Content of lectures: Introduction to enzymology (enzyme classification, catalytic mechanisms, co-factors etc), enzyme kinetics, activity regulators, biocatalyst types and formulation, downstream processing, biocatalyst immobilization, bioprocesses and bioreactor types, biocatalysis in non-conventional media, biocatalytic strategies - Enzymatic cascades and some biocatalytic applications in white biotechnology.
Content of seminar: Round table presentations of several methods in all steps of a biocatalytic process, including methods of cloning, genome editing methods, expression systems, methods of cell lysis and sterilization, methods of protein purification, analytics for determination of enzymatic activity and structure determination.
ΓΜΠ89 - Protein Engineering Spring Semester - MSc elective module
The lectures are split in two major concepts: The first covers topics on identifying new enzymes, techniques of rational design and directed evolution and de novo design. The second one covers the concepts of the design of high-throughput screening, to aid the screening of large libraries.
The seminar provides some hands-on experience covering familiarization with bioinformatic tools, databases, virtual cloning of gene and preparation of a "small but smart library" of interest and the design of a high-throughput screening assay to screen the library we designed.
ΧΗΜ046 - Introduction to biology Spring Semester - ΒSc core module
The module covers the basic concepts of biology for chemistry students. Some chapters of this module are: the introduction to the cells and their chemistry, the energy and the metabolism (anabolism, catabolism), basic biomolecules (DNA, proteins and lipids), the basic dogma of biology, genetics and molecular basis of heredity, cell division and DNA technology.
The module covers the basic principles of bioinformatics needed in protein biotechnology and focuses on practical skills for structure visualization and evaluation, homology model construction, structure-based sequence databases. Moreover, the students are introduced in the lab automation and they are getting their first classes in programming in Python for simple tasks to automatize daily routine in the lab.