiency was determined by recovering albumin from the microspheres using dimethyl sulfoxide and 0.05N NaOH/0.5% SDS then quantifying with the Micro-BCA protein assay. BSA release profiles were also determined by the Micro-BCA protein assay. The microspheres had drug encapsulation efficiencies up to 90% depending on synthesis parameters. Particles were spherical with a smooth or porous surface having a size range less than 5 {mu}m. The surface charge (expressed as zeta potential) was near neutral, optimal for prolonged intravascular survival. The magnetization of these BSA loaded magnetic carriers was 2 to 6 emu/g, depending on the specific magnetic materials used during synthesis.

  7. Bioengineered Vaults: Self-Assembling Protein Shell–Lipophilic Core Nanoparticles for Drug Delivery

    Science.gov (United States)

    2015-01-01

    We report a novel approach to a new class of bioengineered, monodispersed, self-assembling vault nanoparticles consisting of a protein shell exterior with a lipophilic core interior designed for drug and probe delivery. Recombinant vaults were engineered to contain a small amphipathic α-helix derived from the nonstructural protein 5A of hepatitis C virus, thereby creating within the vault lumen a lipophilic microenvironment into which lipophilic compounds could be reversibly encapsulated. Multiple types of electron microscopy showed that attachment of this peptide resulted in larger than expected additional mass internalized within the vault lumen attributable to incorporation of host lipid membrane constituents spanning the vault waist (>35 nm). These bioengineered lipophilic vaults reversibly associate with a sample set of therapeutic compounds, including all-trans retinoic acid, amphotericin B, and bryostatin 1, incorporating hundreds to thousands of drug molecules per vault nanoparticle. Bryostatin 1 is of particular therapeutic interest because of its ability to potently induce expression of latent HIV, thus representing a preclinical lead in efforts to eradicate HIV/AIDS. Vaults loaded with bryostatin 1 released free drug, resulting in activation of HIV from provirus latency in vitro and induction of CD69 biomarker expression following intravenous injection into mice. The ability to preferentially and reversibly encapsulate lipophilic compounds into these novel bioengineered vault nanoparticles greatly advances their potential use as drug delivery systems. PMID:25061969

  8. Modelling heating effects in cryocooled protein crystals

    CERN Document Server

    Nicholson, J; Fayz, K; Fell, B; Garman, E

    2001-01-01

    With the application of intense X-ray beams from third generation synchrotron sources, damage to cryocooled macromolecular crystals is being observed more commonly . In order to fully utilize synchrotron facilities now available for studying biological crystals, it is essential to understand the processes involved in radiation damage and beam heating so that, if possible, action can be taken to slow the rate of damage. Finite Element Analysis (FEA) has been applied to model the heating effects of X-rays on cryocooled protein crystals, and to compare the relative cooling efficiencies of nitrogen and helium.

  9. Bacterial eukaryotic type serine-threonine protein kinases: from structural biology to targeted anti-infective drug design.

    Science.gov (United States)

    Danilenko, Valery N; Osolodkin, Dmitry I; Lakatosh, Sergey A; Preobrazhenskaya, Maria N; Shtil, Alexander A

    2011-01-01

    Signaling through protein kinases is an evolutionary conserved, widespread language of biological regulation. The eukaryotic type serine-threonine protein kinases (STPKs) found in normal human microbiote and in pathogenic bacteria play a key role in regulation of microbial survival, virulence and pathogenicity. Therefore, down-regulation of bacterial STPKs emerges as an attractive approach to cure infections. In this review we focused on actinobacterial STPKs to demonstrate that these enzymes can be used for crystal structure studies, modeling of 3D structure, construction of test systems and design of novel chemical libraries of low molecule as weight inhibitors. In particular, the prototypic pharmacological antagonists of Mycobacterium tuberculosis STPKs are perspective for development of a novel generation of drugs to combat the socially important disease. These inhibitors may modulate both actinobacterial and host STPKs and trigger programmed death of pathogenic bacteria.

  10. Energetics investigation on encapsulation of protein/peptide drugs in carbon nanotubes.

    Science.gov (United States)

    Chen, Qu; Wang, Qi; Liu, Ying-Chun; Wu, Tao; Kang, Yu; Moore, Joshua D; Gubbins, Keith E

    2009-07-07

    This work focuses on the dynamic properties and energetics of the protein/peptide drug during its transport through carbon nanotubes (CNTs). A systematic study was performed on the interaction between the peptide and the CNTs. In the molecular dynamics (MD) simulations, the protein/peptide molecule Zadaxin is observed to be encapsulated inside the nanotube after its spontaneous insertion and oscillates around the center of the tube, where the van der Waals interaction energy is observed to be a minimum. Furthermore, it is found by performing steered MD simulations that the pulling force applied to the peptide reaches a maximum value, which demonstrates the ability of the CNTs to trap protein/peptide drugs. Such effects, attributed to van der Waals interactions, can be influenced by varying the lengths and diameters of the CNTs. Longer nanotubes provide a broader area to trap the peptide, while smaller nanotubes are able to encapsulate the peptide with a deeper interaction energy well. This investigation provides insights into nanoscale pharmaceutical drug delivery devices.

  11. Challenges, applications, and recent advances of protein-ligand docking in structure-based drug design.

    Science.gov (United States)

    Grinter, Sam Z; Zou, Xiaoqin

    2014-07-11

    The docking methods used in structure-based virtual database screening offer the ability to quickly and cheaply estimate the affinity and binding mode of a ligand for the protein receptor of interest, such as a drug target. These methods can be used to enrich a database of compounds, so that more compounds that are subsequently experimentally tested are found to be pharmaceutically interesting. In addition, like all virtual screening methods used for drug design, structure-based virtual screening can focus on curated libraries of synthesizable compounds, helping to reduce the expense of subsequent experimental verification. In this review, we introduce the protein-ligand docking methods used for structure-based drug design and other biological applications. We discuss the fundamental challenges facing these methods and some of the current methodological topics of interest. We also discuss the main approaches for applying protein-ligand docking methods. We end with a discussion of the challenging aspects of evaluating or benchmarking the accuracy of docking methods for their improvement, and discuss future directions.

  12. Challenges, Applications, and Recent Advances of Protein-Ligand Docking in Structure-Based Drug Design

    Directory of Open Access Journals (Sweden)

    Sam Z. Grinter

    2014-07-01

    Full Text Available The docking methods used in structure-based virtual database screening offer the ability to quickly and cheaply estimate the affinity and binding mode of a ligand for the protein receptor of interest, such as a drug target. These methods can be used to enrich a database of compounds, so that more compounds that are subsequently experimentally tested are found to be pharmaceutically interesting. In addition, like all virtual screening methods used for drug design, structure-based virtual screening can focus on curated libraries of synthesizable compounds, helping to reduce the expense of subsequent experimental verification. In this review, we introduce the protein-ligand docking methods used for structure-based drug design and other biological applications. We discuss the fundamental challenges facing these methods and some of the current methodological topics of interest. We also discuss the main approaches for applying protein-ligand docking methods. We end with a discussion of the challenging aspects of evaluating or benchmarking the accuracy of docking methods for their improvement, and discuss future directions.

  13. Mouse models for pre-clinical drug testing in leukemia.

    Science.gov (United States)

    Bhatia, Sanil; Daschkey, Svenja; Lang, Franziska; Borkhardt, Arndt; Hauer, Julia

    2016-11-01

    The development of novel drugs which specifically target leukemic cells, with the overall aim to increase complete remission and to reduce toxicity and morbidity, is the most important prerequisite for modern leukemia treatment. In this regard, the current transition rate of potential novel drugs from bench to bedside is remarkably low. Although many novel drugs show promising data in vitro and in vivo, testing of these medications in clinical phase I trials is often sobering with intolerable toxic side effects leading to failure in FDA approval. Areas covered: In this review, the authors discuss the development of murine model generation in the context of targeted therapy development for the treatment of childhood leukemia, aiming to decrease the attrition rate of progressively complex targeted therapies ranging from small molecules to cell therapy. As more complex therapeutic approaches develop, more complex murine models are needed, to recapitulate closely the human phenotype. Expert opinion: Combining xenograft models for efficacy testing and GEMMs for toxicity testing will be a global approach for pre-clinical testing of complex therapeutics and will contribute to the clinical approval of novel compounds. Finally, this approach is likely to increase clinical approval of novel compounds.

  14. The potential of protein-nanomaterial interaction for advanced drug delivery.

    Science.gov (United States)

    Peng, Qiang; Mu, Huiling

    2016-03-10

    Nanomaterials, like nanoparticles, micelles, nano-sheets, nanotubes and quantum dots, have great potentials in biomedical fields. However, their delivery is highly limited by the formation of protein corona upon interaction with endogenous proteins. This new identity, instead of nanomaterial itself, would be the real substance the organs and cells firstly encounter. Consequently, the behavior of nanomaterials in vivo is uncontrollable and some undesired effects may occur, like rapid clearance from blood stream; risk of capillary blockage; loss of targeting capacity; and potential toxicity. Therefore, protein-nanomaterial interaction is a great challenge for nanomaterial systems and should be inhibited. However, this interaction can also be used to functionalize nanomaterials by forming a selected protein corona. Unlike other decoration using exogenous molecules, nanomaterials functionalized by selected protein corona using endogenous proteins would have greater promise for clinical use. In this review, we aim to provide a comprehensive understanding of protein-nanomaterial interaction. Importantly, a discussion about how to use such interaction is launched and some possible applications of such interaction for advanced drug delivery are presented. Copyright © 2016 Elsevier B.V. All rights reserved.

  15. Site-selective protein-modification chemistry for basic biology and drug development

    Science.gov (United States)

    Krall, Nikolaus; da Cruz, Filipa P.; Boutureira, Omar; Bernardes, Gonçalo J. L.

    2016-02-01

    Nature has produced intricate machinery to covalently diversify the structure of proteins after their synthesis in the ribosome. In an attempt to mimic nature, chemists have developed a large set of reactions that enable post-expression modification of proteins at pre-determined sites. These reactions are now used to selectively install particular modifications on proteins for many biological and therapeutic applications. For example, they provide an opportunity to install post-translational modifications on proteins to determine their exact biological roles. Labelling of proteins in live cells with fluorescent dyes allows protein uptake and intracellular trafficking to be tracked and also enables physiological parameters to be measured optically. Through the conjugation of potent cytotoxicants to antibodies, novel anti-cancer drugs with improved efficacy and reduced side effects may be obtained. In this Perspective, we highlight the most exciting current and future applications of chemical site-selective protein modification and consider which hurdles still need to be overcome for more widespread use.

  16. LIBP-Pred: web server for lipid binding proteins using structural network parameters; PDB mining of human cancer biomarkers and drug targets in parasites and bacteria.

    Science.gov (United States)

    González-Díaz, Humberto; Munteanu, Cristian R; Postelnicu, Lucian; Prado-Prado, Francisco; Gestal, Marcos; Pazos, Alejandro

    2012-03-01

    Lipid-Binding Proteins (LIBPs) or Fatty Acid-Binding Proteins (FABPs) play an important role in many diseases such as different types of cancer, kidney injury, atherosclerosis, diabetes, intestinal ischemia and parasitic infections. Thus, the computational methods that can predict LIBPs based on 3D structure parameters became a goal of major importance for drug-target discovery, vaccine design and biomarker selection. In addition, the Protein Data Bank (PDB) contains 3000+ protein 3D structures with unknown function. This list, as well as new experimental outcomes in proteomics research, is a very interesting source to discover relevant proteins, including LIBPs. However, to the best of our knowledge, there are no general models to predict new LIBPs based on 3D structures. We developed new Quantitative Structure-Activity Relationship (QSAR) models based on 3D electrostatic parameters of 1801 different proteins, including 801 LIBPs. We calculated these electrostatic parameters with the MARCH-INSIDE software and they correspond to the entire protein or to specific protein regions named core, inner, middle, and surface. We used these parameters as inputs to develop a simple Linear Discriminant Analysis (LDA) classifier to discriminate 3D structure of LIBPs from other proteins. We implemented this predictor in the web server named LIBP-Pred, freely available at , along with other important web servers of the Bio-AIMS portal. The users can carry out an automatic retrieval of protein structures from PDB or upload their custom protein structural models from their disk created with LOMETS server. We demonstrated the PDB mining option performing a predictive study of 2000+ proteins with unknown function. Interesting results regarding the discovery of new Cancer Biomarkers in humans or drug targets in parasites have been discussed here in this sense.

  17. Five-Factor Model personality profiles of drug users

    Directory of Open Access Journals (Sweden)

    Crum Rosa M

    2008-04-01

    Full Text Available Abstract Background Personality traits are considered risk factors for drug use, and, in turn, the psychoactive substances impact individuals' traits. Furthermore, there is increasing interest in developing treatment approaches that match an individual's personality profile. To advance our knowledge of the role of individual differences in drug use, the present study compares the personality profile of tobacco, marijuana, cocaine, and heroin users and non-users using the wide spectrum Five-Factor Model (FFM of personality in a diverse community sample. Method Participants (N = 1,102; mean age = 57 were part of the Epidemiologic Catchment Area (ECA program in Baltimore, MD, USA. The sample was drawn from a community with a wide range of socio-economic conditions. Personality traits were assessed with the Revised NEO Personality Inventory (NEO-PI-R, and psychoactive substance use was assessed with systematic interview. Results Compared to never smokers, current cigarette smokers score lower on Conscientiousness and higher on Neuroticism. Similar, but more extreme, is the profile of cocaine/heroin users, which score very high on Neuroticism, especially Vulnerability, and very low on Conscientiousness, particularly Competence, Achievement-Striving, and Deliberation. By contrast, marijuana users score high on Openness to Experience, average on Neuroticism, but low on Agreeableness and Conscientiousness. Conclusion In addition to confirming high levels of negative affect and impulsive traits, this study highlights the links between drug use and low Conscientiousness. These links provide insight into the etiology of drug use and have implications for public health interventions.

  18. Minimalist models for proteins: a comparative analysis.

    Science.gov (United States)

    Tozzini, Valentina

    2010-08-01

    The last decade has witnessed a renewed interest in the coarse-grained (CG) models for biopolymers, also stimulated by the needs of modern molecular biology, dealing with nano- to micro-sized bio-molecular systems and larger than microsecond timescale. This combination of size and timescale is, in fact, hard to access by atomic-based simulations. Coarse graining the system is a route to be followed to overcome these limits, but the ways of practically implementing it are many and different, making the landscape of CG models very vast and complex. In this paper, the CG models are reviewed and their features, applications and performances compared. This analysis, restricted to proteins, focuses on the minimalist models, namely those reducing at minimum the number of degrees of freedom without losing the possibility of explicitly describing the secondary structures. This class includes models using a single or a few interacting centers (beads) for each amino acid. From this analysis several issues emerge. The difficulty in building these models resides in the need for combining transferability/predictive power with the capability of accurately reproducing the structures. It is shown that these aspects could be optimized by accurately choosing the force field (FF) terms and functional forms, and combining different parameterization procedures. In addition, in spite of the variety of the minimalist models, regularities can be found in the parameters values and in FF terms. These are outlined and schematically presented with the aid of a generic phase diagram of the polypeptide in the parameter space and, hopefully, could serve as guidelines for the development of minimalist models incorporating the maximum possible level of predictive power and structural accuracy.

  19. Layer-by-Layer Assembled Milk Protein Coated Magnetic Nanoparticle Enabled Oral Drug Delivery with High Stability in Stomach and Enzyme-Responsive Release in Small Intestine

    Science.gov (United States)

    Huang, Jing; Shu, Qing; Wang, Liya; Wu, Hui; Wang, Andrew Y.; Mao, Hui

    2014-01-01

    We report a novel drug delivery system composed of layer-by-layer (LBL) milk protein casein (CN) coated iron oxide nanoparticles. Doxorubicin (DOX) and indocyanine green (ICG) were selected as model drug molecules, which were incorporated into the inner polymeric layer, and subsequently coated with casein. The resulting casein coated iron oxide nanoparticles (CN-DOX/ICG-IO) were stable in the acidic gastric condition with the presence of gastric protease. On the other hand, the loaded drugs were released when the casein outer layer was gradually degraded by the intestinal protease in the simulated intestine condition. Such unique properties enable maintenance of the bioactivity of the drugs and thus enhance the drug delivery efficiency. Ex vivo experiments showed that the LBL CN-DOX-IO improved the translocation of DOX across microvilli and its absorption in the small intestine sacs. In vivo imaging of mice that were orally administered with these LBL CN-ICG-IO nanostructures further confirmed that the reported drug delivery vehicles could pass the stomach without significant degradation, and then accumulated in the small intestine. In addition, the magnetic iron oxide nanoparticle core offered an MRI contrast enhancing capability for in vivo imaging guided drug delivery. Therefore, the reported LBL CN-DOX/ICG-IO is a promising oral drug delivery nanoplatform, especially for drugs that are poorly soluble in water or degradable in the gastric environment. PMID:25477177

  20. Hidden markov model for the prediction of transmembrane proteins using MATLAB.

    Science.gov (United States)

    Chaturvedi, Navaneet; Shanker, Sudhanshu; Singh, Vinay Kumar; Sinha, Dhiraj; Pandey, Paras Nath

    2011-01-01

    Since membranous proteins play a key role in drug targeting therefore transmembrane proteins prediction is active and challenging area of biological sciences. Location based prediction of transmembrane proteins are significant for functional annotation of protein sequences. Hidden markov model based method was widely applied for transmembrane topology prediction. Here we have presented a revised and a better understanding model than an existing one for transmembrane protein prediction. Scripting on MATLAB was built and compiled for parameter estimation of model and applied this model on amino acid sequence to know the transmembrane and its adjacent locations. Estimated model of transmembrane topology was based on TMHMM model architecture. Only 7 super states are defined in the given dataset, which were converted to 96 states on the basis of their length in sequence. Accuracy of the prediction of model was observed about 74 %, is a good enough in the area of transmembrane topology prediction. Therefore we have concluded the hidden markov model plays crucial role in transmembrane helices prediction on MATLAB platform and it could also be useful for drug discovery strategy. The database is available for free at bioinfonavneet@gmail.comvinaysingh@bhu.ac.in.

  1. Modeling the transport of drugs eluted from stents: physical phenomena driving drug distribution in the arterial wall.

    Science.gov (United States)

    Bozsak, Franz; Chomaz, Jean-Marc; Barakat, Abdul I

    2014-04-01

    Despite recent data that suggest that the overall performance of drug-eluting stents (DES) is superior to that of bare-metal stents, the long-term safety and efficacy of DES remain controversial. The risk of late stent thrombosis associated with the use of DES has also motivated the development of a new and promising treatment option in recent years, namely drug-coated balloons (DCB). Contrary to DES where the drug of choice is typically sirolimus and its derivatives, DCB use paclitaxel since the use of sirolimus does not appear to lead to satisfactory results. Since both sirolimus and paclitaxel are highly lipophilic drugs with similar transport properties, the reason for the success of paclitaxel but not sirolimus in DCB remains unclear. Computational models of the transport of drugs eluted from DES or DCB within the arterial wall promise to enhance our understanding of the performance of these devices. The present study develops a computational model of the transport of the two drugs paclitaxel and sirolimus eluted from DES in the arterial wall. The model takes into account the multilayered structure of the arterial wall and incorporates a reversible binding model to describe drug interactions with the constituents of the arterial wall. The present results demonstrate that the transport of paclitaxel in the arterial wall is dominated by convection while the transport of sirolimus is dominated by the binding process. These marked differences suggest that drug release kinetics of DES should be tailored to the type of drug used.

  2. Mathematical modeling of coupled drug and drug-encapsulated nanoparticle transport in patient-specific coronary artery walls

    KAUST Repository

    Hossain, Shaolie S.

    2011-08-20

    The majority of heart attacks occur when there is a sudden rupture of atherosclerotic plaque, exposing prothrombotic emboli to coronary blood flow, forming clots that can cause blockages of the arterial lumen. Diseased arteries can be treated with drugs delivered locally to vulnerable plaques. The objective of this work was to develop a computational tool-set to support the design and analysis of a catheter-based nanoparticulate drug delivery system to treat vulnerable plaques and diffuse atherosclerosis. A threedimensional mathematical model of coupled mass transport of drug and drug-encapsulated nanoparticles was developed and solved numerically utilizing isogeometric finite element analysis. Simulations were run on a patient-specific multilayered coronary artery wall segment with a vulnerable plaque and the effect of artery and plaque inhomogeneity was analyzed. The method captured trends observed in local drug delivery and demonstrated potential for optimizing drug design parameters, including delivery location, nanoparticle surface properties, and drug release rate. © Springer-Verlag 2011.

  3. Mathematical modeling of coupled drug and drug-encapsulated nanoparticle transport in patient-specific coronary artery walls

    Science.gov (United States)

    Hossain, Shaolie S.; Hossainy, Syed F. A.; Bazilevs, Yuri; Calo, Victor M.; Hughes, Thomas J. R.

    2012-02-01

    The majority of heart attacks occur when there is a sudden rupture of atherosclerotic plaque, exposing prothrombotic emboli to coronary blood flow, forming clots that can cause blockages of the arterial lumen. Diseased arteries can be treated with drugs delivered locally to vulnerable plaques. The objective of this work was to develop a computational tool-set to support the design and analysis of a catheter-based nanoparticulate drug delivery system to treat vulnerable plaques and diffuse atherosclerosis. A three-dimensional mathematical model of coupled mass transport of drug and drug-encapsulated nanoparticles was developed and solved numerically utilizing isogeometric finite element analysis. Simulations were run on a patient-specific multilayered coronary artery wall segment with a vulnerable plaque and the effect of artery and plaque inhomogeneity was analyzed. The method captured trends observed in local drug delivery and demonstrated potential for optimizing drug design parameters, including delivery location, nanoparticle surface properties, and drug release rate.

  4. Xenograft model for therapeutic drug testing in recurrent respiratory papillomatosis.

    Science.gov (United States)

    Ahn, Julie; Bishop, Justin A; Akpeng, Belinda; Pai, Sara I; Best, Simon R A

    2015-02-01

    Identifying effective treatment for papillomatosis is limited by a lack of animal models, and there is currently no preclinical model for testing potential therapeutic agents. We hypothesized that xenografting of papilloma may facilitate in vivo drug testing to identify novel treatment options. A biopsy of fresh tracheal papilloma was xenografted into a NOD-scid-IL2Rgamma(null) (NSG) mouse. The xenograft began growing after 5 weeks and was serially passaged over multiple generations. Each generation showed a consistent log-growth pattern, and in all xenografts, the presence of the human papillomavirus (HPV) genome was confirmed by polymerase chain reaction (PCR). Histopathologic analysis demonstrated that the squamous architecture of the original papilloma was maintained in each generation. In vivo drug testing with bevacizumab (5 mg/kg i.p. twice weekly for 3 weeks) showed a dramatic therapeutic response compared to saline control. We report here the first successful case of serial xenografting of a tracheal papilloma in vivo with a therapeutic response observed with drug testing. In severely immunocompromised mice, the HPV genome and squamous differentiation of the papilloma can be maintained for multiple generations. This is a feasible approach to identify therapeutic agents in the treatment of recurrent respiratory papillomatosis. © The Author(s) 2014.

  5. Pharmacokinetic properties and in silico ADME modeling in drug discovery.

    Science.gov (United States)

    Honório, Kathia M; Moda, Tiago L; Andricopulo, Adriano D

    2013-03-01

    The discovery and development of a new drug are time-consuming, difficult and expensive. This complex process has evolved from classical methods into an integration of modern technologies and innovative strategies addressed to the design of new chemical entities to treat a variety of diseases. The development of new drug candidates is often limited by initial compounds lacking reasonable chemical and biological properties for further lead optimization. Huge libraries of compounds are frequently selected for biological screening using a variety of techniques and standard models to assess potency, affinity and selectivity. In this context, it is very important to study the pharmacokinetic profile of the compounds under investigation. Recent advances have been made in the collection of data and the development of models to assess and predict pharmacokinetic properties (ADME--absorption, distribution, metabolism and excretion) of bioactive compounds in the early stages of drug discovery projects. This paper provides a brief perspective on the evolution of in silico ADME tools, addressing challenges, limitations, and opportunities in medicinal chemistry.

  6. Highly stable, protein capped gold nanoparticles as effective drug delivery vehicles for amino-glycosidic antibiotics

    Energy Technology Data Exchange (ETDEWEB)

    Rastogi, Lori; Kora, Aruna Jyothi; Arunachalam, J., E-mail: aruncccm@gmail.com

    2012-08-01

    A method for the production of highly stable gold nanoparticles (Au NP) was optimized using sodium borohydride as reducing agent and bovine serum albumin as capping agent. The synthesized nanoparticles were characterized using UV-visible spectroscopy, transmission electron microscopy, X-ray diffraction (XRD) and dynamic light scattering techniques. The formation of gold nanoparticles was confirmed from the appearance of pink colour and an absorption maximum at 532 nm. These protein capped nanoparticles exhibited excellent stability towards pH modification and electrolyte addition. The produced nanoparticles were found to be spherical in shape, nearly monodispersed and with an average particle size of 7.8 {+-} 1.7 nm. Crystalline nature of the nanoparticles in face centered cubic structure is confirmed from the selected-area electron diffraction and XRD patterns. The nanoparticles were functionalized with various amino-glycosidic antibiotics for utilizing them as drug delivery vehicles. Using Fourier transform infrared spectroscopy, the possible functional groups of antibiotics bound to the nanoparticle surface have been examined. These drug loaded nanoparticle solutions were tested for their antibacterial activity against Gram-negative and Gram-positive bacterial strains, by well diffusion assay. The antibiotic conjugated Au NP exhibited enhanced antibacterial activity, compared to pure antibiotic at the same concentration. Being protein capped and highly stable, these gold nanoparticles can act as effective carriers for drugs and might have considerable applications in the field of infection prevention and therapeutics. - Highlights: Black-Right-Pointing-Pointer Method for NaBH{sub 4} reduced and BSA capped gold nanoparticle was standardized. Black-Right-Pointing-Pointer Nanoparticles were spherical and nearly monodispersed with a size of 7.8 nm. Black-Right-Pointing-Pointer Nanoparticles are extremely stable towards pH modification and electrolyte addition. Black

  7. Mining protein kinases regulation using graphical models.

    Science.gov (United States)

    Chen, Qingfeng; Chen, Yi-Ping Phoebe

    2011-03-01

    Abnormal kinase activity is a frequent cause of diseases, which makes kinases a promising pharmacological target. Thus, it is critical to identify the characteristics of protein kinases regulation by studying the activation and inhibition of kinase subunits in response to varied stimuli. Bayesian network (BN) is a formalism for probabilistic reasoning that has been widely used for learning dependency models. However, for high-dimensional discrete random vectors the set of plausible models becomes large and a full comparison of all the posterior probabilities related to the competing models becomes infeasible. A solution to this problem is based on the Markov Chain Monte Carlo (MCMC) method. This paper proposes a BN-based framework to discover the dependency correlations of kinase regulation. Our approach is to apply the MCMC method to generate a sequence of samples from a probability distribution, by which to approximate the distribution. The frequent connections (edges) are identified from the obtained sampling graphical models. Our results point to a number of novel candidate regulation patterns that are interesting in biology and include inferred associations that were unknown.

  8. Ligand- and drug-binding studies of membrane proteins revealed through circular dichroism spectroscopy.

    Science.gov (United States)

    Siligardi, Giuliano; Hussain, Rohanah; Patching, Simon G; Phillips-Jones, Mary K

    2014-01-01

    A great number of membrane proteins have proven difficult to crystallise for use in X-ray crystallographic structural determination or too complex for NMR structural studies. Circular dichroism (CD) is a fast and relatively easy spectroscopic technique to study protein conformational behaviour. In this review examples of the applications of CD and synchrotron radiation CD (SRCD) to membrane protein ligand binding interaction studies are discussed. The availability of SRCD has been an important advancement in recent progress, most particularly because it can be used to extend the spectral region in the far-UV region (important for increasing the accuracy of secondary structure estimations) and for working with membrane proteins available in only small quantities for which SRCD has facilitated molecular recognition studies. Such studies have been accomplished by probing in the near-UV region the local tertiary structure of aromatic amino acid residues upon addition of chiral or non-chiral ligands using long pathlength cells of small volume capacity. In particular, this review describes the most recent use of the technique in the following areas: to obtain quantitative data on ligand binding (exemplified by the FsrC membrane sensor kinase receptor); to distinguish between functionally similar drugs that exhibit different mechanisms of action towards membrane proteins (exemplified by secretory phospholipase A2); and to identify suitable detergent conditions to observe membrane protein-ligand interactions using stabilised proteins (exemplified by the antiseptic transporter SugE). Finally, the importance of characterising in solution the conformational behaviour and ligand binding properties of proteins in both far- and near-UV regions is discussed. This article is part of a Special Issue entitled: Structural and biophysical characterisation of membrane protein-ligand binding. © 2013.

  9. Applications and limitations of in silico models in drug discovery.

    Science.gov (United States)

    Sacan, Ahmet; Ekins, Sean; Kortagere, Sandhya

    2012-01-01

    Drug discovery in the late twentieth and early twenty-first century has witnessed a myriad of changes that were adopted to predict whether a compound is likely to be successful, or conversely enable identification of molecules with liabilities as early as possible. These changes include integration of in silico strategies for lead design and optimization that perform complementary roles to that of the traditional in vitro and in vivo approaches. The in silico models are facilitated by the availability of large datasets associated with high-throughput screening, bioinformatics algorithms to mine and annotate the data from a target perspective, and chemoinformatics methods to integrate chemistry methods into lead design process. This chapter highlights the applications of some of these methods and their limitations. We hope this serves as an introduction to in silico drug discovery.

  10. Bacterial mimetics of endocrine secretory granules as immobilized in vivo depots for functional protein drugs

    Science.gov (United States)

    Céspedes, María Virtudes; Fernández, Yolanda; Unzueta, Ugutz; Mendoza, Rosa; Seras-Franzoso, Joaquin; Sánchez-Chardi, Alejando; Álamo, Patricia; Toledo-Rubio, Verónica; Ferrer-Miralles, Neus; Vázquez, Esther; Schwartz, Simó; Abasolo, Ibane; Corchero, José Luis; Mangues, Ramon; Villaverde, Antonio

    2016-01-01

    In the human endocrine system many protein hormones including urotensin, glucagon, obestatin, bombesin and secretin, among others, are supplied from amyloidal secretory granules. These granules form part of the so called functional amyloids, which within the whole aggregome appear to be more abundant than formerly believed. Bacterial inclusion bodies (IBs) are non-toxic, nanostructured functional amyloids whose biological fabrication can be tailored to render materials with defined biophysical properties. Since under physiological conditions they steadily release their building block protein in a soluble and functional form, IBs are considered as mimetics of endocrine secretory granules. We have explored here if the in vivo implantation of functional IBs in a given tissue would represent a stable local source of functional protein. Upon intratumoral injection of bacterial IBs formed by a potent protein ligand of CXCR4 we have observed high stability and prevalence of the material in absence of toxicity, accompanied by apoptosis of CXCR4+ cells and tumor ablation. Then, the local immobilization of bacterial amyloids formed by therapeutic proteins in tumors or other tissues might represent a promising strategy for a sustained local delivery of protein drugs by mimicking the functional amyloidal architecture of the mammals’ endocrine system. PMID:27775083

  11. Bacterial mimetics of endocrine secretory granules as immobilized in vivo depots for functional protein drugs.

    Science.gov (United States)

    Céspedes, María Virtudes; Fernández, Yolanda; Unzueta, Ugutz; Mendoza, Rosa; Seras-Franzoso, Joaquin; Sánchez-Chardi, Alejando; Álamo, Patricia; Toledo-Rubio, Verónica; Ferrer-Miralles, Neus; Vázquez, Esther; Schwartz, Simó; Abasolo, Ibane; Corchero, José Luis; Mangues, Ramon; Villaverde, Antonio

    2016-10-24

    In the human endocrine system many protein hormones including urotensin, glucagon, obestatin, bombesin and secretin, among others, are supplied from amyloidal secretory granules. These granules form part of the so called functional amyloids, which within the whole aggregome appear to be more abundant than formerly believed. Bacterial inclusion bodies (IBs) are non-toxic, nanostructured functional amyloids whose biological fabrication can be tailored to render materials with defined biophysical properties. Since under physiological conditions they steadily release their building block protein in a soluble and functional form, IBs are considered as mimetics of endocrine secretory granules. We have explored here if the in vivo implantation of functional IBs in a given tissue would represent a stable local source of functional protein. Upon intratumoral injection of bacterial IBs formed by a potent protein ligand of CXCR4 we have observed high stability and prevalence of the material in absence of toxicity, accompanied by apoptosis of CXCR4(+) cells and tumor ablation. Then, the local immobilization of bacterial amyloids formed by therapeutic proteins in tumors or other tissues might represent a promising strategy for a sustained local delivery of protein drugs by mimicking the functional amyloidal architecture of the mammals' endocrine system.

  12. Evolution and physics in comparative protein structure modeling.

    Science.gov (United States)

    Fiser, András; Feig, Michael; Brooks, Charles L; Sali, Andrej

    2002-06-01

    From a physical perspective, the native structure of a protein is a consequence of physical forces acting on the protein and solvent atoms during the folding process. From a biological perspective, the native structure of proteins is a result of evolution over millions of years. Correspondingly, there are two types of protein structure prediction methods, de novo prediction and comparative modeling. We review comparative protein structure modeling and discuss the incorporation of physical considerations into the modeling process. A good starting point for achieving this aim is provided by comparative modeling by satisfaction of spatial restraints. Incorporation of physical considerations is illustrated by an inclusion of solvation effects into the modeling of loops.

  13. Drug discovery opportunities and challenges at G protein coupled receptors for long chain free fatty acids

    Directory of Open Access Journals (Sweden)

    Nicholas D Holliday

    2012-01-01

    Full Text Available Discovery of G protein coupled receptors for long chain free fatty acids (FFAs, FFA1 (GPR40 and GPR120, has expanded our understanding of these nutrients as signalling molecules. These receptors have emerged as important sensors for FFA levels in the circulation or the gut lumen, based on evidence from in vitro and rodent models, and an increasing number of human studies. Here we consider their promise as therapeutic targets for metabolic disease, including type 2 diabetes and obesity. FFA1 directly mediates acute FFA-induced glucose-stimulated insulin secretion in pancreatic beta-cells, while GPR120 and FFA1 trigger release of incretins from intestinal endocrine cells, and so indirectly enhance insulin secretion and promote satiety. GPR120 signalling in adipocytes and macrophages also results in insulin sensitizing and beneficial anti-inflammatory effects. Drug discovery has focussed on agonists to replicate acute benefits of FFA receptor signalling, with promising early results for FFA1 agonists in man. Controversy surrounding chronic effects of FFA1 on beta-cells illustrates that long term benefits of antagonists also need exploring. It has proved challenging to generate highly selective potent ligands for FFA1 or GPR120 subtypes, given that both receptors have hydrophobic orthosteric binding sites, which are not completely defined and have modest ligand affinity. Structure activity relationships are also reliant on functional read outs, in the absence of robust binding assays to provide direct affinity estimates. Nevertheless synthetic ligands have already helped dissect specific contributions of FFA1 and GPR120 signalling from the many possible cellular effects of FFAs. Approaches including use of fluorescent ligand binding assays, and targeting allosteric receptor sites, may improve further preclinical ligand development at these receptors, to exploit their unique potential to target multiple facets of diabetes.

  14. Caffeic Acid-PLGA Conjugate to Design Protein Drug Delivery Systems Stable to Irradiation

    Directory of Open Access Journals (Sweden)

    Francesca Selmin

    2015-01-01

    Full Text Available This work reports the feasibility of caffeic acid grafted PLGA (g-CA-PLGA to design biodegradable sterile microspheres for the delivery of proteins. Ovalbumin (OVA was selected as model compound because of its sensitiveness of γ-radiation. The adopted grafting procedure allowed us to obtain a material with good free radical scavenging properties, without a significant modification of Mw and Tg of the starting PLGA (Mw PLGA = 26.3 ± 1.3 kDa vs. Mw g-CA-PLGA = 22.8 ± 0.7 kDa; Tg PLGA = 47.7 ± 0.8 °C vs. Tg g-CA-PLGA = 47.4 ± 0.2 °C. By using a W1/O/W2 technique, g-CA-PLGA improved the encapsulation efficiency (EE, suggesting that the presence of caffeic residues improved the compatibility between components (EEPLGA = 35.0% ± 0.7% vs. EEg-CA-PLGA = 95.6% ± 2.7%. Microspheres particle size distribution ranged from 15 to 50 µm. The zeta-potential values of placebo and loaded microspheres were −25 mV and −15 mV, respectively. The irradiation of g-CA-PLGA at the dose of 25 kGy caused a less than 1% variation of Mw and the degradation patterns of the non-irradiated and irradiated microspheres were superimposable. The OVA content in g-CA-PLGA microspheres decreased to a lower extent with respect to PLGA microspheres. These results suggest that g-CA-PLGA is a promising biodegradable material to microencapsulate biological drugs.

  15. Comparative release studies of two cationic model drugs from different cellulose nanocrystal derivatives.

    Science.gov (United States)

    Akhlaghi, Seyedeh Parinaz; Tiong, Daryl; Berry, Richard M; Tam, Kam Chiu

    2014-09-01

    Native cellulose nanocrystal (CNC), oxidized CNC (CNC-OX) and chitosan oligosaccharide grafted CNC (CNC-CSOS) were evaluated as potential drug delivery carriers for two model drug compounds, procaine hydrochloride (PrHy) and imipramine hydrochloride (IMI). The loading of PrHy and IMI was performed at pH 8 and 7, respectively. IMI displayed higher binding to CNC derivatives than PrHy. Drug selective membranes were prepared for each model drug and a drug selective electrode system was used to measure the drug concentration in the filtrate and release medium. Isothermal Titration Calorimetry (ITC) was used to elucidate the types of interactions between model drugs and CNC and its derivatives. The complexation between model drugs and CNC derivatives was confirmed by zeta potential and transmittance measurements. The binding and release of these drugs correlated with the nature and types of interactions that exist between the CNC and drug molecules.

  16. Simple micromechanical model of protein crystals for their mechanical characterizations

    Directory of Open Access Journals (Sweden)

    Na S.

    2010-06-01

    Full Text Available Proteins have been known to perform the excellent mechanical functions and exhibit the remarkable mechanical properties such as high fracture toughness in spider silk protein [1]. This indicates that the mechanical characterization of protein molecules and/or crystals is very essential to understand such remarkable mechanical function of protein molecules. In this study, for gaining insight into mechanical behavior of protein crystals, we developed the micromechanical model by using the empirical potential field prescribed to alpha carbon atoms of a protein crystal in a unit cell. We consider the simple protein crystals for their mechanical behavior under tensile loading to be compared with full atomic models

  17. Scaffold proteins LACK and TRACK as potential drug targets in kinetoplastid parasites: Development of inhibitors

    Directory of Open Access Journals (Sweden)

    Nir Qvit

    2016-04-01

    Full Text Available Parasitic diseases cause ∼500,000 deaths annually and remain a major challenge for therapeutic development. Using a rational design based approach, we developed peptide inhibitors with anti-parasitic activity that were derived from the sequences of parasite scaffold proteins LACK (Leishmania's receptor for activated C-kinase and TRACK (Trypanosoma receptor for activated C-kinase. We hypothesized that sequences in LACK and TRACK that are conserved in the parasites, but not in the mammalian ortholog, RACK (Receptor for activated C-kinase, may be interaction sites for signaling proteins that are critical for the parasites' viability. One of these peptides exhibited leishmanicidal and trypanocidal activity in culture. Moreover, in infected mice, this peptide was also effective in reducing parasitemia and increasing survival without toxic effects. The identified peptide is a promising new anti-parasitic drug lead, as its unique features may limit toxicity and drug-resistance, thus overcoming central limitations of most anti-parasitic drugs.

  18. X-ray crystallography: Assessment and validation of protein-small molecule complexes for drug discovery

    Science.gov (United States)

    Cooper, David R.; Porebski, Przemyslaw J.; Chruszcz, Maksymilian; Minor, Wladek

    2011-01-01

    Introduction Crystallography is the key initial component for structure-based and fragment-based drug design and can often generate leads that can be developed into high potency drugs. Therefore, huge sums of money are committed based on the outcome of crystallography experiments and their interpretation. Areas covered This review discusses how to evaluate the correctness of an X-ray structure, focusing on the validation of small molecule-protein complexes. Various types of inaccuracies found within the PDB are identified and the ramifications of these errors are discussed. The reader will gain an understanding of the key parameters that need to be inspected before a structure can be used in drug discovery efforts, as well as an appreciation of the difficulties of correctly interpreting electron density for small molecules. The reader will also be introduced to methods for validating small molecules within the context of a macromolecular structure. Expert opinion One of the reasons that ligand identification and positioning, within a macromolecular crystal structure, is so difficult is that the quality of small molecules widely varies in the PDB. For this reason, the PDB can not always be considered a reliable repository of structural information pertaining to small molecules, and this makes the derivation of general principles that govern small molecule-protein interactions more difficult. PMID:21779303

  19. Multi-Component Protein - Protein Docking Based Protocol with External Scoring for Modeling Dimers of G Protein-Coupled Receptors.

    Science.gov (United States)

    Kaczor, Agnieszka A; Guixà-González, Ramon; Carrió, Pau; Poso, Antti; Dove, Stefan; Pastor, Manuel; Selent, Jana

    2015-04-01

    In order to apply structure-based drug design techniques to GPCR complexes, it is essential to model their 3D structure. For this purpose, a multi-component protocol was derived based on protein-protein docking which generates populations of dimers compatible with membrane integration, considering all reasonable interfaces. At the next stage, we applied a scoring procedure based on up to eleven different parameters including shape or electrostatics complementarity. Two methods of consensus scoring were performed: (i) average scores of 100 best scored dimers with respect to each interface, and (ii) frequencies of interfaces among 100 best scored dimers. In general, our multi-component protocol gives correct indications for dimer interfaces that have been observed in X-ray crystal structures of GPCR dimers (opsin dimer, chemokine CXCR4 and CCR5 dimers, κ opioid receptor dimer, β1 adrenergic receptor dimer and smoothened receptor dimer) but also suggests alternative dimerization interfaces. Interestingly, at times these alternative interfaces are scored higher than the experimentally observed ones suggesting them to be also relevant in the life cycle of studied GPCR dimers. Further results indicate that GPCR dimer and higher-order oligomer formation may involve transmembrane helices (TMs) TM1-TM2-TM7, TM3-TM4-TM5 or TM4-TM5-TM6 but not TM1-TM2-TM3 or TM2-TM3-TM4 which is in general agreement with available experimental and computational data.

  20. Stigma, sexual risks, and the war on drugs: Examining drug policy and HIV/AIDS inequities among African Americans using the Drug War HIV/AIDS Inequities Model.

    Science.gov (United States)

    Kerr, Jelani; Jackson, Trinidad

    2016-11-01

    The relationship between drug policy and HIV vulnerability is well documented. However, little research examines the links between racial/ethnic HIV disparities via the Drug War, sexual risk, and stigma. The Drug War HIV/AIDS Inequities Model has been developed to address this dearth. This model contends that inequitable policing and sentencing promotes sexual risks, resource deprivation, and ultimately greater HIV risk for African-Americans. The Drug War also socially marginalizes African Americans and compounds stigma for incarcerated and formerly incarcerated persons living with HIV/AIDS. This marginalization has implications for sexual risk-taking, access to health-promoting resources, and continuum of care participation. The Drug War HIV/AIDS Inequities Model may help illuminate mechanisms that promote increased HIV vulnerability as well as inform structural intervention development and targeting to address racial/ethnic disparities. Copyright © 2016 Elsevier B.V. All rights reserved.

  1. Scaling predictive modeling in drug development with cloud computing.

    Science.gov (United States)

    Moghadam, Behrooz Torabi; Alvarsson, Jonathan; Holm, Marcus; Eklund, Martin; Carlsson, Lars; Spjuth, Ola

    2015-01-26

    Growing data sets with increased time for analysis is hampering predictive modeling in drug discovery. Model building can be carried out on high-performance computer clusters, but these can be expensive to purchase and maintain. We have evaluated ligand-based modeling on cloud computing resources where computations are parallelized and run on the Amazon Elastic Cloud. We trained models on open data sets of varying sizes for the end points logP and Ames mutagenicity and compare with model building parallelized on a traditional high-performance computing cluster. We show that while high-performance computing results in faster model building, the use of cloud computing resources is feasible for large data sets and scales well within cloud instances. An additional advantage of cloud computing is that the costs of predictive models can be easily quantified, and a choice can be made between speed and economy. The easy access to computational resources with no up-front investments makes cloud computing an attractive alternative for scientists, especially for those without access to a supercomputer, and our study shows that it enables cost-efficient modeling of large data sets on demand within reasonable time.

  2. Parametric time-to-onset models were developed to improve causality assessment of adverse drug reactions from antidiabetic drugs

    NARCIS (Netherlands)

    Scholl, Joep H G; van de Ven, Peter M; van Puijenbroek, Eugène P

    2015-01-01

    OBJECTIVES: The aim of this study was to investigate whether the time to onset (TTO) of common adverse drug reactions (ADRs) of antidiabetic drugs could be modeled using parametric distributions and whether these TTO distributions were dependent on patient characteristics. Furthermore, information r

  3. Towards a model for protein production rates

    CERN Document Server

    Dong, J J; Zia, R K P

    2007-01-01

    In the process of translation, ribosomes read the genetic code on an mRNA and assemble the corresponding polypeptide chain. The ribosomes perform discrete directed motion which is well modeled by a totally asymmetric simple exclusion process (TASEP) with open boundaries. Using Monte Carlo simulations and a simple mean-field theory, we discuss the effect of one or two ``bottlenecks'' (i.e., slow codons) on the production rate of the final protein. Confirming and extending previous work by Chou and Lakatos, we find that the location and spacing of the slow codons can affect the production rate quite dramatically. In particular, we observe a novel ``edge'' effect, i.e., an interaction of a single slow codon with the system boundary. We focus in detail on ribosome density profiles and provide a simple explanation for the length scale which controls the range of these interactions.

  4. Towards a Model for Protein Production Rates

    Science.gov (United States)

    Dong, J. J.; Schmittmann, B.; Zia, R. K. P.

    2007-07-01

    In the process of translation, ribosomes read the genetic code on an mRNA and assemble the corresponding polypeptide chain. The ribosomes perform discrete directed motion which is well modeled by a totally asymmetric simple exclusion process (TASEP) with open boundaries. Using Monte Carlo simulations and a simple mean-field theory, we discuss the effect of one or two "bottlenecks" (i.e., slow codons) on the production rate of the final protein. Confirming and extending previous work by Chou and Lakatos, we find that the location and spacing of the slow codons can affect the production rate quite dramatically. In particular, we observe a novel "edge" effect, i.e., an interaction of a single slow codon with the system boundary. We focus in detail on ribosome density profiles and provide a simple explanation for the length scale which controls the range of these interactions.

  5. Effect of Intestinal Flora on Protein Expression of Drug-Metabolizing Enzymes and Transporters in the Liver and Kidney of Germ-Free and Antibiotics-Treated Mice.

    Science.gov (United States)

    Kuno, Takuya; Hirayama-Kurogi, Mio; Ito, Shingo; Ohtsuki, Sumio

    2016-08-01

    Dysbiosis (alteration of intestinal flora) is associated with various host physiologies, including diseases. The purpose of this study was to clarify the effect of dysbiosis on protein expression levels in mouse liver and kidney by quantitative proteomic analysis, focusing in particular on drug-metabolizing enzymes and transporters in order to investigate the potential impact of dysbiosis on drug pharmacokinetics. Germ-free (GF) mice and antibiotics-treated mice were used as dysbiosis models. Expression levels of 825 and 357 proteins were significantly changed in the liver and kidney, respectively, of GF mice (vs specific-pathogen-free mice), while 306 and 178 proteins, respectively, were changed in antibiotics-treated mice (vs vehicle controls). Among them, 52 and 16 drug-metabolizing enzyme and transporter proteins were significantly changed in the liver and kidney, respectively, of GF mice, while 25 and 8, respectively were changed in antibiotics-treated mice. Expression of mitochondrial proteins was also changed in the liver and kidney of both model mice. In GF mice, Oatp1a1 was decreased in both the liver and kidney, while Sult1a1 and two Cyp enzymes were increased and Gstp1, four Cyp enzymes, three Ces enzymes, Bcrp1, and Oct1 were decreased in the liver. In antibiotics-treated mice, Cyp51a1 was increased and three Cyp enzymes, Bcrp1, and Bsep were decreased in the liver. Notably, the expression of Cyp2b10 and Cyp3a11 was greatly decreased in the liver of both models. Cyp2b activity in the liver microsomal fraction was also decreased. Our results indicate that dysbiosis changes the protein expression of multiple drug-metabolizing enzymes and transporters in the liver and kidney and may alter pharmacokinetics in the host.

  6. Challenges and Opportunities for New Protein Crystallization Strategies in Structure-Based Drug Design

    Science.gov (United States)

    Grey, Jessica; Thompson, David

    2010-01-01

    Structure-based drug design (SBDD) has emerged as a valuable pharmaceutical lead discovery tool, showing potential for accelerating the discovery process, while reducing developmental costs and boosting potencies of the drug that is ultimately selected. SBDD is a iterative, rational, lead compound sculpting process that involves both the synthesis of new derivatives and the evaluation of their binding to the target structure either through computational docking or elucidation of the target structure as a complex with the lead compound. This method heavily relies on the production of high-resolution (< 2Å) three-dimensional structures of the drug target, obtained through X-ray crystallographic analysis, in the presence or absence of the drug candidate. The lack of generalized methods for high quality crystal production is still a major bottleneck in the process of macromolecular crystallization. This review provides a brief introduction to SBDD and describes several macromolecular crystallization strategies, with an emphasis on advances and challenges facing researchers in the field today. Recent trends in the development of more universal macromolecular crystallization techniques, particularly nucleation-based techniques that are applicable to both soluble and integral membrane proteins, are also discussed. PMID:21116481

  7. Quantum Mechanics/Molecular Mechanics Modeling of Drug Metabolism

    DEFF Research Database (Denmark)

    Lonsdale, Richard; Fort, Rachel M; Rydberg, Patrik;

    2016-01-01

    The mechanism of cytochrome P450(CYP)-catalyzed hydroxylation of primary amines is currently unclear and is relevant to drug metabolism; previous small model calculations have suggested two possible mechanisms: direct N-oxidation and H-abstraction/rebound. We have modeled the N-hydroxylation of (R......)-mexiletine in CYP1A2 with hybrid quantum mechanics/molecular mechanics (QM/MM) methods, providing a more detailed and realistic model. Multiple reaction barriers have been calculated at the QM(B3LYP-D)/MM(CHARMM27) level for the direct N-oxidation and H-abstraction/rebound mechanisms. Our calculated barriers...... indicate that the direct N-oxidation mechanism is preferred and proceeds via the doublet spin state of Compound I. Molecular dynamics simulations indicate that the presence of an ordered water molecule in the active site assists in the binding of mexiletine in the active site...

  8. Drug discovery of antimicrobial photosensitizers using animal models.

    Science.gov (United States)

    Sharma, Sulbha K; Dai, Tianhong; Kharkwal, Gitika B; Huang, Ying-Ying; Huang, Liyi; De Arce, Vida J Bil; Tegos, George P; Hamblin, Michael R

    2011-01-01

    Antimicrobial photodynamic therapy (aPDT) is an emerging alternative to antibiotics motivated by growing problems with multi-drug resistant pathogens. aPDT uses non-toxic dyes or photosensitizers (PS) in combination with harmless visible of the correct wavelength to be absorbed by the PS. The excited state PS can form a long-lived triplet state that can interact with molecular oxygen to produce reactive oxygen species such as singlet oxygen and hydroxyl radical that kill the microbial cells. To obtain effective PS for treatment of infections it is necessary to use cationic PS with positive charges that are able to bind to and penetrate different classes of microbial cells. Other drug design criteria require PS with high absorption coefficients in the red/near infra-red regions of the spectrum where light penetration into tissue is maximum, high photostability to minimize photobleaching, and devising compounds that will selectively bind to microbial cells rather than host mammalian cells. Several molecular classes fulfill many of these requirements including phenothiazinium dyes, cationic tetrapyrroles such as porphyrins, phthalocyanines and bacteriochlorins, cationic fullerenes and cationic derivatives of other known PS. Larger structures such as conjugates between PS and cationic polymers, cationic nanoparticles and cationic liposomes that contain PS are also effective. In order to demonstrate in vivo efficacy it is necessary to use animal models of localized infections in which both PS and light can be effectively delivered into the infected area. This review will cover a range of mouse models we have developed using bioluminescent pathogens and a sensitive low light imaging system to non-invasively monitor the progress of the infection in real time. Effective aPDT has been demonstrated in acute lethal infections and chronic biofilm infections; in infections caused by Gram-positive, Gram-negative bacteria and fungi; in infections in wounds, third degree burns

  9. The anti-diabetic drug metformin reduces BACE1 protein level by interfering with the MID1 complex.

    Directory of Open Access Journals (Sweden)

    Moritz M Hettich

    Full Text Available Alzheimer's disease (AD, the most common form of dementia in the elderly, is characterized by two neuropathological hallmarks: senile plaques, which are composed of Aβ peptides, and neurofibrillary tangles, which are composed of hyperphosphorylated TAU protein. Diabetic patients with dysregulated insulin signalling are at increased risk of developing AD. Further, several animal models of diabetes show increased Aβ expression and hyperphosphorylated tau. As we have shown recently, the anti-diabetic drug metformin is capable of dephosphorylating tau at AD-relevant phospho-sites. Here, we investigated the effect of metformin on the main amyloidogenic enzyme BACE1 and, thus, on the production of Aβ peptides, the second pathological hallmark of AD. We find similar results in cultures of primary neurons, a human cell line model of AD and in vivo in mice. We show that treatment with metformin decreases BACE1 protein expression by interfering with an mRNA-protein complex that contains the ubiquitin ligase MID1, thereby reducing BACE1 activity. Together with our previous findings these results indicate that metformin may target both pathological hallmarks of AD and may be of therapeutic value for treating and/or preventing AD.

  10. Rhodamine/Nanodiamond as a System Model for Drug Carrier.

    Science.gov (United States)

    Reina, G; Orlanducci, S; Cairone, C; Tamburri, E; Lenti, S; Cianchetta, I; Rossi, M; Terranova, M L

    2015-02-01

    In this paper we present some strategies that are being developed in our labs towards enabling nanodiamond-based applications for drug delivery. Rhodamine B (RhB) has been choosen as model molecule to study the loading of nanodiamonds with active moieties and the conditions for their controlled release. In order to test the chemical/physical interactions between functionalized detonation nanodiamond (DND) and complex molecules, we prepared and tested different RhB@DND systems, with RhB adsorbed or linked by ionic bonding to the DND surface. The chemical state of the DND surfaces before conjugation with the RhB molecules, and the chemical features of the DND-RhB interactions have been deeply analysed by coupling DND with Au nanoparticles and taking advantage of surface enhanced Raman spectroscopy SERS. The effects due to temperature and pH variations on the process of RhB release from the DND carrier have been also investigated. The amounts of released molecules are consistent with those required for effective drug action in conventional therapeutic applications, and this makes the DND promising nanostructured cargos for drug delivery applications.

  11. MR imaging of model drug distribution in simulated vitreous

    Directory of Open Access Journals (Sweden)

    Stein Sandra

    2015-09-01

    Full Text Available The in vitro and in vivo characterization of intravitreal injections plays an important role in developing innovative therapy approaches. Using the established vitreous model (VM and eye movement system (EyeMoS the distribution of contrast agents with different molecular weight was studied in vitro. The impact of the simulated age-related vitreal liquefaction (VL on drug distribution in VM was examined either with injection through the gel phase or through the liquid phase. For comparison the distribution was studied ex vivo in the porcine vitreous. The studies were performed in a magnetic resonance (MR scanner. As expected, with increasing molecular weight the diffusion velocity and the visual distribution of the injected substances decreased. Similar drug distribution was observed in VM and in porcine eye. VL causes enhanced convective flow and faster distribution in VM. Confirming the importance of the injection technique in progress of VL, injection through gelatinous phase caused faster distribution into peripheral regions of the VM than following injection through liquefied phase. VM and MR scanner in combination present a new approach for the in vitro characterization of drug release and distribution of intravitreal dosage forms.

  12. Prediction of intraocular antibody drug stability using ex-vivo ocular model.

    Science.gov (United States)

    Patel, Sulabh; Stracke, Jan Olaf; Altenburger, Ulrike; Mahler, Hanns-Christian; Metzger, Philipp; Shende, Pankaj; Jere, Dhananjay

    2017-03-01

    Following intravitreal (IVT) injection, therapeutic proteins get exposed to physiological pH, temperature and components in the vitreous humor (VH) for a significantly long time. Therefore, it is of interest to study the stability of the proteins in the VH. However, the challenge posed by the isolated VH (such as pH shift upon isolation and incubation due to the formation of smaller molecular weight (MW) degradation products) can result in artefacts when investigating protein stability in relevance for the actual in vivo situation. In this current study, an ex-vivo intravitreal horizontal stability model (ExVit-HS) has been successfully developed and an assessment of long-term stability of a bi-specific monoclonal antibody (mAb) drug in the isolated VH for 3months at physiological conditions has been conducted. The stability assessment was performed using various analytical techniques such as microscopy, UV visible for protein content, target binding ELISA, Differential Scanning Calorimetry (DSC), Capillary-electrophoresis-SDS, Size Exclusion (SEC) and Ion-exchange chromatography (IEC) and SPR-Biacore. The results show that the ExVit-HS model was successful in maintaining the VH at physiological conditions and retained a majority of protein in the VH-compartment throughout the study period. The mAb exhibited significantly less fragmentation in the VH relative to the PBS control; however, chemical stability of the mAb was equally compromised in VH and PBS. Interestingly, in the PBS control, mAb showed a rapid linear loss in the binding affinity. The loss in binding was almost 20% higher compared to that in VH after 3months. The results clearly suggest that the mAb has different degradation kinetics in the VH compared to PBS. These results suggest that it is beneficial to investigate the stability in the VH for drugs intended for IVT injection and that are expected longer residence times in the VH. The studies show that the ExVit-HS model may become a valuable tool

  13. Identification of a Drug Targeting an Intrinsically Disordered Protein Involved in Pancreatic Adenocarcinoma

    Science.gov (United States)

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

    2017-01-01

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

  14. Interactions between Human Liver Fatty Acid Binding Protein and Peroxisome Proliferator Activated Receptor Selective Drugs

    Directory of Open Access Journals (Sweden)

    Tony Velkov

    2013-01-01

    Full Text Available Fatty acid binding proteins (FABPs act as intracellular shuttles for fatty acids as well as lipophilic xenobiotics to the nucleus, where these ligands are released to a group of nuclear receptors called the peroxisome proliferator activated receptors (PPARs. PPAR mediated gene activation is ultimately involved in maintenance of cellular homeostasis through the transcriptional regulation of metabolic enzymes and transporters that target the activating ligand. Here we show that liver- (L- FABP displays a high binding affinity for PPAR subtype selective drugs. NMR chemical shift perturbation mapping and proteolytic protection experiments show that the binding of the PPAR subtype selective drugs produces conformational changes that stabilize the portal region of L-FABP. NMR chemical shift perturbation studies also revealed that L-FABP can form a complex with the PPAR ligand binding domain (LBD of PPARα. This protein-protein interaction may represent a mechanism for facilitating the activation of PPAR transcriptional activity via the direct channeling of ligands between the binding pocket of L-FABP and the PPARαLBD. The role of L-FABP in the delivery of ligands directly to PPARα via this channeling mechanism has important implications for regulatory pathways that mediate xenobiotic responses and host protection in tissues such as the small intestine and the liver where L-FABP is highly expressed.

  15. Specific noncovalent interactions at protein-ligand interface: implications for rational drug design.

    Science.gov (United States)

    Zhou, P; Huang, J; Tian, F

    2012-01-01

    Specific noncovalent interactions that are indicative of attractive, directional intermolecular forces have always been of key interest to medicinal chemists in their search for the "glue" that holds drugs and their targets together. With the rapid increase in the number of solved biomolecular structures as well as the performance enhancement of computer hardware and software in recent years, it is now possible to give more comprehensive insight into the geometrical characteristics and energetic landscape of certain sophisticated noncovalent interactions present at the binding interface of protein receptors and small ligands based on accumulated knowledge gaining from the combination of two quite disparate but complementary approaches: crystallographic data analysis and quantum-mechanical ab initio calculation. In this perspective, we survey massive body of published works relating to structural characterization and theoretical investigation of three kinds of strong, specific, direct, enthalpy-driven intermolecular forces, including hydrogen bond, halogen bond and salt bridge, involved in the formation of protein-ligand complex architecture in order to characterize their biological functions in conferring affinity and specificity for ligand recognition by host protein. In particular, the biomedical implications of raised knowledge are discussed with respect to potential applications in rational drug design.

  16. Expression of Uncoupling Protein 2 in Breast Cancer Tissue and Drug-resistant Cells

    Institute of Scientific and Technical Information of China (English)

    Sun Yan; Yuan Yuan; Zhang Lili; Zhu Hong; Hu Sainan

    2013-01-01

    Objective:To explore the expression of uncoupling protein-2 (UCP2) in clinical breast cancer tissue and drug-resistant cells. Methods:The expression of UCP2 in breast cancer tissue and normal tissue adjacent to carcinoma as well as breast cancer cell MCF-7 and paclitaxel-resistant cell MX-1/T were respectively detected by immunohistochemistry and Western blot. Results:The expression of UCP2 in breast cancer tissue was signiifcantly higher than in normal tissue adjacent to carcinoma, and that in paclitaxel-resistant cell MX-1/T obviously higher than in breast cancer cell MCF-7. Conclusion:UCP2 is highly expressed in breast cancer tissue and drug-resistant cells.

  17. Thermodynamical study of interaction of histone H1 chromosomal protein and mitoxantrone anticancer drug

    Energy Technology Data Exchange (ETDEWEB)

    Jafargholizadeh, Naser [Department of Cell and Molecular Biology, School of Biology, College of Science, University of Tehran, Tehran (Iran, Islamic Republic of); Zargar, Seyed Jalal, E-mail: Zargar@khayam.ut.ac.ir [Department of Cell and Molecular Biology, School of Biology, College of Science, University of Tehran, Tehran (Iran, Islamic Republic of); Safarian, Shahrokh; Habibi-Rezaei, Mehran [Department of Cell and Molecular Biology, School of Biology, College of Science, University of Tehran, Tehran (Iran, Islamic Republic of)

    2012-06-10

    Highlights: Black-Right-Pointing-Pointer For the first time, our results show mitoxantrone anticancer drug binds to histone H1, via hydrophobic, hydrogen, van der Waals and electrostatic interactions. Black-Right-Pointing-Pointer Binding of mitoxantrone molecules to histone H1 is positive cooperative. Black-Right-Pointing-Pointer Histone H1 may be considered as a new target for mitoxantrone at the chromatin level. - Using ultraviolet spectroscopy technique, we have investigated the interaction of anticancer drug, mitoxantrone with calf thymus histone H1 chromosomal protein in 100 mM phosphate buffer, pH 7.0, at temperatures 300 and 310 K. UV spectroscopy results show interactions between mitoxantrone and histone H1 with a positive cooperative binding process which was confirmed by Scatchard plot. According to the obtained results, it is concluded that histone H1 can be considered as a target for mitoxantrone binding at the chromatin level.

  18. Antibodies against G-protein coupled receptors: novel uses in screening and drug development.

    Science.gov (United States)

    Gupta, Achla; Heimann, Andrea S; Gomes, Ivone; Devi, Lakshmi A

    2008-07-01

    Antibodies are components of the body's humoral immune system that are generated in response to foreign pathogens. Modern biomedical research has employed these very specific and efficient molecules designed by nature in the diagnosis of diseases, localization of gene products as well as in the rapid screening of targets for drug discovery and testing. In addition, the introduction of antibodies with fluorescent or enzymatic tags has significantly contributed to advances in imaging and microarray technology, which are revolutionizing disease research and the search for effective therapeutics. More recently antibodies have been used in the isolation of dimeric G protein-coupled receptor (GPCR) complexes. In this review, we discuss antibodies as powerful research tools for studying GPCRs, and their potential to be developed as drugs themselves.

  19. Whey protein mucoadhesive properties for oral drug delivery: Mucin-whey protein interaction and mucoadhesive bond strength.

    Science.gov (United States)

    Hsein, Hassana; Garrait, Ghislain; Beyssac, Eric; Hoffart, Valérie

    2015-12-01

    Whey protein is a natural polymer recently used as an excipient in buccoadhesive tablets but its mucoadhesive properties were barely studied. In this work, we characterize mucoadhesion of whey protein in order to determine the mechanisms and optimal conditions for use as excipient in oral drug delivery. Thus, native and denatured whey protein (NWP and DWP) were investigated and the effect of concentration and pH were also studied. Many methods of characterization were selected to allow the study of chemical and physical interactions with mucin and then the results were bound with an ex vivo experiments. Turbidity of WP-mucin mixture increased at acidic pH 1.2 till 4.5 indicating interaction with mucin but not at pH 6.8. No interaction with mucin was also found by ITC method at pH 6.8 for native and denatured whey protein used at 1% (w/w). Forces of bioadhesion evaluated by viscosity measurements were the best for high concentrated (10.8%) DWP solutions at pH 6.8 and were low at pH 1.2 for NWP and DWP solutions. Addition of chemical blockers indicated that hydrogen bondings and disulfide bridges were the main mechanisms of interactions with mucin. Reticulation of DWP with calcium ions to obtain microparticles (MP) did not influence the ability of interaction with mucin as shown by FTIR analysis. These results correlated with ex vivo study on rat tissue demonstrating important adhesion (75%) of WP MP on the intestine and null on the stomach after 2h of deposit.

  20. Resurgence of alcohol seeking produced by discontinuing non-drug reinforcement as an animal model of drug relapse.

    Science.gov (United States)

    Podlesnik, Christopher A; Jimenez-Gomez, Corina; Shahan, Timothy A

    2006-06-01

    Findings from basic behavioral research suggest that simply discontinuing reinforcement for a recently reinforced operant response can cause the recurrence (i.e. resurgence) of a different previously reinforced response. The present experiment examined resurgence as an animal model of drug relapse. Initially, rats pressed levers to self-administer alcohol during baseline conditions. Next, alcohol self-administration was discontinued and non-drug reinforcers (food pellets) were presented contingent on an alternative response (chain pulling). Finally, when the non-drug reinforcer was discontinued, alcohol seeking recurred even though alcohol was still unavailable for lever pressing. These results suggest that simply discontinuing non-drug reinforcement for a behavior may be sufficient to produce relapse to drug seeking. The resurgence procedure could provide a method to examine environmental, pharmacological, and neurobiological factors that lead to relapse following the loss of a non-drug source of reinforcement.

  1. A Dual-Process Discrete-Time Survival Analysis Model: Application to the Gateway Drug Hypothesis

    Science.gov (United States)

    Malone, Patrick S.; Lamis, Dorian A.; Masyn, Katherine E.; Northrup, Thomas F.

    2010-01-01

    The gateway drug model is a popular conceptualization of a progression most substance users are hypothesized to follow as they try different legal and illegal drugs. Most forms of the gateway hypothesis are that "softer" drugs lead to "harder," illicit drugs. However, the gateway hypothesis has been notably difficult to directly test--that is, to…

  2. Evaluation of the drug solubility and rush ageing on drug release performance of various model drugs from the modified release polyethylene oxide matrix tablets.

    Science.gov (United States)

    Shojaee, Saeed; Nokhodchi, Ali; Maniruzzaman, Mohammed

    2017-02-01

    Hydrophilic matrix systems are currently some of the most widely used drug delivery systems for controlled-release oral dosage forms. Amongst a variety of polymers, polyethylene oxide (PEO) is considered an important material used in pharmaceutical formulations. As PEO is sensitive to thermal oxidation, it is susceptible to free radical oxidative attack. The aim of this study was to investigate the stability of PEO based formulations containing different model drugs with different water solubility, namely propranolol HCl, theophylline and zonisamide. Both polyox matrices 750 and 303 grade were used as model carriers for the manufacture of tablets stored at 40 °C. The results of the present study suggest that the drug release from the matrix was affected by the length of storage conditions, solubility of drugs and the molecular weight of the polymers. Generally, increased drug release rates were prevalent in soluble drug formulations (propranolol) when stored at the elevated temperature (40 °C). In contrast, it was not observed with semi soluble (theophylline) and poorly soluble (zonisamide) drugs especially when formulated with PEO 303 polymer. This indicates that the main parameters controlling the drug release from fresh polyox matrices are the solubility of the drug in the dissolution medium and the molecular weight of the polymer. DSC traces indicated that that there was a big difference in the enthalpy and melting points of fresh and aged PEO samples containing propranolol, whereas the melting point of the aged polyox samples containing theophylline and zonisamide was unaffected. Graphical abstract ᅟ.

  3. A hybrid Markov chain-von Mises density model for the drug-dosing interval and drug holiday distributions.

    Science.gov (United States)

    Fellows, Kelly; Rodriguez-Cruz, Vivian; Covelli, Jenna; Droopad, Alyssa; Alexander, Sheril; Ramanathan, Murali

    2015-03-01

    Lack of adherence is a frequent cause of hospitalizations, but its effects on dosing patterns have not been extensively investigated. The purpose of this work was to critically evaluate a novel pharmacometric model for deriving the relationships of adherence to dosing patterns and the dosing interval distribution. The hybrid, stochastic model combines a Markov chain process with the von Mises distribution. The model was challenged with electronic medication monitoring data from 207 hypertension patients and against 5-year persistence data. The model estimates distributions of dosing runs, drug holidays, and dosing intervals. Drug holidays, which can vary between individuals with the same adherence, were characterized by the patient cooperativity index parameter. The drug holiday and dosing run distributions deviate markedly from normality. The dosing interval distribution exhibits complex patterns of multimodality and can be long-tailed. Dosing patterns are an important but under recognized covariate for explaining within-individual variance in drug concentrations.

  4. Improving Detection of Arrhythmia Drug-Drug Interactions in Pharmacovigilance Data through the Implementation of Similarity-Based Modeling.

    Directory of Open Access Journals (Sweden)

    Santiago Vilar

    Full Text Available Identification of Drug-Drug Interactions (DDIs is a significant challenge during drug development and clinical practice. DDIs are responsible for many adverse drug effects (ADEs, decreasing patient quality of life and causing higher care expenses. DDIs are not systematically evaluated in pre-clinical or clinical trials and so the FDA U. S. Food and Drug Administration relies on post-marketing surveillance to monitor patient safety. However, existing pharmacovigilance algorithms show poor performance for detecting DDIs exhibiting prohibitively high false positive rates. Alternatively, methods based on chemical structure and pharmacological similarity have shown promise in adverse drug event detection. We hypothesize that the use of chemical biology data in a post hoc analysis of pharmacovigilance results will significantly improve the detection of dangerous interactions. Our model integrates a reference standard of DDIs known to cause arrhythmias with drug similarity data. To compare similarity between drugs we used chemical structure (both 2D and 3D molecular structure, adverse drug side effects, chemogenomic targets, drug indication classes, and known drug-drug interactions. We evaluated the method on external reference standards. Our results showed an enhancement of sensitivity, specificity and precision in different top positions with the use of similarity measures to rank the candidates extracted from pharmacovigilance data. For the top 100 DDI candidates, similarity-based modeling yielded close to twofold precision enhancement compared to the proportional reporting ratio (PRR. Moreover, the method helps in the DDI decision making through the identification of the DDI in the reference standard that generated the candidate.

  5. How does fatty acid influence anti-thyroid drugs binding and specificity toward protein human serum albumin? A blind docking simulation study

    Indian Academy of Sciences (India)

    Bijan K Paul; Nikhil Guchhait

    2014-11-01

    This study reports an AutoDock-based blind docking simulation investigation to characterize the binding interaction of a series of anti-thyroid drugs (2-mercapto-1-methylimidazole (MMI), 2-thiouracil (TU), 6-methyl-2-thiouracil (MTU), 6--propyl-2-thiouracil (PTU) with a model plasma protein Human SerumAlbumin (HSA) in the presence and absence of fatty acid (FA). The drug-protein binding efficiency is characterized in terms of binding free energy and the association constant (Ka, which is estimated as the reciprocal of the inhibition constant, Ki) of the drugs to the transport protein. The study also unveils the substantial impact of the presence of fatty acid (FA) on the binding interaction process. It is shown that in the presence of FA the drug-protein binding efficiency is markedly enhanced (except for MTU) and the binding location is changed. Hydrogen bonding interaction appears to play a governing role in the process of FA-induced modifications of binding efficiency and location.

  6. Parasite Mitogen-Activated Protein Kinases as Drug Discovery Targets to Treat Human Protozoan Pathogens

    Directory of Open Access Journals (Sweden)

    Michael J. Brumlik

    2011-01-01

    Full Text Available Protozoan pathogens are a highly diverse group of unicellular organisms, several of which are significant human pathogens. One group of protozoan pathogens includes obligate intracellular parasites such as agents of malaria, leishmaniasis, babesiosis, and toxoplasmosis. The other group includes extracellular pathogens such as agents of giardiasis and amebiasis. An unfortunate unifying theme for most human protozoan pathogens is that highly effective treatments for them are generally lacking. We will review targeting protozoan mitogen-activated protein kinases (MAPKs as a novel drug discovery approach towards developing better therapies, focusing on Plasmodia, Leishmania, and Toxoplasma, about which the most is known.

  7. Animal models of skin disease for drug discovery

    Science.gov (United States)

    Avci, Pinar; Sadasivam, Magesh; Gupta, Asheesh; De Melo, Wanessa CMA; Huang, Ying-Ying; Yin, Rui; Rakkiyappan, Chandran; Kumar, Raj; Otufowora, Ayodeji; Nyame, Theodore; Hamblin, Michael R

    2013-01-01

    Introduction Discovery of novel drugs, treatments, and testing of consumer products in the field of dermatology is a multi-billion dollar business. Due to the distressing nature of many dermatological diseases, and the enormous consumer demand for products to reverse the effects of skin photodamage, aging, and hair loss, this is a very active field. Areas covered In this paper, we will cover the use of animal models that have been reported to recapitulate to a greater or lesser extent the features of human dermatological disease. There has been a remarkable increase in the number and variety of transgenic mouse models in recent years, and the basic strategy for constructing them is outlined. Expert opinion Inflammatory and autoimmune skin diseases are all represented by a range of mouse models both transgenic and normal. Skin cancer is mainly studied in mice and fish. Wound healing is studied in a wider range of animal species, and skin infections such as acne and leprosy also have been studied in animal models. Moving to the more consumer-oriented area of dermatology, there are models for studying the harmful effect of sunlight on the skin, and testing of sunscreens, and several different animal models of hair loss or alopecia. PMID:23293893

  8. High performance affinity chromatography (HPAC) as a high-throughput screening tool in drug discovery to study drug-plasma protein interactions.

    Science.gov (United States)

    Vuignier, Karine; Guillarme, Davy; Veuthey, Jean-Luc; Carrupt, Pierre-Alain; Schappler, Julie

    2013-02-23

    Drug-plasma protein binding is an important parameter that, together with other physicochemical properties such as lipophilicity and pK(a), greatly influences drug absorption, distribution, metabolism, and excretion (ADME). Therefore, it is important for pharmaceutical companies to develop a rapid screening assay to examine plasma protein binding during the early stages of the drug discovery process. Human serum albumin (HSA) and α(1)-acid glycoprotein (AGP) are the most important plasma proteins that are capable of binding drugs. In this work, an automated and high-throughput (high performance affinity chromatography (HPAC) with commercial HSA and AGP columns to evaluate drug-plasma protein interactions for drug screening. A generic gradient was used throughout the study to separate drugs that were weakly and tightly bound to HSA and AGP. To accelerate the analysis time, the system was calibrated in a single run by pooling reference compounds without overloading the column. For both HSA and AGP studies, the developed methods were successfully transferred from HPAC-UV to HPAC-MS with single quadrupole MS detection and ammonium acetate, pH 7.0 as a volatile mobile phase. The MS detection enhanced the sensitivity, selectivity, and throughput of the method by pooling unknown compounds. For HSA analyses, the binding percentages obtained using HPAC were well correlated with the binding percentages from the literature. This method was also able to rank compounds based on their affinity for HSA. Concerning the AGP analyses, the quality of the correlation between the binding percentages obtained in HPAC and those from the literature was weaker. However, the method was able to classify compounds into weak, medium, and strong binders and rank compounds based on their affinity for AGP.

  9. Multiple drug resistance protein (MDR-1, multidrug resistance-related protein (MRP and lung resistance protein (LRP gene expression in childhood acute lymphoblastic leukemia

    Directory of Open Access Journals (Sweden)

    Elvis Terci Valera

    Full Text Available CONTEXT: Despite the advances in the cure rate for acute lymphoblastic leukemia, approximately 25% of affected children suffer relapses. Expression of genes for the multiple drug resistance protein (MDR-1, multidrug resistance-related protein (MRP, and lung resistance protein (LRP may confer the phenotype of resistance to the treatment of neoplasias. OBJECTIVE: To analyze the expression of the MDR-1, MRP and LRP genes in children with a diagnosis of acute lymphoblastic leukemia via the semiquantitative reverse transcription polymerase chain reaction (RT-PCR, and to determine the correlation between expression and event-free survival and clinical and laboratory variables. DESIGN: A retrospective clinical study. SETTING: Laboratory of Pediatric Oncology, Department of Pediatrics, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Brazil. METHODS: Bone marrow aspirates from 30 children with a diagnosis of acute lymphoblastic leukemia were assessed for the expression of messenger RNA for the MDR-1, MRP and LRP genes by semi-quantitative RT-PCR. RESULTS: In the three groups studied, only the increased expression of LRP was related to worsened event-free survival (p = 0.005. The presence of the common acute lymphoblastic leukemia antigen (CALLA was correlated with increased LRP expression (p = 0.009 and increased risk of relapse or death (p = 0.05. The relative risk of relapse or death was six times higher among children with high LRP expression upon diagnosis (p = 0.05, as confirmed by multivariate analysis of the three genes studied (p = 0.035. DISCUSSION: Cell resistance to drugs is a determinant of the response to chemotherapy and its detection via RT-PCR may be of clinical importance. CONCLUSIONS: Evaluation of the expression of genes for resistance to antineoplastic drugs in childhood acute lymphoblastic leukemia upon diagnosis, and particularly the expression of the LRP gene, may be of clinical relevance, and should be the

  10. Reconsidering GHB: orphan drug or new model antidepressant?

    Science.gov (United States)

    Bosch, Oliver G; Quednow, Boris B; Seifritz, Erich; Wetter, Thomas C

    2012-05-01

    For six decades, the principal mode of action of antidepressant drugs is the inhibition of monoamine re-uptake from the synaptic cleft. Tricyclic antidepressants, selective serotonin re-uptake inhibitors (SSRIs) and the new generation of dual antidepressants all exert their antidepressant effects by this mechanism. In the early days of the monoaminergic era, other efforts have been made to ameliorate the symptoms of depression by pharmacological means. The gamma-aminobutyric acid (GABA) system was and possibly still is one of the main alternative drug targets. Gammahydroxybutyrate (GHB) was developed as an orally active GABA analogue. It was tested in animal models of depression and human studies. The effects on sleep, agitation, anhedonia and depression were promising. However, the rise of benzodiazepines and tricyclic antidepressants brought GHB out of the scope of possible treatment alternatives. GHB is a GABA(B) and GHB receptor agonist with a unique spectrum of behavioural, neuroendocrine and sleep effects, and improves daytime sleepiness in various disorders such as narcolepsy, Parkinson's disease and fibromyalgia. Although it was banned from the US market at the end of the 1990s because of its abuse and overdose potential, it later was approved for the treatment of narcolepsy. New research methods and an extended view on other neurotransmitter systems as possible treatment targets of antidepressant treatment brought GHB back to the scene. This article discusses the unique neurobiological effects of GHB, its misuse potential and possible role as a model substance for the development of novel pharmacological treatment strategies in depressive disorders.

  11. A modified resonant recognition model to predict protein-protein interaction

    Institute of Scientific and Technical Information of China (English)

    LIU Xiang; WANG Yifei

    2007-01-01

    Proteins are fundamental components of all living cells and the protein-protein interaction plays an important role in vital movement.This paper briefly introduced the original Resonant Recognition Model (RRM),and then modified it by using the wavelet transform to acquire the Modified Resonant Recognition Model (MRRM).The key characteristic of the new model is that it can predict directly the proteinprotein interaction from the primary sequence,and the MRRM is more suitable than the RRM for this prediction.The results of numerical experiments show that the MRRM is effective for predicting the protein-protein interaction.

  12. Old and new therapeutics for Rheumatoid Arthritis: in vivo models and drug development

    DEFF Research Database (Denmark)

    Sardar, Samra; Andersson, Åsa

    2016-01-01

    Development of novel drugs for treatment of chronic inflammatory diseases is to a large extent dependent on the availability of good experimental in vivo models in order to perform preclinical tests of new drugs and for the identification of novel drug targets. Here, we review a number of existing...... of in vivo models during development of anti-rheumatic drugs; from Methotrexate to various antibody treatments, to novel drugs that are, or have recently been, in clinical trials. For novel drugs, we have explored websites for clinical trials. Although one Rheumatoid Arthritis in vivo model cannot mirror...... the complexity of disease development, there exist a number of good animal models for Rheumatoid Arthritis, each defining some parts in disease development, which are useful for studies of drug response. We find that many of the established drugs were not tested in in vivo models before being used in the clinic...

  13. Skin models for the testing of transdermal drugs

    Science.gov (United States)

    Abd, Eman; Yousef, Shereen A; Pastore, Michael N; Telaprolu, Krishna; Mohammed, Yousuf H; Namjoshi, Sarika; Grice, Jeffrey E; Roberts, Michael S

    2016-01-01

    The assessment of percutaneous permeation of molecules is a key step in the evaluation of dermal or transdermal delivery systems. If the drugs are intended for delivery to humans, the most appropriate setting in which to do the assessment is the in vivo human. However, this may not be possible for ethical, practical, or economic reasons, particularly in the early phases of development. It is thus necessary to find alternative methods using accessible and reproducible surrogates for in vivo human skin. A range of models has been developed, including ex vivo human skin, usually obtained from cadavers or plastic surgery patients, ex vivo animal skin, and artificial or reconstructed skin models. Increasingly, largely driven by regulatory authorities and industry, there is a focus on developing standardized techniques and protocols. With this comes the need to demonstrate that the surrogate models produce results that correlate with those from in vivo human studies and that they can be used to show bioequivalence of different topical products. This review discusses the alternative skin models that have been developed as surrogates for normal and diseased skin and examines the concepts of using model systems for in vitro–in vivo correlation and the demonstration of bioequivalence. PMID:27799831

  14. [Classification models of structure - P-glycoprotein activity of drugs].

    Science.gov (United States)

    Grigorev, V Yu; Solodova, S L; Polianczyk, D E; Raevsky, O A

    2016-01-01

    Thirty three classification models of substrate specificity of 177 drugs to P-glycoprotein have been created using of the linear discriminant analysis, random forest and support vector machine methods. QSAR modeling was carried out using 2 strategies. The first strategy consisted in search of all possible combinations from 1÷5 descriptors on the basis of 7 most significant molecular descriptors with clear physico-chemical interpretation. In the second case forward selection procedure up to 5 descriptors, starting from the best single descriptor was used. This strategy was applied to a set of 387 DRAGON descriptors. It was found that only one of 33 models has necessary statistical parameters. This model was designed by means of the linear discriminant analysis on the basis of a single descriptor of H-bond (ΣC(ad)). The model has good statistical characteristics as evidenced by results to both internal cross-validation, and external validation with application of 44 new chemicals. This confirms an important role of hydrogen bond in the processes connected with penetration of chemical compounds through a blood-brain barrier.

  15. Biotechnology and genetic engineering in the new drug development. Part I. DNA technology and recombinant proteins.

    Science.gov (United States)

    Stryjewska, Agnieszka; Kiepura, Katarzyna; Librowski, Tadeusz; Lochyński, Stanisław

    2013-01-01

    Pharmaceutical biotechnology has a long tradition and is rooted in the last century, first exemplified by penicillin and streptomycin as low molecular weight biosynthetic compounds. Today, pharmaceutical biotechnology still has its fundamentals in fermentation and bioprocessing, but the paradigmatic change affected by biotechnology and pharmaceutical sciences has led to an updated definition. The biotechnology revolution redrew the research, development, production and even marketing processes of drugs. Powerful new instruments and biotechnology related scientific disciplines (genomics, proteomics) make it possible to examine and exploit the behavior of proteins and molecules. Recombinant DNA (rDNA) technologies (genetic, protein, and metabolic engineering) allow the production of a wide range of peptides, proteins, and biochemicals from naturally nonproducing cells. This technology, now approximately 25 years old, is becoming one of the most important technologies developed in the 20(th) century. Pharmaceutical products and industrial enzymes were the first biotech products on the world market made by means of rDNA. Despite important advances regarding rDNA applications in mammalian cells, yeasts still represent attractive hosts for the production of heterologous proteins. In this review we describe these processes.

  16. Discovery: an interactive resource for the rational selection and comparison of putative drug target proteins in malaria

    Directory of Open Access Journals (Sweden)

    Odendaal Christiaan J

    2009-07-01

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

  17. Protein structure similarity clustering (PSSC) and natural product structure as inspiration sources for drug development and chemical genomics

    NARCIS (Netherlands)

    Dekker, Frank J; Koch, Marcus A; Waldmann, Herbert; Dekker, Frans

    Finding small molecules that modulate protein function is of primary importance in drug development and in the emerging field of chemical genomics. To facilitate the identification of such molecules, we developed a novel strategy making use of structural conservatism found in protein domain

  18. Protein structure similarity clustering (PSSC) and natural product structure as inspiration sources for drug development and chemical genomics

    NARCIS (Netherlands)

    Dekker, Frank J; Koch, Marcus A; Waldmann, Herbert; Dekker, Frans

    2005-01-01

    Finding small molecules that modulate protein function is of primary importance in drug development and in the emerging field of chemical genomics. To facilitate the identification of such molecules, we developed a novel strategy making use of structural conservatism found in protein domain architec

  19. Protein metabolism in the rat cerebral cortex in vivo and in vitro as affected by the acquisition enhancing drug piracetam

    NARCIS (Netherlands)

    Nickolson, V.J.; Wolthuis, O.L.

    1976-01-01

    The effect of Piracetam on rat cerebral protein metabolism in vivo and in vitro was studied. It was found that the drug stimulates the uptake of labelled leucine by cerebral cortex slices, has no effect on the incorporation of leucine into cerebral protein, neither in slices nor in vivo, but

  20. Tactile Teaching: Exploring Protein Structure/Function Using Physical Models

    Science.gov (United States)

    Herman, Tim; Morris, Jennifer; Colton, Shannon; Batiza, Ann; Patrick, Michael; Franzen, Margaret; Goodsell, David S.

    2006-01-01

    The technology now exists to construct physical models of proteins based on atomic coordinates of solved structures. We review here our recent experiences in using physical models to teach concepts of protein structure and function at both the high school and the undergraduate levels. At the high school level, physical models are used in a…

  1. Assessment and Challenges of Ligand Docking into Comparative Models of G-Protein Coupled Receptors

    DEFF Research Database (Denmark)

    Nguyen, E.D.; Meiler, J.; Norn, C.;

    2013-01-01

    The rapidly increasing number of high-resolution X-ray structures of G-protein coupled receptors (GPCRs) creates a unique opportunity to employ comparative modeling and docking to provide valuable insight into the function and ligand binding determinants of novel receptors, to assist in virtual...... screening and to design and optimize drug candidates. However, low sequence identity between receptors, conformational flexibility, and chemical diversity of ligands present an enormous challenge to molecular modeling approaches. It is our hypothesis that rapid Monte-Carlo sampling of protein backbone...

  2. Protein tethering enables rapid and label-free SERS platform for screening drugs of abuse (Conference Presentation)

    Science.gov (United States)

    Siddhanta, Soumik; Wróbel, Maciej S.; Barman, Ishan

    2017-02-01

    A quick, cost-effective method for detection of drugs of abuse in biological fluids would be of great value in healthcare, law enforcement, and home testing applications. The alarming rise in narcotics abuse has led to considerable focus on developing potent and versatile analytical tools that can address this societal problem. While laboratory testing plays a key role in the current detection of drug misuse and the evaluation of patients with drug induced intoxication, these typically require expensive reagents and trained personnel, and may take hours to complete. Thus, a significant unmet need is to engineer a facile method that can rapidly detect drugs with little sample preparation, especially the bound fraction that is typically dominant in the blood stream. Here we report an approach that combines the exquisite sensitivity of surface enhanced Raman spectroscopy (SERS) and a facile protein tethering mechanism to reliably detect four different classes of drugs, barbiturate, benzodiazepine, amphetamine and benzoylecgonine. The proposed approach harnesses the reliable and specific attachment of proteins to both drugs and nanoparticle to facilitate the enhancement of spectral markers that are sensitive to the presence of the drugs. In conjunction with chemometric tools, we have shown the ability to quantify these drugs lower than levels achievable by existing clinical immunoassays. Through molecular docking simulations, we also probe the mechanistic underpinnings of the protein tethering approach, opening the door to detection of a broad class of narcotics in biological fluids within a few minutes as well as for groundwater analysis and toxin detection.

  3. In silico structural characterization of protein targets for drug development against Trypanosoma cruzi.

    Science.gov (United States)

    Lima, Carlyle Ribeiro; Carels, Nicolas; Guimaraes, Ana Carolina Ramos; Tufféry, Pierre; Derreumaux, Philippe

    2016-10-01

    Trypanosoma cruzi is the protozoan pathogen responsible for Chagas disease, which is a major public health problem in tropical and subtropical regions of developing countries and particularly in Brazil. Despite many studies, there is no efficient treatment against Chagas disease, and the search for new therapeutic targets specific to T. cruzi is critical for drug development. Here, we have revisited 41 protein sequences proposed by the analogous enzyme pipeline, and found that it is possible to provide structures for T. cruzi sequences with clear homologs or analogs in H. sapiens and likely associated with trypanothione reductase, cysteine synthase, and ATPase functions, and structures for sequences specific to T. cruzi and absent in H. sapiens associated with 2,4-dienoyl-CoA reductase, and leishmanolysin activities. The implications of our structures refined by atomistic molecular dynamics (monomer or dimer states) in their in vitro environments (aqueous solution or membrane bilayers) are discussed for drug development and suggest that all protein targets, except cysteine synthase, merit further investigation.

  4. Physical and chemical gels of lipid nanoparticles for controlled delivery of lipophilic drugs and proteins

    Science.gov (United States)

    Couffin, Anne-Claude; Delmas, Thomas; Thomann, Jean-Sébastien; Cheibani, Ismail; Bayma, Eric; Heinrich, Emilie; Escudé, Marie; Courant, Thomas; Hoang, Antoine; Auzély, Rachel; Texier, Isabelle

    2013-05-01

    The controlled delivery of drugs and biologicals (proteins, antibodies, DNA and derivatives) is a growing need to take the full benefit of new therapeutic strategies. However these new molecules or biomolecules display solubility issues, or high degradation rates once injected. Therefore, both suitable delivery materials for their encapsulation and protection from the surrounding environment, and smart delivery devices (such as micro-needles or implanted pumps) are necessary to achieve controlled delivery of these precious therapeutic agents. We have developed bio-inspired gel materials, based on lipid nanoparticles which act as reservoirs for lipophilic drugs. The lipid nanoparticles, termed lipidots™, are biocompatible, colloidally stable, non-immunogenic, and obtained from a cheap and simple solvent-free process. The particles can be assembled to form physical or chemical gels, with tunable rheological properties. Physico-chemical studies have been carried out to determine the limits of the stability domains for colloidal and gel formulations (choice of surfactants for nanoparticle surface, and composition ratios of lipids, surfactants and co-surfactants). In particular, it is demonstrated that lipid nanoparticles keep their integrity in the gels. Gels of lipidots™ could therefore constitute biocompatible materials for the efficient encapsulation and tuned delivery of lipophilic drugs and biomolecules.

  5. Rodent models for Alzheimer’s disease drug discovery

    Science.gov (United States)

    Puzzo, Daniela; Gulisano, Walter; Palmeri, Agostino; Arancio, Ottavio

    2015-01-01

    Introduction Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by memory loss and personality changes, leading to dementia. Histophatological hallmarks are represented by aggregates of beta-amyloid peptide (Aβ) in senile plaques and deposition of hyperphosphorylated tau protein in neurofibrillary tangles in the brain. Rare forms of early onset familial Alzheimer's disease are due to gene mutations. This has prompted researchers to develop genetically modified animals that could recapitulate the main features of the disease. The use of these models is complemented by non-genetically modified animals. Area covered This review summarizes the characteristics of the most used transgenic (Tg) and non-Tg models of AD. The authors have focused on models mainly used in their laboratories including: APP Tg2576, APP/PS1, 3xAD, single h-Tau, non-Tg mice treated with acute injections of Aβ or tau, and models of physiological aging. Expert opinion Animal models of disease might be very useful for studying the pathophysiology of the disease and for testing new therapeutics in preclinical studies but they do not reproduce the entire clinical features of human AD. When selecting a model, researchers should consider the various factors that might influence the phenotype. They should also consider the timing of testing/treating animals since the age at which each model develops certain aspects of the AD pathology varies. PMID:25927677

  6. Differential representation of liver proteins in obese human subjects suggests novel biomarkers and promising targets for drug development in obesity.

    Science.gov (United States)

    Caira, Simonetta; Iannelli, Antonio; Sciarrillo, Rosaria; Picariello, Gianluca; Renzone, Giovanni; Scaloni, Andrea; Addeo, Pietro

    2017-12-01

    The proteome of liver biopsies from human obese (O) subjects has been compared to those of nonobese (NO) subjects using two-dimensional gel electrophoresis (2-DE). Differentially represented proteins were identified by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS)-based peptide mass fingerprinting (PMF) and nanoflow-liquid chromatography coupled to electrospray-tandem mass spectrometry (nLC-ESI-MS/MS). Overall, 61 gene products common to all of the liver biopsies were identified within 65 spots, among which 25 ones were differently represented between O and NO subjects. In particular, over-representation of short-chain acyl-CoA dehydrogenase, Δ(3,5)-Δ(2,4)dienoyl-CoA isomerase, acetyl-CoA acetyltransferase, glyoxylate reductase/hydroxypyruvate reductase, fructose-biphosphate aldolase B, peroxiredoxin I, protein DJ-1, catalase, α- and β-hemoglobin subunits, 3-mercaptopyruvate S-transferase, calreticulin, aminoacylase 1, phenazine biosynthesis-like domain-containing protein and a form of fatty acid-binding protein, together with downrepresentation of glutamate dehydrogenase, glutathione S-transferase A1, S-adenosylmethionine synthase 1A and a form of apolipoprotein A-I, was associated with the obesity condition. Some of these metabolic enzymes and antioxidant proteins have already been identified as putative diagnostic markers of liver dysfunction in animal models of steatosis or obesity, suggesting additional investigations on their role in these syndromes. Their differential representation in human liver was suggestive of their consideration as obesity human biomarkers and for the development of novel antiobesity drugs.

  7. Pharmacoinformatics elucidation of potential drug targets against migraine to target ion channel protein KCNK18

    Directory of Open Access Journals (Sweden)

    Sehgal SA

    2014-05-01

    Full Text Available Sheikh Arslan Sehgal, Mubashir Hassan, Sajid Rashid National Center for Bioinformatics, Quaid-i-Azam University, Islamabad, Pakistan Abstract: Migraine, a complex debilitating neurological disorder is strongly associated with potassium channel subfamily K member 18 (KCNK18. Research has emphasized that high levels of KCNK18 may be responsible for improper functioning of neurotransmitters, resulting in neurological disorders like migraine. In the present study, a hybrid approach of molecular docking and virtual screening were followed by pharmacophore identification and structure modeling. Screening was performed using a two-dimensional similarity search against recommended migraine drugs, keeping in view the physicochemical properties of drugs. LigandScout tool was used for exploring pharmacophore properties and designing novel molecules. Here, we report the screening of four novel compounds that have showed maximum binding affinity against KCNK18, obtained through the ZINC database, and Drug and Drug-Like libraries. Docking studies revealed that Asp-46, Ile-324, Ile-44, Gly-118, Leu-338, Val-113, and Phe-41 are critical residues for receptor–ligand interaction. A virtual screening approach coupled with docking energies and druglikeness rules illustrated that ergotamine and PB-414901692 are potential inhibitor compounds for targeting KCNK18. We propose that selected compounds may be more potent than the previously listed drug analogs based on the binding energy values. Further analysis of these inhibitors through site-directed mutagenesis could be helpful for exploring the details of ligand-binding pockets. Overall, the findings of this study may be helpful for designing novel therapeutic targets to cure migraine. Keywords: migraine, bioinformatics, modeling and docking, KCNK18, TRESK, virtual screening, pharmacoinformatics

  8. Application of the quality by design approach to the drug substance manufacturing process of an Fc fusion protein: towards a global multi-step design space.

    Science.gov (United States)

    Eon-duval, Alex; Valax, Pascal; Solacroup, Thomas; Broly, Hervé; Gleixner, Ralf; Strat, Claire L E; Sutter, James

    2012-10-01

    The article describes how Quality by Design principles can be applied to the drug substance manufacturing process of an Fc fusion protein. First, the quality attributes of the product were evaluated for their potential impact on safety and efficacy using risk management tools. Similarly, process parameters that have a potential impact on critical quality attributes (CQAs) were also identified through a risk assessment. Critical process parameters were then evaluated for their impact on CQAs, individually and in interaction with each other, using multivariate design of experiment techniques during the process characterisation phase. The global multi-step Design Space, defining operational limits for the entire drug substance manufacturing process so as to ensure that the drug substance quality targets are met, was devised using predictive statistical models developed during the characterisation study. The validity of the global multi-step Design Space was then confirmed by performing the entire process, from cell bank thawing to final drug substance, at its limits during the robustness study: the quality of the final drug substance produced under different conditions was verified against predefined targets. An adaptive strategy was devised whereby the Design Space can be adjusted to the quality of the input material to ensure reliable drug substance quality. Finally, all the data obtained during the process described above, together with data generated during additional validation studies as well as manufacturing data, were used to define the control strategy for the drug substance manufacturing process using a risk assessment methodology.

  9. Protein structure prediction: combining de novo modeling with sparse experimental data.

    Science.gov (United States)

    Latek, Dorota; Ekonomiuk, Dariusz; Kolinski, Andrzej

    2007-07-30

    Routine structure prediction of new folds is still a challenging task for computational biology. The challenge is not only in the proper determination of overall fold but also in building models of acceptable resolution, useful for modeling the drug interactions and protein-protein complexes. In this work we propose and test a comprehensive approach to protein structure modeling supported by sparse, and relatively easy to obtain, experimental data. We focus on chemical shift-based restraints from NMR, although other sparse restraints could be easily included. In particular, we demonstrate that combining the typical NMR software with artificial intelligence-based prediction of secondary structure enhances significantly the accuracy of the restraints for molecular modeling. The computational procedure is based on the reduced representation approach implemented in the CABS modeling software, which proved to be a versatile tool for protein structure prediction during the CASP (CASP stands for critical assessment of techniques for protein structure prediction) experiments (see http://predictioncenter/CASP6/org). The method is successfully tested on a small set of representative globular proteins of different size and topology, including the two CASP6 targets, for which the required NMR data already exist. The method is implemented in a semi-automated pipeline applicable to a large scale structural annotation of genomic data. Here, we limit the computations to relatively small set. This enabled, without a loss of generality, a detailed discussion of various factors determining accuracy of the proposed approach to the protein structure prediction.

  10. Insights into the structural biology of G-protein coupled receptors impacts drug design for central nervous system neurodegenerative processes

    OpenAIRE

    Dalet, Farfán-García Eunice; Guadalupe, Trujillo-Ferrara José; María del Carmen, Castillo-Hernández; Humberto, Guerra-Araiza Christian; Antonio, Soriano-Ursúa Marvin

    2013-01-01

    In the last few years, there have been important new insights into the structural biology of G-protein coupled receptors. It is now known that allosteric binding sites are involved in the affinity and selectivity of ligands for G-protein coupled receptors, and that signaling by these receptors involves both G-protein dependent and independent pathways. The present review outlines the physiological and pharmacological implications of this perspective for the design of new drugs to treat disord...

  11. Protein comparative sequence analysis and computer modeling.

    Science.gov (United States)

    Hambly, Brett D; Oakley, Cecily E; Fajer, Piotr G

    2008-01-01

    A problem frequently encountered by the biological scientist is the identification of a previously unknown gene or protein sequence, where there are few or no clues as to the biochemical function, ligand specificity, gene regulation, protein-protein interactions, tissue specificity, cellular localization, developmental phase of activity, or biological role. Through the process of bioinformatics there are now many approaches for predicting answers to at least some of these questions, often then allowing the design of more insightful experiments to characterize more definitively the new protein.

  12. Structured representation of drug indications: lexical and semantic analysis and object-oriented modeling.

    Science.gov (United States)

    Duclos, C; Venot, A

    2000-03-01

    No standardized representation of drug indications is currently available that could be used in drug knowledge bases. We describe an object-oriented representation of indications that should make it possible to develop new tools for selecting drugs and checking prescriptions in computerized drug prescription systems. The model was developed using the results of a lexical and semantic analysis of drug indications, collected into a single file and processed using natural language processing software. It distinguishes both the diseases for which the drug may be given and the efficiency of the drug for a given indication. Two aspects of the model were evaluated: the differences if two independent evaluators filled the attributes independently and the loss of information induced by the use of the model. A system based on this model, making it possible for the physician to select all the drugs satisfying various criteria, is also presented.

  13. SVM Based Descriptor Selection and Classification of Neurodegenerative Disease Drugs for Pharmacological Modeling.

    Science.gov (United States)

    Shahid, Mohammad; Shahzad Cheema, Muhammad; Klenner, Alexander; Younesi, Erfan; Hofmann-Apitius, Martin

    2013-03-01

    Systems pharmacological modeling of drug mode of action for the next generation of multitarget drugs may open new routes for drug design and discovery. Computational methods are widely used in this context amongst which support vector machines (SVM) have proven successful in addressing the challenge of classifying drugs with similar features. We have applied a variety of such SVM-based approaches, namely SVM-based recursive feature elimination (SVM-RFE). We use the approach to predict the pharmacological properties of drugs widely used against complex neurodegenerative disorders (NDD) and to build an in-silico computational model for the binary classification of NDD drugs from other drugs. Application of an SVM-RFE model to a set of drugs successfully classified NDD drugs from non-NDD drugs and resulted in overall accuracy of ∼80 % with 10 fold cross validation using 40 top ranked molecular descriptors selected out of total 314 descriptors. Moreover, SVM-RFE method outperformed linear discriminant analysis (LDA) based feature selection and classification. The model reduced the multidimensional descriptors space of drugs dramatically and predicted NDD drugs with high accuracy, while avoiding over fitting. Based on these results, NDD-specific focused libraries of drug-like compounds can be designed and existing NDD-specific drugs can be characterized by a well-characterized set of molecular descriptors.

  14. Assessing the structural conservation of protein pockets to study functional and allosteric sites: implications for drug discovery

    Directory of Open Access Journals (Sweden)

    Daura Xavier

    2010-03-01

    Full Text Available Abstract Background With the classical, active-site oriented drug-development approach reaching its limits, protein ligand-binding sites in general and allosteric sites in particular are increasingly attracting the interest of medicinal chemists in the search for new types of targets and strategies to drug development. Given that allostery represents one of the most common and powerful means to regulate protein function, the traditional drug discovery approach of targeting active sites can be extended by targeting allosteric or regulatory protein pockets that may allow the discovery of not only novel drug-like inhibitors, but activators as well. The wealth of available protein structural data can be exploited to further increase our understanding of allosterism, which in turn may have therapeutic applications. A first step in this direction is to identify and characterize putative effector sites that may be present in already available structural data. Results We performed a large-scale study of protein cavities as potential allosteric and functional sites, by integrating publicly available information on protein sequences, structures and active sites for more than a thousand protein families. By identifying common pockets across different structures of the same protein family we developed a method to measure the pocket's structural conservation. The method was first parameterized using known active sites. We characterized the predicted pockets in terms of sequence and structural conservation, backbone flexibility and electrostatic potential. Although these different measures do not tend to correlate, their combination is useful in selecting functional and regulatory sites, as a detailed analysis of a handful of protein families shows. We finally estimated the numbers of potential allosteric or regulatory pockets that may be present in the data set, finding that pockets with putative functional and effector characteristics are widespread across

  15. Binding and inhibition of drug transport proteins by heparin: a potential drug transporter modulator capable of reducing multidrug resistance in human cancer cells.

    Science.gov (United States)

    Chen, Yunliang; Scully, Michael; Petralia, Gloria; Kakkar, Ajay

    2014-01-01

    A major problem in cancer treatment is the development of resistance to chemotherapeutic agents, multidrug resistance (MDR), associated with increased activity of transmembrane drug transporter proteins which impair cytotoxic treatment by rapidly removing the drugs from the targeted cells. Previously, it has been shown that heparin treatment of cancer patients undergoing chemotherapy increases survival. In order to determine whether heparin is capable reducing MDR and increasing the potency of chemotherapeutic drugs, the cytoxicity of a number of agents toward four cancer cell lines (a human enriched breast cancer stem cell line, two human breast cancer cell lines, MCF-7 and MDA-MB-231, and a human lung cancer cell line A549) was tested in the presence or absence of heparin. Results demonstrated that heparin increased the cytotoxicity of a range of chemotherapeutic agents. This effect was associated with the ability of heparin to bind to several of the drug transport proteins of the ABC and non ABC transporter systems. Among the ABC system, heparin treatment caused significant inhibition of the ATPase activity of ABCG2 and ABCC1, and of the efflux function observed as enhanced intracellular accumulation of specific substrates. Doxorubicin cytoxicity, which was enhanced by heparin treatment of MCF-7 cells, was found to be under the control of one of the major non-ABC transporter proteins, lung resistance protein (LRP). LRP was also shown to be a heparin-binding protein. These findings indicate that heparin has a potential role in the clinic as a drug transporter modulator to reduce multidrug resistance in cancer patients.

  16. Design and Characterization of a Silk-Fibroin-Based Drug Delivery Platform Using Naproxen as a Model Drug

    Directory of Open Access Journals (Sweden)

    Tatyana Dyakonov

    2012-01-01

    Full Text Available The objective of this proof-of-concept study was to develop a platform for controlled drug delivery based on silk fibroin (SF and to explore the feasibility of using SF in oral drug delivery. The SF-containing matrixes were prepared via spray-drying and film casting, and the release profile of the model drug naproxen sodium was evaluated. Attenuated total reflectance Fourier transform infrared spectroscopy (FTIR has been used to observe conformational changes in SF- and drug-containing compositions. SF-based films, spray-dried microparticles, and matrixes loaded with naproxen were prepared. Both FTIR spectra and in vitro dissolution data demonstrated that SF β-sheet conformation regulates the release profile of naproxen. The controlled release characteristics of the SF-containing compositions were evaluated as a function of SF concentration, temperature, and exposure to dehydrating solvents. The results suggest that SF may be an attractive polymer for use in controlled drug delivery systems.

  17. Viral M2 ion channel protein: a promising target for anti-influenza drug discovery.

    Science.gov (United States)

    Moorthy, N S Hari Narayana; Poongavanam, Vasanthanathan; Pratheepa, V

    2014-01-01

    Influenza virus is an important RNA virus causing pandemics (Spanish Flu (1918), Asian Flu (1957), Hong Kong Flu (1968) and Swine Flu (2009)) over the last decades. Due to the spontaneous mutations of these viral proteins, currently available antiviral and anti-influenza drugs quickly develop resistance. To account this, only limited antiinfluenza drugs have been approved for the therapeutic use. These include amantadine and rimantadine (M2 proton channel blockers), zanamivir, oseltamivir and peramivir (neuraminidase inhibitors), favipravir (polymerase inhibitor) and laninamivir. This review provides an outline on the strategies to develop novel, potent chemotherapeutic agents against M2 proton channel. Primarily, the M2 proton channel blockers elicit pharmacological activity through destabilizing the helices by blocking the proton transport across the transmembrane. The biologically important compounds discovered using the scaffolds such as bisnoradmantane, noradamantane, triazine, spiroadamantane, isoxazole, amino alcohol, azaspiro, spirene, pinanamine, etc are reported to exhibit anti-influenza activity against wild or mutant type (S31N and V27A) of M2 proton channel protein. The reported studies explained that the adamantane based compounds (amantadine and rimantadine) strongly interact with His37 (through hydrogen bonding) and Ala30, Ile33 and Gly34 residues (hydrophobic interactions). The adamantane and the non-adamantane scaffolds fit perfectly in the active site pocket present in the wild type and the charged amino groups (ammonium) create positive electrostatic potential, which blocks the transport of protons across the pore. In the mutated proteins, larger or smaller binding pocket are created by small or large mutant residues, which do not allow the molecules fit in the active site. This causes the channel to be unblocked and the protons are allowed to transfer inside the pore. The structural analysis of the M2 proton channel blockers illustrated that

  18. Target identification of grape seed extract in colorectal cancer using drug affinity responsive target stability (DARTS) technique: role of endoplasmic reticulum stress response proteins.

    Science.gov (United States)

    Derry, Molly M; Somasagara, Ranganatha R; Raina, Komal; Kumar, Sushil; Gomez, Joe; Patel, Manisha; Agarwal, Rajesh; Agarwal, Chapla

    2014-01-01

    Various natural agents, including grape seed extract (GSE), have shown considerable chemopreventive and anti-cancer efficacy against different cancers in pre-clinical studies; however, their specific protein targets are largely unknown and thus, their clinical usefulness is marred by limited scientific evidences about their direct cellular targets. Accordingly, herein, employing, for the first time, the recently developed drug affinity responsive target stability (DARTS) technique, we aimed to profile the potential protein targets of GSE in human colorectal cancer (CRC) cells. Unlike other methods, which can cause chemical alteration of the drug components to allow for detection, this approach relies on the fact that a drug bound protein may become less susceptible to proteolysis and hence the enriched proteins can be detected by Mass Spectroscopy methods. Our results, utilizing the DARTS technique followed by examination of the spectral output by LC/MS and the MASCOT data, revealed that GSE targets endoplasmic reticulum (ER) stress response proteins resulting in overall down regulation of proteins involved in translation and that GSE also causes oxidative protein modifications, specifically on methionine amino acids residues on its protein targets. Corroborating these findings, mechanistic studies revealed that GSE indeed caused ER stress and strongly inhibited PI3k-Akt-mTOR pathway for its biological effects in CRC cells. Furthermore, bioenergetics studies indicated that GSE also interferes with glycolysis and mitochondrial metabolism in CRC cells. Together, the present study identifying GSE molecular targets in CRC cells, combined with its efficacy in vast pre-clinical CRC models, further supports its usefulness for CRC prevention and treatment.

  19. Mechanical Modeling and Computer Simulation of Protein Folding

    Science.gov (United States)

    Prigozhin, Maxim B.; Scott, Gregory E.; Denos, Sharlene

    2014-01-01

    In this activity, science education and modern technology are bridged to teach students at the high school and undergraduate levels about protein folding and to strengthen their model building skills. Students are guided from a textbook picture of a protein as a rigid crystal structure to a more realistic view: proteins are highly dynamic…

  20. Modeling of the human rhinovirus C capsid suggests possible causes for antiviral drug resistance.

    Science.gov (United States)

    Basta, Holly A; Ashraf, Shamaila; Sgro, Jean-Yves; Bochkov, Yury A; Gern, James E; Palmenberg, Ann C

    2014-01-05

    Human rhinoviruses of the RV-C species are recently discovered pathogens with greater clinical significance than isolates in the RV-A+B species. The RV-C cannot be propagated in typical culture systems; so much of the virology is necessarily derivative, relying on comparative genomics, relative to the better studied RV-A+B. We developed a bioinformatics-based structural model for a C15 isolate. The model showed the VP1-3 capsid proteins retain their fundamental cores relative to the RV-A+B, but conserved, internal RV-C residues affect the shape and charge of the VP1 hydrophobic pocket that confers antiviral drug susceptibility. When predictions of the model were tested in organ cultures or ALI systems with recombinant C15 virus, there was a resistance to capsid-binding drugs, including pleconaril, BTA-188, WIN56291, WIN52035 and WIN52084. Unique to all RV-C, the model predicts conserved amino acids within the pocket and capsid surface pore leading to the pocket may correlate with this activity.

  1. Skin models for the testing of transdermal drugs

    Directory of Open Access Journals (Sweden)

    Abd E

    2016-10-01

    Full Text Available Eman Abd,1 Shereen A Yousef,1 Michael N Pastore,2 Krishna Telaprolu,1 Yousuf H Mohammed,1 Sarika Namjoshi,1 Jeffrey E Grice,1 Michael S Roberts1,2 1Translational Research Institute, School of Medicine, University of Queensland, Brisbane, 2School of Pharmacy and Medical Sciences, University of South Australia, Adelaide, Australia Abstract: The assessment of percutaneous permeation of molecules is a key step in the evaluation of dermal or transdermal delivery systems. If the drugs are intended for delivery to humans, the most appropriate setting in which to do the assessment is the in vivo human. However, this may not be possible for ethical, practical, or economic reasons, particularly in the early phases of development. It is thus necessary to find alternative methods using accessible and reproducible surrogates for in vivo human skin. A range of models has been developed, including ex vivo human skin, usually obtained from cadavers or plastic surgery patients, ex vivo animal skin, and artificial or reconstructed skin models. Increasingly, largely driven by regulatory authorities and industry, there is a focus on developing standardized techniques and protocols. With this comes the need to demonstrate that the surrogate models produce results that correlate with those from in vivo human studies and that they can be used to show bioequivalence of different topical products. This review discusses the alternative skin models that have been developed as surrogates for normal and diseased skin and examines the concepts of using model systems for in vitro–in vivo correlation and the demonstration of bioequivalence. Keywords: percutaneous permeation, dermal delivery, transdermal, bioequivalence, ex vivo skin models, reconstructed skin

  2. Physiologically Based Pharmacokinetic Modeling to Predict Drug-Drug Interactions with Efavirenz Involving Simultaneous Inducing and Inhibitory Effects on Cytochromes.

    Science.gov (United States)

    Marzolini, Catia; Rajoli, Rajith; Battegay, Manuel; Elzi, Luigia; Back, David; Siccardi, Marco

    2017-04-01

    Antiretroviral drugs are among the therapeutic agents with the highest potential for drug-drug interactions (DDIs). In the absence of clinical data, DDIs are mainly predicted based on preclinical data and knowledge of the disposition of individual drugs. Predictions can be challenging, especially when antiretroviral drugs induce and inhibit multiple cytochrome P450 (CYP) isoenzymes simultaneously. This study predicted the magnitude of the DDI between efavirenz, an inducer of CYP3A4 and inhibitor of CYP2C8, and dual CYP3A4/CYP2C8 substrates (repaglinide, montelukast, pioglitazone, paclitaxel) using a physiologically based pharmacokinetic (PBPK) modeling approach integrating concurrent effects on CYPs. In vitro data describing the physicochemical properties, absorption, distribution, metabolism, and elimination of efavirenz and CYP3A4/CYP2C8 substrates as well as the CYP-inducing and -inhibitory potential of efavirenz were obtained from published literature. The data were integrated in a PBPK model developed using mathematical descriptions of molecular, physiological, and anatomical processes defining pharmacokinetics. Plasma drug-concentration profiles were simulated at steady state in virtual individuals for each drug given alone or in combination with efavirenz. The simulated pharmacokinetic parameters of drugs given alone were compared against existing clinical data. The effect of efavirenz on CYP was compared with published DDI data. The predictions indicate that the overall effect of efavirenz on dual CYP3A4/CYP2C8 substrates is induction of metabolism. The magnitude of induction tends to be less pronounced for dual CYP3A4/CYP2C8 substrates with predominant CYP2C8 metabolism. PBPK modeling constitutes a useful mechanistic approach for the quantitative prediction of DDI involving simultaneous inducing or inhibitory effects on multiple CYPs as often encountered with antiretroviral drugs.

  3. In Pursuit of Fully Flexible Protein-Ligand Docking: Modeling the Bilateral Mechanism of Binding.

    Science.gov (United States)

    Henzler, Angela M; Rarey, Matthias

    2010-03-15

    Modern structure-based drug design aims at accounting for the intrinsic flexibility of therapeutic relevant targets. Over the last few years a considerable amount of docking approaches that encounter this challenging problem has emerged. Here we provide the readership with an overview of established methods for fully flexible protein-ligand docking and current developments in the field. All methods are based on one of two fundamental models which describe the dynamic behavior of proteins upon ligand binding. Methods for ensemble docking (ED) model the protein conformational change before the ligand is placed, whereas induced-fit docking (IFD) optimizes the protein structure afterwards. A third category of docking approaches is formed by recent approaches that follow both concepts. This categorization allows to comprehensively discover strengths and weaknesses of the individual processes and to extract information for their applicability in real world docking scenarios.

  4. Prediction of protein-protein interactions between viruses and human by an SVM model

    Directory of Open Access Journals (Sweden)

    Cui Guangyu

    2012-05-01

    Full Text Available Abstract Background Several computational methods have been developed to predict protein-protein interactions from amino acid sequences, but most of those methods are intended for the interactions within a species rather than for interactions across different species. Methods for predicting interactions between homogeneous proteins are not appropriate for finding those between heterogeneous proteins since they do not distinguish the interactions between proteins of the same species from those of different species. Results We developed a new method for representing a protein sequence of variable length in a frequency vector of fixed length, which encodes the relative frequency of three consecutive amino acids of a sequence. We built a support vector machine (SVM model to predict human proteins that interact with virus proteins. In two types of viruses, human papillomaviruses (HPV and hepatitis C virus (HCV, our SVM model achieved an average accuracy above 80%, which is higher than that of another SVM model with a different representation scheme. Using the SVM model and Gene Ontology (GO annotations of proteins, we predicted new interactions between virus proteins and human proteins. Conclusions Encoding the relative frequency of amino acid triplets of a protein sequence is a simple yet powerful representation method for predicting protein-protein interactions across different species. The representation method has several advantages: (1 it enables a prediction model to achieve a better performance than other representations, (2 it generates feature vectors of fixed length regardless of the sequence length, and (3 the same representation is applicable to different types of proteins.

  5. Enzymatic prenylation and oxime ligation for the synthesis of stable and homogeneous protein-drug conjugates for targeted therapy.

    Science.gov (United States)

    Lee, Joong-Jae; Choi, Hyo-Jung; Yun, Misun; Kang, YingJin; Jung, Ji-Eun; Ryu, Yiseul; Kim, Tae Yoon; Cha, Young-Je; Cho, Hyun-Soo; Min, Jung-Joon; Chung, Chul-Woong; Kim, Hak-Sung

    2015-10-05

    Targeted therapy based on protein-drug conjugates has attracted significant attention owing to its high efficacy and low side effects. However, efficient and stable drug conjugation to a protein binder remains a challenge. Herein, a chemoenzymatic method to generate highly stable and homogenous drug conjugates with high efficiency is presented. The approach comprises the insertion of the CaaX sequence at the C-terminal end of the protein binder, prenylation using farnesyltransferase, and drug conjugation through an oxime ligation reaction. MMAF and an EGFR-specific repebody are used as the antitumor agent and protein binder, respectively. The method enables the precisely controlled synthesis of repebody-drug conjugates with high yield and homogeneity. The utility of this approach is illustrated by the notable stability of the repebody-drug conjugates in human plasma, negligible off-target effects, and a remarkable antitumor activity in vivo. The present method can be widely used for generating highly homogeneous and stable PDCs for targeted therapy.

  6. Old and new therapeutics for Rheumatoid Arthritis: in vivo models and drug development.

    Science.gov (United States)

    Sardar, Samra; Andersson, Åsa

    2016-01-01

    Development of novel drugs for treatment of chronic inflammatory diseases is to a large extent dependent on the availability of good experimental in vivo models in order to perform preclinical tests of new drugs and for the identification of novel drug targets. Here, we review a number of existing rodent models for Rheumatoid Arthritis in the context of how these models have been utilized for developing established therapy in Rheumatoid Arthritis and, furthermore, the present use of animal models for studies of novel drug candidates. We have studied the literature in the field for the use of in vivo models during development of anti-rheumatic drugs; from Methotrexate to various antibody treatments, to novel drugs that are, or have recently been, in clinical trials. For novel drugs, we have explored websites for clinical trials. Although a single Rheumatoid Arthritis in vivo model cannot mirror the complexity of disease development, there exist a number of good animal models for Rheumatoid Arthritis, each defining some parts in disease development, which are useful for studies of drug response. We find that many of the established drugs were not tested in in vivo models before being used in the clinic, but rather animal models have been subsequently used to find mechanisms for efficacy. Finally, we report a number of novel drugs, tested in preclinical in vivo models, presently in clinical trials.

  7. The Mesenteric Lymph Duct Cannulated Rat Model: Application to the Assessment of Intestinal Lymphatic Drug Transport

    Science.gov (United States)

    Trevaskis, Natalie L.; Hu, Luojuan; Caliph, Suzanne M.; Han, Sifei; Porter, Christopher J.H.

    2015-01-01

    The intestinal lymphatic system plays key roles in fluid transport, lipid absorption and immune function. Lymph flows directly from the small intestine via a series of lymphatic vessels and nodes that converge at the superior mesenteric lymph duct. Cannulation of the mesenteric lymph duct thus enables the collection of mesenteric lymph flowing from the intestine. Mesenteric lymph consists of a cellular fraction of immune cells (99% lymphocytes), aqueous fraction (fluid, peptides and proteins such as cytokines and gut hormones) and lipoprotein fraction (lipids, lipophilic molecules and apo-proteins). The mesenteric lymph duct cannulation model can therefore be used to measure the concentration and rate of transport of a range of factors from the intestine via the lymphatic system. Changes to these factors in response to different challenges (e.g., diets, antigens, drugs) and in disease (e.g., inflammatory bowel disease, HIV, diabetes) can also be determined. An area of expanding interest is the role of lymphatic transport in the absorption of orally administered lipophilic drugs and prodrugs that associate with intestinal lipid absorption pathways. Here we describe, in detail, a mesenteric lymph duct cannulated rat model which enables evaluation of the rate and extent of lipid and drug transport via the lymphatic system for several hours following intestinal delivery. The method is easily adaptable to the measurement of other parameters in lymph. We provide detailed descriptions of the difficulties that may be encountered when establishing this complex surgical method, as well as representative data from failed and successful experiments to provide instruction on how to confirm experimental success and interpret the data obtained. PMID:25866901

  8. Inhibition of Wnt signalling and breast tumour growth by the multi-purpose drug suramin through suppression of heterotrimeric G proteins and Wnt endocytosis.

    Science.gov (United States)

    Koval, Alexey; Ahmed, Kamal; Katanaev, Vladimir L

    2016-02-15

    Overactivation of the Wnt signalling pathway underlies oncogenic transformation and proliferation in many cancers, including the triple-negative breast cancer (TNBC), the deadliest form of tumour in the breast, taking about a quarter of a million lives annually worldwide. No clinically approved targeted therapies attacking Wnt signalling currently exist. Repositioning of approved drugs is a promising approach in drug discovery. In the present study we show that a multi-purpose drug suramin inhibits Wnt signalling and proliferation of TNBC cells in vitro and in mouse models, inhibiting a component in the upper levels of the pathway. Through a set of investigations we identify heterotrimeric G proteins and regulation of Wnt endocytosis as the likely target of suramin in this pathway. G protein-dependent endocytosis of plasma membrane-located components of the Wnt pathway was previously shown to be important for amplification of the signal in this cascade. Our data identify endocytic regulation within Wnt signalling as a promising target for anti-Wnt and anti-cancer drug discovery. Suramin, as the first example of such drug or its analogues might pave the way for the appearance of first-in-class targeted therapies against TNBC and other Wnt-dependent cancers.

  9. Critical analysis of the successes and failures of homology models of G protein-coupled receptors.

    Science.gov (United States)

    Bhattacharya, Supriyo; Lam, Alfonso Ramon; Li, Hubert; Balaraman, Gouthaman; Niesen, Michiel Jacobus Maria; Vaidehi, Nagarajan

    2013-05-01

    We present a critical assessment of the performance of our homology model refinement method for G protein-coupled receptors (GPCRs), called LITICon that led to top ranking structures in a recent structure prediction assessment GPCRDOCK2010. GPCRs form the largest class of drug targets for which only a few crystal structures are currently available. Therefore, accurate homology models are essential for drug design in these receptors. We submitted five models each for human chemokine CXCR4 (bound to small molecule IT1t and peptide CVX15) and dopamine D3DR (bound to small molecule eticlopride) before the crystal structures were published. Our models in both CXCR4/IT1t and D3/eticlopride assessments were ranked first and second, respectively, by ligand RMSD to the crystal structures. For both receptors, we developed two types of protein models: homology models based on known GPCR crystal structures, and ab initio models based on the prediction method MembStruk. The homology-based models compared better to the crystal structures than the ab initio models. However, a robust refinement procedure for obtaining high accuracy structures is needed. We demonstrate that optimization of the helical tilt, rotation, and translation is vital for GPCR homology model refinement. As a proof of concept, our in-house refinement program LITiCon captured the distinct orientation of TM2 in CXCR4, which differs from that of adrenoreceptors. These findings would be critical for refining GPCR homology models in future. Copyright © 2012 Wiley Periodicals, Inc.

  10. Hydrodynamic multibead modeling: problems, pitfalls, and solutions. 2. Proteins.

    Science.gov (United States)

    Zipper, Peter; Durchschlag, Helmut

    2010-02-01

    Hydrodynamic models of proteins have been generated by recourse to crystallographic data and applying a filling model strategy in order to predict both hydrodynamic and scattering parameters. The design of accurate protein models retaining the majority of the molecule peculiarities requires usage of many beads and consideration of many serious problems. Applying the expertise obtained with ellipsoid models and pilot tests on proteins, we succeeded in constructing precise models for several anhydrous and hydrated proteins of different shape, size, and complexity. The models constructed consist of many beads (up to about 11,000) for the protein constituents (atoms, amino acid residues, groups) and preferentially bound water molecules. While in the case of small proteins, parameter predictions are straightforward, computations for giant proteins necessitate drastic reductions of the number of initially available beads. Among several auxiliary programs, our advanced hydration programs, HYDCRYST and HYDMODEL, and modified versions of García de la Torre's program HYDRO were successfully employed. This allowed the generation of realistic protein models by imaging details of their fine structure and enabled the prediction of reliable molecular parameters including intrinsic viscosities. The appearance of the models and the agreement of molecular properties and distance distribution functions p(r) of unreduced and reduced models can be used for a meticulous inspection of the data obtained.

  11. Protein adsorption on nanoparticles: model development using computer simulation

    Science.gov (United States)

    Shao, Qing; Hall, Carol K.

    2016-10-01

    The adsorption of proteins on nanoparticles results in the formation of the protein corona, the composition of which determines how nanoparticles influence their biological surroundings. We seek to better understand corona formation by developing models that describe protein adsorption on nanoparticles using computer simulation results as data. Using a coarse-grained protein model, discontinuous molecular dynamics simulations are conducted to investigate the adsorption of two small proteins (Trp-cage and WW domain) on a model nanoparticle of diameter 10.0 nm at protein concentrations ranging from 0.5 to 5 mM. The resulting adsorption isotherms are well described by the Langmuir, Freundlich, Temkin and Kiselev models, but not by the Elovich, Fowler-Guggenheim and Hill-de Boer models. We also try to develop a generalized model that can describe protein adsorption equilibrium on nanoparticles of different diameters in terms of dimensionless size parameters. The simulation results for three proteins (Trp-cage, WW domain, and GB3) on four nanoparticles (diameter  =  5.0, 10.0, 15.0, and 20.0 nm) illustrate both the promise and the challenge associated with developing generalized models of protein adsorption on nanoparticles.

  12. Relationship between Methylation Status of Multi-drug Resistance Protein(MRP) and Multi-drug Resistance in Lung Cancer Cell Lines

    Institute of Scientific and Technical Information of China (English)

    LIU Rui-jun; ZHONG Hong

    2007-01-01

    Objective: To study the relationship between the methylation status of multi-drug resistance protein (MRP) gene and the expression of its mRNA and protein in lung cancer cell lines. Methods: Human embryo lung cell line WI-38, lung adenocarcinoma cell line SPCA-1 and its drug-resistant cells induced by different concentrations of doxorubicin were treated with restriction endonuclease Eco47Ⅲ. The methylation status of MRP was examined by PCR, and the expressions of its mRNA and protein were evaluated by in situ hybridization and immunohistochemistry. Results: MRP gene promoter region of WI-38 cells was in hypermethylation status, but the promoter region of MRP in SPCA-1 cells and their resistant derivatives induced by different concentrations of doxorubicin were in hypomethylation status. There were significant differences in the expression of MRP mRNA among WI-38 cell line, SPCA-1 cells and their drug-resistant derivatives induced by different concentration of doxorubicin. Consistently, MRP immunostaining presented similar significant differences. Conclusion: The promoter region of MRP in SPCA-1 lung adenocarcinoma cells was in hypomethylation status. The hypomethylation status of 5' regulatory region of MRP promoter is an important structural basis that can increase the activity of transcription and results in the development of drug resistance in lung cancer.

  13. RNA and protein 3D structure modeling: similarities and differences.

    Science.gov (United States)

    Rother, Kristian; Rother, Magdalena; Boniecki, Michał; Puton, Tomasz; Bujnicki, Janusz M

    2011-09-01

    In analogy to proteins, the function of RNA depends on its structure and dynamics, which are encoded in the linear sequence. While there are numerous methods for computational prediction of protein 3D structure from sequence, there have been very few such methods for RNA. This review discusses template-based and template-free approaches for macromolecular structure prediction, with special emphasis on comparison between the already tried-and-tested methods for protein structure modeling and the very recently developed "protein-like" modeling methods for RNA. We highlight analogies between many successful methods for modeling of these two types of biological macromolecules and argue that RNA 3D structure can be modeled using "protein-like" methodology. We also highlight the areas where the differences between RNA and proteins require the development of RNA-specific solutions.

  14. Interaction of S-layer proteins of Lactobacillus kefir with model membranes and cells.

    Science.gov (United States)

    Hollmann, Axel; Delfederico, Lucrecia; Santos, Nuno Correia; Disalvo, E Anibal; Semorile, Liliana

    2017-01-12

    In previous works, it was shown that S-layer proteins from Lactobacillus kefir were able to recrystallize and stabilize liposomes, this feature reveling a great potential for developing liposomal-based carriers. Despite previous studies on this subject are important milestones, a number of questions remain unanswered; In this context, the feasibility of S-layer proteins as a biomaterial for drug delivery was evaluated in this work. First, S-layer proteins were fully characterized by Electron microscopy, 2D-electrophoresis, and HPAEC-PAD. Afterward, interactions of S-layer proteins with model lipid membranes were evaluated, showing that proteins adsorb to the lipid surface following a non-fickean or anomalous diffusion, when positively charged lipid were employed, suggesting that electrostatic interaction is a key factor in the recrystallization process on these proteins. Finally, the interaction of S-layer coated liposomes with CACO-2 cell line was assessed, First cytotoxicity of formulations was tested showing noncytotoxic effects in S-layer coated vesicles. Second, by flow cytometry, it was observed an increased ability to transfer cargo molecules into CACO-2 cells from S-layer coated liposomes in comparison to control ones. All data put together, supporting the idea that a combination of adhesive properties of S-layer proteins concomitant with higher stability of S-layer coated liposomes represents an exciting starting point in the development of new drug carriers.

  15. Structure of liposome encapsulating proteins characterized by X-ray scattering and shell-modeling

    Energy Technology Data Exchange (ETDEWEB)

    Hirai, Mitsuhiro, E-mail: mhirai@gunma-u.ac.jp; Kimura, Ryota; Takeuchi, Kazuki; Hagiwara, Yoshihiko [Gunma University, 4-2 Aramaki, Maebashi, Gunma 371-8510 (Japan); Kawai-Hirai, Rika [Gunma University, 3-39-15 Shouwa, Maebashi 371-8512 (Japan); Ohta, Noboru [JASRI, 1-1-1 Kuoto, Sayo-cho, Sayo-gun, Hyogo 679-5198 (Japan); Igarashi, Noriyuki; Shimuzu, Nobutaka [KEK-PF, 1-1 Oho, Tsukuba, Ibaraki 305-0801 (Japan)

    2013-11-01

    Wide-angle X-ray scattering data using a third-generation synchrotron radiation source are presented. Lipid liposomes are promising drug delivery systems because they have superior curative effects owing to their high adaptability to a living body. Lipid liposomes encapsulating proteins were constructed and the structures examined using synchrotron radiation small- and wide-angle X-ray scattering (SR-SWAXS). The liposomes were prepared by a sequential combination of natural swelling, ultrasonic dispersion, freeze-throw, extrusion and spin-filtration. The liposomes were composed of acidic glycosphingolipid (ganglioside), cholesterol and phospholipids. By using shell-modeling methods, the asymmetric bilayer structure of the liposome and the encapsulation efficiency of proteins were determined. As well as other analytical techniques, SR-SWAXS and shell-modeling methods are shown to be a powerful tool for characterizing in situ structures of lipid liposomes as an important candidate of drug delivery systems.

  16. Tracking membrane protein association in model membranes.

    Directory of Open Access Journals (Sweden)

    Myriam Reffay

    Full Text Available Membrane proteins are essential in the exchange processes of cells. In spite of great breakthrough in soluble proteins studies, membrane proteins structures, functions and interactions are still a challenge because of the difficulties related to their hydrophobic properties. Most of the experiments are performed with detergent-solubilized membrane proteins. However widely used micellar systems are far from the biological two-dimensions membrane. The development of new biomimetic membrane systems is fundamental to tackle this issue.We present an original approach that combines the Fluorescence Recovery After fringe Pattern Photobleaching technique and the use of a versatile sponge phase that makes it possible to extract crucial informations about interactions between membrane proteins embedded in the bilayers of a sponge phase. The clear advantage lies in the ability to adjust at will the spacing between two adjacent bilayers. When the membranes are far apart, the only possible interactions occur laterally between proteins embedded within the same bilayer, whereas when membranes get closer to each other, interactions between proteins embedded in facing membranes may occur as well.After validating our approach on the streptavidin-biotinylated peptide complex, we study the interactions between two membrane proteins, MexA and OprM, from a Pseudomonas aeruginosa efflux pump. The mode of interaction, the size of the protein complex and its potential stoichiometry are determined. In particular, we demonstrate that: MexA is effectively embedded in the bilayer; MexA and OprM do not interact laterally but can form a complex if they are embedded in opposite bilayers; the population of bound proteins is at its maximum for bilayers separated by a distance of about 200 A, which is the periplasmic thickness of Pseudomonas aeruginosa. We also show that the MexA-OprM association is enhanced when the position and orientation of the protein is restricted by the

  17. From Genomes to Protein Models and Back

    Science.gov (United States)

    Tramontano, Anna; Giorgetti, Alejandro; Orsini, Massimiliano; Raimondo, Domenico

    2007-12-01

    The alternative splicing mechanism allows genes to generate more than one product. When the splicing events occur within protein coding regions they can modify the biological function of the protein. Alternative splicing has been suggested as one way for explaining the discrepancy between the number of human genes and functional complexity. We analysed the putative structure of the alternatively spliced gene products annotated in the ENCODE pilot project and discovered that many of the potential alternative gene products will be unlikely to produce stable functional proteins.

  18. Modelling Formation of a Drug Reservoir in the Stratum Corneum and Its Impact on Drug Monitoring Using Reverse Iontophoresis

    Directory of Open Access Journals (Sweden)

    Yvonne Paulley

    2010-01-01

    Full Text Available Reverse iontophoresis is a relatively new technique for non-invasive drug monitoring in the body. It involves a small electrical current being passed through the skin to facilitate the movement of small charged ions and polar molecules on the skin's surface where the amount of drug can then be measured and hence an accurate estimate of the blood concentration can be made. In vivo studies for several molecules show that initially large amounts of drug are extracted from the body, which are unrelated to the magnitude of the blood concentration; over time the fluxes of extraction decrease to a level proportional to the steady state blood concentration. This suggests that, at first, the drug is being extracted from some source other than the blood; one such candidate for this source is the dead cells which form the stratum corneum. In this paper, we construct two related mathematical models; the first describes the formation of the drug reservoir in the stratum corneum as a consequence of repeated drug intake and natural death of skin cells in the body. The output from this model provides initial conditions for the model of reverse iontophoresis in which charged ions from both the blood and the stratum corneum reservoir compete for the electric current. Model parameters are estimated from data collected for lithium monitoring. Our models will improve interpretation of reverse iontophoretic data by discriminating the subdermal from the skin contribution to the fluxes of extraction. They also suggest that analysis of the skin reservoir might be a valuable tool to investigate patients' exposure to chemicals including therapeutic drugs.

  19. Pharmacological Targeting of AMP-Activated Protein Kinase and Opportunities for Computer-Aided Drug Design.

    Science.gov (United States)

    Miglianico, Marie; Nicolaes, Gerry A F; Neumann, Dietbert

    2016-04-14

    As a central regulator of metabolism, the AMP-activated protein kinase (AMPK) is an established therapeutic target for metabolic diseases. Beyond the metabolic area, the number of medical fields that involve AMPK grows continuously, expanding the potential applications for AMPK modulators. Even though indirect AMPK activators are used in the clinics for their beneficial metabolic outcome, the few described direct agonists all failed to reach the market to date, which leaves options open for novel targeting methods. As AMPK is not actually a single molecule and has different roles depending on its isoform composition, the opportunity for isoform-specific targeting has notably come forward, but the currently available modulators fall short of expectations. In this review, we argue that with the amount of available structural and ligand data, computer-based drug design offers a number of opportunities to undertake novel and isoform-specific targeting of AMPK.

  20. New Protein Vector ApE1 for Targeted Delivery of Anticancer Drugs

    Directory of Open Access Journals (Sweden)

    N. V. Pozdniakova

    2012-01-01

    Full Text Available A new chimeric gene ApE1 encoding the receptor-binding domain of the human alpha-fetoprotein fused to a sequence of 22 glutamic acid residues was constructed. A new bacterial producer strain E. coli SHExT7 ApE1 was selected for ApE1 production in a soluble state. A simplified method was developed to purify ApE1 from bacterial biomass. It was shown that the new vector protein selectively interacts with AFP receptors on the tumor cell surface and can be efficiently accumulated in tumor cells. In addition, ApE1 was shown to be stable in storage and during its chemical modification. An increased number of carboxyl groups in the molecule allows the production of cytotoxic compound conjugates with higher drug-loading capacity and enhanced tumor targeting potential.

  1. First protein drug target's appraisal of lead-likeness descriptors to unfold the intervening chemical space.

    Science.gov (United States)

    Athar, Mohd; Lone, Mohsin Y; Jha, Prakash C

    2017-03-01

    Despite the advances in combinatorial chemistry, high throughput and virtual screening experiments, plethora of clinical studies disquiet due to lead and drug-likeness attritions. For mitigation, the knowledge of physicochemical properties are really useful for guiding and selection of compounds from libraries dictated by certain rule of thumbs. However, robust bio-technological and instrumental innovations have created exponential increase in novel compounds and databases which compelled rethinking of the evaluation procedures. Known desc