From Protein Structure to Function with Bioinformatics.pdf

78 A. FiserA rigorous statistical evaluation (Marti-Renom et al. 2002) of a blind predictionexperiment illustrated that the accuracies of the various model-building methods,using segment matching, rigid body assembly, satisfaction of spatial restraints orany combinations of these are relatively similar when used optimally (Dalton andJackson 2007; Wallner and Elofsson 2005b). This also reflects on the fact that suchmajor factors as template selection and alignment accuracy have a large impact onthe overall model accuracy, and that the core of protein structures is highly conserved.From a practical point of view models should be evaluated by their usefulnessregarding the functional insight they provide. A unique functional role must be connectedwith unique structural features, which is more often found in variable loopregions than in the conserved core. However, functional site descriptions are notonly manually defined but, in an increasing fraction of cases, are missing or incomplete.This particularly applies to the outputs from Structural Genomics projects, whichoften focus specifically and deliberately on proteins of unknown function.Therefore, while large-scale benchmarking of modelling methods through the evaluationof the accuracy of functional annotations based on the resulting models isdesirable, it is not yet straightforward to carry out in practice (Chakravarty andSanchez 2004; Chakravarty et al. 2005).3.3.2 Errors in Comparative ModelsThe overall accuracy of comparative models spans a wide range. At the low end ofthe spectrum are the low resolution models whose only essentially correct featureis their fold. At the high end of the spectrum are the models with an accuracy comparableto medium resolution crystallographic structures (Baker and Sali 2001).Even low resolution models are often useful to address biological questions,because function can many times be predicted from only coarse structural featuresof a model, as later chapters of this book illustrate.The errors in comparative models can be divided into five categories: (1) Errorsin side chain packing. (2) Distortions or shifts of a region that is aligned correctlywith the template structures. (3) Distortions or shifts of a region that does not havean equivalent segment in any of the template structures. (4) Distortions or shifts ofa region that is aligned incorrectly with the template structures. (5) A misfoldedstructure resulting from using an incorrect template. Significant methodologicalimprovements are needed to address each of these errors.Errors 3–5 are relatively infrequent when sequences with more than 40% identityto the templates are modelled. For example, in such a case, approximately 90%of the main chain atoms are likely to be modelled with an RMS error of about 1 Å(Sanchez and Sali 1998). In this range of sequence similarity, the alignment ismostly straightforward to construct, there are not many gaps, and the structuraldifferences between the proteins are usually limited to loops and side chains.When sequence identity is between 30% and 40%, the structural differencesbecome larger, and the gaps in the alignment are more frequent and longer, misalignmentsand insertions in the target sequence become the major problems. As