Structural biology, determining the three-dimensional shapes of biomacromolecules and their complexes, can tell us a lot about how these molecules function and the roles they play within a cell. Data derived from structure determination experiments and Artificial Intelligence (AI)-assisted structure prediction enables life-science researchers to address a wide variety of questions.
This course provides a guide to the commonly used methods and tools in structural bioinformatics to analyse and interpret experimentally determined and AI-predicted macromolecular structure data.
This course explores bioinformatics data resources and tools for the investigation, analysis, and interpretation of both experimentally determined and predicted biomacromolecular structures. It will focus on how best to analyse and interpret available structural data to gain useful information given specific research contexts. The course content will also cover predicting function and exploring interactions with other macromolecules.
Virtual course
You will learn via a mix of pre-recorded lectures, live presentations, and trainer Q&A sessions. Practical experience will be developed through group activities and trainer-led computational exercises. Live sessions will be delivered using Zoom with additional support and asynchronous communication via Slack.
Pre-recorded material may be provided before the course starts that you will need to watch, read, or work through to gain the most out of the actual training event. A brief pre-course session will be held the week beforehand. Computational practicals will run on EMBL-EBI's virtual training infrastructure, meaning you will not require access to a powerful computer or install complex software on your own machines.
You will need to be available between the hours of 09:00 – 18:30 BST each day of the course. Trainers will be available to assist, answer questions, and provide further explanations during these times.
This course is aimed at you if you are a scientist generating structural data or a scientist utilising structural data in your analysis and/or interpretation. No previous experience in the field of structural bioinformatics is required, however good knowledge of protein structure and function would be of benefit.
After the course, you should be able to:
During this course, you will learn about:
AI-predicted protein structures: AlphaFoldDB and AlphaFill