SubjectsSubjects(version: 873)
Course, academic year 2019/2020
  
Advanced chemoinformatics - P143001
Title: Pokročilá chemoinformatika
Guaranteed by: Department of Informatics and Chemistry (143)
Actual: from 2019
Semester: winter
Points: winter s.:0
E-Credits: winter s.:0
Examination process: winter s.:
Hours per week, examination: winter s.:3/0 other [hours/week]
Capacity: unlimited / unknown (unknown)
Min. number of students: unlimited
Language: Czech
Teaching methods: full-time
Level:  
For type: doctoral
Note: course is intended for doctoral students only
can be fulfilled in the future
Guarantor: Svozil Daniel doc. Mgr. Ph.D.
Interchangeability : D143006
Z//Is interchangeable with: AP143001
Annotation -
Last update: Svozil Daniel doc. Mgr. Ph.D. (07.06.2018)
The class covers advanced chemoinformatics and computational drug design techniques, such as lead optimization, biological information in models or the generation and exploration of chemical space.
Aim of the course -
Last update: Svozil Daniel doc. Mgr. Ph.D. (07.06.2018)

Students will:

  • understand advanced chemoinformatics and computationa drug design techniques
  • be able to assess the quality of QSAR classification and regression models
  • optimize lead structures using in silico techniques
  • understand the process of chemical space exploration and the assessment of its chemotype diversity
Literature -
Last update: Svozil Daniel doc. Mgr. Ph.D. (07.06.2018)

Literature

R: Engel T. Gasteiget J. Applied Chemoinformatics: Achievements and Future Opportunities, Wiley-VCH, 2018, ISBN 352734201X

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

Learning resources -
Last update: Svozil Daniel doc. Mgr. Ph.D. (07.06.2018)

Online course materials

Syllabus -
Last update: Svozil Daniel doc. Mgr. Ph.D. (07.06.2018)

Chamoinformatics methods for lead optimization - MMPA (matched molecular pairs analysis), bioisosters, scaffold hopping, multi-objective optimizationoptimalizační metody

Biological information in chemeoinformatics – chemogenomics space, experimental and computational approaches of chemogenomics space exploration, affinity fingerprints and their applications, proteochemometrics, ligand/protein interaction descriptors, protein/ligand interaction space modeling

Information theory and fingerprint engineering

QSAR modeling – QSAR model quality assessment, applicability domain in classification and regression models, deep learning methos in QSAR and their other applications

Generating and exploration of chemical space, chemotype diversity and its assessment, pharmacophore modeling (topological pharmacophores and pharmacophore fingerprints), molecular docking (conformer generation, protein flexibility, consensus scoring)

Course completion requirements -
Last update: Svozil Daniel doc. Mgr. Ph.D. (07.06.2018)

Oral exam

 
VŠCHT Praha