<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Topf, M.</style></author><author><style face="normal" font="default" size="100%">Baker, M. L.</style></author><author><style face="normal" font="default" size="100%">M. A. Marti-Renom</style></author><author><style face="normal" font="default" size="100%">Chiu, W.</style></author><author><style face="normal" font="default" size="100%">Sali, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Refinement of protein structures by iterative comparative modeling and CryoEM density fitting</style></title><secondary-title><style face="normal" font="default" size="100%">J Mol Biol</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amino Acid Sequence Cryoelectron Microscopy *Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Molecular Sequence Data Plant Viruses/chemistry *Protein Conformation Software Viral Proteins/*chemistry/genetics</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=16490207</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5</style></number><volume><style face="normal" font="default" size="100%">357</style></volume><pages><style face="normal" font="default" size="100%">1655-68</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We developed a method for structure characterization of assembly components by iterative comparative protein structure modeling and fitting into cryo-electron microscopy (cryoEM) density maps. Specifically, we calculate a comparative model of a given component by considering many alternative alignments between the target sequence and a related template structure while optimizing the fit of a model into the corresponding density map. The method relies on the previously developed Moulder protocol that iterates over alignment, model building, and model assessment. The protocol was benchmarked using 20 varied target-template pairs of known structures with less than 30% sequence identity and corresponding simulated density maps at resolutions from 5A to 25A. Relative to the models based on the best existing sequence profile alignment methods, the percentage of C(alpha) atoms that are within 5A of the corresponding C(alpha) atoms in the superposed native structure increases on average from 52% to 66%, which is half-way between the starting models and the models from the best possible alignments (82%). The test also reveals that despite the improvements in the accuracy of the fitness function, this function is still the bottleneck in reducing the remaining errors. To demonstrate the usefulness of the protocol, we applied it to the upper domain of the P8 capsid protein of rice dwarf virus that has been studied by cryoEM at 6.8A. The C(alpha) root-mean-square deviation of the model based on the remotely related template, bluetongue virus VP7, improved from 8.7A to 6.0A, while the best possible model has a C(alpha) RMSD value of 5.3A. Moreover, the resulting model fits better into the cryoEM density map than the initial template structure. The method is being implemented in our program MODELLER for protein structure modeling by satisfaction of spatial restraints and will be applicable to the rapidly increasing number of cryoEM density maps of macromolecular assemblies.</style></abstract><notes><style face="normal" font="default" size="100%">Topf, Maya Baker, Matthew L Marti-Renom, Marc A Chiu, Wah Sali, Andrej 2 PN2 EY016525-02/EY/NEI NIH HHS/United States P20RR020647/RR/NCRR NIH HHS/United States P41RR02250/RR/NCRR NIH HHS/United States R01 GM54762/GM/NIGMS NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov’t Research Support, U.S. Gov’t, Non-P.H.S. England Journal of molecular biology J Mol Biol. 2006 Apr 14;357(5):1655-68. Epub 2006 Feb 2.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">M. A. Marti-Renom</style></author><author><style face="normal" font="default" size="100%">Madhusudhan, M. S.</style></author><author><style face="normal" font="default" size="100%">Fiser, A.</style></author><author><style face="normal" font="default" size="100%">Rost, B.</style></author><author><style face="normal" font="default" size="100%">Sali, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Reliability of assessment of protein structure prediction methods</style></title><secondary-title><style face="normal" font="default" size="100%">Structure</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">*Computer Simulation Humans *Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular *Protein Conformation Proteins/*chemistry Reproducibility of Results</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2002</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=12005441</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">435-40</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The reliability of ranking of protein structure modeling methods is assessed. The assessment is based on the parametric Student’s t test and the nonparametric Wilcox signed rank test of statistical significance of the difference between paired samples. The approach is applied to the ranking of the comparative modeling methods tested at the fourth meeting on Critical Assessment of Techniques for Protein Structure Prediction (CASP). It is shown that the 14 CASP4 test sequences may not be sufficient to reliably distinguish between the top eight methods, given the model quality differences and their standard deviations. We suggest that CASP needs to be supplemented by an assessment of protein structure prediction methods that is automated, continuous in time, based on several criteria applied to a large number of models, and with quantitative statistical reliability assigned to each characterization.&lt;/p&gt;</style></abstract><notes><style face="normal" font="default" size="100%">&lt;p&gt;Marti-Renom, Marc A Madhusudhan, M S Fiser, Andras Rost, Burkhard Sali, Andrej GM 54762/GM/NIGMS NIH HHS/United States GM62413/GM/NIGMS NIH HHS/United States Comparative Study Research Support, Non-U.S. Gov’t Research Support, U.S. Gov’t, P.H.S. United States Structure (London, England : 1993) Structure. 2002 Mar;10(3):435-40.&lt;/p&gt;</style></notes></record></records></xml>