Metabolic Stability Models

More recently, other types of QSAR methods have been used to generate predictions for metabolic stability as a general property rather than at the individual enzyme level. For example, recursive partitioning is a powerful 

Recursive partitioning, Bayesian classifier, logisi-tic regression, k-nearest neighbor, support vector machine 

Mixed-integer programming hyperboxes classification, Bayes Network, Naive Bayes, Liblinear, LibSVM, RBF network, SMO, Logistic, IBk, Bagging, Ensemble selection, Logit Boost, LMT, NBTree, Random Forest, DTNB 

N = 470 compounds. Accuracy 82%, precision 76%, recall 75%, kappa = 0.61. An additional test set of 2195 compounds used to show change in predictivity with decreasing Tanimoto similarity. Threshold = 0.7. 

CYP1A2, CYP2C9, CYP3A4 PLS models most predictive, while RT models for CYP2C19 and CYP2D6 were most predictive. 

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Figure 8.6 shows the projection of 1346 compounds from Johnson Johnson on the VolSurf metabolic stability model. The projected compounds are color-coded according to their percentage experimental metabolic stability (%MS) the red color defines compounds with %MS > 95, while the blue color defines compounds with %MS < 40. The figure shows that the great majority of projected compounds with %MS > 95 are predicted to be of medium or high stability for the metabolic activity of the CYP3A4, while compounds with low %MS < 40 are predicted to be unstable. The presence of outliers may be explained by the fact that the experimental %MS of the test set compounds is obtained from the activity of all CYP family enzymes (2C9, 3A4, 2D6 etc.), while the model uses only 3A4 mediated information. 

Figure 8.6. Proiection of 1346 compounds from Johnson, Johnson on the 2D PLS scores plot of the VolSurf metabolic stability model (open grey points). The black line discriminates between unstable and stable compounds in the metabolic stability model projected compounds on the left of the black line are predicted as unstable (%MS < 40), while...

Shen M, Xiao Y, Golbraikh A, Gombar VK, Tropsha A. Development and validation of k-nearest-neighbor QSPR models of metabolic stability of drug candidates. J Med Chem 2003 46 3013-20. 

Bnrsi R, de Gooyer ME, Grootenhuis A, Jacobs PL, van der Louw J, Leysen D. (Q)SAR stndy on the metabolic stability of steroidal androgens. J Mol Graph Modelling 2001 19 552-6. 

Mandagere, A. K., T. N. Thompson, and K. K. Hwang. Graphical model for estimating oral bioavailability of drugs in humans and other species from their Caco-2 permeability and in vitro liver enzyme metabolic stability rates, J. Med. Chem. 2002, 45, 304-311... 

In the following section, the calculation of the VolSurf parameters from GRID interaction energies will be explained and the physico-chemical relevance of these novel descriptors demonstrated by correlation with measured absorption/ distribution/metabolism/elimination (ADME) properties. The applications will be shown by correlating 3D molecular structures with Caco-2 cell permeabilities, thermodynamic solubilities and metabolic stabilities. Special emphasis will be placed on interpretation of the models by multivariate statistics, because a rational design to improve molecular properties is critically dependent on an understanding of how molecular features influence physico-chemical and ADME properties. 

The aim of the present example was to investigate whether the assessment of an in silico model of metabolic stability from a training set of several hundred drugs or drug-like compounds in human CYP3A4 cDNA-expressed microsomal preparations, would offer a suitable approach to predict the metabolic stability of external compounds. 

A simple protocol was used to build the compounds compounds were modeled with the corresponding net charges, after which 2D-3D structure conversion was carried out using the program Concord [21]. The 3D dataset obtained was submitted to the VolSurf program, and principal component analysis (PCA) was applied for chemometric interpretation. No metabolic stability information was applied to the model. 

Such a result appears to be of major interest given that neither any classification of compounds, nor any training information was applied to the PCA model. A more detailed inspection of the score plot in Fig. 17.5 indicates that some compounds are misclassified, although experimental evaluation of these compounds revealed problems with their chemical stability or solubility. Thus, it appears that this model can be used to evaluate the false-positive (or false-negative) experiments. Moreover, it can also be used to evaluate the metabolic stability from the 3D structure of drug candidate prior to experimental measurements. 

This model integrates existing in vitro data, such as Caco-2 permeability (Papp) and metabolic stability in liver S9 or microsomes, to estimate bioavailability as being either low, medium, or high. Oral bioavailability predictions for not only humans but also other species can be made by using the metabolic stability values of drugs in liver microsomal enzyme preparations from that species. A premise of this model is that metabolic clearance is more important than renal or biliary clearance in determining bioavailability. However, despite the lack of in vitro renal... 

Incorporation of fluorine at a site adjacent to a "metabolic soft spot" has also been used as a strategy to increase duration of action. Linopir-dine (24) was among the first clinical compounds that enhanced potassium-evoked release of acetylcholine in preclinical models of AD [22]. Linopirdine showed no clinical efficacy and its human pharmacokinetic profile was suggested as the reason for this lack of clinical efficacy. Specifically noted was the molecule s poor brain exposure and short half-life due to formation of the N-oxides 25 and 26 (Table 3) [23,24]. Optimization of 24 resulted in replacement of the indolone core by the anthracenone 27, which had improved in vitro activity, but still exhibited a short duration of action. To improve the metabolic stability, fluorine... 

COMPUTATIONAL MODELS OF METABOLISM STABILITY AND REGULATION IN METABOLIC... 

The major strategies to enhance transmucosal peptide and other drug absorption include (a) coadministration with protease inhibitors, (b) the use of membrane permeation enhancers, (c) coadministration with a combination of absorption enhancers and protease inhibitors, (d) modification of peptide structure to improve metabolic stability or membrane permeation, and (e) use of nano- or microparticles [27], Some of these strategies have been investigated using the in situ rat model. 

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