Lead optimization of selective tubulin inhibitors as anti-trypanosomal agents

Previously synthesized tubulin inhibitors showed promising in vitro selectivity and activity against Human African Trypanosomiasis. Current aim is to improve the ligand efficiency and reduce overall hydrophobicity of the compounds, by lead optimization. Via combinatorial chemistry, 60 new analogs were synthesized. For biological assay Trypanosoma brucei brucei Lister 427 cell line were used as the parasite model and for the host model human embryonic kidney cell line HEK-293 and mouse macrophage cell line RAW 264.7 were used to test efficacy. Of the newly synthesized compounds 5, 39, 40, and 57 exhibited IC₅₀s below 5?µM inhibiting the growth of trypanosome cells and not harming the mammalian cells at equipotent concentration. Comparably, the newly synthesized compounds have a reduced amount of aromatic moieties resulting in a decrease in molecular weight. Due to importance of tubulin polymerization during protozoan life cycle its activity was assessed by western blot analyses. Our results indicated that compound 5 had a profound effect on tubulin function. A detailed structure activity relationship (SAR) was summarized that will be used to guide future lead optimization.     

α-Santalol, a derivative of sandalwood oil, induces apoptosis in human prostate cancer cells by causing caspase-3 activation

The anticancer effects of α-santalol, a major component of sandalwood oil, have been reported against the development of certain cancers such as skin cancer both in vitro and in vivo. The primary objectives of the current study were to investigate the cancer preventive properties of α-santalol on human prostate cancer cells PC-3 (androgen independent and P-53 null) and LNCaP (androgen dependent and P-53 wild-type), and determine the possible mechanisms of its action. The effect of α-santalol on cell viability was determined by trypan blue dye exclusion assay. Apoptosis induction was confirmed by analysis of cytoplasmic histone-associated DNA fragmentation using both an apoptotic ELISA kit and a DAPI fluorescence assay. Caspase-3 activity was determined using caspase-3 (active) ELISA kit. PARP cleavage was analyzed using immunoblotting. α-Santalol at 25-75 μM decreased cell viability in both cell lines in a concentration and time dependent manner. Treatment of prostate cancer cells with α-santalol resulted in induction of apoptosis as evidenced by DNA fragmentation and nuclear staining of apoptotic cells by DAPI. α-Santalol treatment also resulted in activation of caspase-3 activity and PARP cleavage. The α-santalol-induced apoptotic cell death and activation of caspase-3 was significantly attenuated in the presence of pharmacological inhibitors of caspase-8 and caspase-9. In conclusion, the present study reveals the apoptotic effects of α-santalol in inhibiting the growth of human prostate cancer cells.     

EMPIRICAL COMPARISON OF G MATRIX TEST STATISTICS: FINDING BIOLOGICALLY RELEVANT CHANGE

A central assumption of quantitative genetic theory is that the breeder's equation ( R = GP ⁻¹ S ) accurately predicts the evolutionary response to selection. Recent studies highlight the fact that the additive genetic variance–covariance matrix ( G ) may change over time, rendering the breeder's equation incapable of predicting evolutionary change over more than a few generations. Although some consensus on whether G changes over time has been reached, multiple, often-incompatible methods for comparing G matrices are currently used. A major challenge of G matrix comparison is determining the biological relevance of observed change. Here, we develop a "selection skewers" G matrix comparison statistic that uses the breeder's equation to compare the response to selection given two G matrices while holding selection intensity constant. We present a bootstrap algorithm that determines the significance of G matrix differences using the selection skewers method, random skewers, Mantel's and Bartlett's tests, and eigenanalysis. We then compare these methods by applying the bootstrap to a dataset of laboratory populations of Tribolium castaneum . We find that the results of matrix comparison statistics are inconsistent based on differing a priori goals of each test, and that the selection skewers method is useful for identifying biologically relevant G matrix differences.