Peptide Quantitation
Peptide Quantitation - Related Videos
07:59
A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes
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Cited by 21 •
2014
Biochemical assays with recombinant human MHC II molecules can provide rapid, quantitative insights into immunogenic epitope identification, deletion, or design. Here, a peptide-MHC II binding assay scaled to 384-well plates is described. This cost effective format should prove useful in the fields of protein deimmunization and vaccine design and development.
09:26
Species Determination and Quantitation in Mixtures Using MRM Mass Spectrometry of Peptides Applied to Meat Authentication
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Cited by 4 •
2016
We present a protocol for identifying and quantifying the components in mixtures of species possessing similar proteins. Mass spectrometry detects peptides for identification, and gives relative quantitation by ratios of peak areas. As a tool food for fraud detection, the method can detect 1% horse in beef.
04:00
Immunoaffinity Based Extraction of Ubiquitinylated Peptides: A Technique to Selectively Extract Ubiquitin Tagged Peptides from Purified Peptide Fractions
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2023
This video describes a method to extract and purify ubiquitinylated peptides containing remnant di-glycine peptides from a complex peptide mixture. The presented method may help in identifying original ubiquitination sites in the protein.
08:57
Peptide and Protein Quantification Using Automated Immuno-MALDI (iMALDI)
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Cited by 13 •
2017
A protocol for the protein quantification in complex biological fluids using automated immuno-MALDI (iMALDI) technology is presented.
03:21
Peptide Purification: An RP-HPLC-based Technique to Extract Peptides from Digested Protein Lysates
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2023
In this video, we demonstrate reversed-phase high-performance liquid chromatography to purify peptides from a digested protein lysate mixture. These purified peptides are then lyophilized and stored for downstream applications. Analysis of peptides can help understand the mechanics involved in cellular signaling and cancer.
FAQs
Peptide quantitation by ultraviolet absorbance can produce sequence-dependent results because the measured signal may arise from peptide bonds or aromatic residues. Peptides differ in composition, so equal amounts do not necessarily generate identical absorbance responses. Interpreting a UV-based estimate therefore requires attention to the peptide sequence and the specific signal being used, especially when comparing different peptides.
Copper-based assays translate peptide-driven copper reduction into color. The resulting color signal provides an indirect measurement linked to peptide amount, and its relationship to concentration can depend on peptide composition. Using suitable standards helps relate the observed color to concentration and makes comparisons among samples more defensible.
They improve concentration estimates by addressing limitations of relying on one signal or assay response. Standards provide a reference for interpreting absorbance or color, while complementary methods offer an additional measurement for comparison. Together, they support more reliable decisions when sequence-dependent signals or assay-dependent variation could affect the result.
Measure peptide-containing fractions with an appropriate signal-based assay, then compare the resulting estimates across fractions. This reveals where peptide is present and helps assess recovery through the purification process. Applying the same measurement approach and suitable standards across fractions improves the usefulness and consistency of those comparisons.
Concentration estimates allow researchers to adjust samples so enzymatic or binding assays receive comparable peptide amounts. This reduces variation caused by unequal input rather than by the biochemical activity being studied. Normalization is particularly useful when comparing assay results across preparations or purification fractions.
Peptide quantitation can help evaluate synthetic peptide yield and compare the amount recovered after purification. These measurements do not stand alone because sequence composition and the selected signal can influence the estimate. Interpreting yield alongside standards and, when appropriate, complementary measurements helps distinguish a meaningful production difference from measurement-related variation.