Understanding structural/functional properties of immunoconjugates for cancer therapy by computational approaches.

Monoclonal antibodies coupled to highly toxic molecules (immunoconjugates) are currently being developed for cancer therapy. We have used an in silico procedure for evaluating some physicochemical properties of two tumor-targeting anti-HER2 immunoconjugates: (a) the single-chain antibody scFv(FRP5) linked to a bacterial toxin, that has been recently progressed to phase I clinical trial in human cancer; (b) the putative molecule formed by the intrinsically stable scFv(800E6), which has been proposed as toxin carrier to cancer cells in human therapy, joined to the same toxin of (a). Structural models of the immunoconjugates have been built by homology modeling and assessed by molecular dynamics simulations. The trajectories have been analyzed to extract some biochemical properties and to assess the potential effects of the toxin on the structure and dynamics of the anti-HER2 antibodies. The results of the computational approach indicate that the antibodies maintain their correct folding even in presence of the toxin, whereas a certain stiffness in correspondence of some structural regions is observed. Furthermore, the toxin does not seem to affect the antibody solubility, whereas it enhances the structural stability. The proposed computational approach represent a promising tool for analyzing some physicochemical properties of immunoconjugates and for predicting the effects of the linked toxin on structure, dynamics, and functionality of the antibodies.

IMAGE: a new tool for the prediction of transcription factor binding sites.

IMAGE is an application tool, based on the vector quantization method, aiding the discovery of nucleotidic sequences corresponding to Transcription Factor binding sites. Starting from the knowledge of regulation regions of a number of co-expressed genes, the software is able to predict the occurrence of specific motifs of different lengths (starting from 6 base pairs) with a defined number of punctual mutations.

From the sequence to the superstructural properties of DNAs.

A theoretical model for predicting intrinsic and induced DNA superstructures as well as their thermodynamic properties is presented. Intrinsic sequence-dependent superstructures are evaluated by integrating local deviations from the canonical B-DNA of the different dinucleotide steps. Induced superstructures are obtained by adopting the principle of minimum deformation free energy, evaluated in the Fourier space, in the framework of first-order elasticity. Finally dinucleotide stacking energies and melting temperatures are considered to account for local flexibility. In fact the two scales are strongly correlated. The model works very satisfactorily in predicting the sequence-dependent effects on the DNA experimental behavior, such as the gel electrophoresis retardation, the writhe transitions in topologically constrained domains, the thermodynamic constants of circularization reactions as well as the nucleosome thermodynamic stability constants.