High-resolution global peptide-protein docking using fragments-based PIPER-FlexPepDock

Abstract

Peptide-protein interactions contribute a significant fraction of the protein-protein interactome. Accurate modeling of these interactions is challenging due to the vast conformational space associated with interactions of highly flexible peptides with large receptor surfaces. To address this challenge we developed a fragment based high-resolution peptide-protein docking protocol. By streamlining the Rosetta fragment picker for accurate peptide fragment ensemble generation, the PIPER docking algorithm for exhaustive fragment-receptor rigid-body docking and Rosetta FlexPepDock for flexible full-atom refinement of PIPER docked models, we successfully addressed the challenge of accurate and efficient global peptide-protein docking at high-resolution with remarkable accuracy, as validated on a small but representative set of peptide-protein complex structures well resolved by X-ray crystallography. Our approach opens up the way to high-resolution modeling of many more peptide-protein interactions and to the detailed study of peptide-protein association in general. PIPER-FlexPepDock is freely available to the academic community as a server at http://piperfpd.furmanlab.cs.huji.ac.il.

InterPep2: Global Peptide-Protein Docking with Structural Templates

“…As previously, a prediction counts as correct if within 4.0Å LRMSD from the native. Data for CABSdock, HADDOCK, pepATTRACT, and PIPER-FlexPepDock is taken directly from (Alam et al, 2017), in the form of near-native among top10, which is why no data regarding top1 or how many peptides are positioned at the correct site is shown.…”

“…In previous studies of global peptide-protein docking methods, a smaller set of 27 solved non-redundant structures of peptide-protein interaction complexes for which there exists determined unbound structures of the receptors have been used for evaluation and benchmarking of many methods (Alam et al, 2017). As this set has previously been used for benchmarking, it is possible to compare against otherwise computationally heavier methods or methods which are only available through web-servers with limited programmatical access, such as PIPER-FlexPepDock (Alam et al, 2017), pepATTRACT (Schindler et al, 2015), and HADDOCK (Dominguez et al, 2003).…”

“…The 50 fragments are then extracted from their full structures, and sequence is changed to that of the query peptide using the Rosetta fixbb application (Kuhlman and Baker, 2000). This protocol for generating peptide fragments is similar to that of PIPER-FlexPepDock (Alam et al, 2017), and has been shown to reliably sample near-native peptide conformations.…”

“…Thus, computational methods are crucial for guiding and designing experiments. Global peptide-docking prediction methods such as CABSdock, PIPER-FlexPepDock, pepATTRACT, and GalaxyPepDock have achieved high performances on individual benchmarks, but struggle to consistently produce reliable predictions (Kurcinski et al, 2015;Alam et al, 2017;Schindler et al, 2015;Lee et al, 2015). Local refinement predictions methods such as FlexPepDock, PEP-FOLD3, and DINC 2.0 have achieved high precision in the past, but require good starting positions (Raveh et al, 2010a;Lamiable et al, 2016;Antunes et al, 2017).…”

Protocols for all-atom reconstruction and high-resolution refinement of protein-peptide complex structures

“…However, most of them cannot be easily used to handle more than one protein chain in the reconstructed structure, and use structural template(s) of the protein backbone to enhance the reconstruction accuracy or to maintain the appropriate interface of protein-peptide interaction. With regard to structure refinement of protein-peptide complexes, the performance robustness and accuracy of the Rosetta FlexPepDock tool has been demonstrated in many studies [7][8][9][10][11].…”