Högskolan i Skövde

his.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Bioinformatics analysis on the drug design supporting systems
University of Skövde, School of Bioscience.
2023 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

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.

Place, publisher, year, edition, pages
2023. , p. 51
National Category
Bioinformatics and Computational Biology
Identifiers
URN: urn:nbn:se:his:diva-23635OAI: oai:DiVA.org:his-23635DiVA, id: diva2:1841208
External cooperation
Mahidol University
Subject / course
Bioinformatics
Educational program
Bioinformatics - Master’s Programme
Supervisors
Examiners
Available from: 2024-02-28 Created: 2024-02-28 Last updated: 2025-02-07Bibliographically approved

Open Access in DiVA

fulltext(1815 kB)220 downloads
File information
File name FULLTEXT01.pdfFile size 1815 kBChecksum SHA-512
2699c7e83e679c8e78cdf4ee07744d651f9bc2a06357f3e36fd4c8b192f9d094970357404281bc6888f024c07f5f4d6c9327ac179ca22b997ef75d163eac1851
Type fulltextMimetype application/pdf

By organisation
School of Bioscience
Bioinformatics and Computational Biology

Search outside of DiVA

GoogleGoogle Scholar
Total: 220 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 407 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf