Removal of the N-linked glycan structure from the peanut peroxidase prxPNC2: Influence on protein stability and activity

Lines of transgenic tobacco have been generated that are transformed with either the wild-type peanut peroxidase prxPNC2 cDNA, driven by the CaMV3 5S promoter (designated 35S::prxPNC2-WT) or a mutated PNC2 cDNA in which the asparagine residue (Asn(189)) associated with the point of glycan attachment (Asn(189)) has been replaced with alanine (designated 35S::prxPNC2-M). PCR, using genomic DNA as template, has confirmed the integration of the 35S::prxPNC2-WT and 35::prxPNC2-M constructs into the tobacco genome, and western analysis using anti-PNC2 antibodies has revealed that the prxPNC2-WT protein product (PNC2-WT) accumulates with a molecular mass of 34,670 Da, while the prxPNC2-M protein product (PNC2-M) accumulates with a molecular mass of 32,600 Da. Activity assays have shown that both PNC2-WT and PNC2-M proteins accumulate preferentially in the ionically-bound cell wall fraction, with a significantly higher relative accumulation of the PNC2-WT isoenzyme in the ionically-bound fraction when compared with the PNC2-M isoform. Kinetic analysis of the partially purified PNC2-WT isozyme revealed an affinity constant (apparent K-m) of 11.2 mM for the reductor substrate guaiacol and 1.29 mM for H2O2, while values of 11.9 mM and 1.12 mM were determined for the PNC2-M isozyme. A higher Arrenhius activation energy (E,,) was determined for the PNC2-M isozyme (22.9 kJ mol(-1)), when compared with the PNC2-WT isozyme (17.6 kJ mol(-1)), and enzyme assays have determined that the absence of the glycan influences the thermostability of the PNC2-M isozyme. These results are discussed with respect to the proposed roles of N-linked glycans attached to plant peroxidases. (c) 2005 Elsevier Ltd. All rights reserved.

The 2.1 angstrom crystal structure of copGFP, a representative member of the copepod clade within the green fluorescent protein superfamily

The green fluorescent protein (avGFP), its variants, and the closely related GFP-like proteins are characterized structurally by a cyclic tri-peptide chromophore located centrally within a conserved beta-can fold. Traditionally, these GFP family members have been isolated from the Cnidaria although recently, distantly related GFP-like proteins from the Bilateria, a sister group of the Cnidaria have been described, although no representative structure from this phylum has been reported to date. We have determined to 2.1 angstrom resolution the crystal structure of copGFP, a representative GFP-like protein from a copepod, a member of the Bilateria. The structure of copGFP revealed that, despite sharing only 19% sequence identity with GFP, the tri-peptide chromophore (Gly57-Tyr58-Gly59) of copGFP adopted a cis coplanar conformation within the conserved beta-can fold. However, the immediate environment surrounding the chromophore of copGFP was markedly atypical when compared to other members of the GFP-superfamily, with a large network of bulky residues observed to surround the chromophore. Arg87 and Glu222 (GFP numbering 96 and 222), the only two residues conserved between copGFP, GFP and GFP-like proteins are involved in autocatalytic genesis of the chromophore. Accordingly, the copGFP structure provides an alternative platform for the development of a new suite of fluorescent protein tools. Moreover, the structure suggests that the autocatalytic genesis of the chromophore is remarkably tolerant to a high degree of sequence and structural variation within the beta-can fold of the GFP superfamily. (c) 2006 Elsevier Ltd . All rights reserved.

First- and second-order stimulus length selectivity in New World monkey striate cortex

Motion is a powerful cue for figure-ground segregation, allowing the recognition of shapes even if the luminance and texture characteristics of the stimulus and background are matched. In order to investigate the neural processes underlying early stages of the cue-invariant processing of form, we compared the responses of neurons in the striate cortex (V1) of anaesthetized marmosets to two types of moving stimuli: bars defined by differences in luminance, and bars defined solely by the coherent motion of random patterns that matched the texture and temporal modulation of the background. A population of form-cue-invariant (FCI) neurons was identified, which demonstrated similar tuning to the length of contours defined by first- and second-order cues. FCI neurons were relatively common in the supragranular layers (where they corresponded to 28% of the recorded units), but were absent from layer 4. Most had complex receptive fields, which were significantly larger than those of other V1 neurons. The majority of FCI neurons demonstrated end-inhibition in response to long first- and second-order bars, and were strongly direction selective, Thus, even at the level of V1 there are cells whose variations in response level appear to be determined by the shape and motion of the entire second-order object, rather than by its parts (i.e. the individual textural components). These results are compatible with the existence of an output channel from V1 to the ventral stream of extrastriate areas, which already encodes the basic building blocks of the image in an invariant manner.

Predicting residue-wise contact orders in proteins by support vector regression

Background: The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results: We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion: The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

Spatially localized distortions of event time

A fundamental question about the perception of time is whether the neural mechanisms underlying temporal judgements are universal and centralized in the brain or modality specific and distributed []. Time perception has traditionally been thought to be entirely dissociated from spatial vision. Here we show that the apparent duration of a dynamic stimulus can be manipulated in a local region of visual space by adapting to oscillatory motion or flicker. This implicates spatially localized temporal mechanisms in duration perception. We do not see concomitant changes in the time of onset or offset of the test patterns, demonstrating a direct local effect on duration perception rather than an indirect effect on the time course of neural processing. The effects of adaptation on duration perception can also be dissociated from motion or flicker perception per se. Although 20 Hz adaptation reduces both the apparent temporal frequency and duration of a 10 Hz test stimulus, 5 Hz adaptation increases apparent temporal frequency but has little effect on duration perception. We conclude that there is a peripheral, spatially localized, essentially visual component involved in sensing the duration of visual events.

Refactoring object-z specifications

Object-Z offers an object-oriented means for structuring formal specifications. We investigate the application of refactoring rules to add and remove structure from such specifications to forge object-oriented designs. This allows us to tractably move from an abstract functional description of a system toward a lower-level design suitable for implementation on an object-oriented platform.

Predicting structural disruption of proteins caused by crossover

We present a machine learning model that predicts a structural disruption score from a protein’s primary structure. SCHEMA was introduced by Frances Arnold and colleagues as a method for determining putative recombination sites of a protein on the basis of the full (PDB) description of its structure. The present method provides an alternative to SCHEMA that is able to determine the same score from sequence data only. Circumventing the need for resolving the full structure enables the exploration of yet unresolved and even hypothetical sequences for protein design efforts. Deriving the SCHEMA score from a primary structure is achieved using a two step approach: first predicting a secondary structure from the sequence and then predicting the SCHEMA score from the predicted secondary structure. The correlation coefficient for the prediction is 0.88 and indicates the feasibility of replacing SCHEMA with little loss of precision. ©2005 IEEE