Literature DB >> 11468354

How common is the funnel-like energy landscape in protein-protein interactions?

A Tovchigrechko1, I A Vakser.   

Abstract

The goal of this study is to verify the concept of the funnel-like intermolecular energy landscape in protein-protein interactions by use of a series of computational experiments. Our preliminary analysis revealed the existence of the funnel in many protein-protein interactions. However, because of the uncertainties in the modeling of these interactions and the ambiguity of the analysis procedures, the detection of the funnels requires detailed quantitative approaches to the energy landscape analysis. A number of such approaches are presented in this study. We show that the funnel detection problem is equivalent to a problem of distinguishing between distributions of low-energy intermolecular matches in the funnel and in the low-frequency landscape fluctuations. If the fluctuations are random, the decision about whether the minimum is the funnel is equivalent to determining whether this minimum is significantly different from a would-be random one. A database of 475 nonredundant cocrystallized protein-protein complexes was used to re-dock the proteins by use of smoothed potentials. To detect the funnel, we developed a set of sophisticated models of random matches. The funnel was considered detected if the binding area was more populated by the low-energy docking predictions than by the matches generated in the random models. The number of funnels detected by use of different random models varied significantly. However, the results confirmed that the funnel may be the general feature in protein-protein association.

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Year:  2001        PMID: 11468354      PMCID: PMC2374089          DOI: 10.1110/ps.8701

Source DB:  PubMed          Journal:  Protein Sci        ISSN: 0961-8368            Impact factor:   6.725


  23 in total

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Authors:  C J Camacho; D W Gatchell; S R Kimura; S Vajda
Journal:  Proteins       Date:  2000-08-15

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Authors:  B A Shoemaker; J J Portman; P G Wolynes
Journal:  Proc Natl Acad Sci U S A       Date:  2000-08-01       Impact factor: 11.205

3.  Molecular surface recognition: determination of geometric fit between proteins and their ligands by correlation techniques.

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Journal:  Proc Natl Acad Sci U S A       Date:  1992-03-15       Impact factor: 11.205

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Authors:  I A Vakser
Journal:  Biopolymers       Date:  1996-09       Impact factor: 2.505

5.  A dataset of protein-protein interfaces generated with a sequence-order-independent comparison technique.

Authors:  C J Tsai; S L Lin; H J Wolfson; R Nussinov
Journal:  J Mol Biol       Date:  1996-07-26       Impact factor: 5.469

6.  Protein-protein interaction at crystal contacts.

Authors:  J Janin; F Rodier
Journal:  Proteins       Date:  1995-12

7.  Long-distance potentials: an approach to the multiple-minima problem in ligand-receptor interaction.

Authors:  I A Vakser
Journal:  Protein Eng       Date:  1996-01

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Authors:  I A Vakser
Journal:  Protein Eng       Date:  1995-04

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Authors:  I A Vakser; C Aflalo
Journal:  Proteins       Date:  1994-12

10.  Comparative protein modelling by satisfaction of spatial restraints.

Authors:  A Sali; T L Blundell
Journal:  J Mol Biol       Date:  1993-12-05       Impact factor: 5.469

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  27 in total

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Authors:  Sulin Jiang; Andrei Tovchigrechko; Ilya A Vakser
Journal:  Protein Sci       Date:  2003-08       Impact factor: 6.725

2.  Docking of protein models.

Authors:  Andrei Tovchigrechko; Christopher A Wells; Ilya A Vakser
Journal:  Protein Sci       Date:  2002-08       Impact factor: 6.725

3.  Downhill kinetics of biomolecular interface binding: globally connected scenario.

Authors:  Jin Wang; Weimin Huang; Hongyang Lu; Erkang Wang
Journal:  Biophys J       Date:  2004-10       Impact factor: 4.033

4.  Quantifying the kinetic paths of flexible biomolecular recognition.

Authors:  Jin Wang; Kun Zhang; Hongyang Lu; Erkang Wang
Journal:  Biophys J       Date:  2006-04-14       Impact factor: 4.033

5.  The ruggedness of protein-protein energy landscape and the cutoff for 1/r(n) potentials.

Authors:  Anatoly M Ruvinsky; Ilya A Vakser
Journal:  Bioinformatics       Date:  2009-02-23       Impact factor: 6.937

6.  Protein-protein alternative binding modes do not overlap.

Authors:  Petras J Kundrotas; Ilya A Vakser
Journal:  Protein Sci       Date:  2013-07-03       Impact factor: 6.725

7.  Conformer-specific characterization of nonnative protein states using hydrogen exchange and top-down mass spectrometry.

Authors:  Guanbo Wang; Rinat R Abzalimov; Cedric E Bobst; Igor A Kaltashov
Journal:  Proc Natl Acad Sci U S A       Date:  2013-11-25       Impact factor: 11.205

8.  Chasing funnels on protein-protein energy landscapes at different resolutions.

Authors:  Anatoly M Ruvinsky; Ilya A Vakser
Journal:  Biophys J       Date:  2008-05-30       Impact factor: 4.033

9.  Stochastic gating and drug-ribosome interactions.

Authors:  Andrea C Vaiana; Kevin Y Sanbonmatsu
Journal:  J Mol Biol       Date:  2008-12-24       Impact factor: 5.469

10.  Computational study for protein-protein docking using global optimization and empirical potentials.

Authors:  Kyoungrim Lee
Journal:  Int J Mol Sci       Date:  2008-01-22       Impact factor: 6.208

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