Moab develops minibinder proteins—small, stable, and highly modular molecules—for therapeutic applications. By combining novel protein scaffolds, ultra‑high‑throughput data generation, and advanced AI models, they explore protein design space beyond the capabilities of current frontier AI methods, creating potent binders for partners. Their platform accelerates the discovery of new therapeutics by enabling the design of highly specific, high‑affinity minibinders at scale.
Funding
Funding not disclosed
Founders
Product
Problem
Developing new therapeutic proteins is limited by the size, stability, and design flexibility of conventional protein scaffolds, making it difficult to create potent binders for diverse targets.
Solution
Moab engineers minibinder proteins that are intrinsically small, stable, and highly modular, expanding the range of therapeutic candidates. The company combines novel protein scaffolds with ultra‑high‑throughput experimental data generation and advanced AI-driven design models to explore protein sequence space beyond the capabilities of standard methods. This approach enables rapid discovery of high‑affinity binders for partner programs and fuels Moab’s own therapeutic pipeline. By delivering engineered minibinders that retain potency while offering improved manufacturability and tissue penetration, Moab aims to accelerate the development of next‑generation biologics.
Target Audience
Primary customers are pharmaceutical and biotech companies seeking engineered protein binders for drug discovery, as well as research institutions developing novel biologic therapeutics.
Features
- Custom-designed protein scaffolds optimized for minimal size and high thermodynamic stability
- Ultra‑high‑throughput screening pipelines that generate large datasets for model training and validation
- Proprietary AI models that predict binding affinity and specificity across vast protein design spaces
- Modular minibinder architecture allowing rapid re‑targeting to new disease-relevant epitopes
- Integrated workflow from in silico design through experimental validation to therapeutic candidate selection