Modeling of loops in proteins: a multi-method approach

For a representative set of protein structures of various structural classes test predictions of loop regions have been performed using MODELLER, ROSETTA, and a CABS coarse-grained de novo modeling tool. Loops of various length, from 4 to 25 residues, were modeled assuming an ideal target-template alignment of the remaining portions of the protein. It has been shown that classical modeling with MODELLER is usually better for short loops, while coarse-grained de novo modeling is more effective for longer loops. Even very long missing fragments in protein structures could be effectively modeled. Resolution of such models is usually on the level 2-6 ？, which could be sufficient for guiding protein engineering. Further improvement of modeling accuracy could be achieved by the combination of different methods. In particular, we used 10 top ranked models from sets of 500 models generated by MODELLER as multiple templates for CABS modeling. On average, the resulting molecular models were better than the models from individual methods.Accuracy of protein modeling, as demonstrated for the problem of loop modeling, could be improved by the combinations of different modeling techniques.Comparative modeling remains the most dependable and routinely used method for protein structure prediction [1,2]. The alternative term of homology modeling is frequently used. That is because the identification of a structural template (or templates) is typically based (although not always) on the homology relation between the target protein and the templates, which is usually reflected by a certain level of sequence similarity. When a template is being identified by some advanced Fold Recognition (FR) techniques, it is sometimes possible to identify templates that are structurally similar to the target without any obvious homology relations. This could be a genuine case of convergent evolution or (more frequently) the case when remote homology just can not be detected. Template free, de novo s