Peptide Clustering for Multiplexed Target Binding Screening
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Solution Overview
Problem
Current multiplexed target-binding candidate screening systems are ineffective in detecting similar peptides with insufficient target binding activity, leading to low sensitivity and false negatives in selecting nucleotide-containing peptide libraries for binding to desired targets.
Innovation Solution
A method and system for clustering peptides based on similarity scores using sequencing and quantification information, where peptides are grouped and screened to identify candidates for target binding by computing similarity scores and applying a pre-set threshold, enabling the detection of peptides with collective target binding activity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional screening analysis systems are used to detect peptides with target binding activity, then individual peptides can be screened, but sensitivity is low and false negatives occur for similar peptides with insufficient individual binding activity
Solution Approach 1:
The patent groups similar peptides into clusters based on sequence similarity, then evaluates the collective binding activity of each cluster rather than individual peptides. This merging approach allows the system to detect binding signals that are too weak to be detected individually, thereby improving detection sensitivity and reducing false negatives while maintaining reliable identification of candidate binders.
2Quantity of substance
If individual peptides are screened separately, then each peptide's binding activity can be assessed, but similar peptides with collective binding activity are missed
Solution Approach 1:
By clustering similar peptides and evaluating their collective binding activity, the system increases the effective quantity of detectable peptides. The merging of similar sequences into clusters allows the detection of binding signals that would be below the detection threshold for individual peptides, thereby simultaneously increasing the number of detectable peptides and maintaining detection sensitivity.
3Measurement precision
If clustering of peptides is implemented, then sensitivity is improved by detecting similar peptides collectively, but computational complexity increases
Solution Approach 1:
The patent segments the peptide library into clusters based on sequence similarity, which reduces the computational burden compared to evaluating all peptides individually. By dividing the large set of peptides into smaller, similarity-based groups, the system can efficiently compute collective binding activities for each cluster while maintaining high detection sensitivity, thereby managing computational complexity.
Solution Approach 2:
The clustering approach serves multiple functions simultaneously: it groups similar peptides, reduces computational complexity by evaluating clusters rather than individuals, and improves detection sensitivity by capturing collective binding signals. This multi-functional approach resolves the contradiction between improved sensitivity and increased computational complexity.
Data Source
AI summary
Methods, systems, and computer program products are provided for clustering of similar peptides to detect candidates for target binding. In some embodiments, a method provided herein includes receiving sequencing information and quantification information of a plurality of peptides after target-binding selection in a library. The sequencing information includes amino acid sequences of the plurality of peptides, and the quantification information includes a count of copies of each amino acid sequence in the plurality of peptides. The method further includes computing similarity scores for pairs of the plurality of peptides using the sequencing information. The method further includes grouping the plurality of peptides into clusters based on the similarity scores. The method further includes screening the clusters based on quantification information of peptides in each cluster to obtain candidates for target binding over a pre-set threshold.