首页 | 本学科首页   官方微博 | 高级检索  
   检索      


Large oligomeric complex structures can be computationally assembled by efficiently combining docked interfaces
Authors:Matthias Dietzen  Olga V Kalinina  Katerina Ta?kova  Benny Kneissl  Anna‐Katharina Hildebrandt  Elmar Jaenicke  Heinz Decker  Thomas Lengauer  Andreas Hildebrandt
Institution:1. Max Planck Institute for Informatics, Saarbrücken, Germany;2. Institute of Computer Science, Johannes Gutenberg University, Mainz, Germany;3. Institute for Molecular Biology, Johannes Gutenberg University, Mainz, Germany;4. Roche Pharma Research and Early Development, pRED Informatics, Roche Innovation Center Penzberg, Penzberg, Germany;5. Center for Bioinformatics, Saarland University, Saarbrücken, Germany;6. Institute of Molecular Biophysics, Johannes Gutenberg University, Mainz, Germany
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.
Keywords:macromolecular assembly  structural modeling  protein–  protein interactions  transformation match score  complex match score  3D‐MOSAIC
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号