A Different Look at the Quality of Modeled Three-Dimensional Protein Structures

Abstract

Measuring the accuracy of protein three-dimensional structures is one of the most important problems in protein structure prediction. For structure-based drug design, the accuracy of the binding site is far more important than the accuracy of any other region of the protein. We have developed an automated method for assessing the quality of a protein model by focusing on the set of residues in the small molecule binding site. Small molecule binding sites typically involve multiple regions of the protein coming together in space, and their accuracy has been observed to be sensitive to even small alignment errors. In addition, ligand binding sites contain the critical information required for drug design, making their accuracy particularly important. We analyzed the accuracy of the binding sites on two sets of protein models: the predictions submitted by the top-performing CASP7 groups, and the models generated by four widely used homology modeling packages. The results of our CASP7 analysis significantly differ from the previous findings, implying that the binding site measure does not correlate with the traditional model quality measures used in the structure prediction benchmarks. For the modeling programs, the resolution of binding sites is extremely sensitive to the degree of sequence homology between the query and the template, even when the most accurate alignments are used in the homology modeling process.

Optimal Pairwise Alignment of Fixed Protein Structures in Subquadratic Time

“…Automated methods for pairwise protein structure comparison are of critical importance in several fields, including protein three-dimensional structure prediction, [1][2][3][4][5] protein functional site comparison, [6][7][8] and protein structural and functional annotation. [9][10][11] The protein structure comparison problem is much more challenging than its closely related sequence alignment problem.…”