# 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
