Synthetic Protein Biology
Folding Proteins
Machine Learning-based Protein Design
We are a team of researchers creating and advancing protein design technologies. Using both open source and proprietary computational biology modeling tools, we are helping drive the future of biological sciences. Using custom-designed proteins, we are working to deliver future medical tools that can address the treatment of a wide ranging field of diseases from cancer to the common cold.
Focus Areas
Advancing protein design technologies.
Computational protein design based on vetted models of protein biophysics and metabolic biochemistry coupled with large-scale computing.
Targeted protein-ligand binding to bring to reality the novel biologics of tomorrow that are inaccessible from natural diversity.
Machine learning-based protein research quest to discover new therapeutics. foldexis collaborates with research companies to develop advanced proteins through its machine learning sytems.
Rosetta
Macromolecular Modeling of Proteins
RosettaCommons is the central hub for researchers from 23 universities and laboratories to contribute and share the Rosetta source code. RosettaCommons members develop software improvements to solve their unique computation challenges. New codesets are continually published to help others with their research.
Fold Proteins for Science
Get Involved
Foldit allows you to contribute to important scientific research. Proteins are the workhorses in every cell of every living thing. Proteins come in thousands of different varieties, but they all have a lot in common. For instance, they're made of the same stuff: every protein consists of a long chain of joined-together amino acids. Your input data helps by training computer programs with human pattern-recognition and puzzle-solving abilities to help make the algorithms more efficient at protein pattern-folding tasks. New protein designs can lead to scientific breakthroughs that may cure illnesses and more!