1
|
Wang H, Julien O. CaspSites: A Database and Web Application for Experimentally Observed Human Caspase Substrates Using N-Terminomics. J Proteome Res 2023; 22:454-461. [PMID: 36696595 DOI: 10.1021/acs.jproteome.2c00620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
CaspSites is a free-to-use database and web application for experimentally observed human caspase substrates using N-terminomics. It can be accessed and used by all users at the web URL www.caspsites.org. CaspSites stores cleavage site information identified for human caspases 1-9 in lysates and apoptotic cells, collected from their corresponding published studies. The database can be queried, viewed, and exported using the search page of the web application. The main parameters offered are protein substrate, cleavage site (P4-P4') residues, and individual caspase data sets, which can be connected using OR, AND, or NOT logical operators for custom user-built queries. CaspSites will be regularly updated with new experimental findings for understudied caspases, providing researchers insight into the distinctive roles human caspases play in cellular processes by identifying their target proteins in relation to each other.
Collapse
Affiliation(s)
- Henry Wang
- Department of Biochemistry, University of Alberta, Edmonton, Alberta T6G2H7, Canada
| | - Olivier Julien
- Department of Biochemistry, University of Alberta, Edmonton, Alberta T6G2H7, Canada
| |
Collapse
|
2
|
Gadepalli VS, Kim H, Liu Y, Han T, Cheng L. XDeathDB: a visualization platform for cell death molecular interactions. Cell Death Dis 2021; 12:1156. [PMID: 34907160 PMCID: PMC8669630 DOI: 10.1038/s41419-021-04397-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 08/07/2021] [Accepted: 11/09/2021] [Indexed: 12/23/2022]
Abstract
Lots of cell death initiator and effector molecules, signalling pathways and subcellular sites have been identified as key mediators in both cell death processes in cancer. The XDeathDB visualization platform provides a comprehensive cell death and their crosstalk resource for deciphering the signaling network organization of interactions among different cell death modes associated with 1461 cancer types and COVID-19, with an aim to understand the molecular mechanisms of physiological cell death in disease and facilitate systems-oriented novel drug discovery in inducing cell deaths properly. Apoptosis, autosis, efferocytosis, ferroptosis, immunogenic cell death, intrinsic apoptosis, lysosomal cell death, mitotic cell death, mitochondrial permeability transition, necroptosis, parthanatos, and pyroptosis related to 12 cell deaths and their crosstalk can be observed systematically by the platform. Big data for cell death gene-disease associations, gene-cell death pathway associations, pathway-cell death mode associations, and cell death-cell death associations is collected by literature review articles and public database from iRefIndex, STRING, BioGRID, Reactom, Pathway's commons, DisGeNET, DrugBank, and Therapeutic Target Database (TTD). An interactive webtool, XDeathDB, is built by web applications with R-Shiny, JavaScript (JS) and Shiny Server Iso. With this platform, users can search specific interactions from vast interdependent networks that occur in the realm of cell death. A multilayer spectral graph clustering method that performs convex layer aggregation to identify crosstalk function among cell death modes for a specific cancer. 147 hallmark genes of cell death could be observed in detail in these networks. These potential druggable targets are displayed systematically and tailoring networks to visualize specified relations is available to fulfil user-specific needs. Users can access XDeathDB for free at https://pcm2019.shinyapps.io/XDeathDB/ .
Collapse
Affiliation(s)
- Venkat Sundar Gadepalli
- Research Information Technology, College of Medicine, Ohio State University, 1585 Neil Ave, Columbus, OH, 43210, USA
| | - Hangil Kim
- 1Department of Biomedical Informatics, The Ohio State University, Columbus, OH, 43210, USA
| | - Yueze Liu
- The Grainger College of Engineering, The University of Illinois-Urbana-Champaign, Urbana and Champaign, Champaign, IL, 61801, USA
| | - Tao Han
- 1Department of Biomedical Informatics, The Ohio State University, Columbus, OH, 43210, USA
| | - Lijun Cheng
- 1Department of Biomedical Informatics, The Ohio State University, Columbus, OH, 43210, USA.
| |
Collapse
|
3
|
Tang Y, Chen K, Wu X, Wei Z, Zhang SY, Song B, Zhang SW, Huang Y, Meng J. DRUM: Inference of Disease-Associated m 6A RNA Methylation Sites From a Multi-Layer Heterogeneous Network. Front Genet 2019; 10:266. [PMID: 31001320 PMCID: PMC6456716 DOI: 10.3389/fgene.2019.00266] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2018] [Accepted: 03/11/2019] [Indexed: 01/27/2023] Open
Abstract
Recent studies have revealed that the RNA N 6-methyladenosine (m6A) modification plays a critical role in a variety of biological processes and associated with multiple diseases including cancers. Till this day, transcriptome-wide m6A RNA methylation sites have been identified by high-throughput sequencing technique combined with computational methods, and the information is publicly available in a few bioinformatics databases; however, the association between individual m6A sites and various diseases are still largely unknown. There are yet computational approaches developed for investigating potential association between individual m6A sites and diseases, which represents a major challenge in the epitranscriptome analysis. Thus, to infer the disease-related m6A sites, we implemented a novel multi-layer heterogeneous network-based approach, which incorporates the associations among diseases, genes and m6A RNA methylation sites from gene expression, RNA methylation and disease similarities data with the Random Walk with Restart (RWR) algorithm. To evaluate the performance of the proposed approach, a ten-fold cross validation is performed, in which our approach achieved a reasonable good performance (overall AUC: 0.827, average AUC 0.867), higher than a hypergeometric test-based approach (overall AUC: 0.7333 and average AUC: 0.723) and a random predictor (overall AUC: 0.550 and average AUC: 0.486). Additionally, we show that a number of predicted cancer-associated m6A sites are supported by existing literatures, suggesting that the proposed approach can effectively uncover the underlying epitranscriptome circuits of disease mechanisms. An online database DRUM, which stands for disease-associated ribonucleic acid methylation, was built to support the query of disease-associated RNA m6A methylation sites, and is freely available at: www.xjtlu.edu.cn/biologicalsciences/drum.
Collapse
Affiliation(s)
- Yujiao Tang
- Department of Biological Sciences, Research Center for Precision Medicine, Xi'an Jiaotong-Liverpool University, Suzhou, China
- Institute of Integrative Biology, University of Liverpool, Liverpool, United Kingdom
| | - Kunqi Chen
- Department of Biological Sciences, Research Center for Precision Medicine, Xi'an Jiaotong-Liverpool University, Suzhou, China
- Institute of & Chronic Disease, University of Liverpool, Liverpool, United Kingdom
| | - Xiangyu Wu
- Department of Biological Sciences, Research Center for Precision Medicine, Xi'an Jiaotong-Liverpool University, Suzhou, China
- Institute of & Chronic Disease, University of Liverpool, Liverpool, United Kingdom
| | - Zhen Wei
- Department of Biological Sciences, Research Center for Precision Medicine, Xi'an Jiaotong-Liverpool University, Suzhou, China
- Institute of & Chronic Disease, University of Liverpool, Liverpool, United Kingdom
| | - Song-Yao Zhang
- Key Laboratory of Information Fusion Technology of Ministry of Education, School of Automation, Northwestern Polytechnical University, Xi'an, China
| | - Bowen Song
- Department of Biological Sciences, Research Center for Precision Medicine, Xi'an Jiaotong-Liverpool University, Suzhou, China
- Institute of & Chronic Disease, University of Liverpool, Liverpool, United Kingdom
| | - Shao-Wu Zhang
- Key Laboratory of Information Fusion Technology of Ministry of Education, School of Automation, Northwestern Polytechnical University, Xi'an, China
| | - Yufei Huang
- Department of Epidemiology and Biostatistics, University of Texas Health San Antonio, San Antonio, TX, United States
- Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX, United States
| | - Jia Meng
- Department of Biological Sciences, Research Center for Precision Medicine, Xi'an Jiaotong-Liverpool University, Suzhou, China
- Institute of & Chronic Disease, University of Liverpool, Liverpool, United Kingdom
| |
Collapse
|
4
|
Li JM, Huang LL, Liu F, Tang BS, Yan XX. Can brain impermeable BACE1 inhibitors serve as anti-CAA medicine? BMC Neurol 2017; 17:163. [PMID: 28841840 PMCID: PMC5574137 DOI: 10.1186/s12883-017-0942-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2017] [Accepted: 08/14/2017] [Indexed: 12/21/2022] Open
Abstract
Background Cerebral amyloid angiopathy (CAA) is characterized by the deposition of ß-amyloid peptides (Aß) in and surrounding the wall of microvasculature in the central nervous system, together with parenchymal amyloid plaques collectively referred to as cerebral amyloidosis, which occurs in the brain commonly among the elderly and more frequently in patients with Alzheimer’s disease (AD). CAA is associated with vascular injury and may cause devastating neurological outcomes. No therapeutic approach is available for this lesion to date. Main body ß-Secretase 1 (BACE1) is the enzyme initiating Aß production. Brain permeable BACE1 inhibitors targeting primarily at the parenchymal plaque pathology are currently evaluated in clinical trials. This article presents findings in support of a role of BACE1 elevation in the development of CAA, in addition to plaque pathogenesis. The rationale, feasibility, benefit and strategic issues for developing BACE1 inhibitors against CAA are discussed. Brain impermeable compounds are considered preferable as they might exhibit sufficient anti-CAA efficacy without causing significant neuronal/synaptic side effects. Conclusion Early pharmacological intervention to the pathogenesis of CAA is expected to provide significant protection for cerebral vascular health and hence brain health. Brain impermeable BACE1 inhibitors should be optimized and tested as potential anti-CAA therapeutics.
Collapse
Affiliation(s)
- Jian-Ming Li
- Department of Neurology & Key Laboratory of Hunan Province in Neurodegenerative Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China.,Neuroscience Research Center, Changsha Medical University, Changsha, Hunan, 410219, China
| | - Li-Ling Huang
- Department of Anatomy and Neurobiology, Central South University School of Basic Medical Science, Changsha, Hunan, 410013, China
| | - Fei Liu
- Department of Neurosurgery, The Third Xiangya Hospital, Central South University, Changsha, Hunan, 410013, China
| | - Bei-Sha Tang
- Department of Neurology & Key Laboratory of Hunan Province in Neurodegenerative Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
| | - Xiao-Xin Yan
- Department of Neurology & Key Laboratory of Hunan Province in Neurodegenerative Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China. .,Department of Anatomy and Neurobiology, Central South University School of Basic Medical Science, Changsha, Hunan, 410013, China.
| |
Collapse
|