The University of Texas at Austin
Molecular recognition between biomolecules such as ligand-receptor, protein-DNA and antigen-antibody is essential for many biological processes and biomedical applications from drug discovery to biosensor design. Multiple factors, including shape complementary, electrostatic interaction, solvent effect and protein dynamics, are responsible for the specificity and selectivity in molecular recognition. While computer simulations are routinely utilized in the study of biomolecular structure and interactions, accurate evaluation of binding free energy and thermodynamics for ligand-protein or host-guest systems in general remains elusive due to the lack of adequate potential energy models and difficulty in statistical sampling of dynamic events. To address these challenges, we have been developing a next-generation physical model with improved electrostatic representation based on atomic multipoles and explicit many-body polarization. The AMOEBA polarizable force field has shown encouraging accuracy for a range of molecular systems including ions, small organics and proteins, from gas-phase to liquid and crystal properties. Using this model, we have evaluated binding thermodynamics of several protein-ligand with encouraging successes and demonstrated the importance of accurate modeling of short-ranged electrostatic forces in molecular recognition. I will present these results along with the development of AMOEBA polarizable force field model as well as discussion on the effectiveness of free energy simulation methods.