Current Medicinal Chemistry - Online First

Neurodevelopmental disorders (NDDs) represent a diverse and heterogeneous group of conditions, including global developmental delay (GDD), autism spectrum disorder (ASD), and neurodevelopmental encephalopathy with epilepsy (NDEE). While these disorders often share phenotypic similarities, their underlying genetic causes can vary widely, making clinical diagnosis challenging.

In this study, we performed whole-genome sequencing (WGS) on a family having an autosomal recessive neurodevelopmental disorder. The proband (II-2) underwent WGS, followed by variant filtering through an in-house bioinformatics pipeline. Sanger sequencing and 3D protein modeling were performed to confirm the pathogenicity of the identified variant.

A novel biallelic missense variant in the NAV3 (c.3430T>C; p.Ser1144Pro) was detected using WGS and Sanger sequencing. Subsequently, 3D protein modeling revealed significant alterations in the secondary structure of NAV3, indicating a potential pathogenic effect.

The identification of a novel biallelic missense variant in NAV3 adds a new layer to our understanding of its potential contribution to autosomal recessive neurodevelopmental disorders. This case expands the mutational landscape of NAV3 and underscores its emerging significance in neurodevelopment.

This study reports a novel NAV3 variant in association with autosomal recessive NDD, contributing to the growing body of evidence supporting the involvement of NAV3 in human neurodevelopment. Functional validation and identification of additional patients will be essential to establish definitive genotype-phenotype correlations and uncover the mechanistic pathways underlying NAV3-associated disorders.

Scar heterogeneity, encompassing normal scar (NS) and pathological scars [hypertrophic scar (HS) and keloids], emerges from the dynamic interplay between systemic immune responses and local tissue microenvironment, highlighting the urgent need for drugs targeting different types of scars through both dimensions.

Data from DECODE and EQTLGen databases were used as exposure variables at the protein and mRNA levels in the blood, and data from GTEx and ScQTLbase as exposure variables at the tissue and single-cell levels. Two sample Mendelian Randomization (MR) studies were conducted at the systemic, local, and single-cell levels. The outcome variables were based on the NS, HS, and keloid cohorts in the authoritative FinnGen database. The results were ascertained using seven MR methods, including inverse-variance weighting (IVW), Wald ratio, weighted median, weighted mode, simple median, MR-Egger, and Summary-data-based Mendelian Randomization (SMR). Single-cell RNA-seq data were leveraged to validate the expression profiles and functions of the drug targets.

NUDT2, ATXN3, OGN, UROS, and TSG101 were significantly associated with keloids, while PARK7 and MZT2A showed a significant correlation with HSs, and CDCP1 was significantly linked to NSs. Among them, RNA and protein expression levels of NUDT2 and PARK7 demonstrated significant positive associations with keloids and HSs, respectively, at the blood, skin, and single-cell levels. Functional analysis revealed that the higher expression of NUDT2 was associated with angiogenesis and the cellular response to hormone stimuli, whereas PARK7 was involved in the organization of collagen fibrils and the extracellular matrix structure. Moreover, single-cell sequencing confirmed the high expression of NUDT2 and PARK7 in keloids and HSs. These findings highlight their potential roles in both systemic and local scar pathogenesis and underscore their promise as therapeutic targets.

This study identifies scar subtype-specific targets, particularly NUDT2 and PARK7, expanding therapeutic candidates for scar management. Multi-ethnic cohort studies are warranted to validate target universality.

Collectively, we have identified eight drug targets, with NUDT2 and PARK7 in particular showing potential therapeutic value for keloids and HSs. Additionally, our results suggest the feasibility of both local and systemic drug administrations.

Atherosclerosis (AS) is prevalent among the elderly population and poses a significant global health burden. However, the precise underlying mechanisms linking aging and mitochondrial dysfunction in AS remain unclear.

Through comprehensive utilization of databases including the Gene Expression Omnibus (GEO), MitoCarta, Molecular Signatures Database (MSigDB), and Human Aging Genomic Resources (HAGR), we employed various bioinformatics methods to explore the possible function of EF-hand domain family member D1 (EFHD1). This included the functional enrichment analysis, immune cell infiltration, and the lncRNA-miRNA-EFHD1 network. The validity of EFHD1 was confirmed using additional datasets and through Receiver Operating Characteristic (ROC) curve evaluation. Lastly, in vitro experiments were conducted using THP-1 cells treated with oxidized low-density lipoprotein (ox-LDL) to validate the expression and function of EFHD1 through Western blot and real-time quantitative PCR analyses. Additionally, in vivo experiments were performed on ApoE^-/- mice exhibiting atherosclerotic phenotypes, utilizing immunofluorescence staining.

Totally seven genes associated with aging and mitochondrial function (ALDH3A2, UCP1, BCL2, EFHD1, AHCYL1, HTRA2, and ALDH9A1) were discovered in AS, with EFHD1 identified as the principal hub gene. Immune infiltration analysis indicated that EFHD1 was negatively associated with myeloid suppressor cells (MDSC), activated B cells, and natural killer cells. An evident decline in EFHD1 was noted in unstable or advanced plaques compared to stable or early plaques, accompanied by significant area under the ROC curve (AUC) values of 0.917 (GSE100927) and 0.933 (GSE41571). Moreover, we recorded a reduction in EFHD1 expression in AS tissues and macrophages treated with ox-LDL. Following the silencing of EFHD1, TNF-α and IL-1β decreased, while ALODA, PKM2, MMP-9, JAK2, and STAT3 levels were upregulated. Furthermore, levels of ATP and reactive oxygen species (ROS) were diminished, while calcium ions and mitochondria levels remained unchanged.

To date, the common pathogenic genes associated with aging and mitochondrial dysfunction in atherosclerotic disease have been scarcely investigated. Using bioinformatics approaches, we identified seven hub genes (ALDH3A2, UCP1, BCL2, EFHD1, AHCYL1, HTRA2, and ALDH9A1) related to mitochondrial function and aging. Among these, EFHD1 was determined as the final hub gene. As a calcium sensor, EFHD1 plays a pivotal role in regulating mitochondrial metabolism and has been implicated in the prognosis of various tumors. Our findings demonstrated that EFHD1 knockdown decreased the levels of pro-inflammatory cytokines, such as IL-1β and TNF-α, increased JAK2 and STAT3 protein levels, and elevated MMP-9 levels, all of which may contribute to the vulnerability and progression of atherosclerotic plaques.

Our research revealed a reduction in EFHD1 expression within atherosclerotic tissues, suggesting its potential role in inflammation and mitochondrial energy metabolism as a key regulator of the calcium signaling pathway. This discovery offers possible advancements in the early diagnosis and treatment strategies for AS.

The objective of this study is to obtain inhibitors against mTOR targets with virtual screening, dynamic simulation and bioactivity assessment. This pursuit aims to obtain a rapid and accurate method for the discovery of new mTOR inhibitors.

Firstly, the researchers obtained nearly 9000 compounds by using ROC-guided machine learning from a library of over 200000 compounds. Secondly, virtual screening was used to evaluate the affinity of 45 compounds. Further analysis was performed to identify 6 hit compounds. Simultaneously, MTT antitumor activity evaluation and kinase inhibition assays are conducted for the active compounds to discern the most promising candidates. Furthermore, AO staining and JC-1 assays are performed for the selected compounds. Simultaneously, MTT antitumor activity evaluation and kinase inhibition assays are conducted for the active compounds to discern the most promising candidates. Furthermore, AO staining, JC-1 and hemolytic toxicity evaluation assays are performed for the selected compounds.

The kinase assay demonstrates that these 6 compounds display greater sensitivity to mTOR than to PI3K. Among them, compounds AJ-292/12941271 and AG-205/12550019 show better activity against mTOR target than PI3K, with an IC50 of 2.55 and 4.48 μM, respectively. Additionally, the anti-proliferative activity of the six hit compounds was also considered. Compound AJ-292/12941271 shows the best anticancer activity against A549 cell lines with an IC50 value of 4.3 μM. Further analysis reveals that compound AJ-292/12941271 induces apoptosis in the A549 cell line in a concentration-dependent or time-dependent manner. Hemolytic toxicity evaluation suggests that the compound AJ-292/12941271 is safe for further in vivo study.

This research proposes that the fused method of ROC-based machine learning, virtual screening, and bioactivity evaluation could be used to discover novel mTOR inhibitors quickly and precisely.

Regulatory T cells (Tregs) play an important role in the tumor microenvironment (TME). Currently, there have been no studies of Treg-related genes (TRGs) in lung adenocarcinoma (LUAD).

We integrated the Cancer Genome Atlas (TCGA) dataset with the Gene Expression Omnibus (GEO) dataset and divided the TCGA-GEO dataset patient samples into different cohorts by unsupervised clustering analysis based on the expression of TRGs in LUAD. By analyzing the TME characteristics of different cohorts, we assessed immune cell infiltration and function. In addition, we constructed Cox risk proportional regression models based on TRGs to predict patient prognosis.

The results of unsupervised cluster analysis classified the TCGA-GEO dataset as “immune desert”, “immune evasion” and “immune inflammation”. Moreover, there was a significant survival differential among the three cohorts (p-value < 0.05). Based on the expression of 61 TRGs in LUAD, we screened TFRC, CTLA4, IL1R2, NPTN NPTN and METTL7A to construct a Cox risk proportional regression model to divide the TCGA-GEO dataset into a training cohort and a test cohort. Survival was significantly worse in the high-risk group than in the low-risk group in both the training and test cohorts (p-value < 0.05). Finally, the nomogram scoring system constructed by integrating the model risk scores with clinical parameters can well predict the 1, 3 and 5 year survival of patients.

In conclusion, based on our analysis of the TRGs of LUAD patients, we can classify the patient TME into different immune statuses, which provides insights into adopting appropriate treatment regimens for different patients.

In 2022, the World Health Organisation (WHO) announced new cases of the developing Monkeypox Virus (MPXV), a zoonotic orthopoxvirus viral infection that mimics smallpox signs. Despite the ongoing infection, no proper medication is available to completely overcome this infection.

The study aims to construct a multi-epitope vaccine targeting Monkeypox Virus (MPXV) membrane glycoprotein to provoke robust immune responses.

To construct a potential immuno-dominant epitope vaccine to combat MPXV.

The target sequence, sourced from the UAE-to-India travel case, was analyzed to identify potential B-cell and T-cell epitopes (MHC-I and MHC-II). Immunodominant epitopes were selected and fused with β-defensin-I and PADRE to increase immunogenicity. The vaccine was modeled, docked with TLR3, and subjected to a 500 ns molecular dynamics simulation for stability analysis. Immune responses and bacterial expression were also evaluated.

The vaccine, comprising 230 amino acids, demonstrated antigenicity (0.6620), non-allergenicity, and broad population coverage. Selected epitopes included 3 B-cells, 4 MHC-I, and 2 MHC-II, ensuring a potent immunodominant profile. Docking with TLR3 revealed a binding affinity of -17.2 kcal/mol, while simulations confirmed their stability. Cloning (pET28a (+)) and immune response analyses showed a strong immunogenic profile, including elevated IgG1, IgM, and antigen levels, supported by a Codon Adaptation Index (CAI) of 1.0.

The proposed multi-epitope vaccine shows promise against MPXV. However, further in vivo and in vitro investigations are essential to confirm its immune efficacy.

Endoplasmic reticulum stress (ER stress) plays a crucial role in influencing the malignant behaviors of various tumors. Targeting the expression or degradation of transcription factors (TFs) offers a promising avenue for cancer treatment. However, a detailed understanding of how ER stress affects TF function and their interactions remains limited. This study aims to develop a prognostic model and identify TFs associated with ER stress in pancreatic ductal adenocarcinoma (PDAC).

We obtained gene expression profiles and corresponding clinical data from The Cancer Genome Atlas (TCGA). To develop a prognostic signature, we performed several analyses, including unsupervised clustering, enrichment analysis, immune infiltration assessment, as well as univariate, LASSO, and multivariate Cox regression analyses. Four transcription factors—STAT1, IRF6, NRF1, and RXRA—were incorporated into a risk model, which was subsequently validated using the GSE dataset. Additionally, we examined IRF6 through quantitative PCR, western blotting, flow cytometry, and immunohistochemistry in vitro using pancreatic cancer cell lines and a tissue microarray.

The high-risk group identified by the model exhibited significant associations with immune cell infiltration and poorer survival outcomes, though there was no significant correlation with tumor purity (p = 0.19). Furthermore, IRF6 downregulation in vitro was found to inhibit pancreatic cancer cell proliferation and promote apoptosis. IRF6 depletion also increased the expression of key molecules involved in ER stress at both the transcriptional and translational levels. Immunohistochemical analysis revealed marked differences in IRF6 expression between tumor and adjacent non-tumor tissues (59.29±29.88 vs. 95.22±40.80, p<0.001).

This study provides evidence that the constructed risk model can effectively predict prognosis in PDAC patients. Transcription factors related to ER stress, such as IRF6, show promise as both prognostic biomarkers and potential therapeutic targets for PDAC.

Ciprofol is a novel sedative-anesthetic that functions similarly to propofol. This study aimed to evaluate the efficacy and safety of ciprofol for the induction and maintenance of general anesthesia in patients undergoing thoracoscopic surgery.

A total of 120 patients undergoing thoracoscopic surgery for pulmonary nodules under general anesthesia were randomly assigned to the ciprofol group or the propofol group. Patients in the ciprofol group received an initial dose of 0.4 mg.kg^-1 of ciprofol for anesthesia induction, followed by an infusion rate ranging from 0.4 mg.kg^-1.h^-1 to 2.4 mg.kg^-1.h^-1 for maintenance. In the propofol group, patients were administered an initial dose of 2.0 mg.kg^-1 of propofol for induction, with a maintenance infusion rate ranging from 4.0 mg.kg^-1.h^-1 to 12 mg.kg^-1h^-1. The primary outcome measured was the success rate of sedation. Secondary outcomes included the time to successful induction of anesthesia, changes in hemodynamics and bispectral index (BIS) within 10 minutes after the initial administration of the study medication, time to respiratory recovery and full alertness, and the incidence of adverse events.

The sedation success rate was 100% in both groups. In this study, statistical analyses revealed no significant differences in the time to eyelash reflex disappearance (p=0.599), induction success time (p=0.431), the moment when the BIS value first fell below 60 (p=0.538), the time to respiratory recovery (p=0.505), or the interval until full wakefulness (p=0.837). Notably, within the first 10 minutes following the initial administration of the study medication, the reduction in blood pressure was significantly more pronounced in the propofol group (p<0.05). Additionally, the mean BIS value was significantly higher in the propofol group (p<0.01). The required dosage of sedative medication was significantly lower in the ciprofol group (p<0.001). Compared to the propofol group, the ciprofol group exhibited a significant reduction in the incidence of adverse events during intubation (p=0.01), a marked decrease in injection pain (p=0.001), and a significant decrease in the incidence of intraoperative hypotension (p<0.05).

Ciprofol exhibits comparable efficacy and safety profiles for both the induction and maintenance of general anesthesia in patients undergoing thoracoscopic surgery. Furthermore, it has been associated with a reduced dosage requirement, significantly lower mean BIS values, and a notable decrease in the incidence of injection pain and intraoperative hypotension.

(ChiCTR2400086976).

The pathogenesis of Delayed Encephalopathy After Acute Carbon Monoxide Poisoning (DEACMP) remains mysterious, and specific predictive markers are lacking. This study aimed to elucidate the molecular underpinnings and identify predictive biomarkers of DEACMP through multi-omics and single-nucleusRNA sequencing (snRNA-seq).

Clinical data and blood samples were collected from 105 participants. Untargeted metabolomics sequencing was employed to profile serum metabolites across these participants. Additionally, individuals from the Healthy Controls (HCs), Acute Carbon Monoxide Poisoning patients (ACOP), Non-Delayed Encephalopathy After ACOP (DEACMP-N), and DEACMP groups (n=3 each) were randomly selected for transcriptome sequencing to identify potential predictive targets and pivotal signaling pathways associated with DEACMP. Furthermore, Severe DEACMP and Control rat models were established. Three rats from the Control, DEACMP, and DEACMP + Dexamethasone + Selenomethionine groups were selected for snRNA-seq. Immunofluorescence multiplexing and qRT-PCR (quantitative Reverse Transcription Polymerase Chain Reaction) were then performed to validate the identified predictive targets.

Analysis of clinical data from 105 participants highlights the pivotal role of inflammation in influencing the prognosis of carbon monoxide poisoning. Metabolomics analysis identified 19 metabolites that significantly differed between the DEACMP-N and DEACMP groups. Transcriptomics analysis of 12 participants indicated that DEACMP is primarily associated with six signaling pathways, including lysosome and tuberculosis. Considering that microglia are central nervous system immune effectors, the snRNA-seq analysis revealed altered gene expression and signaling pathways in microglia during DEACMP, with KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis highlighting neutrophil extracellular trap formation, lysosome, and tuberculosis as the predominant pathways. Differential gene analysis from transcriptome and snRNA-seq identified 28 genes differentially expressed in DEACMP. The STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) database, immune multiplexing, and qRT-PCR confirmed the pivotal role of the Ifngr1/Stat1/Ctss axis in DEACMP.

This research identifies the Ifngr1/Stat1/Ctss axis as a key inflammatory mechanism in the pathogenesis of DEACMP, thereby clarifying previous uncertainties regarding the sequelae of carbon monoxide poisoning. The intersection of lysosomal and tuberculosis pathways, as revealed through metabolomic, transcriptomic, and single-nucleus RNA sequencing analyses—especially within microglia—offers novel mechanistic insights that could inform therapeutic interventions. While the integration of multiple omics methodologies enhances the robustness of these findings, their biological relevance to the pathogenesis of DEACMP requires rigorous validation through independent cohort verification approaches.

This study provides a comprehensive overview of serum metabolite expression, differential gene expression, and signaling pathways in DEACMP, offering a theoretical foundation for understanding the pathogenesis of DEACMP.