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检索条件"主题词=Protein secondary structure Prediction"

共 165 条记录，以下是151-160 订阅

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RaptorX server: A Resource for Template-Based protein structure Modeling

RaptorX server: A Resource for Template-Based Protein Struct...

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作者： Morten Källberg Gohar Margaryan Sheng Wang Jianzhu Ma Jinbo Xu

Assigning functional properties to a newly discovered protein is a key challenge in modern biology. To this end, computational modeling of the three-dimensional atomic arrangement of the amino acid chain is often crucial in determining the role of the protein in biological processes. We present a community-wide web-based protocol, RaptorX server (http://*** ), for automated protein secondary structure prediction, template-based tertiary structure modeling, and probabilistic alignment sampling. Given a target sequence, RaptorX server is able to detect even remotely related template sequences by means of a novel nonlinear context-specific alignment potential and probabilistic consistency algorithm. Using the protocol presented here it is thus possible to obtain high-quality structural models for many target protein sequences when only distantly related protein domains have experimentally solved structures. At present, RaptorX server can perform secondary and tertiary structure prediction of a 200 amino acid target sequence in approximately 30 min. less

关键词： protein structure prediction Homology Modeling protein structure Analysis protein secondary structure prediction structure prediction Jmol Model quality assessment protein threading

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An Introduction to Internet Resources for the Molecular and Genetic Analysis of the Lipases

An Introduction to Internet Resources for the Molecular and ...

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作者： Karen Reue

In recent years, cDNA and genomic DNA clones have been isolated for many of the mammalian lipases and phospholipases described in this volume. These DNA clones have provided essential tools for the analysis of lipase expression, structure, and function. In addition, DNA sequence analysis has generated a wealth of information about lipase protein and gene structure, including nucleotide and amino acid sequence, exon/intron organization, chromosome localization, phylogenetic relationships among lipases, and the elucidation of lipase mutations that underlie lipase deficiencies and dyslipidemias. Much of the information derived from the molecular and genetic characterization of genes and proteins has been deposited into electronic databases. With the advent of widespread access to the Internet, researchers throughout the world can contribute to and retrieve information from a wide array of databases that are continuously updated to include the most recent findings. less

关键词： protein Analysis Genetic Analysis DNA Sequence Analysis Physical Mapping PCR Genetic Mapping structure Analysis Sequence Similarity Search PROSITE protein secondary structure prediction protein structure prediction Homology Modeling 2D PAGE Peptide Mass Fingerprinting SDS-PAGE Molecular Modeling GenBank Swiss-Prot Positional cloning Expasy Homo sapiens Mus musculus

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The Method of Screening and Identification of Transcription Factor in

The Method of Screening and Identification of Transcription ...

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作者： Qiang Wu Gao-Qiang Liu Jiang-Shan Ma Qiang Li

This protocol describes a method for verifying the specific transcription factor regulating glycerol dehydratase (GDH) expression in Klebsiella. DNA pull-down accompanied with mass spectrometry is used to screen and identify the transcription factor interacting with the promoter region of the key gene in Klebsiella. EMSA method is used to validate the specific binding of the transcription factor to the promoter region in vitro. In addition, the target DNA fragments are constructed by fusion PCR to prepare competent cells from Klebsiella for electrical transformation and further transformed to obtain key gene deletion strains to verify the transcription factor responsible for the target gene expression in Klebsiella. less

关键词： DNA pull-down assay EMSA Gene Knockout Mass Spectrometry Fusion PCR PCR Western Blot Electrophoresis Spectroscopy Tandem Mass Spectrometry Plasmid Construction GenBank protein Purification Cross-linking protein Sequence Analysis protein secondary structure prediction protein structure Analysis BCA assay protein Electrophoresis Klebsiella Saccharomyces cerevisiae Escherichia coli Transcription factor

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Learning Strategies in protein Directed Evolution

Learning Strategies in Protein Directed Evolution

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作者： Xavier F. Cadet Jean Christophe Gelly Aster Noord Frédéric Cadet Carlos G. Acevedo-Rocha

Synthetic biology is a fast-evolving research field that combines biology and engineering principles to develop new biological systems for medical, pharmacological, and industrial applications. Synthetic biologists use iterative “design, build, test, and learn” cycles to efficiently engineer genetic systems that are reliable, reproducible, and predictable. protein engineering by directed evolution can benefit from such a systematic engineering approach for various reasons. Learning can be carried out before starting, throughout or after finalizing a directed evolution project. Computational tools, bioinformatics, and scanning mutagenesis methods can be excellent starting points, while molecular dynamics simulations and other strategies can guide engineering efforts. Similarly, studying protein intermediates along evolutionary pathways offers fascinating insights into the molecular mechanisms shaped by evolution. The learning step of the cycle is not only crucial for proteins or enzymes that are not suitable for high-throughput screening or selection systems, but it is also valuable for any platform that can generate a large amount of data that can be aided by machine learning algorithms. The main challenge in protein engineering is to predict the effect of a single mutation on one functional parameter—to say nothing of several mutations on multiple parameters. This is largely due to nonadditive mutational interactions, known as epistatic effects—beneficial mutations present in a genetic background may not be beneficial in another genetic background. In this work, we provide an overview of experimental and computational strategies that can guide the user to learn protein function at different stages in a directed evolution project. We also discuss how epistatic effects can influence the success of directed evolution projects. Since machine learning is gaining momentum in protein engineering and the field is becoming more interdisciplinary thanks to collaboration betw

关键词： protein Engineering Mutagenesis Artificial Intelligence Machine Learning Deep learning Molecular Dynamics Simulation High-throughput Screening protein structure Analysis X-ray Crystallography Cryo-EM NMR Molecular Modeling ITASSER Organic Synthesis Recombinant protein Expression Multiple Sequence Alignment Metagenomics PCR Molecular Docking Natural Language Processing protein secondary structure prediction Neural Network Model Statistical Calculation structure Classification Synthetic biology Epistasis Hotspots Rational design Directed evolution

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LOV2-Controlled Photoactivation of protein

LOV2-Controlled Photoactivation of Protein

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作者： Anam Qudrat Abdullah Mosabbir Kevin Truong

protein trans-splicing is a posttranslational modification that joins two protein fragments together via a peptide a bond in a process that does not require exogenous cofactors. Towards achieving cellular control, synthetically engineered systems have used a variety of stimuli such as small molecules and light. Recently, split inteins have been engineered to be photoactive by the LOV2 domain (named LOVInC). Herein, we discuss (1) designing of LOV2-activated target proteins (e.g., inteins), (2) selecting feasible splice sites for the extein, and (3) imaging cells that express LOVInC-based target exteins. less

关键词： PCR SDS-PAGE Molecular Dynamics Simulation protein secondary structure prediction DNA Purification Cell And Tissue Culture Transfection Trypsination MetaMorph Escherichia coli Photoactivation Fluorescence Inteins protein trans-splicing Light-oxygen-voltage domain

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Flour Quality and Related Molecular Characterization of High Molecular Weight Glutenin Subunit Genes from Wild Emmer Wheat Accession TD-256

Flour Quality and Related Molecular Characterization of High...

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第八届全国小麦基因组学及分子育种大会

作者： Dale Zhang Tingting He Huihui Liang Luyu Huang Yazhong Su Yuge Li Suoping Li School of Life Science Henan University

To clarify the effect of high molecular weight glutenin subunit（HMW-GS）from wild emmer wheat on flour quality,which has the same mobility as that from common wheat,the composition and molecular characterization of HMW-GS from wild emmer wheat accession TD-256,as well as its flour quality,were intensively *** is found that the mobilities of Glu-A1 and Glu-B1 subunits from TD-256 are consistent with those of bread wheat cv.'XiaoYan 6'.Nevertheless,dough rheo logical properties of TD-256 reveal its poor flour *** the aspect of molecular structure from HMW-GS,only two conserved cysteine residues can be observed in the deduced protein sequence of1 Bx14 from TD-256,while most Glu-1 Bx contain four conserved cysteine *** addition,as can be predicted from secondary structure,the quantity both of a-helixes and their amino acid residues of the subunits from TD-256 is fewer than those of common *** low molecular weight glutenin subunit（LMW-GS） and gliadin can also greatly influence flour quality,the protein structure of the HMW-GS revealed in this work can partly explain the poor flour quality of wild emmer accession TD-256.

关键词： Triticum dicoccoides high molecular weight glutenin sub unit(HMW-GS) dough rheological properties gene cloning protein secondary structure prediction

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Proteomic Tools for the Analysis of Cytoskeleton proteins

Proteomic Tools for the Analysis of Cytoskeleton Proteins

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作者： Michael Scarpati Mary Ellen Heavner Eliza Wiech Shaneen Singh

Proteomic analyses have become an essential part of the toolkit of the molecular biologist, given the widespread availability of genomic data and open source or freely accessible bioinformatics software. Tools are available for detecting homologous sequences, recognizing functional domains, and modeling the three-dimensional structure for any given protein sequence. Although a wealth of structural and functional information is available for a large number of cytoskeletal proteins, with representatives spanning all of the major subfamilies, the majority of cytoskeletal proteins remain partially or totally uncharacterized. Moreover, bioinformatics tools provide a means for studying the effects of synthetic mutations or naturally occurring variants of these cytoskeletal proteins. This chapter discusses various freely available proteomic analysis tools, with a focus on in silico prediction of protein structure and function. The selected tools are notable for providing an easily accessible interface for the novice, while retaining advanced functionality for more experienced computational biologists. less

关键词： Proteomics Homology Modeling Multiple Sequence Alignment structure Analysis protein secondary structure prediction structure prediction protein structure Analysis NCBI BLAST ClustalO PROSITE Molecular Modeling X-ray Crystallography NMR Jmol ITASSER structure Comparison Sequence Analysis Molecular Dynamics Simulation GenBank Pull-down Assay Threading Comparative modeling Sequence similarity protein domains

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Proteomic Tools for the Analysis of Cytoskeleton proteins

Proteomic Tools for the Analysis of Cytoskeleton Proteins

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作者： Ewa Wywial Vishnubhat Nataraj Dongre Shaneen M. Singh

Proteomic tools have become an essential part of the tool kit of the molecular biologist, and provide techniques for detecting homologous sequences, recognizing functional domains, modeling, and analyzing the three-dimensional structure for any given protein sequence. Although a wealth of structural and functional information is available for a large number of members of the various classes of cytoskeletal proteins, many more members remain uncharacterized. These computational tools that are freely and easily accessible to the scientific community provide an excellent starting point to predict the structural and functional properties of such partially or fully uncharacterized protein sequences, and can lead to elegantly designed experiments to probe the hypothesized function. This chapter discusses various proteomic analysis tools with a focus on protein structure and function predictions. less

关键词： Proteomics Multiple Sequence Alignment Homology Modeling structure Analysis protein secondary structure prediction structure prediction protein structure Analysis NCBI BLAST PROSITE Molecular Modeling X-ray Crystallography NMR Jmol protein Binding Site prediction Pull-down Assay Sequence similarity protein domains

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N- and C-Terminal Truncations to Enhance protein Solubility and Crystallization: Predicting protein Domain Boundaries with Bioinformatics Tools

N- and C-Terminal Truncations to Enhance Protein Solubility ...

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作者： Christopher D. Cooper Brian D. Marsden

Soluble protein expression is a key requirement for biochemical and structural biology approaches to study biological systems in vitro. Production of sufficient quantities may not always be achievable if proteins are poorly soluble which is frequently determined by physico-chemical parameters such as intrinsic disorder. It is well known that discrete protein domains often have a greater likelihood of high-level soluble expression and crystallizability. Determination of such protein domain boundaries can be challenging for novel proteins. Here, we outline the application of bioinformatics tools to facilitate the prediction of potential protein domain boundaries, which can then be used in designing expression construct boundaries for parallelized screening in a range of heterologous expression systems. less

关键词： Recombinant protein Expression protein structure Analysis Crystallization structure prediction protein secondary structure Multiple Sequence Alignment Ligation Independent Cloning (LIC) BLOSUM Sequence Analysis protein secondary structure prediction Genomics Statistical Calculation GlobPlot SDS-PAGE Genome Sequencing Alignment BLAST protein solubility Domain secondary structure Truncations PSIPRED Hidden Markov Model (HMM)

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An Improved CBA prediction Algorithm in Compound Pyramid Model

An Improved CBA Prediction Algorithm in Compound Pyramid Mod...

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2009中国控制与决策会议

作者： Zhou Zhun,Yang Bingru,Hou Wei University of Science and Technology Beijing,Information Engineering School,Beijing 100083

As one of KDTICM[8]theory researches,this paper propose an improved algorithm--CBA,which is based on KDD model and combined with KAAPRO method,for protein secondary structure prediction ***, multi-layer systematic prediction model--Compound Pyramid Model,is *** kernel of this model is CBA which is a classic association rules analysis *** knowledge is used through the model,and the phy-chemical attributes is chosen by Causal Cellular *** experiment,the proteins bias alpha/beta structure are precisely *** structures of amino acids,whose structure are obscure,are predicted well by the improved ***,the result of this model is satisfied.

关键词： Association Rule protein secondary structure prediction Compound Pyramid Model CBA algorithm

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