I have a structure prediction model and now I want to know how well it performs in reproducing the reference structures. But there are so many possible metrics, some for monomers, some for complexes! Is there a package that handles this for me?
Try
It’s a Package for Evaluation of Predicted Poses, Right?
Yes, indeed! It allows you to compute a variety of metrics on your structure predictions for assessing their quality. It supports
all CASP/CAPRI metrics and more
small molecules to huge protein or nucleic acid complexes
easy extension with custom metrics
a command line interface and a Python API
Installation
peppr is available via PyPI:
$ pip install pepprUsage example
Using the CLI, you can either compute a single metric for a system…
$ peppr run dockq reference.cif poses.cif… or run an entire prediction model evaluation on many systems.
# Select the metrics you want to compute (here: RMSD and lDDT)
$ peppr create peppr.pkl monomer-rmsd monomer-lddt
# Run the evaluation on predicted poses and their corresponding references
$ peppr evaluate-batch peppr.pkl "systems/*/reference.cif" "systems/*/poses"
# Select the aggregation method over poses (here: Top-3 and Oracle) and report the results
$ peppr tabulate peppr.pkl table.csv top3 oracleAvailable metrics
RMSD
TM-score
lDDT
lDDT-PLI
fnat
iRMSD
LRMSD
DockQ
… and more!
1 maintainer
Metadata
1 maintainer
Release files for peppr 0.13.1
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Total release size: 157.6 kB
Release files / peppr-0.13.1.tar.gz
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