Evidence map›Paper›PMID 36660427›Full record

ArticleFrontiers in molecular biosciences2022

A hybrid approach to study large conformational transitions of biomolecules from single particle XFEL diffraction data.

Han Asi, Bhaskar Dasgupta, Tetsuro Nagai, Osamu Miyashita, Florence Tama

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Article in Frontiers in molecular biosciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Han AsiDepartment of Physics, Nagoya University, Nagoya, Japan.
Bhaskar DasguptaDivision of Biological Data Science, Research Center for Advanced Science and Technology, The University of Tokyo, Meguro City, Japan.
Tetsuro NagaiDepartment of Advanced Materials Science, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan.
Osamu MiyashitaRIKEN Center for Computational Science, Kobe, Japan.
Florence TamaDepartment of Physics, Nagoya University, Nagoya, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

X-ray free-electron laser (XFEL) is the latest generation of the X-ray source that could become an invaluable technique in structural biology. XFEL has ultrashort pulse duration, extreme peak brilliance, and high spatial coherence, which could enable the observation of the biological molecules in near nature state at room temperature without crystallization. However, for biological systems, due to their low diffraction power and complexity of sample delivery, experiments and data analysis are not straightforward, making it extremely challenging to reconstruct three-dimensional (3D) structures from single particle XFEL data. Given the current limitations to the amount and resolution of the data from such XFEL experiments, we propose a new hybrid approach for characterizing biomolecular conformational transitions by using a single 2D low-resolution XFEL diffraction pattern in combination with another known conformation. In our method, we represent the molecular structure with a coarse-grained model, the Gaussian mixture model, to describe large conformational transitions from low-resolution XFEL data. We obtain plausible 3D structural models that are consistent with the XFEL diffraction pattern by deforming an initial structural model to maximize the similarity between the target pattern and the simulated diffraction patterns from the candidate models. We tested the proposed algorithm on two biomolecules of different sizes with different complexities of conformational transitions, adenylate kinase, and elongation factor 2, using synthetic XFEL data. The results show that, with the proposed algorithm, we can successfully describe the conformational transitions by flexibly fitting the coarse-grained model of one conformation to become consistent with an XFEL diffraction pattern simulated from another conformation. In addition, we showed that the incident beam orientation has some effect on the accuracy of the 3D structure modeling and discussed the reasons for the inaccuracies for certain orientations. The proposed method could serve as an alternative approach for retrieving information on 3D conformational transitions from the XFEL diffraction patterns to interpret experimental data. Since the molecules are represented by Gaussian kernels and no atomic structure is needed in principle, such a method could also be used as a tool to seek initial models for 3D reconstruction algorithms.

Indexed as

3D structure modelingGaussian mixture modelhybrid methodMonte-Carlo samplingX-ray free-electron laser diffraction data analysis

Identifiers

PMID36660427
PMCPMC9846856

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