Binding of MDM2 Inhibitors via Biased Sampling and Multi-Ensemble Markov Models

Abstract

MDM2 is a ubiquitin ligase that acts as a negative regulator to the tumor suppressor protein p53 through interaction with its N-terminal transactivation domain (TAD). Inhibition of the MDM2-p53 TAD interaction (Kd of 0.62 µM) leads to p53-overactivation-dependent cell death in tumor cells and is therefore a system of great therapeutic interest. In this computational study, we consider two families of molecules that have been shown to competitively bind MDM2. The first class of molecules are spiroligomers, chains of bis-amino acids with uniquely defined stereochemistry and functional groups designed by the Schafmeister group to bind MDM2, with measured Kd values ranging from 0.4 to 23 µM. The other class of molecules are halogenated cis-imidazoline analogs such as Nutlin-3a that inhibit MDM2 with IC50 values ranging from 0.086 to 26 µM. To study the thermodynamics and kinetics of binding for these inhibitors, we build multi-ensemble Markov models (MEMMs) from explicit-solvent molecular dynamics trajectories of the binding/unbinding reactions biased by umbrella sampling (US) and scaled non-bonded interactions. This methodology allows us to observe significantly more binding and unbinding events than would be observed with unbiased sampling. We discuss the accuracy of estimated affinities and binding kinetics.