Our approach, QPacker, demonstrates that quantum-annealer-based design can be applied to complex real-world design tasks, producing designed molecules comparable to those produced by widely adopted classical design approaches.read more
Menten uses cutting-edge machine learning and quantum computing to design and engineer tailored proteins for diverse applications in pharmaceutical and chemical industries.
Our hybrid quantum-classical computing approach overcomes the scalability challenges that limit classical approaches and significantly reduce the cost and time required to engineer a target protein for use cases in protein therapeutics and biocatalysis.
We apply cutting-edge computational approaches to rational design to develop next-generation peptide therapeutics with improved chemical and physical properties including extended plasma half-life and permeability.
We employ a mixed approach of active site optimization, machine learning (sequence model prediction, reinforcement learning, quantum maching learning), and molecular dynamic approaches to pre-screen enzyme sequences and computationally optimize activity, specificity, and stability.
Should you be interested in joining our team, please send us your resume and indicate why you want to join us.
For partnership opportunities or additional questions, give us a shout by emailing firstname.lastname@example.org.