Review
Biochemistry & Molecular Biology
Bingting Yu, Ruslan Mamedov, Gwenny M. Fuhler, Maikel P. Peppelenbosch
Summary: The liver plays a crucial role in maintaining biochemical balance, and diseases affecting the liver have a significant impact on human health. However, due to the complexity and uniqueness of hepatic kinase activities, there are challenges in studying them comprehensively. Nevertheless, current kinome profiling approaches show great promise for advancing research in this area.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Biochemical Research Methods
Laura J. Marholz, Joel D. Federspiel, Hyunsuk Suh, Mireia Fernandez Ocana
Summary: This study reports the development of a targeted mass spectrometry-based assay for monitoring various kinases and comparing interspecies variability. Results showed species-specific differences in the kinome of the spleen, especially within certain kinase families. The study also demonstrated the application of these methods in studying species-specific inhibitor profiles.
JOURNAL OF PROTEOME RESEARCH
(2021)
Article
Multidisciplinary Sciences
Chinmaya U. Joisa, Kevin A. Chen, Matthew E. Berginski, Brian T. Golitz, Madison R. Jenner, Gabriela Herrera Loeza, Jen Jen Yeh, Shawn M. Gomez
Summary: Protein kinase activity plays a central role in cellular information transfer and its dysfunction is a common driver of diseases, including cancer. The development of therapies targeting kinases has rapidly grown, making it important to understand the relationship between kinase inhibitor treatment and their effects on cellular phenotype. In this study, computational models were built using large-scale kinome profiling data sets, achieving high prediction accuracy. Well-characterized and understudied kinases that significantly affect cell responses were identified. Experimental validation was conducted, demonstrating that broad quantification of kinome inhibition state is highly predictive of downstream cellular phenotypes.
Article
Biochemistry & Molecular Biology
Emilie Logie, Claudina Perez Novo, Amber Driesen, Pieter Van Vlierberghe, Wim Vanden Berghe
Summary: Protein kinases play a crucial role in transducing cellular signals and orchestrating biological processes through phosphorylation of substrate proteins. Recent studies have shown their involvement in ferroptosis, an iron-dependent cell death linked to toxic lipid peroxidation. Different kinase signaling changes are induced by apoptotic and ferroptotic cell death, indicating that kinome profiling could be a valuable approach to identify sensitization modalities of novel anti-cancer agents.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Oncology
Federica Fabro, Nynke M. Kannegieter, Erik L. de Graaf, Karla Queiroz, Martine L. M. Lamfers, Anna Ressa, Sieger Leenstra
Summary: Glioblastoma is the most deadly brain cancer with poor response to treatment. In this study, 2D and 3D models were used to investigate the effects of small protein kinase inhibitors on patient-derived glioblastoma. The results showed inter-patient variability in drug response, with the ErbB signaling pathway playing a role. It was also observed that the choice of model influenced the analysis of kinases. A new resistance mechanism derived from imatinib treatment was identified in one sample.
FRONTIERS IN ONCOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Ruby Lieshout, Alessandra V. S. Faria, Maikel P. Peppelenbosch, Luc J. W. van der Laan, Monique M. A. Verstegen, Gwenny M. Fuhler
Summary: Kinome profiling is a feasible method to identify druggable targets for cholangiocarcinoma. Growth factor signaling and downstream effectors are more active in cholangiocarcinoma organoids, which could potentially provide targets for treatment. Screening of kinase inhibitors revealed several potential effective inhibitors and compounds with patient-specific efficacy. The sensitivity of kinase inhibitors correlated with the activity of their target kinases, signifying them as potential predictors of response. Furthermore, correlations were found between drug response and kinases not targeted directly by the drugs.
MOLECULAR MEDICINE
(2022)
Article
Multidisciplinary Sciences
Hyejin Park, Sujeong Hong, Myeonghun Lee, Sungil Kang, Rahul Brahma, Kwang-Hwi Cho, Jae-Min Shin
Summary: Researchers proposed the AiKPro model, which combines structure-validated multiple sequence alignments and molecular 3D conformer ensemble descriptors to predict kinase-ligand binding affinities. The deep learning model uses an attention-based mechanism to capture complex patterns in kinase-ligand interactions. Evaluation showed good performance and robustness, potentially facilitating the discovery of novel interactions and selective inhibitors.
SCIENTIFIC REPORTS
(2023)
Article
Multidisciplinary Sciences
Corvin Walter, Adinarayana Marada, Tamara Suhm, Ralf Ernsberger, Vera Muders, Cansu Kuecuekkoese, Pablo Sanchez-Martin, Zehan Hu, Abhishek Aich, Stefan Loroch, Fiorella Andrea Solari, Daniel Poveda-Huertes, Alexandra Schwierzok, Henrike Pommerening, Stanka Matic, Jan Brix, Albert Sickmann, Claudine Kraft, Joern Dengjel, Sven Dennerlein, Tilman Brummer, F. -Nora Voegtle, Chris Meisinger
Summary: The study shows that DYRK1A phosphorylates TOM70 to promote import of precursor proteins into mitochondria. Inhibition of DYRK1A impairs mitochondrial structure and function, leading to a decrease in metabolite carrier import capacity.
NATURE COMMUNICATIONS
(2021)
Article
Multidisciplinary Sciences
Carmen Oi Ning Leung, Yang Yang, Rainbow Wing Hei Leung, Karl Kam Hei So, Hai Jun Guo, Martina Mang Leng Lei, Gregory Kenneth Muliawan, Yuan Gao, Qian Qian Yu, Jing Ping Yun, Stephanie Ma, Qian Zhao, Terence Kin Wah Lee
Summary: The study reveals that CDK6 plays a crucial role in lenvatinib-resistant HCC by promoting the accumulation of liver cancer stem cells and activating the Wnt/beta-catenin signaling pathway. The combination of lenvatinib and palbociclib shows synergistic effects in inhibiting lenvatinib-resistant HCC and reshaping the tumor immune microenvironment.
NATURE COMMUNICATIONS
(2023)
Article
Chemistry, Multidisciplinary
Hirotomo Moriwaki, Shin Saito, Tomoya Matsumoto, Takayuki Serizawa, Ryo Kunimoto
Summary: In drug discovery, predicting activity and absorption, distribution, metabolism, excretion, and toxicity parameters is crucial. Recent research has focused on prediction methods using deep learning and non-deep learning approaches. This study compared and discussed the prediction results of activity using both methods on in-house assay data for hundreds of kinases. The multitask graph neural network (GNN) model outperformed the non-deep learning model and showed extrapolative validity. The findings suggest that ligand-based prediction methods can be used for activity prediction and drug design.
Review
Pharmacology & Pharmacy
Charu Chaudhry, Andrew Tebben, S. John Tokarski, Robert Borzilleri, J. William Pitts, Jonathan Lippy, Litao Zhang
Summary: Kinases, which account for 20% of the human genome, have been a major focus in pharmaceutical drug discovery for over three decades. Despite the challenges in identifying novel kinase inhibitors with good properties, the need for diverse and powerful tools in kinase drug discovery is evident in order to efficiently generate highly optimized kinase inhibitors.
DRUG DISCOVERY TODAY
(2021)
Review
Pharmacology & Pharmacy
Deep Rohan Chatterjee, Saumya Kapoor, Meenakshi Jain, Rudradip Das, Moumita Ghosh Chowdhury, Amit Shard
Summary: The development of proteolysis-targeting chimeras (PROTACs) has led to the discovery of drugs that specifically target undruggable proteins. Small molecule-based PROTACs that target intracellular pathways have entered clinical trials, and their combination with antibodies has shown potent effects in cancer treatment. This review discusses the recent milestones and challenges in this area of drug development, as well as the best path forward.
DRUG DISCOVERY TODAY
(2023)
Article
Chemistry, Medicinal
Chaowei Ren, Ning Sun, Haixia Liu, Ying Kong, Renhong Sun, Xing Qiu, Jinju Chen, Yan Li, Jianshui Zhang, Yuedong Zhou, Hui Zhong, Qianqian Yin, Xiaoling Song, Xiaobao Yang, Biao Jiang
Summary: Proteolysis-targeting chimera (PROTAC) technology in drug discovery has gained much attention, and SIAIS164018, a novel degrader designed from the perspective of clinical benefits, has shown promising results in degrading important oncoproteins, inhibiting cell migration and invasion, and reshuffling kinome ranking compared to its precursor Brigatinib.
JOURNAL OF MEDICINAL CHEMISTRY
(2021)
Article
Biochemistry & Molecular Biology
Xiaoya Ling, Zhigang Cao, Panpan Sun, Hua Zhang, Yaogui Sun, Jia Zhong, Wei Yin, Kuohai Fan, Xiaozhong Zheng, Hongquan Li, Na Sun
Summary: The study aimed to explore the anti-PRRSV targets of matrine in Marc-145 cells. The anti-PRRSV and anti-inflammatory activities of matrine were evaluated, and potential targets were predicted using activity-based protein profiling and network pharmacology. ACAT1, ALB, HMOX1, HSPA8, HSP90AB1, PARP1 and STAT1 were identified as potential targets, related to antiviral capacity and immunity.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Review
Biochemistry & Molecular Biology
Cassandra Kennedy, Katherine McPhie, Katrin Rittinger
Summary: The ubiquitin system offers a wealth of potential drug targets, but there is a lack of effective inhibitors for the proteins within this system. Fragment-based drug discovery (FBDD) provides a screening platform that combines structural biology and proteomics to discover inhibitors within the ubiquitin system. This mini review summarizes the current scope and new frontiers of FBDD in relation to ubiquitin-activating, ubiquitin-conjugating, ubiquitin ligase, and deubiquitinating enzymes.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2022)