Journal
JOURNAL OF STRUCTURAL BIOLOGY
Volume 211, Issue 2, Pages -Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jsb.2020.107545
Keywords
Cryo-EM; Local resolution; Noise suppression; Real-space filter; Over-fitting
Funding
- Wellcome Trust
- Royal Society through a Sir Henry Dale Fellowship [206212/Z/17/Z]
- Medical Research Council [MR/N009614/1]
- Overseas Research Fellowship from the Japan Society for the Promotion of Science
- Wellcome Trust [206212/Z/17/Z] Funding Source: Wellcome Trust
- MRC [MC_UP_A025_1013, MR/N009614/1] Funding Source: UKRI
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Single particle analysis has become a key structural biology technique. Experimental images are extremely noisy, and during iterative refinement it is possible to stably incorporate noise into the reconstruction. Such over-fitting can lead to misinterpretation of the structure and flawed biological results. Several strategies are routinely used to prevent over-fitting, the most common being independent refinement of two sides of a split dataset. In this study, we show that over-fitting remains an issue within regions of low local signal-to-noise, despite independent refinement of half datasets. We propose a modification of the refinement process through the application of a local signal-to-noise filter: SIDESPLITTER. We show that our approach can reduce over-fitting for both idealised and experimental data while maintaining independence between the two sides of a split refinement. SIDESPLITTER refinement leads to improved density, and can also lead to improvement of the final resolution in extreme cases where datasets are prone to severe over-fitting, such as small membrane proteins.
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