Skip to content

The University of Texas at ArlingtonThe University of Texas at Arlington

College of Science

College of Science News

Nam using National Institutes of Health awards to study enzymes and enzymatic reactions

Kwangho Nam
Kwangho Nam

Kwangho Nam, assistant professor of chemistry and biochemistry at The University of Texas at Arlington, has received two grants from the National Institutes of Health (NIH) for projects which examine enzymes and enzymatic reactions.

Enzymes are biological molecules, typically proteins, which help speed up chemical reactions in the body.

Nam received the most recent award, a four-year grant for a total of $1,405,961, for a project which is aimed at increasing knowledge of the mechanisms of complex enzymatic systems and the roles of protein dynamics in enzyme function.

The first grant, for $132,011, came in April for a project which focuses on developing fast and accurate computer simulation approaches for studying enzymatic reactions.

The grants are from the NIH’s National Institute of General Medical Sciences.

“The latest project aims to determine the catalytic and regulatory mechanisms of two enzymes – insulin receptor kinase and adenylate kinase – through the development and application of novel multiscale modeling methodologies,” Nam said. “A clear understanding of their mechanisms will fill in major gaps in our understanding of their functions in various human diseases, notably cancer, and will aid in the design of novel therapeutic approaches targeting these kinases.”

Nam is the principal investigator of the most recent project, which is titled “Multiscale Modeling of Protein Kinase Structure, Catalysis, and Allostery.” The enzymatic system which serves as the focal point of the research is protein kinase (PK), an enzyme that plays a key role in cellular signaling processes. They modify other molecules, mostly proteins, by chemically adding phosphate groups to them in a process called phosphorylation.

“PK is an attractive system for this purpose because it involves both large-scale conformational change and enzymatic catalysis,” Nam said. “Moreover, because of its pathological significance, understanding PK’s molecular mechanism is of fundamental importance in kinase research and also may provide new insights into the development of improved therapies against kinases.”

The project’s central hypothesis, based on Nam’s recent studies and enzyme kinetic data, is that the catalytic activity – the increase in the rate of a chemical reaction caused by the presence of a catalyst – of PK is closely associated with its regulatory function. Thus, any change in regulatory activity affects the catalytic activity of the kinase, which occurs through allosteric modulation of underlying protein dynamics, and together control the overall activity of the kinase. This is in contrast to the conventional view that the inactive-to-active conformational change is the main mechanism for regulating kinase activity, Nam said.

“Our objective in this grant is to examine these two contrasting views on the regulation of kinase activity by the parallel study of two important kinases, insulin receptor kinase and adenylate kinase, which play critical roles in cell homeostasis, and explain their complete molecular mechanisms,” he said.

Nam is co-PI of the first project, titled “Multiscale ab initio QM/MM and machine learning methods for accelerated free energy simulations.” The PI is Evgeny Epifanovsky, a staff scientist at Q-Chem, a state-of-the-art commercial quantum chemistry program designed to solve computational problems faster and with lower cost and greater accuracy.

“In this project, we are seeking to significantly reduce the computational time (about 500,000 CPU hours) required to obtain accurate free energy profiles of enzymatic reactions to about 25,000 CPU hours,” Nam said. “Building upon sophisticated quantum mechanics, this can lead to reliable and quick predictions of enzyme activities.”

Nam said that he and his colleagues are using a multiple time step molecular dynamics simulation method, where a low-level (and less accurate) quantum chemistry method is used to propagate the system (i.e. move all atoms) at each time step, and then a high-level – more accurate and expensive – quantum chemistry method is used to correct the force on the atoms at longer time intervals.

“In this way, the simulation can be performed at the high-level energy surface in a fraction of time, compared with simulations performed only using the high-level quantum chemical method,” he said.

Nam said that the new multiple time step simulation method will make it feasible to routinely perform computational studies on the enzymatic reaction mechanism.

Fred MacDonnell, professor, and chair of the UTA Department of Chemistry and Biochemistry noted that Nam’s projects expand UTA’s influence in the fields of data-driven discovery as well as health and the human condition, which are two of the main areas of emphasis of UTA”s Strategic Plan 2020.

“Dr. Nam and his group are doing innovative research,” MacDonnell said. “His work has the potential to provide an important new understanding of modeling enzyme function, which could in turn help provide more effective treatments for people with diseases such as cancer.”

Nam received B.S. and M.S. degrees from Korea University in 1995 and 1998, respectively. He earned a Ph.D. in Chemistry from the University of Minnesota in 2006 and worked as a postdoctoral researcher at Harvard University from 2006-11. From 2011-16 he worked as an assistant professor and research fellow at Umeå University in Sweden. He came to UTA in October 2016.