Chemical structure elucidation is a serious bottleneck in analytical chemistry today. We address the problem of identifying an unknown chemical threat given its mass spectrum and its chemical formula, a task which might take well trained chemists several days to complete. Given a chemical formula, there could be over a million possible candidate structures. We take a data driven approach to rank these structures by using neural networks to predict the presence of substructures given the mass spectrum, and matching these substructures to the candidate structures. Empirically, we evaluate our approach on a data set of chemical agents built for unknown chemical threat identification. We show that our substructure classifiers can attain over 90 micro F1-score, and we can find the correct structure among the top 20 candidates in 88 and 71 of test cases for two compound classes.
Together with the burgeoning use of high-resolution, high-accuracy MS and tandem MS, alternative identification strategies have arisen that involve the use of online compound database (PubChem @cite_0 and Chemspider @cite_7 ) searching. These have spurred multiple analytical companies such as Thermo Fisher, Agilent Technologies, Waters and ACD Labs to develop commercial software, such as Mass Frontier (Thermo Fisher), Masshunter Profinder (Agilent), Progenesis Q1 (Waters) and ACD MS Workbook Suite (ACD Labs), that make use of these online databases to yield substructure information based on the mass spectrum of the unknown compound. With this information, the chemist can then postulate probable structures on which the software would perform an in-silico fragmentation and from the fragments generated, a match value to the experimental mass spectrum is calculated. However, not only is there a limited amount of spectral databases available for high-resolution and tandem mass spectrometry, the requirement of a well trained chemist to elucidate the unknown structure does not make the structural elucidation process any less of a challenge.
@cite_0 @cite_7
1601495365 1976892175
Abstract PubChem is an open repository for experimental data identifying the biological activities of small molecules. PubChem contents include more than: 1000 bioassays, 28 million bioassay test outcomes, 40 million substance contributed descriptions, and 19 million unique compound structures contributed from over 70 depositing organizations. PubChem provides a significant, publicly accessible platform for mining the biological information of small molecules. ChemSpider is a free, online chemical database offering access to physical and chemical properties, molecular structure, spectral data, synthetic methods, safety information, and nomenclature for almost 25 million unique chemical compounds sourced and linked to almost 400 separate data sources on the Web. ChemSpider is quickly becoming the primary chemistry Internet portal and it can be very useful for both chemical teaching and research.