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In this work we first introduce hNM, a family of mostly novel hinge predictors based on
normal modes. The first member of this family, which we call hNMa for simplicity,
posits that the minima of the normalized squared normal mode fluctuations should
coincide with hinges. This in itself is not novel but we show that for the case of domain
hinge bending, the first (rather than any higher) normal mode is most informative,
addressing a point of some debate in the literature. A second, novel, method designated
hNMb detects the most rigid, continuous structural domain through segmentation of
normal mode motional correlation matrices. Subsidiary predictors, hNMc and hNMd,
use similar information to find additional hinges. To benchmark the method and compare
and integrate it with others, we use the Hinge Atlas Gold, a set of proteins with carefully
annotated hinge locations.
We then turn our attention to existing methods, for purposes of comparison and
integration. We review the following hinge predictors:
StoneHinge recognizes hinges as flexible regions of the protein main chain intervening
between the two largest rigid domains (of at least 20 residues each), as defined by
ProFlex constraint-counting analysis of the protein’s covalent and non-covalent bond
network. Importantly, StoneHinge has some ability to detect proteins that do not move
by hinge bending, but rather fall into some other classification[9]. In the latter case,
hinge prediction results from other predictors are likely to be inapplicable.
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