Total synthesis of podophyllotoxin is an expensive process and availability of the compound from the natural resources is an important issue for pharmaceutical companies that manufacture anticancer drugs. In order to facilitate reasoned scientific decisions on its management and conservation for selective breeding programme, genetic analysis of 28 populations was done with 19 random primers, 11 ISSR primers and 13 AFLP primer pairs. A total of 92.37 %, 83.82 % and 84.40 % genetic polymorphism among the populations of Podophyllum were detected using RAPD, ISSR and AFLP makers, respectively. Similarly the mean coefficient of gene differentiation (Gst) were 0.69, 0.63 and 0.51, indicating that 33.77 %, 29.44 % and 26 % of the genetic diversity resided within the population. Analysis of molecular variance (AMOVA) indicated that 53 %, 62 % and 64 % of the genetic diversity among the studied populations was attributed to geographical location while 47 %, 38 % and 36 % was attributed to differences in their habitats using RAPD, ISSR and AFLP markers. An overall value of mean estimated number of gene flow (Nm) were 0.110, 0.147 and 0.24 from RAPD, ISSR and AFLP markers indicating that there was limited gene flow among the sampled populations.

Podophyllotoxin is the active ingredient in the rhizome of an endangered Indian medicinal herb, Podophyllum hexandrum. Podophyllotoxin content in the P. hexandrum differs greatly in different natural habitats. The podophyllotoxin content reached more than 6.62% when soil pH value was about 4.82, soil organic carbon (C) was more than 3.23%, and nitrogen (N) content was more than 2.7% of soil dry weight. Available phosphorous (P) content of more than 0.419% and potassium (K) content of more than 1.56% resulted in low podophyllotoxin content. The linear relationship detected between podophyllotoxin and soil nutrients, environmental factors, and altitude suggested that further optimization of these factors are important in the conservation and exploitation of P. hexandrum in the northwestern Himalayan region, Himachal Pradesh, India. In this regard, like artificial neural network (ANN) and multiple linear regression (MLR), the prediction model used in this study to map the effect of these factors on podophyllotoxin yield will be helpful.

A quantitative structure-activity relationship (QSAR) model has been developed between cytotoxic activity and structural properties by considering a data set of 119 podophyllotoxin analogs based on 2D and 3D structural descriptors. A systematic stepwise searching approach of zero tests, a missing value test, a simple correlation test, a multicollinearity test, and a genetic algorithm method of variable selection was used to generate the model. A statistically significant model (r(train)(2) = 0.906; q(cv)(2) = 0.893) was obtained with the molecular descriptors. The robustness of the QSAR model 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 overall root mean square error (RMSE) between the experimental and predicted pIC(50) value was 0.265 and r(test)(2) = 0.824, revealing good predictability of the QSAR model. For an external data set of 16 podophyllotoxin analogs, the QSAR model was able to predict the tubulin polymerization inhibition and mechanistically cytotoxic activity with an RMSE value of 0.295 in comparison to experimental values. The QSAR model developed in this study shall aid further design of novel potent podophyllotoxin derivatives.

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