Computationally Modeling Electrostatic Binding Energetics in a Crowded, Dynamic Environment: Physical Insights from a Peptide-DNA System.

The cell is a crowded place, and it may be crucial at times to account for the local environment when studying determinants of molecular recognition. In this work, we use continuum electrostatics calculations on snapshots extracted from molecular dynamics simulations to understand how various aspects of a crowded environment affect electrostatic binding energies between the antimicrobial peptide buforin II and DNA. By comparing multiple models for representing crowding, sequentially introducing layers of model complexity for maximum control, we explore how electrostatic binding energetics depend on crowder physical properties, the sampling of the binding partners and crowder molecules, and the treatment of bulk solvent. We show that physical characteristics can combine to create an interplay of competing effects in this highly charged system. For example, increased ionic strength screening due to crowding partially cancels out the reduced solvent screening due to water depletion. We also quantify the effect of crowders' charge distributions on binding energetics. While we focus on electrostatic effects of crowding on binding, we begin to consider nonpolar components as well, and we implement a thermodynamic cycle accounting for both bound and unbound states to show the necessity of adequate crowder sampling in future studies. The insights developed here provide a rich starting point for experiments to further explore these competing effects and, ultimately, to rationally modulate molecular recognition in the complex cellular environment.