Computer modeling of biochemical processes is part of the multibillion-dollar research effort that aids the design of new pharmaceuticals, helps investigate protein structure and function and advances our understanding of the molecular basis of disease. Despite the widespread use and success of modeling proteins, quantitative biochemical simulations lack reproducibility and community-wide research standards, which negatively affects the quality and speed of research. Dr. Nathan DeYonker’s, assistant professor in Department of Chemistry, research group has been developing software that can automate the design and quantum mechanics-based molecular-level protein simulations. The software package is intended to improve communication between many scientists in different domains of biology and chemistry.
The long-term goals of the research involve improving reproducibility and reducing barriers for entry into the field of quantum chemical modeling of biomolecules. Thus, the scope of the project is somewhat unconventionally “meta”, focusing on how to improve research workflows via data science. However, software design and calibration projects have been carried out in tandem with applications of the improved biomodels. For example, the DeYonker group has studied antibiotic mechanisms, artificial protein engineering, and degradation of biomass and plastics.
From these efforts, DeYonker has recently been awarded a prestigious NSF Early Faculty CAREER award through the Infrastructure Innovation for Biological Research Program, as well as a U.S Department of Energy Small Business Innovation Research Award through the Basic Energy Sciences Program. For more information on this research, contact DeYonker at ndyonker@memphis.edu