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Large-Scale Conformational Changes of Trypanosoma cruzi Proline Racemase Predicted by Accelerated Molecular Dynamics Simulation

Overview of attention for article published in PLoS Computational Biology, October 2011
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Title
Large-Scale Conformational Changes of Trypanosoma cruzi Proline Racemase Predicted by Accelerated Molecular Dynamics Simulation
Published in
PLoS Computational Biology, October 2011
DOI 10.1371/journal.pcbi.1002178
Pubmed ID
Authors

César Augusto F. de Oliveira, Barry J. Grant, Michelle Zhou, J. Andrew McCammon

Abstract

Chagas' disease, caused by the protozoan parasite Trypanosoma cruzi (T. cruzi), is a life-threatening illness affecting 11-18 million people. Currently available treatments are limited, with unacceptable efficacy and safety profiles. Recent studies have revealed an essential T. cruzi proline racemase enzyme (TcPR) as an attractive candidate for improved chemotherapeutic intervention. Conformational changes associated with substrate binding to TcPR are believed to expose critical residues that elicit a host mitogenic B-cell response, a process contributing to parasite persistence and immune system evasion. Characterization of the conformational states of TcPR requires access to long-time-scale motions that are currently inaccessible by standard molecular dynamics simulations. Here we describe advanced accelerated molecular dynamics that extend the effective simulation time and capture large-scale motions of functional relevance. Conservation and fragment mapping analyses identified potential conformational epitopes located in the vicinity of newly identified transient binding pockets. The newly identified open TcPR conformations revealed by this study along with knowledge of the closed to open interconversion mechanism advances our understanding of TcPR function. The results and the strategy adopted in this work constitute an important step toward the rationalization of the molecular basis behind the mitogenic B-cell response of TcPR and provide new insights for future structure-based drug discovery.

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Geographical breakdown

Country Count As %
United States 3 4%
Italy 1 1%
France 1 1%
Unknown 62 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 28%
Researcher 19 28%
Student > Master 7 10%
Professor > Associate Professor 5 7%
Student > Bachelor 3 4%
Other 10 15%
Unknown 4 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 22 33%
Chemistry 12 18%
Biochemistry, Genetics and Molecular Biology 10 15%
Computer Science 5 7%
Physics and Astronomy 5 7%
Other 6 9%
Unknown 7 10%