PhD Scholarship – Membrane protein dynamics and interactions
Supervisors: Prof. Judith Klein-Seetharaman
Start date: 29 September 2014
Application deadline: 16 August 2014
Interviews: 29 August 2014
Funding: Departmental fellowship for 3 years with full UK tuition fees and an
annual stipend at the UK Research Council rate, currently £13,726
Project Background
Membrane proteins (MP’s) are encoded by some 20-30% of typical genomes, yet less
than 100 unique membrane protein structures have been solved. Many MP’s undergo
conformational changes as part of their function, as exemplified by membrane receptors in
signal transduction, requiring studies not only of their structures but also their dynamics.
Generally, little is known about how MP structures fold, move, and interact with lipids,
proteins and other ligands due to the technical difficulties in working with MP’s: Because of
their hydrophobic nature, membrane proteins are prone to aggregate and require membrane
mimetic additives to study them in vitro, adding to the complexity of the systems. Membrane
proteins are of high clinical interest and are under functional investigation in the Metabolic
and Vascular Health Division of the Warwick Medical School.
Applicants can choose from the following sub-projects:
Subproject 1. Structural biology of membrane proteins: Membrane protein folding,
conformational changes and lipid interactions
Model systems of membrane protein folding: The little we know about how
membrane proteins fold into their three-dimensional structures comes mostly from studies
of two proteins that have model system status for membrane protein folding studies,
mammalian rhodopsin (MR) and bacteriorhodopsin (BR). Ground-breaking early work by the
late Nobel Laurete H. Gobind Khorana and his co-workers established BR as a folding
paradigm by fully denaturing and refolding BR in vitro1. The archaebacterial protein BR is a
seven-transmembrane (TM) helical bundle and is one of only two MPs that have been fully
denatured to date1. The possibility of refolding BR in vitro from denatured states established
BR as a model system for studying thermodynamic and kinetics of folding of helical MPs2.
Khorana’s seminal studies of BR fragments led to a folding theory proposed by Popot and
1
2
Huang,K.S. et al. (1981). The Journal of biological chemistry 256(8): p. 3802-9.
Booth, P.J. and P. Curnow (2006) Current opinion in structural biology, 2006. 16(4): p. 480-8.
Engelman: the two-stage hypothesis3. This hypothesis is the prevalent theory for MP folding
today. In this model, secondary structure elements, i.e. the TM helices, fold first and then
come together in a second stage to form a helical bundle.
MR is the dim light photoreceptor and a prototypical G protein coupled receptor. It
also consists of seven TM helices connected by cytoplasmic and extracellular loops. Mutations
in MR have been linked to the retinal degenerative disease, Retinitis Pigmentosa4. This is an
inherited disorder that causes night blindness and leads to progressive loss of vision in later
life due to a gradual reduction of rod and cone photoreceptor cells. Although rare, it is the
main inherited retinal degeneration disease, with about 1 in 4000 people affected worldwide
and more than 150 MR mutations are known to cause this disease. Most of these mutations
lead to misfolding and/or instability of MR5. An understanding of folding mechanisms of MR
may help design effective strategies to combat Retinitis Pigmentosa by providing deeper
insights into the underlying causes of misfolding.
Comparison of BR and MR folding: Unlike BR, it has not been possible so far to fully
denature MR, and even partially denatured states have not been amenable to refolding. The
experimental conditions used to (de)stabilize and study BR and MR are different, making it is
difficult for a direct comparison. To complement such experimental studies, Judith KleinSeetharaman applied computational approaches that only require the input of a crystal
structure 6,7,8. One particularly useful method is the so-called Floppy Inclusions Substructure
Topography (FIRST) method9. In this method, residues in a protein structure are classified as
part of a mutually rigid cluster or free to rotate and the classification is repeated after
breaking hydrogen bonds one at a time intended to simulate the denaturation process. The
FIRST simulated unfolding of BR is dominated by interactions within individual TM helices
consistent with teh 2-stage hypothesis. In contrast, in the denaturation of MR, the largest
rigid cluster is observed to contain segments from multiple helices and loops for most of the
simulated unfolding. This persistent rigidity results from the interconnectivity of structural
elements in MR and portrays a nonlocal cooperativity as opposed to the individuality of
helices observed in BR denaturation. Based on these results, Klein-Seetharaman proposed a
new model, the long-range interactions model for MP folding6. In this model, there is a core
of residual structure in denatured states comprising loop and TM residues from distant parts
in the sequence. It is these long-range interactions that may contribute to the difficulty in
experimentally refolding of MR as opposed to BR. These conclusions are supported by recent
3
Popot, J.L. and D.M. Engelman, (1990) Biochemistry, 1990. 29(17): p. 4031-7. & Popot, J.L., S.E.
Gerchman, and D.M. Engelman, (1987) Journal of molecular biology 198(4): p. 655-76.
4 Retnet, http://www.sph.uth.tmc.edu/Retnet/disease.htm#03.202d
5 Sung, C.H. et al. (1991) PNAS 88, 6481-5. & Kaushal, S. & H.G. Khorana, (1994) Biochemistry 33,
6121-8.
6 Klein-Seetharaman, J., (2005) Trends in pharmacological sciences, 26(4): p. 183-9.
7 Rader, A.J. et al (2004) PNAS 101(19): p. 7246-51.
8 Tastan, O. et al. (2007) Photochemistry and photobiology, 2007. 83(2): p. 351-62.
9 Jacobs, D.J., A.J. Rader, L.A. Kuhn, and M.F. Thorpe, (2001) Proteins 44(2): p. 150-65.
experimental studies using single-molecule dynamic force spectroscopy which indicated a
core of rigid structural segments in MR but not BR10.
Proposed studies: The overall hypothesis that will be tested is that loops play an
important role in the folding of MP’s. Our recent survey of different denaturing conditions of
MR places us in a unique position to test this hypothesis experimentally in this system: we
showed that only high concentrations of SDS and combinations of SDS and urea are suitable
for studying denaturation of MR in detergent micelles without aggregation 11. These studies
have opened the door to in-depth characterization of MR denatured states12. This will allow
us to carry out the very first characterization of unfolded states of MR by sophisticated NMR
spectroscopic approaches, extending those used for soluble proteins to membrane
proteins13. Due to the challenges in working with membrane proteins, we cannot measure
NMR dynamics with atomistic resolution as done with soluble proteins. Instead, we will
gradually increase the level of detail in characterization of denatured states: from global
studies such as CD to more and more spatially resolved studies, ending with site-specific
labelling. The long-range interactions model predicts a folding core at the extracellular
domain. Thus, it is predicted that denatured states should contain residual structure in this
domain. The global analysis will confirm overall denaturation, while the approximate
approach will distinguish the extracellular from the cytoplasmic domain, qualitatively testing
the prediction and the site-specific approach will narrow down the actual sites of residual
structure. We have developed site-specific approaches for the study of conformational
changes in MR14, by combining cysteine mutagenesis with 19F NMR spectroscopy. We will
investigate the disease relevance of any findings on denatured states of MR, by introducing
point mutations that are known to cause Retinitis pigmentosa, and test if these mutations
alter the denatured states.
Extensions to these studies that will tie this work in with the host institution will be to
test the mechanisms of folding for other membrane proteins.
10
Sapra, K.T., P.S. Park, K. Palczewski, and D.J. Muller, Mechanical properties of bovine rhodopsin
and bacteriorhodopsin: possible roles in folding and function. Langmuir : the ACS journal of surfaces
and colloids, 2008. 24(4): p. 1330-7.
11 Dutta, A., K.C. Tirupula, U. Alexiev, and J. Klein-Seetharaman, Characterization of membrane
protein non-native states. 1. Extent of unfolding and aggregation of rhodopsin in the presence of
chemical denaturants. Biochemistry, 2010. 49(30): p. 6317-28.
12 Dutta, A., T.Y. Kim, M. Moeller, J. Wu, U. Alexiev, and J. Klein-Seetharaman, Characterization of
membrane protein non-native states. 2. The SDS-unfolded states of rhodopsin. Biochemistry, 2010.
49(30): p. 6329-40.
13 Klein-Seetharaman, J., M. Oikawa, S.B. Grimshaw, J. Wirmer, E. Duchardt, T. Ueda, T. Imoto, L.J.
Smith, C.M. Dobson, and H. Schwalbe, Long-range interactions within a nonnative protein. Science,
2002. 295(5560): p. 1719-22.
14
Klein-Seetharaman, J., Getmanova, E.V., Loewen, M.C., Reeves, P.J. and Khorana, H.G. (1999) NMR
Spectroscopy in Studies of Light-Induced Structural Changes in Mammalian Rhodopsin: Applicability of Solution
19F NMR. Proc. Natl. Acad. Sci. USA 96, 13744-13749.
Furthermore, it is planned to address the limitation that they have ignored the lipids
in the computational and experimental studies so far. Klein-Seetharaman has significant
experience in modelling the interaction of various soluble proteins with cardiolipin and
cardiolipin containing membranes using molecular docking with Autodock Vina and coarse
grained molecular dynamics simulations using the MARTINI forcefield15, and will extend this
work here to systems of relevance to the Division of Metabolic and Vascular Health.
Finally, Klein-Seetharaman will also apply her site-directed conformational studies to
folded, full-length receptor proteins. Membrane receptors mediate the communication
between the inside and the outside of the cell. There are two types, the G protein coupled
receptors and the type II receptors, with diverse families such as the insulin receptor. G
protein coupled receptors have recently seen amazing advances due to the crystallization of
a large number of receptors. In contrast, type II receptors have only 1 or 2 transmembrane
helices and large extracellular domains, are highly dynamic and are thus difficult to crystallize
in full-length form. While many extracellular and cytoplasmic fragment structures are known,
the hallmark of the receptors function is change in conformation mediated by the TM domain.
We study therefore conformational changes in full-length receptors in order to understand
the signaling mechanism by these receptors, in particular focusing on IFNg receptors, for
which we have an ongoing collaboration with a pharmaceutical company, Materia Medica.
Due to the difficulty in working with MP’s, they employ a wide spectrum of biophysical
techniques, including circular dichroism, absorbance, fluorescence, NMR spectroscopy, mass
spectrometry, chemical derivatization and accessibility studies etc), often adapted specifically
to address this difficulty (e.g. 19F-NMR spectroscopy).
Subproject 2. Systems biology of membrane proteins: From individual protein-protein
interactions to the membrane receptor interactome
Protein-protein interactions (PPI) are the fundamental building blocks of
communication for all organisms. Thousands of such interactions mediate communication
within cells. Cataloguing the full complement of interactions is out of reach despite extensive
efforts. In particular, the false positive and false negative rates of high-throughput methods
for directly identifying interactions are both very high and the ratio between positive and
negative pairs of proteins (interacting vs non-interacting) is very small. Klein-Seetharaman
and others have shown that confidence in identified PPI can be raised and novel binding
partners can be predicted by integrating diverse biological data sources that contain both
direct information on PPI from high-throughput Y2H or mass spectrometry experiments and
implicit information on PPI, such as gene expression or functional annotation data, e.g. 16. By
15
Schlattner, U. et al. (2012) J. Biol. Chem. 288(1):111-21. & Chu, C.T. et al. (2012) Nature Cell
Biol., in press. & Atkinson J, et al. (2011) Nat Commun. 2:497.
16Qi, Y., Bar-Joseph, Z. and Klein-Seetharaman, J. (2005) Proteins - Structure, Function and
Bioinformatics 63, 490-500.
transforming the multiple data sources into a feature vector for every pair of proteins, the
task of PPI prediction is treated as a binary classification problem (interact or not). In her
studies of the yeast interactome17, human membrane receptor interactome17, and the HIV1,human interspecies interactome18, the Salmonella-human interactome19 they have shown
that of various machine learning algorithms the random forest (RF) classifier is one of the best
in predicting PPI from heterogeneous direct and indirect biological data. In a systems biology
framework (outlined schematically in Figure 4), lists of predicted interactions are generated
from integrating many biological databases through computational modeling. The predictions
are tested experimentally and the sites of interactions determined. They have followed up
experimentally on high-ranking pairs involving proteins interacting with the Epidermal
Growth Factor Receptor and have validated a number of the novel predictions made by the
RF classifier for human membrane receptors18. As part of your PhD project, you would
validate these predictions using for additional membrane proteins.
How to apply
Please apply online for the MPhil/PhD in Medical Sciences in Warwick Medical
School
- Please upload a transcript and CV if possible
- Please also ask your referees to submit a reference for you as soon as possible.
Note: when you submit your application an email will automatically be sent to your
referees requesting a reference for you. This will email contain a secure link for your
referee to upload a reference for you.
17Qi,
Y., Dhiman, H.K., Bhola, N.E., Budyak, I., Kar, S., Man, D., Dutta, A., Tirupula, K., Carr, B.,
Grandis, J.R., Bar-Joseph, Z. & Klein-Seetharaman, J. (2009) Systematic prediction of human
membrane receptor interactions Proteomics 9, 5243-5255
18Tastan, O., Qi, Y., Carbonell, J. and Klein-Seetharaman, J. (2009) Prediction of interactions
between HIV-1 and human proteins by information integration. Pacific Symposium on Biocomputing
13, 516-527.
19 Garcia, J., Schleker, S., Klein-Seetharaman, J. and Oliva, B. (2012) BIPS: BIANA Interolog
Prediction Server. A tool for protein-protein interaction inference, Nucl. Acids Res. 40(Web Server
issue), W147-51