Binding of Two Intrinsically Disordered Peptides to a Multi-Specific Protein: A Combined Monte Carlo and Molecular Dynamics Study

The unique ability of intrinsically disordered proteins (IDPs) to fold upon binding to partner molecules makes them functionally well-suited for cellular communication networks. For example, the folding-binding of different IDP sequences onto the same surface of an ordered protein provides a mechanism for signaling in a many-to-one manner. Here, we study the molecular details of this signaling mechanism by applying both Molecular Dynamics and Monte Carlo methods to S100B, a calcium-modulated homodimeric protein, and two of its IDP targets, p53 and TRTK-12. Despite adopting somewhat different conformations in complex with S100B and showing no apparent sequence similarity, the two IDP targets associate in virtually the same manner. As free chains, both target sequences remain flexible and sample their respective bound, natively -helical states to a small extent. Association occurs through an intermediate state in the periphery of the S100B binding pocket, stabilized by nonnative interactions which are either hydrophobic or electrostatic in nature. Our results highlight the importance of overall physical properties of IDP segments, such as net charge or presence of strongly hydrophobic amino acids, for molecular recognition via coupled folding-binding. A substantial fraction of our proteins are believed to be partly or completely disordered, meaning that they contain regions that lack a stable folded structure under typical physiological conditions. This is a feature which plays a key role in their functions. For example, it allows them to have many structurally different binding partners which in turn permits the construction of the intricate signaling and regulatory networks necessary to sustain complex biological organisms such as ourselves. Whereas measuring the binding strengths of associations involving disordered proteins is routine, the binding process itself is today still not fully understood. We use two different computational models to study the interactions of a folded protein, S100B, which can bind various disordered peptides. In particular, we compare two peptides whose structures are known when in complex with S100B. Our results suggest that, although the peptides assume different structures in the bound state, there are similarities in how they associate with S100B. The possibility to computationally model the interplay between proteins is an important complement to experiments, by identifying crucial steps in the binding process. This is essential to understand, e.g., how single mutations sometimes lead to serious diseases.