GalaxyPepDock: a protein–peptide docking tool based on interaction similarity and energy optimization

Abstract

Protein–peptide interactions are involved in a wide range of biological processes and are attractive targets for therapeutic purposes because of their small interfaces. Therefore, effective protein–peptide docking techniques can provide the basis for potential therapeutic applications by enabling an atomic-level understanding of protein interactions. With the increasing number of protein–peptide structures deposited in the protein data bank, the prediction accuracy of protein-peptide docking can be enhanced by utilizing the information provided by the database. The GalaxyPepDock web server, which is freely accessible at http://galaxy.seoklab.org/pepdock, performs similarity-based docking by finding templates from the database of experimentally determined structures and building models using energy-based optimization that allows for structural flexibility. The server can therefore effectively model the structural differences between the template and target protein–peptide complexes. The performance of GalaxyPepDock is superior to those of the other currently available web servers when tested on the PeptiDB set and on recently released complex structures. When tested on the CAPRI target 67, GalaxyPepDock generates models that are more accurate than the best server models submitted during the CAPRI blind prediction experiment.

Protection against β‐amyloid neurotoxicity by a non‐toxic endogenous N‐terminal β‐amyloid fragment and its active hexapeptide core sequence

“…To evaluate the potential interaction of the N‐Aβcore with known target Aβ receptors, we employed computational peptide docking (GalaxyPepDock under GalaxyWEB (Lee et al . )) using the X‐ray crystal structure of the Alpha7 nAChR‐AChBP (binding protein) chimera (Li et al . ).…”

Understanding the challenges of protein flexibility in drug design

“…The most common ones involve (i) a systematic search (e.g., exhaustive search, ensemble-based search, fragment-based search) or (ii) a stochastic search (e.g., Monte Carlo, evolutionary algorithm, swarm optimization, tabu search) [2], [5], [10]. Large ligands and peptides represent bigger challenges for docking, which might exceed the capabilities of many current approaches [11]- [15]. The treatment of ligand flexibility has been extensively reviewed elsewhere [2], [5], [10] and will not be specifically discussed here.…”

Protein-peptide molecular docking with large-scale conformational changes: the p53-MDM2 interaction

“…The flexibility of protein targets is usually neglected or very limited during docking. The state-of-the-art tools for protein-peptide docking are dedicated to exploration of peptide flexibility rather than flexibility of the receptor34567. Incorporation of large structural changes of protein targets in the explicit docking approach remains too computationally demanding for classical modeling tools2.…”