Department of Biochemistry and Molecular Biology, Complex Carbohydrate Research Center, University of Georgia, 315 Riverbend Road, Athens 30602, Georgia.
Department of Pathology and Laboratory Medicine, Emory Vaccine Center, Emory University, 7 Frist Ave, Atlanta 30317, Georgia.
Glycobiology. 2024 Apr 10;34(4). doi: 10.1093/glycob/cwae006.
Modern glycoproteomics experiments require the use of search engines due to the generation of countless spectra. While these tools are valuable, manual validation of search engine results is often required for detailed analysis of glycopeptides as false-discovery rates are often not reliable for glycopeptide data. Near-isobaric mismatches are a common source of misidentifications for the popular glycopeptide-focused search engine pGlyco3.0, and in this technical note we share a strategy and script that improves the accuracy of the search utilizing two manually validated datasets of the glycoproteins CD16a and HIV-1 Env as proof-of-principle.
现代糖蛋白质组学实验由于产生了无数的光谱,因此需要使用搜索引擎。虽然这些工具很有价值,但通常需要手动验证搜索引擎的结果,以便对糖肽进行详细分析,因为假发现率对于糖肽数据通常不可靠。等摩尔质量异位匹配是流行的糖肽重点搜索引擎 pGlyco3.0 中常见的误识别源,在本技术说明中,我们分享了一种策略和脚本,利用 CD16a 和 HIV-1 Env 两种经过手动验证的糖蛋白数据集作为原理验证,提高了搜索的准确性。