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Automated data interpretation based on the concept of "negative signature mass" for mass-mapping disulfide structures of cystinyl proteins
Authors:Qi Jianfeng  Wu Wei  Borges Chad R  Hang Dehua  Rupp Matthew  Torng Eric  Watson J Throck
Institution:Department of Chemistry, Michigan State University, East Lansing, Michigan 48824, USA.
Abstract:An efficient method for data processing and interpretation is needed to support and extend disulfide mass-mapping methodology based on partial reduction and cyanylation-induced cleavage to proteins containing more than four cystines. Here, the concept of "negative signature mass" is introduced as the novel feature of an algorithm designed to identify the disulfide structure of a cystinyl protein given an input of mass spectral data and an amino acid sequence. The "negative signature mass" process is different from the conventional approach in that it does not directly rule-in disulfide linkages, but rather eliminates linkages from a list of all possible theoretical linkages, with the goal of ruling out enough linkages so that only one disulfide structure can be constructed. The operating principles and the effectiveness of the algorithm are described in the context of analyzing ribonuclease A, a 124-residue protein containing eight cysteines in the form of four cystines (disulfides).
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