Dr. Evelyne Deplazes

Evelyne Deplazes
NHMRC Early Career Research Fellow

I am a Research Fellow at Curtin University in Perth and a visiting academic at the University of Queensland.

Contact Details

at Curtin:
Dr. Evelyne Deplazes
School of Biomedical Sciences
Faculty of Health
Bentey, WA 6102, Australia

email evelyne.deplazes|at|curtin.edu.au
Phone: +61 8 9266 56 85

at UQ:
Dr. Evelyne Deplazes
School of Chemistry and Molecular Biosciences (Molecular Dynamics group)
The University of Queensland
St. Lucia, QLD 4072, Australia

email e.deplazes|at|uq.edu.au
Phone: +61 7 3365 7562

Online reserach and publication profiles Curtin staff profile

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Biosketch

I completed a double degree in Chemistry and Computer Science Curtin University in Perth, Western Australia. . During my undergraduate research project I used quantum mechanical calculations to simulate the IR and Raman spectra of histidine in solution (Deplazes et al, 2008). I then did an Honours degree in Computational Chemistry (2007), also at Curtin University, in which my research focuses 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 (Deplazes et. al, 2012). I also carried out fluorescence spectroscopy experiments to study the clustering of mechanosensitive channels (Nomura et. al. 2012). In addition, my PhD project focused on using molecular dynamics and Monte Carlo simulations to aid in the analysis and interpretation of FRET spectroscopy experiments (Deplazes et. al., 2011, Deplazes et. al 2012).

After my PhD I was awarded a Postdoctoral fellowship by the Swiss National Science Foundation to work in the research groups of Prof. Alan Mark (School of Chemistry and Molecular Biosciences, UQ) and Prof. Glenn King (Institute for Molecular Bioscience, UQ). This is a collaborative project that focuses on the use of computational methods to study the molecular interactions between venom-based peptides and their ion channel targets. In addition, I work on the development of computational approaches that in combination with data from optical and spectroscopy techniques can be used to study the lipid-binding properties of peptides. In 2014 I was awarded a NHMRC Early-Career Research Fellowship to continue my work on these projects.

In 2016 I moved to Curtin University where I work as a Research Fellow at the School of Biomedical Sciences. My research focuses primarily on the use and development of Molecular Dynamics techniques and in combination with spectroscopy experiments to study the interactions of peptides with biological membranes.

Research Interests

My main research focus is the development and use of computational methods to understand the structure and dynamic properties of biomolecular systems. In particular, I am interested in using molecular dynamics (MD) simulations and docking approaches to study the structure of membrane proteins and their interactions with peptides for aiding peptide-based drug design. This also includes the evaluation of docking methods for predicting peptide-protein complexes. I also use MD simulations in combination with data from experimental techniques such as surface plasmon resonance, vibrational spectroscopy and NMR to study the binding of peptides to membranes. In addition, I am interested in developing computational methods that enable researchers to make better use of the data from spectroscopy experiment with a particular focus on vibrational spectroscopy and fluorescence resonance energy transfer (FRET).

In my research I aim to combine computational approaches with experimental validation to develop methods that allow us to accurately describe the molecular interactions that govern the function of peptides and proteins. Only through rigorously validated methods can we take advantage of the predictive power of computational methods. When applied properly, computational methods are a powerful tool to gain insight into biological processes at the atomistic level and contribute to our understanding of normal physical functions and the molecular origins of diseases.

My research 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. I am also knowledgeable in many spectroscopy methods such as infrared (IR), Raman, and fluorescence spectroscopy.

For an overview of my current projects, please see my UQ Researchers profile

Publications

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

Student Projects

The following are projects that are suitable for 3rd and 4th year undergraduate students, Honours or Masters students. Feel free to contact me for more information, and also with your own research ideas.

In my research I use of computational methods to understand the structure and dynamic properties of biomolecular systems. This includes simulations of peptides, proteins and lipid bilayers. The projects we work on are at the interface of chemistry, structural biology, biophysics and computer science. These projects are suitable for students with a background in any of these disciplines. The following are just a few suggestions of projects but there is many more projects available in our research group (see on the MD group website) The project will always be adapted to the student’s interest, background knowledge and skills.

Understanding the interactions of venom-derived peptides with lipid bilayers

Project: In this project we use computer simulations in combination with data from surface plasmon resonance and NMR to understand how venom-derived peptides interaction with lipid bilayers (a model of cell membranes). Specially, this project uses molecular dynamics simulations to investigate how these peptides bind to the lipid bilayer. For example, do the peptides interaction only with the lipid head groups or do they partition into the membrane?

Background: Most venom-based peptides act on voltage-gated ion channels (proteins responsible for the electrical signal of nerve conduction). These ion channels are integral membrane proteins which means the peptide binding site is often membrane-embedded. Thus to understand the mechanism of action of these peptides it is important to understand their lipid-binding properties. Part of this project is to combine molecular dynamics simulations with surface plasmon resonance and NMR to investigate the biding of a series of venom-based peptides to lipid bilayers (models of cell membranes). For example we compare the lipid binding properties of venom peptides known to inhibit voltage-gated ion channels by distinctly different mechanisms. We show that, unlike some proposed theories, not all peptides known to inhibit voltage-gated ion channels partition into membranes.

Modeling the interactions of venom-based peptides with ion channel proteins using restraint-driven docking.

Project: In this project we evaluate the accuracy and efficacy of docking programs to predict the structure of complexes formed by peptides and ion channel proteins. In particular we aim to find out what is the most effective use available experimental data. For this we perform a large number of docking experiments and compare the accuracy of the predicted structure of a peptide-channel to the available crystal structure. Using statistical analysis of these results we can assess the accuracy of the docking protocols. This will help experimentalists to make the best use of their data.

Background: Restraint-driven docking approaches in combination with experimental information are often used to derive structural models of peptide-channel complexes. The questions is how reliable are such models and what is the most effective use of available experimental data. Also, structures obtained from docking are often assessed using geometric criteria (e.g. RMSD). This is of limited use to an experimentalist aiming to identify the peptide-channel interactions at the binding interface for later use in lead optimization. Using the complex formed by the venom peptide PcTx1 and the acid sensing ion channel 1 as a case study, we examine the effect of different combinations of restraints and input structures on the reliability of the structures obtained. We are currently looking into extending this study to other peptide-channel complexes.