Determining the architectures of macromolecular assemblies
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 s...
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| Main Authors: | , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
29 November 2007
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| In: |
Nature
Year: 2007, Volume: 450, Issue: 7170, Pages: 683-694 |
| ISSN: | 1476-4687 |
| DOI: | 10.1038/nature06404 |
| Online Access: | Verlag, kostenfrei, Volltext: http://dx.doi.org/10.1038/nature06404 Verlag, kostenfrei, Volltext: https://www.nature.com/nature/journal/v450/n7170/full/nature06404.html 
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| Author Notes: | Frank Alber, Svetlana Dokudovskaya, Liesbeth M. Veenhoff, Wenzhu Zhang, Julia Kipper, Damien Devos, Adisetyantari Suprapto, Orit Karni-Schmidt, Rosemary Williams, Brian T. Chait, Michael P. Rout & Andrej Sali |
| Summary: | 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. |
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| Item Description: | Gesehen am 15.05.2017 |
| Physical Description: | Online Resource |
| ISSN: | 1476-4687 |
| DOI: | 10.1038/nature06404 |