Virtual screening of chemical compounds active against breast cancer cell lines based on cell cycle modelling, prediction of cytotoxicity and interaction with targets.

Bio- and chemoinformatics methods are widely used for the detection of mechanisms of cancer, to search for potential drug targets and their ligands. Regulatory network analysis based on signalling pathways, and cell cycle regulation provides better understanding of diseases with multiple mechanisms of pathogenesis. We developed an approach for in silico prediction of the cytotoxic effect of chemical compounds in non-transformed and breast cancer cell lines. This approach combines the prediction of the interaction between chemical compounds and human proteins, cytotoxicity and regulatory network modelling taking into account gene expression. Application of our approach to virtual screening of libraries of commercially available compounds allowed selection of dozens of promising hits. These molecules are predicted to interact with the identified targets and exhibit cytotoxicity against breast cancer cell lines but not non-tumour human cell lines. Experimental testing of 49 selected compounds against MDA-MB-231 and MCF7 breast cancer cell lines confirmed the activity of eight compounds with IC50 values ranged from 0.8 to 50 μM. Thus, the developed approach may be applied for virtual screening for cytotoxic compounds against tumour cell lines.