C. Bailey-Kellogg, J. Kelley, Clifford Stein, B. Donald
{"title":"Reducing Mass Degeneracy in SAR by MS by Stable Isotopic Labeling","authors":"C. Bailey-Kellogg, J. Kelley, Clifford Stein, B. Donald","doi":"10.1089/106652701300099056","DOIUrl":null,"url":null,"abstract":"Mass spectrometry (MS) promises to be an invaluable tool for functional genomics, by supporting low-cost, high-throughput experiments. However, large-scale MS faces the potential problem of mass degeneracy---indistinguishable masses for multiple biopolymer fragments (e.g., from a limited proteolytic digest). This paper studies the tasks of planning and interpreting MS experiments that use selective isotopic labeling, thereby substantially reducing potential mass degeneracy. Our algorithms support an experimental--computational protocol called structure-activity relation by mass spectrometry (SAR by MS) for elucidating the function of protein-DNA and protein-protein complexes. SAR by MS enzymatically cleaves a crosslinked complex and analyzes the resulting mass spectrum for mass peaks of hypothesized fragments. Depending on binding mode, some cleavage sites will be shielded; the absence of anticipated peaks implicates corresponding fragments as either part of the interaction region or inaccessible due to conformational change upon binding. Thus, different mass spectra provide evidence for different structure--activity relations. We address combinatorial and algorithmic questions in the areas of data analysis (constraining binding mode based on mass signature) and experiment planning (determining an isotopic labeling strategy to reduce mass degeneracy and aid data analysis). We explore the computational complexity of these problems, obtaining upper and lower bounds. We report experimental results from implementations of our algorithms.","PeriodicalId":79420,"journal":{"name":"Proceedings. International Conference on Intelligent Systems for Molecular Biology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2000-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1089/106652701300099056","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. International Conference on Intelligent Systems for Molecular Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1089/106652701300099056","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Mass spectrometry (MS) promises to be an invaluable tool for functional genomics, by supporting low-cost, high-throughput experiments. However, large-scale MS faces the potential problem of mass degeneracy---indistinguishable masses for multiple biopolymer fragments (e.g., from a limited proteolytic digest). This paper studies the tasks of planning and interpreting MS experiments that use selective isotopic labeling, thereby substantially reducing potential mass degeneracy. Our algorithms support an experimental--computational protocol called structure-activity relation by mass spectrometry (SAR by MS) for elucidating the function of protein-DNA and protein-protein complexes. SAR by MS enzymatically cleaves a crosslinked complex and analyzes the resulting mass spectrum for mass peaks of hypothesized fragments. Depending on binding mode, some cleavage sites will be shielded; the absence of anticipated peaks implicates corresponding fragments as either part of the interaction region or inaccessible due to conformational change upon binding. Thus, different mass spectra provide evidence for different structure--activity relations. We address combinatorial and algorithmic questions in the areas of data analysis (constraining binding mode based on mass signature) and experiment planning (determining an isotopic labeling strategy to reduce mass degeneracy and aid data analysis). We explore the computational complexity of these problems, obtaining upper and lower bounds. We report experimental results from implementations of our algorithms.
质谱(MS)通过支持低成本、高通量的实验,有望成为功能基因组学的宝贵工具。然而,大规模MS面临着质量退化的潜在问题——多个生物聚合物片段(例如,来自有限的蛋白水解消化)无法区分的质量。本文研究了计划和解释使用选择性同位素标记的质谱实验的任务,从而大大降低了潜在的质量简并。我们的算法支持一种称为质谱结构-活性关系(SAR by MS)的实验计算方案,用于阐明蛋白质- dna和蛋白质-蛋白质复合物的功能。通过质谱分析合成SAR酶切交联复合物,并分析产生的质谱为假设片段的质量峰。根据结合方式的不同,一些裂解位点会被屏蔽;预期峰的缺失意味着相应的片段要么是相互作用区域的一部分,要么是由于结合时构象的变化而无法进入的。因此,不同的质谱为不同的构效关系提供了证据。我们解决了数据分析(基于质量签名的约束绑定模式)和实验规划(确定同位素标记策略以减少质量简并并辅助数据分析)领域的组合和算法问题。我们探讨了这些问题的计算复杂度,得到了上界和下界。我们报告了算法实现的实验结果。