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在蛋白质结构预测技术关键评估第11轮(CASP11)中基于模板的蛋白质结构全局优化建模

Template based protein structure modeling by global optimization in CASP11.

作者信息

Joo Keehyoung, Joung InSuk, Lee Sun Young, Kim Jong Yun, Cheng Qianyi, Manavalan Balachandran, Joung Jong Young, Heo Seungryong, Lee Juyong, Nam Mikyung, Lee In-Ho, Lee Sung Jong, Lee Jooyoung

机构信息

Center for in Silico Protein Science, Korea Institute for Advanced Study, Seoul, 130-722, Korea.

Center for Advanced Computation, Korea Institute for Advanced Study, Seoul, 130-722, Korea.

出版信息

Proteins. 2016 Sep;84 Suppl 1:221-32. doi: 10.1002/prot.24917. Epub 2015 Sep 14.

Abstract

For the template-based modeling (TBM) of CASP11 targets, we have developed three new protein modeling protocols (nns for server prediction and LEE and LEER for human prediction) by improving upon our previous CASP protocols (CASP7 through CASP10). We applied the powerful global optimization method of conformational space annealing to three stages of optimization, including multiple sequence-structure alignment, three-dimensional (3D) chain building, and side-chain remodeling. For more successful fold recognition, a new alignment method called CRFalign was developed. It can incorporate sensitive positional and environmental dependence in alignment scores as well as strong nonlinear correlations among various features. Modifications and adjustments were made to the form of the energy function and weight parameters pertaining to the chain building procedure. For the side-chain remodeling step, residue-type dependence was introduced to the cutoff value that determines the entry of a rotamer to the side-chain modeling library. The improved performance of the nns server method is attributed to successful fold recognition achieved by combining several methods including CRFalign and to the current modeling formulation that can incorporate native-like structural aspects present in multiple templates. The LEE protocol is identical to the nns one except that CASP11-released server models are used as templates. The success of LEE in utilizing CASP11 server models indicates that proper template screening and template clustering assisted by appropriate cluster ranking promises a new direction to enhance protein 3D modeling. Proteins 2016; 84(Suppl 1):221-232. © 2015 Wiley Periodicals, Inc.

摘要

对于CASP11靶标的基于模板的建模(TBM),我们在先前的CASP协议(CASP7至CASP10)基础上进行改进,开发了三种新的蛋白质建模协议(用于服务器预测的nns以及用于人工预测的LEE和LEER)。我们将强大的构象空间退火全局优化方法应用于三个优化阶段,包括多序列-结构比对、三维(3D)链构建和侧链重塑。为了实现更成功的折叠识别,开发了一种名为CRFalign的新比对方法。它可以在比对分数中纳入敏感的位置和环境依赖性,以及各种特征之间的强非线性相关性。对与链构建过程相关的能量函数形式和权重参数进行了修改和调整。对于侧链重塑步骤,将残基类型依赖性引入到决定旋转异构体进入侧链建模样例库的截止值中。nns服务器方法性能的提高归因于通过结合包括CRFalign在内的多种方法实现的成功折叠识别,以及当前能够纳入多个模板中存在的类似天然结构特征的建模公式。LEE协议与nns协议相同,只是使用了CASP11发布的服务器模型作为模板。LEE在利用CASP11服务器模型方面的成功表明,适当的模板筛选和在适当的聚类排序辅助下的模板聚类为增强蛋白质三维建模提供了一个新方向。《蛋白质》2016年;84(增刊1):221 - 232。© 2015威利期刊公司。

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