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X-ray structures of Na-GST-1 and Na-GST-2 two glutathione s-transferase from the human hookworm Necator americanus

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      Abstract

      Background

      Human hookworm infection is a major cause of anemia and malnutrition of adults and children in the developing world. As part of on-going efforts to control hookworm infection, The Human Hookworm Vaccine Initiative has identified candidate vaccine antigens from the infective L3 larval stages and adult stages of the parasite. Adult stage antigens include the cytosolic glutathione-S-transferases (GSTs). Nematode GSTs facilitate the inactivation and degradation of a variety of electrophilic substrates (drugs) via the nucleophilic addition of reduced glutathione. Parasite GSTs also play significant roles in multi-drug resistance and the modulation of host-immune defense mechanisms.

      Results

      The crystal structures of Na-GST-1 and Na-GST-2, two major GSTs from Necator americanus the main human hookworm parasite, have been solved at the resolution limits of 2.4 Å and 1.9 Å respectively. The structure of Na-GST-1 was refined to R-factor 18.9% (R-free 28.3%) while that of Na-GST-2 was refined to R-factor 17.1% (R-free 21.7%). Glutathione usurped during the fermentation process in bound in the glutathione binding site (G-site) of each monomer of Na-GST-2. Na-GST-1 is uncomplexed and its G-site is abrogated by Gln 50. These first structures of human hookworm parasite GSTs could aid the design of novel hookworm drugs.

      Conclusion

      The 3-dimensional structures of Na-GST-1 and Na-GST-2 show two views of human hookworm GSTs. While the GST-complex structure of Na-GST-2 reveals a typical GST G-site that of Na-GST-1 suggests that there is some conformational flexibility required in order to bind the substrate GST. In addition, the overall binding cavities for both are larger, more open, as well as more accessible to diverse ligands than those of GSTs from organisms that have other major detoxifying mechanisms. The results from this study could aid in the design of novel drugs and vaccine antigens.

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      Most cited references 56

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      This paper reviews the mathematical basis of maximum likelihood. The likelihood function for macromolecular structures is extended to include prior phase information and experimental standard uncertainties. The assumption that different parts of a structure might have different errors is considered. A method for estimating sigma(A) using 'free' reflections is described and its effects analysed. The derived equations have been implemented in the program REFMAC. This has been tested on several proteins at different stages of refinement (bacterial alpha-amylase, cytochrome c', cross-linked insulin and oligopeptide binding protein). The results derived using the maximum-likelihood residual are consistently better than those obtained from least-squares refinement.
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        SWISS-MODEL: An automated protein homology-modeling server.

        SWISS-MODEL (http://swissmodel.expasy.org) is a server for automated comparative modeling of three-dimensional (3D) protein structures. It pioneered the field of automated modeling starting in 1993 and is the most widely-used free web-based automated modeling facility today. In 2002 the server computed 120 000 user requests for 3D protein models. SWISS-MODEL provides several levels of user interaction through its World Wide Web interface: in the 'first approach mode' only an amino acid sequence of a protein is submitted to build a 3D model. Template selection, alignment and model building are done completely automated by the server. In the 'alignment mode', the modeling process is based on a user-defined target-template alignment. Complex modeling tasks can be handled with the 'project mode' using DeepView (Swiss-PdbViewer), an integrated sequence-to-structure workbench. All models are sent back via email with a detailed modeling report. WhatCheck analyses and ANOLEA evaluations are provided optionally. The reliability of SWISS-MODEL is continuously evaluated in the EVA-CM project. The SWISS-MODEL server is under constant development to improve the successful implementation of expert knowledge into an easy-to-use server.
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          Improved methods for building protein models in electron density maps and the location of errors in these models

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            Author and article information

            Affiliations
            [1 ]Department of Pathology and Microbiology, College of Medicine Nebraska Medical Center, Omaha NE 68198-6495, USA
            [2 ]Department of Microbiology, Immunology, and Tropical Medicine, The George Washington University Medical Center, Washington DC, 20037, USA
            Contributors
            Journal
            BMC Struct Biol
            BMC Structural Biology
            BioMed Central (London )
            1472-6807
            2007
            26 June 2007
            : 7
            : 42
            1924862
            1472-6807-7-42
            17594497
            10.1186/1472-6807-7-42
            Copyright © 2007 Asojo et al; licensee BioMed Central Ltd.

            This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

            Categories
            Research Article

            Molecular biology

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