Artigo de Periódico
Comparative protein analysis of the chitin metabolic pathway in extant organisms: A complex network approach
Fecha
2010Registro en:
0303-2647
v. 101, n. 1
Autor
Góes Neto, Aristóteles
Diniz, Marcelo V. C.
Santos, Leonardo B. L.
Pinho, Suani Tavares Rubim de
Miranda, José Garcia Vivas
Lobão, Thierry Corrêa Petit
Borges, Ernesto Pinheiro
El-Hani, Charbel Niño
Andrade, Roberto Fernandes Silva
Góes Neto, Aristóteles
Diniz, Marcelo V. C.
Santos, Leonardo B. L.
Pinho, Suani Tavares Rubim de
Miranda, José Garcia Vivas
Lobão, Thierry Corrêa Petit
Borges, Ernesto Pinheiro
El-Hani, Charbel Niño
Andrade, Roberto Fernandes Silva
Institución
Resumen
Chitin is a structural endogenous carbohydrate, which is a major component of fungal cell walls and arthropod exoskeletons. A renewable resource and the second most abundant polysaccharide in nature
after cellulose, chitin is currently used for waste water clearing, cosmetics, medical, and veterinary applications.
This work comprises data mining of protein sequences related to the chitin metabolic pathway of completely sequenced genomes of extant organisms pertaining to the three life domains, followed by meta-analysis using traditional sequence similarity comparison and complex network approaches. Complex networks involving proteins of the chitin metabolic pathway in extant organisms were constructed based on protein sequence similarity. Several usual network indices were estimated in order to obtain
information on the topology of these networks, including those related to higher order neighborhood properties. Due to the assumed evolutionary character of the system, we also discuss issues related to
modularity properties, with the concept of edge betweenness playing a particularly important role in our analysis. Complex network approach correctly identifies clusters of organisms that belong to phylogenetic groups without any a priori knowledge about the biological features of the investigated protein sequences. We envisage the prospect of using such a complex network approach as a high-throughput
phylogenetic method.