Literature DB >> 19731373

Present and future challenges and limitations in protein-protein docking.

Carles Pons1, Solène Grosdidier, Albert Solernou, Laura Pérez-Cano, Juan Fernández-Recio.   

Abstract

The study of protein-protein interactions that are involved in essential life processes can largely benefit from the recent upraising of computational docking approaches. Predicting the structure of a protein-protein complex from their separate components is still a highly challenging task, but the field is rapidly improving. Recent advances in sampling algorithms and rigid-body scoring functions allow to produce, at least for some cases, high quality docking models that are perfectly suitable for biological and functional annotations, as it has been shown in the CAPRI blind tests. However, important challenges still remain in docking prediction. For example, in cases with significant mobility, such as multidomain proteins, fully unrestricted rigid-body docking approaches are clearly insufficient so they need to be combined with restraints derived from domain-domain linker residues, evolutionary information, or binding site predictions. Other challenging cases are weak or transient interactions, such as those between proteins involved in electron transfer, where the existence of alternative bound orientations and encounter complexes complicates the binding energy landscape. Docking methods also struggle when using in silico structural models for the interacting subunits. Bringing these challenges to a practical point of view, we have studied here the limitations of our docking and energy-based scoring approach, and have analyzed different parameters to overcome the limitations and improve the docking performance. For that, we have used the standard benchmark and some practical cases from CAPRI. Based on these results, we have devised a protocol to estimate the success of a given docking run. (c) 2009 Wiley-Liss, Inc.

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Year:  2010        PMID: 19731373     DOI: 10.1002/prot.22564

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  20 in total

1.  Protein-Protein Docking Using EMAP in CHARMM and Support Vector Machine: Application to Ab/Ag Complexes.

Authors:  Jon D Wright; Karen Sargsyan; Xiongwu Wu; Bernard R Brooks; Carmay Lim
Journal:  J Chem Theory Comput       Date:  2013-08-16       Impact factor: 6.006

2.  On the analysis of protein-protein interactions via knowledge-based potentials for the prediction of protein-protein docking.

Authors:  Elisenda Feliu; Patrick Aloy; Baldo Oliva
Journal:  Protein Sci       Date:  2011-03       Impact factor: 6.725

Review 3.  Software for molecular docking: a review.

Authors:  Nataraj S Pagadala; Khajamohiddin Syed; Jack Tuszynski
Journal:  Biophys Rev       Date:  2017-01-16

4.  Ranking protein-protein docking results using steered molecular dynamics and potential of mean force calculations.

Authors:  Laura J Kingsley; Juan Esquivel-Rodríguez; Ying Yang; Daisuke Kihara; Markus A Lill
Journal:  J Comput Chem       Date:  2016-05-27       Impact factor: 3.376

5.  Determining macromolecular assembly structures by molecular docking and fitting into an electron density map.

Authors:  Keren Lasker; Andrej Sali; Haim J Wolfson
Journal:  Proteins       Date:  2010-11-15

6.  Development of a novel bioinformatics tool for in silico validation of protein interactions.

Authors:  Nicola Barbarini; Luca Simonelli; Alberto Azzalin; Sergio Comincini; Riccardo Bellazzi
Journal:  J Biomed Biotechnol       Date:  2010-06-07

7.  Protein docking by Rotation-Based Uniform Sampling (RotBUS) with fast computing of intermolecular contact distance and residue desolvation.

Authors:  Albert Solernou; Juan Fernandez-Recio
Journal:  BMC Bioinformatics       Date:  2010-06-28       Impact factor: 3.169

8.  Accounting for large amplitude protein deformation during in silico macromolecular docking.

Authors:  Karine Bastard; Adrien Saladin; Chantal Prévost
Journal:  Int J Mol Sci       Date:  2011-02-22       Impact factor: 5.923

9.  Blockade of neuronal α7-nAChR by α-conotoxin ImI explained by computational scanning and energy calculations.

Authors:  Rilei Yu; David J Craik; Quentin Kaas
Journal:  PLoS Comput Biol       Date:  2011-03-03       Impact factor: 4.475

10.  Rice mitogen activated protein kinase kinase and mitogen activated protein kinase interaction network revealed by in-silico docking and yeast two-hybrid approaches.

Authors:  Dhammaprakash Pandhari Wankhede; Mohit Misra; Pallavi Singh; Alok Krishna Sinha
Journal:  PLoS One       Date:  2013-05-30       Impact factor: 3.240

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