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COSMO-RS predictions of logP in the SAMPL7 blind challenge

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Abstract

We applied the COSMO-RS method to predict the partition coefficient logP between water and 1-octanol for 22 small drug like molecules within the framework of the SAMPL7 blind challenge. We carefully collected a set of thermodynamically meaningful microstates, including tautomeric forms of the neutral species, and calculated the logP using the current COSMOtherm implementation on the most accurate level. With this approach, COSMO-RS was ranked as the 6st most accurate method (Measured by the mean absolute error (MAE) of 0.57) over all 17 ranked submissions. We achieved a root mean square deviation (RMSD) of 0.78. The largest deviations from experimental values are exhibited by five SAMPL molecules (SM), which seem to be shifted in most SAMPL7 contributions. In context with previous SAMPL challenges, COSMO-RS demonstrates a wide range of applicability and one of the best in class reliability and accuracy among the physical methods.

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Availability of data and materials

The datasets generated during and analyzed during the current study are available from the corresponding author on reasonable request.

Code availability

The code of our software is commercially available.

Notes

  1. Originally, we submitted transfer free energies in the mol-fraction based reference state (Eq. 2 without the additional term of molar volumes). After realizing that the concentration-based framework was asked, we got the opportunity to resubmit our predicted transfer free energies in the relevant reference state by adding the logarithm of the quotient of the molar volumes (like in Eq. 2).

  2. The AB5 and AWI17 analysis was based on the SAMPL7 analysis of Version 0.7 (https://github.com/samplchallenges/SAMPL7/releases/tag/0.7).

  3. This analysis was based on the SAMPL7 analysis of Version 0.7 (https://github.com/samplchallenges/SAMPL7/releases/tag/0.7).

  4. In SAMPL7, TFE MLR was the most accurate method with an RMSD of 0.58 log units.

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Acknowledgements

The authors thank David Mobley and the organizers for setting up the SAMPL7 challenge and fruitful discussions. We appreciate the National Institutes of Health for its support of the SAMPL project via R01GM124270 to David L. Mobley (UC Irvine). We thank the Ballatore lab at UCSD for carrying out the experimental logP measurements. We thank Andreas Klamt for helpful discussions. We thank Michael Diedenhofen, Johannes Schwöbel and Frank Eckert for conducting a big part of the tautomer and conformer workflow with COSMOconf and COSMOquick as well as for helping us in refining the data and supporting discussions. Judith Warnau thanks Felix Hanke for revising the manuscript.

Funding

Financial interests: All author are employed and have received research support from Company Dassault Systemes Deutschland GmbH. Apart from that, no funding was received for conducting this study.

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Authors and Affiliations

  1. Dassault Systemes Deutschland GmbH, Imbacher Weg 46, 51379, Leverkusen, Germany

    Judith Warnau, Karin Wichmann & Jens Reinisch

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  1. Judith Warnau
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  2. Karin Wichmann
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  3. Jens Reinisch
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Contributions

All authors contributed to developing the research design. Judith Warnau performed material preparation, data collection and analysis. All authors contributed to data analysis decisions and interpretation of the results. Judith Warnau wrote the first draft of the manuscript and all authors revised and commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Judith Warnau.

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Conflict of interest

All authors are employed by Dassault Systemes Deutschland GmbH. Dassault Systemes commercially distributes the software (COSMOtherm, COSMOconf, COSMOquick and Turbomole) which was used to conduct the calculations for this manuscript. Apart from that, there are no conflicts of interests or competing interests.

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Warnau, J., Wichmann, K. & Reinisch, J. COSMO-RS predictions of logP in the SAMPL7 blind challenge. J Comput Aided Mol Des 35, 813–818 (2021). https://doi.org/10.1007/s10822-021-00395-5

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