  Current all-atom potential based molecular dynamics (MD) allow the
identification of a protein's functional motions on a wide-range of
time-scales, up to few tens of ns. However, functional large scale motions of
proteins may occur on a time-scale currently not accessible by all-atom
potential based molecular dynamics. To avoid the massive computational effort
required by this approach several simplified schemes have been introduced. One
of the most satisfactory is the Gaussian Network approach based on the energy
expansion in terms of the deviation of the protein backbone from its native
configuration. Here we consider an extension of this model which captures in a
more realistic way the distribution of native interactions due to the
introduction of effective sidechain centroids. Since their location is entirely
determined by the protein backbone, the model is amenable to the same exact and
computationally efficient treatment as previous simpler models. The ability of
the model to describe the correlated motion of protein residues in
thermodynamic equilibrium is established through a series of successful
comparisons with an extensive (14 ns) MD simulation based on the AMBER
potential of HIV-1 protease in complex with a peptide substrate. Thus, the
model presented here emerges as a powerful tool to provide preliminary, fast
yet accurate characterizations of proteins near-native motion.
