Chai Discovery

1. Upload the target protein sequence to Chai Discovery.

2. Define the desired binding region (epitope).

3. Launch the AI-driven de novo antibody design module.

4. Review the generated antibody candidates and select the most promising ones based on predicted binding affinity and developability scores.

5. Order the selected antibodies for experimental validation.

1. Upload the antibody sequence to Chai Discovery.

2. Select the affinity maturation module.

3. Define the desired affinity improvement target.

4. Launch the AI-driven affinity maturation process.

5. Review the generated antibody variants and select the best one based on predicted binding affinity.

6. Order the selected antibody variant for experimental validation.

1. Upload the antibody sequence to Chai Discovery.

2. Select the developability optimization module.

3. Define the desired developability improvements.

4. Launch the AI-driven developability optimization process.

5. Review the generated antibody variants and select the best one based on predicted solubility and stability.

6. Order the selected antibody variant for experimental validation.

1. Upload the sequences of the two target proteins to Chai Discovery.

2. Select the multi-specific antibody design module.

3. Define the desired binding specificities and affinities.

4. Launch the AI-driven bispecific antibody design process.

5. Review the generated bispecific antibody candidates and select the most promising ones based on predicted binding affinities and developability scores.

6. Order the selected antibodies for experimental validation.

1. Upload the antibody library to Chai Discovery.

2. Define the target protein and desired binding characteristics.

3. Launch the AI-driven screening module.

4. Review the ranked list of antibody candidates based on predicted binding affinity and developability scores.

5. Select the top candidates for experimental validation.