Solubility Scoring API
The solubility scoring API predicts the solubility of an input protein structure.
Examples
Command Line Examples
Submit a PDB for solubility scoring:
lev engine submit solubility-score input.pdb
Python Examples
Submit a PDB for solubility scoring:
from engine.solubility_score.client import SolubilityScoreClient
client = SolubilityScoreClient()
job_id = client.submit(input_pdb="input.pdb")
Inputs
--pdb-file
- Input PDB file — cleaned and/or relaxed PDB
- Prepare a clean PDB using the Clean PDB API
- CLI argument:
--pdb-file input.pdb
- Python submit() argument:
pdb-file=”input.pdb”
- Do not include multimodel (NMR-sourced) PDBs.
- Cyrus strongly recommends using the Relax API on your PDB prior to using this API.
Outputs
predictions.csv
- CSV file containing solubility prediction information, containing:
- Total solubility score for the structure
- per-residue solubility scores
- per-residue SASA percentages
- per-residue absolute SASA in angstroms (Å)
- CSV file containing solubility prediction information, containing:
Notes
Output File interpretation
The solubility score is a measure of how aggregation-prone a residue or structure is, with higher scores representing higher aggregation propensity. The SASA percentage is the accessible surface area when compared to the same residue in a GLY-X-GLY peptide (1.00 meaning 100%, or as exposed as the very-exposed same residue in the GLY-X-GLY peptide). This value may be slightly over 100%.