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Protein Design
Last Updated: 2026-06-03 00:07:32
Abstract
This course explores the principles and methods of protein design and structure prediction, spanning foundational concepts, historical physics-based techniques, and modern deep learning approaches.
Objective
By the end of this course, students will have developed an intuition for fundamental concepts in protein structure prediction and design while exploring core historical approaches. Students will gain familiarity with deep learning techniques used in protein design and learn to apply state-of-the-art methods.
Content
The course is a mix of lectures and code-based exercise sessions. Students wil gain both a theoretical foundation and practical insights into state-of-the-art tools and methods used for protein design. We will begin by reviewing some fundamental concepts of protein structures and folding, followed by a description of early approaches to structure prediction based on energy methods like Rosetta. We will then cover landmark results in protein design, from initial manual strategies to early computational approaches, and progress through key milestones in pre-deep learning protein design, including enzymes and nanomaterials. A major focus is placed on deep learning’s transformative role in protein design. We will study breakthroughs like AlphaFold, and RoseTTAFold for structure prediction and learn how these tools were repurposed for protein design. Current deep learning methods for sequence design, such as ProteinMPNN, will be introduced alongside approaches for backbone generation using diffusion models and inpainting techniques. Finally, we will cover fundamentals of protein language models and their applications to de novo protein design.
Resources
Lecture Notes
Lecture slides will be made available on Moodle.
Literature
Primary literature will be made available on Moodle.
General Information
- Language
- English
- Levels
- DR , MSC
- Frequency
- Yearly recurring
Examination
- Type
- session examination
- Mode
- written 120 minutes
- Aids
- None
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise |
Protein Design
This course takes place in-person in BASEL (no streaming or recording available).
Attention: the lecture will start in the second week of the semester.
|
No time listed | 3 h weekly |
Offered In
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Computational Biology and Bioinformatics Master (More information at: )
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Core Courses (The list of core courses is a closed list - no other courses can be added in this category. The assignment of the courses to the respective subcategory cannot be changed. Students must pass at least one course in each subcategory. A total of 40 ECTS must be acquired in the core course category, including the mandatory CBB seminar.)
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Doctorate Biosystems Science and Engineering (More Information at: )
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Biotechnology Master (More information at: )
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Electives (Open list - other courses (ETH or UNIBAS) may be taken as electives upon approval of the mentor.)
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Advanced Courses (The list of advanced courses is a closed list, no other course can be added to this category.)
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