Selective activation of TNFR1 and NF-κB inhibition by a novel biyouyanagin analogue promotes apoptosis in acute leukemia cells.

BACKGROUND: Acquired resistance towards apoptosis is a hallmark of cancer. Elimination of cells bearing activated oncogenes or stimulation of tumor suppressor mediators may provide a selection pressure to overcome resistance. KC-53 is a novel biyouyanagin analogue known to elicit strong anti-inflammatory and anti-viral activity. The current study was designed to evaluate the anticancer efficacy and molecular mechanisms of KC-53 against human cancer cells. METHODS: Using the MTT assay we examined initially how KC-53 affects the proliferation rates of thirteen representative human cancer cell lines in comparison to normal peripheral blood mononuclear cells (PBMCs) and immortalized cell lines. To decipher the key molecular events underlying its mode of action we selected the human promyelocytic leukemia HL-60 and the acute lymphocytic leukemia CCRF/CEM cell lines that were found to be the most sensitive to the antiproliferative effects of KC-53. RESULTS: KC-53 promoted rapidly and irreversibly apoptosis in both leukemia cell lines at relatively low concentrations. Apoptosis was characterized by an increase in membrane-associated TNFR1, activation of Caspase-8 and proteolytic inactivation of the death domain kinase RIP1 indicating that KC-53 induced mainly the extrinsic/death receptor apoptotic pathway. Regardless, induction of the intrinsic/mitochondrial pathway was also achieved by Caspase-8 processing of Bid, activation of Caspase-9 and increased translocation of AIF to the nucleus. FADD protein knockdown restored HL-60 and CCRF/CEM cell viability and completely blocked KC-53-induced apoptosis. Furthermore, KC-53 administration dramatically inhibited TNFα-induced serine phosphorylation on TRAF2 and on IκBα hindering therefore p65/NF-κΒ translocation to nucleus. Reduced transcriptional expression of pro-inflammatory and pro-survival p65 target genes, confirmed that the agent functionally inhibited the transcriptional activity of p65. CONCLUSIONS: Our findings demonstrate, for the first time, the selective anticancer properties of KC-53 towards leukemic cell lines and provide a detailed understanding of the molecular events underlying its dual anti-proliferative and pro-apoptotic properties. These results provide new insights into the development of innovative and targeted therapies for the treatment of some forms of leukemia.

LiSIs: An Online Scientific Workflow System for Virtual Screening.

Modern methods of drug discovery and development in recent years make a wide use of computational algorithms. These methods utilise Virtual Screening (VS), which is the computational counterpart of experimental screening. In this manner the in silico models and tools initial replace the wet lab methods saving time and resources. This paper presents the overall design and implementation of a web based scientific workflow system for virtual screening called, the Life Sciences Informatics (LiSIs) platform. The LiSIs platform consists of the following layers: the input layer covering the data file input; the pre-processing layer covering the descriptors calculation, and the docking preparation components; the processing layer covering the attribute filtering, compound similarity, substructure matching, docking prediction, predictive modelling and molecular clustering; post-processing layer covering the output reformatting and binary file merging components; output layer covering the storage component. The potential of LiSIs platform has been demonstrated through two case studies designed to illustrate the preparation of tools for the identification of promising chemical structures. The first case study involved the development of a Quantitative Structure Activity Relationship (QSAR) model on a literature dataset while the second case study implemented a docking-based virtual screening experiment. Our results show that VS workflows utilizing docking, predictive models and other in silico tools as implemented in the LiSIs platform can identify compounds in line with expert expectations. We anticipate that the deployment of LiSIs, as currently implemented and available for use, can enable drug discovery researchers to more easily use state of the art computational techniques in their search for promising chemical compounds. The LiSIs platform is freely accessible (i) under the GRANATUM platform at: http://www.granatum.org and (ii) directly at: http://lisis.cs.ucy.ac.cy.