Locomotif: from graphical motif description to RNA motif search

MOTIVATION AND RESULTS: Motivated by the recent rise of interest in small regulatory RNAs, we present Locomotif--a new approach for locating RNA motifs that goes beyond the previous ones in three ways: (1) motif search is based on efficient dynamic programming algorithms, incorporating the established thermodynamic model of RNA secondary structure formation. (2) motifs are described graphically, using a Java-based editor, and search algorithms are derived from the graphics in a fully automatic way. The editor allows us to draw secondary structures, annotated with size and sequence information. They closely resemble the established, but informal way in which RNA motifs are communicated in the literature. Thus, the learning effort for Locomotif users is minimal. (3) Locomotif employs a client-server approach. Motifs are designed by the user locally. Search programs are generated and compiled on a bioinformatics server. They are made available both for execution on the server, and for download as C source code plus an appropriate makefile. AVAILABILITY: Locomotif is available at http://bibiserv.techfak.uni-bielefeld.de/locomotif.     

Protein structural similarity search by Ramachandran codes

Background  

Protein structural data has increased exponentially, such that fast and accurate tools are necessary to access structure similarity search. To improve the search speed, several methods have been designed to reduce three-dimensional protein structures to one-dimensional text strings that are then analyzed by traditional sequence alignment methods; however, the accuracy is usually sacrificed and the speed is still unable to match sequence similarity search tools. Here, we aimed to improve the linear encoding methodology and develop efficient search tools that can rapidly retrieve structural homologs from large protein databases.     

SMOTIF: efficient structured pattern and profile motif search

Background  

A structured motif allows variable length gaps between several components, where each component is a simple motif, which allows either no gaps or only fixed length gaps. The motif can either be represented as a pattern or a profile (also called positional weight matrix). We propose an efficient algorithm, called SMOTIF, to solve the structured motif search problem, i.e., given one or more sequences and a structured motif, SMOTIF searches the sequences for all occurrences of the motif. Potential applications include searching for long terminal repeat (LTR) retrotransposons and composite regulatory binding sites in DNA sequences.     

mmsearch: a motif arrangement language and search program.

This paper presents a language for describing arrangements of motifs in biological sequences, and a program that uses the language to find the arrangements in motif match databases. The program does not by itself search for the constituent motifs, and is thus independent of how they are detected, which allows it to use motif match data of various origins. AVAILABILITY: The program can be tested online at http://hits.isb-sib.ch and the distribution is available from ftp://ftp.isrec.isb-sib.ch/pub/software/unix/mmsearch-1.0.tar.gz CONTACT: Thomas.Junier@isrec.unil.ch SUPPLEMENTARY INFORMATION: The full documentation about mmsearchis available from http://hits.isb-sib.ch/~tjunier/mmsearch/doc.     

Relation between sequence similarity and structural similarity in proteins. Role of important properties of amino acids

In a previous paper we obtained ten (orthogonal) factors, linear combinations of which can express the properties of the 20 naturally occurring amino acids. In this paper, we assume that the most important properties (linear combinations of these ten factors) that determine the three-dimensional structure of a protein are conserved properties, i.e., are those that have been conserved during evolution. Two definitions of a conserved property are presented: (1) a conserved property for an average protein is defined as that linear combination of the ten factors that optimally expresses the similarity of one amino acid to another (hence, little change during evolution), as given by the relatedness odds matrix of Dayhoff et al.; (2) a conserved property for each position in the amino acid sequence (locus) of a specific family of homologous proteins (the cytochromec family or the globin family) is defined as that linear combination of the ten factors that is common among a set of amino acids at a given locus when the sequences are properly aligned. When the specificity at each locus is averaged over all loci, the same features are observed for three expressions of these two definitions, namely the conserved property for an average protein, the average conserved property for the cytochromec family, and the average conserved property for the globin family; we find that bulk and hydrophobicity (information about packing and long-range interactions) are more important than other properties, such as the preference for adopting a specific backbone structure (information about short-range interactions). We also demonstrate that the sequence profile of a conserved property, defined for each locus of a protein family (definition 2), corresponds uniquely to the three-dimensional structure, while the conserved property for an average protein (definition 1) is not useful for the prediction of protein structure. The amino acid sequences of numerous proteins are searched to find those that are similar, in terms of the conserved properties (definition 2), to sequences of the same size from one of the homologous families (cytochromec and globin, respectively) for whose loci the conserved properties were defined. Many similar sequences are found, the number of similarities decreasing with increasing size of the segment. However, the segments must be rather long (15 residues) before the comparisons become meaningful. As an example, one sufficiently large sequence (20 residues) from a protein of known structure (apo-liver alcohol dehydrogenase that is not a member of either family) is found to be similar in the conserved properties to a particular sequence of a member of the family of human hemoglobin chains, and the two sequences have similar structures. This means that, since conserved properties are expected to be structure determinants, we can use the conserved properties to predict an initial protein structure for subsequent energy minimization for a protein for which the conserved properties are similar to those of a family of proteins with a sufficiently large number of homologous amino acid sequences; such a large number of homologous sequences is required to define a conserved property for each locus of the homologous protein family.     

Kappa-alpha plot derived structural alphabet and BLOSUM-like substitution matrix for rapid search of protein structure database

We present a novel protein structure database search tool, 3D-BLAST, that is useful for analyzing novel structures and can return a ranked list of alignments. This tool has the features of BLAST (for example, robust statistical basis, and effective and reliable search capabilities) and employs a kappa-alpha (κ, α) plot derived structural alphabet and a new substitution matrix. 3D-BLAST searches more than 12,000 protein structures in 1.2 s and yields good results in zones with low sequence similarity.     

Prediction of MHC binding peptide using Gibbs motif sampler,weight matrix and artificial neural network

The identification of MHC restricted epitopes is an important goal in peptide based vaccine and diagnostic development. As wet lab experiments for identification of MHC binding peptide are expensive and time consuming, in silico tools have been developed as fast alternatives, however with low performance. In the present study, we used IEDB training and blind validation datasets for the prediction of peptide binding to fourteen human MHC class I and II molecules using Gibbs motif sampler, weight matrix and artificial neural network methods. As compare to MHC class I predictor based on sequence weighting (Aroc=0.95 and CC=0.56) and artificial neural network (Aroc=0.73 and CC=0.25), MHC class II predictor based on Gibbs sampler did not perform well (Aroc=0.62 and CC=0.19). The predictive accuracy of Gibbs motif sampler in identifying the 9-mer cores of a binding peptide to DRB1 alleles are also limited (40¢), however above the random prediction (14¢). Therefore, the size of dataset (training and validation) and the correct identification of the binding core are the two main factors limiting the performance of MHC class-II binding peptide prediction. Overall, these data suggest that there is substantial room to improve the quality of the core predictions using novel approaches that capture distinct features of MHC-peptide interactions than the current approaches.     

PSI: indexing protein structures for fast similarity search

MOTIVATION: We consider the problem of finding similarities in protein structure databases. Current techniques sequentially compare the given query protein to all of the proteins in the database to find similarities. Therefore, the cost of similarity queries increases linearly as the volume of the protein databases increase. As the sizes of experimentally determined and theoretically estimated protein structure databases grow, there is a need for scalable searching techniques. RESULTS: Our techniques extract feature vectors on triplets of SSEs (Secondary Structure Elements). Later, these feature vectors are indexed using a multidimensional index structure. For a given query protein, this index structure is used to quickly prune away unpromising proteins in the database. The remaining proteins are then aligned using a popular alignment tool such as VAST. We also develop a novel statistical model to estimate the goodness of a match using the SSEs. Experimental results show that our techniques improve the pruning time of VAST 3 to 3.5 times while maintaining similar sensitivity.     

Text similarity: an alternative way to search MEDLINE

MOTIVATION: The most widely used literature search techniques, such as those offered by NCBI's PubMed system, require significant effort on the part of the searcher, and inexperienced searchers do not use these systems as effectively as experienced users. Improved literature search engines can save researchers time and effort by making it easier to locate the most important and relevant literature. RESULTS: We have created and optimized a new, hybrid search system for Medline that takes natural text as input and then delivers results with high precision and recall. The combination of a fast, low-sensitivity weighted keyword-based first pass algorithm to cast a wide net to gather an initial set of literature, followed by a unique sentence-alignment based similarity algorithm to rank order those results was developed that is sensitive, fast and easy to use. Several text similarity search algorithms, both standard and novel, were implemented and tested in order to determine which obtained the best results in information retrieval exercises. AVAILABILITY: Literature searching algorithms are implemented in a system called eTBLAST, freely accessible over the web at http://invention.swmed.edu. A variety of other derivative systems and visualization tools provides the user with an enhanced experience and additional capabilities. CONTACT: Harold.Garner@UTSouthwestern.edu.     

Efficient similarity search in protein structure databases by k-clique hashing

MOTIVATION: Graph-based clique-detection techniques are widely used for the recognition of common substructures in proteins. They permit the detection of resemblances that are independent of sequence or fold homologies and are also able to handle conformational flexibility. Their high computational complexity is often a limiting factor and prevents a detailed and fine-grained modeling of the protein structure. RESULTS: We present an efficient two-step method that significantly speeds up the detection of common substructures, especially when used to screen larger databases. It combines the advantages from both clique-detection and geometric hashing. The method is applied to an established approach for the comparison of protein binding-pockets, and some empirical results are presented. AVAILABILITY: Upon request from the authors.     

Identifying coding exons by similarity search: alu-derived and other potentially misleading protein sequences.

The search for significant local similarities with known protein sequences is a powerful method for interpreting anonymous cDNA sequences or locating coding exons within genomic DNA sequences at a stage where the average contig size is still very small. The BLASTx program, implemented on the National Center for Biotechnology Information server, allows a sensitive search of all putative translations of a nucleotide query sequence against all known proteins in a matter of seconds. From an analysis of the current databases, I report a set of protein sequences exhibiting high local similarity to Alu repeat or vector sequences. These entries can lead to misleading interpretations of similarity searches. During the course of this study, the protease of a human spumaretrovirus was found to have integrated the 3' end half of the U2 snRNA.     

Identifying coding exons by similarity search: Alu-derived and other potentially misleading protein sequences

The search for significant local similarities with known protein sequences is a powerful method for interpreting anonymous cDNA sequences or locating coding exons within genomic DNA sequences at a stage where the average contig size is still very small. The BLASTx program, implemented on the National Center for Biotechnology Information server, allows a sensitive search of all putative translations of a nucleotide query sequence against all known proteins in a matter of seconds. From an analysis of the current databases, I report a set of protein sequences exhibiting high local similarity to Alu repeat or vector sequences. These entries can lead to misleading interpretations of similarity searches. During the course of this study, the protease of a human spumaretrovirus was found to have integrated the 3′ end half of the U2 snRNA.     

Relation between birth weight and blood pressure: longitudinal study of infants and children.

OBJECTIVE--To study the relation between birth weight and systolic blood pressure in infancy and early childhood. DESIGN--Longitudinal study of infants from birth to 4 years of age. SETTING--A middle class community in the Netherlands. PARTICIPANTS--476 Dutch infants born in 1980 to healthy women after uncomplicated pregnancies. MAIN OUTCOME MEASURES--Systolic blood pressure and body weight measured at birth and at 3 months and 4 years of age; the relation between systolic blood pressure and birth weight as estimated by multiple regression models that include current weight and previous blood pressure and control for gestational age, length at birth, and sex. RESULTS--Complete data were available on 392 infants. At 4 years of age the relation between blood pressure and birth weight appeared to be U shaped; low and high birthweight infants had raised blood pressure. Current weight and previous blood pressure were also positively associated with blood pressure at that age. Low birthweight infants (birth weight < 3100 g) had a greater gain in blood pressure and weight in early infancy. High birthweight infants (birth weight > or = 3700 g) had high blood pressure at birth, and weight and blood pressure tended to remain high thereafter. CONCLUSIONS--Even among normal infants there seem to be subgroups defined by birth weight in which blood pressure is regulated differently. Future investigations are needed to examine the physiological basis of these differences. Studies of correlates of adult disease related to birth weight should investigate mechanisms related to increased risk separately in infants of low and high birth weight.     

Codon substitution models based on residue similarity and their applications

Codon models are now widely used to draw evolutionary inferences from alignments of homologous sequence data. Incorporating physicochemical properties of amino acids into codon models, two novel codon substitution models describing the evolution of protein-coding DNA sequences are presented based on the similarity scores of amino acids. To describe substitutions between codons a continue-time Markov process is used. Transition/transversion rate bias and nonsynonymous codon usage bias are allowed in the models. In our implementation, the parameters are estimated by maximum-likelihood (ML) method as in previous studies. Furthermore, instantaneous mutations involving more than one nucleotide position of a codon are considered in the second model. Then the two suggested models are applied to five real data sets. The analytic results indicate that the new codon models considering physicochemical properties of amino acids can provide a better fit to the data comparing with existing codon models, and then produce more reliable estimates of certain biologically important measures than existing methods.     

PHAT: a transmembrane-specific substitution matrix. Predicted hydrophobic and transmembrane

MOTIVATION: Database searching algorithms for proteins use scoring matrices based on average protein properties, and thus are dominated by globular proteins. However, since transmembrane regions of a protein are in a distinctly different environment than globular proteins, one would expect generalized substitution matrices to be inappropriate for transmembrane regions. RESULTS: We present the PHAT (predicted hydrophobic and transmembrane) matrix, which significantly outperforms generalized matrices and a previously published transmembrane matrix in searches with transmembrane queries. We conclude that a better matrix can be constructed by using background frequencies characteristic of the twilight zone, where low-scoring true positives have scores indistinguishable from high-scoring false positives, rather than the amino acid frequencies of the database. The PHAT matrix may help improve the accuracy of sequence alignments and evolutionary trees of membrane proteins.