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- Bergström, Christel A S, et al.
(author)
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Absorption classification of oral drugs based on molecular surface properties
- 2003
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In: Journal of Medicinal Chemistry. - : American Chemical Society (ACS). - 0022-2623 .- 1520-4804. ; 46:4, s. 558-570
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Journal article (peer-reviewed)abstract
- The aim of this study was to investigate whether easily calculated and comprehended molecular surface properties can predict drug solubility and permeability with sufficient accuracy to allow theoretical absorption classification of drug molecules. For this purpose, structurally diverse, orally administered model drugs were selected from the World Health Organization (WHO)'s list of essential drugs. The solubility and permeability of the drugs were determined using well-established in vitro methods in highly accurate experimental settings. Descriptors for molecular surface area were generated from low-energy conformations obtained by conformational analysis using molecular mechanics calculations. Correlations between the calculated molecular surface area descriptors, on one hand, and solubility and permeability, on the other, were established with multivariate data analysis (partial least squares projection to latent structures (PLS)) using training and test sets. The obtained models were challenged with external test sets. Both solubility and permeability of the druglike molecules could be predicted with high accuracy from the calculated molecular surface properties alone. The established correlations were used to perform a theoretical biopharmaceutical classification of the WHO-listed drugs into six classes, resulting in a correct prediction for 87% of the essential drugs. An external test set consisting of Food and Drug Administration (FDA) standard compounds for biopharmaceutical classification was predicted with 77% accuracy. We conclude that PLS models of easily comprehended molecular surface properties can be used to rapidly provide absorption profiles of druglike molecules early on in drug discovery.
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| 2. |
- Bergström, Christel A S, et al.
(author)
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Accuracy of calculated pH-dependent aqueous drug solubility.
- 2004
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In: European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences. - : Elsevier BV. - 0928-0987. ; 22:5, s. 387-98
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Journal article (peer-reviewed)abstract
- The aim of the present study was to investigate the extent to which the Henderson-Hasselbalch (HH) relationship can be used to predict the pH-dependent aqueous solubility of cationic drugs. The pH-dependent solubility for 25 amines, carrying a single positive charge, was determined with a small-scale shake flask method. Each sample was prepared as a suspension in 150 mM phosphate buffer. The pH-dependent solubility curves were obtained using at least 10 different pH values. The intrinsic solubility, the solubility at the pKa and the solubility at pH values reflecting the pH of the bulk and acid microclimate in the human small intestine (pH 7.4 and 6.5, respectively) were determined for all compounds. The experimental study revealed a large diversity in slope, from -0.5 (celiprolol) to -8.6 (hydralazine) in the linear pH-dependent solubility interval, which is in sharp contrast to the slope of -1 assumed by the HH equation. In addition, a large variation in the range of solubility between the completely uncharged and completely charged drug species was observed. The range for disopyramide was only 1.1 log units, whereas that for amiodarone was greater than 6.3 log units, pointing at the compound specific response to counter-ion effects. In conclusion, the investigated cationic drugs displayed compound specific pH-dependent solubility profiles, indicating that that the HH equation in many cases will only give rough estimations of the pH-dependent solubility of drugs in divalent buffer systems.
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| 3. |
- Bergström, Christel A. S., 1973-
(author)
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Computational and Experimental Models for the Prediction of Intestinal Drug Solubility and Absorption
- 2003
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Doctoral thesis (other academic/artistic)abstract
- New effective experimental techniques in medicinal chemistry and pharmacology have resulted in a vast increase in the number of pharmacologically interesting compounds. However, the number of new drugs undergoing clinical trial has not augmented at the same pace, which in part has been attributed to poor absorption of the compounds.The main objective of this thesis was to investigate whether computer-based models devised from calculated molecular descriptors can be used to predict aqueous drug solubility, an important property influencing the absorption process. For this purpose, both experimental and computational studies were performed. A new small-scale shake flask method for experimental solubility determination of crystalline compounds was devised. This method was used to experimentally determine solubility values used for the computational model development and to investigate the pH-dependent solubility of drugs. In the computer-based studies, rapidly calculated molecular descriptors were used to predict aqueous solubility and the melting point, a solid state characteristic of importance for the solubility. To predict the absorption process, drug permeability across the intestinal epithelium was also modeled.The results show that high quality solubility data of crystalline compounds can be obtained by the small-scale shake flask method in a microtiter plate format. The experimentally determined pH-dependent solubility profiles deviated largely from the profiles predicted by a traditionally used relationship, highlighting the risk of data extrapolation. The in silico solubility models identified the non-polar surface area and partitioned total surface areas as potential new molecular descriptors for solubility. General solubility models of high accuracy were obtained when combining the surface area descriptors with descriptors for electron distribution, connectivity, flexibility and polarity. The used descriptors proved to be related to the solvation of the molecule rather than to solid state properties. The surface area descriptors were also valid for permeability predictions, and the use of the solubility and permeability models in concert resulted in an excellent theoretical absorption classification. To summarize, the experimental and computational models devised in this thesis are improved absorption screening tools applicable to the lead optimization in the drug discovery process.
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| 5. |
- Bergström, Christel A S, et al.
(author)
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Global and local computational models for aqueous solubility prediction of drug-like molecules.
- 2004
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In: Journal of chemical information and computer sciences. - : American Chemical Society (ACS). - 0095-2338 .- 1520-5142. ; 44:4, s. 1477-88
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Journal article (peer-reviewed)abstract
- The aim of this study was to develop in silico protocols for the prediction of aqueous drug solubility. For this purpose, high quality solubility data of 85 drug-like compounds covering the total drug-like space as identified with the ChemGPS methodology were used. Two-dimensional molecular descriptors describing electron distribution, lipophilicity, flexibility, and size were calculated by Molconn-Z and Selma. Global minimum energy conformers were obtained by Monte Carlo simulations in MacroModel and three-dimensional descriptors of molecular surface area properties were calculated by Marea. PLS models were obtained by use of training and test sets. Both a global drug solubility model (R(2) = 0.80, RMSE(te) = 0.83) and subset specific models (after dividing the 85 compounds into acids, bases, ampholytes, and nonproteolytes) were generated. Furthermore, the final models were successful in predicting the solubility values of external test sets taken from the literature. The results showed that homologous series and subsets can be predicted with high accuracy from easily comprehensible models, whereas consensus modeling might be needed to predict the aqueous drug solubility of datasets with large structural diversity.
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