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Journal articles on the topic 'Therapeutic target identification'

Author: Grafiati

Published: 16 November 2024

Last updated: 25 July 2025

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1

Koscielny, Gautier, Peter An, Denise Carvalho-Silva, et al. "Open Targets: a platform for therapeutic target identification and validation." Nucleic Acids Research 45, no. D1 (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 (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 (2023): 75. http://dx.doi.org/10.1093/bfgp/elac058.

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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 (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 s

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Keerthana N and Koteeswaran K. "Target identification and validation in research." World Journal of Biology Pharmacy and Health Sciences 17, no. 3 (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, incre

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Keerthana, N., and K. Koteeswaran. "Target identification and validation in research." World Journal of Biology Pharmacy and Health Sciences 17, no. 3 (2024): 107–17. https://doi.org/10.5281/zenodo.11351494.

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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, incre

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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 (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, wit

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Hu, Yang, Yinteng Wu, Fu Gan, et al. "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 identifie

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

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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 (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 n

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11

Lin, Chunsheng, Qianqian Tian, Sifan Guo, et al. "Metabolomics for Clinical Biomarker Discovery and Therapeutic Target Identification." Molecules 29, no. 10 (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 pathologic

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12

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 behav

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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 (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 employe

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14

Lan, Ming-Ying, Chi-Long Chen, Kuan-Ting Lin, et al. "From NPC Therapeutic Target Identification to Potential Treatment Strategy." Molecular Cancer Therapeutics 9, no. 9 (2010): 2511–23. http://dx.doi.org/10.1158/1535-7163.mct-09-0966.

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15

Frame, Jenna, Xiaoqian Zhang, James Jin, et al. "RenMice™ HiTS platform enables identification of novel therapeutic antibodies." Journal of Immunology 208, no. 1_Supplement (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 chromo

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Abdelmoez, Alshaimaa, Débora Coraça-Huber, Gudrun C. Thurner, et al. "Screening and identification of molecular targets for cancer therapy." Cancer Letters 387 (January 1, 2017): 3–9. https://doi.org/10.1016/j.canlet.2016.03.002.

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In recent decades, targeted therapeutics have significantly improved therapy results in patients with malignant tumors of different origins. However, malignant diseases characterized by aggressiveness and increased capacity for metastatic spread still require basic researchers and clinicians to direct enormous efforts toward the development of novel therapeutic targets. Potential targets should be selected with the clinical endpoint in view; targeted therapeutics can be developed: for use in combination with currently existing therapeutic approaches in order to improve their efficacy; to overc

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17

Ravi, V., S. Kim, D. Dim, et al. "Identification of therapeutic targets in angiosarcoma." Journal of Clinical Oncology 25, no. 18_suppl (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 fo

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18

Tie, Yan, Jihan Liu, Yushan Wu, et al. "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 (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.

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19

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 (2010): 57–67. http://dx.doi.org/10.1038/nrd3010.

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20

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

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21

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

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22

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

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23

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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24

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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26

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

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27

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 (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

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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 (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 descri

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Panda, Chinmaya, and Rajani Kanta Mahapatra. "Identification of novel therapeutic candidates inCryptosporidium parvum: anin silicoapproach." Parasitology 145, no. 14 (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 wa

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Fernández-Ortega, Celia, Anna Ramírez, Dionne Casillas, et al. "Identification of Vimentin as a Potential Therapeutic Target against HIV Infection." Viruses 8, no. 6 (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 (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 exp

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D'Arcy, Colleen E., Sandra J. Feeney, Catriona A. McLean, et al. "Identification of FHL1 as a therapeutic target for Duchenne muscular dystrophy." Human Molecular Genetics 23, no. 3 (2013): 618–36. http://dx.doi.org/10.1093/hmg/ddt449.

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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 (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 (2013): 1275–85. http://dx.doi.org/10.1517/14728222.2013.829455.

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Hurtz, Christian, Huimin Geng, Erica Ballabio, et al. "Identification Of BCL6 As a Therapeutic Target In MLL-Rearranged ALL." Blood 122, no. 21 (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 analyze

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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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37

Vilasboas-Campos, D., J. Lopes, B. Ferreira-Lomba, et al. "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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38

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 (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. Functi

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Adil Abdelrahim Mohammed Yousif. "CRISPR-Cas9 in Drug Discovery: Revolutionizing Target Identification and Validation." Journal of Biomedicine and Biochemistry 3, no. 4 (2024): 31–38. https://doi.org/10.57238/jbb.2024.7432.1131.

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In recent years, advancements in molecular biology have heralded a trans- formative era in drug discovery, with CRISPR-Cas9 emerging as a pivotal tool for enhancing the precision of target identification and validation. Originally derived from bacterial immune systems, this genome-editing technology allows for highly specific alterations in DNA sequences, thereby facilitating the investigation of gene functions associated with health and disease. Its capability for genome-wide screening has enabled researchers to systematically identify potential therapeutic targets, streamlining the drug deve

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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 (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

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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 na

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Di Stefano, Miriana, Lisa Piazza, Clarissa Poles, et al. "KinasePred: A Computational Tool for Small-Molecule Kinase Target Prediction." International Journal of Molecular Sciences 26, no. 5 (2025): 2157. https://doi.org/10.3390/ijms26052157.

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Protein kinases are key regulators of cellular processes and critical therapeutic targets in diseases like cancer, making them a focal point for drug discovery efforts. In this context, we developed KinasePred, a robust computational workflow that combines machine learning and explainable artificial intelligence to predict the kinase activity of small molecules while providing detailed insights into the structural features driving ligand-target interactions. Our kinase-family predictive tool demonstrated significant performance, validated through virtual screening, where it successfully identi

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Ren, Jialin, and Min Wu. "Identification of Novel Therapeutic Targets for MAFLD Based on Bioinformatics Analysis Combined with Mendelian Randomization." International Journal of Molecular Sciences 26, no. 7 (2025): 3166. https://doi.org/10.3390/ijms26073166.

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Metabolic-associated fatty liver disease (MAFLD) is a chronic liver condition with limited therapeutic options. To identify novel drug targets, we integrated bioinformatics, Mendelian randomization (MR), and colocalization analyses. Using the Gene Expression Omnibus (GEO) database, we identified differentially expressed genes and constructed protein–protein interaction (PPI) networks, pinpointing 10 hub genes. MR and colocalization analyses revealed that Ubiquitin-like with PHD and ring finger domains 1 (UHRF1) is causally associated with MAFLD and driven by the same causal variant locus, sugg

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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 (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 th

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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 (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 bet

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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 (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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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 (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 essent

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Ozen, Mustafa, Effat S. Emamian, and Ali Abdi. "From Data to Knowledge: A Mini-Review on Molecular Network Modeling and Analysis for Therapeutic Target Discovery." Archives of Pharmacology and Therapeutics 5, no. 1 (2023): 36–43. http://dx.doi.org/10.33696/pharmacol.4.043.

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Successful drug development is a risky and lengthy process that can take over ten years and consume billions of dollars. Target discovery is a critical stage of drug development for the identification of key molecules and pathways that can be targeted by novel therapeutics to find more effective treatments. Due to the rapid development in artificial intelligence and machine learning techniques over the past decade, computational approaches have now emerged as powerful tools to unravel complex interactions within biological systems to identify novel therapeutic targets. In particular, modeling

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Tripathi, Anurag, and Uma Kumari. "Comparative Analysis and Drug Target Identification of Human Kidney Cancer." International Journal for Research in Applied Science and Engineering Technology 11, no. 9 (2023): 924–29. http://dx.doi.org/10.22214/ijraset.2023.55777.

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Abstract: Kidney cancer, particularly renal cell carcinoma (RCC), is a significant global health concern characterized by its high morbidity and mortality rates. In this study, we employ a multifaceted approach to gain insights into the molecular mechanisms underlying kidney cancer and to identify potential drug targets for therapeutic intervention. To achieve this, we conducted a comprehensive comparative analysis of gene expression profiles in normal and cancerous kidney tissues, utilizing tools such as BLAST and gene analysis from the COSMIC database. This analysis allowed us to identify ke

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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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