Targeting the conformational transitions of MDM2 and MDMX: Insights into key residues affecting p53 recognition

Molecular function recognition by supervised projection pursuit machine learning

Identifying mechanisms that control molecular function is a significant challenge in pharmaceutical science and molecular engineering. Here, we present a novel projection pursuit recurrent neural network to identify functional mechanisms in the context of iterative supervised machine learning for discovery-based design optimization. Molecular function recognition is achieved by pairing experiments that categorize systems with digital twin molecular dynamics simulations to generate working hypotheses. Feature extraction decomposes emergent properties of a system into a complete set of basis vectors. Feature selection requires signal-to-noise, statistical significance, and clustering quality to concurrently surpass acceptance levels. Formulated as a multivariate description of differences and similarities between systems, the data-driven working hypothesis is refined by analyzing new systems prioritized by a discovery-likelihood. Utility and generality are demonstrated on several benchmarks, including the elucidation of antibiotic resistance in TEM-52 beta-lactamase. The software is freely available, enabling turnkey analysis of massive data streams found in computational biology and material science.

On the interaction mechanisms of a p53 peptide and nutlin with the MDM2 and MDMX proteins: a Brownian dynamics study

The interaction of p53 with its regulators MDM2 and MDMX plays a major role in regulating the cell cycle. Inhibition of this interaction has become an important therapeutic strategy in oncology. Although MDM2 and MDMX share a very high degree of sequence/structural similarity, the small-molecule inhibitor nutlin appears to be an efficient inhibitor only of the p53-MDM2 interaction. Here, we investigate the mechanism of interaction of nutlin with these two proteins and contrast it with that of p53 using Brownian dynamics simulations. In contrast to earlier attempts to examine the bound states of the partners, here we locate initial reaction events in these interactions by identifying the regions of space around MDM2/MDMX, where p53/nutlin experience associative encounters with prolonged residence times relative to that in bulk solution. We find that the initial interaction of p53 with MDM2 is long-lived relative to nutlin, but, unlike nutlin, it takes place at the N- and C termini of the MDM2 protein, away from the binding site, suggestive of an allosteric mechanism of action. In contrast, nutlin initially interacts with MDM2 directly at the clefts of the binding site. The interaction of nutlin with MDMX, however, is very short-lived compared with MDM2 and does not show such direct initial interactions with the binding site. Comparison of the topology of the electrostatic potentials of MDM2 and MDMX and the locations of the initial encounters with p53/nutlin in tandem with structure-based sequence alignment revealed that the origin of the diminished activity of nutlin toward MDMX relative to MDM2 may stem partly from the differing topologies of the electrostatic potentials of the two proteins. Glu25 and Lys51 residues underpin these topological differences and appear to collectively play a key role in channelling nutlin directly toward the binding site on the MDM2 surface and are absent in MDMX. The results, therefore, provide new insight into the mechanism of p53/nutlin interactions with MDM2 and MDMX and could potentially have a broader impact on anticancer drug optimization strategies.

Modeling of arylamide helix mimetics in the p53 peptide binding site of hDM2 suggests parallel and anti-parallel conformations are both stable

The design of novel α-helix mimetic inhibitors of protein-protein interactions is of interest to pharmaceuticals and chemical genetics researchers as these inhibitors provide a chemical scaffold presenting side chains in the same geometry as an α-helix. This conformational arrangement allows the design of high affinity inhibitors mimicking known peptide sequences binding specific protein substrates. We show that GAFF and AutoDock potentials do not properly capture the conformational preferences of α-helix mimetics based on arylamide oligomers and identify alternate parameters matching solution NMR data and suitable for molecular dynamics simulation of arylamide compounds. Results from both docking and molecular dynamics simulations are consistent with the arylamides binding in the p53 peptide binding pocket. Simulations of arylamides in the p53 binding pocket of hDM2 are consistent with binding, exhibiting similar structural dynamics in the pocket as simulations of known hDM2 binders Nutlin-2 and a benzodiazepinedione compound. Arylamide conformations converge towards the same region of the binding pocket on the 20 ns time scale, and most, though not all dihedrals in the binding pocket are well sampled on this timescale. We show that there are two putative classes of binding modes for arylamide compounds supported equally by the modeling evidence. In the first, the arylamide compound lies parallel to the observed p53 helix. In the second class, not previously identified or proposed, the arylamide compound lies anti-parallel to the p53 helix.

Molecular dynamic simulation insights into the normal state and restoration of p53 function

As a tumor suppressor protein, p53 plays a crucial role in the cell cycle and in cancer prevention. Almost 50 percent of all human malignant tumors are closely related to a deletion or mutation in p53. The activity of p53 is inhibited by over-active celluar antagonists, especially by the over-expression of the negative regulators MDM2 and MDMX. Protein-protein interactions, or post-translational modifications of the C-terminal negative regulatory domain of p53, also regulate its tumor suppressor activity. Restoration of p53 function through peptide and small molecular inhibitors has become a promising strategy for novel anti-cancer drug design and development. Molecular dynamics simulations have been extensively applied to investigate the conformation changes of p53 induced by protein-protein interactions and protein-ligand interactions, including peptide and small molecular inhibitors. This review focuses on the latest MD simulation research, to provide an overview of the current understanding of interactions between p53 and its partners at an atomic level.

Molecular dynamics studies on Mdm2 complexes: an analysis of the inhibitor influence

p53 is a powerful anti-tumoral molecule frequently inactivated by mutations or deletions in cancer. However, half of all human tumors expresses wild-type p53, and its activation, by antagonizing its negative regulator Mdm2, might offer a new strategy for therapeutic protocol. In this work, we present a molecular dynamics study on Mdm2 structure bound to two different known inhibitors with the aim to investigate the structural transitions between apo-Mdm2 and Mdm2-inhibitor complexes. We tried to gain information about conformational changes binding a benzodiazepine derivative inhibitor with respect the known nutlin and the apo form. The conformational changes alter the size of the cleft and were mainly in the linker regions, suggesting that the overall dynamic nature of Mdm2 is related to dynamic movements in these regions.

Molecular modeling and molecular dynamics simulation studies on pyrrolopyrimidine-based α-helix mimetic as dual inhibitors of MDM2 and MDMX

Inhibition of the interactions between the tumor suppressor protein p53 and its negative regulators, the MDM2 and MDMX oncogenic proteins, is increasingly gaining interest in cancer therapy and drug design. In this study, we carry out molecular docking, molecular dynamics (MD) simulations, and molecular mechanics Poisson-Boltzmann and generalized Born/surface area (MM-PB/GBSA) binding free energy calculations on an active compound 3a and an inactive compound NC-1, which share a common pyrrolopyrimidine-based scaffold. MD simulations and MM-PB/GBSA calculations show that the compound NC-1 may not bind to MDM2 and MDMX, in agreement with the experimental results. Detailed MM-PB/GBSA calculations on the MDM2-3a and MDMX-3a complexes unravel that the binding free energies are similar for the two complexes. Furthermore, the van der Waals energy is the largest component of the binding free energy for both complexes, which indicates that the interactions between the compound 3a and MDM2 and MDMX are dominated by shape complementarity. In addition, the analysis of individual residue contribution and protein-ligand binding mode show that the three functional groups on R₁, R₂, and R₃ of the compound 3a can mimic the spatial orientation of the side chains of Phe19, Trp23, and Leu26 of p53, respectively. The obtained computational results suggest that the compound 3a can act as a dual inhibitor of MDM2-p53 and MDMX-p53 interactions, consistent with the experimental results.

Modulation of p53 binding to MDM2: computational studies reveal important roles of Tyr100

Background

The tumor suppressor protein p53 is regulated by the ubiquitin ligase MDM2 which down-regulates p53. In tumours with overexpressed MDM2, the p53-MDM2 interaction can be interrupted by a peptide or small molecule to stabilize p53 as a therapeutic strategy. Structural and biochemical/mutagenesis data show that p53 has 3 hydrophobic residues F19, W23 and L26 that embed into the ligand binding pocket of MDM2 which is highly plastic in nature and can modulate its size to accommodate a variety of ligands. This binding pocket is primarily dependent on the orientation of a particular residue, Y100. We have studied the role of the dynamics of Y100 in p53 recognition.

Results

Molecular dynamics simulations show that the Y100 side chain can be in "open" or "closed" states with only the former enabling complex formation. When both p53 and MDM2 are in near native conformations, complex formation is rapid and is driven by the formation of a hydrogen bond between W23 of p53 and L54 of MDM2 or by the embedding of F19 of p53 into MDM2. The transition of Y100 from "closed" to "open" can increase the size of the binding site. Interconversions between these two states can be induced by the N-terminal region of MDM2 or by the conformations of the p53 peptides.

Conclusion

Molecular dynamics simulations have revealed how the binding of p53 to MDM2 is modulated by the conformational mobility of Y100 which is the gatekeeper residue in MDM2. The mobility of this residue can be modulated by the conformations of p53 and the Nterminal lid region of MDM2.