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A microscopic study of functional disorder-order folding transitions coupled to binding is performed for the p27 protein, which derives a kinetic advantage from the intrinsically disordered unbound form on binding with the phosphorylated cyclin A-cyclindependent kinase 2 (Cdk2) complex. Hierarchy of structural loss during p27 coupled unfolding and unbinding is simulated by using high-temperature Monte Carlo simulations initiated from the crystal structure of the tertiary complex. Subsequent determination of the transition-state ensemble and the proposed atomic picture of the folding mechanism coupled to binding provide a microscopic rationale that reconciles the initiation recruitment of p27 at the cyclin A docking site with the kinetic benefit for a disordered α-helix in the unbound form of p27. The emerging structural polarization in the ensemble of unfolding/unbinding trajectories and in the computationally determined transition-state ensemble is not determined by the intrinsic folding preferences of p27 but rather is attributed to the topological requirements of the native intermolecular interface to order β-hairpin and β-strand of p27 that could be critical for nucleating rapid folding transition coupled to binding. In agreement with the experimental data, the disorderorder folding transition for p27 is largely determined by the functional requirement to form a specific intermolecular interface that ultimately dictates the folding mechanism and overwhelms any local folding preferences for creating a stable α-helix in the p27 structure before overcoming the major free energy barrier. [ABSTRACT FROM AUTHOR]

The energy landscape approach has contributed to recent progress in understanding the complexity and simplicity of ligand–macromolecule interactions. Significant advances in computational structure prediction of ligand–protein complexes have been made using approaches that include the effects of protein flexibility and incorporate a hierarchy of energy functions. The results suggest that the complexity of structure prediction in molecular recognition may be determined by low-resolution properties of the underlying binding energy landscapes and by the nature of the energy funnels near the native structures of the complexes. [Copyright &y& Elsevier]