Alexandra M. Schnoes

TL;DR: Today's best protein function prediction algorithms substantially outperform widely used first-generation methods, with large gains on all types of targets, and there is considerable need for improvement of currently available tools.

TL;DR: The results suggest that misannotation in enzyme superfamilies containing multiple families that catalyze different reactions is a larger problem than has been recognized and strategies are suggested for addressing some of the systematic problems contributing to these high levels of misannation.

TL;DR: The Structure-Function Linkage Database (SFLD) as discussed by the authors is a manually curated classification resource describing structure-function relationships for functionally diverse enzyme superfamilies, which can be used to visualize functional trends.

TL;DR: This work examines the experimentally validated annotation of proteins provided by several groups in the GO Consortium, and shows that the distribution of proteins per published study is exponential, with 0.14% of articles providing the source of annotations for 25% of the proteins in the UniProt-GOA compilation.

TL;DR: The discovery of two families of homologous, but stereochemically distinct, MLEs likely provides an example of "pseudoconvergent" evolution of the same function from differenthomologous progenitors within the enolase superfamily, in which different spatial arrangements of active site functional groups and substrate specificity determinants support catalysis of the the same reaction.