Loops In Proteins (LIP)--a comprehensive loop database for homology modelling.
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). In this study, the applicability of LIP to loop prediction in the framework of homology modelling is investigated. Searching the database for loop candidates takes less than 1 s on a desktop PC, and ranking them takes a few minutes. This is an order of magnitude faster than most existing procedures. The 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 <1 A and those of length up to 14 residues with an accuracy better than 2 A. 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.
BCB (Berlin Center for Genome-based Bioinformatics) at the Institute of Biochemistry, Charité (Medical Faculty of the Humboldt University Berlin), Monbijoustrasse 2, D-10117 Berlin, Germany. elke.michalsky@charite.de
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Michalsky
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Goede
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Preissner
D003627:Data Interpretation, Statistical; D030562:Databases, Protein; D008958:Models, Molecular; D017434:Protein Structure, Tertiary; D017385:Sequence Homology