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Enhanced fold recognition using efficient short fragment clustering

机译:使用有效的短片段聚类增强的折叠识别

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The main structure aligner in the CCP4 Software Suite, SSM (Secondary Structure Matching) has a limited applicability on the intermediate stages of the structure solution process, when the secondary structure cannot be reliably computed due to structural incompleteness or a fragmented mainchain. In this study, we describe a new algorithm for the alignment and comparison of protein structures in CCP4, which was designed to overcome SSM's limitations but retain its quality and speed. The new algorithm, named GESAMT (General Efficient Structural Alignment of Macromolecular Targets), employs the old idea of deriving the global structure similarity from a promising set of locally similar short fragments, but uses a few technical solutions that make it considerably faster. A comparative sensitivity and selectivity analysis revealed an unexpected significant improvement in the fold recognition properties of the new algorithm, which also makes it useful for applications in the structural bioinformatics domain. The new tool is included in the CCP4 Software Suite starting from version 6.3.
机译:当由于结构不完整或主链不完整而无法可靠地计算二级结构时,CCP4软件套件中的主要结构对齐器SSM(二级结构匹配)在结构求解过程的中间阶段的适用性有限。在这项研究中,我们描述了一种用于比对和比较CCP4中蛋白质结构的新算法,该算法旨在克服SSM的局限性,但保留其质量和速度。新算法名为GESAMT(大分子目标的通用有效结构比对),采用了旧的思想,即从有希望的局部相似的短片段中推导全局结构相似性,但是使用了一些技术解决方案,从而使其速度大大提高。比较灵敏度和选择性分析显示,新算法的折叠识别特性出乎意料的显着改善,这也使其可用于结构生物信息学领域。从版本6.3开始,新工具包含在CCP4软件套件中。

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