Warning! The directory is not yet complete and will be amended until the beginning of the term.
301186 VU Structural Bioinformatics (2025S)
Labels
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
Details
max. 36 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
see german version
-
N
Wednesday
02.04.
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 -
Thursday
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 -
Friday
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 -
Monday
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 -
Tuesday
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 -
Wednesday
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 -
Thursday
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 -
Friday
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
Aims, contents and method of the course
Assessment and permitted materials
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.
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.
Minimum requirements and assessment criteria
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.
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.
Examination topics
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.
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.
Reading list
M. M. Gromiha. Protein Bioinformatics, Academic Press, 2010
F. Pazos, M. Chagoyen, Practical Protein Bioinformatics, Springer;
F. Pazos, M. Chagoyen, Practical Protein Bioinformatics, Springer;
Association in the course directory
MMB III-1a:, PhD MB
Last modified: Fr 10.01.2025 00:02
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.