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• W2892485441 abstract "Abstract Multi-protein machines are responsible for most cellular tasks, and many efforts have been invested in the systematic identification and characterization of thousands of these macromolecular assemblies. However, unfortunately, the (quasi) atomic details necessary to understand their function are available only for a tiny fraction of the known complexes. The computational biology community is developing strategies to integrate structural data of different nature, from electron microscopy to X-ray crystallography, to model large molecular machines, as it has been done for individual proteins and interactions with remarkable success. However, unlike for binary interactions, there is no reliable gold-standard set of three-dimensional (3D) complexes to benchmark the performance of these methodologies and detect their limitations. Here, we present a strategy to dynamically generate non-redundant sets of 3D heteromeric complexes with three or more components. By changing the values of sequence identity and component overlap between assemblies required to define complex redundancy, we can create sets of representative complexes with known 3D structure (i.e., target complexes). Using an identity threshold of 20% and imposing a fraction of component overlap of https://DynBench3D.irbbarcelona.org ." @default.
• W2892485441 created "2018-10-05" @default.
• W2892485441 creator A5015088787 @default.
• W2892485441 creator A5028126983 @default.
• W2892485441 date "2018-10-01" @default.
• W2892485441 modified "2023-10-08" @default.
• W2892485441 title "DynBench3D, a Web-Resource to Dynamically Generate Benchmark Sets of Large Heteromeric Protein Complexes" @default.
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• W2892485441 doi "https://doi.org/10.1016/j.jmb.2018.09.011" @default.
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