ArticleJournal of computer-aided molecular design2021
COSMO-RS predictions of logP in the SAMPL7 blind challenge.
Article in Journal of computer-aided molecular design, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Toward the Engineering of Chameleonicity: Quantum Mechanical Prediction for the Octanol/Water Distributions of Large Flexible Triazine Macrocycles.Journal of chemical information and modeling · 2026Article
- Development and Test of Highly Accurate End Point Free Energy Methods. 4. Expanding Solvents Capability and logBB Prediction.The journal of physical chemistry. B · 2026Article
- Benchmarking pJournal of chemical information and modeling · 2026Article
- Multi-fidelity graph neural networks for predicting toluene/water partition coefficients.Journal of cheminformatics · 2025Article
- Expanded ensemble predictions of toluene-water partition coefficients in the SAMPL9 logPhysical chemistry chemical physics : PCCP · 2025Article
- pKJournal of computational chemistry · 2025Article
- Predicting absolute aqueous solubility by applying a machine learning model for an artificially liquid-state as proxy for the solid-state.Journal of computer-aided molecular design · 2023Article
- Integrated Molecular Modeling and Machine Learning for Drug Design.Journal of chemical theory and computation · 2023Review
- COSMO-RS blind prediction of distribution coefficients and aqueous pKa values from the SAMPL8 challenge.Journal of computer-aided molecular design · 2023Article
- Multitask Deep Ensemble Prediction of Molecular Energetics in Solution: From Quantum Mechanics to Experimental Properties.Journal of chemical theory and computation · 2023Article
- Multitask machine learning models for predicting lipophilicity (logP) in the SAMPL7 challenge.Journal of computer-aided molecular design · 2021Article
- Evaluation of log P, pKJournal of computer-aided molecular design · 2021Article
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Authors and funding
3 authors.
Funding
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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