Proteomimetic libraries: design, synthesis, and evaluation of p53-MDM2 interaction inhibitors

The p53-MDM2 interaction regulates p53-mediated cellular responses to DNA damage, and MDM2 is overexpressed in 7% of all cancers. Structure-based computational design was applied to this system to design libraries centered on a scaffold that projects side chain functionalities with distance and angular relationships equivalent to those seen in the MDM2 interacting motif of p53. A library of 173 such compounds was synthesized using solution phase parallel chemistry. The in vitro competitive ability of the compounds to block p53 peptide binding to MDM2 was determined using a fluorescence polarization competition assay. The most active compound bound with K(d) = 12 microM, and its binding was characterized by (15)N-(1)H HSQC NMR.

Recapitulation and design of protein binding peptide structures and sequences

An important objective of computational protein design is the generation of high affinity peptide inhibitors of protein-peptide interactions, both as a precursor to the development of therapeutics aimed at disrupting disease causing complexes, and as a tool to aid investigators in understanding the role of specific complexes in the cell. We have developed a computational approach to increase the affinity of a protein-peptide complex by designing N or C-terminal extensions which interact with the protein outside the canonical peptide binding pocket. In a first in silico test, we show that by simultaneously optimizing the sequence and structure of three to nine residue peptide extensions starting from short (1-6 residue) peptide stubs in the binding pocket of a peptide binding protein, the approach can recover both the conformations and the sequences of known binding peptides. Comparison with phage display and other experimental data suggests that the peptide extension approach recapitulates naturally occurring peptide binding specificity better than fixed backbone design, and that it should be useful for predicting peptide binding specificities from crystal structures. We then experimentally test the approach by designing extensions for p53 and dystroglycan-based peptides predicted to bind with increased affinity to the Mdm2 oncoprotein and to dystrophin, respectively. The measured increases in affinity are modest, revealing some limitations of the method. Based on these in silico and experimental results, we discuss future applications of the approach to the prediction and design of protein-peptide interactions.

Computational studies and peptidomimetic design for the human p53-MDM2 complex

The interaction between human p53 and MDM2 is a key event in controlling cell growth. Many studies have suggested that a p53 mimic would be sufficient to inhibit MDM2 to reduce cell growth in cancerous tissue. In order to design a potent p53 mimic, molecular dynamics (MD) simulations were used to examine the binding interface and the effect of mutating key residues in the human p53-MDM2 complex. The Generalized Born surface area (GBSA) method was used to estimate free energies of binding, and a computational alanine-scanning approach was used to calculate the relative effects in the free energy of binding for key mutations. Our calculations determine the free energy of binding for a model p53-MDM2 complex to be -7.4 kcal/mol, which is in very good agreement with the experimentally determined values (-6.6--8.8 kcal/mol). The alanine-scanning results are in good agreement with experimental data and calculations by other groups. We have used the information from our studies of human p53-MDM2 to design a beta-peptide mimic of p53. MD simulations of the mimic bound to MDM2 estimate a free energy of binding of -8.8 kcal/mol. We have also applied alanine scanning to the mimic-MDM2 complex and reveal which mutations are most likely to alter the binding affinity, possibly giving rise to escape mutants. The mimic was compared to nutlins, a new class of inhibitors that block the formation of the p53-MDM2 complex. There are interesting similarities between the nutlins and our mimic, and the differences point to ways that both inhibitors may be improved. Finally, an additional hydrophobic pocket is noted in the interior of MDM2. It may be possible to design new inhibitors to take advantage of that pocket.