Department of Biophysics, University of Texas Southwestern Medical Center at Dallas, Dallas, Texas, 75390; Department of Biochemistry, University of Texas Southwestern Medical Center at Dallas, Dallas, Texas, 75390.
Proteins. 2015 Mar;83(3):411-27. doi: 10.1002/prot.24746. Epub 2015 Jan 13.
Constructing a model of a query protein based on its alignment to a homolog with experimentally determined spatial structure (the template) is still the most reliable approach to structure prediction. Alignment errors are the main bottleneck for homology modeling when the query is distantly related to the template. Alignment methods often misalign secondary structural elements by a few residues. Therefore, better alignment solutions can be found within a limited set of local shifts of secondary structures. We present a refinement method to improve pairwise sequence alignments by evaluating alignment variants generated by local shifts of template-defined secondary structures. Our method SFESA is based on a novel scoring function that combines the profile-based sequence score and the structure score derived from residue contacts in a template. Such a combined score frequently selects a better alignment variant among a set of candidate alignments generated by local shifts and leads to overall increase in alignment accuracy. Evaluation of several benchmarks shows that our refinement method significantly improves alignments made by automatic methods such as PROMALS, HHpred and CNFpred. The web server is available at http://prodata.swmed.edu/sfesa.
基于与具有实验确定空间结构的同源物（模板）的比对来构建查询蛋白的模型仍然是结构预测最可靠的方法。当查询与模板相距较远时，比对错误是同源建模的主要瓶颈。比对方法经常会使二级结构元件错位几个残基。因此，可以在二级结构的有限局部移位范围内找到更好的对齐解决方案。我们提出了一种改进方法，通过评估由模板定义的二级结构的局部移位生成的对齐变体来改进两两序列比对。我们的方法 SFESA 基于一种新的评分函数，该函数结合了基于轮廓的序列评分和从模板中残基接触得出的结构评分。这种组合评分经常在由局部移位生成的一组候选比对中选择更好的比对变体，并导致比对准确性的整体提高。对几个基准的评估表明，我们的改进方法显著提高了 PROMALS、HHpred 和 CNFpred 等自动方法的比对效果。该网络服务器可在 http://prodata.swmed.edu/sfesa 上获得。
