The Generative Biology Revolution: The Protein Structure Prediction Problem

To build better biologic drugs, researchers need to understand exactly how amino acid building blocks interact with one another and fold into functional proteins. This knowledge provides insights into how to engage a drug target or develop an optimal therapeutic. Determining a protein’s structure is a laborious process in the wet lab, but thanks to machine learning, scientists can now use various algorithms to predict structure. 

In this episode, we talk to Mike Nohaile, chief scientific officer at Generate Biomedicines. Since early 2022, Amgen and Generate Biomedicines have been collaborating to discover and create protein therapeutics across several therapeutic areas and multiple modalities, including monoclonal and bispecific antibody drugs. We discuss the challenge of predicting a protein’s structure from its sequence and the steps drug developers are now taking to create novel structures with therapeutic potential using generative biology.

To dive further into this topic, please join Amgen scientists at the Generative Biology Q&A webinar discussion on July 20^th, 2022. Register for the event here.

The Generative Biology Revolution is a special edition podcast series produced by The Scientist’s Creative Services Team.

This series is brought to you by Amgen, a pioneer in the science of using living cells to make biologic medicines. They helped invent the processes and tools that built the global biotech industry, and have since reached millions of patients suffering from serious illnesses around the world with their medicines.

Generative biology is a revolutionary approach to drug discovery and development that leverages machine learning and AI to design novel protein therapeutics. It holds the potential to enhance the speed and efficiency of discovery. In this series, Ray Deshaies, senior vice president of Global Research at Amgen, discusses how generative biology is transforming drug discovery to make it more predictable, shorten timelines, and increase success rates of bringing life-saving medicines to patients who need them most.