Sign in
BioinformaticsbioRxiv
Preprint

InterPep2: Global Peptide-Protein Docking with Structural Templates

Isak Johansson-ÅkheiD, Claudio MirabelloiD, Björn WallneriD

Abstract

MotivationInteractions between proteins and peptides or peptide-like intrinsically disordered regions are involved in many important biological processes, such as gene expression and cell life-cycle regulation. Experimentally determining the structure of such interactions is time-consuming, and because of the disordered nature of the ligand, the interactions are especially difficult to predict through software, requiring specialized solutions. Although several prediction-methods exist, most are limited in performance or availability.\n\nResultsInterPep2 is a freely available method for predicting the structure of peptide-protein interactions. We have previously shown that structural templates can be used to accurately predict peptide-protein binding sites, and that using templates from regular protein-protein interactions will increase the number of sites found. Here, we show that the same principle can be extended to dock the peptide to the binding surface using InterPep2. A key component of InterPep2 is the ability to score plausible interaction templates using a RandomForest trained to predict the DockQ-score using sequence and structural features. InterPep2 is tested on a difficult dataset of 251 peptide-protein complexes, where it correctly positions 136 (54%) at the correct site compared to 114 (45%) for the second best method. Analyzing the confidence score InterPep2 recalls more true positives across all specificity levels compared to the second best method, for example at 10% False Positive Rate it correctly identifies 59% of the complexes compared to 44% for the second best method.\n\nAvailabilityThe program is available from: http://wallnerlab.org/InterPep\n\nContactBjorn Wallner bjorn.wallner@liu.se

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISJohansson-Å '19Tsaban '22Mirabello '17Alam '17Chandra '23Johansson-Å '21
88% semantic matchBioinformatics
Isak Johansson-Åkhe, Claudio Mirabello, Björn Wallner·Scientific Reports·Mar 12, 2019· 71 citations