Deciphering the\nMystery in p300 Taz2–p53 TAD2\nRecognition

Intrinsically disordered proteins (IDPs) engage in various\nfundamental\nbiological activities, and their behavior is of particular importance\nfor a better understanding of the verbose but well-organized signal\ntransduction in cells. IDPs exhibit uniquely paradoxical features\nwith low affinity but simultaneously high specificity in recognizing\ntheir binding targets. The transcription factor p53 plays a crucial\nrole in cancer suppression, carrying out some of its biological functions\nusing its disordered regions, such as N-terminal transactivation domain\n2 (TAD2). Exploration of the binding and unbinding processes between\nproteins is challenging, and the inherently disordered properties\nof these regions further complicate the issue. Computer simulations\nare a powerful tool to complement the experiments to fill gaps to\nexplore the binding/unbinding processes between proteins. Here, we\ninvestigated the binding mechanism between p300 Taz2 and p53 TAD2\nthrough extensive molecular dynamics (MD) simulations using the physics-based\nUNited RESidue (UNRES) force field with additional Go̅-like\npotentials. Distance restraints extracted from the NMR-resolved structures\nwere imposed on intermolecular residue pairs to accelerate binding\nsimulations, in which Taz2 was immobilized in a native-like conformation\nand disordered TAD2 was fully free. Starting from six structures with\nTAD2 placed at different positions around Taz2, we observed a metastable\nintermediate state in which the middle helical segment of TAD2 is\nanchored in the binding pocket, highlighting the significance of the\nTAD2 helix in directing protein recognition. Physics-based binding\nsimulations show that successful binding is achieved after a series\nof stages, including (1) protein collisions to initiate the formation\nof encounter complexes, (2) partial attachment of TAD2, and finally\n(3) full attachment of TAD2 to the correct binding pocket of Taz2.\nFurthermore, machine-learning-based PathDetect-SOM was used to identify\ntwo binding pathways, the encounter complexes, and the intermediate\nstates.