The classification of interfaces between transient, permanent, and obligate, as well as within interfaces as core and rim structures, has been extensively studied from a theoretical standpoint.
For a classification of snakes, see snake.
Using the new feature-based interface similarity, we develop a hierarchical classification of protein interfaces and applied it to a set of 2,806×2,806 interface pairs.
Using the geometrically nonlinear theory of the martensitic transformation, a systematic classification of the interfaces is proposed that is based on crystalline symmetry and predicts the observed geometry of both straight and curved junction planes of the "herring-bone" microstructure.
They have divided protein domain-domain interfaces into different groups (face types), resulting in SCOPPI, a structural classification of protein-protein interfaces [12].
Interestingly, when analyzing the converted similarity measure values calculated for the entire set of 2,806×2,806 interface pairs (which is later used for hierarchical classification; see next section Structure classification of interaction interfaces under Methods), we found that the measure obeys the triangle inequality rule.
Our next goal was to construct a proof-of-concept of a biologically meaningful classification of the interaction interfaces, using the feature-based similarity measure.
Finally, we employ one of the new feature-based similarity measures to (i) define a structure-based hierarchical classification of protein interaction interfaces on a large scale, and (ii) design a data structure for the interface search and retrieval problem.
In particular, classification of the interface light associated with self-organized QDs is given in terms of X-, Y-, and Z-modes.
In addition, we have demonstrated that the high coverage allows generating a comprehensive SCOP-like hierarchical classification of similar interaction interfaces as well as efficiently solving the interface search and retrieval problem.
