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Journal articles on the topic 'Therapeutic target identification'

Author: Grafiati

Published: 16 November 2024

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1

Koscielny, Gautier, Peter An, Denise Carvalho-Silva, Jennifer A. Cham, Luca Fumis, Rippa Gasparyan, Samiul Hasan, et al. "Open Targets: a platform for therapeutic target identification and validation." Nucleic Acids Research 45, no. D1 (November 29, 2016): D985—D994. http://dx.doi.org/10.1093/nar/gkw1055.

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2

Bajorath, Jürgen. "Identification and validation of therapeutic target proteins." TARGETS 1, no. 2 (August 2002): 45–46. http://dx.doi.org/10.1016/s1477-3627(02)02194-3.

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3

Hassan, Md Imtaiyaz. "Multi-omics approaches to therapeutic target identification." Briefings in Functional Genomics 22, no. 2 (March 2023): 75. http://dx.doi.org/10.1093/bfgp/elac058.

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4

Liao, Jianbo, Qinyu Wang, Fengxu Wu, and Zunnan Huang. "In Silico Methods for Identification of Potential Active Sites of Therapeutic Targets." Molecules 27, no. 20 (October 20, 2022): 7103. http://dx.doi.org/10.3390/molecules27207103.

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Target identification is an important step in drug discovery, and computer-aided drug target identification methods are attracting more attention compared with traditional drug target identification methods, which are time-consuming and costly. Computer-aided drug target identification methods can greatly reduce the searching scope of experimental targets and associated costs by identifying the diseases-related targets and their binding sites and evaluating the druggability of the predicted active sites for clinical trials. In this review, we introduce the principles of computer-based active site identification methods, including the identification of binding sites and assessment of druggability. We provide some guidelines for selecting methods for the identification of binding sites and assessment of druggability. In addition, we list the databases and tools commonly used with these methods, present examples of individual and combined applications, and compare the methods and tools. Finally, we discuss the challenges and limitations of binding site identification and druggability assessment at the current stage and provide some recommendations and future perspectives.

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5

Hu, Yang, Yinteng Wu, Fu Gan, Mingyang Jiang, Dongxu Chen, Mingjing Xie, Yiji Jike, and Zhandong Bo. "Identification of Potential Therapeutic Target Genes in Osteoarthritis." Evidence-Based Complementary and Alternative Medicine 2022 (August 13, 2022): 1–15. http://dx.doi.org/10.1155/2022/8027987.

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Objective. Osteoarthritis (OA), also known as joint failure, is characterized by joint pain and, in severe cases, can lead to loss of joint function in patients. Immune-related genes and immune cell infiltration play a crucial role in OA development. We used bioinformatics approaches to detect potential diagnostic markers and available drugs for OA while initially exploring the immune mechanisms of OA. Methods. The training set GSE55235 and validation set GSE51588 and GSE55457 were obtained from the Gene Expression Omnibus (GEO) database and differentially expressed genes (DEGs) were identified by the limma package. Gene set enrichment analysis (GSEA) was performed on the GSE55235 dataset using the cluster profiler package. At the same time, DEGs were analyzed by gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). In addition, protein-protein interaction (PPI) analysis was performed on the common DEGs of the three datasets using the STRING database. Proteins with direct linkage were identified as hub genes, and the relation of hub genes was subsequently analyzed using the GOSemSim package. Hub genes’ expression profiles and diagnostic capabilities (ROC curves) were analyzed and validated using three datasets. In addition, we performed RT-qPCR to validate the levels of hub genes. The immune microenvironment was analyzed using the CIBERSORT package, and the relationship between hub genes and immune cells was evaluated. In addition, we used a linkage map (CMAP) database to identify available drug candidates. Finally, the GSEA of hub genes was used to decipher the potential pathways corresponding to hub genes. Results. Three hub genes (CX3CR1, MYC, and TLR7) were identified. CX3CR1 and TLR7 were highly expressed in patients with OA, whereas the expression of MYC was low. The results of RT-qPCR validation were consistent with those obtained using datasets. Among these genes, CX3CR1 and TLR7 can be used as diagnostic markers. It was found that CX3CR1, MYC, and TLR7 affect the immune microenvironment of OA via different immune cells. In addition, we identified a potential drug for the treatment of OA. Altogether, CX3CR1, MYC, and TLR7 affect the immune response of OA through multiple pathways. Conclusion. CX3CR1, MYC, and TLR7 are associated with various immune cells and are the potential diagnostic markers and therapeutic targets for OA.

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Frühwald, M. C., and C. Plass. "Metastatic medulloblastoma—therapeutic success through molecular target identification?" Pharmacogenomics Journal 2, no. 1 (January 2002): 7–10. http://dx.doi.org/10.1038/sj.tpj.6500077.

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7

Zou, Mingjie, Haiyuan Zhou, Letian Gu, Jingzi Zhang, and Lei Fang. "Therapeutic Target Identification and Drug Discovery Driven by Chemical Proteomics." Biology 13, no. 8 (July 23, 2024): 555. http://dx.doi.org/10.3390/biology13080555.

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Throughout the human lifespan, from conception to the end of life, small molecules have an intrinsic relationship with numerous physiological processes. The investigation into small-molecule targets holds significant implications for pharmacological discovery. The determination of the action sites of small molecules provide clarity into the pharmacodynamics and toxicological mechanisms of small-molecule drugs, assisting in the elucidation of drug off-target effects and resistance mechanisms. Consequently, innovative methods to study small-molecule targets have proliferated in recent years, with chemical proteomics standing out as a vanguard development in chemical biology in the post-genomic age. Chemical proteomics can non-selectively identify unknown targets of compounds within complex biological matrices, with both probe and non-probe modalities enabling effective target identification. This review attempts to summarize methods and illustrative examples of small-molecule target identification via chemical proteomics. It delves deeply into the interactions between small molecules and human biology to provide pivotal directions and strategies for the discovery and comprehension of novel pharmaceuticals, as well as to improve the evaluation of drug safety.

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8

Traa, Annika, Emily Machiela, Paige D. Rudich, Sonja K. Soo, Megan M. Senchuk, and Jeremy M. Van Raamsdonk. "Identification of Novel Therapeutic Targets for Polyglutamine Diseases That Target Mitochondrial Fragmentation." International Journal of Molecular Sciences 22, no. 24 (December 14, 2021): 13447. http://dx.doi.org/10.3390/ijms222413447.

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Huntington’s disease (HD) is one of at least nine polyglutamine diseases caused by a trinucleotide CAG repeat expansion, all of which lead to age-onset neurodegeneration. Mitochondrial dynamics and function are disrupted in HD and other polyglutamine diseases. While multiple studies have found beneficial effects from decreasing mitochondrial fragmentation in HD models by disrupting the mitochondrial fission protein DRP1, disrupting DRP1 can also have detrimental consequences in wild-type animals and HD models. In this work, we examine the effect of decreasing mitochondrial fragmentation in a neuronal C. elegans model of polyglutamine toxicity called Neur-67Q. We find that Neur-67Q worms exhibit mitochondrial fragmentation in GABAergic neurons and decreased mitochondrial function. Disruption of drp-1 eliminates differences in mitochondrial morphology and rescues deficits in both movement and longevity in Neur-67Q worms. In testing twenty-four RNA interference (RNAi) clones that decrease mitochondrial fragmentation, we identified eleven clones—each targeting a different gene—that increase movement and extend lifespan in Neur-67Q worms. Overall, we show that decreasing mitochondrial fragmentation may be an effective approach to treating polyglutamine diseases and we identify multiple novel genetic targets that circumvent the potential negative side effects of disrupting the primary mitochondrial fission gene drp-1.

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9

Keerthana N and Koteeswaran K. "Target identification and validation in research." World Journal of Biology Pharmacy and Health Sciences 17, no. 3 (March 30, 2024): 107–17. http://dx.doi.org/10.30574/wjbphs.2024.17.3.0116.

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Target identification is a critical step in biomedical research because it lays the groundwork for the development of new therapies and drugs. Genetic research, including genome-wide association studies (GWAS), genomic sequencing, functional genomics, and data integration, is crucial for understanding disease genetics and potential treatment targets. Transcriptomics and proteomics give data on gene and protein expression, making it easier to identify targets in dysregulated diseases. Target identification is essential for drug discovery, precision medicine, lowering medication attrition, increasing therapeutic efficacy, and, eventually, transforming patient care and drug development. Target validation is a critical stage in drug development because it verifies that revealed molecular targets play a substantial role in disease progression and are therefore suitable for treatment. It employs a range of approaches, including genetic validation, pharmacological validation, and animal model validation. Target validation assures that discovered targets are physiologically relevant, druggable, and have a direct impact on disease processes, thereby reducing pharmaceutical attrition, promoting precision medicine, and hastening therapeutic development. Historically, target identification relied on limited knowledge, typically through candidate-based techniques based on assumptions or prior observations. Target validation experiments looked into how gene knockdown or RNA interference affected illness symptoms. Genomics, proteomics, and functional genomics have all made advances in recent years, as have high-throughput screening and data integration. CRISPR-based technologies and high-throughput sequencing have assisted in the validation of targets. Single-cell validation, machine learning and artificial intelligence, advanced in vitro models like organoids, and patient-derived models will all help to make future assessments of target relevance and treatment responses more precise and individualized. These developments have the potential to dramatically revolutionize research target identification and validation.

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10

Lin, Chunsheng, Qianqian Tian, Sifan Guo, Dandan Xie, Ying Cai, Zhibo Wang, Hang Chu, Shi Qiu, Songqi Tang, and Aihua Zhang. "Metabolomics for Clinical Biomarker Discovery and Therapeutic Target Identification." Molecules 29, no. 10 (May 8, 2024): 2198. http://dx.doi.org/10.3390/molecules29102198.

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As links between genotype and phenotype, small-molecule metabolites are attractive biomarkers for disease diagnosis, prognosis, classification, drug screening and treatment, insight into understanding disease pathology and identifying potential targets. Metabolomics technology is crucial for discovering targets of small-molecule metabolites involved in disease phenotype. Mass spectrometry-based metabolomics has implemented in applications in various fields including target discovery, explanation of disease mechanisms and compound screening. It is used to analyze the physiological or pathological states of the organism by investigating the changes in endogenous small-molecule metabolites and associated metabolism from complex metabolic pathways in biological samples. The present review provides a critical update of high-throughput functional metabolomics techniques and diverse applications, and recommends the use of mass spectrometry-based metabolomics for discovering small-molecule metabolite signatures that provide valuable insights into metabolic targets. We also recommend using mass spectrometry-based metabolomics as a powerful tool for identifying and understanding metabolic patterns, metabolic targets and for efficacy evaluation of herbal medicine.

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11

Albert, Reka, Bhaskar DasGupta, and Nasim Mobasheri. "Some Perspectives on Network Modeling in Therapeutic Target Prediction." Biomedical Engineering and Computational Biology 5 (January 2013): BECB.S10793. http://dx.doi.org/10.4137/becb.s10793.

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Drug target identification is of significant commercial interest to pharmaceutical companies, and there is a vast amount of research done related to the topic of therapeutic target identification. Interdisciplinary research in this area involves both the biological network community and the graph algorithms community. Key steps of a typical therapeutic target identification problem include synthesizing or inferring the complex network of interactions relevant to the disease, connecting this network to the disease-specific behavior, and predicting which components are key mediators of the behavior. All of these steps involve graph theoretical or graph algorithmic aspects. In this perspective, we provide modelling and algorithmic perspectives for therapeutic target identification and highlight a number of algorithmic advances, which have gotten relatively little attention so far, with the hope of strengthening the ties between these two research communities.

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12

Li, Chengzhang, and Jiucheng Xu. "Identification of Potentially Therapeutic Target Genes of Hepatocellular Carcinoma." International Journal of Environmental Research and Public Health 17, no. 3 (February 7, 2020): 1053. http://dx.doi.org/10.3390/ijerph17031053.

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Background: Hepatocellular carcinoma (HCC) is a major threat to public health. However, few effective therapeutic strategies exist. We aimed to identify potentially therapeutic target genes of HCC by analyzing three gene expression profiles. Methods: The gene expression profiles were analyzed with GEO2R, an interactive web tool for gene differential expression analysis, to identify common differentially expressed genes (DEGs). Functional enrichment analyses were then conducted followed by a protein-protein interaction (PPI) network construction with the common DEGs. The PPI network was employed to identify hub genes, and the expression level of the hub genes was validated via data mining the Oncomine database. Survival analysis was carried out to assess the prognosis of hub genes in HCC patients. Results: A total of 51 common up-regulated DEGs and 201 down-regulated DEGs were obtained after gene differential expression analysis of the profiles. Functional enrichment analyses indicated that these common DEGs are linked to a series of cancer events. We finally identified 10 hub genes, six of which (OIP5, ASPM, NUSAP1, UBE2C, CCNA2, and KIF20A) are reported as novel HCC hub genes. Data mining the Oncomine database validated that the hub genes have a significant high level of expression in HCC samples compared normal samples (t-test, p < 0.05). Survival analysis indicated that overexpression of the hub genes is associated with a significant reduction (p < 0.05) in survival time in HCC patients. Conclusions: We identified six novel HCC hub genes that might be therapeutic targets for the development of drugs for some HCC patients.

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13

Lan, Ming-Ying, Chi-Long Chen, Kuan-Ting Lin, Sheng-An Lee, Wu-Lung R. Yang, Chun-Nan Hsu, Jaw-Ching Wu, Ching-Yin Ho, Jin-Ching Lin, and Chi-Ying F. Huang. "From NPC Therapeutic Target Identification to Potential Treatment Strategy." Molecular Cancer Therapeutics 9, no. 9 (August 17, 2010): 2511–23. http://dx.doi.org/10.1158/1535-7163.mct-09-0966.

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14

Frame, Jenna, Xiaoqian Zhang, James Jin, Rebecca Soto, Shujin Zhang, Xin Li, Jing Zhang, and Yuelei Shen. "RenMice™ HiTS platform enables identification of novel therapeutic antibodies." Journal of Immunology 208, no. 1_Supplement (May 1, 2022): 116.15. http://dx.doi.org/10.4049/jimmunol.208.supp.116.15.

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Abstract Despite an increase in approved cancer-targeting antibody drugs over the last decade, the process of identifying novel therapeutic antibodies is routinely hampered by limitations in the discovery process. Such barriers include immune tolerance of highly homologous genes, antibody sequence humanization, clone selection and models for drug efficacy/safety evaluation. To overcome these challenges and increase the diversity of antibody paratopes and sequences that recognize functional epitopes, we developed the RenMice™ HiTS (Hyperimmune Target Specific) Platform, which consists of chromosome engineered mice with fully human immunoglobulin variable domains replacing the mouse loci, each with a specific target gene knocked out. Immunization of target-specific RenMice™ generates a sizeable diversity of antibodies, including those that recognize conserved regions between the antigen and the endogenous proteins of the immunized species. The platform is ideal for challenging targets, such as proteins with high homology across species, or multi-pass transmembrane proteins, such as GPCRs/ion channels, and can be used to generate antibodies that cross-react with human, monkey, dog, and mouse targets using a hybrid immunization strategy with both human and mouse/dog antigen. Generation of these species cross-reactive antibodies can be used for high-throughput in vivo efficacy screening in wild-type mice, and the preliminary response and toxicity can be assessed in dogs. Altogether, the RenMice™ HiTS platform facilitates the generation of antibodies that recognize novel epitopes and challenging targets while simultaneously allowing for a streamlined and successful preclinical phase based on in vivo efficacy and safety.

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15

Ravi, V., S. Kim, D. Dim, D. Hicks, C. Aggarwal, G. Hostetter, R. T. Cheney, M. Bittner, D. L. Trump, and M. K. Wong. "Identification of therapeutic targets in angiosarcoma." Journal of Clinical Oncology 25, no. 18_suppl (June 20, 2007): 10030. http://dx.doi.org/10.1200/jco.2007.25.18_suppl.10030.

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10030 Background: Human angiosarcoma is an aggressive malignancy with ability to invade locally and metastasize widely. Even with a multimodality approach, the local recurrence rate is 81% and 5 year disease-free survival is 17% for all comers. Durability of the responses to treatment options such as paclitaxel is 4 to 5 months. Our previous work shows that enhanced cell migration and invasion are integral to the chemoresistant angiosarcoma phenotype. However the molecular mechanism of this is unknown. Methods: In order to address this and to identify new therapeutic strategies, we analyzed formalin fixed paraffin embedded (FFPE) archival angiosarcoma specimens from 17 consecutive patients at our institution to identify aberrations at the DNA level that were highly prevalent. DNA was extracted from FFPE angiosarcoma specimens using the proteinase K method. Good quality DNA with an yield more than 5 micrograms was obtained from 10 out of 17 patients and these samples were assayed for DNA dosage differences compared to genomic reference DNA using array comparative genomic hybridization. High density 244K Agilent arrays were used to evaluate these specimens to enhance the precision of the estimates in this rare disease. Results: Statistically significant (p<0.001) aberrations with prevalence greater than 50% were noted in several genes including NOTCH2, MAML1 (notch signaling intermediate), oncomodulin, calnexin, sequestosome1, zinc finger proteins and ADAMTS2. This is particularly important since Notch and its ligand Jagged are developmental genes critical to tumorigenesis and there is emerging evidence of their role in endothelial activation. Conclusions: Aberrations involving the notch signaling pathway occur with a high prevalence in angiosarcomas and may serve as a target for therapeutic intervention. No significant financial relationships to disclose.

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16

Jackson, Aimee L., and Peter S. Linsley. "Recognizing and avoiding siRNA off-target effects for target identification and therapeutic application." Nature Reviews Drug Discovery 9, no. 1 (January 2010): 57–67. http://dx.doi.org/10.1038/nrd3010.

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17

Tie, Yan, Jihan Liu, Yushan Wu, Yining Qiang, Ge’Er Cai’Li, Pingxiang Xu, Ming Xue, Liping Xu, Xiaorong Li, and Xuelin Zhou. "A Dataset for Constructing the Network Pharmacology of Overactive Bladder and Its Application to Reveal the Potential Therapeutic Targets of Rhynchophylline." Pharmaceuticals 17, no. 10 (September 24, 2024): 1253. http://dx.doi.org/10.3390/ph17101253.

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Objectives: Network pharmacology is essential for understanding the multi-target and multi-pathway therapeutic mechanisms of traditional Chinese medicine. This study aims to evaluate the influence of database quality on target identification and to explore the therapeutic potential of rhynchophylline (Rhy) in treating overactive bladder (OAB). Methods: An OAB dataset was constructed through extensive literature screening. Using this dataset, we applied network pharmacology to predict potential targets for Rhy, which is known for its therapeutic effects but lacks a well-defined target profile. Predicted targets were validated through in vitro experiments, including DARTS and CETSA. Results: Our analysis identified Rhy as a potential modulator of the M3 receptor and TRPM8 channel in the treatment of OAB. Validation experiments confirmed the interaction between Rhy and these targets. Additionally, the GeneCards database predicted other targets that are not directly linked to OAB, corroborated by the literature. Conclusions: We established a more accurate and comprehensive dataset of OAB targets, enhancing the reliability of target identification for drug treatments. This study underscores the importance of database quality in network pharmacology and contributes to the potential therapeutic strategies for OAB.

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Nagahata, T. "Identification of RAI3 as a therapeutic target for breast cancer." Endocrine Related Cancer 12, no. 1 (March 1, 2005): 65–73. http://dx.doi.org/10.1677/erc.1.00890.

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19

Turner, Mark D. "The identification of TNFR5 as a therapeutic target in diabetes." Expert Opinion on Therapeutic Targets 21, no. 4 (March 2, 2017): 349–51. http://dx.doi.org/10.1080/14728222.2017.1297426.

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20

Tyner, J. W., M. W. Deininger, M. M. Loriaux, B. H. Chang, J. R. Gotlib, S. G. Willis, H. Erickson, et al. "RNAi screen for rapid therapeutic target identification in leukemia patients." Proceedings of the National Academy of Sciences 106, no. 21 (May 11, 2009): 8695–700. http://dx.doi.org/10.1073/pnas.0903233106.

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21

Arceci, R. J. "RNAi screen for rapid therapeutic target identification in leukemia patients." Yearbook of Oncology 2009 (January 2009): 114–15. http://dx.doi.org/10.1016/s1040-1741(09)79327-3.

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Yamada, T., R. Satow, M. Masuda, and K. Honda. "Integrated Genomic Approaches to Therapeutic Target Identification for Hepatocellular Carcinoma." Annals of Oncology 23 (September 2012): ix536. http://dx.doi.org/10.1016/s0923-7534(20)34218-6.

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Arceci, R. J. "RNAi screen for rapid therapeutic target identification in leukemia patients." Yearbook of Medicine 2009 (January 2009): 172–73. http://dx.doi.org/10.1016/s0084-3873(09)79582-3.

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24

Aoki, Hiroki, Koichi Yoshimura, Yasuhiro Ikeda, Kozo Fujii, Norio Akiyama, Akira Furutani, Yoshinobu Hoshii, et al. "Identification of a Molecular Therapeutic Target for Abdominal Aortic Aneurysm." Journal of Cardiac Failure 11, no. 9 (December 2005): S248. http://dx.doi.org/10.1016/j.cardfail.2005.08.052.

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25

Capela, Rita, Rita Félix, Marta Clariano, Diogo Nunes, Maria de Jesus Perry, and Francisca Lopes. "Target Identification in Anti-Tuberculosis Drug Discovery." International Journal of Molecular Sciences 24, no. 13 (June 22, 2023): 10482. http://dx.doi.org/10.3390/ijms241310482.

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Mycobacterium tuberculosis (Mtb) is the etiological agent of tuberculosis (TB), a disease that, although preventable and curable, remains a global epidemic due to the emergence of resistance and a latent form responsible for a long period of treatment. Drug discovery in TB is a challenging task due to the heterogeneity of the disease, the emergence of resistance, and uncomplete knowledge of the pathophysiology of the disease. The limited permeability of the cell wall and the presence of multiple efflux pumps remain a major barrier to achieve effective intracellular drug accumulation. While the complete genome sequence of Mtb has been determined and several potential protein targets have been validated, the lack of adequate models for in vitro and in vivo studies is a limiting factor in TB drug discovery programs. In current therapeutic regimens, less than 0.5% of bacterial proteins are targeted during the biosynthesis of the cell wall and the energetic metabolism of two of the most important processes exploited for TB chemotherapeutics. This review provides an overview on the current challenges in TB drug discovery and emerging Mtb druggable proteins, and explains how chemical probes for protein profiling enabled the identification of new targets and biomarkers, paving the way to disruptive therapeutic regimens and diagnostic tools.

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Panda, Chinmaya, and Rajani Kanta Mahapatra. "Identification of novel therapeutic candidates inCryptosporidium parvum: anin silicoapproach." Parasitology 145, no. 14 (April 25, 2018): 1907–16. http://dx.doi.org/10.1017/s0031182018000677.

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AbstractUnavailability of vaccines and effective drugs are primarily responsible for the growing menace of cryptosporidiosis. This study has incorporated a bioinformatics-based screening approach to explore potential vaccine candidates and novel drug targets inCryptosporidium parvumproteome. A systematic strategy was defined for comparative genomics, orthology with relatedCryptosporidiumspecies, prioritization parameters and MHC class I and II binding promiscuity. The approach reported cytoplasmic protein cgd7_1830, a signal peptide protein, as a novel drug target. SWISS-MODEL online server was used to generate the 3D model of the protein and was validated by PROCHECK. The model has been subjected toin silicodocking study with screened potent lead compounds from the ZINC database, PubChem and ChEMBL database using Flare software package of Cresset®. Furthermore, the approach reported protein cgd3_1400, as a vaccine candidate. The predicted B- and T-cell epitopes on the proposed vaccine candidate with highest scores were also subjected to docking study with MHC class I and II alleles using ClusPro web server. Results from this study could facilitate selection of proteins which could serve as drug targets and vaccine candidates to efficiently tackle the growing threat of cryptosporidiosis.

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Fernández-Ortega, Celia, Anna Ramírez, Dionne Casillas, Taimi Paneque, Raimundo Ubieta, Marta Dubed, Leonor Navea, et al. "Identification of Vimentin as a Potential Therapeutic Target against HIV Infection." Viruses 8, no. 6 (June 15, 2016): 98. http://dx.doi.org/10.3390/v8060098.

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Buchner, Maike, Lars Klemm, Chen Zhengshan, Huimin Geng, and Markus Muschen. "Identification of FoxM1 As Therapeutic Target in TKI-Resistant Ph+ ALL." Blood 120, no. 21 (November 16, 2012): 874. http://dx.doi.org/10.1182/blood.v120.21.874.874.

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Abstract Abstract 874 Background: Despite initial responsiveness of primary Philadelphia chromosome positive acute lymphoblastic leukemia (Ph+ALL) to tyrosine kinase inhibition (TKI), the majority of patients will relapse and develop TKI-resistant disease. Foxm1 belongs to the forkhead box transcription factor family and is a key regulator of malignant growth by promoting cell cycle and survival through increased DNA damage repair. Foxm1 has been implicated in the progression and chemoresistance in a wide range of solid tumors, including hepatocellular carcinoma and breast cancer. Foxm1 is expressed in dividing cells and regulates the expression of critical regulators for G2/M entry of the cell cycle including Cdc25B, cyclin-B1, Plk-1 and Aurora B kinase. In addition it decreases protein stability of p27kip and p21cip and regulates the expression of antioxidant defense machinery of the cell, e.g. by superoxide dismutase expression. Results: We compared Foxm1 expression levels in Ph+ ALL patient samples and CD19+ B cell precursors from healthy donors and found 12-fold higher levels in the leukemic cells (p=0.011). More importantly, Foxm1 levels at the time of diagnosis in a clinical trial for patients with high risk acute lymphoblastic leukemia (ALL) were predictive of poor outcome (COG P9906; n=207). Comparative analysis of microarray data from matched sample pairs at diagnosis and relapse revealed a significant upregulation of Foxm1 in the relapse samples (n=42; p=0.0025). To further study the role of Foxm1 in Ph+ ALL, we developed a genetic model for inducible inactivation of Foxm1 in Ph+ ALL. To this end, B cell precursors of Foxm1fl/fl mice were transformed with BCR-ABL1 and transduced with a tamoxifen (4-OHT)-inducible Cre. Interestingly, 4-OHT-mediated deletion of Foxm1 resulted in reduced cell viability and an arrest in G0/G1 with a significant decrease of the S-phase of the cell cycle following deletion of Foxm1. The ability to form colonies in vitro was significantly decreased by deletion of Foxm1. In addition, Foxm1−/− ALL cells revealed a strikingly higher sensitivity towards TKI-treatment (Imatinib dose-response curve) compared to the control cells. As a potential therapeutic agent to pharmacologically inhibit Foxm1 function, we evaluated the effects of a previously described ARF peptide that binds and inhibits Foxm1 function. We treated TKI-resistant (BCR-ABL1T315I) and TKI-sensitive patient-derived xenograft Ph+ ALL cells with various ARF peptide concentrations and found significant growth inhibition after 72h (IC50 16.8±4.3μM, n=4), regardless of TKI responsiveness. In addition, treatment of ARF peptide in combination with TKI reduced the viability from 65.7%±1.7 after TKI treatment alone (10μM) to 19%±0.8 after 48h (TKI 10μM ARF peptide 12μM). Ph+ ALL cells treated with similar concentrations of a mutated ARF control peptide revealed 77%±0.9 viable cells and ARF peptide treatment alone decreased the viability to 29.6%±0.4. Hence treatment with the ARF peptide alone induces apoptosis in patient-derived Ph+ ALL cells and enhances the effect of TKI, which confirms the findings of the ALL mouse model for human Ph+ ALL xenografts. In a complementary approach, we used the natural antibiotic Thiostrepton, which functions via Foxm1 blockade. To test the ability of Thiostrepton as a potential anti-leukemia agent, we studied patient-derived TKI-resistant (BCR-ABL1T315I) Ph+ ALL cells. Treatment of these patient derived Ph+ALL cells induced cytotoxicity in nanomolar concentrations of Thiostrepton along with a significant downregulation of Foxm1 protein levels. By contrast, Non-BCR-ABL1 tumor cells including lymphoma cells were not responsive to Thiostrepton treatment at similar concentrations. Conclusion: Our analyses reveal that Foxm1 is a valid therapeutic target for the treatment of TKI sensitive and resistant Ph+ ALL, including BCR-ABL1T315I. We show that Foxm1 has a crucial function in Ph+ ALL and impacts a) leukemia proliferation, b) colony formation, and c) TKI-resistance. These findings identify Foxm1 a rational target for combination therapy with TKI or as a single agent for TKI-resistant Ph+ ALL. Disclosures: No relevant conflicts of interest to declare.

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D'Arcy, Colleen E., Sandra J. Feeney, Catriona A. McLean, Stefan M. Gehrig, Gordon S. Lynch, Jaclyn E. Smith, Belinda S. Cowling, Christina A. Mitchell, and Meagan J. McGrath. "Identification of FHL1 as a therapeutic target for Duchenne muscular dystrophy." Human Molecular Genetics 23, no. 3 (September 18, 2013): 618–36. http://dx.doi.org/10.1093/hmg/ddt449.

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30

Conn, P. Michael, Timothy P. Spicer, Louis Scampavia, and Jo Ann Janovick. "Assay strategies for identification of therapeutic leads that target protein trafficking." Trends in Pharmacological Sciences 36, no. 8 (August 2015): 498–505. http://dx.doi.org/10.1016/j.tips.2015.05.004.

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Li, Bao-Zhu, Hai-Yan Zhang, Hai-Feng Pan, and Dong-Qing Ye. "Identification of MFG-E8 as a novel therapeutic target for diseases." Expert Opinion on Therapeutic Targets 17, no. 11 (August 23, 2013): 1275–85. http://dx.doi.org/10.1517/14728222.2013.829455.

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Hurtz, Christian, Huimin Geng, Erica Ballabio, Gang Xiao, Carina Ng, Behzad Kharabi Masouleh, Cheryl L. Willman, et al. "Identification Of BCL6 As a Therapeutic Target In MLL-Rearranged ALL." Blood 122, no. 21 (November 15, 2013): 72. http://dx.doi.org/10.1182/blood.v122.21.72.72.

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Abstract Background BCL6 has been identified in diffuse large B cell lymphoma (DLBCL), where it is frequently translocated to immunoglobulin loci and acts as a protoncogene and transcriptional repressor. We found in Ph+ acute lymphoblastic leukemia (ALL) that BCL6 is involved in a novel form of drug resistance to tyrosine kinase inhibitors (TKI) by protecting cells from p53-mediated apoptosis (Duy et al., Nature 2011). Our current study is focusing on the function of BCL6 in Non-Ph+ALL based on the finding that high BCL6 levels represent a predictor of poor clinical outcome. Results We analyzed the gene expression data from 207 children with high-risk B cell precursor ALL enrolled in the pediatric clinical trial (COG P9906) and found that high expression levels of BCL6 at the time of diagnosis correlated with a poor overall and relapse-free survival (OS p=0.007; RFS p=0.02). Furthermore, multivariate analyses showed that patients with high BCL6 expression levels and established predictors of poor clinical outcome such as high white blood counts (WBC), a positive minimal residual disease (MRD) or mutations in the tumor suppressor IKZF1 had a significantly poor OS and RFS. Matched sample pairs from 49 patients at diagnosis and relapse showed that BCL6 levels were increased at relapse compared to diagnosis (p=0.003). We next studied BCL6 protein levels in Non-Ph+ cell lines and childhood ALL patient samples and found that BCL6 levels are particularly high in MLL-AF4 ALL (n=19). Surprisingly, the patients from the clinical trial that had high BCL6 levels and MLLR rearrangements were those with the worst clinical outcome (OS p= 0.0009 and RFS p= 0.000208). We next tested if the MLL-AF4 oncogene drives aberrant BCL6 expression. First, we performed a ChIP-analysis with the oncoprotein MLL-AF4 and found that the BCL6 promoter is directly bound by MLL-AF4, suggesting that MLL-AF4 may indeed drive BCL6 expression. We then performed a BCL6 Western Blot of inducible MLL-AF4-transgenic pro-B cells, demonstrating that activation of the MLL-AF4 transgene is sufficient to induce ∼10-fold upregulation of BCL6 protein levels. We conclude that aberrant expression of BCL6 in childhood ALL can be the direct consequence of MLL-AF4 activity. To further elucidate the BCL6 signaling pathway, we performed a ChIP-analysis with human MLL-AF4 leukemia cells and found that tumor suppressor genes (e.g. CDKN1B and BACH2) and B cell linage specific genes like PAX5 and CD19 are repressed by BCL6, potentially explaining the mixed lineage phenotype of MLLR driven B-ALL. We used a genetic mouse model of childhood ALL based on bone marrow precursor cells from BCL6-/- mice to decipher the function of BCL6. Since mutations in the RAS pathway are found in about 30% of childhood ALL cases, we transduced B cell progenitor cells from BCL6-/- and BCL6+/+ mice with Nras using an inducible oncogenic TET-NRASG12D system. Similar to MLL-AF4 driven cells, activation of NRASG12D results in higher BCL6 protein expression. Strikingly, BCL6-deficiency results in a failure of NRASG12DALL cells to initiate leukemia. Clinical relevance To verify if the high BCL6 expression levels in MLL-AF4 patients are important for the disease progression, we transduced primary human childhood ALL xenografts with a dominant-negative BCL6-mutant (BCL6-DN). Expression of BCL6-DN rapidly induced cell cycle arrest and cell death. To test if pharmacological inhibition of BCL6 is of potential use for children with MLL-AF4 leukemia, we treated human MLL-AF4 driven primary human xenograft cells with a recently developed retro-inverso BCL6 peptide inhibitor (RI-BPI). Strikingly, treatment with RI-BPI not only compromised colony formation in methylcellulose it also prevents leukemia-initiation in transplant recipient mice. RI-BPI also had a strong synergistic effect when combined with the chemotherapy drug Vincristine, which represents the backbone for most high risk regimen in pediatric ALL. Conclusions These findings identify BCL6 as an important factor in leukemia initiation and survival and its pharmacological inhibition as a novel strategy to treat childhood ALL. Aberrant expression of BCL6 in MLL-AF4 ALL is the direct consequence of MLL-AF4 activity in these cells. Based on these findings, we propose combinations of BCL6 inhibitors (e.g. RI-BPI) with currently used chemotherapeutics as potential approach to reduce the risk of ALL relapse and improve overall outcome. Disclosures: No relevant conflicts of interest to declare.

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Qing, Lin-Sen, Nan Tang, Ying Xue, Jian Liang, Yi-Ming Liu, and Xun Liao. "Identification of enzyme inhibitors using therapeutic target protein–magnetic nanoparticle conjugates." Analytical Methods 4, no. 6 (2012): 1612. http://dx.doi.org/10.1039/c2ay25320h.

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Vilasboas-Campos, D., J. Lopes, B. Ferreira-Lomba, J. D. da Silva, M. D. da Costa, P. Maciel, and A. Teixeira-Castro. "Chemical screening for novel therapeutic target identification in Machado-Joseph disease." Neuroscience Applied 1 (2022): 100840. http://dx.doi.org/10.1016/j.nsa.2022.100840.

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Kuhn, Jens H., Wenhui Li, Sheli R. Radoshitzky, Hyeryun Choe, and Michael Farzan. "Severe Acute Respiratory Syndrome Coronavirus Entry as a Target of Antiviral Therapies." Antiviral Therapy 12, no. 4_part_2 (January 1, 2005): 639–50. http://dx.doi.org/10.1177/135965350701200s05.1.

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The identification in 2003 of a coronavirus as the aetiological agent of severe acute respiratory syndrome (SARS) intensified efforts to understand the biology of corona-viruses in general and SARS coronavirus (SARS-CoV) in particular. Rapid progress was made in describing the SARS-CoV genome, evolution and lifecycle. Identification of angiotensin-converting enzyme 2 (ACE2) as an obligate cellular receptor for SARS-CoV contributed to understanding of the SARS-CoV entry process, and helped to characterize two targets of antiviral therapeutics: the SARS-CoV spike protein and ACE2. Here we describe the role of these proteins in SARS-CoV replication and potential therapeutic strategies aimed at preventing entry of SARS-CoV into target cells.

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Wang, Chi Chiu, Frank W. Pun, Bonnie Hei Man Liu, Yuezhen Lin, Feng Ren, and Alex Zhavoronkov. "#296 : Identification and Validation of Two Novel Therapeutic Targets for Endometriosis with Artificial Intelligence (AI)." Fertility & Reproduction 05, no. 04 (December 2023): 645. http://dx.doi.org/10.1142/s2661318223743709.

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Background and Aims: It is urgent need to develop new-effective and well-tolerable medical treatment for endometriosis, but normal drug development is tedious, costly and time-consuming. Artificial intelligence (AI) is a powerful tool to drive discovery of novel druggable targets. Here we aim to use AI to identify novel therapeutic targets for endometriosis treatment. Method: Targets associated with endometriosis were prioritized by PandaOmics (a well-established AI-driven target identification platform). Expression levels of druggable targets were tested in human endometriotic lesions. Functional characterizations of the targets were performed by in-vitro and in-vivo endometriosis models. Viability, proliferation and apoptosis were examined. Results: Analysis of 11 public endometriosis bulk transcriptomics databases revealed 2 lists of high confidence and novel druggable targets. Tow novel targets ENDO01 and ENDO02 were selected based on ranking in PandaOmics, consistency of significant dysregulated expression across comparisons, as well as literature evidence relevant to disease-driving mechanisms. Differential expressions were confirmed in human endometriosis tissues. siRNA targeting ENDO01 and ENDO02 significantly reduced cell viability and proliferation, as well as enhanced apoptosis in endometriotic cells in-vitro; and significantly decreased lesion volume and weight with reduced proliferative and enhanced apoptosis in-vivo. Conclusion: Two novel targets for endometriosis were identified with AI and validated by in-vitro and in-vivo experiments within a short period. The study demonstrated how AI could speed up the novel target discovery process from years to months. For diseases remaining incurable or with high morbidity, the application of AI in target discovery could be a new therapeutic regimen that benefits patients.

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Xu, Wenjing, Natalie R. Harris, and Kathleen M. Caron. "Lymphatic Vasculature: An Emerging Therapeutic Target and Drug Delivery Route." Annual Review of Medicine 72, no. 1 (January 27, 2021): 167–82. http://dx.doi.org/10.1146/annurev-med-051419-114417.

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The lymphatic system has received increasing scientific and clinical attention because a wide variety of diseases are linked to lymphatic pathologies and because the lymphatic system serves as an ideal conduit for drug delivery. Lymphatic vessels exert heterogeneous roles in different organs and vascular beds, and consequently, their dysfunction leads to distinct organ-specific outcomes. Although studies in animal model systems have led to the identification of crucial lymphatic genes with potential therapeutic benefit, effective lymphatic-targeted therapeutics are currently lacking for human lymphatic pathological conditions. Here, we focus on the therapeutic roles of lymphatic vessels in diseases and summarize the promising therapeutic targets for modulating lymphangiogenesis or lymphatic function in preclinical or clinical settings. We also discuss considerations for drug delivery or targeting of lymphatic vessels for treatment of lymphatic-related diseases. The lymphatic vasculature is rapidly emerging as a critical system for targeted modulation of its function and as a vehicle for innovative drug delivery.

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Lin, Ping, Lingqiang Meng, and Lei Lyu. "Identification of CeRNA Regulatory Networks in Atrial Fibrillation Using Nanodelivery." Evidence-Based Complementary and Alternative Medicine 2022 (September 29, 2022): 1–9. http://dx.doi.org/10.1155/2022/1046905.

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The initiation and maintenance of AF is a complex biological process that is the ultimate manifestation of many cardiovascular diseases. And the pathogenesis of atrial fibrillation (AF) is unclear. Therefore, this study aimed to find the potential competing endogenous RNAs (ceRNAs) network and molecular dysregulation mechanism associated with AF. GSE135445, GSE2240, and GSE68475 were obtained from the Gene Expression Omnibus (GEO). Differential analysis was utilized to identify the differentially expressed mRNAs, miRNAs, and lncRNAs between AF and sinus rhythms (SR). AF-associated mRNAs and nanomaterials were screened and their biological functions and KEGG signaling pathways were identified. Nanomaterials for targeted delivery are uniquely capable of localizing the delivery of therapeutics and diagnostics to diseased tissues. The target mRNAs and target lncRNAs of differentially expressed miRNAs were identified using TargetScan and LncBase databases. Finally, we constructed the ceRNAs network and its potential molecular regulatory mechanism. We obtained 643 AF-associated mRNAs. They were significantly involved in focal adhesion and the PI3K-Akt signaling pathway. Among the 16 differentially expressed miRNAs identified, 31 differentially expressed target mRNAs, as well as 5 differentially expressed target lncRNAs were identified. Among them, we obtained 2 ceRNAs networks (hsa-miR-125a-5p and hsa-let-7a-3p). The aberrant expression of network target genes in AF mainly activated the HIF-1 signaling pathway. We speculated that the interaction pairs of miR-125a-5p and let-7a-3p with target mRNAs and target lncRNAs may be involved in AF. Our findings have a positive influence on investigating the pathogenesis of AF and identifying potential therapeutic targets.

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Sacre, Sandra M., Evangelos Andreakos, Peter Taylor, Marc Feldmann, and Brian M. Foxwell. "Molecular therapeutic targets in rheumatoid arthritis." Expert Reviews in Molecular Medicine 7, no. 16 (August 24, 2005): 1–20. http://dx.doi.org/10.1017/s1462399405009488.

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In an attempt to combat the pain and damage generated by rheumatoid arthritis (RA), new drugs are being developed to target molecular aspects of the disease process. Recently, a major development has been the use of biologicals (antibodies and soluble receptors) that neutralise the activity of tumour necrosis factor α (TNF-α) and interleukin 1 (IL-1), both of which are involved in disease progression. An increase in our understanding of cell and molecular biology has resulted in the identification and investigation of potential new targets, and also the refinement and improvement of current therapeutic modalities. This review describes therapies that are approved, in clinical trials or under pre-clinical investigation at the laboratory level, particularly focusing on cytokines, although other therapeutic targets of interest are mentioned.

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Zhu, Yanchen, Yahui Wang, Zhaorui Cui, Fani Liu, and Jiqiang Hu. "Identification of pleiotropic and specific therapeutic targets for cardio-cerebral diseases: A large-scale proteome-wide mendelian randomization and colocalization study." PLOS ONE 19, no. 5 (May 31, 2024): e0300500. http://dx.doi.org/10.1371/journal.pone.0300500.

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Background The cardiac-brain connection has been identified as the basis for multiple cardio-cerebral diseases. However, effective therapeutic targets for these diseases are still limited. Therefore, this study aimed to identify pleiotropic and specific therapeutic targets for cardio-cerebral diseases using Mendelian randomization (MR) and colocalization analyses. Methods This study included two large protein quantitative trait loci studies with over 4,000 plasma proteins were included in the discovery and replication cohorts, respectively. We initially used MR to estimate the associations between protein and 20 cardio-cerebral diseases. Subsequently, Colocalization analysis was employed to enhance the credibility of the results. Protein target prioritization was based solely on including highly robust significant results from both the discovery and replication phases. Lastly, the Drug-Gene Interaction Database was utilized to investigate protein-gene-drug interactions further. Results A total of 46 target proteins for cardio-cerebral diseases were identified as robust in the discovery and replication phases by MR, comprising 7 pleiotropic therapeutic proteins and 39 specific target proteins. Followed by colocalization analysis and prioritization of evidence grades for target protein, 6 of these protein-disease pairs have achieved the highly recommended level. For instance, the PILRA protein presents a pleiotropic effect on sick sinus syndrome and Alzheimer’s disease, whereas GRN exerts specific effects on the latter. APOL3, LRP4, and F11, on the other hand, have specific effects on cardiomyopathy and ischemic stroke, respectively. Conclusions This study successfully identified important therapeutic targets for cardio-cerebral diseases, which benefits the development of preventive or therapeutic drugs.

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Huang, Chien-Jung, Lily Hui-Ching Wang, and Yu-Chao Wang. "Identification of Therapeutic Targets for the Selective Killing of HBV-Positive Hepatocytes." Journal of Personalized Medicine 11, no. 7 (July 10, 2021): 649. http://dx.doi.org/10.3390/jpm11070649.

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The hepatitis B virus (HBV) infection is a major risk factor for cirrhosis and hepatocellular carcinoma. Most infected individuals become lifelong carriers of HBV as the drugs currently used to treat the patients can only control the disease, thereby achieving functional cure (loss of the hepatitis B surface antigen) but not complete cure (elimination of infected hepatocytes). Therefore, we aimed to identify the target genes for the selective killing of HBV-positive hepatocytes to develop a novel therapy for the treatment of HBV infection. Our strategy was to recognize the conditionally essential genes that are essential for the survival of HBV-positive hepatocytes, but non-essential for the HBV-negative hepatocytes. Using microarray gene expression data curated from the Gene Expression Omnibus database and the known essential genes from the Online GEne Essentiality database, we used two approaches, comprising the random walk with restart algorithm and the support vector machine approach, to determine the potential targets for the selective killing of HBV-positive hepatocytes. The final candidate genes list obtained using these two approaches consisted of 36 target genes, which may be conditionally essential for the cell survival of HBV-positive hepatocytes; however, this requires further experimental validation. Therefore, the genes identified in this study can be used as potential drug targets to develop novel therapeutic strategies for the treatment of HBV, and may ultimately help in achieving the elusive goal of a complete cure for hepatitis B.

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Goldenberg, Seth J., Jeffrey G. Marblestone, Michael R. Mattern, and Benjamin Nicholson. "Strategies for the identification of ubiquitin ligase inhibitors." Biochemical Society Transactions 38, no. 1 (January 19, 2010): 132–36. http://dx.doi.org/10.1042/bst0380132.

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Dysregulation of the UPS (ubiquitin–proteasome system) has been implicated in a wide range of pathologies including cancer, neurodegeneration and viral infection. Inhibiting the proteasome has been shown to be an effective therapeutic strategy in humans; however, toxicity with this target remains high. E3s (Ub–protein ligases) represent an alternative attractive therapeutic target in the UPS. In this paper, we will discuss current platforms that report on E3 ligase activity and can detect E3 inhibitors, and underline the advantages and disadvantages of each approach.

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Fukusumi, Yoshiyasu. "Therapeutic target for nephrotic syndrome: Identification of novel slit diaphragm associated molecules." World Journal of Nephrology 3, no. 3 (2014): 77. http://dx.doi.org/10.5527/wjn.v3.i3.77.

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Affatato, Roberta, Laura Carrassa, Rosaria Chilà, Monica Lupi, Valentina Restelli, and Giovanna Damia. "Identification of PLK1 as a New Therapeutic Target in Mucinous Ovarian Carcinoma." Cancers 12, no. 3 (March 13, 2020): 672. http://dx.doi.org/10.3390/cancers12030672.

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Mucinous epithelial ovarian cancer (mEOC) is a rare subset of epithelial ovarian cancer. When diagnosed at a late stage, its prognosis is very poor, as it is quite chemo-resistant. To find new therapeutic options for mEOC, we performed high-throughput screening using a siRNA library directed against human protein kinases in a mEOC cell line, and polo-like kinase1 (PLK1) was identified as the kinase whose downregulation interfered with cell proliferation. Both PLK1 siRNA and two specific PLK1 inhibitors (onvansertib and volasertib) were able to inhibit cell growth, induce apoptosis and block cells in the G2/M phase of the cell cycle. We evaluated, in vitro, the combinations of PLK1 inhibitors and different chemotherapeutic drugs currently used in the treatment of mEOC, and we observed a synergistic effect of PLK1 inhibitors and antimitotic drugs. When translated into an in vivo xenograft model, the combination of onvansertib and paclitaxel resulted in stronger tumor regressions and in a longer mice survival than the single treatments. These effects were associated with a higher induction of mitotic block and induction of apoptosis, similarly to what was observed in vitro. These data suggest that the combination onvansertib/paclitaxel could represent a new active therapeutic option in mEOC.

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Zhang, Jie, De-pei Yin, Yan Zhang, Jia-nan Zhang, Yan Yang, Zhi-qing Zhang, Li Zhou, Yan Lv, Hai-wei Huang, and Cong Cao. "Identification of Gαi3 as a novel molecular therapeutic target of cervical cancer." International Journal of Biological Sciences 18, no. 15 (2022): 5667–80. http://dx.doi.org/10.7150/ijbs.77126.

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Lin, Dong, Xin Dong, Kendric Wang, Alexander W. Wyatt, Francesco Crea, Hui Xue, Yuwei Wang, et al. "Identification of DEK as a potential therapeutic target for neuroendocrine prostate cancer." Oncotarget 6, no. 3 (December 11, 2014): 1806–20. http://dx.doi.org/10.18632/oncotarget.2809.

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Huang, Minmin, Xinlei Qin, Yuwei Wang, and Furong Mao. "Identification of AK4 as a novel therapeutic target for serous ovarian cancer." Oncology Letters 20, no. 6 (October 8, 2020): 1. http://dx.doi.org/10.3892/ol.2020.12209.

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Bai, Xiao-Zhi, Jia-Qi Liu, Long-Long Yang, Lei Fan, Ting He, Lin-Lin Su, Ji-Hong Shi, Chao-Wu Tang, Zhao Zheng, and Da-Hai Hu. "Identification of sirtuin 1 as a promising therapeutic target for hypertrophic scars." British Journal of Pharmacology 173, no. 10 (March 23, 2016): 1589–601. http://dx.doi.org/10.1111/bph.13460.

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Glenisson, M., S. Vacher, C. Callens, A. Susini, G. Cizeron-Clairac, R. Le Scodan, D. Meseure, et al. "Identification of New Candidate Therapeutic Target Genes in Triple-Negative Breast Cancer." Genes & Cancer 3, no. 1 (January 1, 2012): 63–70. http://dx.doi.org/10.1177/1947601912449832.

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Madhunapantula, SubbaRao V., Arati Sharma, Raghavendra Gowda, and Gavin P. Robertson. "Identification of glycogen synthase kinase 3α as a therapeutic target in melanoma." Pigment Cell & Melanoma Research 26, no. 6 (September 19, 2013): 886–99. http://dx.doi.org/10.1111/pcmr.12156.

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