posted on 2019-12-03, 16:38authored byChuan Tian, Koushik Kasavajhala, Kellon A. A. Belfon, Lauren Raguette, He Huang, Angela N. Migues, John Bickel, Yuzhang Wang, Jorge Pincay, Qin Wu, Carlos Simmerling
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 molecular
mechanics (MM) force field (FF), a set of functions with adjustable
parameters to compute the potential energies from atomic positions.
However, the overall quality of the FF, such as our previously published
ff99SB and ff14SB, can be limited by assumptions that were made years
ago. In the updated model presented here (ff19SB), we have significantly
improved the backbone profiles for all 20 amino acids. We fit coupled
φ/ψ parameters using 2D φ/ψ conformational
scans for multiple amino acids, using as reference data the entire
2D quantum mechanics (QM) energy surface. We address the polarization
inconsistency during dihedral parameter fitting by using both QM and
MM in aqueous solution. Finally, we examine possible dependency of
the backbone fitting on side chain rotamer. To extensively validate
ff19SB parameters, and to compare to results using other Amber models,
we have performed a total of ∼5 ms MD simulations in explicit
solvent. Our results show that after amino-acid-specific training
against QM data with solvent polarization, ff19SB not only reproduces
the differences in amino-acid-specific Protein Data Bank (PDB) Ramachandran
maps better but also shows significantly improved capability to differentiate
amino-acid-dependent properties such as helical propensities. We also
conclude that an inherent underestimation of helicity is present in
ff14SB, which is (inexactly) compensated for by an increase in helical
content driven by the TIP3P bias toward overly compact structures.
In summary, ff19SB, when combined with a more accurate water model
such as OPC, should have better predictive power for modeling sequence-specific
behavior, protein mutations, and also rational protein design. Of
the explicit water models tested here, we recommend use of OPC with
ff19SB.