WorldWideScience

Sample records for model protein drug

  1. Distribution of Spiked Drugs between Milk Fat, Skim Milk, Whey, Curd, and Milk Protein Fractions: Expansion of Partitioning Models.

    Science.gov (United States)

    Lupton, Sara J; Shappell, Nancy W; Shelver, Weilin L; Hakk, Heldur

    2018-01-10

    The distributions of eight drugs (acetaminophen, acetylsalicylic acid/salicylic acid, ciprofloxacin, clarithromycin, flunixin, phenylbutazone, praziquantel, and thiamphenicol) were determined in milk products (skim milk, milk fat, curd, whey, and whey protein) and used to expand a previous model (from 7 drugs to 15 drugs) for predicting drug distribution. Phenylbutazone and praziquantel were found to distribute with the lipid and curd phases (≥50%). Flunixin distribution was lower but similar in direction (12% in milk fat, 39% in curd). Acetaminophen, ciprofloxacin, and praziquantel preferentially associated with casein proteins, whereas thiamphenicol and clarithromycin associated preferentially to whey proteins. Regression analyses for log [milk fat]/[skim milk] and log [curd]/[whey] had r 2 values of 0.63 and 0.67, respectively, with p of <0.001 for 15 drugs (7 previously tested and 8 currently tested). The robustness of the distribution model was enhanced by doubling the number of drugs originally tested.

  2. Improvement of paracellular transport in the Caco-2 drug screening model using protein-engineered substrates.

    Science.gov (United States)

    DiMarco, Rebecca L; Hunt, Daniel R; Dewi, Ruby E; Heilshorn, Sarah C

    2017-06-01

    The Caco-2 assay has achieved wide popularity among pharmaceutical companies in the past two decades as an in vitro method for estimation of in vivo oral bioavailability of pharmaceutical compounds during preclinical characterization. Despite its popularity, this assay suffers from a severe underprediction of the transport of drugs which are absorbed paracellularly, that is, which pass through the cell-cell tight junctions of the absorptive cells of the small intestine. Here, we propose that simply replacing the collagen I matrix employed in the standard Caco-2 assay with an engineered matrix, we can control cell morphology and hence regulate the cell-cell junctions that dictate paracellular transport. Specifically, we use a biomimetic engineered extracellular matrix (eECM) that contains modular protein domains derived from two ECM proteins found in the small intestine, fibronectin and elastin. This eECM allows us to independently tune the density of cell-adhesive RGD ligands presented to Caco-2 cells as well as the mechanical stiffness of the eECM. We observe that lower amounts of RGD ligand presentation as well as decreased matrix stiffness results in Caco-2 morphologies that more closely resemble primary small intestinal epithelial cells than Caco-2 cells cultured on collagen. Additionally, these matrices result in Caco-2 monolayers with decreased recruitment of actin to the apical junctional complex and increased expression of claudin-2, a tight junction protein associated with higher paracellular permeability that is highly expressed throughout the small intestine. Consistent with these morphological differences, drugs known to be paracellularly transported in vivo exhibited significantly improved transport rates in this modified Caco-2 model. As expected, permeability of transcellularly transported drugs remained unaffected. Thus, we have demonstrated a method of improving the physiological accuracy of the Caco-2 assay that could be readily adopted by

  3. [Drug screening model acting on out-membrane protein OprM in pseudomonas aeruginosa efflux pump system].

    Science.gov (United States)

    Tian, Rui; Yu, Li-yan; Xiao, Chun-ling; Zuo, Lian; Yao, Tian-jue; Yang, Li-xia

    2004-08-01

    To establish an efflux pump inhibitor screening model with the out-membrane protein OprM in Pseudomonas aeruginosa efflux pump system as the target point. Efflux pump out-membrane protein gene oprM was obtained from standard Pseudomonas aeruginosa PA01 strain. Expression of OprM protein was induced in E. coli strain HS151 with T-easy vector as the cloning vector, and pMMB67EH as the expression vector. In order to evaluate the function of OprM protein, we measured intracellular tetracycline concentrations with liquid scintillation counter, measured the diameters of bacteriostatic circles with paper disc, and then established a screening model accordingly. OprM protein was highly expressed. Using Pseudomonas aeruginosa as the main detecting bacteria, we established a drug screening model acting on OprM. A total of 1 600 microbial fermentation samples were screened with this model, among which 56 positive strains were found, with a positive rate of 3.5%. OprM plays an important role in drug efflux. The established model has good specificity and maneuverability.

  4. Modelling human protein interaction networks as metric spaces has potential in disease research and drug target discovery.

    Science.gov (United States)

    Fadhal, Emad; Mwambene, Eric C; Gamieldien, Junaid

    2014-06-14

    We have recently shown by formally modelling human protein interaction networks (PINs) as metric spaces and classified proteins into zones based on their distance from the topological centre that hub proteins are primarily centrally located. We also showed that zones closest to the network centre are enriched for critically important proteins and are also functionally very specialised for specific 'house keeping' functions. We proposed that proteins closest to the network centre may present good therapeutic targets. Here, we present multiple pieces of novel functional evidence that provides strong support for this hypothesis. We found that the human PINs has a highly connected signalling core, with the majority of proteins involved in signalling located in the two zones closest to the topological centre. The majority of essential, disease related, tumour suppressor, oncogenic and approved drug target proteins were found to be centrally located. Similarly, the majority of proteins consistently expressed in 13 types of cancer are also predominantly located in zones closest to the centre. Proteins from zones 1 and 2 were also found to comprise the majority of proteins in key KEGG pathways such as MAPK-signalling, the cell cycle, apoptosis and also pathways in cancer, with very similar patterns seen in pathways that lead to cancers such as melanoma and glioma, and non-neoplastic diseases such as measles, inflammatory bowel disease and Alzheimer's disease. Based on the diversity of evidence uncovered, we propose that when considered holistically, proteins located centrally in the human PINs that also have similar functions to existing drug targets are good candidate targets for novel therapeutics. Similarly, since disease pathways are dominated by centrally located proteins, candidates shortlisted in genome scale disease studies can be further prioritized and contextualised based on whether they occupy central positions in the human PINs.

  5. 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

  6. 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

  7. Three-dimensional models of Mycobacterium tuberculosis proteins Rv1555, Rv1554 and their docking analyses with sildenafil, tadalafil, vardenafil drugs, suggest interference with quinol binding likely to affect protein's function.

    Science.gov (United States)

    Dash, Pallabini; Bala Divya, M; Guruprasad, Lalitha; Guruprasad, Kunchur

    2018-04-18

    Earlier based on bioinformatics analyses, we had predicted the Mycobacterium tuberculosis (M.tb) proteins; Rv1555 and Rv1554, among the potential new tuberculosis drug targets. According to the 'TB-drugome' the Rv1555 protein is 'druggable' with sildenafil (Viagra), tadalafil (Cialis) and vardenafil (Levitra) drugs. In the present work, we intended to understand via computer modeling studies, how the above drugs are likely to inhibit the M.tb protein's function. The three-dimensional computer models for M.tb proteins; Rv1555 and Rv1554 constructed on the template of equivalent membrane anchor subunits of the homologous E.coli quinol fumarate reductase respiratory protein complex, followed by drug docking analyses, suggested that the binding of above drugs interferes with quinol binding sites. Also, we experimentally observed the in-vitro growth inhibition of E.coli bacteria containing the homologous M.tb protein sequences with sildenafil and tadalafil drugs. The predicted binding sites of the drugs is likely to affect the above M.tb proteins function as quinol binding is known to be essential for electron transfer function during anaerobic respiration in the homologous E.coli protein complex. Therefore, sildenafil and related drugs currently used in the treatment of male erectile dysfunction targeting the human phosphodiesterase 5 enzyme may be evaluated for their plausible role as repurposed drugs to treat human tuberculosis.

  8. 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.

  9. Investigation of molecular mechanisms of action of chelating drugs on protein-lipid model membranes by X-ray fluorescence

    International Nuclear Information System (INIS)

    Novikova, N. N.; Zheludeva, S. I.; Koval'chuk, M. V.; Stepina, N. D.; Erko, A. I.; Yur'eva, E. A.

    2009-01-01

    Protein-lipid films based on the enzyme alkaline phosphatase were subjected to the action of chelating drugs, which are used for accelerating the removal of heavy metals from the human body, and the elemental composition of the resulting films was investigated. Total-reflection X-ray fluorescence measurements were performed at the Berlin Electron Storage Ring Company for Synchrotron Radiation (BESSY) in Germany. A comparative estimation of the protective effect of four drugs (EDTA, succimer, xydiphone, and mediphon) on membrane-bound enzymes damaged by lead ions was made. The changes in the elemental composition of the protein-lipid films caused by high doses of chelating drugs were investigated. It was shown that state-of-the-art X-ray techniques can, in principle, be used to develop new methods for the in vitro evaluation of the efficiency of drugs, providing differential data on their actions.

  10. Drug transport proteins in the liver

    NARCIS (Netherlands)

    Faber, Klaas Nico; Muller, M.; Jansen, P.LM

    2003-01-01

    Together with drug metabolising enzymes, transmembrane transporters are important determinants of drug metabolism and drug clearance by the liver. Hepatic uptake of organic anions, cations, prostaglandins and bile salts is supported by dedicated transporter proteins in the basolateral (sinusoidal)

  11. Phenytoin-Bovine Serum Albumin interactions - modeling plasma protein - drug binding: A multi-spectroscopy and in silico-based correlation

    Science.gov (United States)

    Suresh, P. K.; Divya, Naik; Nidhi, Shah; Rajasekaran, R.

    2018-03-01

    The study focused on the analysis of the nature and site of binding of Phenytoin (PHT) -(a model hydrophobic drug) with Bovine Serum Albumin (BSA) (a model protein used as a surrogate for HSA). Interactions with defined amounts of Phenytoin and BSA demonstrated a blue shift (hypsochromic -change in the microenvironment of the tryptophan residue with decrease in the polar environment and more of hydrophobicity) with respect to the albumin protein and a red shift (bathochromic -hydrophobicity and polarity related changes) in the case of the model hydrophobic drug. This shift, albeit lower in magnitude, has been substantiated by a fairly convincing, Phenytoin-mediated quenching of the endogenous fluorophore in BSA. Spectral shifts studied at varying pH, temperatures and incubation periods (at varying concentrations of PHT with a defined/constant BSA concentration) showed no significant differences (data not shown). FTIR analysis provided evidence of the interaction of PHT with BSA with a stretching vibration of 1737.86 cm- 1, apart from the vibrations characteristically associated with the amine and carboxyl groups respectively. Our in vitro findings were extended to molecular docking of BSA with PHT (with the different ionized forms of the drug) and the subsequent LIGPLOT-based analysis. In general, a preponderance of hydrophobic interactions was observed. These hydrophobic interactions corroborate the tryptophan-based spectral shifts and the fluorescence quenching data. These results substantiates our hitherto unreported in vitro/in silico experimental flow and provides a basis for screening other hydrophobic drugs in its class.

  12. 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.

  13. 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.

  14. The Protein Model Portal

    OpenAIRE

    Arnold, Konstantin; Kiefer, Florian; Kopp, J?rgen; Battey, James N. D.; Podvinec, Michael; Westbrook, John D.; Berman, Helen M.; Bordoli, Lorenza; Schwede, Torsten

    2008-01-01

    Structural Genomics has been successful in determining the structures of many unique proteins in a high throughput manner. Still, the number of known protein sequences is much larger than the number of experimentally solved protein structures. Homology (or comparative) modeling methods make use of experimental protein structures to build models for evolutionary related proteins. Thereby, experimental structure determination efforts and homology modeling complement each other in the exploratio...

  15. Phenytoin-Bovine Serum Albumin interactions - modeling plasma protein - drug binding: A multi-spectroscopy and in silico-based correlation.

    Science.gov (United States)

    Suresh, P K; Divya, Naik; Nidhi, Shah; Rajasekaran, R

    2018-03-15

    The study focused on the analysis of the nature and site of binding of Phenytoin (PHT) -(a model hydrophobic drug) with Bovine Serum Albumin (BSA) (a model protein used as a surrogate for HSA). Interactions with defined amounts of Phenytoin and BSA demonstrated a blue shift (hypsochromic -change in the microenvironment of the tryptophan residue with decrease in the polar environment and more of hydrophobicity) with respect to the albumin protein and a red shift (bathochromic -hydrophobicity and polarity related changes) in the case of the model hydrophobic drug. This shift, albeit lower in magnitude, has been substantiated by a fairly convincing, Phenytoin-mediated quenching of the endogenous fluorophore in BSA. Spectral shifts studied at varying pH, temperatures and incubation periods (at varying concentrations of PHT with a defined/constant BSA concentration) showed no significant differences (data not shown). FTIR analysis provided evidence of the interaction of PHT with BSA with a stretching vibration of 1737.86cm -1 , apart from the vibrations characteristically associated with the amine and carboxyl groups respectively. Our in vitro findings were extended to molecular docking of BSA with PHT (with the different ionized forms of the drug) and the subsequent LIGPLOT-based analysis. In general, a preponderance of hydrophobic interactions was observed. These hydrophobic interactions corroborate the tryptophan-based spectral shifts and the fluorescence quenching data. These results substantiates our hitherto unreported in vitro/in silico experimental flow and provides a basis for screening other hydrophobic drugs in its class. Copyright © 2017. Published by Elsevier B.V.

  16. 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.

  17. Predicting adverse drug reaction profiles by integrating protein interaction networks with drug structures.

    Science.gov (United States)

    Huang, Liang-Chin; Wu, Xiaogang; Chen, Jake Y

    2013-01-01

    The prediction of adverse drug reactions (ADRs) has become increasingly important, due to the rising concern on serious ADRs that can cause drugs to fail to reach or stay in the market. We proposed a framework for predicting ADR profiles by integrating protein-protein interaction (PPI) networks with drug structures. We compared ADR prediction performances over 18 ADR categories through four feature groups-only drug targets, drug targets with PPI networks, drug structures, and drug targets with PPI networks plus drug structures. The results showed that the integration of PPI networks and drug structures can significantly improve the ADR prediction performance. The median AUC values for the four groups were 0.59, 0.61, 0.65, and 0.70. We used the protein features in the best two models, "Cardiac disorders" (median-AUC: 0.82) and "Psychiatric disorders" (median-AUC: 0.76), to build ADR-specific PPI networks with literature supports. For validation, we examined 30 drugs withdrawn from the U.S. market to see if our approach can predict their ADR profiles and explain why they were withdrawn. Except for three drugs having ADRs in the categories we did not predict, 25 out of 27 withdrawn drugs (92.6%) having severe ADRs were successfully predicted by our approach. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. 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.

  19. Protein solubility modeling

    Science.gov (United States)

    Agena, S. M.; Pusey, M. L.; Bogle, I. D.

    1999-01-01

    A thermodynamic framework (UNIQUAC model with temperature dependent parameters) is applied to model the salt-induced protein crystallization equilibrium, i.e., protein solubility. The framework introduces a term for the solubility product describing protein transfer between the liquid and solid phase and a term for the solution behavior describing deviation from ideal solution. Protein solubility is modeled as a function of salt concentration and temperature for a four-component system consisting of a protein, pseudo solvent (water and buffer), cation, and anion (salt). Two different systems, lysozyme with sodium chloride and concanavalin A with ammonium sulfate, are investigated. Comparison of the modeled and experimental protein solubility data results in an average root mean square deviation of 5.8%, demonstrating that the model closely follows the experimental behavior. Model calculations and model parameters are reviewed to examine the model and protein crystallization process. Copyright 1999 John Wiley & Sons, Inc.

  20. Smarter Drugs: How Protein Crystallography Revolutionizes Drug Design

    International Nuclear Information System (INIS)

    Smith, Clyde

    2005-01-01

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

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

    Science.gov (United States)

    Rosell, Mireia; Fernández-Recio, Juan

    2018-04-01

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

  2. 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.

  3. Targeted proteins for diabetes drug design

    International Nuclear Information System (INIS)

    Trang Nguyen, Ngoc Doan; Le, Ly Thi

    2012-01-01

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

  4. The Protein Model Portal.

    Science.gov (United States)

    Arnold, Konstantin; Kiefer, Florian; Kopp, Jürgen; Battey, James N D; Podvinec, Michael; Westbrook, John D; Berman, Helen M; Bordoli, Lorenza; Schwede, Torsten

    2009-03-01

    Structural Genomics has been successful in determining the structures of many unique proteins in a high throughput manner. Still, the number of known protein sequences is much larger than the number of experimentally solved protein structures. Homology (or comparative) modeling methods make use of experimental protein structures to build models for evolutionary related proteins. Thereby, experimental structure determination efforts and homology modeling complement each other in the exploration of the protein structure space. One of the challenges in using model information effectively has been to access all models available for a specific protein in heterogeneous formats at different sites using various incompatible accession code systems. Often, structure models for hundreds of proteins can be derived from a given experimentally determined structure, using a variety of established methods. This has been done by all of the PSI centers, and by various independent modeling groups. The goal of the Protein Model Portal (PMP) is to provide a single portal which gives access to the various models that can be leveraged from PSI targets and other experimental protein structures. A single interface allows all existing pre-computed models across these various sites to be queried simultaneously, and provides links to interactive services for template selection, target-template alignment, model building, and quality assessment. The current release of the portal consists of 7.6 million model structures provided by different partner resources (CSMP, JCSG, MCSG, NESG, NYSGXRC, JCMM, ModBase, SWISS-MODEL Repository). The PMP is available at http://www.proteinmodelportal.org and from the PSI Structural Genomics Knowledgebase.

  5. 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.

  6. 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

  7. Large-scale identification of potential drug targets based on the topological features of human protein-protein interaction network.

    Science.gov (United States)

    Li, Zhan-Chao; Zhong, Wen-Qian; Liu, Zhi-Qing; Huang, Meng-Hua; Xie, Yun; Dai, Zong; Zou, Xiao-Yong

    2015-04-29

    Identifying potential drug target proteins is a crucial step in the process of drug discovery and plays a key role in the study of the molecular mechanisms of disease. Based on the fact that the majority of proteins exert their functions through interacting with each other, we propose a method to recognize target proteins by using the human protein-protein interaction network and graph theory. In the network, vertexes and edges are weighted by using the confidence scores of interactions and descriptors of protein primary structure, respectively. The novel network topological features are defined and employed to characterize protein using existing databases. A widely used minimum redundancy maximum relevance and random forests algorithm are utilized to select the optimal feature subset and construct model for the identification of potential drug target proteins at the proteome scale. The accuracies of training set and test set are 89.55% and 85.23%. Using the constructed model, 2127 potential drug target proteins have been recognized and 156 drug target proteins have been validated in the database of drug target. In addition, some new drug target proteins can be considered as targets for treating diseases of mucopolysaccharidosis, non-arteritic anterior ischemic optic neuropathy, Bernard-Soulier syndrome and pseudo-von Willebrand, etc. It is anticipated that the proposed method may became a powerful high-throughput virtual screening tool of drug target. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. Protein structure--based drug design.

    Science.gov (United States)

    Whittle, P J; Blundell, T L

    1994-01-01

    Design cycles will undoubtedly play an increasingly important role in drug discovery in the coming years, as the amount of structural information on protein targets continues to rise. However, the traditional method of drug discovery, based upon random screening and systematic modification of leads by medicinal chemistry techniques, will probably not be abandoned completely because it has a potentially important advantage over more structure-based methods--namely, leads identified in this way are unlikely to show a close resemblance to the natural ligand or substrate. They may, therefore, have advantages in terms of patent novelty, selectivity, or pharmacokinetic profile. However, such leads could then serve as the basis for structure-based, rational modification programs, in which their interactions with target receptors are defined (as we have described) and improved molecules are designed. A final important point to be made about structure-based design in drug discovery is that, while it can be of great use in the initial process of identifying ligands with improved affinity and selectivity in vitro, it can usually say very little about other essential aspects of the drug discovery process, e.g. the need to achieve an adequate pharmacokinetic profile and low toxicity in vivo. This observation reminds us that drug design is a multidisciplinary process, involving molecular biologists, biochemists, pharmacologists, organic chemists, crystallographers, and others. In order to be effective, therefore, structure-based design must be properly integrated into the overall discovery effort.

  9. 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

  10. 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

  11. Drug-model membrane interactions

    International Nuclear Information System (INIS)

    Deniz, Usha K.

    1994-01-01

    In the present day world, drugs play a very important role in medicine and it is necessary to understand their mode of action at the molecular level, in order to optimise their use. Studies of drug-biomembrane interactions are essential for gaining such as understanding. However, it would be prohibitively difficult to carry out such studies, since biomembranes are highly complex systems. Hence, model membranes (made up of these lipids which are important components of biomembranes) of varying degrees of complexity are used to investigate drug-membrane interactions. Bio- as well as model-membranes undergo a chain melting transition when heated, the chains being in a disordered state above the transition point, T CM . This transition is of physiological importance since biomembranes select their components such that T CM is less than the ambient temperature but not very much so, so that membrane flexibility is ensured and porosity, avoided. The influence of drugs on the transition gives valuable clues about various parameters such as the location of the drug in the membrane. Deep insights into drug-membrane interactions are obtained by observing the effect of drugs on membrane structure and the mobilities of the various groups in lipids, near T CM . Investigation of such changes have been carried out with several drugs, using techniques such as DSC, XRD and NMR. The results indicate that the drug-membrane interaction not only depends on the nature of drug and lipids but also on the form of the model membrane - stacked bilayer or vesicles. The light that these results shed on the nature of drug-membrane interactions is discussed. (author). 13 refs., 13 figs., 1 tab

  12. Mathematical modeling of drug delivery.

    Science.gov (United States)

    Siepmann, J; Siepmann, F

    2008-12-08

    Due to the significant advances in information technology mathematical modeling of drug delivery is a field of steadily increasing academic and industrial importance with an enormous future potential. The in silico optimization of novel drug delivery systems can be expected to significantly increase in accuracy and easiness of application. Analogous to other scientific disciplines, computer simulations are likely to become an integral part of future research and development in pharmaceutical technology. Mathematical programs can be expected to be routinely used to help optimizing the design of novel dosage forms. Good estimates for the required composition, geometry, dimensions and preparation procedure of various types of delivery systems will be available, taking into account the desired administration route, drug dose and release profile. Thus, the number of required experimental studies during product development can be significantly reduced, saving time and reducing costs. In addition, the quantitative analysis of the physical, chemical and potentially biological phenomena, which are involved in the control of drug release, offers another fundamental advantage: The underlying drug release mechanisms can be elucidated, which is not only of academic interest, but a pre-requisite for an efficient improvement of the safety of the pharmaco-treatments and for effective trouble-shooting during production. This article gives an overview on the current state of the art of mathematical modeling of drug delivery, including empirical/semi-empirical and mechanistic realistic models. Analytical as well as numerical solutions are described and various practical examples are given. One of the major challenges to be addressed in the future is the combination of mechanistic theories describing drug release out of the delivery systems with mathematical models quantifying the subsequent drug transport within the human body in a realistic way. Ideally, the effects of the design

  13. 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

    2017-09-29

    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.

  14. Mathematical modeling of drug dissolution.

    Science.gov (United States)

    Siepmann, J; Siepmann, F

    2013-08-30

    The dissolution of a drug administered in the solid state is a pre-requisite for efficient subsequent transport within the human body. This is because only dissolved drug molecules/ions/atoms are able to diffuse, e.g. through living tissue. Thus, generally major barriers, including the mucosa of the gastro intestinal tract, can only be crossed after dissolution. Consequently, the process of dissolution is of fundamental importance for the bioavailability and, hence, therapeutic efficacy of various pharmaco-treatments. Poor aqueous solubility and/or very low dissolution rates potentially lead to insufficient availability at the site of action and, hence, failure of the treatment in vivo, despite a potentially ideal chemical structure of the drug to interact with its target site. Different physical phenomena are involved in the process of drug dissolution in an aqueous body fluid, namely the wetting of the particle's surface, breakdown of solid state bonds, solvation, diffusion through the liquid unstirred boundary layer surrounding the particle as well as convection in the surrounding bulk fluid. Appropriate mathematical equations can be used to quantify these mass transport steps, and more or less complex theories can be developed to describe the resulting drug dissolution kinetics. This article gives an overview on the current state of the art of modeling drug dissolution and points out the assumptions the different theories are based on. Various practical examples are given in order to illustrate the benefits of such models. This review is not restricted to mathematical theories considering drugs exhibiting poor aqueous solubility and/or low dissolution rates, but also addresses models quantifying drug release from controlled release dosage forms, in which the process of drug dissolution plays a major role. Copyright © 2013 Elsevier B.V. All rights reserved.

  15. 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.

  16. Systematic identification of proteins that elicit drug side effects

    DEFF Research Database (Denmark)

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

    2013-01-01

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

  17. 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.

  18. 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.

  19. Protein Crystallography: A 'Must' Technology for Drug Design

    International Nuclear Information System (INIS)

    Matsuzaki, Takao

    2004-01-01

    The history of drug-related protein crystallography and drug design is reviewed to show that 'Lead Generation' is high-lighted in the pharmaceutical industry nowadays. A new drug design method has been developed. The method gave very high success rate; 10-60 % gave < 100 μM, 90 % gave < 10 mM. The crystal structures of drug-protein complexes have become even more important to give solid experimental bases for e.g. 1,000 designed structures and to find the new mechanisms of drug action

  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...... 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. Drug Promiscuity in PDB: Protein Binding Site Similarity Is Key.

    Science.gov (United States)

    Haupt, V Joachim; Daminelli, Simone; Schroeder, Michael

    2013-01-01

    Drug repositioning applies established drugs to new disease indications with increasing success. A pre-requisite for drug repurposing is drug promiscuity (polypharmacology) - a drug's ability to bind to several targets. There is a long standing debate on the reasons for drug promiscuity. Based on large compound screens, hydrophobicity and molecular weight have been suggested as key reasons. However, the results are sometimes contradictory and leave space for further analysis. Protein structures offer a structural dimension to explain promiscuity: Can a drug bind multiple targets because the drug is flexible or because the targets are structurally similar or even share similar binding sites? We present a systematic study of drug promiscuity based on structural data of PDB target proteins with a set of 164 promiscuous drugs. We show that there is no correlation between the degree of promiscuity and ligand properties such as hydrophobicity or molecular weight but a weak correlation to conformational flexibility. However, we do find a correlation between promiscuity and structural similarity as well as binding site similarity of protein targets. In particular, 71% of the drugs have at least two targets with similar binding sites. In order to overcome issues in detection of remotely similar binding sites, we employed a score for binding site similarity: LigandRMSD measures the similarity of the aligned ligands and uncovers remote local similarities in proteins. It can be applied to arbitrary structural binding site alignments. Three representative examples, namely the anti-cancer drug methotrexate, the natural product quercetin and the anti-diabetic drug acarbose are discussed in detail. Our findings suggest that global structural and binding site similarity play a more important role to explain the observed drug promiscuity in the PDB than physicochemical drug properties like hydrophobicity or molecular weight. Additionally, we find ligand flexibility to have a minor

  2. High-throughput protein crystallography and drug discovery.

    Science.gov (United States)

    Tickle, Ian; Sharff, Andrew; Vinkovic, Mladen; Yon, Jeff; Jhoti, Harren

    2004-10-20

    Single crystal X-ray diffraction is the technique of choice for studying the interactions of small organic molecules with proteins by determining their three-dimensional structures; however the requirement for highly purified protein and lack of process automation have traditionally limited its use in this field. Despite these shortcomings, the use of crystal structures of therapeutically relevant drug targets in pharmaceutical research has increased significantly over the last decade. The application of structure-based drug design has resulted in several marketed drugs and is now an established discipline in most pharmaceutical companies. Furthermore, the recently published full genome sequences of Homo sapiens and a number of micro-organisms have provided a plethora of new potential drug targets that could be utilised in structure-based drug design programs. In order to take maximum advantage of this explosion of information, techniques have been developed to automate and speed up the various procedures required to obtain protein crystals of suitable quality, to collect and process the raw X-ray diffraction data into usable structural information, and to use three-dimensional protein structure as a basis for drug discovery and lead optimisation. This tutorial review covers the various technologies involved in the process pipeline for high-throughput protein crystallography as it is currently being applied to drug discovery. It is aimed at synthetic and computational chemists, as well as structural biologists, in both academia and industry, who are interested in structure-based drug design.

  3. Protein Nanoparticles as Drug Delivery Carriers for Cancer Therapy

    Directory of Open Access Journals (Sweden)

    Warangkana Lohcharoenkal

    2014-01-01

    Full Text Available 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.

  4. 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

  5. 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

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

    Science.gov (United States)

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

    2018-01-01

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

  7. 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.

  8. 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...

  9. Chromatin proteins and modifications as drug targets

    DEFF Research Database (Denmark)

    Helin, Kristian; Dhanak, Dashyant

    2013-01-01

    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...

  10. Drug disposition in obesity and protein-energy malnutrition.

    Science.gov (United States)

    Boullata, Joseph I

    2010-11-01

    Clinical response to medication can differ between patients. Among the known sources of variability is an individual's nutrition status. This review defines some pharmacokinetic terms, provides relevant body size metrics and describes the physiologic influences of protein-energy malnutrition and obesity on drug disposition. Weight-based drug dosing, which presumes a healthy BMI, can be problematic in the protein-energy malnourished or obese patient. The use of total body weight, lean body weight, or an adjusted body weight depends on the drug and how it is differently handled in malnutrition or obesity. Most of the recognized influences are seen in drug distribution and drug elimination as a result of altered body composition and function. Distribution characteristics of each drug are determined by several drug-related factors (e.g. tissue affinity) in combination with body-related factors (e.g. composition). Drug elimination occurs through metabolic and excretory pathways that can also vary with body composition. The current data are limited to select drugs that have been reported in small studies or case reports. In the meantime, a rational approach to evaluate the potential influences of malnutrition and obesity can be used clinically based on available information. Antimicrobials are discussed as a useful example of this approach. Further advancement in this field would require collaboration between experts in body composition and those in drug disposition. Until more data are available, routine monitoring by the clinician of the protein-energy malnourished or obese patient receiving weight-based drug regimens is necessary.

  11. 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.

  12. 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

  13. A Mathematical Model of the Effect of Immunogenicity on Therapeutic Protein Pharmacokinetics

    OpenAIRE

    Chen, Xiaoying; Hickling, Timothy; Kraynov, Eugenia; Kuang, Bing; Parng, Chuenlei; Vicini, Paolo

    2013-01-01

    A mathematical pharmacokinetic/anti-drug-antibody (PK/ADA) model was constructed for quantitatively assessing immunogenicity for therapeutic proteins. The model is inspired by traditional pharmacokinetic/pharmacodynamic (PK/PD) models, and is based on the observed impact of ADA on protein drug clearance. The hypothesis for this work is that altered drug PK contains information about the extent and timing of ADA generation. By fitting drug PK profiles while accounting for ADA-mediated drug cle...

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

    Science.gov (United States)

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

    2016-01-01

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

  15. May disordered protein cause serious drug side effect?

    Science.gov (United States)

    Tou, Weng Ieong; Chen, Calvin Yu-Chian

    2014-04-01

    Insomnia is a self-reported disease where patients lose their ability to initiate and maintain sleep, leading to daytime performance impairment. Several drug targets to ameliorate insomnia symptoms have been discovered; however, these drug targets lead to serious side effects. Thus, we characterize the structural properties of these sleep-related receptors and the clock complex and discuss a possible drug design that will reduce side effects. Computational prediction shows that disordered property is shared. Over 30% of the structure of CLOCK, PER1/2/3, BMAL-1, muscarinic acetylcholine receptor-M1, melatonin receptor and casein kinase I are structurally disordered (the remaining proteins represent insomnia drugs might be closely related to the protein architecture. Copyright © 2013 Elsevier Ltd. All rights reserved.

  16. 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...

  17. Hydrophobicity – Shake Flasks, Protein Folding and Drug Discovery

    Science.gov (United States)

    Sarkar, Aurijit; Kellogg, Glen E.

    2009-01-01

    Hydrophobic interactions are some of the most important interactions in nature. They are the primary driving force in a number of phenomena. This is mostly an entropic effect and can account for a number of biophysical events such as protein-protein or protein-ligand binding that are of immense importance in drug design. The earliest studies on this phenomenon can be dated back to the end of the 19th century when Meyer and Overton independently correlated the hydrophobic nature of gases to their anesthetic potency. Since then, significant progress has been made in this realm of science. This review briefly traces the history of hydrophobicity research along with the theoretical estimation of partition coefficients. Finally, the application of hydrophobicity estimation methods in the field of drug design and protein folding is discussed. PMID:19929828

  18. Mechanisms of photosensitization by drugs: Involvement of tyrosines in the photomodification of proteins mediated by tiaprofenic acid in vitro.

    Science.gov (United States)

    Miranda, M A; Castell, J V; Sarabia, Z; Hernández, D; Puertes, I; Morera, I M; Gómez-Lechón, M J

    1997-10-01

    The photosensitizing potential of drugs must be related to their photoreactivity towards the target biomolecules. In this context, a representative photosensitizing drug (tiaprofenic acid) was co-irradiated with a model protein, bovine serum albumin (BSA). This led to a significant degree of protein crosslinking and to the formation of trace amounts of drug-BSA photoadducts. Amino acid analysis of the hydrolysed (HC1) protein showed that His and Tyr undergo a dramatic decrease (approx. 90%) as a consequence of drug-mediated photodynamic processes. When the drug was irradiated in the presence of the pure amino acids, extensive phototransformation of the latter was observed. Other photosensitizing drugs gave rise to similar processes when irradiated in the presence of BSA or the isolated amino acids. In conclusion, histidine and tyrosine appear to be key sites for the photosensitized damage to proteins. Photodegradation of the isolated amino acids in vitro may be an indicator of the photosensitizing potential of drugs.

  19. 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.

  20. Automated protein structure modeling with SWISS-MODEL Workspace and the Protein Model Portal.

    Science.gov (United States)

    Bordoli, Lorenza; Schwede, Torsten

    2012-01-01

    Comparative protein structure modeling is a computational approach to build three-dimensional structural models for proteins using experimental structures of related protein family members as templates. Regular blind assessments of modeling accuracy have demonstrated that comparative protein structure modeling is currently the most reliable technique to model protein structures. Homology models are often sufficiently accurate to substitute for experimental structures in a wide variety of applications. Since the usefulness of a model for specific application is determined by its accuracy, model quality estimation is an essential component of protein structure prediction. Comparative protein modeling has become a routine approach in many areas of life science research since fully automated modeling systems allow also nonexperts to build reliable models. In this chapter, we describe practical approaches for automated protein structure modeling with SWISS-MODEL Workspace and the Protein Model Portal.

  1. Hydroxyapatite nanorod-assembled porous hollow polyhedra as drug/protein carriers.

    Science.gov (United States)

    Yu, Ya-Dong; Zhu, Ying-Jie; Qi, Chao; Jiang, Ying-Ying; Li, Heng; Wu, Jin

    2017-06-15

    Hydroxyapatite (HAP) with a porous hollow structure is an ideal biomaterial owing to its excellent biocompatibility and unique architecture. In this study, HAP nanorod-assembled porous hollow polyhedra, consisting of nanorod building blocks, have been successfully prepared at room temperature or under hydrothermal circumstances using a self-sacrificing Ca(OH) 2 template strategy. The hydrothermal treatment (at 180°C for 1h) can promote the HAP nanorods to be arranged with their axial direction normal to the polyhedron surface. The HAP nanorod-assembled porous hollow polyhedra have been explored for the potential application in drug/protein delivery, using ibuprofen (IBU) as a model drug and hemoglobin (Hb) as a model protein. The experimental results indicate that the HAP nanorod-assembled porous hollow polyhedra have a relatively high drug loading capacity and protein adsorption ability, and sustained drug and protein release. The HAP nanorod-assembled porous hollow polyhedra have promising applications in various biomedical fields such as the drug and protein delivery. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Automated Protein Structure Modeling with SWISS-MODEL Workspace and the Protein Model Portal

    OpenAIRE

    Bordoli, Lorenza; Schwede, Torsten

    2012-01-01

    Comparative protein structure modeling is a computational approach to build three-dimensional structural models for proteins using experimental structures of related protein family members as templates. Regular blind assessments of modeling accuracy have demonstrated that comparative protein structure modeling is currently the most reliable technique to model protein structures. Homology models are often sufficiently accurate to substitute for experimental structures in a wide variety of appl...

  3. Nuclear export of proteins and drug resistance in cancer.

    Science.gov (United States)

    Turner, Joel G; Dawson, Jana; Sullivan, Daniel M

    2012-04-15

    The intracellular location of a protein is crucial to its normal functioning in a cell. Cancer cells utilize the normal processes of nuclear-cytoplasmic transport through the nuclear pore complex of a cell to effectively evade anti-neoplastic mechanisms. CRM1-mediated export is increased in various cancers. Proteins that are exported in cancer include tumor-suppressive proteins such as retinoblastoma, APC, p53, BRAC1, FOXO proteins, INI1/hSNF5, galectin-3, Bok, nucleophosmin, RASSF2, Merlin, p21(CIP), p27(KIP1), N-WASP/FAK, estradiol receptor and Tob, drug targets topoisomerase I and IIα and BCR-ABL, and the molecular chaperone protein Hsp90. Here, we review in detail the current processes and known structures involved in the export of a protein through the nuclear pore complex. We also discuss the export receptor molecule CRM1 and its binding to the leucine-rich nuclear export signal of the cargo protein and the formation of a nuclear export trimer with RanGTP. The therapeutic potential of various CRM1 inhibitors will be addressed, including leptomycin B, ratjadone, KOS-2464, and specific small molecule inhibitors of CRM1, N-azolylacrylate analogs, FOXO export inhibitors, valtrate, acetoxychavicol acetate, CBS9106, and SINE inhibitors. We will also discuss examples of how drug resistance may be reversed by targeting the exported proteins topoisomerase IIα, BCR-ABL, and galectin-3. As effective and less toxic CRM1 export inhibitors become available, they may be used as both single agents and in combination with current chemotherapeutic drugs. We believe that the future development of low-toxicity, small-molecule CRM1 inhibitors may provide a new approach to treating cancer. Copyright © 2011 Elsevier Inc. All rights reserved.

  4. 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

  5. Viral capsid assembly as a model for protein aggregation diseases: Active processes catalyzed by cellular assembly machines comprising novel drug targets.

    Science.gov (United States)

    Marreiros, Rita; Müller-Schiffmann, Andreas; Bader, Verian; Selvarajah, Suganya; Dey, Debendranath; Lingappa, Vishwanath R; Korth, Carsten

    2015-09-02

    Viruses can be conceptualized as self-replicating multiprotein assemblies, containing coding nucleic acids. Viruses have evolved to exploit host cellular components including enzymes to ensure their replicative life cycle. New findings indicate that also viral capsid proteins recruit host factors to accelerate their assembly. These assembly machines are RNA-containing multiprotein complexes whose composition is governed by allosteric sites. In the event of viral infection, the assembly machines are recruited to support the virus over the host and are modified to achieve that goal. Stress granules and processing bodies may represent collections of such assembly machines, readily visible by microscopy but biochemically labile and difficult to isolate by fractionation. We hypothesize that the assembly of protein multimers such as encountered in neurodegenerative or other protein conformational diseases, is also catalyzed by assembly machines. In the case of viral infection, the assembly machines have been modified by the virus to meet the virus' need for rapid capsid assembly rather than host homeostasis. In the case of the neurodegenerative diseases, it is the monomers and/or low n oligomers of the so-called aggregated proteins that are substrates of assembly machines. Examples for substrates are amyloid β peptide (Aβ) and tau in Alzheimer's disease, α-synuclein in Parkinson's disease, prions in the prion diseases, Disrupted-in-schizophrenia 1 (DISC1) in subsets of chronic mental illnesses, and others. A likely continuum between virus capsid assembly and cell-to-cell transmissibility of aggregated proteins is remarkable. Protein aggregation diseases may represent dysfunction and dysregulation of these assembly machines analogous to the aberrations induced by viral infection in which cellular homeostasis is pathologically reprogrammed. In this view, as for viral infection, reset of assembly machines to normal homeostasis should be the goal of protein aggregation

  6. Identify drug repurposing candidates by mining the protein data bank.

    Science.gov (United States)

    Moriaud, Fabrice; Richard, Stéphane B; Adcock, Stewart A; Chanas-Martin, Laetitia; Surgand, Jean-Sébastien; Ben Jelloul, Marouane; Delfaud, François

    2011-07-01

    Predicting off-targets by computational methods is gaining increasing interest in early-stage drug discovery. Here, we present a computational method based on full 3D comparisons of 3D structures. When a similar binding site is detected in the Protein Data Bank (PDB) (or any protein structure database), it is possible that the corresponding ligand also binds to that similar site. On one hand, this target hopping case is probably rare because it requires a high similarity between the binding sites. On the other hand, it could be a strong rational evidence to highlight possible off-target reactions and possibly a potential undesired side effect. This target-based drug repurposing can be extended a significant step further with the capability of searching the full surface of all proteins in the PDB, and therefore not relying on pocket detection. Using this approach, we describe how MED-SuMo reproduces the repurposing of tadalafil from PDE5A to PDE4A and a structure of PDE4A with tadalafil. Searching for local protein similarities generates more hits than for whole binding site similarities and therefore fragment repurposing is more likely to occur than for drug-sized compounds. In this work, we illustrate that by mining the PDB for proteins sharing similarities with the hinge region of protein kinases. The experimentally validated examples, biotin carboxylase and synapsin, are retrieved. Further to fragment repurposing, this approach can be applied to the detection of druggable sites from 3D structures. This is illustrated with detection of the protein kinase hinge motif in the HIV-RT non-nucleosidic allosteric site.

  7. Rational drug repositioning guided by an integrated pharmacological network of protein, disease and drug

    Directory of Open Access Journals (Sweden)

    Lee Hee

    2012-07-01

    Full Text Available Abstract Background The process of drug discovery and development is time-consuming and costly, and the probability of success is low. Therefore, there is rising interest in repositioning existing drugs for new medical indications. When successful, this process reduces the risk of failure and costs associated with de novo drug development. However, in many cases, new indications of existing drugs have been found serendipitously. Thus there is a clear need for establishment of rational methods for drug repositioning. Results In this study, we have established a database we call “PharmDB” which integrates data associated with disease indications, drug development, and associated proteins, and known interactions extracted from various established databases. To explore linkages of known drugs to diseases of interest from within PharmDB, we designed the Shared Neighborhood Scoring (SNS algorithm. And to facilitate exploration of tripartite (Drug-Protein-Disease network, we developed a graphical data visualization software program called phExplorer, which allows us to browse PharmDB data in an interactive and dynamic manner. We validated this knowledge-based tool kit, by identifying a potential application of a hypertension drug, benzthiazide (TBZT, to induce lung cancer cell death. Conclusions By combining PharmDB, an integrated tripartite database, with Shared Neighborhood Scoring (SNS algorithm, we developed a knowledge platform to rationally identify new indications for known FDA approved drugs, which can be customized to specific projects using manual curation. The data in PharmDB is open access and can be easily explored with phExplorer and accessed via BioMart web service (http://www.i-pharm.org/, http://biomart.i-pharm.org/.

  8. Rational drug repositioning guided by an integrated pharmacological network of protein, disease and drug.

    Science.gov (United States)

    Lee, Hee Sook; Bae, Taejeong; Lee, Ji-Hyun; Kim, Dae Gyu; Oh, Young Sun; Jang, Yeongjun; Kim, Ji-Tea; Lee, Jong-Jun; Innocenti, Alessio; Supuran, Claudiu T; Chen, Luonan; Rho, Kyoohyoung; Kim, Sunghoon

    2012-07-02

    The process of drug discovery and development is time-consuming and costly, and the probability of success is low. Therefore, there is rising interest in repositioning existing drugs for new medical indications. When successful, this process reduces the risk of failure and costs associated with de novo drug development. However, in many cases, new indications of existing drugs have been found serendipitously. Thus there is a clear need for establishment of rational methods for drug repositioning. In this study, we have established a database we call "PharmDB" which integrates data associated with disease indications, drug development, and associated proteins, and known interactions extracted from various established databases. To explore linkages of known drugs to diseases of interest from within PharmDB, we designed the Shared Neighborhood Scoring (SNS) algorithm. And to facilitate exploration of tripartite (Drug-Protein-Disease) network, we developed a graphical data visualization software program called phExplorer, which allows us to browse PharmDB data in an interactive and dynamic manner. We validated this knowledge-based tool kit, by identifying a potential application of a hypertension drug, benzthiazide (TBZT), to induce lung cancer cell death. By combining PharmDB, an integrated tripartite database, with Shared Neighborhood Scoring (SNS) algorithm, we developed a knowledge platform to rationally identify new indications for known FDA approved drugs, which can be customized to specific projects using manual curation. The data in PharmDB is open access and can be easily explored with phExplorer and accessed via BioMart web service (http://www.i-pharm.org/, http://biomart.i-pharm.org/).

  9. 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.

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

    International Nuclear Information System (INIS)

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

    2012-01-01

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

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

    Science.gov (United States)

    Chen, Lei; Zheng, Ming-Yue; Zhang, Jian; Feng, Kai-Yan; Cai, Yu-Dong

    2013-01-01

    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. PMID:24083237

  12. 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.

  13. In silico structure-based approaches to discover protein-protein interaction-targeting drugs.

    Science.gov (United States)

    Shin, Woong-Hee; Christoffer, Charles W; Kihara, Daisuke

    2017-12-01

    A core concept behind modern drug discovery is finding a small molecule that modulates a function of a target protein. This concept has been successfully applied since the mid-1970s. However, the efficiency of drug discovery is decreasing because the druggable target space in the human proteome is limited. Recently, protein-protein interaction (PPI) has been identified asan emerging target space for drug discovery. PPI plays a pivotal role in biological pathways including diseases. Current human interactome research suggests that the number of PPIs is between 130,000 and 650,000, and only a small number of them have been targeted as drug targets. For traditional drug targets, in silico structure-based methods have been successful in many cases. However, their performance suffers on PPI interfaces because PPI interfaces are different in five major aspects: From a geometric standpoint, they have relatively large interface regions, flat geometry, and the interface surface shape tends to fluctuate upon binding. Also, their interactions are dominated by hydrophobic atoms, which is different from traditional binding-pocket-targeted drugs. Finally, PPI targets usually lack natural molecules that bind to the target PPI interface. Here, we first summarize characteristics of PPI interfaces and their known binders. Then, we will review existing in silico structure-based approaches for discovering small molecules that bind to PPI interfaces. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. The significance of G protein-coupled receptor crystallography for drug discovery.

    Science.gov (United States)

    Salon, John A; Lodowski, David T; Palczewski, Krzysztof

    2011-12-01

    Crucial as molecular sensors for many vital physiological processes, seven-transmembrane domain G protein-coupled receptors (GPCRs) comprise the largest family of proteins targeted by drug discovery. Together with structures of the prototypical GPCR rhodopsin, solved structures of other liganded GPCRs promise to provide insights into the structural basis of the superfamily's biochemical functions and assist in the development of new therapeutic modalities and drugs. One of the greatest technical and theoretical challenges to elucidating and exploiting structure-function relationships in these systems is the emerging concept of GPCR conformational flexibility and its cause-effect relationship for receptor-receptor and receptor-effector interactions. Such conformational changes can be subtle and triggered by relatively small binding energy effects, leading to full or partial efficacy in the activation or inactivation of the receptor system at large. Pharmacological dogma generally dictates that these changes manifest themselves through kinetic modulation of the receptor's G protein partners. Atomic resolution information derived from increasingly available receptor structures provides an entrée to the understanding of these events and practically applying it to drug design. Supported by structure-activity relationship information arising from empirical screening, a unified structural model of GPCR activation/inactivation promises to both accelerate drug discovery in this field and improve our fundamental understanding of structure-based drug design in general. This review discusses fundamental problems that persist in drug design and GPCR structural determination.

  15. Determination of the composition, encapsulation efficiency and loading capacity in protein drug delivery systems using circular dichroism spectroscopy.

    Science.gov (United States)

    Peng, Zhili; Li, Shanghao; Han, Xu; Al-Youbi, Abdulrahman O; Bashammakh, Abdulaziz S; El-Shahawi, Mohammad S; Leblanc, Roger M

    2016-09-21

    Peptides and proteins have become very promising drug candidates in recent decades due to their unique properties. However, the application of these drugs has been limited by their high enzymatic susceptibility, low membrane permeability and poor bioavailability when administered orally. Considerable efforts have been made to design and develop drug delivery systems that could transport peptides and proteins to targeted area. Although it is of great importance to determine the composition after loading a drug to the carrier, the ability to do so is significantly limited by current analytical methods. In this letter, five important proteins, α1-antitrypsin, hemoglobin human, human serum albumin, human transferrin and r-globulin were chemically conjugated to two model drug carriers, namely carbon dots and polymer O-(2-carboxyethyl) polyethylene glycol. A simple yet convenient method based on circular dichroism spectroscopy was developed to determine the compositions of the various protein-carrier conjugates. Copyright © 2016 Elsevier B.V. All rights reserved.

  16. Computational modeling of drug transport across the in vitro cornea.

    Science.gov (United States)

    Pak, Joseph; Chen, Z J; Sun, Kay; Przekwas, Andrzej; Walenga, Ross; Fan, Jianghong

    2018-01-01

    A novel quasi-3D (Q3D) modeling approach was developed to model networks of one dimensional structures like tubes and vessels common in human anatomy such as vascular and lymphatic systems, neural networks, and respiratory airways. Instead of a branching network of the same tissue type, this approach was extended to model an interconnected stack of different corneal tissue layers with membrane junction conditions assigned between the tissues. The multi-laminate structure of the cornea presents a unique barrier design and opportunity for investigation using Q3D modeling. A Q3D model of an in vitro rabbit cornea was created to simulate the drug transport across the cornea, accounting for transcellular and paracellular pathways of passive and convective drug transport as well as physicochemistry of lipophilic partitioning and protein binding. Lipophilic Rhodamine B and hydrophilic fluorescein were used as drug analogs. The model predictions for both hydrophilic and lipophilic tracers were able to match the experimental measurements along with the sharp discontinuities at the epithelium-stroma and stroma-endothelium interfaces. This new modeling approach was successfully applied towards pharmacokinetic modeling for use in topical ophthalmic drug design. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Review of Theoretical Prediction Models for Organic Extract Metabolites, Effect of Drying Temperature on Smooth Muscle Relaxing Activity Induced by Organic Extracts Specially Cecropia Obtusifolia Portal and Web Server Predictors of Drug-Protein Interaction.

    Science.gov (United States)

    Aguirre-Crespo, Francisco; García-Mera, Xerardo; Guillén-Poot, Mónica Anahi; May-Díaz, Héctor Fernado; Tun-Suárez, Adrián; Aguirre-Crespo, A; Hernández-Rodríguez, J; Vergara-Galicia, Jorge; Rodríguez-López, V; Prado-Prado, Francisco J

    2015-02-19

    Cecropia obtusifolia bertol is medicinal specie used in the treatment of diabetes mellitus and hypertension and it has scientific studies that support the traditional use. However, it is required to understand the influence of drying temperature on the yield and pharmacological activity. Drying rate, extraction efficiency, changes in the UV-Vis spectrum and estimating chlorophylls were stimulated with the increasing temperature. Finally, relaxant activity of vascular smooth muscle is increased by 70ºC and reducing ability by the method of CARF increases with temperature. Analytical studies are required to identify changes in the metabolic content and those that ensure the safety and efficacy for human consumption. In this sense, bioinformatic studies may be helpful. Studies such as QSAR can help us to study these metabolites derived from natural products. MIND-BETS model and NL MIND-BETS model to predict DPIs was introduced using MARCH-INSIDE (MI) software to calculate structural parameters for drugs and enzymes respectively. We firstly revised the state-of-art on the design with review of previous works with hypertension activity based on theoretical studies. A study, evaluating the effect of drying temperature of leaves of C. obtusifolia on the relaxing of vascular smooth muscle, antioxidant activity and the presence of chlorophylls, with a focus on Cecropia metabolites. Last, we carried out QSAR studies using MIND-BEST and NL MIND-BEST web servers in order to understand the essential metabolites structural requirement for binding with receptors for FDA proteins.

  18. 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.

  19. Prediction of Drug-Plasma Protein Binding Using Artificial Intelligence Based Algorithms.

    Science.gov (United States)

    Kumar, Rajnish; Sharma, Anju; Siddiqui, Mohammed Haris; Tiwari, Rajesh Kumar

    2017-12-18

    Plasma protein binding (PPB) has vital importance in the characterization of drug distribution in the systemic circulation. Unfavorable PPB can pose a negative effect on clinical development of promising drug candidates. The drug distribution properties should be considered at the initial phases of the drug design and development. Therefore, PPB prediction models are receiving an increased attention. In the current study, we present a systematic approach using Support vector machine, Artificial neural network, k- nearest neighbor, Probabilistic neural network, Partial least square and Linear discriminant analysis to relate various in vitro and in silico molecular descriptors to a diverse dataset of 736 drugs/drug-like compounds. The overall accuracy of Support vector machine with Radial basis function kernel came out to be comparatively better than the rest of applied algorithms. The training set accuracy, validation set accuracy, precision, sensitivity, specificity and F1 score for the Suprort vector machine was found to be 89.73%, 89.97%, 92.56%, 87.26%, 91.97% and 0.898 respectively. This model can potentially be useful in screening of relevant drug candidates at the preliminary stages of drug design and development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  20. 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. Copyright © 2014 Elsevier B.V. All rights reserved.

  1. Context Sensitive Modeling of Cancer Drug Sensitivity.

    Directory of Open Access Journals (Sweden)

    Bo-Juen Chen

    Full Text Available Recent screening of drug sensitivity in large panels of cancer cell lines provides a valuable resource towards developing algorithms that predict drug response. Since more samples provide increased statistical power, most approaches to prediction of drug sensitivity pool multiple cancer types together without distinction. However, pan-cancer results can be misleading due to the confounding effects of tissues or cancer subtypes. On the other hand, independent analysis for each cancer-type is hampered by small sample size. To balance this trade-off, we present CHER (Contextual Heterogeneity Enabled Regression, an algorithm that builds predictive models for drug sensitivity by selecting predictive genomic features and deciding which ones should-and should not-be shared across different cancers, tissues and drugs. CHER provides significantly more accurate models of drug sensitivity than comparable elastic-net-based models. Moreover, CHER provides better insight into the underlying biological processes by finding a sparse set of shared and type-specific genomic features.

  2. 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.

  3. Oral Delivery of Protein Drugs Bioencapsulated in Plant Cells.

    Science.gov (United States)

    Kwon, Kwang-Chul; Daniell, Henry

    2016-08-01

    Plants cells are now approved by the FDA for cost-effective production of protein drugs (PDs) in large-scale current Good Manufacturing Practice (cGMP) hydroponic growth facilities. In lyophilized plant cells, PDs are stable at ambient temperature for several years, maintaining their folding and efficacy. Upon oral delivery, PDs bioencapsulated in plant cells are protected in the stomach from acids and enzymes but are subsequently released into the gut lumen by microbes that digest the plant cell wall. The large mucosal area of the human intestine offers an ideal system for oral drug delivery. When tags (receptor-binding proteins or cell-penetrating peptides) are fused to PDs, they efficiently cross the intestinal epithelium and are delivered to the circulatory or immune system. Unique tags to deliver PDs to human immune or nonimmune cells have been developed recently. After crossing the epithelium, ubiquitous proteases cleave off tags at engineered sites. PDs are also delivered to the brain or retina by crossing the blood-brain or retinal barriers. This review highlights recent advances in PD delivery to treat Alzheimer's disease, diabetes, hypertension, Gaucher's or ocular diseases, as well as the development of affordable drugs by eliminating prohibitively expensive purification, cold chain and sterile delivery.

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

    International Nuclear Information System (INIS)

    Shu Shujun; Sun Lei; Zhang Xinge; Wu Zhongming; Wang Zhen; Li Chaoxing

    2011-01-01

    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.

  5. 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. © 2015 Elsevier Inc. All rights reserved.

  6. 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.

  7. Modelling drug flux through microporated skin.

    Science.gov (United States)

    Rzhevskiy, Alexey S; Guy, Richard H; Anissimov, Yuri G

    2016-11-10

    A simple mathematical equation has been developed to predict drug flux through microporated skin. The theoretical model is based on an approach applied previously to water evaporation through leaf stomata. Pore density, pore radius and drug molecular weight are key model parameters. The predictions of the model were compared with results derived from a simple, intuitive method using porated area alone to estimate the flux enhancement. It is shown that the new approach predicts significantly higher fluxes than the intuitive analysis, with transport being proportional to the total pore perimeter rather than area as intuitively anticipated. Predicted fluxes were in good general agreement with experimental data on drug delivery from the literature, and were quantitatively closer to the measured values than those derived from the intuitive, area-based approach. Copyright © 2016 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

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

    2014-01-01

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

  9. 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

  10. Mathematical modeling of drug release from lipid dosage forms.

    Science.gov (United States)

    Siepmann, J; Siepmann, F

    2011-10-10

    Lipid dosage forms provide an interesting potential for controlled drug delivery. In contrast to frequently used poly(ester) based devices for parenteral administration, they do not lead to acidification upon degradation and potential drug inactivation, especially in the case of protein drugs and other acid-labile active agents. The aim of this article is to give an overview on the current state of the art of mathematical modeling of drug release from this type of advanced drug delivery systems. Empirical and semi-empirical models are described as well as mechanistic theories, considering diffusional mass transport, potentially limited drug solubility and the leaching of other, water-soluble excipients into the surrounding bulk fluid. Various practical examples are given, including lipid microparticles, beads and implants, which can successfully be used to control the release of an incorporated drug during periods ranging from a few hours up to several years. The great benefit of mechanistic mathematical theories is the possibility to quantitatively predict the effects of different formulation parameters and device dimensions on the resulting drug release kinetics. Thus, in silico simulations can significantly speed up product optimization. This is particularly useful if long release periods (e.g., several months) are targeted, since experimental trial-and-error studies are highly time-consuming in these cases. In the future it would be highly desirable to combine mechanistic theories with the quantitative description of the drug fate in vivo, ideally including the pharmacodynamic efficacy of the treatments. Copyright © 2011 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

    Blundell, Tom L

    2017-07-01

    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.

  12. A new strategy to deliver synthetic protein drugs: self-reproducible biologics using minicircles.

    Science.gov (United States)

    Yi, Hyoju; Kim, Youngkyun; Kim, Juryun; Jung, Hyerin; Rim, Yeri Alice; Jung, Seung Min; Park, Sung-Hwan; Ju, Ji Hyeon

    2014-08-05

    Biologics are the most successful drugs used in anticytokine therapy. However, they remain partially unsuccessful because of the elevated cost of their synthesis and purification. Development of novel biologics has also been hampered by the high cost. Biologics are made of protein components; thus, theoretically, they can be produced in vivo. Here we tried to invent a novel strategy to allow the production of synthetic drugs in vivo by the host itself. The recombinant minicircles encoding etanercept or tocilizumab, which are synthesized currently by pharmaceutical companies, were injected intravenously into animal models. Self-reproduced etanercept and tocilizumab were detected in the serum of mice. Moreover, arthritis subsided in mice that were injected with minicircle vectors carrying biologics. Self-reproducible biologics need neither factory facilities for drug production nor clinical processes, such as frequent drug injection. Although this novel strategy is in its very early conceptual stage, it seems to represent a potential alternative method for the delivery of biologics.

  13. Moonlighting adenosine deaminase: a target protein for drug development.

    Science.gov (United States)

    Cortés, Antoni; Gracia, Eduard; Moreno, Estefania; Mallol, Josefa; Lluís, Carme; Canela, Enric I; Casadó, Vicent

    2015-01-01

    Interest in adenosine deaminase (ADA) in the context of medicine has mainly focused on its enzymatic activity. This is justified by the importance of the reaction catalyzed by ADA not only for the intracellular purine metabolism, but also for the extracellular purine metabolism as well, because of its capacity as a regulator of the concentration of extracellular adenosine that is able to activate adenosine receptors (ARs). In recent years, other important roles have been described for ADA. One of these, with special relevance in immunology, is the capacity of ADA to act as a costimulator, promoting T-cell proliferation and differentiation mainly by interacting with the differentiation cluster CD26. Another role is the ability of ADA to act as an allosteric modulator of ARs. These receptors have very general physiological implications, particularly in the neurological system where they play an important role. Thus, ADA, being a single chain protein, performs more than one function, consistent with the definition of a moonlighting protein. Although ADA has never been associated with moonlighting proteins, here we consider ADA as an example of this family of multifunctional proteins. In this review, we discuss the different roles of ADA and their pathological implications. We propose a mechanism by which some of their moonlighting functions can be coordinated. We also suggest that drugs modulating ADA properties may act as modulators of the moonlighting functions of ADA, giving them additional potential medical interest. © 2014 Wiley Periodicals, Inc.

  14. Protein microarray: sensitive and effective immunodetection for drug residues

    Directory of Open Access Journals (Sweden)

    Zer Cindy

    2010-02-01

    Full Text Available Abstract Background Veterinary drugs such as clenbuterol (CL and sulfamethazine (SM2 are low molecular weight ( Results The artificial antigens were spotted on microarray slides. Standard concentrations of the compounds were added to compete with the spotted antigens for binding to the antisera to determine the IC50. Our microarray assay showed the IC50 were 39.6 ng/ml for CL and 48.8 ng/ml for SM2, while the traditional competitive indirect-ELISA (ci-ELISA showed the IC50 were 190.7 ng/ml for CL and 156.7 ng/ml for SM2. We further validated the two methods with CL fortified chicken muscle tissues, and the protein microarray assay showed 90% recovery while the ci-ELISA had 76% recovery rate. When tested with CL-fed chicken muscle tissues, the protein microarray assay had higher sensitivity (0.9 ng/g than the ci-ELISA (0.1 ng/g for detection of CL residues. Conclusions The protein microarrays showed 4.5 and 3.5 times lower IC50 than the ci-ELISA detection for CL and SM2, respectively, suggesting that immunodetection of small molecules with protein microarray is a better approach than the traditional ELISA technique.

  15. Dengue human infection models supporting drug development.

    Science.gov (United States)

    Whitehorn, James; Van, Vinh Chau Nguyen; Simmons, Cameron P

    2014-06-15

    Dengue is a arboviral infection that represents a major global health burden. There is an unmet need for effective dengue therapeutics to reduce symptoms, duration of illness and incidence of severe complications. Here, we consider the merits of a dengue human infection model (DHIM) for drug development. A DHIM could allow experimentally controlled studies of candidate therapeutics in preselected susceptible volunteers, potentially using smaller sample sizes than trials that recruited patients with dengue in an endemic country. In addition, the DHIM would assist the conduct of intensive pharmacokinetic and basic research investigations and aid in determining optimal drug dosage. Furthermore, a DHIM could help establish proof of concept that chemoprophylaxis against dengue is feasible. The key challenge in developing the DHIM for drug development is to ensure the model reliably replicates the typical clinical and laboratory features of naturally acquired, symptomatic dengue. © The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America.

  16. A Mesoscopic Model for Protein-Protein Interactions in Solution

    OpenAIRE

    Lund, Mikael; Jönsson, Bo

    2003-01-01

    Protein self-association may be detrimental in biological systems, but can be utilized in a controlled fashion for protein crystallization. It is hence of considerable interest to understand how factors like solution conditions prevent or promote aggregation. Here we present a computational model describing interactions between protein molecules in solution. The calculations are based on a molecular description capturing the detailed structure of the protein molecule using x-ray or nuclear ma...

  17. Models of protein-ligand crystal structures: trust, but verify

    Science.gov (United States)

    Deller, Marc C.; Rupp, Bernhard

    2015-09-01

    X-ray crystallography provides the most accurate models of protein-ligand structures. These models serve as the foundation of many computational methods including structure prediction, molecular modelling, and structure-based drug design. The success of these computational methods ultimately depends on the quality of the underlying protein-ligand models. X-ray crystallography offers the unparalleled advantage of a clear mathematical formalism relating the experimental data to the protein-ligand model. In the case of X-ray crystallography, the primary experimental evidence is the electron density of the molecules forming the crystal. The first step in the generation of an accurate and precise crystallographic model is the interpretation of the electron density of the crystal, typically carried out by construction of an atomic model. The atomic model must then be validated for fit to the experimental electron density and also for agreement with prior expectations of stereochemistry. Stringent validation of protein-ligand models has become possible as a result of the mandatory deposition of primary diffraction data, and many computational tools are now available to aid in the validation process. Validation of protein-ligand complexes has revealed some instances of overenthusiastic interpretation of ligand density. Fundamental concepts and metrics of protein-ligand quality validation are discussed and we highlight software tools to assist in this process. It is essential that end users select high quality protein-ligand models for their computational and biological studies, and we provide an overview of how this can be achieved.

  18. Drug screening using model systems: some basics

    Directory of Open Access Journals (Sweden)

    Ross Cagan

    2016-11-01

    Full Text Available An increasing number of laboratories that focus on model systems are considering drug screening. Executing a drug screen is complicated enough. But the path for moving initial hits towards the clinic requires a different knowledge base and even a different mindset. In this Editorial I discuss the importance of doing some homework before you start screening. 'Lead hits', 'patentable chemical space' and 'druggability' are all concepts worth exploring when deciding which screening path to take. I discuss some of the lessons I learned that may be useful as you navigate the screening matrix.

  19. Systematic synergy modeling: understanding drug synergy from a systems biology perspective.

    Science.gov (United States)

    Chen, Di; Liu, Xi; Yang, Yiping; Yang, Hongjun; Lu, Peng

    2015-09-16

    Owing to drug synergy effects, drug combinations have become a new trend in combating complex diseases like cancer, HIV and cardiovascular diseases. However, conventional synergy quantification methods often depend on experimental dose-response data which are quite resource-demanding. In addition, these methods are unable to interpret the explicit synergy mechanism. In this review, we give representative examples of how systems biology modeling offers strategies toward better understanding of drug synergy, including the protein-protein interaction (PPI) network-based methods, pathway dynamic simulations, synergy network motif recognitions, integrative drug feature calculations, and "omic"-supported analyses. Although partially successful in drug synergy exploration and interpretation, more efforts should be put on a holistic understanding of drug-disease interactions, considering integrative pharmacology and toxicology factors. With a comprehensive and deep insight into the mechanism of drug synergy, systems biology opens a novel avenue for rational design of effective drug combinations.

  20. Structure determination of drug target proteins by neutron crystallography

    International Nuclear Information System (INIS)

    Tamada, Taro; Adachi, Motoyasu

    2010-01-01

    High resolution X-ray crystallography provides information for most of the atoms comprising the proteins, with the exception of hydrogen atoms. Whereas, neutron crystallography, which is a powerful technique for locating hydrogen atoms, enables us to obtain accurate atomic positions within proteins. Neutron diffraction data can provide information of the location of hydrogen atoms to the structural information determined by X-ray crystallography. Here, we show the recent results of the structural determination of drug-target proteins, porcine pancreatic elastase and human immuno-deficiency virus type-1 protease by both X-ray and neutron diffraction. The structure of porcine pancreatic elastase with its potent inhibitor was determined to 0.094 nm resolution by X-ray diffraction and 0.165 nm resolution by neutron diffraction. The structure of HIV-PR with its potent inhibitor was also determined to 0.093 nm resolution by X-ray diffraction and 0.19 nm resolution by neutron diffraction. The ionization state and the location of hydrogen atoms of the catalytic residue in these enzymes were determined by neutron diffraction. Furthermore, collaborative use of both X-ray and neutron crystallography to identify the location of ambiguous hydrogen atoms will be shown. (author)

  1. Inventory and function of yeast ABC proteins: about sex, stress, pleiotropic drug and heavy metal resistance.

    Science.gov (United States)

    Bauer, B E; Wolfger, H; Kuchler, K

    1999-12-06

    Saccharomyces cerevisiae was the first eukaryotic organism whose complete genome sequence has been determined, uncovering the existence of numerous genes encoding proteins of the ATP-binding cassette (ABC) family. Fungal ABC proteins are implicated in a variety of cellular functions, ranging from clinical drug resistance development, pheromone secretion, mitochondrial function, peroxisome biogenesis, translation elongation, stress response to cellular detoxification. Moreover, some yeast ABC proteins are orthologues of human disease genes, which makes yeast an excellent model system to study the molecular mechanisms of ABC protein-mediated disease. This review provides a comprehensive discussion and update on the function and transcriptional regulation of all known ABC genes from yeasts, including those discovered in fungal pathogens.

  2. Programmable release of multiple protein drugs from aptamer-functionalized hydrogels via nucleic acid hybridization.

    Science.gov (United States)

    Battig, Mark R; Soontornworajit, Boonchoy; Wang, Yong

    2012-08-01

    Polymeric delivery systems have been extensively studied to achieve localized and controlled release of protein drugs. However, it is still challenging to control the release of multiple protein drugs in distinct stages according to the progress of disease or treatment. This study successfully demonstrates that multiple protein drugs can be released from aptamer-functionalized hydrogels with adjustable release rates at predetermined time points using complementary sequences (CSs) as biomolecular triggers. Because both aptamer-protein interactions and aptamer-CS hybridization are sequence-specific, aptamer-functionalized hydrogels constitute a promising polymeric delivery system for the programmable release of multiple protein drugs to treat complex human diseases.

  3. 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.

  4. 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.

  5. Convective transport of highly plasma protein bound drugs facilitates direct penetration into deep tissues after topical application

    Science.gov (United States)

    Dancik, Yuri; Anissimov, Yuri G; Jepps, Owen G; Roberts, Michael S

    2012-01-01

    AIMS To relate the varying dermal, subcutaneous and muscle microdialysate concentrations found in man after topical application to the nature of the drug applied and to the underlying physiology. METHODS We developed a physiologically based pharmacokinetic model in which transport to deeper tissues was determined by tissue diffusion, blood, lymphatic and intersitial flow transport and drug properties. The model was applied to interpret published human microdialysis data, estimated in vitro dermal diffusion and protein binding affinity of drugs that have been previously applied topically in vivo and measured in deep cutaneous tissues over time. RESULTS Deeper tissue microdialysis concentrations for various drugs in vivo vary widely. Here, we show that carriage by the blood to the deeper tissues below topical application sites facilitates the transport of highly plasma protein bound drugs that penetrate the skin, leading to rapid and significant concentrations in those tissues. Hence, the fractional concentration for the highly plasma protein bound diclofenac in deeper tissues is 0.79 times that in a probe 4.5 mm below a superficial probe whereas the corresponding fractional concentration for the poorly protein bound nicotine is 0.02. Their corresponding estimated in vivo lag times for appearance of the drugs in the deeper probes were 1.1 min for diclofenac and 30 min for nicotine. CONCLUSIONS Poorly plasma protein bound drugs are mainly transported to deeper tissues after topical application by tissue diffusion whereas the transport of highly plasma protein bound drugs is additionally facilitated by convective blood, lymphatic and interstitial transport to deep tissues. PMID:21999217

  6. 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.

  7. Acetoxy drug : Protein transacetylase of buffalo liver - Characterization and mass spectrometry of the acetylated protein product

    NARCIS (Netherlands)

    Kohli, E.; Gaspari, M.; Raj, H.G.; Parmar, V.S.; Sharma, S.K.; Greef, J. van der; Kumari, R.; Gupta, G.; Seema; Khurana, P.; Tyagi, Y.K.; Watterson, A.C.; Olsen, C.E.

    2004-01-01

    The purification and characterization of the buffalo liver microsomal transacetylase (TAase) catalyzing the transfer of acetyl groups from a model acetoxy drug: 7,8-diacetoxy-4-methylcoumarin (DAMC) to GST3-3 has been described here. The enzyme was routinely assayed using DAMC and cytosolic GST as

  8. Detection of First-Line Drug Resistance Mutations and Drug-Protein Interaction Dynamics from Tuberculosis Patients in South India.

    Science.gov (United States)

    Nachappa, Somanna Ajjamada; Neelambike, Sumana M; Amruthavalli, Chokkanna; Ramachandra, Nallur B

    2017-08-16

    Diagnosis of drug-resistant tuberculosis predominantly relies on culture-based drug susceptibility testing, which take weeks to produce a result and a more time-efficient alternative method is multiplex allele-specific PCR (MAS-PCR). Also, understanding the role of mutations in causing resistance helps better drug designing. To evaluate the ability of MAS-PCR in the detection of drug resistance and to understand the mechanism of interaction of drugs with mutant proteins in Mycobacterium tuberculosis. Detection of drug-resistant mutations using MAS-PCR and validation through DNA sequencing. MAS-PCR targeted five loci on three genes, katG 315 and inhA -15 for the drug isoniazid (INH), and rpoB 516, 526, and 531 for rifampicin (RIF). Furthermore, the sequence data were analyzed to study the effect on interaction of the anti-TB drug molecule with the target protein using in silico docking. We identified drug-resistant mutations in 8 out of 114 isolates with 2 of them as multidrug-resistant TB using MAS-PCR. DNA sequencing confirmed only six of these, recording a sensitivity of 85.7% and specificity of 99.3% for MAS-PCR. Molecular docking showed estimated free energy of binding (ΔG) being higher for RIF binding with RpoB S531L mutant. Codon 315 in KatG does not directly interact with INH but blocks the drug access to active site. We propose DNA sequencing-based drug resistance detection for TB, which is more accurate than MAS-PCR. Understanding the action of resistant mutations in disrupting the normal drug-protein interaction aids in designing effective drug alternatives.

  9. [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.

  10. Beyond Competitive Inhibition: Regulation of ABC Transporters by Kinases and Protein-Protein Interactions as Potential Mechanisms of Drug-Drug Interactions.

    Science.gov (United States)

    Crawford, Rebecca R; Potukuchi, Praveen K; Schuetz, Erin G; Schuetz, John D

    2018-03-07

    ATP-binding cassette (ABC) transporters are transmembrane efflux transporters mediating the extrusion of an array of substrates ranging from amino acids and lipids to xenobiotics, and many therapeutic compounds, including anticancer drugs. The ABC transporters are also recognized as important contributors to pharmacokinetics, especially in drug-drug interactions and adverse drug effects. Drugs and xenobiotics, as well as pathological conditions, can influence the transcription of ABC transporters, or modify their activity or intracellular localization. Kinases can affect the aforementioned processes for ABC transporters as do protein interactions. In this review, we focus on the ABC transporters ABCB1, ABCB11, ABCC1, ABCC4 and ABCG2 and illustrate how kinases and protein-protein interactions affect these transporters. The clinical relevance of these factors is currently unknown, however these examples suggest that our understanding of drug-drug interactions will benefit from further knowledge of how kinases and protein-protein interactions affect ABC transporters. The American Society for Pharmacology and Experimental Therapeutics.

  11. 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.

  12. Application of Minicircle Technology of Self-Reproducing Synthetic Protein Drugs in Preventing Skin Allograft Rejection.

    Science.gov (United States)

    Lim, Sun Woo; Kim, Young Kyun; Park, Narae; Jin, Long; Jin, Jian; Doh, Kyoung Chan; Ju, Ji Hyeon; Yang, Chul Woo

    2015-07-30

    Recently, it has been reported that minicircle vectors could allow the expression of transgenes using the protein synthesis system of the host. Here, we tested a novel strategy to permit the production of synthetic biologics using minicircle technology and evaluated their feasibility as a therapeutic tool in a skin allograft model. We engineered vectors to carry cassette sequences for tocilizumab [anti-soluble interleukin-6 receptor (sIL-6R) antibody] and/or etanercept [tumor necrosis factor receptor 2 (TNFR2)-Fc fusion protein], and then isolated minicircle vectors from the parent vectors. We verified the production of proteins from minicircles and their duration in HEK293T cells and mice. We also evaluated whether these proteins were expressed at levels sufficient to ameliorate skin allograft rejection in mice. Each minicircle transfected into cells was detectable for at least 30 days. In mice, the drugs were mainly expressed in the liver and were detectable for at least 10 days after a single injection. These drugs were also detected in the blood. Treatment of mice with minicircles prolonged skin allograft survival, which was accompanied by a reduction of the number of interferon-γ+ or interleukin-17+ lymphocytes and an induction of forkhead box P3 expression. These findings suggest that blocking of sIL-6R and/or TNF-α using minicircles encoding tocilizumab and/or etanercept was functionally active and relevant for preventing acute allograft rejection. Self-reproducing synthetic protein drugs produced using minicircle technology are potentially powerful tools for preventing acute rejection in transplantation.

  13. The human multidrug resistance-associated protein MRP is a plasma membrane drug-efflux pump

    NARCIS (Netherlands)

    Zaman, G. J.; Flens, M. J.; van Leusden, M. R.; de Haas, M.; Mülder, H. S.; Lankelma, J.; Pinedo, H. M.; Scheper, R. J.; Baas, F.; Broxterman, H. J.

    1994-01-01

    The multidrug-resistance associated protein MRP is a 180- to 195-kDa membrane protein associated with resistance of human tumor cells to cytotoxic drugs. We have investigated how MRP confers drug resistance in SW-1573 human lung carcinoma cells by generating a subline stably transfected with an

  14. Drug delivery to the kidneys and the bladder with the low molecular weight protein lysozyme

    NARCIS (Netherlands)

    Kok, Robbert J.; Haas, Marijke; Moolenaar, Frits; de Zeeuw, Dick; Meijer, Dirk K.F.

    1998-01-01

    The low molecular weight protein (LMWP) lysozyme is a suitable drug carrier for renal drug targeting. When the tubular reabsorption of a can be prevented, the protein will be excreted in the urine. In this way, lysozyme (LZM) conjugates might also be used as carriers for targeting to the urinary

  15. Drug delivery to the kidneys and the bladder with the low molecular weight protein lysozyme

    NARCIS (Netherlands)

    Kok, RJ; Haas, M; Moolenaar, F; de Zeeuw, D; Meijer, DKF

    1998-01-01

    The low molecular weight protein (LMWP) lysozyme is a suitable drug carrier for renal drug targeting. When the tubular reabsorption of a LMWP can be prevented, the protein will be excreted in the urine. In this way lysozyme (LZM) conjugates might also be used as carriers for targeting to the urinary

  16. Challenges in modelling nanoparticles for drug delivery

    International Nuclear Information System (INIS)

    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. (topical review)

  17. Identification of putative drug targets for human sperm-egg interaction defect using protein network approach.

    Science.gov (United States)

    Sabetian, Soudabeh; Shamsir, Mohd Shahir

    2015-07-18

    Sperm-egg interaction defect is a significant cause of in-vitro fertilization failure for infertile cases. Numerous molecular interactions in the form of protein-protein interactions mediate the sperm-egg membrane interaction process. Recent studies have demonstrated that in addition to experimental techniques, computational methods, namely protein interaction network approach, can address protein-protein interactions between human sperm and egg. Up to now, no drugs have been detected to treat sperm-egg interaction disorder, and the initial step in drug discovery research is finding out essential proteins or drug targets for a biological process. The main purpose of this study is to identify putative drug targets for human sperm-egg interaction deficiency and consider if the detected essential proteins are targets for any known drugs using protein-protein interaction network and ingenuity pathway analysis. We have created human sperm-egg protein interaction networks with high confidence, including 106 nodes and 415 interactions. Through topological analysis of the network with calculation of some metrics, such as connectivity and betweenness centrality, we have identified 13 essential proteins as putative drug targets. The potential drug targets are from integrins, fibronectins, epidermal growth factor receptors, collagens and tetraspanins protein families. We evaluated these targets by ingenuity pathway analysis, and the known drugs for the targets have been detected, and the possible effective role of the drugs on sperm-egg interaction defect has been considered. These results showed that the drugs ocriplasmin (Jetrea©), gefitinib (Iressa©), erlotinib hydrochloride (Tarceva©), clingitide, cetuximab (Erbitux©) and panitumumab (Vectibix©) are possible candidates for efficacy testing for the treatment of sperm-egg interaction deficiency. Further experimental validation can be carried out to confirm these results. We have identified the first potential list of

  18. Protein Reporter Bioassay Systems for the Phenotypic Screening of Candidate Drugs: A Mouse Platform for Anti-Aging Drug Screening

    Directory of Open Access Journals (Sweden)

    Isao Shimokawa

    2012-02-01

    Full Text Available Recent drug discovery efforts have utilized high throughput screening (HTS of large chemical libraries to identify compounds that modify the activity of discrete molecular targets. The molecular target approach to drug screening is widely used in the pharmaceutical and biotechnology industries, because of the amount of knowledge now available regarding protein structure that has been obtained by computer simulation. The molecular target approach requires that the structure of target molecules, and an understanding of their physiological functions, is known. This approach to drug discovery may, however, limit the identification of novel drugs. As an alternative, the phenotypic- or pathway-screening approach to drug discovery is gaining popularity, particularly in the academic sector. This approach not only provides the opportunity to identify promising drug candidates, but also enables novel information regarding biological pathways to be unveiled. Reporter assays are a powerful tool for the phenotypic screening of compound libraries. Of the various reporter genes that can be used in such assays, those encoding secreted proteins enable the screening of hit molecules in both living cells and animals. Cell- and animal-based screens enable simultaneous evaluation of drug metabolism or toxicity with biological activity. Therefore, drug candidates identified in these screens may have increased biological efficacy and a lower risk of side effects in humans. In this article, we review the reporter bioassay systems available for phenotypic drug discovery.

  19. 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.

  20. Protein folding and non-conventional drug design: a primer for nuclear structure physicists

    International Nuclear Information System (INIS)

    Broglia, R.A.; Tiana, G.; Provasi, D.

    2004-01-01

    Some of the paradigms emerging from the study of the phenomena of phase transitions in finite many-body systems, like e.g. the atomic nucleus can be used at profit to solve the protein folding problem within the framework of simple (although not oversimplified) models. From this solution a paradigm emerges for the design of non-conventional drugs, which inhibit enzymatic action without inducing resistance (mutations). The application of these concepts to the design of an inhibitor to the HIV-protease central in the life cycle of the HIV virus is discussed

  1. The evolution of regulators of G protein signalling proteins as drug targets - 20 years in the making: IUPHAR Review 21.

    Science.gov (United States)

    Sjögren, B

    2017-03-01

    Regulators of G protein signalling (RGS) proteins are celebrating the 20th anniversary of their discovery. The unveiling of this new family of negative regulators of G protein signalling in the mid-1990s solved a persistent conundrum in the G protein signalling field, in which the rate of deactivation of signalling cascades in vivo could not be replicated in exogenous systems. Since then, there has been tremendous advancement in the knowledge of RGS protein structure, function, regulation and their role as novel drug targets. RGS proteins play an important modulatory role through their GTPase-activating protein (GAP) activity at active, GTP-bound Gα subunits of heterotrimeric G proteins. They also possess many non-canonical functions not related to G protein signalling. Here, an update on the status of RGS proteins as drug targets is provided, highlighting advances that have led to the inclusion of RGS proteins in the IUPHAR/BPS Guide to PHARMACOLOGY database of drug targets. © 2017 The British Pharmacological Society.

  2. PockDrug-Server: a new web server for predicting pocket druggability on holo and apo proteins.

    Science.gov (United States)

    Hussein, Hiba Abi; Borrel, Alexandre; Geneix, Colette; Petitjean, Michel; Regad, Leslie; Camproux, Anne-Claude

    2015-07-01

    Predicting protein pocket's ability to bind drug-like molecules with high affinity, i.e. druggability, is of major interest in the target identification phase of drug discovery. Therefore, pocket druggability investigations represent a key step of compound clinical progression projects. Currently computational druggability prediction models are attached to one unique pocket estimation method despite pocket estimation uncertainties. In this paper, we propose 'PockDrug-Server' to predict pocket druggability, efficient on both (i) estimated pockets guided by the ligand proximity (extracted by proximity to a ligand from a holo protein structure) and (ii) estimated pockets based solely on protein structure information (based on amino atoms that form the surface of potential binding cavities). PockDrug-Server provides consistent druggability results using different pocket estimation methods. It is robust with respect to pocket boundary and estimation uncertainties, thus efficient using apo pockets that are challenging to estimate. It clearly distinguishes druggable from less druggable pockets using different estimation methods and outperformed recent druggability models for apo pockets. It can be carried out from one or a set of apo/holo proteins using different pocket estimation methods proposed by our web server or from any pocket previously estimated by the user. PockDrug-Server is publicly available at: http://pockdrug.rpbs.univ-paris-diderot.fr. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  3. Recent advances in (therapeutic protein drug development [version 1; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    H.A. Daniel Lagassé

    2017-02-01

    Full Text Available 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.

  4. Investigating drug repositioning opportunities in FDA drug labels through topic modeling.

    Science.gov (United States)

    Bisgin, Halil; Liu, Zhichao; Kelly, Reagan; Fang, Hong; Xu, Xiaowei; Tong, Weida

    2012-01-01

    Drug repositioning offers an opportunity to revitalize the slowing drug discovery pipeline by finding new uses for currently existing drugs. Our hypothesis is that drugs sharing similar side effect profiles are likely to be effective for the same disease, and thus repositioning opportunities can be identified by finding drug pairs with similar side effects documented in U.S. Food and Drug Administration (FDA) approved drug labels. The safety information in the drug labels is usually obtained in the clinical trial and augmented with the observations in the post-market use of the drug. Therefore, our drug repositioning approach can take the advantage of more comprehensive safety information comparing with conventional de novo approach. A probabilistic topic model was constructed based on the terms in the Medical Dictionary for Regulatory Activities (MedDRA) that appeared in the Boxed Warning, Warnings and Precautions, and Adverse Reactions sections of the labels of 870 drugs. Fifty-two unique topics, each containing a set of terms, were identified by using topic modeling. The resulting probabilistic topic associations were used to measure the distance (similarity) between drugs. The success of the proposed model was evaluated by comparing a drug and its nearest neighbor (i.e., a drug pair) for common indications found in the Indications and Usage Section of the drug labels. Given a drug with more than three indications, the model yielded a 75% recall, meaning 75% of drug pairs shared one or more common indications. This is significantly higher than the 22% recall rate achieved by random selection. Additionally, the recall rate grows rapidly as the number of drug indications increases and reaches 84% for drugs with 11 indications. The analysis also demonstrated that 65 drugs with a Boxed Warning, which indicates significant risk of serious and possibly life-threatening adverse effects, might be replaced with safer alternatives that do not have a Boxed Warning. In

  5. Photoactive assemblies of organic compounds and biomolecules: drug-protein supramolecular systems

    OpenAIRE

    Vayá Pérez, Ignacio; Lhiaubet-Vallet, Virginie Lyria; Jiménez Molero, María Consuelo; Miranda Alonso, Miguel Ángel

    2014-01-01

    [EN] The properties of singlet and triplet excited states are strongly medium-dependent. Hence, these species constitute valuable tools as reporters to probe compartmentalised microenvironments, including drug@protein supramolecular systems. In the present review, the attention is focused on the photophysical properties of the probe drugs (rather than those of the protein chromophores) using transport proteins (serum albumins and 1-acid glycoproteins) as hosts. Specifically, f...

  6. 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.

  7. Modeling disordered protein interactions from biophysical principles.

    Directory of Open Access Journals (Sweden)

    Lenna X Peterson

    2017-04-01

    Full Text Available Disordered protein-protein interactions (PPIs, those involving a folded protein and an intrinsically disordered protein (IDP, are prevalent in the cell, including important signaling and regulatory pathways. IDPs do not adopt a single dominant structure in isolation but often become ordered upon binding. To aid understanding of the molecular mechanisms of disordered PPIs, it is crucial to obtain the tertiary structure of the PPIs. However, experimental methods have difficulty in solving disordered PPIs and existing protein-protein and protein-peptide docking methods are not able to model them. Here we present a novel computational method, IDP-LZerD, which models the conformation of a disordered PPI by considering the biophysical binding mechanism of an IDP to a structured protein, whereby a local segment of the IDP initiates the interaction and subsequently the remaining IDP regions explore and coalesce around the initial binding site. On a dataset of 22 disordered PPIs with IDPs up to 69 amino acids, successful predictions were made for 21 bound and 18 unbound receptors. The successful modeling provides additional support for biophysical principles. Moreover, the new technique significantly expands the capability of protein structure modeling and provides crucial insights into the molecular mechanisms of disordered PPIs.

  8. Semiconductor technology in protein kinase research and drug discovery: sensing a revolution.

    Science.gov (United States)

    Bhalla, Nikhil; Di Lorenzo, Mirella; Estrela, Pedro; Pula, Giordano

    2017-02-01

    Since the discovery of protein kinase activity in 1954, close to 600 kinases have been discovered that have crucial roles in cell physiology. In several pathological conditions, aberrant protein kinase activity leads to abnormal cell and tissue physiology. Therefore, protein kinase inhibitors are investigated as potential treatments for several diseases, including dementia, diabetes, cancer and autoimmune and cardiovascular disease. Modern semiconductor technology has recently been applied to accelerate the discovery of novel protein kinase inhibitors that could become the standard-of-care drugs of tomorrow. Here, we describe current techniques and novel applications of semiconductor technologies in protein kinase inhibitor drug discovery. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. 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)…

  10. Comprehensive Analysis of Homologous Proteins for Specific Drug ...

    African Journals Online (AJOL)

    A drug is a chemical substance used in the diagnosis, treatment or prevention of disease or as a component of a medication, should be specific and freedom from side affect. Many issues should be addressed while designing a new drug or improving existing compound. The increase in the interdisciplinary nature of science ...

  11. Protein-protein interactions as a strategy towards protein-specific drug design: the example of ataxin-1.

    Directory of Open Access Journals (Sweden)

    Cesira de Chiara

    Full Text Available A main challenge for structural biologists is to understand the mechanisms that discriminate between molecular interactions and determine function. Here, we show how partner recognition of the AXH domain of the transcriptional co-regulator ataxin-1 is fine-tuned by a subtle balance between self- and hetero-associations. Ataxin-1 is the protein responsible for the hereditary spinocerebellar ataxia type 1, a disease linked to protein aggregation and transcriptional dysregulation. Expansion of a polyglutamine tract is essential for ataxin-1 aggregation, but the sequence-wise distant AXH domain plays an important aggravating role in the process. The AXH domain is also a key element for non-aberrant function as it intervenes in interactions with multiple protein partners. Previous data have shown that AXH is dimeric in solution and forms a dimer of dimers when crystallized. By solving the structure of a complex of AXH with a peptide from the interacting transcriptional repressor CIC, we show that the dimer interface of AXH is displaced by the new interaction and that, when blocked by the CIC peptide AXH aggregation and misfolding are impaired. This is a unique example in which palindromic self- and hetero-interactions within a sequence with chameleon properties discriminate the partner. We propose a drug design strategy for the treatment of SCA1 that is based on the information gained from the AXH/CIC complex.

  12. Micro-Environmental Signature of The Interactions between Druggable Target Protein, Dipeptidyl Peptidase-IV, and Anti-Diabetic Drugs

    OpenAIRE

    Chakraborty, Chiranjib; Mallick, Bidyut; Sharma, Ashish Ranjan; Sharma, Garima; Jagga, Supriya; Doss, C George Priya; Nam, Ju-Suk; Lee, Sang-Soo

    2016-01-01

    Objective Druggability of a target protein depends on the interacting micro-environment between the target protein and drugs. Therefore, a precise knowledge of the interacting micro-environment between the target protein and drugs is requisite for drug discovery process. To understand such micro-environment, we performed in silico interaction analysis between a human target protein, Dipeptidyl Peptidase-IV (DPP-4), and three anti-diabetic drugs (saxagliptin, linagliptin and vildagliptin). ...

  13. Semi-supervised drug-protein interaction prediction from heterogeneous biological spaces.

    Science.gov (United States)

    Xia, Zheng; Wu, Ling-Yun; Zhou, Xiaobo; Wong, Stephen T C

    2010-09-13

    Predicting drug-protein interactions from heterogeneous biological data sources is a key step for in silico drug discovery. The difficulty of this prediction task lies in the rarity of known drug-protein interactions and myriad unknown interactions to be predicted. To meet this challenge, a manifold regularization semi-supervised learning method is presented to tackle this issue by using labeled and unlabeled information which often generates better results than using the labeled data alone. Furthermore, our semi-supervised learning method integrates known drug-protein interaction network information as well as chemical structure and genomic sequence data. Using the proposed method, we predicted certain drug-protein interactions on the enzyme, ion channel, GPCRs, and nuclear receptor data sets. Some of them are confirmed by the latest publicly available drug targets databases such as KEGG. We report encouraging results of using our method for drug-protein interaction network reconstruction which may shed light on the molecular interaction inference and new uses of marketed drugs.

  14. Application of Model Animals in the Study of Drug Toxicology

    Science.gov (United States)

    Song, Yagang; Miao, Mingsan

    2018-01-01

    Drug safety is a key factor in drug research and development, Drug toxicology test is the main method to evaluate the safety of drugs, The body condition of an animal has important implications for the results of the study, Previous toxicological studies of drugs were carried out in normal animals in the past, There is a great deviation from the clinical practice.The purpose of this study is to investigate the necessity of model animals as a substitute for normal animals for toxicological studies, It is expected to provide exact guidance for future drug safety evaluation.

  15. 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.

  16. 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 pprotein

  17. High-throughput oxidation screen of antibody-drug conjugates by analytical protein A chromatography following IdeS digest.

    Science.gov (United States)

    Buecheler, Jakob W; Winzer, Matthias; Weber, Christian; Gieseler, Henning

    2018-05-01

    Oxidation of protein therapeutics is a major chemical degradation pathway which may impact bioactivity, serum half-life and stability. Therefore, oxidation is a relevant parameter which has to be monitored throughout formulation development. Methods such as HIC, RPLC and LC/MS achieve a separation of oxidized and non-oxidized species by differences in hydrophobicity. Antibody-drug conjugates (ADC) although are highly more complex due to the heterogeneity in linker, drug, drug-to-antibody ratio (DAR) and conjugation site. The analytical protein A chromatography can provide a simple and fast alternative to these common methods. A miniature analytical protein A chromatography method in combination with an IdeS digest was developed to analyse ADCs. The IdeS digest efficiency of an IgG1 was monitored using SEC-HPLC and non-reducing SDS-PAGE. An antibody-fluorescent dye conjugate was conjugated at different dye-to-antibody ratios as model construct to mimic an ADC. With IdeS, an almost complete digest of a model IgG1 can be achieved (digested protein amount >98%). This enables subsequent analytical protein A chromatography, which consequently eliminates any interference of payload with the stationary phase. A novel high-throughput method for an interchain cysteine-linked ADC oxidation screens during formulation development was developed. © 2018 Royal Pharmaceutical Society.

  18. 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 .

  19. 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.

  20. Drug discrimination models in anxiety and depression.

    Science.gov (United States)

    Andrews, J S; Stephens, D N

    1990-01-01

    Drug discrimination is a technique for investigating the stimulus properties of centrally active drugs. Although many studies have employed animals to investigate the stimulus properties of substances used clinically for the treatment of anxiety and depression, it would be a mistake to consider the internal discriminative stimuli as being related specifically to the anxiolytic or antidepressant properties of these drugs. Rather drug cues are better considered as relating to the pharmacological action of classes of compounds. Thus, benzodiazepine cues generalize to other compounds acting at benzodiazepine receptors, but not to substances (anxiolytic or otherwise) acting at 5-HT1A receptors. Similarly, antidepressants with different pharmacological properties, for example the tricyclic imipramine, or the phenylaminoketone buproprion produce distinct, unrelated discriminative stimuli. For this reason, the limits of drug discrimination techniques for investigating novel anxiolytic or antidepressant drugs should be clearly recognized. Attempts to identify an anxiogenic discriminative stimulus using pentylenetetrazole have also been misguided. In this technique it has proven difficult to separate unequivocally the pharmacological proconvulsant effects of the drug from the psychological construct anxiety. Nevertheless, drug discrimination remains a valuable technique for investigating pharmacological interactions in animals and man.

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

    Science.gov (United States)

    2014-06-20

    The primary reason for this was that 6 out of the 11 malaria drugs shared the same mechanism of action. They con- sisted of quinine , a natural product...lated to quinine , the original malaria drug. They (amodia- quine, mefloquine, chloroquine, hydroxychloroquine, and primaquine) are synthetic analogs of... quinine and therefore structurally very similar to it. Molecular structures of the hypertension, HIV, and malaria drugs are given in Additional file 1

  2. 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. Copyright © 2011 Wiley-Liss, Inc.

  3. Inhibitors of Trypanosoma cruzi Sir2 related protein 1 as potential drugs against Chagas disease.

    Directory of Open Access Journals (Sweden)

    Luís Gaspar

    2018-01-01

    Full Text Available Chagas disease remains one of the most neglected diseases in the world despite being the most important parasitic disease in Latin America. The characteristic chronic manifestation of chagasic cardiomyopathy is the region's leading cause of heart-related illness, causing significant mortality and morbidity. Due to the limited available therapeutic options, new drugs are urgently needed to control the disease. Sirtuins, also called Silent information regulator 2 (Sir2 proteins have long been suggested as interesting targets to treat different diseases, including parasitic infections. Recent studies on Trypanosoma cruzi sirtuins have hinted at the possibility to exploit these enzymes as a possible drug targets. In the present work, the T. cruzi Sir2 related protein 1 (TcSir2rp1 is genetically validated as a drug target and biochemically characterized for its NAD+-dependent deacetylase activity and its inhibition by the classic sirtuin inhibitor nicotinamide, as well as by bisnaphthalimidopropyl (BNIP derivatives, a class of parasite sirtuin inhibitors. BNIPs ability to inhibit TcSir2rp1, and anti-parasitic activity against T. cruzi amastigotes in vitro were investigated. The compound BNIP Spermidine (BNIPSpd (9, was found to be the most potent inhibitor of TcSir2rp1. Moreover, this compound showed altered trypanocidal activity against TcSir2rp1 overexpressing epimastigotes and anti-parasitic activity similar to the reference drug benznidazole against the medically important amastigotes, while having the highest selectivity index amongst the compounds tested. Unfortunately, BNIPSpd failed to treat a mouse model of Chagas disease, possibly due to its pharmacokinetic profile. Medicinal chemistry modifications of the compound, as well as alternative formulations may improve activity and pharmacokinetics in the future. Additionally, an initial TcSIR2rp1 model in complex with p53 peptide substrate was obtained from low resolution X-ray data (3.5 Å to

  4. CAPILLARY ZONE ELECTROPHORESIS IONSPRAY MASS-SPECTROMETRY OF A SYNTHETIC DRUG PROTEIN CONJUGATE MIXTURE

    NARCIS (Netherlands)

    KOSTIAINEN, R; FRANSSEN, EJF; BRUINS, AP

    1993-01-01

    Low-molecular-mass proteins, such as lysozyme, may be suitable carriers to target drugs to the kidney. Naproxen, an anti-inflammatory drug, has been conjugated with lysozyme via a covalent amide bond formed between the carboxylic acid function of naproxen and the amino group of one of the lysines in

  5. Drug penetration model of vinblastine-treated Caco-2 cultures.

    Science.gov (United States)

    Hellinger, Eva; Bakk, Mónika Laura; Pócza, Péter; Tihanyi, Károly; Vastag, Monika

    2010-09-11

    The penetrability of new chemical entities (NCE) is routinely screened in preclinical drug research. Although Caco-2 is a well-established model for human absorption, the identification of P-glycoprotein (P-gp) substrates and therefore the predictive accuracy of this model is not always satisfactory. Vinblastine has been reported to affect P-gp expression in Caco-2 cells. Therefore, this study was intended to assess the effect of sustained vinblastine treatment on the expression of P-gp, using RT-PCR and Western blot techniques. The P-gp functionality was monitored in transport assay, and metabolic enzyme activities were studied using probe substrates. Completion of culture medium with vinblastine (10nM during both the growing and the differentiation period) increased the P-gp mRNA and the expression at protein level. These changes were associated with the sensitive and steady identification of P-gp substrates in the bidirectional transport assay. While the vinblastine-treated Caco-2 (VB-Caco-2) based model reliably identified the P-gp substrates, the native Caco-2 model failed to recognize 7 out of the 11 reference substrates. The penetrability of passively permeating compounds correlated strongly (r(2)=0.9830) in the two models as expected. Omitting vinblastine from established VB-Caco-2 cultures did not affect either the protein level or the functionality of P-gp. Vinblastine did not alter the CYP mediated activities of the cells either. The higher sensitivity of VB-Caco-2 culture is also supported by the test results of NCEs, where 37% of NCEs were found to be P-gp substrate in VB-Caco-2 verified by verapamil, but only 9% by native Caco-2. Copyright (c) 2010 Elsevier B.V. All rights reserved.

  6. Modeling the modified drug release from curved shape drug delivery systems - Dome Matrix®.

    Science.gov (United States)

    Caccavo, D; Barba, A A; d'Amore, M; De Piano, R; Lamberti, G; Rossi, A; Colombo, P

    2017-12-01

    The controlled drug release from hydrogel-based drug delivery systems is a topic of large interest for research in pharmacology. The mathematical modeling of the behavior of these systems is a tool of emerging relevance, since the simulations can be of use in the design of novel systems, in particular for complex shaped tablets. In this work a model, previously developed, was applied to complex-shaped oral drug delivery systems based on hydrogels (Dome Matrix®). Furthermore, the model was successfully adopted in the description of drug release from partially accessible Dome Matrix® systems (systems with some surfaces coated). In these simulations, the erosion rate was used asa fitting parameter, and its dependence upon the surface area/volume ratio and upon the local fluid dynamics was discussed. The model parameters were determined by comparison with the drug release profile from a cylindrical tablet, then the model was successfully used for the prediction of the drug release from a Dome Matrix® system, for simple module configuration and for module assembled (void and piled) configurations. It was also demonstrated that, given the same initial S/V ratio, the drug release is independent upon the shape of the tablets but it is only influenced by the S/V evolution. The model reveals itself able to describe the observed phenomena, and thus it can be of use for the design of oral drug delivery systems, even if complex shaped. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. Photoactive assemblies of organic compounds and biomolecules: drug-protein supramolecular systems.

    Science.gov (United States)

    Vayá, Ignacio; Lhiaubet-Vallet, Virginie; Jiménez, M Consuelo; Miranda, Miguel A

    2014-06-21

    The properties of singlet and triplet excited states are strongly medium-dependent. Hence, these species constitute valuable tools as reporters to probe compartmentalised microenvironments, including drug@protein supramolecular systems. In the present review, the attention is focused on the photophysical properties of the probe drugs (rather than those of the protein chromophores) using transport proteins (serum albumins and α1-acid glycoproteins) as hosts. Specifically, fluorescence measurements allow investigation of the structural and dynamic properties of biomolecules or their complexes. Thus, the emission quantum yields and the decay kinetics of the drug singlet excited states provide key information to determine important parameters such as the stoichiometry of the complex, the binding constant, the relative degrees of occupancy of the different compartments, etc. Application of the FRET concept allows determination of donor-acceptor interchromophoric distances. In addition, anisotropy measurements can be related to the orientation of the drug within the binding sites, where the degrees of freedom for conformational relaxation are restricted. Transient absorption spectroscopy is also a potentially powerful tool to investigate the binding of drugs to proteins, where formation of encapsulated triplet excited states is favoured over other possible processes leading to ionic species (i.e. radical ions), and their photophysical properties are markedly sensitive to the microenvironment experienced within the protein binding sites. Even under aerobic conditions, the triplet lifetimes of protein-complexed drugs are remarkably long, which provides a broad dynamic range for identification of distinct triplet populations or for chiral discrimination. Specific applications of the laser flash photolysis technique include the determination of drug distribution among the bulk solution and the protein binding sites, competition of two types of proteins to bind a drug

  8. Magnetic field effect corroborated with docking study to explore photoinduced electron transfer in drug-protein interaction.

    Science.gov (United States)

    Chakraborty, Brotati; Roy, Atanu Singha; Dasgupta, Swagata; Basu, Samita

    2010-12-30

    Conventional spectroscopic tools such as absorption, fluorescence, and circular dichroism spectroscopy used in the study of photoinduced drug-protein interactions can yield useful information about ground-state and excited-state phenomena. However, photoinduced electron transfer (PET) may be a possible phenomenon in the drug-protein interaction, which may go unnoticed if only conventional spectroscopic observations are taken into account. Laser flash photolysis coupled with an external magnetic field can be utilized to confirm the occurrence of PET and authenticate the spin states of the radicals/radical ions formed. In the study of interaction of the model protein human serum albumin (HSA) with acridine derivatives, acridine yellow (AY) and proflavin (PF(+)), conventional spectroscopic tools along with docking study have been used to decipher the binding mechanism, and laser flash photolysis technique with an associated magnetic field (MF) has been used to explore PET. The results of fluorescence study indicate that fluorescence resonance energy transfer takes place from the protein to the acridine-based drugs. Docking study unveils the crucial role of Ser 232 residue of HSA in explaining the differential behavior of the two drugs towards the model protein. Laser flash photolysis experiments help to identify the radicals/radical ions formed in the due course of PET (PF(•), AY(•-), TrpH(•+), Trp(•)), and the application of an external MF has been used to characterize their initial spin-state. Owing to its distance dependence, MF effect gives an idea about the proximity of the radicals/radical ions during interaction in the system and also helps to elucidate the reaction mechanisms. A prominent MF effect is observed in homogeneous buffer medium owing to the pseudoconfinement of the radicals/radical ions provided by the complex structure of the protein.

  9. 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...... are useful for understanding drug metabolism....

  10. 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…

  11. The Food and Drug Administration and Drug Legalization: A Brief Model of Regulation

    OpenAIRE

    Kalam, Murad

    2002-01-01

    This paper offers a brief model of FDA regulation of currently illegal narcotics in the United States. Given that nearly three out of four Americans believe that the drug war has failed, recent calls from prominent liberal and conservative thinkers to legalize drugs, and state “compassionate use†ballot initiatives, future drug legalization is at least conceivable in the United States. Yet, how would the FDA regulate NLD’s under its current st...

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

    Science.gov (United States)

    Melak, Tilahun; Gakkhar, Sunita

    2015-12-01

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

  13. Quantitative chemogenomics: machine-learning models of protein-ligand interaction.

    Science.gov (United States)

    Andersson, Claes R; Gustafsson, Mats G; Strömbergsson, Helena

    2011-01-01

    Chemogenomics is an emerging interdisciplinary field that lies in the interface of biology, chemistry, and informatics. Most of the currently used drugs are small molecules that interact with proteins. Understanding protein-ligand interaction is therefore central to drug discovery and design. In the subfield of chemogenomics known as proteochemometrics, protein-ligand-interaction models are induced from data matrices that consist of both protein and ligand information along with some experimentally measured variable. The two general aims of this quantitative multi-structure-property-relationship modeling (QMSPR) approach are to exploit sparse/incomplete information sources and to obtain more general models covering larger parts of the protein-ligand space, than traditional approaches that focuses mainly on specific targets or ligands. The data matrices, usually obtained from multiple sparse/incomplete sources, typically contain series of proteins and ligands together with quantitative information about their interactions. A useful model should ideally be easy to interpret and generalize well to new unseen protein-ligand combinations. Resolving this requires sophisticated machine-learning methods for model induction, combined with adequate validation. This review is intended to provide a guide to methods and data sources suitable for this kind of protein-ligand-interaction modeling. An overview of the modeling process is presented including data collection, protein and ligand descriptor computation, data preprocessing, machine-learning-model induction and validation. Concerns and issues specific for each step in this kind of data-driven modeling will be discussed. © 2011 Bentham Science Publishers

  14. Synthesis, characterization and target protein binding of drug-conjugated quantum dots in vitro and in living cells

    International Nuclear Information System (INIS)

    Choi, Youngseon; Kim, Minjung; Cho, Yoojin; Yun, Eunsuk; Song, Rita

    2013-01-01

    Elucidation of unknown target proteins of a drug is of great importance in understanding cell biology and drug discovery. There have been extensive studies to discover and identify target proteins in the cell. Visualization of targets using drug-conjugated probes has been an important approach to gathering mechanistic information of drug action at the cellular level. As quantum dot (QD) nanocrystals have attracted much attention as a fluorescent probe in the bioimaging area, we prepared drug-conjugated QD to explore the potential of target discovery. As a model drug, we selected a well-known anticancer drug, methotrexate (MTX), which has been known to target dihydrofolate reductase (DHFR) with high affinity binding (K d = 0.54 nM). MTX molecules were covalently attached to amino-PEG-polymer-coated QDs. Specific interactions of MTX-conjugated QDs with DHFR were identified using agarose gel electrophoresis and fluorescence microscopy. Cellular uptake of the MTX-conjugated QDs in living CHO cells was investigated with regard to their localization and distribution pattern. MTX–QD was found to be internalized into the cells via caveolae-medicated endocytosis without significant sequestration in endosomes. A colocalization experiment of the MTX–QD conjugate with antiDHFR-TAT-QD also confirmed that MTX–QD binds to the target DHFR. This study showed the potential of the drug-QD conjugate to identify or visualize drug–target interactions in the cell, which is currently of great importance in the area of drug discovery and chemical biology. (paper)

  15. Inhibition of protein synthesis and malaria parasite development by drug targeting of methionyl-tRNA synthetases.

    Science.gov (United States)

    Hussain, Tahir; Yogavel, Manickam; Sharma, Amit

    2015-04-01

    Aminoacyl-tRNA synthetases (aaRSs) are housekeeping enzymes that couple cognate tRNAs with amino acids to transmit genomic information for protein translation. The Plasmodium falciparum nuclear genome encodes two P. falciparum methionyl-tRNA synthetases (PfMRS), termed PfMRS(cyt) and PfMRS(api). Phylogenetic analyses revealed that the two proteins are of primitive origin and are related to heterokonts (PfMRS(cyt)) or proteobacteria/primitive bacteria (PfMRS(api)). We show that PfMRS(cyt) localizes in parasite cytoplasm, while PfMRS(api) localizes to apicoplasts in asexual stages of malaria parasites. Two known bacterial MRS inhibitors, REP3123 and REP8839, hampered Plasmodium growth very effectively in the early and late stages of parasite development. Small-molecule drug-like libraries were screened against modeled PfMRS structures, and several "hit" compounds showed significant effects on parasite growth. We then tested the effects of the hit compounds on protein translation by labeling nascent proteins with (35)S-labeled cysteine and methionine. Three of the tested compounds reduced protein synthesis and also blocked parasite growth progression from the ring stage to the trophozoite stage. Drug docking studies suggested distinct modes of binding for the three compounds, compared with the enzyme product methionyl adenylate. Therefore, this study provides new targets (PfMRSs) and hit compounds that can be explored for development as antimalarial drugs. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

  16. 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.

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

    Science.gov (United States)

    Zhang, Yan; Yang, Zhijie; Hu, Xi; Zhang, Ling; Li, Feng; Li, Meimei; Tang, Xing; Xiao, Wei

    2015-02-01

    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 Ca2+ 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.

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

    International Nuclear Information System (INIS)

    Xie, Jinbing; Wang, Hongyang; Cao, Yi; Qin, Meng; Wang, Wei

    2015-01-01

    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

  19. Protein Recognition in Drug-Induced DNA Alkylation: When the Moonlight Protein GAPDH Meets S23906-1/DNA Minor Groove Adducts.

    Science.gov (United States)

    Savreux-Lenglet, Gaëlle; Depauw, Sabine; David-Cordonnier, Marie-Hélène

    2015-11-05

    DNA alkylating drugs have been used in clinics for more than seventy years. The diversity of their mechanism of action (major/minor groove; mono-/bis-alkylation; intra-/inter-strand crosslinks; DNA stabilization/destabilization, etc.) has undoubtedly major consequences on the cellular response to treatment. The aim of this review is to highlight the variety of established protein recognition of DNA adducts to then particularly focus on glyceraldehyde-3-phosphate dehydrogenase (GAPDH) function in DNA adduct interaction with illustration using original experiments performed with S23906-1/DNA adduct. The introduction of this review is a state of the art of protein/DNA adducts recognition, depending on the major or minor groove orientation of the DNA bonding as well as on the molecular consequences in terms of double-stranded DNA maintenance. It reviews the implication of proteins from both DNA repair, transcription, replication and chromatin maintenance in selective DNA adduct recognition. The main section of the manuscript is focusing on the implication of the moonlighting protein GAPDH in DNA adduct recognition with the model of the peculiar DNA minor groove alkylating and destabilizing drug S23906-1. The mechanism of action of S23906-1 alkylating drug and the large variety of GAPDH cellular functions are presented prior to focus on GAPDH direct binding to S23906-1 adducts.

  20. 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

  1. 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.

  2. 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

    spectrometry to analyze global proteome and phosphoproteome differences of MCF-7 breast cancer cells expressing high or low levels of TIMP-1. In TIMP-1 high expressing cells, 312 proteins and 452 phosphorylation sites were up-regulated. Among these were the cancer drug targets topoisomerase 1, 2A and 2B, which......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...

  3. 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.

  4. Fast loop modeling for protein structures

    Science.gov (United States)

    Zhang, Jiong; Nguyen, Son; Shang, Yi; Xu, Dong; Kosztin, Ioan

    2015-03-01

    X-ray crystallography is the main method for determining 3D protein structures. In many cases, however, flexible loop regions of proteins cannot be resolved by this approach. This leads to incomplete structures in the protein data bank, preventing further computational study and analysis of these proteins. For instance, all-atom molecular dynamics (MD) simulation studies of structure-function relationship require complete protein structures. To address this shortcoming, we have developed and implemented an efficient computational method for building missing protein loops. The method is database driven and uses deep learning and multi-dimensional scaling algorithms. We have implemented the method as a simple stand-alone program, which can also be used as a plugin in existing molecular modeling software, e.g., VMD. The quality and stability of the generated structures are assessed and tested via energy scoring functions and by equilibrium MD simulations. The proposed method can also be used in template-based protein structure prediction. Work supported by the National Institutes of Health [R01 GM100701]. Computer time was provided by the University of Missouri Bioinformatics Consortium.

  5. Drug targeted virtual screening and molecular dynamics of LipU protein of Mycobacterium tuberculosis and Mycobacterium leprae.

    Science.gov (United States)

    Kaur, Gurkamaljit; Pandey, Bharati; Kumar, Arbind; Garewal, Naina; Grover, Abhinav; Kaur, Jagdeep

    2018-03-20

    The lipolytic protein LipU was conserved in mycobacterium sp. including M. tuberculosis (MTB LipU) and M. leprae (MLP LipU). The MTB LipU was identified in extracellular fraction and was reported to be essential for the survival of mycobacterium. Therefore to address the problem of drug resistance in pathogen, LipU was selected as a drug target and the viability of finding out some FDA approved drugs as LipU inhibitors in both the cases was explored. Three dimensional (3D) model structures of MTB LipU and MLP LipU were generated and stabilized through molecular dynamics (MD). FDA approved drugs were screened against these proteins. The result showed that the top-scoring compounds for MTB LipU were Diosmin, Acarbose and Ouabain with the Glide XP score of -12.8, -11.9 and-11.7 kcal/mol respectively, whereas for MLP LipU protein, Digoxin (-9.2 kcal/mol), Indinavir (-8.2 kcal/mol) and Travoprost (-8.2 kcal/mol) showed highest affinity. These drugs remained bound in the active site pocket of MTB LipU and MLP LipU structure and interaction grew stronger after dynamics. RMSD, RMSF and Rg were found to be persistent throughout the simulation period. Hydrogen bonds along with large number of hydrophobic interactions stabilized the complex structures. Binding free energies obtained through Prime/MM-GBSA were found in the significant range from -63.85 kcal/mol to -34.57 kcal/mol for MTB LipU and -71.33 kcal/mol to -23.91 kcal/mol for MLP LipU. The report suggested high probability of these drugs to demolish the LipU activity and could be probable drug candidates to combat TB and leprosy disease.

  6. Y-Trap Cancer Immunotherapy Drug Targets Two Proteins

    Science.gov (United States)

    Two groups of researchers, working independently, have fused a TGF-beta receptor to a monoclonal antibody that targets a checkpoint protein. The result, this Cancer Currents blog describes, is a single hybrid molecule called a Y-trap that blocks two pathways used by tumors to evade the immune system.

  7. Protein and Drug Interactions in the Minor Groove of DNA

    Czech Academy of Sciences Publication Activity Database

    Morávek, Z.; Neidle, S.; Schneider, Bohdan

    2002-01-01

    Roč. 30, č. 5 (2002), s. 1182-1191 ISSN 0305-1048 R&D Projects: GA MŠk LN00A032 Institutional research plan: CEZ:AV0Z4040901 Keywords : protein * DNA * interactions Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 7.051, year: 2002

  8. A pharmacokinetic drug-drug interaction model of simvastatin and clarithromycin in humans.

    Science.gov (United States)

    Methaneethorn, Janthima; Chaiwong, Krissanapong; Pongpanich, Komwut; Sonsingh, Phakawat; Lohitnavy, Manupat

    2014-01-01

    Simvastatin is a HMG-CoA reductase Inhibitor and a substrate of CYP3A4. Clarithromycin is a commonly used macrolide antibiotics and a potent inhibitor of CYP3A4. When co-administered with simvastatin, clarithromycin can significantly increase simvastatin plasma concentration levels, thereby, increase the risk of rhabdomyolysis. At present, pharmacokinetic data of the interaction between both drugs are available. However, they are being used for semi-quantitative application only, not for quantitative prediction. We aimed to develop a mathematical model describing a drug-drug interaction between simvastatin and clarithromycin in humans. Selected pharmacokinetic interaction study was obtained from PubMed search. Concentration-time course data were subsequently extracted and used for model development. Compartmental pharmacokinetic interaction model was developed using Advanced Continuous Simulating Language Extreme (ACSLX), a FORTRAN language-based computer program. The drug-drug interaction between simvastatin and clarithromycin was modeled simultaneously with a parent-metabolite model for clarithromycin and a one-compartment model for simvastatin linked to its active form, simvastatin hydroxy acid. The simulated simvastatin concentrations obtained from the final model displayed satisfactory goodness of fit to the data from the literature. Our model could successfully describe concentration-time course of simvastatin-clarithromycin interaction. The resulting interaction model can be able to use for further development of a quantitative model predicting rhabdomyolysis occurrence in patients concurrently receiving simvastatin and clarithromycin.

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

    Science.gov (United States)

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

    2014-07-01

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

  10. 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

  11. Mathematical modeling for novel cancer drug discovery and development.

    Science.gov (United States)

    Zhang, Ping; Brusic, Vladimir

    2014-10-01

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

  12. Docking of calcium-binding protein 1 of Entamoeba histolytica using FDA approved drugs

    Directory of Open Access Journals (Sweden)

    Zahid Ahmad

    2017-11-01

    Full Text Available Objective: To find out an alternative potential inhibitor of Entamoeba histolytica calciumbinding protein 1 (EhCaBP1 through in silico studies. Methods: An attempt was made to find a new FDA approved, and cost effective alternative drug for amoebiasis. Sequence of the EhCaBP1 of Entamoeba histolytica was obtained through searching the UniProt database and protein BLAST was performed. The 3D structure of EhCaBP1 was retrieved from Research Collaboratory for Structural Bioinformatics and visualized using Discovery Studio Visualizer® 3.1. A total of 100 drugs were selected and docked using Patchdock and the different sorts of interactions with the target protein were studied using GS viewer, Ligplot and Discovery Studio visualizer. Results: Among the 100 selected drugs, dolutegravir, cefazedone and ergotamine showed large number of interactions with the target protein. Conclusions: The drugs cefazedone and ergotamine showed twenty and nineteen different sorts of interactions respectively with the target protein. These interactions may lead to metabolic changes and can subsequently stop the growth and cause the death of the parasite. Further investigations and experimental analysis are required to unveil the effects of these drugs.

  13. A set of descriptors for identifying the protein-drug interaction in cellular networking.

    Science.gov (United States)

    Nanni, Loris; Lumini, Alessandra; Brahnam, Sheryl

    2014-10-21

    The study of protein-drug interactions is a significant issue for drug development. Unfortunately, it is both expensive and time-consuming to perform physical experiments to determine whether a drug and a protein are interacting with each other. Some previous attempts to design an automated system to perform this task were based on the knowledge of the 3D structure of a protein, which is not always available in practice. With the availability of protein sequences generated in the post-genomic age, however, a sequence-based solution to deal with this problem is necessary. Following other works in this area, we propose a new machine learning system based on several protein descriptors extracted from several protein representations, such as, variants of the position specific scoring matrix (PSSM) of proteins, the amino-acid sequence, and a matrix representation of a protein. The prediction engine is operated by an ensemble of support vector machines (SVMs), with each SVM trained on a specific descriptor and the results of each SVM combined by sum rule. The overall success rate achieved by our final ensemble is notably higher than previous results obtained on the same datasets using the same testing protocols reported in the literature. MATLAB code and the datasets used in our experiments are freely available for future comparison at http://www.dei.unipd.it/node/2357. Copyright © 2014 Elsevier Ltd. All rights reserved.

  14. In silico modeling to predict drug-induced phospholipidosis

    International Nuclear Information System (INIS)

    Choi, Sydney S.; Kim, Jae S.; Valerio, Luis G.; Sadrieh, Nakissa

    2013-01-01

    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

  15. The Protein Model Portal--a comprehensive resource for protein structure and model information.

    Science.gov (United States)

    Haas, Juergen; Roth, Steven; Arnold, Konstantin; Kiefer, Florian; Schmidt, Tobias; Bordoli, Lorenza; Schwede, Torsten

    2013-01-01

    The Protein Model Portal (PMP) has been developed to foster effective use of 3D molecular models in biomedical research by providing convenient and comprehensive access to structural information for proteins. Both experimental structures and theoretical models for a given protein can be searched simultaneously and analyzed for structural variability. By providing a comprehensive view on structural information, PMP offers the opportunity to apply consistent assessment and validation criteria to the complete set of structural models available for proteins. PMP is an open project so that new methods developed by the community can contribute to PMP, for example, new modeling servers for creating homology models and model quality estimation servers for model validation. The accuracy of participating modeling servers is continuously evaluated by the Continuous Automated Model EvaluatiOn (CAMEO) project. The PMP offers a unique interface to visualize structural coverage of a protein combining both theoretical models and experimental structures, allowing straightforward assessment of the model quality and hence their utility. The portal is updated regularly and actively developed to include latest methods in the field of computational structural biology. Database URL: http://www.proteinmodelportal.org.

  16. The Protein Model Portal—a comprehensive resource for protein structure and model information

    Science.gov (United States)

    Haas, Juergen; Roth, Steven; Arnold, Konstantin; Kiefer, Florian; Schmidt, Tobias; Bordoli, Lorenza; Schwede, Torsten

    2013-01-01

    The Protein Model Portal (PMP) has been developed to foster effective use of 3D molecular models in biomedical research by providing convenient and comprehensive access to structural information for proteins. Both experimental structures and theoretical models for a given protein can be searched simultaneously and analyzed for structural variability. By providing a comprehensive view on structural information, PMP offers the opportunity to apply consistent assessment and validation criteria to the complete set of structural models available for proteins. PMP is an open project so that new methods developed by the community can contribute to PMP, for example, new modeling servers for creating homology models and model quality estimation servers for model validation. The accuracy of participating modeling servers is continuously evaluated by the Continuous Automated Model EvaluatiOn (CAMEO) project. The PMP offers a unique interface to visualize structural coverage of a protein combining both theoretical models and experimental structures, allowing straightforward assessment of the model quality and hence their utility. The portal is updated regularly and actively developed to include latest methods in the field of computational structural biology. Database URL: http://www.proteinmodelportal.org PMID:23624946

  17. 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

  18. 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.

  19. hiv prevention among drug and alcohol users: models of ...

    African Journals Online (AJOL)

    Administrator

    HIV PREVENTION AMONG DRUG AND ALCOHOL USERS: MODELS. OF INTERVENTION IN KENYA. Clement S. Deveau. Academy for Educational Development (AED). Capable Partners Program (CAP). Nairobi, Kenya. ABSTRACT. The spread of HIV among drug and alcohol users, as a high-risk group, is a significant ...

  20. NEOGLYCOPROTEINS AS CARRIERS FOR ANTIVIRAL DRUGS - SYNTHESIS AND ANALYSIS OF PROTEIN DRUG CONJUGATES

    NARCIS (Netherlands)

    Molema, Grietje; Jansen, Robert W.; Visser, Jan; Herdewijn, Piet; Moolenaar, Frits; Meijer, Dirk K.F.

    In order to investigate whether neoglycoproteins can potentially act as carriers for targeting of antiviral drugs to certain cell types in the body, various neoglycoproteins were synthesized using thiophosgene-activated p-aminophenyl sugar derivatives. These neoglycoproteins were conjugated with the

  1. Drug Discovery Targeting Serotonin G Protein-Coupled Receptors in the Treatment of Neuropsychiatric Disorders

    Science.gov (United States)

    Felsing, Daniel E.

    Clinical data show that activation of 5-HT2C G protein-coupled receptors (GPCRs) can treat obesity (lorcaserin/BelviqRTM) and psychotic disorders (aripiprazole/Abilify.), including schizophrenia. 5-HT2C GPCRs are members of the 5-HT2 sub-family of 5-HT GPCRs, which include 5-HT2A, 5-HT2B, and 5-HT 2C GPCRs. 5-HT2C is structurally similar to 5-HT2A and 5-HT2B GPCRs, but activation of 5-HT2A and/or 5-HT 2B causes deleterious effects, including hallucinations and cardiac valvulopathy. Thus, there is a challenge to develop drugs that selectively activate only 5-HT2C. Prolonged activation of GPCRs by agonists reduces their function via a regulatory process called desensitization. This has clinical relevance, as 45% of drugs approved by the FDA target GPCRs, and agonist drugs (e.g., morphine) typically lose efficacy over time due to desensitization, which invites tolerance. Agonists that cause less desensitization may show extended clinical efficacy as well as a more acceptable clinical dose range. We hypothesized that structurally distinct agonists of the 5-HT2C receptor may cause varying degrees of desensitization by stabilizing unique 5-HT2C receptor conformations. Discovery of 5-HT2C agonists that exhibit minimal desensitization is therapeutically relevant for the pharmacotherapeutic treatment of chronic diseases such as obesity and psychotic disorders. The 5-HT7 receptor has recently been discovered as a druggable target, and selective activation of the 5-HT7 receptor has been shown to alleviate locomotor deficits in mouse models of Rett Syndrome. Additionally, buspirone has been shown to display therapeutically relevant affinity at 5-HT 1A and is currently in phase II clinical trials to treat stereotypy in children with autism. The 5-PAT chemical scaffold shows high affinity towards the 5-HT7 and 5-HT1A receptors. Modulations around the 5-phenyl moiety were able to improve selectivity in binding towards the 5-HT 7 receptor, whereas modulations of the alkyl chains

  2. Evaluation of a combined drug-delivery system for proteins assembled with polymeric nanoparticles and porous microspheres; characterization and protein integrity studies.

    Science.gov (United States)

    Alcalá-Alcalá, Sergio; Benítez-Cardoza, Claudia G; Lima-Muñoz, Enrique J; Piñón-Segundo, Elizabeth; Quintanar-Guerrero, David

    2015-07-15

    This work presents an evaluation of the adsorption/infiltration process in relation to the loading of a model protein, α-amylase, into an assembled biodegradable polymeric system, free of organic solvents and made up of poly(D,L-lactide-co-glycolide) acid (PLGA). Systems were assembled in a friendly aqueous medium by adsorbing and infiltrating polymeric nanoparticles into porous microspheres. These assembled systems are able to load therapeutic amounts of the drug through adsorption of the protein onto the large surface area characteristic of polymeric nanoparticles. The subsequent infiltration of nanoparticles adsorbed with the protein into porous microspheres enabled the controlled release of the protein as a function of the amount of infiltrated nanoparticles, since the surface area available on the porous structure is saturated at different levels, thus modifying the protein release rate. Findings were confirmed by both the BET technique (N2 isotherms) and in vitro release studies. During the adsorption process, the pH of the medium plays an important role by creating an environment that favors adsorption between the surfaces of the micro- and nano-structures and the protein. Finally, assays of α-amylase activity using 2-chloro-4-nitrophenyl-α-D-maltotrioside (CNP-G3) as the substrate and the circular dichroism technique confirmed that when this new approach was used no conformational changes were observed in the protein after release. Copyright © 2015 Elsevier B.V. All rights reserved.

  3. Nonstructural Proteins of Alphavirus—Potential Targets for Drug Development

    Directory of Open Access Journals (Sweden)

    Farhana Abu Bakar

    2018-02-01

    Full Text Available Alphaviruses are enveloped, positive single-stranded RNA viruses, typically transmitted by arthropods. They often cause arthralgia or encephalitic diseases in infected humans and there is currently no targeted antiviral treatment available. The re-emergence of alphaviruses in Asia, Europe, and the Americas over the last decade, including chikungunya and o’nyong’nyong viruses, have intensified the search for selective inhibitors. In this review, we highlight key molecular determinants within the alphavirus replication complex that have been identified as viral targets, focusing on their structure and functionality in viral dissemination. We also summarize recent structural data of these viral targets and discuss how these could serve as templates to facilitate structure-based drug design and development of small molecule inhibitors.

  4. GRP78 Protein Expression in Ovarian Cancer Patients and Perspectives for a Drug-Targeting Approach

    Directory of Open Access Journals (Sweden)

    Florence Delie

    2012-01-01

    Full Text Available Glucose-regulated protein of 78 kD (GRP78 is a chaperone protein mainly located in the endoplasmic reticulum (ER. This protein is normally present at low levels in adult cells but its expression is triggered by ER stress including glucose deprivation and hypoxia. In tumor cells, it is overexpressed with fraction of protein found at the cell surface. This paper presents the physiology of GRP78 in the context of ovarian cancer and its potential use as drug delivery systems targeting ovarian cancer cell.

  5. Modeling protein structures: construction and their applications.

    Science.gov (United States)

    Ring, C S; Cohen, F E

    1993-06-01

    Although no general solution to the protein folding problem exists, the three-dimensional structures of proteins are being successfully predicted when experimentally derived constraints are used in conjunction with heuristic methods. In the case of interleukin-4, mutagenesis data and CD spectroscopy were instrumental in the accurate assignment of secondary structure. In addition, the tertiary structure was highly constrained by six cysteines separated by many residues that formed three disulfide bridges. Although the correct structure was a member of a short list of plausible structures, the "best" structure was the topological enantiomer of the experimentally determined conformation. For many proteases, other experimentally derived structures can be used as templates to identify the secondary structure elements. In a procedure called modeling by homology, the structure of a known protein is used as a scaffold to predict the structure of another related protein. This method has been used to model a serine and a cysteine protease that are important in the schistosome and malarial life cycles, respectively. The model structures were then used to identify putative small molecule enzyme inhibitors computationally. Experiments confirm that some of these nonpeptidic compounds are active at concentrations of less than 10 microM.

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

    Directory of Open Access Journals (Sweden)

    Ryan J Mailloux

    2010-10-01

    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.

  7. 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...... in the Markov model for this task. Classifications that are purely based on statistical models might not always be biologically meaningful. We present combinatorial methods to incorporate biological background knowledge to enhance the prediction performance....

  8. Mathematical modeling and computational prediction of cancer drug resistance.

    Science.gov (United States)

    Sun, Xiaoqiang; Hu, Bin

    2017-06-23

    Diverse forms of resistance to anticancer drugs can lead to the failure of chemotherapy. Drug resistance is one of the most intractable issues for successfully treating cancer in current clinical practice. Effective clinical approaches that could counter drug resistance by restoring the sensitivity of tumors to the targeted agents are urgently needed. As numerous experimental results on resistance mechanisms have been obtained and a mass of high-throughput data has been accumulated, mathematical modeling and computational predictions using systematic and quantitative approaches have become increasingly important, as they can potentially provide deeper insights into resistance mechanisms, generate novel hypotheses or suggest promising treatment strategies for future testing. In this review, we first briefly summarize the current progress of experimentally revealed resistance mechanisms of targeted therapy, including genetic mechanisms, epigenetic mechanisms, posttranslational mechanisms, cellular mechanisms, microenvironmental mechanisms and pharmacokinetic mechanisms. Subsequently, we list several currently available databases and Web-based tools related to drug sensitivity and resistance. Then, we focus primarily on introducing some state-of-the-art computational methods used in drug resistance studies, including mechanism-based mathematical modeling approaches (e.g. molecular dynamics simulation, kinetic model of molecular networks, ordinary differential equation model of cellular dynamics, stochastic model, partial differential equation model, agent-based model, pharmacokinetic-pharmacodynamic model, etc.) and data-driven prediction methods (e.g. omics data-based conventional screening approach for node biomarkers, static network approach for edge biomarkers and module biomarkers, dynamic network approach for dynamic network biomarkers and dynamic module network biomarkers, etc.). Finally, we discuss several further questions and future directions for the use of

  9. Molecular modeling of protein A affinity chromatography.

    Science.gov (United States)

    Salvalaglio, Matteo; Zamolo, Laura; Busini, Valentina; Moscatelli, Davide; Cavallotti, Carlo

    2009-12-11

    The properties of the complex between fragment B of Protein A and the Fc domain of IgG were investigated adopting molecular dynamics with the intent of providing useful insight that might be exploited to design mimetic ligands with properties similar to those of Protein A. Simulations were performed both for the complex in solution and supported on an agarose surface, which was modeled as an entangled structure constituted by two agarose double chains. The energetic analysis was performed by means of the molecular mechanics Poisson Boltzmann surface area (MM/PBSA), molecular mechanics generalized Born surface area (MM/GBSA), and the linear interaction energy (LIE) approaches. An alanine scan was performed to determine the relative contribution of Protein A key amino acids to the complex interaction energy. It was found that three amino acids play a dominant role: Gln 129, Phe 132 and Lys 154, though also four other residues, Tyr 133, Leu 136, Glu 143 and Gln 151 contribute significantly to the overall binding energy. A successive molecular dynamics analysis of Protein A re-organization performed when it is not in complex with IgG has however shown that Phe 132 and Tyr 133 interact among themselves establishing a significant pi-pi interaction, which is disrupted upon formation of the complex with IgG and thus reduces consistently their contribution to the protein-antibody bond. The effect that adsorbing fragment B of Protein A on an agarose support has on the stability of the protein-antibody bond was investigated using a minimal molecular model and compared to a similar study performed for a synthetic ligand. It was found that the interaction with the surface does not hinder significantly the capability of Protein A to interact with IgG, while it is crucial for the synthetic ligand. These results indicate that ligand-surface interactions should be considered in the design of new synthetic affinity ligands in order to achieve results comparable to those of Protein A

  10. Drug-induced cholestasis: mechanisms, models, and markers.

    Science.gov (United States)

    Chatterjee, Sagnik; Annaert, Pieter

    2018-04-27

    Drug-induced cholestasis is a risk factor in progression of drug candidates, and poses serious health hazard if not detected before going into human. Intrahepatic accumulation of bile acids (BAs) represents a characteristic phenomenon associated with drug-induced cholestasis. The major challenges in obtaining a complete understanding of drug-induced cholestasis lies in the complexity of BA-mediated toxicity mechanisms and the impact of bile acids at different 'targets' such as transporters, enzymes and nuclear receptors. At the same time, it is not trivial to have a relevant in vitro system that recapitulates these features. In addition, lack of sensitive and early preclinical biomarkers, relevant to the clinical situation, complicates proper detection of drug-induced cholestasis. Significant overlap in biomarker signatures between different mechanisms of drug-induced liver injury (DILI) precludes identification of specific mechanisms. Over the last decade the knowledge gaps in drug-induced cholestasis are closing due to growing mechanistic understanding of BA-mediated toxicity at (patho)physiologically relevant BA concentrations. Significant progress has been made in the mechanistic understanding of drug-induced cholestasis and associated toxicity, biomarkers and susceptibility factors. In addition, novel in vitro models are evolving which provide a holistic understanding of processes underlying drug-induced cholestasis. This review summarizes the challenges and recent understandings about drug-induced cholestasis with a potential path forward. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

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

    Science.gov (United States)

    Antal, Miklós A; Böde, Csaba; Csermely, Peter

    2009-04-01

    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. Teratogenic potential of antiepileptic drugs in the zebrafish model.

    Science.gov (United States)

    Lee, Sung Hak; Kang, Jung Won; Lin, Tao; Lee, Jae Eun; Jin, Dong Il

    2013-01-01

    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.

  13. The model of drugs distribution dynamics in biological tissue

    Science.gov (United States)

    Ginevskij, D. A.; Izhevskij, P. V.; Sheino, I. N.

    2017-09-01

    The dose distribution by Neutron Capture Therapy follows the distribution of 10B in the tissue. The modern models of pharmacokinetics of drugs describe the processes occurring in conditioned "chambers" (blood-organ-tumor), but fail to describe the spatial distribution of the drug in the tumor and in normal tissue. The mathematical model of the spatial distribution dynamics of drugs in the tissue, depending on the concentration of the drug in the blood, was developed. The modeling method is the representation of the biological structure in the form of a randomly inhomogeneous medium in which the 10B distribution occurs. The parameters of the model, which cannot be determined rigorously in the experiment, are taken as the quantities subject to the laws of the unconnected random processes. The estimates of 10B distribution preparations in the tumor and healthy tissue, inside/outside the cells, are obtained.

  14. 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.

  15. Coordination conjugates of therapeutic proteins with drug carriers: A new approach for versatile advanced drug delivery

    Czech Academy of Sciences Publication Activity Database

    Kejík, Z.; Bříza, T.; Králová, Jarmila; Poučková, P.; Kral, A.; Martásek, P.; Král, V.

    2011-01-01

    Roč. 21, č. 18 (2011), s. 5514-5520 ISSN 0960-894X R&D Projects: GA ČR GA203/09/1311 Grant - others:MPO(CZ) FR-TI3/521; AV ČR(CZ) KAN200100801 Program:FR; KA Institutional research plan: CEZ:AV0Z50520514 Keywords : combined cancer therapy * photodynamic therapy * targeted drug delivery Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 2.554, year: 2011

  16. Overview on zein protein: a promising pharmaceutical excipient in drug delivery systems and tissue engineering.

    Science.gov (United States)

    Labib, Gihan

    2018-01-01

    Natural pharmaceutical excipients have been applied extensively in the past decades owing to their safety and biocompatibility. Zein, a natural protein of plant origin offers great benefit over other synthetic polymers used in controlled drug and biomedical delivery systems. It was used in a variety of medical fields including pharmaceutical and biomedical drug targeting, vaccine, tissue engineering, and gene delivery. Being biodegradable and biocompatible, the current review focuses on the history and the medical application of zein as an attractive still promising biopolymer. Areas covered: The current review gives a broadscope on zein as a still promising protein excipient in different fields. Zein- based drug and biomedical delivery systems are discussed with special focus on current and potential application in controlled drug delivery systems, and tissue engineering. Expert opinion: Zein as a protein of natural origin can still be considered a promising polymer in the field of drug delivery systems as well as in tissue engineering. Although different researchers spotted light on zein application in different industrial fields extensively, the feasibility of its use in the field of drug delivery replenished by investigators in recent years has not yet been fully approached.

  17. 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.

  18. Chemogenomics Knowledgebased Polypharmacology Analyses of Drug Abuse Related G-Protein Coupled Receptors and Their Ligands

    Directory of Open Access Journals (Sweden)

    Xiang-Qun eXie

    2014-02-01

    Full Text Available Drug abuse (DA and addiction is a complex illness, broadly viewed as a neurobiological impairment with genetic and environmental factors that influence its development and manifestation. Abused substances can disrupt the activity of neurons by interacting with many proteins, particularly G-protein coupled receptors (GPCRs. A few medicines that target the central nervous system (CNS can also modulate DA related proteins, such as GPCRs, which can act in conjunction with the controlled psychoactive substance(s and increase side effects. To fully explore the molecular interaction networks that underlie DA and to effectively modulate the GPCRs in these networks with small molecules for DA treatment, we built a drug-abuse domain specific chemogenomics knowledgebase (DA-KB to centralize the reported chemogenomics research information related to DA and CNS disorders in an effort to benefit researchers across a broad range of disciplines. We then focus on the analysis of GPCRs as many of them are closely related with drug abuse. Their distribution in human tissues was also analyzed for the study of side effects caused by abused drugs. We further implement our computational algorithms/tools to explore DA targets, DA mechanisms and pathways involved in polydrug addiction and to explore polypharmacological effects of the GPCR ligands. Finally, the polypharmacology effects of GPCR-targeted medicines for drug abuse treatment were investigated and such effects can be exploited for the development of drugs with polypharmacophore for drug abuse intervention. The chemogenomics database and the analysis tools will help us better understand the mechanism of drugs abuse and facilitate to design new medications for system pharmacotherapy of drug abuse.

  19. An invertebrate model for CNS drug discovery

    DEFF Research Database (Denmark)

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

    2015-01-01

    , 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...

  20. Plant protein-based hydrophobic fine and ultrafine carrier particles in drug delivery systems.

    Science.gov (United States)

    Malekzad, Hedieh; Mirshekari, Hamed; Sahandi Zangabad, Parham; Moosavi Basri, S M; Baniasadi, Fazel; Sharifi Aghdam, Maryam; Karimi, Mahdi; Hamblin, Michael R

    2018-02-01

    For thousands of years, plants and their products have been used as the mainstay of medicinal therapy. In recent years, besides attempts to isolate the active ingredients of medicinal plants, other new applications of plant products, such as their use to prepare drug delivery vehicles, have been discovered. Nanobiotechnology is a branch of pharmacology that can provide new approaches for drug delivery by the preparation of biocompatible carrier nanoparticles (NPs). In this article, we review recent studies with four important plant proteins that have been used as carriers for targeted delivery of drugs and genes. Zein is a water-insoluble protein from maize; Gliadin is a 70% alcohol-soluble protein from wheat and corn; legumin is a casein-like protein from leguminous seeds such as peas; lectins are glycoproteins naturally occurring in many plants that recognize specific carbohydrate residues. NPs formed from these proteins show good biocompatibility, possess the ability to enhance solubility, and provide sustained release of drugs and reduce their toxicity and side effects. The effects of preparation methods on the size and loading capacity of these NPs are also described in this review.

  1. 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.

  2. 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. Copyright © 2015 Elsevier B.V. All rights reserved.

  3. SEIIrR: Drug abuse model with rehabilitation

    Science.gov (United States)

    Sutanto, Azizah, Afina; Widyaningsih, Purnami; Saputro, Dewi Retno Sari

    2017-05-01

    Drug abuse in the world quite astonish and tend to increase. The increase and decrease on the number of drug abusers showed a pattern of spread that had the same characteristics with patterns of spread of infectious disease. The susceptible infected removed (SIR) and susceptible exposed infected removed (SEIR) epidemic models for infectious disease was developed to study social epidemic. In this paper, SEIR model for disease epidemic was developed to study drug abuse epidemic with rehabilitation treatment. The aims of this paper were to analogize susceptible exposed infected isolated recovered (SEIIrR) model on the drug abusers, to determine solutions of the model, to determine equilibrium point, and to do simulation on β. The solutions of SEIIrR model was determined by using fourth order of Runge-Kutta algorithm, equilibrium point obtained was free-drug equilibrium point. Solutions of SEIIrR showed that the model was able to suppress the spread of drug abuse. The increasing value of contact rate was not affect the number of infected individuals due to rehabilitation treatment.

  4. Developing an Agent-Based Drug Model to Investigate the Synergistic Effects of Drug Combinations.

    Science.gov (United States)

    Gao, Hongjie; Yin, Zuojing; Cao, Zhiwei; Zhang, Le

    2017-12-14

    The growth and survival of cancer cells are greatly related to their surrounding microenvironment. To understand the regulation under the impact of anti-cancer drugs and their synergistic effects, we have developed a multiscale agent-based model that can investigate the synergistic effects of drug combinations with three innovations. First, it explores the synergistic effects of drug combinations in a huge dose combinational space at the cell line level. Second, it can simulate the interaction between cells and their microenvironment. Third, it employs both local and global optimization algorithms to train the key parameters and validate the predictive power of the model by using experimental data. The research results indicate that our multicellular system can not only describe the interactions between the microenvironment and cells in detail, but also predict the synergistic effects of drug combinations.

  5. Prediction of Drug Transfer into Milk Considering Breast Cancer Resistance Protein (BCRP)-Mediated Transport.

    Science.gov (United States)

    Ito, Naoki; Ito, Kousei; Ikebuchi, Yuki; Toyoda, Yu; Takada, Tappei; Hisaka, Akihiro; Oka, Akira; Suzuki, Hiroshi

    2015-08-01

    Drug transfer into milk is of concern due to the unnecessary exposure of infants to drugs. Proposed prediction methods for such transfer assume only passive drug diffusion across the mammary epithelium. This study reorganized data from the literature to assess the contribution of carrier-mediated transport to drug transfer into milk, and to improve the predictability thereof. Milk-to-plasma drug concentration ratios (M/Ps) in humans were exhaustively collected from the literature and converted into observed unbound concentration ratios (M/Punbound,obs). The ratios were also predicted based on passive diffusion across the mammary epithelium (M/Punbound,pred). An in vitro transport assay was performed for selected drugs in breast cancer resistance protein (BCRP)-expressing cell monolayers. M/Punbound,obs and M/Punbound,pred values were compared for 166 drugs. M/Punbound,obs values were 1.5 times or more higher than M/Punbound,pred values for as many as 13 out of 16 known BCRP substrates, reconfirming BCRP as the predominant transporter contributing to secretory transfer of drugs into milk. Predictability of M/P values for selected BCRP substrates and non-substrates was improved by considering in vitro-evaluated BCRP-mediated transport relative to passive diffusion alone. The current analysis improved the predictability of drug transfer into milk, particularly for BCRP substrates, based on an exhaustive data overhaul followed by focused in vitro transport experimentation.

  6. 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

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

    International Nuclear Information System (INIS)

    Mosedale, Merrie; Wu, Hong; Kurtz, C. Lisa; Schmidt, Stephen P.; Adkins, Karissa; Harrill, Alison H.

    2014-01-01

    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

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

    DEFF Research Database (Denmark)

    Peng, Qiang; Mu, Huiling

    2016-01-01

    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 itse...... of such interaction for advanced drug delivery are presented.......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....... 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...

  9. 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

  10. 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.

  11. 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. Copyright © 2014 Elsevier B.V. All rights reserved.

  12. 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...

  13. 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.

  14. 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. Copyright © 2014 Elsevier B.V. All rights reserved.

  15. Assessment of different polymers and drug loads for fused deposition modeling of drug loaded implants.

    Science.gov (United States)

    Kempin, Wiebke; Franz, Christian; Koster, Lynn-Christine; Schneider, Felix; Bogdahn, Malte; Weitschies, Werner; Seidlitz, Anne

    2017-06-01

    The 3D printing technique of fused deposition modeling® (FDM) has lately come into focus as a potential fabrication technique for pharmaceutical dosage forms and medical devices that allows the preparation of delivery systems with nearly any shape. This is particular promising for implants administered at application sites with a high anatomical variability where an individual shape adaption appears reasonable. In this work different polymers (Eudragit®RS, polycaprolactone (PCL), poly(l-lactide) (PLLA) and ethyl cellulose (EC)) were evaluated with respect to their suitability for FDM of drug loaded implants and their drug release behaviour was evaluated. The fluorescent dye quinine was used as a model drug to visualize drug distribution in filaments and implants. Quinine loaded filaments were produced by solvent casting and subsequent hot melt extrusion (HME) and model implants were printed as hollow cylinders using a standard FDM printer. Parameters were found at which model implants (hollow cylinders, outer diameter 4-5mm, height 3mm) could be produced from all tested polymers. The drug release which was examined by incubation of the printed implants in phosphate buffered saline solution (PBS) pH 7.4 was highly dependent on the used polymer. The fastest relative drug release of approximately 76% in 51days was observed for PCL and the lowest for Eudragit®RS and EC with less than 5% of quinine release in 78 and 100days, respectively. For PCL further filaments were prepared with different quinine loads ranging from 2.5% to 25% and thermal analysis proved the presence of a solid dispersion of quinine in the polymer for all tested concentrations. Increasing the drug load also increased the overall percentage of drug released to the medium since nearly the same absolute amount of quinine remained trapped in PCL at the end of drug release studies. This knowledge is valuable for future developments of printed implants with a desired drug release profile that might be

  16. 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

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

    International Nuclear Information System (INIS)

    Gagliardi, Mariacristina

    2012-01-01

    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: ► Preliminary evaluation of haemo- and cytocompatibility of newly-synthesised acrylic copolymers ► Materials adsorb higher amounts of albumin and with a faster rate than fibrinogen. ► Protein adsorption depended on the macromolecular composition and surface properties. ► Cell viability on pure samples and efficacy of paclitaxel release were verified in C2C12 cultures.

  18. HIV infection and drugs of abuse: role of acute phase proteins.

    Science.gov (United States)

    Samikkannu, Thangavel; Rao, Kurapati V K; Arias, Adriana Y; Kalaichezian, Aarthi; Sagar, Vidya; Yoo, Changwon; Nair, Madhavan P N

    2013-09-17

    HIV infection and drugs of abuse such as methamphetamine (METH), cocaine, and alcohol use have been identified as risk factors for triggering inflammation. Acute phase proteins such as C-reactive protein (CRP) and serum amyloid A (SAA) are the biomarkers of inflammation. Hence, the interactive effect of drugs of abuse with acute phase proteins in HIV-positive subjects was investigated. Plasma samples were utilized from 75 subjects with METH use, cocaine use, alcohol use, and HIV-positive alone and HIV-positive METH, cocaine, and alcohol users, and age-matched control subjects. The plasma CRP and SAA levels were measured by ELISA and western blot respectively and the CD4 counts were also measured. Observed results indicated that the CRP and SAA levels in HIV-positive subjects who are METH, cocaine and alcohol users were significantly higher when compared with either drugs of abuse or HIV-positive alone. The CD4 counts were also dramatically reduced in HIV-positive with drugs of abuse subjects compared with only HIV-positive subjects. These results suggest that, in HIV-positive subjects, drugs of abuse increase the levels of CRP and SAA, which may impact on the HIV infection and disease progression.

  19. Prediction of HIV drug resistance from genotype with encoded three-dimensional protein structure.

    Science.gov (United States)

    Yu, Xiaxia; Weber, Irene T; Harrison, Robert W

    2014-01-01

    Drug resistance has become a severe challenge for treatment of HIV infections. Mutations accumulate in the HIV genome and make certain drugs ineffective. Prediction of resistance from genotype data is a valuable guide in choice of drugs for effective therapy. In order to improve the computational prediction of resistance from genotype data we have developed a unified encoding of the protein sequence and three-dimensional protein structure of the drug target for classification and regression analysis. The method was tested on genotype-resistance data for mutants of HIV protease and reverse transcriptase. Our graph based sequence-structure approach gives high accuracy with a new sparse dictionary classification method, as well as support vector machine and artificial neural networks classifiers. Cross-validated regression analysis with the sparse dictionary gave excellent correlation between predicted and observed resistance. The approach of encoding the protein structure and sequence as a 210-dimensional vector, based on Delaunay triangulation, has promise as an accurate method for predicting resistance from sequence for drugs inhibiting HIV protease and reverse transcriptase.

  20. Influence of anticancer drugs on interactions of tumor suppressor protein p53 with DNA

    Czech Academy of Sciences Publication Activity Database

    Pivoňková, Hana; Němcová, Kateřina; Brázdová, Marie; Kašpárková, Jana; Brabec, Viktor; Fojta, Miroslav

    2005-01-01

    Roč. 272, Suppl. 1 (2005), s. 562 ISSN 1474-3833. [FEBS Congress /30./ and IUBMB Conference /9./. 02.07.2005-07.07.2005, Budapest] R&D Projects: GA MZd(CZ) NC7574 Institutional research plan: CEZ:AV0Z50040507 Keywords : tumour suppressor protein p53 * anticancer drugs * interaction with DNA Subject RIV: BO - Biophysics

  1. DNA modifications by platinum antitumor drugs and its recognition by DNA-binding proteins

    Czech Academy of Sciences Publication Activity Database

    Brabec, Viktor

    2004-01-01

    Roč. 271, Suppl. 1 (2004), s. 90 ISSN 0014-2956. [Meeting of the Federation of the European Biochemical Societies /29./. 26.06.2004-01.07.2004, Warsaw] R&D Projects: GA ČR GA305/02/1552 Keywords : platinum drugs * DNA-protein interaction * NF-kappaB Subject RIV: BO - Biophysics

  2. 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.

  3. 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.

  4. Novel films for drug delivery via the buccal mucosa using model soluble and insoluble drugs.

    Science.gov (United States)

    Kianfar, Farnoosh; Chowdhry, Babur Z; Antonijevic, Milan D; Boateng, Joshua S

    2012-10-01

    Bioadhesive buccal films are innovative dosage forms with the ability to adhere to the mucosal surface and subsequently hydrate to release and deliver drugs across the buccal membrane. This study aims to formulate and characterize stable carrageenan (CAR) based buccal films with desirable drug loading capacity. The films were prepared using CAR, poloxamer (POL) 407, various grades of PEG (plasticizer) and loaded with paracetamol (PM) and indomethacin (IND) as model soluble and insoluble drugs, respectively. The films were characterized by texture analysis, thermogravimetric analysis (TGA), DSC, scanning electron microscopy, X-ray powder diffraction (XRPD), and in vitro drug release studies. Optimized films were obtained from aqueous gels comprising 2.5% w/w κ-CAR 911, 4% w/w POL 407 and 6% w/w (PM) and 6.5% w/w (IND) of PEG 600 with maximum drug loading of 1.6% w/w and 0.8 % w/w for PM and IND, respectively. TGA showed residual water content of approximately 5% of films dry weight. DSC revealed a T(g) at 22.25 and 30.77°C for PM and IND, respectively, implying the presence of amorphous forms of both drugs which was confirmed by XRPD. Drug dissolution profiles in simulated saliva showed cumulative percent release of up to 45 and 57% of PM and IND, respectively, within 40 min of contact with dissolution medium simulating saliva.

  5. Relapse Model among Iranian Drug Users: A Qualitative Study.

    Science.gov (United States)

    Jalali, Amir; Seyedfatemi, Naiemeh; Peyrovi, Hamid

    2015-01-01

    Relapse is a common problem in drug user's rehabilitation program and reported in all over the country. An in-depth study on patients' experiences can be used for exploring the relapse process among drug users. Therefore, this study suggests a model for relapse process among Iranian drug users. In this qualitative study with grounded theory approach, 22 participants with rich information about the phenomenon under the study were selected using purposive, snowball and theoretical sampling methods. After obtaining the informed consent, data were collected based on face-to-face, in-depth, semi-structured interviews. All interviews were analyzed in three stages of axial, selective and open coding methods. Nine main categories emerged, including avoiding of drugs, concerns about being accepted, family atmosphere, social conditions, mental challenge, self-management, self-deception, use and remorse and a main category, feeling of loss as the core variable. Mental challenge has two subcategories, evoking pleasure and craving. Relapse model is a dynamic and systematic process including from cycles of drug avoidance to remorse with a core variable as feeling of loss.  Relapse process is a dynamic and systematic process that needs an effective control. Determining a relapse model as a clear process could be helpful in clinical sessions. RESULTS of this research have depicted relapse process among Iranian drugs user by conceptual model.

  6. Scaffold proteins LACK and TRACK as potential drug targets in kinetoplastid parasites: Development of inhibitors.

    Science.gov (United States)

    Qvit, Nir; Schechtman, Deborah; Pena, Darlene Aparecida; Berti, Denise Aparecida; Soares, Chrislaine Oliveira; Miao, Qianqian; Liang, Liying Annie; Baron, Lauren A; Teh-Poot, Christian; Martínez-Vega, Pedro; Ramirez-Sierra, Maria Jesus; Churchill, Eric; Cunningham, Anna D; Malkovskiy, Andrey V; Federspiel, Nancy A; Gozzo, Fabio Cesar; Torrecilhas, Ana Claudia; Manso Alves, Maria Julia; Jardim, Armando; Momar, Ndao; Dumonteil, Eric; Mochly-Rosen, Daria

    2016-04-01

    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.

  7. Self assembling nanocomposites for protein delivery: supramolecular interactions of soluble polymers with protein drugs.

    Science.gov (United States)

    Salmaso, Stefano; Caliceti, Paolo

    2013-01-02

    Translation of therapeutic proteins to pharmaceutical products is often encumbered by their inadequate physicochemical and biopharmaceutical properties, namely low stability and poor bioavailability. Over the last decades, several academic and industrial research programs have been focused on development of biocompatible polymers to produce appropriate formulations that provide for enhanced therapeutic performance. According to their physicochemical properties, polymers have been exploited to obtain a variety of formulations including biodegradable microparticles, 3-dimensional hydrogels, bioconjugates and soluble nanocomposites. Several soluble polymers bearing charges or hydrophobic moieties along the macromolecular backbone have been found to physically associate with proteins to form soluble nanocomplexes. Physical complexation is deemed a valuable alternative tool to the chemical bioconjugation. Soluble protein/polymer nanocomplexes formed by physical specific or unspecific interactions have been found in fact to possess peculiar physicochemical, and biopharmaceutical properties. Accordingly, soluble polymeric systems have been developed to increase the protein stability, enhance the bioavailability, promote the absorption across the biological barriers, and prolong the protein residence in the bloodstream. Furthermore, a few polymers have been found to favour the protein internalisation into cells or boost their immunogenic potential by acting as immunoadjuvant in vaccination protocols. Copyright © 2011 Elsevier B.V. All rights reserved.

  8. Target-mediated drug disposition model and its approximations for antibody-drug conjugates.

    Science.gov (United States)

    Gibiansky, Leonid; Gibiansky, Ekaterina

    2014-02-01

    Antibody-drug conjugate (ADC) is a complex structure composed of an antibody linked to several molecules of a biologically active cytotoxic drug. The number of ADC compounds in clinical development now exceeds 30, with two of them already on the market. However, there is no rigorous mechanistic model that describes pharmacokinetic (PK) properties of these compounds. PK modeling of ADCs is even more complicated than that of other biologics as the model should describe distribution, binding, and elimination of antibodies with different toxin load, and also the deconjugation process and PK of the released toxin. This work extends the target-mediated drug disposition (TMDD) model to describe ADCs, derives the rapid binding (quasi-equilibrium), quasi-steady-state, and Michaelis-Menten approximations of the TMDD model as applied to ADCs, derives the TMDD model and its approximations for ADCs with load-independent properties, and discusses further simplifications of the system under various assumptions. The developed models are shown to describe data simulated from the available clinical population PK models of trastuzumab emtansine (T-DM1), one of the two currently approved ADCs. Identifiability of model parameters is also discussed and illustrated on the simulated T-DM1 examples.

  9. 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

  10. 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.

  11. Modelling of drug release from ensembles of aspirin microcapsules ...

    African Journals Online (AJOL)

    Purpose: In order to determine the drug release profile of an ensemble of aspirin crystals or microcapsules from its particle distribution a mathematical model that considered the individual release characteristics of the component single particles was developed. The model assumed that under sink conditions the release ...

  12. Molecular Modeling: A Powerful Tool for Drug Design and Molecular ...

    Indian Academy of Sciences (India)

    Molecular modeling has become a valuable and essential tool to medicinal chemists in the drug design process. Molecular modeling describes the generation, manipula- tion or representation of three-dimensional structures of molecules and associated physico-chemical properties. It involves a range of computerized ...

  13. Photoreactivity of biologically active compounds. VIII. Photosensitized polymerization of lens proteins by antimalarial drugs in vitro.

    Science.gov (United States)

    Kristensen, S; Wang, R H; Tønnesen, H H; Dillon, J; Roberts, J E

    1995-02-01

    The drugs commonly used in the treatment of malaria are photochemically unstable. Several of these compounds cause dermal and ocular toxic reactions that may be light induced. The in vitro photopolymerization of calf lens proteins in the presence of antimalarial drugs was studied as part of a screening of the photochemical properties and phototoxic capabilities of these compounds. The pseudo-first-order rate constant for the reaction was calculated, and related to the amount of light absorbed by the compounds in order to determine the relative photosensitizing effect of each drug. The reaction mechanisms were evaluated by adding a variety of quenchers to the reaction medium during irradiation. Based on the results obtained in this study and previous knowledge about the pharmacokinetic behavior of these compounds, several of the drugs investigated have to be considered as potential photosensitizers in the human lens, the retina and the skin.

  14. Modeling of activity landscapes for drug discovery.

    Science.gov (United States)

    Bajorath, Jürgen

    2012-06-01

    Activity landscapes (ALs) are graphical representations that integrate compound structure and potency relationships. These computer-generated models enable the interactive large-scale analysis of structure-activity relationships (SARs) and complement traditional approaches to study SARs of individual compound series in a qualitative or quantitative manner. A variety of AL designs have been reported. The concept of activity landscapes is introduced and different methodologies to represent 2D or 3D AL representations of large compound data sets are described on the basis of original literature references. Several AL variants and extensions have been generated for special applications in medicinal chemistry. These include, for example, AL views of evolving data sets with constant topology, selectivity landscapes and multi-target ALs, or molecular mechanism and multi-property maps. Furthermore, the applicability domain of the AL concept is discussed including specific requirements for practical utility in medicinal chemistry opportunities for further developments. AL modeling has substantially extended conventional ways to study SARs. The AL concept is inseparable from the notion of activity cliffs that are of high interest in SAR analysis. AL design is an area of active research at the interface between chemoinformatics and medicinal chemistry with potential for further growth. Special emphasis must be put on increasing the usability of AL models for practicing medicinal chemists.

  15. Polyionic hydrocolloids for the intestinal delivery of protein drugs: alginate and chitosan--a review.

    Science.gov (United States)

    George, Meera; Abraham, T Emilia

    2006-08-10

    The protein pharmaceutical market is rapidly growing, since it is gaining support from the recombinant DNA technology. To deliver these drugs via the oral route, the most preferred route, is the toughest challenge. In the design of oral delivery of peptide or protein drugs, pH sensitive hydrogels like alginate and chitosan have attracted increasing attention, since most of the synthetic polymers are immunogenic and the incorporation of proteins in to these polymers require harsh environment which may denature and inactivate the desired protein. Alginate is a water-soluble linear polysaccharide composed of alternating blocks of 1-4 linked alpha-L-guluronic and beta-D-mannuronic acid residues where as chitosan is a co polymer of D-glucosamine and N-acetyl glucosamine. The incorporation of protein into these two matrices can be done under relatively mild environment and hence the chances of protein denaturation are minimal. The limitations of these polymers, like drug leaching during preparation can be overcome by different techniques which increase their encapsulation efficiency. Alginate, being an anionic polymer with carboxyl end groups, is a good mucoadhesive agent. The pore size of alginate gel microbeads has been shown to be between 5 and 200 nm and coated beads and microspheres are found to be better oral delivery vehicles. Cross-linked alginate has more capacity to retain the entrapped drugs and mixing of alginate with other polymers such as neutral gums, pectin, chitosan, and eudragit have been found to solve the problem of drug leaching. Chitosan has only limited ability for controlling the release of encapsulated compound due to its hydrophilic nature and easy solubility in acidic medium. By simple covalent modifications of the polymer, its physicochemical properties can be changed and can be made suitable for the peroral drug delivery purpose. Ionic interactions between positively charged amino groups in chitosan and the negatively charged mucus gel layer

  16. Modeling the Dynamics of Acute Phase Protein Expression in Human Hepatoma Cells Stimulated by IL-6

    Directory of Open Access Journals (Sweden)

    Zhaobin Xu

    2015-01-01

    Full Text Available Interleukin-6 (IL-6 is a systemic inflammatory mediator that triggers the human body’s acute phase response to trauma or inflammation. Although mathematical models for IL-6 signaling pathways have previously been developed, reactions that describe the expression of acute phase proteins were not included. To address this deficiency, a recent model of IL-6 signaling was extended to predict the dynamics of acute phase protein expression in IL-6-stimulated HepG2 cells (a human hepatoma cell line. This included reactions that describe the regulation of haptoglobin, fibrinogen, and albumin secretion by nuclear transcription factors STAT3 dimer and C/EBPβ. This new extended model was validated against two different sets of experimental data. Using the validated model, a sensitivity analysis was performed to identify seven potential drug targets to regulate the secretion of haptoglobin, fibrinogen, and albumin. The drug-target binding kinetics for these seven targets was then integrated with the IL-6 kinetic model to rank them based upon the influence of their pairing with drugs on acute phase protein dynamics. It was found that gp80, JAK, and gp130 were the three most promising drug targets and that it was possible to reduce the therapeutic dosage by combining drugs aimed at the top three targets in a cocktail. These findings suggest hypotheses for further experimental investigation.

  17. 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.

  18. Emerging drugs to reduce abnormal β-amyloid protein in Alzheimer's disease patients.

    Science.gov (United States)

    Panza, Francesco; Seripa, Davide; Solfrizzi, Vincenzo; Imbimbo, Bruno P; Lozupone, Madia; Leo, Antonio; Sardone, Rodolfo; Gagliardi, Gaetano; Lofano, Lucia; Creanza, Bianca C; Bisceglia, Paola; Daniele, Antonio; Bellomo, Antonello; Greco, Antonio; Logroscino, Giancarlo

    2016-12-01

    Currently available drugs against Alzheimer's disease (AD) target cholinergic and glutamatergic neurotransmissions without affecting the underlying disease process. Putative disease-modifying drugs are in development and target β-amyloid (Aβ) peptide and tau protein, the principal neurophatological hallmarks of the disease. Areas covered: Phase III clinical studies of emerging anti-Aβ drugs for the treatment of AD were searched in US and EU clinical trial registries and in the medical literature until May 2016. Expert opinion: Drugs in Phase III clinical development for AD include one inhibitor of the β-secretase cleaving enzyme (BACE) (verubecestat), three anti-Aβ monoclonal antibodies (solanezumab, gantenerumab, and aducanumab), an inhibitor of receptor for advanced glycation end products (RAGE) (azeliragon) and the combination of cromolyn sodium and ibuprofen (ALZT-OP1). These drugs are mainly being tested in subjects during early phases of AD or in subjects at preclinical stage of familial AD or even in asymptomatic subjects at high risk of developing AD. The hope is to intervene in the disease process when it is not too late. However, previous clinical failures with anti-Aβ drugs and the lack of fully understanding of the pathophysiological role of Aβ in the development of AD, put the new drugs at substantial risk of failure.

  19. Finding candidate drugs for hepatitis C based on chemical-chemical and chemical-protein interactions.

    Directory of Open Access Journals (Sweden)

    Lei Chen

    Full Text Available Hepatitis C virus (HCV is an infectious virus that can cause serious illnesses. Only a few drugs have been reported to effectively treat hepatitis C. To have greater diversity in drug choice and better treatment options, it is necessary to develop more drugs to treat the infection. However, it is time-consuming and expensive to discover candidate drugs using experimental methods, and computational methods may complement experimental approaches as a preliminary filtering process. This type of approach was proposed by using known chemical-chemical interactions to extract interactive compounds with three known drug compounds of HCV, and the probabilities of these drug compounds being able to treat hepatitis C were calculated using chemical-protein interactions between the interactive compounds and HCV target genes. Moreover, the randomization test and expectation-maximization (EM algorithm were both employed to exclude false discoveries. Analysis of the selected compounds, including acyclovir and ganciclovir, indicated that some of these compounds had potential to treat the HCV. Hopefully, this proposed method could provide new insights into the discovery of candidate drugs for the treatment of HCV and other diseases.

  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. Toward a normalized clinical drug knowledge base in China-applying the RxNorm model to Chinese clinical drugs.

    Science.gov (United States)

    Wang, Li; Zhang, Yaoyun; Jiang, Min; Wang, Jingqi; Dong, Jiancheng; Liu, Yun; Tao, Cui; Jiang, Guoqian; Zhou, Yi; Xu, Hua

    2018-04-04

    In recent years, electronic health record systems have been widely implemented in China, making clinical data available electronically. However, little effort has been devoted to making drug information exchangeable among these systems. This study aimed to build a Normalized Chinese Clinical Drug (NCCD) knowledge base, by applying and extending the information model of RxNorm to Chinese clinical drugs. Chinese drugs were collected from 4 major resources-China Food and Drug Administration, China Health Insurance Systems, Hospital Pharmacy Systems, and China Pharmacopoeia-for integration and normalization in NCCD. Chemical drugs were normalized using the information model in RxNorm without much change. Chinese patent drugs (i.e., Chinese herbal extracts), however, were represented using an expanded RxNorm model to incorporate the unique characteristics of these drugs. A hybrid approach combining automated natural language processing technologies and manual review by domain experts was then applied to drug attribute extraction, normalization, and further generation of drug names at different specification levels. Lastly, we reported the statistics of NCCD, as well as the evaluation results using several sets of randomly selected Chinese drugs. The current version of NCCD contains 16 976 chemical drugs and 2663 Chinese patent medicines, resulting in 19 639 clinical drugs, 250 267 unique concepts, and 2 602 760 relations. By manual review of 1700 chemical drugs and 250 Chinese patent drugs randomly selected from NCCD (about 10%), we showed that the hybrid approach could achieve an accuracy of 98.60% for drug name extraction and normalization. Using a collection of 500 chemical drugs and 500 Chinese patent drugs from other resources, we showed that NCCD achieved coverages of 97.0% and 90.0% for chemical drugs and Chinese patent drugs, respectively. Evaluation results demonstrated the potential to improve interoperability across various electronic drug systems

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

    Directory of Open Access Journals (Sweden)

    Yuri Pevzner

    2015-08-01

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

  3. 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.

  4. Industry Perspective on Contemporary Protein-Binding Methodologies: Considerations for Regulatory Drug-Drug Interaction and Related Guidelines on Highly Bound Drugs.

    Science.gov (United States)

    Di, Li; Breen, Christopher; Chambers, Rob; Eckley, Sean T; Fricke, Robert; Ghosh, Avijit; Harradine, Paul; Kalvass, J Cory; Ho, Stacy; Lee, Caroline A; Marathe, Punit; Perkins, Everett J; Qian, Mark; Tse, Susanna; Yan, Zhengyin; Zamek-Gliszczynski, Maciej J

    2017-12-01

    Regulatory agencies have recently issued drug-drug interaction guidelines, which require determination of plasma protein binding (PPB). To err on the conservative side, the agencies recommend that a 0.01 lower limit of fraction unbound (f u ) be used for highly bound compounds (>99%), irrespective of the actual measured values. While this may avoid false negatives, the recommendation would likely result in a high rate of false positive predictions, resulting in unnecessary clinical studies and more stringent inclusion/exclusion criteria, which may add cost and time in delivery of new medicines to patients. In this perspective, we provide a review of current approaches to measure PPB, and important determinants in enabling the accuracy and precision in these measurements. The ability to measure f u is further illustrated by a cross-company data comparison of PPB for warfarin and itraconazole, demonstrating good concordance of the measured f u values. The data indicate that f u values of ≤0.01 may be determined accurately across laboratories when appropriate methods are used. These data, along with numerous other examples presented in the literature, support the use of experimentally measured f u values for drug-drug interaction predictions, rather than using the arbitrary cutoff value of 0.01 as recommended in current regulatory guidelines. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

  5. 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.

  6. Effective cell-free drug screening protocol for protein-protein interaction.

    Science.gov (United States)

    Ashkenazi, Shaked; Plotnikov, Alexander; Bahat, Anat; Dikstein, Rivka

    2017-09-01

    Specific protein-protein interaction (PPI) is an essential feature of many cellular processes however, targeting these interactions by small molecules is highly challenging due to the nature of the interaction interface. Thus, screening for PPI inhibitors requires enormous number of compounds. Here we describe a simple and improved protocol designed for a search of direct PPI inhibitors. We engineered a bacterial expression system for the split-Renilla luciferase (RL) complementation assay that monitors PPI. This enables production of large quantities of the RL fusion proteins in a simple and cost effective manner that is suitable for very large screens. Subsequently, inhibitory compounds are analyzed in a similar complementation assay in living cultured mammalian cells to select for those that can penetrate cells. We applied this method to NF-κB, a family of dimeric transcription factors that plays central roles in immune responses, cell survival and aging, and its dysregulation is linked to many pathological states. This strategy led to the identification of several direct NF-κB inhibitors. As the described protocol is very straightforward and robust it may be suitable for many pairs of interacting proteins. Copyright © 2017 Elsevier Inc. All rights reserved.

  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. Computational and experimental model of transdermal iontophorethic drug delivery system.

    Science.gov (United States)

    Filipovic, Nenad; Saveljic, Igor; Rac, Vladislav; Graells, Beatriz Olalde; Bijelic, Goran

    2017-11-30

    The concept of iontophoresis is often applied to increase the transdermal transport of drugs and other bioactive agents into the skin or other tissues. It is a non-invasive drug delivery method which involves electromigration and electroosmosis in addition to diffusion and is shown to be a viable alternative to conventional administration routs such as oral, hypodermic and intravenous injection. In this study we investigated, experimentally and numerically, in vitro drug delivery of dexamethasone sodium phosphate to porcine skin. Different current densities, delivery durations and drug loads were investigated experimentally and introduced as boundary conditions for numerical simulations. Nernst-Planck equation was used for calculation of active substance flux through equivalent model of homogeneous hydrogel and skin layers. The obtained numerical results were in good agreement with experimental observations. A comprehensive in-silico platform, which includes appropriate numerical tools for fitting, could contribute to iontophoretic drug-delivery devices design and correct dosage and drug clearance profiles as well as to perform much faster in-silico experiments to better determine parameters and performance criteria of iontophoretic drug delivery. Copyright © 2017 Elsevier B.V. All rights reserved.

  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. Ceramic core with polymer corona hybrid nanocarrier for the treatment of osteosarcoma with co-delivery of protein and anti-cancer drug

    Science.gov (United States)

    Ram Prasad, S.; Sampath Kumar, T. S.; Jayakrishnan, A.

    2018-01-01

    For the treatment of metastatic bone cancer, local delivery of therapeutic agents is preferred compared to systemic administration. Delivery of an anti-cancer drug and a protein that helps in bone regeneration simultaneously is a challenging approach. In this study, a nanoparticulate carrier which delivers a protein and an anti-cancer drug is reported. Bovine serum albumin (BSA) as a model protein was loaded into hydroxyapatite (HA) nanoparticles (NPs) and methotrexate (MTX) conjugated to poly(vinyl alcohol) was coated onto BSA-loaded HA NPs. Coating efficiency was in the range of 10–17 wt%. In vitro drug release showed that there was a steady increase in the release of both BSA and MTX with 76% of BSA and 88% of MTX being released in 13 days. Cytotoxicity studies of the NPs performed using human osteosarcoma (OMG-63) cell line showed the NPs were highly biocompatible and exhibited anti-proliferative activity in a concentration-dependent manner.

  12. 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.

  13. 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.

  14. Animal models of pancreatic cancer for drug research.

    Science.gov (United States)

    Kapischke, Matthias; Pries, Alexandra

    2008-10-01

    The operative and conservative results of therapy in pancreatic ductal adenocarcinoma remain appallingly poor. This underlines the demand for further research for effective anticancer drugs. The various animal models remain the essential method for the determination of efficacy of substances during preclinical phase. Unfortunately, most of these tested substances showed a good efficacy in pancreatic carcinoma in the animal model but were not confirmed during the clinical phase. The available literature in PubMed, Medline, Ovid and secondary literature was searched regarding the available animal models for drug testing against pancreatic cancer. The models were analyzed regarding their pros and cons in anticancer drug testing. The different modifications of the orthotopic model (especially in mice) seem at present to be the best model for anticancer testing in pancreatic carcinoma. The value of genetically engineered animal model (GEM) and syngeneic models is on debate. A good selection of the model concerning the questions supposed to be clarified may improve the comparability of the results of animal experiments compared to clinical trials.

  15. 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.

  16. Promiscuity and the conformational rearrangement of drug-like molecules: insight from the protein data bank.

    Science.gov (United States)

    He, Michael W; Lee, Patrick S; Sweeney, Zachary K

    2015-02-01

    Selectivity is a central aspect of lead optimization in the drug discovery process. Medicinal chemists often try to decrease molecular flexibility to improve selectivity, given the common belief that the two are interdependent. To investigate the relationship between polypharmacology and conformational flexibility, we mined the Protein Data Bank and constructed a dataset of pharmaceutically relevant ligands that crystallized in more than one protein target while binding to each co-crystallized receptor with similar in vitro affinities. After analyzing the molecular conformations of these 100 ligands, we found that 59 ligands bound to different protein targets without significantly changing conformation, suggesting that there is no distinct correlation between conformational flexibility and polypharmacology within our dataset. Ligands crystallized in similar proteins and highly ligand-efficient compounds with five or fewer rotatable bonds were less likely to adjust conformation when binding. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Oral delivery of peptides and proteins using lipid-based drug delivery systems

    DEFF Research Database (Denmark)

    Li, Ping; Nielsen, Hanne Mørck; Müllertz, Anette

    2012-01-01

    INTRODUCTION: In order to successfully develop lipid-based drug delivery systems (DDS) for oral administration of peptides and proteins, it is important to gain an understanding of the colloid structures formed by these DDS, the mode of peptide and protein incorporation as well as the mechanism...... by which intestinal absorption of peptides and proteins is promoted. AREAS COVERED: The present paper reviews the literature on lipid-based DDS, employed for oral delivery of peptides and proteins and highlights the mechanisms by which the different lipid-based carriers are expected to overcome the two...... most important barriers (extensive enzymatic degradation and poor transmucosal permeability). This paper also gives a clear-cut idea about advantages and drawbacks of using different lipidic colloidal carriers ((micro)emulsions, solid lipid core particles and liposomes) for oral delivery of peptides...

  18. Exploring the binding sites and binding mechanism for hydrotrope encapsulated griseofulvin drug on γ-tubulin protein.

    Science.gov (United States)

    Das, Shubhadip; Paul, Sandip

    2018-01-01

    The protein γ-tubulin plays an important role in centrosomal clustering and this makes it an attractive therapeutic target for treating cancers. Griseofulvin, an antifungal drug, has recently been used to inhibit proliferation of various types of cancer cells. It can also affect the microtubule dynamics by targeting the γ-tubulin protein. So far, the binding pockets of γ-tubulin protein are not properly identified and the exact mechanism by which the drug binds to it is an area of intense speculation and research. The aim of the present study is to investigate the binding mechanism and binding affinity of griseofulvin on γ-tubulin protein using classical molecular dynamics simulations. Since the drug griseofulvin is sparingly soluble in water, here we also present a promising approach for formulating and achieving delivery of hydrophobic griseofulvin drug via hydrotrope sodium cumene sulfonate (SCS) cluster. We observe that the binding pockets of γ-tubulin protein are mainly formed by the H8, H9 helices and S7, S8, S14 strands and the hydrophobic interactions between the drug and γ-tubulin protein drive the binding process. The release of the drug griseofulvin from the SCS cluster is confirmed by the coordination number analysis. We also find hydrotrope-induced alteration of the binding sites of γ-tubulin protein and the weakening of the drug-protein interactions.

  19. Exploring the binding sites and binding mechanism for hydrotrope encapsulated griseofulvin drug on γ-tubulin protein.

    Directory of Open Access Journals (Sweden)

    Shubhadip Das

    Full Text Available The protein γ-tubulin plays an important role in centrosomal clustering and this makes it an attractive therapeutic target for treating cancers. Griseofulvin, an antifungal drug, has recently been used to inhibit proliferation of various types of cancer cells. It can also affect the microtubule dynamics by targeting the γ-tubulin protein. So far, the binding pockets of γ-tubulin protein are not properly identified and the exact mechanism by which the drug binds to it is an area of intense speculation and research. The aim of the present study is to investigate the binding mechanism and binding affinity of griseofulvin on γ-tubulin protein using classical molecular dynamics simulations. Since the drug griseofulvin is sparingly soluble in water, here we also present a promising approach for formulating and achieving delivery of hydrophobic griseofulvin drug via hydrotrope sodium cumene sulfonate (SCS cluster. We observe that the binding pockets of γ-tubulin protein are mainly formed by the H8, H9 helices and S7, S8, S14 strands and the hydrophobic interactions between the drug and γ-tubulin protein drive the binding process. The release of the drug griseofulvin from the SCS cluster is confirmed by the coordination number analysis. We also find hydrotrope-induced alteration of the binding sites of γ-tubulin protein and the weakening of the drug-protein interactions.

  20. 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

  1. Mathematical modeling of multi-drugs therapy: a challenge for determining the optimal combinations of antiviral drugs.

    Science.gov (United States)

    Koizumi, Yoshiki; Iwami, Shingo

    2014-09-25

    In the current era of antiviral drug therapy, combining multiple drugs is a primary approach for improving antiviral effects, reducing the doses of individual drugs, relieving the side effects of strong antiviral drugs, and preventing the emergence of drug-resistant viruses. Although a variety of new drugs have been developed for HIV, HCV and influenza virus, the optimal combinations of multiple drugs are incompletely understood. To optimize the benefits of multi-drugs combinations, we must investigate the interactions between the combined drugs and their target viruses. Mathematical models of viral infection dynamics provide an ideal tool for this purpose. Additionally, whether drug combinations computed by these models are synergistic can be assessed by two prominent drug combination theories, Loewe additivity and Bliss independence. By combining the mathematical modeling of virus dynamics with drug combination theories, we could show the principles by which drug combinations yield a synergistic effect. Here, we describe the theoretical aspects of multi-drugs therapy and discuss their application to antiviral research.

  2. 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.

  3. 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.

  4. 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.

  5. Mechanism of the pharmacokinetic interaction between methotrexate and benzimidazoles: potential role for breast cancer resistance protein in clinical drug-drug interactions

    NARCIS (Netherlands)

    Breedveld, Pauline; Zelcer, Noam; Pluim, Dick; Sönmezer, Ozgür; Tibben, Matthijs M.; Beijnen, Jos H.; Schinkel, Alfred H.; van Tellingen, Olaf; Borst, Piet; Schellens, Jan H. M.

    2004-01-01

    The antifolate drug methotrexate (MTX) is transported by breast cancer resistance protein (BCRP; ABCG2) and multidrug resistance-associated protein1-4 (MRP1-4; ABCC1-4). In cancer patients, coadministration of benzimidazoles and MTX can result in profound MTX-induced toxicity coinciding with an

  6. A 9-state hidden Markov model using protein secondary structure information for protein fold recognition.

    Science.gov (United States)

    Lee, Sun Young; Lee, Jong Yun; Jung, Kwang Su; Ryu, Keun Ho

    2009-06-01

    In protein fold recognition, the main disadvantage of hidden Markov models (HMMs) is the employment of large-scale model architectures which require large data sets and high computational resources for training. Also, HMMs must consider sequential information about secondary structures of proteins, to improve prediction performance and reduce model parameters. Therefore, we propose a novel method for protein fold recognition based on a hidden Markov model, called a 9-state HMM. The method can (i) reduce the number of states using secondary structure information about proteins for each fold and (ii) recognize protein folds more accurately than other HMMs.

  7. Using existing drugs as leads for broad spectrum anthelmintics targeting protein kinases.

    Directory of Open Access Journals (Sweden)

    Christina M Taylor

    2013-02-01

    Full Text Available As one of the largest protein families, protein kinases (PKs regulate nearly all processes within the cell and are considered important drug targets. Much research has been conducted on inhibitors for PKs, leading to a wealth of compounds that target PKs that have potential to be lead anthelmintic drugs. Identifying compounds that have already been developed to treat neglected tropical diseases is an attractive way to obtain lead compounds inexpensively that can be developed into much needed drugs, especially for use in developing countries. In this study, PKs from nematodes, hosts, and DrugBank were identified and classified into kinase families and subfamilies. Nematode proteins were placed into orthologous groups that span the phylum Nematoda. A minimal kinome for the phylum Nematoda was identified, and properties of the minimal kinome were explored. Orthologous groups from the minimal kinome were prioritized for experimental testing based on RNAi phenotype of the Caenorhabditis elegans ortholog, transcript expression over the life-cycle and anatomic expression patterns. Compounds linked to targets in DrugBank belonging to the same kinase families and subfamilies in the minimal nematode kinome were extracted. Thirty-five compounds were tested in the non-parasitic C. elegans and active compounds progressed to testing against nematode species with different modes of parasitism, the blood-feeding Haemonchus contortus and the filarial Brugia malayi. Eighteen compounds showed efficacy in C. elegans, and six compounds also showed efficacy in at least one of the parasitic species. Hypotheses regarding the pathway the compounds may target and their molecular mechanism for activity are discussed.

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

    OpenAIRE

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

    2010-01-01

    The main pharmacological effects of marijuana, as well as synthetic and endogenous cannabinoids, are mediated through G-protein-coupled receptors (GPCRs), including CB1 and CB2 receptors. The CB1 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 sugge...

  9. The additive damage model: a mathematical model for cellular responses to drug combinations.

    Science.gov (United States)

    Jones, Leslie Braziel; Secomb, Timothy W; Dewhirst, Mark W; El-Kareh, Ardith W

    2014-09-21

    Mathematical models to describe dose-dependent cellular responses to drug combinations are an essential component of computational simulations for predicting therapeutic responses. Here, a new model, the additive damage model, is introduced and tested in cases where varying concentrations of two drugs are applied with a fixed exposure schedule. In the model, cell survival is determined by whether cellular damage, which depends on the concentrations of the drugs, exceeds a lethal threshold, which varies randomly in the cell population with a prescribed statistical distribution. Cellular damage is assumed to be additive, and is expressed as a sum of separate terms for each drug. Each term has a saturable dependence on drug concentration. The model has appropriate behavior over the entire range of drug concentrations, and is predictive, given single-agent dose-response data for each drug. The proposed model is compared with several other models, by testing their ability to fit 24 data sets for platinum-taxane combinations and 21 data sets for various other combinations. The Akaike Information Criterion is used to assess goodness of fit, taking into account the number of unknown parameters in each model. Overall, the additive damage model provides a better fit to the data sets than any previous model. The proposed model provides a basis for computational simulations of therapeutic responses. It predicts responses to drug combinations based on data for each drug acting as a single agent, and can be used as an improved null reference model for assessing synergy in the action of drug combinations. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. Mathematical models for drug diffusion through the compartments of ...

    African Journals Online (AJOL)

    M.A. Khanday

    2016-07-26

    Jul 26, 2016 ... quadratic shape function.10. Moreover, Khanday and. Najar11,12 established the mathematical models on oxygen transport in biological tissues through capillary bed using both analytical and numerical methods. In this study, we extended the diffusion of drug in blood and tissue using three mathemat-.

  11. 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 headach...

  12. Molecular Modeling: A Powerful Tool for Drug Design and Molecular ...

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 9; Issue 5. Molecular Modeling: A Powerful Tool for Drug Design and Molecular Docking. Rama Rao Nadendla. General Article Volume 9 Issue 5 May 2004 pp 51-60. Fulltext. Click here to view fulltext PDF. Permanent link:

  13. Antibodies directed to drug epitopes to investigate the structure of drug-protein photoadducts. Recognition of a common photobound substructure in tiaprofenic acid/ketoprofen cross-photoreactivity.

    Science.gov (United States)

    Lahoz, A; Hernández, D; Miranda, M A; Pérez-Prieto, J; Morera, I M; Castell, J V

    2001-11-01

    Drug-induced photoallergy is an immune adverse reaction to the combined effect of drugs and light. From the mechanistic point of view, it first involves covalent binding of drug to protein resulting in the formation of a photoantigen. Hence, determination of the structures of drug-protein photoadducts is of great relevance to understand the molecular basis of photoallergy and cross-immunoreactivity among drugs. Looking for new strategies to investigate the covalent photobinding of drugs to proteins, we generated highly specific antibodies to drug chemical substructures. The availability of such antibodies has allowed us to discriminate between the different modes by which tiaprofenic acid (TPA), suprofen (SUP), and ketoprofen (KTP) photobind to proteins. The finding that the vast majority of the TPA photoadduct can be accounted for by means of antibody anti-benzoyl strongly supports the view that the drug binds preferentially via the thiophene ring, leaving the benzene ring more accessible. By contrast, selective recognition of SUP-protein photoadducts by antibody anti-thenoyl evidences a preferential coupling via the benzene ring leaving the thiophene moiety more distant from the protein matrix. In the case of KTP, photoadducts are exclusively recognized by antibody anti-benzoyl, indicating that the benzene ring is again more accessible. As a result of this research, we have been able to identify a common substructure that is present in TPA-albumin and KTP-albumin photoadducts. This is remarkable since, at a first sight, the greatest structural similarities can be found between TPA and SUP as they share the same benzoylthiophene chromophore. These findings can explain the previously reported observations of cross-reactivity to KTP (or TPA) in patients photosensitized to TPA (or KTP).

  14. Filovirus proteins for antiviral drug discovery: Structure/function bases of the replication cycle.

    Science.gov (United States)

    Martin, Baptiste; Canard, Bruno; Decroly, Etienne

    2017-05-01

    Filoviruses are important pathogens that cause severe and often fatal hemorrhagic fever in humans, for which no approved vaccines and antiviral treatments are yet available. In an earlier article (Martin et al., Antiviral Research, 2016), we reviewed the role of the filovirus surface glycoprotein in replication and as a target for drugs and vaccines. In this review, we focus on recent findings on the filovirus replication machinery and how they could be used for the identification of new therapeutic targets and the development of new antiviral compounds. First, we summarize the recent structural and functional advances on the molecules involved in filovirus replication/transcription cycle, particularly the NP, VP30, VP35 proteins, and the "large" protein L, which harbors the RNA-dependent RNA polymerase (RdRp) and mRNA capping activities. These proteins are essential for viral mRNA synthesis and genome replication, and consequently they constitute attractive targets for drug design. We then describe how these insights into filovirus replication mechanisms and the structure/function characterization of the involved proteins have led to the development of new and innovative antiviral strategies that may help reduce the filovirus disease case fatality rate through post-exposure or prophylactic treatments. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Mathematical models of tumor heterogeneity and drug resistance

    Science.gov (United States)

    Greene, James

    In this dissertation we develop mathematical models of tumor heterogeneity and drug resistance in cancer chemotherapy. Resistance to chemotherapy is one of the major causes of the failure of cancer treatment. Furthermore, recent experimental evidence suggests that drug resistance is a complex biological phenomena, with many influences that interact nonlinearly. Here we study the influence of such heterogeneity on treatment outcomes, both in general frameworks and under specific mechanisms. We begin by developing a mathematical framework for describing multi-drug resistance to cancer. Heterogeneity is reflected by a continuous parameter, which can either describe a single resistance mechanism (such as the expression of P-gp in the cellular membrane) or can account for the cumulative effect of several mechanisms and factors. The model is written as a system of integro-differential equations, structured by the continuous "trait," and includes density effects as well as mutations. We study the limiting behavior of the model, both analytically and numerically, and apply it to study treatment protocols. We next study a specific mechanism of tumor heterogeneity and its influence on cell growth: the cell-cycle. We derive two novel mathematical models, a stochastic agent-based model and an integro-differential equation model, each of which describes the growth of cancer cells as a dynamic transition between proliferative and quiescent states. By examining the role all parameters play in the evolution of intrinsic tumor heterogeneity, and the sensitivity of the population growth to parameter values, we show that the cell-cycle length has the most significant effect on the growth dynamics. In addition, we demonstrate that the agent-based model can be approximated well by the more computationally efficient integro-differential equations, when the number of cells is large. The model is closely tied to experimental data of cell growth, and includes a novel implementation of

  16. Interplay between unfolded protein response and autophagy promotes tumor drug resistance.

    Science.gov (United States)

    Yan, Ming-Ming; Ni, Jiang-Dong; Song, Deye; Ding, Muliang; Huang, Jun

    2015-10-01

    The endoplasmic reticulum (ER) is involved in the quality control of secreted protein via promoting the correct folding of nascent protein and mediating the degradation of unfolded or misfolded protein, namely ER-associated degradation. When the unfolded or misfolded proteins are abundant, the unfolded protein response (UPR) is elicited, an adaptive signaling cascade from the ER to the nucleus, which restores the homeostatic functions of the ER. Autophagy is a conserved catabolic process where cellular long-lived proteins and damaged organelles are engulfed and degraded for recycling to maintain homeostasis. The UPR and autophagy occur simultaneously and are involved in pathological processes, including tumorigenesis, chemoresistance of malignancies and neurodegeneration. Accumulative data has indicated that the UPR may induce autophagy and that autophagy is able to alleviate the UPR. However, the detailed mechanism of interplay between autophagy and UPR remains to be fully understood. The present review aimed to depict the core pathways of the two processes and to elucidate how autophagy and UPR are regulated. Moreover, the review also discusses the molecular mechanism of crosstalk between the UPR and autophagy and their roles in malignant survival and drug resistance.

  17. Highly stable, protein capped gold nanoparticles as effective drug delivery vehicles for amino-glycosidic antibiotics

    International Nuclear Information System (INIS)

    Rastogi, Lori; Kora, Aruna Jyothi; Arunachalam, J.

    2012-01-01

    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: ► Method for NaBH 4 reduced and BSA capped gold nanoparticle was standardized. ► Nanoparticles were spherical and nearly monodispersed with a size of 7.8 nm. ► Nanoparticles are extremely stable towards pH modification and electrolyte addition. ► Antibiotic conjugated nanoparticles exhibited enhanced antibacterial activity

  18. 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

  19. 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.

  20. 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.

  1. 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.

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

    Science.gov (United States)

    Chakravarty, Koyel; Dalal, D. C.

    2016-10-01

    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 played by diffusion, mass-transfer, particle binding and internalization parameters.

  3. Zebrafish xenograft models of cancer and metastasis for drug discovery.

    Science.gov (United States)

    Brown, Hannah K; Schiavone, Kristina; Tazzyman, Simon; Heymann, Dominique; Chico, Timothy Ja

    2017-04-01

    Patients with metastatic cancer suffer the highest rate of cancer-related death, but existing animal models of metastasis have disadvantages that limit our ability to understand this process. The zebrafish is increasingly used for cancer modelling, particularly xenografting of human cancer cell lines, and drug discovery, and may provide novel scientific and therapeutic insights. However, this model system remains underexploited. Areas covered: The authors discuss the advantages and disadvantages of the zebrafish xenograft model for the study of cancer, metastasis and drug discovery. They summarise previous work investigating the metastatic cascade, such as tumour-induced angiogenesis, intravasation, extravasation, dissemination and homing, invasion at secondary sites, assessing metastatic potential and evaluation of cancer stem cells in zebrafish. Expert opinion: The practical advantages of zebrafish for basic biological study and drug discovery are indisputable. However, their ability to sufficiently reproduce and predict the behaviour of human cancer and metastasis remains unproven. For this to be resolved, novel mechanisms must to be discovered in zebrafish that are subsequently validated in humans, and for therapeutic interventions that modulate cancer favourably in zebrafish to successfully translate to human clinical studies. In the meantime, more work is required to establish the most informative methods in zebrafish.

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

    Science.gov (United States)

    Pignatello, R.; Musumeci, T.; Basile, L.; Carbone, C.; Puglisi, G.

    2011-01-01

    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. PMID:21430952

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

    Science.gov (United States)

    Pignatello, R; Musumeci, T; Basile, L; Carbone, C; Puglisi, G

    2011-01-01

    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.

  6. 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.

  7. 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.

  8. PROTACs: An Emerging Targeting Technique for Protein Degradation in Drug Discovery.

    Science.gov (United States)

    Gu, Shanshan; Cui, Danrui; Chen, Xiaoyu; Xiong, Xiufang; Zhao, Yongchao

    2018-04-01

    Proteolysis-targeting chimeric molecules (PROTACs) represent an emerging technique that is receiving much attention for therapeutic intervention. The mechanism is based on the inhibition of protein function by hijacking a ubiquitin E3 ligase for protein degradation. The hetero-bifunctional PROTACs contain a ligand for recruiting an E3 ligase, a linker, and another ligand to bind with the protein targeted for degradation. Thus, PROTACs have profound potential to eliminate "undruggable" protein targets, such as transcription factors and non-enzymatic proteins, which are not limited to physiological substrates of the ubiquitin-proteasome system. These findings indicate great prospects for PROTACs in the development of therapeutics. However, there are several limitations related to poor stability, biodistribution, and penetrability in vivo. This review provides an overview of the main PROTAC-based approaches that have been developed and discusses the promising opportunities and considerations for the application of this technology in therapies and drug discovery. © 2018 The Authors. BioEssays Published by Wiley Periodicals, Inc.

  9. A generic whole body physiologically based pharmacokinetic model for therapeutic proteins in PK-Sim.

    Science.gov (United States)

    Niederalt, Christoph; Kuepfer, Lars; Solodenko, Juri; Eissing, Thomas; Siegmund, Hans-Ulrich; Block, Michael; Willmann, Stefan; Lippert, Jörg

    2018-04-01

    Proteins are an increasingly important class of drugs used as therapeutic as well as diagnostic agents. A generic physiologically based pharmacokinetic (PBPK) model was developed in order to represent at whole body level the fundamental mechanisms driving the distribution and clearance of large molecules like therapeutic proteins. The model was built as an extension of the PK-Sim model for small molecules incorporating (i) the two-pore formalism for drug extravasation from blood plasma to interstitial space, (ii) lymph flow, (iii) endosomal clearance and (iv) protection from endosomal clearance by neonatal Fc receptor (FcRn) mediated recycling as especially relevant for antibodies. For model development and evaluation, PK data was used for compounds with a wide range of solute radii. The model supports the integration of knowledge gained during all development phases of therapeutic proteins, enables translation from pre-clinical species to human and allows predictions of tissue concentration profiles which are of relevance for the analysis of on-target pharmacodynamic effects as well as off-target toxicity. The current implementation of the model replaces the generic protein PBPK model available in PK-Sim since version 4.2 and becomes part of the Open Systems Pharmacology Suite.

  10. 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.

  11. Local Drug-Drug Interaction of Donepezil with Cilostazol at Breast Cancer Resistance Protein (ABCG2) Increases Drug Accumulation in Heart.

    Science.gov (United States)

    Takeuchi, Ryota; Shinozaki, Kohki; Nakanishi, Takeo; Tamai, Ikumi

    2016-01-01

    Clinical reports indicate that cardiotoxicity due to donepezil can occur after coadministration with cilostazol. We speculated that the concentration of donepezil in heart tissue might be increased as a result of interaction with cilostazol at efflux transporters such as P-glycoprotein (P-gp, ABCB1) and breast cancer resistance protein (BCRP, ABCG2), which are expressed in many tissues including the heart, and our study tested this hypothesis. First, donepezil was confirmed to be a substrate of both BCRP and P-glycoprotein in transporter-transfected cells in vitro. Cilostazol inhibited BCRP and P-glycoprotein with half-inhibitory concentrations of 130 nM and 12.7 μM, respectively. Considering the clinically achievable unbound plasma concentration of cilostazol (about 200 nM), it is plausible that BCRP-mediated transport of donepezil would be affected by cilostazol in vivo. Indeed, in an in vivo rat study, we found that coadministration of cilostazol significantly increased the concentrations of donepezil in the heart and brain, where BCRP functions as a part of the blood-tissue barrier, whereas the plasma concentration of donepezil was unaffected. In addition, in vitro accumulation of donepezil in heart tissue slices of rats was significantly increased in the presence of cilostazol. These results indicate that donepezil-cilostazol interaction at BCRP may be clinically relevant in heart and brain tissues. In other words, the tissue distribution of drugs can be influenced by drug-drug interaction (DDI) at efflux transporters in certain tissues (local DDI) without any apparent change in plasma concentration (systemic DDI). Copyright © 2015 by The American Society for Pharmacology and Experimental Therapeutics.

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

    Science.gov (United States)

    Vilar, Santiago; Hripcsak, George

    2016-01-01

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

  13. Prioritization of potential drug targets against P. aeruginosa by core proteomic analysis using computational subtractive genomics and Protein-Protein interaction network.

    Science.gov (United States)

    Uddin, Reaz; Jamil, Faiza

    2018-03-08

    Pseudomonas aeruginosa is an opportunistic gram-negative bacterium that has the capability to acquire resistance under hostile conditions and become a threat worldwide. It is involved in nosocomial infections. In the current study, potential novel drug targets against P. aeruginosa have been identified using core proteomic analysis and Protein-Protein Interactions (PPIs) studies. The non-redundant reference proteome of 68 strains having complete genome and latest assembly version of P. aeruginosa were downloaded from ftp NCBI RefSeq server in October 2016. The standalone CD-HIT tool was used to cluster ortholog proteins (having >=80% amino acid identity) present in all strains. The pan-proteome was clustered in 12,380 Clusters of Orthologous Proteins (COPs). By using in-house shell scripts, 3252 common COPs were extracted out and designated as clusters of core proteome. The core proteome of PAO1 strain was selected by fetching PAO1's proteome from common COPs. As a result, 1212 proteins were shortlisted that are non-homologous to the human but essential for the survival of the pathogen. Among these 1212 proteins, 321 proteins are conserved hypothetical proteins. Considering their potential as drug target, those 321 hypothetical proteins were selected and their probable functions were characterized. Based on the druggability criteria, 18 proteins were shortlisted. The interacting partners were identified by investigating the PPIs network using STRING v10 database. Subsequently, 8 proteins were shortlisted as 'hub proteins' and proposed as potential novel drug targets against P. aeruginosa. The study is interesting for the scientific community working to identify novel drug targets against MDR pathogens particularly P. aeruginosa. Copyright © 2018 Elsevier Ltd. All rights reserved.

  14. 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

  15. A residue level protein-protein interaction model in electrolyte solutions

    Science.gov (United States)

    Song, Xueyu

    2014-03-01

    The osmotic second virial coefficients B2 are directly related to the solubility of protein molecules in electrolyte solutions and can be useful to narrow down the search parameter space of protein crystallization conditions. Using a residue level model of protein-protein interaction in electrolyte solutions B2 of bovine pancreatic trypsin inhibitor and lysozyme in various solution conditions such as salt concentration, pH and temperature are calculated using an extended Fast Multipole Methods in combination with the boundary element formulation. Overall, the calculated B2 are well correlated with the experimental observations for various solution conditions. In combination with our previous work on the binding affinity calculations of protein complexes it is demonstrated that our residue level model can be used as a reliable model to describe protein-protein interaction in solutions.

  16. Modeling and molecular dynamics simulation of PR-1 protein from ...

    African Journals Online (AJOL)

    Pathogenesis-related (PR) proteins are considered as major weapons in plant's defense tactics against pathogens. The PR-1protein of Solanum tuberosum forms an integral part of the host defense system. We present here the 3D structure of PR-1 protein of S. tuberosum based on homology modeling technique.

  17. 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…

  18. 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.

  19. 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.

  20. Thermodynamical study of interaction of histone H1 chromosomal protein and mitoxantrone anticancer drug

    International Nuclear Information System (INIS)

    Jafargholizadeh, Naser; Zargar, Seyed Jalal; Safarian, Shahrokh; Habibi-Rezaei, Mehran

    2012-01-01

    Highlights: ► For the first time, our results show mitoxantrone anticancer drug binds to histone H1, via hydrophobic, hydrogen, van der Waals and electrostatic interactions. ► Binding of mitoxantrone molecules to histone H1 is positive cooperative. ► 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.

  1. A Systems Dynamic Model for Drug Abuse and Drug-Related Crime in the Western Cape Province of South Africa

    OpenAIRE

    Nyabadza, Farai; Coetzee, Lezanie

    2017-01-01

    The complex problem of drug abuse and drug-related crimes in communities in the Western Cape province cannot be studied in isolation but through the system they are embedded in. In this paper, a theoretical model to evaluate the syndemic of substance abuse and drug-related crimes within the Western Cape province of South Africa is constructed and explored. The dynamics of drug abuse and drug-related crimes within the Western Cape are simulated using STELLA software. The simulation results are...

  2. Facile synthesis of biphasic calcium phosphate microspheres with engineered surface topography for controlled delivery of drugs and proteins.

    Science.gov (United States)

    Zarkesh, Ibrahim; Ghanian, Mohammad Hossein; Azami, Mahmoud; Bagheri, Fatemeh; Baharvand, Hossein; Mohammadi, Javad; Eslaminejad, Mohamadreza Baghaban

    2017-09-01

    Biphasic calcium phosphate (BCP) microspheres are of great interest due to their high stability and osteoinductive properties at specific compositions. However, the need for optimal performance at a unique composition limits their flexibility for tuning drug release by modulation of bulk properties and presents the question of engineering surface topography as an alternative. It is necessary to have a facile method to control surface topography at a defined bulk composition. Here, we have produced BCP microspheres with different surface topographies that have the capability to be used as tunable drug release systems. We synthesized calcium deficient hydroxyapatite (CDHA) microparticles by precipitating calcium and phosphate ions onto ethylenediaminetetraacetic acid (EDTA) templates. The morphology and surface topography of CDHA microparticles were controlled using process parameters, which governed nucleation and growth. These parameters included template concentration, heat rate, and stirring speed. Under low heat rate and static conditions, we could obtain spherical microparticles with long and short nanosheets on their surfaces at low and high EDTA concentrations, respectively. These nanostructured microspheres were subsequently crystallized by thermal treatment to produce EDTA-free BCP microspheres with intact morphology. These biocompatible BCP microspheres were highly effective in loading and prolonged release of both small molecule [dexamethasone (Dex)] and protein [bovine serum albumin (BSA)] models. This strategy has enabled us to control the surface topography of BCP microspheres at defined compositions and holds tremendous promise for drug delivery and tissue engineering applications. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Completion of autobuilt protein models using a database of protein fragments

    International Nuclear Information System (INIS)

    Cowtan, Kevin

    2012-01-01

    Two developments in the process of automated protein model building in the Buccaneer software are described: the use of a database of protein fragments in improving the model completeness and the assembly of disconnected chain fragments into complete molecules. Two developments in the process of automated protein model building in the Buccaneer software are presented. A general-purpose library for protein fragments of arbitrary size is described, with a highly optimized search method allowing the use of a larger database than in previous work. The problem of assembling an autobuilt model into complete chains is discussed. This involves the assembly of disconnected chain fragments into complete molecules and the use of the database of protein fragments in improving the model completeness. Assembly of fragments into molecules is a standard step in existing model-building software, but the methods have not received detailed discussion in the literature

  4. 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.

  5. Five-Factor Model personality profiles of drug users.

    Science.gov (United States)

    Terracciano, Antonio; Löckenhoff, Corinna E; Crum, Rosa M; Bienvenu, O Joseph; Costa, Paul T

    2008-04-11

    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. 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. 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. 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.

  6. Discrete persistent-chain model for protein binding on DNA.

    Science.gov (United States)

    Lam, Pui-Man; Zhen, Yi

    2011-04-01

    We describe and solve a discrete persistent-chain model of protein binding on DNA, involving an extra σ(i) at a site i of the DNA. This variable takes the value 1 or 0, depending on whether or not the site is occupied by a protein. In addition, if the site is occupied by a protein, there is an extra energy cost ɛ. For a small force, we obtain analytic expressions for the force-extension curve and the fraction of bound protein on the DNA. For higher forces, the model can be solved numerically to obtain force-extension curves and the average fraction of bound proteins as a function of applied force. Our model can be used to analyze experimental force-extension curves of protein binding on DNA, and hence deduce the number of bound proteins in the case of nonspecific binding. ©2011 American Physical Society

  7. Modeling of corneal and retinal pharmacokinetics after periocular drug administration.

    Science.gov (United States)

    Amrite, Aniruddha C; Edelhauser, Henry F; Kompella, Uday B

    2008-01-01

    the SD rat corneas. Similar pharmacokinetics models explain drug delivery to the cornea in rat and rabbit animal models. Retinal pharmacokinetics after periocular drug administration can be explained with a four-compartment (periocular space, choroid-containing transfer compartment, retina, and distribution compartment) model with elimination from the periocular space, retina, and choroid compartment. Inclusion of a dissolution-release step before the drug is available for absorption or elimination better explains retinal t(max). Good fits were obtained in both the BN (r = 0.99) and SD (r = 0.99) rats for retinal celecoxib using the same model; however, the parameter estimates differed. Corneal and retinal pharmacokinetics of small lipophilic molecules after periocular administration can be described by compartment models. The modeling analysis shows that (1) leak-back from the site of administration most likely contributes to the apparent lack of an increase phase in corneal concentrations; (2) elimination via the conjunctival or periocular blood and lymphatic systems contributes significantly to drug clearance after periocular injection; (3) corneal pharmacokinetics of small lipophilic molecules can be explained by using similar models in rats and rabbits; and (4) although there are differences in some retinal pharmacokinetics parameters between the pigmented and nonpigmented rats, the physiological basis of these differences has yet to be ascertained.

  8. DNA replication proteins as potential targets for antimicrobials in drug-resistant bacterial pathogens.

    Science.gov (United States)

    van Eijk, Erika; Wittekoek, Bert; Kuijper, Ed J; Smits, Wiep Klaas

    2017-05-01

    With the impending crisis of antimicrobial resistance, there is an urgent need to develop novel antimicrobials to combat difficult infections and MDR pathogenic microorganisms. DNA replication is essential for cell viability and is therefore an attractive target for antimicrobials. Although several antimicrobials targeting DNA replication proteins have been developed to date, gyrase/topoisomerase inhibitors are the only class widely used in the clinic. Given the numerous essential proteins in the bacterial replisome that may serve as a potential target for inhibitors and the relative paucity of suitable compounds, it is evident that antimicrobials targeting the replisome are underdeveloped so far. In this review, we report on the diversity of antimicrobial compounds targeting DNA replication and highlight some of the challenges in developing new drugs that target this process. © The Author 2017. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy.

  9. Micro-Environmental Signature of The Interactions between Druggable Target Protein, Dipeptidyl Peptidase-IV, and Anti-Diabetic Drugs.

    Science.gov (United States)

    Chakraborty, Chiranjib; Mallick, Bidyut; Sharma, Ashish Ranjan; Sharma, Garima; Jagga, Supriya; Doss, C George Priya; Nam, Ju-Suk; Lee, Sang-Soo

    2017-01-01

    Druggability of a target protein depends on the interacting micro-environment between the target protein and drugs. Therefore, a precise knowledge of the interacting micro-environment between the target protein and drugs is requisite for drug discovery process. To understand such micro-environment, we performed in silico interaction analysis between a human target protein, Dipeptidyl Peptidase-IV (DPP-4), and three anti-diabetic drugs (saxagliptin, linagliptin and vildagliptin). During the theoretical and bioinformatics analysis of micro-environmental properties, we performed drug-likeness study, protein active site predictions, docking analysis and residual interactions with the protein-drug interface. Micro-environmental landscape properties were evaluated through various parameters such as binding energy, intermolecular energy, electrostatic energy, van der Waals'+H-bond+desolvo energy (E VHD ) and ligand efficiency (LE) using different in silico methods. For this study, we have used several servers and software, such as Molsoft prediction server, CASTp server, AutoDock software and LIGPLOT server. Through micro-environmental study, highest log P value was observed for linagliptin (1.07). Lowest binding energy was also observed for linagliptin with DPP-4 in the binding plot. We also identified the number of H-bonds and residues involved in the hydrophobic interactions between the DPP-4 and the anti-diabetic drugs. During interaction, two H-bonds and nine residues, two H-bonds and eleven residues as well as four H-bonds and nine residues were found between the saxagliptin, linagliptin as well as vildagliptin cases and DPP-4, respectively. Our in silico data obtained for drug-target interactions and micro-environmental signature demonstrates linagliptin as the most stable interacting drug among the tested anti-diabetic medicines.

  10. Improving Predictive Modeling in Pediatric Drug Development: Pharmacokinetics, Pharmacodynamics, and Mechanistic Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Slikker, William; Young, John F.; Corley, Rick A.; Dorman, David C.; Conolly, Rory B.; Knudsen, Thomas; Erstad, Brian L.; Luecke, Richard H.; Faustman, Elaine M.; Timchalk, Chuck; Mattison, Donald R.

    2005-07-26

    A workshop was conducted on November 18?19, 2004, to address the issue of improving predictive models for drug delivery to developing humans. Although considerable progress has been made for adult humans, large gaps remain for predicting pharmacokinetic/pharmacodynamic (PK/PD) outcome in children because most adult models have not been tested during development. The goals of the meeting included a description of when, during development, infants/children become adultlike in handling drugs. The issue of incorporating the most recent advances into the predictive models was also addressed: both the use of imaging approaches and genomic information were considered. Disease state, as exemplified by obesity, was addressed as a modifier of drug pharmacokinetics and pharmacodynamics during development. Issues addressed in this workshop should be considered in the development of new predictive and mechanistic models of drug kinetics and dynamics in the developing human.

  11. Crypt Organoid Culture as an in Vitro Model in Drug Metabolism and Cytotoxicity Studies.

    Science.gov (United States)

    Lu, Wenqi; Rettenmeier, Eva; Paszek, Miles; Yueh, Mei-Fei; Tukey, Robert H; Trottier, Jocelyn; Barbier, Olivier; Chen, Shujuan

    2017-07-01

    The gastrointestinal tract is enriched with xenobiotic processing proteins that play important roles in xenobiotic bioactivation, metabolism, and detoxification. The application of genetically modified mouse models has been instrumental in characterizing the function of xenobiotic processing genes (XPG) and their proteins in drug metabolism. Here, we report the utilization of three-dimensional crypt organoid cultures from these animal models to study intestinal drug metabolism and toxicity. With the successful culturing of crypt organoids, we profiled the abundance of Phase I and Phase II XPG expression, drug transporter gene expression, and xenobiotic nuclear receptor (XNR) gene expression. Functions of XNRs were examined by treating crypt cells with XNR prototypical agonists. Real-time quantitative polymerase chain reaction demonstrated that the representative downstream target genes were induced. These findings were validated from cultures developed from XNR-null mice. In crypt cultures isolated from Pxr -/- mice, pregnenolone 16 α -carbonitrile failed to induce Cyp3a11 gene expression; similarly, WY14643 failed to induce Cyp4a10 in the Pparα -/- crypts. Crypt cultures from control ( Ugt1 F/F ) and intestinal epithelial cell (IEC) specific Ugt1 null mice ( Ugt1 ΔIEC ) were treated with camptothecin-11, an anticancer prodrug with severe intestinal toxicity that originates from insufficient UGT1A1-dependent glucuronidation of its active metabolite SN-38. In the absence of Ugt1 gene expression, Ugt1 ΔIEC crypt cultures exhibit very limited production of SN-38 glucuronide, concordant with increased apoptosis in comparison with Ugt1 F/F crypt cultures. This study suggests crypt organoid cultures as an effective in vitro model for studying intestinal drug metabolism and toxicity. Copyright © 2017 by The American Society for Pharmacology and Experimental Therapeutics.

  12. Protein adsorption on nanoparticles: model development using computer simulation.

    Science.gov (United States)

    Shao, Qing; Hall, Carol K

    2016-10-19

    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.

  13. Analysis of damaged DNA / proteins interactions: Methodological optimizations and applications to DNA lesions induced by platinum anticancer drugs

    International Nuclear Information System (INIS)

    Bounaix Morand du Puch, Ch

    2010-10-01

    DNA lesions contribute to the alteration of DNA structure, thereby inhibiting essential cellular processes. Such alterations may be beneficial for chemotherapies, for example in the case of platinum anticancer agents. They generate bulky adducts that, if not repaired, ultimately cause apoptosis. A better understanding of the biological response to such molecules can be obtained through the study of proteins that directly interact with the damages. These proteins constitute the DNA lesions interactome. This thesis presents the development of tools aiming at increasing the list of platinum adduct-associated proteins. Firstly, we designed a ligand fishing system made of damaged plasmids immobilized onto magnetic beads. Three platinum drugs were selected for our study: cisplatin, oxali-platin and satra-platin. Following exposure of the trap to nuclear extracts from HeLa cancer cells and identification of retained proteins by proteomics, we obtained already known candidates (HMGB1, hUBF, FACT complex) but also 29 new members of the platinated-DNA interactome. Among them, we noted the presence of PNUTS, TOX4 and WDR82, which associate to form the recently-discovered PTW/PP complex. Their capture was then confirmed with a second model, namely breast cancer cell line MDA MB 231, and the biological consequences of such an interaction now need to be elucidated. Secondly, we adapted a SPRi bio-chip to the study of platinum-damaged DNA/proteins interactions. Affinity of HMGB1 and newly characterized TOX4 for adducts generated by our three platinum drugs could be validated thanks to the bio-chip. Finally, we used our tools, as well as analytical chemistry and biochemistry methods, to evaluate the role of DDB2 (a factor involved in the recognition of UV-induced lesions) in the repair of cisplatin adducts. Our experiments using MDA MB 231 cells differentially expressing DDB2 showed that this protein is not responsible for the repair of platinum damages. Instead, it appears to act

  14. 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.

  15. Modeling Human Nonalcoholic Steatohepatitis-Associated Changes in Drug Transporter Expression Using Experimental Rodent Models

    OpenAIRE

    Canet, Mark J.; Hardwick, Rhiannon N.; Lake, April D.; Dzierlenga, Anika L.; Clarke, John D.; Cherrington, Nathan J.

    2014-01-01

    Nonalcoholic fatty liver disease is a prevalent form of chronic liver disease that can progress to the more advanced stage of nonalcoholic steatohepatitis (NASH). NASH has been shown to alter drug transporter regulation and may have implications in the development of adverse drug reactions. Several experimental rodent models have been proposed for the study of NASH, but no single model fully recapitulates all aspects of the human disease. The purpose of the current study was to determine whic...

  16. 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.

  17. Structural properties governing drug-plasma protein binding determined by high-performance liquid chromatography method.

    Science.gov (United States)

    Kamble, Sharad; Loadman, Paul; Abraham, Michael H; Liu, Xiangli

    2018-02-05

    The high-performance liquid chromatography (HPLC) method employing stationary phases immobilized with plasma proteins was used for this study to investigate the structural properties governing drug-plasma protein binding. A set of 65 compounds with a broad range of structural diversity (in terms of volume, hydrogen-bonding, polarity and electrostatic force) were selected for this purpose. The Abraham linear free energy relationship (LFER) analyses of the retention factors on the immobilized HSA (human serum albumin) and AGP (α 1 -acid glycoprotein) stationary phases showed that McGowan's characteristic molecular volume (V), dipolarity/polarizability (S) and hydrogen bond basicity (B) are the three significant molecular descriptors of solutes determining the interaction with immobilized plasma proteins, whereas excess molar refraction (E) is less important and hydrogen bond acidity (A) is not of statistical significance in both systems, for electrically neutral compounds. It was shown that ionised acids, as carboxylate anions, bind very strongly to the immobilized HSA stationary phase and that ionised bases, as cations bind strongly to the AGP stationary phase. This is the first time that the effect of ionised species on plasma protein binding has been determined quantitatively; the increased binding of acids to HSA is due almost entirely to acids in their ionised form. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. Oral sensitization to food proteins: A Brown Norway rat model

    NARCIS (Netherlands)

    Knippels, L.M.J.; Penninks, A.H.; Spanhaak, S.; Houben, G.F.

    1998-01-01

    Background: Although several in vivo antigenicity assays using parenteral immunization are operational, no adequate enteral sensitization models are available to study food allergy and allergenicity of food proteins. Objective: This paper describes the development of an enteral model for food

  19. Channel Protein-Containing Liposomes as Delivery Vehicles for the Controlled Release of Drugs-Optimization of the Lipid Composition

    NARCIS (Netherlands)

    Šmisterová, J.; Deemter, M. van; Schaaf, G. van der; Meijberg, W.; Robillard, G.

    2005-01-01

    In the design of liposomal drug formulations containing a controllable channel protein (MscL), the lipid composition is dictated in part by this membrane protein. This work addresses the question whether therapeutically optimal lipid compositions (phospholipid with high Tm/cholesterol/PEG) are

  20. 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

  1. 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

  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. Computational models for predicting drug responses in cancer research.

    Science.gov (United States)

    Azuaje, Francisco

    2017-09-01

    The computational prediction of drug responses based on the analysis of multiple types of genome-wide molecular data is vital for accomplishing the promise of precision medicine in oncology. This will benefit cancer patients by matching their tumor characteristics to the most effective therapy available. As larger and more diverse layers of patient-related data become available, further demands for new bioinformatics approaches and expertise will arise. This article reviews key strategies, resources and techniques for the prediction of drug sensitivity in cell lines and patient-derived samples. It discusses major advances and challenges associated with the different model development steps. This review highlights major trends in this area, and will assist researchers in the assessment of recent progress and in the selection of approaches to emerging applications in oncology. © The Author 2016. Published by Oxford University Press.

  4. 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.

  5. Enantiomeric Resolution of Drugs and Metabolites in Polysaccharide- and Protein-Based Chiral Stationary Phases

    Directory of Open Access Journals (Sweden)

    Bonato Pierina S.

    2002-01-01

    Full Text Available Several chiral stationary phases based on polysaccharide derivatives and proteins were evaluated for the resolution of some chiral drugs and their metabolites. The polysaccharide-based stationary phases CHIRALCEL OD-H, CHIRALCEL OB-H, CHIRALCEL OJ, CHIRALPAK AD and CHIRALPAK AS were evaluated under normal phase conditions, using hexane:2-propanol or hexane:ethanol as mobile phase. Diethylamine and trifluoracetic acid were also added to improve peak shape. The CHIRALCEL OJ-R, CHIRALCEL OD-R and CHIRALCEL OD-H columns were evaluated under reversed-phase conditions, using acetonitrile:H2O or acetonitrile:NaClO4 solution. The protein- based stationary phases, CHIRAL AGP and ULTRON ES-OVM columns were used with mobile phases consisting of a buffer solution supplemented with an organic modifier. Among the polysaccharide-based stationary phases, CHIRALPAK AD provided better resolution for almost all drugs and metabolites studied. The ULTRON ES-OVM column was particularly suitable for the resolution of the four enantiomers of thioridazine-2-sulfoxide.

  6. Integration of Drug, Protein, and Gene Delivery Systems with Regenerative Medicine

    Science.gov (United States)

    Lorden, Elizabeth R.; Levinson, Howard M.; Leong, Kam W.

    2013-01-01

    Regenerative medicine has the potential to drastically change the field of health care from reactive to preventative and restorative. Exciting advances in stem cell biology and cellular reprogramming have fueled the progress of this field. Biochemical cues in the form of small molecule drugs, growth factors, zinc finger protein transcription factors and nucleases, transcription activator-like effector nucleases, monoclonal antibodies, plasmid DNA, aptamers, or RNA interference agents can play an important role to influence stem cell differentiation and the outcome of tissue regeneration. Many of these biochemical factors are fragile and must act intracellularly at the molecular level. They require an effective delivery system, which can take the form of a scaffold (e.g. hydrogels and electrospun fibers), carrier (viral and nonviral), nano- and micro-particle, or genetically modified cell. In this review, we will discuss the history and current technologies of drug, protein and gene delivery in the context of regenerative medicine. Next we will present case examples of how delivery technologies are being applied to promote angiogenesis in non-healing wounds or prevent angiogenesis in age related macular degeneration. Finally, we will conclude with a brief discussion of the regulatory pathway from bench-to-bedside for the clinical translation of these novel therapeutics. PMID:25787742

  7. Denatured Whey Protein Powder as a New Matrix Excipient: Design and Evaluation of Mucoadhesive Tablets for Sustained Drug Release Applications.

    Science.gov (United States)

    Hsein, Hassana; Garrait, Ghislain; Tamani, Fahima; Beyssac, Eric; Hoffart, Valérie

    2017-02-01

    In earlier study, we proposed denatured whey protein (DWP) powder obtained by atomization as a new excipient to promote oral drug delivery. In this work, we evaluate the possibility to formulate tablets based on DWP powders and to characterize their role as a matrix mucoadhesive excipient. Tablets containing increased amount of DWP (10 to 30%) were produced by direct compression after mixing with theophylline, microcrystalline cellulose, Aerosil® and magnesium stearate. Dissolution behaviors of obtained tablets were evaluated in different USP buffers (pH 1.2, 4.5 and 6.8) and in simulated gastric and intestinal fluids and mechanisms analyzed by multiple mathematical models. Swelling, erosion and mucoadhesion were also evaluated. Finally, release and absorption were studied in the artificial digestive system (TIM 1). Tablets based on DWP and containing 300 mg of theophylline were obtained by direct compression. These tablets exhibited controlled release driven by diffusion starting from 15% DWP content whatever the pH studied. They also showed a great extent of swelling and water uptake while matrix weight loss was limited. Addition of enzymes accelerated drug release which became governed by erosion according to Peppas model. The present study shows that DWP powders can be successfully used as a pharmaceutical excipient, and in particular as a matrix mucoadhesive controlled release tablets.

  8. Age exacerbates abnormal protein expression in a mouse model of Down syndrome.

    Science.gov (United States)

    Ahmed, Md Mahiuddin; Block, Aaron; Tong, Suhong; Davisson, Muriel T; Gardiner, Katheleen J

    2017-09-01

    The Ts65Dn is a popular mouse model of Down syndrome (DS). It displays DS-relevant features of learning/memory deficits and age-related loss of functional markers in basal forebrain cholinergic neurons. Here we describe protein expression abnormalities in brain regions of 12-month-old male Ts65Dn mice. We show that the magnitudes of abnormalities of human chromosome 21 and non-human chromosome 21 orthologous proteins are greater at 12 months than at ∼6 months. Age-related exacerbations involve the number of components affected in the mechanistic target of rapamycin pathway, the levels of components of the mitogen-activated protein kinase pathway, and proteins associated with Alzheimer's disease. Among brain regions, the number of abnormalities in cerebellum decreased while the number in cortex greatly increased with age. The Ts65Dn is being used in preclinical evaluations of drugs for cognition in DS. Most commonly, drug evaluations are tested in ∼4- to 6-month-old mice. Data on age-related changes in magnitude and specificity of protein perturbations can be used to understand the molecular basis of changes in cognitive ability and to predict potential age-related specificities in drug efficacies. Copyright © 2017 Elsevier Inc. All rights reserved.

  9. 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.

  10. 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

  11. Predicting nucleic acid binding interfaces from structural models of proteins.

    Science.gov (United States)

    Dror, Iris; Shazman, Shula; Mukherjee, Srayanta; Zhang, Yang; Glaser, Fabian; Mandel-Gutfreund, Yael

    2012-02-01

    The function of DNA- and RNA-binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However, the main pitfall of various structure-based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high-resolution three-dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I-TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high-resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I-TASSER produces high-quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared with patches extracted from independent models. Overall, these results suggest that combining information from a collection of low-resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure. Copyright © 2011 Wiley Periodicals, Inc.

  12. Acid-denatured Green Fluorescent Protein (GFP) as model substrate to study the chaperone activity of protein disulfide isomerase.

    Science.gov (United States)

    Mares, Rosa E; Meléndez-López, Samuel G; Ramos, Marco A

    2011-01-01

    Green fluorescent protein (GFP) has been widely used in several molecular and cellular biology applications, since it is remarkably stable in vitro and in vivo. Interestingly, native GFP is resistant to the most common chemical denaturants; however, a low fluorescence signal has been observed after acid-induced denaturation. Furthermore, this acid-denatured GFP has been used as substrate in studies of the folding activity of some bacterial chaperones and other chaperone-like molecules. Protein disulfide isomerase enzymes, a family of eukaryotic oxidoreductases that catalyze the oxidation and isomerization of disulfide bonds in nascent polypeptides, play a key role in protein folding and it could display chaperone activity. However, contrasting results have been reported using different proteins as model substrates. Here, we report the further application of GFP as a model substrate to study the chaperone activity of protein disulfide isomerase (PDI) enzymes. Since refolding of acid-denatured GFP can be easily and directly monitored, a simple micro-assay was used to study the effect of the molecular participants in protein refolding assisted by PDI. Additionally, the effect of a well-known inhibitor of PDI chaperone activity was also analyzed. Because of the diversity their functional activities, PDI enzymes are potentially interesting drug targets. Since PDI may be implicated in the protection of cells against ER stress, including cancer cells, inhibitors of PDI might be able to enhance the efficacy of cancer chemotherapy; furthermore, it has been demonstrated that blocking the reductive cleavage of disulfide bonds of proteins associated with the cell surface markedly reduces the infectivity of the human immunodeficiency virus. Although several high-throughput screening (HTS) assays to test PDI reductase activity have been described, we report here a novel and simple micro-assay to test the chaperone activity of PDI enzymes, which is amenable for HTS of PDI

  13. 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.

  14. Validation of a Spectral Method for Quantitative Measurement of Color in Protein Drug Solutions.

    Science.gov (United States)

    Yin, Jian; Swartz, Trevor E; Zhang, Jian; Patapoff, Thomas W; Chen, Bartolo; Marhoul, Joseph; Shih, Norman; Kabakoff, Bruce; Rahimi, Kimia

    2016-01-01

    A quantitative spectral method has been developed to precisely measure the color of protein solutions. In this method, a spectrophotometer is utilized for capturing the visible absorption spectrum of a protein solution, which can then be converted to color values (L*a*b*) that represent human perception of color in a quantitative three-dimensional space. These quantitative values (L*a*b*) allow for calculating the best match of a sample's color to a European Pharmacopoeia reference color solution. In order to qualify this instrument and assay for use in clinical quality control, a technical assessment was conducted to evaluate the assay suitability and precision. Setting acceptance criteria for this study required development and implementation of a unique statistical method for assessing precision in 3-dimensional space. Different instruments, cuvettes, protein solutions, and analysts were compared in this study. The instrument accuracy, repeatability, and assay precision were determined. The instrument and assay are found suitable for use in assessing color of drug substances and drug products and is comparable to the current European Pharmacopoeia visual assessment method. In the biotechnology industry, a visual assessment is the most commonly used method for color characterization, batch release, and stability testing of liquid protein drug solutions. Using this method, an analyst visually determines the color of the sample by choosing the closest match to a standard color series. This visual method can be subjective because it requires an analyst to make a judgment of the best match of color of the sample to the standard color series, and it does not capture data on hue and chroma that would allow for improved product characterization and the ability to detect subtle differences between samples. To overcome these challenges, we developed a quantitative spectral method for color determination that greatly reduces the variability in measuring color and allows

  15. Effect of ingested lipids on drug dissolution and release with concurrent digestion: a modeling approach

    Science.gov (United States)

    Buyukozturk, Fulden; Di Maio, Selena; Budil, David E.; Carrier, Rebecca L.

    2014-01-01

    Purpose To mechanistically study and model the effect of lipids, either from food or self-emulsifying drug delivery systems (SEDDS), on drug transport in the intestinal lumen. Methods Simultaneous lipid digestion, dissolution/release, and drug partitioning were experimentally studied and modeled for two dosing scenarios: solid drug with a food-associated lipid (soybean oil) and drug solubilized in a model SEDDS (soybean oil and Tween 80 at 1:1 ratio). Rate constants for digestion, permeability of emulsion droplets, and partition coefficients in micellar and oil phases were measured, and used to numerically solve the developed model. Results Strong influence of lipid digestion on drug release from SEDDS and solid drug dissolution into food-associated lipid emulsion were observed and predicted by the developed model. 90 minutes after introduction of SEDDS, there was 9% and 70% drug release in the absence and presence of digestion, respectively. However, overall drug dissolution in the presence of food-associated lipids occurred over a longer period than without digestion. Conclusion A systems-based mechanistic model incorporating simultaneous dynamic processes occurring upon dosing of drug with lipids enabled prediction of aqueous drug concentration profile. This model, once incorporated with a pharmacokinetic model considering processes of drug absorption and drug lymphatic transport in the presence of lipids, could be highly useful for quantitative prediction of impact of lipids on bioavailability of drugs. PMID:24234918

  16. Computational protein structure modeling and analysis of UV-B stress protein in Synechocystis PCC 6803.

    Science.gov (United States)

    Rahman, Md Akhlaqur; Chaturvedi, Navaneet; Sinha, Sukrat; Pandey, Paras Nath; Gupta, Dwijendra Kumar; Sundaram, Shanthy; Tripathi, Ashutosh

    2013-01-01

    This study focuses on Ultra Violet stress (UVS) gene product which is a UV stress induced protein from cyanobacteria, Synechocystis PCC 6803. Three dimensional structural modeling of target UVS protein was carried out by homology modeling method. 3F2I pdb from Nostoc sp. PCC 7120 was selected as a suitable template protein structure. Ultimately, the detection of active binding regions was carried out for characterization of functional sites in modeled UV-B stress protein. The top five probable ligand binding sites were predicted and the common binding residues between target and template protein was analyzed. It has been validated for the first time that modeled UVS protein structure from Synechocystis PCC 6803 was structurally and functionally similar to well characterized UVS protein of another cyanobacterial species, Nostoc sp PCC 7120 because of having same structural motif and fold with similar protein topology and function. Investigations revealed that UVS protein from Synechocystis sp. might play significant role during ultraviolet resistance. Thus, it could be a potential biological source for remediation for UV induced stress.

  17. 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.

  18. 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.

  19. Generation of pharmacophores and classification of drugs using protein-ligand complexes

    Directory of Open Access Journals (Sweden)

    Eliana Velasquez

    2014-04-01

    Full Text Available Pharmacophore identification is a veryimportant step in de novo design, leadoptimization, chemogenomics, and virtualscreening of drugs. Unfortunately,the high cost of comercial software forpharmacophore detection is a commonlimiting factor for researchers with limitedfunding. This paper presents a set offreely available perl routines that weredesigned to help in the process of 3Dpharmacophore identification and QSARstudies. These routines also allowed theclassification of ligands based on theirtridimensional similarity and bindingmechanism. The family of phosphodiesterasesand their inhibitors were used astest model.

  20. Computational analysis of the 3-D structure of human GPR87 protein: implications for structure-based drug design.

    Science.gov (United States)

    Rani, Mukta; Nischal, Anuradha; Sahoo, Ganesh Chandra; Khattri, Sanjay

    2013-01-01

    The G-protein coupled receptor 87 (GPR87) is a recently discovered orphan GPCR which means that the search of their endogenous ligands has been a novel challenge. GPR87 has been shown to be overexpressed in squamous cell carcinomas (SCCs) or adenocarcinomas in lungs and bladder. The 3D structure of GPR87 was here modeled using two templates (2VT4 and 2ZIY) by a threading method. Functional assignment of GPR87 by SVM revealed that along with transporter activity, various novel functions were predicted. The 3D structure was further validated by comparison with structural features of the templates through Verify-3D, ProSA and ERRAT for determining correct stereochemical parameters. The resulting model was evaluated by Ramachandran plot and good 3D structure compatibility was evidenced by DOPE score. Molecular dynamics simulation and solvation of protein were studied through explicit spherical boundaries with a harmonic restraint membrane water system. A DRY-motif (Asp-Arg-Tyr sequence) was found at the end of transmembrane helix3, where GPCR binds and thus activation of signals is transduced. In a search for better inhibitors of GPR87, in silico modification of some substrate ligands was carried out to form polar interactions with Arg115 and Lys296. Thus, this study provides early insights into the structure of a major drug target for SCCs.

  1. Parmodel: a web server for automated comparative modeling of proteins.

    Science.gov (United States)

    Uchôa, Hugo Brandão; Jorge, Guilherme Eberhart; Freitas Da Silveira, Nelson José; Camera, João Carlos; Canduri, Fernanda; De Azevedo, Walter Filgueira

    2004-12-24

    Parmodel is a web server for automated comparative modeling and evaluation of protein structures. The aim of this tool is to help inexperienced users to perform modeling, assessment, visualization, and optimization of protein models as well as crystallographers to evaluate structures solved experimentally. It is subdivided in four modules: Parmodel Modeling, Parmodel Assessment, Parmodel Visualization, and Parmodel Optimization. The main module is the Parmodel Modeling that allows the building of several models for a same protein in a reduced time, through the distribution of modeling processes on a Beowulf cluster. Parmodel automates and integrates the main softwares used in comparative modeling as MODELLER, Whatcheck, Procheck, Raster3D, Molscript, and Gromacs. This web server is freely accessible at .

  2. Distribution patterns of small-molecule ligands in the protein universe and implications for origin of life and drug discovery.

    Science.gov (United States)

    Ji, Hong-Fang; Kong, De-Xin; Shen, Liang; Chen, Ling-Ling; Ma, Bin-Guang; Zhang, Hong-Yu

    2007-01-01

    Extant life depends greatly on the binding of small molecules (such as ligands) with macromolecules (such as proteins), and one ligand can bind multiple proteins. However, little is known about the global patterns of ligand-protein mapping. By examining 2,186 well-defined small-molecule ligands and thousands of protein domains derived from a database of druggable binding sites, we show that a few ligands bind tens of protein domains or folds, whereas most ligands bind only one, which indicates that ligand-protein mapping follows a power law. Through assigning the protein-binding orders (early or late) for bio-ligands, we demonstrate that the preferential attachment principle still holds for the power-law relation between ligands and proteins. We also found that polar molecular surface area, H-bond acceptor counts, H-bond donor counts and partition coefficient are potential factors to discriminate ligands from ordinary molecules and to differentiate super ligands (shared by three or more folds) from others. These findings have significant implications for evolution and drug discovery. First, the chronology of ligand-protein binding can be inferred by the power-law feature of ligand-protein mapping. Some nucleotide-containing ligands, such as ATP, ADP, GDP, NAD, FAD, dihydro-nicotinamide-adenine-dinucleotide phosphate (NDP), nicotinamide-adenine-dinucleotide phosphate (NAP), flavin mononucleotide (FMN) and AMP, are found to be the earliest cofactors bound to proteins, agreeing with the current understanding of evolutionary history. Second, the finding that about 30% of ligands are shared by two or more domains will help with drug discovery, such as in finding new functions from old drugs, developing promiscuous drugs and depending more on natural products.

  3. Developing algorithms for predicting protein-protein interactions of homology modeled proteins.

    Energy Technology Data Exchange (ETDEWEB)

    Martin, Shawn Bryan; Sale, Kenneth L.; Faulon, Jean-Loup Michel; Roe, Diana C.

    2006-01-01

    The goal of this project was to examine the protein-protein docking problem, especially as it relates to homology-based structures, identify the key bottlenecks in current software tools, and evaluate and prototype new algorithms that may be developed to improve these bottlenecks. This report describes the current challenges in the protein-protein docking problem: correctly predicting the binding site for the protein-protein interaction and correctly placing the sidechains. Two different and complementary approaches are taken that can help with the protein-protein docking problem. The first approach is to predict interaction sites prior to docking, and uses bioinformatics studies of protein-protein interactions to predict theses interaction site. The second approach is to improve validation of predicted complexes after docking, and uses an improved scoring function for evaluating proposed docked poses, incorporating a solvation term. This scoring function demonstrates significant improvement over current state-of-the art functions. Initial studies on both these approaches are promising, and argue for full development of these algorithms.

  4. Novel drugs and vaccines based on the structure and function of HIV pathogenic proteins including Nef.

    Science.gov (United States)

    Azad, Ahmed A

    2005-11-01

    Evidence is presented to suggest that HIV-1 accessory protein Nef could be involved in AIDS pathogenesis. When present in extracellular medium, Nef causes the death of a wide variety of cells in vitro and may therefore be responsible for the depletion of bystander cells in lymphoid tissues during HIV infection. When present inside the cell, Nef could prevent the death of infected cells and thereby contribute to increased viral load. Intracellular Nef does this by preventing apoptosis of infected cells by either inhibiting proteins involved in apoptosis or preventing the infected cells from being recognized by CTLs. Neutralization of extracellular Nef could prevent the death of uninfected immune cells and thereby the destruction of the immune system. Neutralization of intracellular Nef could hasten the death of infected cells and help reduce the viral load. Nef is therefore a very important molecular target for developing therapeutics that slow progression to AIDS. The N-terminal region of Nef and the naturally occurring bee venom mellitin have very similar primary and tertiary structures, and they both act by destroying membranes. Chemical analogs of a mellitin inhibitor prevent Nef-mediated cell death and inhibit the interaction of Nef with cellular proteins involved in apoptosis. Naturally occurring bee propolis also contains substances that prevent Nef-mediated cell lysis and increases proliferation of CD4 cells in HIV-infected cultures. These chemical compounds and natural products are water soluble and nontoxic and are therefore potentially very useful candidate drugs.

  5. Discovery of serum protein biomarkers in drug-free patients with major depressive disorder.

    Science.gov (United States)

    Lee, Min Young; Kim, Eun Young; Kim, Se Hyun; Cho, Kyung-Cho; Ha, Kyooseob; Kim, Kwang Pyo; Ahn, Yong Min

    2016-08-01

    Major depressive disorder (MDD) is a systemic and multifactorial disorder involving complex interactions between genetic predisposition and disturbances of various molecular pathways. Its underlying molecular pathophysiology remains unclear, and no valid and objective diagnostic tools for the condition are available. We performed large-scale proteomic profiling to identify novel peripheral biomarkers implicated in the pathophysiology of MDD in 25 drug-free female MDD patients and 25 healthy controls. First, quantitative serum proteome profiles were obtained and analyzed by liquid chromatography-tandem mass spectrometry using serum samples from 10 MDD patients and 10 healthy controls. Next, candidate biomarker sets, including differentially expressed proteins from the profiling experiment and those identified in the literature, were verified using multiple-reaction monitoring in 25 patients and 25 healthy controls. The final panel of potential biomarkers was selected using multiparametric statistical analysis. We identified a serum biomarker panel consisting of six proteins: apolipoprotein D, apolipoprotein B, vitamin D-binding protein, ceruloplasmin, hornerin, and profilin 1, which could be used to distinguish MDD patients from controls with 68% diagnostic accuracy. Our results suggest that modulation of the immune and inflammatory systems and lipid metabolism are involved in the pathophysiology of MDD. Our findings of functional proteomic changes in the peripheral blood of patients with MDD further clarify the molecular biological pathway underlying depression. Further studies using larger, independent cohorts are needed to verify the role of these candidate biomarkers for the diagnosis of MDD. Copyright © 2016 Elsevier Inc. All rights reserved.

  6. Corn Storage Protein - A Molecular Genetic Model

    Energy Technology Data Exchange (ETDEWEB)

    Messing, Joachim [Rutgers Univ., Piscataway, NJ (United States)

    2013-05-31

    Corn is the highest yielding crop on earth and probably the most valuable agricultural product of the United States. Because it converts sun energy through photosynthesis into starch and proteins, we addressed energy savings by focusing on protein quality. People and animals require essential amino acids derived from the digestion of proteins. If proteins are relatively low in certain essential amino acids, the crop becomes nutritionally defective and has to be supplemented. Such deficiency affects meat and fish production and countries where corn is a staple. Because corn seed proteins have relatively low levels of lysine and methionine, a diet has to be supplemented with soybeans for the missing lysine and with chemically synthesized methionine. We therefore have studied genes expressed during maize seed development and their chromosomal organization. A critical technical requirement for the understanding of the molecular structure of genes and their positional information was DNA sequencing. Because of the length of sequences, DNA sequencing methods themselves were insufficient for this type of analysis. We therefore developed the so-called “DNA shotgun sequencing” strategy, where overlapping DNA fragments were sequenced in parallel and used to reconstruct large DNA molecules via overlaps. Our publications became the most frequently cited ones during the decade of 1981-1990 and former Associate Director of Science for the Office of Basic Energy Sciences Patricia M. Dehmer presented our work as one of the great successes of this program. A major component of the sequencing strategy was the development of bacterial strains and vectors, which were also used to develop the first biotechnology crops. These crops possessed new traits thanks to the expression of foreign genes in plants. To enable such expression, chimeric genes had to be constructed using our materials and methods by the industry. Because we made our materials and methods freely available to

  7. 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…

  8. Using Peptide Aptamer Targeted Polymers as a Model Nanomedicine for Investigating Drug Distribution in Cancer Nanotheranostics.

    Science.gov (United States)

    Zhao, Yongmei; Houston, Zachary H; Simpson, Joshua D; Chen, Liyu; Fletcher, Nicholas L; Fuchs, Adrian V; Blakey, Idriss; Thurecht, Kristofer J

    2017-10-02

    Theranostics is a strategy that combines multiple functions such as targeting, stimulus-responsive drug release, and diagnostic imaging into a single platform, often with the aim of developing personalized medicine.1,2 Based on this concept, several well-established hyperbranched polymeric theranostic nanoparticles were synthesized and characterized as model nanomedicines to investigate how their properties affect the distribution of loaded drugs at both the cell and whole animal levels. An 8-mer peptide aptamer was covalently bound to the periphery of the nanoparticles to achieve both targeting and potential chemosensitization functionality against heat shock protein 70 (Hsp70). Doxorubicin was also bound to the polymeric carrier as a model chemotherapeutic drug through a degradable hydrazone bond, enabling pH-controlled release under the mildly acid conditions that are found in the intracellular compartments of tumor cells. In order to track the nanoparticles, cyanine-5 (Cy5) was incorporated into the polymer as an optical imaging agent. In vitro cellular uptake was assessed for the hyperbranched polymer containing both doxorubicin (DOX) and Hsp70 targeted peptide aptamer in live MDA-MB-468 cells, and was found to be greater than that of either the untargeted, DOX-loaded polymer or polymer alone due to the specific affinity of the peptide aptamer for the breast cancer cells. This was also validated in vivo with the targeted polymers showing much higher accumulation within the tumor 48 h postinjection than the untargeted analogue. More detailed assessment of the nanomedicine distribution was achieved by directly following the polymeric carrier and the doxorubicin at both the in vitro cellular level via compartmental analysis of confocal images of live cells and in whole tumors ex vivo using confocal imaging to visualize the distribution of the drug in tumor tissue as a function of distance from blood vessels. Our results indicate that this polymeric carrier shows

  9. Modeling structure of G protein-coupled receptors in huan genome

    KAUST Repository

    Zhang, Yang

    2016-01-26

    G protein-coupled receptors (or GPCRs) are integral transmembrane proteins responsible to various cellular signal transductions. Human GPCR proteins are encoded by 5% of human genes but account for the targets of 40% of the FDA approved drugs. Due to difficulties in crystallization, experimental structure determination remains extremely difficult for human GPCRs, which have been a major barrier in modern structure-based drug discovery. We proposed a new hybrid protocol, GPCR-I-TASSER, to construct GPCR structure models by integrating experimental mutagenesis data with ab initio transmembrane-helix assembly simulations, assisted by the predicted transmembrane-helix interaction networks. The method was tested in recent community-wide GPCRDock experiments and constructed models with a root mean square deviation 1.26 Å for Dopamine-3 and 2.08 Å for Chemokine-4 receptors in the transmembrane domain regions, which were significantly closer to the native than the best templates available in the PDB. GPCR-I-TASSER has been applied to model all 1,026 putative GPCRs in the human genome, where 923 are found to have correct folds based on the confidence score analysis and mutagenesis data comparison. The successfully modeled GPCRs contain many pharmaceutically important families that do not have previously solved structures, including Trace amine, Prostanoids, Releasing hormones, Melanocortins, Vasopressin and Neuropeptide Y receptors. All the human GPCR models have been made publicly available through the GPCR-HGmod database at http://zhanglab.ccmb.med.umich.edu/GPCR-HGmod/ The results demonstrate new progress on genome-wide structure modeling of transmembrane proteins which should bring useful impact on the effort of GPCR-targeted drug discovery.

  10. A theory of drug tolerance and dependence II: the mathematical model.

    Science.gov (United States)

    Peper, Abraham

    2004-08-21

    The preceding paper presented a model of drug tolerance and dependence. The model assumes the development of tolerance to a repeatedly administered drug to be the result of a regulated adaptive process. The oral detection and analysis of exogenous substances is proposed to be the primary stimulus for the mechanism of drug tolerance. Anticipation and environmental cues are in the model considered secondary stimuli, becoming primary in dependence and addiction or when the drug administration bypasses the natural-oral-route, as is the case when drugs are administered intravenously. The model considers adaptation to the effect of a drug and adaptation to the interval between drug taking autonomous tolerance processes. Simulations with the mathematical model demonstrate the model's behaviour to be consistent with important characteristics of the development of tolerance to repeatedly administered drugs: the gradual decrease in drug effect when tolerance develops, the high sensitivity to small changes in drug dose, the rebound phenomenon and the large reactions following withdrawal in dependence. The present paper discusses the mathematical model in terms of its design. The model is a nonlinear, learning feedback system, fully satisfying control theoretical principles. It accepts any form of the stimulus-the drug intake-and describes how the physiological processes involved affect the distribution of the drug through the body and the stability of the regulation loop. The mathematical model verifies the proposed theory and provides a basis for the implementation of mathematical models of specific physiological processes.

  11. DFT application for chlorin derivatives photosensitizer drugs modeling

    Science.gov (United States)

    Machado, Neila; Carvalho, B. G.; Téllez Soto, C. A.; Martin, A. A.; Favero, P. P.

    2018-04-01

    Photodynamic therapy is an alternative form of cancer treatment that meets the desire for a less aggressive approach to the body. It is based on the interaction between a photosensitizer, activating light, and molecular oxygen. This interaction results in a cascade of reactions that leads to localized cell death. Many studies have been conducted to discover an ideal photosensitizer, which aggregates all the desirable characteristics of a potent cell killer and generates minimal side effects. Using Density Functional Theory (DFT) implemented in the program Vienna Ab-initio Simulation Package, new chlorin derivatives with different functional groups were simulated to evaluate the different absorption wavelengths to permit resonant absorption with the incident laser. Gaussian 09 program was used to determine vibrational wave numbers and Natural Bond Orbitals. The chosen drug with the best characteristics for the photosensitizer was a modified model of the original chlorin, which was called as Thiol chlorin. According to our calculations it is stable and is 19.6% more efficient at optical absorption in 708 nm in comparison to the conventional chlorin e6. Vibrational modes, optical and electronic properties were predicted. In conclusion, this study is an attempt to improve the development of new photosensitizer drugs through computational methods that save time and contribute to decrease the numbers of animals for model application.

  12. A Systems Dynamic Model for Drug Abuse and Drug-Related Crime in the Western Cape Province of South Africa

    Directory of Open Access Journals (Sweden)

    Farai Nyabadza

    2017-01-01

    Full Text Available The complex problem of drug abuse and drug-related crimes in communities in the Western Cape province cannot be studied in isolation but through the system they are embedded in. In this paper, a theoretical model to evaluate the syndemic of substance abuse and drug-related crimes within the Western Cape province of South Africa is constructed and explored. The dynamics of drug abuse and drug-related crimes within the Western Cape are simulated using STELLA software. The simulation results are consistent with the data from SACENDU and CrimeStats SA, highlighting the usefulness of such a model in designing and planning interventions to combat substance abuse and its related problems.

  13. Glucuronidation as a mechanism of intrinsic drug resistance in colon cancer cells: contribution of drug transport proteins

    NARCIS (Netherlands)

    Cummings, Jeffrey; Zelcer, Noam; Allen, John D.; Yao, Denggao; Boyd, Gary; Maliepaard, Mark; Friedberg, Thomas H.; Smyth, John F.; Jodrell, Duncan I.

    2004-01-01

    We have recently shown that drug conjugation catalysed by UDP-glucuronosyltransferases (UGTs) functions as an intrinsic mechanism of resistance to the topoisomerase I inhibitors 7-ethyl-10-hydroxycamptothecin and NU/ICRF 505 in human colon cancer cells and now report on the role of drug transport in

  14. Modeling protein network evolution under genome duplication and domain shuffling

    Directory of Open Access Journals (Sweden)

    Isambert Hervé

    2007-11-01

    Full Text Available Abstract Background Successive whole genome duplications have recently been firmly established in all major eukaryote kingdoms. Such exponential evolutionary processes must have largely contributed to shape the topology of protein-protein interaction (PPI networks by outweighing, in particular, all time-linear network growths modeled so far. Results We propose and solve a mathematical model of PPI network evolution under successive genome duplications. This demonstrates, from first principles, that evolutionary conservation and scale-free topology are intrinsically linked properties of PPI networks and emerge from i prevailing exponential network dynamics under duplication and ii asymmetric divergence of gene duplicates. While required, we argue that this asymmetric divergence arises, in fact, spontaneously at the level of protein-binding sites. This supports a refined model of PPI network evolution in terms of protein domains under exponential and asymmetric duplication/divergence dynamics, with multidomain proteins underlying the combinatorial formation of protein complexes. Genome duplication then provides a powerful source of PPI network innovation by promoting local rearrangements of multidomain proteins on a genome wide scale. Yet, we show that the overall conservation and topology of PPI networks are robust to extensive domain shuffling of multidomain proteins as well as to finer details of protein interaction and evolution. Finally, large scale features of direct and indirect PPI networks of S. cerevisiae are well reproduced numerically with only two adjusted parameters of clear biological significance (i.e. network effective growth rate and average number of protein-binding domains per protein. Conclusion This study demonstrates the statistical consequences of genome duplication and domain shuffling on the conservation and topology of PPI networks over a broad evolutionary scale across eukaryote kingdoms. In particular, scale

  15. 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...... the diffusion of neutral and ionic molecules across biomembranes, protonation to mono- or bivalent ions, adsorption to lipids, and electrical attraction or repulsion. Based on simulation results, high and selective accumulation in lysosomes was found for weak mono- and bivalent bases with intermediate to high...... predicted by the model and three were close. Five of the antimalarial drugs were lipophilic weak dibasic compounds. The predicted optimum properties for a selective accumulation of weak bivalent bases in lysosomes are consistent with experimental values and are more accurate than any prior calculation...

  16. Chemical Screens Identify Drugs that Enhance or Mitigate Cellular Responses to Antibody-Toxin Fusion Proteins.

    Directory of Open Access Journals (Sweden)

    Antonella Antignani

    Full Text Available The intersection of small molecular weight drugs and antibody-based therapeutics is rarely studied in large scale. Both types of agents are currently part of the cancer armamentarium. However, very little is known about how to combine them in optimal ways. Immunotoxins are antibody-toxin gene fusion proteins engineered to target cancer cells via antibody binding to surface antigens. For fusion proteins derived from Pseudomonas exotoxin (PE, potency relies on the enzymatic domain of the toxin which catalyzes the ADP-ribosylation of EF2 causing inhibition of protein synthesis leading to cell death. Candidate immunotoxins have demonstrated clear value in clinical trials but generally have not been curative as single agents. Therefore we undertook three screens to discover effective combinations that could act synergistically. From the MIPE-3 library of compounds we identified various enhancers of immunotoxin action and at least one major class of inhibitor. Follow-up experiments confirmed the screening data and suggested that immunotoxins when administered with everolimus or nilotinib exhibit favorable combinatory activity and would be candidates for preclinical development. Mechanistic studies revealed that everolimus-immunotoxin combinations acted synergistically on elements of the protein synthetic machinery, including S61 kinase and 4E-BP1 of the mTORC1 pathway. Conversely, PARP inhibitors antagonized immunotoxins and also blocked the toxicity due to native ADP-ribosylating toxins. Thus, our goal of investigating a chemical library was justified based on the identification of several approved compounds that could be developed preclinically as 'enhancers' and at least one class of mitigator to be avoided.

  17. Application of CYP102A1M11H as a tool for the generation of protein adducts of reactive drug metabolites

    NARCIS (Netherlands)

    Boerma, J.S.; Vermeulen, N.P.E.; Commandeur, J.N.M.

    2011-01-01

    Covalent binding of reactive metabolites (RMs) to proteins is considered to be one of the important mechanisms by which drugs can cause tissue damage. To facilitate the study of drug-protein adducts, we developed a potentially generic method for producing high levels of covalently modified proteins.

  18. A developmental etiological model for drug abuse in men.

    Science.gov (United States)

    Kendler, Kenneth S; Ohlsson, Henrik; Edwards, Alexis C; Sundquist, Jan; Sundquist, Kristina

    2017-10-01

    We attempt to develop a relatively comprehensive structural model of risk factors for drug abuse (DA) in Swedish men that illustrates developmental and mediational processes. We examined 20 risk factors for DA in 48,369 men undergoing conscription examinations in 1969-70 followed until 2011 when 2.34% (n=1134) of them had DA ascertained in medical, criminal and pharmacy registries. Risk factors were organized into four developmental tiers reflecting i) birth, ii) childhood/early adolescence, iii) late adolescence, and iv) young adulthood. Structural equational model fitting was performed using Mplus. The best fitting model explained 47.8% of the variance in DA. The most prominent predictors, in order, were: early adolescent externalizing behavior, early adult criminal behavior, early adolescent internalizing behavior, early adult unemployment, early adult alcohol use disorder, and late adolescent drug use. Two major inter-connecting pathways emerged reflecting i) genetic/familial risk and ii) family dysfunction and psychosocial adversity. Generated on a first and tested on a second random half of the sample, a model from these variables predicted DA with an ROC area under the curve of 83.6%. Fifty-nine percent of DA cases arose from subjects in the top decile of risk. DA in men is a highly multifactorial syndrome with risk arising from familial-genetic, psychosocial, behavioral and psychological factors acting and interacting over development. Among the multiple predisposing factors for DA, a range of psychosocial adversities, externalizing psychopathology and lack of social constraints in early adulthood are predominant. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Modeling the SHG activities of diverse protein crystals

    International Nuclear Information System (INIS)

    Haupert, Levi M.; DeWalt, Emma L.; Simpson, Garth J.

    2012-01-01

    The origins of the diversity in the SHG signal from protein crystals are investigated and potential protein-crystal coverage by SHG microscopy is assessed. A symmetry-additive ab initio model for second-harmonic generation (SHG) activity of protein crystals was applied to assess the likely protein-crystal coverage of SHG microscopy. Calculations were performed for 250 proteins in nine point-group symmetries: a total of 2250 crystals. The model suggests that the crystal symmetry and the limit of detection of the instrument are expected to be the strongest predictors of coverage of the factors considered, which also included secondary-structural content and protein size. Much of the diversity in SHG activity is expected to arise primarily from the variability in the intrinsic protein response as well as the orientation within the crystal lattice. Two or more orders-of-magnitude variation in intensity are expected even within protein crystals of the same symmetry. SHG measurements of tetragonal lysozyme crystals confirmed detection, from which a protein coverage of ∼84% was estimated based on the proportion of proteins calculated to produce SHG responses greater than that of tetragonal lysozyme. Good agreement was observed between the measured and calculated ratios of the SHG intensity from lysozyme in tetragonal and monoclinic lattices

  20. An Integrated Framework Advancing Membrane Protein Modeling and Design.

    Directory of Open Access Journals (Sweden)

    Rebecca F Alford

    2015-09-01

    Full Text Available Membrane proteins are critical functional molecules in the human body, constituting more than 30% of open reading frames in the human genome. Unfortunately, a myriad of difficulties in overexpression and reconstitution into membrane mimetics severely limit our ability to determine their structures. Computational tools are therefore instrumental to membrane protein structure prediction, consequently increasing our understanding of membrane protein function and their role in disease. Here, we describe a general framework facilitating membrane protein modeling and design that combines the scientific principles for membrane protein modeling with the flexible software architecture of Rosetta3. This new framework, called RosettaMP, provides a general membrane representation that interfaces with scoring, conformational sampling, and mutation routines that can be easily combined to create new protocols. To demonstrate the capabilities of this implementation, we developed four proof-of-concept applications for (1 prediction of free energy changes upon mutation; (2 high-resolution structural refinement; (3 protein-protein docking; and (4 assembly of symmetric protein complexes, all in the membrane environment. Preliminary data show that these algorithms can produce meaningful scores and structures. The data also suggest needed improvements to both sampling routines and score functions. Importantly, the applications collectively demonstrate the potential of combining the flexible nature of RosettaMP with the power of Rosetta algorithms to facilitate membrane protein modeling and design.

  1. G protein-coupled receptors as anabolic drug targets in osteoporosis.

    Science.gov (United States)

    Diepenhorst, Natalie; Rueda, Patricia; Cook, Anna E; Pastoureau, Philippe; Sabatini, Massimo; Langmead, Christopher J

    2018-04-01

    Osteoporosis is a progressive bone disorder characterised by imbalance between bone building (anabolism) and resorption (catabolism). Most therapeutics target inhibition of osteoclast-mediated bone resorption, but more recent attention in early drug discovery has focussed on anabolic targets in osteoblasts or their precursors. Two marketed agents that display anabolic properties, strontium ranelate and teriparatide, mediate their actions via the G protein-coupled calcium-sensing and parathyroid hormone-1 receptors, respectively. This review explores their activity, the potential for improved therapeutics targeting these receptors and other putative anabolic GPCR targets, including Smoothened, Wnt/Frizzled, relaxin family peptide, adenosine, cannabinoid, prostaglandin and sphingosine-1-phosphate receptors. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Theoretical model analysis of molecular orientations in liquid protein ...

    African Journals Online (AJOL)

    In this study, some theoretical model functions have been used to explain the molecular behaviour of four different types of proteins; human haemoglobin, Insulin, egg-white lysozyme and β - globulin molecules in solution. The results of the computational fitting procedures showed that the dielectric dispersion of the protein ...

  3. Preparation and In Vitro Release of Drug-Loaded Microparticles for Oral Delivery Using Wholegrain Sorghum Kafirin Protein

    Directory of Open Access Journals (Sweden)

    Esther T. L. Lau

    2015-01-01

    Full Text Available Kafirin microparticles have been proposed as an oral nutraceutical and drug delivery system. This study investigates microparticles formed with kafirin extracted from white and raw versus cooked red sorghum grains as an oral delivery system. Targeted delivery to the colon would be beneficial for medication such as prednisolone, which is used in the management of inflammatory bowel disease. Therefore, prednisolone was loaded into microparticles of kafirin from the different sources using phase separation. Differences were observed in the protein content, in vitro protein digestibility, and protein electrophoretic profile of the various sources of sorghum grains, kafirin extracts, and kafirin microparticles. For all of the formulations, the majority of the loaded prednisolone was not released in in vitro conditions simulating the upper gastrointestinal tract, indicating that most of the encapsulated drug could reach the target area of the lower gastrointestinal tract. This suggests that these kafirin microparticles may have potential as a colon-targeted nutraceutical and drug delivery system.

  4. Encapsulation of proteins in hydrogel carrier systems for controlled drug delivery: influence of network structure and drug size on release rate.

    Science.gov (United States)

    Bertz, Andreas; Wöhl-Bruhn, Stefanie; Miethe, Sebastian; Tiersch, Brigitte; Koetz, Joachim; Hust, Michael; Bunjes, Heike; Menzel, Henning

    2013-01-20

    Novel hydrogels based on hydroxyethyl starch modified with polyethylene glycol methacrylate (HES-P(EG)₆MA) were developed as delivery system for the controlled release of proteins. Since the drug release behavior is supposed to be related to the pore structure of the hydrogel network the pore sizes were determined by cryo-SEM, which is a mild technique for imaging on a nanometer scale. The results showed a decreasing pore size and an increase in pore homogeneity with increasing polymer concentration. Furthermore, the mesh sizes of the hydrogels were calculated based on swelling data. Pore and mesh size were significantly different which indicates that both structures are present in the hydrogel. The resulting structural model was correlated with release data for bulk hydrogel cylinders loaded with FITC-dextran and hydrogel microspheres loaded with FITC-IgG and FITC-dextran of different molecular size. The initial release depended much on the relation between hydrodynamic diameter and pore size while the long term release of the incorporated substances was predominantly controlled by degradation of the network of the much smaller meshes. Copyright © 2012 Elsevier B.V. All rights reserved.

  5. Structural basis for modulation of a G-protein-coupled receptor by allosteric drugs

    Science.gov (United States)

    Dror, Ron O.; Green, Hillary F.; Valant, Celine; Borhani, David W.; Valcourt, James R.; Pan, Albert C.; Arlow, Daniel H.; Canals, Meritxell; Lane, J. Robert; Rahmani, Raphaël; Baell, Jonathan B.; Sexton, Patrick M.; Christopoulos, Arthur; Shaw, David E.

    2013-11-01

    The design of G-protein-coupled receptor (GPCR) allosteric modulators, an active area of modern pharmaceutical research, has proved challenging because neither the binding modes nor the molecular mechanisms of such drugs are known. Here we determine binding sites, bound conformations and specific drug-receptor interactions for several allosteric modulators of the M2 muscarinic acetylcholine receptor (M2 receptor), a prototypical family A GPCR, using atomic-level simulations in which the modulators spontaneously associate with the receptor. Despite substantial structural diversity, all modulators form cation-π interactions with clusters of aromatic residues in the receptor extracellular vestibule, approximately 15Å from the classical, `orthosteric' ligand-binding site. We validate the observed modulator binding modes through radioligand binding experiments on receptor mutants designed, on the basis of our simulations, either to increase or to decrease modulator affinity. Simulations also revealed mechanisms that contribute to positive and negative allosteric modulation of classical ligand binding, including coupled conformational changes of the two binding sites and electrostatic interactions between ligands in these sites. These observations enabled the design of chemical modifications that substantially alter a modulator's allosteric effects. Our findings thus provide a structural basis for the rational design of allosteric modulators targeting muscarinic and possibly other GPCRs.

  6. Role of Breast Cancer Resistance Protein (BCRP/ABCG2) in Cancer Drug Resistance

    Science.gov (United States)

    Natarajan, Karthika; Xie, Yi; Baer, Maria R.; Ross, Douglas D.

    2012-01-01

    Since cloning of the ATP-binding cassette (ABC) family member breast cancer resistance protein (BCRP/ABCG2) and its characterization as a multidrug resistance efflux transporter in 1998, BCRP has been the subject of more than two thousand scholarly articles. In normal tissues, BCRP functions as a defense mechanism against toxins and xenobiotics, with expression in the gut, bile canaliculi, placenta, blood-testis and blood-brain barriers facilitating excretion and limiting absorption of potentially toxic substrate molecules, including many cancer chemotherapeutic drugs. BCRP also plays a key role in heme and folate homeostasis, which may help normal cells survive under conditions of hypoxia. BCRP expression appears to be a characteristic of certain normal tissue stem cells termed “side population cells,” which are identified on flow cytometric analysis by their ability to exclude Hoechst 33342, a BCRP substrate fluorescent dye. Hence, BCRP expression may contribute to the natural resistance and longevity of these normal stem cells. Malignant tissues can exploit the properties of BCRP to survive hypoxia and to evade exposure to chemotherapeutic drugs. Evidence is mounting that many cancers display subpopulations of stem cells that are responsible for tumor self-renewal. Such stem cells frequently manifest the “side population” phenotype characterized by expression of BCRP and other ABC transporters. Along with other factors, these transporters may contribute to the inherent resistance of these neoplasms and their failure to be cured. PMID:22248732

  7. Trends in protein-based biosensor assemblies for drug screening and pharmaceutical kinetic studies.

    Science.gov (United States)

    Gonçalves, Ana M; Pedro, Augusto Q; Santos, Fátima M; Martins, Luís M; Maia, Cláudio J; Queiroz, João A; Passarinha, Luís A

    2014-08-18

    The selection of natural and chemical compounds for potential applications in new pharmaceutical formulations constitutes a time-consuming procedure in drug screening. To overcome this issue, new devices called biosensors, have already demonstrated their versatility and capacity for routine clinical diagnosis. Designed to perform analytical analysis for the detection of a particular analyte, biosensors based on the coupling of proteins to amperometric and optical devices have shown the appropriate selectivity, sensibility and accuracy. During the last years, the exponential demand for pharmacokinetic studies in the early phases of drug development, along with the need of lower molecular weight detection, have led to new biosensor structure materials with innovative immobilization strategies. The result has been the development of smaller, more reproducible biosensors with lower detection limits, and with a drastic reduction in the required sample volumes. Therefore in order to describe the main achievements in biosensor fields, the present review has the main aim of summarizing the essential strategies used to generate these specific devices, that can provide, under physiological conditions, a credible molecule profile and assess specific pharmacokinetic parameters.

  8. Development of New Drugs for an Old Target — The Penicillin Binding Proteins

    Directory of Open Access Journals (Sweden)

    André Luxen

    2012-10-01

    Full Text Available The widespread use of β-lactam antibiotics has led to the worldwide appearance of drug-resistant strains. Bacteria have developed resistance to β-lactams by two main mechanisms: the production of β-lactamases, sometimes accompanied by a decrease of outer membrane permeability, and the production of low-affinity, drug resistant Penicillin Binding Proteins (PBPs. PBPs remain attractive targets for developing new antibiotic agents because they catalyse the last steps of the biosynthesis of peptidoglycan, which is unique to bacteria, and lies outside the cytoplasmic membrane. Here we summarize the “current state of the art” of non-β-lactam inhibitors of PBPs, which have being developed in an attempt to counter the emergence of β-lactam resistance. These molecules are not susceptible to hydrolysis by β-lactamases and thus present a real alternative to β-lactams. We present transition state analogs such as boronic acids, which can covalently bind to the active serine residue in the catalytic site. Molecules containing ring structures different from the β-lactam-ring like lactivicin are able to acylate the active serine residue. High throughput screening methods, in combination with virtual screening methods and structure based design, have allowed the development of new molecules. Some of these novel inhibitors are active against major pathogens, including methicillin-resistant Staphylococcus aureus (MRSA and thus open avenues new for the discovery of novel antibiotics.

  9. Hub nodes in the network of human Mitogen-Activated Protein Kinase (MAPK pathways: Characteristics and potential as drug targets

    Directory of Open Access Journals (Sweden)

    V.K. MD Aksam

    2017-01-01

    Full Text Available Proteins involved in the cross-talk between ERK1/2, ERK5, JNK, and P38 signalling pathways integrate the network of Mitogen-Activated Protein Kinase (MAPK pathways. Graph theory-based approach is used to construct the network of MAPK pathways, and to observe the network organisational principles. Connectivity pattern reveals rich-club among the hubs, enabling structural ordering. A positive correlation between the degree of the nodes and percentage of essential protein showed hubs are central to the network architecture and function. Furthermore, attributes like connectivity, inter/intra-pathway class, position in the pathway, protein type and subcellular localization of the essential and non-essential proteins are characterizing complex functional roles. Shared properties of 34 cancerous essential proteins lack to be drug targets. We identified the seven nodes overlapping properties of the hub, essential and causing side effects on targeting them. We exploit the strategy of cancerous, non-hub and non-essential proteins as potential drug targets and identified 4EBP1, BAD, CHOP10, GADD45, HSP27, MKP1, RNPK, MLTKa/b, cPLA2, eEF2K and elF4E. We have illustrated the implication of targeting hub nodes and proposed network-based drug targets which would cause less side effect.

  10. Analysis of Drug Design for a Selection of G Protein-Coupled Neuro-Receptors Using Neural Network Techniques

    DEFF Research Database (Denmark)

    Agerskov, Claus; Mortensen, Rasmus M.; Bohr, Henrik G.

    2015-01-01

    A study is presented on how well possible drug-molecules can be predicted with respect to their function and binding to a selection of neuro-receptors by the use of artificial neural networks. The ligands investigated in this study are chosen to be corresponding to the G protein-coupled receptors...... computational tools, able to aid in drug-design in a fast and cheap fashion, compared to conventional pharmacological techniques....

  11. Comparative Study of Elastic Network Model and Protein Contact Network for Protein Complexes: The Hemoglobin Case

    Directory of Open Access Journals (Sweden)

    Guang Hu

    2017-01-01

    Full Text Available The overall topology and interfacial interactions play key roles in understanding structural and functional principles of protein complexes. Elastic Network Model (ENM and Protein Contact Network (PCN are two widely used methods for high throughput investigation of structures and interactions within protein complexes. In this work, the comparative analysis of ENM and PCN relative to hemoglobin (Hb was taken as case study. We examine four types of structural and dynamical paradigms, namely, conformational change between different states of Hbs, modular analysis, allosteric mechanisms studies, and interface characterization of an Hb. The comparative study shows that ENM has an advantage in studying dynamical properties and protein-protein interfaces, while PCN is better for describing protein structures quantitatively both from local and from global levels. We suggest that the integration of ENM and PCN would give a potential but powerful tool in structural systems biology.

  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

    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...

  13. eMatchSite: sequence order-independent structure alignments of ligand binding pockets in protein models.

    Directory of Open Access Journals (Sweden)

    Michal Brylinski

    2014-09-01

    Full Text Available Detecting similarities between ligand binding sites in the absence of global homology between target proteins has been recognized as one of the critical components of modern drug discovery. Local binding site alignments can be constructed using sequence order-independent techniques, however, to achieve a high accuracy, many current algorithms for binding site comparison require high-quality experimental protein structures, preferably in the bound conformational state. This, in turn, complicates proteome scale applications, where only various quality structure models are available for the majority of gene products. To improve the state-of-the-art, we developed eMatchSite, a new method for constructing sequence order-independent alignments of ligand binding sites in protein models. Large-scale benchmarking calculations using adenine-binding pockets in crystal structures demonstrate that eMatchSite generates accurate alignments for almost three times more protein pairs than SOIPPA. More importantly, eMatchSite offers a high tolerance to structural distortions in ligand binding regions in protein models. For example, the percentage of correctly aligned pairs of adenine-binding sites in weakly homologous protein models is only 4-9% lower than those aligned using crystal structures. This represents a significant improvement over other algorithms, e.g. the performance of eMatchSite in recognizing similar binding sites is 6% and 13% higher than that of SiteEngine using high- and moderate-quality protein models, respectively. Constructing biologically correct alignments using predicted ligand binding sites in protein models opens up the possibility to investigate drug-protein interaction networks for complete proteomes with prospective systems-level applications in polypharmacology and rational drug repositioning. eMatchSite is freely available to the academic community as a web-server and a stand-alone software distribution at http://www.brylinski.org/ematchsite.

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

    Science.gov (United States)

    Christophersen, P C; Zhang, L; Yang, M; Nielsen, H Mørck; Müllertz, A; Mu, H

    2013-11-01

    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 change in particle surface during the lipolysis process was evaluated using scanning electron microscopy. The lysozyme release profiles from TG14 and TG18 as well as diglyceride particles correlated well with the release of free fatty acids from the lipid particles during the lipolysis and therefore exhibited a lipase-mediated degradation-based release mechanism. The release of lysozyme from monoglyceride particles was independent on lipase degradation due to the instability of the lipid matrix in the lipolysis medium. In conclusion, the established lipolysis model is successfully used to elucidate 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. Copyright © 2013 Elsevier B.V. All rights reserved.

  15. The dengue virus NS5 protein as a target for drug discovery.

    Science.gov (United States)

    Lim, Siew Pheng; Noble, Christian G; Shi, Pei-Yong

    2015-07-01

    The non-structural protein 5 (NS5) of flaviviruses is the most conserved amongst the viral proteins. It is about 900 kDa and bears enzymatic activities that play vital roles in virus replication. Its N-terminal domain encodes dual N7 and 2'-O methyltransferase activities (MTase), and possibly guanylyltransferase (GTase) involved in RNA cap formation. The C-terminal region comprises a RNA-dependent RNA polymerase (RdRp) required for viral RNA synthesis. Both MTase and RdRp activities of dengue virus NS5 are well characterized, structurally and functionally. Numerous crystal structures of the flavivirus MTase and RdRp domains have been solved. Inhibitors of both functions have been identified through screening activities using biochemical and cell-based assays, as well as via rational design approaches. This review summaries the current knowledge as well as prospective views on these aspects. This article forms part of a symposium on flavivirus drug discovery in Antiviral Research. Copyright © 2015 Elsevier B.V. All rights reserved.

  16. Gaia: automated quality assessment of protein structure models.

    Science.gov (United States)

    Kota, Pradeep; Ding, Feng; Ramachandran, Srinivas; Dokholyan, Nikolay V

    2011-08-15

    Increasing use of structural modeling for understanding structure-function relationships in proteins has led to the need to ensure that the protein models being used are of acceptable quality. Quality of a given protein structure can be assessed by comparing various intrinsic structural properties of the protein to those observed in high-resolution protein structures. In this study, we present tools to compare a given structure to high-resolution crystal structures. We assess packing by calculating the total void volume, the percentage of unsatisfied hydrogen bonds, the number of steric clashes and the scaling of the accessible surface area. We assess covalent geometry by determining bond lengths, angles, dihedrals and rotamers. The statistical parameters for the above measures, obtained from high-resolution crystal structures enable us to provide a quality-score that points to specific areas where a given protein structural model needs improvement. We provide these tools that appraise protein structures in the form of a web server Gaia (http://chiron.dokhlab.org). Gaia evaluates the packing and covalent geometry of a given protein structure and provides quantitative comparison of the given structure to high-resolution crystal structures. dokh@unc.edu Supplementary data are available at Bioinformatics online.

  17. A novel, high-sensitivity and drug-tolerant sandwich immunoassay for the quantitative measurement of circulating proteins.

    Science.gov (United States)

    Sloan, John H; Ackermann, Bradley L; Carpenter, John W; Nguyen, Huy T; Stopa, Kimberly; Siegel, Robert W; Konrad, Robert J

    2012-02-01

    Accurate measurement of a total protein target (free plus bound) is essential to optimize dose selection for monoclonal antibody drugs. Herein, we describe a novel sandwich immunoassay format in which the biotherapeutic antibody itself serves as the primary detection antibody. A signal is then generated through the addition of a labeled secondary antibody that recognizes the biotherapeutic antibody. The secondary antibody is conjugated with ruthenium to facilitate electrochemiluminescent analysis. Data are presented from the analysis of two protein biomarkers having disparate size and structure; a 4.5 kDa peptide and a 60 kDa protein. In both cases, validated, highly specific assays were developed and shown to be tolerant to elevated levels of the therapeutic monoclonal antibody in question. Our novel format allows drug-tolerant measurement of soluble protein biomarkers targeted by monoclonal antibodies when only two independent epitopes for antibody binding are available and one is recognized by the therapeutic antibody.

  18. Imatinib (Gleevec@) conformations observed in single crystals, protein-Imatinib co-crystals and molecular dynamics: Implications for drug selectivity

    Science.gov (United States)

    Golzarroshan, B.; Siddegowda, M. S.; Li, Hong qi; Yathirajan, H. S.; Narayana, B.; Rathore, R. S.

    2012-06-01

    Structure and dynamics of the Leukemia drug, Imatinib, were examined using X-ray crystallography and molecular dynamics studies. Comparison of conformations observed in single crystals with several reported co-crystals of protein-drug complexes suggests existence of two conserved conformations of Imatinib, extended and compact (or folded), corresponding to two binding modes of interaction with the receptor. Furthermore, these conformations are conserved throughout a dynamics simulation. The present study attempts to draw a parallel on conformations and binding patterns of interactions, obtained from small-molecule single-crystal and macromolecule co-crystal studies, and provides structural insights for understanding the high selectivity of this drug molecule.

  19. Structure-based drug design, synthesis and biological assays of P. falciparum Atg3-Atg8 protein-protein interaction inhibitors

    Science.gov (United States)

    Villa, Stefania; Legnani, Laura; Colombo, Diego; Gelain, Arianna; Lammi, Carmen; Bongiorno, Daniele; Ilboudo, Denise P.; McGee, Kellen E.; Bosch, Jürgen; Grazioso, Giovanni

    2018-01-01

    The proteins involved in the autophagy (Atg) pathway have recently been considered promising targets for the development of new antimalarial drugs. In particular, inhibitors of the protein-protein interaction (PPI) between Atg3 and Atg8 of Plasmodium falciparum retarded the blood- and liver-stages of parasite growth. In this paper, we used computational techniques to design a new class of peptidomimetics mimicking the Atg3 interaction motif, which were then synthesized by click-chemistry. Surface plasmon resonance has been employed to measure the ability of these compounds to inhibit the Atg3-Atg8 reciprocal protein-protein interaction. Moreover, P. falciparum growth inhibition in red blood cell cultures was evaluated as well as the cyto-toxicity of the compounds.

  20. Structure-based drug design, synthesis and biological assays of P. falciparum Atg3-Atg8 protein-protein interaction inhibitors

    Science.gov (United States)

    Villa, Stefania; Legnani, Laura; Colombo, Diego; Gelain, Arianna; Lammi, Carmen; Bongiorno, Daniele; Ilboudo, Denise P.; McGee, Kellen E.; Bosch, Jürgen; Grazioso, Giovanni

    2018-03-01

    The proteins involved in the autophagy (Atg) pathway have recently been considered promising targets for the development of new antimalarial drugs. In particular, inhibitors of the protein-protein interaction (PPI) between Atg3 and Atg8 of Plasmodium falciparum retarded the blood- and liver-stages of parasite growth. In this paper, we used computational techniques to design a new class of peptidomimetics mimicking the Atg3 interaction motif, which were then synthesized by click-chemistry. Surface plasmon resonance has been employed to measure the ability of these compounds to inhibit the Atg3-Atg8 reciprocal protein-protein interaction. Moreover, P. falciparum growth inhibition in red blood cell cultures was evaluated as well as the cyto-toxicity of the compounds.

  1. Structure of drug-target proteins determined by both X-ray and neutron diffraction

    International Nuclear Information System (INIS)

    Kuroki, Ryota

    2009-01-01

    Crystallography enables us to obtain accurate atomic positions within proteins. High resolution X-ray crystallography provides information for most of the atoms comprising a protein, with the exception of hydrogens. Neutron diffraction data can provide information of the location of hydrogen atoms to the structural information determined by X-ray crystallography. Here, we show the recent of the structural determination of drug-target proteins, porcine pancreatic elastase (PPE) and human immuno-deficiency virus type-1 protease (HIV-PR) by both X-ray and neutron diffraction. The structure of porcine pancreatic elastase with its potent inhibitor (FR13080) was determined to 0.94A resolution by X-ray diffraction and 1.75 A resolution by neutron diffraction. It was found that there are two characteristic hydrogen bonding interactions in which hydrogen atoms were confirmed. One is located between a catalytic aspartate and histidine, another is involved in the inhibitor recognition site. The structure of HIV-PR with its potent inhibitor (KNI-272) was also determined to 0.93 A resolution by X-ray diffraction and 2.3 A resolution by neutron diffraction. The ionization state of the catalytic residues were clarified to show that Asp125 is protonated and Asp25 is deprotonated. The ionization state and the location of hydrogen atoms of the catalytic residue in HIV-PR were firstly determined by neutron diffraction. Furthermore, collaborative use of both X-ray and neutron to identify the location of ambiguous hydrogen atoms will be shown. (author)

  2. 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.

  3. 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

  4. Protein buffering in model systems and in whole human saliva.

    Directory of Open Access Journals (Sweden)

    Andreas Lamanda

    Full Text Available The aim of this study was to quantify the buffer attributes (value, power, range and optimum of two model systems for whole human resting saliva, the purified proteins from whole human resting saliva and single proteins. Two model systems, the first containing amyloglucosidase and lysozyme, and the second containing amyloglucosidase and alpha-amylase, were shown to provide, in combination with hydrogencarbonate and di-hydrogenphosphate, almost identical buffer attributes as whole human resting saliva. It was further demonstrated that changes in the protein concentration as small as 0.1% may change the buffer value of a buffer solution up to 15 times. Additionally, it was shown that there was a protein concentration change in the same range (0.16% between saliva samples collected at the time periods of 13:00 and others collected at 9:00 am and 17:00. The mode of the protein expression changed between these samples corresponded to the change in basic buffer power and the change of the buffer value at pH 6.7. Finally, SDS Page and Ruthenium II tris (bathophenantroline disulfonate staining unveiled a constant protein expression in all samples except for one 50 kDa protein band. As the change in the expression pattern of that 50 kDa protein band corresponded to the change in basic buffer power and the buffer value at pH 6.7, it was reasonable to conclude that this 50 kDa protein band may contain the protein(s belonging to the protein buffer system of human saliva.

  5. An approach to creating a more realistic working model from a protein data bank entry.

    Science.gov (United States)

    Brandon, Christopher J; Martin, Benjamin P; McGee, Kelly J; Stewart, James J P; Braun-Sand, Sonja B

    2015-01-01

    An accurate model of three-dimensional protein structure is important in a variety of fields such as structure-based drug design and mechanistic studies of enzymatic reactions. While the entries in the Protein Data Bank ( http://www.pdb.org ) provide valuable information about protein structures, a small fraction of the PDB structures were found to contain anomalies not reported in the PDB file. The semiempirical PM7 method in MOPAC2012 was used for identifying anomalously short hydrogen bonds, C-H⋯O/C-H⋯N interactions, non-bonding close contacts, and unrealistic covalent bond lengths in recently published Protein Data Bank files. It was also used to generate new structures with these faults removed. When the semiempirical models were compared to those of PDB_REDO (http://www.cmbi.ru.nl/pdb_redo/), the clashscores, as defined by MolProbity ( http://molprobity.biochem.duke.edu/), were better in about 50% of the structures. The semiempirical models also had a lower root-mean-square-deviation value in nearly all cases than those from PDB_REDO, indicative of a better conservation of the tertiary structure. Finally, the semiempirical models were found to have lower clashscores than the initial PDB file in all but one case. Because this approach maintains as much of the original tertiary structure as possible while improving anomalous interactions, it should be useful to theoreticians, experimentalists, and crystallographers investigating the structure and function of proteins.

  6. A resource for benchmarking the usefulness of protein structure models.

    Science.gov (United States)

    Carbajo, Daniel; Tramontano, Anna

    2012-08-02

    Increasingly, biologists and biochemists use computational tools to design experiments to probe the function of proteins and/or to engineer them for a variety of different purposes. The most effective strategies rely on the knowledge of the three-dimensional structure of the protein of interest. However it is often the case that an experimental structure is not available and that models of different quality are used instead. On the other hand, the relationship between the quality of a model and its appropriate use is not easy to derive in general, and so far it has been analyzed in detail only for specific application. This paper describes a database and related software tools that allow testing of a given structure based method on models of a protein representing different levels of accuracy. The comparison of the results of a computational experiment on the experimental structure and on a set of its decoy models will allow developers and users to assess which is the specific threshold of accuracy required to perform the task effectively. The ModelDB server automatically builds decoy models of different accuracy for a given protein of known structure and provides a set of useful tools for their analysis. Pre-computed data for a non-redundant set of deposited protein structures are available for analysis and download in the ModelDB database. IMPLEMENTATION, AVAILABILITY AND REQUIREMENTS: Project name: A resource for benchmarking the usefulness of protein structure models. Project home page: http://bl210.caspur.it/MODEL-DB/MODEL-DB_web/MODindex.php.Operating system(s): Platform independent. Programming language: Perl-BioPerl (program); mySQL, Perl DBI and DBD modules (database); php, JavaScript, Jmol scripting (web server). Other requirements: Java Runtime Environment v1.4 or later, Perl, BioPerl, CPAN modules, HHsearch, Modeller, LGA, NCBI Blast package, DSSP, Speedfill (Surfnet) and PSAIA. License: Free. Any restrictions to use by non-academics: No.

  7. A resource for benchmarking the usefulness of protein structure models.

    KAUST Repository

    Carbajo, Daniel

    2012-08-02

    BACKGROUND: Increasingly, biologists and biochemists use computational tools to design experiments to probe the function of proteins and/or to engineer them for a variety of different purposes. The most effective strategies rely on the knowledge of the three-dimensional structure of the protein of interest. However it is often the case that an experimental structure is not available and that models of different quality are used instead. On the other hand, the relationship between the quality of a model and its appropriate use is not easy to derive in general, and so far it has been analyzed in detail only for specific application. RESULTS: This paper describes a database and related software tools that allow testing of a given structure based method on models of a protein representing different levels of accuracy. The comparison of the results of a computational experiment on the experimental structure and on a set of its decoy models will allow developers and users to assess which is the specific threshold of accuracy required to perform the task effectively. CONCLUSIONS: The ModelDB server automatically builds decoy models of different accuracy for a given protein of known structure and provides a set of useful tools for their analysis. Pre-computed data for a non-redundant set of deposited protein structures are available for analysis and download in the ModelDB database. IMPLEMENTATION, AVAILABILITY AND REQUIREMENTS: Project name: A resource for benchmarking the usefulness of protein structure models. Project home page: http://bl210.caspur.it/MODEL-DB/MODEL-DB_web/MODindex.php.Operating system(s): Platform independent. Programming language: Perl-BioPerl (program); mySQL, Perl DBI and DBD modules (database); php, JavaScript, Jmol scripting (web server). Other requirements: Java Runtime Environment v1.4 or later, Perl, BioPerl, CPAN modules, HHsearch, Modeller, LGA, NCBI Blast package, DSSP, Speedfill (Surfnet) and PSAIA. License: Free. Any restrictions to use by

  8. Binding free energy analysis of protein-protein docking model structures by evERdock.

    Science.gov (United States)

    Takemura, Kazuhiro; Matubayasi, Nobuyuki; Kitao, Akio

    2018-03-14

    To aid the evaluation of protein-protein complex model structures generated by protein docking prediction (decoys), we previously developed a method to calculate the binding free energies for complexes. The method combines a short (2 ns) all-atom molecular dynamics simulation with explicit solvent and solution theory in the energy representation (ER). We showed that this method successfully selected structures similar to the native complex structure (near-native decoys) as the lowest binding free energy structures. In our current work, we applied this method (evERdock) to 100 or 300 model structures of four protein-protein complexes. The crystal structures and the near-native decoys showed the lowest binding free energy of all the examined structures, indicating that evERdock can successfully evaluate decoys. Several decoys that show low interface root-mean-square distance but relatively high binding free energy were also identified. Analysis of the fraction of native contacts, hydrogen bonds, and salt bridges at the protein-protein interface indicated that these decoys were insufficiently optimized at the interface. After optimizing the interactions around the interface by including interfacial water molecules, the binding free energies of these decoys were improved. We also investigated the effect of solute entropy on binding free energy and found that consideration of the entropy term does not necessarily improve the evaluations of decoys using the normal model analysis for entropy calculation.

  9. Binding free energy analysis of protein-protein docking model structures by evERdock

    Science.gov (United States)

    Takemura, Kazuhiro; Matubayasi, Nobuyuki; Kitao, Akio

    2018-03-01

    To aid the evaluation of protein-protein complex model structures generated by protein docking prediction (decoys), we previously developed a method to calculate the binding free energies for complexes. The method combines a short (2 ns) all-atom molecular dynamics simulation with explicit solvent and solution theory in the energy representation (ER). We showed that this method successfully selected structures similar to the native complex structure (near-native decoys) as the lowest binding free energy structures. In our current work, we applied this method (evERdock) to 100 or 300 model structures of four protein-protein complexes. The crystal structures and the near-native decoys showed the lowest binding free energy of all the examined structures, indicating that evERdock can successfully evaluate decoys. Several decoys that show low interface root-mean-square distance but relatively high binding free energy were also identified. Analysis of the fraction of native contacts, hydrogen bonds, and salt bridges at the protein-protein interface indicated that these decoys were insufficiently optimized at the interface. After optimizing the interactions around the interface by including interfacial water molecules, the binding free energies of these decoys were improved. We also investigated the effect of solute entropy on binding free energy and found that consideration of the entropy term does not necessarily improve the evaluations of decoys using the normal model analysis for entropy calculation.

  10. How to calculate clearance of highly protein-bound drugs during continuous venovenous hemofiltration demonstrated with flucloxacillin.

    Science.gov (United States)

    Meyer, Brigitte; Ahmed el Gendy, Salwa; Delle Karth, Georg; Locker, Gottfried J; Heinz, Gottfried; Jaeger, Walter; Thalhammer, Florian

    2003-01-01

    Flucloxacillin is an important antimicrobial drug in the treatment of infections with Staphylococcus aureus and therefore is often used in staphylococcal infections. Furthermore, flucloxacillin has a high protein binding rate as for example ceftriaxone or teicoplanin--drugs which have formerly been characterized as not being dialyzable. The pharmacokinetic parameters of 4.0 g flucloxacillin every 8 h were examined in 10 intensive care patients during continuous venovenous hemofiltration (CVVH) using a polyamide capillary hemofilter. In addition, the difficulty of calculating the hemofiltration clearance of a highly protein-bound drug is described. Flucloxacillin serum levels were significantly lowered (56.9 +/- 24.0%) even though only 15% of the drug was detected in the ultrafiltrate. Elimination half-life, total body clearance and sieving coefficient were 4.9 +/- 0.7 h, 117.2 +/- 79.1 ml/min and 0.21 +/- 0.09, respectively. These discrepancies can be explained by the high protein binding of flucloxacillin, the adsorbing property of polyamide and the equation in order to calculate hemofiltration clearance. The unbound fraction of a 4.0 g flucloxacillin dosage facilitates time above the minimum inhibitory concentration (T > MIC) of 60% only for strains up to a minimum inhibitory concentration (MIC) of 0.5 mg/l. Based on the data of this study, we conclude that intensive care patients with staphylococcal infections on CVVH should be treated with 4.0 g flucloxacillin every 8 h which was safe and well tolerated. Moreover, further studies with highly protein-bound drugs are recommended to check the classical 'hemodialysis' equation as the standard equation in calculating the CVVH clearance of highly protein-bound drugs. Copyright 2003 S. Karger AG, Basel

  11. Promotion of the transdermal delivery of protein drugs by N-trimethyl chitosan nanoparticles combined with polypropylene electret

    Directory of Open Access Journals (Sweden)

    Tu Y

    2016-10-01

    Full Text Available Ye Tu,1,2,* Xinxia Wang,3,* Ying Lu,2,* He Zhang,2 Yuan Yu,2 Yan Chen,2 Junjie Liu,2 Zhiguo Sun,2 Lili Cui,4 Jing Gao,2 Yanqiang Zhong2 1Department of Medical Affairs, East Hospital, Tongji University School of Medicine, 2Department of Pharmaceutical Science, School of Pharmacy, Second Military Medical University, 3Department of Pharmacy, East Hospital of Hepatobiliary Surgery, 4Department of Inorganic Chemistry, School of Pharmacy, Second Military Medical University, Shanghai, People’s Republic of China *These authors contributed equally to this work Abstract: We recently reported that electret, which was prepared by a corona charging system with polypropylene film, could enhance the transdermal delivery of several drugs of low molecular weight. The aim of this study was to investigate whether electret could enhance the transdermal delivery of protein drugs by N-trimethyl chitosan nanoparticles (TMC NPs prepared by an ionic gelation method. A series of experiments were performed, including in vitro skin permeation assays and anti-inflammatory effects, to evaluate the transdermal delivery of protein drugs by TMC NPs in the presence of electret. The results showed that in the presence of electret, the transdermal delivery of protein drugs in TMC NPs was significantly enhanced, as demonstrated by in vitro permeation studies and confocal laser scanning microscopy. Notably, superoxide dismutase-loaded TMC NPs combined with electret exhibited the best inhibitory effect on the edema of the mouse ear. TMC NPs combined with electret represent a novel platform for the transdermal delivery of protein drugs. Keywords: N-trimethyl chitosan nanoparticles, electret, transdermal delivery, protein drugs 

  12. Molecular modeling of protein materials: case study of elastin

    Science.gov (United States)

    Tarakanova, Anna; Buehler, Markus J.

    2013-09-01

    Molecular modeling of protein materials is a quickly growing area of research that has produced numerous contributions in fields ranging from structural engineering to medicine and biology. We review here the history and methods commonly employed in molecular modeling of protein materials, emphasizing the advantages for using modeling as a complement to experimental work. We then consider a case study of the protein elastin, a critically important ‘mechanical protein’ to exemplify the approach in an area where molecular modeling has made a significant impact. We outline the progression of computational modeling studies that have considerably enhanced our understanding of this important protein which endows elasticity and recoil to the tissues it is found in, including the skin, lungs, arteries and the heart. A vast collection of literature has been directed at studying the structure and function of this protein for over half a century, the first molecular dynamics study of elastin being reported in the 1980s. We review the pivotal computational works that have considerably enhanced our fundamental understanding of elastin's atomistic structure and its extraordinary qualities—focusing on two in particular: elastin's superb elasticity and the inverse temperature transition—the remarkable ability of elastin to take on a more structured conformation at higher temperatures, suggesting its effectiveness as a biomolecular switch. Our hope is to showcase these methods as both complementary and enriching to experimental approaches that have thus far dominated the study of most protein-based materials.

  13. Effects of protein interaction data integration, representation and reliability on the use of network properties for drug target prediction

    Science.gov (United States)

    2012-01-01

    Background Previous studies have noted that drug targets appear to be associated with higher-degree or higher-centrality proteins in interaction networks. These studies explicitly or tacitly make choices of different source databases, data integration strategies, representation of proteins and complexes, and data reliability assumptions. Here we examined how the use of different data integration and representation techniques, or different notions of reliability, may affect the efficacy of degree and centrality as features in drug target prediction. Results Fifty percent of drug targets have a degree of less than nine, and ninety-five percent have a degree of less than ninety. We found that drug targets are over-represented in higher degree bins – this relationship is only seen for the consolidated interactome and it is not dependent on n-ary interaction data or its representation. Degree acts as a weak predictive feature for drug-target status and using more reliable subsets of the data does not increase this performance. However, performance does increase if only cancer-related drug targets are considered. We also note that a protein’s membership in pathway records can act as a predictive feature that is better than degree and that high-centrality may be an indicator of a drug that is more likely to be withdrawn. Conclusions These results show that protein interaction data integration and cleaning is an important consideration when incorporating network properties as predictive features for drug-target status. The provided scripts and data sets offer a starting point for further studies and cross-comparison of methods. PMID:23146171

  14. Effects of protein interaction data integration, representation and reliability on the use of network properties for drug target prediction

    Directory of Open Access Journals (Sweden)

    Mora Antonio

    2012-11-01

    Full Text Available Abstract Background Previous studies have noted that drug targets appear to be associated with higher-degree or higher-centrality proteins in interaction networks. These studies explicitly or tacitly make choices of different source databases, data integration strategies, representation of proteins and complexes, and data reliability assumptions. Here we examined how the use of different data integration and representation techniques, or different notions of reliability, may affect the efficacy of degree and centrality as features in drug target prediction. Results Fifty percent of drug targets have a degree of less than nine, and ninety-five percent have a degree of less than ninety. We found that drug targets are over-represented in higher degree bins – this relationship is only seen for the consolidated interactome and it is not dependent on n-ary interaction data or its representation. Degree acts as a weak predictive feature for drug-target status and using more reliable subsets of the data does not increase this performance. However, performance does increase if only cancer-related drug targets are considered. We also note that a protein’s membership in pathway records can act as a predictive feature that is better than degree and that high-centrality may be an indicator of a drug that is more likely to be withdrawn. Conclusions These results show that protein interaction data integration and cleaning is an important consideration when incorporating network properties as predictive features for drug-target status. The provided scripts and data sets offer a starting point for further studies and cross-comparison of methods.

  15. Spectroscopic study of drug-binding characteristics of unmodified and pNPA-based acetylated human serum albumin: Does esterase activity affect microenvironment of drug binding sites on the protein?

    International Nuclear Information System (INIS)

    Moradi, Nastaran; Ashrafi-Kooshk, Mohammad Reza; Ghobadi, Sirous; Shahlaei, Mohsen; Khodarahmi, Reza

    2015-01-01

    Human serum albumin (HSA) is the most prominent extracellular protein in blood plasma. There are several binding sites on the protein which provide accommodation for structurally-unrelated endogenous and exogenous ligands and a wide variety of drugs. “Esterase-like” activity (hydrolysis of p-nitrophenyl esters) by the protein has been also reported. In the current study, we set out to investigate the interaction of indomethacin and ibuprofen with the unmodified and modified HSA (pNPA-modified HSA) using various spectroscopic techniques. Fluorescence data showed that 1:1 binding of drug to HSA is associated with quenching of the protein intrinsic fluorescence. Decrease of protein surface hydrophobicity (PSH), alteration in drug binding affinity and change of the protein stability, after esterase-like activity and permanent acetylation of HSA, were also documented. Analysis of the quenching and thermodynamic parameters indicated that forces involved in drug–HSA interactions change upon the protein modification. - Highlights: • Binding propensity of indomethacin extremely decreased upon the protein acetylation. • There is no ibuprofen binding after protein acetylation. • Protein stability changes upon drug binding as well as protein acetylation. • Drug pharmacokinetics may be influenced under co-administration of HSA-modifier drugs

  16. Spectroscopic study of drug-binding characteristics of unmodified and pNPA-based acetylated human serum albumin: Does esterase activity affect microenvironment of drug binding sites on the protein?

    Energy Technology Data Exchange (ETDEWEB)

    Moradi, Nastaran [Medical Biology Research Center, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Faculty of Pharmaceutical Sciences, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Ashrafi-Kooshk, Mohammad Reza [Medical Biology Research Center, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Ghobadi, Sirous [Department of Biology, Faculty of Sciences, Razi University, Kermanshah (Iran, Islamic Republic of); Shahlaei, Mohsen [Medical Biology Research Center, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Faculty of Pharmaceutical Sciences, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Khodarahmi, Reza, E-mail: rkhodarahmi@mbrc.ac.ir [Medical Biology Research Center, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Faculty of Pharmaceutical Sciences, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of)

    2015-04-15

    Human serum albumin (HSA) is the most prominent extracellular protein in blood plasma. There are several binding sites on the protein which provide accommodation for structurally-unrelated endogenous and exogenous ligands and a wide variety of drugs. “Esterase-like” activity (hydrolysis of p-nitrophenyl esters) by the protein has been also reported. In the current study, we set out to investigate the interaction of indomethacin and ibuprofen with the unmodified and modified HSA (pNPA-modified HSA) using various spectroscopic techniques. Fluorescence data showed that 1:1 binding of drug to HSA is associated with quenching of the protein intrinsic fluorescence. Decrease of protein surface hydrophobicity (PSH), alteration in drug binding affinity and change of the protein stability, after esterase-like activity and permanent acetylation of HSA, were also documented. Analysis of the quenching and thermodynamic parameters indicated that forces involved in drug–HSA interactions change upon the protein modification. - Highlights: • Binding propensity of indomethacin extremely decreased upon the protein acetylation. • There is no ibuprofen binding after protein acetylation. • Protein stability changes upon drug binding as well as protein acetylation. • Drug pharmacokinetics may be influenced under co-administration of HSA-modifier drugs.

  17. Protein Structure Classification and Loop Modeling Using Multiple Ramachandran Distributions

    KAUST Repository

    Najibi, Seyed Morteza

    2017-02-08

    Recently, the study of protein structures using angular representations has attracted much attention among structural biologists. The main challenge is how to efficiently model the continuous conformational space of the protein structures based on the differences and similarities between different Ramachandran plots. Despite the presence of statistical methods for modeling angular data of proteins, there is still a substantial need for more sophisticated and faster statistical tools to model the large-scale circular datasets. To address this need, we have developed a nonparametric method for collective estimation of multiple bivariate density functions for a collection of populations of protein backbone angles. The proposed method takes into account the circular nature of the angular data using trigonometric spline which is more efficient compared to existing methods. This collective density estimation approach is widely applicable when there is a need to estimate multiple density functions from different populations with common features. Moreover, the coefficients of adaptive basis expansion for the fitted densities provide a low-dimensional representation that is useful for visualization, clustering, and classification of the densities. The proposed method provides a novel and unique perspective to two important and challenging problems in protein structure research: structure-based protein classification and angular-sampling-based protein loop structure prediction.

  18. Computational Modeling of Complex Protein Activity Networks

    NARCIS (Netherlands)

    Schivo, Stefano; Leijten, Jeroen; Karperien, Marcel; Post, Janine N.; Prignet, Claude

    2017-01-01

    Because of the numerous entities interacting, the complexity of the networks that regulate cell fate makes it impossible to analyze and understand them using the human brain alone. Computational modeling is a powerful method to unravel complex systems. We recently described the development of a

  19. A human liver microphysiology platform for investigating physiology, drug safety, and disease models.

    Science.gov (United States)

    Vernetti, Lawrence A; Senutovitch, Nina; Boltz, Robert; DeBiasio, Richard; Shun, Tong Ying; Gough, Albert; Taylor, D Lansing

    2016-01-01

    This paper describes the development and characterization of a microphysiology platform for drug safety and efficacy in liver models of disease that includes a human, 3D, microfluidic, four-cell, sequentially layered, self-assembly liver model (SQL-SAL); fluorescent protein biosensors for mechanistic readouts; as well as a microphysiology system database (MPS-Db) to manage, analyze, and model data. The goal of our approach is to create the simplest design in terms of cells, matrix materials, and microfluidic device parameters that will support a physiologically relevant liver model that is robust and reproducible for at least 28 days for stand-alone liver studies and microfluidic integration with other organs-on-chips. The current SQL-SAL uses primary human hepatocytes along with human endothelial (EA.hy926), immune (U937) and stellate (LX-2) cells in physiological ratios and is viable for at least 28 days under continuous flow. Approximately, 20% of primary hepatocytes and/or stellate cells contain fluorescent protein biosensors (called sentinel cells) to measure apoptosis, reactive oxygen species (ROS) and/or cell location by high content analysis (HCA). In addition, drugs, drug metabolites, albumin, urea and lactate dehydrogenase (LDH) are monitored in the efflux media. Exposure to 180 μM troglitazone or 210 μM nimesulide produced acute toxicity within 2-4 days, whereas 28 μM troglitazone produced a gradual and much delayed toxic response over 21 days, concordant with known mechanisms of toxicity, while 600 µM caffeine had no effect. Immune-mediated toxicity was demonstrated with trovafloxacin with lipopolysaccharide (LPS), but not levofloxacin with LPS. The SQL-SAL exhibited early fibrotic activation in response to 30 nM methotrexate, indicated by increased stellate cell migration, expression of alpha-smooth muscle actin and collagen, type 1, alpha 2. Data collected from the in vitro model can be integrated into a database with access to related

  20. Effect of Silk Protein Processing on Drug Delivery from Silk Films

    Science.gov (United States)

    Pritchard, Eleanor M.; Hu, Xiao; Finley, Violet; Kuo, Catherine K.; Kaplan, David L.

    2013-01-01

    Sericin removal from the core fibroin protein of silkworm silk is a critical first step in the use of silk for biomaterial-related applications, but degumming can affect silk biomaterial properties, including molecular weight, viscosity, diffusivity and degradation behavior. Increasing the degumming time (10, 30, 60 and 90 min) decreases the average molecular weight of silk protein in solution, silk solution viscosity, and silk film glass transition temperature, and increases the rate of degradation of silk film by protease. Model compounds spanning a range of physical-chemical properties generally showed an inverse relationship between degumming time and release rate through a varied degumming time silk coating. Degumming provides a useful control point to manipulate silk’s material properties. PMID:23349062

  1. Markov dynamic models for long-timescale protein motion.

    KAUST Repository

    Chiang, Tsung-Han

    2010-06-01

    Molecular dynamics (MD) simulation is a well-established method for studying protein motion at the atomic scale. However, it is computationally intensive and generates massive amounts of data. One way of addressing the dual challenges of computation efficiency and data analysis is to construct simplified models of long-timescale protein motion from MD simulation data. In this direction, we propose to use Markov models with hidden states, in which the Markovian states represent potentially overlapping probabilistic distributions over protein conformations. We also propose a principled criterion for evaluating the quality of a model by its ability to predict long-timescale protein motions. Our method was tested on 2D synthetic energy landscapes and two extensively studied peptides, alanine dipeptide and the villin headpiece subdomain (HP-35 NleNle). One interesting finding is that although a widely accepted model of alanine dipeptide contains six states, a simpler model with only three states is equally good for predicting long-timescale motions. We also used the constructed Markov models to estimate important kinetic and dynamic quantities for protein folding, in particular, mean first-passage time. The results are consistent with available experimental measurements.

  2. Decreased PARP and procaspase-2 protein levels are associated with cellular drug resistance in childhood acute lymphoblastic leukemia

    NARCIS (Netherlands)

    A. Holleman (Amy); M.L. den Boer (Monique); K.M. Kazemier (Karin); H.B. Beverloo (Berna); A.R.M. von Bergh (Anne); G.E. Janka-Schaub (Gritta); R. Pieters (Rob)

    2005-01-01

    textabstractDrug resistance in childhood acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) is associated with impaired ability to induce apoptosis. To elucidate causes of apoptotic defects, we studied the protein expression of Apaf-1, procaspases-2, -3, -6, -7,

  3. Potentials and limitations of the low-molecular-weight protein lysozyme as a carrier for renal drug targeting

    NARCIS (Netherlands)

    Haverdings, RFG; Haas, M; Greupink, AR; de Vries, PAM; Moolenaar, F; de Zeeuw, D; Meijer, DKF

    2001-01-01

    Selective targeting of drugs to the kidney may enable an increased renal effectiveness combined with a reduction of extrarenal toxicity. Intrarenal delivery to the proximal tubular cell can be achieved using low-molecular-weight proteins, such as lysozyme. Administration of high dosages of lysozyme,

  4. Study on expressions of heat shock 27-associated protein 1 and echinoderm microtubule-associated protein-like 5 in drug-resistant epilepsy

    Directory of Open Access Journals (Sweden)

    CHEN Yun

    2012-10-01

    Full Text Available Objective To observe the expressions of heat shock 27-associated protein 1 (HSPBAP1 and echinoderm microtubule-associated protein-like 5 (EML5 in cerebrospinal fluid of drug-resistant epilepsy, and to explore the value in early diagnosis of epilepsy. Methods According to the inclusion and exclusion criteria, 79 patients admitted in Department of Neurology, Hubei Xinhua Hospital and the First and Second Affiliated Hospital of Chongqing Medical University were divided into drug-resistant epilepsy group (n = 39 and non-epileptic control group (n = 40. Cerebrospinal fluid (every sample 4 ml were collected by lumbar puncture specimens, and HSPBAP1 and EML5 were detected by sandwich enzyme-linked immunosorbent assays. SPSS 13.0 software was used for statistical analysis, and P ≤ 0.05 indicated significant differences. Results The expressions of HSPBAP1 and EML5 were 0.17 ± 0.03 and 0.13 ± 0.02 in drug-resistant epilepsy group, while were 0.10 ± 0.03 and 0.08 ± 0.02 in non-epileptic control group. There was significant difference between 2 groups (t = 3.239, P = 0.002; t = 3.294, P = 0.002, respectively. Conclusion The expressions of HSPBAP1 and EML5 were increased in drug-resistant epilepsy patients. This provides a new way for early diagnosis of drug-resistant epilepsy.

  5. 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.

  6. Model of a DNA-protein complex of the architectural monomeric protein MC1 from Euryarchaea.

    Directory of Open Access Journals (Sweden)

    Françoise Paquet

    Full Text Available In Archaea the two major modes of DNA packaging are wrapping by histone proteins or bending by architectural non-histone proteins. To supplement our knowledge about the binding mode of the different DNA-bending proteins observed across the three domains of life, we present here the first model of a complex in which the monomeric Methanogen Chromosomal protein 1 (MC1 from Euryarchaea binds to the concave side of a strongly bent DNA. In laboratory growth conditions MC1 is the most abundant architectural protein present in Methanosarcina thermophila CHTI55. Like most proteins that strongly bend DNA, MC1 is known to bind in the minor groove. Interaction areas for MC1 and DNA were mapped by Nuclear Magnetic Resonance (NMR data. The polarity of protein binding was determined using paramagnetic probes attached to the DNA. The first structural model of the DNA-MC1 complex we propose here was obtained by two complementary docking approaches and is in good agreement with the experimental data previously provided by electron microscopy and biochemistry. Residues essential to DNA-binding and -bending were highlighted and confirmed by site-directed mutagenesis. It was found that the Arg25 side-chain was essential to neutralize the negative charge of two phosphates that come very close in response to a dramatic curvature of the DNA.

  7. Drug-induced protein free radical formation is attenuated by unsaturated fatty acids by scavenging drug-derived phenyl radical metabolites.

    Science.gov (United States)

    Narwaley, Malyaj; Michail, Karim; Arvadia, Pratik; Siraki, Arno G

    2011-07-18

    Aromatic amine drugs like aminoglutethimide (AG) and related congeners have been shown to produce phenyl radicals through metabolism by myeloperoxidase (MPO)/H(2)O(2), which has been proposed to play a role in drug-induced agranulocytosis. AG has also been shown to induce MPO protein radical formation, but the ultimate fate of these metabolically generated phenyl radicals is still unknown. We tested the reactivity of linoleic acid (LA) and GSH with aniline-based compounds in the presence of horseradish peroxidase (HRP)/H(2)O(2) by measuring oxygen consumption. We found a qualitative correlation between drugs or xenobiotics that formed phenyl radical metabolites with the cooxidation of LA. Most compounds that reacted with LA did not react with GSH. Furthermore, an AG-derived phenyl radical was detected by EPR spin-trapping with MNP (2-methyl-2-nitrosopropane), in a reaction containing AG and HRP/H(2)O(2); these spectra were attenuated in the presence of LA and docosahexaenoic acid (DHA) indicating that phenyl radical scavenging occurred. Since it has been proposed that the phenyl radical metabolite leads to protein radical formation on MPO, we investigated the effect of LA and DHA in immuno-spin trapping experiments with MPO-containing HL-60 cell lysate. Using anti-DMPO, a protein radical was detected on a putative MPO fragment from the reaction of DMPO, AG, and glucose/glucose oxidase. When LA or DHA was included in this reaction, protein radical formation was significantly inhibited. Our results show that certain polyunsaturated fatty acids (PUFAs) act as scavengers of aromatic amine drug-derived phenyl radicals which in turn prevent protein radical formation. However, the interaction of phenyl radical drug metabolites with PUFAs will be dictated by their relative concentrations compared to those of other targets. Most importantly, it is possible to differentiate peroxidase substrates that generate phenyl radical metabolites from N-centered radicals on the basis

  8. Modelling responses of broiler chickens to dietary balanced protein

    NARCIS (Netherlands)

    Eits, R.M.

    2004-01-01

    Protein is an important nutrient for growing broiler chickens, as it affects broiler performance, feed cost as well as nitrogen excretion. The objective of this dissertation was to develop a growth model for broiler chickens that could be easily used by practical nutritionists. The model should

  9. A generative, probabilistic model of local protein structure

    DEFF Research Database (Denmark)

    Boomsma, Wouter; Mardia, Kanti V.; Taylor, Charles C.

    2008-01-01

    conformational stabilities. Here, we present a fully probabilistic, continuous model of local protein structure in atomic detail. The generative model makes efficient conformational sampling possible and provides a framework for the rigorous analysis of local sequence-structure correlations in the native state...

  10. Proteomic and biochemical analyses reveal the activation of unfolded protein response, ERK-1/2 and ribosomal protein S6 signaling in experimental autoimmune myocarditis rat model

    Directory of Open Access Journals (Sweden)

    Kim Chan

    2011-10-01

    Full Text Available Abstract Background To investigate the molecular and cellular pathogenesis underlying myocarditis, we used an experimental autoimmune myocarditis (EAM-induced heart failure rat model that represents T cell mediated postinflammatory heart disorders. Results By performing unbiased 2-dimensional electrophoresis of protein extracts from control rat heart tissues and EAM rat heart tissues, followed by nano-HPLC-ESI-QIT-MS, 67 proteins were identified from 71 spots that exhibited significantly altered expression levels. The majority of up-regulated proteins were confidently associated with unfolded protein responses (UPR, while the majority of down-regulated proteins were involved with the generation of precursor metabolites and energy metabolism in mitochondria. Although there was no difference in AKT signaling between EAM rat heart tissues and control rat heart tissues, the amounts and activities of extracellular signal-regulated kinase (ERK-1/2 and ribosomal protein S6 (rpS6 were significantly increased. By comparing our data with the previously reported myocardial proteome of the Coxsackie viruses of group B (CVB-mediated myocarditis model, we found that UPR-related proteins were commonly up-regulated in two murine myocarditis models. Even though only two out of 29 down-regulated proteins in EAM rat heart tissues were also dysregulated in CVB-infected rat heart tissues, other proteins known to be involved with the generation of precursor metabolites and energy metabolism in mitochondria were also dysregulated in CVB-mediated myocarditis rat heart tissues, suggesting that impairment of mitochondrial functions may be a common underlying mechanism of the two murine myocarditis models. Conclusions UPR, ERK-1/2 and S6RP signaling were activated in both EAM- and CVB-induced myocarditis murine models. Thus, the conserved components of signaling pathways in two murine models of acute myocarditis could be targets for developing new therapeutic drugs or

  11. Exploiting conformational ensembles in modeling protein-protein interactions on the proteome scale

    Science.gov (United States)

    Kuzu, Guray; Gursoy, Attila; Nussinov, Ruth; Keskin, Ozlem

    2013-01-01

    Cellular functions are performed through protein-protein interactions; therefore, identification of these interactions is crucial for understanding biological processes. Recent studies suggest that knowledge-based approaches are more useful than ‘blind’ docking for modeling at large scales. However, a caveat of knowledge-based approaches is that they treat molecules as rigid structures. The Protein Data Bank (PDB) offers a wealth of conformations. Here, we exploited ensemble of the conformations in predictions by a knowledge-based method, PRISM. We tested ‘difficult’ cases in a docking-benchmark dataset, where the unbound and bound protein forms are structurally different. Considering alternative conformations for each protein, the percentage of successfully predicted interactions increased from ~26% to 66%, and 57% of the interactions were successfully predicted in an ‘unbiased’ scenario, in which data related to the bound forms were not utilized. If the appropriate conformation, or relevant template interface, is unavailable in the PDB, PRISM could not predict the interaction successfully. The pace of the growth of the PDB promises a rapid increase of ensemble conformations emphasizing the merit of such knowledge-based ensemble strategies for higher success rates in protein-protein interaction predictions on an interactome-scale. We constructed the structural network of ERK interacting proteins as a case study. PMID:23590674

  12. A Spectral Method for Color Quantitation of a Protein Drug Solution.

    Science.gov (United States)

    Swartz, Trevor E; Yin, Jian; Patapoff, Thomas W; Horst, Travis; Skieresz, Susan M; Leggett, Gordon; Morgan, Charles J; Rahimi, Kimia; Marhoul, Joseph; Kabakoff, Bruce

    2016-01-01

    Color is an important quality attribute for biotherapeutics. In the biotechnology industry, a visual method is most commonly utilized for color characterization of liquid drug protein solutions. The color testing method is used for both batch release and on stability testing for quality control. Using that method, an analyst visually determines the color of the sample by choosing the closest matching European Pharmacopeia reference color solution. The requirement to judge the best match makes it a subjective method. Furthermore, the visual method does not capture data on hue or chroma that would allow for improved product characterization and the ability to detect subtle differences between samples. To overcome these challenges, we describe a quantitative method for color determination that greatly reduces the variability in measuring color and allows for a more precise understanding of color differences. Following color industry standards established by International Commission on Illumination, this method converts a protein solution's visible absorption spectra to L*a*b* color space. Color matching is achieved within the L*a*b* color space, a practice that is already widely used in other industries. The work performed here is to facilitate the adoption and transition for the traditional visual assessment method to a quantitative spectral method. We describe here the algorithm used such that the quantitative spectral method correlates with the currently used visual method. In addition, we provide the L*a*b* values for the European Pharmacopeia reference color solutions required for the quantitative method. We have determined these L*a*b* values by gravimetrically preparing and measuring multiple lots of the reference color solutions. We demonstrate that the visual assessment and the quantitative spectral method are comparable using both low- and high-concentration antibody solutions and solutions with varying turbidity. In the biotechnology industry, a visual

  13. Generalized plasma skimming model for cells and drug carriers in the microvasculature.

    Science.gov (United States)

    Lee, Tae-Rin; Yoo, Sung Sic; Yang, Jiho

    2017-04-01

    In microvascular transport, where both blood and drug carriers are involved, plasma skimming has a key role on changing hematocrit level and drug carrier concentration in capillary beds after continuous vessel bifurcation in the microvasculature. While there have been numerous studies on modeling the plasma skimming of blood, previous works lacked in consideration of its interaction with drug carriers. In this paper, a generalized plasma skimming model is suggested to predict the redistributions of both the cells and drug carriers at each bifurcation. In order to examine its applicability, this new model was applied on a single bifurcation system to predict the redistribution of red blood cells and drug carriers. Furthermore, this model was tested at microvascular network level under different plasma skimming conditions for predicting the concentration of drug carriers. Based on these results, the applicability of this generalized plasma skimming model is fully discussed and future works along with the model's limitations are summarized.

  14. Transport proteins determine drug sensitivity and resistance in a protozoan parasite, Trypanosoma brucei

    Directory of Open Access Journals (Sweden)

    Jane Claire Munday

    2015-03-01

    Full Text Available Drug resistance in pathogenic protozoa is very often caused by changes to the ‘transportome’ of the parasites. In Trypanosoma brucei, several transporters have been implicated in uptake of the main classes of drugs, diamidines and melaminophenyl arsenicals. The resistance mechanism had been thought to be due to loss of a transporter known to carry both types of agents: the aminopurine transporter P2, encoded by the gene TbAT1. However, although loss of P2 activity is well-documented as the cause of resistance to the veterinary diamidine diminazene aceturate (Berenil®, cross-resistance between the human-use arsenical melarsoprol and the diamidine pentamidine (MPXR is the result of loss of a separate High Affinity Pentamidine Transporter (HAPT1. A genome-wide RNAi library screen for resistance to pentamidine, published in 2012, gave the key to the genetic identity of HAPT1 by linking the phenomenon to a locus that contains the closely related T. brucei aquaglyceroporin genes TbAQP2 and TbAQP3. Further analysis determined that knockdown of only one pore, TbAQP2, produced the MPXR phenotype. TbAQP2 is an unconventional aquaglyceroporin with unique residues in the selectivity region of the pore, and it was found that in several MPXR lab strains the WT gene was either absent or replaced by a chimeric protein, recombined with parts of TbAQP3. Importantly, wild-type AQP2 was also absent in field isolates of T. b. gambiense, correlating with the outcome of melarsoprol treatment. Expression of a wild-type copy of TbAQP2 in even the most resistant strain completely reversed MPXR and re-introduced HAPT1 function and transport kinetics. Expression of TbAQP2 in Leishmania mexicana introduced a pentamidine transport activity indistinguishable from HAPT1. Although TbAQP2 has been shown to function as a classical aquaglyceroporin it is now clear that it is also a high affinity drug transporter, HAPT1. We discuss here a possible structural rationale for this

  15. Mass spectrometry-guided optimization and characterization of a biologically active transferrin-lysozyme model drug conjugate.

    Science.gov (United States)

    Nguyen, Son N; Bobst, Cedric E; Kaltashov, Igor A

    2013-05-06

    Transferrin is a promising drug carrier that has the potential to deliver metals, small organic molecules and therapeutic proteins to cancer cells and/or across physiological barriers (such as the blood-brain barrier). Despite this promise, very few transferrin-based therapeutics have been developed and reached clinical trials. This modest success record can be explained by the complexity and heterogeneity of protein conjugation products, which also pose great challenges to their analytical characterization. In this work, we use lysozyme conjugated to transferrin as a model therapeutic that targets the central nervous system (where its bacteriostatic properties may be exploited to control infection) and develop analytical protocols based on electrospray ionization mass spectrometry to characterize its structure and interactions with therapeutic targets and physiological partners critical for its successful delivery. Mass spectrometry has already become an indispensable tool facilitating all stages of the protein drug development process, and this work demonstrates the enormous potential of this technique in facilitating the development of a range of therapeutically effective protein-drug conjugates.

  16. Protein carbonylation, protein aggregation and neuronal cell death in a murine model of multiple sclerosis

    Science.gov (United States)

    Dasgupta, Anushka

    Many studies have suggested that oxidative stress plays an important role in the pathophysiology of both multiple sclerosis (MS) and its animal model experimental autoimmune encephalomyelitis (EAE). Yet, the mechanism by which oxidative stress leads to tissue damage in these disorders is unclear. Recent work from our laboratory has revealed that protein carbonylation, a major oxidative modification caused by severe and/or chronic oxidative stress conditions, is elevated in MS and EAE. Furthermore, protein carbonylation has been shown to alter protein structure leading to misfolding/aggregation. These findings prompted me to hypothesize that carbonylated proteins, formed as a consequence of oxidative stress and/or decreased proteasomal activity, promote protein aggregation to mediate neuronal apoptosis in vitro and in EAE. To test this novel hypothesis, I first characterized protein carbonylation, protein aggregation and apoptosis along the spinal cord during the course of myelin-oligodendrocyte glycoprotein (MOG)35-55 peptide-induced EAE in C57BL/6 mice [Chapter 2]. The results show that carbonylated proteins accumulate throughout the course of the disease, albeit by different mechanisms: increased oxidative stress in acute EAE and decreased proteasomal activity in chronic EAE. I discovered not only that there is a temporal correlation between protein carbonylation and apoptosis but also that carbonyl levels are significantly higher in apoptotic cells. A high number of juxta-nuclear and cytoplasmic protein aggregates containing the majority of the oxidized proteins are also present during the course of EAE, which seems to be due to reduced autophagy. In chapter 3, I show that when gluthathione levels are reduced to those in EAE spinal cord, both neuron-like PC12 (nPC12) cells and primary neuronal cultures accumulate carbonylated proteins and undergo cell death (both by necrosis and apoptosis). Immunocytochemical and biochemical studies also revealed a temporal

  17. Crystal Structure of an Integron Gene Cassette-Associated Protein from Vibrio cholerae Identifies a Cationic Drug-Binding Module

    Energy Technology Data Exchange (ETDEWEB)

    Deshpande, Chandrika N.; Harrop, Stephen J.; Boucher, Yan; Hassan, Karl A.; Di Leo, Rosa; Xu, Xiaohui; Cui, Hong; Savchenko, Alexei; Chang, Changsoo; Labbate, Maurizio; Paulsen, Ian T.; Stokes, H.W.; Curmi, Paul M.G.; Mabbutt, Bridget C. (MIT); (UT-Australia); (Macquarie); (Toronto); (New South)

    2012-02-15

    The direct isolation of integron gene cassettes from cultivated and environmental microbial sources allows an assessment of the impact of the integron/gene cassette system on the emergence of new phenotypes, such as drug resistance or virulence. A structural approach is being exploited to investigate the modularity and function of novel integron gene cassettes. We report the 1.8 {angstrom} crystal structure of Cass2, an integron-associated protein derived from an environmental V. cholerae. The structure defines a monomeric beta-barrel protein with a fold related to the effector-binding portion of AraC/XylS transcription activators. The closest homologs of Cass2 are multi-drug binding proteins, such as BmrR. Consistent with this, a binding pocket made up of hydrophobic residues and a single glutamate side chain is evident in Cass2, occupied in the crystal form by polyethylene glycol. Fluorescence assays demonstrate that Cass2 is capable of binding cationic drug compounds with submicromolar affinity. The Cass2 module possesses a protein interaction surface proximal to its drug-binding cavity with features homologous to those seen in multi-domain transcriptional regulators. Genetic analysis identifies Cass2 to be representative of a larger family of independent effector-binding proteins associated with lateral gene transfer within Vibrio and closely-related species. We propose that the Cass2 family not only has capacity to form functional transcription regulator complexes, but represents possible evolutionary precursors to multi-domain regulators associated with cationic drug compounds.

  18. Crystal structure of an integron gene cassette-associated protein from Vibrio cholerae identifies a cationic drug-binding module.

    Directory of Open Access Journals (Sweden)

    Chandrika N Deshpande

    2011-03-01

    Full Text Available The direct isolation of integron gene cassettes from cultivated and environmental microbial sources allows an assessment of the impact of the integron/gene cassette system on the emergence of new phenotypes, such as drug resistance or virulence. A structural approach is being exploited to investigate the modularity and function of novel integron gene cassettes.We report the 1.8 Å crystal structure of Cass2, an integron-associated protein derived from an environmental V. cholerae. The structure defines a monomeric beta-barrel protein with a fold related to the effector-binding portion of AraC/XylS transcription activators. The closest homologs of Cass2 are multi-drug binding proteins, such as BmrR. Consistent with this, a binding pocket made up of hydrophobic residues and a single glutamate side chain is evident in Cass2, occupied in the crystal form by polyethylene glycol. Fluorescence assays demonstrate that Cass2 is capable of binding cationic drug compounds with submicromolar affinity. The Cass2 module possesses a protein interaction surface proximal to its drug-binding cavity with features homologous to those seen in multi-domain transcriptional regulators.Genetic analysis identifies Cass2 to be representative of a larger family of independent effector-binding proteins associated with lateral gene transfer within Vibrio and closely-related species. We propose that the Cass2 family not only has capacity to form functional transcription regulator complexes, but represents possible evolutionary precursors to multi-domain regulators associated with cationic drug compounds.

  19. In Silico Modeling of Gastrointestinal Drug Absorption: Predictive Performance of Three Physiologically Based Absorption Models.

    Science.gov (United States)

    Sjögren, Erik; Thörn, Helena; Tannergren, Christer

    2016-06-06

    Gastrointestinal (GI) drug absorption is a complex process determined by formulation, physicochemical and biopharmaceutical factors, and GI physiology. Physiologically based in silico absorption models have emerged as a widely used and promising supplement to traditional in vitro assays and preclinical in vivo studies. However, there remains a lack of comparative studies between different models. The aim of this study was to explore the strengths and limitations of the in silico absorption models Simcyp 13.1, GastroPlus 8.0, and GI-Sim 4.1, with respect to their performance in predicting human intestinal drug absorption. This was achieved by adopting an a priori modeling approach and using well-defined input data for 12 drugs associated with incomplete GI absorption and related challenges in predicting the extent of absorption. This approach better mimics the real situation during formulation development where predictive in silico models would be beneficial. Plasma concentration-time profiles for 44 oral drug administrations were calculated by convolution of model-predicted absorption-time profiles and reported pharmacokinetic parameters. Model performance was evaluated by comparing the predicted plasma concentration-time profiles, Cmax, tmax, and exposure (AUC) with observations from clinical studies. The overall prediction accuracies for AUC, given as the absolute average fold error (AAFE) values, were 2.2, 1.6, and 1.3 for Simcyp, GastroPlus, and GI-Sim, respectively. The corresponding AAFE values for Cmax were 2.2, 1.6, and 1.3, respectively, and those for tmax were 1.7, 1.5, and 1.4, respectively. Simcyp was associated with underprediction of AUC and Cmax; the accuracy decreased with decreasing predicted fabs. A tendency for underprediction was also observed for GastroPlus, but there was no correlation with predicted fabs. There were no obvious trends for over- or underprediction for GI-Sim. The models performed similarly in capturing dependencies on dose and

  20. Key factors influencing ADME properties of therapeutic proteins: A need for ADME characterization in drug discovery and development

    Science.gov (United States)

    Tibbitts, Jay; Canter, David; Graff, Ryan; Smith, Alison; Khawli, Leslie A.

    2016-01-01

    abstract Protein therapeutics represent a diverse array of biologics including antibodies, fusion proteins, and therapeutic replacement enzymes. Since their inception, they have revolutionized the treatment of a wide range of diseases including respiratory, vascular, autoimmune, inflammatory, infectious, and neurodegenerative diseases, as well as cancer. While in vivo pharmacokinetic, pharmacodynamic, and efficacy studies are routinely carried out for protein therapeutics, studies that identify key factors governing their absorption, distribution, metabolism, and excretion (ADME) properties have not been fully investigated. Thorough characterization and in-depth study of their ADME properties are critical in order to support drug discovery and development processes for the production of safer and more effective biotherapeutics. In this review, we discuss the main factors affecting the ADME characteristics of these large macromolecular therapies. We also give an overview of the current tools, technologies, and approaches available to investigate key factors that influence the ADME of recombinant biotherapeutic drugs, and demonstrate how ADME studies will facilitate their future development. PMID:26636901

  1. Vaccination via Chloroplast Genetics: Affordable Protein Drugs for the Prevention and Treatment of Inherited or Infectious Human Diseases.

    Science.gov (United States)

    Daniell, Henry; Chan, Hui-Ting; Pasoreck, Elise K

    2016-11-23

    Plastid-made biopharmaceuticals treat major metabolic or genetic disorders, including Alzheimer's, diabetes, hypertension, hemophilia, and retinopathy. Booster vaccines made in chloroplasts prevent global infectious diseases, such as tuberculosis, malaria, cholera, and polio, and biological threats, such as anthrax and plague. Recent advances in this field include commercial-scale production of human therapeutic proteins in FDA-approved cGMP facilities, development of tags to deliver protein drugs to targeted human cells or tissues, methods to deliver precise doses, and long-term stability of protein drugs at ambient temperature, maintaining their efficacy. Codon optimization utilizing valuable information from sequenced chloroplast genomes enhanced expression of eukaryotic human or viral genes in chloroplasts and offered unique insights into translation in chloroplasts. Support from major biopharmaceutical companies, development of hydroponic production systems, and evaluation by regulatory agencies, including the CDC, FDA, and USDA, augur well for advancing this novel concept to the clinic and revolutionizing affordable healthcare.

  2. Illustrating and homology modeling the proteins of the Zika virus [version 2; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Sean Ekins

    2016-09-01

    Full Text Available 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.

  3. Examining a Causal Model of Early Drug Involvement Among Inner City Junior High School Youths.

    Science.gov (United States)

    Dembo, Richard; And Others

    Reflecting the need to construct more inclusive, socially and culturally relevant conceptions of drug use than currently exist, the determinants of drug involvement among inner-city youths within the context of a causal model were investigated. The drug involvement of the Black and Puerto Rican junior high school girls and boys was hypothesized to…

  4. Structural mapping of the ClpB ATPases of Plasmodium falciparum: Targeting protein folding and secretion for antimalarial drug design.

    Science.gov (United States)

    AhYoung, Andrew P; Koehl, Antoine; Cascio, Duilio; Egea, Pascal F

    2015-09-01

    Caseinolytic chaperones and proteases (Clp) belong to the AAA+ protein superfamily and are part of the protein quality control machinery in cells. The eukaryotic parasite Plasmodium falciparum, the causative agent of malaria, has evolved an elaborate network of Clp proteins including two distinct ClpB ATPases. ClpB1 and ClpB2 are involved in different aspects of parasitic proteostasis. ClpB1 is present in the apicoplast, a parasite-specific and plastid-like organelle hosting various metabolic pathways necessary for parasite growth. ClpB2 localizes to the parasitophorous vacuole membrane where it drives protein export as core subunit of a parasite-derived protein secretion complex, the Plasmodium Translocon of Exported proteins (PTEX); this process is central to parasite virulence and survival in the human host. The functional associations of these two chaperones with parasite-specific metabolism and protein secretion make them prime drug targets. ClpB proteins function as unfoldases and disaggregases and share a common architecture consisting of four domains-a variable N-terminal domain that binds different protein substrates, followed by two highly conserved catalytic ATPase domains, and a C-terminal domain. Here, we report and compare the first crystal structures of the N terminal domains of ClpB1 and ClpB2 from Plasmodium and analyze their molecular surfaces. Solution scattering analysis of the N domain of ClpB2 shows that the average solution conformation is similar to the crystalline structure. These structures represent the first step towards the characterization of these two malarial chaperones and the reconstitution of the entire PTEX to aid structure-based design of novel anti-malarial drugs. © 2015 The Protein Society.

  5. An evaluation of the utility of physiologically based models of pharmacokinetics in early drug discovery.

    Science.gov (United States)

    Parrott, Neil; Paquereau, Nicolas; Coassolo, Philippe; Lavé, Thierry

    2005-10-01

    Generic physiologically-based models of pharmacokinetics were evaluated for early drug discovery. Plasma profiles after intravenous and oral dosing were simulated in rat for 68 compounds from six chemical classes. Input data consisted of structure based predictions of lipophilicity, ionization, and protein binding plus intrinsic clearance measured in rat hepatocytes, single measured values of aqueous solubility, and artificial membrane permeability. LogP of compounds was high with a mean of 3.9 while free fraction in plasma (mean 9%) and solubility (mean 37 microg/mL) were low. Predicted and observed clearance and volume showed mean fold-error and R2 of 1.8, 0.56, and 1.9, 0.25 respectively. Predicted bioavailability showed strong bias to under prediction correlated to very low aqueous solubility and a theoretical correction for bile salt solubilization in vivo brought some improvement in average prediction error (to 31%). Overall, this evaluation shows that generic simulation may be applicable for typical drug-like compounds to predict differences in pharmacokinetic parameters of more than twofold based upon minimal measured input data. However verification of the simulations with in vivo data for a few compounds of each compound class is recommended since recent discovery compounds may have properties beyond the scope of the current generic models. Copyright (c) 2005 Wiley-Liss, Inc. and the American Pharmacists Association

  6. Controlled slow release of anticancer drugs from protein-hydrophilic vinyl polymer carriers

    International Nuclear Information System (INIS)

    Asano, Masaharu; Yoshida, Masaru; Kaetsu, Isao

    1982-01-01

    The release behavior has been studied for bleomycin hydrochloride (BLM), an anticancer drug, from carrier composities prepared from mixtures of proteins and hydrophilic vinyl monomers by combined procedures of radiation polymerization and thermal denaturation. The magnitude, Q/tsup(1/2), for BLM release was the smallest when albumin was denatured by thermal treatment after the polymerization of albumin-2-hydroxyethyl methacrylate (HEMA) by radiation at -78 0 C. This retardation was further enhanced by the use of cross-linked polymers. On the other hand, the digestion of the albumin-HEMA composite, during the release test carried out in the saline containing some proteases, was markedly suppressed with increasing the HEMA content in the composite. The digestion was lowered more than expected from the albumin content in the composite. In summary of the release tests and the scanning electron microscopic observations, it was concluded that the release of BLM and the digestion of albumin component contained in the composites can be markedly suppressed by the incorporation of the polymeric component. (author)

  7. Detection and characterisation of multi-drug resistance protein 1 (MRP-1) in human mitochondria.

    Science.gov (United States)

    Roundhill, E A; Burchill, S A

    2012-03-13

    Overexpression of plasma membrane multi-drug resistance protein 1 (MRP-1) can lead to multidrug resistance. In this study, we describe for the first time the expression of mitochondrial MRP-1 in untreated human normal and cancer cells and tissues. MRP-1 expression and subcellular localisation in normal and cancer cells and tissues was examined by differential centrifugation and western blotting, and immunofluorescence microscopy. Viable mitochondria were isolated and MRP-1 efflux activity measured using the calcein-AM functional assay. MRP-1 expression was increased using retroviral infection and specific overexpression confirmed by RNA array. Cell viability was determined by trypan blue exclusion and annexin V-propidium iodide labelling of cells. MRP-1 was detected in the mitochondria of cancer and normal cells and tissues. The efflux activity of mitochondrial MRP-1 was more efficient (55-64%) than that of plasma membrane MRP-1 (11-22%; PMRP-1 expression resulted in a preferential increase in mitochondrial MRP-1, suggesting selective targeting to this organelle. Treatment with a non-lethal concentration of doxorubicin (0.85 nM, 8 h) increased mitochondrial and plasma membrane MRP-1, increasing resistance to MRP-1 substrates. For the first time, we have identified MRP-1 with efflux activity in human mitochondria. Mitochondrial MRP-1 may be an exciting new therapeutic target where historically MRP-1 inhibitor strategies have limited clinical success.

  8. Drug-like density: a method of quantifying the "bindability" of a protein target based on a very large set of pockets and drug-like ligands from the Protein Data Bank.

    Science.gov (United States)

    Sheridan, Robert P; Maiorov, Vladimir N; Holloway, M Katharine; Cornell, Wendy D; Gao, Ying-Duo

    2010-11-22

    One approach to estimating the "chemical tractability" of a candidate protein target where we know the atomic resolution structure is to examine the physical properties of potential binding sites. A number of other workers have addressed this issue. We characterize ~290,000 "pockets" from ~42,000 protein crystal structures in terms of a three parameter "pocket space": volume, buriedness, and hydrophobicity. A metric DLID (drug-like density) measures how likely a pocket is to bind a drug-like molecule. This is calculated from the count of other pockets in its local neighborhood in pocket space that contain drug-like cocrystallized ligands and the count of total pockets in the neighborhood. Surprisingly, despite being defined locally, a global trend in DLID can be predicted by a simple linear regression on log(volume), buriedness, and hydrophobicity. Two levels of simplification are necessary to relate the DLID of individual pockets to "targets": taking the best DLID per Protein Data Bank (PDB) entry (because any given crystal structure can have many pockets), and taking the median DLID over all PDB entries for the same target (because different crystal structures of the same protein can vary because of artifacts and real conformational changes). We can show that median DLIDs for targets that are detectably homologous in sequence are reasonably similar and that median DLIDs correlate with the "druggability" estimate of Cheng et al. (Nature Biotechnology 2007, 25, 71-75).

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

    OpenAIRE

    Pignatello, R.; Musumeci, T.; Basile, L.; Carbone, C.; Puglisi, G.

    2011-01-01

    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 physi...

  10. MDM2 Antagonist Nutlin-3a Reverses Mitoxantrone Resistance by Inhibiting Breast Cancer Resistance Protein Mediated Drug Transport

    Science.gov (United States)

    Zhang, Fan; Throm, Stacy L.; Murley, Laura L.; Miller, Laura A.; Zatechka, D. Steven; Guy, R. Kiplin; Kennedy, Rachel; Stewart, Clinton F.

    2011-01-01

    Breast cancer resistance protein (BCRP; ABCG2), a clinical marker for identifying the side population (SP) cancer stem cell subgroup, affects intestinal absorption, brain penetration, hepatobiliary excretion, and multidrug resistance of many anti-cancer drugs. Nutlin-3a is currently under pre-clinical investigation in a variety of solid tumor and leukemia models as a p53 reactivation agent, and has been recently demonstrated to also have p53 independent actions in cancer cells. In the present study, we first report that nutlin-3a can inhibit the efflux function of BCRP. We observed that although the nutlin-3a IC50 did not differ between BCRP over-expressing and vector control cells, nutlin-3a treatment significantly potentiated the cells to treatment with the BCRP substrate mitoxantrone. Combination index calculations suggested synergism between nutlin-3a and mitoxantrone in cell lines over-expressing BCRP. Upon further investigation, it was confirmed that nutlin-3a increased the intracellular accumulation of BCRP substrates such as mitoxantrone and Hoechst 33342 in cells expressing functional BCRP without altering the expression level or localization of BCRP. Interestingly, nutlin-3b, considered virtually “inactive” in disrupting the MDM2/p53 interaction, reversed Hoechst 33342 efflux with the same potency as nutlin-3a. Intracellular accumulation and bi-directional transport studies using MDCKII cells suggested that nutlin-3a is not a substrate of BCRP. Additionally, an ATPase assay using Sf9 insect cell membranes over-expressing wild-type BCRP indicated that nutlin-3a inhibits BCRP ATPase activity in a dose-dependent fashion. In conclusion, our studies demonstrate that nutlin-3a inhibits BCRP efflux function, which consequently reverses BCRP-related drug resistance. PMID:21459080

  11. An Efficient Null Model for Conformational Fluctuations in Proteins

    DEFF Research Database (Denmark)

    Harder, Tim Philipp; Borg, Mikael; Bottaro, Sandro

    2012-01-01

    Protein dynamics play a crucial role in function, catalytic activity, and pathogenesis. Consequently, there is great interest in computational methods that probe the conformational fluctuations of a protein. However, molecular dynamics simulations are computationally costly and therefore are often...... limited to comparatively short timescales. TYPHON is a probabilistic method to explore the conformational space of proteins under the guidance of a sophisticated probabilistic model of local structure and a given set of restraints that represent nonlocal interactions, such as hydrogen bonds or disulfide...... bridges. The choice of the restraints themselves is heuristic, but the resulting probabilistic model is well-defined and rigorous. Conceptually, TYPHON constitutes a null model of conformational fluctuations under a given set of restraints. We demonstrate that TYPHON can provide information...

  12. Ab initio modeling of small proteins by iterative TASSER simulations

    Directory of Open Access Journals (Sweden)

    Zhang Yang

    2007-05-01

    Full Text Available Abstract Background Predicting 3-dimensional protein structures from amino-acid sequences is an important unsolved problem in computational structural biology. The problem becomes relatively easier if close homologous proteins have been solved, as high-resolution models can be built by aligning target sequences to the solved homologous structures. However, for sequences without similar folds in the Protein Data Bank (PDB library, the models have to be predicted from scratch. Progress in the ab initio structure modeling is slow. The aim of this study was to extend the TASSER (threading/assembly/refinement method for the ab initio modeling and examine systemically its ability to fold small single-domain proteins. Results We developed I-TASSER by iteratively implementing the TASSER method, which is used in the folding test of three benchmarks of small proteins. First, data on 16 small proteins (α-root mean square deviation (RMSD of 3.8Å, with 6 of them having a Cα-RMSD α-RMSD α-RMSD of the I-TASSER models was 3.9Å, whereas it was 5.9Å using TOUCHSTONE-II software. Finally, 20 non-homologous small proteins (α-RMSD of 3.9Å was obtained for the third benchmark, with seven cases having a Cα-RMSD Conclusion Our simulation results show that I-TASSER can consistently predict the correct folds and sometimes high-resolution models for small single-domain proteins. Compared with other ab initio modeling methods such as ROSETTA and TOUCHSTONE II, the average performance of I-TASSER is either much better or is similar within a lower computational time. These data, together with the significant performance of automated I-TASSER server (the Zhang-Server in the 'free modeling' section of the recent Critical Assessment of Structure Prediction (CASP7 experiment, demonstrate new progresses in automated ab initio model generation. The I-TASSER server is freely available for academic users http://zhang.bioinformatics.ku.edu/I-TASSER.

  13. Target-based drug discovery for [Formula: see text]-globin disorders: drug target prediction using quantitative modeling with hybrid functional Petri nets.

    Science.gov (United States)

    Mehraei, Mani; Bashirov, Rza; Tüzmen, Şükrü

    2016-10-01

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

  14. Phase diagram of a model of the protein amelogenin

    Science.gov (United States)

    Haaga, Jason; Pemberton, Elizabeth; Gunton, J. D.; Rickman, J. M.

    2016-08-01

    There has been considerable recent interest in the self-assembly and phase behavior of models of colloidal and protein particles with anisotropic interactions. One example of particular interest is amelogenin, an important protein involved in the formation of dental enamel. Amelogenin is primarily hydrophobic with a 25-residue charged C-terminus tail. This protein undergoes a hierarchical assembly process that is crucial to mineral deposition, and experimental work has demonstrated that the deletion of the C-terminus tail prevents this self-assembly. A simplified model of amelogenin has been proposed in which the protein is treated as a hydrophobic sphere, interacting via the Asakura-Oosawa (AO) potential, with a tethered point charge on its surface. In this paper, we examine the effect of the Coulomb interaction between the point charges in altering the phase diagram of the AO model. For the parameter case specific to amelogenin, we find that the previous in vitro experimental and model conditions correspond to the system being near the low-density edge of the metastable region of the phase diagram. Our study illustrates more generally the importance of understanding the phase diagram for proteins, in that the kinetic pathway for self-assembly and the resulting aggregate morphology depends on the location of the initial state in the phase diagram.

  15. Bayesian Proteoform Modeling Improves Protein Quantification of Global Proteomic Measurements

    Energy Technology Data Exchange (ETDEWEB)

    Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.; Datta, Susmita; Payne, Samuel H.; Kang, Jiyun; Bramer, Lisa M.; Nicora, Carrie D.; Shukla, Anil K.; Metz, Thomas O.; Rodland, Karin D.; Smith, Richard D.; Tardiff, Mark F.; McDermott, Jason E.; Pounds, Joel G.; Waters, Katrina M.

    2014-12-01

    As the capability of mass spectrometry-based proteomics has matured, tens of thousands of peptides can be measured simultaneously, which has the benefit of offering a systems view of protein expression. However, a major challenge is that with an increase in throughput, protein quantification estimation from the native measured peptides has become a computational task. A limitation to existing computationally-driven protein quantification methods is that most ignore protein variation, such as alternate splicing of the RNA transcript and post-translational modifications or other possible proteoforms, which will affect a significant fraction of the proteome. The consequence of this assumption is that statistical inference at the protein level, and consequently downstream analyses, such as network and pathway modeling, have only limited power for biomarker discovery. Here, we describe a Bayesian model (BP-Quant) that uses statistically derived peptides signatures to identify peptides that are outside the dominant pattern, or the existence of multiple over-expressed patterns to improve relative protein abundance estimates. It is a research-driven approach that utilizes the objectives of the experiment, defined in the context of a standard statistical hypothesis, to identify a set of peptides exhibiting similar statistical behavior relating to a protein. This approach infers that changes in relative protein abundance can be used as a surrogate for changes in function, without necessarily taking into account the effect of differential post-translational modifications, processing, or splicing in altering protein function. We verify the approach using a dilution study from mouse plasma samples and demonstrate that BP-Quant achieves similar accuracy as the current state-of-the-art methods at proteoform identification with significantly better specificity. BP-Quant is available as a MatLab ® and R packages at https://github.com/PNNL-Comp-Mass-Spec/BP-Quant.

  16. Domain-Based Predictive Models for Protein-Protein Interaction Prediction

    Directory of Open Access Journals (Sweden)

    Chen Xue-Wen

    2006-01-01

    Full Text Available Protein interactions are of biological interest because they orchestrate a number of cellular processes such as metabolic pathways and immunological recognition. Recently, methods for predicting protein interactions using domain information are proposed and preliminary results have demonstrated their feasibility. In this paper, we develop two domain-based statistical models (neural networks and decision trees for protein interaction predictions. Unlike most of the existing methods which consider only domain pairs (one domain from one protein and assume that domain-domain interactions are independent of each other, the proposed methods are capable of exploring all possible interactions between domains and make predictions based on all the domains. Compared to maximum-likelihood estimation methods, our experimental results show that the proposed schemes can predict protein-protein interactions with higher specificity and sensitivity, while requiring less computation time. Furthermore, the decision tree-based model can be used to infer the interactions not only between two domains, but among multiple domains as well.

  17. Prediction of drug distribution in subcutaneous xenografts of human tumor cell lines and healthy tissues in mouse: application of the tissue composition-based model to antineoplastic drugs.

    Science.gov (United States)

    Poulin, Patrick; Chen, Yung-Hsiang; Ding, Xiao; Gould, Stephen E; Hop, Cornelis Eca; Messick, Kirsten; Oeh, Jason; Liederer, Bianca M

    2015-04-01

    Advanced tissue composition-based models can predict the tissue-plasma partition coefficient (Kp ) values of drugs under in vivo conditions on the basis of in vitro and physiological input data. These models, however, focus on healthy tissues and do not incorporate data from tumors. The objective of this study was to apply a tissue composition-based model to six marketed antineoplastic drugs (docetaxel, DOC; doxorubicin, DOX; gemcitabine, GEM; methotrexate, MTX; topotecan, TOP; and fluorouracil, 5-FU) to predict their Kp values in three human tumor xenografts (HCT-116, H2122, and PC3) as well as in healthy tissues (brain, muscle, lung, and liver) under steady-state in vivo conditions in female NCR nude mice. The mechanisms considered in the tissue/tumor composition-based model are the binding to lipids and to plasma proteins, but the transporter effect was also investigated. The method consisted of analyzing tissue composition, performing the pharmacokinetics studies in mice, and calculating the corresponding in vivo Kp values. Analyses of tumor composition indicated that the tumor xenografts contained no or low amounts of common transporters by contrast to lipids. The predicted Kp values were within twofold and threefold of the measured values in 77% and 93% of cases, respectively. However, predictions for brain for each drug, for liver for MTX, and for each tumor xenograft for GEM were disparate from the observed values, and, therefore, not well served by the model. Overall, this study is the first step toward the mechanism-based prediction of Kp values of small molecules in healthy and tumor tissues in mouse when no transporter and permeation limitation effect is evident. This approach will be useful in selecting compounds based on their abilities to penetrate human cancer xenografts with a physiologically based pharmacokinetic (PBPK) model, thereby increasing therapeutic index for chemotherapy in oncology study. © 2015 Wiley Periodicals, Inc. and the American

  18. Mouse Models of Type 2 Diabetes Mellitus in Drug Discovery.

    Science.gov (United States)

    Baribault, Helene

    2016-01-01

    Type 2 diabetes is a fast-growing epidemic in industrialized countries, associated with obesity, lack of physical exercise, aging, family history, and ethnic background. Diagnostic criteria are elevated fasting or postprandial blood glucose levels, a consequence of insulin resistance. Early intervention can help patients to revert the progression of the disease together with lifestyle changes or monotherapy. Systemic glucose toxicity can have devastating effects leading to pancreatic beta cell failure, blindness, nephropathy, and neuropathy, progressing to limb ulceration or even amputation. Existing treatments have numerous side effects and demonstrate variability in individual patient responsiveness. However, several emerging areas of discovery research are showing promises with the development of novel classes of antidiabetic drugs.The mouse has proven to be a reliable model for discovering and validating new treatments for type 2 diabetes mellitus. We review here commonly used methods to measure endpoints relevant to glucose metabolism which show good translatability to the diagnostic of type 2 diabetes in humans: baseline fasting glucose and insulin, glucose tolerance test, insulin sensitivity index, and body type composition. Improvements on these clinical values are essential for the progression of a novel potential therapeutic molecule through a preclinical and clinical pipeline.

  19. Modelling small-angle scattering data from complex protein-lipid systems

    DEFF Research Database (Denmark)

    Kynde, Søren Andreas Røssell

    the techniques very well suited for the study of the nanodisc system. Chapter 3 explains two different modelling approaches that can be used in the analysis of small-angle scattering data from lipid-protein complexes. These are the continuous approach where the system of interest is modelled as a few regular...... are particularly interesting to study because they are common targets for pharmaceutical drugs. At the same time they are unfortunately unstable in solution which make them challenging to study. Phospholipid nanodiscs are small patches of lipid membrane stabilised by a belt of amphipathic helices. They can act...... as carriers of membrane proteins. Together they form monodisperse soluble aggregates of about 10 nm in size. Chapter 2 introduces the method of small-angle scattering. Small-angle X-ray and neutron scattering are well suited for studying particles in solution on length scales from 1 to 100 nm. This makes...

  20. A simple probabilistic model of multibody interactions in proteins

    DEFF Research Database (Denmark)

    Johansson, Kristoffer Enøe; Hamelryck, Thomas

    2013-01-01

    Protein structure prediction methods typically use statistical potentials, which rely on statistics derived from a database of know protein structures. In the vast majority of cases, these potentials involve pairwise distances or contacts between amino acids or atoms. Although some potentials...... arbitrarily limiting the number of contacts. The success of this approach is based on replacing a naive table-based approach with a simple hierarchical model involving suitable probability distributions and conditional independence assumptions. The model captures the joint probability distribution of an amino...

  1. A graph theoretical perspective of a drug abuse epidemic model

    Science.gov (United States)

    Nyabadza, F.; Mukwembi, S.; Rodrigues, B. G.

    2011-05-01

    A drug use epidemic can be represented by a finite number of states and transition rules that govern the dynamics of drug use in each discrete time step. This paper investigates the spread of drug use in a community where some users are in treatment and others are not in treatment, citing South Africa as an example. In our analysis, we consider the neighbourhood prevalence of each individual, i.e., the proportion of the individual’s drug user contacts who are not in treatment amongst all of his or her contacts. We introduce parameters α∗, β∗ and γ∗, depending on the neighbourhood prevalence, which govern the spread of drug use. We examine how changes in α∗, β∗ and γ∗ affect the system dynamics. Simulations presented support the theoretical results.

  2. Toward the virtual screening of potential drugs in the homology modeled NAD+ dependent DNA ligase from Mycobacterium tuberculosis.

    Science.gov (United States)

    Singh, Vijai; Somvanshi, Pallavi

    2010-02-01

    DNA ligase is an important enzyme and it plays vital role in the replication and repair; also catalyzes nick joining between adjacent bases of DNA. The NAD(+) dependent DNA ligase is selectively present in eubacteria and few viruses; but missing in humans. Homology modeling was used to generate 3-D structure of NAD(+) dependent DNA ligase (LigA) of Mycobacterium tuberculosis using the known template (PDB: 2OWO). Furthermore, the stereochemical quality and torsion angle of 3-D structure was validated. Numerous effective drugs were selected and the active amino acid residue in LigA was targeted and virtual screening through molecular docking was done. In this analysis, four drugs Chloroquine, Hydroxychloroquine, Putrienscine and Adriamycin were found more potent in inhibition of M. tuberculosis through the robust binding affinity between protein-drug interactions in comparison with the other studied drugs. A phylogenetic tree was constructed and it was observed that homology of LigA in M. tuberculosis resembled with other Mycobacterium species. The conserved active amino acids of LigA may be useful to target these drugs. These findings could be used as the starting point of a rational design of novel antibacterial drugs and its analogs.

  3. Testing an explanatory model of nurses' intention to report adverse drug reactions in hospital settings.

    Science.gov (United States)

    Angelis, Alessia De; Pancani, Luca; Steca, Patrizia; Colaceci, Sofia; Giusti, Angela; Tibaldi, Laura; Alvaro, Rosaria; Ausili, Davide; Vellone, Ercole

    2017-05-01

    To test an explanatory model of nurses' intention to report adverse drug reactions in hospital settings, based on the theory of planned behaviour. Under-reporting of adverse drug reactions is an important problem among nurses. A cross-sectional design was used. Data were collected with the adverse drug reporting nurses' questionnaire. Confirmatory factor analysis was performed to test the factor validity of the adverse drug reporting nurses' questionnaire, and structural equation modelling was used to test the explanatory model. The convenience sample comprised 500 Italian hospital nurses (mean age = 43.52). Confirmatory factor analysis supported the factor validity of the adverse drug reporting nurses' questionnaire. The structural equation modelling showed a good fit with the data. Nurses' intention to report adverse drug reactions was significantly predicted by attitudes, subjective norms and perceived behavioural control (R² = 0.16). The theory of planned behaviour effectively explained the mechanisms behind nurses' intention to report adverse drug reactions, showing how several factors come into play. In a scenario of organisational empowerment towards adverse drug reaction reporting, the major predictors of the intention to report are support for the decision to report adverse drug reactions from other health care practitioners, perceptions about the value of adverse drug reaction reporting and nurses' favourable self-assessment of their adverse drug reaction reporting skills. © 2017 John Wiley & Sons Ltd.

  4. Are adolescents more vulnerable to drug addiction than adults? Evidence from animal models.

    Science.gov (United States)

    Schramm-Sapyta, Nicole L; Walker, Q David; Caster, Joseph M; Levin, Edward D; Kuhn, Cynthia M

    2009-09-01

    Epidemiological evidence suggests that people who begin experimenting with drugs of abuse during early adolescence are more likely to develop substance use disorders (SUDs), but this correlation does not guarantee causation. Animal models, in which age of onset can be tightly controlled, offer a platform for testing causality. Many animal models address drug effects that might promote or discourage drug intake and drug-induced neuroplasticity. We have reviewed the preclinical literature to investigate whether adolescent rodents are differentially sensitive to rewarding, reinforcing, aversive, locomotor, and withdrawal-induced effects of drugs of abuse. The rodent model literature consistently suggests that the balance of rewarding and aversive effects of drugs of abuse is tipped toward reward in adolescence. However, increased reward does not consistently lead to increased voluntary intake: age effects on voluntary intake are drug and method specific. On the other hand, adolescents are consistently less sensitive to withdrawal effects, which could protect against compulsive drug seeking. Studies examining neuronal function have revealed several age-related effects but have yet to link these effects to vulnerability to SUDs. Taken together, the findings suggest factors which may promote recreational drug use in adolescents, but evidence relating to pathological drug-seeking behavior is lacking. A call is made for future studies to address this gap using behavioral models of pathological drug seeking and for neurobiologic studies to more directly link age effects to SUD vulnerability.

  5. Recent Advances of Computational Modeling for Predicting Drug Metabolism: A Perspective.

    Science.gov (United States)

    Kar, Supratik; Leszczynski, Jerzy

    2017-01-01

    Absorption, Distribution, Metabolism, Excretion (ADME) properties along with drug induced adverse effects are the major reasons for the late stage failure of drug candidates as well as the cause for the expensive withdrawal of many approved drugs from the market. Considering the adverse effects of drugs, metabolism factor has great importance in medicinal chemistry and clinical pharmacology because it influences the deactivation, activation, detoxification and toxification of drugs. Computational methods are effective approaches to reduce the number of safety issues by analyzing possible links between chemical structures and metabolism followed by adverse effects, as they serve the integration of information on several levels to enhance the reliability of outcomes. In silico profiling of drug metabolism can help progress only those molecules along the discovery chain that is less likely to fail later in the drug discovery process. This positively impacts the very high costs of drug discovery and development. Understanding the science behind computational tools, their opportunities, and limitations is essential to make a true influence on drug discovery at different levels. If applied in a scientifically consequential way, computational tools may improve the capability to identify and evaluate potential drug molecules considering pharmacokinetic properties of drugs. Herein, current trends in computational modeling for predicting drug metabolism are reviewed highlighting new computational tools for drug metabolism prediction followed by reporting large and integrated databases of approved drugs associated with diverse metabolism issues. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  6. Fast Proton Titration Scheme for Multiscale Modeling of Protein Solutions.

    Science.gov (United States)

    Teixeira, Andre Azevedo Reis; Lund, Mikael; da Silva, Fernando Luís Barroso

    2010-10-12

    Proton exchange between titratable amino acid residues and the surrounding solution gives rise to exciting electric processes in proteins. We present a proton titration scheme for studying acid-base equilibria in Metropolis Monte Carlo simulations where salt is treated at the Debye-Hückel level. The method, rooted in the Kirkwood model of impenetrable spheres, is applied on the three milk proteins α-lactalbumin, β-lactoglobulin, and lactoferrin, for which we investigate the net-charge, molecular dipole moment, and charge capacitance. Over a wide range of pH and salt conditions, excellent agreement is found with more elaborate simulations where salt is explicitly included. The implicit salt scheme is orders of magnitude faster than the explicit analog and allows for transparent interpretation of physical mechanisms. It is shown how the method can be expanded to multiscale modeling of aqueous salt solutions of many biomolecules with nonstatic charge distributions. Important examples are protein-protein aggregation, protein-polyelectrolyte complexation, and protein-membrane association.

  7. Validation of protein models by a neural network approach

    Directory of Open Access Journals (Sweden)

    Fantucci Piercarlo

    2008-01-01

    Full Text Available Abstract Background The development and improvement of reliable computational methods designed to evaluate the quality of protein models is relevant in the context of protein structure refinement, which has been recently identified as one of the bottlenecks limiting the quality and usefulness of protein structure prediction. Results In this contribution, we present a computational method (Artificial Intelligence Decoys Evaluator: AIDE which is able to consistently discriminate between correct and incorrect protein models. In particular, the method is based on neural networks that use as input 15 structural parameters, which include energy, solvent accessible surface, hydrophobic contacts and secondary structure content. The results obtained with AIDE on a set of decoy structures were evaluated using statistical indicators such as Pearson correlation coefficients, Znat, fraction enrichment, as well as ROC plots. It turned out that AIDE performances are comparable and often complementary to available state-of-the-art learning-based methods. Conclusion In light of the results obtained with AIDE, as well as its comparison with available learning-based methods, it can be concluded that AIDE can be successfully used to evaluate the quality of protein structures. The use of AIDE in combination with other evaluation tools is expected to further enhance protein refinement efforts.

  8. Fluorinated ionic liquids for protein drug delivery systems: Investigating their impact on the structure and function of lysozyme.

    Science.gov (United States)

    Alves, Márcia; Vieira, Nicole S M; Rebelo, Luís Paulo N; Araújo, João M M; Pereiro, Ana B; Archer, Margarida

    2017-06-30

    Since the approval of recombinant human insulin by FDA in 1982, more than 200 proteins are currently available for pharmaceutical use to treat a wide range of diseases. However, innovation is still required to develop effective approaches for drug delivery. Our aim is to investigate the potential use of fluorinated ionic liquids (FILs) as drug delivery systems (DDS) for therapeutic proteins. Some initial parameters need to be assessed before further studies can proceed. This work evaluates the impact of FILs on the stability, function, structure and aggregation state of lysozyme. Different techniques were used for this purpose, which included differential scanning fluorimetry (DSF), spectrophotometric assays, circular dichroism (CD), dynamic light scattering (DLS), and scanning and transmission electron microscopy (SEM/TEM). Ionic liquids composed of cholinium-, imidazolium- or pyridinium- derivatives were combined with different anions and analysed at different concentrations in aqueous solutions (below and above the critical aggregation concentration, CAC). The results herein presented show that the addition of ionic liquids had no significant effect on the stability and hydrolytic activity of lysozyme. Moreover, a distinct behaviour was observed in DLS experiments for non-surfactant and surfactant ionic liquids, with the latter encapsulating the protein at concentrations above the CAC. These results encourage us to further study ionic liquids as promising tools for DDS of protein drugs. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Ligand mapping on protein surfaces by the 3D-RISM theory: toward computational fragment-based drug design.

    Science.gov (United States)

    Imai, Takashi; Oda, Koji; Kovalenko, Andriy; Hirata, Fumio; Kidera, Akinori

    2009-09-02

    In line with the recent development of fragment-based drug design, a new computational method for mapping of small ligand molecules on protein surfaces is proposed. The method uses three-dimensional (3D) spatial distribution functions of the atomic sites of the ligand calculated using the molecular theory of solvation, known as the 3D reference interaction site model (3D-RISM) theory, to identify the most probable binding modes of ligand molecules. The 3D-RISM-based method is applied to the binding of several small organic molecules to thermolysin, in order to show its efficiency and accuracy in detecting binding sites. The results demonstrate that our method can reproduce the major binding modes found by X-ray crystallographic studies with sufficient precision. Moreover, the method can successfully identify some binding modes associated with a known inhibitor, which could not be detected by X-ray analysis. The dependence of ligand-binding modes on the ligand concentration, which essentially cannot be treated with other existing computational methods, is also investigated. The results indicate that some binding modes are readily affected by the ligand concentration, whereas others are not significantly altered. In the former case, it is the subtle balance in the binding affinity between the ligand and water that determines the dominant ligand-binding mode.

  10. DockQ: A Quality Measure for Protein-Protein Docking Models.

    Directory of Open Access Journals (Sweden)

    Sankar Basu

    Full Text Available The state-of-the-art to assess the structural quality of docking models is currently based on three related yet independent quality measures: Fnat, LRMS, and iRMS as proposed and standardized by CAPRI. These quality measures quantify different aspects of the quality of a particular docking model and need to be viewed together to reveal the true quality, e.g. a model with relatively poor LRMS (>10Å might still qualify as 'acceptable' with a descent Fnat (>0.50 and iRMS (<3.0Å. This is also the reason why the so called CAPRI criteria for assessing the quality of docking models is defined by applying various ad-hoc cutoffs on these measures to classify a docking model into the four classes: Incorrect, Acceptable, Medium, or High quality. This classification has been useful in CAPRI, but since models are grouped in only four bins it is also rather limiting, making it difficult to rank models, correlate with scoring functions or use it as target function in machine learning algorithms. Here, we present DockQ, a continuous protein-protein docking model quality measure derived by combining Fnat, LRMS, and iRMS to a single score in the range [0, 1] that can be used to assess the quality of protein docking models. By using DockQ on CAPRI models it is possible to almost completely reproduce the original CAPRI classification into Incorrect, Acceptable, Medium and High quality. An average PPV of 94% at 90% Recall demonstrating that there is no need to apply predefined ad-hoc cutoffs to classify docking models. Since DockQ recapitulates the CAPRI classification almost perfectly, it can be viewed as a higher resolution version of the CAPRI classification, making it possible to estimate model quality in a more quantitative way using Z-scores or sum of top ranked models, which has been so valuable for the CASP community. The possibility to directly correlate a quality measure to a scoring function has been crucial for the development of scoring functions for

  11. [Changes of urinary proteins in a bacterial meningitis rat model].

    Science.gov (United States)

    Ni, Yanying; Zhang, Fanshuang; An, Manxia; Gao, Youhe

    2017-07-25

    Unlike cerebrospinal fluid or blood, urine accumulates metabolic changes of the body and has the potential to be a promising source of early biomarkers discovery. Bacterial meningitis is a major cause of illness among neonates and children worldwide. In this study, we used Escherichia coli-injected rat model to mimic meningitis and collected urine samples on day 1 and day 3. We used two different methods to digest proteins and analyzed peptides by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). We identified 17 and 20 differential proteins by two methods respectively on day 1, and 5 differential proteins by filter-aided digestion method on day 3. Finding these differential proteins laid a foundation to further explore biomarkers of bacterial meningitis.

  12. Statistical modeling of the drug load distribution on trastuzumab emtansine (Kadcyla), a lysine-linked antibody drug conjugate.

    Science.gov (United States)

    Kim, Michael T; Chen, Yan; Marhoul, Joseph; Jacobson, Fred

    2014-07-16

    Trastuzumab emtansine (Kadcyla) is a recently approved antibody-drug conjugate produced by attachment of the anti-tubulin drug, DM1, to lysine amines via the SMCC linker. The resulting product exhibits a drug load distribution from 0 to 8 drugs per antibody that can be quantified using mass spectrometry. Different statistical models were