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structure of the anchor must be highly conserved. Peptide fragments at the end of
MHC binding groove with mean backbone Cα RMSD within 0.15 ± 0.14 Å (Tong
et al. 2004) are ideal for such purpose.
A fast soft-interaction energy function (Fernández-Recio, Totrov, and Abagyan
2002) is adopted to model each probe to the receptor. This is performed using an
Internal Coordinate Mechanics (ICM; Abagyan and Totrov 1999) global
optimization algorithm; with flexible ligand interface side chains and a grid map
representation of the receptor energy localized to small cubic regions of 1.00-Å
radius from the backbone of each probe. Each probe performs a random walk within
their respective grid map. At each random step, the side-chain torsions were changed
using a Biased Monte Carlo procedure, which begins by pseudo-randomly selecting
a set of torsion angles in the probe and subsequently finding the local energy
minimum about those angles. New conformations are adopted upon satisfaction of
the Metropolis criteria with probability min(1, exp[-∆
G/RT
]), where R is the
universal gas constant and
T
is the absolute temperature of the simulation. Loose
restraints were imposed on the positional variables of the ligand molecule to keep it
close to the starting conformation. The stimulation temperature was set to 300 K.
The optimal energy function used during stimulations consisted of the internal
energy of the probe and the intermolecular energy based on the same optimized
potential maps used in the docking step:
solv
el
E
=
E
Hvw
+
E
Cvw
+ 2.16
E
+ 2.53
E
hb
+ 4.35
E
hp
+ 0.20
E
solv
(2)
The internal energy included internal van der Waals interactions, hydrogen
bonding and torsion energy calculated with ECEPP/3 parameters, and the Coulomb
electrostatic energy with a distance-dependent dielectric constant (
e
=4
r
). The
configurational entropy of sidechains and the surface-based solvation energy were
included in the final energy to select the best-refined solutions.
3.4.3.2 Loop Closure of Center Residues
In this stage, an initial conformation of the central loop is generated by satisfaction
of spatial constraints (Sali and Blundell 1993) based on the allowed subspace for
backbone dihedrals in accordance with the conformations of peptides docked into the
ends of the binding groove. This is performed in three steps: (i) Distance and
dihedral angle restraints on the entire peptide sequence are derived from its
alignment with the sequences of probes docked into the binding groove. (ii) The
restraints on spatial features of the unknown center residues are derived by
extrapolation from the known 3D structures of probes in the alignment, expressed as
probability density functions. Stereochemical restraints include bond distances, bond
angles, planarity of peptide groups and side-chain rings, chiralities of Cα atoms and
sidechains, van der Waals contact distances and the bond lengths, bond angles, and
dihedral angles of cysteine disulfide bridges. (iii) Spatial restraints on the unknown
center residues are satisfied by optimization of the molecular probability density
function using variable target function technique that applies the conjugate gradients
algorithm to positions of all nonhydrogen atoms.
