Double electron-electron resonance (DEER) structural study of the holo and apo states of calmodulin.
Journal:
International journal of radiation biology
Published Date:
Jun 16, 2026
Abstract
PURPOSE: Human calmodulin-1 (CaM) undergoes calcium-dependent conformational changes that are difficult to capture owing to substantial structural flexibility. This study aims to show that double electron-electron resonance (DEER) spectroscopy can measure ensembles of CaM conformations. The most probable distances are compared to structural models from experimental structures and deep-learning predictions. MATERIALS AND METHODS: Four double-cysteine variants of a recombinant CaM were engineered for site-directed spin labeling. Spin-labeled CaM was measured with DEER spectroscopy in both the presence (holo CaM) and absence (apo CaM) of Ca(II). Distance distributions were compared with predictions derived from Protein Data Bank structures and models generated from AlphaFold2 and IntFOLD7. DEERefiner was used to generate conformers from these models using the distance-distributions as restraints. RESULTS: The distance distributions from DEER were consistent with conformational heterogeneity. Distance distributions differed between apo and holo conditions. The results with Ca(II) were consistent with an ensemble of conformations including the canonical crystallographic structure (1CLL). Apo state distance distributions were not reproduced well by the models. Upon refinement with the distance distributions the models aligned better with the most probable distances from the apo and holo results. Comparisons of the refined models indicated that Ca(II) binding causes subtle rearrangements between EF-hand domains. CONCLUSIONS: The DEER-derived distance distributions for the four doubly-labeled CaM variants demonstrate that apo and holo CaM populate broad but different conformational ensembles in frozen solution. Comparison of apo and holo distributions indicate that Ca(II) binding induces a subtle, yet significant, structural rearrangement. These results illustrate how DEER-guided modeling can provide deeper insight into flexible protein ensembles that are not captured by existing static structures.
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