Session: COMP Poster Session:

Macromolecular crowding and conformational dynamics can affect molecular recognition and consequently, important cellular functions. In particular, proteins often exist in highly crowded and dynamic environments, which can impact their binding energetics. In this work, we focus on how such environments impact the electrostatic and solvation components of the energy. Specifically, we aim to investigate computationally (1) the impact of dynamics and crowding on optimal electrostatic interactions within the barnase-barstar protein complex and (2) how electrostatic contributions toward binding in the barnase-barstar complex are altered upon crowding. The barnase-barstar interaction has been shown to be mediated by electrostatics, and this work builds on prior studies that have analyzed the determinants of its optimal binding. To accomplish our first goal, we perform explicit-solvent molecular dynamics simulations to generate conformational ensembles of the complex and then, on extracted snapshots, we apply charge optimization, a computational technique using continuum electrostatics, to both crowded and uncrowded versions of each snapshot to determine the hypothetical charge distribution of certain barstar residues that would maximize affinity to barnase in each case. We account for water depletion effects of crowding by surrounding the binding partners within our snapshots with randomly placed uncharged, low-dielectric spherical cavities. To work toward our second goal, we are quantifying the electrostatic contributions of barstar residues D35 and D39 using free energy perturbation via explicit solvent methods as well as implicit-solvent component analysis techniques. We will then introduce lysozyme crowders into the system and repeat these calculations for each residue to assess whether contributions differ in dilute and crowded environments. Ultimately, our goal is to provide a better understanding of the effects of crowding on the electrostatic and solvation components of binding in either natural or designed systems, which can lead to better models of molecular interaction within complex environments.

Mala Radhakrishnan

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