Hosein Mohimani, PhD

Many of the the most potent antitumor small molecules approved by FDA are natural products from plant and microbial organism with diverse mechanisms of action. Examples include Doxorubicin, Actinomycin, Bleomycin and Mitomycin. Part of the research in Dr. Mohimani's lab focuses on using mass spectrometry and machine learning for identification of next generation of antitumor natural products. They do this by collection of LC-MS/MS data on extracts of of hundreds of thousands of microbial cultures, and then they use machine learning to digest this large scale data and predict natural products with novel chemistries and potentially novel mechanisms of action. Then they will purify these small molecules using chromatography techniques, and test them for antitumor activity using panel screening.

Lee, YY., Guler, M., Chigumba, D.N. et al. HypoRiPPAtlas as an Atlas of hypothetical natural products for mass spectrometry database search. Nat Commun 14, 4219 (2023). https://doi.org/10.1038/s41467-023-39905-4

Cao, L., Guler, M., Tagirdzhanov, A. et al. MolDiscovery: learning mass spectrometry fragmentation of small molecules. Nat Commun 12, 3718 (2021).https://doi.org/10.1038/s41467-021-23986-0

Mongia, M., Yasaka, T.M., Liu, Y. et al. Fast mass spectrometry search and clustering of untargeted metabolomics data. Nat Biotechnol 42, 1672–1677 (2024). https://doi.org/10.1038/s41587-023-01985-4

Behsaz, B., Bode, E., Gurevich, A. et al. Integrating genomics and metabolomics for scalable nonribosomal peptide discovery. Nat Commun 12, 3225 (2021). https://doi.org/10.1038/s41467- 021-23502-4