Fueled by the explosion of (meta)genomic data, genome mining of specialized metabolites has become a major technology for drug discovery and studying microbiome ecology. In these efforts, computational tools like antiSMASH have played a central role through the analysis of Biosynthetic Gene Clusters (BGCs). Thousands of candidate BGCs from microbial genomes have been identified and stored in public databases. Interpreting the function and novelty of these predicted BGCs requires comparison with a well-documented set of BGCs of known function. The MIBiG (Minimum Information about a Biosynthetic Gene Cluster) Data Standard and Repository was established in 2015 to enable curation and storage of known BGCs. Here, we present MIBiG 2.0, which encompasses major updates to the schema, the data, and the online repository itself. Over the past five years, 851 new BGCs have been added. Additionally, we performed extensive manual data curation of all entries to improve the annotation quality of our repository. We also redesigned the data schema to ensure the compliance of future annotations. Finally, we improved the user experience by adding new features such as query searches and a statistics page, and enabled direct link-outs to chemical structure databases. The repository is accessible online at https://mibig.secondarymetabolites.org/.

Menin functions as a critical oncogenic cofactor of mixed lineage leukemia (MLL) fusion proteins in the development of acute leukemias, and inhibition of the menin interaction with MLL fusion proteins represents a very promising strategy to reverse their oncogenic activity. MLL interacts with menin in a bivalent mode involving 2 N-terminal fragments of MLL. In the present study, we reveal the first high-resolution crystal structure of human menin in complex with a smallmolecule inhibitor of the menin-MLL interaction, MI-2. The structure shows that the compound binds to the MLL pocket in menin and mimics the key interactions of MLL with menin. Based on the menin-MI-2 structure, we developed MI-2-2, a compound that binds to menin with low nanomolar affinity (K d ‫؍‬ IntroductionTranslocations of the MLL (mixed lineage leukemia) gene frequently occur in aggressive human acute myeloid and lymphoid leukemias in both children and adults. 1 Fusion of MLL with 1 of more than 60 different genes results in chimeric MLL fusion proteins that enhance proliferation and block hematopoietic differentiation, ultimately leading to acute leukemia. 2 Patients with leukemias harboring MLL translocations have very unfavorable prognoses and respond poorly to currently available treatments. 2,3 The relapse risk is very high using conventional chemotherapy and stem cell transplantation, 2 leading to an overall 5-year survival rate of only approximately 35%. 4 All MLL fusion proteins preserve an N-terminal MLL fragment approximately 1400 amino acids in length fused in-frame with the C-terminus of the fusion partner. 3,[5][6][7] Two regions in this fragment of MLL have been shown to be indispensable for leukemogenic transformation: the N-terminal region, which binds to menin 8 and to lens epithelium-derived growth factor (LEDGF), 9 and the conserved region encompassing the CXXC domain, which mediates binding to nonmethylated CpG DNA [10][11][12] and interacts with the polymerase associated factor complex (PAFc). 13,14 Targeting these interactions provides new opportunities for the development of new therapeutic agents for the MLL leukemias. 15 Menin is a tumor-suppressor protein encoded by the MEN1 (multiple endocrine neoplasia 1) gene. 16 Mutations of MEN1 are associated with tumors of the parathyroid glands, pancreatic islet cells, and anterior pituitary gland. 17 Menin is also a highly specific binding partner for MLL and MLL fusion proteins and is required to regulate the expression of MLL target genes, including HOXA9 and MEIS1. 8 Loss of the ability to bind menin abolishes the oncogenic potential of MLL fusion proteins both in vitro and in vivo. 8 Disruption of the interaction between menin and MLL fusion proteins using genetic methods blocks the development of acute leukemia in mice, 8 indicating that menin functions as a critical oncogenic cofactor of MLL fusion proteins and is required for their leukemogenic activity. The menin-MLL interaction represents an attractive therapeutic target for the development of novel drugs for acut...

With an ever-increasing amount of (meta)genomic data being deposited in sequence databases, (meta)genome mining for natural product biosynthetic pathways occupies a critical role in the discovery of novel pharmaceutical drugs, crop protection agents and biomaterials. The genes that encode these pathways are often organised into biosynthetic gene clusters (BGCs). In 2015, we defined the Minimum Information about a Biosynthetic Gene cluster (MIBiG): a standardised data format that describes the minimally required information to uniquely characterise a BGC. We simultaneously constructed an accompanying online database of BGCs, which has since been widely used by the community as a reference dataset for BGCs and was expanded to 2021 entries in 2019 (MIBiG 2.0). Here, we describe MIBiG 3.0, a database update comprising large-scale validation and re-annotation of existing entries and 661 new entries. Particular attention was paid to the annotation of compound structures and biological activities, as well as protein domain selectivities. Together, these new features keep the database up-to-date, and will provide new opportunities for the scientific community to use its freely available data, e.g. for the training of new machine learning models to predict sequence-structure-function relationships for diverse natural products. MIBiG 3.0 is accessible online at https://mibig.secondarymetabolites.org/.

Multipolar interactions involving fluorine and the protein backbone have been frequently observed in protein–ligand complexes. Such fluorine–backbone interactions may substantially contribute to the high affinity of small molecule inhibitors. Here we found that introduction of trifluoromethyl groups into two different sites in the thienopyrimidine class of menin–MLL inhibitors considerably improved their inhibitory activity. In both cases, trifluoromethyl groups are engaged in short interactions with the backbone of menin. In order to understand the effect of fluorine, we synthesized a series of analogues by systematically changing the number of fluorine atoms, and we determined high-resolution crystal structures of the complexes with menin. We found that introduction of fluorine at favorable geometry for interactions with backbone carbonyls may improve the activity of menin–MLL inhibitors as much as 5- to 10-fold. In order to facilitate the design of multipolar fluorine–backbone interactions in protein–ligand complexes, we developed a computational algorithm named FMAP, which calculates fluorophilic sites in proximity to the protein backbone. We demonstrated that FMAP could be used to rationalize improvement in the activity of known protein inhibitors upon introduction of fluorine. Furthermore, FMAP may also represent a valuable tool for designing new fluorine substitutions and support ligand optimization in drug discovery projects. Analysis of the menin–MLL inhibitor complexes revealed that the backbone in secondary structures is particularly accessible to the interactions with fluorine. Considering that secondary structure elements are frequently exposed at protein interfaces, we postulate that multipolar fluorine–backbone interactions may represent a particularly attractive approach to improve inhibitors of protein–protein interactions.

Background: Autophagy plays a role in cancer development. Results: Oncogenic KRAS induces Vacuole Membrane Protein 1 (VMP1) through a novel AKT1-GLI3-p300 pathway and requires VMP1 to regulate autophagy in cancer cells. Conclusion: Define a novel pathway initiated by the oncogene KRAS regulating autophagy. Significance: These findings contribute to the understanding of the mechanism underlying oncogene-induced autophagy.