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Abstract: The knowledge of structural organization of proteins is crucial in understanding their role in the cell and the related molecular mechanisms. Comparative modelling has already become one of the most effective computational approaches in facilitating structural/functional characterization of many protein-coding sequences across genomes and it is based on the assumption that homologous proteins adopt the same fold to have the same function. On this basis, it is possible to model the 3D structure of a protein if it is known at least one experimental model of an homologous protein. However, it is evident that a large number of proteins, probably all, may assume different conformations depending on the different environmental conditions or the interaction with other molecules. Conformational modifications occur when a protein changes its monomeric / oligomeric state, enzymes adapt their conformation to the substrate when it is recognized, but also, very different secondary structures are observed in the normal and pathological forms of the prion protein. We are interested to apply the comparative modelling to predict the different conformations assumed by a protein to exert its biological activities or in different environmental conditions. In this work we applied the comparative modelling methods to create models of the interleukin 1beta (IL-1beta) and to investigate the conformational changes occuring when this protein interacts with its receptor (IL-1R).

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Abstract: Bioinformatics applications require the joint use of different resources: databases, query systems, sequence analysis tools, software for 3D structure prediction and analysis. I am working to set up WEBIOLAB, a bioinformatics laboratory on the web (http://crisceb.area.na.cnr.it/angelo/services.html), where people interested to the investigation of protein structure and function can find tools useful for their work. Up today, the main task of this project was to arrange a large number of public databases (over 60 up to now, and the number is growing), which can be searched by means of the Sequence Retrieval System (SRS). Standard settings of SRS version 5.1.0 provide links among databases, and I am working to improve them with the aim to obtain a more powerful network. WEBIOLAB also includes local copies of public domain web tools for protein sequence analysis and 3D visualization. Many public domain programs for protein structure analysis and prediction are restricted to local users; the plan is to make them available within WEBIOLAB, also by exploiting the ability of SRS to submit entries of databases to applications. The next step of this work will be the implementation of appropriate interfaces to original tools developed to perform specific analyses of 3D structures of proteins, successfully used within our research projects.

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Abstract: Modern biological sciences need informatic support to manage and analyze the large amount of structural and functional information about proteins and nucleic acids. The availability of databases and analysis tools, as well as the opportunity to have special purpose methods and software represents an undoubtful advantage for any research team. For this purpose, our group maintains a web site (http://crisceb.area.na.cnr.it) to support molecular biology research offering public domain bioinformatics software, databases, and developing computational methods for protein and nucleic acid analysis. The SRS - Sequence Retrieval System allows our users to query more than 70 databases. Public domain software are also available (CINEMA, WebMol, Phylodendron). Moreover, we are interested to develop new web tools to meet specific research problems. As an example, we have recently realized a tool to search for helix motifs in protein sequences. Another running project concerns the search for 3D similarities among protein structures. The aim of our work is to integrate all these tools, in order to create a real bioinformatics laboratory on the web.

Abstract: In order to investigate structural/functional relationships of a wheat subtilisin-chymotrypsin inhibitor (WSCI) (1), we decided to explore its secondary and tertiary structures by applying an homology modelling procedure (using the Modeller program as part of the Quanta package) (2). The barley chymotrypsin inhibitor CI-2A (3), which exhibits 89% sequence similarity with the wheat inhibitor, has been chosen as reference structure. The best model structure obtained for WSCI, shows that 50% of its amino acid sequence (72 residues) are involved in motifs of secondary structure; particularly, 11 amino acid residues give rise to an helix, 12 residues form a long loop connecting two parallel strands, each made up of 6 residues. In the spatial model, the relative positions of such motifs are in agreement with the experimental data obtained upon interaction between WSCI and subtilisin; in fact, the bacterial proteinase cleaves, specifically, the inhibitor peptide bond Met48-Glu49 located in the middle of the above connecting loop. The weak interactions observed (H-bonds and salt bridges) in WSCI model are in perfect agreement with those found in the reference structure of CI-2A. Investigations regarding the modality of interaction between WSCI and susceptible proteinases are in progress.

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Abstract: The characterization of proteins from thermophilic organisms is becoming more and more interesting for possible biotechnological applications. Recently, the complete genome of a hyper-thermophilic archaebacterium, P. horikoshii, was sequenced [1] and a sugar binding protein (Ph-SBP) was identified by means of analysis of its sequence similarity. Some preliminary experimental information are available on its binding properties and on its structural features; however, the lack of information about its 3D structure impairs the complete knowledge of its conformational properties and interactions with its ligands. Here, we present the results of the homology modelling strategy we used to predict the 3D structure of Ph-SBP, and the analysis we made on the resulting model in order to assess its reliability, with particular care to its expected thermostability features and sugar binding properties.

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Abstract: The DNA microarray technique makes it possible to analyze the expression patterns of tens of thousands genes in a short time. The wide use of this technique and the rapidly improving different technologies available by several commercial and academic providers has led to the publication of thousands of results, extremely heterogeneous with respect to the type of technology used, to the kind of normalization and analysis subsequently applied to data an so on. This leads to a difficulty in collaborating and exchange data between groups with common research interest, whereas collaborations would be extremely useful due to the high cost of this techniques but also to the consideration that an experiment carefully designed could bring results relevant to different groups, each focusing on a different aspect of a main biological problem. So the awareness for the need of common standards or, at least, comparable technologies is emerging in the scientific community, as shown by the effort of the on-purpose Microarray Gene Expression Data (MGED) Society, which is trying to set up at least experimental methodology, ontology and data format standards. In addition, it is important the ability of being able to compare newly produced data with preceding experiments, so to ensure of keeping high the value of results produced with equipment of the old generation. Otherwise, a large amount of the work produced until the outcome of a new release of technology would be lost. This, considering that the huge amount of data produced is largely underexploited, would be a great loss for the scientific community. In fact, as analysis algorithms are improving, existing data can be re-analyzed to give more precise results, thus helping to adjust the planning of future experiments. We thus started this work with the aim of evaluating the technical variability between three commonly used microarray platforms, such to adapt the first part of the analysis to the peculiarity of each technique, and the feasibility of a common subsequent analysis path, thus taking advantage of the different data-extraction abilities of the three. For this purpose, we used three different commercial chips to study the gene expression profiles of hormone-responsive breast cancer cells with and without stimulation with estradiol: i) the Incyte ‘UniGEM V 2.0’ microarrays, containing over 14,000 PCR-amplified cDNAs, corresponding to 8286 unique genes, spotted at a high density pattern onto glass slides; ii) the Affymetrix technology, based on 25 nucleotide-long oligonucleotides directly synthesized on a GeneChip® array, representing more than 39,000 transcripts derived from approximately 33,000 unique human genes; iii) the Agilent ‘Human 1A Oligo’ Microarray consisting of 60-mer, in situ synthesized oligonucleotide probes for a total of about 18000 different genes. The RNA derived from human breast cancer cells (ZR-75.1) stimulated for 72 hrs with 17beta-estradiol after starvation in steroid-free medium for 4 days; the reference sample was derived from synchronized cells grown in steroid-free environment. The same samples were used to generate fluorescent targets to be hybridized on the different slides. Hybridization reactions were performed with four (for the Agilent slides) and two or three (for the other platforms) technical replicates, with a single (Incyte) or double (Agilent), balanced dye swap for competitive hybridizations. A total combined number of 18,823 unique UniGene clusters were represented among the three platforms used. By focusing only on a subset of 5,733 genes that were present in all the chips, about 50% appeared to be significantly expressed and 25% genes resulted significantly regulated by 17beta-estradiol treatment in our experiment. A quite low overlapping was observed between the lists of regulated genes obtained by the three systems. We are working on understanding the conflicting results on some of the genes. The majority of genes were detected by only the Affymetrix platform, probably as a consequence of the higher sensitivity of this system, which allows the detection of some gene expression levels that are not identified with the other platforms. However, a number of genes was identified only by the cDNA and/or oligonucleotide systems. Another possible experimental explanation is that the DNA sequences spotted on the arrays show different affinity for the target, so each slide has a particular pattern of probe-target annealing, although the same genes are represented on all the platforms. Finally, we are improving the data processing by statistical methods in order to allow the better understanding of the experimental results.

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