Peptide cyclisation
The generation of cyclic peptides usually involve the formation of a disulphide bridge between two cysteins or the formation of a peptide bond between the N-terminus and C-terminus residues.
This can be performed by haddock3 in a two step process, by first generating restraints between the two resiudes involved to induce a pre-cyclic conformation, and then re-generating the topology with an increased range of chemical bond detection (tuning cyclicpept_dist, disulphide_dist and turning on the cyclicpept parameters in [topoaa] module), therefore detecting and creating the covalent cyclic bond and refining again.
Protocol described in: https://doi.org/10.1021/acs.jctc.2c00075
Two examples are provided in examples/peptide-cyclisation/:
- 1SFI, a 14 residue cyclic peptide with both backbone and disulphide bridge cyclisation: cyclise-peptide-full.cfg
- 3WNE, a 6 residue backbone cyclic peptide
The input peptide was generated using PyMOL, using beta and polyproline initial conformation (available in examples/peptide-cyclisation/data/1sfi_peptide-ensemble.pdb).
The first step is using the [flexref] module, setting the unambig_fname to 1sfi_unambig.tbl to drive both the backbone and disulphide bridge cyclisation, giving full flexibility to the peptide (with fle_sta_1, fle_end_1, fle_seg_1 parameters), increasing the number steps by a factor 10 to allow for more flexible refinement (mdsteps_rigid, mdsteps_cool1, mdsteps_cool2, mdsteps_cool3), turning off the electrostatic elecflag = false. By setting sampling_factor = 200, we will generate 200 replicas with different initial seeds for each of the input conformations (in this case 2).
This is followed by an short molecular dynamics simulation in explicit solvent [mdref], also giving full flexibility to the peptide (with fle_sta_1, fle_end_1, fle_seg_1 parameters).
A RMSD clustering step is perfomed using [rmsdmatrix], [clustrmsd] (with criterion="maxclust" and n_clusters=50) to generate a subset of 50 clusters, finalized by [seletopclusts] module setting top_models=1, to only extract one single model per clusters.
[topoaa] module is then used again to re-generate the topology. In this case the three important parameters (cyclicpept_dist, disulphide_dist, and cyclicpept) are set, allowing for the detection of the disulphide bridge and peptide bond at higher distance, therefore generating the proper cyclicised topology.
A second round of [emref], [flexref] and [mdref] is then performed, allowing to reduce the length of the newly formed chemical bonds and optimise the cyclic peptide conformation.
The [caprieval] module is called at various stages during the workflow to assess the conformation of the peptide with respect to the known reference structure. Note that in this case, only the global_rmsd value is computed, as the structure is not a complex.