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PubMed1997

Hydroxynitrile lyase from Hevea brasiliensis: molecular characterization and mechanism of enzyme catalysis.

(S)-Hydroxynitrile lyase (Hnl) from the tropical rubber tree Hevea brasiliensis is a 29 kDa single chain protein that catalyses the breakdown or formation of a C--C bond by reversible addition of hydrocyanic acid to aldehydes or ketones. The primary sequence of Hnl has no significant homology to known proteins. Detailed homology investigations employing PROFILESEARCH and secondary structure prediction algorithms suggest that Hnl is a member of the alpha/beta hydrolase fold protein family and contains a catalytic triad as functional residues for catalysis. The significance of predicted catalytic residues was tested and confirmed by site-directed mutagenesis and expression of mutant and wild-type proteins in the yeast, Saccharomyces cerevisiae. Based on these data we suggest a mechanistic model for the (S)-cyanohydrin synthesis catalyzed by hydroxynitrile lyase from Hevea brasiliensis.

Aldehyde-Lyases↗
PubMedDate not supplied

[Prediction of the structural class of globular proteins from their amino acid sequence].

Two-dimensional representation of consequence of 32 proteins with known three-dimensional structure has been obtained on 20 X 20 matrix of the distribution of amino acid pairs (nearest neighbours). Prediction algorithm of the structural class of globular proteins has been worked out on the basis of the comparison of 20 X 20 matrix of the distribution of amino acid pairs for the proteins of different structural classes. The accuracy of structural class predictions of 32 proteins has been carried out (all the proteins are taken from numerous ones used to obtain the algorithm).

Amino Acid Sequence↗
PubMed1997

Protein topology recognition from secondary structure sequences: application of the hidden Markov models to the alpha class proteins.

The three-dimensional fold of a protein is described by the organization of its secondary structure elements in 3D space, i.e. its "topology". We find that the protein topology can be recognized from the ID sequence of secondary structure states of the residues alone. Automated recognition is facilitated by use of hidden Markov models (HMMs) to represent topology families of proteins. Such models can be trained on the experimentally observed secondary structure sequences of family members using well established algorithms. Here, we model various topology groups in the alpha class of proteins and identify, from a large database, those proteins having the topology described by each model. The correct topology family for protein secondary structure sequences could be recognized 12 out of 14 times. When the observed secondary structure sequences are replaced with predicted sequences recognition is still achievable 8 out of 14 times. The success rate for observed sequences indicates that our approach will become increasingly useful as the accuracy of secondary prediction algorithms is improved. Our study indicates that the HMMs are useful for protein topology recognition even when no detectable primary amino acid sequence similarity is present. To illustrate the potential utility of our method, protein topology recognition is attempted on leptin, the obese gene product, and the human interleukin-6 sequence, for which fold predictions have been previously published.

Algorithms↗
PubMed1987

Prediction of secondary structure by evolutionary comparison: application to the alpha subunit of tryptophan synthase.

The amino acid sequences of the a subunits of tryptophan synthase from ten different microorganisms were aligned by standard procedures. The alpha helices, beta strands and turns of each sequence were predicted separately by two standard prediction algorithms and averaged at homologous sequence positions. Additional evidence for conserved secondary structure was derived from profiles of average hydropathy and chain flexibility values, leading to a joint prediction. There is good agreement between (1) predicted beta strands, maximal hydropathy and minimal flexibility, and (2) predicted loops, great chain flexibility, and protein segments that accept insertions of various lengths in individual sequences. The a subunit is predicted to have eight repeated beta-loop-alpha-loop motifs with an extra N-terminal alpha helix and an intercalated segment of highly conserved residues. This pattern suggests that the territory structure of the a subunit is an eightfold alpha/beta barrel. The distribution of conserved amino acid residues and published data on limited proteolysis, chemical modification, and mutagenesis are consistent with the alpha/beta barrel structure. Both the active site of the a subunit and the combining site for the beta 2 subunit are at the end of the barrel formed by the carboxyl-termini of the beta strands.

Amino Acid Sequence↗
PubMed1983

Assessment of secondary-structure prediction of proteins. Comparison of computerized Chou-Fasman method with others.

A method predicting protein secondary structure from sequence information could be assessed for its real efficiency by applying it to a number of proteins which lie completely outside a given data set. This type of test is performed for the three methods of Chou and Fasman (Adv. Enzymol. 47 (1978) 45-148), Robson and co-workers (J. Mol. Biol. 120 (1978) 97-120) and Lim (J. Mol. Biol. 88 (1974) 873-894) by using data of 19 proteins for the former two methods and 11 proteins for the method of Lim. The prediction abilities of these methods turn out to be of almost the same level, but unexpectedly low: their average scores are commonly less than 55% measured by the three-state assessment (alpha, beta and coil) or less than 45% measured by the four-state assessment (alpha, beta, turn and coil). This level of accuracy is more than 20% lower than that of current expectations as summarized by Schulz and Schirmer (Principles of Protein Structure (1979) Ch. 6, Springer, New York). A joint prediction attempted with the simultaneous usage of the three prediction methods did not improve the results. Causes and implications of the unsatisfactory results are discussed. In this study, computer programs were prepared for the methods of Chou and Fasman and of Robson and co-workers. While difficulties arose in the course of the computerization of the Chou-Fasman method, the prediction algorithm was arranged in a fully automatic form with optimization of the original rules as well as introduction of a modified treatment for solving the overlap among initially predicted regions of the secondary structures. Large discrepancies observed between the original results and those obtained by the computerized method are examined.

Amino Acid Sequence↗
PubMed1997

Meeting review: the Second meeting on the Critical Assessment of Techniques for Protein Structure Prediction (CASP2), Asilomar, California, December 13-16, 1996.

In most fields of scientific endeavor, the outcomes of important experiments are not always known before the experiments are performed. But in protein structure prediction, algorithms are usually developed and tested in situations where the answers are known. In December 1996, the Second Meeting on the Critical Assessment of Techniques for Protein Structure Prediction (CASP2) was held in Asilomar, California to rectify this situation: protein sequences were provided in advance for which the experimental structure had not yet been published. Over 70 research groups provided bona fide predictions on 42 targets in four categories: comparative or 'homology' modeling, fold recognition or 'threading', ab initio structure predictions, and docking predictions. Since the previous CASP meeting in 1994, the role of fold recognition in structure prediction has increased enormously with the largest number of groups participating in this category. In this review, we highlight some of the important developments and give at least a qualitative sense of what kind of methods produced some of the better predictions.

Computer Simulation↗
PubMed2006

A compression-based approach for coding sequences identification. I. Application to prokaryotic genomes.

Most of the gene prediction algorithms for prokaryotes are based on Hidden Markov Models or similar machine-learning approaches, which imply the optimization of a high number of parameters. The present paper presents a novel method for the classification of coding and non-coding regions in prokaryotic genomes, based on a suitably defined compression index of a DNA sequence. The main features of this new method are the non-parametric logic and the costruction of a dictionary of words extracted from the sequences. These dictionaries can be very useful to perform further analyses on the genomic sequences themselves. The proposed approach has been applied on some prokaryotic complete genomes, obtaining optimal scores of correctly recognized coding and non-coding regions. Several false-positive and false-negative cases have been investigated in detail, which have revealed that this approach can fail in the presence of highly structured coding regions (e.g., genes coding for modular proteins) or quasi-random non-coding regions (e.g., regions hosting non-functional fragments of copies of functional genes; regions hosting promoters or other protein-binding sequences). We perform an overall comparison with other gene-finder software, since at this step we are not interested in building another gene-finder system, but only in exploring the possibility of the suggested approach.

Algorithms↗
PubMed2001

Reduced haemostatic factor transfusion using heparinase-modified thrombelastography during cardiopulmonary bypass.

We set out to determine if the heparinase-modified thrombelastogram using anticoagulated blood from patients during cardiac surgery could guide treatment with haemostatic components. In 60 patients a simple algorithm predicted a possible 60-80% decrease in the use of haemostatic components. In a second series, 30 patients were allocated to receive components using this intra-operative algorithm and 30 using clinical criteria and laboratory-based tests. Ten patients in the clinical group received a total of 16 units of fresh frozen plasma and nine platelet concentrates compared with five patients transfused with five units of fresh frozen plasma and one platelet concentrate in the algorithm group. Twelve-hour chest tube losses [algorithm group 470 (295-820) ml, clinically managed group 390 (240-820) ml (median, quartile values)] were not different between groups despite the threefold reduction in the use of haemostatic products, showing that intra-operative monitoring of coagulation in the anticoagulated patient can be used to guide treatment.

Adult↗
PubMed2006

Impact of RNA structure on the prediction of donor and acceptor splice sites.

BACKGROUND: gene identification in genomic DNA sequences by computational methods has become an important task in bioinformatics and computational gene prediction tools are now essential components of every genome sequencing project. Prediction of splice sites is a key step of all gene structural prediction algorithms. RESULTS: we sought the role of mRNA secondary structures and their information contents for five vertebrate and plant splice site datasets. We selected 900-nucleotide sequences centered at each (real or decoy) donor and acceptor sites, and predicted their corresponding RNA structures by Vienna software. Then, based on whether the nucleotide is in a stem or not, the conventional four-letter nucleotide alphabet was translated into an eight-letter alphabet. Zero-, first- and second-order Markov models were selected as the signal detection methods. It is shown that applying the eight-letter alphabet compared to the four-letter alphabet considerably increases the accuracy of both donor and acceptor site predictions in case of higher order Markov models. CONCLUSION: Our results imply that RNA structure contains important data and future gene prediction programs can take advantage of such information.

Algorithms↗
PubMed1998

Structural classification of alphabetabeta and betabetaalpha supersecondary structure units in proteins.

We present a fully automatic structural classification of supersecondary structure units, consisting of two hydrogen-bonded beta strands, preceded or followed by an alpha helix. The classification is performed on the spatial arrangement of the secondary structure elements, irrespective of the length and conformation of the intervening loops. The similarity of the arrangements is estimated by a structure alignment procedure that uses as similarity measure the root mean square deviation of superimposed backbone atoms. Applied to a set of 141 well-resolved nonhomologous protein structures, the classification yields 11 families of recurrent arrangements. In addition, fragments that are structurally intermediate between the families are found; they reveal the continuity of the classification. The analysis of the families shows that the alpha helix and beta hairpin axes can adopt virtually all relative orientations, with, however, some preferable orientations; moreover, according to the orientation, preferences in the left/right handedness of the alpha-beta connection are observed. These preferences can be explained by favorable side by side packing of the alpha helix and the beta hairpin, local interactions in the region of the alpha-beta connection or stabilizing environments in the parent protein. Furthermore, fold recognition procedures and structure prediction algorithms coupled to database-derived potentials suggest that the preferable nature of these arrangements does not imply their intrinsic stability. They usually accommodate a large number of sequences, of which only a subset is predicted to stabilize the motif. The motifs predicted as stable could correspond to nuclei formed at the very beginning of the folding process.

Algorithms↗
PubMed2003

Sensor data validation using gray models.

A new method based on the gray model is described for the online validation of measurements. A gray model is a differential equation describing the behavior of an accumulate generating operation (AGO) data sequence. First-order gray models are fitted to measuring data records using the recursive orthogonal least-squares algorithm. Predictions derived from the fitted gray model are then compared with the actual measurements to generate a prediction error sequence. The quality of the measured value is determined by the prediction errors and variance of the prediction error sequence. Experimental results for detecting the quality of measurements from a thermistor are presented.

Algorithms↗
PubMed1988

A protein secondary structure prediction scheme for the IBM PC and compatibles.

A prediction scheme has been developed for the IBM PC and compatibles containing computer programs which make use of the protein secondary structure prediction algorithms of Nagano (1977a,b), Garnier et al. (1978), Burgess et al. (1974), Chou and Fasman (1974a,b), Lim (1974) and Dufton and Hider (1977). The results of the individual prediction methods are combined as described by Hamodrakas et al. (1982) by the program PLOTPROG to produce joint prediction histograms for a protein, for three types of secondary structure: alpha-helix, beta-sheet and beta-turns. The scheme requires uniform input for the prediction programs, produced by any word processor, spreadsheet, editor or database program and produces uniform output on a printer, a graphics screen or a file. The scheme is independent of any additional software and runs under DOS 2.0 or later releases.

Amino Acid Sequence↗
PubMed2005

Pre-treatment erythropoietin levels cannot be used to predict individual response to epoetin alfa in anaemic cancer patients.

Recombinant human erythropoietin (epoetin alfa) is an effective treatment for anaemia in cancer patients, and over two-thirds of recipients experience a substantial increase in haemoglobin concentration (>2 g/dl). However, it would be helpful to identify responders before starting treatment. Some studies have suggested that high pre-treatment levels of endogenous erythropoietin pre-treatment levels of endogenous erythropoietin or other pre-treatment or early response variables are associated with a poor response to epoetin alfa, and several predictive algorithms have been published. We analysed data pooled from 9 clinical trials of 1010 patients to determine the clinical usefulness of pre-treatment erythropoietin levels and other variables for predicting response. This showed that pre-treatment factors alone do not provide a clinically useful prediction of response. The sensitivity of these models increases slightly if early response variables, such as the change in haemoglobin after 4 weeks, are included, but specificity remains poor. We conclude that, while there may be a statistical relationship between certain factors and response, none approach clinically useful levels of sensitivity or specificity.

Anemia↗
PubMed2004

Human MicroRNA targets.

MicroRNAs (miRNAs) interact with target mRNAs at specific sites to induce cleavage of the message or inhibit translation. The specific function of most mammalian miRNAs is unknown. We have predicted target sites on the 3' untranslated regions of human gene transcripts for all currently known 218 mammalian miRNAs to facilitate focused experiments. We report about 2,000 human genes with miRNA target sites conserved in mammals and about 250 human genes conserved as targets between mammals and fish. The prediction algorithm optimizes sequence complementarity using position-specific rules and relies on strict requirements of interspecies conservation. Experimental support for the validity of the method comes from known targets and from strong enrichment of predicted targets in mRNAs associated with the fragile X mental retardation protein in mammals. This is consistent with the hypothesis that miRNAs act as sequence-specific adaptors in the interaction of ribonuclear particles with translationally regulated messages. Overrepresented groups of targets include mRNAs coding for transcription factors, components of the miRNA machinery, and other proteins involved in translational regulation, as well as components of the ubiquitin machinery, representing novel feedback loops in gene regulation. Detailed information about target genes, target processes, and open-source software for target prediction (miRanda) is available at http://www.microrna.org. Our analysis suggests that miRNA genes, which are about 1% of all human genes, regulate protein production for 10% or more of all human genes.

3' Untranslated Regions↗
PubMed1998

Do transmembrane protein superfolds exist?

A reliable and widely used transmembrane protein structure prediction algorithm was applied to five representative genomic sequence data sets in order to re-examine the hypothesis that in contrast to globular proteins there are no favored transmembrane protein fold families. When the number of predicted membrane spanning segments and the topology of these segments is taken into account then definite biases are observed which suggest that certain transmembrane topologies are significantly more common than others.

Algorithms↗
PubMed2003

Prediction of peroxisomal targeting signal 1 containing proteins from amino acid sequence.

Peroxisomal matrix proteins have to be imported into their target organelle post-translationally. The major translocation pathway depends on a C-terminal targeting signal, termed PTS1. Our previous analysis of sequence variability in the PTS1 motif revealed that, in addition to the known C-terminal tripeptide, at least nine residues directly upstream are important for signal recognition in the PTS1-Pex5 receptor complex. The refined PTS1 motif description was implemented in a prediction tool composed of taxon-specific functions (metazoa, fungi, remaining taxa), capable of recognising potential PTS1s in query sequences. The composite score function consists of classical profile terms and additional terms penalising deviations from the derived physical property pattern over sequence segments. The prediction algorithm has been validated with a self-consistency and three different cross-validation tests. Additionally, we tested the tool on a large set of non-peroxisomal negatives, on mutation data, and compared the prediction rate to the PTS1 component of the PSORT2 program. The sensitivity of our predictor in recognising documented PTS1 signal containing proteins is close to 90% for reliable prediction. The predictor distinguishes even SKL-appended non-peroxisomally targeted proteins such as a mouse dihydrofolate reductase-SKL construct. The corresponding rate of false positives is not worse than 0.8%; thus, the tool can be applied for large-scale unsupervised sequence database annotation. A scan of public protein databases uncovered a number of yet uncharacterised proteins for which the PTS1 signal might be critical for biological function. The predicted presence of a PTS1 signal implies peroxisomal localisation in the absence of N-terminal targeting sequences such as the mitochondrial import signal.

Algorithms↗
PubMed2000

The interconversion of isoforms of seminal ribonuclease: modelling key intermediates and trypsin effects.

The stepwise tryptic degradation of the interconverting quaternary isoforms of seminal ribonuclease has been analysed by structural modelling, based on the experimental results obtained by treating the dimeric protein with trypsin. The results of the analysis were compared with those obtained applying to the action of trypsin on seminal ribonuclease a recently proposed predictive algorithm for limited proteolysis. The attention was focussed on the MxM form of the protein, in which the two subunits swap their N-terminal ends interconverting at equilibrium with the M=M form with no interchange between subunits. The analysis led to the identification of a key intermediate in the interconversion pathway, and to the resolution of the apparent contradiction between prediction and actual experimental data.

Algorithms↗
PubMed2004

Sequence-dependent thermodynamic parameters for locked nucleic acid (LNA)-DNA duplex formation.

The design of modified nucleic acid probes, primers, and therapeutics is improved by considering their thermodynamics. Locked nucleic acid (LNA) is one of the most useful modified backbones, with incorporation of a single LNA providing a substantial increase in duplex stability. In this work, the hybridization DeltaH(o), DeltaS(o), and melting temperature (T(M)) were measured from absorbance melting curves for 100 duplex oligonucleotides with single internal LNA nucleotides on one strand, and the results provided DeltaDeltaH(o), DeltaDeltaS(o), DeltaDelta, and DeltaT(M) relative to reference DNA oligonucleotides. LNA pyrimidines contribute more stability than purines, especially A(L), but there is substantial context dependence for each LNA base. Both the 5' and 3' neighbors must be considered in predicting the effect of an LNA incorporation, with purine neighbors providing more stability. Enthalpy-entropy compensation in DeltaDeltaH(o) and DeltaDeltaS(o) is observed across the set of sequences, suggesting that LNA can stabilize the duplex by either preorganization or improved stacking, but not both simultaneously. Singular value decomposition analysis provides predictive sequence-dependent rules for hybridization of singly LNA-substituted DNA oligonucleotides to their all-DNA complements. The results are provided as sets of DeltaDeltaH(o), DeltaDeltaS(o), and DeltaDelta parameters for all 32 of the possible nearest neighbors for LNA+DNA:DNA hybridization (5' MX(L) and 5' X(L)N, where M, N, and X = A, C, G, or T and X(L) represents LNA). The parameters are applicable within the standard thermodynamic prediction algorithms. They provide T(M) estimates accurate to within 2 degrees C for LNA-containing oligonucleotides, which is significantly better accuracy than previously available.

Algorithms↗