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. © 2012 John Wiley & Sons A/S.