Classical molecular dynamics (MD) simulations provide
unmatched
spatial and time resolution of protein structure and function. However,
the accuracy of MD simulations often depends on the quality of force
field parameters and the time scale of sampling. Another limitation
of conventional MD simulations is that the protonation states of titratable
amino acid residues remain fixed during simulations, even though protonation
state changes coupled to conformational dynamics are central to protein
function. Due to the uncertainty in selecting protonation states,
classical MD simulations are sometimes performed with all amino acids
modeled in their standard charged states at pH 7. Here, we performed
and analyzed classical MD simulations on high-resolution cryo-EM structures
of two large membrane proteins that transfer protons by catalyzing
protonation/deprotonation reactions. In simulations performed with
titratable amino acids modeled in their standard protonation (charged)
states, the structure diverges far from its starting conformation.
In comparison, MD simulations performed with predetermined protonation
states of amino acid residues reproduce the structural conformation,
protein hydration, and protein–water and protein–protein
interactions of the structure much better. The results support the
notion that it is crucial to perform basic protonation state calculations,
especially on structures where protonation changes play an important
functional role, prior to the launch of any conventional MD simulations.
Furthermore, the combined approach of fast protonation state prediction
and MD simulations can provide valuable information about the charge
states of amino acids in the cryo-EM sample. Even though accurate
prediction of protonation states in proteinaceous environments currently
remains a challenge, we introduce an approach of combining pKa prediction with cryo-EM density map analysis
that helps in improving not only the protonation state predictions
but also the atomic modeling of density data.