UltraScan is a comprehensive software package for the analysis of hydrodynamic data from analytical ultracentrifugation and light scattering experiments. Data from such experiments provide insight into the dynamic interactions among macromolecules involved in the processes of the living cell, and allow their study in the solution state which most closely resemble the physiological conditions in the cell. Current studies involving UltraScan focus on the role of macromolecular properties involved in disease and cancer, such as aggregation, and focus on the basic understanding of structure and function of biological polymers like proteins, RNA and DNA. The UltraScan software enjoys a worldwide and growing distribution with over 1200 registered users in academic and industrial environments. With this grant we seek funding to ensure the continued maintenance and further development of the software. The following new projects are proposed: Development of interfaces to integrate the recently commercialized Fluorescence Optical System and the new AU-AOS data acquisition system for the analytical ultracentrifuge into UltraScan. We also propose the development of novel analysis algorithms addressing reversible association, real-time analysis, and the analysis of kinetics in heteroassociating systems. We will provide an interface for the conformational bead modeling approaches proposed in SO MO, and advance parallel computation of Monte Carlo approaches, genetic algorithm optimizations, and the 2-dimensional spectrum analysis. Further, we propose to develop novel approaches for improved nonlinear least squares optimization, to port the software to new platforms and to adapt UltraScan to changes in third-party libraries and compilers. To facilitate collaboration of our GPL release of the source code for UltraScan we will enhance the documentation of source code and expand the user manual. Additional funds are requested to support initiatives for training and education of UltraScan users through workshops and online seminars. The work proposed here will provide software tools that will facilitate high resolution analysis of biophysical and biochemical research addressing the molecular basis of diseases. For example, it may provide clues to identifying pathogenic proteins involved in neurodegenerative diseases, or in the characterization of interactions between proteins and nucleic acids involved in diseases such as cancer.
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