Conformational Entropy as a Determinant of the Thermodynamic

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Conformational Entropy as a Determinant of the Thermodynamic Stability of the p53 Core Domain Aritra Bej,† Juhi A. Rasquinha,† and Sujoy Mukherjee* Structural Biology and Bioinformatics Division, CSIR-Indian Institute of Chemical Biology, Kolkata 700032, West Bengal, India

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S Supporting Information *

ABSTRACT: Mutations in the core domain of tumor suppressor protein p53 have been associated with ∼50% of the occurrences of human cancers. A majority of these mutations inactivate p53 function by destabilizing its native structure. Although studies have shown p53’s function can be restored by stabilizing the mutants to their wild-type conformation with immense therapeutic potential, its applicability has been restricted because of our limited understanding of the precise nature of destabilization arising from changes in the mutant p53’s structure and dynamics. Here, using nuclear magnetic resonance (NMR) spectroscopy and molecular dynamics simulations, we have probed the conformational flexibility in three of the most widespread and clinically important “hot spot” mutants of the p53 core domain. Our results show that NMR order parameter-derived conformational entropy is linearly correlated with the change in free energy of urea-mediated denaturation, the latter being a well-established reporter of stability in p53 core domain mutants. Using a linear regression function, we show that the three parameters of equilibrium denaturation experi2O ments, i.e., the free energy of denaturation (ΔGH D−N), the slope of the transition (m), and the urea concentration at 50% denaturation ([urea]50%), can be used to predict the conformational entropy in p53 core domain mutants, thereby demonstrating a method for using these parameters as predictors of a protein’s conformational entropy, which has been known to shape the functional properties of proteins.

Figure 1. Cancer-associated mutations of p53. Histogram plot of mutation frequency as a function of protein sequence.7 The domains of the p53 protein are shown on the top, and the most frequently occurring “hot spot” mutations are labeled.

of the thermodynamics of denaturation of mutant p53 core domains using urea-mediated equilibrium denaturation experiments reveal that they were characterized by three key 2O parameters, namely, the free energy of denaturation (ΔGH D−N), the slope of the transition (m), and the urea concentration at 50% denaturation ([urea]50%).3,4 However, a link between p53 core domain’s thermodynamic properties (e.g., entropy) and experimentally obtained parameters of instability has not been established. Such a correlation could be important because changes in the conformational entropy (Sconf) of proteins have been found to contribute to changes in their functional properties.8,9 While the extent of instability has been characterized for p53 core domain proteins,3,4 they have not been correlated with experimentally observed changes in conformational entropy. Here, we have probed the backbone dynamics of three “hot spot” structural mutants (G245S, R249S, and R282W) and derived their Sconf values to understand whether any correlation exists between the conformational entropy and thermodynamic instability of the p53 core domain. The {15N,1H} HSQC spectra for structural mutants are shown in Figures S1−S3. Backbone dynamics for three of the four “hot spot” structural mutants were obtained by measuring 15 N relaxation rates (R1 and R2) and steady-state {1H}−15N NOEs (Tables S1−S3). The fourth mutant, R175H, could not be stabilized for nuclear magnetic resonance (NMR) experiments. These results (Table 1) provide qualitative evaluation of motions on the picosecond to nanosecond time scale.10 While the mean (±standard deviation) R1 and R2 values for

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ancers are predominantly associated with the inactivation of tumor suppressor protein p53 by mutations.1 Most of these mutations occur in its DNA-binding domain (Figure 1), reflecting its crucial role in p53’s function.2 Among these mutations, six residues in particular have been identified as mutational “hot spots” that are classified into two groups, namely, DNA-contact (R248Q and R273H) and structural (R175H, G245S, R249S, and R282W) mutants.1 Functional inactivation of structural mutants arises because of the destabilization of the native structure, leading to the formation of a conformational state that has poor DNA-binding ability and is energetically less stable than its wild-type counterpart.3,4 While structures are available for many p53 core domain mutants,5,6 they do not sufficiently explain the changes in the functional properties of mutant p53 and the role of protein dynamics may be necessary to explain them. Previous studies © XXXX American Chemical Society

Received: July 10, 2018 Revised: October 23, 2018 Published: October 26, 2018 A

DOI: 10.1021/acs.biochem.8b00740 Biochemistry XXXX, XXX, XXX−XXX

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Biochemistry Table 1. Summary of Relaxation Rates and Modelfree14 Parameters for p53 Core Domains R1 (s−1)

p53 variant Wild type G245S R249S R282W

a

1.18 0.77 0.83 0.86

± ± ± ±

0.32 0.23 0.23 0.24

R2 (s−1) 24.1 23.7 21.5 22.7

± ± ± ±

τc (ns)

NOE

6.6 6.9 6.7 8.2

0.68 0.65 0.67 0.65

± ± ± ±

0.27 0.30 0.37 0.30

13.5 16.9 15.6 15.1

± ± ± ±

0.2 0.1 0.1 0.2

S2 0.88 0.87 0.86 0.85

± ± ± ±

0.10 0.09 0.11 0.12

a

From a previous work.11

Figure 2. Backbone flexibility of p53 core domain structural mutants. Plot of simulated S2 (from NMR, red) and root-mean-square fluctuation (RMSF) (from molecular dynamics simulations, blue) as a function of protein sequence for (A) G245S, (B) R249S, and (C) R282W mutants. Contiguous residues exhibiting elevated levels of motion are colored gray. Values of S2 and RMSF are mapped on the wild-type p53 structure (Protein Data Bank entry 3KMD12) after the insertion of mutations using PyMol.13 Most rigid and dynamic residues are colored blue and red, respectively, and those without an S2 value are colored gray. Error bars for the RMSF plot denote the standard deviation from a triplicate set of simulations.

Table 2. Summary of the Thermodynamic Parameters for p53 Core Domains p53 variant Wild type G245S R249S R282W

S̅ confa (cal mol−1 K−1) −3.15 −3.06 −2.88 −2.86

± ± ± ±

0.14 0.14 0.15 0.18

d

−1 2O b ΔGH D−N (kcal mol )

10.16 8.94 8.23 6.85

± ± ± ±

mb (kcal mol−1) −3.26 −3.29 −2.91 −3.14

0.18 0.15 0.14 0.15

± ± ± ±

0.11 0.09 0.07 0.39

[urea]50% (M)b 3.25 2.86 2.63 2.19

± ± ± ±

0.01 0.01 0.01 0.03

S̅ conf·NH+SC (cal mol−1 K−1)c −0.90 −0.94 −0.78 −0.75

± ± ± ±

0.13 0.11 0.08 0.19

a

From NMR. bFrom a previous study.4 cFrom MD simulations. dFrom a previous study.11

versus that of R282W at 18 °C, it has been previously noted that at a physiological temperature of 37 °C, it is R282W that is predicted to have a globally denatured state whereas G245S is likely to be weakly destabilized.4 The S2 values of mutants averaged over all residues for which data were available (Table 1) were nearly similar to that of the wild type,11 with significant perturbations localized to four highly mobile and solvent-exposed sites (Figure 2) comprising residues H115− N131, Q165−A189, E221−T230, and G244−G245 of the wild-type sequence. However, the extent of motion within these regions (Tables S4−S6) varied, not only between the mutants and the wild type but also among the mutants. We performed triplicate sets of microsecond-scale, all-atom molecular dynamics (MD) simulations on the wild type and the three structural mutants to complement the NMR studies. The similarity of the residue specific root-mean-square

G245S and R249S, respectively, showed a subtle drop compared to those of other mutants, the R1 values in all structural mutants were significantly lower than the wild-type value.11 This may arise from a change in the global conformation between the structural mutants and the wildtype conformer, matching prior observations with a DNAcontact mutant R273H.11 Subsequently, fitting relaxation data (Tables S1−S3) to various models14 provided the rotational correlation time (τc) and residue specific generalized order parameter (S2), the latter being a quantitative reporter of backbone flexibility. For structural mutants (Table 1), τc values were relatively higher than those of their wild-type counterpart, suggesting that the core domain of the mutants undergo rotational diffusion that is slower than that of the wild type, possibly because of the conformational enlargement upon mutation. Although G245S exhibits a larger increase in τc B

DOI: 10.1021/acs.biochem.8b00740 Biochemistry XXXX, XXX, XXX−XXX

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Biochemistry fluctuation (RMSF) with the NMR-derived S2 confirms the location of the conformational flexibility across these proteins (Figure 2, colored gray). Measurement of additional parameters that report on structural destabilization, including the backbone root-mean-square deviation (RMSD), solvent accessible surface area (SASA), and changes in hydrogen bond network revealed greater perturbation in structural mutants than in the wild type (Table S7), suggesting that the mutants adopt an unstable conformation. Subsequently, we calculated the conformational entropy (Sconf) from NMR-derived S2,8,15 because entropic changes could play important roles in modulating the functional properties of mutant p53. The mean Sconf (S̅ conf) (Table 2), averaged over all residues (Table S8), could be used as an indicator of the thermodynamic stability of the p53 core domain, as has been observed for other proteins.16−18 Among the structural mutants studied, S̅ conf was maximal in R282W, which is a strongly destabilizing mutant with a globally denatured structure, whereas the weakly destabilizing mutant, G245S, showed a minimal S̅ conf.4 Interestingly, the S̅ conf of R249S (−2.88 ± 0.15 cal mol−1 K−1) was similar to that of R282W and significantly higher than that of G245S, which appears to have a larger structural fold based on a high τc (Table 1). On the contrary, it was previously observed19 that in addition to being a weakly destabilizing mutant, R249S is also structurally more perturbed than G245S. This observation suggests that there may be an inverse correlation of Sconf with structural stability, the latter of which can be characterized using the free energy of 2O denaturation (ΔGH D−N) obtained from urea-mediated denaturation experiments. 4 Hence, we plotted S̅ c onf with the 2O 2 corresponding ΔGH D−N, which showed a linear correlation [R = 0.85 (Figure 3A)]. This linearity indicates a possible 2O contribution of S̅ conf to the ΔGH D−N of the p53 core domain. In H2O addition to ΔGD−N, urea-mediated denaturation experiments are also parametrized by the slope (m) and urea concentration at 50% denaturation ([urea]50%). To probe whether a relationship exists between S̅ conf and the urea denaturation parameters (Table 2), we performed multiple regression using H2O , m, and [urea]50%. The result all the three variables, i.e., ΔGD−N of the regression analysis indicates that S̅ conf can be expressed as a linear function of experimentally derived parameters of 2O ΔGH D−N, m, and [urea]50% with an excellent correlation between the predicted and experimental S̅ conf [R2 of ∼0.99 (Figure 3B, solid circles)]. While we have used the average conformational entropy (S̅ conf), the correlation was notably the same when the total conformational entropy of the protein (obtained by the summation of residue specific Sconf, denoted ∑Sconf) was used instead of S̅ conf (Table S8 and Figure S4). Previously, we found that for DNA-contact “hot spot” mutants, R273H but not R248Q showed an enlarged structure indicative of structural perturbation.11 To further establish the robustness of the regression function, the equation derived for the wild type and structural mutants was applied to predict S̅ conf for two DNAcontact mutants, namely, R248Q and R273H (Figure 3B, empty circles). While R248Q was found to be an outlier, the predicted S̅ conf was closer to the experimental value for R273H. Finally, to ascertain whether the observed correlation was specific to structural mutants, we repeated the regression analysis with all of the five available “hot spot” mutants, including the two DNA-contact mutants. The resulting correlation was significantly poorer [R2 ∼ 0.4 (Figure S5)], suggesting that the observed correlation was specific to the structural mutants. Although these results indicate excellent

Figure 3. Correlation between entropy and stability. (A) Plot of H2O 4 . (B) Correlation between predicted NMR-derived S̅ conf with ΔGD−N and NMR-derived S̅ conf obtained using linear regression analysis. S̅ conf values of DNA-contact mutants (R248Q and R273H) were predicted using the same regression function and are depicted as empty circles. 2O 4 (C) Plot of MD simulation-derived S̅ conf·NH+SC with ΔGH D−N. (D) Correlation between predicted and MD-derived S̅ conf obtained using linear regression analysis. Values of R2 for panels A−D are 0.85, ∼0.99, 0.66, and 1, respectively.

correlation between the stability and conformational entropy of p53 core domain structural mutants, using only backbone entropy as an estimator of a protein’s entropy is inadequate20,21 because a significant part of the net entropy originates from side-chain methyl groups.22,23 Hence, using MD data, we predicted backbone N−H (SNH2) and methyl (SMe2) order parameters (Table S9), from which entropies for the backbone and side chains were calculated (Figure S6); for the latter, the coupling between methyl and non-methyl groupbearing side chains was used to extract the total side-chain entropy.22−24 As with NMR-derived S̅ conf, the plot of the H2O average entropy [i.e., S̅ conf·NH+SC (Table 2)] with ΔGD−N 2 showed a good linear correlation [R = 0.66 (Figure 3C)] along with the prediction of S̅ conf·NH+SC as a function of experimentally derived parameters of denaturation, with an excellent correlation [R2 ∼ 1 (Figure 3D)]. While studies have shown that stabilizing mutant p53 to its wild-type conformation can help restore wild-type activity in cancer cells,25,26 its application has been limited because of the difficulty in accurately characterizing the extent of their structural disorder. Here, we have used backbone dynamics of p53 core domains to determine their Sconf, which is known to provide a measure of structural perturbation and regulate functions in proteins.16−18 In enzymes, entropy-tuning mutations have also been shown to allosterically modulate their activity.27,28 Our study shows that a linear correlation can be established between the entropy and stability of p53 core domains, an observation that has not been previously reported. This opens the possibility of using parameters of denaturation experiments for predicting the extent of Sconf associated with instability in the p53 core domain, not only in structural C

DOI: 10.1021/acs.biochem.8b00740 Biochemistry XXXX, XXX, XXX−XXX

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Biochemistry

(6) Joerger, A. C., Ang, H. C., and Fersht, A. R. (2006) Structural basis for understanding oncogenic p53 mutations and designing rescue drugs. Proc. Natl. Acad. Sci. U. S. A. 103, 15056−15061. (7) Olivier, M., Eeles, R., Hollstein, M., Khan, M. A., Harris, C. C., and Hainaut, P. (2002) The IARC TP53 database: new online mutation analysis and recommendations to users. Hum. Mutat. 19, 607−614. (8) Yang, D. W., and Kay, L. E. (1996) Contributions to conformational entropy arising from bond vector fluctuations measured from NMR-derived order parameters: Application to protein folding. J. Mol. Biol. 263, 369−382. (9) Frederick, K. K., Marlow, M. S., Valentine, K. G., and Wand, A. J. (2007) Conformational entropy in molecular recognition by proteins. Nature 448, 325−329. (10) Farrow, N. A., Muhandiram, R., Singer, A. U., Pascal, S. M., Kay, C. M., Gish, G., Shoelson, S. E., Pawson, T., Forman-Kay, J. D., and Kay, L. E. (1994) Backbone dynamics of a free and a phosphopeptide-complexed Src homology 2 domain studied by 15N NMR relaxation. Biochemistry 33, 5984−6003. (11) Rasquinha, J. A., Bej, A., Dutta, S., and Mukherjee, S. (2017) Intrinsic Differences in Backbone Dynamics between Wild Type and DNA-Contact Mutants of the p53 DNA Binding Domain Revealed by Nuclear Magnetic Resonance Spectroscopy. Biochemistry 56, 4962− 4971. (12) Cho, Y., Gorina, S., Jeffrey, P. D., and Pavletich, N. P. (1994) Crystal structure of a p53 tumor suppressor-DNA complex: understanding tumorigenic mutations. Science 265, 346−355. (13) DeLano, W. L. (2002) PyMOL Molecular Graphics System, DeLano Scientific, San Carlos, CA. (14) Mandel, A. M., Akke, M., and Palmer, A. G., III (1995) Backbone dynamics of Escherichia coli ribonuclease HI: Correlations with structure and function in an active enzyme. J. Mol. Biol. 246, 144−163. (15) Li, Z. G., Raychaudhuri, S., and Wand, A. J. (1996) Insights into the local residual entropy of proteins provided by NMR relaxation. Protein Sci. 5, 2647−2650. (16) Karplus, M., Ichiye, T., and Pettitt, B. M. (1987) Configurational entropy of native proteins. Biophys. J. 52, 1083−1085. (17) Matthews, B. W., Nicholson, H., and Becktel, W. J. (1987) Enhanced protein thermostability from site-directed mutations that decrease the entropy of unfolding. Proc. Natl. Acad. Sci. U. S. A. 84, 6663−6667. (18) Baxa, M. C., Haddadian, E. J., Jumper, J. M., Freed, K. F., and Sosnick, T. R. (2014) Loss of conformational entropy in protein folding calculated using realistic ensembles and its implications for NMR-based calculations. Proc. Natl. Acad. Sci. U. S. A. 111, 15396− 15401. (19) Wong, K. B., DeDecker, B. S., Freund, S. M., Proctor, M. R., Bycroft, M., and Fersht, A. R. (1999) Hot-spot mutants of p53 core domain evince characteristic local structural changes. Proc. Natl. Acad. Sci. U. S. A. 96, 8438−8442. (20) Wand, A. J., and Sharp, K. A. (2018) Measuring Entropy in Molecular Recognition by Proteins. Annu. Rev. Biophys. 47, 41−61. (21) Igumenova, T. I., Frederick, K. K., and Wand, A. J. (2006) Characterization of the fast dynamics of protein amino acid side chains using NMR relaxation in solution. Chem. Rev. 106, 1672−1699. (22) Kasinath, V., Sharp, K. A., and Wand, A. J. (2013) Microscopic insights into the NMR relaxation-based protein conformational entropy meter. J. Am. Chem. Soc. 135, 15092−15100. (23) Sharp, K. A., O’Brien, E., Kasinath, V., and Wand, A. J. (2015) On the relationship between NMR-derived amide order parameters and protein backbone entropy changes. Proteins: Struct., Funct., Genet. 83, 922−930. (24) Chatfield, D. C., Szabo, A., and Brooks, B. R. (1998) Molecular Dynamics of Staphylococcal Nuclease: Comparison of Simulation with 15N and 13C NMR Relaxation Data. J. Am. Chem. Soc. 120, 5301−5311. (25) Friedler, A., DeDecker, B. S., Freund, S. M., Blair, C., Rudiger, S., and Fersht, A. R. (2004) Structural distortion of p53 by the

mutants but also in DNA-contact mutants mimicking characteristics of structural mutants. The results are important because changes in Sconf would result in changes in their conformational degrees of freedom, allowing the mutants to explore newer conformational states and functions that are not possible for the wild type. Consequently, entropic changes associated with mutant p53 would facilitate decoding the origin of new functions in p53’s gain-of-function mutants.

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.biochem.8b00740. Details of sample preparation methods, NMR, MD simulations and data analysis, HSQC spectra, correlation between experimental and predicted entropies, tables of NMR spin relaxation rates, Modelf ree analysis, and summary of MD simulations, conformational entropy, and order parameters (PDF)

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected] or [email protected]. Phone: +91 (33) 2499 5715. ORCID

Sujoy Mukherjee: 0000-0001-9783-7664 Author Contributions †

A.B. and J.A.R. contributed equally to this work.

Funding

Funding from DST (Ramanujan fellowship to S.M. and INSPIRE fellowship to A.B.), UGC (fellowship to J.A.R.), and CSIR is acknowledged. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors thank Prof. Siddhartha Roy for stimulating discussion, Prof. Arthur G. Palmer and Prof. J. Patrick Loria for access to NMR data analysis programs, Prof. A. Joshua Wand for helpful suggestions, Shraboni Dutta for help in protein purification, the high-field NMR facility at the Bose Institute for access to the 700 MHz NMR spectrometer, and CSIR-4Pi for computational time.

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REFERENCES

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Biochemistry mutation R249S and its rescue by a designed peptide: implications for ″mutant conformation″. J. Mol. Biol. 336, 187−196. (26) Tal, P., Eizenberger, S., Cohen, E., Goldfinger, N., Pietrokovski, S., Oren, M., and Rotter, V. (2016) Cancer therapeutic approach based on conformational stabilization of mutant p53 protein by small peptides. Oncotarget 7, 11817−11837. (27) Tzeng, S. R., and Kalodimos, C. G. (2012) Protein activity regulation by conformational entropy. Nature 488, 236−240. (28) Saavedra, H. G., Wrabl, J. O., Anderson, J. A., Li, J., and Hilser, V. J. (2018) Dynamic allostery can drive cold adaptation in enzymes. Nature 558, 324−327.

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DOI: 10.1021/acs.biochem.8b00740 Biochemistry XXXX, XXX, XXX−XXX