Enhancing Carbon Acid pKa Prediction by Augmentation of Sparse Experimental Datasets with Accurate A...
Enhancing Carbon Acid pKa Prediction by Augmentation of Sparse Experimental Datasets with Accurate AIBL (QM) Derived Values
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Basel: MDPI AG
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Language
English
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Basel: MDPI AG
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The prediction of the aqueous pKa of carbon acids by Quantitative Structure Property Relationship or cheminformatics-based methods is a rather arduous problem. Primarily, there are insufficient high-quality experimental data points measured in homogeneous conditions to allow for a good global model to be generated. In our computationally efficient...
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Enhancing Carbon Acid pKa Prediction by Augmentation of Sparse Experimental Datasets with Accurate AIBL (QM) Derived Values
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TN_cdi_doaj_primary_oai_doaj_org_article_f511b899d1a94a69838f498397102628
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_f511b899d1a94a69838f498397102628
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ISSN
1420-3049
E-ISSN
1420-3049
DOI
10.3390/molecules26041048
