Universität Wien
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301186 VU Structural Bioinformatics (2025S)

5.00 ECTS (3.00 SWS), SPL 30 - Biologie

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 36 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

Important note!
All registered students, including those on the waiting list, MUST attend the first course!
According to the University rules, for all courses with continuous assessment attendance during the first course unit is mandatory. Students who do not show at the first course must be de-registered and their place will be filled with students from the waiting list.

  • Donnerstag 03.04. 10:00 - 15:00 BZB EDV-Raum CCR01, 6.Ebene 6.505, Dr.-Bohr-Gasse 9, 1030 Wien
    BZB EDV-Raum CCR02, 6.Ebene 6.506, Dr.-Bohr-Gasse 9, 1030 Wien
  • Freitag 04.04. 10:00 - 15:00 BZB EDV-Raum CCR01, 6.Ebene 6.505, Dr.-Bohr-Gasse 9, 1030 Wien
    BZB EDV-Raum CCR02, 6.Ebene 6.506, Dr.-Bohr-Gasse 9, 1030 Wien
  • Montag 07.04. 10:00 - 15:00 BZB EDV-Raum CCR01, 6.Ebene 6.505, Dr.-Bohr-Gasse 9, 1030 Wien
    BZB EDV-Raum CCR02, 6.Ebene 6.506, Dr.-Bohr-Gasse 9, 1030 Wien
  • Dienstag 08.04. 10:00 - 15:00 BZB EDV-Raum CCR01, 6.Ebene 6.505, Dr.-Bohr-Gasse 9, 1030 Wien
    BZB EDV-Raum CCR02, 6.Ebene 6.506, Dr.-Bohr-Gasse 9, 1030 Wien
  • Mittwoch 09.04. 10:00 - 15:00 BZB EDV-Raum CCR01, 6.Ebene 6.505, Dr.-Bohr-Gasse 9, 1030 Wien
    BZB EDV-Raum CCR02, 6.Ebene 6.506, Dr.-Bohr-Gasse 9, 1030 Wien
  • Donnerstag 10.04. 10:00 - 15:00 BZB EDV-Raum CCR01, 6.Ebene 6.505, Dr.-Bohr-Gasse 9, 1030 Wien
    BZB EDV-Raum CCR02, 6.Ebene 6.506, Dr.-Bohr-Gasse 9, 1030 Wien
  • Freitag 11.04. 10:00 - 15:00 BZB EDV-Raum CCR01, 6.Ebene 6.505, Dr.-Bohr-Gasse 9, 1030 Wien
    BZB EDV-Raum CCR02, 6.Ebene 6.506, Dr.-Bohr-Gasse 9, 1030 Wien

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

Aims: Aims:
This 8-day practical course aims to give a comprehensive introduction to structural bioinformatics, offering both theoretical and hands-on experience with a variety of online tools and methods. The course will provide students with practical skills and theoretical knowledge, allowing them to apply bioinformatics tools to protein analysis and drug discovery in their future research. Upon completion of the course, students will:
1. Understand key structural bioinformatics tools: Learn how to use online platforms like BLAST, UniProt, PSIPRED, PDB, PDBsum, IUPred3, ODiNPred, SMART, etc., to analyze protein sequences and structures.
2. Protein Structure Prediction and Analysis: Become familiar with advanced methods for protein structure prediction, including tools like SWISS-MODEL, ESMFold, RoseTTAFold, AlphaFold, and their applications in research.
3. Druggability Prediction: Learn how to utilize online servers such as DoGSiteScorer and FTMap to predict the druggability of proteins and investigate structure-based drug discovery.

Contents:
The course will cover the following topics:
1. Introduction to Molecular Structures:
o Basics of nucleic acid and protein structures.
o Protein folding and the functional aspects of proteins.
2. Protein Structural and Functional Analysis:
o Techniques for predicting and validating protein structures.
o Tools for functional analysis of proteins, including sequence alignments, motif detection, and structural comparisons.
3. Structure-based Drug Discovery:
o Principles of structure-based drug discovery, including virtual screening, high-throughput screening, and fragment-based drug design.
o Methods for assessing protein druggability and identifying potential drug targets.
4. Practical Applications:
o Use of online tools to retrieve protein and DNA sequences, predict protein folding, and model 3D structures.
o Methods for critically analyzing 3D structures, including evaluating the druggability of protein targets.
5. Case Study of Real Drugs:
o Study of the molecular mechanisms behind common drugs, such as aspirin, quinine, and dorzolamide, to understand how structure-based drug discovery is applied in the real world.

Methods:
The course will consist of both lectures and hands-on exercises. The practical exercises will be demonstrated during the course and can be continued by students as self-practice at home.
Lectures: Introduction to various bioinformatics tools and techniques, theoretical background, and application demonstrations.
Exercises: Students will work through exercises that allow them to apply the tools learned in class, with a focus on real-world applications and drug discovery processes.

Art der Leistungskontrolle und erlaubte Hilfsmittel

The assessment will be based on the following components:
1. Active Participation and In-class Performance (40%):
o Engagement in discussions and exercises during the course.
2. Final Written Report (60%):
o The final report will have two parts:
1. Analysis of Given Targets: Students will analyze provided protein targets using the tools and techniques covered in the course.
2. In-depth Examination of a Drug-bound Protein: Students will examine a protein of their choice that is bound to a drug, using the tools and methods learned in the course.
The final report will be submitted after the course, and its format and layout will be explained in class.

Mindestanforderungen und Beurteilungsmaßstab

Minimum Requirements and Assessment Criteria:
Compulsory Attendance: A maximum of 1 day can be missed for an important reason.
Active Participation: Students must actively engage in discussions and exercises.
Final Written Report: Both parts of the report must be completed using the software and tools learned throughout the course.

Prüfungsstoff

Examination Topics:
The examination will cover all materials taught during the course, including:
Protein structure and functional analysis tools.
Structure prediction and validation techniques.
Structure-based drug discovery methods.
Druggability prediction tools.
Real-world applications of bioinformatics in drug development.

Literatur

M. M. Gromiha. Protein Bioinformatics, Academic Press, 2010F.
Pazos, M. Chagoyen, Practical Protein Bioinformatics, Springer;2015

Zuordnung im Vorlesungsverzeichnis

MMB III-1a:, PhD MB

Letzte Änderung: Fr 10.01.2025 00:02