Discovery of novel diaryl substituted isoquinolin-1(2H)-one derivatives as hypoxia-inducible factor-1 signaling inhibitors for the treatment of rheumatoid arthritis.

Since synovial hypoxic microenvironment significantly promotes the pathological progress of rheumatoid arthritis (RA), hypoxia-inducible factor 1 (HIF-1) has been emerged as a promising target for the development of novel therapeutic agents for RA treatment. In this study, we designed and synthesized a series of diaryl substituted isoquinolin-1(2H)-one derivatives as HIF-1 signaling inhibitors using scaffold-hopping strategy. By modifying the substituents on N-atom and 6-position of isoquinolin-1-one, we discovered compound 17q with the most potent activities against HIF-1 (IC50 = 0.55 µM) in a hypoxia-reactive element (HRE) luciferase reporter assay. Further pharmacological studies revealed that 17q concentration-dependently blocked hypoxia-induced HIF-1α protein accumulation, reduced inflammation response, inhibited cellular invasiveness and promoted VHL-dependent HIF-1α degradation in human RA synovial cell line. Moreover, 17q improved the pathological injury of ankle joints, decreased angiogenesis and attenuated inflammation response in the adjuvant-induced arthritis (AIA) rat model, indicating the promising therapeutic potential of compound 17q as an effective HIF-1 inhibitor for RA therapy.

Apolipoprotein E (ApoE) orchestrates adipose tissue inflammation and metabolic disorders through NLRP3 inflammasome.

Obesity is a metabolic disorder characterized by the hypertrophy expansion of adipose tissue, resulting in dysregulated energy metabolism, and accompanied by chronic low-grade inflammation. Adipose tissue macrophages (ATMs), a principal component of inflammation, respond to microenvironment signals and modulate adipose tissue remodeling and metabolic processes situation-specific. However, the mechanisms governing how the organism maintains equilibrium between its chronic inflammation and metabolism still need to be understood. Here, we describe a novel role of apolipoprotein E (ApoE), which associated with lipid particles, in maintaining fat deposition and system metabolic inflammation. Using human samples and mouse models, we show that ApoE is robustly downregulated in obese individuals, db/db mice, and mice of high-fat diet (HFD) feeding and increased in obese subjects with diabetes. Furthermore, we found that ApoE deficiency mice globally prevented obesity by restraining adipose tissue expansion and improved systemic glucose tolerance and insulin sensitivity. However, macrophage contributed to metabolic inflammation due to increased IL-1ß production in adipose tissue from ApoE-/- mice induced by HFD. Our results suggest that the role of ApoE in regulating obesity and obesity-associated glucose dysregulation is inconsistent. Mechanistically, ApoE modulates of the NOD-, LRR- and pyrin domain-containing protein 3 (NLRP3) inflammasome priming and activation step. Thus, our studies might provide new sights into ApoE, which is required for obesity-induced hyperglycemia, hyperinsulinism, and adaptive inflammation responses but diminishes the tolerance towards a subsequent metabolic inflammatory challenge. Our study shed new light on the integral role of apolipoprotein APOE in immunometabolism and adipose tissue homeostasis.

Protein-ligand binding affinity prediction with edge awareness and supervised attention.

Accurate prediction of protein-ligand binding affinity is crucial in structure-based drug design but remains some challenges even with recent advances in deep learning: (1) Existing methods neglect the edge information in protein and ligand structure data; (2) current attention mechanisms struggle to capture true binding interactions in the small dataset. Herein, we proposed SEGSA_DTA, a SuperEdge Graph convolution-based and Supervised Attention-based Drug-Target Affinity prediction method, where the super edge graph convolution can comprehensively utilize node and edge information and the multi-supervised attention module can efficiently learn the attention distribution consistent with real protein-ligand interactions. Results on the multiple datasets show that SEGSA_DTA outperforms current state-of-the-art methods. We also applied SEGSA_DTA in repurposing FDA-approved drugs to identify potential coronavirus disease 2019 (COVID-19) treatments. Besides, by using SHapley Additive exPlanations (SHAP), we found that SEGSA_DTA is interpretable and further provides a new quantitative analytical solution for structure-based lead optimization.

Targeted pharmacokinetics and bioinformatics screening strategy reveals JAK2 as the main target for Xin-Ji-Er-Kang in treatment of MIR injury.

BACKGROUND AND PURPOSE: Xin-Ji-Er-Kang (XJEK) is traditional Chinese formula presented excellent protective effects on several heart diseases, but the potential components and targets are still unclear. The aim of this study is to elucidate the effective components of XJEK and reveal its potential mechanism of cardioprotective effect in myocardial ischemia-reperfusion (MIR) injury. EXPERIMENTAL APPROACH: Firstly, the key compounds in XJEK, plasma and heart tissue were analyzed by high resolution mass spectrometry. Bioinformatics studies were also involved to disclose the potential targets and the binding sites for the key compounds. Secondly, to study the protective effect of XJEK on MIR injury and related mechanism, mice subjected to MIR surgery and gavage administered with XJEK for 6 weeks. Cardiac function parameters and apoptosis level of cardiac tissue were assessed. The potential mechanism was further verified by knock down of target protein in vitro. RESULTS: Pharmacokinetics studies showed that Sophora flavescens alkaloids, primarily composed with matrine, are the key component of XJEK. And, through bioinformatic analysis, we speculated JAK2 could be the potential target for XJEK, and could form stable hydrogen bonds with matrine. Administration of XJEK and matrine significantly improved heart function and reduced apoptosis of cardiomyocytes by increasing the phosphorylation of JAK2 and STAT3. The anti-apoptosis effect of XJEK and matrine was also observed on AC16 cells, and could be reversed by co-treatment with JAK2 inhibitor AG490 or knock-down of JAK2. CONCLUSION: XJEK exerts cardioprotective effect on MIR injury, which may be associated with the activation of JAK2/STAT3 signaling pathway.

Novel deep learning-based transcriptome data analysis for drug-drug interaction prediction with an application in diabetes.

BACKGROUND: Drug-drug interaction (DDI) is a serious public health issue. The L1000 database of the LINCS project has collected millions of genome-wide expressions induced by 20,000 small molecular compounds on 72 cell lines. Whether this unified and comprehensive transcriptome data resource can be used to build a better DDI prediction model is still unclear. Therefore, we developed and validated a novel deep learning model for predicting DDI using 89,970 known DDIs extracted from the DrugBank database (version 5.1.4). RESULTS: The proposed model consists of a graph convolutional autoencoder network (GCAN) for embedding drug-induced transcriptome data from the L1000 database of the LINCS project; and a long short-term memory (LSTM) for DDI prediction. Comparative evaluation of various machine learning methods demonstrated the superior performance of our proposed model for DDI prediction. Many of our predicted DDIs were revealed in the latest DrugBank database (version 5.1.7). In the case study, we predicted drugs interacting with sulfonylureas to cause hypoglycemia and drugs interacting with metformin to cause lactic acidosis, and showed both to induce effects on the proteins involved in the metabolic mechanism in vivo. CONCLUSIONS: The proposed deep learning model can accelerate the discovery of new DDIs. It can support future clinical research for safer and more effective drug co-prescription.

Discovery of an Inhibitor for the TREK-1 Channel Targeting an Intermediate Transition State of Channel Gating.

Modulators can be designed to stabilize the inactive and active states of ion channels, but whether intermediate (IM) states of channel gating are druggable remains underexplored. In this study, using molecular dynamics simulations of the TWIK-related potassium channel 1 (TREK-1) channel, a two-pore domain potassium channel, we captured an IM state during the transition from the down (inactive) state to the up (active-like) state. The IM state contained a druggable allosteric pocket that was not present in the down or up state. Drug design targeting the pocket led to the identification of the TKIM compound as an inhibitor of TREK-1. Using integrated methods, we verified that TKIM binds to the pocket of the IM state of TREK-1, which differs from the binding of common inhibitors, which bind to channels in the inactive state. Overall, this study identified an allosteric ligand-binding site and a new mechanistic inhibitor for TREK-1, suggesting that IM states of ion channels may be promising druggable targets for use in discovering allosteric modulators.

The Mechanism by Which Luteolin Disrupts the Cytoplasmic Membrane of Methicillin-Resistant Staphylococcus aureus.

Methicillin-resistant Staphylococcus aureus (MRSA) is one of the most versatile human pathogens. Luteolin (LUT) has anti-MRSA activity by disrupting the MRSA cytoplasmic membrane. However, the mechanism by which luteolin disrupts the membrane remains unclear. Here, we performed differential scanning calorimetry (DSC) and all-atomic molecular dynamics (AA-MD) simulations to investigate the interactions and effects of LUT on model membranes composed of phosphatidylcholine (PC) and phosphatidylglycerol (PG). We detected the transition thermodynamic parameters of dipalmitoylphosphatidylcholine (DPPC) liposomes, dipalmitoylphosphatidylglycerol (DPPG) liposomes, and liposomes composed of both DPPC and DPPG at different LUT concentrations and showed that LUT molecules were located between polar heads and the hydrophobic region of DPPC/DPPG. In the MD trajectories, LUT molecules ranging from 5 to 50 had different effects on the membranes thickness, fluidity and ordered property of lipids, and lateral pressure of lipid bilayers composed of dioleoylphosphatidylcholine (DOPC) and dioleoylphosphatidylglycerol (DOPG). Also, most LUT molecules were distributed in the region between the phosphorus atoms and C9 atoms of DOPC and DOPG. On the basis of the combination of these results, we conclude that the distinct effects of LUT on lipid bilayers composed of PCs and PGs may elucidate the mechanism by which LUT disrupts the cytoplasmic membrane of MRSA.

Characterizing the interactions of two lipid modifications with lipid rafts: farnesyl anchors vs. palmitoyl anchors.

Farnesyl (Far) and palmitoyl (Pal) anchors play important roles in the traffic of many lipidated proteins. Herein, we show the distinctive interactions and influences of the two lipid modifications on lipid rafts (LRs) and non-raft-like membranes using molecular dynamics simulations. Palmitoyl anchors behave in a more ordered fashion, pack tighter with the lipids of LRs and diffuse at a slower rate than farnesyl anchors in LRs. When interacting with non-raft-like membranes these two types of anchors become less ordered, pack more loosely with lipids, and diffuse at a higher rate. By calculating both the number of contacts per chain and the number of contact atoms per carbon of the two anchors with the lipid components, we found that the palmitoyl chains preferred to associate with the saturated chains of lipids and cholesterol molecules in LRs, while farnesyl chains favored association with saturated chains and unsaturated chains. For non-raft-like membranes, these two lipid anchors had roughly the same preference for the three types of contact lipid chains. Additionally, palmitoyl anchors caused cholesterol to orient more perpendicular to the membrane surface, surrounding lipids to become more ordered, and lipid lateral fluidity to reduce significantly, compared to farnesyl anchors in LRs. By contrast, the POPE and DSPC became much less ordered, cholesterol became more tilted, and lipids became more fluid, when the two types lipid anchors were inserted in non-raft-like membranes. These findings are useful for understanding the traffic mechanisms of lipidated proteins with farnesyl and palmitoyl modifications in cell membranes.

An allosteric ligand-binding site in the extracellular cap of K2P channels.

Two-pore domain potassium (K2P) channels generate leak currents that are responsible for the maintenance of the resting membrane potential, and they are thus potential drug targets for treating diseases. Here, we identify N-(4-cholorphenyl)-N-(2-(3,4-dihydrosioquinolin-2(1H)-yl)-2-oxoethyl)methanesulfonamide (TKDC) as an inhibitor of the TREK subfamily, including TREK-1, TREK-2 and TRAAK channels. Using TKDC as a chemical probe, a study combining computations, mutagenesis and electrophysiology reveals a K2P allosteric ligand-binding site located in the extracellular cap of the channels. Molecular dynamics simulations suggest that ligand-induced allosteric conformational transitions lead to blockage of the ion conductive pathway. Using virtual screening approach, we identify other inhibitors targeting the extracellular allosteric ligand-binding site of these channels. Overall, our results suggest that the allosteric site at the extracellular cap of the K2P channels might be a promising drug target for these membrane proteins.TREKs are members of the two-pore domain potassium (K2P) channels, being important clinical targets. Here the authors identify inhibitors of K2P that bind to an allosteric site located in their extracellular cap, suggesting that it might be a promising drug target for these channels.

Two-quartet G-quadruplexes formed by DNA sequences containing four contiguous GG runs.

The DNA sequence containing four contiguous GG runs (G2NxG2NyG2NzG2, G2 sequence) has the potential to form a two-quartet G-quadruplex. However, the prevalence, structure, and function of G2 sequences have not been well-studied. Here, bioinformatics analysis reveals the abundance of G2 sequences in the human genome and their enrichment in promoter regions. The density of G2 sequences in the genome and promoters is much higher than that of the G3 sequence (G3NxG3NyG3NzG3). Experiments show that the conformations and thermal stabilities of the two-quartet G-quadruplexes of G2 sequences are highly sensitive to the length and composition of the loops. Among the two-quartet G-quadruplexes, the parallel G-quadruplex with a loop length of 1 and the antiparallel G-quadruplex with a loop length of 3 show high thermal stabilities. Additionally, the stable parallel G-quadruplexes are stacked into intermolecular higher-order structures. This work determines the prevalence of G2 sequences in the human genome and demonstrates that the G-quadruplex structures for certain loop lengths and compositions may be stable in vivo. Thus, more attention should be paid to the structure and function of the two-quartet G-quadruplex.