Name
Title | ||
|---|---|---|
Can Descriptors of the Electron Density Distribution Help To Distinguish Functional Groups? |
Abstract | ||
|---|---|---|
Our study is aimed at Understanding the characteristics of functional group descriptors based on peaks of the electronic density distribution p(((r) over right arrow)). The descriptors calculated are the p(((r) over right arrow)) value at peak location, Volume, ellipticity, curvatures of p(((r) over right arrow)) and the peak-functional group distance. By the implementation of all automated we generated a statistically meaningful and global process for large-scale calculation of the descriptors, we 11 data set focusing oil the association between peaks and 77 types of functional groups extracted from 62,936 organic molecules issued from the Cambridge Structural Database. Statistical analyses demonstrated that selected descriptors are capable of discriminating subtypes of functional groups. A projection in a principal component space coupled to a hierarchical clustering confirmed the suitability of the descriptors to provide all appropriate description of the functional groups. The results indicated that functional similarity Or dissimilarity Could be quantified based oil electron density descriptors. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1021/ci800148z | JOURNAL OF CHEMICAL INFORMATION AND MODELING |
Keywords | Field | DocType |
principal component,electron density,hierarchical clustering | Hierarchical clustering,Topology,Electron density,Pattern recognition,Combinatorial chemistry,Electronic density,Artificial intelligence,Organic molecules,Principal component analysis,Mathematics | Journal |
Volume | Issue | ISSN |
48 | 10 | 1549-9596 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Julien Burton | 1 | 0 | 0.34 |
| Nathalie Meurice | 2 | 6 | 1.78 |
| Laurence Leherte | 3 | 20 | 6.75 |
| Daniel P Vercauteren | 4 | 15 | 6.86 |