Practical course date: 21.02.-02.03.2019, 5 days course, 2 days for self-study in-between, 9 am - 5 pm.
Preliminary meeting: In January 2019, exact date will be announced soon.

Place: Campus Mitte, Virchowweg 6 (or surrounding Charité Campus), 10117 Berlin

Research AG Volkamer

Practical Course: Using open source software and libraries for data analysis and computer-aided drug design

This practical course introduces the students to diverse software tools and libraries which can support data generation and analysis in various areas of computer-aided drug design.  The course will sensitize the students to the ease and the profit of using bio-/cheminformatics methods.

The course shall enable the students to set-up their own drug design pipeline including protein target preparation, compound library set-up and filtering (i.e. using drug-like and toxicity filters), docking of the compounds to the target and evaluation of the results. The course will include the following tasks:

• There will be a short introductory part into python programming using the novel and interactive IPython notebooks.
• The students will write their own scripts using, e.g., python libraries for data handling (pandas), protein (BioPython) and compound (RDKit) processing as well as machine learning (scikit-learn) to prepare their compound libraries.  
• Open access tools for protein structure preparation and visual inspection (PyMol) will be used.
• AutoDock software will be engaged for docking of the compounds into the target protein and the results will be evaluated.   

Each day, we will perform a small task from the described computer-aided drug design pipeline (morning lecture followed by practical work asn presentation). The students can work individually or in groups, depending on the total number of participants.