PSBinder: A Web Service for Predicting Polystyrene Surface-Binding Peptides.

ABSTRACT: 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 possibl

SUBMITTER: Li N 

PROVIDER: S-EPMC5763211 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature