Deprecated: Implicit conversion from float 519402.99999999994 to int loses precision in /home/webdocs-subsites/news/site/modules/EmailObfuscation/EmailObfuscation.module on line 211
Warning: Undefined array key "HTTP_ACCEPT_LANGUAGE" in /home/webdocs-subsites/news/site/assets/cache/FileCompiler/site/templates/_init.php on line 36
Deprecated: substr(): Passing null to parameter #1 ($string) of type string is deprecated in /home/webdocs-subsites/news/site/assets/cache/FileCompiler/site/templates/_init.php on line 36 Faculty for Chemistry and Pharmacy- Semester events
This Sonderkolloquium will be aimed particularly at students and be a great opportunity to get to know what organic chemistry research is ongoing in the department.
Session 1 (Wieland-Hörsaal, 11:15 - 12:15)
1. 11:15 - 11:30 Dr. Pavel Kielkowski
2. 11:35 - 11:50 Dr. Dino Berthold
3. 11:55 - 12:10 Dr. Fumito Saito
- lunch break -
Session 2 (Baeyer-Hörsaal, 13:15 - 15:15)
4. 13:15 - 13:30 PD Dr. Armin Ofial
5. 13:35 - 13:50 Prof. Dr. Anja Hoffmann-Röder
6. 13:55 - 14:10 Prof. Dr. Hendrik Zipse
7. 14:15 - 14:30 Prof. Dr. Oliver Trapp
8. 14:35 - 14:50 Prof. Dr. Andrea Rentmeister
9. 14:55 - 15:10 Prof. Dr. Anne Schütz
Ideal is pretty, but irregular more interesting - functionalization of de novo designed proteins by deviating from ideal geometries
Tremendous progress has been made in protein design in part due to advances in machine learning and growth of protein structure databases. However, the ability to reliably introduce function into genetically encodable de novo proteins is still a challenging task. Among the plethora of protein functions, the introduction of catalytic functionality into de novo proteins has proven to be particularly hard. One of the bottlenecks in this endeavor is the limited variability of starting backbones. We recently found that it is possible to overcome this limitation by using machine learning approaches and parametric design. This enabled us to establish a general method for the de novo design of enzymes. Our show-case examples include designs with an activated lysine and metal cofactors of increasing complexity. In this talk, I will highlight our challenges and findings during the development of the design pipeline.
Designing DNA nanostructures for self-assembly: from crystal lattices to reconfigurable and multifarious nanostructures
The control over the self-assembly of complex structures is a long-standing challenge of material science, especially at the colloidal scale, as the desired assembly pathway is often kinetically derailed by the formation of competing alternative structures or amorphous aggregates. The goal of inverse design problem in nanotechnology is hence to find a set of blocks that reliably self-assemble in high yield into a target structure while avoiding kinetic traps and alternative competing states. We present here a design pipeline that uses our coarse-grained model of DNA, called oxDNA, to carry out multiscale molecular simulations of DNA, RNA and proteins to design nanostructures and devices that can be successfully realized in lab. We show applications of our modeling pipeline to design of pyrochlore lattice, a highly coveted 3D lattice structure with promising applications in metamaterial applications. We further show examples of designing finite-size polycube nanostructures built from cube-shaped subunits, and design of self-assembling capsids. We show experimental results showing successful assembly of these multicomponent structure designs using DNA nanotechnology. We will also discuss examples of other recent applications of our modeling tools and show how they can help design different types of nanodevices, including: a multivalent nanosynbodies that inhibit SARS-CoV-2 spike protein binding, and a platform for targeted delivery of therapeutic payloads to cancer cells.
Thu, May 23, 2024
IMPRS Lecture Series,
Max Planck Institute for Biological Intelligence 17:00, MPI Campus Martinsried, Large Lecture Hall
Joergen Kornfeld, MPI for Biological Intelligence
How connectomics is slowly revolutionizing neuroscience
Prof. David Margulies, Weizmann Institute of Science, Israel
Artificial Protein Crosstalk, Combinatorial Sensing, and Bacterial Cell Surface Engineering with Molecules that Interact with Distinct Protein Partners