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• W2891895641 abstract "Summary Symmetrical homomeric proteins are ubiquitous in every domain of life, and information about their structure is essential to decipher function. The size of these complexes often makes them intractable to high-resolution structure determination experiments. Computational docking algorithms offer a promising alternative for modeling large complexes with arbitrary symmetry. Accuracy of existing algorithms, however, is limited by backbone inaccuracies when using homology-modeled monomers. Here, we present Rosetta SymDock2 with a broad search of symmetrical conformational space using a six-dimensional coarse-grained score function followed by an all-atom flexible-backbone refinement, which we demonstrate to be essential for physically-realistic modeling of tightly packed complexes. In global docking of a benchmark set of complexes of different point symmetries — staring from homology-modeled monomers — we successfully dock (defined as predicting three near-native structures in the five top-scoring models) 19 out of 31 cyclic complexes and 5 out of 12 dihedral complexes. Highlights SymDock2 is an algorithm to assemble symmetric protein structures from monomers Coarse-grained score function discriminates near-native conformations Flexible backbone refinement is necessary to create realistic all-atom models Results improve six-fold and outperform other symmetric docking algorithms Graphical Abstract" @default.
• W2891895641 created "2018-09-27" @default.
• W2891895641 creator A5009383312 @default.
• W2891895641 creator A5020423293 @default.
• W2891895641 creator A5034778670 @default.
• W2891895641 date "2018-09-06" @default.
• W2891895641 modified "2023-10-18" @default.
• W2891895641 title "Flexible backbone assembly and refinement of symmetrical homomeric complexes" @default.
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• W2891895641 doi "https://doi.org/10.1101/409730" @default.
• W2891895641 hasPublicationYear "2018" @default.
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