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# AurA wild-type and mutant Folding@home simulations ## Main project repository Additional project documentation, data, and scripts can be found here: [https://github.com/choderalab/AurA-materials][1] ## Explicit solvent trajectories The following Folding@home projects were analyzed for manuscript, and are made available here as full explicit solvent trajectories: 11414: AurA +TPX2, pdb 1OL5 * RUN0: WT * RUN1: Q185C * RUN2: Q185L * RUN3: Q185M * RUN4: Q185N 11419: AurA +TPX2, pdb 1OL5 * RUN0: WT * RUN1: WT * RUN2: WT * RUN3: WT * RUN4: Q185H -- has no data, input was broken * RUN5: C247A * RUN6: C247L 11418: AurA -TPX2, pdb 1OL5 * RUN0: WT * RUN1: WT * RUN2: WT * RUN3: WT * RUN4: WT 11423: AurA -TPX2, pdb 1OL5 * RUN0: Q185C * RUN1: Q185L * RUN2: Q185M * RUN3: Q185N * RUN4: Q185H * RUN5: C247A * RUN6: C247L Each trajectory is available in the appropriate project folder: ``` AurA Folding@home simulations > explicit solvent > <project number>` ``` with trajectory files formatted as `run<RUN>-clone<CLONE>.h5`, with `<RUN>` indexing the mutant or WT replicate and `<CLONE>` denoting different replicates initiated from the same structure but different initial velocities. These trajectories are stored in [MDTraj HDF5 format](http://mdtraj.org/latest/hdf5_format.html). This is a compact, platform-portable format that contains both topology information (atom names, connectivity, and residue information) and trajectory data. You can use the freely-available [MDTraj](http://mdtraj.org/) package to convert to other popular trajectory formats. ## Processed data The processed data can be found in a single archive containing [numpy `.npy` archives](https://docs.scipy.org/doc/numpy/reference/generated/numpy.save.html) as `processed-data.tgz` under "AurA processed data". [1]: https://github.com/choderalab/AurA-materials
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