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Abstract
Orally administered drugs must overcome several barriers before reaching their target site. Such barriers depend largely upon specific membrane transport systems and intracellular drug-metabolizing enzymes. For the first time, the P-glycoprotein (P-gp) and cytochrome P450s, the main line of defense by limiting the oral bioavailability (OB) of drugs, were brought into construction of QSAR modeling for human OB based on 805 structurally diverse drug and drug-like molecules. The linear (multiple linear regression: MLR, and partial least squares regression: PLS) and nonlinear (support-vector machine regression: SVR) methods are used to construct the models with their predictivity verified with five-fold cross-validation and independent external tests. The performance of SVR is slightly better than that of MLR and PLS, as indicated by its determination coefficient (R2) of 0.80 and standard error of estimate (SEE) of 0.31 for test sets. For the MLR and PLS, they are relatively weak, showing prediction abilities of 0.60 and 0.64 for the training set with SEE of 0.40 and 0.31, respectively. Our study indicates that the MLR, PLS and SVR-based in silico models have good potential in facilitating the prediction of oral bioavailability and can be applied in future drug design.
Highlights
A large number of compounds emerging from combinatorial chemistry and high throughput medicinal chemistry programs have increased the demand for new compounds that need to be screened in a wide range of biological assays [1]
Partial Least Squares Analysis (PLS) was carried out to construct the relationships between the bioavailability of the compounds and their molecular structures, which is based on linear transformation from a large number of original descriptors to a new variable space
For the first time, we have constructed a novel chemometric method for prediction of human oral bioavailability (OB) by integrating the information of the ATP-dependent efflux protein P-gp and the cytochrome P4503A4 and P4502D6 metabolizing enzymes, the important defence limiting the absorption of candidate drugs
Summary
A large number of compounds emerging from combinatorial chemistry and high throughput medicinal chemistry programs have increased the demand for new compounds that need to be screened in a wide range of biological assays [1]. Since the predominant and most convenient way to deliver drugs to the systemic circulation for patients is the oral route, the good oral bioavailability (OB). Of a new drug candidate is undoubtedly one of the most important pharmacokinetic parameters along with ADME properties. A low and highly variable bioavailability is the main reason for stopping further development of the drug candidates. In recent years, multiple large-scale experiments drugs candidates have been conducted to assess the OB values of molecules, but they are labor-intensive and time-consuming. Developing a reliable and efficient in silico method that can predict human OB is compelling [5,6], both in the early stage of drug discovery to select the most promising compounds for further optimization and in the later stage to identify final candidates for further clinical development
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