Literature DB >> 17586545

Interaction-site prediction for protein complexes: a critical assessment.

Huan-Xiang Zhou1, Sanbo Qin.   

Abstract

MOTIVATION: Proteins function through interactions with other proteins and biomolecules. Protein-protein interfaces hold key information toward molecular understanding of protein function. In the past few years, there have been intensive efforts in developing methods for predicting protein interface residues. A review that presents the current status of interface prediction and an overview of its applications and project future developments is in order.
SUMMARY: Interface prediction methods rely on a wide range of sequence, structural and physical attributes that distinguish interface residues from non-interface surface residues. The input data are manipulated into either a numerical value or a probability representing the potential for a residue to be inside a protein interface. Predictions are now satisfactory for complex-forming proteins that are well represented in the Protein Data Bank, but less so for under-represented ones. Future developments will be directed at tackling problems such as building structural models for multi-component structural complexes.

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Year:  2007        PMID: 17586545     DOI: 10.1093/bioinformatics/btm323

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  61 in total

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7.  Predicting protein ligand binding sites by combining evolutionary sequence conservation and 3D structure.

Authors:  John A Capra; Roman A Laskowski; Janet M Thornton; Mona Singh; Thomas A Funkhouser
Journal:  PLoS Comput Biol       Date:  2009-12-04       Impact factor: 4.475

8.  Regression applied to protein binding site prediction and comparison with classification.

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Journal:  BMC Bioinformatics       Date:  2009-09-03       Impact factor: 3.169

9.  Prediction of antigenic epitopes on protein surfaces by consensus scoring.

Authors:  Shide Liang; Dandan Zheng; Chi Zhang; Martin Zacharias
Journal:  BMC Bioinformatics       Date:  2009-09-22       Impact factor: 3.169

10.  Prediction of protein binding sites in protein structures using hidden Markov support vector machine.

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Journal:  BMC Bioinformatics       Date:  2009-11-20       Impact factor: 3.169

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