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| Content Provider | Springer Nature Link |
|---|---|
| Author | Hutter, Michael C. |
| Copyright Year | 2003 |
| Abstract | A model for the prediction of the blood–brain distribution (logBB) is obtained by multiple regression analysis of molecular descriptors for a training set of 90 compounds. The majority of the descriptors are derived from quantum chemical information using semi-empirical AM1 calculations to compute fundamental properties of the molecules investigated. The polar surface area of the compounds can be described appropriately by six descriptors derived from the molecular electrostatic potential. This set shows a strong correlation with the observed logBB. Additional quantum chemically computed properties that contribute to the final model comprise the ionization potential and the covalent hydrogen-bond basicity. Complementary descriptors account for the presence of certain chemical groups, the number of hydrogen-bond donors, and the number of rotatable bonds of the compounds. The quality of the fit is further improved by including variables derived from principal component analysis of the molecular geometry. |
| Starting Page | 415 |
| Ending Page | 443 |
| Page Count | 29 |
| File Format | |
| ISSN | 0920654X |
| Journal | Journal of Computer-Aided Molecular Design |
| Volume Number | 17 |
| Issue Number | 7 |
| e-ISSN | 15734951 |
| Language | English |
| Publisher | Kluwer Academic Publishers |
| Publisher Date | 2003-01-01 |
| Publisher Place | Dordrecht |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Computer Applications in Chemistry Physical Chemistry Animal Anatomy / Morphology / Histology |
| Content Type | Text |
| Resource Type | Article |
| Subject | Drug Discovery Physical and Theoretical Chemistry Computer Science Applications |
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