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@ U S T . H K
Proteins are the cell’s workforce. They
carry out an array of functions, often
determined by their shape. However,
proteins are dynamic and constantly
moving, which current experimental
imaging techniques find difficult to
detect. Now cutting-edge research by Prof
Xuhui Huang is realizing novel insights
by leveraging computer simulations to
“add dynamics, make a movie, and help
elucidate what a protein does”.
One of Prof Huang’s main focuses
is the multi-step transcription process
whereby DNA information is used to
create messenger RNA (mRNA), which
after further steps is translated into the
protein molecule encoded in the original
gene. The transcription process is vital to
the cell given that errors at this stage are
implicated in relation to many diseases,
including Alzheimer’s, and in aging.
A major contribution to date has
been to look at the dynamics of the
backtracking step of transcriptional
enzyme RNA polymerase II. This step self-
corrects errors if something goes wrong to
ensure that each messenger RNA matches
the template DNA. “However, the process
DYNAMIC VISION
happens at a millisecond timescale
(10
-3
), and to create a millisecond
computer simulation would previously
have required a 1,000 CPU core from a
super-computing center running non-
stop for 150 years,” Prof Huang said. He
and his team bridged this time-scale gap
through a new theory and algorithm
development, based on the Markov
State Model in combination with other
statistical mechanical theories, bringing
the time required down tomonths.
The advance allowed the team to
collect data and images to examine
the backtracking process. From this,
they identified a residue, amino acid
Rpb1 Threonine 831, which serves as
a sensing probe to detect interaction
difficulties between RNA that is
not incorporated correctly and the
template DNA, among other findings.
The team implemented the project
and carried out data analysis in
collaboration with a computer scientist
at King Abdullah University of Science
and Technology (KAUST) in Saudi
Arabia, where the super computing took
place. “Extensive simulation comprising
Millisecond dynamics of
RNA polymerase II
translocation and backtracking
at atomic resolution.
A lot of biologists have started
to think that structural
dynamics – a ‘computer
telescope’ – is an important
complement to existing
structural biology. You can look
at images as a function of time
and tell how proteins operate
PROF XUHUI HUANG
Padma Harilela Associate Professor of Science
25 billion molecular dynamics (MD)
steps, initiated from crystal structures,
modeled a biological process occurring
at hundreds of microseconds, creating
a massive dataset,” Prof Huang said.
A team member at the University
of San Diego further validated the
results. The research appeared in
Nature
Communications
in 2016.
The Huang Research Group has
worked on other steps in the cycle,
such as translocation (
PNAS
, 2014) and
pyrophosphate release (
Journal of the
American Chemical Society
, 2012). Prof
Huang, who as a postdoctoral fellow at
Stanford was advised by Nobel Laureate
and computational structural biology
pioneer Prof Michael Levitt, is also
looking to develop a kinetic network
model. This will link molecular dynamics
with genomics to explore the impact of
molecular behavior at the system level.
“I want to be able to tell you that
this error in the genome is due
to this mistake of the enzyme
at this particular step due
to this mutation,” Prof
Huang said.
