Adaptive feature thresholding for off-line signature verification

This paper introduces Adaptive Feature Thresholding (AFT) which is a novel method of person-dependent off-line signature verification. AFT enhances how a simple image feature of a signature is converted to a binary feature vector by significantly improving its representation in relation to the training signatures. The similarity between signatures is then easily computed from their corresponding binary feature vectors. AFT was tested on the CEDAR and GPDS benchmark datasets, with classification using either a manual or an automatic variant. On the CEDAR dataset we achieved a classification accuracy of 92% for manual and 90% for automatic, while on the GPDS dataset we achieved over 87% and 85% respectively. For both datasets AFT is less complex and requires fewer images features than the existing state of the art methods, while achieving competitive results

Rubredoxin Variant Folds without Iron

Pyroccocus furiosus rubredoxin (PFRD), like most studied hyperthermophilic proteins, does not undergo reversible folding. The irreversibility of folding is thought to involve PFRD’s iron-binding site. Here we report a PFRD variant (PFRD-XC4) whose iron binding site was redesigned to eliminate iron binding using a computational design algorithm. PFRD-XC4 folds without iron and exhibits reversible folding with a melting temperature of 82 °C, a thermodynamic stability of 3.2 kcal mol^(-1) at 1 °C, and NMR chemical shifts similar to that of the wild-type protein. This variant should provide a tractable model system for studying the thermodynamic origins of protein hyperthermostability

Evaluating and optimizing computational protein design force fields using fixed composition-based negative design

An accurate force field is essential to computational protein design and protein fold prediction studies. Proper force field tuning is problematic, however, due in part to the incomplete modeling of the unfolded state. Here, we evaluate and optimize a protein design force field by constraining the amino acid composition of the designed sequences to that of a well behaved model protein. According to the random energy model, unfolded state energies are dependent only on amino acid composition and not the specific arrangement of amino acids. Therefore, energy discrepancies between computational predictions and experimental results, for sequences of identical composition, can be directly attributed to flaws in the force field's ability to properly account for folded state sequence energies. This aspect of fixed composition design allows for force field optimization by focusing solely on the interactions in the folded state. Several rounds of fixed composition optimization of the 56-residue β1 domain of protein G yielded force field parameters with significantly greater predictive power: Optimized sequences exhibited higher wild-type sequence identity in critical regions of the structure, and the wild-type sequence showed an improved Z-score. Experimental studies revealed a designed 24-fold mutant to be stably folded with a melting temperature similar to that of the wild-type protein. Sequence designs using engrailed homeodomain as a scaffold produced similar results, suggesting the tuned force field parameters were not specific to protein G

Polar residues in the protein core of Escherichia coli thioredoxin are important for fold specificity

Most globular proteins contain a core of hydrophobic residues that are inaccessible to solvent in the folded state. In general, polar residues in the core are thermodynamically unfavorable except when they are able to form intramolecular hydrogen bonds. Compared to hydrophobic interactions, polar interactions are more directional in character and may aid in fold specificity. In a survey of 263 globular protein structures, we found a strong positive correlation between the number of polar residues at core positions and protein size. To probe the importance of buried polar residues, we experimentally tested the effects of hydrophobic mutations at the five polar core residues in Escherichia coli thioredoxin. Proteins with single hydrophobic mutations (D26I, C32A, C35A, T66L, and T77V) all have cooperative unfolding transitions like the wild type (wt), as determined by chemical denaturation. Relative to wt, D26I is more stable while the other point mutants are less stable. The combined 5-fold mutant protein (IAALV) is less stable than wt and has an unfolding transition that is substantially less cooperative than that of wt. NMR spectra as well as amide deuterium exchange indicate that IAALV is likely sampling a number of low-energy structures in the folded state, suggesting that polar residues in the core are important for specifying a well-folded native structure

Ocean color algorithm for remote sensing of chlorophyll

An algorithm for the remote detection of chlorophyll a in the ocean was tested during a Nantucket Shoals experiment conducted by NASA. A set of Multichannel Ocean Color Sensor (MOCS) data selected from one flight for each of the two altitudes flown was used to calibrate the algorithm for chlorophyll a concentration. The equations were then applied to all unsaturated MOCS data collected during the 8-day experiment to generate contour maps of chlorophyll a concentration over the shoals. One additional flight was conducted away from the shoals both on and off the Continental Shelf. Although no solar elevation or environmental corrections were made to the original conversions, the equations in these tests determined chlorophyll a concentrations to an accuracy better than 1.0 micron g/L despite the fact that the solar elevation varied between 20 deg and 56 deg during the data collection periods of the experiments