From snakebite to cancer: designing protein binders faster than we can measure them

What happens when you can design a protein binder faster than you can measure whether it works? That bottleneck is where modern protein design has arrived, and it was the theme of a Fidabio webinar with Professor Timothy Jenkins, associate professor and head of the Center for Translational Protein Design at the Technical University of Denmark (DTU), and founder of the startup Affinity AI. His talk ran from snake venom to cancer, and showed where Flow Induced Dispersion Analysis (FIDA) fits as the fast measurement step.

Why does snakebite need a better answer?

Snakebite is one of the most neglected tropical diseases, killing well over a hundred thousand people a year and permanently disabling many more, mostly in the global south. According to Professor Jenkins, the only specific treatment, antivenom, is still made much as it was a century ago: venom is milked from snakes, injected into horses, and the animals' antibodies are purified from their blood. It saves lives, but much of what is injected into patients is not even directed at snake toxins, and the approach does not scale to the roughly two thousand different toxins found across the world's venomous snakes.

From finding needles to making them

Professor Jenkins's group first tackled this by discovery: screening large libraries of alpaca nanobodies to fish out the rare ones that neutralise toxins. It worked, yielding a handful of broadly neutralising nanobodies that covered about half of sub-Saharan Africa's elapid venoms, but it took roughly five years.

Modern protein design changed the economics. Instead of searching for a needle in a haystack, the group could simply design the needle it wanted. Working with the laboratory of Nobel laureate Professor David Baker, they designed small binders against three-finger toxins, some of the most lethal venom components. According to Professor Jenkins, the designs worked within weeks: high-affinity, thermostable mini-binders that, in what he believes was the first demonstration of its kind, protected mice from lethal doses of toxin in vivo.

The same approach, pointed at cancer

To show the method was not limited to venom, the group applied it to cancer, designing mini binders that direct the immune system to cancer cells for cell therapy. In a nine-month project with colleagues at DTU Health, the designed binders steered immune cells to recognise and destroy cancer cells in the dish, a result that traditionally takes years to reach.

Designing binders faster than you can measure them

The group then asked whether nanobodies could be designed entirely from scratch. Comparing several AI design tools, they took forty-eight designs into the lab, found roughly a ten per cent success rate, and confirmed that the best were specific, well-behaved and, again, protective in mice, in what Professor Jenkins believes were the first de novo designed VHH antibodies tested in vivo.

That success created a new problem. According to Professor Jenkins, once you can design many binders quickly, the bottleneck moves to the wet lab: you have to measure which ones actually bind, and how tightly, faster than the designs pile up. His postdoc, he recalled, jumped in as the hero to screen candidates quickly when the team was against the clock.

Where FIDA comes in

This is where FIDA entered the workflow. Professor Jenkins described using it first as a rapid yes-or-no binding screen on the automation-friendly Fida Evolve, then for target quality control, checking whether a bought-in protein is aggregated or pure before effort is wasted on it, and for measuring binding affinity directly in solution.

"You actually are able to test in-solution binding, we don't really need to purify our sample, we can use low volume. It is not so expensive and it is also automation friendly, at least the new Fida Evolve,"

''BLI and SBR can be both annoying and expensive. And we were looking at least at alternative technologies that could be potentially faster, cheaper, and also give us more interesting data. And so we explored this and we landed on FIDA.'' Professor Jenkins said.

Crucially, the numbers held up against the established methods. According to Professor Jenkins, the affinities FIDA returned were close to identical to those from BLI across around ten different formats and targets.

"The error between SPR, BLI and FIDA is very negligible, it is always within the same order of magnitude," Professor Jenkins said.

FIDA now sits inside a larger effort he called the closed loop for binder design, a strategic partnership between Novo Nordisk and DTU that aims to design, express and test binders in one automated cycle, with FIDA as the measurement step.

What it means for protein design

Professor Jenkins framed the shift as one of the largest in pharmaceuticals: discovery timelines that once ran to years are being rewritten to months, and design can now outpace testing. When design moves that fast, measurement has to keep up. FIDA's appeal, in his account, is that it reads binding, size, sample quality and affinity from small, unpurified samples in solution, on an automation-friendly instrument, so the testing step no longer holds the design loop back.

Curious how FIDA measures binding, size and sample quality in solution? Explore the FIDA technology and the Fida instrument, see how FIDA supports de novo protein design, or browse the peer-reviewed literature. You can also watch the full webinar with Professor Timothy Jenkins.