Characterization of human lung cancer cells resistant to 4'-O-demethyl-4beta-(2"-nitro-4"-fluoroanilino)-4-desoxypodophyllotoxin , a unique compound in the epipodophyllotoxin antitumor class

Chemistry and Biological Activities of Naturally Occurring and Structurally Modified Podophyllotoxins

Plants containing podophyllotoxin and its analogues have been used as folk medicines for centuries. The characteristic chemical structures and strong biological activities of this class of compounds attracted attention worldwide. Currently, more than ninety natural podophyllotoxins were isolated, and structure modifications of these molecules were performed to afford a variety of derivatives, which offered optimized anti-tumor activity. This review summarized up to date reports on natural occurring podophyllotoxins and their sources, structural modification and biological activities. Special attention was paid to both structural modification and optimized antitumor activity. It was noteworthy that etoposide, a derivative of podophyllotoxin, could prevent cytokine storm caused by the recent SARS-CoV-2 viral infection.

Podophyllotoxin: distribution, sources, applications and new cytotoxic derivatives

Several podophyllotoxin derivatives modified in the A, B, C, D and E rings were prepared from podophyllotoxin and methyl isoxazopodophyllic acid and evaluated for their cytotoxicity on several neoplastic cell lines. Chemical transformations performed on these compounds have yielded derivatives more potent and more selective that the parent compound. Most of the compounds maintained their cytotoxicity at the microM level. Distribution, biosynthesis, production, biotechnology, applications and synthesis have also been reviewed.

Antitumor agents. 213. Modeling of epipodophyllotoxin derivatives using variable selection k nearest neighbor QSAR method

We have applied a variable selection k nearest neighbor quantitative structure-activity relationship (kNN QSAR) method to develop predictive QSAR models for 157 epipodophyllotoxins synthesized previously in our ongoing effort to develop potential anticancer agents. QSAR models were generated using multiple topological descriptors of chemical structures, including molecular connectivity indices (MCI) and molecular operating environment descriptors. The 157 compounds were separated into several training and test sets. The robustness of QSAR models was characterized by the values of the internal leave one out cross-validated R2 (q2) for the training set and external predictive R2 for the test set. The significance of the training set models was confirmed by statistically higher values of q2 for the original data set as compared to q2 values for the same data set with randomly shuffled activities. kNN QSAR models were compared with those obtained with the comparative molecular field analysis method; the kNN QSAR approach afforded models with higher values of both q2 and predictive R2. One of the best models obtained from kNN analysis using MCI as descriptors provided q2 and predictive R2 values of 0.60 and 0.62, respectively. QSAR models developed in these studies shall aid in future design of novel potent epipodophyllotoxin derivatives.