Dr. Evelyne Deplazes: Difference between revisions

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'''Book Chapters''' <br>
'''Book Chapters''' <br>


1. Deplazes E., O’Mara M.L., 2014, Polypeptide and Protein Modeling for Drug Design, Encyclopaedia of Computational Neuroscience (accepted for publication) </br>
1. Deplazes E., O’Mara M.L., 2014, Polypeptide and Protein Modeling for Drug Design, Encyclopaedia of Computational Neuroscience. [http://www.springerreference.com/docs/html/chapterdbid/349045.html available online] <br>
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Revision as of 01:30, 14 January 2014

Contact Details

Dr. Evelyne Deplazes
Institute for Molecular Bioscience (King group)
School of Chemistry and Molecular Biosciences (Molecular Dynamics group)
The University of Queensland
St. Lucia, Brisbane
QLD 4072
Australia

email e.deplazes@uq.edu.au


Biography

I completed a double degree in Chemistry and Computer Science at Curtin University in Perth (2003-2006). During my undergraduate research project I used quantum mechanical calculations to simulate the IR and Raman spectra of histidine in solution. After that I completed an Honours in Computational Chemistry (2007) focusing on quantum mechanical calculations of transition metals for modelling the chemical and physical properties of materials.

In 2012 I was awarded my PhD in Computational Biophysics from the University of Western Australia, Perth. As part of my PhD I have developed methods for integrating structural data from spectroscopy experiments into simulations to model the gating behavior of mechanosensitive ion channels that predicted the role of specific structural domains in the gating mechanism of the channel. Furthermore, my PhD project focused on using molecular dynamics and Monte Carlo simulations to aid in the analysis and interpretation of FRET spectroscopy experiments. After finishing my PhD I joined the research groups of Prof. Alan Mark (School of Chemistry and Molecular Biosciences, UQ) and Prof. Glenn King (Institute for Molecular Bioscience, UQ) to work on a collaborative project that focuses on peptides derived from animal venoms for the development of new drugs to treat chronic pain.


Research Interests and Projects

My main research area is the use of computational chemistry for investigating the structure-activity relationship of ion channels and their interactions with drug molecules. This allows me to integrate my knowledge and skills in chemistry, structural biology and computer science. I am experienced in a range of molecular modelling techniques and theoretical approaches including quantum mechanical calculations, Monte Carlo simulations, molecular dynamics simulations, homology modelling and docking. In addition I am interested in the developing computational methods that enables researchers to make better use of the data from spectroscopy experiment, with a particular focus on FRET and EPR.

Development of venom-based drugs for treating chronic pain
The main focus of this project is to develop potent and selective blockers of acid sensing ion channels (ASICs). These ion channels are the primary sensors of acidic conditions in humans and recent studies have shown that ASICs are involved in a range of physiological processes and medical conditions including pain, inflammation, neurological and psychiatric diseases. We are particularly interested in the ASIC3 and ASIC1a subtype as these have been shown to be involved in the perception and transmission of pain in the central and peripheral nervous system. This project combines molecular dynamics simulations and docking with experimental validation to characterize the interactions between a range of venom peptides and ASIC1a and ASIC3. The results from the simulations will aid the optimization of the peptides into small-molecule analgesics that might be more useful therapeutically.
This project is a collaboration between the MD group at the School of Chemistry and Molecular Biosciences (UQ) and the King group at the Institute for Molecular Biosciences (UQ) and is part of the venom-based drug design program in the King group to develop novel therapeutics to treat chronic pain. (See for example this article in ABC Science).

Developing computational methods to improve the accuracy of structural data obtained from DEER spectroscopy
Our ability to understand physiological processes relies on the availability of structural data to create accurate 3D models of the proteins involved. Techniques to gather and process structural data are thus important tools for structural biology and related fields such as rational drug design. Double electron-electron resonance (DEER) spectroscopy is a powerful technique that can be used to measure distances between specific sites in a protein. However, relating the distance distributions from the DEER experiments to the structural model of the protein is challenging. Current methods are often inadequate and limit the accuracy of the resulting structural model. This project employs molecular dynamics simulations to develop new and robust protocols to accurately predict DEER spectra and the corresponding distance distributions. The outcomes of this project are computational methods that will significantly improve the interpretation of DEER experiments and thus increase our ability to obtain accurate structural models of proteins.
This project is a collaboration with Dr. Megan O'Mara at the School of Chemistry and Molecular Biosciences (UQ).

Publications

Links to all my publications can be found on my Google Scholar profile.

Book Chapters

1. Deplazes E., O’Mara M.L., 2014, Polypeptide and Protein Modeling for Drug Design, Encyclopaedia of Computational Neuroscience. available online

Refereed Journal Articles

1. Deplazes E. , Louhivuori M., Jayatilaka D., Marrink SJ., Corry B., 2012, Structural investigation of MscL gating using experimental data and coarse grained MD simulations, PloS Computational Biology, vol 8, issue 9

2. Martinac B. , Petrov E., Cranfield CG, Nomura T., Rhode PR., Battle AR., Landsberg JL, Foo A. Constatine M, Rothnagel R., Carne S., Chi G., Deplazes E., Cronell B., Hankammer, B., 2012, Bacterial mechansosensitive ion channels (Review), accepted for publication in Antioxidant & Redox signalling

3. Nomura T., Cranfield CG, Deplazes E., Owen DM., Macmillan A., Battle AR, Constantine M., Sokabe M., Martinac B. 2012, Differential effects of lipids and lyso-lipids on the mechanosensitivity of the mechanosensitive channels MscL and MscS, PNAS, vol 109 (122), 8770-8775

4. Deplazes E., Jayatilaka D and Corry B., 2011, Testing the use of molecular dynamics to simulate fluorophore motions and FRET, Physcial Chemistry Chemcial Physics, 13 (23), 11045-11054

5. Deplazes E., Jayatilaka D and Corry B., 2011, ExiFRET: A flexible tool for understanding FRET in complex geometries, Journal of Biomedical Optics, 17, 011005

6. Deplazes E., van Bronswijk W., Zhu F., Barron L.D. , Ma S., Nafi A. and Jalkanen K.J., 2010, A combined theoretical and experimental study of the structure and vibrational absorption, vibrational circular dichroism, Raman and Raman optical activity spectra of the L -histidine zwitterion, Theoretical Chemistry Accounts, Vol. 19, no. 1-3, pp. 155 – 176

7. Varganov S.A., Gilbert A.T., Deplazes E., Gill P.M., 2008, Resolution of the Coloumb operator, Journal of Chemical Physics, Vol. 128, no. 20, pp. 201104