Oral exam or, in case of too many students, written exam. 50% of the achievable points from the assignments and the project, individually, are required for exam admission. Points achieved in excess of 50% serve as a bonus for the final exam.

Starting with an overview of its main application area, namely drug design, the
lecture teaches how computer science methods can be used to work with chemical
data, strongly focusing on small organic molecules (compounds). Representation
of compounds (graphs, line notations, file formats) is followed by most
important ways of topological comparison (identity, substructure, similarity).
Relevant applications of topological similarity are introduced (searching, clustering,
library generation). Quantitative Structure-Activity Relationship (QSAR)
is introduced as the cheminformatics branch for predictive modeling of chemical
properties. Finally, the prediction of 3D-structures from topology and similarity
methods for compounds with 3D coordinates are introduced.

Students know how different kinds of chemical data can be handled with computers,
how to represent and to analyse that data with methods from computer
science, and they have an overview of the main application area drug design.
Having understood the fundamental SSimilar Property Principlethey are able
to handle and to analyse experimental screening data and to implement
and apply ligand-based screening methods. Students have a solid knowledge on
standard tools and software libraries for cheminformatics. Project work strengthened
their ability to work in a team and to write down and to present scientific
work.

Lecture slides and additional materials will be provided digitally. Basic knowledge of organic chemistry, graph theory, and programming skills in Python are recommended.

Recommended textbooks:
1) Leach A., Gillet V. An Introduction To Chemoinformatics", Springer 2007
2) Faulon J.-L., Bender A. (Eds.) "Handbook Of Chemoinformatics Algorithms", CRC Press 2010
3) Engel T., Gasteiger J. (Eds.) Chemoinformatics", Wiley-VCH 2018
4) Optional: Klebe G. "Wirkstoffdesign", Springer 2009