Mega-scale experimental analysis of protein folding stability in biology and design

Presentation will be in Japanese language

Date & Time

Thursday, 26 October 2023 | 04:30pm JST

Webinar Description

Advances in DNA sequencing and machine learning are illuminating protein sequences and structures on an enormous scale. However, the energetics driving folding are invisible in these structures and remain largely unknown. The hidden thermodynamics of folding can drive disease, shape protein evolution, and guide protein engineering, and new approaches are needed to reveal these thermodynamics for every sequence and structure.

In this webinar, Dr. Kotaro Tsuboyama will be presenting on cDNA display proteolysis, a new method for measuring thermodynamic folding stability for up to 900,000 protein domains in a one-week experiment. Using this immense dataset, they quantified (1) environmental factors influencing amino acid fitness, (2) the global divergence between evolutionary amino acid usage and protein folding stability and (3) thermodynamic couplings (including unexpected interactions) between protein sites.

What you'll learn in this webinar:
  • Learn about de novo proteins useful in engineering and medicine
  • How DNA synthesis and DNA sequencing technology enable us to obtain large-scale data in protein science
  • How to decode folding stabilities encoded in amino acid sequences
Webinar Registration
Results are specific to the institution where they were obtained and may not reflect the results achievable at other institutions.


Kotaro Tsuboyama, Ph.D.
Institute of Industrial Science, The University of Tokyo

Kotaro Tsuboyama is a Lecturer (PI) at the Institute of Industrial Science, The University of Tokyo. Kotaro got a Ph.D. at The University of Tokyo in 2016, then he moved to Northwestern University to learn how to merge biology and informatics together. His research focuses on high-throughput analysis of protein feature/functions to make de novo protein design more rational and efficient. He is also interested in how de novo proteins can be utilized to answer important biological questions.
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