The central nervous system (CNS) is a nested network at all levels of its organization. In particular, neuronal cellular networks (the neuronal circuits), interconnected to form neuronal systems, are formed by neurons, which operate thanks to their molecular networks. Proteins are the main components of the molecular networks and via protein-protein interactions can be assembled in multimeric complexes, which can work as micro-devices. On this basis, we have introduced the term "fractal logic" to describe networks of networks where at the various levels of the nested organization the same rules (logic) to perform operations are used. If this assumption is true, the description of the information handling at one of the nested levels sheds light on the way in which similar operations are carried out at other levels. This conceptual frame has been used to deduce from some features of neuronal networks the features of the molecular networks as far as modes for inter-node communication and their architecture. It should be noted that these features are such to allow a highly regulated cross-talk between signalling pathways, hence preserving selectivity and privacy. To investigate these aspects, the protein-protein interactions in beta2 Adrenergic Receptor (beta2AR) and Epidermal growth factor receptor (EGFR) signalling pathways have been analysed. The presence of disordered sequences in interacting domains can favour via the "fly-casting mechanism" protein-protein interactions, in addition it favours an induced-fitting rather than a lock-key type of interactions. Thus, by means of a computer assisted analysis the presence of disorder sequences in the main streams of the molecular networks that have beta2AR and EGFR as input proteins leading to MAP kinase activation has been evaluated.

Understanding neuronal molecular networks builds on neuronal cellular network architecture

GUIDOLIN, DIEGO;
2008

Abstract

The central nervous system (CNS) is a nested network at all levels of its organization. In particular, neuronal cellular networks (the neuronal circuits), interconnected to form neuronal systems, are formed by neurons, which operate thanks to their molecular networks. Proteins are the main components of the molecular networks and via protein-protein interactions can be assembled in multimeric complexes, which can work as micro-devices. On this basis, we have introduced the term "fractal logic" to describe networks of networks where at the various levels of the nested organization the same rules (logic) to perform operations are used. If this assumption is true, the description of the information handling at one of the nested levels sheds light on the way in which similar operations are carried out at other levels. This conceptual frame has been used to deduce from some features of neuronal networks the features of the molecular networks as far as modes for inter-node communication and their architecture. It should be noted that these features are such to allow a highly regulated cross-talk between signalling pathways, hence preserving selectivity and privacy. To investigate these aspects, the protein-protein interactions in beta2 Adrenergic Receptor (beta2AR) and Epidermal growth factor receptor (EGFR) signalling pathways have been analysed. The presence of disordered sequences in interacting domains can favour via the "fly-casting mechanism" protein-protein interactions, in addition it favours an induced-fitting rather than a lock-key type of interactions. Thus, by means of a computer assisted analysis the presence of disorder sequences in the main streams of the molecular networks that have beta2AR and EGFR as input proteins leading to MAP kinase activation has been evaluated.
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/2474991
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 32
  • ???jsp.display-item.citation.isi??? 27
social impact