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Abstract Commensal bacteria associated with marine invertebrates are underappreciated sources of chemically novel natural products. Using mass spectrometry, we had previously detected the presence of peptidic natural products in obligate marine bacteria of the genusMicrobulbifercultured from marine sponges. In this report, the isolation and structural characterization of a panel of ureidohexapeptide natural products, termed the bulbiferamides, fromMicrobulbiferstrains is reported wherein the tryptophan side chain indole participates in a macrocyclizing peptide bond formation. Genome sequencing identifies biosynthetic gene clusters encoding production of the bulbiferamides and implicates the involvement of a thioesterase in the indolic macrocycle formation. The structural diversity and widespread presence of bulbiferamides in commensal microbiomes of marine invertebrates point toward a possible ecological role for these natural products. 

Artificial intelligence-driven advances in protein structure prediction in recent years have raised the question: has the protein structure-prediction problem been solved? Here, with a focus on nonglobular proteins, we highlight the many strengths and potential weaknesses of DeepMind’s AlphaFold2 in the context of its biological and therapeutic applications. We summarize the subtleties associated with evaluation of AlphaFold2 model quality and reliability using the predicted local distance difference test (pLDDT) and predicted aligned error (PAE) values. We highlight various classes of proteins that AlphaFold2 can be applied to and the caveats involved. Concrete examples of how AlphaFold2 models can be integrated with experimental data in the form of small-angle X-ray scattering (SAXS), solution NMR, cryo-electron microscopy (cryo-EM) and X-ray diffraction are discussed. Finally, we highlight the need to move beyond structure prediction of rigid, static structural snapshots toward conformational ensembles and alternate biologically relevant states. The overarching theme is that careful consideration is due when using AlphaFold2-generated models to generate testable hypotheses and structural models, rather than treating predicted models as de facto ground truth structures. 

Microbulbiferis a genus of halophilic bacteria that are commonly detected in the commensal marine microbiomes. These bacteria have been recognized for their ability to degrade polysaccharides and other polymeric materials. Increasingly,Microbulbifergenomes indicate these bacteria to be an untapped reservoir for novel natural product discovery and biosynthetic novelty. In this review, we summarize the distribution ofMicrobulbiferbacteria, activities of the various polymer degrading enzymes that these bacteria produce, and an up-to-date summary of the natural products that have been isolated fromMicrobulbiferstrains. We argue that these bacteria have been hiding in plain sight, and contemporary efforts into their genome and metabolome mining are going to lead to a proliferation ofMicrobulbifer-derived natural products in the future. We also describe, where possible, the ecological interactions of these bacteria in marine microbiomes.