User Experience Value

With Discovery Studio Simulation users can predict the paratope binding residues of an antibody without antigen information. They can design alternative protein scaffolds to position protein structural motifs in precise 3D geometries for protein design, including vaccine development. Users can design protein sequence libraries extremely quickly with deep learning ML models. Users can quickly generate diverse protein conformations with an ML model for structure-based design and efficient molecular dynamics. They can identify allosteric binding sites, to improve the effectiveness of drug design at the orthosteric binding site, and identify potential cryptic pockets in previously undruggable targets. In the Molecular Design app, users will be able to visualize and compare the sequence data of protein and nucleic acid structures. Users will have access to the Machine Learning Workbench to build predictive chemistry ML models. Users are able to share their modeling experti