2015
1.
Dietzen, Matthias; Kalinina, Olga V.; Taškova, Katerina; Kneissl, Benny; Hildebrandt, Anna-Katharina; Jaenicke, Elmar; Decker, Heinz; Lengauer, Thomas; Hildebrandt, Andreas
Large oligomeric complex structures can be computationally assembled by efficiently combining docked interfaces Journal Article
In: Proteins: Structure, Function, and Bioinformatics, vol. 83, no. 10, pp. 1887-1899, 2015.
Abstract | Links | BibTeX | Altmetric | PlumX | Tags: 3D-MOSAIC, complex match score, macromolecular assembly, protein–protein interactions, structural modeling, transformation match score
@article{https://doi.org/10.1002/prot.24873,
title = {Large oligomeric complex structures can be computationally assembled by efficiently combining docked interfaces},
author = {Matthias Dietzen and Olga V. Kalinina and Katerina Ta\v{s}kova and Benny Kneissl and Anna-Katharina Hildebrandt and Elmar Jaenicke and Heinz Decker and Thomas Lengauer and Andreas Hildebrandt},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/prot.24873},
doi = {https://doi.org/10.1002/prot.24873},
year = {2015},
date = {2015-01-01},
journal = {Proteins: Structure, Function, and Bioinformatics},
volume = {83},
number = {10},
pages = {1887-1899},
abstract = {ABSTRACT Macromolecular oligomeric assemblies are involved in many biochemical processes of living organisms. The benefits of such assemblies in crowded cellular environments include increased reaction rates, efficient feedback regulation, cooperativity and protective functions. However, an atom-level structural determination of large assemblies is challenging due to the size of the complex and the difference in binding affinities of the involved proteins. In this study, we propose a novel combinatorial greedy algorithm for assembling large oligomeric complexes from information on the approximate position of interaction interfaces of pairs of monomers in the complex. Prior information on complex symmetry is not required but rather the symmetry is inferred during assembly. We implement an efficient geometric score, the transformation match score, that bypasses the model ranking problems of state-of-the-art scoring functions by scoring the similarity between the inferred dimers of the same monomer simultaneously with different binding partners in a (sub)complex with a set of pregenerated docking poses. We compiled a diverse benchmark set of 308 homo and heteromeric complexes containing 6 to 60 monomers. To explore the applicability of the method, we considered 48 sets of parameters and selected those three sets of parameters, for which the algorithm can correctly reconstruct the maximum number, namely 252 complexes (81.8%) in, at least one of the respective three runs. The crossvalidation coverage, that is, the mean fraction of correctly reconstructed benchmark complexes during crossvalidation, was 78.1%, which demonstrates the ability of the presented method to correctly reconstruct topology of a large variety of biological complexes. Proteins 2015; 83:1887\textendash1899. © 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.},
keywords = {3D-MOSAIC, complex match score, macromolecular assembly, protein\textendashprotein interactions, structural modeling, transformation match score},
pubstate = {published},
tppubtype = {article}
}
ABSTRACT Macromolecular oligomeric assemblies are involved in many biochemical processes of living organisms. The benefits of such assemblies in crowded cellular environments include increased reaction rates, efficient feedback regulation, cooperativity and protective functions. However, an atom-level structural determination of large assemblies is challenging due to the size of the complex and the difference in binding affinities of the involved proteins. In this study, we propose a novel combinatorial greedy algorithm for assembling large oligomeric complexes from information on the approximate position of interaction interfaces of pairs of monomers in the complex. Prior information on complex symmetry is not required but rather the symmetry is inferred during assembly. We implement an efficient geometric score, the transformation match score, that bypasses the model ranking problems of state-of-the-art scoring functions by scoring the similarity between the inferred dimers of the same monomer simultaneously with different binding partners in a (sub)complex with a set of pregenerated docking poses. We compiled a diverse benchmark set of 308 homo and heteromeric complexes containing 6 to 60 monomers. To explore the applicability of the method, we considered 48 sets of parameters and selected those three sets of parameters, for which the algorithm can correctly reconstruct the maximum number, namely 252 complexes (81.8%) in, at least one of the respective three runs. The crossvalidation coverage, that is, the mean fraction of correctly reconstructed benchmark complexes during crossvalidation, was 78.1%, which demonstrates the ability of the presented method to correctly reconstruct topology of a large variety of biological complexes. Proteins 2015; 83:1887–1899. © 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.