Integrated virtual screening and molecular dynamics simulation revealed promising drug candidates of p53-MDM2 interaction

Autor: Abdul-Quddus Kehinde, Oyedele, Temitope Isaac, Adelusi, Abdeen Tunde, Ogunlana, Rofiat Oluwabusola, Adeyemi, Opeyemi Emmanuel, Atanda, Musa Oladayo, Babalola, Mojeed Ayoola, Ashiru, Isong Josiah, Ayoola, Ibrahim Damilare, Boyenle
Rok vydání: 2022
Předmět:
Zdroj: Journal of Molecular Modeling. 28
ISSN: 0948-5023
1610-2940
Popis: 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.
Databáze: OpenAIRE
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