DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of the Claims
Claims 1-20 are pending and under consideration in this action.
Priority
The instant application does not claim domestic or foreign benefit, as reflected in the filing receipt mailed 05/19/2023. The filing date of the instant application is the effective filing date of claims 1-20. As such, the effective filing date of claims 1-20 is 05/02/2023.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 05/02/2023 and 03/31/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the IDS’s have been considered by the examiner.
Specification
The disclosure is objected to because it contains an embedded hyperlink and/or other form of browser-executable code (see Specification Para. [0051]). Applicant is required to delete the embedded hyperlink and/or other form of browser-executable code; references to websites should be limited to the top-level domain name without any prefix such as http:// or other browser-executable code. See MPEP § 608.01.
Claim Objections
Claims 3, 11, and 16 are objected to because of the following informalities:
Claims 3, 11 and 16 recite the phrase “wherein the post-translational modification combinations of the biological compound is detected by the following conditions…”, which should be corrected to “wherein the post-translational modification combinations of the biological compound are detected by the following conditions…” for clarity.
Appropriate correction is required.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 14-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 14 recites “a computer readable medium with an executable instruction stored thereon to perform the method for automatic detection of post-translational modifications of a biological compound” in lines 1-2 of the claim. There is insufficient antecedent basis for the method for automatic detection in the claim, since there is no prior mention of this phrase earlier in the claim. This rejection can be overcome by amendment of claim 14 to recite “a computer readable medium with an executable instruction stored thereon to perform a method for automatic detection of post-translational modifications of a biological compound”. Claims 15-20 are also rejected due to their dependency from claim 14.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite mental processes, i.e., concepts performed in the human mind (including observations, evaluations, judgements or opinions) (see MPEP § 2106.04(a)).
Framework with which to evaluate Subject Matter Eligibility as outlined in MPEP § 2106:
Step 1: Are the claims directed to a process, machine, manufacture or composition of matter;
Step 2A, Prong One: Do the claims recite a judicially recognized exception, i.e., a law of nature, a natural phenomenon, or an abstract idea;
Step 2A, Prong Two: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application (Prong Two); and
Step 2B: If the claims do not integrate the judicial exception, do the claims provide an inventive concept.
Framework as it pertains to the instant claims:
Step 1:
In the instant application, claims 1-9 are directed towards a method, and claims 10-13 are directed towards a system, which falls into one of the categories of statutory subject matter (Step 1: YES).
Claims 14-20 are directed towards a computer readable medium, which does not fall within one of the categories of statutory subject matter (Step 1: NO). Regarding claim 14, the BRI of computer readable medium encompasses non-statutory forms of signal transmission and therefore equates to “signals per se”. Claims that equate to “signals per se” are not a statutory category of invention (see MPEP § 2106.03). However, claim 14 could be amended to be statutory subject matter by replacing the phrase “computer readable medium” with the phrase “non-transitory computer readable medium”. Nonetheless, this amendment would still result in a rejection of the claim under 35 U.S.C 101 for recitation of a judicial exception without significantly more. Regarding claims 15-20, these claims are rejected due to their dependency on claim 14, which recited non-statutory subject matter. In the interest of compact prosecution, claims 14-20 have been analyzed using the Alice/Mayo two-part test below.
Step 2A, Prong One:
In accordance with MPEP § 2106, claims found to recite statutory subject matter (Step 1: YES) are then analyzed to determine if the claims recite any concepts that equate to an abstract idea, law of nature or natural phenomenon (Step 2A, Prong One). The following instant claims recite limitations that equate to one or more categories of judicial exceptions:
Claims 1, 10, and 14 recite a mental process (i.e., an evaluation of post-translational modifications using a search algorithm) in “generating post-translational modification combinations and masses thereof by processing user-defined post-translational modifications using a search algorithm”; a mental process (i.e., an evaluation of the mass shift and mass for matching) in “matching the mass shift and a mass of each of the post-translational modification combinations”; and a mental process (i.e., an evaluation of the matching to determine post-translational modifications for the biological compound) in “automatically detecting the post-translational modifications of the biological compound based on the matching”.
Claims 2, 11, and 15 recite a mental process (i.e., an evaluation of the accuracy of matched post-translational modification combinations) in “using a position obtained from the compound-spectrum match to validate the correctness of matched post-translational modification combinations”.
Claims 3, 11, and 16 recite a mental process (i.e., an evaluation of the whether mass differences are within a default value and locations are within a sequence in the compound-spectrum match) in “wherein the post-translational modification combinations of the biological compound is detected by the following conditions: 1) mass difference between the mass shift of the compound-spectrum match and the mass of each of the post-translational modification combinations is within a default value, and 2) locations of post-translational modifications in the post-translational modification combinations are included in a sequence of the compound-spectrum match”.
Claims 5, 12, and 17 recite a mental process (i.e., an evaluation of the search algorithm) in “wherein the search algorithm is a depth-first search algorithm”.
Claims 6, 12, and 18 recite a mental process (i.e., an evaluation of the search algorithm) in “wherein each of the user-defined post-translational modifications is a tree node of the depth-first search”.
Claim 7 recites a mental process (i.e., an evaluation of the biological compound and compound-spectrum match) in “wherein the biological compound is a protein, and the compound-spectrum match is a peptide-spectrum match”.
These recitations are similar to the concepts of collecting information, and displaying certain results of the collection and analysis in Electric Power Group, LLC, v. Alstom (830 F.3d 1350, 119 USPQ2d 1739 (Fed. Cir. 2016)), and comparing information regarding a sample or test to a control or target data in Univ. of Utah Research Found. v. Ambry Genetics Corp. (774 F.3d 755, 113 U.S.P.Q.2d 1241 (Fed. Cir. 2014)) and Association for Molecular Pathology v. USPTO (689 F.3d 1303, 103 U.S.P.Q.2d 1681 (Fed. Cir. 2012)), that the courts have identified as concepts that can be practically performed in the human mind.
The abstract ideas recited in the claims are evaluated under the broadest reasonable interpretation (BRI) of the claim limitations when read in light of and consistent with the specification, and are determined to be directed to mental processes that in the simplest embodiments are not too complex to practically perform in the human mind.
Specifically, claims 1, 10, and 14 involve nothing more than generating post-translational modification combinations using a search algorithm, matching mass shift and masses of the post-translational modification combinations, and using the mass data to detect post-translational modifications of the compound. Since there are no specifics in the methodology, the steps of generating post-translational modification combinations using a search algorithm, matching mass shift and masses of the post-translational modification combinations, and using the mass data to detect post-translational modifications of the compound, are something that under BRI, one could perform mentally. Therefore, the claimed steps are not further defined beyond something that reads on merely looking at data and making a determination. As such, said steps are directed to judicial exceptions. The instant claims must therefore be examined further to determine whether they integrate the abstract idea into a practical application (Step 2A, Prong One: YES).
Step 2A, Prong Two:
In determining whether a claim is directed to a judicial exception, further examination is performed that analyzes if the claim recites additional elements that when examined as a whole integrates the judicial exception(s) into a practical application (MPEP § 2106.04(d)). A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. The claimed additional elements are analyzed to determine if the abstract idea is integrated into a practical application (MPEP § 2106.04(d)(I)). If the claim contains no additional elements beyond the abstract idea, the claim fails to integrate the abstract idea into a practical application (MPEP § 2106.04(d)(III)). The following independent claims recite limitations that equate to additional elements:
Claim 1 recites “acquiring a mass shift of a compound-spectrum match between the biological compound and a spectrum”.
Claim 10 recites “a memory”; “a processor”; and “storing user-defined post-translational modifications and a mass shift of a compound-spectrum match between the biological compound and a spectrum”.
Claim 14 recites “a computer readable medium with an executable instruction stored thereon”; and “acquiring a mass shift of a compound-spectrum match between the biological compound and a spectrum”.
Regarding the above cited limitations in claims 10 and 14 of (i) a memory and a processor (claim 10); and (ii) a computer readable medium with an executable instruction stored thereon (claim 14). These limitations require only a generic computer component, which does not improve computer technology. Therefore, these limitations equate to mere instructions to implement an abstract idea on a generic computer, which the courts have established does not render an abstract idea eligible in Alice Corp. 573 U.S. at 223, 110 USPQ2d at 1983.
Regarding the above cited limitations in claims 1, 10, and 14 of (iii) acquiring a mass shift of a compound-spectrum match between the biological compound and a spectrum (claims 1 and 14); and (iv) storing user-defined post translational modifications and a mass shift of a compound spectrum match between the biological compound and a spectrum (claim 10). These limitations equate to insignificant, extra-solution activity of mere data gathering because these limitations gather data before or after the recited judicial exceptions of generating post-translational modification combinations using a search algorithm, matching mass shift and masses of the post-translational modification combinations, and using the mass data to detect post-translational modifications of the compound (see MPEP § 2106.04(d)).
Additionally, none of the recited dependent claims recite additional elements which would integrate the judicial exception into a practical application. Specifically, claims 4, 9, 13, and 20 recite extra solution activity of exporting data (see MPEP § 2106.05(g)); and claims 8, 13, and 19 further limit the data acquired in claims 1, 10, and 14. As such, claims 1-20 are directed to an abstract idea (Step 2A, Prong Two: NO).
Step 2B:
Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself (Step 2B). The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The instant independent claims recite the same additional elements described in Step 2A, Prong Two above.
Regarding the above cited limitations in claims 10 and 14 of (i) a memory and a processor (claim 10); and (ii) a computer readable medium with an executable instruction stored thereon (claim 14). These limitations equate to instructions to implement an abstract idea on a generic computing environment, which the courts have established does not provide an inventive concept (see MPEP § 2106.05(d) and MPEP § 2106.05(f)).
Regarding the above cited limitations in claims 1, 10, and 14 of (iii) acquiring a mass shift of a compound-spectrum match between the biological compound and a spectrum (claims 1 and 14); and (iv) storing user-defined post translational modifications and a mass shift of a compound spectrum match between the biological compound and a spectrum (claim 10). These limitations when viewed individually and in combination, are WURC limitations as taught by Schulze et al. (Enhancing Open Modification Searches via a Combined Approach Facilitated by Ursgal. J Proteome Res. 20(4): 1986-1996 (2021)). Schulze et al. discloses a comparison of three different open modification search (OMS) algorithms to map potential post-translational modifications (Abstract). Schulze et al. further discloses an example for complex glycopeptides, where in mass shifts were identified using the OMS approach in a subset of spectra. This subset of spectra showed a high level of peptide spectrum match agreement in the identified peptide sequences. Fixed modifications (i.e., user-defined) for the OMS include Carbamidomethylation of C (limitations (iii) and (iv)) (Pg. 1992, Col. 2, Para. 3 – Pg. 1993, Col. 1, Para. 1; and Pg. 1988, Col. 1, Para. 2).
These additional elements do not comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception. Therefore, the instant claims do not amount to significantly more than the judicial exception itself (Step 2B: NO). As such, claims 1-20 are not patent eligible.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
1. Claims 1-4, 7-11, 13-16 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Yu et al. (Identification of modified peptides using localization-aware open search. Nat Commun. 11: 4065 (9 pages) (2020); published 08/13/2020) in view of Schulze et al. (Enhancing Open Modification Searches via a Combined Approach Facilitated by Ursgal. J Proteome Res. 20(4): 1986-1996 (2021); published 01/29/2021).
Regarding claim 1, Yu et al. teaches a method for identification of peptides using a localization-aware open search method (expanding upon MSFragger, called MSFragger LOS), in which both modification-containing (shifted) and regular fragment ions are indexed and used in scoring. The localization-aware open search method identifies modified peptides with significantly higher sensitivity and accuracy (i.e., a method for automatic detection of post-translational modifications of a biological compound) (Abstract). Yu et al. further teaches the overview of the localization-aware open search strategy in Fig. 1 (Pg. 3, Fig. 1). Both shifted and regular ion indexes are generated from a sequence database. For each MS/MS spectrum, the original peaks are matched against the regular ion index to generate list 1. In the meantime, MSFragger matches the subtraction-processed peaks against the shifted ion index. If the top-scored candidate has a calculated mass significantly different from the spectrum’s precursor mass, matched peaks from the regular and shifted ion matching are combined, duplicate matches are removed, and modifications are localized using both the shifted and regular peaks to generate list 2. The top-scored peptide-spectrum matches (PSM) from list 2 is then compared with list 1, and the top-scoring hit is selected as the final hit (i.e., matching the mass shift and a mass of each of the post-translational modification combinations) (Pg. 3, Fig. 1). Yu et al. further teaches that the higher scoring one from the two top candidates (one from regular ion matching only, the other from both regular and shifted ion matching) are selected as the final hit. As part of the process, MSFragger also localizes the delta mass to the most probable location(s) within the identified peptide. It takes the location(s) with the highest score as the localized site(s). MSFragger reports the localization results, including a delta score between the best and the second-best localized residues, in a tab-delimited file (Pg. 7, Col. 2, Para. 4). Yu et al. further teaches the application of the method to large-scale HEK293 cell lysate data to demonstrate that the localization-aware open search can find more post-translational modifications (PTMs). Overall, MSFragger LOS finds more spams from almost all delta masses. PSMs with oxidation, methylation, formylation, water loss, and aminoethylbenzenesulfonylation increased by over 50%, while the increase in PSMs with phosphorylation was smaller due to its labile nature (and thus few fragments containing the modification) (i.e., automatically detecting the post-translational modifications of the biological compound based on the matching) (Pg. 5, Col. 2, Para. 2 – Pg. 6, Col. 1, Para. 2).
Regarding claim 2, Yu et al. teaches that in shifted ion indexing and matching, the accuracy of
p
t
-
p
i
(see Fig. 1a) is dependent on the precursor mass precision and the accuracy of peak matching is dependent on the fragment mass precision. However, some systematic mass deviation within MS and MS/MS spectra is often unavoidable and can diminish database search results. Thus, they developed a method (see “Methods”) to increase both precursor and fragment mass precision by correcting systematic mass deviation, which further increased the accuracy of matching shifted peaks. MSFragger first searches a given spectral file with a relatively small search space. Then, it picks the peptide-spectrum matches (PSMs) with expectation values smaller than 0.001 and divides them into two sets. The first set is used to build two calibration profiles (precursor mass and fragment mass) and the second set is used to evaluate the performance of the calibration. A calibration profile is a 2-D matrix of mass errors in the retention time and m/z dimensions. For each PSM in the first set, MSFragger calculates the precursor mass error and assigns it to the neighbors in the precursor mass calibration profile (Fig. 1c). After processing all PSMs in the first set, MSFragger corrects all PSMs’ precursor masses with the final calibration profile. It also calibrates fragment masses with a similar method (i.e., using a position obtained from the compound-spectrum match to validate the correctness of matched post-translational modification combinations) (Pg. 2, Col. 2, Para. 5 – Pg. 3, Col. 1, Para. 1; and Pg. 3, Fig. 1).
Regarding claim 3, Yu et al. teaches that MSFragger records the matched peaks from regular and shifted ion matching during the search. Then, it calculates hyperscores using the peaks from the regular ion matching only and picks the top-scoring candidate. If the mass difference between the precursor mass and the candidate’s calculated mass falls outside a predefined range (−1.5 to 3.5 Da by default), MSFragger calculates another list of hyperscores by combining the peaks from both regular and shifted ion matching. In this way, MSFragger tries all possible modified locations one-by-one by taking the regular ion matched peaks up to that location and shifted ion matched peaks from that location (i.e., wherein the post-translational modification combinations of the biological compound is detected by the following conditions: 1) a mass difference between the mass shift of the compound-spectrum match of each of the post-translational modification combinations is within a default value). Additionally, as part of the process, MSFragger also localizes the delta mass to the most probable location(s) within the identified peptide. It takes the location(s) with the highest score as the localized site(s) (i.e., wherein the post-translational modification combinations of the biological compound is detected by the following conditions: 2) locations of the post-translational modifications in the post-translational modification combinations are included in a sequence of the compound-spectrum match) (Pg. 7, Col. 2, Para. 4).
Regarding claim 4, Yu et al. teaches that MSFragger reports the localization results, including a delta score between the best and the second-best localized residues, in a tab-delimited file. This delta score can be used as a confidence measure of localization. These generated reports are categorized as post-processing (i.e., exporting matched post-translational modification combinations mapping to the compound spectrum match) (Pg. 7, Col. 2, Para. 4 and Pg. 6, Col. 2, Para. 2).
Regarding claim 7, Yu et al. teaches that the localization aware open search identifies modified peptides (i.e., wherein the biological compound is a protein) (Abstract). Yu et al. further teaches that the calibration/optimization is performed to select peptide-spectrum matches (i.e., wherein the compound-spectrum match is a peptide-spectrum match) (Pg. 2, Col. 2, Para. 5 – Pg. 3, Col. 1, Para. 1).
Regarding claim 8, Yu et al. teaches that they performed two open search analyses using HEK293 cell lysate data, one with MSFragger regular OS, and the other with MSFragger LOS (i.e., acquiring the compound-spectrum match and a mass thereof from an open search strategy) (Pg. 8, Col. 2, Para. 3).
Regarding claim 10, Yu et al. teaches that all tasks were run on a desktop workstation with an Intel Core i7-8700 (12 logical cores, 3.2 GHz) CPU and 32 GB memory (i.e., a system for automatic detection of post-translational modifications of a biological compound comprising a memory and a processor) (Pg. 8, Col. 2, Para. 4). Yu et al. further teaches the limitations of matching the mass shift and a mass of each of the post-translational modification combinations; and automatically detecting the post-translational modifications of the biological compound based on the matching as described for claim 1 above.
Regarding claim 11, Yu et al. teaches the limitations of wherein the processor is configured for using a position obtained from the compound-spectrum match to validate the correctness of matched post-translational modification combinations, and wherein the post-translational modification combinations of the biological compound is detected by the following conditions: 1) a mass difference between the mass shift of the compound-spectrum match and the mass of each of the post-translational modification combinations is within a default value, and 2) locations of post-translational modifications in the post-translational modification combinations are included in a sequence of the compound-spectrum match as described for claims 2 and 3 above.
Regarding claim 13, Yu et al. teaches the limitation of acquiring the compound-spectrum match and a mass thereof from an open search strategy as described for claim 8 above.
Regarding claim 14, Yu et al. teaches that all tasks were run on a desktop workstation with an Intel Core i7-8700 (12 logical cores, 3.2 GHz) CPU and 32 GB memory (i.e., a computer readable medium with an executable instruction stored thereon to perform the method for automatic detection of post-translational modifications of a biological compound) (Pg. 8, Col. 2, Para. 4). Yu et al. further teaches the limitations of matching the mass shift and a mass of each of the post-translational modification combinations; and automatically detecting the post-translational modifications of the biological compound based on the matching as described for claim 1 above.
Regarding claim 15, Yu et al. teaches the limitation of wherein the method further comprises using a position obtained from the compound-spectrum match to validate the correctness of matched post-translational modification combinations as described for claim 2 above.
Regarding claim 16, Yu et al. teaches the limitation of wherein the post-translational modification combinations of the biological compound is detected by the following conditions: 1) a mass difference between the mass shift of the compound-spectrum match and the mass of each of the post-translational modification combinations is within a default value, and 2) locations of post-translational modifications in the post-translational modification combinations are included in a sequence of the compound-spectrum match as described for claim 3 above.
Regarding claim 19, Yu et al. teaches the limitation of wherein the method further comprises acquiring the compound-spectrum match and a mass thereof from an open search strategy as described for claim 8 above.
Yu et al. does not teach acquiring a mass shift of a compound-spectrum match between the biological compound and a spectrum (claims 1 and 14); generating post-translational modification combinations and masses thereof by processing user-defined post-translational modifications using a search algorithm (claims 1, 10, and 14); exporting the post-translational modification combinations to a closed search strategy for identification and validation (claims 9, 13, and 20); and storing user-defined post-translational modifications and a mass shift of a compound-spectrum match between the biological compound and a spectrum (claim 10).
Regarding claim 1, Schulze et al. teaches a method of comparing and combining results from three different open modification search (OMS) engines. The platform (called Ursgal) allows for the combined downstream processing of search results, including the mapping to potential PTMs. The implementation facilitates the straightforward application of the OMS with unified parameters and results files, thereby enabling yet unmatched high throughput, large-scale data analysis (Abstract). Schulze et al. further teaches an example for complex glycopeptides, where in mass shifts were identified using the OMS approach in a subset of spectra. This subset of spectra showed a high level of peptide spectrum match agreement in the identified peptide sequences (i.e., acquiring a mass shift of a compound-spectrum match between the biological compound and a spectrum) (Pg. 1992, Col. 2, Para. 3 - Pg. 1993, Col. 1, Para. 1). Schulze et al. further teaches that the OMS engines MODa, PIPI, MSFragger, and TagGraph have been implemented as protein database search engines. The tools PTM-Shepherd and PTMiner have been included for the downstream processing of mass differences reported by OMS engines. Results from each tool are converted into a unified comma separated values file (CSV) format, in which each row contains a PSM, corresponding to a spectrum, and all properties of the PSM are listed in distinct columns (e.g., “Spectrum Title”, including the file name and spectrum ID; “Sequence”, referring to the peptide sequence; “Modifications”, PTMs given as PSI-MS terms together with their positions and separated by semicolons; “Protein ID”; engine scores, etc.). For the results of OMS engines, this format has been extended by a “Mass Difference” column, comprising the mass difference(s) reported by the engine in Daltons. PTMs assigned by downstream processing tools are included in the column “Mass Difference Annotations” (i.e., generating post-translational modification combinations and masses thereof by processing user-defined post-translational modifications using a search algorithm) (Pg. 1987, Col. 2, Para. 2-3).
Regarding claims 9, 13, and 20, Schulze et al. teaches a closed search (CS) method was compared to the results of the OMS approach. The CS approach increased the total number of identified peptides by 12%. Similar trends were observed for two additional datasets in the study (i.e., exporting the post-translational modification combinations to a closed search strategy for identification and validation) (Pg. 1992, Col. 1, Para. 2 – Col. 2, Para. 1).
Regarding claim 10, Schulze et al. teaches the limitations of acquiring a mass shift of a compound-spectrum match between the biological compound and a spectrum and the use of user-defined post-translational modifications as described for claim 1 above (i.e., storing user-defined post-translational modifications and a mass shift of a compound-spectrum match between the biological compound and a spectrum). Schulze et al. further teaches the limitation of generating post-translational modification combinations and masses thereof by processing user-defined post-translational modifications using a search algorithm as described for claim 1 above.
Regarding claim 14, Schulze et al. teaches the limitations of acquiring a mass shift of a compound-spectrum match between the biological compound and a spectrum and generating post-translational modification combinations and masses thereof by processing user-defined post-translational modifications using a search algorithm as described for claim 1 above.
Therefore, regarding claims 1-4, 7-11, 13-16 and 19-20, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of identifying post-translational modifications of peptides of Yu et al. with the data acquisition and search of Schulze et al. because the method of Schulze et al. integrates multiple open search algorithms through a unified, scriptable platform, providing the basis for a combined approach to increase the overall number of peptide identifications (Schulze et al, Pg. 1993, Col. 2, Para. 1). One of ordinary skill in the art would be able to combine the teachings of Yu et al. with Schulze et al. with reasonable expectation of success due to the same nature of the problem to be solved, since both are drawn towards utilizing an open search method to identify peptide post-translational modifications. Therefore, regarding claims 1-4, 7-11, 13-16 and 19-20, the instant invention is prima facie obvious (MPEP § 2142).
2. Claims 5-6, 12, and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over Yu et al. in view of Schulze et al. as applied to claims 1-4, 7-11, 13-16 and 19-20 above, and further in view of Kertesz-Farkas et al. (PTMTreeSearch: a novel two-stage tree-search algorithm with pruning rules for the identification of post-translational modification of proteins in MS/MS spectra. Bioinformatics 3-(2): 234-241 (2014); published 11/08/2013).
Yu et al. in view of Schulze et al., as applied to claims 1-4, 7-11, 13-16 and 19-20 above, does not teach wherein the search algorithm is a depth-first search algorithm (claims 5, 12, and 17); and wherein each of the user-defined post-translational modifications is a tree node of the depth-first search (claims 6, 12, and 18).
Regarding claims 5, 12, and 17, Kertesz-Farkas et al. teaches an algorithm that uses a large database of known PTMs to identify PTMs from MS/MS data, called PTMTreeSearch. For a given peptide sequence, PTMTreeSearch builds a computational tree wherein each path from the root to the leaves is labeled with the amino acids of a peptide sequence. Branches then represent PTMs (Abstract). Kertesz-Farkas et al. further teaches that the algorithm is a depth-first traversal algorithm, and that the modifications on the peptide can then be extracted from the path between the root and the best goal leaf (i.e., wherein the search algorithm is a depth-first search algorithm) (Pg. 236, Col. 1, Para. 4).
Regarding claims 6, 12, and 18, Kertesz-Farkas et al. teaches an example of a computational tree representation of the search space of the peptide MQLSQL in Fig. 1. The amino acid M can be oxidized, Q can carry 0.98 and 31.9898 modifications, and where the curly bracket shows the structure of a node. Each path from the root to the leaf represents a modified peptide and each branch represents an insertion of a modification to the peptide (Pg. 236, Fig. 1). Kertesz-Farkas et al. further teaches that the modifications in the database are user-defined (i.e., wherein each of the user-defined post-translational modifications is a tree node of the depth-first search) (Pg. 240, Col. 2, Para. 3).
Therefore, regarding claim 5-6, 12, and 17-18, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of identifying post-translational modifications of peptides of Yu et al. in view of Schulze et al. with the search algorithm of Kertesz-Farkas et al. because the search method of Kertesz-Farkas et al. provides a natural way to represent the search space for finding modifications, thereby avoiding redundant calculations. The tree pruning techniques provide more accurate modification identification at a reasonable time cost (Kertesz-Farkas et al., Pg. 240, Col. 2, Para. 2). One of ordinary skill in the art would be able to combine the teachings of Yu et al. in view of Schulze et al. with Kertesz-Farkas et al. with reasonable expectation of success due to the same nature of the problem to be solved, since both are drawn towards utilizing as search method to identify peptide post-translational modifications. Therefore, regarding claims 5-6, 12, and 17-18, the instant invention is prima facie obvious (MPEP § 2142).
Conclusion
No claims allowed.
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/D.P.S./Examiner, Art Unit 1687
/Lori A. Clow/Primary Examiner, Art Unit 1687
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