SubjectsSubjects(version: 912)
Course, academic year 2021/2022
Chemoinformatics - D143006
Title: Chemoinformatika
Guaranteed by: Department of Informatics and Chemistry (143)
Faculty: Faculty of Chemical Technology
Actual: from 2016
Semester: summer
Points: summer s.:0
E-Credits: summer s.:0
Examination process: summer s.:
Hours per week, examination: summer s.:2/2, other [HT]
Capacity: unlimited / unlimited (unknown)
Min. number of students: unlimited
Language: Czech
Teaching methods: full-time
For type:  
Note: course is intended for doctoral students only
can be fulfilled in the future
Guarantor: Svozil Daniel prof. Mgr. Ph.D.
Is interchangeable with: AP143001, P143001
Annotation -
Last update: Kubová Petra Ing. (03.11.2016)
The class covers basic techniques of managing and analyzing chemical data on computers, including representation of 2D and 3D chemical structures, searches in chemical structure databases, reviewing applications and algorithms such as cluster and diversity analysis, quantitative structure–activity relationship (QSAR), virtual screening, predictive modeling, and data mining.
Aim of the course -
Last update: Kubová Petra Ing. (03.11.2016)


Will understand principles of chemical storing

Will study algoritms for substructure and similarity searches in chemical databases

Will understand principles of diversity analysis and chemical library design

Will be able to apply virtual screening methods for the prioritization of chemical compounds for biological activity testing

Literature -
Last update: Kubová Petra Ing. (03.11.2016)


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

Syllabus -
Last update: Kubová Petra Ing. (03.11.2016)

1) Introducing Cheminformatics

2) Representation of 2D structures on computer, characterizing 2D structures with descriptors and fingerprints

3) Algorithms for 2D chemical database searching, reaction representation

4) Chemical File Formats and SMARTS

5) Representation and visualization of 3D chemical structures, 3D alignment

6) Cluster and Diversity analysis

7) Quantitative Structure-Activity Relationships (QSAR)

8) Virtual Screening

9) Predictive modeling

10) Docking and scoring

11) Pharmacophore Modeling

12) Data mining of chemical & biological information

13) Analysis of HTS data

14) Structure and ligand based drug design