Capillarity Theory for the Fly-Casting Mechanism

TL;DR

This paper introduces a capillarity-based model for the flycasting mechanism in biomolecular recognition, highlighting how protein unfolding and chain rigidity influence binding efficiency, supported by simulations and theoretical analysis.

Contribution

It presents a novel simple model for flycasting based on capillarity and polymer statistics, linking protein unfolding barriers and chain rigidity to binding effectiveness.

Findings

Flycasting is most effective with low unfolding barriers.

Rigid chain segments enhance flycasting efficiency.

Simulation results support the analytical model's predictions.

Abstract

Biomolecular folding and function are often coupled. During molecular recognition events, one of the binding partners may transiently or partially unfold, allowing more rapid access to a binding site. We describe a simple model for this flycasting mechanism based on the capillarity approximation and polymer chain statistics. The model shows that flycasting is most effective when the protein unfolding barrier is small and the part of the chain which extends towards the target is relatively rigid. These features are often seen in known examples of flycasting in protein-DNA binding. Simulations of protein-DNA binding based on well-funneled native-topology models with electrostatic forces confirm the trends of the analytical theory.