Journal article
Modeling Conformationally Flexible Proteins With X-ray Scattering and Molecular Simulations
Computational and structural biotechnology journal, Vol.17(2019), pp.570-578
2019
DOI: 10.1016/j.csbj.2019.04.011
PMCID: PMC6495069
PMID: 31073392
Abstract
Proteins and protein complexes with high conformational flexibility participate in a wide range of biological processes. These processes include genome maintenance, gene expression, signal transduction, cell cycle regulation, and many others. Gaining a structural understanding of conformationally flexible proteins and protein complexes is arguably the greatest problem facing structural biologists today. Over the last decade, some progress has been made toward understanding the conformational flexibility of such systems using hybrid approaches. One particularly fruitful strategy has been the combination of small-angle X-ray scattering (SAXS) and molecular simulations. In this article, we provide a brief overview of SAXS and molecular simulations and then discuss two general approaches for combining SAXS data and molecular simulations: minimal ensemble approaches and full ensemble approaches. In minimal ensemble approaches, one selects a minimal ensemble of structures from the simulations that best fit the SAXS data. In full ensemble approaches, one validates a full ensemble of structures from the simulations using SAXS data. We argue that full ensemble models are more realistic than minimal ensemble searches models and that full ensemble approaches should be used wherever possible.
Details
- Title: Subtitle
- Modeling Conformationally Flexible Proteins With X-ray Scattering and Molecular Simulations
- Creators
- Kyle T. Powers - University of IowaMelissa S. Gildenberg - University of IowaM. Todd Washington - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Computational and structural biotechnology journal, Vol.17(2019), pp.570-578
- DOI
- 10.1016/j.csbj.2019.04.011
- PMID
- 31073392
- PMCID
- PMC6495069
- ISSN
- 2001-0370
- eISSN
- 2001-0370
- Grant note
- DOI: 10.13039/100000002, name: National Institutes of Health
- Language
- English
- Date published
- 2019
- Academic Unit
- Radiation Oncology; Biochemistry and Molecular Biology
- Record Identifier
- 9984288730202771
Metrics
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