ChemMedChem

Excessive osteoclast activity contributes to pathological bone loss in osteoporosis, rheumatoid arthritis, and osteolytic malignancies. The effects of small catechol derivatives on receptor activator of nuclear factor-{kappa}B ligand (RANKL)-induced osteoclastogenesis remain poorly understood. This study investigated the effects of 4-methylcatechol (4-MC) on RANKL-induced NF-{kappa}B activation and osteoclast differentiation. 4-MC reduced RANKL-induced NF-{kappa}B luciferase activity in HEK-293T/RANK cells. 4-MC also suppressed RANKL-induced TRAP activity in RAW264.7 cells in a concentration-dependent manner and reduced the number of TRAP-positive multinucleated osteoclasts, without affecting cell viability. Molecular docking predicted non-covalent binding of 4-MC within the ATP-binding hinge region of IKK{beta} (PDB: 4KIK), forming a close polar contact with Glu97, predicted hydrogen bonds with Cys99, and a hydrophobic contact with Ile165, within the pocket occupied by the co-crystallized inhibitor K252a. Covalent docking predicted that the oxidized quinone form of 4-MC engages Cys179 in the IKK{beta} activation loop. Quantum chemical calculations confirmed a markedly higher electrophilicity index for the oxidized quinone than for the parent catechol, supporting this mechanism. In silico ADMET profiling indicated favorable drug-likeness and safety. These findings identify IKK{beta} as a plausible molecular target of 4-MC through both non-covalent and covalent mechanisms. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/741661v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@35a0d3org.highwire.dtl.DTLVardef@d19458org.highwire.dtl.DTLVardef@1623fadorg.highwire.dtl.DTLVardef@1429e8b_HPS_FORMAT_FIGEXP M_FIG C_FIG

Plant-derived small molecules possess highly diverse physicochemical properties, and the computational design of their protein recognition elements depends not only on the global structural quality of candidate backbones, but also on whether the local binding pocket, ligand-contact pattern, and predefined recognition conformation can be consistently retained after sequence design and structural back-prediction. To explore pocket-design strategies for different types of natural-product small molecules, this study selected capsaicin, (4R)-limonene, and quercetin as model ligands, representing a flexible amphipathic molecule, a compact hydrophobic monoterpene, and a rigid polyphenolic flavonoid scaffold, respectively, and covering the dimensions of pungent sensory flavor, volatile aroma, and flavonoid functional constituents. A ligand- physicochemical-property-guided computational design and multi-stage prioritization framework was established for candidate protein binders. The results showed that candidates with favorable initial global structural scores did not necessarily form reasonable local small-molecule binding pockets, indicating that evaluation of the local ligand environment is essential for candidate prioritization. After screening, 31 partial- pocket candidate backbones for capsaicin, 75 buried hydrophobic-pocket candidate backbones for (4R)-limonene, and 56 pocket-qualified candidate backbones for quercetin were obtained. Further sequence design and structural back-prediction analyses indicated that a subset of candidates could maintain the original pocket geometry and major ligand-contact patterns after sequence realization. Overall, these results suggest that the physicochemical properties of different plant-derived small molecules substantially influence the efficiency of de novo protein pocket formation, with compact hydrophobic ligands being more compatible with buried hydrophobic- pocket strategies, whereas flexible or multipolar ligands require a more refined balance between hydrophobic burial and polar exposure. This study provides a pre- experimental computational prioritization framework for natural-product small- molecule-recognizing proteins and offers candidate resources for subsequent protein expression, in vitro binding validation, active-constituent enrichment, and development of small-molecule biorecognition tools. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/743643v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@8fe6c2org.highwire.dtl.DTLVardef@176cef2org.highwire.dtl.DTLVardef@10c8201org.highwire.dtl.DTLVardef@2b28cf_HPS_FORMAT_FIGEXP M_FIG C_FIG

The human immune system excels at generating highly effective antibodies through natural selection and somatic hypermutation, but adapting these antibodies for therapeutic use, referred to as "antibody medicine-likeness", requires careful consideration of biochemical and physiological properties. Traditional redesign methods are often slow and limited in scope. In this study, we introduce a machine learning-based approach to evolve new anti-PD-1 antibodies within a chemically informed latent space using a conditional kernel-elastic autoencoder (CKEA) between nivolumab and pembrolizumab, both of which bind the FG-loop "hotspot" of PD-1 in the most distantly related orientations, differing by 174{degrees}. This generative framework is designed to preserve favorable therapeutic features while exploring variants with different potency, ultimately for improved potency. To evaluate structural and functional viability, we performed molecular dynamics (MD) simulations of the generated antibody - PD-1 complexes and described their MD properties. These simulations reveal detailed free-energy landscapes and identify stable binding conformations, providing a strong basis for experimental validation. To validate our designs, we expressed and experimentally tested the antibodies for binding affinity to PD-1. Upon expression and purification, three out of six designed antibodies exhibited some binding to PD-1, whose properties could likely be improved using other computational saturation mutagenesis or laboratory evolution. Our results demonstrate the potential of artificial intelligence (AI)-guided interpolation methods to generate novel, high-affinity antibodies with therapeutic promise, offering a powerful strategy for next-generation antibody development. SYNOPSIS TOCCombination of MD simulations with machine learning algorithms could revolutionize the antibody-breeding sciences to lead to new antibody discovery that is compatible with or better than naturally occurring antibodies. Topics of Content (TOC)Fingerprints of R86 finger of PD-1 are recognized by our designed P2N_2 anti-PD-1 antibody according to our MD simulations O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=173 SRC="FIGDIR/small/742579v1_ufig1.gif" ALT="Figure 1000"> View larger version (49K): org.highwire.dtl.DTLVardef@1bbeb5eorg.highwire.dtl.DTLVardef@599658org.highwire.dtl.DTLVardef@19d8c69org.highwire.dtl.DTLVardef@6d5f0c_HPS_FORMAT_FIGEXP M_FIG C_FIG

Metastatic melanoma is an aggressive cutaneous malignancy frequently driven by the oncogenic V600E mutation within the BRAF kinase. While first-generation Type IS BRAF inhibitors, such as dabrafenib, are currently prescribed to target this specific molecular vulnerability, paradoxical MAPK pathway activation, and acquired drug resistance necessitate the continuous development of structurally optimized lead molecules. In this study, chemical intuition, bioisosteric replacement, and computational molecular docking were employed to propose two novel BRAFV600E drug candidates. The proposed therapeutics, engineered to incorporate constrained sp3-hybridized aliphatic rings and a sulfoximine bioisostere, demonstrated thermodynamically superior docking scores within the mutant catalytic cleft compared to dabrafenib. Lastly, a homology analysis determined that Mus musculus is a suitable model organism for future preclinical studies and confirmed crucial structural selectivity against microbial off-target kinases.

Cancer immunotherapy has transformed cancer treatment; however, durable responses remain limited by suppressive myeloid populations within the tumor microenvironment. Leukocyte immunoglobulin-like receptor B4 (LILRB4/ILT3) is an emerging myeloid immune checkpoint implicated in immune evasion and resistance to immunotherapy, yet small molecule targeting of ILT3 remains largely unexplored. Here, we report the discovery of small molecule ILT3 modulators identified using a Dianthus-based temperature-related intensity change (TRIC) screening platform. Screening of an 8,961-member Enamine Library identified multiple direct ILT3 binders, with lead compound ICB-7 demonstrating high-affinity binding to recombinant human ILT3 by microscale thermophoresis and robust cellular target engagement in CETSA assays. Molecular docking and molecular dynamics simulations revealed a stable hydrophobic binding pocket within the D2 domain of ILT3. Functionally, ICB-7 disrupted the ILT3-SCG2 interaction and inhibited downstream SHP1, SHP2, and STAT3 signaling. In patient-derived colorectal cancer and acute myeloid leukemia co-culture models, ICB-7 enhanced cytotoxic T-cell activity, and reduced tumor-cell viability. The compound also demonstrated favorable pharmacokinetic and safety properties together with significant anti-tumor efficacy in the CT26 syngeneic colorectal carcinoma model. Collectively, these findings establish ILT3 as a tractable target for small-molecule immunomodulation and support pharmacological targeting of suppressive myeloid checkpoints as a promising cancer immunotherapy strategy.

Protein Kinase Novel 3 (PKN3) understudied kinase with a diverse array of biological functions that are yet to be fully defined. Here, we report the design and development of a novel advanced functional chemical tool inhibitor for PKN3. A pyridyl imidazole series has been synthesized and evaluated against PKN3 in vitro and in cells. These efforts led to the discovery of 6e (URS03-06), a submicromolar cell active functional inhibitor with a narrow kinome spectrum, to enable the elucidation and interrogation of PKN3 cellular biology.

AlphaFold 3 (AF3) and Boltz-2 are state-of-the-art AI-based tools for biomolecular structure prediction, but whether their predictions provide useful guidance for lead optimization, SAR interpretation, and virtual screening remains insufficiently characterized. We benchmarked their performance using newly determined soluble epoxide hydrolase co-crystal structures and matched activity data together with a curated post-training-cutoff dataset spanning kinases, allosteric modulators, covalent systems, PROTACs, molecular glues, fragments, membrane proteins, RNA binders, and activity-cliff pairs. Both models recovered canonical orthosteric enzyme and kinase complexes, including key DFG/C conformational states, whereas allosteric, membrane-protein, and induced-proximity complexes remained challenging. Pharmacophore RMSD was often lower than overall ligand RMSD, indicating preservation of key recognition features despite imperfect whole-ligand alignment. AF3 minPAE correlated with pose accuracy, and very low minPAE values (<0.85 A) were strongly enriched for accurate poses. Model confidence scores were not associated with experimental activity, whereas Boltz-2 predicted affinity captured relative activity trends and distinguished the activity-cliff pair, although its performance varied across ligand series.

Premarineosin A undergoes rapid, chemoselective C12 halogenation under mild conditions, providing brominated, chlorinated, fluorinated, and iodinated analogs. These derivatives retained potent antiplasmodial activity against both chloroquine-sensitive and -resistant Plasmodium falciparum strains and displayed smaller reductions in potency against the resistant strain than the parent compound.

The leukocyte-specific {beta}2-integrin receptor family exerts a wide range of functions: {beta}2-integrins are involved in leukocyte trafficking, where they mediate cell adhesion during inflammatory responses via binding to ICAM-1, ICAM-2, or JAM-C. Furthermore, they are essential for the recognition and phagocytosis of pathogens opsonized by complement. Accordingly, the {beta}2-integrin family is known to be involved in autoimmune and inflammatory diseases, such as systemic lupus erythematosus. Owing to their complex biology, involving multiple conformational transitions, different signaling pathways, and a broad spectrum of ligands, the development of {beta}2-integrin-targeted probes and therapeutics has remained challenging. We aimed to develop macrocyclic peptides, derived from phage display screening, which can be used to unravel ligand binding profiles of {beta}2-integrins with an emphasis on the I domain. The selection of suitable lead peptides, and the characterization of their interaction profiles with different I domains, was enabled by an established in-vitro assay platform. Various peptide sequences were enriched during several rounds of phage display against the I-domain of CR3, of which two peptides with particularly low micromolar binding affinity were further characterized. Both peptides showed direct binding to {beta}2-integrin I-domains and, in a competitive assay, dose-dependent inhibition of the I-domains interactions with their main ligands iC3b and ICAM-1, respectively. These ligand-interfering properties were confirmed in bead- and cell-based adhesion assays. The modulators developed here are expected to provide valuable insight into the (patho-)physiology of CR3 and the other members of the {beta}2-integrin family, as the two peptides were able to compete with different ligands. In the future, this may help to identify potential therapeutic approaches for autoimmune, inflammatory, and age-related diseases.

Mycobacterium tuberculosis possesses a flexible metabolic system helping it to survive inside the host. The type II NADH dehydrogenase, composed of Ndh and NdhA, essential for bacilli, is a promising drug target. Based on ATP depletion values, two quinoline scaffolds were shortlisted after screening of a library of drug like molecules. Structurally, both 64-9C and 64-9D carry ester moieties at the 5- and 8-positions of the quinoline core, respectively. Ease to re-synthesise 64-9D resulted in synthesis of a focused library of compounds, with MIC values of 0.25-4 g/mL, consistent with ATP depletion. These compounds exhibited bactericidal activity against non-replicating mycobacteria, and showed potent efficacy against multidrug-resistant isolates. Altered, intracellular NADH/NAD+ ratio and reduced respiration was indicative of oxidative phosphorylation inhibition. Inhibition of the purified recombinant NDH protein uncompetitively, SNPs in gene encoding NDH-2 for selected one step mutants and, molecular modelling of 4FQN and 2FQN validated NDH-2 as a target for these compounds. The derivative 2FQN exhibited dose-dependent bactericidal efficacy in mice, underscoring the potential of the series as a promising anti-tuberculosis candidates.

The de novo design of proteins that bind chemically complex small molecules has broad chemical and biological implications, but strategies typically rely on a small set of protein scaffolds and require extensive experimental screening. Here, we computationally designed proteins around a minimal aromatic {pi}-stacking motif to bind the anthracycline anticancer drug doxorubicin. Experimental characterization of twelve proteins revealed a {micro}M doxorubicin binder; two additional design cycles improved scaffold stability and binding affinity to yield an 85-residue protein that binds doxorubicin with a dissociation constant of 85 nM. An X-ray crystal structure of the protein-drug complex confirmed the accuracy of the designed {pi}-{pi} stacking interactions. The designed protein could act to protect cultured cells from doxorubicin-induced cytotoxicity. Unlike previous ligand-binding protein designs based on repeat proteins or naturally occurring folds, the designed protein adopts a previously unobserved 5-helix globular fold, indicating that a broader space of folded, functional proteins exists even for compact tertiary structures smaller than 100 residues. These results demonstrate that motif-guided generative protein design can discover compact de novo protein folds capable of high-affinity recognition of chemically complex small molecules.

Tunicamycins are potent inhibitors of dolichyl-phosphate N-acetylglucosamine phosphotransferase (DPAGT1) but are unsuitable for therapeutic development due to non-selective cytotoxicity, acid-labile glycosidic linkages, and poor physicochemical properties. Although prior structural modifications reduced the promiscuous toxicity of tunicamycins, the intrinsic 11'-{beta}-1''- trehalose-type glycosidic linkage remains chemically unstable, limiting biological durability. Here, we report a rationally engineered scaffold-stabilization strategy in which the acid-labile linkage is replaced with a chemically robust cyclitol framework, enabling the concise synthesis of chemically stable and water-soluble tunicamycin analogues in only 12 synthetic steps. From this platform, TM-Cy-TBPA (4) was identified as a lead DPAGT1 inhibitor that potently suppresses the proliferation of breast cancer cells by inducing G2-phase arrest followed by apoptosis, while exhibiting minimal cytotoxicity toward nontransformed cells. The compound shows improved solubility, and favorable pharmacokinetic exposure. These results establish tunicamycin cyclitol analogues as a structurally distinct class of selective DPAGT1-targeted anticancer agents and demonstrate that stabilization of the glycosidic linkage is an effective strategy for enhancing pharmacological selectivity, improving in vivo performance, and simplifying the synthetic route.

Viral RNA-cap MTases are attractive targets for antiviral drug development. We previously identified C7-substituted 7-deaza-SAH analogues as potent inhibitors of the mpox virus 2'-O-MTase VP39. Here, we used structure-guided design to develop branched C7-substituted analogues intended to engage multiple hydrophobic regions of the VP39 SAM-binding pocket. The synthesized compounds were characterized using biochemical and crystallographic approaches. Several analogues effectively inhibited VP39, with the most potent compound displaying an IC50 in the tens-of-nanomolar range. Crystal structures of VP39 in complex with STM1187 and STM1189 confirmed that the branched aromatic substituents extend towards hydrophobic regions adjacent to the SAM binding site. The precise ligand conformations were strongly influenced by linker geometry and the branching groups mode of attachment. STM1078 also inhibited DENV3 NS5 MTase with submicromolar potency, and the complexs structure revealed a conserved binding mode of the SAH-like core accompanied by conformational adaptability of the branched substituent. These results demonstrate how three-dimensional expansion from the 7-deaza position can generate potent inhibitors capable of binding structurally distinct viral MTases.

Filovirus outbreaks caused by Ebola virus (EBOV) and Marburg virus (MARV), pose severe global health threats characterized by high rates of fatal hemorrhagic fever. While species-specific vaccines and therapeutic monoclonal antibodies are approved for Zaire ebolavirus, broadly-active therapeutics remain unavailable, leaving populations vulnerable to MARV and other pathogenic Ebola species, such as Bundibugyo (BDBV) and Sudan (SUDV) ebolaviruses. Here we report a computationally guided, infectious virus validated screening platform for the rapid discovery of broad-spectrum filovirus antivirals. By leveraging quantitative structure-activity relationship (QSAR) models, we screened 142,382 compounds in silico to prioritize 125 high-potential candidates. Subsequent dose-response and viability profiling identified 23 compounds exhibiting potent, low-micromolar pan-filovirus activity and favorable cytotoxicity profiles. Molecular docking indicates these compounds target conserved structural and functional domains--primarily the VP35 and L proteins--which may disrupt essential viral replication and immune antagonism. Furthermore, systematic combinatorial screening revealed three highly synergistic compound pairs, notably NCGC00113249-01 and NCGC00118008-01, demonstrating robust cross-species efficacy. By targeting conserved vulnerabilities across the filovirus family, this integrated in silico and in vitro pipeline provides a scalable framework to rapidly nominate and optimize synergistic therapeutic regimens against both endemic and emerging viral threats including BDBV. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=74 SRC="FIGDIR/small/737586v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@1251baorg.highwire.dtl.DTLVardef@b3a2feorg.highwire.dtl.DTLVardef@191d314org.highwire.dtl.DTLVardef@b8f710_HPS_FORMAT_FIGEXP M_FIG C_FIG

Structure-based drug discovery is known to apply computational methods in a tiered hierarchy, with each layer narrowing the candidate set and refining the binding picture before committing to the next, more expensive step. We present a four-tiered computational benchmarking study evaluating five engines against a panel of 36 compounds targeting B-secretase 1 (BACE1), a validated Alzheimer's disease target with extensive co-crystal ground truth. This study evaluates Flexible Docking and Boltz2 Cofolding as the primary tier, followed by Ensemble Docking, and then Protein-Ligand MD with MM/PBSA and MM/GBSA post-processing. This is then concluded with Relative Binding Free Energy Perturbation (RevFEP) as the terminal refinement layer. Each method was benchmarked against the experimental binding free energies derived from the co-crystal structures spanning -7.85 to -11.35 kcal/mol. Our findings revealed that Flexible Docking reproduced the co-crystal binding mode for 35 of 36 ligands (97.2% within 2.0 A RMSD) but did not rank potency at this resolution. Boltz2 CoFolding provided an orthogonal structural cross-check with a receptor backbone RMSD of 0.293 A against the experimental co-crystal structure. Ensemble Docking identified the optimal receptor conformation for downstream FEP setup. MD with MM/GBSA decomposition identified van der Waals complementarity as the primary potency driver (Pearson r = +0.855, R2 = 0.732 on a 10-compound subset). RevFEP delivered the highest affinity correlation of any method (Pearson r = +0.662, R2 = 0.438, Spearman p = +0.624, mean absolute error 1.02 kcal/mol across all 36 ligands), resolving potency differences within a narrow 3.5 kcal/mol congeneric window that no other engine could discriminate. We characterize what each engine contributes independently and where RevFEP delivers signals no other engine achieves.

Targeting viral macrodomains (Mac) has emerged as a promising strategy for antiviral drug development, especially after the outbreak of COVID-19 that claimed millions of lives worldwide. Several severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Mac1 inhibitors have been reported in the past few years. In the present work, we converted GS-441524 (IC50 of [~]10 M for SARS-CoV-2 Mac1) to KP-S54 (18c), a potent inhibitor of both SARS-CoV-2 Mac1 (IC50: 44 nM) and Middle East respiratory syndrome coronavirus (MERS-CoV) Mac1 (IC50: 91 nM) through an iterative direct-to-biology approach. This approach leverages efficient amide-coupling reaction and the mix-and-read fluorescence polarization (FP) assays where reaction mixtures could be screened directly without purification. Cocrystal structure of a selected derivative (12p) binding to SARS-CoV-2 Mac1 revealed the binding mode, which will guide future drug development against viral macrodomains.

The protein kinase Akt and its isoforms play a crucial role in various diseases. Unique functions of the individual isoforms (Akt1, Akt2, Akt3) might be essential for survival in malignancies. Particularly for Akt2, it was reported that a knock-out led to diabetic phenotype and might be correlated with clinically adverse hyperglycemic effects observed in pan Akt-treatment. Enduring failure of Akt inhibitors in the clinic indicates the necessity for a thorough understanding of the underlying biology, preferably by using highly isoform-selective small molecules. Here we report the structure-guided development of Akt2-selective covalent-allosteric probe molecules, that can be successfully modified within a complex environment using biorthogonal chemistry. Thus, enabling first Akt2-specific pull-down studies and the use in functional studies, such as selective fluorescent labeling in cellular systems. These chemical probes expand our toolbox to dissect the critical questions of Akt2s function in health and disease, thereby paving the way for novel therapeutic strategies based on thorough mechanistic insights.

Monobodies are fibronectin type-III-based binding proteins that specifically bind target proteins and regulate their functions. We previously identified monobodies that selectively recognize either the OPEN or CLOSED conformation of adenylate kinase (Adk), revealing that monobodies can discriminate distinct conformational states of a target protein. However, the molecular basis of OPEN-form recognition has remained unclear because the structure of the complex between an OPEN-form-specific monobody and Adk had not been determined. To address this issue, we determined the crystal structure of the complex between Adk and the OPEN-form-specific monobody OP-4, employing hierarchical clustering analysis of X-ray diffraction datasets. The structure revealed that OP-4 binds to the surface formed by the expanded LID and CORE domains of Adk. Mutations in the interface residues reduced the OP- 4-binding affinity, indicating that the crystallographically identified interface is also relevant in solution. In particular, R123 mutations markedly impaired OP-4 binding. Molecular dynamics simulations further suggested that the R123-D159-R156 hydrogen-bond network is retained in solution and may contribute to efficient complex formation. These findings establish the structural basis for monobody OP-4 binding to open-form Adk and identify the R123-centered interaction network as a key determinant of complex formation. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=153 SRC="FIGDIR/small/742914v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@4b529org.highwire.dtl.DTLVardef@1119ffcorg.highwire.dtl.DTLVardef@1e9469org.highwire.dtl.DTLVardef@1a17eaf_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIThe crystal structure of the OPEN-form adenylate kinase/monobody OP-4 complex was successfully determined. C_LIO_LIThe crystal structure revealed that OP-4 binds to surface formed by the expanded LID and CORE domains in adenylate kinase. C_LIO_LIIsothermal titration calorimetry measurements for adenylate kinase mutants confirmed that the binding modes observed in solution are consistent with those observed in the crystal structure. C_LIO_LIMolecular dynamics simulations suggested that the R123-D159-R156 hydrogen bond network prior to OP-4 binding is important for complex formation. C_LI

Cereblon (CRBN) is widely used in targeted protein degradation, but its ligand space has remained dominated by a narrow set of cyclic imide chemotypes. Here, we show that the accessible CRBN ligand space extends substantially beyond this canonical space. A high-throughput screen of > 40,000 compounds, followed by orthogonal biophysical validation, X-ray crystallography and SAR analyses, identified several chemically distinct ligand classes. These include linear acetyl-based motifs, a phthalide-derived scaffold, steroidal compounds, and a range of bicyclic ligands. They engage CRBN through distinct recognition modes, several of which deviate from the canonical hydrogen-bonding pattern. Steroidal scaffolds were particularly notable: cortisone binds the human CRBN thalidomide-binding domain with an affinity comparable to thalidomide, with its A-ring occupying the tri-tryptophan pocket in a glutarimide-like orientation despite lacking the canonical imide NH donor. SAR within this series showed substantial tolerance for chemical modification and scaffold simplification, raising the possibility that endogenous steroidal metabolites may contribute to the physiological ligand landscape of CRBN. Bicyclic lactams additionally provided synthetically accessible scaffolds with tunable affinity and promising sites for linker attachment. Across the identified ligand classes, none of the tested representatives induced detectable degradation of canonical CRBN neosubstrates, and several showed largely clean proteomic profiles. Together, these findings broaden the chemical, mechanistic and potential physiological landscape of CRBN recognition and provide diverse starting points for alternative, potentially neosubstrate-sparing CRBN recruiters.

GPR183 is an oxysterol-sensing GPCR predominantly expressed in lymphoid organs and tissues. Activation of the receptor by oxysterol 7,25-OHC leads to Gi protein-mediated signaling as well as {beta}-arrestin2 recruitment. GPR183/oxysterol signaling modulates localization of lymphoid cells, consequently the receptor is associated with several inflammation-associated diseases and is an interesting potential drug target. Previously, we reported the discovery of moderately potent G protein-biased partial agonists for GPR183 from a virtual screening based on the scaffold of the antagonist NIBR189. Herein, we present the detailed structure-activity investigations and optimizations, which led to the identification of full agonists for GPR183 with complete bias for Gi protein signaling and low nanomolar potency, including 63 (TUG-2604) with potency and efficacy similar to 7,25-OHC. Notably, 63 was unable to induce migration of human dendritic cells but inhibited migration induced by 7,25-OHC. This compound will be valuable for further explorations of the signaling-specific function and drug target potential of GPR183.