A-Alpha Bio attracts $51M in total funding to advance machine-learning-driven protein interaction research

3D illustration of an antibody [peterschreiber.media/Adobe Stock]

A central hurdle in computational protein design is the mismatch between proteins designed in silico and their actual behavior after synthesis. “You can design millions of proteins on a computer over the course of a week or a month, but computational approaches are just not good enough,” explained David Younger, co-founder and CEO of A-Alpha Bio, in a recent interview. That is, after synthesis, the proteins often do not behave as desired.

Furthermore, the throughput for manual protein experiments is typically low. “You might be able to design millions of proteins, but you might only be able to test 10,” Younger said. The company thus built a platform designed to mitigate this bottleneck by focusing on protein binding — a crucial aspect of protein function.

Established in 2017 as a spinoff from the Institute for Protein Design at the Univers…

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