Current Drug Targets - Volume 26, Issue 11, 2025
Volume 26, Issue 11, 2025
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Targeting Creatine and Creatine Kinase in Cancer: Exploring Potential Therapeutic Strategies
More LessAuthors: Mahla Abdollahzadeh, Razieh Ghodsi, Zhila Taherzadeh and Mahdi HatamipourCreatine kinases (CKs) are a family of vital enzymes implicated in the domain of cellular bioenergy, fulfilling a pivotal role in facilitating the reversible transfer of phosphoryl groups between adenosine triphosphate (ATP) and creatine. This process plays a crucial role in maintaining optimal ATP levels during energy-demanding processes, a requirement that is amplified in rapidly proliferating cells, including cancerous cells. CKs are pivotal in supporting cancer growth and metastasis, making their inhibition a promising therapeutic strategy. The present review discusses a few ways of disrupting the creatine energy production cycle with emphasis on three main areas of research: First, we consider the different strategies that attack the Creatine Transporter (SLC6A8). Since this transporter facilitates the entry of creatine into the cell, it is expected that inhibiting this transporter may lead to reduced availability of creatine for CK-mediated energy production. Second, strategies aimed at directly inhibiting the enzyme carrying out the creatine phosphorylation are described. Lastly, we consider approaches targeting the backward reaction, i.e., the re-conversion of phosphocreatine to creatine and, thereby, the equilibrium of the CK reaction. The current review gives an overview of the structure-activity and structure-property relationships of the currently available CK inhibitors. Understanding these relations in depth is a prerequisite for developing new and more potent and selective CK inhibitors. This review focuses on an in-depth analysis to create better CK inhibitors with possible applications in oncology.
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The Role of PGE2 in Age-related Diseases
More LessAuthors: Jun Guan, Chao Chen, Shanshan Wu and Haihong ZhuIn the past several years, human life expectancy has increased dramatically, and the global aging process is accelerating at an unprecedented rate. Impaired organ functions and systemic inflammation increase the risk of aging-related diseases. It seriously affects the quality of life in older adults and places a heavy burden on the global economy and public health. Inflammation is the cornerstone of many age-related diseases, and among various inflammatory mediators, Prostaglandin E2 (PGE2) has emerged as a key player. For example, PGE2 could participate in the progression of Alzheimer's disease (AD) by modulating neuroinflammation. Plasma PGE2 is regarded as a potential and specific diagnostic biomarker, and higher initial PGE2 levels are positively correlated with longer survival in AD. PGE2 also mediates bone and muscle metabolism to affect age-related musculoskeletal diseases, including sarcopenia, osteoporosis, and osteoarthritis. It activates the EP4 receptor on sensory nerves to inhibit sympathetic nerve activity and modulate bone formation. Moreover, the PGE2/EP4 axis positively regulates muscle mass and strength. In diabetes, increased Cox-2 and m-PGES2 promote PGE2 production. The activated PGE2/EP3 axis exacerbates the progression of type 2 diabetes (T2D) by impairing glucose metabolism and accelerating β-cell senescence. Therefore, the role of PGE2 in age-related diseases deserves greater attention. Its involvement is driven by the dysregulation of its biosynthesis, metabolism, and receptor-mediated signaling. Regulating the concentration of PGE2 or modulating receptor activity represents a promising therapeutic strategy for managing age-related diseases.
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Lipidomics in Breast Cancer: Decoding Metabolic Reprogramming and Unlocking Therapeutic Opportunities
More LessAuthors: Harshita Singhai, Sunny Rathee and Umesh K. PatilLipidomics, a cutting-edge branch of metabolomics provides a comprehensive understanding of the lipidome and its alterations in cellular and systemic processes. In Breast Cancer (BC), a highly heterogeneous disease, lipidomics has emerged as a pivotal tool for exploring metabolic reprogramming, tumor progression, and therapeutic resistance. This review highlights the intricate relationship between lipid metabolism and breast cancer, with a focus on subtype-specific lipid dependencies, oxidative stress, and ferroptosis. Technological advancements, such as mass spectrometry and chromatography, have enabled precise profiling of lipid alterations, revealing distinct lipid signatures across breast cancer subtypes. Key enzymes like acetyl-CoA carboxylase (ACC) and fatty acid synthase (FASN), along with lipid regulators like PPARγ, have been identified as central players in lipid-driven tumorigenesis. Lipidomic studies offer the potential for biomarker discovery and the development of lipid-targeted therapies. Despite challenges in standardization and integration with other omics approaches, lipidomics is poised to revolutionize breast cancer diagnostics and therapeutics, providing novel insights into the metabolic underpinnings of this complex disease.
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Advancing Amyloid Aggregation Research: A Focus on Innovative Therapies, Molecular Modeling and Nano-Delivery Systems in Alzheimer’s Disease
More LessAuthors: Umaira Hasan, Himangini Jain and Ruhi AliIntroductionAlzheimer’s disease (AD), the most common form of dementia, is a major global health issue. Its complex pathology, including amyloid-beta (Aβ) aggregation, leads to neuronal damage and cognitive decline. Since Aβ plays a major role in AD, therapies targeting its production, aggregation, and clearance are being actively explored. This review discusses recent advances in gene therapy, enzyme inhibitors, molecular modeling, and nano-delivery systems aimed at modifying AD progression, highlighting their potential and challenges.
MethodsThis review compiles findings on BACE1 and γ-secretase inhibitors, gene therapies that modify amyloid metabolism, and combination therapies. Studies have been selected based on their focus on Aβ regulation and their impact on disease progression, cognitive function, and breakthroughs in diagnostics, molecular modeling, and drug delivery for neurodegenerative conditions.
ResultsBACE1 inhibitors, such as verubecestat, and γ-secretase inhibitors, shows potential, however, they face significant challenges related to BBB penetration and adverse effects. Gene therapies using AAV vectors and CRISPR/Cas9 technologies are promising, particularly for individuals genetically predisposed to these diseases. Combination therapies targeting amyloid, tau, and neuro-inflammation have emerged as effective approaches. Advancements in PET, SPECT, MRI, small molecule probes, molecular modeling, and nano-particle-based drug delivery are improving diagnostic and treatment options.
DiscussionThe findings emphasize the multifactorial complexity of amyloid disorders and the limitations of mono-therapies. While certain agents demonstrated efficacy in early disease stages, most treatments have failed in advanced phases due to poor central nervous system (CNS) bioavailability, adverse effects, or insufficient target engagement. Novel delivery systems, combination therapies, and computational design approaches offer enhanced translational potential. However, challenges such as immune responses, delivery efficiency, and off-target effects continue to pose significant barriers.
ConclusionAβ-targeted therapies, including enzyme inhibitors and gene therapies, hold promise, though challenges such as BBB penetration and toxicity still remain. Combination therapies, along with advancements in diagnostics and drug delivery technology, are essential for finding effective treatments for Alzheimer’s, Parkinson’s, and other neurodegenerative diseases. Future research should prioritize overcoming the persistent barriers to BBB penetration, enhancing therapeutic selectivity, and refining drug delivery systems to enable more precise, targeted interventions, to ultimately reduce the progression of disease at the molecular level.
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RMNet: An RNA m6A Cross-species Methylation Detection Method for Nanopore Sequencing
More LessAuthors: Qingwen Li, Chen Sun, Daqian Wang and Jizhong LouIntroductionN6-methyladenosine (m6A) is the most prevalent RNA modification in eukaryotic cells, influencing RNA lifecycle processes. Existing m6A detection methods, such as wet-lab techniques and statistical approaches, are time-consuming, labor-intensive, or require control samples, while machine learning models often lack cross-species applicability. This study aims to develop RMNet, a robust cross-species m6A detection method using nanopore sequencing.
MethodsRMNet employs Conformer and RNN architectures, integrating signal and alignment features from nanopore sequencing data. Contrastive learning enhances differentiation between m6A and non-m6A sites. The model was trained and tested on datasets from synthesized RNA, Arabidopsis, and human samples, using a single set of model weights.
ResultsRMNet achieved state-of-the-art performance with accuracies of 99.7% for synthesized RNA, 78.8% for Arabidopsis, and 88.9% for human datasets. It outperformed existing methods (m6Anet, DENA, and RedNano) across six metrics, including AUC and AUPR, demonstrating robust cross-species generalization.
DiscussionRMNet’s ability to detect m6A sites across diverse species with a single model addresses limitations of species-specific models. Its high sensitivity and feature representation enable applications in cancer research, neurodevelopmental studies, and plant biology. Limitations include higher error rates in human datasets for thymine-rich k-mers, likely due to complex secondary structures.
ConclusionRMNet provides an efficient, powerful tool for cross-species m6A detection, advancing epitranscriptomics research with potential applications in precision medicine and agricultural science.
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Volumes & issues
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Volume 26 (2025)
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Volume 25 (2024)
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Volume 24 (2023)
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Volume 23 (2022)
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Volume 22 (2021)
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Volume 21 (2020)
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Volume 20 (2019)
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Volume 19 (2018)
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Volume 18 (2017)
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Volume 17 (2016)
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Volume 16 (2015)
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Volume 15 (2014)
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Volume 14 (2013)
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Volume 13 (2012)
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Volume 12 (2011)
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Volume 11 (2010)
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Volume 10 (2009)
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Volume 9 (2008)
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Volume 8 (2007)
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Volume 7 (2006)
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Volume 6 (2005)
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Volume 5 (2004)
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Volume 4 (2003)
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Volume 3 (2002)
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Volume 2 (2001)
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Volume 1 (2000)
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