Cancer Research Audrey Hepburn  Telomeres
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Cancer Research Clinical Cancer Research
Cancer Epidemiology Biomarkers & Prevention Molecular Cancer Therapeutics
Molecular Cancer Research Cancer Prevention Research
Cancer Prevention Journals Portal Cancer Reviews Online
Annual Meeting Education Book Meeting Abstracts Online

[Cancer Research 45, 4741-4747, October 1, 1985]
© 1985 American Association for Cancer Research

This Article
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Leavitt, S. A.
Right arrow Articles by Mass, M. J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Leavitt, S. A.
Right arrow Articles by Mass, M. J.

Computer-assisted Correlation of Structure and Biological Activity in a Set of Retinoids

Sharon A. Leavitt and Marc J. Mass1

Carcinogenesis and Metabolism Branch, United States Environmental Protection Agency, Research Triangle Park, North Carolina 27711

A computer-assisted pattern-recognition system (ADAPT) designed to elucidate structure-activity relationships was applied to a set of retinoids, potentially useful inhibitors of carcinogenesis. A data set of 67 retinoids was used as input to the ADAPT system; their structures were entered, and their 3-dimensional configurations were optimized by a molecular modelling algorithm. Forty of these retinoids were defined as the "more active" class based upon their ability to reverse keratinization in vitamin A-deficient hamster tracheal organ cultures at 10-10 M or less. The remaining 27 retinoids were defined as the "less active" class due to their lack of ability to elicit this effect at 10-8 M or more. Thirteen descriptors were generated by ADAPT for each of these retinoids based upon their structures, including: number of ring atoms; double bonds; del Ré sigma charges; and principal moments. Pattern recognition analysis techniques were applied to this data set to determine if information contained in these descriptors could generate a discriminant function equation which could separate more active from less active retinoids, successfully. Computer recognition of more active from less active retinoids was demonstrated by a number of pattern recognition techniques, and the discriminant function could predict correctly the relative activity of retinoids of "unknown" activity in 87% of trials. These results indicate the existence of distinct structure-activity relationships in this set of biologically important molecules.

1 To whom requests for reprints should be addressed.

Received 4/ 4/85. Revised 7/ 2/85. Accepted 7/ 5/85.







HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Cancer Research Clinical Cancer Research
Cancer Epidemiology Biomarkers & Prevention Molecular Cancer Therapeutics
Molecular Cancer Research Cancer Prevention Research
Cancer Prevention Journals Portal Cancer Reviews Online
Annual Meeting Education Book Meeting Abstracts Online
Copyright © 1985 by the American Association for Cancer Research.