Literature DB >> 22652759

Purification, characterization and structural determination of chitinases produced by Moniliophthora perniciosa.

Rafaela S Galante1, Alex G Taranto, Maria G B Koblitz, Aristóteles Góes-Neto, Carlos P Pirovani, Júlio C M Cascardo, Sandra H Cruz, Gonçalo A G Pereira, Sandra A de Assis.   

Abstract

The enzyme chitinase from Moniliophthora perniciosa the causative agent of the witches' broom disease in Theobroma cacao, was partially purified with ammonium sulfate and filtration by Sephacryl S-200 using sodium phosphate as an extraction buffer. Response surface methodology (RSM) was used to determine the optimum pH and temperature conditions. Four different isoenzymes were obtained: ChitMp I, ChitMp II, ChitMp III and ChitMp IV. ChitMp I had an optimum temperature at 44-73ºC and an optimum pH at 7.0-8.4. ChitMp II had an optimum temperature at 45-73ºC and an optimum pH at 7.0-8.4. ChitMp III had an optimum temperature at 54-67ºC and an optimum pH at 7.3-8.8. ChitMp IV had an optimum temperature at 60ºC and an optimum pH at 7.0. For the computational biology, the primary sequence was determined in silico from the database of the Genome/Proteome Project of M. perniciosa, yielding a sequence with 564 bp and 188 amino acids that was used for the three-dimensional design in a comparative modeling methodology. The generated models were submitted to validation using Procheck 3.0 and ANOLEA. The model proposed for the chitinase was subjected to a dynamic analysis over a 1 ns interval, resulting in a model with 91.7% of the residues occupying favorable places on the Ramachandran plot and an RMS of 2.68.

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Year:  2012        PMID: 22652759     DOI: 10.1590/s0001-37652012000200016

Source DB:  PubMed          Journal:  An Acad Bras Cienc        ISSN: 0001-3765            Impact factor:   1.753


  2 in total

1.  Lentinula edodes Genome Survey and Postharvest Transcriptome Analysis.

Authors:  Yuichi Sakamoto; Keiko Nakade; Shiho Sato; Kentaro Yoshida; Kazuhiro Miyazaki; Satoshi Natsume; Naotake Konno
Journal:  Appl Environ Microbiol       Date:  2017-05-01       Impact factor: 4.792

2.  Reducing the standard deviation in multiple-assay experiments where the variation matters but the absolute value does not.

Authors:  Pablo Echenique-Robba; María Alejandra Nelo-Bazán; José A Carrodeguas
Journal:  PLoS One       Date:  2013-10-30       Impact factor: 3.240

  2 in total

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