2023
DOI: 10.1186/s13321-023-00752-6
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Prediction of organic compound aqueous solubility using machine learning: a comparison study of descriptor-based and fingerprints-based models

Arash Tayyebi,
Ali S Alshami,
Zeinab Rabiei
et al.

Abstract: A reliable and practical determination of a chemical species’ solubility in water continues to be examined using empirical observations and exhaustive experimental studies alone. Predictions of chemical solubility in water using data-driven algorithms can allow us to create a rationally designed, efficient, and cost-effective tool for next-generation materials and chemical formulations. We present results from two machine learning (ML) modeling studies to adequately predict various species’ solubility using da… Show more

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Cited by 11 publications
(3 citation statements)
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“…Recently, studies investigating different descriptors and fingerprints were performed. 36,98 These studies showed that similarly to the impacts of data quality, 28 molecular representation also has a great impact on models' performance. Despite Tayyebi et al 36 being able to achieve an MAE of 0.64 on solubility challenge 1 when using Morgan fingerprints (MF), Zagidullin et al 98 reported poor performance when using MF.…”
Section: Discussionmentioning
confidence: 99%
See 2 more Smart Citations
“…Recently, studies investigating different descriptors and fingerprints were performed. 36,98 These studies showed that similarly to the impacts of data quality, 28 molecular representation also has a great impact on models' performance. Despite Tayyebi et al 36 being able to achieve an MAE of 0.64 on solubility challenge 1 when using Morgan fingerprints (MF), Zagidullin et al 98 reported poor performance when using MF.…”
Section: Discussionmentioning
confidence: 99%
“…36,98 These studies showed that similarly to the impacts of data quality, 28 molecular representation also has a great impact on models' performance. Despite Tayyebi et al 36 being able to achieve an MAE of 0.64 on solubility challenge 1 when using Morgan fingerprints (MF), Zagidullin et al 98 reported poor performance when using MF. Our approach, on the other hand, is based on extracting information from simple string representations, a more straightforward raw data.…”
Section: Discussionmentioning
confidence: 99%
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