The evolution of function in strictosidine synthase‐like proteins

Abstract

The exponential growth of sequence data provides abundant information for the discovery of new enzyme reactions. Correctly annotating the functions of highly diverse proteins can be difficult, however, hindering use of this information. Global analysis of large superfamilies of related proteins is a powerful strategy for understanding the evolution of reactions by identifying catalytic commonalities and differences in reaction and substrate specificity, even when only a few members have been biochemically or structurally characterized. A comparison of >2500 sequences sharing the six-bladed β-propeller fold establishes sequence, structural and functional links among the three subgroups of the functionally diverse N6P superfamily: the arylesterase-like and senescence marker protein-30/gluconolactonase/luciferin-regenerating enzyme-like (SGL) subgroups, representing enzymes that catalyze lactonase and related hydrolytic reactions, and the so-called “strictosidine synthase-like” (SSL) subgroup. Metal-coordinating residues were identified as broadly conserved in the active sites of all three subgroups except for a few proteins from the SSL subgroup, which have been experimentally determined to catalyze the quite different strictosidine synthase (SS) reaction, a metal-independent condensation reaction. Despite these differences, comparison of conserved catalytic features of the arylesterase-like and SGL enzymes with the SSs identified similar structural and mechanistic attributes between the hydrolytic reactions catalyzed by the former and the condensation reaction catalyzed by SS. The results also suggest that despite their annotations, the great majority of these >500 SSL sequences do not catalyze the SS reaction; rather, they likely catalyze hydrolytic reactions typical of the other two subgroups instead. This prediction was confirmed experimentally for one of these proteins.

Inference of Functional Properties from Large-scale Analysis of Enzyme Superfamilies

“…Even a reasonable fallback position requires the development of new strategies for identifying the few experiments that could be most useful for validation of large-scale computational predictions. As illustrated here and elsewhere (44,45), protein similarity networks represent one way to generate the context needed for choosing those experiments and interpreting the results.…”

Protein Similarity Networks Reveal Relationships among Sequence, Structure, and Function within the Cupin Superfamily

“…They presented protein similarity networks (PSNs) to fulfill this need [22]. PSNs have contributed to our understanding of a number of large groups of proteins including the enolase superfamily [23], the ePK-like superfamily [24], glutathione transferases [25], [26], strictosidine synthase-like proteins [27], cysteine peptidases [28], and proteins used in algal metal transport [29]. These studies have yielded meaningful insights, validated PSN methodology, and provided an understanding of the caveats and limitations of PSNs.…”

Subunit composition of a DEG/ENaC mechanosensory channel of Caenorhabditis elegans

“…First, although MEC-6 did not affect MEC-4 abundance in Xenopus oocytes, loss of mec-6 in vivo led to a drastic reduction in MEC-4::YFP expression in the TRNs (8). Second, studies in Drosophila melanogaster found that, although DEG/ENaC proteins needed for mechanosensation were present (14-18), obvious MEC-6-like proteins were not (19). Third, we wondered about the importance of the puncta and the apparent colocalization of the proteins in them, because in vivo electrophysiological studies of the TRNs (5) showed that the estimated number of active channels equaled the number of puncta, but single channels were unlikely to be visible by fluorescence microscopy.…”