Anti-peptide aptamers recognize amino acid sequence and bind a protein epitope.

In vitro selection of nucleic acid binding species (aptamers) is superficially similar to the immune response. Both processes produce biopolymers that can recognize targets with high affinity and specificity. While antibodies are known to recognize the sequence and conformation of protein surface features (epitopes), very little is known about the precise interactions between aptamers and their epitopes. Therefore, aptamers that could recognize a particular epitope, a peptide fragment of human immunodeficiency virus type I Rev, were selected from a random sequence RNA pool. Several of the selected RNAs could bind the free peptide more tightly than a natural RNA ligand, the Rev-binding element. In accord with the hypothesis that protein and nucleic acid binding cusps are functionally similar, interactions between aptamers and the peptide target could be disrupted by sequence substitutions. Moreover, the aptamers appeared to be able to bind peptides with different solution conformations, implying an induced fit mechanism for binding. Just as anti-peptide antibodies can sometimes recognize the corresponding epitope when presented in a protein, the anti-peptide aptamers were found to specifically bind to Rev.

Global properties of the mapping between local amino acid sequence and local structure in proteins.

Local protein structure prediction efforts have consistently failed to exceed approximately 70% accuracy. We characterize the degeneracy of the mapping from local sequence to local structure responsible for this failure by investigating the extent to which similar sequence segments found in different proteins adopt similar three-dimensional structures. Sequence segments 3-15 residues in length from 154 different protein families are partitioned into neighborhoods containing segments with similar sequences using cluster analysis. The consistency of the sequence-to-structure mapping is assessed by comparing the local structures adopted by sequence segments in the same neighborhood in proteins of known structure. In the 154 families, 45% and 28% of the positions occur in neighborhoods in which one and two local structures predominate, respectively. The sequence patterns that characterize the neighborhoods in the first class probably include virtually all of the short sequence motifs in proteins that consistently occur in a particular local structure. These patterns, many of which occur in transitions between secondary structural elements, are an interesting combination of previously studied and novel motifs. The identification of sequence patterns that consistently occur in one or a small number of local structures in proteins should contribute to the prediction of protein structure from sequence.

An amino acid sequence motif sufficient for subnuclear localization of an arginine/serine-rich splicing factor.

We have identified an amino acid sequence in the Drosophila Transformer (Tra) protein that is capable of directing a heterologous protein to nuclear speckles, regions of the nucleus previously shown to contain high concentrations of spliceosomal small nuclear RNAs and splicing factors. This sequence contains a nucleoplasmin-like bipartite nuclear localization signal (NLS) and a repeating arginine/serine (RS) dipeptide sequence adjacent to a short stretch of basic amino acids. Sequence comparisons from a number of other splicing factors that colocalize to nuclear speckles reveal the presence of one or more copies of this motif. We propose a two-step subnuclear localization mechanism for splicing factors. The first step is transport across the nuclear envelope via the nucleoplasmin-like NLS, while the second step is association with components in the speckled domain via the RS dipeptide sequence.

Prediction of protein folding class using global description of amino acid sequence.

We present a method for predicting protein folding class based on global protein chain description and a voting process. Selection of the best descriptors was achieved by a computer-simulated neural network trained on a data base consisting of 83 folding classes. Protein-chain descriptors include overall composition, transition, and distribution of amino acid attributes, such as relative hydrophobicity, predicted secondary structure, and predicted solvent exposure. Cross-validation testing was performed on 15 of the largest classes. The test shows that proteins were assigned to the correct class (correct positive prediction) with an average accuracy of 71.7%, whereas the inverse prediction of proteins as not belonging to a particular class (correct negative prediction) was 90-95% accurate. When tested on 254 structures used in this study, the top two predictions contained the correct class in 91% of the cases.

Better prediction of protein contact number using a support vector regression analysis of amino acid sequence

Background: Protein tertiary structure can be partly characterized via each amino acid's contact number measuring how residues are spatially arranged. The contact number of a residue in a folded protein is a measure of its exposure to the local environment, and is defined as the number of C-beta atoms in other residues within a sphere around the C-beta atom of the residue of interest. Contact number is partly conserved between protein folds and thus is useful for protein fold and structure prediction. In turn, each residue's contact number can be partially predicted from primary amino acid sequence, assisting tertiary fold analysis from sequence data. In this study, we provide a more accurate contact number prediction method from protein primary sequence. Results: We predict contact number from protein sequence using a novel support vector regression algorithm. Using protein local sequences with multiple sequence alignments (PSI-BLAST profiles), we demonstrate a correlation coefficient between predicted and observed contact numbers of 0.70, which outperforms previously achieved accuracies. Including additional information about sequence weight and amino acid composition further improves prediction accuracies significantly with the correlation coefficient reaching 0.73. If residues are classified as being either contacted or non-contacted, the prediction accuracies are all greater than 77%, regardless of the choice of classification thresholds. Conclusion: The successful application of support vector regression to the prediction of protein contact number reported here, together with previous applications of this approach to the prediction of protein accessible surface area and B-factor profile, suggests that a support vector regression approach may be very useful for determining the structure-function relation between primary sequence and higher order consecutive protein structural and functional properties.

STAR: predicting recombination sites from amino acid sequence

Background: Designing novel proteins with site-directed recombination has enormous prospects. By locating effective recombination sites for swapping sequence parts, the probability that hybrid sequences have the desired properties is increased dramatically. The prohibitive requirements for applying current tools led us to investigate machine learning to assist in finding useful recombination sites from amino acid sequence alone. Results: We present STAR, Site Targeted Amino acid Recombination predictor, which produces a score indicating the structural disruption caused by recombination, for each position in an amino acid sequence. Example predictions contrasted with those of alternative tools, illustrate STAR'S utility to assist in determining useful recombination sites. Overall, the correlation coefficient between the output of the experimentally validated protein design algorithm SCHEMA and the prediction of STAR is very high (0.89). Conclusion: STAR allows the user to explore useful recombination sites in amino acid sequences with unknown structure and unknown evolutionary origin. The predictor service is available from http://pprowler.itee.uq.edu.au/star.

A first case of protease codon 35 amino acid insertion in a HIV-1 subtype B sequence detected in the Bauru region, state of São Paulo, Brazil: case report

Inserções de aminoácidos na protease têm sido raramente descritas em pacientes infectados pelo HIV. Uma destas inserções foi, recentemente, descrita no codon 35, embora seu impacto na resistência mantém-se pouco conhecido. Este trabalho apresenta um caso de uma variante viral com inserção no codon 35 da protease, descrita pela primeira vez em Bauru, São Paulo, Brasil, circulante em um homem, caucasiano, com 38 anos, o qual apresenta infecção assintomática pelo HIV desde 1997. A variante isolada mostrou uma inserção no codon 35 da protease de dois aminoácidos: uma treonina e um ácido aspártico, resultando na sequência de aminoácidos E35E_TD.

PROPENSITIES OF AMINO ACID RESIDUES IN PROTEINS FOR DIFFERENT REGIONS OF THE RAMACHANDRAN MAP

Using a dataset of 1164 crystal structures of largely non-homologous proteins defined at a resolution of 1.5 angstrom or better, we have investigated the (phi,psi) preferences of 20 residue types by considering the residues which occur in loops. Propensities of residue types to occur in the loops with (phi,psi) values in the aa region of the Ramachandran map has a poor correlation coefficient of 0.48 to the Chou-Fasman propensities of the residue types to occur in the a-helical segments. However the correlation coefficient between propensities of residues in loops to adopt beta conformations and those in beta-sheet is much higher (0.95). These observations suggest that a-helix formation is well influenced by the local amino acid sequence while intrinsic preference of residue types for beta-sheet plays a major role in the formation of beta-sheet. The main chain polar groups of residues in loops, that can affect the (phi,psi) values, can be involved in intra-molecular hydrogen bonding. Therefore we investigated further by considering subset of residues in loops with low (0 to 2) number of intra-molecular hydrogen bonds per residue involving main chain polar atoms. For this subset, the correlation coefficients between propensities for alpha-helix and alpha(R) region and between beta-sheet and beta-region are 0.26 and 0.64 respectively. This reiterates higher intrinsic tendency of beta-region favouring residues to adopt beta-sheet than alpha(R) region favouring residues to adopt alpha-helical structure.

Use of a structural alphabet to find compatible folds for amino acid sequences

The structural annotation of proteins with no detectable homologs of known 3D structure identified using sequence-search methods is a major challenge today. We propose an original method that computes the conditional probabilities for the amino-acid sequence of a protein to fit to known protein 3D structures using a structural alphabet, known as Protein Blocks (PBs). PBs constitute a library of 16 local structural prototypes that approximate every part of protein backbone structures. It is used to encode 3D protein structures into 1D PB sequences and to capture sequence to structure relationships. Our method relies on amino acid occurrence matrices, one for each PB, to score global and local threading of query amino acid sequences to protein folds encoded into PB sequences. It does not use any information from residue contacts or sequence-search methods or explicit incorporation of hydrophobic effect. The performance of the method was assessed with independent test datasets derived from SCOP 1.75A. With a Z-score cutoff that achieved 95% specificity (i.e., less than 5% false positives), global and local threading showed sensitivity of 64.1% and 34.2%, respectively. We further tested its performance on 57 difficult CASP10 targets that had no known homologs in PDB: 38 compatible templates were identified by our approach and 66% of these hits yielded correctly predicted structures. This method scales-up well and offers promising perspectives for structural annotations at genomic level. It has been implemented in the form of a web-server that is freely available at http://www.bo-protscience.fr/forsa.

Molecular characterization of Trimeresurus stejnegeri venom L-amino acid oxidase with potential anti-HIV activity

A novel L-amino acid oxidase, named TSV-LAO, has been purified and cloned from the snake Trimeresurus stejnegeri. Fifty percentage cytotoxic concentrations (CC50) of TSV-LAO on C8166 cells were 24 and 390 nM in the absence or presence of catalase (400nM), respectively. However, at concentrations that showed little effect on cell viability, TSV-LAO displayed dose dependent inhibition on HIV-1 infection and replication. The antiviral selectivity indexes (CC50/EC50) were 16 and 6, respectively, corresponding to the measurements of syncytium formation and HIV-1 p24 antigen expression. Interestingly, the presence of catalase resulted in an increase of its antiviral selectivity to 52 and 38. Under the same conditions, no anti-HIV-1 activity was observed by exogenous addition of H2O2. The complete amino acid sequence of TSV-LAO, as deduced from its cDNA, exhibits a high degree of sequence identity with other snake venom LAOs. (C) 2003 Elsevier Inc. All rights reserved.

The four major N- and C-terminal splice variants of the excitatory amino acid transporter GLT-1 form cell surface homomeric and heteromeric assemblies

The L-glutamate transporter GLT-1 is an abundant CNS membrane protein of the excitatory amino acid transporter (EAAT) family which controls extracellular L-glutamate levels and is important in limiting excitotoxic neuronal death. Using RT-PCR, we have determined that four mRNAs encoding GLT-1 exist in mouse brain, with the potential to encode four GLT-1 isoforms that differ in their N- and C-termini. We expressed all four isoforms (termed MAST-KREK, MPK-KREK, MAST-DIETCI and MPK-DIETCI according to amino acid sequence) in a range of cell lines and primary astrocytes and show that each isoform can reach the cell surface. In transfected HEK-293 or COS-7 cells, all four isoforms support high-affinity sodium-dependent L-glutamate uptake with identical pharmacological and kinetic properties. Inserting a viral epitope (V5, HA or FLAG) into the second extracellular domain of each isoform allowed co-immunoprecipitation and tr-FRET studies using transfected HEK-293 cells. Here we show for the first time that each of the four isoforms are able to combine to form homomeric and heteromeric assemblies, each of which are expressed at the cell surface of primary astrocytes. After activation of protein kinase C by phorbol ester, V5-tagged GLT-1 is rapidly removed from the cell surface of HEK-293 cells and degraded. This study provides direct biochemical evidence for oligomeric assembly of GLT-1 and reports the development of novel tools to provide insight into the trafficking of GLT-1.

IntFOLD: an integrated server for modelling protein structures and functions from amino acid sequences

IntFOLD is an independent web server that integrates our leading methods for structure and function prediction. The server provides a simple unified interface that aims to make complex protein modelling data more accessible to life scientists. The server web interface is designed to be intuitive and integrates a complex set of quantitative data, so that 3D modelling results can be viewed on a single page and interpreted by non-expert modellers at a glance. The only required input to the server is an amino acid sequence for the target protein. Here we describe major performance and user interface updates to the server, which comprises an integrated pipeline of methods for: tertiary structure prediction, global and local 3D model quality assessment, disorder prediction, structural domain prediction, function prediction and modelling of protein-ligand interactions. The server has been independently validated during numerous CASP (Critical Assessment of Techniques for Protein Structure Prediction) experiments, as well as being continuously evaluated by the CAMEO (Continuous Automated Model Evaluation) project. The IntFOLD server is available at: http://www.reading.ac.uk/bioinf/IntFOLD/

Critical role for an acidic amino acid region in platelet signaling by the HemITAM (hemi-immunoreceptor tyrosine-based activation motif) containing receptor CLEC-2 (C-type lectin receptor-2)

CLEC-2 is a member of new family of C-type lectin receptors characterized by a cytosolic YXXL downstream of three acidic amino acids in a sequence known as a hemITAM (hemi-immunoreceptor tyrosine-based activation motif). Dimerization of two phosphorylated CLEC-2 molecules leads to recruitment of the tyrosine kinase Syk via its tandem SH2 domains and initiation of a downstream signaling cascade. Using Syk-deficient and Zap-70-deficient cell lines we show that hemITAM signaling is restricted to Syk and that the upstream triacidic amino acid sequence is required for signaling. Using surface plasmon resonance and phosphorylation studies, we demonstrate that the triacidic amino acids are required for phosphorylation of the YXXL. These results further emphasize the distinct nature of the proximal events in signaling by hemITAM relative to ITAM receptors.

Antibacterial and antiparasitic effects of Bothrops marajoensis venom and its fractions: Phospholipase A(2) and L-amino acid oxidase

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)