Soil enzyme activity mediated organic carbon mineralization due to soil erosion in long gentle sloping farmland in the black soil region.

Soil erosion plays a crucial role in soil organic carbon (SOC) redistribution and mineralization. Meanwhile, the soil extracellular enzymes (EEs) drive C mineralization. However, the response of soil EEs mediated SOC mineralization to soil erosion remains unclear. We investigated the SOC and soil EEs distribution in long gentle sloping farmland (LGSF) under slop-ridge tillage (SRT) and cross-ridge tillage (CRT) in the black soil region (BSR) of northeast China. The results indicated that the SOC mineralization at the upper slope position was higher than that on the toe-slope (133 % âˆ¼ 340 %) under CRT. However, for SRT, SOC mineralization on the back-slope was 126 % and 164 % higher than on the summit- and shoulder-slope. The SOC, dissolved organic carbon (DOC) content, and ß-glucosidase (BG) activities underwent spatial migration and deposition in the lower region under both tillage practices. As for CRT, the SOC content of the back-slope was 19.21 % higher than on the summit-slope, while the DOC content at the back-slope was 29.20 % higher than on the toe-slope. The BG activity was the highest at the toe-slope, followed by the foot-and back-slope, which were 41.74 %-74.73 % higher than at the summit-slope. As for SRT, the SOC, DOC, and BG activities on the back-slope were significantly higher than other slope positions (P < 0.05). The SOC on the back-slope were 47.82 % and 31.72 % higher than those on the summit- and shoulder-slope, respectively. The DOC and BG on the back-slope were 10.98 % and 67.78 % higher than on the summit-slope. The soil EES results indicated strong C and P limitation. Spatial differences in soil C distribution resulted in a significant positive correlation between C limitation and mineralization. This indicated that soil C and nutrient distribution under different slope positions driven by soil erosion, leading to soil nutrient limitation, is a key factor influencing spatial differences in C sources or sinks.

Discovery and development of novel 10,12-disubstituted aloperine derivatives against HCoV-OC43 by targeting allosteric site of host TMPRSS2.

By inducing steric activation of the 10CH bond with a 12-acyl group to form a key imine oxime intermediate, 20 novel (10S)-10,12-disubstituted aloperine derivatives were successfully synthesized and assessed for their antiviral efficacy against HCoV-OC43. Of them, compound 3i exhibited the moderate activities against HCoV-OC43, as well as against the SARS-CoV-2 variant EG.5.1 with the comparable EC50 values of 4.7 and 4.1 µM. A mechanism study revealed that it inhibited the protease activity of host TMPRSS2 by binding to an allosteric site, rather than the known catalytic center, different from that of camostat. Also, the combination of compound 3i and molnupiravir, as an RdRp inhibitor, showed an additive antiviral effect against HCoV-OC43. The results provide a new binding mode and lead compound for targeting TMPRSS2, with an advantage in combating broad-spectrum coronavirus.

D3EGFR: a webserver for deep learning-guided drug sensitivity prediction and drug response information retrieval for EGFR mutation-driven lung cancer.

As key oncogenic drivers in non-small-cell lung cancer (NSCLC), various mutations in the epidermal growth factor receptor (EGFR) with variable drug sensitivities have been a major obstacle for precision medicine. To achieve clinical-level drug recommendations, a platform for clinical patient case retrieval and reliable drug sensitivity prediction is highly expected. Therefore, we built a database, D3EGFRdb, with the clinicopathologic characteristics and drug responses of 1339 patients with EGFR mutations via literature mining. On the basis of D3EGFRdb, we developed a deep learning-based prediction model, D3EGFRAI, for drug sensitivity prediction of new EGFR mutation-driven NSCLC. Model validations of D3EGFRAI showed a prediction accuracy of 0.81 and 0.85 for patients from D3EGFRdb and our hospitals, respectively. Furthermore, mutation scanning of the crucial residues inside drug-binding pockets, which may occur in the future, was performed to explore their drug sensitivity changes. D3EGFR is the first platform to achieve clinical-level drug response prediction of all approved small molecule drugs for EGFR mutation-driven lung cancer and is freely accessible at https://www.d3pharma.com/D3EGFR/index.php.

Erratum: Author correction to 'Discovery and identification of EIF2AK2 as a direct key target of berberine for anti-inflammatory effects' [Acta Pharmaceutica Sinica B 13 (2023) 2138-2151].

[This corrects the article DOI: 10.1016/j.apsb.2022.12.009.].

D3Rings: A Fast and Accurate Method for Ring System Identification and Deep Generation of Drug-Like Cyclic Compounds.

Continuous exploration of the chemical space of molecules to find ligands with high affinity and specificity for specific targets is an important topic in drug discovery. A focus on cyclic compounds, particularly natural compounds with diverse scaffolds, provides important insights into novel molecular structures for drug design. However, the complexity of their ring structures has hindered the applicability of widely accepted methods and software for the systematic identification and classification of cyclic compounds. Herein, we successfully developed a new method, D3Rings, to identify acyclic, monocyclic, spiro ring, fused and bridged ring, and cage ring compounds, as well as macrocyclic compounds. By using D3Rings, we completed the statistics of cyclic compounds in three different databases, e.g., ChEMBL, DrugBank, and COCONUT. The results demonstrated the richness of ring structures in natural products, especially spiro, macrocycles, and fused and bridged rings. Based on this, three deep generative models, namely, VAE, AAE, and CharRNN, were trained and used to construct two data sets similar to DrugBank and COCONUT but 10 times larger than them. The enlarged data sets were then used to explore the molecular chemical space, focusing on complex ring structures, for novel drug discovery and development. Docking experiments with the newly generated COCONUT-like data set against three SARS-CoV-2 target proteins revealed that an expanded compound database improves molecular docking results. Cyclic structures exhibited the best docking scores among the top-ranked docking molecules. These results suggest the importance of exploring the chemical space of structurally novel cyclic compounds and continuous expansion of the library of drug-like compounds to facilitate the discovery of potent ligands with high binding affinity to specific targets. D3Rings is now freely available at http://www.d3pharma.com/D3Rings/.

Design and synthesis of cantharidin derivative DCZ5418 as a TRIP13 inhibitor with anti-multiple myeloma activity in vitro and in vivo.

Natural product cantharidin can inhibit multiple myeloma cell growth in vitro, while serious adverse effects limited its clinical application. Therefore, the structural modification of cantharidin is needed. Herein, inspired by the structural similarity of the aliphatic endocyclic moiety in cantharidin and TRIP13 inhibitor DCZ0415, we designed and synthesized DCZ5418 and its nineteen derivatives. The molecular docking study indicated that DCZ5418 had a similar binding mode to TRIP13 protein as DCZ0415 while with a stronger docking score. Moreover, the bioassay studies of the MM-cells viability inhibition, TRIP13 protein binding affinity and enzyme inhibiting activity showed that DCZ5418 had good anti-MM activity in vitro and definite interaction with TRIP13 protein. The acute toxicity test of DCZ5418 showed less toxicity in vivo than cantharidin. Furthermore, DCZ5418 showed good anti-MM effects in vivo with a lower dose administration than DCZ0415 (15 mg/kg vs 25 mg/kg) on the tumor xenograft models. Thus, we obtained a new TRIP13 inhibitor DCZ5418 with improved safety and good activity in vivo, which provides a new example of lead optimization by using the structural fragments of natural products.

Tailored Drug Delivery Platforms: Stimulus-Responsive Core-Shell Structured Nanocarriers.

Core-shell structured nanocarriers have come into the scientific spotlight in recent years due to their intriguing properties and wide applications in materials chemistry, biology, and biomedicine. Tailored core-shell structures to achieve desired performance have emerged as a research frontier in the development of smart drug delivery system. However, systematic reviews on the design and loading/release mechanisms of stimulus-responsive core-shell structured nanocarriers are uncommon. This review starts with the categories of core-shell structured nanocarriers with different means of drug payload, and then highlights the controlled release mechanism realized through stimulus-response processes triggered under different environments. Finally, some multifaceted perspectives on the design of core-shell structured materials as drug carriers are addressed. This work aims to provide new enlightenments and prospects in the drug delivery field for further developing advanced and smart nanocarriers.

Design, synthesis and triglyceride-lowering activity of tricyclic matrine derivatives for the intervention of non-alcoholic fatty liver disease.

Thirty new tricyclicmatrinic derivatives were successively synthesized and evaluated for their inhibitory activity on the accumulation of triglycerides (TG) in AML12 cells, using 12 N-m-trifluoromethylbenzenesulfonyl matrine (1) as the hit compound. Among the analogues, compound 7n possessing 11-trimethylbutylamine quaternary exerted the highest in vitro TG-lowering potency, as well as a good safety profile. 7n significantly attenuated the hepatic injury and steatosis, and ameliorated dyslipidemia and dysglycemia in the mice with non-alcoholic fatty liver disease (NAFLD) induced by a high-fat diet. Primary mechanism study revealed that upregulation of peroxisome proliferator-activated receptors α (PPARα)-carnitine palmitoyltransferase 1A (CPT1A) pathway mediated the efficacy of 7n. Our study provides powerful information for developing this kind of compound into a new class of anti-NAFLD candidates, and compound 7n is worthy of further investigation as an ideal lead compound.

Extracellular vesicles derived from endothelial cells modulate macrophage phenotype in vitro.

Extracellular vesicles (EVs) mediate cell-to-cell communication by horizontally transferring biological materials from host cells to target cells. During exposure to pathogens, pathogen-associated molecular patterns (e.g., lipopolysaccharide, LPS) get in contact with endothelial cells and stimulate the secretion of endothelial cell-derived EVs (E-EVs). The triggered EVs secretion is known to have a modulating influence on the EVs-receiving cells. Macrophages, a major component of innate immunity, are polarized upon receiving external inflammatory stimuli, in which toll-like receptor4 (TLR4)-nuclear factor kappa B (NFκB) pathway plays a key role. However, the functions of LPS-induced E-EVs (ELPS-EVs) in modulating macrophage phenotype and activation remain elusive. We collected the EVs from quiescent endothelial cells (ENor-EVs) and ELPS-EVs to detect their stimulatory role on NR8383 macrophages. Isolated EVs were characterized by transmission electron microscopy (TEM), western blot assay, and nanoparticle tracking analysis (NTA). NR8383 macrophages were stimulated with ELPS-EVs, ENor-EVs, or PBS for 24 h. Hereafter, the uptake of EVs by the macrophages was investigated. Upon EVs stimulation, cellular viability was determined by MTT assay, while macrophage phenotype was analyzed by flow cytometry and immunofluorescence analysis. Furthermore, a western blot assay was conducted to evaluate the potentially involved TLR4-NFκB pathway. Interestingly, upon exposure to LPS, endothelial cells secreted significantly higher amounts of EVs (i.e., ELPS-EVs) when compared to quiescent cells or cells in PBS. The ELPS-EVs were also better internalized by NR8383 macrophages than ENor-EVs. The cellular viability of ELPS-EVs-treated macrophages was 1.2 times higher than those in the ENor-EVs and PBS groups. In addition, ELPS-EVs modulated NR8383 macrophages towards a proinflammatory macrophage M1-like phenotype. This was indicated by the significantly upregulated expressions of proinflammatory macrophage biomarkers CD86 and inducible nitric oxide synthase (iNOS) observed in ELPS-EVs-treated macrophages. The TLR4-NFκB signaling pathway was substantially activated in ELPS-EVs-treated macrophages, indicated by the elevated expressions of makers TLR4 and phosphorylated form of nuclear factor kappa B p65 subunit (p-NFκBp65). Overall, our results indicate that E-EVs play a crucial role in macrophage phenotype modulation under inflammatory conditions.

Basolateral Amygdala Cannabinoid CB1 Receptor Controls Formation and Elimination of Social Fear Memory.

Patients with post-traumatic stress disorder (PTSD) usually manifest persistence of the traumatic memory for a long time after the event, also known as resistance to extinction learning. Numerous studies have shown that the endocannabinoid system, specifically the cannabinoid type-1 receptor (CB1R), plays an important role in traumatic memory. However, the effect of basolateral amygdala (BLA) CB1R in social fear memory formation and elimination is still unclear. Here, we built a mouse model of social avoidance induced by acute social defeat stress to investigate the role of BLA CB1R in social fear memory formation and anxiety- and depression-like behavior. Anterograde knockout of CB1R in BLA neurons facilitates social fear memory formation and manifests an anxiolytic effect but does not influence sociability and social novelty. Retrograde knockout of CB1R in BLA promotes social fear memory formation and shows an anxiogenic effect but does not affect sociability and social novelty. Moreover, intracerebral injection of the CB1R antagonist AM251 in BLA during the memory reconsolidation time window eliminates social fear memory. Our findings suggest the CB1R of BLA can be used as a novel molecular target in social fear memory formation and elimination and potential PTSD therapy with memory retrieval and AM251.

D3CARP: a comprehensive platform with multiple-conformation based docking, ligand similarity search and deep learning approaches for target prediction and virtual screening.

Resource- and time-consuming biological experiments are unavoidable in traditional drug discovery, which have directly driven the evolution of various computational algorithms and tools for drug-target interaction (DTI) prediction. For improving the prediction reliability, a comprehensive platform is highly expected as some previously reported webservers are small in scale, single-method, or even out of service. In this study, we integrated the multiple-conformation based docking, 2D/3D ligand similarity search and deep learning approaches to construct a comprehensive webserver, namely D3CARP, for target prediction and virtual screening. Specifically, 9352 conformations with positive control of 1970 targets were used for molecular docking, and approximately 2 million target-ligand pairs were used for 2D/3D ligand similarity search and deep learning. Besides, the positive compounds were added as references, and related diseases of therapeutic targets were annotated for further disease-based DTI study. The accuracies of the molecular docking and deep learning approaches were 0.44 and 0.89, respectively. And the average accuracy of five ligand similarity searches was 0.94. The strengths of D3CARP encompass the support for multiple computational methods, ensemble docking, utilization of positive controls as references, cross-validation of predicted outcomes, diverse disease types, and broad applicability in drug discovery. The D3CARP is freely accessible at https://www.d3pharma.com/D3CARP/index.php.

ETCM v2.0: An update with comprehensive resource and rich annotations for traditional Chinese medicine.

Existing traditional Chinese medicine (TCM)-related databases are still insufficient in data standardization, integrity and precision, and need to be updated urgently. Herein, an Encyclopedia of Traditional Chinese Medicine version 2.0 (ETCM v2.0, http://www.tcmip.cn/ETCM2/front/#/) was constructed as the latest curated database hosting 48,442 TCM formulas recorded by ancient Chinese medical books, 9872 Chinese patent drugs, 2079 Chinese medicinal materials and 38,298 ingredients. To facilitate the mechanistic research and new drug discovery, we improved the target identification method based on a two-dimensional ligand similarity search module, which provides the confirmed and/or potential targets of each ingredient, as well as their binding activities. Importantly, five TCM formulas/Chinese patent drugs/herbs/ingredients with the highest Jaccard similarity scores to the submitted drugs are offered in ETCM v2.0, which may be of significance to identify prescriptions/herbs/ingredients with similar clinical efficacy, to summarize the rules of prescription use, and to find alternative drugs for endangered Chinese medicinal materials. Moreover, ETCM v2.0 provides an enhanced JavaScript-based network visualization tool for creating, modifying and exploring multi-scale biological networks. ETCM v2.0 may be a major data warehouse for the quality marker identification of TCMs, the TCM-derived drug discovery and repurposing, and the pharmacological mechanism investigation of TCMs against various human diseases.

Evolution and Discovery of Matrine Derivatives as a New Class of Anti-Hepatic Fibrosis Agents Targeting Ewing Sarcoma Breakpoint Region 1 (EWSR1).

A series of new tricyclic matrinane derivatives were continuously synthesized and evaluated for their inhibitory effects on genes and proteins related to hepatic fibrosis at the cellular level, including collagen type I α1 chain (COL1A1), α smooth muscle actin (α-SMA), connective tissue growth factor (CTGF), and matrix metalloprotein 2 (MMP-2). Among them, compound 6k exerted an appealing potency and significantly reduced liver injury and fibrosis in both bile duct ligation (BDL) rats and Mdr2 knockout mice. An activity-based protein profiling (ABPP) assay indicated that 6k might directly bind to Ewing sarcoma breakpoint region 1 (EWSR1) to inhibit its function and affect the expression of downstream liver fibrosis-related genes and thus regulate liver fibrosis. These results provided a potential novel target for the treatment of liver fibrosis and powerful information for the development of tricyclic matrinanes into promising anti-hepatic fibrosis agents.

Preferred microenvironments of halogen bonds and hydrogen bonds revealed using statistics and QM/MM calculation studies.

Hydrogen bonds (HBs) and halogen bonds (XBs) are two essential non-covalent interactions for molecular recognition and drug design. As proteins are heterogeneous in structure, the microenvironments of protein structures should have effects on the formation of HBs and XBs with ligands. However, there are no systematic studies reported on this effect to date. For quantitatively describing protein microenvironments, we defined the local hydrophobicities (LHs) and local dielectric constants (LDCs) in this study. With the defined parameters, we conducted an elaborate database survey on the basis of 22 011 ligand-protein structures to explore the microenvironmental preference of HBs (91 966 in total) and XBs (1436 in total). The statistics show that XBs prefer hydrophobic microenvironments compared to HBs. The polar residues like ASP are more likely to form HBs with ligands, while nonpolar residues such as PHE and MET prefer XBs. Both the LHs and LDCs (10.69 ± 4.36 for HBs; 8.86 ± 4.00 for XBs) demonstrate that XBs are prone to hydrophobic microenvironments compared with HBs with significant differences (p < 0.001), indicating that evaluating their strengths in the corresponding environments should be necessary. Quantum Mechanics-Molecular Mechanics (QM/MM) calculations reveal that in comparison with vacuum environments, the interaction energies of HBs and XBs are decreased to varying degrees given different microenvironments. In addition, the strengths of HBs are impaired more than those of XBs when the local dielectric constant's difference between the XB microenvironments and the HB microenvironments is large.

Discovery and identification of EIF2AK2 as a direct key target of berberine for anti-inflammatory effects.

Using chemoproteomic techniques, we first identified EIF2AK2, eEF1A1, PRDX3 and VPS4B as direct targets of berberine (BBR) for its synergistically anti-inflammatory effects. Of them, BBR has the strongest affinity with EIF2AK2 via two ionic bonds, and regulates several key inflammatory pathways through EIF2AK2, indicating the dominant role of EIF2AK2. Also, BBR could subtly inhibit the dimerization of EIF2AK2, rather than its enzyme activity, to selectively modulate its downstream pathways including JNK, NF-κB, AKT and NLRP3, with an advantage of good safety profile. In EIF2AK2 gene knockdown mice, the inhibitory IL-1ß, IL-6, IL-18 and TNF-α secretion of BBR was obviously attenuated, confirming an EIF2AK2-dependent anti-inflammatory efficacy. The results highlight the BBR's network mechanism on anti-inflammatory effects in which EIF2AK2 is a key target, and inhibition of EIF2AK2 dimerization has a potential to be a therapeutic strategy against inflammation-related disorders.

Bioactive compounds from Huashi Baidu decoction possess both antiviral and anti-inflammatory effects against COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic is an ongoing global health concern, and effective antiviral reagents are urgently needed. Traditional Chinese medicine theory-driven natural drug research and development (TCMT-NDRD) is a feasible method to address this issue as the traditional Chinese medicine formulae have been shown effective in the treatment of COVID-19. Huashi Baidu decoction (Q-14) is a clinically approved formula for COVID-19 therapy with antiviral and anti-inflammatory effects. Here, an integrative pharmacological strategy was applied to identify the antiviral and anti-inflammatory bioactive compounds from Q-14. Overall, a total of 343 chemical compounds were initially characterized, and 60 prototype compounds in Q-14 were subsequently traced in plasma using ultrahigh-performance liquid chromatography with quadrupole time-of-flight mass spectrometry. Among the 60 compounds, six compounds (magnolol, glycyrrhisoflavone, licoisoflavone A, emodin, echinatin, and quercetin) were identified showing a dose-dependent inhibition effect on the SARS-CoV-2 infection, including two inhibitors (echinatin and quercetin) of the main protease (Mpro), as well as two inhibitors (glycyrrhisoflavone and licoisoflavone A) of the RNA-dependent RNA polymerase (RdRp). Meanwhile, three anti-inflammatory components, including licochalcone B, echinatin, and glycyrrhisoflavone, were identified in a SARS-CoV-2-infected inflammatory cell model. In addition, glycyrrhisoflavone and licoisoflavone A also displayed strong inhibitory activities against cAMP-specific 3',5'-cyclic phosphodiesterase 4 (PDE4). Crystal structures of PDE4 in complex with glycyrrhisoflavone or licoisoflavone A were determined at resolutions of 1.54 Å and 1.65 Å, respectively, and both compounds bind in the active site of PDE4 with similar interactions. These findings will greatly stimulate the study of TCMT-NDRD against COVID-19.

Molecular dynamics study on the behavior and binding mechanism of target protein Transgelin-2 with its agonist TSG12 for anti-asthma drug discovery.

Transgelin-2 (TG2) is a novel promising therapeutic target for the treatment of asthma as it plays an important role in relaxing airway smooth muscles and reducing pulmonary resistance in asthma. The compound TSG12 is the only reported TG2 agonist with in vivo anti-asthma activity. However, the dynamic behavior and ligand binding sites of TG2 and its binding mechanism with TSG12 remain unclear. In this study, we performed 12.6 µs molecular dynamics (MD) simulations for apo-TG2 and TG2-TSG12 complex, respectively. The results suggested that the apo-TG2 has 4 most populated conformations, and that its binding of the agonist could expand the conformation distribution space of the protein. The simulations revealed 3 potential binding sites in 3 most populated conformations, one of which is induced by the agonist binding. Free energy decomposition uncovered 8 important residues with contributions stronger than -1 kcal/mol. Computational alanine scanning for the important residues by 100 ns conventional MD simulation for each mutated TG2-TSG12 complexes demonstrated that E27, R49 and F52 are essential residues for the agonist binding. These results should be helpful to understand the dynamic behavior of TG2 and its binding mechanism with the agonist TSG12, which could provide some structural insights into the novel mechanism for anti-asthma drug development.

Biochar improves soil quality and wheat yield in saline-alkali soils beyond organic fertilizer in a 3-year field trial.

The objective of this study was to examine the effects of biochar compared to organic fertilizer on soil quality and wheat yield in the saline-alkaline lands. A 3-year field trial was conducted on moderately saline-alkaline land in the Yellow River Delta region (YRD) with six treatments: biochar (B1: 5 t, B2: 10 t, B3: 20 t ha-1 year-1) and organic fertilizer (OF1: 5 t, OF2: 7.5 t ha-1 year-1) as well as control (CK). The results showed that both biochar and organic fertilizer increased total organic carbon (TOC), total nitrogen (TN), NH4+-N, and NO3--N, and reduced pH, thereby increasing soil microbial biomass carbon (MBC) and nitrogen (MBN), MBC/TOC ratio, and MBN/TN ratio, but organic fertilizer increased soil nutrients and microbial biomass better than biochar. Correlation analysis revealed that soil water content (SWC), soil salt content (SSC), and Na+ were the most important factors influencing wheat yield. When compared to CK, the SSC and Na+ decreased by 5.55-7.52% and 3.86-9.39%, respectively, and SWC increased by 5.14-5.62% in the biochar treatment, while they increased by 1.07-10.19%, 1.08-7.58%, and 2.96-3.84% in the organic fertilizer treatment, respectively. Accordingly, wheat yield of biochar treatment was 0.90-14.71% higher than that of organic fertilizer treatment (4.49-4.80 t ha-1) and CK (4.47 t ha-1). Collectively, B2 had the lowest SSC and Na+ and the highest yield and was significantly better than the organic fertilizer treatment, as well as efficiently increasing soil nutrients and microbial biomass, suggesting that it may be a better agricultural practice for improving soil quality and increasing wheat yield in the YRD.