Proteome Quantification via Peptide Verification and Weighted Mean
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Solution Overview
Problem
Current proteomic label-free quantification methods face challenges in achieving high accuracy and coverage due to high false positive errors, noise interference, and limitations in peptide identification, particularly with peptides having lower signal intensity, which affects the accuracy of protein abundance calculation.
Innovation Solution
A method that uses a weighted mean of the first 3 peptides with maximum abundance values for calculating protein abundance, combined with accurate theoretical isotope pattern method (ATIPM) and charge state verification, to improve peptide identification and quantification accuracy, and selectively utilize high-quality mass spectrometric data for more accurate protein abundance ratio calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If quantification without identification result is used, then more peptides and proteins can be quantified, but the quantified peptides have high false positive error and large noise peak interference
Solution Approach 1:
The patent applies preliminary identification of peptides through secondary mass spectrogram (LC-MS/MS) before performing quantification on primary mass spectrogram (LC-MS). This preliminary action filters out false positives and noise peaks by establishing peptide identity through database searching and quality control, then using this identified information to guide accurate quantification of validated peptides.
2Measurement precision
If quantification with identification result is used, then false positive error is reduced and quantification accuracy is improved, but fewer peptides and proteins can be quantified
Solution Approach 1:
The patent changes the parameters of peptide identification by using accurate theoretical isotope pattern method (ATIPM) to verify peptide presence, incorporating charge state verification, and using a weighted mean of the first 3 peptides with maximum abundance values. These parameter changes improve identification accuracy while maintaining broader quantification coverage by using multiple verification criteria rather than single-threshold filtering.
3Productivity
If traditional area under curve calculation method is used, then quantification can be performed, but the calculation accuracy is not high enough
Solution Approach 1:
The patent applies feedback by using accurate theoretical isotope pattern method (ATIPM) to verify peptide presence and incorporate this verification feedback into the quantification process. The method uses charge state verification and weighted mean calculations based on verified peptides, providing feedback loops that continuously improve quantification accuracy by validating each peptide's presence before including it in abundance calculations.
Data Source
AI summary
The present invention relates to a method for quantifying the relative content of a protein in a sample. The present invention also relates to a method for comprising the relative content of a protein in at least two samples.