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Nature
Article . 2007 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
Nature
Article . 2008
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Determining the architectures of macromolecular assemblies

Authors: Wenzhu Zhang; Michael P. Rout; Julia Kipper; Brian T. Chait; Adisetyantari Suprapto; Frank Alber; Orit Karni-Schmidt; +6 Authors

Determining the architectures of macromolecular assemblies

Abstract

To understand the workings of a living cell, we need to know the architectures of its macromolecular assemblies. Here we show how proteomic data can be used to determine such structures. The process involves the collection of sufficient and diverse high-quality data, translation of these data into spatial restraints, and an optimization that uses the restraints to generate an ensemble of structures consistent with the data. Analysis of the ensemble produces a detailed architectural map of the assembly. We developed our approach on a challenging model system, the nuclear pore complex (NPC). The NPC acts as a dynamic barrier, controlling access to and from the nucleus, and in yeast is a 50 MDa assembly of 456 proteins. The resulting structure, presented in an accompanying paper, reveals the configuration of the proteins in the NPC, providing insights into its evolution and architectural principles. The present approach should be applicable to many other macromolecular assemblies.

Keywords

Proteomics, Saccharomyces cerevisiae Proteins, PREDICTION, Cell Survival, Macromolecular Substances, CRYOELECTRON TOMOGRAPHY, NUCLEAR-PORE COMPLEX, Saccharomyces cerevisiae, Models, Biological, Sensitivity and Specificity, Microscopy, Immunoelectron, IDENTIFICATION, NUCLEOCYTOPLASMIC TRANSPORT, Uncertainty, Computational Biology, PROTEIN INTERACTIONS, ALPHA, Nuclear Pore Complex Proteins, NUCLEOPORINS, SUBUNIT, Nuclear Pore, SACCHAROMYCES, Protein Binding

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    481
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
481
Top 1%
Top 1%
Top 0.1%