Basics of Molecular Modelling of Drugs - GF316
Title: Základy molekulového modelování léčiv
Guaranteed by: Department of Pharmaceutical Chemistry and Pharmaceutical Analysis (16-16190)
Faculty: Faculty of Pharmacy in Hradec Králové
Actual: from 2024
Semester: winter
Points: 0
E-Credits: 3
Examination process: winter s.:written
Hours per week, examination: winter s.:14/14, C+Ex [HS]
Capacity: unlimited / 33 (unknown)
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
Key competences:  
State of the course: taught
Language: Czech
Teaching methods: full-time
Level:  
Note: deregister from the exam date if a requisite was not fulfilled
course can be enrolled in outside the study plan
enabled for web enrollment
Guarantor: doc. PharmDr. Jan Zitko, Ph.D.
Co-requisite : GF342
Incompatibility : GF362
Interchangeability : GF362
In complex pre-requisite: GF1002
Examination dates   WS schedule   
Annotation -
The aim of the course is to acquaint students with basic methods of Computer Aided Drug Design (CADD). CADD methods are routinely used in rational design of new biologically active compounds (drugs). Students will learn basic theoretical principles of modelling of small molecules (drugs), biological structures (receptors) and their interactions. Emphasis will be placed on the practical application of these methods, which will be practiced in seminars. The principle outcome of the course is to learn CADD methods and understand their principles and utilization. Absolvents of the course, are supposed to be able to design and perform a simple CADD project on their own. Themes: Drug targets, Structure of proteins, Information systems and databases, In silico prediction of physicochemical properties, Drug-receptor interactions, Experimental methods to study drug-receptor interactions, Rational design and development of drugs with known receptor (structure-based drug design), Molecular docking. Molecular dynamics, Rational design and development of drugs with unknown receptor (ligand-based drug design), Analysis of Quantitative Structure-Activity Relationships (QSAR), Pharmacophore models, Case studies.
Last update: Zitko Jan, doc. PharmDr., Ph.D. (30.08.2024)
Course completion requirements -

Requirements to obtain the credits: Active participation in all seminars (absence is allowed only for serious reasons and will be solved individually), sufficient outcomes of the tasks solved in the seminars, sufficient outcomes of the final project solved in the last seminar. Successful completion of the exam equals to sufficient scoring in the written exam test.

Last update: Zitko Jan, doc. PharmDr., Ph.D. (30.08.2024)
Literature - Czech

Doporučená:

  • Young, D. C.. Computational Drug Design: A Guide for Computational and Medicinal Chemists. : WILEY-VCH, 2009, 344 s. ISBN 978-0-470-12685-1.
  • Brown, Nathan. In silico medicinal chemistry : computational methods to support drug design. Cambridge: Royal Society of Chemistry, 2016, 220 s. ISBN 978-1-78262-163-8.

Volitelná:

  • Davis, Andrew Ward, Simon E. (eds.). The handbook of medicinal chemistry : principles and practice. Cambridge, UK: Royal Society of Chemistry, 2015, 753 s. ISBN 978-1-84973-625-1.
  • Hans-Dieter Höltje et al.. Molecular Modelling.. : WILEY-VCH, 2008, 320 s. ISBN 978-3-527-31568-0.

Last update: Zitko Jan, doc. PharmDr., Ph.D. (24.03.2025)
Teaching methods - Czech

Výuka formou přednášek a seminářů. Účast na přednáškách je doporučená. Znalosti z přednášek budou ověřovány zkouškovým testem. Přednášky jsou koncipovány tak, aby studenty připravily na práci v následujícím semináři. Semináře slouží k praktickému nácviku práce v programech pro CADD.

Last update: Zitko Jan, doc. PharmDr., Ph.D. (30.09.2022)
Requirements to the exam - Czech

Praktické dovednosti získané na seminářích, teoretické znalosti z přednášek.

Last update: Zitko Jan, doc. PharmDr., Ph.D. (30.09.2022)
Syllabus -
  • Drug targets. Structure of proteins, structure of nucleic acids. The importance of specific amino acids for the tertiary structure of the protein and for the catalysis of biochemical reactions.
  • In silico prediction of 3D structure of proteins. Homology models and possibilities of their use. Creating a homology model, automated web services for creating homology models. Critical evaluation of the quality of homology models (Ramachandran plot).
  • Rational approaches to design and development of new drugs. Combinatorial libraries. Chemical information systems and databases. Biological information systems and databases. Crystallographic databases. Critical assessment of 3D protein structures. Data mining from public sources.
  • The importance of physicochemical properties for the action of drugs. Methods of in silico prediction of physico-chemical properties of compounds. In silico prediction of pharmacokinetic parameters, metabolism and toxicity of compounds.
  • Quantitative Structure-Activity Relationships (QSAR) and Quantitative Structure-Property Relationships (QSPR).
  • Drug-receptor interactions, intermolecular forces, hydrogen bonds.
  • Experimental methods for monitoring drug-receptor interaction. X-ray crystallographic analysis, NMR experiments, radioligands, isothermal titration calorimetry, thermal shift assay.
  • In silico methods for predicting drug-receptor interaction. Molecular docking. Molecular dynamics.
  • Overview of molecular docking methods. Rigid docking, flexible docking. Search function, conformational sampling, scoring functions. Overview of common molecular docking software and comparison of their functions. Freely available software (AutoDock Vina, DOCK), commercially available programs, online docking services (servers).
  • Critical evaluation of results of molecular docking. Special applications of molecular docking - virtual screening (HTVS), ligand modification.
  • Rational methods of design and development of drugs with known receptor (Structure-based drug design).
  • Rational methods of design and development of drugs with unknown receptor (Ligand-based drug design). QSAR. Pharmacophore models. 3D-QSAR.
  • Case studies. Examples of significant active substances developed with Computer Aided Drug Design (CADD) methods.
Last update: Zitko Jan, doc. PharmDr., Ph.D. (30.08.2024)
Learning resources - Czech

E-learning Moodle: Základy molekulového modelování léčiv
https://dl1.cuni.cz/enrol/index.php?id=4846

Last update: Zitko Jan, doc. PharmDr., Ph.D. (30.09.2022)
Learning outcomes -

Course Basics of Molecular Modelling of Drugs builds upon the knowledge and skills acquired in the following courses: General and Bioinorganic Chemistry, Organic Chemistry I and II, Physical Chemistry, Biochemistry, Pharmacology, Pharmaceutical Chemistry (or equivalent courses).Upon successful completion of the course, students are able to use the following terms (including their commonly used abbreviations) in the correct context related to computer-aided modelling of biologically active molecules: ligand, receptor, binding site, intermolecular interactions, hydrogen bond, ionic interaction, halogen bond, pi-pi interaction, hydrophobic interaction, homology model (of a protein), Ramachandran plot, conformation, AlphaFold, PDB, ChEMBL, PubChem, ZINC, CADD, structure-based drug design, ligand-based drug design, SBDD, LBDD, HTVS, de novo design, docking, molecular dynamics, MD, molecular mechanics, MM, quantum mechanics, QM, force field, energy minimization, RMSD, RMSF, QSAR, QSPR, pharmacophore, molecular fingerprint, Tanimoto index.


Learning outcomes:
Based on the acquired knowledge and skills, students:
•    define the basic concepts, principles, and goals of computer-aided drug design (CADD);
•    are able to navigate protein structures, types of bonds, and interactions between drugs and biological targets;
•    identify and describe the fundamental principles of modelling small molecules and biological structures (molecular mechanics, quantum mechanics);
•    use publicly available databases and tools to model 3D structures of biological targets and small molecules;
•    prepare small molecules and receptor structures for modelling purposes;
•    perform basic molecular docking and evaluate its results using scoring functions and visualization tools;
•    search for potential ligands for a given receptor using a 3D pharmacophore model;
•    explain the principles of molecular dynamics and its applications in studying drug–receptor interactions;
•    design and complete a simple CADD project.

Last update: Zitko Jan, doc. PharmDr., Ph.D. (24.03.2025)
Entry requirements - Czech

Předmět vyžaduje základní znalosti získané absolvováním profilového předmětu Farmaceutická chemie I a II a přípravných disciplín jako je organická a bioorganická chemie a biochemie. Dále je předpokládána schopnost základní práce s počítačem (MS Windows, kopírování a přejmenonování souborů, zipování) a znalost anglického jazyka na základní úrovni (terminologie, ovládání software, který není lokalizovaný do češtiny).

Last update: Zitko Jan, doc. PharmDr., Ph.D. (30.09.2022)