Experimental determination and thermodynamic modeling of phase equilibrium and protein partitioning in aqueous two-phase systems containing biodegradable salts

International Nuclear Information System (INIS)

Perez, Brenda; Malpiedi, Luciana Pellegrini; Tubío, Gisela; Nerli, Bibiana; Alcântara Pessôa Filho, Pedro de

2013-01-01

Highlights: ► Binodal data of systems (water + polyethyleneglycol + sodium) succinate are reported. ► Pitzer model describes the phase equilibrium of systems formed by polyethyleneglycol and biodegradable salts satisfactorily. ► This simple thermodynamic framework was able to predict the partitioning behaviour of model proteins acceptably well. - Abstract: Phase diagrams of sustainable aqueous two-phase systems (ATPSs) formed by polyethyleneglycols (PEGs) of different average molar masses (4000, 6000, and 8000) and sodium succinate are reported in this work. Partition coefficients (Kps) of seven model proteins: bovine serum albumin, catalase, beta-lactoglobulin, alpha-amylase, lysozyme, pepsin, urease and trypsin were experimentally determined in these systems and in ATPSs formed by the former PEGs and other biodegradable sodium salts: citrate and tartrate. An extension of Pitzer model comprising long and short-range term contributions to the excess Gibbs free energy was used to describe the (liquid + liquid) equilibrium. Comparison between experimental and calculated tie line data showed mean deviations always lower than 3%, thus indicating a good correlation. The partition coefficients were modeled by using the same thermodynamic approach. Predicted and experimental partition coefficients correlated quite successfully. Mean deviations were found to be lower than the experimental uncertainty for most of the assayed proteins.

Molecular structure, dynamics and hydration studies of soybean storage proteins and model systems by nuclear magnetic resonance

International Nuclear Information System (INIS)

Kakalis, L.T.

1989-01-01

The potential of high-resolution 13 C NMR for the characterization of soybean storage proteins was explored. The spectra of a commercial soy protein isolate as well as those of alkali-denatured 7S and 11S soybean globulins were well resolved and tentatively assigned. Relaxation measurements indicated fast motion for several side chains and the protein backbone. Protein fractions (11S and 7S) were also investigated at various states of molecular association. The large size of the multisubunit soybean storage proteins affected adversely both the resolution and the sensitivity of their 13 C NMR spectra. A comparison of 17 O and 2 H NMR relaxation rates of water in solutions of lysozyme (a model system) as a function of concentration, pH and magnetic field suggested that only 17 O monitors directly the hydration of lysozyme. Analysis of 17 O NMR lysozyme hydration data in terms of a two-state, fast-exchange, anisotropic model resulted in hydration parameters which are consistent with the protein's physico-chemical properties. The same model was applied to the calculation of the amount and mobility of bound water in soy protein dispersions by means of 17 O NMR relaxation measurements as a function of protein concentration. The protein concentration dependences of 1 H transverse NMR relaxation measurements at various pH and ionic strength values were fitted by a viral expansion. The interpretation of the data was based on the effects of protein aggregation, salt binding and protein group ionization on the NMR measurements. In all cases, relaxation rates showed a linear dependence on protein activity

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...

Model system-guided protein interaction mapping for virus isolated from phloem tissue

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Potato leafroll virus (PLRV) is an agriculturally important phloem-limited pathogen that causes significant yield loss in potato (Solanum tuberosum) and a model virus in the Luteoviridae. Encoding only a small repertoire of viral proteins, PLRV relies on carefully orchestrated protein-protein intera...

Models of protein and amino acid requirements for cattle

Directory of Open Access Journals (Sweden)

Luis Orlindo Tedeschi

2015-03-01

Full Text Available Protein supply and requirements by ruminants have been studied for more than a century. These studies led to the accumulation of lots of scientific information about digestion and metabolism of protein by ruminants as well as the characterization of the dietary protein in order to maximize animal performance. During the 1980s and 1990s, when computers became more accessible and powerful, scientists began to conceptualize and develop mathematical nutrition models, and to program them into computers to assist with ration balancing and formulation for domesticated ruminants, specifically dairy and beef cattle. The most commonly known nutrition models developed during this period were the National Research Council (NRC in the United States, Agricultural Research Council (ARC in the United Kingdom, Institut National de la Recherche Agronomique (INRA in France, and the Commonwealth Scientific and Industrial Research Organization (CSIRO in Australia. Others were derivative works from these models with different degrees of modifications in the supply or requirement calculations, and the modeling nature (e.g., static or dynamic, mechanistic, or deterministic. Circa 1990s, most models adopted the metabolizable protein (MP system over the crude protein (CP and digestible CP systems to estimate supply of MP and the factorial system to calculate MP required by the animal. The MP system included two portions of protein (i.e., the rumen-undegraded dietary CP - RUP - and the contributions of microbial CP - MCP as the main sources of MP for the animal. Some models would explicitly account for the impact of dry matter intake (DMI on the MP required for maintenance (MPm; e.g., Cornell Net Carbohydrate and Protein System - CNCPS, the Dutch system - DVE/OEB, while others would simply account for scurf, urinary, metabolic fecal, and endogenous contributions independently of DMI. All models included milk yield and its components in estimating MP required for lactation

Automated de novo phasing and model building of coiled-coil proteins.

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Rämisch, Sebastian; Lizatović, Robert; André, Ingemar

2015-03-01

Models generated by de novo structure prediction can be very useful starting points for molecular replacement for systems where suitable structural homologues cannot be readily identified. Protein-protein complexes and de novo-designed proteins are examples of systems that can be challenging to phase. In this study, the potential of de novo models of protein complexes for use as starting points for molecular replacement is investigated. The approach is demonstrated using homomeric coiled-coil proteins, which are excellent model systems for oligomeric systems. Despite the stereotypical fold of coiled coils, initial phase estimation can be difficult and many structures have to be solved with experimental phasing. A method was developed for automatic structure determination of homomeric coiled coils from X-ray diffraction data. In a benchmark set of 24 coiled coils, ranging from dimers to pentamers with resolutions down to 2.5 Å, 22 systems were automatically solved, 11 of which had previously been solved by experimental phasing. The generated models contained 71-103% of the residues present in the deposited structures, had the correct sequence and had free R values that deviated on average by 0.01 from those of the respective reference structures. The electron-density maps were of sufficient quality that only minor manual editing was necessary to produce final structures. The method, named CCsolve, combines methods for de novo structure prediction, initial phase estimation and automated model building into one pipeline. CCsolve is robust against errors in the initial models and can readily be modified to make use of alternative crystallographic software. The results demonstrate the feasibility of de novo phasing of protein-protein complexes, an approach that could also be employed for other small systems beyond coiled coils.

Protein folding simulations: from coarse-grained model to all-atom model.

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Zhang, Jian; Li, Wenfei; Wang, Jun; Qin, Meng; Wu, Lei; Yan, Zhiqiang; Xu, Weixin; Zuo, Guanghong; Wang, Wei

2009-06-01

Protein folding is an important and challenging problem in molecular biology. During the last two decades, molecular dynamics (MD) simulation has proved to be a paramount tool and was widely used to study protein structures, folding kinetics and thermodynamics, and structure-stability-function relationship. It was also used to help engineering and designing new proteins, and to answer even more general questions such as the minimal number of amino acid or the evolution principle of protein families. Nowadays, the MD simulation is still undergoing rapid developments. The first trend is to toward developing new coarse-grained models and studying larger and more complex molecular systems such as protein-protein complex and their assembling process, amyloid related aggregations, and structure and motion of chaperons, motors, channels and virus capsides; the second trend is toward building high resolution models and explore more detailed and accurate pictures of protein folding and the associated processes, such as the coordination bond or disulfide bond involved folding, the polarization, charge transfer and protonate/deprotonate process involved in metal coupled folding, and the ion permeation and its coupling with the kinetics of channels. On these new territories, MD simulations have given many promising results and will continue to offer exciting views. Here, we review several new subjects investigated by using MD simulations as well as the corresponding developments of appropriate protein models. These include but are not limited to the attempt to go beyond the topology based Gō-like model and characterize the energetic factors in protein structures and dynamics, the study of the thermodynamics and kinetics of disulfide bond involved protein folding, the modeling of the interactions between chaperonin and the encapsulated protein and the protein folding under this circumstance, the effort to clarify the important yet still elusive folding mechanism of protein BBL

Modeling of kinetics of the inducible protein complexes of the SOS system in bacteria E. coli which realize TLS process

International Nuclear Information System (INIS)

Belov, O.V.

2008-01-01

The mathematical model describing kinetics of the inducible genes of the protein complexes, formed during SOS response in bacteria Escherichia coli is developed. Within the bounds of developed approaches the auxiliary mathematical model describing changes in concentrations of the dimers, which are the components of final protein complexes, is developed. The solutions of both models are based on the experimental data concerning expression of the basic genes of the SOS system in bacteria Escherichia coli

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.

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

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.

Protein-protein interactions: an application of Tus-Ter mediated protein microarray system.

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Sitaraman, Kalavathy; Chatterjee, Deb K

2011-01-01

In this chapter, we present a novel, cost-effective microarray strategy that utilizes expression-ready plasmid DNAs to generate protein arrays on-demand and its use to validate protein-protein interactions. These expression plasmids were constructed in such a way so as to serve a dual purpose of synthesizing the protein of interest as well as capturing the synthesized protein. The microarray system is based on the high affinity binding of Escherichia coli "Tus" protein to "Ter," a 20 bp DNA sequence involved in the regulation of DNA replication. The protein expression is carried out in a cell-free protein synthesis system, with rabbit reticulocyte lysates, and the target proteins are detected either by labeled incorporated tag specific or by gene-specific antibodies. This microarray system has been successfully used for the detection of protein-protein interaction because both the target protein and the query protein can be transcribed and translated simultaneously in the microarray slides. The utility of this system for detecting protein-protein interaction is demonstrated by a few well-known examples: Jun/Fos, FRB/FKBP12, p53/MDM2, and CDK4/p16. In all these cases, the presence of protein complexes resulted in the localization of fluorophores at the specific sites of the immobilized target plasmids. Interestingly, during our interactions studies we also detected a previously unknown interaction between CDK2 and p16. Thus, this Tus-Ter based system of protein microarray can be used for the validation of known protein interactions as well as for identifying new protein-protein interactions. In addition, it can be used to examine and identify targets of nucleic acid-protein, ligand-receptor, enzyme-substrate, and drug-protein interactions.

Camel milk protein hydrolysates with improved technofunctional properties and enhanced antioxidant potential in in vitro and in food model systems.

Science.gov (United States)

Al-Shamsi, Kholoud Awad; Mudgil, Priti; Hassan, Hassan Mohamed; Maqsood, Sajid

2018-01-01

Camel milk protein hydrolysates (CMPH) were generated using proteolytic enzymes, such as alcalase, bromelain, and papain, to explore the effect on the technofunctional properties and antioxidant potential under in vitro and in real food model systems. Characterization of the CMPH via degree of hydrolysis, sodium dodecyl sulfate-PAGE, and HPLC revealed that different proteins in camel milk underwent degradation at different degrees after enzymatic hydrolysis using 3 different enzymes for 2, 4, and 6 h, with papain displaying the highest degradation. Technofunctional properties, such as emulsifying activity index, surface hydrophobicity, and protein solubility, were higher in CMPH than unhydrolyzed camel milk proteins. However, the water and fat absorption capacity were lower in CMPH compared with unhydrolyzed camel milk proteins. Antioxidant properties as assessed by 2,2-azinobis(3-ethylbenzthiazoline-6-sulfonic acid) and 2,2-diphenyl-1-picrylhydrazyl radical scavenging activities and metal-chelating activity were enhanced after hydrolysis, in contrast to ferric-reducing antioxidant power which showed a decrease after hydrolysis. The CMPH were also tested in real food model systems for their potential to inhibit lipid peroxidation in fish mince and grape seed oil-in-water emulsion, and we found that papain-produced hydrolysate displayed higher inhibition than alcalase- and bromelain-produced hydrolysates. Therefore, the CMPH demonstrated effective antioxidant potential in vitro as well as in real food systems and showed enhanced functional properties, which guarantees their potential applications in functional foods. The present study is one of few reports available on CMPH being explored in vitro as well as in real food model systems. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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

Interactions Between Flavonoid-Rich Extracts and Sodium Caseinate Modulate Protein Functionality and Flavonoid Bioaccessibility in Model Food Systems.

Science.gov (United States)

Elegbede, Jennifer L; Li, Min; Jones, Owen G; Campanella, Osvaldo H; Ferruzzi, Mario G

2018-05-01

With growing interest in formulating new food products with added protein and flavonoid-rich ingredients for health benefits, direct interactions between these ingredient classes becomes critical in so much as they may impact protein functionality, product quality, and flavonoids bioavailability. In this study, sodium caseinate (SCN)-based model products (foams and emulsions) were formulated with grape seed extract (GSE, rich in galloylated flavonoids) and green tea extract (GTE, rich in nongalloylated flavonoids), respectively, to assess changes in functional properties of SCN and impacts on flavonoid bioaccessibility. Experiments with pure flavonoids suggested that galloylated flavonoids reduced air-water interfacial tension of 0.01% SCN dispersions more significantly than nongalloylated flavonoids at high concentrations (>50 μg/mL). This observation was supported by changes in stability of 5% SCN foam, which showed that foam stability was increased at high levels of GSE (≥50 μg/mL, P < 0.05) but was not affected by GTE. However, flavonoid extracts had modest effects on SCN emulsion. In addition, galloylated flavonoids had higher bioaccessibility in both SCN foam and emulsion. These results suggest that SCN-flavonoid binding interactions can modulate protein functionality leading to difference in performance and flavonoid bioaccessibility of protein-based products. As information on the beneficial health effects of flavonoids expands, it is likely that usage of these ingredients in consumer foods will increase. However, the necessary levels to provide such benefits may exceed those that begin to impact functionality of the macronutrients such as proteins. Flavonoid inclusion within protein matrices may modulate protein functionality in a food system and modify critical consumer traits or delivery of these beneficial plant-derived components. The product matrices utilized in this study offer relevant model systems to evaluate how fortification with flavonoid

A structural systems biology approach for quantifying the systemic consequences of missense mutations in proteins.

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Tammy M K Cheng

Full Text Available Gauging the systemic effects of non-synonymous single nucleotide polymorphisms (nsSNPs is an important topic in the pursuit of personalized medicine. However, it is a non-trivial task to understand how a change at the protein structure level eventually affects a cell's behavior. This is because complex information at both the protein and pathway level has to be integrated. Given that the idea of integrating both protein and pathway dynamics to estimate the systemic impact of missense mutations in proteins remains predominantly unexplored, we investigate the practicality of such an approach by formulating mathematical models and comparing them with experimental data to study missense mutations. We present two case studies: (1 interpreting systemic perturbation for mutations within the cell cycle control mechanisms (G2 to mitosis transition for yeast; (2 phenotypic classification of neuron-related human diseases associated with mutations within the mitogen-activated protein kinase (MAPK pathway. We show that the application of simplified mathematical models is feasible for understanding the effects of small sequence changes on cellular behavior. Furthermore, we show that the systemic impact of missense mutations can be effectively quantified as a combination of protein stability change and pathway perturbation.

Biology of the Heat Shock Response and Protein Chaperones: Budding Yeast (Saccharomyces cerevisiae) as a Model System

Science.gov (United States)

Verghese, Jacob; Abrams, Jennifer; Wang, Yanyu

2012-01-01

Summary: The eukaryotic heat shock response is an ancient and highly conserved transcriptional program that results in the immediate synthesis of a battery of cytoprotective genes in the presence of thermal and other environmental stresses. Many of these genes encode molecular chaperones, powerful protein remodelers with the capacity to shield, fold, or unfold substrates in a context-dependent manner. The budding yeast Saccharomyces cerevisiae continues to be an invaluable model for driving the discovery of regulatory features of this fundamental stress response. In addition, budding yeast has been an outstanding model system to elucidate the cell biology of protein chaperones and their organization into functional networks. In this review, we evaluate our understanding of the multifaceted response to heat shock. In addition, the chaperone complement of the cytosol is compared to those of mitochondria and the endoplasmic reticulum, organelles with their own unique protein homeostasis milieus. Finally, we examine recent advances in the understanding of the roles of protein chaperones and the heat shock response in pathogenic fungi, which is being accelerated by the wealth of information gained for budding yeast. PMID:22688810

Development of a Model Protein Interaction Pair as a Benchmarking Tool for the Quantitative Analysis of 2-Site Protein-Protein Interactions.

Science.gov (United States)

Yamniuk, Aaron P; Newitt, John A; Doyle, Michael L; Arisaka, Fumio; Giannetti, Anthony M; Hensley, Preston; Myszka, David G; Schwarz, Fred P; Thomson, James A; Eisenstein, Edward

2015-12-01

A significant challenge in the molecular interaction field is to accurately determine the stoichiometry and stepwise binding affinity constants for macromolecules having >1 binding site. The mission of the Molecular Interactions Research Group (MIRG) of the Association of Biomolecular Resource Facilities (ABRF) is to show how biophysical technologies are used to quantitatively characterize molecular interactions, and to educate the ABRF members and scientific community on the utility and limitations of core technologies [such as biosensor, microcalorimetry, or analytic ultracentrifugation (AUC)]. In the present work, the MIRG has developed a robust model protein interaction pair consisting of a bivalent variant of the Bacillus amyloliquefaciens extracellular RNase barnase and a variant of its natural monovalent intracellular inhibitor protein barstar. It is demonstrated that this system can serve as a benchmarking tool for the quantitative analysis of 2-site protein-protein interactions. The protein interaction pair enables determination of precise binding constants for the barstar protein binding to 2 distinct sites on the bivalent barnase binding partner (termed binase), where the 2 binding sites were engineered to possess affinities that differed by 2 orders of magnitude. Multiple MIRG laboratories characterized the interaction using isothermal titration calorimetry (ITC), AUC, and surface plasmon resonance (SPR) methods to evaluate the feasibility of the system as a benchmarking model. Although general agreement was seen for the binding constants measured using solution-based ITC and AUC approaches, weaker affinity was seen for surface-based method SPR, with protein immobilization likely affecting affinity. An analysis of the results from multiple MIRG laboratories suggests that the bivalent barnase-barstar system is a suitable model for benchmarking new approaches for the quantitative characterization of complex biomolecular interactions.

Recording information on protein complexes in an information management system.

Science.gov (United States)

Savitsky, Marc; Diprose, Jonathan M; Morris, Chris; Griffiths, Susanne L; Daniel, Edward; Lin, Bill; Daenke, Susan; Bishop, Benjamin; Siebold, Christian; Wilson, Keith S; Blake, Richard; Stuart, David I; Esnouf, Robert M

2011-08-01

The Protein Information Management System (PiMS) is a laboratory information management system (LIMS) designed for use with the production of proteins in a research environment. The software is distributed under the CCP4 licence, and so is available free of charge to academic laboratories. Like most LIMS, the underlying PiMS data model originally had no support for protein-protein complexes. To support the SPINE2-Complexes project the developers have extended PiMS to meet these requirements. The modifications to PiMS, described here, include data model changes, additional protocols, some user interface changes and functionality to detect when an experiment may have formed a complex. Example data are shown for the production of a crystal of a protein complex. Integration with SPINE2-Complexes Target Tracker application is also described. Copyright © 2011 Elsevier Inc. All rights reserved.

A Novel Approach for Protein-Named Entity Recognition and Protein-Protein Interaction Extraction

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Meijing Li

2015-01-01

Full Text Available Many researchers focus on developing protein-named entity recognition (Protein-NER or PPI extraction systems. However, the studies about these two topics cannot be merged well; then existing PPI extraction systems’ Protein-NER still needs to improve. In this paper, we developed the protein-protein interaction extraction system named PPIMiner based on Support Vector Machine (SVM and parsing tree. PPIMiner consists of three main models: natural language processing (NLP model, Protein-NER model, and PPI discovery model. The Protein-NER model, which is named ProNER, identifies the protein names based on two methods: dictionary-based method and machine learning-based method. ProNER is capable of identifying more proteins than dictionary-based Protein-NER model in other existing systems. The final discovered PPIs extracted via PPI discovery model are represented in detail because we showed the protein interaction types and the occurrence frequency through two different methods. In the experiments, the result shows that the performances achieved by our ProNER and PPI discovery model are better than other existing tools. PPIMiner applied this protein-named entity recognition approach and parsing tree based PPI extraction method to improve the performance of PPI extraction. We also provide an easy-to-use interface to access PPIs database and an online system for PPIs extraction and Protein-NER.

Coarse Grained Molecular Dynamics Simulations of Transmembrane Protein-Lipid Systems

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Peter Spijker

2010-06-01

Full Text Available Many biological cellular processes occur at the micro- or millisecond time scale. With traditional all-atom molecular modeling techniques it is difficult to investigate the dynamics of long time scales or large systems, such as protein aggregation or activation. Coarse graining (CG can be used to reduce the number of degrees of freedom in such a system, and reduce the computational complexity. In this paper the first version of a coarse grained model for transmembrane proteins is presented. This model differs from other coarse grained protein models due to the introduction of a novel angle potential as well as a hydrogen bonding potential. These new potentials are used to stabilize the backbone. The model has been validated by investigating the adaptation of the hydrophobic mismatch induced by the insertion of WALP-peptides into a lipid membrane, showing that the first step in the adaptation is an increase in the membrane thickness, followed by a tilting of the peptide.

Caenorhabditis elegans as a model system for studying non-cell-autonomous mechanisms in protein-misfolding diseases

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Carmen I. Nussbaum-Krammer

2014-01-01

Full Text Available Caenorhabditis elegans has a number of distinct advantages that are useful for understanding the basis for cellular and organismal dysfunction underlying age-associated diseases of protein misfolding. Although protein aggregation, a key feature of human neurodegenerative diseases, has been typically explored in vivo at the single-cell level using cells in culture, there is now increasing evidence that proteotoxicity has a non-cell-autonomous component and is communicated between cells and tissues in a multicellular organism. These discoveries have opened up new avenues for the use of C. elegans as an ideal animal model system to study non-cell-autonomous proteotoxicity, prion-like propagation of aggregation-prone proteins, and the organismal regulation of stress responses and proteostasis. This Review focuses on recent evidence that C. elegans has mechanisms to transmit certain classes of toxic proteins between tissues and a complex stress response that integrates and coordinates signals from single cells and tissues across the organism. These findings emphasize the potential of C. elegans to provide insights into non-cell-autonomous proteotoxic mechanisms underlying age-related protein-misfolding diseases.

Dynamical modeling of microRNA action on the protein translation process.

Science.gov (United States)

Zinovyev, Andrei; Morozova, Nadya; Nonne, Nora; Barillot, Emmanuel; Harel-Bellan, Annick; Gorban, Alexander N

2010-02-24

Protein translation is a multistep process which can be represented as a cascade of biochemical reactions (initiation, ribosome assembly, elongation, etc.), the rate of which can be regulated by small non-coding microRNAs through multiple mechanisms. It remains unclear what mechanisms of microRNA action are the most dominant: moreover, many experimental reports deliver controversial messages on what is the concrete mechanism actually observed in the experiment. Nissan and Parker have recently demonstrated that it might be impossible to distinguish alternative biological hypotheses using the steady state data on the rate of protein synthesis. For their analysis they used two simple kinetic models of protein translation. In contrary to the study by Nissan and Parker, we show that dynamical data allow discriminating some of the mechanisms of microRNA action. We demonstrate this using the same models as developed by Nissan and Parker for the sake of comparison but the methods developed (asymptotology of biochemical networks) can be used for other models. We formulate a hypothesis that the effect of microRNA action is measurable and observable only if it affects the dominant system (generalization of the limiting step notion for complex networks) of the protein translation machinery. The dominant system can vary in different experimental conditions that can partially explain the existing controversy of some of the experimental data. Our analysis of the transient protein translation dynamics shows that it gives enough information to verify or reject a hypothesis about a particular molecular mechanism of microRNA action on protein translation. For multiscale systems only that action of microRNA is distinguishable which affects the parameters of dominant system (critical parameters), or changes the dominant system itself. Dominant systems generalize and further develop the old and very popular idea of limiting step. Algorithms for identifying dominant systems in multiscale

Dynamical modeling of microRNA action on the protein translation process

Directory of Open Access Journals (Sweden)

Barillot Emmanuel

2010-02-01

Full Text Available Abstract Background Protein translation is a multistep process which can be represented as a cascade of biochemical reactions (initiation, ribosome assembly, elongation, etc., the rate of which can be regulated by small non-coding microRNAs through multiple mechanisms. It remains unclear what mechanisms of microRNA action are the most dominant: moreover, many experimental reports deliver controversial messages on what is the concrete mechanism actually observed in the experiment. Nissan and Parker have recently demonstrated that it might be impossible to distinguish alternative biological hypotheses using the steady state data on the rate of protein synthesis. For their analysis they used two simple kinetic models of protein translation. Results In contrary to the study by Nissan and Parker, we show that dynamical data allow discriminating some of the mechanisms of microRNA action. We demonstrate this using the same models as developed by Nissan and Parker for the sake of comparison but the methods developed (asymptotology of biochemical networks can be used for other models. We formulate a hypothesis that the effect of microRNA action is measurable and observable only if it affects the dominant system (generalization of the limiting step notion for complex networks of the protein translation machinery. The dominant system can vary in different experimental conditions that can partially explain the existing controversy of some of the experimental data. Conclusions Our analysis of the transient protein translation dynamics shows that it gives enough information to verify or reject a hypothesis about a particular molecular mechanism of microRNA action on protein translation. For multiscale systems only that action of microRNA is distinguishable which affects the parameters of dominant system (critical parameters, or changes the dominant system itself. Dominant systems generalize and further develop the old and very popular idea of limiting step

Metabolizable protein systems in ruminant nutrition: A review

Directory of Open Access Journals (Sweden)

Lalatendu Keshary Das

2014-08-01

Full Text Available Protein available to ruminants is supplied by both microbial and dietary sources. Metabolizable protein (MP is the true protein which is absorbed by the intestine and supplied by both microbial protein and protein which escapes degradation in the rumen; the protein which is available to the animal for maintenance, growth, fetal growth during gestation, and milk production. Thus, the concept of balancing ruminant rations basing on only dietary crude protein (CP content seems erroneous. In India, ruminant rations are still balanced for digestible CP and total digestible nutrients for protein and energy requirements, respectively. Traditional feed analysis methods such as proximate analysis and detergent analysis consider feed protein as a single unit and do not take into account of the degradation processes that occur in rumen and passage rates of feed fractions from rumen to intestine. Therefore, the protein requirement of ruminants should include not only the dietary protein source, but also the microbial CP from rumen. The MP systems consider both the factors, thus predict the protein availability more accurately and precisely. This system is aptly designed to represent the extent of protein degradation in the rumen and the synthesis of microbial protein as variable functions. Feed protein fractions, i.e., rumen degradable protein and rumen undegradable protein play vital roles in meeting protein requirements of rumen microbes and host animal, respectively. With the advent of sophisticated nutrition models such as Cornell net carbohydrate and protein system, National Research Council, Agricultural Research Council, Cornell Penn Miner Dairy and Amino Cow; ration formulation has moved from balancing diets from CP to MP, a concept that describes the protein requirements of ruminantsat intestinal level, and which is available to animals for useful purposes.

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.

Engineering FKBP-Based Destabilizing Domains to Build Sophisticated Protein Regulation Systems.

Directory of Open Access Journals (Sweden)

Wenlin An

Full Text Available Targeting protein stability with small molecules has emerged as an effective tool to control protein abundance in a fast, scalable and reversible manner. The technique involves tagging a protein of interest (POI with a destabilizing domain (DD specifically controlled by a small molecule. The successful construction of such fusion proteins may, however, be limited by functional interference of the DD epitope with electrostatic interactions required for full biological function of proteins. Another drawback of this approach is the remaining endogenous protein. Here, we combined the Cre-LoxP system with an advanced DD and generated a protein regulation system in which the loss of an endogenous protein, in our case the tumor suppressor PTEN, can be coupled directly with a conditionally fine-tunable DD-PTEN. This new system will consolidate and extend the use of DD-technology to control protein function precisely in living cells and animal models.

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.

A resource for benchmarking the usefulness of protein structure models

Directory of Open Access Journals (Sweden)

Carbajo Daniel

2012-08-01

Full Text Available Abstract 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

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

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

Poly lactic acid based injectable delivery systems for controlled release of a model protein, lysozyme.

Science.gov (United States)

Al-Tahami, Khaled; Meyer, Amanda; Singh, Jagdish

2006-02-01

The objective of this study was to evaluate the critical formulation parameters (i.e., polymer concentration, polymer molecular weight, and solvent nature) affecting the controlled delivery of a model protein, lysozyme, from injectable polymeric implants. The conformational stability and biological activity of the released lysozyme were also investigated. Three formulations containing 10%, 20%, and 30% (w/v) poly lactic acid (PLA) in triacetin were investigated. It was found that increasing polymer concentration in the formulations led to a lower burst effect and a slower release rate. Formulation with a high molecular weight polymer showed a greater burst effect as compared to those containing low molecular weight. Conformational stability and biological activity of released samples were studied by differential scanning calorimeter and enzyme activity assay, respectively. The released samples had significantly (P solution kept at same conditions). Increasing polymer concentration increased both the conformational stability and the biological activity of released lysozyme. In conclusion, phase sensitive polymer-based delivery systems were able to deliver a model protein, lysozyme, in a conformationally stable and biologically active form at a controlled rate over an extended period.

Scalable rule-based modelling of allosteric proteins and biochemical networks.

Directory of Open Access Journals (Sweden)

Julien F Ollivier

2010-11-01

Full Text Available Much of the complexity of biochemical networks comes from the information-processing abilities of allosteric proteins, be they receptors, ion-channels, signalling molecules or transcription factors. An allosteric protein can be uniquely regulated by each combination of input molecules that it binds. This "regulatory complexity" causes a combinatorial increase in the number of parameters required to fit experimental data as the number of protein interactions increases. It therefore challenges the creation, updating, and re-use of biochemical models. Here, we propose a rule-based modelling framework that exploits the intrinsic modularity of protein structure to address regulatory complexity. Rather than treating proteins as "black boxes", we model their hierarchical structure and, as conformational changes, internal dynamics. By modelling the regulation of allosteric proteins through these conformational changes, we often decrease the number of parameters required to fit data, and so reduce over-fitting and improve the predictive power of a model. Our method is thermodynamically grounded, imposes detailed balance, and also includes molecular cross-talk and the background activity of enzymes. We use our Allosteric Network Compiler to examine how allostery can facilitate macromolecular assembly and how competitive ligands can change the observed cooperativity of an allosteric protein. We also develop a parsimonious model of G protein-coupled receptors that explains functional selectivity and can predict the rank order of potency of agonists acting through a receptor. Our methodology should provide a basis for scalable, modular and executable modelling of biochemical networks in systems and synthetic biology.

Specific interaction of central nervous system myelin basic protein with lipids effects of basic protein on glucose leakage from liposomes

NARCIS (Netherlands)

Gould, R.M.; London, Y.

1972-01-01

The leakage from liposomes preloaded with glucose was continuously monitored in a Perkin-Elmer Model 356 dual beam spectrophotometer using an enzyme-linked assay system. The central nervous system myelin basic protein (A1 protein) caused a 3–4-fold increase in the rate of leakage from liposomes

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

A mathematical model for generating bipartite graphs and its application to protein networks

International Nuclear Information System (INIS)

Nacher, J C; Ochiai, T; Hayashida, M; Akutsu, T

2009-01-01

Complex systems arise in many different contexts from large communication systems and transportation infrastructures to molecular biology. Most of these systems can be organized into networks composed of nodes and interacting edges. Here, we present a theoretical model that constructs bipartite networks with the particular feature that the degree distribution can be tuned depending on the probability rate of fundamental processes. We then use this model to investigate protein-domain networks. A protein can be composed of up to hundreds of domains. Each domain represents a conserved sequence segment with specific functional tasks. We analyze the distribution of domains in Homo sapiens and Arabidopsis thaliana organisms and the statistical analysis shows that while (a) the number of domain types shared by k proteins exhibits a power-law distribution, (b) the number of proteins composed of k types of domains decays as an exponential distribution. The proposed mathematical model generates bipartite graphs and predicts the emergence of this mixing of (a) power-law and (b) exponential distributions. Our theoretical and computational results show that this model requires (1) growth process and (2) copy mechanism.

A mathematical model for generating bipartite graphs and its application to protein networks

Science.gov (United States)

Nacher, J. C.; Ochiai, T.; Hayashida, M.; Akutsu, T.

2009-12-01

Complex systems arise in many different contexts from large communication systems and transportation infrastructures to molecular biology. Most of these systems can be organized into networks composed of nodes and interacting edges. Here, we present a theoretical model that constructs bipartite networks with the particular feature that the degree distribution can be tuned depending on the probability rate of fundamental processes. We then use this model to investigate protein-domain networks. A protein can be composed of up to hundreds of domains. Each domain represents a conserved sequence segment with specific functional tasks. We analyze the distribution of domains in Homo sapiens and Arabidopsis thaliana organisms and the statistical analysis shows that while (a) the number of domain types shared by k proteins exhibits a power-law distribution, (b) the number of proteins composed of k types of domains decays as an exponential distribution. The proposed mathematical model generates bipartite graphs and predicts the emergence of this mixing of (a) power-law and (b) exponential distributions. Our theoretical and computational results show that this model requires (1) growth process and (2) copy mechanism.

A mathematical model for generating bipartite graphs and its application to protein networks

Energy Technology Data Exchange (ETDEWEB)

Nacher, J C [Department of Complex Systems, Future University-Hakodate (Japan); Ochiai, T [Faculty of Engineering, Toyama Prefectural University (Japan); Hayashida, M; Akutsu, T [Bioinformatics Center, Institute for Chemical Research, Kyoto University (Japan)

2009-12-04

Complex systems arise in many different contexts from large communication systems and transportation infrastructures to molecular biology. Most of these systems can be organized into networks composed of nodes and interacting edges. Here, we present a theoretical model that constructs bipartite networks with the particular feature that the degree distribution can be tuned depending on the probability rate of fundamental processes. We then use this model to investigate protein-domain networks. A protein can be composed of up to hundreds of domains. Each domain represents a conserved sequence segment with specific functional tasks. We analyze the distribution of domains in Homo sapiens and Arabidopsis thaliana organisms and the statistical analysis shows that while (a) the number of domain types shared by k proteins exhibits a power-law distribution, (b) the number of proteins composed of k types of domains decays as an exponential distribution. The proposed mathematical model generates bipartite graphs and predicts the emergence of this mixing of (a) power-law and (b) exponential distributions. Our theoretical and computational results show that this model requires (1) growth process and (2) copy mechanism.

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.

MATHEMATICAL AND COMPUTATIONAL MODELLING OF RIBOSOMAL MOVEMENT AND PROTEIN SYNTHESIS: AN OVERVIEW

Directory of Open Access Journals (Sweden)

Tobias von der Haar

2012-04-01

Full Text Available Translation or protein synthesis consists of a complex system of chemical reactions, which ultimately result in decoding of the mRNA and the production of a protein. The complexity of this reaction system makes it difficult to quantitatively connect its input parameters (such as translation factor or ribosome concentrations, codon composition of the mRNA, or energy availability to output parameters (such as protein synthesis rates or ribosome densities on mRNAs. Mathematical and computational models of translation have now been used for nearly five decades to investigate translation, and to shed light on the relationship between the different reactions in the system. This review gives an overview over the principal approaches used in the modelling efforts, and summarises some of the major findings that were made.

Protein- protein interaction detection system using fluorescent protein microdomains

Science.gov (United States)

Waldo, Geoffrey S.; Cabantous, Stephanie

2010-02-23

The invention provides a protein labeling and interaction detection system based on engineered fragments of fluorescent and chromophoric proteins that require fused interacting polypeptides to drive the association of the fragments, and further are soluble and stable, and do not change the solubility of polypeptides to which they are fused. In one embodiment, a test protein X is fused to a sixteen amino acid fragment of GFP (.beta.-strand 10, amino acids 198-214), engineered to not perturb fusion protein solubility. A second test protein Y is fused to a sixteen amino acid fragment of GFP (.beta.-strand 11, amino acids 215-230), engineered to not perturb fusion protein solubility. When X and Y interact, they bring the GFP strands into proximity, and are detected by complementation with a third GFP fragment consisting of GFP amino acids 1-198 (strands 1-9). When GFP strands 10 and 11 are held together by interaction of protein X and Y, they spontaneous association with GFP strands 1-9, resulting in structural complementation, folding, and concomitant GFP fluorescence.

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.

Virtual Screening of M3 Protein Antagonists for Finding a Model to Study the Gammaherpesvirus Damaged Immune System and Chemokine Related Diseases

Directory of Open Access Journals (Sweden)

Ibrahim Torktaz

2013-12-01

Full Text Available Introduction: M3 protein is a chemokine decoy receptor involved in pathogenesis of persistent infection with gammaherpesvirus and complications related to the latency of this pathogen. We proposed that antagonists of the M3 would provide a unique opportunity for studying new therapeutic strategies in disordered immune system, immune-deficient states and role of chemokines in pathogenesis development. Methods: Comparative modeling and fold recognition algorithms have been used for prediction of M3 protein 3-D model. Evaluation of the models using Q-mean and ProSA-web score, has led to choosing predicted model by fold recognition algorithm as the best model which was minimized regarding energy level using Molegro Virtual Docker 2011.4.3.0 (MVD software. Pockets and active sites of model were recognized using MVD cavity detection, and MetaPocket algorithms. Ten thousand compounds accessible on KEGG database were screened; MVD was used for computer simulated docking study; MolDock SE was selected as docking scoring function and final results were evaluated based on MolDock and Re-rank score. Results: Docking data suggested that prilocaine, which is generally applied as a topical anesthetic, binds strongly to 3-D model of M3 protein. Conclusion: This study proposes that prilocaine is a potential inhibitor of M3 protein and possibly has immune enhancing properties.

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.

PROGRAM SYSTEM AND INFORMATION METADATA BANK OF TERTIARY PROTEIN STRUCTURES

Directory of Open Access Journals (Sweden)

T. A. Nikitin

2013-01-01

Full Text Available The article deals with the architecture of metadata storage model for check results of three-dimensional protein structures. Concept database model was built. The service and procedure of database update as well as data transformation algorithms for protein structures and their quality were presented. Most important information about entries and their submission forms to store, access, and delivery to users were highlighted. Software suite was developed for the implementation of functional tasks using Java programming language in the NetBeans v.7.0 environment and JQL to query and interact with the database JavaDB. The service was tested and results have shown system effectiveness while protein structures filtration.

Reaction mechanisms in the radiolysis of peptides, polypeptides and proteins II reactions at side-chain loci in model systems

International Nuclear Information System (INIS)

Garrison, W.M.

1983-11-01

The major emphasis in radiation biology at the molecular level has been on the nucleic acid component of the nucleic acid-protein complex because of its primary genetic importance. But there is increasing evidence that radiation damage to the protein component also has important biological implications. Damage to capsid protein now appears to be a major factor in the radiation inactivation of phage and other viruses. And, there is increasing evidence that radiation-chemical change in the protein component of chromation leads to changes in the stability of the repressor-operator complexes involved in gene expression. Knowledge of the radiation chemistry of protein is also of importance in other fields such as the application of radiation sterilization to foods and drugs. Recent findings that a class of compounds, the α,α'-diaminodicarboxylic acids, not normally present in food proteins, are formed in protein radiolysis is of particular significance since certain of their peptide derivatives have been showing to exhibit immunological activity. The purpose of this review is to bring together and to correlate our present knowledge of products and mechanisms in the radiolysis of peptides, polypeptides and proteins both aqueous and solid-state. In part 1 we presented a discussion of the radiation-induced reactions of the peptide main-chain in model peptide and polypeptide systems. Here in part 2 the emphasis is on the competing radiation chemistry at side-chain loci of peptide derivatives of aliphatic, aromatic-unsaturated and sulfur-containing amino acids in similar systems. Information obtained with the various experimental techniques of product analysis, competition kinetics, spin-trapping, pulse radiolysis, and ESR spectroscopy are included

Identification of Anaplasma marginale type IV secretion system effector proteins.

Directory of Open Access Journals (Sweden)

Svetlana Lockwood

Full Text Available Anaplasma marginale, an obligate intracellular alphaproteobacterium in the order Rickettsiales, is a tick-borne pathogen and the leading cause of anaplasmosis in cattle worldwide. Complete genome sequencing of A. marginale revealed that it has a type IV secretion system (T4SS. The T4SS is one of seven known types of secretion systems utilized by bacteria, with the type III and IV secretion systems particularly prevalent among pathogenic Gram-negative bacteria. The T4SS is predicted to play an important role in the invasion and pathogenesis of A. marginale by translocating effector proteins across its membrane into eukaryotic target cells. However, T4SS effector proteins have not been identified and tested in the laboratory until now.By combining computational methods with phylogenetic analysis and sequence identity searches, we identified a subset of potential T4SS effectors in A. marginale strain St. Maries and chose six for laboratory testing. Four (AM185, AM470, AM705 [AnkA], and AM1141 of these six proteins were translocated in a T4SS-dependent manner using Legionella pneumophila as a reporter system.The algorithm employed to find T4SS effector proteins in A. marginale identified four such proteins that were verified by laboratory testing. L. pneumophila was shown to work as a model system for A. marginale and thus can be used as a screening tool for A. marginale effector proteins. The first T4SS effector proteins for A. marginale have been identified in this work.

Change detection in the dynamics of an intracellular protein synthesis model using nonlinear Kalman filtering.

Science.gov (United States)

Rigatos, Gerasimos G; Rigatou, Efthymia G; Djida, Jean Daniel

2015-10-01

A method for early diagnosis of parametric changes in intracellular protein synthesis models (e.g. the p53 protein - mdm2 inhibitor model) is developed with the use of a nonlinear Kalman Filtering approach (Derivative-free nonlinear Kalman Filter) and of statistical change detection methods. The intracellular protein synthesis dynamic model is described by a set of coupled nonlinear differential equations. It is shown that such a dynamical system satisfies differential flatness properties and this allows to transform it, through a change of variables (diffeomorphism), to the so-called linear canonical form. For the linearized equivalent of the dynamical system, state estimation can be performed using the Kalman Filter recursion. Moreover, by applying an inverse transformation based on the previous diffeomorphism it becomes also possible to obtain estimates of the state variables of the initial nonlinear model. By comparing the output of the Kalman Filter (which is assumed to correspond to the undistorted dynamical model) with measurements obtained from the monitored protein synthesis system, a sequence of differences (residuals) is obtained. The statistical processing of the residuals with the use of x2 change detection tests, can provide indication within specific confidence intervals about parametric changes in the considered biological system and consequently indications about the appearance of specific diseases (e.g. malignancies).

21 CFR 862.1630 - Protein (fractionation) test system.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Protein (fractionation) test system. 862.1630... Systems § 862.1630 Protein (fractionation) test system. (a) Identification. A protein (fractionation) test system is a device intended to measure protein fractions in blood, urine, cerebrospinal fluid, and other...

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

Directory of Open Access Journals (Sweden)

Sankar Basu

Full Text Available The state-of-the-art to assess the structural quality of docking models is currently based on three related yet independent quality measures: Fnat, LRMS, and iRMS as proposed and standardized by CAPRI. These quality measures quantify different aspects of the quality of a particular docking model and need to be viewed together to reveal the true quality, e.g. a model with relatively poor LRMS (>10Å might still qualify as 'acceptable' with a descent Fnat (>0.50 and iRMS (<3.0Å. This is also the reason why the so called CAPRI criteria for assessing the quality of docking models is defined by applying various ad-hoc cutoffs on these measures to classify a docking model into the four classes: Incorrect, Acceptable, Medium, or High quality. This classification has been useful in CAPRI, but since models are grouped in only four bins it is also rather limiting, making it difficult to rank models, correlate with scoring functions or use it as target function in machine learning algorithms. Here, we present DockQ, a continuous protein-protein docking model quality measure derived by combining Fnat, LRMS, and iRMS to a single score in the range [0, 1] that can be used to assess the quality of protein docking models. By using DockQ on CAPRI models it is possible to almost completely reproduce the original CAPRI classification into Incorrect, Acceptable, Medium and High quality. An average PPV of 94% at 90% Recall demonstrating that there is no need to apply predefined ad-hoc cutoffs to classify docking models. Since DockQ recapitulates the CAPRI classification almost perfectly, it can be viewed as a higher resolution version of the CAPRI classification, making it possible to estimate model quality in a more quantitative way using Z-scores or sum of top ranked models, which has been so valuable for the CASP community. The possibility to directly correlate a quality measure to a scoring function has been crucial for the development of scoring functions for

Synthesis of milligram quantities of proteins using a reconstituted in vitro protein synthesis system.

Science.gov (United States)

Kazuta, Yasuaki; Matsuura, Tomoaki; Ichihashi, Norikazu; Yomo, Tetsuya

2014-11-01

In this study, the amount of protein synthesized using an in vitro protein synthesis system composed of only highly purified components (the PURE system) was optimized. By varying the concentrations of each system component, we determined the component concentrations that result in the synthesis of 0.38 mg/mL green fluorescent protein (GFP) in batch mode and 3.8 mg/mL GFP in dialysis mode. In dialysis mode, protein concentrations of 4.3 and 4.4 mg/mL were synthesized for dihydrofolate reductase and β-galactosidase, respectively. Using the optimized system, the synthesized protein represented 30% (w/w) of the total protein, which is comparable to the level of overexpressed protein in Escherichia coli cells. This optimized reconstituted in vitro protein synthesis system may potentially be useful for various applications, including in vitro directed evolution of proteins, artificial cell assembly, and protein structural studies. Copyright © 2014 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Truly Absorbed Microbial Protein Synthesis, Rumen Bypass Protein, Endogenous Protein, and Total Metabolizable Protein from Starchy and Protein-Rich Raw Materials

NARCIS (Netherlands)

Parand, Ehsan; Vakili, Alireza; Mesgaran, Mohsen Danesh; Duinkerken, Van Gert; Yu, Peiqiang

2015-01-01

This study was carried out to measure truly absorbed microbial protein synthesis, rumen bypass protein, and endogenous protein loss, as well as total metabolizable protein, from starchy and protein-rich raw feed materials with model comparisons. Predictions by the DVE2010 system as a more

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.

Plant G-Proteins Come of Age: Breaking the Bond with Animal Models.

Science.gov (United States)

Trusov, Yuri; Botella, José R

2016-01-01

G-proteins are universal signal transducers mediating many cellular responses. Plant G-protein signaling has been modeled on the well-established animal paradigm but accumulated experimental evidence indicates that G-protein-dependent signaling in plants has taken a very different evolutionary path. Here we review the differences between plant and animal G-proteins reported over past two decades. Most importantly, while in animal systems the G-protein signaling cycle is activated by seven transmembrane-spanning G-protein coupled receptors, the existence of these type of receptors in plants is highly controversial. Instead plant G-proteins have been proven to be functionally associated with atypical receptors such as the Arabidopsis RGS1 and a number of receptor-like kinases. We propose that, instead of the GTP/GDP cycle used in animals, plant G-proteins are activated/de-activated by phosphorylation/de-phosphorylation. We discuss the need of a fresh new look at these signaling molecules and provide a hypothetical model that departs from the accepted animal paradigm.

Preparation of ubiquitin-conjugated proteins using an insect cell-free protein synthesis system.

Science.gov (United States)

Suzuki, Takashi; Ezure, Toru; Ando, Eiji; Nishimura, Osamu; Utsumi, Toshihiko; Tsunasawa, Susumu

2010-01-01

Ubiquitination is one of the most significant posttranslational modifications (PTMs). To evaluate the ability of an insect cell-free protein synthesis system to carry out ubiquitin (Ub) conjugation to in vitro translated proteins, poly-Ub chain formation was studied in an insect cell-free protein synthesis system. Poly-Ub was generated in the presence of Ub aldehyde (UA), a de-ubiquitinating enzyme inhibitor. In vitro ubiquitination of the p53 tumor suppressor protein was also analyzed, and p53 was poly-ubiquitinated when Ub, UA, and Mdm2, an E3 Ub ligase (E3) for p53, were added to the in vitro reaction mixture. These results suggest that the insect cell-free protein synthesis system contains enzymatic activities capable of carrying out ubiquitination. CBB-detectable ubiquitinated p53 was easily purified from the insect cell-free protein synthesis system, allowing analysis of the Ub-conjugated proteins by mass spectrometry (MS). Lys 305 of p53 was identified as one of the Ub acceptor sites using this strategy. Thus, we conclude that the insect cell-free protein synthesis system is a powerful tool for studying various PTMs of eukaryotic proteins including ubiqutination presented here.

Multiway modeling and analysis in stem cell systems biology

Directory of Open Access Journals (Sweden)

Vandenberg Scott L

2008-07-01

Full Text Available Abstract Background Systems biology refers to multidisciplinary approaches designed to uncover emergent properties of biological systems. Stem cells are an attractive target for this analysis, due to their broad therapeutic potential. A central theme of systems biology is the use of computational modeling to reconstruct complex systems from a wealth of reductionist, molecular data (e.g., gene/protein expression, signal transduction activity, metabolic activity, etc.. A number of deterministic, probabilistic, and statistical learning models are used to understand sophisticated cellular behaviors such as protein expression during cellular differentiation and the activity of signaling networks. However, many of these models are bimodal i.e., they only consider row-column relationships. In contrast, multiway modeling techniques (also known as tensor models can analyze multimodal data, which capture much more information about complex behaviors such as cell differentiation. In particular, tensors can be very powerful tools for modeling the dynamic activity of biological networks over time. Here, we review the application of systems biology to stem cells and illustrate application of tensor analysis to model collagen-induced osteogenic differentiation of human mesenchymal stem cells. Results We applied Tucker1, Tucker3, and Parallel Factor Analysis (PARAFAC models to identify protein/gene expression patterns during extracellular matrix-induced osteogenic differentiation of human mesenchymal stem cells. In one case, we organized our data into a tensor of type protein/gene locus link × gene ontology category × osteogenic stimulant, and found that our cells expressed two distinct, stimulus-dependent sets of functionally related genes as they underwent osteogenic differentiation. In a second case, we organized DNA microarray data in a three-way tensor of gene IDs × osteogenic stimulus × replicates, and found that application of tensile strain to a

Preparing and evaluating delivery systems for proteins

DEFF Research Database (Denmark)

Jorgensen, L; Moeller, E H; van de Weert, M

2006-01-01

From a formulation perspective proteins are complex and therefore challenging molecules to develop drug delivery systems for. The success of a formulation depends on the ability of the protein to maintain the native structure and activity during preparation and delivery as well as during shipping...... and long-term storage of the formulation. Therefore, the development and evaluation of successful and promising drug delivery systems is essential. In the present review, some of the particulate drug delivery systems for parenteral delivery of protein are presented and discussed. The challenge...... for incorporation of protein in particulate delivery systems is exemplified by water-in-oil emulsions....

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 ...

21 CFR 862.1640 - Protein-bound iodine test system.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Protein-bound iodine test system. 862.1640 Section... Systems § 862.1640 Protein-bound iodine test system. (a) Identification. A protein-bound iodine test system is a device intended to measure protein-bound iodine in serum. Measurements of protein-bound...

On the characterization and software implementation of general protein lattice models.

Directory of Open Access Journals (Sweden)

Alessio Bechini

Full Text Available models of proteins have been widely used as a practical means to computationally investigate general properties of the system. In lattice models any sterically feasible conformation is represented as a self-avoiding walk on a lattice, and residue types are limited in number. So far, only two- or three-dimensional lattices have been used. The inspection of the neighborhood of alpha carbons in the core of real proteins reveals that also lattices with higher coordination numbers, possibly in higher dimensional spaces, can be adopted. In this paper, a new general parametric lattice model for simplified protein conformations is proposed and investigated. It is shown how the supporting software can be consistently designed to let algorithms that operate on protein structures be implemented in a lattice-agnostic way. The necessary theoretical foundations are developed and organically presented, pinpointing the role of the concept of main directions in lattice-agnostic model handling. Subsequently, the model features across dimensions and lattice types are explored in tests performed on benchmark protein sequences, using a Python implementation. Simulations give insights on the use of square and triangular lattices in a range of dimensions. The trend of potential minimum for sequences of different lengths, varying the lattice dimension, is uncovered. Moreover, an extensive quantitative characterization of the usage of the so-called "move types" is reported for the first time. The proposed general framework for the development of lattice models is simple yet complete, and an object-oriented architecture can be proficiently employed for the supporting software, by designing ad-hoc classes. The proposed framework represents a new general viewpoint that potentially subsumes a number of solutions previously studied. The adoption of the described model pushes to look at protein structure issues from a more general and essential perspective, making

Self-organized critical model for protein folding

Science.gov (United States)

Moret, M. A.

2011-09-01

The major factor that drives a protein toward collapse and folding is the hydrophobic effect. At the folding process a hydrophobic core is shielded by the solvent-accessible surface area of the protein. We study the fractal behavior of 5526 protein structures present in the Brookhaven Protein Data Bank. Power laws of protein mass, volume and solvent-accessible surface area are measured independently. The present findings indicate that self-organized criticality is an alternative explanation for the protein folding. Also we note that the protein packing is an independent and constant value because the self-similar behavior of the volumes and protein masses have the same fractal dimension. This power law guarantees that a protein is a complex system. From the analyzed data, q-Gaussian distributions seem to fit well this class of systems.

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)

Protein model discrimination using mutational sensitivity derived from deep sequencing.

Science.gov (United States)

Adkar, Bharat V; Tripathi, Arti; Sahoo, Anusmita; Bajaj, Kanika; Goswami, Devrishi; Chakrabarti, Purbani; Swarnkar, Mohit K; Gokhale, Rajesh S; Varadarajan, Raghavan

2012-02-08

A major bottleneck in protein structure prediction is the selection of correct models from a pool of decoys. Relative activities of ∼1,200 individual single-site mutants in a saturation library of the bacterial toxin CcdB were estimated by determining their relative populations using deep sequencing. This phenotypic information was used to define an empirical score for each residue (RankScore), which correlated with the residue depth, and identify active-site residues. Using these correlations, ∼98% of correct models of CcdB (RMSD ≤ 4Å) were identified from a large set of decoys. The model-discrimination methodology was further validated on eleven different monomeric proteins using simulated RankScore values. The methodology is also a rapid, accurate way to obtain relative activities of each mutant in a large pool and derive sequence-structure-function relationships without protein isolation or characterization. It can be applied to any system in which mutational effects can be monitored by a phenotypic readout. Copyright © 2012 Elsevier Ltd. All rights reserved.

Hybrid system of semiconductor and photosynthetic protein

International Nuclear Information System (INIS)

Kim, Younghye; Shin, Seon Ae; Lee, Jaehun; Yang, Ki Dong; Nam, Ki Tae

2014-01-01

Photosynthetic protein has the potential to be a new attractive material for solar energy absorption and conversion. The development of semiconductor/photosynthetic protein hybrids is an example of recent progress toward efficient, clean and nanostructured photoelectric systems. In the review, two biohybrid systems interacting through different communicating methods are addressed: (1) a photosynthetic protein immobilized semiconductor electrode operating via electron transfer and (2) a hybrid of semiconductor quantum dots and photosynthetic protein operating via energy transfer. The proper selection of materials and functional and structural modification of the components and optimal conjugation between them are the main issues discussed in the review. In conclusion, we propose the direction of future biohybrid systems for solar energy conversion systems, optical biosensors and photoelectric devices. (topical reviews)

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

A Continuous-Exchange Cell-Free Protein Synthesis System Based on Extracts from Cultured Insect Cells

Science.gov (United States)

Stech, Marlitt; Quast, Robert B.; Sachse, Rita; Schulze, Corina; Wüstenhagen, Doreen A.; Kubick, Stefan

2014-01-01

In this study, we present a novel technique for the synthesis of complex prokaryotic and eukaryotic proteins by using a continuous-exchange cell-free (CECF) protein synthesis system based on extracts from cultured insect cells. Our approach consists of two basic elements: First, protein synthesis is performed in insect cell lysates which harbor endogenous microsomal vesicles, enabling a translocation of de novo synthesized target proteins into the lumen of the insect vesicles or, in the case of membrane proteins, their embedding into a natural membrane scaffold. Second, cell-free reactions are performed in a two chamber dialysis device for 48 h. The combination of the eukaryotic cell-free translation system based on insect cell extracts and the CECF translation system results in significantly prolonged reaction life times and increased protein yields compared to conventional batch reactions. In this context, we demonstrate the synthesis of various representative model proteins, among them cytosolic proteins, pharmacological relevant membrane proteins and glycosylated proteins in an endotoxin-free environment. Furthermore, the cell-free system used in this study is well-suited for the synthesis of biologically active tissue-type-plasminogen activator, a complex eukaryotic protein harboring multiple disulfide bonds. PMID:24804975

A universal DNA-based protein detection system.

Science.gov (United States)

Tran, Thua N N; Cui, Jinhui; Hartman, Mark R; Peng, Songming; Funabashi, Hisakage; Duan, Faping; Yang, Dayong; March, John C; Lis, John T; Cui, Haixin; Luo, Dan

2013-09-25

Protein immune detection requires secondary antibodies which must be carefully selected in order to avoid interspecies cross-reactivity, and is therefore restricted by the limited availability of primary/secondary antibody pairs. Here we present a versatile DNA-based protein detection system using a universal adapter to interface between IgG antibodies and DNA-modified reporter molecules. As a demonstration of this capability, we successfully used DNA nano-barcodes, quantum dots, and horseradish peroxidase enzyme to detect multiple proteins using our DNA-based labeling system. Our system not only eliminates secondary antibodies but also serves as a novel method platform for protein detection with modularity, high capacity, and multiplexed capability.

On prilled Nanotubes-in-Microgel Oral Systems for protein delivery.

Science.gov (United States)

de Kruif, Jan Kendall; Ledergerber, Gisela; Garofalo, Carla; Fasler-Kan, Elizaveta; Kuentz, Martin

2016-04-01

Newly discovered active macromolecules are highly promising for therapy, but poor bioavailability hinders their oral use. Microencapsulation approaches, such as protein prilling into microspheres, may enable protection from gastrointestinal (GI) enzymatic degradation. This would increase bioavailability mainly for local delivery to GI lumen or mucosa. This work's purpose was to design a novel architecture, namely a Nanotubes-in-Microgel Oral System, by prilling for protein delivery. Halloysite nanotubes (HNT) were selected as orally acceptable clay particles and their lumen was enlarged by alkaline etching. This chemical modification increased the luminal volume to a mean of 216.3 μL g(-1) (+40.8%). After loading albumin as model drug, the HNT were entrapped in microgels by prilling. The formation of Nanoparticles-in-Microsphere Oral System (NiMOS) yielded entrapment efficiencies up to 63.2%. NiMOS shape was spherical to toroidal, with a diameter smaller than 320 μm. Release profiles depended largely on the employed system and HNT type. Protein stability was determined throughout prilling and after in vitro enzymatic degradation. Prilling did not harm protein structure, and NiMOS demonstrated higher enzymatic protection than pure nanotubes or microgels, since up to 82% of BSA remained unscathed after in vitro digestion. Therefore, prilled NiMOS was shown to be a promising and flexible multi-compartment system for oral (local) macromolecular delivery. Copyright © 2016 Elsevier B.V. All rights reserved.

Tracer kinetics: Modelling of tracer behaviour in nonlinear and nonsteady state systems exemplified by the evaluation of protein turnover in plant organs

International Nuclear Information System (INIS)

Winkler, E.

1991-01-01

If nonlinear biological processes are investigated by means of tracer experiments they can be modelled with linear kinetic equations (compartment equations) as long as the total system is in a stationary state. But if nonstationary behaviour is included considerations on the kinetics of the individual processes are necessary. Within the range of biological and agricultural investigations especially first order reactions (constant fraction processes), zero order reactions (constant amount process) and saturation reactions (Michaelis-Menten-kinetics) are to be taken into account. A rigorous treatment of data based on system theory can be preceeded by graphic-algebraic procedure which may be more or less uncertain in its results but which can easily be handled. An example is given of methodological considerations concerning the combination of evaluation procedures and the discrimination between different reaction mechanisms. It treats protein turnover in 2 different parts of growing wheat plants investigated by means of an 15 N-tracer experiment. Whereas in a stationary system (upper stalk section) linear tracer equations were sufficient irrespective of the true reaction mechanism, for protein synthesis in the upper leaf as a nonstationary system it was necessary to decide between the hypotheses of a zero order and a first order reaction. In accordance with statements in the literature the unambiguous result was a combination of protein synthesis as a zero order process and of protein degradation as a first order process. (orig.) [de

Hydrophobic interaction chromatography in dual salt system increases protein binding capacity.

Science.gov (United States)

Senczuk, Anna M; Klinke, Ralph; Arakawa, Tsutomu; Vedantham, Ganesh; Yigzaw, Yinges

2009-08-01

Hydrophobic interaction chromatography (HIC) uses weakly hydrophobic resins and requires a salting-out salt to promote protein-resin interaction. The salting-out effects increase with protein and salt concentration. Dynamic binding capacity (DBC) is dependent on the binding constant, as well as on the flow characteristics during sample loading. DBC increases with the salt concentration but decreases with increasing flow rate. Dynamic and operational binding capacity have a major raw material cost/processing time impact on commercial scale production of monoclonal antibodies. In order to maximize DBC the highest salt concentration without causing precipitation is used. We report here a novel method to maintain protein solubility while increasing the DBC by using a combination of two salting-out salts (referred to as dual salt). In a series of experiments, we explored the dynamic capacity of a HIC resin (TosoBioscience Butyl 650M) with combinations of salts. Using a model antibody, we developed a system allowing us to increase the dynamic capacity up to twofold using the dual salt system over traditional, single salt system. We also investigated the application of this novel approach to several other proteins and salt combinations, and noted a similar protein solubility and DBC increase. The observed increase in DBC in the dual salt system was maintained at different linear flow rates and did not impact selectivity.

Energy and environmental implications of novel protein production systems

Energy Technology Data Exchange (ETDEWEB)

Edwardson, W; Lewis, C W; Slesser, M

1981-04-01

The energy requirements of many novel protein production systems are compared with an examination of the relevant environmental implications of these systems. The prospects for single cell protein, leaf protein, fish farming, fish protein concentrate, algal cultivation, and hydroponic plant growth systems are investigated. Single cell protein from carbohydrate substrates, algal protein, and fish protein seem to hold much promise, as they are technologically feasible for near-term implementation and do not require major energy inputs. (2 diagrams, 1 graph, 47 references, 6 tables)

Diffusion-controlled interface kinetics-inclusive system-theoretic propagation models for molecular communication systems

Science.gov (United States)

Chude-Okonkwo, Uche A. K.; Malekian, Reza; Maharaj, B. T.

2015-12-01

Inspired by biological systems, molecular communication has been proposed as a new communication paradigm that uses biochemical signals to transfer information from one nano device to another over a short distance. The biochemical nature of the information transfer process implies that for molecular communication purposes, the development of molecular channel models should take into consideration diffusion phenomenon as well as the physical/biochemical kinetic possibilities of the process. The physical and biochemical kinetics arise at the interfaces between the diffusion channel and the transmitter/receiver units. These interfaces are herein termed molecular antennas. In this paper, we present the deterministic propagation model of the molecular communication between an immobilized nanotransmitter and nanoreceiver, where the emission and reception kinetics are taken into consideration. Specifically, we derived closed-form system-theoretic models and expressions for configurations that represent different communication systems based on the type of molecular antennas used. The antennas considered are the nanopores at the transmitter and the surface receptor proteins/enzymes at the receiver. The developed models are simulated to show the influence of parameters such as the receiver radius, surface receptor protein/enzyme concentration, and various reaction rate constants. Results show that the effective receiver surface area and the rate constants are important to the system's output performance. Assuming high rate of catalysis, the analysis of the frequency behavior of the developed propagation channels in the form of transfer functions shows significant difference introduce by the inclusion of the molecular antennas into the diffusion-only model. It is also shown that for t > > 0 and with the information molecules' concentration greater than the Michaelis-Menten kinetic constant of the systems, the inclusion of surface receptors proteins and enzymes in the models

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.

DockQ: A Quality Measure for Protein-Protein Docking Models

Science.gov (United States)

Basu, Sankar

2016-01-01

The state-of-the-art to assess the structural quality of docking models is currently based on three related yet independent quality measures: Fnat, LRMS, and iRMS as proposed and standardized by CAPRI. These quality measures quantify different aspects of the quality of a particular docking model and need to be viewed together to reveal the true quality, e.g. a model with relatively poor LRMS (>10Å) might still qualify as 'acceptable' with a descent Fnat (>0.50) and iRMS (iRMS to a single score in the range [0, 1] that can be used to assess the quality of protein docking models. By using DockQ on CAPRI models it is possible to almost completely reproduce the original CAPRI classification into Incorrect, Acceptable, Medium and High quality. An average PPV of 94% at 90% Recall demonstrating that there is no need to apply predefined ad-hoc cutoffs to classify docking models. Since DockQ recapitulates the CAPRI classification almost perfectly, it can be viewed as a higher resolution version of the CAPRI classification, making it possible to estimate model quality in a more quantitative way using Z-scores or sum of top ranked models, which has been so valuable for the CASP community. The possibility to directly correlate a quality measure to a scoring function has been crucial for the development of scoring functions for protein structure prediction, and DockQ should be useful in a similar development in the protein docking field. DockQ is available at http://github.com/bjornwallner/DockQ/ PMID:27560519

In-cell protease assay systems based on trans-localizing molecular beacon proteins using HCV protease as a model system.

Directory of Open Access Journals (Sweden)

Jeong Hee Kim

Full Text Available This study describes a sensitive in-cell protease detection system that enables direct fluorescence detection of a target protease and its inhibition inside living cells. This live-cell imaging system provides a fluorescent molecular beacon protein comprised of an intracellular translocation signal sequence, a protease-specific cleavage sequence, and a fluorescent tag sequence(s. The molecular beacon protein is designed to change its intracellular localization upon cleavage by a target protease, i.e., from the cytosol to a subcellular organelle or from a subcellular organelle to the cytosol. Protease activity can be monitored at the single cell level, and accordingly the entire cell population expressing the protease can be accurately enumerated. The clear cellular change in fluorescence pattern makes this system an ideal tool for various life science and drug discovery research, including high throughput and high content screening applications.

Quantification of Protein Hydration, Glass Transitions, and Structural Relaxations of Aqueous Protein and Carbohydrate-Protein Systems.

Science.gov (United States)

Roos, Yrjö H; Potes, Naritchaya

2015-06-11

Water distribution and miscibility of carbohydrate and protein components in biological materials and their structural contributions in concentrated solids are poorly understood. In the present study, structural relaxations and a glass transition of protein hydration water and antiplasticization of the hydration water at low temperatures were measured using dynamic mechanical analysis (DMA) and differential scanning calorimetry (DSC) for bovine whey protein (BWP), aqueous glucose-fructose (GF), and their mixture. Thermal transitions of α-lactalbumin and β-lactoglobulin components of BWP included water-content-dependent endothermic but reversible dehydration and denaturation, and exothermic and irreversible aggregation. An α-relaxation assigned to hydration water in BWP appeared at water-content-dependent temperatures and increased to over the range of 150-200 K at decreasing water content and in the presence of GF. Two separate glass transitions and individual fractions of unfrozen water of ternary GF-BWP-water systems contributed to uncoupled α-relaxations, suggesting different roles of protein hydration water and carbohydrate vitrification in concentrated solids during freezing and dehydration. Hydration water in the BWP fraction of GF-BWP systems was derived from equilibrium water sorption and glass transition data of the GF fraction, which gave a significant universal method to quantify (i) protein hydration water and (ii) the unfrozen water in protein-carbohydrate systems for such applications as cryopreservation, freezing, lyophilization, and dehydration of biological materials. A ternary supplemented phase diagram (state diagram) established for the GF-BWP-water system can be used for the analysis of the water distribution across carbohydrate and protein components in such applications.

Bioluminescence resonance energy transfer system for measuring dynamic protein-protein interactions in bacteria.

Science.gov (United States)

Cui, Boyu; Wang, Yao; Song, Yunhong; Wang, Tietao; Li, Changfu; Wei, Yahong; Luo, Zhao-Qing; Shen, Xihui

2014-05-20

Protein-protein interactions are important for virtually every biological process, and a number of elegant approaches have been designed to detect and evaluate such interactions. However, few of these methods allow the detection of dynamic and real-time protein-protein interactions in bacteria. Here we describe a bioluminescence resonance energy transfer (BRET) system based on the bacterial luciferase LuxAB. We found that enhanced yellow fluorescent protein (eYFP) accepts the emission from LuxAB and emits yellow fluorescence. Importantly, BRET occurred when LuxAB and eYFP were fused, respectively, to the interacting protein pair FlgM and FliA. Furthermore, we observed sirolimus (i.e., rapamycin)-inducible interactions between FRB and FKBP12 and a dose-dependent abolishment of such interactions by FK506, the ligand of FKBP12. Using this system, we showed that osmotic stress or low pH efficiently induced multimerization of the regulatory protein OmpR and that the multimerization induced by low pH can be reversed by a neutralizing agent, further indicating the usefulness of this system in the measurement of dynamic interactions. This method can be adapted to analyze dynamic protein-protein interactions and the importance of such interactions in bacterial processes such as development and pathogenicity. Real-time measurement of protein-protein interactions in prokaryotes is highly desirable for determining the roles of protein complex in the development or virulence of bacteria, but methods that allow such measurement are not available. Here we describe the development of a bioluminescence resonance energy transfer (BRET) technology that meets this need. The use of endogenous excitation light in this strategy circumvents the requirement for the sophisticated instrument demanded by standard fluorescence resonance energy transfer (FRET). Furthermore, because the LuxAB substrate decanal is membrane permeable, the assay can be performed without lysing the bacterial cells

Protein instability and immunogenicity: roadblocks to clinical application of injectable protein delivery systems for sustained release.

Science.gov (United States)

Jiskoot, Wim; Randolph, Theodore W; Volkin, David B; Middaugh, C Russell; Schöneich, Christian; Winter, Gerhard; Friess, Wolfgang; Crommelin, Daan J A; Carpenter, John F

2012-03-01

Protein instability and immunogenicity are two main roadblocks to the clinical success of novel protein drug delivery systems. In this commentary, we discuss the need for more extensive analytical characterization in relation to concerns about protein instability in injectable drug delivery systems for sustained release. We then will briefly address immunogenicity concerns and outline current best practices for using state-of-the-art analytical assays to monitor protein stability for both conventional and novel therapeutic protein dosage forms. Next, we provide a summary of the stresses on proteins arising during preparation of drug delivery systems and subsequent in vivo release. We note the challenges and difficulties in achieving the absolute requirement of quantitatively assessing the degradation of protein molecules in a drug delivery system. We describe the potential roles for academic research in further improving protein stability and developing new analytical technologies to detect protein degradation byproducts in novel drug delivery systems. Finally, we provide recommendations for the appropriate approaches to formulation design and assay development to ensure that stable, minimally immunogenic formulations of therapeutic proteins are created. These approaches should help to increase the probability that novel drug delivery systems for sustained protein release will become more readily available as effective therapeutic agents to treat and benefit patients. Copyright © 2011 Wiley Periodicals, Inc.

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.

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.

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.

Improved feed protein fractionation schemes for formulating rations with the cornell net carbohydrate and protein system.

Science.gov (United States)

Lanzas, C; Broderick, G A; Fox, D G

2008-12-01

Adequate predictions of rumen-degradable protein (RDP) and rumen-undegradable protein (RUP) supplies are necessary to optimize performance while minimizing losses of excess nitrogen (N). The objectives of this study were to evaluate the original Cornell Net Carbohydrate Protein System (CNCPS) protein fractionation scheme and to develop and evaluate alternatives designed to improve its adequacy in predicting RDP and RUP. The CNCPS version 5 fractionates CP into 5 fractions based on solubility in protein precipitant agents, buffers, and detergent solutions: A represents the soluble nonprotein N, B1 is the soluble true protein, B2 represents protein with intermediate rates of degradation, B3 is the CP insoluble in neutral detergent solution but soluble in acid detergent solution, and C is the unavailable N. Model predictions were evaluated with studies that measured N flow data at the omasum. The N fractionation scheme in version 5 of the CNCPS explained 78% of the variation in RDP with a root mean square prediction error (RMSPE) of 275 g/d, and 51% of the RUP variation with RMSPE of 248 g/d. Neutral detergent insoluble CP flows were overpredicted with a mean bias of 128 g/d (40% of the observed mean). The greatest improvements in the accuracy of RDP and RUP predictions were obtained with the following 2 alternative schemes. Alternative 1 used the inhibitory in vitro system to measure the fractional rate of degradation for the insoluble protein fraction in which A = nonprotein N, B1 = true soluble protein, B2 = insoluble protein, C = unavailable protein (RDP: R(2) = 0.84 and RMSPE = 167 g/d; RUP: R(2) = 0.61 and RMSPE = 209 g/d), whereas alternative 2 redefined A and B1 fractions as the non-amino-N and amino-N in the soluble fraction respectively (RDP: R(2) = 0.79 with RMSPE = 195 g/d and RUP: R(2) = 0.54 with RMSPE = 225 g/d). We concluded that implementing alternative 1 or 2 will improve the accuracy of predicting RDP and RUP within the CNCPS framework.

Thermodynamics of protein folding using a modified Wako-Saitô-Muñoz-Eaton model.

Science.gov (United States)

Tsai, Min-Yeh; Yuan, Jian-Min; Teranishi, Yoshiaki; Lin, Sheng Hsien

2012-09-01

Herein, we propose a modified version of the Wako-Saitô-Muñoz-Eaton (WSME) model. The proposed model introduces an empirical temperature parameter for the hypothetical structural units (i.e., foldons) in proteins to include site-dependent thermodynamic behavior. The thermodynamics for both our proposed model and the original WSME model were investigated. For a system with beta-hairpin topology, a mathematical treatment (contact-pair treatment) to facilitate the calculation of its partition function was developed. The results show that the proposed model provides better insight into the site-dependent thermodynamic behavior of the system, compared with the original WSME model. From this site-dependent point of view, the relationship between probe-dependent experimental results and model's thermodynamic predictions can be explained. The model allows for suggesting a general principle to identify foldon behavior. We also find that the backbone hydrogen bonds may play a role of structural constraints in modulating the cooperative system. Thus, our study may contribute to the understanding of the fundamental principles for the thermodynamics of protein folding.

Slc7a11 (xCT) protein expression is not altered in the depressed brain and system xc- deficiency does not affect depression-associated behaviour in the corticosterone mouse model.

Science.gov (United States)

Demuyser, Thomas; Deneyer, Lauren; Bentea, Eduard; Albertini, Giulia; Femenia, Teresa; Walrave, Laura; Sato, Hideyo; Danbolt, Niels C; De Bundel, Dimitri; Michotte, Alex; Lindskog, Maria; Massie, Ann; Smolders, Ilse

2017-09-27

The cystine/glutamate antiporter (system xc-) is believed to contribute to nonvesicular glutamate release from glial cells in various brain areas. Although recent investigations implicate system xc- in mood disorders, unambiguous evidence has not yet been established. Therefore, we evaluated the possible role of system xc- in the depressive state. We conducted a protein expression analysis of the specific subunit of system xc- (xCT) in brain regions of the corticosterone mouse model, Flinders Sensitive Line rat model and post-mortem tissue of depressed patients. We next subjected system xc- deficient mice to the corticosterone model and analysed their behaviour in several tests. Lastly, we subjected additional cohorts of xCT-deficient and wild-type mice to N-acetylcysteine treatment to unveil whether the previously reported antidepressant-like effects are dependent upon system xc-. We did not detect any changes in xCT expression levels in the animal models or patients compared to proper controls. Furthermore, loss of system xc- had no effect on depression- and anxiety-like behaviour. Finally, the antidepressant-like effects of N-acetylcysteine are not mediated via system xc-. xCT protein expression is not altered in the depressed brain and system xc- deficiency does not affect depression-associated behaviour in the corticosterone mouse model.

Green Fluorescent Protein as a Model for Protein Crystal Growth Studies

Science.gov (United States)

Agena, Sabine; Smith, Lori; Karr, Laurel; Pusey, Marc

1998-01-01

Green fluorescent protein (GFP) from jellyfish Aequorea Victoria has become a popular marker for e.g. mutagenesis work. Its fluorescent property, which originates from a chromophore located in the center of the molecule, makes it widely applicable as a research too]. GFP clones have been produced with a variety of spectral properties, such as blue and yellow emitting species. The protein is a single chain of molecular weight 27 kDa and its structure has been determined at 1.9 Angstrom resolution. The combination of GFP's fluorescent property, the knowledge of its several crystallization conditions, and its increasing use in biophysical and biochemical studies, all led us to consider it as a model material for macromolecular crystal growth studies. Initial preparations of GFP were from E.coli with yields of approximately 5 mg/L of culture media. Current yields are now in the 50 - 120 mg/L range, and we hope to further increase this by expression of the GFP gene in the Pichia system. The results of these efforts and of preliminary crystal growth studies will be presented.

Improved Protein Arrays for Quantitative Systems Analysis of the Dynamics of Signaling Pathway Interactions

Energy Technology Data Exchange (ETDEWEB)

Yang, Chin-Rang [National Inst. of Health (NIH), Bethesda, MD (United States). National Heart, Lung and Blood Inst.

2013-12-11

Astronauts and workers in nuclear plants who repeatedly exposed to low doses of ionizing radiation (IR, <10 cGy) are likely to incur specific changes in signal transduction and gene expression in various tissues of their body. Remarkable advances in high throughput genomics and proteomics technologies enable researchers to broaden their focus from examining single gene/protein kinetics to better understanding global gene/protein expression profiling and biological pathway analyses, namely Systems Biology. An ultimate goal of systems biology is to develop dynamic mathematical models of interacting biological systems capable of simulating living systems in a computer. This Glue Grant is to complement Dr. Boothman’s existing DOE grant (No. DE-FG02-06ER64186) entitled “The IGF1/IGF-1R-MAPK-Secretory Clusterin (sCLU) Pathway: Mediator of a Low Dose IR-Inducible Bystander Effect” to develop sensitive and quantitative proteomic technology that suitable for low dose radiobiology researches. An improved version of quantitative protein array platform utilizing linear Quantum dot signaling for systematically measuring protein levels and phosphorylation states for systems biology modeling is presented. The signals are amplified by a confocal laser Quantum dot scanner resulting in ~1000-fold more sensitivity than traditional Western blots and show the good linearity that is impossible for the signals of HRP-amplification. Therefore this improved protein array technology is suitable to detect weak responses of low dose radiation. Software is developed to facilitate the quantitative readout of signaling network activities. Kinetics of EGFRvIII mutant signaling was analyzed to quantify cross-talks between EGFR and other signaling pathways.

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.

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.

Modeling of human factor Va inactivation by activated protein C

Directory of Open Access Journals (Sweden)

Bravo Maria

2012-05-01

Full Text Available Abstract Background Because understanding of the inventory, connectivity and dynamics of the components characterizing the process of coagulation is relatively mature, it has become an attractive target for physiochemical modeling. Such models can potentially improve the design of therapeutics. The prothrombinase complex (composed of the protease factor (FXa and its cofactor FVa plays a central role in this network as the main producer of thrombin, which catalyses both the activation of platelets and the conversion of fibrinogen to fibrin, the main substances of a clot. A key negative feedback loop that prevents clot propagation beyond the site of injury is the thrombin-dependent generation of activated protein C (APC, an enzyme that inactivates FVa, thus neutralizing the prothrombinase complex. APC inactivation of FVa is complex, involving the production of partially active intermediates and “protection” of FVa from APC by both FXa and prothrombin. An empirically validated mathematical model of this process would be useful in advancing the predictive capacity of comprehensive models of coagulation. Results A model of human APC inactivation of prothrombinase was constructed in a stepwise fashion by analyzing time courses of FVa inactivation in empirical reaction systems with increasing number of interacting components and generating corresponding model constructs of each reaction system. Reaction mechanisms, rate constants and equilibrium constants informing these model constructs were initially derived from various research groups reporting on APC inactivation of FVa in isolation, or in the presence of FXa or prothrombin. Model predictions were assessed against empirical data measuring the appearance and disappearance of multiple FVa degradation intermediates as well as prothrombinase activity changes, with plasma proteins derived from multiple preparations. Our work integrates previously published findings and through the cooperative

Escherichia coli Protein Expression System for Acetylcholine Binding Proteins (AChBPs.

Directory of Open Access Journals (Sweden)

Nikita Abraham

Full Text Available Nicotinic acetylcholine receptors (nAChR are ligand gated ion channels, identified as therapeutic targets for a range of human diseases. Drug design for nAChR related disorders is increasingly using structure-based approaches. Many of these structural insights for therapeutic lead development have been obtained from co-crystal structures of nAChR agonists and antagonists with the acetylcholine binding protein (AChBP. AChBP is a water soluble, structural and functional homolog of the extracellular, ligand-binding domain of nAChRs. Currently, AChBPs are recombinantly expressed in eukaryotic expression systems for structural and biophysical studies. Here, we report the establishment of an Escherichia coli (E. coli expression system that significantly reduces the cost and time of production compared to the existing expression systems. E. coli can efficiently express unglycosylated AChBP for crystallography and makes the expression of isotopically labelled forms feasible for NMR. We used a pHUE vector containing an N-terminal His-tagged ubiquitin fusion protein to facilitate AChBP expression in the soluble fractions, and thus avoid the need to recover protein from inclusion bodies. The purified protein yield obtained from the E. coli expression system is comparable to that obtained from existing AChBP expression systems. E. coli expressed AChBP bound nAChR agonists and antagonists with affinities matching those previously reported. Thus, the E. coli expression system significantly simplifies the expression and purification of functional AChBP for structural and biophysical studies.

[Drosophila melanogaster as a model for studying the function of animal viral proteins].

Science.gov (United States)

Omelianchuk, L V; Iudina, O S

2011-07-01

Studies in which Drosophila melanogaster individuals carrying transgenes of animal viruses were used to analyze the action of animal viral proteins on the cell are reviewed. The data presented suggest that host specificity of viruses is determined by their proteins responsible for the penetration of the virus into the cell, while viral proteins responsible for interactions with the host cell are much less host-specific. Due to this, the model of Drosophila with its developed system of searching for genetic interactions can be used to find intracellular targets for the action of viral proteins of the second group.

MECHANISMS IN ENDOCRINOLOGY: Exogenous insulin does not increase muscle protein synthesis rate when administered systemically: a systematic review.

Science.gov (United States)

Trommelen, Jorn; Groen, Bart B L; Hamer, Henrike M; de Groot, Lisette C P G M; van Loon, Luc J C

2015-07-01

Though it is well appreciated that insulin plays an important role in the regulation of muscle protein metabolism, there is much discrepancy in the literature on the capacity of exogenous insulin administration to increase muscle protein synthesis rates in vivo in humans. To assess whether exogenous insulin administration increases muscle protein synthesis rates in young and older adults. A systematic review of clinical trials was performed and the presence or absence of an increase in muscle protein synthesis rate was reported for each individual study arm. In a stepwise manner, multiple models were constructed that excluded study arms based on the following conditions: model 1, concurrent hyperaminoacidemia; model 2, insulin-induced hypoaminoacidemia; model 3, supraphysiological insulin concentrations; and model 4, older, more insulin resistant, subjects. From the presented data in the current systematic review, we conclude that: i) exogenous insulin and amino acid administration effectively increase muscle protein synthesis, but this effect is attributed to the hyperaminoacidemia; ii) exogenous insulin administered systemically induces hypoaminoacidemia which obviates any insulin-stimulatory effect on muscle protein synthesis; iii) exogenous insulin resulting in supraphysiological insulin levels exceeding 50, 000  pmol/l may effectively augment muscle protein synthesis; iv) exogenous insulin may have a diminished effect on muscle protein synthesis in older adults due to age-related anabolic resistance; and v) exogenous insulin administered systemically does not increase muscle protein synthesis in healthy, young adults. © 2015 European Society of Endocrinology.

Effect of homogenisation in formation of thermally induced aggregates in a non- and low- fat milk model system with microparticulated whey proteins

DEFF Research Database (Denmark)

Celigueta Torres, Isabel; Nieto, Gema; Nylander, Tommy

2017-01-01

in the formation of protein aggregates were studied by polyacrylamide gel electrophoresis and the final complexes visualised by darkfield microscopy. Homogenisation of non-fat milk systems led to partial adsorption of caseins onto microparticles, independently of the type of microparticle. On the contrary...... are responsible for the formation of heat-induced aggregates that influence the texture and sensory characteristics of the final product. The formation of heat-induced complexes was studied in non- and low-fat milk model systems, where microparticulated whey protein (MWP) was used as fat replacer. Five MWP types......, homogenisation of low-fat milk resulted in preferential adsorption of caseins onto fat globules, rather than onto microparticles. Further heating of the milk, led to the formation of heat induced complexes with different sizes and characteristics depending on the type of MWP and the presence or not of fat...

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.

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.

Peptide-tagged proteins in aqueous two-phase systems

OpenAIRE

Nilsson, Anna

2002-01-01

This thesis deals with proteins containing peptide tags for improved partitioning in aqueous two-phase systems. Qualitatively the peptide-tagged protein partitioning could be predicted from peptide data, i.e. partitioning trends found for peptides were also found for the peptide-tagged proteins. However, full effect of the tag as expected from peptide partitioning was not found in the tagged protein. When alkyl-ethylene oxide surfactant was included in a two-polymer system, almost full effect...

Comparative Proteomics Identifies Host Immune System Proteins Affected by Infection with Mycobacterium bovis.

Directory of Open Access Journals (Sweden)

Vladimir López

2016-03-01

Full Text Available Mycobacteria of the Mycobacterium tuberculosis complex (MTBC greatly impact human and animal health worldwide. The mycobacterial life cycle is complex, and the mechanisms resulting in pathogen infection and survival in host cells are not fully understood. Eurasian wild boar (Sus scrofa are natural reservoir hosts for MTBC and a model for mycobacterial infection and tuberculosis (TB. In the wild boar TB model, mycobacterial infection affects the expression of innate and adaptive immune response genes in mandibular lymph nodes and oropharyngeal tonsils, and biomarkers have been proposed as correlates with resistance to natural infection. However, the mechanisms used by mycobacteria to manipulate host immune response are not fully characterized. Our hypothesis is that the immune system proteins under-represented in infected animals, when compared to uninfected controls, are used by mycobacteria to guarantee pathogen infection and transmission. To address this hypothesis, a comparative proteomics approach was used to compare host response between uninfected (TB- and M. bovis-infected young (TB+ and adult animals with different infection status [TB lesions localized in the head (TB+ or affecting multiple organs (TB++]. The results identified host immune system proteins that play an important role in host response to mycobacteria. Calcium binding protein A9, Heme peroxidase, Lactotransferrin, Cathelicidin and Peptidoglycan-recognition protein were under-represented in TB+ animals when compared to uninfected TB- controls, but protein levels were higher as infection progressed in TB++ animals when compared to TB- and/or TB+ adult wild boar. MHCI was the only protein over-represented in TB+ adult wild boar when compared to uninfected TB- controls. The results reported here suggest that M. bovis manipulates host immune response by reducing the production of immune system proteins. However, as infection progresses, wild boar immune response recovers to

Comparative Proteomics Identifies Host Immune System Proteins Affected by Infection with Mycobacterium bovis.

Science.gov (United States)

López, Vladimir; Villar, Margarita; Queirós, João; Vicente, Joaquín; Mateos-Hernández, Lourdes; Díez-Delgado, Iratxe; Contreras, Marinela; Alves, Paulo C; Alberdi, Pilar; Gortázar, Christian; de la Fuente, José

2016-03-01

Mycobacteria of the Mycobacterium tuberculosis complex (MTBC) greatly impact human and animal health worldwide. The mycobacterial life cycle is complex, and the mechanisms resulting in pathogen infection and survival in host cells are not fully understood. Eurasian wild boar (Sus scrofa) are natural reservoir hosts for MTBC and a model for mycobacterial infection and tuberculosis (TB). In the wild boar TB model, mycobacterial infection affects the expression of innate and adaptive immune response genes in mandibular lymph nodes and oropharyngeal tonsils, and biomarkers have been proposed as correlates with resistance to natural infection. However, the mechanisms used by mycobacteria to manipulate host immune response are not fully characterized. Our hypothesis is that the immune system proteins under-represented in infected animals, when compared to uninfected controls, are used by mycobacteria to guarantee pathogen infection and transmission. To address this hypothesis, a comparative proteomics approach was used to compare host response between uninfected (TB-) and M. bovis-infected young (TB+) and adult animals with different infection status [TB lesions localized in the head (TB+) or affecting multiple organs (TB++)]. The results identified host immune system proteins that play an important role in host response to mycobacteria. Calcium binding protein A9, Heme peroxidase, Lactotransferrin, Cathelicidin and Peptidoglycan-recognition protein were under-represented in TB+ animals when compared to uninfected TB- controls, but protein levels were higher as infection progressed in TB++ animals when compared to TB- and/or TB+ adult wild boar. MHCI was the only protein over-represented in TB+ adult wild boar when compared to uninfected TB- controls. The results reported here suggest that M. bovis manipulates host immune response by reducing the production of immune system proteins. However, as infection progresses, wild boar immune response recovers to limit pathogen

Enzyme-Triggered Defined Protein Nanoarrays: Efficient Light-Harvesting Systems to Mimic Chloroplasts.

Science.gov (United States)

Zhao, Linlu; Zou, Haoyang; Zhang, Hao; Sun, Hongcheng; Wang, Tingting; Pan, Tiezheng; Li, Xiumei; Bai, Yushi; Qiao, Shanpeng; Luo, Quan; Xu, Jiayun; Hou, Chunxi; Liu, Junqiu

2017-01-24

The elegance and efficiency by which chloroplasts harvest solar energy and conduct energy transfer have been a source of inspiration for chemists to mimic such process. However, precise manipulation to obtain orderly arranged antenna chromophores in constructing artificial chloroplast mimics was a great challenge, especially from the structural similarity and bioaffinity standpoints. Here we reported a design strategy that combined covalent and noncovalent interactions to prepare a protein-based light-harvesting system to mimic chloroplasts. Cricoid stable protein one (SP1) was utilized as a building block model. Under enzyme-triggered covalent protein assembly, mutant SP1 with tyrosine (Tyr) residues at the designated sites can couple together to form nanostructures. Through controlling the Tyr sites on the protein surface, we can manipulate the assembly orientation to respectively generate 1D nanotubes and 2D nanosheets. The excellent stability endowed the self-assembled protein architectures with promising applications. We further integrated quantum dots (QDs) possessing optical and electronic properties with the 2D nanosheets to fabricate chloroplast mimics. By attaching different sized QDs as donor and acceptor chromophores to the negatively charged surface of SP1-based protein nanosheets via electrostatic interactions, we successfully developed an artificial light-harvesting system. The assembled protein nanosheets structurally resembled the natural thylakoids, and the QDs can achieve pronounced FRET phenomenon just like the chlorophylls. Therefore, the coassembled system was meaningful to explore the photosynthetic process in vitro, as it was designed to mimic the natural chloroplast.

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

Modelling Transcapillary Transport of Fluid and Proteins in Hemodialysis Patients.

Directory of Open Access Journals (Sweden)

Mauro Pietribiasi

Full Text Available The kinetics of protein transport to and from the vascular compartment play a major role in the determination of fluid balance and plasma refilling during hemodialysis (HD sessions. In this study we propose a whole-body mathematical model describing water and protein shifts across the capillary membrane during HD and compare its output to clinical data while evaluating the impact of choosing specific values for selected parameters.The model follows a two-compartment structure (vascular and interstitial space and is based on balance equations of protein mass and water volume in each compartment. The capillary membrane was described according to the three-pore theory. Two transport parameters, the fractional contribution of large pores (αLP and the total hydraulic conductivity (LpS of the capillary membrane, were estimated from patient data. Changes in the intensity and direction of individual fluid and solute flows through each part of the transport system were analyzed in relation to the choice of different values of small pores radius and fractional conductivity, lymphatic sensitivity to hydraulic pressure, and steady-state interstitial-to-plasma protein concentration ratio.The estimated values of LpS and αLP were respectively 10.0 ± 8.4 mL/min/mmHg (mean ± standard deviation and 0.062 ± 0.041. The model was able to predict with good accuracy the profiles of plasma volume and serum total protein concentration in most of the patients (average root-mean-square deviation < 2% of the measured value.The applied model provides a mechanistic interpretation of fluid transport processes induced by ultrafiltration during HD, using a minimum of tuned parameters and assumptions. The simulated values of individual flows through each kind of pore and lymphatic absorption rate yielded by the model may suggest answers to unsolved questions on the relative impact of these not-measurable quantities on total vascular refilling and fluid balance.

Improved contact prediction in proteins: Using pseudolikelihoods to infer Potts models

Science.gov (United States)

Ekeberg, Magnus; Lövkvist, Cecilia; Lan, Yueheng; Weigt, Martin; Aurell, Erik

2013-01-01

Spatially proximate amino acids in a protein tend to coevolve. A protein's three-dimensional (3D) structure hence leaves an echo of correlations in the evolutionary record. Reverse engineering 3D structures from such correlations is an open problem in structural biology, pursued with increasing vigor as more and more protein sequences continue to fill the data banks. Within this task lies a statistical inference problem, rooted in the following: correlation between two sites in a protein sequence can arise from firsthand interaction but can also be network-propagated via intermediate sites; observed correlation is not enough to guarantee proximity. To separate direct from indirect interactions is an instance of the general problem of inverse statistical mechanics, where the task is to learn model parameters (fields, couplings) from observables (magnetizations, correlations, samples) in large systems. In the context of protein sequences, the approach has been referred to as direct-coupling analysis. Here we show that the pseudolikelihood method, applied to 21-state Potts models describing the statistical properties of families of evolutionarily related proteins, significantly outperforms existing approaches to the direct-coupling analysis, the latter being based on standard mean-field techniques. This improved performance also relies on a modified score for the coupling strength. The results are verified using known crystal structures of specific sequence instances of various protein families. Code implementing the new method can be found at http://plmdca.csc.kth.se/.

Systemic and oral immunogenicity of hemagglutinin protein of rinderpest virus expressed by transgenic peanut plants in a mouse model

International Nuclear Information System (INIS)

Khandelwal, Abha; Renukaradhya, G.J.; Rajasekhar, M.; Sita, G. Lakshmi; Shaila, M.S.

2004-01-01

Rinderpest causes a devastating disease, often fatal, in wild and domestic ruminants. It has been eradicated successfully using a live, attenuated vaccine from most part of the world leaving a few foci of disease in parts of Africa, the Middle East, and South Asia. We have developed transgenic peanut (Arachis hypogaea L.) plants expressing hemagglutinin (H) protein of rinderpest virus (RPV), which is antigenically authentic. In this work, we have evaluated the immunogenicity of peanut-expressed H protein using mouse model, administered parenterally as well as orally. Intraperitoneal immunization of mice with the transgenic peanut extract elicited antibody response specific to H. These antibodies neutralized virus infectivity in vitro. Oral immunization of mice with transgenic peanut induced H-specific serum IgG and IgA antibodies. The systemic and oral immunogenicity of plant-derived H in absence of any adjuvant indicates the potential of edible vaccine for rinderpest

Protein phosphorylation systems in postmortem human brain

International Nuclear Information System (INIS)

Walaas, S.I.; Perdahl-Wallace, E.; Winblad, B.; Greengard, P.

1989-01-01

Protein phosphorylation systems regulated by cyclic adenosine 3',5'-monophosphate (cyclic AMP), or calcium in conjunction with calmodulin or phospholipid/diacylglycerol, have been studied by phosphorylation in vitro of particulate and soluble fractions from human postmortem brain samples. One-dimensional or two-dimensional gel electrophoretic protein separations were used for analysis. Protein phosphorylation catalyzed by cyclic AMP-dependent protein kinase was found to be highly active in both particulate and soluble preparations throughout the human CNS, with groups of both widely distributed and region-specific substrates being observed in different brain nuclei. Dopamine-innervated parts of the basal ganglia and cerebral cortex contained the phosphoproteins previously observed in rodent basal ganglia. In contrast, calcium/phospholipid-dependent and calcium/calmodulin-dependent protein phosphorylation systems were less prominent in human postmortem brain than in rodent brain, and only a few widely distributed substrates for these protein kinases were found. Protein staining indicated that postmortem proteolysis, particularly of high-molecular-mass proteins, was prominent in deeply located, subcortical regions in the human brain. Our results indicate that it is feasible to use human postmortem brain samples, when obtained under carefully controlled conditions, for qualitative studies on brain protein phosphorylation. Such studies should be of value in studies on human neurological and/or psychiatric disorders

Systemic release of cytokines and heat shock proteins in porcine models of polytrauma and hemorrhage

Science.gov (United States)

Baker, Todd A.; Romero, Jacqueline; Bach, Harold H.; Strom, Joel A.; Gamelli, Richard L.; Majetschak, Matthias

2011-01-01

Objective To define systemic release kinetics of a panel of cytokines and heat shock proteins (HSP) in porcine polytrauma/hemorrhage models and to evaluate whether they could be useful as early trauma biomarkers. Design and Setting Prospective study in a research laboratory. Subjects Twenty-one Yorkshire pigs. Measurements and Main Results Pigs underwent polytrauma (femur fractures/lung contusion, P), hemorrhage (mean arterial pressure 25-30mmHg, H), polytrauma plus hemorrhage (P/H) or sham procedure (S). Plasma was obtained at baseline, in 5-15min intervals during a 60min shock period without intervention and in 60-120min intervals during fluid resuscitation for up to 300min. Plasma was assayed for IL-1β, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12/IL-23p40, IL-13, IL-17, IL-18, IFNγ, TGFβ, TNFα, HSP40, HSP70 and HSP90 by ELISA. All animals after S, P and H survived (n=5/group). Three of six animals after P/H died. IL-10 increased during shock after P and this increase was attenuated after H. TNFα increased during the shock period after P, H and also after S. P/H abolished the systemic IL-10 and TNFα release and resulted in 20-30% increased levels of IL-6 during shock. As fluid resuscitation was initiated TNFα and IL-10 levels decreased after P, H and P/H, HSP 70 increased after P, IL-6 levels remained elevated after P/H and also increased after P and S. Conclusions Differential regulation of the systemic cytokine release after polytrauma and/or hemorrhage, in combination with the effects of resuscitation, can explain the variability and inconsistent association of systemic cytokine/HSP levels with clinical variables in trauma patients. Insults of major severity (P/H) partially suppress the systemic inflammatory response. The plasma concentrations of the measured cytokines/HSPs do not reflect injury severity or physiological changes in porcine trauma models and are unlikely to be able to serve as useful trauma biomarkers in patients. PMID:21983369

Essential amino acid enriched high-protein enteral nutrition modulates insulin-like growth factor-1 system function in a rat model of trauma-hemorrhagic shock.

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Xianfeng Xia

Full Text Available Nutrition support for critically ill patients supplemented with additional modular protein may promote skeletal muscle protein anabolism in addition to counteracting acute nitrogen loss. The present study was designed to investigate whether the essential amino acid (EAA enriched high-protein enteral nutrition (EN modulates the insulin-like growth factor-1 (IGF-1 system and activates the mammalian target of rapamycin (mTOR anabolic signaling pathway in a trauma-hemorrhagic shock (T-HS rat model.Male Sprague-Dawley rats (n = 90, 278.18 ± 0.94 g were randomly assigned to 5 groups: (1 normal control, (2 pair-fed, (3 T-HS, (4 T-HS and standard EN, and (5 T-HS and EAA enriched high-protein EN. Six animals from each group were harvested on days 2, 4, and 6 for serum, gastrocnemius, soleus, and extensor digitorum longus sample collection. T-HS significantly reduced muscle mass. Nutrition support maintained muscle mass, especially the EAA enriched high-protein EN. Meanwhile, a pronounced derangement in IGF-1-IGFBPs axis as well as impaired mTOR transduction was observed in the T-HS group. Compared with animals receiving standard EN, those receiving EAA enriched high-protein EN presented 18% higher serum free IGF-1 levels following 3 days of nutrition support and 22% higher after 5 days. These changes were consistent with the concomitant elevation in serum insulin and reduction in corticosterone levels. In addition, phosphorylations of downstream anabolic signaling effectors - including protein kinase B, mTOR, and ribosomal protein S6 kinase1 - increased significantly in rats receiving EAA enriched high-protein EN.Our findings firstly demonstrate the beneficial effect of EAA enriched high-protein EN on the metabolic modulation of skeletal muscle protein anabolism by regulating the IGF-1 system and downstream anabolic signaling transduction.

Protein Folding: Search for Basic Physical Models

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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.

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.

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.

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...

Complex oscillatory behaviour in a delayed protein cross talk model with periodic forcing

International Nuclear Information System (INIS)

Nikolov, Svetoslav

2009-01-01

The purpose of this paper is to examine the effects of periodic forcing on the time delay protein cross talk model behaviour. We assume periodic variation for the plasma membrane permeability. The dynamic behaviour of the system is simulated and bifurcation diagrams are obtained for different parameters. The results show that periodic forcing can very easily give rise to complex dynamics, including a period-doubling cascade, chaos, quasi-periodic oscillating, and periodic windows. Finally, we calculate the maximal Lyapunov exponent in the regions of the parameter space where chaotic motion of delayed protein cross talk model with periodic forcing exists.

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.

Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

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Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

2015-11-01

Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases.

Effect of homogenisation in formation of thermally induced aggregates in a non- and low- fat milk model system with microparticulated whey proteins.

Science.gov (United States)

Torres, Isabel Celigueta; Nieto, Gema; Nylander, Tommy; Simonsen, Adam Cohen; Tolkach, Alexander; Ipsen, Richard

2017-05-01

The objective of the research presented in this paper was to investigate how different characteristics of whey protein microparticles (MWP) added to milk as fat replacers influence intermolecular interactions occurring with other milk proteins during homogenisation and heating. These interactions are responsible for the formation of heat-induced aggregates that influence the texture and sensory characteristics of the final product. The formation of heat-induced complexes was studied in non- and low-fat milk model systems, where microparticulated whey protein (MWP) was used as fat replacer. Five MWP types with different particle characteristics were utilised and three heat treatments used: 85 °C for 15 min, 90 °C for 5 min and 95 °C for 2 min. Surface characteristics of the protein aggregates were expressed as the number of available thiol groups and the surface net charge. Intermolecular interactions involved in the formation of protein aggregates were studied by polyacrylamide gel electrophoresis and the final complexes visualised by darkfield microscopy. Homogenisation of non-fat milk systems led to partial adsorption of caseins onto microparticles, independently of the type of microparticle. On the contrary, homogenisation of low-fat milk resulted in preferential adsorption of caseins onto fat globules, rather than onto microparticles. Further heating of the milk, led to the formation of heat induced complexes with different sizes and characteristics depending on the type of MWP and the presence or not of fat. The results highlight the importance of controlling homogenisation and heat processing in yoghurt manufacture in order to induce desired changes in the surface reactivity of the microparticles and thereby promote effective protein interactions.

Probing the role of interfacial waters in protein-DNA recognition using a hybrid implicit/explicit solvation model

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Li, Shen; Bradley, Philip

2013-01-01

When proteins bind to their DNA target sites, ordered water molecules are often present at the protein-DNA interface bridging protein and DNA through hydrogen bonds. What is the role of these ordered interfacial waters? Are they important determinants of the specificity of DNA sequence recognition, or do they act in binding in a primarily non-specific manner, by improving packing of the interface, shielding unfavorable electrostatic interactions, and solvating unsatisfied polar groups that are inaccessible to bulk solvent? When modeling details of structure and binding preferences, can fully implicit solvent models be fruitfully applied to protein-DNA interfaces, or must the individualistic properties of these interfacial waters be accounted for? To address these questions, we have developed a hybrid implicit/explicit solvation model that specifically accounts for the locations and orientations of small numbers of DNA-bound water molecules while treating the majority of the solvent implicitly. Comparing the performance of this model to its fully implicit counterpart, we find that explicit treatment of interfacial waters results in a modest but significant improvement in protein sidechain placement and DNA sequence recovery. Base-by-base comparison of the performance of the two models highlights DNA sequence positions whose recognition may be dependent on interfacial water. Our study offers large-scale statistical evidence for the role of ordered water for protein DNA recognition, together with detailed examination of several well-characterized systems. In addition, our approach provides a template for modeling explicit water molecules at interfaces that should be extensible to other systems. PMID:23444044

Systemic GLIPR1-ΔTM protein as a novel therapeutic approach for prostate cancer.

Science.gov (United States)

Karantanos, Theodoros; Tanimoto, Ryuta; Edamura, Kohei; Hirayama, Takahiro; Yang, Guang; Golstov, Alexei A; Wang, Jianxiang; Kurosaka, Shinji; Park, Sanghee; Thompson, Timothy C

2014-04-15

GLIPR1 is a p53 target gene known to be downregulated in prostate cancer, and increased endogenous GLIPR1 expression has been associated with increased production of reactive oxygen species, increased apoptosis, decreased c-Myc protein levels and increased cell cycle arrest. Recently, we found that upregulation of GLIPR1 in prostate cancer cells increases mitotic catastrophe through interaction with heat shock cognate protein 70 (Hsc70) and downregulation of Aurora kinase A and TPX2. In this study, we evaluated the mechanisms of recombinant GLIPR1 protein (glioma pathogenesis-related protein 1-transmembrane domain deleted [GLIPR1-ΔTM]) uptake by prostate cancer cells and the efficacy of systemic GLIPR1-ΔTM administration in a prostate cancer xenograft mouse model. GLIPR1-ΔTM was selectively internalized by prostate cancer cells, leading to increased apoptosis through reactive oxygen species production and to decreased c-Myc protein levels. Interestingly, GLIPR1-ΔTM was internalized through clathrin-mediated endocytosis in association with Hsc70. Systemic administration of GLIPR1-ΔTM significantly inhibited VCaP xenograft growth. GLIPR1-ΔTM showed no evidence of toxicity following elimination from mouse models 8 hr after injection. Our results demonstrate that GLIPR1-ΔTM is selectively endocytosed by prostate cancer cells, leading to increased reactive oxygen species production and apoptosis, and that systemic GLIPR1-ΔTM significantly inhibits growth of VCaP xenografts without substantial toxicity. © 2013 UICC.

Systems and methods for modeling and analyzing networks

Science.gov (United States)

Hill, Colin C; Church, Bruce W; McDonagh, Paul D; Khalil, Iya G; Neyarapally, Thomas A; Pitluk, Zachary W

2013-10-29

The systems and methods described herein utilize a probabilistic modeling framework for reverse engineering an ensemble of causal models, from data and then forward simulating the ensemble of models to analyze and predict the behavior of the network. In certain embodiments, the systems and methods described herein include data-driven techniques for developing causal models for biological networks. Causal network models include computational representations of the causal relationships between independent variables such as a compound of interest and dependent variables such as measured DNA alterations, changes in mRNA, protein, and metabolites to phenotypic readouts of efficacy and toxicity.

In silico modeling and experimental evidence of coagulant protein interaction with precursors for nanoparticle functionalization.

Science.gov (United States)

Okoli, Chuka; Sengottaiyan, Selvaraj; Arul Murugan, N; Pavankumar, Asalapuram R; Agren, Hans; Kuttuva Rajarao, Gunaratna

2013-10-01

The design of novel protein-nanoparticle hybrid systems has applications in many fields of science ranging from biomedicine, catalysis, water treatment, etc. The main barrier in devising such tool is lack of adequate information or poor understanding of protein-ligand chemistry. Here, we establish a new strategy based on computational modeling for protein and precursor linkers that can decorate the nanoparticles. Moringa oleifera (MO2.1) seed protein that has coagulation and antimicrobial properties was used. Superparamagnetic nanoparticles (SPION) with precursor ligands were used for the protein-ligand interaction studies. The molecular docking studies reveal that there are two binding sites, one is located at the core binding site; tetraethoxysilane (TEOS) or 3-aminopropyl trimethoxysilane (APTES) binds to this site while the other one is located at the side chain residues where trisodium citrate (TSC) or Si60 binds to this site. The protein-ligand distance profile analysis explains the differences in functional activity of the decorated SPION. Experimentally, TSC-coated nanoparticles showed higher coagulation activity as compared to TEOS- and APTES-coated SPION. To our knowledge, this is the first report on in vitro experimental data, which endorses the computational modeling studies as a powerful tool to design novel precursors for functionalization of nanomaterials; and develop interface hybrid systems for various applications.

Scoring predictive models using a reduced representation of proteins: model and energy definition.

Science.gov (United States)

Fogolari, Federico; Pieri, Lidia; Dovier, Agostino; Bortolussi, Luca; Giugliarelli, Gilberto; Corazza, Alessandra; Esposito, Gennaro; Viglino, Paolo

2007-03-23

Reduced representations of proteins have been playing a keyrole in the study of protein folding. Many such models are available, with different representation detail. Although the usefulness of many such models for structural bioinformatics applications has been demonstrated in recent years, there are few intermediate resolution models endowed with an energy model capable, for instance, of detecting native or native-like structures among decoy sets. The aim of the present work is to provide a discrete empirical potential for a reduced protein model termed here PC2CA, because it employs a PseudoCovalent structure with only 2 Centers of interactions per Amino acid, suitable for protein model quality assessment. All protein structures in the set top500H have been converted in reduced form. The distribution of pseudobonds, pseudoangle, pseudodihedrals and distances between centers of interactions have been converted into potentials of mean force. A suitable reference distribution has been defined for non-bonded interactions which takes into account excluded volume effects and protein finite size. The correlation between adjacent main chain pseudodihedrals has been converted in an additional energetic term which is able to account for cooperative effects in secondary structure elements. Local energy surface exploration is performed in order to increase the robustness of the energy function. The model and the energy definition proposed have been tested on all the multiple decoys' sets in the Decoys'R'us database. The energetic model is able to recognize, for almost all sets, native-like structures (RMSD less than 2.0 A). These results and those obtained in the blind CASP7 quality assessment experiment suggest that the model compares well with scoring potentials with finer granularity and could be useful for fast exploration of conformational space. Parameters are available at the url: http://www.dstb.uniud.it/~ffogolari/download/.

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.

A multiscale modeling approach for biomolecular systems

Energy Technology Data Exchange (ETDEWEB)

Bowling, Alan, E-mail: bowling@uta.edu; Haghshenas-Jaryani, Mahdi, E-mail: mahdi.haghshenasjaryani@mavs.uta.edu [The University of Texas at Arlington, Department of Mechanical and Aerospace Engineering (United States)

2015-04-15

This paper presents a new multiscale molecular dynamic model for investigating the effects of external interactions, such as contact and impact, during stepping and docking of motor proteins and other biomolecular systems. The model retains the mass properties ensuring that the result satisfies Newton’s second law. This idea is presented using a simple particle model to facilitate discussion of the rigid body model; however, the particle model does provide insights into particle dynamics at the nanoscale. The resulting three-dimensional model predicts a significant decrease in the effect of the random forces associated with Brownian motion. This conclusion runs contrary to the widely accepted notion that the motor protein’s movements are primarily the result of thermal effects. This work focuses on the mechanical aspects of protein locomotion; the effect ATP hydrolysis is estimated as internal forces acting on the mechanical model. In addition, the proposed model can be numerically integrated in a reasonable amount of time. Herein, the differences between the motion predicted by the old and new modeling approaches are compared using a simplified model of myosin V.

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.

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.

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.

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.

Automated Learning of Subcellular Variation among Punctate Protein Patterns and a Generative Model of Their Relation to Microtubules.

Directory of Open Access Journals (Sweden)

Gregory R Johnson

2015-12-01

Full Text Available Characterizing the spatial distribution of proteins directly from microscopy images is a difficult problem with numerous applications in cell biology (e.g. identifying motor-related proteins and clinical research (e.g. identification of cancer biomarkers. Here we describe the design of a system that provides automated analysis of punctate protein patterns in microscope images, including quantification of their relationships to microtubules. We constructed the system using confocal immunofluorescence microscopy images from the Human Protein Atlas project for 11 punctate proteins in three cultured cell lines. These proteins have previously been characterized as being primarily located in punctate structures, but their images had all been annotated by visual examination as being simply "vesicular". We were able to show that these patterns could be distinguished from each other with high accuracy, and we were able to assign to one of these subclasses hundreds of proteins whose subcellular localization had not previously been well defined. In addition to providing these novel annotations, we built a generative approach to modeling of punctate distributions that captures the essential characteristics of the distinct patterns. Such models are expected to be valuable for representing and summarizing each pattern and for constructing systems biology simulations of cell behaviors.

Rapamycin-induced oligomer formation system of FRB-FKBP fusion proteins.

Science.gov (United States)

Inobe, Tomonao; Nukina, Nobuyuki

2016-07-01

Most proteins form larger protein complexes and perform multiple functions in the cell. Thus, artificial regulation of protein complex formation controls the cellular functions that involve protein complexes. Although several artificial dimerization systems have already been used for numerous applications in biomedical research, cellular protein complexes form not only simple dimers but also larger oligomers. In this study, we showed that fusion proteins comprising the induced heterodimer formation proteins FRB and FKBP formed various oligomers upon addition of rapamycin. By adjusting the configuration of fusion proteins, we succeeded in generating an inducible tetramer formation system. Proteins of interest also formed tetramers by fusing to the inducible tetramer formation system, which exhibits its utility in a broad range of biological applications. Copyright © 2015 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Peptide and protein delivery using new drug delivery systems.

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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.

In Silico Characterization and Structural Modeling of Dermacentor andersoni p36 Immunosuppressive Protein

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Martin Omulindi Oyugi

2018-01-01

Full Text Available Ticks cause approximately $17–19 billion economic losses to the livestock industry globally. Development of recombinant antitick vaccine is greatly hindered by insufficient knowledge and understanding of proteins expressed by ticks. Ticks secrete immunosuppressant proteins that modulate the host’s immune system during blood feeding; these molecules could be a target for antivector vaccine development. Recombinant p36, a 36 kDa immunosuppressor from the saliva of female Dermacentor andersoni, suppresses T-lymphocytes proliferation in vitro. To identify potential unique structural and dynamic properties responsible for the immunosuppressive function of p36 proteins, this study utilized bioinformatic tool to characterize and model structure of D. andersoni p36 protein. Evaluation of p36 protein family as suitable vaccine antigens predicted a p36 homolog in Rhipicephalus appendiculatus, the tick vector of East Coast fever, with an antigenicity score of 0.7701 that compares well with that of Bm86 (0.7681, the protein antigen that constitute commercial tick vaccine Tickgard™. Ab initio modeling of the D. andersoni p36 protein yielded a 3D structure that predicted conserved antigenic region, which has potential of binding immunomodulating ligands including glycerol and lactose, found located within exposed loop, suggesting a likely role in immunosuppressive function of tick p36 proteins. Laboratory confirmation of these preliminary results is necessary in future studies.

PCVMZM: Using the Probabilistic Classification Vector Machines Model Combined with a Zernike Moments Descriptor to Predict Protein-Protein Interactions from Protein Sequences.

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Wang, Yanbin; You, Zhuhong; Li, Xiao; Chen, Xing; Jiang, Tonghai; Zhang, Jingting

2017-05-11

Protein-protein interactions (PPIs) are essential for most living organisms' process. Thus, detecting PPIs is extremely important to understand the molecular mechanisms of biological systems. Although many PPIs data have been generated by high-throughput technologies for a variety of organisms, the whole interatom is still far from complete. In addition, the high-throughput technologies for detecting PPIs has some unavoidable defects, including time consumption, high cost, and high error rate. In recent years, with the development of machine learning, computational methods have been broadly used to predict PPIs, and can achieve good prediction rate. In this paper, we present here PCVMZM, a computational method based on a Probabilistic Classification Vector Machines (PCVM) model and Zernike moments (ZM) descriptor for predicting the PPIs from protein amino acids sequences. Specifically, a Zernike moments (ZM) descriptor is used to extract protein evolutionary information from Position-Specific Scoring Matrix (PSSM) generated by Position-Specific Iterated Basic Local Alignment Search Tool (PSI-BLAST). Then, PCVM classifier is used to infer the interactions among protein. When performed on PPIs datasets of Yeast and H. Pylori , the proposed method can achieve the average prediction accuracy of 94.48% and 91.25%, respectively. In order to further evaluate the performance of the proposed method, the state-of-the-art support vector machines (SVM) classifier is used and compares with the PCVM model. Experimental results on the Yeast dataset show that the performance of PCVM classifier is better than that of SVM classifier. The experimental results indicate that our proposed method is robust, powerful and feasible, which can be used as a helpful tool for proteomics research.

QuaBingo: A Prediction System for Protein Quaternary Structure Attributes Using Block Composition

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Chi-Hua Tung

2016-01-01

Full Text Available Background. Quaternary structures of proteins are closely relevant to gene regulation, signal transduction, and many other biological functions of proteins. In the current study, a new method based on protein-conserved motif composition in block format for feature extraction is proposed, which is termed block composition. Results. The protein quaternary assembly states prediction system which combines blocks with functional domain composition, called QuaBingo, is constructed by three layers of classifiers that can categorize quaternary structural attributes of monomer, homooligomer, and heterooligomer. The building of the first layer classifier uses support vector machines (SVM based on blocks and functional domains of proteins, and the second layer SVM was utilized to process the outputs of the first layer. Finally, the result is determined by the Random Forest of the third layer. We compared the effectiveness of the combination of block composition, functional domain composition, and pseudoamino acid composition of the model. In the 11 kinds of functional protein families, QuaBingo is 23% of Matthews Correlation Coefficient (MCC higher than the existing prediction system. The results also revealed the biological characterization of the top five block compositions. Conclusions. QuaBingo provides better predictive ability for predicting the quaternary structural attributes of proteins.

Folding 19 proteins to their native state and stability of large proteins from a coarse-grained model.

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Kapoor, Abhijeet; Travesset, Alex

2014-03-01

We develop an intermediate resolution model, where the backbone is modeled with atomic resolution but the side chain with a single bead, by extending our previous model (Proteins (2013) DOI: 10.1002/prot.24269) to properly include proline, preproline residues and backbone rigidity. Starting from random configurations, the model properly folds 19 proteins (including a mutant 2A3D sequence) into native states containing β sheet, α helix, and mixed α/β. As a further test, the stability of H-RAS (a 169 residue protein, critical in many signaling pathways) is investigated: The protein is stable, with excellent agreement with experimental B-factors. Despite that proteins containing only α helices fold to their native state at lower backbone rigidity, and other limitations, which we discuss thoroughly, the model provides a reliable description of the dynamics as compared with all atom simulations, but does not constrain secondary structures as it is typically the case in more coarse-grained models. Further implications are described. Copyright © 2013 Wiley Periodicals, Inc.

Identification of immunogenic outer membrane proteins of Haemophilus influenzae type b in the infant rat model system

International Nuclear Information System (INIS)

Hansen, E.J.; Frisch, C.F.; McDade, R.L. Jr.; Johnston, K.H.

1981-01-01

Outer membrane proteins of Haemophilus influenzae type b which are immunogenic in infant rats were identified by a radioimmunoprecipitation method. Intact cells of H. influenzae type b were radioiodinated by a lactoperoxidase-catalyzed procedure, and an outer membrane-containing fraction was prepared from these cells. These radioiodinated outer membranes were mixed with sera obtained from rats convalescing from systemic H. influenzae type b disease induced at 6 days of age, and the resultant (antibody-outer membrane protein antigen) complexes were extracted from these membranes by treatment with nonionic detergent and ethylenediaminetetraacetic acid. These soluble antibody-antigen complexes were isolated by means of adsorption to protein A-bearing staphylococci, and the radioiodinated protein antigens were identified by gel electrophoresis followed by autoradiography. Infant rats were shown to mount a readily detectable antibody response to several different proteins present in the outer membrane of H. influenzae type b. Individual infant rats were found to vary both qualitatively and quantitatively in their immune response to these immunogenic outer membrane proteins

The LIKE system, a novel protein expression toolbox for Bacillus subtilis based on the liaI promoter

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2012-01-01

Background Bacillus subtilis is a very important Gram-positive model organism of high biotechnological relevance, which is widely used as a host for the production of both secreted and cytoplasmic proteins. We developed a novel and efficient expression system, based on the liaI promoter (PliaI) from B. subtilis, which is under control of the LiaRS antibiotic-inducible two-component system. In the absence of a stimulus, this promoter is kept tightly inactive. Upon induction by cell wall antibiotics, it shows an over 100-fold increase in activity within 10 min. Results Based on these traits of PliaI, we developed a novel LiaRS-controlled gene expression system for B. subtilis (the “LIKE" system). Two expression vectors, the integrative pLIKE-int and the replicative pLIKE-rep, were constructed. To enhance the performance of the PliaI-derived system, site-directed mutagenesis was employed to optimize the ribosome binding site and alter its spacing to the initiation codon used for the translational fusion. The impact of these genetic modifications on protein production yield was measured using GFP as a model protein. Moreover, a number of tailored B. subtilis expression strains containing different markerless chromosomal deletions of the liaIH region were constructed to circumvent undesired protein production, enhance the positive autoregulation of the LiaRS system and thereby increase target gene expression strength from the PliaI promoter. Conclusions The LIKE protein expression system is a novel protein expression system, which offers a number of advantages over existing systems. Its major advantages are (i) a tightly switched-off promoter during exponential growth in the absence of a stimulus, (ii) a concentration-dependent activation of PliaI in the presence of suitable inducers, (iii) a very fast but transient response with a very high dynamic range of over 100-fold (up to 1,000-fold) induction, (iv) a choice from a range of well-defined, commercially available

Trade-off between positive and negative design of protein stability: from lattice models to real proteins.

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Orly Noivirt-Brik

2009-12-01

Full Text Available Two different strategies for stabilizing proteins are (i positive design in which the native state is stabilized and (ii negative design in which competing non-native conformations are destabilized. Here, the circumstances under which one strategy might be favored over the other are explored in the case of lattice models of proteins and then generalized and discussed with regard to real proteins. The balance between positive and negative design of proteins is found to be determined by their average "contact-frequency", a property that corresponds to the fraction of states in the conformational ensemble of the sequence in which a pair of residues is in contact. Lattice model proteins with a high average contact-frequency are found to use negative design more than model proteins with a low average contact-frequency. A mathematical derivation of this result indicates that it is general and likely to hold also for real proteins. Comparison of the results of correlated mutation analysis for real proteins with typical contact-frequencies to those of proteins likely to have high contact-frequencies (such as disordered proteins and proteins that are dependent on chaperonins for their folding indicates that the latter tend to have stronger interactions between residues that are not in contact in their native conformation. Hence, our work indicates that negative design is employed when insufficient stabilization is achieved via positive design owing to high contact-frequencies.

Computer-aided model analysis for ionic strength-dependent effective charge of protein in ion-exchange chromatography

DEFF Research Database (Denmark)

Lim, Young-il; Jørgensen, Sten Bay; Kim, In-Ho

2005-01-01

differential algebraic equation (PDAE) system, a fast and accurate numerical method (i.e., conservation element/solution element (CE/SE) method), is proposed. Sensitivity and elasticity of the model parameters (e.g., steric/shape factors, adsorption heat coefficient, effective protein charge, equilibrium...... constant, mass transfer coefficient, axial dispersion coefficient and bed voidage) are analyzed for a BSA-salt system in a low protein concentration range. Within a low concentration range of bovine serum albumin (BSA) where linear adsorption isotherms are shown, the adsorption heat coefficient, shape...... salt concentrations, it is proposed that the effective protein charge could depend upon the salt concentration (or ionic strength). The reason for this dependence may be a steric hindrance of protein binding sites combined with a salt shielding effect neutralizing the surface charges of the protein. (c...

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

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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.

An Integrated Framework Advancing Membrane Protein Modeling and Design.

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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.

Multiscale modeling and simulation of microtubule–motor-protein assemblies

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Gao, Tong; Blackwell, Robert; Glaser, Matthew A.; Betterton, M. D.; Shelley, Michael J.

2016-01-01

Microtubules and motor proteins self-organize into biologically important assemblies including the mitotic spindle and the centrosomal microtubule array. Outside of cells, microtubule-motor mixtures can form novel active liquid-crystalline materials driven out of equilibrium by adenosine triphosphate–consuming motor proteins. Microscopic motor activity causes polarity-dependent interactions between motor proteins and microtubules, but how these interactions yield larger-scale dynamical behavior such as complex flows and defect dynamics is not well understood. We develop a multiscale theory for microtubule-motor systems in which Brownian dynamics simulations of polar microtubules driven by motors are used to study microscopic organization and stresses created by motor-mediated microtubule interactions. We identify polarity-sorting and crosslink tether relaxation as two polar-specific sources of active destabilizing stress. We then develop a continuum Doi-Onsager model that captures polarity sorting and the hydrodynamic flows generated by these polar-specific active stresses. In simulations of active nematic flows on immersed surfaces, the active stresses drive turbulent flow dynamics and continuous generation and annihilation of disclination defects. The dynamics follow from two instabilities, and accounting for the immersed nature of the experiment yields unambiguous characteristic length and time scales. When turning off the hydrodynamics in the Doi-Onsager model, we capture formation of polar lanes as observed in the Brownian dynamics simulation. PMID:26764729

Multiscale modeling and simulation of microtubule-motor-protein assemblies.

Science.gov (United States)

Gao, Tong; Blackwell, Robert; Glaser, Matthew A; Betterton, M D; Shelley, Michael J

2015-01-01

Microtubules and motor proteins self-organize into biologically important assemblies including the mitotic spindle and the centrosomal microtubule array. Outside of cells, microtubule-motor mixtures can form novel active liquid-crystalline materials driven out of equilibrium by adenosine triphosphate-consuming motor proteins. Microscopic motor activity causes polarity-dependent interactions between motor proteins and microtubules, but how these interactions yield larger-scale dynamical behavior such as complex flows and defect dynamics is not well understood. We develop a multiscale theory for microtubule-motor systems in which Brownian dynamics simulations of polar microtubules driven by motors are used to study microscopic organization and stresses created by motor-mediated microtubule interactions. We identify polarity-sorting and crosslink tether relaxation as two polar-specific sources of active destabilizing stress. We then develop a continuum Doi-Onsager model that captures polarity sorting and the hydrodynamic flows generated by these polar-specific active stresses. In simulations of active nematic flows on immersed surfaces, the active stresses drive turbulent flow dynamics and continuous generation and annihilation of disclination defects. The dynamics follow from two instabilities, and accounting for the immersed nature of the experiment yields unambiguous characteristic length and time scales. When turning off the hydrodynamics in the Doi-Onsager model, we capture formation of polar lanes as observed in the Brownian dynamics simulation.

Multiscale modeling and simulation of microtubule-motor-protein assemblies

Science.gov (United States)

Gao, Tong; Blackwell, Robert; Glaser, Matthew A.; Betterton, M. D.; Shelley, Michael J.

2015-12-01

Microtubules and motor proteins self-organize into biologically important assemblies including the mitotic spindle and the centrosomal microtubule array. Outside of cells, microtubule-motor mixtures can form novel active liquid-crystalline materials driven out of equilibrium by adenosine triphosphate-consuming motor proteins. Microscopic motor activity causes polarity-dependent interactions between motor proteins and microtubules, but how these interactions yield larger-scale dynamical behavior such as complex flows and defect dynamics is not well understood. We develop a multiscale theory for microtubule-motor systems in which Brownian dynamics simulations of polar microtubules driven by motors are used to study microscopic organization and stresses created by motor-mediated microtubule interactions. We identify polarity-sorting and crosslink tether relaxation as two polar-specific sources of active destabilizing stress. We then develop a continuum Doi-Onsager model that captures polarity sorting and the hydrodynamic flows generated by these polar-specific active stresses. In simulations of active nematic flows on immersed surfaces, the active stresses drive turbulent flow dynamics and continuous generation and annihilation of disclination defects. The dynamics follow from two instabilities, and accounting for the immersed nature of the experiment yields unambiguous characteristic length and time scales. When turning off the hydrodynamics in the Doi-Onsager model, we capture formation of polar lanes as observed in the Brownian dynamics simulation.

Relative quantification of protein-protein interactions using a dual luciferase reporter pull-down assay system.

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Shuaizheng Jia

Full Text Available The identification and quantitative analysis of protein-protein interactions are essential to the functional characterization of proteins in the post-proteomics era. The methods currently available are generally time-consuming, technically complicated, insensitive and/or semi-quantitative. The lack of simple, sensitive approaches to precisely quantify protein-protein interactions still prevents our understanding of the functions of many proteins. Here, we develop a novel dual luciferase reporter pull-down assay by combining a biotinylated Firefly luciferase pull-down assay with a dual luciferase reporter assay. The biotinylated Firefly luciferase-tagged protein enables rapid and efficient isolation of a putative Renilla luciferase-tagged binding protein from a relatively small amount of sample. Both of these proteins can be quantitatively detected using the dual luciferase reporter assay system. Protein-protein interactions, including Fos-Jun located in the nucleus; MAVS-TRAF3 in cytoplasm; inducible IRF3 dimerization; viral protein-regulated interactions, such as MAVS-MAVS and MAVS-TRAF3; IRF3 dimerization; and protein interaction domain mapping, are studied using this novel assay system. Herein, we demonstrate that this dual luciferase reporter pull-down assay enables the quantification of the relative amounts of interacting proteins that bind to streptavidin-coupled beads for protein purification. This study provides a simple, rapid, sensitive, and efficient approach to identify and quantify relative protein-protein interactions. Importantly, the dual luciferase reporter pull-down method will facilitate the functional determination of proteins.

Concentration-Induced Association in a Protein System Caused by a Highly Directional Patch Attraction.

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Li, Weimin; Persson, Björn A; Lund, Mikael; Bergenholtz, Johan; Zackrisson Oskolkova, Malin

2016-09-01

Self-association of the protein lactoferrin is studied in solution using small-angle X-ray scattering techniques. Effective static structure factors have been shown to exhibit either a monotonic or a nonmonotonic dependence on protein concentration in the small wavevector limit, depending on salt concentration. The behavior correlates with a nonmonotonic dependence of the second virial coefficient on salt concentration, such that a maximum appears in the structure factor at a low protein concentration when the second virial coefficient is negative and close to a minimum. The results are interpreted in terms of an integral equation theory with explicit dimers, formulated by Wertheim, which provides a consistent framework able to explain the behavior in terms of a monomer-dimer equilibrium that appears because of a highly directional patch attraction. Short attraction ranges preclude trimer formation, which explains why the protein system behaves as if it were subject to a concentration-dependent isotropic protein-protein attraction. Superimposing an isotropic interaction, comprising screened Coulomb repulsion and van der Waals attraction, on the patch attraction allows for a semiquantitative modeling of the complete transition pathway from monomers in the dilute limit to monomer-dimer systems at somewhat higher protein concentrations.

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

A customized light sheet microscope to measure spatio-temporal protein dynamics in small model organisms.

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Matthias Rieckher

Full Text Available We describe a customizable and cost-effective light sheet microscopy (LSM platform for rapid three-dimensional imaging of protein dynamics in small model organisms. The system is designed for high acquisition speeds and enables extended time-lapse in vivo experiments when using fluorescently labeled specimens. We demonstrate the capability of the setup to monitor gene expression and protein localization during ageing and upon starvation stress in longitudinal studies in individual or small groups of adult Caenorhabditis elegans nematodes. The system is equipped to readily perform fluorescence recovery after photobleaching (FRAP, which allows monitoring protein recovery and distribution under low photobleaching conditions. Our imaging platform is designed to easily switch between light sheet microscopy and optical projection tomography (OPT modalities. The setup permits monitoring of spatio-temporal expression and localization of ageing biomarkers of subcellular size and can be conveniently adapted to image a wide range of small model organisms and tissue samples.

Cooperative working of bacterial chromosome replication proteins generated by a reconstituted protein expression system

Science.gov (United States)

Fujiwara, Kei; Katayama, Tsutomu; Nomura, Shin-ichiro M.

2013-01-01

Replication of all living cells relies on the multirounds flow of the central dogma. Especially, expression of DNA replication proteins is a key step to circulate the processes of the central dogma. Here we achieved the entire sequential transcription–translation–replication process by autonomous expression of chromosomal DNA replication machineries from a reconstituted transcription–translation system (PURE system). We found that low temperature is essential to express a complex protein, DNA polymerase III, in a single tube using the PURE system. Addition of the 13 genes, encoding initiator, DNA helicase, helicase loader, RNA primase and DNA polymerase III to the PURE system gave rise to a DNA replication system by a coupling manner. An artificial genetic circuit demonstrated that the DNA produced as a result of the replication is able to provide genetic information for proteins, indicating the in vitro central dogma can sequentially undergo two rounds. PMID:23737447

Binary polypeptide system for permanent and oriented protein immobilization

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Bailes Julian

2010-05-01

Full Text Available Abstract Background Many techniques in molecular biology, clinical diagnostics and biotechnology rely on binary affinity tags. The existing tags are based on either small molecules (e.g., biotin/streptavidin or glutathione/GST or peptide tags (FLAG, Myc, HA, Strep-tag and His-tag. Among these, the biotin-streptavidin system is most popular due to the nearly irreversible interaction of biotin with the tetrameric protein, streptavidin. The major drawback of the stable biotin-streptavidin system, however, is that neither of the two tags can be added to a protein of interest via recombinant means (except for the Strep-tag case leading to the requirement for chemical coupling. Results Here we report a new immobilization system which utilizes two monomeric polypeptides which self-assemble to produce non-covalent yet nearly irreversible complex which is stable in strong detergents, chaotropic agents, as well as in acids and alkali. Our system is based on the core region of the tetra-helical bundle known as the SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor complex. This irreversible protein attachment system (IPAS uses either a shortened syntaxin helix and fused SNAP25-synaptobrevin or a fused syntaxin-synaptobrevin and SNAP25 allowing a two-component system suitable for recombinant protein tagging, capture and immobilization. We also show that IPAS is suitable for use with traditional beads and chromatography, planar surfaces and Biacore, gold nanoparticles and for protein-protein interaction in solution. Conclusions IPAS offers an alternative to chemical cross-linking, streptavidin-biotin system and to traditional peptide affinity tags and can be used for a wide range of applications in nanotechnology and molecular sciences.

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…

Fly-DPI: database of protein interactomes for D. melanogaster in the approach of systems biology

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Lin Chieh-Hua

2006-12-01

Full Text Available Abstract Background Proteins control and mediate many biological activities of cells by interacting with other protein partners. This work presents a statistical model to predict protein interaction networks of Drosophila melanogaster based on insight into domain interactions. Results Three high-throughput yeast two-hybrid experiments and the collection in FlyBase were used as our starting datasets. The co-occurrences of domains in these interactive events are converted into a probability score of domain-domain interaction. These scores are used to infer putative interaction among all available open reading frames (ORFs of fruit fly. Additionally, the likelihood function is used to estimate all potential protein-protein interactions. All parameters are successfully iterated and MLE is obtained for each pair of domains. Additionally, the maximized likelihood reaches its converged criteria and maintains the probability stable. The hybrid model achieves a high specificity with a loss of sensitivity, suggesting that the model may possess major features of protein-protein interactions. Several putative interactions predicted by the proposed hybrid model are supported by literatures, while experimental data with a low probability score indicate an uncertain reliability and require further proof of interaction. Fly-DPI is the online database used to present this work. It is an integrated proteomics tool with comprehensive protein annotation information from major databases as well as an effective means of predicting protein-protein interactions. As a novel search strategy, the ping-pong search is a naïve path map between two chosen proteins based on pre-computed shortest paths. Adopting effective filtering strategies will facilitate researchers in depicting the bird's eye view of the network of interest. Fly-DPI can be accessed at http://flydpi.nhri.org.tw. Conclusion This work provides two reference systems, statistical and biological, to evaluate

The Protein Information Management System (PiMS): a generic tool for any structural biology research laboratory

International Nuclear Information System (INIS)

Morris, Chris; Pajon, Anne; Griffiths, Susanne L.; Daniel, Ed; Savitsky, Marc; Lin, Bill; Diprose, Jonathan M.; Wilter da Silva, Alan; Pilicheva, Katya; Troshin, Peter; Niekerk, Johannes van; Isaacs, Neil; Naismith, James; Nave, Colin; Blake, Richard; Wilson, Keith S.; Stuart, David I.; Henrick, Kim; Esnouf, Robert M.

2011-01-01

The Protein Information Management System (PiMS) is described together with a discussion of how its features make it well suited to laboratories of all sizes. The techniques used in protein production and structural biology have been developing rapidly, but techniques for recording the laboratory information produced have not kept pace. One approach is the development of laboratory information-management systems (LIMS), which typically use a relational database schema to model and store results from a laboratory workflow. The underlying philosophy and implementation of the Protein Information Management System (PiMS), a LIMS development specifically targeted at the flexible and unpredictable workflows of protein-production research laboratories of all scales, is described. PiMS is a web-based Java application that uses either Postgres or Oracle as the underlying relational database-management system. PiMS is available under a free licence to all academic laboratories either for local installation or for use as a managed service

The Protein Information Management System (PiMS): a generic tool for any structural biology research laboratory

Energy Technology Data Exchange (ETDEWEB)

Morris, Chris [STFC Daresbury Laboratory, Warrington WA4 4AD (United Kingdom); Pajon, Anne [Wellcome Trust Genome Campus, Hinxton CB10 1SD (United Kingdom); Griffiths, Susanne L. [University of York, Heslington, York YO10 5DD (United Kingdom); Daniel, Ed [STFC Daresbury Laboratory, Warrington WA4 4AD (United Kingdom); Savitsky, Marc [University of Oxford, Roosevelt Drive, Oxford OX3 7BN (United Kingdom); Lin, Bill [STFC Daresbury Laboratory, Warrington WA4 4AD (United Kingdom); Diprose, Jonathan M. [University of Oxford, Roosevelt Drive, Oxford OX3 7BN (United Kingdom); Wilter da Silva, Alan [Wellcome Trust Genome Campus, Hinxton CB10 1SD (United Kingdom); Pilicheva, Katya [University of Oxford, Roosevelt Drive, Oxford OX3 7BN (United Kingdom); Troshin, Peter [STFC Daresbury Laboratory, Warrington WA4 4AD (United Kingdom); Niekerk, Johannes van [University of Dundee, Dundee DD1 5EH, Scotland (United Kingdom); Isaacs, Neil [University of Glasgow, Glasgow G12 8QQ, Scotland (United Kingdom); Naismith, James [University of St Andrews, St Andrews, Fife KY16 9ST, Scotland (United Kingdom); Nave, Colin; Blake, Richard [STFC Daresbury Laboratory, Warrington WA4 4AD (United Kingdom); Wilson, Keith S. [University of York, Heslington, York YO10 5DD (United Kingdom); Stuart, David I. [University of Oxford, Roosevelt Drive, Oxford OX3 7BN (United Kingdom); Henrick, Kim [Wellcome Trust Genome Campus, Hinxton CB10 1SD (United Kingdom); Esnouf, Robert M., E-mail: robert@strubi.ox.ac.uk [University of Oxford, Roosevelt Drive, Oxford OX3 7BN (United Kingdom); STFC Daresbury Laboratory, Warrington WA4 4AD (United Kingdom)

2011-04-01

The Protein Information Management System (PiMS) is described together with a discussion of how its features make it well suited to laboratories of all sizes. The techniques used in protein production and structural biology have been developing rapidly, but techniques for recording the laboratory information produced have not kept pace. One approach is the development of laboratory information-management systems (LIMS), which typically use a relational database schema to model and store results from a laboratory workflow. The underlying philosophy and implementation of the Protein Information Management System (PiMS), a LIMS development specifically targeted at the flexible and unpredictable workflows of protein-production research laboratories of all scales, is described. PiMS is a web-based Java application that uses either Postgres or Oracle as the underlying relational database-management system. PiMS is available under a free licence to all academic laboratories either for local installation or for use as a managed service.

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)

Heterologous protein secretion in Lactococcus lactis: a novel antigen delivery system

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Langella P.

1999-01-01

Full Text Available Lactic acid bacteria (LAB are Gram-positive bacteria and are generally regarded as safe (GRAS organisms. Therefore, LAB could be used for heterologous protein secretion and they are good potential candidates as antigen delivery vehicles. To develop such live vaccines, a better control of protein secretion is required. We developed an efficient secretion system in the model LAB, Lactococcus lactis. Staphylococcal nuclease (Nuc was used as the reporter protein. We first observed that the quantity of secreted Nuc correlated with the copy number of the cloning vector. The nuc gene was cloned on a high-copy number cloning vector and no perturbation of the metabolism of the secreting strain was observed. Replacement of nuc native promoter by a strong lactococcal one led to a significant increase of nuc expression. Secretion efficiency (SE of Nuc in L. lactis was low, i.e., only 60% of the synthesized Nuc was secreted. Insertion of a synthetic propeptide between the signal peptide and the mature moiety of Nuc increased the SE of Nuc. On the basis of these results, we developed a secretion system and we applied it to the construction of an L. lactis strain which secretes a bovine coronavirus (BCV epitope-protein fusion (BCV-Nuc. BCV-Nuc was recognized by both anti-BCV and anti-Nuc antibodies. Secretion of this antigenic fusion is the first step towards the development of a novel antigen delivery system based on LAB-secreting strains.

Manufacturing of recombinant therapeutic proteins in microbial systems.

Science.gov (United States)

Graumann, Klaus; Premstaller, Andreas

2006-02-01

Recombinant therapeutic proteins have gained enormous importance for clinical applications. The first recombinant products have been produced in E. coli more than 20 years ago. Although with the advent of antibody-based therapeutics mammalian expression systems have experienced a major boost, microbial expression systems continue to be widely used in industry. Their intrinsic advantages, such as rapid growth, high yields and ease of manipulation, make them the premier choice for expression of non-glycosylated peptides and proteins. Innovative product classes such as antibody fragments or alternative binding molecules will further expand the use of microbial systems. Even more, novel, engineered production hosts and integrated technology platforms hold enormous potential for future applications. This review summarizes current applications and trends for development, production and analytical characterization of recombinant therapeutic proteins in microbial systems.

Biomaterials Derived from Silk-Tropoelastin Protein Systems

Science.gov (United States)

Hu, Xiao; Wang, Xiuli; Rnjak, Jelena; Weiss, Anthony S.; Kaplan, David L.

2010-01-01

A structural protein blend system based on silkworm silk fibroin and recombinant human tropoelastin is described. Silk fibroin, a semicrystalline fibrous protein with beta-sheet crystals provides mechanical strength and controllable biodegradation, while tropoelastin, a noncrystallizable elastic protein provides elasticity. Differential scanning calorimetry (DSC) and temperature modulated DSC (TMDSC) indicated that silk becomes miscible with tropoelastin at different blend ratios, without macrophase separation. Fourier transform infrared spectroscopy (FTIR) revealed secondary structural changes of the blend system (beta-sheet content) before and after methanol treatment. Atomic Force Microscopy (AFM) nano-indentation demonstrated that blending silk and tropoelastin at different ratios resulted in modification of mechanical features, with resilience from ~68% to ~97%, and elastic modulus between 2~9Mpa, depending on the ratio of the two polymers. Some of these values are close to those of native aortic elastin or elastin-like polypeptides. Significantly, during blending and drying silk-tropoelastin form micro- and nano-scale porous morphologies which promote human mesenchymal stem cell attachment and proliferation. These blends offer a new protein biomaterial system for cell support and tailored biomaterial properties to match mechanical needs. PMID:20674969

In silico modelling and validation of differential expressed proteins in lung cancer

Directory of Open Access Journals (Sweden)

Bhagavathi S

2012-05-01

Full Text Available Objective: The present study aims predict the three dimensional structure of three major proteins responsible for causing Lung cancer. Methods: These are the differentially expressed proteins in lung cancer dataset. Initially, the structural template for these proteins is identified from structural database using homology search and perform homology modelling approach to predict its native 3D structure. Three-dimensional model obtained was validated using Ramachandran plot analysis to find the reliability of the model. Results: Four proteins were differentially expressed and were significant proteins in causing lung cancer. Among the four proteins, Matrixmetallo proteinase (P39900 had a known 3D structure and hence was not considered for modelling. The remaining proteins Polo like kinase I Q58A51, Trophinin B1AKF1, Thrombomodulin P07204 were modelled and validated. Conclusions: The three dimensional structure of proteins provides insights about the functional aspect and regulatory aspect of the protein. Thus, this study will be a breakthrough for further lung cancer related studies.

Protein single-model quality assessment by feature-based probability density functions.

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Cao, Renzhi; Cheng, Jianlin

2016-04-04

Protein quality assessment (QA) has played an important role in protein structure prediction. We developed a novel single-model quality assessment method-Qprob. Qprob calculates the absolute error for each protein feature value against the true quality scores (i.e. GDT-TS scores) of protein structural models, and uses them to estimate its probability density distribution for quality assessment. Qprob has been blindly tested on the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) as MULTICOM-NOVEL server. The official CASP result shows that Qprob ranks as one of the top single-model QA methods. In addition, Qprob makes contributions to our protein tertiary structure predictor MULTICOM, which is officially ranked 3rd out of 143 predictors. The good performance shows that Qprob is good at assessing the quality of models of hard targets. These results demonstrate that this new probability density distribution based method is effective for protein single-model quality assessment and is useful for protein structure prediction. The webserver of Qprob is available at: http://calla.rnet.missouri.edu/qprob/. The software is now freely available in the web server of Qprob.

Quality assessment of protein model-structures based on structural and functional similarities.

Science.gov (United States)

Konopka, Bogumil M; Nebel, Jean-Christophe; Kotulska, Malgorzata

2012-09-21

Experimental determination of protein 3D structures is expensive, time consuming and sometimes impossible. A gap between number of protein structures deposited in the World Wide Protein Data Bank and the number of sequenced proteins constantly broadens. Computational modeling is deemed to be one of the ways to deal with the problem. Although protein 3D structure prediction is a difficult task, many tools are available. These tools can model it from a sequence or partial structural information, e.g. contact maps. Consequently, biologists have the ability to generate automatically a putative 3D structure model of any protein. However, the main issue becomes evaluation of the model quality, which is one of the most important challenges of structural biology. GOBA--Gene Ontology-Based Assessment is a novel Protein Model Quality Assessment Program. It estimates the compatibility between a model-structure and its expected function. GOBA is based on the assumption that a high quality model is expected to be structurally similar to proteins functionally similar to the prediction target. Whereas DALI is used to measure structure similarity, protein functional similarity is quantified using standardized and hierarchical description of proteins provided by Gene Ontology combined with Wang's algorithm for calculating semantic similarity. Two approaches are proposed to express the quality of protein model-structures. One is a single model quality assessment method, the other is its modification, which provides a relative measure of model quality. Exhaustive evaluation is performed on data sets of model-structures submitted to the CASP8 and CASP9 contests. The validation shows that the method is able to discriminate between good and bad model-structures. The best of tested GOBA scores achieved 0.74 and 0.8 as a mean Pearson correlation to the observed quality of models in our CASP8 and CASP9-based validation sets. GOBA also obtained the best result for two targets of CASP8, and

Characterizing and modeling protein-surface interactions in lab-on-chip devices

Science.gov (United States)

Katira, Parag

Protein adsorption on surfaces determines the response of other biological species present in the surrounding solution. This phenomenon plays a major role in the design of biomedical and biotechnological devices. While specific protein adsorption is essential for device function, non-specific protein adsorption leads to the loss of device function. For example, non-specific protein adsorption on bioimplants triggers foreign body response, in biosensors it leads to reduced signal to noise ratios, and in hybrid bionanodevices it results in the loss of confinement and directionality of molecular shuttles. Novel surface coatings are being developed to reduce or completely prevent the non-specific adsorption of proteins to surfaces. A novel quantification technique for extremely low protein coverage on surfaces has been developed. This technique utilizes measurement of the landing rate of microtubule filaments on kinesin proteins adsorbed on a surface to determine the kinesin density. Ultra-low limits of detection, dynamic range, ease of detection and availability of a ready-made kinesin-microtubule kit makes this technique highly suitable for detecting protein adsorption below the detection limits of standard techniques. Secondly, a random sequential adsorption model is presented for protein adsorption to PEO-coated surfaces. The derived analytical expressions accurately predict the observed experimental results from various research groups, suggesting that PEO chains act as almost perfect steric barriers to protein adsorption. These expressions can be used to predict the performance of a variety of systems towards resisting protein adsorption and can help in the design of better non-fouling surface coatings. Finally, in biosensing systems, target analytes are captured and concentrated on specifically adsorbed proteins for detection. Non-specific adsorption of proteins results in the loss of signal, and an increase in the background. The use of nanoscale transducers as

Uncoupling of Protein Aggregation and Neurodegeneration in a Mouse Amyotrophic Lateral Sclerosis Model.

Science.gov (United States)

Lee, Joo-Yong; Kawaguchi, Yoshiharu; Li, Ming; Kapur, Meghan; Choi, Su Jin; Kim, Hak-June; Park, Song-Yi; Zhu, Haining; Yao, Tso-Pang

2015-01-01

Aberrant accumulation of protein aggregates is a pathological hallmark of many neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS). Although a buildup of protein aggregates frequently leads to cell death, whether it is the key pathogenic factor in driving neurodegenerative disease remains controversial. HDAC6, a cytosolic ubiquitin-binding deacetylase, has emerged as an important regulator of ubiquitin-dependent quality control autophagy, a lysosome-dependent degradative system responsible for the disposal of misfolded protein aggregates and damaged organelles. Here, we show that in cell models HDAC6 plays a protective role against multiple disease-associated and aggregation-prone cytosolic proteins by facilitating their degradation. We further show that HDAC6 is required for efficient localization of lysosomes to protein aggregates, indicating that lysosome targeting to autophagic substrates is regulated. Supporting a critical role of HDAC6 in protein aggregate disposal in vivo, genetic ablation of HDAC6 in a transgenic SOD1G93A mouse, a model of ALS, leads to dramatic accumulation of ubiquitinated SOD1G93A protein aggregates. Surprisingly, despite a robust buildup of SOD1G93A aggregates, deletion of HDAC6 only moderately modified the motor phenotypes. These findings indicate that SOD1G93A aggregation is not the only determining factor to drive neurodegeneration in ALS, and that HDAC6 likely modulates neurodegeneration through additional mechanisms beyond protein aggregate clearance. © 2015 S. Karger AG, Basel.

Simulation studies of protein-induced bilayer deformations, and lipid-induced protein tilting, on a mesoscopic model for lipid bilayers with embedded proteins

DEFF Research Database (Denmark)

Venturoli, M.; Smit, B.; Sperotto, Maria Maddalena

2005-01-01

membranes. Here we present a mesoscopic model for lipid bilayers with embedded proteins, which we have studied with the help of the dissipative particle dynamics simulation technique. Because hydrophobic matching is believed to be one of the main physical mechanisms regulating lipid-protein interactions......-induced protein tilt, with the hydrophobic mismatch ( positive and negative) between the protein hydrophobic length and the pure lipid bilayer hydrophobic thickness. The protein-induced bilayer perturbation was quantified in terms of a coherence length, xi(P), of the lipid bilayer hydrophobic thickness pro. le...... for positive values of mismatch; a dependence on the protein size appears as well. In the case of large model proteins experiencing extreme mismatch conditions, in the region next to the so-called lipid annulus, there appears an undershooting ( or overshooting) region where the bilayer hydrophobic thickness...

SynechoNET: integrated protein-protein interaction database of a model cyanobacterium Synechocystis sp. PCC 6803

OpenAIRE

Kim, Woo-Yeon; Kang, Sungsoo; Kim, Byoung-Chul; Oh, Jeehyun; Cho, Seongwoong; Bhak, Jong; Choi, Jong-Soon

2008-01-01

Background Cyanobacteria are model organisms for studying photosynthesis, carbon and nitrogen assimilation, evolution of plant plastids, and adaptability to environmental stresses. Despite many studies on cyanobacteria, there is no web-based database of their regulatory and signaling protein-protein interaction networks to date. Description We report a database and website SynechoNET that provides predicted protein-protein interactions. SynechoNET shows cyanobacterial domain-domain interactio...

The ability of in vitro antioxidant assays to predict the efficiency of a cod protein hydrolysate and brown seaweed extract to prevent oxidation in marine food model systems.

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Jónsdóttir, Rósa; Geirsdóttir, Margrét; Hamaguchi, Patricia Y; Jamnik, Polona; Kristinsson, Hordur G; Undeland, Ingrid

2016-04-01

The ability of different in vitro antioxidant assays to predict the efficiency of cod protein hydrolysate (CPH) and Fucus vesiculosus ethyl acetate extract (EA) towards lipid oxidation in haemoglobin-fortified washed cod mince and iron-containing cod liver oil emulsion was evaluated. The progression of oxidation was followed by sensory analysis, lipid hydroperoxides and thiobarbituric acid-reactive substances (TBARS) in both systems, as well as loss of redness and protein carbonyls in the cod system. The in vitro tests revealed high reducing capacity, high DPPH radical scavenging properties and a high oxygen radical absorbance capacity (ORAC) value of the EA which also inhibited lipid and protein oxidation in the cod model system. The CPH had a high metal chelating capacity and was efficient against oxidation in the cod liver oil emulsion. The results indicate that the F. vesiculosus extract has a potential as an excellent natural antioxidant against lipid oxidation in fish muscle foods while protein hydrolysates are more promising for fish oil emulsions. The usefulness of in vitro assays to predict the antioxidative properties of new natural ingredients in foods thus depends on the knowledge about the food systems, particularly the main pro-oxidants present. © 2015 Society of Chemical Industry.

Using modified soy protein to enhance foaming of egg white protein.

Science.gov (United States)

Wang, Guang; Troendle, Molly; Reitmeier, Cheryll A; Wang, Tong

2012-08-15

It is well known that the foaming properties of egg white protein are significantly reduced when a small amount of yolk is mixed in the white. To improve foaming properties of yolk-contaminated egg white protein, soy protein isolate (SPI) and egg proteins were modified to make basic proteins, and effects of these modified proteins on egg white foaming were evaluated in a model and an angel cake system. SPI and egg yolk proteins were modified to have an isoelectric point of 10, and sonication was used to increase protein dispersibility after the ethyl esterification reaction. However, only the addition of sonicated and modified SPI (SMSPI) showed improvement of foaming in the 5% egg protein model system with 0.4% yolk addition. SMSPI was then used in making angel food cake to examine whether the cake performance reduction due to yolk contamination of the white would be restored by such alkaline protein. Cake performance was improved when cream of tartar was used together with SMSPI. Basic soy protein can be made and used to improve egg white foaming properties and cake performance. Copyright © 2012 Society of Chemical Industry.

Seed Storage Proteins as a System for Teaching Protein Identification by Mass Spectrometry in Biochemistry Laboratory

Science.gov (United States)

Wilson, Karl A.; Tan-Wilson, Anna

2013-01-01

Mass spectrometry (MS) has become an important tool in studying biological systems. One application is the identification of proteins and peptides by the matching of peptide and peptide fragment masses to the sequences of proteins in protein sequence databases. Often prior protein separation of complex protein mixtures by 2D-PAGE is needed,…

Human activated protein C variants in a rat model of arterial thrombosis

Directory of Open Access Journals (Sweden)

Dahlbäck Björn

2008-10-01

Full Text Available Abstract Background Activated protein C (APC inhibits coagulation by degrading activated factor V (FVa and factor VIII (FVIIIa, protein S (PS functioning as a cofactor to APC. Methods By mutagenesis of the vitamin K-dependent Gla domain of APC, we have recently created an APC variant having enhanced anticoagulant activity due to increased affinity for negatively charged phospholipid membranes. In the present study, the potential antithrombotic effects of this APC variant, and of a variant APC that is additionally mutated in the serine protease domain, have been evaluated in a blind randomized study in a rat model of arterial thrombosis. In this model, we have previously found the combination of bovine APC and PS to be highly antithrombotic. Four treatment groups each containing 10 rats were, in a blind random fashion, given intravenous bolus injections of wild-type or mutant variants of APC (0.8 mg/kg together with human PS (0.6 mg/kg or human PS (0.6 mg/kg alone. A control group with 20 animals where given vehicle only. Results A trend to increased patency rates was noted in a group receiving one of the APC variants, but it did not reach statistical significance. Conclusion In conclusion, administration of human APC variants having enhanced anticoagulant efficacy together with human PS in a rat model of arterial thrombosis did not give an efficient antithrombotic effect. The lack of effect may be due to species-specific differences between the human protein C system and the rat hemostatic system.

Adsorption and Desorption of Bioactive Proteins on Hydroxyapatite for Protein Delivery Systems

Directory of Open Access Journals (Sweden)

Chie Kojima

2012-01-01

Full Text Available Hydroxyapatite (HA is a precursor of bone and has been studied as a biomaterial. We attempted HA to apply to protein delivery systems. In this study, the association and dissociation properties of two types of bioactive proteins, cytochrom c and insulin, to HA were investigated. Cytochrom c was less associated with HA than insulin, which was easily released from it. However, the release of insulin from HA was slow. Insulin was released from HA at pH 7.4 more rapidly than at pH 3. The association and dissociation properties might be influenced by the size, solubility and net charge of protein. HA is a potential protein carrier with controlled release.

Statistical-mechanical lattice models for protein-DNA binding in chromatin

International Nuclear Information System (INIS)

Teif, Vladimir B; Rippe, Karsten

2010-01-01

Statistical-mechanical lattice models for protein-DNA binding are well established as a method to describe complex ligand binding equilibria measured in vitro with purified DNA and protein components. Recently, a new field of applications has opened up for this approach since it has become possible to experimentally quantify genome-wide protein occupancies in relation to the DNA sequence. In particular, the organization of the eukaryotic genome by histone proteins into a nucleoprotein complex termed chromatin has been recognized as a key parameter that controls the access of transcription factors to the DNA sequence. New approaches have to be developed to derive statistical-mechanical lattice descriptions of chromatin-associated protein-DNA interactions. Here, we present the theoretical framework for lattice models of histone-DNA interactions in chromatin and investigate the (competitive) DNA binding of other chromosomal proteins and transcription factors. The results have a number of applications for quantitative models for the regulation of gene expression.

N-terminally truncated GADD34 proteins are convenient translation enhancers in a human cell-derived in vitro protein synthesis system.

Science.gov (United States)

Mikami, Satoshi; Kobayashi, Tominari; Machida, Kodai; Masutani, Mamiko; Yokoyama, Shigeyuki; Imataka, Hiroaki

2010-07-01

Human cell-derived in vitro protein synthesis systems are useful for the production of recombinant proteins. Productivity can be increased by supplementation with GADD34, a protein that is difficult to express in and purify from E. coli. Deletion of the N-terminal 120 or 240 amino acids of GADD34 improves recovery of this protein from E. coli without compromising its ability to boost protein synthesis in an in vitro protein synthesis system. The use of N-terminally truncated GADD34 proteins in place of full-length GADD34 should improve the utility of human cell-based cell-free protein synthesis systems.

Protein secretion and membrane insertion systems in gram-negative bacteria.

Science.gov (United States)

Saier, Milton H

2006-01-01

In contrast to other organisms, gram-negative bacteria have evolved numerous systems for protein export. Eight types are known that mediate export across or insertion into the cytoplasmic membrane, while eight specifically mediate export across or insertion into the outer membrane. Three of the former secretory pathway (SP) systems, type I SP (ISP, ABC), IIISP (Fla/Path) and IVSP (Conj/Vir), can export proteins across both membranes in a single energy-coupled step. A fourth generalized mechanism for exporting proteins across the two-membrane envelope in two distinct steps (which we here refer to as type II secretory pathways [IISP]) utilizes either the general secretory pathway (GSP or Sec) or the twin-arginine targeting translocase for translocation across the inner membrane, and either the main terminal branch or one of several protein-specific export systems for translocation across the outer membrane. We here survey the various well-characterized protein translocation systems found in living organisms and then focus on the systems present in gram-negative bacteria. Comparisons between these systems suggest specific biogenic, mechanistic and evolutionary similarities as well as major differences.

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

Stochastic lattice model of synaptic membrane protein domains.

Science.gov (United States)

Li, Yiwei; Kahraman, Osman; Haselwandter, Christoph A

2017-05-01

Neurotransmitter receptor molecules, concentrated in synaptic membrane domains along with scaffolds and other kinds of proteins, are crucial for signal transmission across chemical synapses. In common with other membrane protein domains, synaptic domains are characterized by low protein copy numbers and protein crowding, with rapid stochastic turnover of individual molecules. We study here in detail a stochastic lattice model of the receptor-scaffold reaction-diffusion dynamics at synaptic domains that was found previously to capture, at the mean-field level, the self-assembly, stability, and characteristic size of synaptic domains observed in experiments. We show that our stochastic lattice model yields quantitative agreement with mean-field models of nonlinear diffusion in crowded membranes. Through a combination of analytic and numerical solutions of the master equation governing the reaction dynamics at synaptic domains, together with kinetic Monte Carlo simulations, we find substantial discrepancies between mean-field and stochastic models for the reaction dynamics at synaptic domains. Based on the reaction and diffusion properties of synaptic receptors and scaffolds suggested by previous experiments and mean-field calculations, we show that the stochastic reaction-diffusion dynamics of synaptic receptors and scaffolds provide a simple physical mechanism for collective fluctuations in synaptic domains, the molecular turnover observed at synaptic domains, key features of the observed single-molecule trajectories, and spatial heterogeneity in the effective rates at which receptors and scaffolds are recycled at the cell membrane. Our work sheds light on the physical mechanisms and principles linking the collective properties of membrane protein domains to the stochastic dynamics that rule their molecular components.

CONFOLD2: improved contact-driven ab initio protein structure modeling.

Science.gov (United States)

Adhikari, Badri; Cheng, Jianlin

2018-01-25

Contact-guided protein structure prediction methods are becoming more and more successful because of the latest advances in residue-residue contact prediction. To support contact-driven structure prediction, effective tools that can quickly build tertiary structural models of good quality from predicted contacts need to be developed. We develop an improved contact-driven protein modelling method, CONFOLD2, and study how it may be effectively used for ab initio protein structure prediction with predicted contacts as input. It builds models using various subsets of input contacts to explore the fold space under the guidance of a soft square energy function, and then clusters the models to obtain the top five models. CONFOLD2 obtains an average reconstruction accuracy of 0.57 TM-score for the 150 proteins in the PSICOV contact prediction dataset. When benchmarked on the CASP11 contacts predicted using CONSIP2 and CASP12 contacts predicted using Raptor-X, CONFOLD2 achieves a mean TM-score of 0.41 on both datasets. CONFOLD2 allows to quickly generate top five structural models for a protein sequence when its secondary structures and contacts predictions at hand. The source code of CONFOLD2 is publicly available at https://github.com/multicom-toolbox/CONFOLD2/ .

The Protein Information Management System (PiMS): a generic tool for any structural biology research laboratory.

Science.gov (United States)

Morris, Chris; Pajon, Anne; Griffiths, Susanne L; Daniel, Ed; Savitsky, Marc; Lin, Bill; Diprose, Jonathan M; da Silva, Alan Wilter; Pilicheva, Katya; Troshin, Peter; van Niekerk, Johannes; Isaacs, Neil; Naismith, James; Nave, Colin; Blake, Richard; Wilson, Keith S; Stuart, David I; Henrick, Kim; Esnouf, Robert M

2011-04-01

The techniques used in protein production and structural biology have been developing rapidly, but techniques for recording the laboratory information produced have not kept pace. One approach is the development of laboratory information-management systems (LIMS), which typically use a relational database schema to model and store results from a laboratory workflow. The underlying philosophy and implementation of the Protein Information Management System (PiMS), a LIMS development specifically targeted at the flexible and unpredictable workflows of protein-production research laboratories of all scales, is described. PiMS is a web-based Java application that uses either Postgres or Oracle as the underlying relational database-management system. PiMS is available under a free licence to all academic laboratories either for local installation or for use as a managed service.

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.

Hidden Markov model-derived structural alphabet for proteins: the learning of protein local shapes captures sequence specificity.

Science.gov (United States)

Camproux, A C; Tufféry, P

2005-08-05

Understanding and predicting protein structures depend on the complexity and the accuracy of the models used to represent them. We have recently set up a Hidden Markov Model to optimally compress protein three-dimensional conformations into a one-dimensional series of letters of a structural alphabet. Such a model learns simultaneously the shape of representative structural letters describing the local conformation and the logic of their connections, i.e. the transition matrix between the letters. Here, we move one step further and report some evidence that such a model of protein local architecture also captures some accurate amino acid features. All the letters have specific and distinct amino acid distributions. Moreover, we show that words of amino acids can have significant propensities for some letters. Perspectives point towards the prediction of the series of letters describing the structure of a protein from its amino acid sequence.

Review: Milk Proteins as Nanocarrier Systems for Hydrophobic Nutraceuticals.

Science.gov (United States)

Kimpel, Florian; Schmitt, Joachim J

2015-11-01

Milk proteins and milk protein aggregates are among the most important nanovehicles in food technology. Milk proteins have various functional properties that facilitate their ability to carry hydrophobic nutraceutical substances. The main functional transport properties that were examined in the reviewed studies are binding of molecules or ions, surface activity, aggregation, gelation, and interaction with other polymers. Hydrophobic binding has been investigated using caseins and isolated β-casein as well as whey proteins. Surface activity of caseins has been used to create emulsion-based carrier systems. Furthermore, caseins are able to self-assemble into micelles, which can incorporate molecules. Gelation and interaction with other polymers can be used to encapsulate molecules into protein networks. The release of transported substances mainly depends on pH and swelling behavior of the proteins. The targeted use of nanocarrier systems requires specific knowledge about the binding mechanisms between the proteins and the carried substances in a certain food matrix. © 2015 Institute of Food Technologists®

Evolution and Function of Thioester-Containing Proteins and the Complement System in the Innate Immune Response

Directory of Open Access Journals (Sweden)

Upasana Shokal

2017-06-01

Full Text Available The innate immune response is evolutionary conserved among organisms. The complement system forms an important and efficient immune defense mechanism. It consists of plasma proteins that participate in microbial detection, which ultimately results in the production of various molecules with antimicrobial activity. Thioester-containing proteins (TEPs are a superfamily of secreted effector proteins. In vertebrates, certain TEPs act in the innate immune response by promoting recruitment of immune cells, phagocytosis, and direct lysis of microbial invaders. Insects are excellent models for dissecting the molecular basis of innate immune recognition and response to a wide range of microbial infections. Impressive progress in recent years has generated crucial information on the role of TEPs in the antibacterial and antiparasite response of the tractable model insect Drosophila melanogaster and the mosquito malaria vector Anopheles gambiae. This knowledge is critical for better understanding the evolution of TEPs and their involvement in the regulation of the host innate immune system.

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.

Cyclin B1 Destruction Box-Mediated Protein Instability: The Enhanced Sensitivity of Fluorescent-Protein-Based Reporter Gene System

Directory of Open Access Journals (Sweden)

Chao-Hsun Yang

2013-01-01

Full Text Available The periodic expression and destruction of several cyclins are the most important steps for the exact regulation of cell cycle. Cyclins are degraded by the ubiquitin-proteasome system during cell cycle. Besides, a short sequence near the N-terminal of cyclin B called the destruction box (D-box; CDB is also required. Fluorescent-protein-based reporter gene system is insensitive to analysis because of the overly stable fluorescent proteins. Therefore, in this study, we use human CDB fused with both enhanced green fluorescent protein (EGFP at C-terminus and red fluorescent protein (RFP, DsRed at N-terminus in the transfected human melanoma cells to examine the effects of CDB on different fluorescent proteins. Our results indicated that CDB-fused fluorescent protein can be used to examine the slight gene regulations in the reporter gene system and have the potential to be the system for screening of functional compounds in the future.

A Bacillus megaterium System for the Production of Recombinant Proteins and Protein Complexes.

Science.gov (United States)

Biedendieck, Rebekka

2016-01-01

For many years the Gram-positive bacterium Bacillus megaterium has been used for the production and secretion of recombinant proteins. For this purpose it was systematically optimized. Plasmids with different inducible promoter systems, with different compatible origins, with small tags for protein purification and with various specific signals for protein secretion were combined with genetically improved host strains. Finally, the development of appropriate cultivation conditions for the production strains established this organism as a bacterial cell factory even for large proteins. Along with the overproduction of individual proteins the organism is now also used for the simultaneous coproduction of up to 14 recombinant proteins, multiple subsequently interacting or forming protein complexes. Some of these recombinant strains are successfully used for bioconversion or the biosynthesis of valuable components including vitamins. The titers in the g per liter scale for the intra- and extracellular recombinant protein production prove the high potential of B. megaterium for industrial applications. It is currently further enhanced for the production of recombinant proteins and multi-subunit protein complexes using directed genetic engineering approaches based on transcriptome, proteome, metabolome and fluxome data.

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.

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.

Non-linear feedback control of the p53 protein-mdm2 inhibitor system using the derivative-free non-linear Kalman filter.

Science.gov (United States)

Rigatos, Gerasimos G

2016-06-01

It is proven that the model of the p53-mdm2 protein synthesis loop is a differentially flat one and using a diffeomorphism (change of state variables) that is proposed by differential flatness theory it is shown that the protein synthesis model can be transformed into the canonical (Brunovsky) form. This enables the design of a feedback control law that maintains the concentration of the p53 protein at the desirable levels. To estimate the non-measurable elements of the state vector describing the p53-mdm2 system dynamics, the derivative-free non-linear Kalman filter is used. Moreover, to compensate for modelling uncertainties and external disturbances that affect the p53-mdm2 system, the derivative-free non-linear Kalman filter is re-designed as a disturbance observer. The derivative-free non-linear Kalman filter consists of the Kalman filter recursion applied on the linearised equivalent of the protein synthesis model together with an inverse transformation based on differential flatness theory that enables to retrieve estimates for the state variables of the initial non-linear model. The proposed non-linear feedback control and perturbations compensation method for the p53-mdm2 system can result in more efficient chemotherapy schemes where the infusion of medication will be better administered.

Genome-scale analysis of the high-efficient protein secretion system of Aspergillus oryzae

DEFF Research Database (Denmark)

Liu, Lifang; Feizi, Amir; Osterlund, Tobias

2014-01-01

related fungal species such as Aspergillus nidulans and Aspergillus niger. To evaluate the defined component list, we performed transcriptome analysis on three a-amylase over-producing strains with varying levels of secretion capacities. Specifically, secretory components involved in the ER......Background: The koji mold, Aspergillus oryzae is widely used for the production of industrial enzymes due to its particularly high protein secretion capacity and ability to perform post-translational modifications. However, systemic analysis of its secretion system is lacking, generally due...... to the poorly annotated proteome. Results: Here we defined a functional protein secretory component list of A. oryzae using a previously reported secretory model of S. cerevisiae as scaffold. Additional secretory components were obtained by blast search with the functional components reported in other closely...

Model test on the relationship feed energy and protein ratio to the production and quality of milk protein

Science.gov (United States)

Hartanto, R.; Jantra, M. A. C.; Santosa, S. A. B.; Purnomoadi, A.

2018-01-01

The purpose of this research was to find an appropriate relationship model between the feed energy and protein ratio with the amount of production and quality of milk proteins. This research was conducted at Getasan Sub-district, Semarang Regency, Central Java Province, Indonesia using 40 samples (Holstein Friesian cattle, lactation period II-III and lactation month 3-4). Data were analyzed using linear and quadratic regressions, to predict the production and quality of milk protein from feed energy and protein ratio that describe the diet. The significance of model was tested using analysis of variance. Coefficient of determination (R2), residual variance (RV) and root mean square prediction error (RMSPE) were reported for the developed equations as an indicator of the goodness of model fit. The results showed no relationship in milk protein (kg), milk casein (%), milk casein (kg) and milk urea N (mg/dl) as function of CP/TDN. The significant relationship was observed in milk production (L or kg) and milk protein (%) as function of CP/TDN, both in linear and quadratic models. In addition, a quadratic change in milk production (L) (P = 0.003), milk production (kg) (P = 0.003) and milk protein concentration (%) (P = 0.026) were observed with increase of CP/TDN. It can be concluded that quadratic equation was the good fitting model for this research, because quadratic equation has larger R2, smaller RV and smaller RMSPE than those of linear equation.

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.

Protein S-sulfhydration by hydrogen sulfide in cardiovascular system.

Science.gov (United States)

Meng, Guoliang; Zhao, Shuang; Xie, Liping; Han, Yi; Ji, Yong

2018-04-01

Hydrogen sulfide (H 2 S), independently of any specific transporters, has a number of biological effects on the cardiovascular system. However, until now, the detailed mechanism of H 2 S was not clear. Recently, a novel post-translational modification induced by H 2 S, named S-sulfhydration, has been proposed. S-sulfhydration is the chemical modification of specific cysteine residues of target proteins by H 2 S. There are several methods for detecting S-sulfhydration, such as the modified biotin switch assay, maleimide assay with fluorescent thiol modifying regents, tag-switch method and mass spectrometry. H 2 S induces S-sulfhydration on enzymes or receptors (such as p66Shc, phospholamban, protein tyrosine phosphatase 1B, mitogen-activated extracellular signal-regulated kinase 1 and ATP synthase subunit α), transcription factors (such as specific protein-1, kelch-like ECH-associating protein 1, NF-κB and interferon regulatory factor-1), and ion channels (such as voltage-activated Ca 2+ channels, transient receptor potential channels and ATP-sensitive K + channels) in the cardiovascular system. Although significant progress has been achieved in delineating the role of protein S-sulfhydration by H 2 S in the cardiovascular system, more proteins with detailed cysteine sites of S-sulfhydration as well as physiological function need to be investigated in further studies. This review mainly summarizes the role and possible mechanism of S-sulfhydration in the cardiovascular system. The S-sulfhydrated proteins may be potential novel targets for therapeutic intervention and drug design in the cardiovascular system, which may accelerate the development and application of H 2 S-related drugs in the future. This article is part of a themed section on Spotlight on Small Molecules in Cardiovascular Diseases. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v175.8/issuetoc. © 2017 The British Pharmacological Society.

Multi-component adsorption model for pellicle formation: the influence of salivary proteins and non-salivary phospho proteins on the binding of histatin 5 onto hydroxyapatite.

Science.gov (United States)

Yin, A; Margolis, H C; Yao, Y; Grogan, J; Oppenheim, F G

2006-02-01

The acquired enamel pellicle formed by selective adsorption of proteins in whole saliva is a protective integument on the tooth surface. The purpose of the present study was to investigate the formation of human acquired enamel pellicle using an in vitro hydroxyapatite (HA) model and 3H-histatin 5 to allow accurate measurement of histatin 5 binding in a multi-component experimental system. A binary system was employed by mixing 3H-histatin 5 with one unlabeled protein prior to incubation with HA or by first incubating 3H-histatin 5 with the HA which had been pre-coated with one of a panel of unlabeled proteins (human albumin, salivary amylase, lysozyme, acidic PIFs, statherin, the N-terminal fragment of statherin, and egg yolk phosvitin). A ternary system was employed by mixing 3H-histatin 5 with HA sequentially pre-coated with two different unlabeled proteins, including recombinant histatin 1. The results showed that only salivary statherin and egg yolk phosvitin promote histatin 5 adsorption significantly. The amount of histatin 5 adsorbed was also found to increase as a function of the amount of phosvitin and statherin used to pre-coat HA up to a maximum level that was two- to four-fold greater than that observed on untreated HA. These data suggest that specific protein-protein interactions may play important roles in pellicle formation in vivo.

Protein structure analysis using the resonant recognition model and wavelet transforms

International Nuclear Information System (INIS)

Fang, Q.; Cosic, I.

1998-01-01

An approach based on the resonant recognition model and the discrete wavelet transform is introduced here for characterising proteins' biological function. The protein sequence is converted into a numerical series by assigning the electron-ion interaction potential to each amino acid from N-terminal to C-terminal. A set of peaks is found after performing a wavelet transform onto a numerical series representing a group of homologous proteins. These peaks are related to protein structural and functional properties and named characteristic vector of that protein group. Further more, the amino acids contributing mostly to a protein's biological functions, the so-called 'hot spots' amino acids, are predicted by the continuous wavelet transform. It is found that the hot spots are clustered around the protein's cleft structure. The wavelets approach provides a novel methods for amino acid sequence analysis as well as an expansion for the newly established macromolecular interaction model: the resonant recognition model. Copyright (1998) Australasian Physical and Engineering Sciences in Medicine

A Systems Model of Parkinson's Disease Using Biochemical Systems Theory.

Science.gov (United States)

Sasidharakurup, Hemalatha; Melethadathil, Nidheesh; Nair, Bipin; Diwakar, Shyam

2017-08-01

Parkinson's disease (PD), a neurodegenerative disorder, affects millions of people and has gained attention because of its clinical roles affecting behaviors related to motor and nonmotor symptoms. Although studies on PD from various aspects are becoming popular, few rely on predictive systems modeling approaches. Using Biochemical Systems Theory (BST), this article attempts to model and characterize dopaminergic cell death and understand pathophysiology of progression of PD. PD pathways were modeled using stochastic differential equations incorporating law of mass action, and initial concentrations for the modeled proteins were obtained from literature. Simulations suggest that dopamine levels were reduced significantly due to an increase in dopaminergic quinones and 3,4-dihydroxyphenylacetaldehyde (DOPAL) relating to imbalances compared to control during PD progression. Associating to clinically observed PD-related cell death, simulations show abnormal parkin and reactive oxygen species levels with an increase in neurofibrillary tangles. While relating molecular mechanistic roles, the BST modeling helps predicting dopaminergic cell death processes involved in the progression of PD and provides a predictive understanding of neuronal dysfunction for translational neuroscience.

Global low-frequency motions in protein allostery: CAP as a model system.

Science.gov (United States)

Townsend, Philip D; Rodgers, Thomas L; Pohl, Ehmke; Wilson, Mark R; McLeish, Tom C B; Cann, Martin J

2015-06-01

Allostery is a fundamental process by which ligand binding to a protein alters its activity at a distant site. There is considerable evidence that allosteric cooperativity can be communicated by the modulation of protein dynamics without conformational change. The Catabolite Activator Protein (CAP) of Escherichia coli is an important experimental exemplar for entropically driven allostery. Here we discuss recent experimentally supported theoretical analysis that highlights the role of global low-frequency dynamics in allostery in CAP and identify how allostery arises as a natural consequence of changes in global low-frequency protein fluctuations on ligand binding.

A generative, probabilistic model of local protein structure

DEFF Research Database (Denmark)

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

2008-01-01

Despite significant progress in recent years, protein structure prediction maintains its status as one of the prime unsolved problems in computational biology. One of the key remaining challenges is an efficient probabilistic exploration of the structural space that correctly reflects the relative...... conformational stabilities. Here, we present a fully probabilistic, continuous model of local protein structure in atomic detail. The generative model makes efficient conformational sampling possible and provides a framework for the rigorous analysis of local sequence-structure correlations in the native state...

SUPPLEMENTARY FEEDING ON THE NUTRIENT BALANCE OF LACTATING DAIRY COW AT CONTRASTING TEMPERATURE REGIMES: ASSESSMENT USING CORNELL NET CARBOHYDRATE AND PROTEIN SYSTEM (CNCPS) MODEL

OpenAIRE

A. Jayanegara; A. Sofyan

2014-01-01

Dairy cows often do not receive adequate nutrient supply during their lactation period. This condition caneven be worse if the environmental temperature is not in comfortable range which may occur especially intropical regions. The present research was aimed to simulate the effect of supplementary feeding on nutrientbalance of lactating dairy cow at contrasting temperature regimes using Cornell Net Carbohydrate andProtein System (CNCPS) model. Treatments consisted of feeds (R1: Pennisetum pur...

Absorption tuning of the green fluorescent protein chromophore: synthesis and studies of model compounds

DEFF Research Database (Denmark)

Brøndsted Nielsen, Mogens; Andersen, Lars Henrik; Rinza, Tomás Rocha

2011-01-01

The green fluorescent protein (GFP) chromophore is a heterocyclic compound containing a p-hydroxybenzylidine attached to an imidazol-5(4H)-one ring. This review covers the synthesis of a variety of model systems for elucidating the intrinsic optical properties of the chromophore in the gas phase ...

Prediction of RNA-Binding Proteins by Voting Systems

Directory of Open Access Journals (Sweden)

C. R. Peng

2011-01-01

Full Text Available It is important to identify which proteins can interact with RNA for the purpose of protein annotation, since interactions between RNA and proteins influence the structure of the ribosome and play important roles in gene expression. This paper tries to identify proteins that can interact with RNA using voting systems. Firstly through Weka, 34 learning algorithms are chosen for investigation. Then simple majority voting system (SMVS is used for the prediction of RNA-binding proteins, achieving average ACC (overall prediction accuracy value of 79.72% and MCC (Matthew’s correlation coefficient value of 59.77% for the independent testing dataset. Then mRMR (minimum redundancy maximum relevance strategy is used, which is transferred into algorithm selection. In addition, the MCC value of each classifier is assigned to be the weight of the classifier’s vote. As a result, best average MCC values are attained when 22 algorithms are selected and integrated through weighted votes, which are 64.70% for the independent testing dataset, and ACC value is 82.04% at this moment.

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.

Conformational Sampling in Template-Free Protein Loop Structure Modeling: An Overview

OpenAIRE

Li, Yaohang

2013-01-01

Accurately modeling protein loops is an important step to predict three-dimensional structures as well as to understand functions of many proteins. Because of their high flexibility, modeling the three-dimensional structures of loops is difficult and is usually treated as a “mini protein folding problem” under geometric constraints. In the past decade, there has been remarkable progress in template-free loop structure modeling due to advances of computational methods as well as stably increas...

Salivary protein levels as a predictor of perceived astringency in model systems and solid foods.

Science.gov (United States)

Fleming, Erin E; Ziegler, Gregory R; Hayes, John E

2016-09-01

Salivary protein difference value (SP D-value) is a quantitative measure of salivary protein replenishment, which reportedly relates to individual differences in perceived astringency. This in vitro measure is calculated as the difference in total salivary protein before (S1) and after (S2) stimulation with tannic acid, with a greater absolute value (S2-S1) indicating less protein replenishment. Others report that this measure predicts perceived astringency and liking of liquid model systems and beverages containing added polyphenols. Whether this relationship generalizes to astringent compounds other than polyphenols, or to solid foods is unknown. Here, the associations between SP D-values and perceived astringency and overall liking/disliking for alum and tannic acid (experiment 1) as well as solid chocolate-flavored compound coating with added tannic acid or grape seed extract (GSE) (experiment 2) were examined. In both experiments, participants (n=84 and 81, respectively) indicated perceived intensity of astringency, bitterness, sweetness, and sourness, and degree of liking of either aqueous solutions, or solid chocolate-flavored compound coating with added astringents. Data were analyzed via linear regression, and as discrete groups for comparison to prior work. Three discrete groups were formed based on first and third quartile splits of the SP D-value distribution: low (LR), medium (MR), and high responding (HR) individuals. In experiment 1, significantly higher mean astringency ratings were observed for the HR as compared to the LR/MR groups for alum and tannic acid, confirming and extending prior work. In experiment 2, significantly higher mean astringency ratings were also observed for HR as compared to LR groups in solid chocolate-flavored compound containing added tannic acid or GSE. Significant differences in liking were found between HR and LR groups for alum and tannic acid in water, but no significant differences in liking were observed for

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.

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.

A systems biology strategy to identify molecular mechanisms of action and protein indicators of traumatic brain injury.

Science.gov (United States)

Yu, Chenggang; Boutté, Angela; Yu, Xueping; Dutta, Bhaskar; Feala, Jacob D; Schmid, Kara; Dave, Jitendra; Tawa, Gregory J; Wallqvist, Anders; Reifman, Jaques

2015-02-01

The multifactorial nature of traumatic brain injury (TBI), especially the complex secondary tissue injury involving intertwined networks of molecular pathways that mediate cellular behavior, has confounded attempts to elucidate the pathology underlying the progression of TBI. Here, systems biology strategies are exploited to identify novel molecular mechanisms and protein indicators of brain injury. To this end, we performed a meta-analysis of four distinct high-throughput gene expression studies involving different animal models of TBI. By using canonical pathways and a large human protein-interaction network as a scaffold, we separately overlaid the gene expression data from each study to identify molecular signatures that were conserved across the different studies. At 24 hr after injury, the significantly activated molecular signatures were nonspecific to TBI, whereas the significantly suppressed molecular signatures were specific to the nervous system. In particular, we identified a suppressed subnetwork consisting of 58 highly interacting, coregulated proteins associated with synaptic function. We selected three proteins from this subnetwork, postsynaptic density protein 95, nitric oxide synthase 1, and disrupted in schizophrenia 1, and hypothesized that their abundance would be significantly reduced after TBI. In a penetrating ballistic-like brain injury rat model of severe TBI, Western blot analysis confirmed our hypothesis. In addition, our analysis recovered 12 previously identified protein biomarkers of TBI. The results suggest that systems biology may provide an efficient, high-yield approach to generate testable hypotheses that can be experimentally validated to identify novel mechanisms of action and molecular indicators of TBI. © 2014 The Authors. Journal of Neuroscience Research Published by Wiley Periodicals, Inc.

Protein structure modeling for CASP10 by multiple layers of global optimization.

Science.gov (United States)

Joo, Keehyoung; Lee, Juyong; Sim, Sangjin; Lee, Sun Young; Lee, Kiho; Heo, Seungryong; Lee, In-Ho; Lee, Sung Jong; Lee, Jooyoung

2014-02-01

In the template-based modeling (TBM) category of CASP10 experiment, we introduced a new protocol called protein modeling system (PMS) to generate accurate protein structures in terms of side-chains as well as backbone trace. In the new protocol, a global optimization algorithm, called conformational space annealing (CSA), is applied to the three layers of TBM procedure: multiple sequence-structure alignment, 3D chain building, and side-chain re-modeling. For 3D chain building, we developed a new energy function which includes new distance restraint terms of Lorentzian type (derived from multiple templates), and new energy terms that combine (physical) energy terms such as dynamic fragment assembly (DFA) energy, DFIRE statistical potential energy, hydrogen bonding term, etc. These physical energy terms are expected to guide the structure modeling especially for loop regions where no template structures are available. In addition, we developed a new quality assessment method based on random forest machine learning algorithm to screen templates, multiple alignments, and final models. For TBM targets of CASP10, we find that, due to the combination of three stages of CSA global optimizations and quality assessment, the modeling accuracy of PMS improves at each additional stage of the protocol. It is especially noteworthy that the side-chains of the final PMS models are far more accurate than the models in the intermediate steps. Copyright © 2013 Wiley Periodicals, Inc.

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.

Protein homology model refinement by large-scale energy optimization.

Science.gov (United States)

Park, Hahnbeom; Ovchinnikov, Sergey; Kim, David E; DiMaio, Frank; Baker, David

2018-03-20

Proteins fold to their lowest free-energy structures, and hence the most straightforward way to increase the accuracy of a partially incorrect protein structure model is to search for the lowest-energy nearby structure. This direct approach has met with little success for two reasons: first, energy function inaccuracies can lead to false energy minima, resulting in model degradation rather than improvement; and second, even with an accurate energy function, the search problem is formidable because the energy only drops considerably in the immediate vicinity of the global minimum, and there are a very large number of degrees of freedom. Here we describe a large-scale energy optimization-based refinement method that incorporates advances in both search and energy function accuracy that can substantially improve the accuracy of low-resolution homology models. The method refined low-resolution homology models into correct folds for 50 of 84 diverse protein families and generated improved models in recent blind structure prediction experiments. Analyses of the basis for these improvements reveal contributions from both the improvements in conformational sampling techniques and the energy function.

NatalieQ: A web server for protein-protein interaction network querying

NARCIS (Netherlands)

El-Kebir, M.; Brandt, B.W.; Heringa, J.; Klau, G.W.

2014-01-01

Background Molecular interactions need to be taken into account to adequately model the complex behavior of biological systems. These interactions are captured by various types of biological networks, such as metabolic, gene-regulatory, signal transduction and protein-protein interaction networks.

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

A simple quantitative model of macromolecular crowding effects on protein folding: Application to the murine prion protein(121-231)

Science.gov (United States)

Bergasa-Caceres, Fernando; Rabitz, Herschel A.

2013-06-01

A model of protein folding kinetics is applied to study the effects of macromolecular crowding on protein folding rate and stability. Macromolecular crowding is found to promote a decrease of the entropic cost of folding of proteins that produces an increase of both the stability and the folding rate. The acceleration of the folding rate due to macromolecular crowding is shown to be a topology-dependent effect. The model is applied to the folding dynamics of the murine prion protein (121-231). The differential effect of macromolecular crowding as a function of protein topology suffices to make non-native configurations relatively more accessible.

The ESX system in Bacillus subtilis mediates protein secretion.

Directory of Open Access Journals (Sweden)

Laura A Huppert

Full Text Available Esat-6 protein secretion systems (ESX or Ess are required for the virulence of several human pathogens, most notably Mycobacterium tuberculosis and Staphylococcus aureus. These secretion systems are defined by a conserved FtsK/SpoIIIE family ATPase and one or more WXG100 family secreted substrates. Gene clusters coding for ESX systems have been identified amongst many organisms including the highly tractable model system, Bacillus subtilis. In this study, we demonstrate that the B. subtilis yuk/yue locus codes for a nonessential ESX secretion system. We develop a functional secretion assay to demonstrate that each of the locus gene products is specifically required for secretion of the WXG100 virulence factor homolog, YukE. We then employ an unbiased approach to search for additional secreted substrates. By quantitative profiling of culture supernatants, we find that YukE may be the sole substrate that depends on the FtsK/SpoIIIE family ATPase for secretion. We discuss potential functional implications for secretion of a unique substrate.

Possibilities of microscopic detection of isolated porcine proteins in model meat products

Directory of Open Access Journals (Sweden)

Michaela Petrášová

2016-05-01

Full Text Available In recent years, various protein additives intended for manufacture of meat products have increasing importance in the food industry. These ingredients include both, plant-origin as well as animal-origin proteins. Among animal proteins, blood plasma, milk protein or collagen are used most commonly. Collagen is obtained from pork, beef, and poultry or fish skin. Collagen does not contain all the essential amino acids, thus it is not a full protein in terms of essential amino acids supply for one's organism. However, it is rather rich in amino acids of glycine, hydroxyproline and proline which are almost absent in other proteins and their synthesis is very energy intensive. Collagen, which is added to the soft and small meat products in the form of isolated porcine protein, significantly affects the organoleptic properties of these products. This work focused on detection of isolated porcine protein in model meat products where detection of isolated porcine protein was verified by histological staining and light microscopy. Seven model meat products from poultry meat and 7 model meat products from beef and pork in the ratio of 1:1, which contained 2.5% concentration of various commercially produced isolated porcine proteins, were examined. These model meat products were histologically processed by means of cryosections and stained with hematoxylin-eosin staining, toluidine blue staining and Calleja. For the validation phase, Calleja was utilized. To determine the sensitivity and specificity, five model meat products containing the addition of isolated porcine protein and five model meat products free of it were used. The sensitivity was determined for isolated porcine protein at 1.00 and specificity was determined at 1.00. The detection limit of the method was at the level of 0.001% addition. Repeatability of the method was carried out using products with addition as well as without addition of isolated porcine protein and detection was repeated

Revisiting the description of Protein-Protein interfaces. Part II: Experimental study

OpenAIRE

Cazals , Frédéric; Proust , Flavien

2006-01-01

This paper provides a detailed experimental study of an interface model developed in the companion article F. Cazals and F. Proust, Revisiting the description of Protein-Protein interfaces. Part I: algorithms. Our experimental study is concerned with the usual database of protein-protein complexes, split into five families (Proteases, Immune system, Enzyme Complexes, Signal transduction, Misc.) Our findings, which bear some contradictions with usual statements are the following: (i)Connectivi...

A linear programming model for protein inference problem in shotgun proteomics.

Science.gov (United States)

Huang, Ting; He, Zengyou

2012-11-15

Assembling peptides identified from tandem mass spectra into a list of proteins, referred to as protein inference, is an important issue in shotgun proteomics. The objective of protein inference is to find a subset of proteins that are truly present in the sample. Although many methods have been proposed for protein inference, several issues such as peptide degeneracy still remain unsolved. In this article, we present a linear programming model for protein inference. In this model, we use a transformation of the joint probability that each peptide/protein pair is present in the sample as the variable. Then, both the peptide probability and protein probability can be expressed as a formula in terms of the linear combination of these variables. Based on this simple fact, the protein inference problem is formulated as an optimization problem: minimize the number of proteins with non-zero probabilities under the constraint that the difference between the calculated peptide probability and the peptide probability generated from peptide identification algorithms should be less than some threshold. This model addresses the peptide degeneracy issue by forcing some joint probability variables involving degenerate peptides to be zero in a rigorous manner. The corresponding inference algorithm is named as ProteinLP. We test the performance of ProteinLP on six datasets. Experimental results show that our method is competitive with the state-of-the-art protein inference algorithms. The source code of our algorithm is available at: https://sourceforge.net/projects/prolp/. zyhe@dlut.edu.cn. Supplementary data are available at Bioinformatics Online.

Identify High-Quality Protein Structural Models by Enhanced K-Means.

Science.gov (United States)

Wu, Hongjie; Li, Haiou; Jiang, Min; Chen, Cheng; Lv, Qiang; Wu, Chuang

2017-01-01

Background. One critical issue in protein three-dimensional structure prediction using either ab initio or comparative modeling involves identification of high-quality protein structural models from generated decoys. Currently, clustering algorithms are widely used to identify near-native models; however, their performance is dependent upon different conformational decoys, and, for some algorithms, the accuracy declines when the decoy population increases. Results. Here, we proposed two enhanced K -means clustering algorithms capable of robustly identifying high-quality protein structural models. The first one employs the clustering algorithm SPICKER to determine the initial centroids for basic K -means clustering ( SK -means), whereas the other employs squared distance to optimize the initial centroids ( K -means++). Our results showed that SK -means and K -means++ were more robust as compared with SPICKER alone, detecting 33 (59%) and 42 (75%) of 56 targets, respectively, with template modeling scores better than or equal to those of SPICKER. Conclusions. We observed that the classic K -means algorithm showed a similar performance to that of SPICKER, which is a widely used algorithm for protein-structure identification. Both SK -means and K -means++ demonstrated substantial improvements relative to results from SPICKER and classical K -means.

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.

Intracellular Protein Delivery System Using a Target-Specific Repebody and Translocation Domain of Bacterial Exotoxin.

Science.gov (United States)

Kim, Hee-Yeon; Kang, Jung Ae; Ryou, Jeong-Hyun; Lee, Gyeong Hee; Choi, Dae Seong; Lee, Dong Eun; Kim, Hak-Sung

2017-11-17

With the high efficacy of protein-based therapeutics and plenty of intracellular drug targets, cytosolic protein delivery in a cell-specific manner has attracted considerable attention in the field of precision medicine. Herein, we present an intracellular protein delivery system based on a target-specific repebody and the translocation domain of Pseudomonas aeruginosa exotoxin A. The delivery platform was constructed by genetically fusing an EGFR-specific repebody as a targeting moiety to the translocation domain, while a protein cargo was fused to the C-terminal end of the delivery platform. The delivery platform was revealed to efficiently translocate a protein cargo to the cytosol in a target-specific manner. We demonstrate the utility and potential of the delivery platform by showing a remarkable tumor regression with negligible toxicity in a xenograft mice model when gelonin was used as the cytotoxic protein cargo. The present platform can find wide applications to the cell-selective cytosolic delivery of diverse proteins in many areas.

NASCENT: an automatic protein interaction network generation tool for non-model organisms.

Science.gov (United States)

Banky, Daniel; Ordog, Rafael; Grolmusz, Vince

2009-04-24

Large quantity of reliable protein interaction data are available for model organisms in public depositories (e.g., MINT, DIP, HPRD, INTERACT). Most data correspond to experiments with the proteins of Saccharomyces cerevisiae, Drosophila melanogaster, Homo sapiens, Caenorhabditis elegans, Escherichia coli and Mus musculus. For other important organisms the data availability is poor or non-existent. Here we present NASCENT, a completely automatic web-based tool and also a downloadable Java program, capable of modeling and generating protein interaction networks even for non-model organisms. The tool performs protein interaction network modeling through gene-name mapping, and outputs the resulting network in graphical form and also in computer-readable graph-forms, directly applicable by popular network modeling software. http://nascent.pitgroup.org.

Strategies for production of active eukaryotic proteins in bacterial expression system

Institute of Scientific and Technical Information of China (English)

Orawan Khow; Sunutcha Suntrarachun

2012-01-01

Bacteria have long been the favorite expression system for recombinant protein production. However, the flaw of the system is that insoluble and inactive proteins are co-produced due to codon bias, protein folding, phosphorylation, glycosylation, mRNA stability and promoter strength. Factors are cited and the methods to convert to soluble and active proteins are described, for example a tight control of Escherichia coli milieu, refolding from inclusion body and through fusion technology.

DeepQA: Improving the estimation of single protein model quality with deep belief networks

OpenAIRE

Cao, Renzhi; Bhattacharya, Debswapna; Hou, Jie; Cheng, Jianlin

2016-01-01

Background Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality of a single protein model, which is important for selecting a few good models out of a large model pool consisting of mostly low-quality models, is still a largely unsolved problem. Results We introduce a novel single-model quality assessment method DeepQA based on deep belie...

A semi-nonparametric mixture model for selecting functionally consistent proteins.

Science.gov (United States)

Yu, Lianbo; Doerge, Rw

2010-09-28

High-throughput technologies have led to a new era of proteomics. Although protein microarray experiments are becoming more common place there are a variety of experimental and statistical issues that have yet to be addressed, and that will carry over to new high-throughput technologies unless they are investigated. One of the largest of these challenges is the selection of functionally consistent proteins. We present a novel semi-nonparametric mixture model for classifying proteins as consistent or inconsistent while controlling the false discovery rate and the false non-discovery rate. The performance of the proposed approach is compared to current methods via simulation under a variety of experimental conditions. We provide a statistical method for selecting functionally consistent proteins in the context of protein microarray experiments, but the proposed semi-nonparametric mixture model method can certainly be generalized to solve other mixture data problems. The main advantage of this approach is that it provides the posterior probability of consistency for each protein.

Fast Proton Titration Scheme for Multiscale Modeling of Protein Solutions.

Science.gov (United States)

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

2010-10-12

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

Ternary diagram of extract proteins / solvent systems: Sesame, soybean and lupine proteins

Directory of Open Access Journals (Sweden)

Mohamed, S. S.

2004-09-01

Full Text Available Solvent extraction as a method of extracting protein from oilseed meals offers the advantage of higher efficiency. Unfortunately, the published literature points to the gap in the work concerned with the necessary equilibrium diagram to design due process equipment for such extracts. Initiated by this lack of basic knowledge, the present study has been undertaken to provide the equilibrium data for three different ternary systems, namely: sesame protein / sodium hydroxide solution system, soybean protein / sodium hydroxide solution system and lupine protein / sodium hydroxide solution system. These oilseed meals were selected because of their high protein content (53.4 %, 46.2 % and 42.3 % protein, respectively. The study also concentrated on the evaluation of the major parameters affecting the extraction process, i.e. the normality of the sodium hydroxide solution used as extracting solvent and the initial oilseed solvent to meal feeding ratio. The results obtained indicate that the best normality of sodium hydroxide solution used for extracting soybean and lupine protein is 0.02N, while 0.04N solution is required for extracting sesame protein. Also, operating at a liquid to solid feed ratio of 30:1 and 50:1 for soybean, sesame and lupine, respectively, is enough to reach a high protein extract. Correlations were presented for each locus of under flow compositions, graphically acquired, and the data are compared with those calculated by analytical solutions.La extracción con disolventes es un método de extracción de proteínas de las harinas de semillas oleaginosas que ofrece la ventaja de su elevada eficacia. Desafortunadamente, la bibliografía coincide en el vacío existente con respecto a los diagramas de equilibrio necesarios para el diseño de los equipos adecuados. Debido a esta falta de conocimientos, el presente estudio se ha llevado a cabo para obtener datos de tres sistemas ternarios: sistema proteína de sésamo / disolución de

Genome-scale modeling of the protein secretory machinery in yeast

DEFF Research Database (Denmark)

Feizi, Amir; Österlund, Tobias; Petranovic, Dina

2013-01-01

The protein secretory machinery in Eukarya is involved in post-translational modification (PTMs) and sorting of the secretory and many transmembrane proteins. While the secretory machinery has been well-studied using classic reductionist approaches, a holistic view of its complex nature is lacking....... Here, we present the first genome-scale model for the yeast secretory machinery which captures the knowledge generated through more than 50 years of research. The model is based on the concept of a Protein Specific Information Matrix (PSIM: characterized by seven PTMs features). An algorithm...

Prediction of thermodynamic instabilities of protein solutions from simple protein–protein interactions

International Nuclear Information System (INIS)

D’Agostino, Tommaso; Solana, José Ramón; Emanuele, Antonio

2013-01-01

Highlights: ► We propose a model of effective protein–protein interaction embedding solvent effects. ► A previous square-well model is enhanced by giving to the interaction a free energy character. ► The temperature dependence of the interaction is due to entropic effects of the solvent. ► The validity of the original SW model is extended to entropy driven phase transitions. ► We get good fits for lysozyme and haemoglobin spinodal data taken from literature. - Abstract: Statistical thermodynamics of protein solutions is often studied in terms of simple, microscopic models of particles interacting via pairwise potentials. Such modelling can reproduce the short range structure of protein solutions at equilibrium and predict thermodynamics instabilities of these systems. We introduce a square well model of effective protein–protein interaction that embeds the solvent’s action. We modify an existing model [45] by considering a well depth having an explicit dependence on temperature, i.e. an explicit free energy character, thus encompassing the statistically relevant configurations of solvent molecules around proteins. We choose protein solutions exhibiting demixing upon temperature decrease (lysozyme, enthalpy driven) and upon temperature increase (haemoglobin, entropy driven). We obtain satisfactory fits of spinodal curves for both the two proteins without adding any mean field term, thus extending the validity of the original model. Our results underline the solvent role in modulating or stretching the interaction potential

Genome-scale analysis of the high-efficient protein secretion system of Aspergillus oryzae.

Science.gov (United States)

Liu, Lifang; Feizi, Amir; Österlund, Tobias; Hjort, Carsten; Nielsen, Jens

2014-06-24

The koji mold, Aspergillus oryzae is widely used for the production of industrial enzymes due to its particularly high protein secretion capacity and ability to perform post-translational modifications. However, systemic analysis of its secretion system is lacking, generally due to the poorly annotated proteome. Here we defined a functional protein secretory component list of A. oryzae using a previously reported secretory model of S. cerevisiae as scaffold. Additional secretory components were obtained by blast search with the functional components reported in other closely related fungal species such as Aspergillus nidulans and Aspergillus niger. To evaluate the defined component list, we performed transcriptome analysis on three α-amylase over-producing strains with varying levels of secretion capacities. Specifically, secretory components involved in the ER-associated processes (including components involved in the regulation of transport between ER and Golgi) were significantly up-regulated, with many of them never been identified for A. oryzae before. Furthermore, we defined a complete list of the putative A. oryzae secretome and monitored how it was affected by overproducing amylase. In combination with the transcriptome data, the most complete secretory component list and the putative secretome, we improved the systemic understanding of the secretory machinery of A. oryzae in response to high levels of protein secretion. The roles of many newly predicted secretory components were experimentally validated and the enriched component list provides a better platform for driving more mechanistic studies of the protein secretory pathway in this industrially important fungus.

System and methods for predicting transmembrane domains in membrane proteins and mining the genome for recognizing G-protein coupled receptors

Science.gov (United States)

Trabanino, Rene J; Vaidehi, Nagarajan; Hall, Spencer E; Goddard, William A; Floriano, Wely

2013-02-05

The invention provides computer-implemented methods and apparatus implementing a hierarchical protocol using multiscale molecular dynamics and molecular modeling methods to predict the presence of transmembrane regions in proteins, such as G-Protein Coupled Receptors (GPCR), and protein structural models generated according to the protocol. The protocol features a coarse grain sampling method, such as hydrophobicity analysis, to provide a fast and accurate procedure for predicting transmembrane regions. Methods and apparatus of the invention are useful to screen protein or polynucleotide databases for encoded proteins with transmembrane regions, such as GPCRs.

A transgenic model of transactivation by the Tax protein of HTLV-I.

Science.gov (United States)

Bieberich, C J; King, C M; Tinkle, B T; Jay, G

1993-09-01

The human T-lymphotropic virus type I (HTLV-I) Tax protein is a transcriptional regulatory protein that has been suggested to play a causal role in the development of several HTLV-I-associated diseases. Tax regulates expression of its own LTR and of certain cellular promoters perhaps by usurping the function of the host transcriptional machinery. We have established a transgenic mouse model system to define the spectrum of tissues in vivo that are capable of supporting Tax-mediated transcriptional transactivation. Transgenic mice carrying the HTLV-I LTR driving expression of the Escherichia coli beta-galactosidase (beta gal) gene were generated, and this LTR-beta gal gene was transcriptionally inactive in all tissues. When LTR-beta gal mice were mated to transgenic mice carrying the same LTR driving expression of the HTLV-I tax gene, mice that carried both transgenes showed restricted expression of the beta gal reporter gene in several tissues including muscle, bone, salivary glands, skin, and nerve. In addition, a dramatic increase in the number of beta gal-expressing cells was seen in response to wounding. These observations provide direct evidence for viral transactivation in vivo, delimit the tissues capable of supporting that transactivation, and provide a model system to study the mechanism of gene regulation by Tax.

The Phyre2 web portal for protein modeling, prediction and analysis.

Science.gov (United States)

Kelley, Lawrence A; Mezulis, Stefans; Yates, Christopher M; Wass, Mark N; Sternberg, Michael J E

2015-06-01

Phyre2 is a suite of tools available on the web to predict and analyze protein structure, function and mutations. The focus of Phyre2 is to provide biologists with a simple and intuitive interface to state-of-the-art protein bioinformatics tools. Phyre2 replaces Phyre, the original version of the server for which we previously published a paper in Nature Protocols. In this updated protocol, we describe Phyre2, which uses advanced remote homology detection methods to build 3D models, predict ligand binding sites and analyze the effect of amino acid variants (e.g., nonsynonymous SNPs (nsSNPs)) for a user's protein sequence. Users are guided through results by a simple interface at a level of detail they determine. This protocol will guide users from submitting a protein sequence to interpreting the secondary and tertiary structure of their models, their domain composition and model quality. A range of additional available tools is described to find a protein structure in a genome, to submit large number of sequences at once and to automatically run weekly searches for proteins that are difficult to model. The server is available at http://www.sbg.bio.ic.ac.uk/phyre2. A typical structure prediction will be returned between 30 min and 2 h after submission.

Validation of protein models by a neural network approach

Directory of Open Access Journals (Sweden)

Fantucci Piercarlo

2008-01-01

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

A protein secretion system linked to bacteroidete gliding motility and pathogenesis

Science.gov (United States)

Sato, Keiko; Naito, Mariko; Yukitake, Hideharu; Hirakawa, Hideki; Shoji, Mikio; McBride, Mark J.; Rhodes, Ryan G.; Nakayama, Koji

2009-01-01

Porphyromonas gingivalis secretes strong proteases called gingipains that are implicated in periodontal pathogenesis. Protein secretion systems common to other Gram-negative bacteria are lacking in P. gingivalis, but several proteins, including PorT, have been linked to gingipain secretion. Comparative genome analysis and genetic experiments revealed 11 additional proteins involved in gingipain secretion. Six of these (PorK, PorL, PorM, PorN, PorW, and Sov) were similar in sequence to Flavobacterium johnsoniae gliding motility proteins, and two others (PorX and PorY) were putative two-component system regulatory proteins. Real-time RT-PCR analysis revealed that porK, porL, porM, porN, porP, porT, and sov were down-regulated in P. gingivalis porX and porY mutants. Disruption of the F. johnsoniae porT ortholog resulted in defects in motility, chitinase secretion, and translocation of a gliding motility protein, SprB adhesin, to the cell surface, providing a link between a unique protein translocation system and a motility apparatus in members of the Bacteroidetes phylum. PMID:19966289

Generic framework for mining cellular automata models on protein-folding simulations.

Science.gov (United States)

Diaz, N; Tischer, I

2016-05-13

Cellular automata model identification is an important way of building simplified simulation models. In this study, we describe a generic architectural framework to ease the development process of new metaheuristic-based algorithms for cellular automata model identification in protein-folding trajectories. Our framework was developed by a methodology based on design patterns that allow an improved experience for new algorithms development. The usefulness of the proposed framework is demonstrated by the implementation of four algorithms, able to obtain extremely precise cellular automata models of the protein-folding process with a protein contact map representation. Dynamic rules obtained by the proposed approach are discussed, and future use for the new tool is outlined.

Alcohol--Induced Polyelectrolyte-Surfactant Complex Coacervate Systems: Characterization and Applications in Enzyme and Protein Extraction

Science.gov (United States)

Nejati Moshtaghin, Mahboubeh

of FA, oppositely charged amphiphiles (surfactant-polyelectrolyte), and the charge ratio of the surfactant-polyelectrolyte on the extent of coacervation have been investigated. Furthermore, the chemical composition of each phase formed in the coacervate system was determined as a function of HFIP percentage. Phase diagrams of HFIP-PMA-CTAB and 2-propanol-PMA-CTAB were studied. The phase separation occurs over a wide range of polyelectrolyte, surfactant and alcohol concentration. In addition, a study of the dependence of coacervate volume on phase composition in different system (as defined by concentrations and mole charge ratio of amphihiles and alcohols) provided useful insight about possible underlying interactions and mechanisms. It has been concluded that neutralization favors coacervation in both systems. However, according to the compositional analysis of both HFIP and 2-propanol SPCC system, it seems that coacervation mechanisms are different. In Chapter III the properties of 2-propanol--SPCC, with analogous surfactant (CTAB) and polyelectrolyte (PMA) used in Chapter II, will be investigated. In particular, we are interested in examining the difference between the phase separation characteristics of the coacervates induced by 2-propanol and HFIP as coacervator. For this purpose, the phase behavior and the chemical composition of the phases will be analyzed as a function of 2-propanol and constituents concentrations. Chapter IV contains results of our investigations on the activity of a model enzyme (Trypsin) in 2-propanol- and FA-induced SPCC system. These investigations will facilitate understanding whether the aliphatic alcohol, AA- and FA-induced SPCC system denature the model enzymes. Such investigations also help in evaluation of the applicability of the coacervate systems developed in this work in proteomics where the proteolytic activity of enzymes is used for protein digestion. Finally, in Chapter V, the efficiency of the coacervate system (2-propanol

DeepQA: improving the estimation of single protein model quality with deep belief networks.

Science.gov (United States)

Cao, Renzhi; Bhattacharya, Debswapna; Hou, Jie; Cheng, Jianlin

2016-12-05

Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality of a single protein model, which is important for selecting a few good models out of a large model pool consisting of mostly low-quality models, is still a largely unsolved problem. We introduce a novel single-model quality assessment method DeepQA based on deep belief network that utilizes a number of selected features describing the quality of a model from different perspectives, such as energy, physio-chemical characteristics, and structural information. The deep belief network is trained on several large datasets consisting of models from the Critical Assessment of Protein Structure Prediction (CASP) experiments, several publicly available datasets, and models generated by our in-house ab initio method. Our experiments demonstrate that deep belief network has better performance compared to Support Vector Machines and Neural Networks on the protein model quality assessment problem, and our method DeepQA achieves the state-of-the-art performance on CASP11 dataset. It also outperformed two well-established methods in selecting good outlier models from a large set of models of mostly low quality generated by ab initio modeling methods. DeepQA is a useful deep learning tool for protein single model quality assessment and protein structure prediction. The source code, executable, document and training/test datasets of DeepQA for Linux is freely available to non-commercial users at http://cactus.rnet.missouri.edu/DeepQA/ .

@TOME-2: a new pipeline for comparative modeling of protein-ligand complexes.

Science.gov (United States)

Pons, Jean-Luc; Labesse, Gilles

2009-07-01

@TOME 2.0 is new web pipeline dedicated to protein structure modeling and small ligand docking based on comparative analyses. @TOME 2.0 allows fold recognition, template selection, structural alignment editing, structure comparisons, 3D-model building and evaluation. These tasks are routinely used in sequence analyses for structure prediction. In our pipeline the necessary software is efficiently interconnected in an original manner to accelerate all the processes. Furthermore, we have also connected comparative docking of small ligands that is performed using protein-protein superposition. The input is a simple protein sequence in one-letter code with no comment. The resulting 3D model, protein-ligand complexes and structural alignments can be visualized through dedicated Web interfaces or can be downloaded for further studies. These original features will aid in the functional annotation of proteins and the selection of templates for molecular modeling and virtual screening. Several examples are described to highlight some of the new functionalities provided by this pipeline. The server and its documentation are freely available at http://abcis.cbs.cnrs.fr/AT2/

A lock-and-key model for protein–protein interactions

OpenAIRE

Morrison, Julie L.; Breitling, Rainer; Higham, Desmond J.; Gilbert, David R.

2006-01-01

Motivation: Protein–protein interaction networks are one of the major post-genomic data sources available to molecular biologists. They provide a comprehensive view of the global interaction structure of an organism’s proteome, as well as detailed information on specific interactions. Here we suggest a physical model of protein interactions that can be used to extract additional information at an intermediate level: It enables us to identify proteins which share biological interaction motifs,...

Primary Screening for Proteins Differentially Expressed in the Myocardium of a Rat Model of Acute Methamphetamine Intoxication

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Guoqiang Qu

2016-01-01

Full Text Available The mechanism of myocardial injury induced by the cardiovascular toxicity of methamphetamine (MA has been shown to depend on alterations in myocardial proteins caused by MA. Primary screening of the expression of myocardial proteins in a rat model of MA intoxication was achieved by combining two-dimensional electrophoresis and mass spectrometry analyses, which revealed a total of 100 differentially expressed proteins. Of these, 13 displayed significantly altered expression. Moreover, Western blotting and real-time reverse transcription quantitative polymerase chain reaction analyses of several relative proteins demonstrated that acute MA intoxication lowers protein expression and mRNA transcription of aldehyde dehydrogenase-2 and NADH dehydrogenase (ubiquinone 1 alpha subcomplex subunit 10. In contrast, MA intoxication elevated the protein expression and mRNA transcription of heat shock protein family B (small member 1. By combining behavioral assessments of experimental rat models with the histological and pathological changes evident in cardiomyocytes, a mechanism accounting for MA myocardial toxicity was suggested. MA alters the regulation of gene transcription and the subsequent expression of certain proteins that participate in myocardial respiration and in responding to oxidative stress, resulting in myocardial dysfunction and structural changes that affect the functioning of the cardiovascular system.

A finite element model for protein transport in vivo

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Montas Hubert J

2007-06-01

Full Text Available Abstract Background Biological mass transport processes determine the behavior and function of cells, regulate interactions between synthetic agents and recipient targets, and are key elements in the design and use of biosensors. Accurately predicting the outcomes of such processes is crucial to both enhancing our understanding of how these systems function, enabling the design of effective strategies to control their function, and verifying that engineered solutions perform according to plan. Methods A Galerkin-based finite element model was developed and implemented to solve a system of two coupled partial differential equations governing biomolecule transport and reaction in live cells. The simulator was coupled, in the framework of an inverse modeling strategy, with an optimization algorithm and an experimental time series, obtained by the Fluorescence Recovery after Photobleaching (FRAP technique, to estimate biomolecule mass transport and reaction rate parameters. In the inverse algorithm, an adaptive method was implemented to calculate sensitivity matrix. A multi-criteria termination rule was developed to stop the inverse code at the solution. The applicability of the model was illustrated by simulating the mobility and binding of GFP-tagged glucocorticoid receptor in the nucleoplasm of mouse adenocarcinoma. Results The numerical simulator shows excellent agreement with the analytic solutions and experimental FRAP data. Detailed residual analysis indicates that residuals have zero mean and constant variance and are normally distributed and uncorrelated. Therefore, the necessary and sufficient criteria for least square parameter optimization, which was used in this study, were met. Conclusion The developed strategy is an efficient approach to extract as much physiochemical information from the FRAP protocol as possible. Well-posedness analysis of the inverse problem, however, indicates that the FRAP protocol provides insufficient

Reconstruction of the yeast protein-protein interaction network involved in nutrient sensing and global metabolic regulation

DEFF Research Database (Denmark)

Nandy, Subir Kumar; Jouhten, Paula; Nielsen, Jens

2010-01-01

proteins. Despite the value of BioGRID for studying protein-protein interactions, there is a need for manual curation of these interactions in order to remove false positives. RESULTS: Here we describe an annotated reconstruction of the protein-protein interactions around four key nutrient......) and for all the interactions between them (edges). The annotated information is readily available utilizing the functionalities of network modelling tools such as Cytoscape and CellDesigner. CONCLUSIONS: The reported fully annotated interaction model serves as a platform for integrated systems biology studies...

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.

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.

An Antibiotic Selection System For Protein Overproducing Bacteria

DEFF Research Database (Denmark)

Rennig, Maja; Nørholm, Morten

2015-01-01

Introduction: Protein overproduction is a major bottleneck for analyses of membrane proteins and for the construction of cell factories. Screening for optimized protein production can be very time consuming. In this study we show that the coupling of antibiotic resistance to poorly produced...... membrane proteins of Escherichia coli can be used as a fast and simple selection system for protein overproduction.Methods: We designed an expression plasmid encoding the gene of interest and an additional, inducible antibiotic resistance marker. Both genes were linked by a hairpin structure...... that translationally couples the genes. Consequently, high expressing gene variants also allow for higher production of the coupled antibiotic resistance marker. Therefore, high expressing gene variants in a library can be determined either by plating the expression library on selection plates or by growing...

An amino acid depleted cell-free protein synthesis system for the incorporation of non-canonical amino acid analogs into proteins.

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Singh-Blom, Amrita; Hughes, Randall A; Ellington, Andrew D

2014-05-20

Residue-specific incorporation of non-canonical amino acids into proteins is usually performed in vivo using amino acid auxotrophic strains and replacing the natural amino acid with an unnatural amino acid analog. Herein, we present an efficient amino acid depleted cell-free protein synthesis system that can be used to study residue-specific replacement of a natural amino acid by an unnatural amino acid analog. This system combines a simple methodology and high protein expression titers with a high-efficiency analog substitution into a target protein. To demonstrate the productivity and efficacy of a cell-free synthesis system for residue-specific incorporation of unnatural amino acids in vitro, we use this system to show that 5-fluorotryptophan and 6-fluorotryptophan substituted streptavidin retain the ability to bind biotin despite protein-wide replacement of a natural amino acid for the amino acid analog. We envisage this amino acid depleted cell-free synthesis system being an economical and convenient format for the high-throughput screening of a myriad of amino acid analogs with a variety of protein targets for the study and functional characterization of proteins substituted with unnatural amino acids when compared to the currently employed in vivo methodologies. Copyright © 2014 Elsevier B.V. All rights reserved.

Mechanical strength of 17,134 model proteins and cysteine slipknots.

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Mateusz Sikora

2009-10-01

Full Text Available A new theoretical survey of proteins' resistance to constant speed stretching is performed for a set of 17,134 proteins as described by a structure-based model. The proteins selected have no gaps in their structure determination and consist of no more than 250 amino acids. Our previous studies have dealt with 7510 proteins of no more than 150 amino acids. The proteins are ranked according to the strength of the resistance. Most of the predicted top-strength proteins have not yet been studied experimentally. Architectures and folds which are likely to yield large forces are identified. New types of potent force clamps are discovered. They involve disulphide bridges and, in particular, cysteine slipknots. An effective energy parameter of the model is estimated by comparing the theoretical data on characteristic forces to the corresponding experimental values combined with an extrapolation of the theoretical data to the experimental pulling speeds. These studies provide guidance for future experiments on single molecule manipulation and should lead to selection of proteins for applications. A new class of proteins, involving cysteine slipknots, is identified as one that is expected to lead to the strongest force clamps known. This class is characterized through molecular dynamics simulations.

Smart sustainable bottle (SSB) system for E. coli based recombinant protein production.

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Li, Zhaopeng; Carstensen, Bettina; Rinas, Ursula

2014-11-05

Recombinant proteins are usually required in laboratories interested in the protein but not in the production process itself. Thus, technical equipment which is easy to handle and straight forward protein production procedures are of great benefit to those laboratories. Companies selling single use cultivation bags and bioreactors are trying to satisfy at least part of these needs. However, single-use systems can contribute to major costs which might be acceptable when "good manufacturing practices" are required but not acceptable for most laboratories facing tight funding. The assembly and application of a simple self-made "smart sustainable bottle" (SSB) system for E. coli based protein production is presented. The core of the SSB system is a 2-L glass bottle which is operated at constant temperature, air flow, and stirrer speed without measurement and control of pH and dissolved oxygen. Oxygen transfer capacities are in the range as in conventional bioreactors operated at intermediate aeration rates and by far exceed those found in conventional shaking flasks and disposable bioreactors. The SSB system was applied for the production of various recombinant proteins using T7-based expression systems and a defined autoinduction medium. The production performance regarding amount and solubility of proteins with robust and delicate properties was as good as in state-of-the-art stirred tank commercial bioreactors. The SSB system represents a low cost protein production device applicable for easy, effective, and reproducible recombinant protein production.

Anomalous diffusion in neutral evolution of model proteins

Science.gov (United States)

Nelson, Erik D.; Grishin, Nick V.

2015-06-01

Protein evolution is frequently explored using minimalist polymer models, however, little attention has been given to the problem of structural drift, or diffusion. Here, we study neutral evolution of small protein motifs using an off-lattice heteropolymer model in which individual monomers interact as low-resolution amino acids. In contrast to most earlier models, both the length and folded structure of the polymers are permitted to change. To describe structural change, we compute the mean-square distance (MSD) between monomers in homologous folds separated by n neutral mutations. We find that structural change is episodic, and, averaged over lineages (for example, those extending from a single sequence), exhibits a power-law dependence on n . We show that this exponent depends on the alignment method used, and we analyze the distribution of waiting times between neutral mutations. The latter are more disperse than for models required to maintain a specific fold, but exhibit a similar power-law tail.

A Comparison Study for DNA Motif Modeling on Protein Binding Microarray

KAUST Repository

Wong, Ka-Chun; Li, Yue; Peng, Chengbin; Wong, Hau-San

2015-01-01

Transcription Factor Binding Sites (TFBSs) are relatively short (5-15 bp) and degenerate. Identifying them is a computationally challenging task. In particular, Protein Binding Microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner; for instance, a typical PBM experiment can measure binding signal intensities of a protein to all possible DNA k-mers (k=810). Since proteins can often bind to DNA with different binding intensities, one of the major challenges is to build motif models which can fully capture the quantitative binding affinity data. To learn DNA motif models from the non-convex objective function landscape, several optimization methods are compared and applied to the PBM motif model building problem. In particular, representative methods from different optimization paradigms have been chosen for modeling performance comparison on hundreds of PBM datasets. The results suggest that the multimodal optimization methods are very effective for capturing the binding preference information from PBM data. In particular, we observe a general performance improvement using di-nucleotide modeling over mono-nucleotide modeling. In addition, the models learned by the best-performing method are applied to two independent applications: PBM probe rotation testing and ChIP-Seq peak sequence prediction, demonstrating its biological applicability.

A Comparison Study for DNA Motif Modeling on Protein Binding Microarray

KAUST Repository

Wong, Ka-Chun

2015-06-11

Transcription Factor Binding Sites (TFBSs) are relatively short (5-15 bp) and degenerate. Identifying them is a computationally challenging task. In particular, Protein Binding Microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner; for instance, a typical PBM experiment can measure binding signal intensities of a protein to all possible DNA k-mers (k=810). Since proteins can often bind to DNA with different binding intensities, one of the major challenges is to build motif models which can fully capture the quantitative binding affinity data. To learn DNA motif models from the non-convex objective function landscape, several optimization methods are compared and applied to the PBM motif model building problem. In particular, representative methods from different optimization paradigms have been chosen for modeling performance comparison on hundreds of PBM datasets. The results suggest that the multimodal optimization methods are very effective for capturing the binding preference information from PBM data. In particular, we observe a general performance improvement using di-nucleotide modeling over mono-nucleotide modeling. In addition, the models learned by the best-performing method are applied to two independent applications: PBM probe rotation testing and ChIP-Seq peak sequence prediction, demonstrating its biological applicability.

Conformational sampling in template-free protein loop structure modeling: an overview.

Science.gov (United States)

Li, Yaohang

2013-01-01

Accurately modeling protein loops is an important step to predict three-dimensional structures as well as to understand functions of many proteins. Because of their high flexibility, modeling the three-dimensional structures of loops is difficult and is usually treated as a "mini protein folding problem" under geometric constraints. In the past decade, there has been remarkable progress in template-free loop structure modeling due to advances of computational methods as well as stably increasing number of known structures available in PDB. This mini review provides an overview on the recent computational approaches for loop structure modeling. In particular, we focus on the approaches of sampling loop conformation space, which is a critical step to obtain high resolution models in template-free methods. We review the potential energy functions for loop modeling, loop buildup mechanisms to satisfy geometric constraints, and loop conformation sampling algorithms. The recent loop modeling results are also summarized.

CONFORMATIONAL SAMPLING IN TEMPLATE-FREE PROTEIN LOOP STRUCTURE MODELING: AN OVERVIEW

Directory of Open Access Journals (Sweden)

Yaohang Li

2013-02-01

Full Text Available Accurately modeling protein loops is an important step to predict three-dimensional structures as well as to understand functions of many proteins. Because of their high flexibility, modeling the three-dimensional structures of loops is difficult and is usually treated as a “mini protein folding problem” under geometric constraints. In the past decade, there has been remarkable progress in template-free loop structure modeling due to advances of computational methods as well as stably increasing number of known structures available in PDB. This mini review provides an overview on the recent computational approaches for loop structure modeling. In particular, we focus on the approaches of sampling loop conformation space, which is a critical step to obtain high resolution models in template-free methods. We review the potential energy functions for loop modeling, loop buildup mechanisms to satisfy geometric constraints, and loop conformation sampling algorithms. The recent loop modeling results are also summarized.

Exploration of freely available web-interfaces for comparative homology modelling of microbial proteins.

Science.gov (United States)

Nema, Vijay; Pal, Sudhir Kumar

2013-01-01

This study was conducted to find the best suited freely available software for modelling of proteins by taking a few sample proteins. The proteins used were small to big in size with available crystal structures for the purpose of benchmarking. Key players like Phyre2, Swiss-Model, CPHmodels-3.0, Homer, (PS)2, (PS)(2)-V(2), Modweb were used for the comparison and model generation. Benchmarking process was done for four proteins, Icl, InhA, and KatG of Mycobacterium tuberculosis and RpoB of Thermus Thermophilus to get the most suited software. Parameters compared during analysis gave relatively better values for Phyre2 and Swiss-Model. This comparative study gave the information that Phyre2 and Swiss-Model make good models of small and large proteins as compared to other screened software. Other software was also good but is often not very efficient in providing full-length and properly folded structure.

Alkylation damage by lipid electrophiles targets functional protein systems.

Science.gov (United States)

Codreanu, Simona G; Ullery, Jody C; Zhu, Jing; Tallman, Keri A; Beavers, William N; Porter, Ned A; Marnett, Lawrence J; Zhang, Bing; Liebler, Daniel C

2014-03-01

Protein alkylation by reactive electrophiles contributes to chemical toxicities and oxidative stress, but the functional impact of alkylation damage across proteomes is poorly understood. We used Click chemistry and shotgun proteomics to profile the accumulation of proteome damage in human cells treated with lipid electrophile probes. Protein target profiles revealed three damage susceptibility classes, as well as proteins that were highly resistant to alkylation. Damage occurred selectively across functional protein interaction networks, with the most highly alkylation-susceptible proteins mapping to networks involved in cytoskeletal regulation. Proteins with lower damage susceptibility mapped to networks involved in protein synthesis and turnover and were alkylated only at electrophile concentrations that caused significant toxicity. Hierarchical susceptibility of proteome systems to alkylation may allow cells to survive sublethal damage while protecting critical cell functions.

Alkylation Damage by Lipid Electrophiles Targets Functional Protein Systems*

Science.gov (United States)

Codreanu, Simona G.; Ullery, Jody C.; Zhu, Jing; Tallman, Keri A.; Beavers, William N.; Porter, Ned A.; Marnett, Lawrence J.; Zhang, Bing; Liebler, Daniel C.

2014-01-01

Protein alkylation by reactive electrophiles contributes to chemical toxicities and oxidative stress, but the functional impact of alkylation damage across proteomes is poorly understood. We used Click chemistry and shotgun proteomics to profile the accumulation of proteome damage in human cells treated with lipid electrophile probes. Protein target profiles revealed three damage susceptibility classes, as well as proteins that were highly resistant to alkylation. Damage occurred selectively across functional protein interaction networks, with the most highly alkylation-susceptible proteins mapping to networks involved in cytoskeletal regulation. Proteins with lower damage susceptibility mapped to networks involved in protein synthesis and turnover and were alkylated only at electrophile concentrations that caused significant toxicity. Hierarchical susceptibility of proteome systems to alkylation may allow cells to survive sublethal damage while protecting critical cell functions. PMID:24429493

Early postnatal low-protein nutrition, metabolic programming and the autonomic nervous system in adult life

Directory of Open Access Journals (Sweden)

de Oliveira Júlio

2012-09-01

Full Text Available Abstract Protein restriction during lactation has been used as a rat model of metabolic programming to study the impact of perinatal malnutrition on adult metabolism. In contrast to protein restriction during fetal life, protein restriction during lactation did not appear to cause either obesity or the hallmarks of metabolic syndrome, such as hyperinsulinemia, when individuals reached adulthood. However, protein restriction provokes body underweight and hypoinsulinemia. This review is focused on the regulation of insulin secretion and the influence of the autonomic nervous system (ANS in adult rats that were protein-malnourished during lactation. The data available on the topic suggest that the perinatal phase of lactation, when insulted by protein deficit, imprints the adult metabolism and thereby alters the glycemic control. Although hypoinsulinemia programs adult rats to maintain normoglycemia, pancreatic β-cells are less sensitive to secretion stimuli, such as glucose and cholinergic agents. These pancreatic dysfunctions may be attributed to an imbalance of ANS activity recorded in adult rats that experienced maternal protein restriction.

Evolution of the DeNOC-based dynamic modelling for multibody systems

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S. K. Saha

2013-01-01

Full Text Available Dynamic modelling of a multibody system plays very essential role in its analyses. As a result, several methods for dynamic modelling have evolved over the years that allow one to analyse multibody systems in a very efficient manner. One such method of dynamic modelling is based on the concept of the Decoupled Natural Orthogonal Complement (DeNOC matrices. The DeNOC-based methodology for dynamics modelling, since its introduction in 1995, has been applied to a variety of multibody systems such as serial, parallel, general closed-loop, flexible, legged, cam-follower, and space robots. The methodology has also proven useful for modelling of proteins and hyper-degree-of-freedom systems like ropes, chains, etc. This paper captures the evolution of the DeNOC-based dynamic modelling applied to different type of systems, and its benefits over other existing methodologies. It is shown that the DeNOC-based modelling provides deeper understanding of the dynamics of a multibody system. The power of the DeNOC-based modelling has been illustrated using several numerical examples.

Unique Protein Signature of Circulating Microparticles in Systemic Lupus Erythematosus

DEFF Research Database (Denmark)

Østergaard, Ole; Nielsen, Christoffer; Iversen, Line V

2013-01-01

To characterize the unique qualities of proteins associated with circulating subcellular material in systemic lupus erythematosus (SLE) patients compared with healthy controls and patients with other chronic autoimmune diseases.......To characterize the unique qualities of proteins associated with circulating subcellular material in systemic lupus erythematosus (SLE) patients compared with healthy controls and patients with other chronic autoimmune diseases....

Membrane Compartmentalization Reducing the Mobility of Lipids and Proteins within a Model Plasma Membrane.

Science.gov (United States)

Koldsø, Heidi; Reddy, Tyler; Fowler, Philip W; Duncan, Anna L; Sansom, Mark S P

2016-09-01

The cytoskeleton underlying cell membranes may influence the dynamic organization of proteins and lipids within the bilayer by immobilizing certain transmembrane (TM) proteins and forming corrals within the membrane. Here, we present coarse-grained resolution simulations of a biologically realistic membrane model of asymmetrically organized lipids and TM proteins. We determine the effects of a model of cytoskeletal immobilization of selected membrane proteins using long time scale coarse-grained molecular dynamics simulations. By introducing compartments with varying degrees of restraints within the membrane models, we are able to reveal how compartmentalization caused by cytoskeletal immobilization leads to reduced and anomalous diffusional mobility of both proteins and lipids. This in turn results in a reduced rate of protein dimerization within the membrane and of hopping of membrane proteins between compartments. These simulations provide a molecular realization of hierarchical models often invoked to explain single-molecule imaging studies of membrane proteins.

Interpretation of protein quantitation using the Bradford assay: comparison with two calculation models.

Science.gov (United States)

Ku, Hyung-Keun; Lim, Hyuk-Min; Oh, Kyong-Hwa; Yang, Hyo-Jin; Jeong, Ji-Seon; Kim, Sook-Kyung

2013-03-01

The Bradford assay is a simple method for protein quantitation, but variation in the results between proteins is a matter of concern. In this study, we compared and normalized quantitative values from two models for protein quantitation, where the residues in the protein that bind to anionic Coomassie Brilliant Blue G-250 comprise either Arg and Lys (Method 1, M1) or Arg, Lys, and His (Method 2, M2). Use of the M2 model yielded much more consistent quantitation values compared with use of the M1 model, which exhibited marked overestimations against protein standards. Copyright © 2012 Elsevier Inc. All rights reserved.

Major vault protein/lung resistance-related protein (MVP/LRP) expression in nervous system tumors.

Science.gov (United States)

Sasaki, Tsutomu; Hankins, Gerald R; Helm, Gregory A

2002-01-01

Lung resistance-related protein (LRP) was identified as the major vault protein (MVP), the main component of multimeric vault particles. It functions as a transport-associated protein that can be associated with multidrug resistance. In previous studies, expression of MVP/LRP has been documented in tumors of various types. In general, good correlations have been reported for expression of MVP/LRP and decreased sensitivity to chemotherapy and poor prognosis. MVP/LRP expression has been documented in glioblastomas, but its expression in nervous system tumors in general has not been well characterized. Immunohistochemistry using anti-human MVP/LRP antibody (LRP-56) was performed on formalin-fixed, paraffin-embedded archival tissue from 69 primary central nervous system tumors. Expression of MVP/LRP was observed in 81.2% (56/69) of primary nervous system tumors, including astrocytomas (11/13), oligodendrogliomas (1/2), oligoastrocytomas (5/5), ependymoma (1/1), meningiomas (35/45), schwannomas (2/2), and neurofibroma (1/1). Various degrees and distributions of immunoreactivity to MVP/ LRP were observed. Neither the presence nor the degree of immunoreactivity to MVP/LRP showed any correlation with either tumor grade or the presence of brain invasion.

Recombinant expression and purification of the RNA-binding LARP6 proteins from fish genetic model organisms.

Science.gov (United States)

Castro, José M; Horn, Daniel A; Pu, Xinzhu; Lewis, Karen A

2017-06-01

The RNA-binding proteins that comprise the La-related protein (LARP) superfamily have been implicated in a wide range of cellular functions, from tRNA maturation to regulation of protein synthesis. To more expansively characterize the biological function of the LARP6 subfamily, we have recombinantly expressed the full-length LARP6 proteins from two teleost fish, platyfish (Xiphophorus maculatus) and zebrafish (Danio rerio). The yields of the recombinant proteins were enhanced to >2 mg/L using a tandem approach of an N-terminal His 6 -SUMO tag and an iterative solubility screening assay to identify structurally stabilizing buffer components. The domain topologies of the purified fish proteins were probed with limited proteolysis. The fish proteins contain an internal, protease-resistant 40 kDa domain, which is considerably more stable than the comparable domain from the human LARP6 protein. The fish proteins are therefore a lucrative model system in which to study both the evolutionary divergence of this family of La-related proteins and the structure and conformational dynamics of the domains that comprise the LARP6 protein. Copyright © 2017 Elsevier Inc. All rights reserved.

Model for Stress-induced Protein Degradation in Lemna minor1

Science.gov (United States)

Cooke, Robert J.; Roberts, Keith; Davies, David D.

1980-01-01

Transfer of Lemna minor fronds to adverse or stress conditions produces a large increase in the rate of protein degradation. Cycloheximide partially inhibits stress-induced protein degradation and also partially inhibits the protein degradation which occurs in the absence of stress. The increased protein degradation does not appear to be due to an increase in activity of soluble proteolytic enzymes. Biochemical evidence indicates that stress, perhaps acting via hormones, affects the permeability of certain membranes, particularly the tonoplast. A general model for stress-induced protein degradation is presented in which changes in membrane properties allow vacuolar proteolytic enzymes increased access to cytoplasmic proteins. PMID:16661588

Quinone-induced protein handling changes: Implications for major protein handling systems in quinone-mediated toxicity

International Nuclear Information System (INIS)

Xiong, Rui; Siegel, David; Ross, David

2014-01-01

Para-quinones such as 1,4-Benzoquinone (BQ) and menadione (MD) and ortho-quinones including the oxidation products of catecholamines, are derived from xenobiotics as well as endogenous molecules. The effects of quinones on major protein handling systems in cells; the 20/26S proteasome, the ER stress response, autophagy, chaperone proteins and aggresome formation, have not been investigated in a systematic manner. Both BQ and aminochrome (AC) inhibited proteasomal activity and activated the ER stress response and autophagy in rat dopaminergic N27 cells. AC also induced aggresome formation while MD had little effect on any protein handling systems in N27 cells. The effect of NQO1 on quinone induced protein handling changes and toxicity was examined using N27 cells stably transfected with NQO1 to generate an isogenic NQO1-overexpressing line. NQO1 protected against BQ–induced apoptosis but led to a potentiation of AC- and MD-induced apoptosis. Modulation of quinone-induced apoptosis in N27 and NQO1-overexpressing cells correlated only with changes in the ER stress response and not with changes in other protein handling systems. These data suggested that NQO1 modulated the ER stress response to potentiate toxicity of AC and MD, but protected against BQ toxicity. We further demonstrated that NQO1 mediated reduction to unstable hydroquinones and subsequent redox cycling was important for the activation of the ER stress response and toxicity for both AC and MD. In summary, our data demonstrate that quinone-specific changes in protein handling are evident in N27 cells and the induction of the ER stress response is associated with quinone-mediated toxicity. - Highlights: • Unstable hydroquinones contributed to quinone-induced ER stress and toxicity

Quinone-induced protein handling changes: Implications for major protein handling systems in quinone-mediated toxicity

Energy Technology Data Exchange (ETDEWEB)

Xiong, Rui; Siegel, David; Ross, David, E-mail: david.ross@ucdenver.edu

2014-10-15

Para-quinones such as 1,4-Benzoquinone (BQ) and menadione (MD) and ortho-quinones including the oxidation products of catecholamines, are derived from xenobiotics as well as endogenous molecules. The effects of quinones on major protein handling systems in cells; the 20/26S proteasome, the ER stress response, autophagy, chaperone proteins and aggresome formation, have not been investigated in a systematic manner. Both BQ and aminochrome (AC) inhibited proteasomal activity and activated the ER stress response and autophagy in rat dopaminergic N27 cells. AC also induced aggresome formation while MD had little effect on any protein handling systems in N27 cells. The effect of NQO1 on quinone induced protein handling changes and toxicity was examined using N27 cells stably transfected with NQO1 to generate an isogenic NQO1-overexpressing line. NQO1 protected against BQ–induced apoptosis but led to a potentiation of AC- and MD-induced apoptosis. Modulation of quinone-induced apoptosis in N27 and NQO1-overexpressing cells correlated only with changes in the ER stress response and not with changes in other protein handling systems. These data suggested that NQO1 modulated the ER stress response to potentiate toxicity of AC and MD, but protected against BQ toxicity. We further demonstrated that NQO1 mediated reduction to unstable hydroquinones and subsequent redox cycling was important for the activation of the ER stress response and toxicity for both AC and MD. In summary, our data demonstrate that quinone-specific changes in protein handling are evident in N27 cells and the induction of the ER stress response is associated with quinone-mediated toxicity. - Highlights: • Unstable hydroquinones contributed to quinone-induced ER stress and toxicity.

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....

A KINETIC MODEL FOR MONO-LAYER GLOBULAR PROTEIN ADSORPTION ON SOLID/LIQUID INTERFACES

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Kamal I. M. Al-Malah

2012-12-01

Full Text Available A kinetic model was derived for globular protein adsorption. The model takes into account the three possible scenarios of a protein molecule in solution, being exposed to an interface: adsorption step from the solution to the interface; the possible desorption back into the solution; and the surface-induced unfolding or spreading of the protein unto the substrate surface. A globular protein molecule is visualized as a sphere with radius D. In addition to the general case of protein adsorption, which portrays either the surface coverage (Theta or surface concentration (� as a function of the adsorption time, special cases, like equilibrium condition, lowsurface coverage, irreversible, and Langmuirian were also presented and treated in light of the derived model. The general model was simplified for each of the subset cases. The irreversibility versus reversibility of protein adsorption was discussed. The substrate surface energetics or effects are accounted for via the proposition of the percent relative change in D/V ratio for the adsorbing protein, called (D/VPRC parameter. (D/VPRC is calculated with respect to the monolayer surface concentration of protein, where the latter is given by D/Vratio. This can be used as a landmark to protein adsorption isotherms or even kinetics. This is visualized as an indicator for solid substrate effects on the adsorbing proteins. (D/VPRC can be zero (fresh monolayer, negative (aged monolayer, or positive (multi-layer. The reference surface concentration is reported for some selected proteins.

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....

Chromophore-protein coupling beyond nonpolarizable models: understanding absorption in green fluorescent protein

NARCIS (Netherlands)

Daday, C.; Curutchet, C.; Sinicropi, A.; Mennucci, B.; Filippi, Claudia

2015-01-01

The nature of the coupling of the photoexcited chromophore with the environment in a prototypical system like green fluorescent protein (GFP) is to date not understood, and its description still defies state-of-the-art multiscale approaches. To identify which theoretical framework of the

Genome-scale metabolic model of Pichia pastoris with native and humanized glycosylation of recombinant proteins.

Science.gov (United States)

Irani, Zahra Azimzadeh; Kerkhoven, Eduard J; Shojaosadati, Seyed Abbas; Nielsen, Jens

2016-05-01

Pichia pastoris is used for commercial production of human therapeutic proteins, and genome-scale models of P. pastoris metabolism have been generated in the past to study the metabolism and associated protein production by this yeast. A major challenge with clinical usage of recombinant proteins produced by P. pastoris is the difference in N-glycosylation of proteins produced by humans and this yeast. However, through metabolic engineering, a P. pastoris strain capable of producing humanized N-glycosylated proteins was constructed. The current genome-scale models of P. pastoris do not address native nor humanized N-glycosylation, and we therefore developed ihGlycopastoris, an extension to the iLC915 model with both native and humanized N-glycosylation for recombinant protein production, but also an estimation of N-glycosylation of P. pastoris native proteins. This new model gives a better prediction of protein yield, demonstrates the effect of the different types of N-glycosylation of protein yield, and can be used to predict potential targets for strain improvement. The model represents a step towards a more complete description of protein production in P. pastoris, which is required for using these models to understand and optimize protein production processes. © 2015 Wiley Periodicals, Inc.

The type III protein secretion system contributes to Xanthomonas citri subsp. citri biofilm formation

KAUST Repository

Zimaro, Tamara

2014-04-18

Background: Several bacterial plant pathogens colonize their hosts through the secretion of effector proteins by a Type III protein secretion system (T3SS). The role of T3SS in bacterial pathogenesis is well established but whether this system is involved in multicellular processes, such as bacterial biofilm formation has not been elucidated. Here, the phytopathogen Xanthomonas citri subsp. citri (X. citri) was used as a model to gain further insights about the role of the T3SS in biofilm formation. Results: The capacity of biofilm formation of different X. citri T3SS mutants was compared to the wild type strain and it was observed that this secretion system was necessary for this process. Moreover, the T3SS mutants adhered proficiently to leaf surfaces but were impaired in leaf-associated growth. A proteomic study of biofilm cells showed that the lack of the T3SS causes changes in the expression of proteins involved in metabolic processes, energy generation, exopolysaccharide (EPS) production and bacterial motility as well as outer membrane proteins. Furthermore, EPS production and bacterial motility were also altered in the T3SS mutants. Conclusions: Our results indicate a novel role for T3SS in X. citri in the modulation of biofilm formation. Since this process increases X. citri virulence, this study reveals new functions of T3SS in pathogenesis. 2014 Zimaro et al.; licensee BioMed Central Ltd.

Context-specific protein network miner - an online system for exploring context-specific protein interaction networks from the literature

KAUST Repository

Chowdhary, Rajesh

2012-04-06

Background: Protein interaction networks (PINs) specific within a particular context contain crucial information regarding many cellular biological processes. For example, PINs may include information on the type and directionality of interaction (e.g. phosphorylation), location of interaction (i.e. tissues, cells), and related diseases. Currently, very few tools are capable of deriving context-specific PINs for conducting exploratory analysis. Results: We developed a literature-based online system, Context-specific Protein Network Miner (CPNM), which derives context-specific PINs in real-time from the PubMed database based on a set of user-input keywords and enhanced PubMed query system. CPNM reports enriched information on protein interactions (with type and directionality), their network topology with summary statistics (e.g. most densely connected proteins in the network; most densely connected protein-pairs; and proteins connected by most inbound/outbound links) that can be explored via a user-friendly interface. Some of the novel features of the CPNM system include PIN generation, ontology-based PubMed query enhancement, real-time, user-queried, up-to-date PubMed document processing, and prediction of PIN directionality. Conclusions: CPNM provides a tool for biologists to explore PINs. It is freely accessible at http://www.biotextminer.com/CPNM/. © 2012 Chowdhary et al.

Context-specific protein network miner - an online system for exploring context-specific protein interaction networks from the literature

KAUST Repository

Chowdhary, Rajesh; Tan, Sin Lam; Zhang, Jinfeng; Karnik, Shreyas; Bajic, Vladimir B.; Liu, Jun S.

2012-01-01

Background: Protein interaction networks (PINs) specific within a particular context contain crucial information regarding many cellular biological processes. For example, PINs may include information on the type and directionality of interaction (e.g. phosphorylation), location of interaction (i.e. tissues, cells), and related diseases. Currently, very few tools are capable of deriving context-specific PINs for conducting exploratory analysis. Results: We developed a literature-based online system, Context-specific Protein Network Miner (CPNM), which derives context-specific PINs in real-time from the PubMed database based on a set of user-input keywords and enhanced PubMed query system. CPNM reports enriched information on protein interactions (with type and directionality), their network topology with summary statistics (e.g. most densely connected proteins in the network; most densely connected protein-pairs; and proteins connected by most inbound/outbound links) that can be explored via a user-friendly interface. Some of the novel features of the CPNM system include PIN generation, ontology-based PubMed query enhancement, real-time, user-queried, up-to-date PubMed document processing, and prediction of PIN directionality. Conclusions: CPNM provides a tool for biologists to explore PINs. It is freely accessible at http://www.biotextminer.com/CPNM/. © 2012 Chowdhary et al.

HIV-specific probabilistic models of protein evolution.

Directory of Open Access Journals (Sweden)

David C Nickle

2007-06-01

Full Text Available Comparative sequence analyses, including such fundamental bioinformatics techniques as similarity searching, sequence alignment and phylogenetic inference, have become a mainstay for researchers studying type 1 Human Immunodeficiency Virus (HIV-1 genome structure and evolution. Implicit in comparative analyses is an underlying model of evolution, and the chosen model can significantly affect the results. In general, evolutionary models describe the probabilities of replacing one amino acid character with another over a period of time. Most widely used evolutionary models for protein sequences have been derived from curated alignments of hundreds of proteins, usually based on mammalian genomes. It is unclear to what extent these empirical models are generalizable to a very different organism, such as HIV-1-the most extensively sequenced organism in existence. We developed a maximum likelihood model fitting procedure to a collection of HIV-1 alignments sampled from different viral genes, and inferred two empirical substitution models, suitable for describing between-and within-host evolution. Our procedure pools the information from multiple sequence alignments, and provided software implementation can be run efficiently in parallel on a computer cluster. We describe how the inferred substitution models can be used to generate scoring matrices suitable for alignment and similarity searches. Our models had a consistently superior fit relative to the best existing models and to parameter-rich data-driven models when benchmarked on independent HIV-1 alignments, demonstrating evolutionary biases in amino-acid substitution that are unique to HIV, and that are not captured by the existing models. The scoring matrices derived from the models showed a marked difference from common amino-acid scoring matrices. The use of an appropriate evolutionary model recovered a known viral transmission history, whereas a poorly chosen model introduced phylogenetic

A multifunctional multimaterial system for on-demand protein release.

Science.gov (United States)

Tuncaboylu, Deniz Ceylan; Friess, Fabian; Wischke, Christian; Lendlein, Andreas

2018-06-15

In order to provide best control of the regeneration process for each individual patient, the release of protein drugs administered during surgery may need to be timely adapted and/or delayed according to the progress of healing/regeneration. This study aims to establish a multifunctional implant system for a local on-demand release, which is applicable for various types of proteins. It was hypothesized that a tubular multimaterial container kit, which hosts the protein of interest as a solution or gel formulation, would enable on-demand release if equipped with the capacity of diameter reduction upon external stimulation. Using devices from poly(ɛ-caprolactone) networks, it could be demonstrated that a shape-memory effect activated by heat or NIR light enabled on-demand tube shrinkage. The decrease of diameter of these shape-memory tubes (SMT) allowed expelling the payload as demonstrated for several proteins including SDF-1α, a therapeutically relevant chemotactic protein, to achieve e.g. continuous release with a triggered add-on dosing (open tube) or an on-demand onset of bolus or sustained release (sealed tube). Considering the clinical relevance of protein factors in (stem) cell attraction to lesions and the progress in monitoring biomarkers in body fluids, such on-demand release systems may be further explored e.g. in heart, nerve, or bone regeneration in the future. Copyright © 2018. Published by Elsevier B.V.

Fiscal 1999 achievement report on research and development project on intellectual infrastructure creation and utilization technologies. Development of efficient protein expression system (Development of efficient protein expression system utilizing protein folding mechanism of hyperthermophilic bacteria); 1999 nendo kokoritsu tanpakushitsu hatsugen system no kaihatsu seika hokokusho. Chokonetsukin no tanpakushitsu oritatami kiko wo riyoshita kokoritsu tanpakushitsu hatsugen system no kaihatsu

Energy Technology Data Exchange (ETDEWEB)

NONE

2000-03-01

Efforts were exerted to achieve efficient expression of proteins of hyperthermophilic bacteria, hyperthermophilic archaeabacteria in particular, using a heterogene expression system in which Escherichia coli was the host. In an effort to search for genes related to protein folding and to elucidate the mechanism of folding, chaperonin and prefoldin subunit genes, out of various factors participating in protein folding in hyperthermophilic archaeabacteria, were cloned, and expressed in Escherichia coli. As a system for analyzing protein folding reaction, an experimental system was established on a substrate comprising isopropyl malate dehydrogenase, citrate synthase, glucose dehydrogenase, and a green fluorescent protein. Studies were further conducted to elucidate the mechanism of expression of enzyme genes in Escherichia coli for the establishment of a mass production method for useful enzymes. Also carried out was the research and development of an element technology evaluation system involving protein expression. (NEDO)

[The role of protein glycosylation in immune system].

Science.gov (United States)

Ząbczyńska, Marta; Pocheć, Ewa

2015-01-01

Glycosylation is one of the most frequent post-translational modifications of proteins. The majority of cell surface and secreted proteins involved in immune response is glycosylated. The structural diversity of glycans depends on monosaccharide composition, type of glycosidic linkage and branching. These structural modifications determine a great variability of glycoproteins. The oligosaccharide components of proteins are regulated mostly by expression of glycosyltransferases and glycosidases and many environmental factors. Glycosylation influences the function of all immune cells. Glycans play a crucial role in intercellular contacts and leukocytes migration. These interactions are important in activation and proliferation of leukocytes and during immune response. The key immune proteins, such as TCR, MHC, TLR and antibodies are glycosylated. Sugars on the surface of pathogens and self-surface glycoproteins are recognized by special carbohydrate binding proteins called lectins. Changes of glycan structure are common in many pathological processes occurring in immune system, therefore they are used as molecular markers of different diseases.

Refinement of protein termini in template-based modeling using conformational space annealing.

Science.gov (United States)

Park, Hahnbeom; Ko, Junsu; Joo, Keehyoung; Lee, Julian; Seok, Chaok; Lee, Jooyoung

2011-09-01

The rapid increase in the number of experimentally determined protein structures in recent years enables us to obtain more reliable protein tertiary structure models than ever by template-based modeling. However, refinement of template-based models beyond the limit available from the best templates is still needed for understanding protein function in atomic detail. In this work, we develop a new method for protein terminus modeling that can be applied to refinement of models with unreliable terminus structures. The energy function for terminus modeling consists of both physics-based and knowledge-based potential terms with carefully optimized relative weights. Effective sampling of both the framework and terminus is performed using the conformational space annealing technique. This method has been tested on a set of termini derived from a nonredundant structure database and two sets of termini from the CASP8 targets. The performance of the terminus modeling method is significantly improved over our previous method that does not employ terminus refinement. It is also comparable or superior to the best server methods tested in CASP8. The success of the current approach suggests that similar strategy may be applied to other types of refinement problems such as loop modeling or secondary structure rearrangement. Copyright © 2011 Wiley-Liss, Inc.

Unique Features of Halophilic Proteins.

Science.gov (United States)

Arakawa, Tsutomu; Yamaguchi, Rui; Tokunaga, Hiroko; Tokunaga, Masao

2017-01-01

Proteins from moderate and extreme halophiles have unique characteristics. They are highly acidic and hydrophilic, similar to intrinsically disordered proteins. These characteristics make the halophilic proteins soluble in water and fold reversibly. In addition to reversible folding, the rate of refolding of halophilic proteins from denatured structure is generally slow, often taking several days, for example, for extremely halophilic proteins. This slow folding rate makes the halophilic proteins a novel model system for folding mechanism analysis. High solubility and reversible folding also make the halophilic proteins excellent fusion partners for soluble expression of recombinant proteins.

Accurate protein structure modeling using sparse NMR data and homologous structure information.

Science.gov (United States)

Thompson, James M; Sgourakis, Nikolaos G; Liu, Gaohua; Rossi, Paolo; Tang, Yuefeng; Mills, Jeffrey L; Szyperski, Thomas; Montelione, Gaetano T; Baker, David

2012-06-19

While information from homologous structures plays a central role in X-ray structure determination by molecular replacement, such information is rarely used in NMR structure determination because it can be incorrect, both locally and globally, when evolutionary relationships are inferred incorrectly or there has been considerable evolutionary structural divergence. Here we describe a method that allows robust modeling of protein structures of up to 225 residues by combining (1)H(N), (13)C, and (15)N backbone and (13)Cβ chemical shift data, distance restraints derived from homologous structures, and a physically realistic all-atom energy function. Accurate models are distinguished from inaccurate models generated using incorrect sequence alignments by requiring that (i) the all-atom energies of models generated using the restraints are lower than models generated in unrestrained calculations and (ii) the low-energy structures converge to within 2.0 Å backbone rmsd over 75% of the protein. Benchmark calculations on known structures and blind targets show that the method can accurately model protein structures, even with very remote homology information, to a backbone rmsd of 1.2-1.9 Å relative to the conventional determined NMR ensembles and of 0.9-1.6 Å relative to X-ray structures for well-defined regions of the protein structures. This approach facilitates the accurate modeling of protein structures using backbone chemical shift data without need for side-chain resonance assignments and extensive analysis of NOESY cross-peak assignments.

Removal of model proteins by means of low-pressure inductively coupled plasma discharge

International Nuclear Information System (INIS)

Kylian, O; Rauscher, H; Gilliland, D; Bretagnol, F; Rossi, F

2008-01-01

Surgical instruments are intended to come into direct contact with the patients' tissues and thus interact with their first immune defence system. Therefore they have to be cleaned, sterilized and decontaminated, in order to prevent any kind of infections and inflammations or to exclude the possibility of transmission of diseases. From this perspective, the removal of protein residues from their surfaces constitutes new challenges, since certain proteins exhibit high resistance to commonly used sterilization and decontamination techniques and hence are difficult to remove without inducing major damages to the object treated. Therefore new approaches must be developed for that purpose and the application of non-equilibrium plasma discharges represents an interesting option. The possibility to effectively remove model proteins (bovine serum albumin, lysozyme and ubiquitin) from surfaces of different materials (Si wafer, glass, polystyrene and gold) by means of inductively coupled plasma discharges sustained in different argon containing mixtures is demonstrated and discussed in this paper

Removal of model proteins by means of low-pressure inductively coupled plasma discharge

Energy Technology Data Exchange (ETDEWEB)

Kylian, O; Rauscher, H; Gilliland, D; Bretagnol, F; Rossi, F [European Commission, Joint Research Centre, Institute for Health and Consumer Protection, Via E Fermi 2749, 21027 Ispra (Italy)], E-mail: francois.rossi@jrc.it

2008-05-07

Surgical instruments are intended to come into direct contact with the patients' tissues and thus interact with their first immune defence system. Therefore they have to be cleaned, sterilized and decontaminated, in order to prevent any kind of infections and inflammations or to exclude the possibility of transmission of diseases. From this perspective, the removal of protein residues from their surfaces constitutes new challenges, since certain proteins exhibit high resistance to commonly used sterilization and decontamination techniques and hence are difficult to remove without inducing major damages to the object treated. Therefore new approaches must be developed for that purpose and the application of non-equilibrium plasma discharges represents an interesting option. The possibility to effectively remove model proteins (bovine serum albumin, lysozyme and ubiquitin) from surfaces of different materials (Si wafer, glass, polystyrene and gold) by means of inductively coupled plasma discharges sustained in different argon containing mixtures is demonstrated and discussed in this paper.

NovelFam3000 – Uncharacterized human protein domains conserved across model organisms

Science.gov (United States)

Kemmer, Danielle; Podowski, Raf M; Arenillas, David; Lim, Jonathan; Hodges, Emily; Roth, Peggy; Sonnhammer, Erik LL; Höög, Christer; Wasserman, Wyeth W

2006-01-01

Background Despite significant efforts from the research community, an extensive portion of the proteins encoded by human genes lack an assigned cellular function. Most metazoan proteins are composed of structural and/or functional domains, of which many appear in multiple proteins. Once a domain is characterized in one protein, the presence of a similar sequence in an uncharacterized protein serves as a basis for inference of function. Thus knowledge of a domain's function, or the protein within which it arises, can facilitate the analysis of an entire set of proteins. Description From the Pfam domain database, we extracted uncharacterized protein domains represented in proteins from humans, worms, and flies. A data centre was created to facilitate the analysis of the uncharacterized domain-containing proteins. The centre both provides researchers with links to dispersed internet resources containing gene-specific experimental data and enables them to post relevant experimental results or comments. For each human gene in the system, a characterization score is posted, allowing users to track the progress of characterization over time or to identify for study uncharacterized domains in well-characterized genes. As a test of the system, a subset of 39 domains was selected for analysis and the experimental results posted to the NovelFam3000 system. For 25 human protein members of these 39 domain families, detailed sub-cellular localizations were determined. Specific observations are presented based on the analysis of the integrated information provided through the online NovelFam3000 system. Conclusion Consistent experimental results between multiple members of a domain family allow for inferences of the domain's functional role. We unite bioinformatics resources and experimental data in order to accelerate the functional characterization of scarcely annotated domain families. PMID:16533400

NovelFam3000 – Uncharacterized human protein domains conserved across model organisms

Directory of Open Access Journals (Sweden)

Sonnhammer Erik LL

2006-03-01

Full Text Available Abstract Background Despite significant efforts from the research community, an extensive portion of the proteins encoded by human genes lack an assigned cellular function. Most metazoan proteins are composed of structural and/or functional domains, of which many appear in multiple proteins. Once a domain is characterized in one protein, the presence of a similar sequence in an uncharacterized protein serves as a basis for inference of function. Thus knowledge of a domain's function, or the protein within which it arises, can facilitate the analysis of an entire set of proteins. Description From the Pfam domain database, we extracted uncharacterized protein domains represented in proteins from humans, worms, and flies. A data centre was created to facilitate the analysis of the uncharacterized domain-containing proteins. The centre both provides researchers with links to dispersed internet resources containing gene-specific experimental data and enables them to post relevant experimental results or comments. For each human gene in the system, a characterization score is posted, allowing users to track the progress of characterization over time or to identify for study uncharacterized domains in well-characterized genes. As a test of the system, a subset of 39 domains was selected for analysis and the experimental results posted to the NovelFam3000 system. For 25 human protein members of these 39 domain families, detailed sub-cellular localizations were determined. Specific observations are presented based on the analysis of the integrated information provided through the online NovelFam3000 system. Conclusion Consistent experimental results between multiple members of a domain family allow for inferences of the domain's functional role. We unite bioinformatics resources and experimental data in order to accelerate the functional characterization of scarcely annotated domain families.

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 from poly-β-hydroxybutyrate, calculated with the model, the endospore and Cry protein production are not just simultaneous and parallel processes they are also competitive processes.

GRIP: A web-based system for constructing Gold Standard datasets for protein-protein interaction prediction

Directory of Open Access Journals (Sweden)

Zheng Huiru

2009-01-01

Full Text Available Abstract Background Information about protein interaction networks is fundamental to understanding protein function and cellular processes. Interaction patterns among proteins can suggest new drug targets and aid in the design of new therapeutic interventions. Efforts have been made to map interactions on a proteomic-wide scale using both experimental and computational techniques. Reference datasets that contain known interacting proteins (positive cases and non-interacting proteins (negative cases are essential to support computational prediction and validation of protein-protein interactions. Information on known interacting and non interacting proteins are usually stored within databases. Extraction of these data can be both complex and time consuming. Although, the automatic construction of reference datasets for classification is a useful resource for researchers no public resource currently exists to perform this task. Results GRIP (Gold Reference dataset constructor from Information on Protein complexes is a web-based system that provides researchers with the functionality to create reference datasets for protein-protein interaction prediction in Saccharomyces cerevisiae. Both positive and negative cases for a reference dataset can be extracted, organised and downloaded by the user. GRIP also provides an upload facility whereby users can submit proteins to determine protein complex membership. A search facility is provided where a user can search for protein complex information in Saccharomyces cerevisiae. Conclusion GRIP is developed to retrieve information on protein complex, cellular localisation, and physical and genetic interactions in Saccharomyces cerevisiae. Manual construction of reference datasets can be a time consuming process requiring programming knowledge. GRIP simplifies and speeds up this process by allowing users to automatically construct reference datasets. GRIP is free to access at http://rosalind.infj.ulst.ac.uk/GRIP/.

The competitor-introduced Ggamma recruitment system, a new approach for screening affinity-enhanced proteins.

Science.gov (United States)

Fukuda, Nobuo; Ishii, Jun; Tanaka, Tsutomu; Kondo, Akihiko

2010-04-01

We have developed a new approach based on the Ggamma recruitment system to screen affinity-enhanced proteins by expressing a binding competitor. The previously established Ggamma recruitment system is a yeast two-hybrid (Y2H) system that utilizes G-protein signaling, and is based on the fact that membrane localization of the G-protein gamma subunit (Ggamma) is essential for signal transduction in yeast. In the original Y2H system, an engineered Ggamma that lacks membrane localization upon deletion of the lipid modification site (Ggamma(cyto)) is produced, and a candidate protein with an artificial lipidation site and its counterpart fused with Ggamma(cyto) are expressed. As protein-protein interactions bring Ggamma(cyto) towards the plasma membrane, G-protein signaling can be activated, and the interaction is detected by various cellular responses as the readout. In the current study, we expressed a third cytosolic protein that competes with the candidate protein to specifically isolate affinity-enhanced mutants from a mutation library of the candidate protein. Enhancing the affinity of the protein candidate guides the counterpart-Ggamma(cyto) fusion protein towards the plasma membrane and activates signaling. Using mutants of the Z domain derived from Staphylococcus aureus protein A as candidate proteins or competitors, and the Fc portion of human immunoglobulin G (IgG) as the counterpart, we demonstrate that affinity-enhanced proteins can be effectively screened from a library containing a 10 000-fold excess of non-enhanced proteins. This new approach, called the competitor-introduced Ggamma recruitment system, will be useful for efficient discovery of rare valuable candidates hidden among excess ordinary ones.

Mass balances for a biological life support system simulation model

Science.gov (United States)

Volk, Tyler; Rummel, John D.

1987-01-01

Design decisions to aid the development of future space based biological life support systems (BLSS) can be made with simulation models. The biochemistry stoichiometry was developed for: (1) protein, carbohydrate, fat, fiber, and lignin production in the edible and inedible parts of plants; (2) food consumption and production of organic solids in urine, feces, and wash water by the humans; and (3) operation of the waste processor. Flux values for all components are derived for a steady state system with wheat as the sole food source. The large scale dynamics of a materially closed (BLSS) computer model is described in a companion paper. An extension of this methodology can explore multifood systems and more complex biochemical dynamics while maintaining whole system closure as a focus.

A new protein-protein interaction sensor based on tripartite split-GFP association.

Science.gov (United States)

Cabantous, Stéphanie; Nguyen, Hau B; Pedelacq, Jean-Denis; Koraïchi, Faten; Chaudhary, Anu; Ganguly, Kumkum; Lockard, Meghan A; Favre, Gilles; Terwilliger, Thomas C; Waldo, Geoffrey S

2013-10-04

Monitoring protein-protein interactions in living cells is key to unraveling their roles in numerous cellular processes and various diseases. Previously described split-GFP based sensors suffer from poor folding and/or self-assembly background fluorescence. Here, we have engineered a micro-tagging system to monitor protein-protein interactions in vivo and in vitro. The assay is based on tripartite association between two twenty amino-acids long GFP tags, GFP10 and GFP11, fused to interacting protein partners, and the complementary GFP1-9 detector. When proteins interact, GFP10 and GFP11 self-associate with GFP1-9 to reconstitute a functional GFP. Using coiled-coils and FRB/FKBP12 model systems we characterize the sensor in vitro and in Escherichia coli. We extend the studies to mammalian cells and examine the FK-506 inhibition of the rapamycin-induced association of FRB/FKBP12. The small size of these tags and their minimal effect on fusion protein behavior and solubility should enable new experiments for monitoring protein-protein association by fluorescence.

Labeling of multiple HIV-1 proteins with the biarsenical-tetracysteine system.

Directory of Open Access Journals (Sweden)

Cândida F Pereira

Full Text Available Due to its small size and versatility, the biarsenical-tetracysteine system is an attractive way to label viral proteins for live cell imaging. This study describes the genetic labeling of the human immunodeficiency virus type 1 (HIV-1 structural proteins (matrix, capsid and nucleocapsid, enzymes (protease, reverse transcriptase, RNAse H and integrase and envelope glycoprotein 120 with a tetracysteine tag in the context of a full-length virus. We measure the impact of these modifications on the natural virus infection and, most importantly, present the first infectious HIV-1 construct containing a fluorescently-labeled nucleocapsid protein. Furthermore, due to the high background levels normally associated with the labeling of tetracysteine-tagged proteins we have also optimized a metabolic labeling system that produces infectious virus containing the natural envelope glycoproteins and specifically labeled tetracysteine-tagged proteins that can easily be detected after virus infection of T-lymphocytes. This approach can be adapted to other viral systems for the visualization of the interplay between virus and host cell during infection.

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.

Analysis of correlations between sites in models of protein sequences

International Nuclear Information System (INIS)

Giraud, B.G.; Lapedes, A.; Liu, L.C.

1998-01-01

A criterion based on conditional probabilities, related to the concept of algorithmic distance, is used to detect correlated mutations at noncontiguous sites on sequences. We apply this criterion to the problem of analyzing correlations between sites in protein sequences; however, the analysis applies generally to networks of interacting sites with discrete states at each site. Elementary models, where explicit results can be derived easily, are introduced. The number of states per site considered ranges from 2, illustrating the relation to familiar classical spin systems, to 20 states, suitable for representing amino acids. Numerical simulations show that the criterion remains valid even when the genetic history of the data samples (e.g., protein sequences), as represented by a phylogenetic tree, introduces nonindependence between samples. Statistical fluctuations due to finite sampling are also investigated and do not invalidate the criterion. A subsidiary result is found: The more homogeneous a population, the more easily its average properties can drift from the properties of its ancestor. copyright 1998 The American Physical Society

Electrostatics of cysteine residues in proteins: Parameterization and validation of a simple model

Science.gov (United States)

Salsbury, Freddie R.; Poole, Leslie B.; Fetrow, Jacquelyn S.

2013-01-01

One of the most popular and simple models for the calculation of pKas from a protein structure is the semi-macroscopic electrostatic model MEAD. This model requires empirical parameters for each residue to calculate pKas. Analysis of current, widely used empirical parameters for cysteine residues showed that they did not reproduce expected cysteine pKas; thus, we set out to identify parameters consistent with the CHARMM27 force field that capture both the behavior of typical cysteines in proteins and the behavior of cysteines which have perturbed pKas. The new parameters were validated in three ways: (1) calculation across a large set of typical cysteines in proteins (where the calculations are expected to reproduce expected ensemble behavior); (2) calculation across a set of perturbed cysteines in proteins (where the calculations are expected to reproduce the shifted ensemble behavior); and (3) comparison to experimentally determined pKa values (where the calculation should reproduce the pKa within experimental error). Both the general behavior of cysteines in proteins and the perturbed pKa in some proteins can be predicted reasonably well using the newly determined empirical parameters within the MEAD model for protein electrostatics. This study provides the first general analysis of the electrostatics of cysteines in proteins, with specific attention paid to capturing both the behavior of typical cysteines in a protein and the behavior of cysteines whose pKa should be shifted, and validation of force field parameters for cysteine residues. PMID:22777874

[Effect of solution environments on ceramic membrane microfiltration of model system of Chinese medicines].

Science.gov (United States)

Zhang, Lianjun; Lu, Jin; Le, Kang; Fu, Tingming; Guo, Liwei

2010-07-01

To investigate the effect of differents solution environments on the ceramic membrane microfiltration of model system of Chinese medicines. Taking binary system of soybean protein-berberine as the research object, flux, transmittance of berberine and traping rate of protein as indexes, different solution environment on membrane process were investigated. When the concentration of soybean protein was under 1 g x L(-1), the membrane flux was minimum with the traping of berberine decreased slightly as the concentration increased. When pH was 4, the flux was maximum with the traping rate of protein was 99%, and the transmittance of berberine reached above 60%. The efficiency of membrane separation can be improved by optimizing the solution environment of water-extraction of chinese medicines. The efficiency of membrane separation is the best when adjust the pH to the isoelectric point of proteins for the proteins as the main pollutant in aqueous solution.

The plug-based nanovolume Microcapillary Protein Crystallization System (MPCS)

International Nuclear Information System (INIS)

Gerdts, Cory J.; Elliott, Mark; Lovell, Scott; Mixon, Mark B.; Napuli, Alberto J.; Staker, Bart L.; Nollert, Peter; Stewart, Lance

2008-01-01

The Microcapillary Protein Crystallization System (MPCS) is a new protein-crystallization technology used to generate nanolitre-sized crystallization experiments for crystal screening and optimization. Using the MPCS, diffraction-ready crystals were grown in the plastic MPCS CrystalCard and were used to solve the structure of methionine-R-sulfoxide reductase. The Microcapillary Protein Crystallization System (MPCS) embodies a new semi-automated plug-based crystallization technology which enables nanolitre-volume screening of crystallization conditions in a plasticware format that allows crystals to be easily removed for traditional cryoprotection and X-ray diffraction data collection. Protein crystals grown in these plastic devices can be directly subjected to in situ X-ray diffraction studies. The MPCS integrates the formulation of crystallization cocktails with the preparation of the crystallization experiments. Within microfluidic Teflon tubing or the microfluidic circuitry of a plastic CrystalCard, ∼10–20 nl volume droplets are generated, each representing a microbatch-style crystallization experiment with a different chemical composition. The entire protein sample is utilized in crystallization experiments. Sparse-matrix screening and chemical gradient screening can be combined in one comprehensive ‘hybrid’ crystallization trial. The technology lends itself well to optimization by high-granularity gradient screening using optimization reagents such as precipitation agents, ligands or cryoprotectants

Hidden Markov model approach for identifying the modular framework of the protein backbone.

Science.gov (United States)

Camproux, A C; Tuffery, P; Chevrolat, J P; Boisvieux, J F; Hazout, S

1999-12-01

The hidden Markov model (HMM) was used to identify recurrent short 3D structural building blocks (SBBs) describing protein backbones, independently of any a priori knowledge. Polypeptide chains are decomposed into a series of short segments defined by their inter-alpha-carbon distances. Basically, the model takes into account the sequentiality of the observed segments and assumes that each one corresponds to one of several possible SBBs. Fitting the model to a database of non-redundant proteins allowed us to decode proteins in terms of 12 distinct SBBs with different roles in protein structure. Some SBBs correspond to classical regular secondary structures. Others correspond to a significant subdivision of their bounding regions previously considered to be a single pattern. The major contribution of the HMM is that this model implicitly takes into account the sequential connections between SBBs and thus describes the most probable pathways by which the blocks are connected to form the framework of the protein structures. Validation of the SBBs code was performed by extracting SBB series repeated in recoding proteins and examining their structural similarities. Preliminary results on the sequence specificity of SBBs suggest promising perspectives for the prediction of SBBs or series of SBBs from the protein sequences.

Predicting turns in proteins with a unified model.

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Qi Song

Full Text Available MOTIVATION: Turns are a critical element of the structure of a protein; turns play a crucial role in loops, folds, and interactions. Current prediction methods are well developed for the prediction of individual turn types, including α-turn, β-turn, and γ-turn, etc. However, for further protein structure and function prediction it is necessary to develop a uniform model that can accurately predict all types of turns simultaneously. RESULTS: In this study, we present a novel approach, TurnP, which offers the ability to investigate all the turns in a protein based on a unified model. The main characteristics of TurnP are: (i using newly exploited features of structural evolution information (secondary structure and shape string of protein based on structure homologies, (ii considering all types of turns in a unified model, and (iii practical capability of accurate prediction of all turns simultaneously for a query. TurnP utilizes predicted secondary structures and predicted shape strings, both of which have greater accuracy, based on innovative technologies which were both developed by our group. Then, sequence and structural evolution features, which are profile of sequence, profile of secondary structures and profile of shape strings are generated by sequence and structure alignment. When TurnP was validated on a non-redundant dataset (4,107 entries by five-fold cross-validation, we achieved an accuracy of 88.8% and a sensitivity of 71.8%, which exceeded the most state-of-the-art predictors of certain type of turn. Newly determined sequences, the EVA and CASP9 datasets were used as independent tests and the results we achieved were outstanding for turn predictions and confirmed the good performance of TurnP for practical applications.

Protein Delivery System Containing a Nickel-Immobilized Polymer for Multimerization of Affinity-Purified His-Tagged Proteins Enhances Cytosolic Transfer.

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Postupalenko, Viktoriia; Desplancq, Dominique; Orlov, Igor; Arntz, Youri; Spehner, Danièle; Mely, Yves; Klaholz, Bruno P; Schultz, Patrick; Weiss, Etienne; Zuber, Guy

2015-09-01

Recombinant proteins with cytosolic or nuclear activities are emerging as tools for interfering with cellular functions. Because such tools rely on vehicles for crossing the plasma membrane we developed a protein delivery system consisting in the assembly of pyridylthiourea-grafted polyethylenimine (πPEI) with affinity-purified His-tagged proteins pre-organized onto a nickel-immobilized polymeric guide. The guide was prepared by functionalization of an ornithine polymer with nitrilotriacetic acid groups and shown to bind several His-tagged proteins. Superstructures were visualized by electron and atomic force microscopy using 2 nm His-tagged gold nanoparticles as probes. The whole system efficiently carried the green fluorescent protein, single-chain antibodies or caspase 3, into the cytosol of living cells. Transduction of the protease caspase 3 induced apoptosis in two cancer cell lines, demonstrating that this new protein delivery method could be used to interfere with cellular functions. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Protein Maker: an automated system for high-throughput parallel purification

International Nuclear Information System (INIS)

Smith, Eric R.; Begley, Darren W.; Anderson, Vanessa; Raymond, Amy C.; Haffner, Taryn E.; Robinson, John I.; Edwards, Thomas E.; Duncan, Natalie; Gerdts, Cory J.; Mixon, Mark B.; Nollert, Peter; Staker, Bart L.; Stewart, Lance J.

2011-01-01

The Protein Maker instrument addresses a critical bottleneck in structural genomics by allowing automated purification and buffer testing of multiple protein targets in parallel with a single instrument. Here, the use of this instrument to (i) purify multiple influenza-virus proteins in parallel for crystallization trials and (ii) identify optimal lysis-buffer conditions prior to large-scale protein purification is described. The Protein Maker is an automated purification system developed by Emerald BioSystems for high-throughput parallel purification of proteins and antibodies. This instrument allows multiple load, wash and elution buffers to be used in parallel along independent lines for up to 24 individual samples. To demonstrate its utility, its use in the purification of five recombinant PB2 C-terminal domains from various subtypes of the influenza A virus is described. Three of these constructs crystallized and one diffracted X-rays to sufficient resolution for structure determination and deposition in the Protein Data Bank. Methods for screening lysis buffers for a cytochrome P450 from a pathogenic fungus prior to upscaling expression and purification are also described. The Protein Maker has become a valuable asset within the Seattle Structural Genomics Center for Infectious Disease (SSGCID) and hence is a potentially valuable tool for a variety of high-throughput protein-purification applications

Main Strategies of Plant Expression System Glycoengineering for Producing Humanized Recombinant Pharmaceutical Proteins.

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Rozov, S M; Permyakova, N V; Deineko, E V

2018-03-01

Most the pharmaceutical proteins are derived not from their natural sources, rather their recombinant analogs are synthesized in various expression systems. Plant expression systems, unlike mammalian cell cultures, combine simplicity and low cost of procaryotic systems and the ability for posttranslational modifications inherent in eucaryotes. More than 50% of all human proteins and more than 40% of the currently used pharmaceutical proteins are glycosylated, that is, they are glycoproteins, and their biological activity, pharmacodynamics, and immunogenicity depend on the correct glycosylation pattern. This review examines in detail the similarities and differences between N- and O-glycosylation in plant and mammalian cells, as well as the effect of plant glycans on the activity, pharmacokinetics, immunity, and intensity of biosynthesis of pharmaceutical proteins. The main current strategies of glycoengineering of plant expression systems aimed at obtaining fully humanized proteins for pharmaceutical application are summarized.

Prediction of Protein Hotspots from Whole Protein Sequences by a Random Projection Ensemble System

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Jinjian Jiang

2017-07-01

Full Text Available Hotspot residues are important in the determination of protein-protein interactions, and they always perform specific functions in biological processes. The determination of hotspot residues is by the commonly-used method of alanine scanning mutagenesis experiments, which is always costly and time consuming. To address this issue, computational methods have been developed. Most of them are structure based, i.e., using the information of solved protein structures. However, the number of solved protein structures is extremely less than that of sequences. Moreover, almost all of the predictors identified hotspots from the interfaces of protein complexes, seldom from the whole protein sequences. Therefore, determining hotspots from whole protein sequences by sequence information alone is urgent. To address the issue of hotspot predictions from the whole sequences of proteins, we proposed an ensemble system with random projections using statistical physicochemical properties of amino acids. First, an encoding scheme involving sequence profiles of residues and physicochemical properties from the AAindex1 dataset is developed. Then, the random projection technique was adopted to project the encoding instances into a reduced space. Then, several better random projections were obtained by training an IBk classifier based on the training dataset, which were thus applied to the test dataset. The ensemble of random projection classifiers is therefore obtained. Experimental results showed that although the performance of our method is not good enough for real applications of hotspots, it is very promising in the determination of hotspot residues from whole sequences.

Global Structural Flexibility of Metalloproteins Regulates Reactivity of Transition Metal Ion in the Protein Core: An Experimental Study Using Thiol-subtilisin as a Model Protein.

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Matsuo, Takashi; Kono, Takamasa; Shobu, Isamu; Ishida, Masaya; Gonda, Katsuya; Hirota, Shun

2018-02-21

The functions of metal-containing proteins (metalloproteins) are determined by the reactivities of transition metal ions at their active sites. Because protein macromolecular structures have several molecular degrees of freedom, global structural flexibility may also regulate the properties of metalloproteins. However, the influence of this factor has not been fully delineated in mechanistic studies of metalloproteins. Accordingly, we have investigated the relationship between global protein flexibility and the characteristics of a transition metal ion in the protein core using thiol-subtilisin (tSTL) with a Cys-coordinated Cu 2+ ion as a model system. Although tSTL has two Ca 2+ -binding sites, the Ca 2+ -binding status hardly affects its secondary structure. Nevertheless, guanidinium-induced denaturation and amide H/D exchange indicated the increase in the structural flexibility of tSTL by the removal of bound Ca 2+ ions. Electron paramagnetic resonance and absorption spectral changes have revealed that the protein flexibility determines the characteristics of a Cu 2+ ion in tSTL. Therefore, global protein flexibility should be recognized as an important factor that regulates the properties of metalloproteins. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Electronic transport on the spatial structure of the protein: Three-dimensional lattice model

International Nuclear Information System (INIS)

Sarmento, R.G.; Frazão, N.F.; Macedo-Filho, A.

2017-01-01

Highlights: • The electronic transport on the structure of the three-dimensional lattice model of the protein is studied. • The signing of the current–voltage is directly affected by permutations of the weak bonds in the structure. • Semiconductor behave of the proteins suggest a potential application in the development of novel biosensors. - Abstract: We report a numerical analysis of the electronic transport in protein chain consisting of thirty-six standard amino acids. The protein chains studied have three-dimensional structure, which can present itself in three distinct conformations and the difference consist in the presence or absence of thirteen hydrogen-bondings. Our theoretical method uses an electronic tight-binding Hamiltonian model, appropriate to describe the protein segments modeled by the amino acid chain. We note that the presence and the permutations between weak bonds in the structure of proteins are directly related to the signing of the current–voltage. Furthermore, the electronic transport depends on the effect of temperature. In addition, we have found a semiconductor behave in the models investigated and it suggest a potential application in the development of novel biosensors for molecular diagnostics.

Electronic transport on the spatial structure of the protein: Three-dimensional lattice model

Energy Technology Data Exchange (ETDEWEB)

Sarmento, R.G. [Departamento de Ciências Biológicas, Universidade Federal do Piauí, 64800-000 Floriano, PI (Brazil); Frazão, N.F. [Centro de Educação e Saúde, Universidade Federal de Campina Grande, 581750-000 Cuité, PB (Brazil); Macedo-Filho, A., E-mail: amfilho@gmail.com [Campus Prof. Antonio Geovanne Alves de Sousa, Universidade Estadual do Piauí, 64260-000 Piripiri, PI (Brazil)

2017-01-30

Highlights: • The electronic transport on the structure of the three-dimensional lattice model of the protein is studied. • The signing of the current–voltage is directly affected by permutations of the weak bonds in the structure. • Semiconductor behave of the proteins suggest a potential application in the development of novel biosensors. - Abstract: We report a numerical analysis of the electronic transport in protein chain consisting of thirty-six standard amino acids. The protein chains studied have three-dimensional structure, which can present itself in three distinct conformations and the difference consist in the presence or absence of thirteen hydrogen-bondings. Our theoretical method uses an electronic tight-binding Hamiltonian model, appropriate to describe the protein segments modeled by the amino acid chain. We note that the presence and the permutations between weak bonds in the structure of proteins are directly related to the signing of the current–voltage. Furthermore, the electronic transport depends on the effect of temperature. In addition, we have found a semiconductor behave in the models investigated and it suggest a potential application in the development of novel biosensors for molecular diagnostics.

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

Mathematical Modeling of Protein Misfolding Mechanisms in Neurological Diseases: A Historical Overview.

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Carbonell, Felix; Iturria-Medina, Yasser; Evans, Alan C

2018-01-01

Protein misfolding refers to a process where proteins become structurally abnormal and lose their specific 3-dimensional spatial configuration. The histopathological presence of misfolded protein (MP) aggregates has been associated as the primary evidence of multiple neurological diseases, including Prion diseases, Alzheimer's disease, Parkinson's disease, and Creutzfeldt-Jacob disease. However, the exact mechanisms of MP aggregation and propagation, as well as their impact in the long-term patient's clinical condition are still not well understood. With this aim, a variety of mathematical models has been proposed for a better insight into the kinetic rate laws that govern the microscopic processes of protein aggregation. Complementary, another class of large-scale models rely on modern molecular imaging techniques for describing the phenomenological effects of MP propagation over the whole brain. Unfortunately, those neuroimaging-based studies do not take full advantage of the tremendous capabilities offered by the chemical kinetics modeling approach. Actually, it has been barely acknowledged that the vast majority of large-scale models have foundations on previous mathematical approaches that describe the chemical kinetics of protein replication and propagation. The purpose of the current manuscript is to present a historical review about the development of mathematical models for describing both microscopic processes that occur during the MP aggregation and large-scale events that characterize the progression of neurodegenerative MP-mediated diseases.

A modeling strategy for G-protein coupled receptors

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Anna Kahler

2016-03-01

Full Text Available Cell responses can be triggered via G-protein coupled receptors (GPCRs that interact with small molecules, peptides or proteins and transmit the signal over the membrane via structural changes to activate intracellular pathways. GPCRs are characterized by a rather low sequence similarity and exhibit structural differences even for functionally closely related GPCRs. An accurate structure prediction for GPCRs is therefore not straightforward. We propose a computational approach that relies on the generation of several independent models based on different template structures, which are subsequently refined by molecular dynamics simulations. A comparison of their conformational stability and the agreement with GPCR-typical structural features is then used to select a favorable model. This strategy was applied to predict the structure of the herpesviral chemokine receptor US28 by generating three independent models based on the known structures of the chemokine receptors CXCR1, CXCR4, and CCR5. Model refinement and evaluation suggested that the model based on CCR5 exhibits the most favorable structural properties. In particular, the GPCR-typical structural features, such as a conserved water cluster or conserved non-covalent contacts, are present to a larger extent in the model based on CCR5 compared to the other models. A final model validation based on the recently published US28 crystal structure confirms that the CCR5-based model is the most accurate and exhibits 80.8% correctly modeled residues within the transmembrane helices. The structural agreement between the selected model and the crystal structure suggests that our modeling strategy may also be more generally applicable to other GPCRs of unknown structure.

Mathematical modeling of physiological systems: an essential tool for discovery.

Science.gov (United States)

Glynn, Patric; Unudurthi, Sathya D; Hund, Thomas J

2014-08-28

Mathematical models are invaluable tools for understanding the relationships between components of a complex system. In the biological context, mathematical models help us understand the complex web of interrelations between various components (DNA, proteins, enzymes, signaling molecules etc.) in a biological system, gain better understanding of the system as a whole, and in turn predict its behavior in an altered state (e.g. disease). Mathematical modeling has enhanced our understanding of multiple complex biological processes like enzyme kinetics, metabolic networks, signal transduction pathways, gene regulatory networks, and electrophysiology. With recent advances in high throughput data generation methods, computational techniques and mathematical modeling have become even more central to the study of biological systems. In this review, we provide a brief history and highlight some of the important applications of modeling in biological systems with an emphasis on the study of excitable cells. We conclude with a discussion about opportunities and challenges for mathematical modeling going forward. In a larger sense, the review is designed to help answer a simple but important question that theoreticians frequently face from interested but skeptical colleagues on the experimental side: "What is the value of a model?" Copyright © 2014 Elsevier Inc. All rights reserved.

Markov state models of protein misfolding

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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.

Dr. PIAS: an integrative system for assessing the druggability of protein-protein interactions

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Furuya Toshio

2011-02-01

Full Text Available Abstract Background The amount of data on protein-protein interactions (PPIs available in public databases and in the literature has rapidly expanded in recent years. PPI data can provide useful information for researchers in pharmacology and medicine as well as those in interactome studies. There is urgent need for a novel methodology or software allowing the efficient utilization of PPI data in pharmacology and medicine. Results To address this need, we have developed the 'Druggable Protein-protein Interaction Assessment System' (Dr. PIAS. Dr. PIAS has a meta-database that stores various types of information (tertiary structures, drugs/chemicals, and biological functions associated with PPIs retrieved from public sources. By integrating this information, Dr. PIAS assesses whether a PPI is druggable as a target for small chemical ligands by using a supervised machine-learning method, support vector machine (SVM. Dr. PIAS holds not only known druggable PPIs but also all PPIs of human, mouse, rat, and human immunodeficiency virus (HIV proteins identified to date. Conclusions The design concept of Dr. PIAS is distinct from other published PPI databases in that it focuses on selecting the PPIs most likely to make good drug targets, rather than merely collecting PPI data.

Controlling nonspecific protein adsorption in a plug-based microfluidic system by controlling interfacial chemistry using fluorous-phase surfactants.

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Roach, L Spencer; Song, Helen; Ismagilov, Rustem F

2005-02-01

Control of surface chemistry and protein adsorption is important for using microfluidic devices for biochemical analysis and high-throughput screening assays. This paper describes the control of protein adsorption at the liquid-liquid interface in a plug-based microfluidic system. The microfluidic system uses multiphase flows of immiscible fluorous and aqueous fluids to form plugs, which are aqueous droplets that are completely surrounded by fluorocarbon oil and do not come into direct contact with the hydrophobic surface of the microchannel. Protein adsorption at the aqueous-fluorous interface was controlled by using surfactants that were soluble in fluorocarbon oil but insoluble in aqueous solutions. Three perfluorinated alkane surfactants capped with different functional groups were used: a carboxylic acid, an alcohol, and a triethylene glycol group that was synthesized from commercially available materials. Using complementary methods of analysis, adsorption was characterized for several proteins (bovine serum albumin (BSA) and fibrinogen), including enzymes (ribonuclease A (RNase A) and alkaline phosphatase). These complementary methods involved characterizing adsorption in microliter-sized droplets by drop tensiometry and in nanoliter plugs by fluorescence microscopy and kinetic measurements of enzyme catalysis. The oligoethylene glycol-capped surfactant prevented protein adsorption in all cases. Adsorption of proteins to the carboxylic acid-capped surfactant in nanoliter plugs could be described by using the Langmuir model and tensiometry results for microliter drops. The microfluidic system was fabricated using rapid prototyping in poly(dimethylsiloxane) (PDMS). Black PDMS microfluidic devices, fabricated by curing a suspension of charcoal in PDMS, were used to measure the changes in fluorescence intensity more sensitively. This system will be useful for microfluidic bioassays, enzymatic kinetics, and protein crystallization, because it does not require

The Puf family of RNA-binding proteins in plants: phylogeny, structural modeling, activity and subcellular localization

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Tam Michael WC

2010-03-01

Full Text Available Abstract Background Puf proteins have important roles in controlling gene expression at the post-transcriptional level by promoting RNA decay and repressing translation. The Pumilio homology domain (PUM-HD is a conserved region within Puf proteins that binds to RNA with sequence specificity. Although Puf proteins have been well characterized in animal and fungal systems, little is known about the structural and functional characteristics of Puf-like proteins in plants. Results The Arabidopsis and rice genomes code for 26 and 19 Puf-like proteins, respectively, each possessing eight or fewer Puf repeats in their PUM-HD. Key amino acids in the PUM-HD of several of these proteins are conserved with those of animal and fungal homologs, whereas other plant Puf proteins demonstrate extensive variability in these amino acids. Three-dimensional modeling revealed that the predicted structure of this domain in plant Puf proteins provides a suitable surface for binding RNA. Electrophoretic gel mobility shift experiments showed that the Arabidopsis AtPum2 PUM-HD binds with high affinity to BoxB of the Drosophila Nanos Response Element I (NRE1 RNA, whereas a point mutation in the core of the NRE1 resulted in a significant reduction in binding affinity. Transient expression of several of the Arabidopsis Puf proteins as fluorescent protein fusions revealed a dynamic, punctate cytoplasmic pattern of localization for most of these proteins. The presence of predicted nuclear export signals and accumulation of AtPuf proteins in the nucleus after treatment of cells with leptomycin B demonstrated that shuttling of these proteins between the cytosol and nucleus is common among these proteins. In addition to the cytoplasmically enriched AtPum proteins, two AtPum proteins showed nuclear targeting with enrichment in the nucleolus. Conclusions The Puf family of RNA-binding proteins in plants consists of a greater number of members than any other model species studied to

Electrostatics of cysteine residues in proteins: parameterization and validation of a simple model.

Science.gov (United States)

Salsbury, Freddie R; Poole, Leslie B; Fetrow, Jacquelyn S

2012-11-01

One of the most popular and simple models for the calculation of pK(a) s from a protein structure is the semi-macroscopic electrostatic model MEAD. This model requires empirical parameters for each residue to calculate pK(a) s. Analysis of current, widely used empirical parameters for cysteine residues showed that they did not reproduce expected cysteine pK(a) s; thus, we set out to identify parameters consistent with the CHARMM27 force field that capture both the behavior of typical cysteines in proteins and the behavior of cysteines which have perturbed pK(a) s. The new parameters were validated in three ways: (1) calculation across a large set of typical cysteines in proteins (where the calculations are expected to reproduce expected ensemble behavior); (2) calculation across a set of perturbed cysteines in proteins (where the calculations are expected to reproduce the shifted ensemble behavior); and (3) comparison to experimentally determined pK(a) values (where the calculation should reproduce the pK(a) within experimental error). Both the general behavior of cysteines in proteins and the perturbed pK(a) in some proteins can be predicted reasonably well using the newly determined empirical parameters within the MEAD model for protein electrostatics. This study provides the first general analysis of the electrostatics of cysteines in proteins, with specific attention paid to capturing both the behavior of typical cysteines in a protein and the behavior of cysteines whose pK(a) should be shifted, and validation of force field parameters for cysteine residues. Copyright © 2012 Wiley Periodicals, Inc.

Sequence-based prediction of protein-binding sites in DNA: comparative study of two SVM models.

Science.gov (United States)

Park, Byungkyu; Im, Jinyong; Tuvshinjargal, Narankhuu; Lee, Wook; Han, Kyungsook

2014-11-01

As many structures of protein-DNA complexes have been known in the past years, several computational methods have been developed to predict DNA-binding sites in proteins. However, its inverse problem (i.e., predicting protein-binding sites in DNA) has received much less attention. One of the reasons is that the differences between the interaction propensities of nucleotides are much smaller than those between amino acids. Another reason is that DNA exhibits less diverse sequence patterns than protein. Therefore, predicting protein-binding DNA nucleotides is much harder than predicting DNA-binding amino acids. We computed the interaction propensity (IP) of nucleotide triplets with amino acids using an extensive dataset of protein-DNA complexes, and developed two support vector machine (SVM) models that predict protein-binding nucleotides from sequence data alone. One SVM model predicts protein-binding nucleotides using DNA sequence data alone, and the other SVM model predicts protein-binding nucleotides using both DNA and protein sequences. In a 10-fold cross-validation with 1519 DNA sequences, the SVM model that uses DNA sequence data only predicted protein-binding nucleotides with an accuracy of 67.0%, an F-measure of 67.1%, and a Matthews correlation coefficient (MCC) of 0.340. With an independent dataset of 181 DNAs that were not used in training, it achieved an accuracy of 66.2%, an F-measure 66.3% and a MCC of 0.324. Another SVM model that uses both DNA and protein sequences achieved an accuracy of 69.6%, an F-measure of 69.6%, and a MCC of 0.383 in a 10-fold cross-validation with 1519 DNA sequences and 859 protein sequences. With an independent dataset of 181 DNAs and 143 proteins, it showed an accuracy of 67.3%, an F-measure of 66.5% and a MCC of 0.329. Both in cross-validation and independent testing, the second SVM model that used both DNA and protein sequence data showed better performance than the first model that used DNA sequence data. To the best of

Validation of protein evaluation systems by means of milk production experiments with dairy cows.

NARCIS (Netherlands)

Straalen, van W.M.; Salaün, C.; Veen, W.A.G.; Rypkema, Y.S.; Hof, G.; Boxem, T.J.

1994-01-01

Protein evaluation systems (crude protein (CP), digestible crude protein (DCP), protein digested in the intestine (PDI), amino acids truly absorbed in the small intestine (AAT), absorbed protein (AP), metabolizable protein (MP), crude protein flow at the duodenum (AAS) and digestible protein in

Protein modelling of triterpene synthase genes from mangrove plants using Phyre2 and Swiss-model

Science.gov (United States)

Basyuni, M.; Wati, R.; Sulistiyono, N.; Hayati, R.; Sumardi; Oku, H.; Baba, S.; Sagami, H.

2018-03-01

Molecular cloning of five oxidosqualene cyclases (OSC) genes from Bruguiera gymnorrhiza, Kandelia candel, and Rhizophora stylosa had previously been cloned, characterized, and encoded mono and -multi triterpene synthases. The present study analyzed protein modelling of triterpene synthase genes from mangrove using Phyre2 and Swiss-model. The diversity was noted within protein modelling of triterpene synthases using Phyre2 from sequence identity (38-43%) and residue (696-703). RsM2 was distinguishable from others for template structure; it used lanosterol synthase as a template (PDB ID: w6j.1.A). By contrast, other genes used human lanosterol synthase (1w6k.1.A). The predicted bind sites were correlated with the product of triterpene synthase, the product of BgbAS was β-amyrin, while RsM1 contained a significant amount of β-amyrin. Similarly BgLUS and KcMS, both main products was lupeol, on the other hand, RsM2 with the outcome of taraxerol. Homology modelling revealed that 696 residues of BgbAS, BgLUS, RsM1, and RsM2 (91-92% of the amino acid sequence) had been modelled with 100% confidence by the single highest scoring template using Phyre2. This coverage was higher than Swiss-model (85-90%). The present study suggested that molecular cloning of triterpene genes provides useful tools for studying the protein modelling related regulation of isoprenoids biosynthesis in mangrove forests.

A feature-based approach to modeling protein-protein interaction hot spots.

Science.gov (United States)

Cho, Kyu-il; Kim, Dongsup; Lee, Doheon

2009-05-01

Identifying features that effectively represent the energetic contribution of an individual interface residue to the interactions between proteins remains problematic. Here, we present several new features and show that they are more effective than conventional features. By combining the proposed features with conventional features, we develop a predictive model for interaction hot spots. Initially, 54 multifaceted features, composed of different levels of information including structure, sequence and molecular interaction information, are quantified. Then, to identify the best subset of features for predicting hot spots, feature selection is performed using a decision tree. Based on the selected features, a predictive model for hot spots is created using support vector machine (SVM) and tested on an independent test set. Our model shows better overall predictive accuracy than previous methods such as the alanine scanning methods Robetta and FOLDEF, and the knowledge-based method KFC. Subsequent analysis yields several findings about hot spots. As expected, hot spots have a larger relative surface area burial and are more hydrophobic than other residues. Unexpectedly, however, residue conservation displays a rather complicated tendency depending on the types of protein complexes, indicating that this feature is not good for identifying hot spots. Of the selected features, the weighted atomic packing density, relative surface area burial and weighted hydrophobicity are the top 3, with the weighted atomic packing density proving to be the most effective feature for predicting hot spots. Notably, we find that hot spots are closely related to pi-related interactions, especially pi . . . pi interactions.

Structural study of the AOT reverse micellar system. Influence of attractive interactions induced by the solubilisation of native and modified proteins

International Nuclear Information System (INIS)

Cassin, Guillaume

1994-01-01

This research thesis reports the study of the influence of intra-micellar attractions on the thermodynamic behaviour of reverse micellar systems, as well as of the effects induced by the solubilisation of natives or modified proteins. The author proposes a model to explain the decrease of attractions between droplets when the volume fraction occupied by reverse micelles increases. This model which highlights the importance of depletion forces between reverse micelles, allows the building up of a theoretical relationship between the bonding parameter and the volume fraction of reverse micelles. In order to understand the appearance of an attractive term related to the solubilisation of native cytochrome-c in these systems, this protein has been chemically modified. The author highlights the role of the charge born by a micellar probe on the thermodynamic behaviour of micro-emulsions. Then, the author applies the model of dimerizing adhesive spheres to reverse micellar systems containing native cytochrome-c. He shows that theoretical predictions of this model are in agreement with obtained experimental results [fr

Hierarchical graphs for rule-based modeling of biochemical systems

Directory of Open Access Journals (Sweden)

Hu Bin

2011-02-01

Full Text Available Abstract Background In rule-based modeling, graphs are used to represent molecules: a colored vertex represents a component of a molecule, a vertex attribute represents the internal state of a component, and an edge represents a bond between components. Components of a molecule share the same color. Furthermore, graph-rewriting rules are used to represent molecular interactions. A rule that specifies addition (removal of an edge represents a class of association (dissociation reactions, and a rule that specifies a change of a vertex attribute represents a class of reactions that affect the internal state of a molecular component. A set of rules comprises an executable model that can be used to determine, through various means, the system-level dynamics of molecular interactions in a biochemical system. Results For purposes of model annotation, we propose the use of hierarchical graphs to represent structural relationships among components and subcomponents of molecules. We illustrate how hierarchical graphs can be used to naturally document the structural organization of the functional components and subcomponents of two proteins: the protein tyrosine kinase Lck and the T cell receptor (TCR complex. We also show that computational methods developed for regular graphs can be applied to hierarchical graphs. In particular, we describe a generalization of Nauty, a graph isomorphism and canonical labeling algorithm. The generalized version of the Nauty procedure, which we call HNauty, can be used to assign canonical labels to hierarchical graphs or more generally to graphs with multiple edge types. The difference between the Nauty and HNauty procedures is minor, but for completeness, we provide an explanation of the entire HNauty algorithm. Conclusions Hierarchical graphs provide more intuitive formal representations of proteins and other structured molecules with multiple functional components than do the regular graphs of current languages for

Can understanding the packing of side chains improve the design of protein-protein interactions?

Science.gov (United States)

Zhou, Alice; O'Hern, Corey; Regan, Lynne

2011-03-01

With the long-term goal to improve the design of protein-protein interactions, we have begun extensive computational studies to understand how side-chains of key residues of binding partners geometrically fit together at protein-peptide interfaces, e.g. the tetratrico-peptide repeat protein and its cognate peptide). We describe simple atomic-scale models of hydrophobic dipeptides, which include hard-core repulsion, bond length and angle constraints, and Van der Waals attraction. By completely enumerating all minimal energy structures in these systems, we are able to reproduce important features of the probability distributions of side chain dihedral angles of hydrophic residues in the protein data bank. These results are the crucial first step in developing computational models that can predict the side chain conformations of residues at protein-peptide interfaces. CSO acknowledges support from NSF grant no. CMMT-1006527.

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...

Expression, stabilization and purification of membrane proteins via diverse protein synthesis systems and detergents involving cell-free associated with self-assembly peptide surfactants.

Science.gov (United States)

Zheng, Xuan; Dong, Shuangshuang; Zheng, Jie; Li, Duanhua; Li, Feng; Luo, Zhongli

2014-01-01

G-protein coupled receptors (GPCRs) are involved in regulating most of physiological actions and metabolism in the bodies, which have become most frequently addressed therapeutic targets for various disorders and diseases. Purified GPCR-based drug discoveries have become routine that approaches to structural study, novel biophysical and biochemical function analyses. However, several bottlenecks that GPCR-directed drugs need to conquer the problems including overexpression, solubilization, and purification as well as stabilization. The breakthroughs are to obtain efficient protein yield and stabilize their functional conformation which are both urgently requiring of effective protein synthesis system methods and optimal surfactants. Cell-free protein synthesis system is superior to the high yields and post-translation modifications, and early signs of self-assembly peptide detergents also emerged to superiority in purification of membrane proteins. We herein focus several predominant protein synthesis systems and surfactants involving the novel peptide detergents, and uncover the advantages of cell-free protein synthesis system with self-assembling peptide detergents in purification of functional GPCRs. This review is useful to further study in membrane proteins as well as the new drug exploration. Copyright © 2014 Elsevier Inc. All rights reserved.

Compartmental modelling of the pharmacokinetics of a breast cancer resistance protein.

Science.gov (United States)

Grandjean, Thomas R B; Chappell, Mike J; Yates, James T W; Jones, Kevin; Wood, Gemma; Coleman, Tanya

2011-11-01

A mathematical model for the pharmacokinetics of Hoechst 33342 following administration into a culture medium containing a population of transfected cells (HEK293 hBCRP) with a potent breast cancer resistance protein inhibitor, Fumitremorgin C (FTC), present is described. FTC is reported to almost completely annul resistance mediated by BCRP in vitro. This non-linear compartmental model has seven macroscopic sub-units, with 14 rate parameters. It describes the relationship between the concentration of Hoechst 33342 and FTC, initially spiked in the medium, and the observed change in fluorescence due to Hoechst 33342 binding to DNA. Structural identifiability analysis has been performed using two methods, one based on the similarity transformation/exhaustive modelling approach and the other based on the differential algebra approach. The analyses demonstrated that all models derived are uniquely identifiable for the experiments/observations available. A kinetic modelling software package, namely FACSIMILE (MPCA Software, UK), was used for parameter fitting and to obtain numerical solutions for the system equations. Model fits gave very good agreement with in vitro data provided by AstraZeneca across a variety of experimental scenarios. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Acute moderate elevation of TNF-{alpha} does not affect systemic and skeletal muscle protein turnover in healthy humans

DEFF Research Database (Denmark)

Petersen, Anne Marie; Plomgaard, Peter; Fischer, Christian P

2009-01-01

-alpha infusion (rhTNF-alpha). We hypothesize that TNF-alpha increases human muscle protein breakdown and/or inhibit synthesis. Subjects and Methods: Using a randomized controlled, crossover design post-absorptive healthy young males (n=8) were studied 2 hours under basal conditions followed by 4 hours infusion...... with the phenylalanine 3-compartment model showed similar muscle synthesis, breakdown and net muscle degradation after 2 hours basal and after 4 hours Control or rhTNF-alpha infusion. Conclusion: This study is the first to show in humans that TNF-alpha does not affect systemic and skeletal muscle protein turnover, when......Context: Skeletal muscle wasting has been associated with elevations in circulating inflammatory cytokines, in particular TNF-alpha. Objective: In this study, we investigated whether TNF-alpha affects human systemic and skeletal muscle protein turnover, via a 4 hours recombinant human TNF...