Literature DB >> 18831053

Consensus scoring for enriching near-native structures from protein-protein docking decoys.

Shide Liang1, Samy O Meroueh, Guangce Wang, Chao Qiu, Yaoqi Zhou.   

Abstract

The identification of near native protein-protein complexes among a set of decoys remains highly challenging. A strategy for improving the success rate of near native detection is to enrich near native docking decoys in a small number of top ranked decoys. Recently, we found that a combination of three scoring functions (energy, conservation, and interface propensity) can predict the location of binding interface regions with reasonable accuracy. Here, these three scoring functions are modified and combined into a consensus scoring function called ENDES for enriching near native docking decoys. We found that all individual scores result in enrichment for the majority of 28 targets in ZDOCK2.3 decoy set and the 22 targets in Benchmark 2.0. Among the three scores, the interface propensity score yields the highest enrichment in both sets of protein complexes. When these scores are combined into the ENDES consensus score, a significant increase in enrichment of near-native structures is found. For example, when 2000 dock decoys are reduced to 200 decoys by ENDES, the fraction of near-native structures in docking decoys increases by a factor of about six in average. ENDES was implemented into a computer program that is available for download at http://sparks.informatics.iupui.edu.

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 18831053      PMCID: PMC2656599          DOI: 10.1002/prot.22252

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


  27 in total

1.  Physicochemical and residue conservation calculations to improve the ranking of protein-protein docking solutions.

Authors:  Yuhua Duan; Boojala V B Reddy; Yiannis N Kaznessis
Journal:  Protein Sci       Date:  2005-02       Impact factor: 6.725

2.  Refinement of unbound protein docking studies using biological knowledge.

Authors:  Philipp Heuser; Davide Baù; Pascal Benkert; Dietmar Schomburg
Journal:  Proteins       Date:  2005-12-01

3.  Assessment of CAPRI predictions in rounds 3-5 shows progress in docking procedures.

Authors:  Raúl Méndez; Raphaël Leplae; Marc F Lensink; Shoshana J Wodak
Journal:  Proteins       Date:  2005-08-01

4.  Scoring docking models with evolutionary information.

Authors:  Michael Tress; David de Juan; Osvaldo Graña; Manuel J Gómez; Paulino Gómez-Puertas; Jose M González; Gonzalo López; Alfonso Valencia
Journal:  Proteins       Date:  2005-08-01

5.  Protein-Protein Docking Benchmark 2.0: an update.

Authors:  Julian Mintseris; Kevin Wiehe; Brian Pierce; Robert Anderson; Rong Chen; Joël Janin; Zhiping Weng
Journal:  Proteins       Date:  2005-08-01

6.  WHISCY: what information does surface conservation yield? Application to data-driven docking.

Authors:  Sjoerd J de Vries; Aalt D J van Dijk; Alexandre M J J Bonvin
Journal:  Proteins       Date:  2006-05-15

Review 7.  High-resolution protein-protein docking.

Authors:  Jeffrey J Gray
Journal:  Curr Opin Struct Biol       Date:  2006-03-20       Impact factor: 6.809

8.  Efficient restraints for protein-protein docking by comparison of observed amino acid substitution patterns with those predicted from local environment.

Authors:  Vijayalakshmi Chelliah; Tom L Blundell; Juan Fernández-Recio
Journal:  J Mol Biol       Date:  2006-01-31       Impact factor: 5.469

9.  Prediction of protein-protein interaction sites using patch analysis.

Authors:  S Jones; J M Thornton
Journal:  J Mol Biol       Date:  1997-09-12       Impact factor: 5.469

10.  Protein binding site prediction using an empirical scoring function.

Authors:  Shide Liang; Chi Zhang; Song Liu; Yaoqi Zhou
Journal:  Nucleic Acids Res       Date:  2006-08-07       Impact factor: 16.971

View more
  14 in total

Review 1.  Sampling and scoring: a marriage made in heaven.

Authors:  Sandor Vajda; David R Hall; Dima Kozakov
Journal:  Proteins       Date:  2013-08-19

2.  Modeling Protein Complexes and Molecular Assemblies Using Computational Methods.

Authors:  Romain Launay; Elin Teppa; Jérémy Esque; Isabelle André
Journal:  Methods Mol Biol       Date:  2023

3.  Boosting prediction performance of protein-protein interaction hot spots by using structural neighborhood properties.

Authors:  Lei Deng; Jihong Guan; Xiaoming Wei; Yuan Yi; Qiangfeng Cliff Zhang; Shuigeng Zhou
Journal:  J Comput Biol       Date:  2013-10-17       Impact factor: 1.479

4.  A comparative study of AutoDock and PMF scoring performances, and SAR of 2-substituted pyrazolotriazolopyrimidines and 4-substituted pyrazolopyrimidines as potent xanthine oxidase inhibitors.

Authors:  Hamed I Ali; Takayuki Fujita; Eiichi Akaho; Tomohisa Nagamatsu
Journal:  J Comput Aided Mol Des       Date:  2009-12-29       Impact factor: 3.686

5.  CPORT: a consensus interface predictor and its performance in prediction-driven docking with HADDOCK.

Authors:  Sjoerd J de Vries; Alexandre M J J Bonvin
Journal:  PLoS One       Date:  2011-03-25       Impact factor: 3.240

6.  Prediction of ligand binding using an approach designed to accommodate diversity in protein-ligand interactions.

Authors:  Lorraine Marsh
Journal:  PLoS One       Date:  2011-08-10       Impact factor: 3.240

7.  PRUNE and PROBE--two modular web services for protein-protein docking.

Authors:  Pralay Mitra; Debnath Pal
Journal:  Nucleic Acids Res       Date:  2011-05-16       Impact factor: 16.971

8.  DOCKSCORE: a webserver for ranking protein-protein docked poses.

Authors:  Sony Malhotra; Oommen K Mathew; Ramanathan Sowdhamini
Journal:  BMC Bioinformatics       Date:  2015-04-24       Impact factor: 3.169

9.  Accurate prediction of functional effects for variants by combining gradient tree boosting with optimal neighborhood properties.

Authors:  Yuliang Pan; Diwei Liu; Lei Deng
Journal:  PLoS One       Date:  2017-06-14       Impact factor: 3.240

Review 10.  Machine Learning Approaches for Protein⁻Protein Interaction Hot Spot Prediction: Progress and Comparative Assessment.

Authors:  Siyu Liu; Chuyao Liu; Lei Deng
Journal:  Molecules       Date:  2018-10-04       Impact factor: 4.411

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.