Protein structures are dynamic and can explore a large conformational landscape1,2. Only some of these structural substates are important for protein function (such as ligand binding, catalysis and regulation)3,4,5. How evolution shapes the structural ensemble to optimize a specific function is poorly understood3,4. One of the constraints on the evolution of proteins is the stability of the folded ‘native’ state. Despite this, 44% of the human proteome contains intrinsically disordered peptide segments greater than 30 residues in length6, the majority of which have no known function7,8,9. Here we show that the entropic force produced by an intrinsically disordered carboxy terminus (ID-tail) shifts the conformational ensemble of human UDP-α-d-glucose-6-dehydrogenase (UGDH) towards a substate with a high affinity for an allosteric inhibitor. The function of the ID-tail does not depend on its sequence or chemical composition. Instead, the affinity enhancement can be accurately predicted based on the length of the intrinsically disordered segment, and is consistent with the entropic force generated by an unstructured peptide attached to the protein surface10,11,12,13. Our data show that the unfolded state of the ID-tail rectifies the dynamics and structure of UGDH to favour inhibitor binding. Because this entropic rectifier does not have any sequence or structural constraints, it is an easily acquired adaptation. This model implies that evolution selects for disordered segments to tune the energy landscape of proteins, which may explain the persistence of intrinsic disorder in the proteome.
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The authors thank A. P. Karplus, B. W. Matthews, S. N. Savvides and the members of the Z.A.W. laboratory for helpful discussions. We also thank R. Wang of Norclone for producing the R1 truncation constructs. This work was supported by the NIH National Institute of General Medicine grants R01GM114298 awarded to Z.A.W. and P41GM103422 awarded to M.L.G.
Nature thanks J. Gsponer and the other anonymous reviewer(s) for their contribution to the peer review of this work.
The authors declare no competing interests.
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Extended data figures and tables
Extended Data Fig. 1 The crystal structures of UGDH(FL) and UGDH(ΔID) show no significant structural deviations, and structural evidence for UDP-Xyl binding in the NAD+ site.
a–c, Structural overlay (root mean square deviation (r.m.s.d) = 0.385 Å), comparing the UGDH(FL) (cyan) and UGDH(ΔID) (grey) E* hexamers (a, b) and monomers (c). PDB entries for UGDH(FL) and UGDH(ΔID) are 4RJT and 5W4X, respectively (Extended Data Table 1). d, Crystal structure of native UGDH with UDP-Xyl bound in the active site. Difference density map (F0 – Fc) of UDP-Xyl (chain B) calculated at 2.0 Å resolution and contoured at 3.5σ. The map was calculated after omitting the UDP-Xyl and subjecting the model to simulated annealing. e–l, UDP-Xyl can also bind weakly to the NAD+-binding site of native UGDH. Difference electron density maps (F0 – Fc) were calculated as in d. The uracil and xylose in the NAD+-binding sites were contoured at 3.5 and 3σ for chain A (e and f, respectively), chain B (g and h, respectively), chain D (i and j, respectively) and chain E (k and l, respectively). Chains C and F do not contain UDP-Xyl in the NAD+-binding site. UDP-Xyl binding in the NAD+ site is the source of mixed inhibition observed in the UGDH(FL-dimer) and UGDH(ΔID-dimer) constructs. (see Supplementary Information, Section 1). PDB entry: 5VR8 (this work, Extended Data Table 1).
a–w, Inhibition studies with the allosteric inhibitor UDP-Xyl. Data from two or three independent rate curves were globally fit to equation (7) (or equation (8) for dimers c–f) using nonlinear regression (n ≥ 26 data points). See Extended Data Table 2 for the specific number of data points and fit parameters. Dashed lines indicate 95% confidence intervals. x–kk, NAD+ substrate-saturation curves fit to equation (6) using nonlinear regression (n ≥ 10 independent data points). See Extended Data Table 3 for the specific number of data points used in global fitting. Source data
a–s, Plots of the c(s) distributions with oligomeric species labelled as H (hexamer), T (tetramer), D (dimer) or M (monomer). The R2 mutant (h) shows no change in UDP-Xyl affinity (Fig. 2c and Extended Data Table 2), yet shows evidence of a less stable hexamer. Panel s was included to show that the hexamer in h is less stable partly owing to the K465D substitution in the UGDH(R2) construct. The K465D substitution introduces an unfavourable negative charge near E460 in the hexamer interface, which may reduce the stability. t, Relative distributions, s values (S) and r.m.s.d. values for all sedimentation velocity experiments. Source data
a, ClustalO sequence alignment of all vertebrate UGDH ID-tail regions (79 total). Residues are coloured by type, where blue is positive charge (K, R, H), red is negative charge (D, E), peach is hydrophobic (A, V, L, I, M), orange is aromatic (F, W, Y), green is hydrophilic (S, T, N, Q), yellow is cysteine (C), and magenta is special (P, G). b, The ID-tail was extensively randomized and modified. Sequences of UGDH (FL, R1, R2, −Lys, −Pro, and Ser), aligned by position and coloured by residue type. c, Relative evolutionary rate of UGDH residues from the alignment of 79 vertebrate sequences. The ID-tail (red dots) begins at residue 465 and displays an approximately threefold higher rate of divergence than the folded portion of the protein (black dots). For clarity, only a small, representative segment of the folded protein is shown (residues 460–464). All rates were scaled such that the average rate is 1.0 across the entire dataset.
a, Dashed lines outline the traditional, generously allowed regions of the Ramachandran plot, whereas the red circles identify the conformations used in the Monte Carlo simulations. b, The ranges of ϕ and ψ angles depicted in a. The 10 × 10° bins are centred on the first and last numbers in the range. For example, in region 1, the first ϕ, ψ bin (−155°, 90°) represents the ϕ range −155° to −145° and the ψ range 85° to 95°. c, Ratio of ID-tail conformations constrained (Ω2) to the number of conformations when the ID-tail is unconstrained (Ω1). The entropic costs of confining tails of each length were calculated using equation (1). d, e, The results of the 10-residue ID-tail simulations, shown in a surface representing the hexamer-building interface (orange and grey dimers) with the adjacent ID-tail (cyan) that was fixed during simulations. Also depicted is a representative sampling of 20 allowed Ω2 conformations (blue sticks) from the 4,503 identified in the Monte Carlo simulation. f, The same view as in e, but without the protein surface. g–i, Same as in d–f, but now including a sampling of 20 of the 3,002 Ω1 conformations (red sticks) that clash with the fixed adjacent ID-tail (not depicted for clarity). j–l, Same as g–i, but including 750 of the 142,607 Ω1 conformations (tan sticks) that clash with the protein surface.
a, The per cent deuterium uptake of the ID-tail peptide region (residues 457–492; red closed circles) saturates rapidly, consistent with an unfolded peptide31. For comparison, two peptides corresponding to the well-ordered α9 helix region (open blue squares and circles) saturate slowly. Data are mean ± s.d. of independently replicated time points (n = 4). For some points, the standard deviation is less than the dimensions of the data symbol. b, The normalized cumulative changes in the hydrogen–deuterium exchange rates (UGDH(FL-dimer) –UGDH(ΔID-dimer)). Most of the kinetics measurements consisted of six independently replicated time points (n = 4), processed to give the mean exchange (red, blue or green bars). Approximately 5% of the data displayed low signal:noise or was missing, and in those cases the means were derived from four or more time points. Results were normalized by dividing by the number of measurements. The propagation error for each peptide is equal to the square root of the sum of all squared standard deviation values for the collective measurement of UGDH(FL-dimer) and UGDH(ΔID-dimer). Source data
a, b, Transient-state analysis of UDP-Xyl binding kinetics using intrinsic protein fluorescence. Six independent progress curves (coloured traces) at different inhibitor concentrations were globally fit (black line) to the allosteric inhibition model (see Fig. 4b) for UGDH(FL) and UGDH(ΔID). Each progress curve was replicated (n ≥ 4) with similar results, and the final kinetic model was refined against the averaged progress curves (see e for fit parameters). c, d, Confidence contour plots depicting how constrained each globally fit parameter is relative to the others, for all progress curves in a and b (parameters are listed in e). e, Table of the microscopic rate constants from global fitting of the progress curves described in a and b. The best fit and s.e.m. were obtained from global nonlinear regression based on the numerical integration of rate equations for the described model (see main text and Methods). Upper and lower limits were obtained from the confidence contour analysis. Kd = (K1K2K3)−1, where Kn = kn/k−n. f, Enzyme hysteresis is observed as a lag in progress curves. Representative progress curves (of n = 6 independent measurements) for both UGDH(FL) (cyan) and UGDH(ΔID) (grey) are fit to equation (4) (black line). Curves are displayed with the y axis offset for clarity. Final results for all replicate curves are displayed in Fig. 4a. Source data
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Keul, N.D., Oruganty, K., Schaper Bergman, E.T. et al. The entropic force generated by intrinsically disordered segments tunes protein function. Nature 563, 584–588 (2018). https://doi.org/10.1038/s41586-018-0699-5
- Entropic Forces
- Intrinsically Disordered
- Hydrogen/deuterium Exchange Mass Spectrometry
- Allosteric Switch
- Standard Reaction Buffer
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