Skip to content
2000
Volume 3, Issue 9
  • ISSN: 1570-1808
  • E-ISSN: 1875-628X

Abstract

A set of 24 descriptors consisting of quantum and chemical descriptors have been used to model binding constant (logK) of the benzene sulfonamides to human CAII. Simple as well as multiple regression have indicated that MNC (most negative charge) is the most dominating parameter to be used in modeling log K. Excellent results are obtained in multi-parametric regression. The results are critically discussed using a variety of statistics, which indicated that the hydrophobic term (log P) is not essential to yield excellent models.

Loading

Article metrics loading...

/content/journals/lddd/10.2174/157018006778341138
2006-11-01
2025-09-25
Loading full text...

Full text loading...

/content/journals/lddd/10.2174/157018006778341138
Loading

  • Article Type:
    Research Article
Keyword(s): Chemical parameter; Hydrophobicity; QSAR; Quantum parameter; Regression analysis
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test