Characterisation of silent and active genes for a variable large protein of Borrelia recurrentis

Directory of Open Access Journals (Sweden)

Scragg Ian G

2002-10-01

Full Text Available Abstract Background We report the characterisation of the variable large protein (vlp gene expressed by clinical isolate A1 of Borrelia recurrentis; the agent of the life-threatening disease louse-borne relapsing fever. Methods The major vlp protein of this isolate was characterised and a DNA probe created. Use of this together with standard molecular methods was used to determine the location of the vlp1B. recurrentis A1 gene in both this and other isolates. Results This isolate was found to carry silent and expressed copies of the vlp1B. recurrentis A1 gene on plasmids of 54 kbp and 24 kbp respectively, whereas a different isolate, A17, had only the silent vlp1B. recurrentis A17 on a 54 kbp plasmid. Silent and expressed vlp1 have identical mature protein coding regions but have different 5' regions, both containing different potential lipoprotein leader sequences. Only one form of vlp1 is transcribed in the A1 isolate of B. recurrentis, yet both 5' upstream sequences of this vlp1 gene possess features of bacterial promoters. Conclusion Taken together these results suggest that antigenic variation in B. recurrentis may result from recombination of variable large and small protein genes at the junction between lipoprotein leader sequence and mature protein coding region. However, this hypothetical model needs to be validated by further identification of expressed and silent variant protein genes in other B. recurrentis isolates.

Serological and genetic characterisation of bovine respiratory syncytial virus (BRSV) indicates that Danish isolates belong to the intermediate subgroup: no evidence of a selective effect on the variability of G protein nucleotide sequence by prior cell culture adaption and passages in cell culture

DEFF Research Database (Denmark)

Larsen, Lars Erik; Uttenthal, Åse; Arctander, P.

1998-01-01

on the nucleotide sequence of the G protein. These findings indicated that the previously established variabilities of the G protein of RS virus isolates were not attributable to mutations induced during the propagation of the virus. The reactivity of the Danish isolates with G protein-specific MAbs were similar......Danish isolates of bovine respiratory syncytial virus (BRSV) were characterised by nucleotide sequencing of the G glycoprotein and by their reactivity with a panel of monoclonal antibodies (MAbs). Among the six Danish isolates, the overall sequence divergence ranged between 0 and 3...... part of the G gene of additional 11 field BRSV viruses, processed directly from lung samples without prior adaption to cell culture growth. revealed sequence variabilities in the range obtained with the propagated virus. In addition, several passages in cell culture and in calves had no major impact...

Nonlinear deterministic structures and the randomness of protein sequences

CERN Document Server

Huang Yan Zhao

2003-01-01

To clarify the randomness of protein sequences, we make a detailed analysis of a set of typical protein sequences representing each structural classes by using nonlinear prediction method. No deterministic structures are found in these protein sequences and this implies that they behave as random sequences. We also give an explanation to the controversial results obtained in previous investigations.

LZW-Kernel: fast kernel utilizing variable length code blocks from LZW compressors for protein sequence classification.

Science.gov (United States)

Filatov, Gleb; Bauwens, Bruno; Kertész-Farkas, Attila

2018-05-07

Bioinformatics studies often rely on similarity measures between sequence pairs, which often pose a bottleneck in large-scale sequence analysis. Here, we present a new convolutional kernel function for protein sequences called the LZW-Kernel. It is based on code words identified with the Lempel-Ziv-Welch (LZW) universal text compressor. The LZW-Kernel is an alignment-free method, it is always symmetric, is positive, always provides 1.0 for self-similarity and it can directly be used with Support Vector Machines (SVMs) in classification problems, contrary to normalized compression distance (NCD), which often violates the distance metric properties in practice and requires further techniques to be used with SVMs. The LZW-Kernel is a one-pass algorithm, which makes it particularly plausible for big data applications. Our experimental studies on remote protein homology detection and protein classification tasks reveal that the LZW-Kernel closely approaches the performance of the Local Alignment Kernel (LAK) and the SVM-pairwise method combined with Smith-Waterman (SW) scoring at a fraction of the time. Moreover, the LZW-Kernel outperforms the SVM-pairwise method when combined with BLAST scores, which indicates that the LZW code words might be a better basis for similarity measures than local alignment approximations found with BLAST. In addition, the LZW-Kernel outperforms n-gram based mismatch kernels, hidden Markov model based SAM and Fisher kernel, and protein family based PSI-BLAST, among others. Further advantages include the LZW-Kernel's reliance on a simple idea, its ease of implementation, and its high speed, three times faster than BLAST and several magnitudes faster than SW or LAK in our tests. LZW-Kernel is implemented as a standalone C code and is a free open-source program distributed under GPLv3 license and can be downloaded from https://github.com/kfattila/LZW-Kernel. akerteszfarkas@hse.ru. Supplementary data are available at Bioinformatics Online.

Nucleation phenomena in protein folding: the modulating role of protein sequence

International Nuclear Information System (INIS)

Travasso, Rui D M; FaIsca, Patricia F N; Gama, Margarida M Telo da

2007-01-01

For the vast majority of naturally occurring, small, single-domain proteins, folding is often described as a two-state process that lacks detectable intermediates. This observation has often been rationalized on the basis of a nucleation mechanism for protein folding whose basic premise is the idea that, after completion of a specific set of contacts forming the so-called folding nucleus, the native state is achieved promptly. Here we propose a methodology to identify folding nuclei in small lattice polymers and apply it to the study of protein molecules with a chain length of N = 48. To investigate the extent to which protein topology is a robust determinant of the nucleation mechanism, we compare the nucleation scenario of a native-centric model with that of a sequence-specific model sharing the same native fold. To evaluate the impact of the sequence's finer details in the nucleation mechanism, we consider the folding of two non-homologous sequences. We conclude that, in a sequence-specific model, the folding nucleus is, to some extent, formed by the most stable contacts in the protein and that the less stable linkages in the folding nucleus are solely determined by the fold's topology. We have also found that, independently of the protein sequence, the folding nucleus performs the same 'topological' function. This unifying feature of the nucleation mechanism results from the residues forming the folding nucleus being distributed along the protein chain in a similar and well-defined manner that is determined by the fold's topological features

WildSpan: mining structured motifs from protein sequences

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Chen Chien-Yu

2011-03-01

Full Text Available Abstract Background Automatic extraction of motifs from biological sequences is an important research problem in study of molecular biology. For proteins, it is desired to discover sequence motifs containing a large number of wildcard symbols, as the residues associated with functional sites are usually largely separated in sequences. Discovering such patterns is time-consuming because abundant combinations exist when long gaps (a gap consists of one or more successive wildcards are considered. Mining algorithms often employ constraints to narrow down the search space in order to increase efficiency. However, improper constraint models might degrade the sensitivity and specificity of the motifs discovered by computational methods. We previously proposed a new constraint model to handle large wildcard regions for discovering functional motifs of proteins. The patterns that satisfy the proposed constraint model are called W-patterns. A W-pattern is a structured motif that groups motif symbols into pattern blocks interleaved with large irregular gaps. Considering large gaps reflects the fact that functional residues are not always from a single region of protein sequences, and restricting motif symbols into clusters corresponds to the observation that short motifs are frequently present within protein families. To efficiently discover W-patterns for large-scale sequence annotation and function prediction, this paper first formally introduces the problem to solve and proposes an algorithm named WildSpan (sequential pattern mining across large wildcard regions that incorporates several pruning strategies to largely reduce the mining cost. Results WildSpan is shown to efficiently find W-patterns containing conserved residues that are far separated in sequences. We conducted experiments with two mining strategies, protein-based and family-based mining, to evaluate the usefulness of W-patterns and performance of WildSpan. The protein-based mining mode

A branch-heterogeneous model of protein evolution for efficient inference of ancestral sequences.

Science.gov (United States)

Groussin, M; Boussau, B; Gouy, M

2013-07-01

Most models of nucleotide or amino acid substitution used in phylogenetic studies assume that the evolutionary process has been homogeneous across lineages and that composition of nucleotides or amino acids has remained the same throughout the tree. These oversimplified assumptions are refuted by the observation that compositional variability characterizes extant biological sequences. Branch-heterogeneous models of protein evolution that account for compositional variability have been developed, but are not yet in common use because of the large number of parameters required, leading to high computational costs and potential overparameterization. Here, we present a new branch-nonhomogeneous and nonstationary model of protein evolution that captures more accurately the high complexity of sequence evolution. This model, henceforth called Correspondence and likelihood analysis (COaLA), makes use of a correspondence analysis to reduce the number of parameters to be optimized through maximum likelihood, focusing on most of the compositional variation observed in the data. The model was thoroughly tested on both simulated and biological data sets to show its high performance in terms of data fitting and CPU time. COaLA efficiently estimates ancestral amino acid frequencies and sequences, making it relevant for studies aiming at reconstructing and resurrecting ancestral amino acid sequences. Finally, we applied COaLA on a concatenate of universal amino acid sequences to confirm previous results obtained with a nonhomogeneous Bayesian model regarding the early pattern of adaptation to optimal growth temperature, supporting the mesophilic nature of the Last Universal Common Ancestor.

HomPPI: a class of sequence homology based protein-protein interface prediction methods

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Dobbs Drena

2011-06-01

Full Text Available Abstract Background Although homology-based methods are among the most widely used methods for predicting the structure and function of proteins, the question as to whether interface sequence conservation can be effectively exploited in predicting protein-protein interfaces has been a subject of debate. Results We studied more than 300,000 pair-wise alignments of protein sequences from structurally characterized protein complexes, including both obligate and transient complexes. We identified sequence similarity criteria required for accurate homology-based inference of interface residues in a query protein sequence. Based on these analyses, we developed HomPPI, a class of sequence homology-based methods for predicting protein-protein interface residues. We present two variants of HomPPI: (i NPS-HomPPI (Non partner-specific HomPPI, which can be used to predict interface residues of a query protein in the absence of knowledge of the interaction partner; and (ii PS-HomPPI (Partner-specific HomPPI, which can be used to predict the interface residues of a query protein with a specific target protein. Our experiments on a benchmark dataset of obligate homodimeric complexes show that NPS-HomPPI can reliably predict protein-protein interface residues in a given protein, with an average correlation coefficient (CC of 0.76, sensitivity of 0.83, and specificity of 0.78, when sequence homologs of the query protein can be reliably identified. NPS-HomPPI also reliably predicts the interface residues of intrinsically disordered proteins. Our experiments suggest that NPS-HomPPI is competitive with several state-of-the-art interface prediction servers including those that exploit the structure of the query proteins. The partner-specific classifier, PS-HomPPI can, on a large dataset of transient complexes, predict the interface residues of a query protein with a specific target, with a CC of 0.65, sensitivity of 0.69, and specificity of 0.70, when homologs of

Protein 3D structure computed from evolutionary sequence variation.

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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

Protein Function Prediction Based on Sequence and Structure Information

KAUST Repository

Smaili, Fatima Z.

2016-05-25

The number of available protein sequences in public databases is increasing exponentially. However, a significant fraction of these sequences lack functional annotation which is essential to our understanding of how biological systems and processes operate. In this master thesis project, we worked on inferring protein functions based on the primary protein sequence. In the approach we follow, 3D models are first constructed using I-TASSER. Functions are then deduced by structurally matching these predicted models, using global and local similarities, through three independent enzyme commission (EC) and gene ontology (GO) function libraries. The method was tested on 250 “hard” proteins, which lack homologous templates in both structure and function libraries. The results show that this method outperforms the conventional prediction methods based on sequence similarity or threading. Additionally, our method could be improved even further by incorporating protein-protein interaction information. Overall, the method we use provides an efficient approach for automated functional annotation of non-homologous proteins, starting from their sequence.

Simplifying complex sequence information: a PCP-consensus protein binds antibodies against all four Dengue serotypes.

Science.gov (United States)

Bowen, David M; Lewis, Jessica A; Lu, Wenzhe; Schein, Catherine H

2012-09-14

Designing proteins that reflect the natural variability of a pathogen is essential for developing novel vaccines and drugs. Flaviviruses, including Dengue (DENV) and West Nile (WNV), evolve rapidly and can "escape" neutralizing monoclonal antibodies by mutation. Designing antigens that represent many distinct strains is important for DENV, where infection with a strain from one of the four serotypes may lead to severe hemorrhagic disease on subsequent infection with a strain from another serotype. Here, a DENV physicochemical property (PCP)-consensus sequence was derived from 671 unique sequences from the Flavitrack database. PCP-consensus proteins for domain 3 of the envelope protein (EdomIII) were expressed from synthetic genes in Escherichia coli. The ability of the purified consensus proteins to bind polyclonal antibodies generated in response to infection with strains from each of the four DENV serotypes was determined. The initial consensus protein bound antibodies from DENV-1-3 in ELISA and Western blot assays. This sequence was altered in 3 steps to incorporate regions of maximum variability, identified as significant changes in the PCPs, characteristic of DENV-4 strains. The final protein was recognized by antibodies against all four serotypes. Two amino acids essential for efficient binding to all DENV antibodies are part of a discontinuous epitope previously defined for a neutralizing monoclonal antibody. The PCP-consensus method can significantly reduce the number of experiments required to define a multivalent antigen, which is particularly important when dealing with pathogens that must be tested at higher biosafety levels. Copyright © 2012 Elsevier Ltd. All rights reserved.

GuiTope: an application for mapping random-sequence peptides to protein sequences.

Science.gov (United States)

Halperin, Rebecca F; Stafford, Phillip; Emery, Jack S; Navalkar, Krupa Arun; Johnston, Stephen Albert

2012-01-03

Random-sequence peptide libraries are a commonly used tool to identify novel ligands for binding antibodies, other proteins, and small molecules. It is often of interest to compare the selected peptide sequences to the natural protein binding partners to infer the exact binding site or the importance of particular residues. The ability to search a set of sequences for similarity to a set of peptides may sometimes enable the prediction of an antibody epitope or a novel binding partner. We have developed a software application designed specifically for this task. GuiTope provides a graphical user interface for aligning peptide sequences to protein sequences. All alignment parameters are accessible to the user including the ability to specify the amino acid frequency in the peptide library; these frequencies often differ significantly from those assumed by popular alignment programs. It also includes a novel feature to align di-peptide inversions, which we have found improves the accuracy of antibody epitope prediction from peptide microarray data and shows utility in analyzing phage display datasets. Finally, GuiTope can randomly select peptides from a given library to estimate a null distribution of scores and calculate statistical significance. GuiTope provides a convenient method for comparing selected peptide sequences to protein sequences, including flexible alignment parameters, novel alignment features, ability to search a database, and statistical significance of results. The software is available as an executable (for PC) at http://www.immunosignature.com/software and ongoing updates and source code will be available at sourceforge.net.

GuiTope: an application for mapping random-sequence peptides to protein sequences

Directory of Open Access Journals (Sweden)

Halperin Rebecca F

2012-01-01

Full Text Available Abstract Background Random-sequence peptide libraries are a commonly used tool to identify novel ligands for binding antibodies, other proteins, and small molecules. It is often of interest to compare the selected peptide sequences to the natural protein binding partners to infer the exact binding site or the importance of particular residues. The ability to search a set of sequences for similarity to a set of peptides may sometimes enable the prediction of an antibody epitope or a novel binding partner. We have developed a software application designed specifically for this task. Results GuiTope provides a graphical user interface for aligning peptide sequences to protein sequences. All alignment parameters are accessible to the user including the ability to specify the amino acid frequency in the peptide library; these frequencies often differ significantly from those assumed by popular alignment programs. It also includes a novel feature to align di-peptide inversions, which we have found improves the accuracy of antibody epitope prediction from peptide microarray data and shows utility in analyzing phage display datasets. Finally, GuiTope can randomly select peptides from a given library to estimate a null distribution of scores and calculate statistical significance. Conclusions GuiTope provides a convenient method for comparing selected peptide sequences to protein sequences, including flexible alignment parameters, novel alignment features, ability to search a database, and statistical significance of results. The software is available as an executable (for PC at http://www.immunosignature.com/software and ongoing updates and source code will be available at sourceforge.net.

Dynamics of domain coverage of the protein sequence universe

Science.gov (United States)

2012-01-01

Background The currently known protein sequence space consists of millions of sequences in public databases and is rapidly expanding. Assigning sequences to families leads to a better understanding of protein function and the nature of the protein universe. However, a large portion of the current protein space remains unassigned and is referred to as its “dark matter”. Results Here we suggest that true size of “dark matter” is much larger than stated by current definitions. We propose an approach to reducing the size of “dark matter” by identifying and subtracting regions in protein sequences that are not likely to contain any domain. Conclusions Recent improvements in computational domain modeling result in a decrease, albeit slowly, in the relative size of “dark matter”; however, its absolute size increases substantially with the growth of sequence data. PMID:23157439

Dynamics of domain coverage of the protein sequence universe

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Rekapalli Bhanu

2012-11-01

Full Text Available Abstract Background The currently known protein sequence space consists of millions of sequences in public databases and is rapidly expanding. Assigning sequences to families leads to a better understanding of protein function and the nature of the protein universe. However, a large portion of the current protein space remains unassigned and is referred to as its “dark matter”. Results Here we suggest that true size of “dark matter” is much larger than stated by current definitions. We propose an approach to reducing the size of “dark matter” by identifying and subtracting regions in protein sequences that are not likely to contain any domain. Conclusions Recent improvements in computational domain modeling result in a decrease, albeit slowly, in the relative size of “dark matter”; however, its absolute size increases substantially with the growth of sequence data.

MIPS: a database for genomes and protein sequences.

Science.gov (United States)

Mewes, H W; Frishman, D; Güldener, U; Mannhaupt, G; Mayer, K; Mokrejs, M; Morgenstern, B; Münsterkötter, M; Rudd, S; Weil, B

2002-01-01

The Munich Information Center for Protein Sequences (MIPS-GSF, Neuherberg, Germany) continues to provide genome-related information in a systematic way. MIPS supports both national and European sequencing and functional analysis projects, develops and maintains automatically generated and manually annotated genome-specific databases, develops systematic classification schemes for the functional annotation of protein sequences, and provides tools for the comprehensive analysis of protein sequences. This report updates the information on the yeast genome (CYGD), the Neurospora crassa genome (MNCDB), the databases for the comprehensive set of genomes (PEDANT genomes), the database of annotated human EST clusters (HIB), the database of complete cDNAs from the DHGP (German Human Genome Project), as well as the project specific databases for the GABI (Genome Analysis in Plants) and HNB (Helmholtz-Netzwerk Bioinformatik) networks. The Arabidospsis thaliana database (MATDB), the database of mitochondrial proteins (MITOP) and our contribution to the PIR International Protein Sequence Database have been described elsewhere [Schoof et al. (2002) Nucleic Acids Res., 30, 91-93; Scharfe et al. (2000) Nucleic Acids Res., 28, 155-158; Barker et al. (2001) Nucleic Acids Res., 29, 29-32]. All databases described, the protein analysis tools provided and the detailed descriptions of our projects can be accessed through the MIPS World Wide Web server (http://mips.gsf.de).

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

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Jinjian Jiang

2017-07-01

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

A correspondence between solution-state dynamics of an individual protein and the sequence and conformational diversity of its family.

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Gregory D Friedland

2009-05-01

Full Text Available Conformational ensembles are increasingly recognized as a useful representation to describe fundamental relationships between protein structure, dynamics and function. Here we present an ensemble of ubiquitin in solution that is created by sampling conformational space without experimental information using "Backrub" motions inspired by alternative conformations observed in sub-Angstrom resolution crystal structures. Backrub-generated structures are then selected to produce an ensemble that optimizes agreement with nuclear magnetic resonance (NMR Residual Dipolar Couplings (RDCs. Using this ensemble, we probe two proposed relationships between properties of protein ensembles: (i a link between native-state dynamics and the conformational heterogeneity observed in crystal structures, and (ii a relation between dynamics of an individual protein and the conformational variability explored by its natural family. We show that the Backrub motional mechanism can simultaneously explore protein native-state dynamics measured by RDCs, encompass the conformational variability present in ubiquitin complex structures and facilitate sampling of conformational and sequence variability matching those occurring in the ubiquitin protein family. Our results thus support an overall relation between protein dynamics and conformational changes enabling sequence changes in evolution. More practically, the presented method can be applied to improve protein design predictions by accounting for intrinsic native-state dynamics.

Gene Unprediction with Spurio: A tool to identify spurious protein sequences.

Science.gov (United States)

Höps, Wolfram; Jeffryes, Matt; Bateman, Alex

2018-01-01

We now have access to the sequences of tens of millions of proteins. These protein sequences are essential for modern molecular biology and computational biology. The vast majority of protein sequences are derived from gene prediction tools and have no experimental supporting evidence for their translation.  Despite the increasing accuracy of gene prediction tools there likely exists a large number of spurious protein predictions in the sequence databases.  We have developed the Spurio tool to help identify spurious protein predictions in prokaryotes.  Spurio searches the query protein sequence against a prokaryotic nucleotide database using tblastn and identifies homologous sequences. The tblastn matches are used to score the query sequence's likelihood of being a spurious protein prediction using a Gaussian process model. The most informative feature is the appearance of stop codons within the presumed translation of homologous DNA sequences. Benchmarking shows that the Spurio tool is able to distinguish spurious from true proteins. However, transposon proteins are prone to be predicted as spurious because of the frequency of degraded homologs found in the DNA sequence databases. Our initial experiments suggest that less than 1% of the proteins in the UniProtKB sequence database are likely to be spurious and that Spurio is able to identify over 60 times more spurious proteins than the AntiFam resource. The Spurio software and source code is available under an MIT license at the following URL: https://bitbucket.org/bateman-group/spurio.

Structure and Sequence Search on Aptamer-Protein Docking

Science.gov (United States)

Xiao, Jiajie; Bonin, Keith; Guthold, Martin; Salsbury, Freddie

2015-03-01

Interactions between proteins and deoxyribonucleic acid (DNA) play a significant role in the living systems, especially through gene regulation. However, short nucleic acids sequences (aptamers) with specific binding affinity to specific proteins exhibit clinical potential as therapeutics. Our capillary and gel electrophoresis selection experiments show that specific sequences of aptamers can be selected that bind specific proteins. Computationally, given the experimentally-determined structure and sequence of a thrombin-binding aptamer, we can successfully dock the aptamer onto thrombin in agreement with experimental structures of the complex. In order to further study the conformational flexibility of this thrombin-binding aptamer and to potentially develop a predictive computational model of aptamer-binding, we use GPU-enabled molecular dynamics simulations to both examine the conformational flexibility of the aptamer in the absence of binding to thrombin, and to determine our ability to fold an aptamer. This study should help further de-novo predictions of aptamer sequences by enabling the study of structural and sequence-dependent effects on aptamer-protein docking specificity.

AlignMe—a membrane protein sequence alignment web server

Science.gov (United States)

Stamm, Marcus; Staritzbichler, René; Khafizov, Kamil; Forrest, Lucy R.

2014-01-01

We present a web server for pair-wise alignment of membrane protein sequences, using the program AlignMe. The server makes available two operational modes of AlignMe: (i) sequence to sequence alignment, taking two sequences in fasta format as input, combining information about each sequence from multiple sources and producing a pair-wise alignment (PW mode); and (ii) alignment of two multiple sequence alignments to create family-averaged hydropathy profile alignments (HP mode). For the PW sequence alignment mode, four different optimized parameter sets are provided, each suited to pairs of sequences with a specific similarity level. These settings utilize different types of inputs: (position-specific) substitution matrices, secondary structure predictions and transmembrane propensities from transmembrane predictions or hydrophobicity scales. In the second (HP) mode, each input multiple sequence alignment is converted into a hydrophobicity profile averaged over the provided set of sequence homologs; the two profiles are then aligned. The HP mode enables qualitative comparison of transmembrane topologies (and therefore potentially of 3D folds) of two membrane proteins, which can be useful if the proteins have low sequence similarity. In summary, the AlignMe web server provides user-friendly access to a set of tools for analysis and comparison of membrane protein sequences. Access is available at http://www.bioinfo.mpg.de/AlignMe PMID:24753425

The relationship of protein conservation and sequence length

Directory of Open Access Journals (Sweden)

Panchenko Anna R

2002-11-01

Full Text Available Abstract Background In general, the length of a protein sequence is determined by its function and the wide variance in the lengths of an organism's proteins reflects the diversity of specific functional roles for these proteins. However, additional evolutionary forces that affect the length of a protein may be revealed by studying the length distributions of proteins evolving under weaker functional constraints. Results We performed sequence comparisons to distinguish highly conserved and poorly conserved proteins from the bacterium Escherichia coli, the archaeon Archaeoglobus fulgidus, and the eukaryotes Saccharomyces cerevisiae, Drosophila melanogaster, and Homo sapiens. For all organisms studied, the conserved and nonconserved proteins have strikingly different length distributions. The conserved proteins are, on average, longer than the poorly conserved ones, and the length distributions for the poorly conserved proteins have a relatively narrow peak, in contrast to the conserved proteins whose lengths spread over a wider range of values. For the two prokaryotes studied, the poorly conserved proteins approximate the minimal length distribution expected for a diverse range of structural folds. Conclusions There is a relationship between protein conservation and sequence length. For all the organisms studied, there seems to be a significant evolutionary trend favoring shorter proteins in the absence of other, more specific functional constraints.

MIPS: a database for protein sequences and complete genomes.

Science.gov (United States)

Mewes, H W; Hani, J; Pfeiffer, F; Frishman, D

1998-01-01

The MIPS group [Munich Information Center for Protein Sequences of the German National Center for Environment and Health (GSF)] at the Max-Planck-Institute for Biochemistry, Martinsried near Munich, Germany, is involved in a number of data collection activities, including a comprehensive database of the yeast genome, a database reflecting the progress in sequencing the Arabidopsis thaliana genome, the systematic analysis of other small genomes and the collection of protein sequence data within the framework of the PIR-International Protein Sequence Database (described elsewhere in this volume). Through its WWW server (http://www.mips.biochem.mpg.de ) MIPS provides access to a variety of generic databases, including a database of protein families as well as automatically generated data by the systematic application of sequence analysis algorithms. The yeast genome sequence and its related information was also compiled on CD-ROM to provide dynamic interactive access to the 16 chromosomes of the first eukaryotic genome unraveled. PMID:9399795

Can Natural Proteins Designed with ‘Inverted’ Peptide Sequences Adopt Native-Like Protein Folds?

Science.gov (United States)

Sridhar, Settu; Guruprasad, Kunchur

2014-01-01

We have carried out a systematic computational analysis on a representative dataset of proteins of known three-dimensional structure, in order to evaluate whether it would possible to ‘swap’ certain short peptide sequences in naturally occurring proteins with their corresponding ‘inverted’ peptides and generate ‘artificial’ proteins that are predicted to retain native-like protein fold. The analysis of 3,967 representative proteins from the Protein Data Bank revealed 102,677 unique identical inverted peptide sequence pairs that vary in sequence length between 5–12 and 18 amino acid residues. Our analysis illustrates with examples that such ‘artificial’ proteins may be generated by identifying peptides with ‘similar structural environment’ and by using comparative protein modeling and validation studies. Our analysis suggests that natural proteins may be tolerant to accommodating such peptides. PMID:25210740

The SWISS-PROT protein sequence data bank: current status.

OpenAIRE

Bairoch, A; Boeckmann, B

1994-01-01

SWISS-PROT is an annotated protein sequence database established in 1986 and maintained collaboratively, since 1988, by the Department of Medical Biochemistry of the University of Geneva and the EMBL Data Library. The SWISS-PROT protein sequence data bank consist of sequence entries. Sequence entries are composed of different lines types, each with their own format. For standardization purposes the format of SWISS-PROT follows as closely as possible that of the EMBL Nucleotide Sequence Databa...

Partial sequence determination of metabolically labeled radioactive proteins and peptides

International Nuclear Information System (INIS)

Anderson, C.W.

1982-01-01

The author has used the sequence analysis of radioactive proteins and peptides to approach several problems during the past few years. They, in collaboration with others, have mapped precisely several adenovirus proteins with respect to the nucleotide sequence of the adenovirus genome; identified hitherto missed proteins encoded by bacteriophage MS2 and by simian virus 40; analyzed the aminoterminal maturation of several virus proteins; determined the cleavage sites for processing of the poliovirus polyprotein; and analyzed the mechanism of frameshifting by excess normal tRNAs during cell-free protein synthesis. This chapter is designed to aid those without prior experience at protein sequence determinations. It is based primarily on the experience gained in the studies cited above, which made use of the Beckman 890 series automated protein sequencers

Taxonomic colouring of phylogenetic trees of protein sequences

Directory of Open Access Journals (Sweden)

Andrade-Navarro Miguel A

2006-02-01

Full Text Available Abstract Background Phylogenetic analyses of protein families are used to define the evolutionary relationships between homologous proteins. The interpretation of protein-sequence phylogenetic trees requires the examination of the taxonomic properties of the species associated to those sequences. However, there is no online tool to facilitate this interpretation, for example, by automatically attaching taxonomic information to the nodes of a tree, or by interactively colouring the branches of a tree according to any combination of taxonomic divisions. This is especially problematic if the tree contains on the order of hundreds of sequences, which, given the accelerated increase in the size of the protein sequence databases, is a situation that is becoming common. Results We have developed PhyloView, a web based tool for colouring phylogenetic trees upon arbitrary taxonomic properties of the species represented in a protein sequence phylogenetic tree. Provided that the tree contains SwissProt, SpTrembl, or GenBank protein identifiers, the tool retrieves the taxonomic information from the corresponding database. A colour picker displays a summary of the findings and allows the user to associate colours to the leaves of the tree according to any number of taxonomic partitions. Then, the colours are propagated to the branches of the tree. Conclusion PhyloView can be used at http://www.ogic.ca/projects/phyloview/. A tutorial, the software with documentation, and GPL licensed source code, can be accessed at the same web address.

Semi-Supervised Learning for Classification of Protein Sequence Data

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Brian R. King

2008-01-01

Full Text Available Protein sequence data continue to become available at an exponential rate. Annotation of functional and structural attributes of these data lags far behind, with only a small fraction of the data understood and labeled by experimental methods. Classification methods that are based on semi-supervised learning can increase the overall accuracy of classifying partly labeled data in many domains, but very few methods exist that have shown their effect on protein sequence classification. We show how proven methods from text classification can be applied to protein sequence data, as we consider both existing and novel extensions to the basic methods, and demonstrate restrictions and differences that must be considered. We demonstrate comparative results against the transductive support vector machine, and show superior results on the most difficult classification problems. Our results show that large repositories of unlabeled protein sequence data can indeed be used to improve predictive performance, particularly in situations where there are fewer labeled protein sequences available, and/or the data are highly unbalanced in nature.

Sequence motifs in MADS transcription factors responsible for specificity and diversification of protein-protein interaction.

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Aalt D J van Dijk

Full Text Available Protein sequences encompass tertiary structures and contain information about specific molecular interactions, which in turn determine biological functions of proteins. Knowledge about how protein sequences define interaction specificity is largely missing, in particular for paralogous protein families with high sequence similarity, such as the plant MADS domain transcription factor family. In comparison to the situation in mammalian species, this important family of transcription regulators has expanded enormously in plant species and contains over 100 members in the model plant species Arabidopsis thaliana. Here, we provide insight into the mechanisms that determine protein-protein interaction specificity for the Arabidopsis MADS domain transcription factor family, using an integrated computational and experimental approach. Plant MADS proteins have highly similar amino acid sequences, but their dimerization patterns vary substantially. Our computational analysis uncovered small sequence regions that explain observed differences in dimerization patterns with reasonable accuracy. Furthermore, we show the usefulness of the method for prediction of MADS domain transcription factor interaction networks in other plant species. Introduction of mutations in the predicted interaction motifs demonstrated that single amino acid mutations can have a large effect and lead to loss or gain of specific interactions. In addition, various performed bioinformatics analyses shed light on the way evolution has shaped MADS domain transcription factor interaction specificity. Identified protein-protein interaction motifs appeared to be strongly conserved among orthologs, indicating their evolutionary importance. We also provide evidence that mutations in these motifs can be a source for sub- or neo-functionalization. The analyses presented here take us a step forward in understanding protein-protein interactions and the interplay between protein sequences and

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

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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.

Predicting the tolerated sequences for proteins and protein interfaces using RosettaBackrub flexible backbone design.

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Colin A Smith

Full Text Available Predicting the set of sequences that are tolerated by a protein or protein interface, while maintaining a desired function, is useful for characterizing protein interaction specificity and for computationally designing sequence libraries to engineer proteins with new functions. Here we provide a general method, a detailed set of protocols, and several benchmarks and analyses for estimating tolerated sequences using flexible backbone protein design implemented in the Rosetta molecular modeling software suite. The input to the method is at least one experimentally determined three-dimensional protein structure or high-quality model. The starting structure(s are expanded or refined into a conformational ensemble using Monte Carlo simulations consisting of backrub backbone and side chain moves in Rosetta. The method then uses a combination of simulated annealing and genetic algorithm optimization methods to enrich for low-energy sequences for the individual members of the ensemble. To emphasize certain functional requirements (e.g. forming a binding interface, interactions between and within parts of the structure (e.g. domains can be reweighted in the scoring function. Results from each backbone structure are merged together to create a single estimate for the tolerated sequence space. We provide an extensive description of the protocol and its parameters, all source code, example analysis scripts and three tests applying this method to finding sequences predicted to stabilize proteins or protein interfaces. The generality of this method makes many other applications possible, for example stabilizing interactions with small molecules, DNA, or RNA. Through the use of within-domain reweighting and/or multistate design, it may also be possible to use this method to find sequences that stabilize particular protein conformations or binding interactions over others.

Worldwide genetic variability of the Duffy binding protein: insights into Plasmodium vivax vaccine development.

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Nóbrega de Sousa, Taís; Carvalho, Luzia Helena; Alves de Brito, Cristiana Ferreira

2011-01-01

The dependence of Plasmodium vivax on invasion mediated by Duffy binding protein (DBP) makes this protein a prime candidate for development of a vaccine. However, the development of a DBP-based vaccine might be hampered by the high variability of the protein ligand (DBP(II)), known to bias the immune response toward a specific DBP variant. Here, the hypothesis being investigated is that the analysis of the worldwide DBP(II) sequences will allow us to determine the minimum number of haplotypes (MNH) to be included in a DBP-based vaccine of broad coverage. For that, all DBP(II) sequences available were compiled and MNH was based on the most frequent nonsynonymous single nucleotide polymorphisms, the majority mapped on B and T cell epitopes. A preliminary analysis of DBP(II) genetic diversity from eight malaria-endemic countries estimated that a number between two to six DBP haplotypes (17 in total) would target at least 50% of parasite population circulating in each endemic region. Aiming to avoid region-specific haplotypes, we next analyzed the MNH that broadly cover worldwide parasite population. The results demonstrated that seven haplotypes would be required to cover around 60% of DBP(II) sequences available. Trying to validate these selected haplotypes per country, we found that five out of the eight countries will be covered by the MNH (67% of parasite populations, range 48-84%). In addition, to identify related subgroups of DBP(II) sequences we used a Bayesian clustering algorithm. The algorithm grouped all DBP(II) sequences in six populations that were independent of geographic origin, with ancestral populations present in different proportions in each country. In conclusion, in this first attempt to undertake a global analysis about DBP(II) variability, the results suggest that the development of DBP-based vaccine should consider multi-haplotype strategies; otherwise a putative P. vivax vaccine may not target some parasite populations.

CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction

KAUST Repository

Cui, Xuefeng

2016-06-15

Motivation: Protein homology detection, a fundamental problem in computational biology, is an indispensable step toward predicting protein structures and understanding protein functions. Despite the advances in recent decades on sequence alignment, threading and alignment-free methods, protein homology detection remains a challenging open problem. Recently, network methods that try to find transitive paths in the protein structure space demonstrate the importance of incorporating network information of the structure space. Yet, current methods merge the sequence space and the structure space into a single space, and thus introduce inconsistency in combining different sources of information. Method: We present a novel network-based protein homology detection method, CMsearch, based on cross-modal learning. Instead of exploring a single network built from the mixture of sequence and structure space information, CMsearch builds two separate networks to represent the sequence space and the structure space. It then learns sequence–structure correlation by simultaneously taking sequence information, structure information, sequence space information and structure space information into consideration. Results: We tested CMsearch on two challenging tasks, protein homology detection and protein structure prediction, by querying all 8332 PDB40 proteins. Our results demonstrate that CMsearch is insensitive to the similarity metrics used to define the sequence and the structure spaces. By using HMM–HMM alignment as the sequence similarity metric, CMsearch clearly outperforms state-of-the-art homology detection methods and the CASP-winning template-based protein structure prediction methods.

EST2Prot: Mapping EST sequences to proteins

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Lin David M

2006-03-01

Full Text Available Abstract Background EST libraries are used in various biological studies, from microarray experiments to proteomic and genetic screens. These libraries usually contain many uncharacterized ESTs that are typically ignored since they cannot be mapped to known genes. Consequently, new discoveries are possibly overlooked. Results We describe a system (EST2Prot that uses multiple elements to map EST sequences to their corresponding protein products. EST2Prot uses UniGene clusters, substring analysis, information about protein coding regions in existing DNA sequences and protein database searches to detect protein products related to a query EST sequence. Gene Ontology terms, Swiss-Prot keywords, and protein similarity data are used to map the ESTs to functional descriptors. Conclusion EST2Prot extends and significantly enriches the popular UniGene mapping by utilizing multiple relations between known biological entities. It produces a mapping between ESTs and proteins in real-time through a simple web-interface. The system is part of the Biozon database and is accessible at http://biozon.org/tools/est/.

Adaptive compressive learning for prediction of protein-protein interactions from primary sequence.

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Zhang, Ya-Nan; Pan, Xiao-Yong; Huang, Yan; Shen, Hong-Bin

2011-08-21

Protein-protein interactions (PPIs) play an important role in biological processes. Although much effort has been devoted to the identification of novel PPIs by integrating experimental biological knowledge, there are still many difficulties because of lacking enough protein structural and functional information. It is highly desired to develop methods based only on amino acid sequences for predicting PPIs. However, sequence-based predictors are often struggling with the high-dimensionality causing over-fitting and high computational complexity problems, as well as the redundancy of sequential feature vectors. In this paper, a novel computational approach based on compressed sensing theory is proposed to predict yeast Saccharomyces cerevisiae PPIs from primary sequence and has achieved promising results. The key advantage of the proposed compressed sensing algorithm is that it can compress the original high-dimensional protein sequential feature vector into a much lower but more condensed space taking the sparsity property of the original signal into account. What makes compressed sensing much more attractive in protein sequence analysis is its compressed signal can be reconstructed from far fewer measurements than what is usually considered necessary in traditional Nyquist sampling theory. Experimental results demonstrate that proposed compressed sensing method is powerful for analyzing noisy biological data and reducing redundancy in feature vectors. The proposed method represents a new strategy of dealing with high-dimensional protein discrete model and has great potentiality to be extended to deal with many other complicated biological systems. Copyright © 2011 Elsevier Ltd. All rights reserved.

A combinatorial approach to detect coevolved amino acid networks in protein families of variable divergence.

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Julie Baussand

2009-09-01

Full Text Available Communication between distant sites often defines the biological role of a protein: amino acid long-range interactions are as important in binding specificity, allosteric regulation and conformational change as residues directly contacting the substrate. The maintaining of functional and structural coupling of long-range interacting residues requires coevolution of these residues. Networks of interaction between coevolved residues can be reconstructed, and from the networks, one can possibly derive insights into functional mechanisms for the protein family. We propose a combinatorial method for mapping conserved networks of amino acid interactions in a protein which is based on the analysis of a set of aligned sequences, the associated distance tree and the combinatorics of its subtrees. The degree of coevolution of all pairs of coevolved residues is identified numerically, and networks are reconstructed with a dedicated clustering algorithm. The method drops the constraints on high sequence divergence limiting the range of applicability of the statistical approaches previously proposed. We apply the method to four protein families where we show an accurate detection of functional networks and the possibility to treat sets of protein sequences of variable divergence.

Design of Protein Multi-specificity Using an Independent Sequence Search Reduces the Barrier to Low Energy Sequences.

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Alexander M Sevy

2015-07-01

Full Text Available Computational protein design has found great success in engineering proteins for thermodynamic stability, binding specificity, or enzymatic activity in a 'single state' design (SSD paradigm. Multi-specificity design (MSD, on the other hand, involves considering the stability of multiple protein states simultaneously. We have developed a novel MSD algorithm, which we refer to as REstrained CONvergence in multi-specificity design (RECON. The algorithm allows each state to adopt its own sequence throughout the design process rather than enforcing a single sequence on all states. Convergence to a single sequence is encouraged through an incrementally increasing convergence restraint for corresponding positions. Compared to MSD algorithms that enforce (constrain an identical sequence on all states the energy landscape is simplified, which accelerates the search drastically. As a result, RECON can readily be used in simulations with a flexible protein backbone. We have benchmarked RECON on two design tasks. First, we designed antibodies derived from a common germline gene against their diverse targets to assess recovery of the germline, polyspecific sequence. Second, we design "promiscuous", polyspecific proteins against all binding partners and measure recovery of the native sequence. We show that RECON is able to efficiently recover native-like, biologically relevant sequences in this diverse set of protein complexes.

Nonlinear analysis of sequence symmetry of beta-trefoil family proteins

Energy Technology Data Exchange (ETDEWEB)

Li Mingfeng [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China); Huang Yanzhao [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China); Xu Ruizhen [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China); Xiao Yi [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China)]. E-mail: yxiao@mail.hust.edu.cn

2005-07-01

The tertiary structures of proteins of beta-trefoil family have three-fold quasi-symmetry while their amino acid sequences appear almost at random. In the present paper we show that these amino acid sequences have hidden symmetries in fact and furthermore the degrees of these hidden symmetries are the same as those of their tertiary structures. We shall present a modified recurrence plot to reveal hidden symmetries in protein sequences. Our results can explain the contradiction in sequence-structure relations of proteins of beta-trefoil family.

Correlated mutations in protein sequences: Phylogenetic and structural effects

Energy Technology Data Exchange (ETDEWEB)

Lapedes, A.S. [Los Alamos National Lab., NM (United States). Theoretical Div.]|[Santa Fe Inst., NM (United States); Giraud, B.G. [C.E.N. Saclay, Gif/Yvette (France). Service Physique Theorique; Liu, L.C. [Los Alamos National Lab., NM (United States). Theoretical Div.; Stormo, G.D. [Univ. of Colorado, Boulder, CO (United States). Dept. of Molecular, Cellular and Developmental Biology

1998-12-01

Covariation analysis of sets of aligned sequences for RNA molecules is relatively successful in elucidating RNA secondary structure, as well as some aspects of tertiary structure. Covariation analysis of sets of aligned sequences for protein molecules is successful in certain instances in elucidating certain structural and functional links, but in general, pairs of sites displaying highly covarying mutations in protein sequences do not necessarily correspond to sites that are spatially close in the protein structure. In this paper the authors identify two reasons why naive use of covariation analysis for protein sequences fails to reliably indicate sequence positions that are spatially proximate. The first reason involves the bias introduced in calculation of covariation measures due to the fact that biological sequences are generally related by a non-trivial phylogenetic tree. The authors present a null-model approach to solve this problem. The second reason involves linked chains of covariation which can result in pairs of sites displaying significant covariation even though they are not spatially proximate. They present a maximum entropy solution to this classic problem of causation versus correlation. The methodologies are validated in simulation.

Amino acid and structural variability of Yersinia pestis LcrV protein

Energy Technology Data Exchange (ETDEWEB)

Anisimov, A P; Dentovskaya, S V; Panfertsev, E A; Svetoch, T E; Kopylov, P K; Segelke, B W; Zemla, A; Telepnev, M V; Motin, V L

2009-11-09

The LcrV protein is a multifunctional virulence factor and protective antigen of the plague bacterium which is generally conserved between the epidemic strains of Yersinia pestis. They investigated the diversity in the LcrV sequences among non-epidemic Y. pestis strains which have a limited virulence in selected animal models and for humans. Sequencing of lcrV genes from ten Y. pestis strains belonging to different phylogenetic groups (subspecies) showed that the LcrV proteins possess four major variable hotspots at positions 18, 72, 273, and 324-326. These major variations, together with other minor substitutions in amino acid sequences, allowed them to classify the LcrV alleles into five sequence types (A-E). They observed that the strains of different Y. pestis subspecies can have the same typ of LcrV, and different types of LcrV can exist within the same natural plague focus. The LcrV polymorphisms were structurally analyzed by comparing the modeled structures of LcrV from all available strains. All changes except one occurred either in flexible regions or on the surface of the protein, but local chemical properties (i.e. those of a hydrophobic, hydrophilic, amphipathic, or charged nature) were conserved across all of the strains. Polymorphisms in flexible and surface regions are likely subject to less selective pressure, and have a limited impact on the structure. In contrast, the substitution of tryptophan at position 113 with either glutamic acid or glycine likely has a serious influence on the regional structure of the protein, and these mutations might have an effect on the function of LcrV. The polymorphisms at positions 18, 72 and 273 were accountable for differences in oligomerization of LcrV. The importance of the latter property in emergence of epidemic strains of Y. pestis during evolution of this pathogen will need to be further investigated.

Deep sequencing methods for protein engineering and design.

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Wrenbeck, Emily E; Faber, Matthew S; Whitehead, Timothy A

2017-08-01

The advent of next-generation sequencing (NGS) has revolutionized protein science, and the development of complementary methods enabling NGS-driven protein engineering have followed. In general, these experiments address the functional consequences of thousands of protein variants in a massively parallel manner using genotype-phenotype linked high-throughput functional screens followed by DNA counting via deep sequencing. We highlight the use of information rich datasets to engineer protein molecular recognition. Examples include the creation of multiple dual-affinity Fabs targeting structurally dissimilar epitopes and engineering of a broad germline-targeted anti-HIV-1 immunogen. Additionally, we highlight the generation of enzyme fitness landscapes for conducting fundamental studies of protein behavior and evolution. We conclude with discussion of technological advances. Copyright © 2016 Elsevier Ltd. All rights reserved.

Biophysical and structural considerations for protein sequence evolution

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Grahnen Johan A

2011-12-01

Full Text Available Abstract Background Protein sequence evolution is constrained by the biophysics of folding and function, causing interdependence between interacting sites in the sequence. However, current site-independent models of sequence evolutions do not take this into account. Recent attempts to integrate the influence of structure and biophysics into phylogenetic models via statistical/informational approaches have not resulted in expected improvements in model performance. This suggests that further innovations are needed for progress in this field. Results Here we develop a coarse-grained physics-based model of protein folding and binding function, and compare it to a popular informational model. We find that both models violate the assumption of the native sequence being close to a thermodynamic optimum, causing directional selection away from the native state. Sampling and simulation show that the physics-based model is more specific for fold-defining interactions that vary less among residue type. The informational model diffuses further in sequence space with fewer barriers and tends to provide less support for an invariant sites model, although amino acid substitutions are generally conservative. Both approaches produce sequences with natural features like dN/dS Conclusions Simple coarse-grained models of protein folding can describe some natural features of evolving proteins but are currently not accurate enough to use in evolutionary inference. This is partly due to improper packing of the hydrophobic core. We suggest possible improvements on the representation of structure, folding energy, and binding function, as regards both native and non-native conformations, and describe a large number of possible applications for such a model.

MIPS: a database for protein sequences, homology data and yeast genome information.

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Mewes, H W; Albermann, K; Heumann, K; Liebl, S; Pfeiffer, F

1997-01-01

The MIPS group (Martinsried Institute for Protein Sequences) at the Max-Planck-Institute for Biochemistry, Martinsried near Munich, Germany, collects, processes and distributes protein sequence data within the framework of the tripartite association of the PIR-International Protein Sequence Database (,). MIPS contributes nearly 50% of the data input to the PIR-International Protein Sequence Database. The database is distributed on CD-ROM together with PATCHX, an exhaustive supplement of unique, unverified protein sequences from external sources compiled by MIPS. Through its WWW server (http://www.mips.biochem.mpg.de/ ) MIPS permits internet access to sequence databases, homology data and to yeast genome information. (i) Sequence similarity results from the FASTA program () are stored in the FASTA database for all proteins from PIR-International and PATCHX. The database is dynamically maintained and permits instant access to FASTA results. (ii) Starting with FASTA database queries, proteins have been classified into families and superfamilies (PROT-FAM). (iii) The HPT (hashed position tree) data structure () developed at MIPS is a new approach for rapid sequence and pattern searching. (iv) MIPS provides access to the sequence and annotation of the complete yeast genome (), the functional classification of yeast genes (FunCat) and its graphical display, the 'Genome Browser' (). A CD-ROM based on the JAVA programming language providing dynamic interactive access to the yeast genome and the related protein sequences has been compiled and is available on request. PMID:9016498

Formatt: Correcting protein multiple structural alignments by incorporating sequence alignment

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Daniels Noah M

2012-10-01

Full Text Available Abstract Background The quality of multiple protein structure alignments are usually computed and assessed based on geometric functions of the coordinates of the backbone atoms from the protein chains. These purely geometric methods do not utilize directly protein sequence similarity, and in fact, determining the proper way to incorporate sequence similarity measures into the construction and assessment of protein multiple structure alignments has proved surprisingly difficult. Results We present Formatt, a multiple structure alignment based on the Matt purely geometric multiple structure alignment program, that also takes into account sequence similarity when constructing alignments. We show that Formatt outperforms Matt and other popular structure alignment programs on the popular HOMSTRAD benchmark. For the SABMark twilight zone benchmark set that captures more remote homology, Formatt and Matt outperform other programs; depending on choice of embedded sequence aligner, Formatt produces either better sequence and structural alignments with a smaller core size than Matt, or similarly sized alignments with better sequence similarity, for a small cost in average RMSD. Conclusions Considering sequence information as well as purely geometric information seems to improve quality of multiple structure alignments, though defining what constitutes the best alignment when sequence and structural measures would suggest different alignments remains a difficult open question.

Single-molecule protein sequencing through fingerprinting: computational assessment

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Yao, Yao; Docter, Margreet; van Ginkel, Jetty; de Ridder, Dick; Joo, Chirlmin

2015-10-01

Proteins are vital in all biological systems as they constitute the main structural and functional components of cells. Recent advances in mass spectrometry have brought the promise of complete proteomics by helping draft the human proteome. Yet, this commonly used protein sequencing technique has fundamental limitations in sensitivity. Here we propose a method for single-molecule (SM) protein sequencing. A major challenge lies in the fact that proteins are composed of 20 different amino acids, which demands 20 molecular reporters. We computationally demonstrate that it suffices to measure only two types of amino acids to identify proteins and suggest an experimental scheme using SM fluorescence. When achieved, this highly sensitive approach will result in a paradigm shift in proteomics, with major impact in the biological and medical sciences.

Single-molecule protein sequencing through fingerprinting: computational assessment

International Nuclear Information System (INIS)

Yao, Yao; Docter, Margreet; Van Ginkel, Jetty; Joo, Chirlmin; De Ridder, Dick

2015-01-01

Proteins are vital in all biological systems as they constitute the main structural and functional components of cells. Recent advances in mass spectrometry have brought the promise of complete proteomics by helping draft the human proteome. Yet, this commonly used protein sequencing technique has fundamental limitations in sensitivity. Here we propose a method for single-molecule (SM) protein sequencing. A major challenge lies in the fact that proteins are composed of 20 different amino acids, which demands 20 molecular reporters. We computationally demonstrate that it suffices to measure only two types of amino acids to identify proteins and suggest an experimental scheme using SM fluorescence. When achieved, this highly sensitive approach will result in a paradigm shift in proteomics, with major impact in the biological and medical sciences. (paper)

Prediction of Protein Structural Classes for Low-Similarity Sequences Based on Consensus Sequence and Segmented PSSM

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Yunyun Liang

2015-01-01

Full Text Available Prediction of protein structural classes for low-similarity sequences is useful for understanding fold patterns, regulation, functions, and interactions of proteins. It is well known that feature extraction is significant to prediction of protein structural class and it mainly uses protein primary sequence, predicted secondary structure sequence, and position-specific scoring matrix (PSSM. Currently, prediction solely based on the PSSM has played a key role in improving the prediction accuracy. In this paper, we propose a novel method called CSP-SegPseP-SegACP by fusing consensus sequence (CS, segmented PsePSSM, and segmented autocovariance transformation (ACT based on PSSM. Three widely used low-similarity datasets (1189, 25PDB, and 640 are adopted in this paper. Then a 700-dimensional (700D feature vector is constructed and the dimension is decreased to 224D by using principal component analysis (PCA. To verify the performance of our method, rigorous jackknife cross-validation tests are performed on 1189, 25PDB, and 640 datasets. Comparison of our results with the existing PSSM-based methods demonstrates that our method achieves the favorable and competitive performance. This will offer an important complementary to other PSSM-based methods for prediction of protein structural classes for low-similarity sequences.

Scoring protein relationships in functional interaction networks predicted from sequence data.

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Gaston K Mazandu

Full Text Available UNLABELLED: The abundance of diverse biological data from various sources constitutes a rich source of knowledge, which has the power to advance our understanding of organisms. This requires computational methods in order to integrate and exploit these data effectively and elucidate local and genome wide functional connections between protein pairs, thus enabling functional inferences for uncharacterized proteins. These biological data are primarily in the form of sequences, which determine functions, although functional properties of a protein can often be predicted from just the domains it contains. Thus, protein sequences and domains can be used to predict protein pair-wise functional relationships, and thus contribute to the function prediction process of uncharacterized proteins in order to ensure that knowledge is gained from sequencing efforts. In this work, we introduce information-theoretic based approaches to score protein-protein functional interaction pairs predicted from protein sequence similarity and conserved protein signature matches. The proposed schemes are effective for data-driven scoring of connections between protein pairs. We applied these schemes to the Mycobacterium tuberculosis proteome to produce a homology-based functional network of the organism with a high confidence and coverage. We use the network for predicting functions of uncharacterised proteins. AVAILABILITY: Protein pair-wise functional relationship scores for Mycobacterium tuberculosis strain CDC1551 sequence data and python scripts to compute these scores are available at http://web.cbio.uct.ac.za/~gmazandu/scoringschemes.

Worldwide genetic variability of the Duffy binding protein: insights into Plasmodium vivax vaccine development.

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Taís Nóbrega de Sousa

Full Text Available The dependence of Plasmodium vivax on invasion mediated by Duffy binding protein (DBP makes this protein a prime candidate for development of a vaccine. However, the development of a DBP-based vaccine might be hampered by the high variability of the protein ligand (DBP(II, known to bias the immune response toward a specific DBP variant. Here, the hypothesis being investigated is that the analysis of the worldwide DBP(II sequences will allow us to determine the minimum number of haplotypes (MNH to be included in a DBP-based vaccine of broad coverage. For that, all DBP(II sequences available were compiled and MNH was based on the most frequent nonsynonymous single nucleotide polymorphisms, the majority mapped on B and T cell epitopes. A preliminary analysis of DBP(II genetic diversity from eight malaria-endemic countries estimated that a number between two to six DBP haplotypes (17 in total would target at least 50% of parasite population circulating in each endemic region. Aiming to avoid region-specific haplotypes, we next analyzed the MNH that broadly cover worldwide parasite population. The results demonstrated that seven haplotypes would be required to cover around 60% of DBP(II sequences available. Trying to validate these selected haplotypes per country, we found that five out of the eight countries will be covered by the MNH (67% of parasite populations, range 48-84%. In addition, to identify related subgroups of DBP(II sequences we used a Bayesian clustering algorithm. The algorithm grouped all DBP(II sequences in six populations that were independent of geographic origin, with ancestral populations present in different proportions in each country. In conclusion, in this first attempt to undertake a global analysis about DBP(II variability, the results suggest that the development of DBP-based vaccine should consider multi-haplotype strategies; otherwise a putative P. vivax vaccine may not target some parasite populations.

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.

Ultra-fast evaluation of protein energies directly from sequence.

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Gevorg Grigoryan

2006-06-01

Full Text Available The structure, function, stability, and many other properties of a protein in a fixed environment are fully specified by its sequence, but in a manner that is difficult to discern. We present a general approach for rapidly mapping sequences directly to their energies on a pre-specified rigid backbone, an important sub-problem in computational protein design and in some methods for protein structure prediction. The cluster expansion (CE method that we employ can, in principle, be extended to model any computable or measurable protein property directly as a function of sequence. Here we show how CE can be applied to the problem of computational protein design, and use it to derive excellent approximations of physical potentials. The approach provides several attractive advantages. First, following a one-time derivation of a CE expansion, the amount of time necessary to evaluate the energy of a sequence adopting a specified backbone conformation is reduced by a factor of 10(7 compared to standard full-atom methods for the same task. Second, the agreement between two full-atom methods that we tested and their CE sequence-based expressions is very high (root mean square deviation 1.1-4.7 kcal/mol, R2 = 0.7-1.0. Third, the functional form of the CE energy expression is such that individual terms of the expansion have clear physical interpretations. We derived expressions for the energies of three classic protein design targets-a coiled coil, a zinc finger, and a WW domain-as functions of sequence, and examined the most significant terms. Single-residue and residue-pair interactions are sufficient to accurately capture the energetics of the dimeric coiled coil, whereas higher-order contributions are important for the two more globular folds. For the task of designing novel zinc-finger sequences, a CE-derived energy function provides significantly better solutions than a standard design protocol, in comparable computation time. Given these advantages

ProteinSplit: splitting of multi-domain proteins using prediction of ordered and disordered regions in protein sequences for virtual structural genomics

International Nuclear Information System (INIS)

Wyrwicz, Lucjan S; Koczyk, Grzegorz; Rychlewski, Leszek; Plewczynski, Dariusz

2007-01-01

The annotation of protein folds within newly sequenced genomes is the main target for semi-automated protein structure prediction (virtual structural genomics). A large number of automated methods have been developed recently with very good results in the case of single-domain proteins. Unfortunately, most of these automated methods often fail to properly predict the distant homology between a given multi-domain protein query and structural templates. Therefore a multi-domain protein should be split into domains in order to overcome this limitation. ProteinSplit is designed to identify protein domain boundaries using a novel algorithm that predicts disordered regions in protein sequences. The software utilizes various sequence characteristics to assess the local propensity of a protein to be disordered or ordered in terms of local structure stability. These disordered parts of a protein are likely to create interdomain spacers. Because of its speed and portability, the method was successfully applied to several genome-wide fold annotation experiments. The user can run an automated analysis of sets of proteins or perform semi-automated multiple user projects (saving the results on the server). Additionally the sequences of predicted domains can be sent to the Bioinfo.PL Protein Structure Prediction Meta-Server for further protein three-dimensional structure and function prediction. The program is freely accessible as a web service at http://lucjan.bioinfo.pl/proteinsplit together with detailed benchmark results on the critical assessment of a fully automated structure prediction (CAFASP) set of sequences. The source code of the local version of protein domain boundary prediction is available upon request from the authors

Rapid identification of sequences for orphan enzymes to power accurate protein annotation.

Directory of Open Access Journals (Sweden)

Kevin R Ramkissoon

Full Text Available The power of genome sequencing depends on the ability to understand what those genes and their proteins products actually do. The automated methods used to assign functions to putative proteins in newly sequenced organisms are limited by the size of our library of proteins with both known function and sequence. Unfortunately this library grows slowly, lagging well behind the rapid increase in novel protein sequences produced by modern genome sequencing methods. One potential source for rapidly expanding this functional library is the "back catalog" of enzymology--"orphan enzymes," those enzymes that have been characterized and yet lack any associated sequence. There are hundreds of orphan enzymes in the Enzyme Commission (EC database alone. In this study, we demonstrate how this orphan enzyme "back catalog" is a fertile source for rapidly advancing the state of protein annotation. Starting from three orphan enzyme samples, we applied mass-spectrometry based analysis and computational methods (including sequence similarity networks, sequence and structural alignments, and operon context analysis to rapidly identify the specific sequence for each orphan while avoiding the most time- and labor-intensive aspects of typical sequence identifications. We then used these three new sequences to more accurately predict the catalytic function of 385 previously uncharacterized or misannotated proteins. We expect that this kind of rapid sequence identification could be efficiently applied on a larger scale to make enzymology's "back catalog" another powerful tool to drive accurate genome annotation.

Rapid Identification of Sequences for Orphan Enzymes to Power Accurate Protein Annotation

Science.gov (United States)

Ojha, Sunil; Watson, Douglas S.; Bomar, Martha G.; Galande, Amit K.; Shearer, Alexander G.

2013-01-01

The power of genome sequencing depends on the ability to understand what those genes and their proteins products actually do. The automated methods used to assign functions to putative proteins in newly sequenced organisms are limited by the size of our library of proteins with both known function and sequence. Unfortunately this library grows slowly, lagging well behind the rapid increase in novel protein sequences produced by modern genome sequencing methods. One potential source for rapidly expanding this functional library is the “back catalog” of enzymology – “orphan enzymes,” those enzymes that have been characterized and yet lack any associated sequence. There are hundreds of orphan enzymes in the Enzyme Commission (EC) database alone. In this study, we demonstrate how this orphan enzyme “back catalog” is a fertile source for rapidly advancing the state of protein annotation. Starting from three orphan enzyme samples, we applied mass-spectrometry based analysis and computational methods (including sequence similarity networks, sequence and structural alignments, and operon context analysis) to rapidly identify the specific sequence for each orphan while avoiding the most time- and labor-intensive aspects of typical sequence identifications. We then used these three new sequences to more accurately predict the catalytic function of 385 previously uncharacterized or misannotated proteins. We expect that this kind of rapid sequence identification could be efficiently applied on a larger scale to make enzymology’s “back catalog” another powerful tool to drive accurate genome annotation. PMID:24386392

Complete cDNA sequence coding for human docking protein

Energy Technology Data Exchange (ETDEWEB)

Hortsch, M; Labeit, S; Meyer, D I

1988-01-11

Docking protein (DP, or SRP receptor) is a rough endoplasmic reticulum (ER)-associated protein essential for the targeting and translocation of nascent polypeptides across this membrane. It specifically interacts with a cytoplasmic ribonucleoprotein complex, the signal recognition particle (SRP). The nucleotide sequence of cDNA encoding the entire human DP and its deduced amino acid sequence are given.

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.

Prediction of protein-protein interaction sites in sequences and 3D structures by random forests.

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Mile Sikić

2009-01-01

Full Text Available Identifying interaction sites in proteins provides important clues to the function of a protein and is becoming increasingly relevant in topics such as systems biology and drug discovery. Although there are numerous papers on the prediction of interaction sites using information derived from structure, there are only a few case reports on the prediction of interaction residues based solely on protein sequence. Here, a sliding window approach is combined with the Random Forests method to predict protein interaction sites using (i a combination of sequence- and structure-derived parameters and (ii sequence information alone. For sequence-based prediction we achieved a precision of 84% with a 26% recall and an F-measure of 40%. When combined with structural information, the prediction performance increases to a precision of 76% and a recall of 38% with an F-measure of 51%. We also present an attempt to rationalize the sliding window size and demonstrate that a nine-residue window is the most suitable for predictor construction. Finally, we demonstrate the applicability of our prediction methods by modeling the Ras-Raf complex using predicted interaction sites as target binding interfaces. Our results suggest that it is possible to predict protein interaction sites with quite a high accuracy using only sequence information.

Comparative analysis of the prion protein gene sequences in African lion.

Science.gov (United States)

Wu, Chang-De; Pang, Wan-Yong; Zhao, De-Ming

2006-10-01

The prion protein gene of African lion (Panthera Leo) was first cloned and polymorphisms screened. The results suggest that the prion protein gene of eight African lions is highly homogenous. The amino acid sequences of the prion protein (PrP) of all samples tested were identical. Four single nucleotide polymorphisms (C42T, C81A, C420T, T600C) in the prion protein gene (Prnp) of African lion were found, but no amino acid substitutions. Sequence analysis showed that the higher homology is observed to felis catus AF003087 (96.7%) and to sheep number M31313.1 (96.2%) Genbank accessed. With respect to all the mammalian prion protein sequences compared, the African lion prion protein sequence has three amino acid substitutions. The homology might in turn affect the potential intermolecular interactions critical for cross species transmission of prion disease.

Repeat Sequence Proteins as Matrices for Nanocomposites

Energy Technology Data Exchange (ETDEWEB)

Drummy, L.; Koerner, H; Phillips, D; McAuliffe, J; Kumar, M; Farmer, B; Vaia, R; Naik, R

2009-01-01

Recombinant protein-inorganic nanocomposites comprised of exfoliated Na+ montmorillonite (MMT) in a recombinant protein matrix based on silk-like and elastin-like amino acid motifs (silk elastin-like protein (SELP)) were formed via a solution blending process. Charged residues along the protein backbone are shown to dominate long-range interactions, whereas the SELP repeat sequence leads to local protein/MMT compatibility. Up to a 50% increase in room temperature modulus and a comparable decrease in high temperature coefficient of thermal expansion occur for cast films containing 2-10 wt.% MMT.

Detecting Scareware by Mining Variable Length Instruction Sequences

OpenAIRE

Shahzad, Raja Khurram; Lavesson, Niklas

2011-01-01

Scareware is a recent type of malicious software that may pose financial and privacy-related threats to novice users. Traditional countermeasures, such as anti-virus software, require regular updates and often lack the capability of detecting novel (unseen) instances. This paper presents a scareware detection method that is based on the application of machine learning algorithms to learn patterns in extracted variable length opcode sequences derived from instruction sequences of binary files....

Analysis of long-range correlation in sequences data of proteins

OpenAIRE

ADRIANA ISVORAN; LAURA UNIPAN; DANA CRACIUN; VASILE MORARIU

2007-01-01

The results presented here suggest the existence of correlations in the sequence data of proteins. 32 proteins, both globular and fibrous, both monomeric and polymeric, were analyzed. The primary structures of these proteins were treated as time series. Three spatial series of data for each sequence of a protein were generated from numerical correspondences between each amino acid and a physical property associated with it, i.e., its electric charge, its polar character and its dipole moment....

Differential sequence diversity at merozoite surface protein-1 locus of Plasmodium knowlesi from humans and macaques in Thailand.

Science.gov (United States)

Putaporntip, Chaturong; Thongaree, Siriporn; Jongwutiwes, Somchai

2013-08-01

To determine the genetic diversity and potential transmission routes of Plasmodium knowlesi, we analyzed the complete nucleotide sequence of the gene encoding the merozoite surface protein-1 of this simian malaria (Pkmsp-1), an asexual blood-stage vaccine candidate, from naturally infected humans and macaques in Thailand. Analysis of Pkmsp-1 sequences from humans (n=12) and monkeys (n=12) reveals five conserved and four variable domains. Most nucleotide substitutions in conserved domains were dimorphic whereas three of four variable domains contained complex repeats with extensive sequence and size variation. Besides purifying selection in conserved domains, evidence of intragenic recombination scattering across Pkmsp-1 was detected. The number of haplotypes, haplotype diversity, nucleotide diversity and recombination sites of human-derived sequences exceeded that of monkey-derived sequences. Phylogenetic networks based on concatenated conserved sequences of Pkmsp-1 displayed a character pattern that could have arisen from sampling process or the presence of two independent routes of P. knowlesi transmission, i.e. from macaques to human and from human to humans in Thailand. Copyright © 2013 Elsevier B.V. All rights reserved.

Peptide Pattern Recognition for high-throughput protein sequence analysis and clustering

DEFF Research Database (Denmark)

Busk, Peter Kamp

2017-01-01

Large collections of protein sequences with divergent sequences are tedious to analyze for understanding their phylogenetic or structure-function relation. Peptide Pattern Recognition is an algorithm that was developed to facilitate this task but the previous version does only allow a limited...... number of sequences as input. I implemented Peptide Pattern Recognition as a multithread software designed to handle large numbers of sequences and perform analysis in a reasonable time frame. Benchmarking showed that the new implementation of Peptide Pattern Recognition is twenty times faster than...... the previous implementation on a small protein collection with 673 MAP kinase sequences. In addition, the new implementation could analyze a large protein collection with 48,570 Glycosyl Transferase family 20 sequences without reaching its upper limit on a desktop computer. Peptide Pattern Recognition...

Top-Down-Assisted Bottom-Up Method for Homologous Protein Sequencing: Hemoglobin from 33 Bird Species

Science.gov (United States)

Song, Yang; Laskay, Ünige A.; Vilcins, Inger-Marie E.; Barbour, Alan G.; Wysocki, Vicki H.

2015-11-01

Ticks are vectors for disease transmission because they are indiscriminant in their feeding on multiple vertebrate hosts, transmitting pathogens between their hosts. Identifying the hosts on which ticks have fed is important for disease prevention and intervention. We have previously shown that hemoglobin (Hb) remnants from a host on which a tick fed can be used to reveal the host's identity. For the present research, blood was collected from 33 bird species that are common in the U.S. as hosts for ticks but that have unknown Hb sequences. A top-down-assisted bottom-up mass spectrometry approach with a customized searching database, based on variability in known bird hemoglobin sequences, has been devised to facilitate fast and complete sequencing of hemoglobin from birds with unknown sequences. These hemoglobin sequences will be added to a hemoglobin database and used for tick host identification. The general approach has the potential to sequence any set of homologous proteins completely in a rapid manner.

Elman RNN based classification of proteins sequences on account of their mutual information.

Science.gov (United States)

Mishra, Pooja; Nath Pandey, Paras

2012-10-21

In the present work we have employed the method of estimating residue correlation within the protein sequences, by using the mutual information (MI) of adjacent residues, based on structural and solvent accessibility properties of amino acids. The long range correlation between nonadjacent residues is improved by constructing a mutual information vector (MIV) for a single protein sequence, like this each protein sequence is associated with its corresponding MIVs. These MIVs are given to Elman RNN to obtain the classification of protein sequences. The modeling power of MIV was shown to be significantly better, giving a new approach towards alignment free classification of protein sequences. We also conclude that sequence structural and solvent accessible property based MIVs are better predictor. Copyright © 2012 Elsevier Ltd. All rights reserved.

Predicting membrane protein types by fusing composite protein sequence features into pseudo amino acid composition.

Science.gov (United States)

Hayat, Maqsood; Khan, Asifullah

2011-02-21

Membrane proteins are vital type of proteins that serve as channels, receptors, and energy transducers in a cell. Prediction of membrane protein types is an important research area in bioinformatics. Knowledge of membrane protein types provides some valuable information for predicting novel example of the membrane protein types. However, classification of membrane protein types can be both time consuming and susceptible to errors due to the inherent similarity of membrane protein types. In this paper, neural networks based membrane protein type prediction system is proposed. Composite protein sequence representation (CPSR) is used to extract the features of a protein sequence, which includes seven feature sets; amino acid composition, sequence length, 2 gram exchange group frequency, hydrophobic group, electronic group, sum of hydrophobicity, and R-group. Principal component analysis is then employed to reduce the dimensionality of the feature vector. The probabilistic neural network (PNN), generalized regression neural network, and support vector machine (SVM) are used as classifiers. A high success rate of 86.01% is obtained using SVM for the jackknife test. In case of independent dataset test, PNN yields the highest accuracy of 95.73%. These classifiers exhibit improved performance using other performance measures such as sensitivity, specificity, Mathew's correlation coefficient, and F-measure. The experimental results show that the prediction performance of the proposed scheme for classifying membrane protein types is the best reported, so far. This performance improvement may largely be credited to the learning capabilities of neural networks and the composite feature extraction strategy, which exploits seven different properties of protein sequences. The proposed Mem-Predictor can be accessed at http://111.68.99.218/Mem-Predictor. Copyright © 2010 Elsevier Ltd. All rights reserved.

Transforming p21 ras protein: flexibility in the major variable region linking the catalytic and membrane-anchoring domains

DEFF Research Database (Denmark)

Willumsen, B M; Papageorge, A G; Hubbert, N

1985-01-01

or increasing it to 50 amino acids has relatively little effect on the capacity of the gene to induce morphological transformation of NIH 3T3 cells. Assays of GTP binding, GTPase and autophosphorylating activities of such mutant v-rasH-encoded proteins synthesized in bacteria indicated that the sequences...... that is required for post-translational processing, membrane localization and transforming activity of the proteins. We have now used the viral oncogene (v-rasH) of Harvey sarcoma virus to study the major variable region by deleting or duplicating parts of the gene. Reducing this region to five amino acids...... that encode these biochemical activities are located upstream from the major variable region. In the context of transformation, we propose that the region of sequence heterogeneity serves principally to connect the N-terminal catalytic domain with amino acids at the C terminus that are required to anchor...

The HMMER Web Server for Protein Sequence Similarity Search.

Science.gov (United States)

Prakash, Ananth; Jeffryes, Matt; Bateman, Alex; Finn, Robert D

2017-12-08

Protein sequence similarity search is one of the most commonly used bioinformatics methods for identifying evolutionarily related proteins. In general, sequences that are evolutionarily related share some degree of similarity, and sequence-search algorithms use this principle to identify homologs. The requirement for a fast and sensitive sequence search method led to the development of the HMMER software, which in the latest version (v3.1) uses a combination of sophisticated acceleration heuristics and mathematical and computational optimizations to enable the use of profile hidden Markov models (HMMs) for sequence analysis. The HMMER Web server provides a common platform by linking the HMMER algorithms to databases, thereby enabling the search for homologs, as well as providing sequence and functional annotation by linking external databases. This unit describes three basic protocols and two alternate protocols that explain how to use the HMMER Web server using various input formats and user defined parameters. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

Quantiprot - a Python package for quantitative analysis of protein sequences.

Science.gov (United States)

Konopka, Bogumił M; Marciniak, Marta; Dyrka, Witold

2017-07-17

The field of protein sequence analysis is dominated by tools rooted in substitution matrices and alignments. A complementary approach is provided by methods of quantitative characterization. A major advantage of the approach is that quantitative properties defines a multidimensional solution space, where sequences can be related to each other and differences can be meaningfully interpreted. Quantiprot is a software package in Python, which provides a simple and consistent interface to multiple methods for quantitative characterization of protein sequences. The package can be used to calculate dozens of characteristics directly from sequences or using physico-chemical properties of amino acids. Besides basic measures, Quantiprot performs quantitative analysis of recurrence and determinism in the sequence, calculates distribution of n-grams and computes the Zipf's law coefficient. We propose three main fields of application of the Quantiprot package. First, quantitative characteristics can be used in alignment-free similarity searches, and in clustering of large and/or divergent sequence sets. Second, a feature space defined by quantitative properties can be used in comparative studies of protein families and organisms. Third, the feature space can be used for evaluating generative models, where large number of sequences generated by the model can be compared to actually observed sequences.

Detecting remote sequence homology in disordered proteins: discovery of conserved motifs in the N-termini of Mononegavirales phosphoproteins.

Directory of Open Access Journals (Sweden)

David Karlin

Full Text Available Paramyxovirinae are a large group of viruses that includes measles virus and parainfluenza viruses. The viral Phosphoprotein (P plays a central role in viral replication. It is composed of a highly variable, disordered N-terminus and a conserved C-terminus. A second viral protein alternatively expressed, the V protein, also contains the N-terminus of P, fused to a zinc finger. We suspected that, despite their high variability, the N-termini of P/V might all be homologous; however, using standard approaches, we could previously identify sequence conservation only in some Paramyxovirinae. We now compared the N-termini using sensitive sequence similarity search programs, able to detect residual similarities unnoticeable by conventional approaches. We discovered that all Paramyxovirinae share a short sequence motif in their first 40 amino acids, which we called soyuz1. Despite its short length (11-16aa, several arguments allow us to conclude that soyuz1 probably evolved by homologous descent, unlike linear motifs. Conservation across such evolutionary distances suggests that soyuz1 plays a crucial role and experimental data suggest that it binds the viral nucleoprotein to prevent its illegitimate self-assembly. In some Paramyxovirinae, the N-terminus of P/V contains a second motif, soyuz2, which might play a role in blocking interferon signaling. Finally, we discovered that the P of related Mononegavirales contain similarly overlooked motifs in their N-termini, and that their C-termini share a previously unnoticed structural similarity suggesting a common origin. Our results suggest several testable hypotheses regarding the replication of Mononegavirales and suggest that disordered regions with little overall sequence similarity, common in viral and eukaryotic proteins, might contain currently overlooked motifs (intermediate in length between linear motifs and disordered domains that could be detected simply by comparing orthologous proteins.

Osteocalcin protein sequences of Neanderthals and modern primates.

Science.gov (United States)

Nielsen-Marsh, Christina M; Richards, Michael P; Hauschka, Peter V; Thomas-Oates, Jane E; Trinkaus, Erik; Pettitt, Paul B; Karavanic, Ivor; Poinar, Hendrik; Collins, Matthew J

2005-03-22

We report here protein sequences of fossil hominids, from two Neanderthals dating to approximately 75,000 years old from Shanidar Cave in Iraq. These sequences, the oldest reported fossil primate protein sequences, are of bone osteocalcin, which was extracted and sequenced by using MALDI-TOF/TOF mass spectrometry. Through a combination of direct sequencing and peptide mass mapping, we determined that Neanderthals have an osteocalcin amino acid sequence that is identical to that of modern humans. We also report complete osteocalcin sequences for chimpanzee (Pan troglodytes) and gorilla (Gorilla gorilla gorilla) and a partial sequence for orangutan (Pongo pygmaeus), all of which are previously unreported. We found that the osteocalcin sequences of Neanderthals, modern human, chimpanzee, and orangutan are unusual among mammals in that the ninth amino acid is proline (Pro-9), whereas most species have hydroxyproline (Hyp-9). Posttranslational hydroxylation of Pro-9 in osteocalcin by prolyl-4-hydroxylase requires adequate concentrations of vitamin C (l-ascorbic acid), molecular O(2), Fe(2+), and 2-oxoglutarate, and also depends on enzyme recognition of the target proline substrate consensus sequence Leu-Gly-Ala-Pro-9-Ala-Pro-Tyr occurring in most mammals. In five species with Pro-9-Val-10, hydroxylation is blocked, whereas in gorilla there is a mixture of Pro-9 and Hyp-9. We suggest that the absence of hydroxylation of Pro-9 in Pan, Pongo, and Homo may reflect response to a selective pressure related to a decline in vitamin C in the diet during omnivorous dietary adaptation, either independently or through the common ancestor of these species.

Sequence protein identification by randomized sequence database and transcriptome mass spectrometry (SPIDER-TMS): from manual to automatic application of a 'de novo sequencing' approach.

Science.gov (United States)

Pascale, Raffaella; Grossi, Gerarda; Cruciani, Gabriele; Mecca, Giansalvatore; Santoro, Donatello; Sarli Calace, Renzo; Falabella, Patrizia; Bianco, Giuliana

Sequence protein identification by a randomized sequence database and transcriptome mass spectrometry software package has been developed at the University of Basilicata in Potenza (Italy) and designed to facilitate the determination of the amino acid sequence of a peptide as well as an unequivocal identification of proteins in a high-throughput manner with enormous advantages of time, economical resource and expertise. The software package is a valid tool for the automation of a de novo sequencing approach, overcoming the main limits and a versatile platform useful in the proteomic field for an unequivocal identification of proteins, starting from tandem mass spectrometry data. The strength of this software is that it is a user-friendly and non-statistical approach, so protein identification can be considered unambiguous.

Evolutionary rates at codon sites may be used to align sequences and infer protein domain function

Directory of Open Access Journals (Sweden)

Hazelhurst Scott

2010-03-01

Full Text Available Abstract Background Sequence alignments form part of many investigations in molecular biology, including the determination of phylogenetic relationships, the prediction of protein structure and function, and the measurement of evolutionary rates. However, to obtain meaningful results, a significant degree of sequence similarity is required to ensure that the alignments are accurate and the inferences correct. Limitations arise when sequence similarity is low, which is particularly problematic when working with fast-evolving genes, evolutionary distant taxa, genomes with nucleotide biases, and cases of convergent evolution. Results A novel approach was conceptualized to address the "low sequence similarity" alignment problem. We developed an alignment algorithm termed FIRE (Functional Inference using the Rates of Evolution, which aligns sequences using the evolutionary rate at codon sites, as measured by the dN/dS ratio, rather than nucleotide or amino acid residues. FIRE was used to test the hypotheses that evolutionary rates can be used to align sequences and that the alignments may be used to infer protein domain function. Using a range of test data, we found that aligning domains based on evolutionary rates was possible even when sequence similarity was very low (for example, antibody variable regions. Furthermore, the alignment has the potential to infer protein domain function, indicating that domains with similar functions are subject to similar evolutionary constraints. These data suggest that an evolutionary rate-based approach to sequence analysis (particularly when combined with structural data may be used to study cases of convergent evolution or when sequences have very low similarity. However, when aligning homologous gene sets with sequence similarity, FIRE did not perform as well as the best traditional alignment algorithms indicating that the conventional approach of aligning residues as opposed to evolutionary rates remains the

On the relationship between residue structural environment and sequence conservation in proteins.

Science.gov (United States)

Liu, Jen-Wei; Lin, Jau-Ji; Cheng, Chih-Wen; Lin, Yu-Feng; Hwang, Jenn-Kang; Huang, Tsun-Tsao

2017-09-01

Residues that are crucial to protein function or structure are usually evolutionarily conserved. To identify the important residues in protein, sequence conservation is estimated, and current methods rely upon the unbiased collection of homologous sequences. Surprisingly, our previous studies have shown that the sequence conservation is closely correlated with the weighted contact number (WCN), a measure of packing density for residue's structural environment, calculated only based on the C α positions of a protein structure. Moreover, studies have shown that sequence conservation is correlated with environment-related structural properties calculated based on different protein substructures, such as a protein's all atoms, backbone atoms, side-chain atoms, or side-chain centroid. To know whether the C α atomic positions are adequate to show the relationship between residue environment and sequence conservation or not, here we compared C α atoms with other substructures in their contributions to the sequence conservation. Our results show that C α positions are substantially equivalent to the other substructures in calculations of various measures of residue environment. As a result, the overlapping contributions between C α atoms and the other substructures are high, yielding similar structure-conservation relationship. Take the WCN as an example, the average overlapping contribution to sequence conservation is 87% between C α and all-atom substructures. These results indicate that only C α atoms of a protein structure could reflect sequence conservation at the residue level. © 2017 Wiley Periodicals, Inc.

SAAS: Short Amino Acid Sequence - A Promising Protein Secondary Structure Prediction Method of Single Sequence

Directory of Open Access Journals (Sweden)

Zhou Yuan Wu

2013-07-01

Full Text Available In statistical methods of predicting protein secondary structure, many researchers focus on single amino acid frequencies in α-helices, β-sheets, and so on, or the impact near amino acids on an amino acid forming a secondary structure. But the paper considers a short sequence of amino acids (3, 4, 5 or 6 amino acids as integer, and statistics short sequence's probability forming secondary structure. Also, many researchers select low homologous sequences as statistical database. But this paper select whole PDB database. In this paper we propose a strategy to predict protein secondary structure using simple statistical method. Numerical computation shows that, short amino acids sequence as integer to statistics, which can easy see trend of short sequence forming secondary structure, and it will work well to select large statistical database (whole PDB database without considering homologous, and Q3 accuracy is ca. 74% using this paper proposed simple statistical method, but accuracy of others statistical methods is less than 70%.

Computational identification of MoRFs in protein sequences.

Science.gov (United States)

Malhis, Nawar; Gsponer, Jörg

2015-06-01

Intrinsically disordered regions of proteins play an essential role in the regulation of various biological processes. Key to their regulatory function is the binding of molecular recognition features (MoRFs) to globular protein domains in a process known as a disorder-to-order transition. Predicting the location of MoRFs in protein sequences with high accuracy remains an important computational challenge. In this study, we introduce MoRFCHiBi, a new computational approach for fast and accurate prediction of MoRFs in protein sequences. MoRFCHiBi combines the outcomes of two support vector machine (SVM) models that take advantage of two different kernels with high noise tolerance. The first, SVMS, is designed to extract maximal information from the general contrast in amino acid compositions between MoRFs, their surrounding regions (Flanks), and the remainders of the sequences. The second, SVMT, is used to identify similarities between regions in a query sequence and MoRFs of the training set. We evaluated the performance of our predictor by comparing its results with those of two currently available MoRF predictors, MoRFpred and ANCHOR. Using three test sets that have previously been collected and used to evaluate MoRFpred and ANCHOR, we demonstrate that MoRFCHiBi outperforms the other predictors with respect to different evaluation metrics. In addition, MoRFCHiBi is downloadable and fast, which makes it useful as a component in other computational prediction tools. http://www.chibi.ubc.ca/morf/. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

MannDB – A microbial database of automated protein sequence analyses and evidence integration for protein characterization

Directory of Open Access Journals (Sweden)

Kuczmarski Thomas A

2006-10-01

Full Text Available Abstract Background MannDB was created to meet a need for rapid, comprehensive automated protein sequence analyses to support selection of proteins suitable as targets for driving the development of reagents for pathogen or protein toxin detection. Because a large number of open-source tools were needed, it was necessary to produce a software system to scale the computations for whole-proteome analysis. Thus, we built a fully automated system for executing software tools and for storage, integration, and display of automated protein sequence analysis and annotation data. Description MannDB is a relational database that organizes data resulting from fully automated, high-throughput protein-sequence analyses using open-source tools. Types of analyses provided include predictions of cleavage, chemical properties, classification, features, functional assignment, post-translational modifications, motifs, antigenicity, and secondary structure. Proteomes (lists of hypothetical and known proteins are downloaded and parsed from Genbank and then inserted into MannDB, and annotations from SwissProt are downloaded when identifiers are found in the Genbank entry or when identical sequences are identified. Currently 36 open-source tools are run against MannDB protein sequences either on local systems or by means of batch submission to external servers. In addition, BLAST against protein entries in MvirDB, our database of microbial virulence factors, is performed. A web client browser enables viewing of computational results and downloaded annotations, and a query tool enables structured and free-text search capabilities. When available, links to external databases, including MvirDB, are provided. MannDB contains whole-proteome analyses for at least one representative organism from each category of biological threat organism listed by APHIS, CDC, HHS, NIAID, USDA, USFDA, and WHO. Conclusion MannDB comprises a large number of genomes and comprehensive protein

Nonlinear analysis of sequence repeats of multi-domain proteins

Energy Technology Data Exchange (ETDEWEB)

Huang Yanzhao [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China); Li Mingfeng [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China); Xiao Yi [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China)]. E-mail: lmf_bill@sina.com

2007-11-15

Many multi-domain proteins have repetitive three-dimensional structures but nearly-random amino acid sequences. In the present paper, by using a modified recurrence plot proposed by us previously, we show that these amino acid sequences have hidden repetitions in fact. These results indicate that the repetitive domain structures are encoded by the repetitive sequences. This also gives a method to detect the repetitive domain structures directly from amino acid sequences.

The SWISS-PROT protein sequence data bank

OpenAIRE

Bairoch, Amos; Boeckmann, Brigitte

1992-01-01

SWISS-PROT is an annotated protein sequence database established in 1986 and maintained collaboratively, since 1988, by the Department of Medical Biochemistry of the University of Geneva and the EMBL Data Library

Using sequence similarity networks for visualization of relationships across diverse protein superfamilies.

Directory of Open Access Journals (Sweden)

Holly J Atkinson

Full Text Available The dramatic increase in heterogeneous types of biological data--in particular, the abundance of new protein sequences--requires fast and user-friendly methods for organizing this information in a way that enables functional inference. The most widely used strategy to link sequence or structure to function, homology-based function prediction, relies on the fundamental assumption that sequence or structural similarity implies functional similarity. New tools that extend this approach are still urgently needed to associate sequence data with biological information in ways that accommodate the real complexity of the problem, while being accessible to experimental as well as computational biologists. To address this, we have examined the application of sequence similarity networks for visualizing functional trends across protein superfamilies from the context of sequence similarity. Using three large groups of homologous proteins of varying types of structural and functional diversity--GPCRs and kinases from humans, and the crotonase superfamily of enzymes--we show that overlaying networks with orthogonal information is a powerful approach for observing functional themes and revealing outliers. In comparison to other primary methods, networks provide both a good representation of group-wise sequence similarity relationships and a strong visual and quantitative correlation with phylogenetic trees, while enabling analysis and visualization of much larger sets of sequences than trees or multiple sequence alignments can easily accommodate. We also define important limitations and caveats in the application of these networks. As a broadly accessible and effective tool for the exploration of protein superfamilies, sequence similarity networks show great potential for generating testable hypotheses about protein structure-function relationships.

Using sequence similarity networks for visualization of relationships across diverse protein superfamilies.

Science.gov (United States)

Atkinson, Holly J; Morris, John H; Ferrin, Thomas E; Babbitt, Patricia C

2009-01-01

The dramatic increase in heterogeneous types of biological data--in particular, the abundance of new protein sequences--requires fast and user-friendly methods for organizing this information in a way that enables functional inference. The most widely used strategy to link sequence or structure to function, homology-based function prediction, relies on the fundamental assumption that sequence or structural similarity implies functional similarity. New tools that extend this approach are still urgently needed to associate sequence data with biological information in ways that accommodate the real complexity of the problem, while being accessible to experimental as well as computational biologists. To address this, we have examined the application of sequence similarity networks for visualizing functional trends across protein superfamilies from the context of sequence similarity. Using three large groups of homologous proteins of varying types of structural and functional diversity--GPCRs and kinases from humans, and the crotonase superfamily of enzymes--we show that overlaying networks with orthogonal information is a powerful approach for observing functional themes and revealing outliers. In comparison to other primary methods, networks provide both a good representation of group-wise sequence similarity relationships and a strong visual and quantitative correlation with phylogenetic trees, while enabling analysis and visualization of much larger sets of sequences than trees or multiple sequence alignments can easily accommodate. We also define important limitations and caveats in the application of these networks. As a broadly accessible and effective tool for the exploration of protein superfamilies, sequence similarity networks show great potential for generating testable hypotheses about protein structure-function relationships.

PredPPCrys: accurate prediction of sequence cloning, protein production, purification and crystallization propensity from protein sequences using multi-step heterogeneous feature fusion and selection.

Directory of Open Access Journals (Sweden)

Huilin Wang

Full Text Available X-ray crystallography is the primary approach to solve the three-dimensional structure of a protein. However, a major bottleneck of this method is the failure of multi-step experimental procedures to yield diffraction-quality crystals, including sequence cloning, protein material production, purification, crystallization and ultimately, structural determination. Accordingly, prediction of the propensity of a protein to successfully undergo these experimental procedures based on the protein sequence may help narrow down laborious experimental efforts and facilitate target selection. A number of bioinformatics methods based on protein sequence information have been developed for this purpose. However, our knowledge on the important determinants of propensity for a protein sequence to produce high diffraction-quality crystals remains largely incomplete. In practice, most of the existing methods display poorer performance when evaluated on larger and updated datasets. To address this problem, we constructed an up-to-date dataset as the benchmark, and subsequently developed a new approach termed 'PredPPCrys' using the support vector machine (SVM. Using a comprehensive set of multifaceted sequence-derived features in combination with a novel multi-step feature selection strategy, we identified and characterized the relative importance and contribution of each feature type to the prediction performance of five individual experimental steps required for successful crystallization. The resulting optimal candidate features were used as inputs to build the first-level SVM predictor (PredPPCrys I. Next, prediction outputs of PredPPCrys I were used as the input to build second-level SVM classifiers (PredPPCrys II, which led to significantly enhanced prediction performance. Benchmarking experiments indicated that our PredPPCrys method outperforms most existing procedures on both up-to-date and previous datasets. In addition, the predicted crystallization

Microwave-assisted acid and base hydrolysis of intact proteins containing disulfide bonds for protein sequence analysis by mass spectrometry.

Science.gov (United States)

Reiz, Bela; Li, Liang

2010-09-01

Controlled hydrolysis of proteins to generate peptide ladders combined with mass spectrometric analysis of the resultant peptides can be used for protein sequencing. In this paper, two methods of improving the microwave-assisted protein hydrolysis process are described to enable rapid sequencing of proteins containing disulfide bonds and increase sequence coverage, respectively. It was demonstrated that proteins containing disulfide bonds could be sequenced by MS analysis by first performing hydrolysis for less than 2 min, followed by 1 h of reduction to release the peptides originally linked by disulfide bonds. It was shown that a strong base could be used as a catalyst for microwave-assisted protein hydrolysis, producing complementary sequence information to that generated by microwave-assisted acid hydrolysis. However, using either acid or base hydrolysis, amide bond breakages in small regions of the polypeptide chains of the model proteins (e.g., cytochrome c and lysozyme) were not detected. Dynamic light scattering measurement of the proteins solubilized in an acid or base indicated that protein-protein interaction or aggregation was not the cause of the failure to hydrolyze certain amide bonds. It was speculated that there were some unknown local structures that might play a role in preventing an acid or base from reacting with the peptide bonds therein. 2010 American Society for Mass Spectrometry. Published by Elsevier Inc. All rights reserved.

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

Analysis of long-range correlation in sequences data of proteins

Directory of Open Access Journals (Sweden)

ADRIANA ISVORAN

2007-04-01

Full Text Available The results presented here suggest the existence of correlations in the sequence data of proteins. 32 proteins, both globular and fibrous, both monomeric and polymeric, were analyzed. The primary structures of these proteins were treated as time series. Three spatial series of data for each sequence of a protein were generated from numerical correspondences between each amino acid and a physical property associated with it, i.e., its electric charge, its polar character and its dipole moment. For each series, the spectral coefficient, the scaling exponent and the Hurst coefficient were determined. The values obtained for these coefficients revealed non-randomness in the series of data.

Automatic discovery of cross-family sequence features associated with protein function

Directory of Open Access Journals (Sweden)

Krings Andrea

2006-01-01

Full Text Available Abstract Background Methods for predicting protein function directly from amino acid sequences are useful tools in the study of uncharacterised protein families and in comparative genomics. Until now, this problem has been approached using machine learning techniques that attempt to predict membership, or otherwise, to predefined functional categories or subcellular locations. A potential drawback of this approach is that the human-designated functional classes may not accurately reflect the underlying biology, and consequently important sequence-to-function relationships may be missed. Results We show that a self-supervised data mining approach is able to find relationships between sequence features and functional annotations. No preconceived ideas about functional categories are required, and the training data is simply a set of protein sequences and their UniProt/Swiss-Prot annotations. The main technical aspect of the approach is the co-evolution of amino acid-based regular expressions and keyword-based logical expressions with genetic programming. Our experiments on a strictly non-redundant set of eukaryotic proteins reveal that the strongest and most easily detected sequence-to-function relationships are concerned with targeting to various cellular compartments, which is an area already well studied both experimentally and computationally. Of more interest are a number of broad functional roles which can also be correlated with sequence features. These include inhibition, biosynthesis, transcription and defence against bacteria. Despite substantial overlaps between these functions and their corresponding cellular compartments, we find clear differences in the sequence motifs used to predict some of these functions. For example, the presence of polyglutamine repeats appears to be linked more strongly to the "transcription" function than to the general "nuclear" function/location. Conclusion We have developed a novel and useful approach for

Protein sequences from mastodon and Tyrannosaurus rex revealed by mass spectrometry.

Science.gov (United States)

Asara, John M; Schweitzer, Mary H; Freimark, Lisa M; Phillips, Matthew; Cantley, Lewis C

2007-04-13

Fossilized bones from extinct taxa harbor the potential for obtaining protein or DNA sequences that could reveal evolutionary links to extant species. We used mass spectrometry to obtain protein sequences from bones of a 160,000- to 600,000-year-old extinct mastodon (Mammut americanum) and a 68-million-year-old dinosaur (Tyrannosaurus rex). The presence of T. rex sequences indicates that their peptide bonds were remarkably stable. Mass spectrometry can thus be used to determine unique sequences from ancient organisms from peptide fragmentation patterns, a valuable tool to study the evolution and adaptation of ancient taxa from which genomic sequences are unlikely to be obtained.

Structural insights and ab initio sequencing within the DING proteins family

International Nuclear Information System (INIS)

Elias, Mikael; Liebschner, Dorothee; Gotthard, Guillaume; Chabriere, Eric

2011-01-01

DING proteins constitute a recently discovered protein family that is ubiquitous in eukaryotes. The structural insights and the physiological involvements of these intriguing proteins are hereby deciphered. DING proteins constitute an intriguing family of phosphate-binding proteins that was identified in a wide range of organisms, from prokaryotes and archae to eukaryotes. Despite their seemingly ubiquitous occurrence in eukaryotes, their encoding genes are missing from sequenced genomes. Such a lack has considerably hampered functional studies. In humans, these proteins have been related to several diseases, like atherosclerosis, kidney stones, inflammation processes and HIV inhibition. The human phosphate binding protein is a human representative of the DING family that was serendipitously discovered from human plasma. An original approach was developed to determine ab initio the complete and exact sequence of this 38 kDa protein by utilizing mass spectrometry and X-ray data in tandem. Taking advantage of this first complete eukaryotic DING sequence, a immunohistochemistry study was undertaken to check the presence of DING proteins in various mice tissues, revealing that these proteins are widely expressed. Finally, the structure of a bacterial representative from Pseudomonas fluorescens was solved at sub-angstrom resolution, allowing the molecular mechanism of the phosphate binding in these high-affinity proteins to be elucidated

Structural insights and ab initio sequencing within the DING proteins family

Energy Technology Data Exchange (ETDEWEB)

Elias, Mikael, E-mail: mikael.elias@weizmann.ac.il [Weizmann Institute of Science, Rehovot (Israel); Liebschner, Dorothee [CRM2, Nancy Université (France); Gotthard, Guillaume; Chabriere, Eric [AFMB, Université Aix-Marseille II (France)

2011-01-01

DING proteins constitute a recently discovered protein family that is ubiquitous in eukaryotes. The structural insights and the physiological involvements of these intriguing proteins are hereby deciphered. DING proteins constitute an intriguing family of phosphate-binding proteins that was identified in a wide range of organisms, from prokaryotes and archae to eukaryotes. Despite their seemingly ubiquitous occurrence in eukaryotes, their encoding genes are missing from sequenced genomes. Such a lack has considerably hampered functional studies. In humans, these proteins have been related to several diseases, like atherosclerosis, kidney stones, inflammation processes and HIV inhibition. The human phosphate binding protein is a human representative of the DING family that was serendipitously discovered from human plasma. An original approach was developed to determine ab initio the complete and exact sequence of this 38 kDa protein by utilizing mass spectrometry and X-ray data in tandem. Taking advantage of this first complete eukaryotic DING sequence, a immunohistochemistry study was undertaken to check the presence of DING proteins in various mice tissues, revealing that these proteins are widely expressed. Finally, the structure of a bacterial representative from Pseudomonas fluorescens was solved at sub-angstrom resolution, allowing the molecular mechanism of the phosphate binding in these high-affinity proteins to be elucidated.

Solving Classification Problems for Large Sets of Protein Sequences with the Example of Hox and ParaHox Proteins

Directory of Open Access Journals (Sweden)

Stefanie D. Hueber

2016-02-01

Full Text Available Phylogenetic methods are key to providing models for how a given protein family evolved. However, these methods run into difficulties when sequence divergence is either too low or too high. Here, we provide a case study of Hox and ParaHox proteins so that additional insights can be gained using a new computational approach to help solve old classification problems. For two (Gsx and Cdx out of three ParaHox proteins the assignments differ between the currently most established view and four alternative scenarios. We use a non-phylogenetic, pairwise-sequence-similarity-based method to assess which of the previous predictions, if any, are best supported by the sequence-similarity relationships between Hox and ParaHox proteins. The overall sequence-similarities show Gsx to be most similar to Hox2–3, and Cdx to be most similar to Hox4–8. The results indicate that a purely pairwise-sequence-similarity-based approach can provide additional information not only when phylogenetic inference methods have insufficient information to provide reliable classifications (as was shown previously for central Hox proteins, but also when the sequence variation is so high that the resulting phylogenetic reconstructions are likely plagued by long-branch-attraction artifacts.

Protein Science by DNA Sequencing: How Advances in Molecular Biology Are Accelerating Biochemistry.

Science.gov (United States)

Higgins, Sean A; Savage, David F

2018-01-09

A fundamental goal of protein biochemistry is to determine the sequence-function relationship, but the vastness of sequence space makes comprehensive evaluation of this landscape difficult. However, advances in DNA synthesis and sequencing now allow researchers to assess the functional impact of every single mutation in many proteins, but challenges remain in library construction and the development of general assays applicable to a diverse range of protein functions. This Perspective briefly outlines the technical innovations in DNA manipulation that allow massively parallel protein biochemistry and then summarizes the methods currently available for library construction and the functional assays of protein variants. Areas in need of future innovation are highlighted with a particular focus on assay development and the use of computational analysis with machine learning to effectively traverse the sequence-function landscape. Finally, applications in the fundamentals of protein biochemistry, disease prediction, and protein engineering are presented.

An algorithm to find all palindromic sequences in proteins

Indian Academy of Sciences (India)

2013-01-20

Jan 20, 2013 ... 1976; Karrer and Gall 1976; Vogt and Braun 1976) and (iii) in the formation of hairpin loops in the newly transcribed RNA. Palindromic sequences are observed in various classes of proteins like histones (Cheng et al. 1989), prion proteins (Sulkowski 1992; Kazim 1993),. DNA-binding proteins (Suzuki 1992; ...

3D representations of amino acids—applications to protein sequence comparison and classification

Directory of Open Access Journals (Sweden)

Jie Li

2014-08-01

Full Text Available The amino acid sequence of a protein is the key to understanding its structure and ultimately its function in the cell. This paper addresses the fundamental issue of encoding amino acids in ways that the representation of such a protein sequence facilitates the decoding of its information content. We show that a feature-based representation in a three-dimensional (3D space derived from amino acid substitution matrices provides an adequate representation that can be used for direct comparison of protein sequences based on geometry. We measure the performance of such a representation in the context of the protein structural fold prediction problem. We compare the results of classifying different sets of proteins belonging to distinct structural folds against classifications of the same proteins obtained from sequence alone or directly from structural information. We find that sequence alone performs poorly as a structure classifier. We show in contrast that the use of the three dimensional representation of the sequences significantly improves the classification accuracy. We conclude with a discussion of the current limitations of such a representation and with a description of potential improvements.

Sequence- and interactome-based prediction of viral protein hotspots targeting host proteins: a case study for HIV Nef.

Directory of Open Access Journals (Sweden)

Mahdi Sarmady

Full Text Available Virus proteins alter protein pathways of the host toward the synthesis of viral particles by breaking and making edges via binding to host proteins. In this study, we developed a computational approach to predict viral sequence hotspots for binding to host proteins based on sequences of viral and host proteins and literature-curated virus-host protein interactome data. We use a motif discovery algorithm repeatedly on collections of sequences of viral proteins and immediate binding partners of their host targets and choose only those motifs that are conserved on viral sequences and highly statistically enriched among binding partners of virus protein targeted host proteins. Our results match experimental data on binding sites of Nef to host proteins such as MAPK1, VAV1, LCK, HCK, HLA-A, CD4, FYN, and GNB2L1 with high statistical significance but is a poor predictor of Nef binding sites on highly flexible, hoop-like regions. Predicted hotspots recapture CD8 cell epitopes of HIV Nef highlighting their importance in modulating virus-host interactions. Host proteins potentially targeted or outcompeted by Nef appear crowding the T cell receptor, natural killer cell mediated cytotoxicity, and neurotrophin signaling pathways. Scanning of HIV Nef motifs on multiple alignments of hepatitis C protein NS5A produces results consistent with literature, indicating the potential value of the hotspot discovery in advancing our understanding of virus-host crosstalk.

Sequence-based prediction of protein protein interaction using a deep-learning algorithm.

Science.gov (United States)

Sun, Tanlin; Zhou, Bo; Lai, Luhua; Pei, Jianfeng

2017-05-25

Protein-protein interactions (PPIs) are critical for many biological processes. It is therefore important to develop accurate high-throughput methods for identifying PPI to better understand protein function, disease occurrence, and therapy design. Though various computational methods for predicting PPI have been developed, their robustness for prediction with external datasets is unknown. Deep-learning algorithms have achieved successful results in diverse areas, but their effectiveness for PPI prediction has not been tested. We used a stacked autoencoder, a type of deep-learning algorithm, to study the sequence-based PPI prediction. The best model achieved an average accuracy of 97.19% with 10-fold cross-validation. The prediction accuracies for various external datasets ranged from 87.99% to 99.21%, which are superior to those achieved with previous methods. To our knowledge, this research is the first to apply a deep-learning algorithm to sequence-based PPI prediction, and the results demonstrate its potential in this field.

Prediction of protein hydration sites from sequence by modular neural networks

DEFF Research Database (Denmark)

Ehrlich, L.; Reczko, M.; Bohr, Henrik

1998-01-01

The hydration properties of a protein are important determinants of its structure and function. Here, modular neural networks are employed to predict ordered hydration sites using protein sequence information. First, secondary structure and solvent accessibility are predicted from sequence with two...... separate neural networks. These predictions are used as input together with protein sequences for networks predicting hydration of residues, backbone atoms and sidechains. These networks are teined with protein crystal structures. The prediction of hydration is improved by adding information on secondary...... structure and solvent accessibility and, using actual values of these properties, redidue hydration can be predicted to 77% accuracy with a Metthews coefficient of 0.43. However, predicted property data with an accuracy of 60-70% result in less than half the improvement in predictive performance observed...

Relationship between mRNA secondary structure and sequence variability in Chloroplast genes: possible life history implications.

Science.gov (United States)

Krishnan, Neeraja M; Seligmann, Hervé; Rao, Basuthkar J

2008-01-28

Synonymous sites are freer to vary because of redundancy in genetic code. Messenger RNA secondary structure restricts this freedom, as revealed by previous findings in mitochondrial genes that mutations at third codon position nucleotides in helices are more selected against than those in loops. This motivated us to explore the constraints imposed by mRNA secondary structure on evolutionary variability at all codon positions in general, in chloroplast systems. We found that the evolutionary variability and intrinsic secondary structure stability of these sequences share an inverse relationship. Simulations of most likely single nucleotide evolution in Psilotum nudum and Nephroselmis olivacea mRNAs, indicate that helix-forming propensities of mutated mRNAs are greater than those of the natural mRNAs for short sequences and vice-versa for long sequences. Moreover, helix-forming propensity estimated by the percentage of total mRNA in helices increases gradually with mRNA length, saturating beyond 1000 nucleotides. Protection levels of functionally important sites vary across plants and proteins: r-strategists minimize mutation costs in large genes; K-strategists do the opposite. Mrna length presumably predisposes shorter mRNAs to evolve under different constraints than longer mRNAs. The positive correlation between secondary structure protection and functional importance of sites suggests that some sites might be conserved due to packing-protection constraints at the nucleic acid level in addition to protein level constraints. Consequently, nucleic acid secondary structure a priori biases mutations. The converse (exposure of conserved sites) apparently occurs in a smaller number of cases, indicating a different evolutionary adaptive strategy in these plants. The differences between the protection levels of functionally important sites for r- and K-strategists reflect their respective molecular adaptive strategies. These converge with increasing domestication levels of

Protein Function Prediction Based on Sequence and Structure Information

KAUST Repository

Smaili, Fatima Z.

2016-01-01

operate. In this master thesis project, we worked on inferring protein functions based on the primary protein sequence. In the approach we follow, 3D models are first constructed using I-TASSER. Functions are then deduced by structurally matching

Sequence alignment reveals possible MAPK docking motifs on HIV proteins.

Directory of Open Access Journals (Sweden)

Perry Evans

Full Text Available Over the course of HIV infection, virus replication is facilitated by the phosphorylation of HIV proteins by human ERK1 and ERK2 mitogen-activated protein kinases (MAPKs. MAPKs are known to phosphorylate their substrates by first binding with them at a docking site. Docking site interactions could be viable drug targets because the sequences guiding them are more specific than phosphorylation consensus sites. In this study we use multiple bioinformatics tools to discover candidate MAPK docking site motifs on HIV proteins known to be phosphorylated by MAPKs, and we discuss the possibility of targeting docking sites with drugs. Using sequence alignments of HIV proteins of different subtypes, we show that MAPK docking patterns previously described for human proteins appear on the HIV matrix, Tat, and Vif proteins in a strain dependent manner, but are absent from HIV Rev and appear on all HIV Nef strains. We revise the regular expressions of previously annotated MAPK docking patterns in order to provide a subtype independent motif that annotates all HIV proteins. One revision is based on a documented human variant of one of the substrate docking motifs, and the other reduces the number of required basic amino acids in the standard docking motifs from two to one. The proposed patterns are shown to be consistent with in silico docking between ERK1 and the HIV matrix protein. The motif usage on HIV proteins is sufficiently different from human proteins in amino acid sequence similarity to allow for HIV specific targeting using small-molecule drugs.

Feature Selection and the Class Imbalance Problem in Predicting Protein Function from Sequence

NARCIS (Netherlands)

Al-Shahib, A.; Breitling, R.; Gilbert, D.

2005-01-01

Abstract: When the standard approach to predict protein function by sequence homology fails, other alternative methods can be used that require only the amino acid sequence for predicting function. One such approach uses machine learning to predict protein function directly from amino acid sequence

Functional analysis of bipartite begomovirus coat protein promoter sequences

International Nuclear Information System (INIS)

Lacatus, Gabriela; Sunter, Garry

2008-01-01

We demonstrate that the AL2 gene of Cabbage leaf curl virus (CaLCuV) activates the CP promoter in mesophyll and acts to derepress the promoter in vascular tissue, similar to that observed for Tomato golden mosaic virus (TGMV). Binding studies indicate that sequences mediating repression and activation of the TGMV and CaLCuV CP promoter specifically bind different nuclear factors common to Nicotiana benthamiana, spinach and tomato. However, chromatin immunoprecipitation demonstrates that TGMV AL2 can interact with both sequences independently. Binding of nuclear protein(s) from different crop species to viral sequences conserved in both bipartite and monopartite begomoviruses, including TGMV, CaLCuV, Pepper golden mosaic virus and Tomato yellow leaf curl virus suggests that bipartite begomoviruses bind common host factors to regulate the CP promoter. This is consistent with a model in which AL2 interacts with different components of the cellular transcription machinery that bind viral sequences important for repression and activation of begomovirus CP promoters

Protein sequencing via nanopore based devices: a nanofluidics perspective

Science.gov (United States)

Chinappi, Mauro; Cecconi, Fabio

2018-05-01

Proteins perform a huge number of central functions in living organisms, thus all the new techniques allowing their precise, fast and accurate characterization at single-molecule level certainly represent a burst in proteomics with important biomedical impact. In this review, we describe the recent progresses in the developing of nanopore based devices for protein sequencing. We start with a critical analysis of the main technical requirements for nanopore protein sequencing, summarizing some ideas and methodologies that have recently appeared in the literature. In the last sections, we focus on the physical modelling of the transport phenomena occurring in nanopore based devices. The multiscale nature of the problem is discussed and, in this respect, some of the main possible computational approaches are illustrated.

UET: a database of evolutionarily-predicted functional determinants of protein sequences that cluster as functional sites in protein structures.

Science.gov (United States)

Lua, Rhonald C; Wilson, Stephen J; Konecki, Daniel M; Wilkins, Angela D; Venner, Eric; Morgan, Daniel H; Lichtarge, Olivier

2016-01-04

The structure and function of proteins underlie most aspects of biology and their mutational perturbations often cause disease. To identify the molecular determinants of function as well as targets for drugs, it is central to characterize the important residues and how they cluster to form functional sites. The Evolutionary Trace (ET) achieves this by ranking the functional and structural importance of the protein sequence positions. ET uses evolutionary distances to estimate functional distances and correlates genotype variations with those in the fitness phenotype. Thus, ET ranks are worse for sequence positions that vary among evolutionarily closer homologs but better for positions that vary mostly among distant homologs. This approach identifies functional determinants, predicts function, guides the mutational redesign of functional and allosteric specificity, and interprets the action of coding sequence variations in proteins, people and populations. Now, the UET database offers pre-computed ET analyses for the protein structure databank, and on-the-fly analysis of any protein sequence. A web interface retrieves ET rankings of sequence positions and maps results to a structure to identify functionally important regions. This UET database integrates several ways of viewing the results on the protein sequence or structure and can be found at http://mammoth.bcm.tmc.edu/uet/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction

KAUST Repository

Cui, Xuefeng; Lu, Zhiwu; Wang, Sheng; Jing-Yan Wang, Jim; Gao, Xin

2016-01-01

Motivation: Protein homology detection, a fundamental problem in computational biology, is an indispensable step toward predicting protein structures and understanding protein functions. Despite the advances in recent decades on sequence alignment

Improving pairwise comparison of protein sequences with domain co-occurrence

Science.gov (United States)

Gascuel, Olivier

2018-01-01

Comparing and aligning protein sequences is an essential task in bioinformatics. More specifically, local alignment tools like BLAST are widely used for identifying conserved protein sub-sequences, which likely correspond to protein domains or functional motifs. However, to limit the number of false positives, these tools are used with stringent sequence-similarity thresholds and hence can miss several hits, especially for species that are phylogenetically distant from reference organisms. A solution to this problem is then to integrate additional contextual information to the procedure. Here, we propose to use domain co-occurrence to increase the sensitivity of pairwise sequence comparisons. Domain co-occurrence is a strong feature of proteins, since most protein domains tend to appear with a limited number of other domains on the same protein. We propose a method to take this information into account in a typical BLAST analysis and to construct new domain families on the basis of these results. We used Plasmodium falciparum as a case study to evaluate our method. The experimental findings showed an increase of 14% of the number of significant BLAST hits and an increase of 25% of the proteome area that can be covered with a domain. Our method identified 2240 new domains for which, in most cases, no model of the Pfam database could be linked. Moreover, our study of the quality of the new domains in terms of alignment and physicochemical properties show that they are close to that of standard Pfam domains. Source code of the proposed approach and supplementary data are available at: https://gite.lirmm.fr/menichelli/pairwise-comparison-with-cooccurrence PMID:29293498

Discriminating Microbial Species Using Protein Sequence Properties and Machine Learning

NARCIS (Netherlands)

Shahib, Ali Al-; Gilbert, David; Breitling, Rainer

2007-01-01

Much work has been done to identify species-specific proteins in sequenced genomes and hence to determine their function. We assumed that such proteins have specific physico-chemical properties that will discriminate them from proteins in other species. In this paper, we examine the validity of this

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

Directory of Open Access Journals (Sweden)

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

Adhesive proteins of stalked and acorn barnacles display homology with low sequence similarities.

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Jaimie-Leigh Jonker

Full Text Available Barnacle adhesion underwater is an important phenomenon to understand for the prevention of biofouling and potential biotechnological innovations, yet so far, identifying what makes barnacle glue proteins 'sticky' has proved elusive. Examination of a broad range of species within the barnacles may be instructive to identify conserved adhesive domains. We add to extensive information from the acorn barnacles (order Sessilia by providing the first protein analysis of a stalked barnacle adhesive, Lepas anatifera (order Lepadiformes. It was possible to separate the L. anatifera adhesive into at least 10 protein bands using SDS-PAGE. Intense bands were present at approximately 30, 70, 90 and 110 kilodaltons (kDa. Mass spectrometry for protein identification was followed by de novo sequencing which detected 52 peptides of 7-16 amino acids in length. None of the peptides matched published or unpublished transcriptome sequences, but some amino acid sequence similarity was apparent between L. anatifera and closely-related Dosima fascicularis. Antibodies against two acorn barnacle proteins (ab-cp-52k and ab-cp-68k showed cross-reactivity in the adhesive glands of L. anatifera. We also analysed the similarity of adhesive proteins across several barnacle taxa, including Pollicipes pollicipes (a stalked barnacle in the order Scalpelliformes. Sequence alignment of published expressed sequence tags clearly indicated that P. pollicipes possesses homologues for the 19 kDa and 100 kDa proteins in acorn barnacles. Homology aside, sequence similarity in amino acid and gene sequences tended to decline as taxonomic distance increased, with minimum similarities of 18-26%, depending on the gene. The results indicate that some adhesive proteins (e.g. 100 kDa are more conserved within barnacles than others (20 kDa.

Relationships between residue Voronoi volume and sequence conservation in proteins.

Science.gov (United States)

Liu, Jen-Wei; Cheng, Chih-Wen; Lin, Yu-Feng; Chen, Shao-Yu; Hwang, Jenn-Kang; Yen, Shih-Chung

2018-02-01

Functional and biophysical constraints can cause different levels of sequence conservation in proteins. Previously, structural properties, e.g., relative solvent accessibility (RSA) and packing density of the weighted contact number (WCN), have been found to be related to protein sequence conservation (CS). The Voronoi volume has recently been recognized as a new structural property of the local protein structural environment reflecting CS. However, for surface residues, it is sensitive to water molecules surrounding the protein structure. Herein, we present a simple structural determinant termed the relative space of Voronoi volume (RSV); it uses the Voronoi volume and the van der Waals volume of particular residues to quantify the local structural environment. RSV (range, 0-1) is defined as (Voronoi volume-van der Waals volume)/Voronoi volume of the target residue. The concept of RSV describes the extent of available space for every protein residue. RSV and Voronoi profiles with and without water molecules (RSVw, RSV, VOw, and VO) were compared for 554 non-homologous proteins. RSV (without water) showed better Pearson's correlations with CS than did RSVw, VO, or VOw values. The mean correlation coefficient between RSV and CS was 0.51, which is comparable to the correlation between RSA and CS (0.49) and that between WCN and CS (0.56). RSV is a robust structural descriptor with and without water molecules and can quantitatively reflect evolutionary information in a single protein structure. Therefore, it may represent a practical structural determinant to study protein sequence, structure, and function relationships. Copyright © 2017 Elsevier B.V. All rights reserved.

Efficient Feature Selection and Classification of Protein Sequence Data in Bioinformatics

Science.gov (United States)

Faye, Ibrahima; Samir, Brahim Belhaouari; Md Said, Abas

2014-01-01

Bioinformatics has been an emerging area of research for the last three decades. The ultimate aims of bioinformatics were to store and manage the biological data, and develop and analyze computational tools to enhance their understanding. The size of data accumulated under various sequencing projects is increasing exponentially, which presents difficulties for the experimental methods. To reduce the gap between newly sequenced protein and proteins with known functions, many computational techniques involving classification and clustering algorithms were proposed in the past. The classification of protein sequences into existing superfamilies is helpful in predicting the structure and function of large amount of newly discovered proteins. The existing classification results are unsatisfactory due to a huge size of features obtained through various feature encoding methods. In this work, a statistical metric-based feature selection technique has been proposed in order to reduce the size of the extracted feature vector. The proposed method of protein classification shows significant improvement in terms of performance measure metrics: accuracy, sensitivity, specificity, recall, F-measure, and so forth. PMID:25045727

Comprehensive global amino acid sequence analysis of PB1F2 protein of influenza A H5N1 viruses and the influenza A virus subtypes responsible for the 20th-century pandemics.

Science.gov (United States)

Pasricha, Gunisha; Mishra, Akhilesh C; Chakrabarti, Alok K

2013-07-01

PB1F2 is the 11th protein of influenza A virus translated from +1 alternate reading frame of PB1 gene. Since the discovery, varying sizes and functions of the PB1F2 protein of influenza A viruses have been reported. Selection of PB1 gene segment in the pandemics, variable size and pleiotropic effect of PB1F2 intrigued us to analyze amino acid sequences of this protein in various influenza A viruses. Amino acid sequences for PB1F2 protein of influenza A H5N1, H1N1, H2N2, and H3N2 subtypes were obtained from Influenza Research Database. Multiple sequence alignments of the PB1F2 protein sequences of the aforementioned subtypes were used to determine the size, variable and conserved domains and to perform mutational analysis. Analysis showed that 96·4% of the H5N1 influenza viruses harbored full-length PB1F2 protein. Except for the 2009 pandemic H1N1 virus, all the subtypes of the 20th-century pandemic influenza viruses contained full-length PB1F2 protein. Through the years, PB1F2 protein of the H1N1 and H3N2 viruses has undergone much variation. PB1F2 protein sequences of H5N1 viruses showed both human- and avian host-specific conserved domains. Global database of PB1F2 protein revealed that N66S mutation was present only in 3·8% of the H5N1 strains. We found a novel mutation, N84S in the PB1F2 protein of 9·35% of the highly pathogenic avian influenza H5N1 influenza viruses. Varying sizes and mutations of the PB1F2 protein in different influenza A virus subtypes with pandemic potential were obtained. There was genetic divergence of the protein in various hosts which highlighted the host-specific evolution of the virus. However, studies are required to correlate this sequence variability with the virulence and pathogenicity. © 2012 John Wiley & Sons Ltd.

Investigating Correlation between Protein Sequence Similarity and Semantic Similarity Using Gene Ontology Annotations.

Science.gov (United States)

Ikram, Najmul; Qadir, Muhammad Abdul; Afzal, Muhammad Tanvir

2018-01-01

Sequence similarity is a commonly used measure to compare proteins. With the increasing use of ontologies, semantic (function) similarity is getting importance. The correlation between these measures has been applied in the evaluation of new semantic similarity methods, and in protein function prediction. In this research, we investigate the relationship between the two similarity methods. The results suggest absence of a strong correlation between sequence and semantic similarities. There is a large number of proteins with low sequence similarity and high semantic similarity. We observe that Pearson's correlation coefficient is not sufficient to explain the nature of this relationship. Interestingly, the term semantic similarity values above 0 and below 1 do not seem to play a role in improving the correlation. That is, the correlation coefficient depends only on the number of common GO terms in proteins under comparison, and the semantic similarity measurement method does not influence it. Semantic similarity and sequence similarity have a distinct behavior. These findings are of significant effect for future works on protein comparison, and will help understand the semantic similarity between proteins in a better way.

Sequence heterogeneity accelerates protein search for targets on DNA

International Nuclear Information System (INIS)

Shvets, Alexey A.; Kolomeisky, Anatoly B.

2015-01-01

The process of protein search for specific binding sites on DNA is fundamentally important since it marks the beginning of all major biological processes. We present a theoretical investigation that probes the role of DNA sequence symmetry, heterogeneity, and chemical composition in the protein search dynamics. Using a discrete-state stochastic approach with a first-passage events analysis, which takes into account the most relevant physical-chemical processes, a full analytical description of the search dynamics is obtained. It is found that, contrary to existing views, the protein search is generally faster on DNA with more heterogeneous sequences. In addition, the search dynamics might be affected by the chemical composition near the target site. The physical origins of these phenomena are discussed. Our results suggest that biological processes might be effectively regulated by modifying chemical composition, symmetry, and heterogeneity of a genome

Sequence heterogeneity accelerates protein search for targets on DNA

Energy Technology Data Exchange (ETDEWEB)

Shvets, Alexey A.; Kolomeisky, Anatoly B., E-mail: tolya@rice.edu [Department of Chemistry and Center for Theoretical Biological Physics, Rice University, Houston, Texas 77005 (United States)

2015-12-28

The process of protein search for specific binding sites on DNA is fundamentally important since it marks the beginning of all major biological processes. We present a theoretical investigation that probes the role of DNA sequence symmetry, heterogeneity, and chemical composition in the protein search dynamics. Using a discrete-state stochastic approach with a first-passage events analysis, which takes into account the most relevant physical-chemical processes, a full analytical description of the search dynamics is obtained. It is found that, contrary to existing views, the protein search is generally faster on DNA with more heterogeneous sequences. In addition, the search dynamics might be affected by the chemical composition near the target site. The physical origins of these phenomena are discussed. Our results suggest that biological processes might be effectively regulated by modifying chemical composition, symmetry, and heterogeneity of a genome.

Protein sequences clustering of herpes virus by using Tribe Markov clustering (Tribe-MCL)

Science.gov (United States)

Bustamam, A.; Siswantining, T.; Febriyani, N. L.; Novitasari, I. D.; Cahyaningrum, R. D.

2017-07-01

The herpes virus can be found anywhere and one of the important characteristics is its ability to cause acute and chronic infection at certain times so as a result of the infection allows severe complications occurred. The herpes virus is composed of DNA containing protein and wrapped by glycoproteins. In this work, the Herpes viruses family is classified and analyzed by clustering their protein-sequence using Tribe Markov Clustering (Tribe-MCL) algorithm. Tribe-MCL is an efficient clustering method based on the theory of Markov chains, to classify protein families from protein sequences using pre-computed sequence similarity information. We implement the Tribe-MCL algorithm using an open source program of R. We select 24 protein sequences of Herpes virus obtained from NCBI database. The dataset consists of three types of glycoprotein B, F, and H. Each type has eight herpes virus that infected humans. Based on our simulation using different inflation factor r=1.5, 2, 3 we find a various number of the clusters results. The greater the inflation factor the greater the number of their clusters. Each protein will grouped together in the same type of protein.

A machine learning approach for the identification of odorant binding proteins from sequence-derived properties

Directory of Open Access Journals (Sweden)

Suganthan PN

2007-09-01

Full Text Available Abstract Background Odorant binding proteins (OBPs are believed to shuttle odorants from the environment to the underlying odorant receptors, for which they could potentially serve as odorant presenters. Although several sequence based search methods have been exploited for protein family prediction, less effort has been devoted to the prediction of OBPs from sequence data and this area is more challenging due to poor sequence identity between these proteins. Results In this paper, we propose a new algorithm that uses Regularized Least Squares Classifier (RLSC in conjunction with multiple physicochemical properties of amino acids to predict odorant-binding proteins. The algorithm was applied to the dataset derived from Pfam and GenDiS database and we obtained overall prediction accuracy of 97.7% (94.5% and 98.4% for positive and negative classes respectively. Conclusion Our study suggests that RLSC is potentially useful for predicting the odorant binding proteins from sequence-derived properties irrespective of sequence similarity. Our method predicts 92.8% of 56 odorant binding proteins non-homologous to any protein in the swissprot database and 97.1% of the 414 independent dataset proteins, suggesting the usefulness of RLSC method for facilitating the prediction of odorant binding proteins from sequence information.

Induced variability for protein content in bread wheat

International Nuclear Information System (INIS)

Singhal, N.C.; Jain, H.K.; Austin, A.

1978-01-01

The negative correlation observed between seed weight and percentage of protein in the seeds of bread wheat is a function of the fact that increase in seed size is commonly associated with a disproportionately large deposition of starch relative to the protein. The present study, as well as our earlier analysis, shows that exceptional genotypes of bread wheat do exist in which increase in seed weight is associated with a relatively larger synthesis of protein. In the course of the present investigation on radiation-induced variability, genotypes showing more efficient synthesis of storage proteins in their seeds have been identified in the M 2 and M 3 generations. The induced variability, thus, makes it possible to break the negative correlation between seed weight and percentage of protein in the seed. Based on these findings, it has been suggested that in a protein improvement programme on bread wheat it should be useful to select in the segregating generation plants showing increase in seed size, some of which can be expected to be relatively more efficient in protein synthesis and give higher protein yields. (author)

Aligning protein sequence and analysing substitution pattern using ...

Indian Academy of Sciences (India)

Prakash

Aligning protein sequences using a score matrix has became a routine but valuable method in modern biological ..... the amino acids according to their substitution behaviour ...... which may cause great change (e.g. prolonging the helix) in.

Chaos game representation of functional protein sequences, and simulation and multifractal analysis of induced measures

International Nuclear Information System (INIS)

Zu-Guo, Yu; Qian-Jun, Xiao; Long, Shi; Jun-Wu, Yu; Anh, Vo

2010-01-01

Investigating the biological function of proteins is a key aspect of protein studies. Bioinformatic methods become important for studying the biological function of proteins. In this paper, we first give the chaos game representation (CGR) of randomly-linked functional protein sequences, then propose the use of the recurrent iterated function systems (RIFS) in fractal theory to simulate the measure based on their chaos game representations. This method helps to extract some features of functional protein sequences, and furthermore the biological functions of these proteins. Then multifractal analysis of the measures based on the CGRs of randomly-linked functional protein sequences are performed. We find that the CGRs have clear fractal patterns. The numerical results show that the RIFS can simulate the measure based on the CGR very well. The relative standard error and the estimated probability matrix in the RIFS do not depend on the order to link the functional protein sequences. The estimated probability matrices in the RIFS with different biological functions are evidently different. Hence the estimated probability matrices in the RIFS can be used to characterise the difference among linked functional protein sequences with different biological functions. From the values of the D q curves, one sees that these functional protein sequences are not completely random. The D q of all linked functional proteins studied are multifractal-like and sufficiently smooth for the C q (analogous to specific heat) curves to be meaningful. Furthermore, the D q curves of the measure μ based on their CGRs for different orders to link the functional protein sequences are almost identical if q ≥ 0. Finally, the C q curves of all linked functional proteins resemble a classical phase transition at a critical point. (cross-disciplinary physics and related areas of science and technology)

The SBASE protein domain library, release 8.0: a collection of annotated protein sequence segments.

Science.gov (United States)

Murvai, J; Vlahovicek, K; Barta, E; Pongor, S

2001-01-01

SBASE 8.0 is the eighth release of the SBASE library of protein domain sequences that contains 294 898 annotated structural, functional, ligand-binding and topogenic segments of proteins, cross-referenced to most major sequence databases and sequence pattern collections. The entries are clustered into over 2005 statistically validated domain groups (SBASE-A) and 595 non-validated groups (SBASE-B), provided with several WWW-based search and browsing facilities for online use. A domain-search facility was developed, based on non-parametric pattern recognition methods, including artificial neural networks. SBASE 8.0 is freely available by anonymous 'ftp' file transfer from ftp.icgeb.trieste.it. Automated searching of SBASE can be carried out with the WWW servers http://www.icgeb.trieste.it/sbase/ and http://sbase.abc. hu/sbase/.

The nucleotide sequence of human transition protein 1 cDNA

Energy Technology Data Exchange (ETDEWEB)

Luerssen, H; Hoyer-Fender, S; Engel, W [Universitaet Goettingen (West Germany)

1988-08-11

The authors have screened a human testis cDNA library with an oligonucleotide of 81 mer prepared according to a part of the published nucleotide sequence of the rat transition protein TP 1. They have isolated a cDNA clone with the length of 441 bp containing the coding region of 162 bp for human transition protein 1. There is about 84% homology in the coding region of the sequence compared to rat. The human cDNA-clone encodes a polypeptide of 54 amino acids of which 7 are different to that of rat.

Rapid evolution of the sequences and gene repertoires of secreted proteins in bacteria.

Directory of Open Access Journals (Sweden)

Teresa Nogueira

Full Text Available Proteins secreted to the extracellular environment or to the periphery of the cell envelope, the secretome, play essential roles in foraging, antagonistic and mutualistic interactions. We hypothesize that arms races, genetic conflicts and varying selective pressures should lead to the rapid change of sequences and gene repertoires of the secretome. The analysis of 42 bacterial pan-genomes shows that secreted, and especially extracellular proteins, are predominantly encoded in the accessory genome, i.e. among genes not ubiquitous within the clade. Genes encoding outer membrane proteins might engage more frequently in intra-chromosomal gene conversion because they are more often in multi-genic families. The gene sequences encoding the secretome evolve faster than the rest of the genome and in particular at non-synonymous positions. Cell wall proteins in Firmicutes evolve particularly fast when compared with outer membrane proteins of Proteobacteria. Virulence factors are over-represented in the secretome, notably in outer membrane proteins, but cell localization explains more of the variance in substitution rates and gene repertoires than sequence homology to known virulence factors. Accordingly, the repertoires and sequences of the genes encoding the secretome change fast in the clades of obligatory and facultative pathogens and also in the clades of mutualists and free-living bacteria. Our study shows that cell localization shapes genome evolution. In agreement with our hypothesis, the repertoires and the sequences of genes encoding secreted proteins evolve fast. The particularly rapid change of extracellular proteins suggests that these public goods are key players in bacterial adaptation.

Cloning and sequence analysis of cDNA coding for rat nucleolar protein C23

International Nuclear Information System (INIS)

Ghaffari, S.H.; Olson, M.O.J.

1986-01-01

Using synthetic oligonucleotides as primers and probes, the authors have isolated and sequenced cDNA clones encoding protein C23, a putative nucleolus organizer protein. Poly(A + ) RNA was isolated from rat Novikoff hepatoma cells and enriched in C23 mRNA by sucrose density gradient ultracentrifugation. Two deoxyoligonuleotides, a 48- and a 27-mer, were synthesized on the basis of amino acid sequence from the C-terminal half of protein C23 and cDNA sequence data from CHO cell protein. The 48-mer was used a primer for synthesis of cDNA which was then inserted into plasmid pUC9. Transformed bacterial colonies were screened by hybridization with 32 P labeled 27-mer. Two clones among 5000 gave a strong positive signal. Plasmid DNAs from these clones were purified and characterized by blotting and nucleotide sequence analysis. The length of C23 mRNA was estimated to be 3200 bases in a northern blot analysis. The sequence of a 267 b.p. insert shows high homology with the CHO cDNA with only 9 nucleotide differences and an identical amino acid sequence. These studies indicate that this region of the protein is highly conserved

Integrated analysis of RNA-binding protein complexes using in vitro selection and high-throughput sequencing and sequence specificity landscapes (SEQRS).

Science.gov (United States)

Lou, Tzu-Fang; Weidmann, Chase A; Killingsworth, Jordan; Tanaka Hall, Traci M; Goldstrohm, Aaron C; Campbell, Zachary T

2017-04-15

RNA-binding proteins (RBPs) collaborate to control virtually every aspect of RNA function. Tremendous progress has been made in the area of global assessment of RBP specificity using next-generation sequencing approaches both in vivo and in vitro. Understanding how protein-protein interactions enable precise combinatorial regulation of RNA remains a significant problem. Addressing this challenge requires tools that can quantitatively determine the specificities of both individual proteins and multimeric complexes in an unbiased and comprehensive way. One approach utilizes in vitro selection, high-throughput sequencing, and sequence-specificity landscapes (SEQRS). We outline a SEQRS experiment focused on obtaining the specificity of a multi-protein complex between Drosophila RBPs Pumilio (Pum) and Nanos (Nos). We discuss the necessary controls in this type of experiment and examine how the resulting data can be complemented with structural and cell-based reporter assays. Additionally, SEQRS data can be integrated with functional genomics data to uncover biological function. Finally, we propose extensions of the technique that will enhance our understanding of multi-protein regulatory complexes assembled onto RNA. Copyright © 2016 Elsevier Inc. All rights reserved.

Next-Generation Sequencing for Binary Protein-Protein Interactions

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Bernhard eSuter

2015-12-01

Full Text Available The yeast two-hybrid (Y2H system exploits host cell genetics in order to display binary protein-protein interactions (PPIs via defined and selectable phenotypes. Numerous improvements have been made to this method, adapting the screening principle for diverse applications, including drug discovery and the scale-up for proteome wide interaction screens in human and other organisms. Here we discuss a systematic workflow and analysis scheme for screening data generated by Y2H and related assays that includes high-throughput selection procedures, readout of comprehensive results via next-generation sequencing (NGS, and the interpretation of interaction data via quantitative statistics. The novel assays and tools will serve the broader scientific community to harness the power of NGS technology to address PPI networks in health and disease. We discuss examples of how this next-generation platform can be applied to address specific questions in diverse fields of biology and medicine.

Exploring sequence characteristics related to high-level production of secreted proteins in Aspergillus niger.

Directory of Open Access Journals (Sweden)

Bastiaan A van den Berg

Full Text Available Protein sequence features are explored in relation to the production of over-expressed extracellular proteins by fungi. Knowledge on features influencing protein production and secretion could be employed to improve enzyme production levels in industrial bioprocesses via protein engineering. A large set, over 600 homologous and nearly 2,000 heterologous fungal genes, were overexpressed in Aspergillus niger using a standardized expression cassette and scored for high versus no production. Subsequently, sequence-based machine learning techniques were applied for identifying relevant DNA and protein sequence features. The amino-acid composition of the protein sequence was found to be most predictive and interpretation revealed that, for both homologous and heterologous gene expression, the same features are important: tyrosine and asparagine composition was found to have a positive correlation with high-level production, whereas for unsuccessful production, contributions were found for methionine and lysine composition. The predictor is available online at http://bioinformatics.tudelft.nl/hipsec. Subsequent work aims at validating these findings by protein engineering as a method for increasing expression levels per gene copy.

Partial summations of stationary sequences of non-Gaussian random variables

DEFF Research Database (Denmark)

Mohr, Gunnar; Ditlevsen, Ove Dalager

1996-01-01

The distribution of the sum of a finite number of identically distributed random variables is in many cases easily determined given that the variables are independent. The moments of any order of the sum can always be expressed by the moments of the single term without computational problems...... of convergence of the distribution of a sum (or an integral) of mutually dependent random variables to the Gaussian distribution. The paper is closely related to the work in Ditlevsen el al. [Ditlevsen, O., Mohr, G. & Hoffmeyer, P. Integration of non-Gaussian fields. Prob. Engng Mech 11 (1996) 15-23](2)....... lognormal variables or polynomials of standard Gaussian variables. The dependency structure is induced by specifying the autocorrelation structure of the sequence of standard Gaussian variables. Particularly useful polynomials are the Winterstein approximations that distributionally fit with non...

JACOP: A simple and robust method for the automated classification of protein sequences with modular architecture

Directory of Open Access Journals (Sweden)

Pagni Marco

2005-08-01

Full Text Available Abstract Background Whole-genome sequencing projects are rapidly producing an enormous number of new sequences. Consequently almost every family of proteins now contains hundreds of members. It has thus become necessary to develop tools, which classify protein sequences automatically and also quickly and reliably. The difficulty of this task is intimately linked to the mechanism by which protein sequences diverge, i.e. by simultaneous residue substitutions, insertions and/or deletions and whole domain reorganisations (duplications/swapping/fusion. Results Here we present a novel approach, which is based on random sampling of sub-sequences (probes out of a set of input sequences. The probes are compared to the input sequences, after a normalisation step; the results are used to partition the input sequences into homogeneous groups of proteins. In addition, this method provides information on diagnostic parts of the proteins. The performance of this method is challenged by two data sets. The first one contains the sequences of prokaryotic lyases that could be arranged as a multiple sequence alignment. The second one contains all proteins from Swiss-Prot Release 36 with at least one Src homology 2 (SH2 domain – a classical example for proteins with modular architecture. Conclusion The outcome of our method is robust, highly reproducible as shown using bootstrap and resampling validation procedures. The results are essentially coherent with the biology. This method depends solely on well-established publicly available software and algorithms.

Sequence charge decoration dictates coil-globule transition in intrinsically disordered proteins.

Science.gov (United States)

Firman, Taylor; Ghosh, Kingshuk

2018-03-28

We present an analytical theory to compute conformations of heteropolymers-applicable to describe disordered proteins-as a function of temperature and charge sequence. The theory describes coil-globule transition for a given protein sequence when temperature is varied and has been benchmarked against the all-atom Monte Carlo simulation (using CAMPARI) of intrinsically disordered proteins (IDPs). In addition, the model quantitatively shows how subtle alterations of charge placement in the primary sequence-while maintaining the same charge composition-can lead to significant changes in conformation, even as drastic as a coil (swelled above a purely random coil) to globule (collapsed below a random coil) and vice versa. The theory provides insights on how to control (enhance or suppress) these changes by tuning the temperature (or solution condition) and charge decoration. As an application, we predict the distribution of conformations (at room temperature) of all naturally occurring IDPs in the DisProt database and notice significant size variation even among IDPs with a similar composition of positive and negative charges. Based on this, we provide a new diagram-of-states delineating the sequence-conformation relation for proteins in the DisProt database. Next, we study the effect of post-translational modification, e.g., phosphorylation, on IDP conformations. Modifications as little as two-site phosphorylation can significantly alter the size of an IDP with everything else being constant (temperature, salt concentration, etc.). However, not all possible modification sites have the same effect on protein conformations; there are certain "hot spots" that can cause maximal change in conformation. The location of these "hot spots" in the parent sequence can readily be identified by using a sequence charge decoration metric originally introduced by Sawle and Ghosh. The ability of our model to predict conformations (both expanded and collapsed states) of IDPs at a high

The Effects of Delayed Reinforcement on Variability and Repetition of Response Sequences

Science.gov (United States)

Odum, Amy L.; Ward, Ryan D.; Burke, K. Anne; Barnes, Christopher A.

2006-01-01

Four experiments examined the effects of delays to reinforcement on key peck sequences of pigeons maintained under multiple schedules of contingencies that produced variable or repetitive behavior. In Experiments 1, 2, and 4, in the repeat component only the sequence right-right-left-left earned food, and in the vary component four-response…

MODexplorer: an integrated tool for exploring protein sequence, structure and function relationships.

KAUST Repository

Kosinski, Jan; Barbato, Alessandro; Tramontano, Anna

2013-01-01

SUMMARY: MODexplorer is an integrated tool aimed at exploring the sequence, structural and functional diversity in protein families useful in homology modeling and in analyzing protein families in general. It takes as input either the sequence or the structure of a protein and provides alignments with its homologs along with a variety of structural and functional annotations through an interactive interface. The annotations include sequence conservation, similarity scores, ligand-, DNA- and RNA-binding sites, secondary structure, disorder, crystallographic structure resolution and quality scores of models implied by the alignments to the homologs of known structure. MODexplorer can be used to analyze sequence and structural conservation among the structures of similar proteins, to find structures of homologs solved in different conformational state or with different ligands and to transfer functional annotations. Furthermore, if the structure of the query is not known, MODexplorer can be used to select the modeling templates taking all this information into account and to build a comparative model. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://modorama.biocomputing.it/modexplorer. Website implemented in HTML and JavaScript with all major browsers supported. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MODexplorer: an integrated tool for exploring protein sequence, structure and function relationships.

KAUST Repository

Kosinski, Jan

2013-02-08

SUMMARY: MODexplorer is an integrated tool aimed at exploring the sequence, structural and functional diversity in protein families useful in homology modeling and in analyzing protein families in general. It takes as input either the sequence or the structure of a protein and provides alignments with its homologs along with a variety of structural and functional annotations through an interactive interface. The annotations include sequence conservation, similarity scores, ligand-, DNA- and RNA-binding sites, secondary structure, disorder, crystallographic structure resolution and quality scores of models implied by the alignments to the homologs of known structure. MODexplorer can be used to analyze sequence and structural conservation among the structures of similar proteins, to find structures of homologs solved in different conformational state or with different ligands and to transfer functional annotations. Furthermore, if the structure of the query is not known, MODexplorer can be used to select the modeling templates taking all this information into account and to build a comparative model. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://modorama.biocomputing.it/modexplorer. Website implemented in HTML and JavaScript with all major browsers supported. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Comprehensive global amino acid sequence analysis of PB1F2 protein of influenza A H5N1 viruses and the influenza A virus subtypes responsible for the 20th‐century pandemics

Science.gov (United States)

Pasricha, Gunisha; Mishra, Akhilesh C.; Chakrabarti, Alok K.

2012-01-01

Please cite this paper as: Pasricha et al. (2012) Comprehensive global amino acid sequence analysis of PB1F2 protein of influenza A H5N1 viruses and the Influenza A virus subtypes responsible for the 20th‐century pandemics. Influenza and Other Respiratory Viruses 7(4), 497–505. Background  PB1F2 is the 11th protein of influenza A virus translated from +1 alternate reading frame of PB1 gene. Since the discovery, varying sizes and functions of the PB1F2 protein of influenza A viruses have been reported. Selection of PB1 gene segment in the pandemics, variable size and pleiotropic effect of PB1F2 intrigued us to analyze amino acid sequences of this protein in various influenza A viruses. Methods  Amino acid sequences for PB1F2 protein of influenza A H5N1, H1N1, H2N2, and H3N2 subtypes were obtained from Influenza Research Database. Multiple sequence alignments of the PB1F2 protein sequences of the aforementioned subtypes were used to determine the size, variable and conserved domains and to perform mutational analysis. Results  Analysis showed that 96·4% of the H5N1 influenza viruses harbored full‐length PB1F2 protein. Except for the 2009 pandemic H1N1 virus, all the subtypes of the 20th‐century pandemic influenza viruses contained full‐length PB1F2 protein. Through the years, PB1F2 protein of the H1N1 and H3N2 viruses has undergone much variation. PB1F2 protein sequences of H5N1 viruses showed both human‐ and avian host‐specific conserved domains. Global database of PB1F2 protein revealed that N66S mutation was present only in 3·8% of the H5N1 strains. We found a novel mutation, N84S in the PB1F2 protein of 9·35% of the highly pathogenic avian influenza H5N1 influenza viruses. Conclusions  Varying sizes and mutations of the PB1F2 protein in different influenza A virus subtypes with pandemic potential were obtained. There was genetic divergence of the protein in various hosts which highlighted the host‐specific evolution of the virus

Application of native signal sequences for recombinant proteins secretion in Pichia pastoris

DEFF Research Database (Denmark)

Borodina, Irina; Do, Duy Duc; Eriksen, Jens C.

Background Methylotrophic yeast Pichia pastoris is widely used for recombinant protein production, largely due to its ability to secrete correctly folded heterologous proteins to the fermentation medium. Secretion is usually achieved by cloning the recombinant gene after a leader sequence, where...... alpha‐mating factor (MF) prepropeptide from Saccharomyces cerevisiae is most commonly used. Our aim was to test whether signal peptides from P. pastoris native secreted proteins could be used to direct secretion of recombinant proteins. Results Eleven native signal peptides from P. pastoris were tested...... by optimization of expression of three different proteins in P. pastoris. Conclusions Native signal peptides from P. pastoris can be used to direct secretion of recombinant proteins. A novel USER‐based P. pastoris system allows easy cloning of protein‐coding gene with the promoter and leader sequence of choice....

Prediction of glutathionylation sites in proteins using minimal sequence information and their experimental validation.

Science.gov (United States)

Pal, Debojyoti; Sharma, Deepak; Kumar, Mukesh; Sandur, Santosh K

2016-09-01

S-glutathionylation of proteins plays an important role in various biological processes and is known to be protective modification during oxidative stress. Since, experimental detection of S-glutathionylation is labor intensive and time consuming, bioinformatics based approach is a viable alternative. Available methods require relatively longer sequence information, which may prevent prediction if sequence information is incomplete. Here, we present a model to predict glutathionylation sites from pentapeptide sequences. It is based upon differential association of amino acids with glutathionylated and non-glutathionylated cysteines from a database of experimentally verified sequences. This data was used to calculate position dependent F-scores, which measure how a particular amino acid at a particular position may affect the likelihood of glutathionylation event. Glutathionylation-score (G-score), indicating propensity of a sequence to undergo glutathionylation, was calculated using position-dependent F-scores for each amino-acid. Cut-off values were used for prediction. Our model returned an accuracy of 58% with Matthew's correlation-coefficient (MCC) value of 0.165. On an independent dataset, our model outperformed the currently available model, in spite of needing much less sequence information. Pentapeptide motifs having high abundance among glutathionylated proteins were identified. A list of potential glutathionylation hotspot sequences were obtained by assigning G-scores and subsequent Protein-BLAST analysis revealed a total of 254 putative glutathionable proteins, a number of which were already known to be glutathionylated. Our model predicted glutathionylation sites in 93.93% of experimentally verified glutathionylated proteins. Outcome of this study may assist in discovering novel glutathionylation sites and finding candidate proteins for glutathionylation.

RSARF: Prediction of residue solvent accessibility from protein sequence using random forest method

KAUST Repository

Ganesan, Pugalenthi; Kandaswamy, Krishna Kumar Umar; Chou -, Kuochen; Vivekanandan, Saravanan; Kolatkar, Prasanna R.

2012-01-01

Prediction of protein structure from its amino acid sequence is still a challenging problem. The complete physicochemical understanding of protein folding is essential for the accurate structure prediction. Knowledge of residue solvent accessibility gives useful insights into protein structure prediction and function prediction. In this work, we propose a random forest method, RSARF, to predict residue accessible surface area from protein sequence information. The training and testing was performed using 120 proteins containing 22006 residues. For each residue, buried and exposed state was computed using five thresholds (0%, 5%, 10%, 25%, and 50%). The prediction accuracy for 0%, 5%, 10%, 25%, and 50% thresholds are 72.9%, 78.25%, 78.12%, 77.57% and 72.07% respectively. Further, comparison of RSARF with other methods using a benchmark dataset containing 20 proteins shows that our approach is useful for prediction of residue solvent accessibility from protein sequence without using structural information. The RSARF program, datasets and supplementary data are available at http://caps.ncbs.res.in/download/pugal/RSARF/. - See more at: http://www.eurekaselect.com/89216/article#sthash.pwVGFUjq.dpuf

Biological characterization and variability of the nucleocapsid protein gene of Groundnut bud necrosis virus isolates infecting pea from India

Directory of Open Access Journals (Sweden)

Mohammad AKRAM

2012-09-01

Full Text Available A disease of pea characterized by browning in veins, leaves and stems, mostly in growing tips, and brown circular spots on pods, was recorded in four districts of Uttar Pradesh, India. The causal agent of this disease was detected by reverse transcription-polymerase chain reaction (RT-PCR using primers pair HRP 26/HRP 28 and identified as Groundnut bud necrosis virus (GBNV on the basis of nucleocapsid protein (NP gene sequence. Virus isolates from Bareilly (BRY, Kanpur (KNP, Udham Singh Nagar (USN and Shahjahanpur (SJP were designated as GBNV-[Pea_BRY], GBNV-[Pea_KNP], GBNV-[Pea_USN] and GBNV-[Pea_SJP] and their NP genes sequenced. The sequence data of each isolate were deposited at NCBI database (JF281101-JF281104. The complete nucleotide sequence of the NP genes of all the GBNV isolates had a single open reading frame of 831 nucleotides and 276 amino acids. The isolates had among them 2% variability at amino acid level and 2‒3 variability at nucleotide level, but had variability with other GBNV isolates of fabaceous hosts in the range of 0‒6% at amino acid level and 1‒8% at nucleotide level. Though this variation in nucleotide sequences of GBNV isolates from fabaceous hosts is within the limits of species demarcation for tospoviruses, formation of a separate cluster within the GBNV isolates indicates the possibility of distinct variants in GBNV.

Alternative splicing affects the targeting sequence of peroxisome proteins in Arabidopsis.

Science.gov (United States)

An, Chuanjing; Gao, Yuefang; Li, Jinyu; Liu, Xiaomin; Gao, Fuli; Gao, Hongbo

2017-07-01

A systematic analysis of the Arabidopsis genome in combination with localization experiments indicates that alternative splicing affects the peroxisomal targeting sequence of at least 71 genes in Arabidopsis. Peroxisomes are ubiquitous eukaryotic cellular organelles that play a key role in diverse metabolic functions. All peroxisome proteins are encoded by nuclear genes and target to peroxisomes mainly through two types of targeting signals: peroxisomal targeting signal type 1 (PTS1) and PTS2. Alternative splicing (AS) is a process occurring in all eukaryotes by which a single pre-mRNA can generate multiple mRNA variants, often encoding proteins with functional differences. However, the effects of AS on the PTS1 or PTS2 and the targeting of the protein were rarely studied, especially in plants. Here, we systematically analyzed the genome of Arabidopsis, and found that the C-terminal targeting sequence PTS1 of 66 genes and the N-terminal targeting sequence PTS2 of 5 genes are affected by AS. Experimental determination of the targeting of selected protein isoforms further demonstrated that AS at both the 5' and 3' region of a gene can affect the inclusion of PTS2 and PTS1, respectively. This work underscores the importance of AS on the global regulation of peroxisome protein targeting.

Protein sequence annotation in the genome era: the annotation concept of SWISS-PROT+TREMBL.

Science.gov (United States)

Apweiler, R; Gateau, A; Contrino, S; Martin, M J; Junker, V; O'Donovan, C; Lang, F; Mitaritonna, N; Kappus, S; Bairoch, A

1997-01-01

SWISS-PROT is a curated protein sequence database which strives to provide a high level of annotation, a minimal level of redundancy and high level of integration with other databases. Ongoing genome sequencing projects have dramatically increased the number of protein sequences to be incorporated into SWISS-PROT. Since we do not want to dilute the quality standards of SWISS-PROT by incorporating sequences without proper sequence analysis and annotation, we cannot speed up the incorporation of new incoming data indefinitely. However, as we also want to make the sequences available as fast as possible, we introduced TREMBL (TRanslation of EMBL nucleotide sequence database), a supplement to SWISS-PROT. TREMBL consists of computer-annotated entries in SWISS-PROT format derived from the translation of all coding sequences (CDS) in the EMBL nucleotide sequence database, except for CDS already included in SWISS-PROT. While TREMBL is already of immense value, its computer-generated annotation does not match the quality of SWISS-PROTs. The main difference is in the protein functional information attached to sequences. With this in mind, we are dedicating substantial effort to develop and apply computer methods to enhance the functional information attached to TREMBL entries.

Experimental Rugged Fitness Landscape in Protein Sequence Space

OpenAIRE

HAYASHI, Yuuki; 相田, 拓洋; TOYOTA, Hitoshi; 伏見, 譲; URABE, Itaru; YOMO, Tetsuya

2006-01-01

The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12-130 of the initial random polypeptide and selection for infectivity, the selected phag...

A method for partitioning the information contained in a protein sequence between its structure and function.

Science.gov (United States)

Possenti, Andrea; Vendruscolo, Michele; Camilloni, Carlo; Tiana, Guido

2018-05-23

Proteins employ the information stored in the genetic code and translated into their sequences to carry out well-defined functions in the cellular environment. The possibility to encode for such functions is controlled by the balance between the amount of information supplied by the sequence and that left after that the protein has folded into its structure. We study the amount of information necessary to specify the protein structure, providing an estimate that keeps into account the thermodynamic properties of protein folding. We thus show that the information remaining in the protein sequence after encoding for its structure (the 'information gap') is very close to what needed to encode for its function and interactions. Then, by predicting the information gap directly from the protein sequence, we show that it may be possible to use these insights from information theory to discriminate between ordered and disordered proteins, to identify unknown functions, and to optimize artificially-designed protein sequences. This article is protected by copyright. All rights reserved. © 2018 Wiley Periodicals, Inc.

Cultural conservatism and variability in the Acheulian sequence of Gesher Benot Ya'aqov.

Science.gov (United States)

Sharon, Gonen; Alperson-Afil, Nira; Goren-Inbar, Naama

2011-04-01

The Acheulian Technocomplex exhibits two phenomena: variability and conservatism. Variability is expressed in the composition and frequencies of tool types, particularly in the varying frequencies of bifaces (handaxes and cleavers). Conservatism is expressed in the continuous presence of bifaces along an immense time trajectory. The site of Gesher Benot Ya'aqov (GBY) offers a unique opportunity to study aspects of variability and conservatism as a result of its long cultural-stratigraphic sequence containing superimposed lithic assemblages. This study explores aspects of variability and conservatism within the Acheulian lithic assemblages of GBY, with emphasis placed on the bifacial tools. While variability has been studied through a comparison of typological frequencies in a series of assemblages from the site, evidence for conservatism was examined in the production modes expressed by the reduction sequence of the bifaces. We demonstrate that while pronounced typological variability is observed among the GBY assemblages, they were all manufactured by the same technology. The technology, size, and morphology of the bifaces throughout the entire stratigraphic sequence of GBY reflect the strong conservatism of their makers. We conclude that the biface frequency cannot be considered as a chrono/cultural marker that might otherwise allow us to distinguish between different phases within the Acheulian. The variability observed within the assemblages is explained as a result of different activities, tasks, and functions, which were carried out at specific localities along the shores of the paleo-Hula Lake in the early Middle Pleistocene. Copyright © 2010 Elsevier Ltd. All rights reserved.

High production of llama variable heavy-chain antibody fragment (VHH) fused to various reader proteins by Aspergillus oryzae.

Science.gov (United States)

Hisada, Hiromoto; Tsutsumi, Hiroko; Ishida, Hiroki; Hata, Yoji

2013-01-01

Llama variable heavy-chain antibody fragment (VHH) fused to four different reader proteins was produced and secreted in culture medium by Aspergillus oryzae. These fusion proteins consisted of N-terminal reader proteins, VHH, and a C-terminal his-tag sequence which facilitated purification using one-step his-tag affinity chromatography. SDS-PAGE analysis of the deglycosylated purified fusion proteins confirmed that the molecular weight of each corresponded to the expected sum of VHH and the respective reader proteins. The apparent high molecular weight reader protein glucoamylase (GlaB) was found to be suitable for efficient VHH production. The GlaB-VHH-His protein bound its antigen, human chorionic gonadotropin, and was detectable by a new ELISA-based method using a coupled assay with glucoamylase, glucose oxidase, peroxidase, maltose, and 3,3',5,5'-tetramethylbenzidine as substrates. Addition of potassium phosphate to the culture medium induced secretion of 0.61 mg GlaB-VHH-His protein/ml culture medium in 5 days.

Seeing the trees through the forest : sequence-based homo- and heteromeric protein-protein interaction sites prediction using random forest

NARCIS (Netherlands)

Hou, Qingzhen; De Geest, Paul F.G.; Vranken, Wim F.; Heringa, Jaap; Feenstra, K. Anton

2017-01-01

Motivation: Genome sequencing is producing an ever-increasing amount of associated protein sequences. Few of these sequences have experimentally validated annotations, however, and computational predictions are becoming increasingly successful in producing such annotations. One key challenge remains

Combining protein sequence, structure, and dynamics: A novel approach for functional evolution analysis of PAS domain superfamily.

Science.gov (United States)

Dong, Zheng; Zhou, Hongyu; Tao, Peng

2018-02-01

PAS domains are widespread in archaea, bacteria, and eukaryota, and play important roles in various functions. In this study, we aim to explore functional evolutionary relationship among proteins in the PAS domain superfamily in view of the sequence-structure-dynamics-function relationship. We collected protein sequences and crystal structure data from RCSB Protein Data Bank of the PAS domain superfamily belonging to three biological functions (nucleotide binding, photoreceptor activity, and transferase activity). Protein sequences were aligned and then used to select sequence-conserved residues and build phylogenetic tree. Three-dimensional structure alignment was also applied to obtain structure-conserved residues. The protein dynamics were analyzed using elastic network model (ENM) and validated by molecular dynamics (MD) simulation. The result showed that the proteins with same function could be grouped by sequence similarity, and proteins in different functional groups displayed statistically significant difference in their vibrational patterns. Interestingly, in all three functional groups, conserved amino acid residues identified by sequence and structure conservation analysis generally have a lower fluctuation than other residues. In addition, the fluctuation of conserved residues in each biological function group was strongly correlated with the corresponding biological function. This research suggested a direct connection in which the protein sequences were related to various functions through structural dynamics. This is a new attempt to delineate functional evolution of proteins using the integrated information of sequence, structure, and dynamics. © 2017 The Protein Society.

Milk protein-gum tragacanth mixed gels: effect of heat-treatment sequence.

Science.gov (United States)

Hatami, Masoud; Nejatian, Mohammad; Mohammadifar, Mohammad Amin; Pourmand, Hanieh

2014-01-30

The aim of this study was to investigate the role of the heat-treatment sequence of biopolymer mixtures as a formulation parameter on the acid-induced gelation of tri-polymeric systems composed of sodium caseinate (Na-caseinate), whey protein concentrate (WPC), and gum tragacanth (GT). This was studied by applying four sequences of heat treatment: (A) co-heating all three biopolymers; (B) heating the milk-protein dispersion and the GT dispersion separately; (C) heating the dispersion containing Na-caseinate and GT together and heating whey protein alone; and (D) co-heating whey protein with GT and heating Na-caseinate alone. According to small-deformation rheological measurements, the strength of the mixed-gel network decreased in the order: C>B>D>A samples. SEM micrographs show that the network of sample C is much more homogenous, coarse and dense than sample A, while the networks of samples B and D are of intermediate density. The heat-treatment sequence of the biopolymer mixtures as a formulation parameter thus offers an opportunity to control the microstructure and rheological properties of mixed gels. Copyright © 2013 Elsevier Ltd. All rights reserved.

Nonlinear Synchronization for Automatic Learning of 3D Pose Variability in Human Motion Sequences

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Mozerov M

2010-01-01

Full Text Available A dense matching algorithm that solves the problem of synchronizing prerecorded human motion sequences, which show different speeds and accelerations, is proposed. The approach is based on minimization of MRF energy and solves the problem by using Dynamic Programming. Additionally, an optimal sequence is automatically selected from the input dataset to be a time-scale pattern for all other sequences. The paper utilizes an action specific model which automatically learns the variability of 3D human postures observed in a set of training sequences. The model is trained using the public CMU motion capture dataset for the walking action, and a mean walking performance is automatically learnt. Additionally, statistics about the observed variability of the postures and motion direction are also computed at each time step. The synchronized motion sequences are used to learn a model of human motion for action recognition and full-body tracking purposes.

Bm86 midgut protein sequence variation in South Texas cattle fever ticks

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Kammlah Diane M

2010-11-01

Full Text Available Abstract Background Cattle fever ticks, Rhipicephalus (Boophilus microplus and R. (B. annulatus, vector bovine and equine babesiosis, and have significantly expanded beyond the permanent quarantine zone established in South Texas. Currently, there are no vaccines approved for use within the United States for controlling these vectors. Vaccines developed in Australia and Cuba based on the midgut antigen Bm86 have variable efficacy against cattle fever ticks. A possible explanation for this variation in vaccine efficacy is amino acid sequence divergence between the recombinant Bm86 vaccine component and native Bm86 expressed in ticks from different geographical regions of the world. Results There was 91.8% amino acid sequence identity in Bm86 among R. microplus and R. annulatus sequenced from South Texas infestations. When South Texas isolates were compared to the Australian Yeerongpilly and Cuban Camcord vaccine strains, there was 89.8% and 90.0% identity, respectively. Most of the sequence divergence was focused in one region of the protein, amino acids 206-298. Hydrophilicity profiles revealed that two short regions of Bm86 (amino acids 206-210 and 560-570 appear to be more hydrophilic in South Texas isolates compared to vaccine strains. Only one amino acid difference was found between South Texas and vaccine strains within two previously described B-cell epitopes. A total of 4 amino acid differences were observed within three peptides previously shown to induce protective immune responses in cattle. Conclusions Sequence differences between South Texas isolates and Yeerongpilly and Camcord strains are spread throughout the entire Bm86 sequence, suggesting that geographic variation does exist. Differences within previously described B-cell epitopes between South Texas isolates and vaccine strains are minimal; however, short regions of hydrophilic amino acids found unique to South Texas isolates suggest that additional unique surface exposed

A scalable double-barcode sequencing platform for characterization of dynamic protein-protein interactions.

Science.gov (United States)

Schlecht, Ulrich; Liu, Zhimin; Blundell, Jamie R; St Onge, Robert P; Levy, Sasha F

2017-05-25

Several large-scale efforts have systematically catalogued protein-protein interactions (PPIs) of a cell in a single environment. However, little is known about how the protein interactome changes across environmental perturbations. Current technologies, which assay one PPI at a time, are too low throughput to make it practical to study protein interactome dynamics. Here, we develop a highly parallel protein-protein interaction sequencing (PPiSeq) platform that uses a novel double barcoding system in conjunction with the dihydrofolate reductase protein-fragment complementation assay in Saccharomyces cerevisiae. PPiSeq detects PPIs at a rate that is on par with current assays and, in contrast with current methods, quantitatively scores PPIs with enough accuracy and sensitivity to detect changes across environments. Both PPI scoring and the bulk of strain construction can be performed with cell pools, making the assay scalable and easily reproduced across environments. PPiSeq is therefore a powerful new tool for large-scale investigations of dynamic PPIs.

OPAL: prediction of MoRF regions in intrinsically disordered protein sequences.

Science.gov (United States)

Sharma, Ronesh; Raicar, Gaurav; Tsunoda, Tatsuhiko; Patil, Ashwini; Sharma, Alok

2018-06-01

Intrinsically disordered proteins lack stable 3-dimensional structure and play a crucial role in performing various biological functions. Key to their biological function are the molecular recognition features (MoRFs) located within long disordered regions. Computationally identifying these MoRFs from disordered protein sequences is a challenging task. In this study, we present a new MoRF predictor, OPAL, to identify MoRFs in disordered protein sequences. OPAL utilizes two independent sources of information computed using different component predictors. The scores are processed and combined using common averaging method. The first score is computed using a component MoRF predictor which utilizes composition and sequence similarity of MoRF and non-MoRF regions to detect MoRFs. The second score is calculated using half-sphere exposure (HSE), solvent accessible surface area (ASA) and backbone angle information of the disordered protein sequence, using information from the amino acid properties of flanks surrounding the MoRFs to distinguish MoRF and non-MoRF residues. OPAL is evaluated using test sets that were previously used to evaluate MoRF predictors, MoRFpred, MoRFchibi and MoRFchibi-web. The results demonstrate that OPAL outperforms all the available MoRF predictors and is the most accurate predictor available for MoRF prediction. It is available at http://www.alok-ai-lab.com/tools/opal/. ashwini@hgc.jp or alok.sharma@griffith.edu.au. Supplementary data are available at Bioinformatics online.

EST-PAC a web package for EST annotation and protein sequence prediction

Directory of Open Access Journals (Sweden)

Strahm Yvan

2006-10-01

Full Text Available Abstract With the decreasing cost of DNA sequencing technology and the vast diversity of biological resources, researchers increasingly face the basic challenge of annotating a larger number of expressed sequences tags (EST from a variety of species. This typically consists of a series of repetitive tasks, which should be automated and easy to use. The results of these annotation tasks need to be stored and organized in a consistent way. All these operations should be self-installing, platform independent, easy to customize and amenable to using distributed bioinformatics resources available on the Internet. In order to address these issues, we present EST-PAC a web oriented multi-platform software package for expressed sequences tag (EST annotation. EST-PAC provides a solution for the administration of EST and protein sequence annotations accessible through a web interface. Three aspects of EST annotation are automated: 1 searching local or remote biological databases for sequence similarities using Blast services, 2 predicting protein coding sequence from EST data and, 3 annotating predicted protein sequences with functional domain predictions. In practice, EST-PAC integrates the BLASTALL suite, EST-Scan2 and HMMER in a relational database system accessible through a simple web interface. EST-PAC also takes advantage of the relational database to allow consistent storage, powerful queries of results and, management of the annotation process. The system allows users to customize annotation strategies and provides an open-source data-management environment for research and education in bioinformatics.

DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier

KAUST Repository

Kulmanov, Maxat

2017-09-27

Motivation A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often only done rigorously for few selected model organisms. Computational function prediction approaches have been suggested to fill this gap. The functions of proteins are classified using the Gene Ontology (GO), which contains over 40 000 classes. Additionally, proteins have multiple functions, making function prediction a large-scale, multi-class, multi-label problem. Results We have developed a novel method to predict protein function from sequence. We use deep learning to learn features from protein sequences as well as a cross-species protein–protein interaction network. Our approach specifically outputs information in the structure of the GO and utilizes the dependencies between GO classes as background information to construct a deep learning model. We evaluate our method using the standards established by the Computational Assessment of Function Annotation (CAFA) and demonstrate a significant improvement over baseline methods such as BLAST, in particular for predicting cellular locations.

Gene identification and protein classification in microbial metagenomic sequence data via incremental clustering

Directory of Open Access Journals (Sweden)

Li Weizhong

2008-04-01

Full Text Available Abstract Background The identification and study of proteins from metagenomic datasets can shed light on the roles and interactions of the source organisms in their communities. However, metagenomic datasets are characterized by the presence of organisms with varying GC composition, codon usage biases etc., and consequently gene identification is challenging. The vast amount of sequence data also requires faster protein family classification tools. Results We present a computational improvement to a sequence clustering approach that we developed previously to identify and classify protein coding genes in large microbial metagenomic datasets. The clustering approach can be used to identify protein coding genes in prokaryotes, viruses, and intron-less eukaryotes. The computational improvement is based on an incremental clustering method that does not require the expensive all-against-all compute that was required by the original approach, while still preserving the remote homology detection capabilities. We present evaluations of the clustering approach in protein-coding gene identification and classification, and also present the results of updating the protein clusters from our previous work with recent genomic and metagenomic sequences. The clustering results are available via CAMERA, (http://camera.calit2.net. Conclusion The clustering paradigm is shown to be a very useful tool in the analysis of microbial metagenomic data. The incremental clustering method is shown to be much faster than the original approach in identifying genes, grouping sequences into existing protein families, and also identifying novel families that have multiple members in a metagenomic dataset. These clusters provide a basis for further studies of protein families.

Identification and verification of hybridoma-derived monoclonal antibody variable region sequences using recombinant DNA technology and mass spectrometry.

Science.gov (United States)

Babrak, Lmar; McGarvey, Jeffery A; Stanker, Larry H; Hnasko, Robert

2017-10-01

Antibody engineering requires the identification of antigen binding domains or variable regions (VR) unique to each antibody. It is the VR that define the unique antigen binding properties and proper sequence identification is essential for functional evaluation and performance of recombinant antibodies (rAb). This determination can be achieved by sequence analysis of immunoglobulin (Ig) transcripts obtained from a monoclonal antibody (MAb) producing hybridoma and subsequent expression of a rAb. However the polyploidy nature of a hybridoma cell often results in the added expression of aberrant immunoglobulin-like transcripts or even production of anomalous antibodies which can confound production of rAb. An incorrect VR sequence will result in a non-functional rAb and de novo assembly of Ig primary structure without a sequence map is challenging. To address these problems, we have developed a methodology which combines: 1) selective PCR amplification of VR from both the heavy and light chain IgG from hybridoma, 2) molecular cloning and DNA sequence analysis and 3) tandem mass spectrometry (MS/MS) on enzyme digests obtained from the purified IgG. Peptide analysis proceeds by evaluating coverage of the predicted primary protein sequence provided by the initial DNA maps for the VR. This methodology serves to both identify and verify the primary structure of the MAb VR for production as rAb. Published by Elsevier Ltd.

Amino acid sequences of ribosomal proteins S11 from Bacillus stearothermophilus and S19 from Halobacterium marismortui. Comparison of the ribosomal protein S11 family.

Science.gov (United States)

Kimura, M; Kimura, J; Hatakeyama, T

1988-11-21

The complete amino acid sequences of ribosomal proteins S11 from the Gram-positive eubacterium Bacillus stearothermophilus and of S19 from the archaebacterium Halobacterium marismortui have been determined. A search for homologous sequences of these proteins revealed that they belong to the ribosomal protein S11 family. Homologous proteins have previously been sequenced from Escherichia coli as well as from chloroplast, yeast and mammalian ribosomes. A pairwise comparison of the amino acid sequences showed that Bacillus protein S11 shares 68% identical residues with S11 from Escherichia coli and a slightly lower homology (52%) with the homologous chloroplast protein. The halophilic protein S19 is more related to the eukaryotic (45-49%) than to the eubacterial counterparts (35%).

Efficient use of unlabeled data for protein sequence classification: a comparative study.

Science.gov (United States)

Kuksa, Pavel; Huang, Pai-Hsi; Pavlovic, Vladimir

2009-04-29

Recent studies in computational primary protein sequence analysis have leveraged the power of unlabeled data. For example, predictive models based on string kernels trained on sequences known to belong to particular folds or superfamilies, the so-called labeled data set, can attain significantly improved accuracy if this data is supplemented with protein sequences that lack any class tags-the unlabeled data. In this study, we present a principled and biologically motivated computational framework that more effectively exploits the unlabeled data by only using the sequence regions that are more likely to be biologically relevant for better prediction accuracy. As overly-represented sequences in large uncurated databases may bias the estimation of computational models that rely on unlabeled data, we also propose a method to remove this bias and improve performance of the resulting classifiers. Combined with state-of-the-art string kernels, our proposed computational framework achieves very accurate semi-supervised protein remote fold and homology detection on three large unlabeled databases. It outperforms current state-of-the-art methods and exhibits significant reduction in running time. The unlabeled sequences used under the semi-supervised setting resemble the unpolished gemstones; when used as-is, they may carry unnecessary features and hence compromise the classification accuracy but once cut and polished, they improve the accuracy of the classifiers considerably.

TRDistiller: a rapid filter for enrichment of sequence datasets with proteins containing tandem repeats.

Science.gov (United States)

Richard, François D; Kajava, Andrey V

2014-06-01

The dramatic growth of sequencing data evokes an urgent need to improve bioinformatics tools for large-scale proteome analysis. Over the last two decades, the foremost efforts of computer scientists were devoted to proteins with aperiodic sequences having globular 3D structures. However, a large portion of proteins contain periodic sequences representing arrays of repeats that are directly adjacent to each other (so called tandem repeats or TRs). These proteins frequently fold into elongated fibrous structures carrying different fundamental functions. Algorithms specific to the analysis of these regions are urgently required since the conventional approaches developed for globular domains have had limited success when applied to the TR regions. The protein TRs are frequently not perfect, containing a number of mutations, and some of them cannot be easily identified. To detect such "hidden" repeats several algorithms have been developed. However, the most sensitive among them are time-consuming and, therefore, inappropriate for large scale proteome analysis. To speed up the TR detection we developed a rapid filter that is based on the comparison of composition and order of short strings in the adjacent sequence motifs. Tests show that our filter discards up to 22.5% of proteins which are known to be without TRs while keeping almost all (99.2%) TR-containing sequences. Thus, we are able to decrease the size of the initial sequence dataset enriching it with TR-containing proteins which allows a faster subsequent TR detection by other methods. The program is available upon request. Copyright © 2014 Elsevier Inc. All rights reserved.

Sifting through genomes with iterative-sequence clustering produces a large, phylogenetically diverse protein-family resource.

Science.gov (United States)

Sharpton, Thomas J; Jospin, Guillaume; Wu, Dongying; Langille, Morgan G I; Pollard, Katherine S; Eisen, Jonathan A

2012-10-13

New computational resources are needed to manage the increasing volume of biological data from genome sequencing projects. One fundamental challenge is the ability to maintain a complete and current catalog of protein diversity. We developed a new approach for the identification of protein families that focuses on the rapid discovery of homologous protein sequences. We implemented fully automated and high-throughput procedures to de novo cluster proteins into families based upon global alignment similarity. Our approach employs an iterative clustering strategy in which homologs of known families are sifted out of the search for new families. The resulting reduction in computational complexity enables us to rapidly identify novel protein families found in new genomes and to perform efficient, automated updates that keep pace with genome sequencing. We refer to protein families identified through this approach as "Sifting Families," or SFams. Our analysis of ~10.5 million protein sequences from 2,928 genomes identified 436,360 SFams, many of which are not represented in other protein family databases. We validated the quality of SFam clustering through statistical as well as network topology-based analyses. We describe the rapid identification of SFams and demonstrate how they can be used to annotate genomes and metagenomes. The SFam database catalogs protein-family quality metrics, multiple sequence alignments, hidden Markov models, and phylogenetic trees. Our source code and database are publicly available and will be subject to frequent updates (http://edhar.genomecenter.ucdavis.edu/sifting_families/).

DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier

KAUST Repository

Kulmanov, Maxat; Khan, Mohammed Asif; Hoehndorf, Robert

2017-01-01

A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often

RTA, a candidate G protein-coupled receptor: Cloning, sequencing, and tissue distribution

International Nuclear Information System (INIS)

Ross, P.C.; Figler, R.A.; Corjay, M.H.; Barber, C.M.; Adam, N.; Harcus, D.R.; Lynch, K.R.

1990-01-01

Genomic and cDNA clones, encoding a protein that is a member of the guanine nucleotide-binding regulatory protein (G protein)-coupled receptor superfamily, were isolated by screening rat genomic and thoracic aorta cDNA libraries with an oligonucleotide encoding a highly conserved region of the M 1 muscarinic acetylcholine receptor. Sequence analyses of these clones showed that they encode a 343-amino acid protein (named RTA). The RTA gene is single copy, as demonstrated by restriction mapping and Southern blotting of genomic clones and rat genomic DNA. RTA RNA sequences are relatively abundant throughout the gut, vas deferens, uterus, and aorta but are only barely detectable (on Northern blots) in liver, kidney, lung, and salivary gland. In the rat brain, RTA sequences are markedly abundant in the cerebellum. TRA is most closely related to the mas oncogene (34% identity), which has been suggested to be a forebrain angiotensin receptor. They conclude that RTA is not an angiotensin receptor; to date, they have been unable to identify its ligand

Sequence-specific capture of protein-DNA complexes for mass spectrometric protein identification.

Directory of Open Access Journals (Sweden)

Cheng-Hsien Wu

Full Text Available The regulation of gene transcription is fundamental to the existence of complex multicellular organisms such as humans. Although it is widely recognized that much of gene regulation is controlled by gene-specific protein-DNA interactions, there presently exists little in the way of tools to identify proteins that interact with the genome at locations of interest. We have developed a novel strategy to address this problem, which we refer to as GENECAPP, for Global ExoNuclease-based Enrichment of Chromatin-Associated Proteins for Proteomics. In this approach, formaldehyde cross-linking is employed to covalently link DNA to its associated proteins; subsequent fragmentation of the DNA, followed by exonuclease digestion, produces a single-stranded region of the DNA that enables sequence-specific hybridization capture of the protein-DNA complex on a solid support. Mass spectrometric (MS analysis of the captured proteins is then used for their identification and/or quantification. We show here the development and optimization of GENECAPP for an in vitro model system, comprised of the murine insulin-like growth factor-binding protein 1 (IGFBP1 promoter region and FoxO1, a member of the forkhead rhabdomyosarcoma (FoxO subfamily of transcription factors, which binds specifically to the IGFBP1 promoter. This novel strategy provides a powerful tool for studies of protein-DNA and protein-protein interactions.

Sorting of a HaloTag protein that has only a signal peptide sequence into exocrine secretory granules without protein aggregation.

Science.gov (United States)

Fujita-Yoshigaki, Junko; Matsuki-Fukushima, Miwako; Yokoyama, Megumi; Katsumata-Kato, Osamu

2013-11-15

The mechanism involved in the sorting and accumulation of secretory cargo proteins, such as amylase, into secretory granules of exocrine cells remains to be solved. To clarify that sorting mechanism, we expressed a reporter protein HaloTag fused with partial sequences of salivary amylase protein in primary cultured parotid acinar cells. We found that a HaloTag protein fused with only the signal peptide sequence (Met(1)-Ala(25)) of amylase, termed SS25H, colocalized well with endogenous amylase, which was confirmed by immunofluorescence microscopy. Percoll-density gradient centrifugation of secretory granule fractions shows that the distributions of amylase and SS25H were similar. These results suggest that SS25H is transported to secretory granules and is not discriminated from endogenous amylase by the machinery that functions to remove proteins other than granule cargo from immature granules. Another reporter protein, DsRed2, that has the same signal peptide sequence also colocalized with amylase, suggesting that the sorting to secretory granules is not dependent on a characteristic of the HaloTag protein. Whereas Blue Native PAGE demonstrates that endogenous amylase forms a high-molecular-weight complex, SS25H does not participate in the complex and does not form self-aggregates. Nevertheless, SS25H was released from cells by the addition of a β-adrenergic agonist, isoproterenol, which also induces amylase secretion. These results indicate that addition of the signal peptide sequence, which is necessary for the translocation in the endoplasmic reticulum, is sufficient for the transportation and storage of cargo proteins in secretory granules of exocrine cells.

The N-terminal sequence of ribosomal protein L10 from the archaebacterium Halobacterium marismortui and its relationship to eubacterial protein L6 and other ribosomal proteins.

Science.gov (United States)

Dijk, J; van den Broek, R; Nasiulas, G; Beck, A; Reinhardt, R; Wittmann-Liebold, B

1987-08-01

The amino-terminal sequence of ribosomal protein L10 from Halobacterium marismortui has been determined up to residue 54, using both a liquid- and a gas-phase sequenator. The two sequences are in good agreement. The protein is clearly homologous to protein HcuL10 from the related strain Halobacterium cutirubrum. Furthermore, a weaker but distinct homology to ribosomal protein L6 from Escherichia coli and Bacillus stearothermophilus can be detected. In addition to 7 identical amino acids in the first 36 residues in all four sequences a number of conservative replacements occurs, of mainly hydrophobic amino acids. In this common region the pattern of conserved amino acids suggests the presence of a beta-alpha fold as it occurs in ribosomal proteins L12 and L30. Furthermore, several potential cases of homology to other ribosomal components of the three ur-kingdoms have been found.

Sequence of a cDNA encoding turtle high mobility group 1 protein.

Science.gov (United States)

Zheng, Jifang; Hu, Bi; Wu, Duansheng

2005-07-01

In order to understand sequence information about turtle HMG1 gene, a cDNA encoding HMG1 protein of the Chinese soft-shell turtle (Pelodiscus sinensis) was amplified by RT-PCR from kidney total RNA, and was cloned, sequenced and analyzed. The results revealed that the open reading frame (ORF) of turtle HMG1 cDNA is 606 bp long. The ORF codifies 202 amino acid residues, from which two DNA-binding domains and one polyacidic region are derived. The DNA-binding domains share higher amino acid identity with homologues sequences of chicken (96.5%) and mammalian (74%) than homologues sequence of rainbow trout (67%). The polyacidic region shows 84.6% amino acid homology with the equivalent region of chicken HMG1 cDNA. Turtle HMG1 protein contains 3 Cys residues located at completely conserved positions. Conservation in sequence and structure suggests that the functions of turtle HMG1 cDNA may be highly conserved during evolution. To our knowledge, this is the first report of HMG1 cDNA sequence in any reptilian.

Sifting through genomes with iterative-sequence clustering produces a large, phylogenetically diverse protein-family resource

Directory of Open Access Journals (Sweden)

Sharpton Thomas J

2012-10-01

Full Text Available Abstract Background New computational resources are needed to manage the increasing volume of biological data from genome sequencing projects. One fundamental challenge is the ability to maintain a complete and current catalog of protein diversity. We developed a new approach for the identification of protein families that focuses on the rapid discovery of homologous protein sequences. Results We implemented fully automated and high-throughput procedures to de novo cluster proteins into families based upon global alignment similarity. Our approach employs an iterative clustering strategy in which homologs of known families are sifted out of the search for new families. The resulting reduction in computational complexity enables us to rapidly identify novel protein families found in new genomes and to perform efficient, automated updates that keep pace with genome sequencing. We refer to protein families identified through this approach as “Sifting Families,” or SFams. Our analysis of ~10.5 million protein sequences from 2,928 genomes identified 436,360 SFams, many of which are not represented in other protein family databases. We validated the quality of SFam clustering through statistical as well as network topology–based analyses. Conclusions We describe the rapid identification of SFams and demonstrate how they can be used to annotate genomes and metagenomes. The SFam database catalogs protein-family quality metrics, multiple sequence alignments, hidden Markov models, and phylogenetic trees. Our source code and database are publicly available and will be subject to frequent updates (http://edhar.genomecenter.ucdavis.edu/sifting_families/.

Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently

Science.gov (United States)

Currin, Andrew; Swainston, Neil; Day, Philip J.

2015-01-01

The amino acid sequence of a protein affects both its structure and its function. Thus, the ability to modify the sequence, and hence the structure and activity, of individual proteins in a systematic way, opens up many opportunities, both scientifically and (as we focus on here) for exploitation in biocatalysis. Modern methods of synthetic biology, whereby increasingly large sequences of DNA can be synthesised de novo, allow an unprecedented ability to engineer proteins with novel functions. However, the number of possible proteins is far too large to test individually, so we need means for navigating the ‘search space’ of possible protein sequences efficiently and reliably in order to find desirable activities and other properties. Enzymologists distinguish binding (K d) and catalytic (k cat) steps. In a similar way, judicious strategies have blended design (for binding, specificity and active site modelling) with the more empirical methods of classical directed evolution (DE) for improving k cat (where natural evolution rarely seeks the highest values), especially with regard to residues distant from the active site and where the functional linkages underpinning enzyme dynamics are both unknown and hard to predict. Epistasis (where the ‘best’ amino acid at one site depends on that or those at others) is a notable feature of directed evolution. The aim of this review is to highlight some of the approaches that are being developed to allow us to use directed evolution to improve enzyme properties, often dramatically. We note that directed evolution differs in a number of ways from natural evolution, including in particular the available mechanisms and the likely selection pressures. Thus, we stress the opportunities afforded by techniques that enable one to map sequence to (structure and) activity in silico, as an effective means of modelling and exploring protein landscapes. Because known landscapes may be assessed and reasoned about as a whole

Avian reovirus L2 genome segment sequences and predicted structure/function of the encoded RNA-dependent RNA polymerase protein

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Xu Wanhong

2008-12-01

Full Text Available Abstract Background The orthoreoviruses are infectious agents that possess a genome comprised of 10 double-stranded RNA segments encased in two concentric protein capsids. Like virtually all RNA viruses, an RNA-dependent RNA polymerase (RdRp enzyme is required for viral propagation. RdRp sequences have been determined for the prototype mammalian orthoreoviruses and for several other closely-related reoviruses, including aquareoviruses, but have not yet been reported for any avian orthoreoviruses. Results We determined the L2 genome segment nucleotide sequences, which encode the RdRp proteins, of two different avian reoviruses, strains ARV138 and ARV176 in order to define conserved and variable regions within reovirus RdRp proteins and to better delineate structure/function of this important enzyme. The ARV138 L2 genome segment was 3829 base pairs long, whereas the ARV176 L2 segment was 3830 nucleotides long. Both segments were predicted to encode λB RdRp proteins 1259 amino acids in length. Alignments of these newly-determined ARV genome segments, and their corresponding proteins, were performed with all currently available homologous mammalian reovirus (MRV and aquareovirus (AqRV genome segment and protein sequences. There was ~55% amino acid identity between ARV λB and MRV λ3 proteins, making the RdRp protein the most highly conserved of currently known orthoreovirus proteins, and there was ~28% identity between ARV λB and homologous MRV and AqRV RdRp proteins. Predictive structure/function mapping of identical and conserved residues within the known MRV λ3 atomic structure indicated most identical amino acids and conservative substitutions were located near and within predicted catalytic domains and lining RdRp channels, whereas non-identical amino acids were generally located on the molecule's surfaces. Conclusion The ARV λB and MRV λ3 proteins showed the highest ARV:MRV identity values (~55% amongst all currently known ARV and MRV

DNA-binding proteins from marine bacteria expand the known sequence diversity of TALE-like repeats.

Science.gov (United States)

de Lange, Orlando; Wolf, Christina; Thiel, Philipp; Krüger, Jens; Kleusch, Christian; Kohlbacher, Oliver; Lahaye, Thomas

2015-11-16

Transcription Activator-Like Effectors (TALEs) of Xanthomonas bacteria are programmable DNA binding proteins with unprecedented target specificity. Comparative studies into TALE repeat structure and function are hindered by the limited sequence variation among TALE repeats. More sequence-diverse TALE-like proteins are known from Ralstonia solanacearum (RipTALs) and Burkholderia rhizoxinica (Bats), but RipTAL and Bat repeats are conserved with those of TALEs around the DNA-binding residue. We study two novel marine-organism TALE-like proteins (MOrTL1 and MOrTL2), the first to date of non-terrestrial origin. We have assessed their DNA-binding properties and modelled repeat structures. We found that repeats from these proteins mediate sequence specific DNA binding conforming to the TALE code, despite low sequence similarity to TALE repeats, and with novel residues around the BSR. However, MOrTL1 repeats show greater sequence discriminating power than MOrTL2 repeats. Sequence alignments show that there are only three residues conserved between repeats of all TALE-like proteins including the two new additions. This conserved motif could prove useful as an identifier for future TALE-likes. Additionally, comparing MOrTL repeats with those of other TALE-likes suggests a common evolutionary origin for the TALEs, RipTALs and Bats. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

CISAPS: Complex Informational Spectrum for the Analysis of Protein Sequences

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Charalambos Chrysostomou

2015-01-01

Full Text Available Complex informational spectrum analysis for protein sequences (CISAPS and its web-based server are developed and presented. As recent studies show, only the use of the absolute spectrum in the analysis of protein sequences using the informational spectrum analysis is proven to be insufficient. Therefore, CISAPS is developed to consider and provide results in three forms including absolute, real, and imaginary spectrum. Biologically related features to the analysis of influenza A subtypes as presented as a case study in this study can also appear individually either in the real or imaginary spectrum. As the results presented, protein classes can present similarities or differences according to the features extracted from CISAPS web server. These associations are probable to be related with the protein feature that the specific amino acid index represents. In addition, various technical issues such as zero-padding and windowing that may affect the analysis are also addressed. CISAPS uses an expanded list of 611 unique amino acid indices where each one represents a different property to perform the analysis. This web-based server enables researchers with little knowledge of signal processing methods to apply and include complex informational spectrum analysis to their work.

Identification of a novel Plasmopara halstedii elicitor protein combining de novo peptide sequencing algorithms and RACE-PCR

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Madlung Johannes

2010-05-01

Full Text Available Abstract Background Often high-quality MS/MS spectra of tryptic peptides do not match to any database entry because of only partially sequenced genomes and therefore, protein identification requires de novo peptide sequencing. To achieve protein identification of the economically important but still unsequenced plant pathogenic oomycete Plasmopara halstedii, we first evaluated the performance of three different de novo peptide sequencing algorithms applied to a protein digests of standard proteins using a quadrupole TOF (QStar Pulsar i. Results The performance order of the algorithms was PEAKS online > PepNovo > CompNovo. In summary, PEAKS online correctly predicted 45% of measured peptides for a protein test data set. All three de novo peptide sequencing algorithms were used to identify MS/MS spectra of tryptic peptides of an unknown 57 kDa protein of P. halstedii. We found ten de novo sequenced peptides that showed homology to a Phytophthora infestans protein, a closely related organism of P. halstedii. Employing a second complementary approach, verification of peptide prediction and protein identification was performed by creation of degenerate primers for RACE-PCR and led to an ORF of 1,589 bp for a hypothetical phosphoenolpyruvate carboxykinase. Conclusions Our study demonstrated that identification of proteins within minute amounts of sample material improved significantly by combining sensitive LC-MS methods with different de novo peptide sequencing algorithms. In addition, this is the first study that verified protein prediction from MS data by also employing a second complementary approach, in which RACE-PCR led to identification of a novel elicitor protein in P. halstedii.

Prediction of flexible/rigid regions from protein sequences using k-spaced amino acid pairs

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Ruan Jishou

2007-04-01

Full Text Available Abstract Background Traditionally, it is believed that the native structure of a protein corresponds to a global minimum of its free energy. However, with the growing number of known tertiary (3D protein structures, researchers have discovered that some proteins can alter their structures in response to a change in their surroundings or with the help of other proteins or ligands. Such structural shifts play a crucial role with respect to the protein function. To this end, we propose a machine learning method for the prediction of the flexible/rigid regions of proteins (referred to as FlexRP; the method is based on a novel sequence representation and feature selection. Knowledge of the flexible/rigid regions may provide insights into the protein folding process and the 3D structure prediction. Results The flexible/rigid regions were defined based on a dataset, which includes protein sequences that have multiple experimental structures, and which was previously used to study the structural conservation of proteins. Sequences drawn from this dataset were represented based on feature sets that were proposed in prior research, such as PSI-BLAST profiles, composition vector and binary sequence encoding, and a newly proposed representation based on frequencies of k-spaced amino acid pairs. These representations were processed by feature selection to reduce the dimensionality. Several machine learning methods for the prediction of flexible/rigid regions and two recently proposed methods for the prediction of conformational changes and unstructured regions were compared with the proposed method. The FlexRP method, which applies Logistic Regression and collocation-based representation with 95 features, obtained 79.5% accuracy. The two runner-up methods, which apply the same sequence representation and Support Vector Machines (SVM and Naïve Bayes classifiers, obtained 79.2% and 78.4% accuracy, respectively. The remaining considered methods are

Rapid detection and purification of sequence specific DNA binding proteins using magnetic separation

Directory of Open Access Journals (Sweden)

TIJANA SAVIC

2006-02-01

Full Text Available In this paper, a method for the rapid identification and purification of sequence specific DNA binding proteins based on magnetic separation is presented. This method was applied to confirm the binding of the human recombinant USF1 protein to its putative binding site (E-box within the human SOX3 protomer. It has been shown that biotinylated DNA attached to streptavidin magnetic particles specifically binds the USF1 protein in the presence of competitor DNA. It has also been demonstrated that the protein could be successfully eluted from the beads, in high yield and with restored DNA binding activity. The advantage of these procedures is that they could be applied for the identification and purification of any high-affinity sequence-specific DNA binding protein with only minor modifications.

Fast computational methods for predicting protein structure from primary amino acid sequence

Science.gov (United States)

Agarwal, Pratul Kumar [Knoxville, TN

2011-07-19

The present invention provides a method utilizing primary amino acid sequence of a protein, energy minimization, molecular dynamics and protein vibrational modes to predict three-dimensional structure of a protein. The present invention also determines possible intermediates in the protein folding pathway. The present invention has important applications to the design of novel drugs as well as protein engineering. The present invention predicts the three-dimensional structure of a protein independent of size of the protein, overcoming a significant limitation in the prior art.

Analysis of correlations between sites in models of protein sequences

International Nuclear Information System (INIS)

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

1998-01-01

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

Sequence walkers: a graphical method to display how binding proteins interact with DNA or RNA sequences | Center for Cancer Research

Science.gov (United States)

A graphical method is presented for displaying how binding proteins and other macromolecules interact with individual bases of nucleotide sequences. Characters representing the sequence are either oriented normally and placed above a line indicating favorable contact, or upside-down and placed below the line indicating unfavorable contact. The positive or negative height of each letter shows the contribution of that base to the average sequence conservation of the binding site, as represented by a sequence logo.

DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier.

Science.gov (United States)

Kulmanov, Maxat; Khan, Mohammed Asif; Hoehndorf, Robert; Wren, Jonathan

2018-02-15

A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often only done rigorously for few selected model organisms. Computational function prediction approaches have been suggested to fill this gap. The functions of proteins are classified using the Gene Ontology (GO), which contains over 40 000 classes. Additionally, proteins have multiple functions, making function prediction a large-scale, multi-class, multi-label problem. We have developed a novel method to predict protein function from sequence. We use deep learning to learn features from protein sequences as well as a cross-species protein-protein interaction network. Our approach specifically outputs information in the structure of the GO and utilizes the dependencies between GO classes as background information to construct a deep learning model. We evaluate our method using the standards established by the Computational Assessment of Function Annotation (CAFA) and demonstrate a significant improvement over baseline methods such as BLAST, in particular for predicting cellular locations. Web server: http://deepgo.bio2vec.net, Source code: https://github.com/bio-ontology-research-group/deepgo. robert.hoehndorf@kaust.edu.sa. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Determining and comparing protein function in Bacterial genome sequences

DEFF Research Database (Denmark)

Vesth, Tammi Camilla

of this class have very little homology to other known genomes making functional annotation based on sequence similarity very difficult. Inspired in part by this analysis, an approach for comparative functional annotation was created based public sequenced genomes, CMGfunc. Functionally related groups......In November 2013, there was around 21.000 different prokaryotic genomes sequenced and publicly available, and the number is growing daily with another 20.000 or more genomes expected to be sequenced and deposited by the end of 2014. An important part of the analysis of this data is the functional...... annotation of genes – the descriptions assigned to genes that describe the likely function of the encoded proteins. This process is limited by several factors, including the definition of a function which can be more or less specific as well as how many genes can actually be assigned a function based...

FASTERp: A Feature Array Search Tool for Estimating Resemblance of Protein Sequences

Energy Technology Data Exchange (ETDEWEB)

Macklin, Derek; Egan, Rob; Wang, Zhong

2014-03-14

Metagenome sequencing efforts have provided a large pool of billions of genes for identifying enzymes with desirable biochemical traits. However, homology search with billions of genes in a rapidly growing database has become increasingly computationally impractical. Here we present our pilot efforts to develop a novel alignment-free algorithm for homology search. Specifically, we represent individual proteins as feature vectors that denote the presence or absence of short kmers in the protein sequence. Similarity between feature vectors is then computed using the Tanimoto score, a distance metric that can be rapidly computed on bit string representations of feature vectors. Preliminary results indicate good correlation with optimal alignment algorithms (Spearman r of 0.87, ~;;1,000,000 proteins from Pfam), as well as with heuristic algorithms such as BLAST (Spearman r of 0.86, ~;;1,000,000 proteins). Furthermore, a prototype of FASTERp implemented in Python runs approximately four times faster than BLAST on a small scale dataset (~;;1000 proteins). We are optimizing and scaling to improve FASTERp to enable rapid homology searches against billion-protein databases, thereby enabling more comprehensive gene annotation efforts.

muBLASTP: database-indexed protein sequence search on multicore CPUs.

Science.gov (United States)

Zhang, Jing; Misra, Sanchit; Wang, Hao; Feng, Wu-Chun

2016-11-04

The Basic Local Alignment Search Tool (BLAST) is a fundamental program in the life sciences that searches databases for sequences that are most similar to a query sequence. Currently, the BLAST algorithm utilizes a query-indexed approach. Although many approaches suggest that sequence search with a database index can achieve much higher throughput (e.g., BLAT, SSAHA, and CAFE), they cannot deliver the same level of sensitivity as the query-indexed BLAST, i.e., NCBI BLAST, or they can only support nucleotide sequence search, e.g., MegaBLAST. Due to different challenges and characteristics between query indexing and database indexing, the existing techniques for query-indexed search cannot be used into database indexed search. muBLASTP, a novel database-indexed BLAST for protein sequence search, delivers identical hits returned to NCBI BLAST. On Intel Haswell multicore CPUs, for a single query, the single-threaded muBLASTP achieves up to a 4.41-fold speedup for alignment stages, and up to a 1.75-fold end-to-end speedup over single-threaded NCBI BLAST. For a batch of queries, the multithreaded muBLASTP achieves up to a 5.7-fold speedups for alignment stages, and up to a 4.56-fold end-to-end speedup over multithreaded NCBI BLAST. With a newly designed index structure for protein database and associated optimizations in BLASTP algorithm, we re-factored BLASTP algorithm for modern multicore processors that achieves much higher throughput with acceptable memory footprint for the database index.

Isolation and N-terminal sequencing of a novel cadmium-binding protein from Boletus edulis

Science.gov (United States)

Collin-Hansen, C.; Andersen, R. A.; Steinnes, E.

2003-05-01

A Cd-binding protein was isolated from the popular edible mushroom Boletus edulis, which is a hyperaccumulator of both Cd and Hg. Wild-growing samples of B. edulis were collected from soils rich in Cd. Cd radiotracer was added to the crude protein preparation obtained from ethanol precipitation of heat-treated cytosol. Proteins were then further separated in two consecutive steps; gel filtration and anion exchange chromatography. In both steps the Cd radiotracer profile showed only one distinct peak, which corresponded well with the profiles of endogenous Cd obtained by atomic absorption spectrophotometry (AAS). Concentrations of the essential elements Cu and Zn were low in the protein fractions high in Cd. N-terminal sequencing performed on the Cd-binding protein fractions revealed a protein with a novel amino acid sequence, which contained aromatic amino acids as well as proline. Both the N-terminal sequencing and spectrofluorimetric analysis with EDTA and ABD-F (4-aminosulfonyl-7-fluoro-2, 1, 3-benzoxadiazole) failed to detect cysteine in the Cd-binding fractions. These findings conclude that the novel protein does not belong to the metallothionein family. The results suggest a role for the protein in Cd transport and storage, and they are of importance in view of toxicology and food chemistry, but also for environmental protection.

Characterization of Campylobacter jejuni applying flaA short variable region sequencing, multilocus sequencing and Fourier transform infrared spectroscopy

DEFF Research Database (Denmark)

Josefsen, Mathilde Hartmann; Bonnichsen, Lise; Larsson, Jonas

flaA short variable region sequencing and phenetic Fourier transform infrared (FTIR) spectroscopy was applied on a collection of 102 Campylobacter jejuni isolated from continuous sampling of organic, free range geese and chickens. FTIR has been shown to serve as a valuable tool in typing...

Sequence charge decoration dictates coil-globule transition in intrinsically disordered proteins

Science.gov (United States)

Firman, Taylor; Ghosh, Kingshuk

2018-03-01

We present an analytical theory to compute conformations of heteropolymers—applicable to describe disordered proteins—as a function of temperature and charge sequence. The theory describes coil-globule transition for a given protein sequence when temperature is varied and has been benchmarked against the all-atom Monte Carlo simulation (using CAMPARI) of intrinsically disordered proteins (IDPs). In addition, the model quantitatively shows how subtle alterations of charge placement in the primary sequence—while maintaining the same charge composition—can lead to significant changes in conformation, even as drastic as a coil (swelled above a purely random coil) to globule (collapsed below a random coil) and vice versa. The theory provides insights on how to control (enhance or suppress) these changes by tuning the temperature (or solution condition) and charge decoration. As an application, we predict the distribution of conformations (at room temperature) of all naturally occurring IDPs in the DisProt database and notice significant size variation even among IDPs with a similar composition of positive and negative charges. Based on this, we provide a new diagram-of-states delineating the sequence-conformation relation for proteins in the DisProt database. Next, we study the effect of post-translational modification, e.g., phosphorylation, on IDP conformations. Modifications as little as two-site phosphorylation can significantly alter the size of an IDP with everything else being constant (temperature, salt concentration, etc.). However, not all possible modification sites have the same effect on protein conformations; there are certain "hot spots" that can cause maximal change in conformation. The location of these "hot spots" in the parent sequence can readily be identified by using a sequence charge decoration metric originally introduced by Sawle and Ghosh. The ability of our model to predict conformations (both expanded and collapsed states) of IDPs at

Exploring Sequence Characteristics Related to High- Level Production of Secreted Proteins in Aspergillus niger

NARCIS (Netherlands)

Van den Berg, B.A.; Reinders, M.J.T.; Hulsman, M.; Wu, L.; Pel, H.J.; Roubos, J.A.; De Ridder, D.

2012-01-01

Protein sequence features are explored in relation to the production of over-expressed extracellular proteins by fungi. Knowledge on features influencing protein production and secretion could be employed to improve enzyme production levels in industrial bioprocesses via protein engineering. A large

Revised Mimivirus major capsid protein sequence reveals intron-containing gene structure and extra domain

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Suzan-Monti Marie

2009-05-01

Full Text Available Abstract Background Acanthamoebae polyphaga Mimivirus (APM is the largest known dsDNA virus. The viral particle has a nearly icosahedral structure with an internal capsid shell surrounded with a dense layer of fibrils. A Capsid protein sequence, D13L, was deduced from the APM L425 coding gene and was shown to be the most abundant protein found within the viral particle. However this protein remained poorly characterised until now. A revised protein sequence deposited in a database suggested an additional N-terminal stretch of 142 amino acids missing from the original deduced sequence. This result led us to investigate the L425 gene structure and the biochemical properties of the complete APM major Capsid protein. Results This study describes the full length 3430 bp Capsid coding gene and characterises the 593 amino acids long corresponding Capsid protein 1. The recombinant full length protein allowed the production of a specific monoclonal antibody able to detect the Capsid protein 1 within the viral particle. This protein appeared to be post-translationnally modified by glycosylation and phosphorylation. We proposed a secondary structure prediction of APM Capsid protein 1 compared to the Capsid protein structure of Paramecium Bursaria Chlorella Virus 1, another member of the Nucleo-Cytoplasmic Large DNA virus family. Conclusion The characterisation of the full length L425 Capsid coding gene of Acanthamoebae polyphaga Mimivirus provides new insights into the structure of the main Capsid protein. The production of a full length recombinant protein will be useful for further structural studies.

Interactions of rat repetitive sequence MspI8 with nuclear matrix proteins during spermatogenesis

International Nuclear Information System (INIS)

Rogolinski, J.; Widlak, P.; Rzeszowska-Wolny, J.

1996-01-01

Using the Southwestern blot analysis we have studied the interactions between rat repetitive sequence MspI8 and the nuclear matrix proteins of rats testis cells. Starting from 2 weeks the young to adult animal showed differences in type of testis nuclear matrix proteins recognizing the MspI8 sequence. The same sets of nuclear matrix proteins were detected in some enriched in spermatocytes and spermatids and obtained after fractionation of cells of adult animal by the velocity sedimentation technique. (author). 21 refs, 5 figs

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.

Mapping a nucleolar targeting sequence of an RNA binding nucleolar protein, Nop25

International Nuclear Information System (INIS)

Fujiwara, Takashi; Suzuki, Shunji; Kanno, Motoko; Sugiyama, Hironobu; Takahashi, Hisaaki; Tanaka, Junya

2006-01-01

Nop25 is a putative RNA binding nucleolar protein associated with rRNA transcription. The present study was undertaken to determine the mechanism of Nop25 localization in the nucleolus. Deletion experiments of Nop25 amino acid sequence showed Nop25 to contain a nuclear targeting sequence in the N-terminal and a nucleolar targeting sequence in the C-terminal. By expressing derivative peptides from the C-terminal as GFP-fusion proteins in the cells, a lysine and arginine residue-enriched peptide (KRKHPRRAQDSTKKPPSATRTSKTQRRRR) allowed a GFP-fusion protein to be transported and fully retained in the nucleolus. When the peptide was fused with cMyc epitope and expressed in the cells, a cMyc epitope was then detected in the nucleolus. Nop25 did not localize in the nucleolus by deletion of the peptide from Nop25. Furthermore, deletion of a subdomain (KRKHPRRAQ) in the peptide or amino acid substitution of lysine and arginine residues in the subdomain resulted in the loss of Nop25 nucleolar localization. These results suggest that the lysine and arginine residue-enriched peptide is the most prominent nucleolar targeting sequence of Nop25 and that the long stretch of basic residues might play an important role in the nucleolar localization of Nop25. Although Nop25 contained putative SUMOylation, phosphorylation and glycosylation sites, the amino acid substitution in these sites had no effect on the nucleolar localization, thus suggesting that these post-translational modifications did not contribute to the localization of Nop25 in the nucleolus. The treatment of the cells, which expressed a GFP-fusion protein with a nucleolar targeting sequence of Nop25, with RNase A resulted in a complete dislocation of the protein from the nucleolus. These data suggested that the nucleolar targeting sequence might therefore play an important role in the binding of Nop25 to RNA molecules and that the RNA binding of Nop25 might be essential for the nucleolar localization of Nop25

Prediction of Carbohydrate-Binding Proteins from Sequences Using Support Vector Machines

Directory of Open Access Journals (Sweden)

Seizi Someya

2010-01-01

Full Text Available Carbohydrate-binding proteins are proteins that can interact with sugar chains but do not modify them. They are involved in many physiological functions, and we have developed a method for predicting them from their amino acid sequences. Our method is based on support vector machines (SVMs. We first clarified the definition of carbohydrate-binding proteins and then constructed positive and negative datasets with which the SVMs were trained. By applying the leave-one-out test to these datasets, our method delivered 0.92 of the area under the receiver operating characteristic (ROC curve. We also examined two amino acid grouping methods that enable effective learning of sequence patterns and evaluated the performance of these methods. When we applied our method in combination with the homology-based prediction method to the annotated human genome database, H-invDB, we found that the true positive rate of prediction was improved.

Formation of a Multiple Protein Complex on the Adenovirus Packaging Sequence by the IVa2 Protein▿

OpenAIRE

Tyler, Ryan E.; Ewing, Sean G.; Imperiale, Michael J.

2007-01-01

During adenovirus virion assembly, the packaging sequence mediates the encapsidation of the viral genome. This sequence is composed of seven functional units, termed A repeats. Recent evidence suggests that the adenovirus IVa2 protein binds the packaging sequence and is involved in packaging of the genome. Study of the IVa2-packaging sequence interaction has been hindered by difficulty in purifying the protein produced in virus-infected cells or by recombinant techniques. We report the first ...

Multi-region and single-cell sequencing reveal variable genomic heterogeneity in rectal cancer.

Science.gov (United States)

Liu, Mingshan; Liu, Yang; Di, Jiabo; Su, Zhe; Yang, Hong; Jiang, Beihai; Wang, Zaozao; Zhuang, Meng; Bai, Fan; Su, Xiangqian

2017-11-23

Colorectal cancer is a heterogeneous group of malignancies with complex molecular subtypes. While colon cancer has been widely investigated, studies on rectal cancer are very limited. Here, we performed multi-region whole-exome sequencing and single-cell whole-genome sequencing to examine the genomic intratumor heterogeneity (ITH) of rectal tumors. We sequenced nine tumor regions and 88 single cells from two rectal cancer patients with tumors of the same molecular classification and characterized their mutation profiles and somatic copy number alterations (SCNAs) at the multi-region and the single-cell levels. A variable extent of genomic heterogeneity was observed between the two patients, and the degree of ITH increased when analyzed on the single-cell level. We found that major SCNAs were early events in cancer development and inherited steadily. Single-cell sequencing revealed mutations and SCNAs which were hidden in bulk sequencing. In summary, we studied the ITH of rectal cancer at regional and single-cell resolution and demonstrated that variable heterogeneity existed in two patients. The mutational scenarios and SCNA profiles of two patients with treatment naïve from the same molecular subtype are quite different. Our results suggest each tumor possesses its own architecture, which may result in different diagnosis, prognosis, and drug responses. Remarkable ITH exists in the two patients we have studied, providing a preliminary impression of ITH in rectal cancer.

Discovering approximate-associated sequence patterns for protein-DNA interactions

KAUST Repository

Chan, Tak Ming

2010-12-30

Motivation: The bindings between transcription factors (TFs) and transcription factor binding sites (TFBSs) are fundamental protein-DNA interactions in transcriptional regulation. Extensive efforts have been made to better understand the protein-DNA interactions. Recent mining on exact TF-TFBS-associated sequence patterns (rules) has shown great potentials and achieved very promising results. However, exact rules cannot handle variations in real data, resulting in limited informative rules. In this article, we generalize the exact rules to approximate ones for both TFs and TFBSs, which are essential for biological variations. Results: A progressive approach is proposed to address the approximation to alleviate the computational requirements. Firstly, similar TFBSs are grouped from the available TF-TFBS data (TRANSFAC database). Secondly, approximate and highly conserved binding cores are discovered from TF sequences corresponding to each TFBS group. A customized algorithm is developed for the specific objective. We discover the approximate TF-TFBS rules by associating the grouped TFBS consensuses and TF cores. The rules discovered are evaluated by matching (verifying with) the actual protein-DNA binding pairs from Protein Data Bank (PDB) 3D structures. The approximate results exhibit many more verified rules and up to 300% better verification ratios than the exact ones. The customized algorithm achieves over 73% better verification ratios than traditional methods. Approximate rules (64-79%) are shown statistically significant. Detailed variation analysis and conservation verification on NCBI records demonstrate that the approximate rules reveal both the flexible and specific protein-DNA interactions accurately. The approximate TF-TFBS rules discovered show great generalized capability of exploring more informative binding rules. © The Author 2010. Published by Oxford University Press. All rights reserved.

Large-scale analysis of intrinsic disorder flavors and associated functions in the protein sequence universe.

Science.gov (United States)

Necci, Marco; Piovesan, Damiano; Tosatto, Silvio C E

2016-12-01

Intrinsic disorder (ID) in proteins has been extensively described for the last decade; a large-scale classification of ID in proteins is mostly missing. Here, we provide an extensive analysis of ID in the protein universe on the UniProt database derived from sequence-based predictions in MobiDB. Almost half the sequences contain an ID region of at least five residues. About 9% of proteins have a long ID region of over 20 residues which are more abundant in Eukaryotic organisms and most frequently cover less than 20% of the sequence. A small subset of about 67,000 (out of over 80 million) proteins is fully disordered and mostly found in Viruses. Most proteins have only one ID, with short ID evenly distributed along the sequence and long ID overrepresented in the center. The charged residue composition of Das and Pappu was used to classify ID proteins by structural propensities and corresponding functional enrichment. Swollen Coils seem to be used mainly as structural components and in biosynthesis in both Prokaryotes and Eukaryotes. In Bacteria, they are confined in the nucleoid and in Viruses provide DNA binding function. Coils & Hairpins seem to be specialized in ribosome binding and methylation activities. Globules & Tadpoles bind antigens in Eukaryotes but are involved in killing other organisms and cytolysis in Bacteria. The Undefined class is used by Bacteria to bind toxic substances and mediate transport and movement between and within organisms in Viruses. Fully disordered proteins behave similarly, but are enriched for glycine residues and extracellular structures. © 2016 The Protein Society.

Representation of protein-sequence information by amino acid subalphabets

DEFF Research Database (Denmark)

Andersen, C.A.F.; Brunak, Søren

2004-01-01

-sequence information, using machine learning strategies, where the primary goal is the discovery of novel powerful representations for use in AI techniques. In the case of proteins and the 20 different amino acids they typically contain, it is also a secondary goal to discover how the current selection of amino acids...

RStrucFam: a web server to associate structure and cognate RNA for RNA-binding proteins from sequence information.

Science.gov (United States)

Ghosh, Pritha; Mathew, Oommen K; Sowdhamini, Ramanathan

2016-10-07

RNA-binding proteins (RBPs) interact with their cognate RNA(s) to form large biomolecular assemblies. They are versatile in their functionality and are involved in a myriad of processes inside the cell. RBPs with similar structural features and common biological functions are grouped together into families and superfamilies. It will be useful to obtain an early understanding and association of RNA-binding property of sequences of gene products. Here, we report a web server, RStrucFam, to predict the structure, type of cognate RNA(s) and function(s) of proteins, where possible, from mere sequence information. The web server employs Hidden Markov Model scan (hmmscan) to enable association to a back-end database of structural and sequence families. The database (HMMRBP) comprises of 437 HMMs of RBP families of known structure that have been generated using structure-based sequence alignments and 746 sequence-centric RBP family HMMs. The input protein sequence is associated with structural or sequence domain families, if structure or sequence signatures exist. In case of association of the protein with a family of known structures, output features like, multiple structure-based sequence alignment (MSSA) of the query with all others members of that family is provided. Further, cognate RNA partner(s) for that protein, Gene Ontology (GO) annotations, if any and a homology model of the protein can be obtained. The users can also browse through the database for details pertaining to each family, protein or RNA and their related information based on keyword search or RNA motif search. RStrucFam is a web server that exploits structurally conserved features of RBPs, derived from known family members and imprinted in mathematical profiles, to predict putative RBPs from sequence information. Proteins that fail to associate with such structure-centric families are further queried against the sequence-centric RBP family HMMs in the HMMRBP database. Further, all other essential

Domain fusion analysis by applying relational algebra to protein sequence and domain databases.

Science.gov (United States)

Truong, Kevin; Ikura, Mitsuhiko

2003-05-06

Domain fusion analysis is a useful method to predict functionally linked proteins that may be involved in direct protein-protein interactions or in the same metabolic or signaling pathway. As separate domain databases like BLOCKS, PROSITE, Pfam, SMART, PRINTS-S, ProDom, TIGRFAMs, and amalgamated domain databases like InterPro continue to grow in size and quality, a computational method to perform domain fusion analysis that leverages on these efforts will become increasingly powerful. This paper proposes a computational method employing relational algebra to find domain fusions in protein sequence databases. The feasibility of this method was illustrated on the SWISS-PROT+TrEMBL sequence database using domain predictions from the Pfam HMM (hidden Markov model) database. We identified 235 and 189 putative functionally linked protein partners in H. sapiens and S. cerevisiae, respectively. From scientific literature, we were able to confirm many of these functional linkages, while the remainder offer testable experimental hypothesis. Results can be viewed at http://calcium.uhnres.utoronto.ca/pi. As the analysis can be computed quickly on any relational database that supports standard SQL (structured query language), it can be dynamically updated along with the sequence and domain databases, thereby improving the quality of predictions over time.

Adaptive GDDA-BLAST: fast and efficient algorithm for protein sequence embedding.

Directory of Open Access Journals (Sweden)

Yoojin Hong

2010-10-01

Full Text Available A major computational challenge in the genomic era is annotating structure/function to the vast quantities of sequence information that is now available. This problem is illustrated by the fact that most proteins lack comprehensive annotations, even when experimental evidence exists. We previously theorized that embedded-alignment profiles (simply "alignment profiles" hereafter provide a quantitative method that is capable of relating the structural and functional properties of proteins, as well as their evolutionary relationships. A key feature of alignment profiles lies in the interoperability of data format (e.g., alignment information, physio-chemical information, genomic information, etc.. Indeed, we have demonstrated that the Position Specific Scoring Matrices (PSSMs are an informative M-dimension that is scored by quantitatively measuring the embedded or unmodified sequence alignments. Moreover, the information obtained from these alignments is informative, and remains so even in the "twilight zone" of sequence similarity (<25% identity. Although our previous embedding strategy was powerful, it suffered from contaminating alignments (embedded AND unmodified and high computational costs. Herein, we describe the logic and algorithmic process for a heuristic embedding strategy named "Adaptive GDDA-BLAST." Adaptive GDDA-BLAST is, on average, up to 19 times faster than, but has similar sensitivity to our previous method. Further, data are provided to demonstrate the benefits of embedded-alignment measurements in terms of detecting structural homology in highly divergent protein sequences and isolating secondary structural elements of transmembrane and ankyrin-repeat domains. Together, these advances allow further exploration of the embedded alignment data space within sufficiently large data sets to eventually induce relevant statistical inferences. We show that sequence embedding could serve as one of the vehicles for measurement of low

Generalizing and learning protein-DNA binding sequence representations by an evolutionary algorithm

KAUST Repository

Wong, Ka Chun

2011-02-05

Protein-DNA bindings are essential activities. Understanding them forms the basis for further deciphering of biological and genetic systems. In particular, the protein-DNA bindings between transcription factors (TFs) and transcription factor binding sites (TFBSs) play a central role in gene transcription. Comprehensive TF-TFBS binding sequence pairs have been found in a recent study. However, they are in one-to-one mappings which cannot fully reflect the many-to-many mappings within the bindings. An evolutionary algorithm is proposed to learn generalized representations (many-to-many mappings) from the TF-TFBS binding sequence pairs (one-to-one mappings). The generalized pairs are shown to be more meaningful than the original TF-TFBS binding sequence pairs. Some representative examples have been analyzed in this study. In particular, it shows that the TF-TFBS binding sequence pairs are not presumably in one-to-one mappings. They can also exhibit many-to-many mappings. The proposed method can help us extract such many-to-many information from the one-to-one TF-TFBS binding sequence pairs found in the previous study, providing further knowledge in understanding the bindings between TFs and TFBSs. © 2011 Springer-Verlag.

Generalizing and learning protein-DNA binding sequence representations by an evolutionary algorithm

KAUST Repository

Wong, Ka Chun; Peng, Chengbin; Wong, Manhon; Leung, Kwongsak

2011-01-01

Protein-DNA bindings are essential activities. Understanding them forms the basis for further deciphering of biological and genetic systems. In particular, the protein-DNA bindings between transcription factors (TFs) and transcription factor binding sites (TFBSs) play a central role in gene transcription. Comprehensive TF-TFBS binding sequence pairs have been found in a recent study. However, they are in one-to-one mappings which cannot fully reflect the many-to-many mappings within the bindings. An evolutionary algorithm is proposed to learn generalized representations (many-to-many mappings) from the TF-TFBS binding sequence pairs (one-to-one mappings). The generalized pairs are shown to be more meaningful than the original TF-TFBS binding sequence pairs. Some representative examples have been analyzed in this study. In particular, it shows that the TF-TFBS binding sequence pairs are not presumably in one-to-one mappings. They can also exhibit many-to-many mappings. The proposed method can help us extract such many-to-many information from the one-to-one TF-TFBS binding sequence pairs found in the previous study, providing further knowledge in understanding the bindings between TFs and TFBSs. © 2011 Springer-Verlag.

SPiCE : A web-based tool for sequence-based protein classification and exploration

NARCIS (Netherlands)

Van den Berg, B.A.; Reinders, M.J.; Roubos, J.A.; De Ridder, D.

2014-01-01

Background Amino acid sequences and features extracted from such sequences have been used to predict many protein properties, such as subcellular localization or solubility, using classifier algorithms. Although software tools are available for both feature extraction and classifier construction,

Rapid detection, classification and accurate alignment of up to a million or more related protein sequences.

Science.gov (United States)

Neuwald, Andrew F

2009-08-01

The patterns of sequence similarity and divergence present within functionally diverse, evolutionarily related proteins contain implicit information about corresponding biochemical similarities and differences. A first step toward accessing such information is to statistically analyze these patterns, which, in turn, requires that one first identify and accurately align a very large set of protein sequences. Ideally, the set should include many distantly related, functionally divergent subgroups. Because it is extremely difficult, if not impossible for fully automated methods to align such sequences correctly, researchers often resort to manual curation based on detailed structural and biochemical information. However, multiply-aligning vast numbers of sequences in this way is clearly impractical. This problem is addressed using Multiply-Aligned Profiles for Global Alignment of Protein Sequences (MAPGAPS). The MAPGAPS program uses a set of multiply-aligned profiles both as a query to detect and classify related sequences and as a template to multiply-align the sequences. It relies on Karlin-Altschul statistics for sensitivity and on PSI-BLAST (and other) heuristics for speed. Using as input a carefully curated multiple-profile alignment for P-loop GTPases, MAPGAPS correctly aligned weakly conserved sequence motifs within 33 distantly related GTPases of known structure. By comparison, the sequence- and structurally based alignment methods hmmalign and PROMALS3D misaligned at least 11 and 23 of these regions, respectively. When applied to a dataset of 65 million protein sequences, MAPGAPS identified, classified and aligned (with comparable accuracy) nearly half a million putative P-loop GTPase sequences. A C++ implementation of MAPGAPS is available at http://mapgaps.igs.umaryland.edu. Supplementary data are available at Bioinformatics online.

The YPLGVG sequence of the Nipah virus matrix protein is required for budding

Directory of Open Access Journals (Sweden)

Yan Lianying

2008-11-01

Full Text Available Abstract Background Nipah virus (NiV is a recently emerged paramyxovirus capable of causing fatal disease in a broad range of mammalian hosts, including humans. Together with Hendra virus (HeV, they comprise the genus Henipavirus in the family Paramyxoviridae. Recombinant expression systems have played a crucial role in studying the cell biology of these Biosafety Level-4 restricted viruses. Henipavirus assembly and budding occurs at the plasma membrane, although the details of this process remain poorly understood. Multivesicular body (MVB proteins have been found to play a role in the budding of several enveloped viruses, including some paramyxoviruses, and the recruitment of MVB proteins by viral proteins possessing late budding domains (L-domains has become an important concept in the viral budding process. Previously we developed a system for producing NiV virus-like particles (VLPs and demonstrated that the matrix (M protein possessed an intrinsic budding ability and played a major role in assembly. Here, we have used this system to further explore the budding process by analyzing elements within the M protein that are critical for particle release. Results Using rationally targeted site-directed mutagenesis we show that a NiV M sequence YPLGVG is required for M budding and that mutation or deletion of the sequence abrogates budding ability. Replacement of the native and overlapping Ebola VP40 L-domains with the NiV sequence failed to rescue VP40 budding; however, it did induce the cellular morphology of extensive filamentous projection consistent with wild-type VP40-expressing cells. Cells expressing wild-type NiV M also displayed this morphology, which was dependent on the YPLGVG sequence, and deletion of the sequence also resulted in nuclear localization of M. Dominant-negative VPS4 proteins had no effect on NiV M budding, suggesting that unlike other viruses such as Ebola, NiV M accomplishes budding independent of MVB cellular proteins

StralSV: assessment of sequence variability within similar 3D structures and application to polio RNA-dependent RNA polymerase

Energy Technology Data Exchange (ETDEWEB)

Zemla, A; Lang, D; Kostova, T; Andino, R; Zhou, C

2010-11-29

Most of the currently used methods for protein function prediction rely on sequence-based comparisons between a query protein and those for which a functional annotation is provided. A serious limitation of sequence similarity-based approaches for identifying residue conservation among proteins is the low confidence in assigning residue-residue correspondences among proteins when the level of sequence identity between the compared proteins is poor. Multiple sequence alignment methods are more satisfactory - still, they cannot provide reliable results at low levels of sequence identity. Our goal in the current work was to develop an algorithm that could overcome these difficulties and facilitate the identification of structurally (and possibly functionally) relevant residue-residue correspondences between compared protein structures. Here we present StralSV, a new algorithm for detecting closely related structure fragments and quantifying residue frequency from tight local structure alignments. We apply StralSV in a study of the RNA-dependent RNA polymerase of poliovirus and demonstrate that the algorithm can be used to determine regions of the protein that are relatively unique or that shared structural similarity with structures that are distantly related. By quantifying residue frequencies among many residue-residue pairs extracted from local alignments, one can infer potential structural or functional importance of specific residues that are determined to be highly conserved or that deviate from a consensus. We further demonstrate that considerable detailed structural and phylogenetic information can be derived from StralSV analyses. StralSV is a new structure-based algorithm for identifying and aligning structure fragments that have similarity to a reference protein. StralSV analysis can be used to quantify residue-residue correspondences and identify residues that may be of particular structural or functional importance, as well as unusual or unexpected

Unified Deep Learning Architecture for Modeling Biology Sequence.

Science.gov (United States)

Wu, Hongjie; Cao, Chengyuan; Xia, Xiaoyan; Lu, Qiang

2017-10-09

Prediction of the spatial structure or function of biological macromolecules based on their sequence remains an important challenge in bioinformatics. When modeling biological sequences using traditional sequencing models, characteristics, such as long-range interactions between basic units, the complicated and variable output of labeled structures, and the variable length of biological sequences, usually lead to different solutions on a case-by-case basis. This study proposed the use of bidirectional recurrent neural networks based on long short-term memory or a gated recurrent unit to capture long-range interactions by designing the optional reshape operator to adapt to the diversity of the output labels and implementing a training algorithm to support the training of sequence models capable of processing variable-length sequences. Additionally, the merge and pooling operators enhanced the ability to capture short-range interactions between basic units of biological sequences. The proposed deep-learning model and its training algorithm might be capable of solving currently known biological sequence-modeling problems through the use of a unified framework. We validated our model on one of the most difficult biological sequence-modeling problems currently known, with our results indicating the ability of the model to obtain predictions of protein residue interactions that exceeded the accuracy of current popular approaches by 10% based on multiple benchmarks.

ORFer--retrieval of protein sequences and open reading frames from GenBank and storage into relational databases or text files.

Science.gov (United States)

Büssow, Konrad; Hoffmann, Steve; Sievert, Volker

2002-12-19

Functional genomics involves the parallel experimentation with large sets of proteins. This requires management of large sets of open reading frames as a prerequisite of the cloning and recombinant expression of these proteins. A Java program was developed for retrieval of protein and nucleic acid sequences and annotations from NCBI GenBank, using the XML sequence format. Annotations retrieved by ORFer include sequence name, organism and also the completeness of the sequence. The program has a graphical user interface, although it can be used in a non-interactive mode. For protein sequences, the program also extracts the open reading frame sequence, if available, and checks its correct translation. ORFer accepts user input in the form of single or lists of GenBank GI identifiers or accession numbers. It can be used to extract complete sets of open reading frames and protein sequences from any kind of GenBank sequence entry, including complete genomes or chromosomes. Sequences are either stored with their features in a relational database or can be exported as text files in Fasta or tabulator delimited format. The ORFer program is freely available at http://www.proteinstrukturfabrik.de/orfer. The ORFer program allows for fast retrieval of DNA sequences, protein sequences and their open reading frames and sequence annotations from GenBank. Furthermore, storage of sequences and features in a relational database is supported. Such a database can supplement a laboratory information system (LIMS) with appropriate sequence information.

Identification of human microRNA-like sequences embedded within the protein-encoding genes of the human immunodeficiency virus.

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Bryan Holland

Full Text Available BACKGROUND: MicroRNAs (miRNAs are highly conserved, short (18-22 nts, non-coding RNA molecules that regulate gene expression by binding to the 3' untranslated regions (3'UTRs of mRNAs. While numerous cellular microRNAs have been associated with the progression of various diseases including cancer, miRNAs associated with retroviruses have not been well characterized. Herein we report identification of microRNA-like sequences in coding regions of several HIV-1 genomes. RESULTS: Based on our earlier proteomics and bioinformatics studies, we have identified 8 cellular miRNAs that are predicted to bind to the mRNAs of multiple proteins that are dysregulated during HIV-infection of CD4+ T-cells in vitro. In silico analysis of the full length and mature sequences of these 8 miRNAs and comparisons with all the genomic and subgenomic sequences of HIV-1 strains in global databases revealed that the first 18/18 sequences of the mature hsa-miR-195 sequence (including the short seed sequence, matched perfectly (100%, or with one nucleotide mismatch, within the envelope (env genes of five HIV-1 genomes from Africa. In addition, we have identified 4 other miRNA-like sequences (hsa-miR-30d, hsa-miR-30e, hsa-miR-374a and hsa-miR-424 within the env and the gag-pol encoding regions of several HIV-1 strains, albeit with reduced homology. Mapping of the miRNA-homologues of env within HIV-1 genomes localized these sequence to the functionally significant variable regions of the env glycoprotein gp120 designated V1, V2, V4 and V5. CONCLUSIONS: We conclude that microRNA-like sequences are embedded within the protein-encoding regions of several HIV-1 genomes. Given that the V1 to V5 regions of HIV-1 envelopes contain specific, well-characterized domains that are critical for immune responses, virus neutralization and disease progression, we propose that the newly discovered miRNA-like sequences within the HIV-1 genomes may have evolved to self-regulate survival of the

Neural network and SVM classifiers accurately predict lipid binding proteins, irrespective of sequence homology.

Science.gov (United States)

Bakhtiarizadeh, Mohammad Reza; Moradi-Shahrbabak, Mohammad; Ebrahimi, Mansour; Ebrahimie, Esmaeil

2014-09-07

Due to the central roles of lipid binding proteins (LBPs) in many biological processes, sequence based identification of LBPs is of great interest. The major challenge is that LBPs are diverse in sequence, structure, and function which results in low accuracy of sequence homology based methods. Therefore, there is a need for developing alternative functional prediction methods irrespective of sequence similarity. To identify LBPs from non-LBPs, the performances of support vector machine (SVM) and neural network were compared in this study. Comprehensive protein features and various techniques were employed to create datasets. Five-fold cross-validation (CV) and independent evaluation (IE) tests were used to assess the validity of the two methods. The results indicated that SVM outperforms neural network. SVM achieved 89.28% (CV) and 89.55% (IE) overall accuracy in identification of LBPs from non-LBPs and 92.06% (CV) and 92.90% (IE) (in average) for classification of different LBPs classes. Increasing the number and the range of extracted protein features as well as optimization of the SVM parameters significantly increased the efficiency of LBPs class prediction in comparison to the only previous report in this field. Altogether, the results showed that the SVM algorithm can be run on broad, computationally calculated protein features and offers a promising tool in detection of LBPs classes. The proposed approach has the potential to integrate and improve the common sequence alignment based methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

An improved classification of G-protein-coupled receptors using sequence-derived features

Directory of Open Access Journals (Sweden)

Peng Zhen-Ling

2010-08-01

Full Text Available Abstract Background G-protein-coupled receptors (GPCRs play a key role in diverse physiological processes and are the targets of almost two-thirds of the marketed drugs. The 3 D structures of GPCRs are largely unavailable; however, a large number of GPCR primary sequences are known. To facilitate the identification and characterization of novel receptors, it is therefore very valuable to develop a computational method to accurately predict GPCRs from the protein primary sequences. Results We propose a new method called PCA-GPCR, to predict GPCRs using a comprehensive set of 1497 sequence-derived features. The principal component analysis is first employed to reduce the dimension of the feature space to 32. Then, the resulting 32-dimensional feature vectors are fed into a simple yet powerful classification algorithm, called intimate sorting, to predict GPCRs at five levels. The prediction at the first level determines whether a protein is a GPCR or a non-GPCR. If it is predicted to be a GPCR, then it will be further predicted into certain family, subfamily, sub-subfamily and subtype by the classifiers at the second, third, fourth, and fifth levels, respectively. To train the classifiers applied at five levels, a non-redundant dataset is carefully constructed, which contains 3178, 1589, 4772, 4924, and 2741 protein sequences at the respective levels. Jackknife tests on this training dataset show that the overall accuracies of PCA-GPCR at five levels (from the first to the fifth can achieve up to 99.5%, 88.8%, 80.47%, 80.3%, and 92.34%, respectively. We further perform predictions on a dataset of 1238 GPCRs at the second level, and on another two datasets of 167 and 566 GPCRs respectively at the fourth level. The overall prediction accuracies of our method are consistently higher than those of the existing methods to be compared. Conclusions The comprehensive set of 1497 features is believed to be capable of capturing information about amino acid

Determinants of cell-to-cell variability in protein kinase signaling.

Science.gov (United States)

Jeschke, Matthias; Baumgärtner, Stephan; Legewie, Stefan

2013-01-01

Cells reliably sense environmental changes despite internal and external fluctuations, but the mechanisms underlying robustness remain unclear. We analyzed how fluctuations in signaling protein concentrations give rise to cell-to-cell variability in protein kinase signaling using analytical theory and numerical simulations. We characterized the dose-response behavior of signaling cascades by calculating the stimulus level at which a pathway responds ('pathway sensitivity') and the maximal activation level upon strong stimulation. Minimal kinase cascades with gradual dose-response behavior show strong variability, because the pathway sensitivity and the maximal activation level cannot be simultaneously invariant. Negative feedback regulation resolves this trade-off and coordinately reduces fluctuations in the pathway sensitivity and maximal activation. Feedbacks acting at different levels in the cascade control different aspects of the dose-response curve, thereby synergistically reducing the variability. We also investigated more complex, ultrasensitive signaling cascades capable of switch-like decision making, and found that these can be inherently robust to protein concentration fluctuations. We describe how the cell-to-cell variability of ultrasensitive signaling systems can be actively regulated, e.g., by altering the expression of phosphatase(s) or by feedback/feedforward loops. Our calculations reveal that slow transcriptional negative feedback loops allow for variability suppression while maintaining switch-like decision making. Taken together, we describe design principles of signaling cascades that promote robustness. Our results may explain why certain signaling cascades like the yeast pheromone pathway show switch-like decision making with little cell-to-cell variability.

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.

Protein construct storage: Bayesian variable selection and prediction with mixtures.

Science.gov (United States)

Clyde, M A; Parmigiani, G

1998-07-01

Determining optimal conditions for protein storage while maintaining a high level of protein activity is an important question in pharmaceutical research. A designed experiment based on a space-filling design was conducted to understand the effects of factors affecting protein storage and to establish optimal storage conditions. Different model-selection strategies to identify important factors may lead to very different answers about optimal conditions. Uncertainty about which factors are important, or model uncertainty, can be a critical issue in decision-making. We use Bayesian variable selection methods for linear models to identify important variables in the protein storage data, while accounting for model uncertainty. We also use the Bayesian framework to build predictions based on a large family of models, rather than an individual model, and to evaluate the probability that certain candidate storage conditions are optimal.

Epitope Sequences in Dengue Virus NS1 Protein Identified by Monoclonal Antibodies

Directory of Open Access Journals (Sweden)

Leticia Barboza Rocha

2017-10-01

Full Text Available Dengue nonstructural protein 1 (NS1 is a multi-functional glycoprotein with essential functions both in viral replication and modulation of host innate immune responses. NS1 has been established as a good surrogate marker for infection. In the present study, we generated four anti-NS1 monoclonal antibodies against recombinant NS1 protein from dengue virus serotype 2 (DENV2, which were used to map three NS1 epitopes. The sequence 193AVHADMGYWIESALNDT209 was recognized by monoclonal antibodies 2H5 and 4H1BC, which also cross-reacted with Zika virus (ZIKV protein. On the other hand, the sequence 25VHTWTEQYKFQPES38 was recognized by mAb 4F6 that did not cross react with ZIKV. Lastly, a previously unidentified DENV2 NS1-specific epitope, represented by the sequence 127ELHNQTFLIDGPETAEC143, is described in the present study after reaction with mAb 4H2, which also did not cross react with ZIKV. The selection and characterization of the epitope, specificity of anti-NS1 mAbs, may contribute to the development of diagnostic tools able to differentiate DENV and ZIKV infections.

Cloning, sequencing and variability analysis of the gap gene from Mycoplasma hominis

DEFF Research Database (Denmark)

Mygind, Tina; Jacobsen, Iben Søgaard; Melkova, Renata

2000-01-01

The gap gene encodes the glycolytic enzyme glyceraldehyde 3-phosphate dehydrogenase (GAPDH). The gene was cloned and sequenced from the Mycoplasma hominis type strain PG21(T). The intraspecies variability was investigated by inspection of restriction fragment length polymorphism (RFLP) patterns...... after polymerase chain reaction (PCR) amplification of the gap gene from 15 strains and furthermore by sequencing of part of the gene in eight strains. The M. hominis gap gene was found to vary more than the Escherichia coli counterpart, but the variation at nucleotide level gave rise to only a few...

A TALE-inspired computational screen for proteins that contain approximate tandem repeats.

Science.gov (United States)

Perycz, Malgorzata; Krwawicz, Joanna; Bochtler, Matthias

2017-01-01

TAL (transcription activator-like) effectors (TALEs) are bacterial proteins that are secreted from bacteria to plant cells to act as transcriptional activators. TALEs and related proteins (RipTALs, BurrH, MOrTL1 and MOrTL2) contain approximate tandem repeats that differ in conserved positions that define specificity. Using PERL, we screened ~47 million protein sequences for TALE-like architecture characterized by approximate tandem repeats (between 30 and 43 amino acids in length) and sequence variability in conserved positions, without requiring sequence similarity to TALEs. Candidate proteins were scored according to their propensity for nuclear localization, secondary structure, repeat sequence complexity, as well as covariation and predicted structural proximity of variable residues. Biological context was tentatively inferred from co-occurrence of other domains and interactome predictions. Approximate repeats with TALE-like features that merit experimental characterization were found in a protein of chestnut blight fungus, a eukaryotic plant pathogen.

A sequence-based dynamic ensemble learning system for protein ligand-binding site prediction

KAUST Repository

Chen, Peng

2015-12-03

Background: Proteins have the fundamental ability to selectively bind to other molecules and perform specific functions through such interactions, such as protein-ligand binding. Accurate prediction of protein residues that physically bind to ligands is important for drug design and protein docking studies. Most of the successful protein-ligand binding predictions were based on known structures. However, structural information is not largely available in practice due to the huge gap between the number of known protein sequences and that of experimentally solved structures

A sequence-based dynamic ensemble learning system for protein ligand-binding site prediction

KAUST Repository

Chen, Peng; Hu, ShanShan; Zhang, Jun; Gao, Xin; Li, Jinyan; Xia, Junfeng; Wang, Bing

2015-01-01

Background: Proteins have the fundamental ability to selectively bind to other molecules and perform specific functions through such interactions, such as protein-ligand binding. Accurate prediction of protein residues that physically bind to ligands is important for drug design and protein docking studies. Most of the successful protein-ligand binding predictions were based on known structures. However, structural information is not largely available in practice due to the huge gap between the number of known protein sequences and that of experimentally solved structures

Protein backbone angle restraints from searching a database for chemical shift and sequence homology

Energy Technology Data Exchange (ETDEWEB)

Cornilescu, Gabriel; Delaglio, Frank; Bax, Ad [National Institutes of Health, Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases (United States)

1999-03-15

Chemical shifts of backbone atoms in proteins are exquisitely sensitive to local conformation, and homologous proteins show quite similar patterns of secondary chemical shifts. The inverse of this relation is used to search a database for triplets of adjacent residues with secondary chemical shifts and sequence similarity which provide the best match to the query triplet of interest. The database contains 13C{alpha}, 13C{beta}, 13C', 1H{alpha} and 15N chemical shifts for 20 proteins for which a high resolution X-ray structure is available. The computer program TALOS was developed to search this database for strings of residues with chemical shift and residue type homology. The relative importance of the weighting factors attached to the secondary chemical shifts of the five types of resonances relative to that of sequence similarity was optimized empirically. TALOS yields the 10 triplets which have the closest similarity in secondary chemical shift and amino acid sequence to those of the query sequence. If the central residues in these 10 triplets exhibit similar {phi} and {psi} backbone angles, their averages can reliably be used as angular restraints for the protein whose structure is being studied. Tests carried out for proteins of known structure indicate that the root-mean-square difference (rmsd) between the output of TALOS and the X-ray derived backbone angles is about 15 deg. Approximately 3% of the predictions made by TALOS are found to be in error.

Acute Phase Proteins and Variables of Protein Metabolism in Dairy Cows during the Pre- and Postpartal Period

Directory of Open Access Journals (Sweden)

Cs. Tóthová

2008-01-01

Full Text Available The objective of the present study was to compare the concentrations of acute phase proteins and selected variables of protein metabolism in dairy cows of the Slovak Spotted breed from 4 weeks before parturition to 10 weeks after parturition. Acute phase proteins - haptoglobin (Hp and serum amyloid A (SAA - and variables of protein metabolism - total proteins, albumin, urea, creatinine, total immunoglobulins - were evaluated in blood serum. Significant differences were found in average values of the Hp and SAA concentrations in several groups during the monitored period (P P P P P P P P P < 0.001. The above mentioned results indicate that in the time around parturition there are significant changes in concentrations of acute phase proteins, as well as in the whole protein metabolism of dairy cows. These facts suggest that the postparturient period is a critical biological phase, throughout which there is the highest incidence of metabolic disorders.

Combining sequence-based prediction methods and circular dichroism and infrared spectroscopic data to improve protein secondary structure determinations

Directory of Open Access Journals (Sweden)

Lees Jonathan G

2008-01-01

Full Text Available Abstract Background A number of sequence-based methods exist for protein secondary structure prediction. Protein secondary structures can also be determined experimentally from circular dichroism, and infrared spectroscopic data using empirical analysis methods. It has been proposed that comparable accuracy can be obtained from sequence-based predictions as from these biophysical measurements. Here we have examined the secondary structure determination accuracies of sequence prediction methods with the empirically determined values from the spectroscopic data on datasets of proteins for which both crystal structures and spectroscopic data are available. Results In this study we show that the sequence prediction methods have accuracies nearly comparable to those of spectroscopic methods. However, we also demonstrate that combining the spectroscopic and sequences techniques produces significant overall improvements in secondary structure determinations. In addition, combining the extra information content available from synchrotron radiation circular dichroism data with sequence methods also shows improvements. Conclusion Combining sequence prediction with experimentally determined spectroscopic methods for protein secondary structure content significantly enhances the accuracy of the overall results obtained.

Importance of Viral Sequence Length and Number of Variable and Informative Sites in Analysis of HIV Clustering.

Science.gov (United States)

Novitsky, Vlad; Moyo, Sikhulile; Lei, Quanhong; DeGruttola, Victor; Essex, M

2015-05-01

To improve the methodology of HIV cluster analysis, we addressed how analysis of HIV clustering is associated with parameters that can affect the outcome of viral clustering. The extent of HIV clustering and tree certainty was compared between 401 HIV-1C near full-length genome sequences and subgenomic regions retrieved from the LANL HIV Database. Sliding window analysis was based on 99 windows of 1,000 bp and 45 windows of 2,000 bp. Potential associations between the extent of HIV clustering and sequence length and the number of variable and informative sites were evaluated. The near full-length genome HIV sequences showed the highest extent of HIV clustering and the highest tree certainty. At the bootstrap threshold of 0.80 in maximum likelihood (ML) analysis, 58.9% of near full-length HIV-1C sequences but only 15.5% of partial pol sequences (ViroSeq) were found in clusters. Among HIV-1 structural genes, pol showed the highest extent of clustering (38.9% at a bootstrap threshold of 0.80), although it was significantly lower than in the near full-length genome sequences. The extent of HIV clustering was significantly higher for sliding windows of 2,000 bp than 1,000 bp. We found a strong association between the sequence length and proportion of HIV sequences in clusters, and a moderate association between the number of variable and informative sites and the proportion of HIV sequences in clusters. In HIV cluster analysis, the extent of detectable HIV clustering is directly associated with the length of viral sequences used, as well as the number of variable and informative sites. Near full-length genome sequences could provide the most informative HIV cluster analysis. Selected subgenomic regions with a high extent of HIV clustering and high tree certainty could also be considered as a second choice.

DIALIGN: multiple DNA and protein sequence alignment at BiBiServ.

OpenAIRE

Morgenstern, Burkhard

2004-01-01

DIALIGN is a widely used software tool for multiple DNA and protein sequence alignment. The program combines local and global alignment features and can therefore be applied to sequence data that cannot be correctly aligned by more traditional approaches. DIALIGN is available online through Bielefeld Bioinformatics Server (BiBiServ). The downloadable version of the program offers several new program features. To compare the output of different alignment programs, we developed the program AltA...

Oleosome-Associated Protein of the Oleaginous Diatom Fistulifera solaris Contains an Endoplasmic Reticulum-Targeting Signal Sequence

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Yoshiaki Maeda

2014-06-01

Full Text Available Microalgae tend to accumulate lipids as an energy storage material in the specific organelle, oleosomes. Current studies have demonstrated that lipids derived from microalgal oleosomes are a promising source of biofuels, while the oleosome formation mechanism has not been fully elucidated. Oleosome-associated proteins have been identified from several microalgae to elucidate the fundamental mechanisms of oleosome formation, although understanding their functions is still in infancy. Recently, we discovered a diatom-oleosome-associated-protein 1 (DOAP1 from the oleaginous diatom, Fistulifera solaris JPCC DA0580. The DOAP1 sequence implied that this protein might be transported into the endoplasmic reticulum (ER due to the signal sequence. To ensure this, we fused the signal sequence to green fluorescence protein. The fusion protein distributed around the chloroplast as like a meshwork membrane structure, indicating the ER localization. This result suggests that DOAP1 could firstly localize at the ER, then move to the oleosomes. This study also demonstrated that the DOAP1 signal sequence allowed recombinant proteins to be specifically expressed in the ER of the oleaginous diatom. It would be a useful technique for engineering the lipid synthesis pathways existing in the ER, and finally controlling the biofuel quality.

Genetic variability of Echinococcus granulosus from the Tibetan plateau inferred by mitochondrial DNA sequences.

Science.gov (United States)

Yan, Ning; Nie, Hua-Ming; Jiang, Zhong-Rong; Yang, Ai-Guo; Deng, Shi-Jin; Guo, Li; Yu, Hua; Yan, Yu-Bao; Tsering, Dawa; Kong, Wei-Shu; Wang, Ning; Wang, Jia-Hai; Xie, Yue; Fu, Yan; Yang, De-Ying; Wang, Shu-Xian; Gu, Xiao-Bin; Peng, Xue-Rong; Yang, Guang-You

2013-09-01

To analyse genetic variability and population structure, 84 isolates of Echinococcus granulosus (Cestoda: Taeniidae) collected from various host species at different sites of the Tibetan plateau in China were sequenced for the whole mitochondrial nad1 (894 bp) and atp6 (513 bp) genes. The vast majority were classified as G1 genotype (n=82), and two samples from human patients in Sichuan province were identified as G3 genotype. Based on the concatenated sequences of nad1+atp6, 28 different haplotypes (NA1-NA28) were identified. A parsimonious network of the concatenated sequence haplotypes showed star-like features in the overall population, with NA1 as the major haplotype in the population networks. By AMOVA it was shown that variation of E. granulosus within the overall population was the main pattern of the total genetic variability. Neutrality indexes of the concatenated sequence (nad1+atp6) were computed by Tajima's D and Fu's Fs tests and showed high negative values for E. granulosus, indicating significant deviations from neutrality. FST and Nm values suggested that the populations were not genetically differentiated. Copyright © 2013 Elsevier B.V. All rights reserved.

Sequence preservation of osteocalcin protein and mitochondrial DNA in bison bones older than 55 ka

Science.gov (United States)

Nielsen-Marsh, Christina M.; Ostrom, Peggy H.; Gandhi, Hasand; Shapiro, Beth; Cooper, Alan; Hauschka, Peter V.; Collins, Matthew J.

2002-12-01

We report the first complete sequences of the protein osteocalcin from small amounts (20 mg) of two bison bone (Bison priscus) dated to older than 55.6 ka and older than 58.9 ka. Osteocalcin was purified using new gravity columns (never exposed to protein) followed by microbore reversed-phase high-performance liquid chromatography. Sequencing of osteocalcin employed two methods of matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS): peptide mass mapping (PMM) and post-source decay (PSD). The PMM shows that ancient and modern bison osteocalcin have the same mass to charge (m/z) distribution, indicating an identical protein sequence and absence of diagenetic products. This was confirmed by PSD of the m/z 2066 tryptic peptide (residues 1 19); the mass spectra from ancient and modern peptides were identical. The 129 mass unit difference in the molecular ion between cow (Bos taurus) and bison is caused by a single amino-acid substitution between the taxa (Trp in cow is replaced by Gly in bison at residue 5). Bison mitochondrial control region DNA sequences were obtained from the older than 55.6 ka fossil. These results suggest that DNA and protein sequences can be used to directly investigate molecular phylogenies over a considerable time period, the absolute limit of which is yet to be determined.

Sequence analysis corresponding to the PPE and PE proteins in ...

Indian Academy of Sciences (India)

Unknown

AB repeats; Mycobacterium tuberculosis genome; PE-PPE domain; PPE, PE proteins; sequence analysis; surface antigens. J. Biosci. | Vol. ... bacterium tuberculosis genomes resulted in the identification of a previously uncharacterized 225 amino acid- ...... Vega Lopez F, Brooks L A, Dockrell H M, De Smet K A,. Thompson ...

Protein sequence analysis by incorporating modified chaos game and physicochemical properties into Chou's general pseudo amino acid composition.

Science.gov (United States)

Xu, Chunrui; Sun, Dandan; Liu, Shenghui; Zhang, Yusen

2016-10-07

In this contribution we introduced a novel graphical method to compare protein sequences. By mapping a protein sequence into 3D space based on codons and physicochemical properties of 20 amino acids, we are able to get a unique P-vector from the 3D curve. This approach is consistent with wobble theory of amino acids. We compute the distance between sequences by their P-vectors to measure similarities/dissimilarities among protein sequences. Finally, we use our method to analyze four datasets and get better results compared with previous approaches. Copyright © 2016 Elsevier Ltd. All rights reserved.

Determinants of cell-to-cell variability in protein kinase signaling.

Directory of Open Access Journals (Sweden)

Matthias Jeschke

Full Text Available Cells reliably sense environmental changes despite internal and external fluctuations, but the mechanisms underlying robustness remain unclear. We analyzed how fluctuations in signaling protein concentrations give rise to cell-to-cell variability in protein kinase signaling using analytical theory and numerical simulations. We characterized the dose-response behavior of signaling cascades by calculating the stimulus level at which a pathway responds ('pathway sensitivity' and the maximal activation level upon strong stimulation. Minimal kinase cascades with gradual dose-response behavior show strong variability, because the pathway sensitivity and the maximal activation level cannot be simultaneously invariant. Negative feedback regulation resolves this trade-off and coordinately reduces fluctuations in the pathway sensitivity and maximal activation. Feedbacks acting at different levels in the cascade control different aspects of the dose-response curve, thereby synergistically reducing the variability. We also investigated more complex, ultrasensitive signaling cascades capable of switch-like decision making, and found that these can be inherently robust to protein concentration fluctuations. We describe how the cell-to-cell variability of ultrasensitive signaling systems can be actively regulated, e.g., by altering the expression of phosphatase(s or by feedback/feedforward loops. Our calculations reveal that slow transcriptional negative feedback loops allow for variability suppression while maintaining switch-like decision making. Taken together, we describe design principles of signaling cascades that promote robustness. Our results may explain why certain signaling cascades like the yeast pheromone pathway show switch-like decision making with little cell-to-cell variability.

PFP: Automated prediction of gene ontology functional annotations with confidence scores using protein sequence data.

Science.gov (United States)

Hawkins, Troy; Chitale, Meghana; Luban, Stanislav; Kihara, Daisuke

2009-02-15

Protein function prediction is a central problem in bioinformatics, increasing in importance recently due to the rapid accumulation of biological data awaiting interpretation. Sequence data represents the bulk of this new stock and is the obvious target for consideration as input, as newly sequenced organisms often lack any other type of biological characterization. We have previously introduced PFP (Protein Function Prediction) as our sequence-based predictor of Gene Ontology (GO) functional terms. PFP interprets the results of a PSI-BLAST search by extracting and scoring individual functional attributes, searching a wide range of E-value sequence matches, and utilizing conventional data mining techniques to fill in missing information. We have shown it to be effective in predicting both specific and low-resolution functional attributes when sufficient data is unavailable. Here we describe (1) significant improvements to the PFP infrastructure, including the addition of prediction significance and confidence scores, (2) a thorough benchmark of performance and comparisons to other related prediction methods, and (3) applications of PFP predictions to genome-scale data. We applied PFP predictions to uncharacterized protein sequences from 15 organisms. Among these sequences, 60-90% could be annotated with a GO molecular function term at high confidence (>or=80%). We also applied our predictions to the protein-protein interaction network of the Malaria plasmodium (Plasmodium falciparum). High confidence GO biological process predictions (>or=90%) from PFP increased the number of fully enriched interactions in this dataset from 23% of interactions to 94%. Our benchmark comparison shows significant performance improvement of PFP relative to GOtcha, InterProScan, and PSI-BLAST predictions. This is consistent with the performance of PFP as the overall best predictor in both the AFP-SIG '05 and CASP7 function (FN) assessments. PFP is available as a web service at http

Visualization of protein sequence features using JavaScript and SVG with pViz.js.

Science.gov (United States)

Mukhyala, Kiran; Masselot, Alexandre

2014-12-01

pViz.js is a visualization library for displaying protein sequence features in a Web browser. By simply providing a sequence and the locations of its features, this lightweight, yet versatile, JavaScript library renders an interactive view of the protein features. Interactive exploration of protein sequence features over the Web is a common need in Bioinformatics. Although many Web sites have developed viewers to display these features, their implementations are usually focused on data from a specific source or use case. Some of these viewers can be adapted to fit other use cases but are not designed to be reusable. pViz makes it easy to display features as boxes aligned to a protein sequence with zooming functionality but also includes predefined renderings for secondary structure and post-translational modifications. The library is designed to further customize this view. We demonstrate such applications of pViz using two examples: a proteomic data visualization tool with an embedded viewer for displaying features on protein structure, and a tool to visualize the results of the variant_effect_predictor tool from Ensembl. pViz.js is a JavaScript library, available on github at https://github.com/Genentech/pviz. This site includes examples and functional applications, installation instructions and usage documentation. A Readme file, which explains how to use pViz with examples, is available as Supplementary Material A. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Proteins interacting with cloning scars: a source of false positive protein-protein interactions.

Science.gov (United States)

Banks, Charles A S; Boanca, Gina; Lee, Zachary T; Florens, Laurence; Washburn, Michael P

2015-02-23

A common approach for exploring the interactome, the network of protein-protein interactions in cells, uses a commercially available ORF library to express affinity tagged bait proteins; these can be expressed in cells and endogenous cellular proteins that copurify with the bait can be identified as putative interacting proteins using mass spectrometry. Control experiments can be used to limit false-positive results, but in many cases, there are still a surprising number of prey proteins that appear to copurify specifically with the bait. Here, we have identified one source of false-positive interactions in such studies. We have found that a combination of: 1) the variable sequence of the C-terminus of the bait with 2) a C-terminal valine "cloning scar" present in a commercially available ORF library, can in some cases create a peptide motif that results in the aberrant co-purification of endogenous cellular proteins. Control experiments may not identify false positives resulting from such artificial motifs, as aberrant binding depends on sequences that vary from one bait to another. It is possible that such cryptic protein binding might occur in other systems using affinity tagged proteins; this study highlights the importance of conducting careful follow-up studies where novel protein-protein interactions are suspected.

Implication of the cause of differences in 3D structures of proteins with high sequence identity based on analyses of amino acid sequences and 3D structures.

Science.gov (United States)

Matsuoka, Masanari; Sugita, Masatake; Kikuchi, Takeshi

2014-09-18

Proteins that share a high sequence homology while exhibiting drastically different 3D structures are investigated in this study. Recently, artificial proteins related to the sequences of the GA and IgG binding GB domains of human serum albumin have been designed. These artificial proteins, referred to as GA and GB, share 98% amino acid sequence identity but exhibit different 3D structures, namely, a 3α bundle versus a 4β + α structure. Discriminating between their 3D structures based on their amino acid sequences is a very difficult problem. In the present work, in addition to using bioinformatics techniques, an analysis based on inter-residue average distance statistics is used to address this problem. It was hard to distinguish which structure a given sequence would take only with the results of ordinary analyses like BLAST and conservation analyses. However, in addition to these analyses, with the analysis based on the inter-residue average distance statistics and our sequence tendency analysis, we could infer which part would play an important role in its structural formation. The results suggest possible determinants of the different 3D structures for sequences with high sequence identity. The possibility of discriminating between the 3D structures based on the given sequences is also discussed.

A two-step recognition of signal sequences determines the translocation efficiency of proteins.

Science.gov (United States)

Belin, D; Bost, S; Vassalli, J D; Strub, K

1996-02-01

The cytosolic and secreted, N-glycosylated, forms of plasminogen activator inhibitor-2 (PAI-2) are generated by facultative translocation. To study the molecular events that result in the bi-topological distribution of proteins, we determined in vitro the capacities of several signal sequences to bind the signal recognition particle (SRP) during targeting, and to promote vectorial transport of murine PAI-2 (mPAI-2). Interestingly, the six signal sequences we compared (mPAI-2 and three mutated derivatives thereof, ovalbumin and preprolactin) were found to have the differential activities in the two events. For example, the mPAI-2 signal sequence first binds SRP with moderate efficiency and secondly promotes the vectorial transport of only a fraction of the SRP-bound nascent chains. Our results provide evidence that the translocation efficiency of proteins can be controlled by the recognition of their signal sequences at two steps: during SRP-mediated targeting and during formation of a committed translocation complex. This second recognition may occur at several time points during the insertion/translocation step. In conclusion, signal sequences have a more complex structure than previously anticipated, allowing for multiple and independent interactions with the translocation machinery.

Nucleotide sequence of a cDNA for branched chain acyltransferase with analysis of the deduced protein structure

International Nuclear Information System (INIS)

Hummel, K.B.; Litwer, S.; Bradford, A.P.; Aitken, A.; Danner, D.J.; Yeaman, S.J.

1988-01-01

Nucleotide sequence was determined for a 1.6-kilobase human cDNA putative for the branched chain acyltransferase protein of the branched chain α-ketoacid dehydrogenase complex. Translation of the sequence reveals an open reading frame encoding a 315-amino acid protein of molecular weight 35,759 followed by 560 bases of 3'-untranslated sequence. Three repeats of the polyadenylation signal hexamer ATTAAA are present prior to the polyadenylate tail. Within the open reading frame is a 10-amino acid fragment which matches exactly the amino acid sequence around the lipoate-lysine residue in bovine kidney branched chain acyltransferase, thus confirming the identity of the cDNA. Analysis of the deduced protein structure for the human branched chain acyltransferase revealed an organization into domains similar to that reported for the acyltransferase proteins of the pyruvate and α-ketoglutarate dehydrogenase complexes. This similarity in organization suggests that a more detailed analysis of the proteins will be required to explain the individual substrate and multienzyme complex specificity shown by these acyltransferases

Interobserver variability in the evaluation of mismatch repair protein immunostaining

DEFF Research Database (Denmark)

Klarskov, Louise Laurberg; Ladelund, Steen; Holck, Susanne

2010-01-01

Immunohistochemical staining for mismatch repair proteins has during recent years been established as a routine analysis in many pathology laboratories with the aim to identify tumors linked to the hereditary nonpolyposis colorectal cancer syndrome. Despite widespread application, data on reliabi......Immunohistochemical staining for mismatch repair proteins has during recent years been established as a routine analysis in many pathology laboratories with the aim to identify tumors linked to the hereditary nonpolyposis colorectal cancer syndrome. Despite widespread application, data...... on reliability are lacking. We therefore evaluated interobserver variability among 6 pathologists, 3 experienced gastrointestinal pathologists and 3 residents. In total, 225 immunohistochemically stained colorectal cancers were evaluated as having normal, weak, loss of, or nonevaluable mismatch repair protein...... variability was considerable, though experienced pathologists and residents reached the same level of consensus. Because results from immunohistochemical mismatch repair protein stainings are used for decisions on mutation analysis and as an aid in the interpretation of gene variants of unknown significance...

Experimental Rugged Fitness Landscape in Protein Sequence Space

Science.gov (United States)

Hayashi, Yuuki; Aita, Takuyo; Toyota, Hitoshi; Husimi, Yuzuru; Urabe, Itaru; Yomo, Tetsuya

2006-01-01

The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12–130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7×104-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1) the dependence of stationary fitness on library size, which increased gradually, and (2) the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18–24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region. PMID:17183728

Experimental rugged fitness landscape in protein sequence space.

Science.gov (United States)

Hayashi, Yuuki; Aita, Takuyo; Toyota, Hitoshi; Husimi, Yuzuru; Urabe, Itaru; Yomo, Tetsuya

2006-12-20

The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12-130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7x10(4)-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1) the dependence of stationary fitness on library size, which increased gradually, and (2) the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18-24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region.

Experimental rugged fitness landscape in protein sequence space.

Directory of Open Access Journals (Sweden)

Yuuki Hayashi

Full Text Available The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12-130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7x10(4-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1 the dependence of stationary fitness on library size, which increased gradually, and (2 the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18-24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region.

Protein sequences bound to mineral surfaces persist into deep time

DEFF Research Database (Denmark)

Demarchi, Beatrice; Hall, Shaun; Roncal-Herrero, Teresa

2016-01-01

of Laetoli (3.8 Ma) and Olduvai Gorge (1.3 Ma) in Tanzania. By tracking protein diagenesis back in time we find consistent patterns of preservation, demonstrating authenticity of the surviving sequences. Molecular dynamics simulations of struthiocalcin-1 and -2, the dominant proteins within the eggshell......, reveal that distinct domains bind to the mineral surface. It is the domain with the strongest calculated binding energy to the calcite surface that is selectively preserved. Thermal age calculations demonstrate that the Laetoli and Olduvai peptides are 50 times older than any previously authenticated...

Programming molecular self-assembly of intrinsically disordered proteins containing sequences of low complexity

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Simon, Joseph R.; Carroll, Nick J.; Rubinstein, Michael; Chilkoti, Ashutosh; López, Gabriel P.

2017-06-01

Dynamic protein-rich intracellular structures that contain phase-separated intrinsically disordered proteins (IDPs) composed of sequences of low complexity (SLC) have been shown to serve a variety of important cellular functions, which include signalling, compartmentalization and stabilization. However, our understanding of these structures and our ability to synthesize models of them have been limited. We present design rules for IDPs possessing SLCs that phase separate into diverse assemblies within droplet microenvironments. Using theoretical analyses, we interpret the phase behaviour of archetypal IDP sequences and demonstrate the rational design of a vast library of multicomponent protein-rich structures that ranges from uniform nano-, meso- and microscale puncta (distinct protein droplets) to multilayered orthogonally phase-separated granular structures. The ability to predict and program IDP-rich assemblies in this fashion offers new insights into (1) genetic-to-molecular-to-macroscale relationships that encode hierarchical IDP assemblies, (2) design rules of such assemblies in cell biology and (3) molecular-level engineering of self-assembled recombinant IDP-rich materials.

Conformational Entropy as Collective Variable for Proteins.

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Palazzesi, Ferruccio; Valsson, Omar; Parrinello, Michele

2017-10-05

Many enhanced sampling methods rely on the identification of appropriate collective variables. For proteins, even small ones, finding appropriate descriptors has proven challenging. Here we suggest that the NMR S 2 order parameter can be used to this effect. We trace the validity of this statement to the suggested relation between S 2 and conformational entropy. Using the S 2 order parameter and a surrogate for the protein enthalpy in conjunction with metadynamics or variationally enhanced sampling, we are able to reversibly fold and unfold a small protein and draw its free energy at a fraction of the time that is needed in unbiased simulations. We also use S 2 in combination with the free energy flooding method to compute the unfolding rate of this peptide. We repeat this calculation at different temperatures to obtain the unfolding activation energy.

Genome-wide profiling of DNA-binding proteins using barcode-based multiplex Solexa sequencing.

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Raghav, Sunil Kumar; Deplancke, Bart

2012-01-01

Chromatin immunoprecipitation (ChIP) is a commonly used technique to detect the in vivo binding of proteins to DNA. ChIP is now routinely paired to microarray analysis (ChIP-chip) or next-generation sequencing (ChIP-Seq) to profile the DNA occupancy of proteins of interest on a genome-wide level. Because ChIP-chip introduces several biases, most notably due to the use of a fixed number of probes, ChIP-Seq has quickly become the method of choice as, depending on the sequencing depth, it is more sensitive, quantitative, and provides a greater binding site location resolution. With the ever increasing number of reads that can be generated per sequencing run, it has now become possible to analyze several samples simultaneously while maintaining sufficient sequence coverage, thus significantly reducing the cost per ChIP-Seq experiment. In this chapter, we provide a step-by-step guide on how to perform multiplexed ChIP-Seq analyses. As a proof-of-concept, we focus on the genome-wide profiling of RNA Polymerase II as measuring its DNA occupancy at different stages of any biological process can provide insights into the gene regulatory mechanisms involved. However, the protocol can also be used to perform multiplexed ChIP-Seq analyses of other DNA-binding proteins such as chromatin modifiers and transcription factors.

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

Molecular Simulations of Sequence-Specific Association of Transmembrane Proteins in Lipid Bilayers

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Doxastakis, Manolis; Prakash, Anupam; Janosi, Lorant

2011-03-01

Association of membrane proteins is central in material and information flow across the cellular membranes. Amino-acid sequence and the membrane environment are two critical factors controlling association, however, quantitative knowledge on such contributions is limited. In this work, we study the dimerization of helices in lipid bilayers using extensive parallel Monte Carlo simulations with recently developed algorithms. The dimerization of Glycophorin A is examined employing a coarse-grain model that retains a level of amino-acid specificity, in three different phospholipid bilayers. Association is driven by a balance of protein-protein and lipid-induced interactions with the latter playing a major role at short separations. Following a different approach, the effect of amino-acid sequence is studied using the four transmembrane domains of the epidermal growth factor receptor family in identical lipid environments. Detailed characterization of dimer formation and estimates of the free energy of association reveal that these helices present significant affinity to self-associate with certain dimers forming non-specific interfaces.

Protein expression and genetic variability of canine Can f 1 in golden and Labrador retriever service dogs.

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Breitenbuecher, Christina; Belanger, Janelle M; Levy, Kerinne; Mundell, Paul; Fates, Valerie; Gershony, Liza; Famula, Thomas R; Oberbauer, Anita M

2016-01-01

Valued for trainability in diverse tasks, dogs are the primary service animal used to assist individuals with disabilities. Despite their utility, many people in need of service dogs are sensitive to the primary dog allergen, Can f 1, encoded by the Lipocalin 1 gene (LCN1). Several organizations specifically breed service dogs to meet special needs and would like to reduce allergenic potential if possible. In this study, we evaluated the expression of Can f 1 protein and the inherent variability of LCN1 in two breeds used extensively as service dogs. Saliva samples from equal numbers of male and female Labrador retrievers (n = 12), golden retrievers (n = 12), and Labrador-golden crosses (n = 12) were collected 1 h after the morning meal. Can f 1 protein concentrations in the saliva were measured by ELISA, and the LCN1 5' and 3' UTRs and exons sequenced. There was no sex effect (p > 0.2) nor time-of-day effect; however, Can f 1 protein levels varied by breed with Labrador retrievers being lower than golden retrievers (3.18 ± 0.51 and 5.35 ± 0.52 μg/ml, respectively, p < 0.0075), and the Labrador-golden crosses having intermediate levels (3.77 ± 0.48 μg/ml). Although several novel SNPs were identified in LCN1, there were no significant breed-specific sequence differences in the gene and no association of LCN1 genotypes with Can f 1 expression. As service dogs, Labrador retrievers likely have lower allergenic potential and, though there were no DNA sequence differences identified, classical genetic selection on the estimated breeding values associated with salivary Can f 1 expression may further reduce that potential.

Identification of similar regions of protein structures using integrated sequence and structure analysis tools

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Heiland Randy

2006-03-01

Full Text Available Abstract Background Understanding protein function from its structure is a challenging problem. Sequence based approaches for finding homology have broad use for annotation of both structure and function. 3D structural information of protein domains and their interactions provide a complementary view to structure function relationships to sequence information. We have developed a web site http://www.sblest.org/ and an API of web services that enables users to submit protein structures and identify statistically significant neighbors and the underlying structural environments that make that match using a suite of sequence and structure analysis tools. To do this, we have integrated S-BLEST, PSI-BLAST and HMMer based superfamily predictions to give a unique integrated view to prediction of SCOP superfamilies, EC number, and GO term, as well as identification of the protein structural environments that are associated with that prediction. Additionally, we have extended UCSF Chimera and PyMOL to support our web services, so that users can characterize their own proteins of interest. Results Users are able to submit their own queries or use a structure already in the PDB. Currently the databases that a user can query include the popular structural datasets ASTRAL 40 v1.69, ASTRAL 95 v1.69, CLUSTER50, CLUSTER70 and CLUSTER90 and PDBSELECT25. The results can be downloaded directly from the site and include function prediction, analysis of the most conserved environments and automated annotation of query proteins. These results reflect both the hits found with PSI-BLAST, HMMer and with S-BLEST. We have evaluated how well annotation transfer can be performed on SCOP ID's, Gene Ontology (GO ID's and EC Numbers. The method is very efficient and totally automated, generally taking around fifteen minutes for a 400 residue protein. Conclusion With structural genomics initiatives determining structures with little, if any, functional characterization

Genome-Wide Prediction and Analysis of 3D-Domain Swapped Proteins in the Human Genome from Sequence Information.

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Upadhyay, Atul Kumar; Sowdhamini, Ramanathan

2016-01-01

3D-domain swapping is one of the mechanisms of protein oligomerization and the proteins exhibiting this phenomenon have many biological functions. These proteins, which undergo domain swapping, have acquired much attention owing to their involvement in human diseases, such as conformational diseases, amyloidosis, serpinopathies, proteionopathies etc. Early realisation of proteins in the whole human genome that retain tendency to domain swap will enable many aspects of disease control management. Predictive models were developed by using machine learning approaches with an average accuracy of 78% (85.6% of sensitivity, 87.5% of specificity and an MCC value of 0.72) to predict putative domain swapping in protein sequences. These models were applied to many complete genomes with special emphasis on the human genome. Nearly 44% of the protein sequences in the human genome were predicted positive for domain swapping. Enrichment analysis was performed on the positively predicted sequences from human genome for their domain distribution, disease association and functional importance based on Gene Ontology (GO). Enrichment analysis was also performed to infer a better understanding of the functional importance of these sequences. Finally, we developed hinge region prediction, in the given putative domain swapped sequence, by using important physicochemical properties of amino acids.

Conserved hypothetical protein Rv1977 in Mycobacterium tuberculosis strains contains sequence polymorphisms and might be involved in ongoing immune evasion.

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Jiang, Yi; Liu, Haican; Wang, Xuezhi; Li, Guilian; Qiu, Yan; Dou, Xiangfeng; Wan, Kanglin

2015-01-01

Host immune pressure and associated parasite immune evasion are key features of host-pathogen co-evolution. A previous study showed that human T cell epitopes of Mycobacterium tuberculosis are evolutionarily hyperconserved and thus it was deduced that M. tuberculosis lacks antigenic variation and immune evasion. Here, we selected 151 clinical Mycobacterium tuberculosis isolates from China, amplified gene encoding Rv1977 and compared the sequences. The results showed that Rv1977, a conserved hypothetical protein, is not conserved in M. tuberculosis strains and there are polymorphisms existed in the protein. Some mutations, especially one frameshift mutation, occurred in the antigen Rv1977, which is uncommon in M.tb strains and may lead to the protein function altering. Mutations and deletion in the gene all affect one of three T cell epitopes and the changed T cell epitope contained more than one variable position, which may suggest ongoing immune evasion.

Random amino acid mutations and protein misfolding lead to Shannon limit in sequence-structure communication.

Directory of Open Access Journals (Sweden)

Andreas Martin Lisewski

2008-09-01

Full Text Available The transmission of genomic information from coding sequence to protein structure during protein synthesis is subject to stochastic errors. To analyze transmission limits in the presence of spurious errors, Shannon's noisy channel theorem is applied to a communication channel between amino acid sequences and their structures established from a large-scale statistical analysis of protein atomic coordinates. While Shannon's theorem confirms that in close to native conformations information is transmitted with limited error probability, additional random errors in sequence (amino acid substitutions and in structure (structural defects trigger a decrease in communication capacity toward a Shannon limit at 0.010 bits per amino acid symbol at which communication breaks down. In several controls, simulated error rates above a critical threshold and models of unfolded structures always produce capacities below this limiting value. Thus an essential biological system can be realistically modeled as a digital communication channel that is (a sensitive to random errors and (b restricted by a Shannon error limit. This forms a novel basis for predictions consistent with observed rates of defective ribosomal products during protein synthesis, and with the estimated excess of mutual information in protein contact potentials.

Origin and spread of photosynthesis based upon conserved sequence features in key bacteriochlorophyll biosynthesis proteins.

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Gupta, Radhey S

2012-11-01

The origin of photosynthesis and how this capability has spread to other bacterial phyla remain important unresolved questions. I describe here a number of conserved signature indels (CSIs) in key proteins involved in bacteriochlorophyll (Bchl) biosynthesis that provide important insights in these regards. The proteins BchL and BchX, which are essential for Bchl biosynthesis, are derived by gene duplication in a common ancestor of all phototrophs. More ancient gene duplication gave rise to the BchX-BchL proteins and the NifH protein of the nitrogenase complex. The sequence alignment of NifH-BchX-BchL proteins contain two CSIs that are uniquely shared by all NifH and BchX homologs, but not by any BchL homologs. These CSIs and phylogenetic analysis of NifH-BchX-BchL protein sequences strongly suggest that the BchX homologs are ancestral to BchL and that the Bchl-based anoxygenic photosynthesis originated prior to the chlorophyll (Chl)-based photosynthesis in cyanobacteria. Another CSI in the BchX-BchL sequence alignment that is uniquely shared by all BchX homologs and the BchL sequences from Heliobacteriaceae, but absent in all other BchL homologs, suggests that the BchL homologs from Heliobacteriaceae are primitive in comparison to all other photosynthetic lineages. Several other identified CSIs in the BchN homologs are commonly shared by all proteobacterial homologs and a clade consisting of the marine unicellular Cyanobacteria (Clade C). These CSIs in conjunction with the results of phylogenetic analyses and pair-wise sequence similarity on the BchL, BchN, and BchB proteins, where the homologs from Clade C Cyanobacteria and Proteobacteria exhibited close relationship, provide strong evidence that these two groups have incurred lateral gene transfers. Additionally, phylogenetic analyses and several CSIs in the BchL-N-B proteins that are uniquely shared by all Chlorobi and Chloroflexi homologs provide evidence that the genes for these proteins have also been

PANTHER version 6: protein sequence and function evolution data with expanded representation of biological pathways

OpenAIRE

Mi, Huaiyu; Guo, Nan; Kejariwal, Anish; Thomas, Paul D.

2006-01-01

PANTHER is a freely available, comprehensive software system for relating protein sequence evolution to the evolution of specific protein functions and biological roles. Since 2005, there have been three main improvements to PANTHER. First, the sequences used to create evolutionary trees are carefully selected to provide coverage of phylogenetic as well as functional information. Second, PANTHER is now a member of the InterPro Consortium, and the PANTHER hidden markov Models (HMMs) are distri...

Using the Relevance Vector Machine Model Combined with Local Phase Quantization to Predict Protein-Protein Interactions from Protein Sequences

Directory of Open Access Journals (Sweden)

Ji-Yong An

2016-01-01

Full Text Available We propose a novel computational method known as RVM-LPQ that combines the Relevance Vector Machine (RVM model and Local Phase Quantization (LPQ to predict PPIs from protein sequences. The main improvements are the results of representing protein sequences using the LPQ feature representation on a Position Specific Scoring Matrix (PSSM, reducing the influence of noise using a Principal Component Analysis (PCA, and using a Relevance Vector Machine (RVM based classifier. We perform 5-fold cross-validation experiments on Yeast and Human datasets, and we achieve very high accuracies of 92.65% and 97.62%, respectively, which is significantly better than previous works. To further evaluate the proposed method, we compare it with the state-of-the-art support vector machine (SVM classifier on the Yeast dataset. The experimental results demonstrate that our RVM-LPQ method is obviously better than the SVM-based method. The promising experimental results show the efficiency and simplicity of the proposed method, which can be an automatic decision support tool for future proteomics research.

SigniSite: Identification of residue-level genotype-phenotype correlations in protein multiple sequence alignments

DEFF Research Database (Denmark)

Jessen, Leon Ivar; Hoof, Ilka; Lund, Ole

2013-01-01

Site does not require any pre-definition of subgroups or binary classification. Input is a set of protein sequences where each sequence has an associated real number, quantifying a given phenotype. SigniSite will then identify which amino acid residues are significantly associated with the data set......) using a set of human immunodeficiency virus protease-inhibitor genotype–phenotype data and corresponding resistance mutation scores from the Stanford University HIV Drug Resistance Database, and a data set of protein families with experimentally annotated SDPs. For both data sets, SigniSite was found...

Evolutionary conservation of nuclear and nucleolar targeting sequences in yeast ribosomal protein S6A

International Nuclear Information System (INIS)

Lipsius, Edgar; Walter, Korden; Leicher, Torsten; Phlippen, Wolfgang; Bisotti, Marc-Angelo; Kruppa, Joachim

2005-01-01

Over 1 billion years ago, the animal kingdom diverged from the fungi. Nevertheless, a high sequence homology of 62% exists between human ribosomal protein S6 and S6A of Saccharomyces cerevisiae. To investigate whether this similarity in primary structure is mirrored in corresponding functional protein domains, the nuclear and nucleolar targeting signals were delineated in yeast S6A and compared to the known human S6 signals. The complete sequence of S6A and cDNA fragments was fused to the 5'-end of the LacZ gene, the constructs were transiently expressed in COS cells, and the subcellular localization of the fusion proteins was detected by indirect immunofluorescence. One bipartite and two monopartite nuclear localization signals as well as two nucleolar binding domains were identified in yeast S6A, which are located at homologous regions in human S6 protein. Remarkably, the number, nature, and position of these targeting signals have been conserved, albeit their amino acid sequences have presumably undergone a process of co-evolution with their corresponding rRNAs

Preservation of the metaproteome: variability of protein preservation in ancient dental calculus.

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Mackie, Meaghan; Hendy, Jessica; Lowe, Abigail D; Sperduti, Alessandra; Holst, Malin; Collins, Matthew J; Speller, Camilla F

2017-01-01

Proteomic analysis of dental calculus is emerging as a powerful tool for disease and dietary characterisation of archaeological populations. To better understand the variability in protein results from dental calculus, we analysed 21 samples from three Roman-period populations to compare: 1) the quantity of extracted protein; 2) the number of mass spectral queries; and 3) the number of peptide spectral matches and protein identifications. We found little correlation between the quantity of calculus analysed and total protein identifications, as well as no systematic trends between site location and protein preservation. We identified a wide range of individual variability, which may be associated with the mechanisms of calculus formation and/or post-depositional contamination, in addition to taphonomic factors. Our results suggest dental calculus is indeed a stable, long-term reservoir of proteins as previously reported, but further systematic studies are needed to identify mechanisms associated with protein entrapment and survival in dental calculus.

Effect of the sequence data deluge on the performance of methods for detecting protein functional residues.

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Garrido-Martín, Diego; Pazos, Florencio

2018-02-27

The exponential accumulation of new sequences in public databases is expected to improve the performance of all the approaches for predicting protein structural and functional features. Nevertheless, this was never assessed or quantified for some widely used methodologies, such as those aimed at detecting functional sites and functional subfamilies in protein multiple sequence alignments. Using raw protein sequences as only input, these approaches can detect fully conserved positions, as well as those with a family-dependent conservation pattern. Both types of residues are routinely used as predictors of functional sites and, consequently, understanding how the sequence content of the databases affects them is relevant and timely. In this work we evaluate how the growth and change with time in the content of sequence databases affect five sequence-based approaches for detecting functional sites and subfamilies. We do that by recreating historical versions of the multiple sequence alignments that would have been obtained in the past based on the database contents at different time points, covering a period of 20 years. Applying the methods to these historical alignments allows quantifying the temporal variation in their performance. Our results show that the number of families to which these methods can be applied sharply increases with time, while their ability to detect potentially functional residues remains almost constant. These results are informative for the methods' developers and final users, and may have implications in the design of new sequencing initiatives.

RNA2 of grapevine fanleaf virus: sequence analysis and coat protein cistron location.

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Serghini, M A; Fuchs, M; Pinck, M; Reinbolt, J; Walter, B; Pinck, L

1990-07-01

The nucleotide sequence of the genomic RNA2 (3774 nucleotides) of grapevine fanleaf virus strain F13 was determined from overlapping cDNA clones and its genetic organization was deduced. Two rapid and efficient methods were used for cDNA cloning of the 5' region of RNA2. The complete sequence contained only one long open reading frame of 3555 nucleotides (1184 codons, 131K product). The analysis of the N-terminal sequence of purified coat protein (CP) and identification of its C-terminal residue have allowed the CP cistron to be precisely positioned within the polyprotein. The CP produced by proteolytic cleavage at the Arg/Gly site between residues 680 and 681 contains 504 amino acids (Mr 56019) and has hydrophobic properties. The Arg/Gly cleavage site deduced by N-terminal amino acid sequence analysis is the first for a nepovirus coat protein and for plant viruses expressing their genomic RNAs by polyprotein synthesis. Comparison of GFLV RNA2 with M RNA of cowpea mosaic comovirus and with RNA2 of two closely related nepoviruses, tomato black ring virus and Hungarian grapevine chrome mosaic virus, showed strong similarities among the 3' non-coding regions but less similarity among the 5' end non-coding sequences than reported among other nepovirus RNAs.

Structural and sequence analysis of imelysin-like proteins implicated in bacterial iron uptake.

Directory of Open Access Journals (Sweden)

Qingping Xu

Full Text Available Imelysin-like proteins define a superfamily of bacterial proteins that are likely involved in iron uptake. Members of this superfamily were previously thought to be peptidases and were included in the MEROPS family M75. We determined the first crystal structures of two remotely related, imelysin-like proteins. The Psychrobacter arcticus structure was determined at 2.15 Å resolution and contains the canonical imelysin fold, while higher resolution structures from the gut bacteria Bacteroides ovatus, in two crystal forms (at 1.25 Å and 1.44 Å resolution, have a circularly permuted topology. Both structures are highly similar to each other despite low sequence similarity and circular permutation. The all-helical structure can be divided into two similar four-helix bundle domains. The overall structure and the GxHxxE motif region differ from known HxxE metallopeptidases, suggesting that imelysin-like proteins are not peptidases. A putative functional site is located at the domain interface. We have now organized the known homologous proteins into a superfamily, which can be separated into four families. These families share a similar functional site, but each has family-specific structural and sequence features. These results indicate that imelysin-like proteins have evolved from a common ancestor, and likely have a conserved function.

Properties of Sequence Conservation in Upstream Regulatory and Protein Coding Sequences among Paralogs in Arabidopsis thaliana

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Richardson, Dale N.; Wiehe, Thomas

Whole genome duplication (WGD) has catalyzed the formation of new species, genes with novel functions, altered expression patterns, complexified signaling pathways and has provided organisms a level of genetic robustness. We studied the long-term evolution and interrelationships of 5’ upstream regulatory sequences (URSs), protein coding sequences (CDSs) and expression correlations (EC) of duplicated gene pairs in Arabidopsis. Three distinct methods revealed significant evolutionary conservation between paralogous URSs and were highly correlated with microarray-based expression correlation of the respective gene pairs. Positional information on exact matches between sequences unveiled the contribution of micro-chromosomal rearrangements on expression divergence. A three-way rank analysis of URS similarity, CDS divergence and EC uncovered specific gene functional biases. Transcription factor activity was associated with gene pairs exhibiting conserved URSs and divergent CDSs, whereas a broad array of metabolic enzymes was found to be associated with gene pairs showing diverged URSs but conserved CDSs.

Full-Length Venom Protein cDNA Sequences from Venom-Derived mRNA: Exploring Compositional Variation and Adaptive Multigene Evolution.

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Modahl, Cassandra M; Mackessy, Stephen P

2016-06-01

Envenomation of humans by snakes is a complex and continuously evolving medical emergency, and treatment is made that much more difficult by the diverse biochemical composition of many venoms. Venomous snakes and their venoms also provide models for the study of molecular evolutionary processes leading to adaptation and genotype-phenotype relationships. To compare venom complexity and protein sequences, venom gland transcriptomes are assembled, which usually requires the sacrifice of snakes for tissue. However, toxin transcripts are also present in venoms, offering the possibility of obtaining cDNA sequences directly from venom. This study provides evidence that unknown full-length venom protein transcripts can be obtained from the venoms of multiple species from all major venomous snake families. These unknown venom protein cDNAs are obtained by the use of primers designed from conserved signal peptide sequences within each venom protein superfamily. This technique was used to assemble a partial venom gland transcriptome for the Middle American Rattlesnake (Crotalus simus tzabcan) by amplifying sequences for phospholipases A2, serine proteases, C-lectins, and metalloproteinases from within venom. Phospholipase A2 sequences were also recovered from the venoms of several rattlesnakes and an elapid snake (Pseudechis porphyriacus), and three-finger toxin sequences were recovered from multiple rear-fanged snake species, demonstrating that the three major clades of advanced snakes (Elapidae, Viperidae, Colubridae) have stable mRNA present in their venoms. These cDNA sequences from venom were then used to explore potential activities derived from protein sequence similarities and evolutionary histories within these large multigene superfamilies. Venom-derived sequences can also be used to aid in characterizing venoms that lack proteomic profiles and identify sequence characteristics indicating specific envenomation profiles. This approach, requiring only venom, provides

Protein domain analysis of genomic sequence data reveals regulation of LRR related domains in plant transpiration in Ficus.

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Lang, Tiange; Yin, Kangquan; Liu, Jinyu; Cao, Kunfang; Cannon, Charles H; Du, Fang K

2014-01-01

Predicting protein domains is essential for understanding a protein's function at the molecular level. However, up till now, there has been no direct and straightforward method for predicting protein domains in species without a reference genome sequence. In this study, we developed a functionality with a set of programs that can predict protein domains directly from genomic sequence data without a reference genome. Using whole genome sequence data, the programming functionality mainly comprised DNA assembly in combination with next-generation sequencing (NGS) assembly methods and traditional methods, peptide prediction and protein domain prediction. The proposed new functionality avoids problems associated with de novo assembly due to micro reads and small single repeats. Furthermore, we applied our functionality for the prediction of leucine rich repeat (LRR) domains in four species of Ficus with no reference genome, based on NGS genomic data. We found that the LRRNT_2 and LRR_8 domains are related to plant transpiration efficiency, as indicated by the stomata index, in the four species of Ficus. The programming functionality established in this study provides new insights for protein domain prediction, which is particularly timely in the current age of NGS data expansion.

On the Power and Limits of Sequence Similarity Based Clustering of Proteins Into Families

DEFF Research Database (Denmark)

Wiwie, Christian; Röttger, Richard

2017-01-01

Over the last decades, we have observed an ongoing tremendous growth of available sequencing data fueled by the advancements in wet-lab technology. The sequencing information is only the beginning of the actual understanding of how organisms survive and prosper. It is, for instance, equally...... important to also unravel the proteomic repertoire of an organism. A classical computational approach for detecting protein families is a sequence-based similarity calculation coupled with a subsequent cluster analysis. In this work we have intensively analyzed various clustering tools on a large scale. We...... used the data to investigate the behavior of the tools' parameters underlining the diversity of the protein families. Furthermore, we trained regression models for predicting the expected performance of a clustering tool for an unknown data set and aimed to also suggest optimal parameters...

Cloning, sequencing, and expression of dnaK-operon proteins from the thermophilic bacterium Thermus thermophilus.

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Osipiuk, J; Joachimiak, A

1997-09-12

We propose that the dnaK operon of Thermus thermophilus HB8 is composed of three functionally linked genes: dnaK, grpE, and dnaJ. The dnaK and dnaJ gene products are most closely related to their cyanobacterial homologs. The DnaK protein sequence places T. thermophilus in the plastid Hsp70 subfamily. In contrast, the grpE translated sequence is most similar to GrpE from Clostridium acetobutylicum, a Gram-positive anaerobic bacterium. A single promoter region, with homology to the Escherichia coli consensus promoter sequences recognized by the sigma70 and sigma32 transcription factors, precedes the postulated operon. This promoter is heat-shock inducible. The dnaK mRNA level increased more than 30 times upon 10 min of heat shock (from 70 degrees C to 85 degrees C). A strong transcription terminating sequence was found between the dnaK and grpE genes. The individual genes were cloned into pET expression vectors and the thermophilic proteins were overproduced at high levels in E. coli and purified to homogeneity. The recombinant T. thermophilus DnaK protein was shown to have a weak ATP-hydrolytic activity, with an optimum at 90 degrees C. The ATPase was stimulated by the presence of GrpE and DnaJ. Another open reading frame, coding for ClpB heat-shock protein, was found downstream of the dnaK operon.

An expressed sequence tag (EST) data mining strategy succeeding in the discovery of new G-protein coupled receptors.

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Wittenberger, T; Schaller, H C; Hellebrand, S

2001-03-30

We have developed a comprehensive expressed sequence tag database search method and used it for the identification of new members of the G-protein coupled receptor superfamily. Our approach proved to be especially useful for the detection of expressed sequence tag sequences that do not encode conserved parts of a protein, making it an ideal tool for the identification of members of divergent protein families or of protein parts without conserved domain structures in the expressed sequence tag database. At least 14 of the expressed sequence tags found with this strategy are promising candidates for new putative G-protein coupled receptors. Here, we describe the sequence and expression analysis of five new members of this receptor superfamily, namely GPR84, GPR86, GPR87, GPR90 and GPR91. We also studied the genomic structure and chromosomal localization of the respective genes applying in silico methods. A cluster of six closely related G-protein coupled receptors was found on the human chromosome 3q24-3q25. It consists of four orphan receptors (GPR86, GPR87, GPR91, and H963), the purinergic receptor P2Y1, and the uridine 5'-diphosphoglucose receptor KIAA0001. It seems likely that these receptors evolved from a common ancestor and therefore might have related ligands. In conclusion, we describe a data mining procedure that proved to be useful for the identification and first characterization of new genes and is well applicable for other gene families. Copyright 2001 Academic Press.

Sequence and conformational preferences at termini of α-helices in membrane proteins: role of the helix environment.

Science.gov (United States)

Shelar, Ashish; Bansal, Manju

2014-12-01

α-Helices are amongst the most common secondary structural elements seen in membrane proteins and are packed in the form of helix bundles. These α-helices encounter varying external environments (hydrophobic, hydrophilic) that may influence the sequence preferences at their N and C-termini. The role of the external environment in stabilization of the helix termini in membrane proteins is still unknown. Here we analyze α-helices in a high-resolution dataset of integral α-helical membrane proteins and establish that their sequence and conformational preferences differ from those in globular proteins. We specifically examine these preferences at the N and C-termini in helices initiating/terminating inside the membrane core as well as in linkers connecting these transmembrane helices. We find that the sequence preferences and structural motifs at capping (Ncap and Ccap) and near-helical (N' and C') positions are influenced by a combination of features including the membrane environment and the innate helix initiation and termination property of residues forming structural motifs. We also find that a large number of helix termini which do not form any particular capping motif are stabilized by formation of hydrogen bonds and hydrophobic interactions contributed from the neighboring helices in the membrane protein. We further validate the sequence preferences obtained from our analysis with data from an ultradeep sequencing study that identifies evolutionarily conserved amino acids in the rat neurotensin receptor. The results from our analysis provide insights for the secondary structure prediction, modeling and design of membrane proteins. © 2014 Wiley Periodicals, Inc.

The Number, Organization, and Size of Polymorphic Membrane Protein Coding Sequences as well as the Most Conserved Pmp Protein Differ within and across Chlamydia Species.

Science.gov (United States)

Van Lent, Sarah; Creasy, Heather Huot; Myers, Garry S A; Vanrompay, Daisy

2016-01-01

Variation is a central trait of the polymorphic membrane protein (Pmp) family. The number of pmp coding sequences differs between Chlamydia species, but it is unknown whether the number of pmp coding sequences is constant within a Chlamydia species. The level of conservation of the Pmp proteins has previously only been determined for Chlamydia trachomatis. As different Pmp proteins might be indispensible for the pathogenesis of different Chlamydia species, this study investigated the conservation of Pmp proteins both within and across C. trachomatis,C. pneumoniae,C. abortus, and C. psittaci. The pmp coding sequences were annotated in 16 C. trachomatis, 6 C. pneumoniae, 2 C. abortus, and 16 C. psittaci genomes. The number and organization of polymorphic membrane coding sequences differed within and across the analyzed Chlamydia species. The length of coding sequences of pmpA,pmpB, and pmpH was conserved among all analyzed genomes, while the length of pmpE/F and pmpG, and remarkably also of the subtype pmpD, differed among the analyzed genomes. PmpD, PmpA, PmpH, and PmpA were the most conserved Pmp in C. trachomatis,C. pneumoniae,C. abortus, and C. psittaci, respectively. PmpB was the most conserved Pmp across the 4 analyzed Chlamydia species. © 2016 S. Karger AG, Basel.

ProtDCal: A program to compute general-purpose-numerical descriptors for sequences and 3D-structures of proteins.

Science.gov (United States)

Ruiz-Blanco, Yasser B; Paz, Waldo; Green, James; Marrero-Ponce, Yovani

2015-05-16

The exponential growth of protein structural and sequence databases is enabling multifaceted approaches to understanding the long sought sequence-structure-function relationship. Advances in computation now make it possible to apply well-established data mining and pattern recognition techniques to these data to learn models that effectively relate structure and function. However, extracting meaningful numerical descriptors of protein sequence and structure is a key issue that requires an efficient and widely available solution. We here introduce ProtDCal, a new computational software suite capable of generating tens of thousands of features considering both sequence-based and 3D-structural descriptors. We demonstrate, by means of principle component analysis and Shannon entropy tests, how ProtDCal's sequence-based descriptors provide new and more relevant information not encoded by currently available servers for sequence-based protein feature generation. The wide diversity of the 3D-structure-based features generated by ProtDCal is shown to provide additional complementary information and effectively completes its general protein encoding capability. As demonstration of the utility of ProtDCal's features, prediction models of N-linked glycosylation sites are trained and evaluated. Classification performance compares favourably with that of contemporary predictors of N-linked glycosylation sites, in spite of not using domain-specific features as input information. ProtDCal provides a friendly and cross-platform graphical user interface, developed in the Java programming language and is freely available at: http://bioinf.sce.carleton.ca/ProtDCal/ . ProtDCal introduces local and group-based encoding which enhances the diversity of the information captured by the computed features. Furthermore, we have shown that adding structure-based descriptors contributes non-redundant additional information to the features-based characterization of polypeptide systems. This

Modeling compositional dynamics based on GC and purine contents of protein-coding sequences

KAUST Repository

Zhang, Zhang

2010-11-08

Background: Understanding the compositional dynamics of genomes and their coding sequences is of great significance in gaining clues into molecular evolution and a large number of publically-available genome sequences have allowed us to quantitatively predict deviations of empirical data from their theoretical counterparts. However, the quantification of theoretical compositional variations for a wide diversity of genomes remains a major challenge.Results: To model the compositional dynamics of protein-coding sequences, we propose two simple models that take into account both mutation and selection effects, which act differently at the three codon positions, and use both GC and purine contents as compositional parameters. The two models concern the theoretical composition of nucleotides, codons, and amino acids, with no prerequisite of homologous sequences or their alignments. We evaluated the two models by quantifying theoretical compositions of a large collection of protein-coding sequences (including 46 of Archaea, 686 of Bacteria, and 826 of Eukarya), yielding consistent theoretical compositions across all the collected sequences.Conclusions: We show that the compositions of nucleotides, codons, and amino acids are largely determined by both GC and purine contents and suggest that deviations of the observed from the expected compositions may reflect compositional signatures that arise from a complex interplay between mutation and selection via DNA replication and repair mechanisms.Reviewers: This article was reviewed by Zhaolei Zhang (nominated by Mark Gerstein), Guruprasad Ananda (nominated by Kateryna Makova), and Daniel Haft. 2010 Zhang and Yu; licensee BioMed Central Ltd.

Modeling compositional dynamics based on GC and purine contents of protein-coding sequences

KAUST Repository

Zhang, Zhang; Yu, Jun

2010-01-01

Background: Understanding the compositional dynamics of genomes and their coding sequences is of great significance in gaining clues into molecular evolution and a large number of publically-available genome sequences have allowed us to quantitatively predict deviations of empirical data from their theoretical counterparts. However, the quantification of theoretical compositional variations for a wide diversity of genomes remains a major challenge.Results: To model the compositional dynamics of protein-coding sequences, we propose two simple models that take into account both mutation and selection effects, which act differently at the three codon positions, and use both GC and purine contents as compositional parameters. The two models concern the theoretical composition of nucleotides, codons, and amino acids, with no prerequisite of homologous sequences or their alignments. We evaluated the two models by quantifying theoretical compositions of a large collection of protein-coding sequences (including 46 of Archaea, 686 of Bacteria, and 826 of Eukarya), yielding consistent theoretical compositions across all the collected sequences.Conclusions: We show that the compositions of nucleotides, codons, and amino acids are largely determined by both GC and purine contents and suggest that deviations of the observed from the expected compositions may reflect compositional signatures that arise from a complex interplay between mutation and selection via DNA replication and repair mechanisms.Reviewers: This article was reviewed by Zhaolei Zhang (nominated by Mark Gerstein), Guruprasad Ananda (nominated by Kateryna Makova), and Daniel Haft. 2010 Zhang and Yu; licensee BioMed Central Ltd.

An alignment-free method to find similarity among protein sequences via the general form of Chou's pseudo amino acid composition.

Science.gov (United States)

Gupta, M K; Niyogi, R; Misra, M

2013-01-01

In this paper, we propose a method to create the 60-dimensional feature vector for protein sequences via the general form of pseudo amino acid composition. The construction of the feature vector is based on the contents of amino acids, total distance of each amino acid from the first amino acid in the protein sequence and the distribution of 20 amino acids. The obtained cosine distance metric (also called the similarity matrix) is used to construct the phylogenetic tree by the neighbour joining method. In order to show the applicability of our approach, we tested it on three proteins: 1) ND5 protein sequences from nine species, 2) ND6 protein sequences from eight species, and 3) 50 coronavirus spike proteins. The results are in agreement with known history and the output from the multiple sequence alignment program ClustalW, which is widely used. We have also compared our phylogenetic results with six other recently proposed alignment-free methods. These comparisons show that our proposed method gives a more consistent biological relationship than the others. In addition, the time complexity is linear and space required is less as compared with other alignment-free methods that use graphical representation. It should be noted that the multiple sequence alignment method has exponential time complexity.

Analyzing Plasmodium falciparum erythrocyte membrane protein 1 gene expression by a next generation sequencing based method

DEFF Research Database (Denmark)

Jespersen, Jakob S.; Petersen, Bent; Seguin-Orlando, Andaine

2013-01-01

at identifying PfEMP1 features associated with high virulence. Here we present the first effective method for sequence analysis of var genes expressed in field samples: a sequential PCR and next generation sequencing based technique applied on expressed var sequence tags and subsequently on long range PCR......, encoded by ~60 highly variable 'var' genes per haploid genome. PfEMP1 is exported to the surface of infected erythrocytes and is thought to be fundamental to immune evasion by adhesion to host and parasite factors. The highly variable nature has constituted a roadblock in var expression studies aimed...

An intuitive graphical webserver for multiple-choice protein sequence search.

Science.gov (United States)

Banky, Daniel; Szalkai, Balazs; Grolmusz, Vince

2014-04-10

Every day tens of thousands of sequence searches and sequence alignment queries are submitted to webservers. The capitalized word "BLAST" becomes a verb, describing the act of performing sequence search and alignment. However, if one needs to search for sequences that contain, for example, two hydrophobic and three polar residues at five given positions, the query formation on the most frequently used webservers will be difficult. Some servers support the formation of queries with regular expressions, but most of the users are unfamiliar with their syntax. Here we present an intuitive, easily applicable webserver, the Protein Sequence Analysis server, that allows the formation of multiple choice queries by simply drawing the residues to their positions; if more than one residue are drawn to the same position, then they will be nicely stacked on the user interface, indicating the multiple choice at the given position. This computer-game-like interface is natural and intuitive, and the coloring of the residues makes possible to form queries requiring not just certain amino acids in the given positions, but also small nonpolar, negatively charged, hydrophobic, positively charged, or polar ones. The webserver is available at http://psa.pitgroup.org. Copyright © 2014 Elsevier B.V. All rights reserved.

MIToS.jl: mutual information tools for protein sequence analysis in the Julia language

DEFF Research Database (Denmark)

Zea, Diego J.; Anfossi, Diego; Nielsen, Morten

2017-01-01

Motivation: MIToS is an environment for mutual information analysis and a framework for protein multiple sequence alignments (MSAs) and protein structures (PDB) management in Julia language. It integrates sequence and structural information through SIFTS, making Pfam MSAs analysis straightforward....... MIToS streamlines the implementation of any measure calculated from residue contingency tables and its optimization and testing in terms of protein contact prediction. As an example, we implemented and tested a BLOSUM62-based pseudo-count strategy in mutual information analysis. Availability...... and Implementation: The software is totally implemented in Julia and supported for Linux, OS X and Windows. It’s freely available on GitHub under MIT license: http://mitos.leloir.org.ar. Contacts:diegozea@gmail.com or cmb@leloir.org.ar Supplementary information: Supplementary data are available at Bioinformatics...

Nucleotide sequence of Phaseolus vulgaris L. alcohol dehydrogenase encoding cDNA and three-dimensional structure prediction of the deduced protein.

Science.gov (United States)

Amelia, Kassim; Khor, Chin Yin; Shah, Farida Habib; Bhore, Subhash J

2015-01-01

Common beans (Phaseolus vulgaris L.) are widely consumed as a source of proteins and natural products. However, its yield needs to be increased. In line with the agenda of Phaseomics (an international consortium), work of expressed sequence tags (ESTs) generation from bean pods was initiated. Altogether, 5972 ESTs have been isolated. Alcohol dehydrogenase (AD) encoding gene cDNA was a noticeable transcript among the generated ESTs. This AD is an important enzyme; therefore, to understand more about it this study was undertaken. The objective of this study was to elucidate P. vulgaris L. AD (PvAD) gene cDNA sequence and to predict the three-dimensional (3D) structure of deduced protein. positive and negative strands of the PvAD cDNA clone were sequenced using M13 forward and M13 reverse primers to elucidate the nucleotide sequence. Deduced PvAD cDNA and protein sequence was analyzed for their basic features using online bioinformatics tools. Sequence comparison was carried out using bl2seq program, and tree-view program was used to construct a phylogenetic tree. The secondary structures and 3D structure of PvAD protein were predicted by using the PHYRE automatic fold recognition server. The sequencing results analysis showed that PvAD cDNA is 1294 bp in length. It's open reading frame encodes for a protein that contains 371 amino acids. Deduced protein sequence analysis showed the presence of putative substrate binding, catalytic Zn binding, and NAD binding sites. Results indicate that the predicted 3D structure of PvAD protein is analogous to the experimentally determined crystal structure of s-nitrosoglutathione reductase from an Arabidopsis species. The 1294 bp long PvAD cDNA encodes for 371 amino acid long protein that contains conserved domains required for biological functions of AD. The predicted deduced PvAD protein's 3D structure reflects the analogy with the crystal structure of Arabidopsis thaliana s-nitrosoglutathione reductase. Further study is required

Middle Pleistocene protein sequences from the rhinoceros genus Stephanorhinus and the phylogeny of extant and extinct Middle/Late Pleistocene Rhinocerotidae.

Science.gov (United States)

Welker, Frido; Smith, Geoff M; Hutson, Jarod M; Kindler, Lutz; Garcia-Moreno, Alejandro; Villaluenga, Aritza; Turner, Elaine; Gaudzinski-Windheuser, Sabine

2017-01-01

Ancient protein sequences are increasingly used to elucidate the phylogenetic relationships between extinct and extant mammalian taxa. Here, we apply these recent developments to Middle Pleistocene bone specimens of the rhinoceros genus Stephanorhinus . No biomolecular sequence data is currently available for this genus, leaving phylogenetic hypotheses on its evolutionary relationships to extant and extinct rhinoceroses untested. Furthermore, recent phylogenies based on Rhinocerotidae (partial or complete) mitochondrial DNA sequences differ in the placement of the Sumatran rhinoceros ( Dicerorhinus sumatrensis ). Therefore, studies utilising ancient protein sequences from Middle Pleistocene contexts have the potential to provide further insights into the phylogenetic relationships between extant and extinct species, including Stephanorhinus and Dicerorhinus . ZooMS screening (zooarchaeology by mass spectrometry) was performed on several Late and Middle Pleistocene specimens from the genus Stephanorhinus , subsequently followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) to obtain ancient protein sequences from a Middle Pleistocene Stephanorhinus specimen. We performed parallel analysis on a Late Pleistocene woolly rhinoceros specimen and extant species of rhinoceroses, resulting in the availability of protein sequence data for five extant species and two extinct genera. Phylogenetic analysis additionally included all extant Perissodactyla genera ( Equus , Tapirus ), and was conducted using Bayesian (MrBayes) and maximum-likelihood (RAxML) methods. Various ancient proteins were identified in both the Middle and Late Pleistocene rhinoceros samples. Protein degradation and proteome complexity are consistent with an endogenous origin of the identified proteins. Phylogenetic analysis of informative proteins resolved the Perissodactyla phylogeny in agreement with previous studies in regards to the placement of the families Equidae, Tapiridae, and

Oral treponeme major surface protein: Sequence diversity and distributions within periodontal niches.

Science.gov (United States)

You, M; Chan, Y; Lacap-Bugler, D C; Huo, Y-B; Gao, W; Leung, W K; Watt, R M

2017-12-01

Treponema denticola and other species (phylotypes) of oral spirochetes are widely considered to play important etiological roles in periodontitis and other oral infections. The major surface protein (Msp) of T. denticola is directly implicated in several pathological mechanisms. Here, we have analyzed msp sequence diversity across 68 strains of oral phylogroup 1 and 2 treponemes; including reference strains of T. denticola, Treponema putidum, Treponema medium, 'Treponema vincentii', and 'Treponema sinensis'. All encoded Msp proteins contained highly conserved, taxon-specific signal peptides, and shared a predicted 'three-domain' structure. A clone-based strategy employing 'msp-specific' polymerase chain reaction primers was used to analyze msp gene sequence diversity present in subgingival plaque samples collected from a group of individuals with chronic periodontitis (n=10), vs periodontitis-free controls (n=10). We obtained 626 clinical msp gene sequences, which were assigned to 21 distinct 'clinical msp genotypes' (95% sequence identity cut-off). The most frequently detected clinical msp genotype corresponded to T. denticola ATCC 35405 T , but this was not correlated to disease status. UniFrac and libshuff analysis revealed that individuals with periodontitis and periodontitis-free controls harbored significantly different communities of treponeme clinical msp genotypes (Pdiversity than periodontitis-free controls (Mann-Whitney U-test, Pdiversity of Treponema clinical msp genotypes within their subgingival niches. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Proteomic studies related to genetic determinants of variability in protein concentrations

NARCIS (Netherlands)

Horvatovich, Peter; Franke, Lude; Bischoff, Rainer

2014-01-01

Genetic variation has multiple effects on the proteome. It may influence the expression level of proteins, modify their sequences through single nucleotide polymorphisms, the occurrence of allelic variants, or alternative splicing (ASP) events. This perspective paper summarizes the major effects of

Parameters of proteome evolution from histograms of amino-acid sequence identities of paralogous proteins

Directory of Open Access Journals (Sweden)

Yan Koon-Kiu

2007-11-01

Full Text Available Abstract Background The evolution of the full repertoire of proteins encoded in a given genome is mostly driven by gene duplications, deletions, and sequence modifications of existing proteins. Indirect information about relative rates and other intrinsic parameters of these three basic processes is contained in the proteome-wide distribution of sequence identities of pairs of paralogous proteins. Results We introduce a simple mathematical framework based on a stochastic birth-and-death model that allows one to extract some of this information and apply it to the set of all pairs of paralogous proteins in H. pylori, E. coli, S. cerevisiae, C. elegans, D. melanogaster, and H. sapiens. It was found that the histogram of sequence identities p generated by an all-to-all alignment of all protein sequences encoded in a genome is well fitted with a power-law form ~ p-γ with the value of the exponent γ around 4 for the majority of organisms used in this study. This implies that the intra-protein variability of substitution rates is best described by the Gamma-distribution with the exponent α ≈ 0.33. Different features of the shape of such histograms allow us to quantify the ratio between the genome-wide average deletion/duplication rates and the amino-acid substitution rate. Conclusion We separately measure the short-term ("raw" duplication and deletion rates rdup∗ MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGacaGaaiaabeqaaeqabiWaaaGcbaGaemOCai3aa0baaSqaaiabbsgaKjabbwha1jabbchaWbqaaiabgEHiQaaaaaa@3283@, rdel∗ MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGacaGaaiaabeqaaeqabiWaaaGcbaGaemOCai3aa0baaSqaaiabbsga

Amino acid sequences of predicted proteins and their annotation for 95 organism species. - Gclust Server | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us Gclust Server Amino acid sequences of predicted proteins and their annotation for 95 organis...m species. Data detail Data name Amino acid sequences of predicted proteins and their annotation for 95 orga...nism species. DOI 10.18908/lsdba.nbdc00464-001 Description of data contents Amino acid sequences of predicted proteins...Database Description Download License Update History of This Database Site Policy | Contact Us Amino acid sequences of predicted prot...eins and their annotation for 95 organism species. - Gclust Server | LSDB Archive ...

Comparative In silico Study of Sex-Determining Region Y (SRY) Protein Sequences Involved in Sex-Determining.

Science.gov (United States)

Vakili Azghandi, Masoume; Nasiri, Mohammadreza; Shamsa, Ali; Jalali, Mohsen; Shariati, Mohammad Mahdi

2016-04-01

The SRY gene (SRY) provides instructions for making a transcription factor called the sex-determining region Y protein. The sex-determining region Y protein causes a fetus to develop as a male. In this study, SRY of 15 spices included of human, chimpanzee, dog, pig, rat, cattle, buffalo, goat, sheep, horse, zebra, frog, urial, dolphin and killer whale were used for determine of bioinformatic differences. Nucleotide sequences of SRY were retrieved from the NCBI databank. Bioinformatic analysis of SRY is done by CLC Main Workbench version 5.5 and ClustalW (http:/www.ebi.ac.uk/clustalw/) and MEGA6 softwares. The multiple sequence alignment results indicated that SRY protein sequences from Orcinus orca (killer whale) and Tursiopsaduncus (dolphin) have least genetic distance of 0.33 in these 15 species and are 99.67% identical at the amino acid level. Homosapiens and Pantroglodytes (chimpanzee) have the next lowest genetic distance of 1.35 and are 98.65% identical at the amino acid level. These findings indicate that the SRY proteins are conserved in the 15 species, and their evolutionary relationships are similar.

Alignment-free Transcriptomic and Metatranscriptomic Comparison Using Sequencing Signatures with Variable Length Markov Chains.

Science.gov (United States)

Liao, Weinan; Ren, Jie; Wang, Kun; Wang, Shun; Zeng, Feng; Wang, Ying; Sun, Fengzhu

2016-11-23

The comparison between microbial sequencing data is critical to understand the dynamics of microbial communities. The alignment-based tools analyzing metagenomic datasets require reference sequences and read alignments. The available alignment-free dissimilarity approaches model the background sequences with Fixed Order Markov Chain (FOMC) yielding promising results for the comparison of microbial communities. However, in FOMC, the number of parameters grows exponentially with the increase of the order of Markov Chain (MC). Under a fixed high order of MC, the parameters might not be accurately estimated owing to the limitation of sequencing depth. In our study, we investigate an alternative to FOMC to model background sequences with the data-driven Variable Length Markov Chain (VLMC) in metatranscriptomic data. The VLMC originally designed for long sequences was extended to apply to high-throughput sequencing reads and the strategies to estimate the corresponding parameters were developed. The flexible number of parameters in VLMC avoids estimating the vast number of parameters of high-order MC under limited sequencing depth. Different from the manual selection in FOMC, VLMC determines the MC order adaptively. Several beta diversity measures based on VLMC were applied to compare the bacterial RNA-Seq and metatranscriptomic datasets. Experiments show that VLMC outperforms FOMC to model the background sequences in transcriptomic and metatranscriptomic samples. A software pipeline is available at https://d2vlmc.codeplex.com.

Sequence of a cloned cDNA encoding human ribosomal protein S11

Energy Technology Data Exchange (ETDEWEB)

Lott, J B; Mackie, G A

1988-02-11

The authors have isolated a cloned cDNA that encodes human ribosomal protein (rp) S11 by screening a human fibroblast cDNA library with a labelled 204 bp DNA fragment encompassing residues 212-416 of pRS11, a rat rp Sll cDNA clone. The human rp S11 cloned cDNA consists of 15 residues of the 5' leader, the entire coding sequence and all 51 residues of the 3' untranslated region. The predicted amino acid sequence of 158 residues is identical to rat rpS11. The nucleotide sequence in the coding region differs, however, from that in rat in the first position in two codons and in the third position in 44 codons.

An Alignment-Free Algorithm in Comparing the Similarity of Protein Sequences Based on Pseudo-Markov Transition Probabilities among Amino Acids.

Science.gov (United States)

Li, Yushuang; Song, Tian; Yang, Jiasheng; Zhang, Yi; Yang, Jialiang

2016-01-01

In this paper, we have proposed a novel alignment-free method for comparing the similarity of protein sequences. We first encode a protein sequence into a 440 dimensional feature vector consisting of a 400 dimensional Pseudo-Markov transition probability vector among the 20 amino acids, a 20 dimensional content ratio vector, and a 20 dimensional position ratio vector of the amino acids in the sequence. By evaluating the Euclidean distances among the representing vectors, we compare the similarity of protein sequences. We then apply this method into the ND5 dataset consisting of the ND5 protein sequences of 9 species, and the F10 and G11 datasets representing two of the xylanases containing glycoside hydrolase families, i.e., families 10 and 11. As a result, our method achieves a correlation coefficient of 0.962 with the canonical protein sequence aligner ClustalW in the ND5 dataset, much higher than those of other 5 popular alignment-free methods. In addition, we successfully separate the xylanases sequences in the F10 family and the G11 family and illustrate that the F10 family is more heat stable than the G11 family, consistent with a few previous studies. Moreover, we prove mathematically an identity equation involving the Pseudo-Markov transition probability vector and the amino acids content ratio vector.

Amyloid fibril formation from sequences of a natural beta-structured fibrous protein, the adenovirus fiber.

Science.gov (United States)

Papanikolopoulou, Katerina; Schoehn, Guy; Forge, Vincent; Forsyth, V Trevor; Riekel, Christian; Hernandez, Jean-François; Ruigrok, Rob W H; Mitraki, Anna

2005-01-28

Amyloid fibrils are fibrous beta-structures that derive from abnormal folding and assembly of peptides and proteins. Despite a wealth of structural studies on amyloids, the nature of the amyloid structure remains elusive; possible connections to natural, beta-structured fibrous motifs have been suggested. In this work we focus on understanding amyloid structure and formation from sequences of a natural, beta-structured fibrous protein. We show that short peptides (25 to 6 amino acids) corresponding to repetitive sequences from the adenovirus fiber shaft have an intrinsic capacity to form amyloid fibrils as judged by electron microscopy, Congo Red binding, infrared spectroscopy, and x-ray fiber diffraction. In the presence of the globular C-terminal domain of the protein that acts as a trimerization motif, the shaft sequences adopt a triple-stranded, beta-fibrous motif. We discuss the possible structure and arrangement of these sequences within the amyloid fibril, as compared with the one adopted within the native structure. A 6-amino acid peptide, corresponding to the last beta-strand of the shaft, was found to be sufficient to form amyloid fibrils. Structural analysis of these amyloid fibrils suggests that perpendicular stacking of beta-strand repeat units is an underlying common feature of amyloid formation.

Statistical distributions of optimal global alignment scores of random protein sequences

Directory of Open Access Journals (Sweden)

Tang Jiaowei

2005-10-01

Full Text Available Abstract Background The inference of homology from statistically significant sequence similarity is a central issue in sequence alignments. So far the statistical distribution function underlying the optimal global alignments has not been completely determined. Results In this study, random and real but unrelated sequences prepared in six different ways were selected as reference datasets to obtain their respective statistical distributions of global alignment scores. All alignments were carried out with the Needleman-Wunsch algorithm and optimal scores were fitted to the Gumbel, normal and gamma distributions respectively. The three-parameter gamma distribution performs the best as the theoretical distribution function of global alignment scores, as it agrees perfectly well with the distribution of alignment scores. The normal distribution also agrees well with the score distribution frequencies when the shape parameter of the gamma distribution is sufficiently large, for this is the scenario when the normal distribution can be viewed as an approximation of the gamma distribution. Conclusion We have shown that the optimal global alignment scores of random protein sequences fit the three-parameter gamma distribution function. This would be useful for the inference of homology between sequences whose relationship is unknown, through the evaluation of gamma distribution significance between sequences.

Strategies in protein sequencing and characterization: Multi-enzyme digestion coupled with alternate CID/ETD tandem mass spectrometry

Energy Technology Data Exchange (ETDEWEB)

Nardiello, Donatella; Palermo, Carmen, E-mail: carmen.palermo@unifg.it; Natale, Anna; Quinto, Maurizio; Centonze, Diego

2015-01-07

Highlights: • Multi-enzyme digestion for protein sequencing and characterization by CID/ETD. • Simultaneous use of trypsin/chymotrypsin for the maximization of sequence. • Identification of PTMs, sequence variants and species-specific residues. • Increase of accuracy in sequence assignments by orthogonal fragmentation techniques. - Abstract: A strategy based on a simultaneous multi-enzyme digestion coupled with electron transfer dissociation (ETD) and collision-induced dissociation (CID) was developed for protein sequencing and characterization, as a valid alternative platform in ion-trap based proteomics. The effect of different proteolytic procedures using chymotrypsin, trypsin, a combination of both, and Lys-C, was carefully evaluated in terms of number of identified peptides, protein coverage, and score distribution. A systematic comparison between CID and ETD is shown for the analysis of peptides originating from the in-solution digestion of standard caseins. The best results were achieved with a trypsin/chymotrypsin mix combined with CID and ETD operating in alternating mode. A post-database search validation of MS/MS dataset was performed, then, the matched peptides were cross checked by the evaluation of ion scores, rank, number of experimental product ions, and their relative abundances in the MS/MS spectrum. By integrated CID/ETD experiments, high quality-spectra have been obtained, thus allowing a confirmation of spectral information and an increase of accuracy in peptide sequence assignments. Overlapping peptides, produced throughout the proteins, reduce the ambiguity in mapping modifications between natural variants and animal species, and allow the characterization of post translational modifications. The advantages of using the enzymatic mix trypsin/chymotrypsin were confirmed by the nanoLC and CID/ETD tandem mass spectrometry of goat milk proteins, previously separated by two-dimensional gel electrophoresis.

Fast and simple protein-alignment-guided assembly of orthologous gene families from microbiome sequencing reads.

Science.gov (United States)

Huson, Daniel H; Tappu, Rewati; Bazinet, Adam L; Xie, Chao; Cummings, Michael P; Nieselt, Kay; Williams, Rohan

2017-01-25

Microbiome sequencing projects typically collect tens of millions of short reads per sample. Depending on the goals of the project, the short reads can either be subjected to direct sequence analysis or be assembled into longer contigs. The assembly of whole genomes from metagenomic sequencing reads is a very difficult problem. However, for some questions, only specific genes of interest need to be assembled. This is then a gene-centric assembly where the goal is to assemble reads into contigs for a family of orthologous genes. We present a new method for performing gene-centric assembly, called protein-alignment-guided assembly, and provide an implementation in our metagenome analysis tool MEGAN. Genes are assembled on the fly, based on the alignment of all reads against a protein reference database such as NCBI-nr. Specifically, the user selects a gene family based on a classification such as KEGG and all reads binned to that gene family are assembled. Using published synthetic community metagenome sequencing reads and a set of 41 gene families, we show that the performance of this approach compares favorably with that of full-featured assemblers and that of a recently published HMM-based gene-centric assembler, both in terms of the number of reference genes detected and of the percentage of reference sequence covered. Protein-alignment-guided assembly of orthologous gene families complements whole-metagenome assembly in a new and very useful way.

Increased Protein Requirements in Female Athletes after Variable-Intensity Exercise.

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Wooding, Denise J; Packer, Jeff E; Kato, Hiroyuki; West, Daniel W D; Courtney-Martin, Glenda; Pencharz, Paul B; Moore, Daniel R

2017-11-01

Protein requirements are primarily studied in the context of resistance or endurance exercise with little research devoted to variable-intensity intermittent exercise characteristic of many team sports. Further, female populations are underrepresented in dietary sports science studies. We aimed to determine a dietary protein requirement in active females performing variable-intensity intermittent exercise using the indicator amino acid oxidation (IAAO) method. We hypothesized that these requirements would be greater than current IAAO-derived estimates in nonactive adult males. Six females (21.2 ± 0.8 yr, 68.8 ± 4.1 kg, 47.1 ± 1.2 mL O2·kg·min; mean ± SE) completed five to seven metabolic trials during the luteal phase of the menstrual cycle. Participants performed a modified Loughborough Intermittent Shuttle Test before consuming eight hourly mixed meals providing the test protein intake (0.2-2.66 g·kg·d), 6 g·kg·d CHO and sufficient energy for resting and exercise-induced energy expenditure. Protein was provided as crystalline amino acid modeling egg protein with [C]phenylalanine as the indicator amino acid. Phenylalanine turnover (Q) was determined from urinary [C]phenylalanine enrichment. Breath CO2 excretion (FCO2) was analyzed using mixed effects biphase linear regression with the breakpoint and upper 95% confidence interval approximating the estimated average requirement and recommended dietary allowance, respectively. Protein intake had no effect on Q (68.7 ± 7.3 μmol·kg·h; mean ± SE). FCO2 displayed a robust biphase response (R = 0.66) with an estimated average requirement of 1.41 g·kg·d and recommended dietary allowance of 1.71 g·kg·d. The protein requirement estimate of 1.41 and 1.71 g·kg·d for females performing variable-intensity intermittent exercise is greater than the IAAO-derived estimates of adult males (0.93 and 1.2 g·kg·d) and at the upper range of the American College of Sports Medicine athlete recommendations (1.2-2.0 g·kg·d).

Simple sequence proteins in prokaryotic proteomes

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Ramachandran Srinivasan

2006-06-01

Full Text Available Abstract Background The structural and functional features associated with Simple Sequence Proteins (SSPs are non-globularity, disease states, signaling and post-translational modification. SSPs are also an important source of genetic and possibly phenotypic variation. Analysis of 249 prokaryotic proteomes offers a new opportunity to examine the genomic properties of SSPs. Results SSPs are a minority but they grow with proteome size. This relationship is exhibited across species varying in genomic GC, mutational bias, life style, and pathogenicity. Their proportion in each proteome is strongly influenced by genomic base compositional bias. In most species simple duplications is favoured, but in a few cases such as Mycobacteria, large families of duplications occur. Amino acid preference in SSPs exhibits a trend towards low cost of biosynthesis. In SSPs and in non-SSPs, Alanine, Glycine, Leucine, and Valine are abundant in species widely varying in genomic GC whereas Isoleucine and Lysine are rich only in organisms with low genomic GC. Arginine is abundant in SSPs of two species and in the non-SSPs of Xanthomonas oryzae. Asparagine is abundant only in SSPs of low GC species. Aspartic acid is abundant only in the non-SSPs of Halobacterium sp NRC1. The abundance of Serine in SSPs of 62 species extends over a broader range compared to that of non-SSPs. Threonine(T is abundant only in SSPs of a couple of species. SSPs exhibit preferential association with Cell surface, Cell membrane and Transport functions and a negative association with Metabolism. Mesophiles and Thermophiles display similar ranges in the content of SSPs. Conclusion Although SSPs are a minority, the genomic forces of base compositional bias and duplications influence their growth and pattern in each species. The preferences and abundance of amino acids are governed by low biosynthetic cost, evolutionary age and base composition of codons. Abundance of charged amino acids Arginine

In situ detection of a heat-shock regulatory element binding protein using a soluble short synthetic enhancer sequence

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Harel-Bellan, A; Brini, A T; Farrar, W L [National Cancer Institute, Frederick, MD (USA); Ferris, D K [Program Resources, Inc., Frederick, MD (USA); Robin, P [Institut Gustave Roussy, Villejuif (France)

1989-06-12

In various studies, enhancer binding proteins have been successfully absorbed out by competing sequences inserted into plasmids, resulting in the inhibition of the plasmid expression. Theoretically, such a result could be achieved using synthetic enhancer sequences not inserted into plasmids. In this study, a double stranded DNA sequence corresponding to the human heat shock regulatory element was chemically synthesized. By in vitro retardation assays, the synthetic sequence was shown to bind specifically a protein in extracts from the human T cell line Jurkat. When the synthetic enhancer was electroporated into Jurkat cells, not only the enhancer was shown to remain undegraded into the cells for up to 2 days, but also its was shown to bind intracellularly a protein. The binding was specific and was modulated upon heat shock. Furthermore, the binding protein was shown to be of the expected molecular weight by UV crosslinking. However, when the synthetic enhancer element was co-electroporated with an HSP 70-CAT reporter construct, the expression of the reporter plasmid was consistently enhanced in the presence of the exogenous synthetic enhancer.

A protein-tyrosine phosphatase with sequence similarity to the SH2 domain of the protein-tyrosine kinases.

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Shen, S H; Bastien, L; Posner, B I; Chrétien, P

1991-08-22

The phosphorylation of proteins at tyrosine residues is critical in cellular signal transduction, neoplastic transformation and control of the mitotic cycle. These mechanisms are regulated by the activities of both protein-tyrosine kinases (PTKs) and protein-tyrosine phosphatases (PTPases). As in the PTKs, there are two classes of PTPases: membrane associated, receptor-like enzymes and soluble proteins. Here we report the isolation of a complementary DNA clone encoding a new form of soluble PTPase, PTP1C. The enzyme possesses a large noncatalytic region at the N terminus which unexpectedly contains two adjacent copies of the Src homology region 2 (the SH2 domain) found in various nonreceptor PTKs and other cytoplasmic signalling proteins. As with other SH2 sequences, the SH2 domains of PTP1C formed high-affinity complexes with the activated epidermal growth factor receptor and other phosphotyrosine-containing proteins. These results suggest that the SH2 regions in PTP1C may interact with other cellular components to modulate its own phosphatase activity against interacting substrates. PTPase activity may thus directly link growth factor receptors and other signalling proteins through protein-tyrosine phosphorylation.

Electrophoretic mobility shift assay reveals a novel recognition sequence for Setaria italica NAC protein.

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Puranik, Swati; Kumar, Karunesh; Srivastava, Prem S; Prasad, Manoj

2011-10-01

The NAC (NAM/ATAF1,2/CUC2) proteins are among the largest family of plant transcription factors. Its members have been associated with diverse plant processes and intricately regulate the expression of several genes. Inspite of this immense progress, knowledge of their DNA-binding properties are still limited. In our recent publication,1 we reported isolation of a membrane-associated NAC domain protein from Setaria italica (SiNAC). Transactivation analysis revealed that it was a functionally active transcription factor as it could stimulate expression of reporter genes in vivo. Truncations of the transmembrane region of the protein lead to its nuclear localization. Here we describe expression and purification of SiNAC DNA-binding domain. We further report identification of a novel DNA-binding site, [C/G][A/T][T/A][G/C]TC[C/G][A/T][C/G][G/C] for SiNAC by electrophoretic mobility shift assay. The SiNAC-GST protein could bind to the NAC recognition sequence in vitro as well as to sequences where some bases had been reshuffled. The results presented here contribute to our understanding of the DNA-binding specificity of SiNAC protein.

Surface display of a massively variable lipoprotein by a Legionella diversity-generating retroelement.

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Arambula, Diego; Wong, Wenge; Medhekar, Bob A; Guo, Huatao; Gingery, Mari; Czornyj, Elizabeth; Liu, Minghsun; Dey, Sanghamitra; Ghosh, Partho; Miller, Jeff F

2013-05-14

Diversity-generating retroelements (DGRs) are a unique family of retroelements that confer selective advantages to their hosts by facilitating localized DNA sequence evolution through a specialized error-prone reverse transcription process. We characterized a DGR in Legionella pneumophila, an opportunistic human pathogen that causes Legionnaires disease. The L. pneumophila DGR is found within a horizontally acquired genomic island, and it can theoretically generate 10(26) unique nucleotide sequences in its target gene, legionella determinent target A (ldtA), creating a repertoire of 10(19) distinct proteins. Expression of the L. pneumophila DGR resulted in transfer of DNA sequence information from a template repeat to a variable repeat (VR) accompanied by adenine-specific mutagenesis of progeny VRs at the 3'end of ldtA. ldtA encodes a twin-arginine translocated lipoprotein that is anchored in the outer leaflet of the outer membrane, with its C-terminal variable region surface exposed. Related DGRs were identified in L. pneumophila clinical isolates that encode unique target proteins with homologous VRs, demonstrating the adaptability of DGR components. This work characterizes a DGR that diversifies a bacterial protein and confirms the hypothesis that DGR-mediated mutagenic homing occurs through a conserved mechanism. Comparative bioinformatics predicts that surface display of massively variable proteins is a defining feature of a subset of bacterial DGRs.

Camps 2.0: exploring the sequence and structure space of prokaryotic, eukaryotic, and viral membrane proteins.

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Neumann, Sindy; Hartmann, Holger; Martin-Galiano, Antonio J; Fuchs, Angelika; Frishman, Dmitrij

2012-03-01

Structural bioinformatics of membrane proteins is still in its infancy, and the picture of their fold space is only beginning to emerge. Because only a handful of three-dimensional structures are available, sequence comparison and structure prediction remain the main tools for investigating sequence-structure relationships in membrane protein families. Here we present a comprehensive analysis of the structural families corresponding to α-helical membrane proteins with at least three transmembrane helices. The new version of our CAMPS database (CAMPS 2.0) covers nearly 1300 eukaryotic, prokaryotic, and viral genomes. Using an advanced classification procedure, which is based on high-order hidden Markov models and considers both sequence similarity as well as the number of transmembrane helices and loop lengths, we identified 1353 structurally homogeneous clusters roughly corresponding to membrane protein folds. Only 53 clusters are associated with experimentally determined three-dimensional structures, and for these clusters CAMPS is in reasonable agreement with structure-based classification approaches such as SCOP and CATH. We therefore estimate that ∼1300 structures would need to be determined to provide a sufficient structural coverage of polytopic membrane proteins. CAMPS 2.0 is available at http://webclu.bio.wzw.tum.de/CAMPS2.0/. Copyright © 2011 Wiley Periodicals, Inc.

GenProBiS: web server for mapping of sequence variants to protein binding sites.

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Konc, Janez; Skrlj, Blaz; Erzen, Nika; Kunej, Tanja; Janezic, Dusanka

2017-07-03

Discovery of potentially deleterious sequence variants is important and has wide implications for research and generation of new hypotheses in human and veterinary medicine, and drug discovery. The GenProBiS web server maps sequence variants to protein structures from the Protein Data Bank (PDB), and further to protein-protein, protein-nucleic acid, protein-compound, and protein-metal ion binding sites. The concept of a protein-compound binding site is understood in the broadest sense, which includes glycosylation and other post-translational modification sites. Binding sites were defined by local structural comparisons of whole protein structures using the Protein Binding Sites (ProBiS) algorithm and transposition of ligands from the similar binding sites found to the query protein using the ProBiS-ligands approach with new improvements introduced in GenProBiS. Binding site surfaces were generated as three-dimensional grids encompassing the space occupied by predicted ligands. The server allows intuitive visual exploration of comprehensively mapped variants, such as human somatic mis-sense mutations related to cancer and non-synonymous single nucleotide polymorphisms from 21 species, within the predicted binding sites regions for about 80 000 PDB protein structures using fast WebGL graphics. The GenProBiS web server is open and free to all users at http://genprobis.insilab.org. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

UFO: a web server for ultra-fast functional profiling of whole genome protein sequences.

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Meinicke, Peter

2009-09-02

Functional profiling is a key technique to characterize and compare the functional potential of entire genomes. The estimation of profiles according to an assignment of sequences to functional categories is a computationally expensive task because it requires the comparison of all protein sequences from a genome with a usually large database of annotated sequences or sequence families. Based on machine learning techniques for Pfam domain detection, the UFO web server for ultra-fast functional profiling allows researchers to process large protein sequence collections instantaneously. Besides the frequencies of Pfam and GO categories, the user also obtains the sequence specific assignments to Pfam domain families. In addition, a comparison with existing genomes provides dissimilarity scores with respect to 821 reference proteomes. Considering the underlying UFO domain detection, the results on 206 test genomes indicate a high sensitivity of the approach. In comparison with current state-of-the-art HMMs, the runtime measurements show a considerable speed up in the range of four orders of magnitude. For an average size prokaryotic genome, the computation of a functional profile together with its comparison typically requires about 10 seconds of processing time. For the first time the UFO web server makes it possible to get a quick overview on the functional inventory of newly sequenced organisms. The genome scale comparison with a large number of precomputed profiles allows a first guess about functionally related organisms. The service is freely available and does not require user registration or specification of a valid email address.

UFO: a web server for ultra-fast functional profiling of whole genome protein sequences

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Meinicke Peter

2009-09-01

Full Text Available Abstract Background Functional profiling is a key technique to characterize and compare the functional potential of entire genomes. The estimation of profiles according to an assignment of sequences to functional categories is a computationally expensive task because it requires the comparison of all protein sequences from a genome with a usually large database of annotated sequences or sequence families. Description Based on machine learning techniques for Pfam domain detection, the UFO web server for ultra-fast functional profiling allows researchers to process large protein sequence collections instantaneously. Besides the frequencies of Pfam and GO categories, the user also obtains the sequence specific assignments to Pfam domain families. In addition, a comparison with existing genomes provides dissimilarity scores with respect to 821 reference proteomes. Considering the underlying UFO domain detection, the results on 206 test genomes indicate a high sensitivity of the approach. In comparison with current state-of-the-art HMMs, the runtime measurements show a considerable speed up in the range of four orders of magnitude. For an average size prokaryotic genome, the computation of a functional profile together with its comparison typically requires about 10 seconds of processing time. Conclusion For the first time the UFO web server makes it possible to get a quick overview on the functional inventory of newly sequenced organisms. The genome scale comparison with a large number of precomputed profiles allows a first guess about functionally related organisms. The service is freely available and does not require user registration or specification of a valid email address.

Cluster based on sequence comparison of homologous proteins of 95 organism species - Gclust Server | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us Gclust Server Cluster based on sequence comparison of homologous proteins of 95 organism spe...cies Data detail Data name Cluster based on sequence comparison of homologous proteins of 95 organism specie...istory of This Database Site Policy | Contact Us Cluster based on sequence compariso

Highly conserved intragenic HSV-2 sequences: Results from next-generation sequencing of HSV-2 UL and US regions from genital swabs collected from 3 continents.

Science.gov (United States)

Johnston, Christine; Magaret, Amalia; Roychoudhury, Pavitra; Greninger, Alexander L; Cheng, Anqi; Diem, Kurt; Fitzgibbon, Matthew P; Huang, Meei-Li; Selke, Stacy; Lingappa, Jairam R; Celum, Connie; Jerome, Keith R; Wald, Anna; Koelle, David M

2017-10-01

Understanding the variability in circulating herpes simplex virus type 2 (HSV-2) genomic sequences is critical to the development of HSV-2 vaccines. Genital lesion swabs containing ≥ 10 7 log 10 copies HSV DNA collected from Africa, the USA, and South America underwent next-generation sequencing, followed by K-mer based filtering and de novo genomic assembly. Sites of heterogeneity within coding regions in unique long and unique short (U L _U S ) regions were identified. Phylogenetic trees were created using maximum likelihood reconstruction. Among 46 samples from 38 persons, 1468 intragenic base-pair substitutions were identified. The maximum nucleotide distance between strains for concatenated U L_ U S segments was 0.4%. Phylogeny did not reveal geographic clustering. The most variable proteins had non-synonymous mutations in < 3% of amino acids. Unenriched HSV-2 DNA can undergo next-generation sequencing to identify intragenic variability. The use of clinical swabs for sequencing expands the information that can be gathered directly from these specimens. Copyright © 2017 Elsevier Inc. All rights reserved.

Accessible surface area of proteins from purely sequence information and the importance of global features

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Faraggi, Eshel; Zhou, Yaoqi; Kloczkowski, Andrzej

2014-03-01

We present a new approach for predicting the accessible surface area of proteins. The novelty of this approach lies in not using residue mutation profiles generated by multiple sequence alignments as descriptive inputs. Rather, sequential window information and the global monomer and dimer compositions of the chain are used. We find that much of the lost accuracy due to the elimination of evolutionary information is recouped by the use of global features. Furthermore, this new predictor produces similar results for proteins with or without sequence homologs deposited in the Protein Data Bank, and hence shows generalizability. Finally, these predictions are obtained in a small fraction (1/1000) of the time required to run mutation profile based prediction. All these factors indicate the possible usability of this work in de-novo protein structure prediction and in de-novo protein design using iterative searches. Funded in part by the financial support of the National Institutes of Health through Grants R01GM072014 and R01GM073095, and the National Science Foundation through Grant NSF MCB 1071785.

Complete amino acid sequences of the ribosomal proteins L25, L29 and L31 from the archaebacterium Halobacterium marismortui.

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Hatakeyama, T; Kimura, M

1988-03-15

Ribosomal proteins were extracted from 50S ribosomal subunits of the archaebacterium Halobacterium marismortui by decreasing the concentration of Mg2+ and K+, and the proteins were separated and purified by ion-exchange column chromatography on DEAE-cellulose. Ten proteins were purified to homogeneity and three of these proteins were subjected to sequence analysis. The complete amino acid sequences of the ribosomal proteins L25, L29 and L31 were established by analyses of the peptides obtained by enzymatic digestion with trypsin, Staphylococcus aureus protease, chymotrypsin and lysylendopeptidase. Proteins L25, L29 and L31 consist of 84, 115 and 95 amino acid residues with the molecular masses of 9472 Da, 12293 Da and 10418 Da respectively. A comparison of their sequences with those of other large-ribosomal-subunit proteins from other organisms revealed that protein L25 from H. marismortui is homologous to protein L23 from Escherichia coli (34.6%), Bacillus stearothermophilus (41.8%), and tobacco chloroplasts (16.3%) as well as to protein L25 from yeast (38.0%). Proteins L29 and L31 do not appear to be homologous to any other ribosomal proteins whose structures are so far known.

Length and sequence dependence in the association of Huntingtin protein with lipid membranes

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Jawahery, Sudi; Nagarajan, Anu; Matysiak, Silvina

2013-03-01

There is a fundamental gap in our understanding of how aggregates of mutant Huntingtin protein (htt) with overextended polyglutamine (polyQ) sequences gain the toxic properties that cause Huntington's disease (HD). Experimental studies have shown that the most important step associated with toxicity is the binding of mutant htt aggregates to lipid membranes. Studies have also shown that flanking amino acid sequences around the polyQ sequence directly affect interactions with the lipid bilayer, and that polyQ sequences of greater than 35 glutamine repeats in htt are a characteristic of HD. The key steps that determine how flanking sequences and polyQ length affect the structure of lipid bilayers remain unknown. In this study, we use atomistic molecular dynamics simulations to study the interactions between lipid membranes of varying compositions and polyQ peptides of varying lengths and flanking sequences. We find that overextended polyQ interactions do cause deformation in model membranes, and that the flanking sequences do play a role in intensifying this deformation by altering the shape of the affected regions.

Comparative In silico Study of Sex-Determining Region Y (SRY Protein Sequences Involved in Sex-Determining

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Masoume Vakili Azghandi

2016-05-01

Full Text Available Background: The SRY gene (SRY provides instructions for making a transcription factor called the sex-determining region Y protein. The sex-determining region Y protein causes a fetus to develop as a male. In this study, SRY of 15 spices included of human, chimpanzee, dog, pig, rat, cattle, buffalo, goat, sheep, horse, zebra, frog, urial, dolphin and killer whale were used for determine of bioinformatic differences. Methods: Nucleotide sequences of SRY were retrieved from the NCBI databank. Bioinformatic analysis of SRY is done by CLC Main Workbench version 5.5 and ClustalW (http:/www.ebi.ac.uk/clustalw/ and MEGA6 softwares. Results: The multiple sequence alignment results indicated that SRY protein sequences from Orcinus orca (killer whale and Tursiopsaduncus (dolphin have least genetic distance of 0.33 in these 15 species and are 99.67% identical at the amino acid level. Homosapiens and Pantroglodytes (chimpanzee have the next lowest genetic distance of 1.35 and are 98.65% identical at the amino acid level. Conclusion: These findings indicate that the SRY proteins are conserved in the 15 species, and their evolutionary relationships are similar.

C-terminal sequences of hsp70 and hsp90 as non-specific anchors for tetratricopeptide repeat (TPR) proteins.

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Ramsey, Andrew J; Russell, Lance C; Chinkers, Michael

2009-10-12

Steroid-hormone-receptor maturation is a multi-step process that involves several TPR (tetratricopeptide repeat) proteins that bind to the maturation complex via the C-termini of hsp70 (heat-shock protein 70) and hsp90 (heat-shock protein 90). We produced a random T7 peptide library to investigate the roles played by the C-termini of the two heat-shock proteins in the TPR-hsp interactions. Surprisingly, phages with the MEEVD sequence, found at the C-terminus of hsp90, were not recovered from our biopanning experiments. However, two groups of phages were isolated that bound relatively tightly to HsPP5 (Homo sapiens protein phosphatase 5) TPR. Multiple copies of phages with a C-terminal sequence of LFG were isolated. These phages bound specifically to the TPR domain of HsPP5, although mutation studies produced no evidence that they bound to the domain's hsp90-binding groove. However, the most abundant family obtained in the initial screen had an aspartate residue at the C-terminus. Two members of this family with a C-terminal sequence of VD appeared to bind with approximately the same affinity as the hsp90 C-12 control. A second generation pseudo-random phage library produced a large number of phages with an LD C-terminus. These sequences acted as hsp70 analogues and had relatively low affinities for hsp90-specific TPR domains. Unfortunately, we failed to identify residues near hsp90's C-terminus that impart binding specificity to individual hsp90-TPR interactions. The results suggest that the C-terminal sequences of hsp70 and hsp90 act primarily as non-specific anchors for TPR proteins.

A two-step recognition of signal sequences determines the translocation efficiency of proteins.

OpenAIRE

Belin, D; Bost, S; Vassalli, J D; Strub, K

1996-01-01

The cytosolic and secreted, N-glycosylated, forms of plasminogen activator inhibitor-2 (PAI-2) are generated by facultative translocation. To study the molecular events that result in the bi-topological distribution of proteins, we determined in vitro the capacities of several signal sequences to bind the signal recognition particle (SRP) during targeting, and to promote vectorial transport of murine PAI-2 (mPAI-2). Interestingly, the six signal sequences we compared (mPAI-2 and three mutated...

A novel approach to sequence validating protein expression clones with automated decision making

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Mohr Stephanie E

2007-06-01

Full Text Available Abstract Background Whereas the molecular assembly of protein expression clones is readily automated and routinely accomplished in high throughput, sequence verification of these clones is still largely performed manually, an arduous and time consuming process. The ultimate goal of validation is to determine if a given plasmid clone matches its reference sequence sufficiently to be "acceptable" for use in protein expression experiments. Given the accelerating increase in availability of tens of thousands of unverified clones, there is a strong demand for rapid, efficient and accurate software that automates clone validation. Results We have developed an Automated Clone Evaluation (ACE system – the first comprehensive, multi-platform, web-based plasmid sequence verification software package. ACE automates the clone verification process by defining each clone sequence as a list of multidimensional discrepancy objects, each describing a difference between the clone and its expected sequence including the resulting polypeptide consequences. To evaluate clones automatically, this list can be compared against user acceptance criteria that specify the allowable number of discrepancies of each type. This strategy allows users to re-evaluate the same set of clones against different acceptance criteria as needed for use in other experiments. ACE manages the entire sequence validation process including contig management, identifying and annotating discrepancies, determining if discrepancies correspond to polymorphisms and clone finishing. Designed to manage thousands of clones simultaneously, ACE maintains a relational database to store information about clones at various completion stages, project processing parameters and acceptance criteria. In a direct comparison, the automated analysis by ACE took less time and was more accurate than a manual analysis of a 93 gene clone set. Conclusion ACE was designed to facilitate high throughput clone sequence

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

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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.

The two capsid proteins of maize rayado fino virus contain common peptide sequences.

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Falk, B W; Tsai, J H

1986-01-01

Virions of maize rayado fino virus (MRFV) were purified and two major capsid proteins (ca. Mr 29,000 and 22,000) were resolved by SDS-PAGE. When the two major capsid proteins were isolated from gels and compared by one-dimensional peptide mapping after digestion with Staphylococcus aureus V-8 protease, indistinguishable peptide maps were obtained, suggesting that these two proteins contain common peptide sequences. Some preparations also showed minor protein components that were intermediate between the Mr 22,000 and Mr 29,000 capsid proteins. One of the minor proteins, ca. Mr 27,000, gave a peptide map indistinguishable from the major capsid proteins. In vitro ageing of partially purified preparations or virion treatment with proteolytic enzymes failed to show conversion of the Mr 29,000 protein to a Mr 22,000. Protease inhibitors added to the buffers used for virion purification did not affect the apparent 1:3 ratio of 29,000 to 22,000 proteins in the purified preparations.

Automated design evolution of stereochemically randomized protein foldamers

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Ranbhor, Ranjit; Kumar, Anil; Patel, Kirti; Ramakrishnan, Vibin; Durani, Susheel

2018-05-01

Diversification of chain stereochemistry opens up the possibilities of an ‘in principle’ increase in the design space of proteins. This huge increase in the sequence and consequent structural variation is aimed at the generation of smart materials. To diversify protein structure stereochemically, we introduced L- and D-α-amino acids as the design alphabet. With a sequence design algorithm, we explored the usage of specific variables such as chirality and the sequence of this alphabet in independent steps. With molecular dynamics, we folded stereochemically diverse homopolypeptides and evaluated their ‘fitness’ for possible design as protein-like foldamers. We propose a fitness function to prune the most optimal fold among 1000 structures simulated with an automated repetitive simulated annealing molecular dynamics (AR-SAMD) approach. The highly scored poly-leucine fold with sequence lengths of 24 and 30 amino acids were later sequence-optimized using a Dead End Elimination cum Monte Carlo based optimization tool. This paper demonstrates a novel approach for the de novo design of protein-like foldamers.

Genetic variability of attachment (G and Fusion (F protein genes of human metapneumovirus strains circulating during 2006-2009 in Kolkata, Eastern India

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Chawla-Sarkar Mamta

2011-02-01

Full Text Available Abstract Background Human metapneumovirus (hMPV is associated with the acute respiratory tract infection (ARTI in all the age groups. However, there is limited information on prevalence and genetic diversity of human metapneumovirus (hMPV strains circulating in India. Objective To study prevalence and genomic diversity of hMPV strains among ARTI patients reporting in outpatient departments of hospitals in Kolkata, Eastern India. Methods Nasal and/or throat swabs from 2309 patients during January 2006 to December 2009, were screened for the presence of hMPV by RT-PCR of nucleocapsid (N gene. The G and F genes of representative hMPV positive samples were sequenced. Results 118 of 2309 (5.11% clinical samples were positive for hMPV. The majority (≈80% of the positive cases were detected during July−November all through the study period. Genetic analysis revealed that 77% strains belong to A2 subgroup whereas rest clustered in B1 subgroup. G sequences showed higher diversity at the nucleotide and amino acid level. In contrast, less than 10% variation was observed in F gene of representative strains of all four years. Sequence analysis also revealed changes in the position of stop codon in G protein, which resulted in variable length (217-231 aa polypeptides. Conclusion The study suggests that approximately 5% of ARTI in the region were caused by hMPV. This is the first report on the genetic variability of G and F gene of hMPV strains from India which clearly shows that the G protein of hMPV is continuously evolving. Though the study partially fulfills lacunae of information, further studies from other regions are necessary for better understanding of prevalence, epidemiology and virus evolution in Indian subcontinent.

Prediction of host - pathogen protein interactions between Mycobacterium tuberculosis and Homo sapiens using sequence motifs.

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Huo, Tong; Liu, Wei; Guo, Yu; Yang, Cheng; Lin, Jianping; Rao, Zihe

2015-03-26

Emergence of multiple drug resistant strains of M. tuberculosis (MDR-TB) threatens to derail global efforts aimed at reigning in the pathogen. Co-infections of M. tuberculosis with HIV are difficult to treat. To counter these new challenges, it is essential to study the interactions between M. tuberculosis and the host to learn how these bacteria cause disease. We report a systematic flow to predict the host pathogen interactions (HPIs) between M. tuberculosis and Homo sapiens based on sequence motifs. First, protein sequences were used as initial input for identifying the HPIs by 'interolog' method. HPIs were further filtered by prediction of domain-domain interactions (DDIs). Functional annotations of protein and publicly available experimental results were applied to filter the remaining HPIs. Using such a strategy, 118 pairs of HPIs were identified, which involve 43 proteins from M. tuberculosis and 48 proteins from Homo sapiens. A biological interaction network between M. tuberculosis and Homo sapiens was then constructed using the predicted inter- and intra-species interactions based on the 118 pairs of HPIs. Finally, a web accessible database named PATH (Protein interactions of M. tuberculosis and Human) was constructed to store these predicted interactions and proteins. This interaction network will facilitate the research on host-pathogen protein-protein interactions, and may throw light on how M. tuberculosis interacts with its host.

Sequencing Larger Intact Proteins (30-70 kDa) with Activated Ion Electron Transfer Dissociation

Science.gov (United States)

Riley, Nicholas M.; Westphall, Michael S.; Coon, Joshua J.

2018-01-01

The analysis of intact proteins via mass spectrometry can offer several benefits to proteome characterization, although the majority of top-down experiments focus on proteoforms in a relatively low mass range (AI-ETD) to proteins in the 30-70 kDa range. AI-ETD leverages infrared photo-activation concurrent to ETD reactions to improve sequence-informative product ion generation. This method generates more product ions and greater sequence coverage than conventional ETD, higher-energy collisional dissociation (HCD), and ETD combined with supplemental HCD activation (EThcD). Importantly, AI-ETD provides the most thorough protein characterization for every precursor ion charge state investigated in this study, making it suitable as a universal fragmentation method in top-down experiments. Additionally, we highlight several acquisition strategies that can benefit characterization of larger proteins with AI-ETD, including combination of spectra from multiple ETD reaction times for a given precursor ion, multiple spectral acquisitions of the same precursor ion, and combination of spectra from two different dissociation methods (e.g., AI-ETD and HCD). In all, AI-ETD shows great promise as a method for dissociating larger intact protein ions as top-down proteomics continues to advance into larger mass ranges. [Figure not available: see fulltext.

Structural protein descriptors in 1-dimension and their sequence-based predictions.

Science.gov (United States)

Kurgan, Lukasz; Disfani, Fatemeh Miri

2011-09-01

The last few decades observed an increasing interest in development and application of 1-dimensional (1D) descriptors of protein structure. These descriptors project 3D structural features onto 1D strings of residue-wise structural assignments. They cover a wide-range of structural aspects including conformation of the backbone, burying depth/solvent exposure and flexibility of residues, and inter-chain residue-residue contacts. We perform first-of-its-kind comprehensive comparative review of the existing 1D structural descriptors. We define, review and categorize ten structural descriptors and we also describe, summarize and contrast over eighty computational models that are used to predict these descriptors from the protein sequences. We show that the majority of the recent sequence-based predictors utilize machine learning models, with the most popular being neural networks, support vector machines, hidden Markov models, and support vector and linear regressions. These methods provide high-throughput predictions and most of them are accessible to a non-expert user via web servers and/or stand-alone software packages. We empirically evaluate several recent sequence-based predictors of secondary structure, disorder, and solvent accessibility descriptors using a benchmark set based on CASP8 targets. Our analysis shows that the secondary structure can be predicted with over 80% accuracy and segment overlap (SOV), disorder with over 0.9 AUC, 0.6 Matthews Correlation Coefficient (MCC), and 75% SOV, and relative solvent accessibility with PCC of 0.7 and MCC of 0.6 (0.86 when homology is used). We demonstrate that the secondary structure predicted from sequence without the use of homology modeling is as good as the structure extracted from the 3D folds predicted by top-performing template-based methods.

Protein consensus-based surface engineering (ProCoS): a computer-assisted method for directed protein evolution.

Science.gov (United States)

Shivange, Amol V; Hoeffken, Hans Wolfgang; Haefner, Stefan; Schwaneberg, Ulrich

2016-12-01

Protein consensus-based surface engineering (ProCoS) is a simple and efficient method for directed protein evolution combining computational analysis and molecular biology tools to engineer protein surfaces. ProCoS is based on the hypothesis that conserved residues originated from a common ancestor and that these residues are crucial for the function of a protein, whereas highly variable regions (situated on the surface of a protein) can be targeted for surface engineering to maximize performance. ProCoS comprises four main steps: ( i ) identification of conserved and highly variable regions; ( ii ) protein sequence design by substituting residues in the highly variable regions, and gene synthesis; ( iii ) in vitro DNA recombination of synthetic genes; and ( iv ) screening for active variants. ProCoS is a simple method for surface mutagenesis in which multiple sequence alignment is used for selection of surface residues based on a structural model. To demonstrate the technique's utility for directed evolution, the surface of a phytase enzyme from Yersinia mollaretii (Ymphytase) was subjected to ProCoS. Screening just 1050 clones from ProCoS engineering-guided mutant libraries yielded an enzyme with 34 amino acid substitutions. The surface-engineered Ymphytase exhibited 3.8-fold higher pH stability (at pH 2.8 for 3 h) and retained 40% of the enzyme's specific activity (400 U/mg) compared with the wild-type Ymphytase. The pH stability might be attributed to a significantly increased (20 percentage points; from 9% to 29%) number of negatively charged amino acids on the surface of the engineered phytase.

Using structural knowledge in the protein data bank to inform the search for potential host-microbe protein interactions in sequence space: application to Mycobacterium tuberculosis.

Science.gov (United States)

Mahajan, Gaurang; Mande, Shekhar C

2017-04-04

A comprehensive map of the human-M. tuberculosis (MTB) protein interactome would help fill the gaps in our understanding of the disease, and computational prediction can aid and complement experimental studies towards this end. Several sequence-based in silico approaches tap the existing data on experimentally validated protein-protein interactions (PPIs); these PPIs serve as templates from which novel interactions between pathogen and host are inferred. Such comparative approaches typically make use of local sequence alignment, which, in the absence of structural details about the interfaces mediating the template interactions, could lead to incorrect inferences, particularly when multi-domain proteins are involved. We propose leveraging the domain-domain interaction (DDI) information in PDB complexes to score and prioritize candidate PPIs between host and pathogen proteomes based on targeted sequence-level comparisons. Our method picks out a small set of human-MTB protein pairs as candidates for physical interactions, and the use of functional meta-data suggests that some of them could contribute to the in vivo molecular cross-talk between pathogen and host that regulates the course of the infection. Further, we present numerical data for Pfam domain families that highlights interaction specificity on the domain level. Not every instance of a pair of domains, for which interaction evidence has been found in a few instances (i.e. structures), is likely to functionally interact. Our sorting approach scores candidates according to how "distant" they are in sequence space from known examples of DDIs (templates). Thus, it provides a natural way to deal with the heterogeneity in domain-level interactions. Our method represents a more informed application of local alignment to the sequence-based search for potential human-microbial interactions that uses available PPI data as a prior. Our approach is somewhat limited in its sensitivity by the restricted size and

Insights into Protein Sequence and Structure-Derived Features Mediating 3D Domain Swapping Mechanism using Support Vector Machine Based Approach

Directory of Open Access Journals (Sweden)

Khader Shameer

2010-06-01

Full Text Available 3-dimensional domain swapping is a mechanism where two or more protein molecules form higher order oligomers by exchanging identical or similar subunits. Recently, this phenomenon has received much attention in the context of prions and neuro-degenerative diseases, due to its role in the functional regulation, formation of higher oligomers, protein misfolding, aggregation etc. While 3-dimensional domain swap mechanism can be detected from three-dimensional structures, it remains a formidable challenge to derive common sequence or structural patterns from proteins involved in swapping. We have developed a SVM-based classifier to predict domain swapping events using a set of features derived from sequence and structural data. The SVM classifier was trained on features derived from 150 proteins reported to be involved in 3D domain swapping and 150 proteins not known to be involved in swapped conformation or related to proteins involved in swapping phenomenon. The testing was performed using 63 proteins from the positive dataset and 63 proteins from the negative dataset. We obtained 76.33% accuracy from training and 73.81% accuracy from testing. Due to high diversity in the sequence, structure and functions of proteins involved in domain swapping, availability of such an algorithm to predict swapping events from sequence and structure-derived features will be an initial step towards identification of more putative proteins that may be involved in swapping or proteins involved in deposition disease. Further, the top features emerging in our feature selection method may be analysed further to understand their roles in the mechanism of domain swapping.

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

Stellar Variability at the Main-sequence Turnoff of the Intermediate-age LMC Cluster NGC 1846

Science.gov (United States)

Salinas, R.; Pajkos, M. A.; Vivas, A. K.; Strader, J.; Contreras Ramos, R.

2018-04-01

Intermediate-age (IA) star clusters in the Large Magellanic Cloud (LMC) present extended main-sequence turn-offs (MSTO) that have been attributed to either multiple stellar populations or an effect of stellar rotation. Recently it has been proposed that these extended main sequences can also be produced by ill-characterized stellar variability. Here we present Gemini-S/Gemini Multi-Object Spectrometer (GMOS) time series observations of the IA cluster NGC 1846. Using differential image analysis, we identified 73 new variable stars, with 55 of those being of the Delta Scuti type, that is, pulsating variables close the MSTO for the cluster age. Considering completeness and background contamination effects, we estimate the number of δ Sct belonging to the cluster between 40 and 60 members, although this number is based on the detection of a single δ Sct within the cluster half-light radius. This amount of variable stars at the MSTO level will not produce significant broadening of the MSTO, albeit higher-resolution imaging will be needed to rule out variable stars as a major contributor to the extended MSTO phenomenon. Though modest, this amount of δ Sct makes NGC 1846 the star cluster with the highest number of these variables ever discovered. Lastly, our results present a cautionary tale about the adequacy of shallow variability surveys in the LMC (like OGLE) to derive properties of its δ Sct population. Based on observations obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (United States), the National Research Council (Canada), CONICYT (Chile), Ministerio de Ciencia, Tecnología e Innovación Productiva (Argentina), and Ministério da Ciência, Tecnologia e Inovação (Brazil).

Creation and structure determination of an artificial protein with three complete sequence repeats

Energy Technology Data Exchange (ETDEWEB)

Adachi, Motoyasu, E-mail: adachi.motoyasu@jaea.go.jp; Shimizu, Rumi; Kuroki, Ryota [Japan Atomic Energy Agency, Shirakatashirane 2-4, Nakagun Tokaimura, Ibaraki 319-1195 (Japan); Blaber, Michael [Japan Atomic Energy Agency, Shirakatashirane 2-4, Nakagun Tokaimura, Ibaraki 319-1195 (Japan); Florida State University, Tallahassee, FL 32306-4300 (United States)

2013-11-01

An artificial protein with three complete sequence repeats was created and the structure was determined by X-ray crystallography. The structure showed threefold symmetry even though there is an amino- and carboxy-terminal. The artificial protein with threefold symmetry may be useful as a scaffold to capture small materials with C3 symmetry. Symfoil-4P is a de novo protein exhibiting the threefold symmetrical β-trefoil fold designed based on the human acidic fibroblast growth factor. First three asparagine–glycine sequences of Symfoil-4P are replaced with glutamine–glycine (Symfoil-QG) or serine–glycine (Symfoil-SG) sequences protecting from deamidation, and His-Symfoil-II was prepared by introducing a protease digestion site into Symfoil-QG so that Symfoil-II has three complete repeats after removal of the N-terminal histidine tag. The Symfoil-QG and SG and His-Symfoil-II proteins were expressed in Eschericha coli as soluble protein, and purified by nickel affinity chromatography. Symfoil-II was further purified by anion-exchange chromatography after removing the HisTag by proteolysis. Both Symfoil-QG and Symfoil-II were crystallized in 0.1 M Tris-HCl buffer (pH 7.0) containing 1.8 M ammonium sulfate as precipitant at 293 K; several crystal forms were observed for Symfoil-QG and II. The maximum diffraction of Symfoil-QG and II crystals were 1.5 and 1.1 Å resolution, respectively. The Symfoil-II without histidine tag diffracted better than Symfoil-QG with N-terminal histidine tag. Although the crystal packing of Symfoil-II is slightly different from Symfoil-QG and other crystals of Symfoil derivatives having the N-terminal histidine tag, the refined crystal structure of Symfoil-II showed pseudo-threefold symmetry as expected from other Symfoils. Since the removal of the unstructured N-terminal histidine tag did not affect the threefold structure of Symfoil, the improvement of diffraction quality of Symfoil-II may be caused by molecular characteristics of

Large scale identification and categorization of protein sequences using structured logistic regression

DEFF Research Database (Denmark)

Pedersen, Bjørn Panella; Ifrim, Georgiana; Liboriussen, Poul

2014-01-01

Abstract Background Structured Logistic Regression (SLR) is a newly developed machine learning tool first proposed in the context of text categorization. Current availability of extensive protein sequence databases calls for an automated method to reliably classify sequences and SLR seems well...... problem. Results Using SLR, we have built classifiers to identify and automatically categorize P-type ATPases into one of 11 pre-defined classes. The SLR-classifiers are compared to a Hidden Markov Model approach and shown to be highly accurate and scalable. Representing the bulk of currently known...... for further biochemical characterization and structural analysis....

Nucleotide sequence of the coat protein gene of the Skierniewice isolate of plum pox virus (PPV)

International Nuclear Information System (INIS)

Wypijewski, K.; Musial, W.; Augustyniak, J.; Malinowski, T.

1994-01-01

The coat protein (CP) gene of the Skierniewice isolate of plum pox virus (PPV-S) has been amplified using the reverse transcription - polymerase chain reaction (RT-PCR), cloned and sequenced. The nucleotide sequence of the gene and the deduced amino-acid sequences of PPV-S CP were compared with those of other PPV strains. The nucleotide sequence showed very high homology to most of the published sequences. The motif: Asp-Ala-Gly (DAG), important for the aphid transmissibility, was present in the amino-acid sequence. Our isolate did not react in ELISA with monoclonal antibodies MAb06 supposed to be specific for PPV-D. (author). 32 refs, 1 fig., 2 tabs

Protein-Protein Interactions Prediction Using a Novel Local Conjoint Triad Descriptor of Amino Acid Sequences

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Jun Wang

2017-11-01

Full Text Available Protein-protein interactions (PPIs play crucial roles in almost all cellular processes. Although a large amount of PPIs have been verified by high-throughput techniques in the past decades, currently known PPIs pairs are still far from complete. Furthermore, the wet-lab experiments based techniques for detecting PPIs are time-consuming and expensive. Hence, it is urgent and essential to develop automatic computational methods to efficiently and accurately predict PPIs. In this paper, a sequence-based approach called DNN-LCTD is developed by combining deep neural networks (DNNs and a novel local conjoint triad description (LCTD feature representation. LCTD incorporates the advantage of local description and conjoint triad, thus, it is capable to account for the interactions between residues in both continuous and discontinuous regions of amino acid sequences. DNNs can not only learn suitable features from the data by themselves, but also learn and discover hierarchical representations of data. When performing on the PPIs data of Saccharomyces cerevisiae, DNN-LCTD achieves superior performance with accuracy as 93.12%, precision as 93.75%, sensitivity as 93.83%, area under the receiver operating characteristic curve (AUC as 97.92%, and it only needs 718 s. These results indicate DNN-LCTD is very promising for predicting PPIs. DNN-LCTD can be a useful supplementary tool for future proteomics study.

Sequence analysis of the L protein of the Ebola 2014 outbreak: Insight into conserved regions and mutations.

Science.gov (United States)

Ayub, Gohar; Waheed, Yasir

2016-06-01

The 2014 Ebola outbreak was one of the largest that have occurred; it started in Guinea and spread to Nigeria, Liberia and Sierra Leone. Phylogenetic analysis of the current virus species indicated that this outbreak is the result of a divergent lineage of the Zaire ebolavirus. The L protein of Ebola virus (EBOV) is the catalytic subunit of the RNA‑dependent RNA polymerase complex, which, with VP35, is key for the replication and transcription of viral RNA. Earlier sequence analysis demonstrated that the L protein of all non‑segmented negative‑sense (NNS) RNA viruses consists of six domains containing conserved functional motifs. The aim of the present study was to analyze the presence of these motifs in 2014 EBOV isolates, highlight their function and how they may contribute to the overall pathogenicity of the isolates. For this purpose, 81 2014 EBOV L protein sequences were aligned with 475 other NNS RNA viruses, including Paramyxoviridae and Rhabdoviridae viruses. Phylogenetic analysis of all EBOV outbreak L protein sequences was also performed. Analysis of the amino acid substitutions in the 2014 EBOV outbreak was conducted using sequence analysis. The alignment demonstrated the presence of previously conserved motifs in the 2014 EBOV isolates and novel residues. Notably, all the mutations identified in the 2014 EBOV isolates were tolerant, they were pathogenic with certain examples occurring within previously determined functional conserved motifs, possibly altering viral pathogenicity, replication and virulence. The phylogenetic analysis demonstrated that all sequences with the exception of the 2014 EBOV sequences were clustered together. The 2014 EBOV outbreak has acquired a great number of mutations, which may explain the reasons behind this unprecedented outbreak. Certain residues critical to the function of the polymerase remain conserved and may be targets for the development of antiviral therapeutic agents.

Hydrophobic cluster analysis of G protein-coupled receptors: a powerful tool to derive structural and functional information from 2D-representation of protein sequences

NARCIS (Netherlands)

Lentes, K.U.; Mathieu, E.; Bischoff, Rainer; Rasmussen, U.B.; Pavirani, A.

1993-01-01

Current methods for comparative analyses of protein sequences are 1D-alignments of amino acid sequences based on the maximization of amino acid identity (homology) and the prediction of secondary structure elements. This method has a major drawback once the amino acid identity drops below 20-25%,

High genetic diversity in the coat protein and 3' untranslated regions

Indian Academy of Sciences (India)

The 3′ terminal region consisting of the coat protein (CP) coding sequence and 3′ untranslated region (3′UTR) was cloned and sequenced from seven isolates. Sequence comparisons revealed considerable genetic diversity among the isolates in their CP and 3′UTR, making CdMV one of the highly variable members ...

The sequence of cortical activity inferred by response latency variability in the human ventral pathway of face processing.

Science.gov (United States)

Lin, Jo-Fu Lotus; Silva-Pereyra, Juan; Chou, Chih-Che; Lin, Fa-Hsuan

2018-04-11

Variability in neuronal response latency has been typically considered caused by random noise. Previous studies of single cells and large neuronal populations have shown that the temporal variability tends to increase along the visual pathway. Inspired by these previous studies, we hypothesized that functional areas at later stages in the visual pathway of face processing would have larger variability in the response latency. To test this hypothesis, we used magnetoencephalographic data collected when subjects were presented with images of human faces. Faces are known to elicit a sequence of activity from the primary visual cortex to the fusiform gyrus. Our results revealed that the fusiform gyrus showed larger variability in the response latency compared to the calcarine fissure. Dynamic and spectral analyses of the latency variability indicated that the response latency in the fusiform gyrus was more variable than in the calcarine fissure between 70 ms and 200 ms after the stimulus onset and between 4 Hz and 40 Hz, respectively. The sequential processing of face information from the calcarine sulcus to the fusiform sulcus was more reliably detected based on sizes of the response variability than instants of the maximal response peaks. With two areas in the ventral visual pathway, we show that the variability in response latency across brain areas can be used to infer the sequence of cortical activity.

Protein identification from two-dimensional gel electrophoresis analysis of Klebsiella pneumoniae by combined use of mass spectrometry data and raw genome sequences

Directory of Open Access Journals (Sweden)

Zeng An-Ping

2003-12-01

Full Text Available Abstract Separation of proteins by two-dimensional gel electrophoresis (2-DE coupled with identification of proteins through peptide mass fingerprinting (PMF by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS is the widely used technique for proteomic analysis. This approach relies, however, on the presence of the proteins studied in public-accessible protein databases or the availability of annotated genome sequences of an organism. In this work, we investigated the reliability of using raw genome sequences for identifying proteins by PMF without the need of additional information such as amino acid sequences. The method is demonstrated for proteomic analysis of Klebsiella pneumoniae grown anaerobically on glycerol. For 197 spots excised from 2-DE gels and submitted for mass spectrometric analysis 164 spots were clearly identified as 122 individual proteins. 95% of the 164 spots can be successfully identified merely by using peptide mass fingerprints and a strain-specific protein database (ProtKpn constructed from the raw genome sequences of K. pneumoniae. Cross-species protein searching in the public databases mainly resulted in the identification of 57% of the 66 high expressed protein spots in comparison to 97% by using the ProtKpn database. 10 dha regulon related proteins that are essential for the initial enzymatic steps of anaerobic glycerol metabolism were successfully identified using the ProtKpn database, whereas none of them could be identified by cross-species searching. In conclusion, the use of strain-specific protein database constructed from raw genome sequences makes it possible to reliably identify most of the proteins from 2-DE analysis simply through peptide mass fingerprinting.

High dimensional and high resolution pulse sequences for backbone resonance assignment of intrinsically disordered proteins

Energy Technology Data Exchange (ETDEWEB)

Zawadzka-Kazimierczuk, Anna; Kozminski, Wiktor, E-mail: kozmin@chem.uw.edu.pl [University of Warsaw, Faculty of Chemistry (Poland); Sanderova, Hana; Krasny, Libor [Institute of Microbiology, Academy of Sciences of the Czech Republic, Laboratory of Molecular Genetics of Bacteria, Department of Bacteriology (Czech Republic)

2012-04-15

Four novel 5D (HACA(N)CONH, HNCOCACB, (HACA)CON(CA)CONH, (H)NCO(NCA)CONH), and one 6D ((H)NCO(N)CACONH) NMR pulse sequences are proposed. The new experiments employ non-uniform sampling that enables achieving high resolution in indirectly detected dimensions. The experiments facilitate resonance assignment of intrinsically disordered proteins. The novel pulse sequences were successfully tested using {delta} subunit (20 kDa) of Bacillus subtilis RNA polymerase that has an 81-amino acid disordered part containing various repetitive sequences.

Genomic Enzymology: Web Tools for Leveraging Protein Family Sequence-Function Space and Genome Context to Discover Novel Functions.

Science.gov (United States)

Gerlt, John A

2017-08-22

The exponentially increasing number of protein and nucleic acid sequences provides opportunities to discover novel enzymes, metabolic pathways, and metabolites/natural products, thereby adding to our knowledge of biochemistry and biology. The challenge has evolved from generating sequence information to mining the databases to integrating and leveraging the available information, i.e., the availability of "genomic enzymology" web tools. Web tools that allow identification of biosynthetic gene clusters are widely used by the natural products/synthetic biology community, thereby facilitating the discovery of novel natural products and the enzymes responsible for their biosynthesis. However, many novel enzymes with interesting mechanisms participate in uncharacterized small-molecule metabolic pathways; their discovery and functional characterization also can be accomplished by leveraging information in protein and nucleic acid databases. This Perspective focuses on two genomic enzymology web tools that assist the discovery novel metabolic pathways: (1) Enzyme Function Initiative-Enzyme Similarity Tool (EFI-EST) for generating sequence similarity networks to visualize and analyze sequence-function space in protein families and (2) Enzyme Function Initiative-Genome Neighborhood Tool (EFI-GNT) for generating genome neighborhood networks to visualize and analyze the genome context in microbial and fungal genomes. Both tools have been adapted to other applications to facilitate target selection for enzyme discovery and functional characterization. As the natural products community has demonstrated, the enzymology community needs to embrace the essential role of web tools that allow the protein and genome sequence databases to be leveraged for novel insights into enzymological problems.

Nucleotide sequence analysis of the Legionella micdadei mip gene, encoding a 30-kilodalton analog of the Legionella pneumophila Mip protein

DEFF Research Database (Denmark)

Bangsborg, Jette Marie; Cianciotto, N P; Hindersson, P

1991-01-01

After the demonstration of analogs of the Legionella pneumophila macrophage infectivity potentiator (Mip) protein in other Legionella species, the Legionella micdadei mip gene was cloned and expressed in Escherichia coli. DNA sequence analysis of the L. micdadei mip gene contained in the plasmid p...... homology with the mip-like genes of several Legionella species. Furthermore, amino acid sequence comparisons revealed significant homology to two eukaryotic proteins with isomerase activity (FK506-binding proteins)....

Nucleotide sequence of a human cDNA encoding a ras-related protein (rap1B)

Energy Technology Data Exchange (ETDEWEB)

Pizon, V; Lerosey, I; Chardin, P; Tavitian, A [INSERM, Paris (France)

1988-08-11

The authors have previously characterized two human ras-related genes rap1 and rap2. Using the rap1 clone as probe they isolated and sequenced a new rap cDNA encoding the 184aa rap1B protein. The rap1B protein is 95% identical to rap1 and shares several properties with the ras protein suggesting that it could bind GTP/GDP and have a membrane location. As for rap1, the structural characteristics of rap1B suggest that the rap and ras proteins might interact on the same effector.

High Performance Protein Sequence Database Scanning on the Cell Broadband Engine

Directory of Open Access Journals (Sweden)

Adrianto Wirawan

2009-01-01

Full Text Available The enormous growth of biological sequence databases has caused bioinformatics to be rapidly moving towards a data-intensive, computational science. As a result, the computational power needed by bioinformatics applications is growing rapidly as well. The recent emergence of low cost parallel multicore accelerator technologies has made it possible to reduce execution times of many bioinformatics applications. In this paper, we demonstrate how the Cell Broadband Engine can be used as a computational platform to accelerate two approaches for protein sequence database scanning: exhaustive and heuristic. We present efficient parallelization techniques for two representative algorithms: the dynamic programming based Smith–Waterman algorithm and the popular BLASTP heuristic. Their implementation on a Playstation®3 leads to significant runtime savings compared to corresponding sequential implementations.

A structural study for the optimisation of functional motifs encoded in protein sequences

Directory of Open Access Journals (Sweden)

Helmer-Citterich Manuela

2004-04-01

Full Text Available Abstract Background A large number of PROSITE patterns select false positives and/or miss known true positives. It is possible that – at least in some cases – the weak specificity and/or sensitivity of a pattern is due to the fact that one, or maybe more, functional and/or structural key residues are not represented in the pattern. Multiple sequence alignments are commonly used to build functional sequence patterns. If residues structurally conserved in proteins sharing a function cannot be aligned in a multiple sequence alignment, they are likely to be missed in a standard pattern construction procedure. Results Here we present a new procedure aimed at improving the sensitivity and/ or specificity of poorly-performing patterns. The procedure can be summarised as follows: 1. residues structurally conserved in different proteins, that are true positives for a pattern, are identified by means of a computational technique and by visual inspection. 2. the sequence positions of the structurally conserved residues falling outside the pattern are used to build extended sequence patterns. 3. the extended patterns are optimised on the SWISS-PROT database for their sensitivity and specificity. The method was applied to eight PROSITE patterns. Whenever structurally conserved residues are found in the surface region close to the pattern (seven out of eight cases, the addition of information inferred from structural analysis is shown to improve pattern selectivity and in some cases selectivity and sensitivity as well. In some of the cases considered the procedure allowed the identification of functionally interesting residues, whose biological role is also discussed. Conclusion Our method can be applied to any type of functional motif or pattern (not only PROSITE ones which is not able to select all and only the true positive hits and for which at least two true positive structures are available. The computational technique for the identification of

Characterization of the variable-number tandem repeats in vrrA from different Bacillus anthracis isolates

Energy Technology Data Exchange (ETDEWEB)

Jackson, P.J.; Walthers, E.A.; Richmond, K.L. [Los Alamos National Lab., NM (United States)] [and others

1997-04-01

PCR analysis of 198 Bacillus anthracis isolates revealed a variable region of DNA sequence differing in length among the isolates. Five Polymorphisms differed by the presence Of two to six copies of the 12-bp tandem repeat 5{prime}-CAATATCAACAA-3{prime}. This variable-number tandem repeat (VNTR) region is located within a larger sequence containing one complete open reading frame that encodes a putative 30-kDa protein. Length variation did not change the reading frame of the encoded protein and only changed the copy number of a 4-amino-acid sequence (QYQQ) from 2 to 6. The structure of the VNTR region suggests that these multiple repeats are generated by recombination or polymerase slippage. Protein structures predicted from the reverse-translated DNA sequence suggest that any structural changes in the encoded protein are confined to the region encoded by the VNTR sequence. Copy number differences in the VNTR region were used to define five different B. anthracis alleles. Characterization of 198 isolates revealed allele frequencies of 6.1, 17.7, 59.6, 5.6, and 11.1% sequentially from shorter to longer alleles. The high degree of polymorphism in the VNTR region provides a criterion for assigning isolates to five allelic categories. There is a correlation between categories and geographic distribution. Such molecular markers can be used to monitor the epidemiology of anthrax outbreaks in domestic and native herbivore populations. 22 refs., 4 figs., 3 tabs.

RNAcontext: a new method for learning the sequence and structure binding preferences of RNA-binding proteins.

Directory of Open Access Journals (Sweden)

Hilal Kazan

2010-07-01

Full Text Available Metazoan genomes encode hundreds of RNA-binding proteins (RBPs. These proteins regulate post-transcriptional gene expression and have critical roles in numerous cellular processes including mRNA splicing, export, stability and translation. Despite their ubiquity and importance, the binding preferences for most RBPs are not well characterized. In vitro and in vivo studies, using affinity selection-based approaches, have successfully identified RNA sequence associated with specific RBPs; however, it is difficult to infer RBP sequence and structural preferences without specifically designed motif finding methods. In this study, we introduce a new motif-finding method, RNAcontext, designed to elucidate RBP-specific sequence and structural preferences with greater accuracy than existing approaches. We evaluated RNAcontext on recently published in vitro and in vivo RNA affinity selected data and demonstrate that RNAcontext identifies known binding preferences for several control proteins including HuR, PTB, and Vts1p and predicts new RNA structure preferences for SF2/ASF, RBM4, FUSIP1 and SLM2. The predicted preferences for SF2/ASF are consistent with its recently reported in vivo binding sites. RNAcontext is an accurate and efficient motif finding method ideally suited for using large-scale RNA-binding affinity datasets to determine the relative binding preferences of RBPs for a wide range of RNA sequences and structures.

Purification and sequencing of radish seed calmodulin antagonists phosphorylated by calcium-dependent protein kinase.

Science.gov (United States)

Polya, G M; Chandra, S; Condron, R

1993-02-01

A family of radish (Raphanus sativus) calmodulin antagonists (RCAs) was purified from seeds by extraction, centrifugation, batch-wise elution from carboxymethyl-cellulose, and high performance liquid chromatography (HPLC) on an SP5PW cation-exchange column. This RCA fraction was further resolved into three calmodulin antagonist polypeptides (RCA1, RCA2, and RCA3) by denaturation in the presence of guanidinium HCl and mercaptoethanol and subsequent reverse-phase HPLC on a C8 column eluted with an acetonitrile gradient in the presence of 0.1% trifluoroacetic acid. The RCA preparation, RCA1, RCA2, RCA3, and other radish seed proteins are phosphorylated by wheat embryo Ca(2+)-dependent protein kinase (CDPK). The RCA preparation contains other CDPK substrates in addition to RCA1, RCA2, and RCA3. The RCA preparation, RCA1, RCA2, and RCA3 inhibit chicken gizzard calmodulin-dependent myosin light chain kinase assayed with a myosin-light chain-based synthetic peptide substrate (fifty percent inhibitory concentrations of RCA2 and RCA3 are about 7 and 2 microM, respectively). N-terminal sequencing by sequential Edman degradation of RCA1, RCA2, and RCA3 revealed sequences having a high homology with the small subunit of the storage protein napin from Brassica napus and with related proteins. The deduced amino acid sequences of RCA1, RCA2, RCA3, and RCA3' (a subform of RCA3) have agreement with average molecular masses from electrospray mass spectrometry of 4537, 4543, 4532, and 4560 kD, respectively. The only sites for serine phosphorylation are near or at the C termini and hence adjacent to the sites of proteolytic precursor cleavage.

F-Type Lectins: A Highly Diversified Family of Fucose-Binding Proteins with a Unique Sequence Motif and Structural Fold, Involved in Self/Non-Self-Recognition

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Gerardo R. Vasta

2017-11-01

Full Text Available The F-type lectin (FTL family is one of the most recent to be identified and structurally characterized. Members of the FTL family are characterized by a fucose recognition domain [F-type lectin domain (FTLD] that displays a novel jellyroll fold (“F-type” fold and unique carbohydrate- and calcium-binding sequence motifs. This novel lectin family comprises widely distributed proteins exhibiting single, double, or greater multiples of the FTLD, either tandemly arrayed or combined with other structurally and functionally distinct domains, yielding lectin subunits of pleiotropic properties even within a single species. Furthermore, the extraordinary variability of FTL sequences (isoforms that are expressed in a single individual has revealed genetic mechanisms of diversification in ligand recognition that are unique to FTLs. Functions of FTLs in self/non-self-recognition include innate immunity, fertilization, microbial adhesion, and pathogenesis, among others. In addition, although the F-type fold is distinctive for FTLs, a structure-based search revealed apparently unrelated proteins with minor sequence similarity to FTLs that displayed the FTLD fold. In general, the phylogenetic analysis of FTLD sequences from viruses to mammals reveals clades that are consistent with the currently accepted taxonomy of extant species. However, the surprisingly discontinuous distribution of FTLDs within each taxonomic category suggests not only an extensive structural/functional diversification of the FTLs along evolutionary lineages but also that this intriguing lectin family has been subject to frequent gene duplication, secondary loss, lateral transfer, and functional co-option.

Actin and ubiquitin protein sequences support a cercozoan/foraminiferan ancestry for the plasmodiophorid plant pathogens.

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Archibald, John M; Keeling, Patrick J

2004-01-01

The plasmodiophorids are a group of eukaryotic intracellular parasites that cause disease in a variety of economically significant crops. Plasmodiophorids have traditionally been considered fungi but have more recently been suggested to be members of the Cercozoa, a morphologically diverse group of amoeboid, flagellate, and amoeboflagellate protists. The recognition that Cercozoa constitute a monophyletic lineage has come from phylogenetic analyses of small subunit ribosomal RNA genes. Protein sequence data have suggested that the closest relatives of Cercozoa are the Foraminifera. To further test a cercozoan origin for the plasmodiophorids, we isolated actin genes from Plasmodiophora brassicae, Sorosphaera veronicae, and Spongospora subterranea, and polyubiquitin gene fragments from P. brassicae and S. subterranea. We also isolated actin genes from the chlorarachniophyte Lotharella globosa. In protein phylogenies of actin, the plasmodiophorid sequences consistently branch with Cercozoa and Foraminifera, and weakly branch as the sister group to the foraminiferans. The plasmodiophorid polyubiquitin sequences contain a single amino acid residue insertion at the functionally important processing point between ubiquitin monomers, the same place in which an otherwise unique insertion exists in the cercozoan and foraminiferan proteins. Taken together, these results indicate that plasmodiophorids are indeed related to Cercozoa and Foraminifera, although the relationships amongst these groups remain unresolved.