Scientists are using NVIDIA BioNeMo for large-scale language models that generate high-quality proteins that can accelerate drug design and help create more sustainable environments.

Using a pre-trained AI model from NVIDIA, the startup Evozyne has created two proteins with significant potential in healthcare and clean energy.

A joint paper describes the process and the biological building blocks it created. One aims to cure a congenital disease, while the other is designed to consume carbon dioxide to reduce the effects of global warming.

“It’s really encouraging that even in this first round, the AI model has created synthetic proteins that are as good as naturally occurring ones. This tells us that it has properly mastered the rules of nature’s design”,

says Andrew Ferguson, co-founder of Evozyne.

A transformative model of artificial intelligence
Evozyne uses NVIDIA’s implementation of ProtT5, a transformational model that is part of NVIDIA BioNeMo, a software framework and service for creating AI models for healthcare.

“BioNeMo really gave us everything we needed to support training the model and then running tasks with the model very inexpensively – we could generate millions of sequences in just a few seconds.”

says Ferguson, a molecular engineer working at the intersection of chemistry and machine learning.

The model is the basis for Evovyne’s process, called ProT-VAE. It’s a workflow that combines BioNeMo with a variational autoencoder that acts as a filter.

The model studies the ways nature
Like a student reading a book, NVIDIA’s transformational model reads amino acid sequences across millions of proteins. Using the same techniques that neural networks use to understand text, it learns how nature assembles these powerful building blocks of biology.

The model then predicts how to assemble new proteins suitable for the functions Evozyne wants to address.

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