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Identification of FDA-approved drugs that computationally bind to MDM2
Abstract:
The integrity of the p53 tumor suppressor pathway is compromised in the majority of cancers. In 7% of cancers p53 is inactivated by abnormally high levels of MDM2--an E3 ubiquitin ligase that polyubiquitinates p53, marking it for degradation. MDM2 engages p53 through its hydrophobic cleft, and blockage of that cleft by small molecules can re-establish p53 activity. Small molecule MDM2 inhibitors have been developed, but there is likely to be a high cost and long time period before effective drugs reach the market. An alternative is to repurpose FDA-approved drugs. This report describes a new approach, called Computational Conformer Selection, to screen for compounds that potentially inhibit MDM2. This screen was used to computationally generate up to 600 conformers of 3244 FDA-approved drugs. Drug conformer similarities to 41 computationally-generated conformers of MDM2 inhibitor nutlin 3a were ranked by shape and charge distribution. Quantification of similarities by Tanimoto combo scoring resulted in scores that ranged from 0.142 to 0.802. In silico docking of drugs to MDM2 was used to calculate binding energies and to visualize contacts between the top-ranking drugs and the MDM2 hydrophobic cleft. We present 15 FDA-approved drugs predicted to inhibit p53/MDM2 interaction.
Insights
This study used Computational Conformer Selection to screen FDA-approved drugs for potential MDM2 inhibition, identifying 15 candidates to restore p53 tumor suppressor activity in cancer.
Area of Science:
- Oncology
- Computational Chemistry
- Drug Discovery
Background:
- The p53 tumor suppressor pathway is crucial for preventing cancer but is often inactivated by high levels of MDM2.
- MDM2, an E3 ubiquitin ligase, targets p53 for degradation, and inhibiting this interaction can restore p53's tumor-suppressive function.
- Developing novel small molecule MDM2 inhibitors is time-consuming and costly.
Discussion:
- Computational Conformer Selection (CCS) was employed to screen 3244 FDA-approved drugs for potential MDM2 inhibition.
- The CCS approach generated multiple drug conformers and ranked their similarity to known MDM2 inhibitor nutlin 3a based on shape and charge.
- In silico docking analyzed binding energies and interactions within the MDM2 hydrophobic cleft for top-ranking compounds.
Key Insights:
- The study identified 15 FDA-approved drugs predicted to inhibit the p53/MDM2 interaction.
- These repurposed drugs offer a potentially faster and more cost-effective alternative to novel drug development.
- The findings highlight the utility of computational screening for identifying novel therapeutic strategies.
Outlook:
- Further experimental validation is required to confirm the efficacy of the identified drugs in inhibiting MDM2 and restoring p53 activity.
- This computational approach can be expanded to screen larger drug libraries and other cancer targets.
- Successful repurposing of these drugs could lead to new treatment options for various cancers with p53 pathway dysfunction.
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