SANS Spectra with PLUMED: Implementation and Application to Metainference

Cezar, Henrique Musseli; Cascella, M.

doi:10.1021/acs.jcim.3c00724

“…Sampling of the metainference posterior is performed by a multi-replica MD/MC simulation driven by the hybrid energy function associated to Eq 14 . This approach has been extensively used to determine structural ensembles of highly dynamic and disordered systems using NMR spectroscopy [ 76 , 77 ] as well as SAXS/SANS [ 78 , 79 ] data. Metainference was also used to determine structural ensembles from cryo-EM data in our previous EMMI approach based on a Gaussian Mixture Models representation of the cryo-EM map [ 29 , 35 ].…”

Section: Methodsmentioning

confidence: 99%

Accurate model and ensemble refinement using cryo-electron microscopy maps and Bayesian inference

Hoff,

Thomasen,

Lindorff-Larsen

et al. 2024

PLoS Comput Biol

3

0

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Converting cryo-electron microscopy (cryo-EM) data into high-quality structural models is a challenging problem of outstanding importance. Current refinement methods often generate unbalanced models in which physico-chemical quality is sacrificed for excellent fit to the data. Furthermore, these techniques struggle to represent the conformational heterogeneity averaged out in low-resolution regions of density maps. Here we introduce EMMIVox, a Bayesian inference approach to determine single-structure models as well as structural ensembles from cryo-EM maps. EMMIVox automatically balances experimental information with accurate physico-chemical models of the system and the surrounding environment, including waters, lipids, and ions. Explicit treatment of data correlation and noise as well as inference of accurate B-factors enable determination of structural models and ensembles with both excellent fit to the data and high stereochemical quality, thus outperforming state-of-the-art refinement techniques. EMMIVox represents a flexible approach to determine high-quality structural models that will contribute to advancing our understanding of the molecular mechanisms underlying biological functions.

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Beyond Core–Shell Micellar Structures: Complex Structures in Simple Surfactants

Cezar,

Bjørnestad,

Prévost

et al. 2024

Small Structures

0

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Small‐angle X‐ray/neutron scattering (SAXS/SANS) techniques provide valuable nanostructural information of self‐assembling molecules. However, extracting the information from these experiments can be a challenging task, usually relying on predetermined assumptions. Conventional models for surfactant micelles consider a core–shell structure with a hydrophobic tail encapsulated by the hydrophilic part. This approach is successful in many cases but can fail even for common surfactants such as Triton X‐100 (TX‐100). SAXS and SANS combined with Metainference molecular simulations are employed to investigate TX‐100 assemblies, showing how more complex models, with diffuse core–shell boundaries, multilayering, and polydispersity, are needed to explain the aggregation. This is the first time that Metainference is employed with SAXS and SANS simultaneously to obtain the structural ensemble of assemblies. Compared to regular micelles formed by chemically similar C12EO10 molecules, the role of the hydrophobic core in micellization is discussed, finding that the relatively shorter and less hydrophobic tail of TX‐100 favors polymorphism.

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Accurate model and ensemble refinement using cryo-electron microscopy maps and Bayesian inference

Hoff,

Thomasen,

Lindorff-Larsen

et al. 2023

Preprint

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Converting cryo-electron microscopy (cryo-EM) data into high-quality structural models is a challenging problem of outstanding importance. Current refinement methods often generate unbalanced models in which physico-chemical quality is sacrificed for excellent fit to the data. Furthermore, these techniques struggle to represent the conformational heterogeneity averaged out in low-resolution regions of density maps. Here we introduce EMMIVox, a Bayesian inference approach to determine single-structure models as well as structural ensembles from cryo-EM maps. EMMIVox automatically balances experimental information with accurate physico-chemical models of the system and the surrounding environment, including waters, lipids, and ions. Explicit treatment of data correlation and noise as well as inference of accurate B-factors enable determination of structural models and ensembles with both excellent fit to the data and high stereochemical quality, thus outperforming state-of-the-art refinement techniques. EMMIVox represents a flexible approach to determine high-quality structural models that will contribute to advancing our understanding of the molecular mechanisms underlying biological functions.

show abstract

SANS Spectra with PLUMED: Implementation and Application to Metainference

Cited by 3 publications

References 37 publications

Accurate model and ensemble refinement using cryo-electron microscopy maps and Bayesian inference

Accurate model and ensemble refinement using cryo-electron microscopy maps and Bayesian inference

Beyond Core–Shell Micellar Structures: Complex Structures in Simple Surfactants

Accurate model and ensemble refinement using cryo-electron microscopy maps and Bayesian inference

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