Principles and Applications of CF2X Moieties as Unconventional Halogen Bond Donors in Medicinal Chemistry, Chemical Biology, and Drug Discovery.

As an orthogonal principle to the established (hetero)aryl halides, we herein highlight the usefulness of CF2X (X = Cl, Br, or I) moieties. Using tool compounds bearing CF2X moieties, we study their chemical/metabolic stability and their logP/solubility, as well as the role of XB in their small molecular crystal structures. Employing QM techniques, we analyze the observed interactions, provide insights into the conformational flexibilities and preferences in the potential interaction space. For their application in molecular design, we characterize their XB donor capacities and its interaction strength dependent on geometric parameters. Implementation of CF2X acetamides into our HEFLibs and biophysical evaluation (STD-NMR/ITC), followed by X-ray analysis, reveals a highly interesting binding mode for fragment 23 in JNK3, featuring an XB of CF2Br toward the P-loop, as well as chalcogen bonds. We suggest that underexplored chemical space combined with unconventional binding modes provides excellent opportunities for patentable chemotypes for therapeutic intervention.

Revisiting a challenging p53 binding site: a diversity-optimized HEFLib reveals diverse binding modes in T-p53C-Y220C.

The cellular tumor antigen p53 is a key component in cell cycle control. The mutation Y220C heavily destabilizes the protein thermally but yields a druggable crevice. We have screened the diversity-optimized halogen-enriched fragment library against T-p53C-Y220C with STD-NMR and DSF to identify hits, which we validated by 1H,15N-HSQC NMR. We could identify four hits binding in the Y220C cleft, one hit binding covalently and four hits binding to an uncharacterized binding site. Compound 1151 could be crystallized showing a flip of C220 and thus opening subsite 3. Additionally, 4482 was identified to alkylate cysteines. Data shows that the diversity-optimized HEFLib leads to multiple diverse hits. The identified scaffolds can be used to further optimize interactions with T-p53C-Y220C and increase thermal stability.

Screening of a Halogen-Enriched Fragment Library Leads to Unconventional Binding Modes.

We conceived the Halogen-Enriched Fragment Library (HEFLib) to investigate the potential of halogen bonds in the early stages of drug discovery. As the number of competitive interactions increases with ligand size, we reasoned that a binding mode relying on halogen bonding is more likely for fragments than highly decorated molecules. Thus, fragments could feature unexplored binding modes. We screened the HEFLib against the human kinase DYRK1a and verified micromolar binding fragments via isothermal titration calorimetry (ITC). The crystal structure of one fragment revealed a noncanonical binding mode, despite the fragment's classical hinge binding motif. In addition, the fragment occupies a secondary binding site. Both binding modes feature a halogen bond, which we evaluated by ab initio calculations. Structure-affinity relationship (SAR) from a set of analogues improves the affinity, provides a promising fragment-growth vector, and highlights the benefits and applicability of halogen bonds in early lead development.

SYN-View: A Phylogeny-Based Synteny Exploration Tool for the Identification of Gene Clusters Linked to Antibiotic Resistance.

The development of new antibacterial drugs has become one of the most important tasks of the century in order to overcome the posing threat of drug resistance in pathogenic bacteria. Many antibiotics originate from natural products produced by various microorganisms. Over the last decades, bioinformatical approaches have facilitated the discovery and characterization of these small compounds using genome mining methodologies. A key part of this process is the identification of the most promising biosynthetic gene clusters (BGCs), which encode novel natural products. In 2017, the Antibiotic Resistant Target Seeker (ARTS) was developed in order to enable an automated target-directed genome mining approach. ARTS identifies possible resistant target genes within antibiotic gene clusters, in order to detect promising BGCs encoding antibiotics with novel modes of action. Although ARTS can predict promising targets based on multiple criteria, it provides little information about the cluster structures of possible resistant genes. Here, we present SYN-view. Based on a phylogenetic approach, SYN-view allows for easy comparison of gene clusters of interest and distinguishing genes with regular housekeeping functions from genes functioning as antibiotic resistant targets. Our aim is to implement our proposed method into the ARTS web-server, further improving the target-directed genome mining strategy of the ARTS pipeline.