Development of predictive quantitative structure-activity relationship models of epipodophyllotoxin derivatives

J Biomol Screen. 2010 Dec;15(10):1194-203. doi: 10.1177/1087057110380743. Epub 2010 Oct 6.


Epipodophyllotoxins are the most important anticancer drugs used in chemotherapy for various types of cancers. To further, improve their clinical efficacy a large number of epipodophyllotoxin derivatives have been synthesized and tested over the years. In this study, a quantitative structure-activity relationship (QSAR) model has been developed between percentage of cellular protein-DNA complex formation and structural properties by considering a data set of 130 epipodophyllotoxin analogues. A systematic stepwise searching approach of zero tests, missing value test, simple correlation test, multicollinearity test, and genetic algorithm method of variable selection was used to generate the model. A statistically significant model (r((train))(2) = 0.721; q(cv)(2) = 0.678) was obtained with descriptors such as solvent-accessible surface area, heat of formation, Balaban index, number of atom classes, and sum of E-state index of atoms. The robustness of the QSAR models was characterized by the values of the internal leave-one-out cross-validated regression coefficient (q(cv)(2)) for the training set and r((test))(2) for the test set. The root mean square error between the experimental and predicted percentage of cellular protein-DNA complex formation (PCPDCF) was 0.194 and r((test))(2) = 0.689, revealing good predictability of the QSAR model.

MeSH terms

  • Algorithms
  • Animals
  • Antineoplastic Agents, Phytogenic / chemistry*
  • Antineoplastic Agents, Phytogenic / pharmacology
  • Humans
  • Models, Molecular
  • Models, Statistical*
  • Molecular Structure
  • Neoplasms / drug therapy
  • Podophyllotoxin / analogs & derivatives*
  • Podophyllotoxin / chemistry*
  • Podophyllotoxin / pharmacology
  • Quantitative Structure-Activity Relationship


  • Antineoplastic Agents, Phytogenic
  • Podophyllotoxin