ChemRxiv
These are preliminary reports that have not been peer-reviewed. They should not be regarded as conclusive, guide clinical practice/health-related behavior, or be reported in news media as established information. For more information, please see our FAQs.
SAMPL7_Physical_Property_Overview (5).pdf (3.59 MB)

Evaluation of Log P, pKa and Log D Predictions from the SAMPL7 Blind Challenge

preprint
submitted on 21.04.2021, 21:18 and posted on 22.04.2021, 12:46 by Teresa Danielle Bergazin, Nicolas Tielker, Yingying Zhang, Junjun Mao, Marilyn R. Gunner, karol francisco, Carlo Ballatore, Stefan Kast, David Mobley
The Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) challenges focuses the computational modeling community on areas in need of improvement for rational drug design. The SAMPL7 physical property challenge dealt with prediction of octanol-water partition coefficients and pKa for 22 compounds.
The dataset was composed of a series of N-acylsulfonamides and related bioisosteres.
17 research groups participated in the logP challenge, submitting 33 blind submissions total. For the pKa challenge, 7 different groups participated, submitting 9 blind submissions in total. Overall, the accuracy of octanol-water logP predictions in the SAMPL7 challenge was lower than octanol-water logP predictions in SAMPL6, likely due to a more diverse dataset. Compared to the SAMPL6 pKa challenge, accuracy remains unchanged in SAMPL7.
Interestingly, here, though macroscopic pKa values were often predicted with reasonable accuracy, there was dramatically more disagreement among participants as to which microscopic transitions produced these values (with methods often disagreeing even as to the sign of the free energy change associated with certain transitions), indicating far more work needs to be done on pKa prediction methods.

Funding

National Institute of General Medical Sciences (NIGMS)

United States Department of Health and Human Services

Find out more...

History

Email Address of Submitting Author

dmobley@uci.edu

Institution

University of California, Irvine

Country

United States

ORCID For Submitting Author

0000-0002-1083-5533

Declaration of Conflict of Interest

David Mobley serves on the scientific advisory board of OpenEye Scientific Software, and serves as an Open Science Fellow with Silicon Therapeutics.

Licence

Exports