Peptide Spectrum Sampling and Filtering for Faster Identification

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Solution Overview

Problem

Existing methods for identifying peptides are inefficient and costly, particularly in the context of drug development, due to the complexity of isolating and characterizing peptide aptamers, and the limitations of database searching and de novo sequencing methods in mass spectrometry.

Innovation Solution

A computer-implemented method involving generating candidate peptide sequences based on query spectrum parameters, applying signal-to-noise filters, and selecting likely sequences through statistical analysis and random peptide generation, with optional use of annotated libraries and de novo-style rules to narrow the search space.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If database searching and de novo sequencing methods are used for peptide identification, then peptide sequences can be identified, but the process is inefficient and costly with high computational intensity

Engineering Contradiction:

Improvepeptide identification efficiencyVSAvoidtime for cloning and expression

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system performs preliminary actions by generating candidate peptide sequences and creating multiple spectrum samples before the actual identification process. This includes generating theoretical spectra for candidate peptides and preparing filter criteria in advance, which streamlines the subsequent matching process and reduces overall identification time

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The identification process is segmented into distinct stages: generating candidate sequences, creating spectrum samples, applying multiple filters (signal-to-noise, spectral matching, statistical), and selecting final candidates. This segmentation allows each stage to be optimized independently and processes to be run in parallel, improving efficiency

Inventive Principle:

Principle #1Segmentation

2Measurement precision

If multiple spectrum samples are generated and compared with candidate peptide sequences, then identification accuracy is improved, but computational intensity increases

Engineering Contradiction:

Improvepeptide identification accuracyVSAvoidcomputational energy

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The system applies partial action by using a representative subset of spectrum samples rather than exhaustively analyzing all possible samples. Multiple samples are generated and compared, but the process is controlled to use only the necessary number of samples and comparisons needed to achieve confident identification, balancing accuracy with computational cost

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The system extracts key features and characteristics from the spectrum samples and candidate peptide sequences, focusing computational effort on comparing these extracted features rather than processing complete raw data. This includes extracting spectral peaks, intensities, and patterns that are most diagnostic for identification

Inventive Principle:

Principle #2Taking out (Extraction)

3Reliability

If signal-to-noise filters and statistical analysis are applied to candidate peptide sequences, then false positives are reduced, but processing time increases

Engineering Contradiction:

Improvereliability of peptide identificationVSAvoidcomplexity of filtering process

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

Statistical parameters and filter thresholds are determined and set in advance based on training data or theoretical considerations. This preliminary establishment of criteria allows the filtering process to proceed efficiently without real-time complex calculations, maintaining reliability while reducing processing complexity

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system uses computationally inexpensive statistical tests and filters that can be applied rapidly to large numbers of candidate sequences. These filters are designed to be computationally lightweight, allowing many candidates to be screened quickly, with more intensive analysis reserved only for top candidates

Inventive Principle:

Principle #27Cheap short-living objects (Disposable)

Data Source

PatentUS12597487B2Systems and methods for identifying peptides by sampling and filtering

Publication Date: 2026.04.07 YYZ PHARMATECH INC

AI summary

Systems and methods for identifying a peptide for a query spectrum. The methods can involve receiving one or more parameters of a query spectrum; generating one or more candidate peptide sequences based on the one or more parameters of the query spectrum; generating a plurality of samples of the query spectrum; selecting at least one sample from the plurality of samples for comparison with the one or more candidate peptide sequences; determining a likelihood indicator for each of the one or more candidate peptide sequences based on a comparison with the at least one sample; applying a signal to noise filter to the one or more candidate peptide sequences based on the likelihood indicators for the candidate peptide sequences; and selecting at least one candidate peptide sequence as a proposed peptide sequence for the query spectrum based on the filtered candidate peptide sequences.