---
title: "Proteomics: Mass Spectra, Quantification and Interaction Maps"
description: "Mass spectrometry identifies peptides from mass and fragmentation, and quantification turns spectra into abundances that can be compared between conditions. This stop covers what a proteome measuremen"
canonical: https://lightmysky.com/learn/science/proteomics-mass-spectra-quantification-and-interaction-maps-mt_a-8UHB2SFR
source: https://lightmysky.com/learn/science/proteomics-mass-spectra-quantification-and-interaction-maps-mt_a-8UHB2SFR.md
retrieved: 2026-09-12
---

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# Proteomics: Mass Spectra, Quantification and Interaction Maps

Mass spectrometry identifies peptides from mass and fragmentation, and quantification turns spectra into abundances that can be compared between conditions. This stop covers what a proteome measurement misses and how an interaction map is built and misread.

Subject: Science · Area: Biochemistry & Molecular Biology · Ages 23 to 24
Page: https://lightmysky.com/learn/science/proteomics-mass-spectra-quantification-and-interaction-maps-mt_a-8UHB2SFR

## Ready when they can

- Describe how a peptide spectrum is matched to a sequence and what the false discovery rate there controls
- Compare label-free and isotope-label quantification for a stated comparison
- Explain why an affinity-purification interaction list needs both a control pull-down and a scoring step

## Lesson: Weighing proteins piece by piece

Proteins carry out the work genes encode, and abundance plus modifications decide function, not just presence. That is why you study proteins directly instead of reading genes alone. In proteomics, proteins are digested to peptides, ionized, fragmented, and weighed in a mass spectrometer. The masses of the fragments spell out sequence, piece by piece.

**Example.** A measured spectrum is searched against predicted spectra from a sequence database, and the top match above a threshold wins the peptide. The false discovery rate controls the share of false hits accepted among reported matches: a 1 percent rate means one in a hundred reported matches is bogus. Set the threshold loose and the list grows, but so does the junk inside it.

Quantification turns spectra into abundances you can compare between conditions. Label free comparison works run to run with no tags, which is cheap but noisy. Isotope labels multiplex samples in one run, which is precise at higher cost. Pick the method that fits your comparison: screen broadly on a budget, or measure tightly where small changes matter.

**Tip.** Interaction maps need the same skepticism as spectra. Beads pull down the bait plus sticky background, so an affinity purification list needs both a control pull down and a scoring step to separate true partners from junk. When you read any proteomics result, say which proteins were measured, which were inferred, and which were missed by design: peptides that never ionize never testify.

**Recap.** Digest, weigh, match against the database, quantify with honest error rates, and subtract the background.

## Practice

8 questions on this page, each with its working shown.

## Needs first

- [Post-translational Modification and Protein Turnover](https://lightmysky.com/learn/science/post-translational-modification-and-protein-turnover-mt_93cxQwxxkh)
- [Fractionation, Blotting and Pulling Down a Binding Partner](https://lightmysky.com/learn/science/fractionation-blotting-and-pulling-down-a-binding-partner-mt_MRfFQlBIPy)