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DNA-based Killer Automaton: The Innovative Nanomedicine

S. Liu and J.-L. Gaudiot
University of California Irvine, US

the bystander effect, molecular automaton, DNA computing, homologous GJIC channels

Based upon Shapiro’s molecular automaton model, we propose the DNA-based Killer Automaton (DKA), an innovative nanomedicine for cancer treatment. Each DKA is composed of a DNA cancer detector and a cytotoxic chemical. Equipped with an internal DNA Computing algorithm, the DKA cancer detector checks the cell’s mRNA strands to determine whether the cell is cancerous and release the cytotoxic chemical to kill the cell only if the cell is cancerous. In addition, due to the bystander effect, the cytotoxic material carried by DKA will only diffuse to the cells that express cancerous behavior through the homologous GJIC channels, thus completely curing cancer with minimal side effects. In order to predict the efficacy of DKA in cancer treatments, we have constructed a software model to simulate the DKA mechanisms in an artificial multi-cell environment. The results obtained from these simulations show that the efficacy of this nanomedicine is linearly dependent on the dose of injection and the degree of connectivity between cancer cells. Also, the results confirm that due to the bystander effect, as long as DKA can enter five to ten percent of all cancer cells, they are able to propagate to all cancer cells through and thus result in complete tumor regression. In conclusion, it can be inferred from our work that the bystander effect greatly enhances the delivery of nanomedicine in a cancer tumor, thus resulting in a higher killing efficacy.

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