Future Pharmacol., Volume 5, Issue 4 (December 2025) – 7 articles

Introduction: Linezolid is a reserve antibiotic used to treat infections caused by Gram-positive bacteria with resistance genes. In critically ill patients, high intra- and interindividual variability has been observed, prompting the search for alternative methods to reduce this variability and achieve the pharmacokinetic/pharmacodynamic indices necessary for a favorable efficacy–safety balance. Aim of the study: We wished to compare the safety and effectiveness of a continuous infusion (CI) versus an intermittent infusion (II) of linezolid in patients requiring intensive care. Materials and Methods: This study, registered under the number NCT05801484), was a prospective, open-label, single-center, two-arm study. Data on hematologic safety and effectiveness were collected and compared between patients receiving CI and II, respectively, at the same daily dose of linezolid (1200 mg). Results: Twenty-nine patients from the intensive care unit were included, divided into two groups. No statistically significant difference was found in 30-day mortality between the groups, nor in the likelihood of post-treatment culture negativity. However, a significantly greater reduction in C-reactive protein levels was observed in the CI group compared to the II group. Regarding safety, at CrCl < 60 mL/min, the decrease in platelets was statistically significant in group II but not in group CI. Additionally, at the 30-day follow-up, recovery from thrombocytopenia was better in the CI group. Conclusions: Continuous infusion of linezolid proved to be non-inferior to intermittent infusion at the same daily dose in terms of effectiveness. Furthermore, a lower risk of adverse reactions was identified with continuous infusion. Full article

Reactive oxygen species (ROS) are formed by the incomplete reduction of oxygen and play a crucial role in both physiological function and pathological process, being controlled by enzymatic and non-enzymatic antioxidant systems. However, excessive ROS production can exceed the body’s antioxidant capacity, resulting in oxidative stress and causing cell death and oxidation of important biomolecules. In this context, the inhibition and/or modulation of ROS has been shown to be effective in reducing pain, oxidative stress, and inflammation. Among ROS, superoxide anion (O₂^•−) is the first free radical to be formed through the mitochondrial electron transport chain (ETC) or by specific enzymes systems, such as the nicotinamide adenine dinucleotide phosphate (NADPH) oxidase (NOX) complex. O₂^•− plays a significant role in the development and maintenance of pain associated with inflammatory conditions through direct or indirect activation of primary nociceptive neurons and, consequently, peripheral and central sensitization. Experimentally, potassium superoxide (KO₂, a O₂^●− donor) is used to initiate O₂^●− mediated inflammatory and nociceptive responses, making it important for studying the mechanisms associated with ROS-induced pain and evaluating potential therapeutic molecules. This review addresses the production and regulation of O₂^•−, highlighting its biosynthesis, redox control, and its physiological and pathological roles in the development of inflammatory pain, as well as the pharmacological therapies under development aimed at its generation and/or action. Full article

Cerebral vasospasm (CVS) following a subarachnoid hemorrhage (SAH) is a critical complication driven by imbalances between vasodilators and vasoconstrictors. This review explores the bidirectional interplay between nitric oxide (NO) and endothelin-1 (ET-1) in CVS pathogenesis. NO, a potent vasodilator mainly produced by endothelial and neuronal nitric oxide synthase (eNOS/nNOS) under normal physiological conditions, is scavenged early after SAH by hemoglobin derivatives, leading to microcirculatory dysfunction, pericyte constriction, and impaired neurovascular coupling. Conversely, ET-1 exacerbates vasoconstriction by suppressing NO synthesis via ROS-dependent eNOS uncoupling and Rho-kinase activation. The NO/ET-1 axis further influences delayed cerebral ischemia (DCI) through mechanisms like 20-HETE-mediated cGMP suppression and oxidative stress. Emerging therapies—including NO donors, NOS gene therapy, and ET-1 receptor antagonists—aim to restore this balance. Understanding these pathways offers translational potential for mitigating CVS and improving outcomes post-SAH. Full article

Background/Objective: Predicting pharmacological response in cancer remains a key challenge in precision oncology due to intertumoral heterogeneity and the complexity of drug–gene interactions. While machine learning models using multi-omics data have shown promise in predicting pharmacological response, selecting the features with the highest predictive power critically affects model performance and biological interpretability. This study aims to compare computational and biologically informed gene selection strategies for predicting drug response in cancer cell lines and to propose a feature selection strategy that optimizes performance. Methods: Using gene expression and drug response data, we trained models on both data-driven and biologically informed gene sets based on the drug target pathways to predict IC₅₀ values for seven anticancer drugs. Several feature selection methods were tested on gene expression profiles of cancer cell lines, including Recursive Feature Elimination (RFE) with Support Vector Regression (SVR) against gene sets derived from drug-specific pathways in KEGG and CTD databases. The predictability was comparatively analyzed using both AUC and IC₅₀ values and further assessed on proteomics data. Results: RFE with SVR outperformed other computational methods, while pathway-based gene sets showed lower performance compared to data-driven methods. The integration of computational and biologically informed gene sets consistently improved prediction accuracy across several anticancer drugs, while the predictive value of the corresponding proteomic features was significantly lower compared with the mRNA profiles. Conclusions: Integrating biological knowledge into feature selection enhances both the accuracy and interpretability of drug response prediction models. Integrative approaches offer a more robust and generalizable framework with potential applications in biomarker discovery, drug repurposing, and personalized treatment strategies. Full article

Background/Objectives: Colorectal carcinoma (CRC) is among the most commonly diagnosed cancers in both men and women. Although CRC mortality is generally decreasing, new therapeutic options are needed for unresponsive subgroups of CRC patients. Methods: A series of known and new tyrphostin derivatives was tested for their efficacy against three CRC cell lines with varying KRAS, p53, and/or BRAF statuses. Growth inhibition, apoptosis induction, and inhibition of EGFR and VEGFR-2 were investigated. Results: Tyrphostin A9, the known RG13022-related tyrphostin 1a and its dichlorido(p-cymene)ruthenium(II) complex 1b, and the new SF₅-substituted compounds 2a and 2b showed selective antiproliferative activity against KRAS-mutant HCT-116 CRC cells expressing wildtype p53, while p53-knockout HCT-116 and KRAS-wildtype BRAF/p53-mutant HT-29 CRC cells were distinctly less sensitive. In HCT-116 cells, only tyrphostin A9 increased mRNA expression of caspases 3 and 8, as well as the kinases MEK1 and MEK2, whereas 2a reduced caspase 8 mRNA levels. Tyrphostin A9 increased caspase 3 activity and induced apoptosis in HCT-116 p53-wildtype cells while simultaneously inhibiting the receptor tyrosine kinases EGFR and VEGFR-2 at low nanomolar concentrations. Conclusions: Tyrphostin A9 could be a promising therapeutic option for the treatment of KRAS-mutant CRC that expresses wildtype p53. Full article

Introduction: Tumor necrosis factor-α (TNF-α) is a key regulator of inflammatory responses, and its biological activity is dependent on proteolytic processing by the tumor necrosis factor-α-converting enzyme (TACE), also known as ADAM17. Aberrant TACE activity has been associated with various inflammatory and immune-mediated diseases, positioning it as a compelling target for therapeutic intervention. Methods: While our previous study explored TACE inhibition via repositioned FDA-approved drugs, the present study aims to examine previously untested chemical scaffolds from the Enamine compound library, seeking first-in-class TACE inhibitors. We employed an integrated in silico workflow that combined ligand-based virtual screening using a graph convolutional network (GCN) model trained on known TACE inhibitors with structure-based methodologies, including molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations. Results: Several enamine-derived compounds demonstrated strong predicted inhibitory potential, favorable docking scores, and stable interactions with the TACE active site. Among them, Z1459964184, Z2242870510, and Z1450394746 emerged as lead candidates based on their highly stable 300 ns RMSD and robust hydrogen bonding profile as compared to the reference compound BMS-561392. Conclusions: This study highlights the utilization of deep learning-driven screening combined with extended 300 ns molecular simulations to identify novel small-molecule scaffolds for TACE inhibition and supports further exploration of these hits as potential anti-inflammatory therapeutics. Full article