Abstract

Author SummaryCytosolic glutathione transferases (cytGSTs) are a large and diverse superfamily of enzymes that have important roles in metabolism and defense against oxidative damage. They have been studied for several decades but because of the synthetic nature of the chemicals used to test these proteins to determine if they have cytGST activity, little is known about the physiological reactions and roles of cytGSTs. In this large, collaborative study, we constructed networks where more than 13,000 cytGST sequences were grouped by sequence similarity and then used these networks to prioritize new targets for experimental characterization in relatively unexplored regions of the superfamily. We report here experimental results confirming GST-like activity for 82 of them, along with 37 new three-dimensional molecular structures determined for 27 targets. These new data, along with experimental data previously reported in the literature, were painted onto the networks to generate a global view of their sequence-structure-function relationships. The results show how proteins of both known and unknown function relate to each other across the entire superfamily and illuminate the complex ways in which their variations in sequence and structure affect our ability to predict unknown functional properties.

Highlights

  • The cytosolic glutathione transferases, with several Enzyme Commission (E.C.) [1] numbers, principally 2.5.1.18, comprise one of four major groups of enzymes known to catalyze a general reaction involving nucleophilic attack by reduced glutathione (GSH) on compounds that contain an electrophilic carbon, nitrogen, oxygen, or sulfur atom (Reaction (1)) [2,3].GSHzR{X?GSRzHX ð1ÞEach group represents a different superfamily and/or structural fold; the cytGST superfamily described in this work is the largest of these four groups

  • Division of the global level 1 network into 35 subgroups allows more detailed views (Figure 2) of these relationships and provides a foundation for assignment of unknowns either to extant classes or to new classes suggested by these subgroupings. (See Table S2 for counts of representative nodes and member sequences in these subgroups.) Since the canonical classes describe only general functional or other properties resulting from previous experimental studies, we provide a version of the level 2 network to which experimentally determined cytGST reaction types have been mapped (Figure 3)

  • This network view includes a mapping of new experimental results obtained in this study that confirms cytGST-like function for 82 unknowns across the superfamily sequence space and indicates on the networks where the 37 new structures for 27 protein targets occur. (See Table S3 for experimentally determined cytGST reaction types in representative nodes, Table S4 for the substrates of experimentally determined cytGSTs, and Table S5 for a full list of cytGST structures mapped onto the networks described in this study.)

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Summary

Introduction

The cytosolic glutathione transferases (cytGSTs), with several Enzyme Commission (E.C.) [1] numbers, principally 2.5.1.18, comprise one of four major groups of enzymes known to catalyze a general reaction involving nucleophilic attack by reduced glutathione (GSH) on compounds that contain an electrophilic carbon, nitrogen, oxygen, or sulfur atom (Reaction (1)) [2,3].GSHzR{X?GSRzHX ð1ÞEach group represents a different superfamily and/or structural fold; the cytGST superfamily described in this work is the largest of these four groups. The cytGSTs are soluble proteins that occur in a huge group of proteins that share overall structure similarity, the ‘‘thioredoxin-like fold’’ [4] that we hereafter refer to as the ‘‘thioredoxin fold.’’ The cytGST enzymes play many important roles in the cell, including metabolism of endogenous compounds, detoxification of xenobiotics, and defense against oxidative stress. Some of these proteins are of particular interest as targets of antiasthmatic and cancer drugs [2,3,5]. PLOS Biology | www.plosbiology.org cytGST Sequence-Structure-Function Relationships

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