AlphaFold training course​

Course contents

• An introductory guide to AlphaFold’s strengths and limitations
  • What are proteins and how do we know their structures?
  • What is the protein folding problem?
  • What is AlphaFold?
  • Strengths and limitations of AlphaFold2
  • Test your knowledge
• Validation and impact
  • How have AlphaFold2’s predictions of protein structure been validated?
  • How accurate are AlphaFold2 structure predictions?
  • How is AlphaFold2 used by scientists?
• Inputs and outputs
  • AlphaFold2: A high-level overview
  • Evaluating AlphaFold2’s predicted structures using confidence scores
  • pLDDT: Understanding local confidence
  • PAE: A measure of global confidence in AlphaFold2 predictions
  • Confidence scores in AlphaFold-Multimer
  • AlphaFold2 inputs and outputs – Recap
  • Other tools to check quality of the predicted structures
• Accessing and predicting protein structures with AlphaFold2
  • Choosing how to access AlphaFold2
  • Accessing predicted protein structures in the AlphaFold Database
  • What’s the best way to access the database?
  • Predicting protein structures with ColabFold and AlphaFold2 Colab
  • Predicting protein structures using the AlphaFold2 open-source code
  • Other ways to access predicted protein structures
  • How to cite AlphaFold
• Advanced modelling and applications of predicted protein structures
  • Customising AlphaFold2 structure predictions
  • Outputs from ColabFold
  • Using AlphaFold2 predicted structures to tackle deeper questions
  • Enhancements to AlphaFold2 from the wider scientific community
• Future directions and summary
  • Current and future developments of AlphaFold2
  • Key takeaways about AlphaFold2

Date:  Anytime
Duration: 3 hours
Venue: online
This training module on AlphaFold2 has been developed in collaboration with Google DeepMind

find out more