Proteotronics: a toolkit for bioelectronics

The talk gives a bird’s eye view on a procedure named Proteotronics [1], used to analyze some physical properties of biomolecules, in particular proteins and aptamers. The name refers to the principal aim of this method, i.e. to investigate the electronic features of this special kind of matter, starting from its peculiar topology, which is not regular but ordered. In doing so, a complex network approach is used to reproduce the space (3D) structure of the biomolecule, while its electronic features are mimicked by using lumped elements. Particular attention is paid to proteins when used as the active part of electrical biosensors. In that case, the biochemical sequence of actions due to the capture of the specific target is converted into an electrical signal. This signal is the result of the protein-target interaction and is finely captured by an impedance network. Linear and super-linear electrical responses are analyzed in facts and figures, comparing experimental data and theoretical expectations. Affinity is a quite complex concept used to define the quality of binding of two (macro)molecules, and is connected with both topological (structure complementarity) and functional (stability of bonds) features of the partners. As a very recent result, the affinity of different aptamers for their specific targets has been interpreted in terms of some standard topological properties of the analogue complex networks, as well as of the associated resistance. Affinity is also the key concept adopted by several in silico structure prediction procedures and docking methods. Some new tools developed inside the proteotronics framework were applied to the analysis of a set of 5 aptamers whose structure with and without the target protein was obtained by using a computational procedure based on free software, SimRNA and Autodock Vina [2]. The configuration produced for each aptamer belong to two different families one, called hair, in which the aptamer is on the top of the protein, in the natural binding domain; the other, called belt, in which the aptamer hangs the protein often far from the binding domain. The scoring of the structures given by the computational procedure is in line with the closeness of the partner biomolecules, as verified by using the proteotronics approach, but it is not able to select between hair and belt configurations [2]. To better refine this scoring, we build a novel structure-based indicator. The selection based on both the indicators, produces a prevalence of the hair configurations for the highest affinity aptamer, and a prevalence of the belt configurations for lowest affinity aptamer. However, the final say about the role of belt configurations is expected by crystallographic data. In conclusion, we have analyzed several facets of the affinity concept, in different frameworks and by using the proteotronics approach. Present and future results will help us get a deep comprehension of chemical affinity.