Accelerate drug discovery with NVIDIA Clara™ for Biopharma, a collection of frameworks, applications, generative AI solutions, and pretrained models.
Accelerate breakthrough drug identification and improve the accuracy of target and compound selection.
Keep pace with AI innovation and drive outcomes within your organization.
Improve developer productivity and accelerate time to outcome.
Drug discovery is complex, from exploring the chemical universe and predicting protein structures to scanning drug candidates and simulating molecules. Drive breakthroughs in these critical research areas with the powerful NVIDIA NIM™ microservices and tools available in the NVIDIA NGC™ catalog.
The Generative Virtual Screening Blueprint within NVIDIA® BioNeMo™ leverages state-of-the-art AI models packaged within NVIDIA NIM™ microservices to screen and optimize small molecules against a protein target, accelerating drug discovery. The blueprint starts with AlphaFold2, which predicts the 3D structure of the target protein with high accuracy. The initial small molecules are then passed to MolMIM, which is then used to generate diverse small molecules for exploring chemical space to identify potential binders. These small molecules are evaluated by an Oracle model, which scores them based on predicted binding affinity and other crucial properties. Finally, DiffDock is employed to refine the interactions, predicting the optimal binding poses and enhancing the binding configurations. This integrated blueprint streamlines the identification and optimization of promising drug-like molecules, significantly reducing the time and cost associated with traditional drug discovery methods.
Head to the NVIDIA API catalog to experience BioNeMo with NIM microservices now or go to GitHub to start your deployment.
The Protein Binder Design Blueprint within NVIDIA BioNeMo leverages AI models packaged within NIMs to design optimized protein sequences and structures. The blueprint begins with the user passing an amino acid sequence to AlphaFold2, which predicts the initial 3D structure of the target protein. This structural information is then refined and optimized using RfDiffusion, which explores various conformations to identify the most favorable binding configurations. Next, ProteinMPNN generates and optimizes the amino acid sequences according to the RfDiffusion-generated conformational information, ensuring they exhibit the necessary biochemical properties for effective binding. Finally, AlphaFold-Multimer is used to validate the interactions and stability of the resulting protein complexes. This integrated approach enables the precise and efficient design of protein binders, facilitating advancements in therapeutic protein development and other biomedical applications.
Learn more about NVIDIA BioNeMo, a platform composed of managed services, software application frameworks, and reference AI workflows that simplify, accelerate, and scale generative AI for drug discovery.
Using Generative AI to Enhance Biologics Discovery and Development
Drug Discovery Platform Explores Novel Chemical Space with Higher Accuracy
Accelerating Protein Structure Discovery
Fuel Faster Insights for Healthcare and Life Sciences
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