title: Dehydrogenation of the indoline-containing drug 4-chloro-N-(2-methyl-1-indolinyl)-3-sulfamoylbenzamide (indapamide) by CYP3A4: correlation with in silico predictions.
abstract: 4-Chloro-N-(2-methyl-1-indolinyl)-3-sulfamoylbenzamide (indapamide), an indoline-containing diuretic drug, has recently been evaluated in a large Phase III clinical trial (ADVANCE) with a fixed-dose combination of an angiotensin-converting enzyme inhibitor, perindopril, and shown to significantly reduce the risks of major vascular toxicities in people with type 2 diabetes. The original metabolic studies of indapamide reported that the indoline functional group was aromatized to indole through a dehydrogenation pathway by cytochromes P450. However, the enzymatic efficiency of indapamide dehydrogenation was not elucidated. A consequence of indoline aromatization is that the product indoles might have dramatically different therapeutic potencies. Thus, studies that characterize dehydrogenation of the functional indoline of indapamide were needed. Here we identified several indapamide metabolic pathways in vitro with human liver microsomes and recombinant CYP3A4 that include the dehydrogenation of indapamide to its corresponding indole form, and also hydroxylation and epoxidation metabolites, as characterized by liquid chromatography/mass spectrometry. Indapamide dehydrogenation efficiency (V(max)/K(m)=204 min/mM) by CYP3A4 was approximately 10-fold greater than that of indoline dehydrogenation. In silico molecular docking of indapamide into two CYP3A4 crystal structures, to evaluate the active site parameters that control dehydrogenation, produced conflicting results about the interactions of Arg212 with indapamide in the active site. These conflicting theories were addressed by functional studies with a CYP3A4R212A mutant enzyme, which showed that Arg212 does not seem to facilitate positioning of indapamide for dehydrogenation. However, the metabolites of indapamide were precisely consistent with in silico predictions of binding orientations using three diverse computer methods to predict drug metabolism pathways.
authors.affiliation: Lead Generation Group, Department of Pharmacokinetics, Dynamics, and Drug Metabolism, Global Research and Development, Pfizer, Inc., Groton, Connecticut, USA.
authors.forename: Hao
authors.initials: H
authors.lastname: Sun
authors.forename: Chad
authors.initials: C
authors.lastname: Moore
authors.forename: Patrick M
authors.initials: PM
authors.lastname: Dansette
authors.forename: Santosh
authors.initials: S
authors.lastname: Kumar
authors.forename: James R
authors.initials: JR
authors.lastname: Halpert
authors.forename: Garold S
authors.initials: GS
authors.lastname: Yost
mesh_terms: D001711:Biotransformation; D002851:Chromatography, High Pressure Liquid; D051544:Cytochrome P-450 CYP3A / Q000378:metabolism*; D004232:Diuretics / Q000493:pharmacokinetics*; D006801:Humans; D006865:Hydrogenation; D007190:Indapamide / Q000493:pharmacokinetics*; D009682:Magnetic Resonance Spectroscopy; D013058:Mass Spectrometry; D008862:Microsomes, Liver / Q000201:enzymology
chemical_list: D004232:Diuretics; D051544:Cytochrome P-450 CYP3A; C510163:CYP3A4 protein, human; D007190:Indapamide