A Predictive Substrate Model for Rat Glutathione S-Transferase 4-4
Molecular modeling techniques have been used to derive a substrate model for class mu rat glutathione S-transferase 4-4 (GST 4-4). Information on regio- and stereoselective product formation of 20 substrates covering three chemically and structurally different classes was used to construct a substra...
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Veröffentlicht in: | Chemical research in toxicology 1995-07, Vol.8 (5), p.649-658 |
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Sprache: | eng |
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Zusammenfassung: | Molecular modeling techniques have been used to derive a substrate model for class mu rat glutathione S-transferase 4-4 (GST 4-4). Information on regio- and stereoselective product formation of 20 substrates covering three chemically and structurally different classes was used to construct a substrate model containing three interaction sites responsible for Lewis acid--Lewis base interactions (IS1, IS2, and IS3), as well as a region responsible for aromatic interactions (IS4). Experimental data suggest that the first protein interaction site (pIS1, interacting with IS1) corresponds with Tyr115, while the other protein interaction sites (pIS2 and pIS3) probably correspond with other Lewis acidic amino acids. All substrates exhibited positive molecular electrostatic potentials (MEPs) near the site of conjugation with glutathione (GSH), as well as negative MEP values near the position of groups with Lewis base properties (IS1, IS2, or IS3), which interact with pIS1, pIS2, or pIS3, respectively. Obviously, complementarity between the MEPs of substrates and protein in specific regions is important. The substrate specificity and stereoselectivity of GST 4-4 are most likely determined by pIS1 and the distance between the site of GSH attack and Lewis base atoms in the substrates which interact with either pIS2, pIS3, or a combination of these sites. Interaction between aromatic regions in the substrate with aromatic amino acids in the protein further stabilizes the substrate in the active site. The predictive value of the model has been evaluated by rationalizing the conjugation to GSH of 11 substrates of GST 4-4 (representing 3 classes of compounds) which were not used to construct the model. All known metabolites of these substrates are explained with the model. As the computer-aided predictions appear to correlate well with experimental results, the presented substrate model may be useful to identify new potential GST 4-4 substrates. |
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ISSN: | 0893-228X 1520-5010 |
DOI: | 10.1021/tx00047a004 |