Allosteric inhibition through suppression of transient conformational states

Journal name:
Nature Chemical Biology
Year published:
Published online


The ability to inhibit binding or enzymatic activity is key to preventing aberrant behaviors of proteins. Allosteric inhibition is desirable as it offers several advantages over competitive inhibition, but the mechanisms of action remain poorly understood in most cases. Here we show that allosteric inhibition can be effected by destabilizing a low-populated conformational state that serves as an on-pathway intermediate for ligand binding, without altering the protein's ground-state structure. As standard structural approaches are typically concerned with changes in the ground-state structure of proteins, the presence of such a mechanism can go easily undetected. Our data strongly argue for the routine use of NMR tools suited to detect and characterize transiently formed conformational states in allosteric systems. Structure information on such important intermediates can ultimately result in more efficient design of allosteric inhibitors.

At a glance


  1. CAP* transiently populates the active DBD state.
    Figure 1: CAP* transiently populates the active DBD state.

    (a) Relaxation dispersion profiles of 13C side chain methyls of representative CAP* DBD residues in the apo and cGMP-bound form. R2eff is the effective transverse relaxation rate, and νCPMG is the refocusing frequency of the CPMG train pulse. (b) Enhanced R2 relaxation rate (Rex) values of CAP* and CAP*–cGMP2. Rex is caused by the exchange between the ground and excited states. cGMP is shown in orange sticks. For enhanced clarity, the results are mapped on the structure of CAP with the DBD in the active conformation (CAP–cAMP2). (c) Correlation between the 13CH3 Δω and Δωdisp chemical shifts of selected DBD residues. (d) CAP* interconverts between a ground state, which adopts the inactive conformation and is 93% populated, and an excited state, which adopts the active conformation and is only ∼7% populated. cGMP binding to CAP* results in the suppression of the active conformation through an allosteric mechanism.

  2. Energy landscape of CAP* and its manipulation by the inhibitor.
    Figure 2: Energy landscape of CAP* and its manipulation by the inhibitor.

    (a) Selected region from 1H-15N HSQC spectra of CAP* in the apo form and bound to DNA. Gly173 and Gly184 are located in the recognition helix of DBD. The superscript i denotes the inactive DBD conformation, and the superscript a denotes the active conformation. The active conformation is 'invisible' because it is poorly (∼7%) populated. The chemical shifts of the active DBD conformation match with those of the wild-type CAP–cAMP2 form (depicted with gray dots)12. (b) Energy landscape of CAP* showing the two states, inactive (I) and active (A), and their fractional populations (93% and 7%, respectively). DNA binding selects the active conformation in a population shift mechanism. (c) Selected region from 1H-15N HSQC spectra of CAP* in the apo form and bound to cGMP. Binding of cGMP has no effect on the structure of DBD. (d) Selected region from 1H-15N HSQC spectra of CAP* in the cGMP- and cGMP2-DNA–bound form. DNA does not interact with CAP*–cGMP2. (e) Energy landscape of CAP* (dashed line) and CAP*–cGMP2 (orange line) showing that cGMP binding suppresses the active conformation. (f) Energy landscape of CAP*–cGMP2 showing that depletion of the active conformation in CAP*–cGMP2 results in DNA binding inhibition.

  3. Structural characterization of CAP* and CAP*–cGMP2.
    Figure 3: Structural characterization of CAP* and CAP*–cGMP2.

    (a) Structure of wild-type (WT) CAP9. The region outlined by the rectangle is used for the close-up views in the other panels. (b) Superposition of the wild-type CAP and CAP* structures. In CAP*, Leu127 and Ile128 form a hydrophobic cluster with several hydrophobic residues from CBD (Ile51, Leu61 and Trp85) thereby extending C-helices by a turn of helix. (c) Superposition of the CAP* and CAP*–cGMP2 structures. Binding of cGMP disrupts the hydrophobic cluster in CAP*, and as a result the C-helices partly unwind. (d) Superposition of the wild-type CAP and CAP*–cGMP2 structures.

  4. Allosteric inhibition by suppressing an on-pathway transiently populated intermediate.
    Figure 4: Allosteric inhibition by suppressing an on-pathway transiently populated intermediate.

    The protein interconverts between an inactive ground-state conformation (G) and an excited, active state (E). The active state is only transiently formed and is thus invisible. The ligand interacts exclusively with the excited state, giving rise to the complex (C). The inhibitor binds an allosteric site and suppresses the population of the active conformation (I), thereby resulting in binding inhibition. Structural analysis of the G and I proteins using standard approaches would reveal no structural difference in the binding site region.

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  1. Wells, J.A. & McClendon, C.L. Reaching for high-hanging fruit in drug discovery at protein-protein interfaces. Nature 450, 10011009 (2007).
  2. Lee, G.M. & Craik, C.S. Trapping moving targets with small molecules. Science 324, 213215 (2009).
  3. Hardy, J.A. & Wells, J.A. Searching for new allosteric sites in enzymes. Curr. Opin. Struct. Biol. 14, 706715 (2004).
  4. Groebe, D.R. In search of negative allosteric modulators of biological targets. Drug Discov. Today 14, 4149 (2009).
  5. Maksay, G. Allostery in pharmacology: thermodynamics, evolution and design. Prog. Biophys. Mol. Biol. 106, 463473 (2011).
  6. Arkin, M.R. & Wells, J.A. Small-molecule inhibitors of protein-protein interactions: progressing towards the dream. Nat. Rev. Drug Discov. 3, 301317 (2004).
  7. Tzeng, S.-R. & Kalodimos, C.G. Protein dynamics and allostery: an NMR view. Curr. Opin. Struct. Biol. 21, 6267 (2011).
  8. Passner, J.M., Schultz, S. & Steitz, T. Modeling the cAMP-induced allosteric transition using the crystal structure of CAP–cAMP at 2.1 Å resolution. J. Mol. Biol. 304, 847859 (2000).
  9. Popovych, N., Tzeng, S.-R., Tonelli, M., Ebright, R.H. & Kalodimos, C.G. Structural basis for cAMP-mediated allosteric control of the catabolite activator protein. Proc. Natl. Acad. Sci. USA 106, 69276932 (2009).
  10. Gekko, K., Obu, N., Li, J. & Lee, J. A linear correlation between the energetics of allosteric communication and protein flexibility in the Escherichia coli cyclic AMP receptor protein revealed by mutation-induced changes in compressibility and amide hydrogen-deuterium exchange. Biochemistry 43, 38443852 (2004).
  11. Youn, H., Koh, J. & Roberts, G. Two-state allosteric modeling suggests protein equilibrium as an integral component for cyclic AMP (cAMP) specificity in the cAMP receptor protein of Escherichia coli. J. Bacteriol. 190, 45324540 (2008).
  12. Tzeng, S.-R. & Kalodimos, C.G. Dynamic activation of an allosteric regulatory protein. Nature 462, 368372 (2009).
  13. Tzeng, S.-R. & Kalodimos, C.G. Protein activity regulation by conformational entropy. Nature 488, 236240 (2012).
  14. Palmer, A.G., Kroenke, C.D. & Loria, J.P. Nuclear magnetic resonance methods for quantifying microsecond-to-millisecond motions in biological macromolecules. Methods Enzymol. 339, 204238 (2001).
  15. Baldwin, A.J. & Kay, L.E. NMR spectroscopy brings invisible protein states into focus. Nat. Chem. Biol. 5, 808814 (2009).
  16. Youn, H., Kerby, R., Conrad, M. & Roberts, G. Study of highly constitutively active mutants suggests how cAMP activates cAMP receptor protein. J. Biol. Chem. 281, 11191127 (2006).
  17. Loria, J.P., Rance, M. & Palmer, A.G.A. TROSY CPMG sequence for characterizing chemical exchange in large proteins. J. Biomol. NMR 15, 151155 (1999).
  18. Korzhnev, D.M., Kloiber, K., Kanelis, V., Tugarinov, V. & Kay, L.E. Probing slow dynamics in high molecular weight proteins by methyl-TROSY NMR spectroscopy: application to a 723-residue enzyme. J. Am. Chem. Soc. 126, 39643973 (2004).
  19. Bouvignies, G. et al. Solution structure of a minor and transiently formed state of a T4 lysozyme mutant. Nature 477, 111114 (2011).
  20. Boehr, D.D., McElheny, D., Dyson, H. & Wright, P. The dynamic energy landscape of dihydrofolate reductase catalysis. Science 313, 16381642 (2006).
  21. Carroll, M.J. et al. Evidence for dynamics in proteins as a mechanism for ligand dissociation. Nat. Chem. Biol. 8, 246252 (2012).
  22. Masterson, L.R. et al. cAMP-dependent protein kinase A selects the excited state of the membrane substrate phospholamban. J. Mol. Biol. 412, 155164 (2011).
  23. Lipchock, J.M. & Loria, J.P. Nanometer propagation of millisecond motions in V-type allostery. Structure 18, 15961607 (2010).
  24. Neudecker, P. et al. Structure of an intermediate state in protein folding and aggregation. Science 336, 362366 (2012).
  25. Vendruscolo, M. Excited-state control of protein activity. J. Mol. Biol. 412, 153154 (2011).
  26. Boehr, D.D., Nussinov, R. & Wright, P.E. The role of dynamic conformational ensembles in biomolecular recognition. Nat. Chem. Biol. 5, 789796 (2009).
  27. Chen, L. et al. Structural instability tuning as a regulatory mechanism in protein-protein interactions. Mol. Cell 44, 734744 (2011).
  28. Sprangers, R. & Kay, L.E. Quantitative dynamics and binding studies of the 20S proteasome by NMR. Nature 445, 618622 (2007).
  29. Gelis, I. et al. Structural basis for signal-sequence recognition by the translocase motor SecA as determined by NMR. Cell 131, 756769 (2007).
  30. Takeuchi, K., Ng, E., Malia, T.J. & Wagner, G. 1-13C amino acid selective labeling in a 2H15N background for NMR studies of large proteins. J. Biomol. NMR 38, 8998 (2007).
  31. Evenäs, J. et al. Ligand-induced structural changes to maltodextrin-binding protein as studied by solution NMR spectroscopy. J. Mol. Biol. 309, 961974 (2001).
  32. Mandel, A.M., Akke, M. & Palmer, A. Backbone dynamics of Escherichia coli ribonuclease HI: correlations with structure and function in an active enzyme. J. Mol. Biol. 246, 144163 (1995).
  33. Cole, R. & Loria, J. FAST-Modelfree: a program for rapid automated analysis of solution NMR spin-relaxation data. J. Biomol. NMR 26, 203213 (2003).
  34. d'Auvergne, E.J. & Gooley, P. Optimisation of NMR dynamic models I. Minimisation algorithms and their performance within the model-free and Brownian rotational diffusion spaces. J. Biomol. NMR 40, 107119 (2008).
  35. Lipari, G. & Szabo, A. Model-free approach to the interpretation of nuclear magnetic resonance relaxation in macromolecules. 1. Theory and range of validity. J. Am. Chem. Soc. 104, 45464559 (1982).
  36. Tjandra, N., Feller, S., Pastor, R. & Bax, A. Rotational diffusion anisotropy of human ubiquitin from N-15 NMR relaxation. J. Am. Chem. Soc. 117, 1256212566 (1995).
  37. Hwang, P.M., Skrynnikov, N. & Kay, L. Domain orientation in beta-cyclodextrin-loaded maltose binding protein: diffusion anisotropy measurements confirm the results of a dipolar coupling study. J. Biomol. NMR 20, 8388 (2001).
  38. Dosset, P., Hus, J., Blackledge, M. & Marion, D. Efficient analysis of macromolecular rotational diffusion from heteronuclear relaxation data. J. Biomol. NMR 16, 2328 (2000).
  39. Mulder, F.A., Mittermaier, A., Hon, B., Dahlquist, F. & Kay, L. Studying excited states of proteins by NMR spectroscopy. Nat. Struct. Biol. 8, 932935 (2001).
  40. Carver, J.P. & Richards, R.E. A general two-site solution for the chemical exchange produced dependence of T2 upon the Carr-Purcell pulse separation. J. Magn. Reson. 6, 89105 (1972).
  41. Watt, E.D., Shimada, H., Kovrigin, E. & Loria, J. The mechanism of rate-limiting motions in enzyme function. Proc. Natl. Acad. Sci. USA 104, 1198111986 (2007).
  42. Henzler-Wildman, K.A. et al. Intrinsic motions along an enzymatic reaction trajectory. Nature 450, 838844 (2007).
  43. Korzhnev, D.M. et al. Low-populated folding intermediates of Fyn SH3 characterized by relaxation dispersion NMR. Nature 430, 586590 (2004).
  44. Millet, O., Loria, J., Kroenke, C., Pons, M. & Palmer, A. The static magnetic field dependence of chemical exchange linebroadening defines the NMR chemical shift time scale. J. Am. Chem. Soc. 122, 28672877 (2000).
  45. Shen, Y., Delaglio, F., Cornilescu, G. & Bax, A. TALOS+: a hybrid method for predicting protein backbone torsion angles from NMR chemical shifts. J. Biomol. NMR 44, 213223 (2009).

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Author information


  1. Center for Integrative Proteomics Research, Rutgers University, Piscataway, New Jersey, USA.

    • Shiou-Ru Tzeng &
    • Charalampos G Kalodimos
  2. Department of Chemistry & Chemical Biology, Rutgers University, Piscataway, New Jersey, USA.

    • Shiou-Ru Tzeng &
    • Charalampos G Kalodimos


S.-R.T. and C.G.K. conceived the project. S.-R.T. and C.G.K. designed the experiments. S.-R.T. performed all of the experiments. S.-R.T. and C.G.K. analyzed and interpreted the data and wrote the manuscript.

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