Literature DB >> 30698954

Evaluation of Predicted Protein-Protein Complexes by Binding Free Energy Simulations.

Till Siebenmorgen1, Martin Zacharias1.   

Abstract

The accurate prediction of protein-protein complex geometries is of major importance to ultimately model the complete interactome of interacting proteins in a cell. A major bottleneck is the realistic free energy evaluation of predicted docked structures. Typically, simple scoring functions applied to single-complex structures are employed that neglect conformational entropy and often solvent effects completely. The binding free energy of a predicted protein-protein complex can, however, be calculated using umbrella sampling (US) along a predefined dissociation/association coordinate of a complex. We employed atomistic US-molecular dynamics simulations including appropriate conformational and axial restraints and an implicit generalized Born solvent model to calculate binding free energies of a large set of docked decoys for 20 different complexes. Free energies associated with the restraints were calculated separately. In principle, the approach includes all energetic and entropic contributions to the binding process. The evaluation of docked complexes based on binding free energy calculation was in better agreement with experiment compared to a simple scoring based on energy minimization or MD refinement using exactly the same force field description. Even calculated absolute binding free energies of structures close to the native binding geometry showed a reasonable correlation to experiment. However, still for a number of complexes docked decoys of lower free energy than near-native geometries were found indicating inaccuracies in the force field or the implicit solvent model. Although time consuming the approach may open up a new route for realistic ranking of predicted geometries based on calculated free energy of binding.

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Year:  2019        PMID: 30698954     DOI: 10.1021/acs.jctc.8b01022

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  11 in total

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Journal:  Proteins       Date:  2019-11-25

2.  Exploring the Free-Energy Landscape and Thermodynamics of Protein-Protein Association.

Authors:  Celine Tse; Lauren Wickstrom; Mamuka Kvaratskhelia; Emilio Gallicchio; Ronald Levy; Nanjie Deng
Journal:  Biophys J       Date:  2020-08-12       Impact factor: 4.033

Review 3.  Challenges in protein docking.

Authors:  Ilya A Vakser
Journal:  Curr Opin Struct Biol       Date:  2020-08-21       Impact factor: 6.809

4.  Umbrella Sampling-Based Method to Compute Ligand-Binding Affinity.

Authors:  Son Tung Ngo; Minh Quan Pham
Journal:  Methods Mol Biol       Date:  2022

Review 5.  Prediction of Protein-Protein Binding Affinities from Unbound Protein Structures.

Authors:  Alberto Meseguer; Patricia Bota; Narcis Fernández-Fuentes; Baldo Oliva
Journal:  Methods Mol Biol       Date:  2022

6.  Computational Tools for Accurate Binding Free-Energy Prediction.

Authors:  Maria M Reif; Martin Zacharias
Journal:  Methods Mol Biol       Date:  2022

7.  DNA binding modes influence Rap1 activity in the regulation of telomere length and MRX functions at DNA ends.

Authors:  Diego Bonetti; Carlo Rinaldi; Jacopo Vertemara; Marco Notaro; Paolo Pizzul; Renata Tisi; Giuseppe Zampella; Maria Pia Longhese
Journal:  Nucleic Acids Res       Date:  2020-03-18       Impact factor: 16.971

8.  Enhanced Molecular Dynamics Method to Efficiently Increase the Discrimination Capability of Computational Protein-Protein Docking.

Authors:  Nicola Scafuri; Miguel A Soler; Andrea Spitaleri; Walter Rocchia
Journal:  J Chem Theory Comput       Date:  2021-10-15       Impact factor: 6.006

9.  First Principles Calculation of Protein-Protein Dimer Affinities of ALS-Associated SOD1 Mutants.

Authors:  Shawn C C Hsueh; Mark Nijland; Xubiao Peng; Benjamin Hilton; Steven S Plotkin
Journal:  Front Mol Biosci       Date:  2022-03-24

10.  Unbinding ligands from SARS-CoV-2 Mpro via umbrella sampling simulations.

Authors:  Nguyen Minh Tam; Trung Hai Nguyen; Vu Thi Ngan; Nguyen Thanh Tung; Son Tung Ngo
Journal:  R Soc Open Sci       Date:  2022-01-26       Impact factor: 2.963

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