Journal of Natural ProductsMicrobiologyPeer-reviewed journal article
AI-Accelerated Structure Elucidation of Boavistamides A-C, Cyclic Depsipeptides from a Marine Filamentous Cyanobacterium Collected in Cabo Verde
Marine CuauiD, Nicole E. AvaloniD, Byeol RyuiD, Evgenia GlukhoviD, Jehad AlmalitiiD, Adriana RegoiD, Thaiz R. Teixeira, Mai Shingyoji, Mariana Laureano de SouzaiD, Alma Trinidad-Javier, Krittikorn KümpornsiniD, Joseph CheniD, Case W. McNamaraiD, Conor R. CaffreyiD, Elizabeth A. WinzeleriD, Vitor M. VasconcelosiD, Pedro Nuno LeãoiD, William H. GerwickiD
Abstract
Boavistamide A (1), a new alkyne-containing cyclic depsipeptide featuring the rare 3-amino-2-methyl-7-octynoic acid (AMOYA) moiety, was discovered along with two structurally related analogs, boavistamides B and C (2 and 3), from a filamentous marine cyanobacterium collected on Boa Vista Island, Cabo Verde. Their isolation was guided by antiplasmodial activity, GNPS MS/MS molecular networking, LC-MS profiling, and dereplication using the MarinLit database. The planar structures of boavistamides A-C (1-3) were elucidated through comprehensive HRMS and 1D/2D NMR analyses, with annotation support from AI-based tools SMART-NMR 2.1 and DeepSAT. The absolute configurations were established using Marfeys analysis and L-Phe-OMe coupling, complemented by NMR-based conformational studies. Boavistamides A and B exhibited moderate antiplasmodial activity with no mammalian cell cytotoxicity. Microscopic observations and metagenomic binning identified the producer strain as belonging to the genus Okeania (Microcoleaceae). These results expand the chemical diversity of AMOYA-containing cyanobacterial metabolites and highlight the utility of integrated metabolomics and AI-assisted workflows for natural product discovery from environmental samples. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=103 SRC="FIGDIR/small/732064v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@6577feorg.highwire.dtl.DTLVardef@1a8d656org.highwire.dtl.DTLVardef@18fc299org.highwire.dtl.DTLVardef@130d3d0_HPS_FORMAT_FIGEXP M_FIG C_FIG
- assay: metabolomics
- research focus: drug response / drug discovery
- approach: deep learning
- approach: statistical model
- Citations
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- FWCI
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- Field percentile
- 47th percentile
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