Nonlinear Time‐course of Aldehyde Oxidase
Authors: Abbasi Armina , Jones Jeffrey 
Published: June 2021

Many promising drug candidates metabolized by Aldehyde Oxidase (AOX) fail during the clinical trial due to underestimation of their clearance. AOX is species specific and this makes traditional allometric studies a poor choice for estimating human clearance. In this study, we have monitored metabolite formation of six AOX substrates, O6‐benzylguanine (O6BG), DACA, zaleplon, phthalazine, BIBX1382 and zoniporide in purified expressed human aldehyde oxidase (HAO) using LC/MS/MS over a 240‐minute time period. Numerical data fitting to three different kinetic schemes was performed using Mathematica software and the goodness of fit was assessed by Akaike value. Figure 1 shows the comparison between fitting of data for the substrate O6BG to three different schemes, namely Michaelis‐Menten (MM), Dead model and Modulated activity model (MAM). Based on the Akaike values the third kinetic scheme fit the data more closely and therefore was the model that we chose for our further studies.

Our data shows that the total velocity for substrates becomes slower than the initial velocity by 3.1, 6.5, 2.9, 32.2, 2.7 and 0.2 fold for O6BG, DACA, zaleplon, phthalazine, BIBX1382 and zoniporide respectively in HAO while the Km remains constant. Two different hypothesis were considered for this decrease in enzymatic linearity over time. First, reactive oxygen species produced during the catalytic cycle may cause enzyme inactivation. Second, the enzyme's reductive half reaction is slow to reduce oxygen, and the fast rate is an initial rate prior to the reduction of the enzyme.

The first hypothesis was tested by using Super oxide dismutase (SOD) and catalase to remove the reactive oxygen species. However, the results showed no significant effect on enzyme linearity with or without SOD and catalase. The second hypothesis was tested by using 5‐Nitroquinoline (5NQ), an oxidative and reductive substrate of AOX. Recently it has been proposed that the substrate reduction happens on a different site in AOX and it is assumed to be in the Flavin site. Therefore, by using 5NQ, we have introduced competition between oxygen and the reductive substrate for the Flavin site and therefore disrupting the electron shuttling. The data is consistent with this hypothesis and using 5NQ reduces the enzymatic activity and increases enzyme's nonlinearity.

If the oxidation of the enzyme is the rate limiting step, then all the k5 values in the Modulate activity model should be the same but our data shows up to 3‐fold difference between k5 values of different substrates. This observation can be traced back to substrate inhibition that happens in substrates such as DACA and phthalazine. We are proposing that for such substrates, the second substrate molecule would bind to the reduction site and therefore lowering the k5 value further down.

Overall, the main goal of this paper is to show that almost all AOX‐catalyzed reactions are nonlinear over time, and that ignoring this leads to an underestimation of clearance. We believe that the constant under‐prediction of drug clearance by AOX is due to the rapid slowing of the reaction rate once the reaction is started and that even short incubations would not lead to an accurate determination of the kcat.

Support or Funding Information

This work was supported by the National Institute of General Medical Sciences [GM100874].

This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.