A spatiotemporal characterization of the effect of p53 phosphorylation on its interaction with MDM2

Sim, Adelene Y. L.; Lane, David P.; Verma, Chandra; Caves, Leo S. D.

doi:10.4161/15384101.2014.989043

Cited by 11 publications

(6 citation statements)

References 64 publications

(100 reference statements)

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“…Each basin of attraction corresponds to an ensemble of molecular configurations of MDM2-peptide interactions termed the “encounter complex”, representing an essential state distinct from the formation of the nondiffusive final bound complex. Previously, we found that identification of the locations of the basins of attraction, characterization of the molecular configurations of the encounter complexes and computation of the corresponding residence times could provide detailed explanations for the mechanisms of interactions of MDM2 with p53, phosphorylated-p53, and the geometrical isomers of a small molecule inhibitor of the p53-MDM2 interaction, Nutlin. ,, Here, we use this approach to explore the interaction dynamics variations underlying the affinity of MDM2 for the C-terminal variants of the QETFSDLWKLLX p53-based peptide and the MPRFMDYWEGLX phage-derived 12/1 peptide (X = Ser/Ala/Asn/Pro) and relate these to the observed binding affinities.…”

Section: Resultsmentioning

confidence: 99%

Recognition Dynamics of p53 and MDM2: Implications for Peptide Design

2016

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Peptides that inhibit MDM2 and attenuate MDM2-p53 interactions, thus activating p53, are currently being pursued as anticancer drug leads for tumors harboring wild type p53. The thermodynamic determinants of peptide-MDM2 interactions have been extensively studied. However, a detailed understanding of the dynamics that underlie these interactions is largely missing. In this study, we explore the kinetics of the binding of a set of peptides using Brownian dynamics simulations. We systematically investigate the effect of peptide C-terminal substitutions (Ser, Ala, Asn, Pro) of a Q16ETFSDLWKLLP27 p53-based peptide and a M1PRFMDYWEGLN12 12/1 phage-derived peptide on their interaction dynamics with MDM2. The substitutions modulate peptide residence times around the MDM2 protein. In particular, the highest affinity peptide, Q16ETFSDLWKLLS27, has the longest residence time (t ∼ 25 μs) around MDM2, suggesting its potentially important contribution to binding affinity. The binding of the p53-based peptides appears to be kinetically driven while that of the phage-derived series appears to be thermodynamically driven. The phage-derived peptides were found to adopt distinctly different modes of interaction with the MDM2 protein compared to their p53-based counterparts. The p53-based peptides approach the N-terminal region of the MDM2 protein with the peptide C-terminal end oriented toward the protein, while the M1PRFMDYWEGLN12-based peptides adopt the reverse orientation. To probe the determinants of this switch in orientation, a designed mutant of the phage-derived peptide, R3E (M1PEFMDYWEGLN12), was simulated and found to adopt the orientation adopted by the p53-based peptides and also to result in almost a 5-fold increase in the peptide residence time (∼120 μs) relative to the p53-based peptides. On this basis, we suggest that the R3E mutant phage-derived peptide has a higher affinity for MDM2 than the p53-based peptides and would therefore, competitively inhibit MDM2-p53. The study, therefore, provides a novel computational framework for kinetics-based lead optimization for anticancer drug development strategies.

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Section: Resultsmentioning

confidence: 99%

Recognition Dynamics of p53 and MDM2: Implications for Peptide Design

2016

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“…This could explain why the F19A p53 mutant does not bind to MDM2 (Bottger et al, 1997). The detrimental effect of the phosphorylation of p53 Thr18 (Lee et al, 2007), p53 Ser20 (ElSawy et al, 2015), MDM2 Ser17 (Dastidar et al, 2011), and MDMX Tyr99 (Chan et al, 2017) on p53 binding to MDM2 or MDMX have also been extensively studied in MD and Brownian dynamics (BD) simulations.…”

Section: Understanding P53 Interactionsmentioning

confidence: 99%

Roles of computational modelling in understanding p53 structure, biology, and its therapeutic targeting

Tan

Mhoumadi

Verma

2019

Journal of Molecular Cell Biology

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The transcription factor p53 plays pivotal roles in numerous biological processes, including the suppression of tumours. The rich availability of biophysical data aimed at understanding its structure–function relationships since the 1990s has enabled the application of a variety of computational modelling techniques towards the establishment of mechanistic models. Together they have provided deep insights into the structure, mechanics, energetics, and dynamics of p53. In parallel, the observation that mutations in p53 or changes in its associated pathways characterize several human cancers has resulted in a race to develop therapeutic modulators of p53, some of which have entered clinical trials. This review describes how computational modelling has played key roles in understanding structural-dynamic aspects of p53, formulating hypotheses about domains that are beyond current experimental investigations, and the development of therapeutic molecules that target the p53 pathway.

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“…In particular, the residence time of HSP90 and MDM2 inhibitors was computed along with the characterization of the drug‐receptor encounter complexes . A few studies on these systems followed this work using the BD methodology …”

Section: Methodsmentioning

confidence: 99%

Binding Kinetics in Drug Discovery

Ferruz

Fabritiis

2016

Mol. Inf.

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Over the last years, researchers have increasingly become interested in measuring and understanding drugs' binding kinetics, namely the time in which drug and its target associate and dissociate. Historically, drug discovery programs focused on the optimization of target affinity as a proxy of in-vivo efficacy. However, often the efficacy of a ligand is not appropriately described by the in-vitro measured drug-receptor affinity, but rather depends on the lifetime of the in-vivo drug-receptor interaction. In this review we review recent works that highlight the importance of binding kinetics, molecular determinants for rational optimization and the recent emergence of computational methods as powerful tools in measuring and understanding binding kinetics.

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A spatiotemporal characterization of the effect of p53 phosphorylation on its interaction with MDM2

Cited by 11 publications

References 64 publications

Recognition Dynamics of p53 and MDM2: Implications for Peptide Design

Recognition Dynamics of p53 and MDM2: Implications for Peptide Design

Roles of computational modelling in understanding p53 structure, biology, and its therapeutic targeting

Binding Kinetics in Drug Discovery

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