Computational Gene - A Potential Application: in Situ Diagnostics and Therapy of Cancer

A Potential Application: in Situ Diagnostics and Therapy of Cancer

Computational genes might be used in the future to correct aberrant mutations in a gene or group of genes that can trigger disease phenotypes. One of the most prominent examples is the tumor suppressor p53 gene, which is present in every cell, and acts as a guard to control growth. Mutations in this gene can abolish its function, allowing uncontrolled growth that can lead to cancer. For instance, a mutation at codon 249 in the p53 protein is characteristic for hepatocellular cancer. This disease could be treated by the CDB3 peptide which binds to the p53 core domain and stabilises its fold.

A single disease-related mutation can be then diagnosed and treated by the following diagnostic rule,

if protein X_mutated_at_codon_Y then produce_drug fi (1)

Such a rule might be implemented by a molecular automaton consisting of two partially dsDNA molecules and one ssDNA molecule, which corresponds to the disease-related mutation and provides a molecular switch for the linear self-assembly of the functional gene (Fig. 2). The gene structure is completed by a cellular ligase present in both eukaryotic and prokaryotic cells. The transcription and translation machinery of the cell is then in charge of therapy and administers either a wild-type protein or an anti-drug (Fig. 3). The rule (1) may even be generalised to involve mutations from different proteins allowing a combined diagnosis and therapy.

In this way, computational genes might allow implementation in situ of a therapy as soon as the cell starts developing defective material. Computational genes combine the techniques of gene therapy which allows to replace in the genome an aberrant gene by its healthy counterpart, as well as to silence the gene expression (similar to antisense technology).