1/5 Today, I’m sharing 7yrs of work. I believe we discovered a comprehensive mapping from protein structure to glycan structure, a genetic encoding for specific glycans, and a new paradigm in extracellular biology.
https://t.co/eba5yTub5x
#Glycotime
Seems like its finally happening. See you on the new platform. My handle and name are the same.
And honestly, its much more fun and much less icky there.
🦋🦋🦋🦋🦋
It takes two brilliant scientists like @hhefzi and @Nathan_E_Lewis to add fresh insight to a 100-year old phenomenon (subversion of the Warburg effect) AND turn that insight into a perfectly named tool (CHOZeLa) to transform biologics manufacturing.
Check out the preprint!
After ~8 years, happy to share work done w/@Nathan_E_Lewis showing you can eliminate the Warburg effect in mammalian cells-w/out impacting growth rate!-by simultaneous knock out of pyruvate dehydrogenase kinases and lactate dehydrogenases.
Thread below:
https://t.co/MDUI7CVOF4
@chrashwood @GlycomicsExpasy@GlyCosmos@gly_gen The training/test paradigm is more appropriate for predictive modeling which is what we did in manuscript #2. Manuscript #1 is more descriptive analysis which is why we focus more on in-depth validations with specific molecules.
So why does it matter that glycans are genetically encoded?
Glycans can be >50% of protein’s weight, cover >50% of protein surface, and vital in immunology, metastasis, and autoimmune pathogenesis. Yet, many biologists ignored them because they are hard to measure and control
1/5 Today, I’m sharing 7yrs of work. I believe we discovered a comprehensive mapping from protein structure to glycan structure, a genetic encoding for specific glycans, and a new paradigm in extracellular biology.
https://t.co/eba5yTub5x
#Glycotime
@hirenj @chrashwood @GlycomicsExpasy@GlyCosmos@gly_gen Noting the skew in the input data, we also used hierarchical regressions to adjust for representation across proteins (methods section 4, IMR-GEE).
@hirenj @chrashwood @GlycomicsExpasy@GlyCosmos@gly_gen Hi Hiren, in the corresponding text (results section 1) we describe the input data set (FigS1), dimensionality reduction approach (FigS2), and methods for feature engineering (Methods section 1).
Thanks to Meghan Altman, Isaac Shamie, @LCasalino88, @chem_christian, and @RommieAmaro for helping us explore the implications of GlycoTemplating in Influenza back when we could barely predict anything.
1/5 Today, I’m sharing 7yrs of work. I believe we discovered a comprehensive mapping from protein structure to glycan structure, a genetic encoding for specific glycans, and a new paradigm in extracellular biology.
https://t.co/eba5yTub5x
#Glycotime