Synthesis, antimycobacterial evaluation, and QSAR analysis of meso-dihydroguaiaretic acid derivatives

Cytotoxicity Activity of Some meso-Dihydroguaiaretic Acid Derivatives and Mode of Action of the Most Active Compound

The aim of this study was to screen sixteen meso-1 semi-synthetic derivatives bearing ether, esther, carbamate, phosphate or aminoether functional groups against five cancer cell lines: MCF-7 (breast), A549 (lung), HepG2 (liver), HeLa (cervix), and DU145 (prostate) at 25 μM using the MTT assay. Results from the screening showed that two derivatives had the lowest percentage of cell viability at 25 μM, the aminoether derivative meso-11 and the esther derivative meso-20 against A549 (44.15±0.78 %) and MCF-7 (41.60±0.92 %), respectively. Then, it was determined the IC50 value of each compound against their most sensitive cancer cell line. Results showed that aminoether derivative meso-11 showed potent cytotoxicity against A549 (IC50 =17.11±2.11 μM), whereas it resulted more cytotoxic against the LL-47 lung normal cell line (IC50 =9.49±1.19 μM) having a Selective Index (SI) of 0.55. On the other hand, the esther derivative meso-20 exhibited potent activity against MCF-7 (IC50 =18.20±1.98 μM), whereas it displayed moderate cytotoxicity against the MCF-10 breast normal cell line (IC50 =41.22±2.17 μM) with a SI of 2.2. Finally, studies on the mechanism of action of meso-20 indicated disruption of MCF-7 plasma membrane in vitro and the AMPK activation in silico.

Reaching for the bright StARs in chemical space

Visualization of activity data in chemical space is common in drug discovery. Navigating the space in a systematic manner is not trivial, given its size and huge coverage. To this end, methods for data visualization have been developed charting biological activity into chemical space. Herein, we review the progress in different visualization approaches to explore the chemical space aiming at reaching insightful structure-activity relationships (SARs) in the chemical space. We discuss recent methods including consensus diversity plots, ChemMaps, and constellation plots. Several of the methods we review can be extended to analyze other properties of interest in medicinal chemistry, such as structure-toxicity relationships, and can be adapted to postprocess results of virtual screening (VS) of large compound libraries.