They set out to design proteins with specific mechanical properties, for which they used the known unfolding characteristics of various protein sequences to train a diffusion model.

The proteins were also stable at temperatures as high as 95 °C, suggesting that this approach could design proteins that would be robust in real-life conditions.

Study: Generative design of de novo proteins based on secondary-structure constraints using an attention-based diffusion model. Image Credit: PopTika / Shutterstock.com. About the study. In the ...

For the first of these tasks Dr Baker and his colleagues use RF diffusion, an AI model they have developed to predict a ...

The company has integrated the AI model into its internal discovery pipeline and aims to use it in collaborative drug ...

Testing revealed that the proteins designed by AlphaDesign “produce comparable or improved results to the state-of-the-art protein diffusion model, while representing a hallucination-based ...

Hy and colleagues compared ProteinReDiff against eight other computational protein design models based on input and output characteristics and improved ligand-binding ... only ProteinReDiff and a ...

OpenAI has announced that it has collaborated with biotech startup Retro Biosciences to develop an AI model called ' GPT-4b micro ' that can be used for protein design. This GPT-4b micro is a ...

Generative AI can design never-before-seen proteins quickly and at scale, ... Next, a diffusion model "de-noises" the atoms, causing them to fold into the shape of a protein.

A new AI-driven framework, MapDiff, enhances inverse protein folding accuracy, accelerating the design of proteins for emerging therapies and drug development.