A set of programs for analysis of kinetic and equilibrium data

A program package that can be used for analysis of a wide rangeof kinetic and equilibrium data is described. The four programswere written in Turbo Pascal and run on PC, XT, AT and compatibles.The first of the programs allows the user to fit data with 16predefined and one user-defined function, using two differentnon-linear least-squares procedures. Two additional programsare used to test both the evaluation of model functions andthe least-squares fits. One of these programs uses two simpleprocedures to generate a Gaussian-distributed random variablethat is used to simulate the experimental error of measurements.The last program simulates kinetics described by differentialequations that cannot be solved analytically, using numericalintegration. This program helps the user to judge the validityof steady-state assumptions or treatment of kinetic measurementsas relaxations. Received on September 19, 1989; accepted on March 16, 1990     

Statistical analysis and graphical display of multivariate data on the Macintosh

Two Macintosh programs written for multivariate data analysisand multivariate data graphical display are presented. MacMulincludes principal component analysis (PCA), correspondenceanalysis (CA) and multiple correspondence analysis (MCA), witha complete, original and unified set of numerical aids to interpretation.GraphMu is designed for drawing collections of elementary graphics(curves, maps, graphical models) thus allowing comparisons betweenvariables, individuals, and principal axes planes of multivariatemethods. Both programs are self-documented applications andmake full use of the user-oriented graphical interface of theMacintosh to simplify the process of analysing data sets. Anexample is described to show the results obtained on a smallecological data set. Received on January 24, 1989; accepted on July 17, 1989     

VARUN: discovering extensible motifs under saturation constraints

The discovery of motifs in biosequences is frequently torn between the rigidity of the model on one hand and the abundance of candidates on the other hand. In particular, motifs that include wild cards or "don't cares" escalate exponentially with their number, and this gets only worse if a don't care is allowed to stretch up to some prescribed maximum length. In this paper, a notion of extensible motif in a sequence is introduced and studied, which tightly combines the structure of the motif pattern, as described by its syntactic specification, with the statistical measure of its occurrence count. It is shown that a combination of appropriate saturation conditions and the monotonicity of probabilistic scores over regions of constant frequency afford us significant parsimony in the generation and testing of candidate overrepresented motifs. A suite of software programs called Varun is described, implementing the discovery of extensible motifs of the type considered. The merits of the method are then documented by results obtained in a variety of experiments primarily targeting protein sequence families. Of equal importance seems the fact that the sets of all surprising motifs returned in each experiment are extracted faster and come in much more manageable sizes than would be obtained in the absence of saturation constraints.     

GELENT: a sequence gel entry program for keyboard and sonic digitizer input

A program is described for sequence data entry which allowsflexible program control by responding to both the keyboardand a sonic digitizer concurrently. Simplification of the initializationstage of each gel reading has been achieved, in comparison withother programs. Received on July 7, 1988; accepted on January 10, 1989     

Endonuclease (R) subunits of type-I and type-III restriction-modification enzymes contain a helicase-like domain.

A statistically significant amino acid sequence similarity is demonstrated between the endonuclease (R) subunit of EcoK restriction-modification (R-M) enzyme, and RNA and DNA helicases of the so-called 'DEAD' family. It is further shown that all three known sequences of R subunits of type-I and type-III R-M enzymes contain the conserved amino acid sequence motifs typical of the previously described helicase superfamily II [(1989) Nucleic Acids Res. 17, 4713-4730]. A hypothesis is proposed that these enzymes may exert helicase activity possibly required for local unwinding of DNA in the cleavage sites.     

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.     

Screening protein and nucleic acid sequences against libraries of patterns.

We describe programs that can screen nucleic acid and protein sequences against libraries of motifs and patterns. Such comparisons are likely to play an important role in interpreting the function of sequences determined during large scale sequencing projects. In addition we report programs for converting the Prosite protein motif library into a form that is compatible with our searching programs. The programs work on VAX and SUN computers.     

The performance of several multiple-sequence alignment programs in relation to secondary-structure features for an rRNA sequence

The performances of five global multiple-sequence alignment programs (CLUSTAL W, Divide and Conquer, Malign, PileUp, and TreeAlign) were evaluated using part of the animal mitochondrial small subunit (12S) rRNA molecule. Conserved sequence motifs derived from an alignment based on secondary structural information were used to score how well each program aligned a data set of five vertebrate and five invertebrate taxa over a range of parameter values. All of the programs could align the motifs with reasonable accuracy for at least one set of parameter conditions, although if the whole sequence was considered, similarity to the structural alignment was only 25%-34%. Use of small gap costs generally gave more accurate results, although Malign and TreeAlign generated longer alignments when gap costs were low. The programs differed in the consistency of the alignments when gap cost was varied; CLUSTAL W, Divide and Conquer, and TreeAlign were the most accurate and robust, while PileUp performed poorly as gap cost values increased, and the accuracy of Malign fluctuated. Default settings for the programs did not give the best results, and attempting to select similar parameter values in different programs did not always result in more similar alignments. Poor alignment of even well-conserved motifs can occur if these are near sites with insertions or deletions. Since there is no a priori way to determine gap costs and because such costs can vary over the gene, alignment of rRNA sequences, particularly the less well conserved regions, should be treated carefully and aided by secondary structure and conserved motifs. Some motifs are single bases and so are often invisible to alignment programs. Our tests involved the most conserved regions of the 12S rRNA gene, and alignment of less well conserved regions will be more problematical. None of the alignments we examined produced a fully resolved phylogeny for the data set, indicating that this portion of 12S rRNA is insufficient for resolution of distant evolutionary relationships.     

The computer program package "SAMSON" for analysis of primary structure of biopolymers

A program package "SAMSON" for the computer analysis of biopolymer primary structures is described. All possible modes of sequence investigation are considered. The programs for sequence comparison are described in some details. The general principles of a program package organisation and of its user interface are also mentioned. For more complete information see Vernoslov S.E. et al. "Program package "SAMSON" for the analysis of the polymer primary structures", parts 1 and 2, Poustchino, ONTI NCBI, 1989.     

XFINGER: A tool for searching and visualising protein fingerprints and patterns

A tool for searching pattern and fingerprint databases is described.Fingerprints are groups of motifs excised from conserved regionsof sequence alignments and used for iterative database scanning.The constituent motifs are thus encoded as small alignmentsin which sequence information is maximised with each databasepass; they therefore differ from regular-expression patterns,in which alignments are reduced to single consensus sequences.Different database formats have evolved to store these disparatetypes of information, namely the PROSITE dictionary of patternsand the PRINTS fingerprint database, but programs have not beenavailable with the flexibility to search them both. We havedeveloped a facility to do this: the system allows query sequencesto be scanned against either PROSITE, the full PRINTS database,or against individual fingerprints. The results of fingerprintsearches are displayed simultaneously in both text and graphicalwindows to render them more tangible to the user. Where structuralcoordinates are available, identified motifs may be visualisedin a 3D context. The program runs on Silicon Graphics machinesusing GL graphics libraries and on machines with X servers supportingthe PEX extension: its use is illustrated here by depictingthe location of low-density lipoprotein-binding (LDL) motifsand leucine-rich repeats in a mosaic G-protein-coupled receptor(GPCR).     

Protein consensus sequence motifs

The large number of protein consensus sequences that may be recognized without computer analysis are reviewed. These include the extensive range of known phosphorylation site motifs for protein kinases; metal binding sites for calcium, zinc, copper, and iron; enzyme active site motifs; nucleotide binding and covalent attachment sites for prosthetic groups, carbohydrate, and lipids. Of particular note is the increasing realization of the importance for cellular regulation of protein-protein interaction motifs and sequences that target proteins to particular subcellular locations. This article includes an introduction to accessing the many suites of programs for analysis of protein structure, signatures of protein families, and consensus sequences that may be carried out on the internet.     

Accurate recognition of cis-regulatory motifs with the correct lengths in prokaryotic genomes

We present a new computational method for solving a classical problem, the identification problem of cis-regulatory motifs in a given set of promoter sequences, based on one key new idea. Instead of scoring candidate motifs individually like in all the existing motif-finding programs, our method scores groups of candidate motifs with similar sequences, called motif closures, using a P-value, which has substantially improved the prediction reliability over the existing methods. Our new P-value scoring scheme is sequence length independent, hence allowing direct comparisons among predicted motifs with different lengths on the same footing. We have implemented this method as a Motif Recognition Computer (MREC) program, and have extensively tested MREC on both simulated and biological data from prokaryotic genomes. Our test results indicate that MREC can accurately pick out the actual motif with the correct length as the best scoring candidate for the vast majority of the cases in our test set. We compared our prediction results with two motif-finding programs Cosmo and MEME, and found that MREC outperforms both programs across all the test cases by a large margin. The MREC program is available at http://csbl.bmb.uga.edu/~bingqiang/MREC1/.     

Mining protein sequences for motifs.

We use methods from Data Mining and Knowledge Discovery to design an algorithm for detecting motifs in protein sequences. The algorithm assumes that a motif is constituted by the presence of a "good" combination of residues in appropriate locations of the motif. The algorithm attempts to compile such good combinations into a "pattern dictionary" by processing an aligned training set of protein sequences. The dictionary is subsequently used to detect motifs in new protein sequences. Statistical significance of the detection results are ensured by statistically determining the various parameters of the algorithm. Based on this approach, we have implemented a program called GYM. The Helix-Turn-Helix motif was used as a model system on which to test our program. The program was also extended to detect Homeodomain motifs. The detection results for the two motifs compare favorably with existing programs. In addition, the GYM program provides a lot of useful information about a given protein sequence.     

Discriminative motif finding for predicting protein subcellular localization

Many methods have been described to predict the subcellular location of proteins from sequence information. However, most of these methods either rely on global sequence properties or use a set of known protein targeting motifs to predict protein localization. Here, we develop and test a novel method that identifies potential targeting motifs using a discriminative approach based on hidden Markov models (discriminative HMMs). These models search for motifs that are present in a compartment but absent in other, nearby, compartments by utilizing an hierarchical structure that mimics the protein sorting mechanism. We show that both discriminative motif finding and the hierarchical structure improve localization prediction on a benchmark data set of yeast proteins. The motifs identified can be mapped to known targeting motifs and they are more conserved than the average protein sequence. Using our motif-based predictions, we can identify potential annotation errors in public databases for the location of some of the proteins. A software implementation and the data set described in this paper are available from http://murphylab.web.cmu.edu/software/2009_TCBB_motif/.     

A super-secondary structure predicted to be common to several alpha-1,4-D-glucan-cleaving enzymes.

Predictions of protein secondary structure are used with amino acid sequence alignments to show that the N-terminal domains of cyclodextrin glucanotransferases and a yeast alpha-glucosidase may have the same super-secondary structure as alpha-amylases, i.e. an (alpha/beta)8-barrel fold. Sequence similarities provide evidence that glucanotransferases, and possibly the glucosidase, are, like alpha-amylases, Ca2+-containing enzymes. The relationship between substrate specificity and the nature of the amino acid residues proposed at the active site is discussed for the transferases and alpha-glucosidase. A set of three programs for an Apple IIe computer to carry out the calculations described by Garnier, Osguthorpe & Robson [(1978) J. Mol. Biol. 120, 97-120] and a set of four programs for an Apple IIe computer to carry out the calculations described by Levin, Robson & Garnier [(1986) FEBS Lett. 205, 303-308] have been deposited as Supplementary Publication SUP 50149 (25 pages) at the British Library Document Supply Centre, Boston Spa, Wetherby, West Yorkshire LS23 7BQ, U.K., from whom copies can be obtained on the terms indicated in Biochem. J. (1989) 257, 5.