Bilsland, Alan E. published the artcileIdentification of a Selective G1-Phase Benzimidazolone Inhibitor by a Senescence-Targeted Virtual Screen Using Artificial Neural Networks, Computed Properties of 330161-87-0, the publication is Neoplasia (New York, NY, United States) (2015), 17(9), 704-715, database is CAplus and MEDLINE.
Cellular senescence is a barrier to tumorigenesis in normal cells, and tumor cells undergo senescence responses to genotoxic stimuli, which is a potential target phenotype for cancer therapy. However, in this setting, mixed-mode responses are common with apoptosis the dominant effect. Hence, more selective senescence inducers are required. Here we report a machine learning-based in silico screen to identify potential senescence agonists. We built profiles of differentially affected biol. process networks from expression data obtained under induced telomere dysfunction conditions in colorectal cancer cells and matched these to a panel of 17 protein targets with confirmatory screening data in PubChem. We trained a neural network using 3517 compounds identified as active or inactive against these targets. The resulting classification model was used to screen a virtual library of ∼ 2M lead-like compounds One hundred and forty-seven virtual hits were acquired for validation in growth inhibition and senescence-associated β-galactosidase assays. Among the found hits, a benzimidazolone compound, CB-20903630, had low micromolar IC50 for growth inhibition of HCT116 cells and selectively induced senescence-associated β-galactosidase activity in the entire treated cell population without cytotoxicity or apoptosis induction. Growth suppression was mediated by G1 blockade involving increased p21 expression and suppressed cyclin B1, CDK1, and CDC25C. In addition, the compound inhibited growth of multicellular spheroids and caused severe retardation of population kinetics in long-term treatments. Preliminary structure-activity and structure clustering analyses are reported, and expression anal. of CB-20903630 against other cell cycle suppressor compounds suggested a PI3K/AKT-inhibitor-like profile in normal cells, with different pathways affected in cancer cells.
Neoplasia (New York, NY, United States) published new progress about 330161-87-0. 330161-87-0 belongs to indole-building-block, auxiliary class Protein Tyrosine Kinase/RTK,Src, name is SU6656, and the molecular formula is C19H21N3O3S, Computed Properties of 330161-87-0.
Referemce:
https://www.nature.com/articles/s41429-020-0333-2,
Preparation of Indole Containing Building Blocks for the Regiospecific Construction of Indole Appended Pyrazoles and Pyrroles