PEP-FOLD: an online resource for de novo peptide structure prediction
By Julien Maupetit, Philippe Derreumaux, Pierre Tufféry. Nucleic Acids Res., 2009
406 citations recorded by the source corpus.
Rational peptide design and large-scale prediction of peptide structure from sequence remain a challenge for chemical biologists. We present PEP-FOLD, an online service, aimed at de novo modelling of 3D conformations for peptides between 9 and 25 amino acids in aqueous solution. Using a hidden Markov model-derived structural alphabet (SA) of 27 four-residue letters, PEP-FOLD first predicts the SA letter profiles from the amino acid sequence and then assembles the predicted fragments by a greedy procedure driven by a modified version of the OPEP coarse-grained force field. Starting from an amino acid sequence, PEP-FOLD performs series of 50 simulations and returns the most representative conformations identified in terms of energy and population. Using a benchmark of 25 peptides with 9–23 amino acids, and considering the reproducibility of the runs, we find that, on average, PEP-FOLD locates lowest energy conformations differing by 2.6 Å Cα root mean square deviation from the full NMR structures. PEP-FOLD can be accessed at http://bioserv.rpbs.univ-paris-diderot.fr/PEP-FOLD
Subfields: Molecular Biology
View Paper: https://www.semanticscholar.org/paper/aa2fdc80d95f1dbcfc7fb72026e905ae2e2dcf94
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Molecular Biology
- Pierre Thévenet
- Philippe Derreumaux
- Pierre Tufféry
- Julien Rey
- Alexis Lamiable
- Marek Vavrusa
- Julien Maupetit
Citations in the corpus
- PEP-FOLD3: faster de novo structure prediction for linear peptides in solution and in complex (2016, methodology): “These include facilities such as CycloPS (11) for the preparation of cyclic peptides, and servers for the de novo structure prediction of peptides, including PEPStr and PEPStrMod (12), PEP-FOLD (13,14) and PEPLook (15).”
- PEP-FOLD: an updated de novo structure prediction server for both linear and disulfide bonded cyclic peptides (2012, methodology): “The 3D prediction scheme is very similar to that reported in (11) and (23).”