Receptor Ligands Research Articles

Classification of Dopamine D2 receptor ligands using RDKit Molecular descriptors and Machine Learning Algorithms

Identifying and classifying dopamine D2 receptor agonists and antagonists is essential for the drug discovery and development. In this study, we employed machine learning algorithms, namely, XGBoost, LGBM, ExtraTree, and AdaBoost Classifier, in combination with RDKit molecular descriptors, to classify dopamine D2 receptor ligands. The dataset consisted of 195 molecules, comprising 69 dopamine agonists and 126 dopamine antagonists. The models were trained using 75% of the dataset and evaluated on the remaining 25%. The classifiers demonstrated high accuracy and F1 scores, with the AdaBoost Classifier achieving the highest accuracy of 92%. Receiver operating characteristic (ROC) analysis further confirmed the robustness of the model, as indicated by the area under the curve (AUC) values. The AUC values for the AdaBoost, Extra Tree, LGBM, and XGB classifiers were 0.92, 0.90, 0.87, and 0.89, respectively. Feature selection analysis revealed the important molecular descriptors that significantly contribute to the classification models. The ExtraTree classifier selected the highest number of descriptors (167), while the intersection of the selected descriptors among all models indicated 24 common features that crucial for classification. Classification of external compounds using the developed models revealed that sinedabet was classified as a dopamine D2 receptor antagonist, while lisuride, ropinirole, and quinpirole were classified as dopamine D2 receptor agonists.

Low-Basicity 5-HT6 Receptor Ligands from the Group of Cyclic Arylguanidine Derivatives and Their Antiproliferative Activity Evaluation

The serotonin 5-HT6 receptor (5-HT6R), expressed almost exclusively in the brain, affects the Cdk5 signaling as well as the mTOR pathway. Due to the association of 5-HT6R signaling with pathways involved in cancer progression, we decided to check the usefulness of 5-HT6R ligands in the treatment of CNS tumors. For this purpose, a new group of low-base 5-HT6R ligands was developed, belonging to arylsulfonamide derivatives of cyclic arylguanidines. The selected group of molecules was also tested for their antiproliferative activity on astrocytoma (1321N1) and glioblastoma (U87MG, LN-229, U-251) cell lines. Some of the molecules were subjected to ADMET tests in vitro, including lipophilicity, drug binding to plasma proteins, affinity for phospholipids, drug–drug interaction (DDI), the penetration of the membrane (PAMPA), metabolic stability, and hepatotoxicity as well as in vivo cardiotoxicity in the Danio Rerio model. Two antagonists with an affinity constant Ki < 50 nM (PR 68 Ki = 37 nM) were selected. These compounds were characterized by very high selectivity. An analysis of pharmacokinetic parameters for the lead compound PR 68 confirmed favorable properties for administration, including passive diffusion and acceptable metabolic stability (metabolized in 49%, MLMs). The compound did not exhibit the potential for drug–drug interactions.

Systems pharmacology-based drug discovery from Amaryllidaceae alkaloids and investigation of mechanisms of action in treatment of Alzheimer’s disease

Abstract Objectives Given the success of galanthamine in treating Alzheimer’s disease, this study aims to establish an effective method to find drugs from Amaryllidaceae alkaloids and to clarify its mechanism in treating Alzheimer’s disease. Methods The pharmacodynamic basis and mechanism of action between Amaryllidaceae alkaloids and Alzheimer’s disease were explored by constructing a compound-target-disease network, targets protein-protein interaction, gene ontology, Kyoto Encyclopedia of Genes and Genomes pathway enrichment, and molecular docking verification. Key findings In total, a chemical library of 357 potential alkaloids was constructed. A total of 100 active alkaloid components were identified. Thirty-nine associated targets were yielded based on network construction, and the key targets were defined as HSP90AA1, ESR1, NOS3, PTGS2, and PPARG using protein–protein interaction network. Gene ontology items (490) and 68 Kyoto Encyclopedia of Genes and Genomes pathways were selected through the enrichment of target functions, including neuroactive ligand–receptor interaction, calcium signaling pathway, cAMP signaling pathway, Alzheimer disease, and serotonergic synapse that were related to Alzheimer’s disease. Lastly, molecular docking demonstrated good stability in combining selected alkaloids with targets. Conclusions This study explained the mechanisms of Amaryllidaceae alkaloids in preventing and treating Alzheimer’s disease and established a novel strategy to discover new drugs from biological chemical sources.

Therapeutic Potential of Foodborne Indole Derived from Chinese Stinky Tofu in Reducing Intestinal Inflammation and Enhancing Barrier Function to Mitigate Alcoholic Liver Injury.

Indole, a compound in Chinese stinky tofu (ST), acts as a ligand for the aryl hydrocarbon receptor (AHR). Despite extensive research on prebiotic compounds, indole's specific role in ST remains unexplored. This study used an ethanol gavage method to create an ALD (alcoholic liver disease) mouse model and investigate dietary indole's effects on the intestinal barrier. Our findings indicate that after 6 weeks of being fed ST, the indole present (2 mg/day) robustly activated the intestinal AHR, upregulating its target gene, CYP1A1 (cytochrome P450 1A1 enzyme). This activation significantly reduced intestinal permeability, mitigated alcohol-induced oxidative stress and inflammation, and restored intestinal barrier function. Consequently, the study demonstrates that foodborne indole substantially reduces alcohol absorption and lowers the expression levels of liver inflammation-related factors, thereby slowing the progression of ALD. These results highlight indole's therapeutic potential for treating ALD and its role in developing functional foods.

Ligand Recognition and Activation Mechanism of the Alicarboxylic Acid Receptors

Endogenous ligands for alicarboxylic acid receptors are important metabolic intermediates that play a significant role in regulating body energy and maintaining homeostasis. However, the molecular mechanism of alicarboxylate ligand-mediated counterpart receptors is currently unclear. We resolve the active state structure of HCA2-niacin, and the structural analysis explains the mechanism of niacin selectivity in the alicarboxylic acid receptors family. Homology modeling, molecular dynamics simulation and mutagenesis experiments reveal different ligand recognition modes and activation mechanisms of the alicarboxylic acid receptors, analyze the flexibility of the binding pocket and elucidate the important role of disulfide bonds on receptor activation and ligand binding. These more detailed molecular mechanisms further elucidate the relevant mechanisms of human metabolism and provide key clues for subsequent drug development of alicarboxylic acid receptors.

Enhancing cancer immunotherapy using cordycepin and Cordyceps militaris extract to sensitize cancer cells and modulate immune responses

Integrating immunotherapy with natural compounds holds promise in enhancing the immune system’s ability to eliminate cancer cells. Cordyceps militaris, a traditional Chinese medicine, emerges as a promising candidate in this regard. This study investigates the effects of cordycepin and C. militaris ethanolic extract (Cm-EE) on sensitizing cancer cells and regulating immune responses against breast cancer (BC) and hepatocellular carcinoma (HCC) cells. Cordycepin, pentostatin and adenosine were identified in Cm-EE. Cordycepin treatment decreased HLA-ABC-positive cells in pre-treated cancer cells, while Cm-EE increased NKG2D ligand and death receptor expression. Additionally, cordycepin enhanced NKG2D receptor and death ligand expression on CD3-negative effector immune cells, particularly on natural killer (NK) cells, while Cm-EE pre-treatment stimulated IL-2, IL-6, and IL-10 production. Co-culturing cancer cells with effector immune cells during cordycepin or Cm-EE incubation resulted in elevated cancer cell death. These findings highlight the potential of cordycepin and Cm-EE in improving the efficacy of cancer immunotherapy for BC and HCC.

Exploring the potential of Scabiosa columbaria in Alzheimer's disease treatment: An in silico approach

ObjectivesAlzheimer's disease (AD) is posing an increasing global threat and currently lacks effective treatments. Therefore, this study was aimed at exploring phytochemicals in Scabiosa columbaria (S. columbaria) as inhibitors of acetylcholinesterase (AChE), β-site APP cleavage enzyme 1 (BACE1), and TNF-α converting enzyme (TACE) in AD. S. columbaria contains various bioactive compounds, such as chlorogenic acid, linalool, and catechins, which are known for their detoxification properties, capacity to resist and manage harmful moisture buildup, and therapeutic roles in COVID-19. Several studies have also shown that S. columbaria extract has strong antioxidant activity, and may potentially decrease neuroinflammation in AD. Therefore, this study investigated the interactions between S. columbaria phytochemicals and key enzymes associated with AD, thus providing opportunities for the development of new therapeutic candidates. MethodsA total of 27 phytochemicals were evaluated for their inhibitory activity against AChE, BACE1, and TACE with YASARA Structure. ADMET profiles and toxicity were assessed. The top candidate compounds underwent 100 ns MD simulations. ResultsAll ligands met Lipinski's rule and showed low toxicity. Catechins, compared with the known drug galantamine, showed higher inhibitory activity and interacted with additional active sites on AChE, thus suggesting potentially higher efficacy. Moreover, chlorogenic acid showed stronger inhibitory activity against TACE than the control drug (aryl-sulfonamide), thereby suggesting a different mechanism of action. MD simulation revealed that the formed complexes had good stability. However, further exploration is necessary. ConclusionS. columbaria derivative compounds are promising drug candidates because of their properties, including the affinity of chlorogenic acid toward TACE and hydrogen bond enhancing ligand–receptor interactions. MD simulation indicated stable ligand–protein complexes, and the radius of gyration and MM-PBSA calculations revealed favorable binding and interaction energies. Our findings demonstrate the identified compounds' potential for further drug development.

Cationic Lipid Modification of Nuclear Hormone Receptor-Ligands: A Strategy for Developing a New Class of Targeted Anticancer Therapeutics

Ubiquitous expression patterns of nuclear hormone and their receptors (NHRs) have their own roles in performing essential functions in controlling hormone responsive element-promoted gene transcription. In diseased states such as cancer, NHRs play crucial roles and hence targeting these receptors are essential as it gives us a window of opportunity for developing targeted anticancer therapeutics. In comparison to traditional chemotherapy drugs, targeted therapeutic drugs are hypothetically advantageous in terms of efficacy and safety and hence the idea of developing such targeted drugs are inclined to become a mainstream cancer treatment option. This review selectively compiles data regarding NHR-targeting, while majorly focusing on cancer treatment using anticancer small molecules and/or nanotherapeutics targeting estrogen receptor, progesterone receptor, glucocorticoid receptor, and vitamin D receptor. In this study, we selectively emphasized on estrogen receptor. Herein, we mainly highlight the strategy of lipid-modification to convert respective receptor ligands into NHR-targeted anticancer molecules as well as nanotherapeutics. We focused on the strategy of chemical conjugation of those ligands with twin-aliphatic carbon chain-based cationic lipids. The strategy successfully led to the development of a new class of anticancer therapeutics. These are either small-molecule anticancer agents or selfaggregating nanotherapeutics. In spite of great anticancer output, the concept of NHR-targeted anti-cancer therapy still needs to overcome further hurdles before those are projected for clinical settings.

Systematic Evaluation of Regiochemistry and Lipidation of Aryl Trehalose Mincle Agonists.

The Macrophage-Inducible C-type Lectin receptor (Mincle) plays a critical role in innate immune recognition and pathology, and therefore represents a promising target for vaccine adjuvants. Innovative trehalose-based Mincle agonists with improved pharmacology and potency may prove useful in the development of Th17-mediated adaptive immune responses. Herein, we report on in vitro and in silico investigations of specific Mincle ligand-receptor interactions required for the effective receptor engagement and activation of Th17-polarizing cytokines. Specifically, we employed a library of trehalose benzoate scaffolds, varying the degree of aryl lipidation and regiochemistry that produce inflammatory cytokines in a Mincle-dependent fashion. In vitro interleukin-6 (IL-6) cytokine production by human peripheral blood mononuclear cells (hPBMCs) indicated that the lipid regiochemistry is key to potency and maximum cytokine output, with the tri-substituted compounds inducing higher levels of IL-6 in hPBMCs than the di-substituted derivatives. Additionally, IL-6 production trended higher after stimulation with compounds that contained lipids ranging from five to eight carbons long, compared to shorter (below five) or longer (above eight) carbon chains, across all the substitution patterns. An analysis of the additional cytokines produced by hPBMCs revealed that compound 4d, tri-substituted and five carbons long, induced significantly greater levels of interleukin-1β (IL-1β), tumor necrosis factor- α (TNF-α), interleukin-23 (IL-23), and interferon- γ (IFN-γ) than the other compounds tested in this study. An in silico assessment of 4d highlighted the capability of this analogue to bind to the human Mincle carbohydrate recognition domain (CRD) efficiently. Together, these data highlight important structure-activity findings regarding Mincle-specific cytokine induction, generating a lead adjuvant candidate for future formulations and immunological evaluations.

CollectNET: a web server for integrated inference of cell-cell communication network.

Cell-cell communication (CCC) through ligand-receptor (L-R) pairs forms the cornerstone for complex functionalities in multicellular organisms. Deciphering such intercellular signaling can contribute to unraveling disease mechanisms and enable targeted therapy. Nonetheless, notable biases and inconsistencies are evident among the inferential outcomes generated by current methods for inferring CCC network. To fill this gap, we developed collectNET (http://health.tsinghua.edu.cn/collectnet) as a comprehensive web platform for analyzing CCC network, with efficient calculation, hierarchical browsing, comprehensive statistics, advanced searching, and intuitive visualization. collectNET provides a reliable online inference service with prior knowledge of three public L-R databases and systematic integration of three mainstream inference methods. Additionally, collectNET has assembled a human CCC atlas, including 126 785 significant communication pairs based on 343 023 cells. We anticipate that collectNET will benefit researchers in gaining a more holistic understanding of cell development and differentiation mechanisms. Database URL: http://health.tsinghua.edu.cn/collectnet.

The Interactions of T Cells with Myeloid-Derived Suppressor Cells in Peripheral Blood Stem Cell Grafts.

The interaction of myeloid-derived suppressor cells (MDSCs) with T cells within G-CSF-mobilized peripheral blood stem cell (PBSC) grafts in patients undergoing autologous or allogeneic hematopoietic stem cell transplantation remains to be elucidated. Through studying allo- and auto-PBSC grafts, we observed grafts containing large numbers of T cells and MDSCs with intergraft variability in their percentage and number. T cells from autologous grafts compared to allografts expressed relative higher percentages of inhibitory receptors PD-1, CTLA-4, TIM-3, LAG-3, TIGIT and BTLA. Autograft T cells had decreased cell proliferation and IFN-γ secretion, which supported the possible presence of T cell exhaustion. On the contrary, graft monocytic MDSCs (M-MDSCs) expressed multiple inhibitory receptor ligands, including PD-L1, CD86, Galectin-9, HVEM and CD155. The expression of inhibitory receptor ligands on M-MDSCs was correlated with their corresponding inhibitory receptors on T cells in the grafts. Isolated M-MDSCs had the ability to suppress T cell proliferation and IFN-γ secretion and/or promote Treg expansion. Blocking the PD-L1-PD-1 signaling pathway partially reversed the functions of M-MDSCs. Taken together, our data indicated that T cells and M-MDSCs in PBSC grafts express complementary inhibitory receptor-ligand pairing, which may impact the quality of immune recovery and clinical outcome post transplantation.

Multi‑omics identification of a signature based on malignant cell-associated ligand–receptor genes for lung adenocarcinoma

PurposeLung adenocarcinoma (LUAD) significantly contributes to cancer-related mortality worldwide. The heterogeneity of the tumor immune microenvironment in LUAD results in varied prognoses and responses to immunotherapy among patients. Consequently, a clinical stratification algorithm is necessary and inevitable to effectively differentiate molecular features and tumor microenvironments, facilitating personalized treatment approaches.MethodsWe constructed a comprehensive single-cell transcriptional atlas using single-cell RNA sequencing data to reveal the cellular diversity of malignant epithelial cells of LUAD and identified a novel signature through a computational framework coupled with 10 machine learning algorithms. Our study further investigates the immunological characteristics and therapeutic responses associated with this prognostic signature and validates the predictive efficacy of the model across multiple independent cohorts.ResultsWe developed a six-gene prognostic model (MYO1E, FEN1, NMI, ZNF506, ALDOA, and MLLT6) using the TCGA-LUAD dataset, categorizing patients into high- and low-risk groups. This model demonstrates robust performance in predicting survival across various LUAD cohorts. We observed distinct molecular patterns and biological processes in different risk groups. Additionally, analysis of two immunotherapy cohorts (N = 317) showed that patients with a high-risk signature responded more favorably to immunotherapy compared to those in the low-risk group. Experimental validation further confirmed that MYO1E enhances the proliferation and migration of LUAD cells.ConclusionWe have identified malignant cell-associated ligand–receptor subtypes in LUAD cells and developed a robust prognostic signature by thoroughly analyzing genomic, transcriptomic, and immunologic data. This study presents a novel method to assess the prognosis of patients with LUAD and provides insights into developing more effective immunotherapies.

Ablation of LRP6 in alpha-smooth muscle actin-expressing cells abrogates lung inflammation and fibrosis upon bleomycin-induced lung injury.

Low-density lipoprotein receptor-related protein 6 (LRP6) is a receptor for Wnt ligands. Tissue fibrosis is a progressive pathological process with excessive extracellular matrix proteins (ECM) deposition. Myofibroblasts, identified by alpha-smooth muscle actin (αSMA) expression, play an important role in tissue fibrosis by producing ECM production. Here we found that Wnt antagonist Dickkopf1 (DKK1) induced gene expressions associated with inflammation and fibrosis in lung fibroblasts. We demonstrated that genetic deletion of LRP6 in αSMA-expressing cells using Acta2 -cre Lrp6 fl/fl ( Lrp6 AKO ) mice abrogated bleomycin (BLM)-induced lung inflammation and fibrosis phenotype, suggesting an important role of LRP6 in modulating inflammation and fibrotic processes in the lung. Our results highlight the crucial role of LRP6 in fibroblasts in regulating inflammation and fibrosis upon BLM-induced lung injury.

Model-Informed Radiopharmaceutical Therapy Optimization: A Study on the Impact of PBPK Model Parameters on Physical, Biological, and Statistical Measures in 177Lu-PSMA Therapy.

Purpose: To investigate the impact of physiologically based pharmacokinetic (PBPK) parameters on physical, biological, and statistical measures in lutetium-177-labeled radiopharmaceutical therapies (RPTs) targeting the prostate-specific membrane antigen (PSMA). Methods: Using a clinically validated PBPK model, realistic time-activity curves (TACs) for tumors, salivary glands, and kidneys were generated based on various model parameters. These TACs were used to calculate the area-under-the-TAC (AUC), dose, biologically effective dose (BED), and figure-of-merit BED (fBED). The effects of these parameters on radiobiological, pharmacokinetic, time, and statistical features were assessed. Results: Manipulating PBPK parameters significantly influenced AUC, dose, BED, and fBED outcomes across four different BED models. Higher association rates increased AUC, dose, and BED values for tumors, with minimal impact on non-target organs. Increased internalization rates reduced AUC and dose for tumors and kidneys. Higher serum protein-binding rates decreased AUC and dose for all tissues. Elevated tumor receptor density and ligand amounts enhanced uptake and effectiveness in tumors. Larger tumor volumes required dosimetry adjustments to maintain efficacy. Setting the tumor release rate to zero intensified the impact of association and internalization rates, enhancing tumor targeting while minimizing the effects on salivary glands and kidneys. Conclusions: Optimizing PBPK parameters can enhance the efficacy of lutetium-177-labeled RPTs targeting PSMA, providing insights for personalized and effective treatment regimens to minimize toxicity and improve therapeutic outcomes.

Single-Cell RNA Sequencing Reveals Transcriptional Signatures and Cell-Cell Communication in Diabetic Retinopathy.

Diabetic retinopathy (DR) is a major cause of vision loss in workingage individuals worldwide. Cell-to-cell communication between retinal cells and retinal pigment epithelial cells (RPEs) in DR is still unclear, so this study aimed to generate a single-cell atlas and identify receptor‒ligand communication between retinal cells and RPEs. A mouse single-cell RNA sequencing (scRNA-seq) dataset was retrieved from the GEO database (GSE178121) and was further analyzed with the R package Seurat. Cell cluster annotation was performed to further analyze cell‒cell communication. The differentially expressed genes (DEGs) in RPEs were explored through pathway enrichment analysis and the protein‒ protein interaction (PPI) network. Core genes in the PPI were verified by quantitative PCR in ARPE-19 cells. We observed an increased proportion of RPEs in STZ mice. Although some overall intercellular communication pathways did not differ significantly in the STZ and control groups, RPEs relayed significantly more signals in the STZ group. In addition, THBS1, ITGB1, COL9A3, ITGB8, VTN, TIMP2, and FBN1 were found to be the core DEGs of the PPI network in RPEs. qPCR results showed that the expression of ITGB1, COL9A3, ITGB8, VTN, TIMP2, and FBN1 was higher and consistent with scRNA-seq results in ARPE-19 cells under hyperglycemic conditions. Our study, for the first time, investigated how signals that RPEs relay to and from other cells underly the progression of DR based on scRNA-seq. These signaling pathways and hub genes may provide new insights into DR mechanisms and therapeutic targets.

Allosteric modulation of the CXCR4:CXCL12 axis by targeting receptor nanoclustering via the TMV-TMVI domain

CXCR4 is a ubiquitously expressed chemokine receptor that regulates leukocyte trafficking and arrest in both homeostatic and pathological states. It also participates in organogenesis, HIV-1 infection, and tumor development. Despite the potential therapeutic benefit of CXCR4 antagonists, only one, plerixafor (AMD3100), which blocks the ligand-binding site, has reached the clinic. Recent advances in imaging and biophysical techniques have provided a richer understanding of the membrane organization and dynamics of this receptor. Activation of CXCR4 by CXCL12 reduces the number of CXCR4 monomers/dimers at the cell membrane and increases the formation of large nanoclusters, which are largely immobile and are required for correct cell orientation to chemoattractant gradients. Mechanistically, CXCR4 activation involves a structural motif defined by residues in TMV and TMVI. Using this structural motif as a template, we performed in silico molecular modeling followed by in vitro screening of a small compound library to identify negative allosteric modulators of CXCR4 that do not affect CXCL12 binding. We identified AGR1.137, a small molecule that abolishes CXCL12-mediated receptor nanoclustering and dynamics and blocks the ability of cells to sense CXCL12 gradients both in vitro and in vivo while preserving ligand binding and receptor internalization.

Allosteric modulation of the CXCR4:CXCL12 axis by targeting receptor nanoclustering via the TMV-TMVI domain

CXCR4 is a ubiquitously expressed chemokine receptor that regulates leukocyte trafficking and arrest in both homeostatic and pathological states. It also participates in organogenesis, HIV-1 infection, and tumor development. Despite the potential therapeutic benefit of CXCR4 antagonists, only one, plerixafor (AMD3100), which blocks the ligand-binding site, has reached the clinic. Recent advances in imaging and biophysical techniques have provided a richer understanding of the membrane organization and dynamics of this receptor. Activation of CXCR4 by CXCL12 reduces the number of CXCR4 monomers/dimers at the cell membrane and increases the formation of large nanoclusters, which are largely immobile and are required for correct cell orientation to chemoattractant gradients. Mechanistically, CXCR4 activation involves a structural motif defined by residues in TMV and TMVI. Using this structural motif as a template, we performed in silico molecular modeling followed by in vitro screening of a small compound library to identify negative allosteric modulators of CXCR4 that do not affect CXCL12 binding. We identified AGR1.137, a small molecule that abolishes CXCL12-mediated receptor nanoclustering and dynamics and blocks the ability of cells to sense CXCL12 gradients both in vitro and in vivo while preserving ligand binding and receptor internalization.

Differential expression of plasma cytokines in sepsis patients and their clinical implications.

Sepsis, which is characterized by acute systemic inflammation and is associated with high rates of morbidity and mortality, presents a significant challenge in health care. Some scholars have found that the sequential organ failure assessment (SOFA) and quick SOFA scores are not ideal for predicting severe sepsis and mortality. Microbial culture takes a long time (2-3 d) and provides no information for early diagnosis and treatment. Therefore, new diagnostic methods for sepsis need to be explored. To assess cytokine levels in the plasma of sepsis patients and identify potential biomarkers for diagnosing sepsis. Ten sepsis patients admitted to the emergency department within 24 h of onset were enrolled as the observation group, whereas ten noninfected patients served as the control group. Of the 10 noninfected patients, 9 hypertension combined with cerebral infarction, 1 patients with vertiginous syndrome. Plasma Cytokines were measured using the Bio-Plex Pro™ Human Chemokine Panel 40-plex. Differentially expressed cytokines in plasma of sepsis and nonsepsis patients were analyzed using Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Interleukin (IL)-16, granulocyte-macrophage granulocyte-macrophage colony-stimulating factor (GM-CSF), CX3CL1, CXCL9, CXCL16, CCL25, and CCL23 plasma levels were significantly increased in sepsis patients. GO analysis revealed that these cytokines were mainly associated with cellular structures such as intermediates, nuclear plaques, adhesion plaques, lateral plasma membranes, and cell matrix junctions. These genes were involved in various molecular functions, such as cytokine activity, receptor ligand activity, and signal receptor activator activity, contributing to various biological functions, such as leukocyte chemotaxis, migration, and chemotaxis. KEGG analysis indicated involvement in cytokine cytokine receptor interactions, chemokine signaling pathways, virus-protein interactions with cytokines and cytokine receptors, and the tumor necrosis factor signaling pathway. Elevated serum levels of IL-16, GM-CSF, CX3CL1, CXCL9, CXCL16, CCL25, and CCL23 in sepsis patients suggest their potential as diagnostic biomarkers for sepsis.

Computational Screening of T-Muurolol for an Alternative Antibacterial Solution against Staphylococcus aureus Infections: An In Silico Approach for Phytochemical-Based Drug Discovery.

Staphylococcus aureus infections present a significant threat to the global healthcare system. The increasing resistance to existing antibiotics and their limited efficacy underscores the urgent need to identify new antibacterial agents with low toxicity to effectively combat various S. aureus infections. Hence, in this study, we have screened T-muurolol for possible interactions with several S. aureus-specific bacterial proteins to establish its potential as an alternative antibacterial agent. Based on its binding affinity and interactions with amino acids, T-muurolol was identified as a potential inhibitor of S. aureus lipase, dihydrofolate reductase, penicillin-binding protein 2a, D-Ala:D-Ala ligase, and ribosome protection proteins tetracycline resistance determinant (RPP TetM), which indicates its potentiality against S. aureus and its multi-drug-resistant strains. Also, T-muurolol exhibited good antioxidant and anti-inflammatory activity by showing strong binding interactions with flavin adenine dinucleotide (FAD)-dependent nicotinamide adenine dinucleotide phosphate (NAD(P)H) oxidase, and cyclooxygenase-2. Consequently, molecular dynamics (MD) simulation and recalculating binding free energies elucidated its binding interaction stability with targeted proteins. Furthermore, quantum chemical structure analysis based on density functional theory (DFT) depicted a higher energy gap between the highest occupied molecular orbital and lowest unoccupied molecular orbital (EHOMO-LUMO) with a lower chemical potential index, and moderate electrophilicity suggests its chemical hardness and stability and less polarizability and reactivity. Additionally, pharmacological parameters based on ADMET, Lipinski's rules, and bioactivity score validated it as a promising drug candidate with high activity toward ion channel modulators, nuclear receptor ligands, and enzyme inhibitors. In conclusion, the current findings suggest T-muurolol as a promising alternative antibacterial agent that might be a potential phytochemical-based drug against S. aureus. This study also suggests further clinical research before human application.

Effectiveness of Second-Line Cabozantinib in Metastatic Clear Cell Renal Cell Carcinoma Patients After First-Line Treatment with Immune Checkpoint Inhibitor-based Combinations.

Cabozantinib, a tyrosine kinase inhibitor (TKI), is a prevalent second-line (2 L) therapy and was approved for use after progression on TKIs. However, the 1 L treatment setting has changed since the approval of cabozantinib monotherapy in salvage therapy settings. To assess the differential effectiveness of cabozantinib after prior progression on 1 L ipilimumab with nivolumab (IPI + NIVO) compared to programmed death receptor-1 (PD-1) or PD-1 ligand (PD-L1) inhibitors (PD1/L1i) with TKIs. Utilizing a nationwide electronic health record (EHR)-derived de-identified database, we included patients with metastatic clear cell renal cell carcinoma (mccRCC) who received 1 L treatment with an immune checkpoint inhibitor (ICI)-based combination and 2 L treatment with cabozantinib monotherapy. These patients were categorized based on the type of 1 L ICI-based combination received: IPI + NIVO vs. PD1/L1i with TKI. Real-world time to next therapy (rwTTNT) and real-world overall survival (rwOS) were summarized using Kaplan-Meier curves and compared using Cox-proportional hazard models adjusted for International mRCC Database Consortium (IMDC) risk groups. Among 12,285 patients with metastatic renal cell carcinoma, 237 were eligible and included. Median rwTTNT was 8 months for the IPI + NIVO subgroup and 7.5 months for the PD1/L1i + TKI subgroup (HR 1.05, 95% CI: 0.74-1.49, p = 0.8). Median rwOS was 17 months for IPI + NIVO and 16 months for PD1/L1i + TKI subgroup (HR 0.79, 95% CI: 0.52-1.20, p = 0.3). Cabozantinib remains effective as a 2 L therapy for mccRCC independent of the type of prior 1 L ICI-based combination. Further research is needed to validate these findings and explore the ideal sequencing of therapies.