Frank Teets
Head of Computational Biology AI Proteins
Frank holds a Ph.D. in Computational Biology from the University of North Carolina, where he developed a requirement-driven protein design algorithm used to create the first fully rationally designed miniprotein libraries. As Head of Computational Sciences at AI Proteins, he leads the development of AI-driven algorithms supporting protein design and optimization. His work spans generative models as well as predictive tools for protein expression, stability, immunogenicity, and developability and the hardware and network infrastructure required to train and deploy them. His experience sits at the intersection of AI strategy and experimental design, with a focus on building scalable tools that accelerate therapeutic protein development.
Seminars
- Leveraging foundation models to navigate complex protein systems (multi-domain, membrane-embedded, inducedproximity targets) that exceed the limits of single-structure or single-model approaches
- Combining AI-driven protein design with experimental structure generation to resolve ambiguity in binding modes, conformational states, and interaction interfaces
- Closing the loop between AI predictions and wet-lab validation by continuously retraining models on construct performance, structural success, and functional readouts
