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Accuracy of Protein-Protein Binding Sites in High-Throughput Template-Based Modeling

Kundrotas, Petras J.
Vakser, Ilya A.
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Abstract
The accuracy of protein structures, particularly their binding sites, is essential for the success of modeling protein complexes. Computationally inexpensive methodology is required for genome-wide modeling of such structures. For systematic evaluation of potential accuracy in high-throughput modeling of binding sites, a statistical analysis of target-template sequence alignments was performed for a representative set of protein complexes. For most of the complexes, alignments containing all residues of the interface were found. The full interface alignments were obtained even in the case of poor alignments where a relatively small part of the target sequence (as low as 40%) aligned to the template sequence, with a low overall alignment identity (<30%). Although such poor overall alignments might be considered inadequate for modeling of whole proteins, the alignment of the interfaces was strong enough for docking. In the set of homology models built on these alignments, one third of those ranked 1 by a simple sequence identity criteria had RMSD<5 Ã…, the accuracy suitable for low-resolution template free docking. Such models corresponded to multi-domain target proteins, whereas for single-domain proteins the best models had 5 Ã…<RMSD<10 Ã…, the accuracy suitable for less sensitive structure-alignment methods. Overall, ~50% of complexes with the interfaces modeled by high-throughput techniques had accuracy suitable for meaningful docking experiments. This percentage will grow with the increasing availability of co-crystallized protein-protein complexes.
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Date
2010-04-01
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Publisher
Public Library of Science
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Keywords
Binding analysis, Enzyme structure, Protein complexes, Protein interactions, Protein structure, Sequence alignment, Sequence analysis, Sequence databases
Citation
Kundrotas, P. J., & Vakser, I. A. (2010). Accuracy of Protein-Protein Binding Sites in High-Throughput Template-Based Modeling. PLoS Comput Biol, 6(4). http://dx.doi.org/10.1371/journal.pcbi.1000727
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