REDAN: relative entropy-based dynamical allosteric network model

ABSTRACT

Protein allostery is ubiquitous phenomena that are important for cellular signalling processes. Despite extensive methodology development, a quantitative model is still needed to accurately measure protein allosteric response upon external perturbation. Here, we introduced the relative entropy concept from information theory as a quantitative metric to develop a method for measurement of the population shift with regard to protein structure during allosteric transition. This method is referred to as relative entropy-based dynamical allosteric network (REDAN) model. Using this method, protein allostery could be evaluated at three mutually dependent structural levels: allosteric residues, allosteric pathways, and allosteric communities. All three levels are carried out using rigorous searching algorithms based on relative entropy. Application of the REDAN model on the second PDZ domain (PDZ2) in the human PTP1E protein provided metric-based insight into its allostery upon peptide binding.