# US 2025/0166735 A1 · Systems and methods for identifying peptides

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- Number: US 2025/0166735 A1
- Document ID: US20250166735A1
- Status: Published application
- Kind: A1
- Application number: 18/874,453
- Filed: 2023-06-30
- Published: 2025-05-22
- Earliest claimed: 2022-06-30
- Assignees: YYZ Pharmatech, Inc.
- Applicants: YYZ Pharmatech Inc.
- Inventors: John G. MARSHALL; Peter BOWDEN; Jaimie DUFRESNE
- Web page: https://patentgrep.com/patent/US20250166735A1

## CPC

- G16B 30/20: Sequence assembly
- G01N 33/6848: {Methods of protein analysis involving mass spectrometry}
- G16B 30/00: ICT specially adapted for sequence analysis involving nucleotides or amino acids
- G16B 35/20: Screening of libraries
- G16B 40/10: Signal processing, e.g. from mass spectrometry [MS] or from PCR
- G01N 2440/00: Post-translational modifications [PTMs] in chemical analysis of biological material
- G16B: BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q)

## Abstract

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.

## Claims

### Claim 1

A method for identifying a peptide for a query spectrum, the method comprising:
receiving one or more parameters of the 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.

### Claim 2 (depends on 1)

The method of claim 1, wherein selecting at least one sample from the plurality of samples for comparison with the one or more candidate peptide sequences comprises, for each sample:
counting a number of matching sequential b and y spectra lines of that sample; and
if the number of matching sequential b and y spectra lines of that sample is less than a pre-determined minimum number of spectra lines, excluding that sample from comparison with the one or more candidate peptide sequences.

### Claim 3 (depends on 1)

The method of claim 1, wherein selecting at least one sample from the plurality of samples for comparison with the one or more candidate peptide sequences comprises, for each sample:
determining a spectra intensity of that sample;
determine a number of matching b and y spectra lines;
for the matching b and y spectra lines, determining a corresponding sum of the spectra intensity;
determining a total sum of the spectra intensity;
determining a ratio of the sum of the spectra intensity for the matching b and y spectra lines and the total sum of the spectra intensity; and
if the ratio is less than a pre-determined threshold, excluding that sample from comparison with the one or more candidate peptide sequences.

### Claim 4 (depends on 1)

The method of claim 1, wherein selecting at least one sample from the plurality of samples for comparison with the one or more candidate peptide sequences comprises, for each sample:
determining a precursor mass for that sample; and
if the precursor mass is substantially equal to a mass of a candidate peptide sequence, selecting that sample for comparison with the one or more candidate peptide sequences.

### Claim 5 (depends on 4)

The method of claim 4, wherein the precursor mass comprises at least one of a precursor mass at a charge state of 1, 2, or 3 and wherein the precursor mass comprises a mass shift from one or more post-translational modifications.

### Claim 6

(canceled)

### Claim 7 (depends on 1)

The method of claim 1, wherein selecting at least one sample from the plurality of samples for comparison with the one or more candidate peptide sequences comprises, for each sample:
determining a mass of a theoretical ion of the sample; and
if the mass of the theoretical ion is substantially equal to a mass of a base peak, selecting that sample for comparison with the one or more candidate peptide sequences.

### Claim 8 (depends on 1)

The method of claim 1, wherein determining a likelihood indicator for each of the one or more candidate peptide sequences based on a comparison with the at least one sample comprises one or more of:
using one or more of linear regression, multiple linear regression, nested regression or linear model;
using a chi square test to compare theoretical ions of that sample with corresponding theoretical ions of the candidate peptide sequence; and
determining a cross correlation score relative to the candidate peptide sequence.

### Claim 9

(canceled)

### Claim 10

(canceled)

### Claim 11 (depends on 1)

The method of claim 1, wherein applying a signal to noise filter to the one or more candidate peptide sequences based on the likelihood indicators for the candidate peptide sequences comprises:
generating random source noise spectra at high frequencies;
determining a difference between the random source noise spectra at high frequencies to the one or more candidate peptide sequences; and
if the difference exceeds a pre-determined threshold difference, excluding the sample from selection as a proposed peptide sequence for the query spectrum;
otherwise including that sample for selection as a proposed peptide sequence.

### Claim 12

(canceled)

### Claim 13

(canceled)

### Claim 14 (depends on 1)

The method of claim 1, wherein generating one or more candidate peptide sequences based on the one or more parameters of the peptide query comprises one or more of:
storing a plurality of peptide sequences in a computer-readable medium;
selecting, from the computer-readable medium, at least one of the plurality of stored peptide sequences to use as at least one candidate peptide sequence, based on the one or more parameters; and
randomly generating at least one candidate peptide sequence, based on the one or more parameters.

### Claim 15 (depends on 14)

The method of claim 14, wherein:
receiving one or more parameters of the query spectrum comprises receiving the one or more parameters from user input at a computing device; and
the one or more parameters comprise one or more of an amino acid, a position of the amino acid, an amino acid group, a position of the amino acid group, a neutral loss, a post-translational modification shift, an immonium ion, a subtraction of a B ion, or a subtraction of a Y ion.

### Claim 16

(canceled)

### Claim 17 (depends on 14)

The method of claim 14, wherein selecting, from the computer-readable medium, at least one of the plurality of stored peptide sequences to use as at least one candidate peptide sequence, based on the one or more parameters comprises:
identifying a subset of peptide sequences from the plurality of stored peptide sequences, wherein the plurality of stored peptide sequences comprises one or more of: a naturally occurring peptide sequence and a synthetic peptide sequence, each peptide sequence satisfying the one or more parameters; and
selecting the at least one candidate peptide sequence from the subset of peptide sequences.

### Claim 18

(canceled)

### Claim 19 (depends on 14)

The method of claim 14, wherein randomly generating at least one candidate peptide sequence, based on the one or more parameters comprises:
randomly generating a peptide sequence;
determining whether the randomly generated peptide sequence satisfies the one or more parameters; and
if the randomly generated peptide sequence satisfies the one or more parameters, use the randomly generated peptide sequence as a candidate peptide sequence, otherwise discard the randomly generated peptide sequence.

### Claim 20

(canceled)

### Claim 21 (depends on 19)

The method of claim 19, wherein randomly generating at least one candidate peptide sequence, based on the one or more parameters comprises, for each randomly generated candidate peptide sequence:
assigning at least one amino acid to the randomly generated candidate peptide sequence based on the one or more parameters;
randomly selecting an unassigned position of the pre-determined length;
for the unassigned position:
randomly selecting an amino acid; and
assigning the amino acid to the unassigned position; and
continue randomly assigning amino acids to the randomly generated candidate peptide sequence until each position is assigned.

### Claim 22 (depends on 21)

The method of claim 21, wherein randomly selecting an amino acid comprises:
randomly selecting an amino acid group from a plurality of amino acid groups, each amino acid group comprising a plurality of amino acids; and
randomly selecting the amino acid from the randomly selected amino acid group.

### Claim 23 (depends on 22)

The method of claim 22, wherein each randomly generated candidate peptide sequence comprises at least one amino acid from each amino acid group of the plurality of amino acid groups.

### Claim 24

(canceled)

### Claim 25 (depends on 2423)

The method of claim 2423, wherein generating a plurality of samples of the query spectrum comprises one or more of generating experimental spectra or generating simulated spectra, and generating simulated spectra comprises using a Monte Carlo random simulation.

### Claim 26

A system for identifying a peptide for a query spectrum, the system comprising a non-transitory computer readable medium and a processor, the processor operable to:
receive one or more parameters of a query spectrum;
generate one or more candidate peptide sequences based on the one or more parameters of the query spectrum;
generate a plurality of samples of the query spectrum;
select at least one sample from the plurality of samples for comparison with the one or more candidate peptide sequences;
determine a likelihood indicator for each of the one or more candidate peptide sequences based on a comparison with the at least one sample;
apply a signal to noise filter to the one or more candidate peptide sequences based on the likelihood indicators for the candidate peptide sequences; and
select at least one candidate peptide sequence as a proposed peptide sequence for the query spectrum based on the filtered candidate peptide sequences.

### Claim 27 (depends on 26)

The system of claim 26, wherein the processor is operable to, for each sample:
count a number of matching sequential b and y spectra lines of that sample; and
if the number of matching sequential b and y spectra lines of that sample is less than a pre-determined minimum number of spectra lines, exclude that sample from comparison with the one or more candidate peptide sequences.

### Claim 28 (depends on 27)

The system of claim 27, wherein the processor is operable to, for each sample: determine a spectra intensity of that sample;
for the matching sequential b and y spectra lines, determine a corresponding sum of the spectra intensity;
determine a total sum of the spectra intensity;
determine a ratio of the sum of the spectra intensity for the matching sequential b and y spectra lines and the total sum of the spectra intensity; and
if the ratio is less than a pre-determined threshold, exclude that sample from comparison with the one or more candidate peptide sequences.

### Claim 29 (depends on 26)

The system of claim 26, wherein the processor is operable to, for each sample:
determine a precursor mass for that sample; and
if the precursor mass is substantially equal to a mass of a candidate peptide sequence, select that sample for comparison with the one or more candidate peptide sequences.

### Claim 30 (depends on 29)

The system of claim 29, wherein the precursor mass comprises at least one of a precursor mass at a charge state of 1, 2, or 3, and wherein the precursor mass comprises a mass shift from one or more post-translational modifications.

### Claim 31

(canceled)

### Claim 32 (depends on 26)

The system of claim 26, wherein the processor is operable to, for each sample:
determine a mass of a theoretical ion of the sample; and
if the mass of the theoretical ion is substantially equal to a mass of a base peak, select that sample for comparison with the one or more candidate peptide sequences.

### Claim 33 (depends on 26)

The system of claim 26, wherein the processor is operable to, for each sample, use one or more of:
linear regression, multiple linear regression, or nested regression;
a chi square test to compare theoretical ions of that sample with corresponding theoretical ions of the candidate peptide sequence; and
a cross correlation score relative to the candidate peptide sequence, to determine a likelihood indicator for that sample based on a comparison with the one or more candidate peptide sequences.

### Claim 34

(canceled)

### Claim 35

(canceled)

### Claim 36 (depends on 26)

The system of claim 26, wherein the processor is operable to:
generate random source noise spectra at high frequencies;
determine a difference between the random source noise spectra at high frequencies to the one or more candidate peptide sequences; and
if the difference exceeds a pre-determined threshold difference, exclude the sample from selection as a proposed peptide sequence for the query spectrum;
otherwise include that sample for selection as a proposed peptide sequence.

### Claim 37

(canceled)

### Claim 38

(canceled)

### Claim 39 (depends on 26)

The system of claim 26, wherein the processor is operable to:
store a plurality of peptide sequences in a computer-readable medium;
select, from the computer-readable medium, at least one of the plurality of stored peptide sequences to use as at least one candidate peptide sequence of the one or more candidate peptide sequences, based on the one or more parameters; and
randomly generate at least one candidate peptide sequence of the one or more candidate peptide sequences, based on the one or more parameters.

### Claim 40 (depends on 39)

The system of claim 39, wherein the processor is operable to:
receive the one or more parameters from user input at a computing device, the one or more parameters comprise one or more of an amino acid, a position of the amino acid, an amino acid group, a position of the amino acid group, a neutral loss, a post-translational modification shift, an immonium ion, a subtraction of a B ion, or a subtraction of a Y ion.

### Claim 41

(canceled)

### Claim 42 (depends on 39)

The system of claim 39, wherein the processor is operable to:
identify a subset of peptide sequences from the plurality of stored peptide sequences, wherein the plurality of stored peptide sequences comprises one or more of: a naturally occurring peptide sequence and a synthetic peptide sequence, each peptide sequence satisfying the one or more parameters; and
select the at least one candidate peptide sequence from the subset of peptide sequences.

### Claim 43

(canceled)

### Claim 44 (depends on 39)

The system of claim 39, wherein the processor is operable to:
randomly generate a peptide sequence;
determine whether the randomly generated peptide sequence satisfies the one or more parameters; and
if the randomly generated peptide sequence satisfies the one or more parameters, use the randomly generated peptide sequence as a candidate peptide sequence, otherwise discard the randomly generated peptide sequence.

### Claim 45

(canceled)

### Claim 46 (depends on 39)

The system of claim 39, wherein the processor is operable to:
assign at least one amino acid to the randomly generated candidate peptide sequence based on the one or more parameters;
randomly select an unassigned position of the pre-determined length;
for the unassigned position:
randomly select an amino acid; and
assign the amino acid to the unassigned position; and
continue to randomly assign amino acids to the randomly generated candidate peptide sequence until each position is assigned.

### Claim 47 (depends on 46)

The system of claim 46, wherein the processor is operable to:
randomly select an amino acid group from a plurality of amino acid groups, each amino acid group comprising a plurality of amino acids; and
randomly select the amino acid from the randomly selected amino acid group.

### Claim 48 (depends on 47)

The system of claim 47, wherein each randomly generated candidate peptide sequence comprises at least one amino acid from each amino acid group of the plurality of amino acid group.

### Claim 49

(canceled)

### Claim 50 (depends on 26)

The system of claim 26, wherein the processor is operable to generate experimental spectra or simulated spectra, and wherein the processor is operable to use a Monte Carlo random simulation to generate simulated spectra.