MLU
PHA.03532.02 - Drug target identification and validation (Complete module description)
Original version English
PHA.03532.02 10 CP
Module label Drug target identification and validation
Module code PHA.03532.02
Semester of first implementation
Faculty/Institute Institut für Pharmazie
Module used in courses of study / semesters
  • Pharmaceutical Biotechnology (MA120 LP) (Master) > Pharmazie Pharmaceut.Biotech.MA120, Version of accreditation (WS 2008/09 - WS 2015/16) > Pflichtmodule
Responsible person for this module
Further responsible persons
Prof. Dr. W. Sippl
Prerequisites
Skills to be acquired in this module
• Basic understanding of drug substances and drug targets • Knowledge of methods and illustrative examples of drug target identification and valida-tion • Basic understanding of the connection between molecular and clinical effects of drug substances • Knowledge of bioanalytical tools for protein separation and ~identification • Ability to judge the quality of results, i.e., protein identification, protein quantitation • Ability to set up a proteomics workflow in industry • Application of proteomics methods to diseases • Knowledge of edible vaccine concepts • Knowledge of fusion protein strategies • Understanding of differences between stable and transient expression systems • Knowledge of the basic concepts of Computational Biology and Bioinformatics • A first and transparent introduction in comparative modeling and molecular dynamics simulations • Concepts of analyzing proteins/drug targets in 3D • Principles of modeling biological data
Module contents
Course B.1: General aspects of drug target identification and validation • Definition and characteristics of drug substances • Definition and characteristics of molecular drug targets • Interaction of drug substances and drug targets • Propagation of molecular drug effects • Methods and techniques for the identification and validation of drug targets • Correlation and causality of molecular and clinical drug effects
Course B.2: Proteomics • Methods for separating complex protein mixtures (2-DE, LC) • Protein mass spectrometry (ionization methods; mass analyzers) • Protein sequencing • Quantitative proteomics (ICAT, iTRAQ) • Analysis of post-translational modifications (glycosylation, phosphorylation) • Protein-protein interactions • In-vivo proteomics • Proteome analysis for investigation of diseases • Automation of the proteomics workflow
Course B.3: Molecular F(Ph)arming - Basics, Principles and Examples • General overview about expression of human proteins in transgenic organisms including microorganisms and mammalian cells. • Basics of intracellular sorting with special focus to plant cells. • N-glycosylation especially according the differences between plants and mammals. • Plantibody concept • Fusion protein strategies (expression enhancement, stability enhancement • Vaccines from plants including edible vaccine concepts. • Therapeutic antibodies from plants, different recombinant antibody formats. • Plant-based production of therapeutic proteins as human serum albumins and insulin as well as silk proteins for nanomedicine
4. Course B.4: Protein modeling and simulation • Introduction to Bioinformatics and comparative/homology modeling • Introduction in sequence alignment techniques • Analyzing protein structures • Commonly used force fields for protein simulations • Introduction to Molecular Dynamics • Introduction to docking simulations
Forms of instruction Lecture (2 SWS)
Lecture (2 SWS)
Seminar (2 SWS)
Lecture (1 SWS)
Seminar (1 SWS)
Lecture (1 SWS)
Course
Languages of instruction German, English
Duration (semesters) 1 Semester Semester
Module frequency jedes Wintersemester
Module capacity unlimited
Time of examination
Credit points 10 CP
Share on module final degree Course 1: %; Course 2: %; Course 3: %; Course 4: %; Course 5: %; Course 6: %; Course 7: %.
Share of module grade on the course of study's final grade 1
Module course label Course type Course title SWS Workload of compulsory attendance Workload of preparation / homework etc Workload of independent learning Workload (examination and preparation) Sum workload
Course 1 Lecture Proteomics 2 0
Course 2 Lecture Molecular F(Ph)arming - Basics, Principles and Examples 2 0
Course 3 Seminar Protein modeling and simulation 2 0
Course 4 Lecture General aspects of drug target identification and validation 1 0
Course 5 Seminar General aspects of drug target identification and validation 1 0
Course 6 Lecture Protein modeling and simulation 1 0
Course 7 Course Selbststudium 0
Workload by module 300 300
Total module workload 300
Examination Exam prerequisites Type of examination
Course 1
Course 2
Course 3
Course 4
Course 5
Course 6
Course 7
Final exam of module
Klausur
Exam repetition information
Prerequisites and conditions Prerequisites Frequency Compulsory attendance Share on module grade in percent
Course 1 Winter semester No %
Course 2 Winter semester No %
Course 3 Winter semester No %
Course 4 Winter semester No %
Course 5 Winter semester No %
Course 6 Winter semester No %
Course 7 Winter semester No %