Novel tumor necrosis factor-α (TNF-α) inhibitors from small molecule library screening for their therapeutic activity profiles against rheumatoid arthritis using target-driven approaches and binary QSAR models

Deep learning based predictive modeling to screen natural compounds against TNF-alpha for the potential management of rheumatoid arthritis: Virtual screening to comprehensive in silico investigation

Rheumatoid arthritis (RA) affects an estimated 0.1% to 2.0% of the world's population, leading to a substantial impact on global health. The adverse effects and toxicity associated with conventional RA treatment pathways underscore the critical need to seek potential new therapeutic candidates, particularly those of natural sources that can treat the condition with minimal side effects. To address this challenge, this study employed a deep-learning (DL) based approach to conduct a virtual assessment of natural compounds against the Tumor Necrosis Factor-alpha (TNF-α) protein. TNF-α stands out as the primary pro-inflammatory cytokine, crucial in the development of RA. Our predictive model demonstrated appreciable performance, achieving MSE of 0.6, MAPE of 10%, and MAE of 0.5. The model was then deployed to screen a comprehensive set of 2563 natural compounds obtained from the Selleckchem database. Utilizing their predicted bioactivity (pIC50), the top 128 compounds were identified. Among them, 68 compounds were taken for further analysis based on drug-likeness analysis. Subsequently, selected compounds underwent additional evaluation using molecular docking (< - 8.7 kcal/mol) and ADMET resulting in four compounds posing nominal toxicity, which were finally subjected to MD simulation for 200 ns. Later on, the stability of complexes was assessed via analysis encompassing RMSD, RMSF, Rg, H-Bonds, SASA, and Essential Dynamics. Ultimately, based on the total binding free energy estimated using the MM/GBSA method, Imperialine, Veratramine, and Gelsemine are proven to be potential natural inhibitors of TNF-α.

Comprehending interaction mechanism of natural actives of Colchicum autumnale L. for rheumatoid arthritis using integrative chemoinformatic approaches

This research delves into the realm of therapeutic potential within natural compounds derived from Colchicum autumnale L., emphasizing a holistic perspective on medications used in human therapy. Rather than confining the study to their primary actions, the research endeavors to unveil molecular targets for these natural compounds, with a specific focus on their potential applicability in the treatment of rheumatoid arthritis (RA). The study focuses on understanding interactions between specific natural actives that target RA. Fifteen RA target proteins were identified from OMIM, GeneScan and PharmaGKB. Their structures were downloaded from RCSB PDB. Two active components of C. autumnale L. were chosen for mass spectrometry investigation. Ligand characteristics were determined using the ADMETlab and SwissADME software tools. Molecular docking was performed, and the top three complexes were simulated for 200 ns, along with identification of free binding energies. The compounds β-sitosterol-IL-10 (-6.50 kcal/mol), colchicine-IL-10 (-6.01 kcal/mol), linoleic acid-IL-10 (-7.22 kcal/mol) and linoleic acid-IL-10 (-7.22 kcal/mol) exhibited best binding energies. β-Sitosterol and colchicine showed the highest stability in simulations, confirmed by molecular mechanics free energy binding calculations. This work provides insights into the molecular interaction of natural compounds against RA targets, offering potential therapeutic anti-RA medications.

Molecular Docking and Dynamics Simulations of Ammi visnaga L. Constituents as Antimelanogenic, Anti-Inflammatory and Anticoagulant Agents

In this study, anti-melanogenic, anti-inflammatory and anti-coagulant potentials of eighteen selected constituents of Ammi visnaga L. were investigated by Induced Fit Docking (IFD) and molecular dynamic simulation with Schrödinger software. The binding free energies of the selected natural compounds were computed by means of ΔG MM-GBSA studies. Anti-melanogetic activity of the constituent against agaricus bisporus tyrosinase, Priestia megaterium tyrosinase and Homo sapiens tyrosinase were evaluated. The result showed that apiumetin had more negative binding free energy against three tyrosinase enzymes than cognate ligands, tropolone and kojic acid. Docking analysis was also performed to predict the constituents with anti-inflammatory activity against human Tumor necrosis factor, Cyclooxygenase-2, Prostaglandin D2 11-ketoreductase AKR1C3 and Prostaglandin reductase PTGR2. The results showed that pyranocoumarins (visnadin, dihydrosamidin, samidin) have more negative binding free energy against Cyclooxygenase-2 and Prostaglandin D2 11-ketoreductase receptors than cognate drugs, rofecoxib and indomethacin. In addition, docking analysis shows that pyranocoumarins, apiumetin and cimifugin have more negative binding free energy against Vitamin K epoxide reductase than S-warfarin drug, predicting that they have anticoagulant activity. Furthermore, the constituents and their cognate drugs were subjected to 100 ns MD Simulation to predict their stability at the active sites of the enzymes.

Network pharmacology combined with metabolomics and lipidomics to reveal the hypolipidemic mechanism of Alismatis rhizoma in hyperlipidemic mice

Alismatis rhizoma (AR), the dried rhizome of Alisma orientale (Sam) Juzep, is effective in treating hyperlipidemia, but the mechanisms involved require further exploration. This study evaluated the hypolipidemic properties of AR using an integrated strategy combining network pharmacology with metabolomics and lipidomics. Firstly, a hyperlipidemia mouse model induced by a high-fat diet was established to evaluate the therapeutic effects of AR. Secondly, plasma metabolomics and lipidomics were used to identify differential metabolites and lipids, and metabolic pathway analysis was performed using MetaboAnalyst. Thirdly, network pharmacology, based on the metabolic profile of AR in vivo, was used to discover potential therapeutic targets. Finally, key targets were obtained through a compound-target-metabolite network, which was verified by molecular docking and quantitative real-time PCR (qPCR). Biochemistry analysis and histological examinations showed that AR exerted hypolipidemic effects on hyperlipidemic mice. Seventy potential biomarkers for the AR treatment of hyperlipidemia were identified by metabolomics and lipidomics, which were mainly involved in lipid metabolism, energy metabolism and amino acid metabolism. Eighteen potentially active compounds were identified in the plasma of mice after oral administration of AR, which were associated with 83 potential therapeutic targets. The PPAR signaling pathway was considered a crucial signaling pathway of AR against hyperlipidemia by KEGG analysis. The joint analysis showed that 6 upstream key targets were regulated by AR, including ALB, TNF, IL1B, MMP9, PPARA and PPARG. Molecular docking showed that active compounds of AR had high binding affinity with these key targets. qPCR further demonstrated that AR could reverse the mRNA expression of these key targets in hyperlipidemic mice. This study integrates network pharmacology with metabolomics and lipidomics to reveal the regulatory effects of AR on endogenous metabolites and validates key therapeutic targets, and represents the most systematic and in-depth study on the hypolipidemic activity of AR.

In Silico Drug Repurposing for Anti-Inflammatory Therapy: Virtual Search for Dual Inhibitors of Caspase-1 and TNF-Alpha

Inflammation involves a complex biological response of the body tissues to damaging stimuli. When dysregulated, inflammation led by biomolecular mediators such as caspase-1 and tumor necrosis factor-alpha (TNF-alpha) can play a detrimental role in the progression of different medical conditions such as cancer, neurological disorders, autoimmune diseases, and cytokine storms caused by viral infections such as COVID-19. Computational approaches can accelerate the search for dual-target drugs able to simultaneously inhibit the aforementioned proteins, enabling the discovery of wide-spectrum anti-inflammatory agents. This work reports the first multicondition model based on quantitative structure–activity relationships and a multilayer perceptron neural network (mtc-QSAR-MLP) for the virtual screening of agency-regulated chemicals as versatile anti-inflammatory therapeutics. The mtc-QSAR-MLP model displayed accuracy higher than 88%, and was interpreted from a physicochemical and structural point of view. When using the mtc-QSAR-MLP model as a virtual screening tool, we could identify several agency-regulated chemicals as dual inhibitors of caspase-1 and TNF-alpha, and the experimental information later retrieved from the scientific literature converged with our computational results. This study supports the capabilities of our mtc-QSAR-MLP model in anti-inflammatory therapy with direct applications to current health issues such as the COVID-19 pandemic.

Screening of the small molecule library of Meinox enables the identification of anticancer compounds in pathologically distinct cancers

Small molecules are widely used for the modulation of the molecular basis of diseases. This makes them the perfect tool for discovering and developing new therapeutics. In this work, we have established a library of small molecules in house and characterized its molecular and druglike properties. We have shown that most small molecules have molecular weights less than 450. They have pharmaceutically relevant cLogP, cLogS, and druglikeness value distributions. In addition, Meinox’s small molecule library contained small molecules with polar surface areas that are less than 60 square angstroms, suggesting their potent ability to cross the blood-brain barrier. Meinox’s small molecule library was also tested in vitro for pathologically distinct forms of cancer, including pancreatic adenocarcinoma PANC1, breast carcinoma MCF7, and lymphoblastic carcinoma RS4-11 cell lines. Analysis of this library at a dose of 1 μM allowed the discovery of potent, specific or broadly active anticancer compounds against pathologically distinct cancers. This study shows that in vitro analysis of different cancers or other phenotypic assays with Meinox small molecule library may generate novel and potent bioassay-specific compounds.

Predictive value of PAPP-A for ectopic pregnancy and analysis of related factors

The present study was designed to analyze the expression of pregnancy-associated plasma protein-A (PAPP-A) in the serum of patients with ectopic pregnancy (EP) and related factors inducing this condition. Seventy-five patients with EP admitted to the Affiliated Hospital of Jining Medical University from January 2018 to February 2019 were selected as the research group, and another 59 healthy pregnant women of the corresponding age, gravidity and gestational week were enrolled in the control group. ELISA was employed to detect the serum expression levels of PAPP-A and inflammatory factors such as interleukin-8 (IL-8) and tumor necrosis factor-α (TNF-α). ROC was adopted to evaluate the diagnostic value of serum PAPP-A in patients with EP, and Pearson correlation coefficient was applied to analyze the correlation of PAPP-A with inflammatory factors IL-8 and TNF-α. Serum PAPP-A expression was significantly lower in EP patients than those in the control group. The area under the curve (AUC) of serum PAPP-A in diagnosing EP patients was 0.812, and the PAPP-A value in the control group was significantly higher than that of the research group at 7-8 weeks and ≥9 weeks. With regard to the expression of inflammatory factors, the research group presented markedly higher IL-8 and TNF-α levels than the control group. PAPP-A was negatively related to inflammatory factors IL-8 and TNF-α in the research group. In addition, it was revealed that patients with a history of genital surgery, salpingotomy, pelvic infection, EP or low PAPP-A expression were at high risk of EP. In conclusion, PAPP-A was revealed to be lowly expressed in the serum of EP patients, and to negatively be correlated with inflammatory factors IL-8 and TNF-α, which may serve as a useful marker for the diagnosis and prognosis of EP.

Human mesenchymal stem cells promote ischemic repairment and angiogenesis of diabetic foot through exosome miRNA-21-5p

BACKGROUND

Diabetic foot is caused by ischemic disease of lower extremities of diabetic patients, and the effective therapy is very limited. Mesenchymal stem cells (MSCs) based cell therapy had been developed into a new treatment strategy for diabetic foot clinically. However, the underlying molecular mechanism remains to be fully addressed. Exosomes (extracellular vesicles) secreted by MSCs may play crucial role in the processes of MSCs mediated inhibition of inflammatory microenvironment as well as pro-angiogenesis of ischemic tissue of diabetic foot.

METHODS

Exosomes were isolated from MSCs using ultracentrifugation, and further characterized by the nanoparticle tracking analyzer and flow cytometry. Moreover, RNA sequencing, Western Blot, in vitro cell proliferation, in vivo pro-angiogenesis, as well as ischemic repairment of diabetic foot through rat model were performed to evaluate exosome physiological functions.

RESULTS

We found that inflammatory cytokines (tumor necrosis factor α and interleukin-6) and vascularcelladhesion molecule-1 induced MSCs to secrete exosomes heterogeneously, including exosome size and quantity. Through RNA sequencing, we defined a new proangiogenic miRNA, miRNA-21-5p. Further knockdown and overexpression of miRNA-21-5p by manipulating MSCs validated the biological activity of exosome miRNA-21-5p, including in vitro cell proliferation, in vivo pro-angiogenesis in Chick Chorioallantoic Membrane (CAM) assay, and in vivo pro-angiogenesis experiments (tissue injury and repair) in diabetic rat models. Furthermore, we discovered that exosome^miRNA-21-5p promoted angiogenesis through upregulations of vascular endothelial growth factor receptor (VEGFR) as well as activations of serine/threonine kinase (AKT) and mitogen-activated protein kinase (MAPK). Together, our work suggested miRNA-21-5p could be a novel mechanism by which exosomes promote ischemic tissue repair and angiogenesis. Meanwhile, miRNA-21-5p could be potentially developed into a new biomarker for exosomes of MSCs to treat diabetic foot.

CONCLUSIONS

miRNA-21-5p is a new biomarker and a novel mechanism by which exosomes promote ischemic tissue repair and angiogenesis of diabetic foot. Our work could not only provide new scientific evidences for revealing pro-angiogenesis mechanism of MSCs, but also eventually benefit MSCs-based clinical therapy for diabetic foot of diabetes patients.

Investigations of adsorption behavior and anti-inflammatory activity of glycine functionalized Al12N12 and Al12ON11 fullerene-like cages

The adsorption behavior of the amino acid, glycine (Gly), via the carboxyl, hydroxyl, and amino groups onto the surfaces of Al₁₂N₁₂ and Al₁₆N₁₆ fullerene-like cages were computationally evaluated by the combination of density functional theory (DFT) and molecular docking studies. It was found that Gly can chemically bond with the Al₁₂N₁₂ and Al₁₆N₁₆ fullerene-like cages as its amino group being more favorable to interact with the aluminum atoms of the adsorbents compared to carboxyl and hydroxyl groups. Oxygen and carbon doping were reported to reduce steric hindrance for Glycine interaction at Al site of Al₁₂ON₁₁/Gly and Al₁₂CN₁₁/Gly complexes. Interaction was further enhanced by oxygen doping due to its greater electron withdrawing effect. Herein, the Al₁₂ON₁₁/Gly complex where two carbonyl groups of Gly are bonded to the aluminum atoms of the Al₁₂N₁₂ fullerene-like cage is the most stable interaction configuration showing ∆_adsH and ∆_adsG values of -81.74 kcal/mol and -66.21 kcal/mol, respectively. Computational studies also revealed the frequency shifts that occurred due to the interaction process. Molecular docking analysis revealed that the Al₁₂N₁₂/Gly (-11.7 kcal/mol) and the Al₁₂ON₁₁/Gly (-9.2 kcal/mol) complexes have a good binding affinity with protein tumor necrosis factor alpha (TNF-α). TNF-α was implicated as a key cytokine in various diseases, and it has been a validated therapeutic target for the treatment of rheumatoid arthritis. These results suggest that the Al₁₂N₁₂/Gly complex in comparison with the Al₁₆N₁₆/Gly, Al₁₂ON₁₁/Gly, and the Al₁₂CN₁₁/Gly complexes could be efficient inhibitors of TNF-α.

Integrating Ligand and Target-Driven Based Virtual Screening Approaches With in vitro Human Cell Line Models and Time-Resolved Fluorescence Resonance Energy Transfer Assay to Identify Novel Hit Compounds Against BCL-2

Antiapoptotic members of B-cell leukemia/lymphoma-2 (BCL-2) family proteins are one of the overexpressed proteins in cancer cells that are oncogenic targets. As such, targeting of BCL-2 family proteins raises hopes for new therapeutic discoveries. Thus, we used multistep screening and filtering approaches that combine structure and ligand-based drug design to identify new, effective BCL-2 inhibitors from a small molecule database (Specs SC), which includes more than 210,000 compounds. This database is first filtered based on binary “cancer-QSAR” model constructed with 886 training and 167 test set compounds and common 26 toxicity quantitative structure-activity relationships (QSAR) models. Predicted non-toxic compounds are considered for target-driven studies. Here, we applied two different approaches to filter and select hit compounds for further in vitro biological assays and human cell line experiments. In the first approach, a molecular docking and filtering approach is used to rank compounds based on their docking scores and only a few top-ranked molecules are selected for further long (100-ns) molecular dynamics (MD) simulations and in vitro tests. While docking algorithms are promising in predicting binding poses, they can be less prone to precisely predict ranking of compounds leading to decrease in the success rate of in silico studies. Hence, in the second approach, top-docking poses of each compound filtered through QSAR studies are subjected to initially short (1 ns) MD simulations and their binding energies are calculated via molecular mechanics generalized Born surface area (MM/GBSA) method. Then, the compounds are ranked based on their average MM/GBSA energy values to select hit molecules for further long MD simulations and in vitro studies. Additionally, we have applied text-mining approaches to identify molecules that contain “indol” phrase as many of the approved drugs contain indole and indol derivatives. Around 2700 compounds are filtered based on “cancer-QSAR” model and are then docked into BCL-2. Short MD simulations are performed for the top-docking poses for each compound in complex with BCL-2. The complexes are again ranked based on their MM/GBSA values to select hit molecules for further long MD simulations and in vitro studies. In total, seven molecules are subjected to biological activity tests in various human cancer cell lines as well as Time-Resolved Fluorescence Resonance Energy Transfer (TR-FRET) assay. Inhibitory concentrations are evaluated, and biological activities and apoptotic potentials are assessed by cell culture studies. Four molecules are found to be limiting the proliferation capacity of cancer cells while increasing the apoptotic cell fractions.

The Role of NF-κB in Physiological Bone Development and Inflammatory Bone Diseases: Is NF-κB Inhibition "Killing Two Birds with One Stone"?

Nuclear factor-κB (NF-κB) is a transcription factor that regulates the expression of various genes involved in inflammation and the immune response. The activation of NF-κB occurs via two pathways: inflammatory cytokines, such as TNF-α and IL-1β, activate the "classical pathway", and cytokines involved in lymph node formation, such as CD40L, activate the "alternative pathway". NF-κB1 (p50) and NF-κB2 (p52) double-knockout mice exhibited severe osteopetrosis due to the total lack of osteoclasts, suggesting that NF-κB activation is required for osteoclast differentiation. These results indicate that NF-κB may be a therapeutic target for inflammatory bone diseases, such as rheumatoid arthritis and periodontal disease. On the other hand, mice that express the dominant negative form of IκB kinase (IKK)-β specifically in osteoblasts exhibited increased bone mass, but there was no change in osteoclast numbers. Therefore, inhibition of NF-κB is thought to promote bone formation. Taken together, the inhibition of NF-κB leads to "killing two birds with one stone": it suppresses bone resorption and promotes bone formation. This review describes the role of NF-κB in physiological bone metabolism, pathologic bone destruction, and bone regeneration.

Characterization of inflammatory factor-induced changes in mesenchymal stem cell exosomes and sequencing analysis of exosomal microRNAs

BACKGROUND

Treatments utilizing stems cells often require stem cells to be exposed to inflammatory environments, but the effects of such environments are unknown.

AIM

To examine the effects of inflammatory cytokines on the morphology and quantity of mesenchymal stem cell exosomes (MSCs-exo) as well as the differential expression of microRNAs (miRNAs) in the exosomes.

METHODS

MSCs were isolated from human umbilical tissue by enzymatic digestion. Exosomes were then collected after a 48-h incubation period in a serum-free medium with one of the following the inflammatory cytokines: None (control), vascular cell adhesion molecule-1 (VCAM-1), tumor necrosis factor (TNF) α, and interleukin (IL) 6. The morphology and quantity of each group of MSC exosomes were observed and measured. The miRNAs in MSCs-exo were sequenced. We compared the sequenced data with the miRBase and other non-coding databases in order to detect differentially expressed miRNAs and explore their target genes and regulatory mechanisms. In vitro tube formation assays and Western blot were performed in endothelial cells which were used to assess the angiogenic potential of MSCs-exo after inflammatory cytokine stimulation.

RESULTS

MSCs-exo were numerous, small, and regularly shaped in the VCAM-1 group. TNFα stimulated MSCs to secrete larger and irregular exosomes. IL6 led to a reduced quantity of MSCs-exo. Compared to the control group, the TNFα and IL6 groups had more downregulated differentially expressed miRNAs, particularly angiogenesis-related miRNAs. The angiogenic potential of MSCs-exo declined after IL6 stimulation.

CONCLUSION

TNFα and IL6 may influence the expression of miRNAs that down-regulate the PI3K-AKT, MAPK, and VEGF signaling pathways; particularly, IL6 significantly down-regulates the PI3K-AKT signaling pathway. Overall, inflammatory cytokines may lead to changes in exosomal miRNAs that abnormally impact cellular components, molecular function, and biological processes.