Integrating diverse data for structure determination of macromolecular assemblies
Abstract
To understand the cell, we need to determine the macromolecular assembly structures, which may consist of tens to hundreds of components. First, we review the varied experimental data that characterize the assemblies at several levels of resolution. We then describe computational methods for generating the structures using these data. To maximize completeness, resolution, accuracy, precision, and efficiency of the structure determination, a computational approach is required that uses spatial information from a variety of experimental methods. We propose such an approach, defined by its three main components: a hierarchical representation of the assembly, a scoring function consisting of spatial restraints derived from experimental data, and an optimization method that generates structures consistent with the data. This approach is illustrated by determining the configuration of the 456 proteins in the nuclear pore complex (NPC) from baker's yeast. With these tools, we are poised to integrate structural information gathered at multiple levels of the biological hierarchy--from atoms to cells--into a common framework.
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Complementary measurement techniques are beneficial and may ultimately be necessary to gain a full understanding of biological structure across multiple scales.
“A core concept is that complementary measurement techniques are not only beneficial in general, but they may ultimately be necessary to gain a full understanding of biological structure across multiple scales.”
From Mapping the multiscale structure of biological systems (2021) · cites this paper as Alber et al., 2008
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Self-citation
- Authors
- Alber, F., Förster, F., Korkin, D., Topf, M., & Sali, A.
- Affiliations
- QB3 (US)
- Birkbeck, University of London (GB)
- Departments of Biopharmaceutical Sciences and Pharmaceutical Chemistry, and California Institute for Quantitative Biosciences, University of California at San Francisco, California 94158-2330;
- Venue
- Annual Review of Biochemistry
- Publisher
- Annual Reviews
- Published
- 2008-06-01
- Volume
- 77
- Issue
- 1
- Pages
- 443-477
- ISSN
- 0066-4154 (ISSN-L)
- 1545-4509
- OpenAlex
- W2887067015
- Cited by
- 206
- References
- 187
- Citations by year
- 2025: 1 · 2023: 2 · 2022: 5 · 2021: 9 · 2020: 7 · 2019: 14 · 2018: 7 · 2017: 16 · 2016: 11 · 2015: 17 · 2014: 17 · 2013: 19 · 2012: 25
- FWCI
- 1.44
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Annual Review of Biochemistry (publishedVersion)
- PubMed (publishedVersion)
- BIROn (Birkbeck, University of London) (submittedVersion)
- Funders
- National Institute of General Medical Sciences (R01GM054762, R01 GM54762)
- National Center for Research Resources (U54RR022220)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Advanced Electron Microscopy Techniques and Applications
- Keywords
- nuclear pore complex, scoring functions, structural optimization, protein complexes, Saccharomyces cerevisiae
- MeSH terms
- Animals, Biochemistry, Biophysics, Humans, Microscopy, Electron, Models, Molecular, Molecular Conformation, Magnetic Resonance Spectroscopy, Saccharomyces cerevisiae, Scattering, Radiation, Mass Spectrometry, X-Rays, Reproducibility of Results, Nuclear Pore, Macromolecular Substances
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