|
# 2AA-1-complete "Two Amino Acid" data set |
|
|
|
This folder contains a data set of all-atom molecular dynamics trajectories for all 400 |
|
dipeptides, i.e. small proteins composed of two amino acids. |
|
This includes also the peptides missing in the other 2AA datasets. |
|
Each peptide is simulated using classical molecular dynamics and the |
|
water is simulated using an implicit water model. |
|
|
|
For each protein two files are available: |
|
|
|
* `protein-state0.pdb`: contains the topology and initial 3D XYZ coordinates. |
|
* `protein-arrays.npz`: contains trajectory information. |
|
|
|
|
|
## NPZ Information |
|
|
|
The NPZ file contains detailed information for a subset of simulation steps. |
|
There are T such frames and the NPZ file contains the following arrays: |
|
|
|
* 'time': `(T,)` array, simulation time in picoseconds. |
|
* 'energies': `(T,2)` array, each row containing [potential, kinetic] energies |
|
in kJ/mol. |
|
* 'positions': `(T,num_atoms,3)` array, positions in nm. |
|
* 'velocities': `(T,num_atoms,3)` array, velocities in nm/ps. |
|
* 'forces': `(T,num_atoms,3)` array, forces in kJ/(mol nm). |
|
|
|
|
|
## Dataset construction |
|
|
|
The dataset was constructed in the following way: |
|
|
|
1. Construct initial protein using AmberTools's `tleap` program. |
|
2. Process each PDB file using [pdbfixer](https://github.com/openmm/pdbfixer), |
|
adding all missing hydrogen atoms. This is the `state0.pdb` file. |
|
3. For each all-atom PDB file, perform a molecular dynamics simulation: |
|
a.) Use OpenMM with the AMBER99 force field and implicit water model. |
|
b.) Perform an energy minimization (relaxation) from the initial extended |
|
configuration. |
|
c.) Use a second-order Langevin integrator at temperature to T=310K, |
|
friction=0.3/ps, timestep=1.0fs for 50,000 steps to equilibriate |
|
("burn-in phase"). |
|
d.) Use a second-order Langevin integrator at temperature to T=310K, |
|
friction=0.3/ps, timestep=1.0fs for 5e6 steps to sample a trajectory |
|
("sample phase"). |
|
4. Save trajectory information to an `arrays.npz` file. |
|
5. Shuffle and partition the trajectories into a `train` set |
|
(200 trajectories), `val` (80 trajectories), and `test` (100 trajectories). |
|
|
|
|
|
## Credit and Authors |
|
|
|
This dataset was created in October 2022 as part of Timewarp. |
|
|