Research ArticleMicrosecond molecular dynamics simulations reveal the allosteric regulatory mechanism of p53 R249S mutation in p53-associated liver cancer
Introduction
As a transcription factor, the tumor suppressor p53 plays a critical role in many cellular processes, including DNA repair and apoptosis and cell cycle arrest (Hafner et al., 2019; Zuckerman et al., 2009). Abnormality of the p53 activity induced by mutations in p53 has related to ∼50% of human cancers (Thoenen et al., 2019). Indeed, these mutations are mainly located at the DNA binding core domain of p53 (Tang et al., 2019). Thus, targeting p53 mutants has been the subject of drug discovery efforts for cancer therapies. For example, one promising strategy is the design of small molecules bound to the specific p53 mutants, aiming to the reactivation of p53 mutants (Metri et al., 2013; Raghavan et al., 2019; Sirous et al., 2019).
The full length of p53 consists of 393 residues, including the regulatory domains (the N- and C-terminal domains) and the core DNA binding domain (DBD) (Yan and Chen, 2010). The DBD comprised of ∼200 residues is responsible for DNA binding. In the crystal structure of p53-DNA complex (Fig. 1A), the p53 DBD is largely made by 11 β-strands, together with 3 α-helices. Zinc ion is absolutely required for p53 to execute the DNA binding activity. In the structure, zinc ion is in a tetrahedral coordinated mode with residues Cys176 and His179 from the H3 helix and residues Cys238 and Cys242 from the turn between strands 4 and 5 (S4-S5 turn). These coordinated interactions stabilize the p53 structure, enabling it to engage with DNA. In the p53 DBD-DNA binding interface, two major interaction regions are observed (Fig. 1B). The first region is the loop-sheet-helix motif consisting of the S1-S2 turn, S10-H3 turn, and the H3 helix, which interacts with the major groove of DNA. On the other hand, the second region contains the S4-S5 turn and the zinc ion binding motif, which interacts with the minor groove of DNA. Among the most frequent mutations of p53 DBD in human cancers, the R249S mutation located at the S4-S5 turn causes ∼90% of TP53 mutations in human hepatocellular carcinoma (HCC) (Gouas et al., 2010). This mutation is not at the p53 DBD-DNA binding interface. As a result, how the R249S mutation causes the structural changes of p53 DBD that lead to disrupt the binding of p53 mutant to DNA has not clearly understood.
Molecular dynamics (MD) simulations, as a viable complement to experimental methods (Koulgi et al., 2013; Li et al., 2019a, 2019b; Pradhan et al., 2019; Rungsung et al., 2018; Wassman et al., 2013), can provide local structural and dynamical information of wild-type (WT) and mutated proteins, particularly those cancer-associated proteins such as Ras (Lu et al., 2019b), EGFR (X. Lu et al., 2018a; Patel et al., 2018), AKT (Lu et al., 2015), PI3K (Ni et al., 2018; M. Zhang et al., 2019a), and BCR-ABL (H. Zhang et al., 2019a,2019b). In the case of p53, MD simulations have been used by several independent groups to investigate the dynamical properties of WT p53 DBD (Lu et al., 2007; Lukman et al., 2013) and some of its mutants (Sundar et al., 2019). Indeed, extensive MD simulations enable the sampling of large-scale conformational changes of proteins and capture multiple conformations that cannot be captured by crystal structures, because crystal structures represent static snapshots of proteins―averaged temporally and spatially over numerous subtle conformational differences (Lu et al., 2018a,2018b; Shi, 2014; Zheng et al., 2018).
In the present study, microsecond-scale MD simulations of p53 DBD in the WT and R249S mutated states in the absence of DNA binding were performed in explicit water environment to explore the effect of the R249S mutation on the structure and dynamics of p53 DBD. We did not simulate the p53 DBD-DNA complex, because the inclusion of DNA in the mutated state would restrain the conformational changes of p53, particularly in the DNA binding interface. We aim to capture the representative conformation for the R249S p53 mutant from the MD simulations, and subsequently perform molecular modeling studies between the representative conformation of the WT/mutated p53 and DNA to validate whether the mutated p53 can interact with DNA. The obtained results can help to decipher the allosteric regulatory mechanism by which the R249S mutation of p53 DBD affects the p53 DBD-DNA interactions.
Section snippets
Simulated system construction
The crystal structure used for MD simulations was downloaded from Protein Data Bank (PDB code: 1TSR) (Cho et al., 1994). The chain B of p53 DBD (residues Ser96-Leu289) was chosen to simulate the WT system, while the R249S mutant was constructed based on this structure using the Discovery Studio Client through the Mutate action. Zinc ion was treated using the cationic dummy atom (CADA) approach proposed by Pang and coworkers (Tang et al., 2007). In this approach, three coordinated Cys residues
R249S mutation has a minor effect on the global conformation of p53 DBD
The dynamic effects of the R249S mutation on the p53 DBD were investigated by large-scale MD simulations. To check whether the R249S mutation has a significant effect on the overall conformational dynamics of p53 DBD, the root-mean-square deviation (RMSD) of the Cα atoms of the WT and R249S mutant systems was monitored as a function of simulated time, which was calculated in relation to the initial crystal structure of p53 DBD as a reference. As shown in Fig. 2A, after 400 ns simulations, the
Conclusions
In the present study, large-scale MD simulations were performed to examine the effect of the R249S mutation on the conformational dynamics of p53 DBD. The simulations revealed that the R249S mutation did not cause global conformational changes of p53 DBD, but effected the local regions at the mutation site and the DNA binding interface. These are consistent with the experimental NMR data. Further PCA results revealed that the R249S mutant changed the conformational ensemble of p53 DBD compared
Author contributions
Tonggang Liu and Liguo Zhang conceived and designed the experiments; Xianxian Liu and Wenchao Tian performed the experiments; XianXian Liu, Wenchao, Jinying Cheng and Dongmei Li analyzed the data; Tonggang Liu and Liguo Zhang contributed reagents/materials/analysis tools: All authors wrote the paper.
Declaration of Competing Interest
The authors have no conflicts of interest.
Acknowledgements
The study was supported by the Science and Technology Development Plan for Medical and Health of Shandong Province of China (2017WS682).
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