peppr.MonomerRMSD

class peppr.MonomerRMSD(threshold: float, ca_only: bool = True)

Compute the root mean squared deviation (RMSD) between each peptide chain in the reference and the pose and take the mean weighted by the number of heavy atoms.

Parameters:

thresholdfloat

The RMSD threshold to use for the good predictions.

ca_onlybool, optional

If True, only consider \(C_{\alpha}\) atoms. Otherwise, consider all heavy atoms.

evaluate(reference: AtomArray, pose: AtomArray) → float

Apply this metric on the given predicted pose with respect to the given reference.

ABSTRACT: Must be overridden by subclasses.

Parameters:

referenceAtomArray, shape=(n,)

The reference structure of the system. Each separate instance/molecule must have a distinct chain_id.

poseAtomArray, shape=(n,)

The predicted pose. Must have the same length and atom order as the reference.

Returns:

float

The metric computed for each pose. NaN, if the structure is not suitable for this metric.

Notes

Missing atoms in either the reference or the pose can be identified with NaN values.

smaller_is_better() → bool

Whether as smaller value of this metric is considered a better prediction.

ABSTRACT: Must be overridden by subclasses.

Returns:

bool

If true, a smaller value of this metric is considered a better prediction. Otherwise, a larger value is considered a better prediction.