Exploring Free Energy Landscapes of Large Conformational
Changes: Molecular Dynamics with Excited Normal Modes
- Publication date
- Publisher
Abstract
Proteins
are found in solution as ensembles of conformations in
dynamic equilibrium. Exploration of functional motions occurring on
micro- to millisecond time scales by molecular dynamics (MD) simulations
still remains computationally challenging. Alternatively, normal mode
(NM) analysis is a well-suited method to characterize intrinsic slow
collective motions, often associated with protein function, but the
absence of anharmonic effects preclude a proper characterization of
conformational distributions in a multidimensional NM space. Using
both methods jointly appears to be an attractive approach that allows
an extended sampling of the conformational space. In line with this
view, the MDeNM (molecular dynamics with excited normal modes) method
presented here consists of multiple-replica short MD simulations in
which motions described by a given subset of low-frequency NMs are
kinetically excited. This is achieved by adding additional atomic
velocities along several randomly determined linear combinations of
NM vectors, thus allowing an efficient coupling between slow and fast
motions. The relatively high-energy conformations generated with MDeNM
are further relaxed with standard MD simulations, enabling free energy
landscapes to be determined. Two widely studied proteins were selected
as examples: hen egg lysozyme and HIV-1 protease. In both cases, MDeNM
provides a larger extent of sampling in a few nanoseconds, outperforming
long standard MD simulations. A high degree of correlation with motions
inferred from experimental sources (X-ray, EPR, and NMR) and with
free energy estimations obtained by metadynamics was observed. Finally,
the large sets of conformations obtained with MDeNM can be used to
better characterize relevant dynamical populations, allowing for a
better interpretation of experimental data such as SAXS curves and NMR spectra