Computational prediction of hinge axes in proteins

Proteins play a significant role in virtually all biological processes, with motions of interest occurring on the timescale of pico- to nano-seconds. Existing experimental techniques are not able to reliably provide the level of detail required for studying the exact mechanisms of the molecular motion and the underlying structure-function relationship, essential for effective drug screening and design. Theoretical models and computational tools are instrumental for gaining better mechanistic understanding and predictive power. We focus on “hinge” proteins, which exhibit a rotational movement of one region of the protein relative to another; this motion is similar to that allowed by revolute joints. By applying rigidity theoretic techniques that analyze the protein´s geometric structure, we predict a relative axis of motion between a given pair of domains. To the best of our knowledge, this is the first computational method to predict such an axis based on a single conformational state. The most closely related approaches for predicting hinges either use a single conformation to identify the residues permitting the motion (Stonehinge, HingeProt), or require two conformations as input (DynDom). Our results show that rigidity theory can be applied to analyze proteins and accurately predict information that may elucidate conformational changes tied to protein function.