S9 Stability Assay

Understand the metabolism of your compounds by using our S9 stability assay to measure in vitro intrinsic clearance or to identify metabolites formed.

The S9 stability screening service is one of Cyprotex's in vitro ADME screening services. Cyprotex delivers consistent, high quality data with cost-efficiency that comes from a highly automated approach.

Measurement of in vitro intrinsic clearance using S9 fraction:

• The liver is the main site of drug metabolism and therefore in vitro studies are predominantly focused on using hepatocytes or subcellular hepatic fractions such as microsomes or S9.
• Subcellular fractions are easy to prepare, use and store enabling cost efficiencies over whole cell models.
• The S9 fraction (post-mitochondrial supernatant fraction) consists of microsomes and cytosol.
• The advantage of using S9 fraction for in vitro screening is that it contains a wide variety of both phase I and phase II enzymes.
• S9 can be supplemented with cofactors such as UDPGA and PAPS to investigate Phase II metabolic pathways.

Follow on metabolite profiling studies:

Cyprotex's S9 Stability assay can be extended to profile the main breakdown products that are formed. Options include a low resolution analysis to identify whether a metabolite is formed, or a cross species comparison to identify potential differences in metabolism which could in turn help to interpret pharmacology and toxicity data. We can also perform ion-transition analysis in order to understand the derivation of metabolites.

Please refer to our Metabolite Profiling and Identification section for further details.

3 compounds were incubated with mouse liver S9, UDPGA and PAPS in the presence and absence of NADPH. Figure 1 illustrates the dependence of midazolam and testosterone on Phase I metabolism prior to metabolism by Phase II enzymes.

The liver is the main organ of drug metabolism in the body. Subcellular fractions are useful in vitro models of hepatic clearance as they contain many of the drug metabolizing enzymes found in the liver. The two main subcellular fractions used for drug metabolism studies are microsomes and S9 fraction (post-mitochondrial supernatant fraction). Both are easy to prepare and can be stored for long periods of time. They are easily adaptable to high-throughput screens which enable large numbers of compounds to be screened rapidly and inexpensively. S9 fraction consists of both microsomal and cytosolic enzymes, and so contains a wide variety of both Phase I and Phase II enzymes. It can be supplemented with cofactors such as UDPGA and PAPS to investigate Phase II metabolic pathways.

The S9 fraction is incubated with the test compound at 37°C in the presence of the co-factor(s) which initiate the reaction. The reaction is terminated by the addition of acetonitrile. Following centrifugation, the supernatant is diluted into water containing internal standard and analyzed on the LC-TOF-MS. The disappearance of test compound is monitored over a 45 minute time period. An example of a typical depletion profile is shown in Figure 2.

The ln peak area ratio (compound peak area/internal standard peak area) is plotted against time and the gradient of the line determined.

In contrast to hepatocytes, both S9 fraction and microsomes are subcellular fractions which are adaptable to high-throughput screening and enable large numbers of compounds to be screened inexpensively. One of the most common reasons for evaluating S9 is if the compound of interest is metabolized by cytosolic enzymes and a higher throughput, more convenient screen, than hepatocytes, is required.

Investigating metabolism in S9 tends to be much less common than other drug metabolizing systems such as microsomes and hepatocytes. Often S9 incubations are used for qualitative purposes to identify if a metabolite is formed by cytosolic enzymes. Alternatively, compounds may be ranked in terms of their intrinsic clearance values. Unless the compound is a pro-drug, very highly cleared compounds are generally considered to be unfavourable as they are likely to be rapidly cleared in vivo resulting in a short duration of action. Classification bands can be used to categorize compounds into low, medium or high clearance, although this does not tend to be common practice with S9 fraction. Estimated CL_int classification bands for human in Table 1 are calculated from a rearrangement of the well stirred model² detailed in the following equation assuming an extraction ratio (E) of 0.3 and 0.7 for the low and high boundaries, respectively. This can then be scaled to intrinsic clearance (µL/min/mg protein) using the relevant liver weights³ (obtained from the literature) and S9 protein concentration (measured at Cyprotex).

where CL_H = E x Q_H

_{QH = liver blood flow (mL/min/kg)²
E = Extraction Ratio
CLH = Hepatic Clearance (mL/min/kg)
fu = fraction unbound in plasma (assumed at 1)}

Two positive control compounds are included for each species, midazolam and 7-hydroxycoumarin. Midazolam is the marker for Phase I metabolism (Phase I metabolism is prerequisite Phase II metabolism) and 7-hydroxycoumarin is the marker for Phase II metabolism (predominantly metabolized by glucuronidation and sulphation).

A control incubation is performed in the absence of cofactor to reveal any chemical instability or non-cofactor dependent enzymatic degradation.

A control is included that contains all reaction components with the exception of the test compound. This control identifies any potential interfering component which may affect the analysis.

Cyprotex can include a range of different cofactors in the S9 stability assay (i.e. NADPH, UDPGA, PAPS or GSH). In reality, the choice of cofactor is limited to the one most relevant to the investigation. For example it may only necessary to include NADPH if Phase I cytosolic metabolism is being investigated or if glucuronidation is important then the assay may be restricted to NADPH and UDPGA.

_{1) Plant N. (2004) Drug Discovery Today 9(7); 328-336
2) Houston JB. (1994) Biochem Pharmacol 47(9); 1469-1479
3) Davies B. and Morris T. (1993) Pharma Res 10(7); 1093-1095}