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MD22

MD22

Bases: RevMD17

MD22 consists of molecular dynamics (MD) trajectories of four major classes of biomolecules and supramolecules, ranging from a small peptide with 42 atoms to a double-walled nanotube with 370 atoms. The simulation trajectories are sampled at 400K and 500K with a resolution of 1fs. Potential energy and forces are computed using the PBE+MBD level of theory.

Usage: 

from openqdc.datasets import MD22
dataset = MD22()

Reference

https://arxiv.org/abs/2209.14865

Source code in openqdc/datasets/potential/md22.py 
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class MD22(RevMD17):
    """
    MD22 consists of molecular dynamics (MD) trajectories of four major classes of biomolecules and supramolecules,
    ranging from a small peptide with 42 atoms to a double-walled nanotube with 370 atoms. The simulation trajectories
    are sampled at 400K and 500K with a resolution of 1fs. Potential energy and forces are computed using the PBE+MBD
    level of theory.

    Usage:
    ```python
    from openqdc.datasets import MD22
    dataset = MD22()
    ```

    Reference:
        https://arxiv.org/abs/2209.14865
    """

    __name__ = "md22"
    __links__ = {
        f"{x}.npz": f"http://www.quantum-machine.org/gdml/repo/datasets/md22_{x}.npz"
        for x in [
            "Ac-Ala3-NHMe",
            "DHA",
            "stachyose",
            "AT-AT",
            "AT-AT-CG-CG",
            "double-walled_nanotube",
            "buckyball-catcher",
        ]
    }

    def read_raw_entries(self):
        entries_list = []
        for trajectory in trajectories:
            entries_list.append(read_npz_entry(trajectory, self.root))
        return entries_list