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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. Label-free detection of protein biomolecules secreted from a heart-on-a-chip model for drug cardiotoxicity evaluation

    Science.gov (United States)

    DeLuna, Frank; Zhang, Yu Shrike; Bustamante, Gilbert; Li, Le; Lauderdale, Matthew; Dokmeci, Mehmet R.; Khademhosseini, Ali; Ye, Jing Yong

    2018-02-01

    Efficient methods for the accurate analysis of drug toxicities are in urgent demand as failures of newly discovered drug candidates due to toxic side effects have resulted in about 30% of clinical attrition. The high failure rate is partly due to current inadequate models to study drug side effects, i.e., common animal models may fail due to its misrepresentation of human physiology. Therefore, much effort has been allocated in the development of organ-on-a-chip models which offer a variety of human organ models mimicking a multitude of human physiological conditions. However, it is extremely challenging to analyze the transient and long-term response of the organ models to drug treatments during drug toxicity tests, as the proteins secreted from the organ-on-a-chip model are minute due to its volumetric size, and current methods for detecting said biomolecules are not suitable for real-time monitoring. As protein biomolecules are being continuously secreted from the human organ model, fluorescence techniques are practically impossible to achieve real-time fluorescence labeling in the dynamically changing environment, thus making a label-free approach highly desirable for the organ-on-achip applications. In this paper, we report the use of a photonic-crystal biosensor integrated with a microfluidic system for sensitive label-free bioassays of secreted protein biomolecules from a heart-on-the-chip model created with cardiomyocytes derived from human induced pluripotent stem cells.

  3. A Physiologically Based Pharmacokinetic Model to Predict the Pharmacokinetics of Highly Protein-Bound Drugs and Impact of Errors in Plasma Protein Binding

    Science.gov (United States)

    Ye, Min; Nagar, Swati; Korzekwa, Ken

    2015-01-01

    Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data was often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding, and blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for terminal elimination half-life (t1/2, 100% of drugs), peak plasma concentration (Cmax, 100%), area under the plasma concentration-time curve (AUC0–t, 95.4%), clearance (CLh, 95.4%), mean retention time (MRT, 95.4%), and steady state volume (Vss, 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. PMID:26531057

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

    Science.gov (United States)

    Ye, Min; Nagar, Swati; Korzekwa, Ken

    2016-04-01

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

  5. Nanostructures for protein drug delivery.

    Science.gov (United States)

    Pachioni-Vasconcelos, Juliana de Almeida; Lopes, André Moreni; Apolinário, Alexsandra Conceição; Valenzuela-Oses, Johanna Karina; Costa, Juliana Souza Ribeiro; Nascimento, Laura de Oliveira; Pessoa, Adalberto; Barbosa, Leandro Ramos Souza; Rangel-Yagui, Carlota de Oliveira

    2016-02-01

    Use of nanoscale devices as carriers for drugs and imaging agents has been extensively investigated and successful examples can already be found in therapy. In parallel, recombinant DNA technology together with molecular biology has opened up numerous possibilities for the large-scale production of many proteins of pharmaceutical interest, reflecting in the exponentially growing number of drugs of biotechnological origin. When we consider protein drugs, however, there are specific criteria to take into account to select adequate nanostructured systems as drug carriers. In this review, we highlight the main features, advantages, drawbacks and recent developments of nanostructures for protein encapsulation, such as nanoemulsions, liposomes, polymersomes, single-protein nanocapsules and hydrogel nanoparticles. We also discuss the importance of nanoparticle stabilization, as well as future opportunities and challenges in nanostructures for protein drug delivery.

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

    KAUST Repository

    Phelan, Jody

    2016-01-01

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

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

    KAUST Repository

    Phelan, Jody

    2016-03-23

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

  8. Drug-protein interactions assessed by fluorescence measurements in the real complexes and in model dyads

    Science.gov (United States)

    Vayá, Ignacio; Pérez-Ruiz, Raúl; Lhiaubet-Vallet, Virginie; Jiménez, M. Consuelo; Miranda, Miguel A.

    2010-02-01

    In the present work, a systematic fluorescence study on supramolecular systems using two serum albumins (HSA or BSA) as hosts and the nonsteroidal antiinflammatory drugs carprofen (CPF) or naproxen (NPX) as guests has been undertaken. In parallel, model dyads containing Tyr or Trp covalently linked to CPF or NPX have also been investigated. In HSA/(S)-CPF and BSA/(S)-CPF ( λexc = 266 nm), at 1:1 M ratio, an important degree (more than 40%) of singlet-singlet energy transfer (SSET) was observed to take place. The distance ( r) calculated for energy transfer from the SAs to (S)-CPF through a FRET mechanism was found to be ca. 21 Å. In the case of HSA/(S)-NPX and BSA/(S)-NPX, energy transfer occurred to a lower extent (ca. 7%), and r was determined as ca. 24 Å. In order to investigate the possible excited state interactions between bound ligands and the relevant amino acids present in the protein binding sites, four pairs of model dyads were designed and synthesised, namely ( S, S)-TyrCPF, ( S, R)-TyrCPF, ( S, S)-TrpCPF, ( S, R)-TrpCPF, ( S, S)-TyrNPX, ( S, R)-TyrNPX, ( S, S)-TrpNPX and ( S, R)-TrpNPX. A complete SSET was observed from Tyr or Trp to CPF, since no contribution from the amino acids was present in the emission of the dyads. Likewise, a very efficient Tyr or Trp to NPX energy transfer was observed. Remarkably, in ( S, S)-TrpNPX and ( S, R)-TrpNPX a configuration-dependent reduction in the emission intensity was observed, revealing a strong and stereoselective intramolecular quenching. This effect can be attributed to exciplex formation and is dynamic in nature, as the fluorescence lifetimes were much shorter in ( S, R)- and ( S, S)-TrpNPX (1.5 and 3.1 ns, respectively) than in (S)-NPX (11 ns).

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

    KAUST Repository

    Phelan, Jody; Coll, Francesc; McNerney, Ruth; Ascher, David; Pires, Douglas; Furnham, Nick; Coeck, Nele; Hill-Cawthorne, Grant; Nair, Mridul; Mallard, Kim; Ramsay, Andrew; Campino, Susana; Hibberd, Martin; Pain, Arnab; Rigouts, Leen; Clark, Taane

    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

  10. Recombinant Amphiphilic Protein Micelles for Drug Delivery

    OpenAIRE

    Kim, Wookhyun; Xiao, Jiantao; Chaikof, Elliot L.

    2011-01-01

    Amphiphilic block polypeptides can self-assemble into a range of nanostructures in solution, including micelles and vesicles. Our group has recently described the capacity of recombinant amphiphilic diblock copolypeptides to form highly stable micelles. In this report, we demonstrate the utility of protein nanoparticles to serve as a vehicle for controlled drug delivery. Drug-loaded micelles were produced by encapsulating dipyridamole as a model hydrophobic drug with anti-inflammatory activit...

  11. Development of a green fluorescent protein metastatic-cancer chick-embryo drug-screen model.

    Science.gov (United States)

    Bobek, Vladimir; Plachy, Jiri; Pinterova, Daniela; Kolostova, Katarina; Boubelik, Michael; Jiang, Ping; Yang, Meng; Hoffman, Robert M

    2004-01-01

    The chick-embryo model has been an important tool to study tumor growth, metastasis, and angiogenesis. However, an imageable model with a genetic fluorescent tag in the growing and spreading cancer cells that is stable over time has not been developed. We report here the development of such an imageable fluorescent chick-embryo metastatic cancer model with the use of green fluorescent protein (GFP). Lewis lung carcinoma cells, stably expressing GFP, were injected on the 12th day of incubation in the chick embryo. GFP-Lewis lung carcinoma metastases were visualized by fluorescence, after seven days additional incubation, in the brain, heart, and sternum of the developing chick embryo, with the most frequent site being the brain. The combination of streptokinase and gemcitabine was evaluated in this GFP metastatic model. Twelve-day-old chick embryos were injected intravenously with GFP-Lewis lung cancer cells, along with these two agents either alone or in combination. The streptokinase-gemcitabine combination inhibited metastases at all sites. The effective dose of gemcitabine was found to be 10 mg/kg and streptokinase 2000 IU per embryo. The data in this report suggest that this new stably fluorescent imageable metastatic-cancer chick-embryo model will enable rapid screening of new antimetastatic agents.

  12. 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.

  13. 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.

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

    Science.gov (United States)

    Verkhivker, Gennady M

    2016-01-01

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

  15. 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.

  16. Modeling and protein engineering studies of active and inactive states of human dopamine D2 receptor (D2R) and investigation of drug/receptor interactions.

    Science.gov (United States)

    Salmas, Ramin Ekhteiari; Yurtsever, Mine; Stein, Matthias; Durdagi, Serdar

    2015-05-01

    Homology model structures of the dopamine D2 receptor (D2R) were generated starting from the active and inactive states of β2-adrenergic crystal structure templates. To the best of our knowledge, the active conformation of D2R was modeled for the first time in this study. The homology models are built and refined using MODELLER and ROSETTA programs. Top-ranked models have been validated with ligand docking simulations and in silico Alanine-scanning mutagenesis studies. The derived extra-cellular loop region of the protein models is directed toward the binding site cavity which is often involved in ligand binding. The binding sites of protein models were refined using induced fit docking to enable the side-chain refinement during ligand docking simulations. The derived models were then tested using molecular modeling techniques on several marketed drugs for schizophrenia. Alanine-scanning mutagenesis and molecular docking studies gave similar results for marketed drugs tested. We believe that these new D2 receptor models will be very useful for a better understanding of the mechanisms of action of drugs to be targeted to the binding sites of D2Rs and they will contribute significantly to drug design studies involving G-protein-coupled receptors in the future.

  17. A knowledge-based approach for identification of drugs against vivapain-2 protein of Plasmodium vivax through pharmacophore-based virtual screening with comparative modelling.

    Science.gov (United States)

    Yadav, Manoj Kumar; Singh, Amisha; Swati, D

    2014-08-01

    Malaria is one of the most infectious diseases in the world. Plasmodium vivax, the pathogen causing endemic malaria in humans worldwide, is responsible for extensive disease morbidity. Due to the emergence of resistance to common anti-malarial drugs, there is a continuous need to develop a new class of drugs for this pathogen. P. vivax cysteine protease, also known as vivapain-2, plays an important role in haemoglobin hydrolysis and is considered essential for the survival of the parasite. The three-dimensional (3D) structure of vivapain-2 is not predicted experimentally, so its structure is modelled by using comparative modelling approach and further validated by Qualitative Model Energy Analysis (QMEAN) and RAMPAGE tools. The potential binding site of selected vivapain-2 structure has been detected by grid-based function prediction method. Drug targets and their respective drugs similar to vivapain-2 have been identified using three publicly available databases: STITCH 3.1, DrugBank and Therapeutic Target Database (TTD). The second approach of this work focuses on docking study of selected drug E-64 against vivapain-2 protein. Docking reveals crucial information about key residues (Asn281, Cys283, Val396 and Asp398) that are responsible for holding the ligand in the active site. The similarity-search criterion is used for the preparation of our in-house database of drugs, obtained from filtering the drugs from the DrugBank database. A five-point 3D pharmacophore model is generated for the docked complex of vivapain-2 with E-64. This study of 3D pharmacophore-based virtual screening results in identifying three new drugs, amongst which one is approved and the other two are experimentally proved. The ADMET properties of these drugs are found to be in the desired range. These drugs with novel scaffolds may act as potent drugs for treating malaria caused by P. vivax.

  18. Vaginal drug distribution modeling.

    Science.gov (United States)

    Katz, David F; Yuan, Andrew; Gao, Yajing

    2015-09-15

    This review presents and applies fundamental mass transport theory describing the diffusion and convection driven mass transport of drugs to the vaginal environment. It considers sources of variability in the predictions of the models. It illustrates use of model predictions of microbicide drug concentration distribution (pharmacokinetics) to gain insights about drug effectiveness in preventing HIV infection (pharmacodynamics). The modeling compares vaginal drug distributions after different gel dosage regimens, and it evaluates consequences of changes in gel viscosity due to aging. It compares vaginal mucosal concentration distributions of drugs delivered by gels vs. intravaginal rings. Finally, the modeling approach is used to compare vaginal drug distributions across species with differing vaginal dimensions. Deterministic models of drug mass transport into and throughout the vaginal environment can provide critical insights about the mechanisms and determinants of such transport. This knowledge, and the methodology that obtains it, can be applied and translated to multiple applications, involving the scientific underpinnings of vaginal drug distribution and the performance evaluation and design of products, and their dosage regimens, that achieve it. Copyright © 2015 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

    Christophersen, Philip Carsten; Fano, Mathias; Saaby, Lasse; Yang, Mingshi; Nielsen, Hanne Mørck; Mu, Huiling

    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 are summarized. Additionally, the paper provides an overview of recent studies on characterization of solid drug carriers for peptide/protein drugs, drug distribution in particles, drug release and stability in simulated GI fluids, as well as the absorption of peptide/protein drugs in cell-based models. The use of biorelevant media when applicable can increase the knowledge about the quality of DDS for oral protein delivery. Hopefully, the knowledge provided in this review will aid the establishment of improved biorelevant models capable of forecasting the performance of particulate DDS for oral peptide/protein delivery.

  20. Structural modelling and comparative analysis of homologous, analogous and specific proteins from Trypanosoma cruzi versus Homo sapiens: putative drug targets for chagas' disease treatment.

    Science.gov (United States)

    Capriles, Priscila V S Z; Guimarães, Ana C R; Otto, Thomas D; Miranda, Antonio B; Dardenne, Laurent E; Degrave, Wim M

    2010-10-29

    Trypanosoma cruzi is the etiological agent of Chagas' disease, an endemic infection that causes thousands of deaths every year in Latin America. Therapeutic options remain inefficient, demanding the search for new drugs and/or new molecular targets. Such efforts can focus on proteins that are specific to the parasite, but analogous enzymes and enzymes with a three-dimensional (3D) structure sufficiently different from the corresponding host proteins may represent equally interesting targets. In order to find these targets we used the workflows MHOLline and AnEnΠ obtaining 3D models from homologous, analogous and specific proteins of Trypanosoma cruzi versus Homo sapiens. We applied genome wide comparative modelling techniques to obtain 3D models for 3,286 predicted proteins of T. cruzi. In combination with comparative genome analysis to Homo sapiens, we were able to identify a subset of 397 enzyme sequences, of which 356 are homologous, 3 analogous and 38 specific to the parasite. In this work, we present a set of 397 enzyme models of T. cruzi that can constitute potential structure-based drug targets to be investigated for the development of new strategies to fight Chagas' disease. The strategies presented here support the concept of structural analysis in conjunction with protein functional analysis as an interesting computational methodology to detect potential targets for structure-based rational drug design. For example, 2,4-dienoyl-CoA reductase (EC 1.3.1.34) and triacylglycerol lipase (EC 3.1.1.3), classified as analogous proteins in relation to H. sapiens enzymes, were identified as new potential molecular targets.

  1. Protein-Based Drug-Delivery Materials

    OpenAIRE

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

    2017-01-01

    There is a pressing need for long-term, controlled drug release for sustained treatment of chronic or persistent medical conditions and diseases. Guided drug delivery is difficult because therapeutic compounds need to survive numerous transport barriers and binding targets throughout the body. Nanoscale protein-based polymers are increasingly used for drug and vaccine delivery to cross these biological barriers and through blood circulation to their molecular site of action. Protein-based pol...

  2. 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.

  3. 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.

  4. Properties of Protein Drug Target Classes

    Science.gov (United States)

    Bull, Simon C.; Doig, Andrew J.

    2015-01-01

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

  5. Targeted Delivery of Protein Drugs by Nanocarriers

    Directory of Open Access Journals (Sweden)

    Antonella Battisti

    2010-03-01

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

  6. 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.

  7. 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...

  8. 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.

  9. Protein-Protein Docking in Drug Design and Discovery.

    Science.gov (United States)

    Kaczor, Agnieszka A; Bartuzi, Damian; Stępniewski, Tomasz Maciej; Matosiuk, Dariusz; Selent, Jana

    2018-01-01

    Protein-protein interactions (PPIs) are responsible for a number of key physiological processes in the living cells and underlie the pathomechanism of many diseases. Nowadays, along with the concept of so-called "hot spots" in protein-protein interactions, which are well-defined interface regions responsible for most of the binding energy, these interfaces can be targeted with modulators. In order to apply structure-based design techniques to design PPIs modulators, a three-dimensional structure of protein complex has to be available. In this context in silico approaches, in particular protein-protein docking, are a valuable complement to experimental methods for elucidating 3D structure of protein complexes. Protein-protein docking is easy to use and does not require significant computer resources and time (in contrast to molecular dynamics) and it results in 3D structure of a protein complex (in contrast to sequence-based methods of predicting binding interfaces). However, protein-protein docking cannot address all the aspects of protein dynamics, in particular the global conformational changes during protein complex formation. In spite of this fact, protein-protein docking is widely used to model complexes of water-soluble proteins and less commonly to predict structures of transmembrane protein assemblies, including dimers and oligomers of G protein-coupled receptors (GPCRs). In this chapter we review the principles of protein-protein docking, available algorithms and software and discuss the recent examples, benefits, and drawbacks of protein-protein docking application to water-soluble proteins, membrane anchoring and transmembrane proteins, including GPCRs.

  10. 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.

  11. 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.

  12. 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.

  13. 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)

  14. 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

  15. 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.

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

    Science.gov (United States)

    2014-06-20

    studies that have reported antimalarial activities of azole compounds [39-43] lend support to our model predictions. The highest-scored non-malarial...Table 4, verapamil and cimetidine, do not have antimal- arial activities themselves but exhibit synergism when used in combination with antimalarial ... activators . Because of their high frequencies among the antimalarial drugs, according to Eq. 3, the drug-protein interactions contributing most to the

  17. Clinical relevance of drug binding to plasma proteins

    Science.gov (United States)

    Ascenzi, Paolo; Fanali, Gabriella; Fasano, Mauro; Pallottini, Valentina; Trezza, Viviana

    2014-12-01

    Binding to plasma proteins highly influences drug efficacy, distribution, and disposition. Serum albumin, the most abundant protein in plasma, is a monomeric multi-domain macromolecule that displays an extraordinary ligand binding capacity, providing a depot and carrier for many endogenous and exogenous compounds, such as fatty acids and most acidic drugs. α-1-Acid glycoprotein, the second main plasma protein, is a glycoprotein physiologically involved in the acute phase reaction and is the main carrier for basic and neutral drugs. High- and low-density lipoproteins play a limited role in drug binding and are natural drug delivery system only for few lipophilic drugs or lipid-based formulations. Several factors influence drug binding to plasma proteins, such as pathological conditions, concurrent administration of drugs, sex, and age. Any of these factors, in turn, influences drug efficacy and toxicity. Here, biochemical, biomedical, and biotechnological aspects of drug binding to plasma proteins are reviewed.

  18. 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

  19. Peptide and protein delivery using new drug delivery systems.

    Science.gov (United States)

    Jain, Ashish; Jain, Aviral; Gulbake, Arvind; Shilpi, Satish; Hurkat, Pooja; Jain, Sanjay K

    2013-01-01

    Pharmaceutical and biotechnological research sorts protein drug delivery systems by importance based on their various therapeutic applications. The effective and potent action of the proteins/peptides makes them the drugs of choice for the treatment of numerous diseases. Major research issues in protein delivery include the stabilization of proteins in delivery devices and the design of appropriate target-specific protein carriers. Many efforts have been made for effective delivery of proteins/peptidal drugs through various routes of administrations for successful therapeutic effects. Nanoparticles made of biodegradable polymers such as poly lactic acid, polycaprolactone, poly(lactic-co-glycolic acid), the poly(fumaric-co-sebacic) anhydride chitosan, and modified chitosan, as well as solid lipids, have shown great potential in the delivery of proteins/peptidal drugs. Moreover, scientists also have used liposomes, PEGylated liposomes, niosomes, and aquasomes, among others, for peptidal drug delivery. They also have developed hydrogels and transdermal drug delivery systems for peptidal drug delivery. A receptor-mediated delivery system is another attractive strategy to overcome the limitation in drug absorption that enables the transcytosis of the protein across the epithelial barrier. Modification such as PEGnology is applied to various proteins and peptides of the desired protein and peptides also increases the circulating life, solubility and stability, pharmacokinetic properties, and antigenicity of protein. This review focuses on various approaches for effective protein/peptidal drug delivery, with special emphasis on insulin delivery.

  20. Functionalization of protein-based nanocages for drug delivery applications.

    Science.gov (United States)

    Schoonen, Lise; van Hest, Jan C M

    2014-07-07

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

  1. 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

  2. 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.

  3. 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.

  4. 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....

  5. 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.

  6. 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.

  7. 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.

  8. Protein Complex Production from the Drug Discovery Standpoint.

    Science.gov (United States)

    Moarefi, Ismail

    2016-01-01

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

  9. Development of a keratinocyte-based screening model for antipsoriatic drugs using green fluorescent protein under the control of an endogenous promoter.

    Science.gov (United States)

    Pol, Arno; van Ruissen, Fred; Schalkwijk, Joost

    2002-08-01

    Inflamed epidermis (psoriasis, wound healing, ultraviolet-irradiated skin) harbors keratinocytes that are hyperproliferative and display an abnormal differentiation program. A distinct feature of this so-called regenerative maturation pathway is the expression of proteins such as the cytokeratins CK6, CK16, and CK17 and the antiinflammatory protein SKALP/elafin. These proteins are absent in normal skin but highly induced in lesional psoriatic skin. Expression of these genes can be used as a surrogate marker for psoriasis in drug-screening procedures of large compound libraries. The aim of this study was to develop a keratinocyte cell line that contained a reporter gene under the control of a psoriasis-associated endogenous promoter and demonstrate its use in an assay suitable for screening. We generated a stably transfected keratinocyte cell line that expresses enhanced green fluorescent protein (EGFP), under the control of a 0.8-kb fragment derived from the promoter of the SKALP/elafin gene, which confers high levels of tissue-specific expression at the mRNA level. Induction of the SKALP promoter by tumor necrosis factor-alpha resulted in increased expression levels of the secreted SKALP-EGFP fusion protein as assessed by direct readout of fluorescence and fluorescence polarization in 96-well cell culture plates. The fold stimulation of the reporter gene was comparable to that of the endogenous SKALP gene as assessed by enzyme-linked immunosorbent assay. Although the dynamic range of the screening system is limited, the small standard deviation yields a Z factor of 0.49. This indicates that the assay is suitable as a high-throughput screen, and provides proof of the concept that a secreted EGFP fusion protein under the control of a physiologically relevant endogenous promoter can be used as a fluorescence-based high-throughput screen for differentiation-modifying or antiinflammatory compounds that act via the keratinocyte.

  10. 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

  11. The transport of nifurtimox, an anti-trypanosomal drug, in an in vitro model of the human blood-brain barrier: evidence for involvement of breast cancer resistance protein.

    Science.gov (United States)

    Watson, Christopher P; Dogruel, Murat; Mihoreanu, Larisa; Begley, David J; Weksler, Babette B; Couraud, Pierre O; Romero, Ignacio A; Thomas, Sarah A

    2012-02-03

    Human African trypanosomiasis (HAT) is a parasitic disease affecting sub-Saharan Africa. The parasites are able to traverse the blood-brain barrier (BBB), which marks stage 2 (S2) of the disease. Delivery of anti-parasitic drugs across the BBB is key to treating S2 effectively and the difficulty in achieving this goal is likely to be a reason why some drugs require highly intensive treatment regimes to be effective. This study aimed to investigate not only the drug transport mechanisms utilised by nifurtimox at the BBB, but also the impact of nifurtimox-eflornithine combination therapy (NECT) and other anti-HAT drug combination therapies (CTs) on radiolabelled-nifurtimox delivery in an in vitro model of drug accumulation and the human BBB, the hCMEC/D3 cell line. We found that nifurtimox appeared to use several membrane transporters, in particular breast-cancer resistance protein (BCRP), to exit the BBB cells. The addition of eflornithine caused no change in the accumulation of nifurtimox, nor did the addition of clinically relevant doses of the other anti-HAT drugs suramin, nifurtimox or melarsoprol, but a significant increase was observed with the addition of pentamidine. The results provide evidence that anti-HAT drugs are interacting with membrane transporters at the human BBB and suggest that combination with known transport inhibitors could potentially improve their efficacy. Copyright © 2011 Elsevier B.V. All rights reserved.

  12. Multidrug and toxin extrusion proteins as transporters of antimicrobial drugs.

    Science.gov (United States)

    Nies, Anne T; Damme, Katja; Schaeffeler, Elke; Schwab, Matthias

    2012-12-01

    Antimicrobial drugs are essential in the treatment of infectious diseases. A better understanding of transport processes involved in drug disposition will improve the predictability of drug-drug interactions with consequences for drug response. Multidrug And Toxin Extrusion (MATE; SLC47A) proteins are efflux transporters mediating the excretion of several antimicrobial drugs as well as other organic compounds into bile and urine, thereby contributing to drug disposition. This review summarizes current knowledge of the structural and molecular features of human MATE transporters including their functional role in drug transport with a specific focus on antimicrobial drugs. The PubMed database was searched using the terms "MATE1," "MATE-2K," "MATE2," "SLC47A1," "SLC47A2," and "toxin extrusion protein" (up to June 2012). MATE proteins have been recognized as important transporters mediating the final excretion step of cationic drugs into bile and urine. These include the antiviral drugs acyclovir, amprenavir, and ganciclovir, the antibiotics cephalexin, cephradine and levofloxacin, as well as the antimalarial agents chloroquine and quinine. It is therefore important to enhance our understanding of the role of MATEs in drug extrusion with particular emphasis on the functional consequences of genetic variants on disposition of these antimicrobial drugs.

  13. Construction and characterization of a pure protein hydrogel for drug delivery application.

    Science.gov (United States)

    Xu, Xu; Xu, ZhaoKang; Yang, XiaoFeng; He, YanHao; Lin, Rong

    2017-02-01

    Injectable hydrogels have a variety of applications, including regenerative medicine, tissue engineering and controlled drug delivery. In this paper, we reported on a pure protein hydrogel based on tetrameric recombinant proteins for the potential drug delivery application. This protein hydrogel was formed instantly by simply mixing two recombinant proteins (ULD-TIP1 and ULD-GGGWRESAI) through the specific protein-peptide interaction. The protein hydrogel was characterized by rheology and scanning electron microscopy (SEM). In vitro cytotoxicity test indicated that the developed protein hydrogel had no apparent cytotoxicity against L-929 cells and HCEC cells after 48h incubation. The formed protein hydrogels was gradually degraded after incubation in phosphate buffered solution (PBS, pH=7.4) for a period of 144h study, as indicated by in vitro degradation test. Encapsulation of model drug (sodium diclofenac; DIC) were achieved by simple mixing of drugs with hydrogelator and the entrapped drugs was almost completely released from hydrogels within 24h via a diffusion manner. As a conclusion, the simple and mild preparation procedure and good biocompatibility of protein hydrogel would render its good promising candidate for drug delivery applications. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. 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.

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

    Science.gov (United States)

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

    2014-01-01

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

  16. Phenylketonuria as a model for protein misfolding diseases and for the development of next generation orphan drugs for patients with inborn errors of metabolism.

    Science.gov (United States)

    Muntau, Ania C; Gersting, Søren W

    2010-12-01

    The lecture dedicated to Professor Horst Bickel describes the advances, successes, and opportunities concerning the understanding of the biochemical and molecular basis of phenylketonuria and the innovative treatment strategies introduced for these patients during the last 60 years. These concepts were transferred to other inborn errors of metabolism and led to significant reduction in morbidity and to an improvement in quality of life. Important milestones were the successful development of a low-phenylalanine diet for phenylketonuria patients, the recognition of tetrahydrobiopterin as an option to treat these individuals pharmacologically, and finally market approval of this drug. The work related to the discovery of a pharmacological treatment led metabolic researchers and pediatricians to new insights into the molecular processes linked to mutations in the phenylalanine hydroxylase gene at the cellular and structural level. Again, phenylketonuria became a prototype disorder for a previously underestimated but now rapidly expanding group of diseases: protein misfolding disorders with loss of function. Due to potential general biological mechanisms underlying these disorders, the door may soon open to a systematic development of a new class of pharmaceutical products. These pharmacological chaperones are likely to correct misfolding of proteins involved in numerous genetic and nongenetic diseases.

  17. Injectable nanocomposite cryogels for versatile protein drug delivery.

    Science.gov (United States)

    Koshy, Sandeep T; Zhang, David K Y; Grolman, Joshua M; Stafford, Alexander G; Mooney, David J

    2018-01-01

    Sustained, localized protein delivery can enhance the safety and activity of protein drugs in diverse disease settings. While hydrogel systems are widely studied as vehicles for protein delivery, they often suffer from rapid release of encapsulated cargo, leading to a narrow duration of therapy, and protein cargo can be denatured by incompatibility with the hydrogel crosslinking chemistry. In this work, we describe injectable nanocomposite hydrogels that are capable of sustained, bioactive, release of a variety of encapsulated proteins. Injectable and porous cryogels were formed by bio-orthogonal crosslinking of alginate using tetrazine-norbornene coupling. To provide sustained release from these hydrogels, protein cargo was pre-adsorbed to charged Laponite nanoparticles that were incorporated within the walls of the cryogels. The presence of Laponite particles substantially hindered the release of a number of proteins that otherwise showed burst release from these hydrogels. By modifying the Laponite content within the hydrogels, the kinetics of protein release could be precisely tuned. This versatile strategy to control protein release simplifies the design of hydrogel drug delivery systems. Here we present an injectable nanocomposite hydrogel for simple and versatile controlled release of therapeutic proteins. Protein release from hydrogels often requires first entrapping the protein in particles and embedding these particles within the hydrogel to allow controlled protein release. This pre-encapsulation process can be cumbersome, can damage the protein's activity, and must be optimized for each protein of interest. The strategy presented in this work simply premixes the protein with charged nanoparticles that bind strongly with the protein. These protein-laden particles are then placed within a hydrogel and slowly release the protein into the surrounding environment. Using this method, tunable release from an injectable hydrogel can be achieved for a variety of

  18. 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

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

    Science.gov (United States)

    Womersley, Jacqueline S; Uys, Joachim D

    2016-01-01

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

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

    African Journals Online (AJOL)

    ... minimize drug failures by predicting drug efficacy and toxicity. One of the most important pathogenic bacterium is Aeromonas species which causes tissue damage, acute gastroenteritis and neonatal septicemia. Bacterial proteins are the ultimate target to inhibit their growth and these are the executors of cellular function.

  1. Chromatin proteins and modifications as drug targets

    DEFF Research Database (Denmark)

    Helin, Kristian; Dhanak, Dashyant

    2013-01-01

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

  2. Protein and Peptide in Drug Targeting and its Therapeutic Approach

    Directory of Open Access Journals (Sweden)

    Raj K. Keservani

    2015-09-01

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

  3. Physiologically Based Pharmacokinetic Modeling of Therapeutic Proteins.

    Science.gov (United States)

    Wong, Harvey; Chow, Timothy W

    2017-09-01

    Biologics or therapeutic proteins are becoming increasingly important as treatments for disease. The most common class of biologics are monoclonal antibodies (mAbs). Recently, there has been an increase in the use of physiologically based pharmacokinetic (PBPK) modeling in the pharmaceutical industry in drug development. We review PBPK models for therapeutic proteins with an emphasis on mAbs. Due to their size and similarity to endogenous antibodies, there are distinct differences between PBPK models for small molecules and mAbs. The high-level organization of a typical mAb PBPK model consists of a whole-body PBPK model with organ compartments interconnected by both blood and lymph flows. The whole-body PBPK model is coupled with tissue-level submodels used to describe key mechanisms governing mAb disposition including tissue efflux via the lymphatic system, elimination by catabolism, protection from catabolism binding to the neonatal Fc (FcRn) receptor, and nonlinear binding to specific pharmacological targets of interest. The use of PBPK modeling in the development of therapeutic proteins is still in its infancy. Further application of PBPK modeling for therapeutic proteins will help to define its developing role in drug discovery and development. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

  4. Recent trends in drug delivery system using protein nanoparticles.

    Science.gov (United States)

    Sripriyalakshmi, S; Jose, Pinkybel; Ravindran, Aswathy; Anjali, C H

    2014-09-01

    Engineered nanoparticles that can facilitate drug formulation and passively target tumours have been under extensive research in recent years. These successes have driven a new wave of significant innovation in the generation of advanced particles. The fate and transport of diagnostic nanoparticles would significantly depend on nonselective drug delivery, and hence the use of high drug dosage is implemented. In this perspective, nanocarrier-based drug targeting strategies can be used which improve the selective delivery of drugs to the site of action, i.e. drug targeting. Pharmaceutical industries majorly focus on reducing the toxicity and side effects of drugs but only recently it has been realised that carrier systems themselves may pose risks to the patient. Proteins are compatible with biological systems and they are biodegradable. They offer a multitude of moieties for modifications to tailor drug binding, imaging or targeting entities. Thus, protein nanoparticles provide outstanding contributions as a carrier for drug delivery systems. This review summarises recent progress in particle-based therapeutic delivery and discusses important concepts in particle design and biological barriers for developing the next generation of particles drug delivery systems.

  5. Quantifying drug-protein binding in vivo

    International Nuclear Information System (INIS)

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

    2004-01-01

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

  6. 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...... 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...... 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...

  7. Development of novel drug delivery systems using phage display technology for clinical application of protein drugs.

    Science.gov (United States)

    Nagano, Kazuya; Tsutsumi, Yasuo

    2016-01-01

    Attempts are being made to develop therapeutic proteins for cancer, hepatitis, and autoimmune conditions, but their clinical applications are limited, except in the cases of drugs based on erythropoietin, granulocyte colony-stimulating factor, interferon-alpha, and antibodies, owing to problems with fundamental technologies for protein drug discovery. It is difficult to identify proteins useful as therapeutic seeds or targets. Another problem in using bioactive proteins is pleiotropic actions through receptors, making it hard to elicit desired effects without side effects. Additionally, bioactive proteins have poor therapeutic effects owing to degradation by proteases and rapid excretion from the circulatory system. Therefore, it is essential to establish a series of novel drug delivery systems (DDS) to overcome these problems. Here, we review original technologies in DDS. First, we introduce antibody proteomics technology for effective selection of proteins useful as therapeutic seeds or targets and identification of various kinds of proteins, such as cancer-specific proteins, cancer metastasis-related proteins, and a cisplatin resistance-related protein. Especially Ephrin receptor A10 is expressed in breast tumor tissues but not in normal tissues and is a promising drug target potentially useful for breast cancer treatment. Moreover, we have developed a system for rapidly creating functional mutant proteins to optimize the seeds for therapeutic applications and used this system to generate various kinds of functional cytokine muteins. Among them, R1antTNF is a TNFR1-selective antagonistic mutant of TNF and is the first mutein converted from agonist to antagonist. We also review a novel polymer-conjugation system to improve the in vivo stability of bioactive proteins. Site-specific PEGylated R1antTNF is uniform at the molecular level, and its bioactivity is similar to that of unmodified R1antTNF. In the future, we hope that many innovative protein drugs will be

  8. Calibration and LOD/LOQ estimation of a chemiluminescent hybridization assay for residual DNA in recombinant protein drugs expressed in E. coli using a four-parameter logistic model.

    Science.gov (United States)

    Lee, K R; Dipaolo, B; Ji, X

    2000-06-01

    Calibration is the process of fitting a model based on reference data points (x, y), then using the model to estimate an unknown x based on a new measured response, y. In DNA assay, x is the concentration, and y is the measured signal volume. A four-parameter logistic model was used frequently for calibration of immunoassay when the response is optical density for enzyme-linked immunosorbent assay (ELISA) or adjusted radioactivity count for radioimmunoassay (RIA). Here, it is shown that the same model or a linearized version of the curve are equally useful for the calibration of a chemiluminescent hybridization assay for residual DNA in recombinant protein drugs and calculation of performance measures of the assay.

  9. The PMDB Protein Model Database

    Science.gov (United States)

    Castrignanò, Tiziana; De Meo, Paolo D'Onorio; Cozzetto, Domenico; Talamo, Ivano Giuseppe; Tramontano, Anna

    2006-01-01

    The Protein Model Database (PMDB) is a public resource aimed at storing manually built 3D models of proteins. The database is designed to provide access to models published in the scientific literature, together with validating experimental data. It is a relational database and it currently contains >74 000 models for ∼240 proteins. The system is accessible at and allows predictors to submit models along with related supporting evidence and users to download them through a simple and intuitive interface. Users can navigate in the database and retrieve models referring to the same target protein or to different regions of the same protein. Each model is assigned a unique identifier that allows interested users to directly access the data. PMID:16381873

  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. 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

  12. 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.

  13. QSAR Modeling and Prediction of Drug-Drug Interactions.

    Science.gov (United States)

    Zakharov, Alexey V; Varlamova, Ekaterina V; Lagunin, Alexey A; Dmitriev, Alexander V; Muratov, Eugene N; Fourches, Denis; Kuz'min, Victor E; Poroikov, Vladimir V; Tropsha, Alexander; Nicklaus, Marc C

    2016-02-01

    Severe adverse drug reactions (ADRs) are the fourth leading cause of fatality in the U.S. with more than 100,000 deaths per year. As up to 30% of all ADRs are believed to be caused by drug-drug interactions (DDIs), typically mediated by cytochrome P450s, possibilities to predict DDIs from existing knowledge are important. We collected data from public sources on 1485, 2628, 4371, and 27,966 possible DDIs mediated by four cytochrome P450 isoforms 1A2, 2C9, 2D6, and 3A4 for 55, 73, 94, and 237 drugs, respectively. For each of these data sets, we developed and validated QSAR models for the prediction of DDIs. As a unique feature of our approach, the interacting drug pairs were represented as binary chemical mixtures in a 1:1 ratio. We used two types of chemical descriptors: quantitative neighborhoods of atoms (QNA) and simplex descriptors. Radial basis functions with self-consistent regression (RBF-SCR) and random forest (RF) were utilized to build QSAR models predicting the likelihood of DDIs for any pair of drug molecules. Our models showed balanced accuracy of 72-79% for the external test sets with a coverage of 81.36-100% when a conservative threshold for the model's applicability domain was applied. We generated virtually all possible binary combinations of marketed drugs and employed our models to identify drug pairs predicted to be instances of DDI. More than 4500 of these predicted DDIs that were not found in our training sets were confirmed by data from the DrugBank database.

  14. 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.

  15. Bioengineered protein-based nanocage for drug delivery.

    Science.gov (United States)

    Lee, Eun Jung; Lee, Na Kyeong; Kim, In-San

    2016-11-15

    Nature, in its wonders, presents and assembles the most intricate and delicate protein structures and this remarkable phenomenon occurs in all kingdom and phyla of life. Of these proteins, cage-like multimeric proteins provide spatial control to biological processes and also compartmentalizes compounds that may be toxic or unstable and avoids their contact with the environment. Protein-based nanocages are of particular interest because of their potential applicability as drug delivery carriers and their perfect and complex symmetry and ideal physical properties, which have stimulated researchers to engineer, modify or mimic these qualities. This article reviews various existing types of protein-based nanocages that are used for therapeutic purposes, and outlines their drug-loading mechanisms and bioengineering strategies via genetic and chemical functionalization. Through a critical evaluation of recent advances in protein nanocage-based drug delivery in vitro and in vivo, an outlook for de novo and in silico nanocage design, and also protein-based nanocage preclinical and future clinical applications will be presented. Copyright © 2016 Elsevier B.V. All rights reserved.

  16. 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...

  17. 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.

  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. Influence of multidrug resistance and drug transport proteins on chemotherapy drug metabolism.

    Science.gov (United States)

    Joyce, Helena; McCann, Andrew; Clynes, Martin; Larkin, Annemarie

    2015-05-01

    Chemotherapy involving the use of anticancer drugs remains an important strategy in the overall management of patients with metastatic cancer. Acquisition of multidrug resistance remains a major impediment to successful chemotherapy. Drug transporters in cell membranes and intracellular drug metabolizing enzymes contribute to the resistance phenotype and determine the pharmacokinetics of anticancer drugs in the body. ATP-binding cassette (ABC) transporters mediate the transport of endogenous metabolites and xenobiotics including cytotoxic drugs out of cells. Solute carrier (SLC) transporters mediate the influx of cytotoxic drugs into cells. This review focuses on the substrate interaction of these transporters, on their biology and what role they play together with drug metabolizing enzymes in eliminating therapeutic drugs from cells. The majority of anticancer drugs are substrates for the ABC transporter and SLC transporter families. Together, these proteins have the ability to control the influx and the efflux of structurally unrelated chemotherapeutic drugs, thereby modulating the intracellular drug concentration. These interactions have important clinical implications for chemotherapy because ultimately they determine therapeutic efficacy, disease progression/relapse and the success or failure of patient treatment.

  20. Peptides, proteins and peptide/protein-polymer conjugates as drug delivery system.

    Science.gov (United States)

    Mukherjee, Biswajit; Karmakar, Swapna D; Hossain, Chowdhury M; Bhattacharya, Sanchari

    2014-01-01

    In the last few decades, novel drug delivery strategies have been a big priority to the formulation scientists. Peptides and proteins have drawn a special attention for their wide scope in the area. Serum albumin, transferrin, recom- binant proteins, virus capsids etc. are used as carrier for drug and biomolecules. Conjugates of polymers with proteins have also shown strong potency in the field of drug delivery. Polyethylene glycol is one of the most successful polymers that has been used extensively to develop protein conjugated formulations. Besides, polyvinyl pyrrolidone, polylactic-co- glycolic acid, N-(2-hydroxypropyl) methacrylamide copolymer, polyglutamic acid have also been investigated. In this re- view, we will highlight on the most recent overview of various advantages, limitations and marketed products of proteins, peptides and protein/peptide-polymer conjugates as drug carriers, such products in clinical trials and their various uses in the field of modern drug delivery. Understanding the key features of these materials and the vigorous research in this field will develop new drug formulations that will combat various types of life-threatening diseases.

  1. 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 ...

  2. Coarse-grain modelling of protein-protein interactions

    NARCIS (Netherlands)

    Baaden, Marc; Marrink, Siewert J.

    2013-01-01

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

  3. Drug Policy: the "Dutch Model"

    NARCIS (Netherlands)

    van Ooijen-Houben, M.M.J.; Kleemans, E.R.

    2015-01-01

    Dutch drug policy, once considered pragmatic and lenient and rooted in a generally tolerant attitude toward drug use, has slowly but surely shifted from a primarily public health focus to an increasing focus on law enforcement. The "coffee shop" policy and the policy toward MDMA/ecstasy are

  4. 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.

  5. An invertebrate model for CNS drug discovery

    DEFF Research Database (Denmark)

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

    2015-01-01

    BACKGROUND: ABC efflux transporters at the blood brain barrier (BBB), namely the P-glycoprotein (P-gp), restrain the development of central nervous system (CNS) drugs. Consequently, early screening of CNS drug candidates is pivotal to identify those affected by efflux activity. Therefore, simple,...... barriers. CONCLUSION: Findings suggest a conserved mechanism of brain efflux activity between insects and vertebrates, confirming that this model holds promise for inexpensive and high-throughput screening relative to in vivo models, for CNS drug discovery....

  6. Molecular imaging of drug-modulated protein-protein interactions in living subjects.

    Science.gov (United States)

    Paulmurugan, Ramasamy; Massoud, Tarik F; Huang, Jing; Gambhir, Sanjiv S

    2004-03-15

    Networks of protein interactions mediate cellular responses to environmental stimuli and direct the execution of many different cellular functional pathways. Small molecules synthesized within cells or recruited from the external environment mediate many protein interactions. The study of small molecule-mediated interactions of proteins is important to understand abnormal signal transduction pathways in cancer and in drug development and validation. In this study, we used split synthetic renilla luciferase (hRLUC) protein fragment-assisted complementation to evaluate heterodimerization of the human proteins FRB and FKBP12 mediated by the small molecule rapamycin. The concentration of rapamycin required for efficient dimerization and that of its competitive binder ascomycin required for dimerization inhibition were studied in cell lines. The system was dually modulated in cell culture at the transcription level, by controlling nuclear factor kappaB promoter/enhancer elements using tumor necrosis factor alpha, and at the interaction level, by controlling the concentration of the dimerizer rapamycin. The rapamycin-mediated dimerization of FRB and FKBP12 also was studied in living mice by locating, quantifying, and timing the hRLUC complementation-based bioluminescence imaging signal using a cooled charged coupled device camera. This split reporter system can be used to efficiently screen small molecule drugs that modulate protein-protein interactions and also to assess drugs in living animals. Both are essential steps in the preclinical evaluation of candidate pharmaceutical agents targeting protein-protein interactions, including signaling pathways in cancer cells.

  7. 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.

  8. 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.

  9. 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

  10. 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...

  11. 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.

  12. An overview on the delivery of antitumor drug doxorubicin by carrier proteins.

    Science.gov (United States)

    Agudelo, D; Bérubé, G; Tajmir-Riahi, H A

    2016-07-01

    Serum proteins play an increasing role as drug carriers in the clinical settings. In this review, we have compared the binding modalities of anticancer drug doxorubicin (DOX) to three model carrier proteins, human serum albumin (HSA), bovine serum albumin (BSA) and milk beta-lactoglobulin (β-LG) in order to determine the potential application of these model proteins in DOX delivery. Molecular modeling studies showed stronger binding of DOX with HSA than BSA and β-LG with the free binding energies of -10.75 (DOX-HSA), -9.31 (DOX-BSA) and -8.12kcal/mol (DOX-β-LG). Extensive H-boding network stabilizes DOX-protein conjugation and played a major role in drug-protein complex formation. DOX complexation induced major alterations of HSA and BSA conformations, while did not alter β-LG secondary structure. The literature review shows that these proteins can potentially be used for delivery of DOX in vitro and in vivo. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. 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

  14. 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

  15. 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.

  16. ANALYSIS OF DRUG-PROTEIN BINDING BY ULTRAFAST AFFINITY CHROMATOGRAPHY USING IMMOBILIZED HUMAN SERUM ALBUMIN

    Science.gov (United States)

    Mallik, Rangan; Yoo, Michelle J.; Briscoe, Chad J.; Hage, David S.

    2010-01-01

    Human serum albumin (HSA) was explored for use as a stationary phase and ligand in affinity microcolumns for the ultrafast extraction of free drug fractions and the use of this information for the analysis of drug-protein binding. Warfarin, imipramine, and ibuprofen were used as model analytes in this study. It was found that greater than 95% extraction of all these drugs could be achieved in as little as 250 ms on HSA microcolumns. The retained drug fraction was then eluted from the same column under isocratic conditions, giving elution in less than 40 s when working at 4.5 mL/min. The chromatographic behavior of this system gave a good fit with that predicted by computer simulations based on a reversible, saturable model for the binding of an injected drug with immobilized HSA. The free fractions measured by this method were found to be comparable to those determined by ultrafiltration, and equilibrium constants estimated by this approach gave good agreement with literature values. Advantages of this method include its speed and the relatively low cost of microcolumns that contain HSA. The ability of HSA to bind many types of drugs also creates the possibility of using the same affinity microcolumn to study and measure the free fractions for a variety of pharmaceutical agents. These properties make this technique appealing for use in drug binding studies and in the high-throughput screening of new drug candidates. PMID:20227701

  17. 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.

  18. 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

    2018-01-01

    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 the 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.

  19. [A model list of high risk drugs].

    Science.gov (United States)

    Cotrina Luque, J; Guerrero Aznar, M D; Alvarez del Vayo Benito, C; Jimenez Mesa, E; Guzman Laura, K P; Fernández Fernández, L

    2013-12-01

    «High-risk drugs» are those that have a very high «risk» of causing death or serious injury if an error occurs during its use. The Institute for Safe Medication Practices (ISMP) has prepared a high-risk drugs list applicable to the general population (with no differences between the pediatric and adult population). Thus, there is a lack of information for the pediatric population. The main objective of this work is to develop a high-risk drug list adapted to the neonatal or pediatric population as a reference model for the pediatric hospital health workforce. We made a literature search in May 2012 to identify any published lists or references in relation to pediatric and/or neonatal high-risk drugs. A total of 15 studies were found, from which 9 were selected. A model list was developed mainly based on the ISMP one, adding strongly perceived pediatric risk drugs and removing those where the pediatric use was anecdotal. There is no published list that suits pediatric risk management. The list of pediatric and neonatal high-risk drugs presented here could be a «reference list of high-risk drugs » for pediatric hospitals. Using this list and training will help to prevent medication errors in each drug supply chain (prescribing, transcribing, dispensing and administration). Copyright © 2013 Asociación Española de Pediatría. Published by Elsevier Espana. All rights reserved.

  20. Protein Drug Targets of Lavandula angustifolia on treatment of Rat Alzheimer's Disease

    Science.gov (United States)

    Zali, Hakimeh; Zamanian-Azodi, Mona; Rezaei Tavirani, Mostafa; Akbar-zadeh Baghban, Alireza

    2015-01-01

    Different treatment strategies of Alzheimer's disease (AD) are being studied for treating or slowing the progression of AD. Many pharmaceutically important regulation systems operate through proteins as drug targets. Here, we investigate the drug target proteins in beta-amyloid (Aβ) injected rat hippocampus treated with Lavandula angustifolia (LA) by proteomics techniques. The reported study showed that lavender extract (LE) improves the spatial performance in AD animal model by diminishing Aβ production in histopathology of hippocampus, so in this study neuroprotective proteins expressed in Aβ injected rats treated with LE were scrutinized. Rats were divided into three groups including normal, Aβ injected, and Aβ injected that was treated with LE. Protein expression profiles of hippocampus tissue were determined by two-dimensional electrophoresis (2DE) method and dysregulated proteins such as Snca, NF-L, Hspa5, Prdx2, Apoa1, and Atp5a1were identified by MALDI-TOF/TOF. KEGG pathway and gene ontology (GO) categories were used by searching DAVID Bioinformatics Resources. All detected protein spots were used to determine predictedinteractions with other proteins in STRING online database. Different isoforms of important protein, Snca that exhibited neuroprotective effects by anti-apoptotic properties were expressed. NF-L involved in the maintenance of neuronal caliber. Hspa5 likewise Prdx2 displays as anti-apoptotic protein that Prdx2 also involved in the neurotrophic effects. Apoa1 has anti-inflammatory activity and Atp5a1, produces ATP from ADP. To sum up, these proteins as potential drug targets were expressed in hippocampus in response to effective components in LA may have therapeutic properties for the treatment of AD and other neurodegenerative diseases. PMID:25561935

  1. 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.

  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. 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.

  4. 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.

  5. Peptide drugs to target G protein-coupled receptors.

    Science.gov (United States)

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

    2010-09-01

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

  6. 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.

  7. 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

  8. 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

  9. Phylogenetic profiles of all membrane transport proteins of the malaria parasite highlight new drug targets

    Directory of Open Access Journals (Sweden)

    January Weiner 3rd

    2016-08-01

    Full Text Available In order to combat the on-going malaria epidemic, discovery of new drug targets remains vital. Proteins that are essential to survival and specific to malaria parasites are key candidates. To survive within host cells, the parasites need to acquire nutrients and dispose of waste products across multiple membranes. Additionally, like all eukaryotes, they must redistribute ions and organic molecules between their various internal membrane bound compartments. Membrane transport proteins mediate all of these processes and are considered important mediators of drug resistance as well as drug targets in their own right. Recently, using advanced experimental genetic approaches and streamlined life cycle profiling, we generated a large collection of Plasmodium berghei gene deletion mutants and assigned essential gene functions, highlighting potential targets for prophylactic, therapeutic, and transmission-blocking anti-malarial drugs. Here, we present a comprehensive orthology assignment of all Plasmodium falciparum putative membrane transport proteins and provide a detailed overview of the associated essential gene functions obtained through experimental genetics studies in human and murine model parasites. Furthermore, we discuss the phylogeny of selected potential drug targets identified in our functional screen. We extensively discuss the results in the context of the functional assignments obtained using gene targeting available to date.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Preclinical models used for immunogenicity prediction of therapeutic proteins.

    Science.gov (United States)

    Brinks, Vera; Weinbuch, Daniel; Baker, Matthew; Dean, Yann; Stas, Philippe; Kostense, Stefan; Rup, Bonita; Jiskoot, Wim

    2013-07-01

    All therapeutic proteins are potentially immunogenic. Antibodies formed against these drugs can decrease efficacy, leading to drastically increased therapeutic costs and in rare cases to serious and sometimes life threatening side-effects. Many efforts are therefore undertaken to develop therapeutic proteins with minimal immunogenicity. For this, immunogenicity prediction of candidate drugs during early drug development is essential. Several in silico, in vitro and in vivo models are used to predict immunogenicity of drug leads, to modify potentially immunogenic properties and to continue development of drug candidates with expected low immunogenicity. Despite the extensive use of these predictive models, their actual predictive value varies. Important reasons for this uncertainty are the limited/insufficient knowledge on the immune mechanisms underlying immunogenicity of therapeutic proteins, the fact that different predictive models explore different components of the immune system and the lack of an integrated clinical validation. In this review, we discuss the predictive models in use, summarize aspects of immunogenicity that these models predict and explore the merits and the limitations of each of the models.

  18. Multiscale modeling of transdermal drug delivery

    Science.gov (United States)

    Rim, Jee Eun

    2006-04-01

    This study addresses the modeling of transdermal diffusion of drugs, to better understand the permeation of molecules through the skin, and especially the stratum corneum, which forms the main permeation barrier of the skin. In transdermal delivery of systemic drugs, the drugs diffuse from a patch placed on the skin through the epidermis to the underlying blood vessels. The epidermis is the outermost layer of the skin and can be further divided into the stratum corneum (SC) and the viable epidermis layers. The SC consists of keratinous cells (corneocytes) embedded in the lipid multi-bilayers of the intercellular space. It is widely accepted that the barrier properties of the skin mostly arises from the ordered structure of the lipid bilayers. The diffusion path, at least for lipophilic molecules, seems to be mainly through the lipid bilayers. Despite the advantages of transdermal drug delivery compared to other drug delivery routes such as oral dosing and injections, the low percutaneous permeability of most compounds is a major difficulty in the wide application of transdermal drug delivery. In fact, many transdermal drug formulations include one or more permeation enhancers that increase the permeation of the drug significantly. During the last two decades, many researchers have studied percutaneous absorption of drugs both experimentally and theoretically. However, many are based on pharmacokinetic compartmental models, in which steady or pseudo-steady state conditions are assumed, with constant diffusivity and partitioning for single component systems. This study presents a framework for studying the multi-component diffusion of drugs coupled with enhancers through the skin by considering the microstructure of the stratum corneum (SC). A multiscale framework of modeling the transdermal diffusion of molecules is presented, by first calculating the microscopic diffusion coefficient in the lipid bilayers of the SC using molecular dynamics (MD). Then a

  19. 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...

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Fragment-based drug discovery and protein–protein interactions

    Directory of Open Access Journals (Sweden)

    Turnbull AP

    2014-09-01

    Full Text Available Andrew P Turnbull,1 Susan M Boyd,2 Björn Walse31CRT Discovery Laboratories, Department of Biological Sciences, Birkbeck, University of London, London, UK; 2IOTA Pharmaceuticals Ltd, Cambridge, UK; 3SARomics Biostructures AB, Lund, SwedenAbstract: Protein–protein interactions (PPIs are involved in many biological processes, with an estimated 400,000 PPIs within the human proteome. There is significant interest in exploiting the relatively unexplored potential of these interactions in drug discovery, driven by the need to find new therapeutic targets. Compared with classical drug discovery against targets with well-defined binding sites, developing small-molecule inhibitors against PPIs where the contact surfaces are frequently more extensive and comparatively flat, with most of the binding energy localized in “hot spots”, has proven far more challenging. However, despite the difficulties associated with targeting PPIs, important progress has been made in recent years with fragment-based drug discovery playing a pivotal role in improving their tractability. Computational and empirical approaches can be used to identify hot-spot regions and assess the druggability and ligandability of new targets, whilst fragment screening campaigns can detect low-affinity fragments that either directly or indirectly perturb the PPI. Once fragment hits have been identified and confirmed using biochemical and biophysical approaches, three-dimensional structural data derived from nuclear magnetic resonance or X-ray crystallography can be used to drive medicinal chemistry efforts towards the development of more potent inhibitors. A small-scale comparison presented in this review of “standard” fragments with those targeting PPIs has revealed that the latter tend to be larger, be more lipophilic, and contain more polar (acid/base functionality, whereas three-dimensional descriptor data indicate that there is little difference in their three

  5. Animal Migraine Models for Drug Development

    DEFF Research Database (Denmark)

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

    2013-01-01

    Migraine is number seven in WHO's list of all diseases causing disability and the third most costly neurological disorder in Europe. Acute attacks are treatable by highly selective drugs such as the triptans but there is still a huge unmet therapeutic need. Unfortunately, drug development...... 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...... responses elicited by such measures are crucial. The most naturalistic way of inducing attacks is by infusion of endogenous signaling molecules that are known to cause migraine in patients. The most valid response is recording of neural activity in the trigeminal system. The most useful headache related...

  6. 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

  7. Immunogenicity of therapeutic proteins: the use of animal models.

    Science.gov (United States)

    Brinks, Vera; Jiskoot, Wim; Schellekens, Huub

    2011-10-01

    Immunogenicity of therapeutic proteins lowers patient well-being and drastically increases therapeutic costs. Preventing immunogenicity is an important issue to consider when developing novel therapeutic proteins and applying them in the clinic. Animal models are increasingly used to study immunogenicity of therapeutic proteins. They are employed as predictive tools to assess different aspects of immunogenicity during drug development and have become vital in studying the mechanisms underlying immunogenicity of therapeutic proteins. However, the use of animal models needs critical evaluation. Because of species differences, predictive value of such models is limited, and mechanistic studies can be restricted. This review addresses the suitability of animal models for immunogenicity prediction and summarizes the insights in immunogenicity that they have given so far.

  8. 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.

  9. Drug repurposing for aging research using model organisms.

    Science.gov (United States)

    Ziehm, Matthias; Kaur, Satwant; Ivanov, Dobril K; Ballester, Pedro J; Marcus, David; Partridge, Linda; Thornton, Janet M

    2017-10-01

    Many increasingly prevalent diseases share a common risk factor: age. However, little is known about pharmaceutical interventions against aging, despite many genes and pathways shown to be important in the aging process and numerous studies demonstrating that genetic interventions can lead to a healthier aging phenotype. An important challenge is to assess the potential to repurpose existing drugs for initial testing on model organisms, where such experiments are possible. To this end, we present a new approach to rank drug-like compounds with known mammalian targets according to their likelihood to modulate aging in the invertebrates Caenorhabditis elegans and Drosophila. Our approach combines information on genetic effects on aging, orthology relationships and sequence conservation, 3D protein structures, drug binding and bioavailability. Overall, we rank 743 different drug-like compounds for their likelihood to modulate aging. We provide various lines of evidence for the successful enrichment of our ranking for compounds modulating aging, despite sparse public data suitable for validation. The top ranked compounds are thus prime candidates for in vivo testing of their effects on lifespan in C. elegans or Drosophila. As such, these compounds are promising as research tools and ultimately a step towards identifying drugs for a healthier human aging. © 2017 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.

  10. 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

    2018-05-01

    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.

  11. Modeling chemical reactions for drug design.

    Science.gov (United States)

    Gasteiger, Johann

    2007-01-01

    Chemical reactions are involved at many stages of the drug design process. This starts with the analysis of biochemical pathways that are controlled by enzymes that might be downregulated in certain diseases. In the lead discovery and lead optimization process compounds have to be synthesized in order to test them for their biological activity. And finally, the metabolism of a drug has to be established. A better understanding of chemical reactions could strongly help in making the drug design process more efficient. We have developed methods for quantifying the concepts an organic chemist is using in rationalizing reaction mechanisms. These methods allow a comprehensive modeling of chemical reactivity and thus are applicable to a wide variety of chemical reactions, from gas phase reactions to biochemical pathways. They are empirical in nature and therefore allow the rapid processing of large sets of structures and reactions. We will show here how methods have been developed for the prediction of acidity values and of the regioselectivity in organic reactions, for designing the synthesis of organic molecules and of combinatorial libraries, and for furthering our understanding of enzyme-catalyzed reactions and of the metabolism of drugs.

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

    Science.gov (United States)

    Murrell, Ben; de Oliveira, Tulio; Seebregts, Chris; Kosakovsky Pond, Sergei L; Scheffler, Konrad

    2012-01-01

    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.

  14. 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.

  15. Bioengineered Liver Models for Drug Testing and Cell Differentiation Studies

    Directory of Open Access Journals (Sweden)

    Gregory H. Underhill

    2018-01-01

    Full Text Available In vitro models of the human liver are important for the following: (1 mitigating the risk of drug-induced liver injury to human beings, (2 modeling human liver diseases, (3 elucidating the role of single and combinatorial microenvironmental cues on liver cell function, and (4 enabling cell-based therapies in the clinic. Methods to isolate and culture primary human hepatocytes (PHHs, the gold standard for building human liver models, were developed several decades ago; however, PHHs show a precipitous decline in phenotypic functions in 2-dimensional extracellular matrix–coated conventional culture formats, which does not allow chronic treatment with drugs and other stimuli. The development of several engineering tools, such as cellular microarrays, protein micropatterning, microfluidics, biomaterial scaffolds, and bioprinting, now allow precise control over the cellular microenvironment for enhancing the function of both PHHs and induced pluripotent stem cell–derived human hepatocyte-like cells; long-term (4+ weeks stabilization of hepatocellular function typically requires co-cultivation with liver-derived or non–liver-derived nonparenchymal cell types. In addition, the recent development of liver organoid culture systems can provide a strategy for the enhanced expansion of therapeutically relevant cell types. Here, we discuss advances in engineering approaches for constructing in vitro human liver models that have utility in drug screening and for determining microenvironmental determinants of liver cell differentiation/function. Design features and validation data of representative models are presented to highlight major trends followed by the discussion of pending issues that need to be addressed. Overall, bioengineered liver models have significantly advanced our understanding of liver function and injury, which will prove useful for drug development and ultimately cell-based therapies.

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

    KAUST Repository

    Oliva, Romina; Chermak, Edrisse; Cavallo, Luigi

    2015-01-01

    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.

  17. 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.

  18. 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

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

    DEFF Research Database (Denmark)

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

    2012-01-01

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

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

    OpenAIRE

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

    2016-01-01

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

  1. 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.

  2. 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

  3. 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.

  4. 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...

  5. 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 phigh Fe

  6. 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.

  7. 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)

  8. 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

  9. Blood-brain barrier drug delivery of IgG fusion proteins with a transferrin receptor monoclonal antibody.

    Science.gov (United States)

    Pardridge, William M

    2015-02-01

    Biologic drugs are large molecules that do not cross the blood- brain barrier (BBB). Brain penetration is possible following the re-engineering of the biologic drug as an IgG fusion protein. The IgG domain is a MAb against an endogenous BBB receptor such as the transferrin receptor (TfR). The TfRMAb acts as a molecular Trojan horse to ferry the fused biologic drug into the brain via receptor-mediated transport on the endogenous BBB TfR. This review discusses TfR isoforms, models of BBB transport of transferrin and TfRMAbs, and the genetic engineering of TfRMAb fusion proteins, including BBB penetrating IgG-neurotrophins, IgG-decoy receptors, IgG-lysosomal enzyme therapeutics and IgG-avidin fusion proteins, as well as BBB transport of bispecific antibodies formed by fusion of a therapeutic antibody to a TfRMAb targeting antibody. Also discussed are quantitative aspects of the plasma pharmacokinetics and brain uptake of TfRMAb fusion proteins, as compared to the brain uptake of small molecules, and therapeutic applications of TfRMAb fusion proteins in mouse models of neural disease, including Parkinson's disease, stroke, Alzheimer's disease and lysosomal storage disorders. The review covers the engineering of TfRMAb-avidin fusion proteins for BBB targeted delivery of biotinylated peptide radiopharmaceuticals, low-affinity TfRMAb Trojan horses and the safety pharmacology of chronic administration of TfRMAb fusion proteins. The BBB delivery of biologic drugs is possible following re-engineering as a fusion protein with a molecular Trojan horse such as a TfRMAb. The efficacy of this technology will be determined by the outcome of future clinical trials.

  10. 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.

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

    Science.gov (United States)

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

    2016-01-01

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

  12. A biotin-drug extraction and acid dissociation (BEAD) procedure to eliminate matrix and drug interference in a protein complex anti-drug antibody (ADA) isotype specific assay.

    Science.gov (United States)

    Niu, Hongmei; Klem, Thomas; Yang, Jinsong; Qiu, Yongchang; Pan, Luying

    2017-07-01

    Monitoring anti-drug antibody (ADA) responses in patients receiving protein therapeutics treatment is an important safety assessment for regulatory agencies, drug manufacturers, clinicians and patients. Recombinant human IGF-1/IGFBP-3 (rhIGF-1/rhIGFBP-3) is a 1:1 formulation of naturally occurring protein complex. The individual IGF-1 and IGFBP-3 proteins have multiple binding partners in serum matrix with high binding affinity to each other, which presents challenges in ADA assay development. We have developed a biotin-drug extraction with acid dissociation (BEAD) procedure followed by an electrochemiluminescence (ECL) direct assay to overcome matrix and drug interference. The method utilizes two step acid dissociation and excess biotin-drug to extract total ADA, which are further captured by soluble biotin-drug and detected in an ECL semi-homogeneous direct assay format. The pre-treatment method effectively eliminates interference by serum matrix and free drug, and enhances assay sensitivity. The assays passed acceptance criteria for all validation parameters, and have been used for clinical sample Ab testing. This method principle exemplifies a new approach for anti-isotype ADA assays, and could be an effective strategy for neutralizing antibody (NAb), pharmacokinetic (PK) and biomarker analysis in need of overcoming interference factors. Copyright © 2017 Elsevier B.V. All rights reserved.

  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. Preclinical experimental models of drug metabolism and disposition in drug discovery and development

    Directory of Open Access Journals (Sweden)

    Donglu Zhang

    2012-12-01

    Full Text Available Drug discovery and development involve the utilization of in vitro and in vivo experimental models. Different models, ranging from test tube experiments to cell cultures, animals, healthy human subjects, and even small numbers of patients that are involved in clinical trials, are used at different stages of drug discovery and development for determination of efficacy and safety. The proper selection and applications of correct models, as well as appropriate data interpretation, are critically important in decision making and successful advancement of drug candidates. In this review, we discuss strategies in the applications of both in vitro and in vivo experimental models of drug metabolism and disposition.

  15. 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)…

  16. 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.

  17. Protein-Templated Fragment Ligations-From Molecular Recognition to Drug Discovery.

    Science.gov (United States)

    Jaegle, Mike; Wong, Ee Lin; Tauber, Carolin; Nawrotzky, Eric; Arkona, Christoph; Rademann, Jörg

    2017-06-19

    Protein-templated fragment ligation is a novel concept to support drug discovery and can help to improve the efficacy of protein ligands. Protein-templated fragment ligations are chemical reactions between small molecules ("fragments") utilizing a protein's surface as a reaction vessel to catalyze the formation of a protein ligand with increased binding affinity. The approach exploits the molecular recognition of reactive small-molecule fragments by proteins both for ligand assembly and for the identification of bioactive fragment combinations. In this way, chemical synthesis and bioassay are integrated in one single step. This Review discusses the biophysical basis of reversible and irreversible fragment ligations and gives an overview of the available methods to detect protein-templated ligation products. The chemical scope and recent applications as well as future potential of the concept in drug discovery are reviewed. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

    Science.gov (United States)

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

    2014-09-01

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

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

    Directory of Open Access Journals (Sweden)

    Alessandra Lo Sciuto

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

  20. 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.

  1. 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

  2. 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.

  3. 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 .

  4. 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.

  5. Touching proteins with virtual bare hands - Visualizing protein-drug complexes and their dynamics in self-made virtual reality using gaming hardware

    Science.gov (United States)

    Ratamero, Erick Martins; Bellini, Dom; Dowson, Christopher G.; Römer, Rudolf A.

    2018-06-01

    The ability to precisely visualize the atomic geometry of the interactions between a drug and its protein target in structural models is critical in predicting the correct modifications in previously identified inhibitors to create more effective next generation drugs. It is currently common practice among medicinal chemists while attempting the above to access the information contained in three-dimensional structures by using two-dimensional projections, which can preclude disclosure of useful features. A more accessible and intuitive visualization of the three-dimensional configuration of the atomic geometry in the models can be achieved through the implementation of immersive virtual reality (VR). While bespoke commercial VR suites are available, in this work, we present a freely available software pipeline for visualising protein structures through VR. New consumer hardware, such as the uc(HTC Vive) and the uc(Oculus Rift) utilized in this study, are available at reasonable prices. As an instructive example, we have combined VR visualization with fast algorithms for simulating intramolecular motions of protein flexibility, in an effort to further improve structure-led drug design by exposing molecular interactions that might be hidden in the less informative static models. This is a paradigmatic test case scenario for many similar applications in computer-aided molecular studies and design.

  6. Potent antitumor activities of recombinant human PDCD5 protein in combination with chemotherapy drugs in K562 cells

    International Nuclear Information System (INIS)

    Shi, Lin; Song, Quansheng; Zhang, Yingmei; Lou, Yaxin; Wang, Yanfang; Tian, Linjie; Zheng, Yi; Ma, Dalong; Ke, Xiaoyan; Wang, Ying

    2010-01-01

    Conventional chemotherapy is still frequently used. Programmed cell death 5 (PDCD5) enhances apoptosis of various tumor cells triggered by certain stimuli and is lowly expressed in leukemic cells from chronic myelogenous leukemia patients. Here, we describe for the first time that recombinant human PDCD5 protein (rhPDCD5) in combination with chemotherapy drugs has potent antitumor effects on chronic myelogenous leukemia K562 cells in vitro and in vivo. The antitumor efficacy of rhPDCD5 protein with chemotherapy drugs, idarubicin (IDR) or cytarabine (Ara-C), was examined in K562 cells in vitro and K562 xenograft tumor models in vivo. rhPDCD5 protein markedly increased the apoptosis rates and decreased the colony-forming capability of K562 cells after the combined treatment with IDR or Ara-C. rhPDCD5 protein by intraperitoneal administration dramatically improved the antitumor effects of IDR treatment in the K562 xenograft model. The tumor sizes and cell proliferation were significantly decreased; and TUNEL positive cells were significantly increased in the combined group with rhPDCD5 protein and IDR treatment compared with single IDR treatment groups. rhPDCD5 protein, in combination with IDR, has potent antitumor effects on chronic myelogenous leukemia K562 cells and may be a novel and promising agent for the treatment of chronic myelogenous leukemia.

  7. 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

  8. 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.

  9. 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)

  10. 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

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

    International Nuclear Information System (INIS)

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

    2015-01-01

    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 Ca 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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-02-15

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

  13. 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.

  14. 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.

  15. 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.

  16. 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

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

  17. Optimization of protein and peptide drugs based on the mechanisms of kidney clearance.

    Science.gov (United States)

    Huang, Jiaguo; Wu, Huizi

    2018-05-30

    Development of proteins and peptides into drugs has been considered as a promising strategy to target certain diseases. However, only few proteins and peptides has been approved as new drugs into the market each year. One major problem is that proteins and peptides often exhibit short plasma half-life times, which limits the application for their clinical use. In most cases a short half-life time is not effective to deliver sufficient amount of drugs to the target organs and tissues, which is generally caused by fast renal clearance and low plasma stability due to proteolytic degradation during systemic circulation, because the most common clearance pathway of small proteins and peptides is through glomerular filtration by the kidneys. In this review, enzymatic degradation of proteins and peptides were discussed. Furthermore, several approaches to lengthen the half-life of peptides and proteins drugs based on the unique structures of glomerular capillary wall and the mechanisms of glomerular filtration were summarized, such as increasing the size and hydrodynamic diameter; increasing the negative charge to delay the filtration; increasing plasma protein binding to decrease plasma clearance. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  18. Hybrid protein-inorganic nanoparticles: From tumor-targeted drug delivery to cancer imaging.

    Science.gov (United States)

    Elzoghby, Ahmed O; Hemasa, Ayman L; Freag, May S

    2016-12-10

    Recently, a great interest has been paid to the development of hybrid protein-inorganic nanoparticles (NPs) for drug delivery and cancer diagnostics in order to combine the merits of both inorganic and protein nanocarriers. This review primarily discusses the most outstanding advances in the applications of the hybrids of naturally-occurring proteins with iron oxide, gadolinium, gold, silica, calcium phosphate NPs, carbon nanotubes, and quantum dots in drug delivery and cancer imaging. Various strategies that have been utilized for the preparation of protein-functionalized inorganic NPs and the mechanisms involved in the drug loading process are discussed. How can the protein functionalization overcome the limitations of colloidal stability, poor dispersibility and toxicity associated with inorganic NPs is also investigated. Moreover, issues relating to the influence of protein hybridization on the cellular uptake, tumor targeting efficiency, systemic circulation, mucosal penetration and skin permeation of inorganic NPs are highlighted. A special emphasis is devoted to the novel approaches utilizing the protein-inorganic nanohybrids in combined cancer therapy, tumor imaging, and theranostic applications as well as stimuli-responsive drug release from the nanohybrids. Copyright © 2016 Elsevier B.V. All rights reserved.

  19. 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.

  20. Protein stability in pulmonary drug delivery via nebulization.

    Science.gov (United States)

    Hertel, Sebastian P; Winter, Gerhard; Friess, Wolfgang

    2015-10-01

    Protein inhalation is a delivery route which offers high potential for direct local lung application of proteins. Liquid formulations are usually available in early stages of biopharmaceutical development and nebulizers are the device of choice for atomization avoiding additional process steps like drying and enabling fast progression to clinical trials. While some proteins were proven to remain stable throughout aerosolization e.g. DNase, many biopharmaceuticals are more susceptible towards the stresses encountered during nebulization. The main reason for protein instability is unfolding and aggregation at the air-liquid interface, a problem which is of particular challenge in the case of ultrasound and jet nebulizers due to recirculation of much of the generated droplets. Surfactants are an important formulation component to protect the sensitive biomolecules. A second important challenge is warming of ultrasound and vibrating mesh devices, which can be overcome by overfilling, precooled solutions or cooling of the reservoir. Ultimately, formulation development has to go hand in hand with device evaluation. Copyright © 2014 Elsevier B.V. All rights reserved.

  1. 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

  2. Cell physiology based pharmacodynamic modeling of antimicrobial drug combinations

    OpenAIRE

    Hethey, Christoph Philipp

    2017-01-01

    Mathematical models of bacterial growth have been successfully applied to study the relationship between antibiotic drug exposure and the antibacterial effect. Since these models typically lack a representation of cellular processes and cell physiology, the mechanistic integration of drug action is not possible on the cellular level. The cellular mechanisms of drug action, however, are particularly relevant for the prediction, analysis and understanding of interactions between antibiotics. In...

  3. A Structural Model of the Retail Market for Illicit Drugs.

    Science.gov (United States)

    Galenianos, Manolis; Gavazza, Alessandro

    2017-03-01

    We estimate a model of illicit drugs markets using data on purchases of crack cocaine. Buyers are searching for high-quality drugs, but they determine drugs' quality (i.e., their purity) only after consuming them. Hence, sellers can rip off first-time buyers or can offer higher-quality drugs to induce buyers to purchase from them again. In equilibrium, a distribution of qualities persists. The estimated model implies that if drugs were legalized, in which case purity could be regulated and hence observable, the average purity of drugs would increase by approximately 20 percent and the dispersion would decrease by approximately 80 percent. Moreover, increasing penalties may raise the purity and affordability of the drugs traded by increasing sellers’ relative profitability of targeting loyal buyers versus first-time buyers.

  4. 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...

  5. 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

  6. Structural analysis of protein-ligand interactions: the binding of endogenous compounds and of synthetic drugs.

    Science.gov (United States)

    Gallina, Anna M; Bork, Peer; Bordo, Domenico

    2014-02-01

    The large number of macromolecular structures deposited with the Protein Data Bank (PDB) describing complexes between proteins and either physiological compounds or synthetic drugs made it possible a systematic analysis of the interactions occurring between proteins and their ligands. In this work, the binding pockets of about 4000 PDB protein-ligand complexes were investigated and amino acid and interaction types were analyzed. The residues observed with lowest frequency in protein sequences, Trp, His, Met, Tyr, and Phe, turned out to be the most abundant in binding pockets. Significant differences between drug-like and physiological compounds were found. On average, physiological compounds establish with respect to drugs about twice as many hydrogen bonds with protein atoms, whereas drugs rely more on hydrophobic interactions to establish target selectivity. The large number of PDB structures describing homologous proteins in complex with the same ligand made it possible to analyze the conservation of binding pocket residues among homologous protein structures bound to the same ligand, showing that Gly, Glu, Arg, Asp, His, and Thr are more conserved than other amino acids. Also in the cases in which the same ligand is bound to unrelated proteins, the binding pockets showed significant conservation in the residue types. In this case, the probability of co-occurrence of the same amino acid type in the binding pockets could be up to thirteen times higher than that expected on a random basis. The trends identified in this study may provide an useful guideline in the process of drug design and lead optimization. Copyright © 2014 John Wiley & Sons, Ltd.

  7. Protein Kinases C-Mediated Regulations of Drug Transporter Activity, Localization and Expression

    Directory of Open Access Journals (Sweden)

    Abdullah Mayati

    2017-04-01

    Full Text Available Drug transporters are now recognized as major actors in pharmacokinetics, involved notably in drug–drug interactions and drug adverse effects. Factors that govern their activity, localization and expression are therefore important to consider. In the present review, the implications of protein kinases C (PKCs in transporter regulations are summarized and discussed. Both solute carrier (SLC and ATP-binding cassette (ABC drug transporters can be regulated by PKCs-related signaling pathways. PKCs thus target activity, membrane localization and/or expression level of major influx and efflux drug transporters, in various normal and pathological types of cells and tissues, often in a PKC isoform-specific manner. PKCs are notably implicated in membrane insertion of bile acid transporters in liver and, in this way, are thought to contribute to cholestatic or choleretic effects of endogenous compounds or drugs. The exact clinical relevance of PKCs-related regulation of drug transporters in terms of drug resistance, pharmacokinetics, drug–drug interactions and drug toxicity remains however to be precisely determined. This issue is likely important to consider in the context of the development of new drugs targeting PKCs-mediated signaling pathways, for treating notably cancers, diabetes or psychiatric disorders.

  8. 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.

  9. 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

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

    Science.gov (United States)

    Agarwal, Paresh; Bertozzi, Carolyn R

    2015-02-18

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

  11. 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

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

    Science.gov (United States)

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

    2014-01-01

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

  13. Investigation and identification of functional post-translational modification sites associated with drug binding and protein-protein interactions.

    Science.gov (United States)

    Su, Min-Gang; Weng, Julia Tzu-Ya; Hsu, Justin Bo-Kai; Huang, Kai-Yao; Chi, Yu-Hsiang; Lee, Tzong-Yi

    2017-12-21

    Protein post-translational modification (PTM) plays an essential role in various cellular processes that modulates the physical and chemical properties, folding, conformation, stability and activity of proteins, thereby modifying the functions of proteins. The improved throughput of mass spectrometry (MS) or MS/MS technology has not only brought about a surge in proteome-scale studies, but also contributed to a fruitful list of identified PTMs. However, with the increase in the number of identified PTMs, perhaps the more crucial question is what kind of biological mechanisms these PTMs are involved in. This is particularly important in light of the fact that most protein-based pharmaceuticals deliver their therapeutic effects through some form of PTM. Yet, our understanding is still limited with respect to the local effects and frequency of PTM sites near pharmaceutical binding sites and the interfaces of protein-protein interaction (PPI). Understanding PTM's function is critical to our ability to manipulate the biological mechanisms of protein. In this study, to understand the regulation of protein functions by PTMs, we mapped 25,835 PTM sites to proteins with available three-dimensional (3D) structural information in the Protein Data Bank (PDB), including 1785 modified PTM sites on the 3D structure. Based on the acquired structural PTM sites, we proposed to use five properties for the structural characterization of PTM substrate sites: the spatial composition of amino acids, residues and side-chain orientations surrounding the PTM substrate sites, as well as the secondary structure, division of acidity and alkaline residues, and solvent-accessible surface area. We further mapped the structural PTM sites to the structures of drug binding and PPI sites, identifying a total of 1917 PTM sites that may affect PPI and 3951 PTM sites associated with drug-target binding. An integrated analytical platform (CruxPTM), with a variety of methods and online molecular docking

  14. 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.

  15. Modeling Drug-Carrier Interaction in the Drug Release from Nanocarriers

    Directory of Open Access Journals (Sweden)

    Like Zeng

    2011-01-01

    Full Text Available Numerous nanocarriers of various compositions and geometries have been developed for the delivery and release of therapeutic and imaging agents. Due to the high specific surface areas of nanocarriers, different mechanisms such as ion pairing and hydrophobic interaction need to be explored for achieving sustained release. Recently, we developed a three-parameter model that considers reversible drug-carrier interaction and first-order drug release from liposomes. A closed-form analytical solution was obtained. Here, we further explore the ability of the model to capture the release of bioactive molecules such as drugs and growth factors from various nanocarriers. A parameter study demonstrates that the model is capable of resembling major categories of drug release kinetics. We further fit the model to 60 sets of experimental data from various drug release systems, including nanoparticles, hollow particles, fibers, and hollow fibers. Additionally, bootstrapping is used to evaluate the accuracy of parameter determination and validate the model in selected cases. The simplicity and universality of the model and the clear physical meanings of each model parameter render the model useful for the design and development of new drug delivery systems.

  16. 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.

  17. 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 itself...... of such interaction for advanced drug delivery are presented........ 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...

  18. 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.

  19. 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

  20. 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.

  1. Models of crk adaptor proteins in cancer.

    Science.gov (United States)

    Bell, Emily S; Park, Morag

    2012-05-01

    The Crk family of adaptor proteins (CrkI, CrkII, and CrkL), originally discovered as the oncogene fusion product, v-Crk, of the CT10 chicken retrovirus, lacks catalytic activity but engages with multiple signaling pathways through their SH2 and SH3 domains. Crk proteins link upstream tyrosine kinase and integrin-dependent signals to downstream effectors, acting as adaptors in diverse signaling pathways and cellular processes. Crk proteins are now recognized to play a role in the malignancy of many human cancers, stimulating renewed interest in their mechanism of action in cancer progression. The contribution of Crk signaling to malignancy has been predominantly studied in fibroblasts and in hematopoietic models and more recently in epithelial models. A mechanistic understanding of Crk proteins in cancer progression in vivo is still poorly understood in part due to the highly pleiotropic nature of Crk signaling. Recent advances in the structural organization of Crk domains, new roles in kinase regulation, and increased knowledge of the mechanisms and frequency of Crk overexpression in human cancers have provided an incentive for further study in in vivo models. An understanding of the mechanisms through which Crk proteins act as oncogenic drivers could have important implications in therapeutic targeting.

  2. Denatured protein-coated docetaxel nanoparticles: Alterable drug state and cytosolic delivery.

    Science.gov (United States)

    Zhang, Li; Xiao, Qingqing; Wang, Yiran; Zhang, Chenshuang; He, Wei; Yin, Lifang

    2017-05-15

    Many lead compounds have a low solubility in water, which substantially hinders their clinical application. Nanosuspensions have been considered a promising strategy for the delivery of water-insoluble drugs. Here, denatured soy protein isolate (SPI)-coated docetaxel nanosuspensions (DTX-NS) were developed using an anti-solvent precipitation-ultrasonication method to improve the water-solubility of DTX, thus improving its intracellular delivery. DTX-NS, with a diameter of 150-250nm and drug-loading up to 18.18%, were successfully prepared by coating drug particles with SPI. Interestingly, the drug state of DTX-NS was alterable. Amorphous drug nanoparticles were obtained at low drug-loading, whereas at a high drug-loading, the DTX-NS drug was mainly present in the crystalline state. Moreover, DTX-NS could be internalized at high levels by cancer cells and enter the cytosol by lysosomal escape, enhancing cell cytotoxicity and apoptosis compared with free DTX. Taken together, denatured SPI has a strong stabilization effect on nanosuspensions, and the drug state in SPI-coated nanosuspensions is alterable by changing the drug-loading. Moreover, DTX-NS could achieve cytosolic delivery, generating enhanced cell cytotoxicity against cancer cells. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. The Roles of Water in the Protein Matrix: A Largely Untapped Resource for Drug Discovery.

    Science.gov (United States)

    Spyrakis, Francesca; Ahmed, Mostafa H; Bayden, Alexander S; Cozzini, Pietro; Mozzarelli, Andrea; Kellogg, Glen E

    2017-08-24

    The value of thoroughly understanding the thermodynamics specific to a drug discovery/design study is well known. Over the past decade, the crucial roles of water molecules in protein structure, function, and dynamics have also become increasingly appreciated. This Perspective explores water in the biological environment by adopting its point of view in such phenomena. The prevailing thermodynamic models of the past, where water was seen largely in terms of an entropic gain after its displacement by a ligand, are now known to be much too simplistic. We adopt a set of terminology that describes water molecules as being "hot" and "cold", which we have defined as being easy and difficult to displace, respectively. The basis of these designations, which involve both enthalpic and entropic water contributions, are explored in several classes of biomolecules and structural motifs. The hallmarks for characterizing water molecules are examined, and computational tools for evaluating water-centric thermodynamics are reviewed. This Perspective's summary features guidelines for exploiting water molecules in drug discovery.

  4. 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

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

    Science.gov (United States)

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

    2015-01-01

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

  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. Overcoming T. gondii infection and intracellular protein nanocapsules as biomaterials for ultrasonically controlled drug release.

    Science.gov (United States)

    Aw, M S; Paniwnyk, L

    2017-09-26

    One of the pivotal matters of concern in intracellular drug delivery is the preparation of biomaterials containing drugs that are compatible with the host target. Nanocapsules for oral delivery are found to be suitable candidates for targeting Toxoplasma gondii (T. gondii), a maneuvering and smart protozoic parasite found across Europe and America that causes a subtle but deadly infection. To overcome this disease, there is much potential of integrating protein-based cells into bioinspired nanocompartments such as via biodegradable cross-linked disulfide polyelectrolyte nanoparticles. The inner membrane vesicle system of these protein-drugs is not as simple as one might think. It is a complex transport network that includes sequential pathways, namely, endocytosis, exocytosis and autophagy. Unfortunately, the intracellular trafficking routes for nanoparticles in cells have not been extensively and intensively investigated. Hence, there lies the need to create robust protein nanocapsules for precise tracing and triggering of drug release to combat this protozoic disease. Protein nanocapsules have the advantage over other biomaterials due to their biocompatibility, use of natural ingredients, non-invasiveness, patient compliance, cost and time effectiveness. They also offer low maintenance, non-toxicity to healthy cells and a strictly defined route toward intracellular elimination through controlled drug delivery within the therapeutic window. This review covers the unprecedented opportunities that exist for constructing advanced nanocapsules to meet the growing needs arising from many therapeutic fields. Their versatile use includes therapeutic ultrasound for tumor imaging, recombinant DNA, ligand and functional group binding, the delivery of drugs and peptides via protein nanocapsules and polyelectrolytes, ultrasound-(US)-aided drug release through the gastrointestinal (GI) tract, and the recent progress in targeting tumor cells and a vast range of cancer therapies

  8. Altered drug binding to serum proteins in pregnant women: therapeutic relevance.

    OpenAIRE

    Perucca, E; Ruprah, M; Richens, A

    1981-01-01

    The binding of diazepam, phenytoin and valproic acid to serum proteins in vitro has been compared in pregnant women of different gestational ages and in controls. The unbound fraction of each of three drugs was elevated during pregnancy (particularly during the last 8 weeks) probably due, at least in part, to a fall in serum albumin concentration. These findings may provide a partial explanation for the increase in the clearance of certain drugs during pregnancy and need to be taken into acco...

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

    Science.gov (United States)

    2008-04-01

    called the Plasmodium falciparum Chloroquine Transporter (PfCRT). While PfCRT is known to be the main molecular determinant of chloroquine resistance...proteins (such as human P-glycoprotein) and labeled PfCRT with a photoaffinity drug analogue . A manuscript is currently in preparation detailing my results...directly responsible for drug response, the Plasmodium falciparum Chloroquine Resistance Transporter (PfCRT) (Fidock et al 2000). While not a member of

  10. 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.

  11. 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.

  12. 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

  13. 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.

  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. 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.

  16. 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.

  17. 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.

  18. 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

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

    Directory of Open Access Journals (Sweden)

    Kubota K

    2004-06-01

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

  20. 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...... and proteins. EXPERT OPINION: Lipid-based DDS are safe and suitable for oral delivery of peptides and proteins. Significant progress has been made in this area with several technologies on clinical trials. However, a better understanding of the mechanism of action in vivo is needed in order to improve...

  1. 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

  2. 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

  3. Hydration dynamics near a model protein surface

    International Nuclear Information System (INIS)

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

    2003-01-01

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

  4. 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.

  5. Protein-lipid nanohybrids as emerging platforms for drug and gene delivery: Challenges and outcomes.

    Science.gov (United States)

    Gaber, Mohamed; Medhat, Waseem; Hany, Mark; Saher, Nourhan; Fang, Jia-You; Elzoghby, Ahmed

    2017-05-28

    Nanoparticulate drug delivery systems have been long used to deliver a vast range of drugs and bioactives owing to their ability to demonstrate novel physical, chemical, and/or biological properties. An exponential growth has spurred in research and development of these nanocarriers which led to the evolution of a great number of diverse nanosystems including liposomes, nanoemulsions, solid lipid nanoparticles (SLNs), micelles, dendrimers, polymeric nanoparticles (NPs), metallic NPs, and carbon nanotubes. Among them, lipid-based nanocarriers have made the largest progress whether commercially or under development. Despite this progress, these lipid-based nanocarriers suffer from several limitations that led to the development of many protein-coated lipid nanocarriers. To less extent, protein-based nanocarriers suffer from limitations that led to the fabrication of some lipid bilayer enveloping protein nanocarriers. This review discusses in-depth some limitations associated with the lipid-based or protein-based nanocarriers and the fruitful outcomes brought by protein-lipid hybridization. Also discussed are the various hybridization techniques utilized to formulate these protein-lipid nanohybrids and the mechanisms involved in the drug loading process. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. Single chain Fc-dimer-human growth hormone fusion protein for improved drug delivery.

    Science.gov (United States)

    Zhou, Li; Wang, Hsuan-Yao; Tong, Shanshan; Okamoto, Curtis T; Shen, Wei-Chiang; Zaro, Jennica L

    2017-02-01

    Fc fusion protein technology has been successfully used to generate long-acting forms of several protein therapeutics. In this study, a novel Fc-based drug carrier, single chain Fc-dimer (sc(Fc) 2 ), was designed to contain two Fc domains recombinantly linked via a flexible linker. Since the Fc dimeric structure is maintained through the flexible linker, the hinge region was omitted to further stabilize it against proteolysis and reduce FcγR-related effector functions. The resultant sc(Fc) 2 candidate preserved the neonatal Fc receptor (FcRn) binding. sc(Fc) 2 -mediated delivery was then evaluated using a therapeutic protein with a short plasma half-life, human growth hormone (hGH), as the protein drug cargo. This novel carrier protein showed a prolonged in vivo half-life and increased hGH-mediated bioactivity compared to the traditional Fc-based drug carrier. sc(Fc) 2 technology has the potential to greatly advance and expand the use of Fc-technology for improving the pharmacokinetics and bioactivity of protein therapeutics. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Prediction of adverse drug reactions using decision tree modeling.

    Science.gov (United States)

    Hammann, F; Gutmann, H; Vogt, N; Helma, C; Drewe, J

    2010-07-01

    Drug safety is of great importance to public health. The detrimental effects of drugs not only limit their application but also cause suffering in individual patients and evoke distrust of pharmacotherapy. For the purpose of identifying drugs that could be suspected of causing adverse reactions, we present a structure-activity relationship analysis of adverse drug reactions (ADRs) in the central nervous system (CNS), liver, and kidney, and also of allergic reactions, for a broad variety of drugs (n = 507) from the Swiss drug registry. Using decision tree induction, a machine learning method, we determined the chemical, physical, and structural properties of compounds that predispose them to causing ADRs. The models had high predictive accuracies (78.9-90.2%) for allergic, renal, CNS, and hepatic ADRs. We show the feasibility of predicting complex end-organ effects using simple models that involve no expensive computations and that can be used (i) in the selection of the compound during the drug discovery stage, (ii) to understand how drugs interact with the target organ systems, and (iii) for generating alerts in postmarketing drug surveillance and pharmacovigilance.

  8. 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.

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

    Science.gov (United States)

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

    2016-11-07

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

  10. 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....

  11. 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

  12. 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

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

    African Journals Online (AJOL)

    M.A. Khanday

    2016-07-26

    Jul 26, 2016 ... partments have both favourable and adverse effects on human body. The researchers ... absorption, distribution and elimination process of the drug within the body ... models can be used to understand the transport processes.

  14. 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.

  15. 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.

  16. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-12-01

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

  18. Effect of Antimalarial Drugs on Plasmodia Cell-Free Protein Synthesis

    Directory of Open Access Journals (Sweden)

    Ana Ferreras

    2002-04-01

    Full Text Available A cell-free system from Plasmodium falciparum able to translate endogenous mRNA was used to determine the effect of artemisinin, chloroquine and primaquine on the protein synthesis mechanism of the parasite. The antimalarial drugs did not inhibit the incorporation of [³H] methionine into parasite proteins even at concentrations higher than the ones found to strongly inhibit the parasite growth. Results clearly indicate that these compounds do not have a direct effect on protein synthesis activity of P. falciparum coded by endogenous mRNA.

  19. 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.

  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. The effects of drugs on human models of emotional processing: an account of antidepressant drug treatment.

    Science.gov (United States)

    Pringle, Abbie; Harmer, Catherine J

    2015-12-01

    Human models of emotional processing suggest that the direct effect of successful antidepressant drug treatment may be to modify biases in the processing of emotional information. Negative biases in emotional processing are documented in depression, and single or short-term dosing with conventional antidepressant drugs reverses these biases in depressed patients prior to any subjective change in mood. Antidepressant drug treatments also modulate emotional processing in healthy volunteers, which allows the consideration of the psychological effects of these drugs without the confound of changes in mood. As such, human models of emotional processing may prove to be useful for testing the efficacy of novel treatments and for matching treatments to individual patients or subgroups of patients.

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

    Science.gov (United States)

    Lee, Sungsoo Seth

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

  5. G-protein-coupled receptors: new approaches to maximise the impact of GPCRS in drug discovery.

    Science.gov (United States)

    Davey, John

    2004-04-01

    IBC's Drug Discovery Technology Series is a group of conferences highlighting technological advances and applications in niche areas of the drug discovery pipeline. This 2-day meeting focused on G-protein-coupled receptors (GPCRs), probably the most important and certainly the most valuable class of targets for drug discovery. The meeting was chaired by J Beesley (Vice President, European Business Development for LifeSpan Biosciences, Seattle, USA) and included 17 presentations on various aspects of GPCR activity, drug screens and therapeutic analyses. Keynote Addresses covered two of the emerging areas in GPCR regulation; receptor dimerisation (G Milligan, Professor of Molecular Pharmacology and Biochemistry, University of Glasgow, UK) and proteins that interact with GPCRs (J Bockaert, Laboratory of Functional Genomics, CNRS Montpellier, France). A third Keynote Address from W Thomsen (Director of GPCR Drug Screening, Arena Pharmaceuticals, USA) discussed Arena's general approach to drug discovery and illustrated this with reference to the development of an agonist with potential efficacy in Type II diabetes.

  6. 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.

  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. Matricellular proteins in drug delivery: Therapeutic targets, active agents, and therapeutic localization.

    Science.gov (United States)

    Sawyer, Andrew J; Kyriakides, Themis R

    2016-02-01

    Extracellular matrix is composed of a complex array of molecules that together provide structural and functional support to cells. These properties are mainly mediated by the activity of collagenous and elastic fibers, proteoglycans, and proteins such as fibronectin and laminin. ECM composition is tissue-specific and could include matricellular proteins whose primary role is to modulate cell-matrix interactions. In adults, matricellular proteins are primarily expressed during injury, inflammation and disease. Particularly, they are closely associated with the progression and prognosis of cardiovascular and fibrotic diseases, and cancer. This review aims to provide an overview of the potential use of matricellular proteins in drug delivery including the generation of therapeutic agents based on the properties and structures of these proteins as well as their utility as biomarkers for specific diseases. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. 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.

  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. 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.

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

    Science.gov (United States)

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

    2014-01-01

    Our understanding of the structural biology of G protein-coupled receptors has undergone a transformation over the past 5 years. New protein-ligand complexes are described almost monthly in high profile journals. Appreciation of how small molecules and natural ligands bind to their receptors has the potential to impact enormously how medicinal chemists approach this major class of receptor targets. An outline of the key topics in this field and some recent examples of structure- and fragment-based drug design are described. A table is presented with example views of each G protein-coupled receptor for which there is a published X-ray structure, including interactions with small molecule antagonists, partial and full agonists. The possible implications of these new data for drug design are discussed. © 2014 Elsevier B.V. All rights reserved.

  13. Zebrafish models in neuropsychopharmacology and CNS drug discovery.

    Science.gov (United States)

    Khan, Kanza M; Collier, Adam D; Meshalkina, Darya A; Kysil, Elana V; Khatsko, Sergey L; Kolesnikova, Tatyana; Morzherin, Yury Yu; Warnick, Jason E; Kalueff, Allan V; Echevarria, David J

    2017-07-01

    Despite the high prevalence of neuropsychiatric disorders, their aetiology and molecular mechanisms remain poorly understood. The zebrafish (Danio rerio) is increasingly utilized as a powerful animal model in neuropharmacology research and in vivo drug screening. Collectively, this makes zebrafish a useful tool for drug discovery and the identification of disordered molecular pathways. Here, we discuss zebrafish models of selected human neuropsychiatric disorders and drug-induced phenotypes. As well as covering a broad range of brain disorders (from anxiety and psychoses to neurodegeneration), we also summarize recent developments in zebrafish genetics and small molecule screening, which markedly enhance the disease modelling and the discovery of novel drug targets. © 2017 The British Pharmacological Society.

  14. 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)

    Herraez-Hernandez, R.; van de Merbel, N.C.; Brinkman, U.A.T.

    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

  15. 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

  16. 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.

  17. Delivery of peptide and protein drugs over the blood-brain barrier.

    Science.gov (United States)

    Brasnjevic, Ivona; Steinbusch, Harry W M; Schmitz, Christoph; Martinez-Martinez, Pilar

    2009-04-01

    Peptide and protein (P/P) drugs have been identified as showing great promises for the treatment of various neurodegenerative diseases. A major challenge in this regard, however, is the delivery of P/P drugs over the blood-brain barrier (BBB). Intense research over the last 25 years has enabled a better understanding of the cellular and molecular transport mechanisms at the BBB, and several strategies for enhanced P/P drug delivery over the BBB have been developed and tested in preclinical and clinical-experimental research. Among them, technology-based approaches (comprising functionalized nanocarriers and liposomes) and pharmacological strategies (such as the use of carrier systems and chimeric peptide technology) appear to be the most promising ones. This review combines a comprehensive overview on the current understanding of the transport mechanisms at the BBB with promising selected strategies published so far that can be applied to facilitate enhanced P/P drug delivery over the BBB.

  18. Protein Simulation Data in the Relational Model.

    Science.gov (United States)

    Simms, Andrew M; Daggett, Valerie

    2012-10-01

    High performance computing is leading to unprecedented volumes of data. Relational databases offer a robust and scalable model for storing and analyzing scientific data. However, these features do not come without a cost-significant design effort is required to build a functional and efficient repository. Modeling protein simulation data in a relational database presents several challenges: the data captured from individual simulations are large, multi-dimensional, and must integrate with both simulation software and external data sites. Here we present the dimensional design and relational implementation of a comprehensive data warehouse for storing and analyzing molecular dynamics simulations using SQL Server.

  19. 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.

  20. A model in which heat shock protein 90 targets protein-folding clefts: rationale for a new approach to neuroprotective treatment of protein folding diseases.

    Science.gov (United States)

    Pratt, William B; Morishima, Yoshihiro; Gestwicki, Jason E; Lieberman, Andrew P; Osawa, Yoichi

    2014-11-01

    In an EBM Minireview published in 2010, we proposed that the heat shock protein (Hsp)90/Hsp70-based chaperone machinery played a major role in determining the selection of proteins that have undergone oxidative or other toxic damage for ubiquitination and proteasomal degradation. The proposal was based on a model in which the Hsp90 chaperone machinery regulates signaling by modulating ligand-binding clefts. The model provides a framework for thinking about the development of neuroprotective therapies for protein-folding diseases like Alzheimer's disease (AD), Parkinson's disease (PD), and the polyglutamine expansion disorders, such as Huntington's disease (HD) and spinal and bulbar muscular atrophy (SBMA). Major aberrant proteins that misfold and accumulate in these diseases are "client" proteins of the abundant and ubiquitous stress chaperone Hsp90. These Hsp90 client proteins include tau (AD), α-synuclein (PD), huntingtin (HD), and the expanded glutamine androgen receptor (polyQ AR) (SBMA). In this Minireview, we update our model in which Hsp90 acts on protein-folding clefts and show how it forms a rational basis for developing drugs that promote the targeted elimination of these aberrant proteins. © 2014 by the Society for Experimental Biology and Medicine.

  1. 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

  2. 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.

  3. Subcellular localization for Gram positive and Gram negative bacterial proteins using linear interpolation smoothing model.

    Science.gov (United States)

    Saini, Harsh; Raicar, Gaurav; Dehzangi, Abdollah; Lal, Sunil; Sharma, Alok

    2015-12-07

    Protein subcellular localization is an important topic in proteomics since it is related to a protein׳s overall function, helps in the understanding of metabolic pathways, and in drug design and discovery. In this paper, a basic approximation technique from natural language processing called the linear interpolation smoothing model is applied for predicting protein subcellular localizations. The proposed approach extracts features from syntactical information in protein sequences to build probabilistic profiles using dependency models, which are used in linear interpolation to determine how likely is a sequence to belong to a particular subcellular location. This technique builds a statistical model based on maximum likelihood. It is able to deal effectively with high dimensionality that hinders other traditional classifiers such as Support Vector Machines or k-Nearest Neighbours without sacrificing performance. This approach has been evaluated by predicting subcellular localizations of Gram positive and Gram negative bacterial proteins. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Revati eWani

    2014-10-01

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

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. Thiomers and thiomer-based nanoparticles in protein and DNA drug delivery.

    Science.gov (United States)

    Hauptstein, Sabine; Bernkop-Schnürch, Andreas

    2012-09-01

    Thanks to advances in biotechnology, more and more highly efficient protein- and DNA-based drugs have been developed. Unfortunately, these kinds of drugs underlie poor non-parental bioavailability. To overcome hindrances like low mucosal permeability and enzymatic degradation polymeric excipients are utilized as drug carrier whereat thiolated excipients showed several promising qualities in comparison to the analogical unmodified polymer. The article deals with the comparatively easy modification of well-established polymers like chitosan or poly(acrylates) to synthesize thiomers. Further, the recently developed "next generation" thiomers e.g. preactivated or S-protected thiomers are introduced. Designative properties like mucoadhesion, uptake and permeation enhancement, efflux pump inhibition and protection against enzymatic degradation will be discussed and differences between first and next generation thiomers will be pointed out. Additionally, nanoparticles prepared with thiomers will be dealt with regarding to protein and DNA drug delivery as thiomers seem to be a promising approach to avoid parenteral application. Properties of thiomers per se and results of in vivo studies carried out so far for peptide and DNA drugs demonstrate their potential as multifunctional excipients. However, further investigations and optimizations have to be done before establishing a carrier system ready for clinical approval.

  10. 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.

  11. Markov state models of protein misfolding

    Science.gov (United States)

    Sirur, Anshul; De Sancho, David; Best, Robert B.

    2016-02-01

    Markov state models (MSMs) are an extremely useful tool for understanding the conformational dynamics of macromolecules and for analyzing MD simulations in a quantitative fashion. They have been extensively used for peptide and protein folding, for small molecule binding, and for the study of native ensemble dynamics. Here, we adapt the MSM methodology to gain insight into the dynamics of misfolded states. To overcome possible flaws in root-mean-square deviation (RMSD)-based metrics, we introduce a novel discretization approach, based on coarse-grained contact maps. In addition, we extend the MSM methodology to include "sink" states in order to account for the irreversibility (on simulation time scales) of processes like protein misfolding. We apply this method to analyze the mechanism of misfolding of tandem repeats of titin domains, and how it is influenced by confinement in a chaperonin-like cavity.

  12. 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.

  13. 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.

  14. 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.

  15. 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 ...

  16. Animal models of pain and migraine in drug discovery

    DEFF Research Database (Denmark)

    Munro, Gordon; Jansen-Olesen, Inger; Olesen, Jes

    2017-01-01

    of the most commonly used models and methods employed within 'pain and migraine' drug development will be presented. Recent advances within these disciplines suggest that, with the addition of a few extra carefully chosen ancillary models and/or endpoints, the relative value in terms of resources used...

  17. 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.

  18. 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

  19. Pushing the frontiers of atomic models for protein tertiary structure ...

    Indian Academy of Sciences (India)

    as an NP complete or NP hard problem.4,5 This notwith- standing, the dire need for tertiary structures of proteins in drug discovery and other areas6–8 has propelled the development of a multitude of computational recipes. In this article, we focus on ab initio/de novo strategies,. Bhageerath in particular, for protein tertiary ...

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

    Science.gov (United States)

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

    2018-05-30

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

  1. 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

  2. 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.

  3. 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.

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

    Science.gov (United States)

    Peng, Qiang; Mu, Huiling

    2016-03-10

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

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

    Science.gov (United States)

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

    2016-02-01

    Nature has produced intricate machinery to covalently diversify the structure of proteins after their synthesis in the ribosome. In an attempt to mimic nature, chemists have developed a large set of reactions that enable post-expression modification of proteins at pre-determined sites. These reactions are now used to selectively install particular modifications on proteins for many biological and therapeutic applications. For example, they provide an opportunity to install post-translational modifications on proteins to determine their exact biological roles. Labelling of proteins in live cells with fluorescent dyes allows protein uptake and intracellular trafficking to be tracked and also enables physiological parameters to be measured optically. Through the conjugation of potent cytotoxicants to antibodies, novel anti-cancer drugs with improved efficacy and reduced side effects may be obtained. In this Perspective, we highlight the most exciting current and future applications of chemical site-selective protein modification and consider which hurdles still need to be overcome for more widespread use.

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

    Science.gov (United States)

    Tu, Ye; Wang, Xinxia; Lu, Ying; Zhang, He; Yu, Yuan; Chen, Yan; Liu, Junjie; Sun, Zhiguo; Cui, Lili; Gao, Jing; Zhong, Yanqiang

    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.

  7. Structural Model of Drug Use among Students: The Role of Spirituality, Social Modeling and Attitude to Drugs

    Directory of Open Access Journals (Sweden)

    samira yavari

    2015-06-01

    Full Text Available Objective: This study was an attempt to explore the structural relationship between religious activity, religious struggle, attitude to drugs, social modeling, spiritual well-being, and cigarette and tobacco smoking among students. Method: For this purpose, 504 male and female students from Kharazmi University, Agricultural Paradise, and Azad University of Karaj were selected by cluster sampling and they were asked to complete spiritual well-being scale, religious activity scale, religious struggle scale, social modeling scale, negative beliefs about drugs, and the tobacco section of the high-risk behavior questionnaire. Results: The results showed that the effect of religious activity on cigarette and tobacco smoking was mediated by negative beliefs about drugs, social modeling, spiritual well-being, and incentives for drug use. Similarly, the effect of religious struggle on cigarette and tobacco smoking was mediated by spiritual well-being. Conclusion: It seems that religion prevents people joining the unhealthy peer groups by the establishment of moral discipline, internal and external rules, and healthy coping styles therefore, people get less attracted to cigarette and tobacco smoking. Accordingly, these factors should be paid more attention in prevention programs for drug use, particularly cigarette and tobacco that are considered as the gateway to other drugs.

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

    Science.gov (United States)

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

    2009-07-07

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

  9. 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. Keywords: Chagas disease, Leishmaniasis, Peptide, LACK, TRACK, Scaffold protein

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2005-01-01

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

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

    Science.gov (United States)

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

    2012-07-02

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

  12. 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.

  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. Drug Release from ß-Cyclodextrin Complexes and Drug Transfer into Model Membranes Studied by Affinity Capillary Electrophoresis.

    Science.gov (United States)

    Darwish, Kinda A; Mrestani, Yahya; Rüttinger, Hans-Hermann; Neubert, Reinhard H H

    2016-05-01

    Is to characterize the drug release from the ß-cyclodextrin (ß-CD) cavity and the drug transfer into model membranes by affinity capillary electrophoresis. Phospholipid liposomes with and without cholesterol were used to mimic the natural biological membrane. The interaction of cationic and anionic drugs with ß-CD and the interaction of the drugs with liposomes were detected separately by measuring the drug mobility in ß-CD containing buffer and liposome containing buffer; respectively. Moreover, the kinetics of drug release from ß-CD and its transfer into liposomes with or without cholesterol was studied by investigation of changes in the migration behaviours of the drugs in samples, contained drug, ß-CD and liposome, at 1:1:1 molar ratio at different time intervals; zero time, 30 min, 1, 2, 4, 6, 8, 10 and 24 h. Lipophilic drugs such as propranolol and ibuprofen were chosen for this study, because they form complexes with ß-CD. The mobility of the both drug liposome mixtures changed with time to a final state. For samples of liposomal membranes with cholesterol the final state was faster reached than without cholesterol. The study confirmed that the drug release from the CD cavity and its transfer into the model membrane was more enhanced by the competitive displacement of the drug from the ß-CD cavity by cholesterol, the membrane component. The ACE method here developed can be used to optimize the drug release from CD complexes and the drug transfer into model membranes.

  15. 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.

  16. 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.

  17. [Alternatives to the drug research and development model].

    Science.gov (United States)

    Velásquez, Germán

    2015-03-01

    One-third of the global population lacks access to medications; the situation is worse in poor countries, where up to 50% of the population lacks access. The failure of current incentive systems based in intellectual property to offer the necessary pharmaceutical products, especially in the global south, is a call to action. Problems related to drug access cannot be solved solely through improvements or modifications in the existing incentive models. The intellectual property system model does not offer sufficient innovation for developing countries; new mechanisms that effectively promote innovation and drug access simultaneously are needed. A binding international agreement on research and development, negotiated under the auspices of the World Health Organization, could provide an adequate framework for guaranteeing priority-setting, coordination, and sustainable financing of drugs at reasonable prices for developing countries.

  18. Multimodality imaging and mathematical modelling of drug delivery to glioblastomas.

    Science.gov (United States)

    Boujelben, Ahmed; Watson, Michael; McDougall, Steven; Yen, Yi-Fen; Gerstner, Elizabeth R; Catana, Ciprian; Deisboeck, Thomas; Batchelor, Tracy T; Boas, David; Rosen, Bruce; Kalpathy-Cramer, Jayashree; Chaplain, Mark A J

    2016-10-06

    Patients diagnosed with glioblastoma, an aggressive brain tumour, have a poor prognosis, with a median overall survival of less than 15 months. Vasculature within these tumours is typically abnormal, with increased tortuosity, dilation and disorganization, and they typically exhibit a disrupted blood-brain barrier (BBB). Although it has been hypothesized that the 'normalization' of the vasculature resulting from anti-angiogenic therapies could improve drug delivery through improved blood flow, there is also evidence that suggests that the restoration of BBB integrity might limit the delivery of therapeutic agents and hence their effectiveness. In this paper, we apply mathematical models of blood flow, vascular permeability and diffusion within the tumour microenvironment to investigate the effect of these competing factors on drug delivery. Preliminary results from the modelling indicate that all three physiological parameters investigated-flow rate, vessel permeability and tissue diffusion coefficient-interact nonlinearly to produce the observed average drug concentration in the microenvironment.

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

    Science.gov (United States)

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

    2012-10-01

    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. 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 and proteins. Lipid-based DDS are safe and suitable for oral delivery of peptides and proteins. Significant progress has been made in this area with several technologies on clinical trials. However, a better understanding of the mechanism of action in vivo is needed in order to improve the design and development of lipid-based DDS with the desired bioavailability and therapeutic profile.

  20. 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

  1. Cell and small animal models for phenotypic drug discovery

    Directory of Open Access Journals (Sweden)

    Szabo M

    2017-06-01

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

  2. 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.

  3. 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.

  4. PockDrug: A Model for Predicting Pocket Druggability That Overcomes Pocket Estimation Uncertainties.

    Science.gov (United States)

    Borrel, Alexandre; Regad, Leslie; Xhaard, Henri; Petitjean, Michel; Camproux, Anne-Claude

    2015-04-27

    Predicting protein druggability is a key interest in the target identification phase of drug discovery. Here, we assess the pocket estimation methods' influence on druggability predictions by comparing statistical models constructed from pockets estimated using different pocket estimation methods: a proximity of either 4 or 5.5 Å to a cocrystallized ligand or DoGSite and fpocket estimation methods. We developed PockDrug, a robust pocket druggability model that copes with uncertainties in pocket boundaries. It is based on a linear discriminant analysis from a pool of 52 descriptors combined with a selection of the most stable and efficient models using different pocket estimation methods. PockDrug retains the best combinations of three pocket properties which impact druggability: geometry, hydrophobicity, and aromaticity. It results in an average accuracy of 87.9% ± 4.7% using a test set and exhibits higher accuracy (∼5-10%) than previous studies that used an identical apo set. In conclusion, this study confirms the influence of pocket estimation on pocket druggability prediction and proposes PockDrug as a new model that overcomes pocket estimation variability.

  5. Quantitative modeling of selective lysosomal targeting for drug design

    DEFF Research Database (Denmark)

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

    2008-01-01

    log K ow. These findings were validated with experimental results and by a comparison to the properties of antimalarial drugs in clinical use. For ten active compounds, nine were predicted to accumulate to a greater extent in lysosomes than in other organelles, six of these were in the optimum range...... 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...

  6. Addressing drug adherence using an operations management model.

    Science.gov (United States)

    Nunlee, Martin; Bones, Michelle

    2014-01-01

    OBJECTIVE To provide a model that enables health systems and pharmacy benefit managers to provide medications reliably and test for reliability and validity in the analysis of adherence to drug therapy of chronic disease. SUMMARY The quantifiable model described here can be used in conjunction with behavioral designs of drug adherence assessments. The model identifies variables that can be reproduced and expanded across the management of chronic diseases with drug therapy. By creating a reorder point system for reordering medications, the model uses a methodology commonly seen in operations research. The design includes a safety stock of medication and current supply of medication, which increases the likelihood that patients will have a continuous supply of medications, thereby positively affecting adherence by removing barriers. CONCLUSION This method identifies an adherence model that quantifies variables related to recommendations from health care providers; it can assist health care and service delivery systems in making decisions that influence adherence based on the expected order cycle days and the expected daily quantity of medication administered. This model addresses the possession of medication as a barrier to adherence.

  7. PEG-Immobilized Keratin for Protein Drug Sequestration and pH-Mediated Delivery

    Directory of Open Access Journals (Sweden)

    Roche C. de Guzman

    2016-01-01

    Full Text Available Protein drugs like growth factors are promising therapeutics for damaged-tissue repair. Their local delivery often requires biomaterial carriers for achieving the therapeutic dose range while extending efficacy. In this study, polyethylene glycol (PEG and keratin were crosslinked and used as sponge-like scaffolds (KTN-PEG to absorb test proteins with different isoelectric points (pI: albumin (~5, hemoglobin (~7, and lysozyme (~11. The protein release kinetics was influenced by charge at physiological pH 7.4. The keratin network, with pI 5.3, electrostatically attracted lysozyme and repulsed albumin generating the release rate profile: albumin > hemoglobin > lysozyme. However, under acidic conditions (pH 4, all proteins including keratins were positively charged and consequently intermolecular repulsion altered the release hierarchy, now determined by size (MW diffusion: lysozyme (14 kDa > hemoglobin (64 kDa > albumin (66 kDa. Vascular endothelial growth factor C (VEGF-C, with properties comparable to lysozyme, was absorbed into the KTN-PEG scaffold. Endothelial cells cultured on this substrate had significantly larger numbers than on scaffolds without VEGF-C suggesting that the ionically bound and retained growth factor at neutral pH indirectly increased acute cell attachment and viability. PEG and keratin based sequestrations of proteins with basic pIs are therefore a feasible strategy with potential applications for selective biologics delivery.

  8. pH-sensitive polymeric nanoparticles to improve oral bioavailability of peptide/protein drugs and poorly water-soluble drugs.

    Science.gov (United States)

    Wang, Xue-Qing; Zhang, Qiang

    2012-10-01

    pH-sensitive polymeric nanoparticles are promising for oral drug delivery, especially for peptide/protein drugs and poorly water-soluble medicines. This review describes current status of pH-sensitive polymeric nanoparticles for oral drug delivery and introduces the mechanisms of drug release from them as well as possible reasons for absorption improvement, with emphasis on our contribution to this field. pH-sensitive polymeric nanoparticles are prepared mainly with polyanions, polycations, their mixtures or cross-linked polymers. The mechanisms of drug release are the result of carriers' dissolution, swelling or both of them at specific pH. The possible reasons for improvement of oral bioavailability include the following: improve drug stability, enhance mucoadhesion, prolong resident time in GI tract, ameliorate intestinal permeability and increase saturation solubility and dissolution rate for poorly water-soluble drugs. As for the advantages of pH-sensitive nanoparticles over conventional nanoparticles, we conclude that (1) most carriers used are enteric-coating materials and their safety has been approved. (2) The rapid dissolution or swelling of carriers at specific pH results in quick drug release and high drug concentration gradient, which is helpful for absorption. (3) At the specific pH carriers dissolve or swell, and the bioadhesion of carriers to mucosa becomes high because nanoparticles turn from solid to gel, which can facilitate drug absorption. Copyright © 2012 Elsevier B.V. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Jonathan E. Forde

    2016-08-01

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

  10. 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

  11. A hidden markov model derived structural alphabet for proteins.

    Science.gov (United States)

    Camproux, A C; Gautier, R; Tufféry, P

    2004-06-04

    Understanding and predicting protein structures depends on the complexity and the accuracy of the models used to represent them. We have set up a hidden Markov model that discretizes protein backbone conformation as series of overlapping fragments (states) of four residues length. This approach learns simultaneously the geometry of the states and their connections. We obtain, using a statistical criterion, an optimal systematic decomposition of the conformational variability of the protein peptidic chain in 27 states with strong connection logic. This result is stable over different protein sets. Our model fits well the previous knowledge related to protein architecture organisation and seems able to grab some subtle details of protein organisation, such as helix sub-level organisation schemes. Taking into account the dependence between the states results in a description of local protein structure of low complexity. On an average, the model makes use of only 8.3 states among 27 to describe each position of a protein structure. Although we use short fragments, the learning process on entire protein conformations captures the logic of the assembly on a larger scale. Using such a model, the structure of proteins can be reconstructed with an average accuracy close to 1.1A root-mean-square deviation and for a complexity of only 3. Finally, we also observe that sequence specificity increases with the number of states of the structural alphabet. Such models can constitute a very relevant approach to the analysis of protein architecture in particular for protein structure prediction.

  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. 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.

  14. Model for calculation of electrostatic contribution into protein stability

    Science.gov (United States)

    Kundrotas, Petras; Karshikoff, Andrey

    2003-03-01

    Existing models of the denatured state of proteins consider only one possible spatial distribution of protein charges and therefore are applicable to a limited number of cases. In this presentation a more general framework for the modeling of the denatured state is proposed. It is based on the assumption that the titratable groups of an unfolded protein can adopt a quasi-random distribution, restricted by the protein sequence. The model was tested on two proteins, barnase and N-terminal domain of the ribosomal protein L9. The calculated free energy of denaturation, Δ G( pH), reproduces the experimental data essentially better than the commonly used null approximation (NA). It was demonstrated that the seemingly good agreement with experimental data obtained by NA originates from the compensatory effect between the pair-wise electrostatic interactions and the desolvation energy of the individual sites. It was also found that the ionization properties of denatured proteins are influenced by the protein sequence.

  15. 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.

  16. Bcl-2 family of proteins as drug targets for cancer chemotherapy: the long way of BH3 mimetics from bench to bedside.

    Science.gov (United States)

    Vela, Laura; Marzo, Isabel

    2015-08-01

    Bcl-2 proteins are key determinants in the life-death balance. In recent years, proteins in this family have been identified as drug targets in the design of new anti-tumor therapies. Advances in the knowledge of the mechanism of action of anti-apoptotic and pro-apoptotic members of the Bcl-2 family have enabled the development of the so-called 'BH3 mimetics'. These compounds act by inhibiting anti-apoptotic proteins of the family, imitating the function of the BH3-only subset of pro-apoptotic members. Combinations of BH3-mimetics with anti-tumor drugs are being evaluated in both preclinical models and clinical trials. Recent advances in these approaches will be reviewed. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. 2D MI-DRAGON: a new predictor for protein-ligands interactions and theoretic-experimental studies of US FDA drug-target network, oxoisoaporphine inhibitors for MAO-A and human parasite proteins.

    Science.gov (United States)

    Prado-Prado, Francisco; García-Mera, Xerardo; Escobar, Manuel; Sobarzo-Sánchez, Eduardo; Yañez, Matilde; Riera-Fernandez, Pablo; González-Díaz, Humberto

    2011-12-01

    There are many pairs of possible Drug-Proteins Interactions that may take place or not (DPIs/nDPIs) between drugs with high affinity/non-affinity for different proteins. This fact makes expensive in terms of time and resources, for instance, the determination of all possible ligands-protein interactions for a single drug. In this sense, we can use Quantitative Structure-Activity Relationships (QSAR) models to carry out rational DPIs prediction. Unfortunately, almost all QSAR models predict activity against only one target. To solve this problem we can develop multi-target QSAR (mt-QSAR) models. In this work, we introduce the technique 2D MI-DRAGON a new predictor for DPIs based on two different well-known software. We use the software MARCH-INSIDE (MI) to calculate 3D structural parameters for targets and the software DRAGON was used to calculated 2D molecular descriptors all drugs showing known DPIs present in the Drug Bank (US FDA benchmark dataset). Both classes of parameters were used as input of different Artificial Neural Network (ANN) algorithms to seek an accurate non-linear mt-QSAR predictor. The best ANN model found is a Multi-Layer Perceptron (MLP) with profile MLP 21:21-31-1:1. This MLP classifies correctly 303 out of 339 DPIs (Sensitivity = 89.38%) and 480 out of 510 nDPIs (Specificity = 94.12%), corresponding to training Accuracy = 92.23%. The validation of the model was carried out by means of external predicting series with Sensitivity = 92.18% (625/678 DPIs; Specificity = 90.12% (730/780 nDPIs) and Accuracy = 91.06%. 2D MI-DRAGON offers a good opportunity for fast-track calculation of all possible DPIs of one drug enabling us to re-construct large drug-target or DPIs Complex Networks (CNs). For instance, we reconstructed the CN of the US FDA benchmark dataset with 855 nodes 519 drugs+336 targets). We predicted CN with similar topology (observed and predicted values of average distance are equal to 6.7 vs. 6.6). These CNs can be used to explore

  18. Distribution of Animal Drugs among Curd, Whey, and Milk Protein Fractions in Spiked Skim Milk and Whey.

    Science.gov (United States)

    Shappell, Nancy W; Shelver, Weilin L; Lupton, Sara J; Fanaselle, Wendy; Van Doren, Jane M; Hakk, Heldur

    2017-02-01

    It is important to understand the partitioning of drugs in processed milk and milk products, when drugs are present in raw milk, in order to estimate the potential consumer exposure. Radioisotopically labeled erythromycin, ivermectin, ketoprofen, oxytetracycline, penicillin G, sulfadimethoxine, and thiabendazole were used to evaluate the distribution of animal drugs among rennet curd, whey, and protein fractions from skim cow milk. Our previous work reported the distribution of these same drugs between skim and fat fractions of milk. Drug distribution between curd and whey was significantly correlated (R 2 = 0.70) to the drug's lipophilicity (log P), with improved correlation using log D (R 2 = 0.95). Distribution of drugs was concentration independent over the range tested (20-2000 nM). With the exception of thiabendazole and ivermectin, more drug was associated with whey protein than casein on a nmol/g protein basis (oxytetracycline experiment not performed). These results provide insights into the distribution of animal drug residues, if present in cow milk, among milk fractions, with possible extrapolation to milk products.

  19. 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.

  20. 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.

  1. In silico modeling of the yeast protein and protein family interaction network

    Science.gov (United States)

    Goh, K.-I.; Kahng, B.; Kim, D.

    2004-03-01

    Understanding of how protein interaction networks of living organisms have evolved or are organized can be the first stepping stone in unveiling how life works on a fundamental ground. Here we introduce an in silico ``coevolutionary'' model for the protein interaction network and the protein family network. The essential ingredient of the model includes the protein family identity and its robustness under evolution, as well as the three previously proposed: gene duplication, divergence, and mutation. This model produces a prototypical feature of complex networks in a wide range of parameter space, following the generalized Pareto distribution in connectivity. Moreover, we investigate other structural properties of our model in detail with some specific values of parameters relevant to the yeast Saccharomyces cerevisiae, showing excellent agreement with the empirical data. Our model indicates that the physical constraints encoded via the domain structure of proteins play a crucial role in protein interactions.

  2. Prediction of allosteric sites on protein surfaces with an elastic-network-model-based thermodynamic method.

    Science.gov (United States)

    Su, Ji Guo; Qi, Li Sheng; Li, Chun Hua; Zhu, Yan Ying; Du, Hui Jing; Hou, Yan Xue; Hao, Rui; Wang, Ji Hua

    2014-08-01

    Allostery is a rapid and efficient way in many biological processes to regulate protein functions, where binding of an effector at the allosteric site alters the activity and function at a distant active site. Allosteric regulation of protein biological functions provides a promising strategy for novel drug design. However, how to effectively identify the allosteric sites remains one of the major challenges for allosteric drug design. In the present work, a thermodynamic method based on the elastic network model was proposed to predict the allosteric sites on the protein surface. In our method, the thermodynamic coupling between the allosteric and active sites was considered, and then the allosteric sites were identified as those where the binding of an effector molecule induces a large change in the binding free energy of the protein with its ligand. Using the proposed method, two proteins, i.e., the 70 kD heat shock protein (Hsp70) and GluA2 alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptor, were studied and the allosteric sites on the protein surface were successfully identified. The predicted results are consistent with the available experimental data, which indicates that our method is a simple yet effective approach for the identification of allosteric sites on proteins.

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

    Science.gov (United States)

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

    2006-01-01

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

  4. An attention-based effective neural model for drug-drug interactions extraction.

    Science.gov (United States)

    Zheng, Wei; Lin, Hongfei; Luo, Ling; Zhao, Zhehuan; Li, Zhengguang; Zhang, Yijia; Yang, Zhihao; Wang, Jian

    2017-10-10

    Drug-drug interactions (DDIs) often bring unexpected side effects. The clinical recognition of DDIs is a crucial issue for both patient safety and healthcare cost control. However, although text-mining-based systems explore various methods to classify DDIs, the classification performance with regard to DDIs in long and complex sentences is still unsatisfactory. In this study, we propose an effective model that classifies DDIs from the literature by combining an attention mechanism and a recurrent neural network with long short-term memory (LSTM) units. In our approach, first, a candidate-drug-oriented input attention acting on word-embedding vectors automatically learns which words are more influential for a given drug pair. Next, the inputs merging the position- and POS-embedding vectors are passed to a bidirectional LSTM layer whose outputs at the last time step represent the high-level semantic information of the whole sentence. Finally, a softmax layer performs DDI classification. Experimental results from the DDIExtraction 2013 corpus show that our system performs the best with respect to detection and classification (84.0% and 77.3%, respectively) compared with other state-of-the-art methods. In particular, for the Medline-2013 dataset with long and complex sentences, our F-score far exceeds those of top-ranking systems by 12.6%. Our approach effectively improves the performance of DDI classification tasks. Experimental analysis demonstrates that our model performs better with respect to recognizing not only close-range but also long-range patterns among words, especially for long, complex and compound sentences.

  5. 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.

  6. 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

  7. 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

  8. 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.

  9. A comprehensive screening platform for aerosolizable protein formulations for intranasal and pulmonary drug delivery.

    Science.gov (United States)

    Röhm, Martina; Carle, Stefan; Maigler, Frank; Flamm, Johannes; Kramer, Viktoria; Mavoungou, Chrystelle; Schmid, Otmar; Schindowski, Katharina

    2017-10-30

    Aerosolized administration of biopharmaceuticals to the airways is a promising route for nasal and pulmonary drug delivery, but - in contrast to small molecules - little is known about the effects of aerosolization on safety and efficacy of biopharmaceuticals. Proteins are sensitive against aerosolization-associated shear stress. Tailored formulations can shield proteins and enhance permeation, but formulation development requires extensive screening approaches. Thus, the aim of this study was to develop a cell-based in vitro technology platform that includes screening of protein quality after aerosolization and transepithelial permeation. For efficient screening, a previously published aerosolization-surrogate assay was used in a design of experiments approach to screen suitable formulations for an IgG and its antigen-binding fragment (Fab) as exemplary biopharmaceuticals. Efficient, dose-controlled aerosol-cell delivery was performed with the ALICE-CLOUD system containing RPMI 2650 epithelial cells at the air-liquid interface. We could demonstrate that our technology platform allows for rapid and efficient screening of formulations consisting of different excipients (here: arginine, cyclodextrin, polysorbate, sorbitol, and trehalose) to minimize aerosolization-induced protein aggregation and maximize permeation through an in vitro epithelial cell barrier. Formulations reduced aggregation of native Fab and IgG relative to vehicle up to 50% and enhanced transepithelial permeation rate up to 2.8-fold. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

  10. 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

  11. 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.

  12. Post processing of protein-compound docking for fragment-based drug discovery (FBDD): in-silico structure-based drug screening and ligand-binding pose prediction.

    Science.gov (United States)

    Fukunishi, Yoshifumi

    2010-01-01

    For fragment-based drug development, both hit (active) compound prediction and docking-pose (protein-ligand complex structure) prediction of the hit compound are important, since chemical modification (fragment linking, fragment evolution) subsequent to the hit discovery must be performed based on the protein-ligand complex structure. However, the naïve protein-compound docking calculation shows poor accuracy in terms of docking-pose prediction. Thus, post-processing of the protein-compound docking is necessary. Recently, several methods for the post-processing of protein-compound docking have been proposed. In FBDD, the compounds are smaller than those for conventional drug screening. This makes it difficult to perform the protein-compound docking calculation. A method to avoid this problem has been reported. Protein-ligand binding free energy estimation is useful to reduce the procedures involved in the chemical modification of the hit fragment. Several prediction methods have been proposed for high-accuracy estimation of protein-ligand binding free energy. This paper summarizes the various computational methods proposed for docking-pose prediction and their usefulness in FBDD.

  13. The research methods and model of protein turnover in animal

    International Nuclear Information System (INIS)

    Wu Xilin; Yang Feng

    2002-01-01

    The author discussed the concept and research methods of protein turnover in animal body. The existing problems and the research results of animal protein turnover in recent years were presented. Meanwhile, the measures to improve the models of animal protein turnover were analyzed

  14. 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…

  15. 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.

  16. 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

  17. How Diverse are the Protein-Bound Conformations of Small-Molecule Drugs and Cofactors?

    Science.gov (United States)

    Friedrich, Nils-Ole; Simsir, Méliné; Kirchmair, Johannes

    2018-03-01

    Knowledge of the bioactive conformations of small molecules or the ability to predict them with theoretical methods is of key importance to the design of bioactive compounds such as drugs, agrochemicals and cosmetics. Using an elaborate cheminformatics pipeline, which also evaluates the support of individual atom coordinates by the measured electron density, we compiled a complete set (“Sperrylite Dataset”) of high-quality structures of protein-bound ligand conformations from the PDB. The Sperrylite Dataset consists of a total of 10,936 high-quality structures of 4548 unique ligands. Based on this dataset, we assessed the variability of the bioactive conformations of 91 small molecules—each represented by a minimum of ten structures—and found it to be largely independent of the number of rotatable bonds. Sixty-nine molecules had at least two distinct conformations (defined by an RMSD greater than 1 Å). For a representative subset of 17 approved drugs and cofactors we observed a clear trend for the formation of few clusters of highly similar conformers. Even for proteins that share a very low sequence identity, ligands were regularly found to adopt similar conformations. For cofactors, a clear trend for extended conformations was measured, although in few cases also coiled conformers were observed. The Sperrylite Dataset is available for download from http://www.zbh.uni-hamburg.de/sperrylite_dataset.

  18. Addressing challenges of heterogeneous tumor treatment through bispecific protein-mediated pretargeted drug delivery.

    Science.gov (United States)

    Yang, Qi; Parker, Christina L; McCallen, Justin D; Lai, Samuel K

    2015-12-28

    Tumors are frequently characterized by genomically and phenotypically distinct cancer cell subpopulations within the same tumor or between tumor lesions, a phenomenon termed tumor heterogeneity. These diverse cancer cell populations pose a major challenge to targeted delivery of diagnostic and/or therapeutic agents, as the conventional approach of conjugating individual ligands to nanoparticles is often unable to facilitate intracellular delivery to the full spectrum of cancer cells present in a given tumor lesion or patient. As a result, many cancers are only partially suppressed, leading to eventual tumor regrowth and/or the development of drug-resistant tumors. Pretargeting (multistep targeting) approaches involving the administration of 1) a cocktail of bispecific proteins that can collectively bind to the entirety of a mixed tumor population followed by 2) nanoparticles containing therapeutic and/or diagnostic agents that can bind to the bispecific proteins accumulated on the surface of target cells offer the potential to overcome many of the challenges associated with drug delivery to heterogeneous tumors. Despite its considerable success in improving the efficacy of radioimmunotherapy, the pretargeting strategy remains underexplored for a majority of nanoparticle therapeutic applications, especially for targeted delivery to heterogeneous tumors. In this review, we will present concepts in tumor heterogeneity, the shortcomings of conventional targeted systems, lessons learned from pretargeted radioimmunotherapy, and important considerations for harnessing the pretargeting strategy to improve nanoparticle delivery to heterogeneous tumors. Copyright © 2015 Elsevier B.V. All rights reserved.

  19. 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

  20. 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.

  1. 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.

  2. 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

  3. Conformational transition paths harbor structures useful for aiding drug discovery and understanding enzymatic mechanisms in protein kinases.

    Science.gov (United States)

    Wong, Chung F

    2016-01-01

    This short article examines the usefulness of fast simulations of conformational transition paths in elucidating enzymatic mechanisms and guiding drug discovery for protein kinases. It applies the transition path method in the MOIL software package to simulate the paths of conformational transitions between six pairs of structures from the Protein Data Bank. The structures along the transition paths were found to resemble experimental structures that mimic transient structures believed to form during enzymatic catalysis or conformational transitions, or structures that have drug candidates bound. These findings suggest that such simulations could provide quick initial insights into the enzymatic mechanisms or pathways of conformational transitions of proteins kinases, or could provide structures useful for aiding structure-based drug design. © 2015 The Protein Society.

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

    KAUST Repository

    Zhang, Yang

    2016-01-01

    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

  5. A histidine-rich protein 2-based malaria drug sensitivity assay for field use.

    Science.gov (United States)

    Noedl, Harald; Attlmayr, Bernhard; Wernsdorfer, Walther H; Kollaritsch, Herwig; Miller, Robert S

    2004-12-01

    With the spread of antimalarial drug resistance, simple and reliable tools for the assessment of antimalarial drug resistance, particularly in endemic regions and under field conditions, have become more important than ever before. We therefore developed a histidine-rich protein 2 (HRP2)-based drug sensitivity assay for testing of fresh isolates of Plasmodium falciparum in the field. In contrast to the HRP2 laboratory assay, the field assay uses a procedure that further simplifies the handling and culturing of malaria parasites by omitting centrifugation, washing, the use of serum, and dilution with uninfected red blood cells. A total of 40 fresh Plasmodium falciparum isolates were successfully tested for their susceptibility to dihydroartemisinin, mefloquine, quinine, and chloroquine (50% inhibitory concentration [IC50] = 3.43, 61.89, 326.75, and 185.31 nM, respectively). Results very closely matched those obtained with a modified World Health Organization schizont maturation assay (R2 = 0.96, P < 0.001; mean log difference at IC50 = 0.054).

  6. Towards a pragmatic human migraine model for drug testing

    DEFF Research Database (Denmark)

    Hansen, Emma Katrine; Olesen, Jes

    2017-01-01

    Background A model for the testing of novel anti-migraine drugs should preferably use healthy volunteers for ease of recruiting. Isosorbide-5-mononitrate (5-ISMN) provokes headache in healthy volunteers with some migraine features such as pulsating pain quality and aggravation by physical activity.......003). Difference in area under the headache score curve (AUC) 0-4 hours between sumatriptan and placebo was not significant ( p = 0.30). Conclusion 5-ISMN is a very powerful inducer of migraine-like headache in healthy individuals but the headache does not respond to sumatriptan. The model is not useful for future...

  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. Failure of Chemotherapy in Hepatocellular Carcinoma Due to Impaired and Dysregulated Primary Liver Drug Metabolizing Enzymes and Drug Transport Proteins: What to Do?

    Science.gov (United States)

    Ul Islam, Salman; Ahmed, Muhammad Bilal; Shehzad, Adeeb; Ul-Islam, Mazhar; Lee, Young Sup

    2018-05-28

    Most of the drugs are metabolized in the liver by the action of drug metabolizing enzymes. In hepatocellular carcinoma (HCC), primary drug metabolizing enzymes are severely dysregulated, leading to failure of chemotherapy. Sorafenib is the only standard systemic drug available, but it still presents certain limitations, and much effort is required to understand who is responsive and who is refractory to the drug. Preventive and therapeutic approaches other than systemic chemotherapy include vaccination, chemoprevention, liver transplantation, surgical resection, and locoregional therapies. This review details the dysregulation of primary drug metabolizing enzymes and drug transport proteins of the liver in HCC and their influence on chemotherapeutic drugs. Furthermore, it emphasizes the adoption of safe alternative therapeutic strategies to chemotherapy. The future of HCC treatment should emphasize the understanding of resistance mechanisms and the finding of novel, safe, and efficacious therapeutic strategies, which will surely benefit patients affected by advanced HCC. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

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

    International Nuclear Information System (INIS)

    Shao, Qing; Hall, Carol K

    2016-01-01

    The adsorption of proteins on nanoparticles results in the formation of the protein corona, the composition of which determines how nanoparticles influence their biological surroundings. We seek to better understand corona formation by developing models that describe protein adsorption on nanoparticles using computer simulation results as data. Using a coarse-grained protein model, discontinuous molecular dynamics simulations are conducted to investigate the adsorption of two small proteins (Trp-cage and WW domain) on a model nanoparticle of diameter 10.0 nm at protein concentrations ranging from 0.5 to 5 mM. The resulting adsorption isotherms are well described by the Langmuir, Freundlich, Temkin and Kiselev models, but not by the Elovich, Fowler–Guggenheim and Hill–de Boer models. We also try to develop a generalized model that can describe protein adsorption equilibrium on nanoparticles of different diameters in terms of dimensionless size parameters. The simulation results for three proteins (Trp-cage, WW domain, and GB3) on four nanoparticles (diameter  =  5.0, 10.0, 15.0, and 20.0 nm) illustrate both the promise and the challenge associated with developing generalized models of protein adsorption on nanoparticles. (paper)

  10. 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.

  11. Matrix Metalloproteinases Contribute to Neuronal Dysfunction in Animal Models of Drug Dependence, Alzheimer's Disease, and Epilepsy

    Directory of Open Access Journals (Sweden)

    Hiroyuki Mizoguchi

    2011-01-01

    Full Text Available Matrix metalloproteinases (MMPs and tissue inhibitors of metalloproteinases (TIMPs remodel the pericellular environment by regulating the cleavage of extracellular matrix proteins, cell surface components, neurotransmitter receptors, and growth factors that mediate cell adhesion, synaptogenesis, synaptic plasticity, and long-term potentiation. Interestingly, increased MMP activity and dysregulation of the balance between MMPs and TIMPs have also been implicated in various pathologic conditions. In this paper, we discuss various animal models that suggest that the activation of the gelatinases MMP-2 and MMP-9 is involved in pathogenesis of drug dependence, Alzheimer's disease, and epilepsy.

  12. Interaction of S-layer proteins of Lactobacillus kefir with model membranes and cells.

    Science.gov (United States)

    Hollmann, Axel; Delfederico, Lucrecia; Santos, Nuno C; Disalvo, E Anibal; Semorile, Liliana

    2018-06-01

    In previous works, it was shown that S-layer proteins from Lactobacillus kefir were able to recrystallize and stabilize liposomes, this feature reveling a great potential for developing liposomal-based carriers. Despite previous studies on this subject are important milestones, a number of questions remain unanswered. In this context, the feasibility of S-layer proteins as a biomaterial for drug delivery was evaluated in this work. First, S-layer proteins were fully characterized by electron microscopy, 2D-electrophoresis, and anionic exchange chromatography coupled with pulsed amperometric detection (HPAEC-PAD). Afterward, interactions of S-layer proteins with model lipid membranes were evaluated, showing that proteins adsorb to the lipid surface following a non-fickean or anomalous diffusion, when positively charged lipid were employed, suggesting that electrostatic interaction is a key factor in the recrystallization process on these proteins. Finally, the interaction of S-layer coated liposomes with Caco-2 cell line was assessed: First, cytotoxicity of formulations was tested showing no cytotoxic effects in S-layer coated vesicles. Second, by flow cytometry, it was observed an increased ability to transfer cargo molecules into Caco-2 cells from S-layer coated liposomes in comparison to control ones. All data put together, supports the idea that a combination of adhesive properties of S-layer proteins concomitant with higher stability of S-layer coated liposomes represents an exciting starting point in the development of new drug carriers.

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. Mechanistic systems modeling to guide drug discovery and development.

    Science.gov (United States)

    Schmidt, Brian J; Papin, Jason A; Musante, Cynthia J

    2013-02-01

    A crucial question that must be addressed in the drug development process is whether the proposed therapeutic target will yield the desired effect in the clinical population. Pharmaceutical and biotechnology companies place a large investment on research and development, long before confirmatory data are available from human trials. Basic science has greatly expanded the computable knowledge of disease processes, both through the generation of large omics data sets and a compendium of studies assessing cellular and systemic responses to physiologic and pathophysiologic stimuli. Given inherent uncertainties in drug development, mechanistic systems models can better inform target selection and the decision process for advancing compounds through preclinical and clinical research. Copyright © 2012 Elsevier Ltd. All rights reserved.

  18. 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...

  19. Latest animal models for anti-HIV drug discovery.

    Science.gov (United States)

    Sliva, Katja

    2015-02-01

    HIV research is limited by the fact that lentiviruses are highly species specific. The need for appropriate models to promote research has led to the development of many elaborate surrogate animal models. This review looks at the history of animal models for HIV research. Although natural animal lentivirus infections and chimeric viruses such as chimera between HIV and simian immunodeficiency virus and simian-tropic HIV are briefly discussed, the main focus is on small animal models, including the complex design of the 'humanized' mouse. The review also traces the historic evolution and milestones as well as depicting current models and future prospects for HIV research. HIV research is a complex and challenging task that is highly manpower-, money- and time-consuming. Besides factors such as hypervariability and latency, the lack of appropriate animal models that exhibit and recapitulate the entire infectious process of HIV, is one of the reasons behind the failure to eliminate the lentivirus from the human population. This obstacle has led to the exploitation and further development of many sophisticated surrogate animal models for HIV research. While there is no animal model that perfectly mirrors and mimics HIV infections in humans, there are a variety of host species and viruses that complement each other. Combining the insights from each model, and critically comparing the results obtained with data from human clinical trials should help expand our understanding of HIV pathogenesis and drive future drug development.

  20. Assessment and Challenges of Ligand Docking into Comparative Models of G-Protein Coupled Receptors

    DEFF Research Database (Denmark)

    Nguyen, E.D.; Meiler, J.; Norn, C.

    2013-01-01

    screening and to design and optimize drug candidates. However, low sequence identity between receptors, conformational flexibility, and chemical diversity of ligands present an enormous challenge to molecular modeling approaches. It is our hypothesis that rapid Monte-Carlo sampling of protein backbone...... extracellular loop. Furthermore, these models are consistently correlated with low Rosetta energy score. To predict their binding modes, ligand conformers of the 14 ligands co-crystalized with the GPCRs were docked against the top ranked comparative models. In contrast to the comparative models themselves...

  1. Structure of liposome encapsulating proteins characterized by X-ray scattering and shell-modeling

    International Nuclear Information System (INIS)

    Hirai, Mitsuhiro; Kimura, Ryota; Takeuchi, Kazuki; Hagiwara, Yoshihiko; Kawai-Hirai, Rika; Ohta, Noboru; Igarashi, Noriyuki; Shimuzu, Nobutaka

    2013-01-01

    Wide-angle X-ray scattering data using a third-generation synchrotron radiation source are presented. Lipid liposomes are promising drug delivery systems because they have superior curative effects owing to their high adaptability to a living body. Lipid liposomes encapsulating proteins were constructed and the structures examined using synchrotron radiation small- and wide-angle X-ray scattering (SR-SWAXS). The liposomes were prepared by a sequential combination of natural swelling, ultrasonic dispersion, freeze-throw, extrusion and spin-filtration. The liposomes were composed of acidic glycosphingolipid (ganglioside), cholesterol and phospholipids. By using shell-modeling methods, the asymmetric bilayer structure of the liposome and the encapsulation efficiency of proteins were determined. As well as other analytical techniques, SR-SWAXS and shell-modeling methods are shown to be a powerful tool for characterizing in situ structures of lipid liposomes as an important candidate of drug delivery systems

  2. 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.

  3. 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.

  4. 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

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

    Science.gov (United States)

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

    2017-11-27

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

  6. 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.

  7. 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

  8. Rhodamine/Nanodiamond as a System Model for Drug Carrier.

    Science.gov (United States)

    Reina, G; Orlanducci, S; Cairone, C; Tamburri, E; Lenti, S; Cianchetta, I; Rossi, M; Terranova, M L

    2015-02-01

    In this paper we present some strategies that are being developed in our labs towards enabling nanodiamond-based applications for drug delivery. Rhodamine B (RhB) has been choosen as model molecule to study the loading of nanodiamonds with active moieties and the conditions for their controlled release. In order to test the chemical/physical interactions between functionalized detonation nanodiamond (DND) and complex molecules, we prepared and tested different RhB@DND systems, with RhB adsorbed or linked by ionic bonding to the DND surface. The chemical state of the DND surfaces before conjugation with the RhB molecules, and the chemical features of the DND-RhB interactions have been deeply analysed by coupling DND with Au nanoparticles and taking advantage of surface enhanced Raman spectroscopy SERS. The effects due to temperature and pH variations on the process of RhB release from the DND carrier have been also investigated. The amounts of released molecules are consistent with those required for effective drug action in conventional therapeutic applications, and this makes the DND promising nanostructured cargos for drug delivery applications.

  9. The impact of pharmacophore modeling in drug design.

    Science.gov (United States)

    Guner, Osman F

    2005-07-01

    With the reliable use of computer simulations in scientific research, it is possible to achieve significant increases in productivity as well as a reduction in research costs compared with experimental approaches. For example, computer-simulation can substantially enchance productivity by focusing the scientist to better, more informed choices, while also driving the 'fail-early' concept to result in a significant reduction in cost. Pharmacophore modeling is a reliable computer-aided design tool used in the discovery of new classes of compounds for a given therapeutic category. This commentary will briefly review the benefits and applications of this technology in drug discovery and design, and will also highlight its historical evolution. The two most commonly used approaches for pharmacophore model development will be discussed, and several examples of how this technology was successfully applied to identify new potent leads will be provided. The article concludes with a brief outline of the controversial issue of patentability of pharmacophore models.

  10. Quantum Mechanics/Molecular Mechanics Modeling of Drug Metabolism

    DEFF Research Database (Denmark)

    Lonsdale, Richard; Fort, Rachel M; Rydberg, Patrik

    2016-01-01

    )-mexiletine in CYP1A2 with hybrid quantum mechanics/molecular mechanics (QM/MM) methods, providing a more detailed and realistic model. Multiple reaction barriers have been calculated at the QM(B3LYP-D)/MM(CHARMM27) level for the direct N-oxidation and H-abstraction/rebound mechanisms. Our calculated barriers......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...... indicate that the direct N-oxidation mechanism is preferred and proceeds via the doublet spin state of Compound I. Molecular dynamics simulations indicate that the presence of an ordered water molecule in the active site assists in the binding of mexiletine in the active site...

  11. A unified algorithm for predicting partition coefficients for PBPK modeling of drugs and environmental chemicals

    International Nuclear Information System (INIS)

    Peyret, Thomas; Poulin, Patrick; Krishnan, Kannan

    2010-01-01

    The algorithms in the literature focusing to predict tissue:blood PC (P tb ) for environmental chemicals and tissue:plasma PC based on total (K p ) or unbound concentration (K pu ) for drugs differ in their consideration of binding to hemoglobin, plasma proteins and charged phospholipids. The objective of the present study was to develop a unified algorithm such that P tb , K p and K pu for both drugs and environmental chemicals could be predicted. The development of the unified algorithm was accomplished by integrating all mechanistic algorithms previously published to compute the PCs. Furthermore, the algorithm was structured in such a way as to facilitate predictions of the distribution of organic compounds at the macro (i.e. whole tissue) and micro (i.e. cells and fluids) levels. The resulting unified algorithm was applied to compute the rat P tb , K p or K pu of muscle (n = 174), liver (n = 139) and adipose tissue (n = 141) for acidic, neutral, zwitterionic and basic drugs as well as ketones, acetate esters, alcohols, aliphatic hydrocarbons, aromatic hydrocarbons and ethers. The unified algorithm reproduced adequately the values predicted previously by the published algorithms for a total of 142 drugs and chemicals. The sensitivity analysis demonstrated the relative importance of the various compound properties reflective of specific mechanistic determinants relevant to prediction of PC values of drugs and environmental chemicals. Overall, the present unified algorithm uniquely facilitates the computation of macro and micro level PCs for developing organ and cellular-level PBPK models for both chemicals and drugs.

  12. Free fatty acids-sensing G protein-coupled receptors in drug targeting and therapeutics.

    Science.gov (United States)

    Yonezawa, Tomo; Kurata, Riho; Yoshida, Kaori; Murayama, Masanori A; Cui, Xiaofeng; Hasegawa, Akihiko

    2013-01-01

    G protein-coupled receptor (GPCR) (also known as seven-transmembrane domain receptor) superfamily represents the largest protein family in the human genome. These receptors respond to various physiological ligands such as photons, odors, pheromones, hormones, ions, and small molecules including amines, amino acids to large peptides and steroids. Thus, GPCRs are involved in many diseases and the target of around half of all conventional drugs. The physiological roles of free fatty acids (FFAs), in particular, long-chain FFAs, are important for the development of many metabolic disease including obesity, diabetes, and atherosclerosis. In the past half decade, deorphanization of several GPCRs has revealed that GPR40, GPR41, GPR43, GPR84 and GPR120 sense concentration of extracellular FFAs with various carbon chain lengths. GPR40 and GPR120 are activated by medium- and long-chain FFAs. GPR84 is activated by medium- chain, but not long-chain, FFAs. GPR41 and GPR43 are activated by short-chain FFAs. GPR40 is highly expressed in pancreatic beta cells and plays a crucial role in FFAs-induced insulin secretion. GPR120 is mainly expressed in enteroendocrine cells and plays an important role for FFAs-induced glucagon-like peptide-1. GPR43 is abundant in leukocytes and adipose tissue, whilst GPR41 is highly expressed in adipose tissue, the pancreas and leukocytes. GPR84 is expressed in leukocytes and monocyte/macrophage. This review aims to shed light on the physiological roles and development of drugs targeting these receptors.

  13. Biodegradable protein-based rockets for drug transportation and light-triggered release.

    Science.gov (United States)

    Wu, Zhiguang; Lin, Xiankun; Zou, Xian; Sun, Jianmin; He, Qiang

    2015-01-14

    We describe a biodegradable, self-propelled bovine serum albumin/poly-l-lysine (PLL/BSA) multilayer rocket as a smart vehicle for efficient anticancer drug encapsulation/delivery to cancer cells and near-infrared light controlled release. The rockets were constructed by a template-assisted layer-by-layer assembly of the PLL/BSA layers, followed by incorporation of a heat-sensitive gelatin hydrogel containing gold nanoparticles, doxorubicin, and catalase. These rockets can rapidly deliver the doxorubicin to the targeted cancer cell with a speed of up to 68 μm/s, through a combination of biocatalytic bubble propulsion and magnetic guidance. The photothermal effect of the gold nanoparticles under NIR irradiation enable the phase transition of the gelatin hydrogel for rapid release of the loaded doxorubicin and efficient killing of the surrounding cancer cells. Such biodegradable and multifunctional protein-based microrockets provide a convenient and efficient platform for the rapid delivery and controlled release of therapeutic drugs.

  14. [Glucokinase and glucokinase regulatory proteins as molecular targets for novel antidiabetic drugs].

    Science.gov (United States)

    Rubtsov, P M; Igudin, E L; Tiulpakov, A N

    2015-01-01

    The impairment of glucose homeostasis leads to hyperglycemia and type-2 diabetes mellitus. Glucokinase (GK), an enzyme that catalyzes the conversion of glucose to glucose-6-phosphate in pancreatic ß-cells, liver hepatocytes, specific hypothalamic neurons, and intestine enterocytes, is a key regulator of glucose homeostasis. In hepatocytes, GK controls the glucose uptake and glycogen synthesis and inhibits the glucose synthesis via the gluconeogenesis pathway. Glucokinase regulatory protein (GKRP) synthesized in hepatocytes acts as an endogenous GK inhibitor. During fasting, GKRP binds GK, inactivates it, and transports it into the cell nucleus, thus isolating it from the hepatocyte carbohydrate metabolism. In the beginning of the 2000s, the research was mainly focused on the development and trials of the small molecule GK activators as potential antidiabetic glucose-lowering drugs. However, the use of such substances increased the risk of hypoglycemia, and clinical studies of most synthetic GK activators are currently discontinued. Allosteric inhibitors of the GK-GKRP interaction are coming as alternative agents increasing the GK activity that can substitute GKA. In this review, we discuss the recent advances and the current state of art in the development of potential antidiabetic drugs targeted to GK as a key regulator of glucose homeostasis.

  15. 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

  16. 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.

  17. Modelling Protein Dynamics on the Microsecond Time Scale

    DEFF Research Database (Denmark)

    Siuda, Iwona Anna

    Recent years have shown an increase in coarse-grained (CG) molecular dynamics simulations, providing structural and dynamic details of large proteins and enabling studies of self-assembly of biological materials. It is not easy to acquire such data experimentally, and access is also still limited...... in atomistic simulations. During her PhD studies, Iwona Siuda used MARTINI CG models to study the dynamics of different globular and membrane proteins. In several cases, the MARTINI model was sufficient to study conformational changes of small, purely alpha-helical proteins. However, in studies of larger......ELNEDIN was therefore proposed as part of the work. Iwona Siuda’s results from the CG simulations had biological implications that provide insights into possible mechanisms of the periplasmic leucine-binding protein, the sarco(endo)plasmic reticulum calcium pump, and several proteins from the saposin-like proteins...

  18. 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.

  19. Fragment-Based Drug Discovery of Potent Protein Kinase C Iota Inhibitors.

    Science.gov (United States)

    Kwiatkowski, Jacek; Liu, Boping; Tee, Doris Hui Ying; Chen, Guoying; Ahmad, Nur Huda Binte; Wong, Yun Xuan; Poh, Zhi Ying; Ang, Shi Hua; Tan, Eldwin Sum Wai; Ong, Esther Hq; Nurul Dinie; Poulsen, Anders; Pendharkar, Vishal; Sangthongpitag, Kanda; Lee, May Ann; Sepramaniam, Sugunavathi; Ho, Soo Yei; Cherian, Joseph; Hill, Jeffrey; Keller, Thomas H; Hung, Alvin W

    2018-05-24

    Protein kinase C iota (PKC-ι) is an atypical kinase implicated in the promotion of different cancer types. A biochemical screen of a fragment library has identified several hits from which an azaindole-based scaffold was chosen for optimization. Driven by a structure-activity relationship and supported by molecular modeling, a weakly bound fragment was systematically grown into a potent and selective inhibitor against PKC-ι.

  20. 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.

  1. A single microfluidic chip with dual surface properties for protein drug delivery.

    Science.gov (United States)

    Bokharaei, Mehrdad; Saatchi, Katayoun; Häfeli, Urs O

    2017-04-15

    Principles of double emulsion generation were incorporated in a glass microfluidic chip fabricated with two different surface properties in order to produce protein loaded polymer microspheres. The microspheres were produced by integrating two microfluidic flow focusing systems and a multi-step droplet splitting and mixing system into one chip. The chip consists of a hydrophobic and a hydrophilic section with two different heights, 12μm and 45μm, respectively. As a result, the protein is homogenously distributed throughout the polymer microsphere matrix, not just in its center (which has been studied before). In our work, the inner phase was bovine serum albumin (BSA) in phosphate buffered saline, the disperse phase was poly (lactic acid) in chloroform and the continuous phase was an aqueous solution of poly(vinyl alcohol). After solvent removal, BSA loaded microspheres with an encapsulation efficiency of up to 96% were obtained. Our results show the feasibility of producing microspheres loaded with a hydrophilic drug in a microfluidic system that integrates different microfluidic units into one chip. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. 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.

  3. Analyzing research trends on drug safety using topic modeling.

    Science.gov (United States)

    Zou, Chen

    2018-04-06

    Published drug safety data has evolved in the past decade due to scientific and technological advances in the relevant research fields. Considering that a vast amount of scientific literature has been published in this area, it is not easy to identify the key information. Topic modeling has emerged as a powerful tool to extract meaningful information from a large volume of unstructured texts. Areas covered: We analyzed the titles and abstracts of 4347 articles in four journals dedicated to drug safety from 2007 to 2016. We applied Latent Dirichlet allocation (LDA) model to extract 50 main topics, and conducted trend analysis to explore the temporal popularity of these topics over years. Expert Opinion/Commentary: We found that 'benefit-risk assessment and communication', 'diabetes' and 'biologic therapy for autoimmune diseases' are the top 3 most published topics. The topics relevant to the use of electronic health records/observational data for safety surveillance are becoming increasingly popular over time. Meanwhile, there is a slight decrease in research on signal detection based on spontaneous reporting, although spontaneous reporting still plays an important role in benefit-risk assessment. The topics related to medical conditions and treatment showed highly dynamic patterns over time.

  4. Old and new therapeutics for Rheumatoid Arthritis: in vivo models and drug development

    DEFF Research Database (Denmark)

    Sardar, Samra; Andersson, Åsa

    2016-01-01

    Development of novel drugs for treatment of chronic inflammatory diseases is to a large extent dependent on the availability of good experimental in vivo models in order to perform preclinical tests of new drugs and for the identification of novel drug targets. Here, we review a number of existing...... of in vivo models during development of anti-rheumatic drugs; from Methotrexate to various antibody treatments, to novel drugs that are, or have recently been, in clinical trials. For novel drugs, we have explored websites for clinical trials. Although one Rheumatoid Arthritis in vivo model cannot mirror...

  5. 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.

  6. A Network-Based Model of Oncogenic Collaboration for Prediction of Drug Sensitivity

    Directory of Open Access Journals (Sweden)

    Ted G Laderas

    2015-12-01

    Full Text Available Tumorigenesis is a multi-step process, involving the acquisition of multiple oncogenic mutations that transform cells, resulting in systemic dysregulation that enables proliferation, among other cancer hallmarks. High throughput omics techniques are used in precision medicine, allowing identification of these mutations with the goal of identifying treatments that target them. However, the multiplicity of oncogenes required for transformation, known as oncogenic collaboration, makes assigning effective treatments difficult. Motivated by this observation, we propose a new type of oncogenic collaboration where mutations in genes that interact with an oncogene may contribute to its dysregulation, a new genomic feature that we term surrogate oncogenes. By mapping mutations to a protein/protein interaction network, we can determine significance of the observed distribution using permutation-based methods. For a panel of 38 breast cancer cell lines, we identified significant surrogate oncogenes in oncogenes such as BRCA1 and ESR1. In addition, using Random Forest Classifiers, we show that these significant surrogate oncogenes predict drug sensitivity for 74 drugs in the breast cancer cell lines with a mean error rate of 30.9%. Additionally, we show that surrogate oncogenes are predictive of survival in patients. The surrogate oncogene framework incorporates unique or rare mutations on an individual level. Our model has the potential for integrating patient-unique mutations in predicting drug-sensitivity, suggesting a potential new direction in precision medicine, as well as a new approach for drug development. Additionally, we show the prevalence of significant surrogate oncogenes in multiple cancers within the Cancer Genome Atlas, suggesting that surrogate oncogenes may be a useful genomic feature for guiding pancancer analyses and assigning therapies across many tissue types.

  7. Modeling of axonal endoplasmic reticulum network by spastic paraplegia proteins.

    Science.gov (United States)

    Yalçın, Belgin; Zhao, Lu; Stofanko, Martin; O'Sullivan, Niamh C; Kang, Zi Han; Roost, Annika; Thomas, Matthew R; Zaessinger, Sophie; Blard, Olivier; Patto, Alex L; Sohail, Anood; Baena, Valentina; Terasaki, Mark; O'Kane, Cahir J

    2017-07-25

    Axons contain a smooth tubular endoplasmic reticulum (ER) network that is thought to be continuous with ER throughout the neuron; the mechanisms that form this axonal network are unknown. Mutations affecting reticulon or REEP proteins, with intramembrane hairpin domains that model ER membranes, cause an axon degenerative disease, hereditary spastic paraplegia (HSP). We show that Drosophila axons have a dynamic axonal ER network, which these proteins help to model. Loss of HSP hairpin proteins causes ER sheet expansion, partial loss of ER from distal motor axons, and occasional discontinuities in axonal ER. Ultrastructural analysis reveals an extensive ER network in axons, which shows larger and fewer tubules in larvae that lack reticulon and REEP proteins, consistent with loss of membrane curvature. Therefore HSP hairpin-containing proteins are required for shaping and continuity of axonal ER, thus suggesting roles for ER modeling in axon maintenance and function.

  8. 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.

  9. Absence of association between major vault protein (MVP) gene polymorphisms and drug resistance in Chinese Han patients with partial epilepsy.

    Science.gov (United States)

    Zhou, Luo; Zhang, Mengqi; Long, Hongyu; Long, Lili; Xie, Yuanyuan; Liu, Zhaoqian; Kang, Jin; Chen, Qihua; Feng, Li; Xiao, Bo

    2015-11-15

    Drug resistance in epilepsy is common despite many antiepileptic drugs (AEDs) available for treatment. The development of drug resistant epilepsy may be a result of multiple factors. Several previous studies reported that the major vault protein (MVP) was significantly increased in epileptogenic brain tissues resected from patients with partial-onset seizures, indicating the possible involvement of MVP in drug resistance. In this article, we aimed to identify the association between single nucleotide polymorphisms (SNPs) of MVP gene and drug resistance of partial epilepsy in a Chinese Han population. A total of 510 patients with partial-onset seizures and 206 healthy controls were recruited. Among the patients, 222 were drug resistant and 288 were responsive. The selection of tagging SNPs was based on the Hapmap database and Haploview software and the genotyping was conducted on the Sequenom MassARRAY iPLEX platform. For the selected loci rs12149746, rs9938630 and rs4788186 in the MVP gene, there was no significant difference in allele or genotype distribution between the drug resistant and responsive groups, or between all of the patients and healthy controls. Linkage disequilibrium between any two loci was detected but there was no significant difference in haplotype frequency between the drug resistant and responsive groups. Our results suggest that MVP genetic polymorphisms and haplotypes may not be associated with drug resistance of partial epilepsy in the Chinese Han population. Copyright © 2015 Elsevier B.V. All rights reserved.

  10. Exploring G Protein-Coupled Receptors (GPCRs) Ligand Space via Cheminformatics Approaches: Impact on Rational Drug Design

    Science.gov (United States)

    Basith, Shaherin; Cui, Minghua; Macalino, Stephani J. Y.; Park, Jongmi; Clavio, Nina A. B.; Kang, Soosung; Choi, Sun

    2018-01-01

    The primary goal of rational drug discovery is the identification of selective ligands which act on single or multiple drug targets to achieve the desired clinical outcome through the exploration of total chemical space. To identify such desired compounds, computational approaches are necessary in predicting their drug-like properties. G Protein-Coupled Receptors (GPCRs) represent one of the largest and most important integral membrane protein families. These receptors serve as increasingly attractive drug targets due to their relevance in the treatment of various diseases, such as inflammatory disorders, metabolic imbalances, cardiac disorders, cancer, monogenic disorders, etc. In the last decade, multitudes of three-dimensional (3D) structures were solved for diverse GPCRs, thus referring to this period as the “golden age for GPCR structural biology.” Moreover, accumulation of data about the chemical properties of GPCR ligands has garnered much interest toward the exploration of GPCR chemical space. Due to the steady increase in the structural, ligand, and functional data of GPCRs, several cheminformatics approaches have been implemented in its drug discovery pipeline. In this review, we mainly focus on the cheminformatics-based paradigms in GPCR drug discovery. We provide a comprehensive view on the ligand– and structure-based cheminformatics approaches which are best illustrated via GPCR case studies. Furthermore, an appropriate combination of ligand-based knowledge with structure-based ones, i.e., integrated approach, which is emerging as a promising strategy for cheminformatics-based GPCR drug design is also discussed. PMID:29593527

  11. 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.

  12. Model systems for understanding absorption tuning by opsin proteins

    DEFF Research Database (Denmark)

    Nielsen, Mogens Brøndsted

    2009-01-01

    This tutorial review reports on model systems that have been synthesised and investigated for elucidating how opsin proteins tune the absorption of the protonated retinal Schiff base chromophore. In particular, the importance of the counteranion is highlighted. In addition, the review advocates...... is avoided, and it becomes clear that opsin proteins induce blueshifts in the chromophore absorption rather than redshifts....

  13. 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.

  14. 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

  15. SC lipid model membranes designed for studying impact of ceramide species on drug diffusion and permeation--part II: diffusion and permeation of model drugs.

    Science.gov (United States)

    Ochalek, M; Podhaisky, H; Ruettinger, H-H; Wohlrab, J; Neubert, R H H

    2012-10-01

    The barrier function of two quaternary stratum corneum (SC) lipid model membranes, which were previously characterized with regard to the lipid organization, was investigated based on diffusion studies of model drugs with varying lipophilicities. Diffusion experiments of a hydrophilic drug, urea, and more lipophilic drugs than urea (i.e. caffeine, diclofenac sodium) were conducted using Franz-type diffusion cells. The amount of permeated drug was analyzed using either HPLC or CE technique. The subjects of interest in the present study were the investigation of the influence of physicochemical properties of model drugs on their diffusion and permeation through SC lipid model membranes, as well as the study of the impact of the constituents of these artificial systems (particularly ceramide species) on their barrier properties. The diffusion through both SC lipid model membranes and the human SC of the most hydrophilic model drug, urea, was faster than the permeation of the more lipophilic drugs. The slowest rate of permeation through SC lipid systems occurred in the case of caffeine. The composition of SC lipid model membranes has a significant impact on their barrier function. Model drugs diffused and permeated faster through Membrane II (presence of Cer [EOS]). In terms of the barrier properties, Membrane II is much more similar to the human SC than Membrane I. Copyright © 2012 Elsevier B.V. All rights reserved.

  16. 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.

  17. 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...... on conformational fluctuations that is in correspondence with experimental measurements. TYPHON provides a flexible, yet computationally efficient, method to explore possible conformational fluctuations in proteins....

  18. 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.

  19. 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

  20. 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.

  1. SVM Based Descriptor Selection and Classification of Neurodegenerative Disease Drugs for Pharmacological Modeling.

    Science.gov (United States)

    Shahid, Mohammad; Shahzad Cheema, Muhammad; Klenner, Alexander; Younesi, Erfan; Hofmann-Apitius, Martin

    2013-03-01

    Systems pharmacological modeling of drug mode of action for the next generation of multitarget drugs may open new routes for drug design and discovery. Computational methods are widely used in this context amongst which support vector machines (SVM) have proven successful in addressing the challenge of classifying drugs with similar features. We have applied a variety of such SVM-based approaches, namely SVM-based recursive feature elimination (SVM-RFE). We use the approach to predict the pharmacological properties of drugs widely used against complex neurodegenerative disorders (NDD) and to build an in-silico computational model for the binary classification of NDD drugs from other drugs. Application of an SVM-RFE model to a set of drugs successfully classified NDD drugs from non-NDD drugs and resulted in overall accuracy of ∼80 % with 10 fold cross validation using 40 top ranked molecular descriptors selected out of total 314 descriptors. Moreover, SVM-RFE method outperformed linear discriminant analysis (LDA) based feature selection and classification. The model reduced the multidimensional descriptors space of drugs dramatically and predicted NDD drugs with high accuracy, while avoiding over fitting. Based on these results, NDD-specific focused libraries of drug-like compounds can be designed and existing NDD-specific drugs can be characterized by a well-characterized set of molecular descriptors. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  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. 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.

  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. 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.

  6. MRI study of hydrophilic xanthan tablets with incorporated model drug

    OpenAIRE

    Mikac, Urša; Baumgartner, Saša; Sepe, Ana; Kristl, Julijana

    2015-01-01

    Magnetic resonance imaging was used to study swelling dynamics and hydrogel formation of xanthan tablets with or without Pentoxifylline drug in water and HCl pH 1.2 media at two different ionic strengths. Significant changes were observed only in the erosion front positions leading to different hydrogel thicknesses. The impact of the drug on the hydrogel thickness was found to be dependent on the medium conditions at high enough drug amount. The drug does not change the hydrogel thickness ...

  7. Expression and cellular distribution of major vault protein: a putative marker for pharmacoresistance in a rat model for temporal lobe epilepsy

    NARCIS (Netherlands)

    van Vliet, Erwin A.; Aronica, Eleonora; Redeker, Sandra; Gorter, Jan A.

    2004-01-01

    PURPOSE: Because drug transporters might play a role in the development of multidrug resistance (MDR), we investigated the expression of a vesicular drug transporter, the major vault protein (MVP), in a rat model for temporal lobe epilepsy. METHODS: By using real-time polymerase chain reaction (PCR)

  8. Expression and Cellular Distribution of Major Vault Protein: A Putative Marker for Pharmacoresistance in a Rat Model for Temporal Lobe Epilepsy

    NARCIS (Netherlands)

    Vliet van, E.A.; Aronica, E.; Redeker, S.; Gorter, J.A.

    2004-01-01

    Summary: Purpose: Because drug transporters might play a role in the development of multidrug resistance (MDR), we investigated the expression of a vesicular drug transporter, the major vault protein (MVP), in a rat model for temporal lobe epilepsy. Methods: By using real-time polymerase chain

  9. Entrapment of alpha1-acid glycoprotein in high-performance affinity columns for drug-protein binding studies.

    Science.gov (United States)

    Bi, Cong; Jackson, Abby; Vargas-Badilla, John; Li, Rong; Rada, Giana; Anguizola, Jeanethe; Pfaunmiller, Erika; Hage, David S

    2016-05-15

    A slurry-based method was developed for the entrapment of alpha1-acid glycoprotein (AGP) for use in high-performance affinity chromatography to study drug interactions with this serum protein. Entrapment was achieved based on the physical containment of AGP in hydrazide-activated porous silica supports and by using mildly oxidized glycogen as a capping agent. The conditions needed for this process were examined and optimized. When this type of AGP column was used in binding studies, the association equilibrium constant (Ka) measured by frontal analysis at pH 7.4 and 37°C for carbamazepine with AGP was found to be 1.0 (±0.5)×10(5)M(-1), which agreed with a previously reported value of 1.0 (±0.1)×10(5)M(-1). Binding studies based on zonal elution were conducted for several other drugs with such columns, giving equilibrium constants that were consistent with literature values. An entrapped AGP column was also used in combination with a column containing entrapped HSA in a screening assay format to compare the binding of various drugs to AGP and HSA. These results also agreed with previous data that have been reported in literature for both of these proteins. The same entrapment method could be extended to other proteins and to the investigation of additional types of drug-protein interactions. Potential applications include the rapid quantitative analysis of biological interactions and the high-throughput screening of drug candidates for their binding to a given protein. Copyright © 2015 Elsevier B.V. All rights reserved.

  10. 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

  11. 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.

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

    KAUST Repository

    Carbajo, Daniel; Tramontano, Anna

    2012-01-01

    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

  13. A computational model of the LGI1 protein suggests a common binding site for ADAM proteins.

    Directory of Open Access Journals (Sweden)

    Emanuela Leonardi

    Full Text Available Mutations of human leucine-rich glioma inactivated (LGI1 gene encoding the epitempin protein cause autosomal dominant temporal lateral epilepsy (ADTLE, a rare familial partial epileptic syndrome. The LGI1 gene seems to have a role on the transmission of neuronal messages but the exact molecular mechanism remains unclear. In contrast to other genes involved in epileptic disorders, epitempin shows no homology with known ion channel genes but contains two domains, composed of repeated structural units, known to mediate protein-protein interactions.A three dimensional in silico model of the two epitempin domains was built to predict the structure-function relationship and propose a functional model integrating previous experimental findings. Conserved and electrostatic charged regions of the model surface suggest a possible arrangement between the two domains and identifies a possible ADAM protein binding site in the β-propeller domain and another protein binding site in the leucine-rich repeat domain. The functional model indicates that epitempin could mediate the interaction between proteins localized to different synaptic sides in a static way, by forming a dimer, or in a dynamic way, by binding proteins at different times.The model was also used to predict effects of known disease-causing missense mutations. Most of the variants are predicted to alter protein folding while several other map to functional surface regions. In agreement with experimental evidence, this suggests that non-secreted LGI1 mutants could be retained within the cell by quality control mechanisms or by altering interactions required for the secretion process.

  14. 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.

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

    International Nuclear Information System (INIS)

    Tarakanova, Anna; Buehler, Markus J

    2013-01-01

    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. (topical review)

  16. General transfer matrix formalism to calculate DNA-protein-drug binding in gene regulation: application to OR operator of phage lambda.

    Science.gov (United States)

    Teif, Vladimir B

    2007-01-01

    The transfer matrix methodology is proposed as a systematic tool for the statistical-mechanical description of DNA-protein-drug binding involved in gene regulation. We show that a genetic system of several cis-regulatory modules is calculable using this method, considering explicitly the site-overlapping, competitive, cooperative binding of regulatory proteins, their multilayer assembly and DNA looping. In the methodological section, the matrix models are solved for the basic types of short- and long-range interactions between DNA-bound proteins, drugs and nucleosomes. We apply the matrix method to gene regulation at the O(R) operator of phage lambda. The transfer matrix formalism allowed the description of the lambda-switch at a single-nucleotide resolution, taking into account the effects of a range of inter-protein distances. Our calculations confirm previously established roles of the contact CI-Cro-RNAP interactions. Concerning long-range interactions, we show that while the DNA loop between the O(R) and O(L) operators is important at the lysogenic CI concentrations, the interference between the adjacent promoters P(R) and P(RM) becomes more important at small CI concentrations. A large change in the expression pattern may arise in this regime due to anticooperative interactions between DNA-bound RNA polymerases. The applicability of the matrix method to more complex systems is discussed.

  17. A quantitative systems pharmacology approach, incorporating a novel liver model, for predicting pharmacokinetic drug-drug interactions.

    Science.gov (United States)

    Cherkaoui-Rbati, Mohammed H; Paine, Stuart W; Littlewood, Peter; Rauch, Cyril

    2017-01-01

    All pharmaceutical companies are required to assess pharmacokinetic drug-drug interactions (DDIs) of new chemical entities (NCEs) and mathematical prediction helps to select the best NCE candidate with regard to adverse effects resulting from a DDI before any costly clinical studies. Most current models assume that the liver is a homogeneous organ where the majority of the metabolism occurs. However, the circulatory system of the liver has a complex hierarchical geometry which distributes xenobiotics throughout the organ. Nevertheless, the lobule (liver unit), located at the end of each branch, is composed of many sinusoids where the blood flow can vary and therefore creates heterogeneity (e.g. drug concentration, enzyme level). A liver model was constructed by describing the geometry of a lobule, where the blood velocity increases toward the central vein, and by modeling the exchange mechanisms between the blood and hepatocytes. Moreover, the three major DDI mechanisms of metabolic enzymes; competitive inhibition, mechanism based inhibition and induction, were accounted for with an undefined number of drugs and/or enzymes. The liver model was incorporated into a physiological-based pharmacokinetic (PBPK) model and simulations produced, that in turn were compared to ten clinical results. The liver model generated a hierarchy of 5 sinusoidal levels and estimated a blood volume of 283 mL and a cell density of 193 × 106 cells/g in the liver. The overall PBPK model predicted the pharmacokinetics of midazolam and the magnitude of the clinical DDI with perpetrator drug(s) including spatial and temporal enzyme levels changes. The model presented herein may reduce costs and the use of laboratory animals and give the opportunity to explore different clinical scenarios, which reduce the risk of adverse events, prior to costly human clinical studies.

  18. A quantitative systems pharmacology approach, incorporating a novel liver model, for predicting pharmacokinetic drug-drug interactions.

    Directory of Open Access Journals (Sweden)

    Mohammed H Cherkaoui-Rbati

    Full Text Available All pharmaceutical companies are required to assess pharmacokinetic drug-drug interactions (DDIs of new chemical entities (NCEs and mathematical prediction helps to select the best NCE candidate with regard to adverse effects resulting from a DDI before any costly clinical studies. Most current models assume that the liver is a homogeneous organ where the majority of the metabolism occurs. However, the circulatory system of the liver has a complex hierarchical geometry which distributes xenobiotics throughout the organ. Nevertheless, the lobule (liver unit, located at the end of each branch, is composed of many sinusoids where the blood flow can vary and therefore creates heterogeneity (e.g. drug concentration, enzyme level. A liver model was constructed by describing the geometry of a lobule, where the blood velocity increases toward the central vein, and by modeling the exchange mechanisms between the blood and hepatocytes. Moreover, the three major DDI mechanisms of metabolic enzymes; competitive inhibition, mechanism based inhibition and induction, were accounted for with an undefined number of drugs and/or enzymes. The liver model was incorporated into a physiological-based pharmacokinetic (PBPK model and simulations produced, that in turn were compared to ten clinical results. The liver model generated a hierarchy of 5 sinusoidal levels and estimated a blood volume of 283 mL and a cell density of 193 × 106 cells/g in the liver. The overall PBPK model predicted the pharmacokinetics of midazolam and the magnitude of the clinical DDI with perpetrator drug(s including spatial and temporal enzyme levels changes. The model presented herein may reduce costs and the use of laboratory animals and give the opportunity to explore different clinical scenarios, which reduce the risk of adverse events, prior to costly human clinical studies.

  19. 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.

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

    KAUST Repository

    Najibi, Seyed Morteza; Maadooliat, Mehdi; Zhou, Lan; Huang, Jianhua Z.; Gao, Xin

    2017-01-01

    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.

  1. 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).

  2. In vitro membrane binding and protein binding (IAM MB/PB technology to estimate in vivo distribution: applications in early drug discovery

    Directory of Open Access Journals (Sweden)

    Klara Livia Valko

    2017-03-01

    Full Text Available The drug discovery process can be accelerated by chromatographic profiling of the analogs to model in vivo distribution and the major non-specific binding. A balanced potency and chromatographically determined membrane and protein binding (IAM MB/PB data enable selecting drug discovery compounds for further analysis that have the highest probability to show the desired in vivo distribution behavior for efficacy and reduced chance for toxicity. Although the basic principles of the technology have already appeared in numerous publications, the lack of standardized procedures limited its widespread applications especially in academia and small drug discovery biotech companies. In this paper, the standardized procedures are described that has been trademarked as Regis IAM MB/PB Technology®. Comparison between the Drug Efficiency Index (DEI=pIC50-logVdu+2 and generally used Ligand Lipophilicity Efficiency (LLE has been made, demonstrating the advantage of measured IAM and HSA binding over calculated log P. The power of the proposed chromatographic technology is demonstrated using the data of marketed drugs.

  3. 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.

  4. 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.

  5. Roles of beta-turns in protein folding: from peptide models to protein engineering.

    Science.gov (United States)

    Marcelino, Anna Marie C; Gierasch, Lila M

    2008-05-01

    Reverse turns are a major class of protein secondary structure; they represent sites of chain reversal and thus sites where the globular character of a protein is created. It has been speculated for many years that turns may nucleate the formation of structure in protein folding, as their propensity to occur will favor the approximation of their flanking regions and their general tendency to be hydrophilic will favor their disposition at the solvent-accessible surface. Reverse turns are local features, and it is therefore not surprising that their structural properties have been extensively studied using peptide models. In this article, we review research on peptide models of turns to test the hypothesis that the propensities of turns to form in short peptides will relate to the roles of corresponding sequences in protein folding. Turns with significant stability as isolated entities should actively promote the folding of a protein, and by contrast, turn sequences that merely allow the chain to adopt conformations required for chain reversal are predicted to be passive in the folding mechanism. We discuss results of protein engineering studies of the roles of turn residues in folding mechanisms. Factors that correlate with the importance of turns in folding indeed include their intrinsic stability, as well as their topological context and their participation in hydrophobic networks within the protein's structure.

  6. 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.

  7. 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

  8. 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

  9. 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

  10. 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.

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

    KAUST Repository

    Chiang, Tsung-Han; Hsu, David; Latombe, Jean-Claude

    2010-01-01

    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.

  12. Are animal models predictive for human postmortem muscle protein degradation?

    Science.gov (United States)

    Ehrenfellner, Bianca; Zissler, Angela; Steinbacher, Peter; Monticelli, Fabio C; Pittner, Stefan

    2017-11-01

    A most precise determination of the postmortem interval (PMI) is a crucial aspect in forensic casework. Although there are diverse approaches available to date, the high heterogeneity of cases together with the respective postmortal changes often limit the validity and sufficiency of many methods. Recently, a novel approach for time since death estimation by the analysis of postmortal changes of muscle proteins was proposed. It is however necessary to improve the reliability and accuracy, especially by analysis of possible influencing factors on protein degradation. This is ideally investigated on standardized animal models that, however, require legitimization by a comparison of human and animal tissue, and in this specific case of protein degradation profiles. Only if protein degradation events occur in comparable fashion within different species, respective findings can sufficiently be transferred from the animal model to application in humans. Therefor samples from two frequently used animal models (mouse and pig), as well as forensic cases with representative protein profiles of highly differing PMIs were analyzed. Despite physical and physiological differences between species, western blot analysis revealed similar patterns in most of the investigated proteins. Even most degradation events occurred in comparable fashion. In some other aspects, however, human and animal profiles depicted distinct differences. The results of this experimental series clearly indicate the huge importance of comparative studies, whenever animal models are considered. Although animal models could be shown to reflect the basic principles of protein degradation processes in humans, we also gained insight in the difficulties and limitations of the applicability of the developed methodology in different mammalian species regarding protein specificity and methodic functionality.

  13. 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

  14. Illicit drugs and the media: models of media effects for use in drug policy research.

    Science.gov (United States)

    Lancaster, Kari; Hughes, Caitlin E; Spicer, Bridget; Matthew-Simmons, Francis; Dillon, Paul

    2011-07-01

    Illicit drugs are never far from the media gaze and although identified almost a decade ago as 'a new battleground' for the alcohol and other drug (AOD) field there has been limited research examining the role of the news media and its effects on audiences and policy. This paper draws together media theories from communication literature to examine media functions. We illustrate how each function is relevant for media and drugs research by drawing upon the existing literature examining Australian media coverage during the late 1990s of escalating heroin-related problems and proposed solutions. Media can influence audiences in four key ways: by setting the agenda and defining public interest; framing issues through selection and salience; indirectly shaping individual and community attitudes towards risk; and feeding into political debate and decision making. Each has relevance for the AOD field. For example, media coverage of the escalating heroin-related problems in Australia played a strong role in generating interest in heroin overdoses, framing public discourse in terms of a health and/or criminal issue and affecting political decisions. Implications AND CONCLUSION: Media coverage in relation to illicit drugs can have multifarious effects. Incorporating media communication theories into future research and actions is critical to facilitate understanding of the short- and long-term impacts of media coverage on illicit drugs and the avenues by which the AOD field can mitigate or inform future media debates on illicit drugs. © 2010 Australasian Professional Society on Alcohol and other Drugs.

  15. 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

  16. The mechanism of lauric acid-modified protein nanocapsules escape from intercellular trafficking vesicles and its implication for drug delivery.

    Science.gov (United States)

    Jiang, Lijuan; Liang, Xin; Liu, Gan; Zhou, Yun; Ye, Xinyu; Chen, Xiuli; Miao, Qianwei; Gao, Li; Zhang, Xudong; Mei, Lin

    2018-11-01

    Protein nanocapsules have exhibited promising potential applications in the field of protein drug delivery. A major issue with various promising nano-sized biotherapeutics including protein nanocapsules is that owing to their particle size they are subject to cellular uptake via endocytosis, and become entrapped and then degraded within endolysosomes, which can significantly impair their therapeutic efficacy. In addition, many nano-sized biotherapeutics could be also sequestered by autophagosomes and degraded through the autolysosomal pathway. Thus, a limiting step in achieving an effective protein therapy is to facilitate the endosomal escape and auto-lysosomal escape to ensure cytosolic delivery of the protein drugs. Here, we prepared a protein nanocapsule based on BSA (nBSA) and the BSA nanocapsules modified with a bilayer of lauric acid (LA-nBSA) to investigate the escape effects from the endosome and autophagosome. The size distribution of nBSA and LA-nBSA analyzed using DLS presents a uniform diameter centered at 10 nm and 16 nm. The data also showed that FITC-labeled nBSA and LA-nBSA were taken up by the cells mainly through Arf-6-dependent endocytosis and Rab34-mediated macropinocytosis. In addition, LA-nBSA could efficiently escape from endosomal before the degradation in endo-lysosomes. Autophagy could also sequester the LA-nBSA through p62 autophagosome vesicles. These two types of nanocapsules underwent different intracellular destinies and lauric acid (LA) coating played a vital role in intracellular particle retention. In conclusion, the protein nanocapsules modified with LA could enhance the protein nanocapsules escape from intercellular trafficking vesicles, and protect the protein from degradation by the lysosomes.

  17. An in vivo C. elegans model system for screening EGFR-inhibiting anti-cancer drugs.

    Directory of Open Access Journals (Sweden)

    Young-Ki Bae

    Full Text Available The epidermal growth factor receptor (EGFR is a well-established target for cancer treatment. EGFR tyrosine kinase (TK inhibitors, such as gefinitib and erlotinib, have been developed as anti-cancer drugs. Although non-small cell lung carcinoma with an activating EGFR mutation, L858R, responds well to gefinitib and erlotinib, tumors with a doubly mutated EGFR, T790M-L858R, acquire resistance to these drugs. The C. elegans EGFR homolog LET-23 and its downstream signaling pathway have been studied extensively to provide insight into regulatory mechanisms conserved from C. elegans to humans. To develop an in vivo screening system for potential cancer drugs targeting specific EGFR mutants, we expressed three LET-23 chimeras in which the TK domain was replaced with either the human wild-type TK domain (LET-23::hEGFR-TK, a TK domain with the L858R mutation (LET-23::hEGFR-TK[L858R], or a TK domain with the T790M-L858R mutations (LET-23::hEGFR-TK[T790M-L858R] in C. elegans vulval cells using the let-23 promoter. The wild-type hEGFR-TK chimeric protein rescued the let-23 mutant phenotype, and the activating mutant hEGFR-TK chimeras induced a multivulva (Muv phenotype in a wild-type C. elegans background. The anti-cancer drugs gefitinib and erlotinib suppressed the Muv phenotype in LET-23::hEGFR-TK[L858R]-expressing transgenic animals, but not in LET-23::hEGFR-TK[T790M-L858R] transgenic animals. As a pilot screen, 8,960 small chemicals were tested for Muv suppression, and AG1478 (an EGFR-TK inhibitor and U0126 (a MEK inhibitor were identified as potential inhibitors of EGFR-mediated biological function. In conclusion, transgenic C. elegans expressing chimeric LET-23::hEGFR-TK proteins are a model system that can be used in mutation-specific screens for new anti-cancer drugs.

  18. Design of Protein-Coated Carbon Nanotubes Loaded with Hydrophobic Drugs through Sacrificial Templating of Mesoporous Silica Shells.

    Science.gov (United States)

    Fiegel, Vincent; Harlepp, Sebastien; Begin-Colin, Sylvie; Begin, Dominique; Mertz, Damien

    2018-03-26

    One key challenge in the fields of nanomedicine and tissue engineering is the design of theranostic nanoplatforms able to monitor their therapeutic effect by imaging. Among current developed nano-objects, carbon nanotubes (CNTs) were found suitable to combine imaging, photothermal therapy, and to be loaded with hydrophobic drugs. However, a main problem is their resulting low hydrophilicity. To face this problem, an innovative method is developed here, which consists in loading the surface of carbon nanotubes (CNTs) with drugs followed by a protein coating around them. The originality of this method relies on first covering CNTs with a sacrificial template mesoporous silica (MS) shell grafted with isobutyramide (IBAM) binders on which a protein nanofilm is strongly adhered through IBAM-mediated physical cross-linking. This concept is first demonstrated without drugs, and is further improved with the suitable loading of hydrophobic drugs, curcumin (CUR) and camptothecin (CPT), which are retained between the CNTs and human serum albumin (HSA) layer. Such novel nanocomposites with favorable photothermal properties are very promising for theranostic systems, drug delivery, and phototherapy applications. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Fungal lectin MpL enables entry of protein drugs into cancer cells and their subcellular targeting.

    Science.gov (United States)

    Å Urga, Simon; Nanut, Milica Perišić; Kos, Janko; Sabotič, Jerica

    2017-04-18

    Lectins have been recognized as promising carrier molecules for targeted drug delivery. They specifically bind carbohydrate moieties on cell membranes and trigger cell internalization. Fungal lectin MpL (Macrolepiota procera lectin) does not provoke cancer cell cytotoxicity but is able to bind aminopeptidase N (CD13) and integrin α3β1, two glycoproteins that are overexpressed on the membrane of tumor cells. Upon binding, MpL is endocytosed in a clathrin-dependent manner and accumulates initially in the Golgi apparatus and, finally, in the lysosomes. For effective binding and internalization a functional binding site on the α-repeat is needed. To test the potential of MpL as a carrier for delivering protein drugs to cancer cells we constructed fusion proteins consisting of MpL and the cysteine peptidase inhibitors cystatin C and clitocypin. The fused proteins followed the same endocytic route as the unlinked MpL. Peptidase inhibitor-MpL fusions impaired both the intracellular degradation of extracellular matrix and the invasiveness of cancer cells. MpL is thus shown in vitro to be a lectin that can enable protein drugs to enter cancer cells, enhance their internalization and sort them to lysosomes and the Golgi apparatus.

  20. 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.

  1. Simulations of CYP51A from Aspergillus fumigatus in a model bilayer provide insights into triazole drug resistance.

    Science.gov (United States)

    Nash, Anthony; Rhodes, Johanna

    2018-04-01

    Azole antifungal drugs target CYP51A in Aspergillus fumigatus by binding with the active site of the protein, blocking ergosterol biosynthesis. Resistance to azole antifungal drugs is now common, with a leucine to histidine amino acid substitution at position 98 the most frequent, predominantly conferring resistance to itraconazole, although cross-resistance has been reported in conjunction with other mutations. In this study, we create a homology model of CYP51A using a recently published crystal structure of the paralog protein CYP51B. The derived structures, wild type, and L98H mutant are positioned within a lipid membrane bilayer and subjected to molecular dynamics simulations in order improve the accuracy of both models. The structural analysis from our simulations suggests a decrease in active site surface from the formation of hydrogen bonds between the histidine substitution and neighboring polar side chains, potentially preventing the binding of azole drugs. This study yields a biologically relevant structure and set of dynamics of the A. fumigatus Lanosterol 14 alpha-demethylase enzyme and provides further insight into azole antifungal drug resistance.

  2. Modeling the drug transport in the anterior segment of the eye.

    Science.gov (United States)

    Avtar, Ram; Tandon, Deepti

    2008-10-02

    The aim of the present work is the development of a simple mathematical model for the time course concentration profile of topically administered drugs in the anterior chamber aqueous humor and investigation of the effects of various model parameters on the aqueous humor concentration of lipophilic and hydrophilic drugs. A simple pharmacokinetic model for the transient drug transport in the anterior segment has been developed by using the conservation of mass in the precorneal tear film, Fick's law of diffusion and Michaelis-Menten kinetics of drug metabolism in cornea, and the conservation of mass in the anterior chamber. An analytical solution describing the drug concentration in the anterior chamber has been obtained. The model predicts that an increase in the drug metabolic (consumption) rate in the corneal epithelium reduces the drug concentration in the anterior chamber for both lipophilic and hydrophilic molecules. A decrease in the clearance rate and distribution volume of the drug in the anterior chamber raises the aqueous humor concentration significantly. It is also observed that decay rate of drug concentration in the anterior chamber is higher for lipophilic molecules than that for hydrophilic molecules. The bioavailability of drugs applied topically to the eye may be improved by a rise in the precorneal tear volume, diffusion coefficient in corneal epithelium and distribution coefficient across the endothelium anterior chamber interface, and by reducing the drug metabolism, drug clearance rate and distribution volume in anterior chamber.

  3. 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.

  4. [Categories and characteristics of BPH drug evaluation models: a comparative study].

    Science.gov (United States)

    Huang, Dong-Yan; Wu, Jian-Hui; Sun, Zu-Yue

    2014-02-01

    Benign prostatic hyperplasia (BPH) is a worldwide common disease in men over 50 years old, and the exact cause of BPH remains largely unknown. In order to elucidate its pathogenesis and screen effective drugs for the treatment of BPH, many BPH models have been developed at home and abroad. This article presents a comprehensive analysis of the categories and characteristics of BPH drug evaluation models, highlighting the application value of each model, to provide a theoretical basis for the development of BPH drugs.

  5. The alpha2-delta protein: an auxiliary subunit of voltage-dependent calcium channels as a recognized drug target.

    Science.gov (United States)

    Thorpe, Andrew J; Offord, James

    2010-07-01

    Currently, there are two drugs on the market, gabapentin (Neurontin) and pregabalin (Lyrica), that are proposed to exert their therapeutic effect through binding to the alpha2-delta subunit of voltage-sensitive calcium channels. This activity was unexpected, as the alpha2-delta subunit had previously been considered not to be a pharmacological target. In this review, the role of the alpha2-delta subunits is discussed and the mechanism of action of the alpha2-delta ligands in vitro and in vivo is summarized. Finally, new insights into the mechanism of drugs that bind to this protein are discussed.

  6. The evolution of the protein synthesis system. I - A model of a primitive protein synthesis system

    Science.gov (United States)

    Mizutani, H.; Ponnamperuma, C.

    1977-01-01

    A model is developed to describe the evolution of the protein synthesis system. The model is comprised of two independent autocatalytic systems, one including one gene (A-gene) and two activated amino acid polymerases (O and A-polymerases), and the other including the addition of another gene (N-gene) and a nucleotide polymerase. Simulation results have suggested that even a small enzymic activity and polymerase specificity could lead the system to the most accurate protein synthesis, as far as permitted by transitions to systems with higher accuracy.

  7. 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

  8. Data-driven prediction of adverse drug reactions induced by drug-drug interactions.

    Science.gov (United States)

    Liu, Ruifeng; AbdulHameed, Mohamed Diwan M; Kumar, Kamal; Yu, Xueping; Wallqvist, Anders; Reifman, Jaques

    2017-06-08

    The expanded use of multiple drugs has increased the occurrence of adverse drug reactions (ADRs) induced by drug-drug interactions (DDIs). However, such reactions are typically not observed in clinical drug-development studies because most of them focus on single-drug therapies. ADR reporting systems collect information on adverse health effects caused by both single drugs and DDIs. A major challenge is to unambiguously identify the effects caused by DDIs and to attribute them to specific drug interactions. A computational method that provides prospective predictions of potential DDI-induced ADRs will help to identify and mitigate these adverse health effects. We hypothesize that drug-protein interactions can be used as independent variables in predicting ADRs. We constructed drug pair-protein interaction profiles for ~800 drugs using drug-protein interaction information in the public domain. We then constructed statistical models to score drug pairs for their potential to induce ADRs based on drug pair-protein interaction profiles. We used extensive clinical database information to construct categorical prediction models for drug pairs that are likely to induce ADRs via synergistic DDIs and showed that model performance deteriorated only slightly, with a moderate amount of false positives and false negatives in the training samples, as evaluated by our cross-validation analysis. The cross validation calculations showed an average prediction accuracy of 89% across 1,096 ADR models that captured the deleterious effects of synergistic DDIs. Because the models rely on drug-protein interactions, we made predictions for pairwise combinations of 764 drugs that are currently on the market and for which drug-protein interaction information is available. These predictions are publicly accessible at http://avoid-db.bhsai.org . We used the predictive models to analyze broader aspects of DDI-induced ADRs, showing that ~10% of all combinations have the potential to induce ADRs

  9. G protein-coupled receptor transmembrane binding pockets and their applications in GPCR research and drug discovery: a survey.

    Science.gov (United States)

    Kratochwil, Nicole A; Gatti-McArthur, Silvia; Hoener, Marius C; Lindemann, Lothar; Christ, Andreas D; Green, Luke G; Guba, Wolfgang; Martin, Rainer E; Malherbe, Pari; Porter, Richard H P; Slack, Jay P; Winnig, Marcel; Dehmlow, Henrietta; Grether, Uwe; Hertel, Cornelia; Narquizian, Robert; Panousis, Constantinos G; Kolczewski, Sabine; Steward, Lucinda

    2011-01-01

    G protein-coupled receptors (GPCRs) share a common architecture consisting of seven transmembrane (TM) domains. Various lines of evidence suggest that this fold provides a generic binding pocket within the TM region for hosting agonists, antagonists, and allosteric modulators. Hence, an automated method was developed that allows a fast analysis and comparison of these generic ligand binding pockets across the entire GPCR family by providing the relevant information for all GPCRs in the same format. This methodology compiles amino acids lining the TM binding pocket including parts of the ECL2 loop in a so-called 1D ligand binding pocket vector and translates these 1D vectors in a second step into 3D receptor pharmacophore models. It aims to support various aspects of GPCR drug discovery in the pharmaceutical industry. Applications of pharmacophore similarity analysis of these 1D LPVs include definition of receptor subfamilies, prediction of species differences within subfamilies in regard to in vitro pharmacology and identification of nearest neighbors for GPCRs of interest to generate starting points for GPCR lead identification programs. These aspects of GPCR research are exemplified in the field of melanopsins, trace amine-associated receptors and somatostatin receptor subtype 5. In addition, it is demonstrated how 3D pharmacophore models of the LPVs can support the prediction of amino acids involved in ligand recognition, the understanding of mutational data in a 3D context and the elucidation of binding modes for GPCR ligands and their evaluation. Furthermore, guidance through 3D receptor pharmacophore modeling for the synthesis of subtype-specific GPCR ligands will be reported. Illustrative examples are taken from the GPCR family class C, metabotropic glutamate receptors 1 and 5 and sweet taste receptors, and from the GPCR class A, e.g. nicotinic acid and 5-hydroxytryptamine 5A receptor. © 2011 Bentham Science Publishers

  10. 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.

  11. 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.

  12. vPARP Adjusts MVP Expression in Drug-resistant Cell Lines in Conjunction with MDR Proteins.

    Science.gov (United States)

    Wojtowicz, Karolina; Januchowski, Radoslaw; Nowicki, Michal; Zabel, Maciej

    2017-06-01

    The definition of vault (ribonucleoprotein particles) function remains highly complex. Vaults may cooperate with multidrug resistance (MDR) proteins, supporting their role in drug resistance. This topic is the main theme of this publication. The cell viability was determined by an MTT assay. The protein expression was detected by western blot analysis. The proteins were knocked-down using siRNA. No major vault protein (MVP) in the LoVo/Dx and W1PR cell lines after tunicamycin treatment was shown. In W1PR cells with knocked-down MVP, a statistically significant decrease in cell viability was noted. In LoVo/Dx, W1TR and A2780TR cells were vault poly-ADP-ribose polymerase (vPARP) was knockdown, a decrease in cell viability was shown. Also, MVP silencing induced an increase in glycoprotein P (Pgp) expression in LoVo/Dx cells. MVP is important for the drug resistance of cancer cells, but it probably requires the presence of vPARP for full activation. Some correlations between MDR proteins and vaults exist. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

  13. Construction of a biodynamic model for Cry protein production studies.

    Science.gov (United States)

    Navarro-Mtz, Ana Karin; Pérez-Guevara, Fermín

    2014-12-01

    Mathematical models have been used from growth kinetic simulation to gen regulatory networks prediction for B. thuringiensis culture. However, this culture is a time dependent dynamic process where cells physiology suffers several changes depending on the changes in the cell environment. Therefore, through its culture, B. thuringiensis presents three phases related with the predominance of three major metabolic pathways: vegetative growth (Embded-Meyerhof-Parnas pathway), transition (γ-aminobutiric cycle) and sporulation (tricarboxylic acid cycle). There is not available a mathematical model that relates the different stages of cultivation with the metabolic pathway active on each one of them. Therefore, in the present study, and based on published data, a biodynamic model was generated to describe the dynamic of the three different phases based on their major metabolic pathways. The biodynamic model is used to study the interrelation between the different culture phases and their relationship with the Cry protein production. The model consists of three interconnected modules where each module represents one culture phase and its principal metabolic pathway. For model validation four new fermentations were done showing that the model constructed describes reasonably well the dynamic of the three phases. The main results of this model imply that poly-β-hydroxybutyrate is crucial for endospore and Cry protein production. According to the yields of dipicolinic acid and Cry fro