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Our general interest is in theoretical and
computational study of biomolecular structure, dynamics and
function, with particular emphasis on modeling weakly stable
proteins and understanding their roles in important
biological processes such as regulation of transcription and
translation, signal transduction and disease-related protein
misfolding. Specifically, we are currently focusing on the following
areas.
1. Implicit treatment of solvent
De novo simulation of large conformational changes of proteins such
as folding remains one of the greatest challenges in computational
biology. A critical bottleneck is accurate and efficient
description of the solvent environment. Implicit treatment of
solvent arguably provides an optimal balance between description of
the essential physics and computational feasibility. The basic idea
is to capture the mean influence of water on the solute via direct
estimation of the solvation free energy. Important approximations
need to be made in order to estimate the solvation free energy
without extensively sampling all water degrees of freedom. In
particular, it is generally assumed that water dynamics is much
faster than peptide conformational diffusion, such that the solvent
can be effectively described as a continuum medium. As such, only
the solute is represented microscopically, and the system size is
reduced about 10-fold.
The latest implicit solvent models often decompose the total
solvation free energy into nonpolar
and electrostatic contributions, which increases the accuracy and
enhances the ability to describe the conformational dependence of
solvation. Important advances have been made in recent years for
accurate calculation of the solvation free energy on the fly with
only a modest computational overhead, such as using the generalized
Born (GB) theory. A critical remaining limitation is in the
treatment of nonpolar solvation, where the popular surface
area-based models are insufficient in describing the conformational
dependence of nonpolar solvation. A key focus of our research is to
develop better nonpolar solvation models, through studying key
physical properties of nonpolar solvation, devising efficient
numerical methods to model these properties, and consistently
optimizing the solvation model together with the underlying protein
force field.
2. Intrinsically disordered proteins
(Coupled binding and folding of ACTR of p160 nuclear
hormone receptor and NCBD of CBP/p300 transcriptional
coactivator. Demarest et al., Nature 2002)
Intrinsically disordered proteins (IDPs) are an important newly
recognized class of functional proteins that rely on a lack of stable
structures for function. They are highly abundant, play fundamental
roles in biology, and are extensively involved in human
diseases. The heterogeneous and dynamical nature of IDPs, however,
presents substantial challenges for detailed characterization
using experiment alone. This difficulty represents a unique and
exciting opportunity for modeling to make crucial contributions. At
the same time, IDPs also pose substantial new challenges that push the
limits of both the force field accuracy and conformational sampling
capability. Implicit solvent is arguably the best choice for de novo
simulation of IDPs with a necessary balance between accuracy and
speed. One of the key motivations of developing better implicit
solvent protein force fields (see above) is actually to understand
the structure, interaction and control of IDPs. At this stage, we
are mainly interested in understanding the nature of the unbound
states of a set of model regulatory IDPs and the molecular
mechanisms of their interaction with specific substrates. We rely on
close collaborations with NMR experimentalists for reliable
interpretation and critical validation of simulation.
3. Coupled folding, assembly and membrane insertion of helical
peptides
The precise mechanisms of spontaneous insertion and self-assembly of
peptides in membrane remain poorly understood at molecular
level. This limitation is related to both (1) a lack of suitable
molecular modeling tools for simulating such complex processes and
(2) difficulty in designing model peptides to systematically
investigate various factors under controlled conditions. So-called
coarse-grained approaches can extend the accessible time scales by
several orders of magnitude while capturing the essence of
underlying physical interactions. In particular, increasing amount
of experimental evidence, as well as theoretical considerations, has
accumulated to argue that peptides generally fold or refold upon
membrane insertion and that coupling of folding, insertion and
assembly is essential for the actions of membrane-inserting proteins
in biology. There is a need to develop a new generation of CG
protein-lipid force fields that is efficient yet realistic enough to
enable direct simulation of coupled peptide folding during membrane
insertion and self-assembly. At the same time, we are exploiting
model peptide systems that allow specific questions to be formulated
and addressed simultaneously by experiment and simulation. In
particular, M2GlyR-derived channel-forming peptides designed by the
Tomich lab (see below) possess a set of unique properties that make
them an ideal platform for understanding membrane insertion of
helical peptides.
4. Modeling and design of synthetic peptide channels
(A short molecular dynamics simulation of
a designed peptide channel in POPC bilayer)
In close collaboration with the Tomich lab in Biochemistry Department,
our long-term goal is to design, develop and implement the use of
ion-selective, synthetic channel-forming peptides. A primary
application for such technology will be the treatment of
loss-of-function ion channel diseases such as cystic fibrosis. The
Tomich lab has derived a series of pore-forming peptides from the
second transmembrane helix of glycine receptor (M2GlyR) alpha1
subunit with many desired properties (solubility, monomeric, spontaneous
insertion, large conductance, etc). A final remaining barrier is a
lack of sufficient anion selectivity. We are currently exploiting
peptide synthesis, biological testing, structural analysis and
computer modeling to understand the structural and physicochemical
properties responsible for modulating anion selectivity. Given the
challenges of structural characterization of membrane proteins, our
strategy is to combine molecular modeling, solution NMR and various
(low-resolution) structural restraints to build our "best-guess"
structural models of these synthetic channels. Subsequent molecular
simulations will provide important insights for rationale design of
novel sequences with desired characteristics.
5. New simulation and conformational sampling methods
Successful biomolecular simulations hinge on both the quality of
the empirical force field employed and the ability to sufficiently
sample functionally relevant conformational spaces. Brute-force molecular
dynamic simulations have very limited ability to probe biologically
relevant processes, which often occur at time scales much longer what is
accessible by such simulations. Development of nontrivial sampling
techniques is one of the most actively research areas in biomolecular
modeling. This is also an important focus of our research. For
example, we extensively explore so-called replica exchange enhanced
sampling in our peptide simulations. Much remains to be learned
about the actual efficacy of replica exchange and how to improve
it. We are also interested in exploring so-called internal
coordinate molecular dynamics that reduces the number of the degrees
of freedom and allows larger molecular dynamics time steps. Such simulation
technique has found usage in NMR structure calculation and refinement,
flexible protein-ligand docking, etc.
Want to find out more about our research? Check out our latest
publications, or, simply drop by if you can! We are in 34 Chalmers
Hall.
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