
Protein sidechain
modeling in
YASARA
YASARA Structure routinely predicts protein
sidechain conformations ('rotamers'), ranging from single point
mutations to complete homology
models:
 Protein sidechain rotamers are strongly
influenced by the
backbone conformation[1]. YASARA therefore uses the φ and ψ
dihedral
angles to extract the preferred rotamers and the associated
probabilities from a backbone dependent rotamer library[2].
 Based on the available rotamers, YASARA
determines which
sidechains can potentially influence each other and builds a graph of
interacting residues (top half of the figure on right).
 Using a fast repulsive energy function and
deadend
elimination, the complexity of the graph is reduced significantly
(bottom half of the figure on the right). Finally, the remaining graph
portions are further broken down to sets of biconnected components,
which are small enough to be solved by exhaustive enumeration[3].
 The repulsive energy function used in the
previous step
works very well for those sidechains that interact mainly via
repulsive Van der Waals forces, i.e. the hydrophobic residues in the
core. To capture the complex electrostatic interactions on the surface,
YASARA performs another optimization round that explicitly considers
electrostatic and solvation effects, as well as subtle packing
preferences (via multidimensional
knowledge based potentials) and
deviations from the idealized rotamer geometry.
 pH dependent sidechain interactions with
ligands are fully accounted for, as are
unusual
amino acids.
 Backbone dependent sidechain conformations can
alternatively be extracted directly from a
nonredundant subset of the PDB, an approach used for example by the Fleksy docking program.
R E F E R E N C E S
[1] The use of positionspecific
rotamers in model building by homology
Chinea G, Padron G, Hooft RW, Sander C, Vriend G (1995) Proteins 23, 415421
[2] Bayesian statistical analysis of
protein sidechain rotamer preferences
Dunbrack RL Jr., Cohen FE (1997) Protein
Sci. 6,16611681
[3] A
graphtheory algorithm for
rapid protein sidechain prediction
Canutescu AA, Shelenkov AA and Dunbrack RL Jr. (2003), Protein Sci. 12,20012014.
