Ajax Therapeutics Combined Structural Biology With Computational Chemistry for Drug Design

Ajax Therapeutics built its drug-discovery strategy around a combination of structural biology, cancer biology and computational chemistry, using detailed information about protein structure to design more selective JAK inhibitors. The approach ultimately produced AJ1-11095, a first-in-class Type II JAK2 inhibitor that became the company's lead clinical program and was later acquired by Eli Lilly.

Rather than relying primarily on conventional screening and subsequent optimization, Ajax sought to understand how JAK2 adopts different structural conformations and then use computational methods to design molecules capable of selectively binding the desired state.

That strategy is particularly relevant because AJ1-11095 was designed to bind the Type II conformation of JAK2, unlike currently approved JAK2 inhibitors, which bind the Type I conformation.

Starting With the Biology of JAK2

Ajax's approach began with the biology of Janus kinase 2 (JAK2) and its role in myeloproliferative neoplasms (MPNs), including myelofibrosis.

JAK/STAT signaling is an important driver of these blood cancers, with disease-associated mutations involving JAK2, MPL and CALR. Existing JAK2 inhibitors can reduce spleen enlargement and improve symptoms, but patients may eventually lose response or discontinue treatment because of inadequate benefit, adverse events or disease progression.

Ajax therefore pursued a different question: instead of developing another inhibitor that behaved like existing Type I drugs, could researchers exploit another structural state of JAK2 to create a more selective and potentially disease-modifying therapy?

That question became the foundation of the company's discovery program.

Structural Biology Provided the Blueprint

Structural biology was important because proteins are not static structures.

Kinases such as JAK2 can adopt different conformations, and the shape of a binding pocket can change depending on the protein's state. Understanding those structural differences can help researchers identify binding opportunities that may not be accessible—or may not be optimally targeted—when focusing only on one conformation.

Ajax's founding scientists brought expertise in cancer biology and structural biology, while the company partnered with Schrödinger to apply computational structure-based drug-discovery technologies. Ajax says the collaboration was established in 2019 specifically to combine its structural biology insights with Schrödinger's computational platform.

This created a complementary workflow:

Biology → Protein structure → Computational modeling → Molecule design → Experimental testing → Optimization

The objective was to use structural information to guide chemistry rather than treating molecular design as a largely trial-and-error process.

Computational Chemistry Helped Search the Chemical Space

The second part of Ajax's strategy was computational chemistry.

According to Ajax, AJ1-11095 was designed using structure-based drug design and computational methods at scale. The objective was to identify molecules capable of selectively binding the Type II conformation of JAK2.

Computational approaches can help researchers evaluate large numbers of potential molecular structures, predict how compounds may interact with a protein target and prioritize molecules for laboratory testing.

In a conventional discovery process, researchers may synthesize and experimentally test many compounds before identifying a promising lead. Structure-based computational approaches can help narrow that search by focusing chemistry on molecules that fit a particular structural hypothesis.

For Ajax, the computational component was therefore not separate from the biology. It was intended to translate structural understanding into specific chemical designs.

The Schrödinger Collaboration Was Central

Ajax's partnership with Schrödinger became a key part of this model.

The companies established their research collaboration in 2019 to discover novel JAK inhibitors. In 2025, they expanded the collaboration to include an additional JAK target, demonstrating that the partnership was intended to generate a broader pipeline rather than a single molecule.

Schrödinger described the progress of AJ1-11095 as an example of combining its computational platform at scale with Ajax's structural biology insights.

The collaboration illustrates an increasingly common model in modern drug discovery: a biotechnology company contributes disease biology and target expertise, while specialized computational platforms help accelerate molecular design and optimization.

Designing for the Type II JAK2 Conformation

The most important output of this strategy was AJ1-11095.

Ajax designed the molecule as a selective Type II JAK2 inhibitor, making it structurally and mechanistically different from approved JAK2 inhibitors that bind the Type I conformation.

This distinction was not simply a formulation change or a minor chemical modification. The company's goal was to create an inhibitor that interacted with a different structural state of the target.

The potential advantage was significant: Ajax believed Type II inhibition could provide deeper and more durable disease control and potentially retain activity against MPN cells that become resistant to chronic Type I JAK2 inhibition. Preclinical studies reported by the company showed reductions in mutant allele burden and reversal of marrow fibrosis.

Those findings provided the rationale for moving the molecule into clinical development.

From Computational Design to the Clinic

AJ1-11095 entered a Phase 1 clinical trial in myelofibrosis patients who had previously received a Type I JAK2 inhibitor and either failed to respond or lost response.

The trial, designated AJX-101, began in late 2024 and was designed to evaluate safety, tolerability and preliminary efficacy.

The transition from computational design to human testing represents an important validation point for Ajax's discovery model.

Computational predictions alone cannot establish whether a drug will work in patients. Molecules must still demonstrate appropriate pharmacology, safety, exposure and clinical activity.

For AJ1-11095, the first proof-of-concept clinical data presented at the 2026 EHA Congress provided an early indication that the underlying design strategy could translate into measurable biological and clinical effects.

Early Clinical Data Add Weight to the Design Strategy

The first clinical results were notable because they showed activity in patients whose disease had already been treated with a Type I JAK2 inhibitor.

The results included reductions in spleen volume, improvements in symptoms and reductions in driver mutation variant allele frequency. These findings are particularly relevant because Ajax had designed AJ1-11095 around the hypothesis that Type II JAK2 inhibition could produce effects beyond the symptomatic benefits associated with existing therapies.

The clinical data remain early, but they provide an important bridge between structure-guided molecular design and clinical proof of concept.

Why This Approach Matters for Drug Discovery

Ajax's strategy reflects a broader shift in pharmaceutical research.

Drug discovery is increasingly moving toward approaches in which researchers combine:

• Structural biology to understand target shape and binding sites

• Computational chemistry to model molecular interactions

• Large-scale computational screening to prioritize candidate compounds

• Medicinal chemistry to optimize potency and selectivity

• Experimental biology to validate computational predictions

• Clinical research to determine whether the biological hypothesis translates to patients

The advantage is not that computation replaces laboratory science. Instead, computational methods can help researchers make more informed decisions about which molecules to synthesize, test and optimize.

Ajax's experience with JAK2 demonstrates how this integrated model can be applied to a difficult target where conventional approaches may not deliver sufficient selectivity or differentiation.

Lilly's Acquisition Provides a Commercial Validation Point

The importance of Ajax's platform increased significantly when Eli Lilly agreed to acquire the company in April 2026.

At the time of the transaction, AJ1-11095 was still an investigational Phase 1 asset. Lilly highlighted its potential as a first-in-class Type II JAK2 inhibitor and its potential to provide deeper and more durable efficacy than existing therapies.

The acquisition therefore provides another indication of the value pharmaceutical companies place on specialized discovery platforms.

Lilly was not simply acquiring a conventional small-molecule candidate. It was acquiring a program built around a differentiated biological hypothesis and a structure-guided discovery approach.

The Broader Lesson for Pharmaceutical R&D

Ajax's story illustrates how advances in structural biology and computational chemistry are increasingly becoming intertwined.

Structural biology can reveal where and how a target can potentially be manipulated, while computational chemistry can help explore the chemical possibilities around that structural information.

When combined with experimental validation, the approach can create a more rational path from target biology to drug candidate.

For emerging biotechnology companies, this model can also create strategic value. A relatively small organization can combine specialized scientific expertise with external computational capabilities rather than building every discovery technology internally.

Conclusion

Ajax Therapeutics' development of AJ1-11095 demonstrates the potential of combining structural biology with computational chemistry to pursue differentiated drug mechanisms.

By studying the structural behavior of JAK2 and using computational methods to design molecules around the Type II conformation, Ajax developed a candidate that entered clinical testing as a first-in-class Type II JAK2 inhibitor.

The company's collaboration with Schrödinger further illustrates how specialized biotechnology teams can combine biological insight with large-scale computational drug discovery. The first clinical data presented in 2026 now provide an early opportunity to test whether that design philosophy can translate into meaningful patient outcomes.

Ultimately, Ajax's approach represents a broader trend in pharmaceutical R&D: using the three-dimensional structure of disease targets and computational power to design medicines with greater precision, rather than relying solely on experimental trial and error.