Multi-scale enhanced sampling of disordered proteins

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 DESCRIPTION (provided by applicant): The tumor suppressor p53 is the most frequently mutated protein in human cancers. Clinical studies of breast cancer have suggested that the type of p53 mutation can be linked to cancer prognosis, response to drug treatment, and patient survival. It is thus crucial to understand the molecular basis of p53 inactivation by various types of mutations, so as to understand the biological consequences and assess potential cancer intervention strategies. This project contributes to this important goal by determining the structural and functional mechanisms of p53 inactivation by cancer mutants in its transactivation domain (TAD). Intriguingly, p53-TAD is an intrinsically disordered protein (IDP). Its properties are governed by a heterogeneous ensemble of conformations that does not lend itself to description using traditional methods that are geared toward describing a coherent set of similar structures. Reliable atomistic simulations have an important and transformative role to play in terms of describing IDP ensembles and their interactions. At the same time, the heterogeneous and dynamic nature of IDPs like p53-TAD also present important challenges that push the limit of the protein force field accuracy and conformational sampling capability. In this project, we wil leverage our extensive experience and recent contributions in developing advanced techniques for atomistic simulation of IDPs and pursue two parallel specific aims. In Aim 1, we will develop novel multi-scale enhanced sampling techniques for efficient and accurate atomistic simulations of IDP ensembles and their interaction. In Aim 2, we will integrate these advanced simulation techniques with NMR and other biophysical experiments to determine the structural and functional consequences of p53-TAD cancer mutations. Specifically, we will test a novel hypothesis that TAD cancer mutations can modulate unbound conformational ensembles, perturb the balance between p53 binding to negative regulator MDM2 and the general transcriptional co-activator CBP, and further alter how this balance is regulated by multisite phosphorylation of p53-TAD. Successful completion of this project will provide cutting-edge computational tools for de novo simulation of protein conformational equilibria and transitions. The proposed research also represents the first systematic study of the biophysical basis of how disease mutants affect the structure-function relationship of p53-TAD, and provides a paradigm for understanding many other IDPs that are key components of cellular regulatory networks and over-represented in major disease pathways.