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protein-assembly

Design multi-component fusion protein sequences with codon optimization and GC content constraints.

Updated Feb 24, 2026
Search Tags:#bioinformatics#protein engineering#fusion protein#FRET biosensor#codon optimization#gene synthesis
One-click install
npx skills add https://github.com/Zurybr/lefarma-skills --skill protein-assembly-zurybr
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: protein-assembly
Source: https://github.com/Zurybr/lefarma-skills/tree/main/letta/benchmarks/trajectory-only/protein-assembly
Command: npx skills add https://github.com/Zurybr/lefarma-skills --skill protein-assembly-zurybr

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses the complex task of designing and assembling multi-component fusion protein sequences, particularly for applications like FRET biosensors and tagged constructs, by providing a systematic approach to component identification, sequence extraction, and optimization.

Core Features & Use Cases

  • Component Identification: Identifies fluorescent proteins, binding domains, target proteins, and linkers based on spectral properties, ligand specificity, or function.
  • Sequence Extraction & Verification: Extracts and validates sequences from sources like PDB, FPbase API, and GenBank files.
  • Codon Optimization: Optimizes sequences for target organisms with GC content constraints.
  • Use Case: Assembling a novel FRET biosensor by selecting a donor and acceptor fluorescent protein pair, a target protein, and appropriate linkers, then optimizing the final construct for expression in E. coli.

Quick Start

Use the protein-assembly skill to design a fusion protein construct with specific spectral properties and codon optimization requirements.

Frequently Asked Questions about protein-assembly

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I design and assemble a multi-domain fusion protein for a FRET biosensor?▼

To design a FRET biosensor fusion protein, you systematically identify donor and acceptor fluorescent proteins, extract target sequences from PDB or FPbase, select linkers, and optimize the construct for expression.

What's the best way to extract and verify protein sequences from PDB files for fusion constructs?▼

Extracting protein sequences for fusion constructs involves retrieving target domains from PDB entries, validating them against structural data, and preparing the verified sequences for subsequent codon optimization and assembly.

Can I optimize fusion protein codons with specific GC content constraints for E. coli expression?▼

Codon optimization for fusion proteins applies target organism constraints, balancing GC content and codon usage to generate gBlock sequences optimized for efficient E. coli expression.

How do I select fluorescent proteins with specific spectral properties for a fusion construct?▼

Selecting fluorescent proteins for fusion constructs involves querying spectral databases like FPbase to identify donor and acceptor pairs that match your required excitation and emission properties.

Does this fusion protein assembly process handle gBlock sequence generation for gene synthesis?▼

Fusion protein assembly generates gBlock sequences by concatenating verified multi-domain components and performing codon optimization, directly producing the final nucleotide sequences required for gene synthesis.

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