MAISTAS: a tool for automatic structural evaluation of alternative splicing products

Motivation: Analysis of the human genome revealed that the amount of transcribed sequence is an order of magnitude greater than the number of predicted and well-characterized genes. A sizeable fraction of these transcripts is related to alternatively spliced forms of known protein coding genes. Inspection of the alternatively spliced transcripts identified in the pilot phase of the ENCODE project has clearly shown that often their structure might substantially differ from that of other isoforms of the same gene, and therefore that they might perform unrelated functions, or that they might even not correspond to a functional protein. Identifying these cases is obviously relevant for the functional assignment of gene products and for the interpretation of the effect of variations in the corresponding proteins

Innate immune activating ligand SUMOylation affects tumor cell recognition by NK cells

Natural Killer cells are innate lymphocytes involved in tumor immunosurveillance. They express activating receptors able to recognize self-molecules poorly expressed on healthy cells but up-regulated upon stress conditions, including transformation. Regulation of ligand expression in tumor cells mainly relays on transcriptional mechanisms, while the involvement of ubiquitin or ubiquitin-like modifiers remains largely unexplored. Here, we focused on the SUMO pathway and demonstrated that the ligand of DNAM1 activating receptor, PVR, undergoes SUMOylation in multiple myeloma. Concurrently, we found that PVR is preferentially located in intracellular compartments in human multiple myeloma cell lines and malignant plasma cells and that inhibition of the SUMO pathway promotes its translocation to the cell surface, increasing tumor cell susceptibility to NK cell-mediated cytolysis. Our findings provide the first evidence of an innate immune activating ligand regulated by SUMOylation, and confer to this modification a novel role in impairing recognition and killing of tumor cells.Natural Killer cells are innate lymphocytes involved in tumor immunosurveillance. They express activating receptors able to recognize self-molecules poorly expressed on healthy cells but up-regulated upon stress conditions, including transformation. Regulation of ligand expression in tumor cells mainly relays on transcriptional mechanisms, while the involvement of ubiquitin or ubiquitin-like modifiers remains largely unexplored. Here, we focused on the SUMO pathway and demonstrated that the ligand of DNAM1 activating receptor, PVR, undergoes SUMOylation in multiple myeloma. Concurrently, we found that PVR is preferentially located in intracellular compartments in human multiple myeloma cell lines and malignant plasma cells and that inhibition of the SUMO pathway promotes its translocation to the cell surface, increasing tumor cell susceptibility to NK cell-mediated cytolysis. Our findings provide the first evidence of an innate immune activating ligand regulated by SUMOylation, and confer to this modification a novel role in impairing recognition and killing of tumor cells

Evaluating the usefulness of protein structure models for molecular replacement

MOTIVATION: We investigate the relationship between the quality of models of protein structure and their usefulness as search models in molecular replacement, a widely used method to experimentally determine protein structures by X-ray crystallography. RESULTS: We used the available models submitted to the Critical Assessment of Techniques for Protein Structure Prediction to verify in which cases they can be automatically used as search templates for molecular replacement. Our results show that there is a correlation between the quality of the models and their suitability for molecular replacement but that the traditional method of relying on sequence identity between the model and the template used to build it is not diagnostic for the success of the procedure. AVAILABILITY: Additional data are available at http://cassandra.bio.uniroma1.it/mr-results-casp.htm

Mapping the hydropathy of amino acids based on their local solvation structure

In spite of its relevant biological role, no general consensus exists on the quantitative characterization of amino acid's hydropathy. In particular, many hydrophobicity scales exist, often producing quite different rankings for the amino acids. To make progress toward a systematic classification, we analyze amino acids' hydropathy based on the orientation of water molecules at a given distance from them as computed from molecular dynamics simulations. In contrast with what is usually done, we argue that assigning a single number is not enough to characterize the properties of an amino acid, in particular when both hydrophobic and hydrophilic regions are present in a residue. Instead we show that appropriately defined conditional probability densities can be used to map the hydrophilic and hydrophobic groups on the amino acids with greater detail than possible with other available methods. Three indicators are then defined based on the features of these probabilities to quantify the specific hydrophobicity and hydrophilicity of each amino acid. The characterization that we propose can be used to understand some of the ambiguities in the ranking of amino acids in the current scales. The quantitative indicators can also be used in combination with standard bioinformatics tools to predict the location of transmembrane regions of proteins. The method is sensitive to the specific environment of the amino acids and can be applied to unnatural and modified amino acids, as well as to other small organic molecules