A New Program for Optimizing Periodic Boundary Models of Solvated Biomolecules (PBCAID)
Simulations of solvated macromolecules often use
periodic lattices to account for long-range electrostatics
and to approximate the surface effects
of bulk solvent.
The large percentage of solvent molecules in such
models (compared to macromolecular atoms) makes these
procedures computationally expensive. The cost can
be reduced by using periodic cells containing an optimized number
of solvent molecules (subject to a minimal distance between
the solute and the periodic images).
We introduce an easy-to-use program ``PBCAID'' to initialize and optimize
a periodic lattice specified as one of several known space-filling polyhedra.
PBCAID reduces the volume of the periodic cell
by finding the solute rotation that
yields the smallest periodic cell dimensions.
The algorithm examines rotations by using only a subset of
surface atoms to measure solute/image distances, and by
optimizing the distance between the solute and the periodic cell surface.
Once the cell dimension is optimized,
PBCAID incorporates a procedure
for solvating the domain with water by filling
the cell with a water lattice derived from an ice
structure scaled to the bulk density of water.
Results show that PBCAID can optimize system volumes by 20 to 70%
and lead to computational savings in the nonbonded computations from
reduced solvent sizes.
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