Isolation and characterization of target sequences of the chicken CdxA homeobox gene.

PubMed Central

Margalit, Y; Yarus, S; Shapira, E; Gruenbaum, Y; Fainsod, A

1993-01-01

The DNA binding specificity of the chicken homeodomain protein CDXA was studied. Using a CDXA-glutathione-S-transferase fusion protein, DNA fragments containing the binding site for this protein were isolated. The sources of DNA were oligonucleotides with random sequence and chicken genomic DNA. The DNA fragments isolated were sequenced and tested in DNA binding assays. Sequencing revealed that most DNA fragments are AT rich which is a common feature of homeodomain binding sites. By electrophoretic mobility shift assays it was shown that the different target sequences isolated bind to the CDXA protein with different affinities. The specific sequences bound by the CDXA protein in the genomic fragments isolated, were determined by DNase I footprinting. From the footprinted sequences, the CDXA consensus binding site was determined. The CDXA protein binds the consensus sequence A, A/T, T, A/T, A, T, A/G. The CAUDAL binding site in the ftz promoter is also included in this consensus sequence. When tested, some of the genomic target sequences were capable of enhancing the transcriptional activity of reporter plasmids when introduced into CDXA expressing cells. This study determined the DNA sequence specificity of the CDXA protein and it also shows that this protein can further activate transcription in cells in culture. Images PMID:7909943

Terminal sequence importance of de novo proteins from binary-patterned library: stable artificial proteins with 11- or 12-amino acid alphabet.

PubMed

Okura, Hiromichi; Takahashi, Tsuyoshi; Mihara, Hisakazu

2012-06-01

Successful approaches of de novo protein design suggest a great potential to create novel structural folds and to understand natural rules of protein folding. For these purposes, smaller and simpler de novo proteins have been developed. Here, we constructed smaller proteins by removing the terminal sequences from stable de novo vTAJ proteins and compared stabilities between mutant and original proteins. vTAJ proteins were screened from an α3β3 binary-patterned library which was designed with polar/ nonpolar periodicities of α-helix and β-sheet. vTAJ proteins have the additional terminal sequences due to the method of constructing the genetically repeated library sequences. By removing the parts of the sequences, we successfully obtained the stable smaller de novo protein mutants with fewer amino acid alphabets than the originals. However, these mutants showed the differences on ANS binding properties and stabilities against denaturant and pH change. The terminal sequences, which were designed just as flexible linkers not as secondary structure units, sufficiently affected these physicochemical details. This study showed implications for adjusting protein stabilities by designing N- and C-terminal sequences.

On the Origin of Protein Superfamilies and Superfolds

NASA Astrophysics Data System (ADS)

Magner, Abram; Szpankowski, Wojciech; Kihara, Daisuke

2015-02-01

Distributions of protein families and folds in genomes are highly skewed, having a small number of prevalent superfamiles/superfolds and a large number of families/folds of a small size. Why are the distributions of protein families and folds skewed? Why are there only a limited number of protein families? Here, we employ an information theoretic approach to investigate the protein sequence-structure relationship that leads to the skewed distributions. We consider that protein sequences and folds constitute an information theoretic channel and computed the most efficient distribution of sequences that code all protein folds. The identified distributions of sequences and folds are found to follow a power law, consistent with those observed for proteins in nature. Importantly, the skewed distributions of sequences and folds are suggested to have different origins: the skewed distribution of sequences is due to evolutionary pressure to achieve efficient coding of necessary folds, whereas that of folds is based on the thermodynamic stability of folds. The current study provides a new information theoretic framework for proteins that could be widely applied for understanding protein sequences, structures, functions, and interactions.

Optimizing high performance computing workflow for protein functional annotation.

PubMed

Stanberry, Larissa; Rekepalli, Bhanu; Liu, Yuan; Giblock, Paul; Higdon, Roger; Montague, Elizabeth; Broomall, William; Kolker, Natali; Kolker, Eugene

2014-09-10

Functional annotation of newly sequenced genomes is one of the major challenges in modern biology. With modern sequencing technologies, the protein sequence universe is rapidly expanding. Newly sequenced bacterial genomes alone contain over 7.5 million proteins. The rate of data generation has far surpassed that of protein annotation. The volume of protein data makes manual curation infeasible, whereas a high compute cost limits the utility of existing automated approaches. In this work, we present an improved and optmized automated workflow to enable large-scale protein annotation. The workflow uses high performance computing architectures and a low complexity classification algorithm to assign proteins into existing clusters of orthologous groups of proteins. On the basis of the Position-Specific Iterative Basic Local Alignment Search Tool the algorithm ensures at least 80% specificity and sensitivity of the resulting classifications. The workflow utilizes highly scalable parallel applications for classification and sequence alignment. Using Extreme Science and Engineering Discovery Environment supercomputers, the workflow processed 1,200,000 newly sequenced bacterial proteins. With the rapid expansion of the protein sequence universe, the proposed workflow will enable scientists to annotate big genome data.

Optimizing high performance computing workflow for protein functional annotation

PubMed Central

Stanberry, Larissa; Rekepalli, Bhanu; Liu, Yuan; Giblock, Paul; Higdon, Roger; Montague, Elizabeth; Broomall, William; Kolker, Natali; Kolker, Eugene

2014-01-01

Functional annotation of newly sequenced genomes is one of the major challenges in modern biology. With modern sequencing technologies, the protein sequence universe is rapidly expanding. Newly sequenced bacterial genomes alone contain over 7.5 million proteins. The rate of data generation has far surpassed that of protein annotation. The volume of protein data makes manual curation infeasible, whereas a high compute cost limits the utility of existing automated approaches. In this work, we present an improved and optmized automated workflow to enable large-scale protein annotation. The workflow uses high performance computing architectures and a low complexity classification algorithm to assign proteins into existing clusters of orthologous groups of proteins. On the basis of the Position-Specific Iterative Basic Local Alignment Search Tool the algorithm ensures at least 80% specificity and sensitivity of the resulting classifications. The workflow utilizes highly scalable parallel applications for classification and sequence alignment. Using Extreme Science and Engineering Discovery Environment supercomputers, the workflow processed 1,200,000 newly sequenced bacterial proteins. With the rapid expansion of the protein sequence universe, the proposed workflow will enable scientists to annotate big genome data. PMID:25313296

Metamorphic Proteins: Emergence of Dual Protein Folds from One Primary Sequence.

PubMed

Lella, Muralikrishna; Mahalakshmi, Radhakrishnan

2017-06-20

Every amino acid exhibits a different propensity for distinct structural conformations. Hence, decoding how the primary amino acid sequence undergoes the transition to a defined secondary structure and its final three-dimensional fold is presently considered predictable with reasonable certainty. However, protein sequences that defy the first principles of secondary structure prediction (they attain two different folds) have recently been discovered. Such proteins, aptly named metamorphic proteins, decrease the conformational constraint by increasing flexibility in the secondary structure and thereby result in efficient functionality. In this review, we discuss the major factors driving the conformational switch related both to protein sequence and to structure using illustrative examples. We discuss the concept of an evolutionary transition in sequence and structure, the functional impact of the tertiary fold, and the pressure of intrinsic and external factors that give rise to metamorphic proteins. We mainly focus on the major components of protein architecture, namely, the α-helix and β-sheet segments, which are involved in conformational switching within the same or highly similar sequences. These chameleonic sequences are widespread in both cytosolic and membrane proteins, and these folds are equally important for protein structure and function. We discuss the implications of metamorphic proteins and chameleonic peptide sequences in de novo peptide design.

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

PubMed

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

2016-06-15

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. 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. 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. Our program is freely available for download from http://sfb.kaust.edu.sa/Pages/Software.aspx : xin.gao@kaust.edu.sa Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

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

PubMed

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.

Computationally mapping sequence space to understand evolutionary protein engineering.

PubMed

Armstrong, Kathryn A; Tidor, Bruce

2008-01-01

Evolutionary protein engineering has been dramatically successful, producing a wide variety of new proteins with altered stability, binding affinity, and enzymatic activity. However, the success of such procedures is often unreliable, and the impact of the choice of protein, engineering goal, and evolutionary procedure is not well understood. We have created a framework for understanding aspects of the protein engineering process by computationally mapping regions of feasible sequence space for three small proteins using structure-based design protocols. We then tested the ability of different evolutionary search strategies to explore these sequence spaces. The results point to a non-intuitive relationship between the error-prone PCR mutation rate and the number of rounds of replication. The evolutionary relationships among feasible sequences reveal hub-like sequences that serve as particularly fruitful starting sequences for evolutionary search. Moreover, genetic recombination procedures were examined, and tradeoffs relating sequence diversity and search efficiency were identified. This framework allows us to consider the impact of protein structure on the allowed sequence space and therefore on the challenges that each protein presents to error-prone PCR and genetic recombination procedures.

Rosetta stone method for detecting protein function and protein-protein interactions from genome sequences

DOEpatents

Eisenberg, David; Marcotte, Edward M.; Pellegrini, Matteo; Thompson, Michael J.; Yeates, Todd O.

2002-10-15

A computational method system, and computer program are provided for inferring functional links from genome sequences. One method is based on the observation that some pairs of proteins A' and B' have homologs in another organism fused into a single protein chain AB. A trans-genome comparison of sequences can reveal these AB sequences, which are Rosetta Stone sequences because they decipher an interaction between A' and B. Another method compares the genomic sequence of two or more organisms to create a phylogenetic profile for each protein indicating its presence or absence across all the genomes. The profile provides information regarding functional links between different families of proteins. In yet another method a combination of the above two methods is used to predict functional links.

Protein Information Resource: a community resource for expert annotation of protein data

PubMed Central

Barker, Winona C.; Garavelli, John S.; Hou, Zhenglin; Huang, Hongzhan; Ledley, Robert S.; McGarvey, Peter B.; Mewes, Hans-Werner; Orcutt, Bruce C.; Pfeiffer, Friedhelm; Tsugita, Akira; Vinayaka, C. R.; Xiao, Chunlin; Yeh, Lai-Su L.; Wu, Cathy

2001-01-01

The Protein Information Resource, in collaboration with the Munich Information Center for Protein Sequences (MIPS) and the Japan International Protein Information Database (JIPID), produces the most comprehensive and expertly annotated protein sequence database in the public domain, the PIR-International Protein Sequence Database. To provide timely and high quality annotation and promote database interoperability, the PIR-International employs rule-based and classification-driven procedures based on controlled vocabulary and standard nomenclature and includes status tags to distinguish experimentally determined from predicted protein features. The database contains about 200 000 non-redundant protein sequences, which are classified into families and superfamilies and their domains and motifs identified. Entries are extensively cross-referenced to other sequence, classification, genome, structure and activity databases. The PIR web site features search engines that use sequence similarity and database annotation to facilitate the analysis and functional identification of proteins. The PIR-Inter­national databases and search tools are accessible on the PIR web site at http://pir.georgetown.edu/ and at the MIPS web site at http://www.mips.biochem.mpg.de. The PIR-International Protein Sequence Database and other files are also available by FTP. PMID:11125041

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

PubMed

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.

Protein Sequence Classification with Improved Extreme Learning Machine Algorithms

PubMed Central

2014-01-01

Precisely classifying a protein sequence from a large biological protein sequences database plays an important role for developing competitive pharmacological products. Comparing the unseen sequence with all the identified protein sequences and returning the category index with the highest similarity scored protein, conventional methods are usually time-consuming. Therefore, it is urgent and necessary to build an efficient protein sequence classification system. In this paper, we study the performance of protein sequence classification using SLFNs. The recent efficient extreme learning machine (ELM) and its invariants are utilized as the training algorithms. The optimal pruned ELM is first employed for protein sequence classification in this paper. To further enhance the performance, the ensemble based SLFNs structure is constructed where multiple SLFNs with the same number of hidden nodes and the same activation function are used as ensembles. For each ensemble, the same training algorithm is adopted. The final category index is derived using the majority voting method. Two approaches, namely, the basic ELM and the OP-ELM, are adopted for the ensemble based SLFNs. The performance is analyzed and compared with several existing methods using datasets obtained from the Protein Information Resource center. The experimental results show the priority of the proposed algorithms. PMID:24795876

Special AT-rich sequence binding protein 1 promotes tumor growth and metastasis of esophageal squamous cell carcinoma.

PubMed

Ma, Jun; Wu, Kaiming; Zhao, Zhenxian; Miao, Rong; Xu, Zhe

2017-03-01

Esophageal squamous cell carcinoma is one of the most aggressive malignancies worldwide. Special AT-rich sequence binding protein 1 is a nuclear matrix attachment region binding protein which participates in higher order chromatin organization and tissue-specific gene expression. However, the role of special AT-rich sequence binding protein 1 in esophageal squamous cell carcinoma remains unknown. In this study, western blot and quantitative real-time polymerase chain reaction analysis were performed to identify differentially expressed special AT-rich sequence binding protein 1 in a series of esophageal squamous cell carcinoma tissue samples. The effects of special AT-rich sequence binding protein 1 silencing by two short-hairpin RNAs on cell proliferation, migration, and invasion were assessed by the CCK-8 assay and transwell assays in esophageal squamous cell carcinoma in vitro. Special AT-rich sequence binding protein 1 was significantly upregulated in esophageal squamous cell carcinoma tissue samples and cell lines. Silencing of special AT-rich sequence binding protein 1 inhibited the proliferation of KYSE450 and EC9706 cells which have a relatively high level of special AT-rich sequence binding protein 1, and the ability of migration and invasion of KYSE450 and EC9706 cells was distinctly suppressed. Special AT-rich sequence binding protein 1 could be a potential target for the treatment of esophageal squamous cell carcinoma and inhibition of special AT-rich sequence binding protein 1 may provide a new strategy for the prevention of esophageal squamous cell carcinoma invasion and metastasis.

ProfileGrids: a sequence alignment visualization paradigm that avoids the limitations of Sequence Logos.

PubMed

Roca, Alberto I

2014-01-01

The 2013 BioVis Contest provided an opportunity to evaluate different paradigms for visualizing protein multiple sequence alignments. Such data sets are becoming extremely large and thus taxing current visualization paradigms. Sequence Logos represent consensus sequences but have limitations for protein alignments. As an alternative, ProfileGrids are a new protein sequence alignment visualization paradigm that represents an alignment as a color-coded matrix of the residue frequency occurring at every homologous position in the aligned protein family. The JProfileGrid software program was used to analyze the BioVis contest data sets to generate figures for comparison with the Sequence Logo reference images. The ProfileGrid representation allows for the clear and effective analysis of protein multiple sequence alignments. This includes both a general overview of the conservation and diversity sequence patterns as well as the interactive ability to query the details of the protein residue distributions in the alignment. The JProfileGrid software is free and available from http://www.ProfileGrid.org.

A topological approach for protein classification

DOE PAGES

Cang, Zixuan; Mu, Lin; Wu, Kedi; ...

2015-11-04

Here, protein function and dynamics are closely related to its sequence and structure. However, prediction of protein function and dynamics from its sequence and structure is still a fundamental challenge in molecular biology. Protein classification, which is typically done through measuring the similarity between proteins based on protein sequence or physical information, serves as a crucial step toward the understanding of protein function and dynamics.

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

PubMed

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.

Dissecting the relationship between protein structure and sequence variation

NASA Astrophysics Data System (ADS)

Shahmoradi, Amir; Wilke, Claus; Wilke Lab Team

2015-03-01

Over the past decade several independent works have shown that some structural properties of proteins are capable of predicting protein evolution. The strength and significance of these structure-sequence relations, however, appear to vary widely among different proteins, with absolute correlation strengths ranging from 0 . 1 to 0 . 8 . Here we present the results from a comprehensive search for the potential biophysical and structural determinants of protein evolution by studying more than 200 structural and evolutionary properties in a dataset of 209 monomeric enzymes. We discuss the main protein characteristics responsible for the general patterns of protein evolution, and identify sequence divergence as the main determinant of the strengths of virtually all structure-evolution relationships, explaining ~ 10 - 30 % of observed variation in sequence-structure relations. In addition to sequence divergence, we identify several protein structural properties that are moderately but significantly coupled with the strength of sequence-structure relations. In particular, proteins with more homogeneous back-bone hydrogen bond energies, large fractions of helical secondary structures and low fraction of beta sheets tend to have the strongest sequence-structure relation. BEACON-NSF center for the study of evolution in action.

Protein Interaction Profile Sequencing (PIP-seq).

PubMed

Foley, Shawn W; Gregory, Brian D

2016-10-10

Every eukaryotic RNA transcript undergoes extensive post-transcriptional processing from the moment of transcription up through degradation. This regulation is performed by a distinct cohort of RNA-binding proteins which recognize their target transcript by both its primary sequence and secondary structure. Here, we describe protein interaction profile sequencing (PIP-seq), a technique that uses ribonuclease-based footprinting followed by high-throughput sequencing to globally assess both protein-bound RNA sequences and RNA secondary structure. PIP-seq utilizes single- and double-stranded RNA-specific nucleases in the absence of proteins to infer RNA secondary structure. These libraries are also compared to samples that undergo nuclease digestion in the presence of proteins in order to find enriched protein-bound sequences. Combined, these four libraries provide a comprehensive, transcriptome-wide view of RNA secondary structure and RNA protein interaction sites from a single experimental technique. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

Correlation between protein sequence similarity and x-ray diffraction quality in the protein data bank.

PubMed

Lu, Hui-Meng; Yin, Da-Chuan; Ye, Ya-Jing; Luo, Hui-Min; Geng, Li-Qiang; Li, Hai-Sheng; Guo, Wei-Hong; Shang, Peng

2009-01-01

As the most widely utilized technique to determine the 3-dimensional structure of protein molecules, X-ray crystallography can provide structure of the highest resolution among the developed techniques. The resolution obtained via X-ray crystallography is known to be influenced by many factors, such as the crystal quality, diffraction techniques, and X-ray sources, etc. In this paper, the authors found that the protein sequence could also be one of the factors. We extracted information of the resolution and the sequence of proteins from the Protein Data Bank (PDB), classified the proteins into different clusters according to the sequence similarity, and statistically analyzed the relationship between the sequence similarity and the best resolution obtained. The results showed that there was a pronounced correlation between the sequence similarity and the obtained resolution. These results indicate that protein structure itself is one variable that may affect resolution when X-ray crystallography is used.

Complete nucleotide and derived amino acid sequence of cDNA encoding the mitochondrial uncoupling protein of rat brown adipose tissue: lack of a mitochondrial targeting presequence.

PubMed Central

Ridley, R G; Patel, H V; Gerber, G E; Morton, R C; Freeman, K B

1986-01-01

A cDNA clone spanning the entire amino acid sequence of the nuclear-encoded uncoupling protein of rat brown adipose tissue mitochondria has been isolated and sequenced. With the exception of the N-terminal methionine the deduced N-terminus of the newly synthesized uncoupling protein is identical to the N-terminal 30 amino acids of the native uncoupling protein as determined by protein sequencing. This proves that the protein contains no N-terminal mitochondrial targeting prepiece and that a targeting region must reside within the amino acid sequence of the mature protein. Images PMID:3012461

MIPS: a database for genomes and protein sequences.

PubMed Central

Mewes, H W; Heumann, K; Kaps, A; Mayer, K; Pfeiffer, F; Stocker, S; Frishman, D

1999-01-01

The Munich Information Center for Protein Sequences (MIPS-GSF), Martinsried near Munich, Germany, develops and maintains genome oriented databases. It is commonplace that the amount of sequence data available increases rapidly, but not the capacity of qualified manual annotation at the sequence databases. Therefore, our strategy aims to cope with the data stream by the comprehensive application of analysis tools to sequences of complete genomes, the systematic classification of protein sequences and the active support of sequence analysis and functional genomics projects. This report describes the systematic and up-to-date analysis of genomes (PEDANT), a comprehensive database of the yeast genome (MYGD), a database reflecting the progress in sequencing the Arabidopsis thaliana genome (MATD), the database of assembled, annotated human EST clusters (MEST), and the collection of protein sequence data within the framework of the PIR-International Protein Sequence Database (described elsewhere in this volume). MIPS provides access through its WWW server (http://www.mips.biochem.mpg.de) to a spectrum of generic databases, including the above mentioned as well as a database of protein families (PROTFAM), the MITOP database, and the all-against-all FASTA database. PMID:9847138

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cang, Zixuan; Mu, Lin; Wu, Kedi

Here, protein function and dynamics are closely related to its sequence and structure. However, prediction of protein function and dynamics from its sequence and structure is still a fundamental challenge in molecular biology. Protein classification, which is typically done through measuring the similarity between proteins based on protein sequence or physical information, serves as a crucial step toward the understanding of protein function and dynamics.

Understanding protein evolution: from protein physics to Darwinian selection.

PubMed

Zeldovich, Konstantin B; Shakhnovich, Eugene I

2008-01-01

Efforts in whole-genome sequencing and structural proteomics start to provide a global view of the protein universe, the set of existing protein structures and sequences. However, approaches based on the selection of individual sequences have not been entirely successful at the quantitative description of the distribution of structures and sequences in the protein universe because evolutionary pressure acts on the entire organism, rather than on a particular molecule. In parallel to this line of study, studies in population genetics and phenomenological molecular evolution established a mathematical framework to describe the changes in genome sequences in populations of organisms over time. Here, we review both microscopic (physics-based) and macroscopic (organism-level) models of protein-sequence evolution and demonstrate that bridging the two scales provides the most complete description of the protein universe starting from clearly defined, testable, and physiologically relevant assumptions.

Comparative characterization of random-sequence proteins consisting of 5, 12, and 20 kinds of amino acids

PubMed Central

Tanaka, Junko; Doi, Nobuhide; Takashima, Hideaki; Yanagawa, Hiroshi

2010-01-01

Screening of functional proteins from a random-sequence library has been used to evolve novel proteins in the field of evolutionary protein engineering. However, random-sequence proteins consisting of the 20 natural amino acids tend to aggregate, and the occurrence rate of functional proteins in a random-sequence library is low. From the viewpoint of the origin of life, it has been proposed that primordial proteins consisted of a limited set of amino acids that could have been abundantly formed early during chemical evolution. We have previously found that members of a random-sequence protein library constructed with five primitive amino acids show high solubility (Doi et al., Protein Eng Des Sel 2005;18:279–284). Although such a library is expected to be appropriate for finding functional proteins, the functionality may be limited, because they have no positively charged amino acid. Here, we constructed three libraries of 120-amino acid, random-sequence proteins using alphabets of 5, 12, and 20 amino acids by preselection using mRNA display (to eliminate sequences containing stop codons and frameshifts) and characterized and compared the structural properties of random-sequence proteins arbitrarily chosen from these libraries. We found that random-sequence proteins constructed with the 12-member alphabet (including five primitive amino acids and positively charged amino acids) have higher solubility than those constructed with the 20-member alphabet, though other biophysical properties are very similar in the two libraries. Thus, a library of moderate complexity constructed from 12 amino acids may be a more appropriate resource for functional screening than one constructed from 20 amino acids. PMID:20162614

Diversity of the P2 protein among nontypeable Haemophilus influenzae isolates.

PubMed Central

Bell, J; Grass, S; Jeanteur, D; Munson, R S

1994-01-01

The genes for outer membrane protein P2 of four nontypeable Haemophilus influenzae strains were cloned and sequenced. The derived amino acid sequences were compared with the outer membrane protein P2 sequence from H. influenzae type b MinnA and the sequences of P2 from three additional nontypeable H. influenzae strains. The sequences were 76 to 94% identical. The sequences had regions with considerable variability separated by regions which were highly conserved. The variable regions mapped to putative surface-exposed loops of the protein. PMID:8188390

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

PubMed

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%).

"De-novo" amino acid sequence elucidation of protein G'e by combined "top-down" and "bottom-up" mass spectrometry.

PubMed

Yefremova, Yelena; Al-Majdoub, Mahmoud; Opuni, Kwabena F M; Koy, Cornelia; Cui, Weidong; Yan, Yuetian; Gross, Michael L; Glocker, Michael O

2015-03-01

Mass spectrometric de-novo sequencing was applied to review the amino acid sequence of a commercially available recombinant protein G´ with great scientific and economic importance. Substantial deviations to the published amino acid sequence (Uniprot Q54181) were found by the presence of 46 additional amino acids at the N-terminus, including a so-called "His-tag" as well as an N-terminal partial α-N-gluconoylation and α-N-phosphogluconoylation, respectively. The unexpected amino acid sequence of the commercial protein G' comprised 241 amino acids and resulted in a molecular mass of 25,998.9 ± 0.2 Da for the unmodified protein. Due to the higher mass that is caused by its extended amino acid sequence compared with the original protein G' (185 amino acids), we named this protein "protein G'e." By means of mass spectrometric peptide mapping, the suggested amino acid sequence, as well as the N-terminal partial α-N-gluconoylations, was confirmed with 100% sequence coverage. After the protein G'e sequence was determined, we were able to determine the expression vector pET-28b from Novagen with the Xho I restriction enzyme cleavage site as the best option that was used for cloning and expressing the recombinant protein G'e in E. coli. A dissociation constant (K(d)) value of 9.4 nM for protein G'e was determined thermophoretically, showing that the N-terminal flanking sequence extension did not cause significant changes in the binding affinity to immunoglobulins.

Pfarao: a web application for protein family analysis customized for cytoskeletal and motor proteins (CyMoBase).

PubMed

Odronitz, Florian; Kollmar, Martin

2006-11-29

Annotation of protein sequences of eukaryotic organisms is crucial for the understanding of their function in the cell. Manual annotation is still by far the most accurate way to correctly predict genes. The classification of protein sequences, their phylogenetic relation and the assignment of function involves information from various sources. This often leads to a collection of heterogeneous data, which is hard to track. Cytoskeletal and motor proteins consist of large and diverse superfamilies comprising up to several dozen members per organism. Up to date there is no integrated tool available to assist in the manual large-scale comparative genomic analysis of protein families. Pfarao (Protein Family Application for Retrieval, Analysis and Organisation) is a database driven online working environment for the analysis of manually annotated protein sequences and their relationship. Currently, the system can store and interrelate a wide range of information about protein sequences, species, phylogenetic relations and sequencing projects as well as links to literature and domain predictions. Sequences can be imported from multiple sequence alignments that are generated during the annotation process. A web interface allows to conveniently browse the database and to compile tabular and graphical summaries of its content. We implemented a protein sequence-centric web application to store, organize, interrelate, and present heterogeneous data that is generated in manual genome annotation and comparative genomics. The application has been developed for the analysis of cytoskeletal and motor proteins (CyMoBase) but can easily be adapted for any protein.

Conservation of coevolving protein interfaces bridges prokaryote-eukaryote homologies in the twilight zone.

PubMed

Rodriguez-Rivas, Juan; Marsili, Simone; Juan, David; Valencia, Alfonso

2016-12-27

Protein-protein interactions are fundamental for the proper functioning of the cell. As a result, protein interaction surfaces are subject to strong evolutionary constraints. Recent developments have shown that residue coevolution provides accurate predictions of heterodimeric protein interfaces from sequence information. So far these approaches have been limited to the analysis of families of prokaryotic complexes for which large multiple sequence alignments of homologous sequences can be compiled. We explore the hypothesis that coevolution points to structurally conserved contacts at protein-protein interfaces, which can be reliably projected to homologous complexes with distantly related sequences. We introduce a domain-centered protocol to study the interplay between residue coevolution and structural conservation of protein-protein interfaces. We show that sequence-based coevolutionary analysis systematically identifies residue contacts at prokaryotic interfaces that are structurally conserved at the interface of their eukaryotic counterparts. In turn, this allows the prediction of conserved contacts at eukaryotic protein-protein interfaces with high confidence using solely mutational patterns extracted from prokaryotic genomes. Even in the context of high divergence in sequence (the twilight zone), where standard homology modeling of protein complexes is unreliable, our approach provides sequence-based accurate information about specific details of protein interactions at the residue level. Selected examples of the application of prokaryotic coevolutionary analysis to the prediction of eukaryotic interfaces further illustrate the potential of this approach.

Sequence repeats and protein structure

NASA Astrophysics Data System (ADS)

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

2012-11-01

Repeats are frequently found in known protein sequences. The level of sequence conservation in tandem repeats correlates with their propensities to be intrinsically disordered. We employ a coarse-grained model of a protein with a two-letter amino acid alphabet, hydrophobic (H) and polar (P), to examine the sequence-structure relationship in the realm of repeated sequences. A fraction of repeated sequences comprises a distinct class of bad folders, whose folding temperatures are much lower than those of random sequences. Imperfection in sequence repetition improves the folding properties of the bad folders while deteriorating those of the good folders. Our results may explain why nature has utilized repeated sequences for their versatility and especially to design functional proteins that are intrinsically unstructured at physiological temperatures.

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

PubMed Central

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

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

PubMed

Ramkissoon, Kevin R; Miller, Jennifer K; 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.

Dynamics of domain coverage of the protein sequence universe.

PubMed

Rekapalli, Bhanu; Wuichet, Kristin; Peterson, Gregory D; Zhulin, Igor B

2012-11-16

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". 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. 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.

Recombinant protein secretion in Pseudozyma flocculosa and Pseudozyma antarctica with a novel signal peptide.

PubMed

Cheng, Yali; Avis, Tyler J; Bolduc, Sébastien; Zhao, Yingyi; Anguenot, Raphaël; Neveu, Bertrand; Labbé, Caroline; Belzile, François; Bélanger, Richard R

2008-12-01

Secretion of recombinant proteins aims to reproduce the correct posttranslational modifications of the expressed protein while simplifying its recovery. In this study, secretion signal sequences from an abundantly secreted 34-kDa protein (P34) from Pseudozyma flocculosa were cloned. The efficiency of these sequences in the secretion of recombinant green fluorescent protein (GFP) was investigated in two Pseudozyma species and compared with other secretion signal sequences, from S. cerevisiae and Pseudozyma spp. The results indicate that various secretion signal sequences were functional and that the P34 signal peptide was the most effective secretion signal sequence in both P. flocculosa and P. antarctica. The cells correctly processed the secretion signal sequences, including P34 signal peptide, and mature GFP was recovered from the culture medium. This is the first report of functional secretion signal sequences in P. flocculosa. These sequences can be used to test the secretion of other recombinant proteins and for studying the secretion pathway in P. flocculosa and P. antarctica.

Protein 3D Structure Computed from Evolutionary Sequence Variation

PubMed Central

Sheridan, Robert; Hopf, Thomas A.; Pagnani, Andrea; Zecchina, Riccardo; Sander, Chris

2011-01-01

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 Cα-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 structures, new strategies in protein and drug design, and the identification of functional genetic variants in normal and disease genomes. PMID:22163331

Modeling repetitive, non‐globular proteins

PubMed Central

Basu, Koli; Campbell, Robert L.; Guo, Shuaiqi; Sun, Tianjun

2016-01-01

Abstract While ab initio modeling of protein structures is not routine, certain types of proteins are more straightforward to model than others. Proteins with short repetitive sequences typically exhibit repetitive structures. These repetitive sequences can be more amenable to modeling if some information is known about the predominant secondary structure or other key features of the protein sequence. We have successfully built models of a number of repetitive structures with novel folds using knowledge of the consensus sequence within the sequence repeat and an understanding of the likely secondary structures that these may adopt. Our methods for achieving this success are reviewed here. PMID:26914323

Evaluating the protein coding potential of exonized transposable element sequences

PubMed Central

Piriyapongsa, Jittima; Rutledge, Mark T; Patel, Sanil; Borodovsky, Mark; Jordan, I King

2007-01-01

Background Transposable element (TE) sequences, once thought to be merely selfish or parasitic members of the genomic community, have been shown to contribute a wide variety of functional sequences to their host genomes. Analysis of complete genome sequences have turned up numerous cases where TE sequences have been incorporated as exons into mRNAs, and it is widely assumed that such 'exonized' TEs encode protein sequences. However, the extent to which TE-derived sequences actually encode proteins is unknown and a matter of some controversy. We have tried to address this outstanding issue from two perspectives: i-by evaluating ascertainment biases related to the search methods used to uncover TE-derived protein coding sequences (CDS) and ii-through a probabilistic codon-frequency based analysis of the protein coding potential of TE-derived exons. Results We compared the ability of three classes of sequence similarity search methods to detect TE-derived sequences among data sets of experimentally characterized proteins: 1-a profile-based hidden Markov model (HMM) approach, 2-BLAST methods and 3-RepeatMasker. Profile based methods are more sensitive and more selective than the other methods evaluated. However, the application of profile-based search methods to the detection of TE-derived sequences among well-curated experimentally characterized protein data sets did not turn up many more cases than had been previously detected and nowhere near as many cases as recent genome-wide searches have. We observed that the different search methods used were complementary in the sense that they yielded largely non-overlapping sets of hits and differed in their ability to recover known cases of TE-derived CDS. The probabilistic analysis of TE-derived exon sequences indicates that these sequences have low protein coding potential on average. In particular, non-autonomous TEs that do not encode protein sequences, such as Alu elements, are frequently exonized but unlikely to encode protein sequences. Conclusion The exaptation of the numerous TE sequences found in exons as bona fide protein coding sequences may prove to be far less common than has been suggested by the analysis of complete genomes. We hypothesize that many exonized TE sequences actually function as post-transcriptional regulators of gene expression, rather than coding sequences, which may act through a variety of double stranded RNA related regulatory pathways. Indeed, their relatively high copy numbers and similarity to sequences dispersed throughout the genome suggests that exonized TE sequences could serve as master regulators with a wide scope of regulatory influence. Reviewers: This article was reviewed by Itai Yanai, Kateryna D. Makova, Melissa Wilson (nominated by Kateryna D. Makova) and Cedric Feschotte (nominated by John M. Logsdon Jr.). PMID:18036258

On the Role of Aggregation Prone Regions in Protein Evolution, Stability, and Enzymatic Catalysis: Insights from Diverse Analyses

PubMed Central

Buck, Patrick M.; Kumar, Sandeep; Singh, Satish K.

2013-01-01

The various roles that aggregation prone regions (APRs) are capable of playing in proteins are investigated here via comprehensive analyses of multiple non-redundant datasets containing randomly generated amino acid sequences, monomeric proteins, intrinsically disordered proteins (IDPs) and catalytic residues. Results from this study indicate that the aggregation propensities of monomeric protein sequences have been minimized compared to random sequences with uniform and natural amino acid compositions, as observed by a lower average aggregation propensity and fewer APRs that are shorter in length and more often punctuated by gate-keeper residues. However, evidence for evolutionary selective pressure to disrupt these sequence regions among homologous proteins is inconsistent. APRs are less conserved than average sequence identity among closely related homologues (≥80% sequence identity with a parent) but APRs are more conserved than average sequence identity among homologues that have at least 50% sequence identity with a parent. Structural analyses of APRs indicate that APRs are three times more likely to contain ordered versus disordered residues and that APRs frequently contribute more towards stabilizing proteins than equal length segments from the same protein. Catalytic residues and APRs were also found to be in structural contact significantly more often than expected by random chance. Our findings suggest that proteins have evolved by optimizing their risk of aggregation for cellular environments by both minimizing aggregation prone regions and by conserving those that are important for folding and function. In many cases, these sequence optimizations are insufficient to develop recombinant proteins into commercial products. Rational design strategies aimed at improving protein solubility for biotechnological purposes should carefully evaluate the contributions made by candidate APRs, targeted for disruption, towards protein structure and activity. PMID:24146608

ProfileGrids: a sequence alignment visualization paradigm that avoids the limitations of Sequence Logos

PubMed Central

2014-01-01

Background The 2013 BioVis Contest provided an opportunity to evaluate different paradigms for visualizing protein multiple sequence alignments. Such data sets are becoming extremely large and thus taxing current visualization paradigms. Sequence Logos represent consensus sequences but have limitations for protein alignments. As an alternative, ProfileGrids are a new protein sequence alignment visualization paradigm that represents an alignment as a color-coded matrix of the residue frequency occurring at every homologous position in the aligned protein family. Results The JProfileGrid software program was used to analyze the BioVis contest data sets to generate figures for comparison with the Sequence Logo reference images. Conclusions The ProfileGrid representation allows for the clear and effective analysis of protein multiple sequence alignments. This includes both a general overview of the conservation and diversity sequence patterns as well as the interactive ability to query the details of the protein residue distributions in the alignment. The JProfileGrid software is free and available from http://www.ProfileGrid.org. PMID:25237393

SIMAP--a comprehensive database of pre-calculated protein sequence similarities, domains, annotations and clusters.

PubMed

Rattei, Thomas; Tischler, Patrick; Götz, Stefan; Jehl, Marc-André; Hoser, Jonathan; Arnold, Roland; Conesa, Ana; Mewes, Hans-Werner

2010-01-01

The prediction of protein function as well as the reconstruction of evolutionary genesis employing sequence comparison at large is still the most powerful tool in sequence analysis. Due to the exponential growth of the number of known protein sequences and the subsequent quadratic growth of the similarity matrix, the computation of the Similarity Matrix of Proteins (SIMAP) becomes a computational intensive task. The SIMAP database provides a comprehensive and up-to-date pre-calculation of the protein sequence similarity matrix, sequence-based features and sequence clusters. As of September 2009, SIMAP covers 48 million proteins and more than 23 million non-redundant sequences. Novel features of SIMAP include the expansion of the sequence space by including databases such as ENSEMBL as well as the integration of metagenomes based on their consistent processing and annotation. Furthermore, protein function predictions by Blast2GO are pre-calculated for all sequences in SIMAP and the data access and query functions have been improved. SIMAP assists biologists to query the up-to-date sequence space systematically and facilitates large-scale downstream projects in computational biology. Access to SIMAP is freely provided through the web portal for individuals (http://mips.gsf.de/simap/) and for programmatic access through DAS (http://webclu.bio.wzw.tum.de/das/) and Web-Service (http://mips.gsf.de/webservices/services/SimapService2.0?wsdl).

Use of designed sequences in protein structure recognition.

PubMed

Kumar, Gayatri; Mudgal, Richa; Srinivasan, Narayanaswamy; Sandhya, Sankaran

2018-05-09

Knowledge of the protein structure is a pre-requisite for improved understanding of molecular function. The gap in the sequence-structure space has increased in the post-genomic era. Grouping related protein sequences into families can aid in narrowing the gap. In the Pfam database, structure description is provided for part or full-length proteins of 7726 families. For the remaining 52% of the families, information on 3-D structure is not yet available. We use the computationally designed sequences that are intermediately related to two protein domain families, which are already known to share the same fold. These strategically designed sequences enable detection of distant relationships and here, we have employed them for the purpose of structure recognition of protein families of yet unknown structure. We first measured the success rate of our approach using a dataset of protein families of known fold and achieved a success rate of 88%. Next, for 1392 families of yet unknown structure, we made structural assignments for part/full length of the proteins. Fold association for 423 domains of unknown function (DUFs) are provided as a step towards functional annotation. The results indicate that knowledge-based filling of gaps in protein sequence space is a lucrative approach for structure recognition. Such sequences assist in traversal through protein sequence space and effectively function as 'linkers', where natural linkers between distant proteins are unavailable. This article was reviewed by Oliviero Carugo, Christine Orengo and Srikrishna Subramanian.

Increasing Sequence Diversity with Flexible Backbone Protein Design: The Complete Redesign of a Protein Hydrophobic Core

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murphy, Grant S.; Mills, Jeffrey L.; Miley, Michael J.

2015-10-15

Protein design tests our understanding of protein stability and structure. Successful design methods should allow the exploration of sequence space not found in nature. However, when redesigning naturally occurring protein structures, most fixed backbone design algorithms return amino acid sequences that share strong sequence identity with wild-type sequences, especially in the protein core. This behavior places a restriction on functional space that can be explored and is not consistent with observations from nature, where sequences of low identity have similar structures. Here, we allow backbone flexibility during design to mutate every position in the core (38 residues) of a four-helixmore » bundle protein. Only small perturbations to the backbone, 12 {angstrom}, were needed to entirely mutate the core. The redesigned protein, DRNN, is exceptionally stable (melting point >140C). An NMR and X-ray crystal structure show that the side chains and backbone were accurately modeled (all-atom RMSD = 1.3 {angstrom}).« less

Conservation of Shannon's redundancy for proteins. [information theory applied to amino acid sequences

NASA Technical Reports Server (NTRS)

Gatlin, L. L.

1974-01-01

Concepts of information theory are applied to examine various proteins in terms of their redundancy in natural originators such as animals and plants. The Monte Carlo method is used to derive information parameters for random protein sequences. Real protein sequence parameters are compared with the standard parameters of protein sequences having a specific length. The tendency of a chain to contain some amino acids more frequently than others and the tendency of a chain to contain certain amino acid pairs more frequently than other pairs are used as randomness measures of individual protein sequences. Non-periodic proteins are generally found to have random Shannon redundancies except in cases of constraints due to short chain length and genetic codes. Redundant characteristics of highly periodic proteins are discussed. A degree of periodicity parameter is derived.

The Sorcerer II Global Ocean Sampling expedition: expanding the universe of protein families.

PubMed

Yooseph, Shibu; Sutton, Granger; Rusch, Douglas B; Halpern, Aaron L; Williamson, Shannon J; Remington, Karin; Eisen, Jonathan A; Heidelberg, Karla B; Manning, Gerard; Li, Weizhong; Jaroszewski, Lukasz; Cieplak, Piotr; Miller, Christopher S; Li, Huiying; Mashiyama, Susan T; Joachimiak, Marcin P; van Belle, Christopher; Chandonia, John-Marc; Soergel, David A; Zhai, Yufeng; Natarajan, Kannan; Lee, Shaun; Raphael, Benjamin J; Bafna, Vineet; Friedman, Robert; Brenner, Steven E; Godzik, Adam; Eisenberg, David; Dixon, Jack E; Taylor, Susan S; Strausberg, Robert L; Frazier, Marvin; Venter, J Craig

2007-03-01

Metagenomics projects based on shotgun sequencing of populations of micro-organisms yield insight into protein families. We used sequence similarity clustering to explore proteins with a comprehensive dataset consisting of sequences from available databases together with 6.12 million proteins predicted from an assembly of 7.7 million Global Ocean Sampling (GOS) sequences. The GOS dataset covers nearly all known prokaryotic protein families. A total of 3,995 medium- and large-sized clusters consisting of only GOS sequences are identified, out of which 1,700 have no detectable homology to known families. The GOS-only clusters contain a higher than expected proportion of sequences of viral origin, thus reflecting a poor sampling of viral diversity until now. Protein domain distributions in the GOS dataset and current protein databases show distinct biases. Several protein domains that were previously categorized as kingdom specific are shown to have GOS examples in other kingdoms. About 6,000 sequences (ORFans) from the literature that heretofore lacked similarity to known proteins have matches in the GOS data. The GOS dataset is also used to improve remote homology detection. Overall, besides nearly doubling the number of current proteins, the predicted GOS proteins also add a great deal of diversity to known protein families and shed light on their evolution. These observations are illustrated using several protein families, including phosphatases, proteases, ultraviolet-irradiation DNA damage repair enzymes, glutamine synthetase, and RuBisCO. The diversity added by GOS data has implications for choosing targets for experimental structure characterization as part of structural genomics efforts. Our analysis indicates that new families are being discovered at a rate that is linear or almost linear with the addition of new sequences, implying that we are still far from discovering all protein families in nature.

Can natural proteins designed with 'inverted' peptide sequences adopt native-like protein folds?

PubMed

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.

N-Terminal Amino Acid Sequence Determination of Proteins by N-Terminal Dimethyl Labeling: Pitfalls and Advantages When Compared with Edman Degradation Sequence Analysis.

PubMed

Chang, Elizabeth; Pourmal, Sergei; Zhou, Chun; Kumar, Rupesh; Teplova, Marianna; Pavletich, Nikola P; Marians, Kenneth J; Erdjument-Bromage, Hediye

2016-07-01

In recent history, alternative approaches to Edman sequencing have been investigated, and to this end, the Association of Biomolecular Resource Facilities (ABRF) Protein Sequencing Research Group (PSRG) initiated studies in 2014 and 2015, looking into bottom-up and top-down N-terminal (Nt) dimethyl derivatization of standard quantities of intact proteins with the aim to determine Nt sequence information. We have expanded this initiative and used low picomole amounts of myoglobin to determine the efficiency of Nt-dimethylation. Application of this approach on protein domains, generated by limited proteolysis of overexpressed proteins, confirms that it is a universal labeling technique and is very sensitive when compared with Edman sequencing. Finally, we compared Edman sequencing and Nt-dimethylation of the same polypeptide fragments; results confirm that there is agreement in the identity of the Nt amino acid sequence between these 2 methods.

De novo protein sequencing by combining top-down and bottom-up tandem mass spectra.

PubMed

Liu, Xiaowen; Dekker, Lennard J M; Wu, Si; Vanduijn, Martijn M; Luider, Theo M; Tolić, Nikola; Kou, Qiang; Dvorkin, Mikhail; Alexandrova, Sonya; Vyatkina, Kira; Paša-Tolić, Ljiljana; Pevzner, Pavel A

2014-07-03

There are two approaches for de novo protein sequencing: Edman degradation and mass spectrometry (MS). Existing MS-based methods characterize a novel protein by assembling tandem mass spectra of overlapping peptides generated from multiple proteolytic digestions of the protein. Because each tandem mass spectrum covers only a short peptide of the target protein, the key to high coverage protein sequencing is to find spectral pairs from overlapping peptides in order to assemble tandem mass spectra to long ones. However, overlapping regions of peptides may be too short to be confidently identified. High-resolution mass spectrometers have become accessible to many laboratories. These mass spectrometers are capable of analyzing molecules of large mass values, boosting the development of top-down MS. Top-down tandem mass spectra cover whole proteins. However, top-down tandem mass spectra, even combined, rarely provide full ion fragmentation coverage of a protein. We propose an algorithm, TBNovo, for de novo protein sequencing by combining top-down and bottom-up MS. In TBNovo, a top-down tandem mass spectrum is utilized as a scaffold, and bottom-up tandem mass spectra are aligned to the scaffold to increase sequence coverage. Experiments on data sets of two proteins showed that TBNovo achieved high sequence coverage and high sequence accuracy.

Pfarao: a web application for protein family analysis customized for cytoskeletal and motor proteins (CyMoBase)

PubMed Central

Odronitz, Florian; Kollmar, Martin

2006-01-01

Background Annotation of protein sequences of eukaryotic organisms is crucial for the understanding of their function in the cell. Manual annotation is still by far the most accurate way to correctly predict genes. The classification of protein sequences, their phylogenetic relation and the assignment of function involves information from various sources. This often leads to a collection of heterogeneous data, which is hard to track. Cytoskeletal and motor proteins consist of large and diverse superfamilies comprising up to several dozen members per organism. Up to date there is no integrated tool available to assist in the manual large-scale comparative genomic analysis of protein families. Description Pfarao (Protein Family Application for Retrieval, Analysis and Organisation) is a database driven online working environment for the analysis of manually annotated protein sequences and their relationship. Currently, the system can store and interrelate a wide range of information about protein sequences, species, phylogenetic relations and sequencing projects as well as links to literature and domain predictions. Sequences can be imported from multiple sequence alignments that are generated during the annotation process. A web interface allows to conveniently browse the database and to compile tabular and graphical summaries of its content. Conclusion We implemented a protein sequence-centric web application to store, organize, interrelate, and present heterogeneous data that is generated in manual genome annotation and comparative genomics. The application has been developed for the analysis of cytoskeletal and motor proteins (CyMoBase) but can easily be adapted for any protein. PMID:17134497

Confirmation of the "protein-traffic-hypothesis" and the "protein-localization-hypothesis" using the diabetes-mellitus-type-1-knock-in and transgenic-murine-models and the trepitope sequences.

PubMed

Arneth, Borros

2012-10-01

As possible mechanisms to explain the emergence of autoimmune diseases, the current author has suggested in earlier papers two new pathways: the "protein localization hypothesis" and the "protein traffic hypothesis". The "protein localization hypothesis" states that an autoimmune disease develops if a protein accumulates in a previously unoccupied compartment, that did not previously contain that protein. Similarly, the "protein traffic hypothesis" states that a sudden error within the transport of a certain protein leads to the emergence of an autoimmune disease. The current article discusses the usefulness of the different commercially available transgenic murine models of diabetes mellitus type 1 to confirm the aforementioned hypotheses. This discussion shows that several transgenic murine models of diabetes mellitus type 1 are in-line and confirm the aforementioned hypotheses. Furthermore, these hypotheses are additionally inline with the occurrence of several newly discovered protein sequences, the so-called trepitope sequences. These sequences modulate the immune response to certain proteins. The current study analyzed to what extent the hypotheses are supported by the occurrence of these new sequences. Thereby the occurrence of the trepitope sequences provides additional evidence supporting the aforementioned hypotheses. Both the "protein localization hypothesis" and the "protein traffic hypothesis" have the potential to lead to new causal therapy concepts. The "protein localization hypothesis" and the "protein traffic hypothesis" provide conceptional explanations for the diabetes mouse models as well as for the newly discovered trepitope sequences. Copyright © 2012 Elsevier Ltd. All rights reserved.

Dynamics of domain coverage of the protein sequence universe

PubMed Central

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

Rational Protein Engineering Guided by Deep Mutational Scanning

PubMed Central

Shin, HyeonSeok; Cho, Byung-Kwan

2015-01-01

Sequence–function relationship in a protein is commonly determined by the three-dimensional protein structure followed by various biochemical experiments. However, with the explosive increase in the number of genome sequences, facilitated by recent advances in sequencing technology, the gap between protein sequences available and three-dimensional structures is rapidly widening. A recently developed method termed deep mutational scanning explores the functional phenotype of thousands of mutants via massive sequencing. Coupled with a highly efficient screening system, this approach assesses the phenotypic changes made by the substitution of each amino acid sequence that constitutes a protein. Such an informational resource provides the functional role of each amino acid sequence, thereby providing sufficient rationale for selecting target residues for protein engineering. Here, we discuss the current applications of deep mutational scanning and consider experimental design. PMID:26404267

Chameleon sequences in neurodegenerative diseases.

PubMed

Bahramali, Golnaz; Goliaei, Bahram; Minuchehr, Zarrin; Salari, Ali

2016-03-25

Chameleon sequences can adopt either alpha helix sheet or a coil conformation. Defining chameleon sequences in PDB (Protein Data Bank) may yield to an insight on defining peptides and proteins responsible in neurodegeneration. In this research, we benefitted from the large PDB and performed a sequence analysis on Chameleons, where we developed an algorithm to extract peptide segments with identical sequences, but different structures. In order to find new chameleon sequences, we extracted a set of 8315 non-redundant protein sequences from the PDB with an identity less than 25%. Our data was classified to "helix to strand (HE)", "helix to coil (HC)" and "strand to coil (CE)" alterations. We also analyzed the occurrence of singlet and doublet amino acids and the solvent accessibility in the chameleon sequences; we then sorted out the proteins with the most number of chameleon sequences and named them Chameleon Flexible Proteins (CFPs) in our dataset. Our data revealed that Gly, Val, Ile, Tyr and Phe, are the major amino acids in Chameleons. We also found that there are proteins such as Insulin Degrading Enzyme IDE and GTP-binding nuclear protein Ran (RAN) with the most number of chameleons (640 and 405 respectively). These proteins have known roles in neurodegenerative diseases. Therefore it can be inferred that other CFP's can serve as key proteins in neurodegeneration, and a study on them can shed light on curing and preventing neurodegenerative diseases. Copyright © 2016 Elsevier Inc. All rights reserved.

Chameleon sequences in neurodegenerative diseases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bahramali, Golnaz; Goliaei, Bahram, E-mail: goliaei@ut.ac.ir; Minuchehr, Zarrin, E-mail: minuchehr@nigeb.ac.ir

2016-03-25

Chameleon sequences can adopt either alpha helix sheet or a coil conformation. Defining chameleon sequences in PDB (Protein Data Bank) may yield to an insight on defining peptides and proteins responsible in neurodegeneration. In this research, we benefitted from the large PDB and performed a sequence analysis on Chameleons, where we developed an algorithm to extract peptide segments with identical sequences, but different structures. In order to find new chameleon sequences, we extracted a set of 8315 non-redundant protein sequences from the PDB with an identity less than 25%. Our data was classified to “helix to strand (HE)”, “helix tomore » coil (HC)” and “strand to coil (CE)” alterations. We also analyzed the occurrence of singlet and doublet amino acids and the solvent accessibility in the chameleon sequences; we then sorted out the proteins with the most number of chameleon sequences and named them Chameleon Flexible Proteins (CFPs) in our dataset. Our data revealed that Gly, Val, Ile, Tyr and Phe, are the major amino acids in Chameleons. We also found that there are proteins such as Insulin Degrading Enzyme IDE and GTP-binding nuclear protein Ran (RAN) with the most number of chameleons (640 and 405 respectively). These proteins have known roles in neurodegenerative diseases. Therefore it can be inferred that other CFP's can serve as key proteins in neurodegeneration, and a study on them can shed light on curing and preventing neurodegenerative diseases.« less

Comparative analysis of ribosomal protein L5 sequences from bacteria of the genus Thermus.

PubMed

Jahn, O; Hartmann, R K; Boeckh, T; Erdmann, V A

1991-06-01

The genes for the ribosomal 5S rRNA binding protein L5 have been cloned from three extremely thermophilic eubacteria, Thermus flavus, Thermus thermophilus HB8 and Thermus aquaticus (Jahn et al, submitted). Genes for protein L5 from the three Thermus strains display 95% G/C in third positions of codons. Amino acid sequences deduced from the DNA sequence were shown to be identical for T flavus and T thermophilus, although the corresponding DNA sequences differed by two T to C transitions in the T thermophilus gene. Protein L5 sequences from T flavus and T thermophilus are 95% homologous to L5 from T aquaticus and 56.5% homologous to the corresponding E coli sequence. The lowest degrees of homology were found between the T flavus/T thermophilus L5 proteins and those of yeast L16 (27.5%), Halobacterium marismortui (34.0%) and Methanococcus vannielii (36.6%). From sequence comparison it becomes clear that thermostability of Thermus L5 proteins is achieved by an increase in hydrophobic interactions and/or by restriction of steric flexibility due to the introduction of amino acids with branched aliphatic side chains such as leucine. Alignment of the nine protein sequences equivalent to Thermus L5 proteins led to identification of a conserved internal segment, rich in acidic amino acids, which shows homology to subsequences of E coli L18 and L25. The occurrence of conserved sequence elements in 5S rRNA binding proteins and ribosomal proteins in general is discussed in terms of evolution and function.

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

PubMed

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.

FastRNABindR: Fast and Accurate Prediction of Protein-RNA Interface Residues.

PubMed

El-Manzalawy, Yasser; Abbas, Mostafa; Malluhi, Qutaibah; Honavar, Vasant

2016-01-01

A wide range of biological processes, including regulation of gene expression, protein synthesis, and replication and assembly of many viruses are mediated by RNA-protein interactions. However, experimental determination of the structures of protein-RNA complexes is expensive and technically challenging. Hence, a number of computational tools have been developed for predicting protein-RNA interfaces. Some of the state-of-the-art protein-RNA interface predictors rely on position-specific scoring matrix (PSSM)-based encoding of the protein sequences. The computational efforts needed for generating PSSMs severely limits the practical utility of protein-RNA interface prediction servers. In this work, we experiment with two approaches, random sampling and sequence similarity reduction, for extracting a representative reference database of protein sequences from more than 50 million protein sequences in UniRef100. Our results suggest that random sampled databases produce better PSSM profiles (in terms of the number of hits used to generate the profile and the distance of the generated profile to the corresponding profile generated using the entire UniRef100 data as well as the accuracy of the machine learning classifier trained using these profiles). Based on our results, we developed FastRNABindR, an improved version of RNABindR for predicting protein-RNA interface residues using PSSM profiles generated using 1% of the UniRef100 sequences sampled uniformly at random. To the best of our knowledge, FastRNABindR is the only protein-RNA interface residue prediction online server that requires generation of PSSM profiles for query sequences and accepts hundreds of protein sequences per submission. Our approach for determining the optimal BLAST database for a protein-RNA interface residue classification task has the potential of substantially speeding up, and hence increasing the practical utility of, other amino acid sequence based predictors of protein-protein and protein-DNA interfaces.

A novel class of plant-specific zinc-dependent DNA-binding protein that binds to A/T-rich DNA sequences

PubMed Central

Nagano, Yukio; Furuhashi, Hirofumi; Inaba, Takehito; Sasaki, Yukiko

2001-01-01

Complementary DNA encoding a DNA-binding protein, designated PLATZ1 (plant AT-rich sequence- and zinc-binding protein 1), was isolated from peas. The amino acid sequence of the protein is similar to those of other uncharacterized proteins predicted from the genome sequences of higher plants. However, no paralogous sequences have been found outside the plant kingdom. Multiple alignments among these paralogous proteins show that several cysteine and histidine residues are invariant, suggesting that these proteins are a novel class of zinc-dependent DNA-binding proteins with two distantly located regions, C-x2-H-x11-C-x2-C-x(4–5)-C-x2-C-x(3–7)-H-x2-H and C-x2-C-x(10–11)-C-x3-C. In an electrophoretic mobility shift assay, the zinc chelator 1,10-o-phenanthroline inhibited DNA binding, and two distant zinc-binding regions were required for DNA binding. A protein blot with 65ZnCl2 showed that both regions are required for zinc-binding activity. The PLATZ1 protein non-specifically binds to A/T-rich sequences, including the upstream region of the pea GTPase pra2 and plastocyanin petE genes. Expression of the PLATZ1 repressed those of the reporter constructs containing the coding sequence of luciferase gene driven by the cauliflower mosaic virus (CaMV) 35S90 promoter fused to the tandem repeat of the A/T-rich sequences. These results indicate that PLATZ1 is a novel class of plant-specific zinc-dependent DNA-binding protein responsible for A/T-rich sequence-mediated transcriptional repression. PMID:11600698

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

PubMed Central

Sevy, Alexander M.; Jacobs, Tim M.; Crowe, James E.; Meiler, Jens

2015-01-01

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. PMID:26147100

Overproduction, purification, and ATPase activity of the Escherichia coli RuvB protein involved in DNA repair.

PubMed Central

Iwasaki, H; Shiba, T; Makino, K; Nakata, A; Shinagawa, H

1989-01-01

The ruvA and ruvB genes of Escherichia coli constitute an operon which belongs to the SOS regulon. Genetic evidence suggests that the products of the ruv operon are involved in DNA repair and recombination. To begin biochemical characterization of these proteins, we developed a plasmid system that overproduced RuvB protein to 20% of total cell protein. Starting from the overproducing system, we purified RuvB protein. The purified RuvB protein behaved like a monomer in gel filtration chromatography and had an apparent relative molecular mass of 38 kilodaltons in sodium dodecyl sulfate-polyacrylamide gel electrophoresis, which agrees with the value predicted from the DNA sequence. The amino acid sequence of the amino-terminal region of the purified protein was analyzed, and the sequence agreed with the one deduced from the DNA sequence. Since the deduced sequence of RuvB protein contained the consensus sequence for ATP-binding proteins, we examined the ATP-binding and ATPase activities of the purified RuvB protein. RuvB protein had a stronger affinity to ADP than to ATP and weak ATPase activity. The results suggest that the weak ATPase activity of RuvB protein is at least partly due to end product inhibition by ADP. Images PMID:2529252

A combined de novo protein sequencing and cDNA library approach to the venomic analysis of Chinese spider Araneus ventricosus.

PubMed

Duan, Zhigui; Cao, Rui; Jiang, Liping; Liang, Songping

2013-01-14

In past years, spider venoms have attracted increasing attention due to their extraordinary chemical and pharmacological diversity. The recently popularized proteomic method highly improved our ability to analyze the proteins in the venom. However, the lack of information about isolated venom proteins sequences dramatically limits the ability to confidently identify venom proteins. In the present paper, the venom from Araneus ventricosus was analyzed using two complementary approaches: 2-DE/Shotgun-LC-MS/MS coupled to MASCOT search and 2-DE/Shotgun-LC-MS/MS coupled to manual de novo sequencing followed by local venom protein database (LVPD) search. The LVPD was constructed with toxin-like protein sequences obtained from the analysis of cDNA library from A. ventricosus venom glands. Our results indicate that a total of 130 toxin-like protein sequences were unambiguously identified by manual de novo sequencing coupled to LVPD search, accounting for 86.67% of all toxin-like proteins in LVPD. Thus manual de novo sequencing coupled to LVPD search was proved an extremely effective approach for the analysis of venom proteins. In addition, the approach displays impeccable advantage in validating mutant positions of isoforms from the same toxin-like family. Intriguingly, methyl esterifcation of glutamic acid was discovered for the first time in animal venom proteins by manual de novo sequencing. Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.

CDSbank: taxonomy-aware extraction, selection, renaming and formatting of protein-coding DNA or amino acid sequences.

PubMed

Hazes, Bart

2014-02-28

Protein-coding DNA sequences and their corresponding amino acid sequences are routinely used to study relationships between sequence, structure, function, and evolution. The rapidly growing size of sequence databases increases the power of such comparative analyses but it makes it more challenging to prepare high quality sequence data sets with control over redundancy, quality, completeness, formatting, and labeling. Software tools for some individual steps in this process exist but manual intervention remains a common and time consuming necessity. CDSbank is a database that stores both the protein-coding DNA sequence (CDS) and amino acid sequence for each protein annotated in Genbank. CDSbank also stores Genbank feature annotation, a flag to indicate incomplete 5' and 3' ends, full taxonomic data, and a heuristic to rank the scientific interest of each species. This rich information allows fully automated data set preparation with a level of sophistication that aims to meet or exceed manual processing. Defaults ensure ease of use for typical scenarios while allowing great flexibility when needed. Access is via a free web server at http://hazeslab.med.ualberta.ca/CDSbank/. CDSbank presents a user-friendly web server to download, filter, format, and name large sequence data sets. Common usage scenarios can be accessed via pre-programmed default choices, while optional sections give full control over the processing pipeline. Particular strengths are: extract protein-coding DNA sequences just as easily as amino acid sequences, full access to taxonomy for labeling and filtering, awareness of incomplete sequences, and the ability to take one protein sequence and extract all synonymous CDS or identical protein sequences in other species. Finally, CDSbank can also create labeled property files to, for instance, annotate or re-label phylogenetic trees.

Assigning protein functions by comparative genome analysis protein phylogenetic profiles

DOEpatents

Pellegrini, Matteo; Marcotte, Edward M.; Thompson, Michael J.; Eisenberg, David; Grothe, Robert; Yeates, Todd O.

2003-05-13

A computational method system, and computer program are provided for inferring functional links from genome sequences. One method is based on the observation that some pairs of proteins A' and B' have homologs in another organism fused into a single protein chain AB. A trans-genome comparison of sequences can reveal these AB sequences, which are Rosetta Stone sequences because they decipher an interaction between A' and B. Another method compares the genomic sequence of two or more organisms to create a phylogenetic profile for each protein indicating its presence or absence across all the genomes. The profile provides information regarding functional links between different families of proteins. In yet another method a combination of the above two methods is used to predict functional links.

PASS2: an automated database of protein alignments organised as structural superfamilies.

PubMed

Bhaduri, Anirban; Pugalenthi, Ganesan; Sowdhamini, Ramanathan

2004-04-02

The functional selection and three-dimensional structural constraints of proteins in nature often relates to the retention of significant sequence similarity between proteins of similar fold and function despite poor sequence identity. Organization of structure-based sequence alignments for distantly related proteins, provides a map of the conserved and critical regions of the protein universe that is useful for the analysis of folding principles, for the evolutionary unification of protein families and for maximizing the information return from experimental structure determination. The Protein Alignment organised as Structural Superfamily (PASS2) database represents continuously updated, structural alignments for evolutionary related, sequentially distant proteins. An automated and updated version of PASS2 is, in direct correspondence with SCOP 1.63, consisting of sequences having identity below 40% among themselves. Protein domains have been grouped into 628 multi-member superfamilies and 566 single member superfamilies. Structure-based sequence alignments for the superfamilies have been obtained using COMPARER, while initial equivalencies have been derived from a preliminary superposition using LSQMAN or STAMP 4.0. The final sequence alignments have been annotated for structural features using JOY4.0. The database is supplemented with sequence relatives belonging to different genomes, conserved spatially interacting and structural motifs, probabilistic hidden markov models of superfamilies based on the alignments and useful links to other databases. Probabilistic models and sensitive position specific profiles obtained from reliable superfamily alignments aid annotation of remote homologues and are useful tools in structural and functional genomics. PASS2 presents the phylogeny of its members both based on sequence and structural dissimilarities. Clustering of members allows us to understand diversification of the family members. The search engine has been improved for simpler browsing of the database. The database resolves alignments among the structural domains consisting of evolutionarily diverged set of sequences. Availability of reliable sequence alignments of distantly related proteins despite poor sequence identity and single-member superfamilies permit better sampling of structures in libraries for fold recognition of new sequences and for the understanding of protein structure-function relationships of individual superfamilies. PASS2 is accessible at http://www.ncbs.res.in/~faculty/mini/campass/pass2.html

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

PubMed

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.

Computational analysis of sequence selection mechanisms.

PubMed

Meyerguz, Leonid; Grasso, Catherine; Kleinberg, Jon; Elber, Ron

2004-04-01

Mechanisms leading to gene variations are responsible for the diversity of species and are important components of the theory of evolution. One constraint on gene evolution is that of protein foldability; the three-dimensional shapes of proteins must be thermodynamically stable. We explore the impact of this constraint and calculate properties of foldable sequences using 3660 structures from the Protein Data Bank. We seek a selection function that receives sequences as input, and outputs survival probability based on sequence fitness to structure. We compute the number of sequences that match a particular protein structure with energy lower than the native sequence, the density of the number of sequences, the entropy, and the "selection" temperature. The mechanism of structure selection for sequences longer than 200 amino acids is approximately universal. For shorter sequences, it is not. We speculate on concrete evolutionary mechanisms that show this behavior.

Sequence-similar, structure-dissimilar protein pairs in the PDB.

PubMed

Kosloff, Mickey; Kolodny, Rachel

2008-05-01

It is often assumed that in the Protein Data Bank (PDB), two proteins with similar sequences will also have similar structures. Accordingly, it has proved useful to develop subsets of the PDB from which "redundant" structures have been removed, based on a sequence-based criterion for similarity. Similarly, when predicting protein structure using homology modeling, if a template structure for modeling a target sequence is selected by sequence alone, this implicitly assumes that all sequence-similar templates are equivalent. Here, we show that this assumption is often not correct and that standard approaches to create subsets of the PDB can lead to the loss of structurally and functionally important information. We have carried out sequence-based structural superpositions and geometry-based structural alignments of a large number of protein pairs to determine the extent to which sequence similarity ensures structural similarity. We find many examples where two proteins that are similar in sequence have structures that differ significantly from one another. The source of the structural differences usually has a functional basis. The number of such proteins pairs that are identified and the magnitude of the dissimilarity depend on the approach that is used to calculate the differences; in particular sequence-based structure superpositioning will identify a larger number of structurally dissimilar pairs than geometry-based structural alignments. When two sequences can be aligned in a statistically meaningful way, sequence-based structural superpositioning provides a meaningful measure of structural differences. This approach and geometry-based structure alignments reveal somewhat different information and one or the other might be preferable in a given application. Our results suggest that in some cases, notably homology modeling, the common use of nonredundant datasets, culled from the PDB based on sequence, may mask important structural and functional information. We have established a data base of sequence-similar, structurally dissimilar protein pairs that will help address this problem (http://luna.bioc.columbia.edu/rachel/seqsimstrdiff.htm).

Evaluating the efficacy of a structure-derived amino acid substitution matrix in detecting protein homologs by BLAST and PSI-BLAST.

PubMed

Goonesekere, Nalin Cw

2009-01-01

The large numbers of protein sequences generated by whole genome sequencing projects require rapid and accurate methods of annotation. The detection of homology through computational sequence analysis is a powerful tool in determining the complex evolutionary and functional relationships that exist between proteins. Homology search algorithms employ amino acid substitution matrices to detect similarity between proteins sequences. The substitution matrices in common use today are constructed using sequences aligned without reference to protein structure. Here we present amino acid substitution matrices constructed from the alignment of a large number of protein domain structures from the structural classification of proteins (SCOP) database. We show that when incorporated into the homology search algorithms BLAST and PSI-blast, the structure-based substitution matrices enhance the efficacy of detecting remote homologs.

Sequencing proteins with transverse ionic transport in nanochannels.

PubMed

Boynton, Paul; Di Ventra, Massimiliano

2016-05-03

De novo protein sequencing is essential for understanding cellular processes that govern the function of living organisms and all sequence modifications that occur after a protein has been constructed from its corresponding DNA code. By obtaining the order of the amino acids that compose a given protein one can then determine both its secondary and tertiary structures through structure prediction, which is used to create models for protein aggregation diseases such as Alzheimer's Disease. Here, we propose a new technique for de novo protein sequencing that involves translocating a polypeptide through a synthetic nanochannel and measuring the ionic current of each amino acid through an intersecting perpendicular nanochannel. We find that the distribution of ionic currents for each of the 20 proteinogenic amino acids encoded by eukaryotic genes is statistically distinct, showing this technique's potential for de novo protein sequencing.

Evolution of EF-hand calcium-modulated proteins. III. Exon sequences confirm most dendrograms based on protein sequences: calmodulin dendrograms show significant lack of parallelism

NASA Technical Reports Server (NTRS)

Nakayama, S.; Kretsinger, R. H.

1993-01-01

In the first report in this series we presented dendrograms based on 152 individual proteins of the EF-hand family. In the second we used sequences from 228 proteins, containing 835 domains, and showed that eight of the 29 subfamilies are congruent and that the EF-hand domains of the remaining 21 subfamilies have diverse evolutionary histories. In this study we have computed dendrograms within and among the EF-hand subfamilies using the encoding DNA sequences. In most instances the dendrograms based on protein and on DNA sequences are very similar. Significant differences between protein and DNA trees for calmodulin remain unexplained. In our fourth report we evaluate the sequences and the distribution of introns within the EF-hand family and conclude that exon shuffling did not play a significant role in its evolution.

Application of 2D graphic representation of protein sequence based on Huffman tree method.

PubMed

Qi, Zhao-Hui; Feng, Jun; Qi, Xiao-Qin; Li, Ling

2012-05-01

Based on Huffman tree method, we propose a new 2D graphic representation of protein sequence. This representation can completely avoid loss of information in the transfer of data from a protein sequence to its graphic representation. The method consists of two parts. One is about the 0-1 codes of 20 amino acids by Huffman tree with amino acid frequency. The amino acid frequency is defined as the statistical number of an amino acid in the analyzed protein sequences. The other is about the 2D graphic representation of protein sequence based on the 0-1 codes. Then the applications of the method on ten ND5 genes and seven Escherichia coli strains are presented in detail. The results show that the proposed model may provide us with some new sights to understand the evolution patterns determined from protein sequences and complete genomes. Copyright © 2012 Elsevier Ltd. All rights reserved.

The hypervariable region 1 protein of hepatitis C virus broadly reactive with sera of patients with chronic hepatitis C has a similar amino acid sequence with the consensus sequence.

PubMed

Watanabe, K; Yoshioka, K; Ito, H; Ishigami, M; Takagi, K; Utsunomiya, S; Kobayashi, M; Kishimoto, H; Yano, M; Kakumu, S

1999-11-10

Hypervariable region 1 (HVR1) proteins of hepatitis C virus (HCV) have been reported to react broadly with sera of patients with HCV infection. However, the variability of the broad reactivity of individual HVR1 proteins has not been elucidated. We assessed the reactivity of 25 different HVR1 proteins (genotype 1b) with sera of 81 patients with HCV infection (genotype 1b) by Western blot. HVR1 proteins reacted with 2-60 sera. The number of sera reactive with each HVR1 protein significantly correlated with the number of amino acid residues identical to the consensus sequence defined by Puntoriero et al. (G. Puntoriero, A. Lahm, S. Zucchelli, B. B. Ercole, R. Tafi, M. Penzzanera, M. U. Mondelli, R. Cortese, A. Tramontano, G. Galfre', and A. Nicosia. 1998. EMBO J. 17, 3521-3533. ) (r = 0.561, P < 0.005). The most widely reactive HVR1 protein, 12-22, had a sequence similar to the consensus sequence. The peptide with C-terminal 13-amino-acids sequence of HVR1 protein 12-22 (NH2-CSFTSLFTPGPSQK) was injected into rabbits as an immunogen. The rabbit immune sera reacted with 9 of 25 HVR1 proteins of genotype 1b including HVR1 protein 12-22 and with 3 of 12 proteins of genotype 2a. These results indicate that the HVR1 protein broadly reactive with patients' sera has a sequence similar to the consensus sequence, can induce broadly reactive sera, and could be one of the candidate immunogens in a prophylactic vaccine against HCV. Copyright 1999 Academic Press.

The eukaryotic signal sequence, YGRL, targets the chlamydial inclusion

PubMed Central

Kabeiseman, Emily J.; Cichos, Kyle H.; Moore, Elizabeth R.

2014-01-01

Understanding how host proteins are targeted to pathogen-specified organelles, like the chlamydial inclusion, is fundamentally important to understanding the biogenesis of these unique subcellular compartments and how they maintain autonomy within the cell. Syntaxin 6, which localizes to the chlamydial inclusion, contains an YGRL signal sequence. The YGRL functions to return syntaxin 6 to the trans-Golgi from the plasma membrane, and deletion of the YGRL signal sequence from syntaxin 6 also prevents the protein from localizing to the chlamydial inclusion. YGRL is one of three YXXL (YGRL, YQRL, and YKGL) signal sequences which target proteins to the trans-Golgi. We designed various constructs of eukaryotic proteins to test the specificity and propensity of YXXL sequences to target the inclusion. The YGRL signal sequence redirects proteins (e.g., Tgn38, furin, syntaxin 4) that normally do not localize to the chlamydial inclusion. Further, the requirement of the YGRL signal sequence for syntaxin 6 localization to inclusions formed by different species of Chlamydia is conserved. These data indicate that there is an inherent property of the chlamydial inclusion, which allows it to recognize the YGRL signal sequence. To examine whether this “inherent property” was protein or lipid in nature, we asked if deletion of the YGRL signal sequence from syntaxin 6 altered the ability of the protein to interact with proteins or lipids. Deletion or alteration of the YGRL from syntaxin 6 does not appreciably impact syntaxin 6-protein interactions, but does decrease syntaxin 6-lipid interactions. Intriguingly, data also demonstrate that YKGL or YQRL can successfully substitute for YGRL in localization of syntaxin 6 to the chlamydial inclusion. Importantly and for the first time, we are establishing that a eukaryotic signal sequence targets the chlamydial inclusion. PMID:25309881

Different evolutionary patterns of SNPs between domains and unassigned regions in human protein-coding sequences.

PubMed

Pang, Erli; Wu, Xiaomei; Lin, Kui

2016-06-01

Protein evolution plays an important role in the evolution of each genome. Because of their functional nature, in general, most of their parts or sites are differently constrained selectively, particularly by purifying selection. Most previous studies on protein evolution considered individual proteins in their entirety or compared protein-coding sequences with non-coding sequences. Less attention has been paid to the evolution of different parts within each protein of a given genome. To this end, based on PfamA annotation of all human proteins, each protein sequence can be split into two parts: domains or unassigned regions. Using this rationale, single nucleotide polymorphisms (SNPs) in protein-coding sequences from the 1000 Genomes Project were mapped according to two classifications: SNPs occurring within protein domains and those within unassigned regions. With these classifications, we found: the density of synonymous SNPs within domains is significantly greater than that of synonymous SNPs within unassigned regions; however, the density of non-synonymous SNPs shows the opposite pattern. We also found there are signatures of purifying selection on both the domain and unassigned regions. Furthermore, the selective strength on domains is significantly greater than that on unassigned regions. In addition, among all of the human protein sequences, there are 117 PfamA domains in which no SNPs are found. Our results highlight an important aspect of protein domains and may contribute to our understanding of protein evolution.

Prediction of Spontaneous Protein Deamidation from Sequence-Derived Secondary Structure and Intrinsic Disorder.

PubMed

Lorenzo, J Ramiro; Alonso, Leonardo G; Sánchez, Ignacio E

2015-01-01

Asparagine residues in proteins undergo spontaneous deamidation, a post-translational modification that may act as a molecular clock for the regulation of protein function and turnover. Asparagine deamidation is modulated by protein local sequence, secondary structure and hydrogen bonding. We present NGOME, an algorithm able to predict non-enzymatic deamidation of internal asparagine residues in proteins in the absence of structural data, using sequence-based predictions of secondary structure and intrinsic disorder. Compared to previous algorithms, NGOME does not require three-dimensional structures yet yields better predictions than available sequence-only methods. Four case studies of specific proteins show how NGOME may help the user identify deamidation-prone asparagine residues, often related to protein gain of function, protein degradation or protein misfolding in pathological processes. A fifth case study applies NGOME at a proteomic scale and unveils a correlation between asparagine deamidation and protein degradation in yeast. NGOME is freely available as a webserver at the National EMBnet node Argentina, URL: http://www.embnet.qb.fcen.uba.ar/ in the subpage "Protein and nucleic acid structure and sequence analysis".

AlignMe—a membrane protein sequence alignment web server

PubMed Central

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

Evolutionary Dynamics on Protein Bi-stability Landscapes can Potentially Resolve Adaptive Conflicts

PubMed Central

Sikosek, Tobias; Bornberg-Bauer, Erich; Chan, Hue Sun

2012-01-01

Experimental studies have shown that some proteins exist in two alternative native-state conformations. It has been proposed that such bi-stable proteins can potentially function as evolutionary bridges at the interface between two neutral networks of protein sequences that fold uniquely into the two different native conformations. Under adaptive conflict scenarios, bi-stable proteins may be of particular advantage if they simultaneously provide two beneficial biological functions. However, computational models that simulate protein structure evolution do not yet recognize the importance of bi-stability. Here we use a biophysical model to analyze sequence space to identify bi-stable or multi-stable proteins with two or more equally stable native-state structures. The inclusion of such proteins enhances phenotype connectivity between neutral networks in sequence space. Consideration of the sequence space neighborhood of bridge proteins revealed that bi-stability decreases gradually with each mutation that takes the sequence further away from an exactly bi-stable protein. With relaxed selection pressures, we found that bi-stable proteins in our model are highly successful under simulated adaptive conflict. Inspired by these model predictions, we developed a method to identify real proteins in the PDB with bridge-like properties, and have verified a clear bi-stability gradient for a series of mutants studied by Alexander et al. (Proc Nat Acad Sci USA 2009, 106:21149–21154) that connect two sequences that fold uniquely into two different native structures via a bridge-like intermediate mutant sequence. Based on these findings, new testable predictions for future studies on protein bi-stability and evolution are discussed. PMID:23028272

Specific minor groove solvation is a crucial determinant of DNA binding site recognition

PubMed Central

Harris, Lydia-Ann; Williams, Loren Dean; Koudelka, Gerald B.

2014-01-01

The DNA sequence preferences of nearly all sequence specific DNA binding proteins are influenced by the identities of bases that are not directly contacted by protein. Discrimination between non-contacted base sequences is commonly based on the differential abilities of DNA sequences to allow narrowing of the DNA minor groove. However, the factors that govern the propensity of minor groove narrowing are not completely understood. Here we show that the differential abilities of various DNA sequences to support formation of a highly ordered and stable minor groove solvation network are a key determinant of non-contacted base recognition by a sequence-specific binding protein. In addition, disrupting the solvent network in the non-contacted region of the binding site alters the protein's ability to recognize contacted base sequences at positions 5–6 bases away. This observation suggests that DNA solvent interactions link contacted and non-contacted base recognition by the protein. PMID:25429976

MIPS: a database for protein sequences and complete genomes.

PubMed Central

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

Protein evolution analysis of S-hydroxynitrile lyase by complete sequence design utilizing the INTMSAlign software.

PubMed

Nakano, Shogo; Asano, Yasuhisa

2015-02-03

Development of software and methods for design of complete sequences of functional proteins could contribute to studies of protein engineering and protein evolution. To this end, we developed the INTMSAlign software, and used it to design functional proteins and evaluate their usefulness. The software could assign both consensus and correlation residues of target proteins. We generated three protein sequences with S-selective hydroxynitrile lyase (S-HNL) activity, which we call designed S-HNLs; these proteins folded as efficiently as the native S-HNL. Sequence and biochemical analysis of the designed S-HNLs suggested that accumulation of neutral mutations occurs during the process of S-HNLs evolution from a low-activity form to a high-activity (native) form. Taken together, our results demonstrate that our software and the associated methods could be applied not only to design of complete sequences, but also to predictions of protein evolution, especially within families such as esterases and S-HNLs.

Protein evolution analysis of S-hydroxynitrile lyase by complete sequence design utilizing the INTMSAlign software

NASA Astrophysics Data System (ADS)

Nakano, Shogo; Asano, Yasuhisa

2015-02-01

Development of software and methods for design of complete sequences of functional proteins could contribute to studies of protein engineering and protein evolution. To this end, we developed the INTMSAlign software, and used it to design functional proteins and evaluate their usefulness. The software could assign both consensus and correlation residues of target proteins. We generated three protein sequences with S-selective hydroxynitrile lyase (S-HNL) activity, which we call designed S-HNLs; these proteins folded as efficiently as the native S-HNL. Sequence and biochemical analysis of the designed S-HNLs suggested that accumulation of neutral mutations occurs during the process of S-HNLs evolution from a low-activity form to a high-activity (native) form. Taken together, our results demonstrate that our software and the associated methods could be applied not only to design of complete sequences, but also to predictions of protein evolution, especially within families such as esterases and S-HNLs.

New in protein structure and function annotation: hotspots, single nucleotide polymorphisms and the 'Deep Web'.

PubMed

Bromberg, Yana; Yachdav, Guy; Ofran, Yanay; Schneider, Reinhard; Rost, Burkhard

2009-05-01

The rapidly increasing quantity of protein sequence data continues to widen the gap between available sequences and annotations. Comparative modeling suggests some aspects of the 3D structures of approximately half of all known proteins; homology- and network-based inferences annotate some aspect of function for a similar fraction of the proteome. For most known protein sequences, however, there is detailed knowledge about neither their function nor their structure. Comprehensive efforts towards the expert curation of sequence annotations have failed to meet the demand of the rapidly increasing number of available sequences. Only the automated prediction of protein function in the absence of homology can close the gap between available sequences and annotations in the foreseeable future. This review focuses on two novel methods for automated annotation, and briefly presents an outlook on how modern web software may revolutionize the field of protein sequence annotation. First, predictions of protein binding sites and functional hotspots, and the evolution of these into the most successful type of prediction of protein function from sequence will be discussed. Second, a new tool, comprehensive in silico mutagenesis, which contributes important novel predictions of function and at the same time prepares for the onset of the next sequencing revolution, will be described. While these two new sub-fields of protein prediction represent the breakthroughs that have been achieved methodologically, it will then be argued that a different development might further change the way biomedical researchers benefit from annotations: modern web software can connect the worldwide web in any browser with the 'Deep Web' (ie, proprietary data resources). The availability of this direct connection, and the resulting access to a wealth of data, may impact drug discovery and development more than any existing method that contributes to protein annotation.

CombAlign: a code for generating a one-to-many sequence alignment from a set of pairwise structure-based sequence alignments.

PubMed

Zhou, Carol L Ecale

2015-01-01

In order to better define regions of similarity among related protein structures, it is useful to identify the residue-residue correspondences among proteins. Few codes exist for constructing a one-to-many multiple sequence alignment derived from a set of structure or sequence alignments, and a need was evident for creating such a tool for combining pairwise structure alignments that would allow for insertion of gaps in the reference structure. This report describes a new Python code, CombAlign, which takes as input a set of pairwise sequence alignments (which may be structure based) and generates a one-to-many, gapped, multiple structure- or sequence-based sequence alignment (MSSA). The use and utility of CombAlign was demonstrated by generating gapped MSSAs using sets of pairwise structure-based sequence alignments between structure models of the matrix protein (VP40) and pre-small/secreted glycoprotein (sGP) of Reston Ebolavirus and the corresponding proteins of several other filoviruses. The gapped MSSAs revealed structure-based residue-residue correspondences, which enabled identification of structurally similar versus differing regions in the Reston proteins compared to each of the other corresponding proteins. CombAlign is a new Python code that generates a one-to-many, gapped, multiple structure- or sequence-based sequence alignment (MSSA) given a set of pairwise sequence alignments (which may be structure based). CombAlign has utility in assisting the user in distinguishing structurally conserved versus divergent regions on a reference protein structure relative to other closely related proteins. CombAlign was developed in Python 2.6, and the source code is available for download from the GitHub code repository.

A Novel Cylindrical Representation for Characterizing Intrinsic Properties of Protein Sequences.

PubMed

Yu, Jia-Feng; Dou, Xiang-Hua; Wang, Hong-Bo; Sun, Xiao; Zhao, Hui-Ying; Wang, Ji-Hua

2015-06-22

The composition and sequence order of amino acid residues are the two most important characteristics to describe a protein sequence. Graphical representations facilitate visualization of biological sequences and produce biologically useful numerical descriptors. In this paper, we propose a novel cylindrical representation by placing the 20 amino acid residue types in a circle and sequence positions along the z axis. This representation allows visualization of the composition and sequence order of amino acids at the same time. Ten numerical descriptors and one weighted numerical descriptor have been developed to quantitatively describe intrinsic properties of protein sequences on the basis of the cylindrical model. Their applications to similarity/dissimilarity analysis of nine ND5 proteins indicated that these numerical descriptors are more effective than several classical numerical matrices. Thus, the cylindrical representation obtained here provides a new useful tool for visualizing and charactering protein sequences. An online server is available at http://biophy.dzu.edu.cn:8080/CNumD/input.jsp .

Nucleic and Amino Acid Sequences Support Structure-Based Viral Classification.

PubMed

Sinclair, Robert M; Ravantti, Janne J; Bamford, Dennis H

2017-04-15

Viral capsids ensure viral genome integrity by protecting the enclosed nucleic acids. Interactions between the genome and capsid and between individual capsid proteins (i.e., capsid architecture) are intimate and are expected to be characterized by strong evolutionary conservation. For this reason, a capsid structure-based viral classification has been proposed as a way to bring order to the viral universe. The seeming lack of sufficient sequence similarity to reproduce this classification has made it difficult to reject structural convergence as the basis for the classification. We reinvestigate whether the structure-based classification for viral coat proteins making icosahedral virus capsids is in fact supported by previously undetected sequence similarity. Since codon choices can influence nascent protein folding cotranslationally, we searched for both amino acid and nucleotide sequence similarity. To demonstrate the sensitivity of the approach, we identify a candidate gene for the pandoravirus capsid protein. We show that the structure-based classification is strongly supported by amino acid and also nucleotide sequence similarities, suggesting that the similarities are due to common descent. The correspondence between structure-based and sequence-based analyses of the same proteins shown here allow them to be used in future analyses of the relationship between linear sequence information and macromolecular function, as well as between linear sequence and protein folds. IMPORTANCE Viral capsids protect nucleic acid genomes, which in turn encode capsid proteins. This tight coupling of protein shell and nucleic acids, together with strong functional constraints on capsid protein folding and architecture, leads to the hypothesis that capsid protein-coding nucleotide sequences may retain signatures of ancient viral evolution. We have been able to show that this is indeed the case, using the major capsid proteins of viruses forming icosahedral capsids. Importantly, we detected similarity at the nucleotide level between capsid protein-coding regions from viruses infecting cells belonging to all three domains of life, reproducing a previously established structure-based classification of icosahedral viral capsids. Copyright © 2017 Sinclair et al.

Nucleic and Amino Acid Sequences Support Structure-Based Viral Classification

PubMed Central

Sinclair, Robert M.; Ravantti, Janne J.

2017-01-01

ABSTRACT Viral capsids ensure viral genome integrity by protecting the enclosed nucleic acids. Interactions between the genome and capsid and between individual capsid proteins (i.e., capsid architecture) are intimate and are expected to be characterized by strong evolutionary conservation. For this reason, a capsid structure-based viral classification has been proposed as a way to bring order to the viral universe. The seeming lack of sufficient sequence similarity to reproduce this classification has made it difficult to reject structural convergence as the basis for the classification. We reinvestigate whether the structure-based classification for viral coat proteins making icosahedral virus capsids is in fact supported by previously undetected sequence similarity. Since codon choices can influence nascent protein folding cotranslationally, we searched for both amino acid and nucleotide sequence similarity. To demonstrate the sensitivity of the approach, we identify a candidate gene for the pandoravirus capsid protein. We show that the structure-based classification is strongly supported by amino acid and also nucleotide sequence similarities, suggesting that the similarities are due to common descent. The correspondence between structure-based and sequence-based analyses of the same proteins shown here allow them to be used in future analyses of the relationship between linear sequence information and macromolecular function, as well as between linear sequence and protein folds. IMPORTANCE Viral capsids protect nucleic acid genomes, which in turn encode capsid proteins. This tight coupling of protein shell and nucleic acids, together with strong functional constraints on capsid protein folding and architecture, leads to the hypothesis that capsid protein-coding nucleotide sequences may retain signatures of ancient viral evolution. We have been able to show that this is indeed the case, using the major capsid proteins of viruses forming icosahedral capsids. Importantly, we detected similarity at the nucleotide level between capsid protein-coding regions from viruses infecting cells belonging to all three domains of life, reproducing a previously established structure-based classification of icosahedral viral capsids. PMID:28122979

Predicting residue-wise contact orders in proteins by support vector regression.

PubMed

Song, Jiangning; Burrage, Kevin

2006-10-03

The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

Cloning and expression of recombinant adhesive protein Mefp-1 of the blue mussel, Mytilus edulis

DOEpatents

Silverman, Heather G.; Roberto, Francisco F.

2006-01-17

The present invention comprises a Mytilus edulis cDNA sequenc having a nucleotide sequence that encodes for the Mytilus edulis foot protein-1 (Mefp-1), an example of a mollusk foot protein. Mefp-1 is an integral component of the blue mussels' adhesive protein complex, which allows the mussel to attach to objects underwater. The isolation, purification and sequencing of the Mefp-1 gene will allow researchers to produce Mefp-1 protein using genetic engineering techniques. The discovery of Mefp-1 gene sequence will also allow scientists to better understand how the blue mussel creates its waterproof adhesive protein complex.

Determination of the sequences of protein-derived peptides and peptide mixtures by mass spectrometry

PubMed Central

Morris, Howard R.; Williams, Dudley H.; Ambler, Richard P.

1971-01-01

Micro-quantities of protein-derived peptides have been converted into N-acetylated permethyl derivatives, and their sequences determined by low-resolution mass spectrometry without prior knowledge of their amino acid compositions or lengths. A new strategy is suggested for the mass spectrometric sequencing of oligopeptides or proteins, involving gel filtration of protein hydrolysates and subsequent sequence analysis of peptide mixtures. Finally, results are given that demonstrate for the first time the use of mass spectrometry for the analysis of a protein-derived peptide mixture, again without prior knowledge of the protein or components within the mixture. PMID:5158904

Identification of Sequence Specificity of 5-Methylcytosine Oxidation by Tet1 Protein with High-Throughput Sequencing.

PubMed

Kizaki, Seiichiro; Chandran, Anandhakumar; Sugiyama, Hiroshi

2016-03-02

Tet (ten-eleven translocation) family proteins have the ability to oxidize 5-methylcytosine (mC) to 5-hydroxymethylcytosine (hmC), 5-formylcytosine (fC), and 5-carboxycytosine (caC). However, the oxidation reaction of Tet is not understood completely. Evaluation of genomic-level epigenetic changes by Tet protein requires unbiased identification of the highly selective oxidation sites. In this study, we used high-throughput sequencing to investigate the sequence specificity of mC oxidation by Tet1. A 6.6×10(4) -member mC-containing random DNA-sequence library was constructed. The library was subjected to Tet-reactive pulldown followed by high-throughput sequencing. Analysis of the obtained sequence data identified the Tet1-reactive sequences. We identified mCpG as a highly reactive sequence of Tet1 protein. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Primary structures of ribosomal proteins from the archaebacterium Halobacterium marismortui and the eubacterium Bacillus stearothermophilus.

PubMed

Arndt, E; Scholzen, T; Krömer, W; Hatakeyama, T; Kimura, M

1991-06-01

Approximately 40 ribosomal proteins from each Halobacterium marismortui and Bacillus stearothermophilus have been sequenced either by direct protein sequence analysis or by DNA sequence analysis of the appropriate genes. The comparison of the amino acid sequences from the archaebacterium H marismortui with the available ribosomal proteins from the eubacterial and eukaryotic kingdoms revealed four different groups of proteins: 24 proteins are related to both eubacterial as well as eukaryotic proteins. Eleven proteins are exclusively related to eukaryotic counterparts. For three proteins only eubacterial relatives-and for another three proteins no counterpart-could be found. The similarities of the halobacterial ribosomal proteins are in general somewhat higher to their eukaryotic than to their eubacterial counterparts. The comparison of B stearothermophilus proteins with their E coli homologues showed that the proteins evolved at different rates. Some proteins are highly conserved with 64-76% identity, others are poorly conserved with only 25-34% identical amino acid residues.

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

PubMed Central

2011-01-01

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 both the query and the target can be reliably identified. The HomPPI web server is available at http://homppi.cs.iastate.edu/. Conclusions Sequence homology-based methods offer a class of computationally efficient and reliable approaches for predicting the protein-protein interface residues that participate in either obligate or transient interactions. For query proteins involved in transient interactions, the reliability of interface residue prediction can be improved by exploiting knowledge of putative interaction partners. PMID:21682895

Predicting disulfide connectivity from protein sequence using multiple sequence feature vectors and secondary structure.

PubMed

Song, Jiangning; Yuan, Zheng; Tan, Hao; Huber, Thomas; Burrage, Kevin

2007-12-01

Disulfide bonds are primary covalent crosslinks between two cysteine residues in proteins that play critical roles in stabilizing the protein structures and are commonly found in extracy-toplasmatic or secreted proteins. In protein folding prediction, the localization of disulfide bonds can greatly reduce the search in conformational space. Therefore, there is a great need to develop computational methods capable of accurately predicting disulfide connectivity patterns in proteins that could have potentially important applications. We have developed a novel method to predict disulfide connectivity patterns from protein primary sequence, using a support vector regression (SVR) approach based on multiple sequence feature vectors and predicted secondary structure by the PSIPRED program. The results indicate that our method could achieve a prediction accuracy of 74.4% and 77.9%, respectively, when averaged on proteins with two to five disulfide bridges using 4-fold cross-validation, measured on the protein and cysteine pair on a well-defined non-homologous dataset. We assessed the effects of different sequence encoding schemes on the prediction performance of disulfide connectivity. It has been shown that the sequence encoding scheme based on multiple sequence feature vectors coupled with predicted secondary structure can significantly improve the prediction accuracy, thus enabling our method to outperform most of other currently available predictors. Our work provides a complementary approach to the current algorithms that should be useful in computationally assigning disulfide connectivity patterns and helps in the annotation of protein sequences generated by large-scale whole-genome projects. The prediction web server and Supplementary Material are accessible at http://foo.maths.uq.edu.au/~huber/disulfide

Cloning and sequence analysis of a cDNA clone coding for the mouse GM2 activator protein.

PubMed Central

Bellachioma, G; Stirling, J L; Orlacchio, A; Beccari, T

1993-01-01

A cDNA (1.1 kb) containing the complete coding sequence for the mouse GM2 activator protein was isolated from a mouse macrophage library using a cDNA for the human protein as a probe. There was a single ATG located 12 bp from the 5' end of the cDNA clone followed by an open reading frame of 579 bp. Northern blot analysis of mouse macrophage RNA showed that there was a single band with a mobility corresponding to a size of 2.3 kb. We deduce from this that the mouse mRNA, in common with the mRNA for the human GM2 activator protein, has a long 3' untranslated sequence of approx. 1.7 kb. Alignment of the mouse and human deduced amino acid sequences showed 68% identity overall and 75% identity for the sequence on the C-terminal side of the first 31 residues, which in the human GM2 activator protein contains the signal peptide. Hydropathicity plots showed great similarity between the mouse and human sequences even in regions of low sequence similarity. There is a single N-glycosylation site in the mouse GM2 activator protein sequence (Asn151-Phe-Thr) which differs in its location from the single site reported in the human GM2 activator protein sequence (Asn63-Val-Thr). Images Figure 1 PMID:7689829

Isolation and determination of the primary structure of a lectin protein from the serum of the American alligator (Alligator mississippiensis).

PubMed

Darville, Lancia N F; Merchant, Mark E; Maccha, Venkata; Siddavarapu, Vivekananda Reddy; Hasan, Azeem; Murray, Kermit K

2012-02-01

Mass spectrometry in conjunction with de novo sequencing was used to determine the amino acid sequence of a 35kDa lectin protein isolated from the serum of the American alligator that exhibits binding to mannose. The protein N-terminal sequence was determined using Edman degradation and enzymatic digestion with different proteases was used to generate peptide fragments for analysis by liquid chromatography tandem mass spectrometry (LC MS/MS). Separate analysis of the protein digests with multiple enzymes enhanced the protein sequence coverage. De novo sequencing was accomplished using MASCOT Distiller and PEAKS software and the sequences were searched against the NCBI database using MASCOT and BLAST to identify homologous peptides. MS analysis of the intact protein indicated that it is present primarily as monomer and dimer in vitro. The isolated 35kDa protein was ~98% sequenced and found to have 313 amino acids and nine cysteine residues and was identified as an alligator lectin. The alligator lectin sequence was aligned with other lectin sequences using DIALIGN and ClustalW software and was found to exhibit 58% and 59% similarity to both human and mouse intelectin-1. The alligator lectin exhibited strong binding affinities toward mannan and mannose as compared to other tested carbohydrates. Copyright © 2011 Elsevier Inc. All rights reserved.

Evolution of EF-hand calcium-modulated proteins. IV. Exon shuffling did not determine the domain compositions of EF-hand proteins

NASA Technical Reports Server (NTRS)

Kretsinger, R. H.; Nakayama, S.

1993-01-01

In the previous three reports in this series we demonstrated that the EF-hand family of proteins evolved by a complex pattern of gene duplication, transposition, and splicing. The dendrograms based on exon sequences are nearly identical to those based on protein sequences for troponin C, the essential light chain myosin, the regulatory light chain, and calpain. This validates both the computational methods and the dendrograms for these subfamilies. The proposal of congruence for calmodulin, troponin C, essential light chain, and regulatory light chain was confirmed. There are, however, significant differences in the calmodulin dendrograms computed from DNA and from protein sequences. In this study we find that introns are distributed throughout the EF-hand domain and the interdomain regions. Further, dendrograms based on intron type and distribution bear little resemblance to those based on protein or on DNA sequences. We conclude that introns are inserted, and probably deleted, with relatively high frequency. Further, in the EF-hand family exons do not correspond to structural domains and exon shuffling played little if any role in the evolution of this widely distributed homolog family. Calmodulin has had a turbulent evolution. Its dendrograms based on protein sequence, exon sequence, 3'-tail sequence, intron sequences, and intron positions all show significant differences.

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

PubMed

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.

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

PubMed

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.

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

PubMed

Smith, Colin A; Kortemme, Tanja

2011-01-01

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.

A protein block based fold recognition method for the annotation of twilight zone sequences.

PubMed

Suresh, V; Ganesan, K; Parthasarathy, S

2013-03-01

The description of protein backbone was recently improved with a group of structural fragments called Structural Alphabets instead of the regular three states (Helix, Sheet and Coil) secondary structure description. Protein Blocks is one of the Structural Alphabets used to describe each and every region of protein backbone including the coil. According to de Brevern (2000) the Protein Blocks has 16 structural fragments and each one has 5 residues in length. Protein Blocks fragments are highly informative among the available Structural Alphabets and it has been used for many applications. Here, we present a protein fold recognition method based on Protein Blocks for the annotation of twilight zone sequences. In our method, we align the predicted Protein Blocks of a query amino acid sequence with a library of assigned Protein Blocks of 953 known folds using the local pair-wise alignment. The alignment results with z-value ≥ 2.5 and P-value ≤ 0.08 are predicted as possible folds. Our method is able to recognize the possible folds for nearly 35.5% of the twilight zone sequences with their predicted Protein Block sequence obtained by pb_prediction, which is available at Protein Block Export server.

Meta sequence analysis of human blood peptides and their parent proteins.

PubMed

Bowden, Peter; Pendrak, Voitek; Zhu, Peihong; Marshall, John G

2010-04-18

Sequence analysis of the blood peptides and their qualities will be key to understanding the mechanisms that contribute to error in LC-ESI-MS/MS. Analysis of peptides and their proteins at the level of sequences is much more direct and informative than the comparison of disparate accession numbers. A portable database of all blood peptide and protein sequences with descriptor fields and gene ontology terms might be useful for designing immunological or MRM assays from human blood. The results of twelve studies of human blood peptides and/or proteins identified by LC-MS/MS and correlated against a disparate array of genetic libraries were parsed and matched to proteins from the human ENSEMBL, SwissProt and RefSeq databases by SQL. The reported peptide and protein sequences were organized into an SQL database with full protein sequences and up to five unique peptides in order of prevalence along with the peptide count for each protein. Structured query language or BLAST was used to acquire descriptive information in current databases. Sampling error at the level of peptides is the largest source of disparity between groups. Chi Square analysis of peptide to protein distributions confirmed the significant agreement between groups on identified proteins. Copyright 2010. Published by Elsevier B.V.

Prediction of protein tertiary structure from sequences using a very large back-propagation neural network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, X.; Wilcox, G.L.

1993-12-31

We have implemented large scale back-propagation neural networks on a 544 node Connection Machine, CM-5, using the C language in MIMD mode. The program running on 512 processors performs backpropagation learning at 0.53 Gflops, which provides 76 million connection updates per second. We have applied the network to the prediction of protein tertiary structure from sequence information alone. A neural network with one hidden layer and 40 million connections is trained to learn the relationship between sequence and tertiary structure. The trained network yields predicted structures of some proteins on which it has not been trained given only their sequences.more » Presentation of the Fourier transform of the sequences accentuates periodicity in the sequence and yields good generalization with greatly increased training efficiency. Training simulations with a large, heterologous set of protein structures (111 proteins from CM-5 time) to solutions with under 2% RMS residual error within the training set (random responses give an RMS error of about 20%). Presentation of 15 sequences of related proteins in a testing set of 24 proteins yields predicted structures with less than 8% RMS residual error, indicating good apparent generalization.« less

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Chaos game representation walk model for the protein sequences

NASA Astrophysics Data System (ADS)

Gao, Jie; Jiang, Li-Li; Xu, Zhen-Yuan

2009-10-01

A new chaos game representation of protein sequences based on the detailed hydrophobic-hydrophilic (HP) model has been proposed by Yu et al (Physica A 337 (2004) 171). A CGR-walk model is proposed based on the new CGR coordinates for the protein sequences from complete genomes in the present paper. The new CGR coordinates based on the detailed HP model are converted into a time series, and a long-memory ARFIMA(p, d, q) model is introduced into the protein sequence analysis. This model is applied to simulating real CGR-walk sequence data of twelve protein sequences. Remarkably long-range correlations are uncovered in the data and the results obtained from these models are reasonably consistent with those available from the ARFIMA(p, d, q) model.

Conservation of coevolving protein interfaces bridges prokaryote–eukaryote homologies in the twilight zone

PubMed Central

Rodriguez-Rivas, Juan; Marsili, Simone; Juan, David; Valencia, Alfonso

2016-01-01

Protein–protein interactions are fundamental for the proper functioning of the cell. As a result, protein interaction surfaces are subject to strong evolutionary constraints. Recent developments have shown that residue coevolution provides accurate predictions of heterodimeric protein interfaces from sequence information. So far these approaches have been limited to the analysis of families of prokaryotic complexes for which large multiple sequence alignments of homologous sequences can be compiled. We explore the hypothesis that coevolution points to structurally conserved contacts at protein–protein interfaces, which can be reliably projected to homologous complexes with distantly related sequences. We introduce a domain-centered protocol to study the interplay between residue coevolution and structural conservation of protein–protein interfaces. We show that sequence-based coevolutionary analysis systematically identifies residue contacts at prokaryotic interfaces that are structurally conserved at the interface of their eukaryotic counterparts. In turn, this allows the prediction of conserved contacts at eukaryotic protein–protein interfaces with high confidence using solely mutational patterns extracted from prokaryotic genomes. Even in the context of high divergence in sequence (the twilight zone), where standard homology modeling of protein complexes is unreliable, our approach provides sequence-based accurate information about specific details of protein interactions at the residue level. Selected examples of the application of prokaryotic coevolutionary analysis to the prediction of eukaryotic interfaces further illustrate the potential of this approach. PMID:27965389

Purification, characterization and sequence analysis of Omp50,a new porin isolated from Campylobacter jejuni.

PubMed Central

Bolla, J M; Dé, E; Dorez, A; Pagès, J M

2000-01-01

A novel pore-forming protein identified in Campylobacter was purified by ion-exchange chromatography and named Omp50 according to both its molecular mass and its outer membrane localization. We observed a pore-forming ability of Omp50 after re-incorporation into artificial membranes. The protein induced cation-selective channels with major conductance values of 50-60 pS in 1 M NaCl. N-terminal sequencing allowed us to identify the predicted coding sequence Cj1170c from the Campylobacter jejuni genome database as the corresponding gene in the NCTC 11168 genome sequence. The gene, designated omp50, consists of a 1425 bp open reading frame encoding a deduced 453-amino acid protein with a calculated pI of 5.81 and a molecular mass of 51169.2 Da. The protein possessed a 20-amino acid leader sequence. No significant similarity was found between Omp50 and porin protein sequences already determined. Moreover, the protein showed only weak sequence identity with the major outer-membrane protein (MOMP) of Campylobacter, correlating with the absence of antigenic cross-reactivity between these two proteins. Omp50 is expressed in C. jejuni and Campylobacter lari but not in Campylobacter coli. The gene, however, was detected in all three species by PCR. According to its conformation and functional properties, the protein would belong to the family of outer-membrane monomeric porins. PMID:11104668

Cysteine-containing peptide tag for site-specific conjugation of proteins

DOEpatents

Backer, Marina V.; Backer, Joseph M.

2008-04-08

The present invention is directed to a biological conjugate, comprising: (a) a targeting moiety comprising a polypeptide having an amino acid sequence comprising the polypeptide sequence of SEQ ID NO:2 and the polypeptide sequence of a selected targeting protein; and (b) a binding moiety bound to the targeting moiety; the biological conjugate having a covalent bond between the thiol group of SEQ ID NO:2 and a functional group in the binding moiety. The present invention is directed to a biological conjugate, comprising: (a) a targeting moiety comprising a polypeptide having an amino acid sequence comprising the polypeptide sequence of SEQ ID NO:2 and the polypeptide sequence of a selected targeting protein; and (b) a binding moiety that comprises an adapter protein, the adapter protein having a thiol group; the biological conjugate having a disulfide bond between the thiol group of SEQ ID NO:2 and the thiol group of the adapter protein. The present invention is also directed to biological sequences employed in the above biological conjugates, as well as pharmaceutical preparations and methods using the above biological conjugates.

Cysteine-containing peptide tag for site-specific conjugation of proteins

DOEpatents

Backer, Marina V.; Backer, Joseph M.

2010-10-05

The present invention is directed to a biological conjugate, comprising: (a) a targeting moiety comprising a polypeptide having an amino acid sequence comprising the polypeptide sequence of SEQ ID NO:2 and the polypeptide sequence of a selected targeting protein; and (b) a binding moiety bound to the targeting moiety; the biological conjugate having a covalent bond between the thiol group of SEQ ID NO:2 and a functional group in the binding moiety. The present invention is directed to a biological conjugate, comprising: (a) a targeting moiety comprising a polypeptide having an amino acid sequence comprising the polypeptide sequence of SEQ ID NO:2 and the polypeptide sequence of a selected targeting protein; and (b) a binding moiety that comprises an adapter protein, the adapter protein having a thiol group; the biological conjugate having a disulfide bond between the thiol group of SEQ ID NO:2 and the thiol group of the adapter protein. The present invention is also directed to biological sequences employed in the above biological conjugates, as well as pharmaceutical preparations and methods using the above biological conjugates.

Graph pyramids for protein function prediction

PubMed Central

2015-01-01

Background Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Methods Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Results Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data. PMID:26044522

Graph pyramids for protein function prediction.

PubMed

Sandhan, Tushar; Yoo, Youngjun; Choi, Jin; Kim, Sun

2015-01-01

Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data.

Protein Crystal Eco R1 Endonulease-DNA Complex

NASA Technical Reports Server (NTRS)

1998-01-01

Type II restriction enzymes, such as Eco R1 endonulease, present a unique advantage for the study of sequence-specific recognition because they leave a record of where they have been in the form of the cleaved ends of the DNA sites where they were bound. The differential behavior of a sequence -specific protein at sites of differing base sequence is the essence of the sequence-specificity; the core question is how do these proteins discriminate between different DNA sequences especially when the two sequences are very similar. Principal Investigator: Dan Carter/New Century Pharmaceuticals

Genomewide Function Conservation and Phylogeny in the Herpesviridae

PubMed Central

Albà, M. Mar; Das, Rhiju; Orengo, Christine A.; Kellam, Paul

2001-01-01

The Herpesviridae are a large group of well-characterized double-stranded DNA viruses for which many complete genome sequences have been determined. We have extracted protein sequences from all predicted open reading frames of 19 herpesvirus genomes. Sequence comparison and protein sequence clustering methods have been used to construct herpesvirus protein homologous families. This resulted in 1692 proteins being clustered into 243 multiprotein families and 196 singleton proteins. Predicted functions were assigned to each homologous family based on genome annotation and published data and each family classified into seven broad functional groups. Phylogenetic profiles were constructed for each herpesvirus from the homologous protein families and used to determine conserved functions and genomewide phylogenetic trees. These trees agreed with molecular-sequence-derived trees and allowed greater insight into the phylogeny of ungulate and murine gammaherpesviruses. PMID:11156614

Determining protein function and interaction from genome analysis

DOEpatents

Eisenberg, David; Marcotte, Edward M.; Thompson, Michael J.; Pellegrini, Matteo; Yeates, Todd O.

2004-08-03

A computational method system, and computer program are provided for inferring functional links from genome sequences. One method is based on the observation that some pairs of proteins A' and B' have homologs in another organism fused into a single protein chain AB. A trans-genome comparison of sequences can reveal these AB sequences, which are Rosetta Stone sequences because they decipher an interaction between A' and B. Another method compares the genomic sequence of two or more organisms to create a phylogenetic profile for each protein indicating its presence or absence across all the genomes. The profile provides information regarding functional links between different families of proteins. In yet another method a combination of the above two methods is used to predict functional links.

An approach to large scale identification of non-obvious structural similarities between proteins

PubMed Central

Cherkasov, Artem; Jones, Steven JM

2004-01-01

Background A new sequence independent bioinformatics approach allowing genome-wide search for proteins with similar three dimensional structures has been developed. By utilizing the numerical output of the sequence threading it establishes putative non-obvious structural similarities between proteins. When applied to the testing set of proteins with known three dimensional structures the developed approach was able to recognize structurally similar proteins with high accuracy. Results The method has been developed to identify pathogenic proteins with low sequence identity and high structural similarity to host analogues. Such protein structure relationships would be hypothesized to arise through convergent evolution or through ancient horizontal gene transfer events, now undetectable using current sequence alignment techniques. The pathogen proteins, which could mimic or interfere with host activities, would represent candidate virulence factors. The developed approach utilizes the numerical outputs from the sequence-structure threading. It identifies the potential structural similarity between a pair of proteins by correlating the threading scores of the corresponding two primary sequences against the library of the standard folds. This approach allowed up to 64% sensitivity and 99.9% specificity in distinguishing protein pairs with high structural similarity. Conclusion Preliminary results obtained by comparison of the genomes of Homo sapiens and several strains of Chlamydia trachomatis have demonstrated the potential usefulness of the method in the identification of bacterial proteins with known or potential roles in virulence. PMID:15147578

Sequence and structural implications of a bovine corneal keratan sulfate proteoglycan core protein. Protein 37B represents bovine lumican and proteins 37A and 25 are unique

NASA Technical Reports Server (NTRS)

Funderburgh, J. L.; Funderburgh, M. L.; Brown, S. J.; Vergnes, J. P.; Hassell, J. R.; Mann, M. M.; Conrad, G. W.; Spooner, B. S. (Principal Investigator)

1993-01-01

Amino acid sequence from tryptic peptides of three different bovine corneal keratan sulfate proteoglycan (KSPG) core proteins (designated 37A, 37B, and 25) showed similarities to the sequence of a chicken KSPG core protein lumican. Bovine lumican cDNA was isolated from a bovine corneal expression library by screening with chicken lumican cDNA. The bovine cDNA codes for a 342-amino acid protein, M(r) 38,712, containing amino acid sequences identified in the 37B KSPG core protein. The bovine lumican is 68% identical to chicken lumican, with an 83% identity excluding the N-terminal 40 amino acids. Location of 6 cysteine and 4 consensus N-glycosylation sites in the bovine sequence were identical to those in chicken lumican. Bovine lumican had about 50% identity to bovine fibromodulin and 20% identity to bovine decorin and biglycan. About two-thirds of the lumican protein consists of a series of 10 amino acid leucine-rich repeats that occur in regions of calculated high beta-hydrophobic moment, suggesting that the leucine-rich repeats contribute to beta-sheet formation in these proteins. Sequences obtained from 37A and 25 core proteins were absent in bovine lumican, thus predicting a unique primary structure and separate mRNA for each of the three bovine KSPG core proteins.

Investigation of the protein osteocalcin of Camelops hesternus: Sequence, structure and phylogenetic implications

NASA Astrophysics Data System (ADS)

Humpula, James F.; Ostrom, Peggy H.; Gandhi, Hasand; Strahler, John R.; Walker, Angela K.; Stafford, Thomas W.; Smith, James J.; Voorhies, Michael R.; George Corner, R.; Andrews, Phillip C.

2007-12-01

Ancient DNA sequences offer an extraordinary opportunity to unravel the evolutionary history of ancient organisms. Protein sequences offer another reservoir of genetic information that has recently become tractable through the application of mass spectrometric techniques. The extent to which ancient protein sequences resolve phylogenetic relationships, however, has not been explored. We determined the osteocalcin amino acid sequence from the bone of an extinct Camelid (21 ka, Camelops hesternus) excavated from Isleta Cave, New Mexico and three bones of extant camelids: bactrian camel ( Camelus bactrianus); dromedary camel ( Camelus dromedarius) and guanaco ( Llama guanacoe) for a diagenetic and phylogenetic assessment. There was no difference in sequence among the four taxa. Structural attributes observed in both modern and ancient osteocalcin include a post-translation modification, Hyp 9, deamidation of Gln 35 and Gln 39, and oxidation of Met 36. Carbamylation of the N-terminus in ancient osteocalcin may result in blockage and explain previous difficulties in sequencing ancient proteins via Edman degradation. A phylogenetic analysis using osteocalcin sequences of 25 vertebrate taxa was conducted to explore osteocalcin protein evolution and the utility of osteocalcin sequences for delineating phylogenetic relationships. The maximum likelihood tree closely reflected generally recognized taxonomic relationships. For example, maximum likelihood analysis recovered rodents, birds and, within hominins, the Homo-Pan-Gorilla trichotomy. Within Artiodactyla, character state analysis showed that a substitution of Pro 4 for His 4 defines the Capra-Ovis clade within Artiodactyla. Homoplasy in our analysis indicated that osteocalcin evolution is not a perfect indicator of species evolution. Limited sequence availability prevented assigning functional significance to sequence changes. Our preliminary analysis of osteocalcin evolution represents an initial step towards a complete character analysis aimed at determining the evolutionary history of this functionally significant protein. We emphasize that ancient protein sequencing and phylogenetic analyses using amino acid sequences must pay close attention to post-translational modifications, amino acid substitutions due to diagenetic alteration and the impacts of isobaric amino acids on mass shifts and sequence alignments.

Nucleotide sequence of the Saccharomyces cerevisiae PUT4 proline-permease-encoding gene: similarities between CAN1, HIP1 and PUT4 permeases.

PubMed

Vandenbol, M; Jauniaux, J C; Grenson, M

1989-11-15

The complete nucleotide (nt) sequence of the PUT4 gene, whose product is required for high-affinity proline active transport in the yeast Saccharomyces cerevisiae, is presented. The sequence contains a single long open reading frame of 1881 nt, encoding a polypeptide with a calculated Mr of 68,795. The predicted protein is strongly hydrophobic and exhibits six potential glycosylation sites. Its hydropathy profile suggests the presence of twelve membrane-spanning regions flanked by hydrophilic N- and C-terminal domains. The N terminus does not resemble signal sequences found in secreted proteins. These features are characteristic of integral membrane proteins catalyzing translocation of ligands across cellular membranes. Protein sequence comparisons indicate strong resemblance to the arginine and histidine permeases of S. cerevisiae, but no marked sequence similarity to the proline permease of Escherichia coli or to other known prokaryotic or eukaryotic transport proteins. The strong similarity between the three yeast amino acid permeases suggests a common ancestor for the three proteins.

Sequence of the amino-terminal region of rat liver ribosomal proteins S4, S6, S8, L6, L7a, L18, L27, L30, L37, L37a, and L39.

PubMed

Wittmann-Liebold, B; Geissler, A W; Lin, A; Wool, I G

1979-01-01

The sequence of the amino-terminal region of eleven rat liver ribosomal proteins--S4, S6, S8, L6, L7a, L18, L27, L30, L37a, and L39--was determined. The analysis confirmed the homogeneity of the proteins and suggests that they are unique, since no extensive common sequences were found. The N-terminal regions of the rat liver proteins were compared with amino acid sequences in Saccharomyces cerevisiae and in Escherichia coli ribosomal proteins. It seems likely that the proteins L37 from rat liver and Y55 from yeast ribosomes are homologous. It is possible that rat liver L7a or L37a or both are related to S cerevisiae Y44, although the similar sequences are at the amino-terminus of the rat liver proteins and in an internal region of Y44. A number of similarities in the sequences of rat liver and E coli ribosomal proteins have been found; however, it is not yet possible to say whether they connote a common ancestry.

Variability of the protein sequences of lcrV between epidemic and atypical rhamnose-positive strains of Yersinia pestis.

PubMed

Anisimov, Andrey P; Panfertsev, Evgeniy A; Svetoch, Tat'yana E; Dentovskaya, Svetlana V

2007-01-01

Sequencing of lcrV genes and comparison of the deduced amino acid sequences from ten Y. pestis strains belonging mostly to the group of atypical rhamnose-positive isolates (non-pestis subspecies or pestoides group) showed that the LcrV proteins analyzed could be classified into five sequence types. This classification was based on major amino acid polymorphisms among LcrV proteins in the four "hot points" of the protein sequences. Some additional minor polymorphisms were found throughout these sequence types. The "hot points" corresponded to amino acids 18 (Lys --> Asn), 72 (Lys --> Arg), 273 (Cys --> Ser), and 324-326 (Ser-Gly-Lys --> Arg) in the LcrV sequence of the reference Y. pestis strain CO92. One possible explanation for polymorphism in amino acid sequences of LcrV among different strains is that strain-specific variation resulted from adaptation of the plague pathogen to different rodent and lagomorph hosts.

Robustness of Reconstructed Ancestral Protein Functions to Statistical Uncertainty.

PubMed

Eick, Geeta N; Bridgham, Jamie T; Anderson, Douglas P; Harms, Michael J; Thornton, Joseph W

2017-02-01

Hypotheses about the functions of ancient proteins and the effects of historical mutations on them are often tested using ancestral protein reconstruction (APR)-phylogenetic inference of ancestral sequences followed by synthesis and experimental characterization. Usually, some sequence sites are ambiguously reconstructed, with two or more statistically plausible states. The extent to which the inferred functions and mutational effects are robust to uncertainty about the ancestral sequence has not been studied systematically. To address this issue, we reconstructed ancestral proteins in three domain families that have different functions, architectures, and degrees of uncertainty; we then experimentally characterized the functional robustness of these proteins when uncertainty was incorporated using several approaches, including sampling amino acid states from the posterior distribution at each site and incorporating the alternative amino acid state at every ambiguous site in the sequence into a single "worst plausible case" protein. In every case, qualitative conclusions about the ancestral proteins' functions and the effects of key historical mutations were robust to sequence uncertainty, with similar functions observed even when scores of alternate amino acids were incorporated. There was some variation in quantitative descriptors of function among plausible sequences, suggesting that experimentally characterizing robustness is particularly important when quantitative estimates of ancient biochemical parameters are desired. The worst plausible case method appears to provide an efficient strategy for characterizing the functional robustness of ancestral proteins to large amounts of sequence uncertainty. Sampling from the posterior distribution sometimes produced artifactually nonfunctional proteins for sequences reconstructed with substantial ambiguity. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

A discriminative method for protein remote homology detection and fold recognition combining Top-n-grams and latent semantic analysis.

PubMed

Liu, Bin; Wang, Xiaolong; Lin, Lei; Dong, Qiwen; Wang, Xuan

2008-12-01

Protein remote homology detection and fold recognition are central problems in bioinformatics. Currently, discriminative methods based on support vector machine (SVM) are the most effective and accurate methods for solving these problems. A key step to improve the performance of the SVM-based methods is to find a suitable representation of protein sequences. In this paper, a novel building block of proteins called Top-n-grams is presented, which contains the evolutionary information extracted from the protein sequence frequency profiles. The protein sequence frequency profiles are calculated from the multiple sequence alignments outputted by PSI-BLAST and converted into Top-n-grams. The protein sequences are transformed into fixed-dimension feature vectors by the occurrence times of each Top-n-gram. The training vectors are evaluated by SVM to train classifiers which are then used to classify the test protein sequences. We demonstrate that the prediction performance of remote homology detection and fold recognition can be improved by combining Top-n-grams and latent semantic analysis (LSA), which is an efficient feature extraction technique from natural language processing. When tested on superfamily and fold benchmarks, the method combining Top-n-grams and LSA gives significantly better results compared to related methods. The method based on Top-n-grams significantly outperforms the methods based on many other building blocks including N-grams, patterns, motifs and binary profiles. Therefore, Top-n-gram is a good building block of the protein sequences and can be widely used in many tasks of the computational biology, such as the sequence alignment, the prediction of domain boundary, the designation of knowledge-based potentials and the prediction of protein binding sites.

Host Cell Virus Entry Mediated by Australian Bat Lyssavirus Envelope G glycoprotein

DTIC Science & Technology

2013-10-24

39 Figure 7. Comparison of the amino acid sequences of Saccolaimus and Pteropus ABLV G mature protein... sequence analysis revealed that the PCR products were identical. Sequence comparisons of the ABLV N and other lyssavirus N proteins showed that ABLV...Saccolaimus flaviventris) (129). Nucleoprotein sequence comparisons revealed that the Saccolaimus N protein shared 96% amino acid homology with the Pteropus

Extreme Sensory Complexity Encoded in the 10-Megabase Draft Genome Sequence of the Chromatically Acclimating Cyanobacterium Tolypothrix sp. PCC 7601

PubMed Central

Yerrapragada, Shaila; Shukla, Animesh; Hallsworth-Pepin, Kymberlie; Choi, Kwangmin; Wollam, Aye; Clifton, Sandra; Qin, Xiang; Muzny, Donna; Raghuraman, Sriram; Ashki, Haleh; Uzman, Akif; Highlander, Sarah K.; Fryszczyn, Bartlomiej G.; Fox, George E.; Tirumalai, Madhan R.; Liu, Yamei; Kim, Sun

2015-01-01

Tolypothrix sp. PCC 7601 is a freshwater filamentous cyanobacterium with complex responses to environmental conditions. Here, we present its 9.96-Mbp draft genome sequence, containing 10,065 putative protein-coding sequences, including 305 predicted two-component system proteins and 27 putative phytochrome-class photoreceptors, the most such proteins in any sequenced genome. PMID:25953173

Neutrality and evolvability of designed protein sequences

NASA Astrophysics Data System (ADS)

Bhattacherjee, Arnab; Biswas, Parbati

2010-07-01

The effect of foldability on protein’s evolvability is analyzed by a two-prong approach consisting of a self-consistent mean-field theory and Monte Carlo simulations. Theory and simulation models representing protein sequences with binary patterning of amino acid residues compatible with a particular foldability criteria are used. This generalized foldability criterion is derived using the high temperature cumulant expansion approximating the free energy of folding. The effect of cumulative point mutations on these designed proteins is studied under neutral condition. The robustness, protein’s ability to tolerate random point mutations is determined with a selective pressure of stability (ΔΔG) for the theory designed sequences, which are found to be more robust than that of Monte Carlo and mean-field-biased Monte Carlo generated sequences. The results show that this foldability criterion selects viable protein sequences more effectively compared to the Monte Carlo method, which has a marked effect on how the selective pressure shapes the evolutionary sequence space. These observations may impact de novo sequence design and its applications in protein engineering.

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

PubMed

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 information pertaining to an RBP, like overall function annotations, are provided. The web server can be accessed at the following link: http://caps.ncbs.res.in/rstrucfam .

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

PubMed

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.

Correlation of fitness landscapes from three orthologous TIM barrels originates from sequence and structure constraints

PubMed Central

Chan, Yvonne H.; Venev, Sergey V.; Zeldovich, Konstantin B.; Matthews, C. Robert

2017-01-01

Sequence divergence of orthologous proteins enables adaptation to environmental stresses and promotes evolution of novel functions. Limits on evolution imposed by constraints on sequence and structure were explored using a model TIM barrel protein, indole-3-glycerol phosphate synthase (IGPS). Fitness effects of point mutations in three phylogenetically divergent IGPS proteins during adaptation to temperature stress were probed by auxotrophic complementation of yeast with prokaryotic, thermophilic IGPS. Analysis of beneficial mutations pointed to an unexpected, long-range allosteric pathway towards the active site of the protein. Significant correlations between the fitness landscapes of distant orthologues implicate both sequence and structure as primary forces in defining the TIM barrel fitness landscape and suggest that fitness landscapes can be translocated in sequence space. Exploration of fitness landscapes in the context of a protein fold provides a strategy for elucidating the sequence-structure-fitness relationships in other common motifs. PMID:28262665

Protein Sequencing with Tandem Mass Spectrometry

NASA Astrophysics Data System (ADS)

Ziady, Assem G.; Kinter, Michael

The recent introduction of electrospray ionization techniques that are suitable for peptides and whole proteins has allowed for the design of mass spectrometric protocols that provide accurate sequence information for proteins. The advantages gained by these approaches over traditional Edman Degradation sequencing include faster analysis and femtomole, sometimes attomole, sensitivity. The ability to efficiently identify proteins has allowed investigators to conduct studies on their differential expression or modification in response to various treatments or disease states. In this chapter, we discuss the use of electrospray tandem mass spectrometry, a technique whereby protein-derived peptides are subjected to fragmentation in the gas phase, revealing sequence information for the protein. This powerful technique has been instrumental for the study of proteins and markers associated with various disorders, including heart disease, cancer, and cystic fibrosis. We use the study of protein expression in cystic fibrosis as an example.

A plasma membrane sucrose-binding protein that mediates sucrose uptake shares structural and sequence similarity with seed storage proteins but remains functionally distinct.

PubMed

Overvoorde, P J; Chao, W S; Grimes, H D

1997-06-20

Photoaffinity labeling of a soybean cotyledon membrane fraction identified a sucrose-binding protein (SBP). Subsequent studies have shown that the SBP is a unique plasma membrane protein that mediates the linear uptake of sucrose in the presence of up to 30 mM external sucrose when ectopically expressed in yeast. Analysis of the SBP-deduced amino acid sequence indicates it lacks sequence similarity with other known transport proteins. Data presented here, however, indicate that the SBP shares significant sequence and structural homology with the vicilin-like seed storage proteins that organize into homotrimers. These similarities include a repeated sequence that forms the basis of the reiterated domain structure characteristic of the vicilin-like protein family. In addition, analytical ultracentrifugation and nonreducing SDS-polyacrylamide gel electrophoresis demonstrate that the SBP appears to be organized into oligomeric complexes with a Mr indicative of the existence of SBP homotrimers and homodimers. The structural similarity shared by the SBP and vicilin-like proteins provides a novel framework to explore the mechanistic basis of SBP-mediated sucrose uptake. Expression of the maize Glb protein (a vicilin-like protein closely related to the SBP) in yeast demonstrates that a closely related vicilin-like protein is unable to mediate sucrose uptake. Thus, despite sequence and structural similarities shared by the SBP and the vicilin-like protein family, the SBP is functionally divergent from other members of this group.

Metagenome assembly through clustering of next-generation sequencing data using protein sequences.

PubMed

Sim, Mikang; Kim, Jaebum

2015-02-01

The study of environmental microbial communities, called metagenomics, has gained a lot of attention because of the recent advances in next-generation sequencing (NGS) technologies. Microbes play a critical role in changing their environments, and the mode of their effect can be solved by investigating metagenomes. However, the difficulty of metagenomes, such as the combination of multiple microbes and different species abundance, makes metagenome assembly tasks more challenging. In this paper, we developed a new metagenome assembly method by utilizing protein sequences, in addition to the NGS read sequences. Our method (i) builds read clusters by using mapping information against available protein sequences, and (ii) creates contig sequences by finding consensus sequences through probabilistic choices from the read clusters. By using simulated NGS read sequences from real microbial genome sequences, we evaluated our method in comparison with four existing assembly programs. We found that our method could generate relatively long and accurate metagenome assemblies, indicating that the idea of using protein sequences, as a guide for the assembly, is promising. Copyright © 2015 Elsevier B.V. All rights reserved.

A Score of the Ability of a Three-Dimensional Protein Model to Retrieve Its Own Sequence as a Quantitative Measure of Its Quality and Appropriateness

PubMed Central

Martínez-Castilla, León P.; Rodríguez-Sotres, Rogelio

2010-01-01

Background Despite the remarkable progress of bioinformatics, how the primary structure of a protein leads to a three-dimensional fold, and in turn determines its function remains an elusive question. Alignments of sequences with known function can be used to identify proteins with the same or similar function with high success. However, identification of function-related and structure-related amino acid positions is only possible after a detailed study of every protein. Folding pattern diversity seems to be much narrower than sequence diversity, and the amino acid sequences of natural proteins have evolved under a selective pressure comprising structural and functional requirements acting in parallel. Principal Findings The approach described in this work begins by generating a large number of amino acid sequences using ROSETTA [Dantas G et al. (2003) J Mol Biol 332:449–460], a program with notable robustness in the assignment of amino acids to a known three-dimensional structure. The resulting sequence-sets showed no conservation of amino acids at active sites, or protein-protein interfaces. Hidden Markov models built from the resulting sequence sets were used to search sequence databases. Surprisingly, the models retrieved from the database sequences belonged to proteins with the same or a very similar function. Given an appropriate cutoff, the rate of false positives was zero. According to our results, this protocol, here referred to as Rd.HMM, detects fine structural details on the folding patterns, that seem to be tightly linked to the fitness of a structural framework for a specific biological function. Conclusion Because the sequence of the native protein used to create the Rd.HMM model was always amongst the top hits, the procedure is a reliable tool to score, very accurately, the quality and appropriateness of computer-modeled 3D-structures, without the need for spectroscopy data. However, Rd.HMM is very sensitive to the conformational features of the models' backbone. PMID:20830209

NCBI Reference Sequence (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins

PubMed Central

Pruitt, Kim D.; Tatusova, Tatiana; Maglott, Donna R.

2005-01-01

The National Center for Biotechnology Information (NCBI) Reference Sequence (RefSeq) database (http://www.ncbi.nlm.nih.gov/RefSeq/) provides a non-redundant collection of sequences representing genomic data, transcripts and proteins. Although the goal is to provide a comprehensive dataset representing the complete sequence information for any given species, the database pragmatically includes sequence data that are currently publicly available in the archival databases. The database incorporates data from over 2400 organisms and includes over one million proteins representing significant taxonomic diversity spanning prokaryotes, eukaryotes and viruses. Nucleotide and protein sequences are explicitly linked, and the sequences are linked to other resources including the NCBI Map Viewer and Gene. Sequences are annotated to include coding regions, conserved domains, variation, references, names, database cross-references, and other features using a combined approach of collaboration and other input from the scientific community, automated annotation, propagation from GenBank and curation by NCBI staff. PMID:15608248

Coarse-grained sequences for protein folding and design.

PubMed

Brown, Scott; Fawzi, Nicolas J; Head-Gordon, Teresa

2003-09-16

We present the results of sequence design on our off-lattice minimalist model in which no specification of native-state tertiary contacts is needed. We start with a sequence that adopts a target topology and build on it through sequence mutation to produce new sequences that comprise distinct members within a target fold class. In this work, we use the alpha/beta ubiquitin fold class and design two new sequences that, when characterized through folding simulations, reproduce the differences in folding mechanism seen experimentally for proteins L and G. The primary implication of this work is that patterning of hydrophobic and hydrophilic residues is the physical origin for the success of relative contact-order descriptions of folding, and that these physics-based potentials provide a predictive connection between free energy landscapes and amino acid sequence (the original protein folding problem). We present results of the sequence mapping from a 20- to the three-letter code for determining a sequence that folds into the WW domain topology to illustrate future extensions to protein design.

Coarse-grained sequences for protein folding and design

PubMed Central

Brown, Scott; Fawzi, Nicolas J.; Head-Gordon, Teresa

2003-01-01

We present the results of sequence design on our off-lattice minimalist model in which no specification of native-state tertiary contacts is needed. We start with a sequence that adopts a target topology and build on it through sequence mutation to produce new sequences that comprise distinct members within a target fold class. In this work, we use the α/β ubiquitin fold class and design two new sequences that, when characterized through folding simulations, reproduce the differences in folding mechanism seen experimentally for proteins L and G. The primary implication of this work is that patterning of hydrophobic and hydrophilic residues is the physical origin for the success of relative contact-order descriptions of folding, and that these physics-based potentials provide a predictive connection between free energy landscapes and amino acid sequence (the original protein folding problem). We present results of the sequence mapping from a 20- to the three-letter code for determining a sequence that folds into the WW domain topology to illustrate future extensions to protein design. PMID:12963815

Characterization of DNA-protein interactions using high-throughput sequencing data from pulldown experiments

NASA Astrophysics Data System (ADS)

Moreland, Blythe; Oman, Kenji; Curfman, John; Yan, Pearlly; Bundschuh, Ralf

Methyl-binding domain (MBD) protein pulldown experiments have been a valuable tool in measuring the levels of methylated CpG dinucleotides. Due to the frequent use of this technique, high-throughput sequencing data sets are available that allow a detailed quantitative characterization of the underlying interaction between methylated DNA and MBD proteins. Analyzing such data sets, we first found that two such proteins cannot bind closer to each other than 2 bp, consistent with structural models of the DNA-protein interaction. Second, the large amount of sequencing data allowed us to find rather weak but nevertheless clearly statistically significant sequence preferences for several bases around the required CpG. These results demonstrate that pulldown sequencing is a high-precision tool in characterizing DNA-protein interactions. This material is based upon work supported by the National Science Foundation under Grant No. DMR-1410172.

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

PubMed

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.

A Fast Alignment-Free Approach for De Novo Detection of Protein Conserved Regions

PubMed Central

Abnousi, Armen; Broschat, Shira L.; Kalyanaraman, Ananth

2016-01-01

Background Identifying conserved regions in protein sequences is a fundamental operation, occurring in numerous sequence-driven analysis pipelines. It is used as a way to decode domain-rich regions within proteins, to compute protein clusters, to annotate sequence function, and to compute evolutionary relationships among protein sequences. A number of approaches exist for identifying and characterizing protein families based on their domains, and because domains represent conserved portions of a protein sequence, the primary computation involved in protein family characterization is identification of such conserved regions. However, identifying conserved regions from large collections (millions) of protein sequences presents significant challenges. Methods In this paper we present a new, alignment-free method for detecting conserved regions in protein sequences called NADDA (No-Alignment Domain Detection Algorithm). Our method exploits the abundance of exact matching short subsequences (k-mers) to quickly detect conserved regions, and the power of machine learning is used to improve the prediction accuracy of detection. We present a parallel implementation of NADDA using the MapReduce framework and show that our method is highly scalable. Results We have compared NADDA with Pfam and InterPro databases. For known domains annotated by Pfam, accuracy is 83%, sensitivity 96%, and specificity 44%. For sequences with new domains not present in the training set an average accuracy of 63% is achieved when compared to Pfam. A boost in results in comparison with InterPro demonstrates the ability of NADDA to capture conserved regions beyond those present in Pfam. We have also compared NADDA with ADDA and MKDOM2, assuming Pfam as ground-truth. On average NADDA shows comparable accuracy, more balanced sensitivity and specificity, and being alignment-free, is significantly faster. Excluding the one-time cost of training, runtimes on a single processor were 49s, 10,566s, and 456s for NADDA, ADDA, and MKDOM2, respectively, for a data set comprised of approximately 2500 sequences. PMID:27552220

The cDNA sequence of mouse Pgp-1 and homology to human CD44 cell surface antigen and proteoglycan core/link proteins.

PubMed

Wolffe, E J; Gause, W C; Pelfrey, C M; Holland, S M; Steinberg, A D; August, J T

1990-01-05

We describe the isolation and sequencing of a cDNA encoding mouse Pgp-1. An oligonucleotide probe corresponding to the NH2-terminal sequence of the purified protein was synthesized by the polymerase chain reaction and used to screen a mouse macrophage lambda gt11 library. A cDNA clone with an insert of 1.2 kilobases was selected and sequenced. In Northern blot analysis, only cells expressing Pgp-1 contained mRNA species that hybridized with this Pgp-1 cDNA. The nucleotide sequence of the cDNA has a single open reading frame that yields a protein-coding sequence of 1076 base pairs followed by a 132-base pair 3'-untranslated sequence that includes a putative polyadenylation signal but no poly(A) tail. The translated sequence comprises a 13-amino acid signal peptide followed by a polypeptide core of 345 residues corresponding to an Mr of 37,800. Portions of the deduced amino acid sequence were identical to those obtained by amino acid sequence analysis from the purified glycoprotein, confirming that the cDNA encodes Pgp-1. The predicted structure of Pgp-1 includes an NH2-terminal extracellular domain (residues 14-265), a transmembrane domain (residues 266-286), and a cytoplasmic tail (residues 287-358). Portions of the mouse Pgp-1 sequence are highly similar to that of the human CD44 cell surface glycoprotein implicated in cell adhesion. The protein also shows sequence similarity to the proteoglycan tandem repeat sequences found in cartilage link protein and cartilage proteoglycan core protein which are thought to be involved in binding to hyaluronic acid.

DWARF – a data warehouse system for analyzing protein families

PubMed Central

Fischer, Markus; Thai, Quan K; Grieb, Melanie; Pleiss, Jürgen

2006-01-01

Background The emerging field of integrative bioinformatics provides the tools to organize and systematically analyze vast amounts of highly diverse biological data and thus allows to gain a novel understanding of complex biological systems. The data warehouse DWARF applies integrative bioinformatics approaches to the analysis of large protein families. Description The data warehouse system DWARF integrates data on sequence, structure, and functional annotation for protein fold families. The underlying relational data model consists of three major sections representing entities related to the protein (biochemical function, source organism, classification to homologous families and superfamilies), the protein sequence (position-specific annotation, mutant information), and the protein structure (secondary structure information, superimposed tertiary structure). Tools for extracting, transforming and loading data from public available resources (ExPDB, GenBank, DSSP) are provided to populate the database. The data can be accessed by an interface for searching and browsing, and by analysis tools that operate on annotation, sequence, or structure. We applied DWARF to the family of α/β-hydrolases to host the Lipase Engineering database. Release 2.3 contains 6138 sequences and 167 experimentally determined protein structures, which are assigned to 37 superfamilies 103 homologous families. Conclusion DWARF has been designed for constructing databases of large structurally related protein families and for evaluating their sequence-structure-function relationships by a systematic analysis of sequence, structure and functional annotation. It has been applied to predict biochemical properties from sequence, and serves as a valuable tool for protein engineering. PMID:17094801

Indel PDB: a database of structural insertions and deletions derived from sequence alignments of closely related proteins.

PubMed

Hsing, Michael; Cherkasov, Artem

2008-06-25

Insertions and deletions (indels) represent a common type of sequence variations, which are less studied and pose many important biological questions. Recent research has shown that the presence of sizable indels in protein sequences may be indicative of protein essentiality and their role in protein interaction networks. Examples of utilization of indels for structure-based drug design have also been recently demonstrated. Nonetheless many structural and functional characteristics of indels remain less researched or unknown. We have created a web-based resource, Indel PDB, representing a structural database of insertions/deletions identified from the sequence alignments of highly similar proteins found in the Protein Data Bank (PDB). Indel PDB utilized large amounts of available structural information to characterize 1-, 2- and 3-dimensional features of indel sites. Indel PDB contains 117,266 non-redundant indel sites extracted from 11,294 indel-containing proteins. Unlike loop databases, Indel PDB features more indel sequences with secondary structures including alpha-helices and beta-sheets in addition to loops. The insertion fragments have been characterized by their sequences, lengths, locations, secondary structure composition, solvent accessibility, protein domain association and three dimensional structures. By utilizing the data available in Indel PDB, we have studied and presented here several sequence and structural features of indels. We anticipate that Indel PDB will not only enable future functional studies of indels, but will also assist protein modeling efforts and identification of indel-directed drug binding sites.

Sequence Determines Degree of Knottedness in a Coarse-Grained Protein Model

NASA Astrophysics Data System (ADS)

Wüst, Thomas; Reith, Daniel; Virnau, Peter

2015-01-01

Knots are abundant in globular homopolymers but rare in globular proteins. To shed new light on this long-standing conundrum, we study the influence of sequence on the formation of knots in proteins under native conditions within the framework of the hydrophobic-polar lattice protein model. By employing large-scale Wang-Landau simulations combined with suitable Monte Carlo trial moves we show that even though knots are still abundant on average, sequence introduces large variability in the degree of self-entanglements. Moreover, we are able to design sequences which are either almost always or almost never knotted. Our findings serve as proof of concept that the introduction of just one additional degree of freedom per monomer (in our case sequence) facilitates evolution towards a protein universe in which knots are rare.

A Generative Angular Model of Protein Structure Evolution

PubMed Central

Golden, Michael; García-Portugués, Eduardo; Sørensen, Michael; Mardia, Kanti V.; Hamelryck, Thomas; Hein, Jotun

2017-01-01

Abstract Recently described stochastic models of protein evolution have demonstrated that the inclusion of structural information in addition to amino acid sequences leads to a more reliable estimation of evolutionary parameters. We present a generative, evolutionary model of protein structure and sequence that is valid on a local length scale. The model concerns the local dependencies between sequence and structure evolution in a pair of homologous proteins. The evolutionary trajectory between the two structures in the protein pair is treated as a random walk in dihedral angle space, which is modeled using a novel angular diffusion process on the two-dimensional torus. Coupling sequence and structure evolution in our model allows for modeling both “smooth” conformational changes and “catastrophic” conformational jumps, conditioned on the amino acid changes. The model has interpretable parameters and is comparatively more realistic than previous stochastic models, providing new insights into the relationship between sequence and structure evolution. For example, using the trained model we were able to identify an apparent sequence–structure evolutionary motif present in a large number of homologous protein pairs. The generative nature of our model enables us to evaluate its validity and its ability to simulate aspects of protein evolution conditioned on an amino acid sequence, a related amino acid sequence, a related structure or any combination thereof. PMID:28453724

PANTHER: a browsable database of gene products organized by biological function, using curated protein family and subfamily classification.

PubMed

Thomas, Paul D; Kejariwal, Anish; Campbell, Michael J; Mi, Huaiyu; Diemer, Karen; Guo, Nan; Ladunga, Istvan; Ulitsky-Lazareva, Betty; Muruganujan, Anushya; Rabkin, Steven; Vandergriff, Jody A; Doremieux, Olivier

2003-01-01

The PANTHER database was designed for high-throughput analysis of protein sequences. One of the key features is a simplified ontology of protein function, which allows browsing of the database by biological functions. Biologist curators have associated the ontology terms with groups of protein sequences rather than individual sequences. Statistical models (Hidden Markov Models, or HMMs) are built from each of these groups. The advantage of this approach is that new sequences can be automatically classified as they become available. To ensure accurate functional classification, HMMs are constructed not only for families, but also for functionally distinct subfamilies. Multiple sequence alignments and phylogenetic trees, including curator-assigned information, are available for each family. The current version of the PANTHER database includes training sequences from all organisms in the GenBank non-redundant protein database, and the HMMs have been used to classify gene products across the entire genomes of human, and Drosophila melanogaster. The ontology terms and protein families and subfamilies, as well as Drosophila gene c;assifications, can be browsed and searched for free. Due to outstanding contractual obligations, access to human gene classifications and to protein family trees and multiple sequence alignments will temporarily require a nominal registration fee. PANTHER is publicly available on the web at http://panther.celera.com.

The Protein Information Resource: an integrated public resource of functional annotation of proteins

PubMed Central

Wu, Cathy H.; Huang, Hongzhan; Arminski, Leslie; Castro-Alvear, Jorge; Chen, Yongxing; Hu, Zhang-Zhi; Ledley, Robert S.; Lewis, Kali C.; Mewes, Hans-Werner; Orcutt, Bruce C.; Suzek, Baris E.; Tsugita, Akira; Vinayaka, C. R.; Yeh, Lai-Su L.; Zhang, Jian; Barker, Winona C.

2002-01-01

The Protein Information Resource (PIR) serves as an integrated public resource of functional annotation of protein data to support genomic/proteomic research and scientific discovery. The PIR, in collaboration with the Munich Information Center for Protein Sequences (MIPS) and the Japan International Protein Information Database (JIPID), produces the PIR-International Protein Sequence Database (PSD), the major annotated protein sequence database in the public domain, containing about 250 000 proteins. To improve protein annotation and the coverage of experimentally validated data, a bibliography submission system is developed for scientists to submit, categorize and retrieve literature information. Comprehensive protein information is available from iProClass, which includes family classification at the superfamily, domain and motif levels, structural and functional features of proteins, as well as cross-references to over 40 biological databases. To provide timely and comprehensive protein data with source attribution, we have introduced a non-redundant reference protein database, PIR-NREF. The database consists of about 800 000 proteins collected from PIR-PSD, SWISS-PROT, TrEMBL, GenPept, RefSeq and PDB, with composite protein names and literature data. To promote database interoperability, we provide XML data distribution and open database schema, and adopt common ontologies. The PIR web site (http://pir.georgetown.edu/) features data mining and sequence analysis tools for information retrieval and functional identification of proteins based on both sequence and annotation information. The PIR databases and other files are also available by FTP (ftp://nbrfa.georgetown.edu/pir_databases). PMID:11752247

Analysis of secreted proteins from Aspergillus flavus.

PubMed

Medina, Martha L; Haynes, Paul A; Breci, Linda; Francisco, Wilson A

2005-08-01

MS/MS techniques in proteomics make possible the identification of proteins from organisms with little or no genome sequence information available. Peptide sequences are obtained from tandem mass spectra by matching peptide mass and fragmentation information to protein sequence information from related organisms, including unannotated genome sequence data. This peptide identification data can then be grouped and reconstructed into protein data. In this study, we have used this approach to study protein secretion by Aspergillus flavus, a filamentous fungus for which very little genome sequence information is available. A. flavus is capable of degrading the flavonoid rutin (quercetin 3-O-glycoside), as the only source of carbon via an extracellular enzyme system. In this continuing study, a proteomic analysis was used to identify secreted proteins from A. flavus when grown on rutin. The growth media glucose and potato dextrose were used to identify differentially expressed secreted proteins. The secreted proteins were analyzed by 1- and 2-DE and MS/MS. A total of 51 unique A. flavus secreted proteins were identified from the three growth conditions. Ten proteins were unique to rutin-, five to glucose- and one to potato dextrose-grown A. flavus. Sixteen secreted proteins were common to all three media. Fourteen identifications were of hypothetical proteins or proteins of unknown functions. To our knowledge, this is the first extensive proteomic study conducted to identify the secreted proteins from a filamentous fungus.

High-throughput analysis of the protein sequence-stability landscape using a quantitative "yeast surface two-hybrid" system and fragment reconstitution

PubMed Central

Dutta, Sanjib; Koide, Akiko; Koide, Shohei

2008-01-01

Stability evaluation of many mutants can lead to a better understanding of the sequence determinants of a structural motif and of factors governing protein stability and protein evolution. The traditional biophysical analysis of protein stability is low throughput, limiting our ability to widely explore the sequence space in a quantitative manner. In this study, we have developed a high-throughput library screening method for quantifying stability changes, which is based on protein fragment reconstitution and yeast surface display. Our method exploits the thermodynamic linkage between protein stability and fragment reconstitution and the ability of the yeast surface display technique to quantitatively evaluate protein-protein interactions. The method was applied to a fibronectin type III (FN3) domain. Characterization of fragment reconstitution was facilitated by the co-expression of two FN3 fragments, thus establishing a "yeast surface two-hybrid" method. Importantly, our method does not rely on competition between clones and thus eliminates a common limitation of high-throughput selection methods in which the most stable variants are predominantly recovered. Thus, it allows for the isolation of sequences that exhibits a desired level of stability. We identified over one hundred unique sequences for a β-bulge motif, which was significantly more informative than natural sequences of the FN3 family in revealing the sequence determinants for the β-bulge. Our method provides a powerful means to rapidly assess stability of many variants, to systematically assess contribution of different factors to protein stability and to enhance protein stability. PMID:18674545

Extreme Sensory Complexity Encoded in the 10-Megabase Draft Genome Sequence of the Chromatically Acclimating Cyanobacterium Tolypothrix sp. PCC 7601.

PubMed

Yerrapragada, Shaila; Shukla, Animesh; Hallsworth-Pepin, Kymberlie; Choi, Kwangmin; Wollam, Aye; Clifton, Sandra; Qin, Xiang; Muzny, Donna; Raghuraman, Sriram; Ashki, Haleh; Uzman, Akif; Highlander, Sarah K; Fryszczyn, Bartlomiej G; Fox, George E; Tirumalai, Madhan R; Liu, Yamei; Kim, Sun; Kehoe, David M; Weinstock, George M

2015-05-07

Tolypothrix sp. PCC 7601 is a freshwater filamentous cyanobacterium with complex responses to environmental conditions. Here, we present its 9.96-Mbp draft genome sequence, containing 10,065 putative protein-coding sequences, including 305 predicted two-component system proteins and 27 putative phytochrome-class photoreceptors, the most such proteins in any sequenced genome. Copyright © 2015 Yerrapragada et al.

A family of cellular proteins related to snake venom disintegrins.

PubMed

Weskamp, G; Blobel, C P

1994-03-29

Disintegrins are short soluble integrin ligands that were initially identified in snake venom. A previously recognized cellular protein with a disintegrin domain was the guinea pig sperm protein PH-30, a protein implicated in sperm-egg membrane binding and fusion. Here we present peptide sequences that are characteristic for several cellular disintegrin-domain proteins. These peptide sequences were deduced from cDNA sequence tags that were generated by polymerase chain reaction from various mouse tissue and a mouse muscle cell line. Northern blot analysis with four sequence tags revealed distinct mRNA expression patterns. Evidently, cellular proteins containing a disintegrin domain define a superfamily of potential integrin ligands that are likely to function in important cell-cell and cell-matrix interactions.

Identification and application of self-binding zipper-like sequences in SARS-CoV spike protein.

PubMed

Zhang, Si Min; Liao, Ying; Neo, Tuan Ling; Lu, Yanning; Liu, Ding Xiang; Vahlne, Anders; Tam, James P

2018-05-22

Self-binding peptides containing zipper-like sequences, such as the Leu/Ile zipper sequence within the coiled coil regions of proteins and the cross-β spine steric zippers within the amyloid-like fibrils, could bind to the protein-of-origin through homophilic sequence-specific zipper motifs. These self-binding sequences represent opportunities for the development of biochemical tools and/or therapeutics. Here, we report on the identification of a putative self-binding β-zipper-forming peptide within the severe acute respiratory syndrome-associated coronavirus spike (S) protein and its application in viral detection. Peptide array scanning of overlapping peptides covering the entire length of S protein identified 34 putative self-binding peptides of six clusters, five of which contained octapeptide core consensus sequences. The Cluster I consensus octapeptide sequence GINITNFR was predicted by the Eisenberg's 3D profile method to have high amyloid-like fibrillation potential through steric β-zipper formation. Peptide C6 containing the Cluster I consensus sequence was shown to oligomerize and form amyloid-like fibrils. Taking advantage of this, C6 was further applied to detect the S protein expression in vitro by fluorescence staining. Meanwhile, the coiled-coil-forming Leu/Ile heptad repeat sequences within the S protein were under-represented during peptide array scanning, in agreement with that long peptide lengths were required to attain high helix-mediated interaction avidity. The data suggest that short β-zipper-like self-binding peptides within the S protein could be identified through combining the peptide scanning and predictive methods, and could be exploited as biochemical detection reagents for viral infection. Copyright © 2018. Published by Elsevier Ltd.

Graphene Nanopores for Protein Sequencing.

PubMed

Wilson, James; Sloman, Leila; He, Zhiren; Aksimentiev, Aleksei

2016-07-19

An inexpensive, reliable method for protein sequencing is essential to unraveling the biological mechanisms governing cellular behavior and disease. Current protein sequencing methods suffer from limitations associated with the size of proteins that can be sequenced, the time, and the cost of the sequencing procedures. Here, we report the results of all-atom molecular dynamics simulations that investigated the feasibility of using graphene nanopores for protein sequencing. We focus our study on the biologically significant phenylalanine-glycine repeat peptides (FG-nups)-parts of the nuclear pore transport machinery. Surprisingly, we found FG-nups to behave similarly to single stranded DNA: the peptides adhere to graphene and exhibit step-wise translocation when subject to a transmembrane bias or a hydrostatic pressure gradient. Reducing the peptide's charge density or increasing the peptide's hydrophobicity was found to decrease the translocation speed. Yet, unidirectional and stepwise translocation driven by a transmembrane bias was observed even when the ratio of charged to hydrophobic amino acids was as low as 1:8. The nanopore transport of the peptides was found to produce stepwise modulations of the nanopore ionic current correlated with the type of amino acids present in the nanopore, suggesting that protein sequencing by measuring ionic current blockades may be possible.

Adhesive Proteins of Stalked and Acorn Barnacles Display Homology with Low Sequence Similarities

PubMed Central

Jonker, Jaimie-Leigh; Abram, Florence; Pires, Elisabete; Varela Coelho, Ana; Grunwald, Ingo; Power, Anne Marie

2014-01-01

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). PMID:25295513

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

PubMed

Jonker, Jaimie-Leigh; Abram, Florence; Pires, Elisabete; Varela Coelho, Ana; Grunwald, Ingo; Power, Anne Marie

2014-01-01

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).

Meta-structure correlation in protein space unveils different selection rules for folded and intrinsically disordered proteins.

PubMed

Naranjo, Yandi; Pons, Miquel; Konrat, Robert

2012-01-01

The number of existing protein sequences spans a very small fraction of sequence space. Natural proteins have overcome a strong negative selective pressure to avoid the formation of insoluble aggregates. Stably folded globular proteins and intrinsically disordered proteins (IDPs) use alternative solutions to the aggregation problem. While in globular proteins folding minimizes the access to aggregation prone regions, IDPs on average display large exposed contact areas. Here, we introduce the concept of average meta-structure correlation maps to analyze sequence space. Using this novel conceptual view we show that representative ensembles of folded and ID proteins show distinct characteristics and respond differently to sequence randomization. By studying the way evolutionary constraints act on IDPs to disable a negative function (aggregation) we might gain insight into the mechanisms by which function-enabling information is encoded in IDPs.

The limits of protein sequence comparison?

PubMed Central

Pearson, William R; Sierk, Michael L

2010-01-01

Modern sequence alignment algorithms are used routinely to identify homologous proteins, proteins that share a common ancestor. Homologous proteins always share similar structures and often have similar functions. Over the past 20 years, sequence comparison has become both more sensitive, largely because of profile-based methods, and more reliable, because of more accurate statistical estimates. As sequence and structure databases become larger, and comparison methods become more powerful, reliable statistical estimates will become even more important for distinguishing similarities that are due to homology from those that are due to analogy (convergence). The newest sequence alignment methods are more sensitive than older methods, but more accurate statistical estimates are needed for their full power to be realized. PMID:15919194

Advances in Understanding Stimulus Responsive Phase Behavior of Intrinsically Disordered Protein Polymers.

PubMed

Ruff, Kiersten M; Roberts, Stefan; Chilkoti, Ashutosh; Pappu, Rohit V

2018-06-24

Proteins and synthetic polymers can undergo phase transitions in response to changes to intensive solution parameters such as temperature, proton chemical potentials (pH), and hydrostatic pressure. For proteins and protein-based polymers, the information required for stimulus responsive phase transitions is encoded in their amino acid sequence. Here, we review some of the key physical principles that govern the phase transitions of archetypal intrinsically disordered protein polymers (IDPPs). These are disordered proteins with highly repetitive amino acid sequences. Advances in recombinant technologies have enabled the design and synthesis of protein sequences of a variety of sequence complexities and lengths. We summarize insights that have been gleaned from the design and characterization of IDPPs that undergo thermo-responsive phase transitions and build on these insights to present a general framework for IDPPs with pH and pressure responsive phase behavior. In doing so, we connect the stimulus responsive phase behavior of IDPPs with repetitive sequences to the coil-to-globule transitions that these sequences undergo at the single chain level in response to changes in stimuli. The proposed framework and ongoing studies of stimulus responsive phase behavior of designed IDPPs have direct implications in bioengineering, where designing sequences with bespoke material properties broadens the spectrum of applications, and in biology and medicine for understanding the sequence-specific driving forces for the formation of protein-based membraneless organelles as well as biological matrices that act as scaffolds for cells and mediators of cell-to-cell communication. Copyright © 2018. Published by Elsevier Ltd.

Function-based classification of carbohydrate-active enzymes by recognition of short, conserved peptide motifs.

PubMed

Busk, Peter Kamp; Lange, Lene

2013-06-01

Functional prediction of carbohydrate-active enzymes is difficult due to low sequence identity. However, similar enzymes often share a few short motifs, e.g., around the active site, even when the overall sequences are very different. To exploit this notion for functional prediction of carbohydrate-active enzymes, we developed a simple algorithm, peptide pattern recognition (PPR), that can divide proteins into groups of sequences that share a set of short conserved sequences. When this method was used on 118 glycoside hydrolase 5 proteins with 9% average pairwise identity and representing four characterized enzymatic functions, 97% of the proteins were sorted into groups correlating with their enzymatic activity. Furthermore, we analyzed 8,138 glycoside hydrolase 13 proteins including 204 experimentally characterized enzymes with 28 different functions. There was a 91% correlation between group and enzyme activity. These results indicate that the function of carbohydrate-active enzymes can be predicted with high precision by finding short, conserved motifs in their sequences. The glycoside hydrolase 61 family is important for fungal biomass conversion, but only a few proteins of this family have been functionally characterized. Interestingly, PPR divided 743 glycoside hydrolase 61 proteins into 16 subfamilies useful for targeted investigation of the function of these proteins and pinpointed three conserved motifs with putative importance for enzyme activity. Furthermore, the conserved sequences were useful for cloning of new, subfamily-specific glycoside hydrolase 61 proteins from 14 fungi. In conclusion, identification of conserved sequence motifs is a new approach to sequence analysis that can predict carbohydrate-active enzyme functions with high precision.

The primary structure of rat liver ribosomal protein L37. Homology with yeast and bacterial ribosomal proteins.

PubMed

Lin, A; McNally, J; Wool, I G

1983-09-10

The covalent structure of the rat liver 60 S ribosomal subunit protein L37 was determined. Twenty-four tryptic peptides were purified and the sequence of each was established; they accounted for all 111 residues of L37. The sequence of the first 30 residues of L37, obtained previously by automated Edman degradation of the intact protein, provided the alignment of the first 9 tryptic peptides. Three peptides (CN1, CN2, and CN3) were produced by cleavage of protein L37 with cyanogen bromide. The sequence of CN1 (65 residues) was established from the sequence of secondary peptides resulting from cleavage with trypsin and chymotrypsin. The sequence of CN1 in turn served to order tryptic peptides 1 through 14. The sequence of CN2 (15 residues) was determined entirely by a micromanual procedure and allowed the alignment of tryptic peptides 14 through 18. The sequence of the NH2-terminal 28 amino acids of CN3 (31 residues) was determined; in addition the complete sequences of the secondary tryptic and chymotryptic peptides were done. The sequence of CN3 provided the order of tryptic peptides 18 through 24. Thus the sequence of the three cyanogen bromide peptides also accounted for the 111 residues of protein L37. The carboxyl-terminal amino acids were identified after carboxypeptidase A treatment. There is a disulfide bridge between half-cystinyl residues at positions 40 and 69. Rat liver ribosomal protein L37 is homologous with yeast YP55 and with Escherichia coli L34. Moreover, there is a segment of 17 residues in rat L37 that occurs, albeit with modifications, in yeast YP55 and in E. coli S4, L20, and L34.

LenVarDB: database of length-variant protein domains.

PubMed

Mutt, Eshita; Mathew, Oommen K; Sowdhamini, Ramanathan

2014-01-01

Protein domains are functionally and structurally independent modules, which add to the functional variety of proteins. This array of functional diversity has been enabled by evolutionary changes, such as amino acid substitutions or insertions or deletions, occurring in these protein domains. Length variations (indels) can introduce changes at structural, functional and interaction levels. LenVarDB (freely available at http://caps.ncbs.res.in/lenvardb/) traces these length variations, starting from structure-based sequence alignments in our Protein Alignments organized as Structural Superfamilies (PASS2) database, across 731 structural classification of proteins (SCOP)-based protein domain superfamilies connected to 2 730 625 sequence homologues. Alignment of sequence homologues corresponding to a structural domain is available, starting from a structure-based sequence alignment of the superfamily. Orientation of the length-variant (indel) regions in protein domains can be visualized by mapping them on the structure and on the alignment. Knowledge about location of length variations within protein domains and their visual representation will be useful in predicting changes within structurally or functionally relevant sites, which may ultimately regulate protein function. Non-technical summary: Evolutionary changes bring about natural changes to proteins that may be found in many organisms. Such changes could be reflected as amino acid substitutions or insertions-deletions (indels) in protein sequences. LenVarDB is a database that provides an early overview of observed length variations that were set among 731 protein families and after examining >2 million sequences. Indels are followed up to observe if they are close to the active site such that they can affect the activity of proteins. Inclusion of such information can aid the design of bioengineering experiments.

Multi-level machine learning prediction of protein-protein interactions in Saccharomyces cerevisiae.

PubMed

Zubek, Julian; Tatjewski, Marcin; Boniecki, Adam; Mnich, Maciej; Basu, Subhadip; Plewczynski, Dariusz

2015-01-01

Accurate identification of protein-protein interactions (PPI) is the key step in understanding proteins' biological functions, which are typically context-dependent. Many existing PPI predictors rely on aggregated features from protein sequences, however only a few methods exploit local information about specific residue contacts. In this work we present a two-stage machine learning approach for prediction of protein-protein interactions. We start with the carefully filtered data on protein complexes available for Saccharomyces cerevisiae in the Protein Data Bank (PDB) database. First, we build linear descriptions of interacting and non-interacting sequence segment pairs based on their inter-residue distances. Secondly, we train machine learning classifiers to predict binary segment interactions for any two short sequence fragments. The final prediction of the protein-protein interaction is done using the 2D matrix representation of all-against-all possible interacting sequence segments of both analysed proteins. The level-I predictor achieves 0.88 AUC for micro-scale, i.e., residue-level prediction. The level-II predictor improves the results further by a more complex learning paradigm. We perform 30-fold macro-scale, i.e., protein-level cross-validation experiment. The level-II predictor using PSIPRED-predicted secondary structure reaches 0.70 precision, 0.68 recall, and 0.70 AUC, whereas other popular methods provide results below 0.6 threshold (recall, precision, AUC). Our results demonstrate that multi-scale sequence features aggregation procedure is able to improve the machine learning results by more than 10% as compared to other sequence representations. Prepared datasets and source code for our experimental pipeline are freely available for download from: http://zubekj.github.io/mlppi/ (open source Python implementation, OS independent).

The primary structures of ribosomal proteins L16, L23 and L33 from the archaebacterium Halobacterium marismortui.

PubMed

Hatakeyama, T; Hatakeyama, T; Kimura, M

1988-11-21

The complete amino acid sequences of ribosomal proteins L16, L23 and L33 from the archaebacterium Halobacterium marismortui were determined. The sequences were established by manual sequencing of peptides produced with several proteases as well as by cleavage with dilute HCl. Proteins L16, L23 and L33 consist of 119, 154 and 69 amino acid residues, and their molecular masses are 13,538, 16,812 and 7620 Da, respectively. The comparison of their sequences with those of ribosomal proteins from other organisms revealed that L23 and L33 are related to eubacterial ribosomal proteins from Escherichia coli and Bacillus stearothermophilus, while protein L16 was found to be homologous to a eukaryotic ribosomal protein from yeast. These results provide information about the special phylogenetic position of archaebacteria.

[Multiplexing mapping of human cDNAs]. Final report, September 1, 1991--February 28, 1994

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

Using PCR with automated product analysis, 329 human brain cDNA sequences have been assigned to individual human chromosomes. Primers were designed from single-pass cDNA sequences expressed sequence tags (ESTs). Primers were used in PCR reactions with DNA from somatic cell hybrid mapping panels as templates, often with multiplexing. Many ESTs mapped match sequence database records. To evaluate of these matches, the position of the primers relative to the matching region (In), the BLAST scores and the Poisson probability values of the EST/sequence record match were determined. In cases where the gene product was stringently identified by the sequence match hadmore » already been mapped, the gene locus determined by EST was consistent with the previous position which strongly supports the validity of assigning unknown genes to human chromosomes based on the EST sequence matches. In the present cases mapping the ESTs to a chromosome can also be considered to have mapped the known gene product: rolipram-sensitive cAMP phosphodiesterase, chromosome 1; protein phosphatase 2A{beta}, chromosome 4; alpha-catenin, chromosome 5; the ELE1 oncogene, chromosome 10q11.2 or q2.1-q23; MXII protein, chromosome l0q24-qter; ribosomal protein L18a homologue, chromosome 14; ribosomal protein L3, chromosome 17; and moesin, Xp11-cen. There were also ESTs mapped that were closely related to non-human sequence records. These matches therefore can be considered to identify human counterparts of known gene products, or members of known gene families. Examples of these include membrane proteins, translation-associated proteins, structural proteins, and enzymes. These data then demonstrate that single pass sequence information is sufficient to design PCR primers useful for assigning cDNA sequences to human chromosomes. When the EST sequence matches previous sequence database records, the chromosome assignments of the EST can be used to make preliminary assignments of the human gene to a chromosome.« less

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

PubMed Central

Modahl, Cassandra M.; Mackessy, Stephen P.

2016-01-01

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 access to cDNA sequences in the absence of living specimens, even from commercial venom sources, to evaluate important regional differences in venom composition and to study snake venom protein evolution. PMID:27280639

Predicting protein-binding RNA nucleotides with consideration of binding partners.

PubMed

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

2015-06-01

In recent years several computational methods have been developed to predict RNA-binding sites in protein. Most of these methods do not consider interacting partners of a protein, so they predict the same RNA-binding sites for a given protein sequence even if the protein binds to different RNAs. Unlike the problem of predicting RNA-binding sites in protein, the problem of predicting protein-binding sites in RNA has received little attention mainly because it is much more difficult and shows a lower accuracy on average. In our previous study, we developed a method that predicts protein-binding nucleotides from an RNA sequence. In an effort to improve the prediction accuracy and usefulness of the previous method, we developed a new method that uses both RNA and protein sequence data. In this study, we identified effective features of RNA and protein molecules and developed a new support vector machine (SVM) model to predict protein-binding nucleotides from RNA and protein sequence data. The new model that used both protein and RNA sequence data achieved a sensitivity of 86.5%, a specificity of 86.2%, a positive predictive value (PPV) of 72.6%, a negative predictive value (NPV) of 93.8% and Matthews correlation coefficient (MCC) of 0.69 in a 10-fold cross validation; it achieved a sensitivity of 58.8%, a specificity of 87.4%, a PPV of 65.1%, a NPV of 84.2% and MCC of 0.48 in independent testing. For comparative purpose, we built another prediction model that used RNA sequence data alone and ran it on the same dataset. In a 10 fold-cross validation it achieved a sensitivity of 85.7%, a specificity of 80.5%, a PPV of 67.7%, a NPV of 92.2% and MCC of 0.63; in independent testing it achieved a sensitivity of 67.7%, a specificity of 78.8%, a PPV of 57.6%, a NPV of 85.2% and MCC of 0.45. In both cross-validations and independent testing, the new model that used both RNA and protein sequences showed a better performance than the model that used RNA sequence data alone in most performance measures. To the best of our knowledge, this is the first sequence-based prediction of protein-binding nucleotides in RNA which considers the binding partner of RNA. The new model will provide valuable information for designing biochemical experiments to find putative protein-binding sites in RNA with unknown structure. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Probing the Proteome on Earth and Beyond

NASA Astrophysics Data System (ADS)

Ostrom, P.

2008-12-01

Less than a decade ago, protein sequencing was the bane of paleobiology. Since that time researchers have completely sequenced proteins in >50 Ka fossils, been dazzled by reports of collagen peptides in dinosaur bones, and witnessed the development of phylogenetic trees from ancient protein sequences. Enlisting proteomics as biosignature is now in our grasp. In this talk the pitfalls and challenges of mass spectrometric approaches to protein sequencing will be illustrated and phylogenetic applications will be discussed. Work on extinct organisms at Michigan State University, University of Michigan and York University will provide a vantage point to assess methodologies, explore diagenetic alterations, evaluate mass spectra and illustrate issues associated with data base searching. Challenges encountered in the study of paleoproteomics, such as the absence of sequences for extinct organisms in commercially available databases, protein diagenesis and low concentrations of target are parallel to those that will be encountered when protein sequencing is extended to extreme and extraterrestrial environments. Thus, lessons learned from interrogating the ancient proteome are important and necessary step in developing proteomics as a biosignature tools.

Basis of altered RNA-binding specificity by PUF proteins revealed by crystal structures of yeast Puf4p

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, Matthew T.; Higgin, Joshua J.; Hall, Traci M.Tanaka

2008-06-06

Pumilio/FBF (PUF) family proteins are found in eukaryotic organisms and regulate gene expression post-transcriptionally by binding to sequences in the 3' untranslated region of target transcripts. PUF proteins contain an RNA binding domain that typically comprises eight {alpha}-helical repeats, each of which recognizes one RNA base. Some PUF proteins, including yeast Puf4p, have altered RNA binding specificity and use their eight repeats to bind to RNA sequences with nine or ten bases. Here we report the crystal structures of Puf4p alone and in complex with a 9-nucleotide (nt) target RNA sequence, revealing that Puf4p accommodates an 'extra' nucleotide by modestmore » adaptations allowing one base to be turned away from the RNA binding surface. Using structural information and sequence comparisons, we created a mutant Puf4p protein that preferentially binds to an 8-nt target RNA sequence over a 9-nt sequence and restores binding of each protein repeat to one RNA base.« less

Identifying functionally informative evolutionary sequence profiles.

PubMed

Gil, Nelson; Fiser, Andras

2018-04-15

Multiple sequence alignments (MSAs) can provide essential input to many bioinformatics applications, including protein structure prediction and functional annotation. However, the optimal selection of sequences to obtain biologically informative MSAs for such purposes is poorly explored, and has traditionally been performed manually. We present Selection of Alignment by Maximal Mutual Information (SAMMI), an automated, sequence-based approach to objectively select an optimal MSA from a large set of alternatives sampled from a general sequence database search. The hypothesis of this approach is that the mutual information among MSA columns will be maximal for those MSAs that contain the most diverse set possible of the most structurally and functionally homogeneous protein sequences. SAMMI was tested to select MSAs for functional site residue prediction by analysis of conservation patterns on a set of 435 proteins obtained from protein-ligand (peptides, nucleic acids and small substrates) and protein-protein interaction databases. Availability and implementation: A freely accessible program, including source code, implementing SAMMI is available at https://github.com/nelsongil92/SAMMI.git. andras.fiser@einstein.yu.edu. Supplementary data are available at Bioinformatics online.

Efficient farnesylation of an extended C-terminal C(x)3X sequence motif expands the scope of the prenylated proteome.

PubMed

Blanden, Melanie J; Suazo, Kiall F; Hildebrandt, Emily R; Hardgrove, Daniel S; Patel, Meet; Saunders, William P; Distefano, Mark D; Schmidt, Walter K; Hougland, James L

2018-02-23

Protein prenylation is a post-translational modification that has been most commonly associated with enabling protein trafficking to and interaction with cellular membranes. In this process, an isoprenoid group is attached to a cysteine near the C terminus of a substrate protein by protein farnesyltransferase (FTase) or protein geranylgeranyltransferase type I or II (GGTase-I and GGTase-II). FTase and GGTase-I have long been proposed to specifically recognize a four-amino acid C AAX C-terminal sequence within their substrates. Surprisingly, genetic screening reveals that yeast FTase can modify sequences longer than the canonical C AAX sequence, specifically C( x ) 3 X sequences with four amino acids downstream of the cysteine. Biochemical and cell-based studies using both peptide and protein substrates reveal that mammalian FTase orthologs can also prenylate C( x ) 3 X sequences. As the search to identify physiologically relevant C( x ) 3 X proteins begins, this new prenylation motif nearly doubles the number of proteins within the yeast and human proteomes that can be explored as potential FTase substrates. This work expands our understanding of prenylation's impact within the proteome, establishes the biologically relevant reactivity possible with this new motif, and opens new frontiers in determining the impact of non-canonically prenylated proteins on cell function. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Inferences from structural comparison: flexibility, secondary structure wobble and sequence alignment optimization.

PubMed

Zhang, Gaihua; Su, Zhen

2012-01-01

Work on protein structure prediction is very useful in biological research. To evaluate their accuracy, experimental protein structures or their derived data are used as the 'gold standard'. However, as proteins are dynamic molecular machines with structural flexibility such a standard may be unreliable. To investigate the influence of the structure flexibility, we analysed 3,652 protein structures of 137 unique sequences from 24 protein families. The results showed that (1) the three-dimensional (3D) protein structures were not rigid: the root-mean-square deviation (RMSD) of the backbone Cα of structures with identical sequences was relatively large, with the average of the maximum RMSD from each of the 137 sequences being 1.06 Å; (2) the derived data of the 3D structure was not constant, e.g. the highest ratio of the secondary structure wobble site was 60.69%, with the sequence alignments from structural comparisons of two proteins in the same family sometimes being completely different. Proteins may have several stable conformations and the data derived from resolved structures as a 'gold standard' should be optimized before being utilized as criteria to evaluate the prediction methods, e.g. sequence alignment from structural comparison. Helix/β-sheet transition exists in normal free proteins. The coil ratio of the 3D structure could affect its resolution as determined by X-ray crystallography.

Indigenous and introduced potyviruses of legumes and Passiflora spp. from Australia: biological properties and comparison of coat protein sequences

USDA-ARS?s Scientific Manuscript database

Coat protein sequences of 33 Potyvirus isolates from legume and Passiflora spp. were sequenced to determine the identity of infecting viruses. Phylogenetic analysis of the sequences revealed the presence of seven distinct virus species....

In silico characterization and analysis of RTBP1 and NgTRF1 protein through MD simulation and molecular docking - A comparative study.

PubMed

Mukherjee, Koel; Pandey, Dev Mani; Vidyarthi, Ambarish Saran

2015-02-06

Gaining access to sequence and structure information of telomere binding proteins helps in understanding the essential biological processes involve in conserved sequence specific interaction between DNA and the proteins. Rice telomere binding protein (RTBP1) and Nicotiana glutinosa telomere repeat binding factor (NgTRF1) are helix turn helix motif type of proteins that plays role in telomeric DNA protection and length regulation. Both the proteins share same type of domain but till now there is very less communication on the in silico studies of these complete proteins.Here we intend to do a comparative study between two proteins through modeling of the complete proteins, physiochemical characterization, MD simulation and DNA-protein docking. I-TASSER and CLC protein work bench was performed to find out the protein 3D structure as well as the different parameters to characterize the proteins. MD simulation was completed by GROMOS forcefield of GROMACS for 10 ns of time stretch. The simulated 3D structures were docked with template DNA (3D DNA modeled through 3D-DART) of TTTAGGG conserved sequence motif using HADDOCK web server.Digging up all the facts about the proteins it was reveled that around 120 amino acids in the tail part was showing a good sequence similarity between the proteins. Molecular modeling, sequence characterization and secondary structure prediction also indicates the similarity between the protein's structure and sequence. The result of MD simulation highlights on the RMSD, RMSF, Rg, PCA and Energy plots which also conveys the similar type of motional behavior between them. The best complex formation for both the proteins in docking result also indicates for the first interaction site which is mainly the helix3 region of the DNA binding domain. The overall computational analysis reveals that RTBP1 and NgTRF1 proteins display good amount of similarity in their physicochemical properties, structure, dynamics and binding mode.

In Silico Characterization and Analysis of RTBP1 and NgTRF1 Protein Through MD Simulation and Molecular Docking: A Comparative Study.

PubMed

Mukherjee, Koel; Pandey, Dev Mani; Vidyarthi, Ambarish Saran

2015-09-01

Gaining access to sequence and structure information of telomere-binding proteins helps in understanding the essential biological processes involve in conserved sequence-specific interaction between DNA and the proteins. Rice telomere-binding protein (RTBP1) and Nicotiana glutinosa telomere repeat binding factor (NgTRF1) are helix-turn-helix motif type of proteins that plays role in telomeric DNA protection and length regulation. Both the proteins share same type of domain, but till now there is very less communication on the in silico studies of these complete proteins. Here we intend to do a comparative study between two proteins through modeling of the complete proteins, physiochemical characterization, MD simulation and DNA-protein docking. I-TASSER and CLC protein work bench was performed to find out the protein 3D structure as well as the different parameters to characterize the proteins. MD simulation was completed by GROMOS forcefield of GROMACS for 10 ns of time stretch. The simulated 3D structures were docked with template DNA (3D DNA modeled through 3D-DART) of TTTAGGG conserved sequence motif using HADDOCK Web server. By digging up all the facts about the proteins, it was revealed that around 120 amino acids in the tail part were showing a good sequence similarity between the proteins. Molecular modeling, sequence characterization and secondary structure prediction also indicate the similarity between the protein's structure and sequence. The result of MD simulation highlights on the RMSD, RMSF, Rg, PCA and energy plots which also conveys the similar type of motional behavior between them. The best complex formation for both the proteins in docking result also indicates for the first interaction site which is mainly the helix3 region of the DNA-binding domain. The overall computational analysis reveals that RTBP1 and NgTRF1 proteins display good amount of similarity in their physicochemical properties, structure, dynamics and binding mode.

Pyrin gene and mutants thereof, which cause familial Mediterranean fever

DOEpatents

Kastner, Daniel L [Bethesda, MD; Aksentijevichh, Ivona [Bethesda, MD; Centola, Michael [Tacoma Park, MD; Deng, Zuoming [Gaithersburg, MD; Sood, Ramen [Rockville, MD; Collins, Francis S [Rockville, MD; Blake, Trevor [Laytonsville, MD; Liu, P Paul [Ellicott City, MD; Fischel-Ghodsian, Nathan [Los Angeles, CA; Gumucio, Deborah L [Ann Arbor, MI; Richards, Robert I [North Adelaide, AU; Ricke, Darrell O [San Diego, CA; Doggett, Norman A [Santa Cruz, NM; Pras, Mordechai [Tel-Hashomer, IL

2003-09-30

The invention provides the nucleic acid sequence encoding the protein associated with familial Mediterranean fever (FMF). The cDNA sequence is designated as MEFV. The invention is also directed towards fragments of the DNA sequence, as well as the corresponding sequence for the RNA transcript and fragments thereof. Another aspect of the invention provides the amino acid sequence for a protein (pyrin) associated with FMF. The invention is directed towards both the full length amino acid sequence, fusion proteins containing the amino acid sequence and fragments thereof. The invention is also directed towards mutants of the nucleic acid and amino acid sequences associated with FMF. In particular, the invention discloses three missense mutations, clustered in within about 40 to 50 amino acids, in the highly conserved rfp (B30.2) domain at the C-terminal of the protein. These mutants include M6801, M694V, K695R, and V726A. Additionally, the invention includes methods for diagnosing a patient at risk for having FMF and kits therefor.

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

PubMed

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.

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

ERIC Educational Resources Information Center

Wilson, Karl A.; Tan-Wilson, Anna

2013-01-01

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

Cross-Specificities between cII-like Proteins and pRE-like Promoters of Lambdoid Bacteriophages

PubMed Central

Wulff, Daniel L.; Mahoney, Michael E.

1987-01-01

We have investigated the activation of transcription from the pRE promoters of phages λ, 21 and P22 by the λ and 21 cII proteins and the P22 c1 (cII-like) protein, using an in vivo system in which cII protein from a derepressed prophage activates transcription from a pRE DNA fragment on a multicopy plasmid. We find that each protein is highly specific for its own cognate pRE promoter, although measureable cross-reactions are observed. The primary recognition sequence for cII protein on λ pRE is a pair of TTGC repeat sequences in the sequence 5'-TTGCN 6TTGC-3' at the -35 region of the promoter. This same sequence is found in 21 pRE, while P22 pRE has the sequence 5'-TTGCN6TTGT-3', which is the same as that of λctr1, a pRE+ variant of λ. λctr1 pRE is half as active as λ + pRE when assayed with either the λ cII or the P22 c1 proteins. Therefore, the single base change in the P22 repeat sequence cannot explain why the P22 c1 protein is much more active with P22 pRE than λ p RE. The dya5 mutation, a G→A change at position -43 of pRE, makes pRE a stronger promoter when assayed with either the λ or 21 cII proteins or the P22 c1 protein. We conclude that efficient activation of a cII-dependent promoter by a cII protein requires sequence information in addition to the TTGC repeat sequences. We do not know the characteristics of the proteins which are responsible for the specificity of each protein for its own cognate promoter. However, λdya8, which has a Glu27→Lys alteration in the λ cII protein and a cII+ phenotype, results in a mutant cII protein that is much more highly specific than wild-type cII protein for its own cognate λ p RE promoter. This is especially remarkable because the dya8 amino acid alteration makes the helix-2 region (the region of the protein predicted to make contact with the phosphodiester backbone of the DNA) of λ cII protein conform exactly with the helix-2 region of the P22 c1 protein in both charge and charge distribution. PMID:2953649

Sequence co-evolution gives 3D contacts and structures of protein complexes

PubMed Central

Hopf, Thomas A; Schärfe, Charlotta P I; Rodrigues, João P G L M; Green, Anna G; Kohlbacher, Oliver; Sander, Chris; Bonvin, Alexandre M J J; Marks, Debora S

2014-01-01

Protein–protein interactions are fundamental to many biological processes. Experimental screens have identified tens of thousands of interactions, and structural biology has provided detailed functional insight for select 3D protein complexes. An alternative rich source of information about protein interactions is the evolutionary sequence record. Building on earlier work, we show that analysis of correlated evolutionary sequence changes across proteins identifies residues that are close in space with sufficient accuracy to determine the three-dimensional structure of the protein complexes. We evaluate prediction performance in blinded tests on 76 complexes of known 3D structure, predict protein–protein contacts in 32 complexes of unknown structure, and demonstrate how evolutionary couplings can be used to distinguish between interacting and non-interacting protein pairs in a large complex. With the current growth of sequences, we expect that the method can be generalized to genome-wide elucidation of protein–protein interaction networks and used for interaction predictions at residue resolution. DOI: http://dx.doi.org/10.7554/eLife.03430.001 PMID:25255213

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

PubMed

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 analysis of DNA binding by C.Csp231I, a member of a novel class of R-M controller proteins regulating gene expression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shevtsov, M. B.; Streeter, S. D.; Thresh, S.-J.

2015-02-01

The structure of the new class of controller proteins (exemplified by C.Csp231I) in complex with its 21 bp DNA-recognition sequence is presented, and the molecular basis of sequence recognition in this class of proteins is discussed. An unusual extended spacer between the dimer binding sites suggests a novel interaction between the two C-protein dimers. In a wide variety of bacterial restriction–modification systems, a regulatory ‘controller’ protein (or C-protein) is required for effective transcription of its own gene and for transcription of the endonuclease gene found on the same operon. We have recently turned our attention to a new class ofmore » controller proteins (exemplified by C.Csp231I) that have quite novel features, including a much larger DNA-binding site with an 18 bp (∼60 Å) spacer between the two palindromic DNA-binding sequences and a very different recognition sequence from the canonical GACT/AGTC. Using X-ray crystallography, the structure of the protein in complex with its 21 bp DNA-recognition sequence was solved to 1.8 Å resolution, and the molecular basis of sequence recognition in this class of proteins was elucidated. An unusual aspect of the promoter sequence is the extended spacer between the dimer binding sites, suggesting a novel interaction between the two C-protein dimers when bound to both recognition sites correctly spaced on the DNA. A U-bend model is proposed for this tetrameric complex, based on the results of gel-mobility assays, hydrodynamic analysis and the observation of key contacts at the interface between dimers in the crystal.« less

Structure and Sequence Search on Aptamer-Protein Docking

NASA Astrophysics Data System (ADS)

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.

Generate Optimized Genetic Rhythm for Enzyme Expression in Non-native systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

2016-11-03

Most amino acids are represented by more than one codon, resulting in redundancy in the genetic code. Silent codon substitutions that do not alter the amino acid sequence still have an effect on protein expression. We have developed an algorithm, GoGREEN, to enhance the expression of foreign proteins in a host organism. GoGREEN selects codons according to frequency patterns seen in the gene of interest using the codon usage table from the host organism. GoGREEN is also designed to accommodate gaps in the sequence.This software takes for input (1) the aligned protein sequences for genes the user wishes to express,more » (2) the codon usage table for the host organism, (3) and the DNA sequence for the target protein found in the host organism. The program will select codons based on codon usage patterns for the target DNA sequence. The program will also select codons for “gaps” found in the aligned protein sequences using the codon usage table from the host organism.« less

How proteins bind to DNA: target discrimination and dynamic sequence search by the telomeric protein TRF1

PubMed Central

2017-01-01

Abstract Target search as performed by DNA-binding proteins is a complex process, in which multiple factors contribute to both thermodynamic discrimination of the target sequence from overwhelmingly abundant off-target sites and kinetic acceleration of dynamic sequence interrogation. TRF1, the protein that binds to telomeric tandem repeats, faces an intriguing variant of the search problem where target sites are clustered within short fragments of chromosomal DNA. In this study, we use extensive (>0.5 ms in total) MD simulations to study the dynamical aspects of sequence-specific binding of TRF1 at both telomeric and non-cognate DNA. For the first time, we describe the spontaneous formation of a sequence-specific native protein–DNA complex in atomistic detail, and study the mechanism by which proteins avoid off-target binding while retaining high affinity for target sites. Our calculated free energy landscapes reproduce the thermodynamics of sequence-specific binding, while statistical approaches allow for a comprehensive description of intermediate stages of complex formation. PMID:28633355

Sequence- and Interactome-Based Prediction of Viral Protein Hotspots Targeting Host Proteins: A Case Study for HIV Nef

PubMed Central

Sarmady, Mahdi; Dampier, William; Tozeren, Aydin

2011-01-01

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. PMID:21738584

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

PubMed

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.

Inverse statistical physics of protein sequences: a key issues review

NASA Astrophysics Data System (ADS)

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.

Analysis of sequencing data for probing RNA secondary structures and protein-RNA binding in studying posttranscriptional regulations.

PubMed

Hu, Xihao; Wu, Yang; Lu, Zhi John; Yip, Kevin Y

2016-11-01

High-throughput sequencing has been used to study posttranscriptional regulations, where the identification of protein-RNA binding is a major and fast-developing sub-area, which is in turn benefited by the sequencing methods for whole-transcriptome probing of RNA secondary structures. In the study of RNA secondary structures using high-throughput sequencing, bases are modified or cleaved according to their structural features, which alter the resulting composition of sequencing reads. In the study of protein-RNA binding, methods have been proposed to immuno-precipitate (IP) protein-bound RNA transcripts in vitro or in vivo By sequencing these transcripts, the protein-RNA interactions and the binding locations can be identified. For both types of data, read counts are affected by a combination of confounding factors, including expression levels of transcripts, sequence biases, mapping errors and the probing or IP efficiency of the experimental protocols. Careful processing of the sequencing data and proper extraction of important features are fundamentally important to a successful analysis. Here we review and compare different experimental methods for probing RNA secondary structures and binding sites of RNA-binding proteins (RBPs), and the computational methods proposed for analyzing the corresponding sequencing data. We suggest how these two types of data should be integrated to study the structural properties of RBP binding sites as a systematic way to better understand posttranscriptional regulations. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

SIBIS: a Bayesian model for inconsistent protein sequence estimation.

PubMed

Khenoussi, Walyd; Vanhoutrève, Renaud; Poch, Olivier; Thompson, Julie D

2014-09-01

The prediction of protein coding genes is a major challenge that depends on the quality of genome sequencing, the accuracy of the model used to elucidate the exonic structure of the genes and the complexity of the gene splicing process leading to different protein variants. As a consequence, today's protein databases contain a huge amount of inconsistency, due to both natural variants and sequence prediction errors. We have developed a new method, called SIBIS, to detect such inconsistencies based on the evolutionary information in multiple sequence alignments. A Bayesian framework, combined with Dirichlet mixture models, is used to estimate the probability of observing specific amino acids and to detect inconsistent or erroneous sequence segments. We evaluated the performance of SIBIS on a reference set of protein sequences with experimentally validated errors and showed that the sensitivity is significantly higher than previous methods, with only a small loss of specificity. We also assessed a large set of human sequences from the UniProt database and found evidence of inconsistency in 48% of the previously uncharacterized sequences. We conclude that the integration of quality control methods like SIBIS in automatic analysis pipelines will be critical for the robust inference of structural, functional and phylogenetic information from these sequences. Source code, implemented in C on a linux system, and the datasets of protein sequences are freely available for download at http://www.lbgi.fr/∼julie/SIBIS. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

De novo assembly and characterization of the Trichuris trichiura adult worm transcriptome using Ion Torrent sequencing.

PubMed

Santos, Leonardo N; Silva, Eduardo S; Santos, André S; De Sá, Pablo H; Ramos, Rommel T; Silva, Artur; Cooper, Philip J; Barreto, Maurício L; Loureiro, Sebastião; Pinheiro, Carina S; Alcantara-Neves, Neuza M; Pacheco, Luis G C

2016-07-01

Infection with helminthic parasites, including the soil-transmitted helminth Trichuris trichiura (human whipworm), has been shown to modulate host immune responses and, consequently, to have an impact on the development and manifestation of chronic human inflammatory diseases. De novo derivation of helminth proteomes from sequencing of transcriptomes will provide valuable data to aid identification of parasite proteins that could be evaluated as potential immunotherapeutic molecules in near future. Herein, we characterized the transcriptome of the adult stage of the human whipworm T. trichiura, using next-generation sequencing technology and a de novo assembly strategy. Nearly 17.6 million high-quality clean reads were assembled into 6414 contiguous sequences, with an N50 of 1606bp. In total, 5673 protein-encoding sequences were confidentially identified in the T. trichiura adult worm transcriptome; of these, 1013 sequences represent potential newly discovered proteins for the species, most of which presenting orthologs already annotated in the related species T. suis. A number of transcripts representing probable novel non-coding transcripts for the species T. trichiura were also identified. Among the most abundant transcripts, we found sequences that code for proteins involved in lipid transport, such as vitellogenins, and several chitin-binding proteins. Through a cross-species expression analysis of gene orthologs shared by T. trichiura and the closely related parasites T. suis and T. muris it was possible to find twenty-six protein-encoding genes that are consistently highly expressed in the adult stages of the three helminth species. Additionally, twenty transcripts could be identified that code for proteins previously detected by mass spectrometry analysis of protein fractions of the whipworm somatic extract that present immunomodulatory activities. Five of these transcripts were amongst the most highly expressed protein-encoding sequences in the T. trichiura adult worm. Besides, orthologs of proteins demonstrated to have potent immunomodulatory properties in related parasitic helminths were also predicted from the T. trichiura de novo assembled transcriptome. Copyright © 2016. Published by Elsevier B.V.

Genetic characterization of L-Zagreb mumps vaccine strain.

PubMed

Ivancic, Jelena; Gulija, Tanja Kosutic; Forcic, Dubravko; Baricevic, Marijana; Jug, Renata; Mesko-Prejac, Majda; Mazuran, Renata

2005-04-01

Eleven mumps vaccine strains, all containing live attenuated virus, have been used throughout the world. Although L-Zagreb mumps vaccine has been licensed since 1972, only its partial nucleotide sequence was previously determined (accession numbers , and ). Therefore, we sequenced the entire genome of L-Zagreb vaccine strain (Institute of Immunology Inc., Zagreb, Croatia). In order to investigate the genetic stability of the vaccine, sequences of both L-Zagreb master seed and currently produced vaccine batch were determined and no difference between them was observed. A phylogenetic analysis based on SH gene sequence has shown that L-Zagreb strain does not belong to any of established mumps genotypes and that it is most similar to old, laboratory preserved European strains (1950s-1970s). L-Zagreb nucleotide and deduced protein sequences were compared with other mumps virus sequences obtained from the GenBank. Emphasis was put on functionally important protein regions and known antigenic epitopes. The extensive comparisons of nucleotide and deduced protein sequences between L-Zagreb vaccine strain and other previously determined mumps virus sequences have shown that while the functional regions of HN, V, and L proteins are well conserved among various mumps strains, there can be a substantial amino acid difference in antigenic epitopes of all proteins and in functional regions of F protein. No molecular pattern was identified that can be used as a distinction marker between virulent and attenuated strains.

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

PubMed Central

Li, Yushuang; Yang, Jiasheng; Zhang, Yi

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. PMID:27918587

DNA sequence analysis of a 10 624 bp fragment of the left arm of chromosome XV from Saccharomyces cerevisiae reveals a RNA binding protein, a mitochondrial protein, two ribosomal proteins and two new open reading frames.

PubMed

Lafuente, M J; Gamo, F J; Gancedo, C

1996-09-01

We have determined the sequence of a 10624 bp DNA segment located in the left arm of chromosome XV of Saccharomyces cerevisiae. The sequence contains eight open reading frames (ORFs) longer than 100 amino acids. Two of them do not present significant homology with sequences found in the databases. The product of ORF o0553 is identical to the protein encoded by the gene SMF1. Internal to it there is another ORF, o0555 that is apparently expressed. The proteins encoded by ORFs o0559 and o0565 are identical to ribosomal proteins S19.e and L18 respectively. ORF o0550 encodes a protein with an RNA binding signature including RNP motifs and stretches rich in asparagine, glutamine and arginine.

Plastid-targeting peptides from the chlorarachniophyte Bigelowiella natans.

PubMed

Rogers, Matthew B; Archibald, John M; Field, Matthew A; Li, Catherine; Striepen, Boris; Keeling, Patrick J

2004-01-01

Chlorarachniophytes are marine amoeboflagellate protists that have acquired their plastid (chloroplast) through secondary endosymbiosis with a green alga. Like other algae, most of the proteins necessary for plastid function are encoded in the nuclear genome of the secondary host. These proteins are targeted to the organelle using a bipartite leader sequence consisting of a signal peptide (allowing entry in to the endomembrane system) and a chloroplast transit peptide (for transport across the chloroplast envelope membranes). We have examined the leader sequences from 45 full-length predicted plastid-targeted proteins from the chlorarachniophyte Bigelowiella natans with the goal of understanding important features of these sequences and possible conserved motifs. The chemical characteristics of these sequences were compared with a set of 10 B. natans endomembrane-targeted proteins and 38 cytosolic or nuclear proteins, which show that the signal peptides are similar to those of most other eukaryotes, while the transit peptides differ from those of other algae in some characteristics. Consistent with this, the leader sequence from one B. natans protein was tested for function in the apicomplexan parasite, Toxoplasma gondii, and shown to direct the secretion of the protein.

Use of signal sequences as an in situ removable sequence element to stimulate protein synthesis in cell-free extracts

PubMed Central

Ahn, Jin-Ho; Hwang, Mi-Yeon; Lee, Kyung-Ho; Choi, Cha-Yong; Kim, Dong-Myung

2007-01-01

This study developed a method to boost the expression of recombinant proteins in a cell-free protein synthesis system without leaving additional amino acid residues. It was found that the nucleotide sequences of the signal peptides serve as an efficient downstream box to stimulate protein synthesis when they were fused upstream of the target genes. The extent of stimulation was critically affected by the identity of the second codons of the signal sequences. Moreover, the yield of the synthesized protein was enhanced by as much as 10 times in the presence of an optimal second codon. The signal peptides were in situ cleaved and the target proteins were produced in their native sizes by carrying out the cell-free synthesis reactions in the presence of Triton X-100, most likely through the activation of signal peptidase in the S30 extract. The amplification of the template DNA and the addition of the signal sequences were accomplished by PCR. Hence, elevated levels of recombinant proteins were generated within several hours. PMID:17185295

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

PubMed

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.

Tandem mass spectrometry for the detection of plant pathogenic fungi and the effects of database composition on protein inferences.

PubMed

Padliya, Neerav D; Garrett, Wesley M; Campbell, Kimberly B; Tabb, David L; Cooper, Bret

2007-11-01

LC-MS/MS has demonstrated potential for detecting plant pathogens. Unlike PCR or ELISA, LC-MS/MS does not require pathogen-specific reagents for the detection of pathogen-specific proteins and peptides. However, the MS/MS approach we and others have explored does require a protein sequence reference database and database-search software to interpret tandem mass spectra. To evaluate the limitations of database composition on pathogen identification, we analyzed proteins from cultured Ustilago maydis, Phytophthora sojae, Fusarium graminearum, and Rhizoctonia solani by LC-MS/MS. When the search database did not contain sequences for a target pathogen, or contained sequences to related pathogens, target pathogen spectra were reliably matched to protein sequences from nontarget organisms, giving an illusion that proteins from nontarget organisms were identified. Our analysis demonstrates that when database-search software is used as part of the identification process, a paradox exists whereby additional sequences needed to detect a wide variety of possible organisms may lead to more cross-species protein matches and misidentification of pathogens.

BayesMotif: de novo protein sorting motif discovery from impure datasets.

PubMed

Hu, Jianjun; Zhang, Fan

2010-01-18

Protein sorting is the process that newly synthesized proteins are transported to their target locations within or outside of the cell. This process is precisely regulated by protein sorting signals in different forms. A major category of sorting signals are amino acid sub-sequences usually located at the N-terminals or C-terminals of protein sequences. Genome-wide experimental identification of protein sorting signals is extremely time-consuming and costly. Effective computational algorithms for de novo discovery of protein sorting signals is needed to improve the understanding of protein sorting mechanisms. We formulated the protein sorting motif discovery problem as a classification problem and proposed a Bayesian classifier based algorithm (BayesMotif) for de novo identification of a common type of protein sorting motifs in which a highly conserved anchor is present along with a less conserved motif regions. A false positive removal procedure is developed to iteratively remove sequences that are unlikely to contain true motifs so that the algorithm can identify motifs from impure input sequences. Experiments on both implanted motif datasets and real-world datasets showed that the enhanced BayesMotif algorithm can identify anchored sorting motifs from pure or impure protein sequence dataset. It also shows that the false positive removal procedure can help to identify true motifs even when there is only 20% of the input sequences containing true motif instances. We proposed BayesMotif, a novel Bayesian classification based algorithm for de novo discovery of a special category of anchored protein sorting motifs from impure datasets. Compared to conventional motif discovery algorithms such as MEME, our algorithm can find less-conserved motifs with short highly conserved anchors. Our algorithm also has the advantage of easy incorporation of additional meta-sequence features such as hydrophobicity or charge of the motifs which may help to overcome the limitations of PWM (position weight matrix) motif model.

System in biology leading to cell pathology: stable protein-protein interactions after covalent modifications by small molecules or in transgenic cells.

PubMed

Malina, Halina Z

2011-01-19

The physiological processes in the cell are regulated by reversible, electrostatic protein-protein interactions. Apoptosis is such a regulated process, which is critically important in tissue homeostasis and development and leads to complete disintegration of the cell. Pathological apoptosis, a process similar to apoptosis, is associated with aging and infection. The current study shows that pathological apoptosis is a process caused by the covalent interactions between the signaling proteins, and a characteristic of this pathological network is the covalent binding of calmodulin to regulatory sequences. Small molecules able to bind covalently to the amino group of lysine, histidine, arginine, or glutamine modify the regulatory sequences of the proteins. The present study analyzed the interaction of calmodulin with the BH3 sequence of Bax, and the calmodulin-binding sequence of myristoylated alanine-rich C-kinase substrate in the presence of xanthurenic acid in primary retinal epithelium cell cultures and murine epithelial fibroblast cell lines transformed with SV40 (wild type [WT], Bid knockout [Bid-/-], and Bax-/-/Bak-/- double knockout [DKO]). Cell death was observed to be associated with the covalent binding of calmodulin, in parallel, to the regulatory sequences of proteins. Xanthurenic acid is known to activate caspase-3 in primary cell cultures, and the results showed that this activation is also observed in WT and Bid-/- cells, but not in DKO cells. However, DKO cells were not protected against death, but high rates of cell death occurred by detachment. The results showed that small molecules modify the basic amino acids in the regulatory sequences of proteins leading to covalent interactions between the modified sequences (e.g., calmodulin to calmodulin-binding sites). The formation of these polymers (aggregates) leads to an unregulated and, consequently, pathological protein network. The results suggest a mechanism for the involvement of small molecules in disease development. In the knockout cells, incorrect interactions between proteins were observed without the protein modification by small molecules, indicating the abnormality of the protein network in the transgenic system. The irreversible protein-protein interactions lead to protein aggregation and cell degeneration, which are observed in all aging-associated diseases.

System in biology leading to cell pathology: stable protein-protein interactions after covalent modifications by small molecules or in transgenic cells

PubMed Central

2011-01-01

Background The physiological processes in the cell are regulated by reversible, electrostatic protein-protein interactions. Apoptosis is such a regulated process, which is critically important in tissue homeostasis and development and leads to complete disintegration of the cell. Pathological apoptosis, a process similar to apoptosis, is associated with aging and infection. The current study shows that pathological apoptosis is a process caused by the covalent interactions between the signaling proteins, and a characteristic of this pathological network is the covalent binding of calmodulin to regulatory sequences. Results Small molecules able to bind covalently to the amino group of lysine, histidine, arginine, or glutamine modify the regulatory sequences of the proteins. The present study analyzed the interaction of calmodulin with the BH3 sequence of Bax, and the calmodulin-binding sequence of myristoylated alanine-rich C-kinase substrate in the presence of xanthurenic acid in primary retinal epithelium cell cultures and murine epithelial fibroblast cell lines transformed with SV40 (wild type [WT], Bid knockout [Bid-/-], and Bax-/-/Bak-/- double knockout [DKO]). Cell death was observed to be associated with the covalent binding of calmodulin, in parallel, to the regulatory sequences of proteins. Xanthurenic acid is known to activate caspase-3 in primary cell cultures, and the results showed that this activation is also observed in WT and Bid-/- cells, but not in DKO cells. However, DKO cells were not protected against death, but high rates of cell death occurred by detachment. Conclusions The results showed that small molecules modify the basic amino acids in the regulatory sequences of proteins leading to covalent interactions between the modified sequences (e.g., calmodulin to calmodulin-binding sites). The formation of these polymers (aggregates) leads to an unregulated and, consequently, pathological protein network. The results suggest a mechanism for the involvement of small molecules in disease development. In the knockout cells, incorrect interactions between proteins were observed without the protein modification by small molecules, indicating the abnormality of the protein network in the transgenic system. The irreversible protein-protein interactions lead to protein aggregation and cell degeneration, which are observed in all aging-associated diseases. PMID:21247434

The complete CDS of the prion protein (PRNP) gene of African lion (Panthera leo).

PubMed

Maj, Andrzej; Spellman, Garth M; Sarver, Shane K

2008-04-01

We provide the complete PRNP CDS sequence for the African lion, which is different from the previously published sequence and more similar to other carnivore sequences. The newly obtained prion protein sequence differs from the domestic cat sequence at three amino acid positions and contains only four octapeptide repeats. We recommend that this sequence be used as the reference sequence for future studies of the PRNP gene for this species.

Sequence analysis and expression of the M1 and M2 matrix protein genes of hirame rhabdovirus (HIRRV)

USGS Publications Warehouse

Nishizawa, T.; Kurath, G.; Winton, J.R.

1997-01-01

We have cloned and sequenced a 2318 nucleotide region of the genomic RNA of hirame rhabdovirus (HIRRV), an important viral pathogen of Japanese flounder Paralichthys olivaceus. This region comprises approximately two-thirds of the 3' end of the nucleocapsid protein (N) gene and the complete matrix protein (M1 and M2) genes with the associated intergenic regions. The partial N gene sequence was 812 nucleotides in length with an open reading frame (ORF) that encoded the carboxyl-terminal 250 amino acids of the N protein. The M1 and M2 genes were 771 and 700 nucleotides in length, respectively, with ORFs encoding proteins of 227 and 193 amino acids. The M1 gene sequence contained an additional small ORF that could encode a highly basic, arginine-rich protein of 25 amino acids. Comparisons of the N, M1, and M2 gene sequences of HIRRV with the corresponding sequences of the fish rhabdoviruses, infectious hematopoietic necrosis virus (IHNV) or viral hemorrhagic septicemia virus (VHSV) indicated that HIRRV was more closely related to IHNV than to VHSV, but was clearly distinct from either. The putative consensus gene termination sequence for IHNV and VHSV, AGAYAG(A)(7), was present in the N-M1, M1-M2, and M2-G intergenic regions of HIRRV as were the putative transcription initiation sequences YGGCAC and AACA. An Escherichia coli expression system was used to produce recombinant proteins from the M1 and M2 genes of HIRRV. These were the same size as the authentic M1 and M2 proteins and reacted with anti-HIRRV rabbit serum in western blots. These reagents can be used for further study of the fish immune response and to test novel control methods.

An Evolution-Based Approach to De Novo Protein Design and Case Study on Mycobacterium tuberculosis

PubMed Central

Brender, Jeffrey R.; Czajka, Jeff; Marsh, David; Gray, Felicia; Cierpicki, Tomasz; Zhang, Yang

2013-01-01

Computational protein design is a reverse procedure of protein folding and structure prediction, where constructing structures from evolutionarily related proteins has been demonstrated to be the most reliable method for protein 3-dimensional structure prediction. Following this spirit, we developed a novel method to design new protein sequences based on evolutionarily related protein families. For a given target structure, a set of proteins having similar fold are identified from the PDB library by structural alignments. A structural profile is then constructed from the protein templates and used to guide the conformational search of amino acid sequence space, where physicochemical packing is accommodated by single-sequence based solvation, torsion angle, and secondary structure predictions. The method was tested on a computational folding experiment based on a large set of 87 protein structures covering different fold classes, which showed that the evolution-based design significantly enhances the foldability and biological functionality of the designed sequences compared to the traditional physics-based force field methods. Without using homologous proteins, the designed sequences can be folded with an average root-mean-square-deviation of 2.1 Å to the target. As a case study, the method is extended to redesign all 243 structurally resolved proteins in the pathogenic bacteria Mycobacterium tuberculosis, which is the second leading cause of death from infectious disease. On a smaller scale, five sequences were randomly selected from the design pool and subjected to experimental validation. The results showed that all the designed proteins are soluble with distinct secondary structure and three have well ordered tertiary structure, as demonstrated by circular dichroism and NMR spectroscopy. Together, these results demonstrate a new avenue in computational protein design that uses knowledge of evolutionary conservation from protein structural families to engineer new protein molecules of improved fold stability and biological functionality. PMID:24204234

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

PubMed

Liang, Yunyun; Liu, Sanyang; Zhang, Shengli

2015-01-01

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.

DeepText2GO: Improving large-scale protein function prediction with deep semantic text representation.

PubMed

You, Ronghui; Huang, Xiaodi; Zhu, Shanfeng

2018-06-06

As of April 2018, UniProtKB has collected more than 115 million protein sequences. Less than 0.15% of these proteins, however, have been associated with experimental GO annotations. As such, the use of automatic protein function prediction (AFP) to reduce this huge gap becomes increasingly important. The previous studies conclude that sequence homology based methods are highly effective in AFP. In addition, mining motif, domain, and functional information from protein sequences has been found very helpful for AFP. Other than sequences, alternative information sources such as text, however, may be useful for AFP as well. Instead of using BOW (bag of words) representation in traditional text-based AFP, we propose a new method called DeepText2GO that relies on deep semantic text representation, together with different kinds of available protein information such as sequence homology, families, domains, and motifs, to improve large-scale AFP. Furthermore, DeepText2GO integrates text-based methods with sequence-based ones by means of a consensus approach. Extensive experiments on the benchmark dataset extracted from UniProt/SwissProt have demonstrated that DeepText2GO significantly outperformed both text-based and sequence-based methods, validating its superiority. Copyright © 2018 Elsevier Inc. All rights reserved.

Transitive homology-guided structural studies lead to discovery of Cro proteins with 40% sequence identity but different folds

PubMed Central

Roessler, Christian G.; Hall, Branwen M.; Anderson, William J.; Ingram, Wendy M.; Roberts, Sue A.; Montfort, William R.; Cordes, Matthew H. J.

2008-01-01

Proteins that share common ancestry may differ in structure and function because of divergent evolution of their amino acid sequences. For a typical diverse protein superfamily, the properties of a few scattered members are known from experiment. A satisfying picture of functional and structural evolution in relation to sequence changes, however, may require characterization of a larger, well chosen subset. Here, we employ a “stepping-stone” method, based on transitive homology, to target sequences intermediate between two related proteins with known divergent properties. We apply the approach to the question of how new protein folds can evolve from preexisting folds and, in particular, to an evolutionary change in secondary structure and oligomeric state in the Cro family of bacteriophage transcription factors, initially identified by sequence-structure comparison of distant homologs from phages P22 and λ. We report crystal structures of two Cro proteins, Xfaso 1 and Pfl 6, with sequences intermediate between those of P22 and λ. The domains show 40% sequence identity but differ by switching of α-helix to β-sheet in a C-terminal region spanning ≈25 residues. Sedimentation analysis also suggests a correlation between helix-to-sheet conversion and strengthened dimerization. PMID:18227506

The SUPERFAMILY database in 2004: additions and improvements.

PubMed

Madera, Martin; Vogel, Christine; Kummerfeld, Sarah K; Chothia, Cyrus; Gough, Julian

2004-01-01

The SUPERFAMILY database provides structural assignments to protein sequences and a framework for analysis of the results. At the core of the database is a library of profile Hidden Markov Models that represent all proteins of known structure. The library is based on the SCOP classification of proteins: each model corresponds to a SCOP domain and aims to represent an entire superfamily. We have applied the library to predicted proteins from all completely sequenced genomes (currently 154), the Swiss-Prot and TrEMBL databases and other sequence collections. Close to 60% of all proteins have at least one match, and one half of all residues are covered by assignments. All models and full results are available for download and online browsing at http://supfam.org. Users can study the distribution of their superfamily of interest across all completely sequenced genomes, investigate with which other superfamilies it combines and retrieve proteins in which it occurs. Alternatively, concentrating on a particular genome as a whole, it is possible first, to find out its superfamily composition, and secondly, to compare it with that of other genomes to detect superfamilies that are over- or under-represented. In addition, the webserver provides the following standard services: sequence search; keyword search for genomes, superfamilies and sequence identifiers; and multiple alignment of genomic, PDB and custom sequences.

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

PubMed Central

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

2015-01-01

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. PMID:26481363

Molecular characterization of an ependymin precursor from goldfish brain.

PubMed

Königstorfer, A; Sterrer, S; Eckerskorn, C; Lottspeich, F; Schmidt, R; Hoffmann, W

1989-01-01

Ependymins are thought to be implicated in fundamental processes involved in plasticity of the goldfish CNS. Gas-phase sequencing of purified ependymins beta and gamma revealed that they share the same N-terminal sequence. Each sequence displays microheterogeneities at several positions. Based on the protein sequences obtained, we constructed synthetic oligonucleotides and used them as hybridization probes for screening cDNA libraries of goldfish brain. In this article we describe the full-length sequence of a mRNA encoding a precursor of ependymins. A cleavable signal sequence characteristic of secretory proteins is located at the N-terminal end, followed directly by the ependymin sequence. Also, two potential N-glycosylation sites were detected. A computer search revealed that ependymins form a novel family of unique proteins.

Strong minor groove base conservation in sequence logos implies DNA distortion or base flipping during replication and transcription initiation.

PubMed

Schneider, T D

2001-12-01

The sequence logo for DNA binding sites of the bacteriophage P1 replication protein RepA shows unusually high sequence conservation ( approximately 2 bits) at a minor groove that faces RepA. However, B-form DNA can support only 1 bit of sequence conservation via contacts into the minor groove. The high conservation in RepA sites therefore implies a distorted DNA helix with direct or indirect contacts to the protein. Here I show that a high minor groove conservation signature also appears in sequence logos of sites for other replication origin binding proteins (Rts1, DnaA, P4 alpha, EBNA1, ORC) and promoter binding proteins (sigma(70), sigma(D) factors). This finding implies that DNA binding proteins generally use non-B-form DNA distortion such as base flipping to initiate replication and transcription.

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

NASA Astrophysics Data System (ADS)

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.

HMG-D is an architecture-specific protein that preferentially binds to DNA containing the dinucleotide TG.

PubMed Central

Churchill, M E; Jones, D N; Glaser, T; Hefner, H; Searles, M A; Travers, A A

1995-01-01

The high mobility group (HMG) protein HMG-D from Drosophila melanogaster is a highly abundant chromosomal protein that is closely related to the vertebrate HMG domain proteins HMG1 and HMG2. In general, chromosomal HMG domain proteins lack sequence specificity. However, using both NMR spectroscopy and standard biochemical techniques we show that binding of HMG-D to a single DNA site is sequence selective. The preferred duplex DNA binding site comprises at least 5 bp and contains the deformable dinucleotide TG embedded in A/T-rich sequences. The TG motif constitutes a common core element in the binding sites of the well-characterized sequence-specific HMG domain proteins. We show that a conserved aromatic residue in helix 1 of the HMG domain may be involved in recognition of this core sequence. In common with other HMG domain proteins HMG-D binds preferentially to DNA sites that are stably bent and underwound, therefore HMG-D can be considered an architecture-specific protein. Finally, we show that HMG-D bends DNA and may confer a superhelical DNA conformation at a natural DNA binding site in the Drosophila fushi tarazu scaffold-associated region. Images PMID:7720717

MIPS: analysis and annotation of proteins from whole genomes.

PubMed

Mewes, H W; Amid, C; Arnold, R; Frishman, D; Güldener, U; Mannhaupt, G; Münsterkötter, M; Pagel, P; Strack, N; Stümpflen, V; Warfsmann, J; Ruepp, A

2004-01-01

The Munich Information Center for Protein Sequences (MIPS-GSF), Neuherberg, Germany, provides protein sequence-related information based on whole-genome analysis. The main focus of the work is directed toward the systematic organization of sequence-related attributes as gathered by a variety of algorithms, primary information from experimental data together with information compiled from the scientific literature. MIPS 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 database of complete cDNAs (German Human Genome Project, NGFN), the database of mammalian protein-protein interactions (MPPI), the database of FASTA homologies (SIMAP), and the interface for the fast retrieval of protein-associated information (QUIPOS). The Arabidopsis thaliana database, the rice database, the plant EST databases (MATDB, MOsDB, SPUTNIK), as well as the databases for the comprehensive set of genomes (PEDANT genomes) are described elsewhere in the 2003 and 2004 NAR database issues, respectively. All databases described, and the detailed descriptions of our projects can be accessed through the MIPS web server (http://mips.gsf.de).

Gastrointestinal Endogenous Proteins as a Source of Bioactive Peptides - An In Silico Study

PubMed Central

Dave, Lakshmi A.; Montoya, Carlos A.; Rutherfurd, Shane M.; Moughan, Paul J.

2014-01-01

Dietary proteins are known to contain bioactive peptides that are released during digestion. Endogenous proteins secreted into the gastrointestinal tract represent a quantitatively greater supply of protein to the gut lumen than those of dietary origin. Many of these endogenous proteins are digested in the gastrointestinal tract but the possibility that these are also a source of bioactive peptides has not been considered. An in silico prediction method was used to test if bioactive peptides could be derived from the gastrointestinal digestion of gut endogenous proteins. Twenty six gut endogenous proteins and seven dietary proteins were evaluated. The peptides present after gastric and intestinal digestion were predicted based on the amino acid sequence of the proteins and the known specificities of the major gastrointestinal proteases. The predicted resultant peptides possessing amino acid sequences identical to those of known bioactive peptides were identified. After gastrointestinal digestion (based on the in silico simulation), the total number of bioactive peptides predicted to be released ranged from 1 (gliadin) to 55 (myosin) for the selected dietary proteins and from 1 (secretin) to 39 (mucin-5AC) for the selected gut endogenous proteins. Within the intact proteins and after simulated gastrointestinal digestion, angiotensin converting enzyme (ACE)-inhibitory peptide sequences were the most frequently observed in both the dietary and endogenous proteins. Among the dietary proteins, after in silico simulated gastrointestinal digestion, myosin was found to have the highest number of ACE-inhibitory peptide sequences (49 peptides), while for the gut endogenous proteins, mucin-5AC had the greatest number of ACE-inhibitory peptide sequences (38 peptides). Gut endogenous proteins may be an important source of bioactive peptides in the gut particularly since gut endogenous proteins represent a quantitatively large and consistent source of protein. PMID:24901416

Acanthamoeba castellanii STAT protein.

PubMed

Kicinska, Anna; Leluk, Jacek; Jarmuszkiewicz, Wieslawa

2014-01-01

STAT (signal transducers and activators of transcription) proteins are one of the important mediators of phosphotyrosine-regulated signaling in metazoan cells. We described the presence of STAT protein in a unicellular, free-living amoebae with a simple life cycle, Acanthamoeba castellanii. A. castellanii is the only, studied to date, Amoebozoan that does not belong to Mycetozoa but possesses STATs. A sequence of the A. castellanii STAT protein includes domains similar to those of the Dictyostelium STAT proteins: a coiled coil (characteristic for Dictyostelium STAT coiled coil), a STAT DNA-binding domain and a Src-homology domain. The search for protein sequences homologous to A. castellanii STAT revealed 17 additional sequences from lower eukaryotes. Interestingly, all of these sequences come from Amoebozoa organisms that belong to either Mycetozoa (slime molds) or Centramoebida. We showed that there are four separated clades within the slime mold STAT proteins. The A. castellanii STAT protein branches next to a group of STATc proteins from Mycetozoa. We also demonstrate that Amoebozoa form a distinct monophyletic lineage within the STAT protein world that is well separated from the other groups.

Phage display selection of peptides that target calcium-binding proteins.

PubMed

Vetter, Stefan W

2013-01-01

Phage display allows to rapidly identify peptide sequences with binding affinity towards target proteins, for example, calcium-binding proteins (CBPs). Phage technology allows screening of 10(9) or more independent peptide sequences and can identify CBP binding peptides within 2 weeks. Adjusting of screening conditions allows selecting CBPs binding peptides that are either calcium-dependent or independent. Obtained peptide sequences can be used to identify CBP target proteins based on sequence homology or to quickly obtain peptide-based CBP inhibitors to modulate CBP-target interactions. The protocol described here uses a commercially available phage display library, in which random 12-mer peptides are displayed on filamentous M13 phages. The library was screened against the calcium-binding protein S100B.

The Universal Protein Resource (UniProt): an expanding universe of protein information.

PubMed

Wu, Cathy H; Apweiler, Rolf; Bairoch, Amos; Natale, Darren A; Barker, Winona C; Boeckmann, Brigitte; Ferro, Serenella; Gasteiger, Elisabeth; Huang, Hongzhan; Lopez, Rodrigo; Magrane, Michele; Martin, Maria J; Mazumder, Raja; O'Donovan, Claire; Redaschi, Nicole; Suzek, Baris

2006-01-01

The Universal Protein Resource (UniProt) provides a central resource on protein sequences and functional annotation with three database components, each addressing a key need in protein bioinformatics. The UniProt Knowledgebase (UniProtKB), comprising the manually annotated UniProtKB/Swiss-Prot section and the automatically annotated UniProtKB/TrEMBL section, is the preeminent storehouse of protein annotation. The extensive cross-references, functional and feature annotations and literature-based evidence attribution enable scientists to analyse proteins and query across databases. The UniProt Reference Clusters (UniRef) speed similarity searches via sequence space compression by merging sequences that are 100% (UniRef100), 90% (UniRef90) or 50% (UniRef50) identical. Finally, the UniProt Archive (UniParc) stores all publicly available protein sequences, containing the history of sequence data with links to the source databases. UniProt databases continue to grow in size and in availability of information. Recent and upcoming changes to database contents, formats, controlled vocabularies and services are described. New download availability includes all major releases of UniProtKB, sequence collections by taxonomic division and complete proteomes. A bibliography mapping service has been added, and an ID mapping service will be available soon. UniProt databases can be accessed online at http://www.uniprot.org or downloaded at ftp://ftp.uniprot.org/pub/databases/.

Establishing homologies in protein sequences

NASA Technical Reports Server (NTRS)

Dayhoff, M. O.; Barker, W. C.; Hunt, L. T.

1983-01-01

Computer-based statistical techniques used to determine homologies between proteins occurring in different species are reviewed. The technique is based on comparison of two protein sequences, either by relating all segments of a given length in one sequence to all segments of the second or by finding the best alignment of the two sequences. Approaches discussed include selection using printed tabulations, identification of very similar sequences, and computer searches of a database. The use of the SEARCH, RELATE, and ALIGN programs (Dayhoff, 1979) is explained; sample data are presented in graphs, diagrams, and tables and the construction of scoring matrices is considered.

Knowledge-based computational intelligence development for predicting protein secondary structures from sequences.

PubMed

Shen, Hong-Bin; Yi, Dong-Liang; Yao, Li-Xiu; Yang, Jie; Chou, Kuo-Chen

2008-10-01

In the postgenomic age, with the avalanche of protein sequences generated and relatively slow progress in determining their structures by experiments, it is important to develop automated methods to predict the structure of a protein from its sequence. The membrane proteins are a special group in the protein family that accounts for approximately 30% of all proteins; however, solved membrane protein structures only represent less than 1% of known protein structures to date. Although a great success has been achieved for developing computational intelligence techniques to predict secondary structures in both globular and membrane proteins, there is still much challenging work in this regard. In this review article, we firstly summarize the recent progress of automation methodology development in predicting protein secondary structures, especially in membrane proteins; we will then give some future directions in this research field.

Two potato proteins, including a novel RING finger protein (HIP1), interact with the potyviral multifunctional protein HCpro.

PubMed

Guo, Deyin; Spetz, Carl; Saarma, Mart; Valkonen, Jari P T

2003-05-01

Potyviral helper-component proteinase (HCpro) is a multifunctional protein exerting its cellular functions in interaction with putative host proteins. In this study, cellular protein partners of the HCpro encoded by Potato virus A (PVA) (genus Potyvirus) were screened in a potato leaf cDNA library using a yeast two-hybrid system. Two cellular proteins were obtained that interact specifically with PVA HCpro in yeast and in the two in vitro binding assays used. Both proteins are encoded by single-copy genes in the potato genome. Analysis of the deduced amino acid sequences revealed that one (HIP1) of the two HCpro interactors is a novel RING finger protein. The sequence of the other protein (HIP2) showed no resemblance to the protein sequences available from databanks and has known biological functions.

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

PubMed Central

Smith, Geoff M.; Hutson, Jarod M.; Kindler, Lutz; Garcia-Moreno, Alejandro; Villaluenga, Aritza; Turner, Elaine

2017-01-01

Background 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. Methods 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. Results 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 Rhinocerotidae. Stephanorhinus is shown to be most closely related to the genera Coelodonta and Dicerorhinus. The protein sequence data further places the Sumatran rhino in a clade together with the genus Rhinoceros, opposed to forming a clade with the black and white rhinoceros species. Discussion The first biomolecular dataset available for Stephanorhinus places this genus together with the extinct genus Coelodonta and the extant genus Dicerorhinus. This is in agreement with morphological studies, although we are unable to resolve the order of divergence between these genera based on the protein sequences available. Our data supports the placement of the genus Dicerorhinus in a clade together with extant Rhinoceros species. Finally, the availability of protein sequence data for both extinct European rhinoceros genera allows future investigations into their geographic distribution and extinction chronologies. PMID:28316883

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

PubMed

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 Rhinocerotidae. Stephanorhinus is shown to be most closely related to the genera Coelodonta and Dicerorhinus . The protein sequence data further places the Sumatran rhino in a clade together with the genus Rhinoceros , opposed to forming a clade with the black and white rhinoceros species. The first biomolecular dataset available for Stephanorhinus places this genus together with the extinct genus Coelodonta and the extant genus Dicerorhinus . This is in agreement with morphological studies, although we are unable to resolve the order of divergence between these genera based on the protein sequences available. Our data supports the placement of the genus Dicerorhinus in a clade together with extant Rhinoceros species. Finally, the availability of protein sequence data for both extinct European rhinoceros genera allows future investigations into their geographic distribution and extinction chronologies.

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

PubMed

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.

MIPS: a database for genomes and protein sequences

PubMed Central

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). PMID:11752246

MIPS: a database for genomes and protein sequences.

PubMed

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).

Beta.-glucosidase coding sequences and protein from orpinomyces PC-2

DOEpatents

Li, Xin-Liang; Ljungdahl, Lars G.; Chen, Huizhong; Ximenes, Eduardo A.

2001-02-06

Provided is a novel .beta.-glucosidase from Orpinomyces sp. PC2, nucleotide sequences encoding the mature protein and the precursor protein, and methods for recombinant production of this .beta.-glucosidase.

ComplexContact: a web server for inter-protein contact prediction using deep learning.

PubMed

Zeng, Hong; Wang, Sheng; Zhou, Tianming; Zhao, Feifeng; Li, Xiufeng; Wu, Qing; Xu, Jinbo

2018-05-22

ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.

Proteolytic processing of the vitellogenin precursor in the boll weevil, Anthonomus grandis.

PubMed

Heilmann, L J; Trewitt, P M; Kumaran, A K

1993-01-01

The soluble proteins of the eggs of the coleopteran insect Anthonomus grandis Boheman, the cotton boll weevil, consist almost entirely of two vitellin types with M(r)s of 160,000 and 47,000. We sequenced their N-terminal ends and one internal cyanogen bromide fragment of the large vitellin and compared these sequences with the deduced amino acid sequence from the vitellogenin gene. The results suggest that both the boll weevil vitellin proteins are products of the proteolytic cleavage of a single precursor protein. The smaller 47,000 M(r) vitellin protein is derived from the N-terminal portion of the precursor adjacent to an 18 amino acid signal peptide. The cleavage site between the large and small vitellins at amino acid 362 is adjacent to a pentapeptide sequence containing two pairs of arginine residues. Comparison of the boll weevil sequences with limited known sequences from the single 180,000 M(r) honey bee protein show that the honey bee vitellin N-terminal exhibits sequence homology to the N-terminal of the 47,000 M(r) boll weevil vitellin. Treatment of the vitellins with an N-glycosidase results in a decrease in molecular weight of both proteins, from 47,000 to 39,000 and from 160,000 to 145,000, indicating that about 10-15% of the molecular weight of each vitellin consists of N-linked carbohydrate. The molecular weight of the deglycosylated large vitellin is smaller than that predicted from the gene sequence, indicating possible further proteolytic processing at the C-terminal of that protein.

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

PubMed

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.

Direct Calculation of Protein Fitness Landscapes through Computational Protein Design

PubMed Central

Au, Loretta; Green, David F.

2016-01-01

Naturally selected amino-acid sequences or experimentally derived ones are often the basis for understanding how protein three-dimensional conformation and function are determined by primary structure. Such sequences for a protein family comprise only a small fraction of all possible variants, however, representing the fitness landscape with limited scope. Explicitly sampling and characterizing alternative, unexplored protein sequences would directly identify fundamental reasons for sequence robustness (or variability), and we demonstrate that computational methods offer an efficient mechanism toward this end, on a large scale. The dead-end elimination and A∗ search algorithms were used here to find all low-energy single mutant variants, and corresponding structures of a G-protein heterotrimer, to measure changes in structural stability and binding interactions to define a protein fitness landscape. We established consistency between these algorithms with known biophysical and evolutionary trends for amino-acid substitutions, and could thus recapitulate known protein side-chain interactions and predict novel ones. PMID:26745411

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

PubMed

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.

Relation between native ensembles and experimental structures of proteins

PubMed Central

Best, Robert B.; Lindorff-Larsen, Kresten; DePristo, Mark A.; Vendruscolo, Michele

2006-01-01

Different experimental structures of the same protein or of proteins with high sequence similarity contain many small variations. Here we construct ensembles of “high-sequence similarity Protein Data Bank” (HSP) structures and consider the extent to which such ensembles represent the structural heterogeneity of the native state in solution. We find that different NMR measurements probing structure and dynamics of given proteins in solution, including order parameters, scalar couplings, and residual dipolar couplings, are remarkably well reproduced by their respective high-sequence similarity Protein Data Bank ensembles; moreover, we show that the effects of uncertainties in structure determination are insufficient to explain the results. These results highlight the importance of accounting for native-state protein dynamics in making comparisons with ensemble-averaged experimental data and suggest that even a modest number of structures of a protein determined under different conditions, or with small variations in sequence, capture a representative subset of the true native-state ensemble. PMID:16829580

Plant mitochondrial pyruvate dehydrogenase complex: purification and identification of catalytic components in potato.

PubMed Central

Millar, A H; Knorpp, C; Leaver, C J; Hill, S A

1998-01-01

The pyruvate dehydrogenase complex (mPDC) from potato (Solanum tuberosum cv. Romano) tuber mitochondria was purified 40-fold to a specific activity of 5.60 micromol/min per mg of protein. The activity of the complex depended on pyruvate, divalent cations, NAD+ and CoA and was competitively inhibited by both NADH and acetyl-CoA. SDS/PAGE revealed the complex consisted of seven polypeptide bands with apparent molecular masses of 78, 60, 58, 55, 43, 41 and 37 kDa. N-terminal sequencing revealed that the 78 kDa protein was dihydrolipoamide transacetylase (E2), the 58 kDa protein was dihydrolipoamide dehydrogenase (E3), the 43 and 41 kDa proteins were alpha subunits of pyruvate dehydrogenase, and the 37 kDa protein was the beta subunit of pyruvate dehydrogenase. N-terminal sequencing of the 55 kDa protein band yielded two protein sequences: one was another E3; the other was similar to the sequence of E2 from plant and yeast sources but was distinctly different from the sequence of the 78 kDa protein. Incubation of the mPDC with [2-14C]pyruvate resulted in the acetylation of both the 78 and 55 kDa proteins. PMID:9729464

Saccharomyces cerevisiae SSB1 protein and its relationship to nucleolar RNA-binding proteins.

PubMed

Jong, A Y; Clark, M W; Gilbert, M; Oehm, A; Campbell, J L

1987-08-01

To better define the function of Saccharomyces cerevisiae SSB1, an abundant single-stranded nucleic acid-binding protein, we determined the nucleotide sequence of the SSB1 gene and compared it with those of other proteins of known function. The amino acid sequence contains 293 amino acid residues and has an Mr of 32,853. There are several stretches of sequence characteristic of other eucaryotic single-stranded nucleic acid-binding proteins. At the amino terminus, residues 39 to 54 are highly homologous to a peptide in calf thymus UP1 and UP2 and a human heterogeneous nuclear ribonucleoprotein. Residues 125 to 162 constitute a fivefold tandem repeat of the sequence RGGFRG, the composition of which suggests a nucleic acid-binding site. Near the C terminus, residues 233 to 245 are homologous to several RNA-binding proteins. Of 18 C-terminal residues, 10 are acidic, a characteristic of the procaryotic single-stranded DNA-binding proteins and eucaryotic DNA- and RNA-binding proteins. In addition, examination of the subcellular distribution of SSB1 by immunofluorescence microscopy indicated that SSB1 is a nuclear protein, predominantly located in the nucleolus. Sequence homologies and the nucleolar localization make it likely that SSB1 functions in RNA metabolism in vivo, although an additional role in DNA metabolism cannot be excluded.

Comparative Analysis and Distribution of Omega-3 lcPUFA Biosynthesis Genes in Marine Molluscs

PubMed Central

Surm, Joachim M.; Prentis, Peter J.; Pavasovic, Ana

2015-01-01

Recent research has identified marine molluscs as an excellent source of omega-3 long-chain polyunsaturated fatty acids (lcPUFAs), based on their potential for endogenous synthesis of lcPUFAs. In this study we generated a representative list of fatty acyl desaturase (Fad) and elongation of very long-chain fatty acid (Elovl) genes from major orders of Phylum Mollusca, through the interrogation of transcriptome and genome sequences, and various publicly available databases. We have identified novel and uncharacterised Fad and Elovl sequences in the following species: Anadara trapezia, Nerita albicilla, Nerita melanotragus, Crassostrea gigas, Lottia gigantea, Aplysia californica, Loligo pealeii and Chlamys farreri. Based on alignments of translated protein sequences of Fad and Elovl genes, the haeme binding motif and histidine boxes of Fad proteins, and the histidine box and seventeen important amino acids in Elovl proteins, were highly conserved. Phylogenetic analysis of aligned reference sequences was used to reconstruct the evolutionary relationships for Fad and Elovl genes separately. Multiple, well resolved clades for both the Fad and Elovl sequences were observed, suggesting that repeated rounds of gene duplication best explain the distribution of Fad and Elovl proteins across the major orders of molluscs. For Elovl sequences, one clade contained the functionally characterised Elovl5 proteins, while another clade contained proteins hypothesised to have Elovl4 function. Additional well resolved clades consisted only of uncharacterised Elovl sequences. One clade from the Fad phylogeny contained only uncharacterised proteins, while the other clade contained functionally characterised delta-5 desaturase proteins. The discovery of an uncharacterised Fad clade is particularly interesting as these divergent proteins may have novel functions. Overall, this paper presents a number of novel Fad and Elovl genes suggesting that many mollusc groups possess most of the required enzymes for the synthesis of lcPUFAs. PMID:26308548

NADH:ubiquinone oxidoreductase from bovine heart mitochondria. cDNA sequences of the import precursors of the nuclear-encoded 39 kDa and 42 kDa subunits.

PubMed Central

Fearnley, I M; Finel, M; Skehel, J M; Walker, J E

1991-01-01

The 39 kDa and 42 kDa subunits of NADH:ubiquinone oxidoreductase from bovine heart mitochondria are nuclear-coded components of the hydrophobic protein fraction of the enzyme. Their amino acid sequences have been deduced from the sequences of overlapping cDNA clones. These clones were amplified from total bovine heart cDNA by means of the polymerase chain reaction, with the use of complex mixtures of oligonucleotide primers based upon fragments of protein sequence determined at the N-terminals of the proteins and at internal sites. The protein sequences of the 39 kDa and 42 kDa subunits are 345 and 320 amino acid residues long respectively, and their calculated molecular masses are 39,115 Da and 36,693 Da. Both proteins are predominantly hydrophilic, but each contains one or two hydrophobic segments that could possibly be folded into transmembrane alpha-helices. The bovine 39 kDa protein sequence is related to that of a 40 kDa subunit from complex I from Neurospora crassa mitochondria; otherwise, it is not related significantly to any known sequence, including redox proteins and two polypeptides involved in import of proteins into mitochondria, known as the mitochondrial processing peptidase and the processing-enhancing protein. Therefore the functions of the 39 kDa and 42 kDa subunits of complex I are unknown. The mitochondrial gene product, ND4, a hydrophobic component of complex I with an apparent molecular mass of about 39 kDa, has been identified in preparations of the enzyme. This subunit stains faintly with Coomassie Blue dye, and in many gel systems it is not resolved from the nuclearcoded 36 kDa subunit. Images Fig. 1. PMID:1832859

GOLabeler: Improving Sequence-based Large-scale Protein Function Prediction by Learning to Rank.

PubMed

You, Ronghui; Zhang, Zihan; Xiong, Yi; Sun, Fengzhu; Mamitsuka, Hiroshi; Zhu, Shanfeng

2018-03-07

Gene Ontology (GO) has been widely used to annotate functions of proteins and understand their biological roles. Currently only <1% of more than 70 million proteins in UniProtKB have experimental GO annotations, implying the strong necessity of automated function prediction (AFP) of proteins, where AFP is a hard multilabel classification problem due to one protein with a diverse number of GO terms. Most of these proteins have only sequences as input information, indicating the importance of sequence-based AFP (SAFP: sequences are the only input). Furthermore homology-based SAFP tools are competitive in AFP competitions, while they do not necessarily work well for so-called difficult proteins, which have <60% sequence identity to proteins with annotations already. Thus the vital and challenging problem now is how to develop a method for SAFP, particularly for difficult proteins. The key of this method is to extract not only homology information but also diverse, deep- rooted information/evidence from sequence inputs and integrate them into a predictor in a both effective and efficient manner. We propose GOLabeler, which integrates five component classifiers, trained from different features, including GO term frequency, sequence alignment, amino acid trigram, domains and motifs, and biophysical properties, etc., in the framework of learning to rank (LTR), a paradigm of machine learning, especially powerful for multilabel classification. The empirical results obtained by examining GOLabeler extensively and thoroughly by using large-scale datasets revealed numerous favorable aspects of GOLabeler, including significant performance advantage over state-of-the-art AFP methods. http://datamining-iip.fudan.edu.cn/golabeler. zhusf@fudan.edu.cn. Supplementary data are available at Bioinformatics online.

Purification and sequencing of the active site tryptic peptide from penicillin-binding protein 1b of Escherichia coli

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nicholas, R.A.; Suzuki, H.; Hirota, Y.

This paper reports the sequence of the active site peptide of penicillin-binding protein 1b from Escherichia coli. Purified penicillin-binding protein 1b was labeled with (/sup 14/C)penicillin G, digested with trypsin, and partially purified by gel filtration. Upon further purification by high-pressure liquid chromatography, two radioactive peaks were observed, and the major peak, representing over 75% of the applied radioactivity, was submitted to amino acid analysis and sequencing. The sequence Ser-Ile-Gly-Ser-Leu-Ala-Lys was obtained. The active site nucleophile was identified by digesting the purified peptide with aminopeptidase M and separating the radioactive products on high-pressure liquid chromatography. Amino acid analysis confirmed thatmore » the serine residue in the middle of the sequence was covalently bonded to the (/sup 14/C)penicilloyl moiety. A comparison of this sequence to active site sequences of other penicillin-binding proteins and beta-lactamases is presented.« less

Molecular characterization of a phloem-specific gene encoding the filament protein, phloem protein 1 (PP1), from Cucurbita maxima.

PubMed

Clark, A M; Jacobsen, K R; Bostwick, D E; Dannenhoffer, J M; Skaggs, M I; Thompson, G A

1997-07-01

Sieve elements in the phloem of most angiosperms contain proteinaceous filaments and aggregates called P-protein. In the genus Cucurbita, these filaments are composed of two major proteins: PP1, the phloem filament protein, and PP2, the phloem lactin. The gene encoding the phloem filament protein in pumpkin (Cucurbita maxima Duch.) has been isolated and characterized. Nucleotide sequence analysis of the reconstructed gene gPP1 revealed a continuous 2430 bp protein coding sequence, with no introns, encoding an 809 amino acid polypeptide. The deduced polypeptide had characteristics of PP1 and contained a 15 amino acid sequence determined by N-terminal peptide sequence analysis of PP1. The sequence of PP1 was highly repetitive with four 200 amino acid sequence domains containing structural motifs in common with cysteine proteinase inhibitors. Expression of the PP1 gene was detected in roots, hypocotyls, cotyledons, stems, and leaves of pumpkin plants. PP1 and its mRNA accumulated in pumpkin hypocotyls during the period of rapid hypocotyl elongation after which mRNA levels declined, while protein levels remained elevated. PP1 was immunolocalized in slime plugs and P-protein bodies in sieve elements of the phloem. Occasionally, PP1 was detected in companion cells. PP1 mRNA was localized by in situ hybridization in companion cells at early stages of vascular differentiation. The developmental accumulation and localization of PP1 and its mRNA paralleled the phloem lactin, further suggesting an interaction between these phloem-specific proteins.

Rational design of new materials using recombinant structural proteins: Current state and future challenges.

PubMed

Sutherland, Tara D; Huson, Mickey G; Rapson, Trevor D

2018-01-01

Sequence-definable polymers are seen as a prerequisite for design of future materials, with many polymer scientists regarding such polymers as the holy grail of polymer science. Recombinant proteins are sequence-defined polymers. Proteins are dictated by DNA templates and therefore the sequence of amino acids in a protein is defined, and molecular biology provides tools that allow redesign of the DNA as required. Despite this advantage, proteins are underrepresented in materials science. In this publication we investigate the advantages and limitations of using proteins as templates for rational design of new materials. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.

Cloning and expression of recombinant adhesive protein MEFP-2 of the blue mussel, Mytilus edulis

DOEpatents

Silverman, Heather G.; Roberto, Francisco F.

2006-02-07

The present invention includes a Mytilus edulis cDNA having a nucleotide sequence that encodes for the Mytilus edulis foot protein-2 (Mefp-2), an example of a mollusk foot protein. Mefp-2 is an integral component of the blue mussels' adhesive protein complex, which allows the mussel to attach to objects underwater. The isolation, purification and sequencing of the Mefp-2 gene will allow researchers to produce Mefp-2 protein using genetic engineering techniques. The discovery of Mefp-2 gene sequences will also allow scientists to better understand how the blue mussel creates its waterproof adhesive protein complex.

SeqRate: sequence-based protein folding type classification and rates prediction

PubMed Central

2010-01-01

Background Protein folding rate is an important property of a protein. Predicting protein folding rate is useful for understanding protein folding process and guiding protein design. Most previous methods of predicting protein folding rate require the tertiary structure of a protein as an input. And most methods do not distinguish the different kinetic nature (two-state folding or multi-state folding) of the proteins. Here we developed a method, SeqRate, to predict both protein folding kinetic type (two-state versus multi-state) and real-value folding rate using sequence length, amino acid composition, contact order, contact number, and secondary structure information predicted from only protein sequence with support vector machines. Results We systematically studied the contributions of individual features to folding rate prediction. On a standard benchmark dataset, the accuracy of folding kinetic type classification is 80%. The Pearson correlation coefficient and the mean absolute difference between predicted and experimental folding rates (sec-1) in the base-10 logarithmic scale are 0.81 and 0.79 for two-state protein folders, and 0.80 and 0.68 for three-state protein folders. SeqRate is the first sequence-based method for protein folding type classification and its accuracy of fold rate prediction is improved over previous sequence-based methods. Its performance can be further enhanced with additional information, such as structure-based geometric contacts, as inputs. Conclusions Both the web server and software of predicting folding rate are publicly available at http://casp.rnet.missouri.edu/fold_rate/index.html. PMID:20438647

Statistical theory for protein combinatorial libraries. Packing interactions, backbone flexibility, and the sequence variability of a main-chain structure.

PubMed

Kono, H; Saven, J G

2001-02-23

Combinatorial experiments provide new ways to probe the determinants of protein folding and to identify novel folding amino acid sequences. These types of experiments, however, are complicated both by enormous conformational complexity and by large numbers of possible sequences. Therefore, a quantitative computational theory would be helpful in designing and interpreting these types of experiment. Here, we present and apply a statistically based, computational approach for identifying the properties of sequences compatible with a given main-chain structure. Protein side-chain conformations are included in an atom-based fashion. Calculations are performed for a variety of similar backbone structures to identify sequence properties that are robust with respect to minor changes in main-chain structure. Rather than specific sequences, the method yields the likelihood of each of the amino acids at preselected positions in a given protein structure. The theory may be used to quantify the characteristics of sequence space for a chosen structure without explicitly tabulating sequences. To account for hydrophobic effects, we introduce an environmental energy that it is consistent with other simple hydrophobicity scales and show that it is effective for side-chain modeling. We apply the method to calculate the identity probabilities of selected positions of the immunoglobulin light chain-binding domain of protein L, for which many variant folding sequences are available. The calculations compare favorably with the experimentally observed identity probabilities.

Identification and characterization of Theileria ovis surface protein (ToSp) resembled TaSp in Theileria annulata.

PubMed

Shayan, P; Jafari, S; Fattahi, R; Ebrahimzade, E; Amininia, N; Changizi, E

2016-05-01

Ovine theileriosis is an important hemoprotozoal disease of sheep and goats in tropical and subtropical regions which caused high economic loses in the livestock industry. Theileria annulata surface protein (TaSp) was used previously as a tool for serological analysis in livestock. Since the amino acid sequences of TaSp is, at least, in part very conserved in T. annulata, Theileria lestoquardi and Theileria china I and II, it is very important to determine the amino acid sequence of this protein in Theileria ovis as well, to avoid false interpretation of serological data based on this protein in small animal. In the present study, the nucleotide sequence and amino acid sequence of T. ovis surface protein (ToSp) were determined. The comparison of the nucleotide sequence of ToSp showed 96, 96, 99, and 86 % homology to the corresponding nucleotide sequence of TaSp genes by T. annulata, T. China I, T. China II and T. lestoquardi, previously registered in GenBank under accession nos. AJ316260.1, AY274329.1, DQ120058.1, and EF092924.1 respectively. The amino acid sequence analysis showed 95, 81, 98 and 70 % homology to the corresponding amino acid sequence of T. annulata, T chinaI, T china II and T. lestoquardi, registered in GenBank under accession nos. CAC87478.1, AAP36993.1, AAZ30365.1 and AAP36999.11, respectively. Interestingly, in contrast to the C terminus, a significant difference in amino acid sequence in the N teminus of the ToSp protein could be determined compared to the other known corresponding TaSp sequences, which make this region attractive for designing of a suitable tool for serological diagnosis.

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

PubMed

Zemla, Adam T; Lang, Dorothy M; Kostova, Tanya; Andino, Raul; Ecale Zhou, Carol L

2011-06-02

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 help overcome these difficulties by facilitating the identification of structurally (and possibly functionally) relevant residue-residue correspondences between compared protein structures. Here we present StralSV (structure-alignment sequence variability), 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 we demonstrate that the algorithm can be used to determine regions of the protein that are relatively unique, or that share structural similarity with proteins that would be considered distantly related. By quantifying residue frequencies among many residue-residue pairs extracted from local structural 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 residues at a given sequence position. StralSV is provided as a web service at http://proteinmodel.org/AS2TS/STRALSV/.

Stratification of co-evolving genomic groups using ranked phylogenetic profiles

PubMed Central

Freilich, Shiri; Goldovsky, Leon; Gottlieb, Assaf; Blanc, Eric; Tsoka, Sophia; Ouzounis, Christos A

2009-01-01

Background Previous methods of detecting the taxonomic origins of arbitrary sequence collections, with a significant impact to genome analysis and in particular metagenomics, have primarily focused on compositional features of genomes. The evolutionary patterns of phylogenetic distribution of genes or proteins, represented by phylogenetic profiles, provide an alternative approach for the detection of taxonomic origins, but typically suffer from low accuracy. Herein, we present rank-BLAST, a novel approach for the assignment of protein sequences into genomic groups of the same taxonomic origin, based on the ranking order of phylogenetic profiles of target genes or proteins across the reference database. Results The rank-BLAST approach is validated by computing the phylogenetic profiles of all sequences for five distinct microbial species of varying degrees of phylogenetic proximity, against a reference database of 243 fully sequenced genomes. The approach - a combination of sequence searches, statistical estimation and clustering - analyses the degree of sequence divergence between sets of protein sequences and allows the classification of protein sequences according to the species of origin with high accuracy, allowing taxonomic classification of 64% of the proteins studied. In most cases, a main cluster is detected, representing the corresponding species. Secondary, functionally distinct and species-specific clusters exhibit different patterns of phylogenetic distribution, thus flagging gene groups of interest. Detailed analyses of such cases are provided as examples. Conclusion Our results indicate that the rank-BLAST approach can capture the taxonomic origins of sequence collections in an accurate and efficient manner. The approach can be useful both for the analysis of genome evolution and the detection of species groups in metagenomics samples. PMID:19860884

Synthetic signal sequences that enable efficient secretory protein production in the yeast Kluyveromyces marxianus.

PubMed

Yarimizu, Tohru; Nakamura, Mikiko; Hoshida, Hisashi; Akada, Rinji

2015-02-14

Targeting of cellular proteins to the extracellular environment is directed by a secretory signal sequence located at the N-terminus of a secretory protein. These signal sequences usually contain an N-terminal basic amino acid followed by a stretch containing hydrophobic residues, although no consensus signal sequence has been identified. In this study, simple modeling of signal sequences was attempted using Gaussia princeps secretory luciferase (GLuc) in the yeast Kluyveromyces marxianus, which allowed comprehensive recombinant gene construction to substitute synthetic signal sequences. Mutational analysis of the GLuc signal sequence revealed that the GLuc hydrophobic peptide length was lower limit for effective secretion and that the N-terminal basic residue was indispensable. Deletion of the 16th Glu caused enhanced levels of secreted protein, suggesting that this hydrophilic residue defined the boundary of a hydrophobic peptide stretch. Consequently, we redesigned this domain as a repeat of a single hydrophobic amino acid between the N-terminal Lys and C-terminal Glu. Stretches consisting of Phe, Leu, Ile, or Met were effective for secretion but the number of residues affected secretory activity. A stretch containing sixteen consecutive methionine residues (M16) showed the highest activity; the M16 sequence was therefore utilized for the secretory production of human leukemia inhibitory factor protein in yeast, resulting in enhanced secreted protein yield. We present a new concept for the provision of secretory signal sequence ability in the yeast K. marxianus, determined by the number of residues of a single hydrophobic residue located between N-terminal basic and C-terminal acidic amino acid boundaries.

A Sand Fly Salivary Protein Vaccine Shows Efficacy Against Vector-Transmitted Cutaneous Leishmaniasis in Nonhuman Primates

DTIC Science & Technology

2015-06-03

demonstrating its immunogenicity in humans. PdSP15 sequence and structure show no homol- ogy to mammalian proteins, further demonstrating its potential...sequence or structure homology to known human proteins The protective salivary antigen PdSP15 shares sequence homology only to the small odorant binding...salivary proteins PpSP15 and PsSP15, respectively (Fig. 4B). To exclude any structural similarities to human pro teins, the crystal structure of PdPS15

PaperBLAST: Text Mining Papers for Information about Homologs.

PubMed

Price, Morgan N; Arkin, Adam P

2017-01-01

Large-scale genome sequencing has identified millions of protein-coding genes whose function is unknown. Many of these proteins are similar to characterized proteins from other organisms, but much of this information is missing from annotation databases and is hidden in the scientific literature. To make this information accessible, PaperBLAST uses EuropePMC to search the full text of scientific articles for references to genes. PaperBLAST also takes advantage of curated resources (Swiss-Prot, GeneRIF, and EcoCyc) that link protein sequences to scientific articles. PaperBLAST's database includes over 700,000 scientific articles that mention over 400,000 different proteins. Given a protein of interest, PaperBLAST quickly finds similar proteins that are discussed in the literature and presents snippets of text from relevant articles or from the curators. PaperBLAST is available at http://papers.genomics.lbl.gov/. IMPORTANCE With the recent explosion of genome sequencing data, there are now millions of uncharacterized proteins. If a scientist becomes interested in one of these proteins, it can be very difficult to find information as to its likely function. Often a protein whose sequence is similar, and which is likely to have a similar function, has been studied already, but this information is not available in any database. To help find articles about similar proteins, PaperBLAST searches the full text of scientific articles for protein identifiers or gene identifiers, and it links these articles to protein sequences. Then, given a protein of interest, it can quickly find similar proteins in its database by using standard software (BLAST), and it can show snippets of text from relevant papers. We hope that PaperBLAST will make it easier for biologists to predict proteins' functions.

The C-Terminal Sequence of RhoB Directs Protein Degradation through an Endo-Lysosomal Pathway

PubMed Central

Ramos, Irene; Herrera, Mónica; Stamatakis, Konstantinos

2009-01-01

Background Protein degradation is essential for cell homeostasis. Targeting of proteins for degradation is often achieved by specific protein sequences or posttranslational modifications such as ubiquitination. Methodology/Principal Findings By using biochemical and genetic tools we have monitored the localization and degradation of endogenous and chimeric proteins in live primary cells by confocal microscopy and ultra-structural analysis. Here we identify an eight amino acid sequence from the C-terminus of the short-lived GTPase RhoB that directs the rapid degradation of both RhoB and chimeric proteins bearing this sequence through a lysosomal pathway. Elucidation of the RhoB degradation pathway unveils a mechanism dependent on protein isoprenylation and palmitoylation that involves sorting of the protein into multivesicular bodies, mediated by the ESCRT machinery. Moreover, RhoB sorting is regulated by late endosome specific lipid dynamics and is altered in human genetic lipid traffic disease. Conclusions/Significance Our findings characterize a short-lived cytosolic protein that is degraded through a lysosomal pathway. In addition, we define a novel motif for protein sorting and rapid degradation, which allows controlling protein levels by means of clinically used drugs. PMID:19956591

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

PubMed

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.

Structural hot spots for the solubility of globular proteins

PubMed Central

Ganesan, Ashok; Siekierska, Aleksandra; Beerten, Jacinte; Brams, Marijke; Van Durme, Joost; De Baets, Greet; Van der Kant, Rob; Gallardo, Rodrigo; Ramakers, Meine; Langenberg, Tobias; Wilkinson, Hannah; De Smet, Frederik; Ulens, Chris; Rousseau, Frederic; Schymkowitz, Joost

2016-01-01

Natural selection shapes protein solubility to physiological requirements and recombinant applications that require higher protein concentrations are often problematic. This raises the question whether the solubility of natural protein sequences can be improved. We here show an anti-correlation between the number of aggregation prone regions (APRs) in a protein sequence and its solubility, suggesting that mutational suppression of APRs provides a simple strategy to increase protein solubility. We show that mutations at specific positions within a protein structure can act as APR suppressors without affecting protein stability. These hot spots for protein solubility are both structure and sequence dependent but can be computationally predicted. We demonstrate this by reducing the aggregation of human α-galactosidase and protective antigen of Bacillus anthracis through mutation. Our results indicate that many proteins possess hot spots allowing to adapt protein solubility independently of structure and function. PMID:26905391

Scop3D: three-dimensional visualization of sequence conservation.

PubMed

Vermeire, Tessa; Vermaere, Stijn; Schepens, Bert; Saelens, Xavier; Van Gucht, Steven; Martens, Lennart; Vandermarliere, Elien

2015-04-01

The integration of a protein's structure with its known sequence variation provides insight on how that protein evolves, for instance in terms of (changing) function or immunogenicity. Yet, collating the corresponding sequence variants into a multiple sequence alignment, calculating each position's conservation, and mapping this information back onto a relevant structure is not straightforward. We therefore built the Sequence Conservation on Protein 3D structure (scop3D) tool to perform these tasks automatically. The output consists of two modified PDB files in which the B-values for each position are replaced by the percentage sequence conservation, or the information entropy for each position, respectively. Furthermore, text files with absolute and relative amino acid occurrences for each position are also provided, along with snapshots of the protein from six distinct directions in space. The visualization provided by scop3D can for instance be used as an aid in vaccine development or to identify antigenic hotspots, which we here demonstrate based on an analysis of the fusion proteins of human respiratory syncytial virus and mumps virus. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Combining phage display with de novo protein sequencing for reverse engineering of monoclonal antibodies.

PubMed

Rickert, Keith W; Grinberg, Luba; Woods, Robert M; Wilson, Susan; Bowen, Michael A; Baca, Manuel

2016-01-01

The enormous diversity created by gene recombination and somatic hypermutation makes de novo protein sequencing of monoclonal antibodies a uniquely challenging problem. Modern mass spectrometry-based sequencing will rarely, if ever, provide a single unambiguous sequence for the variable domains. A more likely outcome is computation of an ensemble of highly similar sequences that can satisfy the experimental data. This outcome can result in the need for empirical testing of many candidate sequences, sometimes iteratively, to identity one which can replicate the activity of the parental antibody. Here we describe an improved approach to antibody protein sequencing by using phage display technology to generate a combinatorial library of sequences that satisfy the mass spectrometry data, and selecting for functional candidates that bind antigen. This approach was used to reverse engineer 2 commercially-obtained monoclonal antibodies against murine CD137. Proteomic data enabled us to assign the majority of the variable domain sequences, with the exception of 3-5% of the sequence located within or adjacent to complementarity-determining regions. To efficiently resolve the sequence in these regions, small phage-displayed libraries were generated and subjected to antigen binding selection. Following enrichment of antigen-binding clones, 2 clones were selected for each antibody and recombinantly expressed as antigen-binding fragments (Fabs). In both cases, the reverse-engineered Fabs exhibited identical antigen binding affinity, within error, as Fabs produced from the commercial IgGs. This combination of proteomic and protein engineering techniques provides a useful approach to simplifying the technically challenging process of reverse engineering monoclonal antibodies from protein material.

Not all transmembrane helices are born equal: Towards the extension of the sequence homology concept to membrane proteins

PubMed Central

2011-01-01

Background Sequence homology considerations widely used to transfer functional annotation to uncharacterized protein sequences require special precautions in the case of non-globular sequence segments including membrane-spanning stretches composed of non-polar residues. Simple, quantitative criteria are desirable for identifying transmembrane helices (TMs) that must be included into or should be excluded from start sequence segments in similarity searches aimed at finding distant homologues. Results We found that there are two types of TMs in membrane-associated proteins. On the one hand, there are so-called simple TMs with elevated hydrophobicity, low sequence complexity and extraordinary enrichment in long aliphatic residues. They merely serve as membrane-anchoring device. In contrast, so-called complex TMs have lower hydrophobicity, higher sequence complexity and some functional residues. These TMs have additional roles besides membrane anchoring such as intra-membrane complex formation, ligand binding or a catalytic role. Simple and complex TMs can occur both in single- and multi-membrane-spanning proteins essentially in any type of topology. Whereas simple TMs have the potential to confuse searches for sequence homologues and to generate unrelated hits with seemingly convincing statistical significance, complex TMs contain essential evolutionary information. Conclusion For extending the homology concept onto membrane proteins, we provide a necessary quantitative criterion to distinguish simple TMs (and a sufficient criterion for complex TMs) in query sequences prior to their usage in homology searches based on assessment of hydrophobicity and sequence complexity of the TM sequence segments. Reviewers This article was reviewed by Shamil Sunyaev, L. Aravind and Arcady Mushegian. PMID:22024092

Combining phage display with de novo protein sequencing for reverse engineering of monoclonal antibodies

PubMed Central

Rickert, Keith W.; Grinberg, Luba; Woods, Robert M.; Wilson, Susan; Bowen, Michael A.; Baca, Manuel

2016-01-01

ABSTRACT The enormous diversity created by gene recombination and somatic hypermutation makes de novo protein sequencing of monoclonal antibodies a uniquely challenging problem. Modern mass spectrometry-based sequencing will rarely, if ever, provide a single unambiguous sequence for the variable domains. A more likely outcome is computation of an ensemble of highly similar sequences that can satisfy the experimental data. This outcome can result in the need for empirical testing of many candidate sequences, sometimes iteratively, to identity one which can replicate the activity of the parental antibody. Here we describe an improved approach to antibody protein sequencing by using phage display technology to generate a combinatorial library of sequences that satisfy the mass spectrometry data, and selecting for functional candidates that bind antigen. This approach was used to reverse engineer 2 commercially-obtained monoclonal antibodies against murine CD137. Proteomic data enabled us to assign the majority of the variable domain sequences, with the exception of 3–5% of the sequence located within or adjacent to complementarity-determining regions. To efficiently resolve the sequence in these regions, small phage-displayed libraries were generated and subjected to antigen binding selection. Following enrichment of antigen-binding clones, 2 clones were selected for each antibody and recombinantly expressed as antigen-binding fragments (Fabs). In both cases, the reverse-engineered Fabs exhibited identical antigen binding affinity, within error, as Fabs produced from the commercial IgGs. This combination of proteomic and protein engineering techniques provides a useful approach to simplifying the technically challenging process of reverse engineering monoclonal antibodies from protein material. PMID:26852694

Prediction of cis/trans isomerization in proteins using PSI-BLAST profiles and secondary structure information.

PubMed

Song, Jiangning; Burrage, Kevin; Yuan, Zheng; Huber, Thomas

2006-03-09

The majority of peptide bonds in proteins are found to occur in the trans conformation. However, for proline residues, a considerable fraction of Prolyl peptide bonds adopt the cis form. Proline cis/trans isomerization is known to play a critical role in protein folding, splicing, cell signaling and transmembrane active transport. Accurate prediction of proline cis/trans isomerization in proteins would have many important applications towards the understanding of protein structure and function. In this paper, we propose a new approach to predict the proline cis/trans isomerization in proteins using support vector machine (SVM). The preliminary results indicated that using Radial Basis Function (RBF) kernels could lead to better prediction performance than that of polynomial and linear kernel functions. We used single sequence information of different local window sizes, amino acid compositions of different local sequences, multiple sequence alignment obtained from PSI-BLAST and the secondary structure information predicted by PSIPRED. We explored these different sequence encoding schemes in order to investigate their effects on the prediction performance. The training and testing of this approach was performed on a newly enlarged dataset of 2424 non-homologous proteins determined by X-Ray diffraction method using 5-fold cross-validation. Selecting the window size 11 provided the best performance for determining the proline cis/trans isomerization based on the single amino acid sequence. It was found that using multiple sequence alignments in the form of PSI-BLAST profiles could significantly improve the prediction performance, the prediction accuracy increased from 62.8% with single sequence to 69.8% and Matthews Correlation Coefficient (MCC) improved from 0.26 with single local sequence to 0.40. Furthermore, if coupled with the predicted secondary structure information by PSIPRED, our method yielded a prediction accuracy of 71.5% and MCC of 0.43, 9% and 0.17 higher than the accuracy achieved based on the singe sequence information, respectively. A new method has been developed to predict the proline cis/trans isomerization in proteins based on support vector machine, which used the single amino acid sequence with different local window sizes, the amino acid compositions of local sequence flanking centered proline residues, the position-specific scoring matrices (PSSMs) extracted by PSI-BLAST and the predicted secondary structures generated by PSIPRED. The successful application of SVM approach in this study reinforced that SVM is a powerful tool in predicting proline cis/trans isomerization in proteins and biological sequence analysis.

Three copies of a single protein II-encoding sequence in the genome of Neisseria gonorrhoeae JS3: evidence for gene conversion and gene duplication.

PubMed

van der Ley, P

1988-11-01

Gonococci express a family of related outer membrane proteins designated protein II (P.II). These surface proteins are subject to both phase variation and antigenic variation. The P.II gene repertoire of Neisseria gonorrhoeae strain JS3 was found to consist of at least ten genes, eight of which were cloned. Sequence analysis and DNA hybridization studies revealed that one particular P.II-encoding sequence is present in three distinct, but almost identical, copies in the JS3 genome. These genes encode the P.II protein that was previously identified as P.IIc. Comparison of their sequences shows that the multiple copies of this P.IIc-encoding gene might have been generated by both gene conversion and gene duplication.

A Versatile Platform for Nanotechnology Based on Circular Permutation of a Chaperonin Protein

NASA Technical Reports Server (NTRS)

Paavola, Chad; McMillan, Andrew; Trent, Jonathan; Chan, Suzanne; Mazzarella, Kellen; Li, Yi-Fen

2004-01-01

A number of protein complexes have been developed as nanoscale templates. These templates can be functionalized using the peptide sequences that bind inorganic materials. However, it is difficult to integrate peptides into a specific position within a protein template. Integrating intact proteins with desirable binding or catalytic activities is an even greater challenge. We present a general method for modifying protein templates using circular permutation so that additional peptide sequence can be added in a wide variety of specific locations. Circular permutation is a reordering of the polypeptide chain such that the original termini are joined and new termini are created elsewhere in the protein. New sequence can be joined to the protein termini without perturbing the protein structure and with minimal limitation on the size and conformation of the added sequence. We have used this approach to modify a chaperonin protein template, placing termini at five different locations distributed across the surface of the protein complex. These permutants are competent to form the double-ring structures typical of chaperonin proteins. The permuted double-rings also form the same assemblies as the unmodified protein. We fused a fluorescent protein to two representative permutants and demonstrated that it assumes its active structure and does not interfere with assembly of chaperonin double-rings.

The crystal structure of Erwinia amylovora AmyR, a member of the YbjN protein family, shows similarity to type III secretion chaperones but suggests different cellular functions

PubMed Central

Bartho, Joseph D.; Bellini, Dom; Wuerges, Jochen; Demitri, Nicola; Toccafondi, Mirco; Schmitt, Armin O.; Zhao, Youfu; Walsh, Martin A.

2017-01-01

AmyR is a stress and virulence associated protein from the plant pathogenic Enterobacteriaceae species Erwinia amylovora, and is a functionally conserved ortholog of YbjN from Escherichia coli. The crystal structure of E. amylovora AmyR reveals a class I type III secretion chaperone-like fold, despite the lack of sequence similarity between these two classes of protein and lacking any evidence of a secretion-associated role. The results indicate that AmyR, and YbjN proteins in general, function through protein-protein interactions without any enzymatic action. The YbjN proteins of Enterobacteriaceae show remarkably low sequence similarity with other members of the YbjN protein family in Eubacteria, yet a high level of structural conservation is observed. Across the YbjN protein family sequence conservation is limited to residues stabilising the protein core and dimerization interface, while interacting regions are only conserved between closely related species. This study presents the first structure of a YbjN protein from Enterobacteriaceae, the most highly divergent and well-studied subgroup of YbjN proteins, and an in-depth sequence and structural analysis of this important but poorly understood protein family. PMID:28426806

The crystal structure of Erwinia amylovora AmyR, a member of the YbjN protein family, shows similarity to type III secretion chaperones but suggests different cellular functions.

PubMed

Bartho, Joseph D; Bellini, Dom; Wuerges, Jochen; Demitri, Nicola; Toccafondi, Mirco; Schmitt, Armin O; Zhao, Youfu; Walsh, Martin A; Benini, Stefano

2017-01-01

AmyR is a stress and virulence associated protein from the plant pathogenic Enterobacteriaceae species Erwinia amylovora, and is a functionally conserved ortholog of YbjN from Escherichia coli. The crystal structure of E. amylovora AmyR reveals a class I type III secretion chaperone-like fold, despite the lack of sequence similarity between these two classes of protein and lacking any evidence of a secretion-associated role. The results indicate that AmyR, and YbjN proteins in general, function through protein-protein interactions without any enzymatic action. The YbjN proteins of Enterobacteriaceae show remarkably low sequence similarity with other members of the YbjN protein family in Eubacteria, yet a high level of structural conservation is observed. Across the YbjN protein family sequence conservation is limited to residues stabilising the protein core and dimerization interface, while interacting regions are only conserved between closely related species. This study presents the first structure of a YbjN protein from Enterobacteriaceae, the most highly divergent and well-studied subgroup of YbjN proteins, and an in-depth sequence and structural analysis of this important but poorly understood protein family.

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

PubMed

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.

Innate Immune Complexity in the Purple Sea Urchin: Diversity of the Sp185/333 System

PubMed Central

Smith, L. Courtney

2012-01-01

The California purple sea urchin, Strongylocentrotus purpuratus, is a long-lived echinoderm with a complex and sophisticated innate immune system. There are several large gene families that function in immunity in this species including the Sp185/333 gene family that has ∼50 (±10) members. The family shows intriguing sequence diversity and encodes a broad array of diverse yet similar proteins. The genes have two exons of which the second encodes the mature protein and has repeats and blocks of sequence called elements. Mosaics of element patterns plus single nucleotide polymorphisms-based variants of the elements result in significant sequence diversity among the genes yet maintains similar structure among the members of the family. Sequence of a bacterial artificial chromosome insert shows a cluster of six, tightly linked Sp185/333 genes that are flanked by GA microsatellites. The sequences between the GA microsatellites in which the Sp185/333 genes and flanking regions are located, are much more similar to each other than are the sequences outside the microsatellites suggesting processes such as gene conversion, recombination, or duplication. However, close linkage does not correspond with greater sequence similarity compared to randomly cloned and sequenced genes that are unlikely to be linked. There are three segmental duplications that are bounded by GAT microsatellites and include three almost identical genes plus flanking regions. RNA editing is detectible throughout the mRNAs based on comparisons to the genes, which, in combination with putative post-translational modifications to the proteins, results in broad arrays of Sp185/333 proteins that differ among individuals. The mature proteins have an N-terminal glycine-rich region, a central RGD motif, and a C-terminal histidine-rich region. The Sp185/333 proteins are localized to the cell surface and are found within vesicles in subsets of polygonal and small phagocytes. The coelomocyte proteome shows full-length and truncated proteins, including some with missense sequence. Current results suggest that both native Sp185/333 proteins and a recombinant protein bind bacteria and are likely important in sea urchin innate immunity. PMID:22566951

Cloning and expression of cDNA coding for bouganin.

PubMed

den Hartog, Marcel T; Lubelli, Chiara; Boon, Louis; Heerkens, Sijmie; Ortiz Buijsse, Antonio P; de Boer, Mark; Stirpe, Fiorenzo

2002-03-01

Bouganin is a ribosome-inactivating protein that recently was isolated from Bougainvillea spectabilis Willd. In this work, the cloning and expression of the cDNA encoding for bouganin is described. From the cDNA, the amino-acid sequence was deduced, which correlated with the primary sequence data obtained by amino-acid sequencing on the native protein. Bouganin is synthesized as a pro-peptide consisting of 305 amino acids, the first 26 of which act as a leader signal while the 29 C-terminal amino acids are cleaved during processing of the molecule. The mature protein consists of 250 amino acids. Using the cDNA sequence encoding the mature protein of 250 amino acids, a recombinant protein was expressed, purified and characterized. The recombinant molecule had similar activity in a cell-free protein synthesis assay and had comparable toxicity on living cells as compared to the isolated native bouganin.

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

PubMed

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

PubMed Central

Krwawicz, Joanna

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. PMID:28617832

Protein Sectors: Statistical Coupling Analysis versus Conservation

PubMed Central

Teşileanu, Tiberiu; Colwell, Lucy J.; Leibler, Stanislas

2015-01-01

Statistical coupling analysis (SCA) is a method for analyzing multiple sequence alignments that was used to identify groups of coevolving residues termed “sectors”. The method applies spectral analysis to a matrix obtained by combining correlation information with sequence conservation. It has been asserted that the protein sectors identified by SCA are functionally significant, with different sectors controlling different biochemical properties of the protein. Here we reconsider the available experimental data and note that it involves almost exclusively proteins with a single sector. We show that in this case sequence conservation is the dominating factor in SCA, and can alone be used to make statistically equivalent functional predictions. Therefore, we suggest shifting the experimental focus to proteins for which SCA identifies several sectors. Correlations in protein alignments, which have been shown to be informative in a number of independent studies, would then be less dominated by sequence conservation. PMID:25723535

Hyperdiversity of Genes Encoding Integral Light-Harvesting Proteins in the Dinoflagellate Symbiodinium sp

PubMed Central

Boldt, Lynda; Yellowlees, David; Leggat, William

2012-01-01

The superfamily of light-harvesting complex (LHC) proteins is comprised of proteins with diverse functions in light-harvesting and photoprotection. LHC proteins bind chlorophyll (Chl) and carotenoids and include a family of LHCs that bind Chl a and c. Dinophytes (dinoflagellates) are predominantly Chl c binding algal taxa, bind peridinin or fucoxanthin as the primary carotenoid, and can possess a number of LHC subfamilies. Here we report 11 LHC sequences for the chlorophyll a-chlorophyll c 2-peridinin protein complex (acpPC) subfamily isolated from Symbiodinium sp. C3, an ecologically important peridinin binding dinoflagellate taxa. Phylogenetic analysis of these proteins suggests the acpPC subfamily forms at least three clades within the Chl a/c binding LHC family; Clade 1 clusters with rhodophyte, cryptophyte and peridinin binding dinoflagellate sequences, Clade 2 with peridinin binding dinoflagellate sequences only and Clades 3 with heterokontophytes, fucoxanthin and peridinin binding dinoflagellate sequences. PMID:23112815

The Functional Human C-Terminome

PubMed Central

Hedden, Michael; Lyon, Kenneth F.; Brooks, Steven B.; David, Roxanne P.; Limtong, Justin; Newsome, Jacklyn M.; Novakovic, Nemanja; Rajasekaran, Sanguthevar; Thapar, Vishal; Williams, Sean R.; Schiller, Martin R.

2016-01-01

All translated proteins end with a carboxylic acid commonly called the C-terminus. Many short functional sequences (minimotifs) are located on or immediately proximal to the C-terminus. However, information about the function of protein C-termini has not been consolidated into a single source. Here, we built a new “C-terminome” database and web system focused on human proteins. Approximately 3,600 C-termini in the human proteome have a minimotif with an established molecular function. To help evaluate the function of the remaining C-termini in the human proteome, we inferred minimotifs identified by experimentation in rodent cells, predicted minimotifs based upon consensus sequence matches, and predicted novel highly repetitive sequences in C-termini. Predictions can be ranked by enrichment scores or Gene Evolutionary Rate Profiling (GERP) scores, a measurement of evolutionary constraint. By searching for new anchored sequences on the last 10 amino acids of proteins in the human proteome with lengths between 3–10 residues and up to 5 degenerate positions in the consensus sequences, we have identified new consensus sequences that predict instances in the majority of human genes. All of this information is consolidated into a database that can be accessed through a C-terminome web system with search and browse functions for minimotifs and human proteins. A known consensus sequence-based predicted function is assigned to nearly half the proteins in the human proteome. Weblink: http://cterminome.bio-toolkit.com. PMID:27050421

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

PubMed

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.

Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis.

PubMed

Du, Yushen; Wu, Nicholas C; Jiang, Lin; Zhang, Tianhao; Gong, Danyang; Shu, Sara; Wu, Ting-Ting; Sun, Ren

2016-11-01

Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp), we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available. To fully comprehend the diverse functions of a protein, it is essential to understand the functionality of individual residues. Current methods are highly dependent on evolutionary sequence conservation, which is usually limited by sampling size. Sequence conservation-based methods are further confounded by structural constraints and multifunctionality of proteins. Here we present a method that can systematically identify and annotate functional residues of a given protein. We used a high-throughput functional profiling platform to identify essential residues. Coupling it with homologous-structure comparison, we were able to annotate multiple functions of proteins. We demonstrated the method with the PB1 protein of influenza A virus and identified novel functional residues in addition to its canonical function as an RNA-dependent RNA polymerase. Not limited to virology, this method is generally applicable to other proteins that can be functionally selected and about which homologous-structure information is available. Copyright © 2016 Du et al.

High-Resolution Sequence-Function Mapping of Full-Length Proteins

PubMed Central

Kowalsky, Caitlin A.; Klesmith, Justin R.; Stapleton, James A.; Kelly, Vince; Reichkitzer, Nolan; Whitehead, Timothy A.

2015-01-01

Comprehensive sequence-function mapping involves detailing the fitness contribution of every possible single mutation to a gene by comparing the abundance of each library variant before and after selection for the phenotype of interest. Deep sequencing of library DNA allows frequency reconstruction for tens of thousands of variants in a single experiment, yet short read lengths of current sequencers makes it challenging to probe genes encoding full-length proteins. Here we extend the scope of sequence-function maps to entire protein sequences with a modular, universal sequence tiling method. We demonstrate the approach with both growth-based selections and FACS screening, offer parameters and best practices that simplify design of experiments, and present analytical solutions to normalize data across independent selections. Using this protocol, sequence-function maps covering full sequences can be obtained in four to six weeks. Best practices introduced in this manuscript are fully compatible with, and complementary to, other recently published sequence-function mapping protocols. PMID:25790064

PaperBLAST: Text Mining Papers for Information about Homologs

DOE PAGES

Price, Morgan N.; Arkin, Adam P.

2017-08-15

Large-scale genome sequencing has identified millions of protein-coding genes whose function is unknown. Many of these proteins are similar to characterized proteins from other organisms, but much of this information is missing from annotation databases and is hidden in the scientific literature. To make this information accessible, PaperBLAST uses EuropePMC to search the full text of scientific articles for references to genes. PaperBLAST also takes advantage of curated resources (Swiss-Prot, GeneRIF, and EcoCyc) that link protein sequences to scientific articles. PaperBLAST’s database includes over 700,000 scientific articles that mention over 400,000 different proteins. Given a protein of interest, PaperBLAST quicklymore » finds similar proteins that are discussed in the literature and presents snippets of text from relevant articles or from the curators. With the recent explosion of genome sequencing data, there are now millions of uncharacterized proteins. If a scientist becomes interested in one of these proteins, it can be very difficult to find information as to its likely function. Often a protein whose sequence is similar, and which is likely to have a similar function, has been studied already, but this information is not available in any database. To help find articles about similar proteins, PaperBLAST searches the full text of scientific articles for protein identifiers or gene identifiers, and it links these articles to protein sequences. Then, given a protein of interest, it can quickly find similar proteins in its database by using standard software (BLAST), and it can show snippets of text from relevant papers. We hope that PaperBLAST will make it easier for biologists to predict proteins’ functions.« less

PaperBLAST: Text Mining Papers for Information about Homologs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Price, Morgan N.; Arkin, Adam P.

Large-scale genome sequencing has identified millions of protein-coding genes whose function is unknown. Many of these proteins are similar to characterized proteins from other organisms, but much of this information is missing from annotation databases and is hidden in the scientific literature. To make this information accessible, PaperBLAST uses EuropePMC to search the full text of scientific articles for references to genes. PaperBLAST also takes advantage of curated resources (Swiss-Prot, GeneRIF, and EcoCyc) that link protein sequences to scientific articles. PaperBLAST’s database includes over 700,000 scientific articles that mention over 400,000 different proteins. Given a protein of interest, PaperBLAST quicklymore » finds similar proteins that are discussed in the literature and presents snippets of text from relevant articles or from the curators. With the recent explosion of genome sequencing data, there are now millions of uncharacterized proteins. If a scientist becomes interested in one of these proteins, it can be very difficult to find information as to its likely function. Often a protein whose sequence is similar, and which is likely to have a similar function, has been studied already, but this information is not available in any database. To help find articles about similar proteins, PaperBLAST searches the full text of scientific articles for protein identifiers or gene identifiers, and it links these articles to protein sequences. Then, given a protein of interest, it can quickly find similar proteins in its database by using standard software (BLAST), and it can show snippets of text from relevant papers. We hope that PaperBLAST will make it easier for biologists to predict proteins’ functions.« less

PaperBLAST: Text Mining Papers for Information about Homologs

PubMed Central

Arkin, Adam P.

2017-01-01

ABSTRACT Large-scale genome sequencing has identified millions of protein-coding genes whose function is unknown. Many of these proteins are similar to characterized proteins from other organisms, but much of this information is missing from annotation databases and is hidden in the scientific literature. To make this information accessible, PaperBLAST uses EuropePMC to search the full text of scientific articles for references to genes. PaperBLAST also takes advantage of curated resources (Swiss-Prot, GeneRIF, and EcoCyc) that link protein sequences to scientific articles. PaperBLAST’s database includes over 700,000 scientific articles that mention over 400,000 different proteins. Given a protein of interest, PaperBLAST quickly finds similar proteins that are discussed in the literature and presents snippets of text from relevant articles or from the curators. PaperBLAST is available at http://papers.genomics.lbl.gov/. IMPORTANCE With the recent explosion of genome sequencing data, there are now millions of uncharacterized proteins. If a scientist becomes interested in one of these proteins, it can be very difficult to find information as to its likely function. Often a protein whose sequence is similar, and which is likely to have a similar function, has been studied already, but this information is not available in any database. To help find articles about similar proteins, PaperBLAST searches the full text of scientific articles for protein identifiers or gene identifiers, and it links these articles to protein sequences. Then, given a protein of interest, it can quickly find similar proteins in its database by using standard software (BLAST), and it can show snippets of text from relevant papers. We hope that PaperBLAST will make it easier for biologists to predict proteins’ functions. PMID:28845458

Defining a Conformational Consensus Motif in Cotransin-Sensitive Signal Sequences: A Proteomic and Site-Directed Mutagenesis Study

PubMed Central

Klein, Wolfgang; Westendorf, Carolin; Schmidt, Antje; Conill-Cortés, Mercè; Rutz, Claudia; Blohs, Marcus; Beyermann, Michael; Protze, Jonas; Krause, Gerd; Krause, Eberhard; Schülein, Ralf

2015-01-01

The cyclodepsipeptide cotransin was described to inhibit the biosynthesis of a small subset of proteins by a signal sequence-discriminatory mechanism at the Sec61 protein-conducting channel. However, it was not clear how selective cotransin is, i.e. how many proteins are sensitive. Moreover, a consensus motif in signal sequences mediating cotransin sensitivity has yet not been described. To address these questions, we performed a proteomic study using cotransin-treated human hepatocellular carcinoma cells and the stable isotope labelling by amino acids in cell culture technique in combination with quantitative mass spectrometry. We used a saturating concentration of cotransin (30 micromolar) to identify also less-sensitive proteins and to discriminate the latter from completely resistant proteins. We found that the biosynthesis of almost all secreted proteins was cotransin-sensitive under these conditions. In contrast, biosynthesis of the majority of the integral membrane proteins was cotransin-resistant. Cotransin sensitivity of signal sequences was neither related to their length nor to their hydrophobicity. Instead, in the case of signal anchor sequences, we identified for the first time a conformational consensus motif mediating cotransin sensitivity. PMID:25806945

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

PubMed

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.

MIPS: analysis and annotation of proteins from whole genomes

PubMed Central

Mewes, H. W.; Amid, C.; Arnold, R.; Frishman, D.; Güldener, U.; Mannhaupt, G.; Münsterkötter, M.; Pagel, P.; Strack, N.; Stümpflen, V.; Warfsmann, J.; Ruepp, A.

2004-01-01

The Munich Information Center for Protein Sequences (MIPS-GSF), Neuherberg, Germany, provides protein sequence-related information based on whole-genome analysis. The main focus of the work is directed toward the systematic organization of sequence-related attributes as gathered by a variety of algorithms, primary information from experimental data together with information compiled from the scientific literature. MIPS 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 database of complete cDNAs (German Human Genome Project, NGFN), the database of mammalian protein–protein interactions (MPPI), the database of FASTA homologies (SIMAP), and the interface for the fast retrieval of protein-associated information (QUIPOS). The Arabidopsis thaliana database, the rice database, the plant EST databases (MATDB, MOsDB, SPUTNIK), as well as the databases for the comprehensive set of genomes (PEDANT genomes) are described elsewhere in the 2003 and 2004 NAR database issues, respectively. All databases described, and the detailed descriptions of our projects can be accessed through the MIPS web server (http://mips.gsf.de). PMID:14681354

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

PubMed

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.

Protein Structure Determination using Metagenome sequence data

PubMed Central

Ovchinnikov, Sergey; Park, Hahnbeom; Varghese, Neha; Huang, Po-Ssu; Pavlopoulos, Georgios A.; Kim, David E.; Kamisetty, Hetunandan; Kyrpides, Nikos C.; Baker, David

2017-01-01

Despite decades of work by structural biologists, there are still ~5200 protein families with unknown structure outside the range of comparative modeling. We show that Rosetta structure prediction guided by residue-residue contacts inferred from evolutionary information can accurately model proteins that belong to large families, and that metagenome sequence data more than triples the number of protein families with sufficient sequences for accurate modeling. We then integrate metagenome data, contact based structure matching and Rosetta structure calculations to generate models for 614 protein families with currently unknown structures; 206 are membrane proteins and 137 have folds not represented in the PDB. This approach provides the representative models for large protein families originally envisioned as the goal of the protein structure initiative at a fraction of the cost. PMID:28104891

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

PubMed

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.

Draft versus finished sequence data for DNA and protein diagnostic signature development

PubMed Central

Gardner, Shea N.; Lam, Marisa W.; Smith, Jason R.; Torres, Clinton L.; Slezak, Tom R.

2005-01-01

Sequencing pathogen genomes is costly, demanding careful allocation of limited sequencing resources. We built a computational Sequencing Analysis Pipeline (SAP) to guide decisions regarding the amount of genomic sequencing necessary to develop high-quality diagnostic DNA and protein signatures. SAP uses simulations to estimate the number of target genomes and close phylogenetic relatives (near neighbors or NNs) to sequence. We use SAP to assess whether draft data are sufficient or finished sequencing is required using Marburg and variola virus sequences. Simulations indicate that intermediate to high-quality draft with error rates of 10−3–10−5 (∼8× coverage) of target organisms is suitable for DNA signature prediction. Low-quality draft with error rates of ∼1% (3× to 6× coverage) of target isolates is inadequate for DNA signature prediction, although low-quality draft of NNs is sufficient, as long as the target genomes are of high quality. For protein signature prediction, sequencing errors in target genomes substantially reduce the detection of amino acid sequence conservation, even if the draft is of high quality. In summary, high-quality draft of target and low-quality draft of NNs appears to be a cost-effective investment for DNA signature prediction, but may lead to underestimation of predicted protein signatures. PMID:16243783

Selection of a platinum-binding sequence in a loop of a four-helix bundle protein.

PubMed

Yagi, Sota; Akanuma, Satoshi; Kaji, Asumi; Niiro, Hiroya; Akiyama, Hayato; Uchida, Tatsuya; Yamagishi, Akihiko

2018-02-01

Protein-metal hybrids are functional materials with various industrial applications. For example, a redox enzyme immobilized on a platinum electrode is a key component of some biofuel cells and biosensors. To create these hybrid materials, protein molecules are bound to metal surfaces. Here, we report the selection of a novel platinum-binding sequence in a loop of a four-helix bundle protein, the Lac repressor four-helix protein (LARFH), an artificial protein in which four identical α-helices are connected via three identical loops. We created a genetic library in which the Ser-Gly-Gln-Gly-Gly-Ser sequence within the first inter-helical loop of LARFH was semi-randomly mutated. The library was then subjected to selection for platinum-binding affinity by using the T7 phage display method. The majority of the selected variants contained the Tyr-Lys-Arg-Gly-Tyr-Lys (YKRGYK) sequence in their randomized segment. We characterized the platinum-binding properties of mutant LARFH by using quartz crystal microbalance analysis. Mutant LARFH seemed to interact with platinum through its loop containing the YKRGYK sequence, as judged by the estimated exclusive area occupied by a single molecule. Furthermore, a 10-residue peptide containing the YKRGYK sequence bound to platinum with reasonably high affinity and basic side chains in the peptide were crucial in mediating this interaction. In conclusion, we have identified an amino acid sequence, YKRGYK, in the loop of a helix-loop-helix motif that shows high platinum-binding affinity. This sequence could be grafted into loops of other polypeptides as an approach to immobilize proteins on platinum electrodes for use as biosensors among other applications. Copyright © 2017 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

A novel method based on new adaptive LVQ neural network for predicting protein-protein interactions from protein sequences.

PubMed

Yousef, Abdulaziz; Moghadam Charkari, Nasrollah

2013-11-07

Protein-Protein interaction (PPI) is one of the most important data in understanding the cellular processes. Many interesting methods have been proposed in order to predict PPIs. However, the methods which are based on the sequence of proteins as a prior knowledge are more universal. In this paper, a sequence-based, fast, and adaptive PPI prediction method is introduced to assign two proteins to an interaction class (yes, no). First, in order to improve the presentation of the sequences, twelve physicochemical properties of amino acid have been used by different representation methods to transform the sequence of protein pairs into different feature vectors. Then, for speeding up the learning process and reducing the effect of noise PPI data, principal component analysis (PCA) is carried out as a proper feature extraction algorithm. Finally, a new and adaptive Learning Vector Quantization (LVQ) predictor is designed to deal with different models of datasets that are classified into balanced and imbalanced datasets. The accuracy of 93.88%, 90.03%, and 89.72% has been found on S. cerevisiae, H. pylori, and independent datasets, respectively. The results of various experiments indicate the efficiency and validity of the method. © 2013 Published by Elsevier Ltd.

Next-generation sequencing coupled with a cell-free display technology for high-throughput production of reliable interactome data

PubMed Central

Fujimori, Shigeo; Hirai, Naoya; Ohashi, Hiroyuki; Masuoka, Kazuyo; Nishikimi, Akihiko; Fukui, Yoshinori; Washio, Takanori; Oshikubo, Tomohiro; Yamashita, Tatsuhiro; Miyamoto-Sato, Etsuko

2012-01-01

Next-generation sequencing (NGS) has been applied to various kinds of omics studies, resulting in many biological and medical discoveries. However, high-throughput protein-protein interactome datasets derived from detection by sequencing are scarce, because protein-protein interaction analysis requires many cell manipulations to examine the interactions. The low reliability of the high-throughput data is also a problem. Here, we describe a cell-free display technology combined with NGS that can improve both the coverage and reliability of interactome datasets. The completely cell-free method gives a high-throughput and a large detection space, testing the interactions without using clones. The quantitative information provided by NGS reduces the number of false positives. The method is suitable for the in vitro detection of proteins that interact not only with the bait protein, but also with DNA, RNA and chemical compounds. Thus, it could become a universal approach for exploring the large space of protein sequences and interactome networks. PMID:23056904

An Internal Signal Sequence Directs Intramembrane Proteolysis of a Cellular Immunoglobulin Domain Protein*S⃞

PubMed Central

Robakis, Thalia; Bak, Beata; Lin, Shu-huei; Bernard, Daniel J.; Scheiffele, Peter

2008-01-01

Precursor proteolysis is a crucial mechanism for regulating protein structure and function. Signal peptidase (SP) is an enzyme with a well defined role in cleaving N-terminal signal sequences but no demonstrated function in the proteolysis of cellular precursor proteins. We provide evidence that SP mediates intraprotein cleavage of IgSF1, a large cellular Ig domain protein that is processed into two separate Ig domain proteins. In addition, our results suggest the involvement of signal peptide peptidase (SPP), an intramembrane protease, which acts on substrates that have been previously cleaved by SP. We show that IgSF1 is processed through sequential proteolysis by SP and SPP. Cleavage is directed by an internal signal sequence and generates two separate Ig domain proteins from a polytopic precursor. Our findings suggest that SP and SPP function are not restricted to N-terminal signal sequence cleavage but also contribute to the processing of cellular transmembrane proteins. PMID:18981173

Characteristic motifs for families of allergenic proteins

PubMed Central

Ivanciuc, Ovidiu; Garcia, Tzintzuni; Torres, Miguel; Schein, Catherine H.; Braun, Werner

2008-01-01

The identification of potential allergenic proteins is usually done by scanning a database of allergenic proteins and locating known allergens with a high sequence similarity. However, there is no universally accepted cut-off value for sequence similarity to indicate potential IgE cross-reactivity. Further, overall sequence similarity may be less important than discrete areas of similarity in proteins with homologous structure. To identify such areas, we first classified all allergens and their subdomains in the Structural Database of Allergenic Proteins (SDAP, http://fermi.utmb.edu/SDAP/) to their closest protein families as defined in Pfam, and identified conserved physicochemical property motifs characteristic of each group of sequences. Allergens populate only a small subset of all known Pfam families, as all allergenic proteins in SDAP could be grouped to only 130 (of 9318 total) Pfams, and 31 families contain more than four allergens. Conserved physicochemical property motifs for the aligned sequences of the most populated Pfam families were identified with the PCPMer program suite and catalogued in the webserver Motif-Mate (http://born.utmb.edu/motifmate/summary.php). We also determined specific motifs for allergenic members of a family that could distinguish them from non-allergenic ones. These allergen specific motifs should be most useful in database searches for potential allergens. We found that sequence motifs unique to the allergens in three families (seed storage proteins, Bet v 1, and tropomyosin) overlap with known IgE epitopes, thus providing evidence that our motif based approach can be used to assess the potential allergenicity of novel proteins. PMID:18951633

Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis

PubMed Central

Du, Yushen; Wu, Nicholas C.; Jiang, Lin; Zhang, Tianhao; Gong, Danyang; Shu, Sara; Wu, Ting-Ting

2016-01-01

ABSTRACT Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp), we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available. PMID:27803181

Gene encoding the group B streptococcal protein R4, its presence in clinical reference laboratory isolates & R4 protein pepsin sensitivity.

PubMed

Smith, B L; Flores, A; Dechaine, J; Krepela, J; Bergdall, A; Ferrieri, P

2004-05-01

R proteins were first identified by Lancefield in group B Streptococcus (GBS) as resistant to trypsin at pH8 and sensitive to pepsin at pH2. The R4 protein found predominantly in type III and some type II and V invasive isolates conforms to these criteria. The Rib protein, although structurally and epidemiologically similar to R4, was reported as resistant to both proteases. We report here the gene encoding the R4 protein from a type III group B streptococcal isolate (76-043) well characterized in our laboratory. Trypsin extracted GBS proteins were assayed for protease sensitivities by double-diffusion Ouchterlony using varying conditions for the enzyme pepsin. Standard haemoglobin assay was used to examine pepsin enzymatic activity. Thirty clinical isolates of varying protein profiles identified by double-diffusion from our reference strain laboratory were screened by PCR and Southern technique. SDS-PAGE gel purified R4 amino acid sequences were determined and used to design oligonucleotide primers for screening a 76-043 genomic library. R4 was sensitive to pepsin at pH2 but appeared resistant at pH4, the reported pH used for Rib. By standard haemoglobin assay and trypsin extract studies of R4 protein, pepsin was shown to be active at pH2, yet easily inactivated; assays of GBS surface proteins are critical at pH2. Of the amino acids initially sequenced from R4, 88 per cent (61/69) showed identity to Rib; the r4 nucleotide sequence was identical to that of rib. All isolates with strong positive protein reactions for R4 were positive in both PCR and Southern technique, whereas isolates expressing alpha, beta, R1/R4, and R5 (BPS) protein profiles were not. Sequenced PCR products aligned with identity to the R4 and Rib nucleotide sequences and confirmed the identity of these proteins and their molecular sequences.

Confetti: A Multiprotease Map of the HeLa Proteome for Comprehensive Proteomics*

PubMed Central

Guo, Xiaofeng; Trudgian, David C.; Lemoff, Andrew; Yadavalli, Sivaramakrishna; Mirzaei, Hamid

2014-01-01

Bottom-up proteomics largely relies on tryptic peptides for protein identification and quantification. Tryptic digestion often provides limited coverage of protein sequence because of issues such as peptide length, ionization efficiency, and post-translational modification colocalization. Unfortunately, a region of interest in a protein, for example, because of proximity to an active site or the presence of important post-translational modifications, may not be covered by tryptic peptides. Detection limits, quantification accuracy, and isoform differentiation can also be improved with greater sequence coverage. Selected reaction monitoring (SRM) would also greatly benefit from being able to identify additional targetable sequences. In an attempt to improve protein sequence coverage and to target regions of proteins that do not generate useful tryptic peptides, we deployed a multiprotease strategy on the HeLa proteome. First, we used seven commercially available enzymes in single, double, and triple enzyme combinations. A total of 48 digests were performed. 5223 proteins were detected by analyzing the unfractionated cell lysate digest directly; with 42% mean sequence coverage. Additional strong-anion exchange fractionation of the most complementary digests permitted identification of over 3000 more proteins, with improved mean sequence coverage. We then constructed a web application (https://proteomics.swmed.edu/confetti) that allows the community to examine a target protein or protein isoform in order to discover the enzyme or combination of enzymes that would yield peptides spanning a certain region of interest in the sequence. Finally, we examined the use of nontryptic digests for SRM. From our strong-anion exchange fractionation data, we were able to identify three or more proteotypic SRM candidates within a single digest for 6056 genes. Surprisingly, in 25% of these cases the digest producing the most observable proteotypic peptides was neither trypsin nor Lys-C. SRM analysis of Asp-N versus tryptic peptides for eight proteins determined that Asp-N yielded higher signal in five of eight cases. PMID:24696503

Molecular cloning, sequence characterization and recombinant expression of Nanog gene in goat fibroblast cells using lentiviral based expression system.

PubMed

Singhal, Dinesh K; Singhal, Raxita; Malik, Hruda N; Kumar, Surender; Kumar, Sudarshan; Mohanty, Ashok K; Kaushik, Jai K; Malakar, Dhruba

2014-01-01

Nanog is a homeodomain containing protein which plays important roles in regulation of signaling pathways for maintenance and induction of pluripotency in stem cells. Because of its unique expression in stem cells it is also regarded as pluripotency marker. In this study goat Nanog (gNanog) gene has been amplified, cloned and characterized at sequence level with successful over-expression in CHO-K1 cell line using a lentiviral based system. gNanog ORF is 903 bp long which codes for Nanog protein of size 300 amino acids (aas). Complete nucleotide sequence shows some evolutionary mutation in goat in comparision to other species. Protein sequence of goat is highly similar to other species. Overall, gNanog nucleotide sequence and predicted protein sequence showed high similarity and minimum divergence with cattle (96 % identity/4 % divergence) and buffalo (94/5 %) while low similarity and high divergence with pig (84/15 %), human (81/23 %) and mouse (69/40 %) indicating evolutionary closeness of gNanog to cattle and buffalo. gNanog lentiviral expression construct was prepared for over-expression of Nanog gene in adult goat fibroblast cells. Lentiviral expression construct of Nanog enabled continuous protein expression for induction and maintenance of pluripotency. Western blotting revealed the expression of Nanog gene at protein level which supported that the lentiviral expression system is highly promising for Nanog protein expression in differentiated goat cell.

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

PubMed Central

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

2015-01-01

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

Proteomics analysis of "Rovabiot Excel", a secreted protein cocktail from the filamentous fungus Penicillium funiculosum grown under industrial process fermentation.

PubMed

Guais, Olivier; Borderies, Gisèle; Pichereaux, Carole; Maestracci, Marc; Neugnot, Virginie; Rossignol, Michel; François, Jean Marie

2008-12-01

MS/MS techniques are well customized now for proteomic analysis, even for non-sequenced organisms, since peptide sequences obtained by these methods can be matched with those found in databases from closely related sequenced organisms. We used this approach to characterize the protein content of the "Rovabio Excel", an enzymatic cocktail produced by Penicillium funiculosum that is used as feed additive in animal nutrition. Protein separation by bi-dimensional electrophoresis yielded more than 100 spots, from which 37 proteins were unambiguously assigned from peptide sequences. By one-dimensional SDS-gel electrophoresis, 34 proteins were identified among which 8 were not found in the 2-DE analysis. A third method, termed 'peptidic shotgun', which consists in a direct treatment of the cocktail by trypsin followed by separation of the peptides on two-dimensional liquid chromatography, resulted in the identification of two additional proteins not found by the two other methods. Altogether, more than 50 proteins, among which several glycosylhydrolytic, hemicellulolytic and proteolytic enzymes, were identified by combining three separation methods in this enzymatic cocktail. This work confirmed the power of proteome analysis to explore the genome expression of a non-sequenced fungus by taking advantage of sequences from phylogenetically related filamentous fungi and pave the way for further functional analysis of P. funiculosum.

Structure-related statistical singularities along protein sequences: a correlation study.

PubMed

Colafranceschi, Mauro; Colosimo, Alfredo; Zbilut, Joseph P; Uversky, Vladimir N; Giuliani, Alessandro

2005-01-01

A data set composed of 1141 proteins representative of all eukaryotic protein sequences in the Swiss-Prot Protein Knowledge base was coded by seven physicochemical properties of amino acid residues. The resulting numerical profiles were submitted to correlation analysis after the application of a linear (simple mean) and a nonlinear (Recurrence Quantification Analysis, RQA) filter. The main RQA variables, Recurrence and Determinism, were subsequently analyzed by Principal Component Analysis. The RQA descriptors showed that (i) within protein sequences is embedded specific information neither present in the codes nor in the amino acid composition and (ii) the most sensitive code for detecting ordered recurrent (deterministic) patterns of residues in protein sequences is the Miyazawa-Jernigan hydrophobicity scale. The most deterministic proteins in terms of autocorrelation properties of primary structures were found (i) to be involved in protein-protein and protein-DNA interactions and (ii) to display a significantly higher proportion of structural disorder with respect to the average data set. A study of the scaling behavior of the average determinism with the setting parameters of RQA (embedding dimension and radius) allows for the identification of patterns of minimal length (six residues) as possible markers of zones specifically prone to inter- and intramolecular interactions.

Patterns and plasticity in RNA-protein interactions enable recruitment of multiple proteins through a single site

DOE Office of Scientific and Technical Information (OSTI.GOV)

Valley, Cary T.; Porter, Douglas F.; Qiu, Chen

2012-06-28

mRNA control hinges on the specificity and affinity of proteins for their RNA binding sites. Regulatory proteins must bind their own sites and reject even closely related noncognate sites. In the PUF [Pumilio and fem-3 binding factor (FBF)] family of RNA binding proteins, individual proteins discriminate differences in the length and sequence of binding sites, allowing each PUF to bind a distinct battery of mRNAs. Here, we show that despite these differences, the pattern of RNA interactions is conserved among PUF proteins: the two ends of the PUF protein make critical contacts with the two ends of the RNA sites.more » Despite this conserved 'two-handed' pattern of recognition, the RNA sequence is flexible. Among the binding sites of yeast Puf4p, RNA sequence dictates the pattern in which RNA bases are flipped away from the binding surface of the protein. Small differences in RNA sequence allow new modes of control, recruiting Puf5p in addition to Puf4p to a single site. This embedded information adds a new layer of biological meaning to the connections between RNA targets and PUF proteins.« less

Isolation and in silico analysis of a novel H+-pyrophosphatase gene orthologue from the halophytic grass Leptochloa fusca

NASA Astrophysics Data System (ADS)

Rauf, Muhammad; Saeed, Nasir A.; Habib, Imran; Ahmed, Moddassir; Shahzad, Khurram; Mansoor, Shahid; Ali, Rashid

2017-02-01

Structure prediction can provide information about function and active sites of protein which helps to design new functional proteins. H+-pyrophosphatase is transmembrane protein involved in establishing proton motive force for active transport of Na+ across membrane by Na+/H+ antiporters. A full length novel H+-pyrophosphatase gene was isolated from halophytic grass Leptochloa fusca using RT-PCR and RACE method. Full length LfVP1 gene sequence of 2292 nucleotides encodes protein of 764 amino acids. DNA and protein sequences were used for characterization using bioinformatics tools. Various important potential sites were predicted by PROSITE webserver. Primary structural analysis showed LfVP1 as stable protein and Grand average hydropathy (GRAVY) indicated that LfVP1 protein has good hydrosolubility. Secondary structure analysis showed that LfVP1 protein sequence contains significant proportion of alpha helix and random coil. Protein membrane topology suggested the presence of 14 transmembrane domains and presence of catalytic domain in TM3. Three dimensional structure from LfVP1 protein sequence also indicated the presence of 14 transmembrane domains and hydrophobicity surface model showed amino acid hydrophobicity. Ramachandran plot showed that 98% amino acid residues were predicted in the favored region.

Structural classification of proteins using texture descriptors extracted from the cellular automata image.

PubMed

Kavianpour, Hamidreza; Vasighi, Mahdi

2017-02-01

Nowadays, having knowledge about cellular attributes of proteins has an important role in pharmacy, medical science and molecular biology. These attributes are closely correlated with the function and three-dimensional structure of proteins. Knowledge of protein structural class is used by various methods for better understanding the protein functionality and folding patterns. Computational methods and intelligence systems can have an important role in performing structural classification of proteins. Most of protein sequences are saved in databanks as characters and strings and a numerical representation is essential for applying machine learning methods. In this work, a binary representation of protein sequences is introduced based on reduced amino acids alphabets according to surrounding hydrophobicity index. Many important features which are hidden in these long binary sequences can be clearly displayed through their cellular automata images. The extracted features from these images are used to build a classification model by support vector machine. Comparing to previous studies on the several benchmark datasets, the promising classification rates obtained by tenfold cross-validation imply that the current approach can help in revealing some inherent features deeply hidden in protein sequences and improve the quality of predicting protein structural class.

Proteins without unique 3D structures: biotechnological applications of intrinsically unstable/disordered proteins.

PubMed

Uversky, Vladimir N

2015-03-01

Intrinsically disordered proteins (IDPs) and intrinsically disordered protein regions (IDPRs) are functional proteins or regions that do not have unique 3D structures under functional conditions. Therefore, from the viewpoint of their lack of stable 3D structure, IDPs/IDPRs are inherently unstable. As much as structure and function of normal ordered globular proteins are determined by their amino acid sequences, the lack of unique 3D structure in IDPs/IDPRs and their disorder-based functionality are also encoded in the amino acid sequences. Because of their specific sequence features and distinctive conformational behavior, these intrinsically unstable proteins or regions have several applications in biotechnology. This review introduces some of the most characteristic features of IDPs/IDPRs (such as peculiarities of amino acid sequences of these proteins and regions, their major structural features, and peculiar responses to changes in their environment) and describes how these features can be used in the biotechnology, for example for the proteome-wide analysis of the abundance of extended IDPs, for recombinant protein isolation and purification, as polypeptide nanoparticles for drug delivery, as solubilization tools, and as thermally sensitive carriers of active peptides and proteins. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Molecular Cloning and Characterization of Novel Morus alba Germin-Like Protein Gene Which Encodes for a Silkworm Gut Digestion-Resistant Antimicrobial Protein

PubMed Central

Patnaik, Bharat Bhusan; Kim, Dong Hyun; Oh, Seung Han; Song, Yong-Su; Chanh, Nguyen Dang Minh; Kim, Jong Sun; Jung, Woo-jin; Saha, Atul Kumar; Bindroo, Bharat Bhushan; Han, Yeon Soo

2012-01-01

Background Silkworm fecal matter is considered one of the richest sources of antimicrobial and antiviral protein (substances) and such economically feasible and eco-friendly proteins acting as secondary metabolites from the insect system can be explored for their practical utility in conferring broad spectrum disease resistance against pathogenic microbial specimens. Methodology/Principal Findings Silkworm fecal matter extracts prepared in 0.02 M phosphate buffer saline (pH 7.4), at a temperature of 60°C was subjected to 40% saturated ammonium sulphate precipitation and purified by gel-filtration chromatography (GFC). SDS-PAGE under denaturing conditions showed a single band at about 21.5 kDa. The peak fraction, thus obtained by GFC wastested for homogeneityusing C18reverse-phase high performance liquid chromatography (HPLC). The activity of the purified protein was tested against selected Gram +/− bacteria and phytopathogenic Fusarium species with concentration-dependent inhibitionrelationship. The purified bioactive protein was subjected to matrix-assisted laser desorption and ionization-time of flight mass spectrometry (MALDI-TOF-MS) and N-terminal sequencing by Edman degradation towards its identification. The N-terminal first 18 amino acid sequence following the predicted signal peptide showed homology to plant germin-like proteins (Glp). In order to characterize the full-length gene sequence in detail, the partial cDNA was cloned and sequenced using degenerate primers, followed by 5′- and 3′-rapid amplification of cDNA ends (RACE-PCR). The full-length cDNA sequence composed of 630 bp encoding 209 amino acids and corresponded to germin-like proteins (Glps) involved in plant development and defense. Conclusions/Significance The study reports, characterization of novel Glpbelonging to subfamily 3 from M. alba by the purification of mature active protein from silkworm fecal matter. The N-terminal amino acid sequence of the purified protein was found similar to the deduced amino acid sequence (without the transit peptide sequence) of the full length cDNA from M. alba. PMID:23284650

Mining sequential patterns for protein fold recognition.

PubMed

Exarchos, Themis P; Papaloukas, Costas; Lampros, Christos; Fotiadis, Dimitrios I

2008-02-01

Protein data contain discriminative patterns that can be used in many beneficial applications if they are defined correctly. In this work sequential pattern mining (SPM) is utilized for sequence-based fold recognition. Protein classification in terms of fold recognition plays an important role in computational protein analysis, since it can contribute to the determination of the function of a protein whose structure is unknown. Specifically, one of the most efficient SPM algorithms, cSPADE, is employed for the analysis of protein sequence. A classifier uses the extracted sequential patterns to classify proteins in the appropriate fold category. For training and evaluating the proposed method we used the protein sequences from the Protein Data Bank and the annotation of the SCOP database. The method exhibited an overall accuracy of 25% in a classification problem with 36 candidate categories. The classification performance reaches up to 56% when the five most probable protein folds are considered.

Biophysical models of protein evolution: Understanding the patterns of evolutionary sequence divergence

PubMed Central

Echave, Julian; Wilke, Claus O.

2018-01-01

For decades, rates of protein evolution have been interpreted in terms of the vague concept of “functional importance”. Slowly evolving proteins or sites within proteins were assumed to be more functionally important and thus subject to stronger selection pressure. More recently, biophysical models of protein evolution, which combine evolutionary theory with protein biophysics, have completely revolutionized our view of the forces that shape sequence divergence. Slowly evolving proteins have been found to evolve slowly because of selection against toxic misfolding and misinteractions, linking their rate of evolution primarily to their abundance. Similarly, most slowly evolving sites in proteins are not directly involved in function, but mutating them has large impacts on protein structure and stability. Here, we review the studies of the emergent field of biophysical protein evolution that have shaped our current understanding of sequence divergence patterns. We also propose future research directions to develop this nascent field. PMID:28301766

Automatic annotation of protein motif function with Gene Ontology terms.

PubMed

Lu, Xinghua; Zhai, Chengxiang; Gopalakrishnan, Vanathi; Buchanan, Bruce G

2004-09-02

Conserved protein sequence motifs are short stretches of amino acid sequence patterns that potentially encode the function of proteins. Several sequence pattern searching algorithms and programs exist foridentifying candidate protein motifs at the whole genome level. However, a much needed and important task is to determine the functions of the newly identified protein motifs. The Gene Ontology (GO) project is an endeavor to annotate the function of genes or protein sequences with terms from a dynamic, controlled vocabulary and these annotations serve well as a knowledge base. This paper presents methods to mine the GO knowledge base and use the association between the GO terms assigned to a sequence and the motifs matched by the same sequence as evidence for predicting the functions of novel protein motifs automatically. The task of assigning GO terms to protein motifs is viewed as both a binary classification and information retrieval problem, where PROSITE motifs are used as samples for mode training and functional prediction. The mutual information of a motif and aGO term association is found to be a very useful feature. We take advantage of the known motifs to train a logistic regression classifier, which allows us to combine mutual information with other frequency-based features and obtain a probability of correct association. The trained logistic regression model has intuitively meaningful and logically plausible parameter values, and performs very well empirically according to our evaluation criteria. In this research, different methods for automatic annotation of protein motifs have been investigated. Empirical result demonstrated that the methods have a great potential for detecting and augmenting information about the functions of newly discovered candidate protein motifs.

Molecular Design of Performance Proteins With Repetitive Sequences

NASA Astrophysics Data System (ADS)

Vendrely, Charlotte; Ackerschott, Christian; Römer, Lin; Scheibel, Thomas

Most performance proteins responsible for the mechanical stability of cells and organisms reveal highly repetitive sequences. Mimicking such performance proteins is of high interest for the design of nanostructured biomaterials. In this article, flagelliform silk is exemplary introduced to describe a general principle for designing genes of repetitive performance proteins for recombinant expression in Escherichia coli . In the first step, repeating amino acid sequence motifs are reversely transcripted into DNA cassettes, which can in a second step be seamlessly ligated, yielding a designed gene. Recombinant expression thereof leads to proteins mimicking the natural ones. The recombinant proteins can be assembled into nanostructured materials in a controlled manner, allowing their use in several applications.

Investigation of SnSPR1, a novel and abundant surface protein of Sarcocystis neurona merozoites.

PubMed

Zhang, Deqing; Howe, Daniel K

2008-04-15

An expressed sequence tag (EST) sequencing project has produced over 15,000 partial cDNA sequences from the equine pathogen Sarcocystis neurona. While many of the sequences are clear homologues of previously characterized genes, a significant number of the S. neurona ESTs do not exhibit similarity to anything in the extensive sequence databases that have been generated. In an effort to characterize parasite proteins that are novel to S. neurona, a seemingly unique gene was selected for further investigation based on its abundant representation in the collection of ESTs and the predicted presence of a signal peptide and glycolipid anchor addition on the encoded protein. The gene was expressed in E. coli, and monospecific polyclonal antiserum against the recombinant protein was produced by immunization of a rabbit. Characterization of the native protein in S. neurona merozoites and schizonts revealed that it is a low molecular weight surface protein that is expressed throughout intracellular development of the parasite. The protein was designated Surface Protein 1 (SPR1) to reflect its display on the outer surface of merozoites and to distinguish it from the ubiquitous SAG/SRS surface antigens of the heteroxenous Coccidia. Interestingly, infection assays in the presence of the polyclonal antiserum suggested that SnSPR1 plays some role in attachment and/or invasion of host cells by S. neurona merozoites. The work described herein represents a general template for selecting and characterizing the various unidentified gene sequences that are plentiful in the EST databases for S. neurona and other apicomplexans. Furthermore, this study illustrates the value of investigating these novel sequences since it can offer new candidates for diagnostic or vaccine development while also providing greater insight into the biology of these parasites.

The primary structures of ribosomal proteins S14 and S16 from the archaebacterium Halobacterium marismortui. Comparison with eubacterial and eukaryotic ribosomal proteins.

PubMed

Kimura, J; Kimura, M

1987-09-05

The amino acid sequences of two ribosomal proteins, S14 and S16, from the archaebacterium Halobacterium marismortui have been determined. Sequence data were obtained by the manual and solid-phase sequencing of peptides derived from enzymatic digestions with trypsin, chymotrypsin, pepsin, and Staphylococcus aureus protease as well as by chemical cleavage with cyanogen bromide. Proteins S14 and S16 contain 109 and 126 amino acid residues and have Mr values of 11,964 and 13,515, respectively. Comparison of the sequences with those of ribosomal proteins from other organisms demonstrates that S14 has a significant homology with the rat liver ribosomal protein S11 (36% identity) as well as with the Escherichia coli ribosomal protein S17 (37%), and that S16 is related to the yeast ribosomal protein YS22 (40%) and proteins S8 from E. coli (28%) and Bacillus stearothermophilus (30%). A comparison of the amino acid residues in the homologous regions of halophilic and nonhalophilic ribosomal proteins reveals that halophilic proteins have more glutamic acids, asparatic acids, prolines, and alanines, and less lysines, arginines, and isoleucines than their nonhalophilic counterparts. These amino acid substitutions probably contribute to the structural stability of halophilic ribosomal proteins.

Sequence specificity of single-stranded DNA-binding proteins: a novel DNA microarray approach

PubMed Central

Morgan, Hugh P.; Estibeiro, Peter; Wear, Martin A.; Max, Klaas E.A.; Heinemann, Udo; Cubeddu, Liza; Gallagher, Maurice P.; Sadler, Peter J.; Walkinshaw, Malcolm D.

2007-01-01

We have developed a novel DNA microarray-based approach for identification of the sequence-specificity of single-stranded nucleic-acid-binding proteins (SNABPs). For verification, we have shown that the major cold shock protein (CspB) from Bacillus subtilis binds with high affinity to pyrimidine-rich sequences, with a binding preference for the consensus sequence, 5′-GTCTTTG/T-3′. The sequence was modelled onto the known structure of CspB and a cytosine-binding pocket was identified, which explains the strong preference for a cytosine base at position 3. This microarray method offers a rapid high-throughput approach for determining the specificity and strength of ss DNA–protein interactions. Further screening of this newly emerging family of transcription factors will help provide an insight into their cellular function. PMID:17488853

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

PubMed

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.

Identification of DNA-binding proteins by combining auto-cross covariance transformation and ensemble learning.

PubMed

Liu, Bin; Wang, Shanyi; Dong, Qiwen; Li, Shumin; Liu, Xuan

2016-04-20

DNA-binding proteins play a pivotal role in various intra- and extra-cellular activities ranging from DNA replication to gene expression control. With the rapid development of next generation of sequencing technique, the number of protein sequences is unprecedentedly increasing. Thus it is necessary to develop computational methods to identify the DNA-binding proteins only based on the protein sequence information. In this study, a novel method called iDNA-KACC is presented, which combines the Support Vector Machine (SVM) and the auto-cross covariance transformation. The protein sequences are first converted into profile-based protein representation, and then converted into a series of fixed-length vectors by the auto-cross covariance transformation with Kmer composition. The sequence order effect can be effectively captured by this scheme. These vectors are then fed into Support Vector Machine (SVM) to discriminate the DNA-binding proteins from the non DNA-binding ones. iDNA-KACC achieves an overall accuracy of 75.16% and Matthew correlation coefficient of 0.5 by a rigorous jackknife test. Its performance is further improved by employing an ensemble learning approach, and the improved predictor is called iDNA-KACC-EL. Experimental results on an independent dataset shows that iDNA-KACC-EL outperforms all the other state-of-the-art predictors, indicating that it would be a useful computational tool for DNA binding protein identification. .

Saccharomyces cerevisiae SSB1 protein and its relationship to nucleolar RNA-binding proteins.

PubMed Central

Jong, A Y; Clark, M W; Gilbert, M; Oehm, A; Campbell, J L

1987-01-01

To better define the function of Saccharomyces cerevisiae SSB1, an abundant single-stranded nucleic acid-binding protein, we determined the nucleotide sequence of the SSB1 gene and compared it with those of other proteins of known function. The amino acid sequence contains 293 amino acid residues and has an Mr of 32,853. There are several stretches of sequence characteristic of other eucaryotic single-stranded nucleic acid-binding proteins. At the amino terminus, residues 39 to 54 are highly homologous to a peptide in calf thymus UP1 and UP2 and a human heterogeneous nuclear ribonucleoprotein. Residues 125 to 162 constitute a fivefold tandem repeat of the sequence RGGFRG, the composition of which suggests a nucleic acid-binding site. Near the C terminus, residues 233 to 245 are homologous to several RNA-binding proteins. Of 18 C-terminal residues, 10 are acidic, a characteristic of the procaryotic single-stranded DNA-binding proteins and eucaryotic DNA- and RNA-binding proteins. In addition, examination of the subcellular distribution of SSB1 by immunofluorescence microscopy indicated that SSB1 is a nuclear protein, predominantly located in the nucleolus. Sequence homologies and the nucleolar localization make it likely that SSB1 functions in RNA metabolism in vivo, although an additional role in DNA metabolism cannot be excluded. Images PMID:2823109

A novel alignment-free method to classify protein folding types by combining spectral graph clustering with Chou's pseudo amino acid composition.

PubMed

Tripathi, Pooja; Pandey, Paras N

2017-07-07

The present work employs pseudo amino acid composition (PseAAC) for encoding the protein sequences in their numeric form. Later this will be arranged in the similarity matrix, which serves as input for spectral graph clustering method. Spectral methods are used previously also for clustering of protein sequences, but they uses pair wise alignment scores of protein sequences, in similarity matrix. The alignment score depends on the length of sequences, so clustering short and long sequences together may not good idea. Therefore the idea of introducing PseAAC with spectral clustering algorithm came into scene. We extensively tested our method and compared its performance with other existing machine learning methods. It is consistently observed that, the number of clusters that we obtained for a given set of proteins is close to the number of superfamilies in that set and PseAAC combined with spectral graph clustering shows the best classification results. Copyright © 2017 Elsevier Ltd. All rights reserved.

DNA Multiple Sequence Alignment Guided by Protein Domains: The MSA-PAD 2.0 Method.

PubMed

Balech, Bachir; Monaco, Alfonso; Perniola, Michele; Santamaria, Monica; Donvito, Giacinto; Vicario, Saverio; Maggi, Giorgio; Pesole, Graziano

2018-01-01

Multiple sequence alignment (MSA) is a fundamental component in many DNA sequence analyses including metagenomics studies and phylogeny inference. When guided by protein profiles, DNA multiple alignments assume a higher precision and robustness. Here we present details of the use of the upgraded version of MSA-PAD (2.0), which is a DNA multiple sequence alignment framework able to align DNA sequences coding for single/multiple protein domains guided by PFAM or user-defined annotations. MSA-PAD has two alignment strategies, called "Gene" and "Genome," accounting for coding domains order and genomic rearrangements, respectively. Novel options were added to the present version, where the MSA can be guided by protein profiles provided by the user. This allows MSA-PAD 2.0 to run faster and to add custom protein profiles sometimes not present in PFAM database according to the user's interest. MSA-PAD 2.0 is currently freely available as a Web application at https://recasgateway.cloud.ba.infn.it/ .

Automated design evolution of stereochemically randomized protein foldamers

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

Sites Inferred by Metabolic Background Assertion Labeling (SIMBAL): adapting the Partial Phylogenetic Profiling algorithm to scan sequences for signatures that predict protein function

PubMed Central

2010-01-01

Background Comparative genomics methods such as phylogenetic profiling can mine powerful inferences from inherently noisy biological data sets. We introduce Sites Inferred by Metabolic Background Assertion Labeling (SIMBAL), a method that applies the Partial Phylogenetic Profiling (PPP) approach locally within a protein sequence to discover short sequence signatures associated with functional sites. The approach is based on the basic scoring mechanism employed by PPP, namely the use of binomial distribution statistics to optimize sequence similarity cutoffs during searches of partitioned training sets. Results Here we illustrate and validate the ability of the SIMBAL method to find functionally relevant short sequence signatures by application to two well-characterized protein families. In the first example, we partitioned a family of ABC permeases using a metabolic background property (urea utilization). Thus, the TRUE set for this family comprised members whose genome of origin encoded a urea utilization system. By moving a sliding window across the sequence of a permease, and searching each subsequence in turn against the full set of partitioned proteins, the method found which local sequence signatures best correlated with the urea utilization trait. Mapping of SIMBAL "hot spots" onto crystal structures of homologous permeases reveals that the significant sites are gating determinants on the cytosolic face rather than, say, docking sites for the substrate-binding protein on the extracellular face. In the second example, we partitioned a protein methyltransferase family using gene proximity as a criterion. In this case, the TRUE set comprised those methyltransferases encoded near the gene for the substrate RF-1. SIMBAL identifies sequence regions that map onto the substrate-binding interface while ignoring regions involved in the methyltransferase reaction mechanism in general. Neither method for training set construction requires any prior experimental characterization. Conclusions SIMBAL shows that, in functionally divergent protein families, selected short sequences often significantly outperform their full-length parent sequence for making functional predictions by sequence similarity, suggesting avenues for improved functional classifiers. When combined with structural data, SIMBAL affords the ability to localize and model functional sites. PMID:20102603

Successful Recovery of Nuclear Protein-Coding Genes from Small Insects in Museums Using Illumina Sequencing.

PubMed

Kanda, Kojun; Pflug, James M; Sproul, John S; Dasenko, Mark A; Maddison, David R

2015-01-01

In this paper we explore high-throughput Illumina sequencing of nuclear protein-coding, ribosomal, and mitochondrial genes in small, dried insects stored in natural history collections. We sequenced one tenebrionid beetle and 12 carabid beetles ranging in size from 3.7 to 9.7 mm in length that have been stored in various museums for 4 to 84 years. Although we chose a number of old, small specimens for which we expected low sequence recovery, we successfully recovered at least some low-copy nuclear protein-coding genes from all specimens. For example, in one 56-year-old beetle, 4.4 mm in length, our de novo assembly recovered about 63% of approximately 41,900 nucleotides in a target suite of 67 nuclear protein-coding gene fragments, and 70% using a reference-based assembly. Even in the least successfully sequenced carabid specimen, reference-based assembly yielded fragments that were at least 50% of the target length for 34 of 67 nuclear protein-coding gene fragments. Exploration of alternative references for reference-based assembly revealed few signs of bias created by the reference. For all specimens we recovered almost complete copies of ribosomal and mitochondrial genes. We verified the general accuracy of the sequences through comparisons with sequences obtained from PCR and Sanger sequencing, including of conspecific, fresh specimens, and through phylogenetic analysis that tested the placement of sequences in predicted regions. A few possible inaccuracies in the sequences were detected, but these rarely affected the phylogenetic placement of the samples. Although our sample sizes are low, an exploratory regression study suggests that the dominant factor in predicting success at recovering nuclear protein-coding genes is a high number of Illumina reads, with success at PCR of COI and killing by immersion in ethanol being secondary factors; in analyses of only high-read samples, the primary significant explanatory variable was body length, with small beetles being more successfully sequenced.

Successful Recovery of Nuclear Protein-Coding Genes from Small Insects in Museums Using Illumina Sequencing

PubMed Central

Dasenko, Mark A.

2015-01-01

In this paper we explore high-throughput Illumina sequencing of nuclear protein-coding, ribosomal, and mitochondrial genes in small, dried insects stored in natural history collections. We sequenced one tenebrionid beetle and 12 carabid beetles ranging in size from 3.7 to 9.7 mm in length that have been stored in various museums for 4 to 84 years. Although we chose a number of old, small specimens for which we expected low sequence recovery, we successfully recovered at least some low-copy nuclear protein-coding genes from all specimens. For example, in one 56-year-old beetle, 4.4 mm in length, our de novo assembly recovered about 63% of approximately 41,900 nucleotides in a target suite of 67 nuclear protein-coding gene fragments, and 70% using a reference-based assembly. Even in the least successfully sequenced carabid specimen, reference-based assembly yielded fragments that were at least 50% of the target length for 34 of 67 nuclear protein-coding gene fragments. Exploration of alternative references for reference-based assembly revealed few signs of bias created by the reference. For all specimens we recovered almost complete copies of ribosomal and mitochondrial genes. We verified the general accuracy of the sequences through comparisons with sequences obtained from PCR and Sanger sequencing, including of conspecific, fresh specimens, and through phylogenetic analysis that tested the placement of sequences in predicted regions. A few possible inaccuracies in the sequences were detected, but these rarely affected the phylogenetic placement of the samples. Although our sample sizes are low, an exploratory regression study suggests that the dominant factor in predicting success at recovering nuclear protein-coding genes is a high number of Illumina reads, with success at PCR of COI and killing by immersion in ethanol being secondary factors; in analyses of only high-read samples, the primary significant explanatory variable was body length, with small beetles being more successfully sequenced. PMID:26716693

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.

PubMed

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.

The FOXP2 forkhead domain binds to a variety of DNA sequences with different rates and affinities.

PubMed

Webb, Helen; Steeb, Olga; Blane, Ashleigh; Rotherham, Lia; Aron, Shaun; Machanick, Philip; Dirr, Heini; Fanucchi, Sylvia

2017-07-01

FOXP2 is a member of the P subfamily of FOX transcription factors, the DNA-binding domain of which is the winged helix forkhead domain (FHD). In this work we show that the FOXP2 FHD is able to bind to various DNA sequences, including a novel sequence identified in this work, with different affinities and rates as detected using surface plasmon resonance. Combining the experimental work with molecular docking, we show that high-affinity sequences remain bound to the protein for longer, form a greater number of interactions with the protein and induce a greater structural change in the protein than low-affinity sequences. We propose a binding model for the FOXP2 FHD that involves three types of binding sequence: low affinity sites which allow for rapid scanning of the genome by the protein in a partially unstructured state; moderate affinity sites which serve to locate the protein near target sites and high-affinity sites which secure the protein to the DNA and induce a conformational change necessary for functional binding and the possible initiation of downstream transcriptional events. © The Authors 2017. Published by Oxford University Press on behalf of the Japanese Biochemical Society. All rights reserved.

GeneSilico protein structure prediction meta-server.

PubMed

Kurowski, Michal A; Bujnicki, Janusz M

2003-07-01

Rigorous assessments of protein structure prediction have demonstrated that fold recognition methods can identify remote similarities between proteins when standard sequence search methods fail. It has been shown that the accuracy of predictions is improved when refined multiple sequence alignments are used instead of single sequences and if different methods are combined to generate a consensus model. There are several meta-servers available that integrate protein structure predictions performed by various methods, but they do not allow for submission of user-defined multiple sequence alignments and they seldom offer confidentiality of the results. We developed a novel WWW gateway for protein structure prediction, which combines the useful features of other meta-servers available, but with much greater flexibility of the input. The user may submit an amino acid sequence or a multiple sequence alignment to a set of methods for primary, secondary and tertiary structure prediction. Fold-recognition results (target-template alignments) are converted into full-atom 3D models and the quality of these models is uniformly assessed. A consensus between different FR methods is also inferred. The results are conveniently presented on-line on a single web page over a secure, password-protected connection. The GeneSilico protein structure prediction meta-server is freely available for academic users at http://genesilico.pl/meta.

GeneSilico protein structure prediction meta-server

PubMed Central

Kurowski, Michal A.; Bujnicki, Janusz M.

2003-01-01

Rigorous assessments of protein structure prediction have demonstrated that fold recognition methods can identify remote similarities between proteins when standard sequence search methods fail. It has been shown that the accuracy of predictions is improved when refined multiple sequence alignments are used instead of single sequences and if different methods are combined to generate a consensus model. There are several meta-servers available that integrate protein structure predictions performed by various methods, but they do not allow for submission of user-defined multiple sequence alignments and they seldom offer confidentiality of the results. We developed a novel WWW gateway for protein structure prediction, which combines the useful features of other meta-servers available, but with much greater flexibility of the input. The user may submit an amino acid sequence or a multiple sequence alignment to a set of methods for primary, secondary and tertiary structure prediction. Fold-recognition results (target-template alignments) are converted into full-atom 3D models and the quality of these models is uniformly assessed. A consensus between different FR methods is also inferred. The results are conveniently presented on-line on a single web page over a secure, password-protected connection. The GeneSilico protein structure prediction meta-server is freely available for academic users at http://genesilico.pl/meta. PMID:12824313

Characterization of a novel wheat endosperm protein belonging to the prolamin superfamily

USDA-ARS?s Scientific Manuscript database

Starch granule surface-associated proteins were separated by HPLC and identified by direct protein sequencing. Among the proteins identified was one that consisted of two polypeptide chains of 11 kDa and 19 kDa linked by disulfide bonds. Sequencing of tryptic peptides from each of the polypeptide ch...

Predicting protein crystallization propensity from protein sequence

PubMed Central

2011-01-01

The high-throughput structure determination pipelines developed by structural genomics programs offer a unique opportunity for data mining. One important question is how protein properties derived from a primary sequence correlate with the protein’s propensity to yield X-ray quality crystals (crystallizability) and 3D X-ray structures. A set of protein properties were computed for over 1,300 proteins that expressed well but were insoluble, and for ~720 unique proteins that resulted in X-ray structures. The correlation of the protein’s iso-electric point and grand average hydropathy (GRAVY) with crystallizability was analyzed for full length and domain constructs of protein targets. In a second step, several additional properties that can be calculated from the protein sequence were added and evaluated. Using statistical analyses we have identified a set of the attributes correlating with a protein’s propensity to crystallize and implemented a Support Vector Machine (SVM) classifier based on these. We have created applications to analyze and provide optimal boundary information for query sequences and to visualize the data. These tools are available via the web site http://bioinformatics.anl.gov/cgi-bin/tools/pdpredictor. PMID:20177794

Exploiting three kinds of interface propensities to identify protein binding sites.

PubMed

Liu, Bin; Wang, Xiaolong; Lin, Lei; Dong, Qiwen; Wang, Xuan

2009-08-01

Predicting the binding sites between two interacting proteins provides important clues to the function of a protein. In this study, we present a building block of proteins called order profiles to use the evolutionary information of the protein sequence frequency profiles and apply this building block to produce a class of propensities called order profile interface propensities. For comparisons, we revisit the usage of residue interface propensities and binary profile interface propensities for protein binding site prediction. Each kind of propensities combined with sequence profiles and accessible surface areas are inputted into SVM. When tested on four types of complexes (hetero-permanent complexes, hetero-transient complexes, homo-permanent complexes and homo-transient complexes), experimental results show that the order profile interface propensities are better than residue interface propensities and binary profile interface propensities. Therefore, order profile is a suitable profile-level building block of the protein sequences and can be widely used in many tasks of computational biology, such as the sequence alignment, the prediction of domain boundary, the designation of knowledge-based potentials and the protein remote homology detection.

Nucleotide sequence of the gene for the Mr 32,000 thylakoid membrane protein from Spinacia oleracea and Nicotiana debneyi predicts a totally conserved primary translation product of Mr 38,950

PubMed Central

Zurawski, Gerard; Bohnert, Hans J.; Whitfeld, Paul R.; Bottomley, Warwick

1982-01-01

The gene for the so-called Mr 32,000 rapidly labeled photosystem II thylakoid membrane protein (here designated psbA) of spinach (Spinacia oleracea) chloroplasts is located on the chloroplast DNA in the large single-copy region immediately adjacent to one of the inverted repeat sequences. In this paper we show that the size of the mRNA for this protein is ≈ 1.25 kilobases and that the direction of transcription is towards the inverted repeat unit. The nucleotide sequence of the gene and its flanking regions is presented. The only large open reading frame in the sequence codes for a protein of Mr 38,950. The nucleotide sequence of psbA from Nicotiana debneyi also has been determined, and comparison of the sequences from the two species shows them to be highly conserved (>95% homology) throughout the entire reading frame. Conservation of the amino acid sequence is absolute, there being no changes in a total of 353 residues. This leads us to conclude that the primary translation product of psbA must be a protein of Mr 38,950. The protein is characterized by the complete absence of lysine residues and is relatively rich in hydrophobic amino acids, which tend to be clustered. Transcription of spinach psbA starts about 86 base pairs before the first ATG codon. Immediately upstream from this point there is a sequence typical of that found in E. coli promoters. An almost identical sequence occurs in the equivalent region of N. debneyi DNA. Images PMID:16593262

A theoretical method to compute sequence dependent configurational properties in charged polymers and proteins.

PubMed

Sawle, Lucas; Ghosh, Kingshuk

2015-08-28

A general formalism to compute configurational properties of proteins and other heteropolymers with an arbitrary sequence of charges and non-uniform excluded volume interaction is presented. A variational approach is utilized to predict average distance between any two monomers in the chain. The presented analytical model, for the first time, explicitly incorporates the role of sequence charge distribution to determine relative sizes between two sequences that vary not only in total charge composition but also in charge decoration (even when charge composition is fixed). Furthermore, the formalism is general enough to allow variation in excluded volume interactions between two monomers. Model predictions are benchmarked against the all-atom Monte Carlo studies of Das and Pappu [Proc. Natl. Acad. Sci. U. S. A. 110, 13392 (2013)] for 30 different synthetic sequences of polyampholytes. These sequences possess an equal number of glutamic acid (E) and lysine (K) residues but differ in the patterning within the sequence. Without any fit parameter, the model captures the strong sequence dependence of the simulated values of the radius of gyration with a correlation coefficient of R(2) = 0.9. The model is then applied to real proteins to compare the unfolded state dimensions of 540 orthologous pairs of thermophilic and mesophilic proteins. The excluded volume parameters are assumed similar under denatured conditions, and only electrostatic effects encoded in the sequence are accounted for. With these assumptions, thermophilic proteins are found-with high statistical significance-to have more compact disordered ensemble compared to their mesophilic counterparts. The method presented here, due to its analytical nature, is capable of making such high throughput analysis of multiple proteins and will have broad applications in proteomic studies as well as in other heteropolymeric systems.

Protein Sequence Annotation Tool (PSAT): A centralized web-based meta-server for high-throughput sequence annotations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leung, Elo; Huang, Amy; Cadag, Eithon

In this study, we introduce the Protein Sequence Annotation Tool (PSAT), a web-based, sequence annotation meta-server for performing integrated, high-throughput, genome-wide sequence analyses. Our goals in building PSAT were to (1) create an extensible platform for integration of multiple sequence-based bioinformatics tools, (2) enable functional annotations and enzyme predictions over large input protein fasta data sets, and (3) provide a web interface for convenient execution of the tools. In this paper, we demonstrate the utility of PSAT by annotating the predicted peptide gene products of Herbaspirillum sp. strain RV1423, importing the results of PSAT into EC2KEGG, and using the resultingmore » functional comparisons to identify a putative catabolic pathway, thereby distinguishing RV1423 from a well annotated Herbaspirillum species. This analysis demonstrates that high-throughput enzyme predictions, provided by PSAT processing, can be used to identify metabolic potential in an otherwise poorly annotated genome. Lastly, PSAT is a meta server that combines the results from several sequence-based annotation and function prediction codes, and is available at http://psat.llnl.gov/psat/. PSAT stands apart from other sequencebased genome annotation systems in providing a high-throughput platform for rapid de novo enzyme predictions and sequence annotations over large input protein sequence data sets in FASTA. PSAT is most appropriately applied in annotation of large protein FASTA sets that may or may not be associated with a single genome.« less

Protein Sequence Annotation Tool (PSAT): A centralized web-based meta-server for high-throughput sequence annotations

DOE PAGES

Leung, Elo; Huang, Amy; Cadag, Eithon; ...

2016-01-20

In this study, we introduce the Protein Sequence Annotation Tool (PSAT), a web-based, sequence annotation meta-server for performing integrated, high-throughput, genome-wide sequence analyses. Our goals in building PSAT were to (1) create an extensible platform for integration of multiple sequence-based bioinformatics tools, (2) enable functional annotations and enzyme predictions over large input protein fasta data sets, and (3) provide a web interface for convenient execution of the tools. In this paper, we demonstrate the utility of PSAT by annotating the predicted peptide gene products of Herbaspirillum sp. strain RV1423, importing the results of PSAT into EC2KEGG, and using the resultingmore » functional comparisons to identify a putative catabolic pathway, thereby distinguishing RV1423 from a well annotated Herbaspirillum species. This analysis demonstrates that high-throughput enzyme predictions, provided by PSAT processing, can be used to identify metabolic potential in an otherwise poorly annotated genome. Lastly, PSAT is a meta server that combines the results from several sequence-based annotation and function prediction codes, and is available at http://psat.llnl.gov/psat/. PSAT stands apart from other sequencebased genome annotation systems in providing a high-throughput platform for rapid de novo enzyme predictions and sequence annotations over large input protein sequence data sets in FASTA. PSAT is most appropriately applied in annotation of large protein FASTA sets that may or may not be associated with a single genome.« less

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

PubMed

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.

Complementary DNA sequencing and identification of mRNAs from the venomous gland of Agkistrodon piscivorus leucostoma.

PubMed

Jia, Ying; Cantu, Bruno A; Sánchez, Elda E; Pérez, John C

2008-06-15

To advance our knowledge on the snake venom composition and transcripts expressed in venom gland at the molecular level, we constructed a cDNA library from the venom gland of Agkistrodon piscivorus leucostoma for the generation of expressed sequence tags (ESTs) database. From the randomly sequenced 2112 independent clones, we have obtained ESTs for 1309 (62%) cDNAs, which showed significant deduced amino acid sequence similarity (scores >80) to previously characterized proteins in National Center for Biotechnology Information (NCBI) database. Ribosomal proteins make up 47 clones (2%) and the remaining 756 (36%) cDNAs represent either unknown identity or show BLASTX sequence identity scores of <80 with known GenBank accessions. The most highly expressed gene encoding phospholipase A(2) (PLA(2)) accounting for 35% of A. p. leucostoma venom gland cDNAs was identified and further confirmed by crude venom applied to sodium dodecyl sulfate/polyacrylamide gel electrophoresis (SDS-PAGE) electrophoresis and protein sequencing. A total of 180 representative genes were obtained from the sequence assemblies and deposited to EST database. Clones showing sequence identity to disintegrins, thrombin-like enzymes, hemorrhagic toxins, fibrinogen clotting inhibitors and plasminogen activators were also identified in our EST database. These data can be used to develop a research program that will help us identify genes encoding proteins that are of medical importance or proteins involved in the mechanisms of the toxin venom.

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

PubMed

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.

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

PubMed

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.

From non-random molecular structure to life and mind

NASA Technical Reports Server (NTRS)

Fox, S. W.

1989-01-01

The evolutionary hierarchy molecular structure-->macromolecular structure-->protobiological structure-->biological structure-->biological functions has been traced by experiments. The sequence always moves through protein. Extension of the experiments traces the formation of nucleic acids instructed by proteins. The proteins themselves were, in this picture, instructed by the self-sequencing of precursor amino acids. While the sequence indicated explains the thread of the emergence of life, protein in cellular membrane also provides the only known material basis for the emergence of mind in the context of emergence of life.

Refining the Results of a Classical SELEX Experiment by Expanding the Sequence Data Set of an Aptamer Pool Selected for Protein A

PubMed Central

2018-01-01

New, as yet undiscovered aptamers for Protein A were identified by applying next generation sequencing (NGS) to a previously selected aptamer pool. This pool was obtained in a classical SELEX (Systematic Evolution of Ligands by EXponential enrichment) experiment using the FluMag-SELEX procedure followed by cloning and Sanger sequencing. PA#2/8 was identified as the only Protein A-binding aptamer from the Sanger sequence pool, and was shown to be able to bind intact cells of Staphylococcus aureus. In this study, we show the extension of the SELEX results by re-sequencing of the same aptamer pool using a medium throughput NGS approach and data analysis. Both data pools were compared. They confirm the selection of a highly complex and heterogeneous oligonucleotide pool and show consistently a high content of orphans as well as a similar relative frequency of certain sequence groups. But in contrast to the Sanger data pool, the NGS pool was clearly dominated by one sequence group containing the known Protein A-binding aptamer PA#2/8 as the most frequent sequence in this group. In addition, we found two new sequence groups in the NGS pool represented by PA-C10 and PA-C8, respectively, which also have high specificity for Protein A. Comparative affinity studies reveal differences between the aptamers and confirm that PA#2/8 remains the most potent sequence within the selected aptamer pool reaching affinities in the low nanomolar range of KD = 20 ± 1 nM. PMID:29495282

Refining the Results of a Classical SELEX Experiment by Expanding the Sequence Data Set of an Aptamer Pool Selected for Protein A.

PubMed

Stoltenburg, Regina; Strehlitz, Beate

2018-02-24

New, as yet undiscovered aptamers for Protein A were identified by applying next generation sequencing (NGS) to a previously selected aptamer pool. This pool was obtained in a classical SELEX (Systematic Evolution of Ligands by EXponential enrichment) experiment using the FluMag-SELEX procedure followed by cloning and Sanger sequencing. PA#2/8 was identified as the only Protein A-binding aptamer from the Sanger sequence pool, and was shown to be able to bind intact cells of Staphylococcus aureus . In this study, we show the extension of the SELEX results by re-sequencing of the same aptamer pool using a medium throughput NGS approach and data analysis. Both data pools were compared. They confirm the selection of a highly complex and heterogeneous oligonucleotide pool and show consistently a high content of orphans as well as a similar relative frequency of certain sequence groups. But in contrast to the Sanger data pool, the NGS pool was clearly dominated by one sequence group containing the known Protein A-binding aptamer PA#2/8 as the most frequent sequence in this group. In addition, we found two new sequence groups in the NGS pool represented by PA-C10 and PA-C8, respectively, which also have high specificity for Protein A. Comparative affinity studies reveal differences between the aptamers and confirm that PA#2/8 remains the most potent sequence within the selected aptamer pool reaching affinities in the low nanomolar range of K D = 20 ± 1 nM.

Informational structure of genetic sequences and nature of gene splicing

NASA Astrophysics Data System (ADS)

Trifonov, E. N.

1991-10-01

Only about 1/20 of DNA of higher organisms codes for proteins, by means of classical triplet code. The rest of DNA sequences is largely silent, with unclear functions, if any. The triplet code is not the only code (message) carried by the sequences. There are three levels of molecular communication, where the same sequence ``talks'' to various bimolecules, while having, respectively, three different appearances: DNA, RNA and protein. Since the molecular structures and, hence, sequence specific preferences of these are substantially different, the original DNA sequence has to carry simultaneously three types of sequence patterns (codes, messages), thus, being a composite structure in which one had the same letter (nucleotide) is frequently involved in several overlapping codes of different nature. This multiplicity and overlapping of the codes is a unique feature of the Gnomic, language of genetic sequences. The coexisting codes have to be degenerate in various degrees to allow an optimal and concerted performance of all the encoded functions. There is an obvious conflict between the best possible performance of a given function and necessity to compromise the quality of a given sequence pattern in favor of other patterns. It appears that the major role of various changes in the sequences on their ``ontogenetic'' way from DNA to RNA to protein, like RNA editing and splicing, or protein post-translational modifications is to resolve such conflicts. New data are presented strongly indicating that the gene splicing is such a device to resolve the conflict between the code of DNA folding in chromatin and the triplet code for protein synthesis.

Sialome of a Generalist Lepidopteran Herbivore: Identification of Transcripts and Proteins from Helicoverpa armigera Labial Salivary Glands

PubMed Central

Celorio-Mancera, Maria de la Paz; Courtiade, Juliette; Muck, Alexander; Heckel, David G.; Musser, Richard O.; Vogel, Heiko

2011-01-01

Although the importance of insect saliva in insect-host plant interactions has been acknowledged, there is very limited information on the nature and complexity of the salivary proteome in lepidopteran herbivores. We inspected the labial salivary transcriptome and proteome of Helicoverpa armigera, an important polyphagous pest species. To identify the majority of the salivary proteins we have randomly sequenced 19,389 expressed sequence tags (ESTs) from a normalized cDNA library of salivary glands. In parallel, a non-cytosolic enriched protein fraction was obtained from labial salivary glands and subjected to two-dimensional gel electrophoresis (2-DE) and de novo peptide sequencing. This procedure allowed comparison of peptides and EST sequences and enabled us to identify 65 protein spots from the secreted labial saliva 2DE proteome. The mass spectrometry analysis revealed ecdysone, glucose oxidase, fructosidase, carboxyl/cholinesterase and an uncharacterized protein previously detected in H. armigera midgut proteome. Consistently, their corresponding transcripts are among the most abundant in our cDNA library. We did find redundancy of sequence identification of saliva-secreted proteins suggesting multiple isoforms. As expected, we found several enzymes responsible for digestion and plant offense. In addition, we identified non-digestive proteins such as an arginine kinase and abundant proteins of unknown function. This identification of secreted salivary gland proteins allows a more comprehensive understanding of insect feeding and poses new challenges for the elucidation of protein function. PMID:22046331

Hydropathic self-organized criticality: a magic wand for protein physics.

PubMed

Phillips, J C

2012-10-01

Self-organized criticality (SOC) is a popular concept that has been the subject of more than 3000 articles in the last 25 years. The characteristic signature of SOC is the appearance of self-similarity (power-law scaling) in observable properties. A characteristic observable protein property that describes protein-water interactions is the water-accessible (hydropathic) interfacial area of compacted globular protein networks. Here we show that hydropathic power-law (size- or length-scale-dependent) exponents derived from SOC enable theory to connect standard Web-based (BLAST) short-range amino acid (aa) sequence similarities to long-range aa sequence hydropathic roughening form factors that hierarchically describe evolutionary trends in water - membrane protein interactions. Our method utilizes hydropathic aa exponents that define a non-Euclidean metric realistically rooted in the atomic coordinates of 5526 protein segments. These hydropathic aa exponents thereby encapsulate universal (but previously only implicit) non-Euclidean long-range differential geometrical features of the Protein Data Bank. These hydropathic aa exponents easily organize small mutated aa sequence differences between human and proximate species proteins. For rhodopsin, the most studied transmembrane signaling protein associated with night vision, analysis shows that this approach separates Euclidean short- and non-Euclidean long-range aa sequence properties, and shows that they correlate with 96% success for humans, monkeys, cats, mice and rabbits. Proper application of SOC using hydropathic aa exponents promises unprecedented simplifications of exponentially complex protein sequence-structure-function problems, both conceptual and practical.

Mass spectrometry-based protein identification by integrating de novo sequencing with database searching.

PubMed

Wang, Penghao; Wilson, Susan R

2013-01-01

Mass spectrometry-based protein identification is a very challenging task. The main identification approaches include de novo sequencing and database searching. Both approaches have shortcomings, so an integrative approach has been developed. The integrative approach firstly infers partial peptide sequences, known as tags, directly from tandem spectra through de novo sequencing, and then puts these sequences into a database search to see if a close peptide match can be found. However the current implementation of this integrative approach has several limitations. Firstly, simplistic de novo sequencing is applied and only very short sequence tags are used. Secondly, most integrative methods apply an algorithm similar to BLAST to search for exact sequence matches and do not accommodate sequence errors well. Thirdly, by applying these methods the integrated de novo sequencing makes a limited contribution to the scoring model which is still largely based on database searching. We have developed a new integrative protein identification method which can integrate de novo sequencing more efficiently into database searching. Evaluated on large real datasets, our method outperforms popular identification methods.

Prediction of multi-drug resistance transporters using a novel sequence analysis method [version 2; referees: 2 approved

DOE PAGES

McDermott, Jason E.; Bruillard, Paul; Overall, Christopher C.; ...

2015-03-09

There are many examples of groups of proteins that have similar function, but the determinants of functional specificity may be hidden by lack of sequencesimilarity, or by large groups of similar sequences with different functions. Transporters are one such protein group in that the general function, transport, can be easily inferred from the sequence, but the substrate specificity can be impossible to predict from sequence with current methods. In this paper we describe a linguistic-based approach to identify functional patterns from groups of unaligned protein sequences and its application to predict multi-drug resistance transporters (MDRs) from bacteria. We first showmore » that our method can recreate known patterns from PROSITE for several motifs from unaligned sequences. We then show that the method, MDRpred, can predict MDRs with greater accuracy and positive predictive value than a collection of currently available family-based models from the Pfam database. Finally, we apply MDRpred to a large collection of protein sequences from an environmental microbiome study to make novel predictions about drug resistance in a potential environmental reservoir.« less

Identifying and reducing error in cluster-expansion approximations of protein energies.

PubMed

Hahn, Seungsoo; Ashenberg, Orr; Grigoryan, Gevorg; Keating, Amy E

2010-12-01

Protein design involves searching a vast space for sequences that are compatible with a defined structure. This can pose significant computational challenges. Cluster expansion is a technique that can accelerate the evaluation of protein energies by generating a simple functional relationship between sequence and energy. The method consists of several steps. First, for a given protein structure, a training set of sequences with known energies is generated. Next, this training set is used to expand energy as a function of clusters consisting of single residues, residue pairs, and higher order terms, if required. The accuracy of the sequence-based expansion is monitored and improved using cross-validation testing and iterative inclusion of additional clusters. As a trade-off for evaluation speed, the cluster-expansion approximation causes prediction errors, which can be reduced by including more training sequences, including higher order terms in the expansion, and/or reducing the sequence space described by the cluster expansion. This article analyzes the sources of error and introduces a method whereby accuracy can be improved by judiciously reducing the described sequence space. The method is applied to describe the sequence-stability relationship for several protein structures: coiled-coil dimers and trimers, a PDZ domain, and T4 lysozyme as examples with computationally derived energies, and SH3 domains in amphiphysin-1 and endophilin-1 as examples where the expanded pseudo-energies are obtained from experiments. Our open-source software package Cluster Expansion Version 1.0 allows users to expand their own energy function of interest and thereby apply cluster expansion to custom problems in protein design. © 2010 Wiley Periodicals, Inc.

Transcription factor IID in the Archaea: sequences in the Thermococcus celer genome would encode a product closely related to the TATA-binding protein of eukaryotes

NASA Technical Reports Server (NTRS)

Marsh, T. L.; Reich, C. I.; Whitelock, R. B.; Olsen, G. J.; Woese, C. R. (Principal Investigator)

1994-01-01

The first step in transcription initiation in eukaryotes is mediated by the TATA-binding protein, a subunit of the transcription factor IID complex. We have cloned and sequenced the gene for a presumptive homolog of this eukaryotic protein from Thermococcus celer, a member of the Archaea (formerly archaebacteria). The protein encoded by the archaeal gene is a tandem repeat of a conserved domain, corresponding to the repeated domain in its eukaryotic counterparts. Molecular phylogenetic analyses of the two halves of the repeat are consistent with the duplication occurring before the divergence of the archael and eukaryotic domains. In conjunction with previous observations of similarity in RNA polymerase subunit composition and sequences and the finding of a transcription factor IIB-like sequence in Pyrococcus woesei (a relative of T. celer) it appears that major features of the eukaryotic transcription apparatus were well-established before the origin of eukaryotic cellular organization. The divergence between the two halves of the archael protein is less than that between the halves of the individual eukaryotic sequences, indicating that the average rate of sequence change in the archael protein has been less than in its eukaryotic counterparts. To the extent that this lower rate applies to the genome as a whole, a clearer picture of the early genes (and gene families) that gave rise to present-day genomes is more apt to emerge from the study of sequences from the Archaea than from the corresponding sequences from eukaryotes.

``Sequence space soup'' of proteins and copolymers

NASA Astrophysics Data System (ADS)

Chan, Hue Sun; Dill, Ken A.

1991-09-01

To study the protein folding problem, we use exhaustive computer enumeration to explore ``sequence space soup,'' an imaginary solution containing the ``native'' conformations (i.e., of lowest free energy) under folding conditions, of every possible copolymer sequence. The model is of short self-avoiding chains of hydrophobic (H) and polar (P) monomers configured on the two-dimensional square lattice. By exhaustive enumeration, we identify all native structures for every possible sequence. We find that random sequences of H/P copolymers will bear striking resemblance to known proteins: Most sequences under folding conditions will be approximately as compact as known proteins, will have considerable amounts of secondary structure, and it is most probable that an arbitrary sequence will fold to a number of lowest free energy conformations that is of order one. In these respects, this simple model shows that proteinlike behavior should arise simply in copolymers in which one monomer type is highly solvent averse. It suggests that the structures and uniquenesses of native proteins are not consequences of having 20 different monomer types, or of unique properties of amino acid monomers with regard to special packing or interactions, and thus that simple copolymers might be designable to collapse to proteinlike structures and properties. A good strategy for designing a sequence to have a minimum possible number of native states is to strategically insert many P monomers. Thus known proteins may be marginally stable due to a balance: More H residues stabilize the desired native state, but more P residues prevent simultaneous stabilization of undesired native states.

Sequence Alignment to Predict Across Species Susceptibility ...

EPA Pesticide Factsheets

Conservation of a molecular target across species can be used as a line-of-evidence to predict the likelihood of chemical susceptibility. The web-based Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool was developed to simplify, streamline, and quantitatively assess protein sequence/structural similarity across taxonomic groups as a means to predict relative intrinsic susceptibility. The intent of the tool is to allow for evaluation of any potential protein target, so it is amenable to variable degrees of protein characterization, depending on available information about the chemical/protein interaction and the molecular target itself. To allow for flexibility in the analysis, a layered strategy was adopted for the tool. The first level of the SeqAPASS analysis compares primary amino acid sequences to a query sequence, calculating a metric for sequence similarity (including detection of candidate orthologs), the second level evaluates sequence similarity within selected domains (e.g., ligand-binding domain, DNA binding domain), and the third level of analysis compares individual amino acid residue positions identified as being of importance for protein conformation and/or ligand binding upon chemical perturbation. Each level of the SeqAPASS analysis provides increasing evidence to apply toward rapid, screening-level assessments of probable cross species susceptibility. Such analyses can support prioritization of chemicals for further ev

Efficient and Accurate Algorithm for Cleaved Fragments Prediction (CFPA) in Protein Sequences Dataset Based on Consensus and Its Variants: A Novel Degradomics Prediction Application.

PubMed

El-Assaad, Atlal; Dawy, Zaher; Nemer, Georges; Hajj, Hazem; Kobeissy, Firas H

2017-01-01

Degradomics is a novel discipline that involves determination of the proteases/substrate fragmentation profile, called the substrate degradome, and has been recently applied in different disciplines. A major application of degradomics is its utility in the field of biomarkers where the breakdown products (BDPs) of different protease have been investigated. Among the major proteases assessed, calpain and caspase proteases have been associated with the execution phases of the pro-apoptotic and pro-necrotic cell death, generating caspase/calpain-specific cleaved fragments. The distinction between calpain and caspase protein fragments has been applied to distinguish injury mechanisms. Advanced proteomics technology has been used to identify these BDPs experimentally. However, it has been a challenge to identify these BDPs with high precision and efficiency, especially if we are targeting a number of proteins at one time. In this chapter, we present a novel bioinfromatic detection method that identifies BDPs accurately and efficiently with validation against experimental data. This method aims at predicting the consensus sequence occurrences and their variants in a large set of experimentally detected protein sequences based on state-of-the-art sequence matching and alignment algorithms. After detection, the method generates all the potential cleaved fragments by a specific protease. This space and time-efficient algorithm is flexible to handle the different orientations that the consensus sequence and the protein sequence can take before cleaving. It is O(mn) in space complexity and O(Nmn) in time complexity, with N number of protein sequences, m length of the consensus sequence, and n length of each protein sequence. Ultimately, this knowledge will subsequently feed into the development of a novel tool for researchers to detect diverse types of selected BDPs as putative disease markers, contributing to the diagnosis and treatment of related disorders.

Use of a protein engineering strategy to overcome limitations in the production of "Difficult to Express" recombinant proteins.

PubMed

Hussain, Hirra; Fisher, David I; Abbott, W Mark; Roth, Robert G; Dickson, Alan J

2017-10-01

Certain recombinant proteins are deemed "difficult to express" in mammalian expression systems requiring significant cell and/or process engineering to abrogate expression bottlenecks. With increasing demand for the production of recombinant proteins in mammalian cells, low protein yields can have significant consequences for industrial processes. To investigate the molecular mechanisms that restrict expression of recombinant proteins, naturally secreted model proteins were analyzed from the tissue inhibitors of metalloproteinase (TIMP) protein family. In particular, TIMP-2 and TIMP-3 were subjected to detailed study. TIMP proteins share significant sequence homology (∼50% identity and ∼70% similarity in amino acid sequence). However, they show marked differences in secretion in mammalian expression systems despite this extensive sequence homology. Using these two proteins as models, this study characterized the molecular mechanisms responsible for poor recombinant protein production. Our results reveal that both TIMP-2 and TIMP-3 are detectable at mRNA and protein level within the cell but only TIMP-2 is secreted effectively into the extracellular medium. Analysis of protein localization and the nature of intracellular protein suggest TIMP-3 is severely limited in its post-translational processing. To overcome this challenge, modification of the TIMP-3 sequence to include a furin protease-cleavable pro-sequence resulted in secretion of the modified TIMP-3 protein, however, incomplete processing was observed. Based on the TIMP-3 data, the protein engineering approach was optimized and successfully applied in combination with cell engineering, the overexpression of furin, to another member of the TIMP protein family (the poorly expressed TIMP-4). Use of the described protein engineering strategy resulted in successful secretion of poorly (TIMP-4) and non-secreted (TIMP-3) targets, and presents a novel strategy to enhance the production of "difficult" recombinant targets. Biotechnol. Bioeng. 2017;114: 2348-2359. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Recurring sequence-structure motifs in (βα)8-barrel proteins and experimental optimization of a chimeric protein designed based on such motifs.

PubMed

Wang, Jichao; Zhang, Tongchuan; Liu, Ruicun; Song, Meilin; Wang, Juncheng; Hong, Jiong; Chen, Quan; Liu, Haiyan

2017-02-01

An interesting way of generating novel artificial proteins is to combine sequence motifs from natural proteins, mimicking the evolutionary path suggested by natural proteins comprising recurring motifs. We analyzed the βα and αβ modules of TIM barrel proteins by structure alignment-based sequence clustering. A number of preferred motifs were identified. A chimeric TIM was designed by using recurring elements as mutually compatible interfaces. The foldability of the designed TIM protein was then significantly improved by six rounds of directed evolution. The melting temperature has been improved by more than 20°C. A variety of characteristics suggested that the resulting protein is well-folded. Our analysis provided a library of peptide motifs that is potentially useful for different protein engineering studies. The protein engineering strategy of using recurring motifs as interfaces to connect partial natural proteins may be applied to other protein folds. Copyright © 2016 Elsevier B.V. All rights reserved.

DNA Cloning of Plasmodium falciparum Circumsporozoite Gene: Amino Acid Sequence of Repetitive Epitope

NASA Astrophysics Data System (ADS)

Enea, Vincenzo; Ellis, Joan; Zavala, Fidel; Arnot, David E.; Asavanich, Achara; Masuda, Aoi; Quakyi, Isabella; Nussenzweig, Ruth S.

1984-08-01

A clone of complementary DNA encoding the circumsporozoite (CS) protein of the human malaria parasite Plasmodium falciparum has been isolated by screening an Escherichia coli complementary DNA library with a monoclonal antibody to the CS protein. The DNA sequence of the complementary DNA insert encodes a four-amino acid sequence: proline-asparagine-alanine-asparagine, tandemly repeated 23 times. The CS β -lactamase fusion protein specifically binds monoclonal antibodies to the CS protein and inhibits the binding of these antibodies to native Plasmodium falciparum CS protein. These findings provide a basis for the development of a vaccine against Plasmodium falciparum malaria.

THGS: a web-based database of Transmembrane Helices in Genome Sequences

PubMed Central

Fernando, S. A.; Selvarani, P.; Das, Soma; Kumar, Ch. Kiran; Mondal, Sukanta; Ramakumar, S.; Sekar, K.

2004-01-01

Transmembrane Helices in Genome Sequences (THGS) is an interactive web-based database, developed to search the transmembrane helices in the user-interested gene sequences available in the Genome Database (GDB). The proposed database has provision to search sequence motifs in transmembrane and globular proteins. In addition, the motif can be searched in the other sequence databases (Swiss-Prot and PIR) or in the macromolecular structure database, Protein Data Bank (PDB). Further, the 3D structure of the corresponding queried motif, if it is available in the solved protein structures deposited in the Protein Data Bank, can also be visualized using the widely used graphics package RASMOL. All the sequence databases used in the present work are updated frequently and hence the results produced are up to date. The database THGS is freely available via the world wide web and can be accessed at http://pranag.physics.iisc.ernet.in/thgs/ or http://144.16.71.10/thgs/. PMID:14681375

Sequence signatures of allosteric proteins towards rational design.

PubMed

Namboodiri, Saritha; Verma, Chandra; Dhar, Pawan K; Giuliani, Alessandro; Nair, Achuthsankar S

2010-12-01

Allostery is the phenomenon of changes in the structure and activity of proteins that appear as a consequence of ligand binding at sites other than the active site. Studying mechanistic basis of allostery leading to protein design with predetermined functional endpoints is an important unmet need of synthetic biology. Here, we screened the amino acid sequence landscape in search of sequence-signatures of allostery using Recurrence Quantitative Analysis (RQA) method. A characteristic vector, comprised of 10 features extracted from RQA was defined for amino acid sequences. Using Principal Component Analysis, four factors were found to be important determinants of allosteric behavior. Our sequence-based predictor method shows 82.6% accuracy, 85.7% sensitivity and 77.9% specificity with the current dataset. Further, we show that Laminarity-Mean-hydrophobicity representing repeated hydrophobic patches is the most crucial indicator of allostery. To our best knowledge this is the first report that describes sequence determinants of allostery based on hydrophobicity. As an outcome of these findings, we plan to explore possibility of inducing allostery in proteins.

Large-Scale Concatenation cDNA Sequencing

PubMed Central

Yu, Wei; Andersson, Björn; Worley, Kim C.; Muzny, Donna M.; Ding, Yan; Liu, Wen; Ricafrente, Jennifer Y.; Wentland, Meredith A.; Lennon, Greg; Gibbs, Richard A.

1997-01-01

A total of 100 kb of DNA derived from 69 individual human brain cDNA clones of 0.7–2.0 kb were sequenced by concatenated cDNA sequencing (CCS), whereby multiple individual DNA fragments are sequenced simultaneously in a single shotgun library. The method yielded accurate sequences and a similar efficiency compared with other shotgun libraries constructed from single DNA fragments (>20 kb). Computer analyses were carried out on 65 cDNA clone sequences and their corresponding end sequences to examine both nucleic acid and amino acid sequence similarities in the databases. Thirty-seven clones revealed no DNA database matches, 12 clones generated exact matches (≥98% identity), and 16 clones generated nonexact matches (57%–97% identity) to either known human or other species genes. Of those 28 matched clones, 8 had corresponding end sequences that failed to identify similarities. In a protein similarity search, 27 clone sequences displayed significant matches, whereas only 20 of the end sequences had matches to known protein sequences. Our data indicate that full-length cDNA insert sequences provide significantly more nucleic acid and protein sequence similarity matches than expressed sequence tags (ESTs) for database searching. [All 65 cDNA clone sequences described in this paper have been submitted to the GenBank data library under accession nos. U79240–U79304.] PMID:9110174

Predicting protein-binding regions in RNA using nucleotide profiles and compositions.

PubMed

Choi, Daesik; Park, Byungkyu; Chae, Hanju; Lee, Wook; Han, Kyungsook

2017-03-14

Motivated by the increased amount of data on protein-RNA interactions and the availability of complete genome sequences of several organisms, many computational methods have been proposed to predict binding sites in protein-RNA interactions. However, most computational methods are limited to finding RNA-binding sites in proteins instead of protein-binding sites in RNAs. Predicting protein-binding sites in RNA is more challenging than predicting RNA-binding sites in proteins. Recent computational methods for finding protein-binding sites in RNAs have several drawbacks for practical use. We developed a new support vector machine (SVM) model for predicting protein-binding regions in mRNA sequences. The model uses sequence profiles constructed from log-odds scores of mono- and di-nucleotides and nucleotide compositions. The model was evaluated by standard 10-fold cross validation, leave-one-protein-out (LOPO) cross validation and independent testing. Since actual mRNA sequences have more non-binding regions than protein-binding regions, we tested the model on several datasets with different ratios of protein-binding regions to non-binding regions. The best performance of the model was obtained in a balanced dataset of positive and negative instances. 10-fold cross validation with a balanced dataset achieved a sensitivity of 91.6%, a specificity of 92.4%, an accuracy of 92.0%, a positive predictive value (PPV) of 91.7%, a negative predictive value (NPV) of 92.3% and a Matthews correlation coefficient (MCC) of 0.840. LOPO cross validation showed a lower performance than the 10-fold cross validation, but the performance remains high (87.6% accuracy and 0.752 MCC). In testing the model on independent datasets, it achieved an accuracy of 82.2% and an MCC of 0.656. Testing of our model and other state-of-the-art methods on a same dataset showed that our model is better than the others. Sequence profiles of log-odds scores of mono- and di-nucleotides were much more powerful features than nucleotide compositions in finding protein-binding regions in RNA sequences. But, a slight performance gain was obtained when using the sequence profiles along with nucleotide compositions. These are preliminary results of ongoing research, but demonstrate the potential of our approach as a powerful predictor of protein-binding regions in RNA. The program and supporting data are available at http://bclab.inha.ac.kr/RBPbinding .

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.

PubMed

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.

Deciphering the complexities of the wheat flour proteome using quantitative two-dimensional electrophoresis, three proteases and tandem mass spectrometry

PubMed Central

2011-01-01

Background Wheat flour is one of the world's major food ingredients, in part because of the unique end-use qualities conferred by the abundant glutamine- and proline-rich gluten proteins. Many wheat flour proteins also present dietary problems for consumers with celiac disease or wheat allergies. Despite the importance of these proteins it has been particularly challenging to use MS/MS to distinguish the many proteins in a flour sample and relate them to gene sequences. Results Grain from the extensively characterized spring wheat cultivar Triticum aestivum 'Butte 86' was milled to white flour from which proteins were extracted, then separated and quantified by 2-DE. Protein spots were identified by separate digestions with three proteases, followed by tandem mass spectrometry analysis of the peptides. The spectra were used to interrogate an improved protein sequence database and results were integrated using the Scaffold program. Inclusion of cultivar specific sequences in the database greatly improved the results, and 233 spots were identified, accounting for 93.1% of normalized spot volume. Identified proteins were assigned to 157 wheat sequences, many for proteins unique to wheat and nearly 40% from Butte 86. Alpha-gliadins accounted for 20.4% of flour protein, low molecular weight glutenin subunits 18.0%, high molecular weight glutenin subunits 17.1%, gamma-gliadins 12.2%, omega-gliadins 10.5%, amylase/protease inhibitors 4.1%, triticins 1.6%, serpins 1.6%, purinins 0.9%, farinins 0.8%, beta-amylase 0.5%, globulins 0.4%, other enzymes and factors 1.9%, and all other 3%. Conclusions This is the first successful effort to identify the majority of abundant flour proteins for a single wheat cultivar, relate them to individual gene sequences and estimate their relative levels. Many genes for wheat flour proteins are not expressed, so this study represents further progress in describing the expressed wheat genome. Use of cultivar-specific contigs helped to overcome the difficulties of matching peptides to gene sequences for members of highly similar, rapidly evolving storage protein families. Prospects for simplifying this process for routine analyses are discussed. The ability to measure expression levels for individual flour protein genes complements information gained from efforts to sequence the wheat genome and is essential for studies of effects of environment on gene expression. PMID:21314956

Recombinant pinoresinol/lariciresinol reductase, recombinant dirigent protein, and methods of use

DOEpatents

Lewis, Norman G.; Davin, Laurence B.; Dinkova-Kostova, Albena T.; Fujita, Masayuki; Gang, David R.; Sarkanen, Simo; Ford, Joshua D.

2001-04-03

Dirigent proteins and pinoresinol/lariciresinol reductases have been isolated, together with cDNAs encoding dirigent proteins and pinoresinol/lariciresinol reductases. Accordingly, isolated DNA sequences are provided which code for the expression of dirigent proteins and pinoresinol/lariciresinol reductases. In other aspects, replicable recombinant cloning vehicles are provided which code for dirigent proteins or pinoresinol/lariciresinol reductases or for a base sequence sufficiently complementary to at least a portion of dirigent protein or pinoresinol/lariciresinol reductase DNA or RNA to enable hybridization therewith. In yet other aspects, modified host cells are provided that have been transformed, transfected, infected and/or injected with a recombinant cloning vehicle and/or DNA sequence encoding dirigent protein or pinoresinol/lariciresinol reductase. Thus, systems and methods are provided for the recombinant expression of dirigent proteins and/or pinoresinol/lariciresinol reductases.

UniPROBE, update 2011: expanded content and search tools in the online database of protein-binding microarray data on protein-DNA interactions.

PubMed

Robasky, Kimberly; Bulyk, Martha L

2011-01-01

The Universal PBM Resource for Oligonucleotide-Binding Evaluation (UniPROBE) database is a centralized repository of information on the DNA-binding preferences of proteins as determined by universal protein-binding microarray (PBM) technology. Each entry for a protein (or protein complex) in UniPROBE provides the quantitative preferences for all possible nucleotide sequence variants ('words') of length k ('k-mers'), as well as position weight matrix (PWM) and graphical sequence logo representations of the k-mer data. In this update, we describe >130% expansion of the database content, incorporation of a protein BLAST (blastp) tool for finding protein sequence matches in UniPROBE, the introduction of UniPROBE accession numbers and additional database enhancements. The UniPROBE database is available at http://uniprobe.org.

Confirmation of translatability and functionality certifies the dual endothelin1/VEGFsp receptor (DEspR) protein.

PubMed

Herrera, Victoria L M; Steffen, Martin; Moran, Ann Marie; Tan, Glaiza A; Pasion, Khristine A; Rivera, Keith; Pappin, Darryl J; Ruiz-Opazo, Nelson

2016-06-14

In contrast to rat and mouse databases, the NCBI gene database lists the human dual-endothelin1/VEGFsp receptor (DEspR, formerly Dear) as a unitary transcribed pseudogene due to a stop [TGA]-codon at codon#14 in automated DNA and RNA sequences. However, re-analysis is needed given prior single gene studies detected a tryptophan [TGG]-codon#14 by manual Sanger sequencing, demonstrated DEspR translatability and functionality, and since the demonstration of actual non-translatability through expression studies, the standard-of-excellence for pseudogene designation, has not been performed. Re-analysis must meet UNIPROT criteria for demonstration of a protein's existence at the highest (protein) level, which a priori, would override DNA- or RNA-based deductions. To dissect the nucleotide sequence discrepancy, we performed Maxam-Gilbert sequencing and reviewed 727 RNA-seq entries. To comply with the highest level multiple UNIPROT criteria for determining DEspR's existence, we performed various experiments using multiple anti-DEspR monoclonal antibodies (mAbs) targeting distinct DEspR epitopes with one spanning the contested tryptophan [TGG]-codon#14, assessing: (a) DEspR protein expression, (b) predicted full-length protein size, (c) sequence-predicted protein-specific properties beyond codon#14: receptor glycosylation and internalization, (d) protein-partner interactions, and (e) DEspR functionality via DEspR-inhibition effects. Maxam-Gilbert sequencing and some RNA-seq entries demonstrate two guanines, hence a tryptophan [TGG]-codon#14 within a compression site spanning an error-prone compression sequence motif. Western blot analysis using anti-DEspR mAbs targeting distinct DEspR epitopes detect the identical glycosylated 17.5 kDa pull-down protein. Decrease in DEspR-protein size after PNGase-F digest demonstrates post-translational glycosylation, concordant with the consensus-glycosylation site beyond codon#14. Like other small single-transmembrane proteins, mass spectrometry analysis of anti-DEspR mAb pull-down proteins do not detect DEspR, but detect DEspR-protein interactions with proteins implicated in intracellular trafficking and cancer. FACS analyses also detect DEspR-protein in different human cancer stem-like cells (CSCs). DEspR-inhibition studies identify DEspR-roles in CSC survival and growth. Live cell imaging detects fluorescently-labeled anti-DEspR mAb targeted-receptor internalization, concordant with the single internalization-recognition sequence also located beyond codon#14. Data confirm translatability of DEspR, the full-length DEspR protein beyond codon#14, and elucidate DEspR-specific functionality. Along with detection of the tryptophan [TGG]-codon#14 within an error-prone compression site, cumulative data demonstrating DEspR protein existence fulfill multiple UNIPROT criteria, thus refuting its pseudogene designation.

A peptide sequence on carcinoembryonic antigen binds to a 80kD protein on Kupffer cells.

PubMed

Thomas, P; Petrick, A T; Toth, C A; Fox, E S; Elting, J J; Steele, G

1992-10-30

Clearance of carcinoembryonic antigen (CEA) from the circulation is by binding to Kupffer cells in the liver. We have shown that CEA binding to Kupffer cells occurs via a peptide sequence YPELPK representing amino acids 107-112 of the CEA sequence. This peptide sequence is located in the region between the N-terminal and the first immunoglobulin like loop domain. Using native CEA and peptides containing this sequence complexed with a heterobifunctional crosslinking agent and ligand blotting with biotinylated CEA and NCA we have shown binding to an 80kD protein on the Kupffer cell surface. This binding protein may be important in the development of hepatic metastases.

Coiled-coil length: Size does matter.

PubMed

Surkont, Jaroslaw; Diekmann, Yoan; Ryder, Pearl V; Pereira-Leal, Jose B

2015-12-01

Protein evolution is governed by processes that alter primary sequence but also the length of proteins. Protein length may change in different ways, but insertions, deletions and duplications are the most common. An optimal protein size is a trade-off between sequence extension, which may change protein stability or lead to acquisition of a new function, and shrinkage that decreases metabolic cost of protein synthesis. Despite the general tendency for length conservation across orthologous proteins, the propensity to accept insertions and deletions is heterogeneous along the sequence. For example, protein regions rich in repetitive peptide motifs are well known to extensively vary their length across species. Here, we analyze length conservation of coiled-coils, domains formed by an ubiquitous, repetitive peptide motif present in all domains of life, that frequently plays a structural role in the cell. We observed that, despite the repetitive nature, the length of coiled-coil domains is generally highly conserved throughout the tree of life, even when the remaining parts of the protein change, including globular domains. Length conservation is independent of primary amino acid sequence variation, and represents a conservation of domain physical size. This suggests that the conservation of domain size is due to functional constraints. © 2015 Wiley Periodicals, Inc.

Content of intrinsic disorder influences the outcome of cell-free protein synthesis.

PubMed

Tokmakov, Alexander A; Kurotani, Atsushi; Ikeda, Mariko; Terazawa, Yumiko; Shirouzu, Mikako; Stefanov, Vasily; Sakurai, Tetsuya; Yokoyama, Shigeyuki

2015-09-11

Cell-free protein synthesis is used to produce proteins with various structural traits. Recent bioinformatics analyses indicate that more than half of eukaryotic proteins possess long intrinsically disordered regions. However, no systematic study concerning the connection between intrinsic disorder and expression success of cell-free protein synthesis has been presented until now. To address this issue, we examined correlations of the experimentally observed cell-free protein expression yields with the contents of intrinsic disorder bioinformatically predicted in the expressed sequences. This analysis revealed strong relationships between intrinsic disorder and protein amenability to heterologous cell-free expression. On the one hand, elevated disorder content was associated with the increased ratio of soluble expression. On the other hand, overall propensity for detectable protein expression decreased with disorder content. We further demonstrated that these tendencies are rooted in some distinct features of intrinsically disordered regions, such as low hydrophobicity, elevated surface accessibility and high abundance of sequence motifs for proteolytic degradation, including sites of ubiquitination and PEST sequences. Our findings suggest that identification of intrinsically disordered regions in the expressed amino acid sequences can be of practical use for predicting expression success and optimizing cell-free protein synthesis.

Evidence for the principle of minimal frustration in the evolution of protein folding landscapes.

PubMed

Tzul, Franco O; Vasilchuk, Daniel; Makhatadze, George I

2017-02-28

Theoretical and experimental studies have firmly established that protein folding can be described by a funneled energy landscape. This funneled energy landscape is the result of foldable protein sequences evolving following the principle of minimal frustration, which allows proteins to rapidly fold to their native biologically functional conformations. For a protein family with a given functional fold, the principle of minimal frustration suggests that, independent of sequence, all proteins within this family should fold with similar rates. However, depending on the optimal living temperature of the organism, proteins also need to modulate their thermodynamic stability. Consequently, the difference in thermodynamic stability should be primarily caused by differences in the unfolding rates. To test this hypothesis experimentally, we performed comprehensive thermodynamic and kinetic analyses of 15 different proteins from the thioredoxin family. Eight of these thioredoxins were extant proteins from psychrophilic, mesophilic, or thermophilic organisms. The other seven protein sequences were obtained using ancestral sequence reconstruction and can be dated back over 4 billion years. We found that all studied proteins fold with very similar rates but unfold with rates that differ up to three orders of magnitude. The unfolding rates correlate well with the thermodynamic stability of the proteins. Moreover, proteins that unfold slower are more resistant to proteolysis. These results provide direct experimental support to the principle of minimal frustration hypothesis.

Vesicular monoamine transporter-1 (VMAT-1) mRNA and immunoreactive proteins in mouse brain.

PubMed

Ashe, Karen M; Chiu, Wan-Ling; Khalifa, Ahmed M; Nicolas, Antoine N; Brown, Bonnie L; De Martino, Randall R; Alexander, Clayton P; Waggener, Christopher T; Fischer-Stenger, Krista; Stewart, Jennifer K

2011-01-01

Vesicular monoamine transporter 1 (VMAT-1) mRNA and protein were examined (1) to determine whether adult mouse brain expresses full-length VMAT-1 mRNA that can be translated to functional transporter protein and (2) to compare immunoreactive VMAT-1 proteins in brain and adrenal. VMAT-1 mRNA was detected in mouse brain with RT-PCR. The cDNA was sequenced, cloned into an expression vector, transfected into COS-1 cells, and cell protein was assayed for VMAT-1 activity. Immunoreactive proteins were examined on western blots probed with four different antibodies to VMAT-1. Sequencing confirmed identity of the entire coding sequences of VMAT-1 cDNA from mouse medulla oblongata/pons and adrenal to a Gen-Bank reference sequence. Transfection of the brain cDNA into COS-1 cells resulted in transporter activity that was blocked by the VMAT inhibitor reserpine and a proton ionophore, but not by tetrabenazine, which has a high affinity for VMAT-2. Antibodies to either the C- or N- terminus of VMAT-1 detected two proteins (73 and 55 kD) in transfected COS-1 cells. The C-terminal antibodies detected both proteins in extracts of mouse medulla/pons, cortex, hypothalamus, and cerebellum but only the 73 kD protein and higher molecular weight immunoreactive proteins in mouse adrenal and rat PC12 cells, which are positive controls for rodent VMAT-1. These findings demonstrate that a functional VMAT-1 mRNA coding sequence is expressed in mouse brain and suggest processing of VMAT-1 protein differs in mouse adrenal and brain.

Structural characterization of the N-terminal mineral modification domains from the molluscan crystal-modulating biomineralization proteins, AP7 and AP24.

PubMed

Wustman, Brandon A; Morse, Daniel E; Evans, John Spencer

2004-08-05

The AP7 and AP24 proteins represent a class of mineral-interaction polypeptides that are found in the aragonite-containing nacre layer of mollusk shell (H. rufescens). These proteins have been shown to preferentially interfere with calcium carbonate mineral growth in vitro. It is believed that both proteins play an important role in aragonite polymorph selection in the mollusk shell. Previously, we demonstrated the 1-30 amino acid (AA) N-terminal sequences of AP7 and AP24 represent mineral interaction/modification domains in both proteins, as evidenced by their ability to frustrate calcium carbonate crystal growth at step edge regions. In this present report, using free N-terminal, C(alpha)-amide "capped" synthetic polypeptides representing the 1-30 AA regions of AP7 (AP7-1 polypeptide) and AP24 (AP24-1 polypeptide) and NMR spectroscopy, we confirm that both N-terminal sequences possess putative Ca (II) interaction polyanionic sequence regions (2 x -DD- in AP7-1, -DDDED- in AP24-1) that are random coil-like in structure. However, with regard to the remaining sequences regions, each polypeptide features unique structural differences. AP7-1 possesses an extended beta-strand or polyproline type II-like structure within the A11-M10, S12-V13, and S28-I27 sequence regions, with the remaining sequence regions adopting a random-coil-like structure, a trait common to other polyelectrolyte mineral-associated polypeptide sequences. Conversely, AP24-1 possesses random coil-like structure within A1-S9 and Q14-N16 sequence regions, and evidence for turn-like, bend, or loop conformation within the G10-N13, Q17-N24, and M29-F30 sequence regions, similar to the structures identified within the putative elastomeric proteins Lustrin A and sea urchin spicule matrix proteins. The similarities and differences in AP7 and AP24 N-terminal domain structure are discussed with regard to joint AP7-AP24 protein modification of calcium carbonate growth. Copyright 2004 Wiley Periodicals, Inc.

HIPPI: highly accurate protein family classification with ensembles of HMMs.

PubMed

Nguyen, Nam-Phuong; Nute, Michael; Mirarab, Siavash; Warnow, Tandy

2016-11-11

Given a new biological sequence, detecting membership in a known family is a basic step in many bioinformatics analyses, with applications to protein structure and function prediction and metagenomic taxon identification and abundance profiling, among others. Yet family identification of sequences that are distantly related to sequences in public databases or that are fragmentary remains one of the more difficult analytical problems in bioinformatics. We present a new technique for family identification called HIPPI (Hierarchical Profile Hidden Markov Models for Protein family Identification). HIPPI uses a novel technique to represent a multiple sequence alignment for a given protein family or superfamily by an ensemble of profile hidden Markov models computed using HMMER. An evaluation of HIPPI on the Pfam database shows that HIPPI has better overall precision and recall than blastp, HMMER, and pipelines based on HHsearch, and maintains good accuracy even for fragmentary query sequences and for protein families with low average pairwise sequence identity, both conditions where other methods degrade in accuracy. HIPPI provides accurate protein family identification and is robust to difficult model conditions. Our results, combined with observations from previous studies, show that ensembles of profile Hidden Markov models can better represent multiple sequence alignments than a single profile Hidden Markov model, and thus can improve downstream analyses for various bioinformatic tasks. Further research is needed to determine the best practices for building the ensemble of profile Hidden Markov models. HIPPI is available on GitHub at https://github.com/smirarab/sepp .

A frequency-based linguistic approach to protein decoding and design: Simple concepts, diverse applications, and the SCS Package

PubMed Central

Motomura, Kenta; Nakamura, Morikazu; Otaki, Joji M.

2013-01-01

Protein structure and function information is coded in amino acid sequences. However, the relationship between primary sequences and three-dimensional structures and functions remains enigmatic. Our approach to this fundamental biochemistry problem is based on the frequencies of short constituent sequences (SCSs) or words. A protein amino acid sequence is considered analogous to an English sentence, where SCSs are equivalent to words. Availability scores, which are defined as real SCS frequencies in the non-redundant amino acid database relative to their probabilistically expected frequencies, demonstrate the biological usage bias of SCSs. As a result, this frequency-based linguistic approach is expected to have diverse applications, such as secondary structure specifications by structure-specific SCSs and immunological adjuvants with rare or non-existent SCSs. Linguistic similarities (e.g., wide ranges of scale-free distributions) and dissimilarities (e.g., behaviors of low-rank samples) between proteins and the natural English language have been revealed in the rank-frequency relationships of SCSs or words. We have developed a web server, the SCS Package, which contains five applications for analyzing protein sequences based on the linguistic concept. These tools have the potential to assist researchers in deciphering structurally and functionally important protein sites, species-specific sequences, and functional relationships between SCSs. The SCS Package also provides researchers with a tool to construct amino acid sequences de novo based on the idiomatic usage of SCSs. PMID:24688703

A frequency-based linguistic approach to protein decoding and design: Simple concepts, diverse applications, and the SCS Package.

PubMed

Motomura, Kenta; Nakamura, Morikazu; Otaki, Joji M

2013-01-01

Protein structure and function information is coded in amino acid sequences. However, the relationship between primary sequences and three-dimensional structures and functions remains enigmatic. Our approach to this fundamental biochemistry problem is based on the frequencies of short constituent sequences (SCSs) or words. A protein amino acid sequence is considered analogous to an English sentence, where SCSs are equivalent to words. Availability scores, which are defined as real SCS frequencies in the non-redundant amino acid database relative to their probabilistically expected frequencies, demonstrate the biological usage bias of SCSs. As a result, this frequency-based linguistic approach is expected to have diverse applications, such as secondary structure specifications by structure-specific SCSs and immunological adjuvants with rare or non-existent SCSs. Linguistic similarities (e.g., wide ranges of scale-free distributions) and dissimilarities (e.g., behaviors of low-rank samples) between proteins and the natural English language have been revealed in the rank-frequency relationships of SCSs or words. We have developed a web server, the SCS Package, which contains five applications for analyzing protein sequences based on the linguistic concept. These tools have the potential to assist researchers in deciphering structurally and functionally important protein sites, species-specific sequences, and functional relationships between SCSs. The SCS Package also provides researchers with a tool to construct amino acid sequences de novo based on the idiomatic usage of SCSs.

Gene discovery in Eimeria tenella by immunoscreening cDNA expression libraries of sporozoites and schizonts with chicken intestinal antibodies.

PubMed

Réfega, Susana; Girard-Misguich, Fabienne; Bourdieu, Christiane; Péry, Pierre; Labbé, Marie

2003-04-02

Specific antibodies were produced ex vivo from intestinal culture of Eimeria tenella infected chickens. The specificity of these intestinal antibodies was tested against different parasite stages. These antibodies were used to immunoscreen first generation schizont and sporozoite cDNA libraries permitting the identification of new E. tenella antigens. We obtained a total of 119 cDNA clones which were subjected to sequence analysis. The sequences coding for the proteins inducing local immune responses were compared with nucleotide or protein databases and with expressed sequence tags (ESTs) databases. We identified new Eimeria genes coding for heat shock proteins, a ribosomal protein, a pyruvate kinase and a pyridoxine kinase. Specific features of other sequences are discussed.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wemmer, D.E.; Kumar, N.V.; Metrione, R.M.

Toxin II from Radianthus paumotensis (Rp/sub II/) has been investigated by high-resolution NMR and chemical sequencing methods. Resonance assignments have been obtained for this protein by the sequential approach. NMR assignments could not be made consistent with the previously reported primary sequence for this protein, and chemical methods have been used to determine a sequence with which the NMR data are consistent. Analysis of the 2D NOE spectra shows that the protein secondary structure is comprised of two sequences of ..beta..-sheet, probably joined into a distorted continuous sheet, connected by turns and extended loops, without any regular ..cap alpha..-helical segments.more » The residues previously implicated in activity in this class of proteins, D8 and R13, occur in a loop region.« less

Poliovirus replication proteins: RNA sequence encoding P3-1b and the sites of proteolytic processing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Semler, B.L.; Anderson, C.W.; Kitamura, N.

1981-06-01

A partial amino-terminal amino acid sequence of each of the major proteins encoded by the replicase region of the poliovirus genome has been determined. A comparison of this sequence information with the amino acid sequence predicted from the RNA sequence that has been determined for the 3' region of the poliovirus genome has allowed us to locate precisely the proteolytic cleavage sites at which the initial polyprotein is processed to create the poliovirus products P3-1b (NCVP1b), P3-2 (NCVP2), P3-4b (NCVP4b), and P3-7c (NCVP7c). For each of these products, as well as for the small genome-linked protein VPg, proteolytic cleavage occursmore » between a glutamine and a glycine residue to create the amino terminus of each protein. This result suggests that a single proteinase may be responsible for all of these cleavages. The sequence data also allow the precise positioning of the genome-linked protein VPg within the precursor P3-1b just proximal to the amino terminus of polypeptide P3-2.« less

UniDrug-target: a computational tool to identify unique drug targets in pathogenic bacteria.

PubMed

Chanumolu, Sree Krishna; Rout, Chittaranjan; Chauhan, Rajinder S

2012-01-01

Targeting conserved proteins of bacteria through antibacterial medications has resulted in both the development of resistant strains and changes to human health by destroying beneficial microbes which eventually become breeding grounds for the evolution of resistances. Despite the availability of more than 800 genomes sequences, 430 pathways, 4743 enzymes, 9257 metabolic reactions and protein (three-dimensional) 3D structures in bacteria, no pathogen-specific computational drug target identification tool has been developed. A web server, UniDrug-Target, which combines bacterial biological information and computational methods to stringently identify pathogen-specific proteins as drug targets, has been designed. Besides predicting pathogen-specific proteins essentiality, chokepoint property, etc., three new algorithms were developed and implemented by using protein sequences, domains, structures, and metabolic reactions for construction of partial metabolic networks (PMNs), determination of conservation in critical residues, and variation analysis of residues forming similar cavities in proteins sequences. First, PMNs are constructed to determine the extent of disturbances in metabolite production by targeting a protein as drug target. Conservation of pathogen-specific protein's critical residues involved in cavity formation and biological function determined at domain-level with low-matching sequences. Last, variation analysis of residues forming similar cavities in proteins sequences from pathogenic versus non-pathogenic bacteria and humans is performed. The server is capable of predicting drug targets for any sequenced pathogenic bacteria having fasta sequences and annotated information. The utility of UniDrug-Target server was demonstrated for Mycobacterium tuberculosis (H37Rv). The UniDrug-Target identified 265 mycobacteria pathogen-specific proteins, including 17 essential proteins which can be potential drug targets. UniDrug-Target is expected to accelerate pathogen-specific drug targets identification which will increase their success and durability as drugs developed against them have less chance to develop resistances and adverse impact on environment. The server is freely available at http://117.211.115.67/UDT/main.html. The standalone application (source codes) is available at http://www.bioinformatics.org/ftp/pub/bioinfojuit/UDT.rar.

MannDB: A microbial annotation database for protein characterization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, C; Lam, M; Smith, J

2006-05-19

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. MannDB is a relational database that organizes data resulting from fully automated, high-throughput protein-sequence analyses using open-sourcemore » 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. MannDB comprises a large number of genomes and comprehensive protein sequence analyses representing organisms listed as high-priority agents on the websites of several governmental organizations concerned with bio-terrorism. MannDB provides the user with a BLAST interface for comparison of native and non-native sequences and a query tool for conveniently selecting proteins of interest. In addition, the user has access to a web-based browser that compiles comprehensive and extensive reports.« less

Modulation of dimerization by residues distant from the interface in bovine neurophysin-II.

PubMed

Zheng, C; Peyton, D; Breslow, E

1997-09-01

The crystal structure of bovine neurophysin-II in its liganded state (Chen et al. [1991] Proc. Natl. Acad. Sci. USA 88, 4240-4244) indicates that the 1-6 sequence has a disordered conformation, lacks noncovalent contacts to other regions of the protein and is distant from the monomer-monomer interface. Cleavage of the 1-6 sequence by Staphylococcus protease V8 yielded a protein that, for the first time, crystallized in both liganded and unliganded states. Insights into the role of the 1-6 sequence in the unliganded state were obtained by NMR and related biophysical comparisons of the native and des-1-6 proteins. NMR spectra demonstrated that the environment and/or conformation of residues in the 1-6 sequence differed in liganded and unliganded states. Additionally, the unliganded des-1-6 protein exhibited a dimerization constant four to five times that of the native protein, potentially accounting for the observation that its peptide affinity was also increased. NMR studies further indicated that the increased dimerization constant of the des-1-6 protein correlated with the presence in the native protein of two isoenergetic forms of the monomer, in contrast to only a single form in the des-1-6 protein, as evidenced by signals from an internal dimerization-sensitive alpha-proton. Thus, the 1-6 sequence reduces the dimerization constant by stabilization of an alternative monomer conformation. A second product of Staphylococcus protease V8 digestion of the native protein was identified as the des-1-6 protein with an internal clip after binding site residue Glu-47, the clip presumably breaking the short 3,10 helix that most directly connects the interface to the interface to the binding site. This product, although unable to bind peptide, retained the dimerization constant of the des-1-6 protein, suggesting a lack of importance of the helix in dimerization and contrasting with the effects of the 1-6 sequence. A model is proposed in which the 1-6 sequence stabilizes the second conformation of the unliganded monomer via interactions affecting the loop region that separates the two neurophysin domains and which has been shown to influence neurophysin self-association.

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

PubMed

Wang, Huilin; Wang, Mingjun; Tan, Hao; Li, Yuan; Zhang, Ziding; Song, Jiangning

2014-01-01

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 targets of currently non-crystallizable proteins were provided as compendium data, which are anticipated to facilitate target selection and design for the worldwide structural genomics consortium. PredPPCrys is freely available at http://www.structbioinfor.org/PredPPCrys.

Designing pH induced fold switch in proteins

NASA Astrophysics Data System (ADS)

Baruah, Anupaul; Biswas, Parbati

2015-05-01

This work investigates the computational design of a pH induced protein fold switch based on a self-consistent mean-field approach by identifying the ensemble averaged characteristics of sequences that encode a fold switch. The primary challenge to balance the alternative sets of interactions present in both target structures is overcome by simultaneously optimizing two foldability criteria corresponding to two target structures. The change in pH is modeled by altering the residual charge on the amino acids. The energy landscape of the fold switch protein is found to be double funneled. The fold switch sequences stabilize the interactions of the sites with similar relative surface accessibility in both target structures. Fold switch sequences have low sequence complexity and hence lower sequence entropy. The pH induced fold switch is mediated by attractive electrostatic interactions rather than hydrophobic-hydrophobic contacts. This study may provide valuable insights to the design of fold switch proteins.

Predicted secondary structure similarity in the absence of primary amino acid sequence homology: hepatitis B virus open reading frames.

PubMed Central

Schaeffer, E; Sninsky, J J

1984-01-01

Proteins that are related evolutionarily may have diverged at the level of primary amino acid sequence while maintaining similar secondary structures. Computer analysis has been used to compare the open reading frames of the hepatitis B virus to those of the woodchuck hepatitis virus at the level of amino acid sequence, and to predict the relative hydrophilic character and the secondary structure of putative polypeptides. Similarity is seen at the levels of relative hydrophilicity and secondary structure, in the absence of sequence homology. These data reinforce the proposal that these open reading frames encode viral proteins. Computer analysis of this type can be more generally used to establish structural similarities between proteins that do not share obvious sequence homology as well as to assess whether an open reading frame is fortuitous or codes for a protein. PMID:6585835

Sequence and analysis of chromosome 4 of the plant Arabidopsis thaliana.

PubMed

Mayer, K; Schüller, C; Wambutt, R; Murphy, G; Volckaert, G; Pohl, T; Düsterhöft, A; Stiekema, W; Entian, K D; Terryn, N; Harris, B; Ansorge, W; Brandt, P; Grivell, L; Rieger, M; Weichselgartner, M; de Simone, V; Obermaier, B; Mache, R; Müller, M; Kreis, M; Delseny, M; Puigdomenech, P; Watson, M; Schmidtheini, T; Reichert, B; Portatelle, D; Perez-Alonso, M; Boutry, M; Bancroft, I; Vos, P; Hoheisel, J; Zimmermann, W; Wedler, H; Ridley, P; Langham, S A; McCullagh, B; Bilham, L; Robben, J; Van der Schueren, J; Grymonprez, B; Chuang, Y J; Vandenbussche, F; Braeken, M; Weltjens, I; Voet, M; Bastiaens, I; Aert, R; Defoor, E; Weitzenegger, T; Bothe, G; Ramsperger, U; Hilbert, H; Braun, M; Holzer, E; Brandt, A; Peters, S; van Staveren, M; Dirske, W; Mooijman, P; Klein Lankhorst, R; Rose, M; Hauf, J; Kötter, P; Berneiser, S; Hempel, S; Feldpausch, M; Lamberth, S; Van den Daele, H; De Keyser, A; Buysshaert, C; Gielen, J; Villarroel, R; De Clercq, R; Van Montagu, M; Rogers, J; Cronin, A; Quail, M; Bray-Allen, S; Clark, L; Doggett, J; Hall, S; Kay, M; Lennard, N; McLay, K; Mayes, R; Pettett, A; Rajandream, M A; Lyne, M; Benes, V; Rechmann, S; Borkova, D; Blöcker, H; Scharfe, M; Grimm, M; Löhnert, T H; Dose, S; de Haan, M; Maarse, A; Schäfer, M; Müller-Auer, S; Gabel, C; Fuchs, M; Fartmann, B; Granderath, K; Dauner, D; Herzl, A; Neumann, S; Argiriou, A; Vitale, D; Liguori, R; Piravandi, E; Massenet, O; Quigley, F; Clabauld, G; Mündlein, A; Felber, R; Schnabl, S; Hiller, R; Schmidt, W; Lecharny, A; Aubourg, S; Chefdor, F; Cooke, R; Berger, C; Montfort, A; Casacuberta, E; Gibbons, T; Weber, N; Vandenbol, M; Bargues, M; Terol, J; Torres, A; Perez-Perez, A; Purnelle, B; Bent, E; Johnson, S; Tacon, D; Jesse, T; Heijnen, L; Schwarz, S; Scholler, P; Heber, S; Francs, P; Bielke, C; Frishman, D; Haase, D; Lemcke, K; Mewes, H W; Stocker, S; Zaccaria, P; Bevan, M; Wilson, R K; de la Bastide, M; Habermann, K; Parnell, L; Dedhia, N; Gnoj, L; Schutz, K; Huang, E; Spiegel, L; Sehkon, M; Murray, J; Sheet, P; Cordes, M; Abu-Threideh, J; Stoneking, T; Kalicki, J; Graves, T; Harmon, G; Edwards, J; Latreille, P; Courtney, L; Cloud, J; Abbott, A; Scott, K; Johnson, D; Minx, P; Bentley, D; Fulton, B; Miller, N; Greco, T; Kemp, K; Kramer, J; Fulton, L; Mardis, E; Dante, M; Pepin, K; Hillier, L; Nelson, J; Spieth, J; Ryan, E; Andrews, S; Geisel, C; Layman, D; Du, H; Ali, J; Berghoff, A; Jones, K; Drone, K; Cotton, M; Joshu, C; Antonoiu, B; Zidanic, M; Strong, C; Sun, H; Lamar, B; Yordan, C; Ma, P; Zhong, J; Preston, R; Vil, D; Shekher, M; Matero, A; Shah, R; Swaby, I K; O'Shaughnessy, A; Rodriguez, M; Hoffmann, J; Till, S; Granat, S; Shohdy, N; Hasegawa, A; Hameed, A; Lodhi, M; Johnson, A; Chen, E; Marra, M; Martienssen, R; McCombie, W R

1999-12-16

The higher plant Arabidopsis thaliana (Arabidopsis) is an important model for identifying plant genes and determining their function. To assist biological investigations and to define chromosome structure, a coordinated effort to sequence the Arabidopsis genome was initiated in late 1996. Here we report one of the first milestones of this project, the sequence of chromosome 4. Analysis of 17.38 megabases of unique sequence, representing about 17% of the genome, reveals 3,744 protein coding genes, 81 transfer RNAs and numerous repeat elements. Heterochromatic regions surrounding the putative centromere, which has not yet been completely sequenced, are characterized by an increased frequency of a variety of repeats, new repeats, reduced recombination, lowered gene density and lowered gene expression. Roughly 60% of the predicted protein-coding genes have been functionally characterized on the basis of their homology to known genes. Many genes encode predicted proteins that are homologous to human and Caenorhabditis elegans proteins.

Predicting membrane protein types by incorporating protein topology, domains, signal peptides, and physicochemical properties into the general form of Chou's pseudo amino acid composition.

PubMed

Chen, Yen-Kuang; Li, Kuo-Bin

2013-02-07

The type information of un-annotated membrane proteins provides an important hint for their biological functions. The experimental determination of membrane protein types, despite being more accurate and reliable, is not always feasible due to the costly laboratory procedures, thereby creating a need for the development of bioinformatics methods. This article describes a novel computational classifier for the prediction of membrane protein types using proteins' sequences. The classifier, comprising a collection of one-versus-one support vector machines, makes use of the following sequence attributes: (1) the cationic patch sizes, the orientation, and the topology of transmembrane segments; (2) the amino acid physicochemical properties; (3) the presence of signal peptides or anchors; and (4) the specific protein motifs. A new voting scheme was implemented to cope with the multi-class prediction. Both the training and the testing sequences were collected from SwissProt. Homologous proteins were removed such that there is no pair of sequences left in the datasets with a sequence identity higher than 40%. The performance of the classifier was evaluated by a Jackknife cross-validation and an independent testing experiments. Results show that the proposed classifier outperforms earlier predictors in prediction accuracy in seven of the eight membrane protein types. The overall accuracy was increased from 78.3% to 88.2%. Unlike earlier approaches which largely depend on position-specific substitution matrices and amino acid compositions, most of the sequence attributes implemented in the proposed classifier have supported literature evidences. The classifier has been deployed as a web server and can be accessed at http://bsaltools.ym.edu.tw/predmpt. Copyright © 2012 Elsevier Ltd. All rights reserved.

Molecular Cloning and Characterization of cDNA Encoding a Putative Stress-Induced Heat-Shock Protein from Camelus dromedarius

PubMed Central

Elrobh, Mohamed S.; Alanazi, Mohammad S.; Khan, Wajahatullah; Abduljaleel, Zainularifeen; Al-Amri, Abdullah; Bazzi, Mohammad D.

2011-01-01

Heat shock proteins are ubiquitous, induced under a number of environmental and metabolic stresses, with highly conserved DNA sequences among mammalian species. Camelus dromedaries (the Arabian camel) domesticated under semi-desert environments, is well adapted to tolerate and survive against severe drought and high temperatures for extended periods. This is the first report of molecular cloning and characterization of full length cDNA of encoding a putative stress-induced heat shock HSPA6 protein (also called HSP70B′) from Arabian camel. A full-length cDNA (2417 bp) was obtained by rapid amplification of cDNA ends (RACE) and cloned in pET-b expression vector. The sequence analysis of HSPA6 gene showed 1932 bp-long open reading frame encoding 643 amino acids. The complete cDNA sequence of the Arabian camel HSPA6 gene was submitted to NCBI GeneBank (accession number HQ214118.1). The BLAST analysis indicated that C. dromedaries HSPA6 gene nucleotides shared high similarity (77–91%) with heat shock gene nucleotide of other mammals. The deduced 643 amino acid sequences (accession number ADO12067.1) showed that the predicted protein has an estimated molecular weight of 70.5 kDa with a predicted isoelectric point (pI) of 6.0. The comparative analyses of camel HSPA6 protein sequences with other mammalian heat shock proteins (HSPs) showed high identity (80–94%). Predicted camel HSPA6 protein structure using Protein 3D structural analysis high similarities with human and mouse HSPs. Taken together, this study indicates that the cDNA sequences of HSPA6 gene and its amino acid and protein structure from the Arabian camel are highly conserved and have similarities with other mammalian species. PMID:21845074

Nuclear proteins that bind the human gamma-globin gene promoter: alterations in binding produced by point mutations associated with hereditary persistence of fetal hemoglobin.

PubMed Central

Gumucio, D L; Rood, K L; Gray, T A; Riordan, M F; Sartor, C I; Collins, F S

1988-01-01

The molecular mechanisms responsible for the human fetal-to-adult hemoglobin switch have not yet been elucidated. Point mutations identified in the promoter regions of gamma-globin genes from individuals with nondeletion hereditary persistence of fetal hemoglobin (HPFH) may mark cis-acting sequences important for this switch, and the trans-acting factors which interact with these sequences may be integral parts in the puzzle of gamma-globin gene regulation. We have used gel retardation and footprinting strategies to define nuclear proteins which bind to the normal gamma-globin promoter and to determine the effect of HPFH mutations on the binding of a subset of these proteins. We have identified five proteins in human erythroleukemia cells (K562 and HEL) which bind to the proximal promoter region of the normal gamma-globin gene. One factor, gamma CAAT, binds the duplicated CCAAT box sequences; the -117 HPFH mutation increases the affinity of interaction between gamma CAAT and its cognate site. Two proteins, gamma CAC1 and gamma CAC2, bind the CACCC sequence. These proteins require divalent cations for binding. The -175 HPFH mutation interferes with the binding of a fourth protein, gamma OBP, which binds an octamer sequence (ATGCAAAT) in the normal gamma-globin promoter. The HPFH phenotype of the -175 mutation indicates that the octamer-binding protein may play a negative regulatory role in this setting. A fifth protein, EF gamma a, binds to sequences which overlap the octamer-binding site. The erythroid-specific distribution of EF gamma a and its close approximation to an apparent repressor-binding site suggest that it may be important in gamma-globin regulation. Images PMID:2468996

A nonadaptive origin of a beneficial trait: in silico selection for free energy of folding leads to the neutral emergence of mutational robustness in single domain proteins.

PubMed

Pagan, Rafael F; Massey, Steven E

2014-02-01

Proteins are regarded as being robust to the deleterious effects of mutations. Here, the neutral emergence of mutational robustness in a population of single domain proteins is explored using computer simulations. A pairwise contact model was used to calculate the ΔG of folding (ΔG folding) using the three dimensional protein structure of leech eglin C. A random amino acid sequence with low mutational robustness, defined as the average ΔΔG resulting from a point mutation (ΔΔG average), was threaded onto the structure. A population of 1,000 threaded sequences was evolved under selection for stability, using an upper and lower energy threshold. Under these conditions, mutational robustness increased over time in the most common sequence in the population. In contrast, when the wild type sequence was used it did not show an increase in robustness. This implies that the emergence of mutational robustness is sequence specific and that wild type sequences may be close to maximal robustness. In addition, an inverse relationship between ∆∆G average and protein stability is shown, resulting partly from a larger average effect of point mutations in more stable proteins. The emergence of mutational robustness was also observed in the Escherichia coli colE1 Rop and human CD59 proteins, implying that the property may be common in single domain proteins under certain simulation conditions. The results indicate that at least a portion of mutational robustness in small globular proteins might have arisen by a process of neutral emergence, and could be an example of a beneficial trait that has not been directly selected for, termed a "pseudaptation."

Deep sequencing methods for protein engineering and design.

PubMed

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.

General overview on structure prediction of twilight-zone proteins.

PubMed

Khor, Bee Yin; Tye, Gee Jun; Lim, Theam Soon; Choong, Yee Siew

2015-09-04

Protein structure prediction from amino acid sequence has been one of the most challenging aspects in computational structural biology despite significant progress in recent years showed by critical assessment of protein structure prediction (CASP) experiments. When experimentally determined structures are unavailable, the predictive structures may serve as starting points to study a protein. If the target protein consists of homologous region, high-resolution (typically <1.5 Å) model can be built via comparative modelling. However, when confronted with low sequence similarity of the target protein (also known as twilight-zone protein, sequence identity with available templates is less than 30%), the protein structure prediction has to be initiated from scratch. Traditionally, twilight-zone proteins can be predicted via threading or ab initio method. Based on the current trend, combination of different methods brings an improved success in the prediction of twilight-zone proteins. In this mini review, the methods, progresses and challenges for the prediction of twilight-zone proteins were discussed.

Reference System of DNA and Protein Sequences on CD-ROM

NASA Astrophysics Data System (ADS)

Nasu, Hisanori; Ito, Toshiaki

DNASIS-DBREF31 is a database for DNA and Protein sequences in the form of optical Compact Disk (CD) ROM, developed and commercialized by Hitachi Software Engineering Co., Ltd. Both nucleic acid base sequences and protein amino acid sequences can be retrieved from a single CD-ROM. Existing database is offered in the form of on-line service, floppy disks, or magnetic tape, all of which have some problems or other, such as usability or storage capacity. DNASIS-DBREF31 newly adopt a CD-ROM as a database device to realize a mass storage and personal use of the database.

SALAD database: a motif-based database of protein annotations for plant comparative genomics

PubMed Central

Mihara, Motohiro; Itoh, Takeshi; Izawa, Takeshi

2010-01-01

Proteins often have several motifs with distinct evolutionary histories. Proteins with similar motifs have similar biochemical properties and thus related biological functions. We constructed a unique comparative genomics database termed the SALAD database (http://salad.dna.affrc.go.jp/salad/) from plant-genome-based proteome data sets. We extracted evolutionarily conserved motifs by MEME software from 209 529 protein-sequence annotation groups selected by BLASTP from the proteome data sets of 10 species: rice, sorghum, Arabidopsis thaliana, grape, a lycophyte, a moss, 3 algae, and yeast. Similarity clustering of each protein group was performed by pairwise scoring of the motif patterns of the sequences. The SALAD database provides a user-friendly graphical viewer that displays a motif pattern diagram linked to the resulting bootstrapped dendrogram for each protein group. Amino-acid-sequence-based and nucleotide-sequence-based phylogenetic trees for motif combination alignment, a logo comparison diagram for each clade in the tree, and a Pfam-domain pattern diagram are also available. We also developed a viewer named ‘SALAD on ARRAYs’ to view arbitrary microarray data sets of paralogous genes linked to the same dendrogram in a window. The SALAD database is a powerful tool for comparing protein sequences and can provide valuable hints for biological analysis. PMID:19854933

SANSparallel: interactive homology search against Uniprot

PubMed Central

Somervuo, Panu; Holm, Liisa

2015-01-01

Proteins evolve by mutations and natural selection. The network of sequence similarities is a rich source for mining homologous relationships that inform on protein structure and function. There are many servers available to browse the network of homology relationships but one has to wait up to a minute for results. The SANSparallel webserver provides protein sequence database searches with immediate response and professional alignment visualization by third-party software. The output is a list, pairwise alignment or stacked alignment of sequence-similar proteins from Uniprot, UniRef90/50, Swissprot or Protein Data Bank. The stacked alignments are viewed in Jalview or as sequence logos. The database search uses the suffix array neighborhood search (SANS) method, which has been re-implemented as a client-server, improved and parallelized. The method is extremely fast and as sensitive as BLAST above 50% sequence identity. Benchmarks show that the method is highly competitive compared to previously published fast database search programs: UBLAST, DIAMOND, LAST, LAMBDA, RAPSEARCH2 and BLAT. The web server can be accessed interactively or programmatically at http://ekhidna2.biocenter.helsinki.fi/cgi-bin/sans/sans.cgi. It can be used to make protein functional annotation pipelines more efficient, and it is useful in interactive exploration of the detailed evidence supporting the annotation of particular proteins of interest. PMID:25855811

Chicken genome analysis reveals novel genes encoding biotin-binding proteins related to avidin family

PubMed Central

Niskanen, Einari A; Hytönen, Vesa P; Grapputo, Alessandro; Nordlund, Henri R; Kulomaa, Markku S; Laitinen, Olli H

2005-01-01

Background A chicken egg contains several biotin-binding proteins (BBPs), whose complete DNA and amino acid sequences are not known. In order to identify and characterise these genes and proteins we studied chicken cDNAs and genes available in the NCBI database and chicken genome database using the reported N-terminal amino acid sequences of chicken egg-yolk BBPs as search strings. Results Two separate hits showing significant homology for these N-terminal sequences were discovered. For one of these hits, the chromosomal location in the immediate proximity of the avidin gene family was found. Both of these hits encode proteins having high sequence similarity with avidin suggesting that chicken BBPs are paralogous to avidin family. In particular, almost all residues corresponding to biotin binding in avidin are conserved in these putative BBP proteins. One of the found DNA sequences, however, seems to encode a carboxy-terminal extension not present in avidin. Conclusion We describe here the predicted properties of the putative BBP genes and proteins. Our present observations link BBP genes together with avidin gene family and shed more light on the genetic arrangement and variability of this family. In addition, comparative modelling revealed the potential structural elements important for the functional and structural properties of the putative BBP proteins. PMID:15777476

Integrating mRNA and Protein Sequencing Enables the Detection and Quantitative Profiling of Natural Protein Sequence Variants of Populus trichocarpa.

PubMed

Abraham, Paul E; Wang, Xiaojing; Ranjan, Priya; Nookaew, Intawat; Zhang, Bing; Tuskan, Gerald A; Hettich, Robert L

2015-12-04

Next-generation sequencing has transformed the ability to link genotypes to phenotypes and facilitates the dissection of genetic contribution to complex traits. However, it is challenging to link genetic variants with the perturbed functional effects on proteins encoded by such genes. Here we show how RNA sequencing can be exploited to construct genotype-specific protein sequence databases to assess natural variation in proteins, providing information about the molecular toolbox driving cellular processes. For this study, we used two natural genotypes selected from a recent genome-wide association study of Populus trichocarpa, an obligate outcrosser with tremendous phenotypic variation across the natural population. This strategy allowed us to comprehensively catalogue proteins containing single amino acid polymorphisms (SAAPs), as well as insertions and deletions. We profiled the frequency of 128 types of naturally occurring amino acid substitutions, including both expected (neutral) and unexpected (non-neutral) SAAPs, with a subset occurring in regions of the genome having strong polymorphism patterns consistent with recent positive and/or divergent selection. By zeroing in on the molecular signatures of these important regions that might have previously been uncharacterized, we now provide a high-resolution molecular inventory that should improve accessibility and subsequent identification of natural protein variants in future genotype-to-phenotype studies.

SALAD database: a motif-based database of protein annotations for plant comparative genomics.

PubMed

Mihara, Motohiro; Itoh, Takeshi; Izawa, Takeshi

2010-01-01

Proteins often have several motifs with distinct evolutionary histories. Proteins with similar motifs have similar biochemical properties and thus related biological functions. We constructed a unique comparative genomics database termed the SALAD database (http://salad.dna.affrc.go.jp/salad/) from plant-genome-based proteome data sets. We extracted evolutionarily conserved motifs by MEME software from 209,529 protein-sequence annotation groups selected by BLASTP from the proteome data sets of 10 species: rice, sorghum, Arabidopsis thaliana, grape, a lycophyte, a moss, 3 algae, and yeast. Similarity clustering of each protein group was performed by pairwise scoring of the motif patterns of the sequences. The SALAD database provides a user-friendly graphical viewer that displays a motif pattern diagram linked to the resulting bootstrapped dendrogram for each protein group. Amino-acid-sequence-based and nucleotide-sequence-based phylogenetic trees for motif combination alignment, a logo comparison diagram for each clade in the tree, and a Pfam-domain pattern diagram are also available. We also developed a viewer named 'SALAD on ARRAYs' to view arbitrary microarray data sets of paralogous genes linked to the same dendrogram in a window. The SALAD database is a powerful tool for comparing protein sequences and can provide valuable hints for biological analysis.

Detecting Coevolution in and among Protein Domains

PubMed Central

Yeang, Chen-Hsiang; Haussler, David

2007-01-01

Correlated changes of nucleic or amino acids have provided strong information about the structures and interactions of molecules. Despite the rich literature in coevolutionary sequence analysis, previous methods often have to trade off between generality, simplicity, phylogenetic information, and specific knowledge about interactions. Furthermore, despite the evidence of coevolution in selected protein families, a comprehensive screening of coevolution among all protein domains is still lacking. We propose an augmented continuous-time Markov process model for sequence coevolution. The model can handle different types of interactions, incorporate phylogenetic information and sequence substitution, has only one extra free parameter, and requires no knowledge about interaction rules. We employ this model to large-scale screenings on the entire protein domain database (Pfam). Strikingly, with 0.1 trillion tests executed, the majority of the inferred coevolving protein domains are functionally related, and the coevolving amino acid residues are spatially coupled. Moreover, many of the coevolving positions are located at functionally important sites of proteins/protein complexes, such as the subunit linkers of superoxide dismutase, the tRNA binding sites of ribosomes, the DNA binding region of RNA polymerase, and the active and ligand binding sites of various enzymes. The results suggest sequence coevolution manifests structural and functional constraints of proteins. The intricate relations between sequence coevolution and various selective constraints are worth pursuing at a deeper level. PMID:17983264

The characterisation of novel secreted Ly-6 proteins from rat urine by the combined use of two-dimensional gel electrophoresis, microbore high performance liquid chromatography and expressed sequence tag data.

PubMed

Southan, Christopher; Cutler, Paul; Birrell, Helen; Connell, John; Fantom, Kenneth G M; Sims, Matthew; Shaikh, Narjis; Schneider, Klaus

2002-02-01

A proteomic study of rat urine was undertaken using two-dimensional gel electrophoresis, microbore high performance liquid chromatography, mass spectrometry and N-terminal sequencing. Five known urinary proteins were identified but two novel peptide fragments matched a large number of rat expressed sequence tags (ESTs) from a liver library. By combining protein chemical and nucleotide data, two 101-residue open reading frames with 90% amino acid identity were determined, rat urinary protein 1 (RUP-1) and RUP-2. The data established signal peptide removal and provided evidence for N-glycosylation. A third related sequence, rat spleen protein (RSP-1) was confirmed from EST searches. These three proteins have been submitted to SWISS-PROT as P81827, P81828 and Q9QXN2, respectively. A fourth novel homologue was found in porcine and bovine ESTs from embryo libraries. Alignment with known homologues showed conserved cysteine positions characteristic of a secreted subfamily of Ly-6 proteins. In two cases, antineoplastic urinary protein and caltrin, these homologues have unverified functional annotations. The RUP sequences showed high scoring matches to three unrelated rat mRNAs subsequently established to be chimeric. Two of these share extended sectional identity to RUP-1 but the third may represent another novel Ly-6 homologue. These chimeras have caused serious annotation errors in secondary databases.

ZifBASE: a database of zinc finger proteins and associated resources.

PubMed

Jayakanthan, Mannu; Muthukumaran, Jayaraman; Chandrasekar, Sanniyasi; Chawla, Konika; Punetha, Ankita; Sundar, Durai

2009-09-09

Information on the occurrence of zinc finger protein motifs in genomes is crucial to the developing field of molecular genome engineering. The knowledge of their target DNA-binding sequences is vital to develop chimeric proteins for targeted genome engineering and site-specific gene correction. There is a need to develop a computational resource of zinc finger proteins (ZFP) to identify the potential binding sites and its location, which reduce the time of in vivo task, and overcome the difficulties in selecting the specific type of zinc finger protein and the target site in the DNA sequence. ZifBASE provides an extensive collection of various natural and engineered ZFP. It uses standard names and a genetic and structural classification scheme to present data retrieved from UniProtKB, GenBank, Protein Data Bank, ModBase, Protein Model Portal and the literature. It also incorporates specialized features of ZFP including finger sequences and positions, number of fingers, physiochemical properties, classes, framework, PubMed citations with links to experimental structures (PDB, if available) and modeled structures of natural zinc finger proteins. ZifBASE provides information on zinc finger proteins (both natural and engineered ones), the number of finger units in each of the zinc finger proteins (with multiple fingers), the synergy between the adjacent fingers and their positions. Additionally, it gives the individual finger sequence and their target DNA site to which it binds for better and clear understanding on the interactions of adjacent fingers. The current version of ZifBASE contains 139 entries of which 89 are engineered ZFPs, containing 3-7F totaling to 296 fingers. There are 50 natural zinc finger protein entries ranging from 2-13F, totaling to 307 fingers. It has sequences and structures from literature, Protein Data Bank, ModBase and Protein Model Portal. The interface is cross linked to other public databases like UniprotKB, PDB, ModBase and Protein Model Portal and PubMed for making it more informative. A database is established to maintain the information of the sequence features, including the class, framework, number of fingers, residues, position, recognition site and physio-chemical properties (molecular weight, isoelectric point) of both natural and engineered zinc finger proteins and dissociation constant of few. ZifBASE can provide more effective and efficient way of accessing the zinc finger protein sequences and their target binding sites with the links to their three-dimensional structures. All the data and functions are available at the advanced web-based search interface http://web.iitd.ac.in/~sundar/zifbase.

LISTA, LISTA-HOP and LISTA-HON: a comprehensive compilation of protein encoding sequences and its associated homology databases from the yeast Saccharomyces.

PubMed Central

Dölz, R; Mossé, M O; Slonimski, P P; Bairoch, A; Linder, P

1994-01-01

We continued our effort to make a comprehensive database (LISTA) for the yeast Saccharomyces cerevisiae. In this database each sequence has been attributed a single genetic name. In the case of duplicated sequences a simple method has been applied to distinguish between sequences of one and the same gene from non-allelic sequences of duplicated genes. If necessary, synonyms are given in the case of allelic duplicated sequences. Thus sequences can be found either by the name or by synonyms given in LISTA. Each entry contains the genetic name, the mnemonic from the EMBL data bank, the codon bias, reference of the publication of the sequence, Chromosomal location as far as known, Swissprot and EMBL accession numbers. To obtain more information on the included sequences, each entry has been screened against non-redundant nucleotide and protein data bank collections resulting in LISTA-HON and LISTA-HOP. The LISTA data base can be linked to the associated data sets or to nucleotide and protein banks by the Sequence Retrieval System (SRS). PMID:7937046

Preservation of protein clefts in comparative models.

PubMed

Piedra, David; Lois, Sergi; de la Cruz, Xavier

2008-01-16

Comparative, or homology, modelling of protein structures is the most widely used prediction method when the target protein has homologues of known structure. Given that the quality of a model may vary greatly, several studies have been devoted to identifying the factors that influence modelling results. These studies usually consider the protein as a whole, and only a few provide a separate discussion of the behaviour of biologically relevant features of the protein. Given the value of the latter for many applications, here we extended previous work by analysing the preservation of native protein clefts in homology models. We chose to examine clefts because of their role in protein function/structure, as they are usually the locus of protein-protein interactions, host the enzymes' active site, or, in the case of protein domains, can also be the locus of domain-domain interactions that lead to the structure of the whole protein. We studied how the largest cleft of a protein varies in comparative models. To this end, we analysed a set of 53507 homology models that cover the whole sequence identity range, with a special emphasis on medium and low similarities. More precisely we examined how cleft quality - measured using six complementary parameters related to both global shape and local atomic environment, depends on the sequence identity between target and template proteins. In addition to this general analysis, we also explored the impact of a number of factors on cleft quality, and found that the relationship between quality and sequence identity varies depending on cleft rank amongst the set of protein clefts (when ordered according to size), and number of aligned residues. We have examined cleft quality in homology models at a range of seq.id. levels. Our results provide a detailed view of how quality is affected by distinct parameters and thus may help the user of comparative modelling to determine the final quality and applicability of his/her cleft models. In addition, the large variability in model quality that we observed within each sequence bin, with good models present even at low sequence identities (between 20% and 30%), indicates that properly developed identification methods could be used to recover good cleft models in this sequence range.

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

PubMed Central

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. However, studies are required to correlate this sequence variability with the virulence and pathogenicity. PMID:22788742

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

Cancer.gov

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

Towards comprehensive structural motif mining for better fold annotation in the "twilight zone" of sequence dissimilarity

PubMed Central

Jia, Yi; Huan, Jun; Buhr, Vincent; Zhang, Jintao; Carayannopoulos, Leonidas N

2009-01-01

Background Automatic identification of structure fingerprints from a group of diverse protein structures is challenging, especially for proteins whose divergent amino acid sequences may fall into the "twilight-" or "midnight-" zones where pair-wise sequence identities to known sequences fall below 25% and sequence-based functional annotations often fail. Results Here we report a novel graph database mining method and demonstrate its application to protein structure pattern identification and structure classification. The biologic motivation of our study is to recognize common structure patterns in "immunoevasins", proteins mediating virus evasion of host immune defense. Our experimental study, using both viral and non-viral proteins, demonstrates the efficiency and efficacy of the proposed method. Conclusion We present a theoretic framework, offer a practical software implementation for incorporating prior domain knowledge, such as substitution matrices as studied here, and devise an efficient algorithm to identify approximate matched frequent subgraphs. By doing so, we significantly expanded the analytical power of sophisticated data mining algorithms in dealing with large volume of complicated and noisy protein structure data. And without loss of generality, choice of appropriate compatibility matrices allows our method to be easily employed in domains where subgraph labels have some uncertainty. PMID:19208148

TESS: a geometric hashing algorithm for deriving 3D coordinate templates for searching structural databases. Application to enzyme active sites.

PubMed Central

Wallace, A. C.; Borkakoti, N.; Thornton, J. M.

1997-01-01

It is well established that sequence templates such as those in the PROSITE and PRINTS databases are powerful tools for predicting the biological function and tertiary structure for newly derived protein sequences. The number of X-ray and NMR protein structures is increasing rapidly and it is apparent that a 3D equivalent of the sequence templates is needed. Here, we describe an algorithm called TESS that automatically derives 3D templates from structures deposited in the Brookhaven Protein Data Bank. While a new sequence can be searched for sequence patterns, a new structure can be scanned against these 3D templates to identify functional sites. As examples, 3D templates are derived for enzymes with an O-His-O "catalytic triad" and for the ribonucleases and lysozymes. When these 3D templates are applied to a large data set of nonidentical proteins, several interesting hits are located. This suggests that the development of a 3D template database may help to identify the function of new protein structures, if unknown, as well as to design proteins with specific functions. PMID:9385633

The COG database: a tool for genome-scale analysis of protein functions and evolution

PubMed Central

Tatusov, Roman L.; Galperin, Michael Y.; Natale, Darren A.; Koonin, Eugene V.

2000-01-01

Rational classification of proteins encoded in sequenced genomes is critical for making the genome sequences maximally useful for functional and evolutionary studies. The database of Clusters of Orthologous Groups of proteins (COGs) is an attempt on a phylogenetic classification of the proteins encoded in 21 complete genomes of bacteria, archaea and eukaryotes (http://www.ncbi.nlm.nih.gov/COG ). The COGs were constructed by applying the criterion of consistency of genome-specific best hits to the results of an exhaustive comparison of all protein sequences from these genomes. The database comprises 2091 COGs that include 56–83% of the gene products from each of the complete bacterial and archaeal genomes and ~35% of those from the yeast Saccharomyces cerevisiae genome. The COG database is accompanied by the COGNITOR program that is used to fit new proteins into the COGs and can be applied to functional and phylogenetic annotation of newly sequenced genomes. PMID:10592175

Cellular automata and its applications in protein bioinformatics.

PubMed

Xiao, Xuan; Wang, Pu; Chou, Kuo-Chen

2011-09-01

With the explosion of protein sequences generated in the postgenomic era, it is highly desirable to develop high-throughput tools for rapidly and reliably identifying various attributes of uncharacterized proteins based on their sequence information alone. The knowledge thus obtained can help us timely utilize these newly found protein sequences for both basic research and drug discovery. Many bioinformatics tools have been developed by means of machine learning methods. This review is focused on the applications of a new kind of science (cellular automata) in protein bioinformatics. A cellular automaton (CA) is an open, flexible and discrete dynamic model that holds enormous potentials in modeling complex systems, in spite of the simplicity of the model itself. Researchers, scientists and practitioners from different fields have utilized cellular automata for visualizing protein sequences, investigating their evolution processes, and predicting their various attributes. Owing to its impressive power, intuitiveness and relative simplicity, the CA approach has great potential for use as a tool for bioinformatics.

RaptorX server: a resource for template-based protein structure modeling.

PubMed

Källberg, Morten; Margaryan, Gohar; Wang, Sheng; Ma, Jianzhu; Xu, Jinbo

2014-01-01

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

Microgravity

NASA Image and Video Library

1998-12-01

Type II restriction enzymes, such as Eco R1 endonulease, present a unique advantage for the study of sequence-specific recognition because they leave a record of where they have been in the form of the cleaved ends of the DNA sites where they were bound. The differential behavior of a sequence -specific protein at sites of differing base sequence is the essence of the sequence-specificity; the core question is how do these proteins discriminate between different DNA sequences especially when the two sequences are very similar. Principal Investigator: Dan Carter/New Century Pharmaceuticals

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

DOEpatents

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.

Identification of photoactivated adenylyl cyclases in Naegleria australiensis and BLUF-containing protein in Naegleria fowleri.

PubMed

Yasukawa, Hiro; Sato, Aya; Kita, Ayaka; Kodaira, Ken-Ichi; Iseki, Mineo; Takahashi, Tetsuo; Shibusawa, Mami; Watanabe, Masakatsu; Yagita, Kenji

2013-01-01

Complete genome sequencing of Naegleria gruberi has revealed that the organism encodes polypeptides similar to photoactivated adenylyl cyclases (PACs). Screening in the N. australiensis genome showed that the organism also encodes polypeptides similar to PACs. Each of the Naegleria proteins consists of a "sensors of blue-light using FAD" domain (BLUF domain) and an adenylyl cyclase domain (AC domain). PAC activity of the Naegleria proteins was assayed by comparing sensitivities of Escherichia coli cells heterologously expressing the proteins to antibiotics in a dark condition and a blue light-irradiated condition. Antibiotics used in the assays were fosfomycin and fosmidomycin. E. coli cells expressing the Naegleria proteins showed increased fosfomycin sensitivity and fosmidomycin sensitivity when incubated under blue light, indicating that the proteins functioned as PACs in the bacterial cells. Analysis of the N. fowleri genome revealed that the organism encodes a protein bearing an amino acid sequence similar to that of BLUF. A plasmid expressing a chimeric protein consisting of the BLUF-like sequence found in N. fowleri and the adenylyl cyclase domain of N. gruberi PAC was constructed to determine whether the BLUF-like sequence functioned as a sensor of blue light. E. coli cells expressing a chimeric protein showed increased fosfomycin sensitivity and fosmidomycin sensitivity when incubated under blue light. These experimental results indicated that the sequence similar to the BLUF domain found in N. fowleri functioned as a sensor of blue light.

Evolution of sparsity and modularity in a model of protein allostery

NASA Astrophysics Data System (ADS)

Hemery, Mathieu; Rivoire, Olivier

2015-04-01

The sequence of a protein is not only constrained by its physical and biochemical properties under current selection, but also by features of its past evolutionary history. Understanding the extent and the form that these evolutionary constraints may take is important to interpret the information in protein sequences. To study this problem, we introduce a simple but physical model of protein evolution where selection targets allostery, the functional coupling of distal sites on protein surfaces. This model shows how the geometrical organization of couplings between amino acids within a protein structure can depend crucially on its evolutionary history. In particular, two scenarios are found to generate a spatial concentration of functional constraints: high mutation rates and fluctuating selective pressures. This second scenario offers a plausible explanation for the high tolerance of natural proteins to mutations and for the spatial organization of their least tolerant amino acids, as revealed by sequence analysis and mutagenesis experiments. It also implies a faculty to adapt to new selective pressures that is consistent with observations. The model illustrates how several independent functional modules may emerge within the same protein structure, depending on the nature of past environmental fluctuations. Our model thus relates the evolutionary history of proteins to the geometry of their functional constraints, with implications for decoding and engineering protein sequences.

Complete genome sequence of a Watermelon silver mottle virus isolate from China.

PubMed

Rao, Xueqin; Wu, Zhuyan; Li, Yuan

2013-06-01

The complete genome of a Watermelon silver mottle virus (WSMoV) (genus Tospovirus, family Bunyaviridae) isolate (WSMoV-GZ) from Guangdong province, China was sequenced. The genomes of WSMoV-GZ contained 3,603, 4,909, and 8,914 nt of small (S), medium (M), and large (L) RNA segments, respectively, and had a genomic organization characteristic of members of the genus Tospovirus. The amino acid sequence of the nucleocapsid (N) protein, S RNA-encoded nonstructural (NSs) protein, M RNA-encoded nonstructural (NSm) protein, Gn/Gc glycoprotein precursor, and RNA-dependent RNA polymerase (RdRp) protein showed 94.3-97.5 % identity with those of other WSMoV isolates. Phylogenetic analysis showed that the N protein of WSMoV-GZ was clustered together with those of the WSMoV isolates. The full sequence of WSMoV-GZ provides a reference genome for comparison with other tospoviruses.

Top-down analysis of protein samples by de novo sequencing techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vyatkina, Kira; Wu, Si; Dekker, Lennard J. M.

MOTIVATION: Recent technological advances have made high-resolution mass spectrometers affordable to many laboratories, thus boosting rapid development of top-down mass spectrometry, and implying a need in efficient methods for analyzing this kind of data. RESULTS: We describe a method for analysis of protein samples from top-down tandem mass spectrometry data, which capitalizes on de novo sequencing of fragments of the proteins present in the sample. Our algorithm takes as input a set of de novo amino acid strings derived from the given mass spectra using the recently proposed Twister approach, and combines them into aggregated strings endowed with offsets. Themore » former typically constitute accurate sequence fragments of sufficiently well-represented proteins from the sample being analyzed, while the latter indicate their location in the protein sequence, and also bear information on post-translational modifications and fragmentation patterns.« less

Protein sequences bound to mineral surfaces persist into deep time

PubMed Central

Demarchi, Beatrice; Hall, Shaun; Roncal-Herrero, Teresa; Freeman, Colin L; Woolley, Jos; Crisp, Molly K; Wilson, Julie; Fotakis, Anna; Fischer, Roman; Kessler, Benedikt M; Rakownikow Jersie-Christensen, Rosa; Olsen, Jesper V; Haile, James; Thomas, Jessica; Marean, Curtis W; Parkington, John; Presslee, Samantha; Lee-Thorp, Julia; Ditchfield, Peter; Hamilton, Jacqueline F; Ward, Martyn W; Wang, Chunting Michelle; Shaw, Marvin D; Harrison, Terry; Domínguez-Rodrigo, Manuel; MacPhee, Ross DE; Kwekason, Amandus; Ecker, Michaela; Kolska Horwitz, Liora; Chazan, Michael; Kröger, Roland; Thomas-Oates, Jane; Harding, John H; Cappellini, Enrico; Penkman, Kirsty; Collins, Matthew J

2016-01-01

Proteins persist longer in the fossil record than DNA, but the longevity, survival mechanisms and substrates remain contested. Here, we demonstrate the role of mineral binding in preserving the protein sequence in ostrich (Struthionidae) eggshell, including from the palaeontological sites 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 sequence (equivalent to ~16 Ma at a constant 10°C). DOI: http://dx.doi.org/10.7554/eLife.17092.001 PMID:27668515

Evolutionary and biophysical relationships among the papillomavirus E2 proteins.

PubMed

Blakaj, Dukagjin M; Fernandez-Fuentes, Narcis; Chen, Zigui; Hegde, Rashmi; Fiser, Andras; Burk, Robert D; Brenowitz, Michael

2009-01-01

Infection by human papillomavirus (HPV) may result in clinical conditions ranging from benign warts to invasive cancer. The HPV E2 protein represses oncoprotein transcription and is required for viral replication. HPV E2 binds to palindromic DNA sequences of highly conserved four base pair sequences flanking an identical length variable 'spacer'. E2 proteins directly contact the conserved but not the spacer DNA. Variation in naturally occurring spacer sequences results in differential protein affinity that is dependent on their sensitivity to the spacer DNA's unique conformational and/or dynamic properties. This article explores the biophysical character of this core viral protein with the goal of identifying characteristics that associated with risk of virally caused malignancy. The amino acid sequence, 3d structure and electrostatic features of the E2 protein DNA binding domain are highly conserved; specific interactions with DNA binding sites have also been conserved. In contrast, the E2 protein's transactivation domain does not have extensive surfaces of highly conserved residues. Rather, regions of high conservation are localized to small surface patches. Implications to cancer biology are discussed.

Sequence analyses and evolutionary relationships among the energy-coupling proteins Enzyme I and HPr of the bacterial phosphoenolpyruvate: sugar phosphotransferase system.

PubMed Central

Reizer, J.; Hoischen, C.; Reizer, A.; Pham, T. N.; Saier, M. H.

1993-01-01

We have previously reported the overexpression, purification, and biochemical properties of the Bacillus subtilis Enzyme I of the phosphoenolpyruvate: sugar phosphotransferase system (PTS) (Reizer, J., et al., 1992, J. Biol. Chem. 267, 9158-9169). We now report the sequencing of the ptsI gene of B. subtilis encoding Enzyme I (570 amino acids and 63,076 Da). Putative transcriptional regulatory signals are identified, and the pts operon is shown to be subject to carbon source-dependent regulation. Multiple alignments of the B. subtilis Enzyme I with (1) six other sequenced Enzymes I of the PTS from various bacterial species, (2) phosphoenolpyruvate synthase of Escherichia coli, and (3) bacterial and plant pyruvate: phosphate dikinases (PPDKs) revealed regions of sequence similarity as well as divergence. Statistical analyses revealed that these three types of proteins comprise a homologous family, and the phylogenetic tree of the 11 sequenced protein members of this family was constructed. This tree was compared with that of the 12 sequence HPr proteins or protein domains. Antibodies raised against the B. subtilis and E. coli Enzymes I exhibited immunological cross-reactivity with each other as well as with PPDK of Bacteroides symbiosus, providing support for the evolutionary relationships of these proteins suggested from the sequence comparisons. Putative flexible linkers tethering the N-terminal and the C-terminal domains of protein members of the Enzyme I family were identified, and their potential significance with regard to Enzyme I function is discussed. The codon choice pattern of the B. subtilis and E. coli ptsI and ptsH genes was found to exhibit a bias toward optimal codons in these organisms.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:7686067

Expressed sequence tags from the oomycete fish pathogen Saprolegnia parasitica reveal putative virulence factors

PubMed Central

Torto-Alalibo, Trudy; Tian, Miaoying; Gajendran, Kamal; Waugh, Mark E; van West, Pieter; Kamoun, Sophien

2005-01-01

Background The oomycete Saprolegnia parasitica is one of the most economically important fish pathogens. There is a dramatic recrudescence of Saprolegnia infections in aquaculture since the use of the toxic organic dye malachite green was banned in 2002. Little is known about the molecular mechanisms underlying pathogenicity in S. parasitica and other animal pathogenic oomycetes. In this study we used a genomics approach to gain a first insight into the transcriptome of S. parasitica. Results We generated 1510 expressed sequence tags (ESTs) from a mycelial cDNA library of S. parasitica. A total of 1279 consensus sequences corresponding to 525944 base pairs were assembled. About half of the unigenes showed similarities to known protein sequences or motifs. The S. parasitica sequences tended to be relatively divergent from Phytophthora sequences. Based on the sequence alignments of 18 conserved proteins, the average amino acid identity between S. parasitica and three Phytophthora species was 77% compared to 93% within Phytophthora. Several S. parasitica cDNAs, such as those with similarity to fungal type I cellulose binding domain proteins, PAN/Apple module proteins, glycosyl hydrolases, proteases, as well as serine and cysteine protease inhibitors, were predicted to encode secreted proteins that could function in virulence. Some of these cDNAs were more similar to fungal proteins than to other eukaryotic proteins confirming that oomycetes and fungi share some virulence components despite their evolutionary distance Conclusion We provide a first glimpse into the gene content of S. parasitica, a reemerging oomycete fish pathogen. These resources will greatly accelerate research on this important pathogen. The data is available online through the Oomycete Genomics Database [1]. PMID:16076392

A strategy for detecting the conservation of folding-nucleus residues in protein superfamilies.

PubMed

Michnick, S W; Shakhnovich, E

1998-01-01

Nucleation-growth theory predicts that fast-folding peptide sequences fold to their native structure via structures in a transition-state ensemble that share a small number of native contacts (the folding nucleus). Experimental and theoretical studies of proteins suggest that residues participating in folding nuclei are conserved among homologs. We attempted to determine if this is true in proteins with highly diverged sequences but identical folds (superfamilies). We describe a strategy based on comparisons of residue conservation in natural superfamily sequences with simulated sequences (generated with a Monte-Carlo sequence design strategy) for the same proteins. The basic assumptions of the strategy were that natural sequences will conserve residues needed for folding and stability plus function, the simulated sequences contain no functional conservation, and nucleus residues make native contacts with each other. Based on these assumptions, we identified seven potential nucleus residues in ubiquitin superfamily members. Non-nucleus conserved residues were also identified; these are proposed to be involved in stabilizing native interactions. We found that all superfamily members conserved the same potential nucleus residue positions, except those for which the structural topology is significantly different. Our results suggest that the conservation of the nucleus of a specific fold can be predicted by comparing designed simulated sequences with natural highly diverged sequences that fold to the same structure. We suggest that such a strategy could be used to help plan protein folding and design experiments, to identify new superfamily members, and to subdivide superfamilies further into classes having a similar folding mechanism.

Structural and functional analysis of an enhancer GPEI having a phorbol 12-O-tetradecanoate 13-acetate responsive element-like sequence found in the rat glutathione transferase P gene.

PubMed

Okuda, A; Imagawa, M; Maeda, Y; Sakai, M; Muramatsu, M

1989-10-05

We have recently identified a typical enhancer, termed GPEI, located about 2.5 kilobases upstream from the transcription initiation site of the rat glutathione transferase P gene. Analyses of 5' and 3' deletion mutants revealed that the cis-acting sequence of GPEI contained the phorbol 12-O-tetradecanoate 13-acetate responsive element (TRE)-like sequence in it. For the maximal activity, however, GPEI required an adjacent upstream sequence of about 19 base pairs in addition to the TRE-like sequence. With the DNA binding gel-shift assay, we could detect protein(s) that specifically binds to the TRE-like sequence of GPEI fragment, which was possibly c-jun.c-fos complex or a similar protein complex. The sequence immediately upstream of the TRE-like sequence did not have any activity by itself, but augmented the latter activity by about 5-fold.

Recominant Pinoresino-Lariciresinol Reductase, Recombinant Dirigent Protein And Methods Of Use

DOEpatents

Lewis, Norman G.; Davin, Laurence B.; Dinkova-Kostova, Albena T.; Fujita, Masayuki , Gang; David R. , Sarkanen; Simo , Ford; Joshua D.

2003-10-21

Dirigent proteins and pinoresinol/lariciresinol reductases have been isolated, together with cDNAs encoding dirigent proteins and pinoresinol/lariciresinol reductases. Accordingly, isolated DNA sequences are provided from source species Forsythia intermedia, Thuja plicata, Tsuga heterophylla, Eucommia ulmoides, Linum usitatissimum, and Schisandra chinensis, which code for the expression of dirigent proteins and pinoresinol/lariciresinol reductases. In other aspects, replicable recombinant cloning vehicles are provided which code for dirigent proteins or pinoresinol/lariciresinol reductases or for a base sequence sufficiently complementary to at least a portion of dirigent protein or pinoresinol/lariciresinol reductase DNA or RNA to enable hybridization therewith. In yet other aspects, modified host cells are provided that have been transformed, transfected, infected and/or injected with a recombinant cloning vehicle and/or DNA sequence encoding dirigent protein or pinoresinol/lariciresinol reductase. Thus, systems and methods are provided for the recombinant expression of dirigent proteins and/or pinoresinol/lariciresinol reductases.

Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding.

PubMed

Shahi, Payam; Kim, Samuel C; Haliburton, John R; Gartner, Zev J; Abate, Adam R

2017-03-14

Proteins are the primary effectors of cellular function, including cellular metabolism, structural dynamics, and information processing. However, quantitative characterization of proteins at the single-cell level is challenging due to the tiny amount of protein available. Here, we present Abseq, a method to detect and quantitate proteins in single cells at ultrahigh throughput. Like flow and mass cytometry, Abseq uses specific antibodies to detect epitopes of interest; however, unlike these methods, antibodies are labeled with sequence tags that can be read out with microfluidic barcoding and DNA sequencing. We demonstrate this novel approach by characterizing surface proteins of different cell types at the single-cell level and distinguishing between the cells by their protein expression profiles. DNA-tagged antibodies provide multiple advantages for profiling proteins in single cells, including the ability to amplify low-abundance tags to make them detectable with sequencing, to use molecular indices for quantitative results, and essentially limitless multiplexing.

Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding

NASA Astrophysics Data System (ADS)

Shahi, Payam; Kim, Samuel C.; Haliburton, John R.; Gartner, Zev J.; Abate, Adam R.

2017-03-01

Proteins are the primary effectors of cellular function, including cellular metabolism, structural dynamics, and information processing. However, quantitative characterization of proteins at the single-cell level is challenging due to the tiny amount of protein available. Here, we present Abseq, a method to detect and quantitate proteins in single cells at ultrahigh throughput. Like flow and mass cytometry, Abseq uses specific antibodies to detect epitopes of interest; however, unlike these methods, antibodies are labeled with sequence tags that can be read out with microfluidic barcoding and DNA sequencing. We demonstrate this novel approach by characterizing surface proteins of different cell types at the single-cell level and distinguishing between the cells by their protein expression profiles. DNA-tagged antibodies provide multiple advantages for profiling proteins in single cells, including the ability to amplify low-abundance tags to make them detectable with sequencing, to use molecular indices for quantitative results, and essentially limitless multiplexing.

Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding

PubMed Central

Shahi, Payam; Kim, Samuel C.; Haliburton, John R.; Gartner, Zev J.; Abate, Adam R.

2017-01-01

Proteins are the primary effectors of cellular function, including cellular metabolism, structural dynamics, and information processing. However, quantitative characterization of proteins at the single-cell level is challenging due to the tiny amount of protein available. Here, we present Abseq, a method to detect and quantitate proteins in single cells at ultrahigh throughput. Like flow and mass cytometry, Abseq uses specific antibodies to detect epitopes of interest; however, unlike these methods, antibodies are labeled with sequence tags that can be read out with microfluidic barcoding and DNA sequencing. We demonstrate this novel approach by characterizing surface proteins of different cell types at the single-cell level and distinguishing between the cells by their protein expression profiles. DNA-tagged antibodies provide multiple advantages for profiling proteins in single cells, including the ability to amplify low-abundance tags to make them detectable with sequencing, to use molecular indices for quantitative results, and essentially limitless multiplexing. PMID:28290550

[Cloning, sequencing and prokaryotic expression of cDNAs for the antifreeze protein family from the beetle Tenebrio molitor].

PubMed

Liu, Zhong-Yuan; Wang, Yun; Lü, Guo-Dong; Wang, Xian-Lei; Zhang, Fu-Chun; Ma, Ji

2006-12-01

The partial cDNA sequence coding for the antifreeze proteins in the Tenebrio molitor was obtained by RT-PCR. Sequence analysis revealed nine putative cDNAs with a high degree of homology to Tenebrio molitor antifreeze proteins. The recombinant pGEX-4T-1-tmafp-XJ430 was introduced into E. coli BL21 to induce a GST fusion protein by IPTG. SDS-PAGE of the fusion protein demonstrated that the antifreeze protein migrated at a size of 38 kDa. The immunization was performed by intra-muscular injection of pCDNA3-tmafp-XJ430, and then antiserum was detected by ELISA. The titer of the antibody was 1:2,000. Western blotting analysis showed the antiserum was specific against the antifreeze protein. This finding could lead to further investigation of the properties and function of antifreeze proteins.

Computational protein design: validation and possible relevance as a tool for homology searching and fold recognition.

PubMed

Schmidt Am Busch, Marcel; Sedano, Audrey; Simonson, Thomas

2010-05-05

Protein fold recognition usually relies on a statistical model of each fold; each model is constructed from an ensemble of natural sequences belonging to that fold. A complementary strategy may be to employ sequence ensembles produced by computational protein design. Designed sequences can be more diverse than natural sequences, possibly avoiding some limitations of experimental databases. WE EXPLORE THIS STRATEGY FOR FOUR SCOP FAMILIES: Small Kunitz-type inhibitors (SKIs), Interleukin-8 chemokines, PDZ domains, and large Caspase catalytic subunits, represented by 43 structures. An automated procedure is used to redesign the 43 proteins. We use the experimental backbones as fixed templates in the folded state and a molecular mechanics model to compute the interaction energies between sidechain and backbone groups. Calculations are done with the Proteins@Home volunteer computing platform. A heuristic algorithm is used to scan the sequence and conformational space, yielding 200,000-300,000 sequences per backbone template. The results confirm and generalize our earlier study of SH2 and SH3 domains. The designed sequences ressemble moderately-distant, natural homologues of the initial templates; e.g., the SUPERFAMILY, profile Hidden-Markov Model library recognizes 85% of the low-energy sequences as native-like. Conversely, Position Specific Scoring Matrices derived from the sequences can be used to detect natural homologues within the SwissProt database: 60% of known PDZ domains are detected and around 90% of known SKIs and chemokines. Energy components and inter-residue correlations are analyzed and ways to improve the method are discussed. For some families, designed sequences can be a useful complement to experimental ones for homologue searching. However, improved tools are needed to extract more information from the designed profiles before the method can be of general use.

Differential protein expression in alligator leukocytes in response to bacterial lipopolysaccharide injection.

PubMed

Merchant, Mark; Kinney, Clint; Sanders, Paige

2009-12-01

Blood was collected from three juvenile alligators (Alligator mississippiensis) before, and again 24h after, injection with bacterial lipopolysaccharide (LPS). The leukocytes were collected from both samples, and the proteins were extracted. Each group of proteins was labeled with a different fluorescent dye and the differences in protein expression were analyzed by two dimensional differential in-gel expressions (2D-DIGE). The proteins which appeared to be increased or decreased by treatment with LPS were selected and analyzed by MALDI-TOF to determine mass and LC-MS/MS to acquire the partial protein sequences. The peptide sequences were compared to the NCBI protein sequence database to determine homology with other sequences from other species. Several proteins of interest appeared to be increased upon LPS stimulation. Proteins with homology to human transgelin-2, fish glucose-6-phosphate dehydrogenase, amphibian α-enolase, alligator lactate dehydrogenase, fish ubiquitin-activating enzyme, and fungal β-tubulin were also increased after LPS injection. Proteins with homology to fish vimentin 4, murine heterogeneous nuclear ribonucleoprotein A3, and avian calreticulin were found to be decreased in response to LPS. In addition, five proteins, four of which were up-regulated (827, 560, 512, and 650%) and one that exhibited repressed expression (307%), did not show homology to any protein in the database, and thus may represent newly discovered proteins. We are using this biochemical approach to isolate and characterize alligator proteins with potential relevant immune function.

The VP35 and VP40 proteins of filoviruses. Homology between Marburg and Ebola viruses.

PubMed

Bukreyev, A A; Volchkov, V E; Blinov, V M; Netesov, S V

1993-05-03

The fragments of genomic RNA sequences of Marburg (MBG) and Ebola (EBO) viruses are reported. These fragments were found to encode the VP35 and VP40 proteins. The canonic sequences were revealed before and after each open reading frame. It is suggested that these sequences are mRNA extremities and at the same time the regulatory elements for mRNA transcription. Homology between the MBG and EBO proteins was discovered.

Protein location prediction using atomic composition and global features of the amino acid sequence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cherian, Betsy Sheena, E-mail: betsy.skb@gmail.com; Nair, Achuthsankar S.

2010-01-22

Subcellular location of protein is constructive information in determining its function, screening for drug candidates, vaccine design, annotation of gene products and in selecting relevant proteins for further studies. Computational prediction of subcellular localization deals with predicting the location of a protein from its amino acid sequence. For a computational localization prediction method to be more accurate, it should exploit all possible relevant biological features that contribute to the subcellular localization. In this work, we extracted the biological features from the full length protein sequence to incorporate more biological information. A new biological feature, distribution of atomic composition is effectivelymore » used with, multiple physiochemical properties, amino acid composition, three part amino acid composition, and sequence similarity for predicting the subcellular location of the protein. Support Vector Machines are designed for four modules and prediction is made by a weighted voting system. Our system makes prediction with an accuracy of 100, 82.47, 88.81 for self-consistency test, jackknife test and independent data test respectively. Our results provide evidence that the prediction based on the biological features derived from the full length amino acid sequence gives better accuracy than those derived from N-terminal alone. Considering the features as a distribution within the entire sequence will bring out underlying property distribution to a greater detail to enhance the prediction accuracy.« less

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.

PubMed

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.

Protein structure and the sequential structure of mRNA: alpha-helix and beta-sheet signals at the nucleotide level.

PubMed

Brunak, S; Engelbrecht, J

1996-06-01

A direct comparison of experimentally determined protein structures and their corresponding protein coding mRNA sequences has been performed. We examine whether real world data support the hypothesis that clusters of rare codons correlate with the location of structural units in the resulting protein. The degeneracy of the genetic code allows for a biased selection of codons which may control the translational rate of the ribosome, and may thus in vivo have a catalyzing effect on the folding of the polypeptide chain. A complete search for GenBank nucleotide sequences coding for structural entries in the Brookhaven Protein Data Bank produced 719 protein chains with matching mRNA sequence, amino acid sequence, and secondary structure assignment. By neural network analysis, we found strong signals in mRNA sequence regions surrounding helices and sheets. These signals do not originate from the clustering of rare codons, but from the similarity of codons coding for very abundant amino acid residues at the N- and C-termini of helices and sheets. No correlation between the positioning of rare codons and the location of structural units was found. The mRNA signals were also compared with conserved nucleotide features of 16S-like ribosomal RNA sequences and related to mechanisms for maintaining the correct reading frame by the ribosome.

An ensemble approach for large-scale identification of protein-protein interactions using the alignments of multiple sequences

PubMed Central

Wang, Lei; You, Zhu-Hong; Chen, Xing; Li, Jian-Qiang; Yan, Xin; Zhang, Wei; Huang, Yu-An

2017-01-01

Protein–Protein Interactions (PPI) is not only the critical component of various biological processes in cells, but also the key to understand the mechanisms leading to healthy and diseased states in organisms. However, it is time-consuming and cost-intensive to identify the interactions among proteins using biological experiments. Hence, how to develop a more efficient computational method rapidly became an attractive topic in the post-genomic era. In this paper, we propose a novel method for inference of protein-protein interactions from protein amino acids sequences only. Specifically, protein amino acids sequence is firstly transformed into Position-Specific Scoring Matrix (PSSM) generated by multiple sequences alignments; then the Pseudo PSSM is used to extract feature descriptors. Finally, ensemble Rotation Forest (RF) learning system is trained to predict and recognize PPIs based solely on protein sequence feature. When performed the proposed method on the three benchmark data sets (Yeast, H. pylori, and independent dataset) for predicting PPIs, our method can achieve good average accuracies of 98.38%, 89.75%, and 96.25%, respectively. In order to further evaluate the prediction performance, we also compare the proposed method with other methods using same benchmark data sets. The experiment results demonstrate that the proposed method consistently outperforms other state-of-the-art method. Therefore, our method is effective and robust and can be taken as a useful tool in exploring and discovering new relationships between proteins. A web server is made publicly available at the URL http://202.119.201.126:8888/PsePSSM/ for academic use. PMID:28029645

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

PubMed

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.

Modularity of Protein Folds as a Tool for Template-Free Modeling of Structures.

PubMed

Vallat, Brinda; Madrid-Aliste, Carlos; Fiser, Andras

2015-08-01

Predicting the three-dimensional structure of proteins from their amino acid sequences remains a challenging problem in molecular biology. While the current structural coverage of proteins is almost exclusively provided by template-based techniques, the modeling of the rest of the protein sequences increasingly require template-free methods. However, template-free modeling methods are much less reliable and are usually applicable for smaller proteins, leaving much space for improvement. We present here a novel computational method that uses a library of supersecondary structure fragments, known as Smotifs, to model protein structures. The library of Smotifs has saturated over time, providing a theoretical foundation for efficient modeling. The method relies on weak sequence signals from remotely related protein structures to create a library of Smotif fragments specific to the target protein sequence. This Smotif library is exploited in a fragment assembly protocol to sample decoys, which are assessed by a composite scoring function. Since the Smotif fragments are larger in size compared to the ones used in other fragment-based methods, the proposed modeling algorithm, SmotifTF, can employ an exhaustive sampling during decoy assembly. SmotifTF successfully predicts the overall fold of the target proteins in about 50% of the test cases and performs competitively when compared to other state of the art prediction methods, especially when sequence signal to remote homologs is diminishing. Smotif-based modeling is complementary to current prediction methods and provides a promising direction in addressing the structure prediction problem, especially when targeting larger proteins for modeling.

Determinants of the rate of protein sequence evolution

PubMed Central

Zhang, Jianzhi; Yang, Jian-Rong

2015-01-01

The rate and mechanism of protein sequence evolution have been central questions in evolutionary biology since the 1960s. Although the rate of protein sequence evolution depends primarily on the level of functional constraint, exactly what constitutes functional constraint has remained unclear. The increasing availability of genomic data has allowed for much needed empirical examinations on the nature of functional constraint. These studies found that the evolutionary rate of a protein is predominantly influenced by its expression level rather than functional importance. A combination of theoretical and empirical analyses have identified multiple mechanisms behind these observations and demonstrated a prominent role that selection against errors in molecular and cellular processes plays in protein evolution. PMID:26055156

Conservation and diversification of Msx protein in metazoan evolution.

PubMed

Takahashi, Hirokazu; Kamiya, Akiko; Ishiguro, Akira; Suzuki, Atsushi C; Saitou, Naruya; Toyoda, Atsushi; Aruga, Jun

2008-01-01

Msx (/msh) family genes encode homeodomain (HD) proteins that control ontogeny in many animal species. We compared the structures of Msx genes from a wide range of Metazoa (Porifera, Cnidaria, Nematoda, Arthropoda, Tardigrada, Platyhelminthes, Mollusca, Brachiopoda, Annelida, Echiura, Echinodermata, Hemichordata, and Chordata) to gain an understanding of the role of these genes in phylogeny. Exon-intron boundary analysis suggested that the position of the intron located N-terminally to the HDs was widely conserved in all the genes examined, including those of cnidarians. Amino acid (aa) sequence comparison revealed 3 new evolutionarily conserved domains, as well as very strong conservation of the HDs. Two of the three domains were associated with Groucho-like protein binding in both a vertebrate and a cnidarian Msx homolog, suggesting that the interaction between Groucho-like proteins and Msx proteins was established in eumetazoan ancestors. Pairwise comparison among the collected HDs and their C-flanking aa sequences revealed that the degree of sequence conservation varied depending on the animal taxa from which the sequences were derived. Highly conserved Msx genes were identified in the Vertebrata, Cephalochordata, Hemichordata, Echinodermata, Mollusca, Brachiopoda, and Anthozoa. The wide distribution of the conserved sequences in the animal phylogenetic tree suggested that metazoan ancestors had already acquired a set of conserved domains of the current Msx family genes. Interestingly, although strongly conserved sequences were recovered from the Vertebrata, Cephalochordata, and Anthozoa, the sequences from the Urochordata and Hydrozoa showed weak conservation. Because the Vertebrata-Cephalochordata-Urochordata and Anthozoa-Hydrozoa represent sister groups in the Chordata and Cnidaria, respectively, Msx sequence diversification may have occurred differentially in the course of evolution. We speculate that selective loss of the conserved domains in Msx family proteins contributed to the diversification of animal body organization.

Mining for class-specific motifs in protein sequence classification

PubMed Central

2013-01-01

Background In protein sequence classification, identification of the sequence motifs or n-grams that can precisely discriminate between classes is a more interesting scientific question than the classification itself. A number of classification methods aim at accurate classification but fail to explain which sequence features indeed contribute to the accuracy. We hypothesize that sequences in lower denominations (n-grams) can be used to explore the sequence landscape and to identify class-specific motifs that discriminate between classes during classification. Discriminative n-grams are short peptide sequences that are highly frequent in one class but are either minimally present or absent in other classes. In this study, we present a new substitution-based scoring function for identifying discriminative n-grams that are highly specific to a class. Results We present a scoring function based on discriminative n-grams that can effectively discriminate between classes. The scoring function, initially, harvests the entire set of 4- to 8-grams from the protein sequences of different classes in the dataset. Similar n-grams of the same size are combined to form new n-grams, where the similarity is defined by positive amino acid substitution scores in the BLOSUM62 matrix. Substitution has resulted in a large increase in the number of discriminatory n-grams harvested. Due to the unbalanced nature of the dataset, the frequencies of the n-grams are normalized using a dampening factor, which gives more weightage to the n-grams that appear in fewer classes and vice-versa. After the n-grams are normalized, the scoring function identifies discriminative 4- to 8-grams for each class that are frequent enough to be above a selection threshold. By mapping these discriminative n-grams back to the protein sequences, we obtained contiguous n-grams that represent short class-specific motifs in protein sequences. Our method fared well compared to an existing motif finding method known as Wordspy. We have validated our enriched set of class-specific motifs against the functionally important motifs obtained from the NLSdb, Prosite and ELM databases. We demonstrate that this method is very generic; thus can be widely applied to detect class-specific motifs in many protein sequence classification tasks. Conclusion The proposed scoring function and methodology is able to identify class-specific motifs using discriminative n-grams derived from the protein sequences. The implementation of amino acid substitution scores for similarity detection, and the dampening factor to normalize the unbalanced datasets have significant effect on the performance of the scoring function. Our multipronged validation tests demonstrate that this method can detect class-specific motifs from a wide variety of protein sequence classes with a potential application to detecting proteome-specific motifs of different organisms. PMID:23496846

Conservation of hot regions in protein-protein interaction in evolution.

PubMed

Hu, Jing; Li, Jiarui; Chen, Nansheng; Zhang, Xiaolong

2016-11-01

The hot regions of protein-protein interactions refer to the active area which formed by those most important residues to protein combination process. With the research development on protein interactions, lots of predicted hot regions can be discovered efficiently by intelligent computing methods, while performing biology experiments to verify each every prediction is hardly to be done due to the time-cost and the complexity of the experiment. This study based on the research of hot spot residue conservations, the proposed method is used to verify authenticity of predicted hot regions that using machine learning algorithm combined with protein's biological features and sequence conservation, though multiple sequence alignment, module substitute matrix and sequence similarity to create conservation scoring algorithm, and then using threshold module to verify the conservation tendency of hot regions in evolution. This research work gives an effective method to verify predicted hot regions in protein-protein interactions, which also provides a useful way to deeply investigate the functional activities of protein hot regions. Copyright © 2016. Published by Elsevier Inc.

Design, production and molecular structure of a new family of artificial alpha-helicoidal repeat proteins (αRep) based on thermostable HEAT-like repeats.

PubMed

Urvoas, Agathe; Guellouz, Asma; Valerio-Lepiniec, Marie; Graille, Marc; Durand, Dominique; Desravines, Danielle C; van Tilbeurgh, Herman; Desmadril, Michel; Minard, Philippe

2010-11-26

Repeat proteins have a modular organization and a regular architecture that make them attractive models for design and directed evolution experiments. HEAT repeat proteins, although very common, have not been used as a scaffold for artificial proteins, probably because they are made of long and irregular repeats. Here, we present and validate a consensus sequence for artificial HEAT repeat proteins. The sequence was defined from the structure-based sequence analysis of a thermostable HEAT-like repeat protein. Appropriate sequences were identified for the N- and C-caps. A library of genes coding for artificial proteins based on this sequence design, named αRep, was assembled using new and versatile methodology based on circular amplification. Proteins picked randomly from this library are expressed as soluble proteins. The biophysical properties of proteins with different numbers of repeats and different combinations of side chains in hypervariable positions were characterized. Circular dichroism and differential scanning calorimetry experiments showed that all these proteins are folded cooperatively and are very stable (T(m) >70 °C). Stability of these proteins increases with the number of repeats. Detailed gel filtration and small-angle X-ray scattering studies showed that the purified proteins form either monomers or dimers. The X-ray structure of a stable dimeric variant structure was solved. The protein is folded with a highly regular topology and the repeat structure is organized, as expected, as pairs of alpha helices. In this protein variant, the dimerization interface results directly from the variable surface enriched in aromatic residues located in the randomized positions of the repeats. The dimer was crystallized both in an apo and in a PEG-bound form, revealing a very well defined binding crevice and some structure flexibility at the interface. This fortuitous binding site could later prove to be a useful binding site for other low molecular mass partners. Copyright © 2010 Elsevier Ltd. All rights reserved.

Characterization of an AGAMOUS-like MADS Box Protein, a Probable Constituent of Flowering and Fruit Ripening Regulatory System in Banana

PubMed Central

Roy Choudhury, Swarup; Roy, Sujit; Nag, Anish; Singh, Sanjay Kumar; Sengupta, Dibyendu N.

2012-01-01

The MADS-box family of genes has been shown to play a significant role in the development of reproductive organs, including dry and fleshy fruits. In this study, the molecular properties of an AGAMOUS like MADS box transcription factor in banana cultivar Giant governor (Musa sp, AAA group, subgroup Cavendish) has been elucidated. We have detected a CArG-box sequence binding AGAMOUS MADS-box protein in banana flower and fruit nuclear extracts in DNA-protein interaction assays. The protein fraction in the DNA-protein complex was analyzed by mass spectrometry and using this information we have obtained the full length cDNA of the corresponding protein. The deduced protein sequence showed ∼95% amino acid sequence homology with MA-MADS5, a MADS-box protein described previously from banana. We have characterized the domains of the identified AGAMOUS MADS-box protein involved in DNA binding and homodimer formation in vitro using full-length and truncated versions of affinity purified recombinant proteins. Furthermore, in order to gain insight about how DNA bending is achieved by this MADS-box factor, we performed circular permutation and phasing analysis using the wild type recombinant protein. The AGAMOUS MADS-box protein identified in this study has been found to predominantly accumulate in the climacteric fruit pulp and also in female flower ovary. In vivo and in vitro assays have revealed specific binding of the identified AGAMOUS MADS-box protein to CArG-box sequence in the promoters of major ripening genes in banana fruit. Overall, the expression patterns of this MADS-box protein in banana female flower ovary and during various phases of fruit ripening along with the interaction of the protein to the CArG-box sequence in the promoters of major ripening genes lead to interesting assumption about the possible involvement of this AGAMOUS MADS-box factor in banana fruit ripening and floral reproductive organ development. PMID:22984496

Characterization of an AGAMOUS-like MADS box protein, a probable constituent of flowering and fruit ripening regulatory system in banana.

PubMed

Roy Choudhury, Swarup; Roy, Sujit; Nag, Anish; Singh, Sanjay Kumar; Sengupta, Dibyendu N

2012-01-01

The MADS-box family of genes has been shown to play a significant role in the development of reproductive organs, including dry and fleshy fruits. In this study, the molecular properties of an AGAMOUS like MADS box transcription factor in banana cultivar Giant governor (Musa sp, AAA group, subgroup Cavendish) has been elucidated. We have detected a CArG-box sequence binding AGAMOUS MADS-box protein in banana flower and fruit nuclear extracts in DNA-protein interaction assays. The protein fraction in the DNA-protein complex was analyzed by mass spectrometry and using this information we have obtained the full length cDNA of the corresponding protein. The deduced protein sequence showed ~95% amino acid sequence homology with MA-MADS5, a MADS-box protein described previously from banana. We have characterized the domains of the identified AGAMOUS MADS-box protein involved in DNA binding and homodimer formation in vitro using full-length and truncated versions of affinity purified recombinant proteins. Furthermore, in order to gain insight about how DNA bending is achieved by this MADS-box factor, we performed circular permutation and phasing analysis using the wild type recombinant protein. The AGAMOUS MADS-box protein identified in this study has been found to predominantly accumulate in the climacteric fruit pulp and also in female flower ovary. In vivo and in vitro assays have revealed specific binding of the identified AGAMOUS MADS-box protein to CArG-box sequence in the promoters of major ripening genes in banana fruit. Overall, the expression patterns of this MADS-box protein in banana female flower ovary and during various phases of fruit ripening along with the interaction of the protein to the CArG-box sequence in the promoters of major ripening genes lead to interesting assumption about the possible involvement of this AGAMOUS MADS-box factor in banana fruit ripening and floral reproductive organ development.

Exploring representations of protein structure for automated remote homology detection and mapping of protein structure space

PubMed Central

2014-01-01

Background Due to rapid sequencing of genomes, there are now millions of deposited protein sequences with no known function. Fast sequence-based comparisons allow detecting close homologs for a protein of interest to transfer functional information from the homologs to the given protein. Sequence-based comparison cannot detect remote homologs, in which evolution has adjusted the sequence while largely preserving structure. Structure-based comparisons can detect remote homologs but most methods for doing so are too expensive to apply at a large scale over structural databases of proteins. Recently, fragment-based structural representations have been proposed that allow fast detection of remote homologs with reasonable accuracy. These representations have also been used to obtain linearly-reducible maps of protein structure space. It has been shown, as additionally supported from analysis in this paper that such maps preserve functional co-localization of the protein structure space. Methods Inspired by a recent application of the Latent Dirichlet Allocation (LDA) model for conducting structural comparisons of proteins, we propose higher-order LDA-obtained topic-based representations of protein structures to provide an alternative route for remote homology detection and organization of the protein structure space in few dimensions. Various techniques based on natural language processing are proposed and employed to aid the analysis of topics in the protein structure domain. Results We show that a topic-based representation is just as effective as a fragment-based one at automated detection of remote homologs and organization of protein structure space. We conduct a detailed analysis of the information content in the topic-based representation, showing that topics have semantic meaning. The fragment-based and topic-based representations are also shown to allow prediction of superfamily membership. Conclusions This work opens exciting venues in designing novel representations to extract information about protein structures, as well as organizing and mining protein structure space with mature text mining tools. PMID:25080993

First characterization of three cyclophilin family proteins in the oyster, Crassostrea ariakensis Gould.

PubMed

Xu, Ting; Xie, Jiasong; Yang, Shoubao; Ye, Shigen; Luo, Ming; Wu, Xinzhong

2016-08-01

Cyclophilins (CyPs) are a family of proteins that bind the immunosuppressive agent cyclosporin A (CsA) with high-affinity and belong to one of the three superfamilies of peptidyl-prolyl cis-trans isomerases (PPIase). In this report, three cyclophilin genes (Ca-CyPs), including Ca-CyPA, Ca-CyPB and Ca-PPIL3, were identified from oyster, Crassostrea ariakensis Gould in which Ca-CyPA encodes a protein with 165 amino acid sequences, Ca-CyPB encodes a protein with 217 amino acid sequences and Ca-PPIL3 encodes a protein with 162 amino acid sequences. All of the three Ca-CyPs genes contain a typical CyP-PPIase domain with its signature sequences and Ca-CyPB contains an N-signal peptide sequences. Tissue distribution study revealed that Ca-CyPs were ubiquitously expressed in all examined tissues and the highest levels were observed in hemocytes. RLO incubation upregulated the mRNA expression levels of Ca-CyPs, indicating that three Ca-CyPs might be involved in oyster immune response against RLO infection. Copyright © 2016 Elsevier Ltd. All rights reserved.

ProteinWorldDB: querying radical pairwise alignments among protein sets from complete genomes.

PubMed

Otto, Thomas Dan; Catanho, Marcos; Tristão, Cristian; Bezerra, Márcia; Fernandes, Renan Mathias; Elias, Guilherme Steinberger; Scaglia, Alexandre Capeletto; Bovermann, Bill; Berstis, Viktors; Lifschitz, Sergio; de Miranda, Antonio Basílio; Degrave, Wim

2010-03-01

Many analyses in modern biological research are based on comparisons between biological sequences, resulting in functional, evolutionary and structural inferences. When large numbers of sequences are compared, heuristics are often used resulting in a certain lack of accuracy. In order to improve and validate results of such comparisons, we have performed radical all-against-all comparisons of 4 million protein sequences belonging to the RefSeq database, using an implementation of the Smith-Waterman algorithm. This extremely intensive computational approach was made possible with the help of World Community Grid, through the Genome Comparison Project. The resulting database, ProteinWorldDB, which contains coordinates of pairwise protein alignments and their respective scores, is now made available. Users can download, compare and analyze the results, filtered by genomes, protein functions or clusters. ProteinWorldDB is integrated with annotations derived from Swiss-Prot, Pfam, KEGG, NCBI Taxonomy database and gene ontology. The database is a unique and valuable asset, representing a major effort to create a reliable and consistent dataset of cross-comparisons of the whole protein content encoded in hundreds of completely sequenced genomes using a rigorous dynamic programming approach. The database can be accessed through http://proteinworlddb.org

Comparative study of protein unfolding in aqueous urea and dimethyl sulfoxide solutions: surface polarity, solvent specificity, and sequence of secondary structure melting.

PubMed

Roy, Susmita; Bagchi, Biman

2014-05-29

Elucidation of possible pathways between folded (native) and unfolded states of a protein is a challenging task, as the intermediates are often hard to detect. Here, we alter the solvent environment in a controlled manner by choosing two different cosolvents of water, urea, and dimethyl sulfoxide (DMSO) and study unfolding of four different proteins to understand the respective sequence of melting by computer simulation methods. We indeed find interesting differences in the sequence of melting of α helices and β sheets in these two solvents. For example, in 8 M urea solution, β-sheet parts of a protein are found to unfold preferentially, followed by the unfolding of α helices. In contrast, 8 M DMSO solution unfolds α helices first, followed by the separation of β sheets for the majority of proteins. Sequence of unfolding events in four different α/β proteins and also in chicken villin head piece (HP-36) both in urea and DMSO solutions demonstrate that the unfolding pathways are determined jointly by relative exposure of polar and nonpolar residues of a protein and the mode of molecular action of a solvent on that protein.

Programmable DNA-binding proteins from Burkholderia provide a fresh perspective on the TALE-like repeat domain

PubMed Central

de Lange, Orlando; Wolf, Christina; Dietze, Jörn; Elsaesser, Janett; Morbitzer, Robert; Lahaye, Thomas

2014-01-01

The tandem repeats of transcription activator like effectors (TALEs) mediate sequence-specific DNA binding using a simple code. Naturally, TALEs are injected by Xanthomonas bacteria into plant cells to manipulate the host transcriptome. In the laboratory TALE DNA binding domains are reprogrammed and used to target a fused functional domain to a genomic locus of choice. Research into the natural diversity of TALE-like proteins may provide resources for the further improvement of current TALE technology. Here we describe TALE-like proteins from the endosymbiotic bacterium Burkholderia rhizoxinica, termed Bat proteins. Bat repeat domains mediate sequence-specific DNA binding with the same code as TALEs, despite less than 40% sequence identity. We show that Bat proteins can be adapted for use as transcription factors and nucleases and that sequence preferences can be reprogrammed. Unlike TALEs, the core repeats of each Bat protein are highly polymorphic. This feature allowed us to explore alternative strategies for the design of custom Bat repeat arrays, providing novel insights into the functional relevance of non-RVD residues. The Bat proteins offer fertile grounds for research into the creation of improved programmable DNA-binding proteins and comparative insights into TALE-like evolution. PMID:24792163

RNABindRPlus: a predictor that combines machine learning and sequence homology-based methods to improve the reliability of predicted RNA-binding residues in proteins.

PubMed

Walia, Rasna R; Xue, Li C; Wilkins, Katherine; El-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2014-01-01

Protein-RNA interactions are central to essential cellular processes such as protein synthesis and regulation of gene expression and play roles in human infectious and genetic diseases. Reliable identification of protein-RNA interfaces is critical for understanding the structural bases and functional implications of such interactions and for developing effective approaches to rational drug design. Sequence-based computational methods offer a viable, cost-effective way to identify putative RNA-binding residues in RNA-binding proteins. Here we report two novel approaches: (i) HomPRIP, a sequence homology-based method for predicting RNA-binding sites in proteins; (ii) RNABindRPlus, a new method that combines predictions from HomPRIP with those from an optimized Support Vector Machine (SVM) classifier trained on a benchmark dataset of 198 RNA-binding proteins. Although highly reliable, HomPRIP cannot make predictions for the unaligned parts of query proteins and its coverage is limited by the availability of close sequence homologs of the query protein with experimentally determined RNA-binding sites. RNABindRPlus overcomes these limitations. We compared the performance of HomPRIP and RNABindRPlus with that of several state-of-the-art predictors on two test sets, RB44 and RB111. On a subset of proteins for which homologs with experimentally determined interfaces could be reliably identified, HomPRIP outperformed all other methods achieving an MCC of 0.63 on RB44 and 0.83 on RB111. RNABindRPlus was able to predict RNA-binding residues of all proteins in both test sets, achieving an MCC of 0.55 and 0.37, respectively, and outperforming all other methods, including those that make use of structure-derived features of proteins. More importantly, RNABindRPlus outperforms all other methods for any choice of tradeoff between precision and recall. An important advantage of both HomPRIP and RNABindRPlus is that they rely on readily available sequence and sequence-derived features of RNA-binding proteins. A webserver implementation of both methods is freely available at http://einstein.cs.iastate.edu/RNABindRPlus/.

Analysis of Epstein-Barr Virus Genomes and Expression Profiles in Gastric Adenocarcinoma.

PubMed

Borozan, Ivan; Zapatka, Marc; Frappier, Lori; Ferretti, Vincent

2018-01-15

Epstein-Barr virus (EBV) is a causative agent of a variety of lymphomas, nasopharyngeal carcinoma (NPC), and ∼9% of gastric carcinomas (GCs). An important question is whether particular EBV variants are more oncogenic than others, but conclusions are currently hampered by the lack of sequenced EBV genomes. Here, we contribute to this question by mining whole-genome sequences of 201 GCs to identify 13 EBV-positive GCs and by assembling 13 new EBV genome sequences, almost doubling the number of available GC-derived EBV genome sequences and providing the first non-Asian EBV genome sequences from GC. Whole-genome sequence comparisons of all EBV isolates sequenced to date (85 from tumors and 57 from healthy individuals) showed that most GC and NPC EBV isolates were closely related although American Caucasian GC samples were more distant, suggesting a geographical component. However, EBV GC isolates were found to contain some consistent changes in protein sequences regardless of geographical origin. In addition, transcriptome data available for eight of the EBV-positive GCs were analyzed to determine which EBV genes are expressed in GC. In addition to the expected latency proteins (EBNA1, LMP1, and LMP2A), specific subsets of lytic genes were consistently expressed that did not reflect a typical lytic or abortive lytic infection, suggesting a novel mechanism of EBV gene regulation in the context of GC. These results are consistent with a model in which a combination of specific latent and lytic EBV proteins promotes tumorigenesis. IMPORTANCE Epstein-Barr virus (EBV) is a widespread virus that causes cancer, including gastric carcinoma (GC), in a small subset of individuals. An important question is whether particular EBV variants are more cancer associated than others, but more EBV sequences are required to address this question. Here, we have generated 13 new EBV genome sequences from GC, almost doubling the number of EBV sequences from GC isolates and providing the first EBV sequences from non-Asian GC. We further identify sequence changes in some EBV proteins common to GC isolates. In addition, gene expression analysis of eight of the EBV-positive GCs showed consistent expression of both the expected latency proteins and a subset of lytic proteins that was not consistent with typical lytic or abortive lytic expression. These results suggest that novel mechanisms activate expression of some EBV lytic proteins and that their expression may contribute to oncogenesis. Copyright © 2018 American Society for Microbiology.

Cazymes Analysis Toolkit (CAT): Webservice for searching and analyzing carbohydrateactive enzymes in a newly sequenced organism using CAZy database

DOE Office of Scientific and Technical Information (OSTI.GOV)

Karpinets, Tatiana V; Park, Byung; Syed, Mustafa H

2010-01-01

The Carbohydrate-Active Enzyme (CAZy) database provides a rich set of manually annotated enzymes that degrade, modify, or create glycosidic bonds. Despite rich and invaluable information stored in the database, software tools utilizing this information for annotation of newly sequenced genomes by CAZy families are limited. We have employed two annotation approaches to fill the gap between manually curated high-quality protein sequences collected in the CAZy database and the growing number of other protein sequences produced by genome or metagenome sequencing projects. The first approach is based on a similarity search against the entire non-redundant sequences of the CAZy database. Themore » second approach performs annotation using links or correspondences between the CAZy families and protein family domains. The links were discovered using the association rule learning algorithm applied to sequences from the CAZy database. The approaches complement each other and in combination achieved high specificity and sensitivity when cross-evaluated with the manually curated genomes of Clostridium thermocellum ATCC 27405 and Saccharophagus degradans 2-40. The capability of the proposed framework to predict the function of unknown protein domains (DUF) and of hypothetical proteins in the genome of Neurospora crassa is demonstrated. The framework is implemented as a Web service, the CAZymes Analysis Toolkit (CAT), and is available at http://cricket.ornl.gov/cgi-bin/cat.cgi.« less

The Histone Database: an integrated resource for histones and histone fold-containing proteins

PubMed Central

Mariño-Ramírez, Leonardo; Levine, Kevin M.; Morales, Mario; Zhang, Suiyuan; Moreland, R. Travis; Baxevanis, Andreas D.; Landsman, David

2011-01-01

Eukaryotic chromatin is composed of DNA and protein components—core histones—that act to compactly pack the DNA into nucleosomes, the fundamental building blocks of chromatin. These nucleosomes are connected to adjacent nucleosomes by linker histones. Nucleosomes are highly dynamic and, through various core histone post-translational modifications and incorporation of diverse histone variants, can serve as epigenetic marks to control processes such as gene expression and recombination. The Histone Sequence Database is a curated collection of sequences and structures of histones and non-histone proteins containing histone folds, assembled from major public databases. Here, we report a substantial increase in the number of sequences and taxonomic coverage for histone and histone fold-containing proteins available in the database. Additionally, the database now contains an expanded dataset that includes archaeal histone sequences. The database also provides comprehensive multiple sequence alignments for each of the four core histones (H2A, H2B, H3 and H4), the linker histones (H1/H5) and the archaeal histones. The database also includes current information on solved histone fold-containing structures. The Histone Sequence Database is an inclusive resource for the analysis of chromatin structure and function focused on histones and histone fold-containing proteins. Database URL: The Histone Sequence Database is freely available and can be accessed at http://research.nhgri.nih.gov/histones/. PMID:22025671

Molecular evolution of miraculin-like proteins in soybean Kunitz super-family.

PubMed

Selvakumar, Purushotham; Gahloth, Deepankar; Tomar, Prabhat Pratap Singh; Sharma, Nidhi; Sharma, Ashwani Kumar

2011-12-01

Miraculin-like proteins (MLPs) belong to soybean Kunitz super-family and have been characterized from many plant families like Rutaceae, Solanaceae, Rubiaceae, etc. Many of them possess trypsin inhibitory activity and are involved in plant defense. MLPs exhibit significant sequence identity (~30-95%) to native miraculin protein, also belonging to Kunitz super-family compared with a typical Kunitz family member (~30%). The sequence and structure-function comparison of MLPs with that of a classical Kunitz inhibitor have demonstrated that MLPs have evolved to form a distinct group within Kunitz super-family. Sequence analysis of new genes along with available MLP sequences in the literature revealed three major groups for these proteins. A significant feature of Rutaceae MLP type 2 sequences is the presence of phosphorylation motif. Subtle changes are seen in putative reactive loop residues among different MLPs suggesting altered specificities to specific proteases. In phylogenetic analysis, Rutaceae MLP type 1 and type 2 proteins clustered together on separate branches, whereas native miraculin along with other MLPs formed distinct clusters. Site-specific positive Darwinian selection was observed at many sites in both the groups of Rutaceae MLP sequences with most of the residues undergoing positive selection located in loop regions. The results demonstrate the sequence and thereby the structure-function divergence of MLPs as a distinct group within soybean Kunitz super-family due to biotic and abiotic stresses of local environment.

CAZymes Analysis Toolkit (CAT): web service for searching and analyzing carbohydrate-active enzymes in a newly sequenced organism using CAZy database.

PubMed

Park, Byung H; Karpinets, Tatiana V; Syed, Mustafa H; Leuze, Michael R; Uberbacher, Edward C

2010-12-01

The Carbohydrate-Active Enzyme (CAZy) database provides a rich set of manually annotated enzymes that degrade, modify, or create glycosidic bonds. Despite rich and invaluable information stored in the database, software tools utilizing this information for annotation of newly sequenced genomes by CAZy families are limited. We have employed two annotation approaches to fill the gap between manually curated high-quality protein sequences collected in the CAZy database and the growing number of other protein sequences produced by genome or metagenome sequencing projects. The first approach is based on a similarity search against the entire nonredundant sequences of the CAZy database. The second approach performs annotation using links or correspondences between the CAZy families and protein family domains. The links were discovered using the association rule learning algorithm applied to sequences from the CAZy database. The approaches complement each other and in combination achieved high specificity and sensitivity when cross-evaluated with the manually curated genomes of Clostridium thermocellum ATCC 27405 and Saccharophagus degradans 2-40. The capability of the proposed framework to predict the function of unknown protein domains and of hypothetical proteins in the genome of Neurospora crassa is demonstrated. The framework is implemented as a Web service, the CAZymes Analysis Toolkit, and is available at http://cricket.ornl.gov/cgi-bin/cat.cgi.

Generation of 2A-linked multicistronic cassettes by recombinant PCR.

PubMed

Szymczak-Workman, Andrea L; Vignali, Kate M; Vignali, Dario A A

2012-02-01

The need for reliable, multicistronic vectors for multigene delivery is at the forefront of biomedical technology. It is now possible to express multiple proteins from a single open reading frame (ORF) using 2A peptide-linked multicistronic vectors. These small sequences, when cloned between genes, allow for efficient, stoichiometric production of discrete protein products within a single vector through a novel "cleavage" event within the 2A peptide sequence. Expression of more than two genes using conventional approaches has several limitations, most notably imbalanced protein expression and large size. The use of 2A peptide sequences alleviates these concerns. They are small (18-22 amino acids) and have divergent amino-terminal sequences, which minimizes the chance for homologous recombination and allows for multiple, different 2A peptide sequences to be used within a single vector. Importantly, separation of genes placed between 2A peptide sequences is nearly 100%, which allows for stoichiometric and concordant expression of the genes, regardless of the order of placement within the vector. This protocol describes the use of recombinant polymerase chain reaction (PCR) to connect multiple 2A-linked protein sequences. The final construct is subcloned into an expression vector.

Experimental and statistical post-validation of positive example EST sequences carrying peroxisome targeting signals type 1 (PTS1)

PubMed Central

Lingner, Thomas; Kataya, Amr R. A.; Reumann, Sigrun

2012-01-01

We recently developed the first algorithms specifically for plants to predict proteins carrying peroxisome targeting signals type 1 (PTS1) from genome sequences.1 As validated experimentally, the prediction methods are able to correctly predict unknown peroxisomal Arabidopsis proteins and to infer novel PTS1 tripeptides. The high prediction performance is primarily determined by the large number and sequence diversity of the underlying positive example sequences, which mainly derived from EST databases. However, a few constructs remained cytosolic in experimental validation studies, indicating sequencing errors in some ESTs. To identify erroneous sequences, we validated subcellular targeting of additional positive example sequences in the present study. Moreover, we analyzed the distribution of prediction scores separately for each orthologous group of PTS1 proteins, which generally resembled normal distributions with group-specific mean values. The cytosolic sequences commonly represented outliers of low prediction scores and were located at the very tail of a fitted normal distribution. Three statistical methods for identifying outliers were compared in terms of sensitivity and specificity.” Their combined application allows elimination of erroneous ESTs from positive example data sets. This new post-validation method will further improve the prediction accuracy of both PTS1 and PTS2 protein prediction models for plants, fungi, and mammals. PMID:22415050

SEQATOMS: a web tool for identifying missing regions in PDB in sequence context.

PubMed

Brandt, Bernd W; Heringa, Jaap; Leunissen, Jack A M

2008-07-01

With over 46 000 proteins, the Protein Data Bank (PDB) is the most important database with structural information of biological macromolecules. PDB files contain sequence and coordinate information. Residues present in the sequence can be absent from the coordinate section, which means their position in space is unknown. Similarity searches are routinely carried out against sequences taken from PDB SEQRES. However, there no distinction is made between residues that have a known or unknown position in the 3D protein structure. We present a FASTA sequence database that is produced by combining the sequence and coordinate information. All residues absent from the PDB coordinate section are masked with lower-case letters, thereby providing a view of these residues in the context of the entire protein sequence, which facilitates inspecting 'missing' regions. We also provide a masked version of the CATH domain database. A user-friendly BLAST interface is available for similarity searching. In contrast to standard (stand-alone) BLAST output, which only contains upper-case letters, our output retains the lower-case letters of the masked regions. Thus, our server can be used to perform BLAST searching case-sensitively. Here, we have applied it to the study of missing regions in their sequence context. SEQATOMS is available at http://www.bioinformatics.nl/tools/seqatoms/.

Experimental and statistical post-validation of positive example EST sequences carrying peroxisome targeting signals type 1 (PTS1).

PubMed

Lingner, Thomas; Kataya, Amr R A; Reumann, Sigrun

2012-02-01

We recently developed the first algorithms specifically for plants to predict proteins carrying peroxisome targeting signals type 1 (PTS1) from genome sequences. As validated experimentally, the prediction methods are able to correctly predict unknown peroxisomal Arabidopsis proteins and to infer novel PTS1 tripeptides. The high prediction performance is primarily determined by the large number and sequence diversity of the underlying positive example sequences, which mainly derived from EST databases. However, a few constructs remained cytosolic in experimental validation studies, indicating sequencing errors in some ESTs. To identify erroneous sequences, we validated subcellular targeting of additional positive example sequences in the present study. Moreover, we analyzed the distribution of prediction scores separately for each orthologous group of PTS1 proteins, which generally resembled normal distributions with group-specific mean values. The cytosolic sequences commonly represented outliers of low prediction scores and were located at the very tail of a fitted normal distribution. Three statistical methods for identifying outliers were compared in terms of sensitivity and specificity." Their combined application allows elimination of erroneous ESTs from positive example data sets. This new post-validation method will further improve the prediction accuracy of both PTS1 and PTS2 protein prediction models for plants, fungi, and mammals.

Human immunodeficiency virus type 1 LTR TATA and TAR region sequences required for transcriptional regulation.

PubMed Central

Garcia, J A; Harrich, D; Soultanakis, E; Wu, F; Mitsuyasu, R; Gaynor, R B

1989-01-01

The human immunodeficiency virus (HIV) type 1 LTR is regulated at the transcriptional level by both cellular and viral proteins. Using HeLa cell extracts, multiple regions of the HIV LTR were found to serve as binding sites for cellular proteins. An untranslated region binding protein UBP-1 has been purified and fractions containing this protein bind to both the TAR and TATA regions. To investigate the role of cellular proteins binding to both the TATA and TAR regions and their potential interaction with other HIV DNA binding proteins, oligonucleotide-directed mutagenesis of both these regions was performed followed by DNase I footprinting and transient expression assays. In the TATA region, two direct repeats TC/AAGC/AT/AGCTGC surround the TATA sequence. Mutagenesis of both of these direct repeats or of the TATA sequence interrupted binding over the TATA region on the coding strand, but only a mutation of the TATA sequence affected in vivo assays for tat-activation. In addition to TAR serving as the site of binding of cellular proteins, RNA transcribed from TAR is capable of forming a stable stem-loop structure. To determine the relative importance of DNA binding proteins as compared to secondary structure, oligonucleotide-directed mutations in the TAR region were studied. Local mutations that disrupted either the stem or loop structure were defective in gene expression. However, compensatory mutations which restored base pairing in the stem resulted in complete tat-activation. This indicated a significant role for the stem-loop structure in HIV gene expression. To determine the role of TAR binding proteins, mutations were constructed which extensively changed the primary structure of the TAR region, yet left stem base pairing, stem energy and the loop sequence intact. These mutations resulted in decreased protein binding to TAR DNA and defects in tat-activation, and revealed factor binding specifically to the loop DNA sequence. Further mutagenesis which inverted this stem and loop mutation relative to the HIV LTR mRNA start site resulted in even larger decreases in tat-activation. This suggests that multiple determinants, including protein binding, the loop sequence, and RNA or DNA secondary structure, are important in tat-activation and suggests that tat may interact with cellular proteins binding to DNA to increase HIV gene expression. Images PMID:2721501

Predicting Functions of Proteins in Mouse Based on Weighted Protein-Protein Interaction Network and Protein Hybrid Properties

PubMed Central

Shi, Xiaohe; Lu, Wen-Cong; Cai, Yu-Dong; Chou, Kuo-Chen

2011-01-01

Background With the huge amount of uncharacterized protein sequences generated in the post-genomic age, it is highly desirable to develop effective computational methods for quickly and accurately predicting their functions. The information thus obtained would be very useful for both basic research and drug development in a timely manner. Methodology/Principal Findings Although many efforts have been made in this regard, most of them were based on either sequence similarity or protein-protein interaction (PPI) information. However, the former often fails to work if a query protein has no or very little sequence similarity to any function-known proteins, while the latter had similar problem if the relevant PPI information is not available. In view of this, a new approach is proposed by hybridizing the PPI information and the biochemical/physicochemical features of protein sequences. The overall first-order success rates by the new predictor for the functions of mouse proteins on training set and test set were 69.1% and 70.2%, respectively, and the success rate covered by the results of the top-4 order from a total of 24 orders was 65.2%. Conclusions/Significance The results indicate that the new approach is quite promising that may open a new avenue or direction for addressing the difficult and complicated problem. PMID:21283518

A coevolution analysis for identifying protein-protein interactions by Fourier transform.

PubMed

Yin, Changchuan; Yau, Stephen S-T

2017-01-01

Protein-protein interactions (PPIs) play key roles in life processes, such as signal transduction, transcription regulations, and immune response, etc. Identification of PPIs enables better understanding of the functional networks within a cell. Common experimental methods for identifying PPIs are time consuming and expensive. However, recent developments in computational approaches for inferring PPIs from protein sequences based on coevolution theory avoid these problems. In the coevolution theory model, interacted proteins may show coevolutionary mutations and have similar phylogenetic trees. The existing coevolution methods depend on multiple sequence alignments (MSA); however, the MSA-based coevolution methods often produce high false positive interactions. In this paper, we present a computational method using an alignment-free approach to accurately detect PPIs and reduce false positives. In the method, protein sequences are numerically represented by biochemical properties of amino acids, which reflect the structural and functional differences of proteins. Fourier transform is applied to the numerical representation of protein sequences to capture the dissimilarities of protein sequences in biophysical context. The method is assessed for predicting PPIs in Ebola virus. The results indicate strong coevolution between the protein pairs (NP-VP24, NP-VP30, NP-VP40, VP24-VP30, VP24-VP40, and VP30-VP40). The method is also validated for PPIs in influenza and E.coli genomes. Since our method can reduce false positive and increase the specificity of PPI prediction, it offers an effective tool to understand mechanisms of disease pathogens and find potential targets for drug design. The Python programs in this study are available to public at URL (https://github.com/cyinbox/PPI).

Computational mining for hypothetical patterns of amino acid side chains in protein data bank (PDB)

NASA Astrophysics Data System (ADS)

Ghani, Nur Syatila Ab; Firdaus-Raih, Mohd

2018-04-01

The three-dimensional structure of a protein can provide insights regarding its function. Functional relationship between proteins can be inferred from fold and sequence similarities. In certain cases, sequence or fold comparison fails to conclude homology between proteins with similar mechanism. Since the structure is more conserved than the sequence, a constellation of functional residues can be similarly arranged among proteins of similar mechanism. Local structural similarity searches are able to detect such constellation of amino acids among distinct proteins, which can be useful to annotate proteins of unknown function. Detection of such patterns of amino acids on a large scale can increase the repertoire of important 3D motifs since available known 3D motifs currently, could not compensate the ever-increasing numbers of uncharacterized proteins to be annotated. Here, a computational platform for an automated detection of 3D motifs is described. A fuzzy-pattern searching algorithm derived from IMagine an Amino Acid 3D Arrangement search EnGINE (IMAAAGINE) was implemented to develop an automated method for searching of hypothetical patterns of amino acid side chains in Protein Data Bank (PDB), without the need for prior knowledge on related sequence or structure of pattern of interest. We present an example of the searches, which is the detection of a hypothetical pattern derived from known structural motif of C2H2 structural pattern from zinc fingers. The conservation of particular patterns of amino acid side chains in unrelated proteins is highlighted. This approach can act as a complementary method for available structure- and sequence-based platforms and may contribute in improving functional association between proteins.

A coevolution analysis for identifying protein-protein interactions by Fourier transform

PubMed Central

Yin, Changchuan; Yau, Stephen S. -T.

2017-01-01

Protein-protein interactions (PPIs) play key roles in life processes, such as signal transduction, transcription regulations, and immune response, etc. Identification of PPIs enables better understanding of the functional networks within a cell. Common experimental methods for identifying PPIs are time consuming and expensive. However, recent developments in computational approaches for inferring PPIs from protein sequences based on coevolution theory avoid these problems. In the coevolution theory model, interacted proteins may show coevolutionary mutations and have similar phylogenetic trees. The existing coevolution methods depend on multiple sequence alignments (MSA); however, the MSA-based coevolution methods often produce high false positive interactions. In this paper, we present a computational method using an alignment-free approach to accurately detect PPIs and reduce false positives. In the method, protein sequences are numerically represented by biochemical properties of amino acids, which reflect the structural and functional differences of proteins. Fourier transform is applied to the numerical representation of protein sequences to capture the dissimilarities of protein sequences in biophysical context. The method is assessed for predicting PPIs in Ebola virus. The results indicate strong coevolution between the protein pairs (NP-VP24, NP-VP30, NP-VP40, VP24-VP30, VP24-VP40, and VP30-VP40). The method is also validated for PPIs in influenza and E.coli genomes. Since our method can reduce false positive and increase the specificity of PPI prediction, it offers an effective tool to understand mechanisms of disease pathogens and find potential targets for drug design. The Python programs in this study are available to public at URL (https://github.com/cyinbox/PPI). PMID:28430779

An effective approach for annotation of protein families with low sequence similarity and conserved motifs: identifying GDSL hydrolases across the plant kingdom.

PubMed

Vujaklija, Ivan; Bielen, Ana; Paradžik, Tina; Biđin, Siniša; Goldstein, Pavle; Vujaklija, Dušica

2016-02-18

The massive accumulation of protein sequences arising from the rapid development of high-throughput sequencing, coupled with automatic annotation, results in high levels of incorrect annotations. In this study, we describe an approach to decrease annotation errors of protein families characterized by low overall sequence similarity. The GDSL lipolytic family comprises proteins with multifunctional properties and high potential for pharmaceutical and industrial applications. The number of proteins assigned to this family has increased rapidly over the last few years. In particular, the natural abundance of GDSL enzymes reported recently in plants indicates that they could be a good source of novel GDSL enzymes. We noticed that a significant proportion of annotated sequences lack specific GDSL motif(s) or catalytic residue(s). Here, we applied motif-based sequence analyses to identify enzymes possessing conserved GDSL motifs in selected proteomes across the plant kingdom. Motif-based HMM scanning (Viterbi decoding-VD and posterior decoding-PD) and the here described PD/VD protocol were successfully applied on 12 selected plant proteomes to identify sequences with GDSL motifs. A significant number of identified GDSL sequences were novel. Moreover, our scanning approach successfully detected protein sequences lacking at least one of the essential motifs (171/820) annotated by Pfam profile search (PfamA) as GDSL. Based on these analyses we provide a curated list of GDSL enzymes from the selected plants. CLANS clustering and phylogenetic analysis helped us to gain a better insight into the evolutionary relationship of all identified GDSL sequences. Three novel GDSL subfamilies as well as unreported variations in GDSL motifs were discovered in this study. In addition, analyses of selected proteomes showed a remarkable expansion of GDSL enzymes in the lycophyte, Selaginella moellendorffii. Finally, we provide a general motif-HMM scanner which is easily accessible through the graphical user interface ( http://compbio.math.hr/ ). Our results show that scanning with a carefully parameterized motif-HMM is an effective approach for annotation of protein families with low sequence similarity and conserved motifs. The results of this study expand current knowledge and provide new insights into the evolution of the large GDSL-lipase family in land plants.

Predicting Protein-Protein Interactions by Combing Various Sequence-Derived.

PubMed

Zhao, Xiao-Wei; Ma, Zhi-Qiang; Yin, Ming-Hao

2011-09-20

Knowledge of protein-protein interactions (PPIs) plays an important role in constructing protein interaction networks and understanding the general machineries of biological systems. In this study, a new method is proposed to predict PPIs using a comprehensive set of 930 features based only on sequence information, these features measure the interactions between residues a certain distant apart in the protein sequences from different aspects. To achieve better performance, the principal component analysis (PCA) is first employed to obtain an optimized feature subset. Then, the resulting 67-dimensional feature vectors are fed to Support Vector Machine (SVM). Experimental results on Drosophila melanogaster and Helicobater pylori datasets show that our method is very promising to predict PPIs and may at least be a useful supplement tool to existing methods.

Single-molecule protein sequencing through fingerprinting: computational assessment

NASA Astrophysics Data System (ADS)

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.

Understanding sequence similarity and framework analysis between centromere proteins using computational biology.

PubMed

Doss, C George Priya; Chakrabarty, Chiranjib; Debajyoti, C; Debottam, S

2014-11-01

Certain mysteries pointing toward their recruitment pathways, cell cycle regulation mechanisms, spindle checkpoint assembly, and chromosome segregation process are considered the centre of attraction in cancer research. In modern times, with the established databases, ranges of computational platforms have provided a platform to examine almost all the physiological and biochemical evidences in disease-associated phenotypes. Using existing computational methods, we have utilized the amino acid residues to understand the similarity within the evolutionary variance of different associated centromere proteins. This study related to sequence similarity, protein-protein networking, co-expression analysis, and evolutionary trajectory of centromere proteins will speed up the understanding about centromere biology and will create a road map for upcoming researchers who are initiating their work of clinical sequencing using centromere proteins.

Functional region prediction with a set of appropriate homologous sequences-an index for sequence selection by integrating structure and sequence information with spatial statistics

PubMed Central

2012-01-01

Background The detection of conserved residue clusters on a protein structure is one of the effective strategies for the prediction of functional protein regions. Various methods, such as Evolutionary Trace, have been developed based on this strategy. In such approaches, the conserved residues are identified through comparisons of homologous amino acid sequences. Therefore, the selection of homologous sequences is a critical step. It is empirically known that a certain degree of sequence divergence in the set of homologous sequences is required for the identification of conserved residues. However, the development of a method to select homologous sequences appropriate for the identification of conserved residues has not been sufficiently addressed. An objective and general method to select appropriate homologous sequences is desired for the efficient prediction of functional regions. Results We have developed a novel index to select the sequences appropriate for the identification of conserved residues, and implemented the index within our method to predict the functional regions of a protein. The implementation of the index improved the performance of the functional region prediction. The index represents the degree of conserved residue clustering on the tertiary structure of the protein. For this purpose, the structure and sequence information were integrated within the index by the application of spatial statistics. Spatial statistics is a field of statistics in which not only the attributes but also the geometrical coordinates of the data are considered simultaneously. Higher degrees of clustering generate larger index scores. We adopted the set of homologous sequences with the highest index score, under the assumption that the best prediction accuracy is obtained when the degree of clustering is the maximum. The set of sequences selected by the index led to higher functional region prediction performance than the sets of sequences selected by other sequence-based methods. Conclusions Appropriate homologous sequences are selected automatically and objectively by the index. Such sequence selection improved the performance of functional region prediction. As far as we know, this is the first approach in which spatial statistics have been applied to protein analyses. Such integration of structure and sequence information would be useful for other bioinformatics problems. PMID:22643026

ST proteins, a new family of plant tandem repeat proteins with a DUF2775 domain mainly found in Fabaceae and Asteraceae.

PubMed

Albornos, Lucía; Martín, Ignacio; Iglesias, Rebeca; Jiménez, Teresa; Labrador, Emilia; Dopico, Berta

2012-11-07

Many proteins with tandem repeats in their sequence have been described and classified according to the length of the repeats: I) Repeats of short oligopeptides (from 2 to 20 amino acids), including structural cell wall proteins and arabinogalactan proteins. II) Repeats that range in length from 20 to 40 residues, including proteins with a well-established three-dimensional structure often involved in mediating protein-protein interactions. (III) Longer repeats in the order of 100 amino acids that constitute structurally and functionally independent units. Here we analyse ShooT specific (ST) proteins, a family of proteins with tandem repeats of unknown function that were first found in Leguminosae, and their possible similarities to other proteins with tandem repeats. ST protein sequences were only found in dicotyledonous plants, limited to several plant families, mainly the Fabaceae and the Asteraceae. ST mRNAs accumulate mainly in the roots and under biotic interactions. Most ST proteins have one or several Domain(s) of Unknown Function 2775 (DUF2775). All deduced ST proteins have a signal peptide, indicating that these proteins enter the secretory pathway, and the mature proteins have tandem repeat oligopeptides that share a hexapeptide (E/D)FEPRP followed by 4 partially conserved amino acids, which could determine a putative N-glycosylation signal, and a fully conserved tyrosine. In a phylogenetic tree, the sequences clade according to taxonomic group. A possible involvement in symbiosis and abiotic stress as well as in plant cell elongation is suggested, although different STs could play different roles in plant development. We describe a new family of proteins called ST whose presence is limited to the plant kingdom, specifically to a few families of dicotyledonous plants. They present 20 to 40 amino acid tandem repeat sequences with different characteristics (signal peptide, DUF2775 domain, conservative repeat regions) from the described group of 20 to 40 amino acid tandem repeat proteins and also from known cell wall proteins with repeat sequences. Several putative roles in plant physiology can be inferred from the characteristics found.

ST proteins, a new family of plant tandem repeat proteins with a DUF2775 domain mainly found in Fabaceae and Asteraceae

PubMed Central

2012-01-01

Background Many proteins with tandem repeats in their sequence have been described and classified according to the length of the repeats: I) Repeats of short oligopeptides (from 2 to 20 amino acids), including structural cell wall proteins and arabinogalactan proteins. II) Repeats that range in length from 20 to 40 residues, including proteins with a well-established three-dimensional structure often involved in mediating protein-protein interactions. (III) Longer repeats in the order of 100 amino acids that constitute structurally and functionally independent units. Here we analyse ShooT specific (ST) proteins, a family of proteins with tandem repeats of unknown function that were first found in Leguminosae, and their possible similarities to other proteins with tandem repeats. Results ST protein sequences were only found in dicotyledonous plants, limited to several plant families, mainly the Fabaceae and the Asteraceae. ST mRNAs accumulate mainly in the roots and under biotic interactions. Most ST proteins have one or several Domain(s) of Unknown Function 2775 (DUF2775). All deduced ST proteins have a signal peptide, indicating that these proteins enter the secretory pathway, and the mature proteins have tandem repeat oligopeptides that share a hexapeptide (E/D)FEPRP followed by 4 partially conserved amino acids, which could determine a putative N-glycosylation signal, and a fully conserved tyrosine. In a phylogenetic tree, the sequences clade according to taxonomic group. A possible involvement in symbiosis and abiotic stress as well as in plant cell elongation is suggested, although different STs could play different roles in plant development. Conclusions We describe a new family of proteins called ST whose presence is limited to the plant kingdom, specifically to a few families of dicotyledonous plants. They present 20 to 40 amino acid tandem repeat sequences with different characteristics (signal peptide, DUF2775 domain, conservative repeat regions) from the described group of 20 to 40 amino acid tandem repeat proteins and also from known cell wall proteins with repeat sequences. Several putative roles in plant physiology can be inferred from the characteristics found. PMID:23134664

Phylogenetic Relationship of Necoclí Virus to Other South American Hantaviruses (Bunyaviridae: Hantavirus).

PubMed

Montoya-Ruiz, Carolina; Cajimat, Maria N B; Milazzo, Mary Louise; Diaz, Francisco J; Rodas, Juan David; Valbuena, Gustavo; Fulhorst, Charles F

2015-07-01

The results of a previous study suggested that Cherrie's cane rat (Zygodontomys cherriei) is the principal host of Necoclí virus (family Bunyaviridae, genus Hantavirus) in Colombia. Bayesian analyses of complete nucleocapsid protein gene sequences and complete glycoprotein precursor gene sequences in this study confirmed that Necoclí virus is phylogenetically closely related to Maporal virus, which is principally associated with the delicate pygmy rice rat (Oligoryzomys delicatus) in western Venezuela. In pairwise comparisons, nonidentities between the complete amino acid sequence of the nucleocapsid protein of Necoclí virus and the complete amino acid sequences of the nucleocapsid proteins of other hantaviruses were ≥8.7%. Likewise, nonidentities between the complete amino acid sequence of the glycoprotein precursor of Necoclí virus and the complete amino acid sequences of the glycoprotein precursors of other hantaviruses were ≥11.7%. Collectively, the unique association of Necoclí virus with Z. cherriei in Colombia, results of the Bayesian analyses of complete nucleocapsid protein gene sequences and complete glycoprotein precursor gene sequences, and results of the pairwise comparisons of amino acid sequences strongly support the notion that Necoclí virus represents a novel species in the genus Hantavirus. Further work is needed to determine whether Calabazo virus (a hantavirus associated with Z. brevicauda cherriei in Panama) and Necoclí virus are conspecific.

ssHMM: extracting intuitive sequence-structure motifs from high-throughput RNA-binding protein data

PubMed Central

Krestel, Ralf; Ohler, Uwe; Vingron, Martin; Marsico, Annalisa

2017-01-01

Abstract RNA-binding proteins (RBPs) play an important role in RNA post-transcriptional regulation and recognize target RNAs via sequence-structure motifs. The extent to which RNA structure influences protein binding in the presence or absence of a sequence motif is still poorly understood. Existing RNA motif finders either take the structure of the RNA only partially into account, or employ models which are not directly interpretable as sequence-structure motifs. We developed ssHMM, an RNA motif finder based on a hidden Markov model (HMM) and Gibbs sampling which fully captures the relationship between RNA sequence and secondary structure preference of a given RBP. Compared to previous methods which output separate logos for sequence and structure, it directly produces a combined sequence-structure motif when trained on a large set of sequences. ssHMM’s model is visualized intuitively as a graph and facilitates biological interpretation. ssHMM can be used to find novel bona fide sequence-structure motifs of uncharacterized RBPs, such as the one presented here for the YY1 protein. ssHMM reaches a high motif recovery rate on synthetic data, it recovers known RBP motifs from CLIP-Seq data, and scales linearly on the input size, being considerably faster than MEMERIS and RNAcontext on large datasets while being on par with GraphProt. It is freely available on Github and as a Docker image. PMID:28977546

[Molecular cloning and characterization of a novel Clonorchis sinensis antigenic protein containing tandem repeat sequences].

PubMed

Liu, Qian; Xu, Xue-Nian; Zhou, Yan; Cheng, Na; Dong, Yu-Ting; Zheng, Hua-Jun; Zhu, Yong-Qiang; Zhu, Yong-Qiang

2013-08-01

To find and clone new antigen genes from the lambda-ZAP cDNA expression library of adult Clonorchis sinensis, and determine the immunological characteristics of the recombinant proteins. The cDNA expression library of adult C. sinensis was screened by pooled sera of clonorchiasis patients. The sequences of the positive phage clones were compared with the sequences in EST database, and the full-length sequence of the gene (Cs22 gene) was obtained by RT-PCR. cDNA fragments containing 2 and 3 times tandem repeat sequences were generated by jumping PCR. The sequence encoding the mature peptide or the tandem repeat sequence was respectively cloned into the prokaryotic expression vector pET28a (+), and then transformed into E. coli Rosetta DE3 cells for expression. The recombinant proteins (rCs22-2r, rCs22-3r, rCs22M-2r, and rCs22M-3r) were purified by His-bind-resin (Ni-NTA) affinity chromatography. The immunogenicity of rCs22-2r and rCs22-3r was identified by ELISA. To evaluate the immunological diagnostic value of rCs22-2r and rCs22-3r, serum samples from 35 clonorchiasis patients, 31 healthy individuals, 15 schistosomiasis patients, 15 paragonimiasis westermani patients and 13 cysticercosis patients were examined by ELISA. To locate antigenic determinants, the pooled sera of clonorchiasis patients and healthy persons were analyzed for specific antibodies by ELISA with recombinant protein rCs22M-2r and rCs22M-3r containing the tandem repeat sequences. The full-length sequence of Cs22 antigen gene of C. sinensis was obtained. It contained 13 times tandem repeat sequences of EQQDGDEEGMGGDGGRGKEKGKVEGEDGAGEQKEQA. Bioinformatics analysis indicated that the protein (Cs22) belonged to GPI-anchored proteins family. The recombinant proteins rCs22-2r and rCs22-3r showed a certain level of immunogenicity. The positive rate by ELISA coated with the purified PrCs22-2r and PrCs22-3r for sera of clonorchiasis patients both were 45.7% (16/35), and 3.2% (1/31) for those of healthy persons. There was no cross reaction with sera of schistosomiasis and cysticercosis patients. The cross reaction with sera of paragonimiasis westermani patients was 1/15. The recombinant proteins rCs22M-2r and rCs22M-3r which only contained tandem repeats were specifically recognized by pooled sera of clonorchiasis patients. The Cs22 antigen gene of Clonorchis sinensis is obtained, and the recombinant proteins have certain diagnostic value. The antigenic determinant is located in tandem repeat sequences.

Cloning and sequencing of a gene encoding a 21-kilodalton outer membrane protein from Bordetella avium and expression of the gene in Salmonella typhimurium.

PubMed Central

Gentry-Weeks, C R; Hultsch, A L; Kelly, S M; Keith, J M; Curtiss, R

1992-01-01

Three gene libraries of Bordetella avium 197 DNA were prepared in Escherichia coli LE392 by using the cosmid vectors pCP13 and pYA2329, a derivative of pCP13 specifying spectinomycin resistance. The cosmid libraries were screened with convalescent-phase anti-B. avium turkey sera and polyclonal rabbit antisera against B. avium 197 outer membrane proteins. One E. coli recombinant clone produced a 56-kDa protein which reacted with convalescent-phase serum from a turkey infected with B. avium 197. In addition, five E. coli recombinant clones were identified which produced B. avium outer membrane proteins with molecular masses of 21, 38, 40, 43, and 48 kDa. At least one of these E. coli clones, which encoded the 21-kDa protein, reacted with both convalescent-phase turkey sera and antibody against B. avium 197 outer membrane proteins. The gene for the 21-kDa outer membrane protein was localized by Tn5seq1 mutagenesis, and the nucleotide sequence was determined by dideoxy sequencing. DNA sequence analysis of the 21-kDa protein revealed an open reading frame of 582 bases that resulted in a predicted protein of 194 amino acids. Comparison of the predicted amino acid sequence of the gene encoding the 21-kDa outer membrane protein with protein sequences in the National Biomedical Research Foundation protein sequence data base indicated significant homology to the OmpA proteins of Shigella dysenteriae, Enterobacter aerogenes, E. coli, and Salmonella typhimurium and to Neisseria gonorrhoeae outer membrane protein III, Haemophilus influenzae protein P6, and Pseudomonas aeruginosa porin protein F. The gene (ompA) encoding the B. avium 21-kDa protein hybridized with 4.1-kb DNA fragments from EcoRI-digested, chromosomal DNA of Bordetella pertussis and Bordetella bronchiseptica and with 6.0- and 3.2-kb DNA fragments from EcoRI-digested, chromosomal DNA of B. avium and B. avium-like DNA, respectively. A 6.75-kb DNA fragment encoding the B. avium 21-kDa protein was subcloned into the Asd+ vector pYA292, and the construct was introduced into the avirulent delta cya delta crp delta asd S. typhimurium chi 3987 for oral immunization of birds. The gene encoding the 21-kDa protein was expressed equivalently in B. avium 197, delta asd E. coli chi 6097, and S. typhimurium chi 3987 and was localized primarily in the cytoplasmic membrane and outer membrane. In preliminary studies on oral inoculation of turkey poults with S. typhimurium chi 3987 expressing the gene encoding the B. avium 21-kDa protein, it was determined that a single dose of the recombinant Salmonella vaccine failed to elicit serum antibodies against the 21-kDa protein and challenge with wild-type B. avium 197 resulted in colonization of the trachea and thymus with B. avium 197. Images PMID:1447140

A novel progesterone receptor membrane component (PGRMC) in the human and swine parasite Taenia solium: implications to the host-parasite relationship.

PubMed

Aguilar-Díaz, Hugo; Nava-Castro, Karen E; Escobedo, Galileo; Domínguez-Ramírez, Lenin; García-Varela, Martín; Del Río-Araiza, Víctor H; Palacios-Arreola, Margarita I; Morales-Montor, Jorge

2018-03-09

We have previously reported that progesterone (P 4 ) has a direct in vitro effect on the scolex evagination and growth of Taenia solium cysticerci. Here, we explored the hypothesis that the P 4 direct effect on T. solium might be mediated by a novel steroid-binding parasite protein. By way of using immunofluorescent confocal microscopy, flow cytometry analysis, double-dimension electrophoresis analysis, and sequencing the corresponding protein spot, we detected a novel PGRMC in T. solium. Molecular modeling studies accompanied by computer docking using the sequenced protein, together with phylogenetic analysis and sequence alignment clearly demonstrated that T. solium PGRMC is from parasite origin. Our results show that P 4 in vitro increases parasite evagination and scolex size. Using immunofluorescent confocal microscopy, we detected that parasite cells showed expression of a P 4 -binding like protein exclusively located at the cysticercus subtegumental tissue. Presence of the P 4 -binding protein in cyst cells was also confirmed by flow cytometry. Double-dimension electrophoresis analysis, followed by sequencing the corresponding protein spot, revealed a protein that was previously reported in the T. solium genome belonging to a membrane-associated progesterone receptor component (PGRMC). Molecular modeling studies accompanied by computer docking using the sequenced protein showed that PGRMC is potentially able to bind steroid hormones such as progesterone, estradiol, testosterone and dihydrodrotestosterone with different affinities. Phylogenetic analysis and sequence alignment clearly demonstrated that T. solium PGRMC is related to a steroid-binding protein of Echinoccocus granulosus, both of them being nested within a cluster including similar proteins present in platyhelminths such as Schistocephalus solidus and Schistosoma haematobium. Progesterone may directly act upon T. solium cysticerci probably by binding to PGRMC. This research has implications in the field of host-parasite co-evolution as well as the sex-associated susceptibility to this infection. In a more practical matter, present results may contribute to the molecular design of new drugs with anti-parasite actions.

Dr. Sanger's Apprentice: A Computer-Aided Instruction to Protein Sequencing.

ERIC Educational Resources Information Center

Schmidt, Thomas G.; Place, Allen R.

1985-01-01

Modeled after the program "Mastermind," this program teaches students the art of protein sequencing. The program (written in Turbo Pascal for the IBM PC, requiring 128K, a graphics adapter, and an 8070 mathematics coprocessor) generates a polypeptide whose sequence and length can be user-defined (for practice) or computer-generated (for…

Using SQL Databases for Sequence Similarity Searching and Analysis.

PubMed

Pearson, William R; Mackey, Aaron J

2017-09-13

Relational databases can integrate diverse types of information and manage large sets of similarity search results, greatly simplifying genome-scale analyses. By focusing on taxonomic subsets of sequences, relational databases can reduce the size and redundancy of sequence libraries and improve the statistical significance of homologs. In addition, by loading similarity search results into a relational database, it becomes possible to explore and summarize the relationships between all of the proteins in an organism and those in other biological kingdoms. This unit describes how to use relational databases to improve the efficiency of sequence similarity searching and demonstrates various large-scale genomic analyses of homology-related data. It also describes the installation and use of a simple protein sequence database, seqdb_demo, which is used as a basis for the other protocols. The unit also introduces search_demo, a database that stores sequence similarity search results. The search_demo database is then used to explore the evolutionary relationships between E. coli proteins and proteins in other organisms in a large-scale comparative genomic analysis. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

BIOPEP database and other programs for processing bioactive peptide sequences.

PubMed

Minkiewicz, Piotr; Dziuba, Jerzy; Iwaniak, Anna; Dziuba, Marta; Darewicz, Małgorzata

2008-01-01

This review presents the potential for application of computational tools in peptide science based on a sample BIOPEP database and program as well as other programs and databases available via the World Wide Web. The BIOPEP application contains a database of biologically active peptide sequences and a program enabling construction of profiles of the potential biological activity of protein fragments, calculation of quantitative descriptors as measures of the value of proteins as potential precursors of bioactive peptides, and prediction of bonds susceptible to hydrolysis by endopeptidases in a protein chain. Other bioactive and allergenic peptide sequence databases are also presented. Programs enabling the construction of binary and multiple alignments between peptide sequences, the construction of sequence motifs attributed to a given type of bioactivity, searching for potential precursors of bioactive peptides, and the prediction of sites susceptible to proteolytic cleavage in protein chains are available via the Internet as are other approaches concerning secondary structure prediction and calculation of physicochemical features based on amino acid sequence. Programs for prediction of allergenic and toxic properties have also been developed. This review explores the possibilities of cooperation between various programs.

Sirius PSB: a generic system for analysis of biological sequences.

PubMed

Koh, Chuan Hock; Lin, Sharene; Jedd, Gregory; Wong, Limsoon

2009-12-01

Computational tools are essential components of modern biological research. For example, BLAST searches can be used to identify related proteins based on sequence homology, or when a new genome is sequenced, prediction models can be used to annotate functional sites such as transcription start sites, translation initiation sites and polyadenylation sites and to predict protein localization. Here we present Sirius Prediction Systems Builder (PSB), a new computational tool for sequence analysis, classification and searching. Sirius PSB has four main operations: (1) Building a classifier, (2) Deploying a classifier, (3) Search for proteins similar to query proteins, (4) Preliminary and post-prediction analysis. Sirius PSB supports all these operations via a simple and interactive graphical user interface. Besides being a convenient tool, Sirius PSB has also introduced two novelties in sequence analysis. Firstly, genetic algorithm is used to identify interesting features in the feature space. Secondly, instead of the conventional method of searching for similar proteins via sequence similarity, we introduced searching via features' similarity. To demonstrate the capabilities of Sirius PSB, we have built two prediction models - one for the recognition of Arabidopsis polyadenylation sites and another for the subcellular localization of proteins. Both systems are competitive against current state-of-the-art models based on evaluation of public datasets. More notably, the time and effort required to build each model is greatly reduced with the assistance of Sirius PSB. Furthermore, we show that under certain conditions when BLAST is unable to find related proteins, Sirius PSB can identify functionally related proteins based on their biophysical similarities. Sirius PSB and its related supplements are available at: http://compbio.ddns.comp.nus.edu.sg/~sirius.

Phosphoenolpyruvate carboxykinase of Trypanosoma brucei is targeted to the glycosomes by a C-terminal sequence.

PubMed

Sommer, J M; Nguyen, T T; Wang, C C

1994-08-15

Import of proteins into the glycosomes of T. brucei resembles the peroxisomal protein import in that C-terminal SKL-like tripeptide sequences can function as targeting signals. Many of the glycosomal proteins do not, however, possess such C-terminal tripeptide signals. Among these, phosphoenolpyruvate carboxykinase (PEPCK (ATP)) was thought to be targeted to the glycosomes by an N-terminal or an internal targeting signal. A limited similarity to the N-terminal targeting signal of rat peroxisomal thiolase exists at the N-terminus of T. brucei PEPCK. However, we found that this peroxisomal targeting signal does not function for glycosomal protein import in T. brucei. Further studies of the PEPCK gene revealed that the C-terminus of the predicted protein does not correspond to the previously deduced protein sequence of 472 amino acids due to a -1 frame shift error in the original DNA sequence. Readjusting the reading frame of the sequence results in a predicted protein of 525 amino acids in length ending in a tripeptide serine-arginine-leucine (SRL), which is a potential targeting signal for import into the glycosomes. A fusion protein of firefly luciferase, without its own C-terminal SKL targeting signal, and T. brucei PEPCK is efficiently imported into the glycosomes when expressed in procyclic trypanosomes. Deletion of the C-terminal SRL tripeptide or the last 29 amino acids of PEPCK reduced the import only by about 50%, while a deletion of the last 47 amino acids completely abolished the import. These results suggest that T. brucei PEPCK may contain a second, internal glycosomal targeting signal upstream of the C-terminal SRL sequence.

Staphylococcal phosphoenolpyruvate-dependent phosphotransferase system: purification and characterization of the mannitol-specific enzyme III/sup mtl/ of Staphylococcus aureus and Staphylococcus carnosus and homology with the enzyme II/sup mtl/ of Escherichia coli

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reiche, B.; Frank, R.; Deutscher, J.

1988-08-23

Enzyme III/sup mtl/ is part of the mannitol phosphotransferase system of Staphylococcus aureus and Staphylococcus carnosus and is phosphorylated by phosphoenolpyruvate in a reaction sequence requiring enzyme I (phosphoenolpyruvate-protein phosphotransferase) and the histidine-containing protein HPr. In this paper, the authors report the isolation of III/sup mtl/ from both S. aureus and S. carnosus and the characterization of the active center. After phosphorylation of III/sup mtl/ with (/sup 32/P)PEP, enzyme I, and HPr, the phosphorylated protein was cleaved with endoproteinase GLu(C). The amino acid sequence of the S. aureus peptide carrying the phosphoryl group was found to be Gln-Val-Val-Ser-Thr-Phe-Met-Gly-Asn-Gly-Leu-Ala-Ile-Pro-His-Gly-Thr-Asp-Asp. The correspondingmore » peptide from S. carnosus shows an equal sequence except that the first residue is Ala instead of Gln. These peptides both contain a single histidyl residue which they assume to carry the phosphoryl group. All proteins of the PTS so far investigated indeed carry the phosphoryl group attached to a histidyl residue. According to sodium dodecyl sulfate gels, the molecular weight of the III/sup mtl/ proteins was found to be 15,000. They have also determined the N-terminal sequence of both proteins. Comparison of the III/sup mtl/ peptide sequences and the C-terminal part of the enzyme II/sup mtl/ of Escherichia coli reveals considerable sequence homology, which supports the suggestion that II/sup mtl/ of E. coli is a fusion protein of a soluble III protein with a membrane-bound enzyme II.« less

Drosophila Nora virus capsid proteins differ from those of other picorna-like viruses.

PubMed

Ekström, Jens-Ola; Habayeb, Mazen S; Srivastava, Vaibhav; Kieselbach, Thomas; Wingsle, Gunnar; Hultmark, Dan

2011-09-01

The recently discovered Nora virus from Drosophila melanogaster is a single-stranded RNA virus. Its published genomic sequence encodes a typical picorna-like cassette of replicative enzymes, but no capsid proteins similar to those in other picorna-like viruses. We have now done additional sequencing at the termini of the viral genome, extending it by 455 nucleotides at the 5' end, but no more coding sequence was found. The completeness of the final 12,333-nucleotide sequence was verified by the production of infectious virus from the cloned genome. To identify the capsid proteins, we purified Nora virus particles and analyzed their proteins by mass spectrometry. Our results show that the capsid is built from three major proteins, VP4A, B and C, encoded in the fourth open reading frame of the viral genome. The viral particles also contain traces of a protein from the third open reading frame, VP3. VP4A and B are not closely related to other picorna-like virus capsid proteins in sequence, but may form similar jelly roll folds. VP4C differs from the others and is predicted to have an essentially α-helical conformation. In a related virus, identified from EST database sequences from Nasonia parasitoid wasps, VP4C is encoded in a separate open reading frame, separated from VP4A and B by a frame-shift. This opens a possibility that VP4C is produced in non-equimolar quantities. Altogether, our results suggest that the Nora virus capsid has a different protein organization compared to the order Picornavirales. Copyright © 2011 Elsevier B.V. All rights reserved.

CaMELS: In silico prediction of calmodulin binding proteins and their binding sites.

PubMed

Abbasi, Wajid Arshad; Asif, Amina; Andleeb, Saiqa; Minhas, Fayyaz Ul Amir Afsar

2017-09-01

Due to Ca 2+ -dependent binding and the sequence diversity of Calmodulin (CaM) binding proteins, identifying CaM interactions and binding sites in the wet-lab is tedious and costly. Therefore, computational methods for this purpose are crucial to the design of such wet-lab experiments. We present an algorithm suite called CaMELS (CalModulin intEraction Learning System) for predicting proteins that interact with CaM as well as their binding sites using sequence information alone. CaMELS offers state of the art accuracy for both CaM interaction and binding site prediction and can aid biologists in studying CaM binding proteins. For CaM interaction prediction, CaMELS uses protein sequence features coupled with a large-margin classifier. CaMELS models the binding site prediction problem using multiple instance machine learning with a custom optimization algorithm which allows more effective learning over imprecisely annotated CaM-binding sites during training. CaMELS has been extensively benchmarked using a variety of data sets, mutagenic studies, proteome-wide Gene Ontology enrichment analyses and protein structures. Our experiments indicate that CaMELS outperforms simple motif-based search and other existing methods for interaction and binding site prediction. We have also found that the whole sequence of a protein, rather than just its binding site, is important for predicting its interaction with CaM. Using the machine learning model in CaMELS, we have identified important features of protein sequences for CaM interaction prediction as well as characteristic amino acid sub-sequences and their relative position for identifying CaM binding sites. Python code for training and evaluating CaMELS together with a webserver implementation is available at the URL: http://faculty.pieas.edu.pk/fayyaz/software.html#camels. © 2017 Wiley Periodicals, Inc.

SCPRED: accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences.

PubMed

Kurgan, Lukasz; Cios, Krzysztof; Chen, Ke

2008-05-01

Protein structure prediction methods provide accurate results when a homologous protein is predicted, while poorer predictions are obtained in the absence of homologous templates. However, some protein chains that share twilight-zone pairwise identity can form similar folds and thus determining structural similarity without the sequence similarity would be desirable for the structure prediction. The folding type of a protein or its domain is defined as the structural class. Current structural class prediction methods that predict the four structural classes defined in SCOP provide up to 63% accuracy for the datasets in which sequence identity of any pair of sequences belongs to the twilight-zone. We propose SCPRED method that improves prediction accuracy for sequences that share twilight-zone pairwise similarity with sequences used for the prediction. SCPRED uses a support vector machine classifier that takes several custom-designed features as its input to predict the structural classes. Based on extensive design that considers over 2300 index-, composition- and physicochemical properties-based features along with features based on the predicted secondary structure and content, the classifier's input includes 8 features based on information extracted from the secondary structure predicted with PSI-PRED and one feature computed from the sequence. Tests performed with datasets of 1673 protein chains, in which any pair of sequences shares twilight-zone similarity, show that SCPRED obtains 80.3% accuracy when predicting the four SCOP-defined structural classes, which is superior when compared with over a dozen recent competing methods that are based on support vector machine, logistic regression, and ensemble of classifiers predictors. The SCPRED can accurately find similar structures for sequences that share low identity with sequence used for the prediction. The high predictive accuracy achieved by SCPRED is attributed to the design of the features, which are capable of separating the structural classes in spite of their low dimensionality. We also demonstrate that the SCPRED's predictions can be successfully used as a post-processing filter to improve performance of modern fold classification methods.

SCPRED: Accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences

PubMed Central

Kurgan, Lukasz; Cios, Krzysztof; Chen, Ke

2008-01-01

Background Protein structure prediction methods provide accurate results when a homologous protein is predicted, while poorer predictions are obtained in the absence of homologous templates. However, some protein chains that share twilight-zone pairwise identity can form similar folds and thus determining structural similarity without the sequence similarity would be desirable for the structure prediction. The folding type of a protein or its domain is defined as the structural class. Current structural class prediction methods that predict the four structural classes defined in SCOP provide up to 63% accuracy for the datasets in which sequence identity of any pair of sequences belongs to the twilight-zone. We propose SCPRED method that improves prediction accuracy for sequences that share twilight-zone pairwise similarity with sequences used for the prediction. Results SCPRED uses a support vector machine classifier that takes several custom-designed features as its input to predict the structural classes. Based on extensive design that considers over 2300 index-, composition- and physicochemical properties-based features along with features based on the predicted secondary structure and content, the classifier's input includes 8 features based on information extracted from the secondary structure predicted with PSI-PRED and one feature computed from the sequence. Tests performed with datasets of 1673 protein chains, in which any pair of sequences shares twilight-zone similarity, show that SCPRED obtains 80.3% accuracy when predicting the four SCOP-defined structural classes, which is superior when compared with over a dozen recent competing methods that are based on support vector machine, logistic regression, and ensemble of classifiers predictors. Conclusion The SCPRED can accurately find similar structures for sequences that share low identity with sequence used for the prediction. The high predictive accuracy achieved by SCPRED is attributed to the design of the features, which are capable of separating the structural classes in spite of their low dimensionality. We also demonstrate that the SCPRED's predictions can be successfully used as a post-processing filter to improve performance of modern fold classification methods. PMID:18452616

Incorporating information on predicted solvent accessibility to the co-evolution-based study of protein interactions.

PubMed

Ochoa, David; García-Gutiérrez, Ponciano; Juan, David; Valencia, Alfonso; Pazos, Florencio

2013-01-27

A widespread family of methods for studying and predicting protein interactions using sequence information is based on co-evolution, quantified as similarity of phylogenetic trees. Part of the co-evolution observed between interacting proteins could be due to co-adaptation caused by inter-protein contacts. In this case, the co-evolution is expected to be more evident when evaluated on the surface of the proteins or the internal layers close to it. In this work we study the effect of incorporating information on predicted solvent accessibility to three methods for predicting protein interactions based on similarity of phylogenetic trees. We evaluate the performance of these methods in predicting different types of protein associations when trees based on positions with different characteristics of predicted accessibility are used as input. We found that predicted accessibility improves the results of two recent versions of the mirrortree methodology in predicting direct binary physical interactions, while it neither improves these methods, nor the original mirrortree method, in predicting other types of interactions. That improvement comes at no cost in terms of applicability since accessibility can be predicted for any sequence. We also found that predictions of protein-protein interactions are improved when multiple sequence alignments with a richer representation of sequences (including paralogs) are incorporated in the accessibility prediction.

Capturing novel mouse genes encoding chromosomal and other nuclear proteins.

PubMed

Tate, P; Lee, M; Tweedie, S; Skarnes, W C; Bickmore, W A

1998-09-01

The burgeoning wealth of gene sequences contrasts with our ignorance of gene function. One route to assigning function is by determining the sub-cellular location of proteins. We describe the identification of mouse genes encoding proteins that are confined to nuclear compartments by splicing endogeneous gene sequences to a promoterless betageo reporter, using a gene trap approach. Mouse ES (embryonic stem) cell lines were identified that express betageo fusions located within sub-nuclear compartments, including chromosomes, the nucleolus and foci containing splicing factors. The sequences of 11 trapped genes were ascertained, and characterisation of endogenous protein distribution in two cases confirmed the validity of the approach. Three novel proteins concentrated within distinct chromosomal domains were identified, one of which appears to be a serine/threonine kinase. The sequence of a gene whose product co-localises with splicesome components suggests that this protein may be an E3 ubiquitin-protein ligase. The majority of the other genes isolated represent novel genes. This approach is shown to be a powerful tool for identifying genes encoding novel proteins with specific sub-nuclear localisations and exposes our ignorance of the protein composition of the nucleus. Motifs in two of the isolated genes suggest new links between cellular regulatory mechanisms (ubiquitination and phosphorylation) and mRNA splicing and chromosome structure/function.

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

NASA Astrophysics Data System (ADS)

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.

MutaBind estimates and interprets the effects of sequence variants on protein-protein interactions.

PubMed

Li, Minghui; Simonetti, Franco L; Goncearenco, Alexander; Panchenko, Anna R

2016-07-08

Proteins engage in highly selective interactions with their macromolecular partners. Sequence variants that alter protein binding affinity may cause significant perturbations or complete abolishment of function, potentially leading to diseases. There exists a persistent need to develop a mechanistic understanding of impacts of variants on proteins. To address this need we introduce a new computational method MutaBind to evaluate the effects of sequence variants and disease mutations on protein interactions and calculate the quantitative changes in binding affinity. The MutaBind method uses molecular mechanics force fields, statistical potentials and fast side-chain optimization algorithms. The MutaBind server maps mutations on a structural protein complex, calculates the associated changes in binding affinity, determines the deleterious effect of a mutation, estimates the confidence of this prediction and produces a mutant structural model for download. MutaBind can be applied to a large number of problems, including determination of potential driver mutations in cancer and other diseases, elucidation of the effects of sequence variants on protein fitness in evolution and protein design. MutaBind is available at http://www.ncbi.nlm.nih.gov/projects/mutabind/. Published by Oxford University Press on behalf of Nucleic Acids Research 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Computational allergenicity prediction of transgenic proteins expressed in genetically modified crops.

PubMed

Verma, Alok Kumar; Misra, Amita; Subash, Swarna; Das, Mukul; Dwivedi, Premendra D

2011-09-01

Development of genetically modified (GM) crops is on increase to improve food quality, increase harvest yields, and reduce the dependency on chemical pesticides. Before their release in marketplace, they should be scrutinized for their safety. Several guidelines of different regulatory agencies like ILSI, WHO Codex, OECD, and so on for allergenicity evaluation of transgenics are available and sequence homology analysis is the first test to determine the allergenic potential of inserted proteins. Therefore, to test and validate, 312 allergenic, 100 non-allergenic, and 48 inserted proteins were assessed for sequence similarity using 8-mer, 80-mer, and full FASTA search. On performing sequence homology studies, ~94% the allergenic proteins gave exact matches for 8-mer and 80-mer homology. However, 20 allergenic proteins showed non-allergenic behavior. Out of 100 non-allergenic proteins, seven qualified as allergens. None of the inserted proteins demonstrated allergenic behavior. In order to improve the predictability, proteins showing anomalous behavior were tested by Algpred and ADFS separately. Use of Algpred and ADFS softwares reduced the tendency of false prediction to a great extent (74-78%). In conclusion, routine sequence homology needs to be coupled with some other bioinformatic method like ADFS/Algpred to reduce false allergenicity prediction of novel proteins.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zemla, A; Lang, D; Kostova, T

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 facilitatemore » 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 residues at a given sequence position.« less

Sequence diagrams and the presentation of structural and evolutionary relationships among proteins.

PubMed

Thomas, B R

1975-01-01

Protein sequences mapped on two-dimensional diagrams show characteristic patterns that should be of value in visualising sequence information and in distinguishing simpler structures. A convenient map form for comparative purposes is the alpha-helix diagram with aminoacid distribution analogous to the surface of an alpha-helix oriented so that an alpha-helix structure corresponds on the diagram to a vertical band 3.6 residues wide. The sequence diagram for an alpha-keratin, high-sulphur protein suggests a new form of polypeptide helix based on a repeating unit of five which may be an important component of alpha-keratin fibres.

Plasma proteins of rainbow trout (Oncorhynchus mykiss) isolated by binding to lipopolysaccharide from Aeromonas salmonicida.

PubMed

Hoover, G J; el-Mowafi, A; Simko, E; Kocal, T E; Ferguson, H W; Hayes, M A

1998-07-01

In an attempt to find plasma proteins that might be involved in the constitutive resistance of rainbow trout to furunculosis, a disease caused by Aeromonas salmonicida (AS), we purified serum and plasma proteins based on their calcium- and carbohydrate-dependent affinity for A. salmonicida lipopolysaccharide (LPS) coupled to an epoxy-activated synthetic matrix (Toyopearl AF Epoxy 650M). A multimeric family of high molecular weight (96 to 200-kDa) LPS-binding proteins exhibiting both calcium and mannose dependent binding was isolated. Upon reduction the multimers collapsed to subunits of approximately 16-kDa as estimated by 1D-PAGE and exhibited pI values of 5.30 and 5.75 as estimated from 2D-PAGE. Their N-terminal sequences were related to rainbow trout ladderlectin (RT-LL), a Sepharose-binding protein. Polyclonal antibodies to the LPS-purified 16-kDa subunits recognized both the reduced 16-kDa subunits and the non-reduced multimeric forms. A calcium- and N-acetylglucosamine (GlcNAc)-dependent LPS-binding multimeric protein (approximately 207-kDa) composed of 34.5-kDa subunits was purified and found to be identical to trout serum amyloid P (SAP) by N-terminal sequence (DLQDLSGKVFV). A protein of 24-kDa, in reduced and non-reduced conditions, was isolated and had N-terminal sequence identity with a known C-reactive protein (CRP) homologue, C-polysaccharide-binding protein 2 (TCBP2) of rainbow trout. A novel calcium-dependent LPS-binding protein was purified and termed rainbow trout lectin 37 (RT-L37). This protein, composed of dimers, tetramers and pentamers of 37 kDa subunits (pI 5.50-6.10) with N-terminal sequence (IQE(D/N)GHAEAPGATTVLNEILR) showed no close homology to proteins known or predicted from cDNA sequences. These findings demonstrate that rainbow trout have several blood proteins with lectin properties for the LPS of A. salmonicida; the biological functions of these proteins in resistance to furunculosis are still unknown.

Sequence search on a supercomputer.

PubMed

Gotoh, O; Tagashira, Y

1986-01-10

A set of programs was developed for searching nucleic acid and protein sequence data bases for sequences similar to a given sequence. The programs, written in FORTRAN 77, were optimized for vector processing on a Hitachi S810-20 supercomputer. A search of a 500-residue protein sequence against the entire PIR data base Ver. 1.0 (1) (0.5 M residues) is carried out in a CPU time of 45 sec. About 4 min is required for an exhaustive search of a 1500-base nucleotide sequence against all mammalian sequences (1.2M bases) in Genbank Ver. 29.0. The CPU time is reduced to about a quarter with a faster version.

Protein-protein interaction network-based detection of functionally similar proteins within species.

PubMed

Song, Baoxing; Wang, Fen; Guo, Yang; Sang, Qing; Liu, Min; Li, Dengyun; Fang, Wei; Zhang, Deli

2012-07-01

Although functionally similar proteins across species have been widely studied, functionally similar proteins within species showing low sequence similarity have not been examined in detail. Identification of these proteins is of significant importance for understanding biological functions, evolution of protein families, progression of co-evolution, and convergent evolution and others which cannot be obtained by detection of functionally similar proteins across species. Here, we explored a method of detecting functionally similar proteins within species based on graph theory. After denoting protein-protein interaction networks using graphs, we split the graphs into subgraphs using the 1-hop method. Proteins with functional similarities in a species were detected using a method of modified shortest path to compare these subgraphs and to find the eligible optimal results. Using seven protein-protein interaction networks and this method, some functionally similar proteins with low sequence similarity that cannot detected by sequence alignment were identified. By analyzing the results, we found that, sometimes, it is difficult to separate homologous from convergent evolution. Evaluation of the performance of our method by gene ontology term overlap showed that the precision of our method was excellent. Copyright © 2012 Wiley Periodicals, Inc.