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

Badaczewska-Dawid, Aleksandra E.; Kmiecik, Sebastian; Koliński, Michał

doi:10.1101/2020.03.21.001396

Cited by 3 publications

(3 citation statements)

References 49 publications

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“…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 [ 41 , 59 ], GPCRs [ 60 ], and modeling proteolysis mechanisms [ 61 ].…”

Section: Methodsmentioning

confidence: 99%

Protein–Protein Docking with Large-Scale Backbone Flexibility Using Coarse-Grained Monte-Carlo Simulations

Kurciński

Kmiecik

Zalewski

et al. 2021

IJMS

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Most of the protein–protein docking methods treat proteins as almost rigid objects. Only the side-chains flexibility is usually taken into account. The few approaches enabling docking with a flexible backbone typically work in two steps, in which the search for protein–protein orientations and structure flexibility are simulated separately. In this work, we propose a new straightforward approach for docking sampling. It consists of a single simulation step during which a protein undergoes large-scale backbone rearrangements, rotations, and translations. Simultaneously, the other protein exhibits small backbone fluctuations. Such extensive sampling was possible using the CABS coarse-grained protein model and Replica Exchange Monte Carlo dynamics at a reasonable computational cost. In our proof-of-concept simulations of 62 protein–protein complexes, we obtained acceptable quality models for a significant number of cases.

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Section: Methodsmentioning

confidence: 99%

Protein–Protein Docking with Large-Scale Backbone Flexibility Using Coarse-Grained Monte-Carlo Simulations

Kurciński

Kmiecik

Zalewski

et al. 2021

IJMS

Self Cite

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show abstract

“…Its distinctive feature among other tools is the possibility of fast simulation of the large backbone rearrangements of both peptide and protein receptor during binding (see the review on protein-peptide docking tools [57]). The CABS-dock has been used in multiple applications (recently reviewed [55]), including docking to receptors with disordered fragments [39, 49], GPCRs [58], and modeling proteolysis mechanisms [59].…”

Section: Methodsmentioning

confidence: 99%

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

Kurciński

Kmiecik

Zalewski

et al. 2021

Preprint

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Structure prediction of protein-protein complexes is one of the most critical challenges in computational structural biology. It is often difficult to predict the complex structure, even for relatively rigid proteins. Modeling significant structural flexibility in protein docking remains an unsolved problem. This work demonstrates a protein-protein docking protocol with enhanced sampling that accounts for large-scale backbone flexibility. The docking protocol starts from unbound x-ray structures and is not using any binding site information. In docking, one protein partner undergoes multiple fold rearrangements, rotations, and translations during docking simulations, while the other protein exhibits small backbone fluctuations. Including significant backbone flexibility during the search for the binding site has been made possible using the CABS coarse-grained protein model and Replica Exchange Monte Carlo dynamics. In our simulations, we obtained acceptable quality models for the set of 12 protein-protein complexes, while for selected cases, models were close to high accuracy.

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“…In recent years, CABS-dock has been applied or extended to different modeling tasks. These include peptide docking with large structural changes of the receptor structure and disordered structures [ 7 , 8 ], docking with protein–peptide contact information [ 20 ], docking of peptides to GPCR structures [ 24 ] (see also recent review on CABS-dock development and applications [ 6 ]), and identification of peptide cleavage sites for protease–substrate systems [ 9 ].…”

Section: Methodsmentioning

confidence: 99%

Molecular Dynamics Scoring of Protein–Peptide Models Derived from Coarse-Grained Docking

2021

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One of the major challenges in the computational prediction of protein–peptide complexes is the scoring of predicted models. Usually, it is very difficult to find the most accurate solutions out of the vast number of sometimes very different and potentially plausible predictions. In this work, we tested the protocol for Molecular Dynamics (MD)-based scoring of protein–peptide complex models obtained from coarse-grained (CG) docking simulations. In the first step of the scoring procedure, all models generated by CABS-dock were reconstructed starting from their original C-alpha trace representations to all-atom (AA) structures. The second step included geometry optimization of the reconstructed complexes followed by model scoring based on receptor–ligand interaction energy estimated from short MD simulations in explicit water. We used two well-known AA MD force fields, CHARMM and AMBER, and a CG MARTINI force field. Scoring results for 66 different protein–peptide complexes show that the proposed MD-based scoring approach can be used to identify protein–peptide models of high accuracy. The results also indicate that the scoring accuracy may be significantly affected by the quality of the reconstructed protein receptor structures.

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

Cited by 3 publications

References 49 publications

Protein–Protein Docking with Large-Scale Backbone Flexibility Using Coarse-Grained Monte-Carlo Simulations

Protein–Protein Docking with Large-Scale Backbone Flexibility Using Coarse-Grained Monte-Carlo Simulations

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

Molecular Dynamics Scoring of Protein–Peptide Models Derived from Coarse-Grained Docking

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