Poster abstracts
Poster number 96 submitted by Benjamin OBrien
Programmable Nucleic Acid Based Polygons with Controlled Neuroimmunomodulatory Properties for Predictive QSAR Modeling
M. Brittany Johnson, Ian Marriott (Department of Biological Sciences, University of North Carolina at Charlotte), Justin R Halman, Emily Satterwhite, Kirill Afonin (Nanoscale Science Program, Department of Chemistry), Alexey V. Zakharov (National Center for Advancing Translational Sciences, National Institutes of Health), My Bui, Kheiria Benkato, Victoria Goldsworthy, Emil Khisamutdinov (Department of Chemistry, Ball State University), Taejin Kim (Department of Chemistry, New York University), Enping Hong, Marina A. Dobrovlskaia (Nanotechnology Characterization Lab, Cancer Research Technology Program, Leidos Biomedical Research, Inc, Frederick National Laboratory for Cancer Research)
Abstract:
In the past few years, the study of therapeutic RNA nanotechnology has expanded tremendously to encompass a large group of interdisciplinary sciences. It is now evident that rationally designed programmable RNA nanostructures offer unique advantages in addressing contemporary therapeutic challenges such as distinguishing target cell types and ameliorating disease. However, to maximize the therapeutic benefit of these nanostructures, it is essential to understand the immunostimulatory aptitude of such tools and identify potential complications. This paper presents a set of 16 nanoparticle platforms that are highly configurable. These novel nucleic acid based polygonal platforms are programmed for controllable self-assembly from RNA and/or DNA strands via canonical Watson-Crick interactions. It is demonstrated that the immunostimulatory properties of these particular designs can be tuned to elicit the desired immune response or lack thereof. To advance the current understanding of the nanoparticle properties that contribute to the observed immunomodulatory activity and establish corresponding designing principles, quantitative structure-activity relationship modeling is conducted. The results demonstrate that molecular weight, together with melting temperature and half-life, strongly predicts the observed immunomodulatory activity. This framework provides the fundamental guidelines necessary for the development of a new library of nanoparticles with predictable immunomodulatory activity.
Keywords: QSAR, RNA nanotechnology, immunology