Nature - USA (2020-02-13)

(Antfer) #1

Article


PCki=cTP−0os(∨CTki−0)

in which Ti−0 is the vector between the coordinates of i structure and
the chosen reference 0 (4YBQ, in this case), and PCk is one of the major
principal component axes, which can classify and cluster structures,
and extract motion information and transition pathways from them^52 ,^53.
For the MFS ensemble, the first component alone captures about 65%
of the structural variation associated with the rocker switch, thus sepa-
rating the crystallographic structures along the transport cycle. The
angle between the sugar-porter tandem repeats was estimated as the
angle formed by TM2 and TM8, using an in-house Visual Molecular
Dynamics script.


Reporting summary
Further information on research design is available in the Nature
Research Reporting Summary linked to this paper.


Data availability


The coordinates and the structure factors for PfHT1 have been depos-
ited in the PDB 6RW3. All data are available in the paper or Supplemen-
tary Information.



  1. Kota, J., Gilstring, C. F. & Ljungdahl, P. O. Membrane chaperone Shr3 assists in folding
    amino acid permeases preventing precocious ERAD. J. Cell Biol. 176 , 617–628 (2007).

  2. Drew, D. et al. GFP-based optimization scheme for the overexpression and purification of
    eukaryotic membrane proteins in Saccharomyces cerevisiae. Nat. Protoc. 3 , 784–798
    (2008).

  3. Kawate, T. & Gouaux, E. Fluorescence-detection size-exclusion chromatography for
    precrystallization screening of integral membrane proteins. Structure 14 , 673–681
    (2006).

  4. Kabsch, W. XDS. Acta Crystallogr. D 66 , 125–132 (2010).

  5. Evans, P. R. An introduction to data reduction: space-group determination, scaling and
    intensity statistics. Acta Crystallogr. D 67 , 282–292 (2011).

  6. Afonine, P. V. et al. Towards automated crystallographic structure refinement with phenix.
    refine. Acta Crystallogr. D 68 , 352–367 (2012).

  7. DiMaio, F. et al. Improved low-resolution crystallographic refinement with Phenix and
    Rosetta. Nat. Methods 10 , 1102–1104 (2013).

  8. Adams, P. D. et al. PHENIX: a comprehensive Python-based system for macromolecular
    structure solution. Acta Crystallogr. D 66 , 213–221 (2010).

  9. Headd, J. J. et al. Use of knowledge-based restraints in phenix.refine to improve
    macromolecular refinement at low resolution. Acta Crystallogr. D 68 , 381–390 (2012).
    42. Smart, O. S. et al. Exploiting structure similarity in refinement: automated NCS and target-
    structure restraints in BUSTER. Acta Crystallogr. D 68 , 368–380 (2012).
    43. Emsley, P. & Cowtan, K. Coot: model-building tools for molecular graphics. Acta
    Crystallogr. D 60 , 2126–2132 (2004).
    44. Šali, A. & Blundell, T. L. Comparative protein modelling by satisfaction of spatial
    restraints. J. Mol. Biol. 234 , 779–815 (1993).
    45. Jo, S., Kim, T., Iyer, V. G. & Im, W. CHARMM-GUI: a web-based graphical user interface for
    CHARMM. J. Comput. Chem. 29 , 1859–1865 (2008).
    46. Berendsen, H. J. C., Postma, J. P. M., van Gunsteren, W. F., DiNola, A. & Haak, J. R.
    Molecular dynamics with coupling to an external bath. J. Chem. Phys. 81 , 3684 (1984).
    47. Hess, B. P-LINCS: A parallel linear constraint solver for molecular simulation. J. Chem.
    Theory Comput. 4 , 116–122 (2008).
    48. Darden, T., Darrin, Y. & Pedersen, L. Particle mesh Ewald: An N⋅log(N) method for Ewald
    sums in large systems. J. Chem. Phys. 98 , 10089–10092 (1993).
    49. Abraham, M. J. et al. GROMACS: high performance molecular simulations through multi-
    level parallelism from laptops to supercomputers. SoftwareX 1–2, 19–25 (2015).
    50. van der Walt, S. Colbert, S. C. & Varoquaux, G. The NumPy array: a structure for efficient
    numerical computation. Comput. Sci. Eng. 13 , 22 (2011).
    51. Jolliffe, I. T. & Cadima, J. Principal component analysis: a review and recent
    developments. Philos. Trans. A Math. Phys. Eng. Sci. 374 , 20150202 (2016).
    52. Orellana, L., Yoluk, O., Carrillo, O., Orozco, M. & Lindahl, E. Prediction and validation of
    protein intermediate states from structurally rich ensembles and coarse-grained
    simulations. Nat. Commun. 7 , 12575 (2016).
    53. Orellana, L., Gustavsson, J., Bergh, C., Yoluk, O. & Lindahl, E. eBDIMS server: protein
    transition pathways with ensemble analysis in 2D-motion spaces. Bioinformatics 35 ,
    3505–3507 (2019).


Acknowledgements We thank D. Daley for advice on PfHT1 overexpression optimization, and
G. von Heijne and S. Newstead for critical reading of the manuscript. X-ray diffraction data
were collected at the European Synchrotron Radiation Facility beamlines, the Diamond Light
Source beamlines and the MaxIV BioMax beamline with assistance from beamline scientists.
This work was funded by the Knut and Alice Wallenberg Foundation (D.D.) and, the Science for
Life Laboratory (L.D.); D.D. acknowledges support from EMBO through the Young Investigator
Program (YIP).
Author contributions D.D. designed the project. Cloning, expression screening and
crystallization of PfHT1 were carried out by A.A.Q. Data collection, structure determination and
refinement of PfHT1 were carried out by A.A.Q., E.N., J.B., R.M., M.C. and D.D. Experiments for
functional analysis were carried out by A.A.Q. and A.S. Molecular dynamics simulations of
PfHT1 were carried out by S.E.M. and L.D. Sugar porter PCA was carried out by L.O. The
manuscript was prepared by D.D. with contributions from all authors.
Competing interests The authors declare no competing interests.
Additional information
Supplementary information is available for this paper at https://doi.org/10.1038/s41586-020-
1963-z.
Correspondence and requests for materials should be addressed to D.D.
Peer review information Nature thanks Jeff Abramson and the other, anonymous, reviewer(s)
for their contribution to the peer review of this work.
Reprints and permissions information is available at http://www.nature.com/reprints.
Free download pdf