Chemist Awarded $1.1 Million NIH Grant to Model “Long-Time” Molecular Movements
Aug. 13, 2013
AUSTIN, Texas — A University of Texas at Austin chemist has received a $1.1 million grant from the National Institutes of Health to expand research modeling “long-time” biological processes down to the last atom.
These simulations will model biological processes in atomic detail over wide ranges of time, from milliseconds to hours, allowing researchers to observe the fine details of movement in the time ranges they actually occur, said Ron Elber, a professor of chemistry and biochemistry and director of the Institute for Computational Engineering and Sciences’ Center for Computational Life Sciences and Biology. He also holds the W. A. “Tex” Moncrief, Jr. Chair in Computational Life Sciences and Biology.
The grant, which will be awarded over four years, will be used to support more student and senior scientists who will aid in continuing and expanding research.
“Our group is on the forefront of development and applications to study long-time kinetics and investigate broad temporal scales,” said Elber. “In the present cycle we focus on applications to conformational transitions in proteins that provide subtle control for many biological processes.”
Currently, such atomically detailed simulations can typically only be run in time ranges shorter than a millisecond. This is much shorter than many important biochemical processes, including protein conformation change and substrate binding.
Elber has already modeled processes ranging from milliseconds to hours long by applying a technique he developed called Milestoning.
Milestoning uses a selection of atomic conformations at representative times — these are the “milestones” that give the method its name — and applies statistical and mechanistic theory to estimate the movement of atoms from one milestone to the next.
The result is a simulation that shows atomic and global molecular movement over a period of defined time.
The milestones and the atomic movements link them together, are split up and analyzed on high-performance parallel processing computers, which can process many milestones and linking trajectories at one time.
Elber uses the computing resources at the Texas Advanced Computing Center to analyze Milestoning data.
Elber has used the Milestoning method to model the movement of myosin — the protein responsible for muscle movement. He’s also used the technique to model how different molecules diffuse through a cell membrane, and how the HIV virus uses the enzyme reverse transcriptase to create a copy of itself than can be incorporated into a host genome.
In the future, Elber plans to expand on these research topics, including how mutations affect the function of myosin and reverse transcriptase.
“We will expand our studies of HIV reverse transcriptase in collaboration with Ken Johnson,” said Elber, mentioning the fellow UT biochemistry professor. “We will examine selectivity by initial weak binding, and the effect of specific mutations on enzyme evolution, drug resistance and substrate specificity.”
Another area that Elber hopes to investigate concerns a certain “chicken-or-egg” type of question: Does the binding of a molecule to its target initiate a conformational transition, or does the molecule select from conformations already present in the target?
“To address this and other questions we develop strategies to compute and assess alternative molecular mechanisms and pathways,” said Elber.