Do you want to identify new inhibitors for a new target you are researching?
Can’t find good inhibitors for a certain target?
Do you want to go to the laboratory, but you don’t know which compound would be better?
Library Collection contains more than 3 million diverse screening compounds.
Specific Compound Library
Processing of the Compound Library
Processing of the protein (target) structure
Validation & quality of results
At CancerAppy we have developed an AI methodology capable of selecting among several million compounds only those with the best inhibitory activity on the desired target. With a high scientific rigor, and a detailed computational search, we managed to reduce the potential inhibitors to be tested in vitro from millions to a list of only about 10 compounds.
Our Lead Identification process uses the molecular docking technique to search for the best candidates to inhibit a target.
From an initial list of several million, through a scientifically rigorous and validated algorithm, it manages to obtain a small list of potential inhibitors with the following promising characteristics:
• its in silico activity is better than that of current inhibitors (with a difference in energy of more than 2 kcal/mol),
• its activity is highly specific compared to other similar proteins that have been tested in silico,
• its structures are diverse, eliminating redundant results and duplication in laboratory tests that increase costs,
We apply artificial intelligence and big data analysis to de-risk and accelerate the processes of drug discovery and development.
"CancerAppy helps you to think outside the box. With our integration of big data and artificial intelligence we provide you novel hypotheses to optimize your compound."
– CancerAppy Team-