1,721,070 research outputs found
PIGS: a resource for immunoglobulin structure prediction
Pigs (http://arianna.bio.uniroma1.it/pigs) is a web server for the automatic modeling of immunoglobulin
variable domains based on the canonical structure method. It has a user-friendly and flexible interface,
that allows the user to choose templates (for the frameworks and the loops) and modeling strategies in
an automatic or manual fashion. Its final output is a complete three-dimensional model of the target
antibody that can be downloaded or displayed on-line. The server is freely accessible to academic users,
with no restriction on the number of submitted sequences
Tabhu: tools for antibody humanization.
Antibodies are rapidly becoming essential tools in the clinical practice, given their ability to recognize their cognate antigens with high specificity and affinity, and a high yield at reasonable costs in model animals. Unfortunately, when administered to human patients, xenogeneic antibodies can elicit unwanted and dangerous immunogenic responses. Antibody humanization methods are designed to produce molecules with a better safety profile still maintaining their ability to bind the antigen. This can be accomplished by grafting the non-human regions determining the antigen specificity into a suitable human template. Unfortunately, this procedure may results in a partial or complete loss of affinity of the grafted molecule that can be restored by back-mutating some of the residues of human origin to the corresponding murine ones. This trial-and-error procedure is hard and involves expensive and time-consuming experiments. Here we present tools for antibody humanization (Tabhu) a web server for antibody humanization. Tabhu includes tools for human template selection, grafting, back-mutation evaluation, antibody modelling and structural analysis, helping the user in all the critical steps of the humanization experiment protocol
PIGS: automatic prediction of antibody structures
We describe a web server for the automatic prediction of immunoglobulin variable domains based on the canonical structure model. The server is user-friendly and flexible. It allows the user to select the templates for the frameworks and the loops using different strategies. The final output is a full-fledged 3D model of the variable domains of the target immunoglobulin
The MoVIN server for the analysis of protein interaction networks
Abstract Background Protein-protein interactions are at the basis of most cellular processes and crucial for many bio-technological applications. During the last few years the development of high-throughput technologies has produced several large-scale protein-protein interaction data sets for various organisms. It is important to develop tools for dissecting their content and analyse the information they embed by data-integration and computational methods. Results Interactions can be mediated by the presence of specific features, such as motifs, surface patches and domains. The co-occurrence of these features on proteins interacting with the same protein can indicate mutually exclusive interactions and, therefore, can be used for inferring the involvement of the proteins in common biological processes. We present here a publicly available server that allows the user to investigate protein interaction data in light of other biological information, such as their sequences, presence of specific domains, process and component ontologies. The server can be effectively used to construct a high-confidence set of mutually exclusive interactions by identifying similar features in groups of proteins sharing a common interaction partner. As an example, we describe here the identification of common motifs, function, cellular localization and domains in different datasets of yeast interactions. Conclusions The server can be used to analyse user-supplied datasets, it contains pre-processed data for four yeast Protein Protein interaction datasets and the results of their statistical analysis. These show that the presence of common motifs in proteins interacting with the same partner is a valuable source of information, it can be used to investigate the properties of the interacting proteins and provides information that can be effectively integrated with other sources. As more experimental interaction data become available, this tool will become more and more useful to gain a more detailed picture of the interactome.</p
PICMI: mapping point mutations on genomes
Motivation: Several international collaborations and local projects are producing extensive catalogues of genomic variations that are supplementing existing collections such as the OMIM catalogue. The flood of this type of data will keep increasing and, especially, it will be relevant to a wider user base, including not only molecular biologists, geneticists and bioinformaticians, but also clinical researchers. Mapping the observed variations, sometimes only described at the amino acid level, on a genome, identifying whether they affect a gene and-if so-whether they also affect different isoforms of the same gene, is a time consuming and often frustrating task. Results: The PICMI server is an easy to use tool for quickly mapping one or more amino acid or nucleotide variations on a genome and its products, including alternatively spliced isoforms
The association of heavy and light chain variable domains in antibodies: implications for antigen specificity.
The antigen-binding site of immunoglobulins is formed by six regions, three from the light and three from the heavy chain variable domains, which, on association of the two chains, form the conventional antigen-binding site of the antibody. The mode of interaction between the heavy and light chain variable domains affects the relative position of the antigen-binding loops and therefore has an effect on the overall conformation of the binding site. In this article, we analyze the structure of the interface between the heavy and light chain variable domains and show that there are essentially two different modes for their interaction that can be identified by the presence of key amino acids in specific positions of the antibody sequences. We also show that the different packing modes are related to the type of recognized antigen
A database of immunoglobulins with integrated tools: DIGIT
The DIGIT (Database of ImmunoGlobulins with Integrated Tools) database (http://biocomputing.it/digit) is an integrated resource storing sequences of annotated immunoglobulin variable domains and enriched with tools for searching and analyzing them. The annotations in the database include information on the type of antigen, the respective germline sequences and on pairing information between light and heavy chains. Other annotations, such as the identification of the complementarity determining regions, assignment of their structural class and identification of mutations with respect to the germline, are computed on the fly and can also be obtained for user-submitted sequences. The system allows customized BLAST searches and automatic building of 3D models of the domains to be performed
Structural repertoire of immunoglobulin λ light chains
The immunoglobulin λ isotype is present in nearly all vertebrates and plays an important role in the human immune system. Despite its importance, few systematic studies have been performed to analyze the structural conformation of its variable regions, contrary to what is the case for κ and heavy chains. We show here that an analysis of the structures of λ chains allows the definition of a discrete set of recurring conformations (canonical structures) of their hypervariable loops and, most importantly, the identification of sequence constraints that can be used to predict their structure. We also show that the structural repertoire of λ chains is different and more varied than that of the κ chains, consistently with the current view of the involvement of the two major light-chain families in complementary strategies of the immune system to ensure a fine tuning between diversity and stability in antigen recognition. © 2011 Wiley-Liss, Inc
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