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The σ 2 receptor has attracted intense interest in cancer imaging 1 , psychiatric disease 2 , neuropathic pain 3 – 5 and other areas of biology 6 , 7 . Here we determined the crystal structure of this receptor in complex with the clinical candidate roluperidone 2 and the tool compound PB28 8 . These structures templated a large-scale docking screen of 490 million virtual molecules, of which 484 compounds were synthesized and tested. We identified 127 new chemotypes with affinities superior to 1 μM, 31 of which had affinities superior to 50 nM. The hit rate fell smoothly and monotonically with docking score. We optimized three hits for potency and selectivity, and achieved affinities that ranged from 3 to 48 nM, with up to 250-fold selectivity versus the σ 1 receptor. Crystal structures of two ligands bound to the σ 2 receptor confirmed the docked poses. To investigate the contribution of the σ 2 receptor in pain, two potent σ 2 -selective ligands and one potent σ 1 /σ 2 non-selective ligand were tested for efficacy in a mouse model of neuropathic pain. All three ligands showed time-dependent decreases in mechanical hypersensitivity in the spared nerve injury model 9 , suggesting that the σ 2 receptor has a role in nociception. This study illustrates the opportunities for rapid discovery of in vivo probes through structure-based screens of ultra large libraries, enabling study of underexplored areas of biology. Crystal structures of the σ 2 receptor are determined and used to perform a docking screen of nearly 500 million molecules, identifying σ 2 -selective ligands and providing insight into the role of σ 2 in neuropathic pain.

One week after fertilization, human embryos implant into the uterus. This event requires the embryo to form a blastocyst consisting of a sphere encircling a cavity lodging the embryo proper. Stem cells can form a blastocyst model that we called a blastoid 1 . Here we show that naive human pluripotent stem cells cultured in PXGL medium 2 and triply inhibited for the Hippo, TGF-β and ERK pathways efficiently (with more than 70% efficiency) form blastoids generating blastocyst-stage analogues of the three founding lineages (more than 97% trophectoderm, epiblast and primitive endoderm) according to the sequence and timing of blastocyst development. Blastoids spontaneously form the first axis, and we observe that the epiblast induces the local maturation of the polar trophectoderm, thereby endowing blastoids with the capacity to directionally attach to hormonally stimulated endometrial cells, as during implantation. Thus, we propose that such a human blastoid is a faithful, scalable and ethical model for investigating human implantation and development 3 , 4 . Blastoids derived from naive PXGL-cultured human pluripotent stem cells in which Hippo, TGF-β and ERK pathways are inhibited closely recapitulate aspects of blastocyst development, form cells resembling blastocyst-stage cells and thus provide a model system for implantation and development studies.

There is considerable interest in screening ultralarge chemical libraries for ligand discovery, both empirically and computationally 1 – 4 . Efforts have focused on readily synthesizable molecules, inevitably leaving many chemotypes unexplored. Here we investigate structure-based docking of a bespoke virtual library of tetrahydropyridines—a scaffold that is poorly sampled by a general billion-molecule virtual library but is well suited to many aminergic G-protein-coupled receptors. Using three inputs, each with diverse available derivatives, a one pot C–H alkenylation, electrocyclization and reduction provides the tetrahydropyridine core with up to six sites of derivatization 5 – 7 . Docking a virtual library of 75 million tetrahydropyridines against a model of the serotonin 5-HT 2A receptor (5-HT 2A R) led to the synthesis and testing of 17 initial molecules. Four of these molecules had low-micromolar activities against either the 5-HT 2A or the 5-HT 2B receptors. Structure-based optimization led to the 5-HT 2A R agonists ( R ) - 69 and ( R ) - 70, with half-maximal effective concentration values of 41 nM and 110 nM, respectively, and unusual signalling kinetics that differ from psychedelic 5-HT 2A R agonists. Cryo-electron microscopy structural analysis confirmed the predicted binding mode to 5-HT 2A R. The favourable physical properties of these new agonists conferred high brain permeability, enabling mouse behavioural assays. Notably, neither had psychedelic activity, in contrast to classic 5-HT 2A R agonists, whereas both had potent antidepressant activity in mouse models and had the same efficacy as antidepressants such as fluoxetine at as low as 1/40th of the dose. Prospects for using bespoke virtual libraries to sample pharmacologically relevant chemical space will be considered. New agonists of the serotonin 5-HT 2A receptor (5-HT 2A R) confer high brain permeability and antidepressant activity and—in contrast to classic 5-HT 2A R agonists—lack psychedelic activity.

The rational design of novel molecules with the desired bioactivity is a critical but challenging task in drug discovery, especially when treating a novel target family or understudied targets. We propose a Pharmacophore-Guided deep learning approach for bioactive Molecule Generation (PGMG). Through the guidance of pharmacophore, PGMG provides a flexible strategy for generating bioactive molecules. PGMG uses a graph neural network to encode spatially distributed chemical features and a transformer decoder to generate molecules. A latent variable is introduced to solve the many-to-many mapping between pharmacophores and molecules to improve the diversity of the generated molecules. Compared to existing methods, PGMG generates molecules with strong docking affinities and high scores of validity, uniqueness, and novelty. In the case studies, we use PGMG in a ligand-based and structure-based drug de novo design. Overall, the flexibility and effectiveness make PGMG a useful tool to accelerate the drug discovery process. Designing novel molecules with desired bioactivity is a critical challenge in drug discovery, particularly for novel or understudied targets. The authors propose a pharmacophore-guided deep learning approach PGMG to generate diverse active-like molecules with limited activity data.

The diverse collection of microorganisms that inhabit the gastrointestinal tract, collectively called the gut microbiota, profoundly influences many aspects of host physiology, including nutrient metabolism, resistance to infection and immune system development. Studies investigating the gut–brain axis demonstrate a critical role for the gut microbiota in orchestrating brain development and behavior, and the immune system is emerging as an important regulator of these interactions. Intestinal microbes modulate the maturation and function of tissue-resident immune cells in the CNS. Microbes also influence the activation of peripheral immune cells, which regulate responses to neuroinflammation, brain injury, autoimmunity and neurogenesis. Accordingly, both the gut microbiota and immune system are implicated in the etiopathogenesis or manifestation of neurodevelopmental, psychiatric and neurodegenerative diseases, such as autism spectrum disorder, depression and Alzheimer's disease. In this review, we discuss the role of CNS-resident and peripheral immune pathways in microbiota–gut–brain communication during health and neurological disease.

Cancer metabolism is rewired to support cell survival in response to intrinsic and environmental stressors. Identification of strategies to target these adaptions is an area of active research. We previously described a cytosolic aspartate aminotransaminase (GOT1)-driven pathway in pancreatic cancer used to maintain redox balance. Here, we sought to identify metabolic dependencies following GOT1 inhibition to exploit this feature of pancreatic cancer and to provide additional insight into regulation of redox metabolism. Using pharmacological methods, we identify cysteine, glutathione, and lipid antioxidant function as metabolic vulnerabilities following GOT1 withdrawal. We demonstrate that targeting any of these pathways triggers ferroptosis, an oxidative, iron-dependent form of cell death, in GOT1 knockdown cells. Mechanistically, we reveal that GOT1 inhibition represses mitochondrial metabolism and promotes a catabolic state. Consequently, we find that this enhances labile iron availability through autophagy, which potentiates the activity of ferroptotic stimuli. Overall, our study identifies a biochemical connection between GOT1, iron regulation, and ferroptosis. The aspartate aminotransaminase GOT1 is important for maintaining redox balance. Here, the authors show that inhibition of GOT1 in pancreatic cancer cells leads to cell death via ferroptosis.

Drug development based on target proteins has been a successful approach in recent decades. However, the conventional structure-based drug design (SBDD) pipeline is a complex, human-engineered process with multiple independently optimized steps. Here, we propose a sequence-to-drug concept for computational drug design based on protein sequence information by end-to-end differentiable learning. We validate this concept in three stages. First, we design TransformerCPI2.0 as a core tool for the concept, which demonstrates generalization ability across proteins and compounds. Second, we interpret the binding knowledge that TransformerCPI2.0 learned. Finally, we use TransformerCPI2.0 to discover new hits for challenging drug targets, and identify new target for an existing drug based on an inverse application of the concept. Overall, this proof-of-concept study shows that the sequence-to-drug concept adds a perspective on drug design. It can serve as an alternative method to SBDD, particularly for proteins that do not yet have high-quality 3D structures available. Conventional structure-based drug design pipeline is a complex, human-engineered process with multiple independently optimized steps. Here, the authors report a sequence-to-drug concept that discovers drug-like small molecule modulators directly from protein sequences.

The ubiquitin E3 ligase substrate adapter cereblon (CRBN) is a target of thalidomide and lenalidomide 1 , therapeutic agents used in the treatment of haematopoietic malignancies 2 – 4 and as ligands for targeted protein degradation 5 – 7 . These agents are proposed to mimic a naturally occurring degron; however, the structural motif recognized by the thalidomide-binding domain of CRBN remains unknown. Here we report that C-terminal cyclic imides, post-translational modifications that arise from intramolecular cyclization of glutamine or asparagine residues, are physiological degrons on substrates for CRBN. Dipeptides bearing the C-terminal cyclic imide degron substitute for thalidomide when embedded within bifunctional chemical degraders. Addition of the degron to the C terminus of proteins induces CRBN-dependent ubiquitination and degradation in vitro and in cells. C-terminal cyclic imides form adventitiously on physiologically relevant timescales throughout the human proteome to afford a degron that is endogenously recognized and removed by CRBN. The discovery of the C-terminal cyclic imide degron defines a regulatory process that may affect the physiological function and therapeutic engagement of CRBN. C-terminal cyclic imides are physiological degrons that enable the ubiquitin E3 ligase adapter protein cereblon to target substrates for degradation.

Molecular glue compounds induce protein–protein interactions that, in the context of a ubiquitin ligase, lead to protein degradation 1 . Unlike traditional enzyme inhibitors, these molecular glue degraders act substoichiometrically to catalyse the rapid depletion of previously inaccessible targets 2 . They are clinically effective and highly sought-after, but have thus far only been discovered serendipitously. Here, through systematically mining databases for correlations between the cytotoxicity of 4,518 clinical and preclinical small molecules and the expression levels of E3 ligase components across hundreds of human cancer cell lines 3 – 5 , we identify CR8—a cyclin-dependent kinase (CDK) inhibitor 6 —as a compound that acts as a molecular glue degrader. The CDK-bound form of CR8 has a solvent-exposed pyridyl moiety that induces the formation of a complex between CDK12–cyclin K and the CUL4 adaptor protein DDB1, bypassing the requirement for a substrate receptor and presenting cyclin K for ubiquitination and degradation. Our studies demonstrate that chemical alteration of surface-exposed moieties can confer gain-of-function glue properties to an inhibitor, and we propose this as a broader strategy through which target-binding molecules could be converted into molecular glues. The cyclin-dependent kinase inhibitor CR8 acts as a molecular glue compound by inducing the formation of a complex between CDK12–cyclin K and DDB1, which results in the ubiquitination and degradation of cyclin K.

Primary ovarian insufficiency (POI) is a clinical syndrome of ovarian dysfunction characterized by premature exhaustion of primordial follicles. POI causes infertility, severe daily life disturbances and long-term health risks. However, the underlying mechanism remains largely unknown. We previously identified a Basonuclin 1 ( BNC1 ) mutation from a large Chinese POI pedigree and found that mice with targeted Bnc1 mutation exhibit symptoms of POI. In this study, we found that BNC1 plays key roles in ovarian reserve and maintaining lipid metabolism and redox homeostasis in oocytes during follicle development. Deficiency of BNC1 results in premature follicular activation and excessive follicular atresia. Mechanistically, BNC1 deficiency triggers oocyte ferroptosis via the NF2-YAP pathway. We demonstrated that pharmacologic inhibition of YAP signaling or ferroptosis significantly rescues Bnc1 mutation-induced POI. These findings uncover a pathologic mechanism of POI based on BNC1 deficiency and suggest YAP and ferroptosis inhibitors as potential therapeutic targets for POI. Primary ovarian insufficiency (POI) is a clinical syndrome of ovarian dysfunction that results in infertility. Here they show that BCN1 mutation results in premature ovarian follicle activation and atresia through dysregulation of ferroptosis.