Bugyi Fanni, Szabó Dániel, Szabó Győző, Révész Ágnes, Pape Veronika F S, Soltész-Katona Eszter, Tóth Eszter, Kovács Orsolya, Langó Tamás, Vékey Károly, Drahos László
Institute of Organic Chemistry, Research Centre for Natural Sciences, Magyar Tudósok krt 2, H-1117 Budapest, Hungary.
Hevesy György PhD School of Chemistry, Eötvös Loránd University, Pázmány Péter sétány 1/A, H-1117 Budapest, Hungary.
ACS Omega. 2021 Mar 15;6(11):7469-7477. doi: 10.1021/acsomega.0c05997. eCollection 2021 Mar 23.
Comprehensive analysis of post-translation modifications (PTMs) is an important mission of proteomics. However, the consideration of PTMs increases the search space and may therefore impair the efficiency of protein identification. Using thousands of proteomic searches, we investigated the practical aspects of considering multiple PTMs in Byonic searches for the maximization of protein and peptide hits. The inclusion of all PTMs, which occur with at least 2% frequency in the sample, has an advantageous effect on protein and peptide identification. A linear relationship was established between the number of considered PTMs and the number of reliably identified peptides and proteins. Even though they handle multiple modifications less efficiently, the results of MASCOT (using the Percolator function) and Andromeda (the search engine included in MaxQuant) became comparable to those of Byonic, in the case of a few PTMs.
翻译后修饰（PTM）的全面分析是蛋白质组学的一项重要任务。然而，对PTM的考虑会增加搜索空间，因此可能会降低蛋白质鉴定的效率。通过数千次蛋白质组学搜索，我们研究了在Byonic搜索中考虑多种PTM以最大化蛋白质和肽段匹配的实际情况。纳入样本中出现频率至少为2%的所有PTM，对蛋白质和肽段鉴定具有有利影响。在考虑的PTM数量与可靠鉴定的肽段和蛋白质数量之间建立了线性关系。尽管MASCOT（使用Percolator功能）和Andromeda（MaxQuant中包含的搜索引擎）处理多种修饰的效率较低，但在少数PTM的情况下，它们的结果与Byonic的结果相当。
