- Open Access
Stability of the core domain of p53: insights from computer simulations
© Madhumalar et al; licensee BioMed Central Ltd. 2008
- Published: 13 February 2008
The tumour suppressor protein p53 protein has a core domain that binds DNA and is the site for most oncogenic mutations. This domain is quite unstable compared to its homologs p63 and p73. Two key residues in the core domain of p53 (Tyr236, Thr253), have been mutated in-silico, to their equivalent residues in p63 (Phe238 and Ile255) and p73 (Phe238 and Ile255), with subsequent increase in stability of p53. Computational studies have been performed to examine the basis of instability in p53.
Molecular dynamics simulations suggest that mutations in p53 lead to increased conformational sampling of the phase space which stabilizes the system entropically. In contrast, reverse mutations, where p63 and p73 were mutated by replacing the Phe238 and Ile255 by Tyr and Thr respectively (as in p53), showed reduced conformational sampling although the change for p63 was much smaller than that for p73. Barriers to the rotation of sidechains containing aromatic rings at the core of the proteins were reduced several-fold when p53 was mutated; in contrast they increased when p73 was mutated and decreased by a small amount in p63. The rate of ring flipping of a Tyrosine residue at the boundary of two domains can be correlated with the change in stability, with implications for possible pathways of entry of agents that induce unfolding.
A double mutation at the core of the DNA binding domain of p53 leads to enhanced stability by increasing the softness of the protein. A change from a highly directional polar interaction of the core residues Tyr236 and Thr253 to a non-directional apolar interaction between Phe and Ile respectively may enable the system to adapt more easily and thus increase its robustness to structural perturbations, giving it increased stability. This leads to enhanced conformational sampling which in turn is associated with an increased "softness" of the protein core. However the system seems to become more rigid at the periphery. The success of this methodology in reproducing the experimental trends in the stability of p53 suggests that it has the potential to complement structural studies for rapidly estimating changes in stability upon mutations and could be an additional tool in the design of specific classes of proteins.
- Root Mean Square Deviation
- Core Domain
- Conformational Sampling
- Urea Molecule
- Core Residue
p53 is a tumour suppressor protein that regulates the cell cycle and maintains the genomic integrity of the cell by orchestrating the activity of a wide variety of genes involved in repair, apoptosis and senescence [1–3] It is a multidomain protein and functions as a tetramer. Two homologous genes which are shown to share structural and functional homology with p53 are p63 and p73, whose isoforms are known to regulate some of the same apoptotic pathways that are also regulated by p53 [4–6]. These three proteins posses a modular architecture, constituted by an N-terminal transactivation domain, a DNA binding domain (DBD) and a regulatory C-terminal oligomerization domain [7, 8]. The vast majority of tumour-derived p53 mutations map to the DBD . The DBD mutations fall into two categories: (a) mutations that are at the DNA binding region of p53 and hence disable the binding of p53 to DNA and (b) mutations that alter the structural integrity and stability of p53 itself. The latter can cause local and global structural perturbations leading to the unfolding of p53 and so any process that can reverse this is likely to be of therapeutic value. It is known that the destabilizing effects of the latter can be countered by other mutations, the so-called second site suppressor mutations, and also by small molecules [10–19]. This underscores the importance of understanding the basis of the stability of this region.
In an effort to understand the origins of instability of p53, Fersht & co-workers  noticed that the core is characterized by two polar residues, Tyr236 (located in strand S8) and Thr253 (located in strand S9) whose equivalents in p63/p73 are two apolar residues, Phe238 and Ile255. These two residues are two polar residues that are buried in an otherwise hydrophobic core of p53 DBD (Fig 1B). Hypothesizing that the presence of buried polar groups may incur a penalty that might destabilize p53, they replaced the two residues with the apolar equivalents from p63/p73 and found that the stability of mutant p53 had indeed increased (by ~1.6 kcal/mol). Analogous mutations that transform the core of p63 or p73 into that of p53 have not been reported in the literature.
In order to examine this problem computationally, we performed a set of studies that included building homology models of p63 and p73 (as there are no structures of these available in the public domain), and carried out molecular dynamics simulations and reaction path calculations to explore the basis of stability in p53, p63 and p73 and their mutants. We created double mutants of p53, replacing the Tyr236 and Thr253 by Phe and Ile respectively (here after referred as dp53) in the manner of Fersht & co-workers. In addition, we also mutated p63 and p73 by replacing their core residues Phe238 and Ile255 by the corresponding polar residues in p53 ie, Tyr and Thr (here after referred as dp63, dp73).
Principal component analysis
The quasi-harmonic frequencies and associated entropies (cal/mol-K) of the top two principal components during the MD simulations
The enthalpies (with the noncovalent components) and the entropies of the minimum energy structures (in kcal/mol).
Barriers to rotation of key Phe/Tyr residues (in kcal/mol)
In contrast, the barriers for the equivalent Phe in p73 increases almost two-fold in the mutant while in p63 there is actually a decrease by 30%. What is interesting is that the barriers to rotation of the Phe in dp53 are smaller than the corresponding barriers in wtp63 and wtp73. Examining the local environment around the sites of rotation, we find that Val272 in p53 is Ala in p63 and Gly in p73 (Fig 10B), ie the cavity gets progressively less densely packed between p53, p63 and p73 and there is a correlated rise in the barrier height. The other difference in the immediate neighbourhood of the rotating ring is Met133 in p53 which is Leu in both p63 and p73. This suggests that packing helps to ease barriers to the complex processes of ring flips.
In an attempt to establish a structural and energetic basis for the low stability of the DNA binding domain of the tumour suppressor protein p53, we have carried out computational studies of the wild type p53 and its homologues p63 and p73 and their double mutants. The mutations have been guided by the sequence of the homologs p63 and p73 which are known to be more stable. Experimentally, the p53 mutant has been found to have increased stability although the biological activity is yet to be determined . In an effort to correlate observations from simulations to experimentally observed stability issues in proteins, increasing deviation from the starting structures during the course of an MD simulation and, increased positional fluctuations have both been used as evidence for destabilizing influences on a protein's structure ). In our study however, we find that RMSD patterns do not correlate well with changing stabilities. Neither do the "free energies" of the structures that we have modelled. This could reflect both on the quality of our models and/or on the limitations of the force-fields . Despite the overall similarity structurally and energetically (as judged by the fact that the sequences are highly similar and that the net charge is +3, +2 and +3 for p53, p63 and p73 respectively), we have seen that the systems are not equally "stable". A double mutant constructed experimentally , enhances the stability of p53. Our simulations suggest that this arises due to a net increase in fluctuations of the proteins. This would lead to an increased conformational sampling of the phase space which in turn leads to entropic stabilization of the overall free energy of the system. We see this increase when p53 is transformed into dp53, and we know that experimentally the stability of dp53 is increased . We see a decrease when p73 is transformed into dp73 (the effect is not that pronounced for p63); there is no experimental data for this as yet. The pattern of changes seems to be largely determined by PC1 (and the associated entropic changes), which is the dominant mode of motion. Interestingly it is known that motions along the dominant mode are quite robust to sequence variations .
The residues that are under study here are located at the core of the protein suggesting that the increased stability in p53 (and decreased in p73) may arise from the removal (or introduction in p63 and p73) of buried polar groups. Several groups have been investigating the links between the nature of protein cores and overall stabilities. There are reports of increased rigidity associated with increased stability from MD simulations [18, 47, 48]. Lim and colleagues  report agreement between the MD simulations and the antibody-related observations on the nature of mutant structures; they also report agreement with the experimental observations of the change in DNA binding activity of some mutants. Our own observations suggest that enhanced sampling of phase space is linked to increased stability. This issue is as yet unresolved. The effects of core residue modifications upon protein stability remain unresolved. Some studies point out that burying polar groups increases the packing densities of proteins which in turn have a favourable effect on protein stability . Other work has also concluded that burying polar groups leads to increased entropic stabilizations . In contrast, there is other evidence that burying polar group can also destabilize proteins [23, 52, 53]. The observation by Lane & colleagues  that mutations of several surface residues of the DNA binding domain of p53 can have remarkable effects on its stability further highlights the complex nature of the stability issue. The picture is made more complex by observations that certain mutations at the cores of proteins lead to rearrangements that cause partial collapse to offset the size changes and minimize free energies, while in some cases, rearrangements expose polar groups that then attract solvent water from the bulk [55, 56]. Matthews & colleagues  suggest that the landscape underlying such changes is characterized by a complex interaction between fluid like sidechain motions and more rigid peptide backbone motions. Clearly while there is some correlation between core rigidity, packing and overall stability, the issue seems to be far more complex and requires further detailed investigations .
Proteins are complex systems and while the nature of core residues will certainly dominate the overall rigidity, stability is a global property and there will be several other factors that contribute, as has been highlighted for the DNA binding domain of p53 by Lane & colleagues . Our own simulations do point out certain features that seem to be consistent with experimental observations indirectly: the fluctuations of the helical segment that is part of Loop L2 (in both the C-α fluctuations of the original trajectory and in the trajectory along PC1, see Figures 6, 7) only for p53 and p73. The importance of Helix H1 in both p53 and p73 in DNA binding has been reported . If we look at Figure 1, we notice that this region is the one that is involved in the protein-protein dimeric interface thereby hinting at the importance perhaps of dimerization and cooperativity in DNA binding .
In an attempt to understand the root of stability changes in a somewhat different manner, we examined in detail the experiments that have been used to probe stability. These experiments are related to the amount of urea needed to unfold a protein. This requires an understanding of the dynamics of parts of the protein which will form the pathways of entry of urea to the core of the protein . While an exhaustive understanding of the various pathways is not available, we begin the process by examining the mobilities at various locations on the protein surface by computing the energetic barriers that characterize ring flips; such flips cause sufficient local deformation to enable openings for solvent molecules to enter the protein [; see http://www.ysbl.york.ac.uk/~chandra/reaction1.html]. While it is hard to estimate the rates of the processes associated with these ring flips as we have no entropic estimates of the transition states [except in certain cases – see for example ], it is clear from our studies here that (a) the rate at the core increases with increasing stability of the protein; (b) a range of time scales characterize the dynamics of the various parts of the protein; (c) the motions at the surface are very local and uncoupled from each other .
The residues that differ in the neighbourhood of the Tyr rings are: (a) for Tyr126: Pro128 in p53 and p73 is replaced by Thr128 in p63; Asn36 in p53 is replaced by Lys131 in p63 and p73; (b) for Tyr163: Glu171 in p53 and p63 is replaced by Asp171; (c) for Tyr205: Val203 in p53 is replaced by Ala205 in p63 and Val205 in p73; (d) there is a complex interplay of varying timescale motions across the protein surface; while the double mutant of p53 witnesses a dramatic reduction in the rate of flipping of the core aromatic sidechain, suggestive of increasing softness of the protein, the effects on residues that are towards the periphery (Tyr126, Tyr163, Tyr205 and Tyr225) in p53 are one of increasing the barriers to transitions – suggestive of increase in local packing or decreasing "softness". It is clear that small changes in the immediate environments of the rotating rings can affect the local packing in a manner that is reflected in the wide range of barrier heights. This does suggest that despite the fact that the ring flip itself is largely governed by local effects, somehow there are more global influences of the mutations that result in some "tighter" peripheral spots. This may form the basis of the need for larger amounts of urea needed to penetrate through the protein leading to the observed increase in stability. Additionally, two of the rings that we have studied, Tyr126 and Tyr163 are located in the vicinity of the DNA binding and the dimerization surfaces. Analyses of the ring flips and the associated movements clearly show motions that are likely to influence both these interactions (details to be presented elsewhere). It is clear that plasticity of the core residues is communicated to the dynamics of residues at the periphery. These will include those that mediate binding to DNA. How exactly this happens remains to be uncovered.
In conclusion, we find that computational estimates of stability of proteins through their minimized energies partially reproduce experimental trends and may thus be a reasonable metric. Differences in root mean squared deviations over the course of MD simulations do provide some hints at changes in stability, as observed by Pan et al. ; however in our studies, this metric is not entirely discriminating. In our simulations, the enhanced sampling of phase space, dominated by motion along PC1, seems to be responsible for increasing stability. In addition, we have, for the first time to the best of our knowledge, applied methods of activated dynamics to understand protein stability as defined by urea induced unfolding. The mobility at the core of the protein is increased in systems of larger mobility as evidenced from higher rates of ring flips of aromatic residues; this suggests that larger conformational sampling increases the softness of the protein core, thereby making it more robust to structural perturbations. This seems to arise from a change of directed polar interactions to nondirectional apolar interactions. We find that the changes in mobility in surface regions of the protein and access to urea molecules correlates well with changing stabilities in p53 and perhaps in p73. While we do not yet have a measure of transforming these results into quantitative differences between experimental stabilities, we are applying this method to a range of other p53 mutants and other proteins to examine its validity and robustness. Initial results suggest that the method seems to hold the potential to rapidly estimate, at least qualitatively, the effects on the stability of proteins (at least in cases where there are ring-bearing residues at the periphery). If more generally valid, this method may well reduce the number of experiments that need to be carried out to examine the effects of mutagenesis on the stabilities, at least of a class of proteins, and would be an additional tool in protein design strategies.
A concluding point is about the two different force fields used in our analysis. We started the study using AMBER. However as pointed out, at the end of the MD study, we decided to expand the investigations by using methods of reaction paths (TRAVel) in order to explore the origins of stability as measured by urea-induced unfolding. These algorithms currently are only available in CHARMM. However the general differences amongst different force fields is quite small, as has been pointed out in a recent study  leading us to conclude that had we conducted our simulations using CHARMM, the overall conclusions would have been similar to those that we have reported using AMBER.
The initial structure of monomeric p53 core domain was taken from the crystal structure of p53 bound to DNA (RCSB entry 1TUP resolved at 2.2 Å; ); the structures of p63 and p73 were modeled based on the homology with the p53 monomer (sequence similarity to p63 and p73 is 77% and 75% respectively while identity is ~60%). An alignment of the known structure against the sequences was generated by CLUSTALW , followed by manual manipulation using QUANTA . The program MODELLER  was used to generate 20 initial homology models of the p63 and p73 DBD based upon the resulting sequence-structure alignment. The model with the lowest objective function was chosen as the representative model for further study. The double mutants of p53 (Phe236 and Ile253) (referred as dp53), p63 (Tyr238 and Thr255) (referred as dp63), p73 (Phe238 and Ile255) (referred as dp73) were made using QUANTA.
MD simulations were carried out using the AMBER  package. In all the four systems, the Zn ion was coordinated to three Cys residues and one His residue and the parameters for this pseudobond were taken from earlier studies [65, 66]. Each system was solvated with TIP3P water box with the minimum distance of 10 Å to any protein atom. The positive charges in the system were balanced by adding chloride ions. The total number of atoms were 32617(p53), 32645(p63), 31491 (p73), 32621(dp53), 32644(dp63) and 31490(dp73).Parm99 force field was used for intermolecular interactions. Particle Mesh Ewald method (PME)  was used for treating the long range electrostatics. All bonds involving hydrogen were constrained by SHAKE. Time step of 2fs was used for dynamics integration. Before starting the dynamics, the whole system was minimized for 2000 steps, to remove any unfavourable interactions between the protein and solvent. The system was heated to 300K within 75 ps, under NPT conditions. Each system was simulated for 10ns at constant temperature (300K) and pressure (1 atm)  and the structures were stored every 1ps.
Reaction path calculations were carried out using the Conjugate Peak Refinement  algorithm as implemented in the module TRAVel in CHARMM ; this method is very robust and is currently only available in the program CHARMM. The protocol followed is the same as outlined before . Briefly this consists of minimizing each system under a radius-dependant dielectric continuum model with an attenuation factor of 2 and with the non-bonded interactions shifted to zero between 8 and 12 Å. Minimizations were carried out until the change in gradient of potential energy was smaller than 10-5 kcal mol-1 Å -1. Vibrational entropies were computed using the VIBRan module of CHARMM. This required the diagonalization of the full Hessian of the system . The minimum energy state is then defined as the reactant state and the product state is created by simply interchanging the positions of the ring carbon atoms of the benzene ring of Phe/Tyr as the ring flip leads to a symmetric state. The minimum energy path between the reactant and the product state is then calculated using the TRAVel module which yields the saddle point(s) or the transition state(s), and the energy of the highest transition state is taken to tbe the rate limiting barrier height for that particular ring flip process.
Dr Ross Walker, San Diego Super Computer centre, UCSD, for many useful suggestions in creating Zinc parameters. We thank Prof Lennart Nilsson for useful discussions on Zn parameters. The Bioinformatics Institute is an A*STAR (Agency for Science, Technology & Research) institute. All figures were drawn using Pymol .
This article has been published as part of BMC Bioinformatics Volume 9 Supplement 1, 2008: Asia Pacific Bioinformatics Network (APBioNet) Sixth International Conference on Bioinformatics (InCoB2007). The full contents of the supplement are available online at http://www.biomedcentral.com/1471-2105/9?issue=S1.
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