Microsoft has launched BioEmu, an artificial intelligence system designed to speed up the process of understanding how proteins behave in the human body, work that traditionally takes years of complex computer simulations.
Announcing the breakthrough on X, Microsoft Chairman and CEO Satya Nadella said, “Understanding protein motion is essential to understanding biology and advancing drug discovery. Today we’re introducing BioEmu, an AI system that emulates the structural ensembles proteins adopt, delivering insights in hours that would otherwise require years of simulation.”
The AI system, developed by Microsoft Research’s AI for Science team, is capable of predicting the different shapes and movements (or “conformational changes”) that proteins can take as they function inside living organisms. This ability is crucial for understanding how diseases work and how new drugs can be designed to target specific proteins.
In a detailed explanation on X, Microsoft Research stated that BioEmu version 1.1 can closely match real-world experimental protein stability data, with prediction errors of less than 1 kcal/mol and strong correlation scores above 0.6 on large test datasets.
The AI was trained using more than 200 milliseconds of molecular dynamics simulations, data from over 500,000 protein stability experiments, and vast structural information. Unlike traditional methods that require extensive GPU usage over years, BioEmu can now complete the same simulations within hours, saving enormous computing time and cost.
One of BioEmu’s standout features is its ability to predict hard-to-detect changes in protein structure, including the formation of so-called “cryptic” binding pockets, hidden spots on proteins that could be targeted by future drugs.
“BioEmu can emulate equilibrium distributions of millisecond-timescale molecular dynamics simulations at many orders of magnitude faster speeds,” Microsoft Research noted. “It also predicts functionally important movements, like large domain shifts and local unfolding, which are often central to how a protein works.”
The research has been published in the journalScience, showcasing BioEmu as a generative deep learning model designed to replicate the structural ensembles of proteins in lab settings or within the human body.
These protein ensembles are vital to understanding how proteins perform their roles, especially since many proteins constantly shift between different forms.
The launch of BioEmu is expected to have significant impact on fields such as drug development, disease research, and synthetic biology, potentially allowing scientists to discover and test new therapies far faster than ever before.
