Verify knowledge of a pathway (2) manage the immense complexity of hundreds or potentially thousands of cellular componentsĪnd interactions and (3) reveal emergent properties and unanticipated consequences of different pathway configurations. Such models promise to transform biological research by providing a framework to (1) systematically interrogate and experimentally A variety of modeling environments haveīeen developed to simulate biochemical reactions and gene transcription kinetics ( Endy and Brent 2001), cellular physiology ( Loew and Schaff 2001), and metabolic control ( Mendes 1997). Interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.Ĭomputer-aided models of biological networks are a cornerstone of systems biology. SeveralĬase studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in geneĮxpression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional The Core is extensible throughĪ straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Cytoscape's software Core providesīasic functionality to layout and query the network to visually integrate the network with expression profiles, phenotypes,Īnd other molecular states and to link the network to databases of functional annotations. Although applicable to any system of molecular componentsĪnd interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA,Īnd genetic interactions that are increasingly available for humans and model organisms. fumigatus’s metabolism to reveal dapsone, sulfamethazine, lovastatin and 3-bromopyruvic acid as potential drugs for the treatment of Aspergillosis.Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expressionĭata and other molecular states into a unified conceptual framework. Our study provides a deeper insight into the mechanisms of A. Based on docking scores and MM-GBSA results, molecular simulations were carried out for 1AJ2-dapsone, 1DIS-sulfamethazine, 1T02-lovastatin and 70YL-3-bromopyruvic acid complexes, which validated our findings. Further, molecular docking and MM-GBSA analysis were performed with ligands chosen from DrugBank, and PubChem, and validated by experimental evidence and existing literature based on results from kinetic modeling and PPI network analysis. Based on the findings, dihydropteroate-synthase, dihydrofolate-reductase, 4-amino-4-deoxychorismate synthase, HMG-CoA-reductase, PG-isomerase and hexokinase could act as potential drug targets. For further analysis of the interaction of drug targets identified, a protein–protein interaction (PPI) network was built, and hub nodes were identified using the Cytohubba package from Cytoscape. While focusing on the folate biosynthesis, ergosterol biosynthesis and glycolytic pathway sensitivity, time-course and steady-state analysis were performed to find the proteins/enzymes that are essential in the pathway and can be considered as potential drug targets. Our work focused on developing kinetic models of critical pathways crucial for the survival of A. To understand the pathogenicity of any organism, it is critical to identify the significant metabolic pathways that are involved. The diagnosis and treatment are difficult due to the diversity of individuals and risk factors and still pose a challenge for medical professionals. Aspergillosis is a major causative factor for morbidity in those with impaired immune systems, often caused by Aspergillus fumigatus.
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