Next generation computational tools for the analysis and prediction of protein disorder and related gene function

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With many genomes now completely sequenced, life scientists face the challenge of characterizing the biological role of the encoded proteins as to advance our understanding of cell physiology. Over the past decades, several experimental studies reinforced the view that the three dimensional structure of a protein is a prerequisite to its function. Evolution optimized the relative positions of specific protein atoms so that they can perform different tasks, including ligand binding and catalysis of reactions. Recently this view has been revised in light of additional data from eukaryotic species. Indeed, several observations prove that a large number of their proteins include highly flexible segments, which assume a fixed conformation when they recognize their biological partners only. These fragments - or whole proteins - are usually called natively unfolded, intrinsically unstructured or disordered and are predominantly found in multi-cellular organisms where they play key roles in signalling and regulatory processes through the binding to proteins, nucleotides, nucleic acids and metal ions. The identification and functional characterization of disordered proteins has drawn increasing attention. Different assays can produce systematic information on the location of disordered regions. However, these techniques suffer from intrinsic limitations and cannot be reasonably applied to all the proteins that a typical eukaryotic organism expresses. On the other side, thorough analyses showed that the amino acid sequences of these proteins are characterized by clear patterns and so computer programs can distinguish them fairly accurately and quickly. The classification of a protein as natively unfolded and the location of its disordered regions are valuable information. Yet, this is not enough to describe in detail what molecular actions the protein performs and what biological processes they relate to. Although we know that some functional categories are particularly enriched in disordered regions, we cannot afford to experimentally test all possible alternatives. A reasonable solution consists in exploiting computers to further analyze these proteins and then in performing much less lab assays to validate the results of computational analyses. This project aims at the development of a web server that will be accessible to everyone through the Internet and that will output functional predictions - i.e. hints - for disordered proteins. The program will first locate disordered regions within the input sequence using a method we previously developed. It will then exploit the chemical and physical features of some ligands - such as DNA and metal ions - to assess the likelihood for the input protein sequence to interact with them through its potential disordered regions. The results are expected to improve our knowledge of this important class of proteins and prioritize experiments aimed at characterizing their functions.