Binding affinity estimation from restrained umbrella sampling simulations

The protein-ligand binding affinity quantifies the binding strength between a protein and its ligand. Computer modeling and simulations can be used to estimate the binding affinity or binding free energy using data- or physics-driven methods or a combination thereof. Here we discuss a purely physics-based sampling approach based on biased molecular dynamics simulations. Our proposed method generalizes and simplifies previously suggested stratification strategies that use umbrella sampling or other enhanced sampling simulations with additional collective-variable-based restraints. The approach presented here uses a flexible scheme that can be easily tailored for any system of interest. We estimate the binding affinity of human fibroblast growth factor 1 to heparin hexasaccharide based on the available crystal structure of the complex as the initial model and four different variations of the proposed method to compare against the experimentally determined binding affinity obtained from isothermal titration calorimetry experiments.

Automated summary

The protein-ligand binding affinity can be quantified to measure the strength of binding between a protein and its ligand. In this paper, a purely physics-based sampling approach using biased molecular dynamics simulations is presented. The approach simplifies previously suggested strategies and can be tailored for any system of interest. The binding affinity of human fibroblast growth factor 1 to heparin hexasaccharide is estimated using four variations of the proposed method and compared against experimentally determined binding affinity.