Application of ALOGPS 2.1 to Predict log D Distribution Coefficient for Pfizer Proprietary Compounds
- 5 October 2004
- journal article
- letter
- Published by American Chemical Society (ACS) in Journal of Medicinal Chemistry
- Vol. 47 (23) , 5601-5604
- https://doi.org/10.1021/jm049509l
Abstract
Evaluation of the ALOGPS, ACD Labs LogD, and PALLAS PrologD suites to calculate the log D distribution coefficient resulted in high root-mean-squared error (RMSE) of 1.0−1.5 log for two in-house Pfizer's log D data sets of 17 861 and 640 compounds. Inaccuracy in log P prediction was the limiting factor for the overall log D estimation by these algorithms. The self-learning feature of the ALOGPS (LIBRARY mode) remarkably improved the accuracy in log D prediction, and an rmse of 0.64−0.65 was calculated for both data sets.Keywords
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