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Our group's research focuses on developing and
utilizing statistical mechanics theories, bioinformatic, and
simulation methods to explain and predict the behavior of biologically
interesting macromolecules. The current research program aimed at the
understanding of the molecular mechanisms and bioinformatic studies of
protein folding, stability, and binding of ligands, peptides, and DNA. The long-term goal of the
proposed research is to elucidate the relations between the sequence,
structure, and function of proteins and to uncover the molecular
mechanisms underlying different diseases. This will be accomplished by designing simple (yet
realistic) models and by developing statistical mechanics theories and bioinformatic
tools.
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See Publications for Details |
Protein Folding & Structure
Prediction |
Understanding the mechanism of folding and
predicting folded structures are central problems in protein
science. The solution of the protein folding problem is constrained by
computing power. Atomic level models of proteins, built using an
empirical force field (such as CHARMM), can be simulated in explicit
solvent for only tens of nanoseconds, whereas protein folding (in
vitro or in vivo) usually occurs on a time scale that is at least
three orders of magnitude longer. My group addresses the computational
challenge of developing models that are realistic enough to capture
the folding behavior of a given protein and but are simplified for
efficient calculations. We have developed a novel approach that
employs square-well interactions to establish semi-realistic
models. Preliminary studies show that this new all-atom model allows
practical folding simulations using regular personal computers, and
that it yields unprecedented accuracy in predicting the folding
pathway(s) and identifying key residues of a given protein [48,50,53]. In
particular, our results suggest that the mechanism of misfolding, as
manifested in the formation of domain-swapped dimer, is largely
determined by the native structure [50]. The new model
will be further validated with experimental results and used for
predicting the mechanism of folding and disease-causing
misfolding. [  Movies on folding of a model
all-beta protein]
Another challenge in theoretical studies of protein folding is the
lack of accurate interaction potentials that serve to bias the native
structure strongly against nonnative structures of proteins. We are
developing a new reference-state method to extract atomic interactions
from known protein structures. Preliminary studies suggest that the
new method yields the best potential in recognizing native structures
from decoys and in predicting mutation-induced changes in folding
stability among all-atom knowledge-based potentials [52]. The initial
success and productivity provide strong incentives for the further
development and validation of the new method. The results will likely
lead to more accurate methods for ab initio structure prediction as
well as for high throughput structure determination with sparse NMR
data. |
Theoretical and Simulation Studies of
Protein Binding |
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Unlike protein-solute interactions and
protein-protein aggregations, the binding of a ligand to a protein or
the binding between two proteins is highly specific. The high
specificity of non-covalent binding between two macromolecules
(molecular recognition) is critical in cellular assembly, gene
expression, and signal transduction. Protein binding may accompany
local (induced fit) and/or nonlocal conformational changes, the
latter of which is often the source of binding cooperativity
(allosteric effect) between different subunits. Allosteric
interactions that regulate binding affinity occur when the binding of
one ligand at a specific site is influenced by the binding of another
ligand at a distant site. The regulation of binding events is
essential for the orderly development of organisms and for effective
response by organisms to changes in their environment. Aberrations in
regulatory control processes are the causes for many diseases
including cancer. I am interested in developing an accurate
theory of binding. The effect of electrostatic interactions on
binding has been described by the Poisson-Boltzmann (PB)
equation. Despite its success in many applications, the PB equation
is limited to a fixed protein conformation in a dielectric continuum
solvent. Our approach is to extend and develop statistical mechanics
theories [32,37]
that will incorporate the effects of the van der Waals and
hydrogen-bonding interactions as well as molecular flexibility. An
accurate theory of binding will be useful for the development of
computational methods that aid structure-based drug design. One of
the common approaches in drug design is to screen molecules that bind
most to the active sites of proteins. The new theory should provide
at least a semi-quantitative prediction of binding constants. In
addition, the theory can be employed to study conformational changes
upon binding and the role of electrostatics in ion selectivity and
ion transport across a membrane. Simulations using the all-atom
CHARMM force field will be carried out to study protein dynamics,
free energy changes due to mutations, and conformational
changes. These studies with an all-atom realistic model will be
complemented by those using the simpler models described above, so
that both short and longer time-scale dynamics can be observed. The
complementary roles of the simple model and the atomistic model are
demonstrated in our recent work where the simulation of an all-atom
representation of protein crambin quantitatively verified the results
of a simple model in which the native state is a surface-molten solid
state [38,47]. [
Movie on binding dynamics of a hemoglobin]
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| Representative publications |
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Y. Zhou, ``Salt effects on protein titration and binding.'',  102, 10615
(1998). [PDF]
Y. Zhou, D. Vitkup, and M. Karplus, ``Native proteins are surface-molten
solids: Application of the Lindemann criterion for the solid versus liquid
state.'', 
285 , 1371 (1999). [PDF]
Y. Zhou and M. Karplus, ``Interpreting the folding kinetics of helical
proteins.'',  401, 400-403 (1999). [PDF]
H. Zhou and Y. Zhou, ``Folding rate prediction using total contact
distance.'',  82, 458--463 (2002). [PDF]
Y. Zhou and A. Linhananta, ``Thermodynamics of an all-atom off-lattice model
of the fragment B of Staphylococcal protein A: Implication for the origin of the
cooperativity of protein folding'', 106, 1481 (2002). [PDF]
A. Linhananta, H. Zhou and Y. Zhou, ``The dual role of a loop with low
loop contact distance in folding and domain swapping'', 11, 1695
(2002).[PDF]
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times since 10/01/2000. Last modified: September 12, 2006
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