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bioRxiv · 10.1101/2022.12.20.521188

Likelihood-based docking of models into cryo-EM maps

Millan, C.·McCoy, A. J.·Terwilliger, T. C.·Read, R. J.
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Abstract

Optimized docking of models into cryo-EM maps requires exploiting an understanding of the signal expected in the data to minimize the calculation time while maintaining sufficient signal. The likelihood-based rotation function used in crystallography can be employed to establish plausible orientations in a docking search. A phased likelihood translation function yields scores for the placement and rigid-body refinement of oriented models. Optimised strategies for choices of the resolution of data from the cryo-EM maps to use in the calculations and the size of search volumes are based on expected log-likelihood-gain scores, computed in advance of the search calculation. Tests demonstrate that the new procedure is fast, robust and effective at placing models into even challenging cryo-EM maps. SynopsisExploiting analogies to crystallographic molecular replacement, a strategy for docking into cryo-EM maps is informed by calculations of expected log-likelihood-gain scores.

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Millan, C., McCoy, A. J., Terwilliger, T. C., Read, R. J.. 2022-12-20. Likelihood-based docking of models into cryo-EM maps. https://doi.org/10.1101/2022.12.20.521188

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