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Advanced structure prediction methods

Final Activity Report Summary - STRUCTPRED (Advanced structure prediction methods)

The identification of the deoxyribonucleic acid (DNA) binding rules was the objective regarding research on transcription factors. This would allow us to understand the core of neoplastic signalling pathways, as induced by oncogenes and by growth controlling molecules, e.g. trop and might open realistic possibilities to intervene at specific nodes of this signalling network, to switch off tumour specific phenotypes.

Trigger factor (TF) DNA binding code rules dictating the specificity of binding of amino acids to nucleotide bases were determined in a dataset of 100 high resolution protein DNA structures. The frequency and energy of interaction between each amino acid and base and the energetics of water mediated interactions were computed. The analysis was carried out using HINT, a non- Newtonian force field encoding both enthalpic and entropic contributions, and Rank, a geometry-based tool for evaluating hydrogen bond interactions.

A frequency and energy based preferential interaction of Arg and Lys with G, Asp and Glu with C, and Asn and Gln with A was found. Not only favourable, but also unfavourable contacts were found to be conserved. Water mediated interactions strongly increased the probability of Thr-A, Lys-A, and Lys-C contacts. The frequency, interaction energy and water enhancement factors associated with each amino acid base pair were used to predict the base triplet recognised by the helix motif in 45 zinc fingers, which represented an ideal case study for the analysis of one-to-one amino acid base pair contacts. The model correctly predicted 70.4 % of 135 amino acid base pairs and, by weighting the energetic relevance of each amino acid-base pair to the overall recognition energy, it yielded a prediction rate of 89.7 % (Journal of Computational Chemistry 29(12): 1955-1969, 2008).

Taken together, our findings led to the identification of the rules of binding of TF to DNA. This might be fundamenal to understanding the core of the neoplastic program, as specifically induced by oncogenes and growth-controlling molecules. This might also open realistic possibilities to modulate specific steps of these signalling networks, e.g. with small molecule structural mimics or peptides, as novel anti-cancer therapeutic approaches.

On the other hand, trop-2 was a novel, critical controller of tumour cell growth. To understand the role of trop-2 in the regulation of cell to cell adhesion, cell size and cell growth, the transcriptome of tumour cells was analysed. This led to the isolation of a chimeric cyclin D1-trop2 messenger ribonucleic acid (mRNA) from human ovarian and mammary cancer cells. The cyclin D1-trop2 mRNA was shown to be a potent oncogene as it transformed naive, primary cells in vitro and induced aggressive tumour growth in vivo in cooperation with activated RAS. Silencing of the chimeric mRNA inhibited the growth of breast cancer cells. The cyclin D-trop2 mRNA was expressed by a large fraction of the human gastrointestinal, ovarian and endometrial tumours that were analysed. It was most frequently detected in intestinal cell aneuploid cancers and was co-expressed with activated RAS oncogenes, consistent with a cooperative transforming activity in human cancers. The chimeric mRNA was a bicistronic transcript of posttranscriptional origin that independently translated the cyclin D1 and trop-2 proteins. This was a novel mechanism of cyclin D1 activation that achieved the truncation of the cyclin D1 mRNA in the absence of chromosomal rearrangements. This led to a higher cyclin D1 mRNA stability, with inappropriate expression during the cell cycle. The stabilised cyclin D1 mRNA cooperated with TROP2 in stimulating the growth of the expressing cells. These findings showed a novel epigenetic, oncogenic mechanism, which appeared widespread in human cancers, as mentioned in Cancer Research 68: (19): 8113-8121, 2008.