Comparative molecular field analysis and molecular modeling studies of 20-(S)- camptothecin analogs as inhibitors of DNA topoisomerase I and anticancer/antitumor ... View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1997-01

AUTHORS

Sean W. Carrigan, Peter C. Fox, Monroe E. Wall, Mansukh C. Wani, J. Phillip Bowen

ABSTRACT

Conformational studies and comparative molecular field analysis (CoMFA) were undertaken for a series of camptothecin (CPT) analogs to correlate topoisomerase I inhibition with the steric and electrostatic properties of 32 known compounds. The resulting CoMFA models have been used to make predictions on novel CPT derivatives. Using the newly derived MM3 parameters, a molecular database of the 32 CPT analogs was created. Various point atomic charges were generated and assigned to the MM3 minimized structures, which were used in partial least-squares analyses. Overall, CoMFA models with the greatest predictive validity were obtained when both the R- and S-isomers were included in the data set, and semiempirical charges were calculated for MM3 minimized low-energy lactone structures. A cross-validated R2 of 0.758 and a non-cross-validated R2 of 0.916 were obtained for MM3 minimized structures with PM3 ESP charges for the 32 CPT analogs. The derived QSAR equations were used to assign topoisomerase I inhibition values for compounds in this study and compounds not included in the original data set. Prior to its appearance in the literature, an IC50 of 103 nM was predicted for the 10,11-oxazole derivative. This CoMFA predicted value compared favorably with the recently reported value of 150 nM. The CoMFA model was also evaluated by predicting the activities of recently reported 11-aza CPT and trione derivatives. The predicted activity (IC50 = 249 nM) for 11-aza CPT compared well with the reported value of 383 nM. More... »

PAGES

71-78

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1023/a:1008027528218

DOI

http://dx.doi.org/10.1023/a:1008027528218

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1029315896

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/9139114


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