Hue Sun Chan
BSc, University of Hong Kong, 1981
MA, University of California at Berkeley, 1983
PhD, University of California at Berkeley, 1987
Postdoc, University of California at San Francisco (UCSF), 1987-1989
1 King's College Circle
Toronto, ON M5S 1A8
|Lab||Chan Research Group|
Hue Sun Chan was born and raised in Hong Kong. Upon completing his undergraduate degree in physics there, he pursued graduate study in theoretical particle physics at UC Berkeley, specializing in regularization of quantum field theories. After receiving his PhD in 1987, he joined Ken Dill’s research group at UCSF, first as a postdoctoral fellow then as an adjunct faculty, and shifted his research interest to protein biophysics. As one of a few researchers who pioneered theoretical studies of protein folding in the late 1980s, Chan has made seminal contributions during his UCSF years. These include discovering that secondary-structure-like local order can be enhanced by global conformational compactness, developing simple exact lattice protein models such as the HP model that have been widely applied, characterizing the role of kinetic traps and their implications on the folding energy landscape, and coauthoring several influential reviews on folding. In 1998, he left San Francisco to take up his present appointment.
After arriving in Toronto, Chan turned his attention to the physical origins of folding cooperativity. His research interests have also been broadened to include thermodynamics of solvent-mediated interactions, protein evolution, protein interactions involving intrinsically disordered proteins, and DNA topology (see Research Description). He has published more than 150 research papers, which have received a total of more than 18,000 citations (see complete list of publications and invited talks). He is an editorial board member of Proteins: Structure, Function & Bioinformatics.
In the News
Our research involves both analytical and computational modeling. For the computational effort, we employ codes developed by ourselves for coarse-grained biomolecular modeling as well as common molecular dynamics packages. Computational facilities available to us include our own local cluster (pictured above, right) and resources allotted by Compute Canada.
Learn more: Chan Research Group
Theoretical and Computational Investigations of Protein Folding, Interactions, and Evolution
Protein folding and interactions are physico-chemical processes. Our group’s overall research goal is to elucidate their underlying energetics. To this end, a main emphasis of our effort is to develop proteinlike heteropolymer models with coarse-grained interactions and simplified representations of chain geometries. The rationale of these approaches is to capture the essential physics and at the same time allow for a broad coverage of the protein conformational space — and also a broad coverage of the sequence space for evolutionary studies — that is not readily achievable currently in higher-resolution models.
Molecular dynamics simulations using common atomic forcefields and explicit water models are used in our work as well, especially for deciphering subtle properties of solvent-mediated interactions. Various combinations of coarse-grained and atomic methods are being used to gain physical insights into general principles of folding, protein interactions, and evolution. The topics we address including folding cooperativity, origin of enthalpic and volumetric folding barriers, nonnative effects in folding, formation of functional and disease-causing dynamic, “fuzzy” complexes involving intrinsically disordered proteins, and conformational switching in protein evolution. Some of these efforts are highlighted below.
Cooperativity and nonnative interactions in folding
The Levinthal paradox of protein folding is commonly perceived as a statement about the impossibility of folding by a completely random conformational search. Often missed in such narratives is that the question raised by Levinthal was in response to the experimental discovery of two-state, switch-like cooperative folding by calorimetry in the late 1960s, rather than to the issue of conformational search per se. Two-state folding is expected to serve biological functions such as avoidance of aggregation. Folding cooperativity likely emerges from a coupling between local structural preferences and nonlocal packing interactions. To elucidate this local-nonlocal coupling mechanism and other folding properties, we develop native-centric as well as “hybrid” models in which nonnative effects are treated perturbatively. Many-body interactions, hydrogen bonding, sidechain packing and solvation are now being examined for their impact on folding cooperativity.
Intrinsically disordered proteins
While many proteins function in their folded states, it is now clear that intrinsically disordered proteins (IDPs) perform critical functions in transcription, translation and cell cycle regulation. Altering the functions of these IDPs can lead to cancer and other diseases. Molecular recognition by IDPs often involves target-induced folding. However, certain IDPs interact with other proteins without coupled folding-binding. Those cases entail dynamic, “fuzzy” complexes in which the bound IDPs remain largely disordered. In collaboration with experimentalist colleagues, we are developing biophysical models of IDP conformational ensembles. A main focus of our effort is to decipher the role of multisite electrostatic and aromatic interactions in IDP function and malfunction.
Atomic simulations of solvent-mediated interactions
As part of our effort to understand protein energetics, we conduct atomic simulations of aqueous solvation. Comparisons between theory and experiment indicate a prominent role of desolvation barriers in cooperative folding. Desolvation effects are key to resolving an apparent inconsistency between experimentally observed enthalpic barriers and the funnel picture of folding. They also provide novel insights into volumetric barriers to folding. Results from these atomic studies — which are not always obvious a priori — are being used to build physically more accurate coarse-grained models.
Biophysical models of protein evolution
The study of protein evolution requires a model of the mapping between amino acid sequences and the conformational ensembles they encode. Because of their computational tractability, lattice models with biophysics-based interaction schemes are useful for addressing large-scale evolution across many different protein folds. Together with collaborators, we have applied this approach to several fundamental aspects of protein evolution. Our effort has led to the recognition that neutral nets of globular proteins are likely organized as superfunnels, and that sequence-space topology or mutational robustness can have significant impact on evolutionary population and thus can help resolve adaptive conflict.
Mathematical basis of type-2 topoisomerase action
Type-2 topoisomerases (topoIIs) are enzymes that unknot and decatenate DNA circles and reduce the variance of linking number Lk of supercoiled DNA. Given that a topoII is much smaller than the DNA it acts upon, how does a topoII discern the global DNA topology from the limited, local DNA conformational information it can access? To answer this question, we focus on DNA rather than protein conformations. Working with collaborators, we address the hypothesis that topological simplification by topoII is achieved by performing DNA segment passage and re-sealing only at hook-like DNA juxtapositions. To test this “hook juxtaposition hypothesis”, we use exact enumeration and Monte Carlo sampling of conformations with various preformed juxtaposition geometries. Results from cubic-lattice and worm-like chain models indicate that the hypothesis is likely valid because it consistently accounts for a wide range of experimental data.
Awards & Distinctions
2000 — Ontario Premier's Research Excellence Award
2001-2010 — Canada Research Chair
2017 — Siu Lien Ling Wong Visiting Fellow. The Chinese University of Hong Kong (http://www.cuhk.edu.hk/ccc/edu-conference/svfp.html)
2019 — Fellow Biophysical Society of Canada
BCH374Y1 Research Project in Biochemistry
BCH479H1 Advanced Seminar in Biochemistry
JBB2026H Protein Structure, Folding and Design
BCH472Y Advanced Summer Research Project in Biochemistry
BCH372Y Summer Research in Biochemsitry
View all publications on PubMed
Comparative Roles of Charge, π, and Hydrophobic Interactions in Sequence-Dependent Phase Separation of Intrinsically Disordered Proteins.
S. Das, Y.-H. Lin, R.M. Vernon, J.D. Forman-Kay and H.S. Chan
Proceedings of the National Academy of Sciences, USA 117, 28795-28805 (2020). Read
Temperature, Hydrostatic Pressure, and Osmolyte Effects on Liquid-Liquid Phase Separation in Protein Condensates: Physical Chemistry and Biological Implications.
H. Cinar, Z. Fetahaj, S. Cinar, R. M. Vernon, H.S. Chan and R. Winter
Chemistry, A European Journal (Chem. Eur. J.) 25, 13049-13069 (2019). Read
Theories for Sequence-Dependent Phase Behaviors of Biomolecular Condensates.
Y.-H. Lin, J.D. Forman-Kay and H.S. Chan
Biochemistry 57, 2499-2508 (2018). Read
Charge Pattern Matching as a "Fuzzy" Mode of Molecular Recognition for the Functional Phase Separations of Intrinsically Disordered Proteins.
Y.-H. Lin, J.P. Brady, J.D. Forman-Kay and H.S. Chan
New Journal of Physics 19, 115003 (2017). Read
Sequence-Specific Polyampholyte Phase Separation in Membraneless Organelles.
Y.-H. Lin, J. D. Forman-Kay and H.S. Chan
Physical Review Letters 117:178101 (2016). Read
Theoretical Insights into the Biophysics of Protein Bi-Stability and Evolutionary Switches.
T. Sikosek, H. Krobath and H.S. Chan
PLoS Computational Biology 12(6):e1004960 (2016) Read
Theoretical Perspectives on Nonnative Interactions and Intrinsic Disorder in Protein Folding and Binding.
T. Chen, J. Song and H.S. Chan
Current Opinion in Structural Biology 30, 32-42 (2015). Read
Biophysics of Protein Evolution and Evolutionary Protein Biophysics.
T. Sikosek and H.S. Chan
Journal of the Royal Society Interface 11, 20140419 (2014). Read
Polycation-π Interactions are a Driving Force for Molecular Recognition by an Intrinsically Disordered Oncoprotein Family.
J. Song, S.C. Ng, P. Tompa, K.A.W. Lee and H.S. Chan
PLoS Computational Biology 9(9): e1003239 (2013). Read
Transition Paths, Diffusive Processes, and Preequilibria of Protein Folding.
Z. Zhang and H.S. Chan
Proceedings of the National Academy of Sciences, USA 109, 20919-20924 (2012). Read
Escape from Adaptive Conflict Follows from Weak Functional Trade-Offs and Mutational Robustness.
T. Sikosek, H.S. Chan and E. Bornberg-Bauer
Proceedings of the National Academy of Sciences, USA 109, 14888-14893 (2012). Read
Cooperativity, Local-Nonlocal Coupling, and Nonnative Interactions: Principles of Protein Folding from Coarse-Grained Models.
H.S. Chan, Z. Zhang, S. Wallin and Z. Liu
Annual Review of Physical Chemistry 62, 301-326 (2011). Read
Action at Hooked or Twisted-Hooked DNA Juxtapositions Rationalizes Unlinking Preference of Type-2 Topoisomerases.
Z. Liu, L. Zechiedrich and H.S. Chan
Journal of Molecular Biology 400, 963-982 (2010). Read
Competition Between Native Topology and Nonnative Interactions in Simple and Complex Folding Kinetics of Natural and Designed Proteins.
Z. Zhang and H.S. Chan
Proceedings of the National Academy of Sciences, USA 107, 2920-2925 (2010). Read
Theoretical and Experimental Demonstration of the Importance of Specific Nonnative Interactions in Protein Folding.
A. Zarrine-Afsar, S. Wallin, A.M. Neculai, P. Neudecker, P.L. Howell, A.R. Davidson and H.S. Chan
Proceedings of the National Academy of Sciences, USA 105, 9999-10004 (2008). Read
Polyelectrostatic Interactions of Disordered Ligands Suggest a Physical Basis for Ultrasensitivity.
M. Borg, T. Mittag, T. Pawson, M. Tyers, J.D. Forman-Kay and H.S. Chan
Proceedings of the National Academy of Sciences, USA 104, 9650-9655 (2007). Read
Hydrophobic Association of α-Helices, Steric Dewetting and Enthalpic Barriers to Protein Folding.
J. L. MacCallum, M. Sabaye Moghaddam, H.S. Chan and D.P. Tieleman
Proceedings of the National Academy of Sciences, USA 104, 6206-6210 (2007). Read
From Levinthal to Pathways to Funnels.
K.A. Dill and H.S. Chan
Nature Structural Biology 4, 10-19 (1997). Read