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Sample records for protein sequence based

  1. Protein Function Prediction Based on Sequence and Structure Information

    KAUST Repository

    Smaili, Fatima Z.

    2016-01-01

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

  2. Shotgun protein sequencing.

    Energy Technology Data Exchange (ETDEWEB)

    Faulon, Jean-Loup Michel; Heffelfinger, Grant S.

    2009-06-01

    A novel experimental and computational technique based on multiple enzymatic digestion of a protein or protein mixture that reconstructs protein sequences from sequences of overlapping peptides is described in this SAND report. This approach, analogous to shotgun sequencing of DNA, is to be used to sequence alternative spliced proteins, to identify post-translational modifications, and to sequence genetically engineered proteins.

  3. Protein Function Prediction Based on Sequence and Structure Information

    KAUST Repository

    Smaili, Fatima Z.

    2016-05-25

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

  4. Protein sequencing via nanopore based devices: a nanofluidics perspective

    Science.gov (United States)

    Chinappi, Mauro; Cecconi, Fabio

    2018-05-01

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

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

    Directory of Open Access Journals (Sweden)

    Dobbs Drena

    2011-06-01

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

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

    Science.gov (United States)

    Mishra, Pooja; Nath Pandey, Paras

    2012-10-21

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

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

    Science.gov (United States)

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

    2017-05-25

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

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

    Directory of Open Access Journals (Sweden)

    Yunyun Liang

    2015-01-01

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

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

    Science.gov (United States)

    Reiz, Bela; Li, Liang

    2010-09-01

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

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

    NARCIS (Netherlands)

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

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Mahdi Sarmady

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

  12. Sequence-based feature prediction and annotation of proteins

    DEFF Research Database (Denmark)

    Juncker, Agnieszka; Jensen, Lars J.; Pierleoni, Andrea

    2009-01-01

    A recent trend in computational methods for annotation of protein function is that many prediction tools are combined in complex workflows and pipelines to facilitate the analysis of feature combinations, for example, the entire repertoire of kinase-binding motifs in the human proteome....

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

    KAUST Repository

    Chen, Peng

    2015-12-03

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

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

    KAUST Repository

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

    2015-01-01

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

  15. Optimal protein library design using recombination or point mutations based on sequence-based scoring functions.

    Science.gov (United States)

    Pantazes, Robert J; Saraf, Manish C; Maranas, Costas D

    2007-08-01

    In this paper, we introduce and test two new sequence-based protein scoring systems (i.e. S1, S2) for assessing the likelihood that a given protein hybrid will be functional. By binning together amino acids with similar properties (i.e. volume, hydrophobicity and charge) the scoring systems S1 and S2 allow for the quantification of the severity of mismatched interactions in the hybrids. The S2 scoring system is found to be able to significantly functionally enrich a cytochrome P450 library over other scoring methods. Given this scoring base, we subsequently constructed two separate optimization formulations (i.e. OPTCOMB and OPTOLIGO) for optimally designing protein combinatorial libraries involving recombination or mutations, respectively. Notably, two separate versions of OPTCOMB are generated (i.e. model M1, M2) with the latter allowing for position-dependent parental fragment skipping. Computational benchmarking results demonstrate the efficacy of models OPTCOMB and OPTOLIGO to generate high scoring libraries of a prespecified size.

  16. Comparison of Enzymes / Non-Enzymes Proteins Classification Models Based on 3D, Composition, Sequences and Topological Indices

    OpenAIRE

    Munteanu, Cristian Robert

    2014-01-01

    Comparison of Enzymes / Non-Enzymes Proteins Classification Models Based on 3D, Composition, Sequences and Topological Indices, German Conference on Bioinformatics (GCB), Potsdam, Germany (September, 2007)

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

    DEFF Research Database (Denmark)

    Wiwie, Christian; Röttger, Richard

    2017-01-01

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

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

    Science.gov (United States)

    Gupta, Radhey S

    2012-11-01

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

  19. SVM-PB-Pred: SVM based protein block prediction method using sequence profiles and secondary structures.

    Science.gov (United States)

    Suresh, V; Parthasarathy, S

    2014-01-01

    We developed a support vector machine based web server called SVM-PB-Pred, to predict the Protein Block for any given amino acid sequence. The input features of SVM-PB-Pred include i) sequence profiles (PSSM) and ii) actual secondary structures (SS) from DSSP method or predicted secondary structures from NPS@ and GOR4 methods. There were three combined input features PSSM+SS(DSSP), PSSM+SS(NPS@) and PSSM+SS(GOR4) used to test and train the SVM models. Similarly, four datasets RS90, DB433, LI1264 and SP1577 were used to develop the SVM models. These four SVM models developed were tested using three different benchmarking tests namely; (i) self consistency, (ii) seven fold cross validation test and (iii) independent case test. The maximum possible prediction accuracy of ~70% was observed in self consistency test for the SVM models of both LI1264 and SP1577 datasets, where PSSM+SS(DSSP) input features was used to test. The prediction accuracies were reduced to ~53% for PSSM+SS(NPS@) and ~43% for PSSM+SS(GOR4) in independent case test, for the SVM models of above two same datasets. Using our method, it is possible to predict the protein block letters for any query protein sequence with ~53% accuracy, when the SP1577 dataset and predicted secondary structure from NPS@ server were used. The SVM-PB-Pred server can be freely accessed through http://bioinfo.bdu.ac.in/~svmpbpred.

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

    Science.gov (United States)

    Kurgan, Lukasz; Disfani, Fatemeh Miri

    2011-09-01

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

  1. Statistical potential-based amino acid similarity matrices for aligning distantly related protein sequences.

    Science.gov (United States)

    Tan, Yen Hock; Huang, He; Kihara, Daisuke

    2006-08-15

    Aligning distantly related protein sequences is a long-standing problem in bioinformatics, and a key for successful protein structure prediction. Its importance is increasing recently in the context of structural genomics projects because more and more experimentally solved structures are available as templates for protein structure modeling. Toward this end, recent structure prediction methods employ profile-profile alignments, and various ways of aligning two profiles have been developed. More fundamentally, a better amino acid similarity matrix can improve a profile itself; thereby resulting in more accurate profile-profile alignments. Here we have developed novel amino acid similarity matrices from knowledge-based amino acid contact potentials. Contact potentials are used because the contact propensity to the other amino acids would be one of the most conserved features of each position of a protein structure. The derived amino acid similarity matrices are tested on benchmark alignments at three different levels, namely, the family, the superfamily, and the fold level. Compared to BLOSUM45 and the other existing matrices, the contact potential-based matrices perform comparably in the family level alignments, but clearly outperform in the fold level alignments. The contact potential-based matrices perform even better when suboptimal alignments are considered. Comparing the matrices themselves with each other revealed that the contact potential-based matrices are very different from BLOSUM45 and the other matrices, indicating that they are located in a different basin in the amino acid similarity matrix space.

  2. Sequence and 3D structure based analysis of TNT degrading proteins in Arabidopsis thaliana.

    Science.gov (United States)

    Bhattacherjee, Amrita; Mandal, Rahul Shubhra; Das, Santasabuj; Kundu, Sudip

    2014-03-01

    TNT, accidentally released at several manufacturing sites, contaminates ground water and soil. It has a toxic effect to algae and invertebrate, and chronic exposure to TNT also causes harmful effects to human. On the other hand, many plants including Arabidopsis thaliana have the ability to metabolize TNT either completely or at least to a reduced less toxic form. In A. thaliana, the enzyme UDP glucosyltransferase (UDPGT) can further conjugate the reduced forms 2-HADNT and 4-HADNT (2-hydroxylamino-4, 6- dinitrotoluene and 4-hydroxylamino-2, 6- dinitrotoluene) of TNT. Based on the experimental analysis, existing literature and phylogenetic analysis, it is evident that among 107 UDPGT proteins only six are involved in the TNT degrading process. A total of 13 UDPGT proteins including five of these TNT degrading proteins fall within the same group of phylogeny. Thus, these 13 UDPGT proteins have been classified into two groups, TNT-degrading and TNT-non-degrading proteins. To understand the differences in TNT-degrading capacities; using homology modeling we first predicted two structures, taking one representative sequence from both the groups. Next, we performed molecular docking of the modeled structure and TNT reduced form 2-hydroxylamino-4, 6- dinitrotoluene (2-HADNT). We observed that while the Trp residue located within the active site region of the TNT- degrading protein showed π-Cation interaction; such type of interaction was absent in TNT-non-degrading protein, as the respective Trp residue lay outside of the pocket in this case. We observed the conservation of this π-Cation interaction during MD simulation of TNT-degrading protein. Thus, the position and the orientation of the active site residue Trp could explain the presence and absence of TNT-degrading capacity of the UDPGT proteins.

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

    Science.gov (United States)

    Matsuoka, Masanari; Sugita, Masatake; Kikuchi, Takeshi

    2014-09-18

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

  4. A stochastic context free grammar based framework for analysis of protein sequences

    Directory of Open Access Journals (Sweden)

    Nebel Jean-Christophe

    2009-10-01

    Full Text Available Abstract Background In the last decade, there have been many applications of formal language theory in bioinformatics such as RNA structure prediction and detection of patterns in DNA. However, in the field of proteomics, the size of the protein alphabet and the complexity of relationship between amino acids have mainly limited the application of formal language theory to the production of grammars whose expressive power is not higher than stochastic regular grammars. However, these grammars, like other state of the art methods, cannot cover any higher-order dependencies such as nested and crossing relationships that are common in proteins. In order to overcome some of these limitations, we propose a Stochastic Context Free Grammar based framework for the analysis of protein sequences where grammars are induced using a genetic algorithm. Results This framework was implemented in a system aiming at the production of binding site descriptors. These descriptors not only allow detection of protein regions that are involved in these sites, but also provide insight in their structure. Grammars were induced using quantitative properties of amino acids to deal with the size of the protein alphabet. Moreover, we imposed some structural constraints on grammars to reduce the extent of the rule search space. Finally, grammars based on different properties were combined to convey as much information as possible. Evaluation was performed on sites of various sizes and complexity described either by PROSITE patterns, domain profiles or a set of patterns. Results show the produced binding site descriptors are human-readable and, hence, highlight biologically meaningful features. Moreover, they achieve good accuracy in both annotation and detection. In addition, findings suggest that, unlike current state-of-the-art methods, our system may be particularly suited to deal with patterns shared by non-homologous proteins. Conclusion A new Stochastic Context Free

  5. PVP-SVM: Sequence-Based Prediction of Phage Virion Proteins Using a Support Vector Machine

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    Balachandran Manavalan

    2018-03-01

    Full Text Available Accurately identifying bacteriophage virion proteins from uncharacterized sequences is important to understand interactions between the phage and its host bacteria in order to develop new antibacterial drugs. However, identification of such proteins using experimental techniques is expensive and often time consuming; hence, development of an efficient computational algorithm for the prediction of phage virion proteins (PVPs prior to in vitro experimentation is needed. Here, we describe a support vector machine (SVM-based PVP predictor, called PVP-SVM, which was trained with 136 optimal features. A feature selection protocol was employed to identify the optimal features from a large set that included amino acid composition, dipeptide composition, atomic composition, physicochemical properties, and chain-transition-distribution. PVP-SVM achieved an accuracy of 0.870 during leave-one-out cross-validation, which was 6% higher than control SVM predictors trained with all features, indicating the efficiency of the feature selection method. Furthermore, PVP-SVM displayed superior performance compared to the currently available method, PVPred, and two other machine-learning methods developed in this study when objectively evaluated with an independent dataset. For the convenience of the scientific community, a user-friendly and publicly accessible web server has been established at www.thegleelab.org/PVP-SVM/PVP-SVM.html.

  6. PVP-SVM: Sequence-Based Prediction of Phage Virion Proteins Using a Support Vector Machine.

    Science.gov (United States)

    Manavalan, Balachandran; Shin, Tae H; Lee, Gwang

    2018-01-01

    Accurately identifying bacteriophage virion proteins from uncharacterized sequences is important to understand interactions between the phage and its host bacteria in order to develop new antibacterial drugs. However, identification of such proteins using experimental techniques is expensive and often time consuming; hence, development of an efficient computational algorithm for the prediction of phage virion proteins (PVPs) prior to in vitro experimentation is needed. Here, we describe a support vector machine (SVM)-based PVP predictor, called PVP-SVM, which was trained with 136 optimal features. A feature selection protocol was employed to identify the optimal features from a large set that included amino acid composition, dipeptide composition, atomic composition, physicochemical properties, and chain-transition-distribution. PVP-SVM achieved an accuracy of 0.870 during leave-one-out cross-validation, which was 6% higher than control SVM predictors trained with all features, indicating the efficiency of the feature selection method. Furthermore, PVP-SVM displayed superior performance compared to the currently available method, PVPred, and two other machine-learning methods developed in this study when objectively evaluated with an independent dataset. For the convenience of the scientific community, a user-friendly and publicly accessible web server has been established at www.thegleelab.org/PVP-SVM/PVP-SVM.html.

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

    Directory of Open Access Journals (Sweden)

    Lees Jonathan G

    2008-01-01

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

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

    Lifescience Database Archive (English)

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

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

    KAUST Repository

    Zhang, Zhang; Yu, Jun

    2010-01-01

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

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

    KAUST Repository

    Zhang, Zhang

    2010-11-08

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

  11. Structure-sequence based analysis for identification of conserved regions in proteins

    Science.gov (United States)

    Zemla, Adam T; Zhou, Carol E; Lam, Marisa W; Smith, Jason R; Pardes, Elizabeth

    2013-05-28

    Disclosed are computational methods, and associated hardware and software products for scoring conservation in a protein structure based on a computationally identified family or cluster of protein structures. A method of computationally identifying a family or cluster of protein structures in also disclosed herein.

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

    Science.gov (United States)

    Raghav, Sunil Kumar; Deplancke, Bart

    2012-01-01

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

  13. Complete genome sequence of Klebsiella pneumoniae J1, a protein-based microbial flocculant-producing bacterium.

    Science.gov (United States)

    Pang, Changlong; Li, Ang; Cui, Di; Yang, Jixian; Ma, Fang; Guo, Haijuan

    2016-02-20

    Klebsiella pneumoniae J1 is a Gram-negative strain, which belongs to a protein-based microbial flocculant-producing bacterium. However, little genetic information is known about this species. Here we carried out a whole-genome sequence analysis of this strain and report the complete genome sequence of this organism and its genetic basis for carbohydrate metabolism, capsule biosynthesis and transport system. Copyright © 2016 Elsevier B.V. All rights reserved.

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

    DEFF Research Database (Denmark)

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

    2013-01-01

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

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

    Science.gov (United States)

    Orenstein, Yaron; Wang, Yuhao; Berger, Bonnie

    2016-06-15

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

  16. Protein sequence comparison and protein evolution

    Energy Technology Data Exchange (ETDEWEB)

    Pearson, W.R. [Univ. of Virginia, Charlottesville, VA (United States). Dept. of Biochemistry

    1995-12-31

    This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. This tutorial examines how the information conserved during the evolution of a protein molecule can be used to infer reliably homology, and thus a shared proteinfold and possibly a shared active site or function. The authors start by reviewing a geological/evolutionary time scale. Next they look at the evolution of several protein families. During the tutorial, these families will be used to demonstrate that homologous protein ancestry can be inferred with confidence. They also examine different modes of protein evolution and consider some hypotheses that have been presented to explain the very earliest events in protein evolution. The next part of the tutorial will examine the technical aspects of protein sequence comparison. Both optimal and heuristic algorithms and their associated parameters that are used to characterize protein sequence similarities are discussed. Perhaps more importantly, they survey the statistics of local similarity scores, and how these statistics can both be used to improve the selectivity of a search and to evaluate the significance of a match. They them examine distantly related members of three protein families, the serine proteases, the glutathione transferases, and the G-protein-coupled receptors (GCRs). Finally, the discuss how sequence similarity can be used to examine internal repeated or mosaic structures in proteins.

  17. A Bayesian-probability-based method for assigning protein backbone dihedral angles based on chemical shifts and local sequences

    Energy Technology Data Exchange (ETDEWEB)

    Wang Jun; Liu Haiyan [University of Science and Technology of China, Hefei National Laboratory for Physical Sciences at the Microscale, and Key Laboratory of Structural Biology, School of Life Sciences (China)], E-mail: hyliu@ustc.edu.cn

    2007-01-15

    Chemical shifts contain substantial information about protein local conformations. We present a method to assign individual protein backbone dihedral angles into specific regions on the Ramachandran map based on the amino acid sequences and the chemical shifts of backbone atoms of tripeptide segments. The method uses a scoring function derived from the Bayesian probability for the central residue of a query tripeptide segment to have a particular conformation. The Ramachandran map is partitioned into representative regions at two levels of resolution. The lower resolution partitioning is equivalent to the conventional definitions of different secondary structure regions on the map. At the higher resolution level, the {alpha} and {beta} regions are further divided into subregions. Predictions are attempted at both levels of resolution. We compared our method with TALOS using the original TALOS database, and obtained comparable results. Although TALOS may produce the best results with currently available databases which are much enlarged, the Bayesian-probability-based approach can provide a quantitative measure for the reliability of predictions.

  18. Molecular identification based on coat protein sequences of the Barley yellow dwarf virus from Brazil

    Directory of Open Access Journals (Sweden)

    Talita Bernardon Mar

    2013-12-01

    Full Text Available Yellow dwarf disease, one of the most important diseases of cereal crops worldwide, is caused by virus species belonging to the Luteoviridae family. Forty-two virus isolates obtained from oat (Avena sativa L., wheat (Triticum aestivum L., barley (Hordeum vulgare L., corn (Zea mays L., and ryegrass (Lolium multiflorum Lam. collected between 2007 and 2008 from winter cereal crop regions in southern Brazil were screened by polymerase chain reaction (PCR with primers designed on ORF 3 (coat protein - CP for the presence of Barley yellow dwarf virus and Cereal yellow dwarf virus (B/CYDV. PCR products of expected size (~357 bp for subgroup II and (~831 bp for subgroup I were obtained for three and 39 samples, respectively. These products were cloned and sequenced. The subgroup II 3' partial CP amino acid deduced sequences were identified as BYDV-RMV (92 - 93 % of identity with "Illinois" Z14123 isolate. The complete CP amino acid deduced sequences of subgroup I isolates were confirmed as BYDV-PAV (94 - 99 % of identity and established a very homogeneous group (identity higher than 99 %. These results support the prevalence of BYDV-PAV in southern Brazil as previously diagnosed by Enzyme-Linked Immunosorbent Assay (ELISA and suggest that this population is very homogeneous. To our knowledge, this is the first report of BYDV-RMV in Brazil and the first genetic diversity study on B/CYDV in South America.

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

    NARCIS (Netherlands)

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

    2017-01-01

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

  20. STING Millennium: a web-based suite of programs for comprehensive and simultaneous analysis of protein structure and sequence

    Science.gov (United States)

    Neshich, Goran; Togawa, Roberto C.; Mancini, Adauto L.; Kuser, Paula R.; Yamagishi, Michel E. B.; Pappas, Georgios; Torres, Wellington V.; Campos, Tharsis Fonseca e; Ferreira, Leonardo L.; Luna, Fabio M.; Oliveira, Adilton G.; Miura, Ronald T.; Inoue, Marcus K.; Horita, Luiz G.; de Souza, Dimas F.; Dominiquini, Fabiana; Álvaro, Alexandre; Lima, Cleber S.; Ogawa, Fabio O.; Gomes, Gabriel B.; Palandrani, Juliana F.; dos Santos, Gabriela F.; de Freitas, Esther M.; Mattiuz, Amanda R.; Costa, Ivan C.; de Almeida, Celso L.; Souza, Savio; Baudet, Christian; Higa, Roberto H.

    2003-01-01

    STING Millennium Suite (SMS) is a new web-based suite of programs and databases providing visualization and a complex analysis of molecular sequence and structure for the data deposited at the Protein Data Bank (PDB). SMS operates with a collection of both publicly available data (PDB, HSSP, Prosite) and its own data (contacts, interface contacts, surface accessibility). Biologists find SMS useful because it provides a variety of algorithms and validated data, wrapped-up in a user friendly web interface. Using SMS it is now possible to analyze sequence to structure relationships, the quality of the structure, nature and volume of atomic contacts of intra and inter chain type, relative conservation of amino acids at the specific sequence position based on multiple sequence alignment, indications of folding essential residue (FER) based on the relationship of the residue conservation to the intra-chain contacts and Cα–Cα and Cβ–Cβ distance geometry. Specific emphasis in SMS is given to interface forming residues (IFR)—amino acids that define the interactive portion of the protein surfaces. SMS may simultaneously display and analyze previously superimposed structures. PDB updates trigger SMS updates in a synchronized fashion. SMS is freely accessible for public data at http://www.cbi.cnptia.embrapa.br, http://mirrors.rcsb.org/SMS and http://trantor.bioc.columbia.edu/SMS. PMID:12824333

  1. Sequence Based Prediction of Antioxidant Proteins Using a Classifier Selection Strategy.

    Directory of Open Access Journals (Sweden)

    Lina Zhang

    Full Text Available Antioxidant proteins perform significant functions in maintaining oxidation/antioxidation balance and have potential therapies for some diseases. Accurate identification of antioxidant proteins could contribute to revealing physiological processes of oxidation/antioxidation balance and developing novel antioxidation-based drugs. In this study, an ensemble method is presented to predict antioxidant proteins with hybrid features, incorporating SSI (Secondary Structure Information, PSSM (Position Specific Scoring Matrix, RSA (Relative Solvent Accessibility, and CTD (Composition, Transition, Distribution. The prediction results of the ensemble predictor are determined by an average of prediction results of multiple base classifiers. Based on a classifier selection strategy, we obtain an optimal ensemble classifier composed of RF (Random Forest, SMO (Sequential Minimal Optimization, NNA (Nearest Neighbor Algorithm, and J48 with an accuracy of 0.925. A Relief combined with IFS (Incremental Feature Selection method is adopted to obtain optimal features from hybrid features. With the optimal features, the ensemble method achieves improved performance with a sensitivity of 0.95, a specificity of 0.93, an accuracy of 0.94, and an MCC (Matthew's Correlation Coefficient of 0.880, far better than the existing method. To evaluate the prediction performance objectively, the proposed method is compared with existing methods on the same independent testing dataset. Encouragingly, our method performs better than previous studies. In addition, our method achieves more balanced performance with a sensitivity of 0.878 and a specificity of 0.860. These results suggest that the proposed ensemble method can be a potential candidate for antioxidant protein prediction. For public access, we develop a user-friendly web server for antioxidant protein identification that is freely accessible at http://antioxidant.weka.cc.

  2. A modified strategy for sequence specific assignment of protein NMR spectra based on amino acid type selective experiments

    International Nuclear Information System (INIS)

    Schubert, Mario; Labudde, Dirk; Leitner, Dietmar; Oschkinat, Hartmut; Schmieder, Peter

    2005-01-01

    The determination of the three-dimensional structure of a protein or the study of protein-ligand interactions requires the assignment of all relevant nuclei as an initial step. This is nowadays almost exclusively performed using triple-resonance experiments. The conventional strategy utilizes one or more pairs of three dimensional spectra to obtain redundant information and thus reliable assignments. Here, a modified strategy for obtaining sequence specific assignments based on two dimensional amino acid type selective triple-resonance experiments is proposed. These experiments can be recorded with good resolution in a relatively short time. They provide very specific and redundant information, in particular on sequential connectivities, that drastically increases the ease and reliability of the assignment procedure, done either manually or in an automated fashion. The new strategy is demonstrated with the protein domain PB1 from yeast CDC24p

  3. Sequence-based prediction of protein-binding sites in DNA: comparative study of two SVM models.

    Science.gov (United States)

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

    2014-11-01

    As many structures of protein-DNA complexes have been known in the past years, several computational methods have been developed to predict DNA-binding sites in proteins. However, its inverse problem (i.e., predicting protein-binding sites in DNA) has received much less attention. One of the reasons is that the differences between the interaction propensities of nucleotides are much smaller than those between amino acids. Another reason is that DNA exhibits less diverse sequence patterns than protein. Therefore, predicting protein-binding DNA nucleotides is much harder than predicting DNA-binding amino acids. We computed the interaction propensity (IP) of nucleotide triplets with amino acids using an extensive dataset of protein-DNA complexes, and developed two support vector machine (SVM) models that predict protein-binding nucleotides from sequence data alone. One SVM model predicts protein-binding nucleotides using DNA sequence data alone, and the other SVM model predicts protein-binding nucleotides using both DNA and protein sequences. In a 10-fold cross-validation with 1519 DNA sequences, the SVM model that uses DNA sequence data only predicted protein-binding nucleotides with an accuracy of 67.0%, an F-measure of 67.1%, and a Matthews correlation coefficient (MCC) of 0.340. With an independent dataset of 181 DNAs that were not used in training, it achieved an accuracy of 66.2%, an F-measure 66.3% and a MCC of 0.324. Another SVM model that uses both DNA and protein sequences achieved an accuracy of 69.6%, an F-measure of 69.6%, and a MCC of 0.383 in a 10-fold cross-validation with 1519 DNA sequences and 859 protein sequences. With an independent dataset of 181 DNAs and 143 proteins, it showed an accuracy of 67.3%, an F-measure of 66.5% and a MCC of 0.329. Both in cross-validation and independent testing, the second SVM model that used both DNA and protein sequence data showed better performance than the first model that used DNA sequence data. To the best of

  4. Repeat Sequence Proteins as Matrices for Nanocomposites

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-01-01

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

  5. Strategy for complete NMR assignment of disordered proteins with highly repetitive sequences based on resolution-enhanced 5D experiments

    Energy Technology Data Exchange (ETDEWEB)

    Motackova, Veronika; Novacek, Jiri [Masaryk University, Faculty of Science, National Centre for Biomolecular Research (Czech Republic); Zawadzka-Kazimierczuk, Anna; Kazimierczuk, Krzysztof [University of Warsaw, Faculty of Chemistry (Poland); Zidek, Lukas, E-mail: lzidek@chemi.muni.c [Masaryk University, Faculty of Science, National Centre for Biomolecular Research (Czech Republic); Sanderova, Hana; Krasny, Libor [Academy of Sciences of the Czech Republic, Laboratory of Molecular Genetics of Bacteria and Department of Bacteriology, Institute of Microbiology (Czech Republic); Kozminski, Wiktor [University of Warsaw, Faculty of Chemistry (Poland); Sklenar, Vladimir [Masaryk University, Faculty of Science, National Centre for Biomolecular Research (Czech Republic)

    2010-11-15

    A strategy for complete backbone and side-chain resonance assignment of disordered proteins with highly repetitive sequence is presented. The protocol is based on three resolution-enhanced NMR experiments: 5D HN(CA)CONH provides sequential connectivity, 5D HabCabCONH is utilized to identify amino acid types, and 5D HC(CC-TOCSY)CONH is used to assign the side-chain resonances. The improved resolution was achieved by a combination of high dimensionality and long evolution times, allowed by non-uniform sampling in the indirect dimensions. Random distribution of the data points and Sparse Multidimensional Fourier Transform processing were used. Successful application of the assignment procedure to a particularly difficult protein, {delta} subunit of RNA polymerase from Bacillus subtilis, is shown to prove the efficiency of the strategy. The studied protein contains a disordered C-terminal region of 81 amino acids with a highly repetitive sequence. While the conventional assignment methods completely failed due to a very small differences in chemical shifts, the presented strategy provided a complete backbone and side-chain assignment.

  6. Generating markers based on biotic stress of protein system in and tandem repeats sequence for Aquilaria sp

    International Nuclear Information System (INIS)

    Azhar Mohamad; Muhammad Hanif Azhari N; Siti Norhayati Ismail

    2014-01-01

    Aquilaria sp. belongs to the Thymelaeaceae family and is well distributed in Asia region. The species has multipurpose use from root to shoot and is an economically important crop, which generates wide interest in understanding genetic diversity of the species. Knowledge on DNA-based markers has become a prerequisite for more effective application of molecular marker techniques in breeding and mapping programs. In this work, both targeted genes and tandem repeat sequences were used for DNA fingerprinting in Aquilaria sp. A total of 100 ISSR (inter simple sequence repeat) primers and 50 combination pairs of specific primers derived from conserved region of a specific protein known as system in were optimized. 38 ISSR primers were found affirmative for polymorphism evaluation study and were generated from both specific and degenerate ISSR primers. And one utmost combination of system in primers showed significant results in distinguishing the Aquilaria sp. In conclusion, polymorphism derived from ISSR profiling and targeted stress genes of protein system in proved as a powerful approach for identification and molecular classification of Aquilaria sp. which will be useful for diversification in identifying any mutant lines derived from nature. (author)

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

    Science.gov (United States)

    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 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.

  8. mPUMA: a computational approach to microbiota analysis by de novo assembly of operational taxonomic units based on protein-coding barcode sequences.

    Science.gov (United States)

    Links, Matthew G; Chaban, Bonnie; Hemmingsen, Sean M; Muirhead, Kevin; Hill, Janet E

    2013-08-15

    Formation of operational taxonomic units (OTU) is a common approach to data aggregation in microbial ecology studies based on amplification and sequencing of individual gene targets. The de novo assembly of OTU sequences has been recently demonstrated as an alternative to widely used clustering methods, providing robust information from experimental data alone, without any reliance on an external reference database. Here we introduce mPUMA (microbial Profiling Using Metagenomic Assembly, http://mpuma.sourceforge.net), a software package for identification and analysis of protein-coding barcode sequence data. It was developed originally for Cpn60 universal target sequences (also known as GroEL or Hsp60). Using an unattended process that is independent of external reference sequences, mPUMA forms OTUs by DNA sequence assembly and is capable of tracking OTU abundance. mPUMA processes microbial profiles both in terms of the direct DNA sequence as well as in the translated amino acid sequence for protein coding barcodes. By forming OTUs and calculating abundance through an assembly approach, mPUMA is capable of generating inputs for several popular microbiota analysis tools. Using SFF data from sequencing of a synthetic community of Cpn60 sequences derived from the human vaginal microbiome, we demonstrate that mPUMA can faithfully reconstruct all expected OTU sequences and produce compositional profiles consistent with actual community structure. mPUMA enables analysis of microbial communities while empowering the discovery of novel organisms through OTU assembly.

  9. The structural analysis of protein sequences based on the quasi-amino acids code

    International Nuclear Information System (INIS)

    Ping, Zhu; Xu-Qing, Tang; Zhen-Yuan, Xu

    2009-01-01

    Proteomics is the study of proteins and their interactions in a cell. With the successful completion of the Human Genome Project, it comes the postgenome era when the proteomics technology is emerging. This paper studies protein molecule from the algebraic point of view. The algebraic system (Σ, +, *) is introduced, where Σ is the set of 64 codons. According to the characteristics of (Σ, +, *), a novel quasi-amino acids code classification method is introduced and the corresponding algebraic operation table over the set ZU of the 16 kinds of quasi-amino acids is established. The internal relation is revealed about quasi-amino acids. The results show that there exist some very close correlations between the properties of the quasi-amino acids and the codon. All these correlation relationships may play an important part in establishing the logic relationship between codons and the quasi-amino acids during the course of life origination. According to Ma F et al (2003 J. Anhui Agricultural University 30 439), the corresponding relation and the excellent properties about amino acids code are very difficult to observe. The present paper shows that (ZU, ⊕, ) is a field. Furthermore, the operational results display that the codon tga has different property from other stop codons. In fact, in the mitochondrion from human and ox genomic codon, tga is just tryptophane, is not the stop codon like in other genetic code, it is the case of the Chen W C et al (2002 Acta Biophysica Sinica 18(1) 87). The present theory avoids some inexplicable events of the 20 kinds of amino acids code, in other words it solves the problem of 'the 64 codon assignments of mRNA to amino acids is probably completely wrong' proposed by Yang (2006 Progress in Modern Biomedicine 6 3). (cross-disciplinary physics and related areas of science and technology)

  10. Genetic diversity and molecular evolution of Ornithogalum mosaic virus based on the coat protein gene sequence

    Directory of Open Access Journals (Sweden)

    Fangluan Gao

    2018-03-01

    Full Text Available Ornithogalum mosaic virus (OrMV has a wide host range and affects the production of a variety of ornamentals. In this study, the coat protein (CP gene of OrMVwas used to investigate the molecular mechanisms underlying the evolution of this virus. The 36 OrMV isolates fell into two groups which have significant subpopulation differentiation with an FST value of 0.470. One isolate was identified as a recombinant and the other 35 recombination-free isolates could be divided into two major clades under different evolutionary constraints with dN/dS values of 0.055 and 0.028, respectively, indicating a role of purifying selection in the differentiation of OrMV. In addition, the results from analysis of molecular variance (AMOVA indicated that the effect of host species on the genetic divergence of OrMV is greater than that of geography. Furthermore, OrMV isolates from the genera Ornithogalum, Lachenalia and Diuri tended to group together, indicating that OrMV diversification was maintained, in part, by host-driven adaptation.

  11. Novel algorithms for protein sequence analysis

    NARCIS (Netherlands)

    Ye, Kai

    2008-01-01

    Each protein is characterized by its unique sequential order of amino acids, the so-called protein sequence. Biology”s paradigm is that this order of amino acids determines the protein”s architecture and function. In this thesis, we introduce novel algorithms to analyze protein sequences. Chapter 1

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

    Directory of Open Access Journals (Sweden)

    Khader Shameer

    2010-06-01

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

  13. PROCARB: A Database of Known and Modelled Carbohydrate-Binding Protein Structures with Sequence-Based Prediction Tools

    Directory of Open Access Journals (Sweden)

    Adeel Malik

    2010-01-01

    Full Text Available Understanding of the three-dimensional structures of proteins that interact with carbohydrates covalently (glycoproteins as well as noncovalently (protein-carbohydrate complexes is essential to many biological processes and plays a significant role in normal and disease-associated functions. It is important to have a central repository of knowledge available about these protein-carbohydrate complexes as well as preprocessed data of predicted structures. This can be significantly enhanced by tools de novo which can predict carbohydrate-binding sites for proteins in the absence of structure of experimentally known binding site. PROCARB is an open-access database comprising three independently working components, namely, (i Core PROCARB module, consisting of three-dimensional structures of protein-carbohydrate complexes taken from Protein Data Bank (PDB, (ii Homology Models module, consisting of manually developed three-dimensional models of N-linked and O-linked glycoproteins of unknown three-dimensional structure, and (iii CBS-Pred prediction module, consisting of web servers to predict carbohydrate-binding sites using single sequence or server-generated PSSM. Several precomputed structural and functional properties of complexes are also included in the database for quick analysis. In particular, information about function, secondary structure, solvent accessibility, hydrogen bonds and literature reference, and so forth, is included. In addition, each protein in the database is mapped to Uniprot, Pfam, PDB, and so forth.

  14. HIV protein sequence hotspots for crosstalk with host hub proteins.

    Directory of Open Access Journals (Sweden)

    Mahdi Sarmady

    Full Text Available HIV proteins target host hub proteins for transient binding interactions. The presence of viral proteins in the infected cell results in out-competition of host proteins in their interaction with hub proteins, drastically affecting cell physiology. Functional genomics and interactome datasets can be used to quantify the sequence hotspots on the HIV proteome mediating interactions with host hub proteins. In this study, we used the HIV and human interactome databases to identify HIV targeted host hub proteins and their host binding partners (H2. We developed a high throughput computational procedure utilizing motif discovery algorithms on sets of protein sequences, including sequences of HIV and H2 proteins. We identified as HIV sequence hotspots those linear motifs that are highly conserved on HIV sequences and at the same time have a statistically enriched presence on the sequences of H2 proteins. The HIV protein motifs discovered in this study are expressed by subsets of H2 host proteins potentially outcompeted by HIV proteins. A large subset of these motifs is involved in cleavage, nuclear localization, phosphorylation, and transcription factor binding events. Many such motifs are clustered on an HIV sequence in the form of hotspots. The sequential positions of these hotspots are consistent with the curated literature on phenotype altering residue mutations, as well as with existing binding site data. The hotspot map produced in this study is the first global portrayal of HIV motifs involved in altering the host protein network at highly connected hub nodes.

  15. Prunus necrotic ringspot ilarvirus: nucleotide sequence of RNA3 and the relationship to other ilarviruses based on coat protein comparison.

    Science.gov (United States)

    Guo, D; Maiss, E; Adam, G; Casper, R

    1995-05-01

    The RNA3 of prunus necrotic ringspot ilarvirus (PNRSV) has been cloned and its entire sequence determined. The RNA3 consists of 1943 nucleotides (nt) and possesses two large open reading frames (ORFs) separated by an intergenic region of 74 nt. The 5' proximal ORF is 855 nt in length and codes for a protein of molecular mass 31.4 kDa which has homologies with the putative movement protein of other members of the Bromoviridae. The 3' proximal ORF of 675 nt is the cistron for the coat protein (CP) and has a predicted molecular mass of 24.9 kDa. The sequence of the 3' non-coding region (NCR) of PNRSV RNA3 showed a high degree of similarity with those of tobacco streak virus (TSV), prune dwarf virus (PDV), apple mosaic virus (ApMV) and also alfalfa mosaic virus (AIMV). In addition it contained potential stem-loop structures with interspersed AUGC motifs characteristic for ilar- and alfamoviruses. This conserved primary and secondary structure in all 3' NCRs may be responsible for the interaction with homologous and heterologous CPs and subsequent activation of genome replication. The CP gene of an ApMV isolate (ApMV-G) of 657 nt has also been cloned and sequenced. Although ApMV and PNRSV have a distant serological relationship, the deduced amino acid sequences of their CPs have an identity of only 51.8%. The N termini of PNRSV and ApMV CPs have in common a zinc-finger motif and the potential to form an amphipathic helix.

  16. Insights into SCP/TAPS proteins of liver flukes based on large-scale bioinformatic analyses of sequence datasets.

    Directory of Open Access Journals (Sweden)

    Cinzia Cantacessi

    Full Text Available BACKGROUND: SCP/TAPS proteins of parasitic helminths have been proposed to play key roles in fundamental biological processes linked to the invasion of and establishment in their mammalian host animals, such as the transition from free-living to parasitic stages and the modulation of host immune responses. Despite the evidence that SCP/TAPS proteins of parasitic nematodes are involved in host-parasite interactions, there is a paucity of information on this protein family for parasitic trematodes of socio-economic importance. METHODOLOGY/PRINCIPAL FINDINGS: We conducted the first large-scale study of SCP/TAPS proteins of a range of parasitic trematodes of both human and veterinary importance (including the liver flukes Clonorchis sinensis, Opisthorchis viverrini, Fasciola hepatica and F. gigantica as well as the blood flukes Schistosoma mansoni, S. japonicum and S. haematobium. We mined all current transcriptomic and/or genomic sequence datasets from public databases, predicted secondary structures of full-length protein sequences, undertook systematic phylogenetic analyses and investigated the differential transcription of SCP/TAPS genes in O. viverrini and F. hepatica, with an emphasis on those that are up-regulated in the developmental stages infecting the mammalian host. CONCLUSIONS: This work, which sheds new light on SCP/TAPS proteins, guides future structural and functional explorations of key SCP/TAPS molecules associated with diseases caused by flatworms. Future fundamental investigations of these molecules in parasites and the integration of structural and functional data could lead to new approaches for the control of parasitic diseases.

  17. PIPE: a protein-protein interaction prediction engine based on the re-occurring short polypeptide sequences between known interacting protein pairs

    Directory of Open Access Journals (Sweden)

    Greenblatt Jack

    2006-07-01

    Full Text Available Abstract Background Identification of protein interaction networks has received considerable attention in the post-genomic era. The currently available biochemical approaches used to detect protein-protein interactions are all time and labour intensive. Consequently there is a growing need for the development of computational tools that are capable of effectively identifying such interactions. Results Here we explain the development and implementation of a novel Protein-Protein Interaction Prediction Engine termed PIPE. This tool is capable of predicting protein-protein interactions for any target pair of the yeast Saccharomyces cerevisiae proteins from their primary structure and without the need for any additional information or predictions about the proteins. PIPE showed a sensitivity of 61% for detecting any yeast protein interaction with 89% specificity and an overall accuracy of 75%. This rate of success is comparable to those associated with the most commonly used biochemical techniques. Using PIPE, we identified a novel interaction between YGL227W (vid30 and YMR135C (gid8 yeast proteins. This lead us to the identification of a novel yeast complex that here we term vid30 complex (vid30c. The observed interaction was confirmed by tandem affinity purification (TAP tag, verifying the ability of PIPE to predict novel protein-protein interactions. We then used PIPE analysis to investigate the internal architecture of vid30c. It appeared from PIPE analysis that vid30c may consist of a core and a secondary component. Generation of yeast gene deletion strains combined with TAP tagging analysis indicated that the deletion of a member of the core component interfered with the formation of vid30c, however, deletion of a member of the secondary component had little effect (if any on the formation of vid30c. Also, PIPE can be used to analyse yeast proteins for which TAP tagging fails, thereby allowing us to predict protein interactions that are not

  18. Improving accuracy of protein-protein interaction prediction by considering the converse problem for sequence representation

    Directory of Open Access Journals (Sweden)

    Wang Yong

    2011-10-01

    Full Text Available Abstract Background With the development of genome-sequencing technologies, protein sequences are readily obtained by translating the measured mRNAs. Therefore predicting protein-protein interactions from the sequences is of great demand. The reason lies in the fact that identifying protein-protein interactions is becoming a bottleneck for eventually understanding the functions of proteins, especially for those organisms barely characterized. Although a few methods have been proposed, the converse problem, if the features used extract sufficient and unbiased information from protein sequences, is almost untouched. Results In this study, we interrogate this problem theoretically by an optimization scheme. Motivated by the theoretical investigation, we find novel encoding methods for both protein sequences and protein pairs. Our new methods exploit sufficiently the information of protein sequences and reduce artificial bias and computational cost. Thus, it significantly outperforms the available methods regarding sensitivity, specificity, precision, and recall with cross-validation evaluation and reaches ~80% and ~90% accuracy in Escherichia coli and Saccharomyces cerevisiae respectively. Our findings here hold important implication for other sequence-based prediction tasks because representation of biological sequence is always the first step in computational biology. Conclusions By considering the converse problem, we propose new representation methods for both protein sequences and protein pairs. The results show that our method significantly improves the accuracy of protein-protein interaction predictions.

  19. Sequence-Based Prediction of RNA-Binding Proteins Using Random Forest with Minimum Redundancy Maximum Relevance Feature Selection

    Directory of Open Access Journals (Sweden)

    Xin Ma

    2015-01-01

    Full Text Available The prediction of RNA-binding proteins is one of the most challenging problems in computation biology. Although some studies have investigated this problem, the accuracy of prediction is still not sufficient. In this study, a highly accurate method was developed to predict RNA-binding proteins from amino acid sequences using random forests with the minimum redundancy maximum relevance (mRMR method, followed by incremental feature selection (IFS. We incorporated features of conjoint triad features and three novel features: binding propensity (BP, nonbinding propensity (NBP, and evolutionary information combined with physicochemical properties (EIPP. The results showed that these novel features have important roles in improving the performance of the predictor. Using the mRMR-IFS method, our predictor achieved the best performance (86.62% accuracy and 0.737 Matthews correlation coefficient. High prediction accuracy and successful prediction performance suggested that our method can be a useful approach to identify RNA-binding proteins from sequence information.

  20. Partial sequence determination of metabolically labeled radioactive proteins and peptides

    International Nuclear Information System (INIS)

    Anderson, C.W.

    1982-01-01

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

  1. Use of designed sequences in protein structure recognition.

    Science.gov (United States)

    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.

  2. First study on gene expression of cement proteins and potential adhesion-related genes of a membranous-based barnacle as revealed from Next-Generation Sequencing technology

    KAUST Repository

    Lin, Hsiu Chin; Wong, Yue Him; Tsang, Ling Ming; Chu, Ka Hou; Qian, Pei Yuan; Chan, Benny K K

    2013-01-01

    This is the first study applying Next-Generation Sequencing (NGS) technology to survey the kinds, expression location, and pattern of adhesion-related genes in a membranous-based barnacle. A total of 77,528,326 and 59,244,468 raw sequence reads of total RNA were generated from the prosoma and the basis of Tetraclita japonica formosana, respectively. In addition, 55,441 and 67,774 genes were further assembled and analyzed. The combined sequence data from both body parts generates a total of 79,833 genes of which 47.7% were shared. Homologues of barnacle cement proteins - CP-19K, -52K, and -100K - were found and all were dominantly expressed at the basis where the cement gland complex is located. This is the main area where transcripts of cement proteins and other potential adhesion-related genes were detected. The absence of another common barnacle cement protein, CP-20K, in the adult transcriptome suggested a possible life-stage restricted gene function and/or a different mechanism in adhesion between membranous-based and calcareous-based barnacles. © 2013 © 2013 Taylor & Francis.

  3. First study on gene expression of cement proteins and potential adhesion-related genes of a membranous-based barnacle as revealed from Next-Generation Sequencing technology

    KAUST Repository

    Lin, Hsiu Chin

    2013-12-12

    This is the first study applying Next-Generation Sequencing (NGS) technology to survey the kinds, expression location, and pattern of adhesion-related genes in a membranous-based barnacle. A total of 77,528,326 and 59,244,468 raw sequence reads of total RNA were generated from the prosoma and the basis of Tetraclita japonica formosana, respectively. In addition, 55,441 and 67,774 genes were further assembled and analyzed. The combined sequence data from both body parts generates a total of 79,833 genes of which 47.7% were shared. Homologues of barnacle cement proteins - CP-19K, -52K, and -100K - were found and all were dominantly expressed at the basis where the cement gland complex is located. This is the main area where transcripts of cement proteins and other potential adhesion-related genes were detected. The absence of another common barnacle cement protein, CP-20K, in the adult transcriptome suggested a possible life-stage restricted gene function and/or a different mechanism in adhesion between membranous-based and calcareous-based barnacles. © 2013 © 2013 Taylor & Francis.

  4. Sequence based prediction of DNA-binding proteins based on hybrid feature selection using random forest and Gaussian naïve Bayes.

    Directory of Open Access Journals (Sweden)

    Wangchao Lou

    Full Text Available Developing an efficient method for determination of the DNA-binding proteins, due to their vital roles in gene regulation, is becoming highly desired since it would be invaluable to advance our understanding of protein functions. In this study, we proposed a new method for the prediction of the DNA-binding proteins, by performing the feature rank using random forest and the wrapper-based feature selection using forward best-first search strategy. The features comprise information from primary sequence, predicted secondary structure, predicted relative solvent accessibility, and position specific scoring matrix. The proposed method, called DBPPred, used Gaussian naïve Bayes as the underlying classifier since it outperformed five other classifiers, including decision tree, logistic regression, k-nearest neighbor, support vector machine with polynomial kernel, and support vector machine with radial basis function. As a result, the proposed DBPPred yields the highest average accuracy of 0.791 and average MCC of 0.583 according to the five-fold cross validation with ten runs on the training benchmark dataset PDB594. Subsequently, blind tests on the independent dataset PDB186 by the proposed model trained on the entire PDB594 dataset and by other five existing methods (including iDNA-Prot, DNA-Prot, DNAbinder, DNABIND and DBD-Threader were performed, resulting in that the proposed DBPPred yielded the highest accuracy of 0.769, MCC of 0.538, and AUC of 0.790. The independent tests performed by the proposed DBPPred on completely a large non-DNA binding protein dataset and two RNA binding protein datasets also showed improved or comparable quality when compared with the relevant prediction methods. Moreover, we observed that majority of the selected features by the proposed method are statistically significantly different between the mean feature values of the DNA-binding and the non DNA-binding proteins. All of the experimental results indicate that

  5. Sequence analysis reveals how G protein-coupled receptors transduce the signal to the G protein.

    NARCIS (Netherlands)

    Oliveira, L.; Paiva, P.B.; Paiva, A.C.; Vriend, G.

    2003-01-01

    Sequence entropy-variability plots based on alignments of very large numbers of sequences-can indicate the location in proteins of the main active site and modulator sites. In the previous article in this issue, we applied this observation to a series of well-studied proteins and concluded that it

  6. Formatt: Correcting protein multiple structural alignments by incorporating sequence alignment

    Directory of Open Access Journals (Sweden)

    Daniels Noah M

    2012-10-01

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

  7. Simple sequence proteins in prokaryotic proteomes

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    Ramachandran Srinivasan

    2006-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Jinjian Jiang

    2017-07-01

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

  9. Taxonomic colouring of phylogenetic trees of protein sequences

    Directory of Open Access Journals (Sweden)

    Andrade-Navarro Miguel A

    2006-02-01

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

  10. Nonlinear deterministic structures and the randomness of protein sequences

    CERN Document Server

    Huang Yan Zhao

    2003-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  12. WildSpan: mining structured motifs from protein sequences

    Directory of Open Access Journals (Sweden)

    Chen Chien-Yu

    2011-03-01

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

  13. Semi-Supervised Learning for Classification of Protein Sequence Data

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    Brian R. King

    2008-01-01

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

  14. Sequence-Based Analysis of Thermal Adaptation and Protein Energy Landscapes in an Invasive Blue Mussel (Mytilus galloprovincialis).

    Science.gov (United States)

    Saarman, Norah P; Kober, Kord M; Simison, W Brian; Pogson, Grant H

    2017-10-01

    Adaptive responses to thermal stress in poikilotherms plays an important role in determining competitive ability and species distributions. Amino acid substitutions that affect protein stability and modify the thermal optima of orthologous proteins may be particularly important in this context. Here, we examine a set of 2,770 protein-coding genes to determine if proteins in a highly invasive heat tolerant blue mussel (Mytilus galloprovincialis) contain signals of adaptive increases in protein stability relative to orthologs in a more cold tolerant M. trossulus. Such thermal adaptations might help to explain, mechanistically, the success with which the invasive marine mussel M. galloprovincialis has displaced native species in contact zones in the eastern (California) and western (Japan) Pacific. We tested for stabilizing amino acid substitutions in warm tolerant M. galloprovincialis relative to cold tolerant M. trossulus with a generalized linear model that compares in silico estimates of recent changes in protein stability among closely related congeners. Fixed substitutions in M. galloprovincialis were 3,180.0 calories per mol per substitution more stabilizing at genes with both elevated dN/dS ratios and transcriptional responses to heat stress, and 705.8 calories per mol per substitution more stabilizing across all 2,770 loci investigated. Amino acid substitutions concentrated in a small number of genes were more stabilizing in M. galloprovincialis compared with cold tolerant M. trossulus. We also tested for, but did not find, enrichment of a priori GO terms in genes with elevated dN/dS ratios in M. galloprovincialis. This might indicate that selection for thermodynamic stability is generic across all lineages, and suggests that the high change in estimated protein stability that we observed in M. galloprovincialis is driven by selection for extra stabilizing substitutions, rather than by higher incidence of selection in a greater number of genes in this lineage

  15. Classification of G-protein coupled receptors based on a rich generation of convolutional neural network, N-gram transformation and multiple sequence alignments.

    Science.gov (United States)

    Li, Man; Ling, Cheng; Xu, Qi; Gao, Jingyang

    2018-02-01

    Sequence classification is crucial in predicting the function of newly discovered sequences. In recent years, the prediction of the incremental large-scale and diversity of sequences has heavily relied on the involvement of machine-learning algorithms. To improve prediction accuracy, these algorithms must confront the key challenge of extracting valuable features. In this work, we propose a feature-enhanced protein classification approach, considering the rich generation of multiple sequence alignment algorithms, N-gram probabilistic language model and the deep learning technique. The essence behind the proposed method is that if each group of sequences can be represented by one feature sequence, composed of homologous sites, there should be less loss when the sequence is rebuilt, when a more relevant sequence is added to the group. On the basis of this consideration, the prediction becomes whether a query sequence belonging to a group of sequences can be transferred to calculate the probability that the new feature sequence evolves from the original one. The proposed work focuses on the hierarchical classification of G-protein Coupled Receptors (GPCRs), which begins by extracting the feature sequences from the multiple sequence alignment results of the GPCRs sub-subfamilies. The N-gram model is then applied to construct the input vectors. Finally, these vectors are imported into a convolutional neural network to make a prediction. The experimental results elucidate that the proposed method provides significant performance improvements. The classification error rate of the proposed method is reduced by at least 4.67% (family level I) and 5.75% (family Level II), in comparison with the current state-of-the-art methods. The implementation program of the proposed work is freely available at: https://github.com/alanFchina/CNN .

  16. Determining and comparing protein function in Bacterial genome sequences

    DEFF Research Database (Denmark)

    Vesth, Tammi Camilla

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

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

    Science.gov (United States)

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

  18. Putative recombination events and evolutionary history of five economically important viruses of fruit trees based on coat protein-encoding gene sequence analysis.

    Science.gov (United States)

    Boulila, Moncef

    2010-06-01

    To enhance the knowledge of recombination as an evolutionary process, 267 accessions retrieved from GenBank were investigated, all belonging to five economically important viruses infecting fruit crops (Plum pox, Apple chlorotic leaf spot, Apple mosaic, Prune dwarf, and Prunus necrotic ringspot viruses). Putative recombinational events were detected in the coat protein (CP)-encoding gene using RECCO and RDP version 3.31beta algorithms. Based on RECCO results, all five viruses were shown to contain potential recombination signals in the CP gene. Reconstructed trees with modified topologies were proposed. Furthermore, RECCO performed better than the RDP package in detecting recombination events and exhibiting their evolution rate along the sequences of the five viruses. RDP, however, provided the possible major and minor parents of the recombinants. Thus, the two methods should be considered complementary.

  19. Amino Acids Sequence Based in Silico Analysis of RuBisCO (Ribulose-1,5 Bisphosphate Carboxylase Oxygenase Proteins in Some Carthamus L. ssp.

    Directory of Open Access Journals (Sweden)

    Emre SEVİNDİK

    2017-06-01

    Full Text Available RuBisCO is an important enzyme for plants to photosynthesize and balance carbon dioxide in the atmosphere. This study aimed to perform sequence, physicochemical, phylogenetic and 3D (three-dimensional comparative analyses of RuBisCO proteins in the Carthamus ssp. using various bioinformatics tools. The sequence lengths of the RuBisCO proteins were between 166 and 477 amino acids, with an average length of 411.8 amino acids. Their molecular weights (Mw ranged from 18711.47 to 52843.09 Da; the most acidic and basic protein sequences were detected in C. tinctorius (pI = 5.99 and in C. tenuis (pI = 6.92, respectively. The extinction coefficients of RuBisCO proteins at 280 nm ranged from 17,670 to 69,830 M-1 cm-1, the instability index (II values for RuBisCO proteins ranged from 33.31 to 39.39, while the GRAVY values of RuBisCO proteins ranged from -0.313 to -0.250. The most abundant amino acid in the RuBisCO protein was Gly (9.7%, while the least amino acid ratio was Trp (1.6 %. The putative phosphorylation sites of RuBisCO proteins were determined by NetPhos 2.0. Phylogenetic analysis revealed that RuBisCO proteins formed two main clades. A RAMPAGE analysis revealed that 96.3%-97.6% of residues were located in the favoured region of RuBisCO proteins. To predict the three dimensional (3D structure of the RuBisCO proteins PyMOL was used. The results of the current study provide insights into fundamental characteristic of RuBisCO proteins in Carthamus ssp.

  20. B and T Cell Epitope-Based Peptides Predicted from Evolutionarily Conserved and Whole Protein Sequences of Ebola Virus as Vaccine Targets.

    Science.gov (United States)

    Yasmin, T; Nabi, A H M Nurun

    2016-05-01

    Ebola virus (EBV) has become a serious threat to public health. Different approaches were applied to predict continuous and discontinuous B cell epitopes as well as T cell epitopes from the sequence-based and available three-dimensional structural analyses of each protein of EBV. Peptides '(79) VPSATKRWGFRSGVPP(94) ' from GP1 and '(515) LHYWTTQDEGAAIGLA(530) ' from GP2 of Ebola were found to be the consensus peptidic sequences predicted as linear B cell epitope of which the latter contains a region (519) TTQDEG(524) that fulfilled all the criteria of accessibility, hydrophilicity, flexibility and beta turn region for becoming an ideal B cell epitope. Different nonamers as T cell epitopes were obtained that interacted with different numbers of MHC class I and class II alleles with a binding affinity of <100 nm. Interestingly, these alleles also bound to the MHC class I alleles mostly prevalent in African and South Asian regions. Of these, 'LANETTQAL' and 'FLYDRLAST' nonamers were predicted to be the most potent T cell epitopes and they, respectively, interacted with eight and twelve class I alleles that covered 63.79% and 54.16% of world population, respectively. These nonamers were found to be the core sequences of 15mer peptides that interacted with the most common class II allele, HLA-DRB1*01:01. They were further validated for their binding to specific class I alleles using docking technique. Thus, these predicted epitopes may be used as vaccine targets against EBV and can be validated in model hosts to verify their efficacy as vaccine. © 2016 The Foundation for the Scandinavian Journal of Immunology.

  1. Sequence alignment reveals possible MAPK docking motifs on HIV proteins.

    Directory of Open Access Journals (Sweden)

    Perry Evans

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

  2. Biophysical and structural considerations for protein sequence evolution

    Directory of Open Access Journals (Sweden)

    Grahnen Johan A

    2011-12-01

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

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

    OpenAIRE

    Bairoch, A; Boeckmann, B

    1994-01-01

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

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

    Science.gov (United States)

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

    2011-08-21

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

  5. Next-Generation Sequencing for Binary Protein-Protein Interactions

    Directory of Open Access Journals (Sweden)

    Bernhard eSuter

    2015-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Mile Sikić

    2009-01-01

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

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

    Science.gov (United States)

    Hayat, Maqsood; Khan, Asifullah

    2011-02-21

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

  8. Ultra-fast evaluation of protein energies directly from sequence.

    Directory of Open Access Journals (Sweden)

    Gevorg Grigoryan

    2006-06-01

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

  9. Molecular typing of methicillin-resistant Staphylococcus aureus: Comparison of PCR-based open reading frame typing, multilocus sequence typing, and Staphylococcus protein A gene typing.

    Science.gov (United States)

    Ogihara, Shinji; Saito, Ryoichi; Sawabe, Etsuko; Kozakai, Takahiro; Shima, Mari; Aiso, Yoshibumi; Fujie, Toshihide; Nukui, Yoko; Koike, Ryuji; Hagihara, Michio; Tohda, Shuji

    2018-04-01

    The recently developed PCR-based open reading frame typing (POT) method is a useful molecular typing tool. Here, we evaluated the performance of POT for molecular typing of methicillin-resistant Staphylococcus aureus (MRSA) isolates and compared its performance to those of multilocus sequence typing (MLST) and Staphylococcus protein A gene typing (spa typing). Thirty-seven MRSA isolates were collected between July 2012 and May 2015. MLST, spa typing, and POT were performed, and their discriminatory powers were evaluated using Simpson's index analysis. The MRSA isolates were classified into 11, 18, and 33 types by MLST, spa typing, and POT, respectively. The predominant strains identified by MLST, spa typing, and POT were ST8 and ST764, t002, and 93-191-127, respectively. The discriminatory power of MLST, spa typing, and POT was 0.853, 0.875, and 0.992, respectively, indicating that POT had the highest discriminatory power. Moreover, the results of MLST and spa were available after 2 days, whereas that of POT was available in 5 h. Furthermore, POT is rapid and easy to perform and interpret. Therefore, POT is a superior molecular typing tool for monitoring nosocomial transmission of MRSA. Copyright © 2017 Japanese Society of Chemotherapy and The Japanese Association for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

  10. Immunomodulatory Activity of Ganoderma atrum Polysaccharide on Purified T Lymphocytes through Ca2+/CaN and Mitogen-Activated Protein Kinase Pathway Based on RNA Sequencing.

    Science.gov (United States)

    Xiang, Quan-Dan; Yu, Qiang; Wang, Hui; Zhao, Ming-Ming; Liu, Shi-Yu; Nie, Shao-Ping; Xie, Ming-Yong

    2017-07-05

    Our previous study has demonstrated that Ganoderma atrum polysaccharide (PSG-1) has immunomodulatory activity on spleen lymphocytes. However, how PSG-1 exerts its effect on purified lymphocytes is still obscure. Thus, this study aimed to investigate the immunomodulatory activity of PSG-1 on purified T lymphocytes and further elucidate the underlying mechanism based on RNA sequencing (RNA-seq). Our results showed that PSG-1 promoted T lymphocytes proliferation and increased the production of IL-2, IFN-γ, and IL-12. Meanwhile, RNA-seq analysis found 394 differentially expressed genes. KEGG pathway analysis identified 20 significant canonical pathways and seven biological functions. Furthermore, PSG-1 elevated intracellular Ca 2+ concentration and calcineurin (CaN) activity and raised the p-ERK, p-JNK, and p-p38 expression levels. T lymphocytes proliferation and the production of IL-2, IFN-γ, and IL-12 were decreased by the inhibitors of calcium channel and mitogen-activated protein kinases (MAPKs). These results indicated that PSG-1 possesses immunomodulatory activity on purified T lymphocytes, in which Ca 2+ /CaN and MAPK pathways play essential roles.

  11. SNAD: sequence name annotation-based designer

    Directory of Open Access Journals (Sweden)

    Gorbalenya Alexander E

    2009-08-01

    Full Text Available Abstract Background A growing diversity of biological data is tagged with unique identifiers (UIDs associated with polynucleotides and proteins to ensure efficient computer-mediated data storage, maintenance, and processing. These identifiers, which are not informative for most people, are often substituted by biologically meaningful names in various presentations to facilitate utilization and dissemination of sequence-based knowledge. This substitution is commonly done manually that may be a tedious exercise prone to mistakes and omissions. Results Here we introduce SNAD (Sequence Name Annotation-based Designer that mediates automatic conversion of sequence UIDs (associated with multiple alignment or phylogenetic tree, or supplied as plain text list into biologically meaningful names and acronyms. This conversion is directed by precompiled or user-defined templates that exploit wealth of annotation available in cognate entries of external databases. Using examples, we demonstrate how this tool can be used to generate names for practical purposes, particularly in virology. Conclusion A tool for controllable annotation-based conversion of sequence UIDs into biologically meaningful names and acronyms has been developed and placed into service, fostering links between quality of sequence annotation, and efficiency of communication and knowledge dissemination among researchers.

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

    Science.gov (United States)

    Tian, Pengfei; Best, Robert B

    2017-10-17

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

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

    Science.gov (United States)

    Richardson, Dale N.; Wiehe, Thomas

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

  14. CISAPS: Complex Informational Spectrum for the Analysis of Protein Sequences

    Directory of Open Access Journals (Sweden)

    Charalambos Chrysostomou

    2015-01-01

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

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

    Science.gov (United States)

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

    2001-01-01

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

  16. DNA sequence modeling based on context trees

    NARCIS (Netherlands)

    Kusters, C.J.; Ignatenko, T.; Roland, J.; Horlin, F.

    2015-01-01

    Genomic sequences contain instructions for protein and cell production. Therefore understanding and identification of biologically and functionally meaningful patterns in DNA sequences is of paramount importance. Modeling of DNA sequences in its turn can help to better understand and identify such

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

    Science.gov (United States)

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

    1997-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Kevin R Ramkissoon

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

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

    Science.gov (United States)

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

    2013-01-01

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

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

    KAUST Repository

    Cui, Xuefeng

    2016-06-15

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

  1. Complete cDNA sequence coding for human docking protein

    Energy Technology Data Exchange (ETDEWEB)

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

    1988-01-11

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

  2. AlignMe—a membrane protein sequence alignment web server

    Science.gov (United States)

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

    2014-01-01

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

  3. MIPS: a database for protein sequences and complete genomes.

    Science.gov (United States)

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

    1998-01-01

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

  4. Dynamics of domain coverage of the protein sequence universe

    Science.gov (United States)

    2012-01-01

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

  5. Dynamics of domain coverage of the protein sequence universe

    Directory of Open Access Journals (Sweden)

    Rekapalli Bhanu

    2012-11-01

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

  6. Meta-analysis of sequence-based association studies across three cattle breeds reveals 25 QTL for fat and protein percentages in milk at nucleotide resolution.

    Science.gov (United States)

    Pausch, Hubert; Emmerling, Reiner; Gredler-Grandl, Birgit; Fries, Ruedi; Daetwyler, Hans D; Goddard, Michael E

    2017-11-09

    Genotyping and whole-genome sequencing data have been generated for hundreds of thousands of cattle. International consortia used these data to compile imputation reference panels that facilitate the imputation of sequence variant genotypes for animals that have been genotyped using dense microarrays. Association studies with imputed sequence variant genotypes allow for the characterization of quantitative trait loci (QTL) at nucleotide resolution particularly when individuals from several breeds are included in the mapping populations. We imputed genotypes for 28 million sequence variants in 17,229 cattle of the Braunvieh, Fleckvieh and Holstein breeds in order to compile large mapping populations that provide high power to identify QTL for milk production traits. Association tests between imputed sequence variant genotypes and fat and protein percentages in milk uncovered between six and thirteen QTL (P < 1e-8) per breed. Eight of the detected QTL were significant in more than one breed. We combined the results across breeds using meta-analysis and identified a total of 25 QTL including six that were not significant in the within-breed association studies. Two missense mutations in the ABCG2 (p.Y581S, rs43702337, P = 4.3e-34) and GHR (p.F279Y, rs385640152, P = 1.6e-74) genes were the top variants at QTL on chromosomes 6 and 20. Another known causal missense mutation in the DGAT1 gene (p.A232K, rs109326954, P = 8.4e-1436) was the second top variant at a QTL on chromosome 14 but its allelic substitution effects were inconsistent across breeds. It turned out that the conflicting allelic substitution effects resulted from flaws in the imputed genotypes due to the use of a multi-breed reference population for genotype imputation. Many QTL for milk production traits segregate across breeds and across-breed meta-analysis has greater power to detect such QTL than within-breed association testing. Association testing between imputed sequence variant genotypes and

  7. Nonlinear analysis of sequence repeats of multi-domain proteins

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-11-15

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

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

    Directory of Open Access Journals (Sweden)

    Pagni Marco

    2005-08-01

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

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

    Directory of Open Access Journals (Sweden)

    Gaston K Mazandu

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

  10. Analysis of correlations between sites in models of protein sequences

    International Nuclear Information System (INIS)

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

    1998-01-01

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

  11. An algorithm to find all palindromic sequences in proteins

    Indian Academy of Sciences (India)

    2013-01-20

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

  12. Discriminating Microbial Species Using Protein Sequence Properties and Machine Learning

    NARCIS (Netherlands)

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

    2007-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Cheng-Hsien Wu

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

  14. Identification of a novel calcium binding motif based on the detection of sequence insertions in the animal peroxidase domain of bacterial proteins.

    Directory of Open Access Journals (Sweden)

    Saray Santamaría-Hernando

    Full Text Available Proteins of the animal heme peroxidase (ANP superfamily differ greatly in size since they have either one or two catalytic domains that match profile PS50292. The orf PP_2561 of Pseudomonas putida KT2440 that we have called PepA encodes a two-domain ANP. The alignment of these domains with those of PepA homologues revealed a variable number of insertions with the consensus G-x-D-G-x-x-[GN]-[TN]-x-D-D. This motif has also been detected in the structure of pseudopilin (pdb 3G20, where it was found to be involved in Ca(2+ coordination although a sequence analysis did not reveal the presence of any known calcium binding motifs in this protein. Isothermal titration calorimetry revealed that a peptide containing this consensus motif bound specifically calcium ions with affinities ranging between 33-79 µM depending on the pH. Microcalorimetric titrations of the purified N-terminal ANP-like domain of PepA revealed Ca(2+ binding with a K(D of 12 µM and stoichiometry of 1.25 calcium ions per protein monomer. This domain exhibited peroxidase activity after its reconstitution with heme. These data led to the definition of a novel calcium binding motif that we have termed PERCAL and which was abundantly present in animal peroxidase-like domains of bacterial proteins. Bacterial heme peroxidases thus possess two different types of calcium binding motifs, namely PERCAL and the related hemolysin type calcium binding motif, with the latter being located outside the catalytic domains and in their C-terminal end. A phylogenetic tree of ANP-like catalytic domains of bacterial proteins with PERCAL motifs, including single domain peroxidases, was divided into two major clusters, representing domains with and without PERCAL motif containing insertions. We have verified that the recently reported classification of bacterial heme peroxidases in two families (cd09819 and cd09821 is unrelated to these insertions. Sequences matching PERCAL were detected in all kingdoms of

  15. Identification of a novel calcium binding motif based on the detection of sequence insertions in the animal peroxidase domain of bacterial proteins.

    Science.gov (United States)

    Santamaría-Hernando, Saray; Krell, Tino; Ramos-González, María-Isabel

    2012-01-01

    Proteins of the animal heme peroxidase (ANP) superfamily differ greatly in size since they have either one or two catalytic domains that match profile PS50292. The orf PP_2561 of Pseudomonas putida KT2440 that we have called PepA encodes a two-domain ANP. The alignment of these domains with those of PepA homologues revealed a variable number of insertions with the consensus G-x-D-G-x-x-[GN]-[TN]-x-D-D. This motif has also been detected in the structure of pseudopilin (pdb 3G20), where it was found to be involved in Ca(2+) coordination although a sequence analysis did not reveal the presence of any known calcium binding motifs in this protein. Isothermal titration calorimetry revealed that a peptide containing this consensus motif bound specifically calcium ions with affinities ranging between 33-79 µM depending on the pH. Microcalorimetric titrations of the purified N-terminal ANP-like domain of PepA revealed Ca(2+) binding with a K(D) of 12 µM and stoichiometry of 1.25 calcium ions per protein monomer. This domain exhibited peroxidase activity after its reconstitution with heme. These data led to the definition of a novel calcium binding motif that we have termed PERCAL and which was abundantly present in animal peroxidase-like domains of bacterial proteins. Bacterial heme peroxidases thus possess two different types of calcium binding motifs, namely PERCAL and the related hemolysin type calcium binding motif, with the latter being located outside the catalytic domains and in their C-terminal end. A phylogenetic tree of ANP-like catalytic domains of bacterial proteins with PERCAL motifs, including single domain peroxidases, was divided into two major clusters, representing domains with and without PERCAL motif containing insertions. We have verified that the recently reported classification of bacterial heme peroxidases in two families (cd09819 and cd09821) is unrelated to these insertions. Sequences matching PERCAL were detected in all kingdoms of life.

  16. The relationship of protein conservation and sequence length

    Directory of Open Access Journals (Sweden)

    Panchenko Anna R

    2002-11-01

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

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

    International Nuclear Information System (INIS)

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

    2010-01-01

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

  18. Experimental Rugged Fitness Landscape in Protein Sequence Space

    Science.gov (United States)

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

    2006-01-01

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

  19. Experimental rugged fitness landscape in protein sequence space.

    Science.gov (United States)

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

    2006-12-20

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

  20. Experimental rugged fitness landscape in protein sequence space.

    Directory of Open Access Journals (Sweden)

    Yuuki Hayashi

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

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

    Science.gov (United States)

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

    2018-03-01

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

  2. The SWISS-PROT protein sequence data bank

    OpenAIRE

    Bairoch, Amos; Boeckmann, Brigitte

    1992-01-01

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

  3. Aligning protein sequence and analysing substitution pattern using ...

    Indian Academy of Sciences (India)

    Prakash

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

  4. Comparative genomics beyond sequence-based alignments

    DEFF Research Database (Denmark)

    Þórarinsson, Elfar; Yao, Zizhen; Wiklund, Eric D.

    2008-01-01

    Recent computational scans for non-coding RNAs (ncRNAs) in multiple organisms have relied on existing multiple sequence alignments. However, as sequence similarity drops, a key signal of RNA structure--frequent compensating base changes--is increasingly likely to cause sequence-based alignment me...

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

    Science.gov (United States)

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

    2017-09-01

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

  6. Protein 3D structure computed from evolutionary sequence variation.

    Directory of Open Access Journals (Sweden)

    Debora S Marks

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

  7. In Silico Characterization of Pectate Lyase Protein Sequences from Different Source Organisms

    Directory of Open Access Journals (Sweden)

    Amit Kumar Dubey

    2010-01-01

    Full Text Available A total of 121 protein sequences of pectate lyases were subjected to homology search, multiple sequence alignment, phylogenetic tree construction, and motif analysis. The phylogenetic tree constructed revealed different clusters based on different source organisms representing bacterial, fungal, plant, and nematode pectate lyases. The multiple accessions of bacterial, fungal, nematode, and plant pectate lyase protein sequences were placed closely revealing a sequence level similarity. The multiple sequence alignment of these pectate lyase protein sequences from different source organisms showed conserved regions at different stretches with maximum homology from amino acid residues 439–467, 715–816, and 829–910 which could be used for designing degenerate primers or probes specific for pectate lyases. The motif analysis revealed a conserved Pec_Lyase_C domain uniformly observed in all pectate lyases irrespective of variable sources suggesting its possible role in structural and enzymatic functions.

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

    Directory of Open Access Journals (Sweden)

    Suganthan PN

    2007-09-01

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

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

    Science.gov (United States)

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

    2017-07-17

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

  10. MIPS: a database for genomes and protein sequences.

    Science.gov (United States)

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

    2002-01-01

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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    Sridhar, Settu; Guruprasad, Kunchur

    2014-01-01

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

  13. Correlated mutations in protein sequences: Phylogenetic and structural effects

    Energy Technology Data Exchange (ETDEWEB)

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

    1998-12-01

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

  14. Single-molecule protein sequencing through fingerprinting: computational assessment

    Science.gov (United States)

    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.

  15. Single-molecule protein sequencing through fingerprinting: computational assessment

    International Nuclear Information System (INIS)

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

    2015-01-01

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

  16. Deep sequencing methods for protein engineering and design.

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Stefanie D. Hueber

    2016-02-01

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

  18. Structure and Sequence Search on Aptamer-Protein Docking

    Science.gov (United States)

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

    2015-03-01

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

  19. 3D representations of amino acids—applications to protein sequence comparison and classification

    Directory of Open Access Journals (Sweden)

    Jie Li

    2014-08-01

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

  20. Osteocalcin protein sequences of Neanderthals and modern primates.

    Science.gov (United States)

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

    2005-03-22

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

  1. Experimental Rugged Fitness Landscape in Protein Sequence Space

    OpenAIRE

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

    2006-01-01

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

  2. EST2Prot: Mapping EST sequences to proteins

    Directory of Open Access Journals (Sweden)

    Lin David M

    2006-03-01

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

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

    Indian Academy of Sciences (India)

    Unknown

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

  4. Representation of protein-sequence information by amino acid subalphabets

    DEFF Research Database (Denmark)

    Andersen, C.A.F.; Brunak, Søren

    2004-01-01

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

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

    Science.gov (United States)

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

    2012-01-03

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

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

    Directory of Open Access Journals (Sweden)

    Halperin Rebecca F

    2012-01-01

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

  7. The HMMER Web Server for Protein Sequence Similarity Search.

    Science.gov (United States)

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

    2017-12-08

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

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

    Science.gov (United States)

    Neuwald, Andrew F

    2009-08-01

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

  9. Biological sequence analysis: probabilistic models of proteins and nucleic acids

    National Research Council Canada - National Science Library

    Durbin, Richard

    1998-01-01

    ... analysis methods are now based on principles of probabilistic modelling. Examples of such methods include the use of probabilistically derived score matrices to determine the significance of sequence alignments, the use of hidden Markov models as the basis for profile searches to identify distant members of sequence families, and the inference...

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

    Science.gov (United States)

    Garrido-Martín, Diego; Pazos, Florencio

    2018-02-27

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

  11. Sequence heterogeneity accelerates protein search for targets on DNA

    International Nuclear Information System (INIS)

    Shvets, Alexey A.; Kolomeisky, Anatoly B.

    2015-01-01

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

  12. Sequence heterogeneity accelerates protein search for targets on DNA

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-12-28

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

  13. Relationships between residue Voronoi volume and sequence conservation in proteins.

    Science.gov (United States)

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

    2018-02-01

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

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

    Directory of Open Access Journals (Sweden)

    Aalt D J van Dijk

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

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

    Directory of Open Access Journals (Sweden)

    Jun Wang

    2017-11-01

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

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

    DEFF Research Database (Denmark)

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

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

  17. Protein-protein interaction network-based detection of functionally similar proteins within species.

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Holly J Atkinson

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

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

    Science.gov (United States)

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

    2009-01-01

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

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

    Science.gov (United States)

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

    2017-07-01

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

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

    Directory of Open Access Journals (Sweden)

    Colin A Smith

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

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

    International Nuclear Information System (INIS)

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

    1986-01-01

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

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

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    Zhou Yuan Wu

    2013-07-01

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

  4. Protein sequences bound to mineral surfaces persist into deep time

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  5. Computational identification of MoRFs in protein sequences.

    Science.gov (United States)

    Malhis, Nawar; Gsponer, Jörg

    2015-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Bastiaan A van den Berg

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

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

    Directory of Open Access Journals (Sweden)

    Ruan Jishou

    2007-04-01

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

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

    Science.gov (United States)

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

    2016-09-01

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

  9. Functional analysis of bipartite begomovirus coat protein promoter sequences

    International Nuclear Information System (INIS)

    Lacatus, Gabriela; Sunter, Garry

    2008-01-01

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

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

    Directory of Open Access Journals (Sweden)

    TIJANA SAVIC

    2006-02-01

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

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

    Science.gov (United States)

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

    2014-09-07

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

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

    Science.gov (United States)

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

    2016-10-07

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

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

    Directory of Open Access Journals (Sweden)

    Kuczmarski Thomas A

    2006-10-01

    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. Access to MannDB is freely available at http://manndb.llnl.gov/.

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

    Directory of Open Access Journals (Sweden)

    Ji-Yong An

    2016-01-01

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

  15. gEVE: a genome-based endogenous viral element database provides comprehensive viral protein-coding sequences in mammalian genomes.

    Science.gov (United States)

    Nakagawa, So; Takahashi, Mahoko Ueda

    2016-01-01

    In mammals, approximately 10% of genome sequences correspond to endogenous viral elements (EVEs), which are derived from ancient viral infections of germ cells. Although most EVEs have been inactivated, some open reading frames (ORFs) of EVEs obtained functions in the hosts. However, EVE ORFs usually remain unannotated in the genomes, and no databases are available for EVE ORFs. To investigate the function and evolution of EVEs in mammalian genomes, we developed EVE ORF databases for 20 genomes of 19 mammalian species. A total of 736,771 non-overlapping EVE ORFs were identified and archived in a database named gEVE (http://geve.med.u-tokai.ac.jp). The gEVE database provides nucleotide and amino acid sequences, genomic loci and functional annotations of EVE ORFs for all 20 genomes. In analyzing RNA-seq data with the gEVE database, we successfully identified the expressed EVE genes, suggesting that the gEVE database facilitates studies of the genomic analyses of various mammalian species.Database URL: http://geve.med.u-tokai.ac.jp. © The Author(s) 2016. Published by Oxford University Press.

  16. FeatureViewer, a BioJS component for visualization of position-based annotations in protein sequences [v1; ref status: indexed, http://f1000r.es/2u2

    Directory of Open Access Journals (Sweden)

    Leyla Garcia

    2014-02-01

    Full Text Available Summary: FeatureViewer is a BioJS component that lays out, maps, orients, and renders position-based annotations for protein sequences. This component is highly flexible and customizable, allowing the presentation of annotations by rows, all centered, or distributed in non-overlapping tracks. It uses either lines or shapes for sites and rectangles for regions. The result is a powerful visualization tool that can be easily integrated into web applications as well as documents as it provides an export-to-image functionality. Availability: https://github.com/biojs/biojs/blob/master/src/main/javascript/Biojs.FeatureViewer.js; http://dx.doi.org/10.5281/zenodo.7719

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

    Science.gov (United States)

    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.

  18. Prediction of potential drug targets based on simple sequence properties

    Directory of Open Access Journals (Sweden)

    Lai Luhua

    2007-09-01

    Full Text Available Abstract Background During the past decades, research and development in drug discovery have attracted much attention and efforts. However, only 324 drug targets are known for clinical drugs up to now. Identifying potential drug targets is the first step in the process of modern drug discovery for developing novel therapeutic agents. Therefore, the identification and validation of new and effective drug targets are of great value for drug discovery in both academia and pharmaceutical industry. If a protein can be predicted in advance for its potential application as a drug target, the drug discovery process targeting this protein will be greatly speeded up. In the current study, based on the properties of known drug targets, we have developed a sequence-based drug target prediction method for fast identification of novel drug targets. Results Based on simple physicochemical properties extracted from protein sequences of known drug targets, several support vector machine models have been constructed in this study. The best model can distinguish currently known drug targets from non drug targets at an accuracy of 84%. Using this model, potential protein drug targets of human origin from Swiss-Prot were predicted, some of which have already attracted much attention as potential drug targets in pharmaceutical research. Conclusion We have developed a drug target prediction method based solely on protein sequence information without the knowledge of family/domain annotation, or the protein 3D structure. This method can be applied in novel drug target identification and validation, as well as genome scale drug target predictions.

  19. Protein and DNA sequence determinants of thermophilic adaptation.

    Directory of Open Access Journals (Sweden)

    Konstantin B Zeldovich

    2007-01-01

    Full Text Available There have been considerable attempts in the past to relate phenotypic trait--habitat temperature of organisms--to their genotypes, most importantly compositions of their genomes and proteomes. However, despite accumulation of anecdotal evidence, an exact and conclusive relationship between the former and the latter has been elusive. We present an exhaustive study of the relationship between amino acid composition of proteomes, nucleotide composition of DNA, and optimal growth temperature (OGT of prokaryotes. Based on 204 complete proteomes of archaea and bacteria spanning the temperature range from -10 degrees C to 110 degrees C, we performed an exhaustive enumeration of all possible sets of amino acids and found a set of amino acids whose total fraction in a proteome is correlated, to a remarkable extent, with the OGT. The universal set is Ile, Val, Tyr, Trp, Arg, Glu, Leu (IVYWREL, and the correlation coefficient is as high as 0.93. We also found that the G + C content in 204 complete genomes does not exhibit a significant correlation with OGT (R = -0.10. On the other hand, the fraction of A + G in coding DNA is correlated with temperature, to a considerable extent, due to codon patterns of IVYWREL amino acids. Further, we found strong and independent correlation between OGT and the frequency with which pairs of A and G nucleotides appear as nearest neighbors in genome sequences. This adaptation is achieved via codon bias. These findings present a direct link between principles of proteins structure and stability and evolutionary mechanisms of thermophylic adaptation. On the nucleotide level, the analysis provides an example of how nature utilizes codon bias for evolutionary adaptation to extreme conditions. Together these results provide a complete picture of how compositions of proteomes and genomes in prokaryotes adjust to the extreme conditions of the environment.

  20. Protein model discrimination using mutational sensitivity derived from deep sequencing.

    Science.gov (United States)

    Adkar, Bharat V; Tripathi, Arti; Sahoo, Anusmita; Bajaj, Kanika; Goswami, Devrishi; Chakrabarti, Purbani; Swarnkar, Mohit K; Gokhale, Rajesh S; Varadarajan, Raghavan

    2012-02-08

    A major bottleneck in protein structure prediction is the selection of correct models from a pool of decoys. Relative activities of ∼1,200 individual single-site mutants in a saturation library of the bacterial toxin CcdB were estimated by determining their relative populations using deep sequencing. This phenotypic information was used to define an empirical score for each residue (RankScore), which correlated with the residue depth, and identify active-site residues. Using these correlations, ∼98% of correct models of CcdB (RMSD ≤ 4Å) were identified from a large set of decoys. The model-discrimination methodology was further validated on eleven different monomeric proteins using simulated RankScore values. The methodology is also a rapid, accurate way to obtain relative activities of each mutant in a large pool and derive sequence-structure-function relationships without protein isolation or characterization. It can be applied to any system in which mutational effects can be monitored by a phenotypic readout. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

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

    2017-01-25

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

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

    Directory of Open Access Journals (Sweden)

    Huilin Wang

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

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

    Science.gov (United States)

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

    2009-04-29

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

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

    International Nuclear Information System (INIS)

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

    2007-01-01

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

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

    Science.gov (United States)

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

    2015-03-26

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

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

    Science.gov (United States)

    Richard, François D; Kajava, Andrey V

    2014-06-01

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

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

    Science.gov (United States)

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

    2016-12-01

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

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

    Science.gov (United States)

    Meinicke, Peter

    2009-09-02

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

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

    Directory of Open Access Journals (Sweden)

    Seizi Someya

    2010-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Krings Andrea

    2006-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Li Weizhong

    2008-04-01

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

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

    Science.gov (United States)

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

    2009-02-15

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

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

    Science.gov (United States)

    Firman, Taylor; Ghosh, Kingshuk

    2018-03-28

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

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

    Directory of Open Access Journals (Sweden)

    Hazelhurst Scott

    2010-03-01

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

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

    NARCIS (Netherlands)

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

    1993-01-01

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

  16. Mitochondrial DNA sequence-based phylogenetic relationship ...

    Indian Academy of Sciences (India)

    cophaga ranges from 0.037–0.106 and 0.049–0.207 for COI and ND5 genes, respectively (tables 2 and 3). Analysis of genetic distance on the basis of sequence difference for both the mitochondrial genes shows very little genetic difference. The discrepancy in the phylogenetic trees based on individ- ual genes may be due ...

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

    Science.gov (United States)

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

    2012-10-13

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

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

    DEFF Research Database (Denmark)

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

    2017-01-01

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

  19. Feasibilty of zein proteins, simple sequence repeats and phenotypic ...

    African Journals Online (AJOL)

    Widespread adoption of quality protein maize (QPM), especially among tropical farming systems has been slow mainly due to the slow process of generating varieties with acceptable kernel quality and adaptability to different agroecological contexts. A molecular based foreground selection system for opaque 2 (o2), the ...

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

    Directory of Open Access Journals (Sweden)

    Alexander M Sevy

    2015-07-01

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

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

    Science.gov (United States)

    Höps, Wolfram; Jeffryes, Matt; Bateman, Alex

    2018-01-01

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

  2. Efficient Feature Selection and Classification of Protein Sequence Data in Bioinformatics

    Science.gov (United States)

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

    2014-01-01

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

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

    NARCIS (Netherlands)

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

    2005-01-01

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

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

    Science.gov (United States)

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

    2004-05-19

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

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

    KAUST Repository

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

    2016-01-01

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

  6. FeatureMap3D - a tool to map protein features and sequence conservation onto homologous structures in the PDB

    DEFF Research Database (Denmark)

    Wernersson, Rasmus; Rapacki, Krzysztof; Stærfeldt, Hans Henrik

    2006-01-01

    FeatureMap3D is a web-based tool that maps protein features onto 3D structures. The user provides sequences annotated with any feature of interest, such as post-translational modifications, protease cleavage sites or exonic structure and FeatureMap3D will then search the Protein Data Bank (PDB) f...

  7. SNBRFinder: A Sequence-Based Hybrid Algorithm for Enhanced Prediction of Nucleic Acid-Binding Residues.

    Science.gov (United States)

    Yang, Xiaoxia; Wang, Jia; Sun, Jun; Liu, Rong

    2015-01-01

    Protein-nucleic acid interactions are central to various fundamental biological processes. Automated methods capable of reliably identifying DNA- and RNA-binding residues in protein sequence are assuming ever-increasing importance. The majority of current algorithms rely on feature-based prediction, but their accuracy remains to be further improved. Here we propose a sequence-based hybrid algorithm SNBRFinder (Sequence-based Nucleic acid-Binding Residue Finder) by merging a feature predictor SNBRFinderF and a template predictor SNBRFinderT. SNBRFinderF was established using the support vector machine whose inputs include sequence profile and other complementary sequence descriptors, while SNBRFinderT was implemented with the sequence alignment algorithm based on profile hidden Markov models to capture the weakly homologous template of query sequence. Experimental results show that SNBRFinderF was clearly superior to the commonly used sequence profile-based predictor and SNBRFinderT can achieve comparable performance to the structure-based template methods. Leveraging the complementary relationship between these two predictors, SNBRFinder reasonably improved the performance of both DNA- and RNA-binding residue predictions. More importantly, the sequence-based hybrid prediction reached competitive performance relative to our previous structure-based counterpart. Our extensive and stringent comparisons show that SNBRFinder has obvious advantages over the existing sequence-based prediction algorithms. The value of our algorithm is highlighted by establishing an easy-to-use web server that is freely accessible at http://ibi.hzau.edu.cn/SNBRFinder.

  8. Dinoflagellate phylogeny as inferred from heat shock protein 90 and ribosomal gene sequences.

    Directory of Open Access Journals (Sweden)

    Mona Hoppenrath

    2010-10-01

    Full Text Available Interrelationships among dinoflagellates in molecular phylogenies are largely unresolved, especially in the deepest branches. Ribosomal DNA (rDNA sequences provide phylogenetic signals only at the tips of the dinoflagellate tree. Two reasons for the poor resolution of deep dinoflagellate relationships using rDNA sequences are (1 most sites are relatively conserved and (2 there are different evolutionary rates among sites in different lineages. Therefore, alternative molecular markers are required to address the deeper phylogenetic relationships among dinoflagellates. Preliminary evidence indicates that the heat shock protein 90 gene (Hsp90 will provide an informative marker, mainly because this gene is relatively long and appears to have relatively uniform rates of evolution in different lineages.We more than doubled the previous dataset of Hsp90 sequences from dinoflagellates by generating additional sequences from 17 different species, representing seven different orders. In order to concatenate the Hsp90 data with rDNA sequences, we supplemented the Hsp90 sequences with three new SSU rDNA sequences and five new LSU rDNA sequences. The new Hsp90 sequences were generated, in part, from four additional heterotrophic dinoflagellates and the type species for six different genera. Molecular phylogenetic analyses resulted in a paraphyletic assemblage near the base of the dinoflagellate tree consisting of only athecate species. However, Noctiluca was never part of this assemblage and branched in a position that was nested within other lineages of dinokaryotes. The phylogenetic trees inferred from Hsp90 sequences were consistent with trees inferred from rDNA sequences in that the backbone of the dinoflagellate clade was largely unresolved.The sequence conservation in both Hsp90 and rDNA sequences and the poor resolution of the deepest nodes suggests that dinoflagellates reflect an explosive radiation in morphological diversity in their recent

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

    Directory of Open Access Journals (Sweden)

    Heiland Randy

    2006-03-01

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

  10. An efficient, versatile and scalable pattern growth approach to mine frequent patterns in unaligned protein sequences.

    Science.gov (United States)

    Ye, Kai; Kosters, Walter A; Ijzerman, Adriaan P

    2007-03-15

    Pattern discovery in protein sequences is often based on multiple sequence alignments (MSA). The procedure can be computationally intensive and often requires manual adjustment, which may be particularly difficult for a set of deviating sequences. In contrast, two algorithms, PRATT2 (http//www.ebi.ac.uk/pratt/) and TEIRESIAS (http://cbcsrv.watson.ibm.com/) are used to directly identify frequent patterns from unaligned biological sequences without an attempt to align them. Here we propose a new algorithm with more efficiency and more functionality than both PRATT2 and TEIRESIAS, and discuss some of its applications to G protein-coupled receptors, a protein family of important drug targets. In this study, we designed and implemented six algorithms to mine three different pattern types from either one or two datasets using a pattern growth approach. We compared our approach to PRATT2 and TEIRESIAS in efficiency, completeness and the diversity of pattern types. Compared to PRATT2, our approach is faster, capable of processing large datasets and able to identify the so-called type III patterns. Our approach is comparable to TEIRESIAS in the discovery of the so-called type I patterns but has additional functionality such as mining the so-called type II and type III patterns and finding discriminating patterns between two datasets. The source code for pattern growth algorithms and their pseudo-code are available at http://www.liacs.nl/home/kosters/pg/.

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

    Science.gov (United States)

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

    2017-05-25

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

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

    Science.gov (United States)

    Firman, Taylor; Ghosh, Kingshuk

    2018-03-01

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

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

    Science.gov (United States)

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

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

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

    OpenAIRE

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

    2007-01-01

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

  15. Prediction of membrane transport proteins and their substrate specificities using primary sequence information.

    Directory of Open Access Journals (Sweden)

    Nitish K Mishra

    Full Text Available Membrane transport proteins (transporters move hydrophilic substrates across hydrophobic membranes and play vital roles in most cellular functions. Transporters represent a diverse group of proteins that differ in topology, energy coupling mechanism, and substrate specificity as well as sequence similarity. Among the functional annotations of transporters, information about their transporting substrates is especially important. The experimental identification and characterization of transporters is currently costly and time-consuming. The development of robust bioinformatics-based methods for the prediction of membrane transport proteins and their substrate specificities is therefore an important and urgent task.Support vector machine (SVM-based computational models, which comprehensively utilize integrative protein sequence features such as amino acid composition, dipeptide composition, physico-chemical composition, biochemical composition, and position-specific scoring matrices (PSSM, were developed to predict the substrate specificity of seven transporter classes: amino acid, anion, cation, electron, protein/mRNA, sugar, and other transporters. An additional model to differentiate transporters from non-transporters was also developed. Among the developed models, the biochemical composition and PSSM hybrid model outperformed other models and achieved an overall average prediction accuracy of 76.69% with a Mathews correlation coefficient (MCC of 0.49 and a receiver operating characteristic area under the curve (AUC of 0.833 on our main dataset. This model also achieved an overall average prediction accuracy of 78.88% and MCC of 0.41 on an independent dataset.Our analyses suggest that evolutionary information (i.e., the PSSM and the AAIndex are key features for the substrate specificity prediction of transport proteins. In comparison, similarity-based methods such as BLAST, PSI-BLAST, and hidden Markov models do not provide accurate predictions

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

    Directory of Open Access Journals (Sweden)

    Meinicke Peter

    2009-09-01

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

  17. Comparison of ompP5 sequence-based typing and pulsed-filed gel ...

    African Journals Online (AJOL)

    In this study, comparison of the outer membrane protein P5 gene (ompP5) sequence-based typing with pulsed-field gel electrophoresis (PFGE) for the genotyping of Haemophilus parasuis, the 15 serovar reference strains and 43 isolates were investigated. When comparing the two methods, 31 ompP5 sequence types ...

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

    Science.gov (United States)

    Faraggi, Eshel; Zhou, Yaoqi; Kloczkowski, Andrzej

    2014-03-01

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

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

    Science.gov (United States)

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

    2011-10-01

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

  20. Protein structure based prediction of catalytic residues.

    Science.gov (United States)

    Fajardo, J Eduardo; Fiser, Andras

    2013-02-22

    Worldwide structural genomics projects continue to release new protein structures at an unprecedented pace, so far nearly 6000, but only about 60% of these proteins have any sort of functional annotation. We explored a range of features that can be used for the prediction of functional residues given a known three-dimensional structure. These features include various centrality measures of nodes in graphs of interacting residues: closeness, betweenness and page-rank centrality. We also analyzed the distance of functional amino acids to the general center of mass (GCM) of the structure, relative solvent accessibility (RSA), and the use of relative entropy as a measure of sequence conservation. From the selected features, neural networks were trained to identify catalytic residues. We found that using distance to the GCM together with amino acid type provide a good discriminant function, when combined independently with sequence conservation. Using an independent test set of 29 annotated protein structures, the method returned 411 of the initial 9262 residues as the most likely to be involved in function. The output 411 residues contain 70 of the annotated 111 catalytic residues. This represents an approximately 14-fold enrichment of catalytic residues on the entire input set (corresponding to a sensitivity of 63% and a precision of 17%), a performance competitive with that of other state-of-the-art methods. We found that several of the graph based measures utilize the same underlying feature of protein structures, which can be simply and more effectively captured with the distance to GCM definition. This also has the added the advantage of simplicity and easy implementation. Meanwhile sequence conservation remains by far the most influential feature in identifying functional residues. We also found that due the rapid changes in size and composition of sequence databases, conservation calculations must be recalibrated for specific reference databases.

  1. Analysis of long-range correlation in sequences data of proteins

    OpenAIRE

    ADRIANA ISVORAN; LAURA UNIPAN; DANA CRACIUN; VASILE MORARIU

    2007-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Mohr Stephanie E

    2007-06-01

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

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

    Science.gov (United States)

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

    2017-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Yoojin Hong

    2010-10-01

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

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

    NARCIS (Netherlands)

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

    2012-01-01

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

  6. Automated sequence-specific protein NMR assignment using the memetic algorithm MATCH

    International Nuclear Information System (INIS)

    Volk, Jochen; Herrmann, Torsten; Wuethrich, Kurt

    2008-01-01

    MATCH (Memetic Algorithm and Combinatorial Optimization Heuristics) is a new memetic algorithm for automated sequence-specific polypeptide backbone NMR assignment of proteins. MATCH employs local optimization for tracing partial sequence-specific assignments within a global, population-based search environment, where the simultaneous application of local and global optimization heuristics guarantees high efficiency and robustness. MATCH thus makes combined use of the two predominant concepts in use for automated NMR assignment of proteins. Dynamic transition and inherent mutation are new techniques that enable automatic adaptation to variable quality of the experimental input data. The concept of dynamic transition is incorporated in all major building blocks of the algorithm, where it enables switching between local and global optimization heuristics at any time during the assignment process. Inherent mutation restricts the intrinsically required randomness of the evolutionary algorithm to those regions of the conformation space that are compatible with the experimental input data. Using intact and artificially deteriorated APSY-NMR input data of proteins, MATCH performed sequence-specific resonance assignment with high efficiency and robustness

  7. WebScipio: An online tool for the determination of gene structures using protein sequences

    Directory of Open Access Journals (Sweden)

    Waack Stephan

    2008-09-01

    Full Text Available Abstract Background Obtaining the gene structure for a given protein encoding gene is an important step in many analyses. A software suited for this task should be readily accessible, accurate, easy to handle and should provide the user with a coherent representation of the most probable gene structure. It should be rigorous enough to optimise features on the level of single bases and at the same time flexible enough to allow for cross-species searches. Results WebScipio, a web interface to the Scipio software, allows a user to obtain the corresponding coding sequence structure of a here given a query protein sequence that belongs to an already assembled eukaryotic genome. The resulting gene structure is presented in various human readable formats like a schematic representation, and a detailed alignment of the query and the target sequence highlighting any discrepancies. WebScipio can also be used to identify and characterise the gene structures of homologs in related organisms. In addition, it offers a web service for integration with other programs. Conclusion WebScipio is a tool that allows users to get a high-quality gene structure prediction from a protein query. It offers more than 250 eukaryotic genomes that can be searched and produces predictions that are close to what can be achieved by manual annotation, for in-species and cross-species searches alike. WebScipio is freely accessible at http://www.webscipio.org.

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

    Science.gov (United States)

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

    2016-10-07

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

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

    Science.gov (United States)

    Higgins, Sean A; Savage, David F

    2018-01-09

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

  10. In silico characterization of boron transporter (BOR1 protein sequences in Poaceae species

    Directory of Open Access Journals (Sweden)

    Ertuğrul Filiz

    2013-01-01

    Full Text Available Boron (B is essential for the plant growth and development, and its primary function is connected with formation of the cell wall. Moreover, boron toxicity is a shared problem in semiarid and arid regions. In this study, boron transporter protein (BOR1 sequences from some Poaceae species (Hordeum vulgare subsp. vulgare, Zea mays, Brachypodium distachyon, Oryza sativa subsp. japonica, Oryza sativa subsp. indica, Sorghum bicolor, Triticum aestivum were evaluated by bioinformatics tools. Physicochemical analyses revealed that most of BOR1 proteins were basic character and had generally aliphatic amino acids. Analysis of the domains showed that transmembrane domains were identified constantly and three motifs were detected with 50 amino acids length. Also, the motif SPNPWEPGSYDHWTVAKDMFNVPPAYIFGAFIPATMVAGLYYFDHSVASQ was found most frequently with 25 repeats. The phylogenetic tree showed divergence into two main clusters. B. distachyon species were clustered separately. Finally, this study contributes to the new BOR1 protein characterization in grasses and create scientific base for in silico analysis in future.

  11. Microfluidic screening and whole-genome sequencing identifies mutations associated with improved protein secretion by yeast

    DEFF Research Database (Denmark)

    Huang, Mingtao; Bai, Yunpeng; Sjostrom, Staffan L.

    2015-01-01

    There is an increasing demand for biotech-based production of recombinant proteins for use as pharmaceuticals in the food and feed industry and in industrial applications. Yeast Saccharomyces cerevisiae is among preferred cell factories for recombinant protein production, and there is increasing...... interest in improving its protein secretion capacity. Due to the complexity of the secretory machinery in eukaryotic cells, it is difficult to apply rational engineering for construction of improved strains. Here we used high-throughput microfluidics for the screening of yeast libraries, generated by UV...... mutagenesis. Several screening and sorting rounds resulted in the selection of eight yeast clones with significantly improved secretion of recombinant a-amylase. Efficient secretion was genetically stable in the selected clones. We performed whole-genome sequencing of the eight clones and identified 330...

  12. Nonlinear analysis of sequence symmetry of beta-trefoil family proteins

    Energy Technology Data Exchange (ETDEWEB)

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

    2005-07-01

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

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

    Science.gov (United States)

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

    2017-04-15

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

  14. Protein-based stable isotope probing.

    Science.gov (United States)

    Jehmlich, Nico; Schmidt, Frank; Taubert, Martin; Seifert, Jana; Bastida, Felipe; von Bergen, Martin; Richnow, Hans-Hermann; Vogt, Carsten

    2010-12-01

    We describe a stable isotope probing (SIP) technique that was developed to link microbe-specific metabolic function to phylogenetic information. Carbon ((13)C)- or nitrogen ((15)N)-labeled substrates (typically with >98% heavy label) were used in cultivation experiments and the heavy isotope incorporation into proteins (protein-SIP) on growth was determined. The amount of incorporation provides a measure for assimilation of a substrate, and the sequence information from peptide analysis obtained by mass spectrometry delivers phylogenetic information about the microorganisms responsible for the metabolism of the particular substrate. In this article, we provide guidelines for incubating microbial cultures with labeled substrates and a protocol for protein-SIP. The protocol guides readers through the proteomics pipeline, including protein extraction, gel-free and gel-based protein separation, the subsequent mass spectrometric analysis of peptides and the calculation of the incorporation of stable isotopes into peptides. Extraction of proteins and the mass fingerprint measurements of unlabeled and labeled fractions can be performed in 2-3 d.

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

    Science.gov (United States)

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

    2007-04-13

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

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

    Science.gov (United States)

    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.

  17. Integrating genomic information with protein sequence and 3D atomic level structure at the RCSB protein data bank.

    Science.gov (United States)

    Prlic, Andreas; Kalro, Tara; Bhattacharya, Roshni; Christie, Cole; Burley, Stephen K; Rose, Peter W

    2016-12-15

    The Protein Data Bank (PDB) now contains more than 120,000 three-dimensional (3D) structures of biological macromolecules. To allow an interpretation of how PDB data relates to other publicly available annotations, we developed a novel data integration platform that maps 3D structural information across various datasets. This integration bridges from the human genome across protein sequence to 3D structure space. We developed novel software solutions for data management and visualization, while incorporating new libraries for web-based visualization using SVG graphics. The new views are available from http://www.rcsb.org and software is available from https://github.com/rcsb/. andreas.prlic@rcsb.orgSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  18. Data-driven modelling of protein synthesis : A sequence perspective

    NARCIS (Netherlands)

    Gritsenko, A.

    2017-01-01

    Recent advances in DNA sequencing, synthesis and genetic engineering have enabled the introduction of choice DNA sequences into living cells. This is an exciting prospect for the field of industrial biotechnology, which aims at using microorganisms to produce foods, beverages, pharmaceuticals and

  19. Prediction of Protein-Protein Interactions Related to Protein Complexes Based on Protein Interaction Networks

    Directory of Open Access Journals (Sweden)

    Peng Liu

    2015-01-01

    Full Text Available A method for predicting protein-protein interactions based on detected protein complexes is proposed to repair deficient interactions derived from high-throughput biological experiments. Protein complexes are pruned and decomposed into small parts based on the adaptive k-cores method to predict protein-protein interactions associated with the complexes. The proposed method is adaptive to protein complexes with different structure, number, and size of nodes in a protein-protein interaction network. Based on different complex sets detected by various algorithms, we can obtain different prediction sets of protein-protein interactions. The reliability of the predicted interaction sets is proved by using estimations with statistical tests and direct confirmation of the biological data. In comparison with the approaches which predict the interactions based on the cliques, the overlap of the predictions is small. Similarly, the overlaps among the predicted sets of interactions derived from various complex sets are also small. Thus, every predicted set of interactions may complement and improve the quality of the original network data. Meanwhile, the predictions from the proposed method replenish protein-protein interactions associated with protein complexes using only the network topology.

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

    Directory of Open Access Journals (Sweden)

    Sharpton Thomas J

    2012-10-01

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

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

    Science.gov (United States)

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

    2006-10-01

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

  2. Synthesis and characterization of recombinant abductin-based proteins.

    Science.gov (United States)

    Su, Renay S-C; Renner, Julie N; Liu, Julie C

    2013-12-09

    Recombinant proteins are promising tools for tissue engineering and drug delivery applications. Protein-based biomaterials have several advantages over natural and synthetic polymers, including precise control over amino acid composition and molecular weight, modular swapping of functional domains, and tunable mechanical and physical properties. In this work, we describe recombinant proteins based on abductin, an elastomeric protein that is found in the inner hinge of bivalves and functions as a coil spring to keep shells open. We illustrate, for the first time, the design, cloning, expression, and purification of a recombinant protein based on consensus abductin sequences derived from Argopecten irradians . The molecular weight of the protein was confirmed by mass spectrometry, and the protein was 94% pure. Circular dichroism studies showed that the dominant structures of abductin-based proteins were polyproline II helix structures in aqueous solution and type II β-turns in trifluoroethanol. Dynamic light scattering studies illustrated that the abductin-based proteins exhibit reversible upper critical solution temperature behavior and irreversible aggregation behavior at high temperatures. A LIVE/DEAD assay revealed that human umbilical vein endothelial cells had a viability of 98 ± 4% after being cultured for two days on the abductin-based protein. Initial cell spreading on the abductin-based protein was similar to that on bovine serum albumin. These studies thus demonstrate the potential of abductin-based proteins in tissue engineering and drug delivery applications due to the cytocompatibility and its response to temperature.

  3. A Novel Indirect Sequence Readout Component in the E. coli Cyclic AMP Receptor Protein Operator

    DEFF Research Database (Denmark)

    Lindemose, Søren; Nielsen, Peter Eigil; Valentin-Hansen, Poul

    2014-01-01

    binding sites in the E. coli genome, but the exact role of the N6 region in CRP interaction has not previously been systematic examined. Here we employ an in vitro selection system based on a randomized N6 spacer region to demonstrate that CRP binding to the lacP1 site may be enhanced up to 14-fold......The cyclic AMP receptor protein (CRP) from Escherichia coli has been extensively studied for several decades. In particular, a detailed characterization of CRP interaction with DNA has been obtained. The CRP dimer recognizes a consensus sequence AANTGTGANNNNNNTCACANTT through direct amino acid...

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

    Science.gov (United States)

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

    1993-02-01

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

  5. High Performance Protein Sequence Database Scanning on the Cell Broadband Engine

    Directory of Open Access Journals (Sweden)

    Adrianto Wirawan

    2009-01-01

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

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

    DEFF Research Database (Denmark)

    Busk, Peter Kamp

    2017-01-01

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

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

    Science.gov (United States)

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

    2016-01-04

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

  8. Mixed Sequence Reader: A Program for Analyzing DNA Sequences with Heterozygous Base Calling

    Science.gov (United States)

    Chang, Chun-Tien; Tsai, Chi-Neu; Tang, Chuan Yi; Chen, Chun-Houh; Lian, Jang-Hau; Hu, Chi-Yu; Tsai, Chia-Lung; Chao, Angel; Lai, Chyong-Huey; Wang, Tzu-Hao; Lee, Yun-Shien

    2012-01-01

    The direct sequencing of PCR products generates heterozygous base-calling fluorescence chromatograms that are useful for identifying single-nucleotide polymorphisms (SNPs), insertion-deletions (indels), short tandem repeats (STRs), and paralogous genes. Indels and STRs can be easily detected using the currently available Indelligent or ShiftDetector programs, which do not search reference sequences. However, the detection of other genomic variants remains a challenge due to the lack of appropriate tools for heterozygous base-calling fluorescence chromatogram data analysis. In this study, we developed a free web-based program, Mixed Sequence Reader (MSR), which can directly analyze heterozygous base-calling fluorescence chromatogram data in .abi file format using comparisons with reference sequences. The heterozygous sequences are identified as two distinct sequences and aligned with reference sequences. Our results showed that MSR may be used to (i) physically locate indel and STR sequences and determine STR copy number by searching NCBI reference sequences; (ii) predict combinations of microsatellite patterns using the Federal Bureau of Investigation Combined DNA Index System (CODIS); (iii) determine human papilloma virus (HPV) genotypes by searching current viral databases in cases of double infections; (iv) estimate the copy number of paralogous genes, such as β-defensin 4 (DEFB4) and its paralog HSPDP3. PMID:22778697

  9. High Interlaboratory Reprocucibility of DNA Sequence-based Typing of Bacteria in a Multicenter Study

    DEFF Research Database (Denmark)

    Sousa, MA de; Boye, Kit; Lencastre, H de

    2006-01-01

    Current DNA amplification-based typing methods for bacterial pathogens often lack interlaboratory reproducibility. In this international study, DNA sequence-based typing of the Staphylococcus aureus protein A gene (spa, 110 to 422 bp) showed 100% intra- and interlaboratory reproducibility without...... extensive harmonization of protocols for 30 blind-coded S. aureus DNA samples sent to 10 laboratories. Specialized software for automated sequence analysis ensured a common typing nomenclature....

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

    International Nuclear Information System (INIS)

    Lobanov, Michail Yu; Galzitskaya, Oxana V

    2011-01-01

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

  11. Bm86 midgut protein sequence variation in South Texas cattle fever ticks

    Directory of Open Access Journals (Sweden)

    Kammlah Diane M

    2010-11-01

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

  12. Identification of physicochemical selective pressure on protein encoding nucleotide sequences

    Directory of Open Access Journals (Sweden)

    Sainudiin Raazesh

    2006-03-01

    Full Text Available Abstract Background Statistical methods for identifying positively selected sites in protein coding regions are one of the most commonly used tools in evolutionary bioinformatics. However, they have been limited by not taking the physiochemical properties of amino acids into account. Results We develop a new codon-based likelihood model for detecting site-specific selection pressures acting on specific physicochemical properties. Nonsynonymous substitutions are divided into substitutions that differ with respect to the physicochemical properties of interest, and those that do not. The substitution rates of these two types of changes, relative to the synonymous substitution rate, are then described by two parameters, γ and ω respectively. The new model allows us to perform likelihood ratio tests for positive selection acting on specific physicochemical properties of interest. The new method is first used to analyze simulated data and is shown to have good power and accuracy in detecting physicochemical selective pressure. We then re-analyze data from the class-I alleles of the human Major Histocompatibility Complex (MHC and from the abalone sperm lysine. Conclusion Our new method allows a more flexible framework to identify selection pressure on particular physicochemical properties.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    Agarwal, Pratul Kumar [Knoxville, TN

    2011-07-19

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

  15. Identification and characterization of plastid-type proteins from sequence-attributed features using machine learning

    Science.gov (United States)

    2013-01-01

    Background Plastids are an important component of plant cells, being the site of manufacture and storage of chemical compounds used by the cell, and contain pigments such as those used in photosynthesis, starch synthesis/storage, cell color etc. They are essential organelles of the plant cell, also present in algae. Recent advances in genomic technology and sequencing efforts is generating a huge amount of DNA sequence data every day. The predicted proteome of these genomes needs annotation at a faster pace. In view of this, one such annotation need is to develop an automated system that can distinguish between plastid and non-plastid proteins accurately, and further classify plastid-types based on their functionality. We compared the amino acid compositions of plastid proteins with those of non-plastid ones and found significant differences, which were used as a basis to develop various feature-based prediction models using similarity-search and machine learning. Results In this study, we developed separate Support Vector Machine (SVM) trained classifiers for characterizing the plastids in two steps: first distinguishing the plastid vs. non-plastid proteins, and then classifying the identified plastids into their various types based on their function (chloroplast, chromoplast, etioplast, and amyloplast). Five diverse protein features: amino acid composition, dipeptide composition, the pseudo amino acid composition, Nterminal-Center-Cterminal composition and the protein physicochemical properties are used to develop SVM models. Overall, the dipeptide composition-based module shows the best performance with an accuracy of 86.80% and Matthews Correlation Coefficient (MCC) of 0.74 in phase-I and 78.60% with a MCC of 0.44 in phase-II. On independent test data, this model also performs better with an overall accuracy of 76.58% and 74.97% in phase-I and phase-II, respectively. The similarity-based PSI-BLAST module shows very low performance with about 50% prediction

  16. The use of orthologous sequences to predict the impact of amino acid substitutions on protein function.

    Directory of Open Access Journals (Sweden)

    Nicholas J Marini

    2010-05-01

    Full Text Available Computational predictions of the functional impact of genetic variation play a critical role in human genetics research. For nonsynonymous coding variants, most prediction algorithms make use of patterns of amino acid substitutions observed among homologous proteins at a given site. In particular, substitutions observed in orthologous proteins from other species are often assumed to be tolerated in the human protein as well. We examined this assumption by evaluating a panel of nonsynonymous mutants of a prototypical human enzyme, methylenetetrahydrofolate reductase (MTHFR, in a yeast cell-based functional assay. As expected, substitutions in human MTHFR at sites that are well-conserved across distant orthologs result in an impaired enzyme, while substitutions present in recently diverged sequences (including a 9-site mutant that "resurrects" the human-macaque ancestor result in a functional enzyme. We also interrogated 30 sites with varying degrees of conservation by creating substitutions in the human enzyme that are accepted in at least one ortholog of MTHFR. Quite surprisingly, most of these substitutions were deleterious to the human enzyme. The results suggest that selective constraints vary between phylogenetic lineages such that inclusion of distant orthologs to infer selective pressures on the human enzyme may be misleading. We propose that homologous proteins are best used to reconstruct ancestral sequences and infer amino acid conservation among only direct lineal ancestors of a particular protein. We show that such an "ancestral site preservation" measure outperforms other prediction methods, not only in our selected set for MTHFR, but also in an exhaustive set of E. coli LacI mutants.

  17. SNBRFinder: A Sequence-Based Hybrid Algorithm for Enhanced Prediction of Nucleic Acid-Binding Residues.

    Directory of Open Access Journals (Sweden)

    Xiaoxia Yang

    Full Text Available Protein-nucleic acid interactions are central to various fundamental biological processes. Automated methods capable of reliably identifying DNA- and RNA-binding residues in protein sequence are assuming ever-increasing importance. The majority of current algorithms rely on feature-based prediction, but their accuracy remains to be further improved. Here we propose a sequence-based hybrid algorithm SNBRFinder (Sequence-based Nucleic acid-Binding Residue Finder by merging a feature predictor SNBRFinderF and a template predictor SNBRFinderT. SNBRFinderF was established using the support vector machine whose inputs include sequence profile and other complementary sequence descriptors, while SNBRFinderT was implemented with the sequence alignment algorithm based on profile hidden Markov models to capture the weakly homologous template of query sequence. Experimental results show that SNBRFinderF was clearly superior to the commonly used sequence profile-based predictor and SNBRFinderT can achieve comparable performance to the structure-based template methods. Leveraging the complementary relationship between these two predictors, SNBRFinder reasonably improved the performance of both DNA- and RNA-binding residue predictions. More importantly, the sequence-based hybrid prediction reached competitive performance relative to our previous structure-based counterpart. Our extensive and stringent comparisons show that SNBRFinder has obvious advantages over the existing sequence-based prediction algorithms. The value of our algorithm is highlighted by establishing an easy-to-use web server that is freely accessible at http://ibi.hzau.edu.cn/SNBRFinder.

  18. Function-Based Algorithms for Biological Sequences

    Science.gov (United States)

    Mohanty, Pragyan Sheela P.

    2015-01-01

    Two problems at two different abstraction levels of computational biology are studied. At the molecular level, efficient pattern matching algorithms in DNA sequences are presented. For gene order data, an efficient data structure is presented capable of storing all gene re-orderings in a systematic manner. A common characteristic of presented…

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

    KAUST Repository

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

    2017-01-01

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

  20. Nucleotide sequence of cloned cDNA for human sphingolipid activator protein 1 precursor

    International Nuclear Information System (INIS)

    Dewji, N.N.; Wenger, D.A.; O'Brien, J.S.

    1987-01-01

    Two cDNA clones encoding prepro-sphingolipid activator protein 1 (SAP-1) were isolated from a λ gt11 human hepatoma expression library using polyclonal antibodies. These had inserts of ≅ 2 kilobases (λ-S-1.2 and λ-S-1.3) and both were both homologous with a previously isolated clone (λ-S-1.1) for mature SAP-1. The authors report here the nucleotide sequence of the longer two EcoRI fragments of S-1.2 and S-1.3 that were not the same and the derived amino acid sequences of mature SAP-1 and its prepro form. The open reading frame encodes 19 amino acids, which are colinear with the amino-terminal sequence of mature SAP-1, and extends far beyond the predicted carboxyl terminus of mature SAP-1, indicating extensive carboxyl-terminal processing. The nucleotide sequence of cDNA encoding prepro-SAP-1 includes 1449 bases from the assigned initiation codon ATG at base-pair 472 to the stop codon TGA at base-pair 1921. The first 23 amino acids coded after the initiation ATG are characteristic of a signal peptide. The calculated molecular mass for a polypeptide encoded by 1449 bases is ≅ 53 kDa, in keeping with the reported value for pro-SAP-1. The data indicate that after removal of the signal peptide mature SAP-1 is generated by removing an additional 7 amino acids from the amino terminus and ≅ 373 amino acids from the carboxyl terminus. One potential glycosylation site was previously found in mature SAP-1. Three additional potential glycosylation sites are present in the processed carboxyl-terminal polypeptide, which they designate as P-2

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

    Directory of Open Access Journals (Sweden)

    Donald Adjeroh

    2018-03-01

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

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

    Science.gov (United States)

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

    1997-01-01

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

  3. Analysis of long-range correlation in sequences data of proteins

    Directory of Open Access Journals (Sweden)

    ADRIANA ISVORAN

    2007-04-01

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

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

    Science.gov (United States)

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

    2018-05-23

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

  5. Recognition of secretory proteins in Escherichia coli requires signals in addition to the signal sequence and slow folding

    Directory of Open Access Journals (Sweden)

    Flower Ann M

    2002-11-01

    Full Text Available Abstract Background The Sec-dependent protein export apparatus of Escherichia coli is very efficient at correctly identifying proteins to be exported from the cytoplasm. Even bacterial strains that carry prl mutations, which allow export of signal sequence-defective precursors, accurately differentiate between cytoplasmic and mutant secretory proteins. It was proposed previously that the basis for this precise discrimination is the slow folding rate of secretory proteins, resulting in binding by the secretory chaperone, SecB, and subsequent targeting to translocase. Based on this proposal, we hypothesized that a cytoplasmic protein containing a mutation that slows its rate of folding would be recognized by SecB and therefore targeted to the Sec pathway. In a Prl suppressor strain the mutant protein would be exported to the periplasm due to loss of ability to reject non-secretory proteins from the pathway. Results In the current work, we tested this hypothesis using a mutant form of λ repressor that folds slowly. No export of the mutant protein was observed, even in a prl strain. We then examined binding of the mutant λ repressor to SecB. We did not observe interaction by either of two assays, indicating that slow folding is not sufficient for SecB binding and targeting to translocase. Conclusions These results strongly suggest that to be targeted to the export pathway, secretory proteins contain signals in addition to the canonical signal sequence and the rate of folding.

  6. Sequence Identification, Recombinant Production, and Analysis of the Self-Assembly of Egg Stalk Silk Proteins from Lacewing Chrysoperla carnea.

    Science.gov (United States)

    Neuenfeldt, Martin; Scheibel, Thomas

    2017-06-13

    Egg stalk silks of the common green lacewing Chrysoperla carnea likely comprise at least three different silk proteins. Based on the natural spinning process, it was hypothesized that these proteins self-assemble without shear stress, as adult lacewings do not use a spinneret. To examine this, the first sequence identification and determination of the gene expression profile of several silk proteins and various transcript variants thereof was conducted, and then the three major proteins were recombinantly produced in Escherichia coli encoded by their native complementary DNA (cDNA) sequences. Circular dichroism measurements indicated that the silk proteins in aqueous solutions had a mainly intrinsically disordered structure. The largest silk protein, which we named ChryC1, exhibited a lower critical solution temperature (LCST) behavior and self-assembled into fibers or film morphologies, depending on the conditions used. The second silk protein, ChryC2, self-assembled into nanofibrils and subsequently formed hydrogels. Circular dichroism and Fourier transform infrared spectroscopy confirmed conformational changes of both proteins into beta sheet rich structures upon assembly. ChryC3 did not self-assemble into any morphology under the tested conditions. Thereby, through this work, it could be shown that recombinant lacewing silk proteins can be produced and further used for studying the fiber formation of lacewing egg stalks.

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

    OpenAIRE

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

    2006-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-01-07

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

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

    International Nuclear Information System (INIS)

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

    1988-01-01

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

  10. High throughput sequencing and proteomics to identify immunogenic proteins of a new pathogen: the dirty genome approach.

    Science.gov (United States)

    Greub, Gilbert; Kebbi-Beghdadi, Carole; Bertelli, Claire; Collyn, François; Riederer, Beat M; Yersin, Camille; Croxatto, Antony; Raoult, Didier

    2009-12-23

    With the availability of new generation sequencing technologies, bacterial genome projects have undergone a major boost. Still, chromosome completion needs a costly and time-consuming gap closure, especially when containing highly repetitive elements. However, incomplete genome data may be sufficiently informative to derive the pursued information. For emerging pathogens, i.e. newly identified pathogens, lack of release of genome data during gap closure stage is clearly medically counterproductive. We thus investigated the feasibility of a dirty genome approach, i.e. the release of unfinished genome sequences to develop serological diagnostic tools. We showed that almost the whole genome sequence of the emerging pathogen Parachlamydia acanthamoebae was retrieved even with relatively short reads from Genome Sequencer 20 and Solexa. The bacterial proteome was analyzed to select immunogenic proteins, which were then expressed and used to elaborate the first steps of an ELISA. This work constitutes the proof of principle for a dirty genome approach, i.e. the use of unfinished genome sequences of pathogenic bacteria, coupled with proteomics to rapidly identify new immunogenic proteins useful to develop in the future specific diagnostic tests such as ELISA, immunohistochemistry and direct antigen detection. Although applied here to an emerging pathogen, this combined dirty genome sequencing/proteomic approach may be used for any pathogen for which better diagnostics are needed. These genome sequences may also be very useful to develop DNA based diagnostic tests. All these diagnostic tools will allow further evaluations of the pathogenic potential of this obligate intracellular bacterium.

  11. Partial Sequence Analysis of Merozoite Surface Proteine-3α Gene in Plasmodium vivax Isolates from Malarious Areas of Iran

    Directory of Open Access Journals (Sweden)

    H Mirhendi

    2008-12-01

    Full Text Available Background: Approximately 85-90% of malaria infections in Iran are attributed to Plasmodium vivax, while little is known about the genetic of the parasite and its strain types in this region. This study was designed and performed for describing genetic characteristics of Plasmodium vivax population of Iran based on the merozoite surface protein-3α gene sequence. Methods: Through a descriptive study we analyzed partial P. vivax merozoite surface protein-3α gene sequences from 17 clinical P. vivax isolates collected from malarious areas of Iran. Genomic DNA was extracted by Q1Aamp® DNA blood mini kit, amplified through nested PCR for a partial nucleotide sequence of PvMSP-3 gene in P. vivax. PCR-amplified products were sequenced with an ABI Prism Perkin-Elmer 310 sequencer machine and the data were analyzed with clustal W software. Results: Analysis of PvMSP-3 gene sequences demonstrated extensive polymorphisms, but the sequence identity between isolates of same types was relatively high. We identified specific insertions and deletions for the types A, B and C variants of P. vivax in our isolates. In phylogenetic comparison of geographically separated isolates, there was not a significant geo­graphical branching of the parasite populations. Conclusion: The highly polymorphic nature of isolates suggests that more investigations of the PvMSP-3 gene are needed to explore its vaccine potential.

  12. Sequence-based classification using discriminatory motif feature selection.

    Directory of Open Access Journals (Sweden)

    Hao Xiong

    Full Text Available Most existing methods for sequence-based classification use exhaustive feature generation, employing, for example, all k-mer patterns. The motivation behind such (enumerative approaches is to minimize the potential for overlooking important features. However, there are shortcomings to this strategy. First, practical constraints limit the scope of exhaustive feature generation to patterns of length ≤ k, such that potentially important, longer (> k predictors are not considered. Second, features so generated exhibit strong dependencies, which can complicate understanding of derived classification rules. Third, and most importantly, numerous irrelevant features are created. These concerns can compromise prediction and interpretation. While remedies have been proposed, they tend to be problem-specific and not broadly applicable. Here, we develop a generally applicable methodology, and an attendant software pipeline, that is predicated on discriminatory motif finding. In addition to the traditional training and validation partitions, our framework entails a third level of data partitioning, a discovery partition. A discriminatory motif finder is used on sequences and associated class labels in the discovery partition to yield a (small set of features. These features are then used as inputs to a classifier in the training partition. Finally, performance assessment occurs on the validation partition. Important attributes of our approach are its modularity (any discriminatory motif finder and any classifier can be deployed and its universality (all data, including sequences that are unaligned and/or of unequal length, can be accommodated. We illustrate our approach on two nucleosome occupancy datasets and a protein solubility dataset, previously analyzed using enumerative feature generation. Our method achieves excellent performance results, with and without optimization of classifier tuning parameters. A Python pipeline implementing the approach is

  13. Structural insights and ab initio sequencing within the DING proteins family

    International Nuclear Information System (INIS)

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

    2011-01-01

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

  14. Structural insights and ab initio sequencing within the DING proteins family

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-01-01

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

  15. BLAST-based structural annotation of protein residues using Protein Data Bank.

    Science.gov (United States)

    Singh, Harinder; Raghava, Gajendra P S

    2016-01-25

    In the era of next-generation sequencing where thousands of genomes have been already sequenced; size of protein databases is growing with exponential rate. Structural annotation of these proteins is one of the biggest challenges for the computational biologist. Although, it is easy to perform BLAST search against Protein Data Bank (PDB) but it is difficult for a biologist to annotate protein residues from BLAST search. A web-server StarPDB has been developed for structural annotation of a protein based on its similarity with known protein structures. It uses standard BLAST software for performing similarity search of a query protein against protein structures in PDB. This server integrates wide range modules for assigning different types of annotation that includes, Secondary-structure, Accessible surface area, Tight-turns, DNA-RNA and Ligand modules. Secondary structure module allows users to predict regular secondary structure states to each residue in a protein. Accessible surface area predict the exposed or buried residues in a protein. Tight-turns module is designed to predict tight turns like beta-turns in a protein. DNA-RNA module developed for predicting DNA and RNA interacting residues in a protein. Similarly, Ligand module of server allows one to predicted ligands, metal and nucleotides ligand interacting residues in a protein. In summary, this manuscript presents a web server for comprehensive annotation of a protein based on similarity search. It integrates number of visualization tools that facilitate users to understand structure and function of protein residues. This web server is available freely for scientific community from URL http://crdd.osdd.net/raghava/starpdb .

  16. Variation in the prion protein sequence in Dutch goat breeds

    NARCIS (Netherlands)

    Windig, J.J.; Hoving, R.A.H.; Priem, J.; Bossers, A.; Keulen, van L.J.M.; Langeveld, J.P.M.

    2016-01-01

    Scrapie is a neurodegenerative disease occurring in goats and sheep. Several haplotypes of the prion protein increase resistance to scrapie infection and may be used in selective breeding to help eradicate scrapie. In this study, frequencies of the allelic variants of the PrP gene are determined

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Borodovsky Mark

    2006-03-01

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

  19. RVMAB: Using the Relevance Vector Machine Model Combined with Average Blocks to Predict the Interactions of Proteins from Protein Sequences

    Directory of Open Access Journals (Sweden)

    Ji-Yong An

    2016-05-01

    Full Text Available Protein-Protein Interactions (PPIs play essential roles in most cellular processes. Knowledge of PPIs is becoming increasingly more important, which has prompted the development of technologies that are capable of discovering large-scale PPIs. Although many high-throughput biological technologies have been proposed to detect PPIs, there are unavoidable shortcomings, including cost, time intensity, and inherently high false positive and false negative rates. For the sake of these reasons, in silico methods are attracting much attention due to their good performances in predicting PPIs. In this paper, we propose a novel computational method known as RVM-AB that combines the Relevance Vector Machine (RVM model and Average Blocks (AB to predict PPIs from protein sequences. The main improvements are the results of representing protein sequences using the AB feature representation on a Position Specific Scoring Matrix (PSSM, reducing the influence of noise using a Principal Component Analysis (PCA, and using a Relevance Vector Machine (RVM based classifier. We performed five-fold cross-validation experiments on yeast and Helicobacter pylori datasets, and achieved very high accuracies of 92.98% and 95.58% respectively, which is significantly better than previous works. In addition, we also obtained good prediction accuracies of 88.31%, 89.46%, 91.08%, 91.55%, and 94.81% on other five independent datasets C. elegans, M. musculus, H. sapiens, H. pylori, and E. coli for cross-species prediction. To further evaluate the proposed method, we compare it with the state-of-the-art support vector machine (SVM classifier on the yeast dataset. The experimental results demonstrate that our RVM-AB method is obviously better than the SVM-based method. The promising experimental results show the efficiency and simplicity of the proposed method, which can be an automatic decision support tool. To facilitate extensive studies for future proteomics research, we developed

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

    Directory of Open Access Journals (Sweden)

    Jaimie-Leigh Jonker

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

  1. Sequence characterization of heat shock protein gene of Cyclospora cayetanensis isolates from Nepal, Mexico, and Peru.

    Science.gov (United States)

    Sulaiman, Irshad M; Torres, Patricia; Simpson, Steven; Kerdahi, Khalil; Ortega, Ynes

    2013-04-01

    We have described the development of a 2-step nested PCR protocol based on the characterization of the 70-kDa heat shock protein (HSP70) gene for rapid detection of the human-pathogenic Cyclospora cayetanensis parasite. We tested and validated these newly designed primer sets by PCR amplification followed by nucleotide sequencing of PCR-amplified HSP70 fragments belonging to 16 human C. cayetanensis isolates from 3 different endemic regions that include Nepal, Mexico, and Peru. No genetic polymorphism was observed among the isolates at the characterized regions of the HSP70 locus. This newly developed HSP70 gene-based nested PCR protocol provides another useful genetic marker for the rapid detection of C. cayetanensis in the future.

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

    International Nuclear Information System (INIS)

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

    2007-01-01

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

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

    Science.gov (United States)

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

    2012-03-01

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

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

    International Nuclear Information System (INIS)

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

    1996-01-01

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

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

    Science.gov (United States)

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

    2017-07-03

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

  6. Prediction of protein hydration sites from sequence by modular neural networks

    DEFF Research Database (Denmark)

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

    1998-01-01

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

  7. Sequence memory based on coherent spin-interaction neural networks.

    Science.gov (United States)

    Xia, Min; Wong, W K; Wang, Zhijie

    2014-12-01

    Sequence information processing, for instance, the sequence memory, plays an important role on many functions of brain. In the workings of the human brain, the steady-state period is alterable. However, in the existing sequence memory models using heteroassociations, the steady-state period cannot be changed in the sequence recall. In this work, a novel neural network model for sequence memory with controllable steady-state period based on coherent spininteraction is proposed. In the proposed model, neurons fire collectively in a phase-coherent manner, which lets a neuron group respond differently to different patterns and also lets different neuron groups respond differently to one pattern. The simulation results demonstrating the performance of the sequence memory are presented. By introducing a new coherent spin-interaction sequence memory model, the steady-state period can be controlled by dimension parameters and the overlap between the input pattern and the stored patterns. The sequence storage capacity is enlarged by coherent spin interaction compared with the existing sequence memory models. Furthermore, the sequence storage capacity has an exponential relationship to the dimension of the neural network.

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

    Directory of Open Access Journals (Sweden)

    Bjørn P Pedersen

    Full Text Available BACKGROUND: Structured Logistic Regression (SLR is a newly developed machine learning tool first proposed in the context of text categorization. Current availability of extensive protein sequence databases calls for an automated method to reliably classify sequences and SLR seems well-suited for this task. The classification of P-type ATPases, a large family of ATP-driven membrane pumps transporting essential cations, was selected as a test-case that would generate important biological information as well as provide a proof-of-concept for the application of SLR to a large scale bioinformatics problem. RESULTS: Using SLR, we have built classifiers to identify and automatically categorize P-type ATPases into one of 11 pre-defined classes. The SLR-classifiers are compared to a Hidden Markov Model approach and shown to be highly accurate and scalable. Representing the bulk of currently known sequences, we analysed 9.3 million sequences in the UniProtKB and attempted to classify a large number of P-type ATPases. To examine the distribution of pumps on organisms, we also applied SLR to 1,123 complete genomes from the Entrez genome database. Finally, we analysed the predicted membrane topology of the identified P-type ATPases. CONCLUSIONS: Using the SLR-based classification tool we are able to run a large scale study of P-type ATPases. This study provides proof-of-concept for the application of SLR to a bioinformatics problem and the analysis of P-type ATPases pinpoints new and interesting targets for further biochemical characterization and structural analysis.

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

    Science.gov (United States)

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

    1987-08-01

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

  10. Cloning and Sequencing of Protein Kinase cDNA from Harbor Seal (Phoca vitulina Lymphocytes

    Directory of Open Access Journals (Sweden)

    Jennifer C. C. Neale

    2004-01-01

    Full Text Available Protein kinases (PKs play critical roles in signal transduction and activation of lymphocytes. The identification of PK genes provides a tool for understanding mechanisms of immunotoxic xenobiotics. As part of a larger study investigating persistent organic pollutants in the harbor seal and their possible immunomodulatory actions, we sequenced harbor seal cDNA fragments encoding PKs. The procedure, using degenerate primers based on conserved motifs of human protein tyrosine kinases (PTKs, successfully amplified nine phocid PK gene fragments with high homology to human and rodent orthologs. We identified eight PTKs and one dual (serine/threonine and tyrosine kinase. Among these were several PKs important in early signaling events through the B- and T-cell receptors (FYN, LYN, ITK and SYK and a MAP kinase involved in downstream signal transduction. V-FGR, RET and DDR2 were also expressed. Sequential activation of protein kinases ultimately induces gene transcription leading to the proliferation and differentiation of lymphocytes critical to adaptive immunity. PKs are potential targets of bioactive xenobiotics, including persistent organic pollutants of the marine environment; characterization of these molecules in the harbor seal provides a foundation for further research illuminating mechanisms of action of contaminants speculated to contribute to large-scale die-offs of marine mammals via immunosuppression.

  11. Movement Pattern Analysis Based on Sequence Signatures

    Directory of Open Access Journals (Sweden)

    Seyed Hossein Chavoshi

    2015-09-01

    Full Text Available Increased affordability and deployment of advanced tracking technologies have led researchers from various domains to analyze the resulting spatio-temporal movement data sets for the purpose of knowledge discovery. Two different approaches can be considered in the analysis of moving objects: quantitative analysis and qualitative analysis. This research focuses on the latter and uses the qualitative trajectory calculus (QTC, a type of calculus that represents qualitative data on moving point objects (MPOs, and establishes a framework to analyze the relative movement of multiple MPOs. A visualization technique called sequence signature (SESI is used, which enables to map QTC patterns in a 2D indexed rasterized space in order to evaluate the similarity of relative movement patterns of multiple MPOs. The applicability of the proposed methodology is illustrated by means of two practical examples of interacting MPOs: cars on a highway and body parts of a samba dancer. The results show that the proposed method can be effectively used to analyze interactions of multiple MPOs in different domains.

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

    International Nuclear Information System (INIS)

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

    1994-01-01

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

  13. Predicting protein amidation sites by orchestrating amino acid sequence features

    Science.gov (United States)

    Zhao, Shuqiu; Yu, Hua; Gong, Xiujun

    2017-08-01

    Amidation is the fourth major category of post-translational modifications, which plays an important role in physiological and pathological processes. Identifying amidation sites can help us understanding the amidation and recognizing the original reason of many kinds of diseases. But the traditional experimental methods for predicting amidation sites are often time-consuming and expensive. In this study, we propose a computational method for predicting amidation sites by orchestrating amino acid sequence features. Three kinds of feature extraction methods are used to build a feature vector enabling to capture not only the physicochemical properties but also position related information of the amino acids. An extremely randomized trees algorithm is applied to choose the optimal features to remove redundancy and dependence among components of the feature vector by a supervised fashion. Finally the support vector machine classifier is used to label the amidation sites. When tested on an independent data set, it shows that the proposed method performs better than all the previous ones with the prediction accuracy of 0.962 at the Matthew's correlation coefficient of 0.89 and area under curve of 0.964.

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

    Directory of Open Access Journals (Sweden)

    Suzan-Monti Marie

    2009-05-01

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

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

    Directory of Open Access Journals (Sweden)

    Strahm Yvan

    2006-10-01

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

  16. Extreme sequence divergence but conserved ligand-binding specificity in Streptococcus pyogenes M protein.

    Directory of Open Access Journals (Sweden)

    2006-05-01

    Full Text Available Many pathogenic microorganisms evade host immunity through extensive sequence variability in a protein region targeted by protective antibodies. In spite of the sequence variability, a variable region commonly retains an important ligand-binding function, reflected in the presence of a highly conserved sequence motif. Here, we analyze the limits of sequence divergence in a ligand-binding region by characterizing the hypervariable region (HVR of Streptococcus pyogenes M protein. Our studies were focused on HVRs that bind the human complement regulator C4b-binding protein (C4BP, a ligand that confers phagocytosis resistance. A previous comparison of C4BP-binding HVRs identified residue identities that could be part of a binding motif, but the extended analysis reported here shows that no residue identities remain when additional C4BP-binding HVRs are included. Characterization of the HVR in the M22 protein indicated that two relatively conserved Leu residues are essential for C4BP binding, but these residues are probably core residues in a coiled-coil, implying that they do not directly contribute to binding. In contrast, substitution of either of two relatively conserved Glu residues, predicted to be solvent-exposed, had no effect on C4BP binding, although each of these changes had a major effect on the antigenic properties of the HVR. Together, these findings show that HVRs of M proteins have an extraordinary capacity for sequence divergence and antigenic variability while retaining a specific ligand-binding function.

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

    Science.gov (United States)

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

    2003-05-01

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

  18. RESEARCH NOTE Genome-based exome-sequencing analysis ...

    Indian Academy of Sciences (India)

    Navya

    2017-02-22

    Feb 22, 2017 ... Genome-based exome-sequencing analysis identifies GYG1, DIS3L, DDRGK1 genes ... Cardiology Division, Department of Internal Medicine, Severance .... with p values of <0.05 byanalyzing differences in allele distribution.

  19. Swarm-based Sequencing Recommendations in E-learning

    NARCIS (Netherlands)

    Van den Berg, Bert; Tattersall, Colin; Janssen, José; Brouns, Francis; Kurvers, Hub; Koper, Rob

    2005-01-01

    Van den Berg, B., Tattersall, C., Janssen, J., Brouns, F., Kurvers, H., & Koper, R. (2006). Swarm-based Sequencing Recommendations in E-learning. International Journal of Computer Science & Applications, III(III), 1-11.

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

    Science.gov (United States)

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

    2018-01-01

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

  1. Nucleotide and amino acid sequences of a coat protein of an Ukrainian isolate of Potato virus Y: comparison with homologous sequences of other isolates and phylogenetic analysis

    Directory of Open Access Journals (Sweden)

    Budzanivska I. G.

    2014-03-01

    Full Text Available Aim. Identification of the widespread Ukrainian isolate(s of PVY (Potato virus Y in different potato cultivars and subsequent phylogenetic analysis of detected PVY isolates based on NA and AA sequences of coat protein. Methods. ELISA, RT-PCR, DNA sequencing and phylogenetic analysis. Results. PVY has been identified serologically in potato cultivars of Ukrainian selection. In this work we have optimized a method for total RNA extraction from potato samples and offered a sensitive and specific PCR-based test system of own design for diagnostics of the Ukrainian PVY isolates. Part of the CP gene of the Ukrainian PVY isolate has been sequenced and analyzed phylogenetically. It is demonstrated that the Ukrainian isolate of Potato virus Y (CP gene has a higher percentage of homology with the recombinant isolates (strains of this pathogen (approx. 98.8– 99.8 % of homology for both nucleotide and translated amino acid sequences of the CP gene. The Ukrainian isolate of PVY is positioned in the separate cluster together with the isolates found in Syria, Japan and Iran; these isolates possibly have common origin. The Ukrainian PVY isolate is confirmed to be recombinant. Conclusions. This work underlines the need and provides the means for accurate monitoring of Potato virus Y in the agroecosystems of Ukraine. Most importantly, the phylogenetic analysis demonstrated the recombinant nature of this PVY isolate which has been attributed to the strain group O, subclade N:O.

  2. Predicting tissue-specific expressions based on sequence characteristics

    KAUST Repository

    Paik, Hyojung; Ryu, Tae Woo; Heo, Hyoungsam; Seo, Seungwon; Lee, Doheon; Hur, Cheolgoo

    2011-01-01

    In multicellular organisms, including humans, understanding expression specificity at the tissue level is essential for interpreting protein function, such as tissue differentiation. We developed a prediction approach via generated sequence features from overrepresented patterns in housekeeping (HK) and tissue-specific (TS) genes to classify TS expression in humans. Using TS domains and transcriptional factor binding sites (TFBSs), sequence characteristics were used as indices of expressed tissues in a Random Forest algorithm by scoring exclusive patterns considering the biological intuition; TFBSs regulate gene expression, and the domains reflect the functional specificity of a TS gene. Our proposed approach displayed better performance than previous attempts and was validated using computational and experimental methods.

  3. Predicting tissue-specific expressions based on sequence characteristics

    KAUST Repository

    Paik, Hyojung

    2011-04-30

    In multicellular organisms, including humans, understanding expression specificity at the tissue level is essential for interpreting protein function, such as tissue differentiation. We developed a prediction approach via generated sequence features from overrepresented patterns in housekeeping (HK) and tissue-specific (TS) genes to classify TS expression in humans. Using TS domains and transcriptional factor binding sites (TFBSs), sequence characteristics were used as indices of expressed tissues in a Random Forest algorithm by scoring exclusive patterns considering the biological intuition; TFBSs regulate gene expression, and the domains reflect the functional specificity of a TS gene. Our proposed approach displayed better performance than previous attempts and was validated using computational and experimental methods.

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

    Directory of Open Access Journals (Sweden)

    Teresa Nogueira

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

  5. Variation in the prion protein sequence in Dutch goat breeds.

    Science.gov (United States)

    Windig, J J; Hoving, R A H; Priem, J; Bossers, A; van Keulen, L J M; Langeveld, J P M

    2016-10-01

    Scrapie is a neurodegenerative disease occurring in goats and sheep. Several haplotypes of the prion protein increase resistance to scrapie infection and may be used in selective breeding to help eradicate scrapie. In this study, frequencies of the allelic variants of the PrP gene are determined for six goat breeds in the Netherlands. Overall frequencies in Dutch goats were determined from 768 brain tissue samples in 2005, 766 in 2008 and 300 in 2012, derived from random sampling for the national scrapie surveillance without knowledge of the breed. Breed specific frequencies were determined in the winter 2013/2014 by sampling 300 breeding animals from the main breeders of the different breeds. Detailed analysis of the scrapie-resistant K222 haplotype was carried out in 2014 for 220 Dutch Toggenburger goats and in 2015 for 942 goats from the Saanen derived White Goat breed. Nine haplotypes were identified in the Dutch breeds. Frequencies for non-wild type haplotypes were generally low. Exception was the K222 haplotype in the Dutch Toggenburger (29%) and the S146 haplotype in the Nubian and Boer breeds (respectively 7 and 31%). The frequency of the K222 haplotype in the Toggenburger was higher than for any other breed reported in literature, while for the White Goat breed it was with 3.1% similar to frequencies of other Saanen or Saanen derived breeds. Further evidence was found for the existence of two M142 haplotypes, M142 /S240 and M142 /P240 . Breeds vary in haplotype frequencies but frequencies of resistant genotypes are generally low and consequently selective breeding for scrapie resistance can only be slow but will benefit from animals identified in this study. The unexpectedly high frequency of the K222 haplotype in the Dutch Toggenburger underlines the need for conservation of rare breeds in order to conserve genetic diversity rare or absent in other breeds. © 2016 Blackwell Verlag GmbH.

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

    OpenAIRE

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

    1996-01-01

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

  7. DIALIGN: multiple DNA and protein sequence alignment at BiBiServ.

    OpenAIRE

    Morgenstern, Burkhard

    2004-01-01

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

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

    KAUST Repository

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

    2012-01-01

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

  9. Mapping Base Modifications in DNA by Transverse-Current Sequencing

    Science.gov (United States)

    Alvarez, Jose R.; Skachkov, Dmitry; Massey, Steven E.; Kalitsov, Alan; Velev, Julian P.

    2018-02-01

    Sequencing DNA modifications and lesions, such as methylation of cytosine and oxidation of guanine, is even more important and challenging than sequencing the genome itself. The traditional methods for detecting DNA modifications are either insensitive to these modifications or require additional processing steps to identify a particular type of modification. Transverse-current sequencing in nanopores can potentially identify the canonical bases and base modifications in the same run. In this work, we demonstrate that the most common DNA epigenetic modifications and lesions can be detected with any predefined accuracy based on their tunneling current signature. Our results are based on simulations of the nanopore tunneling current through DNA molecules, calculated using nonequilibrium electron-transport methodology within an effective multiorbital model derived from first-principles calculations, followed by a base-calling algorithm accounting for neighbor current-current correlations. This methodology can be integrated with existing experimental techniques to improve base-calling fidelity.

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

    Science.gov (United States)

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

    2002-12-01

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

  11. Parallel algorithms for large-scale biological sequence alignment on Xeon-Phi based clusters.

    Science.gov (United States)

    Lan, Haidong; Chan, Yuandong; Xu, Kai; Schmidt, Bertil; Peng, Shaoliang; Liu, Weiguo

    2016-07-19

    Computing alignments between two or more sequences are common operations frequently performed in computational molecular biology. The continuing growth of biological sequence databases establishes the need for their efficient parallel implementation on modern accelerators. This paper presents new approaches to high performance biological sequence database scanning with the Smith-Waterman algorithm and the first stage of progressive multiple sequence alignment based on the ClustalW heuristic on a Xeon Phi-based compute cluster. Our approach uses a three-level parallelization scheme to take full advantage of the compute power available on this type of architecture; i.e. cluster-level data parallelism, thread-level coarse-grained parallelism, and vector-level fine-grained parallelism. Furthermore, we re-organize the sequence datasets and use Xeon Phi shuffle operations to improve I/O efficiency. Evaluations show that our method achieves a peak overall performance up to 220 GCUPS for scanning real protein sequence databanks on a single node consisting of two Intel E5-2620 CPUs and two Intel Xeon Phi 7110P cards. It also exhibits good scalability in terms of sequence length and size, and number of compute nodes for both database scanning and multiple sequence alignment. Furthermore, the achieved performance is highly competitive in comparison to optimized Xeon Phi and GPU implementations. Our implementation is available at https://github.com/turbo0628/LSDBS-mpi .

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

    Science.gov (United States)

    Wang, Yanbin; You, Zhuhong; Li, Xiao; Chen, Xing; Jiang, Tonghai; Zhang, Jingting

    2017-05-11

    Protein-protein interactions (PPIs) are essential for most living organisms' process. Thus, detecting PPIs is extremely important to understand the molecular mechanisms of biological systems. Although many PPIs data have been generated by high-throughput technologies for a variety of organisms, the whole interatom is still far from complete. In addition, the high-throughput technologies for detecting PPIs has some unavoidable defects, including time consumption, high cost, and high error rate. In recent years, with the development of machine learning, computational methods have been broadly used to predict PPIs, and can achieve good prediction rate. In this paper, we present here PCVMZM, a computational method based on a Probabilistic Classification Vector Machines (PCVM) model and Zernike moments (ZM) descriptor for predicting the PPIs from protein amino acids sequences. Specifically, a Zernike moments (ZM) descriptor is used to extract protein evolutionary information from Position-Specific Scoring Matrix (PSSM) generated by Position-Specific Iterated Basic Local Alignment Search Tool (PSI-BLAST). Then, PCVM classifier is used to infer the interactions among protein. When performed on PPIs datasets of Yeast and H. Pylori , the proposed method can achieve the average prediction accuracy of 94.48% and 91.25%, respectively. In order to further evaluate the performance of the proposed method, the state-of-the-art support vector machines (SVM) classifier is used and compares with the PCVM model. Experimental results on the Yeast dataset show that the performance of PCVM classifier is better than that of SVM classifier. The experimental results indicate that our proposed method is robust, powerful and feasible, which can be used as a helpful tool for proteomics research.

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

    Directory of Open Access Journals (Sweden)

    Hilal Kazan

    2010-07-01

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

  14. The nucleotide sequence of human transition protein 1 cDNA

    Energy Technology Data Exchange (ETDEWEB)

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

    1988-08-11

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

  15. Unraveling the sequence and structure of the protein osteocalcin from a 42 ka fossil horse

    Science.gov (United States)

    Ostrom, Peggy H.; Gandhi, Hasand; Strahler, John R.; Walker, Angela K.; Andrews, Philip C.; Leykam, Joseph; Stafford, Thomas W.; Kelly, Robert L.; Walker, Danny N.; Buckley, Mike; Humpula, James

    2006-04-01

    We report the first complete amino acid sequence and evidence of secondary structure for osteocalcin from a temperate fossil. The osteocalcin derives from a 42 ka equid bone excavated from Juniper Cave, Wyoming. Results were determined by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-MS) and Edman sequencing with independent confirmation of the sequence in two laboratories. The ancient sequence was compared to that of three modern taxa: horse ( Equus caballus), zebra ( Equus grevyi), and donkey ( Equus asinus). Although there was no difference in sequence among modern taxa, MALDI-MS and Edman sequencing show that residues 48 and 49 of our modern horse are Thr, Ala rather than Pro, Val as previously reported (Carstanjen B., Wattiez, R., Armory, H., Lepage, O.M., Remy, B., 2002. Isolation and characterization of equine osteocalcin. Ann. Med. Vet.146(1), 31-38). MALDI-MS and Edman sequencing data indicate that the osteocalcin sequence of the 42 ka fossil is similar to that of modern horse. Previously inaccessible structural attributes for ancient osteocalcin were observed. Glu 39 rather than Gln 39 is consistent with deamidation, a process known to occur during fossilization and aging. Two post-translational modifications were documented: Hyp 9 and a disulfide bridge. The latter suggests at least partial retention of secondary structure. As has been done for ancient DNA research, we recommend standards for preparation and criteria for authenticating results of ancient protein sequencing.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-04-15

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

  17. Deep Sequencing Reveals Uncharted Isoform Heterogeneity of the Protein-Coding Transcriptome in Cerebral Ischemia.

    Science.gov (United States)

    Bhattarai, Sunil; Aly, Ahmed; Garcia, Kristy; Ruiz, Diandra; Pontarelli, Fabrizio; Dharap, Ashutosh

    2018-06-03

    Gene expression in cerebral ischemia has been a subject of intense investigations for several years. Studies utilizing probe-based high-throughput methodologies such as microarrays have contributed significantly to our existing knowledge but lacked the capacity to dissect the transcriptome in detail. Genome-wide RNA-sequencing (RNA-seq) enables comprehensive examinations of transcriptomes for attributes such as strandedness, alternative splicing, alternative transcription start/stop sites, and sequence composition, thus providing a very detailed account of gene expression. Leveraging this capability, we conducted an in-depth, genome-wide evaluation of the protein-coding transcriptome of the adult mouse cortex after transient focal ischemia at 6, 12, or 24 h of reperfusion using RNA-seq. We identified a total of 1007 transcripts at 6 h, 1878 transcripts at 12 h, and 1618 transcripts at 24 h of reperfusion that were significantly altered as compared to sham controls. With isoform-level resolution, we identified 23 splice variants arising from 23 genes that were novel mRNA isoforms. For a subset of genes, we detected reperfusion time-point-dependent splice isoform switching, indicating an expression and/or functional switch for these genes. Finally, for 286 genes across all three reperfusion time-points, we discovered multiple, distinct, simultaneously expressed and differentially altered isoforms per gene that were generated via alternative transcription start/stop sites. Of these, 165 isoforms derived from 109 genes were novel mRNAs. Together, our data unravel the protein-coding transcriptome of the cerebral cortex at an unprecedented depth to provide several new insights into the flexibility and complexity of stroke-related gene transcription and transcript organization.

  18. Sequence variability is correlated with weak immunogenicity in Streptococcus pyogenes M protein.

    Science.gov (United States)

    Lannergård, Jonas; Kristensen, Bodil M; Gustafsson, Mattias C U; Persson, Jenny J; Norrby-Teglund, Anna; Stålhammar-Carlemalm, Margaretha; Lindahl, Gunnar

    2015-10-01

    The M protein of Streptococcus pyogenes, a major bacterial virulence factor, has an amino-terminal hypervariable region (HVR) that is a target for type-specific protective antibodies. Intriguingly, the HVR elicits a weak antibody response, indicating that it escapes host immunity by two mechanisms, sequence variability and weak immunogenicity. However, the properties influencing the immunogenicity of regions in an M protein remain poorly understood. Here, we studied the antibody response to different regions of the classical M1 and M5 proteins, in which not only the HVR but also the adjacent fibrinogen-binding B repeat region exhibits extensive sequence divergence. Analysis of antisera from S. pyogenes-infected patients, infected mice, and immunized mice showed that both the HVR and the B repeat region elicited weak antibody responses, while the conserved carboxy-terminal part was immunodominant. Thus, we identified a correlation between sequence variability and weak immunogenicity for M protein regions. A potential explanation for the weak immunogenicity was provided by the demonstration that protease digestion selectively eliminated the HVR-B part from whole M protein-expressing bacteria. These data support a coherent model, in which the entire variable HVR-B part evades antibody attack, not only by sequence variability but also by weak immunogenicity resulting from protease attack. © 2015 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

  19. Sequence variability is correlated with weak immunogenicity in Streptococcus pyogenes M protein

    Science.gov (United States)

    Lannergård, Jonas; Kristensen, Bodil M; Gustafsson, Mattias C U; Persson, Jenny J; Norrby-Teglund, Anna; Stålhammar-Carlemalm, Margaretha; Lindahl, Gunnar

    2015-01-01

    The M protein of Streptococcus pyogenes, a major bacterial virulence factor, has an amino-terminal hypervariable region (HVR) that is a target for type-specific protective antibodies. Intriguingly, the HVR elicits a weak antibody response, indicating that it escapes host immunity by two mechanisms, sequence variability and weak immunogenicity. However, the properties influencing the immunogenicity of regions in an M protein remain poorly understood. Here, we studied the antibody response to different regions of the classical M1 and M5 proteins, in which not only the HVR but also the adjacent fibrinogen-binding B repeat region exhibits extensive sequence divergence. Analysis of antisera from S. pyogenes-infected patients, infected mice, and immunized mice showed that both the HVR and the B repeat region elicited weak antibody responses, while the conserved carboxy-terminal part was immunodominant. Thus, we identified a correlation between sequence variability and weak immunogenicity for M protein regions. A potential explanation for the weak immunogenicity was provided by the demonstration that protease digestion selectively eliminated the HVR-B part from whole M protein-expressing bacteria. These data support a coherent model, in which the entire variable HVR-B part evades antibody attack, not only by sequence variability but also by weak immunogenicity resulting from protease attack. PMID:26175306

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1999-03-15

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

  1. An assembly sequence planning method based on composite algorithm

    Directory of Open Access Journals (Sweden)

    Enfu LIU

    2016-02-01

    Full Text Available To solve the combination explosion problem and the blind searching problem in assembly sequence planning of complex products, an assembly sequence planning method based on composite algorithm is proposed. In the composite algorithm, a sufficient number of feasible assembly sequences are generated using formalization reasoning algorithm as the initial population of genetic algorithm. Then fuzzy knowledge of assembly is integrated into the planning process of genetic algorithm and ant algorithm to get the accurate solution. At last, an example is conducted to verify the feasibility of composite algorithm.

  2. An optical CDMA system based on chaotic sequences

    Science.gov (United States)

    Liu, Xiao-lei; En, De; Wang, Li-guo

    2014-03-01

    In this paper, a coherent asynchronous optical code division multiple access (OCDMA) system is proposed, whose encoder/decoder is an all-optical generator. This all-optical generator can generate analog and bipolar chaotic sequences satisfying the logistic maps. The formula of bit error rate (BER) is derived, and the relationship of BER and the number of simultaneous transmissions is analyzed. Due to the good property of correlation, this coherent OCDMA system based on these bipolar chaotic sequences can support a large number of simultaneous users, which shows that these chaotic sequences are suitable for asynchronous OCDMA system.

  3. Characterization of upstream sequences of the LIM2 gene that bind developmentally regulated and lens-specific proteins

    Institute of Scientific and Technical Information of China (English)

    HSU Heng; Robert L. CHURCH

    2004-01-01

    During lens development, lens epithelial cells differentiate into fiber cells. To date, four major lens fiber cell intrinsic membrane proteins (MIP) ranging in size from 70 kD to 19 kD have been characterized. The second most abundant lens fiber cell intrinsic membrane protein is MP19. This protein probably is involved with lens cell communication and relates with cataractogenesis. The aim of this research is to characterize upstream sequences of the MP19 (also called LIM2) gene that bind developmentally regulated and lens-specific proteins. We have used the gel mobility assays and corresponding competition experiments to identify and characterize cis elements within approximately 500 bases of LIM2 upstream sequences. Our studies locate the positions of some cis elements, including a "CA" repeat, a methylation Hha I island, an FnuD II site, an Ap1 and an Ap2 consensus sequences, and identify some specific cis elements which relate to lens-specific transcription of LIM2. Our experiments also preliminarily identify trans factors which bind to specific cis elements of the LIM2 promoter and/or regulate transcription of LIM2. We conclude that developmental regulation and coordination of the MP 19 gene in ocular lens fiber cells is controlled by the presence of specific cis elements that bind regulatory trans factors that affect LIM2 gene expression. DNA methylation is one mechanism of controlling LIM2 gene expression during lens development.

  4. Automation tools for accelerator control a network based sequencer

    International Nuclear Information System (INIS)

    Clout, P.; Geib, M.; Westervelt, R.

    1991-01-01

    In conjunction with a major client, Vista Control Systems has developed a sequencer for control systems which works in conjunction with its realtime, distributed Vsystem database. Vsystem is a network-based data acquisition, monitoring and control system which has been applied successfully to both accelerator projects and projects outside this realm of research. The network-based sequencer allows a user to simply define a thread of execution in any supported computer on the network. The script defining a sequence has a simple syntax designed for non-programmers, with facilities for selectively abbreviating the channel names for easy reference. The semantics of the script contains most of the familiar capabilities of conventional programming languages, including standard stream I/O and the ability to start other processes with parameters passed. The script is compiled to threaded code for execution efficiency. The implementation is described in some detail and examples are given of applications for which the sequencer has been used

  5. Protein sequences and redox titrations indicate that the electron acceptors in reaction centers from heliobacteria are similar to Photosystem I

    Science.gov (United States)

    Trost, J. T.; Brune, D. C.; Blankenship, R. E.

    1992-01-01

    Photosynthetic reaction centers isolated from Heliobacillus mobilis exhibit a single major protein on SDS-PAGE of 47 000 Mr. Attempts to sequence the reaction center polypeptide indicated that the N-terminus is blocked. After enzymatic and chemical cleavage, four peptide fragments were sequenced from the Heliobacillus mobilis apoprotein. Only one of these sequences showed significant specific similarity to any of the protein and deduced protein sequences in the GenBank data base. This fragment is identical with 56% of the residues, including both cysteines, found in highly conserved region that is proposed to bind iron-sulfur center Fx in the Photosystem I reaction center peptide that is the psaB gene product. The similarity to the psaA gene product in this region is 48%. Redox titrations of laser-flash-induced photobleaching with millisecond decay kinetics on isolated reaction centers from Heliobacterium gestii indicate a midpoint potential of -414 mV with n = 2 titration behavior. In membranes, the behavior is intermediate between n = 1 and n = 2, and the apparent midpoint potential is -444 mV. This is compared to the behavior in Photosystem I, where the intermediate electron acceptor A1, thought to be a phylloquinone molecule, has been proposed to undergo a double reduction at low redox potentials in the presence of viologen redox mediators. These results strongly suggest that the acceptor side electron transfer system in reaction centers from heliobacteria is indeed analogous to that found in Photosystem I. The sequence similarities indicate that the divergence of the heliobacteria from the Photosystem I line occurred before the gene duplication and subsequent divergence that lead to the heterodimeric protein core of the Photosystem I reaction center.

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

    Science.gov (United States)

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

    2015-05-16

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

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

    Science.gov (United States)

    Mahajan, Gaurang; Mande, Shekhar C

    2017-04-04

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

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

    Science.gov (United States)

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

    1991-08-22

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

  9. High throughput sequencing and proteomics to identify immunogenic proteins of a new pathogen: the dirty genome approach.

    Directory of Open Access Journals (Sweden)

    Gilbert Greub

    Full Text Available BACKGROUND: With the availability of new generation sequencing technologies, bacterial genome projects have undergone a major boost. Still, chromosome completion needs a costly and time-consuming gap closure, especially when containing highly repetitive elements. However, incomplete genome data may be sufficiently informative to derive the pursued information. For emerging pathogens, i.e. newly identified pathogens, lack of release of genome data during gap closure stage is clearly medically counterproductive. METHODS/PRINCIPAL FINDINGS: We thus investigated the feasibility of a dirty genome approach, i.e. the release of unfinished genome sequences to develop serological diagnostic tools. We showed that almost the whole genome sequence of the emerging pathogen Parachlamydia acanthamoebae was retrieved even with relatively short reads from Genome Sequencer 20 and Solexa. The bacterial proteome was analyzed to select immunogenic proteins, which were then expressed and used to elaborate the first steps of an ELISA. CONCLUSIONS/SIGNIFICANCE: This work constitutes the proof of principle for a dirty genome approach, i.e. the use of unfinished genome sequences of pathogenic bacteria, coupled with proteomics to rapidly identify new immunogenic proteins useful to develop in the future specific diagnostic tests such as ELISA, immunohistochemistry and direct antigen detection. Although applied here to an emerging pathogen, this combined dirty genome sequencing/proteomic approach may be used for any pathogen for which better diagnostics are needed. These genome sequences may also be very useful to develop DNA based diagnostic tests. All these diagnostic tools will allow further evaluations of the pathogenic potential of this obligate intracellular bacterium.

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

    Science.gov (United States)

    Camproux, A C; Tufféry, P

    2005-08-05

    Understanding and predicting protein structures depend on the complexity and the accuracy of the models used to represent them. We have recently set up a Hidden Markov Model to optimally compress protein three-dimensional conformations into a one-dimensional series of letters of a structural alphabet. Such a model learns simultaneously the shape of representative structural letters describing the local conformation and the logic of their connections, i.e. the transition matrix between the letters. Here, we move one step further and report some evidence that such a model of protein local architecture also captures some accurate amino acid features. All the letters have specific and distinct amino acid distributions. Moreover, we show that words of amino acids can have significant propensities for some letters. Perspectives point towards the prediction of the series of letters describing the structure of a protein from its amino acid sequence.

  11. Sequence analysis of the Epstein-Barr virus (EBV) latent membrane protein-1 gene and promoter region

    DEFF Research Database (Denmark)

    Sandvej, Kristian; Gratama, J W; Munch, M

    1997-01-01

    Sequence variations in the Epstein-Barr virus (EBV) encoded latent membrane protein-1 (LMP-1) gene have been described in a Chinese nasopharyngeal carcinoma-derived isolate (CAO), and in viral isolates from various EBV-associated tumors. It has been suggested that these genetic changes, which...... include loss of a Xho I restriction site (position 169425) and a C-terminal 30-base pair (bp) deletion (position 168287-168256), define EBV genotypes associated with increased tumorigenicity or with disease among particular geographic populations. To determine the frequency of LMP-1 variations in European...... wild-type virus isolates, we sequenced the LMP-1 promoter and gene in EBV from lymphoblastoid cell lines from healthy carriers and patients without EBV-associated disease. Sequence changes were often present, and defined at least four main groups of viral isolates, which we designate Groups A through D...

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

    Science.gov (United States)

    Putaporntip, Chaturong; Thongaree, Siriporn; Jongwutiwes, Somchai

    2013-08-01

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

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

    Science.gov (United States)

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

    2015-11-01

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

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

    KAUST Repository

    Kosinski, Jan

    2013-02-08

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

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

    Science.gov (United States)

    Osipiuk, J; Joachimiak, A

    1997-09-12

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

  16. Classification of Dutch and German avian reoviruses by sequencing the sigma-C protein.

    NARCIS (Netherlands)

    Kant, A.; Balk, F.R.M.; Born, L.; Roozelaar, van D.; Heijmans, J.; Gielkens, A.; Huurne, ter A.A.H.M.

    2003-01-01

    We have amplified, cloned and sequenced (part of) the open reading frame of the S1 segment encoding the ¿ C protein of avian reoviruses isolated from chickens with different disease conditions in Germany and The Netherlands during 1980 up to 2000. These avian reoviruses were analysed

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

    KAUST Repository

    Kosinski, Jan; Barbato, Alessandro; Tramontano, Anna

    2013-01-01

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

  18. Comment on "Protein sequences from mastodon and Tyrannosaurus rex revealed by mass spectrometry".

    Science.gov (United States)

    Pevzner, Pavel A; Kim, Sangtae; Ng, Julio

    2008-08-22

    Asara et al. (Reports, 13 April 2007, p. 280) reported sequencing of Tyrannosaurus rex proteins and used them to establish the evolutionary relationships between birds and dinosaurs. We argue that the reported T. rex peptides may represent statistical artifacts and call for complete data release to enable experimental and computational verification of their findings.

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

    Science.gov (United States)

    Dong, Zheng; Zhou, Hongyu; Tao, Peng

    2018-02-01

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

  20. SVM-Prot 2016: A Web-Server for Machine Learning Prediction of Protein Functional Families from Sequence Irrespective of Similarity.

    Science.gov (United States)

    Li, Ying Hong; Xu, Jing Yu; Tao, Lin; Li, Xiao Feng; Li, Shuang; Zeng, Xian; Chen, Shang Ying; Zhang, Peng; Qin, Chu; Zhang, Cheng; Chen, Zhe; Zhu, Feng; Chen, Yu Zong

    2016-01-01

    Knowledge of protein function is important for biological, medical and therapeutic studies, but many proteins are still unknown in function. There is a need for more improved functional prediction methods. Our SVM-Prot web-server employed a machine learning method for predicting protein functional families from protein sequences irrespective of similarity, which complemented those similarity-based and other methods in predicting diverse classes of proteins including the distantly-related proteins and homologous proteins of different functions. Since its publication in 2003, we made major improvements to SVM-Prot with (1) expanded coverage from 54 to 192 functional families, (2) more diverse protein descriptors protein representation, (3) improved predictive performances due to the use of more enriched training datasets and more variety of protein descriptors, (4) newly integrated BLAST analysis option for assessing proteins in the SVM-Prot predicted functional families that were similar in sequence to a query protein, and (5) newly added batch submission option for supporting the classification of multiple proteins. Moreover, 2 more machine learning approaches, K nearest neighbor and probabilistic neural networks, were added for facilitating collective assessment of protein functions by multiple methods. SVM-Prot can be accessed at http://bidd2.nus.edu.sg/cgi-bin/svmprot/svmprot.cgi.

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

    Science.gov (United States)

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

    2013-01-01

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

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

    Science.gov (United States)

    Zheng, Jifang; Hu, Bi; Wu, Duansheng

    2005-07-01

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

  3. Monte Carlo simulation of a statistical mechanical model of multiple protein sequence alignment.

    Science.gov (United States)

    Kinjo, Akira R

    2017-01-01

    A grand canonical Monte Carlo (MC) algorithm is presented for studying the lattice gas model (LGM) of multiple protein sequence alignment, which coherently combines long-range interactions and variable-length insertions. MC simulations are used for both parameter optimization of the model and production runs to explore the sequence subspace around a given protein family. In this Note, I describe the details of the MC algorithm as well as some preliminary results of MC simulations with various temperatures and chemical potentials, and compare them with the mean-field approximation. The existence of a two-state transition in the sequence space is suggested for the SH3 domain family, and inappropriateness of the mean-field approximation for the LGM is demonstrated.

  4. Typing of canine parvovirus isolates using mini-sequencing based single nucleotide polymorphism analysis.

    Science.gov (United States)

    Naidu, Hariprasad; Subramanian, B Mohana; Chinchkar, Shankar Ramchandra; Sriraman, Rajan; Rana, Samir Kumar; Srinivasan, V A

    2012-05-01

    The antigenic types of canine parvovirus (CPV) are defined based on differences in the amino acids of the major capsid protein VP2. Type specificity is conferred by a limited number of amino acid changes and in particular by few nucleotide substitutions. PCR based methods are not particularly suitable for typing circulating variants which differ in a few specific nucleotide substitutions. Assays for determining SNPs can detect efficiently nucleotide substitutions and can thus be adapted to identify CPV types. In the present study, CPV typing was performed by single nucleotide extension using the mini-sequencing technique. A mini-sequencing signature was established for all the four CPV types (CPV2, 2a, 2b and 2c) and feline panleukopenia virus. The CPV typing using the mini-sequencing reaction was performed for 13 CPV field isolates and the two vaccine strains available in our repository. All the isolates had been typed earlier by full-length sequencing of the VP2 gene. The typing results obtained from mini-sequencing matched completely with that of sequencing. Typing could be achieved with less than 100 copies of standard plasmid DNA constructs or ≤10¹ FAID₅₀ of virus by mini-sequencing technique. The technique was also efficient for detecting multiple types in mixed infections. Copyright © 2012 Elsevier B.V. All rights reserved.

  5. Thermodynamics-based models of transcriptional regulation with gene sequence.

    Science.gov (United States)

    Wang, Shuqiang; Shen, Yanyan; Hu, Jinxing

    2015-12-01

    Quantitative models of gene regulatory activity have the potential to improve our mechanistic understanding of transcriptional regulation. However, the few models available today have been based on simplistic assumptions about the sequences being modeled or heuristic approximations of the underlying regulatory mechanisms. In this work, we have developed a thermodynamics-based model to predict gene expression driven by any DNA sequence. The proposed model relies on a continuous time, differential equation description of transcriptional dynamics. The sequence features of the promoter are exploited to derive the binding affinity which is derived based on statistical molecular thermodynamics. Experimental results show that the proposed model can effectively identify the activity levels of transcription factors and the regulatory parameters. Comparing with the previous models, the proposed model can reveal more biological sense.

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

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    Yan Koon-Kiu

    2007-11-01

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

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

    Science.gov (United States)

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

    2017-07-01

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

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

    Science.gov (United States)

    Truong, Kevin; Ikura, Mitsuhiko

    2003-05-06

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

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

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    Andreas Martin Lisewski

    2008-09-01

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

  10. Establishment of screening technique for mutant cell and analysis of base sequence in the mutation

    International Nuclear Information System (INIS)

    Sofuni, Toshio; Nomi, Takehiko; Yamada, Masami; Masumura, Kenichi

    2000-01-01

    This research project aimed to establish an easy and quick detection method for radiation-induced mutation using molecular-biological techniques and an effective analyzing method for the molecular changes in base sequence. In this year, Spi mutants derived from γ-radiation exposed mouse were analyzed by PCR method and DNA sequence method. Male transgenic mice were exposed to γ-ray at 5,10, 50 Gy and the transgene was taken out from the genome DNA from the spleen in vivo packaging method. Spi mutant plaques were obtained by infecting the recovered phage to E. coli. Sequence analysis for the mutants was made using ALFred DNA sequencer and SequiTherm TM Long-Red Cycle sequencing kit. Sequence analysis was carried out for 41 of 50 independent Spi mutants obtained. The deletions were classified into 4 groups; Group 1 included 15 mutants that were characterized with a large deletion (43 bp-10 kb) with a short homologous sequence. Group 2 included 11 mutants of a large deletion having no homologous sequence at the connecting region. Group 3 included 11 mutants having a short deletion of less than 20 bp, which occurred in the non-repetitive sequence of gam gene and possibly caused by oxidative breakage of DNA or recombination of DNA fragment produced by the breakage. Group 4 included 4 mutants having deletions as short as 20 bp or less in the repetitive sequence of gam gene, resulting in an alteration of the reading frame. Thus, the synthesis of Gam protein was terminated by the appearance of TGA between code 13 and 14 of redB gene, leading to inactivation of gam gene and redBA gene. These results indicated that most of Spi mutants had a deletion in red/gam region and the deletions in more than half mutants occurred in homologous sequences as short as 8 bp. (M.N.)

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

    Science.gov (United States)

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

    2018-05-07

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

  12. Short Linear Sequence Motif LxxPTPh Targets Diverse Proteins to Growing Microtubule Ends

    NARCIS (Netherlands)

    Kumar, Anil; Manatschal, Cristina; Rai, Ankit; Grigoriev, Ilya; Degen, Miriam Steiner; Jaussi, Rolf; Kretzschmar, Ines; Prota, Andrea E; Volkmer, Rudolf; Kammerer, Richard A.; Akhmanova, Anna; Steinmetz, Michel O.

    2017-01-01

    Microtubule plus-end tracking proteins (+TIPs) are involved in virtually all microtubule-based processes. End-binding (EB) proteins are considered master regulators of +TIP interaction networks, since they autonomously track growing microtubule ends and recruit a plethora of proteins to this

  13. Improving pairwise comparison of protein sequences with domain co-occurrence

    Science.gov (United States)

    Gascuel, Olivier

    2018-01-01

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

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

    Science.gov (United States)

    Jawahery, Sudi; Nagarajan, Anu; Matysiak, Silvina

    2013-03-01

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

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

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    Bryan Holland

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

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

    Science.gov (United States)

    Kimura, M; Kimura, J; Hatakeyama, T

    1988-11-21

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

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

    Science.gov (United States)

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

    2015-01-01

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

  18. In silico sequence analysis and homology modeling of predicted beta-amylase 7-like protein in Brachypodium distachyon L.

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    ERTUĞRUL FILIZ

    2014-04-01

    Full Text Available Beta-amylase (β-amylase, EC 3.2.1.2 is an enzyme that catalyses hydrolysis of glucosidic bonds in polysaccharides. In this study, we analyzed protein sequence of predicted beta-amylase 7-like protein in Brachypodium distachyon. pI (isoelectric point value was found as 5.23 in acidic character, while the instability index (II was found as 50.28 with accepted unstable protein. The prediction of subcellular localization was revealed that the protein may reside in chloroplast by using CELLO v.2.5. The 3D structure of protein was performed using comparative homology modeling with SWISS-MODEL. The accuracy of the predicted 3D structure was checked using Ramachandran plot analysis showed that 95.4% in favored region. The results of our study contribute to understanding of β-amylase protein structure in grass species and will be scientific base for 3D modeling of beta-amylase proteins in further studies.

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

    Science.gov (United States)

    Falk, B W; Tsai, J H

    1986-01-01

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

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

    Science.gov (United States)

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

    2005-01-28

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

  1. Analyses of the Sequence and Structural Properties Corresponding to Pentapeptide and Large Palindromes in Proteins.

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    Settu Sridhar

    Full Text Available The analyses of 3967 representative proteins selected from the Protein Data Bank revealed the presence of 2803 pentapeptide and large palindrome sequences with known secondary structure conformation. These represent 2014 unique palindrome sequences. 60% palindromes are not associated with any regular secondary structure and 28% are in helix conformation, 11% in strand conformation and 1% in the coil conformation. The average solvent accessibility values are in the range between 0-155.28 Å2 suggesting that the palindromes in proteins can be either buried, exposed to the solvent or share an intermittent property. The number of residue neighborhood contacts defined by interactions ≤ 3.2 Ǻ is in the range between 0-29 residues. Palindromes of the same length in helix, strand and coil conformation are associated with different amino acid residue preferences at the individual positions. Nearly, 20% palindromes interact with catalytic/active site residues, ligand or metal ions in proteins and may therefore be important for function in the corresponding protein. The average hydrophobicity values for the pentapeptide and large palindromes range between -4.3 to +4.32 and the number of palindromes is almost equally distributed between the negative and positive hydrophobicity values. The palindromes represent 107 different protein families and the hydrolases, transferases, oxidoreductases and lyases contain relatively large number of palindromes.

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

    Energy Technology Data Exchange (ETDEWEB)

    Macklin, Derek; Egan, Rob; Wang, Zhong

    2014-03-14

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

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

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    Qingping Xu

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

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

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    Yan Lianying

    2008-11-01

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

  5. Structure-based barcoding of proteins.

    Science.gov (United States)

    Metri, Rahul; Jerath, Gaurav; Kailas, Govind; Gacche, Nitin; Pal, Adityabarna; Ramakrishnan, Vibin

    2014-01-01

    A reduced representation in the format of a barcode has been developed to provide an overview of the topological nature of a given protein structure from 3D coordinate file. The molecular structure of a protein coordinate file from Protein Data Bank is first expressed in terms of an alpha-numero code and further converted to a barcode image. The barcode representation can be used to compare and contrast different proteins based on their structure. The utility of this method has been exemplified by comparing structural barcodes of proteins that belong to same fold family, and across different folds. In addition to this, we have attempted to provide an illustration to (i) the structural changes often seen in a given protein molecule upon interaction with ligands and (ii) Modifications in overall topology of a given protein during evolution. The program is fully downloadable from the website http://www.iitg.ac.in/probar/. © 2013 The Protein Society.

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

    Science.gov (United States)

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

    1996-02-01

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

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

    KAUST Repository

    Wong, Ka Chun

    2011-02-05

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

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

    Science.gov (United States)

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

    1990-07-01

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

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

    KAUST Repository

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

    2011-01-01

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

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

    Science.gov (United States)

    Groussin, M; Boussau, B; Gouy, M

    2013-07-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

  12. AlignMiner: a Web-based tool for detection of divergent regions in multiple sequence alignments of conserved sequences

    Directory of Open Access Journals (Sweden)

    Claros M Gonzalo

    2010-06-01

    Full Text Available Abstract Background Multiple sequence alignments are used to study gene or protein function, phylogenetic relations, genome evolution hypotheses and even gene polymorphisms. Virtually without exception, all available tools focus on conserved segments or residues. Small divergent regions, however, are biologically important for specific quantitative polymerase chain reaction, genotyping, molecular markers and preparation of specific antibodies, and yet have received little attention. As a consequence, they must be selected empirically by the researcher. AlignMiner has been developed to fill this gap in bioinformatic analyses. Results AlignMiner is a Web-based application for detection of conserved and divergent regions in alignments of conserved sequences, focusing particularly on divergence. It accepts alignments (protein or nucleic acid obtained using any of a variety of algorithms, which does not appear to have a significant impact on the final results. AlignMiner uses different scoring methods for assessing conserved/divergent regions, Entropy being the method that provides the highest number of regions with the greatest length, and Weighted being the most restrictive. Conserved/divergent regions can be generated either with respect to the consensus sequence or to one master sequence. The resulting data are presented in a graphical interface developed in AJAX, which provides remarkable user interaction capabilities. Users do not need to wait until execution is complete and can.even inspect their results on a different computer. Data can be downloaded onto a user disk, in standard formats. In silico and experimental proof-of-concept cases have shown that AlignMiner can be successfully used to designing specific polymerase chain reaction primers as well as potential epitopes for antibodies. Primer design is assisted by a module that deploys several oligonucleotide parameters for designing primers "on the fly". Conclusions AlignMiner can be used

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

    International Nuclear Information System (INIS)

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

    2005-01-01

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

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

    Science.gov (United States)

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

    2014-01-30

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

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

    International Nuclear Information System (INIS)

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

    1990-01-01

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

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

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  17. (Brassicaceae) based on nuclear ribosomal ITS DNA sequences

    Indian Academy of Sciences (India)

    Home; Journals; Journal of Genetics; Volume 93; Issue 2. Phylogeny and biogeography of Alyssum (Brassicaceae) based on nuclear ribosomal ITS DNA sequences. Yan Li Yan Kong Zhe Zhang Yanqiang Yin Bin Liu Guanghui Lv Xiyong Wang. Research Article Volume 93 Issue 2 August 2014 pp 313-323 ...

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

    Science.gov (United States)

    Mukhyala, Kiran; Masselot, Alexandre

    2014-12-01

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

  19. Designing protein-based biomaterials for medical applications.

    Science.gov (United States)

    Gagner, Jennifer E; Kim, Wookhyun; Chaikof, Elliot L

    2014-04-01

    Biomaterials produced by nature have been honed through billions of years, evolving exquisitely precise structure-function relationships that scientists strive to emulate. Advances in genetic engineering have facilitated extensive investigations to determine how changes in even a single peptide within a protein sequence can produce biomaterials with unique thermal, mechanical and biological properties. Elastin, a naturally occurring protein polymer, serves as a model protein to determine the relationship between specific structural elements and desirable material characteristics. The modular, repetitive nature of the protein facilitates the formation of well-defined secondary structures with the ability to self-assemble into complex three-dimensional architectures on a variety of length scales. Furthermore, many opportunities exist to incorporate other protein-based motifs and inorganic materials into recombinant protein-based materials, extending the range and usefulness of these materials in potential biomedical applications. Elastin-like polypeptides (ELPs) can be assembled into 3-D architectures with precise control over payload encapsulation, mechanical and thermal properties, as well as unique functionalization opportunities through both genetic and enzymatic means. An overview of current protein-based materials, their properties and uses in biomedicine will be provided, with a focus on the advantages of ELPs. Applications of these biomaterials as imaging and therapeutic delivery agents will be discussed. Finally, broader implications and future directions of these materials as diagnostic and therapeutic systems will be explored. Copyright © 2013 Elsevier Ltd. All rights reserved.

  20. A New Images Hiding Scheme Based on Chaotic Sequences

    Institute of Scientific and Technical Information of China (English)

    LIU Nian-sheng; GUO Dong-hui; WU Bo-xi; Parr G

    2005-01-01

    We propose a data hidding technique in a still image. This technique is based on chaotic sequence in the transform domain of covert image. We use different chaotic random sequences multiplied by multiple sensitive images, respectively, to spread the spectrum of sensitive images. Multiple sensitive images are hidden in a covert image as a form of noise. The results of theoretical analysis and computer simulation show the new hiding technique have better properties with high security, imperceptibility and capacity for hidden information in comparison with the conventional scheme such as LSB (Least Significance Bit).

  1. Sequence-engineered mRNA Without Chemical Nucleoside Modifications Enables an Effective Protein Therapy in Large Animals

    Science.gov (United States)

    Thess, Andreas; Grund, Stefanie; Mui, Barbara L; Hope, Michael J; Baumhof, Patrick; Fotin-Mleczek, Mariola; Schlake, Thomas

    2015-01-01

    Being a transient carrier of genetic information, mRNA could be a versatile, flexible, and safe means for protein therapies. While recent findings highlight the enormous therapeutic potential of mRNA, evidence that mRNA-based protein therapies are feasible beyond small animals such as mice is still lacking. Previous studies imply that mRNA therapeutics require chemical nucleoside modifications to obtain sufficient protein expression and avoid activation of the innate immune system. Here we show that chemically unmodified mRNA can achieve those goals as well by applying sequence-engineered molecules. Using erythropoietin (EPO) driven production of red blood cells as the biological model, engineered Epo mRNA elicited meaningful physiological responses from mice to nonhuman primates. Even in pigs of about 20 kg in weight, a single adequate dose of engineered mRNA encapsulated in lipid nanoparticles (LNPs) induced high systemic Epo levels and strong physiological effects. Our results demonstrate that sequence-engineered mRNA has the potential to revolutionize human protein therapies. PMID:26050989

  2. Spike protein assembly into the coronavirion: exploring the limits of its sequence requirements

    International Nuclear Information System (INIS)

    Bosch, Berend Jan; Haan, Cornelis A.M. de; Smits, Saskia L.; Rottier, Peter J.M.

    2005-01-01

    The coronavirus spike (S) protein, required for receptor binding and membrane fusion, is incorporated into the assembling virion by interactions with the viral membrane (M) protein. Earlier we showed that the ectodomain of the S protein is not involved in this process. Here we further defined the requirements of the S protein for virion incorporation. We show that the cytoplasmic domain, not the transmembrane domain, determines the association with the M protein and suffices to effect the incorporation into viral particles of chimeric spikes as well as of foreign viral glycoproteins. The essential sequence was mapped to the membrane-proximal region of the cytoplasmic domain, which is also known to be of critical importance for the fusion function of the S protein. Consistently, only short C-terminal truncations of the S protein were tolerated when introduced into the virus by targeted recombination. The important role of the about 38-residues cytoplasmic domain in the assembly of and membrane fusion by this approximately 1300 amino acids long protein is discussed

  3. Mechanism-based strategies for protein thermostabilization.

    Science.gov (United States)

    Mozhaev, V V

    1993-03-01

    Strategies for stabilizing enzymes can be derived from a two-step model of irreversible inactivation that involves preliminary reversible unfolding, followed by an irreversible step. Reversible unfolding is best prevented by covalent immobilization, whereas methods such as covalent modification of amino acid residues or 'medium engineering' (by the addition of low-molecular-weight compounds) are effective against irreversible 'incorrect' refolding. Genetic modification of the protein sequence is the most effective approach for preventing chemical deterioration.

  4. Preparative Protein Production from Inclusion Bodies and Crystallization: A Seven-Week Biochemistry Sequence

    Science.gov (United States)

    Peterson, Megan J.; Snyder, W. Kalani; Westerman, Shelley; McFarland, Benjamin J.

    2011-01-01

    We describe how to produce and purify proteins from E. coli inclusion bodies by adapting versatile, preparative-scale techniques to the undergraduate laboratory schedule. This seven-week sequence of experiments fits into an annual cycle of research activity in biochemistry courses. Recombinant proteins are expressed as inclusion bodies, which are collected, washed, then solubilized in urea. Stepwise dialysis to dilute urea over the course of a week produces refolded protein. Column chromatography is used to purify protein into fractions, which are then analyzed with gel electrophoresis and concentration assays. Students culminate the project by designing crystallization trials in sitting-drop trays. Student evaluation of the experience has been positive, listing 5–12 new techniques learned, which are transferrable to graduate research in academia and industry. PMID:21691428

  5. Statistical distributions of optimal global alignment scores of random protein sequences

    Directory of Open Access Journals (Sweden)

    Tang Jiaowei

    2005-10-01

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

  6. Sequence variation of koala retrovirus transmembrane protein p15E among koalas from different geographic regions

    Science.gov (United States)

    Ishida, Yasuko; McCallister, Chelsea; Nikolaidis, Nikolas; Tsangaras, Kyriakos; Helgen, Kristofer M.; Greenwood, Alex D.; Roca, Alfred L.

    2014-01-01

    The koala retrovirus (KoRV), which is transitioning from an exogenous to an endogenous form, has been associated with high mortality in koalas. For other retroviruses, the envelope protein p15E has been considered a candidate for vaccine development. We therefore examined proviral sequence variation of KoRV p15E in a captive Queensland and three wild southern Australian koalas. We generated 163 sequences with intact open reading frames, which grouped into 39 distinct haplotypes. Sixteen distinct haplotypes comprising 139 of the sequences (85%) coded for the same polypeptide. Among the remaining 23 haplotypes, 22 were detected only once among the sequences, and each had 1 or 2 non-synonymous differences from the majority sequence. Several analyses suggested that p15E was under purifying selection. Important epitopes and domains were highly conserved across the p15E sequences and in previously reported exogenous KoRVs. Overall, these results support the potential use of p15E for KoRV vaccine development. PMID:25462343

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

    Science.gov (United States)

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

    2012-09-14

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

  8. Skeleton-based human action recognition using multiple sequence alignment

    Science.gov (United States)

    Ding, Wenwen; Liu, Kai; Cheng, Fei; Zhang, Jin; Li, YunSong

    2015-05-01

    Human action recognition and analysis is an active research topic in computer vision for many years. This paper presents a method to represent human actions based on trajectories consisting of 3D joint positions. This method first decompose action into a sequence of meaningful atomic actions (actionlets), and then label actionlets with English alphabets according to the Davies-Bouldin index value. Therefore, an action can be represented using a sequence of actionlet symbols, which will preserve the temporal order of occurrence of each of the actionlets. Finally, we employ sequence comparison to classify multiple actions through using string matching algorithms (Needleman-Wunsch). The effectiveness of the proposed method is evaluated on datasets captured by commodity depth cameras. Experiments of the proposed method on three challenging 3D action datasets show promising results.

  9. antaRNA: ant colony-based RNA sequence design.

    Science.gov (United States)

    Kleinkauf, Robert; Mann, Martin; Backofen, Rolf

    2015-10-01

    RNA sequence design is studied at least as long as the classical folding problem. Although for the latter the functional fold of an RNA molecule is to be found ,: inverse folding tries to identify RNA sequences that fold into a function-specific target structure. In combination with RNA-based biotechnology and synthetic biology ,: reliable RNA sequence design becomes a crucial step to generate novel biochemical components. In this article ,: the computational tool antaRNA is presented. It is capable of compiling RNA sequences for a given structure that comply in addition with an adjustable full range objective GC-content distribution ,: specific sequence constraints and additional fuzzy structure constraints. antaRNA applies ant colony optimization meta-heuristics and its superior performance is shown on a biological datasets. http://www.bioinf.uni-freiburg.de/Software/antaRNA CONTACT: backofen@informatik.uni-freiburg.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

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

    Science.gov (United States)

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

    2018-01-01

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

  11. DNA sequence of 15 base pairs is sufficient to mediate both glucocorticoid and progesterone induction of gene expression

    International Nuclear Information System (INIS)

    Straehle, U.; Klock, G.; Schuetz, G.

    1987-01-01

    To define the recognition sequence of the glucocorticoid receptor and its relationship with that of the progesterone receptor, oligonucleotides derived from the glucocorticoid response element of the tyrosine aminotransferase gene were tested upstream of a heterologous promoter for their capacity to mediate effects of these two steroids. The authors show that a 15-base-pair sequence with partial symmetry is sufficient to confer glucocorticoid inducibility on the promoter of the herpes simplex virus thymidine kinase gene. The same 15-base-pair sequence mediates induction by progesterone. Point mutations in the recognition sequence affect inducibility by glucocorticoids and progesterone similarly. Together with the strong conservation of the sequence of the DNA-binding domain of the two receptors, these data suggest that both proteins recognize a sequence that is similar, if not the same

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

    International Nuclear Information System (INIS)

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

    2006-01-01

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

  13. Sequence of a cloned cDNA encoding human ribosomal protein S11

    Energy Technology Data Exchange (ETDEWEB)

    Lott, J B; Mackie, G A

    1988-02-11

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

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

    Science.gov (United States)

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

    2018-06-01

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

  15. HDOCK: a web server for protein-protein and protein-DNA/RNA docking based on a hybrid strategy.

    Science.gov (United States)

    Yan, Yumeng; Zhang, Di; Zhou, Pei; Li, Botong; Huang, Sheng-You

    2017-07-03

    Protein-protein and protein-DNA/RNA interactions play a fundamental role in a variety of biological processes. Determining the complex structures of these interactions is valuable, in which molecular docking has played an important role. To automatically make use of the binding information from the PDB in docking, here we have presented HDOCK, a novel web server of our hybrid docking algorithm of template-based modeling and free docking, in which cases with misleading templates can be rescued by the free docking protocol. The server supports protein-protein and protein-DNA/RNA docking and accepts both sequence and structure inputs for proteins. The docking process is fast and consumes about 10-20 min for a docking run. Tested on the cases with weakly homologous complexes of server. The HDOCK web server is available at http://hdock.phys.hust.edu.cn/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  16. Neutral evolution of proteins: The superfunnel in sequence space and its relation to mutational robustness

    Science.gov (United States)

    Noirel, Josselin; Simonson, Thomas

    2008-11-01

    Following Kimura's neutral theory of molecular evolution [M. Kimura, The Neutral Theory of Molecular Evolution (Cambridge University Press, Cambridge, 1983) (reprinted in 1986)], it has become common to assume that the vast majority of viable mutations of a gene confer little or no functional advantage. Yet, in silico models of protein evolution have shown that mutational robustness of sequences could be selected for, even in the context of neutral evolution. The evolution of a biological population can be seen as a diffusion on the network of viable sequences. This network is called a "neutral network." Depending on the mutation rate μ and the population size N, the biological population can evolve purely randomly (μN ≪1) or it can evolve in such a way as to select for sequences of higher mutational robustness (μN ≫1). The stringency of the selection depends not only on the product μN but also on the exact topology of the neutral network, the special arrangement of which was named "superfunnel." Even though the relation between mutation rate, population size, and selection was thoroughly investigated, a study of the salient topological features of the superfunnel that could affect the strength of the selection was wanting. This question is addressed in this study. We use two different models of proteins: on lattice and off lattice. We compare neutral networks computed using these models to random networks. From this, we identify two important factors of the topology that determine the stringency of the selection for mutationally robust sequences. First, the presence of highly connected nodes ("hubs") in the network increases the selection for mutationally robust sequences. Second, the stringency of the selection increases when the correlation between a sequence's mutational robustness and its neighbors' increases. The latter finding relates a global characteristic of the neutral network to a local one, which is attainable through experiments or molecular

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

    DEFF Research Database (Denmark)

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

    1991-01-01

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

  18. Epitope Sequences in Dengue Virus NS1 Protein Identified by Monoclonal Antibodies

    Directory of Open Access Journals (Sweden)

    Leticia Barboza Rocha

    2017-10-01

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

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

    Science.gov (United States)

    Archibald, John M; Keeling, Patrick J

    2004-01-01

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

  20. A sequence-dependent rigid-base model of DNA

    Science.gov (United States)

    Gonzalez, O.; Petkevičiutė, D.; Maddocks, J. H.

    2013-02-01

    A novel hierarchy of coarse-grain, sequence-dependent, rigid-base models of B-form DNA in solution is introduced. The hierarchy depends on both the assumed range of energetic couplings, and the extent of sequence dependence of the model parameters. A significant feature of the models is that they exhibit the phenomenon of frustration: each base cannot simultaneously minimize the energy of all of its interactions. As a consequence, an arbitrary DNA oligomer has an intrinsic or pre-existing stress, with the level of this frustration dependent on the particular sequence of the oligomer. Attention is focussed on the particular model in the hierarchy that has nearest-neighbor interactions and dimer sequence dependence of the model parameters. For a Gaussian version of this model, a complete coarse-grain parameter set is estimated. The parameterized model allows, for an oligomer of arbitrary length and sequence, a simple and explicit construction of an approximation to the configuration-space equilibrium probability density function for the oligomer in solution. The training set leading to the coarse-grain parameter set is itself extracted from a recent and extensive database of a large number of independent, atomic-resolution molecular dynamics (MD) simulations of short DNA oligomers immersed in explicit solvent. The Kullback-Leibler divergence between probability density functions is used to make several quantitative assessments of our nearest-neighbor, dimer-dependent model, which is compared against others in the hierarchy to assess various assumptions pertaining both to the locality of the energetic couplings and to the level of sequence dependence of its parameters. It is also compared directly against all-atom MD simulation to assess its predictive capabilities. The results show that the nearest-neighbor, dimer-dependent model can successfully resolve sequence effects both within and between oligomers. For example, due to the presence of frustration, the model can

  1. A sequence-dependent rigid-base model of DNA.

    Science.gov (United States)

    Gonzalez, O; Petkevičiūtė, D; Maddocks, J H

    2013-02-07

    A novel hierarchy of coarse-grain, sequence-dependent, rigid-base models of B-form DNA in solution is introduced. The hierarchy depends on both the assumed range of energetic couplings, and the extent of sequence dependence of the model parameters. A significant feature of the models is that they exhibit the phenomenon of frustration: each base cannot simultaneously minimize the energy of all of its interactions. As a consequence, an arbitrary DNA oligomer has an intrinsic or pre-existing stress, with the level of this frustration dependent on the particular sequence of the oligomer. Attention is focussed on the particular model in the hierarchy that has nearest-neighbor interactions and dimer sequence dependence of the model parameters. For a Gaussian version of this model, a complete coarse-grain parameter set is estimated. The parameterized model allows, for an oligomer of arbitrary length and sequence, a simple and explicit construction of an approximation to the configuration-space equilibrium probability density function for the oligomer in solution. The training set leading to the coarse-grain parameter set is itself extracted from a recent and extensive database of a large number of independent, atomic-resolution molecular dynamics (MD) simulations of short DNA oligomers immersed in explicit solvent. The Kullback-Leibler divergence between probability density functions is used to make several quantitative assessments of our nearest-neighbor, dimer-dependent model, which is compared against others in the hierarchy to assess various assumptions pertaining both to the locality of the energetic couplings and to the level of sequence dependence of its parameters. It is also compared directly against all-atom MD simulation to assess its predictive capabilities. The results show that the nearest-neighbor, dimer-dependent model can successfully resolve sequence effects both within and between oligomers. For example, due to the presence of frustration, the model can

  2. Phenylglyoxal-Based Visualization of Citrullinated Proteins on Western Blots

    Directory of Open Access Journals (Sweden)

    Sanne M. M. Hensen

    2015-04-01

    Full Text Available Citrullination is the conversion of peptidylarginine to peptidylcitrulline, which is catalyzed by peptidylarginine deiminases. This conversion is involved in different physiological processes and is associated with several diseases, including cancer and rheumatoid arthritis. A common method to detect citrullinated proteins relies on anti-modified citrulline antibodies directed to a specific chemical modification of the citrulline side chain. Here, we describe a versatile, antibody-independent method for the detection of citrullinated proteins on a membrane, based on the selective reaction of phenylglyoxal with the ureido group of citrulline under highly acidic conditions. The method makes use of 4-azidophenylglyoxal, which, after reaction with citrullinated proteins, can be visualized with alkyne-conjugated probes. The sensitivity of this procedure, using an alkyne-biotin probe, appeared to be comparable to the antibody-based detection method and independent of the sequence surrounding the citrulline.

  3. Crash sequence based risk matrix for motorcycle crashes.

    Science.gov (United States)

    Wu, Kun-Feng; Sasidharan, Lekshmi; Thor, Craig P; Chen, Sheng-Yin

    2018-04-05

    Considerable research has been conducted related to motorcycle and other powered-two-wheeler (PTW) crashes; however, it always has been controversial among practitioners concerning with types of crashes should be first targeted and how to prioritize resources for the implementation of mitigating actions. Therefore, there is a need to identify types of motorcycle crashes that constitute the greatest safety risk to riders - most frequent and most severe crashes. This pilot study seeks exhibit the efficacy of a new approach for prioritizing PTW crash causation sequences as they relate to injury severity to better inform the application of mitigating countermeasures. To accomplish this, the present study constructed a crash sequence-based risk matrix to identify most frequent and most severe motorcycle crashes in an attempt to better connect causes and countermeasures of PTW crashes. Although the frequency of each crash sequence can be computed from crash data, a crash severity model is needed to compare the levels of crash severity among different crash sequences, while controlling for other factors that also have effects on crash severity such drivers' age, use of helmet, etc. The construction of risk matrix based on crash sequences involve two tasks: formulation of crash sequence and the estimation of a mixed-effects (ME) model to adjust the levels of severities for each crash sequence to account for other crash contributing factors that would have an effect on the maximum level of crash severity in a crash. Three data elements from the National Automotive Sampling System - General Estimating System (NASS-GES) data were utilized to form a crash sequence: critical event, crash types, and sequence of events. A mixed-effects model was constructed to model the severity levels for each crash sequence while accounting for the effects of those crash contributing factors on crash severity. A total of 8039 crashes involving 8208 motorcycles occurred during 2011 and 2013 were

  4. Influence of the Amino Acid Sequence on Protein-Mineral Interactions in Soil

    Science.gov (United States)

    Chacon, S. S.; Reardon, P. N.; Purvine, S.; Lipton, M. S.; Washton, N.; Kleber, M.

    2017-12-01

    The intimate associations between protein and mineral surfaces have profound impacts on nutrient cycling in soil. Proteins are an important source of organic C and N, and a subset of proteins, extracellular enzymes (EE), can catalyze the depolymerization of soil organic matter (SOM). Our goal was to determine how variation in the amino acid sequence could influence a protein's susceptibility to become chemically altered by mineral surfaces to infer the fate of adsorbed EE function in soil. We hypothesized that (1) addition of charged amino acids would enhance the adsorption onto oppositely charged mineral surfaces (2) addition of aromatic amino acids would increase adsorption onto zero charged surfaces (3) Increase adsorption of modified proteins would enhance their susceptibility to alterations by redox active minerals. To test these hypotheses, we generated three engineered proxies of a model protein Gb1 (IEP 4.0, 6.2 kDA) by inserting either negatively charged, positively charged or aromatic amino acids in the second loop. These modified proteins were allowed to interact with functionally different mineral surfaces (goethite, montmorillonite, kaolinite and birnessite) at pH 5 and 7. We used LC-MS/MS and solution-state Heteronuclear Single Quantum Coherence Spectroscopy NMR to observe modifications on engineered proteins as a consequence to mineral interactions. Preliminary results indicate that addition of any amino acids to a protein increase its susceptibility to fragmentation and oxidation by redox active mineral surfaces, and alter adsorption to the other mineral surfaces. This suggest that not all mineral surfaces in soil may act as sorbents for EEs and chemical modification of their structure should also be considered as an explanation for decrease in EE activity. Fragmentation of proteins by minerals can bypass the need to produce proteases, but microbial acquisition of other nutrients that require enzymes such as cellulases, ligninases or phosphatases

  5. Phylogeny of the Serrasalmidae (Characiformes based on mitochondrial DNA sequences

    Directory of Open Access Journals (Sweden)

    Guillermo Ortí

    2008-01-01

    Full Text Available Previous studies based on DNA sequences of mitochondrial (mt rRNA genes showed three main groups within the subfamily Serrasalminae: (1 a "pacu" clade of herbivores (Colossoma, Mylossoma, Piaractus; (2 the "Myleus" clade (Myleus, Mylesinus, Tometes, Ossubtus; and (3 the "piranha" clade (Serrasalmus, Pygocentrus, Pygopristis, Pristobrycon, Catoprion, Metynnis. The genus Acnodon was placed as the sister taxon of clade (2+3. However, poor resolution within each clade was obtained due to low levels of variation among rRNA gene sequences. Complete sequences of the hypervariable mtDNA control region for a total of 45 taxa, and additional sequences of 12S and 16S rRNA from a total of 74 taxa representing all genera in the family are now presented to address intragroup relationships. Control region sequences of several serrasalmid species exhibit tandem repeats of short motifs (12 to 33 bp in the 3' end of this region, accounting for substantial length variation. Bayesian inference and maximum parsimony analyses of these sequences identify the same groupings as before and provide further evidence to support the following observations: (a Serrasalmus gouldingi and species of Pristobrycon (non-striolatus form a monophyletic group that is the sister group to other species of Serrasalmus and Pygocentrus; (b Catoprion, Pygopristis, and Pristobrycon striolatus form a well supported clade, sister to the group described above; (c some taxa assigned to the genus Myloplus (M. asterias, M tiete, M ternetzi, and M rubripinnis form a well supported group whereas other Myloplus species remain with uncertain affinities (d Mylesinus, Tometes and Myleus setiger form a monophyletic group.

  6. Revision of Begomovirus taxonomy based on pairwise sequence comparisons

    KAUST Repository

    Brown, Judith K.

    2015-04-18

    Viruses of the genus Begomovirus (family Geminiviridae) are emergent pathogens of crops throughout the tropical and subtropical regions of the world. By virtue of having a small DNA genome that is easily cloned, and due to the recent innovations in cloning and low-cost sequencing, there has been a dramatic increase in the number of available begomovirus genome sequences. Even so, most of the available sequences have been obtained from cultivated plants and are likely a small and phylogenetically unrepresentative sample of begomovirus diversity, a factor constraining taxonomic decisions such as the establishment of operationally useful species demarcation criteria. In addition, problems in assigning new viruses to established species have highlighted shortcomings in the previously recommended mechanism of species demarcation. Based on the analysis of 3,123 full-length begomovirus genome (or DNA-A component) sequences available in public databases as of December 2012, a set of revised guidelines for the classification and nomenclature of begomoviruses are proposed. The guidelines primarily consider a) genus-level biological characteristics and b) results obtained using a standardized classification tool, Sequence Demarcation Tool, which performs pairwise sequence alignments and identity calculations. These guidelines are consistent with the recently published recommendations for the genera Mastrevirus and Curtovirus of the family Geminiviridae. Genome-wide pairwise identities of 91 % and 94 % are proposed as the demarcation threshold for begomoviruses belonging to different species and strains, respectively. Procedures and guidelines are outlined for resolving conflicts that may arise when assigning species and strains to categories wherever the pairwise identity falls on or very near the demarcation threshold value.

  7. Revision of Begomovirus taxonomy based on pairwise sequence comparisons

    KAUST Repository

    Brown, Judith K.; Zerbini, F. Murilo; Navas-Castillo, Jesú s; Moriones, Enrique; Ramos-Sobrinho, Roberto; Silva, José C. F.; Fiallo-Olivé , Elvira; Briddon, Rob W.; Herná ndez-Zepeda, Cecilia; Idris, Ali; Malathi, V. G.; Martin, Darren P.; Rivera-Bustamante, Rafael; Ueda, Shigenori; Varsani, Arvind

    2015-01-01

    Viruses of the genus Begomovirus (family Geminiviridae) are emergent pathogens of crops throughout the tropical and subtropical regions of the world. By virtue of having a small DNA genome that is easily cloned, and due to the recent innovations in cloning and low-cost sequencing, there has been a dramatic increase in the number of available begomovirus genome sequences. Even so, most of the available sequences have been obtained from cultivated plants and are likely a small and phylogenetically unrepresentative sample of begomovirus diversity, a factor constraining taxonomic decisions such as the establishment of operationally useful species demarcation criteria. In addition, problems in assigning new viruses to established species have highlighted shortcomings in the previously recommended mechanism of species demarcation. Based on the analysis of 3,123 full-length begomovirus genome (or DNA-A component) sequences available in public databases as of December 2012, a set of revised guidelines for the classification and nomenclature of begomoviruses are proposed. The guidelines primarily consider a) genus-level biological characteristics and b) results obtained using a standardized classification tool, Sequence Demarcation Tool, which performs pairwise sequence alignments and identity calculations. These guidelines are consistent with the recently published recommendations for the genera Mastrevirus and Curtovirus of the family Geminiviridae. Genome-wide pairwise identities of 91 % and 94 % are proposed as the demarcation threshold for begomoviruses belonging to different species and strains, respectively. Procedures and guidelines are outlined for resolving conflicts that may arise when assigning species and strains to categories wherever the pairwise identity falls on or very near the demarcation threshold value.

  8. Speeding disease gene discovery by sequence based candidate prioritization

    Directory of Open Access Journals (Sweden)

    Porteous David J

    2005-03-01

    Full Text Available Abstract Background Regions of interest identified through genetic linkage studies regularly exceed 30 centimorgans in size and can contain hundreds of genes. Traditionally this number is reduced by matching functional annotation to knowledge of the disease or phenotype in question. However, here we show that disease genes share patterns of sequence-based features that can provide a good basis for automatic prioritization of candidates by machine learning. Results We examined a variety of sequence-based features and found that for many of them there are significant differences between the sets of genes known to be involved in human hereditary disease and those not known to be involved in disease. We have created an automatic classifier called PROSPECTR based on those features using the alternating decision tree algorithm which ranks genes in the order of likelihood of involvement in disease. On average, PROSPECTR enriches lists for disease genes two-fold 77% of the time, five-fold 37% of the time and twenty-fold 11% of the time. Conclusion PROSPECTR is a simple and effective way to identify genes involved in Mendelian and oligogenic disorders. It performs markedly better than the single existing sequence-based classifier on novel data. PROSPECTR could save investigators looking at large regions of interest time and effort by prioritizing positional candidate genes for mutation detection and case-control association studies.

  9. Disk-based compression of data from genome sequencing.

    Science.gov (United States)

    Grabowski, Szymon; Deorowicz, Sebastian; Roguski, Łukasz

    2015-05-01

    High-coverage sequencing data have significant, yet hard to exploit, redundancy. Most FASTQ compressors cannot efficiently compress the DNA stream of large datasets, since the redundancy between overlapping reads cannot be easily captured in the (relatively small) main memory. More interesting solutions for this problem are disk based, where the better of these two, from Cox et al. (2012), is based on the Burrows-Wheeler transform (BWT) and achieves 0.518 bits per base for a 134.0 Gbp human genome sequencing collection with almost 45-fold coverage. We propose overlapping reads compression with minimizers, a compression algorithm dedicated to sequencing reads (DNA only). Our method makes use of a conceptually simple and easily parallelizable idea of minimizers, to obtain 0.317 bits per base as the compression ratio, allowing to fit the 134.0 Gbp dataset into only 5.31 GB of space. http://sun.aei.polsl.pl/orcom under a free license. sebastian.deorowicz@polsl.pl Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  10. Bidirectional gene sequences with similar homology to functional proteins of alkane degrading bacterium pseudomonas fredriksbergensis DNA

    International Nuclear Information System (INIS)

    Megeed, A.A.

    2011-01-01

    The potential for two overlapping fragments of DNA from a clone of newly isolated alkanes degrading bacterium Pseudomonas frederiksbergensis encoding sequences with similar homology to two parts of functional proteins is described. One strand contains a sequence with high homology to alkanes monooxygenase (alkB), a member of the alkanes hydroxylase family, and the other strand contains a sequence with some homology to alcohol dehydrogenase gene (alkJ). Overlapping of the genes on opposite strands has been reported in eukaryotic species, and is now reported in a bacterial species. The sequence comparisons and ORFS results revealed that the regulation and the genes organization involved in alkane oxidation represented in Pseudomonas frederiksberghensis varies among the different known alkane degrading bacteria. The alk gene cluster containing homologues to the known alkane monooxygenase (alkB), and rubredoxin (alkG) are oriented in the same direction, whereas alcohol dehydrogenase (alkJ) is oriented in the opposite direction. Such genomes encode messages on both strands of the DNA, or in an overlapping but different reading frames, of the same strand of DNA. The possibility of creating novel genes from pre-existing sequences, known as overprinting, which is a widespread phenomenon in small viruses. Here, the origin and evolution of the gene overlap to bacteriophages belonging to the family Microviridae have been investigated. Such a phenomenon is most widely described in extremely small genomes such as those of viruses or small plasmids, yet here is a unique phenomenon. (author)

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

    Science.gov (United States)

    Banky, Daniel; Szalkai, Balazs; Grolmusz, Vince

    2014-04-10

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

  12. TFpredict and SABINE: sequence-based prediction of structural and functional characteristics of transcription factors.

    Directory of Open Access Journals (Sweden)

    Johannes Eichner

    Full Text Available One of the key mechanisms of transcriptional control are the specific connections between transcription factors (TF and cis-regulatory elements in gene promoters. The elucidation of these specific protein-DNA interactions is crucial to gain insights into the complex regulatory mechanisms and networks underlying the adaptation of organisms to dynamically changing environmental conditions. As experimental techniques for determining TF binding sites are expensive and mostly performed for selected TFs only, accurate computational approaches are needed to analyze transcriptional regulation in eukaryotes on a genome-wide level. We implemented a four-step classification workflow which for a given protein sequence (1 discriminates TFs from other proteins, (2 determines the structural superclass of TFs, (3 identifies the DNA-binding domains of TFs and (4 predicts their cis-acting DNA motif. While existing tools were extended and adapted for performing the latter two prediction steps, the first two steps are based on a novel numeric sequence representation which allows for combining existing knowledge from a BLAST scan with robust machine learning-based classification. By evaluation on a set of experimentally confirmed TFs and non-TFs, we demonstrate that our new protein sequence representation facilitates more reliable identification and structural classification of TFs than previously proposed sequence-derived features. The algorithms underlying our proposed methodology are implemented in the two complementary tools TFpredict and SABINE. The online and stand-alone versions of TFpredict and SABINE are freely available to academics at http://www.cogsys.cs.uni-tuebingen.de/software/TFpredict/ and http://www.cogsys.cs.uni-tuebingen.de/software/SABINE/.

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

    Directory of Open Access Journals (Sweden)

    Peng Zhen-Ling

    2010-08-01

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

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

    Science.gov (United States)

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

    2017-06-01

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

  15. Insights into the role of protein molecule size and structure on interfacial properties using designed sequences

    Science.gov (United States)

    Dwyer, Mirjana Dimitrijev; He, Lizhong; James, Michael; Nelson, Andrew; Middelberg, Anton P. J.

    2013-01-01

    Mixtures of a large, structured protein with a smaller, unstructured component are inherently complex and hard to characterize at interfaces, leading to difficulties in understanding their interfacial behaviours and, therefore, formulation optimization. Here, we investigated interfacial properties of such a mixed system. Simplicity was achieved using designed sequences in which chemical differences had been eliminated to isolate the effect of molecular size and structure, namely a short unstructured peptide (DAMP1) and its longer structured protein concatamer (DAMP4). Interfacial tension measurements suggested that the size and bulk structuring of the larger molecule led to much slower adsorption kinetics. Neutron reflectometry at equilibrium revealed that both molecules adsorbed as a monolayer to the air–water interface (indicating unfolding of DAMP4 to give a chain of four connected DAMP1 molecules), with a concentration ratio equal to that in the bulk. This suggests the overall free energy of adsorption is equal despite differences in size and bulk structure. At small interfacial extensional strains, only molecule packing influenced the stress response. At larger strains, the effect of size became apparent, with DAMP4 registering a higher stress response and interfacial elasticity. When both components were present at the interface, most stress-dissipating movement was achieved by DAMP1. This work thus provides insights into the role of proteins' molecular size and structure on their interfacial properties, and the designed sequences introduced here can serve as effective tools for interfacial studies of proteins and polymers. PMID:23303222

  16. Protein backbone chemical shifts predicted from searching a database for torsion angle and sequence homology

    International Nuclear Information System (INIS)

    Shen Yang; Bax, Ad

    2007-01-01

    Chemical shifts of nuclei in or attached to a protein backbone are exquisitely sensitive to their local environment. A computer program, SPARTA, is described that uses this correlation with local structure to predict protein backbone chemical shifts, given an input three-dimensional structure, by searching a newly generated database for triplets of adjacent residues that provide the best match in φ/ψ/χ 1 torsion angles and sequence similarity to the query triplet of interest. The database contains 15 N, 1 H N , 1 H α , 13 C α , 13 C β and 13 C' chemical shifts for 200 proteins for which a high resolution X-ray (≤2.4 A) structure is available. The relative importance of the weighting factors for the φ/ψ/χ 1 angles and sequence similarity was optimized empirically. The weighted, average secondary shifts of the central residues in the 20 best-matching triplets, after inclusion of nearest neighbor, ring current, and hydrogen bonding effects, are used to predict chemical shifts for the protein of known structure. Validation shows good agreement between the SPARTA-predicted and experimental shifts, with standard deviations of 2.52, 0.51, 0.27, 0.98, 1.07 and 1.08 ppm for 15 N, 1 H N , 1 H α , 13 C α , 13 C β and 13 C', respectively, including outliers

  17. HLA class I sequence-based typing using DNA recovered from frozen plasma.

    Science.gov (United States)

    Cotton, Laura A; Abdur Rahman, Manal; Ng, Carmond; Le, Anh Q; Milloy, M-J; Mo, Theresa; Brumme, Zabrina L

    2012-08-31

    We describe a rapid, reliable and cost-effective method for intermediate-to-high-resolution sequence-based HLA class I typing using frozen plasma as a source of genomic DNA. The plasma samples investigated had a median age of 8.5 years. Total nucleic acids were isolated from matched frozen PBMC (~2.5 million) and plasma (500 μl) samples from a panel of 25 individuals using commercial silica-based kits. Extractions yielded median [IQR] nucleic acid concentrations of 85.7 [47.0-130.0]ng/μl and 2.2 [1.7-2.6]ng/μl from PBMC and plasma, respectively. Following extraction, ~1000 base pair regions spanning exons 2 and 3 of HLA-A, -B and -C were amplified independently via nested PCR using universal, locus-specific primers and sequenced directly. Chromatogram analysis was performed using commercial DNA sequence analysis software and allele interpretation was performed using a free web-based tool. HLA-A, -B and -C amplification rates were 100% and chromatograms were of uniformly high quality with clearly distinguishable mixed bases regardless of DNA source. Concordance between PBMC and plasma-derived HLA types was 100% at the allele and protein levels. At the nucleotide level, a single partially discordant base (resulting from a failure to call both peaks in a mixed base) was observed out of >46,975 bases sequenced (>99.9% concordance). This protocol has previously been used to perform HLA class I typing from a variety of genomic DNA sources including PBMC, whole blood, granulocyte pellets and serum, from specimens up to 30 years old. This method provides comparable specificity to conventional sequence-based approaches and could be applied in situations where cell samples are unavailable or DNA quantities are limiting. Copyright © 2012 Elsevier B.V. All rights reserved.

  18. Nanochemistry of protein-based delivery agents

    Science.gov (United States)

    Rajendran, Subin; Udenigwe, Chibuike; Yada, Rickey

    2016-07-01

    The past decade has seen an increased interest in the conversion of food proteins into functional biomaterials, including their use for loading and delivery of physiologically active compounds such as nutraceuticals and pharmaceuticals. Proteins possess a competitive advantage over other platforms for the development of nanodelivery systems since they are biocompatible, amphipathic, and widely available. Proteins also have unique molecular structures and diverse functional groups that can be selectively modified to alter encapsulation and release properties. A number of physical and chemical methods have been used for preparing protein nanoformulations, each based on different underlying protein chemistry. This review focuses on the chemistry of the reorganization and/or modification of proteins into functional nanostructures for delivery, from the perspective of their preparation, functionality, stability and physiological behavior.

  19. Nanochemistry of protein-based delivery agents

    Directory of Open Access Journals (Sweden)

    Subin R.C.K. Rajendran

    2016-07-01

    Full Text Available The past decade has seen an increased interest in the conversion of food proteins into functional biomaterials, including their use for loading and delivery of physiologically active compounds such as nutraceuticals and pharmaceuticals. Proteins possess a competitive advantage over other platforms for the development of nanodelivery systems since they are biocompatible, amphipathic, and widely available. Proteins also have unique molecular structures and diverse functional groups that can be selectively modified to alter encapsulation and release properties. A number of physical and chemical methods have been used for preparing protein nanoformulations, each based on different underlying protein chemistry. This review focuses on the chemistry of the reorganization and/or modification of proteins into functional nanostructures for delivery, from the perspective of their preparation, functionality, stability and physiological behavior.

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

    Science.gov (United States)

    Cascarina, Sean M; Ross, Eric D

    2014-06-01

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

  1. From Sequence and Forces to Structure, Function and Evolution of Intrinsically Disordered Proteins

    Science.gov (United States)

    Forman-Kay, Julie D.; Mittag, Tanja

    2015-01-01

    Intrinsically disordered proteins (IDPs), which lack persistent structure, are a challenge to structural biology due to the inapplicability of standard methods for characterization of folded proteins as well as their deviation from the dominant structure/function paradigm. Their widespread presence and involvement in biological function, however, has spurred the growing acceptance of the importance of IDPs and the development of new tools for studying their structure, dynamics and function. The interplay of folded and disordered domains or regions for function and the existence of a continuum of protein states with respect to conformational energetics, motional timescales and compactness is shaping a unified understanding of structure-dynamics-disorder/function relationships. On the 20th anniversary of this journal, Structure, we provide a historical perspective on the investigation of IDPs and summarize the sequence features and physical forces that underlie their unique structural, functional and evolutionary properties. PMID:24010708

  2. Spike-Based Bayesian-Hebbian Learning of Temporal Sequences.

    Directory of Open Access Journals (Sweden)

    Philip J Tully

    2016-05-01

    Full Text Available Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN learning rule. We find that the formation of distributed memories, embodied by increased periods of firing in pools of excitatory neurons, together with asymmetrical associations between these distinct network states, can be acquired through plasticity. The model's feasibility is demonstrated using simulations of adaptive exponential integrate-and-fire model neurons (AdEx. We show that the learning and speed of sequence replay depends on a confluence of biophysically relevant parameters including stimulus duration, level of background noise, ratio of synaptic currents, and strengths of short-term depression and adaptation. Moreover, sequence elements are shown to flexibly participate multiple times in the sequence, suggesting that spiking attractor networks of this type can support an efficient combinatorial code. The model provides a principled approach towards understanding how multiple interacting plasticity mechanisms can coordinate hetero-associative learning in unison.

  3. Digital chaotic sequence generator based on coupled chaotic systems

    International Nuclear Information System (INIS)

    Shu-Bo, Liu; Jing, Sun; Jin-Shuo, Liu; Zheng-Quan, Xu

    2009-01-01

    Chaotic systems perform well as a new rich source of cryptography and pseudo-random coding. Unfortunately their digital dynamical properties would degrade due to the finite computing precision. Proposed in this paper is a modified digital chaotic sequence generator based on chaotic logistic systems with a coupling structure where one chaotic subsystem generates perturbation signals to disturb the control parameter of the other one. The numerical simulations show that the length of chaotic orbits, the output distribution of chaotic system, and the security of chaotic sequences have been greatly improved. Moreover the chaotic sequence period can be extended at least by one order of magnitude longer than that of the uncoupled logistic system and the difficulty in decrypting increases 2 128 *2 128 times indicating that the dynamical degradation of digital chaos is effectively improved. A field programmable gate array (FPGA) implementation of an algorithm is given and the corresponding experiment shows that the output speed of the generated chaotic sequences can reach 571.4 Mbps indicating that the designed generator can be applied to the real-time video image encryption. (general)

  4. Neisseria meningitidis antigen NMB0088: sequence variability, protein topology and vaccine potential.

    Science.gov (United States)

    Sardiñas, Gretel; Yero, Daniel; Climent, Yanet; Caballero, Evelin; Cobas, Karem; Niebla, Olivia

    2009-02-01

    The significance of Neisseria meningitidis serogroup B membrane proteins as vaccine candidates is continually growing. Here, we studied different aspects of antigen NMB0088, a protein that is abundant in outer-membrane vesicle preparations and is thought to be a surface protein. The gene encoding protein NMB0088 was sequenced in a panel of 34 different meningococcal strains with clinical and epidemiological relevance. After this analysis, four variants of NMB0088 were identified; the variability was confined to three specific segments, designated VR1, VR2 and VR3. Secondary structure predictions, refined with alignment analysis and homology modelling using FadL of Escherichia coli, revealed that almost all the variable regions were located in extracellular loop domains. In addition, the NMB0088 antigen was expressed in E. coli and a procedure for obtaining purified recombinant NMB0088 is described. The humoral immune response elicited in BALB/c mice was measured by ELISA and Western blotting, while the functional activity of these antibodies was determined in a serum bactericidal assay and an animal protection model. After immunization in mice, the recombinant protein was capable of inducing a protective response when it was administered inserted into liposomes. According to our results, the recombinant NMB0088 protein may represent a novel antigen for a vaccine against meningococcal disease. However, results from the variability study should be considered for designing a cross-protective formulation in future studies.

  5. Sequencing and Characterization of Novel PII Signaling Protein Gene in Microalga Haematococcus pluvialis

    Directory of Open Access Journals (Sweden)

    Ruijuan Ma

    2017-10-01

    Full Text Available The PII signaling protein is a key protein for controlling nitrogen assimilatory reactions in most organisms, but little information is reported on PII proteins of green microalga Haematococcus pluvialis. Since H. pluvialis cells can produce a large amount of astaxanthin upon nitrogen starvation, its PII protein may represent an important factor on elevated production of Haematococcus astaxanthin. This study identified and isolated the coding gene (HpGLB1 from this microalga. The full-length of HpGLB1 was 1222 bp, including 621 bp coding sequence (CDS, 103 bp 5′ untranslated region (5′ UTR, and 498 bp 3′ untranslated region (3′ UTR. The CDS could encode a protein with 206 amino acids (HpPII. Its calculated molecular weight (Mw was 22.4 kDa and the theoretical isoelectric point was 9.53. When H. pluvialis cells were exposed to nitrogen starvation, the HpGLB1 expression was increased 2.46 times in 48 h, concomitant with the raise of astaxanthin content. This study also used phylogenetic analysis to prove that HpPII was homogeneous to the PII proteins of other green microalgae. The results formed a fundamental basis for the future study on HpPII, for its potential physiological function in Haematococcus astaxanthin biosysthesis.

  6. Characterization of bud emergence 46 (BEM46) protein: Sequence, structural, phylogenetic and subcellular localization analyses

    International Nuclear Information System (INIS)

    Kumar, Abhishek; Kollath-Leiß, Krisztina; Kempken, Frank

    2013-01-01

    Highlights: •All eukaryotes have at least a single copy of a bem46 ortholog. •The catalytic triad of BEM46 is illustrated using sequence and structural analysis. •We identified indels in the conserved domain of BEM46 protein. •Localization studies of BEM46 protein were carried out using GFP-fusion tagging. -- Abstract: The bud emergence 46 (BEM46) protein from Neurospora crassa belongs to the α/β-hydrolase superfamily. Recently, we have reported that the BEM46 protein is localized in the perinuclear ER and also forms spots close by the plasma membrane. The protein appears to be required for cell type-specific polarity formation in N. crassa. Furthermore, initial studies suggested that the BEM46 amino acid sequence is conserved in eukaryotes and is considered to be one of the widespread conserved “known unknown” eukaryotic genes. This warrants for a comprehensive phylogenetic analysis of this superfamily to unravel origin and molecular evolution of these genes in different eukaryotes. Herein, we observe that all eukaryotes have at least a single copy of a bem46 ortholog. Upon scanning of these proteins in various genomes, we find that there are expansions leading into several paralogs in vertebrates. Usingcomparative genomic analyses, we identified insertion/deletions (indels) in the conserved domain of BEM46 protein, which allow to differentiate fungal classes such as ascomycetes from basidiomycetes. We also find that exonic indels are able to differentiate BEM46 homologs of different eukaryotic lineage. Furthermore, we unravel that BEM46 protein from N. crassa possess a novel endoplasmic-retention signal (PEKK) using GFP-fusion tagging experiments. We propose that three residues namely a serine 188S, a histidine 292H and an aspartic acid 262D are most critical residues, forming a catalytic triad in BEM46 protein from N. crassa. We carried out a comprehensive study on bem46 genes from a molecular evolution perspective with combination of functional

  7. Characterization of bud emergence 46 (BEM46) protein: Sequence, structural, phylogenetic and subcellular localization analyses

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Abhishek; Kollath-Leiß, Krisztina; Kempken, Frank, E-mail: fkempken@bot.uni-kiel.de

    2013-08-30

    Highlights: •All eukaryotes have at least a single copy of a bem46 ortholog. •The catalytic triad of BEM46 is illustrated using sequence and structural analysis. •We identified indels in the conserved domain of BEM46 protein. •Localization studies of BEM46 protein were carried out using GFP-fusion tagging. -- Abstract: The bud emergence 46 (BEM46) protein from Neurospora crassa belongs to the α/β-hydrolase superfamily. Recently, we have reported that the BEM46 protein is localized in the perinuclear ER and also forms spots close by the plasma membrane. The protein appears to be required for cell type-specific polarity formation in N. crassa. Furthermore, initial studies suggested that the BEM46 amino acid sequence is conserved in eukaryotes and is considered to be one of the widespread conserved “known unknown” eukaryotic genes. This warrants for a comprehensive phylogenetic analysis of this superfamily to unravel origin and molecular evolution of these genes in different eukaryotes. Herein, we observe that all eukaryotes have at least a single copy of a bem46 ortholog. Upon scanning of these proteins in various genomes, we find that there are expansions leading into several paralogs in vertebrates. Usingcomparative genomic analyses, we identified insertion/deletions (indels) in the conserved domain of BEM46 protein, which allow to differentiate fungal classes such as ascomycetes from basidiomycetes. We also find that exonic indels are able to differentiate BEM46 homologs of different eukaryotic lineage. Furthermore, we unravel that BEM46 protein from N. crassa possess a novel endoplasmic-retention signal (PEKK) using GFP-fusion tagging experiments. We propose that three residues namely a serine 188S, a histidine 292H and an aspartic acid 262D are most critical residues, forming a catalytic triad in BEM46 protein from N. crassa. We carried out a comprehensive study on bem46 genes from a molecular evolution perspective with combination of functional

  8. Sequence-based classification and identification of Fungi.

    Science.gov (United States)

    Hibbett, David; Abarenkov, Kessy; Kõljalg, Urmas; Öpik, Maarja; Chai, Benli; Cole, James; Wang, Qiong; Crous, Pedro; Robert, Vincent; Helgason, Thorunn; Herr, Joshua R; Kirk, Paul; Lueschow, Shiloh; O'Donnell, Kerry; Nilsson, R Henrik; Oono, Ryoko; Schoch, Conrad; Smyth, Christopher; Walker, Donald M; Porras-Alfaro, Andrea; Taylor, John W; Geiser, David M

    Fungal taxonomy and ecology have been revolutionized by the application of molecular methods and both have increasing connections to genomics and functional biology. However, data streams from traditional specimen- and culture-based systematics are not yet fully integrated with those from metagenomic and metatranscriptomic studies, which limits understanding of the taxonomic diversity and metabolic properties of fungal communities. This article reviews current resources, needs, and opportunities for sequence-based classification and identification (SBCI) in fungi as well as related efforts in prokaryotes. To realize the full potential of fungal SBCI it will be necessary to make advances in multiple areas. Improvements in sequencing methods, including long-read and single-cell technologies, will empower fungal molecular ecologists to look beyond ITS and current shotgun metagenomics approaches. Data quality and accessibility will be enhanced by attention to data and metadata standards and rigorous enforcement of policies for deposition of data and workflows. Taxonomic communities will need to develop best practices for molecular characterization in their focal clades, while also contributing to globally useful datasets including ITS. Changes to nomenclatural rules are needed to enable validPUBLICation of sequence-based taxon descriptions. Finally, cultural shifts are necessary to promote adoption of SBCI and to accord professional credit to individuals who contribute to community resources.

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

    Science.gov (United States)

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

    2016-11-04

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

  10. Towards understanding the first genome sequence of a crenarchaeon by genome annotation using clusters of orthologous groups of proteins (COGs).

    Science.gov (United States)

    Natale, D A; Shankavaram, U T; Galperin, M Y; Wolf, Y I; Aravind, L; Koonin, E V

    2000-01-01

    Standard archival sequence databases have not been designed as tools for genome annotation and are far from being optimal for this purpose. We used the database of Clusters of Orthologous Groups of proteins (COGs) to reannotate the genomes of two archaea, Aeropyrum pernix, the first member of the Crenarchaea to be sequenced, and Pyrococcus abyssi. A. pernix and P. abyssi proteins were assigned to COGs using the COGNITOR program; the results were verified on a case-by-case basis and augmented by additional database searches using the PSI-BLAST and TBLASTN programs. Functions were predicted for over 300 proteins from A. pernix, which could not be assigned a function using conventional methods with a conservative sequence similarity threshold, an approximately 50% increase compared to the original annotation. A. pernix shares most of the conserved core of proteins that were previously identified in the Euryarchaeota. Cluster analysis or distance matrix tree construction based on the co-occurrence of genomes in COGs showed that A. pernix forms a distinct group within the archaea, although grouping with the two species of Pyrococci, indicative of similar repertoires of conserved genes, was observed. No indication of a specific relationship between Crenarchaeota and eukaryotes was obtained in these analyses. Several proteins that are conserved in Euryarchaeota and most bacteria are unexpectedly missing in A. pernix, including the entire set of de novo purine biosynthesis enzymes, the GTPase FtsZ (a key component of the bacterial and euryarchaeal cell-division machinery), and the tRNA-specific pseudouridine synthase, previously considered universal. A. pernix is represented in 48 COGs that do not contain any euryarchaeal members. Many of these proteins are TCA cycle and electron transport chain enzymes, reflecting the aerobic lifestyle of A. pernix. Special-purpose databases organized on the basis of phylogenetic analysis and carefully curated with respect to known and

  11. Protein-Based Drug-Delivery Materials

    OpenAIRE

    Jao, Dave; Xue, Ye; Medina, Jethro; Hu, Xiao

    2017-01-01

    There is a pressing need for long-term, controlled drug release for sustained treatment of chronic or persistent medical conditions and diseases. Guided drug delivery is difficult because therapeutic compounds need to survive numerous transport barriers and binding targets throughout the body. Nanoscale protein-based polymers are increasingly used for drug and vaccine delivery to cross these biological barriers and through blood circulation to their molecular site of action. Protein-based pol...

  12. CGKB: an annotation knowledge base for cowpea (Vigna unguiculata L. methylation filtered genomic genespace sequences

    Directory of Open Access Journals (Sweden)

    Spraggins Thomas A

    2007-04-01

    Full Text Available Abstract Background Cowpea [Vigna unguiculata (L. Walp.] is one of the most important food and forage legumes in the semi-arid tropics because of its ability to tolerate drought and grow on poor soils. It is cultivated mostly by poor farmers in developing countries, with 80% of production taking place in the dry savannah of tropical West and Central Africa. Cowpea is largely an underexploited crop with relatively little genomic information available for use in applied plant breeding. The goal of the Cowpea Genomics Initiative (CGI, funded by the Kirkhouse Trust, a UK-based charitable organization, is to leverage modern molecular genetic tools for gene discovery and cowpea improvement. One aspect of the initiative is the sequencing of the gene-rich region of the cowpea genome (termed the genespace recovered using methylation filtration technology and providing annotation and analysis of the sequence data. Description CGKB, Cowpea Genespace/Genomics Knowledge Base, is an annotation knowledge base developed under the CGI. The database is based on information derived from 298,848 cowpea genespace sequences (GSS isolated by methylation filtering of genomic DNA. The CGKB consists of three knowledge bases: GSS annotation and comparative genomics knowledge base, GSS enzyme and metabolic pathway knowledge base, and GSS simple sequence repeats (SSRs knowledge base for molecular marker discovery. A homology-based approach was applied for annotations of the GSS, mainly using BLASTX against four public FASTA formatted protein databases (NCBI GenBank Proteins, UniProtKB-Swiss-Prot, UniprotKB-PIR (Protein Information Resource, and UniProtKB-TrEMBL. Comparative genome analysis was done by BLASTX searches of the cowpea GSS against four plant proteomes from Arabidopsis thaliana, Oryza sativa, Medicago truncatula, and Populus trichocarpa. The possible exons and introns on each cowpea GSS were predicted using the HMM-based Genscan gene predication program and the

  13. Interaction of the E. coli DNA G:T-mismatch endonuclease (vsr protein) with oligonucleotides containing its target sequence.

    Science.gov (United States)

    Turner, D P; Connolly, B A

    2000-12-15

    The Escherichia coli vsr endonuclease recognises G:T base-pair mismatches in double-stranded DNA and initiates a repair pathway by hydrolysing the phosphate group 5' to the incorrectly paired T. The enzyme shows a preference for G:T mismatches within a particular sequence context, derived from the recognition site of the E. coli dcm DNA-methyltransferase (CC[A/T]GG). Thus, the preferred substrate for the vsr protein is (CT[A/T]GG), where the underlined T is opposed by a dG base. This paper provides quantitative data for the interaction of the vsr protein with a number of oligonucleotides containing G:T mismatches. Evaluation of specificity constant (k(st)/K(D); k(st)=rate constant for single turnover, K(D)=equilibrium dissociation constant) confirms vsr's preference for a G:T mismatch within a hemi-methylated dcm sequence, i.e. the best substrate is a duplex (both strands written in the 5'-3' orientation) composed of CT[A/T]GG and C(5Me)C[T/A]GG. Conversion of the mispaired T (underlined) to dU or the d(5Me)C to dC gave poorer substrates. No interaction was observed with oligonucleotides that lacked a G:T mismatch or did not possess a dcm sequence. An analysis of the fraction of active protein, by "reverse-titration" (i.e. adding increasing amounts of DNA to a fixed amount of protein followed by gel-mobility shift analysis) showed that less than 1% of the vsr endonuclease was able to bind to the substrate. This was confirmed using "competitive titrations" (where competitor oligonucleotides are used to displace a (32)P-labelled nucleic acid from the vsr protein) and burst kinetic analysis. This result is discussed in the light of previous in vitro and in vivo data which indicate that the MutL protein may be needed for full vsr activity. Copyright 2000 Academic Press.

  14. ZifBASE: a database of zinc finger proteins and associated resources

    Directory of Open Access Journals (Sweden)

    Punetha Ankita

    2009-09-01

    Full Text Available Abstract Background 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. Description 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

  15. Blind Test of Physics-Based Prediction of Protein Structures

    Science.gov (United States)

    Shell, M. Scott; Ozkan, S. Banu; Voelz, Vincent; Wu, Guohong Albert; Dill, Ken A.

    2009-01-01

    We report here a multiprotein blind test of a computer method to predict native protein structures based solely on an all-atom physics-based force field. We use the AMBER 96 potential function with an implicit (GB/SA) model of solvation, combined with replica-exchange molecular-dynamics simulations. Coarse conformational sampling is performed using the zipping and assembly method (ZAM), an approach that is designed to mimic the putative physical routes of protein folding. ZAM was applied to the folding of six proteins, from 76 to 112 monomers in length, in CASP7, a community-wide blind test of protein structure prediction. Because these predictions have about the same level of accuracy as typical bioinformatics methods, and do not utilize information from databases of known native structures, this work opens up the possibility of predicting the structures of membrane proteins, synthetic peptides, or other foldable polymers, for which there is little prior knowledge of native structures. This approach may also be useful for predicting physical protein folding routes, non-native conformations, and other physical properties from amino acid sequences. PMID:19186130

  16. An effective approach for annotation of protein families with low sequence similarity and conserved motifs: identifying GDSL hydrolases across the plant kingdom.

    Science.gov (United States)

    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

  17. Sequence-specific inhibition of Dicer measured with a force-based microarray for RNA ligands.

    Science.gov (United States)

    Limmer, Katja; Aschenbrenner, Daniela; Gaub, Hermann E

    2013-04-01

    Malfunction of protein translation causes many severe diseases, and suitable correction strategies may become the basis of effective therapies. One major regulatory element of protein translation is the nuclease Dicer that cuts double-stranded RNA independently of the sequence into pieces of 19-22 base pairs starting the RNA interference pathway and activating miRNAs. Inhibiting Dicer is not desirable owing to its multifunctional influence on the cell's gene regulation. Blocking specific RNA sequences by small-molecule binding, however, is a promising approach to affect the cell's condition in a controlled manner. A label-free assay for the screening of site-specific interference of small molecules with Dicer activity is thus needed. We used the Molecular Force Assay (MFA), recently developed in our lab, to measure the activity of Dicer. As a model system, we used an RNA sequence that forms an aptamer-binding site for paromomycin, a 615-dalton aminoglycoside. We show that Dicer activity is modulated as a function of concentration and incubation time: the addition of paromomycin leads to a decrease of Dicer activity according to the amount of ligand. The measured dissociation constant of paromomycin to its aptamer was found to agree well with literature values. The parallel format of the MFA allows a large-scale search and analysis for ligands for any RNA sequence.

  18. Resolution of a protein sequence ambiguity by X-ray crystallographic and mass spectrometric methods

    International Nuclear Information System (INIS)

    Keefe, L.J.; Lattman, E.E.; Wolkow, C.; Woods, A.; Chevrier, M.; Cotter, R.J.

    1992-01-01

    Ambiguities in amino acid sequences are a potential problem in X-ray crystallographic studies of proteins. Amino acid side chains often cannot be reliably identified from the electron density. Many protein crystal structures that are now being solved are simple variants of a known wild-type structure. Thus, cloning artifacts or other untoward events can readily lead to cases in which the proposed sequence is not correct. An example is presented showing that mass spectrometry provides an excellent tool for analyzing suspected errors. The X-ray crystal structure of an insertion mutant of Staphylococcal nuclease has been solved to 1.67 A resolution and refined to a crystallographic R value of 0.170. A single residue has been inserted in the C-terminal α helix. The inserted amino acid was believed to be an alanine residue, but the final electron density maps strongly indicated that a glycine had been inserted instead. To confirm the observations from the X-ray data, matrix-assisted laser desorption mass spectrometry was employed to verify the glycine insertion. This mass spectrometric technique has sufficient mass accuracy to detect the methyl group that distinguishes glycine from alanine and can be extended to the more common situation in which crystallographic measurements suggest a problem with the sequence, but cannot pinpoint its location or nature. (orig.)

  19. Resolution of a protein sequence ambiguity by X-ray crystallographic and mass spectrometric methods

    Energy Technology Data Exchange (ETDEWEB)

    Keefe, L.J.; Lattman, E.E. (Dept. of Biophysics and Biophysical Chemistry, Johns Hopkins Univ. School of Medicine, Baltimore, MD (United States)); Wolkow, C.; Woods, A.; Chevrier, M.; Cotter, R.J. (Middle Atlantic Mass Spectrometry Lab., Johns Hopkins Univ. School of Medicine, Baltimore, MD (United States))

    1992-04-01

    Ambiguities in amino acid sequences are a potential problem in X-ray crystallographic studies of proteins. Amino acid side chains often cannot be reliably identified from the electron density. Many protein crystal structures that are now being solved are simple variants of a known wild-type structure. Thus, cloning artifacts or other untoward events can readily lead to cases in which the proposed sequence is not correct. An example is presented showing that mass spectrometry provides an excellent tool for analyzing suspected errors. The X-ray crystal structure of an insertion mutant of Staphylococcal nuclease has been solved to 1.67 A resolution and refined to a crystallographic R value of 0.170. A single residue has been inserted in the C-terminal {alpha} helix. The inserted amino acid was believed to be an alanine residue, but the final electron density maps strongly indicated that a glycine had been inserted instead. To confirm the observations from the X-ray data, matrix-assisted laser desorption mass spectrometry was employed to verify the glycine insertion. This mass spectrometric technique has sufficient mass accuracy to detect the methyl group that distinguishes glycine from alanine and can be extended to the more common situation in which crystallographic measurements suggest a problem with the sequence, but cannot pinpoint its location or nature. (orig.).

  20. Prediction of peptide drift time in ion mobility mass spectrometry from sequence-based features

    KAUST Repository

    Wang, Bing; Zhang, Jun; Chen, Peng; Ji, Zhiwei; Deng, Shuping; Li, Chi

    2013-01-01

    Background: Ion mobility-mass spectrometry (IMMS), an analytical technique which combines the features of ion mobility spectrometry (IMS) and mass spectrometry (MS), can rapidly separates ions on a millisecond time-scale. IMMS becomes a powerful tool to analyzing complex mixtures, especially for the analysis of peptides in proteomics. The high-throughput nature of this technique provides a challenge for the identification of peptides in complex biological samples. As an important parameter, peptide drift time can be used for enhancing downstream data analysis in IMMS-based proteomics.Results: In this paper, a model is presented based on least square support vectors regression (LS-SVR) method to predict peptide ion drift time in IMMS from the sequence-based features of peptide. Four descriptors were extracted from peptide sequence to represent peptide ions by a 34-component vector. The parameters of LS-SVR were selected by a grid searching strategy, and a 10-fold cross-validation approach was employed for the model training and testing. Our proposed method was tested on three datasets with different charge states. The high prediction performance achieve demonstrate the effectiveness and efficiency of the prediction model.Conclusions: Our proposed LS-SVR model can predict peptide drift time from sequence information in relative high prediction accuracy by a test on a dataset of 595 peptides. This work can enhance the confidence of protein identification by combining with current protein searching techniques. 2013 Wang et al.; licensee BioMed Central Ltd.

  1. Prediction of peptide drift time in ion mobility mass spectrometry from sequence-based features

    KAUST Repository

    Wang, Bing

    2013-05-09

    Background: Ion mobility-mass spectrometry (IMMS), an analytical technique which combines the features of ion mobility spectrometry (IMS) and mass spectrometry (MS), can rapidly separates ions on a millisecond time-scale. IMMS becomes a powerful tool to analyzing complex mixtures, especially for the analysis of peptides in proteomics. The high-throughput nature of this technique provides a challenge for the identification of peptides in complex biological samples. As an important parameter, peptide drift time can be used for enhancing downstream data analysis in IMMS-based proteomics.Results: In this paper, a model is presented based on least square support vectors regression (LS-SVR) method to predict peptide ion drift time in IMMS from the sequence-based features of peptide. Four descriptors were extracted from peptide sequence to represent peptide ions by a 34-component vector. The parameters of LS-SVR were selected by a grid searching strategy, and a 10-fold cross-validation approach was employed for the model training and testing. Our proposed method was tested on three datasets with different charge states. The high prediction performance achieve demonstrate the effectiveness and efficiency of the prediction model.Conclusions: Our proposed LS-SVR model can predict peptide drift time from sequence information in relative high prediction accuracy by a test on a dataset of 595 peptides. This work can enhance the confidence of protein identification by combining with current protein searching techniques. 2013 Wang et al.; licensee BioMed Central Ltd.

  2. Zucchini yellow mosaic virus: biological properties, detection procedures and comparison of coat protein gene sequences.

    Science.gov (United States)

    Coutts, B A; Kehoe, M A; Webster, C G; Wylie, S J; Jones, R A C

    2011-12-01

    Between 2006 and 2010, 5324 samples from at least 34 weed, two cultivated legume and 11 native species were collected from three cucurbit-growing areas in tropical or subtropical Western Australia. Two new alternative hosts of zucchini yellow mosaic virus (ZYMV) were identified, the Australian native cucurbit Cucumis maderaspatanus, and the naturalised legume species Rhyncosia minima. Low-level (0.7%) seed transmission of ZYMV was found in seedlings grown from seed collected from zucchini (Cucurbita pepo) fruit infected with isolate Cvn-1. Seed transmission was absent in >9500 pumpkin (C. maxima and C. moschata) seedlings from fruit infected with isolate Knx-1. Leaf samples from symptomatic cucurbit plants collected from fields in five cucurbit-growing areas in four Australian states were tested for the presence of ZYMV. When 42 complete coat protein (CP) nucleotide (nt) sequences from the new ZYMV isolates obtained were compared to those of 101 complete CP nt sequences from five other continents, phylogenetic analysis of the 143 ZYMV sequences revealed three distinct groups (A, B and C), with four subgroups in A (I-IV) and two in B (I-II). The new Australian sequences grouped according to collection location, fitting within A-I, A-II and B-II. The 16 new sequences from one isolated location in tropical northern Western Australia all grouped into subgroup B-II, which contained no other isolates. In contrast, the three sequences from the Northern Territory fitted into A-II with 94.6-99.0% nt identities with isolates from the United States, Iran, China and Japan. The 23 new sequences from the central west coast and two east coast locations all fitted into A-I, with 95.9-98.9% nt identities to sequences from Europe and Japan. These findings suggest that (i) there have been at least three separate ZYMV introductions into Australia and (ii) there are few changes to local isolate CP sequences following their establishment in remote growing areas. Isolates from A-I and B

  3. Protein-Level Integration Strategy of Multiengine MS Spectra Search Results for Higher Confidence and Sequence Coverage.

    Science.gov (United States)

    Zhao, Panpan; Zhong, Jiayong; Liu, Wanting; Zhao, Jing; Zhang, Gong

    2017-12-01

    Multiple search engines based on various models have been developed to search MS/MS spectra against a reference database, providing different results for the same data set. How to integrate these results efficiently with minimal compromise on false discoveries is an open question due to the lack of an independent, reliable, and highly sensitive standard. We took the advantage of the translating mRNA sequencing (RNC-seq) result as a standard to evaluate the integration strategies of the protein identifications from various search engines. We used seven mainstream search engines (Andromeda, Mascot, OMSSA, X!Tandem, pFind, InsPecT, and ProVerB) to search the same label-free MS data sets of human cell lines Hep3B, MHCCLM3, and MHCC97H from the Chinese C-HPP Consortium for Chromosomes 1, 8, and 20. As expected, the union of seven engines resulted in a boosted false identification, whereas the intersection of seven engines remarkably decreased the identification power. We found that identifications of at least two out of seven engines resulted in maximizing the protein identification power while minimizing the ratio of suspicious/translation-supported identifications (STR), as monitored by our STR index, based on RNC-Seq. Furthermore, this strategy also significantly improves the peptides coverage of the protein amino acid sequence. In summary, we demonstrated a simple strategy to significantly improve the performance for shotgun mass spectrometry by protein-level integrating multiple search engines, maximizing the utilization of the current MS spectra without additional experimental work.

  4. Context based computational analysis and characterization of ARS consensus sequences (ACS of Saccharomyces cerevisiae genome

    Directory of Open Access Journals (Sweden)

    Vinod Kumar Singh

    2016-09-01

    Full Text Available Genome-wide experimental studies in Saccharomyces cerevisiae reveal that autonomous replicating sequence (ARS requires an essential consensus sequence (ACS for replication activity. Computational studies identified thousands of ACS like patterns in the genome. However, only a few hundreds of these sites act as replicating sites and the rest are considered as dormant or evolving sites. In a bid to understand the sequence makeup of replication sites, a content and context-based analysis was performed on a set of replicating ACS sequences that binds to origin-recognition complex (ORC denoted as ORC-ACS and non-replicating ACS sequences (nrACS, that are not bound by ORC. In this study, DNA properties such as base composition, correlation, sequence dependent thermodynamic and DNA structural profiles, and their positions have been considered for characterizing ORC-ACS and nrACS. Analysis reveals that ORC-ACS depict marked differences in nucleotide composition and context features in its vicinity compared to nrACS. Interestingly, an A-rich motif was also discovered in ORC-ACS sequences within its nucleosome-free region. Profound changes in the conformational features, such as DNA helical twist, inclination angle and stacking energy between ORC-ACS and nrACS were observed. Distribution of ACS motifs in the non-coding segments points to the locations of ORC-ACS which are found far away from the adjacent gene start position compared to nrACS thereby enabling an accessible environment for ORC-proteins. Our attempt is novel in considering the contextual view of ACS and its flanking region along with nucleosome positioning in the S. cerevisiae genome and may be useful for any computational prediction scheme.

  5. Amino acid sequences mediating vascular cell adhesion molecule 1 binding to integrin alpha 4: homologous DSP sequence found for JC polyoma VP1 coat protein

    Directory of Open Access Journals (Sweden)

    Michael Andrew Meyer

    2013-07-01

    Full Text Available The JC polyoma viral coat protein VP1 was analyzed for amino acid sequences homologies to the IDSP sequence which mediates binding of VLA-4 (integrin alpha 4 to vascular cell adhesion molecule 1. Although the full sequence was not found, a DSP sequence was located near the critical arginine residue linked to infectivity of the virus and binding to sialic acid containing molecules such as integrins (3. For the JC polyoma virus, a DSP sequence was found at residues 70, 71 and 72 with homology also noted for the mouse polyoma virus and SV40 virus. Three dimensional modeling of the VP1 molecule suggests that the DSP loop has an accessible site for interaction from the external side of the assembled viral capsid pentamer.

  6. Discovering approximate-associated sequence patterns for protein-DNA interactions

    KAUST Repository

    Chan, Tak Ming

    2010-12-30

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

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

    Science.gov (United States)

    Doxastakis, Manolis; Prakash, Anupam; Janosi, Lorant

    2011-03-01

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

  8. A maize spermine synthase 1 PEST sequence fused to the GUS reporter protein facilitates proteolytic degradation.

    Science.gov (United States)

    Maruri-López, Israel; Rodríguez-Kessler, Margarita; Rodríguez-Hernández, Aída Araceli; Becerra-Flora, Alicia; Olivares-Grajales, Juan Elías; Jiménez-Bremont, Juan Francisco

    2014-05-01

    Polyamines are low molecular weight aliphatic compounds involved in various biochemical, cellular and physiological processes in all organisms. In plants, genes involved in polyamine biosynthesis and catabolism are regulated at transcriptional, translational, and posttranslational level. In this research, we focused on the characterization of a PEST sequence (rich in proline, glutamic acid, serine, and threonine) of the maize spermine synthase 1 (ZmSPMS1). To this aim, 123 bp encoding 40 amino acids of the C-terminal region of the ZmSPMS1 enzyme containing the PEST sequence were fused to the GUS reporter gene. This fusion was evaluated in Arabidopsis thaliana transgenic lines and onion monolayers transient expression system. The ZmSPMS1 PEST sequence leads to specific degradation of the GUS reporter protein. It is suggested that the 26S proteasome may be involved in GUS::PEST fusion degradation in both onion and Arabidopsis. The PEST sequences appear to be present in plant spermine synthases, mainly in monocots. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

  9. Structural analysis of a repetitive protein sequence motif in strepsirrhine primate amelogenin.

    Directory of Open Access Journals (Sweden)

    Rodrigo S Lacruz

    2011-03-01

    Full Text Available Strepsirrhines are members of a primate suborder that has a distinctive set of features associated with the development of the dentition. Amelogenin (AMEL, the better known of the enamel matrix proteins, forms 90% of the secreted organic matrix during amelogenesis. Although AMEL has been sequenced in numerous mammalian lineages, the only reported strepsirrhine AMEL sequences are those of the ring-tailed lemur and galago, which contain a set of additional proline-rich tandem repeats absent in all other primates species analyzed to date, but present in some non-primate mammals. Here, we first determined that these repeats are present in AMEL from three additional lemur species and thus are likely to be widespread throughout this group. To evaluate the functional relevance of these repeats in strepsirrhines, we engineered a mutated murine amelogenin sequence containing a similar proline-rich sequence to that of Lemur catta. In the monomeric form, the MQP insertions had no influence on the secondary structure or refolding properties, whereas in the assembled form, the insertions increased the hydrodynamic radii. We speculate that increased AMEL nanosphere size may influence enamel formation in strepsirrhine primates.

  10. Prediction of the aggregation propensity of proteins from the primary sequence: aggregation properties of proteomes.

    Science.gov (United States)

    Castillo, Virginia; Graña-Montes, Ricardo; Sabate, Raimon; Ventura, Salvador

    2011-06-01

    In the cell, protein folding into stable globular conformations is in competition with aggregation into non-functional and usually toxic structures, since the biophysical properties that promote folding also tend to favor intermolecular contacts, leading to the formation of β-sheet-enriched insoluble assemblies. The formation of protein deposits is linked to at least 20 different human disorders, ranging from dementia to diabetes. Furthermore, protein deposition inside cells represents a major obstacle for the biotechnological production of polypeptides. Importantly, the aggregation behavior of polypeptides appears to be strongly influenced by the intrinsic properties encoded in their sequences and specifically by the presence of selective short regions with high aggregation propensity. This allows computational methods to be used to analyze the aggregation properties of proteins without the previous requirement for structural information. Applications range from the identification of individual amyloidogenic regions in disease-linked polypeptides to the analysis of the aggregation properties of complete proteomes. Herein, we review these theoretical approaches and illustrate how they have become important and useful tools in understanding the molecular mechanisms underlying protein aggregation. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Structure-based inference of molecular functions of proteins of unknown function from Berkeley Structural Genomics Center

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Sung-Hou; Shin, Dong Hae; Hou, Jingtong; Chandonia, John-Marc; Das, Debanu; Choi, In-Geol; Kim, Rosalind; Kim, Sung-Hou

    2007-09-02

    Advances in sequence genomics have resulted in an accumulation of a huge number of protein sequences derived from genome sequences. However, the functions of a large portion of them cannot be inferred based on the current methods of sequence homology detection to proteins of known functions. Three-dimensional structure can have an important impact in providing inference of molecular function (physical and chemical function) of a protein of unknown function. Structural genomics centers worldwide have been determining many 3-D structures of the proteins of unknown functions, and possible molecular functions of them have been inferred based on their structures. Combined with bioinformatics and enzymatic assay tools, the successful acceleration of the process of protein structure determination through high throughput pipelines enables the rapid functional annotation of a large fraction of hypothetical proteins. We present a brief summary of the process we used at the Berkeley Structural Genomics Center to infer molecular functions of proteins of unknown function.

  12. Protein-Based Drug-Delivery Materials

    Directory of Open Access Journals (Sweden)

    Dave Jao

    2017-05-01

    Full Text Available There is a pressing need for long-term, controlled drug release for sustained treatment of chronic or persistent medical conditions and diseases. Guided drug delivery is difficult because therapeutic compounds need to survive numerous transport barriers and binding targets throughout the body. Nanoscale protein-based polymers are increasingly used for drug and vaccine delivery to cross these biological barriers and through blood cir