Ligand binding remodels protein side chain conformational heterogeneity

  1. Stephanie A Wankowicz
  2. Saulo H de Oliveira
  3. Daniel W Hogan
  4. Henry van den Bedem
  5. James S Fraser  Is a corresponding author
  1. University of California, San Francisco, United States
  2. Atomwise, Inc, United States

Abstract

While protein conformational heterogeneity plays an important role in many aspects of biological function, including ligand binding, its impact has been difficult to quantify. Macromolecular X-ray diffraction is commonly interpreted with a static structure, but it can provide information on both the anharmonic and harmonic contributions to conformational heterogeneity. Here, through multiconformer modeling of time- and space-averaged electron density, we measure conformational heterogeneity of 743 stringently matched pairs of crystallographic datasets that reflect unbound/apo and ligand-bound/holo states. When comparing the conformational heterogeneity of side chains, we observe that when binding site residues become more rigid upon ligand binding, distant residues tend to become more flexible, especially in non-solvent exposed regions. Among ligand properties, we observe increased protein flexibility as the number of hydrogen bonds decrease and relative hydrophobicity increases. Across a series of 13 inhibitor bound structures of CDK2, we find that conformational heterogeneity is correlated with inhibitor features and identify how conformational changes propagate differences in conformational heterogeneity away from the binding site. Collectively, our findings agree with models emerging from NMR studies suggesting that residual side chain entropy can modulate affinity and point to the need to integrate both static conformational changes and conformational heterogeneity in models of ligand binding.

Data availability

Refined models are available here: https://zenodo.org/record/5533006#.YVJr2Z5KgUsCode can be found in the following repositories:-Dataset selection: https://github.com/stephaniewankowicz/PDB_selection_pipeline-Refinement/qFit pipeline: https://github.com/stephaniewankowicz/refinement_qFit-Analysis/Figures: https://github.com/fraser-lab/Apo_Holo_Analysis-qFit: https://github.com/ExcitedStates/qfit-3.0.

The following data sets were generated

Article and author information

Author details

  1. Stephanie A Wankowicz

    Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, United States
    Competing interests
    No competing interests declared.
  2. Saulo H de Oliveira

    Atomwise, Inc, San Francisco, United States
    Competing interests
    Saulo H de Oliveira, is an employee of Atomwise Inc..
  3. Daniel W Hogan

    Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, United States
    Competing interests
    No competing interests declared.
  4. Henry van den Bedem

    Atomwise, Inc, San Francisco, United States
    Competing interests
    Henry van den Bedem, is an employee of Atomwise Inc..
  5. James S Fraser

    Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, United States
    For correspondence
    jfraser@fraserlab.com
    Competing interests
    James S Fraser, has equity, has received consulting fees, and has sponsored research agreements with Relay Therapeutics..
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5080-2859

Funding

National Science Foundation (GRFP 2034836)

  • Stephanie A Wankowicz

National Institutes of Health (GM123159)

  • James S Fraser

National Institutes of Health (GM124149)

  • James S Fraser

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2022, Wankowicz et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 4,156
    views
  • 592
    downloads
  • 51
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Stephanie A Wankowicz
  2. Saulo H de Oliveira
  3. Daniel W Hogan
  4. Henry van den Bedem
  5. James S Fraser
(2022)
Ligand binding remodels protein side chain conformational heterogeneity
eLife 11:e74114.
https://doi.org/10.7554/eLife.74114

Share this article

https://doi.org/10.7554/eLife.74114

Further reading

    1. Structural Biology and Molecular Biophysics
    Chris van Hoorn, Andrew P Carter
    Research Article

    Ciliary rootlets are striated bundles of filaments that connect the base of cilia to internal cellular structures. Rootlets are critical for the sensory and motile functions of cilia. However, the mechanisms underlying these functions remain unknown, in part due to a lack of structural information of rootlet organization. In this study, we obtain 3D reconstructions of membrane-associated and purified rootlets from mouse retina using cryo-electron tomography. We show that flexible protrusions on the rootlet surface, which emanate from the cross-striations, connect to intracellular membranes. In purified rootlets, the striations were classified into amorphous (A)-bands, associated with accumulations on the rootlet surface, and discrete (D)-bands corresponding to punctate lines of density that run through the rootlet. These striations connect a flexible network of longitudinal filaments. Subtomogram averaging suggests the filaments consist of two intertwined coiled coils. The rootlet’s filamentous architecture, with frequent membrane-connecting cross-striations, lends itself well for anchoring large membranes in the cell.

    1. Structural Biology and Molecular Biophysics
    Jian Wu, Nisha A Jonniya ... Susan S Taylor
    Research Article

    Although the αC-β4 loop is a stable feature of all protein kinases, the importance of this motif as a conserved element of secondary structure, as well as its links to the hydrophobic architecture of the kinase core, has been underappreciated. We first review the motif and then describe how it is linked to the hydrophobic spine architecture of the kinase core, which we first discovered using a computational tool, local spatial Pattern (LSP) alignment. Based on NMR predictions that a mutation in this motif abolishes the synergistic high-affinity binding of ATP and a pseudo substrate inhibitor, we used LSP to interrogate the F100A mutant. This comparison highlights the importance of the αC-β4 loop and key residues at the interface between the N- and C-lobes. In addition, we delved more deeply into the structure of the apo C-subunit, which lacks ATP. While apo C-subunit showed no significant changes in backbone dynamics of the αC-β4 loop, we found significant differences in the side chain dynamics of K105. The LSP analysis suggests disruption of communication between the N- and C-lobes in the F100A mutant, which would be consistent with the structural changes predicted by the NMR spectroscopy.