PHA.03532.02 - Drug target identification and validation (Vollständige Modulbeschreibung)
PHA.03532.02 | 10 CP |
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Modulbezeichnung | Drug target identification and validation |
Modulcode | PHA.03532.02 |
Semester der erstmaligen Durchführung | |
Fachbereich/Institut | Institut für Pharmazie |
Verwendet in Studiengängen / Semestern |
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Modulverantwortliche/r | |
Weitere verantwortliche Personen |
Prof. Dr. W. Sippl |
Teilnahmevoraussetzungen | |
Kompetenzziele | 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 |
Modulinhalte | 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 |
Lehrveranstaltungsformen |
Vorlesung (2 SWS)
Vorlesung (2 SWS) Seminar (2 SWS) Vorlesung (1 SWS) Seminar (1 SWS) Vorlesung (1 SWS) Kursus |
Unterrichtsprachen | Deutsch, Englisch |
Dauer in Semestern | 1 Semester Semester |
Angebotsrhythmus Modul | jedes Wintersemester |
Aufnahmekapazität Modul | unbegrenzt |
Prüfungsebene | |
Credit-Points | 10 CP |
Modulabschlussnote | LV 1: %; LV 2: %; LV 3: %; LV 4: %; LV 5: %; LV 6: %; LV 7: %. |
Faktor der Modulnote für die Endnote des Studiengangs | 1 |
Modulveranstaltung | Lehrveranstaltungsform | Veranstaltungstitel | SWS | Workload Präsenz | Workload Vor- / Nachbereitung | Workload selbstgestaltete Arbeit | Workload Prüfung incl. Vorbereitung | Workload Summe |
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LV 1 | Vorlesung | Proteomics | 2 | 0 | ||||
LV 2 | Vorlesung | Molecular F(Ph)arming - Basics, Principles and Examples | 2 | 0 | ||||
LV 3 | Seminar | Protein modeling and simulation | 2 | 0 | ||||
LV 4 | Vorlesung | General aspects of drug target identification and validation | 1 | 0 | ||||
LV 5 | Seminar | General aspects of drug target identification and validation | 1 | 0 | ||||
LV 6 | Vorlesung | Protein modeling and simulation | 1 | 0 | ||||
LV 7 | Kursus | Selbststudium | 0 | |||||
Workload modulbezogen | 300 | 300 | ||||||
Workload Modul insgesamt | 300 |
Prüfung | Prüfungsvorleistung | Prüfungsform | |
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LV 1 | |||
LV 2 | |||
LV 3 | |||
LV 4 | |||
LV 5 | |||
LV 6 | |||
LV 7 | |||
Gesamtmodul | Klausur |
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Wiederholungsprüfung |
Regularien | Teilnahmevoraussetzungen | Angebotsrhythmus | Anwesenheitspflicht | Gewicht an Modulnote in % |
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LV 1 | Wintersemester | Nein | % | |
LV 2 | Wintersemester | Nein | % | |
LV 3 | Wintersemester | Nein | % | |
LV 4 | Wintersemester | Nein | % | |
LV 5 | Wintersemester | Nein | % | |
LV 6 | Wintersemester | Nein | % | |
LV 7 | Wintersemester | Nein | % |