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MS2DB: A Mass-Based Hashing Algorithm for the Identification of Disulfide Linkage Patterns in Protein Utilizing Mass Spectrometric Data

机译:MS2DB:一种基于质量的哈希算法,用于利用质谱数据识别蛋白质中的二硫键模式

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The tertiary structure and biological function of a protein can be better understood given knowledge of the number and location of its disulfide bonds. By utilizing mass spectrometric (MS) experimental procedures that produce spectra of the protein''s peptides joined by a disulfide bond, we can make initial identifications of these bonded cysteine pairings. The algorithmic problem then becomes how to match a theoretical mass space of all possible bonded peptides against the MS data. Our solution, MSHashID, utilizes the Expected Amino Acid Mass in combination with a hash structure to improve the time complexity of making an identification from worse than O(n2) to approximately O(n), where n is the size of the mass space. We have developed a software package, MS2DB, which includes an implementation of this algorithm. Experiments using published data show that the MSHashID algorithm efficiently makes the correct initial identifications, which can then be confirmed using tandem mass spectrometry (MS/MS).
机译:只要了解其二硫键的数量和位置,就可以更好地理解蛋白质的三级结构和生物学功能。通过利用产生二硫键连接的蛋白质肽谱的质谱(MS)实验程序,我们可以对这些键合的半胱氨酸配对进行初步鉴定。然后,算法问题就变成了如何将所有可能结合的肽的理论质量空间与MS数据进行匹配。我们的解决方案MSHashID利用预期的氨基酸质量与哈希结构相结合,将进行识别的时间复杂度从劣于O(n2)提高到大约O(n),其中n是质量空间的大小。我们已经开发了一个软件包MS2DB,其中包含该算法的实现。使用公开数据进行的实验表明,MSHashID算法可以有效地进行正确的初始识别,然后可以使用串联质谱(MS / MS)进行确认。

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