ClusPro PeptiDock: efficient global docking of peptide recognition motifs using FFT

2017

115 citations recorded by the source corpus.

Summary We present an approach for the efficient docking of peptide motifs to their free receptor structures. Using a motif based search, we can retrieve structural fragments from the Protein Data Bank (PDB) that are very similar to the peptide's final, bound conformation. We use a Fast Fourier Transform (FFT) based docking method to quickly perform global rigid body docking of these fragments to the receptor. According to CAPRI peptide docking criteria, an acceptable conformation can often be found among the top‐ranking predictions. Availability and Implementation The method is available as part of the protein‐protein docking server ClusPro at https://peptidock.cluspro.org/nousername.php. Contact midas@laufercenter.org or oraf@ekmd.huji.ac.il Supplementary information Supplementary data are available at Bioinformatics online.

Subfields: Clinical Psychology, Plant Science, Tourism, Leisure and Hospitality Management

Citations in the corpus

• Harnessing protein folding neural networks for peptide–protein docking (2021, unknown): “As with PFPD, many focus on efficient low-resolution docking (26,27), to be combined followed by high resolution refinement (e.”
• A Comprehensive Review on Current Advances in Peptide Drug Development and Design (2019, unknown): “The generated peptide conformations are next rigid-body docked in one simulation round [104,105].”
• Improving peptide-protein docking with AlphaFold-Multimer using forced sampling (2021, unknown): “In this study, ZDOCK was used to generate 54,000 decoys for each peptide conformation generated in the early steps of the InterPep2 protocol, similar to earlier ZDOCK studies and to ClusPro Peptidock or PIPER-FlexPepDock (Alam et al., 2017; Porter et al., 2017; Wallner and Mirabello, 2017).”