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A structural-informatics approach for mining beta-sheets: locating sheets in intermediate-resolution density maps.

机译:一种用于挖掘beta图纸的结构信息学方法:在中等分辨率密度图中定位图纸。

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Here, we report a new computational method, called sheetminer, for mining beta-sheets in the density maps at intermediate resolutions of 6 to 10A. The method employs a multi-step ad hoc morphological analysis of density maps to identify the unique characteristics of beta-sheets. It was tested on density maps from 12 protein crystal structures that were artificially blurred to intermediate resolutions. There are a total of 35 independent beta-sheets with a wide distribution of morphology. The method successfully located 34 of them and missed only one. The method was also applied to an experimental 9A electron cryomicroscopic structure and an 8A X-ray density map. In both cases, the sheet-searching results were found to agree very well with known high-resolution crystal structures. Collectively, these results demonstrate clearly the robustness of sheetminer in locating the regions belonging to beta-sheets in the intermediate-resolution density maps. Furthermore, sheetminer is completely complementary to all other existing computational methods, including helixhunter and threading algorithms. Their combined usage has the potential to significantly enhance the computational modeling capacity for a much more complete interpretation of structural data at intermediate resolutions, from which extraction of functional information would be more effective. This is particularly important in the field of structural genomics, in which the fast screening approach may not always yield crystals that diffract to atomic resolution. An exciting future application of sheetminer is as a valuable tool for revealing the structures of amyloid fibrils that are rich in beta-motifs.
机译:在这里,我们报告了一种新的计算方法,称为sheetminer,用于在密度图中以6至10A的中间分辨率挖掘β-表。该方法采用密度图的多步临时形态分析,以识别β-折叠的独特特征。在12个蛋白质晶体结构的密度图上进行了测试,该结构被人工模糊至中等分辨率。共有35个独立的β-折叠,其形态分布广泛。该方法成功定位了其中的34个,仅漏掉了一个。该方法还适用于实验性9A电子冷冻显微镜结构和8A X射线密度图。在这两种情况下,都发现薄片搜索结果与已知的高分辨率晶体结构非常吻合。总的来说,这些结果清楚地证明了sheetminer在定位中等分辨率密度图中属于β-sheets的区域时的鲁棒性。此外,sheetminer是对所有其他现有计算方法(包括helixhunter和线程算法)的完全补充。它们的组合使用有可能显着增强计算建模能力,以便以中等分辨率更完整地解释结构数据,从中提取功能信息将更加有效。这在结构基因组学领域尤其重要,在该领域中,快速筛选方法可能并不总是产生衍射到原子分辨率的晶体。薄板矿机的令人兴奋的未来应用是作为揭示富含β-基序的淀粉样蛋白原纤维结构的有价值的工具。

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