Presentation of antigenic peptides by major histocompatibility complex class II (MHC-II) proteins determines T helper cell reactivity. The MHC-II genetic locus displays a large degree of allelic polymorphism influencing the peptide repertoire presented by the resulting MHC-II protein allotypes. During antigen processing, the human leukocyte antigen (HLA) molecule HLA-DM (DM) encounters these distinct allotypes and catalyzes exchange of the placeholder peptide CLIP by exploiting dynamic features of MHC-II. Here, we investigate 12 highly abundant CLIP-bound HLA-DRB1 allotypes and correlate dynamics to catalysis by DM. Despite large differences in thermodynamic stability, peptide exchange rates fall into a target range that maintains DM responsiveness. A DM-susceptible conformation is conserved in MHC-II molecules, and allosteric coupling between polymorphic sites affects dynamic states that influence DM catalysis. As exemplified for rheumatoid arthritis, we postulate that intrinsic dynamic features of peptide-MHC-II complexes contribute to the association of individual MHC-II allotypes with autoimmune disease.

The microbiota generates diverse metabolites to modulate host physiology and disease, but their protein targets and mechanisms of action have not been fully elucidated. To address this challenge, we explored microbiota-derived indole metabolites and developed photoaffinity chemical reporters for proteomic studies. We identified many potential indole metabolite-interacting proteins, including metabolic enzymes, transporters, immune sensors and G protein-coupled receptors. Notably, we discovered that aromatic monoamines can bind the orphan receptor GPRC5A and stimulate β-arrestin recruitment. Metabolomic and functional profiling also revealed specific amino acid decarboxylase-expressing microbiota species that produce aromatic monoamine agonists for GPRC5A-β-arrestin recruitment. Our analysis of synthetic aromatic monoamine derivatives identified 7-fluorotryptamine as a more potent agonist of GPRC5A. These results highlight the utility of chemoproteomics to identify microbiota metabolite-interacting proteins and the development of small-molecule agonists for orphan receptors.

With an eye toward expanding chemistries used for covalent ligand discovery, we elaborated an umpolung strategy that exploits the 'polarity reversal' of sulfur when cysteine is oxidized to sulfenic acid, a widespread post-translational modification, for selective bioconjugation with C-nucleophiles. Here we present a global map of a human sulfenome that is susceptible to covalent modification by members of a nucleophilic fragment library. More than 500 liganded sulfenic acids were identified on proteins across diverse functional classes, and, of these, more than 80% were not targeted by electrophilic fragment analogs. We further show that members of our nucleophilic fragment library can impair functional protein-protein interactions involved in nuclear oncoprotein transport and DNA damage repair. Our findings reveal a vast expanse of ligandable sulfenic acids in the human proteome and highlight the utility of nucleophilic small molecules in the fragment-based covalent ligand discovery pipeline, presaging further opportunities using non-traditional chemistries for targeting proteins.

Acinetobacter baumannii is a nosocomial Gram-negative pathogen that often displays multidrug resistance. Discovering new antibiotics against A. baumannii has proven challenging through conventional screening approaches. Fortunately, machine learning methods allow for the rapid exploration of chemical space, increasing the probability of discovering new antibacterial molecules. Here we screened ~7,500 molecules for those that inhibited the growth of A. baumannii in vitro. We trained a neural network with this growth inhibition dataset and performed in silico predictions for structurally new molecules with activity against A. baumannii. Through this approach, we discovered abaucin, an antibacterial compound with narrow-spectrum activity against A. baumannii. Further investigations revealed that abaucin perturbs lipoprotein trafficking through a mechanism involving LolE. Moreover, abaucin could control an A. baumannii infection in a mouse wound model. This work highlights the utility of machine learning in antibiotic discovery and describes a promising lead with targeted activity against a challenging Gram-negative pathogen.

The complement receptors C3aR and C5aR1, whose signaling is selectively activated by anaphylatoxins C3a and C5a, are important regulators of both innate and adaptive immune responses. Dysregulations of C3aR and C5aR1 signaling lead to multiple inflammatory disorders, including sepsis, asthma and acute respiratory distress syndrome. The mechanism underlying endogenous anaphylatoxin recognition and activation of C3aR and C5aR1 remains elusive. Here we reported the structures of C3a-bound C3aR and C5a-bound C5aR1 as well as an apo-C3aR structure. These structures, combined with mutagenesis analysis, reveal a conserved recognition pattern of anaphylatoxins to the complement receptors that is different from chemokine receptors, unique pocket topologies of C3aR and C5aR1 that mediate ligand selectivity, and a common mechanism of receptor activation. These results provide crucial insights into the molecular understanding of C3aR and C5aR1 signaling and structural templates for rational drug design for treating inflammation disorders.

Histone acetyltransferases (HATs) are implicated as both oncogene and nononcogene dependencies in diverse human cancers. Acetyl-CoA-competitive HAT inhibitors have emerged as potential cancer therapeutics and the first clinical trial for this class of drugs is ongoing (NCT04606446). Despite these developments, the potential mechanisms of therapeutic response and evolved drug resistance remain poorly understood. Having discovered that multiple regulators of de novo coenzyme A (CoA) biosynthesis can modulate sensitivity to CBP/p300 HAT inhibition (PANK3, PANK4 and SLC5A6), we determined that elevated acetyl-CoA concentrations can outcompete drug-target engagement to elicit acquired drug resistance. This not only affects structurally diverse CBP/p300 HAT inhibitors, but also agents related to an investigational KAT6A/B HAT inhibitor that is currently in Phase 1 clinical trials. Altogether, this work uncovers CoA metabolism as an unexpected liability of anticancer HAT inhibitors and will therefore buoy future efforts to optimize the efficacy of this new form of targeted therapy.