EP4666286A1

EP4666286A1 - Method for compound structure determination from orthogonal ms/ms data

Info

Publication number: EP4666286A1
Application number: EP24705247.5A
Authority: EP
Inventors: Eva DUCHOSLAV; Harini KALUARACHCHI; Disha Atulbhai THAKKAR
Original assignee: DH Technologies Development Pte Ltd
Current assignee: DH Technologies Development Pte Ltd
Priority date: 2023-02-13
Filing date: 2024-02-09
Publication date: 2025-12-24
Also published as: WO2024171013A1

Abstract

Computer-implemented methods and non-transitory computer readable storage media for determining compound structures from two or more MS/MS data sets obtained using orthogonal fragmentation, where the two or more MS/MS data sets may be processed, aligned, and consolidated to determine a lead candidate structure.

Description

METHOD FOR COMPOUND STRUCTURE DETERMINATION FROM ORTHOGONAL MS/MS DATA

RELATED APPLICATIONS

[0001] The present patent application claims the priority benefit of U.S. Provisional Patent Application Ser. No. 63/484,596, filed February 13, 2023, the content of which is hereby incorporated by reference in its entirety into this disclosure.

BACKGROUND

[0002] Mass spectrometry (MS) is an analytical technique used for the detection and quantitation of chemical compounds. MS involves ionizing compounds and analyzing the mass-to-charge (m/z) ratios of the ions with a detector. For singly charged species, the terms “mass” and “m/z” may be used interchangeably. One of ordinary skill in the art understands that a mass can be found from an m/z by multiplying the m/z by the absolute value of the charge. Similarly, the m/z can be found from a mass by dividing the mass by the charge.

[0003] An MS scan includes the selection of a precursor ion or precursor ion range and subsequent mass analysis of the precursor ion or ion range. In some cases, tandem mass spectrometry (also known as MS/MS) can be employed to aid in the structure elucidation of certain peaks from the MS scan. Tandem mass spectrometry or MS/MS involves the ionization of one or more compounds of interest from a sample, selection of one or more precursor ions of the one or more compounds, fragmentation of the one or more precursor ions into product ions, and mass analysis of the product ions. Through this fragmentation and subsequent mass analysis, chemists are able to utilize MS/MS to aid in compound structure determination. Further, both MS and MS/MS data may be collected in both polarity modes on the mass spectrometer (i.e., positive and negative). [0004] Various types of fragmentation techniques (also referred to as dissociation techniques) can be employed in MS/MS experiments. Collision-induced dissociation (CID), electron-based dissociation (ExD), ultraviolet photodissociation (UVPD), and infrared multiphoton photodissociation (IRMPD) are some examples of common fragmentation techniques. CID is the most conventional technique and involves fragmentation through a collision between gas molecules and the sample molecules. ExD can include, but is not limited to, electron-induced dissociation (EID), electron impact excitation in organics (EIEIO), electron capture dissociation (ECD), and electron transfer dissociation (ETD).

[0005] MS/MS fragmentation techniques can generally be grouped into two categories. CID, in-source fragmentation, and IRMPD are examples of thermal dissociation methods. Thermal dissociation methods are non-radical dissociation methods that typically generate heterolytic fragments. The other general category is radical-induced dissociation methods that often generate homolytic fragments. These methods may include, but are not limited to, ExD and UVPD.

[0006] Thus, there are numerous fragmentation techniques that can be utilized to aid in chemical structure determination with MS/MS. As such, there is a need for automated techniques that aid in analyzing and combining this data.

SUMMARY

[0007] In various aspects, a computer-implemented method includes aligning two or more MS/MS data sets of a compound, the two or more MS/MS data sets comprising spectra with mass-to-charge ratio (m/z) peaks, to generate an aligned MS/MS dataset, wherein the aligned MS/MS dataset reconciles peaks in each of the MS/MS data sets that correspond to the same m/z based on the m/z tolerance consistent with the achievable m/z measurement precision. The method further includes generating an aligned annotated MS/MS data set, comprising annotating each fragment peak in the aligned MS/MS data set with elemental compositions and, respectively, candidate fragment structures that correspond to the m/z of fragment peak in the aligned MS/MS data set, wherein each candidate molecule structure is given an aligned MS/MS data set confidence score; and ranking the candidate molecule structures to determine a lead candidate structure. In certain aspects, the two or more MS/MS data sets are collected using orthogonal fragmentation techniques. The orthogonal fragmentation techniques may include collision induced dissociation (CID), electron-based dissociation (ExD), infrared multi-photon photodissociation (IRMPD), and ultraviolet photofragmentation (UVPD).

[0008] In certain aspects, the compound is a degradant of a known compound. In other aspects, the compound is a metabolite of a known compound. In other aspects, the compound is an unknown compound.

[0009] In certain aspects, the list of candidate structures is generated in-silico. In other aspects, the list of candidate structures is retrieved from a compound repository.

[0010] In certain aspects, the computer-implemented method further comprises providing qualitative feedback regarding purities of the two or more MS/MS data sets.

[0011] In other aspects, a computer-implemented method includes processing, with one or more computing devices, two or more MS/MS data sets of a compound against a list of candidate structures, the two or more MS/MS data sets comprising spectra with mass-to-charge ratio (m/z) peaks, wherein the processing further comprises generating two or more annotated MS/MS data sets, comprising annotating each fragment peak in each MS/MS data set with elemental compositions and, respectively, candidate fragments structures that correspond to the m/z of each fragment peak , wherein each candidate molecule structure is given an MS/MS data set confidence score. The method further includes aligning the two or more MS/MS data sets to generate an aligned annotated MS/MS dataset, wherein the aligned annotated MS/MS dataset reconciles the candidate fragment structures from each of the MS/MS datasets that correspond to the same m/z. The method further includes consolidating the candidate molecule structure confidence scores from the two or more MS/MS data sets to generate consolidated candidate structure confidence scores; and ranking the candidate molecule structures to determine a lead consolidated candidate structure. In certain aspects, the two or more MS/MS data sets are collected using orthogonal fragmentation techniques. The orthogonal fragmentation techniques may include collision induced dissociation (CID), electron-based dissociation (ExD), infrared multi-photon photodissociation (IRMPD), and ultraviolet photofragmentation (UVPD).

[0012] In certain aspects, the compound is a degradant of a known compound. In other aspects, the compound is a metabolite of a known compound. In other aspects, the compound is an unknown compound.

[0013] In certain aspects, the processing of each of the two or more MS/MS data sets further comprises ranking the candidate structures in order of each candidate structure’s confidence score.

[0014] In certain aspects, the aligned annotated MS/MS data set reconciles candidate structures from the two or more MS/MS data sets that correspond to the same m/z within a tolerance consistent with the achievable m/z measurement precision.

[0015] In certain aspects, the list of candidate structures is generated in-silico. In other aspects, the list of candidate structures is retrieved from a compound repository.

[0016] In certain aspects, the processing of each of the two or more MS/MS data sets further comprises grouping candidate structures based on structural similarity. In further aspects, the processing further comprises ranking the candidate structures in each group in order of the confidence score of each candidate structure. In further aspects, the processing further comprises, after generating two or more annotated MS/MS data sets, determining the total ion current (TIC) and the portion of the ion current used to generate each of the two or more annotated MS/MS data sets. [0017] In certain aspects, the consolidated candidate structure confidence score of the lead consolidated candidate structure is compared to the other consolidated candidate structure scores using a t-test and reported as a confidence measure.

[0018] In certain aspects, the computer-implemented method further comprises providing qualitative feedback regarding purity of the two or more MS/MS data sets.

[0019] In certain aspects, computer-implemented method further comprises, prior to processing the two or more MS/MS data sets, processing, with one or more computing devices, two or more reference MS/MS data sets of a reference compound against a list of reference structures and annotating the two or more reference MS/MS data sets with the reference structures, and aligning the two or more reference MS/MS data sets to generate an aligned annotated reference data set. The two or more reference MS/MS data sets may be collected using orthogonal fragmentation techniques. The orthogonal fragmentation techniques are selected from collision induced dissociation (CID), electron-based dissociation (ExD), infrared multi-photon photodissociation, and ultraviolet photofragmentation (UVPD). In certain aspects, the candidate structure confidence scores for each candidate structure from the two or more MS/MS data sets are generated from comparison to the reference spectra.

[0020] In certain aspects, the consolidated candidate structure confidence scores are generated according to S = c, Si (1 < i < n), wherein i is an index of the MS/MS data set, a is the contribution of the z^th MS/MS data set confidence score to the consolidated MS/MS data set confidence score, and Si is the MS/MS data set confidence score; and wherein = 1 (1 < i < n). In some aspects, a is generated based on the ion current used for annotating the two or more MS/MS data sets.

[0021] In certain aspects, the two or more MS/MS data sets comprises a first MS/MS data set and a second MS/MS data set. In further aspects, the first MS/MS data set is collected using CID and wherein the second MS/MS data set is collected using EAD. [0022] In certain aspects, the candidate structure confidence scores for each candidate structure from the two or more MS/MS data sets are based on the fragment elemental elemental compositions, and, respectively, fragment positions in the candidate molecule structure. In further aspects, the consolidated candidate structure confidence scores are generated by normalizing the confidence scores from the two or more MS/MS data sets such that the maximum confidence score of each of the two or more MS/MS data sets correspond to their target contributions (c,) to the consolidated candidate structure confidence score.

[0023] In other aspects, one or more non-transitory computer-readable storage media comprise instructions, which when executed by one or more computing devices, cause the one or more computing devices to align two or more MS/MS data sets of a compound analog, the two or more MS/MS data sets comprising spectra with mass-to-charge ratio (m/z) peaks, to generate an aligned MS/MS dataset, wherein the aligned MS/MS dataset reconciles peaks in each of the MS/MS data sets that correspond to the same m/z. Execution of the instructions may further cause the one or more computing devices to generate an aligned annotated MS/MS data set, comprising annotating each fragment peak in the aligned MS/MS data set with candidate structures that correspond to the m/z of each fragment peak in the aligned MS/MS data set, wherein each candidate structure is given an aligned MS/MS data set confidence score and rank the structures to determine a lead candidate structure.

[0024] In other aspects, one or more non-transitory computer-readable storage media comprise instructions, which when executed by one or more computing devices, cause the one or more computing devices to process, with one or more computing devices, two or more MS/MS data sets of a compound analog against a list of candidate structures, the two or more MS/MS data sets comprising spectra with mass-to-charge ratio (m/z) peaks, wherein the processing further comprises generating two or more annotated MS/MS data sets, comprising annotating each fragment peak in each MS/MS data set with candidate structures that correspond to the m/z of each fragment peak, wherein each candidate structure is given an MS/MS data set confidence score. Execution of the instructions may further cause the one or more computing devices to align the two or more MS/MS data sets to generate an aligned annotated MS/MS dataset, wherein the aligned annotated MS/MS dataset reconciles the candidate structures from each of the MS/MS datasets that correspond to the same m/z. Execution of the instructions may further cause the one or more computing devices to consolidate the candidate structure confidence scores from the two or more MS/MS data sets to generate consolidated candidate structure confidence scores, rank the candidate structures to determine a lead consolidated candidate structure, and display a visual representation of the data.

[0025] The various aspects and aspects of the present disclosure include systems, methods, devices, components, and/or software for implementing the various functions and processes described herein.

DESCRIPTION OF DRAWINGS

[0026] Various aspects and embodiments of the present disclosure are shown in the drawings and described therein and elsewhere throughout the disclosure. In the drawings, like references indicate like parts.

[0027] FIG. 1 is a schematic diagram of a mass spectrometer system, in accordance with an example embodiment of the disclosure.

[0028] FIG. 2 is a block diagram that illustrates a computer system, upon which aspects of the present teachings may be implemented.

[0029] FIG. 3 is a flowchart of an analytical process which may be implemented by the mass spectrometer system of FIG. 1.

[0030] FIG. 4 is a flowchart of an analytical process which may be implemented by the mass spectrometer system of FIG. 1. [0031] FIG. 5 is an example MS/MS data set which may be analyzed by the analytical processes of FIG. 3 and FIG. 4.

DETAILED DESCRIPTION

[0032] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the methods described herein belong.

[0033] As utilized herein the terms “circuits” and “circuitry” refer to physical electronic components (e.g., hardware), and any software and/or firmware (“code”) that may configure the hardware, be executed by the hardware, and/or otherwise be associated with the hardware. As used herein, for example, a particular processor and memory (e.g. , a volatile or non-volatile memory device, a general computer-readable medium, etc.) may comprise a first “circuit” when executing a first one or more lines of code and may comprise a second “circuit” when executing a second one or more lines of code. Additionally, a circuit may comprise analog and/or digital circuitry. Such circuitry, for example, may operate on analog and/or digital signals. It should be understood that a circuit may be in a single device or chip, on a single motherboard, in a single chassis, in a plurality of enclosures at a single geographical location, in a plurality of enclosures distributed over a plurality of geographical locations, etc. Similarly, the term “module”, for example, may refer to a physical electronic components (e.g. , hardware) and any software and/or firmware (“code”) that may configure the hardware, be executed by the hardware, and or otherwise be associated with the hardware.

[0034] As utilized herein, circuitry or module is “operable” to perform a function whenever the circuitry or module comprises the necessary hardware and code (if any is necessary) to perform the function, regardless of whether the performance of the function is disabled or not enabled (e.g., by a user-configurable setting, factory trim, etc.). [0035] As utilized herein, “and/or” means any one or more of the items in the list joined by “and/or”. As an example, “x and/or y” means any element of the three-element set { (x), (y), (x, y) } . In other words, “x and/or y” means “one or both of x and y.” As another example, “x, y, and/or z” means any element of the seven-element set { (x), (y), (z), (x, y), (x, z), (y, z), (x, y, z) } . In other words, “x, y and/or z” means “one or more of x, y, and z.”

[0036] As utilized herein, the term “exemplary” means serving as a non-limiting example, instance, or illustration. Further, as utilized herein, the terms “for example” and “e.g.,” set off lists of one or more non-limiting examples, instances, or illustrations.

[0037] The terminology used herein is for the purpose of describing particular examples only and is not intended to be limiting of the disclosure. As used herein, the singular forms are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,” “includes,” “comprising,” “including,” “has,” “have,” “having,” and the like when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

[0038] It will be understood that, although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. Thus, for example, a first element, a first component or a first section discussed below could be termed a second element, a second component or a second section without departing from the teachings of the present disclosure. Similarly, various spatial terms, such as “upper,” “lower,” “side,” and the like, may be used in distinguishing one element from another element in a relative manner. It should be understood, however, that components may be oriented in different manners, for example a semiconductor device may be turned sideways so that its “top” surface is facing horizontally and its “side” surface is facing vertically, without departing from the teachings of the present disclosure.

[0039] FIG. 1 is a non-limiting example of a mass analysis system 100. As shown, the mass analysis system 100 includes a mass spectrometer 110. The mass spectrometer 110 may separate and detect ions of interest from a given sample. The one or more computing devices 170 may be operative to control the operation of the mass spectrometer 110, receive spectral data generated by the mass spectrometer, and manage the spectral data received from the mass spectrometer 110. Typically, the mass spectrometer 110 may format a detected ion signal generated by the ion detector 150 in spectral data representative of one or more mass spectra. The one or more computing devices 170 may receive the spectral data from the mass spectrometer 110 and analyze the spectral data to produce one or more data reports, graphs, etc.

[0040] A mass analyzer 140 may receive the generated ions from the ion source 120 for mass analysis. The mass analyzer 140 may be operative to selectively separate ions of interest from generated ions received from the ion source 120 and to deliver the ions of interest to an ion detector 150 that generates a mass spectrometer signal indicative of detected ions to the one or more computing devices 170. In some aspects, the separate ions of interest may be indicated in an analysis instruction associated with that sample.

[0041] When conducting MS analysis, the mass analyzer 140 may receive the generated ions directly from the ion source. When conducting tandem mass spectrometry analysis (also referred to as MS/MS), the ions generated from the ion source 120 are subjected to fragmentation in a fragmentation cell 130 prior to being received by the mass analyzer 140. The fragmentation cell 130 may be configured to conduct certain fragmentation (also referred to as dissociation) techniques or methodologies. For example, the fragmentation cell 130 may be configured to conduct thermal dissociation methodologies. Thermal dissociation methodologies may include, but are not limited to, collision-induced-dissociation (CID) and infrared multi-photon photodissociation (IRMPD). In other non — limiting aspects, the fragmentation cell may be configured to conduct radical-induced dissociation methodologies, such as electron-based dissociation (ExD) and ultraviolet photodissociation (UVPD). ExD may include, but is not limited to electron-induced dissociation (EID), electron impact excitation in organics (EIEIO), electron capture dissociation (ECD), and electron transfer dissociation (ETD).

[0042] As shown, the mass spectrometer 110 may be coupled to one or more computing devices 170. The one or more computing devices 170 may control operation of the mass spectrometer 110, receive spectral data from the mass spectrometer 110, analyze the spectral data, and present results of such analysis of the spectral data.

[0043] The one or more computing devices 170 may comprise a single computing device or may comprise a plurality of distributed computing devices in operative communication with the mass spectrometer 110 and/or another. FIG. 2 illustrates a high-level block diagram of an example computing device 200 which may implement one or more of the computing devices 170. To this end, the computing device 200 may comprise a bus 202, a processor 204, volatile memory 206, non-volatile storage 208, storage device 210, and a mass spectrometer interface 211. The bus 202 may comprise various signal lines, interfaces, etc., that operatively interconnect components of the computing device 200 such as processor 204, volatile memory 206, non-volatile storage 208, storage device 210, and mass spectrometer interface 211 to permit transfers of information and/or control signals between such components of the computing device 200.

[0044] The processor 204 may include a plurality of processing elements or cores, which may be packaged as a single processor or in a distributed arrangement. Furthermore, in some aspects, a plurality of virtual processing elements may be provided to provide the control or management operations for the computing device 200.

[0045] The memory 206 may include random access memory (RAM) and/or other dynamic storage devices coupled to bus 202. The memory 206 may store instructions executed by processor 204. The memory 206 may also store temporary variables, intermediate information, and/or other data resulting from the execution of the instructions by processor 204. The nonvolatile memory 208 may include read-only-memory (ROM) 208 devices, flash memory devices, and/or other non-volatile memory coupled to bus 202. The non-volatile memory 208 may store static information and instructions for processor 204. The storage device 210 may include one or more magnetic disk drives, optical disk drives, solid-state disk drives, and/or other mass storage devices coupled to bus 202. The storage device 210 may store information and/or instructions in a persistent manner for processor 204.

[0046] The processor 204 may be coupled via bus 202 to the mass spectrometer interface 211. The mass spectrometer interface 211 may operatively couple the computing device 200 and processor 204 to the mass spectrometer 110 and its components. To this end, the mass spectrometer interface 211 may include various I/O and/or networking interfaces. For example, the mass spectrometer interface 211 may include I/O interfaces such as Universal Serial Bus (USB) interfaces, Peripheral Component Interconnect (PCI) interfaces, PCI Express interfaces, Serial Peripheral Interface (SPI) interfaces, FireWire interfaces, etc. Alternatively or additionally, the mass spectrometer interface 211 may include one or more networking interfaces such as Ethernet interfaces, Wi-Fi interfaces, and Bluetooth interfaces.

[0047] The processor 204 may be further coupled via bus 202 to a display 212, such as a light emitting diode (LED) or liquid crystal display (LCD). The processor 204 may use the display 212 to present information to a computer user. An input device 214, including alphanumeric and other keys, may be coupled to bus 202. A computer user may utilize the input device to communicate information and command selections to processor 204. The computing device 200 may further include a cursor control 216 coupled to the bus 202. The cursor control 216 may comprise a mouse, a trackball, cursor direction keys, etc., which permit a computer user to select graphical elements or other aspects presented via the display 212. In some aspects, the cursor control 216 may control the movement of a cursor on display 212 used to select such graphical elements or other aspects presented via the display 212. The cursor control 216 typically has two degrees of freedom in two axes, a first axis (e.g., a horizontal axis or x-axis) and a second axis (e.g., a vertical axis or y-axis), that permits the cursor control 216 to move a cursor across a plane of the display 212 and select an x-y position in the plane.

[0048] Consistent with certain implementations of the present disclosure, the computing device 200 may operate based on processor 204 executing instructions stored in memory 206. Such instructions may be read into memory 206 from another computer-readable medium, such as storage device 210. Execution of the instructions stored in memory 206 may cause processor 204 to perform various processes described herein. Alternatively, hard-wired circuitry may be used in place of or in combination with software instructions to implement various processes described herein. Thus, implementations of the present disclosure may utilize hardware circuitry and/or software to perform the various processes described herein.

[0049] In various aspects, the computing device 200 may be connected to one or more other computing devices across a network to form a networked system. Such other computing devices may be implemented in a manner similar to computing device 200. The network may comprise a private network or a public network such as the Internet. In the networked system, one or more computing devices may store and serve the data to other computing devices. The one or more computing devices 200 that store and serve the data may be referred to as servers, data servers, and/or a data cloud in various cloud-computing scenarios. In some aspects, the one or more computing devices 200 may include one or more web servers that provide other computing devices with web interfaces, web APIs, and/or other access to data and other resources of the one or more computing device. Such computing devices that send and receive data to and from the servers, data servers, and/or the data cloud, regardless of whether via such web servers or web APIs may be referred to as client devices and/or cloud devices.

[0050] The term “computer-readable medium” as used herein refers to any media that participates in providing instructions to processor 204 for execution. Such a medium may take many forms, including transitory media (e.g., transmission media) and non-transitory media (e.g., non-volatile media and volatile media). Transmission media may include, for example, coaxial cables, copper wire, fiber optics, the wires that comprise bus 202, and wireless transmissions. Non-volatile media may include, for example, non-volatile storage devices such as those of the non-volatile memory 208 and/or the storage device 210. Similarly, the volatile media may include, for example, volatile storage devices such as those of the volatile memory 206.

[0051] Common forms of computer-readable media or computer program products include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, or any other magnetic medium, a CD-ROM, digital video disc (DVD), a Blu-ray Disc, any other optical medium, a thumb drive, a memory card, a RAM, PROM, and EPROM, a FLASH-EPROM, any other memory chip or cartridge, or any other tangible medium from which a computer may read.

[0052] Various forms of computer-readable media may be involved in carrying one or more sequences of one or more instructions to processor 204 for execution. For example, the instructions may initially be carried on the magnetic disk of a remote computer. The remote computer may load the instructions into its dynamic memory and send the instructions over a communications link. A modem or other network interface local to the computing device 200 may receive the instructions and transfer the received instructions to memory 206 and/or processor 204 via bus 202. The instructions received by memory 206 may optionally be stored in or on storage device 210 either before or after execution by processor 204.

[0053] Referring now to FIG. 3, a flowchart depicts an embodiment of an analytical process 300 which may be implemented by the mass analysis system 100. As described above, the mass spectrometer 110 may be coupled to one or more computing devices 170, which may receive spectral data from the mass spectrometer 110, analyze the spectral data, and present results of such analysis of the spectral data. At 310, the one or more computing devices 170 may align two or more MS/MS data sets of a compound collected with mass spectrometer 110 to generate an aligned MS/MS data set. The two or more MS/MS data sets comprise spectra with mass-to- charge ratio (m/z) peaks. The aligned MS/MS data set will reconcile m/z peaks in each of the two or more MS/MS data sets that correspond to the same m/z. When reconciling the m/z peaks, the tolerance employed will be chosen such that it is consistent with the achievable m/z measurement precision of the mass spectrometer 110. For example, in some non-limiting aspects, the aligned MS/MS data set reconciles m/z peaks from the two or more MS/MS data sets that correspond to the same m/z within a tolerance of 2 mDa. In other non-limiting aspects, the tolerance will be adjusted depending on the achievable m/z precision of the mass spectrometer 110.

[0054] Referring to FIG. 5, an example MS/MS data set 500 is shown. Two MS/MS spectra are shown in FIG. 5, including an MS/MS spectrum collected using ExD 510 with m/z peaks pointing upwards and an MS/MS data set collected using CID 520 with m/z peaks pointing downward. Each MS/MS data set includes a number of peaks corresponding to a particular m/z. In some instances, the same peak is present in both MS/MS data sets, such as peaks 530, 540, and 550. In other instances, a peak is only present in one of the MS/MS data sets, such as peaks 560 and 570, which are only present in the ExD data set 510. As described above, the aligned MS/MS data set will reconcile m/z peaks in each of the two or more MS/MS data sets that correspond to the same m/z (e.g., peaks 530, 540, and 550).

[0055] Referring to FIG. 3, at 320, the one or more computing devices 170 may generate an aligned annotated MS/MS data set 320. To this end, the one or more computing devices 170 may annotate each fragment peak in the aligned MS/MS data set with elemental compositions and candidate fragment structures that correspond to the m/z of each fragment peak in the aligned MS/MS data set. The one or computing devices 170 may further assign each candidate molecule an aligned MS/MS data set confidence score. In certain aspects, the candidate fragment structures are generated in-silico. In other aspects, the candidate structures are retrieved from a compound repository. The compound repository may be a private or public compound structure source.

[0056] At 330, the one or more computing devices 170 may rank each of the candidate molecule structures from the aligned annotated MS/MS data set to, at 340, determine a lead candidate molecule structure.

[0057] In some aspects, the two or more MS/MS data sets aligned at 310 may be collected using orthogonal fragmentation techniques. Orthogonal fragmentation techniques are MS/MS methodologies that fragment molecules in the fragmentation cell 130 through different mechanisms. For example, the orthogonal fragmentation techniques may be selected from various thermal dissociation methodologies and radical-induced dissociation methodologies. Thermal dissociation methodologies may include, but are not limited to, collision-induced- dissociation (CID) and infrared multi-photon photodissociation (IRMPD). In other nonlimiting aspects, the fragmentation cell 130 may be configured to conduct radical-induced dissociation methodologies, such as electron-based dissociation (ExD) and ultraviolet photodissociation (UVPD). ExD may include, but is not limited to electron-induced dissociation (EID), electron impact excitation in organics (EIEIO), electron capture dissociation (ECD), and electron transfer dissociation (ETD).

[0058] In certain aspects, the compound analyzed by analytical process 300 may be a degradant of a known compound. In other aspects, the compound may be a metabolite of a known compound. In yet other aspects, the compound may be an unknown compound.

[0059] In certain aspects, the one or more computing devices 170 may further provide qualitative feedback regarding the purities of the two or more MS/MS data sets. For example, in certain aspects, the generation of an aligned annotated MS/MS data set 320 may further comprise determining the total ion current (TIC) and the portion of the ion current used to generate the two or more annotated MS/MS data sets.

[0060] Referring now to FIG. 4, a flowchart depicts an embodiment of an analytical process 400 which may be implemented by the mass analysis system 100. As described above, the mass spectrometer 110 may be coupled to one or more computing devices 170, which may receive spectral data from the mass spectrometer 110, analyze the spectral data, and present results of such analysis of the spectral data. At 410, the one or more computing devices 170 may process two or more MS/MS data sets of a compound collected with mass spectrometer 110 against a list of candidate structures. The two or more MS/MS data sets comprise spectra with m/z peaks. In certain aspects, the candidate fragment structures are generated in-silico. In other aspects, the candidate structures are retrieved from a compound repository. The compound repository may be a private or public compound structure source. In some aspects, the processing 410 may further comprise grouping the candidate structures based on certain characteristics. For example, the candidate structures may be grouped based on structural similarity. In some aspects, the processing 410 may further comprise ranking the candidate structures in each group in order of the confidence score of each candidate structure. [0061] The processing 410 may further comprise generating two or more annotated MS/MS data sets, comprising annotating each fragment peak in each MS/MS data set with elemental compositions and, respectively, candidate fragment structures that correspond to the m/z of each fragment peak. The processing 410 may further comprise giving each candidate molecule structure an MS/MS data set confidence score. In certain aspects, the processing 410 may further comprise ranking the candidate structures in order of each candidate structure’s confidence score.

[0062] At 420, the one or more computing devices 170 may align the two or more annotated MS/MS data sets to generate an aligned annotated MS/MS data set. The aligned annotated MS/MS data set generated at 420 will reconcile the candidate fragment structures from each of the MS/MS data sets that correspond to the same m/z (see, e.g., FIG. 5 as discussed above). When reconciling the m/z peaks, the tolerance employed will be chosen such that it is consistent with the achievable m/z measurement precision of the mass spectrometer 110. For example, in some non-limiting aspects, the aligned MS/MS data set reconciles m/z peaks from the two or more MS/MS data sets that correspond to the same m/z within a tolerance of 2 mDa. In other non-limiting aspects, the tolerance will be adjusted depending on the achievable m/z precision of the mass spectrometer 110.

[0063] At 430, the one or more computing devices 170 may consolidate the candidate molecule confidence scores to generate consolidated candidate structure confidence scores. As discussed below, in some aspects a reference compound may be available. For example, a reference compound may be a compound that is analogous to the compound being analyzed by analytical process 300 or 400 (i.e., the analyte). In certain non-limiting aspects, a reference compound may be available when the analyte is a metabolite or a degradant of a known compound. As discussed below, analysis of such a reference compound, when available, may be incorporated into the analytical processes described herein. In other aspects, the analyte may be an unknown compound and a reference compound may not be available. As discussed below, such an unknown compound may be analyzed with the analytical processes described herein utilizing in-silico fragmentation tools.

[0064] At 440, the one or more computing devices 170 may rank each of the candidate molecule structures based on the consolidated candidate structure confidence scores to, at 450, determine a lead consolidated candidate structure.

[0065] In some aspects, the two or more MS/MS data sets aligned at 410 may be collected using orthogonal fragmentation techniques. As discussed above, orthogonal fragmentation techniques are MS/MS methodologies which fragment molecules in the fragmentation cell 130 through different mechanisms. For example, the orthogonal fragmentation techniques may be selected from various thermal dissociation methodologies and radical-induced dissociation methodologies. Thermal dissociation methodologies may include, but are not limited to, CID and IRMPD. In other non-limiting aspects, the fragmentation cell 130 may be configured to conduct radical-induced dissociation methodologies, such as ExD and UVPD. ExD may include, but is not limited to EID, EIEIO, ECD, and ETD.

[0066] In some aspects, the one or more computing devices 170 may further provide qualitative feedback regarding the purity of the two or more MS/MS data sets. For example, in certain aspects, the processing 410 may further comprise, after generating two or more annotated MS/MS data sets, determining the total ion current (TIC) and the portion of the ion current used to generate each of the two or more annotated MS/MS data sets.

[0067] In some aspects, the one or more computing devices 170 may further conduct statistical analyses. For example, the consolidated candidate structure confidence scores generated at 430 may be subjected to such statistical analyses. In some aspects, the one or more computing devices 170 may compare the consolidated candidate structure confidence score of the lead consolidated candidate structure to the other consolidated candidate structure scores using a t-test. The results of the t-test may be reported as a confidence measure.

Reference Compound Analysis

[0068] As discussed above, in some aspects the compound analyzed by analytical process 300 or analytical process 400 may be related to a known compound. For example, the compound may be a degradant or a metabolite of a known compound. In some aspects, the analytical processes 300 or 400 may incorporate analysis of a reference standard of a known compound. For example, utilization of a known reference compound to determine candidate structures may be conducted as described in U.S. Patent No. 10,825,669.

[0069] For example, referring to FIG. 4, prior to processing the two or more MS/MS data sets against a list of candidate structures 410, the one or more computing devices 170 may process two or more reference MS/MS data sets of a reference standard collected with mass spectrometer 110 against a list of reference structures. The processing of the reference standard may further comprise annotating the two or more reference MS/MS data sets with the reference structures. Following processing of the two or more reference MS/MS data sets, the two or more reference MS/MS data sets may be aligned to generate an aligned annotated reference data set. The two or more reference MS/MS data sets comprise spectra with m/z peaks.

[0070] The two or more reference MS/MS data sets may be collected using orthogonal fragmentation techniques. For example, the orthogonal fragmentation techniques of the two or more reference MS/MS data sets may be the same as the two or more MS/MS data sets aligned at 310 or 420. To that end, in some aspects the orthogonal fragmentation techniques may be selected CID, IRMPD, ExD, or UVPD. ExD may include, but is not limited to EID, EIEIO, ECD, and ETD.

[0071] In some aspects, the one or more computing devices 170 may utilize the two or more reference MS/MS data sets to generate candidate structure confidence scores as a part of the analytical process 300 at 320 or as a part of the analytical process 400 at 410. To this end, the one or more computing devices 170 may generate candidate structure confidence scores for each candidate structure from the two or more MS/MS data sets through a comparison of the two or more MS/MS data sets to the two or more reference MS/MS data sets (i.e., reference spectra).

[0072] In some aspects, the consolidated candidate molecule confidence scores 430 may be generated by establishing a relative contribution of each MS/MS data set to the final ranking. For example, the consolidated candidate molecule confidence scores may be generated according to the following formula:

[0073] According to the above formula, i is an index of the MS/MS data set, a is the contribution of the I^th MS/MS data set confidence score to the consolidated MS/MS data set confidence score, and st is the MS/MS data set confidence score. Further, = 1 (1 < i < n). In some aspects, a is generated based on the ion current used for annotating the two or more MS/MS data sets. The ion current used for annotating the two or more MS/MS data sets may be based on the purity of each of the MS/MS data sets and the signal to noise ratio of fragments in each of the MS/MS data sets.

Unknown Compound Analysis

[0074] As discussed above, in some aspects the compound analyzed by analytical process 300 or analytical process 400 may be an unknown compound where a reference compound is not available. In such aspects, in silico fragmentation tools, for example as described in Analytical and Bioanalytical Chemistry (2018) 410:1873-1884, may be incorporated into the method.

[0075] For example, referring to FIG. 4, and as discussed above, the processing 410 comprises annotating each fragment peak in each MS/MS data set with elemental compositions and, respectively, candidate fragment structures that correspond to the m/z of each fragment peak. The processing 410 may further comprise annotating each fragment peak in each MS/MS data set with elemental compositions and, respectively, candidate fragment structures that correspond to the m/z of each fragment peak. Each candidate fragment structure may then be given a candidate molecule (or fragment) structure MS/MS data set confidence score. In some aspects, the MS/MS data set confidence scores generated at 410 for each candidate structure from the two or more MS/MS data sets are based on the fragment elemental compositions, and, respectively, fragment positions in the candidate molecule structures. For example, such an analysis may be employed when the compound analyzed by analytical process 300 or analytical process 400 is an unknown compound where a reference sample is not available. In such situations, the elemental compositions may be determined through a standard MS analysis conducted prior to MS/MS analysis.

[0076] While the present disclosure has described certain aspects, various changes may be made and equivalents may be substituted without departing from the scope of the present invention. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the present disclosure without departing from the scope of the appended claims. Therefore, the present disclosure is not limited to the particular embodiment disclosed, but includes all aspects falling within the scope of the appended claims.

Claims

WHAT IS CLAIMED IS:

1. A computer-implemented method, comprising: aligning two or more MS/MS data sets of a compound, the two or more MS/MS data sets comprising spectra with mass-to-charge ratio (m/z) peaks, to generate an aligned MS/MS dataset, wherein the aligned MS/MS dataset reconciles peaks in each of the MS/MS data sets that correspond to the same m/z based on the m/z tolerance consistent with the achievable m/z measurement precision; generating an aligned annotated MS/MS data set, comprising annotating each fragment peak in the aligned MS/MS data set with elemental compositions and, respectively, candidate molecule structures that correspond to the m/z of fragment peak in the aligned MS/MS data set, wherein each candidate molecule structure is given an aligned MS/MS data set confidence score; and ranking the candidate molecule structures to determine a lead candidate molecule structure.

2. The computer-implemented method of claim 1, wherein the two or more MS/MS data sets are collected using orthogonal fragmentation techniques.

3. The computer-implemented method of claim 2, wherein the orthogonal fragmentation techniques are selected from collision induced dissociation (CID), electron-based dissociation (ExD), infrared multi-photon photodissociation (IRMPD), and ultraviolet photofragmentation (UVPD).

4. The computer-implemented method of any one of claims 1 to 3, wherein the compound is a degradant of a known compound.

5. The computertoimplemented method of any one of claims 1 to 3, wherein the compound is a metabolite of a known compound.

6. The computertoimplemented method of any one of claims 1 to 3, wherein the compound is an unknown compound.

7. The computertoimplemented method of any one of claims 1 to 6, wherein the list of candidate structures is generated intosilico.

8. The computertoimplemented method of any one of claims 1 to 6, wherein the list of candidate structures is retrieved from a compound repository.

9. The computertoimplemented method of any one of claims 1 to 8, further comprising providing qualitative feedback regarding purities of each of the two or more MS/MS data sets.

10. A computertoimplemented method, comprising: processing, with one or more computing devices, two or more MS/MS data sets of a compound against a list of candidate structures, the two or more MS/MS data sets comprising spectra with masstototocharge ratio (m/z) peaks, wherein the processing further comprises generating two or more annotated MS/MS data sets, comprising annotating each fragment peak in each MS/MS data set with elemental compositions and, respectively, candidate molecule structures that correspond to the m/z of each fragment peak, wherein each candidate molecule structure is given an MS/MS data set confidence score; aligning the two or more annotated MS/MS data sets to generate an aligned annotated MS/MS dataset, wherein the aligned annotated MS/MS dataset reconciles the candidate moleculestructures from each of the MS/MS datasets that correspond to the same m/z; consolidating the candidate molecule structure confidence scores from the two or more MS/MS data sets to generate consolidated candidate structure confidence scores; and ranking the candidate molecule structures to determine a lead consolidated candidate structure.

11. The computertoimplemented method of claim 10, wherein the two or more MS/MS data sets are collected using orthogonal fragmentation techniques.

12. The computertoimplemented method of claim 11, wherein the orthogonal fragmentation techniques are selected from collision induced dissociation (CID), electrontobased dissociation (ExD), infrared multitophoton photodissociation (IRMPD), and ultraviolet photofragmentation (UVPD).

13. The computertoimplemented method of any one of claims 10 to 12, wherein the compound is a degradant of a known compound.

14. The computertoimplemented method of any one of claims 10 to 12, wherein the compound is a metabolite of a known compound.

15. The computertoimplemented method of any one of claims 10 to 12, wherein the compound is an unknown compound.

16. The computertoimplemented method of any one of claims 10 to 15, wherein the processing of each of the two or more MS/MS data sets further comprises ranking the candidate structures in order of each candidate structure’s confidence score.

17. The computertoimplemented method of any one of claims 10 to 16, wherein the aligned annotated MS/MS data set reconciles candidate structures from the two or more MS/MS data sets that correspond to the same m/z within a tolerance consistent with the achievable m/z measurement precision.

18. The computertoimplemented method of any one of claims 10 to 17, wherein the list of candidate structures is generated intosilico.

19. The computertoimplemented method of any one of claims 10 to 17, wherein the list of candidate structures is retrieved from a compound repository.

20. The computertoimplemented method of any one of claims 10 to 19, wherein the processing of each of the two or more MS/MS data sets further comprises grouping candidate structures based on structural similarity.

21. The computertoimplemented method of claim 20, further comprising ranking the candidate structures in each group in order of the confidence score of each candidate structure.

22. The computertoimplemented method of any one of claims 10 to 21, wherein the processing further comprises, after generating two or more annotated MS/MS data sets, determining the total ion current (TIC) and the portion of the ion current used to generate each of the two or more annotated MS/MS data sets.

23. The computertoimplemented method of any one of claims 10 to 22, wherein the consolidated candidate structure confidence score of the lead consolidated candidate structure is compared to the other consolidated candidate structure scores using a ttotest and reported as a confidence measure.

24. The computertoimplemented method of any one of claims 10 to 23, further comprising providing qualitative feedback regarding purity of the two or more MS/MS data sets.

25. The computertoimplemented method of any one of claims 10 to 13 or 15 to 24, wherein, prior to processing the two or more MS/MS data sets, processing, with one or more computing devices, two or more reference MS/MS data sets of a reference compound against a list of reference structures and annotating the two or more reference MS/MS data sets with the reference structures; aligning the two or more reference MS/MS data sets to generate an aligned annotated reference data set.

26. The computertoimplemented method of claim 25, wherein the two or more reference MS/MS data sets are collected using orthogonal fragmentation techniques.

27. The computertoimplemented method of claim 26, wherein the orthogonal fragmentation techniques are selected from collision induced dissociation (CID), electrontobased dissociation (ExD), infrared multitophoton photodissociation, and ultraviolet photofragmentation (UVPD).

28. The computertoimplemented method of any one of claims 25 to 27, wherein the candidate structure confidence scores for each candidate structure from the two or more MS/MS data sets are generated from comparison to the reference spectra.

29. The computertoimplemented method of any one of claims 10 to 28, wherein the two or more MS/MS data sets comprises a first MS/MS data set and a second MS/MS data set.

30. The computertoimplemented method of claim 29, wherein the first MS/MS data set is collected using CID and wherein the second MS/MS data set is collected using EAD.

31. The computertoimplemented method of any one of claims 10 to 30, wherein the consolidated candidate structure confidence scores are generated according to:

S = a * Si (1 < i < n) wherein i is an index of the MS/MS data set, a is the contribution of the I^th MS/MS data set confidence score to the consolidated MS/MS data set confidence score, and st is the MS/MS data set confidence score; and wherein (1 < i < n).

32. The computertoimplemented method of claim 31, wherein a is generated based on the ion current used for annotating the two or more MS/MS data sets.

33. The computertoimplemented method of any one of claims 10 to 24, wherein the candidate structure confidence scores for each candidate structure from the two or more MS/MS data sets are based on the fragment elemental compositions, and, respectively, fragment positions in the candidate molecule structure.

34. The computertoimplemented method of claim 33, wherein the consolidated candidate structure confidence scores are generated by normalizing the confidence scores from the two or more MS/MS data sets such that the maximum confidence score of each of the two or more MS/MS data sets correspond to their target contributions (c,) to the consolidated candidate structure confidence score.

35. One or more nontotransitory computertoreadable storage media comprising instructions, which when executed by one or more computing devices, causes the one or more computing devices to: align two or more MS/MS data sets of a compound analog, the two or more MS/MS data sets comprising spectra with masstototocharge ratio (m/z) peaks, to generate an aligned MS/MS dataset, wherein the aligned MS/MS dataset reconciles peaks in each of the MS/MS data sets that correspond to the same m/z; generate an aligned annotated MS/MS data set, comprising annotating each fragment peak in the aligned MS/MS data set with candidate structures that correspond to the m/z of each fragment peak in the aligned MS/MS data set, wherein each candidate structure is given an aligned MS/MS data set confidence score; and rank the structures to determine a lead candidate structure.

36. One or more nontotransitory computertoreadable storage media comprising instructions, which when executed by one or more computing devices, causes the one or more computing devices to: process, with one or more computing devices, two or more MS/MS data sets of a compound analog against a list of candidate structures, the two or more MS/MS data sets comprising spectra with masstototocharge ratio (m/z) peaks, wherein the processing further comprises generating two or more annotated MS/MS data sets, comprising annotating each fragment peak in each MS/MS data set with candidate structures that correspond to the m/z of each fragment peak, wherein each candidate structure is given an MS/MS data set confidence score; align the two or more MS/MS data sets to generate an aligned annotated MS/MS dataset, wherein the aligned annotated MS/MS dataset reconciles the candidate structures from each of the MS/MS datasets that correspond to the same m/z; consolidate the candidate structure confidence scores from the two or more MS/MS data sets to generate consolidated candidate structure confidence scores; rank the candidate structures to determine a lead consolidated candidate structure; and display a visual representation of the data.