SubjectsSubjects(version: 954)
Course, academic year 2019/2020
Computational drug design - M143007
Title: Počítačový návrh léčiv
Guaranteed by: Department of Informatics and Chemistry (143)
Faculty: Faculty of Chemical Technology
Actual: from 2019 to 2020
Semester: summer
Points: summer s.:5
E-Credits: summer s.:5
Examination process: summer s.:
Hours per week, examination: summer s.:2/2, C+Ex [HT]
Capacity: unlimited / unlimited (unknown)
Min. number of students: unlimited
State of the course: taught
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Note: enabled for web enrollment
Guarantor: Svozil Daniel prof. Mgr. Ph.D.
Interchangeability : N143052
Examination dates   Schedule   
This subject contains the following additional online materials
Annotation -
The aim of the course is to introduce basic principles and methods of computational drug design and cheminformatics which deal with computational analysis of relationships between small organic molecules and biomolecules. Topics include e. g. molecular similarity, design of chemical libraries, quantitative structure-activity relationship (QSAR), virtual screening or prediction of pharmacokinetic and toxicologic properties of compounds.
Last update: Svozil Daniel (01.03.2018)
Aim of the course -


  • Will be well informed about molecular data storing and processing.
  • Will be able to assess a similarity between organic structures.
  • Will be able to construct chemical libraries with required physico-chemical properties.
  • Will be able to predict biological activity from the structure.
  • Will understand algorithms used in cheminformatics applications.
Last update: Hladíková Jana (04.01.2018)
Literature -

R: Svozil D. a kol, Počítačový návrh léčiv, Chemické listy 11/2017, special issue of Chemické listy, 10 articles, ISSN 1213-7103, available at

R: Leach A. R., An Introduction to Chemoinformatics, Springer, 2007, ISBN 1402062907

A: Bajorath, J., Chemoinformatics for Drug Discovery, Wiley, 2013, ISBN 1118139100

A: Engel T., Gasteiger T., Chemoinformatics: Basic Concepts and Methods, Wiley-VCH, 2018, ISBN 3527331093.

A: Bunin B. A., Siesel B., Morales G., Bajorath J., Chemoinformatics: Theory, Practice, & Products, Springer, 2010, ISBN 9048172500

Last update: Svozil Daniel (04.11.2018)
Learning resources -


Last update: Hladíková Jana (04.01.2018)
Syllabus -

1. Molecular informatics - what is it, scientific origins and fundamental concepts. Molecular informatics and computational drug discovery. Relationship between molecular informatics, chemoinformatics and bioinformatics, their synergy and differences.

2. Representation and manipulation of 2D molecular structures. Line notations for describing chemical structures (SMILES, InChI, InChIKey). Chemical table file formats (SDF, CTFile family).

3. Structure and substructure searching, practical aspects of structure searching.

4. Molecular descriptors calculated from 2D and 3D molecular representations.

5. Molecular similarity methods - similarity based on 2D fingerprints, similarity coefficients, 3D similarity.

6. Compound classification and selection. Combinatorial chemistry and library design - diverse and focused libraries, diversity estimation, multi-objective design.

7. Ligand- and structure-based virtual screening. Paharmacophores, methods of their derivation and their use in virtual screening.

8. Predictive QSAR (Quantitative Structure-Activity Relationships) modeling - general workflow and data preparation.

9. Predictive QSAR modeling - development and validation of QSAR models.

10. Analysis of high-throughput screening data.

11. Predicting pharmacokinetics (ADME/Tox) properties.

12. Computer-aided molecular design - inverse design and de novo design.

13. Chemoinformatics software and database technologies.

14. Integrated chemo- and bioinformatics approaches to virtual screening and computational drug design.

Last update: Hladíková Jana (04.01.2018)
Registration requirements -

Biochemistry, Organic chemistry, Molecular genetics

Last update: Hladíková Jana (04.01.2018)
Course completion requirements -

A credit is awarded based on the solution of problems during seminars. A final exam is written.

Last update: Svozil Daniel (26.01.2018)
Teaching methods
Activity Credits Hours
Účast na přednáškách 1 28
Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi 1 28
Práce na individuálním projektu 1 28
Příprava na zkoušku a její absolvování 1 28
Účast na seminářích 1 28
5 / 5 140 / 140
Coursework assessment
Form Significance
Report from individual projects 30
Examination test 70