Binding Paths: Describing Small Molecule Interactions with Disordered Proteins via Markov State Models

Disordered proteins are challenging targets for drug discovery because they lack well-defined binding pockets. Although small molecules can form relatively stable complexes with disordered proteins, the highly dynamic nature of these proteins complicates the understanding of their binding mechanism. To address this issue, we studied the binding of Aβ42 and the small molecule 10074-G5, which leads to the formation of a disordered complex. We then developed a Markov state model (MSM) to describe the binding mechanism in terms of binding paths. Binding paths are stochastic trajectories along which a small molecule diffuses across the disordered protein surface, forming transient contacts with overlapping groups of residues. The MSM enabled the quantification of the different states of the disordered complex, the corresponding binding affinities and transition probabilities. The visualization of the MSM via knowledge graphs provided a representation of the binding paths. By generalizing the concept of static binding pockets to dynamic binding paths, our approach characterises a binding mechanism for disordered proteins, providing insights for future drug design programs.