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Blind testing of cross-linking/mass spectrometry hybrid methods in CASP11

机译:CASP11中交联/质谱混合方法的盲法测试

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摘要

Hybrid approaches combine computational methods with experimental data. The information contained in the experimental data can be leveraged to probe the structure of proteins otherwise elusive to computational methods. Compared with computational methods, the structures produced by hybrid methods exhibit some degree of experimental validation. In spite of these advantages, most hybrid methods have not yet been validated in blind tests, hampering their development. Here, we describe the first blind test of a specific cross-link based hybrid method in CASP. This blind test was coordinated by the CASP organizers and utilized a novel, high-density cross-linking/mass-spectrometry (CLMS) approach that is able to collect high-density CLMS data in a matter of days. This experimental protocol was developed in the Rappsilber laboratory. This approach exploits the chemistry of a highly reactive, photoactivatable cross-linker to produce an order of magnitude more cross-links than homobifunctional cross-linkers. The Rappsilber laboratory generated experimental CLMS data based on this protocol, submitted the data to the CASP organizers which then released this data to the CASP11 prediction groups in a separate, CLMS assisted modeling experiment. We did not observe a clear improvement of assisted models, presumably because the properties of the CLMS data-uncertainty in cross-link identification and residue-residue assignment, and uneven distribution over the protein-were largely unknown to the prediction groups and their approaches were not yet tailored to this kind of data. We also suggest modifications to the CLMS-CASP experiment and discuss the importance of rigorous blind testing in the development of hybrid methods. (C) 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.
机译:混合方法将计算方法与实验数据结合在一起。实验数据中包含的信息可用于探查蛋白质的结构,否则将无法利用计算方法。与计算方法相比,混合方法产生的结构表现出一定程度的实验验证。尽管有这些优点,但大多数混合方法尚未在盲法测试中得到验证,从而阻碍了它们的发展。在这里,我们描述了一种基于特定交联的混合方法在CASP中的首次盲测。该盲测由CASP组织者协调,并采用了一种新颖的高密度交联/质谱(CLMS)方法,能够在几天内收集高密度CLMS数据。此实验协议是在Rappsilber实验室开发的。这种方法利用了高反应性,可光活化的交联剂的化学作用,以产生比同双功能交联剂多一个数量级的交联。 Rappsilber实验室根据此协议生成了实验性CLMS数据,并将数据提交给CASP组织者,然后组织者在单独的CLMS辅助建模实验中将该数据发布给CASP11预测小组。我们没有观察到辅助模型的明显改善,大概是因为CLMS数据不确定性在交联识别和残基-残基分配中的特性以及蛋白质上的不均匀分布在很大程度上是预测组及其方法所未知的。尚未针对此类数据量身定制。我们还建议对CLMS-CASP实验进行修改,并讨论在开发混合方法中进行严格盲测的重要性。 (C)2016 The Authors Proteins:Structure,Function,and Bioinformatics由Wiley Periodicals,Inc.出版

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