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bioRxiv · 10.1101/2023.02.25.529934

MDTOMO: Continuous conformational variability analysis in cryo electron subtomogram data using flexible fitting based on Molecular Dynamics simulations

Vuillemot, R.·Rouiller, I.·Jonic, S.
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Abstract

Cryo electron tomography (cryo-ET) allows observing macromolecular complexes in their native environment. The common routine of subtomogram averaging (STA) allows obtaining the three-dimensional (3D) structure of abundant macromolecular complexes, and can be coupled with discrete classification to reveal conformational heterogeneity of the sample. However, the number of complexes extracted from cryo-ET data is usually small, which restricts the discrete-classification results to a small number of enough populated states and, thus, results in a largely incomplete conformational landscape. Alternative approaches are currently being investigated to explore the continuity of the conformational landscapes that in situ cryo-ET studies could provide. In this article, we present MDTOMO, a method for analyzing continuous conformational variability in cryo-ET subtomograms based on Molecular Dynamics (MD) simulations. MDTOMO allows obtaining an atomic-scale model of conformational variability and the corresponding free-energy landscape, from a given set of cryo-ET subtomograms. The article presents the performance of MDTOMO on a synthetic ABC exporter dataset and an in situ SARS-CoV-2 spike dataset. MDTOMO allows analyzing dynamic properties of molecular complexes to understand their biological functions, which could also be useful for structure-based drug discovery.

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Vuillemot, R., Rouiller, I., Jonic, S.. 2023-02-27. MDTOMO: Continuous conformational variability analysis in cryo electron subtomogram data using flexible fitting based on Molecular Dynamics simulations. https://doi.org/10.1101/2023.02.25.529934

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