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Computer-Assisted Drug Design (CADD) Essentials
Last Updated: 2026-06-03 00:07:32
Abstract
This course introduces the concepts of computer-aided drug discovery (CADD) and design, covering essential techniques like compound library analysis, virtual screening, de novo molecular design and optimisation. Through practical exercises, participants will learn to use software and prediction models to identify and optimise bioactive molecules.
Objective
Participants learn to (i) analyse and interpret the output of CADD software; (ii) evaluate the quality of virtual screening hits and computer-generated molecules; (iii) assess the predictive power of models; and (iv) translate results into actionable insights.
Content
The course equips participants with the knowledge to understand and effectively utilise computational approaches in the early drug discovery process. Participants will learn essential concepts of molecular representation and interaction, cheminformatics, ligand- and structure-based molecular design, molecular modeling, property prediction, and applied artificial intelligence in drug discovery.
Resources
Lecture Notes
Accompanying lecture slides are provided.
Literature
G. Klebe: «Drug Design», Springer, 2024. G. Schneider, K.-H. Baringhaus: «Molecular Design - Concepts and Applications», Wiley-VCH, 2008.
General Information
- Language
- English
- Levels
- DR , MSC
- Frequency
- Yearly recurring
Examination
- Type
- ungraded semester performance
Registration & Places
- Max Places
- 20
- Signup End
- 11.10.2026
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise |
Computer-Assisted Drug Design (CADD) Essentials
Block Course: 8-10 September 2026 (all day)
The course takes place in person at D-BSSE in BASEL
|
No time listed | 24 h semesterly |
Offered In
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Computational Biology and Bioinformatics Master (More information at: )
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Advanced Courses (A total of 30 ECTS must be acquired in the advanced course category. Thereof, at least 16 ECTS in the theory and at least 10 ECTS in the biology subcategory.)
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Theory (At least 16 ECTS need to be acquired in this subcategory.)
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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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