Methodology for rigorous modeling of protein conformational changes by Rosetta using DEER Distance Restraints

Diego del Alamo, Kevin L Jagessar, Jens Meiler and Hassane S Mchaourab

PLOS Computational Biology, 2021, vol. 17, issue 6, 1-18

Abstract: We describe an approach for integrating distance restraints from Double Electron-Electron Resonance (DEER) spectroscopy into Rosetta with the purpose of modeling alternative protein conformations from an initial experimental structure. Fundamental to this approach is a multilateration algorithm that harnesses sets of interconnected spin label pairs to identify optimal rotamer ensembles at each residue that fit the DEER decay in the time domain. Benchmarked relative to data analysis packages, the algorithm yields comparable distance distributions with the advantage that fitting the DEER decay and rotamer ensemble optimization are coupled. We demonstrate this approach by modeling the protonation-dependent transition of the multidrug transporter PfMATE to an inward facing conformation with a deviation to the experimental structure of less than 2Å Cα RMSD. By decreasing spin label rotamer entropy, this approach engenders more accurate Rosetta models that are also more closely clustered, thus setting the stage for more robust modeling of protein conformational changes.Author summary: Proteins transition between different conformations during function. Double Electron-Electron Resonance (DEER) spectroscopy enables the direct observation of structural rearrangements that underpin these transitions. Typically, histograms of distances between spin labels, called distance distributions, are measured under different conditions. Structural rearrangements that underlie conformational transitions are manifested by changes in the averages and widths of the distance distributions. To transform these distance distributions into restraints for modeling alternate protein conformations, we developed an algorithm in the modeling suite Rosetta for direct analysis of DEER primary data that yield the optimum ensemble of spin label positions in space, referred to as rotamers, that account for the data. We benchmarked the effectiveness of this algorithm using experimental data collected in two proteins, the model system T4 Lysozyme and the multidrug transporter PfMATE in an outward-facing conformation. We then used optimized spin label rotamers to model the inward-facing conformation of PfMATE from the starting outward-facing conformation. Our results demonstrate substantial improvements in both precision and accuracy among the resulting models. Further improvement of this strategy will enable modeling of protein conformational changes involving complex modes of movements.

Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1009107 (text/html)
https://journals.plos.org/ploscompbiol/article/fil ... 09107&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1009107

DOI: 10.1371/journal.pcbi.1009107

Access Statistics for this article

More articles in PLOS Computational Biology from Public Library of Science
Bibliographic data for series maintained by ploscompbiol ().