Rapid Analysis of DEER Signals Including Short Distances
Source abstract
Abstract
Double electron electron resonance (DEER) spectroscopy is an important technique to measure distance distributions P ( r ) for studying protein structures and protein–protein interactions. DEER data analysis can at times become challenging due to the lack of a detailed analytical signal expression or numerical methods with rapid computation time. We have derived an analytical expression κ FULL, which includes both the pseudo-secular dipolar coupling (PSDC) and the finite pulse effects, especially important for shorter distances. Analyses of experiments by κ FULL yield accurate and consistent P ( r ) values for three DEER nitroxide-rulers with distances ( r AVG ) in the range of 15 to 32 Å, while the current standard analysis produces erroneous results for r AVG < 20 Å. Computation times for deriving P ( r ) vary between 1 min and 4 min, which is usually much shorter than previous methods that include pseudo-secular and other effects. The expression can be applied to all types of DEER spin probes with little or no modifications.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Electron Spin Resonance Studies · Lanthanide and Transition Metal Complexes · Advanced NMR Techniques and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Chemistry & Chemical Biology, Cornell University, Ithaca, New York 14850, United States
National Biomedical Resource for Advanced ESR Spectroscopy (ACERT), Ithaca, New York 14850, United States
Funding
National Institute of General Medical Sciences
References (39)
Show source-provided references
1. 10.1021/ja054991y10.1021/ja054991y ↗
2. 10.1021/ja063122l10.1021/ja063122l ↗
3. 10.1021/ja804517m10.1021/ja804517m ↗
4. 10.1021/jz301788n10.1021/jz301788n ↗
5. 10.1073/pnas.141415511210.1073/pnas.1414155112 ↗
6. 10.1021/jacs.1c0737110.1021/jacs.1c07371 ↗
7. 10.1146/annurev-physchem-032511-14371610.1146/annurev-physchem-032511-143716 ↗
8. 10.1021/jacs.5b1338210.1021/jacs.5b13382 ↗
9. 10.1038/npjqi.2015.1210.1038/npjqi.2015.12 ↗
10. 10.1021/acs.jpclett.9b0320810.1021/acs.jpclett.9b03208 ↗
11. 10.1021/jacs.2c0220110.1021/jacs.2c02201 ↗
12. 10.1038/7895610.1038/78956 ↗
13. 10.1016/j.sbi.2013.06.00810.1016/j.sbi.2013.06.008 ↗
14. 10.1016/j.jmr.2022.10718610.1016/j.jmr.2022.107186 ↗
15. 10.1063/5.020005410.1063/5.0200054 ↗
16. 10.1038/s41534-022-00653-w10.1038/s41534-022-00653-w ↗
17. 10.1016/j.jmr.2004.10.01210.1016/j.jmr.2004.10.012 ↗
18. 10.1126/sciadv.aat521810.1126/sciadv.aat5218 ↗
19. 10.1021/acs.jpclett.7b0237910.1021/acs.jpclett.7b02379 ↗
20. 10.1002/cplu.20190070510.1002/cplu.201900705 ↗
21. 10.1007/BF0316621310.1007/BF03166213 ↗
22. Stein, R. A.; Beth, A. H.; Hustedt, E. J. Methods in Enzymology, Vol. 563; Elsevier, 2015; pp 531–567.10.1016/bs.mie.2015.07.031 ↗
23. 10.1021/jz201521d10.1021/jz201521d ↗
24. 10.1021/ja075544g10.1021/ja075544g ↗
25. 10.1063/1.499408410.1063/1.4994084 ↗
26. 10.1039/C8CP01276H10.1039/C8CP01276H ↗
27. 10.1016/j.physb.2021.41351110.1016/j.physb.2021.413511 ↗
28. Marohn, J. A. UniDyn: Unitary evolution of quantum mechanical operators. Available via the Internet at: https://github.com/JohnMarohn/UniDyn, 2016 (accessed November 11, 2024).
29. 10.1016/j.jmr.2018.01.02110.1016/j.jmr.2018.01.021 ↗
30. 10.5194/mr-1-209-202010.5194/mr-1-209-2020 ↗
31. 10.1006/jmre.2002.259610.1006/jmre.2002.2596 ↗
32. 10.1007/s00723-009-0023-510.1007/s00723-009-0023-5 ↗
33. 10.1016/j.jmr.2012.01.01910.1016/j.jmr.2012.01.019 ↗
34. 10.1039/D3CP00404J10.1039/D3CP00404J ↗
35. 10.1007/s00723-023-01594-z10.1007/s00723-023-01594-z ↗
36. 10.1063/1.46491610.1063/1.464916 ↗
37. 10.1016/j.jmr.2011.12.02410.1016/j.jmr.2011.12.024 ↗
38. 10.1529/biophysj.107.12541910.1529/biophysj.107.125419 ↗
39. 10.1039/D2CP01032A10.1039/D2CP01032A ↗