Background: The accuracy of protein secondary structure prediction has steadily improved over the past 30 years. Now many secondary structure prediction methods routinely achieve an accuracy (Q3) of about 75%. We believe this accuracy could be further improved by including structure (as opposed to sequence) database comparisons as part of the prediction process. Indeed, given the large size of the Protein Data Bank (>35,000 sequences), the probability of a newly identified sequence having a structural homologue is actually quite high.Results: We have developed a method that performs structure-based sequence alignments as part of the secondary structure prediction process. By mapping the structure of a known homologue (sequence ID >25%) onto the query protein's sequence, it is possible to predict at least a portion of that query protein's secondary structure. By integrating this structural alignment approach with conventional (sequence-based) secondary structure methods and then combining it with a "jury-of-experts" system to generate a consensus result, it is possible to attain very high prediction accuracy. Using a sequence-unique test set of 1644 proteins from EVA, this new method achieves an average Q3 score of 81.3%. Extensive testing indicates this is approximately 4–5% better than any other method currently available. Assessments using non sequence-unique test sets (typical of those used in proteome annotation or structural genomics) indicate that this new method can achieve a Q3 score approaching 88%.Conclusion: By using both sequence and structure databases and by exploiting the latest techniques in machine learning it is possible to routinely predict protein secondary structure with an accuracy well above 80%. A program and web server, called PROTEUS, that performs these secondary structure predictions is accessible athttp://wishart.biology.ualberta.ca/proteus. For high throughput or batch sequence analyses, the PROTEUS programs, databases (and server) can be downloaded and run locally.

The cadherins are major mediators of calcium-dependent cell-cell adhesion and are also involved in cell signaling pathways during development. The classical cadherins, which are the definitive group of the cadherin superfamily, are transmembrane proteins that consist of an extracellular domain of five cadherin repeats, including an HAV tripeptide conserved in one binding surface within the first domain, and a highly conserved cytoplasmic domain that interacts with the actin cytoskeleton via the catenin proteins. These cadherins play major roles in vertebrate morphogenesis; they are expressed widely throughout development, antibodies to specific cadherins perturb a variety of developmental processes, and many gene knockouts are lethal at early stages of development. Phylogenetic analysis of the "classical" cadherins shows that in the vertebrates there are four paralog families. The rate of evolutionary change is radically different between the different paralogs, indicating that there are significantly different selection pressures on the functions of the various cadherins, both between the different paralogs in a single organism lineage and between different organism lineages within a single paralog family. There is also evidence for gene conversion between the E-cadherin and P-cadherin paralogs in Gallus gallus and possibly Xenopus laevis, but not between the same paralogs in the mammalian lineages. A scheme for the origin of the paralogs within the vertebrate lineage based on these analyses indicates that the presence of the four paralog families is a characteristic of vertebrates and that variation of cadherin structure and function is a significant factor in morphological evolution of vertebrates.

Biological data sets are increasingly becoming information-dense, making it effective to use a computer science-based analysis. We used convolution neural networks (CNN) and the specific CNN architecture Unet to study sponge behavior over time. We analyzed a large time series of hourly high-resolution still images of a marine sponge, Suberites concinnus (Demospongiae, Suberitidae) captured between 2012 and 2015 using the NEPTUNE seafloor cabled observatory, off the west coast of Vancouver Island, Canada. We applied semantic segmentation with the Unet architecture with some modifications, including adapting parts of the architecture to be more applicable to three-channel images (RGB). Some alterations that made this model successful were the use of a dice-loss coefficient, Adam optimizer and a dropout function after each convolutional layer which provided losses, accuracies and dice scores of up to 0.03, 0.98 and 0.97, respectively. The model was tested with five-fold cross-validation. This study is a first step towards analyzing trends in the behavior of a demosponge in an environment that experiences severe seasonal and inter-annual changes in climate. The end objective is to correlate changes in sponge size (activity) over seasons and years with environmental variables collected from the same observatory platform. Our work provides a roadmap for others who seek to cross the interdisciplinary boundaries between biology and computer science.

The classical cadherins, definitive proteins of the cadherin superfamily, are characterized functionally by their ability to mediate calcium-dependent cell aggregation in vitro. To test hypothetical mechanisms of adhesion, we have constructed two mutants of the chicken E-cadherin protein, one with the highly conserved His-Ala-Val (HAV) sequence motif reversed to Val-Ala-His (VAH), the other lacking the first extracellular domain (EC1). The inversion of HAV to VAH has no effect on the capacity of E-cadherin to mediate adhesion. Deletion of EC1 completely eliminates the ability of E-cadherin to mediate homophilic adhesion, but the deletion mutant is capable of adhering heterophilically to both unmutated E-cadherin and to the HAV/VAH mutant. These results demonstrate that the conserved HAV sequence motif is not involved in cadherin-mediated adhesion as has been suggested previously and supports the idea that in the context of the cell surface, cadherin-mediated cell-cell adhesion involves an interaction of EC1 with other domains of the cadherin extracellular moiety and not the "linear zipper" model, which posits trans interactions only between EC1 on apposing cell surfaces.

The family of voltage-gated potassium channels comprises a functionally diverse group of membrane proteins. They help maintain and regulate the potassium ion-based component of the membrane potential and are thus central to many critical physiological processes. VKCDB (V oltage-gated potassium [K] C hannel D ataB ase) is a database of structural and functional data on these channels. It is designed as a resource for research on the molecular basis of voltage-gated potassium channel function. Voltage-gated potassium channel sequences were identified by using BLASTP to search GENBANK and SWISSPROT. Annotations for all voltage-gated potassium channels were selectively parsed and integrated into VKCDB. Electrophysiological and pharmacological data for the channels were collected from published journal articles. Transmembrane domain predictions by TMHMM and PHD are included for each VKCDB entry. Multiple sequence alignments of conserved domains of channels of the four Kv families and the KCNQ family are also included. Currently VKCDB contains 346 channel entries. It can be browsed and searched using a set of functionally relevant categories. Protein sequences can also be searched using a local BLAST engine. VKCDB is a resource for comparative studies of voltage-gated potassium channels. The methods used to construct VKCDB are general; they can be used to create specialized databases for other protein families. VKCDB is accessible at http://vkcdb.biology.ualberta.ca .