BACKGROUND Computational methods provide approaches to identify epitopes in protein Ags to help characterizing potential biomarkers identified by high-throughput genomic or proteomic experiments. PEPOP version 1.0 was developed as an antigenic or immunogenic peptide prediction tool. We have now improved this tool by implementing 32 new methods (PEPOP version 2.0) to guide the choice of peptides that mimic discontinuous epitopes and thus potentially able to replace the cognate protein Ag in its interaction with an Ab. In the present work, we describe these new methods and the benchmarking of their performances. RESULTS Benchmarking was carried out by comparing the peptides predicted by the different methods and the corresponding epitopes determined by X-ray crystallography in a dataset of 75 Ag-Ab complexes. The Sensitivity (Se) and Positive Predictive Value (PPV) parameters were used to assess the performance of these methods. The results were compared to that of peptides obtained either by chance or by using the SUPERFICIAL tool, the only available comparable method. CONCLUSION The PEPOP methods were more efficient than, or as much as chance, and 33 of the 34 PEPOP methods performed better than SUPERFICIAL. Overall, "optimized" methods (tools that use the traveling salesman problem approach to design peptides) can predict peptides that best match true epitopes in most cases.

中文翻译：

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对模拟不连续表位的PEPOP方法进行基准测试。

背景技术计算方法提供了鉴定蛋白质Ag中的表位的方法，以帮助表征通过高通量基因组或蛋白质组学实验鉴定的潜在生物标记。开发了PEPOP版本1.0作为抗原或免疫原性肽预测工具。现在，我们已经通过实施32种新方法（PEPOP 2.0版）来改进该工具，以指导选择模拟不连续表位的肽，从而有可能在与Ab相互作用时替代同源蛋白Ag。在当前的工作中，我们描述了这些新方法及其性能基准。结果通过在75种Ag-Ab络合物的数据集中比较通过不同方法预测的肽段和通过X射线晶体学测定的相应表位，进行了基准测试。灵敏度（Se）和正预测值（PPV）参数用于评估这些方法的性能。将结果与偶然获得的或通过使用SUPERFICIAL工具（唯一可用的可比较方法）获得的肽的结果进行比较。结论PEPOP方法比偶然方法更有效，甚至更高，并且34种PEPOP方法中有33种的表现优于SUPERFICIAL。总体而言，“优化”方法（使用旅行商问题方法设计肽段的工具）可以预测在大多数情况下最匹配真实表位的肽段。结论PEPOP方法比偶然方法更有效，甚至更多，并且34种PEPOP方法中有33种的表现优于SUPERFICIAL。总体而言，“优化”方法（使用旅行商问题方法设计肽段的工具）可以预测在大多数情况下最匹配真实表位的肽段。结论PEPOP方法比偶然方法更有效，甚至更多，并且34种PEPOP方法中有33种的表现优于SUPERFICIAL。总体而言，“优化”方法（使用旅行商问题法设计肽段的工具）可以预测在大多数情况下最匹配真实表位的肽段。