Literature DB >> 7541840

A continuum model for protein-protein interactions: application to the docking problem.

R M Jackson1, M J Sternberg.   

Abstract

The prediction of protein-protein interactions in solution is a major goal of theoretical structural biology. Here, we implement a continuum description of the thermodynamic processes involved. The model differs considerably from previous models in its use of "molecular surface" area to describe the hydrophobic component to the free energy of conformational change in solution. We have applied this model to a data set of alternative docked conformations of protein-protein complexes which were generated independently of this work. It was found previously that commonly used energy evaluation techniques fail to distinguish between near-native and certain non-native complexes in this data set. Here, we found that an energy function that takes into account (1) total electrostatic free energy, (2) hydrophobic free energy and (3) loss in side-chain conformational energy was able to reliably discriminate between near-native and non-native configurations but only when molecular surface is used as a descriptor of the hydrophobic effect. It is shown that the molecular surface and the more conventional surface descriptor "solvent accessible surface" give very different quantitative measures of hydrophobicity. In terms of the contribution of different energy components to the free energy of complex formation it was found that loss in side-chain conformational entropy is a second order effect. Electrostatic interaction energy (which is commonly used to score docked conformations) was a poor indicator of complementarity when starting from unbound conformations. It was found that electrostatic desolvation energy and the hydrophobic contribution (based on a molecular surface area descriptor) are much less sensitive to local fluctuations in atomic structure than point-to-point interaction energies and thus may be more suited for use as a scoring function when docking unbound conformations, where atomic complementarity is much less apparent. Whilst a combined energy function was able to distinguish near-native from non-native conformations in the six systems studied here, it remains to be determined to what extent more sizeable conformational changes would influence the results.

Mesh:

Substances:

Year:  1995        PMID: 7541840     DOI: 10.1006/jmbi.1995.0375

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  38 in total

1.  Deciphering common failures in molecular docking of ligand-protein complexes.

Authors:  G M Verkhivker; D Bouzida; D K Gehlhaar; P A Rejto; S Arthurs; A B Colson; S T Freer; V Larson; B A Luty; T Marrone; P W Rose
Journal:  J Comput Aided Mol Des       Date:  2000-11       Impact factor: 3.686

2.  Selecting near-native conformations in homology modeling: the role of molecular mechanics and solvation terms.

Authors:  A Janardhan; S Vajda
Journal:  Protein Sci       Date:  1998-08       Impact factor: 6.725

3.  Comparison of binding energies of SrcSH2-phosphotyrosyl peptides with structure-based prediction using surface area based empirical parameterization.

Authors:  D A Henriques; J E Ladbury; R M Jackson
Journal:  Protein Sci       Date:  2000-10       Impact factor: 6.725

4.  Structure prediction of protein complexes by an NMR-based protein docking algorithm.

Authors:  O Kohlbache; A Burchardt; A Moll; A Hildebrandt; P Bayer; H P Lenhof
Journal:  J Biomol NMR       Date:  2001-05       Impact factor: 2.835

5.  Free energy decomposition of protein-protein interactions.

Authors:  S Y Noskov; C Lim
Journal:  Biophys J       Date:  2001-08       Impact factor: 4.033

6.  Computational mapping identifies the binding sites of organic solvents on proteins.

Authors:  Sheldon Dennis; Tamas Kortvelyesi; Sandor Vajda
Journal:  Proc Natl Acad Sci U S A       Date:  2002-03-19       Impact factor: 11.205

7.  Calculations of free-energy contributions to protein-RNA complex stabilization.

Authors:  M A Olson
Journal:  Biophys J       Date:  2001-10       Impact factor: 4.033

8.  A novel approach for assessing macromolecular complexes combining soft-docking calculations with NMR data.

Authors:  X J Morelli; P N Palma; F Guerlesquin; A C Rigby
Journal:  Protein Sci       Date:  2001-10       Impact factor: 6.725

9.  The effect of multiple binding modes on empirical modeling of ligand docking to proteins.

Authors:  R Brem; K A Dill
Journal:  Protein Sci       Date:  1999-05       Impact factor: 6.725

10.  Differential geometry based solvation model II: Lagrangian formulation.

Authors:  Zhan Chen; Nathan A Baker; G W Wei
Journal:  J Math Biol       Date:  2011-01-30       Impact factor: 2.259

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.