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Integrative structural modeling of macromolecular complexes using Assembline

Nature Protocols volume 17, pages 152–176 (2022)Cite this article

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Abstract

Integrative modeling enables structure determination of macromolecular complexes by combining data from multiple experimental sources such as X-ray crystallography, electron microscopy or cross-linking mass spectrometry. It is particularly useful for complexes not amenable to high-resolution electron microscopy—complexes that are flexible, heterogeneous or imaged in cells with cryo-electron tomography. We have recently developed an integrative modeling protocol that allowed us to model multi-megadalton complexes as large as the nuclear pore complex. Here, we describe the Assembline software package, which combines multiple programs and libraries with our own algorithms in a streamlined modeling pipeline. Assembline builds ensembles of models satisfying data from atomic structures or homology models, electron microscopy maps and other experimental data, and provides tools for their analysis. Compared with other methods, Assembline enables efficient sampling of conformational space through a multistep procedure, provides new modeling restraints and includes a unique configuration system for setting up the modeling project. Our protocol achieves exhaustive sampling in less than 100–1,000 CPU-hours even for complexes in the megadalton range. For larger complexes, resources available in institutional or public computer clusters are needed and sufficient to run the protocol. We also provide step-by-step instructions for preparing the input, running the core modeling steps and assessing modeling performance at any stage.

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Fig. 1: Assembline workflow.
Fig. 2: Detailed workflow regarding the calculation of fit libraries.
Fig. 3: Workflow of the global optimization step.
Fig. 4: An example of Xlink Analyzer interface used for configuring the modeling project.
Fig. 5: Workflow of the refinement step.
Fig. 6: Integrative models of ScNPC.
Fig. 7: Integrative modeling of Elongator complex.
Fig. 8: Validation of the integrative model of the Elongator complex by a high-resolution cryo-EM structure.

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Data availability

All datasets needed for the step-by-step tutorials (i.e., for yeast NPC and Elongator complex modeling) are provided at https://git.embl.de/rantos/scnpc_tutorial.git (for the yeast NPC) and https://git.embl.de/kosinski/elongator_tutorial.git (for the Elongator complex).

Code availability

The Assembline software is freely available as an open-source Python package (https://www.embl-hamburg.de/Assembline/), which can be installed from source code (https://git.embl.de/kosinski/Assembline) or from the Anaconda repository (https://anaconda.org/kosinskilab/assembline). Documentation is provided in the Supplementary Manual and can also be found online (https://assembline.readthedocs.io/en/latest/), and in the form of the step-by-step tutorials for modeling the yeast NPC (Supplementary Tutorial 1, online version: https://scnpc-tutorial.readthedocs.io/en/latest/) and Elongator complex (Supplementary Tutorial 2, online version: https://elongator-tutorial.readthedocs.io/en/latest/).

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Acknowledgements

We thank coauthors of the publications in which the Assembline protocol has been applied. We are grateful to D. Ziemianowicz and K. Kaszuba for comments on the manuscript and the protocol, and A. Obarska for feedback on the protocol. The work has been supported by the Federal Ministry of Education and Research of Germany (FKZ 031L0100)

Author information

Authors and Affiliations

  1. Centre for Structural Systems Biology (CSSB), Hamburg, Germany

    Vasileios Rantos, Kai Karius & Jan Kosinski

  2. European Molecular Biology Laboratory Hamburg, Hamburg, Germany

    Vasileios Rantos, Kai Karius & Jan Kosinski

  3. Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany

    Jan Kosinski

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  1. Vasileios Rantos
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  2. Kai Karius
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Contributions

V.R., K.K. and J.K. developed the protocol. V.R and J.K wrote the manuscript.

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Correspondence to Jan Kosinski.

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The authors declare no competing interests.

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Peer review information Nature Protocols thanks André Hoelz, Peter J. Peters and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Related links

Key references using this protocol

Beckham, K. S. H. et al. Sci. Adv. 7, eabg9923 (2021): https://doi.org/10.1126/sciadv.abg9923

Allegretti, M. et al. Nature 586, 796–800 (2020): https://doi.org/10.1038/s41586-020-2670-5

Zimmerli, C. E. et al. Preprint at bioRxiv (2020): https://doi.org/10.1101/2020.07.30.228585

Dauden, M. I. et al. EMBO Rep. 18, 264–279 (2017): https://doi.org/10.15252/embr.201643353

Kosinski, J. et al. Science 352, 363–365 (2016): https://doi.org/10.1126/science.aaf0643

Essential data used in this protocol

Allegretti, M. et al. Nature 586, 796–800 (2020): https://doi.org/10.1038/s41586-020-2670-5

Dauden, M. I. et al. EMBO Rep. 18, 264–279 (2017): https://doi.org/10.15252/embr.201643353

Supplementary information

Supplementary Information

Supplementary Figs. 1–3, Supplementary Manual and Supplementary Tutorials 1 and 2.

Reporting Summary

Supplementary Video 1

CR Y-complex trajectory from global optimization. Animation video depicting the trajectory of the best scoring CR Y-complex model of the wild-type in-cell ScNPC6 produced with global optimization step. The model is shown in the coarse-grained representation inside the respective EM map.

Supplementary Video 2

NR Y-complex trajectory from refinement. Animation video depicting the trajectory of the best scoring NR Y-complex model of the in-cell wild-type ScNPC6 produced with refinement step. The model (and the symmetrical copies) is shown in the coarse-grained representation inside the respective EM map.

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Rantos, V., Karius, K. & Kosinski, J. Integrative structural modeling of macromolecular complexes using Assembline. Nat Protoc 17, 152–176 (2022). https://doi.org/10.1038/s41596-021-00640-z

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