Development of Computational Tools for the Inference of ProteinInteraction Specificity Rules and Functional Annotation Using Structural Information

摘要

Relatively few protein structures are known, compared to the enormous amount of sequence data produced in the sequencing of different genomes, and relatively fewprotein complexes are deposited in the PDB with respect to the great amount ofinteraction data coming from high-throughput experiments (two-hybrid or affinitypurification of protein complexes and mass spectrometry). Nevertheless, we can relyon computational techniques for the extraction of high-quality and information-richdata from the known structures and for their spreading in the protein sequence space.We describe here the ongoing research projects in our group: we analyse the proteincomplexes stored in the PDB and, for each complex involving one domain belongingto a family of interaction domains for which some interaction data are available, wecan calculate its probability of interaction with any protein sequence. We analyse thestructures of proteins encoding a function specified in a PROSITE pattern, whichexhibits relatively low selectivity and specificity, and buildextendedpatterns. Tothis aim, we consider residues that are well-conserved in the structure, even if theirconservation cannot easily be recognized in the sequence alignment of the proteinsholding the function. We also analyse protein surface regions and, through theannotation of the solvent-exposed residues, we annotate protein surface patches via astructural comparison performed with stringent parameters and independently of theresidue order in the sequence. Local surface comparison may also help in identifyingnew sequence patterns, which could not be highlighted with other sequence-basedmethods.