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...

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

Remarks on High Energy Evolution

OpenAIRE

Kovner, Alex; Lublinsky, Michael

2005-01-01

We make several remarks on the B-JIMWLK hierarchy. First, we present a simple and instructive derivation of this equation by considering an arbitrary projectile wave function with small number of valence gluons. We also generalize the equation by including corrections which incorporate effects of high density in the projectile wave function. Second, we systematically derive the dipole model approximation to the hierarchy. We show that in the dipole approximation the hierarchy has a simplifyin...

The PMDB Protein Model Database

Science.gov (United States)

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

2006-01-01

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

Concluding remarks

International Nuclear Information System (INIS)

Nariai, H.

2007-01-01

This document provides the speech presented by Hideki Nariai on May 2007 at the workshop on transparency of nuclear regulatory activities. It aims to propose concluding remarks concerning nuclear safety and the necessity to be transparent to the general public. (A.L.B.)

Transferable coarse-grained potential for de novo protein folding and design.

Directory of Open Access Journals (Sweden)

Ivan Coluzza

Full Text Available Protein folding and design are major biophysical problems, the solution of which would lead to important applications especially in medicine. Here we provide evidence of how a novel parametrization of the Caterpillar model may be used for both quantitative protein design and folding. With computer simulations it is shown that, for a large set of real protein structures, the model produces designed sequences with similar physical properties to the corresponding natural occurring sequences. The designed sequences require further experimental testing. For an independent set of proteins, previously used as benchmark, the correct folded structure of both the designed and the natural sequences is also demonstrated. The equilibrium folding properties are characterized by free energy calculations. The resulting free energy profiles not only are consistent among natural and designed proteins, but also show a remarkable precision when the folded structures are compared to the experimentally determined ones. Ultimately, the updated Caterpillar model is unique in the combination of its fundamental three features: its simplicity, its ability to produce natural foldable designed sequences, and its structure prediction precision. It is also remarkable that low frustration sequences can be obtained with such a simple and universal design procedure, and that the folding of natural proteins shows funnelled free energy landscapes without the need of any potentials based on the native structure.

Modelling of microbial polyhydroxyalkanoate surface binding protein PhaP for rational mutagenesis.

Science.gov (United States)

Zhao, Hongyu; Yao, Zhenyu; Chen, Xiangbin; Wang, Xinquan; Chen, Guo-Qiang

2017-11-01

Phasins are unusual amphiphilic proteins that bind to microbial polyhydroxyalkanoate (PHA) granules in nature and show great potential for various applications in biotechnology and medicine. Despite their remarkable diversity, only the crystal structure of PhaP A h from Aeromonas hydrophila has been solved to date. Based on the structure of PhaP A h , homology models of PhaP A z from Azotobacter sp. FA-8 and PhaP TD from Halomonas bluephagenesis TD were successfully established, allowing rational mutagenesis to be conducted to enhance the stability and surfactant properties of these proteins. PhaP A z mutants, including PhaP A z Q38L and PhaP A z Q78L, as well as PhaP TD mutants, including PhaP TD Q38M and PhaP TD Q72M, showed better emulsification properties and improved thermostability (6-10°C higher melting temperatures) compared with their wild-type homologues under the same conditions. Importantly, the established PhaP homology-modelling approach, based on the high-resolution structure of PhaP A h , can be generalized to facilitate the study of other PhaP members. © 2017 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

RCK: accurate and efficient inference of sequence- and structure-based protein-RNA binding models from RNAcompete data.

Science.gov (United States)

Orenstein, Yaron; Wang, Yuhao; Berger, Bonnie

2016-06-15

Protein-RNA interactions, which play vital roles in many processes, are mediated through both RNA sequence and structure. CLIP-based methods, which measure protein-RNA binding in vivo, suffer from experimental noise and systematic biases, whereas in vitro experiments capture a clearer signal of protein RNA-binding. Among them, RNAcompete provides binding affinities of a specific protein to more than 240 000 unstructured RNA probes in one experiment. The computational challenge is to infer RNA structure- and sequence-based binding models from these data. The state-of-the-art in sequence models, Deepbind, does not model structural preferences. RNAcontext models both sequence and structure preferences, but is outperformed by GraphProt. Unfortunately, GraphProt cannot detect structural preferences from RNAcompete data due to the unstructured nature of the data, as noted by its developers, nor can it be tractably run on the full RNACompete dataset. We develop RCK, an efficient, scalable algorithm that infers both sequence and structure preferences based on a new k-mer based model. Remarkably, even though RNAcompete data is designed to be unstructured, RCK can still learn structural preferences from it. RCK significantly outperforms both RNAcontext and Deepbind in in vitro binding prediction for 244 RNAcompete experiments. Moreover, RCK is also faster and uses less memory, which enables scalability. While currently on par with existing methods in in vivo binding prediction on a small scale test, we demonstrate that RCK will increasingly benefit from experimentally measured RNA structure profiles as compared to computationally predicted ones. By running RCK on the entire RNAcompete dataset, we generate and provide as a resource a set of protein-RNA structure-based models on an unprecedented scale. Software and models are freely available at http://rck.csail.mit.edu/ bab@mit.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by

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

Concluding remarks

International Nuclear Information System (INIS)

Patrick, W.C.

1996-01-01

This section contains the concluding remarks of the workshop on rock mechanics issues in repository design and performance assessment. Technical issues such as spatial variability of rock properties, rock mass strength, measurement of loads, evaluation of long-term seal performance, and integration of data into design were discussed. Programmatic issues such as development of a coherent and consistent design methodology and implementation of that methodology were also reiterated

Effect of altering local protein fluctuations using artificial intelligence

Directory of Open Access Journals (Sweden)

Katsuhiko Nishiyama

2017-03-01

Full Text Available The fluctuations in Arg111, a significantly fluctuating residue in cathepsin K, were locally regulated by modifying Arg111 to Gly111. The binding properties of 15 dipeptides in the modified protein were analyzed by molecular simulations, and modeled as decision trees using artificial intelligence. The decision tree of the modified protein significantly differed from that of unmodified cathepsin K, and the Arg-to-Gly modification exerted a remarkable effect on the peptide binding properties. By locally regulating the fluctuations of a protein, we may greatly alter the original functions of the protein, enabling novel applications in several fields.

Effect of altering local protein fluctuations using artificial intelligence

Science.gov (United States)

Nishiyama, Katsuhiko

2017-03-01

The fluctuations in Arg111, a significantly fluctuating residue in cathepsin K, were locally regulated by modifying Arg111 to Gly111. The binding properties of 15 dipeptides in the modified protein were analyzed by molecular simulations, and modeled as decision trees using artificial intelligence. The decision tree of the modified protein significantly differed from that of unmodified cathepsin K, and the Arg-to-Gly modification exerted a remarkable effect on the peptide binding properties. By locally regulating the fluctuations of a protein, we may greatly alter the original functions of the protein, enabling novel applications in several fields.

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.

Theories of superconductivity (a few remarks)

International Nuclear Information System (INIS)

Ginzburg, V.L.

1992-01-01

The early history in the development of superconductivity. Idea of pairing, Schafroth and BCS types of theories. Some remarks on present state of the microscopical theory of high-temperature superconductors (HTSC). Mean field macroscopic theory of superconductivity and its specific features in HTSC. About generalized macroscopic theory applicable in critical region. Concluding remarks. (orig.)

Composition of Overlapping Protein-Protein and Protein-Ligand Interfaces.

Directory of Open Access Journals (Sweden)

Ruzianisra Mohamed

Full Text Available Protein-protein interactions (PPIs play a major role in many biological processes and they represent an important class of targets for therapeutic intervention. However, targeting PPIs is challenging because often no convenient natural substrates are available as starting point for small-molecule design. Here, we explored the characteristics of protein interfaces in five non-redundant datasets of 174 protein-protein (PP complexes, and 161 protein-ligand (PL complexes from the ABC database, 436 PP complexes, and 196 PL complexes from the PIBASE database and a dataset of 89 PL complexes from the Timbal database. In all cases, the small molecule ligands must bind at the respective PP interface. We observed similar amino acid frequencies in all three datasets. Remarkably, also the characteristics of PP contacts and overlapping PL contacts are highly similar.

A Mesoscopic Model for Protein-Protein Interactions in Solution

OpenAIRE

Lund, Mikael; Jönsson, Bo

2003-01-01

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

A self-organizing algorithm for modeling protein loops.

Directory of Open Access Journals (Sweden)

Pu Liu

2009-08-01

Full Text Available Protein loops, the flexible short segments connecting two stable secondary structural units in proteins, play a critical role in protein structure and function. Constructing chemically sensible conformations of protein loops that seamlessly bridge the gap between the anchor points without introducing any steric collisions remains an open challenge. A variety of algorithms have been developed to tackle the loop closure problem, ranging from inverse kinematics to knowledge-based approaches that utilize pre-existing fragments extracted from known protein structures. However, many of these approaches focus on the generation of conformations that mainly satisfy the fixed end point condition, leaving the steric constraints to be resolved in subsequent post-processing steps. In the present work, we describe a simple solution that simultaneously satisfies not only the end point and steric conditions, but also chirality and planarity constraints. Starting from random initial atomic coordinates, each individual conformation is generated independently by using a simple alternating scheme of pairwise distance adjustments of randomly chosen atoms, followed by fast geometric matching of the conformationally rigid components of the constituent amino acids. The method is conceptually simple, numerically stable and computationally efficient. Very importantly, additional constraints, such as those derived from NMR experiments, hydrogen bonds or salt bridges, can be incorporated into the algorithm in a straightforward and inexpensive way, making the method ideal for solving more complex multi-loop problems. The remarkable performance and robustness of the algorithm are demonstrated on a set of protein loops of length 4, 8, and 12 that have been used in previous studies.

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.

Seven remarkable days

CERN Document Server

This has been a truly remarkable seven days for CERN. Things have moved so fast that it has sometimes been hard to separate fact from fiction – all the more so since facts have often seemed too good to be true. It’s been a week of many firsts. Monday was the first time we’ve had two captured beams in the LHC. It’s the first time the LHC has functioned as a particle accelerator, boosting particles to the highest beam energy so far achieved at CERN. And it’s been a week in which we’ve seen the highest energy proton-proton collisions ever produced at CERN: our last hadron collider, the SPS was a proton-antiproton collider, a technically simpler machine than the LHC. This week’s successes are all the more remarkable precisely because of the complexity of the LHC. Unlike the SPS collider, it is two accelerators not one, making the job of commissioning nearly twice as difficult. I’d like to express my heartfelt thanks and congra...

Altered protein glycosylation predicts Alzheimer's disease and modulates its pathology in disease model Drosophila.

Science.gov (United States)

Frenkel-Pinter, Moran; Stempler, Shiri; Tal-Mazaki, Sharon; Losev, Yelena; Singh-Anand, Avnika; Escobar-Álvarez, Daniela; Lezmy, Jonathan; Gazit, Ehud; Ruppin, Eytan; Segal, Daniel

2017-08-01

The pathological hallmarks of Alzheimer's disease (AD) are pathogenic oligomers and fibrils of misfolded amyloidogenic proteins (e.g., β-amyloid and hyper-phosphorylated tau in AD), which cause progressive loss of neurons in the brain and nervous system. Although deviations from normal protein glycosylation have been documented in AD, their role in disease pathology has been barely explored. Here our analysis of available expression data sets indicates that many glycosylation-related genes are differentially expressed in brains of AD patients compared with healthy controls. The robust differences found enabled us to predict the occurrence of AD with remarkable accuracy in a test cohort and identify a set of key genes whose expression determines this classification. We then studied in vivo the effect of reducing expression of homologs of 6 of these genes in transgenic Drosophila overexpressing human tau, a well-established invertebrate AD model. These experiments have led to the identification of glycosylation genes that may augment or ameliorate tauopathy phenotypes. Our results indicate that OstDelta, l(2)not and beta4GalT7 are tauopathy suppressors, whereas pgnat5 and CG33303 are enhancers, of tauopathy. These results suggest that specific alterations in protein glycosylation may play a causal role in AD etiology. Copyright © 2017 Elsevier Inc. All rights reserved.

Hydra meiosis reveals unexpected conservation of structural synaptonemal complex proteins across metazoans.

Science.gov (United States)

Fraune, Johanna; Alsheimer, Manfred; Volff, Jean-Nicolas; Busch, Karoline; Fraune, Sebastian; Bosch, Thomas C G; Benavente, Ricardo

2012-10-09

The synaptonemal complex (SC) is a key structure of meiosis, mediating the stable pairing (synapsis) of homologous chromosomes during prophase I. Its remarkable tripartite structure is evolutionarily well conserved and can be found in almost all sexually reproducing organisms. However, comparison of the different SC protein components in the common meiosis model organisms Saccharomyces cerevisiae, Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, and Mus musculus revealed no sequence homology. This discrepancy challenged the hypothesis that the SC arose only once in evolution. To pursue this matter we focused on the evolution of SYCP1 and SYCP3, the two major structural SC proteins of mammals. Remarkably, our comparative bioinformatic and expression studies revealed that SYCP1 and SYCP3 are also components of the SC in the basal metazoan Hydra. In contrast to previous assumptions, we therefore conclude that SYCP1 and SYCP3 form monophyletic groups of orthologous proteins across metazoans.

Welcome remarks

International Nuclear Information System (INIS)

Zhao Hong

1993-01-01

In his opening remarks Mr. Zhao Hong stressed the importance of nuclear power for further economic development. He noticed that one of the main factors to obstruct the progress of nuclear energy is nuclear dread in public psychology and that enhancement of the public acceptance of nuclear power is an important task to promote the development of nuclear power. Than he described activities in China in public relation work in the field of nuclear energy. Importance of international cooperation on peaceful use of nuclear energy and supporting non-proliferation regime was stressed

NRC closing remarks

International Nuclear Information System (INIS)

Coffman, F.

1994-01-01

This section contains the edited transcript of the NRC closing remarks made by Mr. Franklin Coffman (Chief, Human Factors Branch, Office of Nuclear Regulatory Research) and Dr. Cecil Thomas (Deputy Director, Division of Reactor Controls and Human Factors, Office of Nuclear Reactor Regulation). This editing consisted of minimal editing to correct grammar and remove extraneous references to microphone volume, etc

The nonstructural proteins of Pneumoviruses are remarkably distinct in substrate diversity and specificity.

Science.gov (United States)

Ribaudo, Michael; Barik, Sailen

2017-11-06

Interferon (IFN) inhibits viruses by inducing several hundred cellular genes, aptly named 'interferon (IFN)-stimulated genes' (ISGs). The only two RNA viruses of the Pneumovirus genus of the Paramyxoviridae family, namely Respiratory Syncytial Virus (RSV) and Pneumonia Virus of Mice (PVM), each encode two nonstructural (NS) proteins that share no sequence similarity but yet suppress IFN. Since suppression of IFN underlies the ability of these viruses to replicate in the host cells, the mechanism of such suppression has become an important area of research. This Short Report is an important extension of our previous efforts in defining this mechanism. We show that, like their PVM counterparts, the RSV NS proteins also target multiple members of the ISG family. While significantly extending the substrate repertoire of the RSV NS proteins, these results, unexpectedly, also reveal that the target preferences of the NS proteins of the two viruses are entirely different. This is surprising since the two Pneumoviruses are phylogenetically close with similar genome organization and gene function, and the NS proteins of both also serve as suppressors of host IFN response. The finding that the NS proteins of the two highly similar viruses suppress entirely different members of the ISG family raises intriguing questions of pneumoviral NS evolution and mechanism of action.

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

Science.gov (United States)

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

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

Unbound color, prefaced by remarks on baryon spectroscopy

International Nuclear Information System (INIS)

Greenberg, O.W.

Theoretical and experimental issues related to the possibility that color is unbound are surveyed. This implies that quarks, gluons and other particles carrying color can exist as isolated objects. It is surprisingly difficult to distinguish models with unbound color from those in which color is permanently confined. None-the-less, the present situation seems discouraging for unbound color because there is no unambiguous support for it and because the crucial prediction of formation of a colored gluon in e + e - collisions has been ruled out wherever sufficient data exists. The above survey is prefaced by remarks on the symmetric quark model for baryon spectroscopy

Some remarks on modeling uncertainties

International Nuclear Information System (INIS)

Ronen, Y.

1983-01-01

Several topics related to the question of modeling uncertainties are considered. The first topic is related to the use of the generalized bias operator method for modeling uncertainties. The method is expanded to a more general form of operators. The generalized bias operator is also used in the inverse problem and applied to determine the anisotropic scattering law. The last topic discussed is related to the question of the limit to accuracy and how to establish its value. (orig.) [de

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 ...

Remarks of Joseph Marrone

International Nuclear Information System (INIS)

Marrone, J.

1985-01-01

The author's remarks are directed primarily at proposals that have been made that would substantially tort law with respect to radiation claims in order to ease the ability of claimants to recovery damages from defendants. The change would be based upon what had been assumed to be a ''scientific'' means of measuring the ''probability'' that exposure to ionizing radiation was the case of a cancer in a particular claimant. The remarks are divided into three parts: a summary description of the nuclear insurance pools, including the tort radiation claims filed against the pools; and a brief description of claims against the Federal Government and its contractors; an examination of the elementary principles of tort law, and an outline of the threat that has developed that would transform it into a hybrid social benefits program; and comment on the danger to the integrity of science when it is injected into the legislative process

A Soluble, Folded Protein without Charged Amino Acid Residues

DEFF Research Database (Denmark)

Højgaard, Casper; Kofoed, Christian; Espersen, Roall

2016-01-01

side chains can maintain solubility, stability, and function. As a model, we used a cellulose-binding domain from Cellulomonas fimi, which, among proteins of more than 100 amino acids, presently is the least charged in the Protein Data Bank, with a total of only four titratable residues. We find......Charges are considered an integral part of protein structure and function, enhancing solubility and providing specificity in molecular interactions. We wished to investigate whether charged amino acids are indeed required for protein biogenesis and whether a protein completely free of titratable...... that the protein shows a surprising resilience toward extremes of pH, demonstrating stability and function (cellulose binding) in the pH range from 2 to 11. To ask whether the four charged residues present were required for these properties of this protein, we altered them to nontitratable ones. Remarkably...

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)

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

What determines the structures of native folds of proteins?

International Nuclear Information System (INIS)

Trovato, Antonio; Hoang, Trinh X; Banavar, Jayanth R; Maritan, Amos; Seno, Flavio

2005-01-01

We review a simple physical model (Hoang et al 2004 Proc. Natl Acad. Sci. USA 101 7960, Banavar et al 2004 Phys. Rev. E at press) which captures the essential physico-chemical ingredients that determine protein structure, such as the inherent anisotropy of a chain molecule, the geometrical and energetic constraints placed by hydrogen bonds, sterics, and hydrophobicity. Within this framework, marginally compact conformations resembling the native state folds of proteins emerge as competing minima in the free energy landscape. Here we demonstrate that a hydrophobic-polar (HP) sequence composed of regularly repeated patterns has as its ground state a β-helical structure remarkably similar to a known architecture in the Protein Data Bank

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.

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

Remarks on lattice gauge models

International Nuclear Information System (INIS)

Grosse, H.

1981-01-01

The author reports a study of the phase structure of lattice gauge models where one takes as a gauge group a non-abelian discrete subgroup of SU(3). In addition he comments on a lattice action proposed recently by Manton and observes that it violates a positivity property. (Auth.)

Remarks on lattice gauge models

International Nuclear Information System (INIS)

Grosse, H.

1981-01-01

The author reports on a study of the phase structure of lattice gauge models where one takes as a gauge group a non-abelian discrete subgroup of SU(3). In addition he comments on a lattice action proposed recently by Manton (1980) and observes that it violates a positivity property. (Auth.)

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.

Remarks on non compact sigma models

International Nuclear Information System (INIS)

Brunini, S.A.; Gomes, M.; Silva, A.J. da.

1988-01-01

O(N,1) noncompact sigma models quantized in an indefinite metric space. In two dimensions, by a direct computation the existence of a positive metric subspace where the S matrix is unitary. Is proved the properties of the model as function of the temperature are investigated in various space time dimensions. (author) [pt

Mechanism of the G-protein mimetic nanobody binding to a muscarinic G-protein-coupled receptor.

Science.gov (United States)

Miao, Yinglong; McCammon, J Andrew

2018-03-20

Protein-protein binding is key in cellular signaling processes. Molecular dynamics (MD) simulations of protein-protein binding, however, are challenging due to limited timescales. In particular, binding of the medically important G-protein-coupled receptors (GPCRs) with intracellular signaling proteins has not been simulated with MD to date. Here, we report a successful simulation of the binding of a G-protein mimetic nanobody to the M 2 muscarinic GPCR using the robust Gaussian accelerated MD (GaMD) method. Through long-timescale GaMD simulations over 4,500 ns, the nanobody was observed to bind the receptor intracellular G-protein-coupling site, with a minimum rmsd of 2.48 Å in the nanobody core domain compared with the X-ray structure. Binding of the nanobody allosterically closed the orthosteric ligand-binding pocket, being consistent with the recent experimental finding. In the absence of nanobody binding, the receptor orthosteric pocket sampled open and fully open conformations. The GaMD simulations revealed two low-energy intermediate states during nanobody binding to the M 2 receptor. The flexible receptor intracellular loops contribute remarkable electrostatic, polar, and hydrophobic residue interactions in recognition and binding of the nanobody. These simulations provided important insights into the mechanism of GPCR-nanobody binding and demonstrated the applicability of GaMD in modeling dynamic protein-protein interactions.

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.

Extremophilic Acinetobacter Strains from High-Altitude Lakes in Argentinean Puna: Remarkable UV-B Resistance and Efficient DNA Damage Repair

Science.gov (United States)

Albarracín, Virginia Helena; Pathak, Gopal P.; Douki, Thierry; Cadet, Jean; Borsarelli, Claudio Darío; Gärtner, Wolfgang; Farias, María Eugenia

2012-06-01

High-Altitude Andean Lakes (HAAL) of the South American Andes are almost unexplored ecosystems of shallow lakes. The HAAL are recognized by a remarkably high UV exposure, strong changes in temperature and salinity, and a high content of toxic elements, especially arsenic. Being exposed to remarkably extreme conditions, they have been classified as model systems for the study of life on other planets. Particularly, Acinetobacter strains isolated from the HAAL were studied for their survival competence under strong UV-B irradiation. Clinical isolates, Acinetobacter baumannii and Acinetobacter johnsonii, served as reference material. Whereas the reference strains rapidly lost viability under UV-B irradiation, most HAAL-derived strains readily survived this exposure and showed less change in cell number after the treatment. Controls for DNA repair activity, comparing dark repair (DR) or photo repair (PR), gave evidence for the involvement of photolyases in the DNA repair. Comparative measurements by HPLC-mass spectrometry detected the number of photoproducts: bipyrimidine dimers under both PR and DR treatments were more efficiently repaired in the HAAL strains (up to 85 % PR and 38 % DR) than in the controls (31 % PR and zero DR ability). Analysis of cosmid-cloned total genomic DNA from the most effective DNA-photorepair strain (Ver3) yielded a gene (HQ443199) encoding a protein with clear photolyase signatures belonging to class I CPD-photolyases. Despite the relatively low sequence similarity of 41 % between the enzymes from Ver3 and from E. coli (PDB 1DNPA), a model-building approach revealed a high structural homology to the CPD-photolyase of E. coli.

Some remarks about large p/sub perpendicular/ spin effects

International Nuclear Information System (INIS)

Field, R.D.

1977-01-01

A discussion of the ingredients necessary to make predictions concerning single and double spin measurements in large p/sub perpendicular to/ inclusive processes is presented. Remarks are made as to what might be expected and what might be learned from such measurements. Various models for the production of large p/sub perpendicular to/ mesons have quite different spin structure and hence can be expected to give differing predictions. However, it is not possible at this time to make quantitative calculations, and it is possible (not probable) that the interesting spin observables will be negligibly small

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.

Concluding Remarks | Ewing | Rwanda Journal

African Journals Online (AJOL)

Rwanda Journal. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives · Journal Home > Vol 2, No 2 (2015) >. Log in or Register to get access to full text downloads. Username, Password, Remember me, or Register. Concluding Remarks. Helen Ewing. Abstract. No Abstract. Full Text:.

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

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.

Hydra meiosis reveals unexpected conservation of structural synaptonemal complex proteins across metazoans

OpenAIRE

Fraune, Johanna; Alsheimer, Manfred; Volff, Jean-Nicolas; Busch, Karoline; Fraune, Sebastian; Bosch, Thomas C. G.; Benavente, Ricardo

2012-01-01

The synaptonemal complex (SC) is a key structure of meiosis, mediating the stable pairing (synapsis) of homologous chromosomes during prophase I. Its remarkable tripartite structure is evolutionarily well conserved and can be found in almost all sexually reproducing organisms. However, comparison of the different SC protein components in the common meiosis model organisms Saccharomyces cerevisiae, Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, and Mus musculus revealed...

Protein Folding: Search for Basic Physical Models

Directory of Open Access Journals (Sweden)

Ivan Y. Torshin

2003-01-01

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

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...

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

Science.gov (United States)

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.

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/.

The remarkably high excitation planetary nebula GC 6537.

Science.gov (United States)

Aller, L H; Hung, S; Feibelman, W A

1999-05-11

NGC 6537 is an unusually high excitation point symmetric planetary nebula with a rich spectrum. Its kinematical structures are of special interest. We are here primarily concerned with the high resolution spectrum as revealed by the Hamilton echelle Spectrograph at Lick Observatory (resolution approximately 0.2 A) and supplemented by UV and near-UV data. These extensive data permit a determination of interstellar extinction, plasma diagnostics, and ionic concentrations. The photoionization models that have been used successfully for many planetary nebulae are not entirely satisfactory here. The plasma electron temperature of a photoionization model cannot much exceed 20,000 K, but plasma diagnostics show that regions emitting radiation of highly ionized atoms such as [NeIV] and [NeV] are much hotter, showing that shock excitation must be important, as suggested by the remarkable kinematics of this object. Hence, instead of employing a strict photoionization model, we are guided by the nebular diagnostics, which reveal how electron temperature varies with ionization potential and accommodates density effects. The predictions of the photoionization model may be useful in estimating ionization correction factor. In effect, we have estimated the chemical composition by using both photoionization and shock considerations.

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.

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.

Remarks on superconductive networks

International Nuclear Information System (INIS)

Dominguez, D.; Lopez, A.R.N.; Simonin, J.M.

1989-01-01

Some remarks on the determination of the normal-superconductor phase boundary in random superconductive networks are made. A recently reported work by Soukoulis, Grest and Li which introduces weak links between nodes as these are removed in the site percolation problem is discussed. By the analysis of two simple geometries, it is shown that this procedure introduces spurious effects which mask the physical properties of the system. These affect in particular the field slope critical index and the sharpness of the normal-superconductor boundary. (Author)

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.

Thermostable trypsin conjugates immobilized to biogenic magnetite show a high operational stability and remarkable reusability for protein digestion

Science.gov (United States)

Pečová, M.; Šebela, M.; Marková, Z.; Poláková, K.; Čuda, J.; Šafářová, K.; Zbořil, R.

2013-03-01

In this work, magnetosomes produced by microorganisms were chosen as a suitable magnetic carrier for covalent immobilization of thermostable trypsin conjugates with an expected applicability for efficient and rapid digestion of proteins at elevated temperatures. First, a biogenic magnetite was isolated from Magnetospirillum gryphiswaldense and its free surface was coated with the natural polysaccharide chitosan containing free amino and hydroxy groups. Prior to covalent immobilization, bovine trypsin was modified by conjugating with α-, β- and γ-cyclodextrin. Modified trypsin was bound to the magnetic carriers via amino groups using 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide and N-hydroxysulfosuccinimide as coupling reagents. The magnetic biomaterial was characterized by magnetometric analysis and electron microscopy. With regard to their biochemical properties, the immobilized trypsin conjugates showed an increased resistance to elevated temperatures, eliminated autolysis, had an unchanged pH optimum and a significant storage stability and reusability. Considering these parameters, the presented enzymatic system exhibits properties that are superior to those of trypsin forms obtained by other frequently used approaches. The proteolytic performance was demonstrated during in-solution digestion of model proteins (horseradish peroxidase, bovine serum albumin and hen egg white lysozyme) followed by mass spectrometry. It is shown that both magnetic immobilization and chemical modification enhance the characteristics of trypsin making it a promising tool for protein digestion.

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.

Remarks on the high-energy behavior of string scattering amplitudes in warped spacetimes. II

International Nuclear Information System (INIS)

Andreev, Oleg

2005-01-01

We study the Regge limit of string amplitudes within the model of Polchinski-Strassler for string scattering in warped spacetimes. We also present some numerical estimations of the Regge slopes and intercepts. It is quite remarkable that the real values of those are inside a range of ours

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

Science.gov (United States)

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.

Inverse statistical physics of protein sequences: a key issues review.

Science.gov (United States)

Cocco, Simona; Feinauer, Christoph; Figliuzzi, Matteo; Monasson, Rémi; Weigt, Martin

2018-03-01

In the course of evolution, proteins undergo important changes in their amino acid sequences, while their three-dimensional folded structure and their biological function remain remarkably conserved. Thanks to modern sequencing techniques, sequence data accumulate at unprecedented pace. This provides large sets of so-called homologous, i.e. evolutionarily related protein sequences, to which methods of inverse statistical physics can be applied. Using sequence data as the basis for the inference of Boltzmann distributions from samples of microscopic configurations or observables, it is possible to extract information about evolutionary constraints and thus protein function and structure. Here we give an overview over some biologically important questions, and how statistical-mechanics inspired modeling approaches can help to answer them. Finally, we discuss some open questions, which we expect to be addressed over the next years.

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

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

Marcelino, Anna Marie C; Gierasch, Lila M

2008-05-01

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

An Integrated Framework Advancing Membrane Protein Modeling and Design.

Directory of Open Access Journals (Sweden)

Rebecca F Alford

2015-09-01

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

Remarks on the Curci-Ferrari Model

Science.gov (United States)

Lavrov, Peter M.

2012-07-01

We study a dependence of Green's functions for the Curci-Ferrari model on the parameter resembling the gauge parameter in massless Yang-Mills theories. It is shown that the on-shell generating functional of vertex functions (effective action) depends on this parameter.

The remarkable similarity between the acid-base properties of ISFETs and proteins and the consequences for the design of ISFET biosensors

NARCIS (Netherlands)

Bergveld, Piet; van Hal, R.E.G.; van Hal, R.E.G.; Eijkel, Jan C.T.

1995-01-01

Studying the acid-base properties of protein molecules led us to reconsider the operational mechanism of ISFETs. Based on the site-dissociation model, applied to the amphoteric metal oxide gate materials used in ISFETs, the sensitivity of ISFETs is described in terms of the intrinsic buffer capacity

Protein (multi-)location prediction: utilizing interdependencies via a generative model.

Science.gov (United States)

Simha, Ramanuja; Briesemeister, Sebastian; Kohlbacher, Oliver; Shatkay, Hagit

2015-06-15

Proteins are responsible for a multitude of vital tasks in all living organisms. Given that a protein's function and role are strongly related to its subcellular location, protein location prediction is an important research area. While proteins move from one location to another and can localize to multiple locations, most existing location prediction systems assign only a single location per protein. A few recent systems attempt to predict multiple locations for proteins, however, their performance leaves much room for improvement. Moreover, such systems do not capture dependencies among locations and usually consider locations as independent. We hypothesize that a multi-location predictor that captures location inter-dependencies can improve location predictions for proteins. We introduce a probabilistic generative model for protein localization, and develop a system based on it-which we call MDLoc-that utilizes inter-dependencies among locations to predict multiple locations for proteins. The model captures location inter-dependencies using Bayesian networks and represents dependency between features and locations using a mixture model. We use iterative processes for learning model parameters and for estimating protein locations. We evaluate our classifier MDLoc, on a dataset of single- and multi-localized proteins derived from the DBMLoc dataset, which is the most comprehensive protein multi-localization dataset currently available. Our results, obtained by using MDLoc, significantly improve upon results obtained by an initial simpler classifier, as well as on results reported by other top systems. MDLoc is available at: http://www.eecis.udel.edu/∼compbio/mdloc. © The Author 2015. Published by Oxford University Press.

Concluding Remarks: Experiment from a materials perspective

International Nuclear Information System (INIS)

Fisk, Z

2011-01-01

The author provides some remarks regarding the current status of experiments in strongly correlated electron systems. By construction, they are biased by the author's perspectives at the time of writing.

Specificity and affinity quantification of protein-protein interactions.

Science.gov (United States)

Yan, Zhiqiang; Guo, Liyong; Hu, Liang; Wang, Jin

2013-05-01

Most biological processes are mediated by the protein-protein interactions. Determination of the protein-protein structures and insight into their interactions are vital to understand the mechanisms of protein functions. Currently, compared with the isolated protein structures, only a small fraction of protein-protein structures are experimentally solved. Therefore, the computational docking methods play an increasing role in predicting the structures and interactions of protein-protein complexes. The scoring function of protein-protein interactions is the key responsible for the accuracy of the computational docking. Previous scoring functions were mostly developed by optimizing the binding affinity which determines the stability of the protein-protein complex, but they are often lack of the consideration of specificity which determines the discrimination of native protein-protein complex against competitive ones. We developed a scoring function (named as SPA-PP, specificity and affinity of the protein-protein interactions) by incorporating both the specificity and affinity into the optimization strategy. The testing results and comparisons with other scoring functions show that SPA-PP performs remarkably on both predictions of binding pose and binding affinity. Thus, SPA-PP is a promising quantification of protein-protein interactions, which can be implemented into the protein docking tools and applied for the predictions of protein-protein structure and affinity. The algorithm is implemented in C language, and the code can be downloaded from http://dl.dropbox.com/u/1865642/Optimization.cpp.

Protein Connectivity in Chemotaxis Receptor Complexes.

Directory of Open Access Journals (Sweden)

Stephan Eismann

2015-12-01

Full Text Available The chemotaxis sensory system allows bacteria such as Escherichia coli to swim towards nutrients and away from repellents. The underlying pathway is remarkably sensitive in detecting chemical gradients over a wide range of ambient concentrations. Interactions among receptors, which are predominantly clustered at the cell poles, are crucial to this sensitivity. Although it has been suggested that the kinase CheA and the adapter protein CheW are integral for receptor connectivity, the exact coupling mechanism remains unclear. Here, we present a statistical-mechanics approach to model the receptor linkage mechanism itself, building on nanodisc and electron cryotomography experiments. Specifically, we investigate how the sensing behavior of mixed receptor clusters is affected by variations in the expression levels of CheA and CheW at a constant receptor density in the membrane. Our model compares favorably with dose-response curves from in vivo Förster resonance energy transfer (FRET measurements, demonstrating that the receptor-methylation level has only minor effects on receptor cooperativity. Importantly, our model provides an explanation for the non-intuitive conclusion that the receptor cooperativity decreases with increasing levels of CheA, a core signaling protein associated with the receptors, whereas the receptor cooperativity increases with increasing levels of CheW, a key adapter protein. Finally, we propose an evolutionary advantage as explanation for the recently suggested CheW-only linker structures.

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…

Protein (multi-)location prediction: utilizing interdependencies via a generative model

Science.gov (United States)

Shatkay, Hagit

2015-01-01

Motivation: Proteins are responsible for a multitude of vital tasks in all living organisms. Given that a protein’s function and role are strongly related to its subcellular location, protein location prediction is an important research area. While proteins move from one location to another and can localize to multiple locations, most existing location prediction systems assign only a single location per protein. A few recent systems attempt to predict multiple locations for proteins, however, their performance leaves much room for improvement. Moreover, such systems do not capture dependencies among locations and usually consider locations as independent. We hypothesize that a multi-location predictor that captures location inter-dependencies can improve location predictions for proteins. Results: We introduce a probabilistic generative model for protein localization, and develop a system based on it—which we call MDLoc—that utilizes inter-dependencies among locations to predict multiple locations for proteins. The model captures location inter-dependencies using Bayesian networks and represents dependency between features and locations using a mixture model. We use iterative processes for learning model parameters and for estimating protein locations. We evaluate our classifier MDLoc, on a dataset of single- and multi-localized proteins derived from the DBMLoc dataset, which is the most comprehensive protein multi-localization dataset currently available. Our results, obtained by using MDLoc, significantly improve upon results obtained by an initial simpler classifier, as well as on results reported by other top systems. Availability and implementation: MDLoc is available at: http://www.eecis.udel.edu/∼compbio/mdloc. Contact: shatkay@udel.edu. PMID:26072505

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.

2011 Asia Pacific Few-Body Conference Summary Remarks

International Nuclear Information System (INIS)

Gibson, B. F.

2013-01-01

These remarks represent the author’s personal perspective regarding ideas presented at this fifth Asia Pacific Conference on Few-Body Problems in Physics. They are not intended as a comprehensive summary of what we witnessed during this week of stimulating presentations and intense discussions. However, these remarks do characterize some of the physics we heard and some of the key questions raised. The ideas presented will hopefully outlive the rapporteurs who brought their work and that of others to our attention here in the International Hall of the Sungkyunkwan University in Seoul, Republic of Korea. (author)

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

Science.gov (United States)

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

Intracellular protein breakdown. 8

International Nuclear Information System (INIS)

Bohley, P.; Kirschke, H.; Langner, J.; Wiederanders, B.; Ansorge, S.

1976-01-01

Double-labelled proteins from rat liver cytosol ( 14 C in long-lived, 3 H in short-lived proteins after in-vivo-labelling) are used as substrates for unlabelled proteinases in vitro. Differences in the degradation rates of short-lived and long-lived proteins in vitro by different proteinases and after addition of different effectors allow conclusions concerning their importance for the in-vivo-turnover of substrate proteins. The main activity (>90%) of soluble lysosomal proteinases at pH 6.1 and pH 6.9 is caused by thiolproteinases, which degrade preferentially short-lived cytosol proteins. These proteinases are inhibited by leupeptin. Autolysis of double-labelled cell fractions shows a remarkably faster breakdown of short-lived substrate proteins only in the soluble part of lysosomes. Microsomal fractions degrade in vitro preferentially long-lived substrate proteins. (author)

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...

Electron transfer in proteins

DEFF Research Database (Denmark)

Farver, O; Pecht, I

1991-01-01

Electron migration between and within proteins is one of the most prevalent forms of biological energy conversion processes. Electron transfer reactions take place between active centers such as transition metal ions or organic cofactors over considerable distances at fast rates and with remarkable...... specificity. The electron transfer is attained through weak electronic interaction between the active sites, so that considerable research efforts are centered on resolving the factors that control the rates of long-distance electron transfer reactions in proteins. These factors include (in addition......-containing proteins. These proteins serve almost exclusively in electron transfer reactions, and as it turns out, their metal coordination sites are endowed with properties uniquely optimized for their function....

The end of a remarkable era

CERN Multimedia

2011-01-01

An important era in particle physics is coming to an end: the US Department of Energy announced on Monday that it will not fund an extension to Tevatron running beyond 2011. It is a poignant moment for particle physics as we prepare to bid farewell to a machine that has changed our view of the Universe, and played a significant role in paving the way for the new era that is opening up with the LHC.   The Tevatron has been at the high-energy frontier of particle physics for over a quarter of a century. That’s a remarkable achievement by any account, and the physics results are there to prove it. As well as bringing us the discovery of the top quark in 1995, the Tevatron’s experiments have provided vitally important precision measurements covering the full spectrum of Standard Model physics, not to mention hints of what may lie beyond. With several months of running still to come, it would be a foolish gambler who bet against further new physics emerging before the Teva...

Remarks on the clump theory

International Nuclear Information System (INIS)

Krommes, J.A.

1986-07-01

Further details are provided of a soon-to-be published dialog [Phys. Fluids 29 (July, 1986)] which discussed the role of the small scales in fluid clump theory. It is argued that the approximation of the clump lifetime which is compatible with exponentially rapid separation of adjacent orbits is inappropriate for the description of the dynamically important large scales. Various other remarks are made relating to the analytic treatment of strong drift-wave-like turbulence

Remarks on the clump theory

International Nuclear Information System (INIS)

Krommes, J.A.

1986-01-01

Further details are provided of a recently published dialog [Phys. Fluids 29 (July, 1986)] which discussed the role of the small scales in fluid clump theory. It is argued that the approximation of the clump lifetime which is compatible with exponentially rapid separation of adjacent orbits is inappropriate for the description of the dynamically important large scales. Various other remarks are made relating to the analytic treatment of strong drift-wave-like turbulence. (author)

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

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.

Proteasomal and lysosomal protein degradation and heart disease.

Science.gov (United States)

Wang, Xuejun; Robbins, Jeffrey

2014-06-01

In the cell, the proteasome and lysosomes represent the most important proteolytic machineries, responsible for the protein degradation in the ubiquitin-proteasome system (UPS) and autophagy, respectively. Both the UPS and autophagy are essential to protein quality and quantity control. Alterations in cardiac proteasomal and lysosomal degradation are remarkably associated with most heart disease in humans and are implicated in the pathogenesis of congestive heart failure. Studies carried out in animal models and in cell culture have begun to establish both sufficiency and, in some cases, the necessity of proteasomal functional insufficiency or lysosomal insufficiency as a major pathogenic factor in the heart. This review article highlights some recent advances in the research into proteasome and lysosome protein degradation in relation to cardiac pathology and examines the emerging evidence for enhancing degradative capacities of the proteasome and/or lysosome as a new therapeutic strategy for heart disease. This article is part of a Special Issue entitled "Protein Quality Control, the Ubiquitin Proteasome System, and Autophagy". Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

Remarks on orthotropic elastic models applied to wood

Directory of Open Access Journals (Sweden)

Nilson Tadeu Mascia

2006-09-01

Full Text Available Wood is generally considered an anisotropic material. In terms of engineering elastic models, wood is usually treated as an orthotropic material. This paper presents an analysis of two principal anisotropic elastic models that are usually applied to wood. The first one, the linear orthotropic model, where the material axes L (Longitudinal, R( radial and T(tangential are coincident with the Cartesian axes (x, y, z, is more accepted as wood elastic model. The other one, the cylindrical orthotropic model is more adequate of the growth caracteristics of wood but more mathematically complex to be adopted in practical terms. Specifically due to its importance in wood elastic parameters, this paper deals with the fiber orientation influence in these models through adequate transformation of coordinates. As a final result, some examples of the linear model, which show the variation of elastic moduli, i.e., Young´s modulus and shear modulus, with fiber orientation are presented.

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/ .

Some remarks on the Bonnor-Swaminarayan solution

International Nuclear Information System (INIS)

Berezdivin, R.; Herrera, L.

1976-01-01

The letter re-examines the Bonnor-Swaminarayan solution with the aim to try a clarification of its physical interpretation. The radiative nature of the solution as suggested by Bicak is questioned and some remarks on this topic are given

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.

Designing sequence to control protein function in an EF-hand protein.

Science.gov (United States)

Bunick, Christopher G; Nelson, Melanie R; Mangahas, Sheryll; Hunter, Michael J; Sheehan, Jonathan H; Mizoue, Laura S; Bunick, Gerard J; Chazin, Walter J

2004-05-19

The extent of conformational change that calcium binding induces in EF-hand proteins is a key biochemical property specifying Ca(2+) sensor versus signal modulator function. To understand how differences in amino acid sequence lead to differences in the response to Ca(2+) binding, comparative analyses of sequence and structures, combined with model building, were used to develop hypotheses about which amino acid residues control Ca(2+)-induced conformational changes. These results were used to generate a first design of calbindomodulin (CBM-1), a calbindin D(9k) re-engineered with 15 mutations to respond to Ca(2+) binding with a conformational change similar to that of calmodulin. The gene for CBM-1 was synthesized, and the protein was expressed and purified. Remarkably, this protein did not exhibit any non-native-like molten globule properties despite the large number of mutations and the nonconservative nature of some of them. Ca(2+)-induced changes in CD intensity and in the binding of the hydrophobic probe, ANS, implied that CBM-1 does undergo Ca(2+) sensorlike conformational changes. The X-ray crystal structure of Ca(2+)-CBM-1 determined at 1.44 A resolution reveals the anticipated increase in hydrophobic surface area relative to the wild-type protein. A nascent calmodulin-like hydrophobic docking surface was also found, though it is occluded by the inter-EF-hand loop. The results from this first calbindomodulin design are discussed in terms of progress toward understanding the relationships between amino acid sequence, protein structure, and protein function for EF-hand CaBPs, as well as the additional mutations for the next CBM design.

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.

Effective Suckling C57BL/6, Kunming, and BALB/c Mouse Models with Remarkable Neurological Manifestation for Zika Virus Infection

Science.gov (United States)

Liu, Xuling; Ke, Changwen; Wu, Qinghua; Lu, Weizhi; Qin, Zhiran; He, Xiaoen; Liu, Yujing; Deng, Jieli; Xu, Suiqi; Li, Ying; Zhu, Li; Wan, Chengsong; Xiao, Weiwei; Xie, Qian; Zhang, Bao; Zhao, Wei

2017-01-01

Since 2015, 84 countries and territories reported evidence of vector-borne Zika Virus (ZIKV) transmission. The World Health Organization (WHO) declared that ZIKV and associated consequences especially the neurological autoimmune disorder Guillain–Barré syndrome (GBS) and microcephaly will remain a significant enduring public health challenge requiring intense action. We apply a standardization of the multi-subcutaneous dorsal inoculation method to systematically summarize clinical neurological manifestation, viral distribution, and tissue damage during the progress of viremia and systemic spread in suckling mouse models. We found that C57BL/6 and Kunming mice (KM) both showed remarkable and uniform neurologic manifestations. C57BL/6 owned the highest susceptibility and pathogenicity to the nervous system, referred to as movement disorders, with 100% incidence, while KM was an economic model for a Chinese study characterized by lower limb weakness with 62% morbidity. Slight yellow extraocular exudates were observed in BALB/c, suggesting the association with similar ocular findings to those of clinical cases. The virus distribution and pathological changes in the sera, brains, livers, kidneys, spleens, and testes during disease progression had strong regularity and uniformity, demonstrating the effectiveness and plasticity of the animal models. The successful establishment of these animal models will be conducive to expound the pathogenic mechanism of GBS. PMID:28661429

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.

Concluding remarks. International Conference on Nuclear Physics, Berkeley, California, August 1980

International Nuclear Information System (INIS)

Feshbach, H.

1980-10-01

Not a conference summary, these concluding remarks consider five major themes that were illuminated during the conference and the problems within them that need to be resolved in the future. The five topics considered and the following: new degrees of freedom (single-particle motion, giant resonances, nuclear molecular resonances, nuclear matter, kaon-produced hypernuclei, implications of the bag model and quantum chromodynamics), new forms of matter, new reaction mechanisms (direct vs compound-nucleus reactions, heavy-ion reactions), new aspects of the weak interactions in nuclei (weak neutral currents, P invariance), and new symmetries. 4 figures

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.

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

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

Remarks about the hypothesis of limiting fragmentation

International Nuclear Information System (INIS)

Chou, T.T.; Yang, C.N.

1987-01-01

Remarks are made about the hypothesis of limiting fragmentation. In particular, the concept of favored and disfavored fragment distribution is introduced. Also, a sum rule is proved leading to a useful quantity called energy-fragmentation fraction. (author). 11 refs, 1 fig., 2 tabs

Nanoparticles-cell association predicted by protein corona fingerprints

Science.gov (United States)

Palchetti, S.; Digiacomo, L.; Pozzi, D.; Peruzzi, G.; Micarelli, E.; Mahmoudi, M.; Caracciolo, G.

2016-06-01

In a physiological environment (e.g., blood and interstitial fluids) nanoparticles (NPs) will bind proteins shaping a ``protein corona'' layer. The long-lived protein layer tightly bound to the NP surface is referred to as the hard corona (HC) and encodes information that controls NP bioactivity (e.g. cellular association, cellular signaling pathways, biodistribution, and toxicity). Decrypting this complex code has become a priority to predict the NP biological outcomes. Here, we use a library of 16 lipid NPs of varying size (Ø ~ 100-250 nm) and surface chemistry (unmodified and PEGylated) to investigate the relationships between NP physicochemical properties (nanoparticle size, aggregation state and surface charge), protein corona fingerprints (PCFs), and NP-cell association. We found out that none of the NPs' physicochemical properties alone was exclusively able to account for association with human cervical cancer cell line (HeLa). For the entire library of NPs, a total of 436 distinct serum proteins were detected. We developed a predictive-validation modeling that provides a means of assessing the relative significance of the identified corona proteins. Interestingly, a minor fraction of the HC, which consists of only 8 PCFs were identified as main promoters of NP association with HeLa cells. Remarkably, identified PCFs have several receptors with high level of expression on the plasma membrane of HeLa cells.In a physiological environment (e.g., blood and interstitial fluids) nanoparticles (NPs) will bind proteins shaping a ``protein corona'' layer. The long-lived protein layer tightly bound to the NP surface is referred to as the hard corona (HC) and encodes information that controls NP bioactivity (e.g. cellular association, cellular signaling pathways, biodistribution, and toxicity). Decrypting this complex code has become a priority to predict the NP biological outcomes. Here, we use a library of 16 lipid NPs of varying size (Ø ~ 100-250 nm) and surface

Remarks on ConstitutiveModeling of Nanofluids

Energy Technology Data Exchange (ETDEWEB)

Massoudi, Mehrdad; Tran X. Phuoc

2012-01-01

Nanofluids are made by adding nanoscale particles in low volumetric fractions to a fluid in order to enhance or improve their rheological, mechanical, optical, and thermal properties. The base fluid can be any liquid such as oil, water, ethylene glycol, or conventional fluid mixtures. Limited available studies on nanofluid viscosity have been reported [1-19]. In most of these studies, the behavior of the viscosity and the shear stress of nanofluids have been interpreted using the widely used empirical model developed by Casson [20].

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.

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.

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 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...

Polypyridyl iron(II) complexes showing remarkable photocytotoxicity ...

Indian Academy of Sciences (India)

aditya

Polypyridyl iron(II) complexes showing remarkable photocytotoxicity in visible light. ADITYA GARAI a. , UTTARA BASU a. , ILA PANT b. , PATURU KONDAIAH*. ,b. AND. AKHIL R. CHAKRAVARTY*. ,a a. Department of Inorganic and Physical Chemistry, Indian Institute of Science, Bangalore. 560012, India. E-mail: ...

Nanobody Technology: A Versatile Toolkit for Microscopic Imaging, Protein-Protein Interaction Analysis, and Protein Function Exploration.

Science.gov (United States)

Beghein, Els; Gettemans, Jan

2017-01-01

Over the last two decades, nanobodies or single-domain antibodies have found their way in research, diagnostics, and therapy. These antigen-binding fragments, derived from Camelid heavy chain only antibodies, possess remarkable characteristics that favor their use over conventional antibodies or fragments thereof, in selected areas of research. In this review, we assess the current status of nanobodies as research tools in diverse aspects of fundamental research. We discuss the use of nanobodies as detection reagents in fluorescence microscopy and focus on recent advances in super-resolution microscopy. Second, application of nanobody technology in investigating protein-protein interactions is reviewed, with emphasis on possible uses in mass spectrometry. Finally, we discuss the potential value of nanobodies in studying protein function, and we focus on their recently reported application in targeted protein degradation. Throughout the review, we highlight state-of-the-art engineering strategies that could expand nanobody versatility and we suggest future applications of the technology in the selected areas of fundamental research.

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.

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.

Transfer functions for protein signal transduction: application to a model of striatal neural plasticity.

Directory of Open Access Journals (Sweden)

Gabriele Scheler

Full Text Available We present a novel formulation for biochemical reaction networks in the context of protein signal transduction. The model consists of input-output transfer functions, which are derived from differential equations, using stable equilibria. We select a set of "source" species, which are interpreted as input signals. Signals are transmitted to all other species in the system (the "target" species with a specific delay and with a specific transmission strength. The delay is computed as the maximal reaction time until a stable equilibrium for the target species is reached, in the context of all other reactions in the system. The transmission strength is the concentration change of the target species. The computed input-output transfer functions can be stored in a matrix, fitted with parameters, and even recalled to build dynamical models on the basis of state changes. By separating the temporal and the magnitudinal domain we can greatly simplify the computational model, circumventing typical problems of complex dynamical systems. The transfer function transformation of biochemical reaction systems can be applied to mass-action kinetic models of signal transduction. The paper shows that this approach yields significant novel insights while remaining a fully testable and executable dynamical model for signal transduction. In particular we can deconstruct the complex system into local transfer functions between individual species. As an example, we examine modularity and signal integration using a published model of striatal neural plasticity. The modularizations that emerge correspond to a known biological distinction between calcium-dependent and cAMP-dependent pathways. Remarkably, we found that overall interconnectedness depends on the magnitude of inputs, with higher connectivity at low input concentrations and significant modularization at moderate to high input concentrations. This general result, which directly follows from the properties of

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.

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.

Closing remarks

International Nuclear Information System (INIS)

Reig, J.

2007-01-01

Good afternoon. Before providing the closing remarks on behalf of the NEA, I would like to take this opportunity and make some personal reflections, if you allow me Mr. Chairman. I have had the opportunity to take part in the three workshops on public communication organised by the NEA. In the first one in Paris in 2000, representing my country, Spain, and in the two last ones in Ottawa in 2004 and Tokyo today, on behalf of the NEA. The topics for the three workshops follow a logical order, first the focus was on investing in trust in a time when public communication was becoming a big challenge for the regulators. Second, maintaining and measuring public confidence to assess how credible regulators are in front of the public; and finally here in Tokyo, transparency, which is a basic element to achieve trust and credibility. In my view, a regulatory decision has three main components, it has to be technically sound. legally correct and well communicated. The emphasis in the early years was in the technical matters, till legal issues became a key element to achieve the political acceptance from governments and local authorities. Finally the public communication aspects resulted into a major effort and challenge to achieve social acceptance. (author)

Concluding theoretical remarks

International Nuclear Information System (INIS)

Ellis, J.

1986-01-01

My task in this talk is to review the happenings of this workshop from a theoretical perspective, and to emphasize lines for possible future research. My remarks are organized into a theoretical overview of the what, why, (mainly the hierarchy problem) how, (supersymmetry must be broken: softly or spontaneously, and if the latter, by means of a new U tilde(1) gauge group or through the chiral superfields) when (how heavy are supersymmetric partner particles in different types of theories) and where (can one find evidence for) supersymmetry. In the last part are discussed various ongoing and future searches for photinos γ tilde, gravitinos G tilde, the U vector boson, shiggses H tilde, squarks q tilde and sleptons l tilde, gluinos g tilde, winos W tilde and other gauginos, as well as hunts for indirect effects of supersymmetry, such as for example in baryon decay. Finally there is a little message of encouragement to our experimental colleagues, based on historical precedent. (orig.)

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.

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

Remarks on the elaboration of an English–Spanish ...

African Journals Online (AJOL)

Spanish word-combination dictionary examined here, some concluding remarks are made with regard to the educational implications of this kind of dictionary primarily aimed at intermediate- to advanced-level Spanish-speaking EFL learners.

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.

MM-ISMSA: An Ultrafast and Accurate Scoring Function for Protein-Protein Docking.

Science.gov (United States)

Klett, Javier; Núñez-Salgado, Alfonso; Dos Santos, Helena G; Cortés-Cabrera, Álvaro; Perona, Almudena; Gil-Redondo, Rubén; Abia, David; Gago, Federico; Morreale, Antonio

2012-09-11

An ultrafast and accurate scoring function for protein-protein docking is presented. It includes (1) a molecular mechanics (MM) part based on a 12-6 Lennard-Jones potential; (2) an electrostatic component based on an implicit solvent model (ISM) with individual desolvation penalties for each partner in the protein-protein complex plus a hydrogen bonding term; and (3) a surface area (SA) contribution to account for the loss of water contacts upon protein-protein complex formation. The accuracy and performance of the scoring function, termed MM-ISMSA, have been assessed by (1) comparing the total binding energies, the electrostatic term, and its components (charge-charge and individual desolvation energies), as well as the per residue contributions, to results obtained with well-established methods such as APBSA or MM-PB(GB)SA for a set of 1242 decoy protein-protein complexes and (2) testing its ability to recognize the docking solution closest to the experimental structure as that providing the most favorable total binding energy. For this purpose, a test set consisting of 15 protein-protein complexes with known 3D structure mixed with 10 decoys for each complex was used. The correlation between the values afforded by MM-ISMSA and those from the other methods is quite remarkable (r(2) ∼ 0.9), and only 0.2-5.0 s (depending on the number of residues) are spent on a single calculation including an all vs all pairwise energy decomposition. On the other hand, MM-ISMSA correctly identifies the best docking solution as that closest to the experimental structure in 80% of the cases. Finally, MM-ISMSA can process molecular dynamics trajectories and reports the results as averaged values with their standard deviations. MM-ISMSA has been implemented as a plugin to the widely used molecular graphics program PyMOL, although it can also be executed in command-line mode. MM-ISMSA is distributed free of charge to nonprofit organizations.

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

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.

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.

How Many Protein Sequences Fold to a Given Structure? A Coevolutionary Analysis.

Science.gov (United States)

Tian, Pengfei; Best, Robert B

2017-10-17

Quantifying the relationship between protein sequence and structure is key to understanding the protein universe. A fundamental measure of this relationship is the total number of amino acid sequences that can fold to a target protein structure, known as the "sequence capacity," which has been suggested as a proxy for how designable a given protein fold is. Although sequence capacity has been extensively studied using lattice models and theory, numerical estimates for real protein structures are currently lacking. In this work, we have quantitatively estimated the sequence capacity of 10 proteins with a variety of different structures using a statistical model based on residue-residue co-evolution to capture the variation of sequences from the same protein family. Remarkably, we find that even for the smallest protein folds, such as the WW domain, the number of foldable sequences is extremely large, exceeding the Avogadro constant. In agreement with earlier theoretical work, the calculated sequence capacity is positively correlated with the size of the protein, or better, the density of contacts. This allows the absolute sequence capacity of a given protein to be approximately predicted from its structure. On the other hand, the relative sequence capacity, i.e., normalized by the total number of possible sequences, is an extremely tiny number and is strongly anti-correlated with the protein length. Thus, although there may be more foldable sequences for larger proteins, it will be much harder to find them. Lastly, we have correlated the evolutionary age of proteins in the CATH database with their sequence capacity as predicted by our model. The results suggest a trade-off between the opposing requirements of high designability and the likelihood of a novel fold emerging by chance. Published by Elsevier Inc.

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.

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.

Diversity in viral anti-PKR mechanisms: a remarkable case of evolutionary convergence.

Directory of Open Access Journals (Sweden)

Elena Domingo-Gil

Full Text Available Most viruses express during infection products that prevent or neutralize the effect of the host dsRNA activated protein kinase (PKR. Translation of Sindbis virus (SINV mRNA escapes to PKR activation and eIF2 phosphorylation in infected cells by a mechanism that requires a stem loop structure in viral 26S mRNA termed DLP to initiate translation in the absence of functional eIF2. Unlike the rest of viruses tested, we found that Alphavirus infection allowed a strong PKR activation and eIF2α phosphorylation in vitro and in infected animals so that the presence of DLP structure in mRNA was critical for translation and replication of SINV. Interestingly, infection of MEFs with some viruses that express PKR inhibitors prevented eIF2α phosphorylation after superinfection with SINV, suggesting that viral anti-PKR mechanisms could be exchangeable. Thus, translation of SINV mutant lacking the DLP structure (ΔDLP in 26S mRNA was partially rescued in cells expressing vaccinia virus (VV E3 protein, a known inhibitor of PKR. This case of heterotypic complementation among evolutionary distant viruses confirmed experimentally a remarkable case of convergent evolution in viral anti-PKR mechanisms. Our data reinforce the critical role of PKR in regulating virus-host interaction and reveal the versatility of viruses to find different solutions to solve the same conflict.

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.

Some remarks on the small-distance derivative model

International Nuclear Information System (INIS)

Jannussis, A.

1985-01-01

In the present work the new expressions of the derivatives for small distance are investigated according to Gonzales-Diaz model. This model is noncanonical, is a particular case of the Lie-admissible formulation and has applications for distance and time scales comparable with the Planck dimensions

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...

Remark on natural models of neutrinos

International Nuclear Information System (INIS)

Fujikawa, Kazuo

2005-01-01

We comment on what 't Hooft's naturalness argument implies with regard to a minimal extension of the Standard Model that incorporates right-handed neutrinos with generic mass terms. If this Lagrangian is taken as that of a low energy effective theory, the idea of pseudo-Dirac neutrinos with very small masses is consistent with 't Hooft's naturalness argument. This argument is based on the observation that the right-handed components of neutrinos in the massless limit exhibit an extra enhanced symmetry which is absent in other charged fermions. This enhanced symmetry is reminiscent of the Nambu-Goldstone fermions associated with spontaneously broken supersymmetry. The conventional seesaw scenario gives another natural solution if the ultra-heavy right-handed neutrinos are integrated out in the formulation of a low energy effective theory. (author)

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.

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

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

Science.gov (United States)

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.

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.

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.

Some Model Theoretic Remarks on Bass Modules

Directory of Open Access Journals (Sweden)

E. Momtahan

2011-09-01

Full Text Available We study Bass modules, Bass rings, and related concepts from a model theoretic point of view. We observe that the class of Bass modules (over a fixed ring is not stable under elementary equivalence. We observe that under which conditions the class of Bass rings are stable under elementary equivalence.

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,...

Protein buffering in model systems and in whole human saliva.

Directory of Open Access Journals (Sweden)

Andreas Lamanda

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

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.

Role of dietary supplementation in the protein content of bovine milk ...

African Journals Online (AJOL)

Feed back response of the caseins and whey proteins was observed in sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) profile by resolving these proteins upon 15% SDS PAGE which showed remarkable variation in the banding pattern of all caseins i.e., α-caseins, β-caseins, κ-casein and whey ...

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.

Subcellular Trafficking of the Papillomavirus Genome during Initial Infection: The Remarkable Abilities of Minor Capsid Protein L2

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Samuel K. Campos

2017-12-01

Full Text Available Since 2012, our understanding of human papillomavirus (HPV subcellular trafficking has undergone a drastic paradigm shift. Work from multiple laboratories has revealed that HPV has evolved a unique means to deliver its viral genome (vDNA to the cell nucleus, relying on myriad host cell proteins and processes. The major breakthrough finding from these recent endeavors has been the realization of L2-dependent utilization of cellular sorting factors for the retrograde transport of vDNA away from degradative endo/lysosomal compartments to the Golgi, prior to mitosis-dependent nuclear accumulation of L2/vDNA. An overview of current models of HPV entry, subcellular trafficking, and the role of L2 during initial infection is provided below, highlighting unresolved questions and gaps in knowledge.

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.

Proteasomal and Lysosomal Protein Degradation and Heart Disease

OpenAIRE

Wang, Xuejun; Robbins, Jeffrey

2013-01-01

In the cell, the proteasome and lysosomes represent the most important proteolytic machineries, responsible for the protein degradation in the ubiquitin-proteasome system (UPS) and autophagy, respectively. Both the UPS and autophagy are essential to protein quality and quantity control. Alterations in cardiac proteasomal and lysosomal degradation are remarkably associated with most heart disease in humans and are implicated in the pathogenesis of congestive heart failure. Studies carried out ...

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.

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.

Bioinformatics analysis identify novel OB fold protein coding genes in C. elegans.

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Daryanaz Dargahi

Full Text Available BACKGROUND: The C. elegans genome has been extensively annotated by the WormBase consortium that uses state of the art bioinformatics pipelines, functional genomics and manual curation approaches. As a result, the identification of novel genes in silico in this model organism is becoming more challenging requiring new approaches. The Oligonucleotide-oligosaccharide binding (OB fold is a highly divergent protein family, in which protein sequences, in spite of having the same fold, share very little sequence identity (5-25%. Therefore, evidence from sequence-based annotation may not be sufficient to identify all the members of this family. In C. elegans, the number of OB-fold proteins reported is remarkably low (n=46 compared to other evolutionary-related eukaryotes, such as yeast S. cerevisiae (n=344 or fruit fly D. melanogaster (n=84. Gene loss during evolution or differences in the level of annotation for this protein family, may explain these discrepancies. METHODOLOGY/PRINCIPAL FINDINGS: This study examines the possibility that novel OB-fold coding genes exist in the worm. We developed a bioinformatics approach that uses the most sensitive sequence-sequence, sequence-profile and profile-profile similarity search methods followed by 3D-structure prediction as a filtering step to eliminate false positive candidate sequences. We have predicted 18 coding genes containing the OB-fold that have remarkably partially been characterized in C. elegans. CONCLUSIONS/SIGNIFICANCE: This study raises the possibility that the annotation of highly divergent protein fold families can be improved in C. elegans. Similar strategies could be implemented for large scale analysis by the WormBase consortium when novel versions of the genome sequence of C. elegans, or other evolutionary related species are being released. This approach is of general interest to the scientific community since it can be used to annotate any genome.

The remarkable similarity between the acid-base properties of ISFETs and proteins and the consequences for the design of ISFET biosensors

OpenAIRE

Bergveld, Piet; van Hal, R.E.G.; van Hal, R.E.G.; Eijkel, Jan C.T.

1995-01-01

Studying the acid-base properties of protein molecules led us to reconsider the operational mechanism of ISFETs. Based on the site-dissociation model, applied to the amphoteric metal oxide gate materials used in ISFETs, the sensitivity of ISFETs is described in terms of the intrinsic buffer capacity of the oxide surface, ßs, and the electrical surface capacitance, Cs. The ISFET sensitivity towards changes in the bulk pH is fully described by the ratio ßs/Cs. Practical measurements support thi...

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

Science.gov (United States)

Mizutani, H.; Ponnamperuma, C.

1977-01-01

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

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.

Remarks concerning two sympatric seedeaters Poliospiza spp. in ...

African Journals Online (AJOL)

Turner, D.A., Finch, B.F, & Hunter, N.D. Remarks concerning the all-black coastal boubous. (Laniarius ... Currently, however, there is little evidence to support such a theory, and it is .... twigs with its beak in order to increase the size of the hole.

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

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....

Chemical physics of electroactive materials: concluding remarks.

Science.gov (United States)

Rutland, Mark W

2017-07-01

It is an honour to be charged with providing the concluding remarks for a Faraday Discussion. As many have remarked before, it is nonetheless a prodigious task, and what follows is necessarily a personal, and probably perverse, view of a watershed event in the Chemical Physics of Electroactive materials. The spirit of the conference was captured in a single sentence during the meeting itself."It is the nexus between rheology, electrochemistry, colloid science and energy storage". The current scientific climate is increasingly dominated by a limited number of global challenges, and there is thus a tendency for research to resemble a football match played by 6 year olds, where everyone on the field chases the (funding) ball instead of playing to their "discipline". It is thus reassuring to see how the application of rigorous chemical physics is leading to ingenious new solutions for both energy storage and harvesting, via, for example, nanoactuation, electrowetting, ionic materials and nanoplasmonics. In fact, the same language of chemical physics allows seamless transition between applications as diverse as mechano-electric energy generation, active moisture transport and plasmonic shutters - even the origins of life were addressed in the context of electro-autocatalysis!

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

Directory of Open Access Journals (Sweden)

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....

Remarkable long-range-systematic in the binding energies of α-nuclei. II

International Nuclear Information System (INIS)

Gross, D.H.E.

2003-01-01

In this Letter I present further data that show the remarkable evidence for the existence of an α-cluster structure in the ground states of even-even N=Z nuclei. Such a remarkable systematic was observed 20 years ago Gross and Nemes [Phys. Lett. B 130 (1983) 131] for these nuclei at A≤72 and is extended here up to A=100

Development of REI meetings (concluding remarks)

International Nuclear Information System (INIS)

Roessler, K.

1988-01-01

It is an honour and a pleasure to deliver the concluding remarks of this Fourth International Conference on Radiation Effects in Insulators. After commenting upon the present meeting, the genesis of REI conferences, their aims and position relative to related meetings in radiation and ion implantation research will be treated, particularly in order to inform new-comers. The development of the last four REI meetings will be discussed on the base of a statistical analysis. Some recommendations and an outlook of future trends will be given. (orig.)

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 European Public Prosecutor's Office (EPPO): Introductory Remarks

NARCIS (Netherlands)

Vervaele, J.A.E.

2018-01-01

These introductory remarks deal with the reasons why the EPPO is perceived by some as a controversial body. These reasons are mirrored with the problem identification and the causes thereof. The size of EU fraud and related corruption and money laundering, both at the income and expenditure side, is

Remarkable resilience of teeth.

Science.gov (United States)

Chai, Herzl; Lee, James J-W; Constantino, Paul J; Lucas, Peter W; Lawn, Brian R

2009-05-05

Tooth enamel is inherently weak, with fracture toughness comparable with glass, yet it is remarkably resilient, surviving millions of functional contacts over a lifetime. We propose a microstructural mechanism of damage resistance, based on observations from ex situ loading of human and sea otter molars (teeth with strikingly similar structural features). Section views of the enamel implicate tufts, hypomineralized crack-like defects at the enamel-dentin junction, as primary fracture sources. We report a stabilization in the evolution of these defects, by "stress shielding" from neighbors, by inhibition of ensuing crack extension from prism interweaving (decussation), and by self-healing. These factors, coupled with the capacity of the tooth configuration to limit the generation of tensile stresses in largely compressive biting, explain how teeth may absorb considerable damage over time without catastrophic failure, an outcome with strong implications concerning the adaptation of animal species to diet.

Protein 3D structure computed from evolutionary sequence variation.

Directory of Open Access Journals (Sweden)

Debora S Marks

Full Text Available The evolutionary trajectory of a protein through sequence space is constrained by its function. Collections of sequence homologs record the outcomes of millions of evolutionary experiments in which the protein evolves according to these constraints. Deciphering the evolutionary record held in these sequences and exploiting it for predictive and engineering purposes presents a formidable challenge. The potential benefit of solving this challenge is amplified by the advent of inexpensive high-throughput genomic sequencing.In this paper we ask whether we can infer evolutionary constraints from a set of sequence homologs of a protein. The challenge is to distinguish true co-evolution couplings from the noisy set of observed correlations. We address this challenge using a maximum entropy model of the protein sequence, constrained by the statistics of the multiple sequence alignment, to infer residue pair couplings. Surprisingly, we find that the strength of these inferred couplings is an excellent predictor of residue-residue proximity in folded structures. Indeed, the top-scoring residue couplings are sufficiently accurate and well-distributed to define the 3D protein fold with remarkable accuracy.We quantify this observation by computing, from sequence alone, all-atom 3D structures of fifteen test proteins from different fold classes, ranging in size from 50 to 260 residues, including a G-protein coupled receptor. These blinded inferences are de novo, i.e., they do not use homology modeling or sequence-similar fragments from known structures. The co-evolution signals provide sufficient information to determine accurate 3D protein structure to 2.7-4.8 Å C(α-RMSD error relative to the observed structure, over at least two-thirds of the protein (method called EVfold, details at http://EVfold.org. This discovery provides insight into essential interactions constraining protein evolution and will facilitate a comprehensive survey of the universe of

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

Remarkable recoveries: research and practice from a patient's perspective.

Science.gov (United States)

Barasch, Marc Ian

2008-08-01

Mind-body therapies are often portrayed in the literature as self-palliative, adjunctive, and complementary, but rarely as contributive to cure. Many physicians continue to view them as acceptable indulgences so long as they are harmless and the patient remains fully compliant with a standard treatment regimen. The possibility that such modalities might help drive the healing process itself is infrequently acknowledged. This article addresses the topic of such therapies, examining remarkable recoveries in cancer, and suggesting the need for a "Remarkable Recovery Registry" to expand the literature on these cases. The author discusses the importance of complementary alternative medicine, and emotional and pyschologic support in the treatment regimen, and the need for health care providers and patients to work together to provide the best emotional environment for the healing process.

Macrocyclic peptide inhibitors for the protein-protein interaction of Zaire Ebola virus protein 24 and karyopherin alpha 5.

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Song, Xiao; Lu, Lu-Yi; Passioura, Toby; Suga, Hiroaki

2017-06-21

Ebola virus infection leads to severe hemorrhagic fever in human and non-human primates with an average case fatality rate of 50%. To date, numerous potential therapies are in development, but FDA-approved drugs or vaccines are yet unavailable. Ebola viral protein 24 (VP24) is a multifunctional protein that plays critical roles in the pathogenesis of Ebola virus infection, e.g. innate immune suppression by blocking the interaction between KPNA and PY-STAT1. Here we report macrocyclic peptide inhibitors of the VP24-KPNA5 protein-protein interaction (PPI) by means of the RaPID (Random non-standard Peptides Integrated Discovery) system. These macrocyclic peptides showed remarkably high affinity to recombinant Zaire Ebola virus VP24 (eVP24), with a dissociation constant in the single digit nanomolar range, and could also successfully disrupt the eVP24-KPNA interaction. This work provides for the first time a chemical probe capable of modulating this PPI interaction and is the starting point for the development of unique anti-viral drugs against the Ebola virus.

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

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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.

Plant proteins as binders in cellulosic paper composites.

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Fahmy, Yehia; El-Wakil, Nahla A; El-Gendy, Ahmed A; Abou-Zeid, Ragab E; Youssef, M A

2010-07-01

Plant proteins are used - for the first time - in this work as bulk binders for cellulosic fibers in paper composites. Soy bean protein and wheat gluten were denatured by two methods, namely by: urea+NaOH and by urea+NaOH+acrylamide. Addition of increased amounts of the denatured proteins resulted in a significant increase in all paper strength properties. Soy protein led, in addition, to a remarkable enhancement in opacity. The use of proteins increased kaolin retention in the paper composites, while keeping the paper strength higher than the blank protein-free paper. The results show that plant proteins are favorable than synthetic adhesives; because they are biodegradable and do not cause troubles in paper recycling i.e. they are environmentally friendly. (c) 2010 Elsevier B.V. All rights reserved.

A Remarkable Recent Transition in the Solar Dynamo

NARCIS (Netherlands)

de Jager, C.; Akasofu, S.-I.; Duhau, S.; Livingston, W.C.; Nieuwenhuijzen, H.; Potgieter, M.S.

2016-01-01

We summarize the major aspects of the remarkable, fairly long lasting period(∼ 2005 to ∼ 2010) of low solar activity, that we will call the Transition. It is the transitionalstage between the Grand Maximum of the 20th century and a forthcoming (most probablyRegular) episode of solar activity. The

Benzalkonium Chloride Provides Remarkable Stability to Liquid Protein Lures for Trapping Anastrepha obliqua (Diptera: Tephritidae).

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Lasa, R; Williams, T

2017-12-05

Hydrolyzed protein lures are widely used to monitor fruit fly pests but are rapidly degraded by microbial activity and must be replaced frequently. To improve the stability of lures, the quaternary ammonium biocide, benzalkonium chloride (BC), was evaluated in mixtures with two hydrolyzed proteins commonly used to monitor Anastrepha spp. The mean number of Anastrepha obliqua adults captured during six consecutive weeks using Captor + borax with the addition of 240 mg BC/liter, not renewed during the test, was similar to Captor + borax that was replaced at weekly intervals and was more effective than Captor + borax without BC. Numbers of A. obliqua flies captured in 30% CeraTrap diluted in water containing 240 mg BC/liter were similar to those caught in traps baited with Captor + borax or 30% CeraTrap without BC in the first 9 d of evaluation but was significantly more effective than both lures after 56 d. After >2 mo of use, 30% CeraTrap containing 240 mg BC/liter remained as effective as newly prepared 30% CeraTrap. The addition of BC to lures reduced surface tension of liquid lures by ~40-50%. However, when BC was increased to 720 mg BC/liter, only a small additional reduction in surface tension was observed and higher concentrations of BC did not increase capture rates. These findings could contribute to reduced costs for trapping networks and the development of long-lasting formulations of liquid protein lures for bait stations and mass-trapping targeted at major tephritid pests. © The Author(s) 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Yeast prions and human prion-like proteins: sequence features and prediction methods.

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Cascarina, Sean M; Ross, Eric D

2014-06-01

Prions are self-propagating infectious protein isoforms. A growing number of prions have been identified in yeast, each resulting from the conversion of soluble proteins into an insoluble amyloid form. These yeast prions have served as a powerful model system for studying the causes and consequences of prion aggregation. Remarkably, a number of human proteins containing prion-like domains, defined as domains with compositional similarity to yeast prion domains, have recently been linked to various human degenerative diseases, including amyotrophic lateral sclerosis. This suggests that the lessons learned from yeast prions may help in understanding these human diseases. In this review, we examine what has been learned about the amino acid sequence basis for prion aggregation in yeast, and how this information has been used to develop methods to predict aggregation propensity. We then discuss how this information is being applied to understand human disease, and the challenges involved in applying yeast prediction methods to higher organisms.

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

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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.

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

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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.

Model systems for understanding absorption tuning by opsin proteins

DEFF Research Database (Denmark)

Nielsen, Mogens Brøndsted

2009-01-01

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

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.

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.

GFP-like proteins as ubiquitous metazoan superfamily: evolution of functional features and structural complexity.

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Shagin, Dmitry A; Barsova, Ekaterina V; Yanushevich, Yurii G; Fradkov, Arkady F; Lukyanov, Konstantin A; Labas, Yulii A; Semenova, Tatiana N; Ugalde, Juan A; Meyers, Ann; Nunez, Jose M; Widder, Edith A; Lukyanov, Sergey A; Matz, Mikhail V

2004-05-01

Homologs of the green fluorescent protein (GFP), including the recently described GFP-like domains of certain extracellular matrix proteins in Bilaterian organisms, are remarkably similar at the protein structure level, yet they often perform totally unrelated functions, thereby warranting recognition as a superfamily. Here we describe diverse GFP-like proteins from previously undersampled and completely new sources, including hydromedusae and planktonic Copepoda. In hydromedusae, yellow and nonfluorescent purple proteins were found in addition to greens. Notably, the new yellow protein seems to follow exactly the same structural solution to achieving the yellow color of fluorescence as YFP, an engineered yellow-emitting mutant variant of GFP. The addition of these new sequences made it possible to resolve deep-level phylogenetic relationships within the superfamily. Fluorescence (most likely green) must have already existed in the common ancestor of Cnidaria and Bilateria, and therefore GFP-like proteins may be responsible for fluorescence and/or coloration in virtually any animal. At least 15 color diversification events can be inferred following the maximum parsimony principle in Cnidaria. Origination of red fluorescence and nonfluorescent purple-blue colors on several independent occasions provides a remarkable example of convergent evolution of complex features at the molecular level.

Editorial - a remark you made

Directory of Open Access Journals (Sweden)

Yngve Nordkvelle

2007-12-01

Full Text Available ”A remark you made” is the title of a wonderful tune by the famous jazz-rock group “Weather Report”, issued on the influential “Heavy weather” LP some 30 years ago. In an age where planning and rationalizing is the main issue in most contexts, whether it’s a matter of studying, teaching, doing research or using a diet, “A remark you made” is a symbol of attending to the unplanned, unforeseen and often, unwanted. In most accounts on cognitive development one is overtly focused on the manageable, on the predictable and expected, and not so attentive to the opposite. “A remark you made” makes us think again and reconsider what might be of value, in what we otherwise might neglect. A remark made by Terry Anderson at a conference last year (2006 was rather telling. Anderson is the renown distance educator from Athabasca University, Alberta Canada, and editor of our fellow e-journal “The International Review of Research in Open and Distance Learning”. I recite it here totally from my own memory, and I have never approached him to have it verified, falsified or commented. That doesn’t matter in this context. Standing on the podium, he lowered his voice and asked if any Danes were present in the room. There weren’t! Then he explained that his argument might be presented differently with Danes present: “You see – Danes seem to think that learning alone is no longer possible!” That remark caused quite a good laugh, not the least because any comment – good or bad – about fellow Scandinavians generally is considered to be a good joke. But it was also a comment on how not only distance education, or open and flexible learning, but learning theory in general is driven by the sociocultural learning theory, - and according to Anderson, particularly so in Denmark! Our first contribution in this issue is about the theory of media theory developed by one of our editors: Lars Qvortrup. Lars is now the rector of the Danish �

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.

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

Nanoscale protein diffusion by STED-based pair correlation analysis.

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Paolo Bianchini

Full Text Available We describe for the first time the combination between cross-pair correlation function analysis (pair correlation analysis or pCF and stimulated emission depletion (STED to obtain diffusion maps at spatial resolution below the optical diffraction limit (super-resolution. Our approach was tested in systems characterized by high and low signal to noise ratio, i.e. Capsid Like Particles (CLPs bearing several (>100 active fluorescent proteins and monomeric fluorescent proteins transiently expressed in living Chinese Hamster Ovary cells, respectively. The latter system represents the usual condition encountered in living cell studies on fluorescent protein chimeras. Spatial resolution of STED-pCF was found to be about 110 nm, with a more than twofold improvement over conventional confocal acquisition. We successfully applied our method to highlight how the proximity to nuclear envelope affects the mobility features of proteins actively imported into the nucleus in living cells. Remarkably, STED-pCF unveiled the existence of local barriers to diffusion as well as the presence of a slow component at distances up to 500-700 nm from either sides of nuclear envelope. The mobility of this component is similar to that previously described for transport complexes. Remarkably, all these features were invisible in conventional confocal mode.

Role of Proteasome-Dependent Protein Degradation in Long-Term Operant Memory in "Aplysia"

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Lyons, Lisa C.; Gardner, Jacob S.; Gandour, Catherine E.; Krishnan, Harini C.

2017-01-01

We investigated the in vivo role of protein degradation during intermediate (ITM) and long-term memory (LTM) in "Aplysia" using an operant learning paradigm. The proteasome inhibitor MG-132 inhibited the induction and molecular consolidation of LTM with no effect on ITM. Remarkably, maintenance of steady-state protein levels through…

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.

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.

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.

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.

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

Science.gov (United States)

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...

A modeling strategy for G-protein coupled receptors

Directory of Open Access Journals (Sweden)

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.

Relation between native ensembles and experimental structures of proteins

DEFF Research Database (Denmark)

Best, R. B.; Lindorff-Larsen, Kresten; DePristo, M. A.

2006-01-01

Different experimental structures of the same protein or of proteins with high sequence similarity contain many small variations. Here we construct ensembles of "high-sequence similarity Protein Data Bank" (HSP) structures and consider the extent to which such ensembles represent the structural...... Data Bank ensembles; moreover, we show that the effects of uncertainties in structure determination are insufficient to explain the results. These results highlight the importance of accounting for native-state protein dynamics in making comparisons with ensemble-averaged experimental data and suggest...... heterogeneity of the native state in solution. We find that different NMR measurements probing structure and dynamics of given proteins in solution, including order parameters, scalar couplings, and residual dipolar couplings, are remarkably well reproduced by their respective high-sequence similarity Protein...

Markov state models of protein misfolding

Science.gov (United States)

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

2016-02-01

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

Photochemistry of triarylmethane dyes bound to proteins

Science.gov (United States)

Indig, Guilherme L.

1996-04-01

Triarylmethanes represent a class of cationic dyes whose potential as photosensitizers for use in photodynamic therapy of neoplastic diseases has never been comprehensively evaluated. Here, the laser-induced photodecomposition of three triarylmethane dyes, crystal violet, ethyl violet, and malachite green, non-covalently bound to bovine serum albumin (a model biological target) was investigated. Upon laser excitation at 532 nm, the bleaching of the corresponding dye-protein molecular complexes follows spectroscopic patterns that suggest the formation of reduced forms of the dyes as major reaction photoproducts. That implies that an electron or hydrogen atom transfer from the protein to the dye's moiety within the guest-host complex is the first step of the photobleaching process. Since the availability of dissolved molecular oxygen was not identified as a limiting factor for the phototransformations to occur, these dyes can be seen as potential phototherapeutic agents for use in hypoxic areas of tumors. These triarylmethane dyes strongly absorb at relatively long wavelengths (absorption maximum around 600 nm; (epsilon) max approximately equals 105 M-1 cm-1), and only minor changes in their absorption characteristics are observed upon binding to the protein. However the binding event leads to a remarkable increase in their fluorescence quantum yield and photoreactivity.

Lipid-regulated sterol transfer between closely apposed membranes by oxysterol-binding protein homologues.

Science.gov (United States)

Schulz, Timothy A; Choi, Mal-Gi; Raychaudhuri, Sumana; Mears, Jason A; Ghirlando, Rodolfo; Hinshaw, Jenny E; Prinz, William A

2009-12-14

Sterols are transferred between cellular membranes by vesicular and poorly understood nonvesicular pathways. Oxysterol-binding protein-related proteins (ORPs) have been implicated in sterol sensing and nonvesicular transport. In this study, we show that yeast ORPs use a novel mechanism that allows regulated sterol transfer between closely apposed membranes, such as organelle contact sites. We find that the core lipid-binding domain found in all ORPs can simultaneously bind two membranes. Using Osh4p/Kes1p as a representative ORP, we show that ORPs have at least two membrane-binding surfaces; one near the mouth of the sterol-binding pocket and a distal site that can bind a second membrane. The distal site is required for the protein to function in cells and, remarkably, regulates the rate at which Osh4p extracts and delivers sterols in a phosphoinositide-dependent manner. Together, these findings suggest a new model of how ORPs could sense and regulate the lipid composition of adjacent membranes.

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.

Protein-based nanostructures as carriers for photo-physically active molecules in biosystems

OpenAIRE

Delcanale, Pietro

2017-01-01

In nature, many proteins function as carriers, being able to bind, transport and possibly release a ligand within a biological system. Protein-based carriers are interesting systems for drug delivery, with the remarkable advantage of being water-soluble and, as inherent components of biosystems, highly bio-compatible. This work focuses on the use of protein-based carriers for the delivery of hydrophobic photo-physically active molecules, whose structure and chemical properties lead to spontan...

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

The role of oligomerization and cooperative regulation in protein function: the case of tryptophan synthase.

Directory of Open Access Journals (Sweden)

M Qaiser Fatmi

Full Text Available The oligomerization/co-localization of protein complexes and their cooperative regulation in protein function is a key feature in many biological systems. The synergistic regulation in different subunits often enhances the functional properties of the multi-enzyme complex. The present study used molecular dynamics and Brownian dynamics simulations to study the effects of allostery, oligomerization and intermediate channeling on enhancing the protein function of tryptophan synthase (TRPS. TRPS uses a set of α/β-dimeric units to catalyze the last two steps of L-tryptophan biosynthesis, and the rate is remarkably slower in the isolated monomers. Our work shows that without their binding partner, the isolated monomers are stable and more rigid. The substrates can form fairly stable interactions with the protein in both forms when the protein reaches the final ligand-bound conformations. Our simulations also revealed that the α/β-dimeric unit stabilizes the substrate-protein conformation in the ligand binding process, which lowers the conformation transition barrier and helps the protein conformations shift from an open/inactive form to a closed/active form. Brownian dynamics simulations with a coarse-grained model illustrate how protein conformations affect substrate channeling. The results highlight the complex roles of protein oligomerization and the fine balance between rigidity and dynamics in protein function.

Some Remarks on Stability of Generalized Equations

Czech Academy of Sciences Publication Activity Database

Outrata, Jiří; Henrion, R.; Kruger, A.Y.

2013-01-01

Roč. 159, č. 3 (2013), s. 681-697 ISSN 0022-3239 R&D Projects: GA AV ČR IAA100750802; GA ČR(CZ) GAP201/12/0671 Institutional support: RVO:67985556 Keywords : Parameterized generalized equation * Regular and limiting coderivative * Constant rank CQ * Mathematical program with equilibrium constraints Subject RIV: BA - General Mathematics Impact factor: 1.406, year: 2013 http://library.utia.cas.cz/separaty/2013/MTR/outrata-some remarks on stability of generalized equations.pdf

Analysis of Pseudomonas aeruginosa Cell Envelope Proteome by Capture of Surface-Exposed Proteins on Activated Magnetic Nanoparticles

OpenAIRE

Vecchietti, Davide; Di Silvestre, Dario; Miriani, Matteo; Bonomi, Francesco; Marengo, Mauro; Bragonzi, Alessandra; Cova, Lara; Franceschi, Eleonora; Mauri, Pierluigi; Bertoni, Giovanni

2012-01-01

We report on specific magneto-capturing followed by Multidimensional Protein Identification Technology (MudPIT) for the analysis of surface-exposed proteins of intact cells of the bacterial opportunistic pathogen Pseudomonas aeruginosa. The magneto-separation of cell envelope fragments from the soluble cytoplasmic fraction allowed the MudPIT identification of the captured and neighboring proteins. Remarkably, we identified 63 proteins captured directly by nanoparticles and 67 proteins embedde...

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.

Modelling Transcapillary Transport of Fluid and Proteins in Hemodialysis Patients.

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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.

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.

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...

C/EBPβ-LAP*/LAP Expression Is Mediated by RSK/eIF4B-Dependent Signalling and Boosted by Increased Protein Stability in Models of Monocytic Differentiation.

Directory of Open Access Journals (Sweden)

René Huber

Full Text Available The transcription factor C/EBPβ plays a key role in monocytic differentiation and inflammation. Its small isoform LIP is associated with proliferation at early premonocytic developmental stages and regulated via mTOR-dependent signalling. During later stages of (premonocytic differentiation there is a considerable increase in the large C/EBPβ isoforms LAP*/LAP which inhibit proliferation thus supporting terminal differentiation. Here, we showed in different models of monocytic differentiation that this dramatic increase in the LAP*/LAP protein and LAP/LIP ratio was accompanied by an only modest/retarded mRNA increase suggesting an important role for (posttranslational mechanisms. We found that LAP*/LAP formation was induced via MEK/RSK-dependent cascades, whereas mTOR/S6K1 were not involved. Remarkably, LAP*/LAP expression was dependent on phosphorylated eIF4B, an acceleratory protein of RNA helicase eIF4A. PKR inhibition reduced the expression of eIF4B and C/EBPβ in an eIF2α-independent manner. Furthermore, under our conditions a marked stabilisation of LAP*/LAP protein occurred, accompanied by reduced chymotrypsin-like proteasome/calpain activities and increased calpastatin levels. Our study elucidates new signalling pathways inducing LAP*/LAP expression and indicates new alternative PKR functions in monocytes. The switch from mTOR- to RSK-mediated signalling to orchestrate eIF4B-dependent LAP*/LAP translation, accompanied by increased protein stability but only small mRNA changes, may be a prototypical example for the regulation of protein expression during selected processes of differentiation/proliferation.

C/EBPβ-LAP*/LAP Expression Is Mediated by RSK/eIF4B-Dependent Signalling and Boosted by Increased Protein Stability in Models of Monocytic Differentiation

Science.gov (United States)

Christmann, Martin; Friesenhagen, Judith; Westphal, Andreas; Pietsch, Daniel; Brand, Korbinian

2015-01-01

The transcription factor C/EBPβ plays a key role in monocytic differentiation and inflammation. Its small isoform LIP is associated with proliferation at early premonocytic developmental stages and regulated via mTOR-dependent signalling. During later stages of (pre)monocytic differentiation there is a considerable increase in the large C/EBPβ isoforms LAP*/LAP which inhibit proliferation thus supporting terminal differentiation. Here, we showed in different models of monocytic differentiation that this dramatic increase in the LAP*/LAP protein and LAP/LIP ratio was accompanied by an only modest/retarded mRNA increase suggesting an important role for (post)translational mechanisms. We found that LAP*/LAP formation was induced via MEK/RSK-dependent cascades, whereas mTOR/S6K1 were not involved. Remarkably, LAP*/LAP expression was dependent on phosphorylated eIF4B, an acceleratory protein of RNA helicase eIF4A. PKR inhibition reduced the expression of eIF4B and C/EBPβ in an eIF2α-independent manner. Furthermore, under our conditions a marked stabilisation of LAP*/LAP protein occurred, accompanied by reduced chymotrypsin-like proteasome/calpain activities and increased calpastatin levels. Our study elucidates new signalling pathways inducing LAP*/LAP expression and indicates new alternative PKR functions in monocytes. The switch from mTOR- to RSK-mediated signalling to orchestrate eIF4B-dependent LAP*/LAP translation, accompanied by increased protein stability but only small mRNA changes, may be a prototypical example for the regulation of protein expression during selected processes of differentiation/proliferation. PMID:26646662

Collisionless shocks and upstream waves and particles: Introductory remarks

International Nuclear Information System (INIS)

Kennel, C.F.

1981-01-01

We discuss more aspects of collisionless shock theory that might be pertinent to the problem of upstream waves and particles. It is hoped that our qualititive remarks may be a useful guide for the general reader as he goes through the detailed papers to come

Some remarks on electron scattering in a laser field

International Nuclear Information System (INIS)

Ehlotzky, F.

1988-01-01

Potential scattering of electrons in a quantized radiation field is reconsidered. Some remarks are made on the validity of the Kroll-Watson scattering formula and on the close connection of this formula with the classical transition rate of scattering in a radiation field. (17 refs.)

From the Protein's Perspective: The Benefits and Challenges of Protein Structure-Based Pharmacophore Modeling

NARCIS (Netherlands)

Sanders, M.P.A.; McGuire, R; Roumen, L.; de Esch, I.J.P.; de Vlieg, J; Klomp, J.P.G; de Graaf, C.

2011-01-01

A pharmacophore describes the arrangement of molecular features a ligand must contain to efficaciously bind a receptor. Pharmacophore models are developed to improve molecular understanding of ligand-protein interactions, and can be used as a tool to identify novel compounds that fulfil the

Analysing the origin of long-range interactions in proteins using lattice models

Directory of Open Access Journals (Sweden)

Unger Ron

2009-01-01

Full Text Available Abstract Background Long-range communication is very common in proteins but the physical basis of this phenomenon remains unclear. In order to gain insight into this problem, we decided to explore whether long-range interactions exist in lattice models of proteins. Lattice models of proteins have proven to capture some of the basic properties of real proteins and, thus, can be used for elucidating general principles of protein stability and folding. Results Using a computational version of double-mutant cycle analysis, we show that long-range interactions emerge in lattice models even though they are not an input feature of them. The coupling energy of both short- and long-range pairwise interactions is found to become more positive (destabilizing in a linear fashion with increasing 'contact-frequency', an entropic term that corresponds to the fraction of states in the conformational ensemble of the sequence in which the pair of residues is in contact. A mathematical derivation of the linear dependence of the coupling energy on 'contact-frequency' is provided. Conclusion Our work shows how 'contact-frequency' should be taken into account in attempts to stabilize proteins by introducing (or stabilizing contacts in the native state and/or through 'negative design' of non-native contacts.

Remarks on the microscopic derivation of the collective model

International Nuclear Information System (INIS)

Toyoda, T.; Wildermuth, K.

1984-01-01

The rotational part of the phenomenological collective model of Bohr and Mottelson and others is derived microscopically, starting with the Schrodinger equation written in projection form and introducing a new set of 'relative Euler angles'. In order to derive the local Schrodinger equation of the collective model, it is assumed that the intrinsic wave functions give strong peaking properties to the overlapping kernels

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.

Toward a rigorous network of protein-protein interactions of the model sulfate reducer Desulfovibrio vulgaris Hildenborough

Energy Technology Data Exchange (ETDEWEB)

Chhabra, S.R.; Joachimiak, M.P.; Petzold, C.J.; Zane, G.M.; Price, M.N.; Gaucher, S.; Reveco, S.A.; Fok, V.; Johanson, A.R.; Batth, T.S.; Singer, M.; Chandonia, J.M.; Joyner, D.; Hazen, T.C.; Arkin, A.P.; Wall, J.D.; Singh, A.K.; Keasling, J.D.

2011-05-01

Protein–protein interactions offer an insight into cellular processes beyond what may be obtained by the quantitative functional genomics tools of proteomics and transcriptomics. The aforementioned tools have been extensively applied to study E. coli and other aerobes and more recently to study the stress response behavior of Desulfovibrio 5 vulgaris Hildenborough, a model anaerobe and sulfate reducer. In this paper we present the first attempt to identify protein-protein interactions in an obligate anaerobic bacterium. We used suicide vector-assisted chromosomal modification of 12 open reading frames encoded by this sulfate reducer to append an eight amino acid affinity tag to the carboxy-terminus of the chosen proteins. Three biological replicates of the 10 ‘pulled-down’ proteins were separated and analyzed using liquid chromatography-mass spectrometry. Replicate agreement ranged between 35% and 69%. An interaction network among 12 bait and 90 prey proteins was reconstructed based on 134 bait-prey interactions computationally identified to be of high confidence. We discuss the biological significance of several unique metabolic features of D. vulgaris revealed by this protein-protein interaction data 15 and protein modifications that were observed. These include the distinct role of the putative carbon monoxide-induced hydrogenase, unique electron transfer routes associated with different oxidoreductases, and the possible role of methylation in regulating sulfate reduction.

Towards a rigorous network of protein-protein interactions of the model sulfate reducer Desulfovibrio vulgaris Hildenborough.

Directory of Open Access Journals (Sweden)

Swapnil R Chhabra

Full Text Available Protein-protein interactions offer an insight into cellular processes beyond what may be obtained by the quantitative functional genomics tools of proteomics and transcriptomics. The aforementioned tools have been extensively applied to study Escherichia coli and other aerobes and more recently to study the stress response behavior of Desulfovibrio vulgaris Hildenborough, a model obligate anaerobe and sulfate reducer and the subject of this study. Here we carried out affinity purification followed by mass spectrometry to reconstruct an interaction network among 12 chromosomally encoded bait and 90 prey proteins based on 134 bait-prey interactions identified to be of high confidence. Protein-protein interaction data are often plagued by the lack of adequate controls and replication analyses necessary to assess confidence in the results, including identification of potential false positives. We addressed these issues through the use of biological replication, exponentially modified protein abundance indices, results from an experimental negative control, and a statistical test to assign confidence to each putative interacting pair applicable to small interaction data studies. We discuss the biological significance of metabolic features of D. vulgaris revealed by these protein-protein interaction data and the observed protein modifications. These include the distinct role of the putative carbon monoxide-induced hydrogenase, unique electron transfer routes associated with different oxidoreductases, and the possible role of methylation in regulating sulfate reduction.

Some concluding remarks about cold moderator development

International Nuclear Information System (INIS)

Carpenter, J.M.

1990-01-01

This paper is the transcription of remarks made at the conclusion of the Workshop on Cold Neutron Sources held at the Los Angeles National Laboratory, Los Alamos, New Mexico, March 5--7, 1990. Areas of interest include the following: scattering functions; cold moderator materials; radiation mixing of chemical composition; comparison of some pulsed moderator spectra; hydrogen mixtures; premoderators and shields; composite reflectors; exotic moderator materials; deuterated methanes; mixed moderator materials; and test facility availabilities. 2 refs., 4 figs., 1 tab

A Review on Recent Advances in Stabilizing Peptides/Proteins upon Fabrication in Hydrogels from Biodegradable Polymers.

Science.gov (United States)

Raza, Faisal; Zafar, Hajra; Zhu, Ying; Ren, Yuan; -Ullah, Aftab; Khan, Asif Ullah; He, Xinyi; Han, Han; Aquib, Md; Boakye-Yiadom, Kofi Oti; Ge, Liang

2018-01-18

Hydrogels evolved as an outstanding carrier material for local and controlled drug delivery that tend to overcome the shortcomings of old conventional dosage forms for small drugs (NSAIDS) and large peptides and proteins. The aqueous swellable and crosslinked polymeric network structure of hydrogels is composed of various natural, synthetic and semisynthetic biodegradable polymers. Hydrogels have remarkable properties of functionality, reversibility, sterilizability, and biocompatibility. All these dynamic properties of hydrogels have increased the interest in their use as a carrier for peptides and proteins to be released slowly in a sustained manner. Peptide and proteins are remarkable therapeutic agents in today's world that allow the treatment of severe, chronic and life-threatening diseases, such as diabetes, rheumatoid arthritis, hepatitis. Despite few limitations, hydrogels provide fine tuning of proteins and peptides delivery with enormous impact in clinical medicine. Novels drug delivery systems composed of smart peptides and molecules have the ability to drive self-assembly and form hydrogels at physiological pH. These hydrogels are significantly important for biological and medical fields. The primary objective of this article is to review current issues concerned with the therapeutic peptides and proteins and impact of remarkable properties of hydrogels on these therapeutic agents. Different routes for pharmaceutical peptides and proteins and superiority over other drugs candidates are presented. Recent advances based on various approaches like self-assembly of peptides and small molecules to form novel hydrogels are also discussed. The article will also review the literature concerning the classification of hydrogels on a different basis, polymers used, "release mechanisms" their physical and chemical characteristics and diverse applications.

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

DEFF Research Database (Denmark)

Kynde, Søren Andreas Røssell

This thesis consists of two parts. The rst part is divided into five chapters. Chapter 1 gives a general introduction to the bio-molecular systems that have been studied. These are membrane proteins and their lipid environments in the form of phospholipid nanodiscs. Membrane proteins...... the techniques very well suited for the study of the nanodisc system. Chapter 3 explains two different modelling approaches that can be used in the analysis of small-angle scattering data from lipid-protein complexes. These are the continuous approach where the system of interest is modelled as a few regular...... combine the bene ts of each of the methods and give unique structural information about relevant bio-molecular complexes in solution. Chapter 4 describes the work behind a proposal of a small-angle neutron scattering instrument for the European Spallation Source under construction in Lund. The instrument...

Lessons from Animal Models of Cytoplasmic Intermediate Filament Proteins.

Science.gov (United States)

Bouameur, Jamal-Eddine; Magin, Thomas M

Cytoplasmic intermediate filaments (IFs) represent a major cytoskeletal network contributing to cell shape, adhesion and migration as well as to tissue resilience and renewal in numerous bilaterians, including mammals. The observation that IFs are dispensable in cultured mammalian cells, but cause tissue-specific, life-threatening disorders, has pushed the need to investigate their function in vivo. In keeping with human disease, the deletion or mutation of murine IF genes resulted in highly specific pathologies. Epidermal keratins, together with desmin, are essential to protect corresponding tissues against mechanical force but also participate in stabilizing cell adhesion and in inflammatory signalling. Surprisingly, other IF proteins contribute to tissue integrity to a much lesser extent than anticipated, pointing towards their role in stress situations. In support, the overexpression of small chaperones or the interference with inflammatory signalling in several settings has been shown to rescue severe tissue pathologies that resulted from the expression of mutant IF proteins. It stills remains an open issue whether the wide range of IF disorders share similar pathomechanisms. Moreover, we lack an understanding how IF proteins participate in signalling processes. Now, with a large number of mouse models in hand, the next challenge will be to develop organotypic cell culture models to dissect pathomechanisms at the molecular level, to employ Crispr/Cas-mediated genome engineering to optimize models and, finally, to combine available animal models with medicinal chemistry for the development of molecular therapies.

Genetic background of Prop1(df) mutants provides remarkable protection against hypothyroidism-induced hearing impairment.

Science.gov (United States)

Fang, Qing; Giordimaina, Alicia M; Dolan, David F; Camper, Sally A; Mustapha, Mirna

2012-04-01

Hypothyroidism is a cause of genetic and environmentally induced deafness. The sensitivity of cochlear development and function to thyroid hormone (TH) mandates understanding TH action in this sensory organ. Prop1(df) and Pou1f1(dw) mutant mice carry mutations in different pituitary transcription factors, each resulting in pituitary thyrotropin deficiency. Despite the same lack of detectable serum TH, these mutants have very different hearing abilities: Prop1(df) mutants are mildly affected, while Pou1f1(dw) mutants are completely deaf. Genetic studies show that this difference is attributable to the genetic backgrounds. Using embryo transfer, we discovered that factors intrinsic to the fetus are the major contributor to this difference, not maternal effects. We analyzed Prop1(df) mutants to identify processes in cochlear development that are disrupted in other hypothyroid animal models but protected in Prop1(df) mutants by the genetic background. The development of outer hair cell (OHC) function is delayed, but Prestin and KCNQ4 immunostaining appear normal in mature Prop1(df) mutants. The endocochlear potential and KCNJ10 immunostaining in the stria vascularis are indistinguishable from wild type, and no differences in neurofilament or synaptophysin staining are evident in Prop1(df) mutants. The synaptic vesicle protein otoferlin normally shifts expression from OHC to IHC as temporary afferent fibers beneath the OHC regress postnatally. Prop1(df) mutants exhibit persistent, abnormal expression of otoferlin in apical OHC, suggesting delayed maturation of synaptic function. Thus, the genetic background of Prop1(df) mutants is remarkably protective for most functions affected in other hypothyroid mice. The Prop1(df) mutant is an attractive model for identifying the genes that protect against deafness.

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

A REMARK ON FORMAL MODELS FOR NONLINEARLY ELASTIC MEMBRANE SHELLS

Institute of Scientific and Technical Information of China (English)

无

2001-01-01

This paper gives all the two-dimensional membrane models obtained from formal asymptotic analysis of the three-dimensional geometrically exact nonlinear model of a thin elastic shell made with a Saint Venant-Kirchhoff material. Therefore, the other models can be quoted as flexural nonlinear ones. The author also gives the formal equations solved by the associated stress tensor and points out that only one of those models leads, by linearization, to the “classical” linear limiting membrane model, whose juetification has already been established by a convergence theorem.

Protein Functionalized Nanodiamond Arrays

Directory of Open Access Journals (Sweden)

Liu YL

2010-01-01

Full Text Available Abstract Various nanoscale elements are currently being explored for bio-applications, such as in bio-images, bio-detection, and bio-sensors. Among them, nanodiamonds possess remarkable features such as low bio-cytotoxicity, good optical property in fluorescent and Raman spectra, and good photostability for bio-applications. In this work, we devise techniques to position functionalized nanodiamonds on self-assembled monolayer (SAMs arrays adsorbed on silicon and ITO substrates surface using electron beam lithography techniques. The nanodiamond arrays were functionalized with lysozyme to target a certain biomolecule or protein specifically. The optical properties of the nanodiamond-protein complex arrays were characterized by a high throughput confocal microscope. The synthesized nanodiamond-lysozyme complex arrays were found to still retain their functionality in interacting with E. coli.

(S)Pinning down protein interactions by NMR

DEFF Research Database (Denmark)

Teilum, Kaare; Kunze, Micha Ben Achim; Erlendsson, Simon

2017-01-01

Protein molecules are highly diverse communication platforms and their interaction repertoire stretches from atoms over small molecules such as sugars and lipids to macromolecules. An important route to understanding molecular communication is to quantitatively describe their interactions...... all types of protein reactions, which can span orders of magnitudes in affinities, reaction rates and lifetimes of states. As the more versatile technique, solution NMR spectroscopy offers a remarkable catalogue of methods that can be successfully applied to the quantitative as well as qualitative...... descriptions of protein interactions. In this review we provide an easy-access approach to NMR for the non-NMR specialist and describe how and when solution state NMR spectroscopy is the method of choice for addressing protein ligand interaction. We describe very briefly the theoretical background...

Global optimization of proteins using a dynamical lattice model: Ground states and energy landscapes

OpenAIRE

Dressel, F.; Kobe, S.

2004-01-01

A simple approach is proposed to investigate the protein structure. Using a low complexity model, a simple pairwise interaction and the concept of global optimization, we are able to calculate ground states of proteins, which are in agreement with experimental data. All possible model structures of small proteins are available below a certain energy threshold. The exact lowenergy landscapes for the trp cage protein (1L2Y) is presented showing the connectivity of all states and energy barriers.

Protein structure modelling and evaluation based on a 4-distance description of side-chain interactions

Directory of Open Access Journals (Sweden)

Inbar Yuval

2010-07-01

Full Text Available Abstract Background Accurate evaluation and modelling of residue-residue interactions within and between proteins is a key aspect of computational structure prediction including homology modelling, protein-protein docking, refinement of low-resolution structures, and computational protein design. Results Here we introduce a method for accurate protein structure modelling and evaluation based on a novel 4-distance description of residue-residue interaction geometry. Statistical 4-distance preferences were extracted from high-resolution protein structures and were used as a basis for a knowledge-based potential, called Hunter. We demonstrate that 4-distance description of side chain interactions can be used reliably to discriminate the native structure from a set of decoys. Hunter ranked the native structure as the top one in 217 out of 220 high-resolution decoy sets, in 25 out of 28 "Decoys 'R' Us" decoy sets and in 24 out of 27 high-resolution CASP7/8 decoy sets. The same concept was applied to side chain modelling in protein structures. On a set of very high-resolution protein structures the average RMSD was 1.47 Å for all residues and 0.73 Å for buried residues, which is in the range of attainable accuracy for a model. Finally, we show that Hunter performs as good or better than other top methods in homology modelling based on results from the CASP7 experiment. The supporting web site http://bioinfo.weizmann.ac.il/hunter/ was developed to enable the use of Hunter and for visualization and interactive exploration of 4-distance distributions. Conclusions Our results suggest that Hunter can be used as a tool for evaluation and for accurate modelling of residue-residue interactions in protein structures. The same methodology is applicable to other areas involving high-resolution modelling of biomolecules.

Some remarks on a scenario of supersymmetry in quantum mechanics

International Nuclear Information System (INIS)

Jannussis, A.; Tsohantzis, I; Vavougios, D.

1990-01-01

Some remarks are given on a recent paper of Lahiri, Kumar Roy and Bagchi who have constructed a scenario of supersymmetry in quantum mechanics by imposing a structure on the raising and lowering operators

Modeling of allergen proteins found in sea food products

Directory of Open Access Journals (Sweden)

Nataly Galán-Freyle

2012-06-01

Full Text Available Shellfish are a source of food allergens, and their consumption is the cause of severe allergic reactions in humans. Tropomyosins, a family of muscle proteins, have been identified as the major allergens in shellfish and mollusks species. Nevertheless, few experimentally determined three-dimensional structures are available in the Protein Data Base (PDB. In this study, 3D models of several homologous of tropomyosins present in marine shellfish and mollusk species (Chaf 1, Met e1, Hom a1, Per v1, and Pen a1 were constructed, validated, and their immunoglobulin E binding epitopes were identified using bioinformatics tools. All protein models for these allergens consisted of long alpha-helices. Chaf 1, Met e1, and Hom a1 had six conserved regions with sequence similarities to known epitopes, whereas Per v1 and Pen a1 contained only one. Lipophilic potentials of identified epitopes revealed a high propensity of hydrophobic amino acids in the immunoglobulin E binding site. This information could be useful to design tropomyosin-specific immunotherapy for sea food allergies.

Model to predict inhomogeneous protein-sugar distribution in powders prepared by spray drying

NARCIS (Netherlands)

Grasmeijer, Niels; Frijlink, Henderik W.; Hinrichs, Wouter L. J.

2016-01-01

A protein can be stabilized by spray drying an aqueous solution of the protein and a sugar, thereby incorporating the protein into a glassy sugar matrix. For optimal stability, the protein should be homogeneously distributed inside the sugar matrix. The aim of this study was to develop a model that

Enrichment and desalting of tryptic protein digests and the protein depletion using boron nitride

Energy Technology Data Exchange (ETDEWEB)

Fischnaller, Martin; Köck, Rainer; Bakry, Rania, E-mail: rania.bakry@uibk.ac.at; Bonn, Günther K.

2014-05-01

Highlights: • Protein tryptic digests were desalted and enriched utilizing hexagonal boron nitride. • Phosphopeptides were desalted with high recovery rates. • Boron nitride exhibits high wettability allowing fast sample preparation. • Boron nitride shows protein depletion capability applied for peptide purification. - Abstract: Sample preparation still remains a great challenge in modern bioanalysis and the interest in new efficient solid phase extraction (SPE) materials still remains high. In this work, hexagonal boron nitride (h-BN) is introduced as a new SPE material for the isolation and enrichment of peptides. The h-BN is isoelectronic and structurally similar to graphite. It has remarkable properties including good thermal conductivity, excellent thermal and chemical stability and a better oxidation resistance than graphite. BN attracts increasing interest because of its wide range of applicability. In the present work, the great potential of h-BN, as a new SPE-material, on the enrichment, preconcentration and desalting of tryptic digest of model proteins is demonstrated. A special attention was dedicated to the efficient enrichment of hydrophilic phosphopeptides. Two elution protocols were developed for the enrichment of peptides compatible for subsequent MALDI-MS and ESI-MS analysis. In addition, the recoveries of 5 peptides and 3 phosphopeptides with wide range of pI values utilizing h-BN materials with different surface areas were investigated. 84–106% recovery rate could be achieved using h-BN materials. The results were compared with those obtained using graphite and silica C18 under the same elution conditions, and lower recoveries were obtained. In addition, h-BN was found to have a capability of protein depletion, which is requisite for the peptide profiling.

Enrichment and desalting of tryptic protein digests and the protein depletion using boron nitride

International Nuclear Information System (INIS)

Fischnaller, Martin; Köck, Rainer; Bakry, Rania; Bonn, Günther K.

2014-01-01

Highlights: • Protein tryptic digests were desalted and enriched utilizing hexagonal boron nitride. • Phosphopeptides were desalted with high recovery rates. • Boron nitride exhibits high wettability allowing fast sample preparation. • Boron nitride shows protein depletion capability applied for peptide purification. - Abstract: Sample preparation still remains a great challenge in modern bioanalysis and the interest in new efficient solid phase extraction (SPE) materials still remains high. In this work, hexagonal boron nitride (h-BN) is introduced as a new SPE material for the isolation and enrichment of peptides. The h-BN is isoelectronic and structurally similar to graphite. It has remarkable properties including good thermal conductivity, excellent thermal and chemical stability and a better oxidation resistance than graphite. BN attracts increasing interest because of its wide range of applicability. In the present work, the great potential of h-BN, as a new SPE-material, on the enrichment, preconcentration and desalting of tryptic digest of model proteins is demonstrated. A special attention was dedicated to the efficient enrichment of hydrophilic phosphopeptides. Two elution protocols were developed for the enrichment of peptides compatible for subsequent MALDI-MS and ESI-MS analysis. In addition, the recoveries of 5 peptides and 3 phosphopeptides with wide range of pI values utilizing h-BN materials with different surface areas were investigated. 84–106% recovery rate could be achieved using h-BN materials. The results were compared with those obtained using graphite and silica C18 under the same elution conditions, and lower recoveries were obtained. In addition, h-BN was found to have a capability of protein depletion, which is requisite for the peptide profiling

Animal Models of Congenital Cardiomyopathies Associated With Mutations in Z-Line Proteins.

Science.gov (United States)

Bang, Marie-Louise

2017-01-01

The cardiac Z-line at the boundary between sarcomeres is a multiprotein complex connecting the contractile apparatus with the cytoskeleton and the extracellular matrix. The Z-line is important for efficient force generation and transmission as well as the maintenance of structural stability and integrity. Furthermore, it is a nodal point for intracellular signaling, in particular mechanosensing and mechanotransduction. Mutations in various genes encoding Z-line proteins have been associated with different cardiomyopathies, including dilated cardiomyopathy, hypertrophic cardiomyopathy, arrhythmogenic right ventricular cardiomyopathy, restrictive cardiomyopathy, and left ventricular noncompaction, and mutations even within the same gene can cause widely different pathologies. Animal models have contributed to a great advancement in the understanding of the physiological function of Z-line proteins and the pathways leading from mutations in Z-line proteins to cardiomyopathy, although genotype-phenotype prediction remains a great challenge. This review presents an overview of the currently available animal models for Z-line and Z-line associated proteins involved in human cardiomyopathies with special emphasis on knock-in and transgenic mouse models recapitulating the clinical phenotypes of human cardiomyopathy patients carrying mutations in Z-line proteins. Pros and cons of mouse models will be discussed and a future outlook will be given. J. Cell. Physiol. 232: 38-52, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Mixing Energy Models in Genetic Algorithms for On-Lattice Protein Structure Prediction

Directory of Open Access Journals (Sweden)

Mahmood A. Rashid

2013-01-01

Full Text Available Protein structure prediction (PSP is computationally a very challenging problem. The challenge largely comes from the fact that the energy function that needs to be minimised in order to obtain the native structure of a given protein is not clearly known. A high resolution 20×20 energy model could better capture the behaviour of the actual energy function than a low resolution energy model such as hydrophobic polar. However, the fine grained details of the high resolution interaction energy matrix are often not very informative for guiding the search. In contrast, a low resolution energy model could effectively bias the search towards certain promising directions. In this paper, we develop a genetic algorithm that mainly uses a high resolution energy model for protein structure evaluation but uses a low resolution HP energy model in focussing the search towards exploring structures that have hydrophobic cores. We experimentally show that this mixing of energy models leads to significant lower energy structures compared to the state-of-the-art results.

Oral sensitization to food proteins: A Brown Norway rat model

NARCIS (Netherlands)

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

1998-01-01

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

Incorporating water-release and lateral protein interactions in modeling equilibrium adsorption for ion-exchange chromatography.

Science.gov (United States)

Thrash, Marvin E; Pinto, Neville G

2006-09-08

The equilibrium adsorption of two albumin proteins on a commercial ion exchanger has been studied using a colloidal model. The model accounts for electrostatic and van der Waals forces between proteins and the ion exchanger surface, the energy of interaction between adsorbed proteins, and the contribution of entropy from water-release accompanying protein adsorption. Protein-surface interactions were calculated using methods previously reported in the literature. Lateral interactions between adsorbed proteins were experimentally measured with microcalorimetry. Water-release was estimated by applying the preferential interaction approach to chromatographic retention data. The adsorption of ovalbumin and bovine serum albumin on an anion exchanger at solution pH>pI of protein was measured. The experimental isotherms have been modeled from the linear region to saturation, and the influence of three modulating alkali chlorides on capacity has been evaluated. The heat of adsorption is endothermic for all cases studied, despite the fact that the net charge on the protein is opposite that of the adsorbing surface. Strong repulsive forces between adsorbed proteins underlie the endothermic heat of adsorption, and these forces intensify with protein loading. It was found that the driving force for adsorption is the entropy increase due to the release of water from the protein and adsorbent surfaces. It is shown that the colloidal model predicts protein adsorption capacity in both the linear and non-linear isotherm regions, and can account for the effects of modulating salt.

Building alternate protein structures using the elastic network model.

Science.gov (United States)

Yang, Qingyi; Sharp, Kim A

2009-02-15

We describe a method for efficiently generating ensembles of alternate, all-atom protein structures that (a) differ significantly from the starting structure, (b) have good stereochemistry (bonded geometry), and (c) have good steric properties (absence of atomic overlap). The method uses reconstruction from a series of backbone framework structures that are obtained from a modified elastic network model (ENM) by perturbation along low-frequency normal modes. To ensure good quality backbone frameworks, the single force parameter ENM is modified by introducing two more force parameters to characterize the interaction between the consecutive carbon alphas and those within the same secondary structure domain. The relative stiffness of the three parameters is parameterized to reproduce B-factors, while maintaining good bonded geometry. After parameterization, violations of experimental Calpha-Calpha distances and Calpha-Calpha-Calpha pseudo angles along the backbone are reduced to less than 1%. Simultaneously, the average B-factor correlation coefficient improves to R = 0.77. Two applications illustrate the potential of the approach. (1) 102,051 protein backbones spanning a conformational space of 15 A root mean square deviation were generated from 148 nonredundant proteins in the PDB database, and all-atom models with minimal bonded and nonbonded violations were produced from this ensemble of backbone structures using the SCWRL side chain building program. (2) Improved backbone templates for homology modeling. Fifteen query sequences were each modeled on two targets. For each of the 30 target frameworks, dozens of improved templates could be produced In all cases, improved full atom homology models resulted, of which 50% could be identified blind using the D-Fire statistical potential. (c) 2008 Wiley-Liss, Inc.

Selectivity analysis of protein kinase CK2 inhibitors DMAT, TBB and resorufin in cisplatin-induced stress responses

DEFF Research Database (Denmark)

Fritz, Gerhard; Issinger, Olaf-Georg; Olsen, Birgitte Brinkmann

2009-01-01

Targeting protein kinases as a therapeutic approach to treat various diseases, especially cancer is currently a fast growing business. Although many inhibitors are available, exhibiting remarkable potency, the major challenge is their selectivity. Here we show that the protein kinase CK2 inhibito...

Inhibition of the Unfolded Protein Response Mechanism Prevents Cardiac Fibrosis.

Directory of Open Access Journals (Sweden)

Jody Groenendyk

Full Text Available Cardiac fibrosis attributed to excessive deposition of extracellular matrix proteins is a major cause of heart failure and death. Cardiac fibrosis is extremely difficult and challenging to treat in a clinical setting due to lack of understanding of molecular mechanisms leading to cardiac fibrosis and effective anti-fibrotic therapies. The objective in this study was to examine whether unfolded protein response (UPR pathway mediates cardiac fibrosis and whether a pharmacological intervention to modulate UPR can prevent cardiac fibrosis and preserve heart function.We demonstrate here that the mechanism leading to development of fibrosis in a mouse with increased expression of calreticulin, a model of heart failure, stems from impairment of endoplasmic reticulum (ER homeostasis, transient activation of the unfolded protein response (UPR pathway and stimulation of the TGFβ1/Smad2/3 signaling pathway. Remarkably, sustained pharmacologic inhibition of the UPR pathway by tauroursodeoxycholic acid (TUDCA is sufficient to prevent cardiac fibrosis, and improved exercise tolerance.We show that the mechanism leading to development of fibrosis in a mouse model of heart failure stems from transient activation of UPR pathway leading to persistent remodelling of cardiac tissue. Blocking the activation of the transiently activated UPR pathway by TUDCA prevented cardiac fibrosis, and improved prognosis. These findings offer a window for additional interventions that can preserve heart function.

[Expressions of neuropathic pain-related proteins in the spinal cord dorsal horn in rats with bilateral chronic constriction injury].

Science.gov (United States)

Shen, Le; Li, Xu; Wang, Hai-tang; Yu, Xue-rong; Huang, Yu-guang

2013-12-01

To evaluate the pain-related behavioral changes in rats with bilateral chronic constriction injury(bCCI)and identify the expressions of neuropathic pain-related proteins. The bCCI models were established by ligating the sciatic nerves in female Sprague Dawley rats. Both mechanical hyperalgesia and cold hyperalgesia were evaluated through electronic von Frey and acetone method. Liquid chromatography-mass spectrometry/mass spectrometry was applied to characterize the differentially expressed proteins. Both mechanical withdrawal threshold and cold hyperalgesia threshold decreased significantly on the postoperative day 7 and 14, when compared with na ve or sham rats(P <0.05). Twenty five differentially expressed proteins associated with bilateral CCI were discovered, with eighteen of them were upregulated and seven of them downregulated. The bCCT rats have remarkably decreased mechanical and cold hyperalgesia thresholds. Twenty five neuropathic pain-related proteins are found in the spinal cord dorsal horn.

The actin-like MreB proteins in Bacillus subtilis: a new turn.

Science.gov (United States)

Chastanet, Arnaud; Carballido-Lopez, Rut

2012-06-01

A decade ago, two breakthrough descriptions were reported: 1) the first helix-like protein localization pattern of MreB and its paralog Mbl in Bacillus subtilis and 2) the crystal structure of Thermotoga maritima MreB1, which was remarkably similar to that of actin. These discoveries strongly stimulated the field of bacterial development, leading to the identification of many new cytoskeletal proteins (1) and the publication of many studies describing the helical patterns of protein, DNA and even lipid domains. However, today, new breakthroughs are shaking up what had become a dogma. Instead of helical structures, MreBs appear to form discrete patches that move circumferentially around the cell, questioning the idea of MreB cables forming an actin-like cytoskeleton. Furthermore, increasing evidence of biochemical properties that are unlike the properties of actin suggest that the molecular behavior of MreB proteins may be different. The aim of this review is to summarize the current knowledge of the so-called "actin-like" MreB cytoskeleton through a discussion of the model Gram-positive bacterium B. subtilis and the most recent findings in this rapidly evolving research field.

Application of model bread baking in the examination of arabinoxylan-protein complexes in rye bread.

Science.gov (United States)

Buksa, Krzysztof

2016-09-05

The changes in molecular mass of arabinoxylan (AX) and protein caused by bread baking process were examined using a model rye bread. Instead of the normal flour, the dough contained starch, water-extractable AX and protein which were isolated from rye wholemeal. From the crumb of selected model breads, starch was removed releasing AX-protein complexes, which were further examined by size exclusion chromatography. On the basis of the research, it was concluded that optimum model mix can be composed of 3-6% AX and 3-6% rye protein isolate at 94-88% of rye starch meaning with the most similar properties to low extraction rye flour. Application of model rye bread allowed to examine the interactions between AX and proteins. Bread baked with a share of AX, rye protein and starch, from which the complexes of the highest molar mass were isolated, was characterized by the strongest structure of the bread crumb. Copyright © 2016 Elsevier Ltd. All rights reserved.

Ceramide-Protein Interactions Modulate Ceramide-Associated Lipotoxic Cardiomyopathy

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Stanley M. Walls

2018-03-01

Full Text Available Lipotoxic cardiomyopathy (LCM is characterized by abnormal myocardial accumulation of lipids, including ceramide; however, the contribution of ceramide to the etiology of LCM is unclear. Here, we investigated the association of ceramide metabolism and ceramide-interacting proteins (CIPs in LCM in the Drosophila heart model. We find that ceramide feeding or ceramide-elevating genetic manipulations are strongly associated with cardiac dilation and defects in contractility. High ceramide-associated LCM is prevented by inhibiting ceramide synthesis, establishing a robust model of direct ceramide-associated LCM, corroborating previous indirect evidence in mammals. We identified several CIPs from mouse heart and Drosophila extracts, including caspase activator Annexin-X, myosin chaperone Unc-45, and lipogenic enzyme FASN1, and remarkably, their cardiac-specific manipulation can prevent LCM. Collectively, these data suggest that high ceramide-associated lipotoxicity is mediated, in part, through altering caspase activation, sarcomeric maintenance, and lipogenesis, thus providing evidence for conserved mechanisms in LCM pathogenesis in mammals.

Proteomic Identification of Altered Cerebral Proteins in the Complex Regional Pain Syndrome Animal Model

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Francis Sahngun Nahm

2014-01-01

Full Text Available Background. Complex regional pain syndrome (CRPS is a rare but debilitating pain disorder. Although the exact pathophysiology of CRPS is not fully understood, central and peripheral mechanisms might be involved in the development of this disorder. To reveal the central mechanism of CRPS, we conducted a proteomic analysis of rat cerebrum using the chronic postischemia pain (CPIP model, a novel experimental model of CRPS. Materials and Methods. After generating the CPIP animal model, we performed a proteomic analysis of the rat cerebrum using a multidimensional protein identification technology, and screened the proteins differentially expressed between the CPIP and control groups. Results. A total of 155 proteins were differentially expressed between the CPIP and control groups: 125 increased and 30 decreased; expressions of proteins related to cell signaling, synaptic plasticity, regulation of cell proliferation, and cytoskeletal formation were increased in the CPIP group. However, proenkephalin A, cereblon, and neuroserpin were decreased in CPIP group. Conclusion. Altered expression of cerebral proteins in the CPIP model indicates cerebral involvement in the pathogenesis of CRPS. Further study is required to elucidate the roles of these proteins in the development and maintenance of CRPS.

Proteomic identification of altered cerebral proteins in the complex regional pain syndrome animal model.

Science.gov (United States)

Nahm, Francis Sahngun; Park, Zee-Yong; Nahm, Sang-Soep; Kim, Yong Chul; Lee, Pyung Bok

2014-01-01

Complex regional pain syndrome (CRPS) is a rare but debilitating pain disorder. Although the exact pathophysiology of CRPS is not fully understood, central and peripheral mechanisms might be involved in the development of this disorder. To reveal the central mechanism of CRPS, we conducted a proteomic analysis of rat cerebrum using the chronic postischemia pain (CPIP) model, a novel experimental model of CRPS. After generating the CPIP animal model, we performed a proteomic analysis of the rat cerebrum using a multidimensional protein identification technology, and screened the proteins differentially expressed between the CPIP and control groups. Results. A total of 155 proteins were differentially expressed between the CPIP and control groups: 125 increased and 30 decreased; expressions of proteins related to cell signaling, synaptic plasticity, regulation of cell proliferation, and cytoskeletal formation were increased in the CPIP group. However, proenkephalin A, cereblon, and neuroserpin were decreased in CPIP group. Altered expression of cerebral proteins in the CPIP model indicates cerebral involvement in the pathogenesis of CRPS. Further study is required to elucidate the roles of these proteins in the development and maintenance of CRPS.

Protein loop modeling using a new hybrid energy function and its application to modeling in inaccurate structural environments.

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Hahnbeom Park

Full Text Available Protein loop modeling is a tool for predicting protein local structures of particular interest, providing opportunities for applications involving protein structure prediction and de novo protein design. Until recently, the majority of loop modeling methods have been developed and tested by reconstructing loops in frameworks of experimentally resolved structures. In many practical applications, however, the protein loops to be modeled are located in inaccurate structural environments. These include loops in model structures, low-resolution experimental structures, or experimental structures of different functional forms. Accordingly, discrepancies in the accuracy of the structural environment assumed in development of the method and that in practical applications present additional challenges to modern loop modeling methods. This study demonstrates a new strategy for employing a hybrid energy function combining physics-based and knowledge-based components to help tackle this challenge. The hybrid energy function is designed to combine the strengths of each energy component, simultaneously maintaining accurate loop structure prediction in a high-resolution framework structure and tolerating minor environmental errors in low-resolution structures. A loop modeling method based on global optimization of this new energy function is tested on loop targets situated in different levels of environmental errors, ranging from experimental structures to structures perturbed in backbone as well as side chains and template-based model structures. The new method performs comparably to force field-based approaches in loop reconstruction in crystal structures and better in loop prediction in inaccurate framework structures. This result suggests that higher-accuracy predictions would be possible for a broader range of applications. The web server for this method is available at http://galaxy.seoklab.org/loop with the PS2 option for the scoring function.

Protein Simulation Data in the Relational Model.

Science.gov (United States)

Simms, Andrew M; Daggett, Valerie

2012-10-01

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

Denatured state is critical in determining the properties of model proteins designed on different folds

DEFF Research Database (Denmark)

Amatori, Andrea; Ferkinghoff-Borg, Jesper; Tiana, Guido

2008-01-01

The thermodynamics of proteins designed on three common folds (SH3, chymotrypsin inhibitor 2 [CI2], and protein G) is studied with a simplified C alpha, model and compared with the thermodynamics of proteins designed on random-generated folds. The model allows to design sequences to fold within a...

A study of quality measures for protein threading models

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Rychlewski Leszek

2001-08-01

Full Text Available Abstract Background Prediction of protein structures is one of the fundamental challenges in biology today. To fully understand how well different prediction methods perform, it is necessary to use measures that evaluate their performance. Every two years, starting in 1994, the CASP (Critical Assessment of protein Structure Prediction process has been organized to evaluate the ability of different predictors to blindly predict the structure of proteins. To capture different features of the models, several measures have been developed during the CASP processes. However, these measures have not been examined in detail before. In an attempt to develop fully automatic measures that can be used in CASP, as well as in other type of benchmarking experiments, we have compared twenty-one measures. These measures include the measures used in CASP3 and CASP2 as well as have measures introduced later. We have studied their ability to distinguish between the better and worse models submitted to CASP3 and the correlation between them. Results Using a small set of 1340 models for 23 different targets we show that most methods correlate with each other. Most pairs of measures show a correlation coefficient of about 0.5. The correlation is slightly higher for measures of similar types. We found that a significant problem when developing automatic measures is how to deal with proteins of different length. Also the comparisons between different measures is complicated as many measures are dependent on the size of the target. We show that the manual assessment can be reproduced to about 70% using automatic measures. Alignment independent measures, detects slightly more of the models with the correct fold, while alignment dependent measures agree better when selecting the best models for each target. Finally we show that using automatic measures would, to a large extent, reproduce the assessors ranking of the predictors at CASP3. Conclusions We show that given a

A rapid and cost-effective fluorescence detection in tube (FDIT) method to analyze protein phosphorylation.

Science.gov (United States)

Jin, Xiao; Gou, Jin-Ying

2016-01-01

Protein phosphorylation is one of the most important post-translational modifications catalyzed by protein kinases in living organisms. The advance of genome sequencing provided the information of protein kinase families in many organisms, including both model and non-model plants. The development of proteomics technologies also enabled scientists to efficiently reveal a large number of protein phosphorylations of an organism. However, kinases and phosphorylation targets are still to be connected to illustrate the complicated network in life. Here we adapted Pro-Q ® Diamond (Pro-Q ® Diamond Phosphoprotein Gel Stain), a widely used phosphoprotein gel-staining fluorescence dye, to establish a rapid, economical and non-radioactive fluorescence detection in tube (FDIT) method to analyze phosphorylated proteins. Taking advantages of high sensitivity and specificity of Pro-Q ® diamond, the FDIT method is also demonstrated to be rapid and reliable, with a suitable linear range for in vitro protein phosphorylation. A significant and satisfactory protein kinase reaction was detected as fast as 15 min from Wheat Kinase START 1.1 (WKS1.1) on a thylakoid ascorbate peroxidase (tAPX), an established phosphorylation target in our earlier study. The FDIT method saves up to 95% of the dye consumed in a gel staining method. The FDIT method is remarkably quick, highly reproducible, unambiguous and capable to be scaled up to dozens of samples. The FDIT method could serve as a simple and sensitive alternative procedure to determine protein kinase reactions with zero radiation exposure, as a supplementation to other widely used radioactive and in-gel assays.

A rapid and cost-effective fluorescence detection in tube (FDIT method to analyze protein phosphorylation

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Xiao Jin

2016-11-01

Full Text Available Abstract Background Protein phosphorylation is one of the most important post-translational modifications catalyzed by protein kinases in living organisms. The advance of genome sequencing provided the information of protein kinase families in many organisms, including both model and non-model plants. The development of proteomics technologies also enabled scientists to efficiently reveal a large number of protein phosphorylations of an organism. However, kinases and phosphorylation targets are still to be connected to illustrate the complicated network in life. Results Here we adapted Pro-Q® Diamond (Pro-Q® Diamond Phosphoprotein Gel Stain, a widely used phosphoprotein gel-staining fluorescence dye, to establish a rapid, economical and non-radioactive fluorescence detection in tube (FDIT method to analyze phosphorylated proteins. Taking advantages of high sensitivity and specificity of Pro-Q® diamond, the FDIT method is also demonstrated to be rapid and reliable, with a suitable linear range for in vitro protein phosphorylation. A significant and satisfactory protein kinase reaction was detected as fast as 15 min from Wheat Kinase START 1.1 (WKS1.1 on a thylakoid ascorbate peroxidase (tAPX, an established phosphorylation target in our earlier study. Conclusion The FDIT method saves up to 95% of the dye consumed in a gel staining method. The FDIT method is remarkably quick, highly reproducible, unambiguous and capable to be scaled up to dozens of samples. The FDIT method could serve as a simple and sensitive alternative procedure to determine protein kinase reactions with zero radiation exposure, as a supplementation to other widely used radioactive and in-gel assays.

Structure Based Thermostability Prediction Models for Protein Single Point Mutations with Machine Learning Tools.

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Lei Jia

Full Text Available Thermostability issue of protein point mutations is a common occurrence in protein engineering. An application which predicts the thermostability of mutants can be helpful for guiding decision making process in protein design via mutagenesis. An in silico point mutation scanning method is frequently used to find "hot spots" in proteins for focused mutagenesis. ProTherm (http://gibk26.bio.kyutech.ac.jp/jouhou/Protherm/protherm.html is a public database that consists of thousands of protein mutants' experimentally measured thermostability. Two data sets based on two differently measured thermostability properties of protein single point mutations, namely the unfolding free energy change (ddG and melting temperature change (dTm were obtained from this database. Folding free energy change calculation from Rosetta, structural information of the point mutations as well as amino acid physical properties were obtained for building thermostability prediction models with informatics modeling tools. Five supervised machine learning methods (support vector machine, random forests, artificial neural network, naïve Bayes classifier, K nearest neighbor and partial least squares regression are used for building the prediction models. Binary and ternary classifications as well as regression models were built and evaluated. Data set redundancy and balancing, the reverse mutations technique, feature selection, and comparison to other published methods were discussed. Rosetta calculated folding free energy change ranked as the most influential features in all prediction models. Other descriptors also made significant contributions to increasing the accuracy of the prediction models.

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

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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/.

The Ising model for prediction of disordered residues from protein sequence alone

International Nuclear Information System (INIS)

Lobanov, Michail Yu; Galzitskaya, Oxana V

2011-01-01

Intrinsically disordered regions serve as molecular recognition elements, which play an important role in the control of many cellular processes and signaling pathways. It is useful to be able to predict positions of disordered residues and disordered regions in protein chains using protein sequence alone. A new method (IsUnstruct) based on the Ising model for prediction of disordered residues from protein sequence alone has been developed. According to this model, each residue can be in one of two states: ordered or disordered. The model is an approximation of the Ising model in which the interaction term between neighbors has been replaced by a penalty for changing between states (the energy of border). The IsUnstruct has been compared with other available methods and found to perform well. The method correctly finds 77% of disordered residues as well as 87% of ordered residues in the CASP8 database, and 72% of disordered residues as well as 85% of ordered residues in the DisProt database

The ModFOLD4 server for the quality assessment of 3D protein models

OpenAIRE

McGuffin, Liam J.; Buenavista, Maria T.; Roche, Daniel B.

2013-01-01

Once you have generated a 3D model of a protein,\\ud how do you know whether it bears any resemblance\\ud to the actual structure? To determine the usefulness\\ud of 3D models of proteins, they must be assessed in\\ud terms of their quality by methods that predict their\\ud similarity to the native structure. The ModFOLD4\\ud server is the latest version of our leading independent\\ud server for the estimation of both the global and\\ud local (per-residue) quality of 3D protein models. The\\ud server ...

A Review on Recent Advances in Stabilizing Peptides/Proteins upon Fabrication in Hydrogels from Biodegradable Polymers

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Faisal Raza

2018-01-01

Full Text Available Hydrogels evolved as an outstanding carrier material for local and controlled drug delivery that tend to overcome the shortcomings of old conventional dosage forms for small drugs (NSAIDS and large peptides and proteins. The aqueous swellable and crosslinked polymeric network structure of hydrogels is composed of various natural, synthetic and semisynthetic biodegradable polymers. Hydrogels have remarkable properties of functionality, reversibility, sterilizability, and biocompatibility. All these dynamic properties of hydrogels have increased the interest in their use as a carrier for peptides and proteins to be released slowly in a sustained manner. Peptide and proteins are remarkable therapeutic agents in today’s world that allow the treatment of severe, chronic and life-threatening diseases, such as diabetes, rheumatoid arthritis, hepatitis. Despite few limitations, hydrogels provide fine tuning of proteins and peptides delivery with enormous impact in clinical medicine. Novels drug delivery systems composed of smart peptides and molecules have the ability to drive self-assembly and form hydrogels at physiological pH. These hydrogels are significantly important for biological and medical fields. The primary objective of this article is to review current issues concerned with the therapeutic peptides and proteins and impact of remarkable properties of hydrogels on these therapeutic agents. Different routes for pharmaceutical peptides and proteins and superiority over other drugs candidates are presented. Recent advances based on various approaches like self-assembly of peptides and small molecules to form novel hydrogels are also discussed. The article will also review the literature concerning the classification of hydrogels on a different basis, polymers used, “release mechanisms” their physical and chemical characteristics and diverse applications.

Exact protein distributions for stochastic models of gene expression using partitioning of Poisson processes.

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Pendar, Hodjat; Platini, Thierry; Kulkarni, Rahul V

2013-04-01

Stochasticity in gene expression gives rise to fluctuations in protein levels across a population of genetically identical cells. Such fluctuations can lead to phenotypic variation in clonal populations; hence, there is considerable interest in quantifying noise in gene expression using stochastic models. However, obtaining exact analytical results for protein distributions has been an intractable task for all but the simplest models. Here, we invoke the partitioning property of Poisson processes to develop a mapping that significantly simplifies the analysis of stochastic models of gene expression. The mapping leads to exact protein distributions using results for mRNA distributions in models with promoter-based regulation. Using this approach, we derive exact analytical results for steady-state and time-dependent distributions for the basic two-stage model of gene expression. Furthermore, we show how the mapping leads to exact protein distributions for extensions of the basic model that include the effects of posttranscriptional and posttranslational regulation. The approach developed in this work is widely applicable and can contribute to a quantitative understanding of stochasticity in gene expression and its regulation.

Exact protein distributions for stochastic models of gene expression using partitioning of Poisson processes

Science.gov (United States)

Pendar, Hodjat; Platini, Thierry; Kulkarni, Rahul V.

2013-04-01

Stochasticity in gene expression gives rise to fluctuations in protein levels across a population of genetically identical cells. Such fluctuations can lead to phenotypic variation in clonal populations; hence, there is considerable interest in quantifying noise in gene expression using stochastic models. However, obtaining exact analytical results for protein distributions has been an intractable task for all but the simplest models. Here, we invoke the partitioning property of Poisson processes to develop a mapping that significantly simplifies the analysis of stochastic models of gene expression. The mapping leads to exact protein distributions using results for mRNA distributions in models with promoter-based regulation. Using this approach, we derive exact analytical results for steady-state and time-dependent distributions for the basic two-stage model of gene expression. Furthermore, we show how the mapping leads to exact protein distributions for extensions of the basic model that include the effects of posttranscriptional and posttranslational regulation. The approach developed in this work is widely applicable and can contribute to a quantitative understanding of stochasticity in gene expression and its regulation.

A 3D model of the membrane protein complex formed by the white spot syndrome virus structural proteins.

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Yun-Shiang Chang

Full Text Available BACKGROUND: Outbreaks of white spot disease have had a large negative economic impact on cultured shrimp worldwide. However, the pathogenesis of the causative virus, WSSV (whit spot syndrome virus, is not yet well understood. WSSV is a large enveloped virus. The WSSV virion has three structural layers surrounding its core DNA: an outer envelope, a tegument and a nucleocapsid. In this study, we investigated the protein-protein interactions of the major WSSV structural proteins, including several envelope and tegument proteins that are known to be involved in the infection process. PRINCIPAL FINDINGS: In the present report, we used coimmunoprecipitation and yeast two-hybrid assays to elucidate and/or confirm all the interactions that occur among the WSSV structural (envelope and tegument proteins VP51A, VP19, VP24, VP26 and VP28. We found that VP51A interacted directly not only with VP26 but also with VP19 and VP24. VP51A, VP19 and VP24 were also shown to have an affinity for self-interaction. Chemical cross-linking assays showed that these three self-interacting proteins could occur as dimers. CONCLUSIONS: From our present results in conjunction with other previously established interactions we construct a 3D model in which VP24 acts as a core protein that directly associates with VP26, VP28, VP38A, VP51A and WSV010 to form a membrane-associated protein complex. VP19 and VP37 are attached to this complex via association with VP51A and VP28, respectively. Through the VP26-VP51C interaction this envelope complex is anchored to the nucleocapsid, which is made of layers of rings formed by VP664. A 3D model of the nucleocapsid and the surrounding outer membrane is presented.

Remarks on the low value obtained for the Hubble constant

International Nuclear Information System (INIS)

Jaakkola, Toivo

1975-01-01

Some remarks are made on the basis of the data given by Sandage and Tamman, suggesting that these authors have over-estimated the distances to the most luminous galaxies and obtained a value too low for the Hubble constant [fr

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

Science.gov (United States)

Dasgupta, Anushka

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

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.

Formulation of probabilistic models of protein structure in atomic detail using the reference ratio method

DEFF Research Database (Denmark)

Valentin, Jan B.; Andreetta, Christian; Boomsma, Wouter

2014-01-01

We propose a method to formulate probabilistic models of protein structure in atomic detail, for a given amino acid sequence, based on Bayesian principles, while retaining a close link to physics. We start from two previously developed probabilistic models of protein structure on a local length s....... The results indicate that the proposed method and the probabilistic models show considerable promise for probabilistic protein structure prediction and related applications. © 2013 Wiley Periodicals, Inc....

Bioengineered protein-based nanocage for drug delivery.

Science.gov (United States)

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

2016-11-15

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

The unfolded protein response has a protective role in yeast models of classic galactosemia

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Evandro A. De-Souza

2014-01-01

Full Text Available Classic galactosemia is a human autosomal recessive disorder caused by mutations in the GALT gene (GAL7 in yeast, which encodes the enzyme galactose-1-phosphate uridyltransferase. Here we show that the unfolded protein response pathway is triggered by galactose in two yeast models of galactosemia: lithium-treated cells and the gal7Δ mutant. The synthesis of galactose-1-phosphate is essential to trigger the unfolded protein response under these conditions because the deletion of the galactokinase-encoding gene GAL1 completely abolishes unfolded protein response activation and galactose toxicity. Impairment of the unfolded protein response in both yeast models makes cells even more sensitive to galactose, unmasking its cytotoxic effect. These results indicate that endoplasmic reticulum stress is induced under galactosemic conditions and underscores the importance of the unfolded protein response pathway to cellular adaptation in these models of classic galactosemia.

Spectroscopic and asteroseismic analysis of the remarkable main-sequence A star KIC 11145123

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Takada-Hidai, Masahide; Kurtz, Donald W.; Shibahashi, Hiromoto; Murphy, Simon J.; Takata, Masao; Saio, Hideyuki; Sekii, Takashi

2017-10-01

A spectroscopic analysis was carried out to clarify the properties of KIC 11145123 - the first main-sequence star with a directly measured core-to-surface rotation profile - based on spectra observed with the High Dispersion Spectrograph (HDS) of the Subaru telescope. The atmospheric parameters (Teff = 7600 K, log g = 4.2, ξ = 3.1 km s-1 and [Fe/H] = -0.71 dex), the radial and rotation velocities, and elemental abundances were obtained by analysing line strengths and fitting line profiles, which were calculated with a 1D LTE model atmosphere. The main properties of KIC 11145123 are: (1) a low [Fe/H] = -0.71 ± 0.11 dex and a high radial velocity of -135.4 ± 0.2 km s-1. These are remarkable among late-A stars. Our best asteroseismic models with this low [Fe/H] have slightly high helium abundance and low masses of 1.4 M⊙. All of these results strongly suggest that KIC 11145123 is a Population II blue straggler; (2) the projected rotation velocity confirms the asteroseismically predicted slow rotation of the star; (3) comparisons of abundance patterns between KIC 11145123 and Am, Ap, and blue stragglers show that KIC 11145123 is neither an Am star nor an Ap star, but has abundances consistent with a blue straggler. We conclude that the remarkably long 100-d rotation period of this star is a consequence of it being a blue straggler, but both pathways for the formation of blue stragglers - merger and mass loss in a binary system - pose difficulties for our understanding of the exceedingly slow rotation. In particular, we show that there is no evidence of any secondary companion star, and we put stringent limits on the possible mass of any such purported companion through the phase modulation technique.

Prions: Beyond a Single Protein

Science.gov (United States)

Das, Alvin S.

2016-01-01

SUMMARY Since the term protein was first coined in 1838 and protein was discovered to be the essential component of fibrin and albumin, all cellular proteins were presumed to play beneficial roles in plants and mammals. However, in 1967, Griffith proposed that proteins could be infectious pathogens and postulated their involvement in scrapie, a universally fatal transmissible spongiform encephalopathy in goats and sheep. Nevertheless, this novel hypothesis had not been evidenced until 1982, when Prusiner and coworkers purified infectious particles from scrapie-infected hamster brains and demonstrated that they consisted of a specific protein that he called a “prion.” Unprecedentedly, the infectious prion pathogen is actually derived from its endogenous cellular form in the central nervous system. Unlike other infectious agents, such as bacteria, viruses, and fungi, prions do not contain genetic materials such as DNA or RNA. The unique traits and genetic information of prions are believed to be encoded within the conformational structure and posttranslational modifications of the proteins. Remarkably, prion-like behavior has been recently observed in other cellular proteins—not only in pathogenic roles but also serving physiological functions. The significance of these fascinating developments in prion biology is far beyond the scope of a single cellular protein and its related disease. PMID:27226089

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.

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

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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.

A Minimalistic Resource Allocation Model to Explain Ubiquitous Increase in Protein Expression with Growth Rate.

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Uri Barenholz

Full Text Available Most proteins show changes in level across growth conditions. Many of these changes seem to be coordinated with the specific growth rate rather than the growth environment or the protein function. Although cellular growth rates, gene expression levels and gene regulation have been at the center of biological research for decades, there are only a few models giving a base line prediction of the dependence of the proteome fraction occupied by a gene with the specific growth rate. We present a simple model that predicts a widely coordinated increase in the fraction of many proteins out of the proteome, proportionally with the growth rate. The model reveals how passive redistribution of resources, due to active regulation of only a few proteins, can have proteome wide effects that are quantitatively predictable. Our model provides a potential explanation for why and how such a coordinated response of a large fraction of the proteome to the specific growth rate arises under different environmental conditions. The simplicity of our model can also be useful by serving as a baseline null hypothesis in the search for active regulation. We exemplify the usage of the model by analyzing the relationship between growth rate and proteome composition for the model microorganism E.coli as reflected in recent proteomics data sets spanning various growth conditions. We find that the fraction out of the proteome of a large number of proteins, and from different cellular processes, increases proportionally with the growth rate. Notably, ribosomal proteins, which have been previously reported to increase in fraction with growth rate, are only a small part of this group of proteins. We suggest that, although the fractions of many proteins change with the growth rate, such changes may be partially driven by a global effect, not necessarily requiring specific cellular control mechanisms.

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.

Understanding ensemble protein folding at atomic detail

International Nuclear Information System (INIS)

Wallin, Stefan; Shakhnovich, Eugene I

2008-01-01

Although far from routine, simulating the folding of specific short protein chains on the computer, at a detailed atomic level, is starting to become a reality. This remarkable progress, which has been made over the last decade or so, allows a fundamental aspect of the protein folding process to be addressed, namely its statistical nature. In order to make quantitative comparisons with experimental kinetic data a complete ensemble view of folding must be achieved, with key observables averaged over the large number of microscopically different folding trajectories available to a protein chain. Here we review recent advances in atomic-level protein folding simulations and the new insight provided by them into the protein folding process. An important element in understanding ensemble folding kinetics are methods for analyzing many separate folding trajectories, and we discuss techniques developed to condense the large amount of information contained in an ensemble of trajectories into a manageable picture of the folding process. (topical review)

Formulation of probabilistic models of protein structure in atomic detail using the reference ratio method.

Science.gov (United States)

Valentin, Jan B; Andreetta, Christian; Boomsma, Wouter; Bottaro, Sandro; Ferkinghoff-Borg, Jesper; Frellsen, Jes; Mardia, Kanti V; Tian, Pengfei; Hamelryck, Thomas

2014-02-01

We propose a method to formulate probabilistic models of protein structure in atomic detail, for a given amino acid sequence, based on Bayesian principles, while retaining a close link to physics. We start from two previously developed probabilistic models of protein structure on a local length scale, which concern the dihedral angles in main chain and side chains, respectively. Conceptually, this constitutes a probabilistic and continuous alternative to the use of discrete fragment and rotamer libraries. The local model is combined with a nonlocal model that involves a small number of energy terms according to a physical force field, and some information on the overall secondary structure content. In this initial study we focus on the formulation of the joint model and the evaluation of the use of an energy vector as a descriptor of a protein's nonlocal structure; hence, we derive the parameters of the nonlocal model from the native structure without loss of generality. The local and nonlocal models are combined using the reference ratio method, which is a well-justified probabilistic construction. For evaluation, we use the resulting joint models to predict the structure of four proteins. The results indicate that the proposed method and the probabilistic models show considerable promise for probabilistic protein structure prediction and related applications. Copyright © 2013 Wiley Periodicals, Inc.

Fragment-based modelling of single stranded RNA bound to RNA recognition motif containing proteins

Science.gov (United States)

de Beauchene, Isaure Chauvot; de Vries, Sjoerd J.; Zacharias, Martin

2016-01-01

Abstract Protein-RNA complexes are important for many biological processes. However, structural modeling of such complexes is hampered by the high flexibility of RNA. Particularly challenging is the docking of single-stranded RNA (ssRNA). We have developed a fragment-based approach to model the structure of ssRNA bound to a protein, based on only the protein structure, the RNA sequence and conserved contacts. The conformational diversity of each RNA fragment is sampled by an exhaustive library of trinucleotides extracted from all known experimental protein–RNA complexes. The method was applied to ssRNA with up to 12 nucleotides which bind to dimers of the RNA recognition motifs (RRMs), a highly abundant eukaryotic RNA-binding domain. The fragment based docking allows a precise de novo atomic modeling of protein-bound ssRNA chains. On a benchmark of seven experimental ssRNA–RRM complexes, near-native models (with a mean heavy-atom deviation of <3 Å from experiment) were generated for six out of seven bound RNA chains, and even more precise models (deviation < 2 Å) were obtained for five out of seven cases, a significant improvement compared to the state of the art. The method is not restricted to RRMs but was also successfully applied to Pumilio RNA binding proteins. PMID:27131381

The interaction between endogenous 30S ribosomal subunit protein S11 and Cucumber mosaic virus LS2b protein affects viral replication, infection and gene silencing suppressor activity.

Directory of Open Access Journals (Sweden)

Ruilin Wang

Full Text Available Cucumber mosaic virus (CMV is a model virus for plant-virus protein interaction and mechanism research because of its wide distribution, high-level of replication and simple genome structure. The 2b protein is a multifunctional protein encoded by CMV that suppresses RNA silencing-based antiviral defense and contributes to CMV virulence in host plants. In this report, 12 host proteins were identified as CMV LS2b binding partners using the yeast two-hybrid screen system from the Arabidopsis thaliana cDNA library. Among the host proteins, 30S ribosomal subunit protein S11 (RPS11 was selected for further studies. The interaction between LS2b and full-length RPS11 was confirmed using the yeast two-hybrid system. Bimolecular fluorescence complementation (BIFC assays observed by confocal laser microscopy and Glutathione S-transferase (GST pull-down assays were used to verify the interaction between endogenous NbRPS11 and viral CMVLS2b both in vivo and in vitro. TRV-based gene silencing vector was used to knockdown NbRPS11 transcription, and immunoblot analysis revealed a decline in infectious viral RNA replication and a decrease in CMV infection in RPS11 down-regulated Nicotiana benthamiana plants. Thus, the knockdown of RPS11 likely inhibited CMV replication and accumulation. The gene silencing suppressor activity of CMV2b protein was reduced by the RPS11 knockdown. This study demonstrated that the function of viral LS2b protein was remarkably affected by the interaction with host RPS11 protein.

Modeling the time evolution of the nanoparticle-protein corona in a body fluid.

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Daniele Dell'Orco

Full Text Available BACKGROUND: Nanoparticles in contact with biological fluids interact with proteins and other biomolecules, thus forming a dynamic corona whose composition varies over time due to continuous protein association and dissociation events. Eventually equilibrium is reached, at which point the continued exchange will not affect the composition of the corona. RESULTS: We developed a simple and effective dynamic model of the nanoparticle protein corona in a body fluid, namely human plasma. The model predicts the time evolution and equilibrium composition of the corona based on affinities, stoichiometries and rate constants. An application to the interaction of human serum albumin, high density lipoprotein (HDL and fibrinogen with 70 nm N-iso-propylacrylamide/N-tert-butylacrylamide copolymer nanoparticles is presented, including novel experimental data for HDL. CONCLUSIONS: The simple model presented here can easily be modified to mimic the interaction of the nanoparticle protein corona with a novel biological fluid or compartment once new data will be available, thus opening novel applications in nanotoxicity and nanomedicine.

Discussant Remarks on Session: Statistical Aspects of Measuring the Internet

Energy Technology Data Exchange (ETDEWEB)

Cottrell, Les

1999-04-02

These remarks will briefly summarize what we learn from the talks in this session, and add some more areas in Internet Measurement that may provide challenges for statisticians. It will also point out some reasons why statisticians may be interested in working in this area.

Some remarks on word formation in Danish

DEFF Research Database (Denmark)

Götzsche, Hans

Abstract for the 25th Scandinavian Conference of Linguistics Some remarks on wordformation in Danish Some Danish word formation phenomena pose a problem for the linguist, being a predicament for analysis. In Danish a train leaves the station when it afgår ‘leaves’, while a minister may gå af......, there are some patterns for these Danish compounds concerning their internal semantics, in that the same lexical items may be used for different purposes depending on whether they are formed as a straightforward linear sequence (a word formation) or a reversed sequence (a phrase). The problem is (i) how the two...

Interaction of sucralose with whey protein: Experimental and molecular modeling studies

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Zhang, Hongmei; Sun, Shixin; Wang, Yanqing; Cao, Jian

2017-12-01

The objective of this research was to study the interactions of sucralose with whey protein isolate (WPI) by using the three-dimensional fluorescence spectroscopy, circular dichroism spectroscopy and molecular modeling. The results showed that the peptide strands structure of WPI had been changed by sucralose. Sucralose binding induced the secondary structural changes and increased content of aperiodic structure of WPI. Sucralose decreased the thermal stability of WPI and acted as a structure destabilizer during the thermal unfolding process of protein. In addition, the existence of sucralose decreased the reversibility of the unfolding of WPI. Nonetheless, sucralose-WPI complex was less stable than protein alone. The molecular modeling result showed that van der Waals and hydrogen bonding interactions contribute to the complexation free binding energy. There are more than one possible binding sites of WPI with sucralose by surface binding mode.

Remarks on ''Neutrino masses and mixing angles in a predictive theory of fermion masses''

International Nuclear Information System (INIS)

Lavoura, L.; Silva, J.P.

1994-01-01

In the extension of the Dimopoulos-Hall-Raby model of the fermion mass matrices to the neutrino sector, there is an entry in the up-quark and neutrino Dirac mass matrices which can be assumed to arise from the Yukawa coupling of a 120, instead of a 10 or a 126, of SO(10). Although this assumption leads to an extra undetermined complex parameter in the model, the resulting lepton mixing matrix exhibits the remarkable feature that the ν τ does not mix with the other two neutrinos. Making a reasonable assumption about the extra parameter, we are able to fit the large-mixing-angle MSW solution of the solar-neutrino problem, and we obtain m ντ ∼10 eV, the right mass range to close the Universe. Other possibilities for explaining the solar-neutrino deficit are also discussed

Remarkable heterogeneity displayed by oval cells in rat and mouse models of stem cell-mediated liver regeneration

DEFF Research Database (Denmark)

Jelnes, Peter; Santoni-Rugiu, Eric; Rasmussen, Morten

2007-01-01

The experimental protocols used in the investigation of stem cell-mediated liver regeneration in rodents are characterized by activation of the hepatic stem cell compartment in the canals of Hering followed by transit amplification of oval cells and their subsequent differentiation along hepatic...... the molecular phenotypes of oval cells in several of the most commonly used protocols of stem cell-mediated liver regeneration-namely, treatment with 2-acetylaminofluorene and partial (70%) hepatectomy (AAF/PHx); a choline-deficient, ethionine-supplemented (CDE) diet; a 3,5-diethoxycarbonyl-1,4-dihydro...... remarkable phenotypic discrepancies exhibited by oval cells in stem cell-mediated liver regeneration between rats and mice and underline the importance of careful extrapolation between individual species....

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

Science.gov (United States)

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.

Dynamic protein assembly by programmable DNA strand displacement

Science.gov (United States)

Chen, Rebecca P.; Blackstock, Daniel; Sun, Qing; Chen, Wilfred

2018-03-01

Inspired by the remarkable ability of natural protein switches to sense and respond to a wide range of environmental queues, here we report a strategy to engineer synthetic protein switches by using DNA strand displacement to dynamically organize proteins with highly diverse and complex logic gate architectures. We show that DNA strand displacement can be used to dynamically control the spatial proximity and the corresponding fluorescence resonance energy transfer between two fluorescent proteins. Performing Boolean logic operations enabled the explicit control of protein proximity using multi-input, reversible and amplification architectures. We further demonstrate the power of this technology beyond sensing by achieving dynamic control of an enzyme cascade. Finally, we establish the utility of the approach as a synthetic computing platform that drives the dynamic reconstitution of a split enzyme for targeted prodrug activation based on the sensing of cancer-specific miRNAs.

Integrating atomistic molecular dynamics simulations, experiments and network analysis to study protein dynamics: strength in unity

Directory of Open Access Journals (Sweden)

Elena ePapaleo

2015-05-01

Full Text Available In the last years, we have been observing remarkable improvements in the field of protein dynamics. Indeed, we can now study protein dynamics in atomistic details over several timescales with a rich portfolio of experimental and computational techniques. On one side, this provides us with the possibility to validate simulation methods and physical models against a broad range of experimental observables. On the other side, it also allows a complementary and comprehensive view on protein structure and dynamics. What is needed now is a better understanding of the link between the dynamic properties that we observe and the functional properties of these important cellular machines. To make progresses in this direction, we need to improve the physical models used to describe proteins and solvent in molecular dynamics, as well as to strengthen the integration of experiments and simulations to overcome their own limitations. Moreover, now that we have the means to study protein dynamics in great details, we need new tools to understand the information embedded in the protein ensembles and in their dynamic signature. With this aim in mind, we should enrich the current tools for analysis of biomolecular simulations with attention to the effects that can be propagated over long distances and are often associated to important biological functions. In this context, approaches inspired by network analysis can make an important contribution to the analysis of molecular dynamics simulations.

Feature-Based and String-Based Models for Predicting RNA-Protein Interaction

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Donald Adjeroh

2018-03-01

Full Text Available In this work, we study two approaches for the problem of RNA-Protein Interaction (RPI. In the first approach, we use a feature-based technique by combining extracted features from both sequences and secondary structures. The feature-based approach enhanced the prediction accuracy as it included much more available information about the RNA-protein pairs. In the second approach, we apply search algorithms and data structures to extract effective string patterns for prediction of RPI, using both sequence information (protein and RNA sequences, and structure information (protein and RNA secondary structures. This led to different string-based models for predicting interacting RNA-protein pairs. We show results that demonstrate the effectiveness of the proposed approaches, including comparative results against leading state-of-the-art methods.

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

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

2015-12-07

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

Protein secondary structure prediction for a single-sequence using hidden semi-Markov models

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Borodovsky Mark

2006-03-01

Full Text Available Abstract Background The accuracy of protein secondary structure prediction has been improving steadily towards the 88% estimated theoretical limit. There are two types of prediction algorithms: Single-sequence prediction algorithms imply that information about other (homologous proteins is not available, while algorithms of the second type imply that information about homologous proteins is available, and use it intensively. The single-sequence algorithms could make an important contribution to studies of proteins with no detected homologs, however the accuracy of protein secondary structure prediction from a single-sequence is not as high as when the additional evolutionary information is present. Results In this paper, we further refine and extend the hidden semi-Markov model (HSMM initially considered in the BSPSS algorithm. We introduce an improved residue dependency model by considering the patterns of statistically significant amino acid correlation at structural segment borders. We also derive models that specialize on different sections of the dependency structure and incorporate them into HSMM. In addition, we implement an iterative training method to refine estimates of HSMM parameters. The three-state-per-residue accuracy and other accuracy measures of the new method, IPSSP, are shown to be comparable or better than ones for BSPSS as well as for PSIPRED, tested under the single-sequence condition. Conclusions We have shown that new dependency models and training methods bring further improvements to single-sequence protein secondary structure prediction. The results are obtained under cross-validation conditions using a dataset with no pair of sequences having significant sequence similarity. As new sequences are added to the database it is possible to augment the dependency structure and obtain even higher accuracy. Current and future advances should contribute to the improvement of function prediction for orphan proteins inscrutable

Remarkable optical red shift and extremely high optical absorption coefficient of V-Ga co-doped TiO2

Science.gov (United States)

Deng, Quanrong; Han, Xiaoping; Gao, Yun; Shao, Guosheng

2012-07-01

A first attempt has been made to study the effect of codoping of transition metal and sp metal on the electronic structure and associated optical properties of TiO2, through V-Ga codoped thin films. V-Ga codoped rutile TiO2 films were fabricated on fused quartz substrates using pulsed laser ablation, followed by heat treatment at high temperatures. Gigantic redshift in the optical absorption edge was observed in V-Ga co-doped TiO2 materials, from UV to infrared region with high absorption coefficient. Through combined structural characterization and theoretical modeling, this is attributed to the p-d hybridization between the two metals. This leads to additional energy bands to overlap with the minimum of the conduction band, leading to remarkably narrowed band gap free of mid-gap states. The direct-gap of the co-doped phase is key to the remarkably high optical absorption coefficient of the coped titania.

Systematic identification of yeast proteins extracted into model wine during aging on the yeast lees.

Science.gov (United States)

Rowe, Jeffrey D; Harbertson, James F; Osborne, James P; Freitag, Michael; Lim, Juyun; Bakalinsky, Alan T

2010-02-24

Total protein and protein-associated mannan concentrations were measured, and individual proteins were identified during extraction into model wines over 9 months of aging on the yeast lees following completion of fermentations by seven wine strains of Saccharomyces cerevisiae. In aged wines, protein-associated mannan increased about 6-fold (+/-66%), while total protein only increased 2-fold (+/-20%), which resulted in a significantly greater protein-associated mannan/total protein ratio for three strains. A total of 219 proteins were identified among all wine samples taken over the entire time course. Of the 17 "long-lived" proteins detected in all 9 month samples, 13 were cell wall mannoproteins, and four were glycolytic enzymes. Most cytosolic proteins were not detected after 6 months. Native mannosylated yeast invertase was assayed for binding to wine tannin and was found to have a 10-fold lower affinity than nonglycosylated bovine serum albumin. Enrichment of mannoproteins in the aged model wines implies greater solution stability than other yeast proteins and the possibility that their contributions to wine quality may persist long after bottling.

Plant Proteins Are Smaller Because They Are Encoded by Fewer Exons than Animal Proteins.

Science.gov (United States)

Ramírez-Sánchez, Obed; Pérez-Rodríguez, Paulino; Delaye, Luis; Tiessen, Axel

2016-12-01

Protein size is an important biochemical feature since longer proteins can harbor more domains and therefore can display more biological functionalities than shorter proteins. We found remarkable differences in protein length, exon structure, and domain count among different phylogenetic lineages. While eukaryotic proteins have an average size of 472 amino acid residues (aa), average protein sizes in plant genomes are smaller than those of animals and fungi. Proteins unique to plants are ∼81aa shorter than plant proteins conserved among other eukaryotic lineages. The smaller average size of plant proteins could neither be explained by endosymbiosis nor subcellular compartmentation nor exon size, but rather due to exon number. Metazoan proteins are encoded on average by ∼10 exons of small size [∼176 nucleotides (nt)]. Streptophyta have on average only ∼5.7 exons of medium size (∼230nt). Multicellular species code for large proteins by increasing the exon number, while most unicellular organisms employ rather larger exons (>400nt). Among subcellular compartments, membrane proteins are the largest (∼520aa), whereas the smallest proteins correspond to the gene ontology group of ribosome (∼240aa). Plant genes are encoded by half the number of exons and also contain fewer domains than animal proteins on average. Interestingly, endosymbiotic proteins that migrated to the plant nucleus became larger than their cyanobacterial orthologs. We thus conclude that plants have proteins larger than bacteria but smaller than animals or fungi. Compared to the average of eukaryotic species, plants have ∼34% more but ∼20% smaller proteins. This suggests that photosynthetic organisms are unique and deserve therefore special attention with regard to the evolutionary forces acting on their genomes and proteomes. Copyright © 2016 The Authors. Production and hosting by Elsevier Ltd.. All rights reserved.

Plant Proteins Are Smaller Because They Are Encoded by Fewer Exons than Animal Proteins

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Obed Ramírez-Sánchez

2016-12-01

Full Text Available Protein size is an important biochemical feature since longer proteins can harbor more domains and therefore can display more biological functionalities than shorter proteins. We found remarkable differences in protein length, exon structure, and domain count among different phylogenetic lineages. While eukaryotic proteins have an average size of 472 amino acid residues (aa, average protein sizes in plant genomes are smaller than those of animals and fungi. Proteins unique to plants are ∼81 aa shorter than plant proteins conserved among other eukaryotic lineages. The smaller average size of plant proteins could neither be explained by endosymbiosis nor subcellular compartmentation nor exon size, but rather due to exon number. Metazoan proteins are encoded on average by ∼10 exons of small size [∼176 nucleotides (nt]. Streptophyta have on average only ∼5.7 exons of medium size (∼230 nt. Multicellular species code for large proteins by increasing the exon number, while most unicellular organisms employ rather larger exons (>400 nt. Among subcellular compartments, membrane proteins are the largest (∼520 aa, whereas the smallest proteins correspond to the gene ontology group of ribosome (∼240 aa. Plant genes are encoded by half the number of exons and also contain fewer domains than animal proteins on average. Interestingly, endosymbiotic proteins that migrated to the plant nucleus became larger than their cyanobacterial orthologs. We thus conclude that plants have proteins larger than bacteria but smaller than animals or fungi. Compared to the average of eukaryotic species, plants have ∼34% more but ∼20% smaller proteins. This suggests that photosynthetic organisms are unique and deserve therefore special attention with regard to the evolutionary forces acting on their genomes and proteomes.

Selective Advantage of Recombination in Evolving Protein Populations:. a Lattice Model Study

Science.gov (United States)

Williams, Paul D.; Pollock, David D.; Goldstein, Richard A.

Recent research has attempted to clarify the contributions of several mutational processes, such as substitutions or homologous recombination. Simplistic, tractable protein models, which determine the compact native structure phenotype from the sequence genotype, are well-suited to such studies. In this paper, we use a lattice-protein model to examine the effects of point mutation and homologous recombination on evolving populations of proteins. We find that while the majority of mutation and recombination events are neutral or deleterious, recombination is far more likely to be beneficial. This results in a faster increase in fitness during evolution, although the final fitness level is not significantly changed. This transient advantage provides an evolutionary advantage to subpopulations that undergo recombination, allowing fixation of recombination to occur in the population.

Mathematical modeling and comparison of protein size distribution in different plant, animal, fungal and microbial species reveals a negative correlation between protein size and protein number, thus providing insight into the evolution of proteomes

Directory of Open Access Journals (Sweden)

Tiessen Axel

2012-02-01

Full Text Available Abstract Background The sizes of proteins are relevant to their biochemical structure and for their biological function. The statistical distribution of protein lengths across a diverse set of taxa can provide hints about the evolution of proteomes. Results Using the full genomic sequences of over 1,302 prokaryotic and 140 eukaryotic species two datasets containing 1.2 and 6.1 million proteins were generated and analyzed statistically. The lengthwise distribution of proteins can be roughly described with a gamma type or log-normal model, depending on the species. However the shape parameter of the gamma model has not a fixed value of 2, as previously suggested, but varies between 1.5 and 3 in different species. A gamma model with unrestricted shape parameter described best the distributions in ~48% of the species, whereas the log-normal distribution described better the observed protein sizes in 42% of the species. The gamma restricted function and the sum of exponentials distribution had a better fitting in only ~5% of the species. Eukaryotic proteins have an average size of 472 aa, whereas bacterial (320 aa and archaeal (283 aa proteins are significantly smaller (33-40% on average. Average protein sizes in different phylogenetic groups were: Alveolata (628 aa, Amoebozoa (533 aa, Fornicata (543 aa, Placozoa (453 aa, Eumetazoa (486 aa, Fungi (487 aa, Stramenopila (486 aa, Viridiplantae (392 aa. Amino acid composition is biased according to protein size. Protein length correlated negatively with %C, %M, %K, %F, %R, %W, %Y and positively with %D, %E, %Q, %S and %T. Prokaryotic proteins had a different protein size bias for %E, %G, %K and %M as compared to eukaryotes. Conclusions Mathematical modeling of protein length empirical distributions can be used to asses the quality of small ORFs annotation in genomic releases (detection of too many false positive small ORFs. There is a negative correlation between average protein size and total number of

Protein dynamics revealed in the excitonic spectra of single LH2 complexes

International Nuclear Information System (INIS)

Valkunas, Leonas; Janusonis, Julius; Rutkauskas, Danielis; Grondelle, Rienk van

2007-01-01

The fluorescence emission spectrum of single peripheral light-harvesting (LH2) complexes of the photosynthetic purple bacterium Rhodopseudomonas acidophila exhibits remarkable dynamics on a time scale of several minutes. Often the spectral properties are quasi-stable; sometimes large spectral jumps to the blue or to the red are observed. To explain the dynamics, every pigment is proposed to be in two conformational substates with different excitation energies, which originate from the conformational state of the protein as a result of pigment-protein interaction. Due to the excitonic coupling in the ring of 18 pigments, the two-state assumption generates a substantial amount of distinct spectroscopic states, which reflect part of the inhomogeneous distributed spectral properties of LH2. To describe the observed dynamics, spontaneous and light-induced transitions are introduced between the two states. For each 'realization of the disorder', the spectral properties are calculated using a disordered exciton model combined with the modified Redfield theory to obtain realistic spectral line shapes. The single-molecule fluorescence peak (FLP) distribution, the distribution dependence on the excitation intensity, and the FLP time traces are well described within the framework of this model

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

Modeling of the structure of ribosomal protein L1 from the archaeon Haloarcula marismortui

Science.gov (United States)

Nevskaya, N. A.; Kljashtorny, V. G.; Vakhrusheva, A. V.; Garber, M. B.; Nikonov, S. V.

2017-07-01

The halophilic archaeon Haloarcula marismortui proliferates in the Dead Sea at extremely high salt concentrations (higher than 3 M). This is the only archaeon, for which the crystal structure of the ribosomal 50S subunit was determined. However, the structure of the functionally important side protuberance containing the abnormally negatively charged protein L1 (HmaL1) was not visualized. Attempts to crystallize HmaL1 in the isolated state or as its complex with RNA using normal salt concentrations (≤500 mM) failed. A theoretical model of HmaL1 was built based on the structural data for homologs of the protein L1 from other organisms, and this model was refined by molecular dynamics methods. Analysis of this model showed that the protein HmaL1 can undergo aggregation due to the presence of a cluster of positive charges unique for proteins L1. This cluster is located at the RNA-protein interface, which interferes with the crystallization of HmaL1 and the binding of the latter to RNA.

Sculpting proteins interactively: continual energy minimization embedded in a graphical modeling system.

Science.gov (United States)

Surles, M C; Richardson, J S; Richardson, D C; Brooks, F P

1994-02-01

We describe a new paradigm for modeling proteins in interactive computer graphics systems--continual maintenance of a physically valid representation, combined with direct user control and visualization. This is achieved by a fast algorithm for energy minimization, capable of real-time performance on all atoms of a small protein, plus graphically specified user tugs. The modeling system, called Sculpt, rigidly constrains bond lengths, bond angles, and planar groups (similar to existing interactive modeling programs), while it applies elastic restraints to minimize the potential energy due to torsions, hydrogen bonds, and van der Waals and electrostatic interactions (similar to existing batch minimization programs), and user-specified springs. The graphical interface can show bad and/or favorable contacts, and individual energy terms can be turned on or off to determine their effects and interactions. Sculpt finds a local minimum of the total energy that satisfies all the constraints using an augmented Lagrange-multiplier method; calculation time increases only linearly with the number of atoms because the matrix of constraint gradients is sparse and banded. On a 100-MHz MIPS R4000 processor (Silicon Graphics Indigo), Sculpt achieves 11 updates per second on a 20-residue fragment and 2 updates per second on an 80-residue protein, using all atoms except non-H-bonding hydrogens, and without electrostatic interactions. Applications of Sculpt are described: to reverse the direction of bundle packing in a designed 4-helix bundle protein, to fold up a 2-stranded beta-ribbon into an approximate beta-barrel, and to design the sequence and conformation of a 30-residue peptide that mimics one partner of a protein subunit interaction. Computer models that are both interactive and physically realistic (within the limitations of a given force field) have 2 significant advantages: (1) they make feasible the modeling of very large changes (such as needed for de novo design), and

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

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

DEFF Research Database (Denmark)

Irani, Zahra Azimzadeh; Kerkhoven, Eduard J.; Shojaosadati, Seyed Abbas

2016-01-01

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....

Structural characterisation of medically relevant protein assemblies by integrating mass spectrometry with computational modelling.

Science.gov (United States)

Politis, Argyris; Schmidt, Carla

2018-03-20

Structural mass spectrometry with its various techniques is a powerful tool for the structural elucidation of medically relevant protein assemblies. It delivers information on the composition, stoichiometries, interactions and topologies of these assemblies. Most importantly it can deal with heterogeneous mixtures and assemblies which makes it universal among the conventional structural techniques. In this review we summarise recent advances and challenges in structural mass spectrometric techniques. We describe how the combination of the different mass spectrometry-based methods with computational strategies enable structural models at molecular levels of resolution. These models hold significant potential for helping us in characterizing the function of protein assemblies related to human health and disease. In this review we summarise the techniques of structural mass spectrometry often applied when studying protein-ligand complexes. We exemplify these techniques through recent examples from literature that helped in the understanding of medically relevant protein assemblies. We further provide a detailed introduction into various computational approaches that can be integrated with these mass spectrometric techniques. Last but not least we discuss case studies that integrated mass spectrometry and computational modelling approaches and yielded models of medically important protein assembly states such as fibrils and amyloids. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Terahertz radiation generation by lasers with remarkable efficiency in electron–positron plasma

International Nuclear Information System (INIS)

Malik, Hitendra K.

2015-01-01

Photo-mixing of spatial-super-Gaussian lasers and electron–positron plasma are proposed for realizing a large amplitude nonlinear current in order to generate an efficient terahertz radiation. An external magnetic field together with a proper index of the lasers helps achieving controllable current and hence, the focused radiation of tunable frequency and power along with a remarkable efficiency of the scheme as ∼6%. - Highlights: • First proposal of photo-mixing of spatial-super-Gaussian (SSG) lasers in electron–positron (e–p) plasma. • Large amplitude nonlinear current due to the contribution of both the plasma species. • Magnetic field as an additional parameter for tunable THz radiation with a remarkable efficiency of ∼6%.

Comparing side chain packing in soluble proteins, protein-protein interfaces, and transmembrane proteins.

Science.gov (United States)

Gaines, J C; Acebes, S; Virrueta, A; Butler, M; Regan, L; O'Hern, C S

2018-05-01

We compare side chain prediction and packing of core and non-core regions of soluble proteins, protein-protein interfaces, and transmembrane proteins. We first identified or created comparable databases of high-resolution crystal structures of these 3 protein classes. We show that the solvent-inaccessible cores of the 3 classes of proteins are equally densely packed. As a result, the side chains of core residues at protein-protein interfaces and in the membrane-exposed regions of transmembrane proteins can be predicted by the hard-sphere plus stereochemical constraint model with the same high prediction accuracies (>90%) as core residues in soluble proteins. We also find that for all 3 classes of proteins, as one moves away from the solvent-inaccessible core, the packing fraction decreases as the solvent accessibility increases. However, the side chain predictability remains high (80% within 30°) up to a relative solvent accessibility, rSASA≲0.3, for all 3 protein classes. Our results show that ≈40% of the interface regions in protein complexes are "core", that is, densely packed with side chain conformations that can be accurately predicted using the hard-sphere model. We propose packing fraction as a metric that can be used to distinguish real protein-protein interactions from designed, non-binding, decoys. Our results also show that cores of membrane proteins are the same as cores of soluble proteins. Thus, the computational methods we are developing for the analysis of the effect of hydrophobic core mutations in soluble proteins will be equally applicable to analyses of mutations in membrane proteins. © 2018 Wiley Periodicals, Inc.

Radiation induced changes in plasma total protein nitrogen and urinary total nitrogen in desert rodent and albino rats subjected to dietary protein deficiency

International Nuclear Information System (INIS)

Roushdy, H.; El-Husseini, M.; Saleh, F.

1986-01-01

The effect of gamma-irradiation on plasma total protein nitrogen and urinary total nitrogen was studied in the desert rodent, psammomy obesus obesus and albino rats subjected to dietary protein deficiency. In albino rats kept on high protein diet, the radiation syndrome resulted in urine retention, while in those kept on non-protein diet, such phenomenon was recorded only with the high radiation level of 1170r. Radiation exposure to 780 and 1170r caused remarkable diuresis in psammomys obesus obesus whereas they induced significant urine retention in albino rats. The levels of plasma total protein nitrogen and urinary total nitrogen were higher in albino rats maintained on high protein diet than in those kept on non-protein diet. Radiation exposure caused an initial drop in plasma total protein nitrogen concentration, concomitant with an initial rise in total urinary nitrogen, radiation exposure of psammomys obesus obesus caused significant increase in the levels of plasma protein nitrogen and urinary total nitrogen. Psammomys obesus obesus seemed to be more affected by radiation exposure than did the albino rats

Remarks on Hamiltonian structures in G2-geometry

International Nuclear Information System (INIS)

Cho, Hyunjoo; Salur, Sema; Todd, A. J.

2013-01-01

In this article, we treat G 2 -geometry as a special case of multisymplectic geometry and make a number of remarks regarding Hamiltonian multivector fields and Hamiltonian differential forms on manifolds with an integrable G 2 -structure; in particular, we discuss existence and make a number of identifications of the spaces of Hamiltonian structures associated to the two multisymplectic structures associated to an integrable G 2 -structure. Along the way, we prove some results in multisymplectic geometry that are generalizations of results from symplectic geometry

Maillard-reaction-induced modification and aggregation of proteins and hardening of texture in protein bar model systems.

Science.gov (United States)

Zhou, Peng; Guo, Mufan; Liu, Dasong; Liu, Xiaoming; Labuza, Teodore P

2013-03-01

The hardening of high-protein bars causes problems in their acceptability to consumers. The objective of this study was to determine the progress of the Maillard reaction in model systems of high-protein nutritional bars containing reducing sugars, and to illustrate the influences of the Maillard reaction on the modification and aggregation of proteins and the hardening of bar matrices during storage. The progress of the Maillard reaction, glycation, and aggregation of proteins, and textural changes in bar matrices were investigated during storage at 25, 35, and 45 °C. The initial development of the Maillard reaction caused little changes in hardness; however, further storage resulted in dramatic modification of protein with formation of high-molecular-weight polymers, resulting in the hardening in texture. The replacement of reducing sugars with nonreducing ingredients such as sugar alcohols in the formula minimized the changes in texture. The hardening of high-protein bars causes problems in their acceptability to consumers. Maillard reaction is one of the mechanisms contributing to the hardening of bar matrix, particularly for the late stage of storage. The replacement of reducing sugars with nonreducing ingredients such as sugar alcohols in the formula will minimize the changes in texture. © 2013 Institute of Food Technologists®

Remarkable separability of circulation response to Arctic sea ice loss and greenhouse gas forcing

Science.gov (United States)

McCusker, K. E.; Kushner, P. J.; Fyfe, J. C.; Sigmond, M.; Kharin, V. V.; Bitz, C. M.

2017-08-01

Arctic sea ice loss may influence midlatitude climate by changing large-scale circulation. The extent to which climate change can be understood as greenhouse gas-induced changes that are modulated by this loss depends on how additive the responses to the separate influences are. A novel sea ice nudging methodology in a fully coupled climate model reveals that the separate effects of doubled atmospheric carbon dioxide (CO2) concentrations and associated Arctic sea ice loss are remarkably additive and insensitive to the mean climate state. This separability is evident in several fields throughout most of the year, from hemispheric to synoptic scales. The extent to which the regional response to sea ice loss sometimes agrees with and sometimes cancels the response to CO2 is quantified. The separability of the responses might provide a means to better interpret the diverse array of modeling and observational studies of Arctic change and influence.

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

Directory of Open Access Journals (Sweden)

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.

Looping and clustering model for the organization of protein-DNA complexes on the bacterial genome

Science.gov (United States)

Walter, Jean-Charles; Walliser, Nils-Ole; David, Gabriel; Dorignac, Jérôme; Geniet, Frédéric; Palmeri, John; Parmeggiani, Andrea; Wingreen, Ned S.; Broedersz, Chase P.

2018-03-01

The bacterial genome is organized by a variety of associated proteins inside a structure called the nucleoid. These proteins can form complexes on DNA that play a central role in various biological processes, including chromosome segregation. A prominent example is the large ParB-DNA complex, which forms an essential component of the segregation machinery in many bacteria. ChIP-Seq experiments show that ParB proteins localize around centromere-like parS sites on the DNA to which ParB binds specifically, and spreads from there over large sections of the chromosome. Recent theoretical and experimental studies suggest that DNA-bound ParB proteins can interact with each other to condense into a coherent 3D complex on the DNA. However, the structural organization of this protein-DNA complex remains unclear, and a predictive quantitative theory for the distribution of ParB proteins on DNA is lacking. Here, we propose the looping and clustering model, which employs a statistical physics approach to describe protein-DNA complexes. The looping and clustering model accounts for the extrusion of DNA loops from a cluster of interacting DNA-bound proteins that is organized around a single high-affinity binding site. Conceptually, the structure of the protein-DNA complex is determined by a competition between attractive protein interactions and loop closure entropy of this protein-DNA cluster on the one hand, and the positional entropy for placing loops within the cluster on the other. Indeed, we show that the protein interaction strength determines the ‘tightness’ of the loopy protein-DNA complex. Thus, our model provides a theoretical framework for quantitatively computing the binding profiles of ParB-like proteins around a cognate (parS) binding site.

Classification of Beta-lactamases and penicillin binding proteins using ligand-centric network models.

Directory of Open Access Journals (Sweden)

Hakime Öztürk

Full Text Available β-lactamase mediated antibiotic resistance is an important health issue and the discovery of new β-lactam type antibiotics or β-lactamase inhibitors is an area of intense research. Today, there are about a thousand β-lactamases due to the evolutionary pressure exerted by these ligands. While β-lactamases hydrolyse the β-lactam ring of antibiotics, rendering them ineffective, Penicillin-Binding Proteins (PBPs, which share high structural similarity with β-lactamases, also confer antibiotic resistance to their host organism by acquiring mutations that allow them to continue their participation in cell wall biosynthesis. In this paper, we propose a novel approach to include ligand sharing information for classifying and clustering β-lactamases and PBPs in an effort to elucidate the ligand induced evolution of these β-lactam binding proteins. We first present a detailed summary of the β-lactamase and PBP families in the Protein Data Bank, as well as the compounds they bind to. Then, we build two different types of networks in which the proteins are represented as nodes, and two proteins are connected by an edge with a weight that depends on the number of shared identical or similar ligands. These models are analyzed under three different edge weight settings, namely unweighted, weighted, and normalized weighted. A detailed comparison of these six networks showed that the use of ligand sharing information to cluster proteins resulted in modules comprising proteins with not only sequence similarity but also functional similarity. Consideration of ligand similarity highlighted some interactions that were not detected in the identical ligand network. Analysing the β-lactamases and PBPs using ligand-centric network models enabled the identification of novel relationships, suggesting that these models can be used to examine other protein families to obtain information on their ligand induced evolutionary paths.

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 subcellular localization prediction using artificial intelligence technology.

Science.gov (United States)

Nair, Rajesh; Rost, Burkhard

2008-01-01

Proteins perform many important tasks in living organisms, such as catalysis of biochemical reactions, transport of nutrients, and recognition and transmission of signals. The plethora of aspects of the role of any particular protein is referred to as its "function." One aspect of protein function that has been the target of intensive research by computational biologists is its subcellular localization. Proteins must be localized in the same subcellular compartment to cooperate toward a common physiological function. Aberrant subcellular localization of proteins can result in several diseases, including kidney stones, cancer, and Alzheimer's disease. To date, sequence homology remains the most widely used method for inferring the function of a protein. However, the application of advanced artificial intelligence (AI)-based techniques in recent years has resulted in significant improvements in our ability to predict the subcellular localization of a protein. The prediction accuracy has risen steadily over the years, in large part due to the application of AI-based methods such as hidden Markov models (HMMs), neural networks (NNs), and support vector machines (SVMs), although the availability of larger experimental datasets has also played a role. Automatic methods that mine textual information from the biological literature and molecular biology databases have considerably sped up the process of annotation for proteins for which some information regarding function is available in the literature. State-of-the-art methods based on NNs and HMMs can predict the presence of N-terminal sorting signals extremely accurately. Ab initio methods that predict subcellular localization for any protein sequence using only the native amino acid sequence and features predicted from the native sequence have shown the most remarkable improvements. The prediction accuracy of these methods has increased by over 30% in the past decade. The accuracy of these methods is now on par with

Equivalence of hyperfractionated and continuous brachytherapy in a rat tumor model and remarkable effectiveness when preceded by external irradiation

International Nuclear Information System (INIS)

Veninga, Theo; Visser, Andries G.; Berg, Ad P. van den; Hooije, Christel van; Geel, Cornelis A.J.F. van; Levendag, Peter C.

2001-01-01

Purpose: In clinical brachytherapy, there is a tendency to replace continuous low-dose-rate (LDR) irradiation by either single-dose or fractionated high-dose-rate (HDR) irradiation. In this study, the equivalence of LDR treatments and fractionated HDR (2 fractions/day) or pulsed-dose-rate (PDR, 4 fractions/day) schedules in terms of tumor cure was investigated in an experimental tumor model. Methods and Materials: Tumors (rat rhabdomyosarcoma R1M) were grown s.c. in the flank of rats and implanted with 4 catheters guided by a template. All interstitial radiation treatment (IRT) schedules were given in the same geometry. HDR was given using an 192 Ir single-stepping source. To investigate small fraction sizes, part of the fractionated HDR and PDR schedules were applied after an external irradiation (ERT) top-up dose. The endpoint was the probability of tumor control at 150 days after treatment. Cell survival was estimated by excision assay. Results: Although there was no fractionation effect for fractionated HDR given in 1 or 2 fractions per day, TCD 50 -values were substantially lower than that for LDR. A PDR schedule with an interfraction interval of 3 h (4 fractions/day), however, was equivalent to LDR. The combination of ERT and IRT resulted in a remarkably increased tumor control probability in all top-up regimens, but no difference was found between 2 or 4 fractions/day. Catheter implantation alone decreased the TCD 50 for single-dose ERT already by 17.4 Gy. Cell viability assessed at 24 h after treatment demonstrated an increased effectiveness of interstitial treatment, but, after 10 Gy ERT followed by 10 Gy IRT (24-h interval), it was not less than that calculated for the combined effect of these treatments given separately. Conclusion: In full fractionation schedules employing large fractions and long intervals, the sparing effect of sublethal damage repair may be significantly counteracted by reoxygenation. During 3-h intervals, however, repair may be

Evolving Transcription Factor Binding Site Models From Protein Binding Microarray Data

KAUST Repository

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

2016-01-01

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. In this paper, we describe the PBM motif model building problem. We apply several evolutionary computation methods and compare their performance with the interior point method, demonstrating their performance advantages. In addition, given the PBM domain knowledge, we propose and describe a novel method called kmerGA which makes domain-specific assumptions to exploit PBM data properties to build more accurate models than the other models built. The effectiveness and robustness of kmerGA is supported by comprehensive performance benchmarking on more than 200 datasets, time complexity analysis, convergence analysis, parameter analysis, and case studies. To demonstrate its utility further, kmerGA is applied to two real world applications: 1) PBM rotation testing and 2) ChIP-Seq peak sequence prediction. The results support the biological relevance of the models learned by kmerGA, and thus its real world applicability.

Evolving Transcription Factor Binding Site Models From Protein Binding Microarray Data

KAUST Repository

Wong, Ka-Chun

2016-02-02

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. In this paper, we describe the PBM motif model building problem. We apply several evolutionary computation methods and compare their performance with the interior point method, demonstrating their performance advantages. In addition, given the PBM domain knowledge, we propose and describe a novel method called kmerGA which makes domain-specific assumptions to exploit PBM data properties to build more accurate models than the other models built. The effectiveness and robustness of kmerGA is supported by comprehensive performance benchmarking on more than 200 datasets, time complexity analysis, convergence analysis, parameter analysis, and case studies. To demonstrate its utility further, kmerGA is applied to two real world applications: 1) PBM rotation testing and 2) ChIP-Seq peak sequence prediction. The results support the biological relevance of the models learned by kmerGA, and thus its real world applicability.

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.

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.

Connecting protein and mRNA burst distributions for stochastic models of gene expression

International Nuclear Information System (INIS)

Elgart, Vlad; Jia, Tao; Fenley, Andrew T; Kulkarni, Rahul

2011-01-01

The intrinsic stochasticity of gene expression can lead to large variability in protein levels for genetically identical cells. Such variability in protein levels can arise from infrequent synthesis of mRNAs which in turn give rise to bursts of protein expression. Protein expression occurring in bursts has indeed been observed experimentally and recent studies have also found evidence for transcriptional bursting, i.e. production of mRNAs in bursts. Given that there are distinct experimental techniques for quantifying the noise at different stages of gene expression, it is of interest to derive analytical results connecting experimental observations at different levels. In this work, we consider stochastic models of gene expression for which mRNA and protein production occurs in independent bursts. For such models, we derive analytical expressions connecting protein and mRNA burst distributions which show how the functional form of the mRNA burst distribution can be inferred from the protein burst distribution. Additionally, if gene expression is repressed such that observed protein bursts arise only from single mRNAs, we show how observations of protein burst distributions (repressed and unrepressed) can be used to completely determine the mRNA burst distribution. Assuming independent contributions from individual bursts, we derive analytical expressions connecting means and variances for burst and steady-state protein distributions. Finally, we validate our general analytical results by considering a specific reaction scheme involving regulation of protein bursts by small RNAs. For a range of parameters, we derive analytical expressions for regulated protein distributions that are validated using stochastic simulations. The analytical results obtained in this work can thus serve as useful inputs for a broad range of studies focusing on stochasticity in gene expression

Experimental strategies for the identification and characterization of adhesive proteins in animals: a review

Science.gov (United States)

Hennebert, Elise; Maldonado, Barbara; Ladurner, Peter; Flammang, Patrick; Santos, Romana

2015-01-01

Adhesive secretions occur in both aquatic and terrestrial animals, in which they perform diverse functions. Biological adhesives can therefore be remarkably complex and involve a large range of components with different functions and interactions. However, being mainly protein based, biological adhesives can be characterized by classical molecular methods. This review compiles experimental strategies that were successfully used to identify, characterize and obtain the full-length sequence of adhesive proteins from nine biological models: echinoderms, barnacles, tubeworms, mussels, sticklebacks, slugs, velvet worms, spiders and ticks. A brief description and practical examples are given for a variety of tools used to study adhesive molecules at different levels from genes to secreted proteins. In most studies, proteins, extracted from secreted materials or from adhesive organs, are analysed for the presence of post-translational modifications and submitted to peptide sequencing. The peptide sequences are then used directly for a BLAST search in genomic or transcriptomic databases, or to design degenerate primers to perform RT-PCR, both allowing the recovery of the sequence of the cDNA coding for the investigated protein. These sequences can then be used for functional validation and recombinant production. In recent years, the dual proteomic and transcriptomic approach has emerged as the best way leading to the identification of novel adhesive proteins and retrieval of their complete sequences. PMID:25657842

APOLLO: a quality assessment service for single and multiple protein models.

Science.gov (United States)

Wang, Zheng; Eickholt, Jesse; Cheng, Jianlin

2011-06-15

We built a web server named APOLLO, which can evaluate the absolute global and local qualities of a single protein model using machine learning methods or the global and local qualities of a pool of models using a pair-wise comparison approach. Based on our evaluations on 107 CASP9 (Critical Assessment of Techniques for Protein Structure Prediction) targets, the predicted quality scores generated from our machine learning and pair-wise methods have an average per-target correlation of 0.671 and 0.917, respectively, with the true model quality scores. Based on our test on 92 CASP9 targets, our predicted absolute local qualities have an average difference of 2.60 Å with the actual distances to native structure. http://sysbio.rnet.missouri.edu/apollo/. Single and pair-wise global quality assessment software is also available at the site.

Insulin as a model to teach three-dimensional structure of proteins

Directory of Open Access Journals (Sweden)

João Batista Teixeira da Rocha

2018-02-01

Proteins are the most ubiquitous macromolecules found in the living cells and have innumerous physiological functions. Therefore, it is fundamental to build a solid knowledge about the proteins three dimensional structure to better understand the living state. The hierarchical structure of proteins is usually studied in the undergraduate discipline of Biochemistry. Here we described pedagogical interventions designed to increase the preservice teacher chemistry students’ knowledge about protein structure. The activities were made using alternative and cheap materials to encourage the application of these simple methodologies by the future teachers in the secondary school. From the primary structure of insulin chains, students had to construct a three-dimensional structure of insulin. After the activities, the students highlighted an improvement of their previous knowledge about proteins structure. The construction of a tridimensional model together with other activities seems to be an efficient way to promote the learning about the structure of proteins to undergraduate students. The methodology used was inexpensiveness and simple and it can be used both in the university and in the high-school.

Nationwide Genomic Study in Denmark Reveals Remarkable Population Homogeneity.

Science.gov (United States)

Athanasiadis, Georgios; Cheng, Jade Y; Vilhjálmsson, Bjarni J; Jørgensen, Frank G; Als, Thomas D; Le Hellard, Stephanie; Espeseth, Thomas; Sullivan, Patrick F; Hultman, Christina M; Kjærgaard, Peter C; Schierup, Mikkel H; Mailund, Thomas

2016-10-01

Denmark has played a substantial role in the history of Northern Europe. Through a nationwide scientific outreach initiative, we collected genetic and anthropometrical data from ∼800 high school students and used them to elucidate the genetic makeup of the Danish population, as well as to assess polygenic predictions of phenotypic traits in adolescents. We observed remarkable homogeneity across different geographic regions, although we could still detect weak signals of genetic structure reflecting the history of the country. Denmark presented genomic affinity with primarily neighboring countries with overall resemblance of decreasing weight from Britain, Sweden, Norway, Germany, and France. A Polish admixture signal was detected in Zealand and Funen, and our date estimates coincided with historical evidence of Wend settlements in the south of Denmark. We also observed considerably diverse demographic histories among Scandinavian countries, with Denmark having the smallest current effective population size compared to Norway and Sweden. Finally, we found that polygenic prediction of self-reported adolescent height in the population was remarkably accurate (R 2 = 0.639 ± 0.015). The high homogeneity of the Danish population could render population structure a lesser concern for the upcoming large-scale gene-mapping studies in the country. Copyright © 2016 by the Genetics Society of America.

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.

Domain analyses of Usher syndrome causing Clarin-1 and GPR98 protein models.

Science.gov (United States)

Khan, Sehrish Haider; Javed, Muhammad Rizwan; Qasim, Muhammad; Shahzadi, Samar; Jalil, Asma; Rehman, Shahid Ur

2014-01-01

Usher syndrome is an autosomal recessive disorder that causes hearing loss, Retinitis Pigmentosa (RP) and vestibular dysfunction. It is clinically and genetically heterogeneous disorder which is clinically divided into three types i.e. type I, type II and type III. To date, there are about twelve loci and ten identified genes which are associated with Usher syndrome. A mutation in any of these genes e.g. CDH23, CLRN1, GPR98, MYO7A, PCDH15, USH1C, USH1G, USH2A and DFNB31 can result in Usher syndrome or non-syndromic deafness. These genes provide instructions for making proteins that play important roles in normal hearing, balance and vision. Studies have shown that protein structures of only seven genes have been determined experimentally and there are still three genes whose structures are unavailable. These genes are Clarin-1, GPR98 and Usherin. In the absence of an experimentally determined structure, homology modeling and threading often provide a useful 3D model of a protein. Therefore in the current study Clarin-1 and GPR98 proteins have been analyzed for signal peptide, domains and motifs. Clarin-1 protein was found to be without any signal peptide and consists of prokar lipoprotein domain. Clarin-1 is classified within claudin 2 super family and consists of twelve motifs. Whereas, GPR98 has a 29 amino acids long signal peptide and classified within GPCR family 2 having Concanavalin A-like lectin/glucanase superfamily. It was found to be consists of GPS and G protein receptor F2 domains and twenty nine motifs. Their 3D structures have been predicted using I-TASSER server. The model of Clarin-1 showed only α-helix but no beta sheets while model of GPR98 showed both α-helix and β sheets. The predicted structures were then evaluated and validated by MolProbity and Ramachandran plot. The evaluation of the predicted structures showed 78.9% residues of Clarin-1 and 78.9% residues of GPR98 within favored regions. The findings of present study has resulted in the

Remarks on the thermopreferendum of palearctic bats in their natural habitats

NARCIS (Netherlands)

Gaisler, Jiří

1970-01-01

This contribution comprises two remarks of ecological rather than physiological character. Contrary to Herter (1952), Herreid (1967), and Harmata (1969), I did not examine the temperature preference, or thermopreferendum, of bats under experimental conditions but concluded on it only on grounds of

Nanobody Technology: A Versatile Toolkit for Microscopic Imaging, Protein–Protein Interaction Analysis, and Protein Function Exploration

Directory of Open Access Journals (Sweden)

Els Beghein

2017-07-01

Full Text Available Over the last two decades, nanobodies or single-domain antibodies have found their way in research, diagnostics, and therapy. These antigen-binding fragments, derived from Camelid heavy chain only antibodies, possess remarkable characteristics that favor their use over conventional antibodies or fragments thereof, in selected areas of research. In this review, we assess the current status of nanobodies as research tools in diverse aspects of fundamental research. We discuss the use of nanobodies as detection reagents in fluorescence microscopy and focus on recent advances in super-resolution microscopy. Second, application of nanobody technology in investigating protein–protein interactions is reviewed, with emphasis on possible uses in mass spectrometry. Finally, we discuss the potential value of nanobodies in studying protein function, and we focus on their recently reported application in targeted protein degradation. Throughout the review, we highlight state-of-the-art engineering strategies that could expand nanobody versatility and we suggest future applications of the technology in the selected areas of fundamental research.

Nanobody Technology: A Versatile Toolkit for Microscopic Imaging, Protein–Protein Interaction Analysis, and Protein Function Exploration

Science.gov (United States)

Beghein, Els; Gettemans, Jan

2017-01-01

Over the last two decades, nanobodies or single-domain antibodies have found their way in research, diagnostics, and therapy. These antigen-binding fragments, derived from Camelid heavy chain only antibodies, possess remarkable characteristics that favor their use over conventional antibodies or fragments thereof, in selected areas of research. In this review, we assess the current status of nanobodies as research tools in diverse aspects of fundamental research. We discuss the use of nanobodies as detection reagents in fluorescence microscopy and focus on recent advances in super-resolution microscopy. Second, application of nanobody technology in investigating protein–protein interactions is reviewed, with emphasis on possible uses in mass spectrometry. Finally, we discuss the potential value of nanobodies in studying protein function, and we focus on their recently reported application in targeted protein degradation. Throughout the review, we highlight state-of-the-art engineering strategies that could expand nanobody versatility and we suggest future applications of the technology in the selected areas of fundamental research. PMID:28725224

Prion protein modulates glucose homeostasis by altering intracellular iron.

Science.gov (United States)

Ashok, Ajay; Singh, Neena

2018-04-26

The prion protein (PrP C ), a mainly neuronal protein, is known to modulate glucose homeostasis in mouse models. We explored the underlying mechanism in mouse models and the human pancreatic β-cell line 1.1B4. We report expression of PrP C on mouse pancreatic β-cells, where it promoted uptake of iron through divalent-metal-transporters. Accordingly, pancreatic iron stores in PrP knockout mice (PrP -/- ) were significantly lower than wild type (PrP +/+ ) controls. Silencing of PrP C in 1.1B4 cells resulted in significant depletion of intracellular (IC) iron, and remarkably, upregulation of glucose transporter GLUT2 and insulin. Iron overloading, on the other hand, resulted in downregulation of GLUT2 and insulin in a PrP C -dependent manner. Similar observations were noted in the brain, liver, and neuroretina of iron overloaded PrP +/+ but not PrP -/- mice, indicating PrP C -mediated modulation of insulin and glucose homeostasis through iron. Peripheral challenge with glucose and insulin revealed blunting of the response in iron-overloaded PrP +/+ relative to PrP -/- mice, suggesting that PrP C -mediated modulation of IC iron influences both secretion and sensitivity of peripheral organs to insulin. These observations have implications for Alzheimer's disease and diabetic retinopathy, known complications of type-2-diabetes associated with brain and ocular iron-dyshomeostasis.

An Outlook on Biothermodynamics: Needs, Problems, and New Developments. I. Stability and Hydration of Proteins

Science.gov (United States)

Keller, Jürgen U.

2008-12-01

The application of concepts, principles, and methods of thermodynamics of equilibria and processes to bioengineering systems has led to a new and growing field: engineering biothermodynamics. This article, which is meant as the first in a series, gives an outline of basic aspects, changes, and actual examples in this field. After a few introductory remarks, the basic concepts and laws of thermodynamics extended to systems with internal variables, which serve as models for biofluids and other biosystems, are given. The method of thermodynamics is then applied to the problem of thermal stability of aqueous protein solutions, especially to that of myoglobin solutions. After this, the phenomenon of hydration of proteins by adsorption and intrusion of water molecules is considered. Several other phenomena like the adsorption of proteins on solid surfaces or cell membranes and their temperature and pressure-related behavior represented by an equation of state, or the thermodynamics of bacterial solutions including chemical reactions like wine fermentation, etc., will be presented in Parts II and III of this article.

Remarkable Women in a Remarkable Age. On the Genesis of the English Public Sphere, 1642-1752

Directory of Open Access Journals (Sweden)

Eleonora Cappuccilli

2015-06-01

Full Text Available During the era of the English Revolutions and shortly after that, some spaces, albeit limited, of female visibility open up. Thanks to the window of opportunity caused by the collapse of censorship, the participation in the radical sects and in the Civil war, some remarkable women succeed in introducing themselves in the public sphere, shaping it since its very genesis. Moreover, analysing law institutions as jointure and feoffment, the attempt is to reconstruct some fragments of juridical female autonomy, which belie the total pervasiveness of coverture in the XVII century. As in private law, in public law women, in the role of queens, gain centrality: the principle of female authority, while safeguards the holding of the monarchical regime, destabilizes its patriarchal structure. Going through the works of Katherine Chidley, Margaret Cavendish, Damaris Masham and Mary Astell, the essay aims at reconstructing women's public voice, a voice which upsets the consolidated frames and subverts the established positions, questioning the same social hierarchies.

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.

Truncated forms of the prion protein PrP demonstrate the need for complexity in prion structure

Energy Technology Data Exchange (ETDEWEB)

Wan, William; Stöhr, Jan; Kendall, Amy; Stubbs, Gerald

2015-09-01

Self-propagation of aberrant protein folds is the defining characteristic of prions. Knowing the structural basis of self-propagation is essential to understanding prions and their related diseases. Prion rods are amyloid fibrils, but not all amyloids are prions. Prions have been remarkably intractable to structural studies, so many investigators have preferred to work with peptide fragments, particularly in the case of the mammalian prion protein PrP. We compared the structures of a number of fragments of PrP by X-ray fiber diffraction, and found that although all of the peptides adopted amyloid conformations, only the larger fragments adopted conformations that modeled the complexity of self-propagating prions, and even these fragments did not always adopt the PrP structure. It appears that the relatively complex structure of the prion form of PrP is not accessible to short model peptides, and that self-propagation may be tied to a level of structural complexity unobtainable in simple model systems. The larger fragments of PrP, however, are useful to illustrate the phenomenon of deformed templating (heterogeneous seeding), which has important biological consequences.

Truncated forms of the prion protein PrP demonstrate the need for complexity in prion structure.

Science.gov (United States)

Wan, William; Stöhr, Jan; Kendall, Amy; Stubbs, Gerald

2015-01-01

Self-propagation of aberrant protein folds is the defining characteristic of prions. Knowing the structural basis of self-propagation is essential to understanding prions and their related diseases. Prion rods are amyloid fibrils, but not all amyloids are prions. Prions have been remarkably intractable to structural studies, so many investigators have preferred to work with peptide fragments, particularly in the case of the mammalian prion protein PrP. We compared the structures of a number of fragments of PrP by X-ray fiber diffraction, and found that although all of the peptides adopted amyloid conformations, only the larger fragments adopted conformations that modeled the complexity of self-propagating prions, and even these fragments did not always adopt the PrP structure. It appears that the relatively complex structure of the prion form of PrP is not accessible to short model peptides, and that self-propagation may be tied to a level of structural complexity unobtainable in simple model systems. The larger fragments of PrP, however, are useful to illustrate the phenomenon of deformed templating (heterogeneous seeding), which has important biological consequences.

Gold(III) complexes with 2-substituted pyridines as experimental anticancer agents: solution behavior, reactions with model proteins, antiproliferative properties.

Science.gov (United States)

Maiore, Laura; Cinellu, Maria Agostina; Nobili, Stefania; Landini, Ida; Mini, Enrico; Gabbiani, Chiara; Messori, Luigi

2012-03-01

Gold(III) compounds form a family of promising cytotoxic and potentially anticancer agents that are currently undergoing intense preclinical investigations. Four recently synthesized and characterized gold(III) derivatives of 2-substituted pyridines are evaluated here for their biological and pharmacological behavior. These include two cationic adducts with 2-pyridinyl-oxazolines, [Au(pyox(R))Cl(2)][PF(6)], [pyox(R)=(S)-4-benzyl-2-(pyridin-2-yl)-4,5-dihydrooxazole, I; (S)-4-iso-propyl-2-(pyridin-2-yl)-4,5-dihydrooxazole, II] and two neutral complexes [Au(N,N'OH)Cl(2)], III, and [Au(N,N',O)Cl], IV, containing the deprotonated ligand N-(1-hydroxy-3-iso-propyl-2-yl)pyridine-2-carboxamide, N,N'H,OH, resulting from ring opening of bound pyox(R) ligand of complex II by hydroxide ions. The solution behavior of these compounds was analyzed. These behave as classical prodrugs: activation of the metal center typically takes place through release of the labile chloride ligands while the rest of the molecule is not altered; alternatively, activation may occur through gold(III) reduction. All compounds react eagerly with the model protein cyt c leading to extensive protein metalation. ESI MS experiments revealed details of gold-cyt c interactions and allowed us to establish the nature of protein bound metal containing fragments. The different behavior displayed by I and II compared to III and IV is highlighted. Remarkable cytotoxic properties, against the reference human ovarian carcinoma cell lines A2780/S and A2780/R were disclosed for all tested compounds with IC(50) values ranging from 1.43 to 6.18 μM in the sensitive cell line and from 1.59 to 10.86 μM in the resistant one. The common ability of these compounds to overcome cisplatin resistance is highlighted. The obtained results are thoroughly discussed in the frame of current knowledge on cytotoxic gold compounds. Copyright © 2011 Elsevier Inc. All rights reserved.

Tinkering with Translation: Protein Synthesis in Virus-Infected Cells

Science.gov (United States)

Walsh, Derek; Mathews, Michael B.; Mohr, Ian

2013-01-01

Viruses are obligate intracellular parasites, and their replication requires host cell functions. Although the size, composition, complexity, and functions encoded by their genomes are remarkably diverse, all viruses rely absolutely on the protein synthesis machinery of their host cells. Lacking their own translational apparatus, they must recruit cellular ribosomes in order to translate viral mRNAs and produce the protein products required for their replication. In addition, there are other constraints on viral protein production. Crucially, host innate defenses and stress responses capable of inactivating the translation machinery must be effectively neutralized. Furthermore, the limited coding capacity of the viral genome needs to be used optimally. These demands have resulted in complex interactions between virus and host that exploit ostensibly virus-specific mechanisms and, at the same time, illuminate the functioning of the cellular protein synthesis apparatus. PMID:23209131

Crystal structure of the Japanese encephalitis virus envelope protein.

Science.gov (United States)

Luca, Vincent C; AbiMansour, Jad; Nelson, Christopher A; Fremont, Daved H

2012-02-01

Japanese encephalitis virus (JEV) is the leading global cause of viral encephalitis. The JEV envelope protein (E) facilitates cellular attachment and membrane fusion and is the primary target of neutralizing antibodies. We have determined the 2.1-Å resolution crystal structure of the JEV E ectodomain refolded from bacterial inclusion bodies. The E protein possesses the three domains characteristic of flavivirus envelopes and epitope mapping of neutralizing antibodies onto the structure reveals determinants that correspond to the domain I lateral ridge, fusion loop, domain III lateral ridge, and domain I-II hinge. While monomeric in solution, JEV E assembles as an antiparallel dimer in the crystal lattice organized in a highly similar fashion as seen in cryo-electron microscopy models of mature flavivirus virions. The dimer interface, however, is remarkably small and lacks many of the domain II contacts observed in other flavivirus E homodimers. In addition, uniquely conserved histidines within the JEV serocomplex suggest that pH-mediated structural transitions may be aided by lateral interactions outside the dimer interface in the icosahedral virion. Our results suggest that variation in dimer structure and stability may significantly influence the assembly, receptor interaction, and uncoating of virions.

Polyphenol-enriched berry extracts naturally modulate reactive proteins in model foods.

Science.gov (United States)

Lila, Mary Ann; Schneider, Maggie; Devlin, Amy; Plundrich, Nathalie; Laster, Scott; Foegeding, E Allen

2017-12-13

Healthy foods like polyphenol-rich berries and high quality edible proteins are in demand in today's functional food marketplace, but it can be difficult to formulate convenient food products with physiologically-relevant amounts of these ingredients and still maintain product quality. In part, this is because proteins can interact with other food ingredients and precipitate destabilizing events, which can disrupt food structure and diminish shelf life. Proteins in foods can also interact with human receptors to provoke adverse consequences such as allergies. When proteins and polyphenols were pre-aggregated into stable colloidal particles prior to use as ingredients, highly palatable food formulations (with reduced astringency of polyphenols) could be prepared, and the overall structural properties of food formulations were significantly improved. All of the nutritive and phytoactive benefits of the proteins and concentrated polyphenols remained highly bioavailable, but the protein molecules in the particle matrix did not self-aggregate into networks or react with other food ingredients. Both the drainage half-life (a marker of structural stability) and the yield stress (resistance to flow) of model foams made with the protein-polyphenol particles were increased in a dose-dependent manner. Of high significance in this complexation process, the reactive allergenic epitopes of certain proteins were effectively blunted by binding with polyphenols, attenuating the allergenicity of the food proteins. Porcine macrophages produced TNF-α proinflammatory cytokine when provoked with whey protein, but, this response was blocked completely when the cells were stimulated with particles that complexed whey protein with cinnamon-derived polyphenols. Cytokine and chemokine production characteristic of allergic reactions were blocked by the polyphenols, allowing for the potential creation of hypoallergenic protein-berry polyphenol enriched foods.

PDB2Graph: A toolbox for identifying critical amino acids map in proteins based on graph theory.

Science.gov (United States)

Niknam, Niloofar; Khakzad, Hamed; Arab, Seyed Shahriar; Naderi-Manesh, Hossein

2016-05-01

The integrative and cooperative nature of protein structure involves the assessment of topological and global features of constituent parts. Network concept takes complete advantage of both of these properties in the analysis concomitantly. High compatibility to structural concepts or physicochemical properties in addition to exploiting a remarkable simplification in the system has made network an ideal tool to explore biological systems. There are numerous examples in which different protein structural and functional characteristics have been clarified by the network approach. Here, we present an interactive and user-friendly Matlab-based toolbox, PDB2Graph, devoted to protein structure network construction, visualization, and analysis. Moreover, PDB2Graph is an appropriate tool for identifying critical nodes involved in protein structural robustness and function based on centrality indices. It maps critical amino acids in protein networks and can greatly aid structural biologists in selecting proper amino acid candidates for manipulating protein structures in a more reasonable and rational manner. To introduce the capability and efficiency of PDB2Graph in detail, the structural modification of Calmodulin through allosteric binding of Ca(2+) is considered. In addition, a mutational analysis for three well-identified model proteins including Phage T4 lysozyme, Barnase and Ribonuclease HI, was performed to inspect the influence of mutating important central residues on protein activity. Copyright © 2016 Elsevier Ltd. All rights reserved.

Towards predictive resistance models for agrochemicals by combining chemical and protein similarity via proteochemometric modelling.

Science.gov (United States)

van Westen, Gerard J P; Bender, Andreas; Overington, John P

2014-10-01

Resistance to pesticides is an increasing problem in agriculture. Despite practices such as phased use and cycling of 'orthogonally resistant' agents, resistance remains a major risk to national and global food security. To combat this problem, there is a need for both new approaches for pesticide design, as well as for novel chemical entities themselves. As summarized in this opinion article, a technique termed 'proteochemometric modelling' (PCM), from the field of chemoinformatics, could aid in the quantification and prediction of resistance that acts via point mutations in the target proteins of an agent. The technique combines information from both the chemical and biological domain to generate bioactivity models across large numbers of ligands as well as protein targets. PCM has previously been validated in prospective, experimental work in the medicinal chemistry area, and it draws on the growing amount of bioactivity information available in the public domain. Here, two potential applications of proteochemometric modelling to agrochemical data are described, based on previously published examples from the medicinal chemistry literature.

On the turn-inducing properties of asparagine: the structuring role of the amide side chain, from isolated model peptides to crystallized proteins.

Science.gov (United States)

Habka, S; Sohn, W Y; Vaquero-Vara, V; Géléoc, M; Tardivel, B; Brenner, V; Gloaguen, E; Mons, M

2018-01-31

Asparagine (Asn) is a powerful turn-inducer residue, with a large propensity to occupy the second position in the central region of β-turns of proteins. The present work aims at investigating the role of a local anchoring between the Asn side chain and the main chain in this remarkable property. For this purpose, the H-bonding patterns of an asparagine residue in an isolated protein chain fragment forming a γ- or a β-turn have been determined using IR/UV double resonance gas phase spectroscopy on laser-desorbed, jet-cooled short models in conjunction with relevant quantum chemistry calculations. These gas phase data provide evidence for an original double anchoring linking the Asn primary amide side chain (SC), which adopts a gauche+ rotameric form, to its main chain (MC) local environment. From both IR spectroscopic evidence (H-bond induced red shifts) and quantum chemistry, Asn SC is found to behave as a stronger H-bond acceptor than donor, resulting in stronger MC→SC H-bonds than SC→MC ones. These gas phase structural data, relevant to a hydrophobic environment, have been used as a reference to assess the anchoring taking place in high resolution crystallized proteins of the Protein Data Bank. This approach reveals that, when the SC adopts a gauche+ orientation, the stronger MC→SC bonds are preserved in many cases whereas the SC→MC bonds are always disrupted, in qualitative agreement with the gas phase ranking of these interactions. Most interestingly, when Asn occupies the second position of central part of a β-turn (i.e., the very turn-inducer position), the MC→SC H-bonds are also disrupted and replaced by a water-mediated SC to MC anchoring. Owing to the specific features of the hydrated Asn side chain, we propose that it could be a turn precursor structure, able to facilitate turn formation in the early events of the folding process.

Exploring the Role of Conventionality in Children's Interpretation of Ironic Remarks

Science.gov (United States)

Burnett, Debra L.

2015-01-01

Irony comprehension in seven- and eight-year-old children with typically developing language skills was explored under the framework of the graded salience hypothesis. Target ironic remarks, either conventional or novel/situation-specific, were presented following brief story contexts. Children's responses to comprehension questions were used to…

Remarks of the SFRP working group about ICRP recommendations

International Nuclear Information System (INIS)

Schieber, C.; Cordoliani, Y.S.

2005-01-01

Remarks of the SFRP working group about ICRP recommendations. The International Commission on Radiological Protection has proposed last summer on its Web site the draft text of the 2005 ICRP recommendations for consultation. As it was done for the previous drafts, the French Society for Radiation Protection, has sent his comments to the ICRP, through a specific working group. The text sent to the ICRP is presented here to the readers of the SFRP's Journal. (author)

Emergence of modularity and disassortativity in protein-protein interaction networks.

Science.gov (United States)

Wan, Xi; Cai, Shuiming; Zhou, Jin; Liu, Zengrong

2010-12-01

In this paper, we present a simple evolution model of protein-protein interaction networks by introducing a rule of small-preference duplication of a node, meaning that the probability of a node chosen to duplicate is inversely proportional to its degree, and subsequent divergence plus nonuniform heterodimerization based on some plausible mechanisms in biology. We show that our model cannot only reproduce scale-free connectivity and small-world pattern, but also exhibit hierarchical modularity and disassortativity. After comparing the features of our model with those of real protein-protein interaction networks, we believe that our model can provide relevant insights into the mechanism underlying the evolution of protein-protein interaction networks. © 2010 American Institute of Physics.

The interface of protein structure, protein biophysics, and molecular evolution

Science.gov (United States)

Liberles, David A; Teichmann, Sarah A; Bahar, Ivet; Bastolla, Ugo; Bloom, Jesse; Bornberg-Bauer, Erich; Colwell, Lucy J; de Koning, A P Jason; Dokholyan, Nikolay V; Echave, Julian; Elofsson, Arne; Gerloff, Dietlind L; Goldstein, Richard A; Grahnen, Johan A; Holder, Mark T; Lakner, Clemens; Lartillot, Nicholas; Lovell, Simon C; Naylor, Gavin; Perica, Tina; Pollock, David D; Pupko, Tal; Regan, Lynne; Roger, Andrew; Rubinstein, Nimrod; Shakhnovich, Eugene; Sjölander, Kimmen; Sunyaev, Shamil; Teufel, Ashley I; Thorne, Jeffrey L; Thornton, Joseph W; Weinreich, Daniel M; Whelan, Simon

2012-01-01

Abstract The interface of protein structural biology, protein biophysics, molecular evolution, and molecular population genetics forms the foundations for a mechanistic understanding of many aspects of protein biochemistry. Current efforts in interdisciplinary protein modeling are in their infancy and the state-of-the art of such models is described. Beyond the relationship between amino acid substitution and static protein structure, protein function, and corresponding organismal fitness, other considerations are also discussed. More complex mutational processes such as insertion and deletion and domain rearrangements and even circular permutations should be evaluated. The role of intrinsically disordered proteins is still controversial, but may be increasingly important to consider. Protein geometry and protein dynamics as a deviation from static considerations of protein structure are also important. Protein expression level is known to be a major determinant of evolutionary rate and several considerations including selection at the mRNA level and the role of interaction specificity are discussed. Lastly, the relationship between modeling and needed high-throughput experimental data as well as experimental examination of protein evolution using ancestral sequence resurrection and in vitro biochemistry are presented, towards an aim of ultimately generating better models for biological inference and prediction. PMID:22528593

Insight into the intermolecular recognition mechanism between Keap1 and IKKβ combining homology modelling, protein-protein docking, molecular dynamics simulations and virtual alanine mutation.

Directory of Open Access Journals (Sweden)

Zheng-Yu Jiang

Full Text Available Degradation of certain proteins through the ubiquitin-proteasome pathway is a common strategy taken by the key modulators responsible for stress responses. Kelch-like ECH-associated protein-1(Keap1, a substrate adaptor component of the Cullin3 (Cul3-based ubiquitin E3 ligase complex, mediates the ubiquitination of two key modulators, NF-E2-related factor 2 (Nrf2 and IκB kinase β (IKKβ, which are involved in the redox control of gene transcription. However, compared to the Keap1-Nrf2 protein-protein interaction (PPI, the intermolecular recognition mechanism of Keap1 and IKKβ has been poorly investigated. In order to explore the binding pattern between Keap1 and IKKβ, the PPI model of Keap1 and IKKβ was investigated. The structure of human IKKβ was constructed by means of the homology modeling method and using reported crystal structure of Xenopus laevis IKKβ as the template. A protein-protein docking method was applied to develop the Keap1-IKKβ complex model. After the refinement and visual analysis of docked proteins, the chosen pose was further optimized through molecular dynamics simulations. The resulting structure was utilized to conduct the virtual alanine mutation for the exploration of hot-spots significant for the intermolecular interaction. Overall, our results provided structural insights into the PPI model of Keap1-IKKβ and suggest that the substrate specificity of Keap1 depend on the interaction with the key tyrosines, namely Tyr525, Tyr574 and Tyr334. The study presented in the current project may be useful to design molecules that selectively modulate Keap1. The selective recognition mechanism of Keap1 with IKKβ or Nrf2 will be helpful to further know the crosstalk between NF-κB and Nrf2 signaling.

Intrinsically disordered segments and the evolution of protein half-life

Science.gov (United States)

Babu, M.

2013-03-01

Precise turnover of proteins is essential for cellular homeostasis and is primarily mediated by the proteasome. Thus, a fundamental question is: What features make a protein an efficient substrate for degradation? Here I will present results that proteins with a long terminal disordered segment or internal disordered segments have a significantly shorter half-life in yeast. This relationship appears to be evolutionarily conserved in mouse and human. Furthermore, upon gene duplication, divergence in the length of terminal disorder or variation in the number of internal disordered segments results in significant alteration of the half-life of yeast paralogs. Many proteins that exhibit such changes participate in signaling, where altered protein half-life will likely influence their activity. We suggest that variation in the length and number of disordered segments could serve as a remarkably simple means to evolve protein half-life and may serve as an underappreciated source of genetic variation with important phenotypic consequences. MMB acknowledges the Medical Research Council for funding his research program.

Remarkable convergent evolution in specialized parasitic Thecostraca (Crustacea)

DEFF Research Database (Denmark)

Pérez-Losada, Marcos; Høeg, Jens Thorvald; Crandall, Keith A

2009-01-01

the metamorphosis found in the Facetotecta and Rhizocephala suggests a common evolutionary origin, but until now no comprehensive study has looked at the basic evolution of these thecostracan groups. Results To this end, we collected DNA sequences from three nuclear genes [18S rRNA (2,305), 28S rRNA (2...... analyses indicate a convergent evolution of the very similar and highly reduced slug-shaped stages found during metamorphosis of both the Rhizocephala and the Facetotecta. This provides a remarkable case of convergent evolution and implies that the advanced endoparasitic mode of life known from...

Remark to the Comment on "New pseudoclassical model for Weyl particles"

OpenAIRE

Gitman, D. M.; Gonçalves, A. E.; Tyutin, I. V.

1996-01-01

We present here our considerations concerning the problem of classical consistency of pseudoclassical models touched upon in a recent comment on our paper "New pseudoclassical model for Weyl particle".

Computational Modeling of Proteins based on Cellular Automata: A Method of HP Folding Approximation.

Science.gov (United States)

Madain, Alia; Abu Dalhoum, Abdel Latif; Sleit, Azzam

2018-06-01

The design of a protein folding approximation algorithm is not straightforward even when a simplified model is used. The folding problem is a combinatorial problem, where approximation and heuristic algorithms are usually used to find near optimal folds of proteins primary structures. Approximation algorithms provide guarantees on the distance to the optimal solution. The folding approximation approach proposed here depends on two-dimensional cellular automata to fold proteins presented in a well-studied simplified model called the hydrophobic-hydrophilic model. Cellular automata are discrete computational models that rely on local rules to produce some overall global behavior. One-third and one-fourth approximation algorithms choose a subset of the hydrophobic amino acids to form H-H contacts. Those algorithms start with finding a point to fold the protein sequence into two sides where one side ignores H's at even positions and the other side ignores H's at odd positions. In addition, blocks or groups of amino acids fold the same way according to a predefined normal form. We intend to improve approximation algorithms by considering all hydrophobic amino acids and folding based on the local neighborhood instead of using normal forms. The CA does not assume a fixed folding point. The proposed approach guarantees one half approximation minus the H-H endpoints. This lower bound guaranteed applies to short sequences only. This is proved as the core and the folds of the protein will have two identical sides for all short sequences.