App Note

Comparison of Mass Spectrometry and Next-Generation Protein Sequencing Analysis 

How new approaches in protein sequencing address the inherent challenges of mass spectrometry

Mass spectrometry (MS) has long been the gold standard in protein identification and analysis. However, several inherent challenges limit its effectiveness in unambiguously mapping individual peptides. With a reliance on complex search algorithms and databases, unexpected or missed cleavages or modifications can lead to unidentified peptides. For example, it can be difficult to differentiate between isomers like asymmetric and symmetric dimethylarginine or identify peptides with subtle chemical modifications, including those introduced by LC-MS ionization. A high level of knowledge and expertise is often required to identify these variations during analytics. These challenges combined with complex workflows, cost, outsourcing turnaround times, and limitations in resolving certain amino acids pose significant barriers. 

How new approaches in protein sequencing address the inherent challenges of mass spectrometry

Alternative protein sequencing technology presents new opportunities for rapid identification of proteins with amino acid and peptide-level resolution. This application note details a comparative study of MS and next-generation protein sequencing technology analyzing three proteins. It provides a comprehensive overview of how each method fares in real-world scenarios, leveraging services from an MS core facility and noting differences in peptide identification, including where MS workflows rely on expert intervention to resolve. 

Delve deeper and download this application note to learn more about:

  • The specific challenges and limitations of mass spectrometry in protein analysis
  • A streamlined, simplified workflow for rapid, accessible in-house protein analysis
  • How performance and resolution compare across the two methods, including which peptides were identified with each technology
  • Considerations for protein identification using each approach

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