Literature DB >> 8756522

Low-resolution docking: prediction of complexes for underdetermined structures.

I A Vakser1.   

Abstract

One of the most fundamental questions concerning ligand-receptor interaction is whether such a process of intermolecular association is generally determined by local structural elements of the participating molecules, or whether there are also large-scale motifs in molecule structures that facilitate complex formation. From the point of view of practical docking computations, the elaborate character of local structural details in ligand-receptor interaction creates a large number of false-positive matches, which interfere with determination of the best fit. Another significant obstacle in protein docking is the problem of structural data inaccuracy (poor structure resolution, conformational changes upon complex formation, etc.). Our study [Vakser (1995) Protein Eng., 8, 371-377], based on ultralow (approximately 7 A resolution) representation of molecular structures, allowes to average all high-resolution structural details, and still predict most of the structural features of the ligand-receptor complex. The approach dramatically improves the signal-to-noise ratio in determination of the best fit, and moves the structure inaccuracy tolerance to the range of the macrostructure. In the present paper, we describe a further validation of the main principles of this approach and a detailed analysis of the low-resolution docking results. This includes clustering of ligand positions around the receptor molecule and cross-validation of ligands and receptors from different complexes. We also discuss the important implications of the approach to the multiple-minima problem and a possible role of different structural elements in the recognition mechanism.

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Year:  1996        PMID: 8756522     DOI: 10.1002/(SICI)1097-0282(199609)39:3%3C455::AID-BIP16%3E3.0.CO;2-A

Source DB:  PubMed          Journal:  Biopolymers        ISSN: 0006-3525            Impact factor:   2.505


  41 in total

1.  A systematic study of low-resolution recognition in protein--protein complexes.

Authors:  I A Vakser; O G Matar; C F Lam
Journal:  Proc Natl Acad Sci U S A       Date:  1999-07-20       Impact factor: 11.205

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

Authors:  A Tovchigrechko; I A Vakser
Journal:  Protein Sci       Date:  2001-08       Impact factor: 6.725

3.  Docking of protein models.

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

4.  ClusPro: a fully automated algorithm for protein-protein docking.

Authors:  Stephen R Comeau; David W Gatchell; Sandor Vajda; Carlos J Camacho
Journal:  Nucleic Acids Res       Date:  2004-07-01       Impact factor: 16.971

5.  Shorter side chains optimize helix-helix packing.

Authors:  Sulin Jiang; Ilya A Vakser
Journal:  Protein Sci       Date:  2004-04-09       Impact factor: 6.725

6.  How good is automated protein docking?

Authors:  Dima Kozakov; Dmitri Beglov; Tanggis Bohnuud; Scott E Mottarella; Bing Xia; David R Hall; Sandor Vajda
Journal:  Proteins       Date:  2013-10-17

7.  Complete predicted three-dimensional structure of the facilitator transmembrane protein and hepatitis C virus receptor CD81: conserved and variable structural domains in the tetraspanin superfamily.

Authors:  Michel Seigneuret
Journal:  Biophys J       Date:  2006-01-01       Impact factor: 4.033

8.  Interactions of the sweet protein brazzein with the sweet taste receptor.

Authors:  D Eric Walters; Göran Hellekant
Journal:  J Agric Food Chem       Date:  2006-12-27       Impact factor: 5.279

9.  Defining the interface between the C-terminal fragment of alpha-transducin and photoactivated rhodopsin.

Authors:  Christina M Taylor; Gregory V Nikiforovich; Garland R Marshall
Journal:  Biophys J       Date:  2007-03-09       Impact factor: 4.033

10.  Monte Carlo refinement of rigid-body protein docking structures with backbone displacement and side-chain optimization.

Authors:  Stephan Lorenzen; Yang Zhang
Journal:  Protein Sci       Date:  2007-10-26       Impact factor: 6.725

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