Artificial Intelligence for Targeted Protein Degradation
Discover Zepto.Degrader, Kantify's solution for Targeted Protein Degrader discovery using Artificial Intelligence
Targeted Protein Degraders
Targeted Protein Degraders (TPDs) are a new and promising modality in the field of drug discovery, utilizing small molecules to direct the destruction of disease-causing proteins. Key components of TPDs are the "warheads," which are responsible for binding to the target protein, "E3 ligase ligands," which direct the destruction of the target protein to the E3 ubiquitin ligase machinery, and "linkers," which connect the warhead to the E3 ligase ligand.
TPDs work by forming a ternary complex between themselves, the targeted protein and the E3 ligase, leading to the targeted destruction of the target protein. The advantages of TPDs include their ability to specifically target disease-causing proteins that are often resistant to traditional drugs, leading to improved therapeutic outcomes.
However, the design of TPDs is challenging, with difficulties in finding appropriate warheads and E3 ligases, as well as designing effective linkers and ensuring selectivity and degradation of the target protein. These challenges, along with the limited number of computational methods available for PROTAC design, often result in a need for the synthesis of hundreds of TPDs to find just one effective one, making the process time-consuming and expensive.
Kantify’s TPD discovery solution Zepto.Degrader
Zepto.Degrader is a group of machine-learning algorithms that solve these major challenges in TPD design, including:
Ligand binding prediction
Optimal linker design
Our state-of-the-art algorithms can dramatically reduce the number of TPDs that need to be synthesized, making the drug discovery process more efficient and cost-effective.
Contact us via the below form to learn more about using our hit prediction solution Zepto.Degrader
Funded by Innoviris