This framework links function-altering mutations in p53 to long-range interactions in intrinsically disordered regions, suggesting improvements in protein design.
The dynamic ensembles of intrinsically disordered regions (IDRs) are fundamental to their function yet designing them with specific behaviors remains a major challenge. Current AI models and coarse-grained simulations fail to reliably predict the specific intramolecular interactions that define an IDR’s transient structure. To address this gap, we developed the Interaction Map, a framework that decodes an IDR’s ensemble by normalizing all-atom simulation data against an ideal polymer model. This method distills complex contact data into an intuitive visualization of key attractive and repulsive long-range interactions. We demonstrate its power by linking function-altering mutations in p53 to specific changes in its interaction landscape and by accurately predicting the solution sensitivity of IDR ensembles. Leveraging this insight, we developed a “mutation scanning” method for rational protein design, successfully engineering IDR mutants of UPF2 and TDG with altered and predictable solution sensitivities. To make this tool accessible, we also deployed a version based on coarse-grained simulations on Google Colab for experimentalists. The Interaction Map is not only a powerful tool for engineering IDR function but also serves as a critical encoding method to guide the next generation of AI models for predicting dynamic protein ensembles.
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Yu et al. (2026) studied this question.