Is experimental data quality the limiting factor in predicting the aqueous solubility of druglike molecules?
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We report the results of testing quantitative structure-property relationships (QSPR) that were trained upon the same druglike molecules but two different sets of solubility data: (i) data extracted from several different sources from the published literature, for which the experimental uncertainty is estimated to be 0.6-0.7 log S units (referred to mol/L); (ii) data measured by a single accurate experimental method (CheqSol), for which experimental uncertainty is typically <0.05 log S units. Contrary to what might be expected, the models derived from the CheqSol experimental data are not more accurate than those derived from the "noisy" literature data. The results suggest that, at the present time, it is the deficiency of QSPR methods (algorithms and/or descriptor sets), and not, as is commonly quoted, the uncertainty in the experimental measurements, which is the limiting factor in accurately predicting aqueous solubility for pharmaceutical molecules.
Palmer , D S & Mitchell , J B O 2014 , ' Is experimental data quality the limiting factor in predicting the aqueous solubility of druglike molecules? ' , Molecular Pharmaceutics , vol. 11 , no. 8 , pp. 2962-2972 . https://doi.org/10.1021/mp500103r
Copyright © 2014 © 2014 American Chemical Society. Open Access. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
DescriptionD.S.P. is grateful for funding from the European Commission through a Marie Curie Intra-European Fellowship within the seventh European Community Framework Programme (FP7-PEOPLE-2010-IEF). D.S.P. thanks the University of Strathclyde for support through its Strategic Appointment and Investment Scheme. Computations were performed at the EPSRC funded ARCHIE-WeSt High Performance Computer (www.archie-west.ac.uk, EPSRC grant no. EP K0005861). J.B.O.M. thanks the Scottish Universities Life Sciences Alliance (SULSA) for financial support and EaStCHEM for access to the EaStCHEM Research Computing Facility.
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