BackgroundIn living cells, proteins are in continuous motion and interaction with the surrounding medium and/or other proteins and ligands. These interactions are mediated by protein features such as electrostatic and lipophilic potentials. The availability of protein structures enables the study of their surfaces and surface characteristics, based on atomic contribution. Traditionally, these properties are calculated by physico-chemical programs and visualized as range of colors that vary according to the tool used and imposes the necessity of a legend to decrypt it. The use of color to encode both characteristics makes the simultaneous visualization almost impossible, requiring these features to be visualized in different images. In this work, we describe a novel and intuitive code for the simultaneous visualization of these properties.MethodsRecent advances in 3D animation and rendering software have not yet been exploited for the representation of biomolecules in an intuitive, animated form. For our purpose we use Blender, an open-source, free, cross-platform application used professionally for 3D work.On the basis Blender, we developed BioBlender, dedicated to biological work: elaboration of protein motion with simultaneous visualization of their chemical and physical features.Electrostatic and lipophilic potentials are calculated using physico-chemical software and scripts, organized and accessed through BioBlender interface.ResultsA new visual code is introduced for molecular lipophilic potential: a range of optical features going from smooth-shiny for hydrophobic regions to rough-dull for hydrophilic ones. Electrostatic potential is represented as animated line particles that flow along field lines, proportional to the total charge of the protein.ConclusionsOur system permits visualization of molecular features and, in the case of moving proteins, their continuous perception, calculated for each conformation during motion. Using real world tactile/sight feelings, the nanoscale world of proteins becomes more understandable, familiar to our everyday life, making it easier to introduce "un-seen" phenomena (concepts) such as hydropathy or charges. Moreover, this representation contributes to gain insight into molecular functions by drawing viewer's attention to the most active regions of the protein. The program, available for Windows, Linux and MacOS, can be downloaded freely from the dedicated website http://www.bioblender.eu

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Chemical changes were observed by Fourier transform microspectroscopy (FT-IR-M) in DNA and RNA samples treated with increasing amounts of ozone. The nucleobase reactivity and conformational changes in nucleic acids were followed through the trend of certain spectroscopic parameters calculated from the spectra. The P1 and P2 parameters (calculated from the ratios of the optical densities of the bands at 1692 and 1654 and at 1728 and 1654 cm−1, respectively), involving base absorptions, are sensitive to the chemical action of ozone on covalent bonds of purinic and pirimidinic bases. The P3 parameter (calculated from the ratios of the optical densities of the bands at 1230 and 1090 cm−1) is sensitive to conformational changes in the phosphate-ribose backbone of nucleic acids. We found that, as the amount of ozone increases, the P1, P2, and P3 parameters increase for both the DNA and RNA sample spectra, but the curve trend and the concentration range that gave significant parameter changes were different for DNA and RNA. DNA spectra showed a sigmoidal increase in P1 and P2 parameters ( C1/2 = 1.6 mg/mL, the concentration of ozone at which the parameters observed changed by 50%), a plateau between 2 and 4.5 mg/mL of ozone, and a slow linear increase for ozone concentrations >5 mg/mL. Instead, a C1/2 = 2.5 mg/mL was evaluated from the P3 vs. ozone concentration plot. The plots of P1, P2, and P3 parameters calculated from the RNA sample spectra vs. ozone concentration showed a saturation-shape curve that reached its maximum value between 0 and 1.9 mg/mL. On the basis of these results, several hypotheses are suggested to explain the reaction mechanism of DNA and RNA nucleobases and the conformational changes in nucleic acids.

Stroke is the second single highest cause of death in Europe. The low reliability of animal models in replicating the human disease is one of the most serious problems in the field of medical and pharmaceutical research about stroke. The standard models for the study of ischemic stroke are often poorly predictive as they simulate only partially the human disease. This work aims at investigating animal models with diseases typically associated with the onset of stroke in human patients. We have designed and realised a knowledge base for collecting, elaborating, and extracting analytical results of genomic, proteomic, biochemical, morphological investigations from animal models of cerebral stroke. Data analysis techniques are tailored to make the data available for processing and correlation, in\ud order to increase the predictive value of the preclinical data, to perform biosimulation studies, and to support both academic and industrial research in the area of cerebral stroke therapy. A first statistical analysis of the retrieved information leads to the validation of our animal models and suggests a predictive and translational value for parameters related to a specific model. In particular, concerning gene expression data, we have applied a data analysis pipeline that initially takes into account an initial set of 64,000 genes and brings down the focus on a few tens of them