A unified theory of carcinogenesis based on order–disorder transitions in DNA structure as studied in the human ovary and breast

Fourier transform-infrared/statistics models demonstrate that the malignant transformation of morphologically normal human ovarian and breast tissues involves the creation of a high degree of structural modification (disorder) in DNA, before restoration of order in distant metastases. Order–disorder transitions were revealed by methods including principal components analysis of infrared spectra in which DNA samples were represented by points in two-dimensional space. Differences between the geometric sizes of clusters of points and between their locations revealed the magnitude of the order–disorder transitions. Infrared spectra provided evidence for the types of structural changes involved. Normal ovarian DNAs formed a tight cluster comparable to that of normal human blood leukocytes. The DNAs of ovarian primary carcinomas, including those that had given rise to metastases, had a high degree of disorder, whereas the DNAs of distant metastases from ovarian carcinomas were relatively ordered. However, the spectra of the metastases were more diverse than those of normal ovarian DNAs in regions assigned to base vibrations, implying increased genetic changes. DNAs of normal female breasts were substantially disordered (e.g., compared with the human blood leukocytes) as were those of the primary carcinomas, whether or not they had metastasized. The DNAs of distant breast cancer metastases were relatively ordered. These findings evoke a unified theory of carcinogenesis in which the creation of disorder in the DNA structure is an obligatory process followed by the selection of ordered, mutated DNA forms that ultimately give rise to metastases.

Folding funnels and frustration in off-lattice minimalist protein landscapes

A full quantitative understanding of the protein folding problem is now becoming possible with the help of the energy landscape theory and the protein folding funnel concept. Good folding sequences have a landscape that resembles a rough funnel where the energy bias towards the native state is larger than its ruggedness. Such a landscape leads not only to fast folding and stable native conformations but, more importantly, to sequences that are robust to variations in the protein environment and to sequence mutations. In this paper, an off-lattice model of sequences that fold into a β-barrel native structure is used to describe a framework that can quantitatively distinguish good and bad folders. The two sequences analyzed have the same native structure, but one of them is minimally frustrated whereas the other one exhibits a high degree of frustration.