SIRIUS is a Java-based open-source software for the identification of small molecules from fragmentation mass spectrometry data without the use of spectral libraries. It combines the analysis of isotope patterns in MS1 spectra with the analysis of fragmentation patterns in MS2 spectra. SIRIUS is the umbrella application comprising CSI:FingerID, CANOPUS, COSMIC and ZODIAC. SIRIUS, including its web services for structural elucidation, is freely available to use for academic research. Bright Giant GmbH offers subscription-based access to the SIRIUS web services for commercial users. SIRIUS is not suitable for analyzing proteomics MS data.
History The SIRIUS software is developed by the group of Sebastian Böcker at the Friedrich Schiller University Jena, Germany and since 2019 together with Bright Giant GmbH. SIRIUS development started in 2009 as a software for identification of the molecular formula by decomposing high-resolution isotope patterns (also called MS1 data). The name is an akronym resulting from this original purpose: Sum formula Identification by Ranking Isotope patterns Using mass Spectrometry. In 2008 the group introduced the concept of fragmentation trees for identification of the molecular formula based on fragmentation mass spectrometry data, also called tandem MS or MS2 data. Back then, identification of small molecules was approached by searching in a reference spectral library. Examples of such libraries include MassBank, METLIN, or NIST/EPA/NIH EI-MS Library. However, this is limited to known molecules with available standards that have been measured and put in a reference spectral library. For unknown molecules, identification of the molecular formula is a crucial step. In 2011/2012, the group conceived fragmentation trees as a means of structural elucidation by automatically comparing these fragmentation trees. Fragmentation pattern similarities are strongly correlated with the chemical similarity of molecules. Thus, aligning the fragmentation tree of an unknown molecule to a set of known molecules helps to elucidate its structure. Fragmentation trees were introduced in SIRIUS 2. Also in 2012, the group of Juho Rousu at University of Helsinki, Finland, introduced a machine learning method to predict molecular properties from tandem MS data. This concept was brought together with the fragmentation tree concept in 2015 resulting in CSI:FingerID, being introduced in SIRIUS 3. The fragmentation tree is used to predict a molecular fingerprint of the unknown molecule using machine learning, which in turn is used to search a molecular structure database such as PubChem. Molecular structure databases are orders of magnitude larger than reference spectra libraries (PubChem containing ~111 million compounds in 2021 compared to NIST Tandem Mass Spectral Library containing ~50.000 compounds in 2023). This kind of structure identification refers to the identity and connectivity (with bond multiplicities) of the atoms, but not stereochemistry information. Elucidation of stereochemistry is currently beyond the power of automated search engines. SIRIUS 3 also introduced the graphical user interface (GUI). In 2020, in cooperation with the group of Pieter C Dorrestein at UC San Diego, USA, molecular formula identification was improved based on derivative networks from complete biological datasets to rank molecular formula candidates. This method is called ZODIAC and has been integrated into SIRIUS 4. Also in 2020, in cooperation with Rousu's and Dorrestein's groups, CANOPUS for systematic compound class annotation was introduced to SIRIUS 4. In 2022, the COSMIC confidence score was added to the CSI:FingerID structure identification workflow in SIRIUS 4, allowing users to determine the trustworthiness of the identification. In 2024, the de novo generation of candidate structures through MSNovelist was introduced with SIRIUS 6.
Data SIRIUS is using data from liquid-chromatography tandem mass spectrometry (LC-MS/MS). It requires high-resolution, high mass accuracy MS1 and MS2 data as input. LC is not mandatory for SIRIUS, however is often required to separate individual compounds in complex samples.
MS1 data refers mainly to the isotope pattern of the compound. Due to the natural isotopic distributions of the elements, several peaks in the mass spectrum correspond to the same type of sample molecule, reflecting its isotope pattern. MS2 data refers to the fragmentation pattern of the compound. MS2 is also known as tandem mass spectrometry or MS/MS. The statistical model of SIRIUS and the machine learning model of CSI:FingerID were trained on MS2 spectra created by collision-induced dissociation (CID), as commonly applied in LC-MS/MS experiments. SIRIUS expects both, MS1 and MS2 spectra, as input. Omitting the MS1 data is possible, but it will make the analysis more time-consuming and can lead to poorer results. SIRIUS and CSI:FingerID have been trained on a wide variety of data, including data from different instrument types. Certain aspects of the mass spectra are important to successfully process the data:
High mass accuracy: The mass deviation of the input spectra should be within 20 ppm. Mass spectrometry devices such as TOF, Orbitrap and FT-ICR usually provide data with high mass accuracy, as do coupled devices such as Q-TOF, IT-TOF or IT-Orbitrap. Spectra measured with a quadrupole or linear trap do not provide the required accuracy for data analysis with SIRIUS. Rich fragmentation spectra: It is not possible to deduce the structure or even the molecular formula from an MS2 spectrum that contains almost no peaks. Prior noise filtering of the spectra is not necessary and not favorable. SIRIUS considers up to 60 peaks in the fragmentation spectrum and decides for itself which of these peaks are regarded as noise. Centroided MS data: SIRIUS does not contain routines for peak picking from profile-mode spectra. msConvert in ProteoWizard can be used to convert to centroided data. Additionally, there are several tools specialized for the preprocessing task, such as OpenMS, MZmine or XCMS. OpenMS and MZmine 3 both provide export functions tailored to the needs for SIRIUS. Different common MS file formats, such as .csv, .ms or .mgf files, can be imported to SIRIUS. SIRIUS can import full LC-MS-runs (.mzML) or single compounds. At present, SIRIUS only handles single-charged compounds.
Features SIRIUS identifies small molecules in a two step approach:
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