Drugs and Drug Candidates

Background/Objectives: Malaria is a prominent vector-borne disease, with a high mortality rate, particularly in children under five years old. Despite the use of various insecticides for its control, the emergence of resistant mosquitoes poses a significant public health threat. Acetylcholinesterase (AChE) is a crucial enzyme in nerve transmission and a primary target for insecticide development due to its role in preventing repeated nerve impulses. Recent studies have identified difluoromethyl ketone (DFK) as a potent inhibitor of both sensitive and resistant Anopheles gambiae acetylcholinesterase (AgAChE). This study aimed to identify novel AgAChE inhibitors that could be explored for malaria prevention. Methods: We performed a virtual screening on the PubChem database using a pharmacophore model from difluoromethyl ketone-inhibited AgAChE’s crystal structure. The most promising compound was then subjected to molecular docking and dynamics studies with AgAChE to confirm initial findings. ADMET and agrochemical likeness (ag-like) properties were also analyzed to assess its potential as an agrochemical agent. Results: PubChem18463786 was identified as the most suitable compound from the virtual screening. Molecular docking and molecular dynamics studies confirmed its strong interaction with AgAChE. The ADMET and ag-like analyses indicated that PubChem18463786 possesses physicochemical properties suggesting a high probability of non-absorption in humans and meets the criteria for agrochemical similarity. Conclusions: Our findings suggest that PubChem18463786 is a potential AgAChE inhibitor candidate. After validation through in vitro and in vivo experiments, it could be exploited for malaria prevention and serve as a lead compound for the synthesis of new, more effective, and selective agrochemical agents. Full article

Substance use during pregnancy is an increasingly important yet under-recognized threat to maternal and child health. This narrative review synthesizes the current evidence available on the epidemiology, pathophysiology, clinical management, and policy landscape of prenatal exposure to alcohol, tobacco, opioids, benzodiazepines, cocaine, cannabis, methamphetamines, and other synthetic drugs. All major psychoactive substances readily cross the placenta and can remain detectable in breast milk, leading to a shared cascade of obstetric complications (hypertensive disorders, placental abruption, pre-term labor), fetal consequences (growth restriction, structural malformations), and neonatal morbidities such as neonatal abstinence syndrome and sudden infant death. Mechanistically, trans-placental diffusion, oxidative stress, inflammatory signaling, and placental vascular dysfunction converge to disrupt critical neuro- and cardiovascular developmental windows. Early identification hinges on the combined use of validated screening questionnaires (4 P’s Plus, CRAFFT, T-ACE, AUDIT-C, TWEAK) and matrix-specific biomarkers (PEth, EtG, FAEE, CDT), while effective treatment requires integrated obstetric, addiction, and mental health services. Medication for opioid use disorders, particularly buprenorphine, alone or with naloxone, confers superior neonatal outcomes compared to methadone and underscores the value of harm-reducing non-punitive care models. Public-health strategies, such as Mexico’s “first 1 000 days” framework, wrap-around clinics, and home-visiting programs, demonstrate the potential of multisectoral interventions, but are hampered by structural inequities and punitive legislation that deter care-seeking. Research gaps persist in polysubstance exposure, culturally tailored therapies, and long-term neurodevelopmental trajectories. Multigenerational, omics-enabled cohorts, and digital longitudinal-care platforms represent promising avenues for closing these gaps and informing truly preventive perinatal health policies. Full article

Background: Based on our previously reported series of novel 1,3,5-tris[(4-(substituted-aminomethyl)phenyl)methyl]benzene and 1,3,5-tris[(4-(substituted-aminomethyl)phenoxy)methyl]benzene derivatives, we have now designed, synthesized, and tested a new series of novel restricted and simplified structural analogues of these compounds against Plasmodium falciparum in vitro; i.e., the 1,3-bis[(4-(substituted-aminomethyl)phenyl)methyl]benzene and 1,3-bis[(4-(substituted-aminomethyl)phenoxy)methyl]benzene compounds. Methods & Results: The pharmacological results revealed significant antimalarial activity, with IC₅₀ values in the submicromolar to micromolar range. Additionally, the in vitro cytotoxicity of these new nitrogen-containing polyphenyl- or -phenoxymethylbenzene compounds was evaluated on human HepG2 cells. The compound 1f, the 1,3-bis[(4-(3-(morpholin-1-yl)propyl)aminomethyl)phenoxy)methyl]benzene derivative, emerged as one of the most potent and promising antimalarial candidates, demonstrating a cytotoxicity/antiprotozoal activity ratio of 594 against the chloroquine-sensitive Plasmodium falciparum 3D7 strain. Additionally, the 1,3-bis[((substituted aminomethyl)phenyl)methyl]benzene compound 1j and the 1,3-bis[((substituted aminomethyl)phenoxy)methyl]benzenes 2p and 2q also showed strong antimalarial potential, with selectivity indexes (SI) of over 303, 280, and 217, respectively, against the 3D7 strain, which has mefloquine-reduced sensitivity. Furthermore, the 1,3-bis[(4-(pyridin-2-ylethylaminomethyl)phenyl)methyl]benzene 2k was identified as the most noteworthy antimalarial compound, exhibiting a selectivity index (SI) that was superior to 178 against the chloroquine-resistant Plasmodium falciparum W2 strain. It has previously been suggested that the telomeres of P. falciparum may serve as potential targets for these polyaromatic compounds; thus, we assessed the ability of our novel derivatives to stabilize parasitic telomeric G-quadruplexes using a FRET melting assay. Conclusions: However, regarding the stabilization of the protozoan G-quadruplex, it was noted that the few substituted derivatives, which showed interesting stabilization profiles, were not necessarily the most effective antimalarial compounds against both Plasmodium strains. Moreover, these new compounds did not show promising stabilizing effects on the different G4 sequences. Therefore, no correlation arises between their antimalarial activity and the selectivity of their binding to G-quadruplexes. Full article

Background: Drug development for leishmaniases treatment follows a very selective process in order to propose drug candidates that possess all the qualities that meet the strict specifications of the pharmaceutical industry. Drug resistance is a limiting factor that can impact the lifespan of a marketed drug. It is now essential that the risk of drug resistance be evaluated at the early stage of in vitro studies to discard a lead compound that could quickly generate drug resistance once available on the market. Objectives: This article aims to estimate the risk of drug resistance emergence for a promising drug candidate at the in vitro early stage of drug development. Methods: A sequential method is proposed to study some of the phenotypic characteristics and parameters of resistant parasites such as time to achieve maximal resistance during stepwise drug pressure, resistance amplitude, stability, fitness, and infectivity both in vitro and in vivo. Results: Some examples with drugs in clinical use and former drug candidates are given. Conclusions: This method providing an evaluation of the risk of drug resistance from an in vitro model of Leishmania donovani be extrapolated to other Leishmania species. Full article

The kallikrein–kinin system and its B1 and B2 receptors are key regulators in metabolic disorders such as obesity, diabetes, and insulin resistance. Obesity, a chronic and multifactorial condition often associated with comorbidities like type 2 diabetes and dyslipidemia, remains poorly understood at the metabolic level. The kinin B2 receptor (B2R) is involved in blood pressure regulation and glucose metabolism, promoting glucose uptake in skeletal muscle via bradykinin. Studies in B2R-KO mice demonstrate that the absence of this receptor predisposes animals to glucose intolerance under a high-fat diet and impairs adaptive thermogenesis, indicating a protective role for B2R in metabolic homeostasis and insulin sensitivity. In contrast, the kinin B1 receptor (B1R) is inducible under pathological conditions and is activated by kinin metabolites. Mouse models lacking B1R exhibit improved metabolic profiles, including protection against high-fat diet-induced obesity and insulin resistance, enhanced energy expenditure, and increased leptin sensitivity. B1R inactivation in adipocytes enhances insulin responsiveness and glucose tolerance, supporting its role in the development of insulin resistance. Moreover, B1R deficiency improves energy metabolism and thermogenic responses to adrenergic and cold stimuli, promoting the activation of brown adipose tissue and the browning of white adipose tissue. Collectively, these findings suggest that B1R and B2R represent promising therapeutic targets for the treatment of metabolic disorders. Full article

Rheumatoid arthritis (RA) is a chronic systemic inflammatory disorder primarily targeting joints, leading to pain, swelling, and stiffness. RA results from the body’s own immune system attacking its own tissues. Currently, there are various treatments available for RA including disease-modifying antirheumatic drugs (DMARDs) and NSAIDs. Leflunomide (LEF) is a USFDA-approved synthetic DMARD which is being widely prescribed for the management of RA; however, it faces several challenges such as prolonged drug elimination, hepatotoxicity, and others. LEF exerts its therapeutic effects by inhibiting dihydroorotate dehydrogenase (DHODH), thereby suppressing pyrimidine synthesis and modulating immune responses. Emerging nanotechnology-based therapies help in encountering the current challenges faced in LEF delivery to RA patients. This review enlists the LEF’s pharmacokinetics, mechanism of action, and clinical efficacy in RA management. A comparative analysis with methotrexate, biologics, and other targeted therapies, highlighting its role in monotherapy and combination regimens and the safety concerns, including hepatotoxicity, gastrointestinal effects, and teratogenicity, is discussed alongside recommended monitoring strategies. Additionally, emerging trends in novel formulations and drug delivery approaches are explored to enhance efficacy and minimize adverse effects. Overall, LEF remains a perfect remedy for RA patients, specifically individuals contraindicated with drugs like methotrexate. The therapeutic applicability of LEF could be enhanced by developing more customized treatments and advanced drug delivery approaches. Full article

Background: Hypertension is a serious global health issue affecting over one billion adults and leading to severe complications if left unmanaged. Despite medical advancements, only a fraction of patients effectively have their hypertension under control. Among the factors that hinder adherence to hypertensive drugs are the debilitating side effects of the drugs. The lack of adherence results in poorer patient outcomes as patients opt to live with their condition, instead of having to deal with the side effects. Hence, there is a need to discover new hypertension drug molecules with better side effects to increase patient treatment options. To this end, computational methods such as artificial intelligence (AI) have become an exciting option for modern drug discovery. AI-based computational drug discovery methods generate numerous new lead antihypertensive drug molecules. However, predicting their potential side effects remains a significant challenge because of the complexity of biological interactions and limited data on these molecules. Methods: This paper presents a machine learning approach to predict the potential side effects of computationally synthesised antihypertensive drug molecules based on their molecular properties, particularly functional groups. We curated a dataset combining information from the SIDER 4.1 and ChEMBL databases, enriched with molecular descriptors (logP, PSA, HBD, HBA) using RDKit. Results: Gradient Boosting gave the most stable generalisation, with a weighted F1 of 0.80, and AUC-ROC of 0.62 on the independent test set. SHAP analysis over the cross-validation folds showed polar surface area and logP contributing the largest global impact, followed by hydrogen bond counts. Conclusions: Functional group patterns, augmented with key ADMET descriptors, offer a first-pass screen for identifying side-effect risks in AI-designed antihypertensive leads. Full article

Background/Objective: Cerivastatin (Cer), a cholesterol-lowering statin, was withdrawn from the market due to fatal cases of rhabdomyolysis, particularly when co-administered with gemfibrozil (Gem), a strong CYP2C8 inhibitor. However, the pharmacokinetic (PK) mechanisms underlying these adverse events remain unclear. This study investigates the impact of drug–drug interactions (DDIs) involving Gem and itraconazole (Itr), a potent CYP3A4 inhibitor, on plasma concentrations of Cer and its major metabolites—M23, M1, and cerivastatin lactone (Cer-L)—with a focus on the risk of excessive Cer-L accumulation. Methods: We applied a newly developed Metabolite-Linked Model that simultaneously characterizes parent drug and metabolite kinetics by estimating metabolite formation fractions (f_M) and elimination rate constants (K_eM). The model was calibrated using observed DDI data from Cer + Gem and Cer + Itr scenarios and then used to predict outcomes in an untested Cer + Gem + Itr combination. Results: The model accurately reproduced observed metabolite profiles in single-inhibitor DDIs. Predicted AUCR values for Cer-L were 4.2 (Cer + Gem) and 2.1 (Cer + Itr), with reduced K_eM indicating CYP2C8 and CYP3A4 as primary elimination pathways. In the dual-inhibitor scenario, Cer-L AUCR reached ~70—far exceeding that of the parent drug—suggesting severe clearance impairment and toxic accumulation. Conclusions: Dual inhibition of CYP2C8 and CYP3A4 may cause dangerously elevated Cer-L levels, contributing to Cer-associated rhabdomyolysis. This modeling approach offers a powerful framework for evaluating DDI risks involving active or toxic metabolites, supporting safer drug development and regulatory assessment. Full article

Background/Objectives: Severe malaria, mainly caused by Plasmodium falciparum, remains a significant therapeutic challenge due to increasing drug resistance and adverse effects. Flavonoids, known for their wide range of bioactivities, offer a promising route for antimalarial drug discovery. The aim of this study was to elucidate key structural features associated with antimalarial activity in flavonoids and to develop accurate, interpretable predictive models. Methods: Curated databases of flavonoid structures and their activity against P. falciparum strains and enzymes were constructed. Molecular fingerprinting and decision tree analyses were used to identify key pharmacophoric groups. Subsequently, molecular descriptors were generated and reduced to build multiple classification and regression models. Results: These models demonstrated high predictive accuracy, with test set accuracies ranging from 92.85% to 100%, and R² values from 0.64 to 0.97. Virtual screening identified novel flavonoid candidates with potential inhibitory activity. These were further evaluated using molecular docking and molecular dynamics simulations to assess binding affinity and stability with Plasmodium proteins (FabG, FabZ, and FabI). The predicted active ligands exhibited stable pharmacophore interactions with key protein residues, providing insights into binding mechanisms. Conclusions: This study provides highly predictive models for antimalarial flavonoids and enhances the understanding of structure–activity relationships, offering a strong foundation for further experimental validation. Full article

Suzetrigine represents a groundbreaking advancement in acute pain management as the first FDA-approved selective Na_v1.8 inhibitor. This comprehensive review synthesizes data from clinical trials, pharmacological studies, and prescribing information to evaluate its mechanism, efficacy, safety, and clinical implications. With demonstrated superiority over placebo in pivotal trials (SPID48: 29.3–48.4; p < 0.0001) and a favorable safety profile devoid of opioid-like addiction risks, suzetrigine offers a much-needed alternative in the opioid crisis era. However, its modest effect size compared to full-dose opioids, CYP3A-mediated drug interactions, and limited long-term data warrant judicious use. This article provides a balanced perspective on suzetrigine’s role in modern pain management protocols. Full article

Background: Shirakiopsis indica (Willd.) (Family: Euphorbiaceae), a mangrove species found in the Asian region, is a popular folkloric plant. Locally, the plant is traditionally used to treat various types of ailments, especially for pain relief. Therefore, the current study investigates the neuropharmacological, antipyretic, thrombolytic, and anthelmintic properties of the S. indica fruit methanolic extract (SIF-ME). Methods: The neuropharmacological activity was evaluated using several bioactive assays, and the antipyretic effect was investigated using the yeast-induced pyrexia method, both in Swiss albino mice models. Human blood clot lysis was employed to assess thrombolytic activity, while in vitro anthelmintic characteristics were tested on Tubifex tubifex. Insights into phytochemicals from SIF-ME have also been reported from a literature review, which were further subjected to molecular docking, pass prediction, and ADME/T analysis and validated the wet-lab outcomes. Results: In the elevated plus maze test, SIF-ME at 400 mg/kg demonstrated significant anxiolytic effects (200.16 ± 1.76 s in the open arms, p < 0.001). SIF-ME-treated mice exhibited increased head dipping behavior and spent a longer time in the light box, confirming strong anxiolytic activity in the hole board and light–dark box tests, respectively. It (400 mg/kg) also significantly reduced depressive behavior during forced swimming and tail suspension tests (98.2 ± 3.83 s and 126.33 ± 1.20 s, respectively). The extract induced strong locomotor activity, causing mice’s mobility to gradually decrease over time in the open field and hole cross tests. The antipyretic effect of SIF-ME (400 mg/kg) was minimal using the yeast-induced pyrexia method, while it (100 μg/mL) killed T. tubifex in 69.33 ± 2.51 min, indicating a substantial anthelmintic action. SIF-ME significantly reduced blood clots by 67.74% (p < 0.001), compared to the control group’s 5.56%. The above findings have also been predicted by in silico molecular docking studies. According to the molecular docking studies, the extract’s constituents have binding affinities ranging from 0 to −10.2 kcal/mol for a variety of human target receptors, indicating possible pharmacological activity. Conclusions: These findings indicate that SIF-ME could serve as a promising natural source of compounds with neuropharmacological, anthelmintic, thrombolytic, and antipyretic properties. Full article

Background: Bacterial resistance to antimicrobial drugs is a critical phenomenon that is hampering clinical treatments, raising the need for promising compounds that can be explored as pharmaceutical products. This study investigated the antimicrobial potential of α-Ag₂WO₄–alpha phase, orthorhombic structure silver tungstate nanoparticles (STN), against clinical isolates of Staphylococcus aureus, Pseudomonas aeruginosa and Escherichia coli, alone and combined to clinically relevant antimicrobial drugs. Methods: We used classical methods (MIC/checkerboard) to investigate the antimicrobial activity of STN. We characterized STN using X-ray diffraction, photoluminescence and scanning electron microscopy. We also performed cytotoxicity tests on BGM cells and anti-inflammatory tests in vitro. Results: STN was effective at 128 µg/mL for S. aureus and at 256 µg/mL for E. coli, but was not effective against P. aeruginosa. When combined with antimicrobials, STN decreased their MIC values, and its anti-inflammatory potential was confirmed. CC₅₀ of STN was of 16.23 ± 1.09 μg/mL against BGM cells. Conclusions: Our data open doors for further studies in animal models to investigate the effects on STN in infectious diseases. Full article

Background: Malaria remains a significant global health burden, particularly in sub-Saharan Africa, accounting for high rates of illness and death. The growing resistance to frontline antimalarial therapies underscores the urgent need for novel drug targets and therapeutics. Bromodomain-containing proteins, which regulate gene expression through chromatin remodeling, have gained attention as potential targets. Plasmodium falciparum bromodomain protein 1 (PfBDP1), a 55 kDa nuclear protein, plays a key role in recognizing acetylated lysine residues and facilitating transcription during parasite development. Methods: This study investigated ex vivo PfBDP1 gene mutations and identified potential small molecule inhibitors using computational approaches. Malaria-positive blood samples were collected. Genomic DNA was extracted, assessed for quality, and amplified using PfBDP1-specific primers. DNA sequencing and alignment were performed to determine single-nucleotide polymorphism (SNP). Structural modeling used the PfBDP1 crystal structure (PDB ID: 7M97), and active site identification was conducted using CASTp 3.0. Virtual screening and pharmacophore modeling were performed using Pharmit and AutoDock Vina, followed by ADME/toxicity evaluations with SwissADME, OSIRIS, and Discovery Studio. GROMACS was used for 100 ns molecular dynamics simulations. Results: The malaria prevalence rate stood at 12.24%, and the sample size was 165. Sequencing results revealed conserved PfBDP1 gene sequences compared to the 3D7 reference strain. Virtual screening identified nine lead compounds with binding affinities ranging from −9.8 to −10.7 kcal/mol. Of these, CHEMBL2216838 had a binding affinity of −9.9 kcal/mol, with post-screening predictions of favorable drug-likeness (8.60), a high drug score (0.78), superior pharmacokinetics, and a low toxicity profile compared to chloroquine. Molecular dynamics simulations confirmed its stable interaction within the PfBDP1 active site. Conclusions: Overall, this study makes a significant contribution to the ongoing search for novel antimalarial drug targets by providing both molecular and computational evidence for PfBDP1 as a promising therapeutic target. The prediction of CHEMBL2216838 as a lead compound with favorable binding affinity, drug-likeness, and safety profile, surpassing those of existing drugs like chloroquine, sets the stage for preclinical validation and further structure-based drug design efforts. These findings are supported by prior experimental evidence showing significant parasite inhibition and gene suppression capability of predicted hits. Full article

The methods utilized in the drug discovery pipeline routinely combine machine learning and deep learning algorithms to enhance the outputs. The generation of a drug target, through virtual screening and computational analysis of databases used for target discovery, has increased the reliability of the machine learning and deep learning incorporated techniques. Recent technological advances in human immunology have provided improved tools that allow a better understanding of the biological and molecular mechanisms leading to the protective human immune response to pathogens, inspiring new strategies for vaccine design. Immunoinformatics approaches are more beneficial, and thus there is a demand for modern technologies such as reverse vaccinology, structural vaccinology, and system approaches in developing potential vaccine candidates. System theory, defined as a set of machine learning, control theory, and optimization-based methods applied to networked systems, provides a unifying framework for modeling and analyzing biological complexity. In this review, we explore the application of such computational methods at every stage of the therapeutic pipeline, including lead discovery, optimization, and dosing, as well as vaccine target prediction and immunogen design. Here, we summarize the system theoretic methods which provide insights into developed approaches and their applications in rational drug discovery and vaccine formulations. The approaches ranged in the review yield accurate predictions and insights. This review is intended to serve as a resource for researchers seeking to understand, adopt, or build upon system theoretic techniques in drug and vaccine development, offering both conceptual foundations and practical directions. Full article

Background/Objectives: Since the emergence of the COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the discovery of compounds with antiviral potential from medicinal plants has been extensively researched. This study aimed to investigate plant metabolites with in vitro inhibitory potential against SARS-CoV-2 targets, including 3CL_pro, PL_pro, Spike protein, and RdRp. Methods: A systematic review was conducted following PRISMA guidelines, with literature searches performed in six electronic databases (Scielo, ScienceDirect, Scopus, Springer, Web of Science, and PubMed) from January 2020 to February 2024. Computational analyses using SwissADME, pkCSM, ADMETlab, ProTox3, Toxtree, and DataWarrior were performed to predict the absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiles as well as other medicinal chemistry parameters of these compounds. Results: A total of 330 plant-derived compounds with inhibitory activities against the proposed targets were identified, with compounds showing IC₅₀ values as low as 0.01 μM. Our findings suggest that several plant metabolites exhibit significant in vitro inhibition of SARS-CoV-2 targets; however, few molecules exhibit drug development viability without further adjustments. Additionally, after these evaluations, two phenolic acids, salvianic acid A and protocatechuic acid methyl ester, stood out for their potential as candidates for developing antiviral therapies, with IC₅₀ values of 2.15 μM against 3CL_pro and 3.76 μM against PL_pro; respectively; and satisfactory in silico drug-likeness and ADMET profiles. Conclusions: These results reinforce the importance of plant metabolites as potential targets for antiviral drug discovery. Full article

Background: One of the challenges of applying artificial intelligence (AI) methods to drug discovery is the difficulty of laboratory synthesizability for many AI-discovered molecules. Often, in silico techniques and metrics such as the computationally enabled synthesizability score and AI-based retrosynthesis analysis are used. Methods: In this paper, we present a predictive synthesizability method that integrates the gains of synthetic accessibility scoring and the benefits of AI-driven retrosynthesis analysis tools to evaluate the synthesizability of AI-generated lead drug molecules. Results: We explored the proposed method by using it to analyze the synthesizability of a set of 123 novel molecules generated using AI models. The analysis of the synthesis route of the four best molecules from the set in terms of synthesizability, as identified using the proposed method, is presented. Conclusions: This strategy enables quick initial screening and more comprehensive actionable synthetic pathways, thereby balancing speed and detail, and favoring simple routes to avoid the risk of pursuing non-synthesizable compounds in the drug development pipeline. Full article

Background: TMPRSS2 plays an important role in the viral entry mechanisms of influenza viruses and coronaviruses. Therefore, TMPRSS2 seems to be a suitable antiviral drug target. To exclude possible side effects of TMPRSS2 truncation in an early stage of drug in-vitro testing, this study aims to analyze the impact of TMPRSS2 truncation via antisense peptide-conjugated phosphorodiamidate morpholino oligomer (PPMO) targeting immune cells, using the example of regulatory T cells (Treg). Methods: TMPRSS2 was truncated in human Tregs using a splice-modulating PPMO. Effects on Treg function were analyzed by evaluation of surface marker and transcription factor expression, cytokine secretion, and effector cell suppression capability. Results: PPMO treatment led to a slight concentration-dependent toxicity in Tregs. Tregs with truncated TMPRSS2 behave similarly to untreated and control PPMO-treated cells in the analyzed assays. Conclusions: Treg function is not altered after TMPRSS2 truncation and therefore, no unwanted side effects in regard of Tregs are expected when using TMPRSS2-truncating PPMO as an anti-viral drug. Full article

Cytochrome P450 (CYP450) enzymes are pivotal in the metabolism of numerous anticancer agents, with CYP3A4 being the predominant isoform involved. Inhibition of CYP450 enzymes is a major mechanism underlying clinically significant drug-drug interactions (DDIs), particularly in oncology, where polypharmacy is frequent. This review aims to provide a comprehensive and critical overview of CYP450 enzyme inhibition, focusing specifically on the impact of kinase inhibitors (KIs) and poly adenosine diphosphate-ribose polymerase (PARP) inhibitors. A systematic review of the current literature was conducted, focusing on the molecular mechanisms of CYP450 inhibition, including reversible, time-dependent, mechanism-based, and pseudo-irreversible inhibition. Specific attention was given to the inhibitory profiles of clinically relevant KIs and PARP inhibitors, with analysis of pharmacokinetic consequences and regulatory considerations. Many KIs, such as abemaciclib and ibrutinib, demonstrate time-dependent or quasi-irreversible inhibition of CYP3A4, while PARP inhibitors like olaparib and rucaparib exhibit moderate reversible and time-dependent CYP3A4 inhibition. These inhibitory activities can significantly alter the pharmacokinetics of co-administered drugs, leading to increased risk of toxicity or therapeutic failure. Regulatory guidelines now recommend early identification of time-dependent and mechanism-based inhibition using physiologically based pharmacokinetic) (PBPK) modeling. CYP450 inhibition by KIs and PARP inhibitors represents a critical but often underappreciated challenge in oncology pharmacotherapy. Understanding the mechanistic basis of these interactions is essential for optimizing treatment regimens, improving patient safety, and supporting personalized oncology care. Greater clinical vigilance and the integration of predictive modeling tools are necessary to mitigate the risks associated with CYP-mediated DDIs. Full article

Breast cancer continues to represent one of the most widespread and lethal health afflictions on a global scale. The advancement of this malignancy is predominantly influenced by genetic mutations that precipitate unregulated cellular growth and proliferation, with oxidative stress being a crucial factor in all phases of carcinogenic development. Oxidative stress emerges from a disruption in the equilibrium between reactive oxygen species (ROS) and antioxidants, which inflicts damage on cellular components and facilitates the onset of cancer. Although numerous studies have advocated the notion that augmenting antioxidant levels may confer protection against cancer, other investigations have yielded contradictory results. Nevertheless, the effectiveness of antioxidants in cancer prophylaxis remains contentious, with research exhibiting variable outcomes. Certain studies have indicated that a high consumption of fruits and vegetables abundant in antioxidants may lower cancer risk. However, the irrefutable evidence is currently absent. Furthermore, the chemotherapeutic agents, such as taxanes and cisplatin, utilized in breast cancer management are reported to produce ROS as an integral aspect of their therapeutic mechanisms, thereby highlighting the intricate interplay between redox equilibrium and oncological treatment. This review emphasizes the pro-oxidant hypothesis, which asserts that heightened levels of ROS may selectively annihilate cancer cells, given that normal cells generally sustain low levels of ROS. Some recent reports have indicated that the application of plant-based molecules as a therapeutic supplement may help treat breast cancer effectively. However, a comprehensive understanding of the role of oxidative stress in breast cancer and use of antioxidants could pave the way for more precisely targeted therapeutic strategies aimed at the modulation of redox homeostasis. Full article