Organophosphorus-Catalyzed Direct Dehydroxylative Thioetherification of Alcohols with Hypervalent Organosulfur Compounds.

A metal-free and thiol-free organophosphorus-catalyzed method for forming thioethers was disclosed, driven by PIII/PV═O redox cycling. In this work, one-step dehydroxylative thioetherification of alcohols was fulfilled with various hypervalent organosulfur compounds. This established strategy features an excellent functional group tolerance and broad substrate scope, especially inactivated alcohols. The scale-up reaction and further transformation of the product were also successful. Additionally, this method offers a protecting-group-free and step-efficient approach for synthesizing peroxisome proliferator-activated receptor agonists which exhibited promising potential for treating osteoporosis in mammals.

Synthesis of C(3) SCF3-Substituted Pyrrolidinoindoline by PIII/PV Redox Catalysis Using CF3SO2Cl as Electrophilic CF3S Reagent.

This work reports a method for the catalytic synthesis of C(3) SCF3-substituted pyrrolidinindoline using a small-ring organophosphorus-based catalyst and a hydrosilane reductant, with trifluoromethanesulfonyl chloride as the electrophilic SCF3 reagent. This method can drive the conversion of tryptamine to the C(3) SCF3-substituted pyrrolidine indoline. The readily available, inexpensive trifluoromethanesulfonyl chloride could be activated as an electrophilic SCF3 source by PIII/PV redox catalysis and could efficiently participate in the reaction of tryptamines, thus providing various substituted C(3) SCF3-substituted pyrrolidinoindoline in moderate to excellent yields. This presented strategy features a broad substrate scope, and the structure has value for in-depth research.

Design, Synthesis, and Biological Evaluation of Chroman Derivatives as PD-1/PD-L1 Antagonists.

Programmed death-ligand 1 (PD-L1) has emerged as a promising therapeutic target for various cancers due to its crucial role in promoting tumor immune evasion. Here, we report a novel class of chroman-like small-molecule PD-L1 inhibitors exhibiting significant activity in inhibiting the PD-1/PD-L1 interaction. Employing a "ring-close" strategy for conformational restriction, we have achieved compound C27, which demonstrates superior PD-1/PD-L1 inhibitory activity compared to the positive control. Molecular dynamics simulation and binding free energy calculation predict that (R)-C27 with inhibitory activity surpassed (S)-C27. The experimental results from bioassay and X-ray structural analysis corroborate these findings. All these results collectively indicate that (R)-C27 is a promising lead compound deserving further exploration.

GDCL-NcDA: identifying non-coding RNA-disease associations via contrastive learning between deep graph learning and deep matrix factorization.

Non-coding RNAs (ncRNAs) draw much attention from studies widely in recent years because they play vital roles in life activities. As a good complement to wet experiment methods, computational prediction methods can greatly save experimental costs. However, high false-negative data and insufficient use of multi-source information can affect the performance of computational prediction methods. Furthermore, many computational methods do not have good robustness and generalization on different datasets. In this work, we propose an effective end-to-end computing framework, called GDCL-NcDA, of deep graph learning and deep matrix factorization (DMF) with contrastive learning, which identifies the latent ncRNA-disease association on diverse multi-source heterogeneous networks (MHNs). The diverse MHNs include different similarity networks and proven associations among ncRNAs (miRNAs, circRNAs, and lncRNAs), genes, and diseases. Firstly, GDCL-NcDA employs deep graph convolutional network and multiple attention mechanisms to adaptively integrate multi-source of MHNs and reconstruct the ncRNA-disease association graph. Then, GDCL-NcDA utilizes DMF to predict the latent disease-associated ncRNAs based on the reconstructed graphs to reduce the impact of the false-negatives from the original associations. Finally, GDCL-NcDA uses contrastive learning (CL) to generate a contrastive loss on the reconstructed graphs and the predicted graphs to improve the generalization and robustness of our GDCL-NcDA framework. The experimental results show that GDCL-NcDA outperforms highly related computational methods. Moreover, case studies demonstrate the effectiveness of GDCL-NcDA in identifying the associations among diversiform ncRNAs and diseases.

Synthesis of Functionalized Thiazolidin-2-imine and Oxazolidin-2-one Derivatives from p-Quinamines via [3 + 2] Annulation of Isothiocyanates and CO2.

An efficient and environmentally friendly synthetic approach to prepare thiazolidine-2-imine and oxazolidine-2-one derivatives has been developed. Thiazolidine-2-imines are synthesized in good to excellent yields by [3 + 2] annulation of p-quinamines with isothiocyanates under catalyst- and solvent-free conditions. Oxazolidine-2-ones are produced in good to excellent yields via [3 + 2] annulation of p-quinamines with CO2 using triethylenediamine (DABCO) as an organocatalyst. Furthermore, this strategy can be performed on a gram scale and tolerate a wide range of functional groups.

Discovery of a Novel Macrocyclic ATP Citrate Lyase Inhibitor.

ATP citrate lyase (ACLY) is an important metabolic enzyme involved in the synthesis of fatty acid and cholesterol. The inhibition of ACLY is considered as a promising therapeutic strategy for various metabolic diseases and numerous malignancies. In this study, a novel macrocyclic compound 2 has been identified as a potent ACLY inhibitor with the "ring closing" strategy for conformational restriction based on NDI-091143. It showed potent ACLY inhibitory activity and binding affinity comparable to the positive control. Furthermore, compared with the positive control (T1/2 = 3.36 min), the metabolic stability of 2 in HLMs (T1/2 = 531.22 min) was significantly improved. All of these results characterized 2 as a promising lead compound worthy of further study.

Discovery of Novel Small Molecule Inhibitors Disrupting the PCSK9-LDLR Interaction.

Proprotein convertase subtilisin kexin 9 (PCSK9) has been identified as a reliable therapeutic target for hypercholesterolemia and coronary artery heart diseases since the monoclonal antibodies of PCSK9 have launched. Disrupting the protein-protein interaction (PPI) between PCSK9 and the low-density lipoprotein receptor (LDLR) has been considered as a promising approach for developing PCSK9 inhibitors. However, PPIs have been traditionally considered difficult to target by small molecules since the PPI surface is usually large, flat, featureless, and without a "pocket" or "groove" for ligand binding. The PCSK9-LDLR PPI interface is such a typical case. In this study, a potential binding pocket was generated on the PCSK9-LDLR PPI surface of PCSK9 through induced-fit docking. On the basis of this induced binding pocket, virtual screening, molecular dynamics (MD) simulation, and biological evaluations have been applied for the identification of novel small molecule inhibitors of PCSK9-LDLR PPI. Among the selected compounds, compound 13 exhibited certain PCSK9-LDLR PPI inhibitory activity (IC50: 7.57 ± 1.40 µM). The direct binding affinity between 13 and PCSK9 was determined with a KD value of 2.50 ± 0.73 µM. The LDLR uptake function could be also restored to a certain extent by 13 in HepG2 cells. This well-characterized hit compound will facilitate the further development of novel small molecule inhibitors of PCSK9-LDLR PPI.

Synthesis, biological evaluation and SAR studies of ursolic acid 3ß-ester derivatives as novel CETP inhibitors.

Cholesteryl ester transfer protein (CETP) is an attractive therapeutic target for the prevention and treatment of cardiovascular diseases by lowering low-density lipoprotein cholesterol levels as well as raising high-density lipoprotein cholesterol levels in human plasma. Herein, a series of ursolic acid 3ß-ester derivatives were designed, synthesized and evaluated for the CETP inhibiting activities. Among these compounds, the most active compound is U12 with an IC50 value of 2.4 µM in enzymatic assay. The docking studies showed that the possible hydrogen bond interactions between the carboxyl groups at both ends of the molecule skeleton and several polar residues (such as Ser191, Cys13 and Ser230) in the active site region of CETP could significantly enhance the inhibition activity. This study provides structural insight of the interactions between these pentacyclic triterpenoid 3ß-ester derivatives and CETP protein for the further modification and optimization.

Discovery of Novel Peroxisome Proliferator-Activated Receptor α (PPARα) Agonists by Virtual Screening and Biological Evaluation.

Nonalcoholic steatohepatitis (NASH) is one of the important causes of cirrhosis and hepatocellular carcinoma worldwide. PPARα is highly expressed in the liver and plays a critical role in hepatic lipid metabolism. Our analysis of the gene expression profiles in the liver of humanized mice treated with a PPARα agonist and NASH patients suggested that PPARα might be a potential target for NASH therapy. This promoted us to find novel PPARα agonists. The results of virtual screening and biological evaluation identified compound A-4 as a selective PPARα agonist. It significantly regulated the target genes of PPARα involved in fatty acid metabolism and inflammation, exhibiting cellular anti-inflammatory activity. The key residues involved in the binding between PPARα ligand-binding domain (LBD) and compound A-4 were revealed by molecular dynamics (MD) simulation and further experimentally validated by the mutation study. Together, compound A-4 was well characterized as a novel lead compound for developing potent and selective PPARα agonists.

Discovery of Ubiquitin-Specific Protease 7 (USP7) Inhibitors with Novel Scaffold Structures by Virtual Screening, Molecular Dynamics Simulation, and Biological Evaluation.

USP7 has been regarded as a potential therapeutic target for cancer. In this study, virtual screening, molecular dynamics (MD) simulation, and biological evaluation have been applied for the discovery of novel USP7 inhibitors targeting the catalytic active site. Among the obtained compounds, compound 12 with a novel scaffold structure exhibited certain USP7 inhibitory activity (Ub-AMC assay IC50 = 18.40 ± 1.75 µM, Ub-Rho assay IC50 = 7.75 µM). The binding affinity between USP7CD (USP7 catalytic domain) and this hit compound was confirmed with a KD value of 4.46 ± 0.86 µM. Preliminary in vitro studies disclosed its antiproliferative activity on human prostate cancer cell line LNCaP with an IC50 value of 15.43 ± 3.49 µM. MD simulation revealed the detailed differences of protein-ligand interactions between USP7CD and the ligands, including the reference compound ALM4 and compound 12, providing some important information for improving the bioactivity of 12. This hit compound will serve as a promising starting point for facilitating the further discovery of novel USP7 inhibitors.

A Selectivity Study of FFAR4/FFAR1 Agonists by Molecular Modeling.

FFAR4 has been considered as a potential target for metabolic diseases, including diabetes. Some compounds with biphenyl scaffold, represented by compound SR13 reported by our group, showed significant FFAR4 selectivity. However, the molecular basis for their selectivity has not been definitely disclosed. This study provided insights into the protein-ligand interactions between agonists and FFAR4/FFAR1 by molecular modeling. The important residues identified were consistent with those found in experimental studies. Moreover, the results proposed that the selectivity of SR13 between FFAR4 and FFAR1 depended on whether it can enter the ligand-binding site through the entrance region by adopting its preferential conformation. The big difference between the preferential conformation of SR13 and the narrow entrance region determined its poor agonist activity against FFAR1. These findings will facilitate the further development of selective FFAR4 agonists.

A selectivity study of sodium-dependent glucose cotransporter 2/sodium-dependent glucose cotransporter 1 inhibitors by molecular modeling.

Sodium-dependent glucose cotransporters (SGLTs) play an important role in glucose reabsorption in the kidney and have been identified as promising targets to treat diabetes. Because of the side effects like glucose and galactose malabsorption by targeting SGLT1, highly selective SGLT2 inhibitors are more promising in the treatment of diabetes. To understand the mechanism of selectivity, we conducted selectivity-based three-dimensional quantitative structure-activity relationship studies to highlight the structure requirements for highly selective SGLT2 inhibitors. The best comparative molecular field analysis and comparative molecular similarity indices analysis models showed the noncross-validated coefficient (r(2) ) of 0.967 and 0.943, respectively. The predicted correlation coefficients (r(2) pred ) of 0.974 and 0.938 validated the reliability and predictability of these models. Besides, homology models of SGLT2 and SGLT1 were also constructed to investigate the selective mechanism from structure-based perspective. Molecular dynamics simulation and binding free energy calculation were performed on the systems of a potent and selective compound interacting with SGLT2 and SGLT1 to compare the different binding modes. The simulation results showed that the stretch of the methylthio group on Met241 had an essential effect on the different binding modes between SGLT1 and SGLT2, which was consistent with the three-dimensional quantitative structure-activity relationship analysis. Hydrogen bond analysis and binding free energy calculation revealed that SGLT2 binding complex was more stable and favorable than SGLT1 complex, which was highly correlated with the experimental results. Our obtained results give useful information for the investigation of the inhibitors' selectivity between SGLT2 and SGLT1 and will help for further development of highly selective SGLT2 inhibitors.

Molecular modeling of exquisitely selective c-Met inhibitors through 3D-QSAR and molecular dynamics simulations.

c-Met has been considered as an attractive target for developing antitumor agents. The highly selective c-Met inhibitors provide invaluable opportunities for the combination with other therapies safely to achieve the optimal efficacy. In this work, a series of triazolopyrazine c-Met inhibitors with exquisitely selectivity were investigated using a combination of molecular docking, three-dimensional quantitative structure-activity relationship (3D-QSAR), and molecular dynamics simulation. Comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) models were developed to reveal the structural determinants for c-Met inhibition. Both models were validated to have high reliability and predictability, and contour map analysis suggested feature requirements for different substituents on the scaffold. It is worth noting that an important hydrogen bond rich region was identified in the unique narrow channel, which is distinct from other kinases. Molecular dynamics simulations and binding free energy calculations provided further support that suitable groups in this hydrogen bond rich region made great contributions to the binding of ligands. Moreover, hydrogen bonds with residues of the narrow channel were also indicated to be essential to improve the activity and selectivity. This study will facilitate the discovery and optimization of novel c-Met inhibitors with higher activity and selectivity.

Discovery of novel aromatase inhibitors using a homogeneous time-resolved fluorescence assay.

AIM: Aromatase is an important target for drugs to treat hormone-dependent diseases, including breast cancer. The aim of this study was to develop a homogeneous time-resolved fluorescence (HTRF) aromatase assay suitable for high-throughput screening (HTS). METHODS: A 384-well aromatase HTRF assay was established, and used to screen about 7000 compounds from a compound library. Anti-proliferation activity of the hit was evaluated using alamarBlue(R) assay in a hormone-dependent breast cancer cell line T47D. Molecular docking was conducted to elucidate the binding mode of the hit using the Discovery Studio program. RESULTS: The Z' value and signal to background (S/B) ratio were 0.74 and 5.4, respectively. Among the 7000 compounds, 4 hits (XHN22, XHN26, XHN27 and triptoquinone A) were found to inhibit aromatase with IC50 values of 1.60±0.07, 2.76±0.24, 0.81±0.08 and 45.8±11.3 µmol /L, respectively. The hits XHN22, XHN26 and XHN27 shared the same chemical scaffold of 4-imidazolyl quinoline. Moreover, the most potent hit XHN27 at 10 and 50 µmol/L inhibited the proliferation of T47D cells by 45.3% and 35.2%, respectively. The docking study revealed that XHN27 docked within the active site of aromatase and might form a hydrogen bond and had a π-cation interaction with amino acid residues of the protein. CONCLUSION: XHN27, an imidazolyl quinoline derivative of flavonoid, is a potent aromatase inhibitor with anti-proliferation activity against breast cancer in vitro. The established assay can be used in HTS for discovering novel aromatase inhibitor.

An efficient multistep ligand-based virtual screening approach for GPR40 agonists.

G protein-coupled receptor 40/free fatty acid receptor 1 (GPR40/FFAR1) is a member of the GPCR superfamily, and GPR40 agonists have therapeutic potential for type 2 diabetes. With the crystal structure of GPR40 currently unavailable, various ligand-based virtual screening approaches can be applied to identify novel agonists of GPR40. It is known that each ligand-based method has its own advantages and limitations. To improve the efficiency of individual ligand-based methods, an efficient multistep ligand-based virtual screening approach is presented in this study, including the pharmacophore-based screening, physicochemical property filtering, protein-ligand interaction fingerprint similarity analysis, and 2D-fingerprint structural similarity search. A focused decoy library was generated and used to evaluate the efficiency of this virtual screening protocol. This multistep workflow not only significantly improved the hit rate compared with each individual ligand-based method, but also identified diverse known actives from decoys. This protocol may serve as an efficient virtual screening tool for the targets without crystal structures available to discover novel active compounds.

Multi-view multiattention graph learning with stack deep matrix factorization for circRNA-drug sensitivity association identification.

Identifying circular RNA (circRNA)-drug sensitivity association (CDsA) is crucial for advancing drug development. As conducting traditional wet experiments for determining CDsA is costly and inefficient, calculation methods have already proven to be a valid approach to cope with this problem. However, there exists limited research addressing the prediction of the CDsA prediction problem, and certain discrepancies persist, particularly concerning false-negative associations. As a consequence, we present a multi-view framework, called MAGSDMF, for identifying latent CDsA. Firstly, MAGSDMF applies Multiple Attention mechanisms and Graph learning methods to dynamically extract features and strengthen the features of inside and across multi-similarity networks of circRNA and drug. Secondly, the Stack Deep Matrix Factorization (SDMF) is devised to directly extract features from CDsAs. We consider multi-similarity networks with the original CDsAs as multi-view information. Thirdly, MAGSDMF utilizes a multiattention channel mechanism to integrate these features for the purpose of reconstructing CDsA. Finally, MAGSDMF performs another DMF based on the reconstruction to identify the latent CDsAs. Simultaneously, contrastive learning (CL) is implemented to enhance the generalization capability of MAGSDMF and oversee the learning process of the underlying links prediction task. In comparative experiments, MAGSDMF achieves superior performance on two datasets with AUC values of 0.9743 and 0.9739 based on 5-fold cross-validation. Moreover, in case studies, the achievements further validate the identification reliability of MAGSDMF.

Discovery of 2,3-Dihydro[1,4]dioxino[2,3-g]benzofuran Derivatives as Protease Activated Receptor 4 (PAR4) Antagonists with Potent Antiplatelet Aggregation Activity and Low Bleeding Tendency.

Patients with arterial embolic disease have benefited greatly from antiplatelet therapy. However, hemorrhage risk of antiplatelet agents cannot be ignored. Herein, we describe the discovery of 2,3-dihydro[1,4]dioxino[2,3-g]benzofuran compounds as novel PAR4 antagonists. Notably, the isomers 36 and 37 with the chemotype of phenoxyl methylene substituted on the 2,3-dihydro-1,4-dioxine ring exhibited potent in vitro antiplatelet activity (IC50 = 26.13 nM for 36 and 14.26 nM for 37) and significantly improved metabolic stability in human liver microsomes (T1/2 = 97.6 min for 36 and 11.1 min for BMS-986120). 36 also displayed good oral PK profiles (mice: T1/2 = 7.32 h and F = 45.11%). Both of them showed overall potent ex vivo antiplatelet activity at concentrations of 6 and 12 mg/kg, with no impact on the coagulation system and low bleeding liability. Our work will facilitate development of novel PAR4 antagonists as a safer therapeutic option for arterial embolism.

Design, synthesis, and biological evaluation of piperazine derivatives as pan-PPARs agonists for the treatment of liver fibrosis.

Liver fibrosis is commonly occurred in chronic liver diseases, but there is no approved drug for clinical use. The nuclear receptor peroxisome proliferator-activated receptors (PPARs) could not only regulate metabolic homeostasis but also possess anti-inflammatory and antifibrotic effects, and pan-PPARs agonist was considered as a potential anti-liver fibrosis agent. In this study, a series of novel piperazine pan-PPARs agonists were developed, and the preferred compound 12 displayed potent and well-balanced pan-PPARs agonistic activity. Moreover, compound 12 could dose-dependently stimulate the PPARs target genes expression and showed high selectivity over other related nuclear receptors. Importantly, compound 12 exhibited excellent pharmacokinetic profiles and good anti-liver fibrosis effects in vivo. Collectively, compound 12 holds promise for developing an anti-liver fibrosis agent.

PIII/PV-Catalyzed Beckmann Reaction and Sequential [2,3]-Sigmatropic Rearrangement to Construct 2-Amidopyridines.

An organophosphorus catalytic method for the synthesis of substituted 2-amidopyridines is reported. The method employs a small-ring organophosphorus-based catalyst and a hydrosilane reductant to drive the conversion of ketoximes and pyridine-N-oxides into 2-amidopyridines through sequential Beckmann rearrangement followed by [2,3]-sigmatropic rearrangement. The readily available ketoximes could be activated to nitrilium ions in PIII/PV redox catalysis and could efficiently participate in the domino reaction of pyridine-N-oxides, thus providing various substituted 2-amidopyridines in moderate to excellent yields. This presented strategy features excellent functional group tolerance and a broad substrate scope.

Discovery of Novel PD-L1 Small-Molecular Inhibitors with Potent In Vivo Anti-tumor Immune Activity.

Programmed death-ligand 1 (PD-L1) has surfaced as a promising therapeutic target for various cancers due to its pivotal role in facilitating tumor immune evasion. Herein, we report a series of novel small-molecule PD-L1 inhibitors exhibiting remarkable inhibitory activity against the PD-1/PD-L1 interaction (X18: IC50 = 1.3 nM) and reinstating the suppressive effect of PD-L1 on T cells (X18: EC50 = 152.8 nM). Crystallographic studies revealed the binding mode of X18 and PD-L1. Through a rational prodrug design approach, we have successfully optimized the oral pharmacokinetic properties of X22, effectively addressing the poor oral pharmacokinetic profile of PD-L1 small-molecule inhibitors. Notably, X22 demonstrated significant antitumor efficacy in murine models of MC38 and CT26 colon cancer through the upregulation of tumor infiltration and cytotoxicity of CD8+ T cells partially. These findings offer promising prospects for the advancement of PD-L1 inhibitors as innovative agents in cancer immunotherapy.