Evaluation of the Structure-Activity Relationship of Hemoproteins through Physicochemical Studies: Hemoglobins as a Prototype of Biosensor

In the present work, we have studied a group of prerequisites in terms of “structure-function relationship” of hemoproteins, especially hemoglobins, emphasizing the role of the heme and its chemical environment in the biochemical and physicochemical properties of the biomolecule. We have discussed the ferrous center and its properties as coordination center; the macrocyclic ligands, especially the porphyrins; the esterochemical and electronic properties of the iron-porphyrins (heme groups); and the interaction between heme groups and globins, which is related to several redox and oligomeric properties of hemoprotein systems and its potential applications with respect to novel materials. One of the main uses of hemoglobins in new materials is also discussed, which is its employment as a biosensor. Therefore, we have discussed the development of novel biosensors based on hemoglobins and their physico-chemical properties as well as on the main molecules of biological relevance that have been detected by these biosensors, such as hydrogen peroxide (H2O2), nitric oxide (NO), and cholesterol, among others. Indeed, several important biomolecules and biological processes can be detected and/or evaluated by devices that present hemoglobins as leading chemical components. Different apparatus are covered with respect to distinct characteristics, such as chemical stability, sensitivity, selectivity, reproducibility, durability, optimum conditions of measurements, etc. and their respective characteristics are analyzed

Towards a genome-wide transcriptogram: the Saccharomyces cerevisiae case

A genome modular classification that associates cellular processes to modules could lead to a method to quantify the differences in gene expression levels in different cellular stages or conditions: the transcriptogram, a powerful tool for assessing cell performance, would be at hand. Here we present a computational method to order genes on a line that clusters strongly interacting genes, defining functional modules associated with gene ontology terms. The starting point is a list of genes and a matrix specifying their interactions, available at large gene interaction databases. Considering the Saccharomyces cerevisiae genome we produced a succession of plots of gene transcription levels for a fermentation process. These plots discriminate the fermentation stage the cell is going through and may be regarded as the first versions of a transcriptogram. This method is useful for extracting information from cell stimuli/responses experiments, and may be applied with diagnostic purposes to different organisms