Title: Predicting Protein Conformational Ensembles Using AlphaFoldTemplate for Projects

Project duration: 08.2023 – 12.2023

Research Area: Life Science and Medicine

Our goal is to accurately predict the range of conformations a protein can adopt, thereby understanding its functional mechanisms. We aim to develop a method that enhances AlphaFold’s predictions, enabling the exploration of protein dynamics and the identification of transient structural states.

Aims

• Accurately predict the range of conformations a protein can adopt.
• Understand the functional mechanisms of proteins through conformational analysis.
• Develop a method to enhance AlphaFold’s predictions, to
  • enable exploration of protein dynamics using improved predictive models
  • identify transient structural states of proteins for deeper functional insights.

Problems

Proteins are dynamic molecules that can adopt multiple conformations, crucial for their function. Traditional structure prediction methods often fail to capture this conformational diversity, limiting our understanding of protein functionality and dynamics.

Practical Example

We applied our enhanced AlphaFold method to predict the conformational ensemble of the HER2 protein, implicated in breast cancer. Our predictions matched experimental data, demonstrating the method’s potential in drug discovery by identifying novel therapeutic targets.

Technology

We utilize AlphaFold2, a deep learning-based protein structure prediction algorithm. Our method involves manipulating the input multiple sequence alignments (MSAs) to AlphaFold, enabling it to predict a broader range of protein conformations.

Outlook

This project has the potential to revolutionize our understanding of protein dynamics, opening new avenues in drug discovery, vaccine development, and the design of novel enzymes. Future research will focus on refining and applying our method to a broader range of proteins to explore the dynamic protein fold space further.

Publications

• Sala, D et al. “Modeling conformational states of proteins with AlphaFold.” Current opinion in structural biology vol. 81 (2023): 102645. doi:10.1016/j.sbi.2023.102645

Team

Lead

• Prof. Dr. Jens Meiler (Leipzig University)

Team Members

• Felipe Engelberger (Leipzig University)

Partners

• Prof. Sergey Ovchinikov (MIT)
• Prof. Cesar Ramirez-Sarmiento (Pontificia Universidad Católica de Chile)