Department of Statistics, Macquarie University, North Ryde, Australia.
Bioinformatics. 2010 Aug 1;26(15):1849-56. doi: 10.1093/bioinformatics/btq294. Epub 2010 Jun 4.
Template-based modelling can approximate the unknown structure of a target protein using an homologous template structure. The core of the resulting prediction then comprises the structural regions conserved between template and target. Target prediction could be improved by rigidly repositioning such single template, structurally conserved fragment regions. The purpose of this article is to quantify the extent to which such improvements are possible and to relate this extent to properties of the target, the template and their alignment.
The improvement in accuracy achievable when rigid fragments from a single template are optimally positioned was calculated using structure pairs from the HOMSTRAD database, as well as CASP7 and CASP8 target/best template pairs. Over the union of the structurally conserved regions, improvements of 0.7 A in root mean squared deviation (RMSD) and 6% in GDT_HA were commonly observed. A generalized linear model revealed that the extent to which a template can be improved can be predicted using four variables. Templates with the greatest scope for improvement tend to have relatively more fragments, shorter fragments, higher percentage of helical secondary structure and lower sequence identity. Optimal positioning of the template fragments offers the potential for improving loop modelling. These results demonstrate that substantial improvement could be made on many templates if the conserved fragments were to be optimally positioned. They also provide a basis for identifying templates for which modification of fragment positions may yield such improvements.
基于模板的建模可以使用同源模板结构来近似目标蛋白质的未知结构。然后，预测的核心包含模板和目标之间保守的结构区域。通过刚性重新定位这种单一模板、结构上保守的片段区域，可以改进目标预测。本文的目的是量化这种改进的程度，并将其与目标、模板及其比对的性质联系起来。
使用 HOMSTRAD 数据库中的结构对以及 CASP7 和 CASP8 目标/最佳模板对，计算了最佳定位单个模板中的刚性片段时可实现的准确性提高程度。在结构保守区域的并集中，通常观察到 RMSD 提高 0.7 A 和 GDT_HA 提高 6%。广义线性模型表明，可以使用四个变量来预测模板可以改进的程度。具有最大改进空间的模板往往具有相对更多的片段、较短的片段、更高的螺旋二级结构百分比和更低的序列同一性。模板片段的最佳定位为改进环建模提供了潜力。这些结果表明，如果保守片段能够最佳定位，则可以对许多模板进行实质性改进。它们还为确定可以通过修改片段位置来实现这些改进的模板提供了依据。
