Protein Engineering 2003, vol.16, no.12, pp. 1-7

One of the most important and challenging tasks in protein modelling is the prediction of loops, as can be seen in the large variety of existing approaches. Loops In Proteins (LIP) is a database that includes all protein segments of a length up to 15 residues contained in the Protein Data Bank (PDB). Searching the database for loop candidates takes less than one second on a desktop PC, ranking them a few minutes. This is an order of magnitude faster than most existing procedures.

In this study, the applicability of LIP to loop prediction in the framework of homology modelling is investigated. Measure of accuracy is the Root Mean Square Deviation (RMSD) with respect to the main-chain atoms after local superposition of target loop and predicted loop. Loops of up to nine residues length were modelled with a local RMSD less than 1 Å, those of length up to 14 residues with an accuracy better than 2 Å. The results were compared in detail with a thoroughly evaluated and tested ab initio method published recently, and additionally with two further methods for a small loop test set. The LIP-method produced very good predictions. In particular for longer loops it outperformed other methods (please see some results).

        Test sets used in this study can be downloaded here.