Promising disruptors of p53-MDM2 dimerization from some medicinal plant phytochemicals: a molecular modeling study.

Cancer is a major global health issue that has a high mortality rate. p53, which functions as a tumor suppressor, is critical in preventing tumor development by regulating the cell cycle and inducing apoptosis in damaged cells. However, the tumor suppressor function of p53 is effectively inhibited by its direct interaction with the hydrophobic cleft of MDM2 protein via multiple mechanisms As a result, restoring p53 activity by blocking the p53-MDM2 protein-protein interaction has been proposed as a compelling therapeutic strategy for cancer treatment. The use of molecular docking and phytochemical screening procedures are appraised to inhibit MDM2's hydrophobic cleft and disrupt the p53-MDM2 interaction. For this purpose, a library of 51 bioactive compounds from 10 medicinal plants was compiled and subjected to structure-based virtual screening. Out of these, only 3 compounds (Atalantoflavone, Cudraxanthone 1, and Ursolic acid) emerged as promising inhibitors of MDM2-p53 based on their binding affinities (-9.1 kcal/mol, -8.8 kcal/mol, and -8.8 kcal/mol respectively) when compared to the standard (-8.8 kcal/mol). Moreover, these compounds showed better pharmacokinetic and drug-like profiling than the standard inhibitor (Chromonotriazolopyrimidine 1). Finally, the 100 ns MD simulation analysis confirmed no significant perturbation in the conformational dynamics of the simulated binary complexes when compared to the standard. In particular, Ursolic acid was found to satisfy the molecular enumeration the most compared to the other inhibitors. Our overall molecular modeling finding shows why these compounds may emerge as potent arsenals for cancer therapeutics. Nonetheless, extensive experimental and clinical research is needed to augment their use in clinics.Communicated by Ramaswamy H. Sarma.

EGCG binds intrinsically disordered N-terminal domain of p53 and disrupts p53-MDM2 interaction.

Epigallocatechin gallate (EGCG) from green tea can induce apoptosis in cancerous cells, but the underlying molecular mechanisms remain poorly understood. Using SPR and NMR, here we report a direct, µM interaction between EGCG and the tumor suppressor p53 (KD = 1.6 ± 1.4 µM), with the disordered N-terminal domain (NTD) identified as the major binding site (KD = 4 ± 2 µM). Large scale atomistic simulations (>100 µs), SAXS and AUC demonstrate that EGCG-NTD interaction is dynamic and EGCG causes the emergence of a subpopulation of compact bound conformations. The EGCG-p53 interaction disrupts p53 interaction with its regulatory E3 ligase MDM2 and inhibits ubiquitination of p53 by MDM2 in an in vitro ubiquitination assay, likely stabilizing p53 for anti-tumor activity. Our work provides insights into the mechanisms for EGCG's anticancer activity and identifies p53 NTD as a target for cancer drug discovery through dynamic interactions with small molecules.

An integrated in silico screening strategy for identifying promising disruptors of p53-MDM2 interaction.

The p53 protein, also called guardian of the genome, plays a critical role in the cell cycle regulation and apoptosis. This protein is frequently inactivated in several types of human cancer by abnormally high levels of its negative regulator, mouse double minute 2 (MDM2). As a result, restoration of p53 function by inhibiting p53-MDM2 protein-protein interaction has been pursued as a compelling strategy for cancer therapy. To date, a limited number of small-molecules have been reported as effective p53-MDM2 inhibitors. X-ray structures of MDM2 in complex with some ligands are available in Protein Data Bank and herein, these data have been exploited to efficiently identify new p53-MDM2 interaction antagonists through a hierarchical virtual screening strategy. For this purpose, the first step was aimed at compiling a focused library of 686,630 structurally suitable compounds, from PubChem database, similar to two known effective inhibitors, Nutlin-3a and DP222669. These compounds were subjected to the subsequent structure-based approaches (quantum polarized ligand docking and molecular dynamics simulation) to select potential compounds with highest binding affinity for MDM2 protein. Additionally, ligand binding energy, ADMET properties and PAINS analysis were also considered as filtering criteria for selecting the most promising drug-like molecules. On the basis of these analyses, three top-ranked hit molecules, CID_118439641, CID_60452010 and CID_3106907, were found to have acceptable pharmacokinetics properties along with superior in silico inhibitory ability towards the p53-MDM2 interaction compared to known inhibitors. Molecular docking and molecular dynamics results well confirmed the interactions of the final selected compounds with critical residues within p53 binding site on the MDM2 hydrophobic clefts with satisfactory thermodynamics stability. Consequently, the new final scaffolds identified by the presented computational approach could offer a set of guidelines for designing promising anti-cancer agents targeting p53-MDM2 interaction.

Artificial Intelligence Approach to Find Lead Compounds for Treating Tumors.

It has been demonstrated that MMP13 enzyme is related to most cancer cell tumors. The world's largest traditional Chinese medicine database was applied to screen for structure-based drug design and ligand-based drug design. To predict drug activity, machine learning models (Random Forest (RF), AdaBoost Regressor (ABR), Gradient Boosting Regressor (GBR)), and Deep Learning models were utilized to validate the Docking results, and we obtained an R2 of 0.922 on the training set and 0.804 on the test set in the RF algorithm. For the Deep Learning algorithm, R2 of the training set is 0.90, and R2 of the test set is 0.810. However, these TCM compounds fly away during the molecular dynamics (MD) simulation. We seek another method: peptide design. All peptide database were screened by the Docking process. Modification peptides were optimized the interaction modes, and the affinities were assessed with ZDOCK protocol and Refine Docked protein protocol. The 300 ns MD simulation evaluated the stability of receptor-peptide complexes. The double-site effect appeared on S2, a designed peptide based on a known inhibitor, when complexed with BCL2. S3, a designed peptide referred from endogenous inhibitor P16, competed against cyclin when binding with CDK6. The MDM2 inhibitors S5 and S6 were derived from the P53 structure and stable binding with MDM2. A flexible region of peptides S5 and S6 may enhance the binding ability by changing its own conformation, which was unforeseen. These peptides (S2, S3, S5, and S6) are potentially interesting to treat cancer; however, these findings need to be affirmed by biological testing, which will be conducted in the near future.

Identification of new inhibitors of Mdm2-p53 interaction via pharmacophore and structure-based virtual screening.

BACKGROUND: The tumor suppressor protein p53 plays an important role in preventing tumor formation and progression through its involvement in cell division control and initiation of apoptosis. Mdm2 protein controls the activity of p53 protein through working as ubiquitin E3 ligase promoting p53 degradation through the proteasome degradation pathway. Inhibitors for Mdm2-p53 interaction have restored the activity of p53 protein and induced cancer fighting properties in the cell. PURPOSE: The objective of this study is to use computer-aided drug discovery techniques to search for new Mdm2-p53 interaction inhibitors. METHODS: A set of pharmacophoric features were created based on a standard Mdm2 inhibitor and this was used to screen a commercial drug-like ligand library; then potential inhibitors were docked and ranked in a multi-step protocol using GLIDE. Top ranked ligands from docking were evaluated for their inhibition activity of Mdm2-p53 interaction using ELISA testing. RESULTS: Several compounds showed inhibition activity at the submicromolar level, which is comparable to the standard inhibitor Nutlin-3a. Furthermore, the discovered inhibitors were evaluated for their anticancer activities against different breast cancer cell lines, and they showed an interesting inhibition pattern. CONCLUSION: The reported inhibitors can represent a starting point for further SAR studies in the future and can help in the discovery of new anticancer agents.

Antiproliferative and apoptosis-induction studies of 5-hydroxy 3',4',7-trimethoxyflavone in human breast cancer cells MCF-7: an in vitro and in silico approach.

The aim of this study was to find the efficacy of 5-hydroxy 3',4',7-trimethoxyflavone (HTMF), a flavonoid compound isolated from the medicinal plant Lippia nodiflora, in inhibiting the proliferation and inducing apoptosis in human breast cancer cell line MCF-7. The anti-proliferative effect of the compound HTMF was confirmed using MTT cytotoxicity assay. Increased apoptotic induction by HTMF was demonstrated by acridine orange/ethidium bromide (AO/EtBr) and Hoechst 33258 staining studies. The phosphatidylserine translocation, an early feature of apoptosis and DNA damage were revealed through AnnexinV-Cy3 staining and comet assay. Moreover, the significant elevation of cellular ROS was observed in the treated cells, as measured by 2,7-diacetyl dichlorofluorescein (DCFH-DA). The mRNA expression studies also supported the effectiveness of HTMF by shifting the Bax:Bcl-2 ratio. The treatment of MCF-7 cells with HTMF encouraged apoptosis through the modulation of apoptotic markers, such as p53, Bcl-2, Bax, and cleaved PARP. In silico molecular docking and dynamics studies with MDM2-p53 protein revealed that HTMF was more potent compound that could inhibit the binding of MDM2 with p53 and, therefore, could trigger apoptosis in cancer cell. Overall, this study brings up scientific evidence for the efficacy of HTMF against MCF-7 breast cancer cells.

Screening of medicinal plant phytochemicals as natural antagonists of p53-MDM2 interaction to reactivate p53 functioning.

In most types of cancer, overexpression of murine double minute 2 (MDM2) often leads to inactivation of p53. The crystal structure of MDM2, with a 109-residue amino-terminal domain, reveals that MDM2 has a core hydrophobic region to which p53 binds as an amphipathic α helix. The interface depends on the steric complementarity between MDM2 and the hydrophobic region of p53. Especially, on p53's triad, amino acids Phe19, Trp23 and Leu26 bind to the MDM2 core. Results from studies suggest that the structural motif of both p53 and MDM2 can be attributed to similarities in the amphipathic α helix. Thus, in the current investigation it is hypothesized that the similarity in the structural motif might be the cause of p53 inactivation by MDM2. Hence, molecular docking and phytochemical screening approaches are appraised to inhibit the hydrophobic cleft of MDM2 and to stop p53-MDM2 interaction, resulting in reactivation of p53 activity. For this purpose, a library of 2295 phytochemicals were screened against p53-MDM2 to find potential candidates. Of these, four phytochemicals including epigallocatechin gallate, alvaradoin M, alvaradoin E and nordihydroguaiaretic acid were found to be potential inhibitors of p53-MDM2 interaction. The screened phytochemicals, derived from natural extracts, may have negligible side effects and can be explored as potent antagonists of p53-MDM2 interactions, resulting in reactivation of the normal transcription of p53.

Searching for Dual Inhibitors of the MDM2-p53 and MDMX-p53 Protein-Protein Interaction by a Scaffold-Hopping Approach.

Two libraries of substituted benzimidazoles were designed using a 'scaffold-hopping' approach based on reported MDM2-p53 inhibitors. Substituents were chosen following library enumeration and docking into an MDM2 X-ray structure. Benzimidazole libraries were prepared using an efficient solution-phase approach and screened for inhibition of the MDM2-p53 and MDMX-p53 protein-protein interactions. Key examples showed inhibitory activity against both targets.

A re-examination of the MDM2/p53 interaction leads to revised design criteria for novel inhibitors.

The general model of epitope-type MDM2 inhibitor was developed based on the structural information on the complexes between MDM2 and various low molecular weight ligands found in the PDB database. Application of this model to our in-house library has led us to a new scaffold capable of interrupting protein-protein interactions. A synthetic library based on this and related scaffolds resulted in new classes of compounds that possess biochemical and cellular activity and good pharmacokinetic properties. We assume that such general approach to PPI inhibitors design may be useful for the development of inhibitors of various PPI types, including Bcl/XL.

Ligand binding mode prediction by docking: mdm2/mdmx inhibitors as a case study.

The p53-binding domains of Mdm2 and Mdmx, two negative regulators of the tumor suppressor p53, are validated targets for cancer therapeutics, but correct binding poses of some proven inhibitors, particularly the nutlins, have been difficult to obtain with standard docking procedures. Virtual screening pipelines typically draw from a database of compounds represented with 1D or 2D structural information from which one or more 3D conformations must be generated. These conformations are then passed to a docking algorithm that searches for optimal binding poses on the target protein. This work tests alternative pipelines using several commonly used conformation generation programs (LigPrep, ConfGen, MacroModel, and Corina/Rotate) and docking programs (GOLD, Glide, MOE-dock, and AutoDock Vina) for their ability to reproduce known poses for a series of Mdmx and/or Mdm2 inhibitors, including several nutlins. Most combinations of these programs using default settings fail to find correct poses for the nutlins but succeed for all other compounds. Docking success for the nutlin class requires either computationally intensive conformational exploration or an "anchoring" procedure that incorporates knowledge of the orientation of the central imidazoline ring.

Virtual screening of low molecular weight mushrooms compounds as potential Mdm2 inhibitors.

In some human cancer cases, the activity of p53 is inhibited by over-expressed Mdm2. The Mdm2 acts as an ubiquitin ligase, resulting in p53 ubiquitination and subsequent p53 proteasomal degradation. The disruption of the Mdm2-p53 interaction using small-molecule inhibitors is recognized as a promising strategy for anti-cancer drug design. Mushrooms are an important source of powerful compounds with anti-tumour properties. In this study, the first virtual screening of low molecular weight compounds present in mushroom is presented as potential Mdm2 inhibitors. A re-docking and cross-docking method was used to validate the virtual screening protocol. The steroids: ganoderic acids X (K(i) = 16nM), Y (K(i) = 22nM) and F (K(i) = 69nM); 5,6-epoxy-24(R)-methylcholesta-7,22-dien-3ß-ol (K(i) = 74nM) and polyporenic acid C (K(i) = 59nM) stand out as the top ranked potential inhibitors of Mdm2. The docking pose of the most promising compounds were carefully analysed and the information provided shows several interesting starting points for further development of Mdm2 inhibitors.

Rewiring kinase specificity with a synthetic adaptor protein.

Signaling cascades are managed in time and space by interactions between and among proteins. These interactions are often aided by adaptor proteins, which guide enzyme-substrate pairs into proximity. Miniature proteins are a class of small, well-folded protein domains possessing engineered binding properties. Here we made use of two miniature proteins with complementary binding properties to create a synthetic adaptor protein that effectively redirects a ubiquitous signaling event: tyrosine phosphorylation. We report that miniature-protein-based adaptor 3 uses templated catalysis to redirect the Src family kinase Hck to phosphorylate hDM2, a negative regulator of the p53 tumor suppressor and a poor Hck substrate. Phosphorylation occurs with multiple turnover and at a single site targeted by c-Abl kinase in the cell.

Toward a general approach for RNA-templated hierarchical assembly of split-proteins.

The ability to conditionally turn on a signal or induce a function in the presence of a user-defined RNA target has potential applications in medicine and synthetic biology. Although sequence-specific pumilio repeat proteins can target a limited set of ssRNA sequences, there are no general methods for targeting ssRNA with designed proteins. As a first step toward RNA recognition, we utilized the RNA binding domain of argonaute, implicated in RNA interference, for specifically targeting generic 2-nucleotide, 3' overhangs of any dsRNA. We tested the reassembly of a split-luciferase enzyme guided by argonaute-mediated recognition of newly generated nucleotide overhangs when ssRNA is targeted by a designed complementary guide sequence. This approach was successful when argonaute was utilized in conjunction with a pumilio repeat and expanded the scope of potential ssRNA targets. However, targeting any desired ssRNA remained elusive as two argonaute domains provided minimal reassembled split-luciferase. We next designed and tested a second hierarchical assembly, wherein ssDNA guides are appended to DNA hairpins that serve as a scaffold for high affinity zinc fingers attached to split-luciferase. In the presence of a ssRNA target containing adjacent sequences complementary to the guides, the hairpins are brought into proximity, allowing for zinc finger binding and concomitant reassembly of the fragmented luciferase. The scope of this new approach was validated by specifically targeting RNA encoding VEGF, hDM2, and HER2. These approaches provide potentially general design paradigms for the conditional reassembly of fragmented proteins in the presence of any desired ssRNA target.

Knowledge-based virtual screening: application to the MDM4/p53 protein-protein interaction.

Chemogenomics knowledge-based drug discovery approaches aim to extract the knowledge gained from one target and to apply it for the discovery of ligands and hopefully drugs of a new target which is related to the parent target by homology or conserved molecular recognition. Herein, we demonstrate the potential of knowledge-based virtual screening by applying it to the MDM4-p53 protein-protein interaction where the MDM2-p53 protein-protein interaction constitutes the parent reference system; both systems are potentially relevant to cancer therapy. We show that a combination of virtual screening methods, including homology based similarity searching, QSAR (Quantitative Structure-Activity Relationship) methods, HTD (High Throughput Docking), and UNITY pharmacophore searching provide a successful approach to the discovery of inhibitors. The virtual screening hit list is of the magnitude of 50,000 compounds picked from the corporate compound library of approximately 1.2 million compounds. Emphasis is placed on the facts that such campaigns are only feasible because of the now existing HTCP (High throughput Cherry-Picking) automation systems in combination with robust MTS (Medium Throughput Screening) fluorescence-based assays. Given that the MDM2-p53 system constitutes the reference system, it is not surprising that significantly more and stronger hits are found for this interaction compared to the MDM4-p53 system. Novel, selective and dual hits are discovered for both systems. A hit rate analysis will be provided compared to the full HTS (High-throughput Screening).

NMR screening for lead compounds using tryptophan-mutated proteins.

NMR-based drug screening methods provide the most reliable characterization of binding propensities of ligands to their target proteins. They are, however, one of the least effective methods in terms of the amount of protein required and the time needed for acquiring an NMR experiment. We show here that the introduction of tryptophan to proteins permits rapid screening by monitoring a simple 1D proton NMR signal of the NH side chain ((N)H(epsilon)) of the tryptophan. The method could also provide quantitative characterization of the antagonist-protein and antagonist-protein-protein interactions in the form of KDs and fractions of the released proteins from their mutual binding. We illustrate the method with the lead compounds that block the Mdm2-p53 interaction and by studying inhibitors that bind to cyclin-dependent kinase 2 (CDK2).