Chemistry Reference
In-Depth Information
MD simulations can yield mean square displacement of groups of atoms and
velocity autocorrelation functions; analysis of energy components; including
interactions between user-defined groups of atoms; root mean square deviations
(rmsd) between a reference structure and a trajectory; complete rmsd matrix of a
trajectory against itself or against another trajectory; analysis of the orientation of
solvent molecules around solutes; radial distribution functions; rmsd of pairs of
distances; hydrogen bond analysis; analysis of formation and breaking of bridges;
chemical shifts; analysis of orientation of solvent molecules; ramachandran plots;
positional root-mean-square fluctuations and radius of gyration of sets of atoms.
When entropic contribution and solvation effects among others are not
considered, many demerits associated with scoring functions could be avoided
via
MD. It is possible to study effects of explicit solvent molecule as well as obtain
different thermodynamic parameters (interaction energies, entropies,
etc
) using
MD. This offers a widely applied computational method for investigating
macromolecules. Although computationally expensive, there are numerous quite
rigorous MD-based methods for determining binding affinities (free energy
perturbation (FEP), thermodynamic integration (TI)) [364-366].
Effectively, MD can used to account explicitly for the effect of solvent molecules
on protein-ligand complexes. However, for receptor flexibility it is more difficult
in conventional docking. It is also used for refinement of experimentally derived
structures. MD is now a well-established molecular technique. However although
the core concepts in MD are now mature there is still continuous improvements in
related innovations and improvements in force field models. MD is also supported
by advances in high performance computing and graphic processor units making
computational demands no longer a limiting factor.
Representative simplified MD approaches are Molecular mechanics/Poisson-
Boltzmann surface area (MM/PBSA) method and linear interaction energy
method (LIE). With a number of simple approximations, MM/PBSA and LIE can
provide relatively good binding affinity at a moderate computational cost.
MM/PBSA approximates binding affinities combining molecular mechanics and
continuum solvent approaches with difficulty, however, to predict the entropic
contribution to the binding affinity. LIE is a semi-empirical MD approach which
