This research project investigates the interactions of staurosporine, a potent kinase inhibitor, with 11 ligands, highlighting its role in drug design and bioinformatics. Focusing on the selectivity and promiscuity of staurosporine in binding to protein kinases, the study employs the MANORAA database for data extraction. A Python script was developed to automate the retrieval and organisation of data, particularly targeting ligands with known affinity numbers. This method efficiently structures complex biochemical information into a comprehensible format. The research culminated in the creation of a website that presents detailed data on staurosporine’s molecular interactions and binding affinities. This website can serve as a valuable tool for researchers, offering insights into the drug's mechanism of action and its implications in therapeutic applications. The study methods included Python scripting for data handling and API integration for efficient data extraction, emphasising the importance of computational tools in bioinformatics. The findings reveal significant insights into the binding dynamics of staurosporine, identifying conserved and variable regions in kinase binding pockets that influence drug efficacy. These results contribute to a deeper understanding of staurosporine's broad spectrum of kinase inhibition and provide a model for future research in drug-protein interaction analysis. This project underscores the significance of accessible data presentation in bioinformatics, facilitating advanced research and development in drug design.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:his-23635 |
| Date | January 2023 |
| Creators | Guszpit, Emilia |
| Publisher | Högskolan i Skövde, Institutionen för biovetenskap |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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