From Protein Structure to Function with Bioinformatics.pdf

12 Prediction of Protein Function from Theoretical Models 295a large number of sequences with relatively homogenous rates of divergence,from which patterns of duplications can be inferred. Such methods also encounterproblems in cases where sequences do not retain their function despiteorthology.Analyses of function conservation can be greatly aided by consideration ofsequence not only as a linear string of amino acid residues, but also in a contextof its three-dimensional structure. Since function is typically conferred by aminoacids that are close in space and not necessarily in sequence, functional considerationsmay be restricted to analyzing only a given functional site. Thus, functionalconservation typically requires the spatial conservation of importantamino acid residues and not necessarily the conservation of the overall sequenceidentity. This approach can be illustrated by a simple case: the loss of just onecatalytic residue has a small effect on global sequence similarity, but typicallycompletely eliminates one aspect of protein function (e.g. the protein may stillbind the substrate, but no longer catalyze the reaction that requires a functionalgroup of the missing residue). Thus, comparison of residues in functional sitesand analysis of more diffuse properties such as various features of protein surface(see Chapters 7 and 8.) are more appropriate for comparative functionalanalyses than considerations of linear sequences. However, such analyses obviouslyrequire knowledge of the protein structure. In this chapter we will discusshow computational modelling can contribute to providing these structures and,in particular, show how the models enhance our understanding of proteinfunction.12.2 Protein Models as a Community ResourceAs also mentioned in Chapter 3, one of the aims of the structural genomics approach,in particular the Protein Structure Initiative (PSI), is to experimentally obtain suchprotein structures that would maximize coverage of protein fold space. Over the past7 years PSI centres have determined nearly 3,000 protein structures, about 40% ofall the novel structures, with previously uncharacterized folds, deposited in theProtein Data Bank (PDB), a global repository for protein structures (Service 2008a).At the same time, in the field of protein structure prediction, much effort has beendevoted to the improvement of algorithms and tools enabling the theoretical structuralmodels to be as close to the experimentally solved structures as possible. Thesuccessive rounds of Critical Assessment of Structure Prediction (Kryshtafovych etal. 2005) modelling benchmark (CASP) have shown that the accuracy of the predictedstructures improves continuously. This would be of little practical use of theresulting models were of poor quality but, in fact, for 80% of CASP’s targets on theaverage, models are built that are close enough to the true structures to add usefulinformation over the template (Kryshtafovych et al. 2007). (The added value ofmodels with respect to sequences and templates is discussed in more detail below).The growing number of structurally characterized new folds by structural genomics