Current Medicinal Chemistry - Volume 32, Issue 38, 2025

The Instituto Nacional de Neurología y Neurocirugía Manuel Velasco Suárez (INNNMVS), established nearly six decades ago, was initially designed as a specialized hospital for neurological care. However, over time, it has evolved into a multifaceted health institute, encompassing three fundamental pillars: clinical care, scientific research, and academic education in neurology.

The purpose of this study is to strengthen and expand knowledge in the field of neurology. Within the context of INNNMVS, sixtieth anniversary, our goal is to examine bibliometric data from this tertiary healthcare institution, providing evidence of productivity and progress in the research field within the institute and demonstrating scientific trends and their correlation with prevalent neurological diseases in Mexico, to enhance international recognition of this institution.

The research data from the Scopus database were obtained from the INNNMVS starting from its establishment in 1964 until 2023. We systematically classified each article and conducted a comprehensive analysis of various variables, including topic, type, citations, journal of publication, year of publication, language, collaboration, and other relevant factors. The INNNMVS has published a total of 3,915 articles between the years 1964 and 2023, with publication commencing in 1968. Since 2005, the INNNMVS has consistently published over 100 articles annually.

The predominant causes of illness and death in Mexico, which have received significant research attention at the INNNMVS, include strokes, tumors, psychiatric disorders, infectious diseases, epilepsy, Parkinson's disease, and autoimmune diseases. Simultaneously, these are the most frequently cited data. The scientific output of the INNNMVS has experienced substantial growth over the past few decades.

The most successful articles possess attributes that are absent in the majority of articles published by the INNNMVS. We extend an invitation to this institution to engage in collaborative partnerships with international affiliations and to contribute scholarly articles to esteemed international journals.

This study seeks to develop a prognostic risk signature for head and neck squamous cell carcinoma (HNSCC) based on cholesterol-related genes (CholRG), aiming to enhance prognostic accuracy in clinical practice.

HNSCC poses significant challenges due to its aggressive behavior and limited response to standard treatments, resulting in elevated morbidity and mortality rates. In order to improve prognostic prediction in HNSCC, our study is inspired by the realization that cholesterol metabolism plays a critical role in accelerating the progression of cancer. To this end, we are developing a unique risk signature using CholRG.

The aim of this study was to create a CholRG-based risk signature to predict HNSCC prognosis, aiding in clinical decision-making accurately.

The TCGA HNSCC dataset, along with GSE41613 and GSE65858, was obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases, respectively. A CholRG-based risk signature was then developed and validated across various independent HNSCC cohorts. Moreover, a nomogram model incorporating CholRG-based risk signature was established. Additionally, functional enrichment analysis was conducted, and the immune landscapes of the high- and low-risk groups were compared. Finally, in vitro experiments were performed using lipid-based transfection to deliver siRNAs targeting ACAT1 to SCC1 and SCC23 cell lines, further examining the effects of ACAT1 knockdown on these cells.

Utilizing RNA-seq, microarray, and clinical data from public databases, we constructed and validated a CholRG-based risk signature that includes key genes such as ACAT1, CYP19A1, CYP27A1, FAXDC2, INSIG2, PRKAA2, and SEC14L2, which can effectively predict the clinical outcome of HNSCC. Additionally, our findings were reinforced by a nomogram model that integrates the risk score with clinical variables for more clinically practical prognostic assessment. In addition, patients at high risk show hypoxia and increased oncogenic pathways such as mTORC1 signaling, as well as a suppressed immune microenvironment marked by a reduction in the infiltration of important immune cells. Notably, in vitro experiments showed that ACAT1 depletion significantly suppressed the proliferation, colony formation, and invasion capabilities of HNSCC cells, confirming ACAT1's role in promoting malignancy.

Collectively, our study not only underscores the importance of cholesterol metabolism in HNSCC pathogenesis but also highlights the CholRG-based risk signature as a promising tool for enhancing prognostic accuracy and personalizing therapeutic strategies.

Cartilage oligomeric matrix protein (COMP) is a protein that has been implicated in the development of some tumors, but its exact role in gastric cancer (GC) remains unclear.

The study aims to comprehensively examine COMP in GC and to confirm its effects through experimental methods.

The research harnessed data from the Cancer Genome Atlas (TCGA) to explore the significance of COMP in GC and its potential as a diagnostic tool. The study also examined the regulatory networks involving COMP, including its interactions with immune cells, immune checkpoint genes, tumor mutational burden (TMB), microsatellite instability (MSI), and the stemness index based on mRNA expression (mRNAsi). Additionally, the study explored the relationship between COMP expression and drug sensitivity in GC. Genomic variations of COMP in GC were assessed. The expression of COMP was validated by the GEPIA2 tool and confirmed with quantitative reverse transcription PCR (qRT-PCR) in cell lines (normal human gastric epithelial cells GES-1 and GC cell lines AGS and HGC-27).

Abnormal expression patterns of COMP were observed in various cancers, including GC. Higher levels of COMP in GC were significantly associated with the pathologic T stage and a history of reflux (p < 0.05 for both). Elevated COMP expression was correlated with poorer progression-free survival (PFS) (p = 0.027). COMP expression levels were identified as an independent prognostic factor for GC (p = 0.017). COMP was linked to TCF-dependent signaling in response to ECM receptor interaction, focal adhesion, and other pathways. There was an association between COMP expression and immune infiltration, immune checkpoint genes, TMB/MSI, and mRNAsi in GC. COMP expression was inversely correlated with the sensitivity to several drugs, indicating that higher levels of COMP may reduce the effectiveness of these drugs. COMP was found to be significantly up-regulated in GC cell lines.

COMP could serve as a prognostic biomarker and a potential therapeutic target for the treatment of GC.

Melanogenesis, the process responsible for melanin production, is a critical determinant of skin pigmentation. Dysregulation of this process can lead to hyperpigmentation disorders.

In this study, we identified a novel Reed Rhizome extract, (1'S, 2'S)-syringyl glycerol 3'-O-β-D-glucopyranoside (compound 5), and evaluated its anti-melanogenic potential in zebrafish models and in vitro assays. Compound 5 inhibited melanin synthesis by 36.66% ± 14.00% and tyrosinase in vivo by 48.26% ± 6.94%, surpassing the inhibitory effects of arbutin. Network pharmacological analysis revealed key targets, including HSP90AA1, HRAS, and PIK3R1, potentially involved in the anti-melanogenic effects of compound 5.

Molecular docking studies supported the interactions between compound 5 and these targets. Further, gene expression analysis in zebrafish indicated that compound 5 up-regulates hsp90aa1.1, hrasa, and pik3r1, and subsequently down-regulating mitfa, tyr, and tyrp1, critical genes in melanogenesis.

These findings suggest that compound 5 inhibits melanin production via PI3K-Akt and Ras-Raf-MEK-ERK signaling pathways, positioning it as a promising candidate for the treatment of hyperpigmentation.

This study aimed to screen the potential phytochemicals derived from Asparagus racemosus (Shatavari) against Thymidylate Kinase (TMPK) and D9 decapping enzyme, which is the vital target of the monkeypox virus and helps in the host- pathogen interaction mechanism, using integrated docking, QSAR analysis, and a molecular dynamics approach.

The Monkeypox Virus (MPXV) is a recently emerging outbreak with ongoing infection cases. Drugs and vaccines for smallpox are being used to reduce the infection. However, no specific drugs or vaccines are available to combat this infection.

The TMPK and D9 decapping enzymes were retrieved from the MPXV virus UK strain in FASTA format. Due to the unavailability of an experimentally determined structure, the 3D structure was modelled via SWISS-MODEL and further enhanced and validated. The structure was subjected to docking analysis with the derived phytochemicals from Asparagus racemosus using a maestro module. The potential inhibitors were examined via QSAR analysis. Additionally, through MD simulation 250 ns, the stability was analyzed, and the MM-GBSA was employed to calculate the binding affinities.

The molecular investigation revealed asparoside-C (PubChem ID: 158598) and asparoside-D (PubChem ID: 158597) to be potential hits among others for both targets (TMPK and D9 decapping enzyme) compared to the reference drugs, i.e., tecovirimat, brincidofovir, and cidofovir, possessing antiviral and required bioactivity analyzed via the ADME and QSAR analyses. Moreover, the simulation study of over 250 ns revealed strong stability, followed by RMSD, RMSF, etc. The free energy calculation via MM-GBSA exhibited strong affinities of asparoside-C and asparoside-D towards the TMPK and the D9 decapping enzyme according to their respective scores.

The docking, QSAR, and simulation investigation revealed dual-target inhibitors activity of phytochemicals from Asparagus racemosus towards the MPXV via targeting TMPK and D9 decapping enzyme. It has been observed that asparoside-D and asparoside-C can potentially combat MPXV.

Tobacco smoke is an important inducer of airway epithelial cell aging. Punicalagin(PCG) is a natural anti-aging compound. The effect of PCG on tobacco smoke-induced airway epithelial cell senescence is unknown.

Our study investigated whether PCG can treat the human bronchial epithelial cell line (BEAS-2B) aging by inhibiting the protease-activated receptor 2 (PAR2)/mTOR pathway.

Bioinformatics techniques were used to analyze the potential biological functions of PAR2. Molecular dynamics evaluated the binding ability of PCG and PAR2. The CCK8 assay was used to detect the cytotoxicity of CSE and PCG. The activity of the PAR2/mTOR pathway and the expression of the characteristic aging markers p16, p21, and SIRT1 are detected by qRT-PCR and Western blotting. Cell senescence was observed by Senescence-associated β-galactosidase (SA-β-gal) staining. The senescence-associated secretory phenotype (SASP): concentrations of interleukin IL-6, IL-8, and TNF-α were detected by ELISA.

The GSE57148 bioinformatics analysis dataset showed that PAR2 regulates lung senescence through the mTOR signaling pathway. Molecular dynamics results found that PCG and PAR2 had a strong and stable binding force. CSE induces BEAS-2B cell senescence and activates the PAR2/mTOR pathway. Inhibition of PAR2 mitigated the senescence changes. In addition, PCG's pretreatment can significantly alleviate CSE-induced BEAS-2B cell senescence while inhibiting the PAR2/mTOR pathway.

PCG has a therapeutic effect on the senescence of airway epithelial cells.

We aimed to explore diagnostic biomarkers of postmenopausal osteoporosis (PMOP).

PMOP brings enormous physical and economic burden to elderly women.

This study aims to screen new biomarkers for osteoporosis, providing insights for early diagnosis and therapeutic targets of osteoporosis.

Weighted gene co-expression network analysis (WGCNA) was applied to identify osteoporosis-related hub genes. Single-cell transcriptomic atlas of osteoporosis was depicted and the heterogeneity of monocytes was analyzed, based on which the biomarkers for osteoporosis were screened. Gene set enrichment analysis (GSEA) was conducted on the biomarkers. The diagnostic model (nomogram) was established and evaluated based on the expression levels of biomarkers. Additionally, the transcription factor (TF) regulatory network was constructed to predict the potential TF and targeted miRNA of biomarkers. The drugs with significant correlation with biomarkers were identified by Spearman correlation analysis.

We obtained 30 osteoporosis-associated hub genes. 9 cell types were identified, and the monocytes were subdivided to 4 subtypes. Three biomarkers, DHX29, LSM5, and UBE2V2, were screened. DHX29 and UBE2V2 were highly expressed in non-classical monocytes, while LSM5 exhibited the highest expression in other monocytes, followed by non-classical monocytes. GSEA indicated that osteoporosis may be correlated with vascular calcification and the biomarkers may be involved in the formation of immune cells. Then, nomogram was constructed and exhibited good robustness. In addition, MYC and SETDB1 were the shared IF in three biomarkers, which may play critical regulatory roles in the progression of osteoporosis. Moreover, 41, 49, and 68 drugs appeared significant correlations with DHX29, LSM5, and UBE2V2, respectively.

This study provided a basis for early diagnosis and targeted treatment of osteoporosis.

Polycystic Ovary Syndrome (PCOS) is a common endocrine disorder that negatively affects female reproductive capacity. Although the association between autophagy and PCOS is known, there are few detailed studies on the association between autophagy-related genes and PCOS.

Publicly available gene expression datasets (GSE102293, GSE138518, GSE34526, GSE114419, GSE137684, GSE155489) were used in a comprehensive analysis to identify a role for autophagy in PCOS. Batch effects were mitigated using the sva package, followed by WGCNA (weighted gene correlation network analysis) and ssGSEA (single sample gene set enrichment analysis) to identify autophagy-related genes. Recursive feature elimination (RFE) and LASSO COX methods were used to identify important hub genes, and their correlation with immune cell activity was assessed using ssGSEA and Pearson correlation analysis.

High autophagy scores were observed in PCOS samples, and the dark green gene module with the highest autophagy correlation was identified. The differential analysis identified a total of 169 up-regulated genes versus 2 down-regulated genes in the PCOS samples, which were intersected by taking the intersection with the deep green module genes and resulted in 121 key genes. Subsequently, 6 hub genes (MMP25, CSF3R, SLPI, MMP9, CLEC4E, and SIGLEC10) were further identified based on RFE and LASSO algorithms. Diagnostic efficacy based on ROC curves showed six autophagy-associated hub genes with AUC values as high as 0.959 and 0.896 in the training and validation sets, respectively. Finally, we observed that these hub genes are strongly associated with immune function, especially chronic inflammation and aberrant immune activation pathways.

In this study, we identified autophagy genes closely related to PCOS and constructed a gene model with high diagnostic accuracy. These findings not only provided potential new biomarkers for the diagnosis of PCOS but also revealed the key role of autophagy in the pathogenesis of PCOS.