TY - JOUR
T1 - Gaia
T2 - Automated quality assessment of protein structure models
AU - Kota, Pradeep
AU - Ding, Feng
AU - Ramachandran, Srinivas
AU - Dokholyan, Nikolay V.
N1 - Funding Information:
Funding: American Heart Association Predoctoral Fellowship (to S.R. 09PRE2090068); the University of North Carolina Research Council (to F.D.); the National Institutes of Health (to N.V.D. grant number R01GM080742 and ARRA supplements GM080742-03S1 and GM066940-06S1).
PY - 2011/8
Y1 - 2011/8
N2 - Motivation: Increasing use of structural modeling for understanding structure-function relationships in proteins has led to the need to ensure that the protein models being used are of acceptable quality. Quality of a given protein structure can be assessed by comparing various intrinsic structural properties of the protein to those observed in high-resolution protein structures.Results: In this study, we present tools to compare a given structure to high-resolution crystal structures. We assess packing by calculating the total void volume, the percentage of unsatisfied hydrogen bonds, the number of steric clashes and the scaling of the accessible surface area. We assess covalent geometry by determining bond lengths, angles, dihedrals and rotamers. The statistical parameters for the above measures, obtained from high-resolution crystal structures enable us to provide a quality-score that points to specific areas where a given protein structural model needs improvement.
AB - Motivation: Increasing use of structural modeling for understanding structure-function relationships in proteins has led to the need to ensure that the protein models being used are of acceptable quality. Quality of a given protein structure can be assessed by comparing various intrinsic structural properties of the protein to those observed in high-resolution protein structures.Results: In this study, we present tools to compare a given structure to high-resolution crystal structures. We assess packing by calculating the total void volume, the percentage of unsatisfied hydrogen bonds, the number of steric clashes and the scaling of the accessible surface area. We assess covalent geometry by determining bond lengths, angles, dihedrals and rotamers. The statistical parameters for the above measures, obtained from high-resolution crystal structures enable us to provide a quality-score that points to specific areas where a given protein structural model needs improvement.
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U2 - 10.1093/bioinformatics/btr374
DO - 10.1093/bioinformatics/btr374
M3 - Article
C2 - 21700672
AN - SCOPUS:79961202365
SN - 1367-4803
VL - 27
SP - 2209
EP - 2215
JO - Bioinformatics
JF - Bioinformatics
IS - 16
M1 - btr374
ER -