Recent Developments in Data-Assisted Modeling of Flexible Proteins
- PMID: 35004845
- PMCID: PMC8740120
- DOI: 10.3389/fmolb.2021.765562
Recent Developments in Data-Assisted Modeling of Flexible Proteins
Abstract
Many proteins can fold into well-defined conformations. However, intrinsically-disordered proteins (IDPs) do not possess a defined structure. Moreover, folded multi-domain proteins often digress into alternative conformations. Collectively, the conformational dynamics enables these proteins to fulfill specific functions. Thus, most experimental observables are averaged over the conformations that constitute an ensemble. In this article, we review the recent developments in the concept and methods for the determination of the dynamic structures of flexible peptides and proteins. In particular, we describe ways to extract information from nuclear magnetic resonance small-angle X-ray scattering (SAXS), and chemical cross-linking coupled with mass spectroscopy (XL-MS) measurements. All these techniques can be used to obtain ensemble-averaged restraints or to re-weight the simulated conformational ensembles.
Keywords: chemical cross-linking coupled with mass spectroscopy; coarse graining; conformational ensembles; data-assisted modeling; molecular dynamics; nuclear magnetic resonance; proteins; small-angle X-ray scattering.
Copyright © 2021 Czaplewski, Gong, Lubecka, Xue, Tang and Liwo.
Conflict of interest statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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References
-
- Abraham M. J., Murtola T., Schulz R., Páll S., Smith J. C., Hess B., et al. (2015). GROMACS: High Performance Molecular Simulations through Multi-Level Parallelism from Laptops to Supercomputers. SoftwareX 1-2, 19–25. 10.1016/j.softx.2015.06.001 - DOI
-
- Amirkulova D. B., White A. D. (2019). Recent Advances in Maximum Entropy Biasing Techniques for Molecular Dynamics. Mol. Simul. 45, 1285–1294. 10.1080/08927022.2019.1608988 - DOI
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