Transition-Tempered Metadynamics Is a Promising Tool for Studying the Permeation of Drug-like Molecules through...

Metadynamics is an important enhanced sampling technique in molecular dynamics simulation to efficiently explore potential energy surfaces. The recently developed transition-tempered metadynamics (TTMetaD) has been proven to converge asymptotically without sacrificing exploration of the collective variable space in the early stages of simulations, unlike other convergent metadynamics (MetaD) methods. We have applied TTMetaD to study the permeation of drug-like molecules through a lipid bilayer to further investigate the usefulness of this method as applied to problems of relevance to medicinal chemistry. First, ethanol permeation through a lipid bilayer was studied to compare TTMetaD with nontempered metadynamics and well-tempered metadynamics. The bias energies computed from various metadynamics simulations were compared to the potential of mean force calculated from umbrella sampling. Though all of the MetaD simulations agree with one another asymptotically, TTMetaD is able to predict the most accurate and reliable estimate of the potential of mean force for permeation in the early stages of the simulations and is robust to the choice of required additional parameters. We also show that using multiple randomly initialized replicas allows convergence analysis and also provides an efficient means to converge the simulations in shorter wall times and, more unexpectedly, in shorter CPU times; splitting the CPU time between multiple replicas appears to lead to less overall error. After validating the method, we studied the permeation of a more complicated drug-like molecule, trimethoprim. Three sets of TTMetaD simulations with different choices of collective variables were carried out, and all converged within feasible simulation time. The minimum free energy paths showed that TTMetaD was able to predict almost identical permeation mechanisms in each case despite significantly different definitions of collective variables.