The immense size of protein sequence space and poor understanding of sequence-function relationships renders current protein library design methods highly inefficient. Deep learning based technology developed by Biomatter Designs – ProteinGAN – provides a way to generate highly diverse and functional synthetic enzyme libraries. Due to high amounts of mutations in each synthetic enzyme sequence (up to 50% currently shown) and their retained catalytic activity, the designed libraries can be subjected to exceptionally potent screening for improved activity, thermostability and other characteristics.
FIELDS OF APPLICATION
Protein engineering.
INTELLECTUAL PROPERTY
Patent applications: LT2018 542,LT2019 524, PCT/IB2019/058545.
Applicants: UAB „Biomatter Designs“ and Vilnius University.
PUBLICATIONS
Repecka et al. (2019)Expanding functional protein sequence space using generative adversarial networks.bioRxiv 789719; doi: https://doi.org/10.1101/789719.
Current development status
Laboratory prototypes
Vilnius University is the largest Lithuanian higher education and research institution. We are open for collaborative research, contract research or any cooperation activities with partners from business and public organizations. Multidisciplinary approach on R&D activities at Vilnius University provides unique opportunity to incorporate methodologies, perspectives, data and concepts from all scientific fields – biomedical, physical sciences, technologies, social sciences and humanities. We believe that the right mix of shared intentions with our partners and clients, outstanding teams of university researchers and open access to modern R&D infrastructure deliver remarkable solutions that can change organizations, markets and society in general.
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