Resveratrol ameliorates aging-related metabolic phenotypes by inhibiting cAMP phosphodiesterases.

Resveratrol, a polyphenol in red wine, has been reported as a calorie restriction mimetic with potential antiaging and antidiabetogenic properties. It is widely consumed as a nutritional supplement, but its mechanism of action remains a mystery. Here, we report that the metabolic effects of resveratrol result from competitive inhibition of cAMP-degrading phosphodiesterases, leading to elevated cAMP levels. The resulting activation of Epac1, a cAMP effector protein, increases intracellular Ca(2+) levels and activates the CamKKß-AMPK pathway via phospholipase C and the ryanodine receptor Ca(2+)-release channel. As a consequence, resveratrol increases NAD(+) and the activity of Sirt1. Inhibiting PDE4 with rolipram reproduces all of the metabolic benefits of resveratrol, including prevention of diet-induced obesity and an increase in mitochondrial function, physical stamina, and glucose tolerance in mice. Therefore, administration of PDE4 inhibitors may also protect against and ameliorate the symptoms of metabolic diseases associated with aging.

3D-SMGE: a pipeline for scaffold-based molecular generation and evaluation.

In the process of drug discovery, one of the key problems is how to improve the biological activity and ADMET properties starting from a specific structure, which is also called structural optimization. Based on a starting scaffold, the use of deep generative model to generate molecules with desired drug-like properties will provide a powerful tool to accelerate the structural optimization process. However, the existing generative models remain challenging in extracting molecular features efficiently in 3D space to generate drug-like 3D molecules. Moreover, most of the existing ADMET prediction models made predictions of different properties through a single model, which can result in reduced prediction accuracy on some datasets. To effectively generate molecules from a specific scaffold and provide basis for the structural optimization, the 3D-SMGE (3-Dimensional Scaffold-based Molecular Generation and Evaluation) work consisting of molecular generation and prediction of ADMET properties is presented. For the molecular generation, we proposed 3D-SMG, a novel deep generative model for the end-to-end design of 3D molecules. In the 3D-SMG model, we designed the cross-aggregated continuous-filter convolution (ca-cfconv), which is used to achieve efficient and low-cost 3D spatial feature extraction while ensuring the invariance of atomic space rotation. 3D-SMG was proved to generate valid, unique and novel molecules with high drug-likeness. Besides, the proposed data-adaptive multi-model ADMET prediction method outperformed or maintained the best evaluation metrics on 24 out of 27 ADMET benchmark datasets. 3D-SMGE is anticipated to emerge as a powerful tool for hit-to-lead structural optimizations and accelerate the drug discovery process.

Ergone Derivatives from the Deep-Sea-Derived Fungus Aspergillus terreus YPGA10 and 25,28-Dihydroxyergone-Induced Apoptosis in Human Colon Cancer SW620 Cells.

Ten new ergone derivatives (1-10) and five known analogues (11-15) were isolated from the deep-sea-derived fungus Aspergillus terreus YPGA10. The structures including the absolute configurations were established by detailed analysis of the NMR spectroscopic data, HRESIMS, ECD calculation, and coupling constant calculation. All the structures are characterized by a highly conjugated 25-hydroxyergosta-4,6,8(14),22-tetraen-3-one nucleus. Structurally, compound 2 bearing a 15-carbonyl group and compounds 5-7 possessing a 15ß-OH/OCH3 group are rarely encountered in ergone derivatives. Bioassay results showed that compounds 1 and 11 demonstrated cytotoxic effects on human colon cancer SW620 cells with IC50 values of 8.4 and 3.1 µM, respectively. Notably, both compounds exhibited negligible cytotoxicity on the human normal lung epithelial cell BEAS-2B. Compound 11 was selected for preliminary mechanistic study and was found to inhibit cell proliferation and induce apoptosis in human colon cancer SW620 cells. In addition, compound 1 displayed cytotoxic activity against five human leukemia cell lines with IC50 values ranging from 5.7 to 8.9 µM. Our study demonstrated that compound 11 may serve as a potential candidate for the development of anticolorectal cancer agents.

Discovery of Oxidized p-Terphenyls as Phosphodiesterase 4 Inhibitors from Marine-Derived Fungi.

Four new p-terphenyl derivatives, talaroterphenyls A-D (1-4), together with three biosynthetically related known ones (5-7), were obtained from the mangrove sediment-derived Talaromyces sp. SCSIO 41412. Compounds 1-3 are rare p-terphenyls, which are completely substituted on the central benzene ring by oxygen atoms; this is the first report of their isolation from natural sources. Their structures were elucidated through NMR spectroscopy, HRESIMS, and X-ray diffraction. Genome sequence analysis revealed that 1-7 were biosynthesized from tyrosine and phenylalanine, involving four key biosynthetic genes (ttpB-ttpE). These p-terphenyls (1-7) and 36 marine-derived terphenyl analogues (8-43) were screened for phosphodiesterase 4 (PDE4) inhibitory activities, and 1-5, 14, 17, 23, and 26 showed notable activities with IC50 values of 0.40-16 µM. The binding pattern of p-terphenyl inhibitors 1-3 with PDE4 were explored by molecular docking analysis. Talaroterphenyl A (1), with a low cytotoxicity, showed obvious anti-inflammatory activity in LPS-stimulated RAW264.7 cells. Furthermore, in the TGF-ß1-induced medical research council cell strain-5 (MRC-5) pulmonary fibrosis model, 1 could down-regulate the expression levels of FN1, COL1, and α-SMA significantly at concentrations of 5-20 µM. This study suggests that the oxidized p-terphenyl 1, as a marine-derived PDE4 inhibitor, could be used as a promising antifibrotic agent.

Structural optimization of Moracin M as novel selective phosphodiesterase 4 inhibitors for the treatment of idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, and high mortality lung disease. Although the antifibrotic drugs pirfenidone and nintedanib could slow the rate of lung function decline, the usual course of the condition is inexorably to respiratory failure and death. Therefore, new approaches and novel therapeutic drugs for the treatment of IPF are urgently needed. And the selective PDE4 inhibitor has in vivo and in vitro anti-fibrotic effects in IPF models. But the clinical application of most PDE4 inhibitors are limited by their unexpected and severe side effects such as nausea, vomiting, and diarrhea. Herein, structure-based optimizations of the natural product Moracin M resulted in a novel a novel series of 2-arylbenzofurans as potent PDE4 inhibitors. The most potent inhibitor L13 has an IC50 of 36 ± 7 nM with remarkable selectivity across the PDE families and administration of L13·citrate (10.0 mg/kg) exhibited comparable anti-pulmonary fibrosis effects to pirfenidone (300 mg/kg) in a bleomycin-induced IPF mice model, indicate that L13 is a potential lead for the treatment of IPF.

An Open Source Graph-Based Weighted Cycle Closure Method for Relative Binding Free Energy Calculations.

Free energy perturbation-relative binding free energy (FEP-RBFE) prediction has shown its reliability and accuracy in the prediction of protein-ligand binding affinities, which plays a fundamental role in structure-based drug design. In FEP-RBFE predictions, the calculation of each mutation path is associated with a statistical error, and cycle closure (cc) has proven to be an effective method in improving the calculation accuracy by correcting the hysteresis (summation of errors) of each closed cycle to the theoretical value 0. However, a primary hypothesis was made in the current cycle closure method that the hysteresis is evenly distributed to all paths, which is unlikely to be true in practice and may limit the further improvement of the calculation accuracy when better error estimation methods are available. Moreover, being a closed source software makes the current cycle closure method unachievable in many studies. In this paper, a newly implemented open source graph-based weighted cycle closure (wcc) algorithm was developed and introduced, not only including functions from the original cc method but also containing a new wcc method which can consider different error contributions from different paths and further improve the calculation accuracy. The wcc program also provides a new path-independent molecular error calculation method, which can be quite useful in many studies (like structure-activity relationship (SAR)) compared with the path-dependent method of the original cc program.

Accelerating and Automating the Free Energy Perturbation Absolute Binding Free Energy Calculation with the RED-E Function.

The accurate prediction of the binding affinities between small molecules and biological macromolecules plays a fundamental role in structure-based drug design, which is still challenging. The free energy perturbation-based absolute binding free energy (FEP-ABFE) approach has shown potential in its reliability. To correctly calculate the energy related to the ligand being restrained by the receptor, additional restraints between the ligand and the receptor are needed. However, determining the restraint parameters for individual ligands empirically is too trivial to be automated, and usually gives rise to numerical instabilities, which set back the applications of FEP-ABFE. To address these issues, we derived the analytical expression for the probability distribution of energy differences, P(ΔU), during the process of restraint addition, which is called the RED-E (restraint energy distribution at equilibrium position) function. Simulations indicated that the RED-E function can accurately describe P(ΔU) when restraints are added at the equilibrium position. Based on the RED-E function, an automatic restraint selection method was proposed to select the best restraint. With this method, there is a high phase-space overlap between the free and restrained states, such that using a 2-λ perturbation can accurately calculate the free energy of the restraint addition, which is a nearly 6 times acceleration compared with current widely used 12-λ perturbation method. The RED-E function gives insight into the non-Gaussian behavior of the sampled P(ΔU) in certain FEP processes in an analytical way. The highly automated and accelerated restraint selection also makes it possible for the large-scale application of FEP-ABFE in real drug discovery practices.

Structure Revisions of Phenolic Bisabolane Sesquiterpenes and a Ferroptosis Inhibitor from the Marine-Derived Fungus Aspergillus versicolor YPH93.

Seven new phenolic bisabolane sesquiterpenoids (1-7), along with 10 biogenetically related analogues (8-17), were obtained from the deep-sea-derived fungus Aspergillus versicolor YPH93. The structures were elucidated based on extensive analyses of the spectroscopic data. Compounds 1-3 are the first examples of phenolic bisabolanes that contain two hydroxy groups attached to the pyran ring. The structures of sydowic acid derivatives (1-6 and 8-10) were carefully studied, leading to the structure revisions of six known analogues, including a revision of the absolute configuration for sydowic acid (10). All metabolites were evaluated for their effects on ferroptosis. Compound 7 exerted inhibition on erastin/RSL3-induced ferroptosis with EC50 values ranging from 2 to 4 µM, while it exhibited no effects on TNFα-induced necroptosis or H2O2-induced cell necrosis.

Identify potent SARS-CoV-2 main protease inhibitors via accelerated free energy perturbation-based virtual screening of existing drugs.

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global crisis. There is no therapeutic treatment specific for COVID-19. It is highly desirable to identify potential antiviral agents against SARS-CoV-2 from existing drugs available for other diseases and thus repurpose them for treatment of COVID-19. In general, a drug repurposing effort for treatment of a new disease, such as COVID-19, usually starts from a virtual screening of existing drugs, followed by experimental validation, but the actual hit rate is generally rather low with traditional computational methods. Here we report a virtual screening approach with accelerated free energy perturbation-based absolute binding free energy (FEP-ABFE) predictions and its use in identifying drugs targeting SARS-CoV-2 main protease (Mpro). The accurate FEP-ABFE predictions were based on the use of a restraint energy distribution (RED) function, making the practical FEP-ABFE-based virtual screening of the existing drug library possible. As a result, out of 25 drugs predicted, 15 were confirmed as potent inhibitors of SARS-CoV-2 Mpro The most potent one is dipyridamole (inhibitory constant Ki = 0.04 µM) which has shown promising therapeutic effects in subsequently conducted clinical studies for treatment of patients with COVID-19. Additionally, hydroxychloroquine (Ki = 0.36 µM) and chloroquine (Ki = 0.56 µM) were also found to potently inhibit SARS-CoV-2 Mpro We anticipate that the FEP-ABFE prediction-based virtual screening approach will be useful in many other drug repurposing or discovery efforts.

Free energy perturbation-based large-scale virtual screening for effective drug discovery against COVID-19.

As a theoretically rigorous and accurate method, FEP-ABFE (Free Energy Perturbation-Absolute Binding Free Energy) calculations showed great potential in drug discovery, but its practical application was difficult due to high computational cost. To rapidly discover antiviral drugs targeting SARS-CoV-2 Mpro and TMPRSS2, we performed FEP-ABFE-based virtual screening for ∼12,000 protein-ligand binding systems on a new generation of Tianhe supercomputer. A task management tool was specifically developed for automating the whole process involving more than 500,000 MD tasks. In further experimental validation, 50 out of 98 tested compounds showed significant inhibitory activity towards Mpro, and one representative inhibitor, dipyridamole, showed remarkable outcomes in subsequent clinical trials. This work not only demonstrates the potential of FEP-ABFE in drug discovery but also provides an excellent starting point for further development of anti-SARS-CoV-2 drugs. Besides, ∼500 TB of data generated in this work will also accelerate the further development of FEP-related methods.

Therapeutic targets and potential agents for the treatment of COVID-19.

The outbreak of coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, has become a global crisis. As of November 9, COVID-19 has already spread to more than 190 countries with 50,000,000 infections and 1,250,000 deaths. Effective therapeutics and drugs are in high demand. The structure of SARS-CoV-2 is highly conserved with those of SARS-CoV and Middle East respiratory syndrome-CoV. Enzymes, including RdRp, Mpro /3CLpro , and PLpro , which play important roles in viral transcription and replication, have been regarded as key targets for therapies against coronaviruses, including SARS-CoV-2. The identification of readily available drugs for repositioning in COVID-19 therapy is a relatively rapid approach for clinical treatment, and a series of approved or candidate drugs have been proven to be efficient against COVID-19 in preclinical or clinical studies. This review summarizes recent progress in the development of drugs against SARS-CoV-2 and the targets involved.

Discovery of effective phosphodiesterase 2 inhibitors with antioxidant activities for the treatment of Alzheimer's disease.

The multi-target-directed-ligand (MTDL) strategy has been widely applied in the discovery of novel drugs for the treatment of Alzheimer's disease (AD) because of the multifactorial pathological mechanisms of AD. Phosphodiesterase-2 (PDE2) has been identified to be a novel and promising target for AD. However, MTDL combining with the inhibitory activity against PDE2A and other anti-AD factors such as antioxidants has not been developed yet. Herein, a novel series of PDE2 inhibitors with antioxidant capacities were designed, synthesized, and evaluated. Most compounds showed remarkable inhibitory activities against PDE2A as well as antioxidant activities. Compound 6d was selected, which showed good IC50 of 6.1 nM against PDE2A, good antioxidant activity (ORAC (Trolox) = 8.4 eq.) and no cytotoxicity to SH-SY5Y cells. Molecular docking and dynamics simulations were applied for the rational design and explanation of structure-activity relationship (SAR) of lead compounds.

Design, synthesis and biological evaluation of novel pyrazolopyrimidone derivatives as potent PDE1 inhibitors.

Phosphodiesterase-1 (PDE1) is a promising drug target closely related to central and peripheral diseases. With the assistance of molecular docking and dynamics simulations, we designed and synthesized a novel series of pyrazolopyrimidone derivatives as effective and metabolically stable inhibitors against PDE1. Most compounds have good inhibitory activities against PDE1 at the concentration of 20 nM. Compound 2j with the IC50 of 21 nM against PDE1B, shows good metabolic stability in the rat liver microsomes (RLM) (t1/2 of 28.5 min), indicating that compound 2j can be used as a tool to explore the molecular recognition mechanism between inhibitors and the target protein PDE1.

Occupational noise exposure and the prevalence of dyslipidemia in a cross-sectional study.

BACKGROUND: Occupational noise exposure was related to cardiovascular disease, of which dyslipidemia was an important inducement. This study investigated the relationship between occupational noise exposure and dyslipidemia. METHODS: Four hundred ninety-two occupational noise-exposed workers and 664 non-exposed workers were recruited to conduct environmental noise tests and personal occupational physical examinations. A lasso-logistic regression model was used to estimate the relative risk of dyslipidemia. A restricted cubic spline was used to estimate the association between noise exposure years and dyslipidemia after adjusting for potential confounding factors. RESULTS: A crude association was observed between the occupational noise exposure (75-85 dB(A)) and dyslipidemia. After adjusting for confounding factors, there was a non-linear relationship between noise exposure years and dyslipidemia (P for non-linearity =0.01). Workers exposed to 75-85 dB(A) for 11 to 24.5 years had a higher risk of dyslipidemia than non-exposed workers. CONCLUSIONS: A positive and non-linear exposure-response relationship was found in workers exposed to 75-85 dB(A) whose exposure years were between 11 and 24.5. Workers had the highest risk of dyslipidemia when exposed for 13.5 years.

Heightened Local Th17 Cell Inflammation Is Associated with Severe Community-Acquired Pneumonia in Children under the Age of 1 Year.

Severe community-acquired pneumonia (sCAP) early in life is a leading cause of morbidity, mortality, and irreversible sequelae. Herein, we report the clinical, etiological, and immunological characteristics of 62 children age < 1 year. We measured 27 cytokines in plasma and bronchoalveolar lavage (BAL) from 62 children age < 1 year who were diagnosed with CAP, and then, we analyzed correlations among disease severity, clinical parameters, and etiology. Of the entire cohort, three cytokines associated with interleukin-17- (IL-17-) producing helper T cells (Th17 cells), IL-1ß, IL-6, and IL-17, were significantly elevated in sCAP patients with high fold changes (FCs); in BAL, these cytokines were intercorrelated and associated with blood neutrophil counts, Hb levels, and mixed bacterial-viral infections. BAL IL-1ß (area under the curve (AUC) 0.820), BAL IL-17 (AUC 0.779), and plasma IL-6 (AUC 0.778) had remarkable predictive power for sCAP. Our findings revealed that increased local Th17 cell immunity played a critical role in the development of sCAP in children age < 1 year. Th17 cell-related cytokines could serve as local and systemic inflammatory indicators of sCAP in this age group.

Design, Synthesis, and Evaluation of Dihydropyranopyrazole Derivatives as Novel PDE2 Inhibitors for the Treatment of Alzheimer's Disease.

Phosphodiesterase 2 (PDE2) has been regarded as a novel target for the treatment of Alzheimer's disease (AD). In this study, we obtained (R)-LZ77 as a hit compound with moderate PDE2 inhibitory activity (IC50 = 261.3 nM) using a high-throughput virtual screening method based on molecular dynamics. Then, we designed and synthesized 28 dihydropyranopyrazole derivatives as PDE2 inhibitors. Among them, compound (+)-11h was the most potent PDE2 inhibitor, with an IC50 value of 41.5 nM. The molecular docking of PDE2-(+)-11h reveals that the 4-(trifluoromethyl)benzyl)oxyl side chain of the compound enters the H-pocket and forms strong hydrophobic interactions with L770/L809/F862, which improves inhibitory activity. The above results may provide insight for further structural optimization of highly potent PDE2 inhibitors and may lay the foundation for their use in the treatment of AD.

The immunomodulatory role of PDEs inhibitors in immune cells: therapeutic implication in rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterized by inflammatory synovitis and progressive joint. Although the etiology is extremely complex, overwhelming evidence suggests that dysregulation or imbalance of the immune system plays a central role in disease pathogenesis. The bone loss and joint destruction are immunological insults mediated by infiltration and abnormal activation of various immune cells. Since pharmacological inhibition of cyclic nucleotide phosphodiesterases (PDEs), which degrade cyclic AMP and cyclic GMP, can regulate the activity of multiple immune cells, which are considered as a potential strategy for treating RA. Therefore, this review attempted to summarize the modulating effects of PDEs on immune cells and described the molecular underpinnings and potential clinical application of PDEs inhibitors for RA.

Design, synthesis and evaluation of pyrazolopyrimidinone derivatives as novel PDE9A inhibitors for treatment of Alzheimer's disease.

Phosphodiesterase-9 (PDE9) is a promising target for the treatment of Alzheimer's disease (AD). To discover efficient PDE9 inhibitors with good metabolic stability and solubility, a series of novel pyrazolopyrimidinone derivatives have been designed with the assistance of molecular docking and dynamics simulations. All the fourteen synthesized compounds gave excellent inhibition ratio against PDE9 at 10 nM. Compound 1k with the IC50 of 2.0 nM against PDE9, showed good metabolic stability (t1/2 of 57 min) in the RLM as well as good solubility (195 mg/L). The analysis on binding modes of targeted compounds may provide insight for further structural modification.

Single-Particle Enzyme Activity Assay with Spectral-Resolved Dark-Field Optical Microscopy.

In a clinical assay, enzymes are essential biomarkers for human disease diagnosis. In this work, a spectral-resolved single-particle detection (SPD) method is introduced to quantify alkaline phosphatase (ALP) activity in human serum with a supraparticle (SP) based on MnO2-modified gold nanoparticle (denoted as GNP@MnO2 SP) as the probe. In the presence of ALP, 2-phospho-l-ascorbic acid trisodium salt can be hydrolyzed into l-ascorbic acid, which serves as a good reduction agent to trigger the decomposition of the MnO2 shell on the GNP surface. Given that a trace amount of ALP exists, noticeable scattering color change can be detected at the single-particle level due to the sensitive localized surface plasmon resonance (LSPR) effect from GNPs. With spectral-resolved dark-field optical microscopy, a linear dynamic range of 0.06 to 2.48 mU/mL ( R2 = 0.99) and a very low limit of detection of 5.8 µU/mL for the ALP assay are readily achieved, which is more sensitive over the methods based on ensemble sample measurement. As a consequence, this strategy opens a new avenue for the design of an ultrasensitive detection method for disease-correlated biomarker diagnosis in the future.

Dual functional cholinesterase and PDE4D inhibitors for the treatment of Alzheimer's disease: Design, synthesis and evaluation of tacrine-pyrazolo[3,4-b]pyridine hybrids.

A series of tacrine-pyrazolo[3,4-b]pyridine hybrids were synthesised and evaluated as dual cholinesterase (ChE) and phosphodiesterase 4D (PDE4D) inhibitors for the treatment of Alzheimer's disease (AD). Compound 10j, which is tacrine linked with pyrazolo[3,4-b]pyridine moiety by a six-carbon spacer, was the most potent acetylcholinesterase (AChE) with IC50 value of 0.125 µM. Moreover, compound 10j provided a desired balance of AChE and butylcholinesterase (BuChE) and PDE4D inhibition activities, with IC50 value of 0.449 and 0.271 µM, respectively. The above results indicated that this hybrid was a promising dual functional agent for the treatment of AD.