Τρίτη 10 Ιανουαρίου 2017

Structure prediction and network analysis of chitinases from the Cape sundew, Drosera capensis

Publication date: March 2017
Source:Biochimica et Biophysica Acta (BBA) - General Subjects, Volume 1861, Issue 3
Author(s): Megha H. Unhelkar, Vy T. Duong, Kaosoluchi N. Enendu, John E. Kelly, Seemal Tahir, Carter T. Butts, Rachel W. Martin
BackgroundCarnivorous plants possess diverse sets of enzymes with novel functionalities applicable to biotechnology, proteomics, and bioanalytical research. Chitinases constitute an important class of such enzymes, with future applications including human-safe antifungal agents and pesticides. Here, we compare chitinases from the genome of the carnivorous plant Drosera capensis to those from related carnivorous plants and model organisms.MethodsUsing comparative modeling, in silico maturation, and molecular dynamics simulation, we produce models of the mature enzymes in aqueous solution. We utilize network analytic techniques to identify similarities and differences in chitinase topology.ResultsHere, we report molecular models and functional predictions from protein structure networks for eleven new chitinases from D. capensis, including a novel class IV chitinase with two active domains. This architecture has previously been observed in microorganisms but not in plants. We use a combination of comparative and de novo structure prediction followed by molecular dynamics simulation to produce models of the mature forms of these proteins in aqueous solution. Protein structure network analysis of these and other plant chitinases reveal characteristic features of the two major chitinase families.General significanceThis work demonstrates how computational techniques can facilitate quickly moving from raw sequence data to refined structural models and comparative analysis, and to select promising candidates for subsequent biochemical characterization. This capability is increasingly important given the large and growing body of data from high-throughput genome sequencing, which makes experimental characterization of every target impractical.

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