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Biomedical subjects

Gabriele Ausiello

Publications and source records attributed to Gabriele Ausiello.

8 recordsLinked to original sources

Phospho3D: a database of three-dimensional structures of protein phosphorylation sites.

Phosphorylation is the most common protein post-translational modification. Phosphorylated residues (serine, threonine and tyrosine) play critical roles in the regulation of many cellular processes. Since the amount of data produced by screening assays is growing continuously, the development of computational tools for collecting and analysing experimental data has become a pivotal task for unravelling the complex network of interactions regulating eukaryotic cell life. Here we present Phospho3D, http://cbm.bio.uniroma2.it/phospho3d, a database of 3D structures of phosphorylation sites, which stores information retrieved from the phospho.ELM database and is enriched with structural information and annotations at the residue level. The database also collects the results of a large-scale structural comparison procedure providing clues for the identification of new putative phosphorylation sites.

Databases, Protein↗

A neural strategy for the inference of SH3 domain-peptide interaction specificity.

BACKGROUND: The SH3 domain family is one of the most representative and widely studied cases of so-called Peptide Recognition Modules (PRM). The polyproline II motif PxxP that generally characterizes its ligands does not reflect the complex interaction spectrum of the over 1500 different SH3 domains, and the requirement of a more refined knowledge of their specificity implies the setting up of appropriate experimental and theoretical strategies. Due to the limitations of the current technology for peptide synthesis, several experimental high-throughput approaches have been devised to elucidate protein-protein interaction mechanisms. Such approaches can rely on and take advantage of computational techniques, such as regular expressions or position specific scoring matrices (PSSMs) to pre-process entire proteomes in the search for putative SH3 targets. In this regard, a reliable inference methodology to be used for reducing the sequence space of putative binding peptides represents a valuable support for molecular and cellular biologists. RESULTS: Using as benchmark the peptide sequences obtained from in vitro binding experiments, we set up a neural network model that performs better than PSSM in the detection of SH3 domain interactors. In particular our model is more precise in its predictions, even if its performance can vary among different SH3 domains and is strongly dependent on the number of binding peptides in the benchmark. CONCLUSION: We show that a neural network can be more effective than standard methods in SH3 domain specificity detection. Neural classifiers identify general SH3 domain binders and domain-specific interactors from a PxxP peptide population, provided that there are a sufficient proportion of true positives in the training sets. This capability can also improve peptide selection for library definition in array experiments. Further advances can be achieved, including properly encoded domain sequences and structural information as input for a global neural network.

Amino Acid Motifs↗

Query3d: a new method for high-throughput analysis of functional residues in protein structures.

BACKGROUND: The identification of local similarities between two protein structures can provide clues of a common function. Many different methods exist for searching for similar subsets of residues in proteins of known structure. However, the lack of functional and structural information on single residues, together with the low level of integration of this information in comparison methods, is a limitation that prevents these methods from being fully exploited in high-throughput analyses. RESULTS: Here we describe Query3d, a program that is both a structural DBMS (Database Management System) and a local comparison method. The method conserves a copy of all the residues of the Protein Data Bank annotated with a variety of functional and structural information. New annotations can be easily added from a variety of methods and known databases. The algorithm makes it possible to create complex queries based on the residues' function and then to compare only subsets of the selected residues. Functional information is also essential to speed up the comparison and the analysis of the results. CONCLUSION: With Query3d, users can easily obtain statistics on how many and which residues share certain properties in all proteins of known structure. At the same time, the method also finds their structural neighbours in the whole PDB. Programs and data can be accessed through the PdbFun web interface.

Algorithms↗

Functional annotation by identification of local surface similarities: a novel tool for structural genomics.

BACKGROUND: Protein function is often dependent on subsets of solvent-exposed residues that may exist in a similar three-dimensional configuration in non homologous proteins thus having different order and/or spacing in the sequence. Hence, functional annotation by means of sequence or fold similarity is not adequate for such cases. RESULTS: We describe a method for the function-related annotation of protein structures by means of the detection of local structural similarity with a library of annotated functional sites. An automatic procedure was used to annotate the function of local surface regions. Next, we employed a sequence-independent algorithm to compare exhaustively these functional patches with a larger collection of protein surface cavities. After tuning and validating the algorithm on a dataset of well annotated structures, we applied it to a list of protein structures that are classified as being of unknown function in the Protein Data Bank. By this strategy, we were able to provide functional clues to proteins that do not show any significant sequence or global structural similarity with proteins in the current databases. CONCLUSION: This method is able to spot structural similarities associated to function-related similarities, independently on sequence or fold resemblance, therefore is a valuable tool for the functional analysis of uncharacterized proteins. Results are available at http://cbm.bio.uniroma2.it/surface/structuralGenomics.html.

Algorithms↗

pdbFun: mass selection and fast comparison of annotated PDB residues.

pdbFun (http://pdbfun.uniroma2.it) is a web server for structural and functional analysis of proteins at the residue level. pdbFun gives fast access to the whole Protein Data Bank (PDB) organized as a database of annotated residues. The available data (features) range from solvent exposure to ligand binding ability, location in a protein cavity, secondary structure, residue type, sequence functional pattern, protein domain and catalytic activity. Users can select any residue subset (even including any number of PDB structures) by combining the available features. Selections can be used as probe and target in multiple structure comparison searches. For example a search could involve, as a query, all solvent-exposed, hydrophylic residues that are not in alpha-helices and are involved in nucleotide binding. Possible examples of targets are represented by another selection, a single structure or a dataset composed of many structures. The output is a list of aligned structural matches offered in tabular and also graphical format.

Algorithms↗

SURFACE: a database of protein surface regions for functional annotation.

The SURFACE (SUrface Residues and Functions Annotated, Compared and Evaluated, URL http://cbm.bio.uniroma2.it/surface/) database is a repository of annotated and compared protein surface regions. SURFACE contains the results of a large-scale protein annotation and local structural comparison project. A non-redundant set of protein chains is used to build a database of protein surface patches, defined as putative surface functional sites. Each patch is annotated with sequence and structure-derived information about function or interaction abilities. A new procedure for structure comparison is used to perform an all-versus-all patches comparison. Selection of the results obtained with stringent parameters offers a similarity score that can be used to associate different patches and allows reliable annotation by similarity. Annotation exerted through the comparison of regions of protein surface allows the highlighting of similarities that cannot be recognized by other methods of sequence or structure comparison. A graphic representation of the surface patches, functional annotations and the structural superpositions is available through the web interface.

Algorithms↗

ELM server: A new resource for investigating short functional sites in modular eukaryotic proteins.

Multidomain proteins predominate in eukaryotic proteomes. Individual functions assigned to different sequence segments combine to create a complex function for the whole protein. While on-line resources are available for revealing globular domains in sequences, there has hitherto been no comprehensive collection of small functional sites/motifs comparable to the globular domain resources, yet these are as important for the function of multidomain proteins. Short linear peptide motifs are used for cell compartment targeting, protein-protein interaction, regulation by phosphorylation, acetylation, glycosylation and a host of other post-translational modifications. ELM, the Eukaryotic Linear Motif server at http://elm.eu.org/, is a new bioinformatics resource for investigating candidate short non-globular functional motifs in eukaryotic proteins, aiming to fill the void in bioinformatics tools. Sequence comparisons with short motifs are difficult to evaluate because the usual significance assessments are inappropriate. Therefore the server is implemented with several logical filters to eliminate false positives. Current filters are for cell compartment, globular domain clash and taxonomic range. In favourable cases, the filters can reduce the number of retained matches by an order of magnitude or more.

Amino Acid Motifs↗

MINT: a Molecular INTeraction database.

Protein interaction databases represent unique tools to store, in a computer readable form, the protein interaction information disseminated in the scientific literature. Well organized and easily accessible databases permit the easy retrieval and analysis of large interaction data sets. Here we present MINT, a database (http://cbm.bio.uniroma2.it/mint/index.html) designed to store data on functional interactions between proteins. Beyond cataloguing binary complexes, MINT was conceived to store other types of functional interactions, including enzymatic modifications of one of the partners. Release 1.0 of MINT focuses on experimentally verified protein-protein interactions. Both direct and indirect relationships are considered. Furthermore, MINT aims at being exhaustive in the description of the interaction and, whenever available, information about kinetic and binding constants and about the domains participating in the interaction is included in the entry. MINT consists of entries extracted from the scientific literature by expert curators assisted by 'MINT Assistant', a software that targets abstracts containing interaction information and presents them to the curator in a user-friendly format. The interaction data can be easily extracted and viewed graphically through 'MINT Viewer'. Presently MINT contains 4568 interactions, 782 of which are indirect or genetic interactions.

Amino Acid Sequence↗