Current Medicinal Chemistry - Online First

One of the most effective osteoanabolic drugs for treating osteoporosis is romosozumab, which was developed as a consequence of growing knowledge of the Wnt signaling system. This review explored how romosozumab affects the bone mineral density (BMD) in osteoporotic patients.

Up until January 2024, PubMed, Web of Science, and Scopus were reviewed for any randomized controlled trials (RCTs) evaluating the impact of osteoporotic treatment with romosozumab on BMD changes and bone metabolism markers in primary osteoporosis patients. Pooled Hedges’ g indices, which were consistently used across all included studies to measure standardized mean differences, were computed along with their corresponding 95% confidence intervals using either a random-effects or fixed-effects model.

Out of the 1855 papers, 24 RCTs met the inclusion criteria. Patients with osteoporosis who received romosozumab for a period of time demonstrated an augmentation in their lumbar spine BMD. The study findings indicated that the total hip and femoral neck BMD demonstrated significant enhancement in 22 (out of 23) and 19 (out of 21) studies, respectively.

In patients with osteoporosis, romosozumab could markedly increase the total hip, lumbar spine, and femoral neck BMD. This finding could be verified by measuring bone turnover indicators such as PINP, TRACP-5b, and CTX.

Low back pain (LBP) and sciatica are among the most prevalent musculoskeletal disorders, leading to significant disability and an economic burden. Neurotrophic factors, including nerve growth factor (NGF), brain-derived neurotrophic factor (BDNF), and glial cell-derived neurotrophic factor (GDNF), play critical roles in pain modulation and neuronal function. While NGF-targeting monoclonal antibodies have shown potential in treating chronic pain, their efficacy and safety remain under debate. This study employs Mendelian Randomization (MR) to assess the causal relationships between NGF, BDNF, GDNF, and the risk of LBP and sciatica.

We conducted a two-sample MR analysis using genetic instruments for NGF, BDNF, and GDNF. LBP and sciatica data were obtained from FinnGen. The inverse variance weighted (IVW) method was applied as the primary causal estimation, with the weighted median (WM) and MR-Egger regression used for sensitivity analyses. Reverse MR was performed to evaluate bidirectional causality. Furthermore, we used expression quantitative trait loci (eQTLs) within 50 kb of each gene locus as genetic instruments for NGF regulation, ensuring that the genetic variants used directly influence neurotrophic factor expression.

MR analysis revealed a significant causal association between NGF and an increased risk of LBP (OR = 1.121, 95% CI 1.021-1.230, p = 0.016) and sciatica (OR = 1.158, 95% CI 1.034-1.296, p = 0.010), while BDNF and GDNF showed no significant associations with pain outcomes. Sensitivity analyses confirmed the robustness of the NGF findings, with no evidence of horizontal pleiotropy or heterogeneity. Reverse MR analysis showed no significant causal effect of LBP or sciatica on NGF levels (p > 0.05), ruling out reverse causality. Additionally, we investigated the NGF-eQTL, which captures genetically regulated NGF expression, and found a significant association between the NGF-eQTL and LBP (OR = 1.040, 95% CI 1.010-1.070, p = 0.007). Unlike external NGF measurements, the NGF-eQTL minimizes environmental confounding and reverse causation, providing stronger genetic evidence supporting NGF as a therapeutic target for LBP.

Our findings provide strong genetic evidence that nerve growth factor (NGF) plays a causal role in the development of low back pain and sciatica, supporting NGF inhibition as a promising therapeutic strategy. These results align with clinical observations where anti-NGF monoclonal antibodies demonstrated pain-relieving effects, though safety concerns remain. In contrast, no causal associations were observed for BDNF or GDNF, underscoring the specificity of NGF in peripheral pain sensitization. The study demonstrates the value of Mendelian Randomization in minimizing confounding and reverse causation, thereby strengthening causal inference. Future work should focus on pharmacogenomic predictors to identify patients most likely to benefit from NGF-targeted interventions while minimizing adverse effects.

This study provides genetic evidence that NGF plays a causal role in LBP and sciatica, reinforcing its potential as a therapeutic target. However, BDNF and GDNF were not significantly associated with pain outcomes, suggesting distinct mechanisms of pain modulation. While clinical trials of anti-NGF monoclonal antibodies have demonstrated efficacy in pain reduction, concerns about adverse effects, such as joint degeneration, habe limited their widespread clinical use. Future research should explore genetic predictors of anti-NGF therapy response to optimize treatment strategies for LBP and related musculoskeletal pain disorders.

Many medications associated with an increased risk of dementia do not have adequate warning labels, leading to a significant underestimation of their potential dangers. This study aims to leverage the FAERS database to identify drugs strongly linked to dementia and to examine the relationship between these drugs using Mendelian randomization techniques. The ultimate goal is to mitigate the risk of developing dementia.

We utilized the FAERS database to identify medications significantly associated with dementia cases. The DrugBank, OpenTargets, and STITCH databases were employed to pinpoint the target genes of these drugs. We then conducted Mendelian randomization analysis to explore the correlation between the expression of drug target genes and the incidence of dementia. Additionally, a time-to-onset analysis assessed the temporal relationships of drug ingestions. Furthermore, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein-Protein Interaction Network (PPI) analyses were performed to investigate the molecular pathways linked to target genes related to drugs associated with dementia.

A total of 28,139 dementia events were recorded in the FAERS database. Our Mendelian randomization analysis revealed a significant association between the expression of all identified drug target genes and dementia in both blood and brain tissues. Specifically, we identified nine drug target genes with significant correlations, implicating quetiapine, clozapine, valproic acid, alendronate, and digoxin as being strongly associated with dementia, which could provide insight into areas of clinical concern regarding dementia occurrence.

The adverse event data sourced from the FAERS database indicate that certain medications are associated with an increased risk of developing dementia, a finding corroborated by our Mendelian randomization analysis. Establishing a comprehensive monitoring and risk assessment program is crucial for identifying high-risk individuals and facilitating informed medication choices, thereby potentially reducing the incidence of dementia.

Tyrosinase, a copper-containing enzyme, is responsible for melanin production, and its overactivity can lead to hyperpigmentation.

This study aimed to evaluate triazolothiadiazoles (3a-h, 4a-f) and triazolothiadiazines (5a-h) against human and mushroom tyrosinase isozymes.

Several derivatives, such as 3a-3b, 3d, 4c-4f, 5d, and 5e, were identified as potent and selective inhibitors of mushroom tyrosinase, with IC50 values ranging from 1.9 to 15.2 µM. Similarly, compounds 3f, 4b, 5a, and 5b effectively inhibited human tyrosinase, with IC50 values between 12.6 and 18.5 µM. Mechanism-based studies revealed that these active compounds exhibited competitive inhibition against both isozymes without any cytotoxic effects. In-silico analysis further demonstrated that these compounds fit well into the active site of both tyrosinase isozymes.

Additionally, the pharmacokinetic profile of these compounds highlighted promising drug-like properties, making them potential candidates for the development of effective therapeutics for skin disorders.

Gastroesophageal reflux disease (GERD) is a prevalent digestive disorder, yet the causal roles of modifiable risk factors remain unclear. This study aims to investigate the causal relationships between 28 modifiable risk factors (including obesity traits, mental health disorders, sleep traits, metabolic comorbidities, and serum parameters) and GERD using two-sample Mendelian randomization (MR). Gastroesophageal reflux disease (GERD). Our findings aim to inform targeted prevention and treatment strategies for GERD.

This study obtained data from extensive genome-wide association studies (GWAS). Pooled data associated with gastroesophageal reflux associations were obtained from the 23andMe Research team’s research, which included a total of 129,080 cases of gastroesophageal reflux and 473,524 controls of European ancestry. We conducted a univariable Mendelian randomization (MR) analysis to ascertain whether genetic evidence of exposure demonstrated a statistically significant association with the risk of GERD. Subsequently, a multivariable MR analysis was carried out to estimate the independent effects of the exposures on GERD.

Univariable MR analysis utilizing extensive GWAS data suggested that genetic factors such as BMI, Waist circumference, Arm fat mass (left and right), Leg fat mass (left and right), Attention Deficit and Hyperactivity Disorder (ADHD), Major Depressive Disorder (MDD), Schizophrenia, Negative emotions (including nervousness, anxiety, tension, or depression), Insomnia, Sleep apnea syndrome, Sleep duration, and Snoring, as well as Total cholesterol levels and Apolipoprotein B levels, are associated with the development of GERD. Multivariate Mendelian randomization of BMI and Negative emotion as correction factors showed that Waist circumference, Arm fat mass (left and right), Leg fat mass (left and right), ADHD, Insomnia, Sleep apnea syndrome, and Snoring were associated with an increased risk of GERD (p< 0.05). Conversely, longer sleep duration was associated with a reduced risk of GERD (p< 0.05).

This MR study reveals novel causal mechanisms in GERD pathogenesis: (1) Peripheral adiposity (arm/leg fat mass) exerts independent effects beyond central obesity, indicating site-specific fat distribution significance; (2) ADHD emerges as a distinct psychiatric risk factor independent of mental disorders; (3) Sleep apnea operates through BMI-independent pathways. Collectively, these findings redefine GERD pathophysiology, highlighting fat depot specificity and brain-gut interactions as critical mechanistic drivers.

Overall, our findings suggest that multiple risk factors are associated with the risk of GERD. These results provide a theoretical basis for controlling body weight and plasticity, improving sleep habits, and preventing and timely seeking medical attention to reduce the occurrence of psychiatric disorders, which will be important strategies to prevent and alleviate GERD.

Seven new 4-[2-(dichloromethyl)pyrazolo[1,5-a][1,3,5]triazine derivatives were investigated for anticancer activity, possible molecular mechanisms of anticancer action, and ADMET properties.

The 4-benzenesulfonamide derivatives of pyrazolo[1,5-a][1,3,5]triazine were synthesized using the condensation of N-(2,2-dichloro-1-cyanovinyl)-amides IV with 1H-pyrazol-5-amine. Compound antitumor activities were evaluated using the NCI-60 human cancer cell line. AutoDockTools and AutoDock Vina software were used for molecular modeling. Using the ADMETlab 3.0 and pkCSM web sources, the ADMET properties of compounds 4, 5, and 7 were calculated.

Seven new pyrazolo[1,5-a][1,3,5]triazine derivatives were synthesized. The compounds 4, 5, and 7 exhibit high activity >1 µM against leukemia, colon, and renal cancer. Compound 4 exhibited the most potent activity, with IC50 values of 0.32  µM against leukemia, 0.49-0.89  µM against colon cancer, and 0.92  µM against renal cancer. Molecular modeling has demonstrated a potential antitumor mechanism involving CDK. The predicted ADMET profile of compounds 4, 5, and 7 is favorable.

The seven novel pyrazolo[1,5-a][1,3,5]triazines, as purine bioisosteres, were developed, synthesized, and investigated by in vitro and in silico methods.

Seven novel pyrazolo[1,5-a][1,3,5]triazine derivatives exhibited anticancer activity against the NCI-60 cancer cell lines. The compounds 4, 5, and 7 demonstrated strong anticancer activity, with growth inhibition (GI) values exceeding 50% across all nine cancer types tested. The most active compound, 4, is against leukemia, colon cancer, renal cancer, and lung cancer. All compounds exhibit low toxicity, with LC50 values of 100 µM or greater. The molecular docking of compounds 4, 5, and 7 revealed the potential to inhibit cancer-associated cyclin-dependent kinases. The predicted ADMET profiles of their compounds are favorable, providing a basis for further improvement of their anticancer activity.

Metabolic dysregulation, encompassing conditions such as type 2 diabetes mellitus, obesity, metabolic syndrome, and dyslipidemia, poses an increasing global health burden. The dysregulation of 11β-hydroxysteroid dehydrogenase 1 (11β-HSD1), a key enzyme in glucocorticoid metabolism, has been strongly implicated in the pathogenesis of these disorders by influencing glucose homeostasis, lipid metabolism, and insulin sensitivity. Consequently, targeting 11β-HSD1 offers a promising therapeutic strategy for mitigating metabolic dysregulation and its associated complications.

The study aimed to identify resveratrol derivatives with high binding affinity and inhibitory potential against 11β-HSD1, using computational approaches to evaluate their pharmacokinetic and toxicity profiles.

A library of resveratrol derivatives was screened using molecular docking to identify high-affinity compounds. The hit compounds were further evaluated for absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties, followed by molecular dynamics simulations to assess their stability.

The resveratrol cis-dehydrodimer emerged as the most promising candidate, demonstrating high binding affinity, favorable ADMET properties, and stability over a 200 ns simulation period. These findings suggest its potential as a small-molecule inhibitor of 11β-HSD1.

The resveratrol cis-dehydrodimer represents a viable candidate for further experimental validation as a therapeutic agent for metabolic disorders. Future studies should include synthetic validation and in vivo testing to confirm its efficacy.