Macrocyclic peptides: a new "Goldilocks" drug class? | Empirical Health

Test your cholesterol and 100+ other biomarkers for $190 server-island-start<br>Macrocyclic peptides: a new "Goldilocks" drug class?<br>Brandon Ballinger · Jul 26, 2026

Traditionally, medicines were either small molecules or biologics. 90% of marketed drugs are small molecules like aspirin, atorvastatin, metformin. Small molecules are cheap to manufacture, chemically stable, and small enough (150,000 daltons, which makes them able to cover an entire protein surface, but they have to be injected since otherwise they would be destroyed by your digestive enzymes.

(A dalton is just a small unit of mass, about 1/12 the mass of a carbon atom.)

What if there were a middle category? Now there is. Macrocyclic peptides are large peptides (like GLP-1s) folded into a ring structure.

The first oral macrocyclic peptide was approved by the FDA last week. It’s a pill form of PCSK9 inhibitor that lowers LDL cholesterol by about 60%, comparable to injected PCSK9. This means we now have the precise targeting of a biologic with the stability of pills.

Enlicitide diagram. 6 of the 8 amino acids don’t occur in nature. Rings are used to stabilize the structure. Source: American Peptide Society, Lipfendra prescribing information.

Macrocyclic peptides violate the traditional Rule of Five , the 1997 guideline that predicts whether a compound will be absorbed when swallowed: under 500 daltons, fewer than five hydrogen bond donors, fewer than ten acceptors. Medicinal chemists now describe this territory as “beyond Rule of Five” space, which is a polite way of saying the old predictions stop working and you have to measure everything yourself.

This post covers why PCSK9 was such a tough target for small-molecule chemistry, how a screening technology from a startup found the molecule, the difficult parts of the 13 year timeline, and whether AI would have helped each phase.

Why PCSK9 is a hard target for small molecule drugs

PCSK9 destroys the liver’s LDL receptors, which pull cholesterol out of your blood. Blocking PCSK9 works spectacularly well: drugs like Repatha can lower LDL cholesterol by 60% alone or 85% as part of triple therapy.

But three problems make PCSK9 an unusually cruel target for a pill:

Its enzyme activity is actually a red herring. PCSK9 is a protease, so the obvious move is to jam its active site. But McNutt and colleagues built a catalytically dead version in 2007, and found it still destroyed LDL receptors. This means PCSK9 works more like an escort than a pair of scissors.

Its natural deep, well-shaped cavity is already plugged by its own prodomain.

The obvious target is flat . The surface where PCSK9 grips the LDL receptor sits more than 20 angstroms from the natural pocket. Merck’s own chemists called both surfaces “flat, featureless.”

In 2019, Merck published a paper describing its own failure to find a conventional pill for this target. In contrast, targeting PCSK9 is “great for antibodies because they’re huge (as explained by Douglas Johns, a clinical director on the team that developed enlicitide.)

Lipfendra took 13 years to develop. Would AI have sped it up?

Development of Lipfendra took 13 years divided across four phases: 1. find a molecule that binds a flat surface, 2. increase binding potentancy, 3. get it across the gut wall 4. and manufacture it at scale.

Four stages of enlicitide’s development.

For the most part, this was all done using traditional biotech tools (e.g., in vitro screening techniques). In 2026, an obvious question is: how much would AI help with each of these four stages? Let’s go stage by stage.

Stage 1: how mRNA display found the starting molecule

Merck licensed an mRNA display technology from a startup, Ra Pharmaceuticals, in 2013. Ra isa Cambridge company built around an mRNA display platform derived from Nobel laureate Jack Szostak’s work. The terms were $4.5 million up front and up to $56 million in milestones, which for a drug now forecast at multibillion-dollar peak sales is one of the better options anyone has bought. UCB ultimately acquired Ra for $2.1 billion in 2020.

mRNA display is an in vitro technology. It physically tethers each peptide to the strand of mRNA that encodes it, using a small molecule (puromycin) as a sort of molecular “leash.” The process is repeated iteratively in a test tube, which lets the screen test trillions of potential DNA sequences.

How mRNA display works: peptides stay tethered to the mRNA that encodes them, so survivors can be sequenced and amplified.

Would AI have sped this up? More than any later stage, yes. De novo macrocycle design genuinely works now. Baker’s lab published RFpeptides in June 2025, getting 12 binders from 39 molecules synthesized, including 9.4 nM against a bacterial protein the authors call “considerably flatter and difficult to target.” Latent Labs reports hit rates of 91% to 100% against standard benchmarks. So you can now run stage 1...