Journal
BIOMED RESEARCH INTERNATIONAL
Volume 2017, Issue -, Pages -Publisher
HINDAWI LTD
DOI: 10.1155/2017/5761517
Keywords
-
Funding
- National Natural Science Foundation of China [61571095]
- Fundamental Research Funds for the Central Universities of China [ZYGX2015Z006]
Ask authors/readers for more resources
Polystyrene surface-binding peptides (PSBPs) are useful as affinity tags to build a highly effective ELISA system. However, they are also a quite common type of target-unrelated peptides (TUPs) in the panning of phage-displayed random peptide library. As TUP, PSBP will mislead the analysis of panning results if not identified. Therefore, it is necessary to find a way to quickly and easily foretell if a peptide is likely to be a PSBP or not. In this paper, we describe PSBinder, a predictor based on SVM. To our knowledge, it is the first web server for predicting PSBP. The SVM model was built with the feature of optimized dipeptide composition and 87.02% (MCC = 0.74; AUC = 0.91) of peptides were correctly classified by fivefold cross-validation. PSBinder can be used to exclude highly possible PSBP from biopanning results or to find novel candidates for polystyrene affinity tags. Either way, it is valuable for biotechnology community.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available