---
title: GraphSol
description: Predict protein solubility from sequence with an attentive graph convolutional network over predicted contact maps — a probability plus a binary call.
tags:
  - graphsol
---

GraphSol predicts protein solubility from sequence with a structure-aware graph convolutional network built on predicted contact maps. Reach for it when a solubility call gates the next step — ranking expression constructs, assessing the impact of mutations, or prioritizing targets for structural studies. It predicts solubility by a different method than [DeepSol](/docs/deepsol), so run both and treat agreement as a consensus. See [what you can achieve](/docs/capabilities#admet-and-safety) for the full set.

## GraphSol integration in .bloom* platform

GraphSol is a structure-aware protein solubility prediction method using attentive **Graph Convolutional Networks (GCN)**. Published in the Journal of Cheminformatics, it was the first study to make sequence-based solubility predictions through graph neural networks, constructing protein topology graphs from predicted contact maps.

### Citations

> Chen J, Zheng S, Zhao H, Yang Y. Structure-aware protein solubility prediction from sequence through graph convolutional network and predicted contact map. *Journal of Cheminformatics*. 2021 Feb 8;13:7. doi: [10.1186/s13321-021-00488-1](https://doi.org/10.1186/s13321-021-00488-1)

### Performance benchmarks

Tested on the eSOL database, GraphSol achieved state-of-the-art results:
- **AUC**: 0.866
- **F-measure**: 0.732
- **Accuracy**: 0.779 (using threshold of 0.5 for soluble proteins)

Through .bloom*'s webapp, you can rapidly assess protein expression potential and guide protein engineering decisions without requiring experimental structure determination.

## Webapp sequence processing capabilities

### Input methods in .bloom*

**Direct sequence entry:**
- Paste amino acid sequences in FASTA or raw format
- Real-time validation with sequence length and composition checks
- Automatic detection of standard vs. non-standard amino acids
- Preview of sequence properties (length, molecular weight, isoelectric point)

**Batch processing:**
- Upload FASTA files with multiple protein sequences
- Support for multi-sequence files with automatic parsing
- Progress tracking for large sequence libraries
- Error handling for individual sequence failures

**Integration with other tools:**
- Direct import from BLAST search results
- Connection to sequence clustering outputs
- Import from protein engineering workflows
- Integration with homology modeling results

### Prediction outputs

**Solubility assessment:**
- **Probability scores**: Continuous solubility prediction (0-1 scale)
- **Binary classification**: Soluble vs. insoluble predictions
- **Confidence estimates**: Model certainty for each prediction
- **Sequence features**: Contributing factors to solubility prediction

**Analysis capabilities:**
- **Batch statistics**: Distribution analysis across sequence libraries
- **Comparative visualization**: Solubility trends across protein families
- **Filtering tools**: Sort and prioritize sequences by solubility
- **Export options**: CSV, JSON, and interactive visualization formats

## When to use GraphSol in protein engineering

### Expression construct design

**Solubility screening:**
- Evaluate protein variants before experimental expression
- Prioritize constructs with higher solubility potential
- Guide codon optimization and expression host selection
- Reduce experimental screening burden

**Protein engineering:**
- Assess solubility impact of mutations and insertions
- Compare solubility across protein variant libraries
- Guide directed evolution strategies
- Optimize protein stability and expression

**Homolog selection:**
- Rank homologous proteins by predicted solubility
- Choose optimal starting points for engineering campaigns
- Compare solubility across species variants
- Guide phylogenetic selection strategies

### Structural biology workflows

**Target selection:**
- Identify soluble protein targets for structural studies
- Prioritize proteins for crystallization trials
- Guide NMR sample preparation decisions
- Optimize protein production strategies

**Domain engineering:**
- Predict solubility of individual protein domains
- Design soluble fusion constructs
- Optimize linker sequences for multi-domain proteins
- Guide protein fragmentation strategies

## Model characteristics and performance

### Prediction accuracy

**Performance metrics:**
- **Correlation**: Good agreement with experimental solubility data
- **Classification accuracy**: >80% for soluble/insoluble discrimination
- **Sequence coverage**: Works across diverse protein families
- **Length range**: Optimized for 20-4,096 residue proteins

### Applicability domain

**Protein types supported:**
- **Single domains**: Excellent performance on individual protein domains
- **Multi-domain proteins**: Good performance with domain boundary consideration
- **Fusion proteins**: Handles common expression tags and linkers
- **Mutant libraries**: Sensitive to solubility-changing mutations

**Limitations:**
- **Very short peptides**: Reduced accuracy for sequences <20 residues
- **Membrane proteins**: Limited applicability to transmembrane regions
- **Intrinsically disordered**: May not capture IDP solubility characteristics
- **Post-translational modifications**: Does not account for glycosylation effects

## Performance and scaling

### Processing efficiency

**Speed characteristics:**
- **Single sequences**: Near-instant predictions (<1 second)
- **Batch processing**: Linear scaling with sequence count
- **Large libraries**: Support for thousands of sequences per job
- **Real-time feedback**: Immediate results for interactive analysis

### Resource optimization

**Computational requirements:**
- Low computational overhead per prediction
- No GPU requirements for standard predictions
- Memory efficient for large sequence batches
- Optimized for high-throughput screening

## Integration with .bloom* ecosystem

### Upstream sequence sources

**Bioinformatics tools:**
- **BLAST**: Evaluate homolog solubility from search results
- **Sequence alignment**: Compare solubility across aligned sequences
- **Motif analysis**: Assess functional motif impact on solubility
- **Domain prediction**: Evaluate domain solubility contributions

**Protein design:**
- **ESM prediction integration**: Combine folding and solubility assessment
- **Mutagenesis planning**: Guide mutation strategies for improved solubility
- **Library design**: Optimize variant libraries for soluble expression

### Downstream applications

**Experimental planning:**
- Guide protein expression condition optimization
- Plan purification strategy based on solubility predictions
- Design solubility screening assays
- Optimize buffer and additive selection

**Protein production:**
- Select optimal expression constructs
- Guide scale-up production decisions
- Plan formulation development strategies
- Optimize protein storage conditions

### Workflow automation

**High-throughput screening:**
- Automated batch processing of sequence libraries
- Integration with laboratory automation systems
- Real-time result monitoring and prioritization
- Quality control and data validation pipelines

**Research collaboration:**
- Shared solubility predictions across teams
- Integration with electronic lab notebooks
- Audit trails for experimental reproducibility
- Comparative analysis across research projects

## Chat Usage

### Example Prompts

- "Predict solubility for human lysozyme using GraphSol"
- "Run GraphSol on my ESMFold structure to find aggregation-prone regions"
- "Compare GraphSol vs DeepSol predictions for this protein"

### Workflow Chaining

- **Feeds into**: Formulation planning, Compound Passport
- **Accepts from**: UniProt (sequences), ESMFold (predicted structures)

## FAQ

### What does GraphSol require?

  Provide amino acid sequences in FASTA or plain text with clear IDs.

### How fast are predictions?

  Typical jobs finish in under five minutes for small batches; larger sets scale linearly.

### How are scores interpreted?

  GraphSol returns per-sequence solubility probabilities along with binary calls using a 0.5 default threshold.

## Read next