Abstract
We have used topological, topochemical and geometrical parameters in predicting: (a) normal boiling point of a set of 1023 chemicals and (b) lipophilicity (log P, octanol/water) of 219 chemicals. The results show that topological and topochemical variables can explain most of the variance in the data. The addition of geometrical parameters to the models provide marginal improvement in the model's predictive power. Among the three classes of descriptors, the topochemical indices were the most effective in predicting properties.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: Journal of Chemical Information and Computer Sciences
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.