Research Interests:
Structural and mechanical properties of muscle Probing myosin kinetics in cells via systems analysis Applied computational physiology and biophysics
Image adapted from D. Maughan and B. Palmer
Overview My research efforts combine computational analyses and experimental measurements to identify, characterize, and describe molecular mechanism modulating muscle contraction. My interdisciplinary training has benefited from many exciting collaborations that motivate an ever evolving set of studies. Structural and mechanical properties of muscle that coordinate myosin cross-bridge behavior Actin (blue) and myosin (red) are the contractile proteins that generate force in muscle cells, comprising one of the most ubiquitous molecular motor systems found in nature. Actin and myosin form thin and thick filaments, respectively. These filaments are organized in lattice-like configuration within the sarcomere. Multiple proteins must work together to maintain proper architecture and underlying mechanical properties of the muscle filament lattice (shown here in cross-section) to facilitate normal contraction. My PhD research at University of Washington focused on creating a half-sarcomere representation of the muscle filament lattice in silico. I have used this spatially-explicit computational modeling to probe how ensemble behavior of actin-myosin cross-bridges is effected by structural and mechanical characteristics of the muscle filament network. Simulations have shown: -- the ratio and arrangement of thick and thin filaments influences cooperative cross-bridge binding -- energy consumption varies strongly with timing between neural activation and force production -- apparent rates of cooperative force production slow with diminished stiffness of the myofilament lattice -- spatial characteristics of thin filament activation in skeletal muscle play the dominant role in cooperative cross-bridge binding I envision future applications of this modeling paradigm
will illustrate spatial and mechanical mechanisms by which additional sarcomeric
proteins modulate normal and dysfunctional muscle contraction. Applications include specific protein targets
that undergo dynamic phosphorylation such as troponin, tropomyosin, myosin
regulatory light chain, titin, or myosin binding protein-C or reductions in
myosin cycling kinetics due to aging or disease. Back to Top
Mechanical system analysis to measure myosin cross-bridge kinetics in muscle cells  my PhD arose from a motor system with strain-dependent or load-dependent
kinetics. This behavior implies that
fundamental characteristics of muscle, such as force production, power output,
and shortening and lengthening, rely upon the way cross-
bridges
sense strain and respond to load.
However, strain-dependent myosin kinetics are difficult to measure on
the single
molecule level and cross-bridges work as an ensemble within a
highly-ordered lattice filaments in muscle.
Therefore, I have
been learning and developing mechanical system
analysis methods throughout my post-doctoral training at University of Vermont.
I was awarded
a postdoctoral fellowship from the National Science Foundation to develop stochastic system analysis methods
to quantify the effect of strain on
myosin cycling kinetics in muscle fibers.
These methods enabled the first measure of strain-dependent myosin
attachment time in a muscle fiber during periods of linear shortening and
lengthening. Ongoing experimental
and computational studies are building on this
analysis technique to investigate the molecular basis of power output in
oscillatory muscle systems such as insect-flight and cardiac muscles.
Back to Top
Back to Top Applied computational physiology and biophysics  While my training primarily has primarily focused on muscle mechanics at the molecular and cellular level, I have a broad appreciation for the powerful role that physics and mathematics can play in quantitative descriptions of biological system behavior. The computational tools I employ are applicable to studying a wide range of network behavior in biological systems—from genomes to ecosystems.
My earliest training in computational biophysics. |
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