The validity of log P calculations is checked for the substructure methods CLOGP, KOWWIN, and AB/logP and the whole-molecule method SciLogP via experimental log P for 174 molecules, comprising 90 simple organics and 84 more complex drugs. Averaged absolute residual sums (AARS) give the following ranking for the entire set: CLOGP > KOWWIN AB/logP > SciLogP. Separate analysis of simple organics yields: CLOGP > KOWWIN > AB/logP > SciLogP. For the drugs we find: CLOGP KOWWIN AB/LogP > SciLogP. In a second step, we compared the validity of the calculation programs focussing on structural factors with a critical impact on log P such as resonance and H-bonding interactions AARS values show that CLOGP and KOWWIN scored slightly better than AB/I,ogP and SciLogP; this agrees with the good performance of CLOGP and KOWWIN when dealing with simple compounds. AB/LogP averaged correction factors obtained from both simple and complex compounds, so it produced a slightly lower accuracy. α-Effects, representing strong interactions between conjugated n-electrons within polar functional groups, were identified from compounds lacking "isolating carbons". which break α-effects. All compounds in this data set are difficult to deal with for the substructure methods, but should be easy to deal with for the whole-molecule approach. In practice, however, SciLogP performed worse than the substructure methods. The best performance was shown by CLOGP, followed by KOWWIN and AB/LogP. Taken together, all substructure methods produced better results than the whole-molecule method. The possible explanation may be that substructure methods automatically account for unknown effects by splitting compounds into fragments and/or conducting class-specific analyses. Whole-molecule approaches cannot account for unknown effects, as long as they neglect class-specific analyses. Among the substructure approaches, our results correlate with the methodology of algorithm development. CLOGP and KOWWIN were developed in a long iterative process, using simple organics for increment derivation and complex drugs for algorithm refinement. AB/LogP was developed in a fast two-step procedure that did not discriminate between simple and complex compounds. So it produced slightly lower accuracy for simple organics, but not lower accuracy for the complex drugs.
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