TOPCONS: consensus prediction of membrane protein topology

TOPCONS (http://topcons.net/) is a web server for consensus prediction of membrane protein topology. The underlying algorithm combines an arbitrary number of topology predictions into one consensus prediction and quantifies the reliability of the prediction based on the level of agreement between the underlying methods, both on the protein level and on the level of individual TM regions. Benchmarking the method shows that overall performance levels match the best available topology prediction methods, and for sequences with high reliability scores, performance is increased by ∼10 percentage points. The web interface allows for constraining parts of the sequence to a known inside/outside location, and detailed results are displayed both graphically and in text format

Hastings-Levitov aggregation in the small-particle limit

We establish some scaling limits for a model of planar aggregation. The model is described by the composition of a sequence of independent and identically distributed random conformal maps, each corresponding to the addition of one particle. We study the limit of small particle size and rapid aggregation. The process of growing clusters converges, in the sense of Caratheodory, to an inflating disc. A more refined analysis reveals, within the cluster, a tree structure of branching fingers, whose radial component increases deterministically with time. The arguments of any finite sample of fingers, tracked inwards, perform coalescing Brownian motions. The arguments of any finite sample of gaps between the fingers, tracked outwards, also perform coalescing Brownian motions. These properties are closely related to the evolution of harmonic measure on the boundary of the cluster, which is shown to converge to the Brownian web

An Expressive Robotic Table to Enhance Social Interactions

We take initial steps into prototyping an expressive robotic table that can serve as a social mediator. The work is constructed through a rapid prototyping process consisting of five workshopbased phases with five interaction design participants. We report on the various prototyping techniques that led to the generated concept of an expressive robotic table. Our design process explores how expressive motion cues such as respiratory movements can be leveraged to mediate social interactions between people in cold outdoor environments. We conclude by discussing the implications of the different prototyping methods applied and the envisioned future directions of the work within the scope of expressive robotics

Transmembrane protein topology prediction using support vector machines

Background: Alpha-helical transmembrane (TM) proteins are involved in a wide range of important biological processes such as cell signaling, transport of membrane-impermeable molecules, cell-cell communication, cell recognition and cell adhesion. Many are also prime drug targets, and it has been estimated that more than half of all drugs currently on the market target membrane proteins. However, due to the experimental difficulties involved in obtaining high quality crystals, this class of protein is severely under-represented in structural databases. In the absence of structural data, sequence-based prediction methods allow TM protein topology to be investigated.Results: We present a support vector machine-based (SVM) TM protein topology predictor that integrates both signal peptide and re-entrant helix prediction, benchmarked with full cross-validation on a novel data set of 131 sequences with known crystal structures. The method achieves topology prediction accuracy of 89%, while signal peptides and re-entrant helices are predicted with 93% and 44% accuracy respectively. An additional SVM trained to discriminate between globular and TM proteins detected zero false positives, with a low false negative rate of 0.4%. We present the results of applying these tools to a number of complete genomes. Source code, data sets and a web server are freely available from http://bioinf.cs.ucl.ac.uk/psipred/.Conclusion: The high accuracy of TM topology prediction which includes detection of both signal peptides and re-entrant helices, combined with the ability to effectively discriminate between TM and globular proteins, make this method ideally suited to whole genome annotation of alpha-helical transmembrane proteins

IgTM: An algorithm to predict transmembrane domains and topology in proteins

<p>Abstract</p> <p>Background</p> <p>Due to their role of receptors or transporters, membrane proteins play a key role in many important biological functions. In our work we used Grammatical Inference (GI) to localize transmembrane segments. Our GI process is based specifically on the inference of Even Linear Languages.</p> <p>Results</p> <p>We obtained values close to 80% in both specificity and sensitivity. Six datasets have been used for the experiments, considering different encodings for the input sequences. An encoding that includes the topology changes in the sequence (from inside and outside the membrane to it and vice versa) allowed us to obtain the best results. This software is publicly available at: <url>http://www.dsic.upv.es/users/tlcc/bio/bio.html</url></p> <p>Conclusion</p> <p>We compared our results with other well-known methods, that obtain a slightly better precision. However, this work shows that it is possible to apply Grammatical Inference techniques in an effective way to bioinformatics problems.</p

A comprehensive assessment of N-terminal signal peptides prediction methods

Background: Amino-terminal signal peptides (SPs) are short regions that guide the targeting of secretory proteins to the correct subcellular compartments in the cell. They are cleaved off upon the passenger protein reaching its destination. The explosive growth in sequencing technologies has led to the deposition of vast numbers of protein sequences necessitating rapid functional annotation techniques, with subcellular localization being a key feature. Of the myriad software prediction tools developed to automate the task of assigning the SP cleavage site of these new sequences, we review here, the performance and reliability of commonly used SP prediction tools. Results: The available signal peptide data has been manually curated and organized into three datasets representing eukaryotes, Gram-positive and Gram-negative bacteria. These datasets are used to evaluate thirteen prediction tools that are publicly available. SignalP (both the HMM and ANN versions) maintains consistency and achieves the best overall accuracy in all three benchmarking experiments, ranging from 0.872 to 0.914 although other prediction tools are narrowing the performance gap. Conclusion: The majority of the tools evaluated in this study encounter no difficulty in discriminating between secretory and non-secretory proteins. The challenge clearly remains with pinpointing the correct SP cleavage site. The composite scoring schemes employed by SignalP may help to explain its accuracy. Prediction task is divided into a number of separate steps, thus allowing each score to tackle a particular aspect of the prediction.12 page(s

Characterization of Leishmania donovani Aquaporins Shows Presence of Subcellular Aquaporins Similar to Tonoplast Intrinsic Proteins of Plants

Leishmania donovani, a protozoan parasite, resides in the macrophages of the mammalian host. The aquaporin family of proteins form important components of the parasite-host interface. The parasite-host interface could be a potential target for chemotherapy. Analysis of L. major and L. infantum genomes showed the presence of five aquaporins (AQPs) annotated as AQP9 (230aa), AQP putative (294aa), AQP-like protein (279aa), AQP1 (314aa) and AQP-like protein (596aa). We report here the structural modeling, localization and functional characterization of the AQPs from L. donovani. LdAQP1, LdAQP9, LdAQP2860 and LdAQP2870 have the canonical NPA-NPA motifs, whereas LdAQP putative has a non-canonical NPM-NPA motif. In the carboxyl terminal to the second NPA box of all AQPs except AQP1, a valine/alanine residue was found instead of the arginine. In that respect these four AQPs are similar to tonoplast intrinsic proteins in plants, which are localized to intracellular organelles. Confocal microscopy of L. donovani expressing GFP-tagged AQPs showed an intracellular localization of LdAQP9 and LdAQP2870. Real-time PCR assays showed expression of all aquaporins except LdAQP2860, whose level was undetectable. Three-dimensional homology modeling of the AQPs showed that LdAQP1 structure bears greater topological similarity to the aquaglyceroporin than to aquaporin of E. coli. The pore of LdAQP1 was very different from the rest in shape and size. The cavity of LdAQP2860 was highly irregular and undefined in geometry. For functional characterization, four AQP proteins were heterologously expressed in yeast. In the fps1Δ yeast cells, which lacked the key aquaglyceroporin, LdAQP1 alone displayed an osmosensitive phenotype indicating glycerol transport activity. However, expression of LdAQP1 and LdAQP putative in a yeast gpd1Δ strain, deleted for glycerol production, conferred osmosensitive phenotype indicating water transport activity or aquaporin function. Our analysis for the first time shows the presence of subcellular aquaporins and provides structural and functional characterization of aquaporins in Leishmania donovani