Open AccessThis article is
- freely available
Epitope Prediction Based on Random Peptide Library Screening: Benchmark Dataset and Prediction Tools Evaluation
Faculty of Chemistry, Northeast Normal University, Changchun 130024, China
School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China
National Engineering Laboratory for Druggable Gene and Protein Screening, Northeast Normal University, Changchun 130024, China
* Authors to whom correspondence should be addressed.
Received: 28 February 2011; in revised form: 1 June 2011 / Accepted: 10 June 2011 / Published: 16 June 2011
Abstract: Epitope prediction based on random peptide library screening has become a focus as a promising method in immunoinformatics research. Some novel software and web-based servers have been proposed in recent years and have succeeded in given test cases. However, since the number of available mimotopes with the relevant structure of template-target complex is limited, a systematic evaluation of these methods is still absent. In this study, a new benchmark dataset was defined. Using this benchmark dataset and a representative dataset, five examples of the most popular epitope prediction software products which are based on random peptide library screening have been evaluated. Using the benchmark dataset, in no method did performance exceed a 0.42 precision and 0.37 sensitivity, and the MCC scores suggest that the epitope prediction results of these software programs are greater than random prediction about 0.09–0.13; while using the representative dataset, most of the values of these performance measures are slightly improved, but the overall performance is still not satisfactory. Many test cases in the benchmark dataset cannot be applied to these pieces of software due to software limitations. Moreover chances are that these software products are overfitted to the small dataset and will fail in other cases. Therefore finding the correlation between mimotopes and genuine epitope residues is still far from resolved and much larger dataset for mimotope-based epitope prediction is desirable.
Keywords: epitope prediction; mimotope; template-target complex; benchmark dataset; evaluation
Citations to this Article
Cite This Article
MDPI and ACS Style
Sun, P.; Chen, W.; Huang, Y.; Wang, H.; Ma, Z.; Lv, Y. Epitope Prediction Based on Random Peptide Library Screening: Benchmark Dataset and Prediction Tools Evaluation. Molecules 2011, 16, 4971-4993.
Sun P, Chen W, Huang Y, Wang H, Ma Z, Lv Y. Epitope Prediction Based on Random Peptide Library Screening: Benchmark Dataset and Prediction Tools Evaluation. Molecules. 2011; 16(6):4971-4993.
Sun, Pingping; Chen, Wenhan; Huang, Yanxin; Wang, Hongyan; Ma, Zhiqiang; Lv, Yinghua. 2011. "Epitope Prediction Based on Random Peptide Library Screening: Benchmark Dataset and Prediction Tools Evaluation." Molecules 16, no. 6: 4971-4993.