Mass spectrometry is the main analytical technique currently used to address the challenges of glycomics as it offers unrivalled levels of sensitivity and the ability to handle complex mixtures of different glycan variations. Determination of glycan structures from analysis of MS data is a major bottleneck in high-throughput glycomics projects, and robust solutions to this problem are of critical importance. However, all the approaches currently available have inherent restrictions to the type of glycans they can identify and none of them has proved to be a definitive tool for glycomics.GlycoWorkbench is a software tool developed by the EUROCarbDB initiative to assist the manual interpretation of MS data. The main task of GlycoWorkbench is to evaluate a set of structures proposed by the user by matching the corresponding theoretical list of fragment masses against the list of peaks derived from the spectrum. The tool provides an easy to use graphical interface, a comprehensive and increasing set of structural constituents, an exhaustive collection of fragmentation types, and a broad list of annotation options. The aim of GlycoWorkbench is to offer complete support for the routine interpretation of MS data. The software is available for download from: http://www.eurocarbdb.org/applications/ms-tools.

DISULFIND is a server for predicting the disulfide bonding state of cysteines and their disulfide connectivity starting from sequence alone. Optionally, disulfide connectivity can be predicted from sequence and a bonding state assignment given as input. The output is a simple visualization of the assigned bonding state (with confidence degrees) and the most likely connectivity patterns. The server is available at .

During the EUROCarbDB project our group developed the GlycanBuilder and GlycoWorkbench glycoinformatics tools. This short communication summarizes the capabilities of these two tools and updates which have been made since the original publications in 2007 and 2008. GlycanBuilder is a tool that allows for the fast and intuitive drawing of glycan structures; this tool can be used standalone, embedded in web pages and can also be integrated into other programs. GlycoWorkbench has been designed to semi-automatically annotate glycomics data. This tool can be used to annotate mass spectrometry (MS) and MS/MS spectra of free oligosaccharides, N and O-linked glycans, GAGs (glycosaminoglycans) and glycolipids, as well as MS spectra of glycoproteins.

Accurate predictions of metal-binding sites in proteins by using sequence as the only source of information can significantly help in the prediction of protein structure and function, genome annotation, and in the experimental determination of protein structure. Here, we introduce a method for identifying histidines and cysteines that participate in binding of several transition metals and iron complexes. The method predicts histidines as being in either of two states (free or metal bound) and cysteines in either of three states (free, metal bound, or in disulfide bridges). The method uses only sequence information by utilizing position-specific evolutionary profiles as well as more global descriptors such as protein length and amino acid composition. Our solution is based on a two-stage machine-learning approach. The first stage consists of a support vector machine trained to locally classify the binding state of single histidines and cysteines. The second stage consists of a bidirectional recurrent neural network trained to refine local predictions by taking into account dependencies among residues within the same protein. A simple finite state automaton is employed as a postprocessing in the second stage in order to enforce an even number of disulfide-bonded cysteines. We predict histidines and cysteines in transition-metal-binding sites at 73% precision and 61% recall. We observe significant differences in performance depending on the ligand (histidine or cysteine) and on the metal bound. We also predict cysteines participating in disulfide bridges at 86% precision and 87% recall. Results are compared to those that would be obtained by using expert information as represented by PROSITE motifs and, for disulfide bonds, to state-of-the-art methods.