Denoising and iterative phase recovery reveal low-occupancy populations in protein crystals
File(s)
Published version
Author(s)
Fadini, Alisia
Apostolopoulou, Virginia
Lane, Thomas
van Thor, Jasper
Type
Journal Article
Abstract
Advances in structural biology increasingly focus on uncovering protein dynamics and transient macromolecular complexes. Such studies require modeling of low-occupancy species like time-evolving intermediates and bound ligands. In protein crystallography, difference maps that compare paired perturbed and reference datasets are a powerful way to identify and aid modeling of low-occupancy species. Current methods to generate difference maps, however, rely on manually tuned parameters and, when signals are weak due to low occupancy, can fail to extract clear, chemically interpretable signals. We address these issues, first by showing that negentropy – a measure of how different a signal looks from anticipated Gaussian noise – is an effective metric to assess difference map quality and can therefore be used to automatically determine difference map calculation parameters. Leveraging this, we apply total variation denoising, an image restoration technique that requires a choice of regularization parameter, to crystallographic difference maps. We show that total variation denoising improves map signal-to-noise and enables us to estimate the latent phase contribution of low-occupancy states. We implement this technology in an open-source Python package, METEOR. METEOR opens new possibilities, for time-resolved and ligand-screening crystallography especially, allowing detection of low-occupancy states that could not previously be resolved.
Date Issued
2025-11-24
Date Acceptance
2025-09-10
Citation
Communications Biology, 2025, 8
ISSN
2399-3642
Publisher
Nature Portfolio
Journal / Book Title
Communications Biology
Volume
8
Copyright Statement
© The Author(s) 2026. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
License URL
Identifier
10.1038/s42003-025-09031-6
Publication Status
Published
Article Number
ARTN 1649