Methods to Predict Log D at Arbitrary pH

While there are plenty of methods to predict 1-octanol-water partition coefficients, logP (see Chapters 14 and 15), the number of approaches to predict 1-octanol-water distribution coefficients is rather limited. This is due to a lower availability of log D data and, in general, higher computational complexity of this property compared to that of log P. The approaches to predict log D can be roughly classified into two major categories (i) calculation of log D at an arbitrary pH and (ii) calculation of log D at a fixed pH. 

These are more general, and they can perform log D calculation at any pH and ionic strength. The distribution coefficient for monoprotic base given by Eq. (2) can be simplified to Eq. (3) assuming that only the neutral form of a molecule will partition into the organic phase and thus D is zero. 

The ionic partition in the octanol phase could invalidate Fq. (3) for pfCa-pH 3 log units, when partitioning of ionic species starts to play a significant contribution. The partition of ionic species in the octanol phase was recently considered 

Equation (2) for monoprotic base can be rewritten using a definition of the Scherrer pfCa pffa.oci (see Section 16.3.2.1) as  

Considering the failure of available log D methods to predict in-house data and taking into account that such data are usually generated just for a few fixed pH values, a number of companies started to elaborate in-house methods for log D prediction at fixed pH. Up to date several companies have reported development of such methods. For example, Cerep has developed methods to predict log D at pH 7.4 and 6.5 included in their Bio Print package [107], but details of their method are not pubhshed. HQSAR Tripos descriptors were used by Bayer to develop log D models at pH 2.3 and 7.5 using 70000 (qi =0.76, STD =0.60) and 7000 (qi =0.83, STD =0.67) compounds, respectively [108] however, again, no details of the approach were provided. 

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