多肽组学分析是解析加工过程中多肽变化规律的关键。该文主要就PepOSX软件在已知肽混标和食源性蛋白酶解产物中的多肽组学鉴定应用效果进行评价，并探讨了不同鉴定方式、工作参数对单多肽检出率和鉴定结果准确率的影响。结果表明：Exhaust引擎在不依赖序列库的条件下，对胶原肽和酪蛋白肽混标的鉴定结果准确率分别为67.86%和36.36%，对应准确检出率达80%和100%，反映该引擎对发现未知短肽具有较好的适应性；Search引擎基于序列搜库，对前述混标的鉴定结果准确率分别高达71.43%和90.48%，检出率分别高达91.30%和100%，展现对已知蛋白源样品分析的优越性能。将上述引擎联动用于酶解产物的组学分析，并将其与SEQUEST、MyriMatch和X! Tandem进行对比，发现PepOSX的准确检出率远优于其他三者，且在酪蛋白、大豆蛋白酶解产物的鉴定中获得了约3~4倍于后者的鉴定数量，充分展示了PepOSX在非特异性多肽鉴定中的适用性与可靠性。未来，PepOSX将有望为探索新活性肽或揭示多肽变化机制提供有效的技术支持。

Peptidomic analysis is the key to elucidating the changing trend of peptides during processing. In this paper, the performance of the PepOSX software in peptidomic identification of the peptides in food-derived protein hydrolysates spiked with known peptide standards was evaluated, and the effects of different identification approaches and working parameters on the detection rates and accuracy of single peptides were studied. For the sequence database-independent analysis of the known collagen and casein peptide standard mixtures, the accuracy rates of the Exhaust engine were 67.86% and 36.36%, respectively, and the corresponding detection rates reached 80% and 100%, respectively, indicating the good adaptivity of the engine for discovering unknown short peptides. The accuracy rates of the Search engine based on sequence database for the identification of the above-mentioned mixed standards were as high as 71.43% and 90.48%, respectively, with the corresponding detection rates being 91.30% and 100%, showing the superior capabilities of the engine in analyzing peptides from the samples with known protein sources. The above-mentioned engines were combined and applied in peptidomic analysis of protein hydrolysates. Compared with the performance of SEQUEST, MyriMatch and X! Tandem, PepOSX has a much higher accuracy rate, and the number of identified peptides rom the casein and soybean protein hydrolysates was about 3~4 times that of the latter. This fully demonstrated the applicability and reliability of the PepOSX workstation in the identification of non-specific peptides. In the future, PepOSX is expected to provide effective technical support for exploring new bio-active peptides or revealing the mechanism underlying the changes in peptides.

广东省科技创新战略专项市县科技创新支撑（大专项+任务清单）项目-暨2023年江门市关键核心技术“揭榜挂帅”制项目（2023780200060009632）；广东省基础与应用基础研究基金联合基金青年基金项目（2022A1515110711）；五邑大学创新创业基金项目（2023111500000432；5081700304XJ）