The Computational Core research plan has been revised to address specific questions and concerns raised by the reviewers, and to emphasize the principle focus of this core. The primary goals of the Computational Core are 1) to develop a set of computational tools and protocols to facilitate the analysis and interpretation of EPR spectral data, including distance measurements obtained from DEER experiments for doubly spin-labeled proteins, and 2) provide basic computational support for the individual research projects. For Project 1, basic computational support entails a series of equilibrium MD simulations to support EPR spectral calculations. In Project 2, this computational support includes detailed equilibrium MD simulations for CDB3 to explore possible conformational changes triggered by the P327R point mutant, and preliminary results are described above in the Project 2 Research Plan. Basic computational support for Project 3 includes routine structure refinement calculations for conventional 2D-NMR experiments and paramagnetic resonance enhancement NMR experiments, as well as MD simulations to explore conformational trends for spin labels introduced in the amyloid-beta peptides. This conformational analysis will be important to address distance dependencies on spin label side chain conformational behavior in both EPR experiments and paramagnetic resonance enhancement NMR studies. The development of practical computational tools and protocols to facilitate EPR data analysis depends crucially on data obtained in Project 1, and requires several discreet steps. First, it is important to establish that we can use conventional equilibrium MD simulations that describe spin label side chain dynamics and protein backbone dynamics, coupled with Brownian dynamics calculations that model global protein tumbling, to compute EPR spectra directly for singly labeled proteins. As the reviewers noted, previous published attempts to exploit this type of strategy have not been completely satisfactory or convincing. However, these previous studies were based on rather limited MD simulations, and possibly suffered from some other issues that we address in more detail in the Research Plan below. It is essential to establish that a simulation strategy can be used to compute EPR spectra, in order to establish that we can capture the important features and behavior of spin-labeled proteins that give rise to unique EPR spectra for different samples (e.g., the sharp, distinct spectral signal typical of a completely mobile spin label versus the broader, more complex signals representative of partially immobilized spin labels). As discussed in the Project 1 Research Plan, we now have preliminary results that indicate we can compute EPR spectra more accurately and reliably than has been reported previously. There is still need for improvement, and we present detailed analysis of current MD-based EPR spectral simulations below that highlight possible inadequacies in the current methodology, and discuss specific strategies and tests to address these problems. Only after we have established convincingly that we can calculate EPR spectra directly with the combined MD/Brownian dynamics simulation protocol can we address seriously the calculation of spin label pair distances obtained in EPR DEER experiments, or pursue development of simpler computational strategies that do not require multiple, lengthy MD simulations with explicit solvent to estimate these distances. A number of issues impact the reliable MD simulation of spin label pair distances, including several raised by the reviewers for Project 1 (E.g., potential function parameters, electrostatics treatment, periodic boundary effects, etc.) We present preliminary data in the revised Research Plan below that addresses these issues and other important factors, and the strategies to achieve improved EPR spectral calculations and DEER distance estimates are presented in the context of a new Specific Aim 1.

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