How to Read a COA for Research Peptides
Understanding Certificates of Analysis is essential for verifying peptide quality and purity
What is a Certificate of Analysis (COA)?
A Certificate of Analysis (COA) is a document issued by an independent, accredited laboratory that verifies the identity, purity, and quality of a research peptide. It provides detailed analytical data from various testing methods to ensure the product meets specified standards.
Key Components of a Peptide COA
1. Product Information
The COA should clearly identify the peptide name, CAS number, molecular formula, and molecular weight. It should also include batch/lot numbers and testing dates for traceability.
2. HPLC Analysis
High-Performance Liquid Chromatography (HPLC) is the primary method for determining peptide purity. The COA will show:
- •Purity Percentage: Should be 98% or higher for research-grade peptides
- •Chromatogram: A graph showing peaks that represent different compounds
- •Retention Time: The time it takes for the peptide to pass through the column
3. Mass Spectrometry (MS)
Mass spectrometry confirms the molecular weight and identity of the peptide. The COA should show:
- •Expected Mass: The theoretical molecular weight
- •Found Mass: The actual measured molecular weight
- •Accuracy: These values should match within acceptable limits (typically ±0.1%)
4. Additional Testing
Quality COAs may also include:
- •Water Content: Measured by Karl Fischer titration
- •Peptide Content: The actual amount of peptide in the vial
- •Appearance: Visual inspection results
Red Flags to Watch For
- •Purity below 95%
- •Missing or incomplete testing data
- •No laboratory information or accreditation
- •Molecular weight doesn't match expected values
- •COA is generic or not specific to the batch
Why COAs Matter
COAs are essential for research integrity. They provide independent verification that you're working with the correct compound at the stated purity. Without a COA, you cannot be certain of your research material's quality, which can compromise experimental results and waste valuable research time and resources.