---
title: Preparing GraphSol inputs
description: 'Supply FASTA, UniProt accessions or a previous job output — 20 to 4,096 residues each, 25 MB per upload, the 20 standard amino acids, unique identifiers.'
---

You provide proteins as sequences — pasted in FASTA, fetched from UniProt IDs, or imported from a previous job. The one thing that most affects your result is sequence integrity: use standard amino acids and unique identifiers, and keep each sequence within the accepted length range so the graph features generate cleanly.

## Webapp input methods

The .bloom* webapp provides three input methods for GraphSol protein solubility prediction:

## Input method selection

| Input Method | Description |
|--------------|-------------|
| **FASTA Sequences** | Paste protein sequences in FASTA format |
| **UniProt IDs** | Enter UniProt accessions for automatic sequence retrieval |
| **From Previous Job** | Import sequences from BLAST or other protein analysis jobs |

### FASTA sequences input (default)

- **Format**: Standard FASTA with header lines starting with `>`
- **Multiline textarea**: 6 rows for sequence entry
- **Example placeholder**:
  ```
  >protein1
  MRLVQLSRHSIAFPSPEGALREPNGLLALGGDLSPARLLMAYQRGIFPWFSPGDPILWWSPDPRAVLWPESLHISRSMK
  >protein2
  MQEIYRFIDDAIEADRQRYTDIADQIWDHPETRFEEFWSAEHLASALESAGFTVTRNVGNIPNAFIASFGQGKPVIALL
  ```
- **Validation**: Must include `>` header lines

### UniProt IDs input

- **Dynamic list**: Add multiple UniProt IDs with "Add UniProt ID" button
- **Format**: Standard UniProt accessions (e.g., `P00533`)
- **Auto-fetch**: System retrieves sequences from UniProt database
- **Validation**: Alphanumeric characters and underscores only

### From previous job

- **Job Output Selector**: Browse completed jobs with protein sequence outputs
- **Data type**: Requires `protein_sequence` output
- **Compatible tools**: BLAST results, ESMFold inputs, other protein analysis

## Webapp parameters

### Job options

| Parameter | Default | Description |
|-----------|---------|-------------|
| **Job Title** | (optional) | Custom identifier for tracking |
| **Output Filename Stem** | `graphsol_prediction` | Base name for output files |

### Personalized settings

- **Use Personalized Settings**: Toggle for project-specific configuration
- Loads settings from Supabase when enabled

## Submit button

- **Label**: "Predict Protein Solubility"
- **Disabled when**: Input validation fails (no sequences/IDs or invalid format)

## Output information

The tool provides:
- Main results CSV with solubility predictions and confidence scores
- Quality metrics summary for feature generation assessment
- Detailed feature files organized by protein (PSI-BLAST, HH-Suite, contact predictions)

## Protein sequence input methods in .bloom* platform

GraphSol accepts various protein sequence formats through .bloom*'s intuitive web interface. The tool provides real-time validation, sequence preview, and automatic format detection to ensure reliable solubility predictions.

## Direct sequence entry methods

### Single sequence input

**FASTA format:**
- Standard FASTA format with header line starting with ">"
- Descriptive headers for result tracking (e.g., ">MyProtein_001")
- Single protein sequence per submission
- Automatic validation and preview

**Raw sequence:**
- Plain amino acid sequence without headers
- Direct paste of sequence strings
- Automatic format detection and conversion
- Real-time sequence property calculation

### Batch sequence processing

**Multi-sequence FASTA files:**
- Upload FASTA files containing multiple protein sequences
- Automatic parsing of headers and sequences
- Progress tracking for large sequence libraries
- Error reporting for individual sequence issues

**Tab-separated format:**
- Text files with `<identifier>\t<sequence>` format
- One sequence per line
- Automatic delimiter detection
- Support for custom identifiers

## Sequence validation and preprocessing

### Character validation

**Amino acid alphabet:**
- Only standard amino acids accepted: ACDEFGHIKLMNPQRSTVWY
- Automatic removal of whitespace, numbers, and special characters
- Case-insensitive processing (converted to uppercase)
- Warning for non-standard characters

**Sequence cleaning:**
- Automatic whitespace stripping
- Number and punctuation removal
- Invalid character filtering
- Sequence normalization for consistency

### Length and size requirements

**Sequence length limits:**
- **Minimum**: 20 amino acid residues
- **Maximum**: 4,096 amino acid residues
- **Optimal range**: 50-2,000 residues for best performance
- **Very short sequences**: May have reduced prediction accuracy

**File size constraints:**
- **Maximum file size**: 25 MB per submission
- **Compression support**: Automatic gzip (.gz) detection
- **Large datasets**: Split into multiple jobs if needed
- **Batch limits**: Thousands of sequences supported

## Sequence quality control

### Identifier management

**Unique identifiers:**
- Each sequence must have a unique identifier
- Automatic duplicate detection and removal
- Warning messages for duplicate sequences
- Preservation of original identifiers in results

**Identifier formatting:**
- Descriptive but concise headers recommended
- Avoid special characters in identifiers
- Consistent naming conventions across batches
- Support for alphanumeric characters and underscores

### Sequence integrity checks

**Format validation:**
- Proper FASTA header formatting
- No empty lines between headers and sequences
- Consistent sequence representation
- UTF-8 encoding requirement

**Content validation:**
- Amino acid composition analysis
- Sequence length verification
- Basic physicochemical property calculation
- Unusual composition warnings

## Advanced input options

### Integration with other tools

**BLAST results import:**
- Direct import from BLAST sequence search results
- Automatic extraction of hit sequences
- Preservation of alignment information
- Batch processing of homologous sequences

**Sequence analysis workflows:**
- Import from multiple sequence alignment outputs
- Connection to motif analysis results
- Integration with domain prediction tools
- Support for clustered sequence datasets

### File handling features

**Format conversion:**
- Automatic conversion between input formats
- Standardization to internal representation
- Preservation of sequence metadata
- Error recovery for malformed inputs

**Batch processing:**
- Parallel validation of multiple sequences
- Individual error handling per sequence
- Progress monitoring for large files
- Partial success reporting for mixed-quality inputs

## Input preparation workflows

### Research laboratory workflow

1. **Export sequences** from your analysis software
2. **Format as FASTA** with descriptive headers
3. **Validate locally** using sequence analysis tools
4. **Upload to .bloom** through the GraphSol interface
5. **Review validation results** before submission

### High-throughput screening

1. **Prepare sequence libraries** in batch FASTA format
2. **Apply consistent naming** conventions
3. **Compress large files** using gzip
4. **Upload and validate** through web interface
5. **Monitor batch processing** progress
6. **Review results** and plan next steps

### Protein engineering pipeline

1. **Generate variant sequences** from design software
2. **Format with variant identifiers** for tracking
3. **Batch validation** of all variants
4. **Submit for solubility prediction** in parallel
5. **Compare results** across variant libraries
6. **Select optimal candidates** for experimental testing

## Troubleshooting input issues

### Common validation errors

**Invalid amino acids:**
- Check for non-standard amino acid codes
- Remove ambiguous characters (B, J, O, U, X, Z)
- Verify sequence source and translation accuracy
- Use sequence cleaning tools if needed

**Length violations:**
- Split very long sequences into domains
- Check for sequence concatenation errors
- Verify translation frame for DNA-derived sequences
- Consider domain-specific solubility analysis

**File format issues:**
- Ensure proper FASTA header formatting
- Check for encoding problems (use UTF-8)
- Remove empty lines and formatting artifacts
- Validate with text editors or sequence tools

**Duplicate sequences:**
- Implement unique identifier schemes
- Remove true duplicates from input files
- Use version numbers for variant tracking
- Consider if duplicates are intentional (controls)

## Best practices for input preparation

### Quality assurance

- Always validate sequences before submission
- Use consistent naming conventions across projects
- Document sequence sources and modifications
- Keep backup copies of original sequence files

### Performance optimization

- Batch similar-length sequences together
- Compress large files to reduce upload time
- Use descriptive but concise identifiers
- Consider splitting very large batches into manageable jobs

### Result traceability

- Include meaningful identifiers for result interpretation
- Document sequence modifications and sources
- Maintain version control for sequence datasets
- Link predictions back to experimental constructs

## Read next