Docking of peptides to GPCRs using a combination of CABS-dock with FlexPepDock refinement

Abstract

The structural description of peptide ligands bound to G protein-coupled receptors (GPCRs) is important for the discovery of new drugs and deeper understanding of the molecular mechanisms of life. Here we describe a three-stage protocol for the molecular docking of peptides to GPCRs using a set of different programs: (1) CABS-dock for docking fully flexible peptides; (2) PD2 method for the reconstruction of atomistic structures from C-alpha traces provided by CABS-dock and (3) Rosetta FlexPepDock for the refinement of protein–peptide complex structures and model scoring. We evaluated the proposed protocol on the set of seven different GPCR–peptide complexes (including one containing a cyclic peptide), for which crystallographic structures are available. We show that CABS-dock produces high resolution models in the sets of top-scored models. These sets of models, after reconstruction to all-atom representation, can be further improved by Rosetta high-resolution refinement and/or minimization, leading in most of the cases to sub-Angstrom accuracy in terms of interface root-mean-square-deviation measure.

Protein-protein docking with large-scale backbone flexibility using coarse-grained Monte-Carlo simulations

“…Its distinctive feature among other tools is the possibility of fast simulation of the large backbone rearrangements of both peptide and protein receptors during binding (see the review on protein-peptide docking tools [58]). In addition, the CABS-dock has been used in multiple applications (recently reviewed [56]), including docking to receptors with disordered fragments [40,50], GPCRs [59], and modeling proteolysis mechanisms [60].…”

Multiscale Modeling of Amyloid Fibrils Formed by Aggregating Peptides Derived from the Amyloidogenic Fragment of the A-Chain of Insulin

“…Such a knowledge-based force field has been derived by statistical analysis of structures accessible in properly sorted PDB [19] entries to avoid overrepresentation of the most frequent folds. The CABS method has proven to be an efficient tool for de novo structure prediction [20][21][22], comparative modeling, simulation of protein dynamics, and protein-peptide docking [23,24], including free docking of small proteins to protein receptors [25].…”

“…However, it needs to be stressed that the presented models were the best (with the lowest values of RMSD when compared to the reference structure) found in the set of 100 top-scored structures resulting from 10 independent docking simulations for each system. The identification of the most accurate structure in the generated model set of top-scored structures is always a challenging task [14,23,24], and many different scoring methods have been developed for such a purpose [12,40]. The obtained fibril models reveal a high degree of similarity to the reference experimentally determined structures.…”

“…The CABS-dock method has proven to be a very efficient and versatile tool for modeling a wide range of protein and peptide systems [12,14], including protein-peptide docking [13,14], docking of peptides to membrane receptors [23], peptide docking with large structural changes of the protein receptor and disordered structures [42,43] and also identification of peptide cleavage sites for protease-substrate systems [24]. We also showed above that this method is effective for the prediction of protofilaments formed by even longer peptides (with more than 20 amino acid residues).…”

“…A straightforward scoring method has been proposed to evaluate and select the most reliable structure of protofilaments for the further construction of amyloid fibril models. Since amyloid fibrils consist of a large number of identical peptide chains forming long stacks of β-sheets with a quasitranslational symmetry along the long fibril axis [23], all peptide monomers in the predicted protofilament model should have very similar chain conformations. We used the symmetry criteria to select the best models of protofilaments.…”