PDB-score 1.0.6

A tool to massively calculate protein scores using PDB files.

PDB-score

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Features

Implemented GDT scoring for a large number of predicted and actual protein models, along with calculating RMSD after coordinate alignment, which can be used to evaluate the prediction models.

Installation

pip install PDB-score

Usage

psc [-h] -c /path/to/control -t /path/to/treatment -o /path/to/output [-T THREAT] [-B BATCH]

• -c Directory where the experimental PDB files are stored.
• -t Directory where the predicted PDB files are stored.
• -o Directory for saving the output scores.
• -T Specify the number of cores, default is 4.
• -B Specify the Batch size, default is 5000.

Output

/path/to/output/protein_scores.csv

name	RMSD	1A	2A	...	128A	Average
Protein1	rmsd (float)	Score	Score	...	Score	Score
Protein2	rmsd (float)	Score	Score	...	Score	Score
...	...	...	...	...	...	...

Calculation Method

• Perform coordinate alignment using Biopython.
• Scores are calculated using the GDT (Global Distance Test) algorithm.
• All ligands are removed, and only the alpha carbon atoms are used to represent the residue coordinates.
• When the count of alpha carbons differs, the extra or missing residues are directly considered as failing to meet the accuracy criteria (regardless of the accuracy setting).

Performance

• Test Environment:
  • Default parameters: -T 4 -B 5000
  • Test Machine: Windows 11 PC, CPU Intel 12600k
  • Single sample size: 146KB with 154 residues
• Comparing 50,000 samples took 387061ms.
• Memory usage is less than 6GB.

Additional Notes

• Only analyze .pdb and .ent files with the same name (excluding extensions) in the two input directories.
• The -o option only specifies the output directory, not the file name.
• Outputs a .csv file with a fixed file name, so be careful not to overwrite it.

Acknowledgments

• JetBrains
• ChatGPT

@SiriNatsume
Wishing you happiness :)