Cradle is AI-powered software that allows users to quickly and accurately design improved variants of protein sequences. With Cradle, users can import analysis data from current projects or start from scratch with a single startup sequence. The software generates sequences with predicted performance scores, reducing surprises in the lab. It learns from each experimental cycle, coming up with better variations over time and dramatically reducing time to market. Cradle also allows users to optimize multiple properties simultaneously, saving time and speeding up the learning process.

Main Features:

1. Protein Engineering Made Simple: Cradle simplifies protein engineering by providing a user-friendly interface that requires just a few clicks to design improved protein variants.

2. Predicted performance scores: Each generated sequence is accompanied by a predicted performance score, allowing users to make informed decisions about which variation to pursue without relying solely on trial-and-error experimentation.

3. Multi-property optimization: Unlike traditional methods, Cradle is designed to handle multiple properties and optimization tasks in a single cycle. Users can optimize various characteristics such as activity, thermostability, solvent stability, solubility, substrate specificity, E-coli expression for proteins; epitope coverage for vaccines; enzymatic efficiency for enzymes; and binding affinity for antibodies.

Use case:

1. Biotechnology Research Teams: Leading biotechnology teams use Cradle to accelerate new projects and revisit difficult ones by designing optimized protein variants more efficiently.

2. Pharmaceutical Industry: Cradle helps pharmaceutical companies streamline their drug discovery processes by rapidly generating high-performance protein sequences with desired properties.

3. Enzyme engineering: Researchers working on enzyme engineering can leverage Cradle’s multi-property optimization capabilities to improve the efficiency of enzymes for various applications such as industrial processes or biofuel production.

Conclusion:

Cradle is revolutionizing protein engineering by combining machine learning algorithms with user-friendly features that simplify the process of designing improved protein variants. Its ability to predict performance scores reduces uncertainty within the laboratory, saving time and resources. With Cradle, users can optimize multiple properties simultaneously, accelerating research and development in various industries such as biotechnology, pharmaceuticals and enzyme engineering. By providing a secure platform that respects user privacy and intellectual property, Cradle enables scientists to unlock the full potential of protein design.