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Interpreting physicochemical experimental data sets

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Abstract

With the wealth of experimental physicochemical data available to chemoinformaticians from the literature, commercial, and company databases an increasing challenge is the interpretation of such datasets. Subtle differences in experimental methodology used to generate these datasets can give rise to variations in physicochemical property values. Such methodology nuances will be apparent to an expert experimentalist but not necessarily to the data analyst and modeller. This paper describes the differences between common methodologies for measuring the four most important physicochemical properties namely aqueous solubility, octan-1-ol/water distribution coefficient, pK a and plasma protein binding highlighting key factors that can lead to systematic differences. Insight is given into how to identify datasets suitable for combining.

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Acknowledgments

The authors would like to thank the AstraZeneca scientists who have worked in the physical chemistry field across the company (Alderley Park, Charnwood, Reims, Wilmington, Lund, Södertälje, Mölndal, Montreal, Boston) over the last 25 years who have generated much of the data discussed in this paper. Also thanks to our colleagues at Pharmaron who have generated the more recent physical property results. In particular the authors would like to thank our Alderley Park and Charnwood physical chemistry colleagues past and present for the many discussions which have contributed to the learning presented in this paper.

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Colclough, N., Wenlock, M.C. Interpreting physicochemical experimental data sets. J Comput Aided Mol Des 29, 779–794 (2015). https://doi.org/10.1007/s10822-015-9850-7

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