Highly accurate carbohydrate-binding site prediction with DeepGlycanSite.

As the most abundant organic substances in nature, carbohydrates are essential for life. Understanding how carbohydrates regulate proteins in the physiological and pathological processes presents opportunities to address crucial biological problems and develop new therapeutics. However, the diversity and complexity of carbohydrates pose a challenge in experimentally identifying the sites where carbohydrates bind to and act on proteins. Here, we introduce a deep learning model, DeepGlycanSite, capable of accurately predicting carbohydrate-binding sites on a given protein structure. Incorporating geometric and evolutionary features of proteins into a deep equivariant graph neural network with the transformer architecture, DeepGlycanSite remarkably outperforms previous state-of-the-art methods and effectively predicts binding sites for diverse carbohydrates. Integrating with a mutagenesis study, DeepGlycanSite reveals the guanosine-5'-diphosphate-sugar-recognition site of an important G-protein coupled receptor. These findings demonstrate DeepGlycanSite is invaluable for carbohydrate-binding site prediction and could provide insights into molecular mechanisms underlying carbohydrate-regulation of therapeutically important proteins.

Structural basis for recognition of 26RFa by the pyroglutamylated RFamide peptide receptor.

The neuropeptide 26RFa, a member of the RF-amide peptide family, activates the pyroglutamylated RF-amide peptide receptor (QRFPR), a class A GPCR. The 26RFa/QRFPR system plays critical roles in energy homeostasis, making QRFPR an attractive drug target for treating obesity, diabetes, and eating disorders. However, the lack of structural information has hindered our understanding of the peptide recognition and regulatory mechanism of QRFPR, impeding drug design efforts. In this study, we determined the cryo-EM structure of the Gq-coupled QRFPR bound to 26RFa. The structure reveals a unique assembly mode of the extracellular region of the receptor and the N-terminus of the peptide, and elucidates the recognition mechanism of the C-terminal heptapeptide of 26RFa by the transmembrane binding pocket of QRFPR. The study also clarifies the similarities and distinctions in the binding pattern of the RF-amide moiety in five RF-amide peptides and the RY-amide segment in neuropeptide Y. These findings deepen our understanding of the RF-amide peptide recognition, aiding in the rational design of drugs targeting QRFPR and other RF-amide peptide receptors.

Dimerization and antidepressant recognition at noradrenaline transporter.

The noradrenaline transporter has a pivotal role in regulating neurotransmitter balance and is crucial for normal physiology and neurobiology1. Dysfunction of noradrenaline transporter has been implicated in numerous neuropsychiatric diseases, including depression and attention deficit hyperactivity disorder2. Here we report cryo-electron microscopy structures of noradrenaline transporter in apo and substrate-bound forms, and as complexes with six antidepressants. The structures reveal a noradrenaline transporter dimer interface that is mediated predominantly by cholesterol and lipid molecules. The substrate noradrenaline binds deep in the central binding pocket, and its amine group interacts with a conserved aspartate residue. Our structures also provide insight into antidepressant recognition and monoamine transporter selectivity. Together, these findings advance our understanding of noradrenaline transporter regulation and inhibition, and provide templates for designing improved antidepressants to treat neuropsychiatric disorders.

Mechanisms of ligand recognition and activation of melanin-concentrating hormone receptors.

Melanin-concentrating hormone (MCH) is a cyclic neuropeptide that regulates food intake, energy balance, and other physiological functions by stimulating MCHR1 and MCHR2 receptors, both of which are class A G protein-coupled receptors. MCHR1 predominately couples to inhibitory G protein, Gi/o, and MCHR2 can only couple to Gq/11. Here we present cryo-electron microscopy structures of MCH-activated MCHR1 with Gi and MCH-activated MCHR2 with Gq at the global resolutions of 3.01 Å and 2.40 Å, respectively. These structures reveal that MCH adopts a consistent cysteine-mediated hairpin loop configuration when bound to both receptors. A central arginine from the LGRVY core motif between the two cysteines of MCH penetrates deeply into the transmembrane pocket, triggering receptor activation. Integrated with mutational and functional insights, our findings elucidate the molecular underpinnings of ligand recognition and MCH receptor activation and offer a structural foundation for targeted drug design.

Cryo-electron microscopy for GPCR research and drug discovery in endocrinology and metabolism.

G protein-coupled receptors (GPCRs) are the largest family of cell surface receptors, with many GPCRs having crucial roles in endocrinology and metabolism. Cryogenic electron microscopy (cryo-EM) has revolutionized the field of structural biology, particularly regarding GPCRs, over the past decade. Since the first pair of GPCR structures resolved by cryo-EM were published in 2017, the number of GPCR structures resolved by cryo-EM has surpassed the number resolved by X-ray crystallography by 30%, reaching >650, and the number has doubled every ~0.63 years for the past 6 years. At this pace, it is predicted that the structure of 90% of all human GPCRs will be completed within the next 5-7 years. This Review highlights the general structural features and principles that guide GPCR ligand recognition, receptor activation, G protein coupling, arrestin recruitment and regulation by GPCR kinases. The Review also highlights the diversity of GPCR allosteric binding sites and how allosteric ligands could dictate biased signalling that is selective for a G protein pathway or an arrestin pathway. Finally, the authors use the examples of glycoprotein hormone receptors and glucagon-like peptide 1 receptor to illustrate the effect of cryo-EM on understanding GPCR biology in endocrinology and metabolism, as well as on GPCR-related endocrine diseases and drug discovery.

Enhancing geometric representations for molecules with equivariant vector-scalar interactive message passing.

Geometric deep learning has been revolutionizing the molecular modeling field. Despite the state-of-the-art neural network models are approaching ab initio accuracy for molecular property prediction, their applications, such as drug discovery and molecular dynamics (MD) simulation, have been hindered by insufficient utilization of geometric information and high computational costs. Here we propose an equivariant geometry-enhanced graph neural network called ViSNet, which elegantly extracts geometric features and efficiently models molecular structures with low computational costs. Our proposed ViSNet outperforms state-of-the-art approaches on multiple MD benchmarks, including MD17, revised MD17 and MD22, and achieves excellent chemical property prediction on QM9 and Molecule3D datasets. Furthermore, through a series of simulations and case studies, ViSNet can efficiently explore the conformational space and provide reasonable interpretability to map geometric representations to molecular structures.

ASD2023: towards the integrating landscapes of allosteric knowledgebase.

Allosteric regulation, induced by perturbations at an allosteric site topographically distinct from the orthosteric site, is one of the most direct and efficient ways to fine-tune macromolecular function. The Allosteric Database (ASD; accessible online at http://mdl.shsmu.edu.cn/ASD) has been systematically developed since 2009 to provide comprehensive information on allosteric regulation. In recent years, allostery has seen sustained growth and wide-ranging applications in life sciences, from basic research to new therapeutics development, while also elucidating emerging obstacles across allosteric research stages. To overcome these challenges and maintain high-quality data center services, novel features were curated in the ASD2023 update: (i) 66 589 potential allosteric sites, covering > 80% of the human proteome and constituting the human allosteric pocketome; (ii) 748 allosteric protein-protein interaction (PPI) modulators with clear mechanisms, aiding protein machine studies and PPI-targeted drug discovery; (iii) 'Allosteric Hit-to-Lead,' a pioneering dataset providing panoramic views from 87 well-defined allosteric hits to 6565 leads and (iv) 456 dualsteric modulators for exploring the simultaneous regulation of allosteric and orthosteric sites. Meanwhile, ASD2023 maintains a significant growth of foundational allosteric data. Based on these efforts, the allosteric knowledgebase is progressively evolving towards an integrated landscape, facilitating advancements in allosteric target identification, mechanistic exploration and drug discovery.

Identification of a carbohydrate recognition motif of purinergic receptors.

As a major class of biomolecules, carbohydrates play indispensable roles in various biological processes. However, it remains largely unknown how carbohydrates directly modulate important drug targets, such as G-protein coupled receptors (GPCRs). Here, we employed P2Y purinoceptor 14 (P2Y14), a drug target for inflammation and immune responses, to uncover the sugar nucleotide activation of GPCRs. Integrating molecular dynamics simulation with functional study, we identified the uridine diphosphate (UDP)-sugar-binding site on P2Y14, and revealed that a UDP-glucose might activate the receptor by bridging the transmembrane (TM) helices 2 and 7. Between TM2 and TM7 of P2Y14, a conserved salt bridging chain (K2.60-D2.64-K7.35-E7.36 [KDKE]) was identified to distinguish different UDP-sugars, including UDP-glucose, UDP-galactose, UDP-glucuronic acid, and UDP-N-acetylglucosamine. We identified the KDKE chain as a conserved functional motif of sugar binding for both P2Y14 and P2Y purinoceptor 12 (P2Y12), and then designed three sugar nucleotides as agonists of P2Y12. These results not only expand our understanding for activation of purinergic receptors but also provide insights for the carbohydrate drug development for GPCRs.

Sugars and other types of carbohydrates are biomolecules which play a range of key roles in the body. In particular, they are important messengers that help to coordinate immune responses. For example, a carbohydrate known as UDP-Glucose (a kind of UDP-sugar) can activate P2Y14, a receptor studded through the surface of many cells; this event then triggers a cascade of molecular events associated with asthma, kidney injury and lung inflammation. Yet it remains unclear how exactly UDP-Glucose recognizes P2Y14 ­ and, more broadly, how carbohydrates interact with purinergic receptors, the class of proteins that P2Y14 belongs to. To examine this question, Zhao et al. combined functional experiments in the laboratory with molecular dynamics simulations, a computational approach. This work revealed that UDP-Glucose may activate P2Y14 by bridging its segments anchored within the cell membrane. A component of P2Y14, known as the KDKE chain, was found to have an important role in distinguishing between highly similar types of UDP-sugars. This allowed Zhao et al. to design three sugar molecules which could activate another purinergic receptor that also contained a KDKE chain. Purinergic receptors are promising therapeutic targets. A finer understanding of how they recognise the molecules that activate them is therefore important to be able to identify and design new drug compounds.

Discovery of a novel GPR35 agonist with high and equipotent species potency for oral treatment of IBD.

The G protein-coupled receptor 35 (GPR35) has been identified as a potential target in the treatment of inflammatory bowel disease (IBD). However, the lack of high and equipotent agonists on both human and mouse GPR35 has limited the in vivo study of GPR35 agonists in mouse models of IBD. In this study, structural modifications to lodoxamide provides a series of high and equivalent agonists on human, mouse, and rat GPR35. These molecules eliminate the species selectivity of human to mouse and rat orthologs that have been prevalent with GPR35 agonists including lodoxamide. The cLogP properties are also optimized to make the compounds more obedient to drug-like rules, yielding compound 4b (cLogP = 2.41), which activates human, mouse or rat GPR35 with EC50 values of 76.0, 63.7 and 77.8 nM, respectively. Oral administration of compound 4b at 20 mg/kg alleviates clinical symptoms of DSS-induced IBD in mice, and is slightly more effective than 5-ASA at 200 mg/kg. In summary, it can serve as a new start point for exploiting more potent GPR35 agonists without species differences for the treatment of IBD, and warrants further study.

Molecular recognition of niacin and lipid-lowering drugs by the human hydroxycarboxylic acid receptor 2.

Niacin, an age-old lipid-lowering drug, acts through the hydroxycarboxylic acid receptor 2 (HCAR2), a G-protein-coupled receptor (GPCR). Yet, its use is hindered by side effects like skin flushing. To address this, specific HCAR2 agonists, like MK-6892 and GSK256073, with fewer adverse effects have been created. However, the activation mechanism of HCAR2 by niacin and these new agonists is not well understood. Here, we present three cryoelectron microscopy structures of Gi-coupled HCAR2 bound to niacin, MK-6892, and GSK256073. Our findings show that different ligands induce varying binding pockets in HCAR2, influenced by aromatic amino acid clusters (W91ECL1, H1614.59, W1885.38, H1895.39, and F1935.43) from receptors ECL1, TM4, and TM5. Additionally, conserved residues R1113.36 and Y2847.43, unique to the HCA receptor family, likely initiate activation signal propagation in HCAR2. This study provides insights into ligand recognition, receptor activation, and G protein coupling mediated by HCAR2, laying the groundwork for developing HCAR2-targeted drugs.

Chiral Sensing of Tryptophan Enantiomers Based on the Enzyme Mimics of ß-Cyclodextrin-Modified Sulfur Quantum Dots.

Chiral recognition of amino acid plays a significant role in pharmaceutical, medical, and food science. This study describes a chiral sensing system of ß-cyclodextrin (ß-CD)-coated sulfur quantum dots (CD-SQDs) for the selective fluorescence recognition of tryptophan (Trp) enantiomers. CD-SQDs were prepared by a facile assembly fission method and could selectively recognize L-Trp by the different binding ability between L/D-Trp and ß-CD. The inclusion of L-Trp and the stereoselective catalysis of CD-SQDs enzyme mimics cause the increased fluorescence intensity of CD-SQDs, which has a linear response ranging from 10 to 500 nM and the detection limit as 2.3 nM. CD-SQDs also show great selectivity for L-Trp from the commercial compound amino acid injection. The study could provide an effective method for the chiral recognition of amino acid enantiomers based on the catalytic activity of nanoenzymes.

Recognition of methamphetamine and other amines by trace amine receptor TAAR1.

Trace amine-associated receptor 1 (TAAR1), the founding member of a nine-member family of trace amine receptors, is responsible for recognizing a range of biogenic amines in the brain, including the endogenous ß-phenylethylamine (ß-PEA)1 as well as methamphetamine2, an abused substance that has posed a severe threat to human health and society3. Given its unique physiological role in the brain, TAAR1 is also an emerging target for a range of neurological disorders including schizophrenia, depression and drug addiction2,4,5. Here we report structures of human TAAR1-G-protein complexes bound to methamphetamine and ß-PEA as well as complexes bound to RO5256390, a TAAR1-selective agonist, and SEP-363856, a clinical-stage dual agonist for TAAR1 and serotonin receptor 5-HT1AR (refs. 6,7). Together with systematic mutagenesis and functional studies, the structures reveal the molecular basis of methamphetamine recognition and underlying mechanisms of ligand selectivity and polypharmacology between TAAR1 and other monoamine receptors. We identify a lid-like extracellular loop 2 helix/loop structure and a hydrogen-bonding network in the ligand-binding pockets, which may contribute to the ligand recognition in TAAR1. These findings shed light on the ligand recognition mode and activation mechanism for TAAR1 and should guide the development of next-generation therapeutics for drug addiction and various neurological disorders.

Loops Mediate Agonist-Induced Activation of the Stimulator of Interferon Genes Protein.

The stimulator of interferon genes (STING) is an important therapeutic target for cancer diseases. The activated STING recruits downstream tank-binding kinase 1 (TBK1) to trigger several important immune responses. However, the molecular mechanism of how agonist molecules mediate the STING-TBK1 interactions remains elusive. Here, we performed molecular dynamics simulations to capture the conformational changes of STING and TBK1 upon agonist binding. Our simulations revealed that multiple helices (α5-α7) and especially three loops (loop 6, loop 8, and C-terminal tail) of STING participated in the allosteric mediation of the STING-TBK1 interactions. Consistent results were also observed in the simulations of the constitutive activating mutant of STING (R284S). We further identified α5 as a key region in this agonist-induced activation mechanism of STING. Free-energy perturbation calculations of multiple STING agonists demonstrated that an alkynyl group targeting α5 is a determinant for agonist activities. These results not only offer deeper insights into the agonist-induced allosteric mediation of STING-TKB1 interactions but also provide a guidance for future drug development of this important therapeutic target.

GPCR activation and GRK2 assembly by a biased intracellular agonist.

Phosphorylation of G-protein-coupled receptors (GPCRs) by GPCR kinases (GRKs) desensitizes G-protein signalling and promotes arrestin signalling, which is also modulated by biased ligands1-6. The molecular assembly of GRKs on GPCRs and the basis of GRK-mediated biased signalling remain largely unknown owing to the weak GPCR-GRK interactions. Here we report the complex structure of neurotensin receptor 1 (NTSR1) bound to GRK2, Gαq and the arrestin-biased ligand SBI-5537. The density map reveals the arrangement of the intact GRK2 with the receptor, with the N-terminal helix of GRK2 docking into the open cytoplasmic pocket formed by the outward movement of the receptor transmembrane helix 6, analogous to the binding of the G protein to the receptor. SBI-553 binds at the interface between GRK2 and NTSR1 to enhance GRK2 binding. The binding mode of SBI-553 is compatible with arrestin binding but clashes with the binding of Gαq protein, thus providing a mechanism for its arrestin-biased signalling capability. In sum, our structure provides a rational model for understanding the details of GPCR-GRK interactions and GRK2-mediated biased signalling.

AIMD-Chig: Exploring the conformational space of a 166-atom protein Chignolin with ab initio molecular dynamics.

Molecular dynamics (MD) simulations have revolutionized the modeling of biomolecular conformations and provided unprecedented insight into molecular interactions. Due to the prohibitive computational overheads of ab initio simulation for large biomolecules, dynamic modeling for proteins is generally constrained on force field with molecular mechanics, which suffers from low accuracy as well as ignores the electronic effects. Here, we report AIMD-Chig, an MD dataset including 2 million conformations of 166-atom protein Chignolin sampled at the density functional theory (DFT) level with 7,763,146 CPU hours. 10,000 conformations were initialized covering the whole conformational space of Chignolin, including folded, unfolded, and metastable states. Ab initio simulations were driven by M06-2X/6-31 G* with a Berendsen thermostat at 340 K. We reported coordinates, energies, and forces for each conformation. AIMD-Chig brings the DFT level conformational space exploration from small organic molecules to real-world proteins. It can serve as the benchmark for developing machine learning potentials for proteins and facilitate the exploration of protein dynamics with ab initio accuracy.

Improving machine learning force fields for molecular dynamics simulations with fine-grained force metrics.

Machine learning force fields (MLFFs) have gained popularity in recent years as they provide a cost-effective alternative to ab initio molecular dynamics (MD) simulations. Despite a small error on the test set, MLFFs inherently suffer from generalization and robustness issues during MD simulations. To alleviate these issues, we propose global force metrics and fine-grained metrics from element and conformation aspects to systematically measure MLFFs for every atom and every conformation of molecules. We selected three state-of-the-art MLFFs (ET, NequIP, and ViSNet) and comprehensively evaluated on aspirin, Ac-Ala3-NHMe, and Chignolin MD datasets with the number of atoms ranging from 21 to 166. Driven by the trained MLFFs on these molecules, we performed MD simulations from different initial conformations, analyzed the relationship between the force metrics and the stability of simulation trajectories, and investigated the reason for collapsed simulations. Finally, the performance of MLFFs and the stability of MD simulations can be further improved guided by the proposed force metrics for model training, specifically training MLFF models with these force metrics as loss functions, fine-tuning by reweighting samples in the original dataset, and continued training by recruiting additional unexplored data.

Conserved class B GPCR activation by a biased intracellular agonist.

Class B G-protein-coupled receptors (GPCRs), including glucagon-like peptide 1 receptor (GLP1R) and parathyroid hormone 1 receptor (PTH1R), are important drug targets1-5. Injectable peptide drugs targeting these receptors have been developed, but orally available small-molecule drugs remain under development6,7. Here we report the high-resolution structure of human PTH1R in complex with the stimulatory G protein (Gs) and a small-molecule agonist, PCO371, which reveals an unexpected binding mode of PCO371 at the cytoplasmic interface of PTH1R with Gs. The PCO371-binding site is totally different from all binding sites previously reported for small molecules or peptide ligands in GPCRs. The residues that make up the PCO371-binding pocket are conserved in class B GPCRs, and a single alteration in PTH2R and two residue alterations in GLP1R convert these receptors to respond to PCO371. Functional assays reveal that PCO371 is a G-protein-biased agonist that is defective in promoting PTH1R-mediated arrestin signalling. Together, these results uncover a distinct binding site for designing small-molecule agonists for PTH1R and possibly other members of the class B GPCRs and define a receptor conformation that is specific only for G-protein activation but not arrestin signalling. These insights should facilitate the design of distinct types of class B GPCR small-molecule agonist for various therapeutic indications.