Theoretical and Mechanistic Validation of Global Kinetic Parameters of the Inactivation of GABA Aminotransferase by OV329 and CPP-115.

Abstract

((S)-3-Amino-(difluoromethylenyl)cyclopent-1-ene-1-carboxylic acid (OV329) is a recently discovered inactivator of γ-aminobutyric acid aminotransferase (GABA-AT), which has 10 times better inactivation efficiency than its predecessor, CPP-115, despite the only structural difference being an endocyclic double bond in OV329. Both compounds are mechanism-based enzyme inactivators (MBEIs), which inactivate GABA-AT by a similar mechanism. Here, a combination of a variety of computational chemistry tools and experimental methods, including quantum mechanical (QM) calculations, molecular dynamic simulations, progress curve analysis, and deuterium kinetic isotope effect (KIE) experiments, are utilized to comprehensively study the mechanism of inactivation of GABA-AT by CPP-115 and OV329 and account for their experimentally obtained global kinetic parameters kinact and KI. Our first key finding is that the rate-limiting step of the inactivation mechanism is the deprotonation step, and according to QM calculations and the KIE experiments, kinact accurately represents the enhancement of the rate-limiting step for the given mechanism. Second, the present study shows that the widely used simple QM models do not accurately represent the geometric criteria that are present in the enzyme for the deprotonation step. In contrast, QM cluster models successfully represent both the ground state destabilization and the transition state stabilization, as revealed by natural bond orbital analysis. Furthermore, the globally derived KI values for both of the inactivators represent the inhibitor constants for the initial binding complexes (Kd) and indicate the inactivator competition with the substrate according to progress curve analysis and the observed binding isotope effect. The configurational entropy loss accounts for the difference in KI values between the inactivators. The approach we describe in this work can be employed to determine the validity of globally derived parameters in the process of MBEI optimization for given inactivation mechanisms.