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Yeast As a Chassis for Developing Functional Assays to Study Human P53
Published on: August 4, 2019
Integrated virtual screening and molecular dynamics simulation revealed promising drug candidates of p53-MDM2
Abdul-Quddus Kehinde Oyedele1,2, Temitope Isaac Adelusi1, Abdeen Tunde Ogunlana1
1Computational Biology/Drug Discovery Laboratory, Department of Biochemistry, Ladoke Akintola University of Technology, Ogbomosho, Nigeria.
Abstract:
In the vast majority of malignancies, the p53 tumor suppressor pathway is compromised. In some cancer cells, high levels of MDM2 polyubiquitinate p53 and mark it for destruction, thereby leading to a corresponding downregulation of the protein. MDM2 interacts with p53 via its hydrophobic pocket, and chemical entities that block the dimerization of the protein-protein complex can restore p53 activity. Thus far, only a few chemical compounds have been reported as potent arsenals against p53-MDM2. The Protein Data Bank has crystallogaphic structures of MDM2 in complex with certain compounds. Herein, we have exploited one of the complexes in the identification of new p53-MDM2 antagonists using a hierarchical virtual screening technique. The initial stage was to compile a targeted library of structurally appropriate compounds related to a known effective inhibitor, Nutlin 2, from the PubChem database. The identified 57 compounds were subjected to virtual screening using molecular docking to discover inhibitors with high binding affinity for MDM2. Consequently, five compounds with higher binding affinity than the standard emerged as the most promising therapeutic candidates. When compared to Nutlin 2, four of the drug candidates (CID_140017825, CID_69844501, CID_22721108, and CID_22720965) demonstrated satisfactory pharmacokinetic and pharmacodynamic profiles. Finally, MD simulation of the dynamic behavior of lead-protein complexes reveals the stability of the complexes after a 100,000 ps simulation period. In particular, when compared to the other three leads, overall computational modeling found CID_140017825 to be the best pharmacological candidate. Following thorough experimental trials, it may emerge as a promising chemical entity for cancer therapy.
Insights
Researchers identified new potential cancer drugs by virtually screening compounds to block the p53-MDM2 interaction, a key pathway in many cancers. CID_140017825 showed the most promise as a therapeutic candidate.
Area of Science:
- Oncology
- Computational Chemistry
- Drug Discovery
Background:
- The p53 tumor suppressor pathway is frequently compromised in malignancies.
- MDM2 overexpression in cancer cells leads to p53 degradation, promoting tumor growth.
- Inhibiting the p53-MDM2 interaction can restore p53 tumor suppressor activity.
Purpose of the Study:
- To identify novel chemical compounds that antagonize the p53-MDM2 interaction.
- To discover potent inhibitors with high binding affinity for MDM2.
- To evaluate potential drug candidates for cancer therapy.
Main Methods:
- Hierarchical virtual screening of a targeted compound library.
- Molecular docking to assess binding affinity to MDM2.
- Pharmacokinetic and pharmacodynamic profiling.
- Molecular dynamics simulations to evaluate complex stability.
Main Results:
- Five compounds exhibited higher binding affinity to MDM2 than the standard inhibitor.
- Four compounds demonstrated favorable pharmacokinetic and pharmacodynamic profiles.
- Molecular dynamics simulations confirmed the stability of lead-protein complexes.
- CID_140017825 was identified as the most promising pharmacological candidate.
Conclusions:
- Virtual screening successfully identified novel p53-MDM2 antagonists.
- CID_140017825 represents a promising lead compound for further development in cancer therapy.
- Computational modeling provides a robust approach for discovering new anti-cancer agents.

