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Methods and Principles in Medicinal Chemistry - Mannhold R.

Mannhold R., Kubinyi H., Timmerman H. Methods and Principles in Medicinal Chemistry - Wiley-VCH, 2001. - 155 p.
Download (direct link): pharmacokinetiksmedicanalchemistri2001.pdf
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The hierarchical model is closest to the traditional approach and meets the needs of a focused, disciplined approach, where molecules are drug-like, with a real possibility of passing some of the ADME criteria. The horizontal model is optimum for looking for exceptions to drug-like property rules and can build SAR streams much
Physicochemical analysis Measured or computed
Fig. 10.1 Hierarchical and horizontal in vitro (top) ADME data is collected only on com-
screening sequences. In each phase only com- pounds with adequate potency and selectivity.
pounds possessing certain criteria would move In the horizontal model (bottom) ADME data
to the next phase. In the hierarchical model is collected on all compounds synthesized.
10.3 Physicochemistry 135
more rapidly so allowing very comprehensive real-time SAR of the type normally reserved for retrospective analysis. These two models indicate a divergence of how the data is handled. The hierarchical model means that full data is available on a few compounds, can be manipulated on a spreadsheet and is within the understanding of a medicinal chemist. This relates to the data being unimportant and the information being retained to drive the process. The horizontal model could result in more than 5000 data points to collate as SAR. This immediately requires computational systems and complex analysis to process and optimize. Some progress has been made in methods used in early ADME evaluation [6] with in silico and higher throughput physicochemical methods being linked to appropriate in vitro models [7]. The next sections give an inventory of some of these approaches.
10.3 Physicochemistry
The importance of physicochemisty to drug disposition and ADME is summarized in tabular form in Table 10.1.
Tab. 10.1 Physicochemical properties and the relationship to key disposition processes.
Lipophilicity Molecular size Hydrogen bonding Ionization Melting point, crystal packing
Dissolution vvv i vv vvv i
Membrane permeation, lipoidal vvv 1 vv vv v
Membrane permeation, aqueous vvv i
Non-specific binding to proteins and phospholipids vvv 1 vvv
Carrier transport
Metabolism vvv 1 v
Renal clearance vvv i
Number of ticks indicate relative importance and the arrows indicates how an increase in the physicochemical property affects the ADME property, e. g. dissolution is decreased by increasing lipophilicity.
136 | 10 High(er) Throughput ADME Studies
10.3.1 Solubility
Solubility is a key parameter for dissolution of compounds following oral administration (Section 3.1). The process depends on the surface area of the dissolving solid and the solubility of the drug at the surface of the dissolving solid. Solubility is inversely proportional to the number and type of lipophilic functions within the molecule and the tightness of the crystal packing of the molecule. Rapid, robust methods reliant on turbidimetry to measure solubility have been developed [10, 11], which can handle large numbers of compounds. Since ionization can also govern solubility, approaches for the rapid measurement of pK values of sparingly soluble drug compounds have also been developed [12]. Ideally only soluble compounds would be synthesized in a Discovery programme which is where predictive solubility methods using neural networks [13, 14], would be such an advantage.
10.3.2
Lipophilicity
Lipophilicity is the key physicochemical parameter linking membrane permeability, and hence drug absorption and distribution with route of clearance (metabolic or renal). Measured or calculated lipophilicity of a compound is readily amenable to automation. Many of these calculation approaches rely on fragment values, but simple methods based on molecular size to calculate log P values have been demonstrated to be extremely versatile [15]. A combination of measured and fragmental approaches allow extremely accurate prediction of new compound properties. For actual measurement rather than prediction, investigations in using alternatives to octanol/water partitioning include applications of immobilized artificial membranes (IAM) [16] and liposome/water partitioning [17, 18]. The IAM method offers speed of measurement as an advantage over the classical octanol/water system. Liposome binding may possibly be transferred to a higher throughput system and could provide a “volume of distribution” screen when linked with other properties. Hydrogen bonding capacity of a drug solute is now recognized as an important constituent of the concept of lipophilicty. Initially AlogP, the difference between octanol/water and alkane/water partitioning was used as a measure for solute H-bondingbut this technique is limited by the poor solubility of many compounds in the alkane phase. Computational approaches to this range through simple heteroatom counts (O and N), division into acceptors and donors, and more sophisticated measures such as free energy factors (used in program Hybot) and polar surface area.
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