Molecular dynamics (MD) simulations have become increasingly popular in studying the motions and functions of biomolecules. The accuracy of the simulation, however, is highly determined by the classical force field (FF), a set of functions with adjustable parameters to compute the potential energies from atomic positions. Most current force fields share similar functional forms, such as harmonic terms for covalent bond stretching and angle bending, Lennard-Jones term for vdW interactions, Coulomb term with fixed partial atomic charges for electrostatics, and Fourier series as a function of dihedral for rotational energies. The differences tend to be in the model systems and type of reference data used for training the parameters in the force field. This work builds on ff99SB and ff14SB to further improve the accuracy of the protein force field. Results have shown that the new FF not only better reproduced various types of experimental measurements, but also improved secondary structure prediction in both small peptides and proteins in solution. Most of the simulations were performed with a GPU-accelerated software application AMBER on high-performance supercomputers equipped with thousands of GPUs.

FF18SB: Improving the accuracy of biomolecular simulation with a physics-based force field

256th National Meeting (2018)

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