Skip to content Skip to main navigation Report an accessibility issue

Dr. Tongye Shen


kraken_2In collaboration with ORNL experimenters using world-class neutron technology and supercomputing facilities applied to the signaling protein, kinase A (PKA), Tongye Shen targets the challenge of studying complex protein systems with a powerful combination of modeling, theoretical, and computational tools.

From the point of view of physics, the functions of protein molecules—and whether they act for good or ill—relate to the changing of states or configurations of those molecules. That is, how they function in a biological system depends upon how stable each configuration is and how fast the molecules make transitions between configurations. Each molecule has multiple stable configurations (or “conformations”) and a range of simple to complicated dynamics (or “conformational” dynamics).

Modern biology identifies many diseases as malfunctions at the molecular level of protein systems. Thus, understanding the mechanisms of these macromolecules is of critical importance to the bioengineering of new diagnostics and therapies for diseases.

shen_2

As a biophysicist Shen’s expertise is grounded in statistical and soft-matter physics and advanced computation. This project gives him the additional opportunity to collaborate in a multidisciplinary study of the large-scale, dynamic motions of signaling proteins using the cutting-edge technique of small-angle neutron scattering (SANS). However, we need better ways to interpret the valuable SANS observations related to flexible, large-scale motions of a signaling protein complex.

Enter Shen’s team—including post doc Ricky Nellas and undergraduate Richard Linsay—with “coarse-grained” modeling. The method sacrifices detailed information for the positive advantage of extending both the spatial scale (in terms of size or extent of dynamic motion of the signaling protein) and the time scale. While the calculations are formulated to take less than a few minutes, the approach is sensitive to small perturbations and void of sampling errors.

The complementary LDRD project headed by William T. Heller examines conformational changes in PKA with SANS and is an ideal testbed for validating and applying Shen’s statistical modeling tools to biomedical research. High-performance computer simulations led by Loukas Petridis will complement the joint effort. Both teams expect to continue their multidisciplinary collaboration both at UT-ORNL and with researchers at other institutions such as the University of California-San Diego and the University of Utah, while pursuing funding for further coarse-grained study of the dynamics of protein in complex environments and interfaces.


JDRD project:
Coarse-grained modeling of the conformational dynamics of signaling protein complex
Tongye Shen, UT Biochemistry and Cellular and Molecular Biology Department, UT-ORNL Graduate School of Genome Science and Technology, and UT-ORNL Center for Molecular Biophysics

LDRD project:
Probing the structure-function relationship in protein kinase A
William Heller, ORNL Biology and Soft Matter Division


trinh_narayan_2Single cell production, as it is called, intrigues genetic and metabolic engineers Cong Trinh and ORNL’s Adam Guss. The two have joined forces to find out what it would take to turn common yeast, S. cerevisiae, and E. Coli into miniature cell factories that directly convert fermentable sugars, lignin, and the chemical inhibitors found in biomass into an array of advanced biofuels and other biochemicals.

All living organisms select nutritious substances, reject poisonous ones, and organize the sequential chemical reactions required to transform food chemicals into energy. The series of steps required to get from food consumption to growth and reproduction are called metabolic pathways.

Nature creates a network of pathways, Trinh says. So microorganisms can be redesigned to use atypical pathways and, as a result, yield different products. To Trinh and Guss, microbial metabolism offers a playground of opportunity to design microbes capable of producing valuable end products.

Guss’s LDRD team set out to redesign the bacteria E. coil to convert lignin and biomass inhibitors into isobutanol; Trinh’s JDRD team is reengineering the yeast Saccharomyces to change sugars and biomass inhibitors (specifically acetate) into biodiesel instead of ethanol, its usual end product.

Cong Trihn's research teamIn year one Trinh, PhD graduate student Adam Thompston, and postdoc Narayan Niraula mapped out Saccharomyces’ metabolic pathways and then used computer simulation to design the most optimal paths for converting glucose and acetate to biodiesels. This part of the project takes advantage of a huge database of information from industries that use Saccharomyces species to make bread, wine, and beer. Their simulations help determine what laboratory methods to use to create and characterize the required genetic changes—a process they continued into year two of the project.

Their preliminary results detected and quantified biodiesel production in S. cerevisiae and generated isobutanol from E. coli with better physical properties than reported by others in previous research.

“Ultimately we want to create microbial cell factories that will not only make biodiesels, but could also become a platform for other biochemicals derived from biomass,” Trinh says.


JDRD project:
Redesigning yeast metabolism for optimal biodiesel production from biomass (year 2)
Cong Trinh, UT Chemical and Biomolecular Engineering Department

LDRD project:
Synthetic metabolic pathways for bioconversion of lignin and biomass inhibitors
Adam Guss, ORNL Biosciences Division