  This paper deals with the relations among structural, topological, and
chemical properties of the E.Coli proteome from the vantage point of the
solubility/aggregation propensity of proteins. Each E.Coli protein is initially
represented according to its known folded 3D shape. This step consists in
representing the available E.Coli proteins in terms of graphs. We first analyze
those graphs by considering pure topological characterizations, i.e., by
analyzing the mass fractal dimension and the distribution underlying both
shortest paths and vertex degrees. Results confirm the general architectural
principles of proteins. Successively, we focus on the statistical properties of
a representation of such graphs in terms of vectors composed of several
numerical features, which we extracted from their structural representation. We
found that protein size is the main discriminator for the solubility, while
however there are other factors that help explaining the solubility degree. We
finally analyze such data through a novel one-class classifier, with the aim of
discriminating among very and poorly soluble proteins. Results are encouraging
and consolidate the potential of pattern recognition techniques when employed
to describe complex biological systems.
