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.
Many central biological events rely on protein–ligand interactions. The identification and characterization of protein-binding sites for ligands are crucial for the understanding of functions of both ...endogenous ligands and synthetic drug molecules. G protein-coupled receptors (GPCRs) typically detect extracellular signal molecules on the cell surface and transfer these chemical signals across the membrane, inducing downstream cellular responses via G proteins or β-arrestin. GPCRs mediate many central physiological processes, making them important targets for modern drug discovery. Here, we focus on the most recent breakthroughs in finding new binding sites and binding modes of GPCRs and their potentials for the development of new medicines.
G protein-coupled receptors (GPCRs) mediate numerous physiological activities in the body. Recently resolved crystal structures reveal an increasing number of allosteric ligands. In this review, we systematically cluster the locations of these binding sites from the extracellular, the transmembrane, to the intracellular regions. We also analyze the protein–ligand interactions between these allosteric ligands and their corresponding GPCRs.
Whether the intriguing binding modes of these ligands can be rationalized for designing new drug molecules remains an open question. Allosteric sites offer new opportunities to improve ligand selectivity. However, generalizing the application of allosteric binding can be difficult. Certain binding sites, such as that in the intracellular regions, may overlap with the G protein-binding sites. This might reduce ligand specificity and unexpected side effects in clinical applications.
Nevertheless, a number of allosteric ligands bind to the receptor–lipid interface. Despite the shallow topology in such region for successful structure-based drug design, these locations appear to have a pivotal role in receptor activation and should not be neglected. More importantly, designing allosteric ligands that target orthosteric and the D2.50×50 allosteric sites simultaneously is a more robust strategy for applying rational drug design. Yet, we expect more allosteric sites to be discovered to open more options for developing new medicines.
Abstract
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.
NLRP3/IL-1β activation via thioredoxin (TRX)/thioredoxin-interacting protein (TXNIP) following mitochondria ROS (mtROS) overproduction plays a key role in inflammation. However, the involvement of ...this process in tubular damage in the kidneys of patients with diabetic nephropathy (DN) is unclear. Here, we demonstrated that mtROS overproduction is accompanied by decreases in TRX expression and TXNIP up-regulation. In addition, we discovered that mtROS overproduction is also associated with increases in NLRP3/IL-1β and TGF-β expression in the kidneys of patients with DN and db/db mice. We reversed these changes in db/db mice by administering a peritoneal injection of MitoQ, an antioxidant targeting mtROS. Similar results were observed in human tubular HK-2 cells subjected to high-glucose (HG) conditions and treated with MitoQ. Treating HK-2 cells with MitoQ suppressed the dissociation of TRX from TXNIP and subsequently blocked the interaction between TXNIP and NLRP3, leading to the inhibition of NLRP3 inflammasome activation and IL-1β maturation. The effects of MitoQ were enhanced by pretreatment with TXNIP siRNA and abolished by pretreatment with monosodium urate (MSU) and TRX siRNA in vitro. These results suggest that mitochondrial ROS-TXNIP/NLRP3/IL-1β axis activation is responsible for tubular oxidative injury, which can be ameliorated by MitoQ via the inhibition of mtROS overproduction.
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•Reactive oxygen species promotes renal damage in diabetic nephropathy.•Mitochondrial ROS- TXNIP-NLRP3 biological axis involved in tubular injury of DN.•Inhibition of mitochondrial ROS by MitoQ ameliorated the renal tubular injury.
Human endocannabinoid systems modulate multiple physiological processes mainly through the activation of cannabinoid receptors CB1 and CB2. Their high sequence similarity, low agonist selectivity, ...and lack of activation and G protein-coupling knowledge have hindered the development of therapeutic applications. Importantly, missing structural information has significantly held back the development of promising CB2-selective agonist drugs for treating inflammatory and neuropathic pain without the psychoactivity of CB1. Here, we report the cryoelectron microscopy structures of synthetic cannabinoid-bound CB2 and CB1 in complex with Gi, as well as agonist-bound CB2 crystal structure. Of important scientific and therapeutic benefit, our results reveal a diverse activation and signaling mechanism, the structural basis of CB2-selective agonists design, and the unexpected interaction of cholesterol with CB1, suggestive of its endogenous allosteric modulating role.
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•3D structures of CB2-AM12033-Gi, CB1-AM841-Gi, and CB2-AM12033 are determined•Structural evidence of G protein selectivity by CB1 and CB2 is identified•MD simulations reveal the distinct binding behavior of HU308 in CB2 and CB1•Cholesterol molecule as an endogenous allosteric modulator of CB1 is uncovered
Structure and simulations of cannabinoid receptors CB2 and CB1 in their inactive, active-like, and activated signaling states reveal residue differences that may provide G protein selectivity, the distinct binding behavior of CB2 agonists in CB2 and CB1, as well as evidence for modulation of CB1 by cholesterol binding.
Engineering of enzymes on the basis of protein structures are rational and efficient approaches to acquire biocatalysts of desired performances. In this study, we focused on a special mono- and ...diacylglycerol lipase (MDGL) isolated from the lipolytic enzyme-enriched fungus Aspergillus oryzae and discovered improved variants based on its crystal structure. We first solved the crystal structure of Aspergillus oryzae lipase (AOL) at 1.7 Å resolution. Structure analysis and sequence alignment of AOL and other MDGLs revealed that the residue V269 is of vital importance for catalysis. Replacement of the V269 in AOL with the corresponding residues in other MDGLs has led to noticeable changes in hydrolysis without sacrificing the thermostability and substrate specificity. Among the investigated variants, V269D exhibited about a six-fold higher hydrolysis activity compared to the wild type. Molecular dynamics simulations and protein–ligand interaction frequency analyses revealed that the Asp substitution enhanced the substrate affinity of AOL. Our work sheds light on understanding the catalytic process of AOL and helps tailoring MDGLs with desired catalytic performance to fulfill the demand for biotechnological applications.
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.
Gasdermin D (GSDMD) has been proven to be a key protein in the activation of pyroptosis. Pyroptosis of renal tubular epithelial cells contributes to the progression of tubular injury in kidney ...diseases. However, it remains elusive whether and how GSDMD is involved in the regulation of diabetic kidney disease (DKD). In this study, we found that tubular injury is accompanied by the up-regulation of Toll-like receptor 4 (TLR4) and GSDMD in patients with diabetic kidney disease. In addition, we discovered that the expressions of cleaved Caspase-1, active N-terminal fragments of GSDMD (GSDMD-NT), IL-18, and the secretion of IL-1β also increased in the kidneys of db/db mice. These changes were partially ameliorated following intraperitoneal injection of TAK-242, an inhibitor of TLR4. Similar results were observed in human tubular cells (HK-2) subjected to high-glucose (HG) conditions and treated with TAK-242 or parthenolide (inhibitor of NF-κB) by Western blot, Enzyme-linked immunosorbent assay (ELISA), and flow cytometry. These results indicated that TLR4/NF-κB signaling could induce GSDMD-mediated pyroptosis in tubular cells in DKD.
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.
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.
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