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Computational Biology and Bioinformatics in Anti-SARS-CoV-2 Drug Development
Published in Debmalya Barh, Kenneth Lundstrom, COVID-19, 2022
Drug repurposing or repositioning represents one of the more efficient approaches for finding potential therapeutics via identification of new applications for existing drugs at a lower cost and in a shorter time [129–139]. In applications to SARS-CoV-2, computational drug-repositioning approaches can be grouped into network-based models, structure-based approaches, signature- based approaches, molecular docking, genome-wide association studies (GWAS), and AI approaches [130, 140]. In signature-based drug repositioning, high-throughput omics data (transcriptomic, proteomic, or metabolomic), as well as molecular structures, and adverse effect profiles are used to compare the pattern of gene expression profiles of a drug against gene expression profiles of another drug (i.e., drug–drug comparison), disease (i.e., drug-disease comparison), or clinical phenotype [141]. In molecular docking, which is an important component of the structure-based drug repurposing (SBDR) techniques [142], unknown interactions between receptor target and leads are discovered by screening of compound libraries against targets to discover candidates for drug repurposing processes [143]. The network-based and pathway-based drug repurposing relies on the construction of biological networks by using different data types, such as disease pathology, gene expression patterns, and protein interactions [144]. The differences in genetic material related to common diseases that can be found by GWAS generate an important knowledge that can give rise to repurposing of drugs [145].
Will Systems Biology Transform Clinical Decision Support?
Published in Paul Cerrato, John Halamka, Reinventing Clinical Decision Support, 2020
The P100 Wellness Project did not limit itself to collecting health data; it also provided participants with health coaching over the 9-month period. The goal was to recommend lifestyle changes that would alter biomarkers that have been linked to disease. The program reported 4 significant findings: First, thousands of statistically significant inter-omic correlations were computed using personal, dense, dynamic data clouds to identify many associations that could be followed up with perturbation experiments. Second, we partitioned the correlations into data communities, which placed biomarkers in context within biological networks…. Third, we identified molecular correlates of polygenic disease risk scores computed from published GWAS data, revealing possible ways in which genetic predisposition is manifested through analyte changes. Finally, on average participants significantly improved their clinical biomarkers … during the course of this pilot study (e.g., type 2 diabetes and cardiovascular risk factors).24
Gene Expression Profiling to Detect New Treatment Targets in Leukemia and Lymphoma: A Future Perspective
Published in Gertjan J. L. Kaspers, Bertrand Coiffier, Michael C. Heinrich, Elihu Estey, Innovative Leukemia and Lymphoma Therapy, 2019
Torsten Haferlach, Wolfgang Kern, Alexander Kohlmann
The identification of diagnostic, prognostic, or therapeutic markers in leukemia and lymphoma following microarray experiments and their biostatistical read outs have to then focus on the discovery of important pathways in these tumors. Several programs exist in order to identify pathways involved. These include Pathway Assist (http://www.ariadnegenomics.com/products/pathway.html), DAVID (http://appsl.niaid.nih.gov/david/), and Ingenuity (http://www.ingenuity.com/). As one example, Ingenuity enables researchers to model, analyze, and understand complex biological systems foundational to human health and disease. This includes pathways analysis software and knowledge databases for biologists and biostatisticians and enterprise knowledge management infrastructure. Today, Ingenuity is a useful knowledge base of biological networks with curated relationships between proteins, genes, complexes, cells, tissues, drugs, and diseases.
Rewiring of miRNA-mRNA bipartite co-expression network as a novel way to understand the prostate cancer related players
Published in Systems Biology in Reproductive Medicine, 2023
Mohammad Mehdi Naghizadeh, Behnaz Bakhshandeh, Farshid Noorbakhsh, Marjan Yaghmaie, Ali Masoudi-Nejad
Biological networks are dynamic ones and with high variety because of disturbances (noises) that come from different sources like the environment. In systems biology, various methods and algorithms (Mousavian, Diaz, et al. 2016; Mousavian, Kavousi, et al. 2016) are proposed to evaluate the macromolecule interactions (Lanjanian et al. 2021), detected novel biomarkers for early detection of cancers (Kouhsar et al. 2019) and repurpose the known drugs for different treatments (Kouhsar et al. 2019; Masoudi-Sobhanzadeh et al. 2019b, 2019a, 2020). So, the networks are repeatedly rewired to be compatible with the stresses (Mitra et al. 2013). Rewiring is defined as the changes in network topology from one state to another such as normal to cancer states (Barabasi et al. 2011). In other words, different molecules can continue to work by finding new pathways or molecules to play various roles (Ideker and Krogan 2012). For example, experiments have shown that different regulatory components may be activated or deactivated under different conditions and represent highly dynamic entities contrary to their static appearance (Creixell et al. 2012).
LCK, FOXC1 and hsa-miR-146a-5p as potential immune effector molecules associated with rheumatoid arthritis
Published in Biomarkers, 2023
Xuemeng Chen, Li Xie, Yi Jiang, Ronghua Zhang, Wei Wu
Genes causing complex diseases always participate in common biological processes in various kinds of biological networks (Zhang et al. 2020). Co-expression networks could provide information of co-regulation genes that function in the regulation processes and relationships of transcriptome components disturbed, and enrichment analysis of DEGs is necessary (Kotni et al. 2016, Kliebenstein 2020). We constructed a PPI network encoded by DEGs and identified the subsequent top 10 closely related genes: LCK, GZMA, GZMB, CD2, LAG3, IL-15, TNFRSF4, CD247, CCR5 and CCR7. These genes are key nodes for the construction a PPI network and play a distinct role in the pathogenesis of RA. Lymphocyte-specific protein tyrosine kinase (LCK), an Src family member, is a lymphoid-specific cytosolic protein tyrosine kinase that is essential for activating T cell receptor signalling and T cells (Isakov and Biesinger 2000).
Multi-target mechanism of Tripteryguim wilfordii Hook for treatment of ankylosing spondylitis based on network pharmacology and molecular docking
Published in Annals of Medicine, 2021
Jing Zhang, Yiting Zhou, Zhiyuan Ma
Tripterygium wilfordii Hook (TWH), a woody vine of the genus Tripterygium, is a traditional Chinese medicine with anti-inflammatory, anti-rheumatic and immunomodulatory effects. Therefore, it is widely used in a variety of autoimmune diseases, including rheumatic diseases, Crohn’s disease, systemic lupus erythematosus, and Behcet’s disease. Triptolide, a principal ingredient in TWH, could reduce collagen formation, alkaline phosphatase activity and calcium deposition in vitro, therefore suggests a potential therapeutic agent for the treatment of AS [7]. Additionally, comprising of triptolides, tripterygium glycosides tablet is proved to have beneficial effects in improving the clinical features and regulating serum biomarkers of patients with AS [8]. However, the mechanism underlying the therapeutic effects of TWH on AS is unknown. Based on public databases and publicly available data, network pharmacology is a novel, promising, and cost-effective approach in discovering bioactive ingredients, predicting drug action targets, and analyzing drug action mechanisms from the perspective of biological network balance [9]. Besides, compared with experimental pharmacology methods, network pharmacology emphasizes multi-channel regulation of signalling pathways, therefore especially suitable for the explanation of the mechanism of traditional Chinese medicine with multiple chemical components and molecular targets [10].