Details zur Publikation |
| Kategorie | Textpublikation |
| Referenztyp | Zeitschriften |
| DOI | 10.1021/ci100306k |
| Titel (primär) | Comparative analysis of QSAR models for predicting pKa of organic oxygen acids and nitrogen bases from molecular structure |
| Autor | Yu, H.; Kühne, R.
; Ebert, R.-U.; Schüürmann, G. |
| Quelle | Journal of Chemical Information and Modeling |
| Erscheinungsjahr | 2010 |
| Department | OEC |
| Band/Volume | 50 |
| Heft | 11 |
| Seite von | 1949 |
| Seite bis | 1960 |
| Sprache | englisch |
| Abstract | For 1143 organic compounds comprising 580 oxygen acids and 563 nitrogen bases that cover more than 17 orders of experimental pKa (from -5.00 to 12.23), the pKa prediction performances of ACD, SPARC, and two calibrations of a semiempirical quantum chemical (QC) AM1 approach have been analyzed. The overall root-mean-square errors (rms) for the acids are 0.41, 0.58 (0.42 without ortho-substituted phenols with intramolecular H-bonding), and 0.55 and for the bases are 0.65, 0.70, 1.17, and 1.27 for ACD, SPARC, and both QC methods, respectively. Method-specific performances are discussed in detail for six acid subsets (phenols and aromatic and aliphatic carboxylic acids with different substitution patterns) and nine base subsets (anilines, primary, secondary and tertiary amines, meta/para-substituted and ortho-substituted pyridines, pyrimidines, imidazoles, and quinolines). The results demonstrate an overall better performance for acids than for bases but also a substantial variation across subsets. For the overall best-performing ACD, rms ranges from 0.12 to 1.11 and 0.40 to 1.21 pKa units for the acid and base subsets, respectively. With regard to the squared correlation coefficient r2, the results are 0.86 to 0.96 (acids) and 0.79 to 0.95 (bases) for ACD, 0.77 to 0.95 (acids) and 0.85 to 0.97 (bases) for SPARC, and 0.64 to 0.87 (acids) and 0.43 to 0.83 (bases) for the QC methods, respectively. Attention is paid to structural and method-specific causes for observed pitfalls. The significant subset dependence of the prediction performances suggests a consensus modeling approach. |
| dauerhafte UFZ-Verlinkung | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=10683 |
| Yu, H., Kühne, R., Ebert, R.-U., Schüürmann, G. (2010): Comparative analysis of QSAR models for predicting pKa of organic oxygen acids and nitrogen bases from molecular structure J. Chem Inf. Model. 50 (11), 1949 - 1960 10.1021/ci100306k |
|