ArticleScientific reports2023
MDTOMO method for continuous conformational variability analysis in cryo electron subtomograms based on molecular dynamics simulations.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Resolving structural heterogeneity in situ through cryogenic electron tomography.Current opinion in structural biology · 2026Review
- Deciphering conformational dynamics in AFM data using fast nonlinear NMA and FFT-based search with AFMFit.Communications biology · 2025Article
- Building molecular model series from heterogeneous CryoEM structures using Gaussian mixture models and deep neural networks.Communications biology · 2025Article
- 3D animation as a tool for integrative modeling of dynamic molecular mechanisms.Structure (London, England : 1993) · 2024Review
- Predictive identification and design of potent inhibitors targeting resistance-inducing candidate genes fromFrontiers in bioinformatics · 2024Article
- MDSPACE and MDTOMO Software for Extracting Continuous Conformational Landscapes from Datasets of Single Particle Images and Subtomograms Based on Molecular Dynamics Simulations: Latest Developments in ContinuousFlex Software Package.International journal of molecular sciences · 2023Article
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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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