Computational approaches such as genome and metabolome mining are becoming essential to natural products (NPs) research. Consequently, a need exists for an automated structure-type classification system to handle the massive amounts of data appearing for NP structures. An ideal semantic ontology for the classification of NPs should go beyond the simple presence/absence of chemical substructures, but also include the taxonomy of the producing organism, the nature of the biosynthetic pathway, and/or their biological properties. Thus, a holistic and automatic NP classification framework could have considerable value to comprehensively navigate the relatedness of NPs, and especially so when analyzing large numbers of NPs. Here, we introduce NPClassifier, a deep-learning tool for the automated structural classification of NPs from their counted Morgan fingerprints. NPClassifier is expected to accelerate and enhance NP discovery by linking NP structures to their underlying properties.

Genomics and metabolomics are widely used to explore specialized metabolite diversity. The Paired Omics Data Platform is a community initiative to systematically document links between metabolome and (meta)genome data, aiding identification of natural product biosynthetic origins and metabolite structures.

Somatic gain-of-function mutations of GNAQ and GNA11, which encode α subunits of heterotrimeric Gα_q/11 proteins, occur in about 85% of cases of uveal melanoma (UM), the most common cancer of the adult eye. Molecular therapies to directly target these oncoproteins are lacking, and current treatment options rely on radiation, surgery, or inhibition of effector molecules downstream of these G proteins. A hallmark feature of oncogenic Gα_q/11 proteins is their reduced intrinsic rate of hydrolysis of guanosine triphosphate (GTP), which results in their accumulation in the GTP-bound, active state. Here, we report that the cyclic depsipeptide FR900359 (FR) directly interacted with GTPase-deficient Gα_q/11 proteins and preferentially inhibited mitogenic ERK signaling rather than canonical phospholipase Cβ (PLCβ) signaling driven by these oncogenes. Thereby, FR suppressed the proliferation of melanoma cells in culture and inhibited the growth of Gα_q-driven UM mouse xenografts in vivo. In contrast, FR did not affect tumor growth when xenografts carried mutated B-Raf^V600E as the oncogenic driver. Because FR enabled suppression of malignant traits in cancer cells that are driven by activating mutations at codon 209 in Gα_q/11 proteins, we envision that similar approaches could be taken to blunt the signaling of non-Gα_q/11 G proteins.