Virtual course
Structural bioinformatics
A guide to the commonly used methods and tools in structural bioinformatics to analyse and interpret experimentally determined and AI-predicted macromolecular structure data.
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 virtual 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.
This course will be a virtual event delivered via a mixture of live-streamed sessions, pre-recorded lectures, and tutorials with live support. We will be using Zoom to run the live sessions (all fully password protected with automated English closed captioning and transcription) with support and both scientific and social networking opportunities provided by Slack and other methods, taking different time zones into account. In order to make the most out of the course, you should make sure to have a stable internet connection throughout the week and are available between 09:00-18:00 UTC-0 each day. In the week before the course there will be a brief induction session. Computational practicals will run on EMBL-EBI's virtual training infrastructure, meaning participants will not require access to a powerful computer or install complex software on their own machines.
Selected participants may be sent materials prior to the course. These might include pre-recorded talks and required reading or online training that will be essential to fully engage with the course.
Who is this course for?
This course is aimed at scientists generating structural data or scientists utilising structural data in their 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.
What will I learn?
Learning outcomes
After the course you should be able to:
- Access and browse a range of structural data repositories
- Determine whether appropriate structural information exists about a given small molecule, macromolecule or complex, applying available structure-quality information
- Build a structural model for a protein which has a structurally characterised relative and evaluate its quality
- Predict the function of a protein-based on sequence and structure data, and navigate & assess AI-predicted protein structures.
- Explore protein-complex modeling approaches
Course content
During this course you will learn about:
- Public repositories of structural data: Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB), and tools to search and analyse information in these repositories from PDBe (Protein Data Bank in Europe) including PDBe-KB
- UniProt and basic Sequence alignment tools
- Protein structure analysis and classification: InterPro, Pfam, CATH
- Protein docking: HADDOCK
- Structure validation and assessment tools and strategies
- Tools and resources for drug discovery: ChEMBL
- AI-predicted protein structures: AlphaFoldDB and AlphaFill
Trainers
David Armstrong
EMBL-EBI Piv Gopalasingam
EMBL-EBI Gerard Kleywegt
EMBL-EBI Typhaine Paysan-Lafosse
EMBL-EBI Sara Rocio Chuguransky
EMBL-EBI Mihaly Varadi
EMBL-EBI Michael Sternberg
Imperial College London Robbie Joosten
Netherlands Cancer Institute Rodrigo Vargas Honorato
Utrecht University Isabel Romero Calvo
EMBL Fabio Marques Madeira
EMBL-EBI Pedro Raposo
EMBL-EBI
EMBL-EBI
EMBL-EBI
EMBL-EBI
EMBL-EBI
EMBL-EBI
EMBL-EBI
Imperial College London
Netherlands Cancer Institute
Utrecht University
EMBL
EMBL-EBI
EMBL-EBI
Programme
Please note the programme below is subject to minor changes.
Time (BST) | Topic | Trainer |
Thursday 13th October | ||
14:00-15:00 | Onboarding and technical test - Live session | Juanita Riveros and Piv Gopalasingam |
Day one – Monday 17 October 2022 - Introductory talks | ||
12:00-12:45 | Welcome presentation and icebreakers | Piv Gopalasingam and Juanita Riveros |
12:45-13:45 | Delegate elevator pitches and EMBL-EBI resources | All trainees and Piv Gopalasingam |
13:45-14:00 | Intro to scientific networking | Juanita Riveros and Piv Gopalasingam |
14:00-14:30 | Break | |
14:30-15:30 | Introduction to structural biology data | Gerard Kleywegt |
15:30-16:00 | Sequences: Alignments and Annotation Live Q&A | Fabio Madeira and Pedro Raposo |
16:00-17:00 | Networking / Poster session | All attendees |
17:00 | End of day 1 | |
Time | Topic | Trainer |
Day two – Tuesday 18 October 2022 - Folds, families and experimental structures | ||
09:00-10:00 | Keynote Lecture | Dame Janet Thornton |
10:00-11:30 | Sequence classification using InterPro and HMMER | Typhaine Paysan-Lafosse and Sara Chuguransky |
11:30-13:00 | CATH DB - Protein folds and structural family resources | Ian Sillitoe |
13:00-14:00 | Break | |
14:00-15:30 | PDBe and Molstar | David Armstrong and Genevieve Evans |
15:30-15:45 | Break | |
15:45-16:45 | Structure validation and PDB-Redo | Robbie Joosten |
16:45 | End of day 2 | |
Time | Topic | Trainer |
Day three – Wednesday 19 October 2022 - Protein structure prediction | ||
09:00-11:00 | Modelling protein structure and missense variants: Phyre2 and Missense3D in the context of AlphaFold models | Michael Sternberg, Alessia David and Harry Powell |
11:00-11:30 | Break | |
11:30-13:00 | AlphaFold and running AlphaFold using Google Colab | Sara Chuguransky and David Burke |
13:00-14:00 | Break | |
14:00-15:00 | Alphafold Database | David Armstrong and Damian Bertoni |
15:00-15:45 | Completing AI-predicted Structures using AlphaFill | Robbie Joosten |
15:45-16:45 | AI to predict disordered proteins | Bálint Mészáros |
16:45-17:00 | Break | |
17:00-18:00 | Networking and poster session | All attendees |
18:00 | End of day 3 | |
Time | Topic | Trainer |
Day four – Thursday 20 October 2022 - Proteins complexes and Protein Function | ||
09:00-10:30 | Exploring protein docking with HADDOCK - lecture | Alexandre Bonvin and Rodrigo Vargas Honorato |
10:30-11:00 | Break | |
11:00-13:00 | Exploring protein docking with HADDOCK - practical | Alexandre Bonvin and Rodrigo Vargas Honorato |
13:00-14:00 | Break | |
14:00-16:00 | PDBe-KnowledgeBase | David Armstrong and Preeti Choudhary, PDBe-KB team |
16:00-16:15 | Break | |
16:15-17:45 | ChEMBL - big molecular data to explore ligand biology | Barbara Zdrazil and Melissa Adasme |
17:45 | End of day 4 | |
Time | Topic | Trainer |
Day five – Friday 21 October 2022 - Structural biology at different scales | ||
09:00-10:30 | Electron Microscopy Data Bank | Jack Turner, EMDB team |
10:30-11:00 | Break | |
11:00-12:30 | Using the Ensembl Variant Effect Predictor (VEP) | Aleena Mushtaq |
12:30-13:00 | Break | |
13:00-14:00 | Keynote: Molecular visualisation for Structural biology | Isabel Romero Calvo |
14:00-14:25 | Course wrap-up and close | Piv Gopalasingam and Ajay Mishra |
14:30 | End of course |
Please read our page on application advice before starting your application. In order to be considered for a place on this course, you must do the following:
- Complete the online application form.
- Ensure you add relevant information to the "application submission" section where you are asked to provide three 100-word paragraphs that cover your:
- scientific biography
- work history
- current research interests
- Upload a letter of support from your supervisor or a senior colleague detailing reasons why you should be selected for this course; and also that you can dedicate your time to this virtual course.
Please submit all documents during the application process by 29 July 2022.
Incomplete applications will not be considered.
All applicants will be informed of the status of their application (successful, waiting list, rejected) by 12 August 2022. If you have any questions regarding the application process please contact Juanita Riveros.