This workflow shows how generative AI can generate DNA sequences that can be translated into proteins for bioengineering.

This blueprint shows how generative AI and accelerated NIM microservices can design protein binders smarter and faster.

Fragment-Based Molecular Generation by Discrete Diffusion.

Predicts the 3D structure of a protein from its amino acid sequence.

Generates embeddings of proteins from their amino acid sequences.

Predicts the 3D structure of a protein from its amino acid sequence.

This blueprint shows how generative AI and accelerated NIM microservices can design optimized small molecules smarter and faster.

ProteinMPNN is a deep learning model for predicting amino acid sequences for protein backbones.

A generative model of protein backbones for protein binder design.

MolMIM performs controlled generation, finding molecules with the right properties.

Predicts the 3D structure of a protein from its amino acid sequence.

Predicts the 3D structure of how a molecule interacts with a protein.