We propose to continue development and support for the UltraScan-III (US3) software suite and develop new code and methods to address challenging biomedical research questions that can be solved with the latest instruments available for analytical ultracentrifugation and at beamlines for small-angle X-ray and neutron scattering experiments (SAXS/SANS) experiments. UltraScan is a comprehensive toolkit for the analysis of data from hydrodynamic experiments and simulations. Such experiments include analytical ultracentrifugation, SAXS/SANS, as well as bead modeling simulations. Support for this project will assure continued availability of a mature multi-platform analysis suite with important and unique capabilities not found in any other software packages. Chief among them are tight integration of supercomputing capabilities, LIMS support for collaboration, and specialized analysis routines. US3 enjoys widespread use in the AUC and SAXS/SANS communities, and offers the most robust optimization and simulation algorithms available, resulting in unmatched detail. UltraScan provides the highest throughput, a flexible, modern GUI, and a comprehensive list of analysis routines. Proposed developments include automated data acquisition and analysis workflows, improvements in the fitting of floating data, improved two-dimensional grids, support for density distribution analysis critical for the accurate characterization and quantification of viral vectors, lipid nanoparticles loaded with cancer drugs or nucleic acids, and other vectors used for the delivery of medicines or CRISPR technology.
The proposed work will further develop and continue to maintain the UltraScan software suite, which contributes to the analysis of biophysical solution data with unmatched resolution and efficiency. Among the proposed developments are codes to improve analysis efficiency, to support automated data acquisition from the Beckman-Coulter Optima AUC?TM instrument, and measuring the loading efficiency of lipid nanoparticle vectors for medicines, siRNA and CRISPR technology. These efforts are highly relevant for many current NIH and NSF investigations, support the development of therapeutics against any disease studied on the molecular level, and contribute important tools for studies into the mechanisms of aging, cancer, HIV, neurodegenerative diseases and help with the testing of drugs and their interactions with drug targets.
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