1
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Nakano M, Miyashita O, Tama F. Molecular size dependence on achievable resolution from XFEL single-particle 3D reconstruction. STRUCTURAL DYNAMICS (MELVILLE, N.Y.) 2023; 10:024101. [PMID: 36942031 PMCID: PMC10024609 DOI: 10.1063/4.0000175] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 02/16/2023] [Indexed: 05/03/2023]
Abstract
Single-particle analysis using x-ray free-electron lasers (XFELs) is a novel method for obtaining structural information of samples in a state close to nature. In particular, it is suitable for observing the inner structure of large biomolecules by taking advantage of the high transmittance of x-rays. However, systematic studies on the resolution achievable for large molecules are lacking. In this study, the molecular size dependence of the resolution of a three-dimensional (3D) structure resulting from XFEL single-particle reconstruction is evaluated using synthetic data. Evidently, 3D structures of larger molecules can be restored with higher detail (defined relative to the molecular sizes) than smaller ones; however, reconstruction with high absolute resolution (defined in nm-1) is challenging. Our results provide useful information for the experimental design of 3D structure reconstruction using coherent x-ray diffraction patterns of single-particles.
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Affiliation(s)
- Miki Nakano
- RIKEN Center for Computational Science, 6-7-1, Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Osamu Miyashita
- RIKEN Center for Computational Science, 6-7-1, Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
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2
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Asi H, Dasgupta B, Nagai T, Miyashita O, Tama F. A hybrid approach to study large conformational transitions of biomolecules from single particle XFEL diffraction data. Front Mol Biosci 2022; 9:913860. [PMID: 36660427 PMCID: PMC9846856 DOI: 10.3389/fmolb.2022.913860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 07/04/2022] [Indexed: 01/06/2023] Open
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.
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Affiliation(s)
- Han Asi
- Department of Physics, Nagoya University, Nagoya, Japan
| | - Bhaskar Dasgupta
- Division of Biological Data Science, Research Center for Advanced Science and Technology, The University of Tokyo, Meguro City, Japan
| | - Tetsuro Nagai
- Department of Advanced Materials Science, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan
| | - Osamu Miyashita
- RIKEN Center for Computational Science, Kobe, Japan,*Correspondence: Osamu Miyashita, ; Florence Tama,
| | - Florence Tama
- Department of Physics, Nagoya University, Nagoya, Japan,RIKEN Center for Computational Science, Kobe, Japan,Institute of Transformative Bio-Molecules, Nagoya University, Nagoya, Japan,*Correspondence: Osamu Miyashita, ; Florence Tama,
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3
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Tokuhisa A, Akinaga Y, Terayama K, Okamoto Y, Okuno Y. Single-Image Super-Resolution Improvement of X-ray Single-Particle Diffraction Images Using a Convolutional Neural Network. J Chem Inf Model 2022; 62:3352-3364. [PMID: 35820663 PMCID: PMC9326892 DOI: 10.1021/acs.jcim.2c00660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
![]()
Femtosecond X-ray pulse lasers are promising probes for
the elucidation
of the multiconformational states of biomolecules because they enable
snapshots of single biomolecules to be observed as coherent diffraction
images. Multi-image processing using an X-ray free-electron laser
has proven to be a successful structural analysis method for viruses.
However, the performance of single-particle analysis (SPA) for flexible
biomolecules with sizes ≤100 nm remains difficult. Owing to
the multiconformational states of biomolecules and noisy character
of diffraction images, diffraction image improvement by multi-image
processing is often ineffective for such molecules. Herein, a single-image
super-resolution (SR) model was constructed using an SR convolutional
neural network (SRCNN). Data preparation was performed in silico to
consider the actual observation situation with unknown molecular orientations
and the fluctuation of molecular structure and incident X-ray intensity.
It was demonstrated that the trained SRCNN model improved the single-particle
diffraction image quality, corresponding to an observed image with
an incident X-ray intensity (approximately three to seven times higher
than the original X-ray intensity), while retaining the individuality
of the diffraction images. The feasibility of SPA for flexible biomolecules
with sizes ≤100 nm was dramatically increased by introducing
the SRCNN improvement at the beginning of the various structural analysis
schemes.
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Affiliation(s)
- Atsushi Tokuhisa
- RIKEN Center for Computational Science, 7-1-26, Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.,RIKEN Medical Sciences Innovation Hub Program, 1-7-22, Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
| | - Yoshinobu Akinaga
- RIKEN Center for Computational Science, 7-1-26, Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.,RIKEN Medical Sciences Innovation Hub Program, 1-7-22, Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.,VINAS Co., Ltd., Keihan Dojima Bldg., Dojima 2 1 31, Kita-ku, Osaka 530-0003, Japan
| | - Kei Terayama
- Graduate School of Medical Life Science, Yokohama City University, 1-7-29, Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.,RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihombashi, Chuo-ku, Tokyo 103-0027, Japan
| | - Yuji Okamoto
- Graduate School of Medicine, Kyoto University, Shogoin-Kawaharacho, Sakyo-ku, Kyoto 606-8507, Japan
| | - Yasushi Okuno
- RIKEN Center for Computational Science, 7-1-26, Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.,RIKEN Medical Sciences Innovation Hub Program, 1-7-22, Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.,Center for Cluster Development and Coordination, Foundation for Biomedical Research and Innovation at Kobe, 6-3-5, Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.,Graduate School of Medicine, Kyoto University, Shogoin-Kawaharacho, Sakyo-ku, Kyoto 606-8507, Japan
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4
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Dasgupta B, Miyashita O, Uchihashi T, Tama F. Reconstruction of Three-Dimensional Conformations of Bacterial ClpB from High-Speed Atomic-Force-Microscopy Images. Front Mol Biosci 2021; 8:704274. [PMID: 34422905 PMCID: PMC8376356 DOI: 10.3389/fmolb.2021.704274] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Accepted: 07/13/2021] [Indexed: 11/14/2022] Open
Abstract
ClpB belongs to the cellular disaggretase machinery involved in rescuing misfolded or aggregated proteins during heat or other cellular shocks. The function of this protein relies on the interconversion between different conformations in its native condition. A recent high-speed-atomic-force-microscopy (HS-AFM) experiment on ClpB from Thermus thermophilus shows four predominant conformational classes, namely, open, closed, spiral, and half-spiral. Analyses of AFM images provide only partial structural information regarding the molecular surface, and thus computational modeling of three-dimensional (3D) structures of these conformations should help interpret dynamical events related to ClpB functions. In this study, we reconstruct 3D models of ClpB from HS-AFM images in different conformational classes. We have applied our recently developed computational method based on a low-resolution representation of 3D structure using a Gaussian mixture model, combined with a Monte-Carlo sampling algorithm to optimize the agreement with target AFM images. After conformational sampling, we obtained models that reflect conformational variety embedded within the AFM images. From these reconstructed 3D models, we described, in terms of relative domain arrangement, the different types of ClpB oligomeric conformations observed by HS-AFM experiments. In particular, we highlighted the slippage of the monomeric components around the seam. This study demonstrates that such details of information, necessary for annotating the different conformational states involved in the ClpB function, can be obtained by combining HS-AFM images, even with limited resolution, and computational modeling.
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Affiliation(s)
- Bhaskar Dasgupta
- Computational Structural Biology Research Team, RIKEN-Center for Computational Science, Kobe, Japan
| | - Osamu Miyashita
- Computational Structural Biology Research Team, RIKEN-Center for Computational Science, Kobe, Japan
| | - Takayuki Uchihashi
- Institute for Glyco-core Research (iGCORE), Nagoya University, Nagoya, Japan.,Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, Okazaki, Japan.,Department of Physics, Graduate School of Science, Nagoya University, Nagoya, Japan
| | - Florence Tama
- Computational Structural Biology Research Team, RIKEN-Center for Computational Science, Kobe, Japan.,Department of Physics, Graduate School of Science, Nagoya University, Nagoya, Japan.,Institute of Transformative Bio-Molecules, Nagoya University, Nagoya, Japan
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5
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Tiwari SP, Tama F, Miyashita O. Protocol for Retrieving Three-Dimensional Biological Shapes for a Few XFEL Single-Particle Diffraction Patterns. J Chem Inf Model 2021; 61:4108-4119. [PMID: 34357759 DOI: 10.1021/acs.jcim.1c00602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
X-ray free-electron laser (XFEL) scattering promises to probe single biomolecular complexes without crystallization, enabling the study of biomolecular structures under near-physiological conditions at room temperature. However, such structural determination of biomolecules is extremely challenging thus far. In addition to the large numbers of diffraction patterns required, the orientation of each diffraction pattern needs to be accurately estimated and the missing phase information needs to be recovered for three-dimensional (3D) structure reconstruction. Given the current limitations to the amount and resolution of the data available from single-particle XFEL scattering experiments, we propose an alternative approach to find plausible 3D biological shapes from a limited number of diffraction patterns to serve as a starting point for further analyses. In our proposed strategy, small sets of input (e.g., five) XFEL diffraction patterns were matched against a library of diffraction patterns simulated from 1628 electron microscopy (EM) models to find potential matching 3D models that are consistent with the input diffraction patterns. This approach was tested for three example cases: EMD-3457 (Thermoplasma acidophilum 20S proteasome), EMD-5141 (Escherichia coli 70S ribosome complex), and EMD-5152 (budding yeast Nup84 complex). We observed that choosing the best strategy to define matching regions on the diffraction patterns is critical for identifying correctly matching diffraction patterns. While increasing the number of input diffraction patterns improved the matches in some cases, we found that the resulting matches are more dependent on the uniqueness or complexity of the shape as captured in the individual input diffraction patterns and the availability of a similar 3D biological shape in the search library. The protocol could be useful for finding candidate models for a limited amount of low-resolution data, even when insufficient for reconstruction, performing a quick exploration of new data upon collection, and the analysis of the conformational heterogeneity of the particle of interest as captured within the diffraction patterns.
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Affiliation(s)
- Sandhya P Tiwari
- RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan.,Graduate School of Integrated Sciences for Life, Hiroshima University, Higashi-Hiroshima, Hiroshima 739-8521, Japan
| | - Florence Tama
- RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan.,Graduate School of Science, Department of Physics, Nagoya University, Nagoya, Aichi 464-8601, Japan.,Institute of Transformative Bio-Molecules (WPI-ITbM), Nagoya University, Nagoya, Aichi 464-8601, Japan
| | - Osamu Miyashita
- RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
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Tokuhisa A, Kanada R, Chiba S, Terayama K, Isaka Y, Ma B, Kamiya N, Okuno Y. Coarse-Grained Diffraction Template Matching Model to Retrieve Multiconformational Models for Biomolecule Structures from Noisy Diffraction Patterns. J Chem Inf Model 2020; 60:2803-2818. [PMID: 32469517 DOI: 10.1021/acs.jcim.0c00131] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Biomolecular imaging using X-ray free-electron lasers (XFELs) has been successfully applied to serial femtosecond crystallography. However, the application of single-particle analysis for structure determination using XFELs with 100 nm or smaller biomolecules has two practical problems: the incomplete diffraction data sets for reconstructing 3D assembled structures and the heterogeneous conformational states of samples. A new diffraction template matching method is thus presented here to retrieve a plausible 3D structural model based on single noisy target diffraction patterns, assuming candidate structures. Two concepts are introduced here: prompt candidate diffraction, generated by enhanced sampled coarse-grain (CG) candidate structures, and efficient molecular orientation searching for matching based on Bayesian optimization. A CG model-based diffraction-matching protocol is proposed that achieves a 100-fold speed increase compared to exhaustive diffraction matching using an all-atom model. The conditions that enable multiconformational analysis were also investigated by simulated diffraction data for various conformational states of chromatin and ribosomes. The proposed method can enable multiconformational analysis, with a structural resolution of at least 20 Å for 270-800 Å flexible biomolecules, in experimental single-particle structure analyses that employ XFELs.
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Affiliation(s)
- Atsushi Tokuhisa
- RIKEN Cluster for Science and Technology Hub, 6-3-5, Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.,RIKEN Center for Computational Science, 6-3-5, Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.,RIKEN Medical Sciences Innovation Hub Program, 1-7-22, Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan
| | - Ryo Kanada
- RIKEN Cluster for Science and Technology Hub, 6-3-5, Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Shuntaro Chiba
- RIKEN Medical Sciences Innovation Hub Program, 1-7-22, Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan
| | - Kei Terayama
- RIKEN Medical Sciences Innovation Hub Program, 1-7-22, Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan.,RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihombashi, Chuo-ku, Tokyo 103-0027, Japan.,Graduate School of Medicine, Kyoto University, Shogoin-Kawaharacho, Sakyo-ku, Kyoto 606-8507, Japan
| | - Yuta Isaka
- RIKEN Cluster for Science and Technology Hub, 6-3-5, Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.,Center for Cluster Development and Coordination, Foundation for Biomedical Research and Innovation at Kobe, 6-3-5, Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Biao Ma
- RIKEN Cluster for Science and Technology Hub, 6-3-5, Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.,Center for Cluster Development and Coordination, Foundation for Biomedical Research and Innovation at Kobe, 6-3-5, Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Narutoshi Kamiya
- Graduate School of Simulation Studies, University of Hyogo, 7-1-28, Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Yasushi Okuno
- RIKEN Cluster for Science and Technology Hub, 6-3-5, Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.,RIKEN Medical Sciences Innovation Hub Program, 1-7-22, Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan.,Graduate School of Medicine, Kyoto University, Shogoin-Kawaharacho, Sakyo-ku, Kyoto 606-8507, Japan.,Center for Cluster Development and Coordination, Foundation for Biomedical Research and Innovation at Kobe, 6-3-5, Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
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7
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Srivastava A, Tiwari SP, Miyashita O, Tama F. Integrative/Hybrid Modeling Approaches for Studying Biomolecules. J Mol Biol 2020; 432:2846-2860. [DOI: 10.1016/j.jmb.2020.01.039] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Revised: 01/20/2020] [Accepted: 01/24/2020] [Indexed: 12/12/2022]
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Dasgupta B, Miyashita O, Tama F. Reconstruction of low-resolution molecular structures from simulated atomic force microscopy images. Biochim Biophys Acta Gen Subj 2019; 1864:129420. [PMID: 31472175 DOI: 10.1016/j.bbagen.2019.129420] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Revised: 08/22/2019] [Accepted: 08/26/2019] [Indexed: 12/16/2022]
Abstract
BACKGROUND Atomic Force Microscopy (AFM) is an experimental technique to study structure-function relationship of biomolecules. AFM provides images of biomolecules at nanometer resolution. High-speed AFM experiments produce a series of images following dynamics of biomolecules. To further understand biomolecular functions, information on three-dimensional (3D) structures is beneficial. METHOD We aim to recover 3D information from an AFM image by computational modeling. The AFM image includes only low-resolution representation of a molecule; therefore we represent the structures by a coarse grained model (Gaussian mixture model). Using Monte-Carlo sampling, candidate models are generated to increase similarity between AFM images simulated from the models and target AFM image. RESULTS The algorithm was tested on two proteins to model their conformational transitions. Using a simulated AFM image as reference, the algorithm can produce a low-resolution 3D model of the target molecule. Effect of molecular orientations captured in AFM images on the 3D modeling performance was also examined and it is shown that similar accuracy can be obtained for many orientations. CONCLUSIONS The proposed algorithm can generate 3D low-resolution protein models, from which conformational transitions observed in AFM images can be interpreted in more detail. GENERAL SIGNIFICANCE High-speed AFM experiments allow us to directly observe biomolecules in action, which provides insights on biomolecular function through dynamics. However, as only partial structural information can be obtained from AFM data, this new AFM based hybrid modeling method would be useful to retrieve 3D information of the entire biomolecule.
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Affiliation(s)
- Bhaskar Dasgupta
- Center for Computational Science, RIKEN, Kobe, Hyogo, 650-0047, Japan.
| | - Osamu Miyashita
- Center for Computational Science, RIKEN, Kobe, Hyogo, 650-0047, Japan.
| | - Florence Tama
- Center for Computational Science, RIKEN, Kobe, Hyogo, 650-0047, Japan; Department of Physics, Graduate School of Science, Nagoya University, Aichi, 464-8602, Japan; Institute of Transformative Bio-Molecules (WPI-ITbM), Nagoya University, Aichi, 464-8601, Japan.
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Jonic S, Miyashita O, Callebaut I. Editorial: Hybrid Biomolecular Modeling. Front Mol Biosci 2018; 5:98. [PMID: 30474030 PMCID: PMC6238118 DOI: 10.3389/fmolb.2018.00098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Accepted: 10/23/2018] [Indexed: 12/03/2022] Open
Affiliation(s)
- Slavica Jonic
- Sorbonne Université, UMR CNRS 7590, Muséum National d'Histoire Naturelle, IRD, Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie, IMPMC, Paris, France
| | | | - Isabelle Callebaut
- Sorbonne Université, UMR CNRS 7590, Muséum National d'Histoire Naturelle, IRD, Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie, IMPMC, Paris, France
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Srivastava A, Nagai T, Srivastava A, Miyashita O, Tama F. Role of Computational Methods in Going beyond X-ray Crystallography to Explore Protein Structure and Dynamics. Int J Mol Sci 2018; 19:E3401. [PMID: 30380757 PMCID: PMC6274748 DOI: 10.3390/ijms19113401] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2018] [Revised: 10/20/2018] [Accepted: 10/27/2018] [Indexed: 12/13/2022] Open
Abstract
Protein structural biology came a long way since the determination of the first three-dimensional structure of myoglobin about six decades ago. Across this period, X-ray crystallography was the most important experimental method for gaining atomic-resolution insight into protein structures. However, as the role of dynamics gained importance in the function of proteins, the limitations of X-ray crystallography in not being able to capture dynamics came to the forefront. Computational methods proved to be immensely successful in understanding protein dynamics in solution, and they continue to improve in terms of both the scale and the types of systems that can be studied. In this review, we briefly discuss the limitations of X-ray crystallography in studying protein dynamics, and then provide an overview of different computational methods that are instrumental in understanding the dynamics of proteins and biomacromolecular complexes.
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Affiliation(s)
- Ashutosh Srivastava
- Institute of Transformative Bio-Molecules (WPI), Nagoya University, Nagoya, Aichi 464-8601, Japan.
| | - Tetsuro Nagai
- Department of Physics, Graduate School of Science, Nagoya University, Nagoya, Aichi 464-8602, Japan.
| | - Arpita Srivastava
- Department of Physics, Graduate School of Science, Nagoya University, Nagoya, Aichi 464-8602, Japan.
| | - Osamu Miyashita
- RIKEN-Center for Computational Science, Kobe, Hyogo 650-0047, Japan.
| | - Florence Tama
- Institute of Transformative Bio-Molecules (WPI), Nagoya University, Nagoya, Aichi 464-8601, Japan.
- Department of Physics, Graduate School of Science, Nagoya University, Nagoya, Aichi 464-8602, Japan.
- RIKEN-Center for Computational Science, Kobe, Hyogo 650-0047, Japan.
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11
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Nagai T, Mochizuki Y, Joti Y, Tama F, Miyashita O. Gaussian mixture model for coarse-grained modeling from XFEL. OPTICS EXPRESS 2018; 26:26734-26749. [PMID: 30469754 DOI: 10.1364/oe.26.026734] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2018] [Accepted: 09/01/2018] [Indexed: 06/09/2023]
Abstract
We explore the advantage of Gaussian mixture model (GMM) for interpretation of single particle diffraction patterns from X-ray free electron laser (XFEL) experiments. GMM approximates a biomolecular shape by the superposition of Gaussian distributions. As the Fourier transformation of GMM can be quickly performed, we can efficiently simulate XFEL diffraction patterns from approximated structure models. We report that the resolution that GMM can accurately reproduce is proportional to the cubic root of the number of Gaussians used in the modeling. This behavior can be attributed to the correspondence between the number of adjustable parameters in GMM and the amount of sampling points in diffraction space. Furthermore, GMMs can successfully be used to perform angular assignment and to detect conformational variation. These results demonstrate that GMMs serve as useful coarse-grained models for hybrid approach in XFEL single particle experiments.
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12
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Tiwari SP, Tama F, Miyashita O. Searching for 3D structural models from a library of biological shapes using a few 2D experimental images. BMC Bioinformatics 2018; 19:320. [PMID: 30208849 PMCID: PMC6134691 DOI: 10.1186/s12859-018-2358-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2017] [Accepted: 09/03/2018] [Indexed: 01/08/2023] Open
Abstract
Background Advancements in biophysical experimental techniques have pushed the limits in terms of the types of phenomena that can be characterized, the amount of data that can be produced and the resolution at which we can visualize them. Single particle techniques such as Electron Microscopy (EM) and X-ray free electron laser (XFEL) scattering require a large number of 2D images collected to resolve three-dimensional (3D) structures. In this study, we propose a quick strategy to retrieve potential 3D shapes, as low-resolution models, from a few 2D experimental images by searching a library of 2D projection images generated from existing 3D structures. Results We developed the protocol to assemble a non-redundant set of 3D shapes for generating the 2D image library, and to retrieve potential match 3D shapes for query images, using EM data as a test. In our strategy, we disregard differences in volume size, giving previously unknown structures and conformations a greater number of 3D biological shapes as possible matches. We tested the strategy using images from three EM models as query images for searches against a library of 22750 2D projection images generated from 250 random EM models. We found that our ability to identify 3D shapes that match the query images depends on how complex the outline of the 2D shapes are and whether they are represented in the search image library. Conclusions Through our computational method, we are able to quickly retrieve a 3D shape from a few 2D projection images. Our approach has the potential for exploring other types of 2D single particle structural data such as from XFEL scattering experiments, for providing a tool to interpret low-resolution data that may be insufficient for 3D reconstruction, and for estimating the mixing of states or conformations that could exist in such experimental data. Electronic supplementary material The online version of this article (10.1186/s12859-018-2358-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Sandhya P Tiwari
- Computational Structural Biology Unit, RIKEN Center for Computational Science, Kobe, Japan
| | - Florence Tama
- Computational Structural Biology Unit, RIKEN Center for Computational Science, Kobe, Japan. .,Graduate School of Science, Department of Physics & Institute of Transformative Bio-Molecules (WPI-ITbM), Nagoya University, Nagoya, Japan.
| | - Osamu Miyashita
- Computational Structural Biology Unit, RIKEN Center for Computational Science, Kobe, Japan
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Nakano M, Miyashita O, Jonic S, Tokuhisa A, Tama F. Single-particle XFEL 3D reconstruction of ribosome-size particles based on Fourier slice matching: requirements to reach subnanometer resolution. JOURNAL OF SYNCHROTRON RADIATION 2018; 25:1010-1021. [PMID: 29979162 DOI: 10.1107/s1600577518005568] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2017] [Accepted: 04/10/2018] [Indexed: 06/08/2023]
Abstract
Three-dimensional (3D) structures of biomolecules provide insight into their functions. Using X-ray free-electron laser (XFEL) scattering experiments, it was possible to observe biomolecules that are difficult to crystallize, under conditions that are similar to their natural environment. However, resolving 3D structure from XFEL data is not without its challenges. For example, strong beam intensity is required to obtain sufficient diffraction signal and the beam incidence angles to the molecule need to be estimated for diffraction patterns with significant noise. Therefore, it is important to quantitatively assess how the experimental conditions such as the amount of data and their quality affect the expected resolution of the resulting 3D models. In this study, as an example, the restoration of 3D structure of ribosome from two-dimensional diffraction patterns created by simulation is shown. Tests are performed using the diffraction patterns simulated for different beam intensities and using different numbers of these patterns. Guidelines for selecting parameters for slice-matching 3D reconstruction procedures are established. Also, the minimum requirements for XFEL experimental conditions to obtain diffraction patterns for reconstructing molecular structures to a high-resolution of a few nanometers are discussed.
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Affiliation(s)
- Miki Nakano
- Advanced Institute of Computational Science, RIKEN, 6-7-1 Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Osamu Miyashita
- Advanced Institute of Computational Science, RIKEN, 6-7-1 Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Slavica Jonic
- IMPMC, Sorbonne Universités - CNRS UMR 7590, UPMC Université Paris 6, MNHN, IRD UMR 206, Paris 75005, France
| | - Atsushi Tokuhisa
- Advanced Institute of Computational Science, RIKEN, 6-7-1 Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Florence Tama
- Advanced Institute of Computational Science, RIKEN, 6-7-1 Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
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Nakano M, Miyashita O, Jonic S, Song C, Nam D, Joti Y, Tama F. Three-dimensional reconstruction for coherent diffraction patterns obtained by XFEL. JOURNAL OF SYNCHROTRON RADIATION 2017; 24:727-737. [PMID: 28664878 PMCID: PMC5493022 DOI: 10.1107/s1600577517007767] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2016] [Accepted: 05/24/2017] [Indexed: 05/19/2023]
Abstract
The three-dimensional (3D) structural analysis of single particles using an X-ray free-electron laser (XFEL) is a new structural biology technique that enables observations of molecules that are difficult to crystallize, such as flexible biomolecular complexes and living tissue in the state close to physiological conditions. In order to restore the 3D structure from the diffraction patterns obtained by the XFEL, computational algorithms are necessary as the orientation of the incident beam with respect to the sample needs to be estimated. A program package for XFEL single-particle analysis based on the Xmipp software package, that is commonly used for image processing in 3D cryo-electron microscopy, has been developed. The reconstruction program has been tested using diffraction patterns of an aerosol nanoparticle obtained by tomographic coherent X-ray diffraction microscopy.
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Affiliation(s)
- Miki Nakano
- Advanced Institute of Computational Science, RIKEN, 6-7-1 Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Osamu Miyashita
- Advanced Institute of Computational Science, RIKEN, 6-7-1 Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Slavica Jonic
- IMPMC, Sorbonne Universités – CNRS UMR 7590, UPMC Univ Paris 6, MNHN, IRD UMR 206, Paris 75005, France
| | - Changyong Song
- Department of Physics, Pohang University of Science and Technology (POSTECH), Pohang 790-784, Republic of Korea
| | - Daewoong Nam
- Department of Physics, Pohang University of Science and Technology (POSTECH), Pohang 790-784, Republic of Korea
| | - Yasumasa Joti
- XFEL Utilization Division, Japan Synchrotron Radiation Research Institute (JASRI), 1-1-1 Kouto, Sayo-cho, Sayo-gun, Hyogo 679-5198, Japan
| | - Florence Tama
- Advanced Institute of Computational Science, RIKEN, 6-7-1 Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
- Department of Physics, Graduate School of Science, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8602, Japan
- Institute of Transformative Bio-Molecules, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8602, Japan
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Wang H, Liu H. Determining Complex Structures using Docking Method with Single Particle Scattering Data. Front Mol Biosci 2017; 4:23. [PMID: 28487857 PMCID: PMC5403940 DOI: 10.3389/fmolb.2017.00023] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Accepted: 03/29/2017] [Indexed: 11/23/2022] Open
Abstract
Protein complexes are critical for many molecular functions. Due to intrinsic flexibility and dynamics of complexes, their structures are more difficult to determine using conventional experimental methods, in contrast to individual subunits. One of the major challenges is the crystallization of protein complexes. Using X-ray free electron lasers (XFELs), it is possible to collect scattering signals from non-crystalline protein complexes, but data interpretation is more difficult because of unknown orientations. Here, we propose a hybrid approach to determine protein complex structures by combining XFEL single particle scattering data with computational docking methods. Using simulations data, we demonstrate that a small set of single particle scattering data collected at random orientations can be used to distinguish the native complex structure from the decoys generated using docking algorithms. The results also indicate that a small set of single particle scattering data is superior to spherically averaged intensity profile in distinguishing complex structures. Given the fact that XFEL experimental data are difficult to acquire and at low abundance, this hybrid approach should find wide applications in data interpretations.
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Affiliation(s)
| | - Haiguang Liu
- Complex Systems Division, Beijing Computational Science Research CenterBeijing, China
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16
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X-ray free electron laser single-particle analysis for biological systems. Curr Opin Struct Biol 2017; 43:163-169. [DOI: 10.1016/j.sbi.2017.03.014] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2016] [Revised: 03/24/2017] [Accepted: 03/30/2017] [Indexed: 02/01/2023]
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