Protein Binder Design

Guide generative AI protein structure screening.

Workloads

Generative AI

Industries

Healthcare and Life Sciences

Business Goal

Innovation
Return on Investment

Products

NVIDIA BioNeMo

Generative Protein Binder Design

Protein binder design in drug discovery grapples with considerable challenges, such as the immense diversity of protein structures and the significant costs and time associated with experimental methods. These protein binders, engineered to selectively interact with specific protein targets, are critical in developing new therapeutics, diagnostic tools, and biotechnological applications.

Scientists can now explore complex protein space more efficiently by leveraging accelerated computing and biomolecular generative AI models. These technologies enable the rapid generation of novel protein designs tailored to bind with targeted proteins. This approach significantly reduces the time and costs traditionally required by prioritizing candidates with the highest potential for success and providing deeper insights into the underlying structure-activity relationships.

NVIDIA’s accelerated computing and AI platform for drug discovery, BioNeMo™, enables researchers and application developers to:

  • Tailor and implement AI models for predicting 3D protein structures, generating novel and controlled protein designs, and predicting protein complex formation.
  • Access pretrained models through NVIDIA NIM™ APIs for accelerated inference.
  • Flexibly test and build enterprise-grade generative AI workflows with portable NIM deployments on any cloud or on-premises computing infrastructure.

More Use Cases

Biomolecular Generation

Protein Structure Prediction