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RECURSIVE PROTEIN MODELING: A DIVIDE AND CONQUER STRATEGY FOR PROTEIN STRUCTURE PREDICTION AND ITS CASE STUDY IN CASP9

机译:递归蛋白质建模:蛋白质结构预测的划分和征服策略及其在CASP9中的案例研究

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摘要

After decades of research, protein structure prediction remains a very challenging problem. In order to address the different levels of complexity of structural modeling, two types of modeling techniques — template-based modeling and template-free modeling — have been developed. Template-based modeling can often generate a moderate- to high-resolution model when a similar, homologous template structure is found for a query protein but fails if no template or only incorrect templates are found. Template-free modeling, such as fragment-based assembly, may generate models of moderate resolution for small proteins of low topological complexity. Seldom have the two techniques been integrated together to improve protein modeling. Here we develop a recursive protein modeling approach to selectively and collaboratively apply template-based and template-free modeling methods to model template-covered (i.e. certain) and template-free (i.e. uncertain) regions of a protein. A preliminary implementation of the approach was tested on a number of hard modeling cases during the 9th Critical Assessment of Techniques for Protein Structure Prediction (CASP9) and successfully improved the quality of modeling in most of these cases. Recursive modeling can signicantly reduce the complexity of protein structure modeling and integrate template-based and template-free modeling to improve the quality and efficiency of protein structure prediction.
机译:经过几十年的研究,蛋白质结构预测仍然是一个非常具有挑战性的问题。为了解决结构建模的不同程度的结构建模,已经开发出两种类型的建模技术 - 基于模板的建模和模板建模 - 已经开发出来。基于模板的建模通常可以在发现类似的同源模板结构时生成中等到高分辨率模型,但如果没有找到模板或仅找到不正确的模板,则失败。无模板建模,例如基于片段的组装,可以生成用于小拓扑复杂性的小蛋白质的中等分辨率的模型。很少有两种技术集成在一起以改善蛋白质建模。在这里,我们开发一种递归蛋白质建模方法,以选择性地和协作应用基于模板的模板和模板的建模方法,以模拟模板覆盖的(即某些)和蛋白质的无模板(即不确定)区域。在蛋白质结构预测(CASP9)技术的第9次批判性评估期间,在蛋白质结构预测(CASP9)的第9次批判性评估中进行了初步实施,并在大多数情况下成功提高了建模质量。递归建模可以显着降低蛋白质结构建模的复杂性,并集成基于模板和模板的模型,提高蛋白质结构预测的质量和效率。

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