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

Abstract EN

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.