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Numerous valuable contributions have been made to the computational prediction of
protein hinges. If the structure has been solved in two different conformations, then the
hinge can be identified by visual inspection (Flores et al., submitted) or by use of
FlexProt[26] or DynDom. A much more difficult problem arises when only one
conformation is known. In an early contribution, Janin and Wodak[7] developed a
domain interface area calculation method. The FIRST algorithm[15, 18, 19, 32, 62] uses
graph theory to economically identify rigid substructures. FRODA uses geometric
simulation under constraints assigned by FIRST to generate alternate conformations of
proteins which have been shown to be consistent with crystallographic and NMR data for
certain proteins[60], but this ignores many important intra-molecular interactions and is
more useful for loop motions than for domain hinge bending. Similarly, DisEMBL
successfully predicts flexible or disordered regions in proteins using a neural network,
but this local flexibility alone is not a very strong predictor of hinges (Flores et al.,
submitted). The TLSMD[63] procedure analyzes the distribution of atomic displacement
parameters associated with the mean position of each atom, and generates Translation-
Libration-Screw descriptions of rigid groups of atoms, but has no means of identifying
the group responsible for the principal hinge bending mechanism, and is limited to X-ray
crystal structures of sufficient resolution. The Gaussian Network Model[64] (GNM, see
Chapter 4 for further details) is an approximate algorithm for normal mode extraction
widely used in flexibility prediction. FlexOracle is a complementary new addition to this
set of tools.
Methods
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