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The glucagon-like peptide-1 receptor (GLP-1R), which belongs to the class B1 G protein-coupled receptor (GPCR) family, is an important target for treatment of metabolic disorders, including type 2 diabetes and obesity. The growing interest in GLP-1R-based therapies is driven by the development of various functional agonists as well as the huge commercial market. Thus, understanding the structural details of ligand-induced signaling are important for developing improved GLP-1R drugs. Here, we investigated the conformational dynamics of the receptor in complex with a selection of prototypical functional agonists, including CHU-128 (small molecule-biased), danuglipron (small molecule balanced), and Peptide 19 (peptide balanced), which exhibit unique, distinct binding modes and induced helix packing. Furthermore, our all-atom molecular dynamics (MD) simulations revealed atomic feature how different those ligands led to signaling pathway preference. Our findings offer valuable insights into the mechanistic principle of GLP-1R activation, which are helpful for the rational design of next-generation GLP-1R drug molecules.

New drug discovery has been acknowledged as a complicated, expensive, time-consuming, and challenging project. It has been estimated that around 12 years and 2.7 billion USD, on average, are demanded for a new drug discovery traditional drug development pipeline. How to reduce the research cost and speed up the development process of new drug discovery has become a challenging, urgent question for the pharmaceutical industry. Computer-aided drug discovery (CADD) has emerged as a powerful, and promising technology for faster, cheaper, and more effective drug design. Recently, the rapid growth of computational tools for drug discovery, including anticancer therapies, has exhibited a significant and outstanding impact on anticancer drug design, and has also provided fruitful insights into the area of cancer therapy. In this work, we discussed the different subareas of the computer-aided drug discovery process with a focus on anticancer drugs.

Predicting protein-ligand binding free energy rapidly and accurately remains a challenging question in modern drug discovery. Molecular mechanics/Poisson-Boltzmann (Generalized Born) surface area (MM/PB(GB)SA) has emerged as an essential tool for accelerating cost-efficient binding free energy calculation. This study presents benchmarks with three membrane-bound protein systems and six soluble protein systems. Different parameters were sampled for different benchmarks to explore the highest accuracy. These include ligand charges, protein force fields, extra points, GB models, nonpolar optimization methods, internal dielectric constants and membrane dielectric constants. Comparisons of accuracy were made between MM/PB(GB)SA, docking and free energy perturbation (FEP). The results reveal a competitive performance between MM/PB(GB)SA and FEP. In summary, MM/PB(GB)SA is a powerful approach to predict ligand binding free energy rapidly and accurately. Parameters of MM/PB(GB)SA calculations, such as the GB models and membrane dielectric constants, need to be optimized for different systems. This method can be served as a powerful tool for drug design.

Pentameric ligand-gated ion channels (pLGICs) of the Cys-loop receptor family are key players in fast signal transduction throughout the nervous system. They have been shown to be modulated by the lipid environment, however the underlying mechanism is not well understood. We report three structures of the Cys-loop 5-HT 3A serotonin receptor (5HT 3 R) reconstituted into saposin-based lipid bilayer discs: a symmetric and an asymmetric apo state, and an asymmetric agonist-bound state. In comparison to previously published 5HT 3 R conformations in detergent, the lipid bilayer stabilises the receptor in a more tightly packed, ‘coupled’ state, involving a cluster of highly conserved residues. In consequence, the agonist-bound receptor conformation adopts a wide-open pore capable of conducting sodium ions in unbiased molecular dynamics (MD) simulations. Taken together, we provide a structural basis for the modulation of 5HT 3 R by the membrane environment, and a model for asymmetric activation of the receptor. Pentameric ligand-gated ion channels (pLGICs) are key players in neurotransmission and have been shown to be modulated by the lipid environment, however the underlying mechanism is not well understood. Here, the authors report structures of the pLGIC 5-HT 3A serotonin receptor reconstituted into lipid bilayer discs and reveal lipid–protein interactions as well as asymmetric activation of the homopentameric receptor.

G protein-coupled receptors (GPCRs) are the largest human membrane protein family that transduce extracellular signals into cellular responses. They are major pharmacological targets, with approximately 26% of marketed drugs targeting GPCRs, primarily at their orthosteric binding site. Despite their prominence, predicting the pharmacological effects of novel GPCR-targeting drugs remains challenging due to the complex functional dynamics of these receptors. Recent advances in X-ray crystallography, cryo-electron microscopy, spectroscopic techniques and molecular simulations have enhanced our understanding of receptor conformational dynamics and ligand interactions with GPCRs. These developments have revealed novel ligand-binding modes, mechanisms of action and druggable pockets. In this Review, we highlight such aspects for recently discovered small-molecule drugs and drug candidates targeting GPCRs, focusing on three categories: allosteric modulators, biased ligands, and bivalent and bitopic compounds. Although studies so far have largely been retrospective, integrating structural data on ligand-induced receptor functional dynamics into the drug discovery pipeline has the potential to guide the identification of drug candidates with specific abilities to modulate GPCR interactions with intracellular effector proteins such as G proteins and β-arrestins, enabling more tailored selectivity and efficacy profiles. Recent advances in structural biology techniques and computational simulations have enhanced our understanding of the conformational dynamics of G protein-coupled receptors and their interactions with ligands. This Review highlights how such advances may be used in the discovery and optimization of drugs that target G protein-coupled receptors, focusing on three categories: allosteric modulators, biased ligands, and bivalent and bitopic compounds.

Neural networks and deep learning have been successfully applied to tackle problems in drug discovery with increasing accuracy over time. There are still many challenges and opportunities to improve molecular property predictions with satisfactory accuracy even further. Here, we proposed a deep-learning architecture model, namely Bidirectional long short-term memory with Channel and Spatial Attention network (BCSA), of which the training process is fully data-driven and end to end. It is based on data augmentation and SMILES tokenization technology without relying on auxiliary knowledge, such as complex spatial structure. In addition, our model takes the advantages of the long- and short-term memory network (LSTM) in sequence processing. The embedded channel and spatial attention modules in turn specifically identify the prime factors in the SMILES sequence for predicting properties. The model was further improved by Bayesian optimization. In this work, we demonstrate that the trained BSCA model is capable of predicting aqueous solubility. Furthermore, our proposed method shows noticeable superiorities and competitiveness in predicting oil–water partition coefficient, when compared with state-of-the-art graphs models, including graph convoluted network (GCN), message-passing neural network (MPNN), and AttentiveFP.

Pannexin 2 (Panx2) is a large-pore ATP-permeable channel with critical roles in various physiological processes, such as the inflammatory response, energy production and apoptosis. Its dysfunction is related to numerous pathological conditions including ischemic brain injury, glioma and glioblastoma multiforme. However, the working mechanism of Panx2 remains unclear. Here, we present the cryo-electron microscopy structure of human Panx2 at a resolution of 3.4 Å. Panx2 structure assembles as a heptamer, forming an exceptionally wide channel pore across the transmembrane and intracellular domains, which is compatible with ATP permeation. Comparing Panx2 with Panx1 structures in different states reveals that the Panx2 structure corresponds to an open channel state. A ring of seven arginine residues located at the extracellular entrance forms the narrowest site of the channel, which serves as the critical molecular filter controlling the permeation of substrate molecules. This is further verified by molecular dynamics simulations and ATP release assays. Our studies reveal the architecture of the Panx2 channel and provide insights into the molecular mechanism of its channel gating. Pannexin 2 plays critical roles in many physiological processes but its mechanism remain unclear. Here, authors report the cryo-EM structure of human Panx2 in the open state and identify critical residues for its gating.

Abstract The Yersinia outer protein J (YopJ) family effectors are widely deployed through the type III secretion system by both plant and animal pathogens. As non-canonical acetyltransferases, the enzymatic activities of YopJ family effectors are allosterically activated by the eukaryote-specific ligand inositol hexaphosphate (InsP6). However, the underpinning molecular mechanism remains undefined. Here we present the crystal structure of apo-PopP2, a YopJ family member secreted by the plant pathogen Ralstonia solanacearum . Structural comparison of apo-PopP2 with the InsP6-bound PopP2 reveals a substantial conformational readjustment centered in the substrate-binding site. Combining biochemical and computational analyses, we further identify a mechanism by which the association of InsP6 with PopP2 induces an α-helix-to-β-strand transition in the catalytic core, resulting in stabilization of the substrate recognition helix in the target protein binding site. Together, our study uncovers the molecular basis governing InsP6-mediated allosteric regulation of YopJ family acetyltransferases and further expands the paradigm of fold-switching proteins.

Diabetic nephropathy frequently coexists with membranous nephropathy (MN), yet their combined clinical characteristics and prognosis remain poorly understood. We retrospectively analyzed 276 patients with biopsy-confirmed kidney disease from 2015 to 2023, including 34 patients with diabetic nephropathy and MN (DN-MN), 44 diabetes mellitus combined with MN (DM-MN), and 198 MN patients. Clinical manifestations, pathological characteristics, treatment regimens, and outcomes were compared among the three groups, and a nomogram to predict renal complete remission (CR) was constructed. At baseline, patients with DN-MN had worse renal function than the other groups. Median estimated glomerular filtration rate (eGFR) was 68.2 (41.7-104.8) mL/min/1.73 m in the DN-MN group, compared with 100.3 (91.4-112.1) mL/min/1.73 m in the DM-MN group and 101.4 (89.2-113.0) mL/min/1.73 m in the MN group (  < 0.001). During 26.0 months (Interquartile Range: 17.5-40.0 months) follow-up, when renal CR was defined as the endpoint, 7 patients (20.6%) with DN-MN, 21 (47.7%) with DM-MN, and 94 (47.5%) with MN achieved CR. Pathological features including glomerular segmental sclerosis, interstitial fibrosis and tubular atrophy, and segmental mesangial proliferation were identified as factors associated with renal complete remission. Notably, both DN-MN and DM-MN patients showed comparable rates of renal complete remission between the glucocorticoid and non-glucocorticoid groups in this cohort. These findings indicate that DN-MN patients exhibit worse renal function, more severe pathological lesions, and poorer prognosis than DM-MN and MN patients, with chronic renal pathological lesions serving as important prognostic factors.

The emergence and rapid spread of methicillin‐resistant Staphylococcus aureus (MRSA) raise a critical need for alternative therapeutic options. New antibacterial drugs and targets are required to combat MRSA‐associated infections. Based on this study, celastrol, a natural product from the roots of Tripterygium wilfordii Hook. f., effectively combats MRSA in vitro and in vivo. Multi‐omics analysis suggests that the molecular mechanism of action of celastrol may be related to Δ1‐pyrroline‐5‐carboxylate dehydrogenase (P5CDH). By comparing the properties of wild‐type and rocA‐deficient MRSA strains, it is demonstrated that P5CDH, the second enzyme of the proline catabolism pathway, is a tentative new target for antibacterial agents. Using molecular docking, bio‐layer interferometry, and enzyme activity assays, it is confirmed that celastrol can affect the function of P5CDH. Furthermore, it is found through site‐directed protein mutagenesis that the Lys205 and Glu208 residues are key for celastrol binding to P5CDH. Finally, mechanistic studies show that celastrol induces oxidative stress and inhibits DNA synthesis by binding to P5CDH. The findings of this study indicate that celastrol is a promising lead compound and validate P5CDH as a potential target for the development of novel drugs against MRSA. Schematic diagram summarizing the antibacterial mechanisms of celastrol against MRSA. Celastrol activates multiple pathways including inhibiting DNA and protein biosynthesis, generating ROS and inducing cell death by competitively binding to P5CDH.