Binding without Docking: Small-Molecule Binding Paths on Disordered Proteins

Disordered proteins are challenging targets for drug design because they lack well-defined binding pockets. Small molecules can bind them, but when the bound state remains conformationally heterogeneous, these interactions are not readily characterized in terms of conventional binding pockets. Here, we use the concept of binding paths to describe how small molecules interact with disordered proteins. A binding path is a stochastic sequence of transient residue clusters that a ligand engages as it diffuses across a disordered protein, with each cluster forming and breaking up on time scales comparable to the overall residence time. We formalize this approach using a Markov state model (MSM), in which each state corresponds to a set of residues simultaneously contacting the ligand and the transition probabilities capture how the ligand moves between these sets. We apply this framework to the interactions of 10074-G5 with Aβ42 and of fasudil with α-synuclein, two disordered proteins associated with Alzheimer's disease and Parkinson's disease, respectively. The MSM enables both a dynamic mapping of transient binding sites and a calculation of dissociation constants consistent with experimental measurements. By generalizing the concept of static binding pockets to dynamic binding paths, this approach provides a quantitative framework for characterizing small-molecule binding by disordered proteins and for identifying druggable regions on these challenging targets.