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(Structural Classification of Proteins) database. For purposes of the above algorithms
and classifications, however, domains are defined as proteins or regions of proteins
having a common evolutionary origin; flexibility is not a consideration. Indeed most
small and medium sized proteins, such as those prevalent in the Hinge Atlas, consist of a
single domain. Therefore the problem of finding flexible hinges is not solved by finding
domain boundaries as defined for these methods. Schlessinger et al[39] developed a
method to predict B-factors from sequence, but it is not clear that B-factors obtained in
this way would yield accurate flexibility predictions[40, 41]. In light of the limitations of
existing methods, the prediction of domain hinges from sequence is considered an open
problem[33].
In this article we focus on the characterization of these hinges based on sequence. To
that end, we compiled the Hinge Atlas, a manually annotated dataset of hinge bending
motions, as well as a separate computer annotated dataset, both available for further
studies. The Hinge Atlas has several applications. First, the statistical properties of
hinges can be studied (composition, sequence correlations, coincidence with active sites,
etc). Second, it can be used to benchmark hinge prediction programs. Third, by
homology hinge annotations could potentially be transferred to proteins where the
existence and location of a hinge are unknown. Fourth, the annotations could
conceivably be used in future protein motion prediction programs. The first application
was of most interest to us in the current work.
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