ar9b00473_si_001.pdf (2.67 MB)
Taming Rugged Free Energy Landscapes Using an Average Force
journal contribution
posted on 2019-11-01, 20:44 authored by Haohao Fu, Xueguang Shao, Wensheng Cai, Christophe ChipotConspectusThe observation
of complex structural transitions in biological
and abiological molecular objects within time scales amenable to molecular
dynamics (MD) simulations is often hampered by significant free energy
barriers associated with entangled movements. Importance-sampling
algorithms, a powerful class of numerical schemes for the investigation
of rare events, have been widely used to extend simulations beyond
the time scale common to MD. However, probing processes spanning milliseconds
through microsecond molecular simulations still constitutes in practice
a daunting challenge because of the difficulty of taming the ruggedness
of multidimensional free energy surfaces by means of naive transition
coordinates. To address this limitation, in recent years we have elaborated
importance-sampling methods relying on an adaptive biasing force (ABF).
In this Account, we review recent developments of algorithms aimed
at mapping rugged free energy landscapes that correspond to complex
processes of physical, chemical, and biological relevance. Through
these developments, we have broadened the spectrum of applications
of the popular ABF algorithm while improving its computational efficiency,
notably for multidimensional free energy calculations. One major algorithmic
advance, coined meta-eABF, merges the key features of metadynamics
and an extended Lagrangian variant of ABF (eABF) by simultaneously
shaving the barriers and flooding the valleys of the free energy landscape,
and it possesses a convergence rate up to 5-fold greater than those
of other importance-sampling algorithms. Through faster convergence
and enhanced ergodic properties, meta-eABF represents a significant
step forward in the simulation of millisecond-time-scale events. Here
we introduce extensions of the algorithm, notably its well-tempered
and replica-exchange variants, which further boost the sampling efficiency
while gaining in numerical stability, thus allowing quantum-mechanical/molecular-mechanical
free energy calculations to be performed at a lower cost. As a paradigm
to bridge microsecond simulations to millisecond events by means of
free energy calculations, we have applied the ABF family of algorithms
to decompose complex movements in molecular objects of biological
and abiological nature. We show here how water lubricates the shuttling
of an amide-based rotaxane by altering the mechanism that underlies
the concerted translation and isomerization of the macrocycle. Introducing
novel collective variables in a computational workflow for the rigorous
determination of standard binding free energies, we predict with utmost
accuracy the thermodynamics of protein–ligand reversible association.
Because of their simplicity, versatility, and robust mathematical
foundations, the algorithms of the ABF family represent an appealing
option for the theoretical investigation of a broad range of problems
relevant to physics, chemistry, and biology.