Protein Engineering seminars
December 2024
2024 Nobel Prize Lectures in Chemistry
David Baker, Demis Hassabis, John Jumper· University of Washington, Seattle, WA, USA; Howard Hughes Medical Institute, USA
Recorded
David Baker, Demis Hassabis and John Jumper examine two complementary computational problems: designing proteins with desired properties and predicting the structures adopted by natural amino acid sequences. Baker describes the development of methods for creating new protein structures and functions. Hassabis discusses the use of artificial intelligence to accelerate scientific discovery, while Jumper explains the integration of chemical and biological reasoning into protein-structure prediction. The programme connects sequence, three-dimensional structure and function, and shows how computational approaches changed what researchers can attempt in protein science. It preserves the distinction between de novo design and prediction while explaining why advances in both can support biological understanding and the creation of useful molecules.
January 2023
Engineering an inhibitor-resistant human CSF1R variant for microglia replacement
Terhi Lohela· University of Helsinki
Recorded
October 2022
Minimal genetically encoded tags for fluorescent protein labeling in living neurons
Aleksandra Arsic· Werner Reichardt Centre for Integrative Neuroscience (CIN), Tübingen University
Thu, Oct 20 · 16:00 UTC · Online
June 2021
Multiphoton imaging with next-generation indicators
Manuel Mohr· Stanford University
Wed, Jun 30 · 16:00 UTC · Online
Two-photon (2P) in vivo functional imaging of genetically encoded fluorescent Ca2+indicators (GECIs) for neuronal activity has become a broadly applied standard tool in modern neuroscience, because it allows simultaneous imaging of the activity of many neurons at high spatial resolution within living animals. Unfortunately, the most commonly used light-sources – tunable femtosecond pulsed ti:sapphire lasers – can be prohibitively expensive for many labs and fall short of delivering sufficient powers for some new ultra-fast 2P microscopy modalities. Inexpensive homebuilt or industrial light sources such as Ytterbium fiber lasers (YbFLs) show great promise to overcome these limitations as they are becoming widely available at costs orders of magnitude lower and power outputs of up to many times higher than conventional ti:sapphire lasers. However, these lasers are typically bound to emitting a single wavelength (i.e., not tunable) centered around 1020-1060 nm, which fails to efficiently excite state of the art green GECIs such as jGCaMP7 or 8. To this end, we designed and characterized spectral variants (yellow CaMP = YCaMP) of the ultrasensitive genetically encoded calcium indicator jGCaMP7, that allows for efficient 2P-excitation at wavelengths above 1010nm. In this talk I will give a brief overview over some of the reasons why using a fiber laser for 2P excitation might be right for you. I will talk about the development of jYCaMP and some exciting new experimental avenues that it has opened while touching on the prospect that shifting biosensors yellow could have for the 2P imaging community. Please join me for an interesting and fun discussion on whether “yellow is the new green” after the talk!
August 2020
“Discovery of Novel Gain-of-Function Mutations Guided by Structure-Based Deep Learning”
Ross Thyer· Rice University
Tue, Aug 25 · 05:45 UTC · Online
Life of biological molecules spans time and length scales relevant at atomic to cellular time and length scales. Hence, novel molecular modeling approaches are required to be inherently multi-scale. Here we describe multiple methodologies developed in our laboratory: rapid discrete molecular dynamics simulation algorithm, protein design and structural refinement tools. Using these methodologies, we describe therapeutic strategies to combat this HIV and cancer, as well as design novel approaches for controlling proteins in living cells and organisms.
July 2020
Deep learning for protein design
Lucy Colwell· Google Research - Cambridge UK
Wed, Jul 29 · 03:45 UTC · Online
End of results.