PubMed İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/397
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Article Identification of Potential Dual HDAC6 and HSP90 Inhibitors for the Treatment of Cancer Using Molecular Docking, Molecular Dynamics and MM/PBSA Studies: A Comprehensive In Silico Study(Bentham Science Publ Ltd, 2026) Yucel, Muhsin Samet; Akcok, IsmailBackground Histone deacetylase 6 (HDAC6) and heat shock protein 90 (Hsp90) are crucial therapeutic targets in cancer research with their interconnected roles in regulating protein homeostasis and cellular processes. The interaction of these proteins within the cytosolic complex plays a critical role in regulating cancer cell survival and progression. Notably, current studies highlight that the simultaneous inhibition of HDAC6 and Hsp90 can produce synergistic effects and offer a promising therapeutic potential for combating malignant cancers.Objective The objective of this study was to explore potential compounds that can inhibit both HDAC6 and Hsp90 proteins.Methods In this study, a number of in-silico computational techniques were employed. A total of 791 molecules, sharing at least 30% similarity with previously identified four HDAC inhibitors, were obtained from the ZINC15 database and subjected to docking on HDAC6 and Hsp90 proteins. The top eight ligands demonstrating the best binding scores against both targets, with panobinostat and ganetespib serving as reference compounds for HDAC6 and Hsp90, respectively, were selected for further analysis. Subsequently, ADME prediction and molecular dynamics simulations were conducted on the selected ligands.Results A detailed molecular docking, molecular dynamics simulations and ADME studies have revealed that ZINC27653366 exhibited the highest inhibitory potential against both Hsp90 and HDAC6 target proteins, making it the most promising inhibitor.Conclusion In conclusion, although additional in vitro and in vivo studies are required for the validation, in silico evaluation of ZINC27653366 may position it as a promising candidate for the treatment of different types of cancers.Article Unveiling the Therapeutic Role of 3D-Cultured Mesenchymal Stem Cells in Diabetic Foot Ulcers through Transcriptomic Integration and Fibroblast Modulation(Springer, 2026-03-31) Ozturk, Esengul; Bicer, MesudeBackground Diabetic foot ulcers (DFUs) are among the most severe complications of diabetes mellitus and remain difficult to manage due to chronic inflammation, defective angiogenesis, delayed tissue repair, which increase the risk of recurrence and limb amputation. Standard treatments, such as debridement, infection management, pressure off-loading and revascularization, are commonly used, however; these interventions often inadequate to fully restore effective wound repair. Mesenchymal stem cells (MSCs) have attracted remarkable interest due to their potential regenerative ability and paracrine activity. Nevertheless, the molecular interaction between MSCs and fibroblasts under hyperglycemic conditions has not been fully elucidated. Objective This study aimed to examine differentially expressed genes (DEGs) associated with DFUs and MSC-related regenerative mechanisms using transcriptomic datasets (such as GSE143735, GSE199939, and GSE217709). Methods and results Differentially expressed genes and protein-protein interaction (PPI) network analysis were performed to determine central regulatory genes. Four key genes including CXCL1, MMP9, THBS1, and POSTN were recognized as hub genes related to inflammatory response, extracellular matrix reorganization, and angiogenesis. For experimental validation, L929 murine fibroblasts were exposed to high-glucose conditions to set-up an in vitro diabetic model and subsequently treated with MSCs with/without a 3D platform. Hyperglycemic conditions significantly reduced fibroblast proliferation and migration downregulated the expression of the identified hub genes and enhanced apoptotic activity. MSC treatment partially increased cellular function, while MSCs embedded into 3D culture enhanced a more pronounced recovery in both gene expression patterns and functional assays. Conclusions These findings suggest that high glucose impair fibroblast functions for wound repair, while 3D-cultured MSCs enhance regenerative responses and may represent a promising strategy for diabetic wound healing.Article TEffectBayes: A Nextflow Pipeline for Exploring the Potential Effect of Transposable Elements in Gene Regulatory Network with Multi-Omic Bayesian Network Model(Springer Heidelberg, 2026-03-10) Karakülah, Gökhan; Güner, Hüseyin; Kutlu, Necati KaanTransposable elements (TEs) are critical contributors to gene regulatory networks, yet their repetitive and abundant nature complicates efforts to elucidate their precise regulatory roles. While existing computational tools facilitate systematic identification of associations between TEs and gene expression, these methods typically cannot account for confounding variables or capture causal and directional interactions. To address these limitations, we developed TEffectBayes, a Nextflow-based pipeline leveraging a multi-omic Bayesian network (BN) framework designed to systematically infer directional, probabilistic regulatory dependencies involving TEs. TEffectBayes integrates diverse omics datasets, including RNA-seq-derived gene and locus-specific TE expression, along with ChIP-seq-based histone modification data processed via custom R and Python scripts. Integrated multi-omic datasets are subsequently employed to build gene-centric Bayesian models, enabling robust inference of context-dependent, probabilistic relationships between TEs, chromatin modifications, and gene expression. TEffectBayes thus provides a reproducible and scalable computational framework for unraveling the complex regulatory landscape shaped by TEs. In summary, TEffectBayes supports systematic prioritization of TE-chromatin-gene regulatory candidates for downstream benchmarking and experimental validation, enabling hypothesis-driven follow-up studies in diverse biological contexts. The pipeline, along with comprehensive user tutorials and example datasets, is publicly accessible at https://github.com/nkaan-kutlu/TEffectBayes.Article Integrative Bioinformatics Prediction of West Nile Virus-Derived microRNAs Reveals Potential Host Regulatory Interactions(Elsevier Sci Ltd, 2026-08) Demirci, Muserref Duygu Sacar; Orhan, Mehmet Emin; Erginkoc, Altay Nida; Saçar Demirci, Müşerref DuyguWest Nile virus (WNV) is a mosquito-borne flavivirus linked to severe neuroinvasive disease. Although host and vector microRNAs (miRNAs) have been implicated in viral infection, the presence and functional relevance of WNV-encoded miRNAs remain largely unexplored. Here, we developed an integrative bioinformatics pipeline that combines multiple miRNA prediction algorithms with secondary structure screening and host transcriptomic data to identify high-confidence candidate WNV-derived mature miRNAs. Overlap-based confidence scoring and differential expression support from RNA-seq datasets prioritized a small subset of putative miRNA-mRNA interactions with potential roles in infection-associated gene regulation. A competitive endogenous RNA network constructed from predicted mRNA, lncRNA, and circRNA targets highlighted pathways involving innate immunity, GPCR and Wnt signaling, RNA degradation, and viral replication. Together, these findings provide a reproducible computational workflow and nominate testable regulatory interactions for future experimental validation.Article Borax-Doped Fe2O3 and CeO2 Nanoparticles Regulate Dose-Dependently Inflammation, the Cell Cycle, and Migration in LPS-Activated THP-1 Cells(Wiley-VCH Verlag GmbH, 2026-03) Sulak, Mine; Ceylan Ekiz, Yağmur; Şen, Alaattin; Acar, Büşra; Çelik Turgut, Gurbet; Aktaş Pepe, NihanThis study examined the biological effects of borax-doped Fe2O3 and CeO2 nanoparticles (NPs) on lipopolysaccharide (LPS)-activated THP-1 cells. The morphology and composition of the nanocomposites were confirmed via scanning electron microscopy (SEM) and energy-dispersive x-ray spectroscopy (EDX). Cell viability (resazurin and crystal violet assays), apoptosis/necrosis (annexin V/propidium iodide [PI]), cell cycle (flow cytometry), migration (scratch assay), and inflammatory response (Iba1 immunofluorescence staining, inducible nitric oxide synthase [iNOS] activity, and RT-PCR) were evaluated. The particle sizes ranged from 21.34 to 33.47 nm (Fe2O3-B-NPs) and 31.07 to 36.62 nm (CeO2-B-NPs). The IC10 and IC50 dose ranges were defined for each nanocomposite and applied across different cell lines to evaluate dose-dependent biological effects. Fe2O3-B-NPs altered cell cycle progression, increasing the number of S phase cells. Both nanocomposites promoted migration at low doses but inhibited it at high doses. CeO2-B-NPs reduced Iba1 levels, whereas Fe2O3-B-NPs increased inflammatory marker levels at higher concentrations. CeO2-B-NPs suppressed TNF-alpha and IL-1 beta gene expression at the IC50 dose, while both nanocomposites reduced iNOS activity. These results indicate that the dose-dependent effects of nanocomposites should be carefully evaluated.Article Follow-up of Health-Related Physical Fitness Elements in Mild Intellectual Disability for Three Years: A Sex Comparison(PeerJ Inc., 2026-03-04) Bozdağ, Berkan; Sönmez, Hüseyin Gazi; Prieto-González, Pablo; Karahan, Mustafa; Canli, Umut; Ergin, Murat; Koçak, Çalık VeliChildren with mild intellectual disability (MID) have significant limitations in both intellectual functioning and cognitive, social, and motor skill behaviors. Understanding the development of physical fitness in boys and girls with MID, and identifying sex-related differences can help devise interventional programs to improve physical fitness in these groups. The aim of this study was to compare sex differences in the time-dependent changes in health-related physical fitness components in individuals with MID. A longitudinal design was employed over three years. A total of 111 individuals with MID (46 girls and 65 boys) aged between 10 and 14 years (mean age 11.97 +/- 1.39 years) participated in the study. The physical fitness levels of the participants were assessed using the Brockport Physical Fitness Test (BPFT) battery. The tests included body composition (body height, body mass, and body mass index), aerobic endurance (15 m Progressive Aerobic Cardiovascular Endurance Run (PACER) test), and musculoskeletal function (dominant handgrip strength, back-saver sit-and-reach, and trunk lift). The results revealed that, over time, the longitudinal developmental trajectories for body mass, body height, aerobic endurance, and dominant handgrip strength were more favorable for boys. However, the longitudinal development curves for body mass index (BMI), trunk lift, and flexibility were similar for both boys and girls. The findings of this study provide valuable evidence for developing targeted physical activity programs for individuals with MID, and demonstrate the need for programs aimed at increasing aerobic endurance and muscle strength in girls with MID.Article Thermal Stresses in SOFC Stacks: The Role of Mismatch Among Thermal Conductivity of Adjacent Components(Tubitak Scientific & Technological Research Council Turkey, 2021-06-30) Aydin, Ozgur; Matsumoto, Go; Shiratori, YusukeGenerating power from renewable biogas in solid oxide fuel cells (SOFCs) is an environment-friendly, efficient, and promising energy conversion process. Biogas can be used in SOFCs via a reforming process for which dry reforming is more suitable as the reforming agent exists in the biogas mixture. Biogas can be directly reformed to H-2 -rich fuel stream in the anode chamber of a SOFC by the heat released during power generation. Exploiting the heat and water produced in the SOFC for internal reforming of biogas makes the energy conversion process very efficient; however, various challenges are reported. Thus, indirect internal reforming is opted for which a separate reforming domain is required. In an indirect internal reformer operating at usual conditions, dry reforming rate is quite high in the inlet and it decreases steeply toward the fuel outlet. Great temperature gradients develop over the reformer, since the dry reforming reaction is strongly endothermic. The abruptly varying rate of the reforming reaction affects the temperature fields in the adjacent components of SOFC and hence intolerable thermal stresses emerge on the SOFC components. In our preceding study, we graded the reforming domain, homogenized the temperature profile over the reforming domain, and executed performance and durability experiments. However, most of the experiments failed due to fracturing SOFC components hinting at existence of thermal stresses. In that study, we focused on minimizing the temperature gradients within the reforming domain; namely, we neglected the other processes. To eliminate the thermal stresses, we modeled the entire module of SOFC equipped with a reformer featuring a graded reforming domain. We found that the mismatch between the thermal conductivities of the adjacent module components is the major reason for the thermal stresses. When the mismatch is eliminated, thermal stresses disappear even if the reforming domain is not graded.Article Citation - WoS: 9Citation - Scopus: 9Therapeutic Potential of Nitrogen-Substituted Oleanolic Acid Derivatives in Neuroinflammatory and Cytokine Pathways: Insights From Cell-Based and Computational Models(Wiley-VCH Verlag GmbH, 2025-04-22) Turgut, Gurbet Celik; Pepe, Nihan Aktas; Ekiz, Yagmur Ceylan; Senol, Halil; Sen, AlaattinThis study was conducted to investigate the mechanism of the potential and anti-inflammatory properties of nitrogen-substituted oleanolic acid derivatives that can be used to treat neuroinflammatory diseases. Nitrogen-containing oleanolic acid derivatives have been evaluated for their anti-neuroinflammatory effects in vitro in neuronal and monocytic cell lines at nontoxic doses, and the production of cytokines (TNF-alpha, IL-6 and IL-17), the inflammatory enzyme induced nitric oxide synthase (iNOS) and NF-kappa B signalling under LPS-stimulated conditions, and the expression of genes associated with Alzheimer's disease have been assessed. In addition, molecular docking and molecular dynamics simulation assessments are conducted in silico. Key protein markers of neurodegenerative diseases, especially Alzheimer's disease and neuroinflammation, TAU protein levels, and microglial activation, as well as ionised calcium-binding adaptor protein-1 (IBA1) levels, were significantly reduced with the addition of oleanolic acid derivatives. LPS-induced NF-kappa B luciferase reporter activity and iNOS activity were significantly inhibited, approaching the levels in uninduced controls. The mRNA expression of proinflammatory cytokines critical for neuroinflammation, such as TNF-alpha, NF-kappa B, IL-6 and IL-17, was reduced twofold to sevenfold. Furthermore, the molecular docking and MD simulation analyses revealed potential interactions with the TNF-alpha and NF-kappa B proteins. These findings underscore the potential of oleanolic acid derivatives, particularly compound 16, as candidates for further development as therapeutic agents for neurodegenerative diseases associated with chronic inflammation.Article Citation - WoS: 9Citation - Scopus: 13The Impact and Future of Artificial Intelligence in Medical Genetics and Molecular Medicine: An Ongoing Revolution(Springer Heidelberg, 2024-08) Ozcelik, Firat; Dundar, Mehmet Sait; Yildirim, A. Baki; Henehan, Gary; Vicente, Oscar; Sanchez-Alcazar, Jose A.; Dundar, MunisArtificial intelligence (AI) platforms have emerged as pivotal tools in genetics and molecular medicine, as in many other fields. The growth in patient data, identification of new diseases and phenotypes, discovery of new intracellular pathways, availability of greater sets of omics data, and the need to continuously analyse them have led to the development of new AI platforms. AI continues to weave its way into the fabric of genetics with the potential to unlock new discoveries and enhance patient care. This technology is setting the stage for breakthroughs across various domains, including dysmorphology, rare hereditary diseases, cancers, clinical microbiomics, the investigation of zoonotic diseases, omics studies in all medical disciplines. AI's role in facilitating a deeper understanding of these areas heralds a new era of personalised medicine, where treatments and diagnoses are tailored to the individual's molecular features, offering a more precise approach to combating genetic or acquired disorders. The significance of these AI platforms is growing as they assist healthcare professionals in the diagnostic and treatment processes, marking a pivotal shift towards more informed, efficient, and effective medical practice. In this review, we will explore the range of AI tools available and show how they have become vital in various sectors of genomic research supporting clinical decisions.Article Citation - WoS: 4Citation - Scopus: 6Prediction of Biomechanical Properties of Ex Vivo Human Femoral Cortical Bone Using Raman Spectroscopy and Machine Learning Algorithms(Elsevier, 2025-09) Unal, Mustafa; Unlu, Ramazan; Uppuganti, Sasidhar; Nyman, Jeffry S.This study applied Raman spectroscopy (RS) to ex vivo human cadaveric femoral mid-diaphysis cortical bone specimens (n = 118 donors; age range 21-101 years) to predict fracture toughness properties via machine learning (ML) models. Spectral features, together with demographic variables (age, sex) and structural parameters (cortical porosity, volumetric bone mineral density), were fed into support vector regression (SVR), extreme tree regression (ETR), extreme gradient boosting (XGB), and ensemble models to predict fracture-toughness metrics such as crack-initiation toughness (Kinit) and energy-to-fracture (J-integral). Feature selection was based on Raman-derived mineral and organic matrix parameters, such as nu 1Phosphate (PO4)/CH2-wag, nu 1PO4/ Amide I, and others, to capture the complex composition of bone. Our results indicate that ensemble models consistently outperformed individual models, with the best performance for crack initiation toughness (Kinit) prediction being achieved using the ensemble approach. This yielded a coefficient of determination (R2) of 0.623, root-mean squared error (RMSE) of 1.320, mean absolute error (MAE) of 1.015, and mean percentage absolute error (MAPE) of 0.134. For prediction of the overall energy to propagate a crack (J-integral), the XGB model achieved an R2 of 0.737, RMSE of 2.634, MAE of 2.283, and MAPE of 0.240. This study highlights the importance of incorporating mineral quality properties (MP) and organic matrix properties (OMP) for enhanced prediction accuracy. This work represents the first-ever study combining Raman spectroscopy with other clinical and structural features to predict fracture toughness of human cortical bone, demonstrating the potential of artificial intelligence (AI) and ML in advancing bone research. Future studies could focus on larger datasets and more advanced modeling techniques to further improve predictive capabilities.
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