gcell-protein

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Protein structure and interaction analysis using gcell. Use this skill when users ask about: - Protein sequences from gene names - AlphaFold2 structure predictions and pLDDT scores - UniProt protein information - 3D protein structure visualization - Protein-protein interactions (STRING database) Triggers: protein structure, AlphaFold, pLDDT, UniProt, protein sequence, 3D structure, protein interaction, STRING

GET-Foundation By GET-Foundation schedule Updated 1/16/2026

name: gcell-protein description: | Protein structure and interaction analysis using gcell. Use this skill when users ask about: - Protein sequences from gene names - AlphaFold2 structure predictions and pLDDT scores - UniProt protein information - 3D protein structure visualization - Protein-protein interactions (STRING database) Triggers: protein structure, AlphaFold, pLDDT, UniProt, protein sequence, 3D structure, protein interaction, STRING

Protein Structure Analysis

Get Protein Sequences

from gcell.protein.data import (
    get_seq_from_gene_name,
    get_uniprot_from_gene_name
)

# Get protein sequence from gene name
seq = get_seq_from_gene_name('TP53')
seq = get_seq_from_gene_name('EGFR')
seq = get_seq_from_gene_name('BRCA1')

# Get UniProt accession
uniprot_id = get_uniprot_from_gene_name('TP53')

AlphaFold2 Confidence Scores

from gcell.protein.data import get_lddt_from_gene_name

# Get pLDDT (predicted local distance difference test) scores
# Higher scores = higher confidence in structure prediction
plddt = get_lddt_from_gene_name('TP53')
plddt = get_lddt_from_gene_name('EGFR')

# pLDDT interpretation:
# > 90: Very high confidence
# 70-90: Confident
# 50-70: Low confidence
# < 50: Very low confidence (likely disordered)

Full Protein Analysis

from gcell.protein.protein import Protein

# Load protein from gene name
protein = Protein.from_gene_name('EGFR')
protein = Protein.from_gene_name('TP53')

# Access protein data
print(protein.sequence)
print(protein.length)
print(protein.plddt)  # AlphaFold confidence

# 3D structure visualization
protein.plot_structure()  # Interactive 3D view

Protein-Protein Interactions

from gcell.protein.string import get_string_interactions

# Get interactions from STRING database
interactions = get_string_interactions('TP53')

# Filter by confidence score
high_conf = interactions[interactions['score'] > 0.7]

Key Classes and Functions

Name Purpose
Protein Full protein analysis class
get_seq_from_gene_name() Get amino acid sequence
get_uniprot_from_gene_name() Get UniProt ID
get_lddt_from_gene_name() Get AlphaFold pLDDT scores
get_string_interactions() Get protein interactions

Data Sources

  • Protein sequences: UniProt
  • Structures: AlphaFold Database
  • Interactions: STRING Database
  • Data cached in: ~/.gcell_data/cache/
Install via CLI
npx skills add https://github.com/GET-Foundation/gcell --skill gcell-protein
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