The Critical Assessment of Small Molecule Identification, or CASMI, contest was founded in 2012 to provide scientists with a common open dataset to evaluate their identification methods. In this article, the challenges and solutions for the inaugural CASMI 2012 are presented. The contest was split into four categories corresponding with tasks to determine molecular formula and molecular structure, each from two measurement types, liquid chromatography-high resolution mass spectrometry (LC-HRMS), where preference was given to high mass accuracy data, and gas chromatography-electron impact-mass spectrometry (GC-MS), i.e., unit accuracy data. These challenges were obtained from plant material, environmental samples and reference standards. It was surprisingly difficult to obtain data suitable for a contest, especially for GC-MS data where existing databases are very large. The level of difficulty of the challenges is thus quite varied. In this article, the challenges and the answers are discussed, and recommendations for challenge selection in subsequent CASMI contests are given.

The Critical Assessment of Small Molecule Identification (CASMI) Contest was founded in 2012 to provide scientists with a common open dataset to evaluate their identification methods. In this review, we summarize the submissions, evaluate procedures and discuss the results. We received five submissions (three external, two internal) for LC–MS Category 1 (best molecular formula) and six submissions (three external, three internal) for LC–MS Category 2 (best molecular structure). No external submissions were received for the GC–MS Categories 3 and 4. The team of Dunn et al. from Birmingham had the most answers in the 1st place for Category 1, while Category 2 was won by H. Oberacher. Despite the low number of participants, the external and internal submissions cover a broad range of identification strategies, including expert knowledge, database searching, automated methods and structure generation. The results of Category 1 show that complementing automated strategies with (manual) expert knowledge was the most successful approach, while no automated method could compete with the power of spectral searching for Category 2—if the challenge was present in a spectral library. Every participant topped at least one challenge, showing that different approaches are still necessary for interpretation diversity.

The task in the critical assessment of small molecule identification (CASMI) contest category 2 was to determine the identification of (initially) unknown compounds for which high-resolution tandem mass spectra were published. We focused on computer-assisted methods that tried to correctly identify the compound automatically and entered the contest with MetFrag and MetFusion to score candidate structures retrieved from the PubChem structure database. MetFrag was combined with the metabolite-likeness score, which helped to improve the performance for the natural product challenges. We present the results, discuss the performance, and give details of how to interpret the MetFrag and MetFusion output.