Electrostatic interactions are of fundamental importance for the structures and functions of biomolecules. Their accurate modeling is crucial in the design and development of physical models in computational studies of biomolecules. It is known that widely used point-charge models cannot capture subtle multibody effects and molecular polarization anisotropicity. Recently emerged point multipole models, in the meantime, face a so-called “polarization catastrophe” difficulty that requires artificial truncation and omission of important short-range interactions. Considering these limitations, we are developing a new polarizable Gaussian multipole (pGM) framework, which is capable of describing the short-range interactions more accurately without greatly increasing computational cost. Our data shows that the new model greatly improves the modeling of molecular polarization anisotropicity, interaction energy between molecules, and multibody effects. We have developed a MD algorithm for the pGM model that achieves comfortable energy conservation comparable to the Amber point charge model, derived and implemented stress tensor calculation for the pGM model to realize constant pressure simulations, and optimized several iteration methods to accomplish fast induction convergence. With all the preparation nearly done, we believe that the pGM model will soon be ready for real-world biomolecular modeling.

Polarizable gaussian multipole framework for electrostatic interactions in biomolecules

ACS Fall 2021

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