Protein Assembly Skill

This skill provides systematic approaches for designing multi-component fusion protein sequences, with emphasis on FRET biosensor construction, spectral matching, and codon optimization.

Task Decomposition Strategy

Complex protein assembly tasks require systematic decomposition into discrete, verifiable sub-tasks. Establish clear success criteria for each phase before proceeding.

Phase 1: Component Identification

Break the assembly into individual components that must be identified:

1. Fluorescent proteins - Identify by spectral properties (excitation/emission wavelengths)
2. Binding domains - Identify by ligand/substrate specificity (e.g., SNAP-tag for O6-benzylguanine)
3. Target proteins - Identify by function (e.g., antibody targets, enzymes)
4. Linker sequences - Determine type and length requirements

For each component, document:

• The identification criteria (wavelength, ligand, function)
• The source (PDB ID, database entry, plasmid file)
• The extracted sequence (verify before proceeding)

Phase 2: Sequence Extraction

Extract and verify each protein sequence before assembly:

1. PDB sequences: Use RCSB PDB FASTA endpoint (https://www.rcsb.org/fasta/entry/{PDB_ID})
2. Fluorescent proteins: Query FPbase API with wavelength filters
3. Plasmid sequences: Parse GenBank format files completely (handle truncation)
4. Validate extraction: Confirm sequence length and expected features

Phase 3: Assembly and Optimization

Assemble components in specified order with linkers, then optimize:

1. Apply N-terminal methionine rules (remove internal Met starts)
2. Insert linker sequences between domains
3. Perform codon optimization for target organism
4. Validate constraints (length, GC content windows)

Critical Verification Checkpoints

Establish verification checkpoints to prevent cascading errors:

Checkpoint 1: Spectral Matching

• For FRET pairs, verify donor emission overlaps with acceptor excitation
• Match filter cube specifications exactly (not approximately)
• Document the specific wavelength values being matched

Checkpoint 2: Sequence Completeness

• Verify API responses are not truncated
• If data exceeds buffer limits, implement pagination or filtering
• Cross-reference sequence lengths with expected values

Checkpoint 3: Assembly Validation

• Verify component order matches requirements
• Confirm linker lengths within specified constraints
• Check total nucleotide count against limits

Checkpoint 4: Optimization Validation

• Calculate GC content in sliding windows (typically 50nt)
• Verify all windows fall within acceptable range (e.g., 30-70%)
• Confirm codon usage matches target organism

Common Pitfalls and Mitigations

Data Truncation

Problem: API responses or file reads may be truncated at character limits. Mitigation:

• Check response completeness before parsing
• Use targeted queries with filters rather than downloading entire databases
• Request specific ranges when reading large files
• Implement pagination for large result sets

Imprecise Wavelength Matching

Problem: Selecting proteins with "close enough" wavelengths instead of exact matches. Mitigation:

• Use FPbase API filtering parameters for excitation/emission ranges
• Query for specific wavelength values, not ranges
• Verify FRET compatibility (donor emission must overlap acceptor excitation)

Premature Assembly

Problem: Attempting to assemble sequences before all components are verified. Mitigation:

• Create explicit checkpoints after each component is identified
• Document each sequence extraction with source and verification
• Do not proceed to assembly until all sequences are confirmed

Missing Constraint Validation

Problem: Generating sequences without validating requirements. Mitigation:

• Build validation logic early in the process
• Check constraints incrementally during codon optimization
• Final validation pass before output generation

Incomplete File Parsing

Problem: Assuming sequence identity without extracting from source files. Mitigation:

• Parse GenBank files to extract CDS features explicitly
• Do not assume sequence identity based on file names
• Verify extracted sequences against annotations

Systematic Workflow

Step 1: Parse Requirements

Extract all constraints from the task specification:

• Required spectral properties (exact wavelengths)
• Component ordering requirements
• Linker specifications (type, length range)
• Optimization constraints (GC content, length limits)
• Output format requirements

Step 2: Identify Components Individually

For each required protein component:

1. Determine identification criteria from requirements
2. Query appropriate database/source
3. Handle complete response (paginate if needed)
4. Extract candidate sequences
5. Verify match against criteria
6. Document source and sequence

Step 3: Validate FRET Compatibility (if applicable)

For fluorescent protein pairs:

1. Confirm donor excitation matches source
2. Confirm acceptor emission matches detector
3. Verify spectral overlap for energy transfer
4. Document the FRET pair selection rationale

Step 4: Assemble Construct

1. Order components per specification
2. Remove internal methionines as required
3. Insert appropriate linkers
4. Generate nucleotide sequence

Step 5: Optimize Codons

1. Select codon table for target organism
2. Optimize with GC content constraints
3. Apply sliding window validation
4. Iterate until all windows pass

Step 6: Final Validation

1. Verify total length within limits
2. Confirm GC content in all windows
3. Translate back to verify protein sequence
4. Save to specified output location

Database Query Strategies

FPbase Queries

• Use wavelength range parameters for initial filtering
• Query individual proteins for detailed spectral data
• Cross-reference excitation AND emission requirements

PDB Queries

• Fetch FASTA sequences via REST API
• Verify chain identifiers when multiple chains present
• Handle homo-multimeric structures appropriately

SMILES/Chemical Structure Identification

• Use PubChem or ChEBI for structure identification
• Cross-reference with protein binding databases
• Verify binding protein identity through literature

Output Generation

gBlock Sequences

• Verify sequence is within synthesis limits (typically under 3000nt)
• Check for problematic sequences (extreme GC, repeats)
• Include 5' and 3' sequences if required for cloning
• Save to specified output file path

Documentation

• Record all component sources
• Document selection rationale for each protein
• Note any assumptions or approximations made