Enzymatic Synthesis of 3-O-Acylbetulinic Acid Derivatives and Prediction of Acylation Using Response Surface Methodology and Artificial Neural Network Analyses

In this study, 3-O-acyl-betulinic acid derivatives were synthesized by the reaction of betulinic acid with various anhydrides using lipase as a biocatalyst in organic solvents. The reaction between betulinic acid and phthalic anhydride was chosen as the model reaction for optimization studies. The immobilized lipase from Candida antarctica (Novozym 435) was selected as a biocatalyst. The effects of different reaction parameters were investigated and optimized in the model reaction using one-variable-ata- time technique for the first time. Optimum conditions to produce 3-O-phthalylbetulinic acid up to 61.8% were observed at a reaction time of 24 hours; amount of enzyme, 176 mg; betulinic acid to phthalic anhydride molar ratio of 1:1; amount of celite, 170 mg and 6 mg of K2CO3 in a mixture of n-hexane-chloroform (1:1, v/v) as organic solvent at 55'C. The response surface methodology (RSM), based on a five-level, four-variable central composite rotatable design (CCRD), was employed to evaluate the effects of synthesis parameters of the model reaction. Using the RSM analysis, it was observed that the maximum yield of 3-O-phthalyl-betulinic acid (65.8%) could be obtained using 145.6 mg of enzyme, reaction temperature of 53.9°C, reaction time of 20.3 hours and betulinic acid to phthalic anhydride molar ratio of 1:1.11. The actual experimental value obtained was at 64.7%. Artificial neural network (ANN) was successfully developed to model and predict the enzymatic synthesis of 3-O-phthalyl-betulinic acid. The network consists of an input layer, a hidden layer and an output layer. Inputs for the network were reaction time, reaction temperature, enzyme amount and substrate molar ratio, while the output was percentage isolated yield of ester. Four different training algorithms, belonging to two classes, namely gradient descent and Levenberg-Marquardt, were used to train ANN. The best results were obtained from the quick propagation algorithm (QP) with 4-9-1 topology. Based on the ANN analysis, the optimal conditions to obtain the highest yield were 148.3 mg enzyme, reaction temperature of 53.1°C, reaction time of 20.3 hours and betulinic acid to phthalic anhydride molar ratio of 1:1.24. The predicted and actual yields were 64.9 and 64.3%, respectively. In this work, the ANN and RSM analysis were investigated on the enzymatic synthesis of 3-O-phthalyl-betulinic acid for the first time. Finally, several betulinic acid esters (compounds 57-66) were synthesized using the optimal operation conditions which were obtained by the RSM technique. Esterification of betulinic acid with various anhydrides was performed at 54ºC in a mixture of n-hexane- chloroform (1:1, v/v) for 20.3 hours, catalyzed by Novozym 435, gave 24.7 to 79.3% yield. Five new compounds (58, 62, 64, 65 and 66) were synthesized for the first time in the present study. In brief, the anti-cancer activity of betulinic acid (1) and its 3-O-acylated derivatives (compounds 57-66) were evaluated against human lung carcinoma (A549) and human ovarian (CAOV3) cancer cell lines. In particular, compounds (59), (61) and (63) were found to show IC50 < 10 μg/ml against A549 cancer cell line tested and showed better cytotoxicity than betulinic acid. In the ovarian cancer cell line, all betulinic acid derivatives prepared revealed weaker cytotoxicity than betulinic acid

Enzymatic synthesis of betulinic acid ester as an anticancer agent: optimization study

Immobilized Candida antarctica lipase, Novozym 435, was used to catalyze the esterification reaction between betulinic acid and phthalic anhydride to synthesize 3-O-phthalyl betulinic acid in n-hexane/chloroform. Response surface methodology based on a five-level, four-variable central composite rotatable design was employed to evaluate the effects of synthesis parameters such as reaction time, reaction temperature, enzyme amount and substrate molar ratio on the yield of ester. Based on the response surface model, the optimal enzymatic synthesis conditions were predicted to be: reaction time 20.3 h, reaction temperature 53.9°C, enzyme amount 145.6 mg, betulinic acid to phthalic anhydride molar ratio 1:1.11. The predicted yield was 65.8% and the actual yield was 64.7%

Spectroscopic data of 3-O-acetyl-betulinic acid: an antitumor reagent

In this paper, the spectroscopic data of the 3-O-acetyl betulinic acid is reported. This compound was prepared by enzymatic reaction of betulinic acid and acetic anhydride in the presence of lipase from Candida antarctica (Novozem® 435) at 54oC for 20 h in 79.3 % yield

Synthesis and characterization of silver/montmorillonite/chitosan bionanocomposites by chemical reduction method and their antibacterial activity

Silver nanoparticles (AgNPs) of a small size were successfully synthesized using the wet chemical reduction method into the lamellar space layer of montmorillonite/chitosan (MMT/Cts) as an organomodified mineral solid support in the absence of any heat treatment. AgNO3, MMT, Cts, and NaBH4 were used as the silver precursor, the solid support, the natural polymeric stabilizer, and the chemical reduction agent, respectively. MMT was suspended in aqueous AgNO3/Cts solution. The interlamellar space limits were changed (d-spacing = 1.24–1.54 nm); therefore, AgNPs formed on the interlayer and external surface of MMT/Cts with d-average = 6.28–9.84 nm diameter. Characterizations were done using different methods, ie, ultraviolet-visible spectroscopy, powder X-ray diffraction, transmission electron microscopy, scanning electron microscopy, energy dispersive X-ray fluorescence spectrometry, and Fourier transform infrared spectroscopy. Silver/montmorillonite/chitosan bionanocomposite (Ag/MMT/Cts BNC) systems were examined. The antibacterial activity of AgNPs in MMT/Cts was investigated against Gram-positive bacteria, ie, Staphylococcus aureus and methicillin-resistant S. aureus and Gram-negative bacteria, ie, Escherichia coli, E. coli O157:H7, and Pseudomonas aeruginosa by the disc diffusion method using Mueller Hinton agar at different sizes of AgNPs. All of the synthesized Ag/MMT/Cts BNCs were found to have high antibacterial activity. These results show that Ag/MMT/Cts BNCs can be useful in different biological research and biomedical applications, including surgical devices and drug delivery vehicles

Artificial neural network modeling studies to predict the yield of enzymatic synthesis of betulinic acid ester

3β-O-phthalic ester of betulinic acid was synthesized from reaction of betulinic acid and phthalic anhydride using lipase as biocatalyst. This ester has clinical potential as an anticancer agent. In this study, artificial neural network (ANN) analysis of Candida antarctica lipase (Novozym 435) -catalyzed esterification of betulinic acid with phthalic anhydride was carried out. A multilayer feed-forward neural network trained with an error back-propagation algorithm was incorporated for developing a predictive model. The input parameters of the model are reaction time, reaction temperature, enzyme amount and substrate molar ratio while the percentage isolated yield of ester is the output. Four different training algorithms, belonging to two classes, namely gradient descent and Levenberg-Marquardt (LM), were used to train ANN. The paper makes a robust comparison of the performances of the above four algorithms employing standard statistical indices. The results showed that the quick propagation algorithm (QP) with 4-9-1 arrangement gave the best performances. The root mean squared error (RMSE), coefficient of determination (R2) and absolute average deviation (AAD) between the actual and predicted yields were determined as 0.0335, 0.9999 and 0.0647 for training set, 0.6279, 0.9961 and 1.4478 for testing set and 0.6626, 0.9488 and 1.0205 for validation set using quick propagation algorithm (QP)