RESEARCH: PROTEIN-DYNAMICS-MODELING
FOLDING PROJECT #19507 PROFILE

The project relates to creating AI that can simulate how proteins move and interact. This could help us understand viruses better and design new drugs.

Summary The AI4Science Group at Freie Universität Berlin develops machine learning methods for physical sciences, with a focus on physics-constrained learning algorithms, complex dynamical systems analysis, efficient generative learning methods for statistical mechanics, and highly accurate machine learning methods for quantum mechanics.

They are an interdisciplinary team of mathematicians, chemists, physicists, and computer scientists. Details The primary objective of this project is to develop large-scale artificial intelligence (AI) models to efficiently sample protein dynamics and predict the stability of folded states and protein-protein interactions.

Being able to do this efficiently and accurately would be a game-changer for the prediction of virus mutants and the design of therapies for various diseases.

AI techniques have demonstrated exceptional performance on benchmark systems and have the potential to vastly speed up computations yet maintain comparable levels of accuracy as classical molecular dynamics simulations. The project aims to generate a comprehensive dataset of small protein systems that will provide the necessary information for creating the next generation of AI models for protein simulations.

We will collaborate with the Clementi Group at Freie Universität Berlin to achieve this goal.

artificial intelligence

The ability of a computer or a robot controlled by a computer to do tasks that are usually done by humans because they require human intelligence and discernment.

Artificial intelligence (AI) is a branch of computer science focused on creating intelligent agents, which are systems that can reason, learn, and act autonomously. AI has wide-ranging applications, including natural language processing, image recognition, and decision-making.