O projeto é apoiado em parte pela Alfred P. Sloan Foundation, NSF Prémio Carreira (DBI 1027394), eo Instituto Nacional de Ciências Médicas Gerais (GM083107, GM084222).

<ol>
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Não há conflitos de interesse declarados.

O protocolo apresentado acima é uma diretriz geral para a estrutura e função de modelagem usando o servidor I-TASSER. Embora, este procedimento automatizado funciona muito bem para a maioria das proteínas, as intervenções humanas muitas vezes ajudam a melhorar significativamente a precisão de modelagem, especialmente para as proteínas que faltam modelos de perto na biblioteca PDB. Os usuários podem intervir durante a modelagem I-TASSER das seguintes formas: (a) divisão de multi-domínio proteínas; (b) fornecimento de restrições externas para melhorar a estrutura de montagem, e (c) remover modelos durante a modelagem. Proteína multi-domínio divisão: Muitas seqüências de proteínas longo freqüentemente contêm vários domínios amarrados por regiões linker flexível, o que torna difícil a sua elucidação da estrutura através de técnicas experimentais e computacionais. No entanto, como os domínios são dobráveis ​​independentemente entidades e pode executar a função molecular distinta, édesejável para dividir longas multi-domínio proteínas e modelo de cada domínio separadamente. Domínios de modelagem, individualmente, não só acelerar o processo de previsão, mas também aumenta a qualidade da consulta de modelo de alinhamento, resultando em uma estrutura mais confiável e previsões função. Limites de domínio em seqüências de proteínas pode ser predita usando livremente disponível externo programas online como o NCBI CDD 24, 25 ou Pfam InterProScan 26. Além disso, se LOMETS alinhamentos threading estão disponíveis para consulta a proteína, os limites de domínio podem ser localizados por identificar visualmente longos trechos de resíduos não alinhado nos modelos top threading (veja o Passo 5.4). Estas regiões não alinhado em sua maioria correspondem a regiões linker domínio. Se multi-domínio modelos já estão disponíveis na biblioteca de modelos PDB com todos os domínios de consulta alinhados, então a proteína consulta pode ser modelado como comprimento total. Fornecer restrições externas <pclass = &quot;jove_content&quot;&gt; As simulações estrutura de montagem em I-TASSER são principalmente guiada por restrições espaciais coletados do LOMETS threading modelos. Para proteínas de consulta que atingiram boa threading (Norm. Z-score&gt; 1) na biblioteca de modelo, derivado restrições espaciais são principalmente de alta precisão e I-TASSER irá gerar modelos de alta resolução estrutural para essas proteínas. Ao contrário, para as proteínas consulta que têm pouca ou nenhuma hit threading (Norm. Z-score &lt;1), coletados restrições espaciais muitas vezes contêm erros devido à incerteza do modelo e do alinhamento. Para estas proteínas alvo, especificados pelo usuário informação espacial pode ser muito útil para melhorar a qualidade do modelo previsto. Usuários podem fornecer restrições externas para o servidor I-TASSER de duas maneiras: A. Especifique contato / distância restrições Experimentalmente caracterizadas inter-resíduos contatos / distâncias, por exemplo, de NMR oucross-linking experimentos, pode ser especificado pelo upload de um arquivo moderação. Um arquivo de exemplo é mostrado na Figura 8, onde Coluna 1 especifica o tipo de restrição, ou seja, &quot;DIST&quot; ou &quot;CONTATO&quot;. De contenção à distância (DIST), colunas 2 e 4 contêm resíduos de posições (i, j), colunas 3 e 5 contêm o átomo tipos de resíduos e na coluna 6 especifica a distância entre os dois átomos especificado. No caso dos apoios de contato (CONTACT), colunas 2 e 3 contêm as posições (i, j) de resíduos que deve estar em contato. A distância entre o centro cadeias laterais desses pares resíduos entrar em contato é decidido com base em distâncias observadas em estruturas conhecidas no PDB. I-TASSER vai tentar tirar esses pares de átomos perto da distância especificada durante as simulações refinamento estrutura. B. Especifique um modelo de estrutura de proteínas Programas LOMETS threading usar uma biblioteca representativa PDB para encontrar dobras plausível para a prot consultaein. Embora o uso de uma biblioteca de estrutura representativa ajuda a reduzir o tempo necessário para calcular a alinhamentos de seqüência-estrutura, é possível que uma proteína bom modelo é perdida na biblioteca ou o modelo não pode ter sido identificado por LOMETS programas threading, embora seja presentes na biblioteca. Nestes casos, o usuário deve especificar a estrutura da proteína desejada como modelo. Para especificar a estrutura da proteína como um modelo adicional, os usuários podem fazer upload de um arquivo de estrutura PDB formatado ou especificar o ID PDB de uma estrutura de proteína depositada na biblioteca PDB. O I-TASSER irá gerar o alinhamento template-consulta usando o programa Muster 23 e irá recolher as restrições espaciais de tanto o usuário especificado modelo e modelos LOMETS para orientar a simulação de montagem da estrutura. Porque a precisão das restrições LOMETS é diferente para diferentes alvos, o peso das restrições LOMETS é mais forte em fácil (homóloga) targets do que em disco rígido (não-homólogos) metas, que têm sido sistematicamente ligado em nosso treinamento benchmark. Os usuários também podem especificar suas próprias consulta template-alinhamentos. O servidor aceita o alinhamento em dois formatos: o formato FASTA (Figura 9A) eo formato 3D (Figura 9B). O formato FASTA é padrão e descrito em <a href="http://zhanglab.%20ccmb.med.umich.edu/FASTA/">http://zhanglab. ccmb.med.umich.edu / FASTA /</a> . O formato 3D é semelhante ao formato padrão PDB ( <a href="http://www.wwpdb.org/documentation/format32/sect9.html">http://www.wwpdb.org/documentation/format32/sect9.html</a> ), mas duas colunas adicionais derivados dos modelos são adicionados aos registros ATOM (ver Figura 9B): Colunas 1-30: Atom (C-alfa apenas) e resíduo de nomes para a seqüência de consulta. Colunas 31-54: Coordenadas do C-alfa átomos da consulta copiado dos átomos correspondentes no modelo. Colunas 55-59: Número de resíduos correspondente no modelo baseado em alinhamento Colunas 60-64: Nome do resíduo correspondente no modelo Excluir proteínas modelos Proteínas são moléculas flexíveis e podem adotar vários estados conformacionais de mudar sua atividade biológica. Por exemplo, as estruturas de proteínas quinases e proteínas da membrana muitos foram resolvidos na conformação ativos e inativos. Também presença ou ausência de ligante ligado pode causar grandes movimentos estruturais. Enquanto todos os estados conformacionais do modelo são iguais para os programas de threading, é desejável que o modelo de consulta utilizando templates em apenas um estado particular. Uma nova opção no servidor permite ao usuário excluir proteínas modelo durante a modelagem da estrutura. Este recurso também permite ao usuário escolher o nível de homologia de modelos a serem utilizados para a modelagem. Os usuários podem excluir template proteínas from a biblioteca I-TASSER por: A. A especificação de um corte de identidade de seqüência Os usuários podem usar esta opção para excluir proteínas homólogas da biblioteca de modelos I-TASSER. O nível de homologia é definida com base no corte de identidade de seqüência, ou seja, o número de resíduos idênticos entre a consulta ea proteína modelo, dividido pelo comprimento da seqüência da seqüência de consulta. Por exemplo, se o usuário digita em &quot;70%&quot; na forma prevista, todas as proteínas modelos que têm uma identidade de seqüência&gt; 70% para a proteína I-consulta será excluído da biblioteca de modelos I-TASSER. B. Exclude proteínas modelo específico Proteínas modelo específico pode ser excluído da biblioteca de modelos I-TASSER fazendo o upload de uma lista contendo IDs PDB das estruturas a serem excluídos. Um arquivo de exemplo é mostrado na Figura 10. Como a mesma proteína pode existir como várias entradas na biblioteca PDB, I-TASSER siRVer, por padrão, excluir os modelos especificados (em coluna1), bem como todos os outros modelos da biblioteca que tem uma identidade&gt; 90% para os modelos especificados. Os usuários também podem especificar uma identidade diferente de corte, por exemplo, 70%, onde todos os modelos com a identidade&gt; 70% às proteínas modelo especificado serão excluídos.

<ol><li> FASTA formatado seqüência de aminoácidos da proteína a ser modelada (ver, <a href="http://www.ncbi.nlm.nih.gov/BLAST/fasta.shtml">http://www.ncbi.nlm.nih.gov/BLAST/fasta.shtml</a> ). </li><li> Um computador pessoal com acesso à internet e um navegador web. </li><li> Software visualização molecular, por exemplo, RasMol ou PyMOL, para analisar a estrutura prevista terciário e sites funcionais. </li></ol>

a protocol for computer-based protein structure and function prediction

Projetos de seqüenciamento do genoma tem ciphered milhões de seqüência de proteína, que exigem conhecimento de sua estrutura e função de melhorar a compreensão de seu papel biológico. Embora os métodos experimentais podem fornecer informações detalhadas para uma pequena fração dessas proteínas, modelagem computacional é necessário para a maioria das moléculas de proteínas que são experimentalmente descaracterizados. O servidor I-TASSER é uma bancada on-line de alta resolução de modelagem da estrutura da proteína ea função. Dada uma seqüência de proteína, uma saída típica do servidor I-TASSER inclui previsão de estrutura secundária, previu acessibilidade solvente de cada resíduo, proteínas homólogas modelo detectado por threading e alinhamentos estrutura, até cinco full-length terciário modelos estruturais, e baseado em estrutura anotações funcionais para a classificação das enzimas, termos Gene Ontology e proteína-ligante sítios de ligação. Todas as previsões são marcados com uma pontuação de confiança queconta como precisas as previsões são sem conhecer os dados experimentais. Para facilitar a pedidos especiais de usuários finais, o servidor fornece canais de aceitar especificado pelo usuário resíduos inter-distância e entre em contato mapas interativamente alterar a modelagem I-TASSER, mas também permite aos usuários especificar quaisquer proteínas como modelo ou excluir qualquer modelo proteínas durante as simulações de montagem da estrutura. As informações estruturais poderiam ser recolhidos pelos usuários com base em evidências experimentais ou insights biológicos com a finalidade de melhorar a qualidade de I-TASSER previsões. O servidor foi avaliado como o melhor programas para a estrutura da proteína e previsões função na recente experimentos CASP em toda a comunidade. Existem actualmente&gt; 20.000 cientistas registrados em mais de 100 países que estão usando o servidor on-line I-TASSER.

Watch this Scientific Journal Video about A Protocol for Computer-Based Protein Structure and Function Prediction at JoVE.com

A Protocol for Computer-Based Protein Structure and Function Prediction

Diretrizes para computador baseado caracterização estrutural e funcional da proteína usando o pipeline I-TASSER é descrito. A partir de seqüência de proteína de consulta, os modelos 3D são gerados usando vários alinhamentos threading e iterativo simulações de montagem estrutural. Inferências funcionais são posteriormente elaborado com base em correspondências às proteínas com estrutura conhecida e funções.

Um protocolo para Computer-Based Estrutura de Proteínas e de Previsão de Função

Genome sequencing projects have ciphered millions of protein sequence, which require knowledge of their structure and function to improve the ...

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Research

JoVE Journal

Biology

68.1K visualizações.  University of Michigan. Diretrizes para computador baseado caracterização estrutural e funcional da proteína usando o pipeline I-TASSER é descrito. A partir de seqüência de proteína de consulta, os modelos 3D são gerados usando vários alinhamentos threading e iterativo simulações de montagem estrutural. Inferências funcionais são posteriormente elaborado com base em correspondências às proteínas com estrutura conhecida e funções.

Vídeo: A Protocol for Computer-Based Protein Structure and Function Prediction

The Importance of Correct Protein Concentration for Kinetics and Affinity Determination in Structure-function Analysis 

In this study, we explore the interaction between the bovine cysteine protease inhibitor cystatin B and a catalytically inactive form of papain (Fig. 1), a plant cysteine protease, by real-time label-free analysis using Biacore X100. Several cystatin B variants with point mutations in areas of interaction with papain, are produced. For each cystatin B variant we determine its specific binding concentration using calibration-free concentration analysis (CFCA) and compare the values obtained with total protein concentration as determined by A280. After that, the kinetics of each cystatin B variant binding to papain is measured using single-cycle kinetics (SCK). We show that one of the four cystatin B variants we examine is only partially active for binding. This partial activity, revealed by CFCA, translates to a significant difference in the association rate constant (ka) and affinity (KD), compared to the values calculated using total protein concentration. Using CFCA in combination with kinetic analysis in a structure-function study contributes to obtaining reliable results, and helps to make the right interpretation of the interaction mechanism.

The Importance of Correct Protein Concentration for Kinetics and Affinity Determination in Structure-function Analysis

We apply label-free protein interaction analysis using Biacore X100 for structure-function analysis of the binding of several cystatin B mutants to papain through kinetic characterization. Calibration-free concentration analysis (CFCA) measures the concentration of protein with retained binding activity without the need for a standard curve. We show that confirmation of concentrations using CFCA increases the reliability of the kinetic analysis and that kinetic constants can reliably be determined even if the activity of a recombinant protein is reduced.

A importância da concentração de proteína correta para Cinética e Determinação Affinity na estrutura-função Análise

In this study, we explore the interaction between the bovine cysteine protease inhibitor cystatin B and a catalytically inactive form of papain (Fig. 1), ...

Biologia

Using the GELFREE 8100 Fractionation System for Molecular Weight-Based Fractionation with Liquid Phase Recovery

The GELFREE 8100 Fractionation System is a novel protein fractionation system designed to maximize protein recovery during molecular weight based fractionation. The system is comprised of single-use, 8-sample capacity cartridges and a benchtop GELFREE Fractionation Instrument. During separation, a constant voltage is applied between the anode and cathode reservoirs, and each protein mixture is electrophoretically driven from a loading chamber into a specially designed gel column gel. Proteins are concentrated into a tight band in a stacking gel, and separated based on their respective electrophoretic mobilities in a resolving gel. As proteins elute from the column, they are trapped and concentrated in liquid phase in the collection chamber, free of the gel. The instrument is then paused at specific time intervals, and fractions are collected using a pipette. This process is repeated until all desired fractions have been collected. If fewer than 8 samples are run on a cartridge, any unused chambers can be used in subsequent separations.
This novel technology facilitates the quick and simple separation of up to 8 complex protein mixtures simultaneously, and offers several advantages when compared to previously available fractionation methods. This system is capable of fractionating up to 1mg of total protein per channel, for a total of 8mg per cartridge. Intact proteins over a broad mass range are separated on the basis of molecular weight, retaining important physiochemical properties of the analyte. The liquid phase entrapment provides for high recovery while eliminating the need for band or spot cutting, making the fractionation process highly reproducible1.

The accompanying video describes the use of the GELFREE 8100 Fractionation System, which partitions complex protein samples on the basis of molecular weight and recovers the fractions in liquid phase. The video describes how the technology works, how it is used, and provides resultant data, with polyacrylamide gel electrophoresis analysis of fractionated bovine liver homogenate.

Usando o sistema de fracionamento GELFREE 8100 para Fracionamento baseada no peso molecular com Recovery Fase Líquida

The GELFREE 8100 Fractionation System is a novel protein fractionation system designed to maximize protein recovery during molecular weight based ...

Analysis of the Development of a Morphological Phenotype as a Function of Protein Concentration in Budding Yeast

Gene deletion and protein overexpression are common methods for studying functions of proteins. In this article, we describe a protocol for analysis of phenotype development as a function of protein concentration at population and single-cell levels in Saccharomyces cerevisiae. Although this protocol is based on the overexpression of a protein, it can easily be adapted for morphological phenotypes dependent on suppression of protein expression. Our lab is interested in studying the signaling properties of the endocytic adaptor protein epsin. To that purpose we used a dominant negative approach in which we over-expressed the conserved Epsin N-Terminal Homology (ENTH) domain in order to interfere with the functions of endogenous epsin-2 (Ent2 or YLR206W). We observed that overexpression of the ENTH domain of Ent2 (ENTH2) in wild type cells led to a cell division defect that is dependent on the mislocalization of a family of scaffolding proteins, septins.

Gene deletion and protein overexpression are common methods for studying functions of proteins. In this article, we describe a protocol for analysis of phenotype development as a function of protein concentration at population and single-cell levels in Saccharomyces cerevisiae.

Análise do desenvolvimento de um fenótipo morfológico como uma função da concentração de proteínas em levedura de brotamento

Gene deletion and protein overexpression are common methods for studying functions of proteins. In this article, we describe a protocol for analysis of ...

A Protocol for the Identification of Protein-protein Interactions Based on 15N Metabolic Labeling, Immunoprecipitation, Quantitative Mass Spectrometry and Affinity Modulation

Protein-protein interactions are fundamental for many biological processes in the cell. Therefore, their characterization plays an important role in current research and a plethora of methods for their investigation is available1. Protein-protein interactions often are highly dynamic and may depend on subcellular localization, post-translational modifications and the local protein environment2. Therefore, they should be investigated in their natural environment, for which co-immunoprecipitation approaches are the method of choice3. Co-precipitated interaction partners are identified either by immunoblotting in a targeted approach, or by mass spectrometry (LC-MS/MS) in an untargeted way. The latter strategy often is adversely affected by a large number of false positive discoveries, mainly derived from the high sensitivity of modern mass spectrometers that confidently detect traces of unspecifically precipitating proteins. A recent approach to overcome this problem is based on the idea that reduced amounts of specific interaction partners will co-precipitate with a given target protein whose cellular concentration is reduced by RNAi, while the amounts of unspecifically precipitating proteins should be unaffected. This approach, termed QUICK for QUantitative Immunoprecipitation Combined with Knockdown4, employs Stable Isotope Labeling of Amino acids in Cell culture (SILAC)5 and MS to quantify the amounts of proteins immunoprecipitated from wild-type and knock-down strains. Proteins found in a 1:1 ratio can be considered as contaminants, those enriched in precipitates from the wild type as specific interaction partners of the target protein. Although innovative, QUICK bears some limitations: first, SILAC is cost-intensive and limited to organisms that ideally are auxotrophic for arginine and/or lysine. Moreover, when heavy arginine is fed, arginine-to-proline interconversion results in additional mass shifts for each proline in a peptide and slightly dilutes heavy with light arginine, which makes quantification more tedious and less accurate5,6. Second, QUICK requires that antibodies are titrated such that they do not become saturated with target protein in extracts from knock-down mutants.
Here we introduce a modified QUICK protocol which overcomes the abovementioned limitations of QUICK by replacing SILAC for 15N metabolic labeling and by replacing RNAi-mediated knock-down for affinity modulation of protein-protein interactions. We demonstrate the applicability of this protocol using the unicellular green alga Chlamydomonas reinhardtii as model organism and the chloroplast HSP70B chaperone as target protein7 (Figure 1). HSP70s are known to interact with specific co-chaperones and substrates only in the ADP state8. We exploit this property as a means to verify the specific interaction of HSP70B with its nucleotide exchange factor CGE19.

A Protocol for the Identification of Protein-protein Interactions Based on 15N Metabolic Labeling, Immunoprecipitation, Quantitative Mass Spectrometry and Affinity Modulation

We present a variation of the QUICK (QUantitative Immunoprecipitation Combined with Knockdown) approach that was introduced previously to distinguish between true and false protein-protein interactions. Our approach is based on 15N metabolic labeling, the modulation of affinities of protein-protein interactions by the presence/absence of ATP, immunoprecipitation, and quantitative mass spectrometry.

Um protocolo para a identificação de interações proteína-proteína Baseado<sup&gt; 15</sup&gt; Etiquetagem N Metabólica, imunoprecipitação, Quantitativa Espectrometria de Massa e Affinity Modulação

Protein-protein interactions are fundamental for many biological processes in the cell. Therefore, their characterization plays an important role in ...

Using High Resolution Computed Tomography to Visualize the Three Dimensional Structure and Function of Plant Vasculature

High resolution x-ray computed tomography (HRCT) is a non-destructive diagnostic imaging technique with sub-micron resolution capability that is now being used to evaluate the structure and function of plant xylem network in three dimensions (3D) (e.g. Brodersen et al. 2010; 2011; 2012a,b). HRCT imaging is based on the same principles as medical CT systems, but a high intensity synchrotron x-ray source results in higher spatial resolution and decreased image acquisition time. Here, we demonstrate in detail how synchrotron-based HRCT (performed at the Advanced Light Source-LBNL Berkeley, CA, USA) in combination with Avizo software (VSG Inc., Burlington, MA, USA) is being used to explore plant xylem in excised tissue and living plants. This new imaging tool allows users to move beyond traditional static, 2D light or electron micrographs and study samples using virtual serial sections in any plane. An infinite number of slices in any orientation can be made on the same sample, a feature that is physically impossible using traditional microscopy methods.
Results demonstrate that HRCT can be applied to both herbaceous and woody plant species, and a range of plant organs (i.e. leaves, petioles, stems, trunks, roots). Figures presented here help demonstrate both a range of representative plant vascular anatomy and the type of detail extracted from HRCT datasets, including scans for coast redwood (Sequoia sempervirens), walnut (Juglans spp.), oak (Quercus spp.), and maple (Acer spp.) tree saplings to sunflowers (Helianthus annuus), grapevines (Vitis spp.), and ferns (Pteridium aquilinum and Woodwardia fimbriata). Excised and dried samples from woody species are easiest to scan and typically yield the best images. However, recent improvements (i.e. more rapid scans and sample stabilization) have made it possible to use this visualization technique on green tissues (e.g. petioles) and in living plants. On occasion some shrinkage of hydrated green plant tissues will cause images to blur and methods to avoid these issues are described. These recent advances with HRCT provide promising new insights into plant vascular function.

High resolution x-ray computed tomography (HRCT) is a non-destructive diagnostic imaging technique that can be used to study the structure and function of plant vasculature in 3D. We demonstrate how HRCT facilitates exploration of xylem networks across a wide range of plant tissues and species.

Usando tomografia de tórax para visualizar a estrutura tridimensional e Função da Usina Vasculatura

High resolution x-ray computed tomography (HRCT) is a non-destructive diagnostic imaging technique with sub-micron resolution capability that is now being ...

RNA Secondary Structure Prediction Using High-throughput SHAPE

Understanding the function of RNA involved in biological processes requires a thorough knowledge of RNA structure. Toward this end, the methodology dubbed "high-throughput selective 2' hydroxyl acylation analyzed by primer extension", or SHAPE, allows prediction of RNA secondary structure with single nucleotide resolution. This approach utilizes chemical probing agents that preferentially acylate single stranded or flexible regions of RNA in aqueous solution. Sites of chemical modification are detected by reverse transcription of the modified RNA, and the products of this reaction are fractionated by automated capillary electrophoresis (CE). Since reverse transcriptase pauses at those RNA nucleotides modified by the SHAPE reagents, the resulting cDNA library indirectly maps those ribonucleotides that are single stranded in the context of the folded RNA. Using ShapeFinder software, the electropherograms produced by automated CE are processed and converted into nucleotide reactivity tables that are themselves converted into pseudo-energy constraints used in the RNAStructure (v5.3) prediction algorithm. The two-dimensional RNA structures obtained by combining SHAPE probing with in silico RNA secondary structure prediction have been found to be far more accurate than structures obtained using either method alone.

High-throughput selective 2' hydroxyl acylation analyzed by primer extension (SHAPE) utilizes a novel chemical probing technology, reverse transcription, capillary electrophoresis and secondary structure prediction software to determine the structures of RNAs from several hundred to several thousand nucleotides at single nucleotide resolution.

RNA Secundária Previsão Estrutura Usando SHAPE de alta capacidade

Understanding the function of RNA involved in biological processes requires a thorough knowledge of RNA structure. Toward this end, the methodology dubbed ...

A Protocol for Phage Display and Affinity Selection Using Recombinant Protein Baits

Using recombinant phage as a scaffold to present various protein portions encoded by a directionally cloned cDNA library to immobilized bait molecules is an efficient means to discover interactions. The technique has largely been used to discover protein-protein interactions but the bait molecule to be challenged need not be restricted to proteins. The protocol presented here has been optimized to allow a modest number of baits to be screened in replicates to maximize the identification of independent clones presenting the same protein. This permits greater confidence that interacting proteins identified are legitimate interactors of the bait molecule. Monitoring the phage titer after each affinity selection round provides information on how the affinity selection is progressing as well as on the efficacy of negative controls. One means of titering the phage, and how and what to prepare in advance to allow this process to progress as efficiently as possible, is presented. Attributes of amplicons retrieved following isolation of independent plaque are highlighted that can be used to ascertain how well the affinity selection has progressed. Trouble shooting techniques to minimize false positives or to bypass persistently recovered phage are explained. Means of reducing viral contamination flare up are discussed.

Phage display is a powerful technique to capture proteins or protein moieties that interact with an immobilized molecule of interest. Once a decision of the type of phage cDNA library to create and screen has been made, the protocol described here permits efficient affinity selection leading to identification of interactors.

Um protocolo para exibição Fago e Affinity Seleção Usando Iscas proteína recombinante

Using  recombinant phage as a scaffold to present various protein portions encoded by  a directionally cloned cDNA library to immobilized bait molecules ...

Discovering Protein Interactions and Characterizing Protein Function Using HaloTag Technology

Research in proteomics has exploded in recent years with advances in mass spectrometry capabilities that have led to the characterization of numerous proteomes, including those from viruses, bacteria, and yeast.&#160; In comparison, analysis of the human proteome lags behind, partially due to the sheer number of proteins which must be studied, but also the complexity of networks and interactions these present. To specifically address the challenges of understanding the human proteome, we have developed HaloTag technology for protein isolation, particularly strong for isolation of multiprotein complexes and allowing more efficient capture of weak or transient interactions and/or proteins in low abundance. &#160;HaloTag is a genetically encoded protein fusion tag, designed for covalent, specific, and rapid immobilization or labelling of proteins with various ligands. Leveraging these properties, numerous applications for mammalian cells were developed to characterize protein function and here we present methodologies including: protein pull-downs used for discovery of novel interactions or functional assays, and cellular localization. We find significant advantages in the speed, specificity, and covalent capture of fusion proteins to surfaces for proteomic analysis as compared to other traditional non-covalent approaches. We demonstrate these and the broad utility of the technology using two important epigenetic proteins as examples, the human bromodomain protein BRD4, and histone deacetylase HDAC1.&#160; These examples demonstrate the power of this technology in enabling &#160;the discovery of novel interactions and characterizing cellular localization in eukaryotes, which will together further understanding of human functional proteomics. &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;

HaloTag technology is a multifunctional technology which has shown significant success in isolation of both small and large protein complexes from mammalian cells.&#160; Here we highlight the advantages of this technology compared to existing alternatives and demonstrate its utility to study numerous aspects of protein function inside eukaryotic cells.

Descobrindo Interações proteína e caracterização da função das proteínas Usando HaloTag Tecnologia

Research in proteomics has exploded in recent years with advances in mass spectrometry capabilities that have led to the characterization of numerous ...

Functional Reconstitution and Channel Activity Measurements of Purified Wildtype and Mutant CFTR Protein

The Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) is a unique channel-forming member of the ATP Binding Cassette (ABC) superfamily of transporters. The phosphorylation and nucleotide dependent chloride channel activity of CFTR has been frequently studied in whole cell systems and as single channels in excised membrane patches. Many Cystic Fibrosis-causing mutations have been shown to alter this activity. While a small number of purification protocols have been published, a fast reconstitution method that retains channel activity and a suitable method for studying population channel activity in a purified system have been lacking. Here rapid methods are described for purification and functional reconstitution of the full-length CFTR protein into proteoliposomes of defined lipid composition that retains activity as a regulated halide channel. This reconstitution method together with a novel flux-based assay of channel activity is a suitable system for studying the population channel properties of wild type CFTR and the disease-causing mutants F508del- and G551D-CFTR. Specifically, the method has utility in studying the direct effects of phosphorylation, nucleotides and small molecules such as potentiators and inhibitors on CFTR channel activity. The methods are also amenable to the study of other membrane channels/transporters for anionic substrates.

Described here is a rapid and effective procedure for functional reconstitution of purified wild-type and mutant CFTR protein that preserves activity for this chloride channel, which is defective in Cystic Fibrosis. Iodide efflux from reconstituted proteoliposomes mediated by CFTR allows studies of channel activity and the effects of small molecules.

Reconstituição funcional e atividade do canal Medidas de purificada tipo selvagem e mutante CFTR Protein

The Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) is a unique channel-forming member of the ATP Binding Cassette (ABC) superfamily of ...

Inducible LAP-tagged Stable Cell Lines for Investigating Protein Function, Spatiotemporal Localization and Protein Interaction Networks

Multi-protein complexes, rather than single proteins acting in isolation, often govern molecular pathways regulating cellular homeostasis. Based on this principle, the purification of critical proteins required for the functioning of these pathways along with their native interacting partners has not only allowed the mapping of the protein constituents of these pathways, but has also provided a deeper understanding of how these proteins coordinate to regulate these pathways. Within this context, understanding a protein's spatiotemporal localization and its protein-protein interaction network can aid in defining its role within a pathway, as well as how its misregulation may lead to disease pathogenesis. To address this need, several approaches for protein purification such as tandem affinity purification (TAP) and localization and affinity purification (LAP) have been designed and used successfully. Nevertheless, in order to apply these approaches to pathway-scale proteomic analyses, these strategies must be supplemented with modern technological developments in cloning and mammalian stable cell line generation. Here, we describe a method for generating LAP-tagged human inducible stable cell lines for investigating protein subcellular localization and protein-protein interaction networks. This approach has been successfully applied to the dissection of multiple cellular pathways including cell division and is compatible with high-throughput proteomic analyses.

We describe a method for generating localization and affinity purification (LAP)-tagged inducible stable cell lines for investigating protein function, spatiotemporal subcellular localization and protein-protein interaction networks.

Induzíveis linhas celulares estáveis ​​marcado-LAP para investigar a função da proteína, Spatiotemporal Localização e redes de interação de proteínas

Multi-protein complexes, rather than single proteins acting in isolation, often govern molecular pathways regulating cellular homeostasis. Based on this ...