Automatic generation of 3D motifs for classification of protein binding sites

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This paper presents the first algorithmic pipeline for the fully automatic generation of binding site 3D motifs. The pipeline includes protein clustering based on computational alignment of the 3D structure of their binding sites and generation of discriminative consensus 3D patterns. Validation by a biochemist (2nd author) demonstrates the produced 3D patterns have biological significance and therefore can be called 3D motifs. Results show these motifs can be used for protein annotation and the even more challenging task of detecting proteins which have evolved convergently.