constructboundary

Name: constructboundary
Availability: InStock
Author: farnunglab

Predict optimal protein construct boundaries from sequence data.

27|4|Updated Feb 8, 2026

Search Tags:#pdb #alphafold #uniprot #domain-boundaries #construct-boundaries #protein-expression #truncation-design

Ready to run

npx skills add https://github.com/farnunglab/benchaid --skill constructboundary

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: constructboundary
Source: https://github.com/farnunglab/benchaid/tree/main/skills/constructboundary
Command: npx skills add https://github.com/farnunglab/benchaid --skill constructboundary

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This tool analyzes protein sequences to identify optimal truncation boundaries for recombinant expression constructs, enabling efficient structural biology workflows and higher-quality purified proteins.

Core Features & Use Cases

Boundary prediction: Suggest domain-based and disorder-informed truncations that maximize expression and crystallization potential.
Input flexibility: Accepts UniProt IDs, gene names, or raw sequences to generate boundary options.
Evidence-informed design: Leverages data from UniProt, AlphaFold DB, and PDB to align predicted boundaries with known structures and confidence scores.

Quick Start

Run with a UniProt ID (for example CHD1_HUMAN) to obtain predicted construct boundaries.

Frequently Asked Questions about constructboundary

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

FAQPage Schema

How do I predict protein construct boundaries for recombinant expression?▼

The tool identifies optimal truncation boundaries by analyzing protein sequences to maximize recombinant expression and crystallization potential. It suggests domain-based and disorder-informed truncations that improve purified protein quality for structural biology workflows.

What inputs are accepted for designing protein truncations?▼

Protein truncation design accepts UniProt IDs, gene names, or raw sequences as valid inputs. This flexibility allows you to generate boundary options regardless of whether you have a database identifier or just sequence data.

Can I use AlphaFold and PDB data to guide construct boundary prediction?▼

Yes, construct boundary prediction leverages evidence from UniProt, AlphaFold DB, and PDB data. It aligns predicted boundaries with known structures and confidence scores to ensure evidence-informed design.

What is the best way to define domain boundaries for protein expression?▼

The best way to define domain boundaries is using an explicit scoring scheme that ranks boundary predictions based on structural evidence. Applying domain boundaries, truncations, and disordered regions ensures constructs maximize expression potential.

Does construct boundary prediction work with disordered regions in protein targets?▼

Yes, construct boundary prediction works with disordered regions across protein targets. It suggests disorder-informed truncations that remove flexible regions to maximize expression and crystallization potential.