Literature DB >> 16600360

Identifying protein-protein interfacial residues in heterocomplexes using residue conservation scores.

Jing-Jing Li1, De-Shuang Huang, Bing Wang, Pen Chen.   

Abstract

Identifying protein-protein interfaces is crucial for structural biology. Because of the constraints in wet experiments, many computational methods have been proposed. Without knowing any information about the partner chains, a new method of predicting protein-protein interaction interface residues purely based on evolutionary information in heterocomplexes is proposed here. Unlike traditional approaches using multiple sequence alignment profiles to represent the conservation level for each residue, we make predictions based on the concept of residue conservation scores so that the dimension of the feature vector for each residue can be drastically reduced, at least 20 times less than conventional methods. Based on the representation approach, a simple linear discriminant function is used to make predictions, so the computational complexity of the whole prediction procedure can also be greatly decreased. By testing our approach on 69 heterocomplex chains, experimental results demonstrate the performance of our approach is indeed superior to current existing methods.

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Year:  2006        PMID: 16600360     DOI: 10.1016/j.ijbiomac.2006.02.024

Source DB:  PubMed          Journal:  Int J Biol Macromol        ISSN: 0141-8130            Impact factor:   6.953


  7 in total

1.  Using support vector machine combined with post-processing procedure to improve prediction of interface residues in transient complexes.

Authors:  Rong Liu; Yanhong Zhou
Journal:  Protein J       Date:  2009-10       Impact factor: 2.371

2.  Reconstruction of the yeast protein-protein interaction network involved in nutrient sensing and global metabolic regulation.

Authors:  Subir K Nandy; Paula Jouhten; Jens Nielsen
Journal:  BMC Syst Biol       Date:  2010-05-25

3.  ProDis-ContSHC: learning protein dissimilarity measures and hierarchical context coherently for protein-protein comparison in protein database retrieval.

Authors:  Jingyan Wang; Xin Gao; Quanquan Wang; Yongping Li
Journal:  BMC Bioinformatics       Date:  2012-05-08       Impact factor: 3.169

4.  CRF-based models of protein surfaces improve protein-protein interaction site predictions.

Authors:  Zhijie Dong; Keyu Wang; Truong Khanh Linh Dang; Mehmet Gültas; Marlon Welter; Torsten Wierschin; Mario Stanke; Stephan Waack
Journal:  BMC Bioinformatics       Date:  2014-08-13       Impact factor: 3.169

Review 5.  Progress and challenges in predicting protein interfaces.

Authors:  Reyhaneh Esmaielbeiki; Konrad Krawczyk; Bernhard Knapp; Jean-Christophe Nebel; Charlotte M Deane
Journal:  Brief Bioinform       Date:  2015-05-13       Impact factor: 11.622

6.  Predicting Protein-Protein Interactions Based on Ensemble Learning-Based Model from Protein Sequence.

Authors:  Xinke Zhan; Mang Xiao; Zhuhong You; Chenggang Yan; Jianxin Guo; Liping Wang; Yaoqi Sun; Bingwan Shang
Journal:  Biology (Basel)       Date:  2022-06-30

Review 7.  Review of computational methods for virus-host protein interaction prediction: a case study on novel Ebola-human interactions.

Authors:  Anup Kumar Halder; Pritha Dutta; Mahantapas Kundu; Subhadip Basu; Mita Nasipuri
Journal:  Brief Funct Genomics       Date:  2018-11-26       Impact factor: 4.241

  7 in total

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